The association of an exercise and rehabilitation clinical workflow algorithm on sedentary behavior and performance status from time of breast cancer diagnosis and throughout care

Breast Cancer Research and Treatment · 2026-04-17

Dietary Patterns Associated With Weight Loss Among Patients With Colorectal Cancer During the First 6 Months After Diagnosis: A Cross-Sectional Analysis From the ColoCare Study

Journal of the Academy of Nutrition and Dietetics · 2026-03-31

Identification of circulating lipidomic biomarkers of malnutrition risk among oncology patients in the Total Cancer Care (TCC) Study: a cross-sectional analysis

Journal of Nutrition · 2026-05-01

Abstract 3628: Obesity, metabolic dysfunction, and cancer risk: Uncovering the metabolic landscape

Cancer Research · 2026-04-03

Abstract As smoking rates decline, obesity has emerged as the leading modifiable risk factor for cancer in the United States. With obesity rates rising, especially in younger populations, its association with increased cancer risk is becoming more evident. There is an urgent need to understand the mechanisms underlying the relationship between obesity related metabolic dysregulation and cancer risk. This session highlights transdisciplinary research from the NCI-sponsored Metabolic Dysregulation and Obesity Cancer Risk (MeDOC) Consortium, which applies integrative methods across basic science, translational models, and clinical research. The MeDOC Consortium aims to discover mechanisms linking obesity and cancer to define markers that will enhance cancer risk prediction and identify targets for intervention. Metabolic alterations include immune dysfunction, metabolite signaling, hormonal imbalance, gut microbiome and adipocyte metabolism which can disrupt several downstream signaling pathways related to cancer initiation and progression. In our novel triangulation approach, we synthesize evidence from randomized controlled trials, mechanistic animal studies, and large-scale secondary data analyses establishing population-level patterns with clinical relevance to build a comprehensive metabolic atlas of cancer risk factors. Our research topics include the gut microbiome, lipid signaling, circulating metabolites, and local and systemic immune landscape, with a focus on how these processes influence the development of colorectal, breast, and liver cancers. We will highlight complementary research projects that bridge animal studies, human cohorts, and data science across diet, inflammation, microbiome, immunity, and obesity and weight loss. We will review current evidence and describe novel applications of systems biology with big data analytics featured as tools to integrate mechanistic insights and population-level patterns to establish robust causal frameworks. Early-career investigators will participate in an open discussion on emerging challenges and opportunities in obesity and cancer research. Specifically, we will report on the role of fatty acid binding protein, ceramides, bile acids, hormones, inflammation, and gut microbiome metabolites in cancers of the colon, breast, and liver, Through a translational lens, the session will emphasize how combining data science, bench studies, and interventional trials can accelerate the discovery of biomarkers, risk stratification tools, and actionable targets for cancer prevention or interception. Citation Format: Liza Makowski, Mary Playdon, Bing Li, Sonia L. Sugg, Scott A. Summers, Cornelia M. Ulrich, Deirdre Tobias, Edward L. Giovannucci, Xuehong Zhang, James R. Hébert, E. Angela Murphy, Joeseph F. Pierre, Loretta DiPietro, Lorne J. Hofseth, Marinella Temprosa. Obesity, metabolic dysfunction, and cancer risk: Uncovering the metabolic landscape [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 3628.

Abstract 5036: Ultra-processed foods and disease-free survival after colorectal cancer diagnosis: Findings from the Colocare Study

