Integrative microarray analysis of pathways dysregulated in metastatic prostate cancer

Different Roles of Tocopherols and Tocotrienols in Chemoprevention and Treatment of Prostate Cancer

The vitamin E family contains α-tocopherol (αT), βT, γT, and δT and α-tocotrienol (TE), βTE, γTE, and δTE. Research has revealed distinct roles of these vitamin E forms in prostate cancer (PCa). The ATBC trial showed that αT at a modest dose significantly decreased PCa mortality among heavy smokers. However, other randomized controlled trials including the Selenium and Vitamin E Cancer Prevention Trial (SELECT) indicate that supplementation of high-dose αT (≥400 IU) does not prevent PCa among nonsmokers. Preclinical cell and animal studies also do not support chemopreventive roles of high-dose αT and offer explanations for increased incidence of early-stage PCa reported in the SELECT. In contrast, accumulating animal studies have demonstrated that γT, δT, γTE, and δTE appear to be effective for preventing early-stage PCa from progression to adenocarcinoma in various PCa models. Existing evidence also support therapeutic roles of γTE and its related combinations against advanced PCa. Mechanistic and cell-based studies show that different forms of vitamin E display varied efficacy, that is, δTE ≥ γTE > δT ≥ γT >> αT, in inhibiting cancer hallmarks and enabling characteristics, including uncontrolled cell proliferation, angiogenesis, and inflammation possibly via blocking 5-lipoxygenase, nuclear factor κB, hypoxia-inducible factor-1α, modulating sphingolipids, and targeting PCa stem cells. Overall, existing evidence suggests that modest αT supplement may be beneficial to smokers and γT, δT, γTE, and δTE are promising agents for PCa prevention for modest-risk to relatively high-risk population. Despite encouraging preclinical evidence, clinical research testing γT, δT, γTE, and δTE for PCa prevention is sparse and should be considered.

Comprehensive assessment of cellular senescence in the tumor microenvironment

Cellular senescence (CS), a state of permanent growth arrest, is intertwined with tumorigenesis. Due to the absence of specific markers, characterizing senescence levels and senescence-related phenotypes across cancer types remain unexplored. Here, we defined computational metrics of senescence levels as CS scores to delineate CS landscape across 33 cancer types and 29 normal tissues and explored CS-associated phenotypes by integrating multiplatform data from ~20 000 patients and ~212 000 single-cell profiles. CS scores showed cancer type-specific associations with genomic and immune characteristics and significantly predicted immunotherapy responses and patient prognosis in multiple cancers. Single-cell CS quantification revealed intra-tumor heterogeneity and activated immune microenvironment in senescent prostate cancer. Using machine learning algorithms, we identified three CS genes as potential prognostic predictors in prostate cancer and verified them by immunohistochemical assays in 72 patients. Our study provides a comprehensive framework for evaluating senescence levels and clinical relevance, gaining insights into CS roles in cancer- and senescence-related biomarker discovery.

BPA-induced prostatic hyperplasia in vitro is correlated with the unbalanced gene expression of AR and ER in the epithelium and stroma

As a typical environmental endocrine disruptor (EED), bisphenol A (BPA) can induce pathological hyperplasia of the prostatic epithelium and stroma. This study concentrates mainly on the effect and underlying mechanisms of BPA on prostatic hyperplasia, which is based on the culture of primary human prostate epithelial cells (HPEpiC) and human prostate fibroblasts (HPrF). In an effect to screen the optimal pro-survival BPA levels, HPEpiC and HPrF were, respectively, exposed to concentration gradients of BPA (10^-12 M-10^-4 M) solution diluted with two corresponding medium and incubated for 72 h at 37°C. CCK-8 assay showed that 10^-9 M-10^-5 M BPA could facilitate the proliferation of HPEpiC, while similar proliferative effect of HPrF only needed 10^-11 M-10^-7 M BPA. HPrF were more sensitive to BPA than HPEpiC. The qualification of PCNA gene expression measured using quantitative real-time polymerase chain reaction (qRT-PCR) also mirrored the BPA-induced cell proliferation. Additionally, our results considered that androgen receptor (AR), estrogen receptor (ERα, ERβ), and NFKB1 gene expressions exhibited up-regulation in HPEpiC treated with 10^-9 M BPA for 72 h. However, in HPrF, the identical BPA treatment could activate ERα, ERβ, and NFKB1 gene expressions and down-regulated the expression of AR levels. It is further confirmed that low-dose BPA can indeed promote the proliferation of human prostate cells in vitro, and the mechanisms of BPA for prostatic epithelial and stromal hyperplasia may not be consistent.

Functional genomics meta-analysis to identify gene set enrichment networks in cardiac hypertrophy

In order to take advantage of the continuously increasing number of transcriptome studies, it is important to develop strategies that integrate multiple expression datasets addressing the same biological question to allow a robust analysis. Here, we propose a meta-analysis framework that integrates enriched pathways identified through the Gene Set Enrichment Analysis (GSEA) approach and calculates for each meta-pathway an empirical p-value. Validation of our approach on benchmark datasets showed comparable or even better performance than existing methods and an increase in robustness with increasing number of integrated datasets. We then applied the meta-analysis framework to 15 functional genomics datasets of physiological and pathological cardiac hypertrophy. Within these datasets we grouped expression sets measured at time points that represent the same hallmarks of heart tissue remodeling ('aggregated time points') and performed meta-analysis on the expression sets assigned to each aggregated time point. To facilitate biological interpretation, results were visualized as gene set enrichment networks. Here, our meta-analysis framework identified well-known biological mechanisms associated with pathological cardiac hypertrophy (e.g., cardiomyocyte apoptosis, cardiac contractile dysfunction, and alteration in energy metabolism). In addition, results highlighted novel, potentially cardioprotective mechanisms in physiological cardiac hypertrophy involving the down-regulation of immune cell response, which are worth further investigation.

Significance of nuclear factor - kappa beta activation on prostate needle biopsy samples in the evaluation of Gleason score 6 prostatic carcinoma indolence

Background

The goal of our study was to find out whether the immunohistochemical expression of nuclear factor-kappa beta (NF-κB) p65 in biopsy samples with Gleason score 3 + 3 = 6 (GS 6) can be a negative predictive factor for Prostate cancer (PCa) indolence.

Patients and methods

Study was conducted on a retrospective cohort of 123 PCa patients with initial total PSA ≤ 10 ng/ml, number of needle biopsy specimens ≥ 8, GS 6 on biopsy and T1/T2 estimated clinical stage who underwent laparoscopic radical prostatectomy and whose archived formalin-fixed and paraffin-embedded (FFPE) prostate needle biopsy specimens were used for additional immunohistochemistry staining for detection of NF-κB p65. Both cytoplasmic and nuclear NF-κB p65 expression in biopsy cores with PCa were correlated with postoperative pathological stage, positive surgical margins, GS and biochemical progression of disease.

Results

After follow-up of 66 months, biochemical progression (PSA ≥ 0.2 ng/ml) occurred in 6 (5.1%) patients, 3 (50%) with GS 6 and 3 (50%) with GS 7 after radical prostatectomy. Both cytoplasmic and nuclear NF-κB p65 expressions were not significantly associated with pathological stage, positive surgical margin and postoperative GS. Patients with positive cytoplasmic NF-kB reaction had significantly more frequent biochemical progression than those with negative cytoplasmic NF-kB reaction with PSA 0.2 ng/ml as cutoff point (p = 0.015) and a trend towards more biochemical progression with PSA ≥ 0.05 ng/ml as cutoff point (p = 0.068).

Conclusions

Cytoplasmic expression of NF-κB is associated with more biochemical progression and might be an independent prognostic factor for recurrence-free survival (RFS), but further studies including larger patient cohorts are needed to confirm these initial results.

