Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/36196
Title: Probabilistic graphical models relate immune status with response to neoadjuvant chemotherapy in breast cancer.
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Issue Date: 12-Jun-2018
Citation: Oncotarget.2018 Jun;(9)45:27586-27594
Abstract: 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.
PMID: 29963222
URI: https://hdl.handle.net/20.500.12530/36196
Rights: openAccess
Appears in Collections:Fundaciones e Institutos de Investigación > IIS H. U. La Paz > Artículos
Hospitales > H. U. La Paz > Artículos

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