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. 2023 Jun 23;24(1):48-61.
doi: 10.2174/1389202924666230503122134.

Comprehensive Analysis of Alternative Polyadenylation Events Associated with the Tumor Immune Microenvironment in Colon Adenocarcinoma

Fangning Pang  1   2 , Peng Yang  2 , Tongfei Wang  3 , Xuzhao Li  4 , Xiaoyong Wu  5 , Rong Yue  6 , Bin Bai  7 , Qingchuan Zhao  7
Affiliations

Comprehensive Analysis of Alternative Polyadenylation Events Associated with the Tumor Immune Microenvironment in Colon Adenocarcinoma

Fangning Pang et al. Curr Genomics. .

Abstract

Objective: Colon adenocarcinoma (COAD) is one of the leading causes of cancer death worldwide. Alternative polyadenylation (APA) is relevant to the variability of the 3'-UTR of mRNA. However, the posttranscriptional dysregulation of APA in COAD is poorly understood.

Methods: We collected APA data from The Cancer Genome Atlas (TCGA) COAD (n =7692). APA events were evaluated using PDUI values, and the prognostically significant APA events were screened by LASSO Cox regression to construct a prognostic model. Then, prognostic model functions and possible regulatory genes of characteristic APA events were analyzed. Finally, the immune regulatory network based on APA regulatory genes was analyzed and established.

Results: A total of 95 APA events were found to influence the COAD outcomes. Among them, 39 genes were screened as characteristic prognostic APA events by LASSO Cox regression to construct a COAD prognostic signature. The analysis results suggested that a high signature score was associated with poor prognosis and was significantly correlated with a variety of immune cells, including NK and Th1, 2 and 17 cells. Further analysis showed that APA regulators mainly served roles in the prognosis of COAD. Based on the above results, we constructed an immunoregulatory network for APA regulatory genes-APA genes-immune cells.

Conclusion: Our study revealed that APA events in COAD may regulate tumor progression by influencing immune cells, which provides a new direction for exploring the influencing mechanism of the tumor immune microenvironment and is expected to provide a potential new target for COAD immunotherapy.

Keywords: 3'-UTR; Alternative polyadenylation; COAD; NK cells; T cells; immunity.

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Conflict of interest statement

The authors declare no conflict of interest, financial or otherwise.

Figures

Fig. (1)
Fig. (1)
Flow chart of overall study design framework and analysis process. APA data from The Cancer Genome Atlas (TCGA) COAD (n =7692) was collected. APA events were evaluated using PDUI values, and the prognostically significant APA events were screened by LASSO Cox regression to construct a prognostic model. Then, prognostic model functions and possible regulatory genes of characteristic APA events were analyzed. Finally, the immune regulatory network based on APA regulatory genes was analyzed and established.
Fig. (2)
Fig. (2)
Construction of the prognostic model for APA events. (A) The top 10 APA events with prognostic significance. (B) The choice of lambda for LASSO regression. (C) Characteristic APA event selection for LASSO regression.
Fig. (3)
Fig. (3)
Relationship between the APA signature and clinical features of COAD. (A) The influence of the APA signature on the prognosis of COAD. The prognostic analysis of OS, DSS, DFI and PFI is presented from top to bottom. Abbreviations: OS: overall survival; DFI: disease-free interval; PFI: progression-free interval; DSS: disease-specific survival. (B) The relationship between the APA signature and COAD clinical information.
Fig. (4)
Fig. (4)
Functional analysis of the APA prognostic model. (A) Volcano plot of difference analysis between high and low expression groups. Red: high expression; Blue: low expression. (B) GSEA result of difference analysis, where the color represents the specific p value and higher-intensity blue color correlates with smaller p value. (C) Heatmap of immune cells and the APA model. (D) Relationship between tumor-related pathways and the APA prognostic model.
Fig. (5)
Fig. (5)
Overall landscape of APA regulatory genes. (A) Differential expression of APA regulatory genes in COAD (cancer vs. normal). (B) Relationship between APA regulatory genes and prognosis of COAD. Red: significant differences; gray: no significant differences. (C) Relationship between APA regulatory genes and COAD copy number variation. Red represents an increase in copy number, and blue represents a decline in copy number. (D) Analysis of mutations in APA regulatory genes.
Fig. (6)
Fig. (6)
Potential regulatory mechanisms of the APA prognostic model. (A) Analysis of COAD characteristic APA events regulated by regulatory genes. (B) The influences of APA events on gene expression.
Fig. (7)
Fig. (7)
APA regulatory genes-APA genes-immune cells regulatory network. Blue nodes: APA regulatory genes; Green nodes: APA genes; Orange nodes: immune cells.
See this image and copyright information in PMC

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