New developments in the mechanism and application of immune checkpoint inhibitors in cancer therapy (Review)
- Authors:
- Published online on: June 12, 2023 https://doi.org/10.3892/ijo.2023.5534
- Article Number: 86
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Copyright: © Wang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
1. Introduction
Cancer is a major public health concern worldwide. According to the American Cancer Society, it was estimated that 1.9 million new cases and 610,000 cancer-related deaths occurred in the United States in 2022, posing a serious threat to human health (1). Conventional cancer treatments include surgery, radiotherapy, chemotherapy and targeted therapy; however, certain types of advanced or metastatic cancer are difficult to cure using traditional treatments, and novel tools and approaches are required. Research has shown that the immune system serves a pivotal role in maintaining the stability of the internal environment (2); however, cancer cells often escape surveillance and destruct the host immune system (3). Therefore, research has focused on the development of immunotherapy that inhibits tumor-induced immune tolerance and restores the immune response against tumor cells. Unlike conventional cancer treatments which mainly act on cancer cells, immunotherapy indirectly promotes cancer control through activating the antitumor immune responses of the patient (4,5). The concept of antitumor immunotherapy has been around for over a century, starting with Coley's toxins and Erlich's hypothesis that the immune system suppresses cancer development (4), but it has developed rapidly in the past two decades and is currently a major focus in cancer therapy.
Among the different types of cancer immunotherapy, immune checkpoint inhibitors (ICIs) demonstrate a broad impact. ICIs are monoclonal antibodies (mAbs) that specifically target the inhibitory receptors on T cells, known as immune checkpoint molecules. These act as negative co-regulators that inhibit further T-cell activation and are essential for the maintenance of self-tolerance (4). Tumor cells often escape host immunity through immune checkpoint dysregulation, and ICIs are immunomodulators that reinforce antitumor immune responses (6-10). Moreover, ICIs have demonstrated notable outcomes in multiple tumor types (11), either as a single treatment or combined with conventional treatments. ICIs may be used in both advanced and metastatic cancer, either as adjuvant or neoadjuvant treatment in the early stage of cancer (12). Notably, ICIs are considered revolutionary in cancer treatment, highlighted by the 2018 Nobel Prize in Physiology or Medicine awarded jointly to James Allison and Tasuku Honjo, for their discovery of cancer treatment via suppression of negative immune regulation (12). The present review aimed to summarize the current knowledge and novel advances regarding the mechanisms and applications of various ICIs. This study may provide a theoretical basis for further associated research and the application of immunotherapy.
2. Tumor-immune interactions
During the tumor immune response process, T lymphocytes act as the final effector cell, and the activation of T cells requires two signals. The first signal originates from the specific recognition of antigen-major histocompatibility complex (MHC) complexes by T-cell receptors (TCRs). The second signal originates from the interaction between co-stimulatory molecules on the surface of T cells with the corresponding ligands. Co-stimulatory signals are required to enhance the antigen receptor signals that induce transcription factor activation and PI3K activation, thereby ensuring full activation of T cells (13). Compared with these activating co-stimulatory molecules, certain inhibitory molecules exist on the surface of T cells that downregulate activation signals. These inhibitory receptors function to prevent T-cell proliferation and cytokine production, in order to prevent excessive immune responses that can lead to destructive inflammatory or autoimmune conditions (14,15). Moreover, the strict regulation between co-stimulatory and inhibitory molecules serves a critical role in immune homeostasis. Co-stimulatory molecules include CD28, 4-1BB and inducible co-stimulator (CD278), and inhibitory molecules include cytotoxic T lymphocyte associated antigen-4 (CTLA-4) and programmed death-1 (PD-1), which are both categorized as immune checkpoint molecules (15). Notably, immune checkpoint molecules refer to 'brake' proteins that inhibit the activation of immune cells (Fig. 1). Tumor cells often inhibit the effects of T cells through the immune checkpoint pathway, leading to immune escape.
3. ICI therapy for the treatment of cancer
CTLA-4 and anti-CTLA-4 therapy
In 1987, the CTLA-4 gene was initially discovered in mice by Brunet et al (16) and the human CTLA-4 gene was cloned the following year (17). Krummel and Allison (17) confirmed the function of CTLA-4 as a negative regulator of T-cell activation; this was the first immune checkpoint molecule described (17). CTLA-4, also known as CD152, is a transmembrane receptor on T cells. In the early stages of T-cell activation, CTLA-4 is induced and binds to the same co-stimulatory ligands (B7-1 and B7-2) expressed on antigen-presenting cells (APCs) as CD28. Compared with CD28, CTLA-4 possesses a higher avidity and affinity for the ligands, thereby preventing the CD28-dependent co-stimulation signal required for T-cell activation (18-20). CTLA-4 has been shown to interact with the serine/threonine phosphatase PP2A, which blocks Akt activation and downstream signals of T cells, and CTLA-4 may also reduce the formation of the ζ chain of TCR associated protein kinase 70 kDa (ZAP-70) microcluster, thus limiting T-cell activation. In addition, CTLA-4-associated SHP-2 has phosphatase activity toward the RAS regulator p52, thereby affecting the downstream RAS pathway. All of these effects can lead to the suppression of T-cell activation, which is critical for immunologic tolerance in physiological conditions (21). Notably, the biallelic genetic deletion of Ctla4 leads to lymphoproliferation disorders with early lethality in mice (22,23).
CTLA-4 not only prevents the activation of self-reactive T cells, but also other T cells, by binding to the ligand for CD28. In addition, CTLA-4 exerts inhibitory effects that are mediated through regulatory T cells (Tregs). Tregs express high levels of CTLA-4 on the cell surface, and specific loss of CTLA-4 leads to an increased susceptibility to autoimmune diseases. This indicates that Treg-derived CTLA-4 is required to maintain immunologic tolerance (24,25). Moreover, Tregs directly remove the co-stimulatory ligands, B7-1 and B7-2, from the surface of APCs via trans-endocytosis. CTLA-4 promotes T-cell motility through antagonizing the formation of microclusters, thus reducing the T cell/APC dwell times (26). In addition, CTLA-4 negatively regulates the immune response through inhibiting the maturation and antigen presentation of APCs (27), and inducing the production of indolamine-2,3-dioxygenase (IDO) by APCs (28). As CTLA-4 was the first immune checkpoint molecule to be discovered, the associated regulatory mechanisms have been extensively studied. However, further investigations into the function of downstream signal components are crucial, and future studies should focus on evaluating CTLA-4-mediated regulation of T-cell activity.
Following the discovery of the role of CTLA-4 in immune suppression, research has focused on restoring the antitumor function of T cells through inhibiting the binding of CTLA-4 to B7. Using animal models (29), anti-CTLA-4 immunoglobulin (Ig)G1 mAb was developed in 1999, and later named ipilimumab. In 2010, ipilimumab was successfully used in the treatment of metastatic melanoma in a phase III clinical trial. Results of this study demonstrated that the median overall survival (OS) among patients receiving ipilimumab alone was 10.1 months (30). Subsequently, the United States Food and Drug Administration (FDA) approved ipilimumab as a first-line drug in the treatment of advanced melanoma in 2011; this was the first approved immunotherapy drug (Table I). After 4 years, ipilimumab was approved as an adjuvant treatment for stage III melanoma. In addition, the efficacy of ipilimumab has been demonstrated in other solid tumors, including lung, renal, pancreatic and prostate cancer (31-33). However, the effects of ipilimumab in these solid tumors have been reported to be limited, and this may be due to low tumor immunogenicity and a potently immunosuppressive tumor microenvironment (TME) (34). In addition to ipilimumab, tremelimumab is currently undergoing clinical trials in a variety of tumors as an additional CTLA-4 blockade (11,35). In 2015, tremelimumab was granted orphan drug qualification by the FDA in the treatment of malignant mesothelioma. In 2020, in combination with durvalumab, tremelimumab was also used to treat hepatocellular carcinoma (HCC). As well as regulating T-cell activation, CTLA-4 blockade may limit the penetration of Tregs into the TME, to prevent Tregs from inhibiting the activity of cytotoxic T cells and enhancing antitumor activity. However, associated research is limited at present (36,37).
PD-1 and anti-PD-1 therapy
In 1992, PD-1 was initially identified by Ishida et al (38) at Kyoto University. In 1999, preclinical data established the central role of PD-1 in immune suppression (39). In the same year, Dong et al (40) discovered the third member of the B7 family, B7-H1. Freeman et al (41) later confirmed that B7-H1 is programmed cell death-ligand 1 (PD-L1) that binds to PD-1. PD-1, which belongs to the CD28 Ig superfamily, is induced transiently on activated T, B, natural killer (NK) T and myeloid cells (42,43). PD-1 binds to the B7 family ligands, PD-L1 (B7-H1) and PD-L2 (B7-DC), and inhibits the proliferation and effector functions of immune cells. Specifically, the ligation of PD-L1 and PD-1 leads to tyrosine phosphorylation of the immunoreceptor tyrosine-based inhibitory motif (ITIM) and immunoreceptor tyrosine-based switch motif (ITSM) of PD-1. Binding of the ITSM by SHP-1 or SHP-2 results in the inhibition of casein kinase II, the induction of PTEN phosphatase activity and thus the suppression of the PI3K/Akt pathway (43). Other signaling pathways initiated by TCR ligation are also inhibited by PD-1, including ZAP70 and protein kinase Cθ activation. PD-1 ligation can also inhibit the activation of phospholipase C-γ1 and downstream Ras signaling, resulting in decreased activation of the MEK/Erk pathway (44,45). Furthermore, PD-1 signaling may lead to a decrease in T-cell proliferation, survival and protein synthesis, which is essential for maintaining peripheral tolerance. Notably, the genetic loss of Pdcd1, which encodes PD-1, may cause autoimmune pathologies (39,46).
Unlike CTLA-4, PD-1 expression is transient in the early stage of T-cell activation and then decreases when the activating antigen is removed. However, PD-1 expression is high if the antigen is present for a prolonged period of time; for example, during chronic infection or in a tumor (47,48). It has previously been demonstrated that PD-1 expression is increased on the majority of tumor-infiltrating T lymphocytes (TILs) in various tumor types, and this is an important cause of tumor immune escape (49,50). The two ligands of PD-1 are comparable with other B7 immune regulatory ligand family members, and the affinity of PD-L2 to PD-1 has been reported to be higher than that of PD-L1 (46,51). The expression levels of PD-Ls are different in different human cells. Notably, PD-L1 is expressed on hematopoietic cells, such as B cells, T cells, macrophages, dendritic cells (DCs) and mesenchymal stem cells (MSCs) (52), and is also expressed on nonhematopoietic cells, including vascular endothelial cells, fibroblastic reticular cells, astrocytes, liver cells, pancreatic cells and neurons (43). By contrast, PD-L2 is mainly expressed on APCs, such as macrophages and DCs, and peritoneal B1 cells (53). In addition, the main PD-1 ligand expressed on solid tumor cells is PD-L1 (54,55). Results of previous studies have suggested that PD-L1 is upregulated in multiple cancer types, including melanoma, ovarian cancer and lung cancer (56-58). Activated T cells also produce cytokines that promote the expression of PD-L1 on cancer cells (56). When PD-L1 on cancer cells binds to PD-1 on T cells, immunosuppression occurs. In addition, PD-L1 specifically interacts with the B7-1 (CD80) co-stimulatory molecule to inhibit T-cell responses (59). Collectively, these mechanisms cause cancer cells to evade the immune system.
A previous study found that the CTLA-4 inhibitor was effective only for certain cases of advanced melanoma, and serious side effects may occur in treating other types of tumors (34). Notably, ICIs were not widely accepted until the use of PD-1/PD-L1 antibodies was established in the clinic in 2014. Although PD-1/PD-L1 antibodies mainly function through upregulating T-cell activation, they also block the host-derived PD-L1 signals from non-tumor cells in the microenvironment, as well as the interactions between PD-L1 and B7-1 (11). At present, a total of six PD-1/PD-L1 inhibitors have been approved by the FDA, including nivolumab, pembrolizumab, atezolizumab, avelumab, durvalumab and cemiplima. The associated indications include melanoma, Hodgkin's lymphoma, non-small cell lung cancer (NSCLC), renal cell cancer (RCC), gastric cancer, liver cancer, colorectal cancer (CRC), cutaneous squamous cell cancer and urothelial cancer (UC). These indications are displayed in Table I.
In 2006, the first clinical trial of a PD-1 inhibitor, nivolumab, was conducted in refractory solid tumors. Notably, nivolumab was known as IgG4 anti-PD-1 mAb and Opdivo (MDX-1106, ONO-4538, BMS-936558), and was developed by Bristol-Myers Squibb. In December 2014, nivolumab was approved by the FDA for the treatment of metastatic melanoma, with the results of the CheckMate 037 clinical trial demonstrating an objective response rate of 31.7% in the nivolumab group, and 10.6% in the chemotherapy group (dacarbazine orcarboplatin) (54). At present, the indications have extended to various advanced solid tumors, including NSCLC, RCC, UC, squamous cell carcinoma of head and neck, Hodgkin's lymphoma, HCC, CRC and esophageal squamous cell carcinoma (59-63).
In September 2014, an additional PD-1 inhibitor, pembrolizumab (Keytruda, lambrolizumab, MK-3475), was approved by the FDA for the treatment of unresectable or metastatic melanoma. Pembrolizumab, a fully humanized IgG4 with high-affinity and high-selectivity, demonstrated an objective response rate of >30% in patients with advanced melanoma (NCT01866319) (63). At present, pembrolizumab is approved for use in >14 indications of 10 tumor types (64-69).
In September 2018, another PD-1 inhibitor, cemiplimab (Libtayo), was approved by the FDA for treatment of metastatic or locally advanced non-resectable cutaneous squamous cell carcinoma. Notably, this was the first drug approved by the FDA that was specifically for the treatment of patients with advanced cutaneous squamous cell carcinoma (70).
Atezolizumab (Tecentriq), a human IgG1 anti-PD-L1 mAb, was the first PD-L1 inhibitor approved by the FDA for the treatment of advanced or metastatic UC. Results of a phase II clinical trial demonstrated an objective response rate of 15% in all patients and 26% in patients with the highest levels of PD-L1 expression following treatment with atezolizumab (71). The indications of atezolizumab have subsequently extended to NSCLC, small cell lung cancer, breast cancer, HCC and melanoma (71-75).
An additional PD-L1 inhibitor, avelumab (Bavencio), not only functions via blocking PD-1/PD-L1 interactions, but also through antibody-dependent cell-mediated cytotoxicity (76). In March 2017, avelumab was approved by the FDA for the treatment of metastasis Merkel cell carcinoma in adolescents and adults >12 years of age, and the indication was subsequently expanded to UC and RCC.
In May 2017, the FDA-approved durvalumab (Imfinzi), an additional PD-L1 antibody, for the treatment of advanced UC, using accelerated approval. Results of a previous study demonstrated that durvalumab substantially improved the progression-free survival of patients with NSCLC, compared with the placebo (16.8 months vs. 5.6 months) (77). Subsequently, the FDA expanded the indications to include Stage III NSCLC in February 2018.
A novel PD-L1 inhibitor, envafolimab (KN035), was awarded Orphan Drug Designation by the FDA for the treatment of biliary tract cancer. Notably, the PD-1/PD-L1 inhibitors approved by the FDA may continue to be approved for additional indications. However, alternative anti-PD-1/PD-L1 axis-targeted therapies, such as pidilizumab (CT-011) and BMS-936559 (MDX-1105) are under investigation in clinical trials, and these treatment options may exhibit potential in a broad range of tumor types (78,79).
