There is a need for novel drugs for sarcoma treatment. In the present study, to identify inhibitors with potential therapeutic utility in sarcomas, we screened the growth inhibitory effects of 361 inhibitors, including experimental reagents and anti-cancer drugs approved for use in non-sarcoma malignancies and those under clinical trials. The inhibitors were initially tested using 10 osteosarcoma cell lines. The half-maximal inhibitory concentration (IC50) of leptomycin B, actinomycin D, chetomin, and staurosporine was <100 nM in all the cell lines. As the promiscuous effects of staurosporine on kinases make it unsuitable for clinical applications, the other three inhibitors were tested in an additional 15 sarcoma cell lines derived from synovial sarcoma, fibrosarcoma, liposarcoma, rhabdomyosarcoma, malignant peripheral nerve sheath tumor, leiomyosarcoma, and Ewing’s sarcoma. The IC50 of leptomycin B and actinomycin D was <100 nM in all cell lines and that of chetomin was <100 nM in all but three synovial sarcoma cell lines. Although the clinical development of leptomycin B, a chromosomal region maintenance (CRM)1/exportin (XPO)1 inhibitor, was discontinued because of toxicity, a previous clinical trial revealed that other CRM1/XPO1 inhibitors, such as selinexor, have anti-tumor effects in sarcomas. Actinomycin D has proven clinical utility in the treatment of sarcomas. Chetomin disrupts the interaction of hypoxia-inducible factor-1 with the transcriptional coactivator p300 and its clinical utility has not been established in sarcomas. Chetomin exhibited growth inhibitory effects on sarcoma cells with different histological subtypes. Library screening is a powerful approach to detect the potential utility of anti-cancer drugs in sarcoma treatment.
Glioblastoma (GBM) is the most common brain tumor in adults. Although the surgical and chemoradiotherapy approaches for treatment have improved, the prognosis of patients with GBM is still poor and novel drugs are urgently required. Therefore, we investigated small molecular inhibitors to target GBM on the basis of gene expression data by using a Connectivity Map (CMAP)–based approach. Using meta-analysis performed with publically available gene expression data, we identified the gene expression signature of GBM. The CMAP analysis identified 15 candidate drugs for GBM treatment. We confirmed the anticancer cell proliferation activity of cantharidin as one of the top 15 drugs with high negative enrichment scores in CMAP analysis by using GBM cell lines. Our results indicate the potential utility of CMAP to discover the potent drugs in the GBM treatment. This approach can be applied to other malignancies than GBM.
Autoimmune mechanisms have been hypothesized to underlie a number of human disorders in which both disease pathogenesis and diagnostic biomarkers remain poorly understood. This is partly due to a lack of efficient techniques for identification of plasma autoantibodies associated with specific pathophysiological conditions. We have developed a novel proteomic methodology to comprehensively identify plasma IgG-bound proteins using liquid chromatography tandem mass spectrometry (LC-MS/MS) after denaturing enriched plasma IgG to solubilize and release low molecular weight proteins. In total, we identified 44 proteins using this method that were undetectable in unprocessed plasma, 21 of which were not identified in the Human Plasma Proteome Draft of 2017. Comparison of plasma IgG-bound proteins between healthy subjects and patients with isolated adrenocorticotropic hormone deficiency, a rare endocrine disorder speculated to involve autoimmune mechanisms, revealed several distinct IgG-bound proteins specifically detected in patient plasma but not in healthy subjects. Our results suggest that solubilization of low molecular weight proteins bound to enriched plasma IgG and subsequent proteomic analysis by LC-MS/MS could provide a promising strategy for identification of autoantigens in human peripheral blood.
Phosphorylation, one of the most common post-translational modifications of proteins, plays a critical role in many biological processes. We have previously developed several analytical methods for determining the phosphorylation status of certain proteins by using a phosphate-capturing binuclear metal complex known as Phos-tag. Here, we describe a novel method for the gel-based in vitro analysis of the phosphorylation status of a protein by a simple and rapid fluorometric staining method that uses a tetramethylrhodamine (TAMRA)-labeled Phos-tag derivative (TAMRA–Phos-tag). The entire staining protocol, which requires less than 2 h to complete, uses three buffer solutions for staining, washing, and dilution, respectively, at room temperature. The gel-based analysis of phosphoproteins in a polyacrylamide gel can be conducted by using a fluorescence imaging scanner with a 532-nm excitation laser and a 580-nm longpass emission filter. As a practical example of the use of the TAMRA–Phos-tag staining method, we examined the time course of dephosphorylation of ovalbumin by an alkaline phosphatase. In addition, inhibitor profiling of a tyrosine kinase Abl was performed by using an Abl-substrate (GST-Abltide) and an Abl-inhibitor (Imatinib).
Proteogenomics is a novel approach to understand the molecular backgrounds of diseases. In cancer research, proteomic studies have been conducted without using the genome data of individual samples. For example, a common public database has always been used to identify proteins by mass spectrometry. However, tumor genomes, even tumors of the same type of cancer, can differ considerably, and such differences affect the response to treatments. Thus, genomic backgrounds should be considered when identifying proteins by mass spectrometry. In cancer proteogenomics, a virtual proteome database is generated using the genome data of identical samples for the mass spectrometric identification of proteins reflecting genetic mutations, which are not common and not cited in the commonly used databases. Such proteins are candidate biomarkers and therapeutic targets. Although previous studies have reported software capable of translating genomic data to proteomic data, a standard protocol has not been established. In addition, the utility of proteogenomics has also not been established, and it is not self-evident that proteins with mutations unique to certain groups can be exploited for innovative treatments or to provide clues for the resolution of biological problems in cancers. Collaborative efforts by cancer researchers and specialists in mass spectrometry and bioinformatics are required for fruitful advancements.
Chronic kidney disease (CKD) is a common disorder and cause of death in cats. In the classification proposed by the International Renal Interest Society (IRIS), stage I and II CKD are difficult to diagnose accurately using markers, in comparison with normal controls. We recently described a simple and highly reproducible two-step method for identifying potential disease-marker candidates among low-abundance urine proteins. Urine samples were taken from 56 normal control cats as the control group and from 56 cats with CKD (stage I). A carboxylesterase 5A fragment and filaggrin-2 fragment were identified as two proteins with higher levels in normal control cats. The performance of the ELISA of urine carboxylesterase 5A fragment was satisfactory in terms of recovery (97.2–102.4%) and within-run (1.3–3.6%) and between-day (1.5–4.1%) reproducibility. Urine carboxylesterase 5A fragment levels were significantly greater in normal cats (3.4±0.6 mg/dL) than in CKD (stage I) (1.9±0.5 mg/dL) (p<0.001). A carboxylesterase 5A fragment may be useful as a complementary marker to P-Cre and BUN for detection of CKD (stage I).