In silico enhancer mining reveals SNS-032 and EHMT2 inhibitors as therapeutic candidates in high-grade serous ovarian cancer.

Autor: Quintela M; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK., James DW; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK., Garcia J; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK., Edwards K; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK., Margarit L; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK.; Cwm Taf Morgannwg University Health Board, Swansea, SA2 8QA, UK., Das N; Swansea Bay University Health Board, Swansea, SA12 7BR, UK., Lutchman-Singh K; Swansea Bay University Health Board, Swansea, SA12 7BR, UK., Beynon AL; Porvair Sciences Ltd., Wrexham, LL13 9XS, UK., Rioja I; Immunology Research Unit, GlaxoSmithKline, Medicines Research Centre, Stevenage, SG1 2NY, UK., Prinjha RK; Immunology Research Unit, GlaxoSmithKline, Medicines Research Centre, Stevenage, SG1 2NY, UK., Harker NR; Immunology Research Unit, GlaxoSmithKline, Medicines Research Centre, Stevenage, SG1 2NY, UK., Gonzalez D; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK., Steven Conlan R; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK., Francis LW; Swansea University Medical School, Swansea University, Swansea, SA2 8PP, UK. l.francis@swansea.ac.uk.
Jazyk: angličtina
Zdroj: British journal of cancer [Br J Cancer] 2023 Jul; Vol. 129 (1), pp. 163-174. Date of Electronic Publication: 2023 Apr 29.
DOI: 10.1038/s41416-023-02274-2
Abstrakt: Background: Epigenomic dysregulation has been linked to solid tumour malignancies, including ovarian cancers. Profiling of re-programmed enhancer locations associated with disease has the potential to improve stratification and thus therapeutic choices. Ovarian cancers are subdivided into histological subtypes that have significant molecular and clinical differences, with high-grade serous carcinoma representing the most common and aggressive subtype.
Methods: We interrogated the enhancer landscape(s) of normal ovary and subtype-specific ovarian cancer states using publicly available data. With an initial focus on H3K27ac histone mark, we developed a computational pipeline to predict drug compound activity based on epigenomic stratification. Lastly, we substantiated our predictions in vitro using patient-derived clinical samples and cell lines.
Results: Using our in silico approach, we highlighted recurrent and privative enhancer landscapes and identified the differential enrichment of a total of 164 transcription factors involved in 201 protein complexes across the subtypes. We pinpointed SNS-032 and EHMT2 inhibitors BIX-01294 and UNC0646 as therapeutic candidates in high-grade serous carcinoma, as well as probed the efficacy of specific inhibitors in vitro.
Conclusion: Here, we report the first attempt to exploit ovarian cancer epigenomic landscapes for drug discovery. This computational pipeline holds enormous potential for translating epigenomic profiling into therapeutic leads.
(© 2023. The Author(s).)
Databáze: MEDLINE
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