Protein interactome of muscle invasive bladder cancer

Identifying the mRNAs associated with Bladder cancer recurrence

OBJECTIVE

To identify the mRNAs associated with bladder cancer (BC) recurrence.

METHODS

The transcription profile of GSE31684 including 39 recurrent BC tumor samples and 54 non-recurrent BC tumor samples as well as transcription profile of GSE13507 including 36 recurrent BC tumor samples and 67 non-recurrent BC tumor samples were downlaoded from the Gene Expression Omnibus. Then, the differentially expressed genes (DEGs) were identified using linear models for microarray data (limma) and the intersections of DEGs from the two datasets were further screened. The weighed gene co-expression network analysis (WGCNA) was used to screen the modules related to BC recurrence. Protein-protein interaction (PPI) network analysis was used to analyze the genes interaction. Their functions were predicted by Gene Ontology and KEGG pathway enrichment. Moreover, The Comparative Toxicogenomics Database 2017 update (CTD) was used to search the BC related pathway. The univariate cox regression analysis was used to identify DEGs associated to the recurrence. Kaplan-Meier plots were used to illustrate recurrence free survival time (RFS).

RESULTS

A total of 692 intersections DEGs were screened. WGCNA showed that 7 modules (2279 genes) were stable in both the datasets. A total of 169 intersection DEGs were mapped to the 7 modules. There existed 149 interaction relationships among 81 proteins (18 down-regulated and 63 up-regulated DEGs) in the PPI network. Two KEGG pathways including Focal adhesion and ECM-receptor interaction were enriched which were also found in the CTD. The univariate cox regression analysis showed that 3 DEGs (COL4A1, COL1A2 and COL5A1) were significant related to the prognosis. Multivariate cox regression analysis revealed that pathologic_N (N0-N1 vs N2-N3, p= 0.033) were independent prognostic factors for overall survival in patients with BC.

CONCLUSION

COL4A1, COL1A2 and COL5A1 could be associated with BC recurrence.

Mass spectrometric detection combined with bioinformatic analysis identified possible protein markers and key pathways associated with bladder cancer

We aimed to find possible protein markers and key pathways related to bladder cancer. In total, we extracted three bladder cancer tissues and three paracancerous tissues from Jiangsu Provincial People's Hospital Urology Department, and performed mass spectrometric detection with Q Exactive. Subsequently, we screened the differentially expressed proteins in the disease group and the normal group using the LIMMA package, and performed functional enrichment analyses using DAVID. Further, we constructed protein-protein interaction (PPI) networks with Cytoscape software, and analyzed modules with ClusterONE. In total, 165 differentially expressed proteins including 19 upregulated and 146 downregulated ones were obtained. ACTA2 (Actin, Alpha 2, Smooth Muscle, Aorta), ACTN1 (Actinin, Alpha 1), and VCL (Vinculin) were significant nodes with higher degrees in the PPI network. These three nodes were also hub nodes in module 2. Besides, functional enrichment analysis suggested that ECM-receptor interaction and focal adhesion were significant pathways, and these two pathways were also enriched in three network modules. In addition, ACTN1 and VCL were enriched in the focal adhesion pathway in module 2. Thus, ACTA2, ACTN1, and VCL may play important roles in bladder cancer progression and may be protein markers for this disease. The ECM-receptor interaction pathway and the focal adhesion pathway may be involved in the progression of bladder cancer. Furthermore, ACTN1 and VCL may play roles in bladder cancer development, partly via the focal adhesion pathway.

Proteomics analysis of bladder cancer invasion: Targeting EIF3D for therapeutic intervention

Patients with advanced bladder cancer have poor outcomes, indicating a need for more efficient therapeutic approaches. This study characterizes proteomic changes underlying bladder cancer invasion aiming for the better understanding of disease pathophysiology and identification of drug targets. High resolution liquid chromatography coupled to tandem mass spectrometry analysis of tissue specimens from patients with non-muscle invasive (NMIBC, stage pTa) and muscle invasive bladder cancer (MIBC, stages pT2+) was conducted. Comparative analysis identified 144 differentially expressed proteins between analyzed groups. These included proteins previously associated with bladder cancer and also additional novel such as PGRMC1, FUCA1, BROX and PSMD12, which were further confirmed by immunohistochemistry. Pathway and interactome analysis predicted strong activation in muscle invasive bladder cancer of pathways associated with protein synthesis e.g. eIF2 and mTOR signaling. Knock-down of eukaryotic translation initiation factor 3 subunit D (EIF3D) (overexpressed in muscle invasive disease) in metastatic T24M bladder cancer cells inhibited cell proliferation, migration, and colony formation in vitro and decreased tumor growth in xenograft models. By contrast, knocking down GTP-binding protein Rheb (which is upstream of EIF3D) recapitulated the effects of EIF3D knockdown in vitro, but not in vivo. Collectively, this study represents a comprehensive analysis of NMIBC and MIBC providing a resource for future studies. The results highlight EIF3D as a potential therapeutic target.

