New and emerging strategies for targeting cancers: Challenges and opportunities (Review)

Introduction

Cancer management involves a range of treatment options, such as surgery, chemotherapy, targeted therapy, radiation therapy, endocrine therapy and immunotherapy. Most cancers are initially sensitive to chemotherapy and/or immunotherapy. Over time, cancer cells develop resistance, resulting in the formation of aggressive tumors (1–3). Multiple intrinsic (innate) and extrinsic (acquired) factors, intratumor heterogeneity and stromal factors all contribute to the development of resistance to cancer therapies. Tumor heterogeneity, pre-existing genetic mutations, increased DNA repair mechanisms and drug inactivation are considered key intrinsic factors (4–7). Tumor microenvironment (TME), drug-efflux proteins such as P-glycoprotein (P-gp) and ATP-binding cassette transporters (ABCG2), microRNAs, anti-apoptotic proteins (8), and oncogenic pathways are the key extrinsic factors that contribute to the development of therapeutic resistance in cancer cells. Recently, studies using targeted drugs have increasingly focused on specific molecular alterations to reduce toxicity to normal tissue. These targeted therapies demonstrate limited efficacy in treating patients due to adaptive responses and multiple mechanisms of resistance. Further elucidation of these resistance mechanisms could enable the identification of predictive biomarkers for clinical use to inform the development of optimal therapeutic strategies. Such an actionable strategy, based on insights into the mechanisms of chemotherapy and immunotherapy resistance, can improve clinical outcomes for patients.

Resistance to treatment

Intrinsic resistance

A lack of a significant clinical response to therapy is attributed to intrinsic, or primary, resistance. Intrinsic resistance is natural resistance to a drug or immunotherapy that exists before the start of treatment. However, acquired resistance to chemotherapy or immunotherapy develops over time (9,10). Tumor heterogeneity, genetic mutations and the activation of defense mechanisms can cause intrinsic resistance. Some of the identified mechanisms include activation of mitogen-activated protein kinase (MAPK) or loss of phosphatase and tensin homolog (PTEN) expression, leading to enhanced PI3K signaling, increased WNT/β-catenin signaling and a loss of T-cell response. Examples of intrinsic resistance in cancer include Herceptin (trastuzumab), an anti-HER2 therapy [monoclonal antibody (mAb)] in breast cancer. In breast tumors with Herceptin resistance, there is higher PI3K/Akt activity compared to Herceptin-sensitive tumors (11,12). The difference between intrinsic and acquired Herceptin-resistant breast cancer is that intrinsic resistance tumors do not activate HER2 signaling; in contrast, HER2 signaling is activated in tumors with acquired resistance (13,14), suggesting that intrinsic resistance to Herceptin is independent of HER2 signaling, while acquired resistance depends on HER2 signaling. Patients with gastric cancer showed higher levels of HER2 expression and resistance to cisplatin treatment (15). Certain breast cancer subtypes display inherent therapy resistance. Even prior to treatment, they harbor pre-existing molecular and genetic traits-such as high CD44 and low CD24 expression-that limit treatment efficacy. Additionally, variations in the BRAF V600E mutation alter their sensitivity to targeted BRAF (16–18). Immune checkpoint blockade therapy (ICBT), which blocks immune-inhibitory signals to maintain antitumor responses in cancer patients, has been shown to improve clinical outcomes. The TME controls T-cell infiltration, distribution and functions in tumor tissues. However, low tumor immunogenicity or an immunosuppressive TME can lead to significant intrinsic resistance to ICBT (6). Loss of PTEN leads to increased PI3K signaling in numerous types of cancer, including 30% of melanomas, and is associated with resistance to immune checkpoint therapy (19). Drug transport and metabolism help regulate intrinsic drug resistance. The ATP-binding cassette (ABC) transporter protein family transports different drugs across the plasma membrane. This protein family comprises ~49 members, including the multidrug resistance protein 1 (MDR1). MDR1 overexpression in breast, prostate, and lung cancer is associated with intrinsic drug resistance (20–22). Breast cancer resistance protein, an MDR protein, plays a significant role in drug efflux and is associated with chemotherapeutic resistance in breast cancer and leukemias (23–25). Cancer stem cells (CSCs), naturally resistant to drugs, also exhibit higher levels of drug-efflux proteins (26).

