"Topological significance" analysis of gene expression and proteomic profiles from prostate cancer cells reveals key mechanisms of androgen response

The Heterogeneity of Lipid Metabolism in Cancer

The study of cancer cell metabolism has traditionally focused on glycolysis and glutaminolysis. However, lipidomic technologies have matured considerably over the last decade and broadened our understanding of how lipid metabolism is relevant to cancer biology [1-3]. Studies now suggest that the reprogramming of cellular lipid metabolism contributes directly to malignant transformation and progression [4, 5]. For example, de novo lipid synthesis can supply proliferating tumor cells with phospholipid components that comprise the plasma and organelle membranes of new daughter cells [6, 7]. Moreover, the upregulation of mitochondrial β-oxidation can support tumor cell energetics and redox homeostasis [8], while lipid-derived messengers can regulate major signaling pathways or coordinate immunosuppressive mechanisms [9-11]. Lipid metabolism has, therefore, become implicated in a variety of oncogenic processes, including metastatic colonization, drug resistance, and cell differentiation [10, 12-16]. However, whether we can safely and effectively modulate the underlying mechanisms of lipid metabolism for cancer therapy is still an open question.

Microfluidic cell sorting by stiffness to examine heterogenic responses of cancer cells to chemotherapy

Cancers consist of a heterogeneous populations of cells that may respond differently to treatment through drug-resistant sub-populations. The scarcity of these resistant sub-populations makes it challenging to understand how to counter their resistance. We report a label-free microfluidic approach to separate cancer cells treated with chemotherapy into sub-populations enriched in chemoresistant and chemosensitive cells based on the differences in cellular stiffness. The sorting approach enabled analysis of the molecular distinctions between resistant and sensitive cells. Consequently, the role of multiple mechanisms of drug resistance was identified, including decreased sensitivity to apoptosis, enhanced metabolism, and extrusion of drugs, and, for the first time, the role of estrogen receptor in drug resistance of leukemia cells. To validate these findings, several inhibitors for the identified resistance pathways were tested with chemotherapy to increase cytotoxicity sevenfold. Thus, microfluidic sorting can identify molecular mechanisms of drug resistance to examine heterogeneous responses of cancers to therapies.

Identification of Transcription Factor YY1 as a Regulator of a Prostate Cancer-Specific Pathway Using Proteomic Analysis

Prostate-specific antigen, a biomarker used to diagnose prostate cancer, exhibits poor sensitivity. Although previous studies have focused on identifying a new diagnostic biomarker, the molecules or networks identified in these studies are also present in other cancers, making it difficult to detect prostate cancer specifically. A unique characteristic of the prostate gland is the increased mitochondrial energy metabolism when normal prostate cells progress to cancer cells. Thus, we attempted to find a prostate cancer-specific signature present in this unique environment. Proteins that were differentially expressed between a prostate cell line and three prostate cancer cell lines were identified using proteomic analysis. Not surprisingly, the most prevalent proteins detected by network analysis of proteins that were up-regulated at least 1.2-fold in cancer cells, compared to that in normal prostate cells, were those involved in mitochondrial energy metabolism. In addition, we showed that Yin Yang 1 (YY1) was a major transcription factor involved in regulating energy metabolism. To determine whether YY1 regulates genes associated with mitochondrial energy metabolism in prostate cells, cells were subjected to quantitative polymerase chain reaction analysis in the presence or absence of the YY1 inhibitor NP-001. Notably, inhibition of YY1 resulted in reduced expression of genes related to the Krebs cycle and electron transport chain in prostate cancer cell lines. Based on this finding, we suggest that there is a tumor-specific signature that regulates mitochondrial energy metabolism in prostate cancer cells. This work provides a foundation for further work on identifying a means for the specific diagnosis of prostate cancer.

