Two first-line treatments are commonly used for metastatic pancreatic cancer: FOLFIRINOX and gemcitabine plus nab-paclitaxel. However, a direct head-to-head comparison in a randomized clinical trial has not yet been conducted. Collecting enough data for this comparison requires collaboration among multiple partner institutions. Herein we use a privacy enhancing technology called federated learning combined with a novel algorithmic methodology: FedECA. This method aims to facilitate collaboration by enabling institutions to retain ownership of their data, sharing only aggregated information across a network. We deployed a federated network across three cancer centers: the Fédération Francophone de Cancérologie Digestive (FFCD) hosting data from two past clinical trials (PRODIGE 35 - NCT02352337, PRODIGE 37 - NCT02827201), the Institut d’Investigació Biomèdica de Girona (IDIBGI) and the Pancreatic Cancer Action Network (PanCAN) that hold data from clinical practice. Patients with metastatic pancreatic adenocarcinoma, a performance status eastern cooperative oncology group (ECOG) no larger than 2, and receiving one of the two treatments as first-line were included. To compare the efficacy of the two treatments, we applied FedECA, the federated version of Inverse Probability of Treatment Weighting (IPTW). The following covariates were used as confounders to estimate the propensity score: age, biological gender, liver metastasis and ECOG score. Missing covariates were imputed using the MissForest algorithms independently on each center. The hazard ratio computed with a propensity score-weighted Cox Model is the estimand of the treatment effect on overall survival. The bootstrap variance estimator is used as advised when using IPTW. The entire analysis was performed without data leaving the servers of the corresponding institutions. 514 patients were included for the treatment effect estimation (215 FOLFIRINOX and 299 gemcitabine plus nab-paclitaxel). The estimated hazard ratio output by our method, FedECA, is 0.75 (95% CI=0.63-0.92, p=0.005) in favor of FOLFIRINOX over gemcitabine plus nab-placlitaxel. These results show the survival benefit of using FOLFIRINOX over gemcitabine plus nab-paclitaxel. The same analysis conducted in each center independently failed to demonstrate a significant effect likely due to the statistical tests being underpowered. In this observational study leveraging historical trial data and real-world data, we find that FOLFIRINOX is superior to gemcitabine plus nab-paclitaxel. FedECA is the first method to allow performing IPTW in a federated setting i.e. without pooling data on a central server, facilitating collaboration across institutions and countries while ensuring data privacy. Quentin Klopfenstein, Jean Ogier du Terrail, Honghao Li, Imke Mayer, Nicolas Loiseau, Mohammad Hallal, Michael Debouver, Thibault Camalon, Thibault Fouqueray, Jorge Arellano Castro, Zahia Yanes, Laëtitia Dahan, Julien Taïeb, Pierre Laurent-Puig, Jean-Baptiste Bachet, Shulin Zhao, Remy Nicolle, Jérôme Cros, Daniel Gonzalez, Robert Carreras-Torres, Adelaida Garcia Velasco, Kawther Abdilleh, Sudheer Doss, Félix Balazard, Mathieu Andreux. Comparative efficacy of FOLFIRINOX versus gemcitabine plus nab-paclitaxel in metastatic pancreatic cancer: computing IPTW estimator while limiting patient data exposure with federated learning across 3 institutions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3654.

This table includes the overall sample description stratified by colorectal cancer (CRC) status and smoking status.

This file details the two-step interaction tests, and the gene-based aggregate test.

Supplementary Figure from Beyond GWAS of Colorectal Cancer: Evidence of Interaction with Alcohol Consumption and Putative Causal Variant for the 10q24.2 Region

This file includes the expression imputation statistics and included SNPs from the elastin net models.

Supplementary Table 1 shows the power calculation for the associations of PWY-5022 and propionate with CRC risk.

