DFMO inhibition of neuroblastoma tumorigenesis.

BACKGROUND: Most high-risk neuroblastoma patients who relapse succumb to disease despite the existing therapy. We recently reported increased event-free and overall survival in neuroblastoma patients receiving difluoromethylornithine (DFMO) during maintenance therapy. The effect of DFMO on cellular processes associated with neuroblastoma tumorigenesis needs further elucidation. Previous studies have shown cytotoxicity with IC50 values >5-15 mM, these doses are physiologically unattainable in patients, prompting further mechanistic studies at therapeutic doses. METHODS: We characterized the effect of DFMO on cell viability, cell cycle, apoptosis, neurosphere formation, and protein expression in vitro using five established neuroblastoma cell lines (BE2C, CHLA-90, SHSY5Y, SMS-KCNR, and NGP) at clinically relevant doses of 0, 50, 100, 500, 1000, and 2500 µM. Limiting Dilution studies of tumor formation in murine models were performed. Statistical analysis was done using GraphPad and the level of significance set at p = 0.05. RESULTS: There was not a significant loss of cell viability or gain of apoptotic activity in the in vitro assays (p > 0.05). DFMO treatment initiated G1 to S phase cell cycle arrest. There was a dose-dependent decrease in frequency and size of neurospheres and a dose-dependent increase in beta-galactosidase activity in all cell lines. Tumor formation was decreased in xenografts both with DFMO-pretreated cells and in mice treated with DFMO. CONCLUSION: DFMO treatment is cytostatic at physiologically relevant doses and inhibits tumor initiation and progression in mice. This study suggests that DFMO, inhibits neuroblastoma by targeting cellular processes integral to neuroblastoma tumorigenesis at clinically relevant doses.

Altered Proteome of Extracellular Vesicles Derived from Bladder Cancer Patients Urine.

Proteomic analysis of extracellular vesicles (EVs) from biological fluid is a powerful approach to discover potential biomarkers for human diseases including cancers, as EV secreted to biological fluids are originated from the affected tissue. In order to investigate significant molecules related to the pathogenesis of bladder cancer, EVs were isolated from patient urine which was analyzed by mass spectrometry based proteomics. Comparison of the EV proteome to the whole urine proteome demonstrated an increased number of protein identification in EV. Comparative MS analyses of urinary EV from control subjects and bladder cancer patients identified a total of 1,222 proteins. Statistical analyses provided 56 proteins significantly increased in bladder cancer urine, including proteins for which expression levels varied by cancer stage (P-value < 0.05). While urine represents a valuable, noninvasive specimen for biomarker discovery in urologic cancers, there is a high degree of intra- and inter-individual variability in urine samples. The enrichment of urinary EV demonstrated its capability and applicability of providing a focused identification of biologically relevant proteins in urological diseases.

Exosomal proteome analysis of cerebrospinal fluid detects biosignatures of neuromyelitis optica and multiple sclerosis.

Quantitative proteomic analysis of exosomes isolated from cerebrospinal fluid (CSF) of neuromyelitis optica (NMO) patients detected signature proteins differentiating NMO from multiple sclerosis (MS) and idiopathic longitudinally extensive transverse myelitis. Exosomes with good yields were obtained using ultracentrifugation from pooled CSF assisted by chemokine-based clustering strategy, which improved target molecule identification by providing amplified fold change values. 442 significant proteins generated a list of signature molecules of diseases validated primarily by the identification of known markers such as glial fibrillary acidic protein (GFAP) and fibronectin specific to NMO and MS respectively. MetaCore pathway analysis of significant proteins supported the involvement of these proteins in disease progression via neurological pathway. Expression levels of target molecules from orthogonal label-free quantification employing quadrupole-Orbitrap hybrid mass spectrometry were in good agreement with those from Western blotting. Additional investigation of GFAP and fibronectin as representative disease molecules revealed their presence in intact exosomes as detected by flow cytometry. This comprehensive study suggests that the exosomal proteomic analysis of CSF can be applied to the identification and characterization of inflammatory disorders of the central nervous system.

A draft map of rhesus monkey tissue proteome for biomedical research.

Though the rhesus monkey is one of the most valuable non-human primate animal models for various human diseases because of its manageable size and genetic and proteomic similarities with humans, proteomic research using rhesus monkeys still remains challenging due to the lack of a complete protein sequence database and effective strategy. To investigate the most effective and high-throughput proteomic strategy, comparative data analysis was performed employing various protein databases and search engines. The UniProt databases of monkey, human, bovine, rat and mouse were used for the comparative analysis and also a universal database with all protein sequences from all available species was tested. At the same time, de novo sequencing was compared to the SEQUEST search algorithm to identify an optimal work flow for monkey proteomics. Employing the most effective strategy, proteomic profiling of monkey organs identified 3,481 proteins at 0.5% FDR from 9 male and 10 female tissues in an automated, high-throughput manner. Data are available via ProteomeXchange with identifier PXD001972. Based on the success of this alternative interpretation of MS data, the list of proteins identified from 12 organs of male and female subjects will benefit future rhesus monkey proteome research.

