Integrated genomic and transcriptomic profiling reveals distinct molecular features of colorectal cancer in an Indian cohort
Year: 2026
Type: article
Study design: Observational Study
Abstract: Colorectal cancer (CRC) exhibits substantial molecular heterogeneity, requiring integrative approaches to define clinically meaningful tumour subtypes. Although large international consortia have extensively profiled CRC, global datasets underrepresent many ethnicities. Understanding how local tumors align with/diverge from globally characterized cohorts is essential to contextualize disease biology and refine precision oncology strategies. This study was designed as a comparative, hypothesis-generating analysis benchmarked against a Global Genomic Landscape (GGL) of 2,023 CRC tumors. Whole exome and transcriptome sequencing was performed on pathologically confirmed tumors (N = 20) and normal tissues (N = 5) using the Illumina HiSeqX. Bioinformatic pipelines identified somatic variants and dysregulated genes, which were compared with GGL data. We identified 814 dysregulated genes and ∼16,440 somatic variants. While the single base substitution (SBS) profile was similar to GGL, one double base substitution signature (DBS17) and two insertion-deletion signatures (ID7, ID19) were unique to our cohort. Six driver genes (ACVR2A/BAX/PRDM2/RGS12/RNF43/TCF7L2) with recurrent variants were observed in our cohort. Only three genes with emerging roles in CRC (MET/SOX9/TGIF1) overlapped across dysregulation, somatic variation, and GGL datasets. Indel hotspot variants in EIF2B3 (p.Ala151GlnfsTer57) and UBR5 (p.Glu2121LysfsTer28) were exclusive in non-survivors. The prevalence of canonical Western driver mutations (APC, TP53, KRAS, PIK3CA, SMAD4) was markedly lower in our cohort. Few drug-targetable genes overlapped with GGL; however, several approved or high-confidence targets were identified. Compared with the global genomic landscape, our findings suggest potential population-associated differences in driver architecture and therapeutic opportunities that warrant validation in larger independent Indian cohorts.
Source: Neoplasia
Language: English
Subfield: Pathology and Forensic Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,530
OpenAlex ID: W7222733128
