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Introduction: Increased accessibility to next-generation sequencing within the last decade has led to a paradigm shift in cancer treatment from one-size-fits-all medicine to precision medicine providing therapeutic strategies tailored to the requirements of individual patients. However, the effect of even the most successful agent yet tested is only transient, and durable efficacy has yet to be achieved. Genome- and transcriptome-based approaches cannot fully predict the diversity of protein expression patterns or post-translational modifications that directly contribute to cancer pathogenesis and physiology. This underscores the need for concordant proteomic analysis in the next stage of precision medicine. Areas covered: This review begins with an overview of the recent advances and trends in precision medicine that currently rely on genomics, and highlights the utility of antibody-based reverse-phase protein array (RPPA) technology as a proteomic tool in this context. Expert commentary: RPPA is well suited for pharmacodynamics analysis in view of its ability to precisely map signaling status using limited amounts of clinical samples. In addition, the cost-effectiveness and rapid turn-around time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in clinical settings.

Pancreatic cancer is one of the most lethal tumors, and reliable detection of early-stage pancreatic cancer and risk diseases for pancreatic cancer is essential to improve the prognosis. As 260 genes were previously reported to be upregulated in invasive ductal adenocarcinoma of pancreas (IDACP) cells, quantification of the corresponding proteins in plasma might be useful for IDACP diagnosis. Therefore, the purpose of the present study was to identify plasma biomarkers for early detection of IDACP by using two proteomics strategies: antibody-based proteomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. Among the 260 genes, we focused on 130 encoded proteins with known function for which antibodies were available. Twenty-three proteins showed values of the area under the curve (AUC) of more than 0.8 in receiver operating characteristic (ROC) analysis of reverse-phase protein array (RPPA) data of IDACP patients compared with healthy controls, and these proteins were selected as biomarker candidates. We then used our high-throughput selected reaction monitoring or multiple reaction monitoring (SRM/MRM) methodology, together with an automated sample preparation system, micro LC and auto analysis system, to quantify these candidate proteins in plasma from healthy controls and IDACP patients on a large scale. The results revealed that insulin-like growth factor-binding protein (IGFBP)2 and IGFBP3 have the ability to discriminate IDACP patients at an early stage from healthy controls, and IGFBP2 appeared to be increased in risk diseases of pancreatic malignancy, such as intraductal papillary mucinous neoplasms (IPMNs). Furthermore, diagnosis of IDACP using the combination of carbohydrate antigen 19-9 (CA19-9), IGFBP2 and IGFBP3 is significantly more effective than CA19-9 alone. This suggests that IGFBP2 and IGFBP3 may serve as compensatory biomarkers for CA19-9. Early diagnosis with this marker combination may improve the prognosis of IDACP patients., Competing Interests: The authors declare no competing financial interest. One of our authors, W.H., is a CEO of Abnova and receives salary from Abnova. He also owns stock in Abnova. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Deregulation of intracellular signaling through accumulation of genetic alterations is a hallmark of cancer. In the past few decades, concerted and systematic efforts have been made to identify key genetic alterations and to develop therapeutic agents targeting active signaling molecules. However, the efficacy of molecular therapeutics often varies among individuals, and precise mapping of active molecules in individual patients is now considered an essential for therapy optimization. Reverse-phase protein array or microarray (RPPA or RPPM) is an emerging antibody-based highly quantitative proteomic technology, especially suitable for profiling of expression and modification of signaling proteins in low abundance. Because the supply of clinical materials is often limited, RPPA technology is highly advantageous for clinical proteomics in view of its high sensitivity as well as accurate quantification. RPPA has now begun to be incorporated into various clinical trials employing molecular-targeted therapeutics. In this article we review and discuss the application of RPPA technology in the fields of basic, preclinical, and clinical research. The RPPA Global Workshop was recently launched to accelerate the exchange of rapidly expanding knowledge of this fascinating technology among academic laboratories and industries worldwide. This article is part of a Special Issue entitled: Medical Proteomics., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Cancer biomarkers for the early detection of malignancies and selection of therapeutic strategies have been requested in the clinical field. Accurate and informative cancer biomarkers hold significant promise for improvements in the early detection of disease and in the selection of the most effective therapeutic strategies. Recently, significant progress in the comprehensive analysis of the human genome, epigenome, transcriptome, proteome and metabolome has led to revolutionary changes in the discovery of cancer biomarkers. The Human Proteome Organization has launched a global Human Proteome Project to map the entire human protein set. The Human Proteome Project research group has focused on three working proteomic pillars-mass spectrometry-based, antibody-based and knowledge-based proteomics-and each of these technologies is advancing rapidly. In this review, we introduce the proteomic platforms that are currently being used for cancer biomarker discovery, and describe examples of novel cancer biomarkers that were identified with each proteomic technology.

