Evidence map›Paper›PMID 42286854›Full record

ArticleCancer reports (Hoboken, N.J.)2026

Unveiling Candidate Markers for Drug Resistance or Synthetic Lethality in Cervical Cancer: Integrative Analysis of Genetic and Pharmacoprofiling.

Suzy Scholl, Elaine Del Nery, Pierre Gestraud, Maral Halladjian, Elodie Girard, Adèle Soria, Elodie Anthony, Leanne De Koning, Nicolas Servant, Els Berns and 1 more

Abstract read
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2026. 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

11 authors.

Suzy SchollDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, Paris, France.ORCID 0000-0003-0277-6219
Elaine Del NeryBiophenics High-Content Screening Laboratory, PICT-IBiSA, Paris Biofoundry/UMR168, Department of Translational Research, Institut Curie, PSL Research University, Paris, France.
Pierre GestraudComputational Oncology, PSL Research University, Mines Paris Tech, INSERM U1331, Paris, France.
Maral HalladjianDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, Paris, France.
Elodie GirardComputational Oncology, PSL Research University, Mines Paris Tech, INSERM U1331, Paris, France.ORCID 0000-0001-8737-5371
Adèle SoriaBiophenics High-Content Screening Laboratory, PICT-IBiSA, Paris Biofoundry/UMR168, Department of Translational Research, Institut Curie, PSL Research University, Paris, France.
Elodie AnthonyBiophenics High-Content Screening Laboratory, PICT-IBiSA, Paris Biofoundry/UMR168, Department of Translational Research, Institut Curie, PSL Research University, Paris, France.
Leanne De KoningDepartment of Translational Research, Institut Curie, PSL Research University, Paris, France.
Nicolas ServantComputational Oncology, PSL Research University, Mines Paris Tech, INSERM U1331, Paris, France.
Els BernsDepartment of Medical Oncology, Erasmus MC, Rotterdam, the Netherlands.
Maud KamalDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, Paris, France.

Funding

European Unions Seventh Program for Research, Technological Development and Demonstration 304810Fondation ARC Pour la Recherche Contre le Cancer
6 · The paper itself

Abstract

introductionSystemic cervical cancer management continues to be challenging. Numerous chemotherapies have been approved, but predicting response is difficult due to the lack of biomarkers. Here, we analyze the genetic and protein profiles of 20 cervical cancer cell lines (CCCLs) and explore their correlation with drug response patterns to commonly used drugs, aiming to identify novel biomarkers of treatment response or resistance. MATERIAL AND

methodsTwenty cell lines (CLs) were characterized for HPV type, for genetic alterations, and protein expression profiles. Pharmacoprofiling in 10 selected CLs was carried out against 34 drugs used in the clinic, assessing drug concentrations needed to reach half maximal inhibitory concentration (IC50) in nanomolar and micromolar ranges. Subtractive bioinformatics analyses aimed to identify genetic alterations (609 genes of clinical interest), associated with CL drug resistance or on the contrary with synthetic lethality.

resultsDespite a small sample size, genetic alteration frequencies and types of CCCLs were in line with those in clinical samples, except for the detection of a higher frequencyin specific genetic alterations such as NBPF1 and STK11 in CLs. Pharmacological screening identified drugs exhibiting therapeutic activity in most CLs while others were highly selective. Bioinformatics analyses suggested, loss-of-function (LoF) alterations in PAPBC3 in CLs sensitive to microtubule interfering agentsin addition to 50 variably present alterations in the microtubule pathway. LoF alterations in CSMD3, OBSCN, ZNF 717, ALPK2, CLDND1, GTF3A, NLRP1, SI, and TRIM66 were associated with Epigenetic acting drug activity and LoF of OSBPL1A with Eprenetapopt (APR-246) activity. Drug synergistic effects were observed with certain drug combinations.

conclusionThis paper reports genetic variants in 20 CLs as well as the results of the assessment on whether those variants may help predict response or resistance to certain drug families. With a few exceptions, genetic alteration frequency in CCCLs, conducted in the same analytical batches, compares favorably with published patient data. Results need confirmation in independent larger studies both in CLs and in clinical settings.

Indexed as

Antineoplastic AgentsBiomarkers, TumorDrug Resistance, NeoplasmSynthetic Lethal MutationsUterine Cervical NeoplasmsCell Line, TumorFemaleGene Expression Regulation, NeoplasticHuman Papillomavirus VirusesHumansAntineoplastic AgentsBiomarkers, TumorBioRAIDScell linescervical cancerepigenetic targetinggenetic biomarkersHPVmicrotubule targetingpharmacoprofilingprotein biomarkersstandard therapy

Identifiers

PMID42286854
PMCPMC13263414

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Registered trials

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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.