PD-1/PD-L1 inhibitors are used in the treatment of various types of cancer. However, results may differ between patients, and the mechanistic basis for the variation in response patterns are multifaceted. For example, a previous study reported that patients with melanoma that respond to these inhibitors had a higher proportion of BRCA2 mutations (80). In addition, innately resistant tumors display a transcriptional signature, indicating concurrent increased expression of genes involved in the regulation of mesenchymal transition, cell adhesion, extracellular matrix remodeling, angiogenesis and wound healing (80). Moreover, PD-1 inhibitor monotherapy for patients with NSCLC accompanied by EGFR mutations exhibit low response rates and unsatisfactory efficacy. PD-1 inhibitors may be ineffective in microsatellite stable type carcinoma (81), and PD-1/PD-L1 inhibitors exert minimal effects on certain types of tumors, such as multiple myeloma and uveal melanoma (78). However, further investigations into the specific molecular and cellular mechanisms of PD-1/PD-L1 inhibitors in antitumor immune enhancement are required.
Alternative immune checkpoint molecules and therapy
Following the discovery of CTLA-4 and PD-1/PD-L1 in antitumor treatment, further preclinical and clinical studies have focused on additional immune checkpoint molecules.
Lymphocyte activation gene-3 (LAG-3), also known as CD223, is a member of the Ig superfamily and a homologous protein of CD4+, which can bind to MHC-II molecules with high affinity. LAG-3 is expressed on active NK cells, T cells, B cells, TILs, Tregs and DCs, and is required for immune homeostasis (82-84). However, persistent antigen stimulation in cancer may lead to chronic LAG-3 expression, promoting T-cell exhaustion. Results of previous studies have demonstrated that LAG-3 is highly expressed on the TILs of multiple tumors (85-88). The signaling pathways downstream of LAG-3 responsible for its inhibitory function are still unclear, but the KIEELE motif of the LAG-3 cytoplasmic tail has been shown to be essential for the inhibitory function (84). At present, research is focused on numerous therapeutic agents targeting LAG-3, for the treatment of multiple types of human cancer (89,90).
T-cell Ig mucin (Tim)-3, a member of the Tim family, is a type I transmembrane glycoprotein, which was initially recognized in CD4+ T helper and CD8+ T cytotoxic cells, and was subsequently shown to be expressed in Tregs, NK cells, monocytes and DCs (84,91). Several ligands of Tim-3 have been recognized, including galectin-9 (Gal-9), phosphatidyl serine (PS), high-mobility group box 1 (HMGB1) and carcinoembryonic antigen cell adhesion molecule 1 (Ceacam-1) (92). Notably, the binding of Tim-3 and Gal-9 induces T-cell death and reduces the immune response (92). The binding of Tim-3 and PS mediates the phagocytosis of apoptotic cells and cross-presentation (93). The binding of Tim-3 and HMGB1 inhibits antitumor immune responses mediated by HMGB1 (94). Ceacam-1 was identified as a novel ligand for Tim-3. In the absence of Ceacam-1, the negative regulatory function of Tim-3 is defective, indicating that the interaction between Ceacam-1 and Tim-3 is required for optimal Tim-3 function (95). Bat-3 and Fyn bind to the same region on the cytoplasmic tail of Tim-3, the binding of Gal-9 or Ceacam-1 to Tim-3 can trigger the dissociation of Bat-3 from the cytoplasmic tail of Tim-3, thus allowing Fyn to bind, which is implicated in the induction of T-cell anergy (84). Tim-3 expression is indicative of dysfunctional or exhausted T cells in cancer, and is elevated in various tumors (96-99). In addition, the co-blockade of Tim-3/PD-1 demonstrated increased efficacy in treating tumors, compared with blocking Tim-3 or PD-1 alone (100).
T-cell Ig and ITIM domain (TIGIT) is a member of the Ig superfamily, and is expressed on NK cells, activated T cells, memory T cells, follicular T helper cells and Tregs (101-104). The ligands of TIGIT, including CD155 (PVR) and CD112 (PVRL2, nectin-2), are expressed on APCs, T cells, nonhematopoietic cells and tumor cells (101,105). CD155/TIGIT can suppress the function of NK cells through inhibiting PI3K/MAPK and NF-κB signaling, and can suppress the function of T cells through inhibiting AKT/mTOR signaling. In addition, TIGIT can reduce the activity of the co-stimulatory molecule CD226 during the antitumor T-cell response (84). At present, three phase I/II clinical studies targeting TIGIT for cancer immunotherapy are ongoing (NCT05130177, NCT04354246 and NCT04995523; 106-108).
B- and T-lymphocyte attenuator (BTLA), also known as CD272, belongs to the CD28 Ig superfamily. The protein structure of BTLA is comparable with that of PD-1 and CTLA-4. BTLA is expressed on B cells, T cells, NK cells, DCs and macrophages (109,110). The ligand of BTLA is herpes virus entry mediator (HVEM), which belongs to the tumor necrosis factor receptor family. HVEM is widely expressed in B cells, T cells, NK cells, monocytes and DCs (109). Engagement of BTLA leads to the recruitment of SHP-1 and SHP-2 in T cells, thereby downregulating TCR signaling and the transmission of inhibitory signals (111). Results of previous studies have demonstrated that BTLA is highly expressed in melanoma, lung cancer, RCC, lymphoma, B-cell small lymphocytic lymphoma and chronic lymphocytic leukemia (109-112). At present, preclinical studies of BTLA or HVEM inhibitors are ongoing, and subsequent clinical studies will be developed (109-111).
V-domain Ig suppressor of T-cell activation (VISTA), also known as C10 or f54, is a member of the CD28 family. VISTA is a novel immune checkpoint expressed on myeloid cells and lymphoid cells, which is upregulated in various tumors (113). VISTA has two proven ligands, P-selectin glycoprotein ligand-1 (PSGL-1) and Ig superfamily member 11 (IGSF-11); PSGL-1 only functions at neutral pH and the affinity declines fourfold at pH 6.0 (113). VISTA can serve as both a ligand and receptor to suppress T cell-associated immune responses; however, the mechanism remains to be elucidated (113). Several clinical trials of VISTA inhibitors are ongoing for the treatment of multiple types of cancer (NCT02812875, NCT02671955 and NCT04475523; 114-116).
The FDA-approved ICIs classified by cancer type are summarized in Fig. 2. The characteristics of various immune checkpoint molecules and their associated roles in tumor immunotherapy differ. An increased understanding of the basic biological functions of these molecules is essential for the development of novel ICI therapies.
4. Biomarkers for ICIs
Although ICIs have demonstrated high levels of success in improving therapeutic efficacy in some patients, previous studies have demonstrated that only ≤20-30% of patients with NSCLC, melanoma or RCC benefit from ICIs (30,117-120). Non-responders include patients who do not respond to treatment at all and patients who relapse after remission to ICIs (121). These non-responders endure high treatment costs and associated levels of toxicity with little benefit from the treatment. Moreover, inappropriate application may cause disease progression (122). Therefore, the development of predictive biomarkers is required for prescribing ICIs in a personalized manner.
PD-L1
Results of a previous study suggested that PD-L1 expression in tumor cells and the tumor environment is positively associated with the response to PD-1/PD-L1-blocking antibodies (123). Immunohistochemistry (IHC) analyses performed on patients with metastatic melanoma, colon cancer, NSCLC, prostate cancer and RCC who received PD-1/PD-L1 targeted therapy demonstrated that PD-L1 upregulation acted as a potential biomarker (63,119,124-126). Different PD-L1 expression cutoffs and scoring systems have been used in different trials of FDA-approved drugs directed by PD-1/PD-L1 (123). However, PD-L1 may not be optimal as a potential biomarker, as the overall response rate of PD-1/PD-L1-blocking antibodies in patients with negative PD-L1 expression can also reach 0-20% (127,128). There are some limitations that must be considered when selecting PD-L1 as an immunotherapy biomarker. Notably, the expression of PD-L1 is induced and dynamic; thus, different treatment methods may impact the expression of PD-L1 in different stages of treatment (129,130). Besides, the expression between primary and metastatic tumors may be heterogeneous. As a result, the expression of PD-L1 at a certain time or location cannot accurately reflect the expression of PD-L1 in tumors (131,132). In addition, different commercially available PD-L1 IHC tests were used in different trials, and different cutoff scores were set to detect or quantify tumor PD-L1 expression, resulting in clinical failure to select patients according to a unified standard (133).
Mutation signatures and microsatellite instability (MSI)
Following the development of gene sequencing and bioinformatics, genomics technology is more frequently used for discovering biomarkers associated with ICIs. Previous clinical studies revealed that mismatch repair deficiency (dMMR) or MSI-high (MSI-H) are associated with response to ICIs (81,134). MMR is an important DNA repair mechanism that makes alterations in DNA mismatches, and dMMR may lead to MSI, which can be used for the clinical detection of dMMR (135). dMMR or MSI-H are often present in various types of cancer (136,137). The results of previous studies suggested that dMMR tumors exhibit high neoantigen load, tumor mutational burden (TMB), T-cell infiltration and upregulation of multiple immune checkpoints, including PD-1, PD-L1, CTLA-4 and LAG-3 (138-141), which may lead to high response rates to ICIs. Notably, MSI has been recognized by the FDA as a predictive biomarker for ICI responsiveness (142). Moreover, pembrolizumab was specifically approved in the treatment of multiple solid tumors with MSI-H or dMMR. This was the first FDA-approved tumor immunotherapy that was not based on tumor tissue type and instead based solely on genetic characteristics. Therefore, further investigations should focus on identifying MMR and MMR-like tumors. Further analysis of specific DNA repair gene sets, or bioinformatics analysis of specific DNA damage characteristics associated with specific DNA repair defects in the cancer genome, are required to assess the potential sensitivity to ICIs (143).
TMB
TMB refers to the total number of base substitution, insertion or deletion mutations in the coding region of exons of evaluated genes in tumor tissue samples. Notably, a higher TMB may affect the probability of immunogenic peptide generation; thus, affecting the response of patients to ICIs (144,145). As a result, the association between TMB and the efficacy of ICIs has been the focus of multiple studies. Notably, TMB may be associated with clinical benefits of ICIs in patients with melanoma, NSCLC, UC, squamous cell carcinoma of head and neck, and small cell lung cancer, while those with lower TMB, such as pancreatic cancer and prostate cancer, may exhibit poor responses to ICIs (71,146-152). In 2020, TMB became the second FDA-approved predictive biomarker for the efficacy of ICIs. However, there are notable limitations. Firstly, different testing platforms are used in the clinical studies of TMB at present, and there is no standard definition of high TMB. Thus, the mutation load of different tumors is varied and different cutoffs must be established (146,147). Moreover, TMB alone may not distinguish all responders from non-responders. For example, the immunogenicity of tumor neoantigens may be improved by epigenetic modification in tumors with low TMB, leading to improved therapeutic responses to ICIs (62,153). However, for those tumors with high TMB, there may be other immunosuppressive molecules in the tumor immune microenvironment, such as IL-10 and metabolism-related enzyme IDO, which may affect the efficacy of ICIs (9,154). Consequently, TMB alone may be inadequate in predicting the efficacy of ICIs. Moreover, further investigations into cost control, application of dynamic biomarkers and blood-based TMB detection are required.
TILs
TILs are the effector cells of antitumor immunity and the target cells of ICIs. TILs act as a representative of tumor-immune system interaction; therefore, assessing the presence of TILs may aid in identifying patients who benefit from immunotherapy. In a study of pembrolizumab in the treatment of advanced melanoma, CD8+ T-cell infiltration in the tumor tissue or invasion margin was revealed to be higher in responders than in patients who did not respond (155). Results of previous studies have also demonstrated that TILs may be used to predict the immunotherapeutic response and prognosis of numerous types of cancer, including breast cancer and CRC (156-160). Adding immunoscore based on TILs to the existing tumor, lymph node and metastasis classification system may improve the development of effective treatment plans and allow clinicians to provide more accurate prognoses (161). However, the widespread application of TILs as a predictive tool for immunotherapy response requires further validation and standardization.
Specific mutated genes
Specific gene mutations may exert effects on tumor cells that impact immune surveillance. Notably, several single gene biomarkers may impact treatment decisions with ICIs. In patients with melanoma, several gene mutations, including BRAF, JAK1/2, β2-microglobulin (β2M) and mutations in the interferon γ (IFN-γ) pathway, are associated with the efficacy of immunotherapies (162-167). SERPINB3 and SERPINB4 mutations have also been shown to be associated with the response to anti-CTLA4 immunotherapy in patients with melanoma, independent of tumor stage, TMB and patient age (168). In addition, inactivation of PTEN may be associated with resistance to ICIs in melanoma and uterine leiomyosarcoma (169,170). Patients with NSCLC and STK11/LKB1 or EGFR mutations, or ALK rearrangements, exhibited decreased efficacy and low response rates to ICIs. By contrast, KRAS/TP53 mutations were associated with improved clinical outcomes (171-173). In patients with RCC, PBRM1 mutations may be associated with clinical benefits of ICIs (174-178). Moreover, high-throughput clustered regularly interspaced short palindromic repeats screening has identified numerous genes associated with improved clinical benefits of ICIs, such as PTPN2, APLNR and SWI/SNF complex genes (179-181).
A collection of peptides presented to the cell surface by class I and class II human leukocyte antigen (HLA) molecules are referred to as the immunopeptidome. Cancer cells may have defective HLA-I functions, leading to abnormal tumor antigen presentation and the destruction of antigen-MHC binding; thus, evading immune surveillance and impacting the efficacy of immunotherapy (182,183). Results of a previous study demonstrated that loss of HLA expression impacted the response to ICI therapy (184). Moreover, a further study analyzed the HLA-I genotype of 1,535 patients with advanced tumors treated with ICIs. The results demonstrated that in patients with maximal heterozygosity at the HLA-I loci ('A', 'B', and 'C'), OS was improved following treatment with ICIs, compared with that of patients who were homozygous for at least one HLA locus. This may improve the ability of providing a wider range of tumor antigens to T cells (185). Therefore, these studies indicated that the recognition of neoantigens by peripheral T lymphocytes is the main mechanism of antitumor immune response. The widespread application of these technologies still requires further validation.
Peripheral blood biomarkers
Considering the advantages of non-invasive surgery, peripheral blood detection technology has remained the focus of research surrounding hematological markers associated with the efficacy of ICIs. In patients with metastatic melanoma treated with ipilimumab, previous studies demonstrated that survival was significantly associated with low serum lactate dehydrogenase, absolute monocyte counts, myeloid-derived suppressor cells (MDSCs), high CD8 effector-memory type 1 T cells, absolute eosinophil counts and absolute lymphocyte counts (186-189). Moreover, baseline absolute neutrophil counts and derived neutrophil-to-lymphocyte ratios have been reported to be significantly associated with the survival of patients with melanoma treated with ipilimumab (187). The neutrophil-to-lymphocyte ratio was also shown to be significantly associated with survival in patients with metastatic RCC (190). In patients with melanoma treated with pembrolizumab, results of a previous study demonstrated that increased relative lymphocyte count at baseline was associated with improved clinical outcomes (191). In patients with NSCLC treated with anti-PD-1/PD-L1 agents as second- or third-line therapies, PD-L1 expression in circulating tumor cells exhibited potential as a prognostic biomarker (192). In addition, numerous features of peripheral blood components are associated with the response to ICIs, including classical monocyte (CD14+CD16− CD33+HLA-DR+) frequency (193), serum vascular endothelial growth factor level (194,195), soluble CD25 levels (188), and serum cytokine levels of IFN-γ, IL-18, IL-6 and IL-8 (124,196,197). Moreover, circulating exosomes containing PD-L1, PD-1 or CD28 may be associated with responses to ICIs (198-200). These blood-based biomarkers may be obtained in a clinical setting and do not incur any additional costs to the patient. However, there is still much to learn from more retrospective and prospective studies evaluating the value of both approved and developing peripheral blood biomarkers, meanwhile care should be taken to avoiding redundancy between biomarkers.
