Comprehensive analysis, diagnosis, prognosis, and cordycepin (CD) regulations for GSDME expressions in pan-cancers.

The Gasdermin E gene (GSDME) plays roles in deafness and cancers. However, the roles and mechanisms in cancers are complex, and the same gene exhibits different mechanisms and actions in different types of cancers. Online databases, such as GEPIA2, cBioPortal, and DNMIVD, were used to comprehensively analyze GSDME profiles, DNA methylations, mutations, diagnosis, and prognosis in patients with tumor tissues and matched healthy tissues. Western blotting and RT-PCR were used to monitor the regulation of GSDME by Cordycepin (CD) in cancer cell lines. We revealed that GSDME expression is significantly upregulated in eight cancers (ACC, DLBC, GBM, HNSC, LGG, PAAD, SKCM, and THYM) and significantly downregulated in seven cancers (COAD, KICH, LAML, OV, READ, UCES, and UCS). The overall survival was longer only in ACC, but shorter in four cancers, including COAD, KIRC, LIHC, and STAD, when GSDME was highly expressed in cancers compared with the corresponding normal tissues. Moreover, the high expression of GSDME was negatively correlated with the poor prognosis of ACC, while the low expression of GSDME was negatively correlated with the poor prognosis of COAD, suggesting that GSDME might serve as a good prognostic factor in these two cancer types. Accordingly, results indicated that the DNA methylations of those 7 CpG sites constitute a potentially effective signature to distinguish different tumors from adjacent healthy tissues. Gene mutations for GSDME were frequently observed in a variety of tumors, with UCES having the highest frequency. Moreover, CD treatment inhibited GSDME expression in different cancer cell lines, while overexpression of GSDME promoted cell migration and invasion. Thus, we have systematically and successfully clarified the GSDME expression profiles, diagnostic values, and prognostic values in pan-cancers. Targeting GSDME with CD implies therapeutic significance and a mechanism for antitumor roles in some types of cancers via increasing the sensitivity of chemotherapy. Altogether, our study may provide a strategy and biomarker for clinical diagnosis, prognostics, and treatment of cancers by targeting GSDME.

How does SARS-CoV-2 infection impact on immunity, procession and treatment of pan cancers.

We identified 14 immune-related differentially Expressed Genes (DEGs) between COVID-19 patients and normal controls and the receiver operator characteristic curve results showed that they could be used to discriminate COVID-19 patients from healthy controls. Single-sample gene set enrichment analysis and CIBERSORT analysis displayed immune landscape of COVID-19 patients that the fraction of immune cells (like B cell subtypes and T cell subtypes) decreased distinctly in the first SARS-CoV-2 infection which may further weaken immunity of cancer patients and increasing inflammatory cells (Neutrophils and Macrophages) may further promote inflammatory response of cancer patients. Based on expression levels of 14 DEGs we found that first SARS-CoV-2 infection may accelerate progression of cancer patients by Kaplan-Meier survival, immune subtypes and tumor microenvironment analyses, and may weaken anti-PD-1 monoclonal antibody treatment effect of cancer patients by weighted gene co-expression network, tumor mutation burden and microsatellite instability analysis. The second SARS-CoV-2 infection was beneficial to control development of tumor seemingly, but it may be difficult for cancer patients to experience destroy successfully from first SARS-CoV-2 infection, let alone benefits from second SARS-CoV-2 infection. In addition, this study also emphasized significance of multi-factor analysis when analyzing impacts of SARS-CoV-2 infection on cancer patients.

A Comprehensive Prognostic Analysis of Tumor-Related Blood Group Antigens in Pan-Cancers Suggests That SEMA7A as a Novel Biomarker in Kidney Renal Clear Cell Carcinoma.

