Lung cancer is the greatest contributor to tumor-derived death. Traditionally, platinum-based chemotherapies are the primary treatment for most patients. However, intrinsic drug resistance and side effects limit the efficacy of platinum-based chemotherapies. Previous studies demonstrated that Pol ζ can modulate cellular sensitivity to chemotherapy. The primary aim of this study was to investigate the potential role of the polymorphism of Pol ζ in platinum-based chemotherapy tolerance and side effects. A total of 663 patients who were newly histologically diagnosed with advanced NSCLC were enrolled. Their treatment response was classified into four categories: complete response (CR), partial response (PR), stable disease (SD) and progressive disease (PD). The gastrointestinal and hematological toxicity incidence was assessed twice a week during the entire first line of treatment. Thirteen SNPs of REV3 and REV7 were genotyped. The associations between SNPs and the treatment response or toxicity were analyzed with a logistic regression model. We discovered that five SNPs were correlated with the treatment response. Specifically, rs240969 was significantly associated with the treatment response, after a Bonferroni correction, in smokers and a combined cohort (P=0.048 and P=0.0082, respectively) as well as with rs3218573 in smokers (P=0.036). In addition, we discovered that the incidence of grade 3 or 4 gastrointestinal toxicity was significantly higher in patients carrying a G/G genotype of rs240966 or an A allele of rs456865. We also identified that five SNPs, namely rs240966, rs4945880, rs465646, rs2233025 and rs2336030, that were correlated with an increased risk of grade 3 or grade 4 hematologic toxicity. The REV3 and REV7 polymorphisms are in a catalytic subunit and an accessory subunit of Pol ζ, respectively, and participate in platinum-chemotherapy tolerance and side effects. Key words: REV3, REV7, Pol ζ, platinum-based chemotherapies, translesion synthesis, toxicityLung cancer is the highest contributor to cancer-related deaths, and non-small cell lung cancer (NSCLC) accounts for nearly 80% of all lung cancer deaths [1]. The incidence rate of lung cancer is rapidly rising due to tobacco use, air pollution, and other cancer-causing factors [2]. Although targeted therapy is very efficient and tremendously improves the progress-free survival (PFS) and overall survival (OS) of lung cancer patients [3][4][5], however,over 70% of patients lack the positive biomarkers that are considered necessary for platinum-based chemotherapies as the traditional front-line treatment [6,7]. The efficacy of platinum-based chemotherapies is severely limited by intrinsic drug resistance. In addition, while platinum can kill uncontrollably dividing tumor cells by coupling to DNA and terminating the replication of DNA, normal cells will also be inevitably damaged [8].Previous studies have shown that DNA repair systems play an essential role in platinum-based chemotherapy tolerance [8][9][10][11]. DNA inter-or intra-crosslinking cause...

Background Zeste White 10 interactor (ZW10 interactor, ZWINT) is a centromeric complex required for a mitotic spindle checkpoint. According to previous studies, it was overexpressed in people with recurrent tumors. However, the expression of ZWINT in breast cancer has not been thoroughly studied. In addition, the correlations of ZWINT to prognosis in breast cancer remain unclear. Methods In this study, the expression of ZWINT in different types of tumors was analyzed based on the Oncomine database, and the effect of ZWINT expression on clinical prognosis was evaluated by Kaplan-Meier plotter. Results In breast cancer, lung cancer, sarcoma, ovarian cancer, bladder cancer, liver cancer and cervical cancer, the expression of ZWINT was higher than that in normal tissues, but in gastric cancer, prostate cancer, myeloma, renal cancer and pancreatic cancer, the expression of ZWINT was lower. In addition, a meta-analysis of 22 cancer database studies found that the ZWINT gene was over-expressed in breast cancer tissues compared with normal tissues (P=4.05×10 −6 ). Through the survival analysis of Kaplan-Meier plotter, it is found that the high expression of ZWINT is related to the worse overall survival (OS) [hazard ratio (HR) =1.73, 95% confidence interval (CI): 1.39–2.51, P=5.4×10 −7 ], RFS (HR =1.68, 95% CI: 1.51–1.88, P<1×10 −16 ) and distant metastasis-free survival (DMFS) (HR =1.55, 95% CI: 1.28–1.89, P=7.9×10 −6 ) in all BC patients. Conclusions Our results strongly suggest that over expression of ZWINT is closely related to poor prognosis of breast cancer. ZWINT may be a prognostic biomarker for the treatment of BC.