Intestinal microbiota
Previous studies have demonstrated that intestinal microbiota may affect the occurrence and development of cancer, through modulating immunity and regulating cell metabolism (201,202). Within antitumor immunotherapy, intestinal microbiota may impact the therapeutic effects of ICIs. Results of a previous study demonstrated that tumors in antibiotic-treated or germ-free mice did not respond to a CTLA inhibitor; however, treatment response occurred following gavage with Bacteroides fragilis (203). Moreover, results of a further study demonstrated that treatment with an oral microorganism combined with a PD-L1 antibody reduced tumor outgrowth in mice (204). These studies demonstrated that controlling the microbiota may aid in regulating cancer immunotherapy. Notably, comparable results were observed in the clinic. Results of a clinical retrospective study demonstrated that clinical benefits were reduced in patients who used antibiotics before and after treatment with ICIs, compared with patients who did not use antibiotics. Notably, the antibiotics may have impacted the homeostasis of the intestinal microflora (205). Patients with NSCLC, RCC, metastatic melanoma or UC with a high microbial diversity, including specific species such as Ruminococcus, Bifidobacterium or Enterococcus, exhibited favorable responses to PD-1 inhibitors (205-207). Moreover, results of previous studies demonstrated that germ-free mice that received fecal microbiota transplantation from patients with cancer who responded to ICIs exhibited improved responses to ICIs, compared with those that received fecal microbiota transplantation from non-responders (203,205,206). Collectively, these results demonstrated that intestinal microbiota are influential in antitumor immunity and responses to ICI. At present, the immune regulation mechanism of intestinal microbiota is not fully understood. With the development of the Human Microbiome Program and the advancement of sequencing analysis technology, research on intestinal microbiota is increasing, and metabolomics analysis technology further enhances the exploration of the relationship between intestinal microbiota and host immunity. Two caveats should be mentioned regarding research on intestinal microbiota. First, the differences in the application of microbial sequencing analysis techniques among different studies have limited comparability between research results. Second, the intestinal microbiota is influenced by various factors, such as diet, medication, age and environment, and there is also serious interference between different microorganisms. Regardless, reasonable antibiotic selection provides new possibilities for improving the antitumor efficacy and reducing adverse reactions of ICIs (204).
In addition, epigenetic signatures, liquid biomarkers and the tumor metabolism microenvironment may be associated with responses to ICIs (206,208). In conclusion, there are numerous potential biomarkers for predicting the effectiveness of ICIs; however, these efficacy prediction biomarkers often do not work alone, and different biomarkers interact in tumor specimens or blood specimens. The combined application of multiple predictive biomarkers can better screen out the population that will respond best to ICIs, and maximize the clinical benefits of patients. Thus, further large-scale prospective studies for comparison and validation are required prior to use in clinical practice. Further detection of multiple biomarkers, establishing standard biomarker test procedures, and maintaining high repeatability and low costs are all considerations that must be addressed.
5. Resistance mechanisms to ICIs
ICIs exhibit potential in the treatment of some advanced tumors; however, the majority of patients do not benefit from ICIs as a single therapy due to the complexity of drug resistance mechanisms. Improving the current understanding of mechanisms limiting cancer immunotherapy may aid in the discovery of novel therapeutic targets and provide potential combination treatment strategies. Multiple tumor-intrinsic and -extrinsic factors may contribute to both primary resistance, in which tumors do not respond to initial therapy, and acquired resistance, such as relapse after an initial response.
Tumor-intrinsic factors for primary resistance
Tumor cells may escape from immune surveillance through abnormal antigen processing and presentation. Genetic mutations in β2M, a component of the MHC-I molecule required for antigen presentation, are present in various cancer types and associated with evading the T-cell immune response (166,183,209-212). Therefore, alterations in antigen-presenting machinery must be taken into consideration prior to ICI treatment.
Gene alterations in specific signaling pathways also serve significant and complex roles in mediating immunotherapy resistance. Alterations in oncogenic signaling pathways include: i) Loss of IFN-γ signaling pathways; ii) upregulation of the Wnt-β-catenin signaling pathway; and iii) loss of PTEN expression, which enhances PI3K signaling. Loss-of-function mutations in JAK1 and/or JAK2 involved in the IFN-γ signaling pathway have been observed in patients who exhibited resistance to PD-1 inhibitors (167). Other genetic mutations in the IFN-γ pathway, including IFN-γ receptor 1 and 2, and interferon regulatory factor 1, have also been observed in patients who exhibited resistance to CTLA-4 inhibitors (165). These mutations may inhibit IFN-γ signal transduction and allow tumor cells to escape from T cells. In addition, mutations in this pathway may lead to the downregulation of PD-L1 expression following IFN-γ exposure, thus reducing the therapeutic effect of PD-1/PD-L1 antibodies (213). Upregulation of the Wnt-β-catenin signaling pathway has been detected in a subset of patients with melanoma, and this was revealed to be associated with resistance to ICIs (214). Notably, β-catenin suppresses CCL4 secretion, a chemokine that attracts DCs, subsequently leading to failure of T-cell activation and function (215). Loss of PTEN expression has also been associated with ICI resistance, resulting from enhanced PI3K signaling (169,170,216). Moreover, mutations in the MAPK signaling pathway may lead to cancer immune evasion, through enhancing the expression of the immunoregulatory cytokines IL-6 and IL-10 (217).
An additional tumor intrinsic mechanism is the compensatory upregulation of other immune checkpoints, such as VISTA, Tim-3 and TIGIT (218-220). Moreover, the transition of epithelial cells to mesenchymal cells, characterized by increased migration and invasion, and resistance to apoptosis, may also have a role in ICI resistance (221-223). Numerous genes have been reported to be associated with a lack of response to PD-1 blockade, known as innate anti-PD-1 resistance signatures (80). Further understanding of these resistance mechanisms is required for informing clinical management and developing personalized therapies.
Tumor-extrinsic factors for primary resistance
The highly immunosuppressive TME is considered the tumor extrinsic mechanism of ICI resistance. The TME includes immunosuppressive cells, cytokines, chemokines and metabolites that restrain antitumor immunity (121). The immunosuppressive cells include Tregs, MDSCs, tumor-associated macrophages (TAMs) and MSCs, and these suppress immune responses through numerous mechanisms (224-228). The immunosuppressive cytokines, chemokines and metabolites, such as transforming growth factor-β (TGF-β), CCL5, CXCL8 and IDO are secreted by cancer cells and immunosuppressive cells in the TME (229-232). Collectively, these factors create a functionally inhibitory microenvironment that causes resistance to immunotherapy.
Acquired resistance to immunotherapy
Acquired resistance refers to cancer that progresses and relapses following initial responses to immunotherapy. The potential mechanisms underlying acquired resistance include the inability of T cells to recognize tumor cells, due to lack of antigen expression or antigen presentation function defects, upregulation of alternative immune checkpoints, T-cell depletion, and immune escape. The mechanisms of abnormal antigen recognition or upregulation of other immune checkpoints have been aforementioned. The factors that lead to T-cell depletion are multifaceted. For example, epigenetic dysfunction makes T cells resistant to remodeling and activation (233). In addition, elevated IDO or lactate dehydrogenase in the TME may diminish T-cell responses. Furthermore, impaired production of memory T cells may lead to the weakening of the effects of ICIs over time, leading to acquired drug resistance (233).
Although resistance to immunotherapy may manifest at different times, from initial therapy to relapse after an initial response, similar or overlapping mechanisms enable tumor cells to evade antitumor immune responses. For example, IFN-γ signaling pathways are key factors for both primary and acquired drug resistance (165,167,213,233). Moreover, resistance mechanisms are dynamic (233). Therefore, targeting a single drug resistance mechanism is unlikely to be sufficient to eradicate immunotherapeutically refractory tumors. Thus, the precise selection of sensitive populations, dynamic monitoring of drug resistance, an increased search for synergistic combination therapies, and the development of novel targets and drugs are required to overcome resistance to immunotherapy.
6. Combination of ICIs with other therapeutic strategies
The effectiveness of ICI therapy is limited by various factors, and further investigations into reducing resistance are required. To determine an optimal antitumor immune response, combination treatments that combine ICIs with other therapeutic strategies, such as surgery, radiotherapy, chemotherapy and other forms of immunotherapy are required.
Immunotherapy may be combined with surgery in a neoadjuvant setting (before surgery) or an adjuvant setting (after surgery). Neoadjuvant treatment using chemotherapy or radiotherapy before surgery exhibits specific advantages over adjuvant treatment; however, current literature surrounding neoadjuvant immunotherapy is lacking. From a biological standpoint, neoadjuvant immunotherapy may reinvigorate exhausted cytotoxic T cells when antigens are encountered, and the exposure to antigens during the presence of major tumor mass may increase the breadth and persistence of tumor-specific T-cell responses. Compared with adjuvant immunotherapy, neoadjuvant immunotherapy may effectively reduce tumor mass and improve the probability of complete surgical resection (234). Besides, neoadjuvant immunotherapy has been reported to be superior to adjuvant immunotherapy in eradicating micrometastases, thereby reducing the probability of recurrence (234). Moreover, fewer infusions of neoadjuvant immunotherapy provides reduced exposure to immunotherapy, limiting the development of resistant clones in relapsed patients. The results of previous preclinical and clinical studies have demonstrated that neoadjuvant immunotherapy can improve response and survival rates, compared with the same therapy administered in the adjuvant setting (234-236). In the first clinical trial that performed a head-to-head comparison of neoadjuvant and adjuvant ICIs for the treatment of stage III resectable melanoma, the patients were treated either post-surgery for 12 weeks with a combination of ipilimumab + nivolumab, or in a split design for 6 weeks before surgery and for 6 weeks post-surgery (NCT02437279). The result showed that OS was 90% for patients treated with neoadjuvant ICI therapy and 67% for patients treated with adjuvant ICI therapy at a median follow-up time of 32 months (234). At the European Society of Internal Oncology Immunooncology Conference in 2022, a phase II CA209-8D8 study of neoadjuvant therapy for NSCLC based on nivolumab, led by Professor Wu Yilong (Guangdong Provincial People's Hospital, Guangzhou, China), also announced the advantages of neoadjuvant immunotherapy (237). Specifically, patients can benefit from nivolumab + chemotherapy regardless of PD-L1 expression, and the neoadjuvant therapy does not affect the timing and feasibility of surgery, nor does it increase the difficulty of surgery (237). However, further investigations into the optimal duration of neoadjuvant immunotherapy and surgery, the optimal type of immunotherapy, and the efficacy and safety of neoadjuvant immunotherapy are required.
Radiotherapy and chemotherapy may induce apoptosis of tumor cells, also known as immunogenic cell death, resulting in greater antigen presentation and enhanced antitumor immune responses (238). The results of previous studies demonstrated improved efficacy when radiotherapy or chemotherapy was used in combination with ICIs (239-243). Combined targeting of multiple immune checkpoints, including CTLA-4, PD-1, LAG-3, Tim-3, OX40 and glucocorticoid-induced tumor necrosis factor receptor exerts significant survival benefits, compared with single targeting (164,244-246). However, some immune checkpoints are expressed only after initial T-cell priming; thus, ICIs may be limited to tumors that require reverse exhaustion and restoration of T-cell function (247). In addition to antibody-based immunotherapy, the combination of ICIs with other forms of immunotherapy, such as cancer vaccines, oncolytic viruses or T-cell adoptive therapies are being explored in clinical trials at present (248-252). Moreover, the combination of ICIs with small molecule inhibitors targeting i) immunosuppressive cells, such as MDSCs and TAMs; ii) cytokines, such as TGF-β; or iii) metabolites, such as IDO, are being developed to enhance responses to ICIs (229,253). Notably, these studies provide guidance on delivering combination therapies. There are still a number of issues that need to be addressed before these combination therapies become clinical standards, including indications, applicable population, combination medication sequence, medication time, dosage, efficacy evaluation standards and adverse reaction prediction. Therefore, further preclinical investigations and clinical trial designs are required.
7. Adverse events associated with ICIs
The application of ICIs, either alone or in combination with other therapeutic strategies, has increased in patients with refractory metastatic cancer, and also as adjuvant or neoadjuvant therapy in the early stages of cancer. Although these treatments are often well tolerated, immune-related adverse events (irAEs) may also occur, resulting from activation of the immune system and off-target immune attack on healthy tissues of the host, which may affect almost any organ system with varying severities (254). Notably, irAEs are often graded using the National Cancer Institute Common Terminology Criteria for Adverse events (254).
As a systemic adverse reaction, fatigue is the most commonly reported, followed by infusion reactions (255). Moreover, adverse reactions of the skin and gastrointestinal tract are the most common following treatment with any approved ICI. Skin rash and pruritus are the most widely reported symptoms of skin toxicity. Notably, anti-CTLA-4 treatment causes the highest rate of adverse reactions, occurring in 40-50% of cases, followed by anti-PD-1 treatment (30-40%). In addition, anti-PD-L1 treatment causes the lowest rate of adverse reactions, occurring in 1-7% of cases (255,256). Other skin toxicities include vitiligo, photosensitive reaction and xerosis. Rare cases of Stevens-Johnson syndrome and toxic epidermal necrolysis have been reported, and these may be fatal (255). Often, the majority of skin toxicities are low-grade and easily managed with emollients, oral antihistamines and topical corticosteroids, while high-grade adverse events require permanent cessation of ICIs. Gastrointestinal toxicities often present as diarrhea and/or colitis. In total, in a previous study, ~30% of patients who received anti-CTLA-4 treatment, 20% of patients who received anti-PD-1 treatment and 45% of patients who received combination treatment developed diarrhea (257,258). Prompt recognition and intervention are crucial in preventing additional complications, such as colonic perforation. It is generally recommended that all patients receiving ICIs who present with diarrhea should undergo stool analyses for enteric pathogens and Clostridium difficile toxins. Patients with grade ≥2 diarrhea may require steroid treatment, whereas patients with grade 4 diarrhea/colitis or recurrent diarrhea should stop ICI treatment permanently (259). Endocrine toxicity associated with ICI therapy may involve the thyroid, pituitary or adrenal gland. The most common adverse effect is hypophysitis; however, others include hypothyroidism, hyperthyroidism, thyroiditis, primary adrenal insufficiency, type 1 diabetes mellitus and hypoparathyroidism. Therefore, examination of thyroid function pre-treatment and monitoring during treatment are essential (260). Hepatic adverse events that occur following ICI therapy often present as increases in asymptomatic transaminase, with or without increases in bilirubin; however, autoimmune-like hepatitis with increased severity and acute liver failure may also occur. Patients with grade ≥2 toxicities should be treated with systemic steroid treatment (253). Pulmonary irAEs, such as pneumonitis, are uncommon; however, these may be fatal. The incidence rate of pulmonary irAEs is higher following treatment with anti-PD-1 and/or combined treatment, compared with anti-CTLA-4 treatment. Timing of systemic steroid treatment is crucial and potential infection should be excluded (261). Other irAEs, such as neurologic, ocular, renal, hematological, rheumatologic and cardiovascular toxicities are rare. Following single drug treatment, the incidence rate of these events is <2%; however, following the development of grade 3-4 adverse reactions, patients should stop ICI treatment permanently (259).
Although treatment options are available for irAEs, these can progress, and in some cases, be life threatening. Management of irAEs is often complex and requires close collaboration with clinical experts. Further identification of predictive biomarkers of irAEs, such as T-cell or B-cell biomarkers, microbiome biomarkers and genomic biomarkers, will aid in guiding treatment decisions (262). Furthermore, it is necessary to encourage the establishment of a large-scale pharmacovigilance registration system and collect the records of irAEs in real-world patients following treatment with ICIs. This can not only verify the existing conclusions obtained through real-world large sample data, but also use these records for new research, such as determining the clinical characteristics of various irAEs, exploring their important risk factors, and providing an important basis for the diagnosis and treatment of irAEs.