Natural forms of vitamin E and metabolites-regulation of cancer cell death and underlying mechanisms

The disappointing results from large clinical studies of α-tocopherol (αT), the major form of vitamin E in tissues, for prevention of chronic diseases including cancer have cast doubt on not only αT but also other forms of vitamin E regarding their role in preventing carcinogenesis. However, basic research has shown that specific forms of vitamin E such as γ-tocopherol (γT), δ-tocopherol (δT), γ-tocotrienol (γTE) and δ-tocotrienol (δTE) can inhibit the growth and induce death of many types of cancer cells, and are capable of suppressing cancer development in preclinical cancer models. For these activities, these vitamin E forms are much stronger than αT. Further, recent research revealed novel anti-inflammatory and anticancer effects of vitamin E metabolites including 13'-carboxychromanols. This review focuses on anti-proliferation and induction of death in cancer cells by vitamin E forms and metabolites, and discuss mechanisms underlying these anticancer activities. The existing in vitro and in vivo evidence indicates that γT, δT, tocotrienols and 13'-carboxychromanols have anti-cancer activities via modulating key signaling or mediators that regulate cell death and tumor progression, such as eicosanoids, NF-κB, STAT3, PI3K, and sphingolipid metabolism. These results provide useful scientific rationales and mechanistic understanding for further translation of basic discoveries to the clinic with respect to potential use of these vitamin E forms and metabolites for cancer prevention and therapy. © 2018 IUBMB Life, 71(4):495-506, 2019.

Androgen receptor activity modulates responses to cisplatin treatment in bladder cancer

Cisplatin (CDDP)-based combination chemotherapy remains the mainstream treatment for advanced bladder cancer. However, its efficacy is often limited due to the development of resistance for which underlying mechanisms are poorly understood. Meanwhile, emerging evidence has indicated the involvement of androgen-mediated androgen receptor (AR) signals in bladder cancer progression. In this study, we aimed to investigate whether AR signals have an impact on sensitivity to CDDP in bladder cancer cells. UMUC3-control-short hairpin RNA (shRNA) cells with endogenous AR and AR-negative 647V/5637 cells stably expressing AR were significantly more resistant to CDDP treatment at its pharmacological concentrations, compared with UMUC3-AR-shRNA and 647V-vector/5637-vector control cells, respectively. A synthetic androgen R1881 significantly reduced CDDP sensitivity in UMUC3, 647V-AR, or 5637-AR cells, and the addition of an anti-androgen hydroxyflutamide inhibited the effect of R1881. In these AR-positive cells, R1881 treatment also induced the expression levels of NF-κB, which is known to involve CDDP resistance, and its phosphorylated form, as well as nuclear translocation of NF-κB. In CDDP-resistant bladder cancer sublines established following long-term culture with CDDP, the expression levels of AR as well as NF-κB and phospho-NF-κB were considerably elevated, compared with respective control sublines. In bladder cancer specimens, there was a strong trend to correlate between AR positivity and chemoresistance. These results suggest that AR activation correlates with CDDP resistance presumably via modulating NF-κB activity in bladder cancer cells. Targeting AR during chemotherapy may thus be a useful strategy to overcome CDDP resistance in patients with AR-positive bladder cancer.

Regulation of mRNA gene expression of members of the NF-κB transcription factor gene family by angiotensin II and relaxin 2 in normal and cancer prostate cell lines

An increasing number of researchers are focusing on the influence of local peptide hormones such as angiotensin II (Ang II) and relaxin 2 (RLN2) in the regulation of inflammation and carcinogenesis. The interaction between the renin‑angiotensin system (RAS) and relaxin family peptide system (RFPS) is known to influence the proliferation, adhesion and migration of normal and cancer prostate cell lines. The aim of the present study was to evaluate changes in the expression of nuclear factor‑κB subunit 1 (NFKB1), nuclear factor‑κB subunit 2 (NFKB2), REL proto‑oncogene nuclear factor‑κB p65 subunit (REL), RELA proto‑oncogene nuclear factor‑κB subunit (RELA) and RELB proto‑oncogene nuclear factor‑κB subunit (RELB) mRNA caused by Ang II and RLN2. The members of NF‑kB family are involved in many processes associated with cancer development and metastasis. Reverse transcription‑quantitative polymerase chain reaction analysis identified that both peptide hormones have an influence on the relative expression of nuclear factor‑κB. Following treatment with either peptide, NFKB1 expression was downregulated in all prostate cancer cell lines (LNCaP, DU‑145 and PC3), but not in normal epithelial cells (PNT1A). Conversely, RELB mRNA was enhanced only in non‑cancerous prostate cells. RELA expression was strongly stimulated in the most aggressive cell line, whereas REL mRNA was unchanged. In many cases, the effect was strictly dependent on the cell line and/or the type of peptide: Ang II increased expression of both RELA and REL genes in the androgen‑dependent cell line while RLN2 enhanced NFKB2 and RELA mRNA in androgen‑independent cells (DU‑145). Further research is needed to understand the regulation of NF‑κB family members by key renin‑angiotensin system and RFPS peptides in prostate cancer cells; however, prostate carcinogenesis appears to be influenced by the balance between the cross‑regulation of nuclear factor‑κB (NF‑κB) and androgen receptor pathways by Ang II and relaxin 2.

DANUBE: Data-driven meta-ANalysis using UnBiased Empirical distributions-applied to biological pathway analysis

Identifying the pathways and mechanisms that are significantly impacted in a given phenotype is challenging. Issues include patient heterogeneity and noise. Many experiments do not have a large enough sample size to achieve the statistical power necessary to identify significantly impacted pathways. Meta-analysis based on combining p-values from individual experiments has been used to improve power. However, all classical meta-analysis approaches work under the assumption that the p-values produced by experiment-level statistical tests follow a uniform distribution under the null hypothesis. Here we show that this assumption does not hold for three mainstream pathway analysis methods, and significant bias is likely to affect many, if not all such meta-analysis studies. We introduce DANUBE, a novel and unbiased approach to combine statistics computed from individual studies. Our framework uses control samples to construct empirical null distributions, from which empirical p-values of individual studies are calculated and combined using either a Central Limit Theorem approach or the additive method. We assess the performance of DANUBE using four different pathway analysis methods. DANUBE is compared with five meta-analysis approaches, as well as with a pathway analysis approach that employs multiple datasets (MetaPath). The 25 approaches have been tested on 16 different datasets related to two human diseases, Alzheimer's disease (7 datasets) and acute myeloid leukemia (9 datasets). We demonstrate that DANUBE overcomes bias in order to consistently identify relevant pathways. We also show how the framework improves results in more general cases, compared to classical meta-analysis performed with common experiment-level statistical tests such as Wilcoxon and t-test.

CX4945 suppresses the growth of castration-resistant prostate cancer cells by reducing AR-V7 expression

PURPOSE

The aberrant expression of casein kinase 2 (CK2) has been reported to be involved in the tumorigenesis and progression of prostate cancer. The inhibition of CK2 activity represses androgen-dependent prostate cancer cells by attenuating the androgen receptor (AR) signaling pathway. In this study, we examined the effect of CK2 inhibition in castration-resistant prostate cancer (CRPC) cells, in which AR variants (ARVs) play a predominant role.

METHODS

A newly synthetic CK2 selective inhibitor CX4945 was utilized to study the effect of CK2 inhibition in CRPC cells by CCK8 assay and colony formation assay. Protein and mRNA levels of full-length AR (AR-FL) and AR-V7 were determined by qPCR and western blot, respectively. The nuclear translocation of p50 and p65 was assessed to reflect the activity of the NF-κB pathway.

RESULTS

CX4945 reduced the proliferation of CRPC cells in a dose-dependent and time-dependent manner. AR-V7 rather than AR-FL was downregulated by CX4945 in both the mRNA and protein level. Furthermore, CX4945 could restore the sensitivity of CRPC cells to bicalutamide. The analysis of possible mechanisms demonstrated that the inhibition of CK2 diminished the phosphorylation of p65 at ser529 and thus attenuated the activity of the NF-κB pathway.

