Evidence map›Paper›PMID 41856042›Full record

ArticleCell systems2026

Haplotype-resolved reconstruction and functional interrogation of cancer karyotypes.

Gregory J Brunette, Richard W Tourdot, Jinyu Wang, Darawalee Wangsa, David Pellman, Cheng-Zhong Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Gregory J BrunetteDepartment of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA; Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: gbrunette@g.harvard.edu.
Richard W TourdotDepartment of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
Jinyu WangDepartment of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA.
Darawalee WangsaNational Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
David PellmanDepartment of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA; Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA.
Cheng-Zhong ZhangBroad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA. Electronic address: cheng-zhong_zhang@dfci.harvard.edu.

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
Mechanisms Driving the Rapid Evolution of Cancer GenomesR35CA293978 · NCI · DANA-FARBER CANCER INST · PI DAVID S PELLMAN · 2024 to 2026
$3.1M
Probing the role of somatic X-chromosome alterations in shaping cancer sex differencesR01CA286652 · NCI · DANA-FARBER CANCER INST · PI VISWANATHAN, SRINIVAS RAGHAVAN, ZHANG, CHENG-ZHONG · 2023 to 2025
$2.7M
Enhancement and further development of informatics methods for long-read cancer sequencingU24CA294203 · NCI · DANA-FARBER CANCER INST · PI Catarina D. Campbell, Heng Li · 2024 to 2026
$2.6M
Single-cell analysis of mutagenesis: from mutational mechanisms to functional consequencesK22CA216319 · NCI · DANA-FARBER CANCER INST · PI ZHANG, CHENG-ZHONG · 2017 to 2019
$596k
NCI NIH HHS K22 CA216319NCI NIH HHS R01 CA286652NCI NIH HHS R35 CA293978NCI NIH HHS U24 CA294203NLM NIH HHS T15 LM007092
6 · The paper itself

Abstract

Complex karyotype changes are widespread in cancer genomes. A major gap in cancer genome characterization is the resolution of rearranged chromosomes with chromosome-length continuity. Here, we describe a two-tiered approach to determine the segmental composition of rearranged chromosomes with haplotype resolution. First, we present refLinker, a bioinformatic method for robust determination of chromosomal haplotypes using cancer Hi-C data. By contrast with existing methods, refLinker is insensitive to the presence of large-scale DNA deletions, duplications, and high-level amplification in cancer genomes. Second, we demonstrate a computational strategy to determine the segmental structure of rearranged chromosomes using haplotype-specific Hi-C contacts. We apply these methods to breast cancer genomes and provide direct evidence for long-range transcriptional changes associated with rearrangements of the inactive X chromosome. Together, these results highlight refLinker's broad utility for studying the functional consequences of chromosomal rearrangements.

Indexed as

HaplotypesNeoplasmsBreast NeoplasmsComputational BiologyFemaleGene RearrangementHumansKaryotypeKaryotypingcancer genome assemblydigital karyotypehaplotype phasingX chromosome inactivation

Identifiers

PMID41856042
PMCPMC13127165

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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.