Meta-analysis of human lung cancer microRNA expression profiling studies comparing cancer tissues with normal tissues

Abstract

BackgroundLung cancer is the major cause of cancer death globally, it is often diagnosed at an advanced stage and has one of the lowest survival rates of any type of cancer. The common interest in the field of lung cancer research is the identification of biomarkers for early diagnosis and accurate prognosis. There is increasing evidence to suggest that microRNAs play important and complex roles in lung cancer.MethodsA meta-analysis was conducted to review the published microRNA expression profiling studies that compared the microRNAs expression profiles in lung cancer tissues with those in normal lung tissues. A vote-counting strategy that considers the total number of studies reporting its differential expression, the total number of tissue samples used in the studies and the average fold change was employed.ResultsA total of 184 differentially expressed microRNAs were reported in the fourteen microRNA expression profiling studies that compared lung cancer tissues with normal tissues, with 61 microRNAs were reported in at least two studies. In the panel of consistently reported up-regulated microRNAs, miR-210 was reported in nine studies and miR-21 was reported in seven studies. In the consistently reported down-regulated microRNAs, miR-126 was reported in ten studies and miR-30a was reported in eight studies. Four up-regulated microRNAs (miR-210, miR-21, miR-31 and miR-182) and two down-regulated mcroiRNAs (miR-126 and miR-145) were consistently reported both in squamous carcinoma and adenocarcinoma-based subgroup analysis, with the other 14 microRNAs solely reported in one or the other subset.ConclusionsIn conclusion, the top two most consistently reported up-regulated microRNAs were miR-210 and miR-21. The results of this meta-analysis of human lung cancer microRNA expression profiling studies might provide some clues of the potential biomarkers in lung cancer. Further mechanistic and external validation studies are needed for their clinical significance and role in the development of lung cancer.

Different micro-RNA expression profiles distinguish subtypes of neuroendocrine tumors of the lung: results of a profiling study

“…2,5,[38][39][40] The let-7d expression was significantly associated with overall survival, suggesting that let-7d could have an important role in metastasis and tumor progression. The miRNAs miR-21 and miR-155, both reported to be overexpressed in neuroendocrine lung cancers, 1,3 did not show a significant association with overall survival in our cohort. Similar results were revealed for miR-210, a miRNA overexpressed in cancer tissue vs normal lung parenchyma.…”

“…Similar results were revealed for miR-210, a miRNA overexpressed in cancer tissue vs normal lung parenchyma. 1 Especially miR-21 turns out to be an interesting target, because it is a key regulator of the mTOR pathway and is reported to be differentially regulated in neuroendocrine tumors. 49 In addition, miR-96 expression co-induces the methylation pattern of normal cells and is upregulated in non-small cell lung cancer.…”

“…1,2 Pulmonary neuroendocrine tumors form a distinct group of neoplasms that share characteristic morphological, immunohistochmical, ultrastructural and molecular features. 3 These tumors considerably differ in their biological behaviors, thus, they are classified as either low-grade typical carcinoids, intermediate-grade atypical carcinoids, high-grade large cell neuroendocrine lung cancer, or small cell lung cancer.…”

Down-regulation of miRNA-30c predicts poor prognosis in Colorectal Cancer patients

“…Recently, it was reported that human miRNA-30c was down-regulated in non-small cell lung cancer (NSCLC) and breast cancer [18,19], this informed that miRNA-30c functioned as a tumor suppressor. Quintavalle et al reported that miRNA-30c could suppress apoptosis of lung cancer cells [20].…”

MicroRNA expression profiling studies on bronchopulmonary dysplasia: a systematic review and meta-analysis

“…The challenge is to effectively analyze and collect results of different miRNA expression profiling studies that used different profiling platforms and methods of evaluating differential expression levels, such as normalization or significance thresholds. To solve these difficulties, Chan et al (2008) and Guan et al (2012) proposed a vote-counting strategy to identify consistent markers when raw data are unavailable, which inspired the present meta-analysis of miRNA expression profiling studies in BPD.…”