Abstract 5075: Integrated clinicopathologic, genomic and transcriptomic characterization of gastric cancer by race/ethnicity in a national multi-institutional cohort

Abstract Background: Although gastric cancer outcomes vary by race/ethnicity, a molecular basis for these differences has not been fully elucidated. To address this gap, we used the Tempus Lens Platform (Tempus AI, Inc., Chicago, IL) to query the multimodal de-identified database in order to establish and subsequently analyze a cohort of patients with gastric adenocarcinoma who underwent germline and tumor testing using xT (DNA) and xR (RNA). Methods: Patients were categorized by R/E. RNA-seq data were normalized as transcripts per million (TPM) and reported as log2(TPM+1). Single-sample Gene Set Enrichment Analysis (ssGSEA) using Hallmark gene sets was used to compare cell signaling pathway activity. Real-world overall survival (rwOS) was defined as the time from biopsy to death or last known follow-up. rwOS survival curves were estimated using the Kaplan Meier (KM) approach and differences tested using log-rank tests. Hazard ratios (HR) were calculated using Cox proportional hazard models. Results: Among 1,842 patients with reported race/ethnicity data, 1,186 (64%) identified as White, 327 (17.7%) as Hispanic/Latino (HL), 217 (11.8%) as Black or African American (AA) and 112 (6.1%) as Asian. In the multivariable Cox model, compared to White patients, rwOS was longer for HL (HR 0.65, 95% CI 0.48-0.88, p=0.005) and Asian (HR 0.64, 95% CI 0.41-0.98, p=0.042) patients. Asian patients had longer median rwOS compared to White patients (19 vs 10.9 months, log-rank p<0.001). Compared to White patients, HL patients were younger at diagnosis (median 57 vs 67 years, p<0.001) and a greater proportion were female (45% vs 28%, p<0.001). Tumor grade, microsatellite instability, tumor mutational burden, and CLDN18.2 expression differed significantly across groups (all p<0.01), whereas HER2 and PD-L1 status did not. At the genomic level, the frequency of somatic alterations in TP53 (57% HL vs 75% White), CDKN2A (11% Asian vs 21% White), CDH1 (6.9% AA vs 16% HL) differed between groups (all p,q<0.001). Pathogenic germline variants were identified in 10.1% of AA, 10.7% of Asian, 10.7% of HL, and 15.8% of White patients, most commonly involving HDAC2, ATR, ATM, and MUTYH, respectively. Transcriptomic profiling via ssGSEA revealed an inflammatory pathway activation among HL and Asian patients, with a significant increase in IL6/JAK/STAT3 and IFN-γ signaling vs White patients (all q<0.001). HL patients also demonstrated greater enrichment of the IL2/STAT5, TNFα and complement response pathways vs White patients (q<0.001). Conclusion: This study represents the largest and most diverse clinico-genomic analysis of gastric cancer. Collectively, these findings highlight distinct clinical presentations, molecular alterations and survival outcomes by race/ethnicity, promoting the critical need for broad molecular testing to inform precision cancer care. Citation Format: Kyle D. Klingbeil, Sinead Cullina, Natalie N. Martinez, Mariah B. Blegen, Kyla E. Wright, R. Vanessa Mora Molina, Ami Hayashi, Adam J. Dugan, Unnati Jariwala, Stamatina Fragkogianni, Jonathan Boiarsky, Lee S. Rosen, Mark D. Girgis, Brian E. Kadera. Integrated clinicopathologic, genomic and transcriptomic characterization of gastric cancer by race/ethnicity in a national multi-institutional cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5075.

