scholarly journals Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Carlos Roberto Arias ◽  
Hsiang-Yuan Yeh ◽  
Von-Wun Soo
Keyword(s):  
Prostate Cancer ◽  
Protein Interaction ◽  
Microarray Data ◽  
Shortest Paths ◽  
Gene Prioritization ◽  
The Other ◽  
Biomarker Identification ◽  
Lymph Nodes Metastasis ◽  
Prioritization Method ◽  
Voting Scheme

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well.

scholarly journals A computational and structural analysis of germline and somatic variants affecting the DDR mechanism, and their impact on human diseases

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lorena Magraner-Pardo ◽  
Roman A. Laskowski ◽  
Tirso Pons ◽  
Janet M. Thornton
Keyword(s):  
Prostate Cancer ◽  
Dna Damage ◽  
Dna Damage Response ◽  
Protein Interaction ◽  
Three Dimensional ◽  
Protein Protein Interaction ◽  
Variants Of Unknown Significance ◽  
Damage Response ◽  
Dna Variants ◽  
Unknown Significance

AbstractDNA-Damage Response (DDR) proteins are crucial for maintaining the integrity of the genome by identifying and repairing errors in DNA. Variants affecting their function can have severe consequences since failure to repair damaged DNA can result in cells turning cancerous. Here, we compare germline and somatic variants in DDR genes, specifically looking at their locations in the corresponding three-dimensional (3D) structures, Pfam domains, and protein–protein interaction interfaces. We show that somatic variants in metastatic cases are more likely to be found in Pfam domains and protein interaction interfaces than are pathogenic germline variants or variants of unknown significance (VUS). We also show that there are hotspots in the structures of ATM and BRCA2 proteins where pathogenic germline, and recurrent somatic variants from primary and metastatic tumours, cluster together in 3D. Moreover, in the ATM, BRCA1 and BRCA2 genes from prostate cancer patients, the distributions of germline benign, pathogenic, VUS, and recurrent somatic variants differ across Pfam domains. Together, these results provide a better characterisation of the most recurrent affected regions in DDRs and could help in the understanding of individual susceptibility to tumour development.

scholarly journals GAMBARAN KEJADIAN KANKER PROSTAT PADA PENDERITA DIABETES MELLITUS DI RSUP H. ADAM MALIK MEDAN

2018 ◽  
Vol 1 (1) ◽  
pp. 52-56
Author(s):  
Surya Martua Horas Harahap
Keyword(s):  
Prostate Cancer ◽  
Diabetes Mellitus ◽  
Prostate Cancer Patient ◽  
Transitional Cell ◽  
Descriptive Study ◽  
The Other ◽  
Genetic Mutations ◽  
Cross Sectional ◽  
Prostatic Gland ◽  
Age Range

According to Kemenkes RI, in 2013, the number of prostate cancer patient is 0.2% or approximately 25,012 patients. Prostate cancer is a malignancy in the prostatic gland and more than 95% of prostate cancer is adenocarcinoma, the other 5% is transitional cell and neuroendocrine carcinoma or sarcoma. Up to now, the etiology of prostate cancer is still unknown, but it involves multifactor and genetic mutations. This study is a descriptive study design with a retrospective cross sectional in the Urology Division of the Department of Surgery, General Hospital of H. Adam Malik Medan during period January to December 2014. From this study we found about 261 patients of Diabetes Mellitus who visited surgery, but only as many as 41 people (15.7%) performed prostate biopsy, and of the 41 people who had the most prostate cancer were 24 people (58.5%). The highest age range was 70-74 years (37.5%), with PSA values more than 50 ng / ml as much (33.3%), and the highest Gleason score in the range of 5-6 (50%)

scholarly journals Identification ofInfluenza A/H7N9 Virus Infection-Related Human Genes Based on Shortest Paths in a Virus-Human Protein Interaction Network

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Ning Zhang ◽  
Min Jiang ◽  
Tao Huang ◽  
Yu-Dong Cai
Keyword(s):  
Virus Infection ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Influenza A ◽  
Shortest Paths ◽  
Interaction Network ◽  
Human Protein ◽  
H7n9 Virus ◽  
Human Protein Interaction ◽  
Human Genes

The recently emergingInfluenza A/H7N9 virus is reported to be able to infect humans and cause mortality. However, viral and host factors associated with the infection are poorly understood. It is suggested by the “guilt by association” rule that interacting proteins share the same or similar functions and hence may be involved in the same pathway. In this study, we developed a computational method to identifyInfluenza A/H7N9 virus infection-related human genes based on this rule from the shortest paths in a virus-human protein interaction network. Finally, we screened out the most significant 20 human genes, which could be the potential infection related genes, providing guidelines for further experimental validation. Analysis of the 20 genes showed that they were enriched in protein binding, saccharide or polysaccharide metabolism related pathways and oxidative phosphorylation pathways. We also compared the results with those from human rhinovirus (HRV) and respiratory syncytial virus (RSV) by the same method. It was indicated that saccharide or polysaccharide metabolism related pathways might be especially associated with the H7N9 infection. These results could shed some light on the understanding of the virus infection mechanism, providing basis for future experimental biology studies and for the development of effective strategies for H7N9 clinical therapies.

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