Investigation of Precise Molecular Mechanistic Action of Tobacco-Associated Carcinogen `NNK´ Induced Carcinogenesis: A System Biology Approach.

Clicks: 454
ID: 32067
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #4 of 80 articles by views in genes

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Cancer is the second deadliest disease listed by the WHO. One of the major causes of cancer disease is tobacco and consumption possibly due to its main component, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). A plethora of studies have been conducted in the past aiming to decipher the association of NNK with other diseases. However, it is strongly linked with cancer development. Despite these studies, a clear molecular mechanism and the impact of NNK on various system-level networks is not known. In the present study, system biology tools were employed to understand the key regulatory mechanisms and the perturbations that will happen in the cellular processes due to NNK. To investigate the system level influence of the carcinogen, NNK rewired protein-protein interaction network (PPIN) was generated from 544 reported proteins drawn out from 1317 articles retrieved from PubMed. The noise was removed from PPIN by the method of modulation. Gene ontology (GO) enrichment was performed on the seed proteins extracted from various modules to find the most affected pathways by the genes/proteins. For the modulation, Molecular COmplex DEtection (MCODE) was used to generate 19 modules containing 115 seed proteins. Further, scrutiny of the targeted biomolecules was done by the graph theory and molecular docking. GO enrichment analysis revealed that mostly cell cycle regulatory proteins were affected by NNK.
Reference Key
nolastname2019investigationgenes Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors , ;Dhasmana, Anupam;Uniyal, Swati;Somvanshi, Pallavi;Bhardwaj, Uma;Gupta, Meenu;Haque, Shafiul;Lohani, Mohtashim;Kumar, Dhruv;Ruokolainen, Janne;Kesari, Kavindra Kumar;
Journal genes
Year 2019
DOI
E564
URL
Keywords
photo-electric characteristics process optimization pyramidal texture quantitative characterization relative standard deviation silicon cell

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.