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Introduction: Lung cancer is the most common cancer worldwide in mortality and the second in incidence. Epidemiological studies found a higher lung cancer risk for smoking women in comparison to men, but these sex differences, irrespective of smoking habits, remain controversial. One of the hypotheses concerns the genetic contribution of the sex chromosomes. However, while genome-wide association studies identified many lung cancer susceptibility loci, these analyses have excluded X-linked loci., Methods: To account for nongenetic factors, we first presented an association test based on an additive-multiplicative hazard model accounting for random/nonrandom X-inactivation process. A simulation study was performed to investigate the properties of the proposed test as compared with the Wald test from a Cox model with random X-inactivation process and the partial likelihood ratio test proposed by Xu et al. accounting for nonrandom X-inactivation process. Then, we performed an X chromosome-wide association study on 9,261 individuals from the population-based cohort CARTaGENE to identify susceptibility loci for lung cancer among current and past smokers. We adjusted for the PLCOm2012 lung cancer risk score used in screening programs., Results: Simulation results show the good behavior of the proposed test in terms of power and type I error probability as compared to the Xu et al. and the Wald test. Using the proposed test statistic and adjusting for the PLCOm2012 score, the X chromosome-wide statistical analysis identified two SNPs in low-linkage disequilibrium located in the IL1RAPL1 (IL-1 R accessory protein-like) gene: rs12558491 (p = 2.75×10-9) and rs12835699 (p = 1.26×10-6). For both SNPs, the minor allele was associated with lower lung cancer risk. Adjusting for multiple testing, no signal was detected using the Wald or the Xu et al. likelihood ratio tests., Conclusion: By taking into account smoking behavior and the X-inactivation process, the investigation of the X chromosome has shed a new light on the association between X-linked loci and lung cancer. We identified two loci associated with lung cancer located in the IL1RAPL1 gene. This finding would have been overlooked by examining only results from other test statistics., (© 2024 The Author(s). Published by S. Karger AG, Basel.)

Background: The PLCO m2012 prediction tool for risk of lung cancer has been proposed for a pilot program for lung cancer screening in Quebec, but has not been validated in this population. We sought to validate PLCO m2012 in a cohort of Quebec residents, and to determine the hypothetical performance of different screening strategies., Methods: We included smokers without a history of lung cancer from the population-based CARTaGENE cohort. To assess PLCO m2012 calibration and discrimination, we determined the ratio of expected to observed number of cases, as well as the sensitivity, specificity and positive predictive values of different risk thresholds. To assess the performance of screening strategies if applied between Jan. 1, 1998, and Dec. 31, 2015, we tested different thresholds of the PLCO m2012 detection of lung cancer over 6 years (1.51%, 1.70% and 2.00%), the criteria of Quebec's pilot program (for people aged 55-74 yr and 50-74 yr) and recommendations from 2021 United States and 2016 Canada guidelines. We assessed shift and serial scenarios of screening, whereby eligibility was assessed annually or every 6 years, respectively., Results: Among 11 652 participants, 176 (1.51%) lung cancers were diagnosed in 6 years. The PLCO m2012 tool underestimated the number of cases (expected-to-observed ratio 0.68, 95% confidence interval [CI] 0.59-0.79), but the discrimination was good (C-statistic 0.727, 95% CI 0.679-0.770). From a threshold of 1.51% to 2.00%, sensitivities ranged from 52.3% (95% CI 44.6%-59.8%) to 44.9% (95% CI 37.4%-52.6%), specificities ranged from 81.6% (95% CI 80.8%-82.3%) to 87.7% (95% CI 87.0%-88.3%) and positive predictive values ranged from 4.2% (95% CI 3.4%-5.1%) to 5.3% (95% CI 4.2%-6.5%). Overall, 8938 participants had sufficient data to test performance of screening strategies. If eligibility was estimated annually, Quebec pilot criteria would have detected fewer cancers than PLCO m2012 at a 2.00% threshold (48.3% v. 50.2%) for a similar number of scans per detected cancer. If eligibility was estimated every 6 years, up to 26 fewer lung cancers would have been detected; however, this scenario led to higher positive predictive values (highest for PLCO m2012 with a 2.00% threshold at 6.0%, 95% CI 4.8%-7.3%)., Interpretation: In a cohort of Quebec smokers, the PLCO m2012 risk prediction tool had good discrimination in detecting lung cancer, but it may be helpful to adjust the intercept to improve calibration. The implementation of risk prediction models in some of the provinces of Canada should be done with caution., Competing Interests: Competing interests: Nicole Ezer reports funding from the Canadian Institutes of Health Research and Rossy Cancer Network, a speaker fee from GSK, advisory board participation with GSK and receipt of study materials from COVIS Pharma. Martin Tammemägi developed the PLCOm2012 lung cancer risk prediction models (and related models), used in the current study. To date, he has not received any money for use of the model, nor does he anticipate any payments in the future. No other competing interests were declared., (© 2023 CMA Impact Inc. or its licensors.)