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Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-5075
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Cancer Genomics and Diagnostics
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article

Abstract 5075: Integrated clinicopathologic, genomic and transcriptomic characterization of gastric cancer by race/ethnicity in a national multi-institutional cohort

Unnati Jariwala, Kyla Wright, Adam Dugan, Lee S. Rosen et al.
Cancer Research
Cancer Genomics and Diagnostics
article

Abstract 5075: Integrated clinicopathologic, genomic and transcriptomic characterization of gastric cancer by race/ethnicity in a national multi-institutional cohort

Unnati Jariwala, Kyla Wright, Adam Dugan, Lee S. Rosen, Mark D. Girgis, Ami Hayashi, Natalie Martinez, Brian E. Kadera, Sinéad Cullina, Kyle D. Klingbeil, Stamatina Fragkogianni, Mariah B. Blegen, Jonathan Boiarsky, R. Vanessa Mora Molina
article en

Abstract

Abstract Background: Although gastric cancer outcomes vary by race/ethnicity, a molecular basis for these differences has not been fully elucidated. To address this gap, we used the Tempus Lens Platform (Tempus AI, Inc., Chicago, IL) to query the multimodal de-identified database in order to establish and subsequently analyze a cohort of patients with gastric adenocarcinoma who underwent germline and tumor testing using xT (DNA) and xR (RNA). Methods: Patients were categorized by R/E. RNA-seq data were normalized as transcripts per million (TPM) and reported as log2(TPM+1). Single-sample Gene Set Enrichment Analysis (ssGSEA) using Hallmark gene sets was used to compare cell signaling pathway activity. Real-world overall survival (rwOS) was defined as the time from biopsy to death or last known follow-up. rwOS survival curves were estimated using the Kaplan Meier (KM) approach and differences tested using log-rank tests. Hazard ratios (HR) were calculated using Cox proportional hazard models. Results: Among 1,842 patients with reported race/ethnicity data, 1,186 (64%) identified as White, 327 (17.7%) as Hispanic/Latino (HL), 217 (11.8%) as Black or African American (AA) and 112 (6.1%) as Asian. In the multivariable Cox model, compared to White patients, rwOS was longer for HL (HR 0.65, 95% CI 0.48-0.88, p=0.005) and Asian (HR 0.64, 95% CI 0.41-0.98, p=0.042) patients. Asian patients had longer median rwOS compared to White patients (19 vs 10.9 months, log-rank p<0.001). Compared to White patients, HL patients were younger at diagnosis (median 57 vs 67 years, p<0.001) and a greater proportion were female (45% vs 28%, p<0.001). Tumor grade, microsatellite instability, tumor mutational burden, and CLDN18.2 expression differed significantly across groups (all p<0.01), whereas HER2 and PD-L1 status did not. At the genomic level, the frequency of somatic alterations in TP53 (57% HL vs 75% White), CDKN2A (11% Asian vs 21% White), CDH1 (6.9% AA vs 16% HL) differed between groups (all p,q<0.001). Pathogenic germline variants were identified in 10.1% of AA, 10.7% of Asian, 10.7% of HL, and 15.8% of White patients, most commonly involving HDAC2, ATR, ATM, and MUTYH, respectively. Transcriptomic profiling via ssGSEA revealed an inflammatory pathway activation among HL and Asian patients, with a significant increase in IL6/JAK/STAT3 and IFN-γ signaling vs White patients (all q<0.001). HL patients also demonstrated greater enrichment of the IL2/STAT5, TNFα and complement response pathways vs White patients (q<0.001). Conclusion: This study represents the largest and most diverse clinico-genomic analysis of gastric cancer. Collectively, these findings highlight distinct clinical presentations, molecular alterations and survival outcomes by race/ethnicity, promoting the critical need for broad molecular testing to inform precision cancer care. Citation Format: Kyle D. Klingbeil, Sinead Cullina, Natalie N. Martinez, Mariah B. Blegen, Kyla E. Wright, R. Vanessa Mora Molina, Ami Hayashi, Adam J. Dugan, Unnati Jariwala, Stamatina Fragkogianni, Jonathan Boiarsky, Lee S. Rosen, Mark D. Girgis, Brian E. Kadera. Integrated clinicopathologic, genomic and transcriptomic characterization of gastric cancer by race/ethnicity in a national multi-institutional cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5075.

Cancer ResearchVol. 86(7_Supplement)
APLA Health (US), UCLA Health (US), Tempus Labs (United States) (US)
Openalex Percentile: Top 8%
Cancer Genomics and Diagnostics
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