Evidence map›Paper›PMID 40466638›Full record

ArticleCell reports. Medicine2025

Screening a living biobank identifies cabazitaxel as a strategy to combat acquired taxol resistance in high-grade serous ovarian cancer.

Anthony Tighe, Louisa Nelson, Robert D Morgan, Bethany M Barnes, I-Hsuan Lin, Samantha Littler, James Altringham, Jean Ling Tan, Joanne C McGrail, Stephen S Taylor

Abstract read
In one paragraph

Article in Cell reports. Medicine, 2025. 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

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

10 authors.

Anthony TigheDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK.
Louisa NelsonDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK.
Robert D MorganDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK; Department of Medical Oncology, The Christie NHS Foundation Trust, Wilmslow Road, Manchester M20 4BX, UK.
Bethany M BarnesDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK.
I-Hsuan LinBioinformatics Core Facility, Faculty of Biology, Medicine and Health, University of Manchester, Michael Smith Building, Dover Street, Manchester M13 9PT, UK.
Samantha LittlerDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK.
James AltringhamDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK.
Jean Ling TanDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK.
Joanne C McGrailDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK.
Stephen S TaylorDivision of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Cancer Research Centre, 555 Wilmslow Road, Manchester M20 4GJ, UK. Electronic address: stephen.taylor@manchester.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The anti-mitotic agent taxol (paclitaxel) remains a cornerstone of ovarian cancer treatment. To tackle drug resistance and toxicity, second-generation targeted anti-mitotic agents and combination strategies are being explored but have yet to demonstrate meaningful clinical benefits. A limitation is the lack of a platform to compare strategies in models that capture disease heterogeneity. To overcome this, we screen 83 patient-derived ex vivo ovarian cancer models that exhibit extensive intra- and inter-patient heterogeneity, testing four distinct approaches to enhance taxol sensitivity. Inhibitors of the HSET kinesin or the Mps1 spindle assembly checkpoint kinase show minimal impact on the taxol sensitivity landscape. By contrast, Bcl-xL inhibition exerts a global anti-proliferative effect. Inhibition of the MDR1 drug efflux pump restores taxol sensitivity in models characterized by ABCB1 overexpression. These MDR1-driven resistant models also respond to cabazitaxel, which is a poor MDR1 substrate, highlighting a potential therapeutic option for ovarian cancers with acquired taxol resistance.

Indexed as

Cystadenocarcinoma, SerousDrug Resistance, NeoplasmOvarian NeoplasmsPaclitaxelTaxoidsATP Binding Cassette Transporter, Subfamily BCell Cycle ProteinsCell Line, TumorCell ProliferationFemaleHumansNeoplasm GradingProtein Serine-Threonine KinasesABCB1 protein, humanATP Binding Cassette Transporter, Subfamily BcabazitaxelCell Cycle ProteinsPaclitaxelProtein Serine-Threonine KinasesTaxoidsABCB1centrosome amplificationchromosome instabilitydrug resistanceintrinsic apoptosis pathwayMDR1ovarian cancerpaclitaxelspindle assembly checkpointtaxol

Identifiers

PMID40466638
PMCPMC12208324

What Socratic holds

Textmetadata
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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 Socratic graph.