Abstract Background: Advances in cancer treatment and surveillance have increased survivorship, consequently elevating the risk of multiple primary cancers (MPC). However, distinguishing single primaries (SP) and MPC from recurrences or metastases remains a key barrier to studying gene and environmental drivers of second malignancies at scale. Methods: We developed an automated algorithm to classify tumors as distinct primaries versus recurrences/metastases using IARC criteria, curated exceptions, and clinical and molecular data from Memorial Sloan Kettering’s Cancer Data Science Initiative in 91,906 cancer patients. The classifier was validated against an expert-adjudicated dataset. Standardized incidence ratios (SIRs) were computed using age and sex-adjusted SEER-21 reference rates. To assess therapy-related risk, MPCs were stratified by exposure and analyzed for latency and survival. Inherited etiology based on rare germline pathogenic variants (PV) and cancer-specific polygenic risk scores (PRS) was assessed. Results: The classifier achieved 93% concordance in distinguishing MPC from SP tumors. Applied to 91,906 patients in the MSK-IMPACT cohort, the algorithm identified 16,990 (18.5%) with MPC. Among metachronous cases, the median latency to a second primary was 8.2 years. Twenty-one cancer pairs showed elevated SIRs, including four matching known hereditary syndromes. Excess risk persisted in non-carriers of PV, suggesting polygenic or exposure-related causes. Treatment-related pairs included ovary-leukemia (SIR=5.7), breast-leukemia (SIR=4.0), breast-lung (SIR=2.9), breast-uterus (SIR=2.7), and male bladder-lung (SIR=3.3). Therapy exposure significantly modified risk and latency. Tamoxifen exposure conferred a 3.5-fold higher uterine cancer hazard with earlier onset yet improved survival. Among radiotherapy-exposed breast cancer survivors (n=3,482), higher chest irradiation correlated with a 4-fold secondary lung cancer hazard. Platinum exposure for ovarian cancer (n=2,811) increased Acute Myeloid leukemia (AML) hazard by 4.4-fold while alkylating agents for breast cancer (n=9,497) conferred a 2.9-fold AML risk, with shorter latency supporting treatment-related mechanisms. In male bladder cancer survivors, smokers had 9.1-fold increased hazard of subsequent lung cancer (n=1,316). Among smokers, older age at bladder cancer diagnosis predicted shorter latency to lung cancer. Increased SIR persisted in several cancer pairs, even after accounting for rare PV and PRS, suggesting undiscovered genetic and environmental factors and interactions. Conclusions: Automated classification of MPC reveals genetic and exposure-related patterns in secondary cancer risk, timing, and survival. Ongoing work is integrating tumor genomics as well as polygenic risk scores to identify inherited and therapy-related drivers of cancer development and aggressiveness. (Supported by MSK Niehaus Center and BCRF). Citation Format: Johnathan Amsalem, Ying Liu, Aliya Khurram, Yelena Kemel, Andrew Marderstein, Mitul Waghmare, Semanti Mukherjee, Michael Conry, Vignesh Ravichandran, Saibaba Magunta, Ritika Kundra, Matthew Buas, Christopher Fong, Justin Jee, Michael Berger, Jian Carrot-Zhang, Zsofia Stadler, Venkatraman Seshan, Nikolaus Schultz, Kenneth Offit, Vijai Joseph. Multifactorial risks for multiple primary cancers [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 5222.
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