Microabstract: Integration of Next Generation Sequencing (NGS) information for use in distinguishing between Multiple Primary Lung Cancer and intrapulmonary metastasis was evaluated. We used a probabilistic model, comprehensive histologic assessment and NGS to classify patients. Integrating NGS data confirmed initial diagnosis (n = 41), revised the diagnosis (n = 12), while resulted in non-informative data (n = 8). Accuracy of diagnosis can be significantly improved with integration of NGS data., Background: Distinguishing between multiple primary lung cancers (MPLC) and intrapulmonary metastases (IPM) is challenging. The goal of this study was to evaluate how Next Generation Sequencing (NGS) information may be integrated in the diagnostic strategy., Patients and Methods: Patients with multiple lung adenocarcinomas were classified using both the comprehensive histologic assessment and NGS. We computed the joint probability of each pair having independent mutations by chance (thus being classified as MPLC). These probabilities were computed using the marginal mutation rates of each mutation, and the known negative dependencies between driver genes and different gene loci. With these NGS-driven data, cases were re-classified as MPLC or IPM., Results: We analyzed 61 patients with a total of 131 tumors. The most frequent mutation was KRAS (57.3%) which occured at a rate higher than expected (p < 0.001) in lung cancer. No mutation was detected in 25/131 tumors (19.1%). Discordant molecular findings between tumor sites were found in 46 patients (75.4%); 11 patients (18.0%) had concordant molecular findings, and 4 patients (6.6%) had concordant molecular findings at 2 of the 3 sites. After integration of the NGS data, the initial diagnosis was confirmed for 41 patients (67.2%), the diagnosis was revised for 12 patients (19.7%) or was considered as non-informative for 8 patients (13.1%)., Conclusion: Integrating the information of NGS data may significantly improve accuracy of diagnosis and staging., (Copyright © 2021. Published by Elsevier Ltd.)

In randomized clinical trials where the times to event of two treatment groups are compared under a proportional hazards assumption, it has been established that omitting prognostic factors from the model entails an underestimation of the hazards ratio. Heterogeneity due to unobserved covariates in cancer patient populations is a concern since genomic investigations have revealed molecular and clinical heterogeneity in these populations. In HIV prevention trials, heterogeneity is unavoidable and has been shown to decrease the treatment effect over time. This article assesses the influence of trial duration on the bias of the estimated hazards ratio resulting from omitting covariates from the Cox analysis. The true model is defined by including an unobserved random frailty term in the individual hazard that reflects the omitted covariate. Three frailty distributions are investigated: gamma, log-normal, and binary, and the asymptotic bias of the hazards ratio estimator is calculated. We show that the attenuation of the treatment effect resulting from unobserved heterogeneity strongly increases with trial duration, especially for continuous frailties that are likely to reflect omitted covariates, as they are often encountered in practice. The possibility of interpreting the long-term decrease in treatment effects as a bias induced by heterogeneity and trial duration is illustrated by a trial in oncology where adjuvant chemotherapy in stage 1B NSCLC was investigated., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Non-small-cell lung cancer (NSCLC) is a heterogeneous disease, with a burden of genomic alterations exceeding most other tumors. The goal of our study was to evaluate the frequencies of co-occurring mutations and copy-number aberrations (CNAs) within the same tumor and to evaluate their potential clinical impact. Mass-spectrometry based mutation profiling using a customized lung cancer panel evaluating 214 mutations across 26 key NSCLC genes was performed on 230 nonsquamous NSCLC and integrated with genome-wide CNAs and clinical variables. Among the 138 cases having at least one mutation, one-third (41, 29.7%) showed two or more mutations, either in the same gene (double mutation) or in different genes (co-mutations). In epidermal growth factor receptor (EGFR) mutant cancers, there was a double mutation in 18% and co-mutations in the following genes: TP53 (10%), PIK3CA (8%), STK11 (6%) and MET (4%). Significant relationships were detected between EGFR mutation and 1p, 7p copy gains (harboring the EGFR gene) as well as 13q copy loss. KRAS mutation was significantly related with 1q gain and 3q loss. For Stage I, tumors harboring at least one mutation or PIK3CA mutation were significantly correlated with poor prognosis (p-value = 0.02). When combining CNAs and mutational status, patients having both KRAS mutation and the highest related CNA (3q22.3 copy loss) showed a significant poorer prognosis (p-value = 0.03). Our study highlights the clinical relevance of studying tumor complexity by integrative genomic analysis and the need for developing assays that broadly screen for both "actionable" mutations and copy-number alterations to improve precision of stratified treatment approaches., (© 2014 UICC.)

