Identifying differentially expressed genes and small molecule drugs for prostate cancer by a bioinformatics strategy

Vitamin D and K Supplementation Is Associated with Changes in the Methylation Profile of U266-Multiple Myeloma Cells, Influencing the Proliferative Potential and Resistance to Bortezomib

Multiple myeloma (MM) is a plasma cell malignancy that, despite recent advances in therapy, continues to pose a major challenge to hematologists. Currently, different classes of drugs are applied to treat MM, among others, proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies. Most of them participate in an interplay with the immune system, hijacking its effector functions and redirecting them to anti-MM activity. Therefore, adjuvant therapies boosting the immune system may be potentially beneficial in MM therapy. Vitamin D (VD) and vitamin K (VK) have multiple so called "non-classical" actions. They exhibit various anti-inflammatory and anti-cancer properties. In this paper, we investigated the influence of VD and VK on epigenetic alterations associated with the proliferative potential of MM cells and the development of BTZ resistance. Our results showed that the development of BTZ resistance is associated with a global decrease in DNA methylation. On the contrary, both control MM cells and BTZ-resistant MM cells exposed to VD alone and to the combination of VD and VK exhibit a global increase in methylation. In conclusion, VD and VK in vitro have the potential to induce epigenetic changes that reduce the proliferative potential of plasma cells and may at least partially prevent the development of resistance to BTZ. However, further ex vivo and in vivo studies are needed to confirm the results and introduce new supplementation recommendations as part of adjuvant therapy.

Endocrine Disrupting Chemicals Influence Hub Genes Associated with Aggressive Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed cancers among men in the world. Its prevention has been limited because of an incomplete understanding of how environmental exposures to chemicals contribute to the molecular pathogenesis of aggressive PCa. Environmental exposures to endocrine-disrupting chemicals (EDCs) may mimic hormones involved in PCa development. This research aims to identify EDCs associated with PCa hub genes and/or transcription factors (TF) of these hub genes in addition to their protein-protein interaction (PPI) network. We are expanding upon the scope of our previous work, using six PCa microarray datasets, namely, GSE46602, GSE38241, GSE69223, GSE32571, GSE55945, and GSE26126, from the NCBI/GEO, to select differentially expressed genes based on |log2FC| (fold change) ≥ 1 and an adjusted p-value < 0.05. An integrated bioinformatics analysis was used for enrichment analysis (using DAVID.6.8, GO, KEGG, STRING, MCODE, CytoHubba, and GeneMANIA). Next, we validated the association of these PCa hub genes in RNA-seq PCa cases and controls from TCGA. The influence of environmental chemical exposures, including EDCs, was extrapolated using the chemical toxicogenomic database (CTD). A total of 369 overlapping DEGs were identified associated with biological processes, such as cancer pathways, cell division, response to estradiol, peptide hormone processing, and the p53 signaling pathway. Enrichment analysis revealed five up-regulated (NCAPG, MKI67, TPX2, CCNA2, CCNB1) and seven down-regulated (CDK1, CCNB2, AURKA, UBE2C, BUB1B, CENPF, RRM2) hub gene expressions. Expression levels of these hub genes were significant in PCa tissues with high Gleason scores ≥ 7. These identified hub genes influenced disease-free survival and overall survival of patients 60-80 years of age. The CTD studies showed 17 recognized EDCs that affect TFs (NFY, CETS1P54, OLF1, SRF, COMP1) that are known to bind to our PCa hub genes, namely, NCAPG, MKI67, CCNA2, CDK1, UBE2C, and CENPF. These validated differentially expressed hub genes can be potentially developed as molecular biomarkers with a systems perspective for risk assessment of a wide-ranging list of EDCs that may play overlapping and important role(s) in the prognosis of aggressive PCa.

Functional impact of multi-omic interactions in breast cancer subtypes

Multi-omic approaches are expected to deliver a broader molecular view of cancer. However, the promised mechanistic explanations have not quite settled yet. Here, we propose a theoretical and computational analysis framework to semi-automatically produce network models of the regulatory constraints influencing a biological function. This way, we identified functions significantly enriched on the analyzed omics and described associated features, for each of the four breast cancer molecular subtypes. For instance, we identified functions sustaining over-representation of invasion-related processes in the basal subtype and DNA modification processes in the normal tissue. We found limited overlap on the omics-associated functions between subtypes; however, a startling feature intersection within subtype functions also emerged. The examples presented highlight new, potentially regulatory features, with sound biological reasons to expect a connection with the functions. Multi-omic regulatory networks thus constitute reliable models of the way omics are connected, demonstrating a capability for systematic generation of mechanistic hypothesis.