Background: Early detection would be one of the most effective means to improve the outcome of renal cell carcinoma (RCC). We searched for a new plasma marker for RCC using a label-free quantitative shotgun proteomics method., Methods: Plasma proteins were digested by trypsin, and the resulting peptides were analyzed by 2-Dimensional Image Converted Analysis of Liquid chromatography mass spectrometry (2DICAL). An identified biomarker candidate was subjected to validation using the Amplified Luminescent Proximity Homogeneous Assay (AlphaLISA)., Results: Among a total of 23,407 independent MS peaks, we found that the mean intensity of 59 peaks significantly differed between 20 clear cell RCC patients and 20 healthy controls. MS/MS spectra from 16 of the 59 peaks matched the amino acid sequences of the fibronectin 1 (FN1) gene product. The increased plasma level of FN1 in RCC patients was validated in a cohort of in 77 patients and 130 healthy controls (p < 0.0001)., Conclusions: The FN1 is considered to be a promising biomarker candidate for clear cell RCC. Furthermore, AlphaLISA is an alternate to the conventional enzyme-linked immunosorbent assay and should prove useful for the rapid validation of biomarker candidates.

Plasma proteome analysis requires sufficient power to compare numerous samples and detect changes in protein modification, because the protein content of human samples varies significantly among individuals, and many plasma proteins undergo changes in the bloodstream. A label-free proteomics platform developed in our laboratory, termed "Two-Dimensional Image Converted Analysis of Liquid chromatography and mass spectrometry (2DICAL)," is capable of these tasks. Here, we describe successful detection of novel prolyl hydroxylation of alpha-fibrinogen using 2DICAL, based on comparison of plasma samples of 38 pancreatic cancer patients and 39 healthy subjects. Using a newly generated monoclonal antibody 11A5, we confirmed the increase in prolyl-hydroxylated alpha-fibrinogen plasma levels and identified prolyl 4-hydroxylase A1 as a key enzyme for the modification. Competitive enzyme-linked immunosorbent assay of 685 blood samples revealed dynamic changes in prolyl-hydroxylated alpha-fibrinogen plasma level depending on clinical status. Prolyl-hydroxylated alpha-fibrinogen is presumably controlled by multiple biological mechanisms, which remain to be clarified in future studies.

We previously reported the development of an integrated proteome platform, namely 2-Dimensional Image Converted Analysis of Liquid chromatography and mass spectrometry (2DICAL), for quantitative comparison of large peptide datasets generated by nano-flow liquid chromatography (LC) and mass spectrometry (MS). The key technology of 2DICAL was the precise adjustment of the retention time of LC by dynamic programming. In order to apply 2DICAL to clinical studies that require comparison of a large number of patient samples we further refined the calculation algorithm and increased the accuracy and speed of the peptide peak alignment using a greedy algorithm, which had been used for fast DNA sequence alignment. The peptide peaks of each sample with the same m/z were extracted every 1 m/z and displayed with along the horizontal axis. Here we report a precise comparison of more than 150,000 typtic peptide ion peaks derived from 70 serum samples (40 patients with uterine endometrial cancer and 30 controls). The levels of 49 MS peaks were found to differ significantly between cancer patients and controls (P < 0.01, Welch's t-test and interquartile range [IQR] of >40), and the differential expression and identification of selected three proteins was validated by immunoblotting. 2DICAL was is highly advantageous for large-scale clinical proteomics because of its simple procedure, high throughput, and quantification accuracy.

