Integration of pharmacoproteomic and computational approaches reveals the cellular signal transduction pathways affected by apatinib in gastric cancer cell lines.

Apatinib is known to be a highly selective vascular endothelial growth factor receptor 2 (VEGFR2) inhibitor with anti-angiogenic and anti-tumor properties. In a phase III study, the objective response rate to apatinib was low. It remains unclear why the effectivity of apatinib varies among patients and what type of patients are candidates for the treatment. In this study, we investigated the anti-tumor efficacy of apatinib against 13 gastric cancer cell lines and found that it differed depending on the cell line. Using integrated wet and dry approaches, we showed that apatinib was a multi-kinase inhibitor of c-Kit, RAF1, VEGFR1, VEGFR2, and VEGFR3, predominantly inhibiting c-Kit. Notably, KATO-III, which was the most apatinib-sensitive among the gastric cancer cell lines investigated, was the only cell line expressing c-Kit, RAF1, VEGFR1, and VEGFR3 but not VEGFR2. Furthermore, we identified SNW1 as a molecule affected by apatinib that plays an important role in cell survival. Finally, we identified the molecular network related to SNW1 that was affected by treatment with apatinib. These results suggest that the mechanism of action of apatinib in KATO-III cells is independent of VEGFR2 and that the differential efficacy of apatinib was due to differences in expression patterns of receptor tyrosine kinases. Furthermore, our results suggest that the differential efficacy of apatinib in gastric cell lines may be attributed to SNW1 phosphorylation levels at a steady state. These findings contribute to a deeper understanding of the mechanism of action of apatinib in gastric cancer cells.

Temporal dynamics from phosphoproteomics using endoscopic biopsy specimens provides new therapeutic targets in stage IV gastric cancer.

Phosphoproteomic analysis expands our understanding of cancer biology. However, the feasibility of phosphoproteomic analysis using endoscopically collected tumor samples, especially with regards to dynamic changes upon drug treatment, remains unknown in stage IV gastric cancer. Here, we conducted a phosphoproteomic analysis using paired endoscopic biopsy specimens of pre- and post-treatment tumors (Ts) and non-tumor adjacent tissues (NATs) obtained from 4 HER2-positive gastric cancer patients who received trastuzumab-based treatment and from pre-treatment Ts and NATs of 4 HER2-negative gastric cancer patients. Our analysis identified 14,622 class 1 phosphosites with 12,749 quantified phosphosites and revealed molecular changes by HER2 positivity and treatment. An inhibitory signature of the ErbB signaling was observed in the post-treatment HER2-positive T group compared with the pre-treatment HER2-positive T group. Phosphoproteomic profiles obtained by a case-by-case review using paired pre- and post-treatment HER2-positive T could be utilized to discover predictive or resistant biomarkers. Furthermore, these data nominated therapeutic kinase targets which were exclusively activated in the patient unresponded to the treatment. The present study suggests that a phosphoproteomic analysis of endoscopic biopsy specimens provides information on dynamic molecular changes which can individually characterize biologic features upon drug treatment and identify therapeutic targets in stage IV gastric cancer.

Identification of CD14 and lipopolysaccharide-binding protein as novel biomarkers for sarcoidosis using proteomics of serum extracellular vesicles.

Sarcoidosis is a complex, polygenic, inflammatory granulomatous multi-organ disease of unknown cause. The granulomatous inflammation in sarcoidosis is driven by the interplay between T cells and macrophages. Extracellular vesicles (EVs) play important roles in intercellular communication. We subjected serum EVs, isolated by size exclusion chromatography, from seven patients with sarcoidosis and five control subjects to non-targeted proteomics analysis. Non-targeted, label-free proteomics analysis detected 2292 proteins in serum EVs; 42 proteins were up-regulated in patients with sarcoidosis relative to control subjects; and 324 proteins were down-regulated. The protein signature of EVs from patients with sarcoidosis reflected disease characteristics such as antigen presentation and immunological disease. Candidate biomarkers were further verified by targeted proteomics analysis (selected reaction monitoring) in 46 patients and 10 control subjects. Notably, CD14 and lipopolysaccharide-binding protein (LBP) were validated by targeted proteomics analysis. Up-regulation of these proteins was further confirmed by immunoblotting, and their expression was strongly increased in macrophages of lung granulomatous lesions. Consistent with these findings, CD14 levels were increased in lipopolysaccharide-stimulated macrophages during multinucleation, concomitant with increased levels of CD14 and LBP in EVs. The area under the curve values of CD14 and LBP were 0.81 and 0.84, respectively, and further increased to 0.98 in combination with angiotensin-converting enzyme and soluble interleukin-2 receptor. These findings suggest that CD14 and LBP in serum EVs, which are associated with granulomatous pathogenesis, can improve the diagnostic accuracy in patients with sarcoidosis.

