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Uncovering Stage-Specific Biomarkers in Colorectal Cancer: RNA-Seq Analysis of Adenoma and Carcinoma Progression

ABSTRACT: Colorectal cancer (CRC) progresses through distinct molecular mechanisms, tumor stage playing a pivotal role in prognosis and treatment outcomes. Despite advances in CRC treatment, the lack of stage-specific biomarkers limits the potential for reliable diagnostic and treatment strategies. This study aims to identify stage-specific gene expression profiles and the molecular mechanisms through comparative transcriptomic analysis of adenoma (n = 10), carcinoma in situ (n = 8) and adenocarcinoma (n = 11) samples. Utilizing RNA-seq from FFPE samples processed with absGSEA, we identified significant cellular pathways influenced from each CRC stage. In adenocarcinoma, pathways related to transcriptional co-regulatory mechanisms and protein kinase functional activity, critical for tumor growth and metastasis, were significantly enriched compared to adenoma. While apoptotic processes and Wnt signaling pathways were prominent in carcinoma in situ compared to adenoma samples. Extracellular matrix organization pathway was significantly enriched between adenocarcinoma and carcinoma in situ. Transcriptomics data and bioinformatics analysis revealed that in adenocarcinoma cohorts, genes such as COL1A2, CEBPZ, MED10, and PAWR were overexpressed, highlighting their potential roles in advanced disease progression. Conversely, in adenoma samples, the overexpression of genes such as ARRB1, CTBP1, and CTBP2 underscores their involvement in early tumorigenesis. COL1A2 and CEBPZ were implicated in extracellular matrix remodeling and transcriptional regulation respectively, while and ARRB1 were associated with early tumorigenesis. These findings highlight the complexity of gene regulation in CRC and provide a foundation for developing stage-specific diagnostic and prognostic biomarkers, and to ultimately improve therapeutic strategies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE289499 | GEO | 2025/03/06

REPOSITORIES: GEO

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Project description:Background. Most colorectal cancers (CRC) arise in a progression through adenoma to carcinoma phenotypes as a consequence of altered genetic information. Clinical progression of CRC may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence. Methodology/Principal Findings. Studies were performed on normal mucosa, adenoma, and CRC samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. RNA was isolated from 105 macro- and 40 microdissected specimens. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data were generated using two normalization algorithms: MAS5 and GCRMA with LVS. The data were evaluated using pair-wise comparisons and data decomposition into SVD modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Based on a consensus of the results obtained by two tissue handling procedures, two normalization algorithms, and two probe set sorting criteria, we identified six KEGG signaling and metabolic pathways (cell cycle, DNA replication, p53 signaling pathway, purine metabolism, pyrimidine metabolism, and RNA polymerase) that are significantly altered in both macro- and microdissected tumor samples compared to normal colon. On the other hand, pathways altered between benign and malignant tumors were identified only in the macrodissected tissues. Conclusion/Significance. Multidirectional analyses of microarray data allow the identification of essential signaling alterations underlying CRC development. Although the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results. Gene expression profiles of 40 tissue samples representing distant full-thickness normal colon, normal colon mucosa dissected from tumor, adenoma, and carcinoma. Gene expression profiles of 105 tissue samples representing colon carcinomas, adenocarcinomas, and normal colon samples.

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Uncovering Stage-Specific Biomarkers in Colorectal Cancer: RNA-Seq Analysis of Adenoma and Carcinoma Progression

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