Dataset Information

MicroRNA-31 predicts the presence of lymph node metastases and survival in patients with lung adenocarcinoma.

ABSTRACT: PURPOSE:We conducted genome-wide miRNA-sequencing (miRNA-seq) in primary cancer tissue from patients of lung adenocarcinoma to identify markers for the presence of lymph node metastasis. EXPERIMENTAL DESIGN:Markers for lymph node metastasis identified by sequencing were validated in a separate cohort using quantitative PCR. After additional validation in the The Cancer Genome Atlas (TCGA) dataset, functional characterization studies were conducted in vitro. RESULTS:MiR-31 was upregulated in lung adenocarcinoma tissues from patients with lymph node metastases compared with those without lymph node metastases. We confirmed miR-31 to be upregulated in lymph node-positive patients in a separate patient cohort (P = 0.009, t test), and to be expressed at higher levels in adenocarcinoma tissue than in matched normal adjacent lung tissues (P < 0.0001, paired t test). MiR-31 was then validated as a marker for lymph node metastasis in an external validation cohort of 233 lung adenocarcinoma cases of the TCGA (P = 0.031, t test). In vitro functional assays showed that miR-31 increases cell migration, invasion, and proliferation in an ERK1/2 signaling-dependent manner. Notably, miR-31 was a significant predictor of survival in a multivariate cox regression model even when controlling for cancer staging. Exploratory in silico analysis showed that low expression of miR-31 is associated with excellent survival for T2N0 patients. CONCLUSIONS:We applied miRNA-seq to study microRNomes in lung adenocarcinoma tissue samples for the first time and potentially identified a miRNA predicting the presence of lymph node metastasis and survival outcomes in patients of lung adenocarcinoma.

SUBMITTER: Meng W

PROVIDER: S-EPMC3823052 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MicroRNA-31 predicts the presence of lymph node metastases and survival in patients with lung adenocarcinoma.

Meng Wei W Ye Zhenqing Z Cui Ri R Perry James J Dedousi-Huebner Vaia V Huebner Alexander A Wang Yao Y Li Bin B Volinia Stefano S Nakanishi Hiroshi H Kim Taewan T Suh Sung-Suk SS Ayers Leona W LW Ross Patrick P Croce Carlo M CM Chakravarti Arnab A Jin Victor X VX Lautenschlaeger Tim T

Clinical cancer research : an official journal of the American Association for Cancer Research 20130814 19

<h4>Purpose</h4>We conducted genome-wide miRNA-sequencing (miRNA-seq) in primary cancer tissue from patients of lung adenocarcinoma to identify markers for the presence of lymph node metastasis.<h4>Experimental design</h4>Markers for lymph node metastasis identified by sequencing were validated in a separate cohort using quantitative PCR. After additional validation in the The Cancer Genome Atlas (TCGA) dataset, functional characterization studies were conducted in vitro.<h4>Results</h4>MiR-31 w ...[more]

PMID: 23946296

Similar Datasets

Project description:BackgroundThe essential roles of the tumor microenvironment (TME) have been recognized during the initiation and progression of primary lung adenocarcinoma (LUAD). The aim of the present study was to delineate the immune landscape in both primary cancer and matched lymph node metastasis from a cohort of locally advanced stage LUAD patients with distinct outcomes.MethodsFormalin-fixed, paraffin-embedded samples were collected from 36 locally advanced LUAD patients. Transcriptome data of the tumor immune microenvironment were resolved using an immune oncology panel RNA sequencing platform. Bioinformatics approaches were used to determine the differentially expressed genes (DEGs), dysregulated pathways, and immune cell fraction between patients with early recurrence (ER) and late recurrence (LR).ResultsHere, we showed that in primary cancer tissues, 23 DEGs were obtained between patients with ER and LR. Functional analysis revealed that the LR in LUAD patients may be associated with enriched gene sets belonging to the antigen presentation and MHC protein complex, innate immune response, and IFN-γ signaling pathways. Next, the transcriptome data were adopted to quantify immune cell fractions, indicating that high infiltration of mast cells and neutrophils was correlated with ER. Interestingly, similar findings were observed in metastatic lymph nodes from patients suffering from ER or LR. By analyzing the shared immune features of primary cancers and lymphatic metastases, we unraveled the prognostic value and joint utility of two DEGs, CORO1A and S100A8.ConclusionsIn LUAD, the enrichment in antigen presentation, MHC protein complex, and IFN-γ signaling, and low infiltration of neutrophils in primary or metastatic nodules may be indications for a favorable prognosis. Integrated with bioinformatics approaches, transcriptome data of immune-related genes from formalin-fixed, paraffin-embedded (FFPE) samples can effectively profile the landscape of the tumor immune microenvironment and help predict clinical outcomes.

Project description:Background & aimsPancreatic ductal adenocarcinomas (PDACs) frequently metastasize to the lymph nodes; strategies are needed to identify patients at highest risk for lymph node metastases. We performed genome-wide expression profile analyses of PDAC specimens, collected during surgery or endoscopic ultrasound-guided fine-need aspiration (EUS-FNA), to identify a microRNA (miRNA) signature associated with metastasis to lymph nodes.MethodsFor biomarker discovery, we analyzed miRNA expression profiles of primary pancreatic tumors from 3 public data sets (The Cancer Genome Atlas, GSE24279, and GSE32688). We then analyzed 157 PDAC specimens (83 from patients with lymph node metastases and 74 without) from Japan, collected from 2001 through 2017, for the training cohort and 107 PDAC specimens (63 from patients with lymph node metastases and 44 without) from a different medical center in Japan, from 2002 through 2016, for the validation cohort. We also analyzed samples collected by EUS-FNA before surgery from 47 patients (22 patients with lymph node metastases and 25 without; 17 for the training cohort and 30 from the validation cohort) and 62 specimens before any treatment from patients who received neoadjuvant chemotherapy (9 patients with lymph node metastasis and 53 without) for additional validation. Multivariate logistic regression analyses were used to evaluate the statistical differences in miRNA expression between patients with vs without metastases.ResultsWe identified an miRNA expression pattern associated with diagnosis of PDAC metastasis to lymph nodes. Using logistic regression analysis, we optimized and trained a 6-miRNA risk prediction model for the training cohort; this model discriminated patients with vs without lymph node metastases with an area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.77-0.89). In the validation cohort, the model identified patients with vs without lymph node metastases with an AUC of 0.73 (95% CI, 0.64-0.81). In EUS-FNA biopsy samples, the model identified patients with vs without lymph node metastases with an AUC of 0.78 (95% CI, 0.63-0.89). The miRNA expression pattern was an independent predictor of PDAC metastasis to lymph nodes in the validation cohort (odds ratio, 17.05; 95% CI, 2.43-119.57) and in the EUS-FNA cohort (95% CI, 0.65-0.87).ConclusionsUsing data and tumor samples from 3 independent cohorts, we identified an miRNA signature that identifies patients at risk for PDAC metastasis to lymph nodes. The signature has similar levels of accuracy in the analysis of resected tumor specimens and EUS-FNA biopsy specimens. This model might be used to select treatment and management strategies for patients with PDAC.

Dataset Information

MicroRNA-31 predicts the presence of lymph node metastases and survival in patients with lung adenocarcinoma.

Publications

MicroRNA-31 predicts the presence of lymph node metastases and survival in patients with lung adenocarcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets