Prognostic and Immune Infiltration Value of Proteasome Assembly Chaperone (PSMG) Family Genes in Lung Adenocarcinoma.

The complexity of lung adenocarcinoma (LUAD) including many interacting biological processes makes it difficult to find therapeutic biomarkers for treatment. Previous studies demonstrated that PSMG (proteasome assembly chaperone) family members regulate the degradation of abnormal proteins. However, transcript expressions of this gene family in LUAD still need to be more fully investigated. Therefore, we used a holistic bioinformatics approach to explore PSMG genes involved in LUAD patients by integrating several high-throughput databases and tools including The Cancer Genome Atlas (TCGA), and Kaplan-Meier plotter database. These data demonstrated that PSMG3 and PSMG4 were expressed at significantly higher levels in neoplastic cells than in normal lung tissues. Notably, increased expressions of these proteins were correlated with poor prognoses of lung cancer patients, which probably confirmed their fundamental roles in the staging of LUAD tumors. Meanwhile, it was also indicated that there were positive correlations between PSMG family genes and the immune response, metabolism of ubiquinone, cell cycle regulatory pathways, and heat shock protein 90 (HSP90)/phosphatidylinositol 3-kinase (PI3K)/Wnt signaling. Experimental data also confirmed that the knockdown of PSMG4 in LUAD cell lines decreased cell proliferation and influenced expressions of downstream molecules. Collectively, this study revealed that PSMG family members are novel prognostic biomarkers for LUAD progression, which also provide new therapeutic targets of LUAD patients.

Glutamine synthetase regulates the immune microenvironment and cancer development through the inflammatory pathway.

Although adjuvant tamoxifen therapy is beneficial to estrogen receptor-positive (ER+) breast cancer patients, a significant number of patients still develop metastasis or undergo recurrence. Therefore, identifying novel diagnostic and prognostic biomarkers for these patients is urgently needed. Predictive markers and therapeutic strategies for tamoxifen-resistant ER+ breast cancer are not clear, and micro (mi)RNAs have recently become a focal research point in cancer studies owing to their regulation of gene expressions, metabolism, and many other physiological processes. Therefore, systematic investigation is required to understand the modulation of gene expression in tamoxifen-resistant patients. High-throughput technology uses a holistic approach to observe differences among expression profiles of thousands of genes, which provides a comprehensive level to extensively investigate functional genomics and biological processes. Through a bioinformatics analysis, we revealed that glutamine synthetase/glutamate-ammonia ligase (GLUL) might play essential roles in the recurrence of tamoxifen-resistant ER+ patients. GLUL increases intracellular glutamine usage via glutaminolysis, and further active metabolism-related downstream molecules in cancer cell. However, how GLUL regulates the tumor microenvironment for tamoxifen-resistant ER+ breast cancer remains unexplored. Analysis of MetaCore pathway database demonstrated that GLUL is involved in the cell cycle, immune response, interleukin (IL)-4-induced regulators of cell growth, differentiation, and metabolism-related pathways. Experimental data also confirmed that the knockdown of GLUL in breast cancer cell lines decreased cell proliferation and influenced expressions of specific downstream molecules. Through a Connectivity Map (CMap) analysis, we revealed that certain drugs/molecules, including omeprazole, methacholine chloride, ioversol, fulvestrant, difenidol, cycloserine, and MK-801, may serve as potential treatments for tamoxifen-resistant breast cancer patients. These drugs may be tested in combination with current therapies in tamoxifen-resistant breast cancer patients. Collectively, our study demonstrated the crucial roles of GLUL, which provide new targets for the treatment of tamoxifen-resistant breast cancer patients.

Comprehensive analysis of prognostic significance of cadherin (CDH) gene family in breast cancer.

