Identification of Hub Genes of Lung Adenocarcinoma Based on Weighted Gene Co-Expression Network in Chinese Population

Unraveling the intricate molecular landscape and potential biomarkers in lung adenocarcinoma through integrative epigenomic and transcriptomic profiling

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortalities, characterized by substantial genetic heterogeneity that challenges a comprehensive understanding of its progression. This study employs next-generation sequencing data analysis to transform our comprehension of LUAD pathogenesis. Integrating epigenetic and transcriptomic data of LUAD patients, this approach assessed the critical regulatory occurrences, identified therapeutic targets, and offered profound insights into cancer molecular foundations. We employed the DNA methylation data to identify differentially methylated CpG sites and explored the transcriptome profiles of their adjacent genes. An intersectional analysis of gene expression profiles uncovered 419 differentially expressed genes (DEGs) influenced by smoke-induced differential DNA methylation, among which hub genes, including mitochondrial ribosomal proteins (MRPs), and ribosomal proteins (RPs) such as MRPS15, MRPS5, MRPL33, RPL24, RPL7L1, MRPL15, TUFM, MRPL22, and RSL1D1, were identified using a network-based approach. These hub genes were overexpressed and enriched to RNA processing, ribosome biogenesis, and mitochondrial translation, which is critical in LUAD progression. Enhancer Linking Methylation/Expression Relationship (ELMER) analysis revealed transcription factor (TF) binding motifs, such as JUN, NKX23, FOSB, RUNX3, and FOSL1, which regulated these hub genes through methylation-dependent enhancer dynamics. Predominant hypomethylation of MRPs and RPs disrupted mitochondrial function, contributed to oxidative phosphorylation (OXPHOS) and metabolic reprogramming, favoring cancer cell survival. The survival analysis validated the clinical relevance of these hub genes, with high-expression cohorts exhibiting poor overall survival (OS) outcomes enlightened their relevance in LUAD pathogenesis and presented the potential for developing novel targeted therapeutic strategies.

Analysis of Human Papillomavirus-Associated Cervical Cancer Differentially Expressed Genes and Identification of Prognostic Factors using Integrated Bioinformatics Approaches

Background

Human papillomavirus (HPV)-induced cervical cancer progresses through a series of steps. Despite our limited understanding of the mechanisms driving this progression, identifying the key genes involved could significantly improve early detection and treatment.

Materials and Methods

Two gene expression profiles of GSE9750 and GSE6791, which included cervical cancer HPV-positive and -negative samples, were evaluated using the R limma package with established cut-off criteria of P value < 0.05 and | fold change| ≥ 1. KEGG pathway enrichment was performed to identify potential pathways. Weighted gene co-expression network analysis (WGCNA) was used to discover co-expressed gene modules and trait-module connections.

Results

Considering the defined criteria, 115 differentially expressed genes (DEGs) were identified. The DEG's KEGG pathway enrichment analysis revealed enrichment in highly relevant pathways to the HPV infection, including cell cycle, viral carcinogenesis, autophagy-animal, Epstein-Barr virus infection, human T-cell leukemia virus 1 infection, and microRNAs in cancer. WGCNA results in 13 co-expression modules, and the magenta module is identified with significant relations to HPV, cervical cancer stage, and metastasis traits. The survival analysis identified BEX1 and CDC45 as potential prognostic factors in HPV-associated cervical cancer.

Conclusion

The innovation of our work lies in identifying essential genes associated with the multi-step process of cervical carcinogenesis. In fact, the current study has the potential to give a distinct viewpoint on the molecular pathways linked to cervical cancer. Considering the potential importance of the hub genes, we recommend conducting in-depth wet lab research to determine their impact on the biological mechanisms of cervical cancer.

KIAA1429-mediated RXFP1 attenuates non-small cell lung cancer tumorigenesis via N6-methyladenosine modification

BACKGROUND

N6-methyladenosine (m6A) modification has been associated with non-small cell lung cancer (NSCLC) tumorigenesis.

OBJECTIVES

This study aimed to determine the functions of Vir-like m6A methyltransferase-associated (KIAA1429) and relaxin family peptide receptor 1 (RXFP1) in NSCLC.

METHODS

A quantitative real-time polymerase chain reaction was used to analyze the mRNA levels of KIAA1429 and RXFP1 in NSCLC. After silencing KIAA1429 or RXFP1 in NSCLC cells, changes in the malignant phenotypes of NSCLC cells were assessed using cell counting kit-8, colony formation, and transwell assays. Finally, the m6A modification of RXFP1 mediated by KIAA1429 was confirmed using luciferase, methylated RNA immunoprecipitation, and western blot assays.

RESULTS

KIAA1429 and RXFP1 were upregulated and downregulated in NSCLC, respectively. Silencing of KIAA1429 attenuated the viability, migration, and invasion of NSCLC cells, whereas silencing of RXFP1 showed the opposite function in NSCLC cells. Moreover, RXFP1 expression was inhibited by KIAA1429 via m6A-modification. Therefore, silencing RXFP1 reversed the inhibitory effect of KIAA1429 knockdown in NSCLC cells.

CONCLUSION

Our findings confirmed that the KIAA1429/RXFP1 axis promotes NSCLC tumorigenesis. This is the first study to reveal the inhibitory function of RXFP1 in NSCLC via KIAA1429-mediated m6A-modification. These findings may help identify new biomarkers for targeted NSCLC therapy.