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Contains fulltext : 190038.pdf (Publisher’s version ) (Open Access) Background: The increasing sub-classification of cancer patients due to more detailed molecular classification of tumors, and limitations of current trial designs, require innovative research designs. We present the design, governance and current standing of three comprehensive nationwide cohorts including pancreatic, esophageal/gastric, and colorectal cancer patients (NCT02070146). Multidisciplinary collection of clinical data, tumor tissue, blood samples, and patient-reported outcome (PRO) measures with a nationwide coverage, provides the infrastructure for future and novel trial designs and facilitates research to improve outcomes of gastrointestinal cancer patients.Material and methods: All patients aged ≥18 years with pancreatic, esophageal/gastric or colorectal cancer are eligible. Patients provide informed consent for: (1) reuse of clinical data; (2) biobanking of primary tumor tissue; (3) collection of blood samples; (4) to be informed about relevant newly identified genomic aberrations; (5) collection of longitudinal PROs; and (6) to receive information on new interventional studies and possible participation in cohort multiple randomized controlled trials (cmRCT) in the future.Results: In 2015, clinical data of 21,758 newly diagnosed patients were collected in the Netherlands Cancer Registry. Additional clinical data on the surgical procedures were registered in surgical audits for 13,845 patients. Within the first two years, tumor tissue and blood samples were obtained from 1507 patients; during this period, 1180 patients were included in the PRO registry. Response rate for PROs was 90%. The consent rate to receive information on new interventional studies and possible participation in cmRCTs in the future was >85%. The number of hospitals participating in the cohorts is steadily increasing.Conclusion: A comprehensive nationwide multidisciplinary gastrointestinal cancer cohort is feasible and surpasses the limitations of classical study designs. With this initiative, novel and innovative studies can be performed in an efficient, safe, and comprehensive setting. 8 p.

Given the natural history of colorectal and breast cancer, early diagnosis appears to be the most appropriate tool to reduce disease-related mortality.[6;7] Currently, there is no early diagnostic test with high sensitivity, specificity and positive predictive value, which can be used as a routine screening tool. Therefore, there is a need for new biomarkers for both types of cancer that can improve early diagnosis, monitoring of disease progression and therapeutic response and detect disease recurrence. Proteomic expression profiles generated with mass spectrometry have been suggested as potential tools for the early diagnosis of cancer and other diseases. Because it is still in its infancy, many problems have to be overcome before clinical proteomics can be transferred form bench to bedside. Chapter 2 gives an insight in the different fields of translational research in colorectal cancer by our group. In chapter 3 reliability of human serum protein profiling using MALDI-TOF mass spectrometry is analysed. We present a pipeline for pre-processing, statistical data analysis and presentation of MALDI-TOF spectra. This novel analysis method was used to assess the effect of variable pre-analytical conditions on human serum protein profiles, and their effect on reproducibility. In line with the logistic conditions in a routine clinical setting, the effects of sample handling and storage, and also circadian rhythm factors on the serum protein profiles were analysed. In chapter 4 and 5 the feasibility of mass spectrometry based protein profiling for the discrimination of colorectal cancer patients from healthy individuals was assessed. In addition to standardizing technical factors and biological variations, we performed blinded tests and employed a randomised block design experimentation to minimize impact of potential confounding factors and to avoid bias. Especially, validation of our classifier, as a possible pitfall, was given much attention. Therefore, we performed a linear discriminant analysis with double cross-validation to separate cancer patients from healthy subjects. Chapter 6 reports on results from an identical designed protein profiling study for the detection of breast cancer. In chapter 7 a first validated study on the detection of breast cancer based on mass spectrometry generated protein profiles is described. In this study the same randomised blocked design and double cross validation is used, however the classifier was validated in an independent set of new patients and controls. Finally, the results and conclusions of all above mentioned studies and especially the current status of clinical proteomics in cancer are discussed in chapter 8. A Dutch summary of this thesis is written in chapter 9.