Acquired resistance

This type of drug resistance develops gradually over time during therapy for the following reasons: i) Stress-induced driver genes that activate a second proto-oncogene, ii) modifications of drug targets due to mutations or altered expression levels, and iii) changes in the TME. Acquired drug resistance will allow the tumors to regrow (27). Some of the mechanisms are discussed below.

Drug inactivation and alteration in drug targets

Drug inactivation is a mechanism of resistance applicable to chemotherapeutic and molecularly targeted agents (Fig. 1). For instance, platinum drugs can be inactivated by the thiol glutathione (28). Capecitabine, a fluoropyrimidine prodrug, is converted into active 5-fluorouracil (5-FU) by the enzyme thymidine phosphorylase. However, inactivation of the gene encoding this enzyme can occur through methylation, leading to capecitabine resistance (29,30). Antiestrogens such as tamoxifen or aromatase inhibitors are effective initially in most estrogen receptor-positive breast tumors; however, prolonged use can lead to drug resistance (31,32). Tamoxifen resistance may arise from mutations in the estrogen receptor, decreased receptor levels or reduced conversion of tamoxifen to its active form (33,34). In prostate cancers, roughly ~30% of the patients have increased androgen receptor (AR), which is associated with acquired resistance to androgen deprivation therapy using leuprolide, testosterone-lowering drugs and AR antagonists such as bicalutamide (35). In addition to overexpression, a point mutation in AR leads to promiscuity towards other steroid ligands and the expression of variants lacking ligand-binding domains is associated with acquired resistance to newer-generation androgen/AR therapies (36). Approximately 20% of advanced cancer patients undergoing newer-generation androgen/AR therapies develop a complete loss of AR and acquisition of lineage plasticity, leading to a neuroendocrine phenotype in tumors (37). Cancer cells can alter drug targets through changes in expression levels, secondary mutations in the target protein or epigenetic alterations, leading to resistance. Tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptors (EGFR), such as gefitinib and erlotinib, show reasonable initial response rates in non-small cell lung cancer (NSCLC) (38,39). However, half of patients who respond to treatment develop resistance within a year, often with the EGFR-T790M mutation (40,41). However, tumors with an EGFR mutation at threonine 790 to methionine showed enhanced ATP affinity and impaired binding of gefitinib and erlotinib to the kinase (42). Crizotinib (a TKI) that inhibits Anaplastic Lymphoma Kinase (ALK) and Mesenchymal-Epithelial transition (MET) showed a response rate of ~60% in patients with ALK-positive NSCLC. However, some patients relapse within a year due to mutations in the tyrosine kinase domain of the ALK gene (43,44).

Figure 1. Mechanisms that regulate sensitivity and resistance in cancer cells. (A) Chemotherapeutic drugs are effective when they enter cancer cells and activate multiple pathways, such as inhibiting DNA repair, increasing the expression of apoptotic proteins, inducing an immune response, and inhibiting oncoproteins. These actions lead to DNA damage and cell death. (B) In resistant cells, higher levels of efflux proteins decrease drug accumulation within cancer cells, increase metabolism of inactive compounds, inhibit apoptotic proteins, alter drug targets, result in insufficient drug levels within cells, decrease immune responses, and enhance survival responses (e.g., proinflammatory cytokines). Preexisting templates were used to create figures in BioRender (https://www.biorender.com/ free online version).

Enhanced DNA repair

Chemotherapeutic drugs, including cisplatin and 5-FU, as well as radiation therapy, such as X-rays, induce DNA damage and kill cancer cells. However, improving DNA repair mechanisms in response to this damage can lead to the development of drug resistance (45). Studies suggest that DNA repair genes, such as RAD23 nucleotide excision repair protein B, Fanconi anemia complementation group G and Flap structure-specific endonuclease 1, are upregulated in response to chemotherapy (46). DNA damage triggers cell cycle arrest in normal cells, allowing them to repair the damage. However, mutations or alterations in oncogenes can disrupt cell cycle arrest. However, a mutation in p53 can interrupt cell cycle arrest (47). Additionally, p53 plays a significant role in regulating apoptosis, and its mutation reduces drug-induced apoptosis, leading to resistance (48). As a therapeutic strategy, inhibition of the DNA damage response machinery has been developed, targeting the single-strand break repair enzyme poly(ADP-ribose) polymerase 1 (PARP1) (49). Breast and ovarian tumors harboring mutations in BRCA1 or BRCA2 are sensitive to PARP inhibitors due to impaired homologous recombination DNA repair (50). Resistance to PARP inhibitors was observed in tumors with in-frame BRCA2 deletions that restore DNA repair, allowing cells to survive treatment (51,52).