Metabolomic mechanisms of gypenoside against liver fibrosis in rats: An integrative analysis of proteomics and metabolomics data

Aims

To investigate mechanisms and altered pathways of gypenoside against carbon tetrachloride (CCl₄)-induced liver fibrosis based on integrative analysis of proteomics and metabolomics data.

Methods

CCl₄-induced liver fibrosis rats were administrated gypenoside. The anti-fibrosis effects were evaluated by histomorphology and liver hydroxyproline (Hyp) content. Protein profiling and metabolite profiling of rats liver tissues were examined by isobaric tags for relative and absolute quantitation (iTRAQ) approach and gas chromatography-mass spectrometer (GC-MS) technology. Altered pathways and pivotal proteins and metabolites were searched by integrative analysis of proteomics and metabolomics data. The levels of some key proteins in altered pathways were determined by western blot.

Results

Histopathological changes and Hyp content in gypenoside group had significant improvements (P<0.05). Compared to liver fibrosis model group, we found 301 up-regulated and 296 down-regulated proteins, and 9 up-regulated and 8 down-regulated metabolites in gypenoside group. According to integrative analysis, some important pathways were found, including glycolysis or gluconeogenesis, fructose and mannose metabolism, glycine, serine and threonine metabolism, lysine degradation, arginine and proline metabolism, glutathione metabolism, and sulfur metabolism. Furthermore, the levels of ALDH1B1, ALDH2 and ALDH7A1 were found increased and restored to normal levels after gypenoside treated (P<0.05).

Conclusions

Gypenoside inhibited CCl₄-induced liver fibrosis, which may be involved in the alteration of glycolysis metabolism and the protection against the damage of aldehydes and lipid peroxidation by up-regulating ALDH.

Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies

Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially expressed cancer-related proteins in four major solid cancers (colon, breast, liver and lung). Using signalling and protein–protein interaction network resources integrated with mutational and expression datasets, we analysed the properties of the direct and indirect interactors (first and second neighbours) of cancer-related proteins, not found previously related to the given cancer type. We found that first neighbours have at least as high degree, betweenness centrality and clustering coefficient as cancer-related proteins themselves, indicating a previously unknown central network position. We identified a complementary strategy for mutated and differentially expressed proteins, where the affect of differentially expressed proteins having smaller network centrality is compensated with high centrality first neighbours. These first neighbours can be considered as key, so far hidden, components in cancer rewiring, with similar importance as mutated proteins. These observations strikingly suggest targeting first neighbours as a novel strategy for disrupting cancer-specific networks. Remarkably, our survey revealed 223 marketed drugs already targeting first neighbour proteins but applied mostly outside oncology, providing a potential list for drug repurposing against solid cancers. For the very central first neighbours, whose direct targeting would cause several side effects, we suggest a cancer-mimicking strategy by targeting their interactors (second neighbours of cancer-related proteins, having a central protein affecting position, similarly to the cancer-related proteins). Hence, we propose to include first neighbours to network medicine based approaches for (but not limited to) anticancer therapies.

Cancer is considered a systems disease in which the interactors of cancer-related proteins have a key role, also as targets to fight cancer. New therapeutic approaches are needed to improve success rates and to identify suitable proteins as novel, alternative drug targets. We designed a computational approach, combining mutation and differential expression data with network information, to analyse the interactions of cancer-related proteins in colon, breast, liver and lung cancer. We found that first (direct) neighbours, not linked previously to the given cancer type, are similarly important as mutated proteins known to be involved in cancer development. We found 223 drugs already in the clinic targeting these proteins but not yet used against cancer as their oncology relevance was hidden so far. Our observations open up new strategies for target selection and anti-cancer drug discovery.

