Global Geo-Pharmacogenomics: Environmental Mutational Signatures Drive Population-Level Heterogeneity in Anticancer Drug Response

The interplay between the environmental exposome and the cancer genome remains a critical "blind spot" in precision oncology. While somatic mutational signatures genomic fossils imprinted by exposures such as ultraviolet radiation, tobacco smoke, and industrial pollutants are well characterized for their etiological significance, their functional impact on therapeutic efficacy remains largely unexplored. We hypothesized that these environmental "genomic scars" induce distinct pharmacogenomic vulnerabilities (collateral sensitivity) and resistance mechanisms (collateral resistance) that vary by geographical exposure patterns. Here, we present the first global "Geo-Pharmacogenomic" atlas, integrating 41 COSMIC mutational signatures with drug response profiles from 1,001 cancer cell lines across four large-scale pharmacogenomic screens (GDSC1, GDSC2, CTRP, CCLE). By harmonizing disparate drug sensitivity metrics and applying rigorous statistical controls for tissue lineage, we identified and validated 608 significant signature-drug interactions (P < 0.01). We demonstrate that UV-associated signature SBS7a is a broad-spectrum driver of therapeutic resistance, conferring intrinsic insensitivity to BRAF inhibitors (PLX-4720, P < 10-4) and Notch inhibitors globally. Conversely, we uncover a novel synthetic lethal vulnerability wherein pollution-driven oxidative stress (SBS18) sensitizes tumors to p38 MAPK inhibition (VX-702, r = -0.45, P < 10-9). Synthesizing these findings with satellite-derived atmospheric data (World Bank/NASA AOD), we constructed a Kriging-interpolated risk surface spanning 122 nations. This analysis predicts distinct "Resistance Landscapes with high-intensity drug resistance predicted in pollution-dense megacities (e.g., Beijing, New Delhi) challenging the paradigm of uniform drug efficacy. Our results establish environmental history as a functional biomarker, necessitating a paradigm shift towards geographically stratified precision medicine.