CONCLUSION

The inhibition of CK2 by CX4945 can repress the viability of CRPC cells and restore their sensitivity to anti-androgen therapy by suppressing AR-V7. This finding presents a potential option for the treatment of prostate cancer, especially CRPC.

Effect of PI3K/Akt Signaling Pathway on the Process of Prostate Cancer Metastasis to Bone

We sought to study the effects of PI3K/Akt pathway and its downstream substrate NF-κB on prostate cancer bone metastatic process. Expression level of active p-Akt in PC3 cells was upregulated by transient expression with constitutively active plasmid CA-Akt or, alternatively, suppressed by dominant negative construct DN-Akt. NF-κB activity was determined by luciferase reporter assays. mRNA and protein expressions of receptor activator of NF-κB ligand (RANKL), parathyroid hormone-related protein (PTHrP), and bone morphogenetic protein 2 (BMP-2) were evaluated using RT-PCR and Western blotting. The effect of cross-talk between PC3 and SaOS2 cells on cell proliferation was analyzed using a co-culture system. Stimulation of p-Akt promoted NF-κB activity, and led to an increase in mRNA and protein expressions of RANKL, PTHrP, and BMP-2 in PC3 PCa cells through NF-κB. Co-culturing PC3 and SaOS2 cells significantly increased the expression of p-Akt and the activity of NF-κB, and promoted proliferation of both PC3 and SaOS2 cells. Increasing expression levels of p-Akt by transfection with CA-Akt led to further increase in cells proliferation, whereas NF-κB inhibitor PDTC partially blocked this effect. PI3K/Akt pathway stimulates the expressions of RANKL, PTHrP, and BMP-2 partly through NF-κB, suggesting its importance for bone metastasis of prostate carcinoma. Interaction of prostate cancer cells with bone cells has a stimulatory effect on cell proliferation.

Activation of GRP/GRP-R signaling contributes to castration-resistant prostate cancer progression

Numerous studies indicate that androgen receptor splice variants (ARVs) play a critical role in the development of castration-resistant prostate cancer (CRPC), including the resistance to the new generation of inhibitors of androgen receptor (AR) action. Previously, we demonstrated that activation of NF-κB signaling increases ARVs expression in prostate cancer (PC) cells, thereby promoting progression to CRPC. However, it is unclear how NF-κB signaling is activated in CRPC. In this study, we report that long-term treatment with anti-androgens increases a neuroendocrine (NE) hormone - gastrin-releasing peptide (GRP) and its receptor (GRP-R) expression in PC cells. In addition, activation of GRP/GRP-R signaling increases ARVs expression through activating NF-κB signaling. This results in an androgen-dependent tumor progressing to a castrate resistant tumor. The knock-down of AR-V7 restores sensitivity to antiandrogens of PC cells over-expressing the GRP/GRP-R signaling pathway. These findings strongly indicate that the axis of Androgen-Deprivation Therapy (ADT) induces GRP/GRP-R activity, activation NF-κB and increased levels of AR-V7 expression resulting in progression to CRPC. Both prostate adenocarcinoma and small cell NE prostate cancer express GRP-R. Since the GRP-R is clinically targetable by analogue-based approach, this provides a novel therapeutic approach to treat advanced CRPC.

hsa-miR-135a-1 inhibits prostate cancer cell growth and migration by targeting EGFR

Prostate cancer is one of the leading causes of death in men worldwide. Differentially expressed microRNAs (miRNAs) are associated with metastatic prostate cancer. However, their potential roles for affecting prostate cancer initiation and progression remain largely unknown. Here, we examined the aberrant expression profiles of miRNAs in human metastatic prostate cancer tissues. We further validated our miRNA expression data using two large, independent clinical prostate cancer datasets from the Memorial Sloan Kettering Cancer Center (MSKCC) and The Cancer Genome Atlas (TCGA). Our data support a model in which hsa-miR-135-1 acts as a potential tumor suppressor in metastatic prostate cancer. First, its downregulation was positively correlated with late TNM stage, high Gleason score, and adverse prognosis. Second, cell growth, cell cycle progression, cell migration and invasion, and xenograft tumor formation were dramatically inhibited by miR-135a overexpression. Third, in the microarray gene expression data analysis using Gene Set Enrichment Analysis (GSEA), Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis, Ingenuity Pathway Analysis (IPA), and Oncomine concept analysis, we showed that miR-135a targets multiple oncogenic pathways including epidermal growth factor receptor (EGFR), which we verified using functional experimental assays. These results help advance our understanding of the function of miRNAs in metastatic prostate cancer and provide a basis for further clinical investigation.

β-Ionone and its analogs as promising anticancer agents

β-Ionone is an end-ring analog of β-carotenoids which widely distributed in fruit and vegetables. Recent studies have demonstrated anti-proliferative, anti-metastatic and apoptosis induction properties of β-ionone in vitro and in vivo. Also, the studies have focused on investigating the β-ionone action on different types of malignant cells and the possible mechanisms of action. Moreover, the quest of new synthetic β-ionone-based compounds possessing anti-proliferative, anti-metastatic and apoptosis induction activities may enable the discovery of compounds which can be used in combination regimes thus overcoming tumor resistance to conventional anticancer agents. These new agents will also be useful for targeting distinct signaling pathways, to activate selectively mechanisms for apoptosis in cancer cells but devoid of undesirable side effects. In this paper, we reviewed the potentialities of β-ionone and related compounds in cancer prevention and chemotherapy.

Genome-wide DNA methylation modified by soy phytoestrogens: role for epigenetic therapeutics in prostate cancer?

In prostate cancer, DNA methylation is significantly associated with tumor initiation, progression, and metastasis. Previous studies have suggested that soy phytoestrogens might regulate DNA methylation at individual candidate gene loci and that they play a crucial role as potential therapeutic agents for prostate cancer. The purpose of our study was to examine the modulation effects of phytoestrogens on a genome-wide scale in regards to DNA methylation in prostate cancer. Prostate cancer cell lines DU-145 and LNCaP were treated with 40 μM of genistein and 110 μM of daidzein. DNMT inhibitor 5-azacytidine (2 μM) and the methylating agent budesonide (2 μM) were used to compare their demethylation/methylation effects with phytoestrogens. The regulatory effects of phytoestrogens on DNA methylation were analyzed by using a methyl-DNA immunoprecipitation method coupled with Human DNA Methylation Microarrays (MeDIP-chip). We observed that the methylation profiles of 58 genes were altered by genistein and daidzein treatments in DU-145 and LNCaP prostate cancer cells. In addition, the methylation frequencies of the MAD1L1, TRAF7, KDM4B, and hTERT genes were remarkably modified by genistein treatment. Our results suggest that the modulation effects of phytoestrogens on DNA methylation essentially lead to inhibition of cell growth and induction of apoptosis. Genome-wide methylation profiling reported here suggests that epigenetic regulation mechanisms and, by extension, epigenetics-driven novel therapeutic candidates warrant further consideration in future "omics" studies of prostate cancer.

Negative regulation of RelA phosphorylation: emerging players and their roles in cancer

NF-κB signaling contributes to human disease processes, notably inflammatory diseases and cancer. Many advances have been made in understanding mechanisms responsible for abnormal NF-κB activation with RelA post-translational modification, particularly phosphorylation, proven to be critical for RelA function. While the majority of studies have focused on identifying kinases responsible for NF-κB phosphorylation and pathway activation, recently progress has also been made in understanding the negative regulators important for restraining RelA activity. Here we summarize negative regulators of RelA phosphorylation, their targeting sites in RelA and biological functions through negative regulation of RelA activation. Finally, we emphasize the tumor suppressor-like roles that these negative regulators can assume in human cancers.

