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

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 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.

SUBMITTER: Liu L

PROVIDER: S-EPMC8417605 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundUlcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affects mucosal homeostasis and triggers an inappropriate immune response. Single-cell RNA sequencing (scRNA-seq) can be used to rapidly obtain the precise gene expression patterns of thousands of cells in the intestine, analyze the characteristics of cells with the same phenotype, and provide new insights into the growth and development of intestinal organs, the clonal evolution of cells, and immune cell changes. These findings can provide new ideas for the diagnosis and treatment of intestinal diseases.AimTo identify clinical phenotypes and biomarkers that can predict the response of UC patients to specific therapeutic drugs and thus aid the diagnosis and treatment of UC.MethodsUsing the Gene Expression Omnibus (GEO) database, we analyzed peripheral blood cell subtypes of patients with UC by scRNA-seq combined with bulk RNA sequencing (RNA-seq) to reveal the core genes of UC. We then combined weighted gene correlation network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analysis to reveal diagnostic markers of UC.ResultsAfter processing the scRNA-seq data, we obtained data from approximately 24340 cells and identified 17 cell types. Through intercellular communication analysis, we selected monocyte marker genes as the candidate gene set for the prediction model. Construction of a WGCNA coexpression network identified RhoB, cathepsin D (CTSD) and zyxin (ZYX) as core genes. Immune infiltration analysis showed that these three core genes were strongly correlated with immune cells. Functional enrichment analysis showed that the differentially expressed genes were closely related to immune and inflammatory responses, which are associated with many challenges in the diagnosis and treatment of UC.ConclusionThrough scRNA-seq analysis, LASSO diagnostic model building and WGCNA, we identified RhoB, CTSD and ZYX as core genes of UC that are closely related to monocyte infiltration that may serve as diagnostic markers and molecular targets for UC therapeutic intervention.

Project description:IntroductionColorectal cancer (CRC) is a highly heterogeneous cancer. The molecular and cellular characteristics differ between the colon and rectal cancer type due to the differences in their anatomical location and pathological properties. With the advent of single-cell sequencing, it has become possible to analyze inter- and intra-tumoral tissue heterogeneities.MethodsA comprehensive CRC immune atlas, comprising 62,398 immune cells, was re-structured into 33 immune cell clusters at the single-cell level. Further, the immune cell lineage heterogeneity of colon, rectal, and paracancerous tissues was explored. Simultaneously, we characterized the TAM phenotypes and analyzed the transcriptomic factor regulatory network of each macrophage subset using SCENIC. In addition, monocle2 was used to elucidate the B cell developmental trajectory. The crosstalk between immune cells was explored using CellChat and the patterns of incoming and outgoing signals within the overall immune cell population were identified. Afterwards, the bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) were combined and the relative infiltration abundance of the identified subpopulations was analyzed using CIBERSORT. Moreover, cell composition patterns could be classified into five tumor microenvironment (TME) subtypes by employing a consistent non-negative matrix algorithm. Finally, the co-expression and interaction between SPP1+TAMs and Treg cells in the tumor microenvironment were analyzed by multiplex immunohistochemistry.ResultsIn the T cell lineage, we found that CXCL13+T cells were more widely distributed in colorectal cancer tissues, and the proportion of infiltration was increased. In addition, Th17 was found accounted for the highest proportion in CD39+CD101+PD1+T cells. Mover, Ma1-SPP1 showed the characteristics of M2 phenotypes and displayed an increased proportion in tumor tissues, which may promote angiogenesis. Plasma cells (PCs) displayed a significantly heterogeneous distribution in tumor as well as normal tissues. Specifically, the IgA+ PC population could be shown to be decreased in colorectal tumor tissues whereas the IgG+ PC one was enriched. In addition, information flow mediated by SPP1 and CD44, regulate signaling pathways of tumor progression. Among the five TME subtypes, the TME-1 subtype displayed a markedly reduced proportion of T-cell infiltration with the highest proportion of macrophages which was correlated to the worst prognosis. Finally, the co-expression and interaction between SPP1+TAMs and Treg cells were observed in the CD44 enriched region.DiscussionThe heterogeneity distribution and phenotype of immune cells were analyzed in colon cancer and rectal cancer at the single-cell level. Further, the prognostic role of major tumor-infiltrating lymphocytes and TME subtypes in CRC was evaluated by integrating bulk RNA. These findings provide novel insight into the immunotherapy of CRC.

Project description:BackgroundAn accumulating amount of studies are highlighting the impacts of cancer-associated fibroblasts (CAFs) on the initiation, metastasis, invasion, and immune evasion of lung cancer. However, it is still unclear how to tailor treatment regimens based on the transcriptomic characteristics of CAFs in the tumor microenvironment of patients with lung cancer.MethodsOur study examined single-cell RNA-sequencing data from the Gene Expression Omnibus (GEO) database to identify expression profiles for CAF marker genes and constructed a prognostic signature of lung adenocarcinoma using these genes in The Cancer Genome Atlas (TCGA) database. The signature was validated in 3 independent GEO cohorts. Univariate and multivariate analyses were used to confirm the clinical significance of the signature. Next, multiple differential gene enrichment analysis methods were used to explore the biological pathways related to the signature. Six algorithms were used to assess the relative proportion of infiltrating immune cells, and the relationship between the signature and immunotherapy response of lung adenocarcinoma (LUAD) was explored based on the tumor immune dysfunction and exclusion (TIDE) algorithm.ResultsThe signature related to CAFs in this study showed good accuracy and predictive capacity. In all clinical subgroups, the high-risk patients had a poor prognosis. The univariate and multivariate analyses confirmed that the signature was an independent prognostic marker. Moreover, the signature was closely associated with particular biological pathways related to cell cycle, DNA replication, carcinogenesis, and immune response. The 6 algorithms used to assess the relative proportion of infiltrating immune cells indicated that a lower infiltration of immune cells in the tumor microenvironment was associated with high-risk scores. Importantly, we found a negative correlation between TIDE, exclusion score, and risk score.ConclusionsOur study constructed a prognostic signature based on CAF marker genes useful for prognosis and immune infiltration estimation of lung adenocarcinoma. This tool could enhance therapy efficacy and allow individualized treatments.

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

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