Cancer Research · 2026-04-03

Abstract Introduction: Ultra-processed foods (UPFs), industrially formulated products high in fat, sugar, and additives, account for ∼60% of daily calories in the United States. UPF intake has been linked to obesity, diabetes, and risk of some cancers, yet its impact on colorectal cancer (CRC) survivorship remains unclear. CRC survivors often face treatment-related dietary challenges and may rely on UPFs for convenience or to meet energy needs. Methods: We analyzed 418 stage I-III CRC patients in the ColoCare Study across four U.S. sites. Baseline demographic, lifestyle, and clinical data were collected. Dietary intake was assessed 6 months post-diagnosis using a food frequency questionnaire (FFQ) reflecting the prior six months. Foods were classified into one of four NOVA groups: unprocessed, minimally processed, processed, and ultra-processed foods (UPFs). We focused on UPF intake (NOVA Group 4), categorized into quartiles (Quartile 1 = lowest; Quartile 4 = highest) using two metrics: absolute intake (grams/day) and relative intake (percent of total grams/day). Cox proportional models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for disease-free-survival (DFS), adjusting for study site, age, sex, tumor site adjuvant treatment, BMI, and total caloric intake (kcal). Sensitivity analyses without BMI/kcal adjustment were also done. Results: Participants had a mean age of 58 years (standard deviation [SD]=13y) and a mean BMI of 29 kg/m2 (SD=6.8). 50% of participants were female, 49% were diagnosed with stage III CRC, and 59% with colon cancer. The median follow-up was 4 years (SD=2y). UPFs comprised ∼16% of the total daily food intake by weight. The mean Healthy Eating Index (HEI) score was 63 (SD=10), but scores decreased across quartiles of UPF consumption (p < 0.001). When evaluated by g/day, BMI differed by UPF quartiles (p=0.04), and a similar pattern was observed when quartiles of % g/day were used (p=0.12). UPF consumption, whether in g/day or percent of total intake, was not significantly associated with DFS. For g/day quartiles, HRs (95% CI) for quartiles 2-4 vs 1 were 0.92 (0.52-1.65), 0.88 (0.47-1.62), and 0.88 (0.45-1.74). For percentage-based quartiles, HRs were 1.12 (0.61- 2.09), 1.02 (0.54-1.93), and 1.27 (0.70-2.30). Results were consistent in both unadjusted models and those without BMI/kcal adjustment. Discussion: In this large, multi-center cohort, UPF intake was common among CRC survivors and associated with lower diet quality. However, UPF consumption was not associated with DFS, regardless of whether intake was measured in g/day or percentage of total intake. Modest differences in HR direction likely reflect how absolute versus relative intake captures dietary patterns. These findings offer important insights into post-diagnosis diet and cancer outcomes. Citation Format: Patricia A. Erickson, Rachel Hoobler, Victoria Maria Bandera, Victoria Damerell, Ildiko Strehli, Megan Mclaws, Lyen Huang, Jessica N. Cohan, Erin Siegel, Doratha Armenthus Byrd, Adetunji T. Toriola, David Shibata, Christopher I. Li, Jane C. Figueiredo, Biljana Gigic, Mary Playdon, Sheetal Hardikar, Cornelia M. Ulrich. Ultra-processed foods and disease-free survival after colorectal cancer diagnosis: Findings from the Colocare Study [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 5036.

Metabolomic profiling of genotype-derived ABO blood group, secretor status, and Lewis antigens and association with pancreatic ductal adenocarcinoma risk

American Journal of Epidemiology · 2026-03-10

The ABO locus is associated with pancreatic ductal adenocarcinoma (PDAC). Potential metabolic mechanisms underlying these associations have not been investigated. We examined associations between genotype-derived ABO blood group (rs505922 and rs8176746) and 1478 pre-diagnostic serum metabolites in 4042 participants from eight nested case-control studies within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study using linear regression and fixed-effect meta-analysis. We then examined associations between the identified ABO-associated metabolites and PDAC in two nested case-control studies (493 cases, 640 controls) using logistic regression and evaluated metabolite mediation of the ABO-PDAC association. Non-O and A (versus O) blood groups were associated with 13 and 20 metabolites, respectively, at false discovery rate < 0.20, with nine in common. The ABO-associated metabolites, sphingosine (non-O: β = 0.15), aspartate (A: β = -0.11), and aspartylphenylalanine (A: β = -0.16) were positively, and fibrinopeptide B (1-13) (non-O: β = 0.13; A: β = 0.21) was inversely associated with PDAC (P < 0.05). Non-O (OR = 1.50, 95% confidence interval [CI] = 1.16-1.94) and A (OR = 1.46, 95%CI = 1.10-1.92) (versus O) blood groups were associated with PDAC (OR = 0.96-1.07 per SD change log10-metabolite), however none significantly mediated the association between ABO blood group and PDAC. Our results suggest the ABO-associated metabolites are independent risk factors for PDAC.