Inhibition of NF-kappa B signaling restores responsiveness of castrate-resistant prostate cancer cells to anti-androgen treatment by decreasing androgen receptor-variant expression

Androgen receptor splicing variants (ARVs) that lack the ligand-binding domain (LBD) are associated with the development of castration-resistant prostate cancer (CRPC), including resistance to the new generation of high-affinity anti-androgens. However, the mechanism by which ARV expression is regulated is not fully understood. In this study, we show that the activation of classical nuclear factor-kappa B (NF-κB) signaling increases the expression of ARVs in prostate cancer (PCa) cells and converts androgen-sensitive PCa cells to become androgen-insensitive, whereas downregulation of NF-κB signaling inhibits ARV expression and restores responsiveness of CRPC to anti-androgen therapy. In addition, we demonstrated that combination of anti-androgen with NF-κB-targeted therapy inhibits efficiently tumor growth of human CRPC xenografts. These results indicate that induction of ARVs by activated NF-κB signaling in PCa cells is a critical mechanism by which the PCa progresses to CRPC. This has important implications as it can prolong the survival of CRPC patients by restoring the tumors to once again respond to conventional androgen-deprivation therapy (ADT).

NF-κB gene signature predicts prostate cancer progression

In many patients with prostate cancer, the cancer will be recurrent and eventually progress to lethal metastatic disease after primary treatment, such as surgery or radiation therapy. Therefore, it would be beneficial to better predict which patients with early-stage prostate cancer would progress or recur after primary definitive treatment. In addition, many studies indicate that activation of NF-κB signaling correlates with prostate cancer progression; however, the precise underlying mechanism is not fully understood. Our studies show that activation of NF-κB signaling via deletion of one allele of its inhibitor, IκBα, did not induce prostatic tumorigenesis in our mouse model. However, activation of NF-κB signaling did increase the rate of tumor progression in the Hi-Myc mouse prostate cancer model when compared with Hi-Myc alone. Using the nonmalignant NF-κB-activated androgen-depleted mouse prostate, a NF-κB-activated recurrence predictor 21 (NARP21) gene signature was generated. The NARP21 signature successfully predicted disease-specific survival and distant metastases-free survival in patients with prostate cancer. This transgenic mouse model-derived gene signature provides a useful and unique molecular profile for human prostate cancer prognosis, which could be used on a prostatic biopsy to predict indolent versus aggressive behavior of the cancer after surgery.

A study exploring critical pathways in clear cell renal cell carcinoma

Renal cell carcinoma (RCC) is the most lethal type of cancer in the urinary system and often presents as a metastatic disease. Furthermore, there are no effective treatments for the disease. Several studies based on gene expression profiling have been performed with the aim of gaining insights into the pathogenesis of RCC; however, few studies have investigated RCC at the pathway level to search for the possible pathways involved in clear cell RCC (CCRCC). In this study, gene set enrichment analysis (GSEA) was conducted on microarray datasets from CCRCC tissue. DAVID functional enrichment analysis was performed based on the dysregulated genes that were identified in a meta-analysis performed on the microarray datasets from CCRCC tissue. In GSEA, 17 down- and 12 upregulated pathways coexisted in six datasets. The majority of the upregulated pathways were associated with the immune system. In addition, 32 dysregulated pathways were obtained from DAVID functional enrichment analysis, based on the abnormal genes identified by meta-analysis. This study demonstrated that cross-GSEA is a useful method for exploring the critical pathways involved CCRCC; however, an individual dataset with a small sample may introduce bias. A cross-GSEA based on certain well-designed datasets may be required to further the progress made in this study, following the analysis of its results.

Functional networking of human divergently paired genes (DPGs)

Divergently paired genes (DPGs), also known as bidirectional (head-to-head positioned) genes, are conserved across species and lineages, and thus deemed to be exceptional in genomic organization and functional regulation. Despite previous investigations on the features of their conservation and gene organization, the functional relationship among DPGs in a given species and lineage has not been thoroughly clarified. Here we report a network-based comprehensive analysis on human DPGs and our results indicate that the two members of the DPGs tend to participate in different biological processes while enforcing related functions as modules. Comparing to randomly paired genes as a control, the DPG pairs have a tendency to be clustered in similar “cellular components” and involved in similar “molecular functions”. The functional network bridged by DPGs consists of three major modules. The largest module includes many house-keeping genes involved in core cellular activities. This module also shows low variation in expression in both CNS (central nervous system) and non-CNS tissues. Based on analyses of disease transcriptome data, we further suggest that this particular module may play crucial roles in HIV infection and its disease mechanism.

Tumor necrosis factor receptor associated factor-4: an adapter protein overexpressed in metastatic prostate cancer is regulated by microRNA-29a

The tumor necrosis factor receptor (TNFR)-associated factor 4 (TRAF4) is a member of TRAF family proteins that act as major signal transducers of the TNF receptor and the interleukin-1 receptor/Toll-like receptor (IL-1R/TLR) superfamily. TRAF4 has been reported to be overexpressed in various human cancers. However, the exact mechanisms that regulate the expression of TRAF4 still remain elusive. The objective of the present study was to investigate the regulatory mechanism of TRAF4 expression in prostate cancer. We initially identified microRNA-29a (miR‑29a) as a possible candidate to bind TRAF4 3' untranslated region (3'UTR) by the algorithm, TargetScan. The expression of TRAF4 mRNA and protein was inversely associated with miR-29a expression in prostate cancer cell lines (LNCaP, DU145 and PC3). TRAF4 expression was reduced by the introduction of mimic miR-29a in LNCaP cells. Luciferase activity from the construct harboring wild-type TRAF4 3'UTR was reduced by the mimic miR-29a and this reduction was diminished by introducing mutations at the predicted miR-29a binding site. On the other hand, TRAF4 was upregulated when transfected with the inhibitor of miR-29a in DU145 and PC3 cells. TRAF4 was significantly upregulated in patients with metastatic prostate cancer compared to those with localized prostate cancer. Furthermore, there was a significant inverse correlation between TRAF4 and miR-29a expression in tumor tissues from radical prostatectomy. Considered together, our results suggest that the tumor suppressor microRNA, miR-29a, is one of the regulators of TRAF4 expression in metastatic prostate cancer.

Discovery of cellular proteins required for the early steps of HCV infection using integrative genomics

Successful viral infection requires intimate communication between virus and host cell, a process that absolutely requires various host proteins. However, current efforts to discover novel host proteins as therapeutic targets for viral infection are difficult. Here, we developed an integrative-genomics approach to predict human genes involved in the early steps of hepatitis C virus (HCV) infection. By integrating HCV and human protein associations, co-expression data, and tight junction-tetraspanin web specific networks, we identified host proteins required for the early steps in HCV infection. Moreover, we validated the roles of newly identified proteins in HCV infection by knocking down their expression using small interfering RNAs. Specifically, a novel host factor CD63 was shown to directly interact with HCV E2 protein. We further demonstrated that an antibody against CD63 blocked HCV infection, indicating that CD63 may serve as a new therapeutic target for HCV-related diseases. The candidate gene list provides a source for identification of new therapeutic targets.

Activation of NF-kappa B signaling promotes growth of prostate cancer cells in bone

Patients with advanced prostate cancer almost invariably develop osseous metastasis. Although many studies indicate that the activation of NF-κB signaling appears to be correlated with advanced cancer and promotes tumor metastasis by influencing tumor cell migration and angiogenesis, the influence of altered NF-κB signaling in prostate cancer cells within boney metastatic lesions is not clearly understood. While C4-2B and PC3 prostate cancer cells grow well in the bone, LNCaP cells are difficult to grow in murine bone following intraskeletal injection. Our studies show that when compared to LNCaP, NF-κB activity is significantly higher in C4-2B and PC3, and that the activation of NF-κB signaling in prostate cancer cells resulted in the increased expression of the osteoclast inducing genes PTHrP and RANKL. Further, conditioned medium derived from NF-κB activated LNCaP cells induce osteoclast differentiation. In addition, inactivation of NF-κB signaling in prostate cancer cells inhibited tumor formation in the bone, both in the osteolytic PC3 and osteoblastic/osteoclastic mixed C4-2B cells; while the activation of NF-κB signaling in LNCaP cells promoted tumor establishment and proliferation in the bone. The activation of NF-κB in LNCaP cells resulted in the formation of an osteoblastic/osteoclastic mixed tumor with increased osteoclasts surrounding the new formed bone, similar to metastases commonly seen in patients with prostate cancer. These results indicate that osteoclastic reaction is required even in the osteoblastic cancer cells and the activation of NF-κB signaling in prostate cancer cells increases osteoclastogenesis by up-regulating osteoclastogenic genes, thereby contributing to bone metastatic formation.

TNF-α gene knockout in triple negative breast cancer cell line induces apoptosis

Tumor necrosis factor alpha (TNF-α) is a pro-inflammatory cytokine involved in the promotion and progression of cancer, including triple negative breast cancer cells. Thus, there is significant interest in understanding the molecular signaling pathways that connect TNF-α with the survival of tumor cells. In our experiments, we used as an in vitro model for triple negative breast cancer the cell line Hs578T. The purpose of this study is to determine the gene expression profiling of apoptotic signaling networks after blocking TNF-α formation by using specially designed siRNA molecules to target TNF-α messenger RNA. Knockdown of TNF-α gene was associated with cell proliferation inhibition and apoptosis, as observed by monitoring the cell index using the xCELLigence RTCA System and flow cytometry. PCR array technology was used to examine the transcript levels of 84 genes involved in apoptosis. 15 genes were found to be relevant after comparing the treated group with the untreated one of which 3 were down-regulated and 12 up-regulated. The down-regulated genes are all involved in cell survival, whereas the up-regulated ones are involved in and interact with pro-apoptotic pathways. The results described here indicate that the direct target of TNF-α in the Hs578T breast cancer cell line increases the level of certain pro-apoptotic factors that modulate different cellular networks that direct the cells towards death.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Molecular pathways involved in prostate carcinogenesis: insights from public microarray datasets

BACKGROUND

Prostate cancer is currently the most frequently diagnosed malignancy in men and the second leading cause of cancer-related deaths in industrialized countries. Worldwide, an increase in prostate cancer incidence is expected due to an increased life-expectancy, aging of the population and improved diagnosis. Although the specific underlying mechanisms of prostate carcinogenesis remain unknown, prostate cancer is thought to result from a combination of genetic and environmental factors altering key cellular processes. To elucidate these complex interactions and to contribute to the understanding of prostate cancer progression and metastasis, analysis of large scale gene expression studies using bioinformatics approaches is used to decipher regulation of core processes.

METHODOLOGY/PRINCIPAL FINDINGS

In this study, a standardized quality control procedure and statistical analysis (http://www.arrayanalysis.org/) were applied to multiple prostate cancer datasets retrieved from the ArrayExpress data repository and pathway analysis using PathVisio (http://www.pathvisio.org/) was performed. The results led to the identification of three core biological processes that are strongly affected during prostate carcinogenesis: cholesterol biosynthesis, the process of epithelial-to-mesenchymal transition and an increased metabolic activity.

CONCLUSIONS

This study illustrates how a standardized bioinformatics evaluation of existing microarray data and subsequent pathway analysis can quickly and cost-effectively provide essential information about important molecular pathways and cellular processes involved in prostate cancer development and disease progression. The presented results may assist in biomarker profiling and the development of novel treatment approaches.

Histone methyltransferase NSD2/MMSET mediates constitutive NF-κB signaling for cancer cell proliferation, survival, and tumor growth via a feed-forward loop

Constitutive NF-κB activation by proinflammatory cytokines plays a major role in cancer progression. However, the underlying mechanism is still unclear. We report here that histone methyltransferase NSD2 (also known as MMSET or WHSC1), a target of bromodomain protein ANCCA/ATAD2, acts as a strong coactivator of NF-κB by directly interacting with NF-κB for activation of target genes, including those for interleukin-6 (IL-6), IL-8, vascular endothelial growth factor A (VEGFA), cyclin D, Bcl-2, and survivin, in castration-resistant prostate cancer (CRPC) cells. NSD2 is recruited to the target gene promoters upon induction and mediates NF-κB activation-associated elevation of histone H3K36me2 and H3K36me3 marks at the promoter, which involves its methylase activity. Interestingly, we found that NSD2 is also critical for cytokine-induced recruitment of NF-κB and acetyltransferase p300 and histone hyperacetylation. Importantly, NSD2 is overexpressed in prostate cancer tumors, and its overexpression correlates with NF-κB activation. Furthermore, NSD2 expression is strongly induced by tumor necrosis factor alpha (TNF-α) and IL-6 via NF-κB and plays a crucial role in tumor growth. These results identify NSD2 to be a key chromatin regulator of NF-κB and mediator of the cytokine autocrine loop for constitutive NF-κB activation and emphasize the important roles played by NSD2 in cancer cell proliferation and survival and tumor growth.

Sensitive detection of pathway perturbations in cancers

Background

The normal functioning of a living cell is characterized by complex interaction networks involving many different types of molecules. Associations detected between diseases and perturbations in well-defined pathways within such interaction networks have the potential to illuminate the molecular mechanisms underlying disease progression and response to treatment.

Results

In this paper, we present a computational method that compares expression profiles of genes in cancer samples to samples from normal tissues in order to detect perturbations of pre-defined pathways in the cancer. In contrast to many previous methods, our scoring function approach explicitly takes into account the interactions between the gene products in a pathway. Moreover, we compute the sub-pathway that has the highest score, as opposed to merely computing the score for the entire pathway. We use a permutation test to assess the statistical significance of the most perturbed sub-pathway. We apply our method to 20 pathways in the Netpath database and to the Global Cancer Map of gene expression in 18 cancers. We demonstrate that our method yields more sensitive results than alternatives that do not consider interactions or measure the perturbation of a pathway as a whole. We perform a sensitivity analysis to show that our approach is robust to modest changes in the input data. Our method confirms numerous well-known connections between pathways and cancers.

Conclusions

Our results indicate that integrating differential gene expression with the interaction structure in a pathway is a powerful approach for detecting links between a cancer and the pathways perturbed in it. Our results also suggest that even well-studied pathways may be perturbed only partially in any given cancer. Further analysis of cancer-specific sub-pathways may shed new light on the similarities and differences between cancers.

Accurate evaluation and analysis of functional genomics data and methods

The development of technology capable of inexpensively performing large-scale measurements of biological systems has generated a wealth of data. Integrative analysis of these data holds the promise of uncovering gene function, regulation, and, in the longer run, understanding complex disease. However, their analysis has proved very challenging, as it is difficult to quickly and effectively assess the relevance and accuracy of these data for individual biological questions. Here, we identify biases that present challenges for the assessment of functional genomics data and methods. We then discuss evaluation methods that, taken together, begin to address these issues. We also argue that the funding of systematic data-driven experiments and of high-quality curation efforts will further improve evaluation metrics so that they more-accurately assess functional genomics data and methods. Such metrics will allow researchers in the field of functional genomics to continue to answer important biological questions in a data-driven manner.

Comprehensive literature review and statistical considerations for microarray meta-analysis

With the rapid advances of various high-throughput technologies, generation of ‘-omics’ data is commonplace in almost every biomedical field. Effective data management and analytical approaches are essential to fully decipher the biological knowledge contained in the tremendous amount of experimental data. Meta-analysis, a set of statistical tools for combining multiple studies of a related hypothesis, has become popular in genomic research. Here, we perform a systematic search from PubMed and manual collection to obtain 620 genomic meta-analysis papers, of which 333 microarray meta-analysis papers are summarized as the basis of this paper and the other 249 GWAS meta-analysis papers are discussed in the next companion paper. The review in the present paper focuses on various biological purposes of microarray meta-analysis, databases and software and related statistical procedures. Statistical considerations of such an analysis are further scrutinized and illustrated by a case study. Finally, several open questions are listed and discussed.

