Dataset Information

Neuron-Specific Enolase Is an Independent Prognostic Factor in Resected Lung Adenocarcinoma Patients with Anaplastic Lymphoma Kinase Gene Rearrangements.

ABSTRACT: BACKGROUND An extensive body of research reveals the clinical value of serum tumor markers in lung cancer patients, including carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCCA), cytokeratin-19 fragments (Cyfra21-1), and neuron-specific enolase (NSE), but little is known about the clinical properties of these serum tumor markers in anaplastic lymphoma kinase (ALK)-positive lung cancer patients. MATERIAL AND METHODS We retrospectively analyzed 54 patients harboring ALK rearrangements and 520 patients without ALK rearrangements, and all these patients were treated exclusively by surgery between 2011 and 2016. RESULTS NSE level (P=0.007 for OS) was identified as an independent prognostic factor among patients with resected ALK-positive adenocarcinoma of the lung. CONCLUSIONS A high level of NSE is associated with worse outcome among resected lung adenocarcinoma patients harboring ALK rearrangements.

SUBMITTER: Li S

PROVIDER: S-EPMC6353286 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Neuron-Specific Enolase Is an Independent Prognostic Factor in Resected Lung Adenocarcinoma Patients with Anaplastic Lymphoma Kinase Gene Rearrangements.

Li Shouying S Cao Lianjing L Wang Xinyue X Wang Fan F Wang Liuchun L Jiang Richeng R

Medical science monitor : international medical journal of experimental and clinical research 20190123

BACKGROUND An extensive body of research reveals the clinical value of serum tumor markers in lung cancer patients, including carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCCA), cytokeratin-19 fragments (Cyfra21-1), and neuron-specific enolase (NSE), but little is known about the clinical properties of these serum tumor markers in anaplastic lymphoma kinase (ALK)-positive lung cancer patients. MATERIAL AND METHODS We retrospectively analyzed 54 patients harboring ALK rearrang ...[more]

PMID: 30673691

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Project description:Purpose:To develop a radiogenomics classifier to assess anaplastic lymphoma kinase (ALK) gene rearrangement status in pretreated solid lung adenocarcinoma noninvasively. Materials and Methods:This study consisted of 140 consecutive pretreated solid lung adenocarcinoma patients with complete enhanced CT scans who were tested for both EGFR mutations and ALK status. Pre-contrast CT and standard post-contrast CT radiogenomics machine learning classifiers were designed as two separate classifiers. In each classifier, dataset was randomly split into training and independent testing group on a 7:3 ratio, accordingly subjected to a 5-fold cross-validation. After normalization, best feature subsets were selected by Pearson correlation coefficient (PCC) and analysis of variance (ANOVA) or recursive feature elimination (RFE), whereupon a radiomics classifier was built with support vector machine (SVM). The discriminating performance was assessed with the area under receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results:In classifier one, 98 cases were selected as training data set, 42 cases as independent testing data set. In classifier two, 87 cases were selected as training data set, 37 cases as independent testing data set. Both classifiers extracted 851 radiomics features. The top 25 pre-contrast features and top 19 post-contrast features were selected to build optimal ALK+ radiogenomics classifiers accordingly. The accuracies, AUCs, sensitivity, specificity, PPV, and NPV of pre-contrast CT classifier were 78.57%, 80.10% (CI: 0.6538-0.9222), 71.43%, 82.14%, 66.67%, and 85.19%, respectively. Those results of standard post-contrast CT classifier were 81.08%, 82.85% (CI: 0.6630-0.9567), 76.92%, 83.33%, 71.43%, and 86.96%. Conclusion:Solid lung adenocarcinoma ALK+ radiogenomics classifier of standard post-contrast CT radiomics biomarkers produced superior performance compared with that of pre-contrast one, suggesting that post-contrast CT radiomics should be recommended in the context of solid lung adenocarcinoma radiogenomics AI. Standard post-contrast CT machine learning radiogenomics classifier could help precisely identify solid adenocarcinoma ALK rearrangement status, which may act as a pragmatic and cost-efficient substitute for traditional invasive ALK status test.

Dataset Information

Neuron-Specific Enolase Is an Independent Prognostic Factor in Resected Lung Adenocarcinoma Patients with Anaplastic Lymphoma Kinase Gene Rearrangements.

Publications

Neuron-Specific Enolase Is an Independent Prognostic Factor in Resected Lung Adenocarcinoma Patients with Anaplastic Lymphoma Kinase Gene Rearrangements.

Similar Datasets

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