Evidence map›Paper›PMID 41064807›Full record

ArticleNAR cancer2025

Reference-free RNA profiling predicts triple negative breast cancer chemoresistance to neoadjuvant treatment.

Nouritza Torossian, Marc Gabriel, Panagiotis Papoutsoglou, Dominika Foretek, Camille Brochard, Maud Kamal, Linda Ramdani, Constance Lamy, Charlotte Lecerf, Maral Halladjian and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NAR cancer, 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. Trial
  2. Review
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

19 authors.

Nouritza TorossianncRNA, Epigenetic and Genome Fluidity, CNRS UMR3244, Sorbonne University, PSL University, Institut Curie, Centre de Recherche, 75005 Paris, France.
Marc GabrielncRNA, Epigenetic and Genome Fluidity, CNRS UMR3244, Sorbonne University, PSL University, Institut Curie, Centre de Recherche, 75005 Paris, France.
Panagiotis PapoutsoglouncRNA, Epigenetic and Genome Fluidity, CNRS UMR3244, Sorbonne University, PSL University, Institut Curie, Centre de Recherche, 75005 Paris, France.
Dominika ForetekncRNA, Epigenetic and Genome Fluidity, CNRS UMR3244, Sorbonne University, PSL University, Institut Curie, Centre de Recherche, 75005 Paris, France.
Camille BrochardDepartment of Pathology, Institut Curie, 75005 Paris, France.
Maud KamalDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, 75005Paris, France.
Linda RamdaniDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, 75005Paris, France.
Constance LamyDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, 75005Paris, France.ORCID 0000-0003-0311-8031
Charlotte LecerfDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, 75005Paris, France.
Maral HalladjianDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, 75005Paris, France.
Celia DupainDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, 75005Paris, France.
Josiane LafleurSegal Cancer Center, Lady Davis Institute, Jewish General Hospital, H3T 1E2 Montreal, Quebec, Canada.
Adriana Aguilar-MahechaSegal Cancer Center, Lady Davis Institute, Jewish General Hospital, H3T 1E2 Montreal, Quebec, Canada.
Mark BasikSegal Cancer Center, Lady Davis Institute, Jewish General Hospital, H3T 1E2 Montreal, Quebec, Canada.
Anne Vincent-SalomonDepartment of Pathology, Institut Curie, 75005 Paris, France.ORCID 0000-0001-5754-5771
Christophe L E TourneauDepartment of Drug Development and Innovation (D3i), Institut Curie, Paris-Saclay University, 75005Paris, France.
Sergio Roman-RomanDepartment of Translational Research, Institut Curie, 75005 Paris, France.
Daniel GautheretUniversité Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), 91190 Gif-sur-Yvette, France.ORCID 0000-0002-1508-8469
Antonin MorillonncRNA, Epigenetic and Genome Fluidity, CNRS UMR3244, Sorbonne University, PSL University, Institut Curie, Centre de Recherche, 75005 Paris, France.ORCID 0000-0002-0575-5264

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple negative breast cancer (TNBC) is the most aggressive breast cancer (BC) and often affects young women. TNBCs are highly heterogeneous and do not benefit from personalized medicine at localized stages. Most TNBC patients undergo neoadjuvant chemotherapy (NAC) before surgery. In case of chemoresistance with residual tumor after NAC, survival is poor despite execution of complete tumor resection. There is currently no clinically useful biomarker to predict TNBC chemoresistance to NAC that would enable targeted therapeutic intensification. We analyzed here a unique cohort of 106 TNBC tumors before NAC, including 58 chemoresistant and 48 chemosensitive cases, from 2 independent hospitals. Using machine learning under a nested cross-validation design, we obtained two transcriptomic signatures respectively generated from standard differential gene expression analysis and reference-free analysis of differential fragments of transcripts, without any annotation bias. This approach resulted in accurate signatures of TNBC chemoresistance to NAC. Gene ontology analyses of reference-free signatures highlighted DNA repair, replication, and metabolism, in agreement with current knowledge of TNBC resistance biology. In summary, these results show the potential of a reference-free generated transcriptomic signature as predictive biomarker of early TNBC chemoresistance.

Indexed as

Drug Resistance, NeoplasmGene Expression ProfilingTriple Negative Breast NeoplasmsAdultAgedBiomarkers, TumorFemaleGene Expression Regulation, NeoplasticHumansMachine LearningMiddle AgedNeoadjuvant TherapyTranscriptomeBiomarkers, Tumor

Identifiers

PMID41064807
PMCPMC12501781

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.