SNP-SNP Interaction in Genes Encoding PD-1/PD-L1 Axis as a Potential Risk Factor for Clear Cell Renal Cell Carcinoma. Cancers (Basel). 2020;12. [PMID: 33255938 PMCID: PMC7760680 DOI: 10.3390/cancers12123521]

Novel progressive deep learning algorithm for uncovering multiple single nucleotide polymorphism interactions to predict paclitaxel clearance in patients with nonsmall cell lung cancer

Background

The rate at which the anticancer drug paclitaxel is cleared from the body markedly impacts its dosage and chemotherapy effectiveness. Importantly, paclitaxel clearance varies among individuals, primarily because of genetic polymorphisms. This metabolic variability arises from a nonlinear process that is influenced by multiple single nucleotide polymorphisms (SNPs). Conventional bioinformatics methods struggle to accurately analyze this complex process and, currently, there is no established efficient algorithm for investigating SNP interactions.

Methods

We developed a novel machine-learning approach called GEP-CSIs data mining algorithm. This algorithm, an advanced version of GEP, uses linear algebra computations to handle discrete variables. The GEP-CSI algorithm calculates a fitness function score based on paclitaxel clearance data and genetic polymorphisms in patients with nonsmall cell lung cancer. The data were divided into a primary set and a validation set for the analysis.

Results

We identified and validated 1184 three-SNP combinations that had the highest fitness function values. Notably, SERPINA1, ATF3 and EGF were found to indirectly influence paclitaxel clearance by coordinating the activity of genes previously reported to be significant in paclitaxel clearance. Particularly intriguing was the discovery of a combination of three SNPs in genes FLT1, EGF and MUC16. These SNPs-related proteins were confirmed to interact with each other in the protein-protein interaction network, which formed the basis for further exploration of their functional roles and mechanisms.

Conclusion

We successfully developed an effective deep-learning algorithm tailored for the nuanced mining of SNP interactions, leveraging data on paclitaxel clearance and individual genetic polymorphisms.

Effect of HVEM/CD160 Variations on the Clear Cell Renal Carcinoma Risk and Overall Survival

Renal cell carcinoma (RCC) accounts for approximately 90-95% of all kidney cancers in adults, with clear cell RCC (ccRCC) being the most frequently identified subtype. RCC is known for its responsiveness to immunotherapy, making it an area of significant research interest. Immune checkpoint (IC) molecules, which regulate immune surveillance, are established therapeutic targets in RCC. The aim of this study was to analyze the influence of HVEM and CD160 gene polymorphisms on ccRCC susceptibility and patient overall survival (OS) over a ten-year period of observation. We genotyped three HVEM single nucleotide polymorphisms (SNPs): rs1886730, rs2234167, and rs8725, as well as two CD160 SNPs: rs744877 and rs2231375, in 238 ccRCC patients and 521 controls. Our findings indicated that heterozygosity within rs2231375 and/or rs2234167 increases ccRCC risk. Furthermore, in women, heterozygosity within HVEM SNPs rs8725 and rs1886730 is also associated with an increased ccRCC risk. The presence of a minor allele for rs1886730, rs2234167, rs8725, and rs2231375 was also correlated with certain clinical features of ccRCC. Moreover, rs1886730 was found to be associated with OS. In conclusion, our study highlights an association between HVEM and CD160 polymorphisms and the risk of developing ccRCC as well as OS.

Regulatory mechanisms of PD-1/PD-L1 in cancers

Immune evasion contributes to cancer growth and progression. Cancer cells have the ability to activate different immune checkpoint pathways that harbor immunosuppressive functions. The programmed death protein 1 (PD-1) and programmed cell death ligands (PD-Ls) are considered to be the major immune checkpoint molecules. The interaction of PD-1 and PD-L1 negatively regulates adaptive immune response mainly by inhibiting the activity of effector T cells while enhancing the function of immunosuppressive regulatory T cells (Tregs), largely contributing to the maintenance of immune homeostasis that prevents dysregulated immunity and harmful immune responses. However, cancer cells exploit the PD-1/PD-L1 axis to cause immune escape in cancer development and progression. Blockade of PD-1/PD-L1 by neutralizing antibodies restores T cells activity and enhances anti-tumor immunity, achieving remarkable success in cancer therapy. Therefore, the regulatory mechanisms of PD-1/PD-L1 in cancers have attracted an increasing attention. This article aims to provide a comprehensive review of the roles of the PD-1/PD-L1 signaling in human autoimmune diseases and cancers. We summarize all aspects of regulatory mechanisms underlying the expression and activity of PD-1 and PD-L1 in cancers, including genetic, epigenetic, post-transcriptional and post-translational regulatory mechanisms. In addition, we further summarize the progress in clinical research on the antitumor effects of targeting PD-1/PD-L1 antibodies alone and in combination with other therapeutic approaches, providing new strategies for finding new tumor markers and developing combined therapeutic approaches.

