Proteome analysis of prostate cancer

Sample-Wise and Gene-Wise Comparisons Confirm a Greater Similarity of RNA and Protein Expression Data at the Level of Molecular Pathways and Suggest an Approach for the Data Quality Check in High-Throughput Expression Databases

Identification of genes and molecular pathways with congruent profiles in the proteomic and transcriptomic datasets may result in the discovery of promising transcriptomic biomarkers that would be more relevant to phenotypic changes. In this study, we conducted comparative analysis of 943 paired RNA and proteomic profiles obtained for the same samples of seven human cancer types from The Cancer Genome Atlas (TCGA) and NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) [two major open human cancer proteomic and transcriptomic databases] that included 15,112 protein-coding genes and 1611 molecular pathways. Overall, our findings demonstrated statistically significant improvement of the congruence between RNA and proteomic profiles when performing analysis at the level of molecular pathways rather than at the level of individual gene products. Transition to the molecular pathway level of data analysis increased the correlation to 0.19-0.57 (Pearson) and 0.14-057 (Spearman), or 2-3-fold for some cancer types. Evaluating the gain of the correlation upon transition to the data analysis the pathway level can be used to refine the omics data by identifying outliers that can be excluded from the comparison of RNA and proteomic profiles. We suggest using sample- and gene-wise correlations for individual genes and molecular pathways as a measure of quality of RNA/protein paired molecular data. We also provide a database of human genes, molecular pathways, and samples related to the correlation between RNA and protein products to facilitate an exploration of new cancer transcriptomic biomarkers and molecular mechanisms at different levels of human gene expression.

An overview of advances in multi-omics analysis in prostate cancer

Prostate cancer (PCa) is a deadly disease for men, and studies of all types of omics data are necessary to promote precision medicine. The maturity of sequencing technology, the improvements of computer processing power, and the progress achieved in omics analysis methods have improved research efficiency and saved research costs. The occurrence and development of PCa is due to multisystem and multilevel pathological changes. Although omics research at a single level is important, this approach often has limitations. In contrast, the combined analysis of multiple types of omics data can better analyze PCa changes as a whole, thus ensuring the validity of research results to the greatest extent. This paper introduces the applications of single omics in PCa and then summarizes research progress in the combined analysis of two or more types of omics data, so as to systematically and comprehensively analyze the necessity of combined analysis of multiple omics data in PCa.

Integrative proteomic and phosphoproteomic profiling of prostate cell lines

Background

Prostate cancer is a major public health issue, mainly because patients relapse after androgen deprivation therapy. Proteomic strategies, aiming to reflect the functional activity of cells, are nowadays among the leading approaches to tackle the challenges not only of better diagnosis, but also of unraveling mechanistic details related to disease etiology and progression.

Methods

We conducted here a large SILAC-based Mass Spectrometry experiment to map the proteomes and phosphoproteomes of four widely used prostate cell lines, namely PNT1A, LNCaP, DU145 and PC3, representative of different cancerous and hormonal status.

Results

We identified more than 3000 proteins and phosphosites, from which we quantified more than 1000 proteins and 500 phosphosites after stringent filtering. Extensive exploration of this proteomics and phosphoproteomics dataset allowed characterizing housekeeping as well as cell-line specific proteins, phosphosites and functional features of each cell line. In addition, by comparing the sensitive and resistant cell lines, we identified protein and phosphosites differentially expressed in the resistance context. Further data integration in a molecular network highlighted the differentially expressed pathways, in particular migration and invasion, RNA splicing, DNA damage repair response and transcription regulation.

Conclusions

Overall, this study proposes a valuable resource toward the characterization of proteome and phosphoproteome of four widely used prostate cell lines and reveals candidates to be involved in prostate cancer progression for further experimental validation.

2D gel blood serum biomarkers reveal differential clinical proteomics of the neurodegenerative diseases

This review addresses the challenges of neuroproteomics and recent progress in biomarkers and tests for neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. The review will discuss how the application of quantitative 2D gel electrophoresis, combined with appropriate single-variable and multivariate biostatistics, allows for selection of disease-specific serum biomarkers. It will also address how the use of large cohorts of specifically targeted patient blood serum samples and complimentary age-matched controls, in parallel with the use of selected panels of these biomarkers, are being applied to the development of blood tests to specifically address unmet pressing needs in the differential diagnosis of these diseases, and to provide potential avenues for mechanism-based drug targeting and treatment monitoring. While exploring recent findings in this area, the review discusses differences in critical pathways of immune/inflammation and amyloid formation between Parkinson's disease and amyotrophic lateral sclerosis, as well as discernable synergistic relationships between these pathways that are revealed by this approach. The potential for pathway measurement in blood tests for differential diagnosis, disease burden and therapeutic monitoring is also outlined.

