Dataset Information

MDC and BLC are independently associated with the significant risk of early stage lung adenocarcinoma.

ABSTRACT:

Background

This prospective study was designed to investigate the association between ten circulating inflammatory biomarkers and the risk for early stage lung adenocarcinoma.

Methods

All inflammatory biomarkers were measured in 228 patients with early stage (IA to IIB) lung adenocarcinoma and 228 age-, sex- and smoking-matched healthy controls by using the Luminex bead-based assay.

Results

Only two biomarkers were significantly associated with the risk of early stage lung adenocarcinoma after the Bonferroni correction: the multivariate odd ratio (OR) (95% confidence interval or CI) was 0.29 (0.16-0.53) for MDC and 4.17 (2.23-7.79) for BLC for the comparison of patients in the 4th quartile with the 1st quartile (both P<0.0001). When analysis was restricted to never smokers (196 patients/196 controls), MDC and BLC were still significantly associated with the risk of early stage lung adenocarcinoma (OR, 95% CI, P: 0.37, 0.21-0.66, P<0.0001 for MDC and 2.78, 1.48-5.22, P =0.001 for BLC). Furthermore, elevated BLC was associated with a 2.90-fold (95% CI: 1.03-8.17, P=0.037) increased risk of subcentimeter lung adenocarcinoma, and there was an increasing trend for BLC with the progression of subcentimeter lung adenocarcinoma.

Conclusion

Our findings demonstrated that MDC and BLC were independently associated with the significant risk of early stage lung adenocarcinoma, even in non-smokers and in stage IA patients. BLC was further identified to play a carcinogenic role in the progression of lung adenocarcinoma.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC5347752 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Publications

MDC and BLC are independently associated with the significant risk of early stage lung adenocarcinoma.

Zhang Yanwei Y Yu Keke K Hu Song S Lou Yuqing Y Liu Chunxing C Xu Jianlin J Li Rong R Zhang Xueyan X Wang Huimin H Han Baohui B

Oncotarget 20161201 50

<h4>Background</h4>This prospective study was designed to investigate the association between ten circulating inflammatory biomarkers and the risk for early stage lung adenocarcinoma.<h4>Methods</h4>All inflammatory biomarkers were measured in 228 patients with early stage (IA to IIB) lung adenocarcinoma and 228 age-, sex- and smoking-matched healthy controls by using the Luminex bead-based assay.<h4>Results</h4>Only two biomarkers were significantly associated with the risk of early stage lung ...[more]

PMID: 27811371

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Project description:BackgroundIn East Asia, the number of patients with adenocarcinoma, especially those presenting with ground-glass nodules (GGNs), is gradually increasing. Family aggregation of pulmonary GGNs is not uncommon; however, genetic predisposition in these patients remains poorly understood and identification of genes involved in the cause of these early-stage lung cancers might contribute to understanding of the underlying mechanisms and potential prevention strategies.MethodsFifty patients with early-stage lung adenocarcinoma (LUAD) presenting as GGNs and a first-degree family history of lung cancer (FHLC) from 34 independent families were enrolled into this study. Germline mutations of these patients were analyzed with whole exome sequencing (WES) and compared with age- and sex-matched 39 patients with sporadic lung cancer and 689 local healthy people. We used a stepwise variant filtering strategy, gene-based burden testing, and enrichment analysis to investigate rare but potentially pathogenic heritable mutations. Somatic tumor mutations were analyzed to consolidate germline findings.ResultsIn total, 1,571 single nucleotide variants (SNVs) and 238 frameshifts with a minor allele frequency (MAF) <0.01, which were rare, recurrent, and potentially damaging candidates, were finally identified through the filtering in the GGN cohort. Pathway analysis showed the extracellular matrix to be the top dysregulated pathway. Gene-based burden testing of these highly disruptive risk-conferring heritable variants showed that MSH5 [odds ratio (OR), 9.28, 95% confidence interval (CI): 2.49-35.87], MMP9 (OR, 8.11, 95% CI: 2.22-28.43), and CYP2D6 (OR, 8.09, 95% CI: 2.68-24.92) were significantly enriched in our cohort (P<0.05). The number of rare damaging germline variants in non-smoking patients was significantly higher than that of smoking-affected patients (Spearman's ρ=-0.39, P=0.02).ConclusionsHeritable, potentially deleterious, and rare candidate variants of MSH5, MMP9 and CYP2D6 were significantly associated with early-stage LUAD presenting with GGNs. Nonsmoking patients likely have a higher genetic predisposition to this type of cancer than smoking-affected patients. These results have extended our understanding of the underlying mechanisms of early-stage LUAD.

Project description:ImportanceRecommendations for adjuvant therapy after surgical resection of lung adenocarcinoma (LUAD) are based solely on TNM classification but are agnostic to genomic and high-risk clinicopathologic factors. Creation of a prediction model that integrates tumor genomic and clinicopathologic factors may better identify patients at risk for recurrence.ObjectiveTo identify tumor genomic factors independently associated with recurrence, even in the presence of aggressive, high-risk clinicopathologic variables, in patients with completely resected stages I to III LUAD, and to develop a computational machine-learning prediction model (PRecur) to determine whether the integration of genomic and clinicopathologic features could better predict risk of recurrence, compared with the TNM system.Design, setting, and participantsThis prospective cohort study included 426 patients treated from January 1, 2008, to December 31, 2017, at a single large cancer center and selected in consecutive samples. Eligibility criteria included complete surgical resection of stages I to III LUAD, broad-panel next-generation sequencing data with matched clinicopathologic data, and no neoadjuvant therapy. External validation of the PRecur prediction model was performed using The Cancer Genome Atlas (TCGA). Data were analyzed from 2014 to 2018.Main outcomes and measuresThe study end point consisted of relapse-free survival (RFS), estimated using the Kaplan-Meier approach. Associations among clinicopathologic factors, genomic alterations, and RFS were established using Cox proportional hazards regression. The PRecur prediction model integrated genomic and clinicopathologic factors using gradient-boosting survival regression for risk group generation and prediction of RFS. A concordance probability estimate (CPE) was used to assess the predictive ability of the PRecur model.ResultsOf the 426 patients included in the analysis (286 women [67%]; median age at surgery, 69 [interquartile range, 62-75] years), 318 (75%) had stage I cancer. Association analysis showed that alterations in SMARCA4 (clinicopathologic-adjusted hazard ratio [HR], 2.44; 95% CI, 1.03-5.77; P = .042) and TP53 (clinicopathologic-adjusted HR, 1.73; 95% CI, 1.09-2.73; P = .02) and the fraction of genome altered (clinicopathologic-adjusted HR, 1.03; 95% CI, 1.10-1.04; P = .005) were independently associated with RFS. The PRecur prediction model outperformed the TNM-based model (CPE, 0.73 vs 0.61; difference, 0.12 [95% CI, 0.05-0.19]; P < .001) for prediction of RFS. To validate the prediction model, PRecur was applied to the TCGA LUAD data set (n = 360), and a clear separation of risk groups was noted (log-rank statistic, 7.5; P = .02), confirming external validation.Conclusions and relevanceThe findings suggest that integration of tumor genomics and clinicopathologic features improves risk stratification and prediction of recurrence after surgical resection of early-stage LUAD. Improved identification of patients at risk for recurrence could enrich and enhance accrual to adjuvant therapy clinical trials.

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Dataset Information

MDC and BLC are independently associated with the significant risk of early stage lung adenocarcinoma.

Background

Methods

Results

Conclusion

Publications

MDC and BLC are independently associated with the significant risk of early stage lung adenocarcinoma.

Similar Datasets

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