Breast cancer is the most commonly diagnosed malignancy in women; thus, more cancer prevention research is urgently needed. The aim of this study was to predict potential therapeutic agents for breast cancer and determine their molecular mechanisms using integrated bioinformatics. Summary data from a large genome-wide association study of breast cancer was derived from the UK Biobank. The gene expression profile of breast cancer was from the Oncomine database. We performed a network-wide association study and gene set enrichment analysis to identify the significant genes in breast cancer. Then, we performed Gene Ontology analysis using the STRING database and conducted Kyoto Encyclopedia of Genes and Genomes pathway analysis using Cytoscape software. We verified our results using the Gene Expression Profile Interactive Analysis, PROgeneV2, and Human Protein Atlas databases. Connectivity map analysis was used to identify small-molecule compounds that are potential therapeutic agents for breast cancer. We identified 10 significant genes in breast cancer based on the gene expression profile and genome-wide association study. A total of 65 small-molecule compounds were found to be potential therapeutic agents for breast cancer.

The significant changes of CDCA expression in transcription level between different types of HNSCC and normal tissues (Oncomine database).

BackgroundMicrotubule-associated proteins (MAPs) have been considered to play significant roles in the tumor evolution of non-small cell lung cancer (NSCLC). Nevertheless, mRNA transcription levels and prognostic value of distinct MAPs in patients with NSCLC remain to be clarified.MethodsIn this study, the Oncomine database, Gene Expression Profiling Interactive Analysis (GEPIA) database, and Human Protein Atlas were utilized to analyze the relationship between mRNA/protein expression of different MAPs and clinical characteristics in NSCLC patients, including tumor type and pathological stage. The correlation between the transcription level of MAPs and overall survival (OS) of NSCLC patients was analyzed by Kaplan–Meier plotter. Besides, 50 frequently altered neighbor genes of the MAPs were screened out, and a network has been constructed via the cBioPortal and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) dataset. Meanwhile, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis on the expression data of MAPs and their 50 frequently altered neighbor genes in NSCLC tissues. Furthermore, The Cancer Immunome Atlas (TCIA) was utilized to analyze the relationship between MAP expression and the response to immunotherapy. Finally, we used reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to verify the expression of MAPs in 20 patients with NSCLC.ResultsThe present study discovered that the mRNA transcription levels of MAP7/7D2 were enriched in NSCLC tissues, while those of the MAP2/4/6/7D3 were lower in NSCLC specimens than those in control specimens. The mRNA transcription level of MAP6 was significantly associated with the advanced stage of NSCLC. Besides, survival analysis indicated that higher mRNA expressions of MAP2/4/6/7/7D3 were correlated considerably with favorable OS of NSCLC patients, whereas increased mRNA expression levels of MAP1A/1S were associated with poor OS. Moreover, the expression of MAP1A/1B/1S/4/6/7D1/7D3 was significantly correlated with immunophenoscore (IPS) in NSCLC patients.ConclusionsOur analysis indicated that MAP1A/1S could serve as potential personalized therapeutic targets for patients with NSCLC, and the enriched MAP2/4/6/7/7D3 expression could serve as a biomarker for favorable prognosis in NSCLC. Besides, the expression of MAP1A/1B/1S/4/6/7D1/7D3 was closely related to the response to immunotherapy. Taken together, MAP expression has potential application value in the clinical treatment and prognosis assessment of NSCLC patients, and further verifiable experiments can be conducted to verify our results.

