The intersection of geography and oncology is no longer a speculative frontier—it is rapidly becoming the new standard in understanding who gets cancer, who survives it, and why. At a recent session at AACR 2026 bringing together leading researchers from the Fred Hutch Cancer Center, Harvard, and UCSF, the consensus was clear: geospatial methods are fundamentally altering how epidemiologists interrogate the cancer continuum, from incidence to mortality, from prevention to palliative care.
Trang VoPham, PhD, from Fred Hutch opened proceedings with a sweeping overview of how location data is being weaponized against cancer disparities. Her team’s work exemplifies the field’s evolution beyond crude ecological fallacies toward granular, individual-level exposure assessment. “We linked geospatial data on agricultural pesticide operations with all death certificates in the U.S. from 1989 to 2023,” she explained, detailing their findings that higher linuron use correlated with a 16% increased risk of colorectal cancer mortality among under-50s—higher than the 11% seen in older populations. The precision matters: “It is absolutely critical… can you access or generate residential address histories, not just baseline, not just at diagnosis, to consider life course exposures, timing of exposures, during relevant and critical time periods?”

VoPham’s lab is already translating these insights into population health interventions. Their GeoXMap web application—developed with community advisory boards across Washington State—enables neighborhood-level mapping of over 175 health variables, each paired with actionable mitigation strategies. “When you map radon, you can click on the tips button and see strategies for exposure mitigation, like where to get free radon test kits,” she noted. During 2023’s wildfire season, her team used Epic electronic health records to identify and contact 64,000 high-risk patients, resulting in over 4,000 same-day virtual primary care appointments. “This approach could absolutely be scaled to target other populations… to empower high-risk patients with information to help protect themselves from environmental hazards.”
Jaime Hart, ScD, from Harvard, shifted focus to the atmospheric dimensions of cancer risk, tracing how air pollution research has matured since IARC’s 2013 carcinogen declaration. She noted that evidence at the time was largely restricted to lung cancer data. Today, the picture has broadened considerably. Hart highlighted recent consortium work linking traffic-related nitrogen dioxide with premenopausal and Black women’s breast cancer risk—”mostly being driven by premenopausal breast cancer and breast cancer among Black women and non-Hispanic white women”—while PM2.5 associations remain more equivocal for this site.

The mechanistic sophistication has advanced in parallel. Hart detailed how particulate matter can “translocate across your lungs, get into your circulation and deposit in every tissue in your body,” even ascending the nasal pathway to breach the blood-brain barrier. Her collaboration with VoPham on wildfire-specific PM2.5 revealed that “even for the same increase in air pollution exposure… if that PM2.5 is coming more from wildfires than not, you saw an elevated risk,” suggesting source-specific toxicity profiles that carry profound regulatory implications.
Iona Cheng, PhD, from University of California, San Francisco, anchored the session in the structural determinants that underlie these spatial patterns. Her work on redlining—historical mortgage discrimination encoded into contemporary health disparities—demonstrates how geospatial tools can excavate systemic injustice. “In Detroit… about 70% [of non-Hispanic white men with prostate cancer] do live in an area that has not been redlined, in contrast to about 30%,” she reported, whereas “almost 60%” of African American patients resided in the most heavily denied neighborhoods. The mortality gradient was stark: “Higher prostate cancer mortality, or lower survival, associated with living in neighborhoods with more redlining, for both Black and white men.”

Cheng emphasized that these are not proxy measures for individual behavior but independent contextual effects. “We do see that the neighborhood itself has contributions,” she said, describing how her team is developing racially-ethnic-specific composite indices of structural racism across housing, education, employment, and judicial domains. The community-engaged methodology proved essential: working with Hawaiian advisory boards revealed that non-Hispanic white reference groups made little demographic sense for the islands, prompting recalibration.
The session closed with a palpable sense of acceleration. From Google’s nascent geospatial reasoning AI to wearable sensor validation of satellite models; from street-view imagery classifying 350 million U.S. locations to ecological momentary assessment tracking real-time exposures, the toolkit is expanding exponentially. As Hart observed: “The places where we live, work, and play influence our risk of cancer, impose diagnostic outcomes. There are robust biological mechanisms that underlie this.” The geospatial revolution in cancer epidemiology, it seems, is only getting started.
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