Dataset Information

Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment.

ABSTRACT: Purpose:The aim of this study was to explore the effective immune scoring method and mine the novel and potential immune microenvironment-related diagnostic and prognostic markers for cervical squamous cell carcinoma (CSSC). Materials and Methods:The Cancer Genome Atlas (TCGA) data was downloaded and multiple data analysis approaches were initially used to search for the immune-related scoring system on the basis of Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm. Afterwards, the representative genes in the gene modules correlated with immune-related scores based on ESTIMATE algorithm were further screened using Weighted Gene Co-expression Network Analysis (WGCNA) and network topology analysis. Gene functions were mined through enrichment analysis, followed by exploration of the correlation between these genes and immune checkpoint genes. Finally, survival analysis was applied to search for genes with significant association with overall survival and external database was employed for further validation. Results:The immune-related scores based on ESTIMATE algorithm was closely associated with other categories of scores, the HPV infection status, prognosis and the mutation levels of multiple CSCC-related genes (HLA and TP53). Eighteen new representative immune microenvironment-related genes were finally screened closely associated with patient prognosis and were further validated by the independent dataset GSE44001. Conclusion:Our present study suggested that the immune-related scores based on ESTIMATE algorithm can help to screen out novel immune-related diagnostic indicators, therapeutic targets and prognostic predictors in CSCC.

SUBMITTER: Ma J

PROVIDER: S-EPMC7450998 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment.

Ma Jiong J Cheng Pu P Chen Xuejun X Zhou Chunxia C Zheng Wei W

PeerJ 20200824

<h4>Purpose</h4>The aim of this study was to explore the effective immune scoring method and mine the novel and potential immune microenvironment-related diagnostic and prognostic markers for cervical squamous cell carcinoma (CSSC).<h4>Materials and methods</h4>The Cancer Genome Atlas (TCGA) data was downloaded and multiple data analysis approaches were initially used to search for the immune-related scoring system on the basis of Estimation of STromal and Immune cells in MAlignant Tumour tissue ...[more]

PMID: 32904067

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Project description:The Nobel Prize in Physiology or Medicine for the year 2021 was awarded to Ardem Patapoutian and David Julius for their discoveries of temperature-sensitive receptors (TRP channels) and tactile receptors (Piezo channels), both of which were previously unknown. TRP channels are at the heart of the human ability to detect temperature, and they also play crucial regulatory functions in the occurrence and progression of cancer. Despite this, there have been no research conducted on the prognostic significance of TRP channels in individuals with esophageal squamous cell carcinoma (ESCC). In GEO and TCGA cohorts, unsupervised clustering was first conducted based on 18 TRP channel-associated differentially expressed genes (DEGs) extracted from MSigDB database and KEGG database. Two TRP subtypes were identified and patients in subtype B had the best prognosis among the two subtypes. Significant differences in staging and grading existed among the different subtypes. In GEO cohort, univariate Cox analysis were performed to screen prognosis related genes. A TRP channel-related prognostic signature, which included 7 signature-related genes, was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression. Patients were divided into a high-risk group and low-risk group by the median risk score. In GEO and TCGA cohorts, Receiver operating characteristic (ROC) curves, principal component analysis (PCA), and univariate and multivariate Cox regression were performed to confirm the validity of signature. Following a more in-depth study of the TME based on the risk signature, it was discovered that the high-risk group had higher immune cell infiltration and lower tumor purity, indicating a bad prognosis. Patients with high risk scores also had increased immune checkpoint expression, indicating that these patients may be more likely to benefit from immunotherapy than other patients. We also found that paclitaxel, cisplatin, and 5-fluorouracil displayed a better response in treating the low-risk score ESCC patients. This study also adopted GTEx and qRT-PCR to perform experimental verification processes. In summary, we identified a TRP channel-associated prognostic signature. This signature can predict prognosis and immune microenvironment in ESCC.

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Dataset Information

Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment.

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Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment.

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