scholarly journals Proteomic Characterization of Primary and Metastatic Prostate Cancer Reveals Reduced Proteinase Activity in Aggressive Tumors

2021 ◽  
Author(s):  
Qing Kay Li ◽  
Jing Chen ◽  
Yingwei Hu ◽  
Naseruddin Hoti ◽  
Stefani N Thomas ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Large Scale ◽  
Validation Cohort ◽  
Protein Profile ◽  
Specific Antigen ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Dipeptidyl Peptidase 4 ◽  
Molecular Abnormalities ◽  
Substrate Peptide

Abstract BackgroundProstate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. Clinically, it is critical to separate and treat aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with PCa, it is still challenge to separate AG from NAG. To better understand the functional consequence of PCa progression and the unique features of AG from NAG, we studied proteomic signatures of primary AG, NAG and metastatic PCa.Methodes39 PCa and 10 benign prostate controls in discovery cohort and 57 PCa in independent-collected validation cohort were analyzed using data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using validation cohort, as well as by comparison with TCGA mRNA expression and immnunochemistry on PCa tissue microarray (TMA).Results4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed the reduced expression of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis using SWATH data further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates in AG tumors, including the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using independent-collected cohort, by comparison with TCGA mRNA data, and the immunochemical stains of our tumor microarray (TMA).ConclusionsOur study is the first large-scale proteomics analysis of PCa tissue using DIA SWATH-MS platform. It not only provides an interrogative proteomic signature of PCa subtypes, but also indicates critical roles of certain proteinases, especially DPP4, in PCa progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in the PCa progression as well as for the development of a clinical assay to distinguish aggressive from indolent PCa.

scholarly journals Proteomic characterization of primary and metastatic prostate cancer reveals reduced proteinase activity in aggressive tumors

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Kay Li ◽  
Jing Chen ◽  
Yingwei Hu ◽  
Naseruddin Höti ◽  
Tung-Shing Mamie Lih ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Functional Analysis ◽  
Large Scale ◽  
Validation Cohort ◽  
Protein Profile ◽  
Specific Antigen ◽  
Pathway Enrichment Analysis ◽  
Dipeptidyl Peptidase 4 ◽  
Molecular Abnormalities ◽  
Substrate Peptide

AbstractProstate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. In order to improve patient outcomes, it is critical to clinically separate aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with aggressive PCa, it is still challenging to separate AG from NAG. To better understand the functional consequences of PCa progression and the unique features of the AG subtype, we studied the proteomic signatures of primary AG, NAG and metastatic PCa. 39 PCa and 10 benign prostate controls in a discovery cohort and 57 PCa in a validation cohort were analyzed using a data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using a validation cohort; and was also compared with a TCGA mRNA expression dataset and confirmed by immunohistochemistry (IHC) using PCa tissue microarray (TMA). 4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed reduced expressions of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates and the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using an independently-collected tumor cohort, correlated with a TCGA mRNA dataset, and confirmed by immunohistochemical stains of PCa tumor microarray (TMA). Our study is the first large-scale proteomics analysis of PCa tissue using a DIA SWATH-MS platform. It provides not only an interrogative proteomic signature of PCa subtypes, but also indicates the critical roles played by certain proteinases during tumor progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in PCa and for the development of a clinical assay to distinguish aggressive from indolent PCa.

scholarly journals Serum MiR-4687-3p Has Potential for Diagnosis and Carcinogenesis in Non-small Cell Lung Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Man Liu ◽  
Qiufang Si ◽  
Songyun Ouyang ◽  
Zhigang Zhou ◽  
Meng Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Validation Cohort ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Pathway Enrichment Analysis ◽  
Small Cell Lung ◽  
Invasion And Migration ◽  
Pathway Enrichment ◽  
And Migration