Prostate cancer (PCa) is one of the leading causes of deaths in America. The major cause of mortality can be attributed to metastasis. Cancer metastasis involves sequential and interrelated events. miRNAs and epithelial-mesenchymal transition (EMT) are implicated in this process. miR-195 is downregulated in many human cancers. However, the roles of miR-195 in PCa metastasis and EMT remain unclear. In this study, data from Memorial Sloan Kettering Cancer Center (MSKCC) prostate cancer database were re-analysed to detect miR-195 expression and its roles in PCa. miR-195 was then overexpressed in castration-resistant PCa cell lines, DU-145 and PC-3. The role of miR-195 in migration and invasion in vitro was also investigated, and common markers in EMT were evaluated through Western blot analysis. A luciferase reporter assay was conducted to confirm the target gene of miR-195; were validated in PCa cells. In MSKCC data re-analyses, miR-195 was poorly expressed in metastatic PCa; miR-195 could be used to diagnose metastatic PCa by measuring the corresponding expression. Area under the receiver operating characteristic curve (AUC-ROC) was 0.705 (P = 0.017). Low miR-195 expression was characterised with a shorter relapse-free survival (RFS) time. miR-195 overexpression suppressed cell migration, invasion and EMT. Fibroblast growth factor 2 (FGF2) was confirmed as a direct target of miR-195. FGF2 knockdown also suppressed migration, invasion and EMT; by contrast, increased FGF2 partially reversed the suppressive effect of miR-195. And data from ONCOMINE prostate cancer database showed that PCa patients with high FGF2 expression showed shorter RFS time (P = 0.046). Overall, this study demonstrated that miR-195 suppressed PCa cell metastasis by downregulating FGF2. miR-195 restoration may be considered as a new therapeutic method to treat metastatic PCa.

Protein-Protein, Genetic, and Chemical Interactions for Ramadoss S (2011):Transducin β-like protein 1 recruits nuclear factor κB to the target gene promoter for transcriptional activation. curated by BioGRID (https://thebiogrid.org); ABSTRACT: Nuclear factor κB (NF-κB) signaling controls a wide range of cellular functions such as tumor progression and invasion by inducing gene expression. Upon stimulation, NF-κB is translocated to the nucleus and binds to its target gene promoters to activate transcription by recruiting transcription coactivators. Although significant progress has been made in understanding NF-κB-mediated transactivation, little is known about how NF-κB is recruited to its target gene promoters. Here, we report that transducin β-like protein 1 (TBL1) controls the expression of NF-κB target genes by directly binding with NF-κB and facilitating its recruitment to target gene promoters. Tumor necrosis factor alpha stimulation triggered the formation of an NF-κB and TBL1 complex and subsequent target gene promoter binding. Knockdown of TBL1 impaired the recruitment of NF-κB to its target gene promoters. Interestingly, analysis of the Oncomine database revealed that TBL1 mRNA levels were significantly higher in invasive breast cancer tissues than in breast adenocarcinoma tissue. Consistently, TBL1 knockdown significantly reduced the invasive potential of breast cancer cells by inhibiting NF-κB. Our results reveal a new mechanism for the regulation of NF-κB activation, with important implications for the development of novel strategies for cancer therapy by targeting NF-κB.

Protein-Protein, Genetic, and Chemical Interactions for Jaeaeskelaeinen T (2011):Histone H2B ubiquitin ligases RNF20 and RNF40 in androgen signaling and prostate cancer cell growth. curated by BioGRID (https://thebiogrid.org); ABSTRACT: Since data-mining from the Oncomine database revealed that expression of histone H2B K120 monoubiquitin (H2Bub1) ligase RNF20 is decreased in metastatic prostate cancer, we elucidated the effect of RNF20 and its homolog RNF40 on androgen receptor (AR)-dependent transcription and prostate cancer cell growth. Both RNF20 and RNF40 were able to functionally and physically interact with the AR and modulate its transcriptional activity in intact cells. Chromatin immunoprecipitation analyses showed that the androgen induction of FKBP51 and PSA in LNCaP prostate cancer cells is accompanied with a dynamic increase in the H2Bub1 within the transcribed regions of these loci. Interestingly, depletion of RNF20 or RNF40 strongly retarded the growth of LNCaP cells, which was however unlikely to be due to altered androgen signaling, but due to decreased expression of several cell cycle promoters. Collectively, our results suggest that RNF20 and RNF40, either via ubiquitylation of H2B or other targets, are coupled to the proliferation of prostate cancer cells.

Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal cancer, with a poor prognosis. Our study aimed to identify a biomarker that is significantly associated with ccRCC prognosis and novel immunotherapeutic targets, as well as some novel molecular drugs for ccRCC. Based on the overlap of The Cancer Genome Atlas (TCGA)-Kidney Renal Clear Cell Carcinoma (KIRC) data and the ImmPort database, we obtained 1,292 immune-related genes (IRGs) and constructed a weighed co-expression network based on the IRGs. A total of 39 hub genes were screened out in three modules. CTLA4, which had the highest connectivity degree among the screened genes in a protein–protein interaction network (degree = 24), was selected. Internal validation based on the GEPIA database revealed that patients with a higher expression of CTLA4 had a significantly shorter overall survival time and disease-free survival time. Expression of CTLA4 was also closely correlated with local recurrence, pathologic stage, and immune infiltration level. External validation based on the Oncomine database and merged microarray-acquired dataset validated the mRNA expression level of hub genes. Gene-set enrichment analysis revealed that six KEGG signaling pathways, which were significantly associated with CTLA4, were enriched on immune-related pathways. Further analysis according to the TIMER database demonstrated that CTLA4 expression was positively related to dendritic cells (cor = 0.446, P = 1.32E-23) and negatively associated with tumor purity (cor = −0.267, P = 5.51E-09). Finally, we screened out 293 differentially expressed genes by integrating six datasets from the GEO database. The Connectivity Map (CMap) analysis revealed the strong potential of three small molecule drugs (monensin, quercetin, and fenbufen) for ccRCC treatment. In conclusion, CTLA4 was identified and validated in prognosis of ccRCC. CTLA4 may be a new prognostic biomarker and immunotherapeutic target for ccRCC. Monensin, quercetin, and fenbufen may be novel choices for ccRCC treatment.

Protein-Protein, Genetic, and Chemical Interactions for Ding K (2019):RNA splicing factor USP39 promotes glioma progression by inducing TAZ mRNA maturation. curated by BioGRID (https://thebiogrid.org); ABSTRACT: Increasing evidence demonstrates that ubiquitin specific protease 39 (USP39) plays an oncogenic role in various human tumors. Here, using expression analysis of the publicly available Oncomine database, clinical glioma patient samples, and glioma cells, we found that USP39 was overexpressed in human gliomas. Knockdown of USP39 in glioma cells demonstrated that the protein promoted cell growth, invasion and migration in vitro and in a tumor model in nude mice. To identify mediators of USP39 growth-promoting properties, we used luciferase reporter constructs under transcriptional control of various promoters specific to seven canonical cancer-associated pathways. Luciferase activity from a synthetic TEAD-dependent YAP/TAZ-responsive reporter, as a direct readout of the Hippo signaling pathway, was decreased by 92% in cells with USP39 knockdown, whereas the luciferase activities from the other six cancer pathways, including MAPK/ERK, MAPK/JNK, NF?B, Notch, TGF?, and Wnt, remained unchanged. TAZ protein expression however was decreased independent of canonical Hippo signaling. Immunohistochemistry revealed a positive correlation between USP39 and TAZ proteins in orthotopic xenografts derived from modified glioma cells expressing USP39 shRNAs and primary human glioma samples (p?

TGFβR2 expression in normal lung and NSCLC tissues.

