Evidence map›Paper›PMID 40081367›Full record

ArticleCell reports methods2025

A sequence context-based approach for classifying tumor structural variants without paired normal samples.

Wolu Chukwu, Siyun Lee, Alexander Crane, Shu Zhang, Sophie Webster, Oumayma Dakhama, Ipsa Mittra, Carlos Rauert, Marcin Imielinski, Rameen Beroukhim and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports methods, 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. Article
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

12 authors.

Wolu ChukwuCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Siyun LeeCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Alexander CraneCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Shu ZhangCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Sophie WebsterCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Oumayma DakhamaCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Ipsa MittraCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Carlos RauertCharité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Institute of Pathology, Berlin, Germany.
Marcin ImielinskiDepartment of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA; New York Genome Center, New York, NY, USA; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA; Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA; Department of Pathology and Perlmutter Cancer Center, NYU Grossman School of Medicine, New York, NY, USA.
Rameen BeroukhimCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Frank DuboisCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Institute of Pathology, Berlin, Germany. Electronic address: frank.dubois@charite.de.
Simona DalinCancer Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA. Electronic address: sdalin@broadinstitute.org.

Funding

Genetic evolution of glioblastomas during radiation and temozolomide therapyR01CA188228 · NCI · DANA-FARBER CANCER INST · PI BEROUKHIM, RAMEEN, CHAKRAVARTI, ARNAB · 2015 to 2025
$6.9M
Factors Shaping the Genomic Spectrum of Structural VariantsK99GM155595 · NIGMS · BROAD INSTITUTE, INC. · PI DALIN, SIMONA · 2024 to 2025
$324k
Differential resistance mechanisms to monofunctional vs bifunctional alkylating agents in gliomaF32CA261024 · NCI · BROAD INSTITUTE, INC. · PI DALIN, SIMONA · 2021 to 2023
$208k
NCI NIH HHS F32 CA261024NCI NIH HHS R01 CA188228NIGMS NIH HHS K99 GM155595
6 · The paper itself

Abstract

Although several recent studies have characterized structural variants (SVs) in germline and cancer genomes independently, the genomic contexts of these SVs have not been comprehensively compared. We examined similarities and differences between 2 million germline and 115 thousand tumor SVs from a cohort of 963 patients from The Cancer Genome Atlas. We found significant differences in features related to their genomic sequences and localization that suggest differences between SV-generating processes and selective pressures. For example, our results show that features linked to transposon-mediated processes are associated with germline SVs, while somatic SVs more frequently show features characteristic of chromoanagenesis. These genomic differences enabled us to develop a classifier-the Germline and Tumor Structural Variant or "the great GaTSV" -that accurately distinguishes between germline and cancer SVs in tumor samples that lack a matched normal sample.

Indexed as

Genomic Structural VariationNeoplasmsGenome, HumanGenomicsHumanscancerchromosomal rearrangementsCP: cancer biologyCP: geneticsgenomic structural variantsgermline and somatic structural variantsmachine learning classifierWGS

Identifiers

PMID40081367
PMCPMC12049684

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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.