Dataset Information

A molecular and staging model predicts survival in patients with resected non-small cell lung cancer.

ABSTRACT:

Background

The current TNM staging system is far from perfect in predicting the survival of individual non-small cell lung cancer (NSCLC) patients. In this study, we aim to combine clinical variables and molecular biomarkers to develop a prognostic model for patients with NSCLC.

Methods

Candidate molecular biomarkers were extracted from the Gene Expression Omnibus (GEO), and Cox regression analysis was performed to determine significant prognostic factors. The survival prediction model was constructed based on multivariable Cox regression analysis in a cohort of 152 NSCLC patients. The predictive performance of the model was assessed by the Area under the Receiver Operating Characteristic Curve (AUC) and Kaplan-Meier survival analysis.

Results

The survival prediction model consisting of two genes (TPX2 and MMP12) and two clinicopathological factors (tumor stage and grade) was developed. The patients could be divided into either high-risk group or low-risk group. Both disease-free survival and overall survival were significantly different among the diverse groups (P?ConclusionsWe developed a novel prognostic model which can accurately predict outcomes for patients with NSCLC after surgery.

SUBMITTER: Liu L

PROVIDER: S-EPMC6180609 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Publications

A molecular and staging model predicts survival in patients with resected non-small cell lung cancer.

Liu Lei L Shi Minxin M Wang Zhiwei Z Lu Haimin H Li Chang C Tao Yu Y Chen Xiaoyan X Zhao Jun J

BMC cancer 20181011 1

<h4>Background</h4>The current TNM staging system is far from perfect in predicting the survival of individual non-small cell lung cancer (NSCLC) patients. In this study, we aim to combine clinical variables and molecular biomarkers to develop a prognostic model for patients with NSCLC.<h4>Methods</h4>Candidate molecular biomarkers were extracted from the Gene Expression Omnibus (GEO), and Cox regression analysis was performed to determine significant prognostic factors. The survival prediction ...[more]

PMID: 30305064

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Project description:BackgroundThe frequent recurrence of early-stage non-small-cell lung cancer (NSCLC) is generally attributable to metastatic disease undetected at complete resection. Management of such patients depends on prognostic staging to identify the individuals most likely to have occult disease. We aimed to develop and validate a practical, reliable assay that improves risk stratification compared with conventional staging.MethodsA 14-gene expression assay that uses quantitative PCR, runs on formalin-fixed paraffin-embedded tissue samples, and differentiates patients with heterogeneous statistical prognoses was developed in a cohort of 361 patients with non-squamous NSCLC resected at the University of California, San Francisco. The assay was then independently validated by the Kaiser Permanente Division of Research in a masked cohort of 433 patients with stage I non-squamous NSCLC resected at Kaiser Permanente Northern California hospitals, and on a cohort of 1006 patients with stage I-III non-squamous NSCLC resected in several leading Chinese cancer centres that are part of the China Clinical Trials Consortium (CCTC).FindingsKaplan-Meier analysis of the Kaiser validation cohort showed 5 year overall survival of 71·4% (95% CI 60·5-80·0) in low-risk, 58·3% (48·9-66·6) in intermediate-risk, and 49·2% (42·2-55·8) in high-risk patients (p(trend)=0·0003). Similar analysis of the CCTC cohort indicated 5 year overall survivals of 74·1% (66·0-80·6) in low-risk, 57·4% (48·3-65·5) in intermediate-risk, and 44·6% (40·2-48·9) in high-risk patients (p(trend)<0·0001). Multivariate analysis in both cohorts indicated that no standard clinical risk factors could account for, or provide, the prognostic information derived from tumour gene expression. The assay improved prognostic accuracy beyond National Comprehensive Cancer Network criteria for stage I high-risk tumours (p<0·0001), and differentiated low-risk, intermediate-risk, and high-risk patients within all disease stages.InterpretationOur practical, quantitative-PCR-based assay reliably identified patients with early-stage non-squamous NSCLC at high risk for mortality after surgical resection.FundingUCSF Thoracic Oncology Laboratory and Pinpoint Genomics.

Project description:BackgroundLocoregional recurrence is of high risk and is associated with a poor prognosis in terms of OS for non-small cell lung cancer (NSCLC). Local control is essential for radical cure of NSCLC. Previous studies have investigated the clinicopathological risk factors for locoregional recurrence, but the genomic biomarkers associated with locoregional recurrence have been inadequately studied.MethodsA total of 118 patients who underwent tumor resection with mutation-detected tumor specimens were included. Tumor samples at surgery and pretreatment/postoperative blood samples were collected for mutational profiling.ResultsAmong 48 patients with disease recurrence, 46% developed locoregional recurrence (LR) and 75% developed distant metastasis (DM). The 3-year actuarial risk of LR and DM was 25% and 43%, respectively. The first sites of failure were locoregional only (29%), locoregional and distant (10%), and distant only (61%). Patients with LR showed significantly higher ctDNA level than those with only DM at the time of initial recurrence. On multivariate analysis of baseline risk factors, the presence of allele frequency heterogeneity and baseline ctDNA shedding were found to be independently associated with a higher risk of LR. Patients with disruptive TP53 mutations had significantly lower LR-free survival as compared to patients with wild-type TP53 or nondisruptive mutations. EGFR mutations showed a favorable prognostic value for LR and is not induced by EGFR tyrosine kinase inhibitor therapy. Both disruptive TP53 mutation and EGFR mutation remained the significant prognostic factor after adjustment for histological type, pathologic nodal stage and adjuvant therapy.ConclusionsNearly half of disease recurrences after surgery for NSCC involved locoregional sites. We identified genomic biomarkers from baseline tumor and ctDNA samples which showed promising prognostic value for LR only. This can help identify patients who had a higher risk of locoregional recurrence regardless of the risk of distant metastasis.

Dataset Information

A molecular and staging model predicts survival in patients with resected non-small cell lung cancer.

Background

Methods

Results

Publications

A molecular and staging model predicts survival in patients with resected non-small cell lung cancer.

Similar Datasets

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