Dataset Information

Prognostic Role of Tumor Mutation Burden Combined With Immune Infiltrates in Skin Cutaneous Melanoma Based on Multi-Omics Analysis.

ABSTRACT: Tumor mutation burden (TMB) and tumor infiltrating lymphocytes have been well-recognized as molecular determinants of immunotherapeutic responsiveness in many types of cancer. However, the relationship between TMB with immune infiltrates and their prognostic role are reported occasionally in skin cutaneous melanoma (SKCM). We obtained the somatic mutation data and transcriptome profiles of 454 SKCM patients from The Cancer Genome Atlas (TCGA) database, and analyzed the mutation profiles using "maftools" package. Correlation analysis revealed that lower TMB levels conferred poor survival outcomes, associated with lower age and advanced pathological stage. Differential analysis was conducted to the genome expression between two TMB groups using "limma" package, and we identified four hub TMB-related immune genes including CNTFR, CRABP2, GAL, and PAEP. We further analyzed the underlying relationships of the copy number variations (CNVs) of four hub genes with immune infiltrates in SKCM microenvironment through TIMER database. The results indicated that diverse forms of CNVs carried by hub genes could commonly inhibit immune infiltrates. Based on the CIBERSORT method, we compared the proportions of 22 immune cells in two TMB groups and assessed their prognostic value. The data revealed that infiltrations levels of regulatory T (Treg) cell and dendritic activated cells in high-TMB group were lower than that in low-TMB group, while M1 and M2 macrophages showed the opposite trend, especially the levels of neutrophil and macrophage correlated positively with prognosis of SKCM. Finally, we constructed a TMB Prognostic Index (TMBPI) to evaluate the predictive accuracy of the four hub TMB-related immune genes. The ROC curve was drawn to assess the predictive accuracy with AUC = 0.664 and higher TMBPI conferred poor survival outcomes, which warranted further investigation and larger samples to validate.

SUBMITTER: Yan J

PROVIDER: S-EPMC7683772 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Prognostic Role of Tumor Mutation Burden Combined With Immune Infiltrates in Skin Cutaneous Melanoma Based on Multi-Omics Analysis.

Yan Junya J Wu Xiaowen X Yu Jiayi J Zhu Yanyan Y Cang Shundong S

Frontiers in oncology 20201110

Tumor mutation burden (TMB) and tumor infiltrating lymphocytes have been well-recognized as molecular determinants of immunotherapeutic responsiveness in many types of cancer. However, the relationship between TMB with immune infiltrates and their prognostic role are reported occasionally in skin cutaneous melanoma (SKCM). We obtained the somatic mutation data and transcriptome profiles of 454 SKCM patients from The Cancer Genome Atlas (TCGA) database, and analyzed the mutation profiles using "m ...[more]

PMID: 33240814

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Project description:BackgroundAs a member of tumor, Skin cutaneous melanoma (SKCM) poses a serious threat to people's health because of its strong malignancy. Unfortunately, effective treatment methods for SKCM remain lacking. FANCI plays a vital role in the occurrence and metastasis of various tumor types. However, its regulatory role in SKCM is unclear. The purpose of this study was to explore the association of FANCI with SKCM.MethodsThis study investigated the expression of FANCI in GSE46517, GSE15605, and GSE114445 from the Gene Expression Omnibus database and The Cancer Genome Atlas (TCGA)-SKCM datasets using the package "limma" or "DESeq2" in R environment and also investigated the prognostic significance of FANCI by utilizing the GEPIA database. Additionally, our research made use of real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemical (IHC) staining to verify FANCI expression between SKCM and normal tissues and developed the knockdown of FANCI in A375 and A875 cells to further analyze the function of FANCI. Finally, this study analyzed the correlation of FANCI and tumor-infiltrating immune cells by CIBERSORT, ESTIMATE, and ssGSEA algorithms.ResultsThe FANCI level was increasing in SKCM tissues from GSE46517, GSE15605, GSE114445, and TCGA-SKCM. However, high FANCI expression correlated with poor overall survival. The RT-qPCR and IHC confirmed the accuracy of bioinformatics. Knocking down FANCI suppresses A375 and A875 cell proliferation, migration, and invasion. FANCI could be involved in the immunological milieu of SKCM by regulating immune responses and infiltrating numerous immune cells, particularly neutrophils, CD8+ T cells, and B cells. Furthermore, patients with SKCM who have a high FANCI expression level are reported to exhibit immunosuppression, whereas those with a low FANCI expression level are more likely to experience positive outcomes from immunotherapy.ConclusionsThe increased FANCI expression in SKCM can be a prognostic biomarker. Knockdown FANCI can reduce the occurrence and progression of SKCM. The FANCI expression provides a foundation for predicting the immune status and treatment of SKCM.