Associations of PD-1 and PD-L1 gene polymorphisms with cancer risk: a meta-analysis based on 50 studies

Programmed death-1 and its ligand-1 (PD-1/PD-L1), immune checkpoints proteins, play a crucial role in anti-tumor responses. A large number of studies have evaluated the relationships of PD-1/PD-L1 polymorphisms with risk of cancer, but evidence for the associations remains inconsistent. Therefore, we performed a meta-analysis to examine the associations between PD-1/PD-L1 single nucleotide polymorphisms (SNPs) and cancer predisposition. Results showed that PD-1.3 and PD-L1 rs17718883 were significantly correlated with overall cancer risk. PD-1.5 was prominently linked with cervical cancer (CC), non-small cell lung cancer (NSCLC), TC (thyroid cancer), brain tumor, AML (acute myelocytic leukemia) and UCC (urothelial cell carcinoma) risk, PD-1.9 with breast cancer (BC), AML, esophageal cancer (EC) and ovarian cancer (OC) risk, and PD-1.3 with colorectal cancer (CRC) and BCC (basal cell carcinoma) risk. PD-1.1 polymorphism slightly elevated BC and OC susceptibility, whereas the rs4143815 variant notably decreased the risk of gastric cancer (GC), hepatocellular carcinoma (HCC) and OC, but increased the risk of BC. PD-1.6 was closely linked with AML risk, PD-L1 rs2890658 with NSCLC, HCC and BC risk, rs17718883 with HCC and GC risk, rs10815225 with GC risk, and rs2297136 with NSCLC and HCC risk. Interestingly, the rs7421861, rs10815225, and rs10815225 markedly reduced cancer susceptibility among Asians. The rs7421861 polymrophism decreased cancer risk among Caucasians, rather than the rs10815225 elevated cancer risk. Our results supported that PD-1 and PD-L1 SNPs were dramatically correlated with cancer risk.

SEL1L3 as a link molecular between renal cell carcinoma and atherosclerosis based on bioinformatics analysis and experimental verification

BACKGROUND

Renal cancer, the most common type of kidney cancer, develops in the renal tubular epithelium. Atherosclerosis of the aorta is the primary cause of atherosclerosis. However, the underlying mechanisms remain unclear.

METHODS

The renal clear cell carcinoma RNA sequence profile was obtained from The Cancer Genome Atlas (TCGA) database, and the atherosclerosis datasets GSE28829 and GSE43292 based on GPL570 and GPL6244 was obtained from the Gene Expression Omnibus (GEO) database. The difference and hub genes were identified by the Limma protein-protein interaction (PPI) network in R software. Functional enrichment, survival, and immunoinfiltration analyses were performed. The role of SEL1L3 in the ErbB/PI3K/mTOR signaling pathway, apoptosis, invasion, cell cycle, and inflammation was analyzed using western blotting.

RESULTS

764 DEGs were identified from TCGA Kidney Renal Clear Cell Carcinoma (KIRC) dataset. A total of 344 and 117 DEGs were screened from the GSE14762 and GSE53757 datasets, respectively. Functional enrichment analysis results primarily indicated enrichment in the transporter complex, DNA-binding transcription activator activity, morphogenesis of the embryonic epithelium, stem cell proliferation, adrenal overactivity and so on. Fifteen common DEGs overlapped among the three datasets. The PPI network revealed that SEL1L3 was the core gene. Survival analysis showed that lower SEL1L3 expression levels led to a worse prognosis. Immune cell infiltration analysis showed that SEL1L3 expression was significantly correlated with antibody-drug conjugates (aDC), B cells, eosinophils, interstitial dendritic cells (iDC), macrophages, and more.

CONCLUSIONS

SEL1L3 plays an important role in renal clear cell carcinoma and atherosclerosis and may be a potential link between them.

The Variations' in Genes Encoding TIM-3 and Its Ligand, Galectin-9, Influence on ccRCC Risk and Prognosis

Renal cell cancer is the most common type of kidney cancer in adults, and clear cell renal cell carcinoma (ccRCC) is the most diagnosed type. T cell immunoglobulin and mucin-domain-containing-3 (TIM-3) belongs to immunological checkpoints that are key regulators of the immune response. One of the known TIM-3 ligands is galectin-9 (LGALS9). A limited number of studies have shown an association between TIM-3 polymorphisms and cancer risk in the Asian population; however, there is no study on the role of LGALS9 polymorphisms in cancer. The present study aimed to analyze the influence of TIM-3 and LGALS9 polymorphisms on susceptibility to ccRCC and patient overall survival (OS), with over ten years of observations. Using TaqMan probes, ARMS-PCR, and RFPL-PCR, we genotyped two TIM-3 single-nucleotide polymorphisms (SNPs): rs1036199 and rs10057302, and four LGALS9 SNPs: rs361497, rs3751093, rs4239242, and rs4794976. We found that the presence of the rs10057302 A allele (AC + AA genotypes) as well as the rs4794976 T allele (GT + TT genotypes) decreased susceptibility to ccRCC by two-fold compared to corresponding homozygotes. A subgroup analysis showed the association of some SNPs with clinical features. Moreover, TIM-3 rs1036199 significantly influenced OS. Our results indicate that variations within TIM-3 and LGALS9 genes are associated with ccRCC risk and OS.