8. Conclusions
Immunotherapy has emerged as a novel cancer treatment. The present review summarized the history and novel developments of ICIs. However, the number of patients benefiting from ICIs remains low, and further studies should focus on understanding the specific interactions between tumors and the immune system, and resistance mechanisms relevant to immunotherapy. Notably, the immune system of each patient is dynamic and constantly evolving, highlighting that personalized treatment options are required. Future research should focus on developing ICIs for use in an increased number of patients with cancer. In addition, ICIs should also be developed for use in all fields of oncology, to expand the options available for combination strategies. ICIs may be combined with surgery, chemotherapy, radiotherapy, targeted therapy and other forms of immunotherapy; however, efficient toxicity management strategies are required.
Moreover, identification of novel biomarkers that predict response or resistance is essential for accurately selecting specific ICIs. Existing biomarkers, such as PD-L1, dMMR, MSI-H and TMB, are widely used in clinical practice; however, factors such as tumor type, tumor heterogeneity, tumor dynamics and testing procedures may impact the accuracy of these biomarkers. Therefore, optimizing existing biomarkers, and developing new biomarkers or new biomarker systems that integrate immune profiling, tumor biology and treatment history are key in future investigations.
The field of immunotherapy is challenging, but also exhibits potential. In the future, immunotherapy will require developments at a multi-directional level. Further investigations should explore novel inhibitory checkpoints and pathways, and also integrate other fields, such as cancer biology, genetics and epigenetics. Moreover, further high-quality clinical trials of ICIs are required, to advance evidence-based medicine and develop new cancer treatment options.
Availability of data and materials
Not applicable.
Authors' contributions
HC and JHW contributed to the conception and design of the review. YJW and SY wrote the first draft of the manuscript. LW and WL wrote sections of the manuscript. Data authentication is not applicable. All authors contributed to manuscript revision, and read and approved the final manuscript.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Acknowledgments
Not applicable.
Funding
This work was supported by the National Natural Science Foundation of China (grant no. 82100238), the Science and Technology Program of Guangzhou (grant no. 202201011046), the High-level Hospital Construction Project (grant no. DFJH201923) and the Medical Scientific Research Foundation of Guangdong Province (grant no. A2019063).
References
Li K and Tian H: Development of small-molecule immune checkpoint inhibitors of PD-1/PD-L1 as a new therapeutic strategy for tumour immunotherapy. J Drug Target. 27:244–256. 2019. View Article : Google Scholar | |
Hanahan D and Weinberg RA: Hallmarks of cancer: The next generation. Cell. 144:646–674. 2011. View Article : Google Scholar : PubMed/NCBI | |
Dunn GP, Bruce AT, Ikeda H, Old LJ and Schreiber RD: Cancer immunoediting: From immunosurveillance to tumor escape. Nat Immunol. 3:991–998. 2002. View Article : Google Scholar : PubMed/NCBI | |
Dillman RO: Cancer immunotherapy. Cancer Biother Radiopharm. 26:1–64. 2011.PubMed/NCBI | |
Stewart TJ and Smyth MJ: Improving cancer immunotherapy by targeting tumor-induced immune suppression. Cancer Metastasis Rev. 30:125–140. 2011. View Article : Google Scholar : PubMed/NCBI | |
Sharma P, Wagner K, Wolchok JD and Allison JP: Novel cancer immunotherapy agents with survival benefit: Recent successes and next steps. Nat Rev Cancer. 11:805–812. 2011. View Article : Google Scholar : PubMed/NCBI | |
Pardoll DM: The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 12:252–264. 2012. View Article : Google Scholar : PubMed/NCBI | |
Sharma P and Allison JP: The future of immune checkpoint therapy. Science. 348:56–61. 2015. View Article : Google Scholar : PubMed/NCBI | |
Topalian SL, Drake CG and Pardoll DM: Immune checkpoint blockade: A common denominator approach to cancer therapy. Cancer Cell. 27:450–461. 2015. View Article : Google Scholar : PubMed/NCBI | |
Hoos A: Development of immuno-oncology drugs-from CTLA4 to PD1 to the next generations. Nat Rev Drug Discov. 15:235–247. 2016. View Article : Google Scholar : PubMed/NCBI | |
Wei SC, Duffy CR and Allison JP: Fundamental mechanisms of immune checkpoint blockade therapy. Cancer Discov. 8:1069–1086. 2018. View Article : Google Scholar : PubMed/NCBI | |
Sharma P and Allison JP: Immune checkpoint targeting in cancer therapy: Toward combination strategies with curative potential. Cell. 161:205–214. 2015. View Article : Google Scholar : PubMed/NCBI | |
Sharpe AH: Mechanisms of costimulation. Immunol Rev. 229:5–11. 2009. View Article : Google Scholar : PubMed/NCBI | |
Rudd CE, Taylor A and Schneider H: CD28 and CTLA-4 coreceptor expression and signal transduction. Immunol Rev. 229:12–26. 2009. View Article : Google Scholar : PubMed/NCBI | |
Chen L and Flies DB: Molecular mechanisms of T cell co-stimulation and co-inhibition. Nat Rev Immunol. 13:227–242. 2013. View Article : Google Scholar : PubMed/NCBI | |
Brunet JF, Denizot F, Luciani MF, Roux-Dosseto M, Suzan M, Mattei MG and Golstein P: A new member of the immunoglobulin superfamily-CTLA-4. Nature. 328:267–270. 1987. View Article : Google Scholar : PubMed/NCBI | |
Krummel MF and Allison JP: CD28 and CTLA-4 have opposing effects on the response of T cells to stimulation. J Exp Med. 182:459–465. 1995. View Article : Google Scholar : PubMed/NCBI | |
Linsley PS, Brady W, Urnes M, Grosmaire LS, Damle NK and Ledbetter JA: CTLA-4 is a second receptor for the B cell activation antigen B7. J Exp Med. 174:561–569. 1991. View Article : Google Scholar : PubMed/NCBI | |
Walunas TL, Lenschow DJ, Bakker CY, Linsley PS, Freeman GJ, Green JM, Thompson CB and Bluestone JA: Pillars article: CTLA-4 can function as a negative regulator of T cell activation. Immunity. 1994. 1: 405-413. J Immunol. 187:3466–3474. 2011.PubMed/NCBI | |
Linsley PS, Greene JL, Brady W, Bajorath J, Ledbetter JA and Peach R: Human B7-1 (CD80) and B7-2 (CD86) bind with similar avidities but distinct kinetics to CD28 and CTLA-4 receptors. Immunity. 1:793–801. 1994. View Article : Google Scholar : PubMed/NCBI | |
Gibson HM, Hedgcock CJ, Aufiero BM, Wilson AJ, Hafner MS, Tsokos GC and Wong HK: Induction of the CTLA-4 gene in human lymphocytes is dependent on NFAT binding the proximal promoter. J Immunol. 179:3831–3840. 2007. View Article : Google Scholar : PubMed/NCBI | |
Waterhouse P, Penninger JM, Timms E, Wakeham A, Shahinian A, Lee KP, Thompson CB, Griesser H and Mak TW: Lymphoproliferative disorders with early lethality in mice deficient in Ctla-4. Science. 270:985–988. 1995. View Article : Google Scholar : PubMed/NCBI | |
Tivol EA, Borriello F, Schweitzer AN, Lynch WP, Bluestone JA and Sharpe AH: Loss of CTLA-4 leads to massive lymphoproliferation and fatal multiorgan tissue destruction, revealing a critical negative regulatory role of CTLA-4. Immunity. 3:541–547. 1995. View Article : Google Scholar : PubMed/NCBI | |
Read S, Greenwald R, Izcue A, Robinson N, Mandelbrot D, Francisco L, Sharpe AH and Powrie F: Blockade of CTLA-4 on CD4+CD25+ regulatory T cells abrogates their function in vivo. J Immunol. 177:4376–4383. 2006. View Article : Google Scholar : PubMed/NCBI | |
Wing K, Onishi Y, Prieto-Martin P, Yamaguchi T, Miyara M, Fehervari Z, Nomura T and Sakaguchi S: CTLA-4 control over Foxp3+ regulatory T cell function. Science. 322:271–275. 2008. View Article : Google Scholar : PubMed/NCBI | |
Schneider H, Smith X, Liu H, Bismuth G and Rudd CE: CTLA-4 disrupts ZAP70 microcluster formation with reduced T cell/APC dwell times and calcium mobilization. Eur J Immunol. 38:40–47. 2008. View Article : Google Scholar | |
Wang XB, Fan ZZ, Anton D, Vollenhoven AV, Ni ZH, Chen XF and Lefvert AK: CTLA4 is expressed on mature dendritic cells derived from human monocytes and influences their maturation and antigen presentation. BMC Immunol. 12:212011. View Article : Google Scholar : PubMed/NCBI | |
Boasso A, Herbeuval JP, Hardy AW, Winkler C and Shearer GM: Regulation of indoleamine 2,3-dioxygenase and tryptophanyl-tRNA-synthetase by CTLA-4-Fc in human CD4+ T cells. Blood. 105:1574–1581. 2005. View Article : Google Scholar | |
Leach DR, Krummel MF and Allison JP: Enhancement of antitumor immunity by CTLA-4 blockade. Science. 271:1734–1736. 1996. View Article : Google Scholar : PubMed/NCBI | |
Hodi FS, O'Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, Gonzalez R, Robert C, Schadendorf D, Hassel JC, et al: Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 363:711–723. 2010. View Article : Google Scholar : PubMed/NCBI | |
Hammers HJ, Plimack ER, Infante JR, Rini BI, McDermott DF, Lewis LD, Voss MH, Sharma P, Pal SK, Razak ARA, et al: Safety and efficacy of nivolumab in combination with ipilimumab in metastatic renal cell carcinoma: The CheckMate 016 study. J Clin Oncol. 35:3851–3858. 2017. View Article : Google Scholar : PubMed/NCBI | |
Kwon ED, Drake CG, Scher HI, Fizazi K, Bossi A, van den Eertwegh AJ, Krainer M, Houede N, Santos R, Mahammedi H, et al: Ipilimumab versus placebo after radiotherapy in patients with metastatic castration-resistant prostate cancer that had progressed after docetaxel chemotherapy (CA184-043): A multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol. 15:700–712. 2014. View Article : Google Scholar : PubMed/NCBI | |
Le DT, Lutz E, Uram JN, Sugar EA, Onners B, Solt S, Zheng L, Diaz LA Jr, Donehower RC, Jaffee EM and Laheru DA: Evaluation of ipilimumab in combination with allogeneic pancreatic tumor cells transfected with a GM-CSF gene in previously treated pancreatic cancer. J Immunother. 36:382–389. 2013. View Article : Google Scholar : PubMed/NCBI | |
Zhao X and Subramanian S: Intrinsic resistance of solid tumors to immune checkpoint blockade therapy. Cancer Res. 77:817–822. 2017. View Article : Google Scholar : PubMed/NCBI | |
Duffy AG, Ulahannan SV, Makorova-Rusher O, Rahma O, Wedemeyer H, Pratt D, Davis JL, Hughes MS, Heller T, ElGindi M, et al: Tremelimumab in combination with ablation in patients with advanced hepatocellular carcinoma. J Hepatol. 66:545–551. 2017. View Article : Google Scholar : | |
Selby MJ, Engelhardt JJ, Quigley M, Henning KA, Chen T, Srinivasan M and Korman AJ: Anti-CTLA-4 antibodies of IgG2a isotype enhance antitumor activity through reduction of intratumoral regulatory T cells. Cancer Immunol Res. 1:32–42. 2013. View Article : Google Scholar | |
Marangoni F, Zhakyp A, Corsini M, Geels SN, Carrizosa E, Thelen M, Mani V, Prüßmann JN, Warner RD, Ozga AJ, et al: Expansion of tumor-associated Treg cells upon disruption of a CTLA-4-dependent feedback loop. Cell. 184:3998–4015.e19. 2021. View Article : Google Scholar : PubMed/NCBI | |
Ishida Y, Agata Y, Shibahara K and Honjo T: Induced expression of PD-1, a novel member of the immunoglobulin gene superfamily, upon programmed cell death. EMBO J. 11:3887–3895. 1992. View Article : Google Scholar : PubMed/NCBI | |
Nishimura H, Nose M, Hiai H, Minato N and Honjo T: Development of lupus-like autoimmune diseases by disruption of the PD-1 gene encoding an ITIM motif-carrying immunoreceptor. Immunity. 11:141–151. 1999. View Article : Google Scholar : PubMed/NCBI | |
Dong H, Zhu G, Tamada K and Chen L: B7-H1, a third member of the B7 family, co-stimulates T-cell proliferation and interleukin-10 secretion. Nat Med. 5:1365–1369. 1999. View Article : Google Scholar : PubMed/NCBI | |
Freeman GJ, Long AJ, Iwai Y, Bourque K, Chernova T, Nishimura H, Fitz LJ, Malenkovich N, Okazaki T, Byrne MC, et al: Engagement of the PD-1 immunoinhibitory receptor by a novel B7 family member leads to negative regulation of lymphocyte activation. J Exp Med. 192:1027–1034. 2000. View Article : Google Scholar : PubMed/NCBI | |
Agata Y, Kawasaki A, Nishimura H, Ishida Y, Tsubata T, Yagita H and Honjo T: Expression of the PD-1 antigen on the surface of stimulated mouse T and B lymphocytes. Int Immunol. 8:765–772. 1996. View Article : Google Scholar : PubMed/NCBI | |
Keir ME, Butte MJ, Freeman GJ and Sharpe AH: PD-1 and its ligands in tolerance and immunity. Annu Rev Immunol. 26:677–704. 2008. View Article : Google Scholar : PubMed/NCBI | |
Latchman Y, Wood CR, Chernova T, Chaudhary D, Borde M, Chernova I, Iwai Y, Long AJ, Brown JA, Nunes R, et al: PD-L2 is a second ligand for PD-1 and inhibits T cell activation. Nat Immunol. 2:261–268. 2001. View Article : Google Scholar : PubMed/NCBI | |
Okazaki T and Honjo T: The PD-1-PD-L pathway in immunological tolerance. Trends Immunol. 27:195–201. 2006. View Article : Google Scholar : PubMed/NCBI | |
Zamani MR, Aslani S, Salmaninejad A, Javan MR and Rezaei N: PD-1/PD-L and autoimmunity: A growing relationship. Cell Immunol. 310:27–41. 2016. View Article : Google Scholar : PubMed/NCBI | |
Barber DL, Wherry EJ, Masopust D, Zhu B, Allison JP, Sharpe AH, Freeman GJ and Ahmed R: Restoring function in exhausted CD8 T cells during chronic viral infection. Nature. 439:682–687. 2006. View Article : Google Scholar | |
Pauken KE and Wherry EJ: Overcoming T cell exhaustion in infection and cancer. Trends Immunol. 36:265–276. 2015. View Article : Google Scholar : PubMed/NCBI | |
Ahmadzadeh M, Johnson LA, Heemskerk B, Wunderlich JR, Dudley ME, White DE and Rosenberg SA: Tumor antigen-specific CD8 T cells infiltrating the tumor express high levels of PD-1 and are functionally impaired. Blood. 114:1537–1544. 2009. View Article : Google Scholar : PubMed/NCBI | |
