Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer

Crosstalk between lncRNAs and Wnt/β-catenin signaling pathways in lung cancers: From cancer progression to therapeutic response

Lung cancer (LC) is considered to have the highest mortality rate around the world. Because there are no early diagnostic signs or efficient clinical alternatives, distal metastasis and increasing numbers of recurrences are a challenge in the clinical management of LC. Long non-coding RNAs (lncRNAs) have recently been recognized as a critical regulator involved in the progression and treatment response to LC. The Wnt/β-catenin pathway has been shown to influence LC occurrence and progress. Therefore, discovering connections between Wnt signaling pathway and lncRNAs may offer new therapeutic targets for improving LC treatment and management. In this review, the purpose of this article is to present possible therapeutic approaches by reviewing particular relationships, key processes, and molecules associated to the beginning and development of LC.

Prognostic and onco-immunological value of immune-related eRNAs-driven genes in lung adenocarcinoma

BACKGROUND

We aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.

MATERIALS AND METHODS

Pearson's correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.

RESULTS

Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.

CONCLUSION

Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.

Exploring miRNA‑target gene profiles associated with drug resistance in patients with breast cancer receiving neoadjuvant chemotherapy

Exosomal microRNAs (miRNAs) are closely related to drug resistance in patients with breast cancer (BC); however, only a few roles of the exosomal miRNA-target gene networks have been clinically implicated in drug resistance in BC. Therefore, the present study aimed to identify the differential expression of exosomal miRNAs associated with drug resistance and their target mRNAs. In vitro microarray analysis was used to verify differentially expressed miRNAs (DEMs) in drug-resistant BC. Next, tumor-derived exosomes (TDEs) were isolated. Furthermore, it was determined whether the candidate drug-resistant miRNAs were also significant in TDEs, and then putative miRNAs in TDEs were validated in plasma samples from 35 patients with BC (20 patients with BC showing no response and 15 patients with BC showing a complete response). It was confirmed that the combination of five exosomal miRNAs, including miR-125b-5p, miR-146a-5p, miR-484, miR-1246-5p and miR-1260b, was effective for predicting therapeutic response to neoadjuvant chemotherapy, with an area under the curve value of 0.95, sensitivity of 75%, and specificity of 95%. Public datasets were analyzed to identify differentially expressed genes (DEGs) related to drug resistance and it was revealed that BAK1, NOVA1, PTGER4, RTKN2, AGO1, CAP1, and ETS1 were the target genes of exosomal miRNAs. Networks between DEMs and DEGs were highly correlated with mitosis, metabolism, drug transport, and immune responses. Consequently, these targets could be used as predictive markers and therapeutic targets for clinical applications to enhance treatment outcomes for patients with BC.

The dual roles of circRNAs in Wnt/β-Catenin signaling and cancer progression

Cancer, a complex pathophysiological condition, arises from the abnormal proliferation and survival of cells due to genetic mutations. Dysregulation of cell cycle control, apoptosis, and genomic stability contribute to uncontrolled growth and metastasis. Tumor heterogeneity, microenvironmental influences, and immune evasion further complicate cancer dynamics. The intricate interplay between circular RNAs (circRNAs) and the Wnt/β-Catenin signalling pathway has emerged as a pivotal axis in the landscape of cancer biology. The Wnt/β-Catenin pathway, a critical regulator of cell fate and proliferation, is frequently dysregulated in various cancers. CircRNAs, a class of non-coding RNAs with closed-loop structures, have garnered increasing attention for their diverse regulatory functions. This review systematically explores the intricate crosstalk between circRNAs and the Wnt/β-Catenin pathway, shedding light on their collective impact on cancer initiation and progression. The review explores the diverse mechanisms through which circRNAs modulate the Wnt/β-Catenin pathway, including sponging microRNAs, interacting with RNA-binding proteins, and influencing the expression of key components in the pathway. Furthermore, the review highlights specific circRNAs implicated in various cancer types, elucidating their roles as either oncogenic or tumour-suppressive players in the context of Wnt/β-Catenin signaling. The intricate regulatory networks formed by circRNAs in conjunction with the Wnt/β-Catenin pathway are discussed, providing insights into potential therapeutic targets and diagnostic biomarkers. This comprehensive review delves into the multifaceted roles of circRNAs in orchestrating tumorigenesis through their regulatory influence on the Wnt/β-Catenin pathway.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.