Tumor heterogeneity

Cancer cells endure constant stress and continually evolve to survive in diverse environments, resulting in a heterogeneous tumor population. Intertumoral heterogeneity arises from various germline, somatic, and/or environmental factors, as well as diverse tumor subpopulations, including cancer cells, immune cells, and stromal cells. Previous studies indicate that cancer cell subpopulations have different genetic makeups that co-exist in tumors of e.g. breast cancer, ovarian cancer and renal cell carcinoma (53–55). These clonal variants exhibit different sensitivities to chemotherapy, so the initial treatment will kill some tumor cells, while less sensitive cancer cells will survive. The genomic heterogeneity of subpopulations evolves under drug treatment through a Darwinian selection process, as evidenced by changes in subclone composition at different stages of treatment (56–58). Recent studies employing high-throughput methods, such as single-cell RNA sequencing and mutation characterization, have identified evolutionary dynamics within a tumor from the same patient and across tumors from different patients (59,60). These genomic changes were associated with tumor evolution and contributed to the development of multidrug resistance (61,62). In addition, immune analysis of HBV-associated human hepatocellular carcinoma (HCC) revealed reduced T-cell infiltration, suggesting the regulation of an intra-tumoral immune-suppressive microenvironment (63). Thus, tumor heterogeneity and altered immune landscapes, predominantly immune-suppressive, are significant challenges to understanding resistance mechanisms and treatment strategies (Fig. 2).

Figure 2. The CSC model demonstrates cancer cells' ability to adapt to therapeutic pressure by rerouting signaling pathways, providing a selective advantage to therapy and leading to treatment resistance. Chemotherapy or immunotherapy treatment leads to the evolution of drug-resistant CSCs due to their inherent ability to self-renew, low proliferation rates, enhanced DNA repair mechanisms, and their capacity to reside in a protective tumor microenvironment, allowing them to survive and repopulate after therapy. CSC, cancer stem cell.

Cancer cell plasticity

Tumor cell plasticity, as evidenced by an epithelial-mesenchymal transition (EMT), has been shown to confer chemo- and immunotherapeutic resistance in cancers and to recapitulate stem cell characteristics (64–66). Cancer cells that undergo EMT exhibit several phenotypic changes, including increased motility, enhanced migratory capacity and resistance to apoptosis (64,67,68). A defining feature of EMT in cancer is the acquisition of mesenchymal features, characterized by increased levels of mesenchymal markers, such as vimentin and N-cadherin, and decreased expression of epithelial markers, such as E-cadherin. EMT-activating transcription factors such as snail family transcriptional repressor 1 (SNAIL1), twist family bHLH transcription factor 1 (TWIST1), and zinc finger E-box binding homeobox 1 (ZEB1) induce epithelial cells to gain mesenchymal traits, such as motility and invasiveness, without fully undergoing a phenotypic shift. This transition promotes metastasis and strengthens chemoresistance by reinforcing CSC traits that natively resist standard treatment. EMT-induced chemoresistance is driven by multiple mechanisms, including improved DNA repair, increased expression of drug efflux pumps (ABC transporters), and the activation of survival pathways such as PI3K/AKT and nuclear factor (NF)-κB (65,69,70). An example of EMT in cancer drug resistance includes breast cancer, where acetylation of Slug at lysines 166 and 211 by CREB-binding protein boosts its stability, facilitates EMT and augments breast cancer cell motility by downregulating E-cadherin and upregulating N-cadherin and vimentin (71). In cervical cancer cells, YTH N6-methyladenosine RNA-binding protein F2 facilitates motility, invasion, and EMT, while diminishing cisplatin chemosensitivity via stabilizing AXIN1; its knockdown mitigates these effects and increases drug sensitivity. Protein arginine methyltransferase 5 facilitates EMT and metastasis in high-risk neuroblastoma by modulating the EGFR and AKT pathways, activating NF-κB and upregulating ZEB1, SNAIL and TWIST1; its suppression curtails tumor proliferation and the expression of EMT transcription factors (72). In prostate cancer, Ephrin-A2 facilitates metastasis, angiogenesis and EMT by downregulating epithelial markers and upregulating mesenchymal markers; its silencing counteracts these effects (73). Immunotherapy has the advantage in the context of tumor heterogeneity, as the adaptive immune system can recognize multiple tumor antigens within a heterogeneous cancer cell population. However, tumors inhibit the immune system by upregulating suppressive ligands such as programmed death ligand 1 (PD-L1) and TGF-β, and by recruiting myeloid-derived suppressor cells (MDSCs) and T-regulatory cells (Tregs). The tumor cell plasticity manifested as an EMT has been identified as a major obstacle in effectively treating cancer patients. New drugs are being developed to target the EMT-regulating factors to reduce EMT changes. However, it is proving difficult due to redundancy and overlap among pathways regulating tumor cell plasticity (74,75). Nevertheless, new agents that reduce EMT should be developed to combine with immunotherapies to improve treatment strategies.