Identification of anti-metastatic drug and natural compound targets in isogenic colorectal cancer cells.

Therapeutic strategies for cancer treatment often remain challenging due to the cumulative risk derived from metastasis, which has been described as an aggressive state of cancer cell proliferation often resulting in failure of clinical therapy. In the current study, anti-metastatic properties of three chemotherapeutic drugs and three compounds from natural sources were investigated by comparative proteomic analysis. Proteomic profile comparison of the isogenic primary and metastatic colon cancer cell lines SW480 and SW620 identified two potential metastasis related molecular targets: fatty acid synthase and histone H4. To demonstrate their biological roles in cancer metastasis, the expression of these target genes was suppressed by siRNA transfection. Subsequent cell migration assays demonstrated reduced migratory effects. SW620 cells were treated with six anti-cancerous components. Through comprehensive proteomic analysis, three of the tested compounds, oxaliplatin, ginsenoside 20(S)-Rg3 and curcumin, were revealed to have a suppressive effect on FASN and histone H4 expression. SW620 cells treated with these drugs showed significantly reduced migratory activity, which suggests that drug-induced targeted suppression of these genes may affect cell migration. The validity of the proteomic datasets was verified by knowledgebase pathway analysis and immunoblotting assays. The anti-metastatic components revealed by the current proteomic analysis represent promising chemotherapeutic candidates for the treatment of colorectal adenocarcinoma. BIOLOGICAL SIGNIFICANCE: The current study demonstrates anti-metastatic activity of chemotherapeutics and natural components by the suppression of target molecules, fatty acid synthase and histone H4 identified by a comparative proteomic analysis employing the isogenic primary and metastatic colon cancer cell lines, SW480 and SW620. Three tested drugs, namely, oxaliplatin, ginsenoside 20(S)-Rg3 and curcumin were revealed to possess suppressive effects on fatty acid synthase and histone H4 and reduce metastasis as determined by cell migration assay. Data were confirmed by the correlation between spectral counts from proteomic data and Western blot analysis, which were in good agreement with immunohistochemistry.

Data supporting the identification of anti-metastatic drug and natural compound targets in isogenic colorectal cancer cells.

To investigate molecular therapeutic targets in cancer metastasis, comparative proteomic analysis was performed using the isogenic colorectal cancer cell lines SW480 and SW620. Two potential metastasis related molecular targets were identified: fatty acid synthase and histone H4. Subsequently, metastatic SW620 cells were treated with six anti-cancerous components and suppressive effects were observed in target protein expression. Through comprehensive proteomic analysis, three of the tested compounds, oxaliplatin, ginsenoside 20(S)-Rg3 and curcumin, were determined to have a suppressive effect on fatty acid synthase and histone H4 expression [1]. The current article contains one table exhibiting a list of proteins differentially expressed in metastatic SW620 cell lines compared to the primary SW480 cell line (Supplementary Table 1). Additionally, six tables demonstrate proteome changes in SW620 resulting from the treatment of three chemotherapeutics and three natural components (Supplementary Tables 1-7). The anti-metastatic components revealed by the current proteomic analysis represent promising chemotherapeutic candidates for the treatment of colorectal adenocarcinoma.

Proteomic strategy for probing complementary lethality of kinase inhibitors against pancreatic cancer.

In the present study, proteomic analysis was performed to discover combinational molecular targets for therapy and chemoresistance by comparing differential protein expression from Panc-1 cells treated with FDA-approved drugs such as sunitinib, imatinib mesylate, dasatinib, and PD184352. A total of 4041 proteins were identified in the combined data from all of the treatment groups by nano-electrospray ultra-performance LC and MS/MS analysis. Most of the proteins with significant changes are involved in apoptosis, cytoskeletal remodeling, and epithelial-to-mesenchymal transition. These processes are associated with increased chemoresistance and progression of pancreatic cancer. Among the differentially expressed proteins, heme oxygenase-1 (HO-1) was found in the sunitinib and imatinib mesylate treatment groups, which possibly acts as a specific target for synthetic lethality in combinational treatment. HO-1 was found to play a key role in sensitizing the chemoresistant Panc-1 cell line to drug therapy. Viability was significantly decreased in Panc-1 cells cotreated with sunitinib and imatinib mesylate at low doses, compared to those treated with sunitinib or imatinib mesylate alone. The results suggest that induction of chemosensitization by manipulating specific molecular targets can potentiate synergistic chemotherapeutic effects at lower, better tolerated doses, and in turn reduce the toxicity of multidrug treatment of pancreatic cancer.

Identification of differentially expressed proteins from primary versus metastatic pancreatic cancer cells using subcellular proteomics.

