Quantitative analysis of energy metabolic pathways in MCF-7 breast cancer cells by selected reaction monitoring assay

Proteomic signatures of angiogenesis in androgen-independent prostate cancer

INTRODUCTION

The observation that angiogenesis, the process of new blood vessel formation, in healthy prostate and early prostate cancer is androgen-dependent gave rise to significant questions on how hypervascularization and increased angiogenesis is also achieved at the molecular level in advanced androgen-independent prostate cancer. The exact paracrine molecular network that is hardwired into the proteome of the endothelial and cancer subpopulations participating in this process remains partially understood.

METHODS

Here, we interrogated the signaling pathways and the molecular functional signatures across the proteome of endothelial cells after interacting with various secretomes produced by androgen-dependent and -independent prostate cancer cells.

RESULTS

We found the significant overexpression (P < 0.05) of prominent markers of angiogenesis, such as vonWillebrand factor (vWF) (∼ 2.5-fold) and CD31 (∼ 2-fold) in HUVECs stimulated with conditioned media from the androgen-independent prostate cancer cell line PC3. By mining the proteome of PC3 conditioned media, we discovered a signature of chemokine CXC motif ligands (i.e., CXCL3, CXCL5, CXCL6 and CXCL8) that could potentially coordinate increased angiogenesis in androgen-independent prostate cancer and verified their increased expression (P < 0.05) in both in vitro and xenograft models of androgen-independence.

DISCUSSION

Our findings form the basis for understanding the regulation of crucial metastatic phenomena during the transition of androgen-dependent prostate cancer into the highly aggressive, androgen-independent state and provide further insight on potential therapeutic targets of cancer-related angiogenesis.

Systematic nucleo-cytoplasmic trafficking of proteins following exposure of MCF7 breast cancer cells to estradiol

We have used a proteomics subcellular spatial razor approach to look at changes in total protein abundance and in protein distribution between the nucleus and cytoplasm following exposure of MCF7 breast cancer cells to estradiol. The dominant response of MCF7 cells to estrogen stimulation involves dynamic changes in protein subcellular spatial distribution rather than changes in total protein abundance. Of the 3604 quantitatively monitored proteins, only about 2% show substantial changes in total abundance (>2-fold), whereas about 20% of the proteins show substantial changes in local abundance and/or redistribution of their subcellular location, with up to 16-fold changes in their local concentration in the nucleus or the cytoplasm. We propose that dynamic redistribution of the subcellular location of multiple proteins in response to stimuli is a fundamental characteristic of cells and suggest that perturbation of cellular spatial control may be an important feature of cancer.

Assessment of peptide chemical modifications on the development of an accurate and precise multiplex selected reaction monitoring assay for apolipoprotein e isoforms

Apolipoprotein E (ApoE) is a polymorphic protein that plays a major role in lipid metabolism in the central nervous system and periphery. It has three common allelic isoforms, ApoE2, ApoE3, and ApoE4, that differ in only one or two amino acids. ApoE isoforms have been associated with the occurrence and progression of several pathological conditions, such as coronary atherosclerosis and Alzheimer's disease. The aim of this study was to develop a mass spectrometry (MS)-based assay for absolute quantification of ApoE isoforms in cerebrospinal fluid and plasma samples using isotope-labeled peptides. The assay included five tryptic peptides: CLAVYQAGAR (ApoE2), LGADMEDVCGR (ApoE2 and 3), LAVYQAGAR (ApoE3 and 4), LGADMEDVR (ApoE4), and LGPLVEQGR (total ApoE). Both cerebrospinal fluid and plasma samples were assayed to validate the method. The digestion yield and the extension of chemical modifications in selected amino acid residues (methionine oxidation, glutamine deamidation, and cyclization of N-terminus carbamidomethylcysteine) were also studied. The ApoE phenotype was successfully assigned to all samples analyzed in a blinded manner. The method showed good linearity (R(2) > 0.99) and reproducibility (within laboratory imprecision <13%). The comparison of the MS-based assay with an ELISA for total ApoE concentration showed a moderate correlation (R(2) = 0.59). This MS-based assay can serve as an important tool in clinical studies aiming to elucidate the association between ApoE genotype, total ApoE, and ApoE isoform concentrations in various disorders related to ApoE polymorphisms.