Blood group antigen is a class of heritable antigenic substances present on the erythrocyte membrane. However, the role of blood group antigens in cancer prognosis is still largely unclear. In this study, we investigated the expression of 33 blood group antigen genes and their association with the prognosis of 30 types of cancers in 31,870 tumor tissue samples. Our results revealed that blood group antigens are abnormally expressed in a variety of cancers. The high expression of these antigen genes was mainly related to the activation of the epithelial-mesenchymal transition (EMT) pathway. High expression of seven antigen genes, i.e., FUT7, AQP1, P1, C4A, AQP3, KEL and DARC, were significantly associated with good OS (Overall Survival) in six types of cancers, while ten genes, i.e., AQP1, P1, C4A, AQP3, BSG, CD44, CD151, LU, FUT2, and SEMA7A, were associated with poor OS in three types of cancers. Kidney renal clear cell carcinoma (KIRC) is associated with the largest number (14 genes) of prognostic antigen genes, i.e., CD44, CD151, SEMA7A, FUT7, CR1, AQP1, GYPA, FUT3, FUT6, FUT1, SLC14A1, ERMAP, C4A, and B3GALT3. High expression of SEMA7A gene was significantly correlated with a poor prognosis of KIRC in this analysis but has not been reported previously. SEMA7A might be a putative biomarker for poor prognosis in KIRC. In conclusion, our analysis indicates that blood group antigens may play functional important roles in tumorigenesis, progression, and especially prognosis. These results provide data to support prognostic marker development and future clinical management.

Construction of an immune-related LncRNA signature with prognostic significance for bladder cancer.

Bladder cancer (BLCA) is one of the most common urological cancer with increasing cases and deaths every year. In the present study, we aim to construct an immune-related prognostic lncRNA signature (IRPLS) in bladder cancer (BLCA) patients and explore its immunogenomic implications in pan-cancers. First, the immune-related differentially expressed lncRNAs (IRDELs) were identified by 'limma' R package and the score of IRPLS in every patient were evaluated by Cox regression. The dysregulation of IRDELs expression between cancer and para-cancer normal tissues was validated through RT-qPCR. Then, we further explore the biological functions of a novel lncRNA from IRPLS, RP11-89 in BLCA using CCK8 assay, Transwell assay and Apoptosis analysis, which indicated that RP11-89 was able to promote cell proliferation and invasive capacity while inhibits cell apoptosis in BLCA. In addition, we performed bioinformatic methods and RIP to investigate and validate the RP11-89/miR-27a-3p/PPARγ pathway in order to explore the mechanism. Next, CIBERSORT and ESTIMATE algorithm were used to evaluate abundance of tumour-infiltrating immune cells and scores of tumour environment elements in BLCA with different level of IRPLS risk scores. Finally, multiple bioinformatic methods were performed to show us the immune landscape of these four lncRNAs for pan-cancers. In conclusion, this study first constructed an immune-related prognostic lncRNA signature, which consists of RP11-89, PSORS1C3, LINC02672 and MIR100HG and might shed lights on novel targets for individualized immunotherapy for BLCA patients.

Comprehensive analysis of multiple parameters associated with tumor immune microenvironment in ARID1A mutant cancers.

Aim: To verify the relationship between ARID1A and tumor immune microenvironment thus immune checkpoint inhibitors (ICIs) response. Material & methods: Several public databases were used to characterize the association between ARID1A gene alteration and tumor immunity. Results: The gene mutation frequency was 8.2% in all cancer types. The ARID1A-mutated cancers have higher scores of mutation count, tumor mutational burden, neoantigen load (p < 0.001) and T cell repertoire, B cell repertoire diversity (p < 0.05). The gene mutation has tight association with multiple-activated immune cells. Survival analysis suggested that patients with ARID1A mutant cancers benefit more from ICIs treatment (p = 0.013). Conclusion: The ARID1A gene mutation was correlated with higher tumor immunogenicity and activated antitumor immune microenvironment, resulting in superior cohort that respond well to ICIs.

Pan-cancer genetic analysis of disulfidptosis-related gene set.