Breast cancer is one of the leading deaths in all kinds of malignancies; therefore, it is important for early detection. At the primary tumor site, tumor cells could take on mesenchymal properties, termed the epithelial-to-mesenchymal transition (EMT). This process is partly regulated by members of the cadherin (CDH) family of genes, and it is an essential step in the formation of metastases. There has been a lot of study of the roles of some of the CDH family genes in cancer; however, a holistic approach examining the roles of distinct CDH family genes in the development of breast cancer remains largely unexplored. In the present study, we used a bioinformatics approach to examine expression profiles of CDH family genes using the Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), cBioPortal, MetaCore, and Tumor IMmune Estimation Resource (TIMER) platforms. We revealed that CDH1/2/4/11/12/13 messenger (m)RNA levels are overexpressed in breast cancer cells compared to normal cells and were correlated with poor prognoses in breast cancer patients' distant metastasis-free survival. An enrichment analysis showed that high expressions of CDH1/2/4/11/12/13 were significantly correlated with cell adhesion, the extracellular matrix remodeling process, the EMT, WNT/beta-catenin, and interleukin-mediated immune responses. Collectively, CDH1/2/4/11/12/13 are thought to be potential biomarkers for breast cancer progression and metastasis.

Comparison of Transcriptomic Signatures between Monkeypox-Infected Monkey and Human Cell Lines.

Monkeypox virus (MPV) is a smallpox-like virus belonging to the genus Orthopoxvirus of the family Poxviridae. Unlike smallpox with no animal reservoir identified and patients suffering from milder symptoms with less mortality, several animals were confirmed to serve as natural hosts of MPV. The reemergence of a recently reported monkeypox epidemic outbreak in nonendemic countries has raised concerns about a global outburst. Since the underlying mechanism of animal-to-human transmission remains largely unknown, comprehensive analyses to discover principal differences in gene signatures during disease progression have become ever more critical. In this study, two MPV-infected in vitro models, including human immortal epithelial cancer (HeLa) cells and rhesus monkey (Macaca mulatta) kidney epithelial (MK2) cells, were chosen as the two subjects to identify alterations in gene expression profiles, together with co-regulated genes and pathways that are affected during monkeypox disease progression. Using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and MetaCore analyses, we discovered that elevated expression of genes associated with interleukins (ILs), G protein-coupled receptors (GPCRs), heat shock proteins (HSPs), Toll-like receptors (TLRs), and metabolic-related pathways play major roles in disease progression of both monkeypox-infected monkey MK2 and human HeLa cell lines. Interestingly, our analytical results also revealed that a cluster of differentiation 40 (CD40), plasmin, and histamine served as major regulators in the monkeypox-infected monkey MK2 cell line model, while interferons (IFNs), macrophages, and neutrophil-related signaling pathways dominated the monkeypox-infected human HeLa cell line model. Among immune pathways of interest, apart from traditional monkeypox-regulated signaling pathways such as nuclear factor- (NF-κB), mitogen-activated protein kinases (MAPKs), and tumor necrosis factors (TNFs), we also identified highly significantly expressed genes in both monkey and human models that played pivotal roles during the progression of monkeypox infection, including CXCL1, TNFAIP3, BIRC3, IL6, CCL2, ZC3H12A, IL11, CSF2, LIF, PTX3, IER3, EGR1, ADORA2A, and DUOX1, together with several epigenetic regulators, such as histone cluster family gene members, HIST1H3D, HIST1H2BJ, etc. These findings might contribute to specific underlying mechanisms related to the pathophysiology and provide suggestions regarding modes of transmission, post-infectious sequelae, and vaccine development for monkeypox in the future.

Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer.

The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan-Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer.

Prognostic and immune infiltration signatures of proteasome 26S subunit, non-ATPase (PSMD) family genes in breast cancer patients.