Background: Gastric cancer (GC) is one of the most common malignancies worldwide, exhibiting a high morbidity, and mortality. As the various treatment methods for gastric cancer are limited by disadvantages, many efforts to improve the efficacy of these treatments are being taken. Metabolic recombination is an important characteristic of cancer and has gradually caused a recent upsurge in research. However, systematic analysis of the interaction between glycolysis and GC patient prognosis and its potential associations with immune infiltration is lacking but urgently needed.Methods: We obtained the gene expression data and clinical materials of GC derived from The Cancer Genome Atlas (TCGA) dataset. Univariate and multivariate Cox proportional regression analyses were performed to select the optimal prognosis-related genes for subsequent modeling. We then validated our data in the GEO database and further verified the gene expression using the Oncomine database and PCR experiments. Besides, Gene set variation analysis (GSVA) analysis was employed to further explore the differences in activation status of biological pathways between the high and low risk groups. Furthermore, a nomogram was adopted to predict the individualized survival rate of GC patients. Finally, a violin plot and a TIMMER analysis were performed to analyse the characteristics of immune infiltration in the microenvironment.Results: A seven-gene signature, including STC1, CLDN9, EFNA3, ZBTB7A, NT5E, NUP50, and CXCR4, was established. Based on this seven-gene signature, the patients in the training set and testing sets could be divided into high-risk and low-risk groups. In addition, a nomogram based on risk and age showed good calibration and moderate discrimination. The results proved that the seven-gene signature had a strong capacity to predict the GC patient prognosis. Collectively, the violin plot and TIMMER analysis demonstrated that an immunosuppressive tumor microenvironment caused by hyperglycolysis led to poor prognosis.Conclusion: Taken together, these results established a genetic signature for gastric cancer based on glycolysis, which has reference significance for the in-depth study of the metabolic mechanism of gastric cancer and the exploration of new clinical treatment strategies.

Dysregulated lipid metabolism contributes to cancer progression. Our previous study indicates that long-chain fatty acyl-Co A synthetase (ACSL) 3 is essential for lipid upregulation induced by endoplasmic reticulum stress. In this report, we aimed to identify the role of ACSL family in cancer with systematic analysis and in vitro experiment. We explored the ACSL expression using Oncomine database to determine the gene alteration during carcinogenesis and identified the association between ACSL expression and the survival of cancer patient using PrognoScan database. ACSL1 may play a potential oncogenic role in colorectal and breast cancer and play a potential tumor suppressor role in lung cancer. Co-expression analysis revealed that ACSL1 was coexpressed with MYBPH, PTPRE, PFKFB3, SOCS3 in colon cancer and with LRRFIP1, TSC22D1 in lung cancer. In accordance with PrognoScan analysis, downregulation of ACSL1 in colon and breast cancer cell line inhibited proliferation, migration, and anchorage-independent growth. In contrast, increase of oncogenic property was observed in lung cancer cell line by attenuating ACSL1. High ACSL3 expression predicted a better prognosis in ovarian cancer; in contrast, high ACSL3 predicted a worse prognosis in melanoma. ACSL3 was coexpressed with SNUPN, TRIP13, and SEMA5A in melanoma. High expression of ACSL4 predicted a worse prognosis in colorectal cancer, but predicted better prognosis in breast, brain and lung cancer. ACSL4 was coexpressed with SERPIN2, HNRNPCL1, ITIH2, PROCR, LRRFIP1. High expression of ACSL5 predicted good prognosis in breast, ovarian, and lung cancers. ACSL5 was coexpressed with TMEM140, TAPBPL, BIRC3, PTPRE, and SERPINB1. Low ACSL6 predicted a worse prognosis in acute myeloid leukemia. ACSL6 was coexpressed with SOX6 and DARC. Altogether, different members of ACSLs are implicated in diverse types of cancer development. ACSL-coexpressed molecules may be used to further investigate the role of ACSL family in individual type of cancers.

Log—rank test.Univariate analysis of overall survival based on patients stratified by clinical characteristics.

