Evidence map›Paper›PMID 41288728›Full record

ArticleChromosoma2025

Sustainable integrative cell biology: CENP-C is guilty by association.

Natalia Y Kochanova, Itaru Samejima, William C Earnshaw

Abstract read
In one paragraph

Article in Chromosoma, 2025. 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.

No citing paper in PubMed yet.

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

3 authors.

Natalia Y KochanovaInstitute of Cell Biology, The University of Edinburgh, Edinburgh, Scotland, EH9 3BF, UK. natalia.kochanova@ed.ac.uk.
Itaru SamejimaInstitute of Cell Biology, The University of Edinburgh, Edinburgh, Scotland, EH9 3BF, UK.
William C EarnshawInstitute of Cell Biology, The University of Edinburgh, Edinburgh, Scotland, EH9 3BF, UK. bill.earnshaw@ed.ac.uk.

Funding

Wellcome Trust
6 · The paper itself

Abstract

In the 40 years since the discovery of the CENP proteins, many studies have examined the role of these proteins and their interactions with other chromosomal proteins of the centromere and beyond. Together, these studies have yielded vast amounts of sequencing and proteomics data. Typically, each study has focused on a single question and the majority of each dataset remains largely unexplored. Often the interesting details of publicly deposited data are left behind, buried in archives online, while more and more new data are generated. Reanalysing these databases can represent a new paradigm for investigating diverse biological pathways in unprecedented detail. Here, we explore two publicly available pan-cancer proteomic datasets to compare proteins whose abundance correlates with CENP proteins, with a particular focus on CENP-C. Our analysis confirms an expected link between CENP-C and cohesin levels but reveals a surprising and unexpected correlation between CENP-C and proteins of the inner nuclear membrane and the NuMA protein. This guilt-by-association analysis has the potential to identify proteins that act in common pathways but never associate or colocalize and may not even be expressed at the same time in cells. As an example, we show here that it can reveal unexpected links that expand our conception of centromeric chromatin beyond chromosome segregation.

Indexed as

Chromosomal Proteins, Non-HistoneCell Cycle ProteinsCentromereCohesinsHumansNeoplasmsNuclear Matrix-Associated ProteinsProteomicsCell Cycle Proteinscentromere protein CChromosomal Proteins, Non-HistoneCohesinsNuclear Matrix-Associated ProteinsNUMA1 protein, humanCell biologyCentromeresCorrelationDiscovery of CENPsGuilt by association

Identifiers

PMID41288728
PMCPMC12647346

What OpenQuestion holds

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LicenceCC BY
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.