Transcriptomics

Dataset Information

0

RNA-seq of the primary patient-derived GBM cell line G797 following siRNA-mediated knockdown and pcDNA3.1-Neomycin-mediated overexpression of the lncRNA HOXA10-AS


ABSTRACT: We used a machine-learning framework to systematically discover prognostic long non-coding RNAs (lncRNAs) in 9,446 patient tumors of 30 types. We identified 166 prognostic lncRNAs whose transcript abundance correlated with patient risk and improved the performance of common clinical variables and molecular tumor subtypes. In lower-grade gliomas, discrete activation of HOXA10-AS indicated poor patient prognosis, neurodevelopmental pathway activation and a transcriptomic similarity to glioblastomas. To understand the role of HOXA10-AS in the hallmark pathways of glioma, we used RNA-seq to profile the patient-derived G797 glioma cells with siRNA-mediated HOXA10-AS knockdown (KD) and pcDNA3.1-Neomycin-mediated overexpression (OE) phenotypes. Both KD and OE were validated using RT-PCR. We found a pronounced transcriptional response to HOXA10-AS deregulation with 1,715 and 408 differentially expressed protein-coding genes detected in KD and OE cells, respectively (FDR < 0.05, absolute FC > 1.2), including 23 genes detected in both experiments, as well as known genes involved in glioma biology and Hippo signaling. Our study underscores the pan-cancer potential of the non-coding transcriptome for developing molecular biomarkers and innovative therapeutic strategies.

INSTRUMENT(S): Illumina NovaSeq 6000, NextSeq 500

ORGANISM(S): Homo sapiens  

DISEASE(S): Brain Glioblastoma

SUBMITTER: Christian Lee   Jüri Reimand  

PROVIDER: E-MTAB-10944 | ArrayExpress | 2021-10-02

SECONDARY ACCESSION(S): ERP131886

REPOSITORIES: ArrayExpress, ENA

Dataset's files

Source:
Action DRS
E-MTAB-10944.idf.txt Idf
E-MTAB-10944.processed.1.zip Processed
E-MTAB-10944.sdrf.txt Txt
Items per page:
1 - 3 of 3
altmetric image

Publications


Long non-coding RNAs (lncRNAs) are increasingly recognized as functional units in cancer and powerful biomarkers; however, most remain uncharacterized. Here, we analyze 5,592 prognostic lncRNAs in 9,446 cancers of 30 types using machine learning. We identify 166 lncRNAs whose expression correlates with survival and improves the accuracy of common clinical variables, molecular features, and cancer subtypes. Prognostic lncRNAs are often characterized by switch-like expression patterns. In low-grad  ...[more]

Similar Datasets

2018-01-01 | S-EPMC6151881 | BioStudies
2019-01-01 | S-EPMC6929382 | BioStudies
2020-01-01 | S-EPMC7077533 | BioStudies
2020-01-01 | S-EPMC7270031 | BioStudies
2020-01-01 | GSE123694 | GEO
2020-01-01 | S-EPMC6920228 | BioStudies
2020-01-01 | S-EPMC7436175 | BioStudies
2020-01-01 | S-EPMC7310421 | BioStudies
2018-01-01 | S-EPMC5835862 | BioStudies
2020-01-01 | S-EPMC7443412 | BioStudies