Identification of Crucial Candidate Genes and Pathways in Glioblastoma Multiform by Bioinformatics Analysis

HE2Gene: image-to-RNA translation via multi-task learning for spatial transcriptomics data

MOTIVATION

Tissue context and molecular profiling are commonly used measures in understanding normal development and disease pathology. In recent years, the development of spatial molecular profiling technologies (e.g. spatial resolved transcriptomics) has enabled the exploration of quantitative links between tissue morphology and gene expression. However, these technologies remain expensive and time-consuming, with subsequent analyses necessitating high-throughput pathological annotations. On the other hand, existing computational tools are limited to predicting only a few dozen to several hundred genes, and the majority of the methods are designed for bulk RNA-seq.

RESULTS

In this context, we propose HE2Gene, the first multi-task learning-based method capable of predicting tens of thousands of spot-level gene expressions along with pathological annotations from H&E-stained images. Experimental results demonstrate that HE2Gene is comparable to state-of-the-art methods and generalizes well on an external dataset without the need for re-training. Moreover, HE2Gene preserves the annotated spatial domains and has the potential to identify biomarkers. This capability facilitates cancer diagnosis and broadens its applicability to investigate gene-disease associations.

AVAILABILITY AND IMPLEMENTATION

The source code and data information has been deposited at https://github.com/Microbiods/HE2Gene.

Small molecule drug discovery for glioblastoma treatment based on bioinformatics and cheminformatics approaches

Background: Glioblastoma (GBM) is a common and highly aggressive brain tumor with a poor prognosis for patients. It is urgently needed to identify potential small molecule drugs that specifically target key genes associated with GBM development and prognosis. Methods: Differentially expressed genes (DEGs) between GBM and normal tissues were obtained by data mining the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Gene function annotation was performed to investigate the potential functions of the DEGs. A protein-protein interaction (PPI) network was constructed to explore hub genes associated with GBM. Bioinformatics analysis was used to screen the potential therapeutic and prognostic genes. Finally, potential small molecule drugs were predicted using the DGIdb database and verified using chemical informatics methods including absorption, distribution, metabolism, excretion, toxicity (ADMET), and molecular docking studies. Results: A total of 429 DEGs were identified, of which 19 hub genes were obtained through PPI analysis. The hub genes were confirmed as potential therapeutic targets by functional enrichment and mRNA expression. Survival analysis and protein expression confirmed centromere protein A (CENPA) as a prognostic target in GBM. Four small molecule drugs were predicted for the treatment of GBM. Conclusion: Our study suggests some promising potential therapeutic targets and small molecule drugs for the treatment of GBM, providing new ideas for further research and targeted drug development.

Knockdown of MRPL35 promotes cell apoptosis and inhibits cell proliferation in non-small-cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) is a major pathological type of lung cancer. However, its pathogenesis remains largely unclear. MRPL35 is a regulatory subunit of the mitoribosome, which can regulate the assembly of cytochrome c oxidases and plays an important role in the occurrence of NSCLC.

METHODS

The expression of MRPL35 in NSCLC was detected by tissue microarray and immunohistochemistry. H1299 cells were infected with lentivirus to knockdown MRPL35, and the cells were subjected to crystal violet staining to assess the results of colony formation assays. A549 cells were infected by lentiviral particles-expressing shMRPL35 or shControl, and then subcutaneously injected into nude mice. Tumorigenesis in mice was detected by in vivo imaging. The potential pathway of MRPL35 in NSCLC was assessed by Western blotting.

RESULTS

MRPL35 was over-expressed in NSCLC tissue compared to para-cancerous and normal tissues. Knockdown of MRPL35 suppressed cell proliferation and decreased NSCLC progression both in vitro and in vivo. The possible molecular mechanisms were also clarified, which indicated that MRPL35 could be involved in cell apoptosis and proliferation by modulating the expression levels of CDK1, BIRC5, CHEK1, STMN1 and MCM2. Knockdown of MRPL35 activated p53 signaling pathway and inhibited cell cycle regulation.

CONCLUSIONS

The oncogenic role of MRPL35 in NSCLC was potentially mediated through the cell cycle regulatory genes such as BIRC5, STMN1, CDK1, CHEK1 and MCM2, as well as activation of P53 signaling pathway.

Small networks of expressed genes in the whole blood and relationships to profiles in circulating metabolites provide insights in inter-individual variability of feed efficiency in growing pigs

BACKGROUND

Feed efficiency is a research priority to support a sustainable meat production. It is recognized as a complex trait that integrates multiple biological pathways orchestrated in and by various tissues. This study aims to determine networks between biological entities to explain inter-individual variation of feed efficiency in growing pigs.

RESULTS

The feed conversion ratio (FCR), a measure of feed efficiency, and its two component traits, average daily gain and average daily feed intake, were obtained from 47 growing pigs from a divergent selection for residual feed intake and fed high-starch or high-fat high-fiber diets during 58 days. Datasets of transcriptomics (60 k porcine microarray) in the whole blood and metabolomics (1H-NMR analysis and target gas chromatography) in plasma were available for all pigs at the end of the trial. A weighted gene co-expression network was built from the transcriptomics dataset, resulting in 33 modules of co-expressed molecular probes. The eigengenes of eight of these modules were significantly ([Formula: see text]) or tended to be ([Formula: see text]) correlated to FCR. Great homogeneity in the enriched biological pathways was observed in these modules, suggesting co-expressed and co-regulated constitutive genes. They were mainly enriched in genes participating to immune and defense-related processes, and to a lesser extent, to translation, cell development or learning. They were also generally associated with growth rate and percentage of lean mass. In the whole network, only one module composed of genes participating to the response to substances, was significantly associated with daily feed intake and body adiposity. The plasma profiles in circulating metabolites and in fatty acids were summarized by weighted linear combinations using a dimensionality reduction method. Close association was thus found between a module composed of co-expressed genes participating to T cell receptor signaling and cell development process in the whole blood and related to FCR, and the circulating concentrations of polyunsaturated fatty acids in plasma.

