Network‐based identification of key proteins and repositioning of drugs for non‐small cell lung cancer

Abstract

Background

NSCLC is a lethal cancer that is highly prevalent and accounts for 85% of cases of lung cancer. Conventional cancer treatments, such as chemotherapy and radiation, frequently exhibit limited efficacy and notable adverse reactions. Therefore, a drug repurposing method is proposed for effective NSCLC treatment.

Aims

This study aims to evaluate candidate drugs that are effective for NSCLC at the clinical level using a systems biology and network analysis approach.

Methods

Differentially expressed genes in transcriptomics data were identified using the systems biology and network analysis approaches. A network of gene co‐expression was developed with the aim of detecting two modules of gene co‐expression. Following that, the Drug–Gene Interaction Database was used to find possible drugs that target important genes within two gene co‐expression modules linked to non‐small cell lung cancer (NSCLC). The use of Cytoscape facilitated the creation of a drug–gene interaction network. Finally, gene set enrichment analysis was done to validate candidate drugs.

Results

Unlike previous research on repositioning drugs for NSCLC, which uses a gene co‐expression network, this project is the first to research both gene co‐expression and co‐occurrence networks. And the co‐occurrence network also accounts for differentially expressed genes in cancer cells and their adjacent normal cells. For effective management of non‐small cell lung cancer (NSCLC), drugs that show higher gene regulation and gene affinity within the drug–gene interaction network are thought to be important. According to the discourse, NSCLC genes have a lot of control over medicines like vincristine, fluorouracil, methotrexate, clotrimazole, etoposide, tamoxifen, sorafenib, doxorubicin, and pazopanib.

Conclusion

Hence, there is a possibility of repurposing these drugs for the treatment of non‐small‐cell lung cancer.