BACKGROUND: A recent study has identified a novel programmed cell death pathway, termed disulfidptosis, which is based on disulfide proteins. This discovery provides new insight into the mechanisms of cell death and may have implications for therapeutic strategies targeting cell death pathways. This study aimed to evaluate the pan-cancer genomics and clinical association of disulfidptosis and disulfidptosis-related cell death genes, including SLC7A11, INF2, CD2AP, PDLIM1, ACTN4, MYH9, MYH10, IQGAP1, FLNA, FLNB, TLN1, MYL6, ACTB, DSTN, and CAPZB. METHODS: Using multi-omics profiling data, this study provides a comprehensive and systematic characterization of disulfidptosis genes across more than 9000 samples of over 30 types of cancer. RESULTS: FLNA and FLNB were the two most frequently mutated disulfidptosis cell death genes in cancer. UCEC and SKCM were the two cancer types that have the highest mutation rates while the mutation of ACTN4 was associated with worse survival of CESC and ESCA. Breast cancer was potentially affected by disulfidptosis because its subtypes are different in disulfidptosis gene expression. Similarly, KIRC might also be associated with disulfidptosis. Additionally, the association of disulfidptosis-related cell death genes with survival was analyzed, with MESO and LGG as the top cancer types with survival associated with disulfidptosis cell death genes. The correlation between CNV and survival across multiple cancer types found that UCEC, KIRP, LGG, and KIRC were the top cancer types where the CNV level was associated with survival. There was a negative correlation between expression and methylation for most of the genes and there was only a slight correlation between methylation levels and survival of cancer in LGG. About half of the disulfidptosis-related cell death proteins were associated with the activation of EMT. Disulfidptosis genes were correlated to immune cell infiltration levels in cancers. Multiple compounds were identified as potential drugs that might be affected by disulfidptosis-related cell death for future study. CONCLUSION: Disulfidptosis cell death genes are potentially involved in many cancer types and can be developed as candidates for cancer diagnosis, prognosis, and therapeutic biomarkers.

Identification of alternative splicing associated with clinical features: from pan-cancers to genitourinary tumors.

Background: Alternative splicing events (ASEs) are vital causes of tumor heterogeneity in genitourinary tumors and many other cancers. However, the clinicopathological relevance of ASEs in cancers has not yet been comprehensively characterized. Methods: By analyzing splicing data from the TCGA SpliceSeq database and phenotype data for all TCGA samples from the UCSC Xena database, we identified differential clinical feature-related ASEs in 33 tumors. CIBERSORT immune cell infiltration data from the TIMER2.0 database were used for differential clinical feature-related immune cell infiltration analysis. Gene function enrichment analysis was used to analyze the gene function of ASEs related to different clinical features in tumors. To reveal the regulatory mechanisms of ASEs, we integrated race-related ASEs and splicing quantitative trait loci (sQTLs) data in kidney renal clear cell carcinoma (KIRC) to comprehensively assess the impact of SNPs on ASEs. In addition, we predicted regulatory RNA binding proteins in bladder urothelial carcinoma (BLCA) based on the enrichment of motifs around alternative exons for ASEs. Results: Alternative splicing differences were systematically analyzed between different groups of 58 clinical features in 33 cancers, and 30 clinical features in 24 cancer types were identified to be associated with more than 50 ASEs individually. The types of immune cell infiltration were found to be significantly different between subgroups of primary diagnosis and disease type. After integrating ASEs with sQTLs data, we found that 63 (58.9%) of the race-related ASEs were significantly SNP-correlated ASEs in KIRC. Gene function enrichment analyses showed that metastasis-related ASEs in KIRC mainly enriched Rho GTPase signaling pathways. Among those ASEs associated with metastasis, alternative splicing of GIT2 and TUBB3 might play key roles in tumor metastasis in KIRC patients. Finally, we identified several RNA binding proteins such as PCBP2, SNRNP70, and HuR, which might contribute to splicing differences between different groups of neoplasm grade in BLCA. Conclusion: We demonstrated the significant clinical relevance of ASEs in multiple cancer types. Furthermore, we identified and validated alternative splicing of TUBB3 and RNA binding proteins such as PCBP2 as critical regulators in the progression of urogenital cancers.

Comprehensive analysis, immune, and cordycepin regulation for SOX9 expression in pan-cancers and the matched healthy tissues.