Project description:BackgroundHepatocellular carcinoma (HCC) was the sixth common malignancies characteristic with highly aggressive in the world. It was well established that tumor mutation burden (TMB) act as indicator of immunotherapeutic responsiveness in various tumors. However, the role of TMB in tumor immune microenvironment (TIME) is still obscure.MethodThe mutation data was analyzed by employing "maftools" package. Weighted gene co-expression network analysis (WGCNA) was implemented to determine candidate module and significant genes correlated with TMB value. Differential analysis was performed between different level of TMB subgroups employing R package "limma". Gene ontology (GO) enrichment analysis was implemented with "clusterProfiler", "enrichplot" and "ggplot2" packages. Then risk score signature was developed by systematical bioinformatics analyses. K-M survival curves and receiver operating characteristic (ROC) plot were further analyzed for prognostic validity. To depict comprehensive context of TIME, XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT, and CIBERSORT-ABS algorithm were employed. Additionally, the potential role of risk score on immune checkpoint blockade (ICB) immunotherapy was further explored. The quantitative real-time polymerase chain reaction was performed to detect expression of HTRA3.ResultsTMB value was positively correlated with older age, male gender and early T status. A total of 75 intersection genes between TMB-related genes and differentially expressed genes (DEGs) were screened and enriched in extracellular matrix-relevant pathways. Risk score based on three hub genes significantly affected overall survival (OS) time, infiltration of immune cells, and ICB-related hub targets. The prognostic performance of risks score was validated in the external testing group. Risk-clinical nomogram was constructed for clinical application. HTRA3 was demonstrated to be a prognostic factor in HCC in further exploration. Finally, mutation of TP53 was correlated with risk score and do not interfere with risk score-based prognostic prediction.ConclusionCollectively, a comprehensive analysis of TMB might provide novel insights into mutation-driven mechanism of tumorigenesis further contribute to tailored immunotherapy and prognosis prediction of HCC.

Project description:Background: Tumor mutation burden (TMB) is considered as a novel biomarker of response to immunotherapy and correlated with survival outcomes in various malignancies. Here, TMB-related genes (TRGs) expression signatures were constructed to investigate the association between TMB and prognosis in epithelial ovarian cancer (EOC), and the potential mechanism in immunoregulation was also explored. Methods: Based on somatic mutation data of 436 EOC samples from The Cancer Genome Atlas database, we examined the relationship between TMB level and overall survival (OS), as well as disease-free survival (DFS). Next, the TRGs signatures were constructed and validated. Differential abundance of immune cell infiltration, expression levels of immunomodulators and functional enrichment in high- and low-risk groups were also analyzed. Results: Higher TMB level revealed better OS and DFS, and correlated with earlier clinical stages in EOCs (P = 2.796e-04). The OS-related prognostic model constructed based on seven TRGs (B3GALT1, LIN7B, ANGPT2, D2HGDH, TAF13, PFDN4 and DNAJC19) significantly stratified EOC patients into high- and low-risk groups (P < 0.001). The AUC values of the seven-gene prognostic signature at 1 year, 3 years, and 5 years were 0.703, 0.758 and 0.777. While the DFS-related prognostic model was constructed based on the 4 TRGs (LPIN3, PXYLP1, IGSF23 and B3GALT1), with AUCs of 0.617, 0.756, and 0.731, respectively. Functional analysis indicated that immune-related pathways were enriched in low-risk groups. When considering the infiltration patterns of immune cells, we found higher proportions of follicular helper T (Tfh) cell and M1 macrophage, while lower infiltration of M0 macrophage in low-risk groups (P < 0.05). Accordingly, TMB levels of low-risk patients were significantly higher both in OS and DFS model (P < 0.01). Conclusions: Our TRGs-based models are reliable predictive tools for OS and DFS. High TMB may confer with an immunogenic microenvironment and predict favorable outcomes in EOCs.

Project description:BackgroundThe like-Smith (LSM) family is a group of RNA-binding proteins involved in RNA metabolism. However, their involvement in tumors, particularly skin cutaneous melanoma (SKCM), is not fully understood. In this study, we focused on the expression profiles and prognostic values of the LSM family in SKCM.MethodsRaw data were downloaded from The Cancer Genome Atlas. The expression profile and prognostic value of LSM genes in SKCM were explored using the GEPIA, cBioPortal, and HPA databases. Protein-protein and gene-gene interaction analyses were performed using STRING and GeneMANIA. Enrichment and Cox regression analysis were conducted using R software. The TISIDB database was used to explore the relationship between LSMs and immunomodulators. Receiver operating characteristic curves and nomogram models were constructed to validate prognostic values.ResultsmRNA and protein expression levels of LSM2, LSM4, and LSM12 were significantly elevated in SKCM. The upregulated mRNA expression of LSM2 (p = 0.0013) and LSM4 (p = 0.0043) was significantly correlated with poor overall survival in patients with SKCM, whereas only LSM2 (p = 0.049) overexpression was markedly associated with worse disease-free survival. LSM2 overexpression was an independent risk factor (p = 0.013) and was confirmed to have a high prognostic value in SKCM using the receiver operating characteristic curve (AUC = 0.942) and nomogram models. All LSM genes were identified as genomic mutations, whereas alteration of LSM2 (p = 0.0153) significantly affected the overall survival in patients with SKCM. Significant correlations were observed between LSM family expression, immune cell infiltration, and immunomodulator. Furthermore, function and pathway enrichment analysis showed that the LSM family was mainly RNA binding proteins and involved in RNA splicing and degradation.ConclusionExpression profiles and prognostic values of LSM in SKCM were inconsistent. Among the LSM family, only LSM2 may serve as a potential poor prognosticator and immunotherapeutic target of SKCM.

Dataset Information

Prognostic Role of Tumor Mutation Burden Combined With Immune Infiltrates in Skin Cutaneous Melanoma Based on Multi-Omics Analysis.

Publications

Prognostic Role of Tumor Mutation Burden Combined With Immune Infiltrates in Skin Cutaneous Melanoma Based on Multi-Omics Analysis.

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