Citations

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

Abstract Branched-chain amino acid transaminase 1 (BCAT1) is upregulated selectively in human isocitrate dehydrogenase (IDH) wildtype (WT) but not mutant glioblastoma multiforme (GBM) and promotes IDHWT GBM growth. Through a metabolic synthetic lethal screen, we report here that α-ketoglutarate (AKG) kills IDHWT GBM cells when BCAT1 protein is lost, which is reversed by reexpression of BCAT1 or supplementation with branched-chain α-ketoacids (BCKA), downstream metabolic products of BCAT1. In patient-derived IDHWT GBM tumors in vitro and in vivo, cotreatment of BCAT1 inhibitor gabapentin and AKG resulted in synthetic lethality. However, AKG failed to evoke a synthetic lethal effect with loss of BCAT2, BCKDHA, or GPT2 in IDHWT GBM cells. Mechanistically, loss of BCAT1 increased the NAD+/NADH ratio but impaired oxidative phosphorylation, mTORC1 activity, and nucleotide biosynthesis. These metabolic alterations were synergistically augmented by AKG treatment, thereby causing mitochondrial dysfunction and depletion of cellular building blocks, including ATP, nucleotides, and proteins. Partial restoration of ATP, nucleotides, proteins, and mTORC1 activity by BCKA supplementation prevented IDHWT GBM cell death conferred by the combination of BCAT1 loss and AKG. These findings define a targetable metabolic vulnerability in the most common subset of GBM that is currently incurable. Significance: Metabolic synthetic lethal screening in IDHWT glioblastoma defines a vulnerability to ΑΚG following BCAT1 loss, uncovering a therapeutic strategy to improve glioblastoma treatment. See related commentary by Meurs and Nagrath, p. 2354

Abstract Background: Somatic EGFR mutations define a subset of non–small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. Methods: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. Results: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74–0.77) in the training and 0.77 (95% CI, 0.74–0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. Conclusions: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. Impact: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.

Interleukin- (IL-) 17 is important in the development of asthma and host defense against pneumococci. We determined the role of IL-17 in the risk of pneumococcal pneumonia. We challenged mice intranasally with a bioluminescentStreptococcus pneumoniaestrain after sensitization and challenge with ovalbumin (OVA). We measured the levels of cytokines, including IL-17 (pg/mL), in the lung homogenate in experimental mice with and without OVA sensitization/challenge, as well as those with and without pneumococcal pneumonia. IL-17 levels were significantly lower in OVA-sensitized/challenged mice (9.69±1.49), compared to the control mice (20.92±1.82,P< 0.001). In our overall analysis, including IL-4 and IL-17 levels and OVA sensitization/challenge, IL-4 levels (OR: 81.9, 95%CI: 4.3–1523 per increment of 1.0 pg/mL,P= 0.003) were more significant than IL-17 levels (OR: 1.1, 95%CI: 1.03–1.17 per increment of 1.0 pg/mL,P= 0.003) in determining the risk of pneumococcal pneumonia. IL-17 levels result in a much smaller impact on the risk for pneumococcal pneumonia, compared to IL-4 levels.