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Closing the gap: prognostic and predictive biomarker validation for personalized care in a Latin American hormone-dependent breast cancer cohort.
Alves da Quinta, Daniela; Rocha, Darío; Retamales, Javier; Giunta, Diego; Artagaveytia, Nora; Velazquez, Carlos; Daneri-Navarro, Adrian; Müller, Bettina; Abdelhay, Eliana; Bravo, Alicia I; Castro, Mónica; Rosales, Cristina; Alcoba, Elsa; Acosta Haab, Gabriela; Carrizo, Fernando; Sorin, Irene; Di Sibio, Alejandro; Marques-Silveira, Márcia; Binato, Renata; Caserta, Benedicta; Greif, Gonzalo; Del Toro-Arreola, Alicia; Quintero-Ramos, Antonio; Gómez, Jorge; Podhajcer, Osvaldo L; Fernández, Elmer A; Llera, Andrea S.
Afiliación
  • Alves da Quinta D; Laboratorio de Terapia Molecular y Celular, Fundación Instituto Leloir-CONICET, Ciudad de Buenos Aires, Argentina.
  • Rocha D; Universidad Argentina de la Empresa (UADE), Instituto de Tecnología (INTEC), Buenos Aires, Argentina.
  • Retamales J; Universidad Nacional de Córdoba, Facultad de Ciencias Exactas, Físicas y Naturales, Córdoba, Argentina.
  • Giunta D; Grupo Oncológico Cooperativo Chileno de Investigación, Santiago de Chile, Chile.
  • Artagaveytia N; Instituto Universitario Hospital Italiano de Buenos Aires-CONICET, Buenos Aires, Argentina.
  • Velazquez C; Hospital de Clínicas Manuel Quintela, Universidad de la República, Montevideo, Uruguay.
  • Daneri-Navarro A; Universidad de Sonora, Hermosillo, Mexico.
  • Müller B; Universidad de Guadalajara, Guadalajara, Mexico.
  • Abdelhay E; Instituto Nacional del Cáncer, Santiago de Chile, Chile.
  • Bravo AI; Bone Marrow Transplantation Unit, Instituto Nacional de Câncer, Rio de Janeiro, RJ, Brazil.
  • Castro M; Hospital Regional de Agudos Eva Perón, San Martín, Provincia de Buenos Aires, Argentina.
  • Rosales C; Instituto de Oncología Angel Roffo, Ciudad de Buenos Aires, Argentina.
  • Alcoba E; Hospital Municipal de Oncología María Curie, Ciudad de Buenos Aires, Argentina.
  • Acosta Haab G; Hospital Municipal de Oncología María Curie, Ciudad de Buenos Aires, Argentina.
  • Carrizo F; Hospital Municipal de Oncología María Curie, Ciudad de Buenos Aires, Argentina.
  • Sorin I; Hospital Regional de Agudos Eva Perón, San Martín, Provincia de Buenos Aires, Argentina.
  • Di Sibio A; Bone Marrow Transplantation Unit, Instituto Nacional de Câncer, Rio de Janeiro, RJ, Brazil.
  • Marques-Silveira M; Hospital General de Agudos "Dr.Cosme Argerich", Buenos Aires, Argentina.
  • Binato R; Molecular Oncology Research Center, Hospital do Câncer de Barretos, Barretos, Brazil.
  • Caserta B; Bone Marrow Transplantation Unit, Instituto Nacional de Câncer, Rio de Janeiro, RJ, Brazil.
  • Greif G; Department of Pathology, Centro Hospitalario Pereira Rossell, Montevideo, Uruguay.
  • Del Toro-Arreola A; Institut Pasteur de Montevideo, Montevideo, Uruguay.
  • Quintero-Ramos A; Universidad de Guadalajara, Guadalajara, Mexico.
  • Gómez J; Universidad de Guadalajara, Guadalajara, Mexico.
  • Podhajcer OL; Health Sciences Center, Texas A&M University, Bryan, TX 77807, United States.
  • Fernández EA; Laboratorio de Terapia Molecular y Celular, Fundación Instituto Leloir-CONICET, Ciudad de Buenos Aires, Argentina.
  • Llera AS; CONICET, Córdoba, Argentina.
Oncologist ; 2024 Aug 08.
Article en En | MEDLINE | ID: mdl-39115892
ABSTRACT

BACKGROUND:

Several guidelines recommend the use of different classifiers to determine the risk of recurrence (ROR) and treatment decisions in patients with HR+HER2- breast cancer. However, data are still lacking for their usefulness in Latin American (LA) patients. Our aim was to evaluate the comparative prognostic and predictive performance of different ROR classifiers in a real-world LA cohort.

METHODS:

The Molecular Profile of Breast Cancer Study (MPBCS) is an LA case-cohort study with 5-year follow-up. Stages I and II, clinically node-negative HR+HER2- patients (n = 340) who received adjuvant hormone therapy and/or chemotherapy, were analyzed. Time-dependent receiver-operator characteristic-area under the curve, univariate and multivariate Cox proportional hazards regression (CPHR) models were used to compare the prognostic performance of several risk biomarkers. Multivariate CPHR with interaction models tested the predictive ability of selected risk classifiers.

RESULTS:

Within this cohort, transcriptomic-based classifiers such as the recurrence score (RS), EndoPredict (EP risk and EPClin), and PAM50-risk of recurrence scores (ROR-S and ROR-PC) presented better prognostic performances for node-negative patients (univariate C-index 0.61-0.68, adjusted C-index 0.77-0.80, adjusted hazard ratios [HR] between high and low risk 4.06-9.97) than the traditional classifiers Ki67 and Nottingham Prognostic Index (univariate C-index 0.53-0.59, adjusted C-index 0.72-0.75, and adjusted HR 1.85-2.54). RS (and to some extent, EndoPredict) also showed predictive capacity for chemotherapy benefit in node-negative patients (interaction P = .0200 and .0510, respectively).

CONCLUSION:

In summary, we could prove the clinical validity of most transcriptomic-based risk classifiers and their superiority over clinical and immunohistochemical-based methods in the heterogenous, real-world node-negative HR+HER2- MPBCS cohort.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Oncologist Asunto de la revista: NEOPLASIAS Año: 2024 Tipo del documento: Article País de afiliación: Argentina

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Oncologist Asunto de la revista: NEOPLASIAS Año: 2024 Tipo del documento: Article País de afiliación: Argentina