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2026 conference-abstract

Abstract 5430: Allostatic load connects tumor genomics, disease trajectory, and pre-diagnosis wearable activity.

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Abstract Background: Allostatic load (AL), a composite index of physiological stress from routine labs and vitals, reflects multisystem strain and predicts survival in cancer. Building on prior validation of cancer-modulated AL (cmAL), we examined how cmAL varies across disease states, relates to tumor genomics, and aligns with wearable-measured activity before diagnosis. Methods: We analyzed 12,689 adults treated at MSK with pre-treatment labs and vitals across NSCLC, colorectal, prostate, ovarian, breast, pancreatic, endometrial, and bladder cancers. cmAL was computed from ten cardiovascular, metabolic, renal, and immune biomarkers and compared across disease phases using rank-sum tests with multiple-testing correction. Per-cancer-type genomic models used multivariable logistic regression relating cmAL to recurrent oncogenic alterations while adjusting for clinical covariates and comorbidity burden. Wearable activity was evaluated in 77 MSK patients (Apple HealthKit) and 1,867 All of Us participants (Fitbit) using median daily step counts across cmAL levels, Spearman correlation, and continuous trend tests. Pre-diagnosis steps were summarized using a 90-day window before first cancer diagnosis. Results: cmAL decreased during remission (median change -0.42, p<0.001) and increased with progression (median change +0.61, p<0.001), with the highest values observed within six months of death (p<1×10-40). Higher cmAL correlated with cardiometabolic comorbidity (diabetes OR=0.74; renal OR=0.54). In NSCLC, higher cmAL was less common in patients with EGFR mutations and more common in those with KRAS mutations. Across both wearable datasets, higher cmAL was linked to lower pre-diagnosis activity. In the MSK cohort, median daily steps declined from 4,914 at (cmAL=1) to 1,092 at (cmAL=5) (Spearman ρ=-0.388, p=0.0005). In All of Us, median steps declined from 6,276 (cmAL=1) to 4,091 (cmAL=5) (ρ=-0.248, p<0.0001), demonstrating reproducibility in a population cohort. Conclusions: cmAL increases with disease progression and quantifies cumulative physiologic strain across body systems. Elevated cmAL is associated with specific genomic patterns in NSCLC, greater comorbidity burden, and lower pre-diagnosis step counts in both institutional and population cohorts. These findings support cmAL as a scalable and potentially modifiable biomarker integrating molecular, physiologic, and behavioral domains in real-world cancer survivorship. Citation Format: Christopher J. Fong, Kaicheng U, Cheryl Phua, Xuechun Bai, Karl Pichotta, Kathryn Tsai, Anzhi Chen, Meixuan Zhang, Jie Yu, Whitney Underwood, Chenlian Fu, Michele Waters, Sanna Goyert, Adam Schoenfeld, Nikolaus Schultz, Justin Jee, Jessica Scott, Luke Pike, Jian Carrot-Zhang. Allostatic load connects tumor genomics, disease trajectory, and pre-diagnosis wearable activity [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 5430.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Abstract 5430: Allostatic load connects tumor genomics, disease trajectory, and pre-diagnosis wearable activity.
Date Crossref
03/04/2026
Éditeur
American Association for Cancer Research (AACR)
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

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Les sujets associés

Cardiovascular Health and Risk FactorsFerroptosis and cancer prognosisRadiomics and Machine Learning in Medical Imaging

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