SRY-box transcription factor 9 (SOX9) (OMIM 608160) is a transcription factor. The expression of SOX9 in pan-cancers and the regulation by small molecules in cancer cell lines are unclear. In the current study, we comprehensively analyzed the expression of SOX9 in normal tissues, tumor tissues and their matched healthy tissues in pan-cancers. The study examined the correlation between immunomodulators and immune cell infiltrations in normal and tumor tissues. Cordycepin (CD), an adenosine analog for SOX9 expression regulation, was also conducted on cancer cells. The results found that SOX9 protein is expressed in a variety of organs, including high expression in 13 organs and no expression in only two organs; in 44 tissues, there was high expression in 31 tissues, medium expression in four tissues, low expression in two tissues, and no expression in the other seven tissues. In pan-cancers with 33 cancer types, SOX9 expression was significantly increased in fifteen cancers, including CESC, COAD, ESCA, GBM, KIRP, LGG, LIHC, LUSC, OV, PAAD, READ, STAD, THYM, UCES, and UCS, but significantly decreased in only two cancers (SKCM and TGCT) compared with the matched healthy tissues. It suggests that SOX9 expression is upregulated in the most cancer types (15/33) as a proto-oncogene. The fact that the decrease of SOX9 expression in SKCM and the increase of SOX9 in the cell lines of melanoma inhibit tumorigenicity in both mouse and human ex vivo models demonstrates that SOX9 could also be a tumor suppressor. Further analyzing the prognostic values for SOX9 expression in cancer individuals revealed that OS is long in ACC and short in LGG, CESC, and THYM, suggesting that high SOX9 expression is positively correlated with the worst OS in LGG, CESC, and THYM, which could be used as a prognostic maker. In addition, CD inhibited both protein and mRNA expressions of SOX9 in a dose-dependent manner in 22RV1, PC3, and H1975 cells, indicating CD's anticancer roles likely via SOX9 inhibition. Moreover, SOX9 might play an important role in tumor genesis and development by participating in immune infiltration. Altogether, SOX9 could be a biomarker for diagnostics and prognostics for pan-cancers and an emerging target for the development of anticancer drugs.

A tumor-associated endothelial signature score model in immunotherapy and prognosis across pan-cancers.

Background: The tumor-associated endothelial cell (TAE) component plays a vital role in tumor immunity. However, systematic tumor-associated endothelial-related gene assessment models for predicting cancer immunotherapy (CIT) responses and survival across human cancers have not been explored. Herein, we investigated a TAE gene risk model to predict CIT responses and patient survival in a pan-cancer analysis. Methods: We analyzed publicly available datasets of tumor samples with gene expression and clinical information, including gastric cancer, metastatic urothelial cancer, metastatic melanoma, non-small cell lung cancer, primary bladder cancer, and renal cell carcinoma. We further established a binary classification model to predict CIT responses using the least absolute shrinkage and selection operator (LASSO) computational algorithm. Results: The model demonstrated a high predictive accuracy in both training and validation cohorts. The response rate of the high score group to immunotherapy in the training cohort was significantly higher than that of the low score group, with CIT response rates of 51% and 27%, respectively. The survival analysis showed that the prognosis of the high score group was significantly better than that of the low score group (all p < 0·001). Tumor-associated endothelial gene signature scores positively correlated with immune checkpoint genes, suggesting that immune checkpoint inhibitors may benefit patients in the high score group. The analysis of TAE scores across 33 human cancers revealed that the TAE model could reflect immune cell infiltration and predict the survival of cancer patients. Conclusion: The TAE signature model could represent a CIT response prediction model with a prognostic value in multiple cancer types.

Analysis of CFTR gene expression as an immunological and prognostic biomarker in pan-cancers.