Molecular Diagnosis and Biomarker Identification on SELDI proteomics data by ADTBoost method

Clinical proteomics is an emerging field that will have great impact on molecular diagnosis, identification of disease biomarkers, drug discovery and clinical trials in the post-genomic era. Protein profiling in tissues and fluids in disease and pathological control and other proteomics techniques will play an important role in molecular diagnosis with therapeutics and personalized healthcare. We introduced a new robust diagnostic method based on ADTboost algorithm, a novel algorithm in proteomics data analysis to improve classification accuracy. It generates classification rules, which are often smaller and easier to interpret. This method often gives most discriminative features, which can be utilized as biomarkers for diagnostic purpose. Also, it has a nice feature of providing a measure of prediction confidence. We carried out this method in amyotrophic lateral sclerosis (ALS) disease data acquired by surface enhanced laser-desorption/ionization-time-of-flight mass spectrometry (SELDI-TOF MS) experiments. Our method is shown to have outstanding prediction capacity through the cross-validation, ROC analysis results and comparative study. Our molecular diagnosis method provides an efficient way to distinguish ALS disease from neurological controls. The results are expressed in a simple and straightforward alternating decision tree format or conditional format. We identified most discriminative peaks in proteomic data, which can be utilized as biomarkers for diagnosis. It will have broad application in molecular diagnosis through proteomics data analysis and personalized medicine in this post-genomic era.

Application of proteomic technologies for prostate cancer detection, prognosis, and tailored therapy

Prostate cancer affects 3 in 10 men over the age of 50 years, and, unfortunately, the clinical course of the disease is poorly predicted. At present, there is no means that can distinguish indolent from aggressive/metastatic tumors. Thus, a personalized clinical approach could be helpful in diagnosing clinically relevant disease and guiding appropriate patient therapy. Individualized medicine requires a deep knowledge of the molecular mechanisms underpinning prostate cancer carcinogenesis. Proteomics may be the most powerful way to uncover biomarkers of detection, prognosis, and prediction, as proteins do the work of the cell and represent the majority of the diagnostic markers and drug targets today. Proteomic technologies are rapidly advancing beyond the two-dimensional gel separation techniques of the past to new types of mass spectrometry and protein microarray analyses. Biological fluids and tissue-cell proteomes from men with prostate cancer are being explored to identify diagnostic and prognostic biomarkers and therapeutic targets using these new proteomic approaches. Traditional and novel proteomic technology and their application to prostate cancer studies in translational research will be presented and discussed in this review. Proteomics coupled with powerful nanotechnology-based biomarker discovery approaches may provide a new and exciting opportunity for body fluid-borne biomarker discovery and characterization. While innovative mass spectrometry technology and nanotrap could be applied to improve the discovery and measurement of biomarkers for the early detection of prostate cancer, the use of tissue proteomic tools such as the reverse-phase protein microarray may provide new approaches for personalization of therapies tailored to each tumor's unique pathway activation network.

Structural markers in prostate cancer serum imaged ex vivo using cryogenic transmission electron microscopy

We used cryogenic transmission electron microscopy (cryo-TEM) to identify differences in macromolecular structures present in the serum from healthy individuals (HI) and prostate cancer (PCa) patients and show that these differences are potential markers for disease. Using a murine orthotopic model of human PCa, we determined that some of these structural markers in serum are associated with the tumour burden. These findings signify the potential of this nanoscale ex vivo imaging technology of body fluids as a platform for discovering early markers of PCa and other diseases.

High expression of HSP47 in ulcerative colitis-associated carcinomas: proteomic approach

BACKGROUND

Ulcerative colitis (UC) is a chronic relapsing inflammatory bowel disease, known to be associated with a markedly increased risk of colorectal carcinoma development.

METHODS

Using proteomic analysis with two-dimensional gel electrophoresis and mass spectrometry, differentially expressed proteins were assessed between UC-associated cancer and sporadic colon cancer cell lines. Western blot and immunostaining were performed for confirming the expression.

RESULTS

Heat-shock protein of 47 kDa (HSP47) was identified as one of the proteins expressed more highly in UC-associated cancer cell lines, and an immunohistochemical examination confirmed significantly higher levels of HSP47 in UC-associated colon cancers than in sporadic counterparts, the expression increasing with a progression of neoplastic lesions. Heat-shock protein of 47 kDa was further found to be coexpressed with type I collagen in the cytoplasm, and both HSP47 and type I collagen were released from cultured cells into the culture medium.