Background: We aimed to identify the key differentially expressed genes (DEGs) associated with poor prognosis in gastric cancer (GC) and to elucidate the underlying molecular mechanisms in order to provide a therapeutic target for this disease.Methods: The DEGs common in two datasets, GSE54129 and GSE79973, were screened. GO and KEGG enrichment analyses were then performed for these DEGs using DAVID's tool. STRING and the Cytoscope software were also used to analyze the protein-protein interaction (PPI) networks of the DEGs common between the two datasets.Results: A total of 164 common DEGs were identified from GSE79973 and GSE54129 datasets, 42 were up-regulated and 122 were down-regulated in GC. KEGG analysis demonstrated that up-regulated DEGs were mainly enriched for focal adhesion, ECM-receptor interaction, PI3K-Akt signaling pathway, protein digestion and absorption, and vascular smooth muscle contraction, while down-regulated DEGs were enriched for chemical carcinogenesis, metabolism of xenobiotics by cytochrome P450, drug metabolismcytochrome P450, and retinol metabolism (P<0.05). Obtained PPI network for the 164 DEGs via Cytotype software, using MCODE app of Cytotype software we identified 13 hub genes. Twelve of these genes were found to be associated with poor prognosis in GC by survival analysis. Post validation by the GEPIA, Oncomine, and Human Protein Atlas databases, eight genes (COL4A1,

Purpose. Breast cancer (BC) has a poor prognosis when brain metastases (BM) occur, and the treatment effect is limited. In this study, we aim to identify representative candidate biomarkers for clinical prognosis of patients with BM and explore the mechanisms underlying the progression of BC.Methods. Herein, we examined the Microarray datasets (GSE125989) obtained from the Gene Expression Omnibus database to find the target genes in BC patients with BM. We employed the GEO2R tool to filter the differentially expressed genes (DEGs) that participate in primary BC and BC with BM. Subsequently, using the DAVID tool, we conducted an enrichment analysis with the screened DEGs based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) functional annotation. The STRING database was employed to analyze the protein-protein interactions of the DEGs and visualized using Cytoscape software. Lastly, the Kaplan-Meier plotter database was employed to determine the prognostic potential of hub genes in BC.Results. We screened out 311 upregulated DEGs and 104 downregulated DEGs. The enrichment analyses revealed that all the DEGs were` enriched in the biological process of extracellular matrix organization, cell adhesion, proteolysis, collagen catabolic process and immune response. The significant enrichment pathways were focal adhesion, protein absorption and digestion, ECM-receptor interaction, PI3K-Akt signalling pathway, and Pathways in cancer. The top ten hub nodes screened out included FN1, VEGFA, COL1A1, MMP2, COL3A1, COL1A2, POSTN, DCN, BGN and LOX. The Kaplan-Meier plotter results showed that the three hub genes (FN1, VEGFA and DCN) are candidate biomarkers for clinical prognosis of patients with BM.Conclusion. we identified seven genes related to poor prognosis in BCBM. FN1, VEGFA and DCN can be considered as potential prognostic markers for BCBM. Meantime, COL1A1, POSTN, BGN and LOX may be linked to the distant transformation of BC.

Purpose. Breast cancer (BC) has a poor prognosis when brain metastases (BM) occur, and the treatment effect is limited. In this study, we aim to identify representative candidate biomarkers for clinical prognosis of patients with BM and explore the mechanisms underlying the progression of BC.Methods. Herein, we examined the Microarray datasets (GSE125989) obtained from the Gene Expression Omnibus database to find the target genes in BC patients with BM. We employed the GEO2R tool to filter the differentially expressed genes (DEGs) that participate in primary BC and BC with BM. Subsequently, using the DAVID tool, we conducted an enrichment analysis with the screened DEGs based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) functional annotation. The STRING database was employed to analyze the protein-protein interactions of the DEGs and visualized using Cytoscape software. Lastly, the Kaplan-Meier plotter database was employed to determine the prognostic potential of hub genes in BC.Results. We screened out 311 upregulated DEGs and 104 downregulated DEGs. The enrichment analyses revealed that all the DEGs were` enriched in the biological process of extracellular matrix organization, cell adhesion, proteolysis, collagen catabolic process and immune response. The significant enrichment pathways were focal adhesion, protein absorption and digestion, ECM-receptor interaction, PI3K-Akt signalling pathway, and Pathways in cancer. The top ten hub nodes screened out included FN1, VEGFA, COL1A1, MMP2, COL3A1, COL1A2, POSTN, DCN, BGN and LOX. The Kaplan-Meier plotter results showed that the three hub genes (FN1, VEGFA and DCN) are candidate biomarkers for clinical prognosis of patients with BM.Conclusion. we identified seven genes related to poor prognosis in BCBM. FN1, VEGFA and DCN can be considered as potential prognostic markers for BCBM. Meantime, COL1A1, POSTN, BGN and LOX may be linked to the distant transformation of BC.