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Kishan, A. U.

Publications and source records attributed to Kishan, A. U..

2 recordsLinked to original sources

Intratumoral dose heterogeneity promotes adaptive anti-tumor immunity and predicts clinical response to radiopharmaceutical therapy

Radiopharmaceutical therapies (RPT) deliver non-uniform radiation dose in tumors and the impact of this on response is poorly understood. Dose heterogeneity could engender treatment resistance in low dose regions, yet we hypothesize that a broader array of dose-dependent immuno-radiobiological mechanisms in tumor microenvironments (TME) and preservation of immune function in low-dose regions could promote adaptive anti-tumor immunity and response. In murine models, non-uniform lutetium-177 delivering <2.5 Gy to >20 Gy in a TME induced broader immunomodulatory effects and T cell-dependent survival improvement compared to more uniform distributions. Preserving low-dose regions promoted dendritic cell activation and TME infiltration of clonally expanded CD8+ T cells. In three independent cohorts of patients with prostate cancer, heterogeneous tumor dose distribution strongly correlated with improved clinical outcomes. These findings defy expected radiobiological dose-response and define a novel mechanism of action for RPT, supporting clinical investigation of dose distribution for optimizing patient selection and personalized dosing.

cancer biology↗

Germline determinants of the prostate tumor genome

A persons germline genome strongly influences their risk of developing cancer. Yet the molecular mechanisms linking the host genome to the specific somatic molecular phenotypes of individual cancers are largely unknown. We quantified the relationships between germline polymorphisms and somatic mutational features in prostate cancer. Across 1,991 prostate tumors, we identified 23 co-occurring germline and somatic events in close 2D or 3D spatial genomic proximity, affecting 10 cancer driver genes. These driver quantitative trait loci (dQTLs) overlap active regulatory regions, and shape the tumor epigenome, transcriptome and proteome. Some dQTLs are active in multiple cancer types, and information content analyses imply hundreds of undiscovered dQTLs. Specific dQTLs explain at least 16.7% ancestry-biases in rates of TMPRSS2-ERG gene fusions and 67.3% of ancestry-biases in rates of FOXA1 point mutations. These data reveal extensive influences of common germline variation on somatic mutational landscapes.

cancer biology↗