scholarly journals The pattern of gene copy number variations (CNVs) in hepatocellular carcinoma; in silico analysis

2020 ◽  
Author(s):  
Hossein Ansari ◽  
Arman Shahrisa ◽  
Maryam Tahmaseby ◽  
Zahra Mohammadi ◽  
Vinicio Carloni ◽  
...  
Keyword(s):  
Tumor Suppressor ◽  
In Silico ◽  
Copy Number ◽  
In Silico Analysis ◽  
Multivesicular Body ◽  
Copy Number Variations ◽  
Molecular Networks ◽  
Gene Copy ◽  
Body Protein ◽  
Silico Analysis

Abstract Cancer-associated death is the second leading cause of death worldwide. Study of the involved molecular networks of cancers can identify the potential target for early diagnosis, efficient therapies, and predictive prognosis of patients with cancer. Copy number variations are one type of DNA mutations which has been connected with human cancers. The CNVs can be used to find the regions of the genome involved in cancer phenotypes. This study is aimed to perform genome-wide chromosomal CNVs in HCC samples to find hotspot regions of disease using in silico analysis. The obtained data showed that gain of chromosome 1q and loss of 8p were frequently observed in target cancerous tissues. All the gains and losses were associated with tumor grade and metastasis. However, the amplification of YY1AP1 (Yin Yang-1 Associated Protein 1) and deletion of CHMP7 (Charged Multivesicular Body Protein 7) were observed in most of patients. These expression levels of YY1AP1 and CHMP7 were also upregulated and downregulated in cancerous samples respectively. Additionally, these two genes interact with critical oncogene and tumor suppressor genes like MDM2 (Mouse double minute 2 homolog) and VHL (von Hippel-Lindau tumor suppressor) showing the potential of these genes in HCC pathogenesis. Based on the observed data we suggest the 1q and 8p as candidate regions for HCC for researches especially YY1AP1 and CHMP7 loci.

scholarly journals The pattern of gene copy number alteration (CNAs) in hepatocellular carcinoma: an in silico analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Arman Shahrisa ◽  
Maryam Tahmasebi-Birgani ◽  
Hossein Ansari ◽  
Zahra Mohammadi ◽  
Vinicio Carloni ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
In Silico ◽  
Copy Number ◽  
Copy Number Alteration ◽  
Gene Copy Number ◽  
In Silico Analysis ◽  
Gene Copy ◽  
Sequencing Data ◽  
Silico Analysis

Abstract Background Hepatocellular carcinoma (HCC) is the most common type of liver cancer that occurs predominantly in patients with previous liver conditions. In the absence of an ideal screening modality, HCC is usually diagnosed at an advanced stage. Recent studies show that loss or gain of genomic materials can activate the oncogenes or inactivate the tumor suppressor genes to predispose cells toward carcinogenesis. Here, we evaluated both the copy number alteration (CNA) and RNA sequencing data of 361 HCC samples in order to locate the frequently altered chromosomal regions and identify the affected genes. Results Our data show that the chr1q and chr8p are two hotspot regions for genomic amplifications and deletions respectively. Among the amplified genes, YY1AP1 (chr1q22) possessed the largest correlation between CNA and gene expression. Moreover, it showed a positive correlation between CNA and tumor grade. Regarding deleted genes, CHMP7 (chr8p21.3) possessed the largest correlation between CNA and gene expression. Protein products of both genes interact with other cellular proteins to carry out various functional roles. These include ASH1L, ZNF496, YY1, ZMYM4, CHMP4A, CHMP5, CHMP2A and CHMP3, some of which are well-known cancer-related genes. Conclusions Our in-silico analysis demonstrates the importance of copy number alterations in the pathology of HCC. These findings open a door for future studies that evaluate our results by performing additional experiments.

scholarly journals The pattern of gene copy number variations (CNVs) in hepatocellular carcinoma; in silico analysis

2021 ◽  
Author(s):  
Arman Shahrisa ◽  
Maryam Tahmaseby ◽  
Hossein Ansari ◽  
Zahra Mohammadi ◽  
Vinicio Carloni ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Tumor Suppressor ◽  
In Silico ◽  
Tumor Suppressor Genes ◽  
Copy Number ◽  
Gene Copy ◽  
Suppressor Genes ◽  
Body Protein ◽  
Yin Yang 1 ◽  
Yin Yang

Abstract Recent studies showed that genetic lost or gain in the genome can predispose cells toward malignancy. Hepatocellular carcinoma (HCC) is the most common type of liver cancer which occurs predominantly in patients with underlying chronic liver disease and cirrhosis. Prognosis of HCC is strongly connected with diagnostic delay. To date, no ideal screening modality has been developed for HCC. Recent findings demonstrated that Copy number variation (CNVs) can lead to activation of oncogenes and inactivation of tumor suppressor genes in cancers. In this study, CNV profile of 361 HCC samples was evaluated to reveal the potent - chromosomal regions involved in the disease. The obtained data showed that the chr1q and chr8p were two hotspot regions for gene amplifications and deletions in studied samples respectively. In this research, YY1AP1 (Yin Yang-1 Associated Protein 1) on chr1q22 was the most amplified gene in HCC samples and showed the positive correlation with tumor grade. Deletion of CHMP7 (Charged Multivesicular Body Protein 7) on chr8p21.3 was another frequently observed CNV among HCC patients. Both genes were interacted with variety of well-known oncogenes and tumor suppressor genes including YY1 (Yin Yang 1), CCND1 (Cyclin D1), HDAC1 (Histone deacetylase 1), VHL (von Hippel-Lindau tumor suppressor), MAD2L2 (Mitotic Arrest Deficient 2 Like 2), CEBPA (CCAAT/enhancer-binding protein alpha), CHMP4A, CHMP5, CHMP2A, CHMP3 and ENSG00000249884 (RNF103-CHMP3 gene), all of them are well-known in carcinogenesis. Although this study was based on in silico evaluations, our findings can open a new window for researchers of HCC to focus on such candidate genes during experimental assays.

