Development and validation of a gene expression-based Breast Cancer Purity Score.


Journal

NPJ precision oncology
ISSN: 2397-768X
Titre abrégé: NPJ Precis Oncol
Pays: England
ID NLM: 101708166

Informations de publication

Date de publication:
24 Oct 2024
Historique:
received: 20 03 2024
accepted: 06 10 2024
medline: 25 10 2024
pubmed: 25 10 2024
entrez: 25 10 2024
Statut: epublish

Résumé

The prevalence of malignant cells in clinical specimens, or tumour purity, is affected by both intrinsic biological factors and extrinsic sampling bias. Molecular characterization of large clinical cohorts is typically performed on bulk samples; data analysis and interpretation can be biased by tumour purity variability. Transcription-based strategies to estimate tumour purity have been proposed, but no breast cancer specific method is available yet. We interrogated over 6000 expression profiles from 10 breast cancer datasets to develop and validate a 9-gene Breast Cancer Purity Score (BCPS). BCPS outperformed existing methods for estimating tumour content. Adjusting transcriptomic profiles using the BCPS reduces sampling bias and aids data interpretation. BCPS-estimated tumour purity improved prognostication in luminal breast cancer, correlated with pathologic complete response in on-treatment biopsies from triple-negative breast cancer patients undergoing neoadjuvant treatment and effectively stratified the risk of relapse in HER2+ residual disease post-neoadjuvant treatment.

Identifiants

pubmed: 39448787
doi: 10.1038/s41698-024-00730-7
pii: 10.1038/s41698-024-00730-7
doi:

Types de publication

Journal Article

Langues

eng

Pagination

242

Investigateurs

Luca Gianni (L)
Giancarlo Bisagni (G)
Marco Colleoni (M)
Lucia Del Mastro (L)
Claudio Zamagni (C)
Mauro Mansutti (M)
Milvia Zambetti (M)
Antonio Frassoldati (A)
Luca Gianni (L)
Filippo Montemurro (F)
Claudio Zamagni (C)
Lucia Del Mastro (L)
Carmelo Bengala (C)
Marco Colleoni (M)
Gabriella Mariani (G)
Anna Gambaro (A)
Stefania Zambelli (S)
Giampaolo Bianchini (G)
Giancarlo Bisagni (G)
Stefania Russo (S)
Chiun-Sheng Huang (CS)
Shou-Tung Chen (ST)
Ming Feng Hou (MF)
Liang-Chih Liu (LC)
Ling Ming Tseng (LM)
Catherine Kelly (C)
Seamus O'Reilly (S)
Patrick Morris (P)
John Kennedy (J)
Miriam O'Connor (M)
Richard Greil (R)
Daniel Egle (D)
Mark Thill (M)
Jacqueline Sagasser (J)
Gerd Graffunder (G)
Dirk Behringer (D)
Hans Tesch (H)
Hans-Joachim Lück (HJ)
Andreas Schneeweiss (A)
Claudia Schumacher (C)
Wolfram Malter (W)
Vladimir Semiglazov (V)
Mona Frolova (M)
Alexander Vasiliev Gennadievich (AV)
Nikita Volkov (N)
Begoña Bermejo (B)
Catalina Falo (C)
Elena Sevillano (E)
Eva Maria Ciruelos Gil (EM)
José Ángel García Sáenz (JÁ)
Anton Antón-Torres (A)

Informations de copyright

© 2024. The Author(s).

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Auteurs

Marco Barreca (M)

Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy.
Fondazione Michelangelo, Milan, Italy.

Matteo Dugo (M)

IRCCS San Raffaele Hospital, Milan, Italy.

Barbara Galbardi (B)

IRCCS San Raffaele Hospital, Milan, Italy.

Balázs Győrffy (B)

Department of Bioinformatics, Semmelweis University, H-1094, Budapest, Hungary.
Department of Biophysics, Medical School, University of Pecs, H-7624, Pecs, Hungary.
Cancer Biomarker Research Group, Institute of Molecular Life Sciences, Research Centre for Natural Sciences, H-1117, Budapest, Hungary.

Pinuccia Valagussa (P)

Fondazione Michelangelo, Milan, Italy.

Daniela Besozzi (D)

Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy.
Bicocca Bioinformatics, Biostatistics and Bioimaging (B4) Research Centre, Milan, Italy.

Giuseppe Viale (G)

European Institute of Oncology, Milan, Italy.

Giampaolo Bianchini (G)

IRCCS San Raffaele Hospital, Milan, Italy. bianchini.giampaolo@hsr.it.
Università Vita-Salute San Raffaele, Milan, Italy. bianchini.giampaolo@hsr.it.

Luca Gianni (L)

Fondazione Michelangelo, Milan, Italy. luca.gianni@fondazionemichelangelo.org.

Maurizio Callari (M)

Fondazione Michelangelo, Milan, Italy. maurizio.callari@fondazionemichelangelo.org.

Classifications MeSH