Aureon Laboratories, Inc.

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

Stefan Hamann

Michael Donovan

Carlos Cordon-Cardo

Mark Clayton

Gerardo Fernandez

Faisal Khan

Ricardo Mesa-Tejada

Angeliki Kotsianti

Jose Costa

Douglas Powell

Valentina Bayer Zubek

Jason Alter

Douglas A Powell

Michael J Donovan

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

A method of in situ immunohistochemical analysis of a biological sample is provided. The method allows for the multiplex and simultaneous detection of multiple antigens, including multiple nuclear antigens, in a tissue sample.

Multiplex in situ immunohistochemical analysis

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New Rochelle, NY, United States of America

Stefan Hamann