Background: Among men in the U.S., prostate cancer is the most common cancer and the second leading cause of cancer death. Despite its prevalence, there are few established risk factors for prostate cancer. Some studies have found that intake of certain foods/nutrients may be associated with prostate cancer risk, but few have accounted for how intake and metabolic factors may interact to influence bioavailable nutrient levels and subsequent disease risk. Presentation of the hypothesis: The composition of the gastrointestinal (GI) microbiome may influence metabolism of dietary compounds and nutrients (e.g., plant phenols, calcium, choline) that may be relevant to prostate cancer risk. We, therefore, propose the hypothesis that GI microbiota may have a markedly different composition among individuals with higher prostate cancer risk. These individuals could have microbial profiles that are conducive to intestinal inflammation and/or are less favorable for the metabolism and uptake of chemopreventive agents. Testing the hypothesis: Because very little preliminary data exist on this potential association, a case–control study may provide valuable information on this topic. Such a study could evaluate whether the GI microbial profile is markedly different between three groups of individuals: healthy men, those with latent prostate cancer, and those with invasive prostate cancer. Any findings could then be validated in a larger study, designed to collect a series of specimens over time. Implications of the hypothesis: Given the plethora of information emerging from the Human Microbiome Project, this is an opportune time to explore associations between the microbiome and complex human diseases. Identification of profiles that alter the host’s risk for disease may clarify inconsistencies in the literature on dietary factors and cancer risk, and could provide valuable targets for novel cancer prevention strategies.

Background/Objectives: The tumor microenvironment (TME) plays a critical role in cancer progression by shaping immune responses and influencing patient outcomes. We hypothesized that the relative proximity of specific immune cell pairs to cancer cells within the TME could help predict their pro- or anti-tumor functions and reflect clinically relevant immune dynamics. Methods: We analyzed imaging mass cytometry (IMC) data from lung adenocarcinoma (LUAD) and triple-negative breast cancer (TNBC) cohorts. For each immune cell pair, we calculated a relative distance (RD) score, which quantifies the spatial difference in proximity to cancer cells. We assessed the prognostic and predictive significance of these RD-scores by comparing them with conventional features such as cell fractions, densities, and individual cell distances. To account for variations in cell abundance, we also derived normalized RD-scores (NRD-scores). Results: RD-scores were more strongly associated with overall patient survival than standard immunological metrics. Among all immune cell pairs, the RD-score comparing the proximity of B cells to that of intermediate monocytes showed the most significant association with improved survival. In TNBC, RD-scores also improved the distinction between responders and non-responders to immunochemotherapy and chemotherapy. Normalized RD-scores reinforced these findings by minimizing the influence of cell density and further highlighting the importance of immune cell spatial relationships. Conclusions: RD-scores offer a spatially informed biomarker that outperforms traditional metrics in predicting survival and treatment response. This approach provides a new perspective on immune cell behavior in the TME and has potential utility in guiding personalized cancer therapies and patient stratification.

Increasing rates of human papillomavirus (HPV)–driven oropharyngeal cancer (OPC) have largely offset declines in tobacco-associated head and neck squamous cell carcinoma (HNSCC) at non-OPC sites. Host immunity is an important modulator of HPV infection, persistence, and clearance, and also of immune evasion in both virally- and nonvirally-driven cancers. However, the association between collective known cancer-related immune gene variants and HNSCC susceptibility has not been fully characterized. Here, we conducted a genetic association study in the multiethnic Veterans Affairs Million Veteran Program cohort, evaluating 16,050 variants in 1,576 immune genes in 4,012 HNSCC cases (OPC = 1,823; non-OPC = 2,189) and 16,048 matched controls. Significant polymorphisms were further examined in a non-Hispanic white (NHW) validation cohort (OPC = 1,206; non-OPC = 955; controls = 4,507). For overall HNSCC susceptibility in NHWs, we discovered and validated a novel 9q31.1 SMC2 association and replicated the known 6p21.32 HLA-DQ-DR association. Six loci/genes for overall HNSCC susceptibility were selectively enriched in African-Americans (6p21.32 HLA-G, 9q21.33 GAS1, 11q12.2 CD6, 11q23.2 NCAM1/CD56, 17p13.1 CD68, 18q22.2 SOCS6); all 6 genes function in antigen-presenting regulation and T-cell activation. Two additional loci (10q26 DMBT1, 15q22.2 TPM1) were uncovered for non-OPC susceptibility, and three loci (11q24 CRTAM, 16q21 CDH5, 18q12.1 CDH2) were identified for HPV-positive OPC susceptibility. This study underscores the role of immune gene variants in modulating susceptibility for both HPV-driven and non-HPV-driven HNSCC. Additional large studies, particularly in racially diverse populations, are needed to further validate the associations and to help elucidate other potential immune factors and mechanisms that may underlie HNSCC risk. Significance: Several inherited variations in immune system genes are significantly associated with susceptibility to head and neck cancer, which could help improve personalized cancer risk estimates.

Background: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. Methods: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. Results: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10−8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. Conclusions: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. Impact: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.