Volume 33, Issue 161 (November & December 2025)                   J Adv Med Biomed Res 2025, 33(161): 4-4 | Back to browse issues page

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Jha A K, Almoyad M A A, Wahab S, Gupta G, Goh K W, Sahebkar A et al . Computational Identification of Dysregulated Genes and Pathways in Non-Small Cell Lung Cancer: A Systems Biology Approach. J Adv Med Biomed Res 2025; 33 (161) :4-4
URL: http://journal.zums.ac.ir/article-1-7825-en.html
Computational Identification of Dysregulated Genes and Pathways in Non-Small Cell Lung Cancer: A Systems Biology Approach
Aditya Kumar Jha1 , Mohammad Ali Abdullah Almoyad2 , Shadma Wahab2 , Garima Gupta3 , Khang Wen Goh4 , Amirhossein Sahebkar *5 , Prashant Kesharwani6
1- High-School Junior, VIBGYOR High School, Mumbai
2- King Khalid University, Abha, Khamis Mushyt, PO Box. 4536, ZIP., 61412 Saudi Arabia
3- Graphic Era Hill University, Dehradun, 248002, India
4- Faculty of Data Science and Information Technology, INTI International University, Nilai, Malaysia
5- Mashhad University of Medical Sciences, Mashhad, Iran , amir_saheb2000@yahoo.com
6- Department of Pharmaceutical Sciences, Dr. Harisingh Gour Vishwavidyalaya, Sagar, Madhya Pradesh, 470003, India
Abstract:   (10 Views)
Non-small cell lung cancer (NSCLC) is the most prevalent form of lung malignancy globally and remains a leading cause of cancer-related mortality. This study presents a systematic bioinformatics-based investigation aimed at identifying differentially expressed genes (DEGs) and potential therapeutic targets associated with NSCLC. Publicly available RNA expression datasets were analyzed using advanced in silico tools, including the enrichr() function from the GSEApy package and R statistical software (v4.3.1), to uncover molecular pathways involved in disease progression. Key oncogenic signaling pathways such as TGF-β signaling, Wnt/β-catenin, PI3K-AKT-mTOR, and MAPK were found to be significantly associated with genes including AGER, ANK3, CSTA, FGG, AGR2, BRCA1, HDAC1, miR-577, TRIM29, PIK3CA, and JNK. Pathway enrichment analysis further identified significant involvement in chronic myeloid leukemia, longevity regulation, thyroid hormone signaling, viral carcinogenesis, Epstein-Barr virus infection, and microRNAs in cancer. The correlation analysis revealed that TRIM29 was highly expressed in control samples, while AGR2 showed prominent expression in NSCLC samples. Additionally, HDAC1 and BRCA1 emerged as promising diagnostic biomarkers. These findings enhance our understanding of NSCLC pathogenesis and highlight novel molecular candidates for the development of more effective, personalized therapeutic strategies, potentially improving clinical outcomes for patients.
Keywords: Non-small cell lung cancer (NSCLC), Bioinformatics analysis, Differentially expressed genes (DEGs), Pathway enrichment, RNA-seq, Therapeutic targets
     
Type of Study: Original Research Article | Subject: Life Science
Received: 2025/08/16 | Accepted: 2025/11/11 | Published: 2025/12/12
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