scholarly journals Copy number variant detection with low-coverage whole-genome sequencing is a viable replacement for the traditional array-CGH

2020 ◽  
Author(s):  
Marcel Kucharik ◽  
Jaroslav Budis ◽  
Michaela Hyblova ◽  
Gabriel Minarik ◽  
Tomas Szemes
Keyword(s):  
In Silico ◽  
Copy Number ◽  
Normal Population ◽  
Genetic Disorders ◽  
Prenatal Testing ◽  
In Silico Analysis ◽  
Copy Number Variant ◽  
Detection Algorithm ◽  
Copy Number Variations ◽  
Cnv Detection

Copy number variations (CNVs) are a type of structural variant involving alterations in the number of copies of specific regions of DNA, which can either be deleted or duplicated. CNVs contribute substantially to normal population variability; however, abnormal CNVs cause numerous genetic disorders. Nowadays, several methods for CNV detection are used, from the conventional cytogenetic analysis through microarray-based methods (aCGH) to next-generation sequencing (NGS). We present GenomeScreen - NGS based CNV detection method based on a previously described CNV detection algorithm used for non-invasive prenatal testing (NIPT). We determined theoretical limits of its accuracy and confirmed it with extensive in-silico study and already genotyped samples. Theoretically, at least 6M uniquely mapped reads are required to detect CNV with a length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in-silico analysis showed the requirement at least 8M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has a 200 kb mean resolution. GenomeScreen and aCGH both detected 59 deviations, GenomeScreen furthermore detected 134 other (usually) smaller variations. Furthermore, the overall cost per sample is about 2-3x lower in the case of GenomeScreen.

scholarly journals A comprehensive molecular characterization of the 8q22.2 region reveals the prognostic relevance of OSR2 mRNA in muscle invasive bladder cancer

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248342
Author(s):  
Daniel Uysal ◽  
Karl-Friedrich Kowalewski ◽  
Maximilian Christian Kriegmair ◽  
Ralph Wirtz ◽  
Zoran V. Popovic ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
In Silico ◽  
Copy Number ◽  
In Silico Analysis ◽  
Copy Number Alterations ◽  
Muscle Invasive Bladder Cancer ◽  
Mrna Gene ◽  
Muscle Invasive ◽  
Silico Analysis

Technological advances in molecular profiling have enabled the comprehensive identification of common regions of gene amplification on chromosomes (amplicons) in muscle invasive bladder cancer (MIBC). One such region is 8q22.2, which is largely unexplored in MIBC and could harbor genes with potential for outcome prediction or targeted therapy. To investigate the prognostic role of 8q22.2 and to compare different amplicon definitions, an in-silico analysis of 357 patients from The Cancer Genome Atlas, who underwent radical cystectomy for MIBC, was performed. Amplicons were generated using the GISTIC2.0 algorithm for copy number alterations (DNA_Amplicon) and z-score normalization for mRNA gene overexpression (RNA_Amplicon). Kaplan-Meier survival analysis, univariable, and multivariable Cox proportional hazard ratios were used to relate amplicons, genes, and clinical parameters to overall (OS) and disease-free survival (DFS). Analyses of the biological functions of 8q22.2 genes and genomic events in MIBC were performed to identify potential targets. Genes with prognostic significance from the in silico analysis were validated using RT-qPCR of MIBC tumor samples (n = 46). High 8q22.2 mRNA expression (RNA-AMP) was associated with lymph node metastases. Furthermore, 8q22.2 DNA and RNA amplified patients were more likely to show a luminal subtype (DNA_Amplicon_core: p = 0.029; RNA_Amplicon_core: p = 0.01). Overexpression of the 8q22.2 gene OSR2 predicted shortened DFS in univariable (HR [CI] 1.97 [1.2; 3.22]; p = 0.01) and multivariable in silico analysis (HR [CI] 1.91 [1.15; 3.16]; p = 0.01) and decreased OS (HR [CI] 6.25 [1.37; 28.38]; p = 0.0177) in RT-qPCR data analysis. Alterations in different levels of the 8q22.2 region are associated with manifestation of different clinical characteristics in MIBC. An in-depth comprehensive molecular characterization of genomic regions involved in cancer should include multiple genetic levels, such as DNA copy number alterations and mRNA gene expression, and could lead to a better molecular understanding. In this study, OSR2 is identified as a potential biomarker for survival prognosis.

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

In-Silico Analysis of Chromone Containing Sulfonamide Derivatives as Human Carbonic Anhydrase Inhibitors

2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas
Keyword(s):  
Carbonic Anhydrase ◽  
In Silico ◽  
In Silico Analysis ◽  
Carbonic Anhydrase Inhibitors ◽  
Human Carbonic Anhydrase ◽  
Silico Analysis
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