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

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.

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Publication Details

Journal
npj Precision Oncology
Published
2024-10-24
DOI
https://doi.org/10.1038/s41698-024-00730-7
Citations
2
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.47

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article

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

Balázs Győrffy, Barbara Galbardi, Maurizio Callari, Giampaolo Bianchini et al.
2 citations
npj Precision Oncology
Gene expression and cancer classification
0.47
article

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

Balázs Győrffy, Barbara Galbardi, Maurizio Callari, Giampaolo Bianchini, Luca Gianni, Marco Barreca, Pinuccia Valagussa, Matteo Dugo, Daniela Besozzi, Giuseppe Viale
article en
2 citations

Abstract

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.

npj Precision OncologyVol. 8(1)
Semmelweis University (HU), University of Udine (IT), Vita-Salute San Raffaele University (IT), China Medical University (TW), Heidelberg University (DE), Paracelsus Medical University (AT), Russian Railways (RU), University Hospital Waterford (IE), Beaumont Hospital (IE), University Hospital Augsburg (DE), University Hospital Heidelberg (DE), Cork University Hospital (IE), Kaohsiung Medical University Chung-Ho Memorial Hospital (TW), Taipei Veterans General Hospital (TW), Mater Misericordiae University Hospital (IE), Hospital Clínico San Carlos (ES), Luigi Sacco Hospital (IT), Elisabeth-Krankenhaus Essen (DE), Klinik für Frauenheilkunde (DE), Azienda Sanitaria Unità Locale di Reggio Emilia (IT), Russian Cancer Research Center NN Blokhin (RU), BrustGesundheitZentrum Tirol (AT), Hospital Clínico Universitario de Valencia (ES), IRCCS Azienda Ospedliero-Universitaria di Bologna Policlinico di Sant'Orsola (IT), Fondazione Michelangelo (IT), Hospital Universitario 12 De Octubre (ES), Institut Català d'Oncologia (ES), St. Elisabeth-Hospital Bochum (DE), National Center for Tumor Diseases (DE), Hospital Universitario Miguel Servet (ES), Ospedale Santa Maria (IT), Institute of Oncology NN Petrov (RU), Azienda USL di Bologna (IT), Augusta-Kranken-Anstalt (DE), Ospedale Santa Maria della Misericordia di Udine (IT), Arcispedale Sant'Anna (IT), China Medical University Hospital (TW), Krankenhaus Bethanien (DE), National Taiwan University Hospital (TW), IRCCS Ospedale San Raffaele (IT), Hospital Universitario HM Sanchinarro (ES), Duran i Reynals Hospital (ES), Tumori Foundation (US), Ospedale Policlinico San Martino (IT), Agaplesion Markus Hospital (DE), Istituti di Ricovero e Cura a Carattere Scientifico (IT), St. James's Hospital (IE), Fondazione IRCCS Istituto Nazionale dei Tumori (IT), Changhua Christian Hospital (TW), Berlin Center for Epidemiology and Health Research (DE), Krankenhaus Köln-Holweide (DE), Russian Scientific Center "Applied Chemistry" (RU), Fondazione Piemontese per la Ricerca sul Cancro Onlus (IT), Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele (IT), European Institute of Oncology (IT), University of Milano-Bicocca (IT), University of Pecs (HU), HUN-REN Research Centre for Natural Sciences (HU)
Breast Cancer Research Foundation, Dipartimenti di Eccellenza, Università degli Studi di Milano-Bicocca, Associazione Italiana per la Ricerca sul Cancro
Good health and well-being
Openalex Percentile: Top 34%
Gene expression and cancer classification
0.47
DOIOpen Access PDFOpenAlex
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