Dataset Information

Potential Impact of ALKBH5 and YTHDF1 on Tumor Immunity in Colon Adenocarcinoma.

ABSTRACT:

Background

ALKBH5 and YTHDF1 are regarded as the eraser and reader, respectively, in N6-methyladenosine (m6A) modification. Recently, immune contexture has been drawing increasing attention in terms of the progression and treatment of cancers. This study aimed to determine the relationship between ALKBH5/YTHDF1 and immunological characteristics of colon adenocarcinoma (COAD).

Methods

Expression of ALKBH5 and YTHDF1 was investigated across TCGA and GEO validated in our study. Patients with COAD were divided into two clusters using consensus clustering based on the expression of ALKBH5 and YTHDF1. We then compared their clinical characteristics and performed gene set enrichment analysis (GSEA) to identify the functional differences. Immune infiltration analyses were conducted using ESTIMATE, CIBERSORT, and ssGSEA. In addition, we evaluated the expression of the targets of immune checkpoint inhibitors (ICIs) and calculated the tumor mutation burden (TMB) of the tumor samples. Weighted gene co-expression network analysis (WGCNA) was used to identify the genes related to both ALKBH5/YTHDF1 expression and immunity. GSE39582 was utilized for external validation of immunological features between the two clusters.

Results

Cluster 2 had high expression of ALKBH5 and lesser so of YTHDF1, whereas Cluster 1 had just the reverse. Cluster 1 had a higher N stage and pathological stage than Cluster 2. The latter had stronger immune infiltration, higher expression of targets of ICIs, more TMB, and a larger proportion of deficiency in mismatch repair-microsatellite instability-high (dMMR-MSI-H) status than Cluster 1. Moreover, WGCNA revealed 14 genes, including PD1 and LAG3, related to both the expression of ALKBH5/YTHDF1 and immune scores.

Conclusions

ALKBH5 and YTHDF1 influence immune contexture and can potentially transform cold tumors into hot tumors in patients with COAD.

SUBMITTER: Yan G

PROVIDER: S-EPMC8165310 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Colon adenocarcinoma (COAD) is one of the diseases with the highest morbidity and mortality in the world. At present, immunotherapy has become a valuable method for the treatment of COAD. Tumor mutational burden (TMB) is considered to be the most common biomarker for predicting immunotherapy. According to reports, the mutation rate of COAD ranks third. However, whether these gene mutations are related to TMB and immune response is still unknown. Here, COAD somatic mutation data were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Bioinformatics methods were used to study the relationships among gene mutations, COAD survival prognosis, and tumor immune response. A total of 22 of the top 40 mutations in TCGA and ICGC databases were the same. Among them, the USH2A mutation was associated with high TMB and poor clinical prognosis. According to Gene Set Enrichment Analysis (GSEA) and the CIBERSORT algorithm, we determined that the USH2A mutation upregulates signaling pathways involved in the immune system and the antitumor immune response. In cases with a USH2A mutation, the immune score and MSI score of TCGA samples increased, the expression of immune checkpoint genes decreased significantly, and the TIDE score decreased significantly. Dependent on the presence or absence of a USH2A mutation, TCGA COAD samples were analyzed for differentially expressed genes, 522 of which were identified. Using a univariate Cox analysis and LASSO COX analysis of these differential genes, a prediction model was established, which established significant differences in the infiltration of immune cells, immune checkpoint gene expression, immune score, MSI score, TMB, and TIDE in patients in high- and low-risk groups. In conclusion, mutation of USH2A is frequent in COAD and is related to an increase in TMB and the antitumor immunity. The differential genes screened by USH2A mutation allowed the construction of a risk model for predicting the survival and prognosis of cancer patients, in addition to providing new ideas for COAD immunotherapy.