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Frontiers in immunology
2021;12 644350.

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

Lei Liu, Qiuchen Zhao, Chao Cheng, Jingwen Yi, Hongyan Sun, Qi Wang, Weili Quan, Yaqiang Xue, Luguo Sun, Xianling Cong, Yi Zhang
Author Information
  1. Lei Liu: National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun, China.
  2. Qiuchen Zhao: Center of Genome Analysis, ABLife BioBigData Institute, Wuhan, China.
  3. Chao Cheng: Center of Genome Analysis, ABLife BioBigData Institute, Wuhan, China.
  4. Jingwen Yi: Research Center of Agriculture and Medicine Gene Engineering of Ministry of Education, Northeast Normal University, Changchun, China.
  5. Hongyan Sun: Tissue Bank, China-Japan Union Hospital, Jilin University, Changchun, China.
  6. Qi Wang: Center of Genome Analysis, ABLife BioBigData Institute, Wuhan, China.
  7. Weili Quan: Center of Genome Analysis, ABLife BioBigData Institute, Wuhan, China.
  8. Yaqiang Xue: Center of Genome Analysis, ABLife BioBigData Institute, Wuhan, China.
  9. Luguo Sun: National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun, China.
  10. Xianling Cong: Tissue Bank, China-Japan Union Hospital, Jilin University, Changchun, China.
  11. Yi Zhang: Center of Genome Analysis, ABLife BioBigData Institute, Wuhan, China.
PMID: 34489925 DOI: 10.3389/fimmu.2021.644350

Abstract

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 , , , and 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.

Keywords

ERG FOXM1 MYBL2 TAL1 immune cell types immune infiltration pan-cancers transcription factor

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MeSH Term

Biomarkers, Tumor
CD4-Positive T-Lymphocytes
Dendritic Cells
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Humans
Immune System
Macrophages
Mutation
Neoplasms
Prognosis
Sequence Analysis, RNA
Transcription Factors
Tumor Microenvironment

Chemicals

Biomarkers, Tumor
Transcription Factors
Journal Article Research Support, Non-U.S. Gov't

Links to CNCB-NGDC Resources

GEN: GEND000503 (50 pairs of transcriptomes from 50 patients covering 9 types of cancer)

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