We investigated the aberrant expression of plasma proteins in patients with pancreatic cancer. High-abundance plasma proteins (albumin, transferrin, haptoglobin, alpha-1-antitrypsin, IgG and IgA) were depleted by use of an immuno-affinity column, and low-abundance ones were separated into five fractions by anion-exchange chromatography. The fractionated plasma proteins were subjected to 2D-DIGE with highly sensitive fluorescent dyes. The quantitative protein expression profiles obtained by 2D-DIGE were compared between two plasma protein mixtures: one from five non-cancer bearing healthy donors and the other from five patients with pancreatic cancer. Among 1200 protein spots, we found that 33 protein spots were differently expressed between the two mixtures; 27 of these were up-regulated and six were down-regulated in cancer. Mass spectrometry and database searching allowed the identification of the proteins corresponding to the gel spots. Up-regulation of leucine-rich alpha-2-glycoprotein (LRG), which has not previously been implicated in pancreatic cancer, was observed. Western blotting with an anti-LRG antibody validated the up-regulation of LRG in an independent series of plasma samples from healthy controls, patients with chronic pancreatitis, and patients with pancreatic cancer. Our results demonstrate the application of a combination of multi-dimensional liquid chromatography with 2D-DIGE for plasma proteomics and suggest the clinical utility of LRG plasma level measurement.

We developed an integrated platform consisting of machinery and software modules that can apply vast amounts of data generated by nanoflow LC-MS to differential protein expression analyses. Unlabeled protein samples were completely digested with modified trypsin and separated by low speed (200 nl/min) one-dimensional HPLC. Mass spectra were obtained every 1 s by using the survey mode of a hybrid Q-TOF mass spectrometer and displayed in a two-dimensional plane with m/z values along the x axis, and retention time was displayed along the y axis. The time jitter of nano-LC was adjusted using newly developed software based on a dynamic programming algorithm. The comprehensiveness (60,000-160,000 peaks above the predetermined threshold detectable in 60-microg cell protein samples), reproducibility (average coefficient of variance of 0.35-0.39 and correlation coefficient of over 0.92 between duplicates), and accurate quantification with a wide dynamic range (over 10(3)) of our platform warrant its application to various types of experimental and translational proteomics.

To identify the proteomic alterations associated with carcinogenesis of hepatocellular carcinoma (HCC), we compared the protein expression profiles of nine HCC cell lines with those of primary cultured hepatocytes established from five individuals. A differential proteomic study was performed by two-dimensional difference gel electrophoresis, in which protein samples are labeled with different fluorescent dyes and separated according to their isoelectric point and molecular weight. To label the protein samples, we used a newly developed and highly sensitive fluorescent dye, which reacts with all reduced cysteine residues of proteins. Principal component analysis based on the intensity of 1238 protein spots indicated that the HCC cells and the normal hepatocytes had distinct proteomic profiles. The Wilcoxon test was used to determine the protein spots whose intensity was differentially regulated in the HCC cells compared with the normal hepatocytes, and mass spectrometric analysis was used to identify the proteins corresponding to the spots. The proteins identified are involved in cell cycle regulation, binding to a tumor-suppressor gene product, fatty acid binding, and regulation of translation. Western blotting with specific antibodies revealed the overexpression of PCNA, EB1 and E-FABP in HCC tissues compared with noncancerous tissues. Aberrant regulation of EB1 and E-FABP has not previously been implicated in the development of HCC.

Alpha fetoprotein (AFP) has been implicated in the development of hepatocellular carcinoma and is considered to be a diagnostic and prognostic tumor marker. Because elevated expression of AFP is associated with many characteristics of hepatocellular carcinoma tissues, we hypothesized that multiple proteins may function in a coordinated manner with AFP. To identify such proteins, we performed global protein expression analysis, namely a proteomic study. The protein expression profiles of 9 AFP-producing liver cancer cell lines (JHH-5, HuH-1, PLC/PRL/5, Hep3B, HT-17, JHH-7, HuH-7, HepG2, Li-7) and 7 nonproducing liver cancer cell lines (HLE, JHH-6, Sk-Hep-1, JHH-4, HLF, RBE, SSP-25) were generated by fluorescence 2-dimensional difference gel electrophoresis. In fluorescence 2-dimensional difference gel electrophoresis, proteins are labeled with fluorescent dyes before electrophoresis for more accurate quantitative expression analysis. We identified 11 protein spots that distinguished AFP-producing cell lines from nonproducing cell lines by multivariate studies. The spots showed consistent alterations in amount in AFP-producing cell lines (6 up-regulated and 5 down-regulated). An additional 5 liver cancer cell lines (KIM-1, KYN-2, KYN-3, PH5-CH, PH5-T) also were correctly grouped with respect to their AFP production on the basis of the intensity of the 11 protein spots. The proteins corresponding to the 11 selected spots were identified by mass spectrometry and were categorized into 4 groups based on their known role in apoptosis, glucose metabolism, cytoskeletal organization, or translation. In conclusion, we found a novel association of AFP with other proteins. Their interaction should provide insight into the biology of AFP-producing hepatocellular carcinoma cells., (Copyright 2004 American Association for the Study of Liver Diseases)

