A Genetic Polymorphism in CTLA-4 Is Associated with Overall Survival in Sunitinib-Treated Patients with Clear Cell Metastatic Renal Cell Carcinoma

PD-L1 Expression and Treatment Implications in Metastatic Clear Cell Renal Cell Carcinoma: A Systematic Review

BACKGROUND: Over the past decade, immune checkpoint inhibitors (ICIs) have increasingly become the standard of care for various advanced malignancies, including metastatic clear cell renal cell carcinoma (mccRCC). Most ICIs currently used in clinical practice inhibit the interaction between the programmed cell death protein-1 (PD-1) and programmed death ligand-1 (PD-L1) complex. A deeper understanding of this interaction and PD-L1 expression in tumors has led to more effective therapies in the treatment of advanced cancers, but the debate regarding the utility of PD-L1 as a biomarker continues. OBJECTIVE: We aimed to systematically evaluate the role of PD-L1 in mccRCC in terms of expression and treatment implications. METHODS: Following PRISMA guidelines, we performed a systematic literature search using PubMed and Embase through August 31, 2020. Titles and abstracts were screened to identify articles for full-text review. A hand search was also performed using Google Scholar and the bibliography to relevant studies. RESULTS: A total of 26 articles were identified, and relevant data were extracted and organized. The available information regarding PD-L1 expression in mccRCC from both prospective clinical trials and retrospective studies were summarized. We discussed the utility of PD-L1 as a predictive and prognostic biomarker in mccRCC, its association with other potential biomarkers, and the pattern and level of expression of PD-L1 in primary versus metastatic tumors. CONCLUSIONS: Although significant progress has been made, much more remains to be learned regarding the differences between PD-L1+ and PD-L1- ccRCC tumors, in terms of both the underlying biology and clinical responses to immunotherapy and other agents.

Identification of a Novel Glycolysis-Related Gene Signature Correlates With the Prognosis and Therapeutic Responses in Patients With Clear Cell Renal Cell Carcinoma

Background

Accumulating evidences indicate significant alterations in the aerobic glycolysis in clear cell renal cell carcinoma (ccRCC). We aim to develop and validate a glycolysis-related genes signature for predicting the clinical outcomes of patients with ccRCC.

Methods

mRNA expression profiling of ccRCC was obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. The protein expression levels of the core genes were obtained from the Human Protein Atlas database. We used four external independent data sets to verify the predictive power of the model for prognosis, tyrosine kinase inhibitor (TKI) therapy, and immunotherapy responses, respectively. Finally, we explored the potential mechanism of this signature through gene set enrichment analysis (GSEA).

Results

Through the GSEA, glycolysis-related gene sets were significantly different between ccRCC tissues and normal tissues. Next, we identified and constructed a seven-mRNA signature (GALM, TGFA, RBCK1, CD44, HK3, KIF20A, and IDUA), which was significantly correlated with worse survival outcome and was an independent prognostic indicator for ccRCC patients. Furthermore, the expression levels of hub genes were validated based on the Human Protein Atlas databases. More importantly, the model can predict patients’ response to TKI therapy and immunotherapy. These findings were successfully validated in the external independent ccRCC cohorts. The mechanism exploration showed that the model may influence the prognosis by influencing tumor proliferation, base mismatch repair system and immune status of patients.

Conclusions

Our study has built up a robust glycolysis-based molecular signature that predicts the prognosis and TKI therapy and immunotherapy responses of patients with ccRCC with high accuracy, which might provide important guidance for clinical assessment. Also, clinical investigations in large ccRCC cohorts are greatly needed to validate our findings.

Association of cytotoxic T lymphocyte-associated protein 4 gene -1772T/C polymorphism with gastric cancer risk: A prisma-compliant meta-analysis

BACKGROUND

We performed a meta-analysis to more precisely evaluate the association between the cytotoxic T lymphocyte-associated protein 4 (CTLA-4) -1772T/C polymorphism and overall gastric cancer (GC) risk and the influence of ethnicity and the source of controls on that association.