CONCLUSION

These systemic approaches have highlighted networks of entities driving key biological processes involved in the phenotypic difference in feed efficiency between animals. Connecting transcriptomics and metabolic levels together had some additional benefits.

Unveiling the prognostic implications of RPLP1 upregulation in osteosarcoma

Osteosarcoma, a malignant bone tumor characterized by a high rate of metastasis and poor survival, presents a critical need for identifying novel biomarkers associated with metastasis. In this study, we conducted an extensive analysis utilizing transcriptional and clinical data sourced from databases such as GEO, TCGA, CCLE, R2, and Xena. And we discovered that Ribosomal protein LP1 (RPLP1) ranked among the top upregulated genes in relation to osteosarcoma metastasis. Notably, RPLP1 exhibited significant expression in both osteosarcoma cell lines and patient samples. Moreover, multiple osteosarcoma studies revealed a strong correlation between RPLP1 overexpression and worse metastasis-free survival as well as overall survival. Additionally, we observed a consistent association between dysregulation of RPLP1 and reduced overall survival across various tumor types. Knocking down of RPLP1 led to the down-regulation of MYL5 and functional enrichment toward cell cycle and cellular interaction. Based on these findings, we propose that RPLP1 has the potential to serve as a prognostic biomarker, indicating increased metastasis and worse survival outcomes in osteosarcoma. These insights contribute to a better understanding of the disease and may pave the way for future research and therapeutic approaches.

Antiproliferative effect of Potentilla fulgens on glioblastoma cancer cells through downregulation of Akt/mTOR signaling pathway

BACKGROUND

Glioblastoma multiforme (GBM) is the most aggressive brain tumor that is common among adults. This aggression is due to increased invasion, migration, proliferation, angiogenesis, and decreased apoptosis. Plant-based compounds have a high potential to be used as an anticancer agent due to their various mechanisms and less undesirable side effects. Potentilla fulgens is a medicinal plant, and methanolic root extract of P. fulgens (PRE) has anti-inflammatory and anticancer properties.

OBJECTIVE

In this study, we aimed to investigate antiproliferative effect of PRE on U118 and T98G glioblastoma cancer cells and to reveal which molecular signaling pathways regulate this mechanism of action.

MATERIALS AND METHODS

The effect of PRE on cell viability of GBM cells was investigated by MTT assay. Involvement of PRE with cell growth and survival signaling pathways, phosphatidylinositol 3-kinase (PI3K)/Akt/mTOR and c-Src/signal transducer and activator of transcription 3 (STAT3), was examined using Western Blot.

RESULTS

PRE reduced cell viability of GBM and human dermal fibroblast (HDF) cells in a dose-and time-independent manner. PI3K expression/phosphorylation level remained unchanged in both GBM and HDF cells after PRE treatment, but Akt/mTOR signaling pathway was downregulated in PRE-treated cells. PRE treatment did not affect c-Src expression/phosphorylation level in GBM cells; however, expression of c-Src was suppressed in HDF cells. Similar results were observed for STAT3 expression and phosphorylation status.

CONCLUSION

PRE has the ability to suppress cell viability in GBM cells, by targeting the Akt/mTOR signaling pathway.

Identification and validation of a fatty acid metabolism gene signature for the promotion of metastasis in liver cancer

Metastasis is a fatal status for liver cancer, and the identification of an effective prediction model and promising therapeutic target is essential. Given the known relationship between fatty acid (FA) metabolism and the liver, the present study aimed to investigate dysregulation of genes associated with FA metabolism in liver cancer. Bioinformatics analyses were performed on data from patients with hepatocellular carcinoma (HCC) obtained from The Cancer Genome Atlas database using R software packages. Online public tools such as the Human Protein Atlas, Tumor Immune Single-Cell Hub and the University of Alabama at Birmingham Cancer Data Analysis portal were also utilized. Some essential results were further verified using in vitro experiments using HepG2 liver cancer cells. A signature consisting of three genes associated with the progression and prognosis of HCC and FA metabolism was identified. When samples were scored based on the expression of these genes and divided according to the median value, the higher score group showed a worse outcome and repressive immune microenvironment than the lower score group. Downstream pathways such as hypoxia, IL6/JAK/STAT3 and epithelial-mesenchymal transition were found to be significantly activated in the higher score group. As the core factor in the signature, mitochondrial ribosomal protein L35 (MRPL35) was found to be upregulated in HCC and to have certain impacts on the dysregulation of effective immunity. Further investigations and in vitro experiments indicated that MRPL35 facilitates the migration and invasion abilities of liver cancer, and the resistance of HCC to treatment. These findings have important implications regarding the characteristics and mechanisms of metastasis in liver cancer, and provide a promising signature based on FA metabolism-related genes that may be used to predict outcomes and explored as a novel therapeutic target in liver cancer.

Potential Candidate Genes for Therapeutic Targeting in Chronic Myeloid Leukemia: A Pilot Study

BACKGROUND

Chronic myeloid leukemia (CML) is a prevalent hematological malignancy known for the presence of the Philadelphia chromosome and activation of the BCR-Abl kinase activity. Although tyrosine kinase inhibitors are widely used as the standard treatment, resistance remains a concern among certain patients. This study aimed to investigate the gene expression profile of a group of CML patients in comparison to a control group in order to identify novel candidate genes associated with the disease.

METHODS

Whole transcriptome sequencing was performed, and gene expression levels were validated using quantitative real-time PCR. Additionally, single nucleotide and insertion/deletion variants were analyzed in the selected candidate genes among 10 CML patients and 4 healthy control subjects.

RESULTS

Analysis revealed a set of differentially expressed genes, whose up- or downregulation was further confirmed by qRT-PCR. Among the upregulated genes in the patient group were ribosomal protein like (RPL) members, specifically RPL9, RPL34, RPL36A, and RPL39, while downregulation was observed in CCDC170, LDB1, and SBF1 compared to the healthy subjects. Furthermore, gene variant studies identified novel genetic changes in these candidate genes, suggesting potential clinical significance in CML.

