Estimating the carcinogenesis timelines in early-onset versus late-onset cancers and changes across birth cohorts

Abstract Understanding the timing of key mutational events in cancer development is critical for informing cancer prevention and detection strategies, particularly for early-onset cases that have increased in recent years. Yet intermediate mutational events are challenging to observe in humans. Here, we extend a tumor kinetic model we recently developed and long-term cancer registries data to estimate the expected timing of intermediate mutational events for breast, colorectal, and thyroid cancers. We formulate three distinct systems of ordinary differential equations, each describing cell evolution sequentially through three stages of carcinogenesis, up to the first occurrence of malignant transition. We further apply a convolution-based method to derive probability distributions and compute the expected age for each transition, based on parameters fit to incidence and tumor size data for each cancer. The models estimate the initial mutation occurs early in life for all three cancer types. For breast and colorectal cancers, estimated malignant transformation occurs more than a decade faster and hence earlier in early-onset than late-onset cases (in late 30s vs. late 40s to early 50s). In contrast, early- and late-onset thyroid cancers show similar early timelines (malignant transformation in late 20s), consistent with known early-life thyroid clonal activity. We also quantify early-onset carcinogenesis timelines for three key birth cohorts (born during 1950-1954, 1965-1969, and 1980-1984) and identify a shift toward earlier malignant transformation in more recent cohorts, largely due to faster progressions of later stage transitions, for all three cancer types. These findings can inform early-onset cancer etiologic studies and intervention strategies. Significance Statement Carcinogenic mutational events are crucial for cancer etiology but challenging to observe. Here, we circumvent the research challenges to trace key mutations stepwise through the emergence of malignancy by combining long-term cancer registry data and tumor kinetic modeling for three key cancer types (breast, colorectal, and thyroid). We find early-life initial mutations but diverging timelines in cancer progression between early- and late-onset cases and temporal changes across birth cohorts. We estimate faster progression and hence earlier onset in more recent birth cohorts, consistent with the reported increases in early-onset cancer incidence. Our study provides the first direct, cohort-specific estimates on when key mutational transitions occur over the life course, which can inform early-onset cancer etiologic studies and intervention strategies. Competing Interest Statement The authors have declared no competing interest. Funding Statement N Mohammad Mirzaei and W Yang were supported by the National Cancer Institute (R01CA257971). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The data that support the findings of this study are publicly available from the Surveillance, Epidemiology, and End Results Program at https://seer.cancer.gov/data-software/, and from the National Health and Nutrition Examination Survey at https://wwwn.cdc.gov/nchs/nhanes/. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data availability statement The data that support the findings of this study are publicly available from the Surveillance, Epidemiology, and End Results Program at https://seer.cancer.gov/data-software/, and from the National Health and Nutrition Examination Survey at https://wwwn.cdc.gov/nchs/nhanes/. Further information is available from the corresponding author upon request.