HROC348Met Cells

HROC348Met is a human colorectal carcinoma cell line established from a metachronous liver metastasis of a colorectal adenocarcinoma resected from an adult patient within the HROC (Hansestadt Rostock Colorectal Cancer) model collection. The HROC platform was generated through a standardized biobanking and tumor-modeling pipeline integrating clinical annotation, molecular characterization, patient-derived xenografts (PDX), and corresponding in vitro cultures. HROC348Met represents one of the metastatic models derived from surgically resected colorectal cancer tissue and was established under low-passage conditions to preserve tumor-specific biological features.

Within the HROC collection, metastatic specimens – particularly liver metastases – demonstrated a high engraftment efficiency in immunodeficient mice, with an overall PDX take rate of approximately 68% across the cohort, and even higher success for metastatic compared to primary tumors. Multivariate analyses identified nodal involvement and activating mutations in KRAS and BRAF as independent predictors of successful model establishment. The collection encompasses all major molecular subtypes of colorectal carcinoma, including chromosomal instability (CIN), CpG island methylator phenotype (CIMP), microsatellite stable (MSS), and microsatellite instability-high (MSI-H) tumors, ensuring molecular representativeness of advanced-stage disease. HROC348Met was established within this rigorously characterized framework, with clinicopathological and molecular annotation according to standardized protocols.

As a metastasis-derived, low-passage colorectal carcinoma model, HROC348Met is suitable for investigations of metastatic tumor biology, genotype-phenotype correlations, and therapeutic response testing in both 2D culture and in vivo PDX settings. The integrated biobank approach underlying its generation ensures availability of matched clinical data and, where applicable, corresponding xenograft material, enabling translational studies in precision oncology and drug-response prediction.