Learning from estrogen receptor antagonism: structure-based identification of novel antiandrogens effective against multiple clinically relevant androgen receptor mutants

Current treatment strategy for advanced prostate cancer is to suppress androgen receptor (AR) by castration and antiandrogens. However, several clinically relevant AR mutations cause insensitivity to current antiandrogens and convert them into agonists. We aim to identify full AR antagonists even for AR mutants. As crystal structure of AR ligand-binding domain (LBD) at antagonistic form is not available, we decided to learn from estrogen receptor (ER) antagonism: (i) We built a structural model of wild-type AR-LBD complexed with antiandrogen bicalutamide (wild type/bicalutamide) using ERα-LBD/hydroxytamoxifen structure as the template for helix-12. (ii) By comparative structural analysis of 24 ERα-LBD complexes, we found residues D351 and L354 at helix-3 adopt unique conformations, and distance between them is a marker of ERα-LBD/antagonist complexes. The AR residues corresponding to D351 and L354 are E709 and L712, respectively. We found distance between E709 and L712 of the wild type/bicalutamide model is substantially different from that of AR-LBD/agonist complexes, suggesting this distance could be a marker of antagonistic AR-LBD, which was supported by molecular dynamics simulations. Based on the wild type/bicalutamide model, we discovered compound 3 is a novel antiandrogen effective against the wild type and T877A-, W741C-, and H874Y-mutated androgen receptors. We found compound 3 has dual functions, inhibiting androgen receptor and IKK(β) .

Integrating multiple microarray datasets on oral squamous cell carcinoma to reveal dysregulated networks

BACKGROUND

Oral squamous cell carcinoma (OSCC) is the sixth most common type of carcinoma worldwide. The pathogenic pathways involved in this cancer are mostly unknown; therefore, a better characterization of the OSCC gene expression profile would represent a considerable advance. The public availability of gene expression datasets was meant to obtain new insights on biological processes.

METHODS

We integrated 4 public microarray datasets on OSCC to evaluate the degree of consistency among the biological results obtained in these different studies and to identify common regulatory pathways that could be responsible for tumor growth.

RESULTS

Twelve altered cellular pathways implicated in OSCC and 4 genes altered in the extracellular matrix (ECM) receptor pathway were validated by quantitative real-time polymerase chain reaction (qRT-PCR).

CONCLUSION

Using 4 expression array datasets, we have developed a robust method for analyzing pathways altered in OSCC.

ARTEMIN synergizes with TWIST1 to promote metastasis and poor survival outcome in patients with ER negative mammary carcinoma

Introduction

ARTEMIN (ARTN) is an estrogen regulated growth factor, the expression of which promotes resistance to antiestrogen therapies and predicts poorer survival outcome of patients with estrogen receptor (ER) positive mammary carcinoma (ER+MC) treated with tamoxifen. ARTN is also expressed in ER negative mammary carcinoma (ER-MC). Herein, we determined the role of ARTN in ER-MC and defined the mechanism of action producing poor patient prognosis.

Methods

We modulated the expression of ARTN in two ER- (mesenchymal/claudin-low) mammary carcinoma cell lines (BT549 and MDA-MB-231) by forced expression or small interfering RNA (siRNA) mediated depletion. The effects of modulation of ARTN expression were examined by various in vitro measures of oncogenicity, including the expression of TWIST1 messenger RNA (mRNA) and protein. In vitro results were correlated to xenograft studies in immunodeficient mice. Co-expression of ARTN and TWIST1 and their association to poor survival outcome were examined in a cohort of patients with ER-MC. Pathway analysis was performed by pharmacological inhibition of phosphorylation of AKT (pAKT-Ser 473) or modulation of TWIST1 expression.

Results

ARTN expression resulted in ER-MC cells with enhanced mesenchymal characteristics, including increased invasion and a gene expression profile consistent with enhanced mesenchymal phenotype. ARTN stimulated ER-MC cell anchorage independent and 3D matrigel growth, endothelial cell adhesion and transmigration of ER-MC cells through an endothelial cell barrier. Forced expression of ARTN produced a larger, locally invasive tumour mass with tumour emboli that produced distant metastasis. ARTN regulated TWIST1 expression in ER-MC cells and ARTN expression was significantly correlated to TWIST1 expression in a panel of mammary carcinoma cell lines and in a cohort of patients with ER-MC. Low expression of both ARTN and TWIST1 predicted 100% relapse free and overall survival in patients with ER-MC, whereas high expression of both ARTN and TWIST1 was associated with a poor survival outcome. ARTN stimulated an increase in TWIST1 expression via increased AKT activity. siRNA mediated depletion of TWIST1 abrogated ARTN stimulated cellular behaviour associated with metastasis, and forced expression of TWIST1 abrogated the functional effects of ARTN depletion.

Conclusions

ARTN and TWIST1 synergize to produce a worse outcome in ER-MC and combined inhibition of ARTN and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) may therefore provide a novel therapeutic strategy in this subtype of mammary carcinoma.

A network-based approach to prioritize results from genome-wide association studies

Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call ‘trait prioritized sub-networks.’ As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn’s disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn’s disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses.

Immunotherapy of prostate cancer: should we be targeting stem cells and EMT?

Cancer stem cells have been implicated in a number of solid malignancies including prostate cancer. In the case of localised prostate cancer, patients are often treated with surgery (radical prostatectomy) and/or radiotherapy. However, disease recurrence is an issue in about 30% of patients, who will then go on to receive hormone ablation therapy. Hormone ablation therapy is often palliative in a vast proportion of individuals, and for hormone-refractory patients, there are several immunotherapies targeting a number of prostate tumour antigens which are currently in development. However, clinical responses in this setting are inconsistent, and it is believed that the failure to achieve full and permanent tumour eradication is due to a small, resistant population of cells known as 'cancer stem cells' (CSCs). The stochastic and clonal evolution models are among several models used to describe cancer development. The general consensus is that cancer may arise in any cell as a result of genetic mutations in oncogenes and tumour suppressor genes, which consequently result in uncontrolled cell growth. The cancer stem cell theory, however, challenges previous opinion and proposes that like normal tissues, tumours are hierarchical and only the rare subpopulation of cells at the top of the hierarchy possess the biological properties required to initiate tumourigenesis. Furthermore, where most cancer models infer that every cell within a tumour is equally malignant, i.e. equally capable of reconstituting new tumours, the cancer stem cell theory suggests that only the rare cancer stem cell component possess tumour-initiating capabilities. Hence, according to this model, cancer stem cells are implicated in both tumour initiation and progression. In recent years, the role of epithelial--mesenchymal transition (EMT) in the advancement of prostate cancer has become apparent. Therefore, CSCs and EMT are both likely to play critical roles in prostate cancer tumourigenesis. This review summarises the current immunotherapeutic strategies targeting prostate tumour antigens taking into account the need to consider treatments that target cancer stem cells and cells involved in epithelial--mesenchymal transition.

Network clustering revealed the systemic alterations of mitochondrial protein expression

The mitochondrial protein repertoire varies depending on the cellular state. Protein component modifications caused by mitochondrial DNA (mtDNA) depletion are related to a wide range of human diseases; however, little is known about how nuclear-encoded mitochondrial proteins (mt proteome) changes under such dysfunctional states. In this study, we investigated the systemic alterations of mtDNA-depleted (ρ⁰) mitochondria by using network analysis of gene expression data. By modularizing the quantified proteomics data into protein functional networks, systemic properties of mitochondrial dysfunction were analyzed. We discovered that up-regulated and down-regulated proteins were organized into two predominant subnetworks that exhibited distinct biological processes. The down-regulated network modules are involved in typical mitochondrial functions, while up-regulated proteins are responsible for mtDNA repair and regulation of mt protein expression and transport. Furthermore, comparisons of proteome and transcriptome data revealed that ρ⁰ cells attempted to compensate for mtDNA depletion by modulating the coordinated expression/transport of mt proteins. Our results demonstrate that mt protein composition changed to remodel the functional organization of mitochondrial protein networks in response to dysfunctional cellular states. Human mt protein functional networks provide a framework for understanding how cells respond to mitochondrial dysfunctions.