The lack of a useful biomarker partly contributes to the increased mortality of non-small cell lung cancer (NSCLC). MiRNAs have become increasingly appreciated in diagnosis of NSCLC. In the present study, we used microarray to screen 2,549 miRNAs in serum samples from the training cohort (NSCLC, n = 10; the healthy, n = 10) to discover differentially expressed miRNAs (DEMs). Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) assay was applied to validate the expression level of selected overexpressed DEMs of NSCLC in a validation cohort (NSCLC, n = 30; the healthy, n = 30). Area under the receiver operating characteristic curve (AUC) was performed to evaluate diagnostic capability of the DEMs. The expression of the miRNAs in tissues was analyzed based on the TCGA database. Subsequently, the target genes of the miR-4687-3p were predicted by TargetScan. Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were tested by R software (ClusterProfiler package). NSCLC cells were transfected with inhibitor or mimic to down-regulate or up-regulate the miR-4687-3p level. The function of miR-4687-3p on proliferation, invasion, and migration of lung cancer cells were investigated through CCK-8 and Transwell assays, respectively. In the results, we identified serum miR-4687-3p that provided a high diagnostic accuracy of NSCLC (AUC = 0.679, 95%CI: 0.543–0.815) in the validation cohort. According to the TCGA database, we found that the miR-4687-3p level was significantly higher in NSCLC tissues than in normal lung tissues (p < 0.05). GO and KEGG pathway enrichment analysis showed that postsynaptic specialization and TGF-β signaling pathway were significantly enriched. Down-regulation of miR-4687-3p could suppress the proliferation, invasion, and migration of the NSCLC cells, compared with inhibitor negative control (NC). Meanwhile, overexpression of miR-4687-3p could promote the proliferation, invasion, and migration of the NSCLC cells compared with mimic NC. As a conclusion, our study first discovered that serum miR-4687-3p might have clinical potential as a non-invasive diagnostic biomarker for NSCLC and play an important role in the development of NSCLC.

scholarly journals Association between ALS and retroviruses: evidence from bioinformatics analysis

2019 ◽  
Vol 20 (S24) ◽  
Author(s):  
Jon P. Klein ◽  
Zhifu Sun ◽  
Nathan P. Staff
Keyword(s):  
Protein Interaction ◽  
Drug Targets ◽  
Large Scale ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Pathway Enrichment Analysis ◽  
Protein Database ◽  
Core Cluster

Abstract Background Emerging evidence suggests retroviruses play a role in the pathophysiology of amyotrophic lateral sclerosis (ALS). Specifically, activation of ancient viral genes embedded in the human genome is theorized to lead to motor neuron degeneration. We explore whether connections exist between ALS and retroviruses through protein interaction networks (PIN) and pathway analysis, and consider the potential roles in drug target discovery. Protein database and pathway/network analytical software including Ingenuity Pathway BioProfiler, STRING, and CytoScape were utilized to identify overlapping protein interaction networks and extract core cluster (s) of retroviruses and ALS. Results Topological and statistical analysis of the ALS-PIN and retrovirus-PIN identified a shared, essential protein network and a core cluster with significant connections with both networks. The identified core cluster has three interleukin molecules IL10, Il-6 and IL-1B, a central apoptosis regulator TP53, and several major transcription regulators including MAPK1, ANXA5, SQSTM1, SREBF2, and FADD. Pathway enrichment analysis showed that this core cluster is associated with the glucocorticoid receptor singling and neuroinflammation signaling pathways. For confirmation purposes, we applied the same methodology to the West Nile and Polio virus, which demonstrated trivial connectivity with ALS, supporting the unique connection between ALS and retroviruses. Conclusions Bioinformatics analysis provides evidence to support pathological links between ALS and retroviral activation. The neuroinflammation and apoptotic regulation pathways are specifically implicated. The continuation and further analysis of large scale genome studies may prove useful in exploring genes important in retroviral activation and ALS, which may help discover new drug targets.

scholarly journals PPARG Drives Molecular Networks as an Inhibitor for the Pathologic Development and Progression of Lung Adenocarcinoma

PPAR Research ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Min Zhao ◽  
Xiaoyang Li ◽  
Yunxiang Zhang ◽  
Hongming Zhu ◽  
Zhaoqing Han ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Lung Adenocarcinoma ◽  
Large Scale ◽  
Enrichment Analysis ◽  
Molecular Networks ◽  
Pathway Enrichment Analysis ◽  
Molecular Pathways ◽  
Functional Connection ◽  
Regulatory Pathways ◽  
Protein Protein Interaction

