Improving upon the Gleason score from biopsy in prostate cancer prognostic algorithms: An injection of computational pathology.

Department of Health and Human Services, National Institutes of Health, National Cancer Institute, Office of Acquisitions, 9609 Medical Center Drive, Room 1E144, Rockville, MD 20850, UNITED STATES The National Cancer Institute (NCI), Division of Cancer Epidemiology and Genetics (DCEG), Metabolic Epidemiology Branch (MEB) plans to procure, on a sole source basis, the use of hematoxylin and eosin (H&E) stained tissues located at the Mayo Clinic, 200 First Street SW Rochester, MN 55905. This acquisition will be processed under FAR Part 12 - Acquisition for Commercial Items and will be made pursuant to the authority in FAR 13.106-1 (b)(2) and 13.501-(a)(1) using simplified acquisition procedures for commercial acquisitionist. The North American Industry Classification System code is 541380 and the business size standard is $15M. It has been determined there are no opportunities to acquire green products or services for this procurement. Current prognostic algorithms for prostate cancer progression have areas under the receiver operating characteristic curve (AUCs) of ~0.70. These values indicate moderate-to-good prediction for the likelihood of disease progression but remain limited in their ability to identify a substantial proportion of patients who may be at risk of disease recurrence or death. Gleason grade is an essential component of these prognostic algorithms and remains the most important predictive tool for prostate cancer prognosis. Nevertheless, roughly 15-35% of patients with - favorable' Gleason grades experience disease recurrence within ten years of initial treatment. If prediction algorithms for prostate cancer recurrence can be improved, surveillance and treatment decisions could be refined to benefit patient outcomes. In this study, DCEG hypothesizes that novel components of the prostate tumor architecture can be used to supplement Gleason grade and improve existing prognostic algorithms. The burgeoning area of large-scale automated pathology holds great promise for elucidating morphologic features with prognostic value. By combining automated pathology combined with machine learning-based methods, findings from this study may be able to supplement current pathology review practices by identifying new clinically predictive, morphological features that can be objectively scored with high consistency. DCEG seeks to acquire hematoxylin and eosin (H&E) stained prostate cancer tissues located at the Mayo Clinic. The tissues of interest arise from a cohort of men diagnosed with early-to-intermediate stage prostate cancer between 1992 and 2012. The Mayo Clinic is well versed in the clinical management of the men included in the cohort and has established expertise in the field of prostate cancer prognostication through the identification of biomarkers linked to prostate cancer progression and survival. DCEG will have access to prostate cancer biopsies for 200 subjects who progressed or died from their disease and will be able to match these to 200 subjects who did not progress given a similar diagnosis. In addition, DCEG will have access to radical prostatectomy specimens from 645 subjects who subsequently experienced systemic progression or prostate cancer death and will be able to match these to 645 similar subjects who did not progress. The Mayo Clinic is uniquely qualified to provide prostate cancer tissues of cases with sufficient follow-up to identify morphologic features linked to prostate cancer progression and will also serve as a collaborator whose extent of knowledge will aid in the interpretation of morphologic features linked to progression. There are no other known resources to which DCEG can access prostate tumor tissues with the breadth of associated clinical data, follow-up, and collaborator expertise. Further, the sample size is suitable for epidemiologic analysis (n=1,690) and provides the statistical power for the proposed study. This notice is not a request for competitive quotation. However, if any interested party, especially small business believes it can meet the above requirement, it may submit a proposal or quote for the Government to consider. The response and any other information furnished must be in writing and must contain material in sufficient detail to allow NCI to determine if the party can perform the requirement. Responses must be received in the contracting office by 3:00 PM ET, on August 3, 2018. All responses and questions must be via email to Miguel Diaz, Contracting Officer at contact@example.gov. A determination by the Government not to compete this proposed requirement based upon responses to this notice is solely within the discretion of the Government. Information received will be considered solely for the purpose of determining whether to conduct a competitive procurement. In order to receive an award, contractors must be registered and have valid certification through SAM.GOV and have Representations and Certifications filled out. Reference: N02RC85020-45 on all correspondence.