Environmental Phenol and Paraben Exposure Risks and Their Potential Influence on the Gene Expression Involved in the Prognosis of Prostate Cancer

Prostate cancer (PCa) is one of the leading malignant tumors in US men. The lack of understanding of the molecular pathology on the risk of food supply chain exposures of environmental phenol (EP) and paraben (PB) chemicals limits the prevention, diagnosis, and treatment options. This research aims to utilize a risk assessment approach to demonstrate the association of EP and PB exposures detected in the urine samples along with PCa in US men (NHANES data 2005−2015). Further, we employ integrated bioinformatics to examine how EP and PB exposure influences the molecular pathways associated with the progression of PCa. The odds ratio, multiple regression model, and Pearson coefficients were used to evaluate goodness-of-fit analyses. The results demonstrated associations of EPs, PBs, and their metabolites, qualitative and quantitative variables, with PCa. The genes responsive to EP and PB exposures were identified using the Comparative Toxicogenomic Database (CTD). DAVID.6.8, GO, and KEGG enrichment analyses were used to delineate their roles in prostate carcinogenesis. The plug-in CytoHubba and MCODE completed identification of the hub genes in Cytoscape software for their roles in the PCa prognosis. It was then validated by using the UALCAN database by evaluating the expression levels and predictive values of the identified hub genes in prostate cancer prognosis using TCGA data. We demonstrate a significant association of higher levels of EPs and PBs in the urine samples, categorical and numerical confounders, with self-reported PCa cases. The higher expression levels of the hub genes (BUB1B, TOP2A, UBE2C, RRM2, and CENPF) in the aggressive stages (Gleason score > 8) of PCa tissues indicate their potential role(s) in the carcinogenic pathways. Our results present an innovative approach to extrapolate and validate hub genes responsive to the EPs and PBs, which may contribute to the severity of the disease prognosis, especially in the older population of US men.

The role of GTPase-activating protein ARHGAP26 in human cancers

Rho GTPases are molecular switches that play an important role in regulating the behavior of a variety of tumor cells. RhoA GTPase-activating protein 26 (ARHGAP26) is a GTPase-activating protein and inhibits the activity of Rho GTPases by promoting the hydrolytic ability of Rho GTPases. It also affects tumorigenesis and progression of various tumors through several methods, including formation of abnormal fusion genes and circular RNA. This review summarizes the biological functions and molecular mechanisms of ARHGAP26 in different tumors, proposes the potential clinical value of ARHGAP26 in cancer treatment, and discusses current issues that need to be addressed.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients

Background

Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients.

Methods

We obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration.

Results

We initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells.

Conclusion

The autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning

PURPOSE

Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient prognosis based on immune-related genes (IRGs).

METHODS

We analyzed the ES gene expression profile dataset, GSE17679, from the GEO database and extracted differential expressed IRGs (DEIRGs). Then, we conducted functional correlation and protein-protein interaction (PPI) analyses of the DEIRGs and used the machine learning algorithm-iterative Lasso Cox regression analysis to build an optimal DEIRG signature. In addition, we applied ES samples from the ICGC database to test the optimal gene signature. We performed univariate and multivariate Cox regressions on clinicopathological characteristics and optimal gene signature to evaluate whether signature is an important prognostic factor. Finally, we calculated the infiltration of 24 immune cells in ES using the ssGSEA algorithm, and analyzed the correlation between the DEIRGs in the optimal gene signature and immune cells.

RESULTS

A total of 249 DEIRGs were screened and an 11-gene signature with the strongest correlation with patient prognoses was analyzed using a machine learning algorithm. The 11-gene signature also had a high prognostic value in the ES external verification set. Univariate and multivariate Cox regression analyses showed that 11-gene signature is an independent prognostic factor. We found that macrophages and cytotoxic, CD8 T, NK, mast, B, NK CD56bright, TEM, TCM, and Th2 cells were significantly related to patient prognoses; the infiltration of cytotoxic and CD8 T cells in ES was significantly different. By correlating prognostic biomarkers with immune cell infiltration, we found that FABP4 and macrophages, and NDRG1 and Th2 cells had the strongest correlation.