Cystic fibrosis transmembrane conductance regulator (CFTR) is a cAMP-activated chloride channel that regulates fluid homeostasis via ATP binding and uses energy to transport relevant substrates across cytomembranes. It has been reported that CFTR plays a crucial role in the incidence and development of various types of cancers by regulating proliferation, metastasis, invasion and apoptosis. However, aberrant CFTR gene expression across different cancers makes it difficult to propose CFTR as a possible pan-cancer biomarker. Here, multiple databases (ONCOMINE, PrognoScan, Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA)), were accessed to investigate the relationship between CFTR gene expression with the immunological and prognostic roles in pan-cancers. The results showed higher CFTR gene expression in tumor tissues compared to normal tissues for most cancers except for CHOL, ESCA, KICH, LAML, SKCM and STAD. Higher expression of the CFTR gene directly correlated with better prognosis for BRCA, GBM, COAD, KIRP, LAML, LUAD, PRAD, SARC and STAD, and CFTR gene expression was higher in stage Ⅰ_Ⅱ compared to stage Ⅲ_ Ⅳ. Furthermore, CFTR gene expression levels were significantly associated with immune infiltrates and immunocytes, in particular, immune checkpoints, in COAD, LIHC, LUAD and LUSC. In conclusion, CFTR can be used as a prognostic marker for nine types of cancers examined in this study where CFTR expression levels play a vital role in forecasting the clinical efficacy of immune checkpoint suppression therapy.

SMO mutation predicts the effect of immune checkpoint inhibitor: From NSCLC to multiple cancers.

Background: The emergence of immune checkpoint inhibitors (ICIs) is one of the most promising breakthroughs for the treatment of multiple cancer types, but responses vary. Growing evidence points to a link between developmental signaling pathway-related genes and antitumor immunity, but the association between the genomic alterations in these genes and the response to ICIs still needs to be elucidated. Methods: Clinical data and sequencing data from published studies and our cohort were collected to analyze the association of the mutation status of SMO with the efficacy of ICI therapy in the non-small cell lung cancer (NSCLC) cohort and the pan-cancer cohort. Furthermore, the correlation between SMO mutation and immunotherapeutic biomarkers such as immune cell infiltration, immune-related genes, and underlying signaling pathways was analyzed. Three SMO mutant plasmids were transfected into cells to explore the SMO mutation status in the context of its expression and cell growth. Result: In the NSCLC discovery cohort, the median progression-free survival in the SMO mutant (SMO_MUT) was longer than that in the wild type (SMO_WT) (23.0 vs. 3.8 months, adjusted p = 0.041). This finding was further confirmed in the NSCLC validation cohort (8.7 vs. 5.1 months, adjusted p = 0.013). In the pan-cancer cohort (n = 1,347), a significant overall survival advantage was observed in patients with SMO mutations [not reached (NR) vs. 18 months, adjusted p = 0.024]. In the subgroup analysis, the survival advantage of SMO_MUT against SMO_WT was prominent and consistent across genders, ages, treatment types, cancer types, and the tumor mutation burden (TMB) status (all p interaction > 0.05). In an in vitro experiment, we found that both the mutant and wild-type plasmids can promote the expression of SMO, but the mutant plasmid had lower SMO mRNA and protein levels than the wild type. In CCK-8 experiments, we found that SMO_MUT plasmids can improve the growth of Calu-1 and PC-9 cells, but this capability varied between different mutations and cells. Upon further exploration, the SMO mutation status was found to be related to a higher TMB, more neoantigen load, more DNA damage repair (DDR) mutations, higher microsatellite instability (MSI) score, and higher CD8+ T-cell infiltration. Conclusions: The SMO mutation status is an independent prognostic factor that can be used to predict better clinical outcomes of ICI treatment across multiple cancer types.

Prognostic Pathways Guide Drug Indications in Pan-Cancers.

Pathway-level analysis is a powerful approach enabling the interpretation of post-genomic data at a higher level than that of individual molecules. Molecular-targeted therapy focusing on cascade signaling pathways has become a new paradigm in anticancer therapy, instead of a single protein. However, the approaches to narrowing down the long list of biological pathways are limited. Here, we proposed a strategy for in silico Drug Prescription on biological pathways across pan-Cancers (CDP), by connecting drugs to candidate pathways. Applying on a list of 120 traditional Chinese medicines (TCM), we especially identified the "TCM-pathways-cancers" triplet and constructed it into a heterogeneous network across pan-cancers. Applying them into TCMs, the computational prescribing methods deepened the understanding of the efficacy of TCM at the molecular level. Further applying them into Western medicines, CDP could promote drug reposition avoiding time-consuming developments of new drugs.

