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Different cancers favour different organs, and so do different patients. A model that predicts which organ is at risk could target surveillance and prevention.
Site of relapse is recorded in registries and trial datasets but almost never modelled as an outcome. Linking primary tumour genomics, transcriptomics and digital pathology to first-relapse site across tens of thousands of patients would produce an organotropism predictor, and would identify the features that drive lung, liver, bone and brain tropism in humans rather than in mice.
Shares AACR Project GENIE, SEER (Surveillance, Epidemiology, and End Results), Weak real-world evidence and registries, Data silos.
Shares cBioPortal for Cancer Genomics, AACR Project GENIE, Metastasis is understood least and studied last, Data silos.
Shares cBioPortal for Cancer Genomics, AACR Project GENIE, Pathology & radiology foundation models, RNA sequencing & expression profiling.
Shares SEER (Surveillance, Epidemiology, and End Results), Weak real-world evidence and registries, Data silos.
Shares AACR Project GENIE, SEER (Surveillance, Epidemiology, and End Results), Weak real-world evidence and registries.
Shares cBioPortal for Cancer Genomics, SEER (Surveillance, Epidemiology, and End Results), Data silos.
Shares cBioPortal for Cancer Genomics, AACR Project GENIE, Weak real-world evidence and registries, Data silos.
Shares SEER (Surveillance, Epidemiology, and End Results), Weak real-world evidence and registries, Data silos.