C1q is the first subcomponent of the classical pathway of the complement system and belongs to the C1q/Tumor Necrosis Factor superfamily. C1q can perform a diverse range of immune and non-immune functions in a complement-dependent as well as -independent manner. Being a pattern recognition molecule of the innate immunity, C1q can recognize a number of self, non-self and altered-self ligands and bring about effector mechanisms designed to clear pathogens via opsonisation and inflammatory response. C1q is locally synthesized by macrophages and dendritic cells, and thus, can get involved in a range of biological processes, such as angiogenesis and tissue remodeling, immune modulation, and immunologic tolerance. The notion of C1q involvement in the pathogenesis of cancer is still evolving. C1q appears to have a dual role in cancer: tumor promoting as well as tumor-protective, depending on the context of the disease. In the current study, we performed a bioinformatics analysis to investigate whether C1q can serve as a potential prognostic marker for human carcinoma. We used the Oncomine database and the survival analysis platforms Kaplan-Meier plotter. Our results showed that high levels of C1q have a favorable prognostic index in basal-like breast cancer for disease-free survival, and in HER2-positive breast cancer for overall survival, while it showed a pro-tumorigenic role of C1q in lung adenocarcinoma, and in clear cell renal cell carcinoma. This in silico study, if validated via a retrospective study, can be a step forward in establishing C1q as a new tool as a prognostic biomarker for various carcinoma.

BackgroundLung cancer is one of the most common malignant tumors and the leading causes of cancer-related deaths worldwide. As a component of the nuclear division cycle 80 complex, NUF2 is a part of the conserved protein complex related to the centromere. Although the high expression of NUF2 has been reported in many different types of human cancers, the multi-omics analysis in non-small cell lung cancer (NSCLC) of NUF2 remains to be elucidated.MethodsIn this analysis, NUF2 expression difference analysis in non-small cell lung cancer was evaluated by Oncomine, TIMER, GEO, and TCGA database. And the prognosis analysis of NUF2 based on Kaplan-Meier was performed. R language was used to analyze the differential expression genes, functional annotation and protein-protein interaction (PPI). GSEA analysis of differential expression genes was also carried out. Mechanism analysis about exploring the characteristic of NUF2, multi-omics, and correlation analysis was carried out using UALCAN, cBioportal, GEPIA, TIMER, and TISIDB, respectively.ResultsThe expression of NUF2 in NSCLC, both lung adenocarcinoma (LUAD) and squamous lung cancer (LUSC), was significantly higher than that in normal tissues. The analysis of UALCAN database samples proved that NUF2 expression was connected with stage and smoking habits. Meanwhile, the overall survival curve also validated that high expression of NUF2 has a poorer prognosis in NSCLC. GO, KEGG, GSEA, subcellular location from COMPARTMENTS indicated that NUF2 may regulate the cell cycle. Correlation analysis also showed that NUF2 was mainly positively associated with cell cycle and tumor-related genes. NUF2 altered group had a poorer prognosis than unaltered group in NSCLC. Immune infiltration analysis showed that the NUF2 expression mainly have negatively correlation with immune cells and immune subtypes in LUAD and LUSC. Furthermore, quantitative PCR was used to validate the expression difference of NUF2 in LUAD and LUSC.ConclusionOur findings elucidated that NUF2 may play an important role in cell cycle, and significantly associated with tumor-related gene in NSCLC; we consider that NUF2 may be a prognostic biomarkers in NSCLC.

BackgroundYTH N6-methyladenosine RNA binding protein 1 (YTHDF1) has been indicated proven to participate in the cross-presentation of tumor antigens in dendritic cells and the cross-priming of CD8+ T cells. However, the role of YTHDF1 in prognosis and immunology in human cancers remains largely unknown.MethodsAll original data were downloaded from TCGA and GEO databases and integrated via R 3.2.2. YTHDF1 expression was explored with the Oncomine, TIMER, GEPIA, and BioGPS databases. The effect of YTHDF1 on prognosis was analyzed via GEPIA, Kaplan-Meier plotter, and the PrognoScan database. The TISIDB database was used to determine YTHDF1 expression in different immune and molecular subtypes of human cancers. The correlations between YTHDF1 expression and immune checkpoints (ICP), tumor mutational burden (TMB), microsatellite instability (MSI), and neoantigens in human cancers were analyzed via the SangerBox database. The relationships between YTHDF1 expression and tumor-infiltrated immune cells were analyzed via the TIMER and GEPIA databases. The relationships between YTHDF1 and marker genes of tumor-infiltrated immune cells in urogenital cancers were analyzed for confirmation. The genomic alterations of YTHDF1 were investigated with the c-BioPortal database. The differential expression of YTHDF1 in urogenital cancers with different clinical characteristics was analyzed with the UALCAN database. YTHDF1 coexpression networks were studied by the LinkedOmics database.ResultsIn general, YTHDF1 expression was higher in tumors than in paired normal tissue in human cancers. YTHDF1 expression had strong relationships with prognosis, ICP, TMB, MSI, and neoantigens. YTHDF1 plays an essential role in the tumor microenvironment (TME) and participates in immune regulation. Furthermore, significant strong correlations between YTHDF1 expression and tumor immune-infiltrated cells (TILs) existed in human cancers, and marker genes of TILs were significantly related to YTHDF expression in urogenital cancers. TYHDF1 coexpression networks mostly participated in the regulation of immune response and antigen processing and presentation.ConclusionYTHDF1 may serve as a potential prognostic and immunological pan-cancer biomarker. Moreover, YTHDF1 could be a novel target for tumor immunotherapy.