CONCLUSIONS

This study highlights RPL9, RPL34, RPL36A, RPL39, CCDC170, LDB1, and SBF1 as potential targets in CML. Additionally, it underscores the importance of investigating these genes and their variants in larger cohort studies to assess their clinical significance in CML patients.

Recent advancements and theranostics strategies in glioblastoma therapy

Glioblastoma (GBM) is the most aggressive and lethal malignant brain tumor, and it is challenging to cure with surgery and treatment. The prevention of permanent brain damage and tumor invasion, which is the ultimate cause of recurrence, are major obstacles in GBM treatment. Besides, emerging treatment modalities and newer genetic findings are helping to understand and manage GBM in patients. Accordingly, researchers are focusing on advanced nanomaterials-based strategies for tackling the various problems associated with GBM. In this context, researchers explored novel strategies with various alternative treatment approaches such as early detection techniques and theranostics approaches. In this review, we have emphasized the recent advancement of GBM cellular models and their roles in designing GBM therapeutics. We have added a special emphasis on the novel genetic and drug target findings as well as strategies for early detection. Besides, we have discussed various theranostic approaches such as hyperthermia therapy, phototherapy and image-guided therapy. Approaches utilized for targeted drug delivery to the GBM were also discussed. This article also describes the recentin vivo, in vitroandex vivoadvances using innovative theranostic approaches.

Identification of genomic biomarkers and their pathway crosstalks for deciphering mechanistic links in glioblastoma

Glioblastoma is a grade IV pernicious neoplasm occurring in the supratentorial region of brain. As its causes are largely unknown, it is essential to understand its dynamics at the molecular level. This necessitates the identification of better diagnostic and prognostic molecular candidates. Blood-based liquid biopsies are emerging as a novel tool for cancer biomarker discovery, guiding the treatment and improving its early detection based on their tumour origin. There exist previous studies focusing on the identification of tumour-based biomarkers for glioblastoma. However, these biomarkers inadequately represent the underlying pathological state and incompletely illustrate the tumour because of non-recursive nature of this approach to monitor the disease. Also, contrary to the tumour biopsies, liquid biopsies are non-invasive and can be performed at any interval during the disease span to surveil the disease. Therefore, in this study, a unique dataset of blood-based liquid biopsies obtained primarily from tumour-educated blood platelets (TEP) is utilised. This RNA-seq data from ArrayExpress is acquired comprising human cohort with 39 glioblastoma subjects and 43 healthy subjects. Canonical and machine learning approaches are applied for identification of the genomic biomarkers for glioblastoma and their crosstalks. In our study, 97 genes appeared enriched in 7 oncogenic pathways (RAF-MAPK, P53, PRC2-EZH2, YAP conserved, MEK-MAPK, ErbB2 and STK33 signalling pathways) using GSEA, out of which 17 have been identified participating actively in crosstalks. Using PCA, 42 genes are found enriched in 7 pathways (cytoplasmic ribosomal proteins, translation factors, electron transport chain, ribosome, Huntington's disease, primary immunodeficiency pathways, and interferon type I signalling pathway) harbouring tumour when altered, out of which 25 actively participate in crosstalks. All the 14 pathways foster well-known cancer hallmarks and the identified DEGs can serve as genomic biomarkers, not only for the diagnosis and prognosis of Glioblastoma but also in providing a molecular foothold for oncogenic decision making in order to fathom the disease dynamics. Moreover, SNP analysis for the identified DEGs is performed to investigate their roles in disease dynamics in an elaborated manner. These results suggest that TEPs are capable of providing disease insights just like tumour cells with an advantage of being extracted anytime during the course of disease in order to monitor it.

Role of A-Kinase Anchoring Protein 12 in the Central Nervous System

A-kinase anchoring protein (AKAP) 12 is a scaffolding protein that anchors various signaling proteins to the plasma membrane. These signaling proteins include protein kinase A, protein kinase C, protein phosphatase 2B, Src-family kinases, cyclins, and calmodulin, which regulate their respective signaling pathways. AKAP12 expression is observed in the neurons, astrocytes, endothelial cells, pericytes, and oligodendrocytes of the central nervous system (CNS). Its physiological roles include promoting the development of the blood-brain barrier, maintaining white-matter homeostasis, and even regulating complex cognitive functions such as long-term memory formation. Under pathological conditions, dysregulation of AKAP12 expression levels may be involved in the pathology of neurological diseases such as ischemic brain injury and Alzheimer's disease. This minireview aimed to summarize the current literature on the role of AKAP12 in the CNS.

Exploitation of a shared genetic signature between obesity and endometrioid endometrial cancer

Aims

The findings in epidemiological studies suggest that endometrioid endometrial cancer (EEC) is associated with obesity. However, evidence from gene expression data for the relationship between the two is still lacking. The purpose of this study was to explore the merits of establishing an obesity-related genes (ORGs) signature in the treatment and the prognostic assessment of EEC.

Methods

Microarray data from GSE112307 were utilized to identify ORGs by using weighted gene co-expression network analysis. Based on the sequencing data from TCGA, we established the prognostic ORGs signature, confirmed its value as an independent risk factor, and constructed a nomogram. We further investigated the association between grouping based on ORGs signature and clinicopathological characteristics, immune infiltration, tumor mutation burden and drug sensitivity.

Results

A total of 10 ORGs were identified as key genes for the construction of the signature. According to the ORGs score computed from the signature, EEC patients were divided into high and low-scoring groups. Overall survival (OS) was shorter in EEC patients in the high-scoring group compared with the low-scoring group (P < 0.001). The results of the Cox regression analysis showed that ORGs score was an independent risk factor for OS in EEC patients (HR = 1.017, 95% confidence interval = 1.011-1.023; P < 0.001). We further revealed significant disparities between scoring groups in terms of clinical characteristics, tumor immune cell infiltration, and tumor mutation burden. Patients in the low-scoring group may be potential beneficiaries of immunotherapy and targeted therapies.

Conclusions

The ORGs signature established in this study has promising prognostic predictive power and may be a useful tool for the selection of EEC patients who benefit from immunotherapy and targeted therapies.