Biomarker verification using selected reaction monitoring and shotgun proteomics

Shotgun proteomics (liquid chromatography-electrospray ionization-mass spectrometry, LC-ESI-MS/MS) has dominated the strategies for global protein expression in subcells, cells, tissues, and whole organisms with several types of approaches, as isobaric tags for relative and absolute quantification (iTRAQ), isotope-coded affinity tags (ICAT), or stable isotope labeling using amino acids in cell culture (SILAC) and non-labeling (label free) methods. Shotgun proteomics practically replaced the classical 2D gel electrophoresis. Selected reaction monitoring (SRM), also denominated multiple reaction monitoring (MRM), is a targeted quantitative technology that uses a complex mixture of tryptic peptides that can be selectively detected by liquid chromatography coupled to electrospray triple-quadrupole mass spectrometer; this system can select precursor ions in combination with their correspondent product ions during collision-induced dissociation to produce specific detection related to a particular protein. Here we describe protocols that are efficient to produce a complete enzymatic trypsin digestion from complex biological matrices and concomitant material to be used for LC-SRM-MS and LC-ESI-MS/MS (labeled or label free).

Cancer metabolism and mass spectrometry-based proteomics

Cancer metabolism has been extensively investigated by various tools, and the fact of diverse metabolic reprogramming in cancer cells has been gradually unveiled. In this review, we discuss some contributions in cancer metabolism by general proteomic analysis and post-translational modification analysis using mass spectrometry (MS) technique. Instead of following one or several metabolic enzymes/pathways, the current MS approach can quickly identify a large number of proteins and compare their expression levels in different samples, providing a potentially comprehensive picture of cancer metabolism. The MS analyses from pancreatic cancer cells support a hypothesis that hypoxia promotes cells in solid tumor to reprogram metabolic pathways in order to minimize the oxygen consumption. The oxidative stress in pancreatic cancer cells is lower than that in normal duct cells, and the cancer cells adaptively express less antioxidant proteins, contrary to claims that oxidative stress is higher in cancer cells. Separately, the MS analyses confirm that pyruvate kinase isoform 2 (PKM2) can be detected in both cancer and normal cells, disagreeing with report that tumor cells express exclusively PKM2. In addition, MS analyses from pancreatic cancer cells demonstrate that lactate dehydrogenase-B is significantly upregulated in pancreatic cancer cells, whereas previous reports show that lactate dehydrogenase-A is overexpressed and is responsible for lactate production in cancer cells. Lastly, the result from MS analysis suggests that the glutaminolysis in pancreatic cancer cells is different from that observed in glioblastoma cells.

Determination of an angiotensin II-regulated proteome in primary human kidney cells by stable isotope labeling of amino acids in cell culture (SILAC)

Angiotensin II (AngII), the major effector of the renin-angiotensin system, mediates kidney disease progression by signaling through the AT-1 receptor (AT-1R), but there are no specific measures of renal AngII activity. Accordingly, we sought to define an AngII-regulated proteome in primary human proximal tubular cells (PTEC) to identify potential AngII activity markers in the kidney. We utilized stable isotope labeling with amino acids (SILAC) in PTECs to compare proteomes of AngII-treated and control cells. Of the 4618 quantified proteins, 83 were differentially regulated. SILAC ratios for 18 candidates were confirmed by a different mass spectrometry technique called selected reaction monitoring. Both SILAC and selected reaction monitoring revealed heme oxygenase-1 (HO-1) as the most significantly up-regulated protein in response to AngII stimulation. AngII-dependent regulation of the HO-1 gene and protein was further verified in PTECs. To extend these in vitro observations, we overlaid a network of significantly enriched gene ontology terms from our AngII-regulated proteins with a dataset of differentially expressed kidney genes from AngII-treated wild type mice and AT-1R knock-out mice. Five gene ontology terms were enriched in both datasets and included HO-1. Furthermore, HO-1 kidney expression and urinary excretion were reduced in AngII-treated mice with PTEC-specific AT-1R deletion compared with AngII-treated wild-type mice, thus confirming AT-1R-mediated regulation of HO-1. Our in vitro approach identified novel molecular markers of AngII activity, and the animal studies demonstrated that these markers are relevant in vivo. These interesting proteins hold promise as specific markers of renal AngII activity in patients and in experimental models.

Breast cancer biomarkers: proteomic discovery and translation to clinically relevant assays

Although the molecular classification and prognostic assessment of breast tumors based on gene expression profiling is well established, a number of proteomic studies that propose potential breast cancer biomarkers has not yet led to any new diagnostic, prognostic or predictive test in wide clinical use. This review examines the current status of breast cancer biomarkers, discusses sample types (including plasma, tumor tissue, nipple aspirate and ductal lavage, as well as cell culture models) and different electrophoretic and mass spectrometry methods that have been widely used for the discovery of proteomic biomarkers in breast cancer, and also considers several approaches to biomarker validation. The pathway leading from the initial proteomic discovery and validation process to translation into a clinically useful test is also discussed.

