Renal cell carcinoma (RCC) is a group of neoplastic
diseases that affect the renal parenchyma and represent 2–3% of all
cancer diagnoses (1). In 2022, the
GLOBOCAN database estimated the global incidence of RCC as 434,419
cases, which were associated with 155,702 deaths (2). RCC is more commonly diagnosed in men
(ratio men to women, 2:1), and in the sixth decade of life
(3). Up to 70% of patients are
incidentally diagnosed with RCC, 50% of them with metastatic
disease (4); although localized RCC
is curable, in up to 30% of patients this will progress to
metastatic disease, which has a median survival time of 6–10 months
(5). Among the different types of
RCCs, 80% of all diagnoses consist of the clear cell histological
variety (ccRCC), which is followed in frequency by the papillary
variant (10–15% of cases), the chromophobe cell variant (4–5% of
cases), and other molecularly defined phenotypes (<1% of cases)
(6).
The high rates of mortality that are observed in RCC
have been associated with factors such as the high prevalence of
advanced disease at diagnosis (7)
and the intrinsic chemoresistance of RCC tumors, which is mostly
related to apoptotic resistance, the upregulation of xenobiotic
excretion systems (8–10) and the metabolic dependence of such
tumors on the Warburg effect (11).
In total, <10% of patients with RCC will respond to cytotoxic
chemotherapy (12), which makes it
necessary to use novel approaches for which little clinical
information is available. Current RCC treatments can be grouped
into the following categories: cytotoxic chemotherapy, surgery,
local therapy, recombinant-cytokine therapy, targeted
anti-angiogenic therapy, immunotherapy [immune checkpoint blockade
(ICB)], and other therapies that include the use of inhibitors of
the mechanistic target of rapamycin pathway (Table I). Despite the broad diversity and
availability of RCC treatments, the need for a prognostic tool for
use in selecting the treatment of choice and evaluating the
clinical responses of patients remains a matter of controversy
(13). Treatment selection depends
on factors such as the histological variety, cellular grade and
clinical stage of the disease, as well as the failure of previous
treatments (14–16). In this regard, there are currently
several scales that have been validated for risk classification and
clinical decision-making in patients with RCC; among these, the
Heng score (International Metastatic RCC Database Consortium or
IMDC), the MSKCC scale (Memorial Sloan-Kettering Cancer Center),
and the general physical status according to ECOG-PS criteria (the
Eastern Cooperative Oncology Group performance score) (17–19)
stand out (Table II).
In the last decade, the use of monoclonal antibodies
for reversing the ‘exhaustion’ state in tumor infiltrating
lymphocytes (TILs) has proven to be a valuable treatment for
numerous solid tumors and hematologic cancers. In 2015, the
ChekMate-025 study demonstrated the efficacy of nivolumab (which
was initially approved for treating melanoma and non-small cell
lung cancer) in treating patients with RCC (20). In addition to nivolumab [which
blocks the programmed cell death protein 1 (PD-1) receptor], four
other monoclonal antibodies are currently approved for use in RCC,
all of which reverse the inhibition of lymphocyte immune effectors:
Pembrolizumab, which is also a PD-1 blocker; ipilimumab, which
blocks the cytotoxic T-lymphocyte associated protein 4; and
atezolizumab/avelumab, which blocks PD-1 ligand in myeloid and
tumor cells and prevents PD-1 inhibitory signals in lymphocytes
(Table III) (20–30).
In the following section, the current knowledge of
the cellular mechanisms that lead to lymphocyte exhaustion within
the highly dynamic tumor-immune microenvironment (TIME) was
reviewed. It was concluded with a short description of experimental
biomarkers that have been used to predict the patients' responses
to ICB therapy.
The TIME comprises a network of interacting elements
within the tumor tissue that can be categorized as follows: Cells
(tumor, stroma and infiltrating immune cells), small soluble
elements (proteins, cytokines, growth factors, metabolites and
chemokines), and the extracellular matrix (31). The growth of tumors requires two
conditions: Cell transformation, whether genetic or acquired
(32) and immune dysfunction
(33). This second requirement
explains the association between immunodeficiency status and cancer
development (34). The clearance of
transformed cells from tissues requires the activation of cytotoxic
immunity that is achieved through the infiltration of
CD8+ cytotoxic lymphocytes and natural killer cells into
a tumor (35). Antitumor immunity
is so efficient that even though transformation and cell damage
occur over the course of every life, cancer develops only in a
small proportion of patients; the occurrence of cancer is promoted
by immune dysfunction.
Tumor cells proliferate at higher rates compared
with normal cells. This accelerated proliferation, which is linked
to metabolic changes that take place within the tumor bed, results
in dysfunctional local immunity and further selection of the
best-adapted tumor cells (36–38).
Cytotoxic chemotherapy exploits this increased proliferative rate,
and cytotoxic treatments are widely used in most neoplastic
diseases other than RCC. The peculiarities of RCC include its
intrinsic aggressive nature, its increased infiltration with
lipids, its high rate of metastasis, and its resistance to
cytotoxic chemotherapy (39). This
chemo-resistance has numerous causal factors, both intrinsic (or
genetic) and acquired. It is important to note that the epithelial
renal cells normally have secretion systems for xenobiotics and
intrinsic antioxidant mechanisms protecting the cells from toxic
damage (40). Given that most RCC
subtypes arise from renal epithelia, it is not surprising that such
mechanisms are enhanced in renal carcinoma. In addition, renal
tumor cells have increased expression of anti-apoptotic proteins
Bcl-2, Bcl-XL, ARC (apoptosis repressor with a caspase
recruitment domain) and XIAP (X-linked inhibitor of apoptosis)
while pro-apoptotic proteins such as Bim are decreased.