Comprehensive analysis of ZFPM2-AS1 prognostic value, immune microenvironment, drug sensitivity, and co-expression network: from gastric adenocarcinoma to pan-cancers.

BACKGROUND: ZFPM2-AS1, as an oncogenic lncRNA, plays an essential role in the progression of several tumors. However, the prognostic significance, biological function, and molecular mechanism of ZFPM2-AS1 in most tumors have not been fully elucidated. METHODS: We analyzed differentially expressed immune-related lncRNAs (IRlncRNAs) and clustered gastric adenocarcinoma (GAC) samples based on these lncRNAs expression. Then, WGCNA and survival analysis were performed to determine key IRlncRNA (ZFPM2-AS1) in GAC. The comprehensive analysis was performed to evaluate the association between ZFPM2-AS1 expression and survival, tumor microenvironment (TME), immune-related factors, and related signal pathways in pan-cancers. Furthermore, we constructed a co-expression network of ZFPM2-AS1, and NUP107 and C8orf76 were identified as target mRNAs. We further evaluated the role of NUP107 and C8orf76 in the GAC microenvironment. More importantly, real-time polymerase chain reaction (qRT-PCR) was employed to validate ZFPM2-AS1, NUP107 and C8orf76 expression. RESULTS: ZFPM2-AS1 was remarkably overexpressed and correlated with poor overall survival in most tumors. Further analysis showed that ZFPM2-AS1 was related to various immune cells infiltrated in the microenvironment of most tumors. GSEA revealed that ZFPM2-AS1 in GAC was primarily involved in immune-related pathways. Furthermore, NUP107 and C8orf76 were identified as potential target mRNAs of ZFPM2-AS1, which was related to infiltrating immune cells in the GAC microenvironment. qRT-PCR verified that ZFPM2-AS, NUP107 and C8orf76 were highly expressed in gastric cancer cells. CONCLUSION: ZFPM2-AS1 could be a potential biomarker for cancer prognosis, and a promising immune target for cancer therapy. Furthermore, ZFPM2-AS1 might play an immunosuppressive role in the GAC microenvironment.

Diagnostic value of oncofetal miRNAs in cancers: A comprehensive analysis of circulating miRNAs in pan-cancers and UCB.

BACKGROUND: Circulating miRNAs are promising biomarkers for detection of various cancers. As a "developmental" disorder, cancer showed great similarities with embryos. OBJECTIVE: A comprehensive analysis of circulating miRNAs in umbilical cord blood (UCB) and pan-cancers was conducted to identify circulating miRNAs with potential for cancer detection. METHODS: A total of 3831 cancer samples (2050 serum samples from 15 types of cancers and 1781 plasma samples from 13 types of cancers) and 248 UCB samples (120 serum and 128 plasma samples) with corresponding NCs from Chinese populations were analyzed via consistent experiment workflow with Exiqon panel followed by multiple-stage validation with qRT-PCR. RESULTS: Thirty-four serum and 32 plasma miRNAs were dysregulated in at least one type of cancer. Eighteen serum and 16 plasma miRNAs were related with embryos. Among them, 9 serum and 8 plasma miRNAs with consistent expression patterns between pan-cancers and UCB were identified as circulating oncofetal miRNAs. Retrospective analysis confirmed the diagnostic ability of circulating oncofetal miRNAs for specific cancers. And the oncofetal miRNAs were mainly up-regulated in tissues of pan-cancers. CONCLUSIONS: Our study might serve as bases for the potential application of the non-invasive biomarkers in the future clinical.

Multi-Omics Analysis of Cancer Cell Lines with High/Low Ferroptosis Scores and Development of a Ferroptosis-Related Model for Multiple Cancer Types.

