Inferring therapeutic targets from heterogeneous data: HKDC1 is a novel potential therapeutic target for cancer

Gong-Hua Li1, Jing-Fei Huang

  • 1State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences and Kunming Institute of Zoology, Chinese University of Hongkong Joint Research Center for Bio-resources and Human Disease Mechanisms, Kunming, Yunnan 650223, China.

Abstract

Insights

Computational biology methods identify novel cancer therapeutic targets. A new analysis reveals HKDC1 as a promising target for lung cancer treatment, with potential for drug development.

Area of Science:

  • Computational biology
  • Genomics
  • Cancer research

Background:

  • Cancer remains a significant global health challenge despite numerous therapeutic targets.
  • Advancements in cancer-related data necessitate innovative computational approaches for target discovery.

Purpose of the Study:

  • To develop and validate a computational method for identifying novel therapeutic targets in cancer.
  • To predict potential drug targets for lung cancer using integrated biological data.

Main Methods:

  • Anticancer activity enrichment analysis was employed to identify potential therapeutic genes.
  • Gene expression data was combined with the analysis to predict candidate targets.

Main Results:

  • The developed method demonstrated a high likelihood (>60%) of identifying clinically relevant targets.
  • Fifty candidate targets for lung cancer were predicted; 19 of the top 20 are already in clinical development.
  • Hexokinase domain-containing protein 1 (HKDC1) was identified as a novel potential target not yet in clinical trials.

Conclusions:

  • A robust protocol for identifying potential therapeutic targets from heterogeneous data was established.
  • HKDC1 is proposed as a novel and promising therapeutic target for lung cancer.

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