Mitochondria are dynamic organelles that are essential for energy production and cellular processes in eukaryotic cells, and their functional failure is a major cause of age-associated degenerative diseases. To meet the specific needs of different cellular states, mitochondrial protein repertoires are adjusted. It is critical to characterize the systemic alterations of mitochondria to different cellular states to understand the dynamic organization of mitochondrial systems. In this study, we modularized the quantified proteomics data into protein functional networks to characterize gene expression changes under dysfunctional mitochondrial conditions. Our results demonstrate that mitochondrial protein repertoires changed to compensate for dysfunctional cellular states by reorganizing mitochondrial protein functional network. Through network clustering analysis, we discovered that cells respond to pathological conditions by modulating the coordinated expression/transport of mitochondrial proteins. Network analysis of mt proteins can advance our understanding of dysfunctional mitochondrial systems and elucidate the candidate mt proteins involved in human mitochondrial diseases.

Frequent gene products and molecular pathways altered in prostate cancer- and metastasis-initiating cells and their progenies and novel promising multitargeted therapies

Recent gene expression profiling analyses and gain- and loss-of-function studies performed with distinct prostate cancer (PC) cell models indicated that the alterations in specific gene products and molecular pathways often occur in PC stem/progenitor cells and their progenies during prostate carcinogenesis and metastases at distant sites, including bones. Particularly, the sustained activation of epidermal growth factor receptor (EGFR), hedgehog, Wnt/β-catenin, Notch, hyaluronan (HA)/CD44 and stromal cell-derived factor-1 (SDF-1)/CXC chemokine receptor 4 (CXCR4) during the epithelial-mesenchymal transition (EMT) process may provide critical functions for PC progression to locally invasive, metastatic and androgen-independent disease states and treatment resistance. Moreover, an enhanced glycolytic metabolism in PC stem/progenitor cells and their progenies concomitant with the changes in their local microenvironment, including the induction of tumor hypoxia and release of diverse soluble factors by tumor myofibroblasts, also may promote the tumor growth, angiogenesis and metastases. More particularly, these molecular transforming events may cooperate to upregulate Akt, nuclear factor (NF)-κB, hypoxia-inducible factors (HIFs) and stemness gene products such as Oct3/4, Sox2, Nanog and Bmi-1 in PC cells that contribute to their acquisition of high self-renewal, tumorigenic and invasive capacities and survival advantages during PC progression. Consequently, the molecular targeting of these deregulated gene products in the PC- and metastasis-initiating cells and their progenies represent new promising therapeutic strategies of great clinical interest for eradicating the total PC cell mass and improving current antihormonal treatments and docetaxel-based chemotherapies, thereby preventing disease relapse and the death of PC patients.

The androgen receptor induces integrin α6β1 to promote prostate tumor cell survival via NF-κB and Bcl-xL Independently of PI3K signaling

Recent studies indicate that androgen receptor (AR) signaling is critical for prostate cancer cell survival, even in castration-resistant disease wherein AR continues to function independently of exogenous androgens. Integrin-mediated adhesion to the extracellular matrix is also important for prostate cell survival. AR-positive prostate cancer cells express primarily integrin α6β1 and adhere to a laminin-rich matrix. In this study, we show that active nuclear-localized AR protects prostate cancer cells from death induced by phosphoinositide 3-kinase (PI3K) inhibition when cells adhere to laminin. Resistance to PI3K inhibition is mediated directly by an AR-dependent increase in integrin α6β1 mRNA transcription and protein expression. Subsequent signaling by integrin α6β1 in AR-expressing cells increased NF-κB activation and Bcl-xL expression. Blocking AR, integrin α6, NF-κB, or Bcl-xL concurrent with inhibition of PI3K was sufficient and necessary to trigger death of laminin-adherent AR-expressing cells. Taken together, these results define a novel integrin-dependent survival pathway in prostate cancer cells that is regulated by AR, independent of and parallel to the PI3K pathway. Our findings suggest that combined targeting of both the AR/α6β1 and PI3K pathways may effectively trigger prostate cancer cell death, enhancing the potential therapeutic value of PI3K inhibitors being evaluated in this setting.

Novel approaches and future directions in castration-resistant prostate cancer

Recent advances in the treatment of castration-resistant prostate cancer (CRPC) have started to change the therapeutic landscape allowing clinicians to choose from a broad range of treatment options. Understanding the mechanisms that transform prostate cancer (PCA) into a castration-resistant state has enabled investigators to explore critical pathways involved in such process allowing for rational therapeutic design. These novel therapies complement the modest success that chemotherapy has demonstrated in recent years. In this review, we discuss the different mechanisms that render PCA castration resistant and elaborate on the nonchemotherapy approaches evolving in CRPC. These include agents targeting the epidermal growth factor receptor, endothelin receptor antagonists, angiogenesis inhibitors, immunomodulatory agents, immunotherapy, novel antiandrogens, and delivery of cytotoxic agents via therapeutic antibodies. This timely review coincides with the identification of newer therapies in this setting affirming our steady movement towards better disease control.

A CD133-related gene expression signature identifies an aggressive glioblastoma subtype with excessive mutations

Cancer cells are heterogeneous and, it has been proposed, fall into at least two classes: the tumor-initiating cancer stem cells (CSC) and the more differentiated tumor cells. The transmembrane protein CD133 has been widely used to isolate putative CSC populations in several cancer types, but its validity as a CSC marker and hence its clinical ramifications remain controversial. Here, we conducted transcriptomic profiling of sorted CD133(+) and CD133(-) cells from human glioblastoma multiforme (GBM) and, by subtractive analysis, established a CD133 gene expression signature composed of 214 differentially expressed genes. Extensive computational comparisons with a compendium of published gene expression profiles reveal that the CD133 gene signature transcriptionally resembles human ES cells and in vitro cultured GBM stem cells, and this signature successfully distinguishes GBM from lower-grade gliomas. More importantly, the CD133 gene signature identifies an aggressive subtype of GBM seen in younger patients with shorter survival who bear excessive genomic mutations as surveyed through the Cancer Genome Atlas Network GBM mutation spectrum. Furthermore, the CD133 gene signature distinguishes higher-grade breast and bladder cancers from their lower-grade counterparts. Our systematic analysis provides molecular and genetic support for the stem cell-like nature of CD133(+) cells and an objective means for evaluating cancer aggressiveness.

DEGAS: de novo discovery of dysregulated pathways in human diseases

Background

Molecular studies of the human disease transcriptome typically involve a search for genes whose expression is significantly dysregulated in sick individuals compared to healthy controls. Recent studies have found that only a small number of the genes in human disease-related pathways show consistent dysregulation in sick individuals. However, those studies found that some pathway genes are affected in most sick individuals, but genes can differ among individuals. While a pathway is usually defined as a set of genes known to share a specific function, pathway boundaries are frequently difficult to assign, and methods that rely on such definition cannot discover novel pathways. Protein interaction networks can potentially be used to overcome these problems.

Methodology/Principal Findings

We present DEGAS (DysrEgulated Gene set Analysis via Subnetworks), a method for identifying connected gene subnetworks significantly enriched for genes that are dysregulated in specimens of a disease. We applied DEGAS to seven human diseases and obtained statistically significant results that appear to home in on compact pathways enriched with hallmarks of the diseases. In Parkinson's disease, we provide novel evidence for involvement of mRNA splicing, cell proliferation, and the 14-3-3 complex in the disease progression. DEGAS is available as part of the MATISSE software package (http://acgt.cs.tau.ac.il/matisse).

Conclusions/Significance

The subnetworks identified by DEGAS can provide a signature of the disease potentially useful for diagnosis, pinpoint possible pathways affected by the disease, and suggest targets for drug intervention.

Meta-analysis for pathway enrichment analysis when combining multiple genomic studies

MOTIVATION

Many pathway analysis (or gene set enrichment analysis) methods have been developed to identify enriched pathways under different biological states within a genomic study. As more and more microarray datasets accumulate, meta-analysis methods have also been developed to integrate information among multiple studies. Currently, most meta-analysis methods for combining genomic studies focus on biomarker detection and meta-analysis for pathway analysis has not been systematically pursued.