Stress-induced reduction of Na+/H+ exchanger isoform 1 promotes maladaptation of neuroplasticity and exacerbates depressive behaviors

Major depression disorder (MDD) is a neuropsychiatric disorder characterized by abnormal neuronal activity in specific brain regions. A factor that is crucial in maintaining normal neuronal functioning is intracellular pH (pHi) homeostasis. In this study, we show that chronic stress, which induces depression-like behaviors in animal models, down-regulates the expression of the hippocampal Na⁺/H⁺ exchanger isoform 1, NHE1, a major determinant of pHi in neurons. Knockdown of NHE1 in CA1 hippocampal pyramidal neurons leads to intracellular acidification, promotes dendritic spine loss, lowers excitatory synaptic transmission, and enhances the susceptibility to stress exposure in rats. Moreover, E3 ubiquitin ligase cullin4A may promote ubiquitination and degradation of NHE1 to induce these effects of an unbalanced pHi on synaptic processes. Electrophysiological data further suggest that the abnormal excitability of hippocampal neurons caused by maladaptation of neuroplasticity may be involved in the pathogenesis of this disease. These findings elucidate a mechanism for pHi homeostasis alteration as related to MDD.

COMBING: Clustering in Oncology for Mathematical and Biological Identification of Novel Gene Signatures

Precision medicine is a paradigm shift in healthcare relying heavily on genomics data. However, the complexity of biological interactions, the large number of genes as well as the lack of comparisons on the analysis of data, remain a tremendous bottleneck regarding clinical adoption. In this paper, we introduce a novel, automatic and unsupervised framework to discover low-dimensional gene biomarkers. Our method is based on the LP-Stability algorithm, a high dimensional center-based unsupervised clustering algorithm. It offers modularity as concerns metric functions and scalability, while being able to automatically determine the best number of clusters. Our evaluation includes both mathematical and biological criteria to define a quantitative metric. The recovered signature is applied to a variety of biological tasks, including screening of biological pathways and functions, and characterization relevance on tumor types and subtypes. Quantitative comparisons among different distance metrics, commonly used clustering methods and a referential gene signature used in the literature, confirm state of the art performance of our approach. In particular, our signature, based on 27 genes, reports at least 30 times better mathematical significance (average Dunn's Index) and 25% better biological significance (average Enrichment in Protein-Protein Interaction) than those produced by other referential clustering methods. Finally, our signature reports promising results on distinguishing immune inflammatory and immune desert tumors, while reporting a high balanced accuracy of 92% on tumor types classification and averaged balanced accuracy of 68% on tumor subtypes classification, which represents, respectively 7% and 9% higher performance compared to the referential signature.

A Novel Necroptosis-Related Prognostic Signature of Glioblastoma Based on Transcriptomics Analysis and Single Cell Sequencing Analysis

Background: Glioblastoma (GBM) is the most common and deadly brain tumor. The clinical significance of necroptosis (NCPS) genes in GBM is unclear. The goal of this study is to reveal the potential prognostic NCPS genes associated with GBM, elucidate their functions, and establish an effective prognostic model for GBM patients. Methods: Firstly, the NCPS genes in GBM were identified by single-cell analysis of the GSE182109 dataset in the GEO database and weighted co-expression network analysis (WGCNA) of The Cancer Genome Atlas (TCGA) data. Three machine learning algorithms (Lasso, SVM-RFE, Boruta) combined with COX regression were used to build prognostic models. The subsequent analysis included survival, immune microenvironments, and mutations. Finally, the clinical significance of NCPS in GBM was explored by constructing nomograms. Results: We constructed a GBM prognostic model composed of NCPS-related genes, including CTSD, AP1S1, YWHAG, and IER3, which were validated to have good performance. According to the above prognostic model, GBM patients in the TCGA and CGGA groups could be divided into two groups according to NCPS, with significant differences in survival analysis between the two groups and a markedly worse prognostic status in the high NCPS group (p < 0.001). In addition, the high NCPS group had higher levels of immune checkpoint-related gene expression, suggesting that they may be more likely to benefit from immunotherapy. Conclusions: Four genes (CTSD, AP1S1, YWHAG, and IER3) were screened through three machine learning algorithms to construct a prognostic model for GBM. These key and novel diagnostic markers may become new targets for diagnosing and treating patients with GBM.

Sp1 induced gene TIMP1 is related to immune cell infiltration in glioblastoma

Tumor immune microenvironment exerts a profound effect on the population of infiltrating immune cells. Tissue inhibitor of matrix metalloproteinase 1 (TIMP1) is frequently overexpressed in a variety of cells, particularly during inflammation and tissue injury. However, its function in cancer and immunity remains enigmatic. In this study, we find that TIMP1 is substantially up-regulated during tumorigenesis through analyzing cancer bioinformatics databases, which is further confirmed by IHC tissue microarrays of clinical samples. The TIMP1 level is significantly increased in lymphocytes infiltrating the tumors and correlated with cancer progression, particularly in GBM. Notably, we find that the transcriptional factor Sp1 binds to the promoter of TIMP1 and triggers its expression in GBM. Together, our findings suggest that the Sp1-TIMP1 axis can be a potent biomarker for evaluating immune cell infiltration at the tumor sites and therefore, the malignant progression of GBM.

Identification of hub genes and biological pathways in glioma via integrated bioinformatics analysis

OBJECTIVE

Glioma is the most common intracranial primary malignancy, but its pathogenesis remains unclear.

METHODS

We integrated four eligible glioma microarray datasets from the gene expression omnibus database using the robust rank aggregation method to identify a group of significantly differently expressed genes (DEGs) between glioma and normal samples. We used these DEGs to explore key genes closely associated with glioma survival through weighted gene co-expression network analysis. We then constructed validations of prognosis and survival analyses for the key genes via multiple databases. We also explored their potential biological functions using gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA).