The complexity of breast cancer includes many interacting biological processes that make it difficult to find appropriate therapeutic treatments. Therefore, identifying potential diagnostic and prognostic biomarkers is urgently needed. Previous studies demonstrated that 26S proteasome delta subunit, non-ATPase (PSMD) family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcriptional expressions of PSMD family genes in breast cancer still remain largely unexplored. Consequently, we used a holistic bioinformatics approach to explore PSMD genes involved in breast cancer patients by integrating several high-throughput databases, including The Cancer Genome Atlas (TCGA), cBioPortal, Oncomine, and Kaplan-Meier plotter. These data demonstrated that PSMD1, PSMD2, PSMD3, PSMD7, PSMD10, PSMD12, and PSMD14 were expressed at significantly higher levels in breast cancer tissue compared to normal tissues. Notably, the increased expressions of PSMD family genes were correlated with poor prognoses of breast cancer patients, which suggests their roles in tumorigenesis. Meanwhile, network and pathway analyses also indicated that PSMD family genes were positively correlated with ubiquinone metabolism, immune system, and cell-cycle regulatory pathways. Collectively, this study revealed that PSMD family members are potential prognostic biomarkers for breast cancer progression and possible promising clinical therapeutic targets.

Gene signatures and potential therapeutic targets of Middle East respiratory syndrome coronavirus (MERS-CoV)-infected human lung adenocarcinoma epithelial cells.

BACKGROUND: Pathogenic coronaviruses include Middle East respiratory syndrome coronavirus (MERS-CoV), severe acute respiratory syndrome coronavirus (SARS-CoV), and SARS-CoV-2. These viruses have induced outbreaks worldwide, and there are currently no effective medications against them. Therefore, there is an urgent need to develop potential drugs against coronaviruses. METHODS: High-throughput technology is widely used to explore differences in messenger (m)RNA and micro (mi)RNA expression profiles, especially to investigate protein-protein interactions and search for new therapeutic compounds. We integrated miRNA and mRNA expression profiles in MERS-CoV-infected cells and compared them to mock-infected controls from public databases. RESULTS: Through the bioinformatics analysis, there were 251 upregulated genes and eight highly differentiated miRNAs that overlapped in the two datasets. External validation verified that these genes had high expression in MERS-CoV-infected cells, including RC3H1, NF-κB, CD69, TNFAIP3, LEAP-2, DUSP10, CREB5, CXCL2, etc. We revealed that immune, olfactory or sensory system-related, and signal-transduction networks were discovered from upregulated mRNAs in MERS-CoV-infected cells. In total, 115 genes were predicted to be related to miRNAs, with the intersection of upregulated mRNAs and miRNA-targeting prediction genes such as TCF4, NR3C1, and POU2F2. Through the Connectivity Map (CMap) platform, we suggested potential compounds to use against MERS-CoV infection, including diethylcarbamazine, harpagoside, bumetanide, enalapril, and valproic acid. CONCLUSIONS: The present study illustrates the crucial roles of miRNA-mRNA interacting networks in MERS-CoV-infected cells. The genes we identified are potential targets for treating MERS-CoV infection; however, these could possibly be extended to other coronavirus infections.

Analysis of LAGEs Family Gene Signature and Prognostic Relevance in Breast Cancer.

Breast cancer (BRCA) is one of the most complex diseases and involves several biological processes. Members of the L-antigen (LAGE) family participate in the development of various cancers, but their expressions and prognostic values in breast cancer remain to be clarified. High-throughput methods for exploring disease progression mechanisms might play a pivotal role in the improvement of novel therapeutics. Therefore, gene expression profiles and clinical data of LAGE family members were acquired from the cBioportal database, followed by verification using the Oncomine and The Cancer Genome Atlas (TCGA) databases. In addition, the Kaplan-Meier method was applied to explore correlations between expressions of LAGE family members and prognoses of breast cancer patients. MetaCore, GlueGo, and GluePedia were used to comprehensively study the transcript expression signatures of LAGEs and their co-expressed genes together with LAGE-related signal transduction pathways in BRCA. The result indicated that higher LAGE3 messenger (m)RNA expressions were observed in BRCA tissues than in normal tissues, and they were also associated with the stage of BRCA patients. Kaplan-Meier plots showed that overexpression of LAGE1, LAGE2A, LAGE2B, and LAGE3 were highly correlated to poor survival in most types of breast cancer. Significant associations of LAGE family genes were correlated with the cell cycle, focal adhesion, and extracellular matrix (ECM) receptor interactions as indicated by functional enrichment analyses. Collectively, LAGE family members' gene expression levels were related to adverse clinicopathological factors and prognoses of BRCA patients; therefore, LAGEs have the potential to serve as prognosticators of BRCA patients.

