Dataset Information

Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma.

ABSTRACT: OBJECTIVE:The tumour microenvironment is one of the significant factors driving the carcinogenesis of Pancreatic adenocarcinoma (PAAD). However, the underlying mechanism of how the tumour microenvironment impacts the prognosis of PAAD is not completely clear. RESULTS:The transcriptome and clinical data of 182 PAAD program cases were downloaded from the TCGA database. Three hundred thirty-three differentially expressed genes (DEGs) between high and low stromal groups and 314 DEGs between high and low immune score groups were identified using ESTIMATE score. Based on the 203 genes differentially expressed simultaneously in two score-related comparisons, we established an 8-mRNA signature to evaluate the prognosis of PAAD patients. Kaplan-Meier curves showed significantly worse survival for patients with high-risk scores in both the training and validation groups. The risk score was an independent prognostic factor and had a high predictive value for the prognosis of patients with PAAD. By searching the TCGA database, we showed that CA9, CXCL9, and GIMAP7 from the 8-mRNA signature were associated with the infiltration levels of immunocytes by regulating FOXO1 expression in PAAD. CONCLUSIONS:Unlike traditional methods of screening for differential genes in cancer and healthy tissues, we constructed a novel 8-mRNA signature to predict the prognosis of PAAD patients by applying ESTIMATE scoring to RNA-seq-based transcriptome data. Most importantly, we identified CA9, CXCL9, and GIMAP7 from the above eight genes as regulators of immunocyte infiltration by adjusting the expression of FOXO1 in PAAD. Thus, CA9, CXCL9, and GIMAP7 might be the ideal targets of immune therapy of PAAD. METHODS:ESTIMATE scoring was used to determine the stromal and immune scores of transcriptome datasets downloaded from the TCGA database. An mRNA-based prognostic signature was built for the training cohort via the LASSO Cox regression model. The signature was verified using a validation cohort. Kaplan-Meier curves and log-rank analysis were used to identify survival differences. Western blot analysis and RT-qPCR analysis were carried out to analyze the expression of specific proteins and mRNAs. IHC was performed to assess the protein levels of Forkhead box-O 1 (FOXO1), Carbonic anhydrase 9 (CA9), C-X-C motif chemokine ligand 9 (CXCL9), and GTPase, IMAP family member 7 (GIMAP7) in the tissue microarray of PAAD.

SUBMITTER: Meng Z

PROVIDER: S-EPMC7138590 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma.

Meng Zibo Z Ren Dianyun D Zhang Kun K Zhao Jingyuan J Jin Xin X Wu Heshui H

Aging 20200317 6

<h4>Objective</h4>The tumour microenvironment is one of the significant factors driving the carcinogenesis of Pancreatic adenocarcinoma (PAAD). However, the underlying mechanism of how the tumour microenvironment impacts the prognosis of PAAD is not completely clear.<h4>Results</h4>The transcriptome and clinical data of 182 PAAD program cases were downloaded from the TCGA database. Three hundred thirty-three differentially expressed genes (DEGs) between high and low stromal groups and 314 DEGs b ...[more]

PMID: 32181755

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Dataset Information

Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma.

Publications

Using ESTIMATE algorithm to establish an 8-mRNA signature prognosis prediction system and identify immunocyte infiltration-related genes in Pancreatic adenocarcinoma.

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