The combination of laser microdissection and two-dimensional gel electrophoresis (2-D PAGE) has been developed to perform proteomic analysis on specific populations of cells in cancer tissues. However, as conventional low sensitivity silver staining was used for spot detection, the microdissection required to obtain an adequate amount of protein for 2-D PAGE is laborious and only a restricted number of protein spots could be visualized. As a consequence, this technology was impractical for direct clinical applications and had a limited impact on cancer studies. To solve these problems, we developed an application in which fluorescent dyes label the proteins extracted from microdissected tissues prior to 2-D PAGE separation. In this application, a small amount of protein, less than 6.6 microg, was enough to generate a 2-D profile with approximately 1500 protein spots. This technique was applied to compare the proteome of normal intestinal epithelium with that of adenoma in Min mice. Thirty-seven protein spots reproducibly showed significant differences in intensities. Mass spectrometric analysis and Western blotting identified eight of them, including prohibitin, 14-3-3zeta, tropomyosin 3 and Hsp84. These results indicate that fluorescence labeling of proteins from microdissected tissues prior to 2-D PAGE is a powerful cancer proteomic study tool.

Treatment of advanced oral squamous cell carcinoma ( OSCC) requires the integration of multimodal approaches. The aim of this study was to identify predictors of tumor sensitivity to preoperative radiotherapy/chemotherapy for OSCC in order to allow oncologists to determine optimum therapeutic strategies without the associated adverse effects. Here, the protein expression profiles of formalin-fixed paraffin-embedded ( FFPE) tissue samples from 18 OSCC patients, termed learning cases, who received preoperative chemotherapy and/or radiotherapy followed by surgery were analyzed by quantitative proteomics and validated by immunohistochemistry in 68 test cases as well as in the 18 learning cases. We identified galectin-7 as a potential predictive marker of chemotherapy and/or radiotherapy resistance, and the sensitivity and specificity of the galectin-7 prediction score ( G7PS) in predicting this resistance was of 96.0% and 39.5%, respectively, in the 68 test cases. The cumulative 5-year disease-specific survival rate was 75.2% in patients with resistant prediction using G7PS and 100% in patients with sensitive prediction. In vitro overexpression of galectin-7 significantly decreased cell viability in OSCC cell line. Therefore, our findings suggest that galectin-7 is a potential predictive marker of chemotherapy and/or radiotherapy resistance in patients with OSCC. [ABSTRACT FROM AUTHOR]

Objective: Osteosarcoma (OS) is the most frequent primary malignant bone tumor in children and young adults. Although the introduction of combined neoadjuvant chemotherapy has significantly prolonged survival, the outcome for OS patients showing a poor response to chemotherapy is still unfavorable. In order to develop new therapeutic approaches, elucidation of the entire molecular pathway regulating OS cell proliferation would be desirable. Methods: MicroRNA (miRNA) are highly conserved noncoding RNA that play important roles in the development and progression of various other cancers. Using miRNA microarrays capable of detecting a known number of 933 miRNA, 108 miRNA were found to be commonly expressed in 24 samples of OS tissue and subjected to a cell proliferation assay. Results: We found that inhibition of 5 let-7 family miRNA (hsa-let-7a, b, f, g and i) significantly suppressed the proliferation of OS cells. Using a quantitative shotgun proteomics approach, we also found that the let-7 family miRNA regulated the expression of vimentin and serpin H1 proteins. Conclusions: Our present results indicate the involvement of let-7 family miRNA in regulation of the cell proliferation as well as epithelial-mesenchymal transition of OS. Thus, let-7 family miRNA may potentially provide novel targets for the development of therapeutic strategies against OS. © 2014 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Background: Early detection would be one of the most effective means to improve the outcome of renal cell carcinoma (RCC). We searched for a new plasma marker for RCC using a label-free quantitative shotgun proteomics method. Methods: Plasma proteins were digested by trypsin, and the resulting peptides were analyzed by 2-Dimensional Image Converted Analysis of Liquid chromatography mass spectrometry (2DICAL). An identified biomarker candidate was subjected to validation using the Amplified Luminescent Proximity Homogeneous Assay (AlphaLISA). Results: Among a total of 23,407 independent MS peaks, we found that the mean intensity of 59~peaks significantly differed between 20 clear cell RCC patients and 20~healthy controls. MS/MS spectra from 16 of the 59~peaks matched the amino acid sequences of the fibronectin 1 (FN1) gene product. {The increased plasma level of FN1 in RCC patients was validated in a cohort of in 77 patients and 130 healthy controls (p<0.0001).} Conclusions: The FN1 is considered to be a promising biomarker candidate for clear cell RCC. Furthermore, AlphaLISA is an alternate to the conventional enzyme-linked immunosorbent assay and should prove useful for the rapid validation of biomarker candidates. [ABSTRACT FROM AUTHOR]