Multi-metabolite scores of alignment with the 2018 World Cancer Research Fund (WCRF)/ American Institute for Cancer Research (AICR) Cancer Prevention Recommendations in the Interactive Diet and Activity Tracking in AARP (IDATA) Study

Journal of Nutrition · 2026-05-01

Abstract 2316: Circulating lipid and bile acid metabolites as predictors of colorectal cancer risk: A multi-cohort metabolomics meta-analysis

Cancer Research · 2026-04-03

Abstract Background: Metabolic dysregulation has been implicated in colorectal cancer (CRC) development but not fully characterized. We conducted a large-scale metabolomics meta-analysis to identify circulating metabolites associated with future CRC risk across heterogeneous populations. Methods: We harmonized pre-diagnostic metabolomic and covariate data from seven prospective cohorts: the Cancer Prevention Study II Nutrition Cohort (CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), the Women’s Health Initiative Metabolomics in Nutrition Study (WoMIN), the Nurses’ Health Study (NHS), the Health Professionals Follow-up Study (HPFS), the Shanghai Women’s Health Study (SWHS), and the Shanghai Men’s Health Study (SMHS). Using multivariable logistic regression, we applied fixed-effects meta-analysis to evaluate associations between 1,039 harmonized metabolites and CRC risk, adjusting for body mass index and other covariates. Results: Across seven cohorts (N = 3,779, 50% cases), participants were predominantly female (59.5%), with a median age of 68 years (IQR 62-73) and median BMI of 25.0 kg/m2 (IQR 23.0-28.0). Fourteen metabolites were significantly associated with CRC risk (FDR &amp;lt; 0.05). Inverse associations were observed for phospholipids and ether lipids enriched in polyunsaturated fatty acids (e.g., PE(20:0/18:2), PE(22:6/P-18:1), PC(22:6/18:0); OR range 0.47-0.63, p-value range 6.2E-04 to 6.8E-13). Positive associations included monoacylglycerols (MG(18:3)), bile acids (e.g., glycochenodeoxycholate), and xenobiotic compounds (e.g., N-undecylbenzenesulfonic acid). Heterogeneity was low (mean I2 across the significant metabolites was ∼ 15%), and directionality was consistent across studies. Conclusions: This multi-cohort analysis identified lipid metabolism and bile acid signaling as key pathways in CRC etiology, among others, independent of adiposity. The inverse associations with polyunsaturated lipid species and the positive association with bile acids and xenobiotics suggest that membrane lipid remodeling, gut-liver axis perturbations, and environmental exposures may play mechanistic roles in CRC development. Ongoing external validation in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort using untargeted metabolomic data will inform the utility of these metabolites as biomarkers for CRC risk stratification and prevention. Citation Format: Mary Playdon, Emma Braun, Kelly Santucci, A. Heather Eliassen, Edward L. Giovannucci, Marc Gunter, Steven Moore, Lorelei A. Mucci, Xiao-Ou Shu, Mingyang Song, Ying Wang, Danxia Yu, Wei Zheng, Cornelia M. Ulrich, Jennifer Ose. Circulating lipid and bile acid metabolites as predictors of colorectal cancer risk: A multi-cohort metabolomics meta-analysis [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 2316.

Evaluating the Evolving Real‐World Adverse Events of <scp>GLP</scp> ‐ <scp>1RAs</scp> Using <scp>FDA</scp> Adverse Event Reporting System ( <scp>FAERS</scp> )

