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Novel functional profiling approach combining reverse phase protein microarrays and human 3-D ex vivo tissue cultures: expression of apoptosis-related proteins in human colon cancer. | LitMetric

AI Article Synopsis

Article Abstract

Cancer is caused by a complex pattern of molecular perturbations. To understand the biology of cancer, it is thus important to look at the activation state of key proteins and signaling networks. The limited amount of available sample material from patients and the complexity of protein expression patterns make the use of traditional protein analysis methods particularly difficult. In addition, the only approach that is currently available for performing functional studies is the use of serial biopsies, which is limited by ethical constraints and patient acceptance. The goal of this work was to establish a 3-D ex vivo culture technique in combination with reverse-phase protein microarrays (RPPM) as a novel experimental tool for use in cancer research. The RPPM platform allows the parallel profiling of large numbers of protein analytes to determine their relative abundance and activation level. Cancer tissue and the respective corresponding normal tissue controls from patients with colorectal cancer were cultured ex vivo. At various time points, the cultured samples were processed into lysates and analyzed on RPPM to assess the expression of carcinoembryonic antigen (CEA) and 24 proteins involved in the regulation of apoptosis. The methodology displayed good robustness and low system noise. As a proof of concept, CEA expression was significantly higher in tumor compared with normal tissue (p<0.0001). The caspase 9 expression signal was lower in tumor tissue than in normal tissue (p<0.001). Cleaved Caspase 8 (p=0.014), Bad (p=0.007), Bim (p=0.007), p73 (p=0.005), PARP (p<0.001), and cleaved PARP (p=0.007) were differentially expressed in normal liver and normal colon tissue. We demonstrate here the feasibility of using RPPM technology with 3-D ex vivo cultured samples. This approach is useful for investigating complex patterns of protein expression and modification over time. It should allow functional proteomics in patient samples with various applications such as pharmacodynamic analyses in drug development.

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http://dx.doi.org/10.1002/pmic.200800159DOI Listing

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