RESULTS

We investigated two approaches of meta-analysis for pathway enrichment (MAPE) by combining statistical significance across studies at the gene level (MAPE_G) or at the pathway level (MAPE_P). Simulation results showed increased statistical power of meta-analysis approaches compared to a single study analysis and showed complementary advantages of MAPE_G and MAPE_P under different scenarios. We also developed an integrated method (MAPE_I) that incorporates advantages of both approaches. Comprehensive simulations and applications to real data on drug response of breast cancer cell lines and lung cancer tissues were evaluated to compare the performance of three MAPE variations. MAPE_P has the advantage of not requiring gene matching across studies. When MAPE_G and MAPE_P show complementary advantages, the hybrid version of MAPE_I is generally recommended.

AVAILABILITY

http://www.biostat.pitt.edu/bioinfo/

CONTACT

ctseng@pitt.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Discovery of prostate cancer biomarkers by microarray gene expression profiling

Prostate cancer is the most commonly diagnosed malignancy in males in the Western world. This review focuses on advances in biomarker discovery for prostate cancer by microarray profiling of mRNA and microRNA expression. Novel biomarkers are strongly needed to enable more accurate detection of prostate cancer, improve prediction of tumor aggressiveness and facilitate discovery of new therapeutic targets for tailored medicine. Promising molecular markers identified from gene expression profiling studies include AMACR, EZH2, TMPRSS2-ERG, miR-221 and miR-141, which are described in more detail. In addition, a compilation of prognostic gene expression signatures for prediction of prostate cancer patient outcome is provided, and their possible clinical utility is discussed. Furthermore, limitations in the application of microarray-based expression profiling for identification of prostate cancer biomarkers are addressed.

Apomictic and sexual ovules of Boechera display heterochronic global gene expression patterns

We have compared the transcriptomic profiles of microdissected live ovules at four developmental stages between a diploid sexual and diploid apomictic Boechera. We sequenced >2 million SuperSAGE tags and identified (1) heterochronic tags (n = 595) that demonstrated significantly different patterns of expression between sexual and apomictic ovules across all developmental stages, (2) stage-specific tags (n = 577) that were found in a single developmental stage and differentially expressed between the sexual and apomictic ovules, and (3) sex-specific (n = 237) and apomixis-specific (n = 1106) tags that were found in all four developmental stages but in only one reproductive mode. Most heterochronic and stage-specific tags were significantly downregulated during early apomictic ovule development, and 110 were associated with reproduction. By contrast, most late stage-specific tags were upregulated in the apomictic ovules, likely the result of increased gene copy number in apomictic (hexaploid) versus sexual (triploid) endosperm or of parthenogenesis. Finally, we show that apomixis-specific gene expression is characterized by a significant overrepresentation of transcription factor activity. We hypothesize that apomeiosis is associated with global downregulation at the megaspore mother cell stage. As the diploid apomict analyzed here is an ancient hybrid, these data are consistent with the postulated link between hybridization and asexuality and provide a hypothesis for multiple evolutionary origins of apomixis in the genus Boechera.

Modelling p-value distributions to improve theme-driven survival analysis of cancer transcriptome datasets

Background

Theme-driven cancer survival studies address whether the expression signature of genes related to a biological process can predict patient survival time. Although this should ideally be achieved by testing two separate null hypotheses, current methods treat both hypotheses as one. The first test should assess whether a geneset, independent of its composition, is associated with prognosis (frequently done with a survival test). The second test then verifies whether the theme of the geneset is relevant (usually done with an empirical test that compares the geneset of interest with random genesets). Current methods do not test this second null hypothesis because it has been assumed that the distribution of p-values for random genesets (when tested against the first null hypothesis) is uniform. Here we demonstrate that such an assumption is generally incorrect and consequently, such methods may erroneously associate the biology of a particular geneset with cancer prognosis.

Results

To assess the impact of non-uniform distributions for random genesets in such studies, an automated theme-driven method was developed. This method empirically approximates the p-value distribution of sets of unrelated genes based on a permutation approach, and tests whether predefined sets of biologically-related genes are associated with survival. The results from a comparison with a published theme-driven approach revealed non-uniform distributions, suggesting a significant problem exists with false positive rates in the original study. When applied to two public cancer datasets our technique revealed novel ontological categories with prognostic power, including significant correlations between "fatty acid metabolism" with overall survival in breast cancer, as well as "receptor mediated endocytosis", "brain development", "apical plasma membrane" and "MAPK signaling pathway" with overall survival in lung cancer.

Conclusions

Current methods of theme-driven survival studies assume uniformity of p-values for random genesets, which can lead to false conclusions. Our approach provides a method to correct for this pitfall, and provides a novel route to identifying higher-level biological themes and pathways with prognostic power in clinical microarray datasets.

Meta-analysis of glioblastoma multiforme versus anaplastic astrocytoma identifies robust gene markers

Background

Anaplastic astrocytoma (AA) and its more aggressive counterpart, glioblastoma multiforme (GBM), are the most common intrinsic brain tumors in adults and are almost universally fatal. A deeper understanding of the molecular relationship of these tumor types is necessary to derive insights into the diagnosis, prognosis, and treatment of gliomas. Although genomewide profiling of expression levels with microarrays can be used to identify differentially expressed genes between these tumor types, comparative studies so far have resulted in gene lists that show little overlap.

Results

To achieve a more accurate and stable list of the differentially expressed genes and pathways between primary GBM and AA, we performed a meta-analysis using publicly available genome-scale mRNA data sets. There were four data sets with sufficiently large sample sizes of both GBMs and AAs, all of which coincidentally used human U133 platforms from Affymetrix, allowing for easier and more precise integration of data. After scoring genes and pathways within each data set, we combined the statistics across studies using the nonparametric rank sum method to identify the features that differentiate GBMs and AAs. We found >900 statistically significant probe sets after correction for multiple testing from the >22,000 tested. We also used the rank sum approach to select >20 significant Biocarta pathways after correction for multiple testing out of >175 pathways examined. The most significant pathway was the hypoxia-inducible factor (HIF) pathway. Our analysis suggests that many of the most statistically significant genes work together in a HIF1A/VEGF-regulated network to increase angiogenesis and invasion in GBM when compared to AA.

Conclusion

We have performed a meta-analysis of genome-scale mRNA expression data for 289 human malignant gliomas and have identified a list of >900 probe sets and >20 pathways that are significantly different between GBM and AA. These feature lists could be utilized to aid in diagnosis, prognosis, and grade reduction of high-grade gliomas and to identify genes that were not previously suspected of playing an important role in glioma biology. More generally, this approach suggests that combined analysis of existing data sets can reveal new insights and that the large amount of publicly available cancer data sets should be further utilized in a similar manner.

Error control variability in pathway-based microarray analysis

Motivation: The decision to commit some or many false positives in practice rests with the investigator. Unfortunately, not all error control procedures perform the same. Our problem is to choose an error control procedure to determine a P-value threshold for identifying differentially expressed pathways in high-throughput gene expression studies. Pathway analysis involves fewer tests than differential gene expression analysis, on the order of a few hundred. We discuss and compare methods for error control for pathway analysis with gene expression data.

Results: In consideration of the variability in test results, we find that the widely used Benjamini and Hochberg's (BH) false discovery rate (FDR) analysis is less robust than alternative procedures. BH's error control requires a large number of hypothesis tests, a reasonable assumption for differential gene expression analysis, though not the case with pathway-based analysis. Therefore, we advocate through a series of simulations and applications to real gene expression data that researchers control the number of false positives rather than the FDR.

Availability: Our R package, EPath.omg is available at http://sphhp.buffalo.edu/biostat/research/software.

Contact:dlgold@buffalo.edu

Supplementary information:Supplementary data are available at Bioinformatics online.