ePoster Display session ePoster

48P - Target mining and drug repurposing for hepatocellular carcinoma via bioinformatic and computational approaches (ID 267)

Presentation Number
48P
Lecture Time
14:16 - 14:16
Speakers
  • Gouri Nair (Bangalore, India)
Session Name
ePoster Display session
Room
ePoster gallery
Date
Tue, 02.03.2021
Time
08:00 - 20:00
Authors
  • Gouri Nair (Bangalore, India)
  • Ganesan Rajalekshmi Saraswathy (Bangalore, India)
  • G.N.S Hema Sree (Bangalore, India)

Abstract

Background

Sorafenib is the only therapy to treat hepatocellular carcinoma (HCC), yet offers limited survival benefits due to drug resistance. Advanced oncotherapeutic research demands a thorough insight into pathological cascades involved in the progression of preneoplastic lesions to HCC. Hence, target mining to unearth key genetic players of HCC followed by screening drug databases against the identified targets will be a rational way forward.

Methods

GSE6764 gene expression profile dataset encompassing microarray data of 10 normal, 10 cirrhosis, 17 dysplastic nodules, 18 early and 17 advanced HCC was analyzed using GEO2R. Subsequently, a protein-protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes and visualized through Cytoscape. Crucial targets were identified based on the overall survival (OS) and hazard ratio (HR > 1) of hub genes from the Kaplan-Meier plotter. The identified targets were screened against all FDA-approved drugs by molecular docking studies through extra precision mode (XP) in the Schrodinger drug design suite. Further, the free energy of binding of shortlisted drugs was evaluated by MM/GBSA analysis.

Results

STAT1 and MX1 are substantially overexpressed in cirrhosis while, CCL19 and IL7R are significantly downregulated between dysplastic nodule and cirrhosis. HMMR overexpression is linked with poor prognosis in the evolution of dysplastic nodule to early HCC. Furthermore, overexpression of pathological hallmarks of poor prognosis such as CDK1, CDC20, BUB1, MAD2L1, CCNB2, CENPF, TPX2, TOP2A and PBK was identified in the furtherance from early and advanced HCC. Based on OS with significant HR, CDC20 was shortlisted and subjected to molecular docking and MM-GBSA analysis. Labetalol, a beta-blocker was spotlighted as a hit due to its highest docking score of -7.075, ΔG value -54.08 kcal/mol alongside its stable and stronger ligand-protein complex.

Conclusions

This study reveals a series of key cross-talk genetic underpinnings from pre-neoplastic lesions to HCC and suggests the pertinence of labetalol as a potential repurposable drug in the treatment for HCC.

Legal entity responsible for the study

Gouri Nair.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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