Adaptive and oncogenic bypass mechanisms for resistance

Prior studies have shown that EGFR activation results in resistance to chemotherapeutic agents (63,76,77). EGFR-targeted therapies have demonstrated increased sensitivity to chemotherapeutics such as 5-FU, paclitaxel and TNF superfamily member 10 in in vitro and/or in vivo cancer models (63,76,77). However, colorectal cancer with a KRas mutation was resistant to pharmacological targeting of EGFR because oncogenic KRas functions independently of upstream EGFR activation. Data show that membrane-associated metalloproteases, ADAM, cleave and activate various growth factor ligands. They play a significant role in regulating adaptive resistance (63,78). Research has shown that inhibiting ADAM metallopeptidase domain 17, in combination with chemotherapy, results in a synergistic effect that significantly inhibits tumor growth across multiple cancer types (79,80). The erb-b2 receptor tyrosine kinase 3 (ERBB3) (or HER3)-induced PI3K-AKT pathway is essential for regulating adaptive resistance to pharmacological targeting of EGFR (81–83). This ‘oncogenic bypass’ occurs because the primary drug target remains unaltered and continues to inhibit tumor growth. However, when an alternative kinase is activated by an adaptive feedback loop, it results in the emergence of an adaptive resistance mechanism; for example, MET amplification activates ERBB3-dependent PI3K, leading to resistance to EGFR inhibitors in ~20% of patients with EGFR-driven lung cancer (84).

CSCs and drug resistance

Residual tumors after chemotherapy and/or radiation therapies contain more CSCs than untreated tumors, which are thought to significantly contribute to therapeutic resistance and the eventual disease relapse (85–88). CSCs are well known for their ability to self-renew and differentiate into various cancer cell types (86).

CSCs are quiescent and, therefore, resistant to chemotherapy, which targets rapidly dividing cells (Fig. 2) (89). Furthermore, CSCs are highly resistant to conventional therapies partly due to high expression of aldehyde dehydrogenase, CD44, anti-apoptotic proteins such as BCL-2 and BCL-XL, drug efflux-inducing ABC transporter proteins, DNA repair and activation of pro-survival signaling molecules, including WNT, NOTCH and NF-κB (89–94). One of the CSC markers, phosphorylated CD44 (Ser-291), inhibits ubiquitin E3 ligase F-box protein 21. As a result, proteasomal degradation of P-gp in breast and ovarian cancer cells is diminished, thereby enhancing drug efflux and reducing the cytotoxic efficacy of the drug (89–93). CSCs are known to reside in the region of tumors with hypoxic niches where the pH is low, leading to stressful conditions. Such a tumor environment leads to hypoxia-inducible factor (HIF)-1α activation, which stimulates the expression of ABC transporters, such as multidrug resistance-associated protein 1, which are downstream targets of the HIF-1α axis in CSCs (95). Furthermore, lower CSC proliferation rates and poor blood vessel formation result in insufficient drug availability to CSCs (96). The plasticity of tumors allows differentiated cells to revert to a stem cell-like state. Therefore, targeting the tumor cells and the CSC population is essential to prevent drug resistance and disease relapse.

