# Immunophenotyping of colon cancer for identification of potential antigens for colon cancer vaccines

**Authors:** Xuan Wang, Jingjiang Lai, Dawei Wang, Keyi Wei, Jing Yang

PMC · DOI: 10.3389/fonc.2025.1403256 · Frontiers in Oncology · 2025-04-07

## TL;DR

This study identifies CUL7, ENO2, and MPP2 as potential antigens for colon cancer mRNA vaccines and classifies colon cancer into three immune subtypes with distinct survival outcomes.

## Contribution

The study introduces a novel classification of colon cancer into three immune subtypes and identifies new potential antigens for mRNA vaccines.

## Key findings

- CUL7, ENO2, and MPP2 show significant associations with immune cell infiltration and survival in colon cancer.
- Three immune subtypes (C1-C3) were identified with distinct clinical and molecular features, including C2 having the best survival outcomes.
- RT-PCR and immunohistochemistry validated the expression of the identified antigens in colon cancer.

## Abstract

Colon cancer is a prevalent malignancy that significantly threatens human health. In recent years, mRNA cancer vaccines have demonstrated considerable potential and distinct advantages in colon cancer treatment. Thus, This study identifies CUL7, ENO2, and MPP2 as potential antigens for colon cancer mRNA vaccines. Through multi-omics analysis, we classify COAD into three immune subtypes (C1-C3) with distinct molecular and clinical features.

Data from TCGA and GEO databases were analyzed using bioinformatics tools. Prognostic indices were calculated with GEPIA2, and TIMER assessed antigen-presenting cell infiltration. Survival analysis was performed using Kaplan-Meier curves and Cox proportional hazards models. Immune subtypes were classified via non-negative matrix factorization (NMF) clustering, with k=3 determined by cophenetic correlation (0.92) and silhouette width (average = 0.85). Drug sensitivity, immune cell infiltration, and gene set variation were analyzed using R packages such as “pRRophetic,” CIBERSORT, and GSVA. Functional enrichment analysis was performed with GO, KEGG, and GSEA. Experimental validation included immunohistochemistry and RT-PCR to confirm gene expression.

Analysis of TCGA-COAD data revealed copy number variants in 16,354 genes, with CUL7, ENO2, and MPP2 showing significant antigen-presenting cell infiltration and associations with overall survival (OS) and relapse-free survival (RFS). Based on molecular mechanisms, cellular features, and clinical characteristics, colon cancer was categorized into three immune subtypes (C1, C2, and C3) distinct from Thorsson’s pan-cancer subtypes (C1-C6) in pathway enrichment, with the C2 subtype exhibited significantly longer overall survival (OS) than C1 and C3 (median OS: C2 = 68 months vs. C1 = 42 months, C3 = 37 months; log-rank P < 0.001). The distribution of these immune subtypes showed disparities in immune patterns, and a correlation between key components and immune cells was observed. Prognostic correlation analysis indicated that the gray and turquoise modules were closely linked to colorectal cancer prognosis. Additionally, RT-PCR confirmed the association of CUL7, ENO2, and MPP2 expression levels with colon cancer.

CUL7, ENO2, and MPP2 were identified as potential antigens for colon cancer mRNA vaccines, with MPP2 showing particular immunological relevance. This study provides a foundation for mRNA vaccine development and patient stratification for vaccination in colon cancer.

## Linked entities

- **Genes:** CUL7 (cullin 7) [NCBI Gene 9820], ENO2 (enolase 2) [NCBI Gene 2026], MPP2 (MAGUK p55 scaffold protein 2) [NCBI Gene 4355]
- **Diseases:** colon cancer (MONDO:0002032)

## Full-text entities

- **Genes:** ENO2 (enolase 2) [NCBI Gene 2026] {aka HEL-S-279, NSE}, CUL7 (cullin 7) [NCBI Gene 9820] {aka 3M1, CUL-7, KIAA0076, dJ20C7.5}, MPP2 (MAGUK p55 scaffold protein 2) [NCBI Gene 4355] {aka DLG2}
- **Diseases:** COAD (MESH:D029424), cancer (MESH:D009369), Colon cancer (MESH:D015179)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

13 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12009704/full.md

## References

43 references — full list in the complete paper: https://tomesphere.com/paper/PMC12009704/full.md

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Source: https://tomesphere.com/paper/PMC12009704