METHODS

A systematic literature search was performed in PubMed, EMBASE, the Cochrane Library, Web of Science (WOS) Database, Chinese National Knowledge Infrastructure (CNKI), China biomedical literature database (CBM), Wanfang database, and VIP. Two investigators independently reviewed the articles, and disagreements were resolved by discussion and consensus. The odds ratio (OR) with 95% confidence intervals (CIs) was used to assess the strength of the association between the CTLA-4 -1722T/C polymorphism and GC risk, based on the genotype frequencies in cases and controls. The meta-analyses were performed with Stata 12.0, using two-sided P values. Trial sequential analysis (TSA) was calculated by TSA Software.

RESULTS

Overall, we identified 5 studies including 1039 GC cases and 2136 controls that evaluated the association of the CTLA-4 -1722T/C polymorphism and GC risk. Overall, there was no significant association between the CTLA-4-1722T/C polymorphism and the risk of GC. In the subgroup analysis based on ethnicity, the results showed that the relationship between the CTLA-4 -1722T/C polymorphism and GC susceptibility was strongest in the Chinese population rather than in the Iranian population (TC vs CC: OR = 1.405, 95% CI: 1.100-1.796, P = .007; TC+TT vs CC: OR = 1.329, 95% CI: 1.052-1.680, P = .017). Then, there was a significant association between the CTLA-4 -1722T/C polymorphism and the risk of GC in studies with HB controls. However, the above correlation can only be reflected in specific populations and gene models. Therefore, we believe that the evidence of this correlation is insufficient.

CONCLUSION

Our meta-analysis showed that the CTLA-4 -1722T/C polymorphism may be associated with the susceptibility to GC. However, the slight correlation can only be reflected in specific populations and gene models. Therefore, we believe that this association is negligible. The large and well-designed case-control studies are needed to validate our findings.

Cell death-related molecules and biomarkers for renal cell carcinoma targeted therapy

Renal cell carcinoma (RCC) is not sensitive to conventional radio- and chemotherapies and is at least partially resistant to impairments in cell death-related signaling pathways. The hallmarks of RCC formation include diverse signaling pathways, such as maintenance of proliferation, cell death resistance, angiogenesis induction, immune destruction avoidance, and DNA repair. RCC diagnosed during the early stage has the possibility of cure with surgery. For metastatic RCC (mRCC), molecular targeted therapy, especially antiangiogenic therapy (e.g., tyrosine kinase inhibitors, TKIs, such as sunitinib), is one of the main partially effective therapeutics. Various forms of cell death that may be associated with the resistance to targeted therapy because of the crosstalk between targeted therapy and cell death resistance pathways were originally defined and differentiated into apoptosis, necroptosis, pyroptosis, ferroptosis and autophagic cell death based on cellular morphology. Particularly, as a new form of cell death, T cell-induced cell death by immune checkpoint inhibitors expands the treatment options beyond the current targeted therapy. Here, we provide an overview of cell death-related molecules and biomarkers for the progression, prognosis and treatment of mRCC by targeted therapy, with a focus on apoptosis and T cell-induced cell death, as well as other forms of cell death.

Germinal immunogenetics as a predictive factor for immunotherapy

Clinical response to checkpoint inhibitors-based (CPIs) therapies can vary among tumor types and between patients. This led to a significant amount of pre-clinical and clinical research into biomarker identification. Biomarkers have been found to cover both the tumor itself and the tumor microenvironment. Entering host-related parameters into the equation should provide a valuable strategy for identifying not only factors predictive of treatment efficacy but also of treatment-related toxicity. It is clear that germline variants can offer efficient and easily-assessable indicators (blood DNA) to enlarge the spectrum of predictive markers for CPI-based treatment. A major issue concerns the real functional significance of the reported single-nucleotide polymorphisms (SNPs) linked to CPI-treatment outcome. Powered calculations should lead to an optimal trade-off between sample size and allele frequency. New molecular technologies and new analytical methods should provide opportunities to bridge the knowledge gap between SNP-CPI treatment associations and the functional impact of these SNPs.