Primary and acquired resistance to immunotherapy

The immune system continuously interacts with cancer cells during tumor progression, a process influenced by immune evasion mechanisms. T-cells are activated when major histocompatibility complex (MHC) molecules of the antigen-presenting cells present antigens to specific T-cell receptors on naïve T cells. This interaction of CD28 and B7 (CD80 and CD86) receptors is essential for T-cell activation. However, this process is tightly regulated by inhibitory checkpoints to prevent collateral damage to healthy cells and the emergence of autoimmunity. The effector T cells are inactivated by CTLA-4 receptors, which, in turn, compete with CD28 for B7 ligands, thereby inhibiting T-cell proliferation and IL-2 secretion (97,98). In metastatic melanoma, ~25-33% of the patients who respond to checkpoint blockade therapy with anti-CTLA-4 or anti-programmed cell death 1 (PD-1) agents relapse over time despite initial response to these therapies (99,100).

The loss of T-cell function, the development of escape mutations, and reduced or absent T-cell recognition due to the repression of tumor antigen presentation appear to be potential mechanisms. Immunotherapy treatments initially show a promising response, characterized by reduced IL-2 secretion and the use of tumor-infiltrating lymphocyte adoptive cell therapy. However, over time, it develops resistance due to the loss of β-2-microglobulin (B2M), a critical component shared by all human leukocyte antigen (HLA) class I molecules. B2M is essential for proper folding and transportation of HLA class I to the cell surface, and its reduction or elimination leads to diminished HLA class I presentation on the cell surface (101,102). In cases of anti-PD-1 therapy, the resistant cells often harbor a B2M truncation, leading to complete loss of cell-surface HLA class I expression (Fig. 3) (103).

Figure 3. Tumor cells' expression of immune checkpoint blockade molecules inhibits T cell activity in the tumor microenvironment. PD-L1/2, Programmed death-ligand 1/2; and CD80/86, Cluster of Differentiation expression on tumor cells leads to binding of PD-1, Programmed death-1; and CTLA-4, cytotoxic T-lymphocyte antigen 4 on T cells. This binding inhibits TCR signaling, leading to T-cell inactivation. ICB, Immune Checkpoint Blockade inhibitors; anti-PD/PD-L1/2, and anti-CTLA-4 antibodies block the interactions between PD-1/PD-L1/2 and CTLA-4/CD80/86, respectively. This inhibition relieves the negative regulation of T cells, leading to their activation and subsequent T-cell-mediated killing of tumor cells. Preexisting templates were used to create figures in BioRender (https://www.biorender.com).

In cancers such as breast cancer, lung cancer, and glioblastoma, the chemotaxis of pro-inflammatory M1 macrophages towards cytokines released by tumor CSCs results in their conversion to M2 (anti-inflammatory) macrophages at the tumor site. M2 macrophages secrete TGF-β, IL-10, IL-23, and arginase I, creating an immune-suppressive TME (103–106). For example, in HCC, CD133+ cells release the pro-inflammatory cytokine IL-8, which promotes the M2 polarization of tumor-associated macrophages (TAMs) and, in turn, stimulates therapeutic resistance (107). TAMs activated by CSCs inhibit T-cell cytotoxicity by promoting the overexpression of cancer immune checkpoint receptors, such as PD-L1 and CD80/CD86. These immune checkpoint receptors then interact with PD-1 and CTLA-4 on the surface of CD8+ T cells, leading to the subsequent impairment of the immune response and increased resistance to therapy (108,109).

The intrinsic factors that contribute to chemo and/or immunotherapy resistance include mutation(s) or nongenetic alterations in the target or other proteins that interfere with drug- and/or immuno-targeting, or overexpression of the target, leading to a stoichiometric imbalance between the drug and its cellular target. Additionally, redundancy in cytokine function and in the drugs' protein targets, coupled with compensatory overexpression of another membrane receptor and its downstream signaling, often serves as a significant mechanism of resistance (110,111). Signaling through the MAPK pathway, enhanced PI3K signaling following PTEN loss, the WNT/β-catenin pathway, and interferon-γ signaling result in a diminished or absent T-cell response due to reduced or lost tumor antigen expression. These resistance mechanisms may then evolve into adaptive resistance. For example, activation of the oncogenic MAPK pathway induces suppressed T-cell recruitment and function (112).