Expression of Cancer Stem Cell Markers EpCAM and CD90 Is Correlated with Anti- and Pro-Oncogenic EphA2 Signaling in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. Additionally, the efficacy of targeted molecular therapies with multiple tyrosine kinase inhibitors is limited. In this study, we focused on the cellular signaling pathways common to diverse HCC cells and used quantitative reverse phase protein array (RPPA) and statistical analyses to elucidate the molecular mechanisms determining its malignancy. We examined the heterogeneity of 17 liver cancer cell lines by performing cluster analysis of their expression of CD90 and EpCAM cancer stem cell markers. Gaussian mixture model clustering identified three dominant clusters: CD90-positive and EpCAM-negative (CD90+), EpCAM-positive and CD90-negative (EpCAM+) and EpCAM-negative and CD90-negative (Neutral). A multivariate analysis by partial least squares revealed that the former two cell populations showed distinct patterns of protein expression and phosphorylation in the EGFR and EphA2 signaling pathways. The CD90+ cells exhibited higher abundance of AKT, EphA2 and its phosphorylated form at Ser897, whereas the EpCAM+ cells exhibited higher abundance of ERK, RSK and its phosphorylated form. This demonstrates that pro-oncogenic, ligand-independent EphA2 signaling plays a dominant role in CD90+ cells with higher motility and metastatic activity than EpCAM+ cells. We also showed that an AKT inhibitor reduced the proliferation and survival of CD90+ cells but did not affect those of EpCAM+ cells. Taken together, our results suggest that AKT activation may be a key pro-oncogenic regulator in HCC.

Proteomics of serum extracellular vesicles identifies a novel COPD biomarker, fibulin-3 from elastic fibres.

There is an unmet need for novel biomarkers in the diagnosis of multifactorial COPD. We applied next-generation proteomics to serum extracellular vesicles (EVs) to discover novel COPD biomarkers. EVs from 10 patients with COPD and six healthy controls were analysed by tandem mass tag-based non-targeted proteomics, and those from elastase-treated mouse models of emphysema were also analysed by non-targeted proteomics. For validation, EVs from 23 patients with COPD and 20 healthy controls were validated by targeted proteomics. Using non-targeted proteomics, we identified 406 proteins, 34 of which were significantly upregulated in patients with COPD. Of note, the EV protein signature from patients with COPD reflected inflammation and remodelling. We also identified 63 upregulated candidates from 1956 proteins by analysing EVs isolated from mouse models. Combining human and mouse biomarker candidates, we validated 45 proteins by targeted proteomics, selected reaction monitoring. Notably, levels of fibulin-3, tripeptidyl-peptidase 2, fibulin-1, and soluble scavenger receptor cysteine-rich domain-containing protein were significantly higher in patients with COPD. Moreover, six proteins; fibulin-3, tripeptidyl-peptidase 2, UTP-glucose-1-phosphate uridylyl transferase, CD81, CD177, and oncoprotein-induced transcript 3, were correlated with emphysema. Upregulation of fibulin-3 was confirmed by immunoblotting of EVs and immunohistochemistry in lungs. Strikingly, fibulin-3 knockout mice spontaneously developed emphysema with age, as evidenced by alveolar enlargement and elastin destruction. We discovered potential pathogenic biomarkers for COPD using next-generation proteomics of EVs. This is a novel strategy for biomarker discovery and precision medicine.

Panomicon: A web-based environment for interactive, visual analysis of multi-omics data.

Multi-omics analyses, combining transcriptomics, genomics, proteomics, and so on, have led to important insights in many areas of biology and medicine. To support these analyses, software that can handle the difficulties associated with multi-omics datasets is crucial. Here, we describe Panomicon, a web-based, interactive analysis environment for multi-omics data. Building on Toxygates, a tool previously created to study single-omics data that features interactive clustering, heatmaps, and user data uploads, Panomicon introduces improvements for the storage and handling of additional omics types, as well as tools for the generation and visualization of interaction networks between different types of omics data. Panomicon is a new type of environment for the collaborative study of multi-omics data, both for users uploading data to our server and for groups wishing to host their own deployment of Panomicon. We demonstrate Panomicon's capabilities by revisiting a microRNA-mRNA interaction networks study in a non-small cell lung cancer dataset.

Comparative analysis of seven types of superoxide dismutases for their ability to respond to oxidative stress in Bombyx mori.

Insects are well adapted to changing environmental conditions. They have unique systems for eliminating reactive oxygen species (ROS). Superoxide dismutase (SOD) is a key enzyme that plays a primary role in removing ROS. Bombyx mori is a lepidopteran insect, whose body size is larger than the model insect Drosophila melanogaster, which enabled us to more easily examine gene expression at the tissue level. We searched B. mori SOD (BmSOD) genes using genome database, and we analyzed their function under different type of oxidative stress. Consequently, we identified four new types of BmSODs in addition to the three types already known. Two of the seven types had a unique domain architecture that has not been discovered previously in the SOD family, and they were expressed in different tissues and developmental stages. Furthermore, these BmSODs responded differently to several kinds of stressors. Our results showed that the seven types of BmSODs are likely to play different roles in B. mori; therefore, B. mori could be used to distinguish the functions of each SOD for resistance to oxidative stress that changes with the environmental conditions.