Previous studies showed that low PPARG expression was associated with poor prognosis of lung adenocarcinoma (LA) with limited mechanisms identified. We first conducted a large-scale literature-based data mining to identify potential molecular pathways where PPARG could exert influence on the pathological development of LA. Then a mega-analysis using 13 independent LA expression datasets and a Pathway Enrichment Analysis (PEA) was conducted to study the gene expression levels and the functionalities of PPARG and the PPARG-driven triggers within the molecular pathways. Finally, a protein-protein interaction (PPI) network was established to reveal the functional connection between PPARG and its driven molecules. We identified 25 PPARG-driven molecule triggers forming multiple LA-regulatory pathways. Mega-analysis using 13 LA datasets supported these pathways and confirmed the downregulation of PPARG in the case of LA (p=1.07e−05). Results from the PEA and PPI analysis suggested that PPARG might inhibit the development of LA through the regulation of tumor cell proliferation and transmission-related molecules, including an LA tumor cell suppressor MIR145. Our results suggested that increased expression of PPARG could drive multiple molecular triggers against the pathologic development and prognosis of LA, indicating PPARG as a valuable therapeutic target for LA treatment.

Changes in the Protein Profile of Cervical Cancer Mice Xenograft Model in Response to Streblus asper Treatment

2020 ◽  
Vol 20 (3) ◽  
pp. 149
Author(s):  
Muhammad Nabil ◽  
Azman Seeni ◽  
Wan Ismahanisa Ismail ◽  
Mohd Hafiz Mail ◽  
Nurhidayah Ab. Rahim
Keyword(s):  
Cervical Cancer ◽  
Protein Modification ◽  
Protein Profile ◽  
Xenograft Model ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Potential Candidate ◽  
Established Relationship ◽  
Streblus Asper ◽  
External Stimuli

Cervical cancer is the third most prevalent cancer in females (2018) with an estimation of 569,847 incidences and 311,365 deaths worldwide despite the rapid advancement of current technology in treating cervical cancer. Radiotherapy and chemotherapy pose side effects and subsequently hinder treatment efficacy. Therefore, taken together with the previous reports of the plants’ ability in treating cancers,<em> Streblus asper</em> is suggested to be a potential candidate for cervical cancer. This study was conducted to investigate the anti-cervical cancer potential of <em>Streblus asper</em> through the identification of key proteins and their expression that are regulated in the treatment using mice xenograft model. By employing the use of Liquid Chromatography Mass Spectrometry (LCMS), several proteins associated with cancer growth mechanisms were successfully identified. Four-hundred and fifty-two proteins common to both groups were identified, and 122 proteins were found able to be quantified. Among those proteins, 52 proteins were expressed more than 2-fold changes and 12 proteins were selected based on its established relationship with cancers, including annexin A2, 14-3-3 protein, transgelin-2, galectin-1, keratin, heat shock protein 10 and 70, glucose regulated protein (78kDa), gelsolin, alpha enolase, cofilin-1, vimentin, and calreticulin. All these proteins were downregulated upon treatment of cervical cancer tumour by <em>Streblus asper.</em> Pathway enrichment analysis revealed 40 related pathways which include among others, metabolism of protein, post-translational protein modification, cellular responses to external stimuli and stress, cell cycle, and apoptosis. These analyses may improve our molecular insight of the mechanisms involved in the treatment of cervical cancer tumour by <em>Streblus asper</em> extract.

scholarly journals Genetics of Behçet's Disease: Functional Genetic Analysis and Estimating Disease Heritability

2021 ◽  
Vol 8 ◽  
Author(s):  
Lourdes Ortiz-Fernández ◽  
Amr H. Sawalha
Keyword(s):  
Behçet’S Disease ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Behcet’S Disease ◽  
Behçet's Disease ◽  
Enrichment Analysis ◽  
Genetic Component ◽  
Pathway Enrichment Analysis ◽  
Inflammatory Disorder ◽  
Behcet's Disease

