Comprehensive Analysis of Gene Expression Profiles Identifies a P4HA1-Related Gene Panel as a Prognostic Model in Colorectal Cancer Patients

Identification of a novel Immune-Related prognostic model for patients with colorectal cancer based on 3 subtypes

BACKGROUND

The mechanism of immunity in the development of colorectal cancer (CRC) has been studied in-depth, but knowledge of its role in the treatment of CRC is limited.

OBJECTIVE

This study aimed to classify CRC based on immunology and construct an immune-related prognostic model.

METHODS

Nine expression profile datasets of CRC, comprising 1640 samples, were downloaded from the NCBI GEO database. Immune infiltration of CRC was estimated using 5 algorithms. Based on the relative infiltration level of immune cells, immune score, and stromal score, immunosubtype analysis of tumors was conducted. Differentially expressed genes (DEGs) between the two subtypes were screened, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Hematoxylin eosin (HE) staining, immunohistochemical (IHC) staining and qPCR were used to verify the correlation between DEGs and differentiation degree of cancer and the expression of Ki67. Subsequently, a risk signature was constructed based on the least absolute shrinkage and selection operator (LASSO) model.

RESULTS

Based on the infiltration level, immune score, and stromal score of each immune cell, CRC was divided into three immune cell subtypes. Most immune checkpoint genes showed highly significant differences among the three cell subtypes, and most of the co-stimulatory and co-inhibitory molecules were lower in cluster 1 and the highest in cluster 3. Next, 50 common DEGs were determined from the intersections of the different subtypes. Among these common DEGs, 25 were identified to be relevant to the prognosis of CRC patients. The mRNA expressions of C5orf46, CYP1B1, MIR100HG, SFRP2 and CXCL13 was related to clinical prognostic indicators. Finally, these 5 DEGs were included in a prognostic risk signature model, which effectively identified high-risk groups among CRC patients in both the training and validation sets.

CONCLUSION

In this study, CRCs were divided into three subtypes based on immunology, and the different subtypes led to different prognosis. Additionally, a prognostic model was constructed based on five immune-related DEGs to distinguish the three subtypes.

A systematic analysis of C5ORF46 in gastrointestinal tumors as a potential prognostic and immunological biomarker

Background: Chromosome 5 open reading frame 46 (C5ORF46), also known as antimicrobial peptide with 64 amino acid residues (AP-64) and skin and saliva-secreted protein 1 (SSSP1), belongs to the family of open reading frame genes and encodes a small exosomal protein. C5ORF46 has been implicated in antibacterial activity and associated with patient prognosis in pancreatic cancer, colorectal cancer, and stomach cancer. These findings highlight the importance of C5ORF46 in gastrointestinal (GI) tumor inception and development. However, the prognostic and immunological value of C5ORF46 in human GI tumors remains largely unknown. In this study, we sought to explore the potential value of C5ORF46 in GI tumor prognosis and immunology.

Method: RNA sequencing (RNA-seq) was performed on the tumor and tumor-adjacent normal samples we collected to identify potential target genes for GI tumors. Apart from our RNA-seq data, all original data were downloaded from The Cancer Genome Atlas (TCGA) database and integrated via Strawberry Perl (v 5.32.0) and R (v 4.1.1). The differential expression of C5ORF46 was examined with Oncomine, Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), Cancer Cell Line Encyclopedia (CCLE), the Human Protein Atlas (HPA) and TCGA databases. The c-BioPortal database was used to investigate the genomic alterations of C5ORF46. The effect of C5ORF46 on prognosis and clinical phenotypes was explored via bioinformatics analyses on the TCGA and GEPIA databases. We used the bioinformatics analyses based on the TCGA database to analyze tumor mutational burden (TMB), microsatellite instability (MSI), tumor immune cell infiltration, and the correlations between C5ORF46 expression and several immune-related genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was carried out via the DAVID website and presented as bubble charts using ShengXinRen online tools. Gene set enrichment analysis (GSEA) was performed using R scripts based on data downloaded from the GSEA website. Immunohistochemistry (IHC) was used to validate the expression of C5ORF46 in GI tumors.

Results: The results of our RNA-seq data indicated a critical role for C5ORF46 in colon carcinogenesis. Consistently, we demonstrated that C5ORF46 was highly expressed in tumor tissues compared to normal tissues in human GI tumors. Moreover, a strong correlation was observed between C5ORF46 expression levels and patient prognosis, staging, TMB, MSI, and immune cell infiltration. Further, C5ORF46 presented as an important regulator in the tumor microenvironment (TME) and was active in the regulation of cancer immune functions. C5ORF46 is significantly correlated with genes regulating inflammation and immune responses.

Conclusion:C5ORF46 may serve as a biomarker for GI tumor prognosis and immunology. C5ORF46 could be a novel target for GI tumor immunotherapy.