Mouse anti-Human MYOT monoclonal antibody, clone STP45

Purpose: The present study is to discover a new genes associated with drug resistance development in ovarian cancer. Methods: We used microarray analysis to determine alterations in the level of expression of genes in cisplatin-(CisPt), doxorubicin-(Dox), topotecan-(Top), and paclitaxel-(Pac) resistant variants of W1 and A2780 ovarian cancer cell lines. Immunohistochemistry assay was used to determine protein expression in ovarian cancer patients. Results: We observed alterations in the expression of 22 genes that were common to all three cell lines that were resistant to the same cytostatic drug. The level of expression of 13 genes was upregulated and that of nine genes was downregulated. In the CisPt-resistant cell line, we observed downregulated expression of ABCC6, BST2, ERAP2 and MCTP1; in the Pac-resistant cell line, we observe upregulated expression of ABCB1, EPHA7 and RUNDC3B and downregulated expression of LIPG, MCTP1, NSBP1, PCDH9, PTPRK and SEMA3A. The expression levels of three genes, ABCB1, ABCB4 and IFI16, were upregulated in the Dox-resistant cell lines. In the Top-resistant cell lines, we observed increased expression levels of ABCG2, HERC5, IFIH1, MYOT, S100A3, SAMD4A, SPP1 and TGFBI and decreased expression levels of MCTP1 and PTPRK. The expression of EPHA7, IFI16, SPP1 and TGFBI was confirmed at protein level in analyzed ovarian cancer patients. Conclusions: The expression profiles of the investigated cell lines indicated that new candidate genes are related to the development of resistance to the cytostatic drugs that are used in first-and second-line chemotherapy of ovarian cancer.

Introduction: Myofibrillar myopathies are characterized by progressive muscle weakness and impressive abnormal protein aggregation in muscle fibers. In about 10 % of patients, the disease is caused by mutations in the MYOT gene encoding myotilin. The aim of our study was to decipher the composition of protein deposits in myotilinopathy to get new information about aggregate pathology. Results: Skeletal muscle samples from 15 myotilinopathy patients were included in the study. Aggregate and control samples were collected from muscle sections by laser microdissection and subsequently analyzed by a highly sensitive proteomic approach that enables a relative protein quantification. In total 1002 different proteins were detected. Seventy-six proteins showed a significant over-representation in aggregate samples including 66 newly identified aggregate proteins. Z-disc-associated proteins were the most abundant aggregate components, followed by sarcolemmal and extracellular matrix proteins, proteins involved in protein quality control and degradation, and proteins with a function in actin dynamics or cytoskeletal transport. Forty over-represented proteins were evaluated by immunolocalization studies. These analyses validated our mass spectrometric data and revealed different regions of protein accumulation in abnormal muscle fibers. Comparison of data from our proteomic analysis in myotilinopathy with findings in other myofibrillar myopathy subtypes indicates a characteristic basic pattern of aggregate composition and resulted in identification of a highly sensitive and specific diagnostic marker for myotilinopathy. Conclusions: Our findings i) indicate that main protein components of aggregates belong to a network of interacting proteins, ii) provide new insights into the complex regulation of protein degradation in myotilinopathy that may be relevant for new treatment strategies, iii) imply a combination of a toxic gain-of-function leading to myotilin-positive protein aggregates and a loss-of-function caused by a shift in subcellular distribution with a deficiency of myotilin at Z-discs that impairs the integrity of myofibrils, and iv) demonstrate that proteomic analysis can be helpful in differential diagnosis of protein aggregate myopathies.