Using, GPR158 as a query, we searched the Oncomine database and the applied co-expression filter with the gene rank threshold by top 10%. We selected the genes with a correlation score of ≥ 0.5 and 20 out of 28 correlated genes were found to be expressed in NE cells of various organs as indicated in the table.Co-expression analysis of GPR158 in the Oncomine Ma Breast 4 dataset.

Summary

This metadata record provides details of the data supporting the claims of the related manuscript: “RIPK1 is a negative mediator in Aquaporin 1-driven triple-negative breast carcinoma progression and metastasis”.

The related study reports the aberrant expression of Aquaporin 1 (AQP1) and receptor-interacting protein kinase 1 (RIPK1) in triple-negative breast carcinoma (TNBC) that are associated with different prognoses, then validates the interaction of AQP1 and RIPK1 and the suppressive effect of RIPK1 on AQP1-driven TNBC progression and metastasis, and finally identifies the underlying mechanism of TNBC cell death resistance that AQP1 binds to the D324 site of RIPK1 and facilitates RIPK1 cleavage by promoting the caspase-8/RIPK1 negative feedback loop.

Type of data: mass spectrometry

Subject of data: Homo sapiens; Eukaryotic cell lines; Mus musculus

Population characteristics: human patients were female, diagnosed with TNBC and average age 45.4 years; seven-week-old female BALB/c mice

Recruitment: consecutively recruited between May 1, 2012 and April 30, 2013 at Tianjin Medical University Cancer Institute and Hospital and the First Affiliated Hospital of Xiamen University

Data access

The public data resources used in the related study are openly available from the following sources: the Oncomine database (http://www.oncomine.org), the Cancer Genome Atlas (TCGA, https://identifiers.org/cbioportal:brca_tcga), Genotype-Tissue Expression (GTEx, https://gtexportal.org), and the Gene Expression Omnibus data repository (GEO, https://identifiers.org/geo:GSE1456, https://identifiers.org/geo:GSE6532, and https://identifiers.org/geo:GSE7390).

The majority of the GraphPad Prism files underlying the figures and supplementary figures of the related article are openly available as part of this data record. However, several are saved in institutional storage and are not publicly available to protect the patient privacy. These may be available from the corresponding author upon reasonable request.

All the uncropped western blots generated during this study are available in Supplementary Figure 6.

Corresponding author(s) for this study

Fanxin Zeng, Ph.D., Department of Clinical Research Center, Dazhou Central Hospital, No.56 Nanyuemiao St, Tongchuan District, Dazhou, 635000, China, Phone: +86- 818-2381051, E-mail: zengfx@pku.edu.cn.

Huiwen Ren, Ph.D., Department of Pharmacology, School of Basic Medical Sciences, Tianjin Medical University, No.22 Qixiangtai Rd. Heping District, Tianjin, 300070, China, Phone: +86-22-83336668, E-mail: renhuiwen@tmu.edu.cn.