Yaghoubi N, Soltani A, Ghazvini K, Hassanian SM and Hashemy SI: PD-1/PD-L1 blockade as a novel treatment for colorectal cancer. Biomed Pharmacother. 110:312–318. 2019. View Article : Google Scholar | |
Patsoukis N, Wang Q, Strauss L and Boussiotis VA: Revisiting the PD-1 pathway. Sci Adv. 6:eabd27122020. View Article : Google Scholar : PubMed/NCBI | |
Sharpe AH, Wherry EJ, Ahmed R and Freeman GJ: The function of programmed cell death 1 and its ligands in regulating autoimmunity and infection. Nat Immunol. 8:239–245. 2007. View Article : Google Scholar : PubMed/NCBI | |
Zhong X, Tumang JR, Gao W, Bai C and Rothstein TL: PD-L2 expression extends beyond dendritic cells/macrophages to B1 cells enriched for V(H)11/V(H)12 and phosphatidylcholine binding. Eur J Immunol. 37:2405–2410. 2007. View Article : Google Scholar : PubMed/NCBI | |
Sharpe AH and Pauken KE: The diverse functions of the PD1 inhibitory pathway. Nat Rev Immunol. 18:153–167. 2018. View Article : Google Scholar | |
Ribas A and Hu-Lieskovan S: What does PD-L1 positive or negative mean? J Exp Med. 213:2835–2840. 2016. View Article : Google Scholar : PubMed/NCBI | |
Dong H, Strome SE, Salomao DR, Tamura H, Hirano F, Flies DB, Roche PC, Lu J, Zhu G, Tamada K, et al: Tumor-associated B7-H1 promotes T-cell apoptosis: A potential mechanism of immune evasion. Nat Med. 8:793–800. 2002. View Article : Google Scholar : PubMed/NCBI | |
Brown JA, Dorfman DM, Ma FR, Sullivan EL, Munoz O, Wood CR, Greenfield EA and Freeman GJ: Blockade of programmed death-1 ligands on dendritic cells enhances T cell activation and cytokine production. J Immunol. 170:1257–1266. 2003. View Article : Google Scholar : PubMed/NCBI | |
Konishi J, Yamazaki K, Azuma M, Kinoshita I, Dosaka-Akita H and Nishimura M: B7-H1 expression on non-small cell lung cancer cells and its relationship with tumor-infiltrating lymphocytes and their PD-1 expression. Clin Cancer Res. 10:5094–5100. 2004. View Article : Google Scholar : PubMed/NCBI | |
Brahmer JR, Drake CG, Wollner I, Powderly JD, Picus J, Sharfman WH, Stankevich E, Pons A, Salay TM, McMiller TL, et al: Phase I study of single-agent anti-programmed death-1 (MDX-1106) in refractory solid tumors: Safety, clinical activity, pharmacodynamics, and immunologic correlates. J Clin Oncol. 28:3167–3175. 2010. View Article : Google Scholar : PubMed/NCBI | |
Gettinger S, Rizvi NA, Chow LQ, Borghaei H, Brahmer J, Ready N, Gerber DE, Shepherd FA, Antonia S, Goldman JW, et al: Nivolumab monotherapy for first-line treatment of advanced non-small-cell lung cancer. J Clin Oncol. 34:2980–2987. 2016. View Article : Google Scholar : PubMed/NCBI | |
Rizvi NA, Mazières J, Planchard D, Stinchcombe TE, Dy GK, Antonia SJ, Horn L, Lena H, Minenza E, Mennecier B, et al: Activity and safety of nivolumab, an anti-PD-1 immune checkpoint inhibitor, for patients with advanced, refractory squamous non-small-cell lung cancer (CheckMate 063): A phase 2, single-arm trial. Lancet Oncol. 16:257–265. 2015. View Article : Google Scholar : PubMed/NCBI | |
Motzer RJ, Escudier B, McDermott DF, George S, Hammers HJ, Srinivas S, Tykodi SS, Sosman JA, Procopio G, Plimack ER, et al: Nivolumab versus everolimus in advanced renal-cell carcinoma. N Engl J Med. 373:1803–1813. 2015. View Article : Google Scholar : PubMed/NCBI | |
Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, Powderly JD, Carvajal RD, Sosman JA, Atkins MB, et al: Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 366:2443–2454. 2012. View Article : Google Scholar : PubMed/NCBI | |
Robert C, Ribas A, Wolchok JD, Hodi FS, Hamid O, Kefford R, Weber JS, Joshua AM, Hwu WJ, Gangadhar TC, et al: Anti-p rogrammed-death-receptor-1 treatment with pembrolizumab in ipilimumab-refractory advanced melanoma: A randomised dose-comparison cohort of a phase 1 trial. Lancet. 384:1109–1117. 2014. View Article : Google Scholar : PubMed/NCBI | |
Ribas A, Puzanov I, Dummer R, Schadendorf D, Hamid O, Robert C, Hodi FS, Schachter J, Pavlick AC, Lewis KD, et al: Pembrolizumab versus investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A randomised, controlled, phase 2 trial. Lancet Oncol. 16:908–918. 2015. View Article : Google Scholar : PubMed/NCBI | |
Garon EB, Rizvi NA, Hui R, Leighl N, Balmanoukian AS, Eder JP, Patnaik A, Aggarwal C, Gubens M, Horn L, et al: Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med. 372:2018–2028. 2015. View Article : Google Scholar : PubMed/NCBI | |
Patnaik A, Kang SP, Rasco D, Papadopoulos KP, Elassaiss-Schaap J, Beeram M, Drengler R, Chen C, Smith L, Espino G, et al: Phase I study of pembrolizumab (MK-3475; anti-PD-1 monoclonal antibody) in patients with advanced solid tumors. Clin Cancer Res. 21:4286–4293. 2015. View Article : Google Scholar : PubMed/NCBI | |
Rihawi K, Gelsomino F, Sperandi F, Melotti B, Fiorentino M, Casolari L and Ardizzoni A: Pembrolizumab in the treatment of metastatic non-small cell lung cancer: A review of current evidence. Ther Adv Respir Dis. 11:353–373. 2017. View Article : Google Scholar : PubMed/NCBI | |
Suzman DL, Agrawal S, Ning YM, Maher VE, Fernandes LL, Karuri S, Tang S, Sridhara R, Schroeder J, Goldberg KB, et al: FDA approval summary: Atezolizumab or pembrolizumab for the treatment of patients with advanced urothelial carcinoma ineligible for cisplatin-containing chemotherapy. Oncologist. 24:563–569. 2019. View Article : Google Scholar | |
U.S. Food and Drug: FDA approves first treatment for advanced form of the second most common skin cancer. https://www.fda.gov/news-events/press-announcements/fda-approves-first-treatment-advanced-form-second-most-common-skin-cancer-0. Accessed January 20, 2023 | |
Rosenberg JE, Hoffman-Censits J, Powles T, van der Heijden MS, Balar AV, Necchi A, Dawson N, O'Donnell PH, Balmanoukian A, Loriot Y, et al: Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: A single-arm, multicentre, phase 2 trial. Lancet. 387:1909–1920. 2016. View Article : Google Scholar : PubMed/NCBI | |
Peters S, Gettinger S, Johnson ML, Jänne PA, Garassino MC, Christoph D, Toh CK, Rizvi NA, Chaft JE, Carcereny Costa E, et al: Phase II trial of atezolizumab as first-line or subsequent therapy for patients with programmed death-ligand 1-selected advanced non-small-cell lung cancer (BIRCH). J Clin Oncol. 35:2781–2789. 2017. View Article : Google Scholar : PubMed/NCBI | |
Balar AV, Galsky MD, Rosenberg JE, Powles T, Petrylak DP, Bellmunt J, Loriot Y, Necchi A, Hoffman-Censits J, Perez-Gracia JL, et al: Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: A single-arm, multicentre, phase 2 trial. Lancet. 389:67–76. 2017. View Article : Google Scholar | |
Petrylak DP, Powles T, Bellmunt J, Braiteh F, Loriot Y, Morales-Barrera R, Burris HA, Kim JW, Ding B, Kaiser C, et al: Atezolizumab (MPDL3280A) monotherapy for patients with metastatic urothelial cancer: Long-term outcomes from a phase 1 study. JAMA Oncol. 4:537–544. 2018. View Article : Google Scholar : PubMed/NCBI | |
Socinski MA, Jotte RM, Cappuzzo F, Orlandi F, Stroyakovskiy D, Nogami N, Rodriguez-Abreu D, Moro-Sibilot D, Thomas CA, Barlesi F, et al: Atezolizumab for first-line treatment of metastatic nonsquamous NSCLC. N Engl J Med. 378:2288–2301. 2018. View Article : Google Scholar : PubMed/NCBI | |
Hamilton G and Rath B: Avelumab: Combining immune checkpoint inhibition and antibody-dependent cytotoxicity. Expert Opin Biol Ther. 17:515–523. 2017. View Article : Google Scholar : PubMed/NCBI | |
Antonia SJ, Villegas A, Daniel D, Vicente D, Murakami S, Hui R, Yokoi T, Chiappori A, Lee KH, de Wit M, et al: Durvalumab after chemoradiotherapy in stage III non-small-cell lung cancer. N Engl J Med. 377:1919–1929. 2017. View Article : Google Scholar : PubMed/NCBI | |
Sunshine J and Taube JM: PD-1/PD-L1 inhibitors. Curr Opin Pharmacol. 23:32–38. 2015. View Article : Google Scholar : PubMed/NCBI | |
Gay CL, Bosch RJ, Ritz J, Hataye JM, Aga E, Tressler RL, Mason SW, Hwang CK, Grasela DM, Ray N, et al: Clinical trial of the anti-PD-L1 antibody BMS-936559 in HIV-1 infected participants on suppressive antiretroviral therapy. J Infect Dis. 215:1725–1733. 2017. View Article : Google Scholar : PubMed/NCBI | |
Hugo W, Zaretsky JM, Sun L, Song C, Moreno BH, Hu-Lieskovan S, Berent-Maoz B, Pang J, Chmielowski B, Cherry G, et al: Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell. 165:35–44. 2016. View Article : Google Scholar : PubMed/NCBI | |
Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, Skora AD, Luber BS, Azad NS, Laheru D, et al: PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med. 372:2509–2520. 2015. View Article : Google Scholar : PubMed/NCBI | |
Workman CJ and Vignali DAA: Negative regulation of T cell homeostasis by lymphocyte activation gene-3 (CD223). J Immunol. 174:688–695. 2005. View Article : Google Scholar : PubMed/NCBI | |
Goldberg MV and Drake CG: LAG-3 in cancer immunotherapy. Curr Top Microbiol Immunol. 344:269–278. 2011. | |
Anderson AC, Joller N and Kuchroo VK: Lag-3, Tim-3, and TIGIT: Co-inhibitory receptors with specialized functions in immune regulation. Immunity. 44:989–1004. 2016. View Article : Google Scholar : PubMed/NCBI | |
Demeure CE, Wolfers J, Martin-Garcia N, Gaulard P and Triebel F: T Lymphocytes infiltrating various tumour types express the MHC class II ligand lymphocyte activation gene-3 (LAG-3): Role of LAG-3/MHC class II interactions in cell-cell contacts. Eur J Cancer. 37:1709–1718. 2001. View Article : Google Scholar : PubMed/NCBI | |
Gandhi MK, Lambley E, Duraiswamy J, Dua U, Smith C, Elliott S, Gill D, Marlton P, Seymour J and Khanna R: Expression of LAG-3 by tumor-infiltrating lymphocytes is coincident with the suppression of latent membrane antigen-specific CD8+ T-cell function in Hodgkin lymphoma patients. Blood. 108:2280–2289. 2006. View Article : Google Scholar : PubMed/NCBI | |
Matsuzaki J, Gnjatic S, Mhawech-Fauceglia P, Beck A, Miller A, Tsuji T, Eppolito C, Qian F, Lele S, Shrikant P, et al: Tumor-infiltrating NY-ESO-1-specific CD8+ T cells are negatively regulated by LAG-3 and PD-1 in human ovarian cancer. Proc Natl Acad Sci USA. 107:7875–7880. 2010. View Article : Google Scholar : PubMed/NCBI | |
Li FJ, Zhang Y, Jin GX, Yao L and Wu DQ: Expression of LAG-3 is coincident with the impaired effector function of HBV-specific CD8(+) T cell in HCC patients. Immunol Lett. 150:116–122. 2013. View Article : Google Scholar | |
Andrews LP, Marciscano AE, Drake CG and Vignali DA: LAG3 (CD223) as a cancer immunotherapy target. Immunol Rev. 276:80–96. 2017. View Article : Google Scholar : PubMed/NCBI | |
Ruffo E, Wu RC, Bruno TC, Workman CJ and Vignali DAA: Lymphocyte-activation gene 3 (LAG3): The next immune checkpoint receptor. Semin Immunol. 42:1013052019. View Article : Google Scholar : PubMed/NCBI | |
Gleason MK, Lenvik TR, McCullar V, Felices M, O'Brien MS, Cooley SA, Verneris MR, Cichocki F, Holman CJ, Panoskaltsis-Mortari A, et al: Tim-3 is an inducible human natural killer cell receptor that enhances interferon gamma production in response to galectin-9. Blood. 119:3064–3072. 2012. View Article : Google Scholar : PubMed/NCBI | |
Anderson AC: Tim-3, a negative regulator of anti-tumor immunity. Curr Opin Immunol. 24:213–216. 2012. View Article : Google Scholar : PubMed/NCBI | |
Nakayama M, Akiba H, Takeda K, Kojima Y, Hashiguchi M, Azuma M, Yagita H and Okumura K: Tim-3 mediates phagocytosis of apoptotic cells and cross-presentation. Blood. 113:3821–3830. 2009. View Article : Google Scholar : PubMed/NCBI | |
Tang D and Lotze MT: Tumor immunity times out: TIM-3 and HMGB1. Nat Immunol. 13:808–810. 2012. View Article : Google Scholar : PubMed/NCBI | |
Huang YH, Zhu C, Kondo Y, Anderson AC, Gandhi A, Russell A, Dougan SK, Petersen BS, Melum E, Pertel T, et al: CEACAM1 regulates TIM-3-mediated tolerance and exhaustion. Nature. 517:386–390. 2015. View Article : Google Scholar | |
Fourcade J, Sun Z, Benallaoua M, Guillaume P, Luescher IF, Sander C, Kirkwood JM, Kuchroo V and Zarour HM: Upregulation of Tim-3 and PD-1 expression is associated with tumor antigen-specific CD8+ T cell dysfunction in melanoma patients. J Exp Med. 207:2175–2186. 2010. View Article : Google Scholar : PubMed/NCBI | |
Li H, Wu K, Tao K, Chen L, Zheng Q, Lu X, Liu J, Shi L, Liu C, Wang G and Zou W: Tim-3/galectin-9 signaling pathway mediates T-cell dysfunction and predicts poor prognosis in patients with hepatitis B virus-associated hepatocellular carcinoma. Hepatology. 56:1342–1351. 2012. View Article : Google Scholar : PubMed/NCBI | |
Yang ZZ, Grote DM, Ziesmer SC, Niki T, Hirashima M, Novak AJ, Witzig TE and Ansell SM: IL-12 upregulates TIM-3 expression and induces T cell exhaustion in patients with follicular B cell non-Hodgkin lymphoma. J Clin Invest. 122:1271–1282. 2012. View Article : Google Scholar : PubMed/NCBI | |
Gao X, Zhu Y, Li G, Huang H, Zhang G, Wang F, Sun J, Yang Q, Zhang X and Lu B: TIM-3 expression characterizes regulatory T cells in tumor tissues and is associated with lung cancer progression. PLoS One. 7:e306762012. View Article : Google Scholar : PubMed/NCBI | |
Markwick LJ, Riva A, Ryan JM, Cooksley H, Palma E, Tranah TH, Manakkat Vijay GK, Vergis N, Thursz M, Evans A, et al: Blockade of PD1 and TIM3 restores innate and adaptive immunity in patients with acute alcoholic hepatitis. Gastroenterology. 148:590–602 e10. 2015. View Article : Google Scholar | |
Stanietsky N, Simic H, Arapovic J, Toporik A, Levy O, Novik A, Levine Z, Beiman M, Dassa L, Achdout H, et al: The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity. Proc Natl Acad Sci USA. 106:17858–17863. 2009. View Article : Google Scholar : PubMed/NCBI | |