Background Previous prediction models for adiposity gain have not yet achieved sufficient predictive ability for clinical relevance. We investigated whether traditional and genetic factors accurately predict adiposity gain. Methods A 5-year gain of >= 5% in body mass index (BMI) and waist-to-hip ratio (WHR) from baseline were predicted in mid-late adulthood individuals (median of 55 years old at baseline). Proportional hazards models were fi tted in 245,699 participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort to identify robust environmental predictors. Polygenic risk scores (PRS) of 5 proxies of adiposity [BMI, WHR, and three body shape phenotypes (PCs)] were computed using genetic weights from an independent cohort (UK Biobank). Environmental and genetic models were validated in 29,953 EPIC participants. Findings Environmental models presented a remarkable predictive ability (AUCBMI: 0.69, 95% CI: 0.68-0.70; AUCWHR: 0.75, 95% CI: 0.74-0.77). The genetic geographic distribution for WHR and PC1 (overall adiposity) showed higher predisposition in North than South Europe. Predictive ability of PRSs was null (AUC: similar to 0.52) and did not improve when combined with environmental models. However, PRSs of BMI and PC1 showed some prediction ability for BMI gain from self-reported BMI at 20 years old to baseline observation (early adulthood) (AUC: 0.60-0.62). Interpretation Our study indicates that environmental models to discriminate European individuals at higher risk of adiposity gain can be integrated in standard prevention protocols. PRSs may play a robust role in predicting adiposity gain at early rather than mid-late adulthood suggesting a more important role of genetic factors in this life period.

This file includes the association parameters (OR [95% CI]) for the identified SNPs with significant interaction term for smoking intensity by genotypes.

This table includes the association parameters of smoking habits for colorectal cancer risk stratified by study type.

This figure depicts the flowchart of the two-step interaction test.

This figure depicts the two-step EDGE test plots of prioritized SNPs.

This figure depicts the LocusZoom plots for SNPs interacting with smoking intensity for colorectal cancer risk.

This file includes the association parameters of the interaction component (OR [95% CI]) for the identified SNPs for smoking habits stratified by tumor molecular markers.

This file includes the association parameters (OR [95% CI]) for the identified SNPs for smoking habits stratified by study type, sex and tumour site.

This file includes the association parameters (OR [95% CI]) for the identified SNPs with suggestive interaction term for smoking status by genotypes.

The indexed individual, from now on termed M116, was the world's oldest verified living person from January 17th 2023 until her passing on August 19th 2024, reaching the age of 117 years and 168 days (https://www.supercentenarian.com/records.html). She was a Caucasian woman born on March 4th 1907 in San Francisco, USA, from Spanish parents and settled in Spain since she was 8. Although centenarians are becoming more common in the demographics of human populations, the so-called supercentenarians (over 110 years old) are still a rarity. In Catalonia, the historic nation where M116 lived, the life-expectancy for women is 86 years, so she exceeded the average by more than 30 years (https://www.idescat.cat). In a similar manner to premature aging syndromes, such as Hutchinson-Gilford Progeria and Werner syndrome, which can provide relevant clues about the mechanisms of aging, the study of supercentenarians might also shed light on the pathways involved in lifespan. To unfold the biological properties exhibited by such a remarkable human being, we developed a comprehensive multiomics analysis of her genomic, transcriptomic, metabolomic, proteomic, microbiomic and epigenomic landscapes in different tissues, comparing the results with those observed in non-supercentenarian populations. The picture that emerges from our study shows that extremely advanced age and poor health are not intrinsically linked and that both processes can be distinguished and dissected at the molecular level. ### Competing Interest Statement Dr. Esteller declares past grants from Ferrer International and Incyte and personal fees from Quimatryx and Eucerin, outside the submitted work.

