Gene signatures and prognostic analyses of the Tob/BTG pituitary tumor-transforming gene (PTTG) family in clinical breast cancer patients

Pituitary tumor transforming gene 1 promotes proliferation and malignant phenotype in osteosarcoma via NF-κB signaling

BACKGROUND

Pituitary tumor transforming gene (PTTG) is an oncogene reported to be actively promotes tumorigenesis in multiple tumors. Osteosarcoma (OS) is the most common primary osseous sarcoma, however, the functional significance and mechanisms underlying whether and how PTTG1 promotes OS remain largely unknown.

METHODS

Here, in our study, PTTG1 levels in clinical samples and cell lines were determined by western blotting and immunohistochemistry. The viability and migratory/invasive potential of OS cells were assessed using Cell Counting Kit-8, colony formation, wound healing, and Transwell assays. The effects of PTTG1 on NF-κB signaling pathways were evaluated both in vivo and in vitro.

RESULTS

An abnormally elevated expression of PTTG1was confirmed in human OS tissues and OS cell lines and PTTG1 levels were positively correlated with OS clinicopathological grade. We further showed that knocking down PTTG1 attenuated the viability and migratory/invasive capacity of OS cells (MG63 and HOS-8603). Additionally, the following key mechanistic principle was revealed: knockdown PTTG1-mediated OS tumorgenesis supression was associated with inactivation of the NF-κB pathway. We confirmed these results by additional nonpharmacological intervention and same conclusions were obtained in the context of opposite functional analyses. Furthermore, we also demonstrated that OS cell lines overexpressed PTTG1 showed increased tumorigenesis in athymic nude mice.

CONCLUSIONS

To sum up, the present study suggests that PTTG1 is involved in the enhancement of the malignancy and carcinogenesis of OS by regulating NF-κB signaling. Accordingly, PTTG1 likely functions as an oncogene in OS and may represent a potential therapeutic target for this cancer.

Synthetic Thioesters of Thiamine: Promising Tools for Slowing Progression of Neurodegenerative Diseases

Thiamine (vitamin B1) is essential for the brain. This is attributed to the coenzyme role of thiamine diphosphate (ThDP) in glucose and energy metabolism. The synthetic thiamine prodrug, the thioester benfotiamine (BFT), has been extensively studied and has beneficial effects both in rodent models of neurodegeneration and in human clinical studies. BFT has no known adverse effects and improves cognitive outcomes in patients with mild Alzheimer's disease. In cell culture and animal models, BFT has antioxidant and anti-inflammatory properties that seem to be mediated by a mechanism independent of the coenzyme function of ThDP. Recent in vitro studies show that another thiamine thioester, O,S-dibenzoylthiamine (DBT), is even more efficient than BFT, especially with respect to its anti-inflammatory potency, and is effective at lower concentrations. Thiamine thioesters have pleiotropic properties linked to an increase in circulating thiamine concentrations and possibly in hitherto unidentified open thiazole ring derivatives. The identification of the active neuroprotective metabolites and the clarification of their mechanism of action open extremely promising perspectives in the field of neurodegenerative, neurodevelopmental, and psychiatric conditions. The present review aims to summarize existing data on the neuroprotective effects of thiamine thioesters and give a comprehensive account.

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.

Risk Stratification for Breast Cancer Patient by Simultaneous Learning of Molecular Subtype and Survival Outcome Using Genetic Algorithm-Based Gene Set Selection

Simple Summary

Patient stratification is clinically important because it allows us to understand the characteristics and establish treatment strategies for a group. Transcriptomic data play an important role in determining molecular subtypes and predicting survival. In the case of breast cancer, although the order of prognosis according to molecular subtypes is well known, there is heterogeneity even within a subtype. Therefore, patient stratification considering both molecular subtypes and survival outcomes is required. In this study, a methodology to handle this problem is presented. A genetic algorithm is used to select a set of genes, and a risk score is assigned to each patient using their expression level. According to the risk score, patients are ordered and stratified considering molecular subtypes and survival outcomes. Consequently, informative genes for patient stratification with respect to both aspects could be nominated, and the usefulness of the risk score was shown through comparison with other indicators.