CONCLUSION

These results suggest that overexpression of HSP47 is a unique characteristic of UC-associated carcinoma related to type I collagen synthesis, with possible clinical applications.

Bioinformatics Processing of Protein and Transcript Profiles of Normal and Transformed Cell Lines Indicates Functional Impairment of Transcriptional Regulators in Buccal Carcinoma

Normal and two transformed buccal keratinocyte lines were cultured under a standardized condition to explore mechanisms of carcinogenesis and tumor marker expression at transcript and protein levels. An approach combining three bioinformatic programs allowed coupling of abundant proteins and large-scale transcript data to low-abundance transcriptional regulators. The analysis identified previously proposed and suggested novel protein biomarkers, gene ontology categories, molecular networks, and functionally impaired key regulator genes for buccal/oral carcinoma.

Labeling and identification of LNCaP cell surface proteins: a pilot study

BACKGROUND

Membrane proteins provide the interface between the cell and its environment and are responsible for cell adhesion, mobility, and intracellular signaling. Previous studies have focused on the LNCaP whole cell proteome and transcriptome but little is known about proteins at the prostate cell membrane and how they change in response to androgens.

MATERIALS AND METHODS

Following treatment with R1881 or vehicle, membrane proteins of the prostate cancer LNCaP cell line were tagged with biotin using EZ-link sulfo-NHS-LC-biotin. Using the tag membrane proteins were purified and separated using two-dimensional gel electrophoresis and identified using mass spectrometry. E-cadherin and low density lipoprotein receptor (LDLR) were used as positive controls and also investigated following bicalutamide treatment. Membrane localization and androgen-regulation of proteins was confirmed using sub-cellular fractionation, Western blotting and microscopy.

RESULTS

We have demonstrated efficient and specific protein biotinylation and purification of LNCaP plasma membrane proteins using Western analysis. E-cadherin and LDLR were regulated at the cell surface in response to R1881 and bicalutamide. Mass spectrometry identified several androgen-regulated membrane associated proteins including Prx-3 and GRP78 which are known to localize to other cellular compartments as well as the plasma membrane. We confirmed the localization of the identified proteins in LNCaP cells by co-localization with E-cadherin and immunohistochemistry of prostate tissue.

CONCLUSION

Cell surface biotinylation is an effective technique for identifying membrane proteins in the LNCaP prostate cancer cell line. We have demonstrated the identification of androgen-regulated membrane proteins and their validation in tissue samples.

Recent advances in capillary electrophoresis for biomarker discovery

The use of non-invasive methods for detecting biomarkers opens a new era in patient care, since clinical investigators have long been searching for accurate and reproducible measurements of putative biomarkers. There are many factors which make this research challenging, beginning with lack of standardization of sample collection and continuing through the entire analytical procedure. Among the variety of methods so far used for biomarker screening, capillary electrophoresis represents a robust, reliable, and widely used analytical tool. This review will focus on recent applications of CE to the analysis of body fluids and tissues for identification of biomarkers.

Disease proteomics of high-molecular-mass proteins by two-dimensional gel electrophoresis with agarose gels in the first dimension (Agarose 2-DE)

Agarose gel is the preferred electrophoretic medium currently used for separating high molecular mass (HMM) proteins (MW>100 kDa). Agarose gels are widely used for both SDS-agarose gel electrophoresis and agarose isoelectric focusing (IEF). A two-dimensional gel electrophoresis method employing agarose gels in the first dimension (agarose 2-DE) that is sufficiently good at separating up to 1.5mg of HMM proteins with molecular masses as large as 500 kDa has been used to separate proteins from various diseased tissues and cells. Although resolution of the agarose 2-DE pattern always depends on the tissue being analyzed, sample preparation procedures including (i) protein extraction with an SDS sample buffer; (ii) ultracentrifugation of a tissue homogenate; and (iii) 1% SDS in both stacking and separation gels of the second-dimension SDS-PAGE gel, are generally effective for HMM protein detection. In a comprehensive prostate cancer proteome study using agarose 2-DE, the HMM region of the gel was rich in proteins of particular gene/protein expression groups (39.1% of the HMM proteins but only 28.4% of the LMM ones were classified as transcription/translation-related proteins). Examples include transcription factors, DNA or RNA binding proteins, and ribosomal proteins. To understand oxidative stress-induced cellular damage at the protein level, a novel proteomic method, in which protein carbonyls were derivatized with biotin hydrazide followed by agarose 2-DE, was useful for detecting HMM protein carbonyls in tissues of both a diabetes model Ostuka Long-Evans Tokushima Fatty (OLETF) rat and a control Long-Evans Tokushima Otsuka (LETO) rat. In this paper, we review the use of agarose gels for separation of HMM proteins and disease proteomics of HMM proteins in general, with particular attention paid to our proteome analyzes based on the use of agarose 2-DE for protein separation followed by the use of mass spectrometry for protein identification.

