Research Papers: Immunology:

Probabilistic graphical models relate immune status with response to neoadjuvant chemotherapy in breast cancer

Andrea Zapater-Moros, Angelo Gámez-Pozo, Guillermo Prado-Vázquez, Lucía Trilla-Fuertes, Jorge M. Arevalillo, Mariana Díaz-Almirón, Hilario Navarro, Paloma Maín, Jaime Feliú, Pilar Zamora, Enrique Espinosa and Juan Ángel Fresno Vara _

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Oncotarget. 2018; 9:27586-27594. https://doi.org/10.18632/oncotarget.25496

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Andrea Zapater-Moros1, Angelo Gámez-Pozo1,2, Guillermo Prado-Vázquez1, Lucía Trilla-Fuertes2, Jorge M. Arevalillo3, Mariana Díaz-Almirón4, Hilario Navarro3, Paloma Maín5, Jaime Feliú6,7, Pilar Zamora6, Enrique Espinosa6,7 and Juan Ángel Fresno Vara1,2,7

1 Molecular Oncology & Pathology Laboratory, Institute of Medical and Molecular Genetics-INGEMM, La Paz University Hospital-IdiPAZ, Madrid, Spain

2 Biomedica Molecular Medicine SL, Madrid, Spain

3 Operational Research and Numerical Analysis, National Distance Education University (UNED), Madrid, Spain

4 Biostatistics Unit, La Paz University Hospital-IdiPAZ, Madrid, Spain

5 Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, Madrid, Spain

6 Medical Oncology Service, La Paz University Hospital-IdiPAZ, Madrid, Spain

7 CIBERONC, Madrid, Spain

Correspondence to:

Juan Ángel Fresno Vara, email: [email protected]

Keywords: breast cancer; neoadjuvant chemotherapy; molecular subtypes; probabilistic graphical models; immune status; Immunology

Received: December 21, 2017    Accepted: May 08, 2018    Published: June 12, 2018


Breast cancer is the most frequent tumor in women and its incidence is increasing. Neoadjuvant chemotherapy has become standard of care as a complement to surgery in locally advanced or poor-prognosis early stage disease. The achievement of a complete response to neoadjuvant chemotherapy correlates with prognosis but it is not possible to predict who will obtain an excellent response. The molecular analysis of the tumor offers a unique opportunity to unveil predictive factors. In this work, gene expression profiling in 279 tumor samples from patients receiving neoadjuvant chemotherapy was performed and probabilistic graphical models were used. This approach enables addressing biological and clinical questions from a Systems Biology perspective, allowing to deal with large gene expression data and their interactions. Tumors presenting complete response to neoadjuvant chemotherapy had a higher activity of immune related functions compared to resistant tumors. Similarly, samples from complete responders presented higher expression of lymphocyte cell lineage markers, immune-activating and immune-suppressive markers, which may correlate with tumor infiltration by lymphocytes (TILs). These results suggest that the patient’s immune system plays a key role in tumor response to neoadjuvant treatment. However, future studies with larger cohorts are necessary to validate these hypotheses.

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