Evidence map›Paper›PMID 42007974›Full record

ArticleCancer research communications2026

Integrated Single-Cell Whole-Genome Sequencing and Spatial Transcriptomics Reveal Intratumoral Heterogeneity in Ovarian Cancer.

Rania Bassiouni, Yuxin Jin, Lee D Gibbs, Jing Qian, Solomon O Rotimi, Heather Miller, Michelle G Webb, Seeta Rajpara, Javier Arias-Stella, David W Craig and 2 more

Abstract read
In one paragraph

Article in Cancer research communications, 2026. 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

5 · Who and what money

Authors and funding

12 authors.

Rania BassiouniDepartment of Integrative Translational Sciences, Beckman Research Institute, City of Hope, Duarte, California.ORCID 0000-0002-4754-9311
Yuxin JinDepartment of Integrative Translational Sciences, Beckman Research Institute, City of Hope, Duarte, California.ORCID 0000-0002-6124-9681
Lee D GibbsDepartment of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, California.ORCID 0000-0003-0713-109X
Jing QianDepartment of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, California.ORCID 0009-0008-7026-9386
Solomon O RotimiDepartment of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, California.ORCID 0000-0002-3678-9977
Heather MillerDepartment of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, California.ORCID 0000-0003-1330-7450
Michelle G WebbDepartment of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, California.ORCID 0000-0002-7613-5759
Seeta RajparaDepartment of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, California.ORCID 0000-0003-2241-8910
Javier Arias-StellaDepartment of Pathology, City of Hope Comprehensive Cancer Center, Duarte, California.ORCID 0000-0002-5155-4893
David W CraigDepartment of Integrative Translational Sciences, Beckman Research Institute, City of Hope, Duarte, California.ORCID 0000-0003-2040-1955
Lynda RomanDepartment of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, California.ORCID 0000-0002-6960-4414
John D CarptenDepartment of Integrative Translational Sciences, Beckman Research Institute, City of Hope, Duarte, California.ORCID 0000-0002-6862-2821

Funding

Beckman Research Institute, City of Hope (BRI)Keck School of Medicine of USC (Keck Medicine of USC)
6 · The paper itself

Abstract

The mortality rate of ovarian cancer remains disproportionately high compared with its incidence. This is partly due to a high level of intratumoral heterogeneity, driven by genomic instability, that promotes disease recurrence and treatment failure. In this study, we describe degrees of heterogeneity revealed by single-cell whole-genome sequencing and spatial transcriptomics (ST) of five late-stage, treatment-naïve primary epithelial ovarian carcinomas, including high-grade serous and clear-cell subtypes. All samples exhibited widespread copy-number (CN) aberrations, with the greatest intraspecimen diversification in regions of CN gain. Diversification was also associated with whole-genome doubling in all samples. In two samples, we identify persistent, clonal pseudodiploid cells evolutionarily consistent with a premalignant phenotype. In multiclonal samples, we interpret clonal evolution in the context of single-cell CN, loss of heterozygosity analysis, and somatic mutations and correlate these with tissue histology and gene expression programs. In one high-grade serous carcinoma, we identify functionally consequential CN alterations that contribute to molecular diversity, cell proliferation, and inflammation in a minor clone that persisted without major expansion alongside a more complex major clone. In another clear-cell carcinoma, we describe a complex evolutionary history, including a spontaneous functional reversion of a CTNNB1 driver mutation in a secondary clone, which correlated with a switch in oncogenic expression programs. These examples highlight various consequences of genomic instability on clonal heterogeneity and plasticity in ovarian cancer. SIGNIFICANCE: We utilize single-cell DNA sequencing and ST to illustrate the wide extent of intratumoral heterogeneity within late-stage ovarian tumors. We describe several consequences of chromosomal instability, including divergent biology in multiclonal tumors, persistence of a premalignant cell population, and functional reversion of an oncogenic driver mutation.

Indexed as

Ovarian NeoplasmsWhole Genome SequencingDNA Copy Number VariationsFemaleGenetic HeterogeneityGenomic InstabilityHumansLoss of HeterozygosityMutationSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisSpatial Transcriptomics

Identifiers

PMID42007974
PMCPMC13137417

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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.