Evidence map›Paper›PMID 37398147›Full record

ArticlebioRxiv : the preprint server for biology2023

A survey of CIN measures across mechanistic models.

Andrew R Lynch, Shermineh Bradford, Amber S Zhou, Kim Oxendine, Les Henderson, Vanessa L Horner, Beth A Weaver, Mark E Burkard

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Andrew R LynchCarbone Cancer Center, University of Wisconsin - Madison, Madison, WI, USA.
Shermineh BradfordCarbone Cancer Center, University of Wisconsin - Madison, Madison, WI, USA.
Amber S ZhouCarbone Cancer Center, University of Wisconsin - Madison, Madison, WI, USA.
Kim OxendineWisconsin State Laboratory of Hygiene, University of Wisconsin - Madison, Madison, WI, USA.
Les HendersonWisconsin State Laboratory of Hygiene, University of Wisconsin - Madison, Madison, WI, USA.
Vanessa L HornerWisconsin State Laboratory of Hygiene, University of Wisconsin - Madison, Madison, WI, USA.
Beth A WeaverCarbone Cancer Center, University of Wisconsin - Madison, Madison, WI, USA.
Mark E BurkardCarbone Cancer Center, University of Wisconsin - Madison, Madison, WI, USA.
University of Wisconsin–Madison · USUniversity of Wisconsin System · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Justine Yang Bruce · 1985 to 2026
$142.6M
Viral VectorP30CA086862 · NCI · UNIVERSITY OF IOWA · PI Jon C.D. Houtman · 2000 to 2026
$70.0M
Institutional Training in the Genomic SciencesT32HG002760 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI Qiongshi Lu · 2003 to 2026
$17.7M
Training Program In Molecular AND Cellular PharmacologyT32GM008688 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI AUDHYA, ANJON · 1998 to 2020
$6.0M
Impact of chromosomal instability on sensitivity to microtubule-targeting drugs in breast cancerR01CA234904 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI BURKARD, MARK E, WEAVER, BETH A · 2019 to 2023
$2.7M
Multi-color Benchtop Flow CytometerS10RR025483 · NCRR · UNIVERSITY OF WISCONSIN-MADISON · PI BUSHMAN, WADE A · 2009 to 2009
$449k
Frequency and consequences of chromosome missegregation in breast cancerF31CA254247 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI LYNCH, ANDREW · 2021 to 2022
$67k
NCI NIH HHS F31 CA254247NCI NIH HHS P30 CA014520NCI NIH HHS P30 CA086862NCI NIH HHS R01 CA234904NCRR NIH HHS S10 RR025483NHGRI NIH HHS T32 HG002760NIGMS NIH HHS T32 GM008688
6 · The paper itself

Abstract

Chromosomal instability (CIN) is the persistent reshuffling of cancer karyotypes via chromosome mis-segregation during cell division. In cancer, CIN exists at varying levels that have differential effects on tumor progression. However, mis-segregation rates remain challenging to assess in human cancer despite an array of available measures. We evaluated measures of CIN by comparing quantitative methods using specific, inducible phenotypic CIN models of chromosome bridges, pseudobipolar spindles, multipolar spindles, and polar chromosomes. For each, we measured CIN fixed and timelapse fluorescence microscopy, chromosome spreads, 6-centromere FISH, bulk transcriptomics, and single cell DNA sequencing (scDNAseq). As expected, microscopy of tumor cells in live and fixed samples correlated well (R=0.77; p<0.01) and sensitively detect CIN. Cytogenetics approaches include chromosome spreads and 6-centromere FISH, which also correlate well (R=0.77; p<0.01) but had limited sensitivity for lower rates of CIN. Bulk genomic DNA signatures and bulk transcriptomic scores, CIN70 and HET70, did not detect CIN. By contrast, single-cell DNA sequencing (scDNAseq) detects CIN with high sensitivity, and correlates very well with imaging methods (R=0.83; p<0.01). In summary, single-cell methods such as imaging, cytogenetics, and scDNAseq can measure CIN, with the latter being the most comprehensive method accessible to clinical samples. To facilitate comparison of CIN rates between phenotypes and methods, we propose a standardized unit of CIN: Mis-segregations per Diploid Division (MDD). This systematic analysis of common CIN measures highlights the superiority of single-cell methods and provides guidance for measuring CIN in the clinical setting.

Indexed as

aneuploidychromosomal instabilityclinical biomarkersmitosis

Identifiers

PMID37398147
PMCPMC10312700
OpenAlexW4380792117

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.