Expression of PD-1 and CTLA-4 Are Negative Prognostic Markers in Renal Cell Carcinoma

Immuno-oncological therapy with checkpoint inhibition (CI) has become a new standard treatment in metastatic renal cell carcinoma (RCC), but the prognostic value of the expression of CI therapy target molecules is still controversial. 342 unselected consecutive RCC tumor samples were analyzed regarding their PD-1, PD-L1, and CTLA-4 expression by immunohistochemistry (IHC). The prognostic values for cancer-specific survival (CSS) and overall survival (OS) were analyzed for those not exposed to CI therapy. The expression of PD-1 in tumor-infiltrating mononuclear cells (TIMC) and PD-L1 in tumor cells was detected in 9.4% and 12.3%, respectively (Immune reactive score (IRS) > 0). Furthermore, PD-L1 expression in TIMC (IRS > 0) and CTLA-4 expression in TIMC (>1% positive cells) was detected in 4.8% and 6.3%. PD-1 expression and CTLA-4 expression were significantly associated with a worse OS and CSS in log rank survival analysis and univariate Cox regression analysis. CTLA-4 expression is a prognostic marker that is independently associated with a worse outcome in multivariate Cox regression analysis in the whole cohort (OS: p = 0.013; CSS: p = 0.048) as well as in a non-metastatic subgroup analysis (OS: p = 0.028; CSS: p = 0.022). Patients with combined CTLA-4 expression and PD-1-expression are at highest risk in OS and CSS. In RCC patients, PD-1 expression in TIMC and CTLA-4 expression in TIMC are associated with a worse OS and CSS. The combination of PD-1 expression in TIMC and CTLA-4 expression in TIMC might identify high risk patients. This is, to our knowledge, the first description of CTLA-4 expression to be a prognostic marker in RCC.

Genetic variants in a long noncoding RNA related to Sunitinib Resistance predict risk and survival of patients with renal cell carcinoma

Objective

LncARSR (lncRNA Activated in RCC with Sunitinib Resistance, ENST00000424980) is a newly identified lncRNA to promote the sunitinib resistance of renal cell carcinoma (RCC), which may contribute to tumorigenesis and progression. This study aimed to explore the association of lncARSR tagSNPs with the risk and prognosis of RCC.

Methods

In this study, a 2‐stage case‐control study was performed to evaluate the association between 2 tagging SNPs (rs1417080 and rs7859384) and RCC susceptibility. Odds ratios (ORs) and 95% confidence intervals (CIs) were obtained by unconditional logistic regression analyses. Different survival time was estimated by the Kaplan‐Meier method and compared by the Log‐rank test. Hazard ratios (HRs) and their 95% CIs were calculated to determine predictive factors by Cox proportion hazards model.

Results

When combing discovery and validation sets together, rs7859384 was determined to be significantly associated with the decreased RCC risk with all P < 0.05 in 4 models (co‐dominant model, additive model, dominant model and recessive model). stratified analyses showed prominent risk effect of SNP rs7859384 GA/GG genotypes was found in clinical subgroups of stage I and stage II (P = 0.009, OR = 0.77, 95% CI = 0.64‐0.94) and individuals with clear cell RCC (P = 0.014, OR = 0.79, 95% CI = 0.65‐0.95). A protective effect of SNP rs7859384 GA/GG genotypes was observed among individuals with BMI > 24 (P = 0.025, OR = 0.74, 95% CI = 0.56‐0.96), without hypertension (P = 0.037, OR = 0.79, 95% CI = 0.63‐0.99), without family history of cancer (P = 0.048, OR = 0.83, 95% CI = 0.68‐1.00). Survival analyses revealed individuals with GA/GG genotypes had higher survival rate compared with the corresponding AA wild genotypes in the dominant model (log‐rank P = 0.005, adjusted HR = 0.34, 95% CI = 0.16‐0.73).

Conclusion

This study suggests that rs7859384 of lncARSR was associated with RCC susceptibility and may act as a prognostic biomarker for patients with RCC.