Novel signaling pathways regulate SARS-CoV and SARS-CoV-2 infectious disease.

ABSTRACT: Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 induces severe infection, and it is responsible for a worldwide disease outbreak starting in late 2019. Currently, there are no effective medications against coronavirus. In the present study, we utilized a holistic bioinformatics approach to study gene signatures of SARS-CoV- and SARS-CoV-2-infected Calu-3 lung adenocarcinoma cells. Through the Gene Ontology platform, we determined that several cytokine genes were up-regulated after SARS-CoV-2 infection, including TNF, IL6, CSF2, IFNL1, IL-17C, CXCL10, and CXCL11. Differentially regulated pathways were detected by the Kyoto Encyclopedia of Genes and Genomes, gene ontology, and Hallmark platform, including chemokines, cytokines, cytokine receptors, cytokine metabolism, inflammation, immune responses, and cellular responses to the virus. A Venn diagram was utilized to illustrate common overlapping genes from SARS-CoV- and SARS-CoV-2-infected datasets. An Ingenuity pathway analysis discovered an enrichment of tumor necrosis factor- (TNF-) and interleukin (IL)-17-related signaling in a gene set enrichment analysis. Downstream networks were predicted by the Database for Annotation, Visualization, and Integrated Discovery platform also revealed that TNF and TNF receptor 2 signaling elicited leukocyte recruitment, activation, and survival of host cells after coronavirus infection. Our discovery provides essential evidence for transcript regulation and downstream signaling of SARS-CoV and SARS-CoV-2 infection.

Gene signatures of SARS-CoV/SARS-CoV-2-infected ferret lungs in short- and long-term models.

Coronaviruses (CoVs) consist of six strains, and the severe acute respiratory syndrome coronavirus (SARS-CoV), newly found coronavirus (SARS-CoV-2) has rapidly spread leading to a global outbreak. The ferret (Mustela putorius furo) serves as a useful animal model for studying SARS-CoV/SARS-CoV-2 infection and developing therapeutic strategies. A holistic approach for distinguishing differences in gene signatures during disease progression is lacking. The present study discovered gene expression profiles of short-term (3 days) and long-term (14 days) ferret models after SARS-CoV/SARS-CoV-2 infection using a bioinformatics approach. Through Gene Ontology (GO) and MetaCore analyses, we found that the development of stemness signaling was related to short-term SARS-CoV/SARS-CoV-2 infection. In contrast, pathways involving extracellular matrix and immune responses were associated with long-term SARS-CoV/SARS-CoV-2 infection. Some highly expressed genes in both short- and long-term models played a crucial role in the progression of SARS-CoV/SARS-CoV-2 infection, including DPP4, BMP2, NFIA, AXIN2, DAAM1, ZNF608, ME1, MGLL, LGR4, ABHD6, and ACADM. Meanwhile, we revealed that metabolic, glucocorticoid, and reactive oxygen species-associated networks were enriched in both short- and long-term infection models. The present study showed alterations in gene expressions from short-term to long-term SARS-CoV/SARS-CoV-2 infection. The current result provides an explanation of the pathophysiology for post-infectious sequelae and potential targets for treatment.

PODXL2 maintains cellular stemness and promotes breast cancer development through the Rac1/Akt pathway.

