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Abstract

Bulk transcriptomic analyses of high-grade serous ovarian cancer (HGSOC) so far have not uncovered potential drug targets, possibly because subtle, disease-relevant transcriptional patterns are overshadowed by dominant, non-relevant ones. Our aim was to uncover disease-outcome-related patterns in HGSOC transcriptomes that may reveal novel drug targets. Using consensus-independent component analysis, we dissected 678 HGSOC transcriptomes of systemic therapy naïve patients—sourced from public repositories—into statistically independent transcriptional components (TCs). To enhance c-ICA’s robustness, we added 447 transcriptomes from non-serous histotypes, low-grade serous, and non-cancerous ovarian tissues. Cox regression and survival tree analysis were performed to determine the association between TC activity and overall survival (OS). Finally, we determined the activity of the OS-associated TCs in 11 publicly available spatially resolved ovarian cancer transcriptomes. We identified 374 TCs, capturing prominent and subtle transcriptional patterns linked to specific biological processes. Six TCs, age, and tumor stage stratified patients with HGSOC receiving platinum-based chemotherapy into ten distinct OS groups. Three TCs were linked to copy-number alterations affecting expression levels of genes involved in replication, apoptosis, proliferation, immune activity, and replication stress. Notably, the TC identifying patients with the shortest OS captured a novel transcriptional pattern linked to synaptic signaling, which was active in tumor regions within all spatially resolved transcriptomes. The association between a synaptic signaling-related TC and OS supports the emerging role of neurons and their axons as cancer hallmark-inducing constituents of the tumor microenvironment. These constituents might offer a novel drug target for patients with HGSOC.

Details

1009240
Title
Transcriptional pattern enriched for synaptic signaling is associated with shorter survival of patients with high-grade serous ovarian cancer
Author
Bhattacharya Arkajyoti 1   VIAFID ORCID Logo  ; Stutvoet, Thijs S 1 ; Perla Mirela 1 ; Loipfinger Stefan 1   VIAFID ORCID Logo  ; Jalving Mathilde 1 ; Reyners Anna KL 1 ; Vermeer, Paola D 2   VIAFID ORCID Logo  ; Drapkin Ronny 3 ; de Bruyn Marco 4   VIAFID ORCID Logo  ; de Vries Elisabeth GE 1 ; de, Jong Steven 1 ; Fehrmann, Rudolf SN 1   VIAFID ORCID Logo 

 https://ror.org/012p63287 Department of Medical Oncology, University Medical Center Groningen, University of Groningen Groningen Netherlands 
 https://ror.org/00sfn8y78 Cancer Biology and Immunotherapies Group, Sanford Research Sioux Falls United States 
 https://ror.org/00b30xv10 Penn Ovarian Cancer Research Center and Basser Center for BRCA, University of Pennsylvania, Perelman School of Medicine Philadelphia United States 
 https://ror.org/012p63287 Department of Obstetrics and Gynecology, University Medical Center Groningen, University of Groningen Groningen Netherlands 
Publication title
eLife; Cambridge
Volume
13
Publication year
2025
Publication date
2025
Publisher
eLife Sciences Publications Ltd.
Place of publication
Cambridge
Country of publication
United Kingdom
University/institution
U.S. National Institutes of Health/National Library of Medicine
Publication subject
e-ISSN
2050084X
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-05-13
Publication history
 
 
   First posting date
13 May 2025
ProQuest document ID
3204558717
Document URL
https://www.proquest.com/scholarly-journals/transcriptional-pattern-enriched-synaptic/docview/3204558717/se-2?accountid=208611
Copyright
© 2024, Bhattacharya, Stutvoet, Perla et al This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-05-16
Database
ProQuest One Academic