Saurolactam Inhibits Proliferation, Migration, and Invasion of Human Osteosarcoma Cells

Osteosarcoma is a common type of malignant bone tumor with features of osteoid formation or osteolytic lesions of bone. New therapeutic approaches are urgently needed since it lacks response to chemotherapeutic treatments. Saurolactam, a natural compound isolated from the aerial portions of Saururus chinensis, was reported to have an anti-inflammatory activity. Here, we demonstrate that saurolactam shows anti-cancer activity against human osteosarcoma cells. Saurolactam treatment inhibited proliferation of human osteosarcoma cell lines MG-63 and HOS and decreased colony formation in soft agar in a dose-dependent manner. Intraperitoneal administration of saurolactam at 25 mg/kg of body weight for 21 days dramatically inhibited the growth of MG-63 xenografts in nude mice. Flow cytometric analysis indicated that saurolactam treatment (20 μM) led to G1 cell cycle arrest and induced apoptosis in these two cell lines. Western analysis suggested that saurolactam treatment resulted in a reduction of Akt/PKB, phospho-Ser473-Akt, c-Myc, and S-phase kinase-associated protein 2 (Skp2) in MG-63 and HOS osteosarcoma cells. Akt overexpression significantly abolished saurolactam-induced decrease in protein and phosphorylation levels of Akt, c-Myc, and Skp2 protein levels, implying that Akt inactivation was a causal mediator of saurolactam-induced inhibition of c-Myc and Skp2. Moreover, Skp2 overexpression in MG-63 cells partly abolished the growth inhibition induced by saurolactam. Saurolactam treatment repressed migration and invasion ability, and Skp2 overexpression significantly blocked these inhibitory effects of saurolactam in MG-63 Cells. The present study indicates that saurolactam might represent a new promising agent to improve osteosarcoma treatment.

Dichotomy in the Epigenetic Mark Lysine Acetylation is Critical for the Proliferation of Prostate Cancer Cells

The dynamics of lysine acetylation serve as a major epigenetic mark, which regulates cellular response to inflammation, DNA damage and hormonal changes. Microarray assays reveal changes in gene expression, but cannot predict regulation of a protein function by epigenetic modifications. The present study employs computational tools to inclusively analyze microarray data to understand the potential role of acetylation during development of androgen-independent PCa. The data revealed that the androgen receptor interacts with 333 proteins, out of which at least 92 proteins were acetylated. Notably, the number of cellular proteins undergoing acetylation in the androgen-dependent PCa was more as compared to the androgen-independent PCa. Specifically, the 32 lysine-acetylated proteins in the cellular models of androgen-dependent PCa were mainly involved in regulating stability as well as pre- and post-processing of mRNA. Collectively, the data demonstrate that protein lysine acetylation plays a crucial role during the transition of androgen-dependent to -independent PCa, which importantly, could also serve as a functional axis to unravel new therapeutic targets.

Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib

Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug’s known mechanism of action. Also, the models predict each drug’s potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets.

Feasibility of implementing molecular-guided therapy for the treatment of patients with relapsed or refractory neuroblastoma

The primary objective of the study was to evaluate the feasibility and safety of a process which would utilize genome-wide expression data from tumor biopsies to support individualized treatment decisions. Current treatment options for recurrent neuroblastoma are limited and ineffective, with a survival rate of <10%. Molecular profiling may provide data which will enable the practitioner to select the most appropriate therapeutic option for individual patients, thus improving outcomes. Sixteen patients with neuroblastoma were enrolled of which fourteen were eligible for this study. Feasibility was defined as completion of tumor biopsy, pathological evaluation, RNA quality control, gene expression profiling, bioinformatics analysis, generation of a drug prediction report, molecular tumor board yielding a treatment plan, independent medical monitor review, and treatment initiation within a 21 day period. All eligible biopsies passed histopathology and RNA quality control. Expression profiling by microarray and RNA sequencing were mutually validated. The average time from biopsy to report generation was 5.9 days and from biopsy to initiation of treatment was 12.4 days. No serious adverse events were observed and all adverse events were expected. Clinical benefit was seen in 64% of patients as stabilization of disease for at least one cycle of therapy or partial response. The overall response rate was 7% and the progression free survival was 59 days. This study demonstrates the feasibility and safety of performing real-time genomic profiling to guide treatment decision making for pediatric neuroblastoma patients.

