Identification of Key Biological Processes, Pathways, Networks, and Genes with Potential Prognostic Values in Hepatocellular Carcinoma Using a Bioinformatics Approach

DSN1 may predict poor prognosis of lower-grade glioma patients and be a potential target for immunotherapy

DSN1 has been previously found to be positively correlated with various cancers. However, the effect of DSN1 or its methylation on the prognosis, molecular characteristics, and immune cell infiltration of low-grade glioma (LGG) has not yet been studied. We obtained 1046 LGG samples from the The Cancer Genome Atlas, The Chinese Glioma Genome Atlas (CGGA) microarray, and CGGA RNA-Seq databases. Bioinformatic methods (gene set enrichment analysis (GSEA), chi-square test, multivariate), and laboratory validation were used to investigate DSN1 in LGG. The expression levels of DSN1 mRNA and protein in LGG were substantially higher than those in normal brain tissue, and their expression was negatively regulated by methylation. The survival time of patients with low expression of DSN1 and cg12601032 hypermethylation was considerably prolonged. DSN1 was a risk factor, and of good diagnostic and prognostic value for LGG. Importantly, the expression of DSN1 is related to many types of tumor-infiltrating immune cells and has a positive correlation with PDL1. DSN1 promoted the activation of multiple cancer-related pathways, such as the cell cycle. Additionally, knockdown of DSN1 substantially inhibited the proliferation and invasion of LGG cells. To the best of our knowledge, this study is the first comprehensive analysis of the mechanism of DSN1 leading to poor prognosis of LGG, which provides a new perspective for revealing the pathogenesis of LGG. DSN1 or its methylation has diagnostic value for the prognosis of glioma, and may become a new biological target of anti-tumor immunotherapy.

Analysis of pharmacological effects and mechanisms of compound essential oils via GC-MS and network pharmacology

Aromatherapy based on essential oil (EO) has been widely used for alleviating pain and intense where no compound EO reports its application on pharmacological effects. In order to explore the active pharmaceutical ingredients (API) and mechanism of a compound EO, a blend of Artemisia argyi, Boswellia carterii, Commiphora myrrha, Cinnamomum cassia, Zingiber oj-jicinale, and Ilex pubescens EO, in treating neck and shoulder pain (NSP). Network pharmacology hyphenated with mice model was employed to investigate. Gas chromatography-mass spectrometry (GC-MS) was applied for the identification of constituents in compound EO. Lastly, transdermal absorption of compound EO was studied before verifying analgesic and anti-inflammatory effects in mice. Totally, 75 compounds were tentatively identified through GC-MS, predicting 46 potential analgesic targets. Moreover, 11 core targets were obtained through network topology screening. Animal test resulted that the compound EO had significantly stronger anti-inflammatory and analgesic effects compared to single EO. Multiple API in compound EO affected on targets and exerted therapeutic effects on NSP through multiple pathways. Afterwards, eucalyptol, camphor, and borneol from compound EO exhibited a sustained-release effect, which provide scientific basis to illustrate the application of compound EO in clinical.

Impact of NDUFAF6 on breast cancer prognosis: linking mitochondrial regulation to immune response and PD-L1 expression

BACKGROUND

Breast cancer is a major global health concern, and there is a continuous search for novel biomarkers to predict its prognosis. The mitochondrial protein NDUFAF6, previously studied in liver cancer, is now being investigated for its role in breast cancer. This study aims to explore the expression and functional significance of NDUFAF6 in breast cancer using various databases and experimental models.

METHODS

We analyzed breast cancer samples from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA) databases, supplemented with immunohistochemistry (IHC) staining to assess NDUFAF6 expression. A breast cancer cell xenograft mouse model was used to evaluate tumor growth, apoptosis, and NDUFAF6 expression. Survival probabilities were estimated through Kaplan-Meier plots and Cox regression analysis. A Protein-Protein Interaction (PPI) network was constructed, and differentially expressed genes related to NDUFAF6 were analyzed using GO, KEGG, and GSEA. The relationship between NDUFAF6 expression, immune checkpoints, and immune infiltration was also evaluated.

RESULTS

NDUFAF6 was found to be overexpressed in breast cancer patients and in the xenograft mouse model. Its expression correlated with worse clinical features and prognosis. NDUFAF6 expression was an independent predictor of breast cancer outcomes in both univariate and multivariate analyses. Functionally, NDUFAF6 is implicated in several immune-related pathways. Crucially, NDUFAF6 expression correlated with various immune infiltrating cells and checkpoints, particularly promoting PD-L1 expression by inhibiting the NRF2 signaling pathway.

