Identification of differentially expressed genes in small and non-small cell lung cancer based on meta-analysis of
Nitesh Shriwash1, Prithvi Singh2, Shweta Arora3
1Department of Computer Science, Faculty of Natural Science, Jamia Millia Islamia, New Delhi, 110025, India.
Abstract:
Lung cancer has the lowest survival rate spread globally resulting in a large number of deaths. This is attributed to insufficient measures such as lack of early detection and chemoresistance in the patients. It can be subdivided into two histological groups: Non-Small-Cell Lung Cancer (NSCLC), which is most prevalent (85% of all lung cancers) but less destructive; and Small-Cell Lung Cancer (SCLC), which is intermittently metastatic and less prevalent (15% of all lung cancers). The present study deals with the analysis of gene expression of two subtypes to identify the Differentially Expressed Genes (DEGs). For this study, we selected two datasets from the Omnibus database, which included 50 non-small cell lung cancer samples, 31 small cell lung cancer samples, and 48 samples from normal lung tissue. After DEGs identification using the meta-analysis approach, they were then subjected to further analysis following p-value adjustment via the Benjamini-Hochberg method. We identified 440 overexpressed and 489 underexpressed genes in NSCLC, and 489 overexpressed and 525 underexpressed genes in SCLC, compared with normal lung tissues. Furthermore, we identified 3 overlapping genes between upregulated DEGs in NSCLC and downregulated DEGs in SCLC; and 8 overlapping genes between upregulated DEGs in SCLC and downregulated DEGs in NSCLC. Accordingly, a Protein-Protein Interaction (PPI) network of the overlapping genes was generated, which contained a total of 261 genes, of which the top five were TRIM29, ANK3, CSTA, FGG, and AGR2. These five candidate genes reported herein may prove to be potential therapeutic targets.
Insights
This study analyzed gene expression in Non-Small-Cell Lung Cancer (NSCLC) and Small-Cell Lung Cancer (SCLC) to find key differences. Researchers identified potential therapeutic targets for lung cancer treatment.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Lung cancer has a low survival rate globally, with early detection and chemoresistance being major challenges.
- Lung cancer is classified into Non-Small-Cell Lung Cancer (NSCLC, 85%) and Small-Cell Lung Cancer (SCLC, 15%).
- Understanding gene expression differences is crucial for developing effective lung cancer therapies.
Purpose of the Study:
- To identify Differentially Expressed Genes (DEGs) in NSCLC and SCLC subtypes.
- To compare gene expression profiles between cancer subtypes and normal lung tissue.
- To uncover potential therapeutic targets through overlapping gene analysis.
Main Methods:
- Utilized meta-analysis on two public datasets from the Omnibus database.
- Analyzed gene expression in 50 NSCLC, 31 SCLC, and 48 normal lung tissue samples.
- Applied Benjamini-Hochberg method for p-value adjustment and constructed a Protein-Protein Interaction (PPI) network.
Main Results:
- Identified 440 overexpressed and 489 underexpressed genes in NSCLC.
- Identified 489 overexpressed and 525 underexpressed genes in SCLC.
- Discovered overlapping DEGs and constructed a PPI network highlighting TRIM29, ANK3, CSTA, FGG, and AGR2 as key candidates.
Conclusions:
- The identified overlapping genes, particularly TRIM29, ANK3, CSTA, FGG, and AGR2, represent potential therapeutic targets.
- Gene expression analysis provides insights into NSCLC and SCLC heterogeneity.
- Further research into these candidate genes could lead to novel lung cancer treatments.
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