Translational tumor research laboratory
Publications in PubMed (Knösel T)
Interests:
Gastrointestinal Pathology
Soft tissue tumors
Translational tumor research
From Biomarkers to distinct subgroups
Methods:
-TMAs (Tissue Micro Arrays)
-Evaluation of Biomarkers
-Protein Level (Immunohistochemistry)
-DNA Level (FISH)
-RNA Level (RNA in situ hybridisation)
-Mutational analysis
-Cell culture
Chromosomal signatures and immunoprofiles in tumor progression of colorectal carcinomas
Aims: Metastasis is responsible for most cancer deaths. It represents the essential step during cancer progression from a locally growing tumor to a metastatic killer.
Methods: To provide cytogenetic and immunohistological (IHC) data in colorectal carcinomas (CRC) we investigated 85 tumor specimens with Comparative Genomic Hybridization (CGH), 36 primary tumors, metastasis from the lung (n=13), liver (n=13), lymph nodes (n=12), brain (n=6), abdominal wall (n=4) and ovary (n=1). Furthermore, 6721 specimens of CRC were analyzed with IHC by the synergy of TMAs and unsupervised hierarchical clustering.
Results: In general, hematogenous metastases showed more alterations than lymph node metastases, particularly more deletions at 1p, 3, 4, 5q, 10q, 14 and 21q2 and gains at 1q, 7p, 12qter, 13, 16 and 22q. Additionally liver and lung metastases showed distinct signatures, particularly lung metastases gains on 2q, 5p and losses at 1p, 3p, 8p, 9q, 12q, 17q, 19p, 21q21 and 22q. Furthermore we show that unsupervised hierarchical clustering of the IHC data identified specific diagnostic and prognostic subgroups.
Conclusions: Based our results we wish to suggest a metastatic progression model. Specific sub-populations of metastatic cells have a distinct metastatic potential which is reflected by a non-random accumulation of chromosomal alterations. Furthermore the synergy of hiercharchical clustering and TMA-IHC is a useful, promising and very powerful tool to decipher diagnostic and prognostic signatures of cancer subtypes and may refine the morphological histopathological classification.