Systems-based analyses of brain regions functionally impacted in Parkinson's disease reveals underlying causal mechanisms

Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson's disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson's disease, and may be instrumental to understand, diagnose and follow Parkinson's disease progression.

Quantitative analysis of castration resistant prostate cancer progression through phosphoproteome signaling

Background

Although recent progress has been made in treating castration resistant prostate cancer, the interplay of signaling pathways which enable castration resistant growth is incompletely understood. A data driven, multivariate approach, was used in this study to predict prostate cancer cell survival based on the phosphorylation levels of key proteins in PC3, LNCaP, and MDA-PCa-2b cell lines in response to EGF, IGF1, IL6, TNFα, dihydrotestosterone, and docetaxel treatment.

Methods

The prostate cancer cell lines were treated with ligands or inhibitors, cell lyates were collected, and the amount of phosphoprotein quantified using 384 well ELISA assays. In separate experiments, relative cell viability was determined using an MTT assay. Normalized data was imported into Matlab where regression analysis was performed.

Results

Based on a linear model developed using partial least squares regression, p-Erk1/2 was found to correlate with castration resistant survival along with p-RPS6, and this model was determined to have a leave-one-out cross validated R² value of 0.61. The effect of androgen on the phosphoproteome was examined, and increases in PI3K related phosphoproteins (p-Akt, p-RPS6, and p-GSK3) were observed which accounted for the majority of the significant increase in androgen-mediated cell survival. Simultaneous inhibition of the PI3K pathway and treatment with androgen resulted in a non-significant increase in survival. Given the strong effect of PI3K related signaling in enabling castration resistant survival, the specific effect of mTor versus complete inhibition was examined using targeted inhibitors. It was determine that mTor inhibition accounts for 52% of the effect of complete PI3K inhibition on cell survival. The differences in signaling between the cell lines were explored it was observed that MDA-PCa-2b exhibited far less activation of p-Erk in response to varying treatments, explaining one of the reasons for the lack of castration resistance.

Conclusion

In this work, regression analysis to the phosphoproteome was used to illustrate the sources of castration resistance between the cell lines including reduced p-Erk signaling in MDA-PCa-2b and variations in p-JNK across the cell lines, as well as studying the signaling pathways which androgen acts through, and determining the response to treatment with targeted inhibitors.

Proteomics of osteosarcoma

Osteosarcoma (OS) is the most common primary malignant tumor of bone and the third most common cancer in childhood and adolescence. Nowadays, early diagnosis, drug resistance and recurrence of the disease represent the major challenges in OS treatment. Post-genomics, and in particular proteomic technologies, offer an invaluable opportunity to address the level of biological complexity expressed by OS. Although the main goal of OS oncoproteomics is focused on diagnostic and prognostic biomarker discovery, in this review we describe and discuss global protein profiling approaches to other aspects of OS biology and pathophysiology, or to investigate the mechanism of action of chemotherapeutics. In addition, we present proteomic analyses carried out on OS cell lines as in vitro models for studying osteoblastic cell biology and the attractive opportunity offered by proteomics of OS cancer stem cells.

Difference in protein expression profile and chemotherapy drugs response of different progression stages of LNCaP sublines and other human prostate cancer cells

