Neighborhood disadvantage is associated with KRAS-mutated non-small cell lung cancer risk.

PURPOSE: It remains unclear why individuals living in disadvantaged neighborhoods have shorter non-small cell lung cancer (NSCLC) survival. It is possible that living in these deprived areas is linked with increased risk of developing aggressive NSCLC biology. Here, we explored the association of somatic KRAS mutations, which are associated with shorter survival in NSCLC patients, and 11 definitions of neighborhood disadvantage spanning socioeconomic and structural environmental elements. METHODS: We analyzed data from 429 NSCLC patients treated at a Comprehensive Cancer Center from 2015 to 2018. Data were abstracted from medical records and each patient's home address was used to assign publicly available indices of neighborhood disadvantage. Prevalence Ratios (PRs) for the presence of somatic KRAS mutations were estimated using modified Poisson regression models adjusted for age, sex, smoking status, race/ethnicity, educational attainment, cancer stage, and histology. RESULTS: In the NSCLC cohort, 29% had KRAS mutation-positive tumors. We found that five deprivation indices of socioeconomic disadvantage were associated with KRAS mutation. A one decile increase in several of these socioeconomic disadvantage indices was associated with a 1.06 to 1.14 increased risk of KRAS mutation. Measures of built structural environment were not associated with KRAS mutation status. CONCLUSION: Socioeconomic disadvantage at the neighborhood level is associated with higher risk of KRAS mutation while disadvantage related to built environmental structural measures was inversely associated. Our results indicate not only that neighborhood disadvantage may contribute to aggressive NSCLC biology, but the pathways linking biology to disadvantage are likely operating through socioeconomic-related stress.

The Role of Neighborhood Air Pollution Exposure on Somatic Non-Small Cell Lung Cancer Mutations in the Los Angeles Basin (2013-2018).

Limited previous work has identified a relationship between exposure to ambient air pollution and aggressive somatic lung tumor mutations. More work is needed to confirm this relationship, especially using spatially resolved air pollution. We aimed to quantify the association between different air pollution metrics and aggressive tumor biology. Among patients treated at City of Hope Comprehensive Cancer Center in Duarte, CA (2013-2018), three non-small cell lung cancer somatic tumor mutations, TP53, KRAS, and KRAS G12C/V, were documented. PM2.5 exposure was assessed using state-of-the art ensemble models five and ten years before lung cancer diagnosis. We also explored the role of NO2 using inverse-distance-weighting approaches. We fitted logistic regression models to estimate odds ratio (OR) and their 95% confidence intervals (CIs). Among 435 participants (median age: 67, female: 51%), an IQR increase in NO2 exposure (3.5 µg/m3) five years before cancer diagnosis was associated with an increased risk in TP53 mutation (OR, 95% CI: 1.30, 0.99-1.71). We found an association between highly-exposed participants to PM2.5 (>12 µg/m3) five and ten years before cancer diagnosis and TP53 mutation (OR, 95% CI: 1.61, 0.95-2.73; 1.57, 0.93-2.64, respectively). Future studies are needed to confirm this association and better understand how air pollution impacts somatic profiles and the molecular mechanisms through which they operate.

Leveraging an Informatics Approach to Identify an Unmet Clinical Need for BRCA1/2 Testing Among Patients With Ovarian Cancer.

PURPOSE: Although BRCA1/2 testing in ovarian cancer improves outcomes, it is vastly underutilized. Scalable approaches are urgently needed to improve genomically guided care. METHODS: We developed a Natural Language Processing (NLP) pipeline to extract electronic medical record information to identify recipients of BRCA testing. We applied the NLP pipeline to assess testing status in 308 patients with ovarian cancer receiving care at a National Cancer Institute Comprehensive Cancer Center (main campus [MC] and five affiliated clinical network sites [CNS]) from 2017 to 2019. We compared characteristics between (1) patients who had/had not received testing and (2) testing utilization by site. RESULTS: We found high uptake of BRCA testing (approximately 78%) from 2017 to 2019 with no significant differences between the MC and CNS. We observed an increase in testing over time (67%-85%), higher uptake of testing among younger patients (mean age tested = 61 years v untested = 65 years, P = .01), and higher testing among Hispanic (84%) compared with White, Non-Hispanic (78%), and Asian (75%) patients (P = .006). Documentation of referral for an internal genetics consultation for BRCA pathogenic variant carriers was higher at the MC compared with the CNS (94% v 31%). CONCLUSION: We were able to successfully use a novel NLP pipeline to assess use of BRCA testing among patients with ovarian cancer. Despite relatively high levels of BRCA testing at our institution, 22% of patients had no documentation of genetic testing and documentation of referral to genetics among BRCA carriers in the CNS was low. Given success of the NLP pipeline, such an informatics-based approach holds promise as a scalable solution to identify gaps in genetic testing to ensure optimal treatment interventions in a timely manner.

Recall of Genomic Testing Results Among Patients with Cancer.

BACKGROUND: Genomic testing of somatic and germline DNA has transformed cancer care. However, low genetic knowledge among patients may compromise care and health outcomes. Given the rise in genomic testing, we sought to understand patients' knowledge of their genetic test results. MATERIALS AND METHODS: We conducted a survey-based study with 85 patients at a comprehensive cancer center. We compared self-reported recall of (a) having had somatic/germline testing and (b) their specific somatic/germline results to the genomic test results documented in the medical record. RESULTS: Approximately 30% of patients did not recall having had testing. Of those who recalled having testing, 44% of patients with pathogenic/likely pathogenic germline mutations and 57% of patients with reported somatic alterations did not accurately recall their specific gene or variant-level results. CONCLUSION: Given significant knowledge gaps in patients' recall of genomic testing, there is a critical need to improve patient-directed education and return-of-results strategies.

The Association between Polluted Neighborhoods and TP53-Mutated Non-Small Cell Lung Cancer.

BACKGROUND: Poor patients often reside in neighborhoods of lower socioeconomic status (SES) with high levels of airborne pollutants. They also have higher mortality from non-small cell lung cancer (NSCLC) than those living in wealthier communities. We investigated whether living in polluted neighborhoods is associated with somatic mutations linked with lower survival rates, i.e., TP53 mutations. METHODS: In a retrospective cohort of 478 patients with NSCLC treated at a comprehensive cancer center between 2015 and 2018, we used logistic regression to assess associations between individual demographic and clinical characteristics, including somatic TP53 mutation status and environmental risk factors of annual average particulate matter (PM2.5) levels, and neighborhood SES. RESULTS: 277 patients (58%) had somatic TP53 mutations. Of those, 45% lived in neighborhoods with "moderate" Environmental Protection Agency-defined PM2.5 exposure, compared with 39% of patients without TP53 mutations. We found significant associations between living in neighborhoods with "moderate" versus "good" PM2.5 concentrations and minority population percentage [OR, 1.06; 95% confidence interval (CI), 1.04-1.08]. There was a significant association between presence of TP53 mutations and PM2.5 exposure (moderate versus good: OR, 1.66; 95% CI, 1.02-2.72) after adjusting for patient characteristics, other environmental factors, and neighborhood-level SES. CONCLUSIONS: When controlling for individual- and neighborhood-level confounders, we find that the odds of having a TP53-mutated NSCLC are increased in areas with higher PM2.5 exposure. IMPACT: The link between pollution and aggressive biology may contribute to the increased burden of adverse NSCLC outcomes in individuals living in lower SES neighborhoods.