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Abstract PR007: Tumor-adjacent visceral adipose tissue displays an altered transcriptomic landscape in early-onset colorectal cancer patients: Results from the ColoCare Study

2025· article· en· W4417203867 on OpenAlexaboutno aff
Victoria M. Bandera, Patricia Erıckson, Caroline Himbert, Elaine M. Glenny, Tengda Lin, Sheetal Hardikar, Aik Choon Tan, Jennifer Ose, Victoria Damerell, Christy A. Warby, Олена Федорівна Аксьонова, Chris Stubben, David A. Nix, Kenneth M. Boucher, Peter Schirmacher, Ildiko Strehli, Alejandro Sánchez, Jolanta Jedrzkiewicz, Lyen C. Huang, Vaia Florou, Jessica N. Cohan, Alexander Brobeil, Hans‐Ulrich Kauczor, Christoph Kahlert, Meghana Karchi, Elizabeth H. Wood, Doratha A. Byrd, Erin M. Siegel, Adetunji T. Toriola, David Shibata, Christopher I. Li, Jane C. Figueiredo, Biljana Gigic, Jatin Roper, Stephen D. Hursting, Cornelia M. Ulrich

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldMedicine
TopicLipid metabolism and disorders
Canadian institutionsnot available
Fundersnot available
KeywordsColorectal cancerTranscriptomeAdipose tissueParacrine signallingCancerBody mass indexEndocrine system

Abstract

fetched live from OpenAlex

Abstract Introduction: Obesity is commonly characterized by high levels of internal (visceral) adiposity. Visceral adipose tissue (VAT) is highly metabolically active and secretes proteins and metabolites in paracrine and endocrine signaling pathways. The phenotype of tumor-adjacent VAT may be an unexplored factor for risk and progression of early-onset colorectal cancer (EOCRC). Thus, we aimed to identify transcriptomic differences in tumor-adjacent visceral adipose tissue (VAT) in patients with EOCRC (<50 years at diagnosis) vs. those diagnosed with later-onset colorectal cancer (LOCRC; >50 years at diagnosis). Methods: VAT samples were collected from 332 patients with stage 0-III colorectal cancer enrolled in the ColoCare Study and recruited at Huntsman Cancer Institute (Utah), Heidelberg University Hospital (Germany), University of Tennessee Health Science Center (Tennessee), and Moffitt Cancer Center (Florida). Patients in our study were treatment naïve. VAT tissue was collected 1-3 cm from the colorectal tumor during surgery. VAT transcriptomes were measured with bulk RNA sequencing. Participants were classified as EOCRC vs. LOCRC. Normalized differentially expressed genes were identified (DESeq2), with analyses adjusted for sex, body mass index (BMI), study site, and tumor stage. Gene set enrichment analysis (GSEA) identified enriched pathways within the 2025 Hallmark gene sets. Significance was assessed using false discovery rate (FDR) p-adj<0.05. We replicated our analyses, adjusting for tumor site (colon vs. rectal), to account for potential differences by anatomical subgroup. Results: Patients with EOCRC (n=45, average age: 41±9 years) had higher disease stages compared to LOCRC patients (n=287, average age: 66±10 years) (EOCRC: 64% Stage III vs LOCRC: 39% Stage III) and similar BMI (EOCRC: 28.8±7.0 kg/m2 vs. LOCRC: 28.5±5.9 kg/m2). GSEA revealed 5 significantly enriched gene sets (FDR p-adj<0.05) in VAT when comparing EOCRC to LOCRC patients. VAT of EOCRC patients exhibited upregulation of immune pathways (Interferon Alpha Response, Interferon Gamma Response, TNFA Signaling via NF- κB), and fibrosis Hallmark pathways (Epithelial Mesenchymal Transition) (Normalized Enrichment Score (NES) >1.5, p-adj<0.05). Additionally, the VAT of patients with EOCRC showed upregulation of the glycolysis gene set relative to LOCRC (NES>1.5, p-adj<0.05). These pathways remained significantly enriched regardless of tumor site adjustment. Conclusions: VAT of patients with EOCRC displays a differential gene expression landscape relative to LOCRC patients, suggesting enhanced immune, fibrotic, and metabolic activity. These findings suggest that tumor-adjacent VAT physiology may be a relevant factor of the tumor-microenvironment in EOCRC progression. Citation Format: Victoria M. Bandera, Patricia Erickson, Caroline Himbert, Elaine M. Glenny, Tengda Lin, Sheetal Hardikar, Aik Choon Tan, Jennifer Ose, Victoria Damerell, Christy Warby, Olena Aksonova, Chris Stubben, David Nix, Kenneth Boucher, Peter Schirmacher, Ildiko Strehli, Megan Mclaws, Alejandro Sanchez, Jolanta Jedrzkiewicz, Lyen C. Huang, Vaia Florou, Jessica N. Cohan, Alexander Brobeil, Hans-Ulrich Kauczor, Christoph Kahlert, Meghana Karchi, Elizabeth H. Wood, Doratha A. Byrd, Erin M. Siegel, Adetunji T. Toriola, David Shibata, Christopher I. Li, Jane C. Figueiredo, Biljana Gigic, Jatin Roper, Stephen Hursting, Cornelia M. Ulrich. Tumor-adjacent visceral adipose tissue displays an altered transcriptomic landscape in early-onset colorectal cancer patients: Results from the ColoCare Study [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr PR007.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.084
GPT teacher head0.467
Teacher spread0.383 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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