Androgen ablation therapy is the primary treatment for metastatic prostate cancer. However, 80-90% of the patients who receive androgen ablation therapy ultimately develop recurrent tumors in 12-33 months after treatment with a median overall survival time of 1-2 years after relapse. LNCaP is a commonly used cell line established from a human lymph node metastatic lesion of prostatic adenocarcinoma. We previously established two relapsed androgen receptor (AR)-rich androgen-independent LNCaP sublines 104-R1 (androgen depleted for 12 months) and 104-R2 cells (androgen depleted for 24 months) from AR-positive androgen-dependent LNCaP 104-S cells. LNCaP 104-R1 and 104-R2 mimics the AR-positive hormone-refractory relapsed tumors in patients receiving androgen ablation therapy. Androgen treatment stimulates proliferation of 104-S cells, but causes growth inhibition and G1 cell cycle arrest in 104-R1 and 104-R2 cells. We investigated the protein expression profile difference between LNCaP 104-S vs. LNCaP 104-R1, 104-R2, PC-3, and DU-145 cells as well as examined the sensitivity of these prostate cancer cells to different chemotherapy drugs and small molecule inhibitors. Compared to 104-S cells, 104-R1 and 104-R2 cells express higher protein levels of AR, PSA, c-Myc, Skp2, BCL-2, P53, p-MDM2 S166, Rb, and p-Rb S807/811. The 104-R1 and 104-R2 cells express higher ratio of p-Akt S473/Akt, p-EGFR/EGFR, and p-Src/Src, but lower ratio of p-ERK/ERK than 104-S cells. PC-3 and DU-145 cells express higher c-Myc, Skp2, Akt, Akt1, and phospho-EGFR but less phospho-Akt and phospho-ERK. Overexpression of Skp2 increased resistance of LNCaP cells to chemotherapy drugs. Paclitaxel, androgen, and inhibitors for PI3K/Akt, EGFR, Src, or Bcl-2 seem to be potential choices for treatment of advanced prostate cancers. Our study provides rationale for targeting Akt, EGFR, Src, Bcl-2, and AR signaling as a treatment for AR-positive relapsed prostate tumors after hormone therapy.

Cholestane-3β, 5α, 6β-triol suppresses proliferation, migration, and invasion of human prostate cancer cells

Oxysterols are oxidation products of cholesterol. Cholestane-3β, 5α, 6β-triol (abbreviated as triol) is one of the most abundant and active oxysterols. Here, we report that triol exhibits anti-cancer activity against human prostate cancer cells. Treatment of cells with triol dose-dependently suppressed proliferation of LNCaP CDXR-3, DU-145, and PC-3 human prostate cancer cells and reduced colony formation in soft agar. Oral administration of triol at 20 mg/kg daily for three weeks significantly retarded the growth of PC-3 xenografts in nude mice. Flow cytometric analysis revealed that triol treatment at 10–40 µM caused G1 cell cycle arrest while the TUNEL assay indicated that triol treatment at 20–40 µM induced apoptosis in all three cell lines. Micro-Western Arrays and traditional Western blotting methods indicated that triol treatment resulted in reduced expression of Akt1, phospho-Akt Ser473, phospho-Akt Thr308, PDK1, c-Myc, and Skp2 protein levels as well as accumulation of the cell cycle inhibitor p27^Kip. Triol treatment also resulted in reduced Akt1 protein expression in PC-3 xenografts. Overexpression of Skp2 in PC-3 cells partially rescued the growth inhibition caused by triol. Triol treatment suppressed migration and invasion of DU-145, PC-3, and CDXR-3 cells. The expression levels of proteins associated with epithelial-mesenchymal transition as well as focal adhesion kinase were affected by triol treatment in these cells. Triol treatment caused increased expression of E-cadherin protein levels but decreased expression of N-cadherin, vimentin, Slug, FAK, phospho-FAK Ser722, and phospho-FAK Tyr861 protein levels. Confocal laser microscopy revealed redistribution of β-actin and α-tubulin at the periphery of the CDXR-3 and DU-145 cells. Our observations suggest that triol may represent a promising therapeutic agent for advanced metastatic prostate cancer.

