On the informative value of community-based indoor radon values in relation to lung cancer.

BACKGROUND: Radon is a radioactive gas and a major risk factor for lung cancer (LC). METHODS: We investigated the dose-response relationship between radon and LC risk in the International Lung Cancer Consortium with 8927 cases and 5562 controls from Europe, North America, and Israel, conducted between 1992 and 2016. Spatial indoor radon exposure in the residential area (sIR) obtained from national surveys was linked to the participants' residential geolocation. Parametric linear and spline functions were fitted within a logistic regression framework. RESULTS: We observed a non-linear spatial-dose response relationship for sIR < 200 Bq/m3. The lowest risk was observed for areas of mean exposure of 58 Bq/m3 (95% CI: 56.1-59.2 Bq/m3). The relative risk of lung cancer increased to the same degree in areas averaging 25 Bq/m3 (OR = 1.31, 95% CI: 1.01-1.59) as in areas with a mean of 100 Bq/m3 (OR = 1.34, 95% CI: 1.20-1.45). The strongest association was observed for small cell lung cancer and the weakest for squamous cell carcinoma. A stronger association was also observed in men, but only at higher exposure levels. The non-linear association is primarily observed among the younger population (age < 69 years), but not in the older population, which can potentially represent different biological radiation responses. CONCLUSIONS: The sIR is useful as proxy of individual radon exposure in epidemiological studies on lung cancer. The usual assumption of a linear, no-threshold dose-response relationship, as can be made for individual radon exposures, may not be optimal for sIR values of less than 200 Bq/m3.

Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response.

With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS, a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy.