Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death. Developing minimally invasive techniques that can diagnose NSCLC, particularly at an early stage, may improve its outcome. Using microarray platforms, we previously identified 12 microRNAs (miRNAs) the aberrant expressions of which in primary lung tumors are associated with early-stage NSCLC. Here, we extend our previous research by investigating whether the miRNAs could be used as potential plasma biomarkers for NSCLC. We initially validated expressions of the miRNAs in paired lung tumor tissues and plasma specimens from 28 stage I NSCLC patients by real-time quantitative reverse transcription PCR, and then evaluated diagnostic value of the plasma miRNAs in a cohort of 58 NSCLC patients and 29 healthy individuals. The altered miRNA expressions were reproducibly confirmed in the tumor tissues. The miRNAs were stably present and reliably measurable in plasma. Of the 12 miRNAs, five displayed significant concordance of the expression levels in plasma and the corresponding tumor tissues (all r>0.850, all P<0.05). A logistic regression model with the best prediction was defined on the basis of the four genes (miRNA-21, -126, -210, and 486-5p), yielding 86.22% sensitivity and 96.55% specificity in distinguishing NSCLC patients from the healthy controls. Furthermore, the panel of miRNAs produced 73.33% sensitivity and 96.55% specificity in identifying stage I NSCLC patients. In addition, the genes have higher sensitivity (91.67%) in diagnosis of lung adenocarcinomas compared with squamous cell carcinomas (82.35%) (P<0.05). Altered expressions of the miRNAs in plasma would provide potential blood-based biomarkers for NSCLC.

Non-small cell lung cancer (NSCLC) is the leading cause of cancer death, reflecting the need for better understanding the oncogenesis, and developing new diagnostic and therapeutic targets for the malignancy. Emerging evidence suggests that small nucleolar RNAs (snoRNAs) have malfunctioning roles in tumorigenesis. Our recent study demonstrated that small nucleolar RNA 42 (SNORA42) was overexpressed in lung tumors. Here, we investigate the role of SNORA42 in tumorigenesis of NSCLC. We simultaneously assess genomic dosages and expression levels of SNORA42 and its host gene, KIAA0907, in 10 NSCLC cell lines and a human bronchial epithelial cell line. We then determine in vitro functional significance of SNORA42 in lung cancer cell lines through gain- and loss-of-function analyses. We also inoculate cancer cells with SNORA42-siRNA into mice through either tail vein or subcutaneous injection. We finally evaluate expression level of SNORA42 on frozen surgically resected lung tumor tissues of 64 patients with stage I NSCLC by using quantitative reverse transcriptase PCR assay. Genomic amplification and associated high expression of SNORA42 rather than KIAA0907 are frequently observed in lung cancer cells, suggesting that SNORA42 overexpression is activated by its genomic amplification. SNORA42 knockdown in NSCLC cells inhibits in vitro and in vivo tumorigenicity, whereas enforced SNORA42 expression in bronchial epitheliums increases cell growth and colony formation. Such pleiotropy of SNORA42 suppression could be achieved at least partially through increased apoptosis of NSCLC cells in a p53-dependent manner. SNORA42 expression in lung tumor tissue specimens is inversely correlated with survival of NSCLC patients. Therefore, SNORA42 activation could have an oncogenic role in lung tumorigenesis and provide potential diagnostic and therapeutic targets for the malignancy.

BackgroundNon-small-cell lung cancer (NSCLC) is the leading cause of cancer death. Early detection of NSCLC will improve its outcome. The current techniques for NSCLC early detection are either invasive or have low accuracy. Molecular analyses of clinical specimens present promising diagnostic approaches. Non-coding RNAs (ncRNAs) play an important role in tumorigenesis and could be developed as biomarkers for cancer. Here we aimed to develop small nucleolar RNAs (snoRNAs), a common class of ncRNAs, as biomarkers for NSCLC early detection. The study comprised three phases: (1) profiling snoRNA signatures in 22 NSCLC tissues and matched noncancerous lung tissues by GeneChip Array, (2) validating expressions of the signatures by RT-qPCR in the tissues, and (3) evaluating plasma expressions of the snoRNAs in 37 NSCLC patients, 26 patients with chronic obstructive pulmonary disease (COPD), and 22 healthy subjects.ResultsIn the surgical tissues, six snoRNAs were identified, which were overexpressed in all tumour tissues compared with their normal counterparts. The overexpressions of the genes in tumors were confirmed by RT-qPCR. The snoRNAs were stably present and reliably detectable in plasma. Of the six genes, three (SNORD33, SNORD66 and SNORD76) displayed higher plasma expressions in NSCLC patients compared with the cancer-free individuals (All < 0.01). The use of the three genes produced 81.1% sensitivity and 95.8% specificity in distinguishing NSCLC patients from both normal and COPD subjects. The plasma snoRNA expressions were not associated with stages and histological types of NSCLC (All > 0.05).ConclusionsThe identified snoRNAs provide potential markers for NSCLC early detection.

BackgroundMaking a definitive preoperative diagnosis of solitary pulmonary nodules (SPNs) found by CT has been a clinical challenge. We previously demonstrated that microRNAs (miRNAs) could be used as biomarkers for lung cancer diagnosis. Here we investigate whether plasma microRNAs are useful in identifying lung cancer among individuals with CT-detected SPNs.MethodsBy using quantitative reverse transcriptase PCR analysis, we first determine plasma expressions of five miRNAs in a training set of 32 patients with malignant SPNs, 33 subjects with benign SPNs, and 29 healthy smokers to define a panel of miRNAs that has high diagnostic efficiency for lung cancer. We then validate the miRNA panel in a testing set of 76 patients with malignant SPNs and 80 patients with benign SPNs.ResultsIn the training set, miR-21 and miR-210 display higher plasma expression levels, whereas miR-486-5p has lower expression level in patients with malignant SPNs, as compared to subjects with benign SPNs and healthy controls (all P ≤ 0.001). A logistic regression model with the best prediction was built on the basis of miR-21, miR-210, and miR-486-5p. The three miRNAs used in combination produced the area under receiver operating characteristic curve at 0.86 in distinguishing lung tumors from benign SPNs with 75.00% sensitivity and 84.95% specificity. Validation of the miRNA panel in the testing set confirms their diagnostic value that yields significant improvement over any single one.ConclusionsThe plasma miRNAs provide potential circulating biomarkers for noninvasively diagnosing lung cancer among individuals with SPNs, and could be further evaluated in clinical trials.