Cancer cells have unique features that enable them to evade immune recognition by exploiting TME, thereby conferring resistance. In recent years, researchers have also explored combining immunotherapy with other treatment modalities, such as chemotherapy, radiation therapy, and targeted therapy. Overall, the development of novel immunotherapies and the combination of different treatment modalities hold great promise for improving outcomes in cancer patients, particularly those with previously untreatable or advanced diseases. Some immunotherapies approved for treatment by the Food and Drug Administration (FDA) are discussed in the following chapter.

Clinically approved single-agent and combination regimens for solid tumors

Overall, the development of novel therapies and the combination of different treatment modalities hold great promise for improving outcomes in cancer patients, particularly those with previously untreatable or advanced diseases. However, more research is needed to better understand the complex interactions among cancer cells, the surrounding matrix, and the immune system, and to identify new immunotherapy targets that can overcome resistance mechanisms and lead to more durable responses.

Crosstalk between CSCs and immune cells

This bidirectional process involves mechanisms that protect cancer cells from chemotherapy and from immune attack, and vice versa. CSCs influence the TME by secreting specific cytokines and chemokines, which alter immune-cell infiltration and polarization within the tumor, thereby promoting therapeutic resistance and immune evasion (Fig. 4) (113–115). Chemoresistant cells activate EMT pathways, including Wnt/β-catenin (116), expression of chemokines such as C-C motif chemokine ligand-1, −2 and −5, IL-8 (115,117) and NF-κB, which also contribute to immune evasion by secreting IL-6, in turn activating the JAK/STAT3 pathway, which can drive EMT and CSC self-renewal (64), and TGF-β can activate SMAD signaling, which can reinforce stemness and promote immunosuppressive effects (113–115,118). EMT changes reduce MHC molecules, which impairs the ability of T-cells to recognize them (119). In addition, TAMs, MDSCs, and Tregs release cytokines such as IL-10, IL-6, and TGF-β, which enhance stemness and chemoresistance by activating the STAT3, NF-κB, and SMAD signaling pathways (120). This dynamic adaptation undermines the therapies targeting static CSCs in patients. Although EMT-directed therapies present significant therapeutic potential because of their complexity and microenvironmental context dependency, no effective targeting approach has been successful. A better understanding of how bidirectional interactions between EMT and the TME will be critical for improving therapeutic outcomes.

Figure 4. Mechanisms illustrate a bidirectional relationship between CSCs and immune cells: CSCs and immune cells release soluble mediators that influence each other, affecting immune cells' recruitment, function, and phenotypic changes in the tumor microenvironment and cancer stem cells. IL-6, interleukin-6; STAT3, signal transducer and activator of transcription 3; MDSC, myeloid-derived suppressor cell; CSC, cancer stem cells, EMT, epithelial-mesenchymal transition; JAK1, Janus kinase 1; GM-CSF, granulocyte-macrophage colony-stimulating factor; TGF-β, transforming growth factor-β; ROS, reactive oxygen species; PDL-1, programmed death-ligand 1; CD47, cluster of differentiation 47; TAM, tumor-associated macrophage; CCL, chronic lymphocytic leukemia.