Abstract

Patient stratification is a clinically important task because it allows us to establish and develop efficient treatment strategies for particular groups of patients. Molecular subtypes have been successfully defined using transcriptomic profiles, and they are used effectively in clinical practice, e.g., PAM50 subtypes of breast cancer. Survival prediction contributed to understanding diseases and also identifying genes related to prognosis. It is desirable to stratify patients considering these two aspects simultaneously. However, there are no methods for patient stratification that consider molecular subtypes and survival outcomes at once. Here, we propose a methodology to deal with the problem. A genetic algorithm is used to select a gene set from transcriptome data, and their expression quantities are utilized to assign a risk score to each patient. The patients are ordered and stratified according to the score. A gene set was selected by our method on a breast cancer cohort (TCGA-BRCA), and we examined its clinical utility using an independent cohort (SCAN-B). In this experiment, our method was successful in stratifying patients with respect to both molecular subtype and survival outcome. We demonstrated that the orders of patients were consistent across repeated experiments, and prognostic genes were successfully nominated. Additionally, it was observed that the risk score can be used to evaluate the molecular aggressiveness of individual patients.

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.

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.

Update on Thiamine Triphosphorylated Derivatives and Metabolizing Enzymatic Complexes

While the cellular functions of the coenzyme thiamine (vitamin B1) diphosphate (ThDP) are well characterized, the triphosphorylated thiamine derivatives, thiamine triphosphate (ThTP) and adenosine thiamine triphosphate (AThTP), still represent an intriguing mystery. They are present, generally in small amounts, in nearly all organisms, bacteria, fungi, plants, and animals. The synthesis of ThTP seems to require ATP synthase by a mechanism similar to ATP synthesis. In E. coli, ThTP is synthesized during amino acid starvation, while in plants, its synthesis is dependent on photosynthetic processes. In E. coli, ThTP synthesis probably requires oxidation of pyruvate and may play a role at the interface between energy and amino acid metabolism. In animal cells, no mechanism of regulation is known. Cytosolic ThTP levels are controlled by a highly specific cytosolic thiamine triphosphatase (ThTPase), coded by thtpa, and belonging to the ubiquitous family of the triphosphate tunnel metalloenzymes (TTMs). While members of this protein family are found in nearly all living organisms, where they bind organic and inorganic triphosphates, ThTPase activity seems to be restricted to animals. In mammals, THTPA is ubiquitously expressed with probable post-transcriptional regulation. Much less is known about the recently discovered AThTP. In E. coli, AThTP is synthesized by a high molecular weight protein complex from ThDP and ATP or ADP in response to energy stress. A better understanding of these two thiamine derivatives will require the use of transgenic models.

Potential Prognostic Biomarkers of OSBPL Family Genes in Patients with Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal malignancy with poor survival outcomes. In addition, oxysterol-binding protein-like (OSBPL) family members are reported to be involved in lipid binding and transport and play critical roles in tumorigenesis. However, relationships between PDAC and OSBPL family members have not comprehensively been elucidated. In this study, we used the Oncomine and GEPIA 2 databases to analyze OSBPL transcription expressions in PDAC. The Kaplan–Meier plotter and TIMER 2.0 were used to assess the relationships between overall survival (OS) and immune-infiltration with OSBPL family members. Co-expression data from cBioPortal were downloaded to assess the correlated pathways with OSBPL gene family members using DAVID. The expressions of OSBPL3, OSBPL8, OSBPL10, and OSBPL11 were found to be highly upregulated in PDAC. Low expressions of OSBPL3, OSBPL8, and OSBPL10 indicated longer OS. The functions of OSBPL family members were mainly associated with several potential signaling pathways in cancer cells, including ATP binding, integrin binding, receptor binding, and the renin-angiotensin system (RAS) signaling pathway. The transcription levels of OSBPL gene family members were connected with several immune infiltrates. Collectively, OSBPL family members are influential biomarkers for the early diagnosis of PDAC and have prognostic value, with the promise of precise treatment of PDAC in the future.

Prognoses and genomic analyses of proteasome 26S subunit, ATPase (PSMC) family genes in clinical breast cancer

Breast cancer is a complex disease, and several processes are involved in its development. Therefore, potential therapeutic targets need to be discovered for these patients. Proteasome 26S subunit, ATPase gene (PSMC) family members are well reported to be involved in protein degradation. However, their roles in breast cancer are still unknown and need to be comprehensively researched. Leveraging publicly available databases, such as cBioPortal and Oncomine, for high-throughput transcriptomic profiling to provide evidence-based targets for breast cancer is a rapid and robust approach. By integrating the aforementioned databases with the Kaplan–Meier plotter database, we investigated potential roles of six PSMC family members in breast cancer at the messenger RNA level and their correlations with patient survival. The present findings showed significantly higher expression profiles of PSMC2, PSMC3, PSMC4, PSMC5, and PSMC6 in breast cancer compared to normal breast tissues. Besides, positive correlations were also revealed between PSMC family genes and ubiquinone metabolism, cell cycle, and cytoskeletal remodeling. Meanwhile, we discovered that high levels of PSMC1, PSMC3, PSMC4, PSMC5, and PSMC6 transcripts were positively correlated with poor survival, which likely shows their importance in breast cancer development. Collectively, PSMC family members have the potential to be novel and essential prognostic biomarkers for breast cancer development.

Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach

Breast cancer is a heterogeneous disease involving complex interactions of biological processes; thus, it is important to develop therapeutic biomarkers for treatment. Members of the dipeptidyl peptidase (DPP) family are metalloproteases that specifically cleave dipeptides. This family comprises seven members, including DPP3, DPP4, DPP6, DPP7, DPP8, DPP9, and DPP10; however, information on the involvement of DPPs in breast cancer is lacking in the literature. As such, we aimed to study their roles in this cancerous disease using publicly available databases such as cBioportal, Oncomine, and Kaplan–Meier Plotter. These databases comprise comprehensive high-throughput transcriptomic profiles of breast cancer across multiple datasets. Furthermore, together with investigating the messenger RNA expression levels of these genes, we also aimed to correlate these expression levels with breast cancer patient survival. The results showed that DPP3 and DPP9 had significantly high expression profiles in breast cancer tissues relative to normal breast tissues. High expression levels of DPP3 and DPP4 were associated with poor survival of breast cancer patients, whereas high expression levels of DPP6, DPP7, DPP8, and DPP9 were associated with good prognoses. Additionally, positive correlations were also revealed of DPP family genes with the cell cycle, transforming growth factor (TGF)-beta, kappa-type opioid receptor, and immune response signaling, such as interleukin (IL)-4, IL6, IL-17, tumor necrosis factor (TNF), and interferon (IFN)-alpha/beta. Collectively, DPP family members, especially DPP3, may serve as essential prognostic biomarkers in breast cancer.

Comprehensive Analysis of Prognostic and Genetic Signatures for General Transcription Factor III (GTF3) in Clinical Colorectal Cancer Patients Using Bioinformatics Approaches

Colorectal cancer (CRC) has the fourth-highest incidence of all cancer types, and its incidence has steadily increased in the last decade. The general transcription factor III (GTF3) family, comprising GTF3A, GTF3B, GTF3C1, and GTFC2, were stated to be linked with the expansion of different types of cancers; however, their messenger (m)RNA expressions and prognostic values in colorectal cancer need to be further investigated. To study the transcriptomic expression levels of GTF3 gene members in colorectal cancer in both cancerous tissues and cell lines, we first performed high-throughput screening using the Oncomine, GEPIA, and CCLE databases. We then applied the Prognoscan database to query correlations of their mRNA expressions with the disease-specific survival (DSS), overall survival (OS), and disease-free survival (DFS) status of the colorectal cancer patient. Furthermore, proteomics expressions of GTF3 family members in clinical colorectal cancer specimens were also examined using the Human Protein Atlas. Finally, genomic alterations of GTF3 family gene expressions in colorectal cancer and their signal transduction pathways were studied using cBioPortal, ClueGO, CluePedia, and MetaCore platform. Our findings revealed that GTF3 family members' expressions were significantly correlated with the cell cycle, oxidative stress, WNT/β-catenin signaling, Rho GTPases, and G-protein-coupled receptors (GPCRs). Clinically, high GTF3A and GTF3B expressions were significantly correlated with poor prognoses in colorectal cancer patients. Collectively, our study declares that GTF3A was overexpressed in cancer tissues and cell lines, particularly colorectal cancer, and it could possibly step in as a potential prognostic biomarker.

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

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.

CCDC167 as a potential therapeutic target and regulator of cell cycle-related networks in breast cancer

According to cancer statistics reported in 2020, breast cancer constitutes 30% of new cancer cases diagnosed in American women. Histological markers of breast cancer are expressions of the estrogen receptor (ER), the progesterone receptor (PR), and human epidermal growth factor receptor (HER)-2. Up to 80% of breast cancers are grouped as ER-positive, which implies a crucial role for estrogen in breast cancer development. Therefore, identifying potential therapeutic targets and investigating their downstream pathways and networks are extremely important for drug development in these patients. Through high-throughput technology and bioinformatics screening, we revealed that coiled-coil domain-containing protein 167 (CCDC167) was upregulated in different types of tumors; however, the role of CCDC167 in the development of breast cancer still remains unclear. Integrating many kinds of databases including ONCOMINE, MetaCore, IPA, and Kaplan-Meier Plotter, we found that high expression levels of CCDC167 predicted poor prognoses of breast cancer patients. Knockdown of CCDC167 attenuated aggressive breast cancer growth and proliferation. We also demonstrated that treatment with fluorouracil, carboplatin, paclitaxel, and doxorubicin resulted in decreased expression of CCDC167 and suppressed growth of MCF-7 cells. Collectively, these findings suggest that CCDC167 has high potential as a therapeutic target for breast cancer.