CONCLUSION

The study establishes NDUFAF6 as a potential prognostic biomarker in breast cancer. Its mechanism of action, involving the inhibition of NRF2 to upregulate PD-L1, highlights its significance in the disease's progression and potential as a target for immunotherapy.

Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning

Hepatocellular carcinoma (HCC) is the most common lethal malignancy of the liver worldwide. Thus, it is important to dig the key genes for uncovering the molecular mechanisms and to improve diagnostic and therapeutic options for HCC. This study aimed to encompass a set of statistical and machine learning computational approaches for identifying the key candidate genes for HCC. Three microarray datasets were used in this work, which were downloaded from the Gene Expression Omnibus Database. At first, normalization and differentially expressed genes (DEGs) identification were performed using limma for each dataset. Then, support vector machine (SVM) was implemented to determine the differentially expressed discriminative genes (DEDGs) from DEGs of each dataset and select overlapping DEDGs genes among identified three sets of DEDGs. Enrichment analysis was performed on common DEDGs using DAVID. A protein-protein interaction (PPI) network was constructed using STRING and the central hub genes were identified depending on the degree, maximum neighborhood component (MNC), maximal clique centrality (MCC), centralities of closeness, and betweenness criteria using CytoHubba. Simultaneously, significant modules were selected using MCODE scores and identified their associated genes from the PPI networks. Moreover, metadata were created by listing all hub genes from previous studies and identified significant meta-hub genes whose occurrence frequency was greater than 3 among previous studies. Finally, six key candidate genes (TOP2A, CDC20, ASPM, PRC1, NUSAP1, and UBE2C) were determined by intersecting shared genes among central hub genes, hub module genes, and significant meta-hub genes. Two independent test datasets (GSE76427 and TCGA-LIHC) were utilized to validate these key candidate genes using the area under the curve. Moreover, the prognostic potential of these six key candidate genes was also evaluated on the TCGA-LIHC cohort using survival analysis.

CircPDSS1 promotes the proliferation, invasion, migration, and EMT of breast cancer cell via regulating miR-320c/CKAP5 axis

Background

Breast cancer (BC) poses serious threats to women’s health. A large number of reports have proved that circular RNAs (circRNAs) exert vital functions in human cancers, including BC.

Methods

The function of circPDSS1 in BC cells was tested by CCK-8, colony formation, TUNEL, transwell-invasion, wound healing, and IF assays. RNA pull down, luciferase reporter and RIP assays were employed to verify the relationship among circPDSS1, miR-320c and CKAP5.

Results

CircPDSS1 was upregulated in BC cells, and circPDSS1 knockdown repressed BC cell malignant behaviors. Further, circPDSS1 was found to bind to miR-320c in BC cells, and miR-320c overexpression suppressed malignant processes of BC cells. MiR-320c could also bind to CKAP5. Moreover, miR-320c inhibition increased the level of CKAP5, but circPDSS1 downregulation decreased the level of CKAP5. Finally, rescue experiments indicated that CKAP5 knockdown countervailed the promoting effect of miR-320c inhibition on the malignant behaviors of circPDSS1-depleted BC cells.

Conclusions

CircPDSS1 promotes proliferation, invasion, migration as well as EMT of BC cells by modulating miR-320c/CKAP5 axis. Our finding may be useful for researchers to find new potential therapeutic or diagnostic targets for BC.

Cell Development Deficiency and Gene Expression Dysregulation of Trisomy 21 Retina Revealed by Single-Nucleus RNA Sequencing

Retina is a crucial tissue for capturing and processing light stimulus. It is critical to describe the characteristics of retina at the single-cell level for understanding its biological functions. A variety of abnormalities in terms of morphology and function are present in the trisomy 21 (T21) retina. To evaluate the consequences of chromosome aneuploidy on retina development, we identified the single-cell transcriptional profiles of a T21 fetus and performed comprehensive bioinformatic analyses. Our data revealed the diversity and heterogeneity of cellular compositions in T21 retina, as well as the abnormal constitution of T21 retina compared to disomic retina. In total, we identified seven major cell types and several subtypes within each cell type, followed by the detection of corresponding molecular markers, including previously reported ones and a series of novel markers. Through the analysis of the retinal differentiation process, subtypes of retinal progenitor cells (RPCs) exhibiting the potential of different retinal cell-type commitments and certain Müller glial cells (MGs) with differentiating potency were identified. Moreover, the extensive communication networks between cellular types were confirmed, among which a few ligand–receptor interactions were related to the formation and function of retina and immunoregulatory interactions. Taken together, our data provides the first ever single-cell transcriptome profiles for human T21 retina, which facilitates the understanding on the dosage effects of chromosome 21 on the development of retina.