Evidence map›Paper›PMID 42298170›Full record

ArticleNPJ digital medicine2026

Deep learning analysis of breast cancer histology predicts ATM pathogenic variant carrier status.

Nicolas M Viart, Lucie Thibault, Tristan Lazard, Séverine Eon-Marchais, Yue Jiao, Laetitia Fuhrmann, Dorothée Le Gal, Eve Cavaciuti, Marie-Gabrielle Dondon, Juana Beauvallet and 12 more

Abstract read
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In one paragraph

Article in NPJ digital medicine, 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

22 authors.

Nicolas M ViartInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Lucie ThibaultDepartment of Pathology, Institut Curie, Paris, France.
Tristan LazardInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Séverine Eon-MarchaisInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Yue JiaoInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Laetitia FuhrmannDepartment of Pathology, Institut Curie, Paris, France.
Dorothée Le GalInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Eve CavaciutiInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Marie-Gabrielle DondonInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Juana BeauvalletInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Marina De BrotDepartment of Anatomic Pathology, A.C. Camargo Cancer Center, São Paulo, Brazil.
Joanne NgeowCancer Genetics Service, National Cancer Centre Singapore, Singapore, Singapore.
Soo-Hwang TeoMalaysia Cancer Research Program, Department of Surgery, Faculty of Medicine, University of Malaysia, Kuala Lumpur, Malaysia, Jalan Universiti, Kuala Lumpur, Malaysia.
Maria Isabel AchatzCentro de Oncologia, Hospital Sírio-Libanês, São Paulo, Brazil.
Elizabeth Santana Dos SantosDepartment of Anatomic Pathology, A.C. Camargo Cancer Center, São Paulo, Brazil.
Fergus J CouchMayo Clinic, Rochester, NY, USA.
Dominique Stoppa-LyonnetService de Génétique, Institut Curie, Paris, France, Université Paris Cité, Paris, France, Inserm, Paris, France.
Melissa C SoutheyMonash University, Clayton, Australia, University of Melbourne, Parkville, VIC, Australia.
Anne Vincent-SalomonCenter for Computational Biology (CBIO), Mines Paris, Paris, France, PSL University, Paris, France.
Thomas WalterInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Nadine AndrieuInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France.
Fabienne LesueurInserm, U1331, Institut Curie, Paris, France, PSL University, Paris, France, Mines Paris, Paris, France. fabienne.lesueur@curie.fr.

Funding

Core-001U01CA164920 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Irene Andrulis, Sarah Violet Colonna · 2018 to 2026
$17.0M
NCI NIH HHS U01 CA164920NHMRC GNT2017325
6 · The paper itself

Abstract

We performed deep learning analysis of histopathological whole-slide (full-face) images (WSI) to predict ATM pathogenic or likely pathogenic variant (PV/LPV) status of women with breast cancer and identify specific histological patterns of their tumor.In the discovery set composed of tumors from PV/LPV carriers (58 WSI) and noncarriers (129 WSI), our deep learning model predicted ATM status of patients with an area under the curve of 0.90 [95%CI: 0.85-0.95] and a balanced accuracy of 0.80 [95%CI: 0.72-0.88]. In the replication set (29 WSI from carriers and 22 WSI from noncarriers), corresponding results were 0.85 [95%CI: 0.70-1.00] and 0.67 [95%CI: 0.51-0.83]. We found that tumors developed by ATM PV/LPV carriers often displayed discohesive neoplastic cells as observed in invasive lobular carcinomas, and dense lymphocytic infiltrate reflecting an immune-enriched microenvironment.Recognizing these tumors at the time of diagnosis is a critical first step toward precision medicine in affected women and precision prevention in family members.

Identifiers

PMID42298170
PMCPMC13631238

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.