Fundacao D. Anna Sommer Champalimaud E Dr. Carlos Montez Champalimaud

Jason Alter

Carlos Cordon-Cardo

Gerardo Fernandez

Michael Donovan

Faisal Khan

Jose Costa

Ricardo Mesa-Tejada

Stefan Hamann

Valentina Bayer Zubek

Douglas Powell

Douglas A Powell

Carlos Cardon-Cardo

Clinical information, molecular information and/or computer-generated morphometric information is used in a predictive model for predicting the occurrence of a medical condition. In an embodiment, a model predicts whether a patient is likely to have a favorable pathological stage of prostate cancer, where the model is based on features including one or more (e.g., all) of preoperative PSA, Gleason Score, a measurement of expression of androgen receptor (AR) in epithelial and stromal nuclei and/or a measurement of expression of Ki67-positive epithelial nuclei, a morphometric measurement of a ratio of area of epithelial nuclei outside gland units to area of epithelial nuclei within gland units, and a morphometric measurement of area of epithelial nuclei distributed away from gland units. In some embodiments, quantitative measurements of protein expression in cell lines are utilized to objectively assess assay (e.g., multiplex immunofluorescence (IF)) performance and/or to normalize features for use within a predictive model.

System for evaluating a pathological stage of prostate cancer

Growing community of inventors

Stamford, CT, United States of America

Jason Alter