Background: Ferroptosis is a newly identified regulated cell death characterized by iron-dependent lipid peroxidation and subsequent membrane oxidative damage, which has been implicated in multiple types of cancers. The multi-omics differences between cancer cell lines with high/low ferroptosis scores remain to be elucidated. Methods and Materials: We used RNA-seq gene expression, gene mutation, miRNA expression, metabolites, copy number variation, and drug sensitivity data of cancer cell lines from DEPMAP to detect multi-omics differences associated with ferroptosis. Based on the gene expression data of cancer cell lines, we performed LASSO-Logistic regression analysis to build a ferroptosis-related model. Lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), esophageal cancer (ESCA), bladder cancer (BLCA), cervical cancer (CESC), and head and neck cancer (HNSC) patients from the TCGA database were used as validation cohorts to test the efficacy of this model. Results: After stratifying the cancer cell lines into high score (HS) and low score (LS) groups according to the median of ferroptosis scores generated by gene set variation analysis, we found that IC50 of 66 agents such as oxaliplatin (p < 0.001) were significantly different, among which 65 were higher in the HS group. 851 genes such as KEAP1 and NRAS were differentially muted between the two groups. Differentially expressed genes, miRNAs and metabolites were also detected-multiple items such as IL17F (logFC = 6.58, p < 0.001) differed between the two groups. Unlike the TCGA data generated by bulk RNA-seq, the gene expression data in DEPMAP are from pure cancer cells, so it could better reflect the traits of tumors in cancer patients. Thus, we built a 15-signature model (AUC = 0.878) based on the gene expression data of cancer cell lines. The validation cohorts demonstrated a higher mutational rate of NFE2L2 and higher expression levels of 12 ferroptosis-related genes in HS groups. Conclusion: This article systemically analyzed multi-omics differences between cancer cell lines with high/low ferroptosis scores and a ferroptosis-related model was developed for multiple cancer types. Our findings could improve our understanding of the role of ferroptosis in cancer and provide new insight into treatment for malignant tumors.

Systematic analysis of molecular characterization and clinical relevance of m6A regulators in digestive system pan-cancers.

Digestive system tumors, which mainly include esophagus, stomach, colorectum, liver, pancreas, bile duct, and some other tumors, often have a poor prognosis. N6-methyladenosine (m6A) has critical functions in development and tumorigenesis and may help improve the molecular mechanisms of digestive system tumors. However, current understanding of the reconstitution of m6A in digestive system tumors is far from comprehensive. Herein, this study systematically analyzed multi-layered genomic characteristics and clinical relevance of m6A regulators in 1906 patients involving seven digestive system tumor types. We discovered that m6A regulators showed extensive genetic changes and highly consistent expression regulation. The m6A expression was closely related to the activity of cancer pathways. At the same time, we also identified m6A regulators significantly related to the common cancer pathways of digestive system tumors and specific cancer pathways of digestive tract and digestive glands. These cancer pathways may explain the prognostic differences of patients with digestive tract tumors. In addition, m6A regulators demonstrated strong potential in prognostic stratification and drug development, especially in multiple research cohorts on pancreatic cancer, pointing to a strong prognostic stratification capability of m6A regulators. Finally, a m6A scoring model significantly related to highly active ubiquitin-mediated proteolysis, mismatch repair, cell cycle, ebasal transcription factors was constructed and had a strong prognostic stratification ability in digestive gland tumors. The score showed a significant negative correlation with the tumor immune microenvironment. This study demonstrated that the similarities and difference of the action mechanism m6A regulators in the digestive tract and digestive gland tumor progression could guide potential drug development.

LINC02257, an Enhancer RNA of Prognostic Value in Colon Adenocarcinoma, Correlates With Multi-Omics Immunotherapy-Related Analysis in 33 Cancers.

