Evidence map›Paper›PMID 39353885›Full record

ArticleNature communications2024

Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data.

Adam C Weiner, Marc J Williams, Hongyu Shi, Ignacio Vázquez-García, Sohrab Salehi, Nicole Rusk, Samuel Aparicio, Sohrab P Shah, Andrew McPherson

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Adam C WeinerComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0002-5968-3606
Marc J WilliamsComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0001-5524-4174
Hongyu ShiComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Ignacio Vázquez-GarcíaComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Sohrab SalehiComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Nicole RuskComputational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.ORCID 0000-0003-2663-6288
Samuel AparicioDepartment of Molecular Oncology, British Columbia Cancer, Vancouver, BC, Canada.ORCID 0000-0002-0487-9599
Sohrab P Shah *Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. shahs3@mskcc.org.ORCID 0000-0001-6402-523X
Andrew McPherson *Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. mcphera1@mskcc.org.ORCID 0000-0002-5654-5101

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Center for Integrated Cellular Analysis - Valeria A. Sanchez EstradaRM1HG011014 · NHGRI · NEW YORK GENOME CENTER · PI LANDAU, DAN, SATIJA, RAHUL · 2020 to 2025
$22.1M
Causal determinants of drug resistance and metastasis in cancer with multimodal single cell dataK99CA277562 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI SALEHI, SOHRAB · 2023 to 2024
$232k
Single cell quantification of genomic instability in cancer as a determinant of therapeutic responseK99CA256508 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI WILLIAMS, MARC · 2021 to 2022
$200k
Quantifying replication dynamics to predict clonal evolution and drug sensitivity in cancer cells using single-cell whole genome sequencingF31CA271673 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI WEINER, ADAM CLAYTON · 2023 to 2024
$77k
Cancer Research UK (CRUK) GC-243330NCI NIH HHS F31 CA271673NCI NIH HHS K99 CA256508NCI NIH HHS K99 CA277562NCI NIH HHS P30 CA008748NHGRI NIH HHS RM1 HG011014U.S. Department of Health & Human Services | National Institutes of Health (NIH) RM1-HG011014U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) P30-CA008748
6 · The paper itself

Abstract

Dysregulated DNA replication is a cause and a consequence of aneuploidy in cancer, yet the interplay between copy number alterations (CNAs), replication timing (RT) and cell cycle dynamics remain understudied in aneuploid tumors. We developed a probabilistic method, PERT, for simultaneous inference of cell-specific replication and copy number states from single-cell whole genome sequencing (scWGS) data. We used PERT to investigate clone-specific RT and proliferation dynamics in  >50,000 cells obtained from aneuploid and clonally heterogeneous cell lines, xenografts and primary cancers. We observed bidirectional relationships between RT and CNAs, with CNAs affecting X-inactivation producing the largest RT shifts. Additionally, we found that clone-specific S-phase enrichment positively correlated with ground-truth proliferation rates in genomically stable but not unstable cells. Together, these results demonstrate robust computational identification of S-phase cells from scWGS data, and highlight the importance of RT and cell cycle properties in studying the genomic evolution of aneuploid tumors.

Indexed as

AneuploidyCell ProliferationDNA Copy Number VariationsDNA Replication TimingSingle-Cell AnalysisAnimalsCell CycleCell Line, TumorDNA ReplicationHumansMiceNeoplasmsSequence Analysis, DNAS PhaseWhole Genome Sequencing

Identifiers

PMID39353885
PMCPMC11445576

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.