Long Noncoding RNA Expression Profiles of Lung Adenocarcinoma Ascertained by Microarray Analysis

<div><p>Background</p><p>Long noncoding RNAs (lncRNAs) have been shown to be involved in the development and progression of lung cancer. However, the roles of lncRNAs in lung cancer are not well understood.</p><p>Methodology/Principal Findings</p><p>We used a high-throughput microarray to compare the lncRNA and messenger RNA (mRNA) expression profiles in lung adenocarcinoma and normal tissue (NT) samples. Several candidate adenocarcinoma-associated lncRNAs were verified by real-time quantitative reverse transcription polymerase chain reaction (PCR) analysis. Using abundant and varied probes, we were able to assess 30,586 lncRNAs and 26,109 mRNAs in our microarray. We found that 2,420 lncRNAs and 1,109 mRNAs were differentially expressed (≥2-fold change) in lung adenocarcinoma samples and NT, indicating that many lncRNAs were significantly upregulated or downregulated in lung adenocarcinoma. We also found, via quantitative PCR, that 19 lncRNAs were aberrantly expressed in lung adenocarcinoma compared with matched histologically normal lung tissues. Among these, LOC100132354 and RPLP0P2 were the most aberrantly expressed lncRNAs, as estimated by quantitative PCR in 100 pairs of lung adenocarcinoma and NT samples.</p><p>Conclusions/Significance</p><p>Our study ascertained the expression patterns of lncRNAs in lung adenocarcinoma by microarray. The results revealed that many lncRNAs were differentially expressed in lung adenocarcinoma tissues and NT, suggesting that they may play a key role in tumor development.</p></div

The expression level of RPLPOP2 and LOC100132354 between one hundred lung adenocarcinoma sample and the normal lung sample.

<p>LOC100132354 expression of lung adenocarcinoma was significantly higher than the adjacent tissues (Mann-Whitney U = 126.00, P = 0.01), while RPLP0P2 expression of lung adenocarcinoma was significantly lower than the adjacent tissues (Mann-Whitney U = 178.78, P = 0.002).</p

Box plots and Scatter plots showing the variation in lncRNA and mRNA expression between the lung adenocarcinoma and normal lung tissue arrays.

<p>(A–B) Box plots showing the distribution of the lncRNA (A) and mRNA (B) profiles. After normalization, the distributions of the log2-ratios among the tested samples were nearly the same. (C–D) Scatter plots showing the variation in lncRNA (C) and mRNA (D) expression between the lung adenocarcinoma and normal lung tissue arrays. The values of the X and Y axes in the scatter plot are averaged normalized values in each group (log2-scaled). The lncRNAs above the top green line and below the bottom green line are those with a >3-fold change in expression between tissues.</p

Pathway analysis of downregulated mRNAs in lung adenocarcinoma.

<p>Twenty-four downregulated pathways were identified, including propionate metabolism and fatty acid metabolism pathways.</p

Heat map and hierarchical clustering of lncRNA and mRNA profile comparison between the lung adenocarcinoma and normal lung samples.

<p>(A) lncRNA (B) mRNA.</p

Comparison between gene chip data and qPCR result.

<p>RP11-1C1.7, RP4-575N6.5, RP11-473M20.11, XLOC_003286, CTA-363E6.2, RP5-826L7.1, ZNF295-AS1, RPLP0P2, AC079776.2, RP13-514E23.1, LOC100499405, RP1-90D4.3, XLOC_012255, RP11-445K13.2, LOC100132354, AC004166.7, XLOC_003405, RP11-893F2.6, RP11-909N17.3 determined to be differentially expressed in lung adenocarcinoma samples compared with NT samples in six patients by microarray were validated by qPCR. The heights of the columns in the chart represent the log-transformed median fold changes (T/N) in expression across the six patients for each of the four lncRNAs validated; the bars represent standard errors. The validation results of the 19 lncRNAs indicated that the microarray data correlated well with the qPCR results.</p

Pathway analysis of upregulated mRNAs in lung adenocarcinoma.

<p>Seven upregulated pathways were identified, including ethanol metabolism, viral carcinogenesis, RNA transduction, and cell cycle pathways.</p