Proteomic profile identifies dysregulated pathways in Cornelia de Lange syndrome cells with distinct mutations in SMC1A and SMC3 genes

Mutations in cohesin genes have been identified in Cornelia de Lange syndrome (CdLS), but its etiopathogenetic mechanisms are still poorly understood. To define biochemical pathways that are affected in CdLS, we analyzed the proteomic profile of CdLS cell lines carrying mutations in the core cohesin genes, SMC1A and SMC3. Dysregulated protein expression was found in CdLS probands compared to controls. The proteomics analysis was able to discriminate between probands harboring mutations in the different domains of the SMC proteins. In particular, proteins involved in the response to oxidative stress were specifically down-regulated in hinge mutated probands. In addition, the finding that CdLS cell lines show an increase in global oxidative stress argues that it could contribute to some CdLS phenotypic features such as premature physiological aging and genome instability. Finally, the c-MYC gene represents a convergent hub lying at the center of dysregulated pathways, and is down-regulated in CdLS. This study allowed us to highlight, for the first time, specific biochemical pathways that are affected in CdLS, providing plausible causal evidence for some of the phenotypic features seen in CdLS.

Knowledge-based analysis of proteomics data

As it is the case with any OMICs technology, the value of proteomics data is defined by the degree of its functional interpretation in the context of phenotype. Functional analysis of proteomics profiles is inherently complex, as each of hundreds of detected proteins can belong to dozens of pathways, be connected in different context-specific groups by protein interactions and regulated by a variety of one-step and remote regulators. Knowledge-based approach deals with this complexity by creating a structured database of protein interactions, pathways and protein-disease associations from experimental literature and a set of statistical tools to compare the proteomics profiles with this rich source of accumulated knowledge. Here we describe the main methods of ontology enrichment, interactome topology and network analysis applied on a comprehensive, manually curated and semantically consistent knowledge source MetaBase and demonstrate several case studies in different disease areas.

Cell stiffness is a biomarker of the metastatic potential of ovarian cancer cells

The metastatic potential of cells is an important parameter in the design of optimal strategies for the personalized treatment of cancer. Using atomic force microscopy (AFM), we show, consistent with previous studies conducted in other types of epithelial cancer, that ovarian cancer cells are generally softer and display lower intrinsic variability in cell stiffness than non-malignant ovarian epithelial cells. A detailed examination of highly invasive ovarian cancer cells (HEY A8) relative to their less invasive parental cells (HEY), demonstrates that deformability is also an accurate biomarker of metastatic potential. Comparative gene expression analyses indicate that the reduced stiffness of highly metastatic HEY A8 cells is associated with actin cytoskeleton remodeling and microscopic examination of actin fiber structure in these cell lines is consistent with this prediction. Our results indicate that cell stiffness may be a useful biomarker to evaluate the relative metastatic potential of ovarian and perhaps other types of cancer cells.

Androgen-sensitive microsomal signaling networks coupled to the proliferation and differentiation of human prostate cancer cells

Increasing evidence suggests that the disruption of androgen-mediated cellular processes, such as cell proliferation and cell differentiation, contributes to the development of early-stage androgen-dependent prostate cancers. Large-scale mRNA profiling experiments have paved the way in identifying androgen-regulated gene networks that control the proliferation, survival, and differentiation of prostate cancer cells. Despite these extensive research efforts, it remains to be determined whether all androgen-mediated mRNA changes faithfully translate into changes in protein abundance that influence prostate tumorigenesis. Here, we report on a mass spectrometry-based quantitative proteomics analysis that identified known androgen signaling pathways and also novel, androgen-sensitive microsome-associated proteins and protein networks that had not been discovered by gene network studies in human LNCaP prostate cancer cells. Androgen-sensitive microsome-associated proteins encoded components of the insulin growth factor-1 (IGF-1), phosphoinositide 3-kinase (PI3K)/AKT, and extracellular signal-regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) signaling pathways. Further bioinformatic analyses showed most of the androgen-sensitive microsome-associated protein networks play roles in cell proliferation and differentiation. Functional validation experiments showed that the androgen-sensitive microsome-associated proteins Janus kinase 2 (JAK2) and I-kappa B kinase complex-associated protein (IKAP) modulated the expression of prostate epithelial and neuronal markers, attenuated proliferation through an androgen receptor-dependent mechanism, and co-regulated androgen receptor-mediated transcription in LNCaP cells. Further biochemical analyses showed that the increased proliferation in JAK2 knockdown cells was mediated by activation of the mammalian target of rapamycin (mTOR), as determined by increased phosphorylation of several downstream targets (p70 S6 kinase, translational repressor 4E-BP1, and 40S ribosomal S6 protein). We conclude that the expression of microsome-associated proteins that were previously implicated in the tumorigenesis of prostate epithelial cells is strongly influenced by androgens. These findings provide a molecular framework for exploring the mechanisms underlying prostate tumorigenesis and how these protein networks might be attenuated or potentiated in disrupting the growth and survival of human prostate cancers.