RESULTS

We selected DLGAP5, CDCA8, NCAPH, and CCNB2, as four genes that were abnormally up-regulated in glioma samples, for verification. They showed high levels of isocitrate dehydrogenase gene mutation and tumor grades, as well as good prognostic and diagnostic value for glioma. Their methylation levels were generally lower in glioma samples. GSEA and GSVA analyses suggested the genes were closely involved with glioma proliferation.

CONCLUSION

These findings provide new insights into the pathogenesis of glioma. The hub genes have the potential to be used as diagnostic and therapeutic markers.

The Single Nucleotide Polymorphisms of AP1S1 are Associated with Risk of Esophageal Squamous Cell Carcinoma in Chinese Population

Background

The σ1A subunit of the adaptor protein 1 (AP1S1) participates in various intracellular transport pathways, especially the maintenance of copper homeostasis, which is pivotal in carcinogenesis. It is therefore rational to presume that AP1S1 might also be involved in carcinogenesis. In this hospital-based case-control study, we investigated the genetic susceptibility to ESCC in relation to SNPs of AP1S1 among Chinese population.

Methods

A database containing a total of 1303 controls and 1043 ESCC patients were retrospectively studied. The AP1S1 SNPs were analyzed based on ligation detection reaction (LDR) method. Then, the relationship between ESCC and SNPs of AP1S1 was determined with a significant crude P<0.05. Then the logistic regression analysis was used for the calculation for adjusted P in the demographic stratification comparison if a significant difference was observed in the previous step.

Results

AP1S1 rs77387752 C>T genotype TT was an independent risk factor for ESCC, while rs4729666 C>T genotype TC and rs35208462 C>T genotype TC were associated with a lower risk for ESCC, especially in co-dominant model and allelic test for younger, male subjects who are not alcohol-drinkers nor cigarette smokers.

Conclusion

AP1S1 rs77387752, rs4729666 and rs35208462 polymorphisms are associated with susceptibility to ESCC in Chinese individuals. AP1S1 SNPs may exert an important role in esophageal carcinogenesis and could serve as potential diagnostic biomarkers.

Role of adaptin protein complexes in intracellular trafficking and their impact on diseases

Adaptin proteins (APs) play a crucial role in intracellular cell trafficking. The 'classical' role of APs is carried out by AP1‒3, which bind to clathrin, cargo, and accessory proteins. Accordingly, AP1-3 are crucial for both vesicle formation and sorting. All APs consist of four subunits that are indispensable for their functions. In fact, based on studies using cells, model organism knockdown/knock-out, and human variants, each subunit plays crucial roles and contributes to the specificity of each AP. These studies also revealed that the sorting and intracellular trafficking function of AP can exert varying effects on pathology by controlling features such as cell development, signal transduction related to the apoptosis and proliferation pathways in cancer cells, organelle integrity, receptor presentation, and viral infection. Although the roles and functions of AP1‒3 are relatively well studied, the functions of the less abundant and more recently identified APs, AP4 and AP5, are still to be investigated. Further studies on these APs may enable a better understanding and targeting of specific diseases.APs known or suggested locations and functions.

Integrated Analysis of the Roles of RNA Binding Proteins and Their Prognostic Value in Clear Cell Renal Cell Carcinoma

Methods

We downloaded the RNA sequencing data of ccRCC from the Cancer Genome Atlas (TCGA) database and identified differently expressed RBPs in different tissues. In this study, we used bioinformatics to analyze the expression and prognostic value of RBPs; then, we performed functional analysis and constructed a protein interaction network for them. We also screened out some RBPs related to the prognosis of ccRCC. Finally, based on the identified RBPs, we constructed a prognostic model that can predict patients' risk of illness and survival time. Also, the data in the HPA database were used for verification.

Results

In our experiment, we obtained 539 ccRCC samples and 72 normal controls. In the subsequent analysis, 87 upregulated RBPs and 38 downregulated RBPs were obtained. In addition, 9 genes related to the prognosis of patients were selected, namely, RPL36A, THOC6, RNASE2, NOVA2, TLR3, PPARGC1A, DARS, LARS2, and U2AF1L4. We further constructed a prognostic model based on these genes and plotted the ROC curve. This ROC curve performed well in judgement and evaluation. A nomogram that can judge the patient's life span is also made.

Conclusion

In conclusion, we have identified differentially expressed RBPs in ccRCC and carried out a series of in-depth research studies, the results of which may provide ideas for the diagnosis of ccRCC and the research of new targeted drugs.

Using Tumor-Infiltrating Immune Cells and a ceRNA Network Model to Construct a Prognostic Analysis Model of Thyroid Carcinoma

Thyroid carcinoma is a solid malignant tumor that has had a fast-growing incidence in recent years. Our research used thyroid carcinoma gene expression profiling from TCGA (The Cancer Genome Atlas) database to identify differentially expressed ceRNAs. Using the gene expression profiling from 502 carcinoma thyroid tissues and 58 normal thyroid tissues from the TCGA database, we established the thyroid carcinoma-specific competitive endogenous RNA (ceRNA) network and found nine overall survival (OS)-associated genes (PRDM1, TGFBR3, E2F1, FGF1, ADAM12, ALPL, RET, AL928654.2, AC128688.2). We quantified the proportions of immune cells using the algorithm “CIBERSORT”, found three OS-associated immune cells (memory B cells, M0 macrophages, and activated dendritic cells), and established a thyroid carcinoma-specific immune cell network based on that. The good reliabilities AUC (area under the curve) of 10-year survival (0.955, 0.944, respectively) were accessed from the nomograms of genes and immune cells. Subsequently, by conducting co-expression analyses, we found a potential regulation network among ceRNAs and immune cells. Besides, we found that ALPL (alkaline phosphatase) and hsa-miR-204-5p were significantly correlated and that ALPL was related to activated dendritic cells. We took advantage of multi-dimensional databases to verify our discovery. Besides, immunohistochemistry (IHC) assays were conducted to detect the expression of a dendritic cell marker (CD11c) and ALPL in thyroid carcinoma (TC) and paracancerous tissues. In summary, our study found a potential mechanism in which hsa-miR-204-5p regulated ALPL in activated dendritic cells, which may allow them to play a critical role in thyroid carcinoma. These findings provide potential prognostic biomarkers and therapeutic targets for thyroid carcinoma.