Ten Years of Proteomics in Bladder Cancer: Progress and Future Directions

Research efforts targeting the identification of bladder cancer biomarkers have been extensive during the past decade. Investigations have been performed at the genome, transcriptome, proteome, and metabolome levels and outputs have started appearing including the sketching of disease molecular subtypes. Proteins are directly linked to cell phenotype hence they accumulate special interest as both biomarkers and therapeutic targets. Multiple technical challenges exist, of the main, being the protein concentration vast dynamic range and presence of proteins in modified forms. The scope of this review is to summarize the contribution of proteomics research in this quest of bladder cancer biomarkers. To obtain an unbiased and comprehensive overview, the scientific literature was searched for manuscripts describing proteomic studies on urothelial cancer from the last ten years and those including independent verification studies in urine, tissue and blood are briefly presented. General observations include: a) in most cases, suboptimal experimental design including healthy controls in biomarker discovery and frequently biomarker verification, is followed; b) variability in protein findings between studies can be observed, to some extent reflecting complexity of experimental approaches and proteome itself; c) consistently reported biomarkers include mainly plasma proteins and d) compilation of protein markers into diagnostic panels appears the most promising way forward. Two main avenues of research can now be foreseen: targeting integration of the existing disparate data with proteomic findings being placed in the context of existing knowledge on bladder cancer subtypes and in parallel, accumulation of clinical samples to support proper validation studies of promising marker combinations.

Integrative analysis of extracellular and intracellular bladder cancer cell line proteome with transcriptome: improving coverage and validity of -omics findings

Characterization of disease-associated proteins improves our understanding of disease pathophysiology. Obtaining a comprehensive coverage of the proteome is challenging, mainly due to limited statistical power and an inability to verify hundreds of putative biomarkers. In an effort to address these issues, we investigated the value of parallel analysis of compartment-specific proteomes with an assessment of findings by cross-strategy and cross-omics (proteomics-transcriptomics) agreement. The validity of the individual datasets and of a “verified” dataset based on cross-strategy/omics agreement was defined following their comparison with published literature. The proteomic analysis of the cell extract, Endoplasmic Reticulum/Golgi apparatus and conditioned medium of T24 vs. its metastatic subclone T24M bladder cancer cells allowed the identification of 253, 217 and 256 significant changes, respectively. Integration of these findings with transcriptomics resulted in 253 “verified” proteins based on the agreement of at least 2 strategies. This approach revealed findings of higher validity, as supported by a higher level of agreement in the literature data than those of individual datasets. As an example, the coverage and shortlisting of targets in the IL-8 signalling pathway are discussed. Collectively, an integrative analysis appears a safer way to evaluate -omics datasets and ultimately generate models from valid observations.

Vascular endothelial growth factor A as predictive marker for mTOR inhibition in relapsing high-grade serous ovarian cancer

Background

Development of resistance against first line drug therapy including cisplatin and paclitaxel in high-grade serous ovarian cancer (HGSOC) presents a major challenge. Identifying drug candidates breaking resistance, ideally combined with predictive biomarkers allowing precision use are needed for prolonging progression free survival of ovarian cancer patients.

Modeling of molecular processes driving drug resistance in tumor tissue further combined with mechanism of action of drugs provides a strategy for identification of candidate drugs and associated predictive biomarkers.

Results

Consolidation of transcriptomics profiles and biomedical literature mining results provides 1242 proteins linked with ovarian cancer drug resistance. Integrating this set on a protein interaction network followed by graph segmentation results in a molecular process model representation of drug resistant HGSOC embedding 409 proteins in 24 molecular processes. Utilizing independent transcriptomics profiles with follow-up data on progression free survival allows deriving molecular biomarker-based classifiers for predicting recurrence under first line therapy. Biomarkers of specific relevance are identified in a molecular process encapsulating TGF-beta, mTOR, Jak-STAT and Neurotrophin signaling. Mechanism of action molecular model representations of cisplatin and paclitaxel embed the very same signaling components, and specifically proteins afflicted with the activation status of the mTOR pathway become evident, including VEGFA. Analyzing mechanism of action interference of the mTOR inhibitor sirolimus shows specific impact on the drug resistance signature imposed by cisplatin and paclitaxel, further holding evidence for a synthetic lethal interaction to paclitaxel mechanism of action involving cyclin D1.