Severe Immune-Related Adverse Events in Patients Treated with Nivolumab for Metastatic Renal Cell Carcinoma Are Associated with PDCD1 Polymorphism

Single nucleotide polymorphisms (SNPs) reportedly influence the effect of nivolumab in metastatic renal cell carcinoma (mRCC). This study aimed to evaluate the relationship between the clinical outcomes of patients with mRCC and SNPs in programmed cell death protein 1 (PD-1) protein-coding gene (PDCD1) and explore any potential correlation with patient prognosis and incidence of immune-related adverse events (irAEs). In total, 106 patients with mRCC, who were treated with nivolumab alone (n = 59) or nivolumab and ipilimumab (n = 47), were enrolled in the study. Three SNPs in the PDCD1 gene, namely PD-1.3, PD-1.5, and PD-1.6, were assessed. Patients harboring the PD-1.6 G allele experienced more severe (odds ratio, 3.390; 95% confidence interval 1.517–7.756; p = 0.003) and multiple (OR, 2.778; 95% CI, 1.020–6.993 p = 0.031) irAEs than those harboring the AA genotype. Thus, the existence of the PDCD1 PD-1.6 polymorphism (G allele) was associated with the occurrence of severe and multiple irAEs in patients with mRCC. Further evaluation of PDCD1 polymorphisms might help identify patients experiencing irAE by nivolumab treatment.

Association of PD-1 and PDL-1 gene polymorphisms with colorectal cancer risk and prognosis

BACKGROUND

Programmed Cell Death-1 (PD-1) together with Programmed Death Ligand 1 (PDL-1) have crucial roles in anti-tumor immune response, cancer susceptibility and prognosis. Since PD-1 and PDL-1 have been considered as important genetic risk factors in cancer development and their functions can be affected by polymorphic sites, we investigated the effects of PD-1 rs2227981, rs2227982, rs36084323 and PDL-1 rs2282055, rs822336 gene polymorphisms on colorectal cancer (CRC) risk and prognosis in Turkish subjects.

METHODS AND RESULTS

Our study group consisted of 5-FU or Capacitabine prescribed CRC diagnosed patients and healthy controls. Genotype analyses of PD1 and PDL-1 polymorphisms were performed with Agena MassARRAY platform. rs36084323 CT genotype frequency was found to be higher in controls compared to cases (p < 0.001). rs36084323 CT genotype was highly associated with reduced CRC risk compared to CC genotype (OR 0.068, 95% CI 0.022-0.211, p < 0.001). In adjusted analysis, rs2282055 GG genotype was found to be associated with reduced CRC risk (OR 0.271, 95% CI 0.078-0.940, p = 0.040). rs2282055 TT genotype was found to be related to longer progression-free (Bonferroni corrected Log rank p = 0.013) and overall survival (Bonferroni corrected Log rank p = 0.009) to that of GG genotypes. Patients with rs822336 GC+CC genotypes showed longer overall survival times compared to GG (Log rank p = 0.044).

CONCLUSIONS

According to our results, PD-1 rs822336 G > C polymorphism might be useful in predicting CRC prognosis. PDL-1 rs2282055 T > G polymorphism might be useful in predicting both CRC risk and prognosis. Further studies should be conducted in larger and different populations to clear the roles of PD-1 and PDL-1 polymorphisms in CRC risk and prognosis.

Immunotherapy against programmed death-1/programmed death ligand 1 in hepatocellular carcinoma: Importance of molecular variations, cellular heterogeneity, and cancer stem cells

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy related to diverse etiological factors. Different oncogenic mechanisms and genetic variations lead to multiple HCC molecular classifications. Recently, an immune-based strategy using immune checkpoint inhibitors (ICIs) was presented in HCC therapy, especially with ICIs against the programmed death-1 (PD-1) and its ligand PD-L1. However, despite the success of anti-PD-1/PD-L1 in other cancers, a substantial proportion of HCC patients fail to respond. In this review, we gather current information on biomarkers of anti-PD-1/PD-L1 treatment and the contribution of HCC heterogeneity and hepatic cancer stem cells (CSCs). Genetic variations of PD-1 and PD-L1 are associated with chronic liver disease and progression to cancer. PD-L1 expression in tumoral tissues is differentially expressed in CSCs, particularly in those with a close association with the tumor microenvironment. This information will be beneficial for the selection of patients and the management of the ICIs against PD-1/PD-L1.