Human/eukaryotic ribosomal protein L14 (RPL14/eL14) overexpression represses proliferation, migration, invasion and EMT process in nasopharyngeal carcinoma

Although human/eukaryotic ribosomal protein L14 (RPL14/eL14) is known to be associated with a variety of cancers, its role in nasopharyngeal carcinoma (NPC) remains unclear. The aim of this study was to explore the impact of RPL14(eL14) in NPC. The results of quantitative real-time polymerase chain reaction (qRT-PCR), western blot, and immunohistochemical staining revealed that the expression of RPL14(eL14) significantly reduced in NPC tissues and cells. Furthermore, the protein expression of RPL14(eL14) was linked to NPC-related clinical pathological features, including the T and N classification of Tumor Node Metastasis (TNM) staging (all p < 0.05). Cell counting kit-8 (CCK-8) assay and colony formation assay revealed that RPL14(eL14) overexpression repressed NPC cell proliferation. In cell cycle assay, RPL14(eL14) overexpression significantly blocked NPC cells in S phase. Overexpression of RPL14(eL14) repressed cell migration and invasion in NPC as shown by transwell assay and cell scratch healing assay. In addition, RPL14(eL14) was closely correlated with the expression of epithelial–mesenchymal transition (EMT) biomarkers, including E-cadherin, N-cadherin, and vimentin as detected by western blot. In conclusion, our results revealed that RPL14(eL14) may be considered as an antioncogene in NPC, which greatly suppresses cancer progression.

Depletion of MRPL35 inhibits gastric carcinoma cell proliferation by regulating downstream signaling proteins

BACKGROUND

Gastric carcinoma (GC) is a digestive system disease with high morbidity and mortality. However, early clinical detection is difficult, and the therapeutic effect for advanced disease is not satisfactory. Thus, finding new tumor markers and therapeutic targets conducive to the treatment of GC is imperative. MRPL35 is a member of the large subunit family of mitochondrial ribosomal protein. MRPL35 shows the characteristic of oncogene in colorectal cancer and esophageal cancer, which promotes the exploration of the correlation between MRPL35 and GC. We proposed that the expression of MRPL35 might be critical in GC.

AIM

To study the effect of MRPL35 knockdown on GC cell proliferation.

METHODS

The expression of MRPL35 in GC was evaluated based on data from the public tumor database UALCAN (http://www.ualcan.path.uab.edu). The effect of the expression of MRPL35 on the prognosis was evaluated with KMplot (http://www.kmplot.com). The expression of MRPL35 was assessed on the tissue microarray by immunohistochemistry and the level of MRPL35 mRNA in 25 pairs of clinical GC tissues and matched adjacent tissues was detected by quantitative reverse transcription-polymerase chain reaction. Celigo cell count assay, colony formation assay, and flow cytometry were used to assess the role of MRPL35 in GC cell proliferation and apoptosis in vitro. Additionally, tumor formation experiment in BALB/c nude mice was utilized to determine the effect of MRPL35 on GC cell proliferation. After knockdown of MRPL35, related proteins were identified by isobaric tags for relative and absolute quantification analysis, and the expression of related proteins was detected by Western blot.

RESULTS

The expression of MRPL35 was up-regulated in GC (P = 1.77 × 10^-4). The Kaplan-Meier plots of the overall survival indicated that high expression of MRPL35 was associated with a poor survival in GC. Compared with adjacent tissues, the expression of MRPL35 in GC tissues was increased, which was related to age (P = 0.03), lymph node metastasis (P = 0.007), and pathological tumor-node-metastasis stage (P = 0.024). Knockdown of MRPL35 inhibited GC cell proliferation and colony formation and induced apoptosis. Animal experiment results showed that knockdown of MRPL35 inhibited tumor formation in BALB/c nude mice. Western blotting analysis showed that after knockdown of MRPL35, the expression of PICK1 and BCL-XL proteins decreased, and that of AGR2 protein increased.

CONCLUSION

Collectively, our findings demonstrate that knockdown of MRPL35 inhibits GC cell proliferation through related proteins including PICK1, BCL-XL, and AGR2.

The myosin regulatory light chain Myl5 localizes to mitotic spindle poles and is required for proper cell division

Myosins are ATP-dependent actin-based molecular motors critical for diverse cellular processes like intracellular trafficking, cell motility, and cell invasion. During cell division, myosin MYO10 is important for proper mitotic spindle assembly, the anchoring of the spindle to the cortex, and positioning of the spindle to the cell mid-plane. However, myosins are regulated by myosin regulatory light chains (RLCs), and whether RLCs are important for cell division has remained unexplored. Here, we have determined that the previously uncharacterized myosin RLC Myl5 associates with the mitotic spindle and is required for cell division. We show that Myl5 localizes to the leading edge and filopodia during interphase and to mitotic spindle poles and spindle microtubules during early mitosis. Importantly, depletion of Myl5 led to defects in mitotic spindle assembly, chromosome congression, and chromosome segregation and to a slower transition through mitosis. Furthermore, Myl5 bound to MYO10 in vitro and co-localized with MYO10 at the spindle poles. These results suggest that Myl5 is important for cell division and that it may be performing its function through MYO10.

MPscore: A Novel Predictive and Prognostic Scoring for Progressive Meningioma

Simple Summary

Subtyping for meningioma is urgently required to stratify the patients with high risks of recurrence and progression due to the intertumoral heterogeneity in meningioma. Here, we performed a consensus clustering of 179 meningiomas and identified progressive subtype (subtype 3) based the transcriptome profiles. Loss of chromosome 1q along with Neurofibromin 2 (NF2) mutation or loss of chromosome 22p is exclusively presented in subtype 3 meningioma. DNA methylation analyses of meningioma subtypes also suggested hypermethylation was observed in subtype 3 meningioma. Our findings identified low expression of Alkaline Phosphatase (ALPL) is the most significant feature in progressive subtype of meningioma. We constructed and validated a meningioma progression score (MPscore) to characterize the progressive phenotype in meningioma. The predictive accuracy has also been validated in three independent cohorts. Therefore, MPscore can be potentially useful for meningioma recurrence prediction and stratification.