Chemoprevention activity of dipyridamole in the MMTV-PyMT transgenic mouse model of breast cancer

Dipyridamole (DPM) is widely used to prevent strokes and vascular thrombosis. Combination therapy of DPM and antimetabolites has shown synergistic anticancer activity. This study investigated the chemopreventive effects of DPM in the mouse mammary tumor virus promoter-driven polyoma middle T oncoprotein metastatic breast cancer model. We also investigated the effects of DPM on gene and miRNA expression. Chemopreventive activity was assessed by comparing the time to onset of palpable lesions, primary tumor growth kinetics, and the number of lung metastases in transgenic mice treated with DPM or vehicle. Gene expression and miRNA expression profiles of mammary tumor tissues were then analyzed using the Affymetrix GeneChip or miRNA 2.0 arrays. Real-time quantitative PCR was used to confirm changes in gene expression. Treatment with DPM beginning at the age of 4 weeks delayed the onset of palpable lesions, delayed tumor progression, and suppressed lung metastasis. Microarray gene expression analysis identified 253 genes differentially expressed between DPM-treated and control mammary tumors. miRNA expression analysis revealed that 53 miRNAs were altered by DPM treatment. The results indicate that DPM has chemoprevention activity against breast cancer tumorigenesis and metastasis in mice. The array analyses provide insights into potential mechanisms of DPM's chemopreventive effects, involving upregulation of several genes and miRNAs known to suppress cancer growth and/or metastasis and downregulation of genes known to promote cancer. Some of these genes have not been previously studied in breast cancer and may serve as novel molecular targets for breast cancer chemoprevention.

Risk assessment, disease prevention and personalised treatments in breast cancer: is clinically qualified integrative approach in the horizon?

Breast cancer is a multifactorial disease. A spectrum of internal and external factors contributes to the disease promotion such as a genetic predisposition, chronic inflammatory processes, exposure to toxic compounds, abundant stress factors, a shift-worker job, etc. The cumulative effects lead to high incidence of breast cancer in populations worldwide. Breast cancer in the USA is currently registered with the highest incidence rates amongst all cancer related patient cohorts. Currently applied diagnostic approaches are frequently unable to recognise early stages in tumour development that impairs individual outcomes. Early diagnosis has been demonstrated to be highly beneficial for significantly enhanced therapy efficacy and possibly full recovery. Actual paper shows that the elaboration of an integrative diagnostic approach combining several levels of examinations creates a robust platform for the reliable risk assessment, targeted preventive measures and more effective treatments tailored to the person in the overall task of breast cancer management. The levels of examinations are proposed, and innovative technological approaches are described in the paper. The absolute necessity to create individual patient profiles and extended medical records is justified for the utilising by routine medical services. Expert recommendations are provided to promote further developments in the field.

Proteomics analysis of tumor microenvironment: Implications of metabolic and oxidative stresses in tumorigenesis

Tumorigenesis is always concomitant with microenvironmental alterations. The tumor microenvironment is a heterogeneous and complex milieu, which exerts a variety of stresses on tumor cells for proliferation, survival, or death. Recently, accumulated evidence revealed that metabolic and oxidative stresses both play significant roles in tumor development and progression that converge on a common autophagic pathway. Tumor cells display increased metabolic autonomy, and the hallmark is the exploitation of aerobic glycolysis (termed Warburg effect), which increased glucose consumption and decreased oxidative phosphorylation to support growth and proliferation. This characteristic renders cancer cells more aggressive; they devour tremendous amounts of nutrients from microenvironment to result in an ever-growing appetite for new tumor vessel formation and the release of more "waste," including key determinants of cell fate like lactate and reactive oxygen species (ROS). The intracellular ROS level of cancer cells can also be modulated by a variety of stimuli in the tumor microenvironment, such as pro-growth and pro-inflammatory factors. The intracellular redox state serves as a double-edged sword in tumor development and progression: ROS overproduction results in cytotoxic effects and might lead to apoptotic cell death, whereas certain level of ROS can act as a second-messenger for regulation of such cellular processes as cell survival, proliferation, and metastasis. The molecular mechanisms for cancer cell responses to metabolic and oxidative stresses are complex and are likely to involve multiple molecules or signaling pathways. In addition, the expression and modification of these proteins after metabolic or oxidative stress challenge are diverse in different cancer cells and endow them with different functions. Therefore, MS-based high-throughput platforms, such as proteomics, are indispensable in the global analysis of cancer cell responses to metabolic and oxidative stress. Herein, we highlight recent advances in the understanding of the metabolic and oxidative stresses associated with tumor progression with proteomics-based systems biology approaches.

Cancer metabolism: what we can learn from proteomic analysis by mass spectrometry

A variety of genomic and proteomic tools have been used to study cancer metabolism and metabolomics in order to understand how cancer cells survive in their environment. Throughout the past decade, mass spectrometry has been routinely used for large-scale protein identification of complex biological mixtures. In this review, we discuss some recent developments in cancer metabolism by proteomic analysis using mass spectrometric techniques, focusing on pyruvate kinase, L-lactate dehydrogenase, Warburg effect, glutamine metabolism and oxidative stress.