PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
April 19, 2026Cancer Research0 citations

Abstract LB172: RNA-seq-based molecular and microenvironmental stratification of colorectal cancer in a Korean real-world cohort

View Full Paper
JYJinseon YooKSKyu Jin SongJKJae‐Joong Kim

Key Points

  • To achieve precise molecular stratification of colorectal cancer by analyzing transcriptomic profiles and microenvironmental factors.
  • Analyzed 476 fresh-frozen colorectal specimens, including tumors and adjacent normal tissues.
  • Integrated RNA sequencing data with clinicopathological variables and survival outcomes.
  • Conducted computational analyses to identify biologically distinct molecular subgroups.
  • Identified distinct transcriptional pathways differentiating tumor and normal tissues.
  • Defined four molecular subgroups based on tumor microenvironment signatures.
  • Observed significant differences in clinical outcomes among subgroups, with immune-fibroblast-enriched tumors showing the worst prognosis.

Abstract

Abstract Colorectal cancer (CRC) continues to represent a major cause of cancer-related death, emphasizing the limitations of traditional staging systems in capturing clinically relevant biological heterogeneity. To enable more precise molecular stratification, we analyzed comprehensive transcriptomic profiles from 476 fresh-frozen colorectal specimens, including tumor and adjacent normal tissues, obtained from a real-world Korean cohort treated at Samsung Medical Center (SMC). By integrating RNA sequencing-derived expression data with clinicopathological variables and survival outcomes, we observed distinct transcriptional pathways separating tumor and normal tissues. Tumor samples displayed coordinated activation of pathways governing cell cycle progression, extracellular matrix (ECM) organization, and DNA damage response (DDR), whereas normal tissues were predominantly characterized by metabolic pathway activity. The enrichment of DNA repair-related pathways in tumors prompted focused evaluation of homologous recombination signaling, and homologous recombination deficiency (HRD) was quantified using a transcriptome-based scoring framework. Computational analyses incorporating tumor microenvironment (TME) signatures resolved four biologically distinct molecular subgroups. Tumors enriched for fibroblasts or combined immune-fibroblast features showed strong correspondence with the stromal-dominant CMS4 subtype, while immune-dominant tumors aligned preferentially with CMS1. Deconvolution of cellular composition and immune profiling revealed pronounced subgroup-specific differences in immune infiltration, stromal activation, and HRD burden. Importantly, these transcriptome-defined subgroups demonstrated significant divergence in clinical outcomes, with immune-fibroblast-enriched tumors exhibiting the most unfavorable prognosis independent of pathological stage. Moreover, combined assessment of HRD scores and CRC-relevant immune gene expression enabled further refinement of patient risk stratification into biologically coherent and clinically meaningful categories. In summary, this large-scale real-world transcriptomic analysis of Korean CRC patients delineates clinically actionable molecular subgroups defined by distinct TME architecture and homologous recombination status, underscoring the value of integrating RNA-seq-derived HRD and microenvironmental profiling to improve prognostic assessment and guide personalized therapeutic strategies in CRC. Citation Format: Jinseon Yoo, Kyu Jin Song, Jimin Kim, Keeok Haam, Soobok Joe, Jongbum Jeon. RNA-seq-based molecular and microenvironmental stratification of colorectal cancer in a Korean real-world cohort abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts) ; 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86 (8Suppl): Abstract nr LB172.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Yoo et al. (2026) studied this question.

synapsesocial.com/papers/69e4734c010ef96374d8f25fhttps://doi.org/10.1158/1538-7445.am2026-lb172
Ask AI
Helpful
Bookmark
Share
View Full Paper