Severe hematologic toxicity generally requires dose reduction or postponement strategies, which often compromise treatment efficacy and survival outcome. At present, there is no established predictive tool to identify patients at risk of a severe adverse event after any type of chemotherapy regimen. We have carried out a proteomics study using plasma samples from pancreatic cancer patients who had received the same gemcitabine treatment to identify new biomarkers that might be useful for prediction of gemcitabine-induced neutropenia and thrombocytopenia. We found that the baseline plasma level of haptoglobin showed a correlation with the severity of neutropenia and thrombocytopenia. In this short review, we summarize the available evidence regarding the prediction of hematologic adverse events after cytotoxic chemotherapy. Knowledge of predictive factors for toxicity should be incorporated into more intelligent selection of chemotherapy regimen and dosing to get closer to the ideal of personalized therapy. [ABSTRACT FROM AUTHOR]

Background & Aims: β-Catenin is a downstream effector of the Wnt signaling pathway and is believed to exert its oncogenic function by activating T-cell factor (TCF)/lymphoid enhancer factor (LEF) family transcriptional factors. However, it is still uncertain whether the diverse effects of β-catenin are caused solely by aberrant gene transactivation. In this study, we used a proteomics approach to obtain further insight into the functional properties of nuclear β-catenin. Methods: The protein assembly of a native β-catenin-containing complex in nuclear extracts from a colorectal cancer cell line, DLD-1, was identified using immunoprecipitation and mass spectrometry. Results: β-Catenin physically interacted with fusion (FUS)/translocated in liposarcoma (TLS) and various RNA-binding proteins. The expression of FUS/TLS was closely associated with the accumulation of β-catenin and with the undifferentiated status of intestinal epithelial cells. The transient transfection of FUS suppressed β-catenin-evoked gene transactivation of TCF/LEF, and β-catenin transfection affected the splicing pattern of the E1A minigene and induced a novel splicing variant of estrogen receptor (ER)-β exerting a dominant-negative activity. Conclusions: Human cancer expresses a large variety of alternatively spliced messenger RNA (mRNA), but the precise molecular mechanisms responsible for cancer-related alternative splicing are largely unknown. In this study, we demonstrated the interaction of β-catenin with FUS/TLS and other RNA-binding proteins involved in the regulation of pre-mRNA splicing. Certain mRNA splicing abbreviations seen in human cancers may be induced by the activation of the Wnt signaling pathway. [Copyright &y& Elsevier]

Abstract: Lung cancer, COPD and cardiovascular diseases are highlighted as some of the most common disease that cause mortality, and for that reason are the most active areas for drug development. This perspective paper overviews the urgent need to develop a health care system for a rapidly growing patient population in Japan, including forthcoming demands on clinical care, expecting outcomes, and economics. There is an increasing requirement to build on the strengths of the current health care system, thereby delivering urgent solutions for the future. There is also a declaration from the Ministry of Health, Labour and Welfare (MHLW), to develop new biomarker diagnostics, which is intended for patient stratification, aiding in diagnostic phenotype selection for responders to drug treatment of Japanese patients. This perspective was written by the panel in order to introduce novel technologies and diagnostic capabilities with successful implementation. The next generation of personalized drugs for targeted and stratified patient treatment will soon be available in major disease areas such as, lifestyle-related cancers, especially lung cancers with the highest mortality including a predisposing disorder chronic obstructive pulmonary disease, cardiovascular disease, and other diseases. Mass spectrometric technologies can provide the “phenotypic fingerprint” required for the concept of Personalized Medicine. Mass spectrometry-driven target biomarker diagnoses in combination with high resolution computed tomography can provide a critical pathway initiative facilitated by a fully integrated e-Health infrastructure system. We strongly recommend integrating validated biomarkers based on clinical proteomics, medical imaging with clinical care supported by e-Health model to support personalized treatment paradigms to reduce mortality and healthcare costs of chronic and co-morbid diseases in the elderly population of Japan. [Copyright &y& Elsevier]