The cluster of differentiation 34 (CD34) family, which includes CD34, podocalyxin-like protein 1 (PODXL), and PODXL2, are type-I transmembrane sialomucins and markers of hematopoietic stem cells (HSCs) and vascular-associated tissues. CD34 family proteins are expressed by endothelial cells and hematopoietic precursors. PODXL is well known to be associated with invadopodia formation and to promote the epithelial-mesenchymal transition, tumor migration and invasion. PODXL expression was correlated with poor survival of cancer patients. However, the role of PODXL2 in cancer has been less fully explored. To reveal the novel role of PODXL2 in breast cancer, the present study evaluated PODXL2 levels in relation to clinical outcomes of cancer patients by performing a bioinformatics analysis using the Oncomine database, Kaplan-Meier plots, and the CCLE database. Empirical validation of bioinformatics predictions was conducted utilizing the short hairpin (sh)-RNA silencing method for PODXL2 in the BT474 invasive ductal breast carcinoma cell line. The bioinformatics analysis revealed that PODXL2 overexpression was correlated with poor survival of breast cancer patients, suggesting an oncogenic role of PODXL2 in breast carcinoma. In a validation experiment, knockdown of PODXL2 in BT474 cells slightly influenced cell proliferation, suppressed migration, and inhibited expressions of downstream molecules, including Ras-related C3 botulinum toxin substrate 1 (Rac1), phosphorylated (p)-Akt (S473), and p-paxillin (Y31) proteins. In addition, knockdown of PODXL2 reduced expression levels of cancer stem cell (CSC) markers, including Oct-4 and Nanog, and the breast CSC marker aldehyde dehydrogenase 1 (ALDH1). Collectively, our present study demonstrated that PODXL2 plays a crucial role in cancer development and could serve as a potential prognostic biomarker in breast cancer patients.

Overexpressed gene signature of EPH receptor A/B family in cancer patients-comprehensive analyses from the public high-throughput database.

Although a previous study suggested that erythropoietin-producing hepatoma (EPH) receptors play important roles in tumor progression and the overexpression of EPHs in cancer patients is related to poor prognoses, high-throughput gene expression profiling of EPH family members in different types and subtypes of cancers has so far not been conducted. We herein carried out a series of bioinformatic analyses on expressive profiles of every EPH member across 21 different types of clinical cancers versus matched normal tissues gathered from the Oncomine platform. We validated these results by protein expression study of all EPHs family members by The Human Protein Atlas repository. Our results uncovered the overexpression of most EPH subunits in numerous cancer types, especially the dramatic overexpression of six EPHs members, namely EPHA1, EPHA2, EPHA3, EPHA4 and EPHB1, EPHB2, EPHB3, EPHB4 in bladder, colorectal, esophageal, gastric, and prostate cancers. Furthermore, EPHB2 was specifically highly expressed in cervical cancer, EPHA3 in liver cancer, and EPHB1 in uterine cancer. Collectively, expressive profiles of these EPHs were confirmed and correlated with different cancer subtypes as potential biomarkers. This study provides useful information for further studies on cancer development and clinical treatments.

Gene signatures and potential therapeutic targets of amino acid metabolism in estrogen receptor-positive breast cancer.

Increased activity of amino acid transporters has been observed in a wide variety of cancers. However, whether amino acid metabolism is related to estrogen receptor-positive (ER+) breast cancer has been less well studied. We identified the rate-limiting enzyme involved in amino acid metabolism associated with ER+ breast cancer by integrating numerous bioinformatics tools and laboratory studies. The bioinformatics analysis revealed that highly expressed genes in ER+ breast cancer patients were correlated with breast cancer-related pathways, including ESR1 and PI3K signaling. The metabolic signaling and the amino acid metabolism were significantly regulated in breast neoplasms. We used the ER+ breast cancer cell line MCF-7 and breast cancer tissue from National Cheng Kung University Hospital to validate our findings in bioinformatics. In estradiol-treated MCF-7 cells, genes associated with anabolic metabolism of serine and methionine and genes associated with catabolic metabolism of tyrosine, phenylalanine and arginine were upregulated. Furthermore, the expression levels of ARG2, PSAT1, PSPH, TH, PAH, and MAT1A mRNA were increased in breast cancer patients relative to controls. The aforementioned genes were also found to be highly correlated with distant metastasis-free survival in breast cancer patients. High expression levels of ARG2, CBS, PHGDH, AHCY, HAL, TDO2, SHMT2, MAT1A, MAT2A, GLDC, GLS2, BCAT2, GLUD1, PAH and MTR contributed to poor prognoses, whereas high mRNA expression levels of HECA, CTH, PRODH, TAT, and MAT2B were correlated with good prognoses. FDA-approved drugs, including piperlongumine, ellipticine, etidronic acid, harmine, and meclozine, may have novel therapeutic effects in ER+ patients based on connectivity map (CMap) analyses. Collectively, our present study demonstrated that amino acid metabolism genes play crucial roles in tumor development and may serve as prospective drug targets or biomarkers for ER+ breast cancer.