Purpose: East-Asian (EA) patients with non-small-cell lung cancer (NSCLC) are associated with a high proportion of nonsmoking women, epidermal growth factor receptor (EGFR)-activating somatic mutations, and clinical responses to tyrosine kinase inhibitors. We sought to identify novel molecular differences between NSCLCs from EA and Western European (WE) patients., Experimental Design: A total of 226 lung adenocarcinoma samples from EA (n = 90) and WE (n = 136) patients were analyzed for copy number aberrations (CNA) by using a common high-resolution SNP (single nucleotide polymorphism) microarray platform. Univariate and multivariate analyses were carried out to identify CNAs specifically related to smoking history, EGFR mutation status, and ethnicity., Results: The overall genomic profiles of adenocarcinomas from EA and WE patients were highly similar. Univariate analyses revealed several CNAs significantly associated with ethnicity, EGFR mutation, and smoking, but not to gender, and KRAS or p53 mutations. A multivariate model identified four ethnic-specific recurrent CNAs-significantly higher rates of copy number gain were observed on 16p13.13 and 16p13.11 in EA tumors, whereas higher rates of genomic loss on 19p13.3 and 19p13.11 were observed in tumors from WE patients. We identified several potential driver genes in these regions, showing a positive correlation between cis-localized copy number changes and transcriptomic changes., Conclusion: 16p copy number gains (EA) and 19p losses (WE) are ethnic-specific chromosomal aberrations in lung adenocarcinoma. Patient ethnicity should be considered when evaluating future NSCLC therapies targeting genes located on these areas., (©2011 AACR.)

Purpose: This study aimed to investigate the role of the neurotensin/neurotensin receptor I (NTSR1) complex in non-small cell lung cancer (NSCLC) progression., Experimental Design: The expression of neurotensin and NTSR1 was studied by transcriptome analysis and immunohistochemistry in two series of 74 and 139 consecutive patients with pathologic stage I NSCLC adenocarcinoma. The findings were correlated with clinic-pathologic features. Experimental tumors were generated from the malignant human lung carcinoma cell line A459, and a subclone of LNM35, LNM-R. The role of the neurotensin signaling system on tumor growth and metastasis was investigated by small hairpin RNA-mediated silencing of NTSR1 and neurotensin., Results: Transcriptome analysis carried out in a series of 74 patients showed that the positive regulation of NTSR1 put it within the top 50 genes related with relapse-free survival. Immunohistochemistry revealed neurotensin- and NTSR1-positive staining in 60.4% and 59.7% of lung adenocarcinomas, respectively. At univariate analysis, NTSR1 expression was strongly associated with worse 5-year overall survival rate (P = 0.0081) and relapse-free survival (P = 0.0024). Multivariate analysis showed that patients over 65 years of age (P = 0.0018) and NTSR1 expression (P = 0.0034) were independent negative prognostic factors. Experimental tumor xenografts generated by neurotensin- and NTSR1-silenced human lung cancer cells revealed that neurotensin enhanced primary tumor growth and production of massive nodal metastasis via autocrine and paracrine regulation loops., Conclusion: NTSR1 expression was identified as a potential new prognostic biomarker for surgically resected stage I lung adenocarcinomas, as NTSR1 activation was shown to participate in lung cancer progression.

The role of adjuvant chemotherapy in patients with stage IB non-small-cell lung cancer (NSCLC) is controversial. Identifying patient subgroups with the greatest risk of relapse and, consequently, most likely to benefit from adjuvant treatment thus remains an important clinical challenge. Here, we hypothesized that recurrent patterns of genomic amplifications and deletions in lung tumors could be integrated with gene expression information to establish a robust predictor of clinical outcome in stage IB NSCLC. Using high-resolution microarrays, we generated tandem DNA copy number and gene expression profiles for 85 stage IB lung adenocarcinomas/large cell carcinomas. We identified specific copy number alterations linked to relapse-free survival and selected genes within these regions exhibiting copy number-driven expression to construct a novel integrated signature (IS) capable of predicting clinical outcome in this series (P = 0.02). Importantly, the IS also significantly predicted clinical outcome in two other independent stage I NSCLC cohorts (P = 0.003 and P = 0.025), showing its robustness. In contrast, a more conventional molecular predictor based solely on gene expression, while capable of predicting outcome in the initial series, failed to significantly predict outcome in the two independent data sets. Our results suggest that recurrent copy number alterations, when combined with gene expression information, can be successfully used to create robust predictors of clinical outcome in early-stage NSCLC. The utility of the IS in identifying early-stage NSCLC patients as candidates for adjuvant treatment should be further evaluated in a clinical trial.