Distinct Prognostic Values of BCL2 Anti-apoptotic Members in Lung Cancer: An In-Silico Analysis

2021 ◽  
pp. 345-353
Author(s):  
Pooja Mittal ◽  
Indrakant Kumar Singh ◽  
Archana Singh
Keyword(s):  
Lung Cancer ◽  
In Silico ◽  
In Silico Analysis ◽  
Silico Analysis

Distribution and pathogenicity of nsSNPs in receptor tyrosine kinases (RTKs) in non-small cell lung cancer (NSCLC) patients (pts).

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e20618-e20618
Author(s):  
Ari M. Vanderwalde ◽  
Matthew K Stein ◽  
Lindsay Kaye Morris ◽  
Srishti Sareen ◽  
Saradasri Karri ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tyrosine Kinases ◽  
In Silico ◽  
Transmembrane Domain ◽  
Stage Iv ◽  
In Silico Analysis ◽  
Large Cell ◽  
Kinase Domain ◽  
Tyrosine Kinase Domain ◽  
Silico Analysis

e20618 Background: Non-synonymous SNPs (nsSNPs) in RTKs can alter kinase activity and are not exclusive to the tyrosine kinase domain (TKD). In NSCLC, EGFR lesions were previously identified using TKD-limited tests; however, next-generation sequencing (NGS) enables the entire protein sequence of many RTKs to be interrogated. Methods: We analyzed all nsSNPs in 28 RTKs in lung cancer pts who received tumor profiling with Caris NGS from 2013-2015. Mutations were classified by location including the TKD, extracellular domain (ECD), transmembrane domain (TM), juxtamembrane domain (JM), and carboxy-terminal (CT) regions. nsSNPs underwent in silico analysis using PolyPhen-2 (Harvard) to predict pathogenicity. Results: 167 pts (156 NSCLC, 11 SC) were identified with a median age 65 (range 26-85); 51% male; 65% white, 31% black; 77% ≥20 pack-years (py), 11% non-smokers; 52% samples tested were metastases. NSCLC pts were 63% adenocarcinoma, 22%, squamous, 8% large-cell; 81% stage IV, 14% III; 17 were EGFR+, 6 BRAF+, 3 HER2+, 3 ROS1 rearranged and 1 MET exon 14. A total 300 nsSNPs (286 NSCLC, 14 SC) were found in 28 RTKs, excluding EGFR. 123/156 NSCLC pts (79%) and 9/11 SC (82%) had ≥1 RTK lesion with median 2 (range 0-8); 143/300 (48%) nsSNPs were predicted-damaging (pnsSNP) by in silico and 89 pts (53%) had ≥1 pnsSNP (median 1; range 0-5). 28/28 RTKs had ≥3 mutations, with median 11 (range 3-23), and 26/28 contained ≥1 pnsSNP (median 5; range 0-14). RTKs in NSCLC with the most frequent nsSNPs were EPHA3 (14/23 variants were pnsSNP), EPHA5 (11/17), EPHB1 (10/11), RET (9/11), ERBB4 (8/12), ALK (7/16), NTRK3 (7/15), ROS1 (6/22) and FLT1 (6/15). 6/14 lesions in SC pts were pnsSNPs in ERBB3, ERBB4, FGFR1, FLT1, RET and ROS1. nsSNPs were found along RTKs: 57% were ECD (72/172 pnsSNP), 26% TKD (47/77), 10% CT (14/29), 6% JM (8/18) and 1% TM (2/4). 6/6 SC pnsSNPs were ECD. 67% BRAF+ and ROS1-rearranged, 59% EGFR+, 33% HER2+ and 0/1 MET exon 14 pts had ≥1 pnsSNP. Conclusions: Nearly 80% NSCLC and SC pts had ≥1 nsSNP in 28 RTKs, excluding EGFR, with 48% pnsSNPs by in silico analysis. As > 70% nsSNPs were extra-TKD lesions, further characterization is needed to identify kinase-effecting variants and their potential clinical significance.

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

In Silico Analysis of Single Nucleotide Polymorphism in Human Prothrombin Gene

2019 ◽  
Author(s):  
I. Farah ◽  
A. El-Mubark ◽  
M. Osman ◽  
A. Soliman ◽  
F. Ali ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
In Silico ◽  
In Silico Analysis ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Prothrombin Gene ◽  
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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