CONCLUSION

Overall, the IRG-related 11-gene signature can be used as a reliable ES prognostic biomarker and can provide guidance for personalized ES therapy.

MiR-509-3-5p-NONHSAT112228.2 Axis Regulates p21 and Suppresses Proliferation and Migration of Lung Cancer Cells

Background:

Although the involvement of individual microRNA and lncRNA in the regulation of p21 expression has largely been evidenced, less is known about the roles of functional interactions between miRNAs and lncRNAs in p21 expression. Our previous work demonstrated that miR-509- 3-5p could block cancer cell growth.

Methods:

To gain an insight into the role of miR-509-3-5p in the regulation of p21 expression, we performed in silico prediction and showed that miR-509-3-5p might target the NONHSAT112228.2, a sense-overlapping lncRNA transcribed by a non-code gene overlapping with p21 gene. Mutation and luciferase report analysis suggested that miR-509-3-5p could target NONHSAT112228.2, thereby blocking its expression. Consistently, NONHSAT112228.2 expression was inversely correlated with both miR-509-3-5p and p21 expression in cancer cells. Ectopic expression of miR-509-3-5p and knockdown of NONHSAT112228.2 both promoted proliferation and migration of cancer cells.

Results:

Interestingly, high-expression of NONHSAT112228.2 accompanied by low-expression of p21 was observed in lung cancer tissues and associated with lower overall survival.

Conclusion:

Taken together, our study found a new regulatory pathway of p21, in which MiR-509-3-5p functionally interacts with NONHSAT112228.2 to release p21 expression. MiR-509-3-5p— NONHSAT112228.2 regulatory axis can inhibit the proliferation and migration of lung cancer cells.

Gene Expression Profiling Analysis Reveals Putative Phytochemotherapeutic Target for Castration-Resistant Prostate Cancer

Prostate cancer is the leading cause of cancer death among men globally, with castration development resistant contributing significantly to treatment failure and death. By analyzing the differentially expressed genes between castration-induced regression nadir and castration-resistant regrowth of the prostate, we identified soluble guanylate cyclase 1 subunit alpha as biologically significant to driving castration-resistant prostate cancer. A virtual screening of the modeled protein against 242 experimentally-validated anti-prostate cancer phytochemicals revealed potential drug inhibitors. Although, the identified four non-synonymous somatic point mutations of the human soluble guanylate cyclase 1 gene could alter its form and ligand binding ability, our analysis identified compounds that could effectively inhibit the mutants together with wild-type. Of the identified phytochemicals, (8′R)-neochrome and (8′S)-neochrome derived from the Spinach (Spinacia oleracea) showed the highest binding energies against the wild and mutant proteins. Our results identified the neochromes and other phytochemicals as leads in pharmacotherapy and as nutraceuticals in management and prevention of castration-resistance prostate cancers.

The emerging role of miR-506 in cancer

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression. They are involved in almost all biological processes, and many have been identified as potential oncogenes or tumor suppressor genes. miR-506 was recently discovered to play pivotal roles in regulating cell proliferation, differentiation, migration and invasion. Dysregulation of miR-506 has been demonstrated in multiple types of cancers; however, whether it functions as an oncogene or a tumor suppressor seems to be context-dependent. Altered miR-506 expression in cancer is caused by promoter methylation and changes in upstream transcription factors. In this review, we summarize the current understanding of the diverse roles and underlying mechanisms of miR-506 and its involvement in cancer, and suggest the potential therapeutic strategy based on miR-506.