Accumulated evidence supports that long non-coding RNAs (lncRNAs) are involved significantly in the development of human cancers. Enhancer RNAs (eRNAs), a subtype of lncRNAs, have recently attracted much attention about their roles in carcinogenesis. Colon adenocarcinoma is one of the most commonly diagnosed tumors with unfavorable prognosis. It highlights the great significance of screening and identifying novel biomarkers. More importantly, it remains to be elucidated with respect to the function of eRNAs in colon adenocarcinoma, as is in pan-cancers. The expression of LINC02257 was determined based on the data obtained from The Cancer Genome Atlas (TCGA). Further evaluation was performed on the basis of the following analyses: clinicopathology and survival analysis, gene ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, as well as multi-omics immunotherapy-related analysis and co-expression analysis. The statistical analysis was conducted in R software, and immune cell infiltration of LINC02257 expression in cancers was investigated by using the CIBERSORT algorithm. By large-scale data mining, our study highlighted that a total of 39 eRNA genes were associated with colon adenocarcinoma prognosis, among which 25 eRNAs showed significant associations with their predicted target genes. LINC02257 was identified as the most significant survival-associated eRNA, with DUSP10 as its target gene. Besides, the high expression of LINC02257 in colon adenocarcinoma was more vulnerable to unfavorable prognosis and correlated with various clinical characteristics. GO and KEGG analyses revealed that LINC02257 was closely correlated with extracellular matrix organization via the PI3K-Akt signaling pathway. Besides, LINC02257 expression correlated with a multi-omics analysis of 33 cancer types, such as survival analysis [overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI)] and immunotherapy-related analysis [tumor microenvironment (TME), tumor mutational burden (TMB), and microsatellite instability (MSI)]. Finally, we investigated the co-expression genes of LINC02257 and its potential signaling pathways across different cancer types. LINC02257 is screened and can function as an independent prognostic biomarker through the PI3K-Akt signaling pathway for colon adenocarcinoma. Simultaneously, LINC02257 may be a multifaceted and significant immunotherapy-related eRNA in different cancers.

Analysis of Bulk RNA Sequencing Data Reveals Novel Transcription Factors Associated With Immune Infiltration Among Multiple Cancers.

Tumor-infiltrating immune cells shape the tumor microenvironment and are closely related to clinical outcomes. Several transcription factors (TFs) have also been reported to regulate the antitumor activity and immune cell infiltration. This study aimed to quantify the populations of different immune cells infiltrated in tumor samples based on the bulk RNA sequencing data obtained from 50 cancer patients using the CIBERSORT and the EPIC algorithm. Weighted gene coexpression network analysis (WGCNA) identified eigengene modules strongly associated with tumorigenesis and the activation of CD4+ memory T cells, dendritic cells, and macrophages. TF genes FOXM1, MYBL2, TAL1, and ERG are central in the subnetworks of the eigengene modules associated with immune-related genes. The analysis of The Cancer Genome Atlas (TCGA) cancer data confirmed these findings and further showed that the expression of these potential TF genes regulating immune infiltration, and the immune-related genes that they regulated, was associated with the survival of patients within multiple cancers. Exome-seq was performed on 24 paired samples that also had RNA-seq data. The expression quantitative trait loci (eQTL) analysis showed that mutations were significantly more frequent in the regions flanking the TF genes compared with those of non-TF genes, suggesting a driver role of these TF genes regulating immune infiltration. Taken together, this study presented a practical method for identifying genes that regulate immune infiltration. These genes could be potential biomarkers for cancer prognosis and possible therapeutic targets.

A Hybrid Ensemble Approach for Identifying Robust Differentially Methylated Loci in Pan-Cancers.

DNA methylation is a widely investigated epigenetic mark that plays a vital role in tumorigenesis. Advancements in high-throughput assays, such as the Infinium 450K platform, provide genome-scale DNA methylation landscapes in single-CpG locus resolution, and the identification of differentially methylated loci has become an insightful approach to deepen our understanding of cancers. However, the situation with extremely unbalanced numbers of samples and loci (approximately 1:1,000) makes it rather difficult to explore differential methylation between the sick and the normal. In this article, a hybrid approach based on ensemble feature selection for identifying differentially methylated loci (HyDML) was proposed by incorporating instance perturbation and multiple function models. Experiments on data from The Cancer Genome Atlas showed that HyDML not only achieved effective DML identification, but also outperformed the single-feature selection approach in terms of classification performance and the robustness of feature selection. The intensive analysis of the DML indicated that different types of cancers have mutual patterns, and the stable DML sharing in pan-cancers is of the great potential to be biomarkers, which may strengthen the confidence of domain experts to implement biological validations.