Transcriptomics

Dataset Information

0

The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancer


ABSTRACT: The high-grade serous ovarian cancer (HG-SOC) tumor microenvironment (TME) is constellated by cellular elements and a network of soluble constituents that contribute to tumor progression. In the multitude of the secreted molecules, the endothelin-1 (ET-1) has emerged to be implicated in the tumor/TME interplay, however the molecular mechanisms induced by the ET-1-driven feed-forward loops (FFL) and associated with the HG-SOC metastatic potential need to be further investigated. The tracking of the patient-derived (PD) HG-SOC cell transcriptome by RNA-seq identified the vascular endothelial growth factor (VEGF) gene and its associated signature among those mostly upregulated by ET-1 and down-modulated by the dual ET-1R antagonist macitentan. Within the ligand-receptor pairs concurrently expressed in PD-HG-SOC cells, endothelial cells and activated fibroblasts, we discovered two intertwined FFL, the ET-1/ET-1R and VEGF/VEGF receptors, concurrently activated by ET-1 and shutting-down by macitentan, or by the anti-VEGF antibody bevacizumab. In parallel, we observed that ET-1 fine-tuned the tumoral and stromal secretome towards a pro-invasive pattern. Into the fray of the HG-SOC/TME double and triple co-cultures, the secretion of ET-1 and VEGF, that share a common co-regulation, was inhibited upon the administration of macitentan. Functionally, macitentan, mimicking the effect of bevacizumab, interfered with the HG-SOC/TME FFL-driven communication that fuel the HG-SOC invasive behaviour. The identification of ET-1 and VEGF FFL as tumor and TME actionable vulnerabilities, reveal how ET-1R blockade, targeting the HG-SOC cells and the TME simultaneously, may represent an effective therapeutic option for HG-SOC patients.

ORGANISM(S): Homo sapiens

PROVIDER: GSE268498 | GEO | 2024/07/17

REPOSITORIES: GEO

Dataset's files

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

Similar Datasets

2023-01-11 | GSE196065 | GEO
2013-12-01 | E-GEOD-48880 | biostudies-arrayexpress
2010-05-31 | E-GEOD-20521 | biostudies-arrayexpress
2009-11-16 | E-GEOD-18195 | biostudies-arrayexpress
2020-05-04 | GSE147882 | GEO
2019-12-16 | E-MTAB-7683 | biostudies-arrayexpress
2013-12-01 | GSE48880 | GEO
2017-01-31 | GSE76689 | GEO
2015-12-03 | GSE59476 | GEO
2009-09-22 | GSE18195 | GEO