Levin SD, Taft DW, Brandt CS, Bucher C, Howard ED, Chadwick EM, Johnston J, Hammond A, Bontadelli K, Ardourel D, et al: Vstm3 is a member of the CD28 family and an important modulator of T-cell function. Eur J Immunol. 41:902–915. 2011. View Article : Google Scholar : PubMed/NCBI | |
Boles KS, Vermi W, Facchetti F, Fuchs A, Wilson TJ, Diacovo TG, Cella M and Colonna M: A novel molecular interaction for the adhesion of follicular CD4 T cells to follicular DC. Eur J Immunol. 39:695–703. 2009. View Article : Google Scholar : PubMed/NCBI | |
Kurtulus S, Sakuishi K, Ngiow SF, Joller N, Tan DJ, Teng MW, Smyth MJ, Kuchroo VK and Anderson AC: TIGIT predominantly regulates the immune response via regulatory T cells. J Clin Invest. 125:4053–4062. 2015. View Article : Google Scholar : PubMed/NCBI | |
Manieri NA, Chiang EY and Grogan JL: TIGIT: A Key inhibitor of the cancer immunity cycle. Trends Immunol. 38:20–28. 2017. View Article : Google Scholar | |
U.S. National Library of Medicine: Zimberelimab (AB122) With TIGIT Inhibitor Domvanalimab (AB154) in PD-1 Relapsed/Refractory Melanoma. https://clinicaltrials.gov/ct2/show/NCT05130177?term=NCT05130177&draw=2&rank=1. Accessed January 20, 2023 | |
U.S. National Library of Medicine: COM902 (A TIGIT Inhibitor) in Subjects With Advanced Malignancies. https://clinicaltrials.gov/ct2/show/NCT04354246?term=NCT04354246&draw=2&rank=1. Accessed January 20, 2023 | |
U.S. National Library of Medicine: Study to Assess the Safety and Efficacy of AZD2936 in Participants With Advanced or Metastatic Non-small Cell Lung Cancer (ARTEMIDE-01). https://clinicaltrials.gov/ct2/show/NCT04995523?term=NCT04995523&draw=2&rank=1. Accessed January 20, 2023 | |
Watanabe N, Gavrieli M, Sedy JR, Yang J, Fallarino F, Loftin SK, Hurchla MA, Zimmerman N, Sim J, Zang X, et al: BTLA is a lymphocyte inhibitory receptor with similarities to CTLA-4 and PD-1. Nat Immunol. 4:670–679. 2003. View Article : Google Scholar : PubMed/NCBI | |
Karakatsanis S, Bertsias G, Roussou P and Boumpas D: Programmed death 1 and B and T lymphocyte attenuator immunoreceptors and their association with malignant T-lymphoproliferative disorders: Brief review. Hematol Oncol. 32:113–119. 2014. View Article : Google Scholar | |
Pasero C and Olive D: Interfering with coinhibitory molecules: BTLA/HVEM as new targets to enhance anti-tumor immunity. Immunol Lett. 151:71–75. 2013. View Article : Google Scholar : PubMed/NCBI | |
M'Hidi H, Thibult ML, Chetaille B, Rey F, Bouadallah R, Nicollas R, Olive D and Xerri L: High expression of the inhibitory receptor BTLA in T-follicular helper cells and in B-cell small lymphocytic lymphoma/chronic lymphocytic leukemia. Am J Clin Pathol. 132:589–596. 2009. View Article : Google Scholar : PubMed/NCBI | |
Hosseinkhani N, Derakhshani A, Shadbad MA, Argentiero A, Racanelli V, Kazemi T, Mokhtarzadeh A, Brunetti O, Silvestris N and Baradaran B: The role of V-domain Ig suppressor of T cell activation (VISTA) in cancer therapy: Lessons learned and the road ahead. Front Immunol. 12:6761812021. View Article : Google Scholar : PubMed/NCBI | |
U.S. National Library of Medicine: A Study of CA-170 (Oral PD-L1 PD-L2 and VISTA Checkpoint Antagonist) in Patients With Advanced Tumors and Lymphomas. https://clinicaltrials.gov/ct2/show/NCT02812875?term=NCT02812875&draw=2&rank=1. Accessed January 20, 2023 | |
U.S. National Library of Medicine: A Study of Safety Pharmacokinetics, Pharmacodynamics of JNJ-61610588 in Participants With Advanced Cancer. https://clinicaltrials.gov/ct2/show/NCT02671955?term=NCT02671955&draw=2&rank=1. Accessed January 20, 2023 | |
U.S. National Library of Medicine: Phase 1 Study of CI-8993 Anti-VISTA Antibody in Patients With Advanced Solid Tumor Malignancies. https://clinicaltrials.gov/ct2/show/NCT04475523?term=NCT04475523&draw=2&rank=1. Accessed January 20, 2023 | |
Motzer RJ, Rini BI, McDermott DF, Redman BG, Kuzel TM, Harrison MR, Vaishampayan UN, Drabkin HA, George S, Logan TF, et al: Nivolumab for metastatic renal cell carcinoma: Results of a randomized phase II trial. J Clin Oncol. 33:1430–1437. 2015. View Article : Google Scholar | |
Gettinger SN, Horn L, Gandhi L, Spigel DR, Antonia SJ, Rizvi NA, Powderly JD, Heist RS, Carvajal RD, Jackman DM, et al: Overall survival and long-term safety of nivolumab (anti-programmed death 1 antibody, BMS-936558, ONO-4538) in patients with previously treated advanced non-small-cell lung cancer. J Clin Oncol. 33:2004–2012. 2015. View Article : Google Scholar : PubMed/NCBI | |
Hamid O, Robert C, Daud A, Hodi FS, Hwu WJ, Kefford R, Wolchok JD, Hersey P, Joseph RW, Weber JS, et al: Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. N Engl J Med. 369:134–144. 2013. View Article : Google Scholar : PubMed/NCBI | |
McDermott DF, Sosman JA, Sznol M, Massard C, Gordon MS, Hamid O, Powderly JD, Infante JR, Fassò M, Wang YV, et al: Atezolizumab, an anti-programmed death-ligand 1 antibody, in metastatic renal cell carcinoma: Long-term safety, clinical activity, and immune correlates from a phase Ia study. J Clin Oncol. 34:833–842. 2016. View Article : Google Scholar : PubMed/NCBI | |
Augustin RC, Delgoffe GM and Najjar YG: Characteristics of the tumor microenvironment that influence immune cell functions: Hypoxia, oxidative stress, metabolic alterations. Cancers (Basel). 12:38022020. View Article : Google Scholar : PubMed/NCBI | |
Wang DR, Wu XL and Sun YL: Therapeutic targets and biomarkers of tumor immunotherapy: Response versus non-response. Signal Transduct Target Ther. 7:3312022. View Article : Google Scholar : PubMed/NCBI | |
Doroshow DB, Bhalla S, Beasley MB, Sholl LM, Kerr KM, Gnjatic S, Wistuba II, Rimm DL, Tsao MS and Hirsch FR: PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat Rev Clin Oncol. 18:345–362. 2021. View Article : Google Scholar : PubMed/NCBI | |
Herbst RS, Soria JC, Kowanetz M, Fine GD, Hamid O, Gordon MS, Sosman JA, McDermott DF, Powderly JD, Gettinger SN, et al: Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature. 515:563–567. 2014. View Article : Google Scholar : PubMed/NCBI | |
Herbst RS, Baas P, Kim DW, Felip E, Pérez-Gracia JL, Han JY, Molina J, Kim JH, Arvis CD, Ahn MJ, et al: Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): A randomised controlled trial. Lancet. 387:1540–1550. 2016. View Article : Google Scholar | |
Zou W, Wolchok JD and Chen L: PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Sci Transl Med. 8:328rv42016. View Article : Google Scholar : PubMed/NCBI | |
Patel SP and Kurzrock R: PD-L1 expression as a predictive biomarker in cancer immunotherapy. Mol Cancer Ther. 14:847–856. 2015. View Article : Google Scholar : PubMed/NCBI | |
Mahoney KM and Atkins MB: Prognostic and predictive markers for the new immunotherapies. Oncology (Williston Park). 28(Suppl 3): S39–S48. 2014. | |
Kim J, Myers AC, Chen L, Pardoll DM, Truong-Tran QA, Lane AP, McDyer JF, Fortuno L and Schleimer RP: Constitutive and inducible expression of b7 family of ligands by human airway epithelial cells. Am J Respir Cell Mol Biol. 33:280–289. 2005. View Article : Google Scholar : PubMed/NCBI | |
Chen J, Jiang CC, Jin L and Zhang XD: Regulation of PD-L1: A novel role of pro-survival signalling in cancer. Ann Oncol. 27:409–416. 2016. View Article : Google Scholar | |
Meng X, Huang Z, Teng F, Xing L and Yu J: Predictive biomarkers in PD-1/PD-L1 checkpoint blockade immunotherapy. Cancer Treat Rev. 41:868–876. 2015. View Article : Google Scholar : PubMed/NCBI | |
Mansfield AS, Murphy SJ, Peikert T, Yi ES, Vasmatzis G, Wigle DA and Aubry MC: Heterogeneity of programmed cell death ligand 1 expression in multifocal lung cancer. Clin Cancer Res. 22:2177–2182. 2016. View Article : Google Scholar | |
Topalian SL, Taube JM, Anders RA and Pardoll DM: Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy. Nat Rev Cancer. 16:275–287. 2016. View Article : Google Scholar : PubMed/NCBI | |
Lee V, Murphy A, Le DT and Diaz LA Jr: Mismatch repair deficiency and response to immune checkpoint blockade. Oncologist. 21:1200–1211. 2016. View Article : Google Scholar : PubMed/NCBI | |
Lynch HT, Jascur T, Lanspa S and Boland CR: Making sense of missense in Lynch syndrome: The clinical perspective. Cancer Prev Res (Phila). 3:1371–1374. 2010. View Article : Google Scholar : PubMed/NCBI | |
Boland CR and Goel A: Microsatellite instability in colorectal cancer. Gastroenterology. 138:2073–2087.e3. 2010. View Article : Google Scholar : PubMed/NCBI | |
Ratner D and Lennerz JK: Implementing keytruda/pembrolizumab testing in clinical practice. Oncologist. 23:647–649. 2018. View Article : Google Scholar : PubMed/NCBI | |
Schwitalle Y, Kloor M, Eiermann S, Linnebacher M, Kienle P, Knaebel HP, Tariverdian M, Benner A and von Knebel Doeberitz M: Immune response against frameshift-induced neopeptides in HNPCC patients and healthy HNPCC mutation carriers. Gastroenterology. 134:988–997. 2008. View Article : Google Scholar : PubMed/NCBI | |
Drescher KM, Sharma P, Watson P, Gatalica Z, Thibodeau SN and Lynch HT: Lymphocyte recruitment into the tumor site is altered in patients with MSI-H colon cancer. Fam Cancer. 8:231–239. 2009. View Article : Google Scholar : PubMed/NCBI | |
Llosa NJ, Cruise M, Tam A, Wicks EC, Hechenbleikner EM, Taube JM, Blosser RL, Fan H, Wang H, Luber BS, et al: The vigorous immune microenvironment of microsatellite instable colon cancer is balanced by multiple counter-inhibitory checkpoints. Cancer Discov. 5:43–51. 2015. View Article : Google Scholar : | |
Goel G and Sun W: Advances in the management of gastrointestinal cancers-an upcoming role of immune checkpoint blockade. J Hematol Oncol. 8:862015. View Article : Google Scholar | |
Mouw KW, Goldberg MS, Konstantinopoulos PA and D'Andrea AD: DNA damage and repair biomarkers of immunotherapy response. Cancer Discov. 7:675–693. 2017. View Article : Google Scholar : PubMed/NCBI | |
Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, Bignell GR, Bolli N, Borg A, Børresen-Dale AL, et al: Signatures of mutational processes in human cancer. Nature. 500:415–421. 2013. View Article : Google Scholar : PubMed/NCBI | |
Schumacher TN and Schreiber RD: Neoantigens in cancer immunotherapy. Science. 348:69–74. 2015. View Article : Google Scholar : PubMed/NCBI | |
Gubin MM, Zhang X, Schuster H, Caron E, Ward JP, Noguchi T, Ivanova Y, Hundal J, Arthur CD, Krebber WJ, et al: Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature. 515:577–581. 2014. View Article : Google Scholar : PubMed/NCBI | |
Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, Walsh LA, Postow MA, Wong P, Ho TS, et al: Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 371:2189–2199. 2014. View Article : Google Scholar : PubMed/NCBI | |
Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, Sucker A, Hillen U, Foppen MHG, Goldinger SM, et al: Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 350:207–211. 2015. View Article : Google Scholar : PubMed/NCBI | |
Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, Lee W, Yuan J, Wong P, Ho TS, et al: Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 348:124–128. 2015. View Article : Google Scholar : PubMed/NCBI | |
Hellmann MD, Callahan MK, Awad MM, Calvo E, Ascierto PA, Atmaca A, Rizvi NA, Hirsch FR, Selvaggi G, Szustakowski JD, et al: Tumor mutational burden and efficacy of nivolumab monotherapy and in combination with ipilimumab in small-cell lung cancer. Cancer Cell. 33:853–861.e4. 2018. View Article : Google Scholar : PubMed/NCBI | |
Hellmann MD, Ciuleanu TE, Pluzanski A, Lee JS, Otterson GA, Audigier-Valette C, Minenza E, Linardou H, Burgers S, Salman P, et al: Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden. N Engl J Med. 378:2093–2104. 2018. View Article : Google Scholar : PubMed/NCBI | |
Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, Schrock A, Campbell B, Shlien A, Chmielecki J, et al: Analysis of 100,000 human c'ancer genomes reveals the landscape of tumor mutational burden. Genome Med. 9:342017. View Article : Google Scholar | |
Yarchoan M, Hopkins A and Jaffee EM: Tumor mutational burden and response rate to PD-1 inhibition. N Engl J Med. 377:2500–2501. 2017. View Article : Google Scholar : PubMed/NCBI | |
Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, Carter SL, Stewart C, Mermel CH, Roberts SA, et al: Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 499:214–218. 2013. View Article : Google Scholar : PubMed/NCBI | |
Pardoll D: Cancer and the immune system: Basic concepts and targets for intervention. Semin Oncol. 42:523–538. 2015. View Article : Google Scholar : PubMed/NCBI | |
Tumeh PC, Harview CL, Yearley JH, Shintaku IP, Taylor EJ, Robert L, Chmielowski B, Spasic M, Henry G, Ciobanu V, et al: PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature. 515:568–571. 2014. View Article : Google Scholar : PubMed/NCBI | |
Adams S, Gray RJ, Demaria S, Goldstein L, Perez EA, Shulman LN, Martino S, Wang M, Jones VE, Saphner TJ, et al: Prognostic value of tumor-infiltrating lymphocytes in triple-negative breast cancers from two phase III randomized adjuvant breast cancer trials: ECOG 2197 and ECOG 1199. J Clin Oncol. 32:2959–2966. 2014. View Article : Google Scholar : PubMed/NCBI | |
Salgado R, Denkert C, Campbell C, Savas P, Nuciforo P, Aura C, de Azambuja E, Eidtmann H, Ellis CE, Baselga J, et al: Tumor-infiltrating lymphocytes and associations with pathological complete response and event-free survival in HER2-positive early-stage breast cancer treated with lapatinib and trastuzumab: a secondary analysis of the NeoALTTO trial. JAMA Oncol. 1:448–454. 2015. View Article : Google Scholar : PubMed/NCBI | |