Distinct expression of CDCA3, CDCA5, and CDCA8 leads to shorter relapse free survival in breast cancer patient.

Breast cancer is a dangerous disease that results in high mortality rates for cancer patients. Many methods have been developed for the treatment and prevention of this disease. Determining the expression patterns of certain target genes in specific subtypes of breast cancer is important for developing new therapies for breast cancer. In the present study, we performed a holistic approach to screening the mRNA expression of six members of the cell division cycle-associated gene family (CDCA) with a focus on breast cancer using the Oncomine and The Cancer Cell Line Encyclopedia (CCLE) databases. Furthermore, Gene Expression-Based Outcome for Breast Cancer Online (GOBO) was also used to deeply mine the expression of each CDCA gene in clinical breast cancer tissue and breast cancer cell lines. Finally, the mRNA expression of the CDCA genes as related to breast cancer patient survival were analyzed using a Kaplan-Meier plot. CDCA3, CDCA5, and CDCA8 mRNA expression levels were significantly higher than the control sample in both clinical tumor sample and cancer cell lines. These highly expressed genes in the tumors of breast cancer patients dramatically reduced patient survival. The interaction network of CDCA3, CDCA5, and CDCA8 with their co-expressed genes also revealed that CDCA3 expression was highly correlated with cell cycle related genes such as CCNB2, CDC20, CDKN3, and CCNB1. CDCA5 expression was correlated with BUB1 and TRIP13, while CDCA8 expression was correlated with BUB1 and CCNB1. Altogether, these findings suggested CDCA3, CDCA5, and CDCA8 could have a high potency as targeted breast cancer therapies.

TGF-beta1 increases motility and alphavbeta3 integrin up-regulation via PI3K, Akt and NF-kappaB-dependent pathway in human chondrosarcoma cells.

Transforming growth factor-beta1 (TGF-beta1) plays an essential role in tumor progression and metastasis. Integrins are the major adhesive molecules in mammalian cells. Here we found that TGF-beta1 increased the migration and cell surface expression of alphavbeta3 integrin in human chondrosarcoma cells (JJ012 cells). Phosphatidylinositol 3-kinase inhibitor (PI3K; Ly294002) or Akt inhibitor inhibited the TGF-beta1-induced increase the migration of chondrosarcoma cells. TGF-beta1 stimulation increased the phosphorylation of p85 subunit of PI3K, and serine 473 of Akt. In addition, treatment of JJ102 cells with NF-kappaB inhibitor (PDTC) or IkappaB protease inhibitor (TPCK) inhibited TGF-beta1-induced cells migration and integrins expression. Treatment of JJ012 cells with TGF-beta1-induced IkappaB kinase alpha/beta (IKKalpha/beta) phosphorylation, IkappaBalpha phosphorylation, p65 Ser(536) phosphorylation, and kappaB-luciferase activity. The TGF-beta1-mediated increases in IKKalpha/beta phosphorylation and p65 Ser(536) phosphorylation were inhibited by Ly294002 and Akt inhibitor. Cotransfection with p85 and Akt mutants also reduced the TGF-beta1-induced kappaB-luciferase activity. Taken together, these results suggest that the TGF-beta1 acts through PI3K/Akt, which in turn activates IKKalpha/beta and NF-kappaB, resulting in the activations of alphavbeta3 integrins and contributing the migration of chondrosarcoma cells.