This Shared Instrumentation Grant proposal is focused on the acquisition of the VectraTM and inFormTM automated image analysis system to support projects in the Dan L. Duncan Cancer Center at Baylor College of Medicine. This microscope, camera and software system permits automated and quantitative imaging of either slide sets (up to 200) or tissue arrays. Camera and software permits segment quantitation of both fluorescent and visible light range colors that allows for quantitative analysis of multiple color markers on a per cell or per tissue field basis. Software is trainable to allow for maximum flexibility. Initial use of this instrumentation will greatly benefit the SPORE in Prostate Cancer, the U54 Tumor Microenvironment Project, the U01 Mouse Models of Human Cancer Consortium Project and two R01 projects. The instrumentation will be available to Cancer Center members outside the Prostate Research Program and other faculty at Baylor College of Medicine. The immediate objectives of this Shared Instrumentation project is to utilize the multiple modalities of this instrument to provide reliable and automated quantitative image analysis of multiple biomarkers at the cellular level using large tissue arrays or slide samples. This quantitative data cannot be accurately and reasonably acquired using any other methodology. We believe that this instrument will provide data that will essentially revolutionize biomarker research. One of the broad objectives of the Dan L. Duncan Cancer Center is to provide better cancer care through new discovery that involves both prognostic indicators and new therapeutic approaches. This instrumentation system will be used by many investigators on several different projects that are each evaluating biomarkers for cancer progression in both the primary cancer cells and in the tumor microenvironment. The team of investigators has collaborated for many years with an excellent track record of publications in biomarker research and defining the tumor microenvironment. The requested instrumentation is state of the art and will permit the acquisition of data that would not otherwise be possible. We fully anticipate this data will extend the field of cancer and tumor microenvironment research in new directions and will evolve into key findings that will translate to more clear understandings of disease processes, better prognostics, and improved health care delivery.
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