Abstract

Meningioma is the most common tumor in central nervous system (CNS). Although most cases of meningioma are benign (WHO grade I) and curable by surgical resection, a few tumors remain diagnostically and therapeutically challenging due to the frequent recurrence and progression. The heterogeneity of meningioma revealed by DNA methylation profiling suggests the demand of subtyping for meningioma. Therefore, we performed a clustering analyses to characterize the progressive features of meningioma and constructed a meningioma progression score to predict the risk of the recurrence. A total of 179 meningioma transcriptome from RNA sequencing was included for progression subtype clustering. Four biologically distinct subtypes (subtype 1, subtype 2, subtype 3 and subtype 4) were identified. Copy number alternation and genomewide DNA methylation of each subtype was also characterized. Immune cell infiltration was examined by the microenvironment cell populations counter. All anaplastic meningiomas (7/7) and most atypical meningiomas (24/32) are enriched in subtype 3 while no WHO II or III meningioma presents in subtype 1, suggesting subtype 3 meningioma is a progressive subtype. Stemness index and immune response are also heterogeneous across four subtypes. Monocytic lineage is the most immune cell type in all meningiomas, except for subtype 1. CD8 positive T cells are predominantly observed in subtype 3. To extend the clinical utility of progressive meningioma subtyping, we constructed the meningioma progression score (MPscore) by the signature genes in subtype 3. The predictive accuracy and prognostic capacity of MPscore has also been validated in three independent cohort. Our study uncovers four biologically distinct subtypes in meningioma and the MPscore is potentially helpful in the recurrence risk prediction and response to treatments stratification in meningioma.

Transcriptome Analyses Identify an RNA Binding Protein Related Prognostic Model for Clear Cell Renal Cell Carcinoma

RNA binding proteins (RBPs) play a key role in post-transcriptional gene regulation. They have been shown to be dysfunctional in a variety of cancers and are closely related to the occurrence and progression of cancers. However, the biological function and clinical significance of RBPs in clear cell renal carcinoma (ccRCC) are unclear. In our current study, we downloaded the transcriptome data of ccRCC patients from The Cancer Genome Atlas (TCGA) database and identified differential expression of RBPs between tumor tissue and normal kidney tissue. Then the biological function and clinical value of these RBPs were explored by using a variety of bioinformatics techniques. We identified a total of 40 differentially expressed RBPs, including 10 down-regulated RBPs and 30 up-regulated RBPs. Eight RBPs (APOBEC3G, AUH, DAZL, EIF4A1, IGF2BP3, NR0B1, RPL36A, and TRMT1) and nine RBPs (APOBEC3G, AUH, DDX47, IGF2BP3, MOV10L1, NANOS1, PIH1D3, TDRD9, and TRMT1) were identified as prognostic related to overall survival (OS) and disease-free survival (DFS), respectively, and prognostic models for OS and DFS were constructed based on these RBPs. Further analysis showed that OS and DFS were worse in high-risk group than in the low-risk group. The area under the receiver operator characteristic curve of the model for OS was 0.702 at 3 years and 0.726 at 5 years in TCGA cohort and 0.783 at 3 years and 0.795 at 5 years in E-MTAB-1980 cohort, showing good predictive performance. Both models have been shown to independently predict the prognosis of ccRCC patients. We also established a nomogram based on these prognostic RBPs for OS and performed internal validation in the TCGA cohort, showing an accurate prediction of ccRCC prognosis. Stratified analysis showed a significant correlation between the prognostic model for OS and ccRCC progression.

Identification of ribosomal protein family in triple-negative breast cancer by bioinformatics analysis

Triple-negative breast cancer (TNBC) accounts for ∼20% of all breast cancer (BC) cases. The management of TNBC represents a challenge due to its worse prognosis, heterogeneity and lack of targeted therapy. Moreover, its mechanisms are not fully clear. The aim of the study is to identify crucial genes between TNBC and non-TNBC for underlying targets for diagnostic and therapeutic methods of TNBC. The differentially expressed genes (DEGs) between TNBC and non-TNBC were selected from the Gene Expression Omnibus (GEO) database after the integrated analysis of two datasets (GSE65194 and GSE76124). Then Gene ontology (GO) and KEGG analysis were performed by DAVID database, protein-protein interaction (PPI) of DEGs was constructed by Search Tool for the Retrieval of Reciprocity Genes (STRING) database. Furthermore, centrality analysis and module analysis were carried out by Cytoscape to analyze the TNBC-related PPI. Subsequently, overall survival (OS) analysis was performed by GEPIA. Finally, the expressions of these key genes in TNBC and non-TNBC tissues were tested by qRT-PCR. The results showed that 955 DEGs were obtained, which were mainly enriched in ribosome, ribosomal subunit, and so on. Moreover, 19 candidate genes were focused on by centrality analysis and module analysis. Furthermore, we found the low expressions of ribosomal protein S9 (RPS9), ribosomal protein S14 (RPS14), ribosomal protein S27 (RPS27), ribosomal protein L11 (RPL11) and ribosomal protein L14 (RPL14) were related to a poor OS in BC patients. Additionally, qRT-PCR results suggested that these five genes were notably down-regulated in TNBC tissues. In summary, the present study suggests that ribosomal proteins are related to TNBC, and they may play an important role in the diagnosis, treatment and prognosis of TNBC.