Basile D, Pelizzari G, Vitale MG, Lisanti C, Cinausero M, Iacono D and Puglisi F: Atezolizumab for the treatment of breast cancer. Expert Opin Biol Ther. 18:595–603. 2018. View Article : Google Scholar : PubMed/NCBI | |
Denkert C, von Minckwitz G, Darb-Esfahani S, Lederer B, Heppner BI, Weber KE, Budczies J, Huober J, Klauschen F, Furlanetto J, et al: Tumour-infiltrating lymphocytes and prognosis in different subtypes of breast cancer: A pooled analysis of 3771 patients treated with neoadjuvant therapy. Lancet Oncol. 19:40–50. 2018. View Article : Google Scholar | |
Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pagès C, Tosolini M, Camus M, Berger A, Wind P, et al: Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science. 313:1960–1964. 2006. View Article : Google Scholar : PubMed/NCBI | |
Pagès F, Mlecnik B, Marliot F, Bindea G, Ou FS, Bifulco C, Lugli A, Zlobec I, Rau TT, Berger MD, et al: International validation of the consensus immunoscore for the classification of colon cancer: A prognostic and accuracy study. Lancet. 391:2128–2139. 2018. View Article : Google Scholar : PubMed/NCBI | |
Khalili JS, Liu S, Rodríguez-Cruz TG, Whittington M, Wardell S, Liu C, Zhang M, Cooper ZA, Frederick DT, Li Y, et al: Oncogenic BRAF(V600E) promotes stromal cell-mediated immunosuppression via induction of interleukin-1 in melanoma. Clin Cancer Res. 18:5329–5340. 2012. View Article : Google Scholar : PubMed/NCBI | |
Frederick DT, Piris A, Cogdill AP, Cooper ZA, Lezcano C, Ferrone CR, Mitra D, Boni A, Newton LP, Liu C, et al: BRAF inhibition is associated with enhanced melanoma antigen expression and a more favorable tumor microenvironment in patients with metastatic melanoma. Clin Cancer Res. 19:1225–1231. 2013. View Article : Google Scholar : PubMed/NCBI | |
Wolchok JD, Chiarion-Sileni V, Gonzalez R, Rutkowski P, Grob JJ, Cowey CL, Lao CD, Wagstaff J, Schadendorf D, Ferrucci PF, et al: Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N Engl J Med. 377:1345–1356. 2017. View Article : Google Scholar : PubMed/NCBI | |
Gao J, Shi LZ, Zhao H, Chen J, Xiong L, He Q, Chen T, Roszik J, Bernatchez C, Woodman SE, et al: Loss of IFN-γ pathway genes in tumor cells as a mechanism of resistance to anti-CTLA-4 therapy. Cell. 167:397–404.e9. 2016. View Article : Google Scholar | |
Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W, Hu-Lieskovan S, Torrejon DY, Abril-Rodriguez G, Sandoval S, Barthly L, et al: Mutations associated with acquired resistance to PD-1 blockade in melanoma. N Engl J Med. 375:819–829. 2016. View Article : Google Scholar : PubMed/NCBI | |
Shin DS, Zaretsky JM, Escuin-Ordinas H, Garcia-Diaz A, Hu-Lieskovan S, Kalbasi A, Grasso CS, Hugo W, Sandoval S, Torrejon DY, et al: Primary resistance to PD-1 blockade mediated by JAK1/2 mutations. Cancer Discov. 7:188–201. 2017. View Article : Google Scholar : | |
Riaz N, Havel JJ, Kendall SM, Makarov V, Walsh LA, Desrichard A, Weinhold N and Chan TA: Recurrent SERPINB3 and SERPINB4 mutations in patients who respond to anti-CTLA4 immunotherapy. Nat Genet. 48:1327–1329. 2016. View Article : Google Scholar : PubMed/NCBI | |
Peng W, Chen JQ, Liu C, Malu S, Creasy C, Tetzlaff MT, Xu C, McKenzie JA, Zhang C, Liang X, et al: Loss of PTEN promotes resistance to T cell-mediated immunotherapy. Cancer Discov. 6:202–216. 2016. View Article : Google Scholar : | |
George S, Miao D, Demetri GD, Adeegbe D, Rodig SJ, Shukla S, Lipschitz M, Amin-Mansour A, Raut CP, Carter SL, et al: Loss of PTEN is associated with resistance to Anti-PD-1 checkpoint blockade therapy in metastatic uterine leiomyosarcoma. Immunity. 46:197–204. 2017. View Article : Google Scholar : PubMed/NCBI | |
Dong ZY, Zhong WZ, Zhang XC, Su J, Xie Z, Liu SY, Tu HY, Chen HJ, Sun YL, Zhou Q, et al: Potential predictive value of TP53 and KRAS mutation status for response to PD-1 blockade immunotherapy in lung adenocarcinoma. Clin Cancer Res. 23:3012–3024. 2017. View Article : Google Scholar : PubMed/NCBI | |
Skoulidis F, Goldberg ME, Greenawalt DM, Hellmann MD, Awad MM, Gainor JF, Schrock AB, Hartmaier RJ, Trabucco SE, Gay L, et al: STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discov. 8:822–835. 2018. View Article : Google Scholar : PubMed/NCBI | |
Lisberg A, Cummings A, Goldman JW, Bornazyan K, Reese N, Wang T, Coluzzi P, Ledezma B, Mendenhall M, Hunt J, et al: A phase II study of pembrolizumab in EGFR-mutant, PD-L1+, tyrosine kinase inhibitor Naïve patients with advanced NSCLC. J Thorac Oncol. 13:1138–1145. 2018. View Article : Google Scholar : PubMed/NCBI | |
Cancer Genome Atlas Research Network: Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature. 499:43–49. 2013. View Article : Google Scholar : PubMed/NCBI | |
Kapur P, Peña-Llopis S, Christie A, Zhrebker L, Pavía-Jiménez A, Rathmell WK, Xie XJ and Brugarolas J: Effects on survival of BAP1 and PBRM1 mutations in sporadic clear-cell renal-cell carcinoma: A retrospective analysis with independent validation. Lancet Oncol. 14:159–167. 2013. View Article : Google Scholar : PubMed/NCBI | |
Pawłowski R, Mühl SM, Sulser T, Krek W, Moch H and Schraml P: Loss of PBRM1 expression is associated with renal cell carcinoma progression. Int J Cancer. 132:E11–E17. 2013. View Article : Google Scholar | |
Nam SJ, Lee C, Park JH and Moon KC: Decreased PBRM1 expression predicts unfavorable prognosis in patients with clear cell renal cell carcinoma. Urol Oncol. 33:340.e9–e16. 2015. View Article : Google Scholar : PubMed/NCBI | |
Miao D, Margolis CA, Gao W, Voss MH, Li W, Martini DJ, Norton C, Bossé D, Wankowicz SM, Cullen D, et al: Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma. Science. 359:801–806. 2018. View Article : Google Scholar : PubMed/NCBI | |
Manguso RT, Pope HW, Zimmer MD, Brown FD, Yates KB, Miller BC, Collins NB, Bi K, LaFleur MW, Juneja VR, et al: In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target. Nature. 547:413–418. 2017. View Article : Google Scholar : PubMed/NCBI | |
Patel SJ, Sanjana NE, Kishton RJ, Eidizadeh A, Vodnala SK, Cam M, Gartner JJ, Jia L, Steinberg SM, Yamamoto TN, et al: Identification of essential genes for cancer immunotherapy. Nature. 548:537–542. 2017. View Article : Google Scholar : PubMed/NCBI | |
Pan D, Kobayashi A, Jiang P, Ferrari de Andrade L, Tay RE, Luoma AM, Tsoucas D, Qiu X, Lim K, Rao P, et al: A major chromatin regulator determines resistance of tumor cells to T cell-mediated killing. Science. 359:770–775. 2018. View Article : Google Scholar : PubMed/NCBI | |
Shukla SA, Rooney MS, Rajasagi M, Tiao G, Dixon PM, Lawrence MS, Stevens J, Lane WJ, Dellagatta JL, Steelman S, et al: Comprehensive analysis of cancer-associated somatic mutations in class I HLA genes. Nat Biotechnol. 33:1152–1158. 2015. View Article : Google Scholar : PubMed/NCBI | |
McGranahan N, Rosenthal R, Hiley CT, Rowan AJ, Watkins TBK, Wilson GA, Birkbak NJ, Veeriah S, Van Loo P, Herrero J, et al: Allele-specific HLA loss and immune escape in lung cancer evolution. Cell. 171:1259–1271.e11. 2017. View Article : Google Scholar : PubMed/NCBI | |
Rodig SJ, Gusenleitner D, Jackson DG, Gjini E, Giobbie-Hurder A, Jin C, Chang H, Lovitch SB, Horak C, Weber JS, et al: MHC proteins confer differential sensitivity to CTLA-4 and PD-1 blockade in untreated metastatic melanoma. Sci Transl Med. 10:eaar33422018. View Article : Google Scholar : PubMed/NCBI | |
Chowell D, Morris LGT, Grigg CM, Weber JK, Samstein RM, Makarov V, Kuo F, Kendall SM, Requena D, Riaz N, et al: Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science. 359:582–587. 2018. View Article : Google Scholar : | |
Simeone E, Gentilcore G, Giannarelli D, Grimaldi AM, Caracò C, Curvietto M, Esposito A, Paone M, Palla M, Cavalcanti E, et al: Immunological and biological changes during ipilimumab treatment and their potential correlation with clinical response and survival in patients with advanced melanoma. Cancer Immunol Immunother. 63:675–683. 2014. View Article : Google Scholar : PubMed/NCBI | |
Martens A, Wistuba-Hamprecht K, Geukes Foppen M, Yuan J, Postow MA, Wong P, Romano E, Khammari A, Dreno B, Capone M, et al: Baseline peripheral blood biomarkers associated with clinical outcome of advanced melanoma patients treated with ipilimumab. Clin Cancer Res. 22:2908–2918. 2016. View Article : Google Scholar : PubMed/NCBI | |
Martens A, Wistuba-Hamprecht K, Yuan J, Postow MA, Wong P, Capone M, Madonna G, Khammari A, Schilling B, Sucker A, et al: Increases in absolute lymphocytes and circulating CD4+ and CD8+ T cells are associated with positive clinical outcome of melanoma patients treated with ipilimumab. Clin Cancer Res. 22:4848–4858. 2016. View Article : Google Scholar : PubMed/NCBI | |
Wistuba-Hamprecht K, Martens A, Heubach F, Romano E, Geukes Foppen M, Yuan J, Postow M, Wong P, Mallardo D, Schilling B, et al: Peripheral CD8 effector-memory type 1 T-cells correlate with outcome in ipilimumab-treated stage IV melanoma patients. Eur J Cancer. 73:61–70. 2017. View Article : Google Scholar : PubMed/NCBI | |
Kuzman JA, Stenehjem DD, Merriman J, Agarwal AM, Patel SB, Hahn AW, Alex A, Albertson D, Gill DM and Agarwal N: Neutrophil-lymphocyte ratio as a predictive biomarker for response to high dose interleukin-2 in patients with renal cell carcinoma. BMC Urol. 17:12017. View Article : Google Scholar : PubMed/NCBI | |
Weide B, Martens A, Hassel JC, Berking C, Postow MA, Bisschop K, Simeone E, Mangana J, Schilling B, Di Giacomo AM, et al: Baseline biomarkers for outcome of melanoma patients treated with pembrolizumab. Clin Cancer Res. 22:5487–5496. 2016. View Article : Google Scholar : PubMed/NCBI | |
Dall'Olio FG, Gelsomino F, Conci N, Marcolin L, De Giglio A, Grilli G, Sperandi F, Fontana F, Terracciano M, Fragomeno B, et al: PD-L1 expression in circulating tumor cells as a promising prognostic biomarker in advanced non-small-cell lung cancer treated with immune checkpoint inhibitors. Clin Lung Cancer. 22:423–431. 2021. View Article : Google Scholar : PubMed/NCBI | |
Krieg C, Nowicka M, Guglietta S, Schindler S, Hartmann FJ, Weber LM, Dummer R, Robinson MD, Levesque MP and Becher B: High-dimensional single-cell analysis predicts response to anti-PD-1 immunotherapy. Nat Med. 24:144–153. 2018. View Article : Google Scholar : PubMed/NCBI | |
Yuan J, Zhou J, Dong Z, Tandon S, Kuk D, Panageas KS, Wong P, Wu X, Naidoo J, Page DB, et al: Pretreatment serum VEGF is associated with clinical response and overall survival in advanced melanoma patients treated with ipilimumab. Cancer Immunol Res. 2:127–132. 2014. View Article : Google Scholar : PubMed/NCBI | |
Zang J, Hu Y, Xu X, Ni J, Yan D, Liu S, He J, Xue J, Wu J and Feng J: Elevated serum levels of vascular endothelial growth factor predict a poor prognosis of platinum-based chemotherapy in non-small cell lung cancer. Onco Targets Ther. 10:409–415. 2017. View Article : Google Scholar : PubMed/NCBI | |
Powles T, Eder JP, Fine GD, Braiteh FS, Loriot Y, Cruz C, Bellmunt J, Burris HA, Petrylak DP, Teng SL, et al: MPDL3280A (anti-PD-L1) treatment leads to clinical activity in metastatic bladder cancer. Nature. 515:558–562. 2014. View Article : Google Scholar : PubMed/NCBI | |
Schalper KA, Carleton M, Zhou M, Chen T, Feng Y, Huang SP, Walsh AM, Baxi V, Pandya D, Baradet T, et al: Elevated serum interleukin-8 is associated with enhanced intratumor neutrophils and reduced clinical benefit of immune-checkpoint inhibitors. Nat Med. 26:688–692. 2020. View Article : Google Scholar : PubMed/NCBI | |
Chen G, Huang AC, Zhang W, Zhang G, Wu M, Xu W, Yu Z, Yang J, Wang B, Sun H, et al: Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response. Nature. 560:382–386. 2018. View Article : Google Scholar : PubMed/NCBI | |
Yang Y, Li CW, Chan LC, Wei Y, Hsu JM, Xia W, Cha JH, Hou J, Hsu JL, Sun L and Hung MC: Exosomal PD-L1 harbors active defense function to suppress T cell killing of breast cancer cells and promote tumor growth. Cell Res. 28:862–864. 2018. View Article : Google Scholar : PubMed/NCBI | |
Tucci M, Passarelli A, Mannavola F, Stucci LS, Ascierto PA, Capone M, Madonna G, Lopalco P and Silvestris F: Serum exosomes as predictors of clinical response to ipilimumab in metastatic melanoma. Oncoimmunology. 7:e13877062017. View Article : Google Scholar | |
Garrett WS: Cancer and the microbiota. Science. 348:80–86. 2015. View Article : Google Scholar : PubMed/NCBI | |
Zitvogel L, Ayyoub M, Routy B and Kroemer G: Microbiome and anticancer immunosurveillance. Cell. 165:276–287. 2016. View Article : Google Scholar : PubMed/NCBI | |
Vétizou M, Pitt JM, Daillère R, Lepage P, Waldschmitt N, Flament C, Rusakiewicz S, Routy B, Roberti MP, Duong CP, et al: Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science. 350:1079–1084. 2015. View Article : Google Scholar : PubMed/NCBI | |
Sivan A, Corrales L, Hubert N, Williams JB, Aquino-Michaels K, Earley ZM, Benyamin FW, Lei YM, Jabri B, Alegre ML, et al: Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science. 350:1084–1089. 2015. View Article : Google Scholar : PubMed/NCBI | |
Routy B, Le Chatelier E, Derosa L, Duong CPM, Alou MT, Daillère R, Fluckiger A, Messaoudene M, Rauber C, Roberti MP, et al: Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science. 359:91–97. 2018. View Article : Google Scholar | |
Gopalakrishnan V, Spencer CN, Nezi L, Reuben A, Andrews MC, Karpinets TV, Prieto PA, Vicente D, Hoffman K, Wei SC, et al: Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science. 359:97–103. 2018. View Article : Google Scholar | |
Matson V, Fessler J, Bao R, Chongsuwat T, Zha Y, Alegre ML, Luke JJ and Gajewski TF: The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science. 359:104–108. 2018. View Article : Google Scholar : PubMed/NCBI | |
