Prognostic and Predictive Significance of the Immunological Tumor Environment
Dr. Dirk Jäger, Director Medical Oncology, National Center for Tumor Diseases (NCT), University Medical Center Heidelberg, Heidelberg, Germany
The prognostic role of infiltrating T cells has been shown for many tumor entities. We analyzed the predictive significance of T cell infiltrating in patients undergoing chemotherapy. We could show that patients with high density infiltrates at the invasive margin have significant better outcome under chemotherapy, and have significant PFS...
COIN-ing Potential Clinically Translatable Markers in Metastatic Colorectal Cancer Through Tissue Phenomics
Dr. Ryan Hutchinson, Fellow in Molecular Pathology, Department of Pathology, Melbourne and Centre for Translational Pathology, University of Melbourne, Melbourne, Australia
The MRC COIN trial is the largest metastatic colorectal cancer clinical trial carried out to date with the recruitment of 2,445 patients, which investigated whether the addition of cetuximab to standard chemotherapy could benefit patients by increasing lifespan. Conventional EGFR IHC scoring did not indicate any predictive value for treatment...
Improving Therapy-Relevant Breast Cancer Protein Profiling Using Quantitative Immunofluorescence
Dr. Amy Ryder Peck, Senior Research Scientist, Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
Improving clinical management of breast cancer will depend on better molecular characterization of diverse breast cancer subtypes in the context of subtype-responsiveness to therapy. Quantitative immunofluorescent detection of druggable protein targets may facilitate identification of novel therapy-relevant breast cancer subtypes that cannot be discerned by standard pathology methods. High-throughput and...
Applying Tissue Phenomics to Colorectal Clinical Questions
Peter Caie, Senior Research Fellow, University of St. Andrews, Scotland
Surgical resection is considered curative for Dukes B colorectal cancer patients, however 20-30% of patients experience disease recurrence and disease specific death. We aim to stratify Dukes B patients into high and low risk subgroups through novel image based analysis algorithms. Firstly we developed an image analysis algorithm to quantify...
Novel Patient Stratification and Predictive Imaging Biomarkers for Development of Oncology Therapies
Dr. Belma Dogdas, Associate Principal Scientist, Merck, Rahway, New Jersey, USA
In oncology studies, biomarkers have been effectively used to measure tumor progression and to evaluate efficacy of therapies. Increasingly they have been utilized to stratify different patient groups and develop personalized therapeutic strategies. Towards this goal, immunohistochemistry (IHC) has been playing an increasing role in developing imaging biomarkers to help...