Behçet's disease is a chronic multisystemic inflammatory disorder characterized by recurrent oral and genital ulcers. Although its etiology remains unclear, it is thought that both genetic and environmental factors contribute to the onset and progression of Behçet's disease. Here, we provide an updated view of the genetic landscape and architecture of Behçet's disease. Large-scale genetic studies performed to date revealed 21 genetic susceptibility loci associated with the disease at a GWAS level of significance (p-value = 5 × 10−8). We performed epigenetic pattern enrichment analysis in Behçet's disease associated loci, providing new insights into the molecular mechanisms underlying its pathophysiology. Our data suggest the crucial involvement of several immune cell types, including natural killer cells, monocytes, and B cells in the pathogenesis of the disease. Pathway enrichment analysis identified important biological processes involved. Using large-scale genetic data available from ~200 immune-related loci (Immunochip), we estimate Behçet's disease heritability to be at least 16%. We further used the same approach to estimate the heritability explained by the known Behçet's disease-associated loci, suggesting that they explain ~ 60% of the genetic component underlying Behçet's disease. These results indicate a significant role of non-genetic factors in causing Behçet's disease and that additional genetic variation influencing the risk of Behçet's disease remains to be identified. Finally, we calculated a cumulative genetic risk score across populations reinforcing the link between geographic variations in disease prevalence with its genetic component.

scholarly journals Genome-Wide Identification and Characterization of Potato Long Non-coding RNAs Associated With Phytophthora infestans Resistance

2021 ◽  
Vol 12 ◽  
Author(s):  
Weilin Cao ◽  
Liming Gan ◽  
Chenchen Wang ◽  
Xuechen Zhao ◽  
Mingyu Zhang ◽  
...  
Keyword(s):  
Phytophthora Infestans ◽  
Large Scale ◽  
Learning Algorithm ◽  
Enrichment Analysis ◽  
R Package ◽  
Pathway Enrichment Analysis ◽  
Similar Distribution ◽  
Sequencing Data ◽  
Biotic And Abiotic Stress ◽  
Characteristic Analysis

Long non-coding RNA (lncRNA) is a crucial regulatory mechanism in the plant response to biotic and abiotic stress. However, their roles in potato (Solanum tuberosum L.) resistance to Phytophthora infestans (P. infestans) largely remain unknown. In this study, we identify 2857 lncRNAs and 33,150 mRNAs of the potato from large-scale published RNA sequencing data. Characteristic analysis indicates a similar distribution pattern of lncRNAs and mRNAs on the potato chromosomes, and the mRNAs were longer and had more exons than lncRNAs. Identification of alternative splicing (AS) shows that there were a total of 2491 lncRNAs generated from AS and the highest frequency (46.49%) of alternative acceptors (AA). We performed R package TCseq to cluster 133 specific differentially expressed lncRNAs from resistance lines and found that the lncRNAs of cluster 2 were upregulated. The lncRNA targets were subject to KEGG pathway enrichment analysis, and the interactive network between lncRNAs and mRNAs was constructed by using GENIE3, a random forest machine learning algorithm. Transient overexpression of StLNC0004 in Nicotiana benthamiana significantly suppresses P. infestans growth compared with a control, and the expression of extensin (NbEXT), the ortholog of the StLNC0004 target gene, was significantly upregulated in the overexpression line. Together, these results suggest that lncRNAs play potential functional roles in the potato response to P. infestans infection.

scholarly journals Accumulation of Minor Alleles of Common SNPs in Schizophrenia

2017 ◽  
Author(s):  
Pei He ◽  
Xiaoyun Lei ◽  
Dejian Yuan ◽  
Zuobin Zhu ◽  
Shi Huang
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Enrichment Analysis ◽  
Individual Risk ◽  
Pathway Enrichment Analysis ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Risk Alleles ◽  
Minor Alleles ◽  
Public Datasets

Schizophrenia is a common neuropsychiatric disorder with a lifetime risk of 1%. A number of large scale genome wide association studies have identified numerous individual risk single nucleotide polymorphisms (SNPs) whose precise roles in schizophrenia remain unknown. Accumulation of many of these risk alleles has been found to be a more important risk factor. Consistently, recent studies showed a role for enrichment of minor alleles (MAs) in complex diseases. Here we studied the role of MAs in general in schizophrenia using public datasets. Relative to matched controls, schizophrenia cases showed higher minor allele content (MAC), especially for the sporadic cases. By linkage analysis, we identified 82 419 SNPs that could be used to predict 2.2% schizophrenia cases with 100% certainty. Pathway enrichment analysis of these SNPs identified 17 pathways, 15 of which are known to be linked with Schizophrenia with the remaining 2 associated with other mental disorders. These results suggest a role for a collective effect of MAs in schizophrenia and provide a method to genetically screen for schizophrenia.

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