Arora S, Velichinskii R, Lesh RW, Ali U, Kubiak M, Bansal P, Borghaei H, Edelman MJ and Boumber Y: Existing and emerging biomarkers for immune checkpoint immunotherapy in solid tumors. Adv Ther. 36:2638–2678. 2019. View Article : Google Scholar : PubMed/NCBI | |
Sucker A, Zhao F, Real B, Heeke C, Bielefeld N, Maβen S, Horn S, Moll I, Maltaner R, Horn PA, et al: Genetic evolution of T-cell resistance in the course of melanoma progression. Clin Cancer Res. 20:6593–6604. 2014. View Article : Google Scholar : PubMed/NCBI | |
Rooney MS, Shukla SA, Wu CJ, Getz G and Hacohen N: Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell. 160:48–61. 2015. View Article : Google Scholar : PubMed/NCBI | |
Sade-Feldman M, Jiao YJ, Chen JH, Rooney MS, Barzily-Rokni M, Eliane JP, Bjorgaard SL, Hammond MR, Vitzthum H, Blackmon SM, et al: Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat Commun. 8:11362017. View Article : Google Scholar : PubMed/NCBI | |
Gettinger S, Choi J, Hastings K, Truini A, Datar I, Sowell R, Wurtz A, Dong W, Cai G, Melnick MA, et al: Impaired HLA class I antigen processing and presentation as a mechanism of acquired resistance to immune checkpoint inhibitors in lung cancer. Cancer Discov. 7:1420–1435. 2017. View Article : Google Scholar : PubMed/NCBI | |
Benci JL, Xu B, Qiu Y, Wu TJ, Dada H, Twyman-Saint Victor C, Cucolo L, Lee DSM, Pauken KE, Huang AC, et al: Tumor interferon signaling regulates a multigenic resistance program to immune checkpoint blockade. Cell. 167:1540–1554.e12. 2016. View Article : Google Scholar : PubMed/NCBI | |
Spranger S, Bao R and Gajewski TF: Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature. 523:231–235. 2015. View Article : Google Scholar : PubMed/NCBI | |
Wang B, Tian T, Kalland KH, Ke X and Qu Y: Targeting Wnt/β-catenin signaling for cancer immunotherapy. Trends Pharmacol Sci. 39:648–658. 2018. View Article : Google Scholar : PubMed/NCBI | |
Cancer Genome Atlas Network: Genomic classification of cutaneous melanoma. Cell. 161:1681–1696. 2015. View Article : Google Scholar : PubMed/NCBI | |
Sumimoto H, Imabayashi F, Iwata T and Kawakami Y: The BRAF-MAPK signaling pathway is essential for cancer-immune evasion in human melanoma cells. J Exp Med. 203:1651–1656. 2006. View Article : Google Scholar : PubMed/NCBI | |
Koyama S, Akbay EA, Li YY, Herter-Sprie GS, Buczkowski KA, Richards WG, Gandhi L, Redig AJ, Rodig SJ, Asahina H, et al: Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints. Nat Commun. 7:105012016. View Article : Google Scholar : PubMed/NCBI | |
Gao J, Ward JF, Pettaway CA, Shi LZ, Subudhi SK, Vence LM, Zhao H, Chen J, Chen H, Efstathiou E, et al: VISTA is an inhibitory immune checkpoint that is increased after ipilimumab therapy in patients with prostate cancer. Nat Med. 23:551–555. 2017. View Article : Google Scholar : PubMed/NCBI | |
Saleh R and Elkord E: Acquired resistance to cancer immunotherapy: Role of tumor-mediated immunosuppression. Semin Cancer Biol. 65:13–27. 2020. View Article : Google Scholar | |
Brabletz T, Kalluri R, Nieto MA and Weinberg RA: EMT in cancer. Nat Rev Cancer. 18:128–134. 2018. View Article : Google Scholar : PubMed/NCBI | |
Wang L, Saci A, Szabo PM, Chasalow SD, Castillo-Martin M, Domingo-Domenech J, Siefker-Radtke A, Sharma P, Sfakianos JP, Gong Y, et al: EMT- and stroma-related gene expression and resistance to PD-1 blockade in urothelial cancer. Nat Commun. 9:35032018. View Article : Google Scholar : PubMed/NCBI | |
Terry S, Savagner P, Ortiz-Cuaran S, Mahjoubi L, Saintigny P, Thiery JP and Chouaib S: New insights into the role of EMT in tumor immune escape. Mol Oncol. 11:824–846. 2017. View Article : Google Scholar : PubMed/NCBI | |
Arce Vargas F, Furness AJS, Solomon I, Joshi K, Mekkaoui L, Lesko MH, Miranda Rota E, Dahan R, Georgiou A, Sledzinska A, et al: Fc-optimized anti-CD25 depletes tumor-infiltrating regulatory T cells and synergizes with PD-1 blockade to eradicate established tumors. Immunity. 46:577–586. 2017. View Article : Google Scholar : PubMed/NCBI | |
Shitara K and Nishikawa H: Regulatory T cells: A potential target in cancer immunotherapy. Ann N Y Acad Sci. 1417:104–115. 2018. View Article : Google Scholar : PubMed/NCBI | |
Gebhardt C, Sevko A, Jiang H, Lichtenberger R, Reith M, Tarnanidis K, Holland-Letz T, Umansky L, Beckhove P, Sucker A, et al: Myeloid cells and related chronic inflammatory factors as novel predictive markers in melanoma treatment with ipilimumab. Clin Cancer Res. 21:5453–5459. 2015. View Article : Google Scholar : PubMed/NCBI | |
Ruffell B and Coussens LM: Macrophages and therapeutic resistance in cancer. Cancer Cell. 27:462–472. 2015. View Article : Google Scholar : PubMed/NCBI | |
Arlauckas SP, Garris CS, Kohler RH, Kitaoka M, Cuccarese MF, Yang KS, Miller MA, Carlson JC, Freeman GJ, Anthony RM, et al: In vivo imaging reveals a tumor-associated macrophage-mediated resistance pathway in anti-PD-1 therapy. Sci Transl Med. 9:eaal36042017. View Article : Google Scholar : PubMed/NCBI | |
Mariathasan S, Turley SJ, Nickles D, Castiglioni A, Yuen K, Wang Y, Kadel EE III, Koeppen H, Astarita JL, Cubas R, et al: TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature. 554:544–548. 2018. View Article : Google Scholar : PubMed/NCBI | |
Highfill SL, Cui Y, Giles AJ, Smith JP, Zhang H, Morse E, Kaplan RN and Mackall CL: Disruption of CXCR2-mediated MDSC tumor trafficking enhances anti-PD1 efficacy. Sci Transl Med. 6:237ra672014. View Article : Google Scholar : PubMed/NCBI | |
Holmgaard RB, Zamarin D, Munn DH, Wolchok JD and Allison JP: Indoleamine 2,3-dioxygenase is a critical resistance mechanism in antitumor T cell immunotherapy targeting CTLA-4. J Exp Med. 210:1389–1402. 2013. View Article : Google Scholar : PubMed/NCBI | |
Holmgaard RB, Zamarin D, Li Y, Gasmi B, Munn DH, Allison JP, Merghoub T and Wolchok JD: Tumor-expressed IDO recruits and activates MDSCs in a treg-dependent manner. Cell Rep. 13:412–424. 2015. View Article : Google Scholar : PubMed/NCBI | |
Sharma P, Hu-Lieskovan S, Wargo JA and Ribas A: Primary, adaptive, and acquired resistance to cancer immunotherapy. Cell. 168:707–723. 2017. View Article : Google Scholar : PubMed/NCBI | |
O'Donnell JS, Hoefsmit EP, Smyth MJ, Blank CU and Teng MWL: The promise of neoadjuvant immunotherapy and surgery for cancer treatment. Clin Cancer Res. 25:5743–5751. 2019. View Article : Google Scholar : PubMed/NCBI | |
Liu J, Blake SJ, Yong MC, Harjunpää H, Ngiow SF, Takeda K, Young A, O'Donnell JS, Allen S, Smyth MJ and Teng MW: Improved efficacy of neoadjuvant compared to adjuvant immunotherapy to eradicate metastatic disease. Cancer Discov. 6:1382–1399. 2016. View Article : Google Scholar : PubMed/NCBI | |
Amaria RN, Reddy SM, Tawbi HA, Davies MA, Ross MI, Glitza IC, Cormier JN, Lewis C, Hwu WJ, Hanna E, et al: Neoadjuvant immune checkpoint blockade in high-risk resectable melanoma. Nat Med. 24:1649–1654. 2018. View Article : Google Scholar : PubMed/NCBI | |
Liu SY, Dong S, Liao RQ, Jiang B, Zhang JT, Lin JT, Zhang S, Yang J, Nie Q, Yang X, et al: LBA2 phase II study of PD-L1 expression guidance on neoadjuvant (NA) Nivolumab (Nivo) monotherapy with or without platinum-doublet chemotherapy in resectable NSCLC. ESMO. 16(Suppl 1): S103632022. | |
Hannani D, Sistigu A, Kepp O, Galluzzi L, Kroemer G and Zitvogel L: Prerequisites for the antitumor vaccine-like effect of chemotherapy and radiotherapy. Cancer J. 17:351–358. 2011. View Article : Google Scholar : PubMed/NCBI | |
Teng F, Kong L, Meng X, Yang J and Yu J: Radiotherapy combined with immune checkpoint blockade immunotherapy: Achievements and challenges. Cancer Lett. 365:23–29. 2015. View Article : Google Scholar : PubMed/NCBI | |
Ngiow SF, McArthur GA and Smyth MJ: Radiotherapy complements immune checkpoint blockade. Cancer Cell. 27:437–438. 2015. View Article : Google Scholar : PubMed/NCBI | |
Twyman-Saint Victor C, Rech AJ, Maity A, Rengan R, Pauken KE, Stelekati E, Benci JL, Xu B, Dada H, Odorizzi PM, et al: Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer. Nature. 520:373–377. 2015. View Article : Google Scholar : PubMed/NCBI | |
Langer CJ, Gadgeel SM, Borghaei H, Papadimitrakopoulou VA, Patnaik A, Powell SF, Gentzler RD, Martins RG, Stevenson JP, Jalal SI, et al: Carboplatin and pemetrexed with or without pembrolizumab for advanced, non-squamous non-small-cell lung cancer: A randomised, phase 2 cohort of the open-label KEYNOTE-021 study. Lancet Oncol. 17:1497–1508. 2016. View Article : Google Scholar : PubMed/NCBI | |
Wang C, Wang J, Zhang X, Yu S, Wen D, Hu Q, Ye Y, Bomba H, Hu X, Liu Z, et al: In situ formed reactive oxygen species-responsive scaffold with gemcitabine and checkpoint inhibitor for combination therapy. Sci Transl Med. 10:eaan36822018. View Article : Google Scholar : PubMed/NCBI | |
Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Cowey CL, Lao CD, Schadendorf D, Dummer R, Smylie M, Rutkowski P, et al: Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med. 373:23–34. 2015. View Article : Google Scholar : PubMed/NCBI | |
Redmond WL, Linch SN and Kasiewicz MJ: Combined targeting of costimulatory (OX40) and coinhibitory (CTLA-4) pathways elicits potent effector T cells capable of driving robust antitumor immunity. Cancer Immunol Res. 2:142–153. 2014. View Article : Google Scholar : PubMed/NCBI | |
Mayes PA, Hance KW and Hoos A: The promise and challenges of immune agonist antibody development in cancer. Nat Rev Drug Discov. 17:509–527. 2018. View Article : Google Scholar : PubMed/NCBI | |
Popovic A, Jaffee EM and Zaidi N: Emerging strategies for combination checkpoint modulators in cancer immunotherapy. J Clin Invest. 128:3209–3218. 2018. View Article : Google Scholar : PubMed/NCBI | |
Kuai R, Ochyl LJ, Bahjat KS, Schwendeman A and Moon JJ: Designer vaccine nanodiscs for personalized cancer immunotherapy. Nat Mater. 16:489–496. 2017. View Article : Google Scholar : | |
Madan RA, Mohebtash M, Arlen PM, Vergati M, Rauckhorst M, Steinberg SM, Tsang KY, Poole DJ, Parnes HL, Wright JJ, et al: Ipilimumab and a poxviral vaccine targeting prostate-specific antigen in metastatic castration-resistant prostate cancer: A phase 1 dose-escalation trial. Lancet Oncol. 13:501–508. 2012. View Article : Google Scholar : PubMed/NCBI | |
Chesney J, Puzanov I, Collichio F, Singh P, Milhem MM, Glaspy J, Hamid O, Ross M, Friedlander P, Garbe C, et al: Randomized, open-label phase II study evaluating the efficacy and safety of talimogene laherparepvec in combination with ipilimumab versus ipilimumab alone in patients with advanced, unresectable melanoma. J Clin Oncol. 36:1658–1667. 2018. View Article : Google Scholar : | |
Liu X, Ranganathan R, Jiang S, Fang C, Sun J, Kim S, Newick K, Lo A, June CH, Zhao Y and Moon EK: A chimeric switch-receptor targeting PD1 augments the efficacy of second-generation CAR T cells in advanced solid tumors. Cancer Res. 76:1578–1590. 2016. View Article : Google Scholar : PubMed/NCBI | |
Gay F, D'Agostino M, Giaccone L, Genuardi M, Festuccia M, Boccadoro M and Bruno B: Immuno-oncologic approaches: CAR-T cells and checkpoint inhibitors. Clin Lymphoma Myeloma Leuk. 17:471–478. 2017. View Article : Google Scholar : PubMed/NCBI | |
De Henau O, Rausch M, Winkler D, Campesato LF, Liu C, Cymerman DH, Budhu S, Ghosh A, Pink M, Tchaicha J, et al: Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells. Nature. 539:443–447. 2016. View Article : Google Scholar : PubMed/NCBI | |
Abdel-Wahab N, Shah M and Suarez-Almazor ME: Adverse events associated with immune checkpoint blockade in patients with cancer: A systematic review of case reports. PLoS One. 11:e01602212016. View Article : Google Scholar : PubMed/NCBI | |
Palmieri DJ and Carlino MS: Immune checkpoint inhibitor toxicity. Curr Oncol Rep. 20:722018. View Article : Google Scholar : PubMed/NCBI | |
Boutros C, Tarhini A, Routier E, Lambotte O, Ladurie FL, Carbonnel F, Izzeddine H, Marabelle A, Champiat S, Berdelou A, et al: Safety profiles of anti-CTLA-4 and anti-PD-1 antibodies alone and in combination. Nat Rev Clin Oncol. 13:473–486. 2016. View Article : Google Scholar : PubMed/NCBI | |
Cousin S, Seneschal J and Italiano A: Toxicity profiles of immunotherapy. Pharmacol Ther. 181:91–100. 2018. View Article : Google Scholar | |
Sznol M, Ferrucci PF, Hogg D, Atkins MB, Wolter P, Guidoboni M, Lebbé C, Kirkwood JM, Schachter J, Daniels GA, et al: Pooled analysis safety profile of nivolumab and ipilimumab combination therapy in patients with advanced melanoma. J Clin Oncol. 35:3815–3822. 2017. View Article : Google Scholar : PubMed/NCBI | |
Kottschade LA: Incidence and management of immune-related adverse events in patients undergoing treatment with immune checkpoint inhibitors. Curr Oncol Rep. 20:242018. View Article : Google Scholar : PubMed/NCBI | |
Martins F, Sofiya L, Sykiotis GP, Lamine F, Maillard M, Fraga M, Shabafrouz K, Ribi C, Cairoli A, Guex-Crosier Y, et al: Adverse effects of immune-checkpoint inhibitors: Epidemiology, management and surveillance. Nat Rev Clin Oncol. 16:563–580. 2019. View Article : Google Scholar : PubMed/NCBI | |
Haanen JBAG, Carbonnel F, Robert C, Kerr KM, Peters S, Larkin J and Jordan K; ESMO Guidelines Committee: Management of toxicities from immunotherapy: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 28(Suppl 4): iv119–iv142. 2017. View Article : Google Scholar : PubMed/NCBI | |
Sullivan RJ and Weber JS: Immune-related toxicities of checkpoint inhibitors: Mechanisms and mitigation strategies. Nat Rev Drug Discov. 21:495–508. 2022. View Article : Google Scholar |