S2595
Radiobiology - Preclinical biomarkers
ESTRO 2026
Santiago, Santiago de Compostela, Spain. 4 Consellería de Sanidade, Xunta de Galicia, Santiago de Compostela, Spain. 5 Fédération Universitaire d’oncologie radiothérapie d’Occitanie Méditerranée, ICM, INSERM U1194 IRCM, Univ Montpellier, Montpellier, France. 6 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany. 7 Cancer Epidemiology Group, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 8 The Christie Hospital NHS Foundation Trust, University of Manchester, Manchester, United Kingdom. 9 Department of Radiation Oncology, Maastricht University Medical Center, Maastricht, Netherlands. 10 Department of Oncology, University of Cambridge, Cambridge, United Kingdom. 11 Hereditary Cancer Genetics Group, Vall d’Hebron Institute of Oncology (VHIO), Vall d’Hebron Barcelona Hospital Campus, Barcelona, Spain. 12 Radiation Oncology, Medical College of Wisconsin, Wisconsin, USA. 13 Radiation Oncology, KU Leuven, Leuven, Belgium. 14 Unit of Data Science, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy. 15 Leicester Cancer Research Centre, University of Leicester, Leicester, United Kingdom. 16 Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York, USA. 17 Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA. 18 Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. 19 Department of Genetics and Genome Biology, University of Leicester, Leicester, United Kingdom. 20 Radiation Oncology, Ghent University Hospital and Ghent University, Ghent, Belgium. 21 Translational Radiobiology Group, Division of Cancer Sciences, The University of Manchester, Manchester, United Kingdom. 22 Genetics in Cancer and Rare Disease Group, Instituto de Investigación Sanitaria de Santiago (IDIS), Fundación Pública Galega de Medicina Xenómica (FPGMX), Santiago de Compostela, Spain. 23 Biomedical Network on Rare Diseases (CIBERER), Instituto de Salud Carlos III, Madrid, Spain Purpose/Objective: Radiogenomic studies investigate genetic factors influencing individual responses to radiotherapy (RT). Genome-wide analyses have identified candidate genes linked to RT-induced toxicity, including TANC1, involved in muscle repair and regeneration [Fachal 2014]. As many organs at risk contain muscular components, we hypothesised that genetic variation in muscle repair pathways contributes to both acute and late RT toxicities. To test this hypothesis, we conducted an association analysis of genetic variants and RT-related adverse effects in prostate, breast, and lung cancer cohorts. Material/Methods: A total of 4,347 cancer patients treated with RT (prostate = 1,760; breast = 2,057; lung = 530) were included [REQUITE project ISRCTN98496463]. Global acute and late toxicities were summarised using Standardized Total Average Toxicity (STAT) scores, adjusted for clinical covariates, with residuals used as the phenotype for association testing. Toxicities were evaluated across tumour types: in breast, atrophy, oedema, telangiectasia, lymphoedema, among others; in prostate, gastrointestinal and genitourinary events such as proctitis, rectal bleeding, and urinary symptoms, among others; and in lung, respiratory, oesophageal, and cardiothoracic effects including pneumonitis, fibrosis, and oesophagitis, among others.Genomic DNA was extracted from peripheral blood samples collected before the start of radiotherapy. Genotyping was performed using the Infinium OncoArray-500K BeadChip and imputed with TOPMed (version r3, GRCh38) following quality control. Associations between toxicity phenotypes and variants in the myogenesis (15,361 single nucleotide polymorphisms (SNPs)) and myoblast fusion (9,908 SNPs) pathways were analysed using
Optimal Sequence-Kernel-Association-Test (SKAT-O) to aggregate variants. Analyses included variants with a minor allele frequency between 0.01 and 0.1, adjusting for population structure using 10 principal components. Results: In the myogenesis pathway, CDH4 and CTNNA2 were significantly associated (P ≤ 0.05) with late toxicity in breast cancer, while MEF2B was associated with acute toxicity in lung cancer, late toxicity in prostate cancer, and across all three tumour types combined. Within the myoblast fusion pathway, several genes were linked to acute toxicity—including ADGRB3, FER1L5, KCNH1, MYH9, MYMK, and PLEKHD1—whereas PITX2 and TANC1 were associated with late toxicities when all cancers were analysed together. [Fig 1]
Conclusion: Low-frequency genetic variants emerge as promising biomarkers for predicting post-radiotherapy toxicity. Variants in the myogenesis pathway and the myoblast fusion process are consistently associated with toxicities. Moreover, aggregating rare variants within genes of these pathways captures relevant genetic signals contributing to global toxicity across all three cancer types. References: Fachal 2014. Nat Genet. 2014 Aug;46(8):891-4. doi:10.1038/ng.3020.EU-FP7 grant 601826 (REQUITE Project); AECC (PRYES211091VEGA), Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds (PI25/00744, PI22/00589, INT24/00023, DTS24/00083); the Autonomous Government of Galicia (Consolidation and structuring program: IN607B2025/09). Keywords: Muscle repair, Toxicity, Radiogenomics Digital Poster 3993 Catabolic crosstalk index (zCCI): A RNAseq biomarker that could quantify tumour–muscle signalling in pancreatic and liver cancer Lina Al-Zerikat 1 , Ahmed Salem 2 , Fatima Farhan 1,3 , Abdelrahman Masheh 1 , Badie Abuzaid 1 , Mohammad Akash 1 1 Faculty of Medicine, The Hashemite University, Zarqa, Jordan. 2 Department of Anatomy, Physiology and Biochemistry, Faculty of Medicine, The Hashemite University, Zarqa, Jordan. 3 Clinical Bioinformatician, Bionl, MA, USA Purpose/Objective: Cachexia is frequent in upper gastrointestinal and hepatobiliary cancers, yet biomarkers capturing tumour–muscle signalling remain limited. We developed the catabolic crosstalk index (zCCI), a RNAseq metric integrating tumour-derived ligands with skeletal-muscle
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