Long non-coding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. In order to delineate genome-wide lncRNA expression, we curated 7,256 RNA-Seq libraries from tumors, normal tissues, and cell lines comprising over 43 terabases of sequence from 25 independent studies. We applied ab initio assembly methodology to this dataset, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% (48,952) were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements and 7% (3,900) overlapped disease-associated single nucleotide polymorphisms (SNPs). To prioritize lineage-specific, disease-associated lncRNA expression we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light into normal biology and cancer pathogenesis, and be valuable for future biomarker development.
We and others previously identified NKX2-1, also known as TITF1 and TTF-1, as a lineage-survival oncogene in lung adenocarcinomas. Here we show that NKX2-1 induces the expression of the receptor tyrosine kinase-like orphan receptor 1 (ROR1), which in turn sustains a favorable balance between prosurvival PI3K-AKT and pro-apoptotic p38 signaling, in part through ROR1 kinase-dependent c-Src activation, as well as kinase activity-independent sustainment of the EGFR-ERBB3 association, ERBB3 phosphorylation, and consequential PI3K activation. Notably, ROR1 knockdown effectively inhibited lung adenocarcinoma cell lines, irrespective of their EGFR status, including those with resistance to the EGFR tyrosine kinase inhibitor gefitinib. Our findings thus identify ROR1 as an "Achilles' heel" in lung adenocarcinoma, warranting future development of therapeutic strategies for this devastating cancer.
Molecular classification of cancers into subtypes has resulted in an advance in our understanding of tumour biology and treatment response across multiple tumour types. However, to date, cancer profiling has largely focused on protein-coding genes, which comprise <1% of the genome. Here we leverage a compendium of 58,648 long noncoding RNAs (lncRNAs) to subtype 947 breast cancer samples. We show that lncRNA-based profiling categorizes breast tumours by their known molecular subtypes in breast cancer. We identify a cohort of breast cancer-associated and oestrogen-regulated lncRNAs, and investigate the role of the top prioritized oestrogen receptor (ER)-regulated lncRNA, DSCAM-AS1. We demonstrate that DSCAM-AS1 mediates tumour progression and tamoxifen resistance and identify hnRNPL as an interacting protein involved in the mechanism of DSCAM-AS1 action. By highlighting the role of DSCAM-AS1 in breast cancer biology and treatment resistance, this study provides insight into the potential clinical implications of lncRNAs in breast cancer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.