Conclusions

Stratifying drug resistant high grade serous ovarian cancer via VEGFA, and specifically treating with mTOR inhibitors in case of activation of the pathway may allow adding precision for overcoming resistance to first line therapy.

Characteristics of Patients With Transitional Cell Carcinoma of the Urinary Bladder in Kermanshah Province, Iran

BACKGROUND

In Iran, bladder cancer is one of the most common malignancy sites among men, ranking as the fifth with age-specific incidence rate of about 11.2 per 100,000 males. It causes 8% of all malignancies in men and 3% of all malignancies in women.

OBJECTIVES

The aim of this study was to report the epidemiological, clinical, and pathological features of bladder cancer in Western Iran compared to other studies.

PATIENTS AND METHODS

This is a retrospective study between 2003 and 2014 when forty-four patients with bladder cancer referred to Hematology Clinic of Kermanshah, Kermanshah, Iran. Transitional cell carcinoma (TCC) was in 39 patients.

RESULTS

In the patients with TCC, the mean age in diagnosis for them was 65.43 years (± 11.64), range of age 42 to 88 years , thirty-three patients (84.6%) were male, and six patients (15.4%) were female. Of 39 patients with TCC, 16 patients (41%) had metastasis. 21 patients (53.8%) were smoker and 16 patients (41%) had muscle invasive. 35 patients (89.7%) were histological high grade and the rest of patients were low grade. In the TCC patients with increasing age, metastasis and muscle invasive increased.

CONCLUSIONS

The age presentation of TCC in West Iran was similar to other studies. Percentage of patients with high grade is more than other studies, and also the number of patients with bladder cancer has increased during last 4 years. For better results, studies must be conducted with more patients in this area, and other areas of Iran with checking of genetics, race and environmental factors.

BcCluster: A Bladder Cancer Database at the Molecular Level

BACKGROUND

Bladder Cancer (BC) has two clearly distinct phenotypes. Non-muscle invasive BC has good prognosis and is treated with tumor resection and intravesical therapy whereas muscle invasive BC has poor prognosis and requires usually systemic cisplatin based chemotherapy either prior to or after radical cystectomy. Neoadjuvant chemotherapy is not often used for patients undergoing cystectomy. High-throughput analytical omics techniques are now available that allow the identification of individual molecular signatures to characterize the invasive phenotype. However, a large amount of data produced by omics experiments is not easily accessible since it is often scattered over many publications or stored in supplementary files.

OBJECTIVE

To develop a novel open-source database, BcCluster (http://www.bccluster.org/), dedicated to the comprehensive molecular characterization of muscle invasive bladder carcinoma.

MATERIALS

A database was created containing all reported molecular features significant in invasive BC. The query interface was developed in Ruby programming language (version 1.9.3) using the web-framework Rails (version 4.1.5) (http://rubyonrails.org/).

RESULTS

BcCluster contains the data from 112 published references, providing 1,559 statistically significant features relative to BC invasion. The database also holds 435 protein-protein interaction data and 92 molecular pathways significant in BC invasion. The database can be used to retrieve binding partners and pathways for any protein of interest. We illustrate this possibility using survivin, a known BC biomarker.

CONCLUSIONS

BcCluster is an online database for retrieving molecular signatures relative to BC invasion. This application offers a comprehensive view of BC invasiveness at the molecular level and allows formulation of research hypotheses relevant to this phenotype.

Molecular Architecture of Spinal Cord Injury Protein Interaction Network

Spinal cord injury (SCI) is associated with complex pathophysiological processes that follow the primary traumatic event and determine the extent of secondary damage and functional recovery. Numerous reports have used global and hypothesis-driven approaches to identify protein changes that contribute to the overall pathology of SCI in an effort to identify potential therapeutic interventions. In this study, we use a semi-automatic annotation approach to detect terms referring to genes or proteins dysregulated in the SCI literature and develop a curated SCI interactome. Network analysis of the SCI interactome revealed the presence of a rich-club organization corresponding to a “powerhouse” of highly interacting hub-proteins. Studying the modular organization of the network have shown that rich-club proteins cluster into modules that are specifically enriched for biological processes that fall under the categories of cell death, inflammation, injury recognition and systems development. Pathway analysis of the interactome and the rich-club revealed high similarity indicating the role of the rich-club proteins as hubs of the most prominent pathways in disease pathophysiology and illustrating the centrality of pro-and anti-survival signal competition in the pathology of SCI. In addition, evaluation of centrality measures of single nodes within the rich-club have revealed that neuronal growth factor (NGF), caspase 3, and H-Ras are the most central nodes and potentially an interesting targets for therapy. Our integrative approach uncovers the molecular architecture of SCI interactome, and provide an essential resource for evaluating significant therapeutic candidates.