Proteomic profiling of androgen-independent prostate cancer cell lines reveals a role for protein S during the development of high grade and castration-resistant prostate cancer

Androgen deprivation constitutes the principal therapy for advanced and metastatic prostate cancers. However, this therapeutic intervention usually results in the transition to a more aggressive androgen-independent prostate cancer. The elucidation of molecular alterations during the progression to androgen independence is an integral step toward discovering more effective targeted therapies. With respect to identifying crucial mediators of this transition, we compared the proteomes of androgen-independent (PC3, DU145, PPC1, LNCaP-SF, and 22Rv1) and androgen-dependent (LNCaP and VCaP) and/or normal prostate epithelial (RWPE) cell lines using mass spectrometry. We identified more than 100 proteins that were differentially secreted in the androgen-independent cell lines. Of these, Protein S (PROS1) was elevated in the secretomes of all of the androgen-independent prostate cancer cell lines, with no detectable secretion in normal and androgen-dependent cell lines. Using quantitative PCR, we observed significantly higher (p < 0.05) tissue expression levels of PROS1 in prostate cancer samples, further indicating its importance in prostate cancer progression. Similarly, immunohistochemistry analysis revealed elevation of PROS1 in high grade prostate cancer (Gleason grade ≥ 8), and further elevation in castration-resistant metastatic prostate cancer lesions. We also observed its significant (p < 0.05) elevation in high grade prostate cancer seminal plasma samples. Taken together, these results show that PROS1 is elevated in high grade and castration-resistant prostate cancer and could serve as a potential biomarker of aggressive disease.

A systems biology approach reveals common metastatic pathways in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models.

RESULTS

mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a "shortest-path" algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including "Cytoskeleton remodeling/TGF/WNT", "Cytoskeleton remodeling/Cytoskeleton remodeling", and "Cell adhesion/Chemokines and adhesion". Of these, the "Cytoskeleton remodeling/TGF/WNT" was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the "Cytoskeleton remodeling/TGF/WNT" pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform.

CONCLUSIONS

In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS.

Integration of proteomics into systems biology of cancer

Deciphering the complexity and heterogeneity of cancer, benefits from integration of proteomic level data into systems biology efforts. The opportunities available as a result of advances in proteomic technologies, the successes to date, and the challenges involved in integrating diverse datasets are addressed in this review.

Androgen suppresses proliferation of castration-resistant LNCaP 104-R2 prostate cancer cells through androgen receptor, Skp2, and c-Myc

