Long non-coding RNAs (lncRNAs) have emerged as key players in a remarkably variety of biological processes and pathologic conditions, including cancer. Next-generation sequencing technologies and bioinformatics procedures predict the existence of tens of thousands of lncRNAs, from which we know the functions of only a handful of them, and very little is known in cancer types such as head and neck squamous cell carcinomas (HNSCCs).
Here, researchers from CIEMAT use RNA-seq expression data from The Cancer Genome Atlas (TCGA) and various statistic and software tools in order to get insight about the lncRNome in HNSCC. Based on lncRNAs expression across 426 samples, they discovered five distinct tumor clusters that they compared with reported clusters based on various genomic/genetic features. The results demonstrated significant associations between lncRNA-based clustering and DNA-methylation, TP53 mutation, and human papillomavirus infection. Using “guilt by association” procedures, the researchers infered the possible biological functions of representative lncRNAs of each cluster. Furthermore, they found that lncRNA clustering is correlated with some important clinical and pathologic features, including patient survival after treatment, tumor grade or sub-anatomical location.
lncRNA clusters and other molecular aberrations
A) LncRNA-based clustering of HNSCC samples is significantly associated with clustering based in diverse molecular features, mainly DNA methylation and expression of PCGs (mRNA). Significance values are plot upon Chi-square test computation. Dashed red line: threshold of significance (p-val<0.05). B) and C) Association with HPV infection and HNSCC mutations with lncRNA clusters. Chi-square or odds ratio values are plot upon Chi-square test (B) or Fisher’s exact test (C) computation, respectively. D) Distribution of lncRNA clusters and HPV infected samples, or samples with mutations in KMT2D or NSD1. Note the enrichment of HPV infection in c5, the NSD1 mutations in c1 and the KMT2D mutations in c2 (red lines), and the depletion of KMT2D mutations in c4 (blue line). P-values are calculated with Fisher’s exact test. Vertical black lines in panel D showed HPV+ samples and mutated samples for the selected genes KMT2D and NSD1, respectively.
The researchers present a landscape of lncRNAs in HNSCC, and provide associations with important genotypic and phenotypic features that may help to understand the disease.