Colorectal cancer (CRC) is a major public health concern, with incidence rates increasing over the past decades particularly among younger adults. The identification of novel intervention targets for CRC prevention becomes imperative. In the present study we explored patterns of genes and pathways underlying the observed associations using estimates from genome-wide interaction studies (GWIS) of 15 exposures with established or putative CRC risk. GWIS estimates were derived from a pool of 36 primary studies including up to 38, 578 CRC cases and 49, 658 controls. The 15 risk factors included body mass index (BMI), height, physical activity, smoking, type 2 diabetes, hormone replacement therapy (HRT), and intake of non-steroidal anti-inflammatory drugs (NSAIDs) including aspirin, alcohol, calcium, fiber, folate, fruits, processed meat, red meat, and vegetables. We conducted pathway-environment interaction analysis for CRC risk to identify associated pathways using the adaptive combination of Bayes Factors (ADABF) framework. The pathway findings were further investigated by exploring the relevance of the enriched genes for CRC using publicly available resources [hallmarks of cancer, Open Targets Platform (OTP)]. Using the ADABF, a total of 1, 973 pathways were enriched out of the 2, 950 analyzed for at least one exposure. Additionally, within the enriched pathways, 1, 227 genes showed evidence of interaction with at least one exposure. A high overlap of associated genes was observed between the three exposures with higher number of associated genes: BMI (n=768), followed by smoking (n=223) and NSAIDs (n=173), while for remaining exposures the number of enriched genes ranged from 3 to 27. Data were available for 811/1, 227 genes in the OTP, of which an overall association score >0.05 was found for 241 coding genes. Fifty percent of the genes (617/1, 227) mapped to at least one hallmark of cancer, most of which (388/617) pertained to the Sustaining Proliferative Signaling hallmark. Our findings reflect previously established pathways for CRC risk, such as mitogen-activated protein kinase (MAPK), Notch, PI3K/AKT, transforming growth factor-β (TGF-β), Wnt, and participating genes, for BMI, NSAIDs, and smoking, and highlight the emerging importance of several less studied genes (such as argonaute RISC component, UDP-glucuronosyltransferase, and taste receptor coding genes). Common pathways were found for several combinations of exposures (mostly for BMI, NSAIDs, and smoking), potentially suggesting common underlying mechanisms. The results of the present analysis can be used in future investigations, and, if confirmed, may aid in elucidating the etiological associations and inform personalized CRC prevention strategies. Emmanouil Bouras, Ren Yu, Andre E. Kim, Georgios Markozannes, Neil Murphy, Demetrius Albanes, Laura N. Anderson, Elizabeth L. Barry, Hermann Brenner, Peter T. Campbell, Robert Carreras-Torres, Andrew T. Chan, Jenny Chang-Claude, Iona Cheng, Matthew A. Devall, Niki Dimou, David A. Drew, Stephen B. Gruber, Andrea Gsur, Li Hsu, Jeroen R. Huyghe, Temitope O. Keku, Anshul Kundaje, Loïc Le Marchand, Li Li, Brigid M. Lynch, Victor Moreno, John Morrison, Christina C. Newton, Nikos Papadimitriou, Andrew J. Pellatt, Anita R. Peoples, Paul D. Pharoah, Elizabeth A. Platz, Conghui Qu, Joel Sanchez Mendez, Robert E. Schoen, Mariana C. Stern, Claire E. Thomas, Caroline Y. Um, Pavel Vodicka, Veronika Vymetalkova, Emily White, Alicja Wolk, Anna H. Wu, Marc J. Gunter, W. James Gauderman, Ulrike Peters, Marina Evangelou, Konstantinos K. Tsilidis. Using gene-environment interactions to explore pathways for colorectal cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3817.

BACKGROUND:Colorectal cancer (CRC) is a significant public health concern, highlighting the critical need for identifying novel intervention targets for its prevention. METHODS:We conducted genome-wide interaction analyses for 15 exposures with established or putative CRC risk [body mass index (BMI), height, physical activity, smoking, type 2 diabetes, use of menopausal hormone therapy, non-steroidal anti-inflammatory drugs, and intake of alcohol, calcium, fibre, folate, fruits, processed meat, red meat, and vegetables], and used interaction estimates to explore pathways and genes underlying CRC risk. The adaptive combination of Bayes Factors (ADABF), and over-representation analysis (ORA) were used for pathway analyses, and findings were further investigated using publicly available resources [hallmarks of cancer, Open Targets Platform (OTP)]. FINDINGS:A total of 1973 pathways using ADABF, and 840 pathways using ORA, out of the 2950 analysed, were enriched (P < 0.05) for at least one exposure, as well as 1227 genes within the enriched pathways. Data were available for 811/1227 coding genes in the OTP, 241 of which were supported by strong relative abundance of prior evidence (overall OTP score > 0.05). Fifty percent of the genes (617/1227) mapped to at least one hallmark of cancer, most of which (388/617) pertained to the Sustaining Proliferative Signalling hallmark. Our findings reflect previously established pathways for CRC risk and highlight the emerging importance of several less studied genes. Common pathways were found for several combinations of exposures, potentially suggesting common underlying mechanisms. INTERPRETATION:The results of the present analysis provide a basis for further functional research. If confirmed, they may help elucidate the etiological associations between risk factors and CRC risk and ultimately inform personalized prevention strategies. FUNDING:This study was funded by Cancer Research UK (CRUK; grant number:PPRCPJT∖100005) and World Cancer Research Fund International (WCRF; IIG_FULL_2020_022). Funding for grant IIG_FULL_2020_022 was obtained from Wereld Kanker Onderzoek Fonds (WKOF) as part of the World Cancer Research Fund International grant programme. Full funding details for the individual consortia are provided in the acknowledgements.

This file includes the association parameters (OR [95% CI]) for the imputed gene expression levels of genes associated with lead SNPs.

This table includes the smoking habits descriptives per studies included in the analysis.