Dataset Information

Integrated analysis of dysregulated lncRNA expression in breast cancer cell identified by RNA-seq study.

ABSTRACT: Among all the sequencing techniques, RNA sequencing (RNA-seq) has galloped with pace adopting the profiling of transcriptomic data in almost every biological analytics area like gene regulation study, development biology and clinical research. Recently the discovery of differentially expressed genes across different conditions has outshone the barrier of genetic & epigenetic regulations. The present work identified and analyzed differentially expressed novel long non-coding RNAs (lncRNAs) for breast cancer. A complex computational pipeline was adopted for the study which includes analysis of 18498 differentially expressed genes with 4114 up-regulated and 3475 down-regulated transcripts. The overexpression of lnc-MTAP (CDKN2B-AS1), lnc-PCP4 (DSCAM-S1), and lnc-FAM (H19) in breast cells suggests that these lncRNAs may have significant role to play in breast cancer. These results validated the relevance of the dysregulation pattern in cancer cells due to the presence of lncRNAs. The study further opens a new scope for experimental analysis to confirm the aberrant expression pattern of these lncRNAs which may act as potential bio-markers for the diagnosis and early detection of breast cancer.

SUBMITTER: Tripathi R

PROVIDER: S-EPMC6096410 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Integrated analysis of dysregulated lncRNA expression in breast cancer cell identified by RNA-seq study.

Tripathi Rashmi R Soni Apoorva A Varadwaj Pritish Kumar PK

Non-coding RNA research 20160921 1

Among all the sequencing techniques, RNA sequencing (RNA-seq) has galloped with pace adopting the profiling of transcriptomic data in almost every biological analytics area like gene regulation study, development biology and clinical research. Recently the discovery of differentially expressed genes across different conditions has outshone the barrier of genetic & epigenetic regulations. The present work identified and analyzed differentially expressed novel long non-coding RNAs (lncRNAs) for br ...[more]

PMID: 30159409

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Project description:Breast cancer is the most commonly diagnosed cancer in the world, with triple-negative breast cancer (TNBC) making up 12% of these diagnoses. TNBC tumours are highly heterogeneous in both inter-tumour and intra-tumour gene expression profiles, where they form subclonal populations of varying levels of aggressiveness. These aspects make it difficult to study and treat TNBC, requiring further research into tumour heterogeneity as well as potential therapeutic targets and biomarkers. Recently, it was discovered that the majority of the transcribed genome comprises non-coding RNAs, in particular long non-coding RNAs (lncRNAs). LncRNAs are transcripts of >200 nucleotides in length that do not encode a protein. They have been characterised as regulatory molecules and their expression can be associated with a malignant phenotype. We set out to explore TNBC tumour heterogeneity in vivo at a single cell level to investigate whether lncRNA expression varies across different cells within the tumour, even if cells are coming from the same cell line, and whether lncRNA expression is sufficient to define cellular subpopulations. We applied single-cell expression profiling due to its ability to capture expression signals of lncRNAs expressed in small subpopulations of cells. Overall, we observed most lncRNAs to be expressed at low, but detectable levels in TNBC xenografts, with a median of 25 lncRNAs detected per cell. LncRNA expression alone was insufficient to define a subpopulation of cells, and lncRNAs showed highly heterogeneous expression patterns, including ubiquitous expression, subpopulation-specific expression, and a hybrid pattern of lncRNAs expressed in several, but not all subpopulations. These findings reinforce that transcriptionally defined tumour cell subpopulations can be identified in cell-line derived xenografts, and uses single-cell RNA-seq (scRNA-seq) to detect and characterise lncRNA expression across these subpopulations in xenografted tumours. Future studies will aim to investigate the spatial distribution of lncRNAs within xenografts and patient tissues, and study the potential of subclone-specific lncRNAs as new therapeutic targets and/or biomarkers.

Dataset Information

Integrated analysis of dysregulated lncRNA expression in breast cancer cell identified by RNA-seq study.

Publications

Integrated analysis of dysregulated lncRNA expression in breast cancer cell identified by RNA-seq study.

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