Study approval

The study conformed to the Ethical Guidelines of the Helsinki Declaration, and was approved by the Ethics Committee of Tianjin Medical University Cancer Institute and Hospital, Tianjin, and the Ethics Committee of the First Affiliated Hospital of Xiamen University, Xiamen, People’s Republic of China.

Background: The SERPINH1 gene plays a vital part in tumorigenesis and development, whereas its potential as an immunotherapy target is still unknown. Hence, this research aimed to probe the roles of SERPINH1 in human tumors.Method: Using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) database, Oncomine, and SangerBox software, the pan-cancer expression of SERPINH1 and its correlation were systematically analyzed. SERPINH1 protein information was detected by the Human Protein Atlas (HPA) database and STRING database. The genomic alterations of SERPINH1 were studied using the c-BioPortal database. The influence of SERPINH1 on prognosis was analyzed using Kaplan–Meier plotter. The R package “clusterProfiler” was used for enrichment analysis to detect the role of SERPINH1. The TIMER2 database was used to further analyze the correlation between the immune cell infiltration score of TCGA samples and the expression of SERPINH1.Results: SERPINH1 overexpression was related to worse survival status in pan-cancer. In addition, high expression of SERPINH1 was positively associated with tumor stage and poor prognosis. Moreover, SERPINH1 played an important role in tumor microenvironment and immune regulation. Our study revealed that SERPINH1 expression has a strong correlation with immune cell filtration, immune regulation, chemokines, and immune checkpoints.Conclusion: Our research found that SERPINH1 was a risk factor and predictor of poor prognosis in various tumors. High expression of SERPINH1 may contribute to tumor immune-suppressive status. Also, SERPINH1 may become a potential immunotherapy target in pan-cancer.

Background: REV1 is a member of the translesion synthesis DNA polymerase Y family. It is an essential player in a variety of DNA replication activities, and perform major roles in the production of both spontaneous and DNA damage-induced mutations. This study aimed to explore the role of REV1 as a prognostic biomarker and its potential function regulating the sensitivity of anti-tumor drugs in various cancers.Methods: We analyzed the impact of REV1 gene alterations on patient prognosis and the impact of different REV1 single nucleotide polymorphisms (SNP) on protein structure and function using multiple online prediction servers. REV1 expression was assessed using data from Oncomine, TCGA, and TIMER database. The correlation between REV1 expression and patient prognosis was performed using the PrognoScan and Kaplan-Meier plotter databases. The IC50 values of anti-cancer drugs were downloaded from the Genomics of Drug Sensitivity in Cancer database and the correlation analyses between REV1 expression and each drug pathway’s IC50 value in different tumor types were conducted.Results: Progression free survival was longer in REV1 gene altered group comparing to unaltered group [Median progression free survival (PFS), 107.80 vs. 60.89 months, p value = 7.062e-3]. REV1 SNP rs183737771 (F427L) was predicted to be deleterious SNP. REV1 expression differs in different tumour types. Low REV1 expression is associated with better prognosis in colorectal disease specific survival (DSS), disease-free survival (DFS), gastric overall survival (OS), post progression survival (PPS) and ovarian (OS, PPS) cancer while high REV1 expression is associated with better prognosis in lung [OS, relapse free survival (RFS), first progession (FP), PPS] and breast (DSS, RFS) cancer. In colon adenocarcinoma and rectum adenocarcinoma and lung adenocarcinoma, low expression of REV1 may suggest resistance to drugs in certain pathways. Conversely, high expression of REV1 in acute myeloid leukemia, brain lower grade glioma, small cell lung cancer and thyroid carcinoma may indicate resistance to drugs in certain pathways.Conclusion: REV1 plays different roles in different tumor types, drug susceptibility, and related biological events. REV1 expression is significantly correlated with different prognosis in colorectal, ovarian, lung, breast, and gastric cancer. REV1 expression can be used as predictive marker for various drugs of various pathways in different tumors.

Voltage-gated calcium channels (VGCCs) are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org), a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I) are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment.