Dataset Information

Establishment and validation of a 7-microRNA prognostic signature for non-small cell lung cancer.

ABSTRACT: Purpose:A series of microRNAs (miRNAs) have been identified as associated with the survival of patients with non-small-cell lung cancer (NSCLC). The aim of the present study was to explore whether combination of these experimentally validated individual miRNA biomarkers could be used to further increase their prognostic power in NSCLC. Patients and methods:Based on previously validated NSCLC prognostic miRNAs, gene signatures that could discriminate high-risk subgroups with poor clinical outcome in four NSCLC miRNA expression datasets (GSE13937, GSE16025, The Cancer Genome Atlas Lung Adenocarcinoma, and TCGA lung squamous cell carcinoma) were developed using the SurvMicro tool. The potential of the miRNA signature established was validated by quantitative real-time PCR analysis of clinical NSCLC samples, and its prognostic power evaluated using the survivalROC method. Results:We developed two miRNA signatures with prognostic significance for NSCLC, comprising 12- and 7-miRNAs. The 7-miRNA signature (miR-148b, miR-365, miR-32, miR-375, miR-21, miR-125b, and miR-155) was a subset of a 12-miRNA set that retained prognostic power across NSCLC cohorts. Compared with previously established miRNA signatures, our 7-miRNA signature has similar potential, while comprising fewer miRNA components. The prognostic ability of the 7-miRNA signature was validated experimentally in an independent NSCLC cohort using real-time PCR (HR=3.4847, 95% CI=1.3693-8.8680, P=0.0092), and this signature, combined with tumor pathological stage, had superior prognostic ability compared with tumor stage alone. Conclusion:Our data indicate that the established 7-miRNA signature is simple, robust, and may have greater clinical prognostic utility for patients with NSCLC.

SUBMITTER: Wang N

PROVIDER: S-EPMC6140736 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Establishment and validation of a 7-microRNA prognostic signature for non-small cell lung cancer.

Wang Nan N Guo Huihui H Dong Zhaohuo Z Chen Qiuqiang Q Zhang Xilin X Shen Weiyun W Bao Ying Y Wang Xiang X

Cancer management and research 20180912

<h4>Purpose</h4>A series of microRNAs (miRNAs) have been identified as associated with the survival of patients with non-small-cell lung cancer (NSCLC). The aim of the present study was to explore whether combination of these experimentally validated individual miRNA biomarkers could be used to further increase their prognostic power in NSCLC.<h4>Patients and methods</h4>Based on previously validated NSCLC prognostic miRNAs, gene signatures that could discriminate high-risk subgroups with poor c ...[more]

PMID: 30254489

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Project description:BackgroundCT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.ResultsBlood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n?=?363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n?=?138 in the first validation and n?=?135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation.ConclusionsSelecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules.

Project description:Importance:The prevalence of early-stage non-small cell lung cancer (NSCLC) is expected to increase with recent implementation of annual screening programs. Reliable prognostic biomarkers are needed to identify patients at a high risk for recurrence to guide adjuvant therapy. Objective:To develop a robust, individualized immune signature that can estimate prognosis in patients with early-stage nonsquamous NSCLC. Design, Setting, and Participants:This retrospective study analyzed the gene expression profiles of frozen tumor tissue samples from 19 public NSCLC cohorts, including 18 microarray data sets and 1 RNA-Seq data set for The Cancer Genome Atlas (TCGA) lung adenocarcinoma cohort. Only patients with nonsquamous NSCLC with clinical annotation were included. Samples were from 2414 patients with nonsquamous NSCLC, divided into a meta-training cohort (729 patients), meta-testing cohort (716 patients), and 3 independent validation cohorts (439, 323, and 207 patients). All patients underwent surgery with a negative surgical margin, received no adjuvant or neoadjuvant therapy, and had publicly available gene expression data and survival information. Data were collected from July 22 through September 8, 2016. Main Outcomes and Measures:Overall survival. Results:Of 2414 patients (1205 men [50%], 1111 women [46%], and 98 of unknown sex [4%]; median age [range], 64 [15-90] years), a prognostic immune signature of 25 gene pairs consisting of 40 unique genes was constructed using the meta-training data set. In the meta-testing and validation cohorts, the immune signature significantly stratified patients into high- vs low-risk groups in terms of overall survival across and within subpopulations with stage I, IA, IB, or II disease and remained as an independent prognostic factor in multivariate analyses (hazard ratio range, 1.72 [95% CI, 1.26-2.33; P?<?.001] to 2.36 [95% CI, 1.47-3.79; P?<?.001]) after adjusting for clinical and pathologic factors. Several biological processes, including chemotaxis, were enriched among genes in the immune signature. The percentage of neutrophil infiltration (5.6% vs 1.8%) and necrosis (4.6% vs 1.5%) was significantly higher in the high-risk immune group compared with the low-risk groups in TCGA data set (P?<?.003). The immune signature achieved a higher accuracy (mean concordance index [C-index], 0.64) than 2 commercialized multigene signatures (mean C-index, 0.53 and 0.61) for estimation of survival in comparable validation cohorts. When integrated with clinical characteristics such as age and stage, the composite clinical and immune signature showed improved prognostic accuracy in all validation data sets relative to molecular signatures alone (mean C-index, 0.70 vs 0.63) and another commercialized clinical-molecular signature (mean C-index, 0.68 vs 0.65). Conclusions and Relevance:The proposed clinical-immune signature is a promising biomarker for estimating overall survival in nonsquamous NSCLC, including early-stage disease. Prospective studies are needed to test the clinical utility of the biomarker in individualized management of nonsquamous NSCLC.

Project description:Despite decades of efforts, non-small-cell lung cancer (NSCLC) remains the leading cause of cancer mortality globally primarily due to the challenge in early detection of the cancer. Being an important player in cancer development, the dysregulated miRNAs have been shown promising values as non-invasive diagnostic and prognostic biomarkers for NSCLC. The aim of our study is to access the efficacy and reliability of a potential circulating miRNA panel in early diagnosis of NSCLC. We first selected eight candidate miRNAs, miR-146b, miR-205, miR-29c, miR-31, miR-30b, miR-337, miR-411, and miR-708, which have been shown frequently aberrant in primary NSCLC patients based on our previous studies and other reports. The serum level of each of these miRNAs was evaluated by quantitative real-time PCR (qRT-PCR) in training and testing sets. We found that 5 out of 8 miRNAs (miR-146b, miR-205, miR-29c, miR-30b, and miR-337) were significantly up-regulated in NSCLCs patients compared to healthy or cancer-free controls in both training and testing sets. Based on the logistic regression model, a 4-miRNAs set (miR-146b, miR-205, miR-29c and miR-30b) was picked out of the 5 miRNAs owing to its excellent diagnostic power for NSCLC patients in the training set (AUC=0.99, accuracy=95.00%), the testing set (AUC=0.93, accuracy=89.69%), and the training-testing combined set ( AUC=0.96, accuracy=92.00%). When pathological subtypes of NSCLC are compared, this 4-miRNA panel carried a relatively higher prediction power and higher sensitivity for adenocarcinoma (AC) (AUC=0.98, sensitivity=99.10%) than for squamous cell carcinoma (SCC) (AUC=0.93, sensitivity=90.32%). Additionally, this panel demonstrated a comparable diagnostic capacity for stage I (AUC=0.96) and stage II-III (AUC=0.95) of NSCLC, suggesting its role in reflecting the tumor load. Importantly, the high levels of miR-146b and miR-29c in serum were significantly associated with poor 5-year overall survival (OS) (both p=0.04). Further survival analysis showed that high level of miR-146b in serum is specifically correlated with poor survival rate in SCC patients (p=0.0035) but not in AC patients (p=0.83), consistent with our previous finding that the high tissue expression of miR-146b in lung cancer specimen is indicative of a poor prognosis for SCC patients. Altogether, our study demonstrated that the 4-miRNA panel is a novel, sensitive and non-invasive serum marker for the early diagnosis of NSCLC.

Dataset Information

Establishment and validation of a 7-microRNA prognostic signature for non-small cell lung cancer.

Publications

Establishment and validation of a 7-microRNA prognostic signature for non-small cell lung cancer.

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