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Pathology

Colorectal and gastric cancer

Secondary prevention of gastrointestinal cancer

Colorectal cancer (CRC) is the second leading cause of cancer death in the western world with over 4200 deaths per year in the Netherlands. Secondary prevention is the most realistic approach for reducing this high number of colorectal cancer deaths. At present, options for secondary prevention include immunological fecal occult blood testing (FIT) and endoscopic screening. FIT is easy and well tolerated, but has a low sensitivity and specificity. Therefore, a need exists for more sensitive and specific CRC tests, using molecular (DNA, RNA or protein) biomarkers. Understanding the molecular pathology of CRC is crucial to unravel candidate biomarkers. Candidate diagnostic biomarkers have been and are being identified based on two complementary approaches, i.e. tumor profiling studies of large collections of clinically well-characterized tumor samples, and functional analysis of the effects of candidate biomarkers on tumor biology. To this end it is investigated whether promoter methylation, DNA copy number status, miRNA profiling, and protein detection can be used as a molecular test in CRC population screening.
Endoscopic screening has a ±90% sensitivity for detecting adenomas (the precursors of colorectal cancer), but since only 5% of all adenomas ever progress to cancer, endoscopy has a low specificity in terms of cancer prevention. Moreover, colonoscopy is a burdensome procedure for screenees. Therefore, a need exists for more specific, non-invasive imaging of CRC. Molecular imaging by MRI is a promising, non-invasive technique to gain molecular information about colon tumors. To this end, we aim to identify imageable biomarkers for progressive adenomas and CRCs.

Tumor profiling of gastrointestinal (i.e. gastric & colorectal) cancer

Gastrointestinal cancer causes >25% of cancer death in the western world, with death rates of 50% (colorectal cancer) to 80-90% (gastric and esophageal cancer). Once cancer has been diagnosed, standard surgical and medical oncological therapy regimens are followed. For both gastric and colorectal cancer we and others have demonstrated the existence of substantial genomic variation, which correlates to clinical outcome. Yet, the standard therapy regimens mentioned above largely neglect the existence and relevance of this genomic variation.
The aim of our program is to improve outcome of gastrointestinal cancer by stratification of GI cancer patients based on tumor profiles for optimized therapy selection.
(I) Gastric cancer
For long, surgery has been the main treatment of gastric cancer, but new systemic therapies are being introduced. Up until now the type of treatment largely depends on the stage of the disease. However, our group has recently shown that gastric carcinomas are heterogeneous in their molecular profiles depending on many patient and tumor characteristics. These differences could explain why only approximately 30% of patients respond to chemotherapy.
(II) Colorectal cancer (CRC).
CRC biologically is a heterogeneous disease, and therefore prognosis and response to chemotherapy are highly variable. Nevertheless, most patients are treated empirically with regimens containing (oral) 5-fluorouracil (5FU) formulations, usually combined with oxaliplatin or irinotecan, while novel targeted therapies containing e.g. cetuximab or bevacizumab will be implemented shortly. For several biological factors like microsatellite instability (MSI) and a number of chromosomal aberrations, like loss of 18q and gain of 20q, an association with response to chemotherapy or prognosis has been determined, which includes work of our own group.

Genomics from technique to therapy

Research within the Micro Array (MA) facility at VUMC focuses on the development of genomic techniques for implementation in research, prognostic and diagnostics of diseases. We aid in the implementation from technique to therapy. Thereby we primarily focus on cancer and but also hereditary, inflammatory and communicable diseases. Chromosomal copy numbers are a hall mark of cancer and bear much specificity. We stratify patients based on these copy numbers, by embryological origin, patient prognosis and therapy.
The aim of our research is personalized therapy through genomic stratification. We develop, implement and provide the technologies, equipment and data-analysis infrastructure for personalized therapy through genomics, whilst disseminating our progress through (scientific) publications, conferences and (online) media.
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ICT infrastructure for translational research

The Translational Research Working Group of the NIH defines Translational Research in the following way: "Translational research transforms scientific discoveries arising from laboratory, clinical, or population studies into clinical applications to reduce cancer incidence, morbidity, and mortality."
Large scale translational research projects like CTMM DeCoDe require substantial efforts in data and biobanking, starting with standardized collection and storage protocols for biosamples and clinical data down to data handling and analysis. To this end appropriate physical and ICT infrastructure needs to be put into place using proven technology according to best industrial practices. This will facilitate massive cross talk between the different research projects and will lead to comprehensive utilization of findings generated within the research projects.
We initiated the CTMM TraIT (Translational research IT) project aiming at the development of a long-lasting IT infrastructure for translational medicine that will facilitate the collection, storage, analysis, archiving, sharing and securing of the data generated in the CTMM's operational translational research projects. The TraIT project will build on existing expertise to create an IT infrastructure that will help to accelerate the translational research in the Dutch Life Sciences and Health sector. A research environment will be created to expedite new discoveries and innovations to improve the medical care for patients. The TraIT project is a joint initiative between CTMM, Dutch Cancer Society, Dutch Heart Foundation, the Netherlands Federation of University Medical Centers (NFU), the Netherlands Bioinformatics Centre (NBIC), the String of Pearls Initiative (PSI) and the Netherlands eScience Center (NLeSC).

Digital microscopy

Histology is the backbone of oncology and many other areas of biomedical research. Yet, standard histopathological evaluation still implies subjective and time consuming assessment of microscopic slides. At the same time, biomedical research is witnessing a revolution in high throughput functional assays (e.g. siRNA libraries, rescue screens) and molecular biology (expression microarrays, arrayCGH, proteomics). Before the results of these efforts can be translated into clinical applications, confirmation of these findings in human tumour and other tissues, frequently by immunohistochemistry and in situ hybridization, is mandatory. To facilitate this and to keep in pace with the high throughput methods mentioned above, an up scaling of technology in the pathology research lab is required. The aim of our program is the implementation and/or development of image processing algorithms and applications (with an emphasis on tissue micro array (TMA) image analysis) that will assist pathologists and biologists in obtaining quantitative information from microscopic images for making objective diagnostic, prognostic and therapeutic decisions, and to integrate this with the bioinformatics infrastructure of other (high throughput) research facilities on the campus like the microarray and proteomics core facilities.