creation-and-maintenance-of-a-living-biobank-how-we-do-it

Creation and Maintenance of a Living Biobank - How We Do It

In light of the growing knowledge about the inter-individual properties and heterogeneity of cancers, the emerging field of personalized medicine requires ...

University Medical Center Rostock

Over the time period from 2006 to 2017, consecutive patients operated on at the University Medical Center Rostock participated in the comprehensive biobanking and tumor-modelling approach known as the HROC collection. Samples were collected using strict standard operating procedures including blood (serum and lymphocytes), tumor tissue (vital and snap frozen), and adjacent normal epithelium. Patient and tumor data including classification, molecular type, clinical outcome, and results of the model establishment are the essential pillars. Overall, 149 patient-derived xenografts with 34 primary and 35 secondary cell lines were successfully established and encompass all colorectal carcinoma anatomic sites, grading and staging types, and molecular classes. The HROC collection represents one of the largest model assortments from consecutive clinical colorectal carcinoma (CRC) cases worldwide. Statistical analysis identified a variety of clinicopathological and molecular factors associated with model success in univariate analysis. Several of them not identified before include localization, mutational status of K-Ras and B-Raf, MSI-status, and grading and staging parameters. In a multivariate analysis model, success solely correlated positively with the nodal status N1 and mutations in the genes K-Ras and B-Raf. These results imply that generating CRC tumor models on the individual patient level is worth considering especially for advanced tumor cases with a dismal prognosis.

Integrated Biobanking and Tumor Model Establishment of Human Colorectal Carcinoma Provides Excellent Tools for Preclinical Research.

To improve and focus preclinical testing, we combine tumor models based on a decellularized tissue matrix with bioinformatics to stratify tumors according to stage-specific mutations that are linked to central cancer pathways. We generated tissue models with -mutant colorectal cancer (CRC) cells (HROC24 and HROC87) and compared treatment responses to two-dimensional (2D) cultures and xenografts. As the BRAF inhibitor vemurafenib is-in contrast to melanoma-not effective in CRC, we combined it with the EGFR inhibitor gefitinib. In general, our 3D models showed higher chemoresistance and in contrast to 2D a more active HGFR after gefitinib and combination-therapy. In xenograft models murine HGF could not activate the human HGFR, stressing the importance of the human microenvironment. In order to stratify patient groups for targeted treatment options in CRC, an in silico topology with different stages including mutations and changes in common signaling pathways was developed. We applied the established topology for in silico simulations to predict new therapeutic options for BRAF-mutated CRC patients in advanced stages. Our in silico tool connects genome information with a deeper understanding of tumor engines in clinically relevant signaling networks which goes beyond the consideration of single drivers to improve CRC patient stratification.

Connecting Cancer Pathways to Tumor Engines: A Stratification Tool for Colorectal Cancer Combining Human In Vitro Tissue Models with Boolean In Silico Models.

Article	Year
Integrated Biobanking and Tumor Model Establishment of Human Colorectal Carcinoma Provides Excellent Tools for Preclinical Research. Cancers\| PubMed ID: 31601052	2019
Connecting Cancer Pathways to Tumor Engines: A Stratification Tool for Colorectal Cancer Combining Human In Vitro Tissue Models with Boolean In Silico Models. Cancers\| PubMed ID: 31861874	2019

Stephanie Matschos

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