MiR-509-3-5p causes aberrant mitosis and anti-proliferative effect by suppression of PLK1 in human lung cancer A549 cells

MicroRNAs (miRNAs) are potent post-transcriptional regulators of gene expression and play roles in DNA damage response (DDR). PLK1 is identified as a modulator of DNA damage checkpoint. Although down-regulation of PLK1 by certain microRNAs has been reported, little is known about the interplay between PLK1 and miR-509-3-5p in DDR. Here we have demonstrated that miR-509-3-5p repressed PLK1 expression by targeting PLK1 3'-UTR, thereby causing mitotic aberration and growth arrest of human lung cancer A549 cells. Repression of PLK1 by miR-509-3-5p was further evidenced by over-expression of miR-509-3-5p in A549, HepG2 and HCT116p53(-/-) cancer cells, in which PLK1 protein was suppressed. Consistently, miR-509-3-5p was stimulated, while PLK1 protein was down-regulated in A549 cells exposed to CIS and ADR, suggesting that suppression of PLK1 by miR-509-3-5p is a component of CIS/ADR-induced DDR pathway. Flow cytometry and immunofluorescence labeling showed that over-expression of miR-509-3-5p in A549 induced G2/M arrest and aberrant mitosis characterized by abnormal bipolar mitotic spindles, condensed chromosomes, lagging DNA and chromosome bridges. In addition, over-expression of miR-509-3-5p markedly blocked A549 cell proliferation and sensitized the cells to CIS and ADR treatment. Taken together, miR-509-3-5p is a feasible suppressor for cancer by targeting PLK1. Our data may provide aid in potential design of combined chemotherapy and in our better understanding of the roles of microRNAs in response to DNA damage.

Expression Profiling Identifies Bezafibrate as Potential Therapeutic Drug for Lung Adenocarcinoma

Drug-induced gene expression patterns that invert disease profiles have recently been illustrated to be a new strategy for drug-repositioning. In the present study, we validated this approach and focused on prediction of novel drugs for lung adenocarcinoma (AC), for which there is a pressing need to find novel therapeutic compounds. Firstly, connectivity map (CMap) analysis computationally predicted bezafibrate as a putative compound against lung AC. Then this hypothesis was verified by in vitro assays of anti-proliferation and cell cycle arrest. In silico docking evidence indicated that bezafibrate could target cyclin dependent kinase 2(CDK2), which regulates progression through the cell cycle. Furthermore, we found that bezafibrate can significantly down-regulate the expression of CDK2 mRNA and p-CDK2. Using a nude mice xenograft model, we also found that bezafibrate could inhibit tumor growth of lung AC in vivo. In conclusion, this study proposed bezafibrate as a potential therapeutic option for lung AC patients, illustrating the potential of in silico drug screening.

Cellular prostatic acid phosphatase (cPAcP) serves as a useful biomarker of histone deacetylase (HDAC) inhibitors in prostate cancer cell growth suppression

Background

Prostate cancer (PCa) is the most commonly diagnosed solid tumor and the second leading cancer death in the United States, and also one of the major cancer-related deaths in Chinese. Androgen deprivation therapy (ADT) is the first line treatment for metastatic PCa. PCa ultimately relapses with subsequent ADT treatment failure and becomes castrate-resistant (CR). It is important to develop effective therapies with a surrogate marker towards CR PCa.

Method

Histone deacetylase (HDAC) inhibitors were examined to determine their effects in androgen receptor (AR)/cellular prostatic acid phosphatase (cPAcP)-positive PCa cells, including LNCaP C-33, C-81, C4-2 and C4-2B and MDA PCa2b androgen-sensitive and androgen-independent cells, and AR/cPAcP-negative PCa cells, including PC-3 and DU 145 cells. Cell growth was determined by cell number counting. Western blot analyses were carried out to determine AR, cPAcP and PSA protein levels.

Results

cPAcP protein level was increased by HDAC inhibitor treatment. Valproic acid, a HDAC inhibitor, suppressed the growth of AR/cPAcP-positive PCa cells by over 50% in steroid-reduced conditions, higher than on AR/cPAcP-negative PCa cells. Further, HDAC inhibitor pretreatments increased androgen responsiveness as demonstrated by PSA protein level quantitation.

Conclusion

Our results clearly demonstrate that HDAC inhibitors can induce cPAcP protein level, increase androgen responsiveness, and exhibit higher inhibitory activities on AR/cPAcP-positive PCa cells than on AR/cPAcP-negative PCa cells. Upon HDAC inhibitor pretreatment, PSA level was greatly elevated by androgens. This data indicates the potential clinical importance of cPAcP serving as a useful biomarker in the identification of PCa patient sub-population suitable for HDAC inhibitor treatment.