Clinical diagnostic research relies upon the collection of tissue samples, and for those samples to be representative of the in vivo situation. Tissue collection procedures, including post-operative ischemia, can impact the molecular profile of the tissue at the genetic and proteomic level. Understanding the influence of factors such as ischemia on tissue samples is imperative in order to develop both markers of tissue quality and ultimately accurate diagnostic tests. Using NanoPro1000 technology, a rapid and highly sensitive immunoassay platform, the phosphorylation status of clinically relevant cancer-related biomarkers in response to ischemia was quantified in tissue samples from 20 patients with primary colorectal cancer. Tumor tissue and adjacent normal tissue samples were collected and subjected to cold ischemia prior to nanoproteomic analysis of AKT, ERK1/2, MEK1/2, and c-MET. Ischemia-induced relative changes in overall phosphorylation and phosphorylation of individual isoforms were calculated and statistical significance determined. Any differences in baseline levels of phosphorylation between tumor tissue and normal tissue were also analyzed. Changes in overall phosphorylation of the selected proteins in response to ischemia revealed minor variations in both normal and tumor tissue; however, significant changes were identified in the phosphorylation of individual isoforms. In normal tissue post-operative ischemia, phosphorylation was increased in two AKT isoforms, two ERK1/2 isoforms, and one MEK1/2 isoform and decreased in one MEK1/2 isoform and one c-MET isoform. Following ischemia in tumor tissue, one AKT isoform showed decreased phosphorylation and there was an overall increase in unphosphorylated ERK1/2, whereas an increase in the phosphorylation of two MEK1/2 isoforms was observed. There were no changes in c-MET phosphorylation in tumor tissue. This study provides insight into the influence of post-operative ischemia on tissue sample biology, which may inform the future development of markers of tissue quality and assist in the development of diagnostic tests.

Background: In retrospective studies, loss of p27^Kip1 (p27), a cyclin-dependent kinase inhibitor, has been associated with poor prognosis following colorectal cancer treatment. In a prospective study, we validated this relationship in patients enrolled on a trial of adjuvant chemotherapy for stage III colon cancer. Methods: Cancer and Leukemia Group B protocol 89803 randomized 1,264 stage III colon cancer patients to receive weekly bolus 5-fluorouracil/leucovorin or weekly bolus irinotecan, 5-fluorouracil, and leucovorin (IFL). The primary endpoint was overall survival (OS); disease-free survival was a secondary endpoint. Expression of p27 and DNA mismatch repair proteins were determined by immunohistochemistry in primary tumor and normal tissue from paraffin blocks. Data were analyzed using log-rank test. Results: Of 601 tumors analyzed, 207 (34.4%) showed p27 loss, 377 (62.8%) retained p27, and 17 (2.8%) were indeterminate. Patients with p27-negative tumors showed reduced OS [5-year OS 66%: 95% confidence interval (95% CI), 0.59-0.72 versus 75%: 95% CI, 0.70-0.79; log-rank P = 0.021]. This relationship was not influenced by treatment arm. Combination of p27 status with mismatch repair status, however, identified a small subset of patients that may benefit from IFL (n = 36; 5-year disease-free survival 81%: 95% CI, 0.64-0.98 versus 47%: 95% CI, 0.21-0.72; log-rank P = 0.042; 5-year OS 81%: 95% CI, 0.64-0.98 versus 60%: 95% CI, 0.35-0.85; log-rank P = 0.128). Conclusions: Loss of p27 is associated with reduced survival in stage III colon cancer but by itself does not indicate a significant difference in outcome between patients treated IFL or 5-fluorouracil/leucovorin.

BLOODPAC is a public‐private consortium that develops best practices, coordinates clinical and translational research, and manages the BLOODPAC Data Commons to broadly support the liquid biopsy community and accelerate regulatory review to aid patient accessibility. BLOODPAC previously recommended 11 preanalytical minimal technical data elements (MTDEs) for BLOODPAC‐sponsored studies and data submitted to BLOODPAC Data Commons. The current landscape analysis evaluates the overlap of the BLOODPAC MTDEs with current best practices, guidelines, and standards documents related to clinical and research liquid biopsy applications. Our findings indicate an existing high degree of concordance among these documents. Where differences exist, the BLOODPAC preanalytical MTDEs can be considered a minimal practicable set for organizations to utilize. These MTDEs were developed following extensive examination of best practices and iterative conversations with the U.S. FDA. BLOODPAC recommends the use of these MTDEs in submissions to data commons and to support liquid biopsy clinical trials and research globally.

Scottsdale, Arizona ''Prediction is very difficult, especially if it's about the future.'' Niels Bohr (1885-1962), Theoretical Physicist and Nobel Laureate Prognostication is fundamental to the practice of medicine. For the patient, it goes to the heart of their primary concern. What will happen to me? How likely am I to survive or die? For the physician, it shapes decision making and management strategy. For others, such as translational researchers, population scientists, payors, and healthcare analysts, it helps to classify patients into meaningful groups for comparison. Despite its essential role, prognostication is one of the most challenging tasks in cancer medicine. The complexity of prognostication is directly related to the complex biological nature of both cancer itself and the individual patient in which it arises. It is further complicated by man-made prognostic factors referable to the medical environment in which the patient is managed and the medical teams administering the care. Like all biological entities, cancer is classified as a complex adaptive system, characterized by unpredictable behavior and the emergence of new properties as it evolves. It is comprised of innumerable parts but is also more than the sum of its parts. Given these daunting realities about the very nature of cancer, it could be argued that accurate predictions of outcome are impossible. At present, this may be true. However, like forecasting the weather, another complex adaptive system, predictive accuracy can be improved by advanced data collection techniques, information science, and analytical innovation. We are moving forward on all