Anti-apoptotic and pro-apoptotic proteins are regulated by NF-κB
and von Hippel-Lindau (VHL) pathways, respectively (8,10,41).
In addition, although the presence of TILs is a
favorable prognostic factor for most cancers, such infiltrative
cells are associated with poor outcomes in RCC (44,45).
Consequently, a hostile TIME develops that leads to the selection
of tumors that are resistant to hypoxia, acidosis and the low
availability of nutrients. In addition, a hostile TIME negatively
affects lymphocyte-dependent antitumor immunity (Fig. 1 and Table IV) (31,46–51).
Previous studies suggested that dysbiosis is an important element
to be considered when evaluating either the responses of tumors to
ICB or the general prognosis of patients with neoplastic diseases
(52,53). The molecular basis for lymphocyte
dysfunction involves several mechanisms that are associated with
peripheral tolerance, namely anergy, suppression and exhaustion
(54). Immune cell exhaustion is
reversed by ICB, which blocks interactions between the inhibitory
receptors of lymphocytes and their ligands (55). The PD-1/programmed death-ligand 1
(PD-L1) axis is the most studied of these interactions within TILs
(56,57).
Even though numerous patients achieve complete
clinical response to ICB therapy, a significant proportion of
patients show only a partial response or no response at all, which
is occasionally accompanied by signs of systemic toxicity (58). This situation explains why the
search for prognostic markers for ICB in patients with RCC is a
highly active area of research. Most prognostic markers for RCC can
be divided into those addressing disease progression and those
addressing responses to treatments, in particular immunotherapy and
directed therapies. Thus, predicting the ICB responsiveness will
impact in selecting the patients who will benefit the most and have
the lowest probability of developing adverse events after receiving
immunotherapy. There are currently no standardized and validated
methods for properly assessing the risk/benefit ratio of using ICB
therapy. Therefore, the goal of the present review was to
synthesize the reported findings of the studies that have focused
on this important topic.
ICB therapy is associated with an average mortality
rate of 1%, with death mostly caused by immune-related adverse
events (58). After the reporting
of successful results from the CheckMate-025 study, and given the
low predictability and consistency of ICB responsiveness (59), interest has been increasing in the
search for reliable markers of ICB responsiveness. Among the
biomarkers that have been studied, three stand out for their
consistency: the level of C-reactive protein (CRP), the number of
TILs and the basal expression levels of exhaustion markers in tumor
tissue. CRP is an acute phase reactant that is frequently used for
evaluating systemic inflammation, making it a logical putative
marker for ICB responsiveness given the close association between
inflammation and cancer. Previous studies have indicated that low
basal CRP levels or low normalized levels of CRP measured after
patients received their first ICB doses were predictive of their
ICB responsiveness (60–63). Studies investigating TILs found that
a patient's prognosis is associated with the nature of his or her
infiltrating cells; infiltration with inflammatory leukocytes was
associated with the best responses to ICB therapy (64–66).
In peripheral blood, a recent study observed that increased numbers
of circulating eosinophils were associated with an improved
response to ICB, which is an intriguing result given the regulatory
role that eosinophils play in systemic inflammation (67). Interestingly, the basal expression
level of PD-L1 has not been consistently predictive of ICB
responsiveness (68–70), whereas the basal expression level of
T cell immunoglobulin and mucin-domain containing-3 (TIM-3) appears
to be (71).
Several additional markers have been studied for
predicting the response to ICB in patients with RCC. For example,
longer responses to ICB have been associated with decreased levels
of circulating tumor DNA, increased levels of chemokine CXCL14,
increased levels of circulating miR-22 and miR-24, and the presence
of immunogenic transcriptional signatures (72–75).
In this context, several markers have been associated with poor
responses after ICB therapy (increased levels of interleukin-8) or
predictive of the development of immune-related adverse events
(decreased levels of miR-146a) (76,77).
All the studies described in this section are summarized in
Table V.
From a technical perspective, the evaluation of
leukocytes' exhaustion markers require the performance of
histopathology after the direct sampling of tissue, which is not
feasible for all diagnoses (78).
In this context, the studies assessing the suitability of
peripheral biomarkers for predicting ICB responsiveness are
encouraging (79,80).
Several limitations currently prevent the formal use
of markers to predict ICB responsiveness. First, the inconsistency
of reported outcomes is mostly related to heterogeneity in the
target population and the low number of patients that have been
studied. In addition, a lack of standardization in the use of
methods and reagents is complicating the replication of pioneering
studies. Furthermore, the relationship between the expression of
such potential biomarkers and the underlying mechanisms of
resistance to ICB is not fully understood, making it difficult not
only to predict ICB responsiveness but also to know the clinical
safety of using ICB. Finally, the intrinsic resistance of RCCs to
chemotherapy and the complex combinations required for treatment
make it difficult to determine a logical approach for studying the
expression of putative cancer biomarkers. In the future, by
integrating multi-omics data and machine-learning approaches, it
should be possible to create more accurate prediction models that
will help in the identification of novel biomarkers for ICB
responsiveness.
The authors are grateful to Dr. Susana Chávez
(Department for Research Assistance, University Hospital ‘José
Eleuterio González’, Autonomous University of Nuevo León) for
reviewing the English language in this manuscript.
The present study was supported by CONAHCYT México (grant no.
783446).
Not applicable.
RGG and MMT performed the literature review, wrote
the manuscript, made the illustrations and constructed the tables.
AGG, MCSC and MMT revised the manuscript. RGG and MMT were involved
in the conception of the study. All authors read and approved the
final version of the manuscript. Data authentication is not
applicable.
Not applicable.
Not applicable.
The authors declare that they have no competing
interests.
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