Obesity · 2026-03-09 · 2 citations

OBJECTIVE: This study aimed to assess the spectrum and frequency of adverse events (AEs) linked to glucagon-like peptide-1 receptor agonists (GLP-1RAs) using the US FDA Adverse Event Reporting System (FAERS). Emphasis was placed on emerging safety concerns in context-specific use. METHODS: A retrospective analysis of FAERS reports between 2012 and 2025 was conducted. Five commonly prescribed FDA-approved GLP-1RAs were included. Disproportionality analyses were applied to detect AE signals. Subgroup analyses evaluated associations by indication, GLP-1RAs compared to other drugs, and AEs specific to individual GLP-1RAs. RESULTS: From over 18 million FAERS reports, 137,451 involved GLP-1RAs. The most frequent AEs were gastrointestinal, nutritional and metabolic, and psychiatric disorders, occurring at higher rates compared to other drugs. In diabetes use, GLP-1RAs were associated with retinopathy, hearing loss, and cataracts. In contrast, when prescribed for weight management/obesity, nutritional, metabolic, and psychiatric AEs predominated. We also developed an open-access portal for AE exploration, available at http://glp1.tanlab.org. CONCLUSIONS: GLP-1RAs are linked to a broad range of AEs across indications. These findings stress the need for careful clinical monitoring and long-term safety evaluation. This study also illustrates how real-world evidence can inform safety communications, as well as hypothesis generation for research on next-generation GLP-1RAs.

Abstract 875: Identifying novel therapeutic targets for cancer-related fatigue in colorectal cancer patients using lipidomics: Results from the ColoCare Study.

Cancer Research · 2026-04-03

Abstract Background: Cancer-related fatigue (CRF) is the most frequently reported symptom among patients with colorectal cancer (CRC), with limited therapeutic options. Alterations in metabolic pathways related to lipid metabolism have been shown to play a role in non-cancer fatigue-associated diseases, and are hypothesized to influence CRF. The purpose of the present study was to investigate serum lipidomic biomarkers to identify longitudinal predictors of CRF in a prospective cohort of patients with CRC. Methods: The ColoCare Study enrolled men and women ages 18 to 89 with newly diagnosed primary stage I-IV CRC at six U.S. sites and one German site. CRF was measured using the fatigue subscale of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTC QLQ-C30) at T0 (CRC surgery/baseline), T1 (6 months post-surgery), T2 (12 months), and T3 (24 months). Using blood collected at each time point, we performed targeted lipidomics following comprehensive protocols for measurement and quality control. For the present study, participants with stage I-III disease and at least one measurement of CRF and lipidomic profiling (N=863) were included. Using linear mixed effects models with an interaction term with time point and subject-specific random intercepts, we assessed associations between individual lipids and CRF at each time point. We adjusted for multiple testing using the Benjamini-Hochberg correction for false-discovery rate. Models also adjusted for age, sex, tumor site, stage, body mass index, chemotherapy, radiation, and study site. We used elastic net regression on a training subset (n=176) to identify lipids at T1 (when first-line treatment was nearing completion) that were predictive of fatigue at T2. Further analyses validating prediction models and using metabolic pathway analyses are ongoing. Results: Mean age was 61.6 years (SD: 12.7). N=305 total lipids were identified. In linear mixed effects models, no lipids were associated with CRF at T0 or T1. At T2 and T3, higher levels of ceramides (20), monohexosylceramides (11), gangliosides (4), trihexosylceramides (1), and sphingomyelins (16) were associated with lower CRF after adjustment for multiple testing. Predictive modeling identified higher levels of three sphingolipids at T1 associated with lower CRF at T2 and higher levels of two lipids (one diglyceride and one ceramide) at T1 associated with higher CRF at T2. Conclusions: Specific sphingolipids, including ceramides, monohexosylceramides, and sphingomyelins, were inversely associated with CRF, suggesting a protective role. Predictive modeling supports their potential as targetable biomarkers of fatigue. These findings highlight lipid metabolism as a promising target for understanding and mitigating fatigue in cancer survivors, warranting external validation and mechanistic research. Citation Format: Nicole C. Loroña, Mary C. Playdon, James E. Cox, Alan Maschek, Xiaoyin Li, Aasha I. Hoogland, Maria F. Gomez, Patricia A. Erickson, Mmadili N. Ilozumba, Victoria Damerell, Ildiko Strehli, Megan Mclaws, Lyen C. Huang, Paul Stewart, Sheetal Hardikar, Jennifer Ose, Anita R. Peoples, Brent Small, David Shibata, Doratha A. Byrd, Adetunji T. Toriola, Christopher I. Li, Cornelia M. Ulrich, Biljana Gigic, Heather S. Jim, Jane C. Figueiredo. Identifying novel therapeutic targets for cancer-related fatigue in colorectal cancer patients using lipidomics: Results from the ColoCare Study [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 875.