Strategies to overcome drug resistance

Treatment with single drugs can lead to resistance over time due to complex interactions between heterogeneous tumor cells and the surrounding TME (4,121,122). Therefore, it is vital to understand how cancer cells regulate resistance to specific drugs or immunotherapies to improve therapeutic efficacy. Additionally, specific tumor cells can reprogram stromal and immune cells through factors such as cytokines, thereby promoting tumor progression and inhibiting cell death (123). CSCs play a crucial role in regulating resistance (124). Understanding the crosstalk between CSCs and immunotherapy is important; for example, studies have shown that low-dose chemotherapy can ‘prime’ the immune system by depleting MDSCs or inducing immune cell death, making the tumor more susceptible to immunotherapy (125). However, high doses can harm effector T cells, underscoring the importance of precise timing and sequencing in combination therapies. Conventionally, cancers were treated with the highest tolerated dose of chemotherapy or targeted drugs. However, such a treatment strategy leads to tumors selecting cells within tumors that are resistant to the drug. Recent cancer treatment strategies involve low-dose dose-escalating chemotherapy, followed by low-dose chemotherapy, then high-dose chemotherapy again; this cycling prevents cells from initiating an adaptive response to the drug, thereby delaying the development of drug resistance (126). For example, melanoma cells that acquired resistance after treatment with BRAF- and MEK-targeted therapy displayed robust drug addiction and were sensitive to drug withdrawal (127). A combination therapy that inhibits two crucial immune checkpoints, CTLA-4 and PD-1, significantly increased response rates and improved overall survival of patients with metastatic melanoma (128,129). Another strategy involves combining molecularly targeted therapy with immunotherapy (Table I). Targeting oncogenic BRAF alone in melanoma provided limited disease control. However, it is associated with positive effects in the TME, including increased antigen presentation, HLA expression, T-cell infiltration and improved T-cell function (2,113–116), which, in turn, increases PD-L1 expression through adaptive resistance (130). Another strategy to circumvent resistance is to block energy to tumor cells. Cancer cells appear to require higher ATP levels for survival and drug resistance. Extracellular ATP degradation or inhibition of ATP internalization can be considered for combination therapy with chemotherapy or immunotherapy to enhance the anticancer efficacy of TKIs (2,131–133).

Table I. Examples of clinical trials exploring the efficacy of monotherapy and combination therapies and their outcomes in solid tumors.

Table I.

Examples of clinical trials exploring the efficacy of monotherapy and combination therapies and their outcomes in solid tumors.

A, Completed clinical trials for solid tumors
Type of cancer	Treatment monotherapy	Combination therapy	Outcomes
High risk & metastatic TNBC	Pembrolizumab (Keytruda), immune checkpoint inhibitor for PD-1 protein (NCT02447003)	Pembrolizumab plus chemotherapy (NCT03036488)	Combination therapy reduced the risk of disease progression/death by 35% and PFS to 9.7 vs. 5.6 months compared to chemotherapy alone in clinical trials
Metastatic TNBC	Atezolizumab (Tecentriq) (PD-L1 inhibitor) (NCT02425891)	Atezolizumab plus carboplatin (NCT03206203)	Combination therapy extended median PFS from 2.2 to 4.1 months and OS from 8.6 to 12.6 months compared to carboplatin alone
Prostate cancer	Ipilimumab (anti-CTLA-4 monoclonal antibody) (NCT02279862)	Ipilimumab plus ADT (NCT01194271)	Ipilimumab plus ADT has high PSA response rates; it is associated with significant immune-related adverse events and does not improve OS compared to standard treatment
		Ipilimumab plus nivolumab (NCT02985957)	Combination therapy showed a moderate ORR of 25-40% and improved survival in selected patients with mCRPC compared with single-agent ipilimumab
Glioblastoma	Anti-PD-1 plus CAR T cells (NCT03726515)	Pembrolizumab plus CART-EGFRvIII T cells (NCT03726515)	Anti-PD-1 plus CAR T cells in GBM have yielded limited long-term efficacy. Combination therapy did not significantly boost clinical efficacy due to antigen loss and tumor heterogeneity
Squamous cell carcinoma	Bintrafusp alfa (NCT04428047)	PD-L1 and TGF inhibitors (NCT02699515)	In a phase I study of pretreated advanced squamous cell carcinoma of the head and neck, bintrafusp alfa, a bifunctional fusion protein targeting both TGF-β and PD-L1 achieved an ORR of 13-30.5% (partial response), with a disease control rate of 34%.
B, Recently FDA-approved clinical trials for solid tumors
Type of cancer	Treatment monotherapy	Combination therapy	Outcomes
Ovarian cancer	Platinum	Platinum plus Pembrolizumab	For platinum-resistant ovarian cancer
Solid tumors	Augtyro (repotrectinib)	Not applicable	Its next-generation tyrosine kinase inhibitor was approved in 2024 for locally advanced or metastatic solid tumors harboring a neurotrophic tyrosine receptor kinase gene fusion
Breast cancer	Vepdegestrant (Veppanu)	Not applicable	Vepdegestrant a heterobifunctional protein degrader, for ER-positive, HER2-negative ESR1-mutated advanced or metastatic breast cancer (FDA approval 2026)
Ovarian, fallopian tube or peritoneal cancer	Not applicable	Pembrolizumab plus Paclitaxel	Pembrolizumab plus Paclitaxel for platinum-resistant cancers (FDA approval 2026)
Colorectal cancer	Not applicable	Encorafenib plus Cetuximab plus Chemotherapy	Metastatic colorectal cancer with BRAF V600E mutations (FDA approval 2026)
Gastric and gastroesophageal junction cancers	Not applicable	Durvalumab (Imfinzi) + chemotherapy	Early-stage gastric and gastroesophageal junction cancers to be used before and after surgery (FDA approval 2025)
Small cell lung cancer	Tarlatamab (Imdelltra)	Not applicable	Approved for small cell lung cancer (2025).

