Abstract PR005: Uncovering the Etiology of Early-Onset Gastric Cancer in Latinos Through Germline and Tumor Genomic Profiling
Bibliographic record
Abstract
Abstract Gastric cancer (GC) is a leading cancer health disparity among U.S. Latinos and a major cause of cancer mortality across Latin America. The incidence of early-onset GC (diagnosed before age 50) is increasing, yet the causes of this rise remain unclear. Potential contributors include the obesity epidemic and microbiome dysbiosis, but data specific to Latino populations are limited. We conducted a comprehensive genomic study of Latino GC patients, including whole-exome germline sequencing from 500 individuals and somatic tumor profiling from over 200 cases. Most patients were diagnosed before age 50. This study aimed to investigate both genetic and non-genetic etiologies of GC in Latinos. Germline analyses revealed a high prevalence of pathogenic variants in intermediate- to high-penetrance cancer susceptibility genes. We also identified several novel candidate genes and found evidence supporting a role for mosaicism in disease development. Somatic analyses showed that 82% of early-onset tumors belonged to the genetically stable subtype, compared to 28% in TCGA data. Significant differences in driver mutation frequencies were observed between early- and late-onset cases. Early-onset tumors had higher mutation rates in CDH1 (24% vs. 14%), ZNF99 (16% vs. 7%), and ROCK1 (11% vs. 4%), and lower rates in PIK3CA (3% vs. 14%) and RHOA (0% vs. 12%). Additionally, a history of Helicobacter pylori infection was associated with increased tumor mutation burden (TMB) in early-onset patients (p=0.023), but not in late-onset cases (p=0.76), suggesting exposure to more aggressive bacterial strains or a distinct tumor microbiome. Ongoing analyses are focused on mutational signatures and tumor microbiome variation and will be presented at the meeting. Together, these findings reveal key molecular differences between early- and late-onset GC in Latinos and suggest that non-genetic factors may play a significant role in the etiology of early-onset disease in this population. Citation Format: Luis G. Carvajal-Carmona. Uncovering the Etiology of Early-Onset Gastric Cancer in Latinos Through Germline and Tumor Genomic Profiling. [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 PR005.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".