Transcriptomics

Dataset Information

0

Phenotypic consequences of SLC25A40-ABCB1 fusions beyond drug resistance in High Grade Serous Ovarian Cancer


ABSTRACT: Purpose: Our laboratory recently identified the most common mechanism of acquired drug resistance in High Grade Serous Ovarian Cancer (HGSOC) to date, SLC25A40-ABCB1 fusions. The primary aim of this study was to examine the transcriptional profile of drug resistant fusion-positive SLC25A40-ABCB1 fusion positive cells. Single cell fusion-positive and negative clones were derived from the human HGSOC cell line AOCS-18.5 Methods: Three independent replicates of RNA was collected from five SLC25A40-ABCB1 fusion-negative AOCS 18.5 clones (B,C, D,E,F) and five SLC25A40-ABCB1 fusion-positive AOCS 18.5 clones (8,9,13, 15B, 18B) and submitted for NextSeq 100bp paired-end, polyA RNA-sequencing. Cells were collected 48-72hrs post seeding. 20 million paired end reads per sample were generated. Reads were mapped to the human reference GRCh37.92 using the STAR two pass method (v2.6.0b). Counts were generated on the ensemble release GRCh37.92 GTF annotation using HTSeq (v0.10.0). Counts were normalized to logged TMM values using edgeR (v3.28.1). TPM expression values were also generated. Differential gene expression analysis was performed using DESeq2 (v1.26.0) on the raw counts. In all, 3333 genes were significantly upregulated (>1.5 log2 fold change, p-adj<0.1) in fusion-positive lines, with 1751 genes significantly downregulated Conclusions: Using a stringent cut-off of >2.0 fold change (n=2238 differentially expressed genes), Metascape pathway analysis revealed that the most significantly enriched pathways in fusion-positive clones included the NABA matrisome associated pathway (160/751 genes, 7.24%), followed by external encapsulating structure organization (102/398 genes, 4.62%) and regulation of cell adhesion (139/734 genes, 6.29%).

ORGANISM(S): Homo sapiens

PROVIDER: GSE183210 | GEO | 2021/09/03

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2010-09-01 | E-GEOD-21425 | biostudies-arrayexpress
2010-09-01 | GSE21425 | GEO
| PRJNA126379 | ENA
2020-07-04 | GSE133859 | GEO
2013-04-06 | GSE45268 | GEO
2020-05-02 | GSE149723 | GEO
2020-05-01 | E-MTAB-6713 | biostudies-arrayexpress
2014-03-11 | E-GEOD-55716 | biostudies-arrayexpress
2014-02-02 | GSE52536 | GEO
2013-10-01 | GSE49605 | GEO