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Alvarez-Frutos L, Barriuso D, Duran M, Infante M, Kroemer G, Palacios-Ramirez R, Senovilla L. Multiomics insights on the onset, progression, and metastatic evolution of breast cancer. Front Oncol 2023; 13:1292046. [PMID: 38169859 PMCID: PMC10758476 DOI: 10.3389/fonc.2023.1292046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 11/23/2023] [Indexed: 01/05/2024] Open
Abstract
Breast cancer is the most common malignant neoplasm in women. Despite progress to date, 700,000 women worldwide died of this disease in 2020. Apparently, the prognostic markers currently used in the clinic are not sufficient to determine the most appropriate treatment. For this reason, great efforts have been made in recent years to identify new molecular biomarkers that will allow more precise and personalized therapeutic decisions in both primary and recurrent breast cancers. These molecular biomarkers include genetic and post-transcriptional alterations, changes in protein expression, as well as metabolic, immunological or microbial changes identified by multiple omics technologies (e.g., genomics, epigenomics, transcriptomics, proteomics, glycomics, metabolomics, lipidomics, immunomics and microbiomics). This review summarizes studies based on omics analysis that have identified new biomarkers for diagnosis, patient stratification, differentiation between stages of tumor development (initiation, progression, and metastasis/recurrence), and their relevance for treatment selection. Furthermore, this review highlights the importance of clinical trials based on multiomics studies and the need to advance in this direction in order to establish personalized therapies and prolong disease-free survival of these patients in the future.
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Affiliation(s)
- Lucia Alvarez-Frutos
- Laboratory of Cell Stress and Immunosurveillance, Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid – Centro Superior de Investigaciones Cientificas (CSIC), Valladolid, Spain
| | - Daniel Barriuso
- Laboratory of Cell Stress and Immunosurveillance, Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid – Centro Superior de Investigaciones Cientificas (CSIC), Valladolid, Spain
| | - Mercedes Duran
- Laboratory of Molecular Genetics of Hereditary Cancer, Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid – Centro Superior de Investigaciones Cientificas (CSIC), Valladolid, Spain
| | - Mar Infante
- Laboratory of Molecular Genetics of Hereditary Cancer, Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid – Centro Superior de Investigaciones Cientificas (CSIC), Valladolid, Spain
| | - Guido Kroemer
- Centre de Recherche des Cordeliers, Equipe labellisée par la Ligue contre le cancer, Université Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France
- Metabolomics and Cell Biology Platforms, Institut Gustave Roussy, Villejuif, France
- Department of Biology, Institut du Cancer Paris CARPEM, Hôpital Européen Georges Pompidou, Paris, France
| | - Roberto Palacios-Ramirez
- Laboratory of Cell Stress and Immunosurveillance, Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid – Centro Superior de Investigaciones Cientificas (CSIC), Valladolid, Spain
| | - Laura Senovilla
- Laboratory of Cell Stress and Immunosurveillance, Unidad de Excelencia Instituto de Biomedicina y Genética Molecular (IBGM), Universidad de Valladolid – Centro Superior de Investigaciones Cientificas (CSIC), Valladolid, Spain
- Centre de Recherche des Cordeliers, Equipe labellisée par la Ligue contre le cancer, Université Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France
- Metabolomics and Cell Biology Platforms, Institut Gustave Roussy, Villejuif, France
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Vliek SB, Hilbers FS, Jager A, Retèl VP, Bueno de Mesquita JM, Drukker CA, Veltkamp SC, Zeillemaker AM, Rutgers EJ, van Tinteren H, van Harten WH, van 't Veer LJ, van de Vijver MJ, Linn SC. Ten-year follow-up of the observational RASTER study, prospective evaluation of the 70-gene signature in ER-positive, HER2-negative, node-negative, early breast cancer. Eur J Cancer 2022; 175:169-179. [PMID: 36126477 DOI: 10.1016/j.ejca.2022.07.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Prognostic gene expression signatures can be used in combination with classical clinicopathological factors to guide adjuvant chemotherapy decisions in ER-positive, HER2-negative breast cancer. However, long-term outcome data after introduction of genomic testing in the treatment decision-making process are limited. METHODS In the prospective RASTER study, the tumours of 427 patients with cTanyN0M0 breast cancer were tested to assess the 70-gene signature (MammaPrint). The results were provided to their treating physician to be incorporated in the decision-making on adjuvant systemic therapy. Here, we report the long-term outcome of the 310 patients with ER-positive, HER2-negative tumours by clinical and genomic risk categories at a median follow-up of 10.3 years. RESULTS Among the clinically high-risk patients, 45 (49%) were classified as genomically low risk. In this subgroup, at 10 years, distant recurrence free interval (DRFI) was similar between patients treated with (95.7% [95% CI 87.7-100]) and without (95.5% [95% CI 87.1-100]) chemotherapy. Within the group of clinically low-risk patients, 56 (26%) were classified as genomically high risk. Within the clinically low-risk group, beyond 5 years, a difference emerged between the genomically high- and low-risk subgroup resulting in a 10-year DRFI of 84.3% (95% CI 74.8-95.0) and 93.4% (95% CI 89.5-97.5), respectively. Interestingly, genomic ultralow-risk patients have a 10-year DRFI of 96.7% (95% CI 90.5-100), largely (79%) without systemic therapy. CONCLUSIONS These data confirm that clinically high-risk, genomically low-risk tumours have an excellent outcome in the real-world setting of shared decision-making. Together with the updated results of the MINDACT trial, these data support the use of the MammaPrint, in ER-positive, HER2-negative, node-negative, clinically high-risk breast cancer patients. REGISTRY ISRCTN71917916.
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Affiliation(s)
- Sonja B Vliek
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Florentine S Hilbers
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Agnes Jager
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
| | - Valesca P Retèl
- Departmentment of Psycosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Health Technology and Services Research, University of Twente, Enschede, the Netherlands
| | - Jolien M Bueno de Mesquita
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Addiction Medicin & Psychiatry, Brijder/Parnassia Group, The Hague, the Netherlands
| | - Caroline A Drukker
- Department of Surgical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Sanne C Veltkamp
- Department of Surgery, Amstelland Ziekenhuis, Amstelveen, the Netherlands
| | - Anneke M Zeillemaker
- Department of Surgical Oncology, Alrijne Ziekenhuis, Leiderdorp, the Netherlands
| | - Emiel J Rutgers
- Department of Surgical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Harm van Tinteren
- Department of Biometrics, The Netherlands Cancer Institute, Amsterdam, Netherlands; Trial and Data Center, Princes Maxima Centrum, Utrecht, the Netherlands
| | - Wim H van Harten
- Departmentment of Psycosocial Research and Epidemiology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Health Technology and Services Research, University of Twente, Enschede, the Netherlands
| | - Laura J van 't Veer
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, USA
| | - Marc J van de Vijver
- Department of Pathology, Amsterdam University Medical Centers, Amsterdam, the Netherlands
| | - Sabine C Linn
- Department of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Medical Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands.
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