Abnormal Expression of Mitochondrial Ribosomal Proteins and Their Encoding Genes with Cell Apoptosis and Diseases

Mammalian mitochondrial ribosomes translate 13 proteins encoded by mitochondrial genes, all of which play roles in the mitochondrial respiratory chain. After a long period of reconstruction, mitochondrial ribosomes are the most protein-rich ribosomes. Mitochondrial ribosomal proteins (MRPs) are encoded by nuclear genes, synthesized in the cytoplasm and then, transported to the mitochondria to be assembled into mitochondrial ribosomes. MRPs not only play a role in mitochondrial oxidative phosphorylation (OXPHOS). Moreover, they participate in the regulation of cell state as apoptosis inducing factors. Abnormal expressions of MRPs will lead to mitochondrial metabolism disorder, cell dysfunction, etc. Many researches have demonstrated the abnormal expression of MRPs in various tumors. This paper reviews the basic structure of mitochondrial ribosome, focuses on the structure and function of MRPs, and their relationships with cell apoptosis and diseases. It provides a reference for the study of the function of MRPs and the disease diagnosis and treatment.

AKAP12 Signaling Complex: Impacts of Compartmentalizing cAMP-Dependent Signaling Pathways in the Heart and Various Signaling Systems

Heart failure is a complex clinical syndrome, represented as an impairment in ventricular filling and myocardial blood ejection. As such, heart failure is one of the leading causes of death in the United States. With a mortality rate of 1 per 8 individuals and a prevalence of 6.2 million Americans, it has been projected that heart failure prevalence will increase by 46% by 2030. Cardiac remodeling (a general determinant of heart failure) is regulated by an extensive network of intertwined intracellular signaling pathways. The ability of signalosomes (molecular signaling complexes) to compartmentalize several cellular pathways has been recently established. These signalosome signaling complexes provide an additional level of specificity to general signaling pathways by regulating the association of upstream signals with downstream effector molecules. In cardiac myocytes, the AKAP12 (A-kinase anchoring protein 12) scaffolds a large signalosome that orchestrates spatiotemporal signaling through stabilizing pools of phosphatases and kinases. Predominantly upon β-AR (β2-adrenergic-receptor) stimulation, the AKAP12 signalosome is recruited near the plasma membrane and binds tightly to β-AR. Thus, one major function of AKAP12 is compartmentalizing PKA (protein kinase A) signaling near the plasma membrane. In addition, it is involved in regulating desensitization, downregulation, and recycling of β-AR. In this review, the critical roles of AKAP12 as a scaffold protein in mediating signaling downstream GPCRs (G protein-coupled receptor) are discussed with an emphasis on its reported and potential roles in cardiovascular disease initiation and progression.

LncRNA-mediated ceRNA network was identified as a crucial determinant of differential effects in periodontitis and periimplantitis by high-throughput sequencing

BACKGROUND AND OBJECTIVE

Although periimplantitis and periodontitis share similar features, particularly clinical features, they are two different diseases and should be analyzed separately. Thus far, few omics-level differences in periimplantitis and periodontitis have been reported. This study was aimed at exploring the differential effects of expression mRNAs, lncRNAs, and miRNAs in periodontitis and periimplantitis by high-throughput sequencing and competitive endogenous RNA (ceRNA) analysis.

METHODS

Gingival tissues of healthy individuals (HI) and periimplantitis (PI) and periodontitis (P) patients were collected and used for genome-wide sequencing. The differentially expressed genes (DEGs) were screened and visualized by R software. The functions and pathways of DEGs were analyzed using Metascape, and the ceRNA network was constructed using the Cytoscape software. Finally, gene set enrichment analysis (GSEA) was used to predict the function of key nodes in ceRNA.

RESULTS AND CONCLUSION

By constructing the regulated ceRNA network, six genes (FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1) and 16 miRNAs (hsa-miR-338-5p, hsa-miR-650, hsa-miR-9-5p, hsa-miR-1290, hsa-miR-544a, hsa-miR-3179, hsa-miR-1269a, hsa-miR-3679-5p, hsa-miR-149-5p, hsa-miR-615-3p, hsa-miR-33b-5p, hsa-miR-31-5p, hsa-miR-4639-5p, hsa-miR-204-5p, hsa-miR-5588-5p, and hsa-mir-196a-5p) were detected. Five long non-coding RNAs (lnc-CORO2B-1, lnc-MBL2-7, lnc-TRIM45-1, lnc-CHST10-2, and lnc-TNP1-6) were found to target these miRNAs in this ceRNA network. The ceRNA network based on transcriptome data revealed that FAM126B, SORL1, PRLR, CPEB2, RAP2C, and YOD1 were crucial proteins of differential effects in periodontitis and periimplantitis. The lncRNA-miRNA-mRNA interaction involved the regulation of the Hippo signaling pathway, Wnt signaling pathway, Toll-like receptor signaling pathway, NOD signaling pathway, oxidative stress, and innate immune process. These regulated pathways and biological processes may be factors contributing to the pathogenesis of periimplantitis being distinct from that of periodontitis.

Identification of key candidate genes and pathways in glioblastoma by integrated bioinformatical analysis

Glioblastoma (GBM), characterized by high morbidity and mortality, is one of the most common lethal diseases worldwide. To identify the molecular mechanisms that contribute to the development of GBM, three cohort profile datasets (GSE50161, GSE90598 and GSE104291) were integrated and thoroughly analyzed; these datasets included 57 GBM cases and 22 cases of normal brain tissue. The current study identified differentially expressed genes (DEGs), and analyzed potential candidate genes and pathways. Additionally, a DEGs-associated protein-protein interaction (PPI) network was established for further investigation. Then, the hub genes associated with prognosis were identified using a Kaplan-Meier analysis based on The Cancer Genome Atlas database. Firstly, the current study identified 378 consistent DEGs (240 upregulated and 138 downregulated). Secondly, a cluster analysis of the DEGs was performed based on functions of the DEGs and signaling pathways were analyzed using the enrichment analysis tool on DAVID. Thirdly, 245 DEGs were identified using PPI network analysis. Among them, two co-expression modules comprising of 30 and 27 genes, respectively, and 35 hub genes were identified using Cytoscape MCODE. Finally, Kaplan-Meier analysis of the hub genes revealed that the increased expression of calcium-binding protein 1 (CABP1) was negatively associated with relapse-free survival. To summarize, all enriched Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways may participate in mechanisms underlying GBM occurrence and progression, however further studies are required. CABP1 may be a key gene associated with the biological process of GBM development and may be involved in a crucial mechanism of GBM progression.