Application of proteomic strategies to the identification of urinary biomarkers for prostate cancer: a review

In the post-genomic era, genes and proteins are now studied on a more comprehensive scale. Studying disease processes at only the genetic or transcriptomic level will give an incomplete amount of information. A proteomic approach potentially allows for a more global overview of how disease processes affect the proteins present in cells, tissues and organisms. The challenge arises in determining which proteins are affected in specific diseases and establishing which of these changes are unique to a particular disease. Existing and emerging proteomic technologies allow for high throughput analysis of proteins in a variety of sample types. Prostate cancer is a significant male health problem in the Western world. It is widely accepted that more specific prognostic and diagnostic markers of prostate cancer are urgently required. The present paper suggests that urine may be an attractive biofluid in which to pursue the identification of novel biomarkers of prostate cancer. This review introduces some proteomic techniques including mass spectrometry and the newer, quantitative proteomic strategies. It focuses on the potential application of these platforms to novel urinary biomarker identification in prostate malignancy. It also includes a synopsis of the current literature on urinary proteomics.

C-terminal ladder sequencing of peptides using an alternative nucleophile in carboxypeptidase Y digests

A method for improved sequence coverage in C-terminal sequencing of peptides, based on carboxypeptidase digestion, is described. In conventional carboxypeptidase digestions, the peptide substrate is usually extensively degraded and a full amino acid sequence cannot be obtained due to the lack of a complete peptide ladder. In the presented method, a protecting group is introduced at the C terminus of a fraction of the peptide fragments formed in the digest, and thereby further degradation of the C-terminally modified peptides are slowed down. The protecting group was attached to the C-terminal amino acid through a carboxypeptidase-catalyzed reaction with an alternative nucleophile, 2-pyridylmethylamine, added to the aqueous digestion buffer. Six peptides were digested by carboxypeptidase Y with and without 2-pyridylmethylamine present in the digest buffer, and the resulting fragments subsequently were analyzed with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Comparison of the two digestion methods showed that the probability of successful ladder sequencing increased, by more than 50% using 2-pyridylmethylamine as a competing nucleophile in carboxypeptidase Y digests.

Application of Genomic Technologies to Human Prostate Cancer

Prostate cancer is the most commonly diagnosed non-cutaneous malignancy in U.S. males and has a broad spectrum of clinical behavior ranging from indolent to lethal. Microarray technology has provided unprecedented opportunity to explore the genetic processes underlying prostate cancer by providing a comprehensive survey of a cell's transcriptional landscape. Prostate cancer, however, has posed significant challenges that have contributed to inconsistent results between studies and difficulty replicating findings. Despite these challenges, several important insights have been gained along with new clinical biomarkers of diagnosis and prognosis. Continued improvements in methods of tissue preparation, microarray technology and data analysis will overcome existing challenges and fuel future discoveries.

Complement C3c and related protein biomarkers in amyotrophic lateral sclerosis and Parkinson's disease

We have used quantitative 2D gel electrophoresis to analyze serum proteins from 422 patients with neurodegenerative diseases and normal individuals in an unbiased approach to identify biomarkers. Differences in abnormal serum levels were found between amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), and related disorders for 34 protein biomarker spots, nine of which were related to the complement system. Of these nine, four spots originated from the Complement C3b-alpha-chain (C3c(1), C3c(2a), C3c(2b), and C3dg). The C3c spots (C3c(1), C3c(2a), and C3c(2b)) had the same amino acid sequence and glycosylation, though only C3c(1) was phosphorylated. In addition, Complement Factors H, Bb, and Pre-Serum amyloid protein displayed different serum concentrations in ALS, PD, and normal sera, whereas Complement C4b gamma-chain and Complement Factor I did not. The differential expression of the complement proteins provides potentially useful biomarkers as well as evidence for the involvement of inflammatory processes in the pathogenesis of ALS and PD.

Progress in capillary electrophoresis of biomarkers and metabolites between 2002 and 2005

Biomarker discovery and metabolite research is a fast-growing and extremely important domain not only for the early detection of certain diseases but also for controlling its progress as well as in pharmaceutical investigations. For the analytical separation and identification, CE plays an indisputable role. Capillary systems enhancing different selectivity are applied and connected to different kind of detection systems. As the choice of buffer and its composition is responsible for a successful separation, special emphasis is put on solvent effects in this review. Altogether the most important capillary electrophoretic techniques applied for biomarker and metabolites analysis published between 2002 and 2005 are summarized and discussed.