Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer

Abstract

Background: Long intergenic non-coding RNAs (lncRNAs) represent an emerging and under-studied class of transcripts that play a significant role in human cancers. Due to the tissue-and cancer-specific expression patterns observed for many lncRNAs it is believed that they could serve as ideal diagnostic biomarkers. However, until each tumor type is examined more closely, many of these lncRNAs will remain elusive. Results: Here we characterize the lncRNA landscape in lung cancer using publicly available transcriptome sequencing data from a cohort of 567 adenocarcinoma and squamous cell carcinoma tumors. Through this compendium we identify over 3,000 unannotated intergenic transcripts representing novel lncRNAs. Through comparison of both adenocarcinoma and squamous cell carcinomas with matched controls we discover 111 differentially expressed lncRNAs, which we term lung cancer-associated lncRNAs (LCALs). A pan-cancer analysis of 324 additional tumor and adjacent normal pairs enable us to identify a subset of lncRNAs that display enriched expression specific to lung cancer as well as a subset that appear to be broadly deregulated across human cancers. Integration of exome sequencing data reveals that expression levels of many LCALs have significant associations with the mutational status of key oncogenes in lung cancer. Functional validation, using both knockdown and overexpression, shows that the most differentially expressed lncRNA, LCAL1, plays a role in cellular proliferation.

Pan-cancer transcriptome analysis reveals long noncoding RNAs with conserved function

“…Our computational analysis confirmed previous reports that CCAT1 is altered in CRC, 31 LUAD, 34 and LUSC 34 ( Fig. 6A).…”

“…Onco-lncRNA-21, also known as FENDRR, has been implicated in a lethal lung development disorder 35 and lung cancer. 34 As shown in Figure 3C, in addition to LUAD and LUSC, oncolncRNA-21 expression levels are also significantly downregulated in BLCA and CRC. Taken together, we have reconfirmed altered expression of lncRNAs previously implicated in cancer interspersed among many uncharacterized lncRNAs that are recurrently altered across multiple cancer types.…”

“…Figure 3B shows the expression levels of onco-lncRNA-1, which is up-regulated in 5 of the 8 cancers (BLCA, BRCA, LUAD, LUSC, and UCEC) but has only previously been implicated in lung cancer. 34 Despite not being significant in the remaining 3 cohorts, it appears that the tumor samples in these cancer types also show a trend of higher tumor expression relative to the normal samples. Additionally, even though our differential expression analysis only included tumors with matched normal tissue, the unpaired tumor samples appear to have expression levels similar to the paired tumor samples.…”

“…48 Therefore, as a first determination of the potential for CCAT1 to alter cell cycle in lung cancer, and thus demonstrating that the function of CCAT1 is conserved across multiple cancer types, we performed cell growth experiments in 2 lung cancer cell lines previously shown to have high expression of CCAT1. 34 Greater than 50% knockdown of CCAT1 in NCI-H322M and NCI-H522 cells using 2 different small interfering RNAs (siRNAs) resulted in decreased cell growth of »20% and »40%, respectively, as measured by cell counting for 6 d (Fig. 6C-D).…”

141 Small RNA deep sequencing discriminates subsets of extracellular vesicles released by melanoma cells - evidence of unique microRNA cargos

“…In this study we identified 1041 miRNAs altogether in the extracellular vesicle and cell samples studied, which are more than most array systems would detect. [22][23][24][25][26][27]42,43 Further, comparison among expression of miRNAs is possible with deep sequencing approaches, if the absolute number of copies in the sample can be quantified. 44 In this study, by using the Quantile normalization method for all samples, miRNA expression showed positive relationship between the samples, although many detected miRNA are unique in the different subsets of vesicles ( Fig.…”