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Introduction: SCLC has traditionally been considered to arise from toxic exposure factors, such as smoking. Recent evidence has revealed that germline mutations may also affect the development of SCLC; however, these alterations remain understudied. We sought to identify novel germline mutations in SCLC including germline copy number variations (CNVs) in our cohort of patients. Methods: We designed a custom hybrid-capture gene panel to evaluate germline alterations in 192 cancer-predisposition and frequently mutated genes in SCLC. We applied this panel to germline analysis of a treatment-naive cohort of 67 patients with SCLC at our institution. Subsequently, we annotated the variants using the American College of Medical Genetics criteria and further classified variants of uncertain significance using a set of in silico tools, including DeepMind AlphaMissense, MutationTaster, SIFT, and Polyphen2. Results: We identified American College of Medical Genetics pathogenic or likely pathogenic alterations in seven of 67 patients. Five (71%) were novel alterations (BCORL1, FANCC, ATR, and BBC3) and a novel CNV (SLFN11) with two (29%) previously described mutations (CHEK1 and BRIP1). We also identified 191 variants of uncertain significance in 60 of 67 patients, of which, depending on the in silico tool, 5% to 14% were predicted to be pathogenic. Patients with SCLC with the seven pathogenic alterations were observed to have a numerically longer overall survival (hazard ratio = 0.50) and progression-free survival (hazard ratio = 0.45) though not statistically significant compared with the remaining cohort. Conclusions: Our study identifies novel germline alterations, including a CNV, and provides additional evidence that germline factors could be important contributing factors to the development of SCLC.

Introduction: Real-world evidence is important in regulatory and funding decisions. Manual data extraction from electronic health records (EHRs) is time-consuming and challenging to maintain. Automated extraction using natural language processing (NLP) and artificial intelligence may facilitate this process. Whereas NLP offers a faster solution than manual methods of extraction, the validity of extracted data remains in question. The current study compared manual and automated data extraction from the EHR of patients with advanced lung cancer. Methods: Previously, we extracted EHRs from 1209 patients diagnosed with advanced lung cancer (stage IIIB or IV) between January 2015 and December 2017 at Princess Margaret Cancer Centre (Toronto, Canada) using the commercially available artificial intelligence engine, DARWEN (Pentavere, Ontario, Canada). For comparison, 100 of 333 patients that received systemic therapy were randomly selected and clinical data manually extracted by two trained abstractors using the same accepted gold standard feature definitions, including patient, disease characteristics, and treatment data. All cases were re-reviewed by an expert adjudicator. Accuracy and concordance between automated and manual methods are reported. Results: Automated extraction required considerably less time (

Introduction: In addition to the higher prevalence of EGFR mutations found among lung cancer cases in East Asian patients, it is unclear whether there are differences in treatment outcomes by ethnicity—that is, East Asian versus non–East Asian. Methods: Patients diagnosed with EGFR-mutant lung cancer between January 2004 and October 2014 at a single center were reviewed. Data captured included demographics, tumor and treatment information, and survival. Survival of patients of East Asian and non–East Asian ancestry was compared, including in the subgroup that received EGFR tyrosine kinase inhibitor (TKI) for advanced disease and in those with early-stage disease that underwent surgical resection. Results: A total of 348 patients with EGFR-mutant NSCLC were identified. There was a higher proportion of nonsmokers among those of East Asian ethnicity. No significant difference in survival was seen between patients of East Asian and non–East Asian ethnicity, median 6.7 years (95% confidence interval [CI]: 5.4–not applicable) and 5.4 years (95% CI: 4.1–7.2), respectively (p = 0.09). Among 196 patients that received treatment with EGFR TKI, the median survival from TKI initiation was also similar for those of East Asian and non–East Asian ethnicity, 3.0 years (95% CI: 2.1–3.5) and 2.7 years (95% CI: 2.2–3.5), respectively. Among the early-stage patients that underwent surgical resection (n = 163), those of East Asian ethnicity had similar median recurrence-free survival from surgery compared with non–East Asian patients, 5.3 years (95% CI: 3.5–not applicable) and 5.1 years (95% CI: 3.3–7.2), respectively. Conclusions: In a cohort of patients with EGFR-mutant lung cancer with access to uniform standards of care, East Asian ethnicity was not associated with improved survival after treatment with EGFR TKI or surgical resection.