Androgen ablation therapy is the primary treatment for metastatic prostate cancer. However, this therapy is associated with several undesired side-effects, including increased risk of cardiovascular diseases. To study if termination of long-term androgen ablation and restoration of testosterone levels could suppress the growth of relapsed hormone-refractory prostate tumors, we implanted testosterone pellets in castrated nude mice carrying androgen receptor (AR)-positive LNCaP 104-R2 cells, which relapsed from androgen-dependent LNCaP 104-S cells after long-term androgen deprivation. 104-R2 tumor xenografts regressed after testosterone pellets were implanted. Of 33 tumors, 24 adapted to elevation of testosterone level and relapsed as androgen-insensitive tumors. Relapsed tumors (R2Ad) expressed less AR and prostate-specific antigen. We then studied the molecular mechanism underlying the androgenic regulation of prostate cancer cell proliferation. Androgen suppresses proliferation of 104-R2 by inducing G(1) cell cycle arrest through reduction of S-phase kinase-associated protein 2 (Skp2) and c-Myc, and induction of p27(Kip1). 104-R2 cells adapted to androgen treatment and the adapted cells, R2Ad, were androgen-insensitive cells with a slower growth rate and low protein level of AR, high levels of c-Myc and Skp2, and low levels of p27(Kip1). Nuclear AR and prostate-specific antigen expression is present in 104-R2 cells but not R2Ad cells when androgen is absent. Overexpression of AR in R2Ad cells regenerated an androgen-repressed phenotype; knockdown of AR in 104-R2 cells generated an androgen-insensitive phenotype. Overexpression of Skp2 and c-Myc in 104-R2 cells blocked the growth inhibition caused by androgens. We concluded that androgens cause growth inhibition in LNCaP 104-R2 prostate cancer cells through AR, Skp2, and c-Myc.

Metabolomic profiling reveals a role for androgen in activating amino acid metabolism and methylation in prostate cancer cells

Prostate cancer is the second leading cause of cancer related death in American men. Development and progression of clinically localized prostate cancer is highly dependent on androgen signaling. Metastatic tumors are initially responsive to anti-androgen therapy, however become resistant to this regimen upon progression. Genomic and proteomic studies have implicated a role for androgen in regulating metabolic processes in prostate cancer. However, there have been no metabolomic profiling studies conducted thus far that have examined androgen-regulated biochemical processes in prostate cancer. Here, we have used unbiased metabolomic profiling coupled with enrichment-based bioprocess mapping to obtain insights into the biochemical alterations mediated by androgen in prostate cancer cell lines. Our findings indicate that androgen exposure results in elevation of amino acid metabolism and alteration of methylation potential in prostate cancer cells. Further, metabolic phenotyping studies confirm higher flux through pathways associated with amino acid metabolism in prostate cancer cells treated with androgen. These findings provide insight into the potential biochemical processes regulated by androgen signaling in prostate cancer. Clinically, if validated, these pathways could be exploited to develop therapeutic strategies that supplement current androgen ablative treatments while the observed androgen-regulated metabolic signatures could be employed as biomarkers that presage the development of castrate-resistant prostate cancer.

Cyclin D1 is a selective modifier of androgen-dependent signaling and androgen receptor function

D-type cyclins regulate cellular outcomes in part through cyclin-dependent, kinase-independent mechanisms that modify transcription factor action, and recent in vivo studies showed that cyclin D1 associates with a large number of transcriptional regulators in cells of the retina and breast. Given the frequency of cyclin D1 alterations in cancer, it is imperative to delineate the molecular mechanisms by which cyclin D1 controls key transcription factor networks in human disease. Prostate cancer was used as a paradigm because this tumor type is reliant at all stages of the disease on androgen receptor (AR) signaling, and cyclin D1 has been shown to negatively modulate AR-dependent expression of prostate-specific antigen (KLK3/PSA). Strategies were employed to control cyclin D1 expression under conditions of hormone depletion, and the effect of cyclin D1 on subsequent androgen-dependent gene expression was determined using unbiased gene expression profiling. Modulating cyclin D1 conferred widespread effects on androgen signaling and revealed cyclin D1 to be a selective effector of hormone action. A subset of androgen-induced target genes, known to be directly regulated by AR, was strongly suppressed by cyclin D1. Analyses of AR occupancy at target gene regulatory loci of clinical relevance demonstrated that cyclin D1 limits AR residence after hormone stimulation. Together, these findings reveal a new function for cyclin D1 in controlling hormone-dependent transcriptional outcomes and demonstrate a pervasive role for cyclin D1 in regulating transcription factor dynamics.