Evidence map›Paper›PMID 40909508›Full record

ArticlebioRxiv : the preprint server for biology2025

Multi-modal characterization of transcriptional programs that drive metastatic cascades to solid sites and ascites in ovarian cancer.

Kaiyang Zhang, Essi Kahelin, Giovanni Marchi, Oskari Lehtonen, Shams Salloum, Kari Lavikka, Yilin Li, Felix Dietlein, Alexandra Lahtinen, Jaana Oikkonen and 5 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Kaiyang ZhangResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Essi KahelinResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Giovanni MarchiResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Oskari LehtonenResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Shams SalloumResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Kari LavikkaResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-4163-4945
Yilin LiResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Felix DietleinComputational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Alexandra LahtinenResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Jaana OikkonenResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Sakari HietanenDepartment of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland.
Johanna HynninenDepartment of Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland.
Antti HäkkinenComputational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
Anni VirtanenResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Sampsa HautaniemiResearch Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland.ORCID 0000-0002-7749-2694

Funding

Defining the universal genomic language of hallmarks in tumor developmentDP2CA290196 · NCI · BOSTON CHILDREN'S HOSPITAL · PI Felix Dietlein · 2023 to 2026
$2.7M
A pan-cancer atlas of driver mutations in >100,000 patients based on a hypothesis-driven combined computational and experimental approachR00CA262152 · NCI · BOSTON CHILDREN'S HOSPITAL · PI DIETLEIN, FELIX · 2022 to 2024
$712k
NCI NIH HHS DP2 CA290196NCI NIH HHS R00 CA262152
6 · The paper itself

Abstract

Ovarian high-grade serous carcinoma (HGSC) is characterized by extensive intra-peritoneal dissemination and tumor heterogeneity. In the metastatic cascade, tumors utilize several transcriptional programs to translocate and survive in distant tissues. Here, we analyzed multi-modal, real-world data from 350 tumor samples across 160 patients with HGSC to identify transcriptional programs that drive intra-peritoneal metastasis and heterogeneity. We identified nine transcriptional programs, including those regulating epithelial-mesenchymal transition and immune modulation and cytoskeletal reorganization, which shape distinct metastatic trajectories to solid and ascitic environments and are associated to treatment response. Our results reveal pronounced intra-patient transcriptional heterogeneity, which in some cases surpassed inter-patient heterogeneity, highlighting the importance of multi-site sampling for accurate prognostication and combinatorial treatments in HGSC. Our extensive characterization offers novel insights into intra-peritoneal metastasis with significant prognostic implications, reveals histomorphological biomarkers for patient stratification and paves the way for innovative therapeutic strategies aimed at impairing cancer cell adaptability and limiting metastasis.

Indexed as

EMTmetastasisOvarian cancerpatient-centered researchtranscriptional programs

Identifiers

PMID40909508
PMCPMC12407970

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.