[i] TNBC, triple-negative breast cancer; PD-L1, programmed death-ligand 1; CTLA-4, cytotoxic T-lymphocyte antigen 4; CAR T, chimeric antigen receptor T-cells; ADT, androgen deprivation therapy; TGF, transforming growth factor; PFS, progression-free survival; OS, overall survival; PSA, prostate-specific antigen; ORR, objective response rate; mCRPC, metastatic castration-resistant prostate cancer; GBM, glioblastoma.

Conclusions and future directions

Drug resistance to therapy is multifaceted, allowing uncontrolled cancer progression and tumor relapses, leading to reduced patient survival. Significant factors contributing to drug resistance include therapeutic pressure, tumor heterogeneity, the TME, increased drug metabolism, and altered drug targets. Targeted therapies are vital in combating cancer and reducing toxicity to normal cells (134). However, single-drug treatment strategies lead to the development of resistance over time due to complex interactions between heterogeneous tumor cells and the surrounding TME. The newer strategy of targeting multiple driver genes responsible for chemo and/or immunological resistance could significantly reduce or eliminate resistance and prolong patients' lives. Emerging strategies to overcome drug resistance include combination therapies, personalized immunotherapy, adoptive cell therapy, and the development of novel chemotherapeutic and immunotherapeutic agents. For instance, in high-risk metastatic TNBC, pembrolizumab alone is rarely used as primary treatment. However, pembrolizumab plus chemotherapy is recognized as the standard of care. Combination therapy reduces the risk of disease progression/death by ~35% and improves PFS to 9.7 vs. 5.6 months with chemotherapy alone in clinical trials. However, patients often experience the compounding side effects of both treatments. By contrast, in glioblastoma, the brain's immunosuppressive environment and tumor heterogeneity have limited the long-term efficacy of anti-PD-1 plus CAR T cells. Combination therapy did not significantly boost clinical efficacy due to antigen loss and tumor heterogeneity (Table I) (135,136). Furthermore, CSC plasticity and heterogeneity can limit the effectiveness of therapies. Ongoing research and development in these areas can lead to further improvements in cancer treatment outcomes and in the quality of life for cancer patients. Additional studies are necessary to determine if resistance mechanisms or phenotypes vary across different tissue microenvironments within the same host. Identifying distinct subpopulations with unique therapeutic vulnerabilities may lead to the development of novel strategies for cancer treatment. Advanced technologies, including high-throughput techniques, next-generation sequencing and large-scale data analysis, are crucial for identifying predictive biomarkers that facilitate patient stratification. These integrated advances will pave the way for the next generation of anticancer therapies.

Acknowledgements

Not applicable.

Funding

This work is supported by the Departments of Pathology (to KBR), Wayne State University (WSU) and Urology (to SRC), WSU, the Department of Veterans Affairs Merit Review grant (to AKR) and the Department of Veterans Affairs Basic Laboratory Research & Development Research Career Scientist award (to AKR).

Availability of data and materials

Not applicable.

Authors' contributions

All authors have substantially contributed to the writing and revision of the manuscript. KBR developed the conceptual framework of the review and wrote the manuscript. SRC and AKR contributed to the critical discussion of the literature and manuscript revision, as well as to the generation of figures and tables. Data authentication is not applicable. All authors 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.

Glossary

Abbreviations

Abbreviations:

References