Abstract C032: Visceral fat area and age-related differences in visceral adipose tissue gene expression: implications for early-onset colorectal cancer
Bibliographic record
Abstract
Abstract Introduction: Obesity is a known risk factor for colorectal cancer (CRC). Specifically, visceral adipose tissue (VAT) can contribute to tumor development through mechanisms such as adipokine secretion and insulin resistance. With aging, changes in VAT composition are accompanied by shifts in its metabolic and immune functions, potentially altering its interaction with adjacent tumors. These age-related differences may influence CRC development and progression and give rise to early-onset CRC (EOCRC), defined as those diagnosed before the age of 50. To explore this, we examined how visceral fat area (VFA), used as a validated proxy for total VAT volume, relates to VAT gene expression in CRC patients, and whether these associations differed by age at diagnosis. Methods: Tumor-adjacent VAT was collected in 88 stage I-III CRC patients undergoing primary surgery as part of the ColoCare Study at Huntsman Cancer Institute (HCI), University of Utah, and Heidelberg University Hospital, Germany. RNA sequencing was performed on VAT at the HCI genomics core. VFA was quantified from computed tomography (CT) scans, derived from a single-slice CT image at the L3 level, and categorized, as based on median VFA value, [CU1] as low (<196 cm2) or high (≥196 cm2). We assessed differential[CU2] gene expression in relation to high vs. low VFA within each age stratum (<50 years and ≥50 years), adjusting for study site, sex, tumor stage, and tumor site. Ranked genes were analyzed with GSEA software to identify enriched gene sets and pathways. Results: Of 88 patients, 10 were EOCRC (median age 46, SD 8.3) and 78 w[PE3] [PE4] [PE5] ere later-onset CRC (LOCRC, median age 67, SD 15.8). Among EOCRC patients, 60% had low VFA (<196 cm2), while in the LOCRC group, 47% had low VFA (≥196 cm2). GSEA identified several immune-related pathways positively enriched among genes upregulated in high vs low VFA within both age strata. Notably, Hematopoietic Cell Lineage was concordantly enriched in both EOCRC and LOCRC. Age-specific patterns emerged: extracellular matrix and cytokine-cytokine receptor interaction pathways were predominantly enriched in LOCRC patients, whereas adaptive immune signaling and immunodeficiency pathways were specific to EOCRC patients. Conclusion: High VFA is associated with distinct VAT gene expression profiles in CRC patients, and age-specific pathways emerged. These findings indicate that VAT may modulate CRC biology in an age-dependent manner, potentially contributing to the development of EOCRC. Citation Format: Patricia A. Erickson, Victoria M. Bandera, Bettina K. Budai, Tengda Lin, Nicole C. Loroña, Caroline Himbert, Sheetal Hardikar, Mmadili N. Ilozumba, Jeffrey T. Yap, Elaine M. Glenny, Aik C. Tan, Jennifer Ose, Christy A. Warby, Olena Aksonova, Tobias Nonnenmacher, Chris Stubben, David Nix, Kenneth Boucher, Peter Schirmacher, Ildiko Strehli, Megan Mclaws, Alejandro Sanchez, Jolanta Jedrzkiewicz, Lyen C. Huang, Jessica N. Cohan, Alexander Brobeil, Hans-Ulrich Kauczor, Christoph Kahlert, Victoria Damerell, Erin M. Siegel, Doratha A. Byrd, Adetunji T. Toriola, David Shibata, Christopher I. Li, Jane C. Figueiredo, Jatin Roper, Biljana Gigic, Stephen Hursting, Cornelia M. Ulrich. Visceral fat area and age-related differences in visceral adipose tissue gene expression: implications for early-onset colorectal cancer [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 C032.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".