Pancreatic cancer is an aggressive disease with nearly equal yearly rates of diagnosis and death. Current therapies have failed to improve outcomes due to rapid disease progression and late stage at presentation. Recently, pathways involved in progression and metastasis have been elucidated; however, new knowledge has not generated more effective therapies. We report on the use of subcellular fractionation and liquid chromatography (LC)-mass spectrometry to identify 3,907 proteins in four pancreatic cancer cell lines, 540 of which are unique to primary cancer cells, and 487 unique to cells derived from metastatic sites. Statistical analysis identified 134 proteins significantly differentially expressed between the two populations. The subcellular localization of these proteins was determined and expression levels for four targets were validated using western blot techniques. These identified proteins can be further investigated to determine their roles in progression and metastasis and may serve as therapeutic targets in the development of more effective treatments for pancreatic cancer.

Subcellular tissue proteomics of hepatocellular carcinoma for molecular signature discovery.

Hepatocellular carcinoma (HCC) is one of the leading causes of mortality from solid organ malignancy worldwide. Because of the complexity of proteins within liver cells and tissues, the discovery of therapeutic targets of HCC has been difficult. To investigate strategies for decreasing the complexity of tissue samples for detecting meaningful protein mediators of HCC, we employed subcellular fractionation combined with 1D-gel electrophoresis and liquid chromatography-tandem mass spectrometry analysis. Moreover, we utilized a statistical method, namely, the Power Law Global Error Model (PLGEM), to distinguish differentially expressed proteins in a duplicate proteomic data set. Mass spectrometric analysis identified 3045 proteins in nontumor and HCC from cytosolic, membrane, nuclear, and cytoskeletal fractions. The final lists of highly differentiated proteins from the targeted fractions were searched for potentially translocated proteins in HCC from soluble compartments to the nuclear or cytoskeletal compartments. This analysis refined our targets of interest to include 21 potential targets of HCC from these fractions. Furthermore, we validated the potential molecular targets of HCC, MATR3, LETM1, ILF2, and IQGAP2 by Western blotting, immunohistochemisty, and immunofluorescent microscopy. Here we demonstrate an efficient strategy of subcellular tissue proteomics toward molecular target discovery of one of the most complicated human disease, HCC.

Discovery of putative pancreatic cancer biomarkers using subcellular proteomics.

Pancreatic cancer (PC) is a highly aggressive disease that frequently remains undetected until it has progressed to an advanced, systemic stage. Successful treatment of PC is hindered by the lack of early detection. The application of proteomic analysis to PC combined with subcellular fractionation has introduced new possibilities in the field of biomarker discovery. We utilized matched pairs of pancreas tumor and non-tumor pancreas from patients undergoing tumor resection. The tissues were treated to obtain cellular protein fractions corresponding to cytosol, membrane, nucleus and cytoskeleton. The fractions were then separated by molecular weight and digested with trypsin, followed by liquid chromatography and tandem mass spectrometry. The spectra obtained were searched using Sequest engine and combined into a single analysis file to obtain a semi-quantitative number, spectral count, using Scaffold software. We identified 2393 unique proteins in non-tumor and cancer pancreas. Utilizing PLGEM statistical analysis we determined 104 proteins were significantly changed in cancer. From these, we further validated four secreted proteins that are up-regulated in cancer and have potential for development as minimally-invasive diagnostic markers. We conclude that subcellular fractionation followed by gel electrophoresis and tandem mass spectrometry is a powerful strategy for identification of differentially expressed proteins in pancreatic cancer.

Gene expression profiling of ovarian tissues for determination of molecular pathways reflective of tumorigenesis.

Ovarian cancer is the fourth leading cause of gynecological cancer death among women in the United States. Early detection is a critical prerequisite to initiating effective cancer therapy. Gene microarray technology and proteomics have provided much of the biomarkers with potential use for diagnosis. However, more research is needed to fully understand disease onset and progression. To this end, we have performed microarray analysis with the goal of identifying molecular interaction networks defining tumor growth. Microarray analysis was performed on a limited set of ovarian tissues with various pathological diagnoses using Human Genome Focus Array (HGFA) for the detection of approximately 8500 human transcripts. Hierarchical clustering identified groups of ovarian tissues reflective of low malignant potential/early cancer onset and possible pre-cancerous stages involving small molecule, cytokine and/or hormone-dependent feed-back responses specific to the pelvic reproductive system and a priori initiated tumor suppression mechanisms. ANOVA followed by post hoc Scheffe confirmed our hypotheses. Moreover, we established a protein/protein interaction database associated with HGFA probe sets. This database was used to build and visualize molecular networks integrating small but significant changes in gene expression. In conclusion, we were able for the first time to delineate an intersecting genetic pattern linking ovarian tissues reflective of low potential malignancy/early cancer onset stages via long distance signaling between tissues of gynecological origin.