Whole-transcriptome analysis links trastuzumab sensitivity of breast tumors to both HER2 dependence and immune cell infiltration
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Tiziana Triulzi1,*, Loris De Cecco2,*, Marco Sandri1, Aleix Prat3,4, Marta Giussani1, Biagio Paolini5, Marialuisa L. Carcangiu5, Silvana Canevari2, Alberto Bottini6, Andrea Balsari1,7, Sylvie Menard1, Daniele Generali6, Manuela Campiglio1, Serena Di Cosimo8, Elda Tagliabue1
1Department of Experimental Oncology and Molecular Medicine, Molecular Targeting Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
2Department of Experimental Oncology and Molecular Medicine, Functional Genomics Core Facility, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
3Translational Genomics Group, Vall d’Hebron Institute of Oncology, Barcelona, Spain
4Medical Oncology Department, Hospital Clínic i Provincial, Barcelona, Spain
5Department of Pathology, Anatomic Pathology A Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
6Dipartimento di Terapia Molecolare e Farmacogenomica, Istituti Ospitalieri di Cremona, Italy
7Dipartimento di Scienze Biomediche per la Salute, Università degli Studi di Milano, Italy
8Department of Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
*These authors have contributed equally to this work
Tagliabue E, e-mail: [email protected]
Keywords: breast cancer, trastuzumab benefit, gene expression profiling, lymphocytes
Received: April 22, 2015 Accepted: June 19, 2015 Published: July 01, 2015
While results thus far demonstrate the clinical benefit of trastuzumab, some patients do not respond to this therapy. To identify a molecular predictor of trastuzumab benefit, we conducted whole-transcriptome analysis of primary HER2+ breast carcinomas obtained from patients treated with trastuzumab-containing therapies and correlated the molecular portrait with treatment benefit.
The estimated association between gene expression and relapse-free survival allowed development of a trastuzumab risk model (TRAR), with ERBB2 and ESR1 expression as core elements, able to identify patients with high and low risk of relapse. Application of the TRAR model to 24 HER2+ core biopsies from patients treated with neo-adjuvant trastuzumab indicated that it is predictive of trastuzumab response. Examination of TRAR in available whole-transcriptome datasets indicated that this model stratifies patients according to response to trastuzumab-based neo-adjuvant treatment but not to chemotherapy alone. Pathway analysis revealed that TRAR-low tumors expressed genes of the immune response, with higher numbers of CD8-positive cells detected immunohistochemically compared to TRAR-high tumors.
The TRAR model identifies tumors that benefit from trastuzumab-based treatment as those most enriched in CD8-positive immune infiltrating cells and with high ERBB2 and low ESR1 mRNA levels, indicating the requirement for both features in achieving trastuzumab response.
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