Characterization of microRNA transcriptome in lung cancer by next‐generation deep sequencing. Issue 7 (15th April 2014)

• Record Type: Journal Article
• Authors: Ma, Jie; Mannoor, Kaiissar; Gao, Lu; Tan, Afang; Guarnera, Maria A.; Zhan, Min; Shetty, Amol; Stass, Sanford A.; Xing, Lingxiao; Jiang, Feng
• Is Part Of: Molecular oncology. Volume 8:Issue 7(2014:Oct.)
• Page Start: 1208
• Page End: 1219
• Publication Date: 2014-04-15
• Subjects: Lung cancer -- microRNA -- Biomarkers -- Therapy -- Deep sequencing; Cancer -- Molecular aspects -- Periodicals; 616.994005
• DOI: 10.1016/j.molonc.2014.03.019
• Languages: English
• ISSNs: 1574-7891

Abstract

Abstract : Non‐small cell lung cancer (NSCLC) is the leading cause of cancer death. Systematically characterizing miRNAs in NSCLC will help develop biomarkers for its diagnosis and subclassification, and identify therapeutic targets for the treatment. We used next‐generation deep sequencing to comprehensively characterize miRNA profiles in eight lung tumor tissues consisting of two major types of NSCLC, squamous cell carcinoma (SCC) and adenocarcinoma (AC). We used quantitative PCR (qPCR) to verify the findings in 40 pairs of stage I NSCLC tissues and the paired normal tissues, and 60 NSCLC tissues of different types and stages. We also investigated the function of identified miRNAs in lung tumorigenesis. Deep sequencing identified 896 known miRNAs and 14 novel miRNAs, of which, 24 miRNAs displayed dysregulation with fold change ≥4.5 in either stage I ACs or SCCs or both relative to normal tissues. qPCR validation showed that 14 of 24 miRNAs exhibited consistent changes with deep sequencing data. Seven miRNAs displayed distinctive expressions between SCC and AC, from which, a panel of four miRNAs (miRs‐944, 205‐3p, 135a‐5p, and 577) was identified that cold differentiate SCC from AC with 93.3% sensitivity and 86.7% specificity. Manipulation of miR‐944 expression in NSCLC cells affected cell growth, proliferation, and invasion by targeting a tumor suppressor, SOCS4. Evaluating miR‐944 in 52 formalin‐fixed paraffin‐embedded SCC tissues revealed that miR‐944 expression was associated with lymph node metastasis. This study presents the earliest use of deep sequencing for profiling miRNAs in lung tumor specimens. The identified miRNA signatures may provide biomarkers for early detection, subclassification, and predicting metastasis, and potential therapeutic targets of NSCLC. Highlights: Using deep sequencing to characterize miRNAs in lung tumor tissues. Validating the findings in additional tumor tissues. Investigating the function of identified miRNAs in vitro and in vivo. The miRNAs provide markers for classification and outcome of lung cancer. The identified miRNAs provide potential therapeutic targets of lung cancer.