An informatics-assisted label-free approach for personalized tissue membrane proteomics: case study on colorectal cancer

β-Amyloid Induces Pathology-Related Patterns of Tau Hyperphosphorylation at Synaptic Terminals

A synergy between β-amyloid (Aβ) and tau appears to occur in Alzheimer disease (AD), but the mechanisms of interaction, and potential locations, are little understood. This study investigates the possibility of such interactions within the cortical synaptic compartments of APP/PS1 mice. We used label-free quantitative mass spectrometry to study the phosphoproteome of synaptosomes, covering 2400 phosphopeptides and providing an unbiased survey of phosphorylation changes associated with amyloid pathology. Hyperphosphorylation was detected on 36 synaptic proteins, many of which are associated with the cytoskeleton. Importantly, tau is one of the most hyperphosphorylated proteins at the synapse, upregulated at both proline-directed kinase (PDK) sites (S199/S202, S396/S404) and nonPDK sites (S400). These PDK sites correspond to well-known pathological tau epitopes in AD patients, recognized by AT8 and PHF-1 antibodies, respectively. Hyperphosphorylation at S199/S202, a rarely examined combination, was further validated in patient-derived human synaptosomes by immunoblotting. Global surveys of upregulated phosphosites revealed 2 potential kinase motifs, which resemble those of cyclin-dependent kinase 5 (CDK5, a PDK) and casein kinase II (CK2, a nonPDK). Our data demonstrate that, within synaptic compartments, amyloid pathology is associated with tau hyperphosphorylation at disease-relevant epitopes. This provides a plausible mechanism by which Aβ promotes the spreading of tauopathy.

Membrane proteome characterization of periodontal ligament cell sets from deciduous and permanent teeth

BACKGROUND

Physiological roles for the periodontal ligament (PDL) include tooth eruption and anchorage, force absorption, and provision of proprioceptive information. Despite the advances in understanding the biology of PDL cells, there is a lack of information regarding the molecular signature of deciduous (DecPDL) and permanent (PermPDL) PDL tissues. Thus, the present study was designed to characterize the membrane proteome of DecPDL and PermPDL cells.

METHODS

Primary PDL cells were obtained (n = 6) and a label-free quantitative proteome of cell membrane-enriched components was performed. Proteome findings were validated by quantitative polymerase chain reaction and Western blot assays in fresh human tissues (n = 8) and primary cell cultures (n = 6). In addition, confocal microscopy was used to verify the expression of target factors in the PDL cell cultures.

RESULTS

Comparative gene ontology enrichment analysis evidenced that most stickling differences involved "endomembrane system" (PICALM, STX4, and LRP10), "hydrolase activity" (NCSTN and XRCC6), "protein binding" (PICALM, STX4, GPNMB, VASP, extended-synaptotagmin 2 [ESYT2], and leucine-rich repeat containing 15 [LRRC15]), and "isomerase activity" (FKBP8). Data are available via ProteomeXchange with identifier PXD010226. At the transcript level, high PICALM in DecPDL and ESYT2 and LRRC15 in PermPDL were confirmed in fresh PDL tissues. Furthermore, Western blot analysis confirmed increased levels of PICALM, LRRC15, and ESYT2 in cells and/or fresh tissues, and confocal microscopy confirmed the trends for PICALM and LRRC15 expression in PDL cells.

CONCLUSION

We report the first comprehensive characterization of the membrane protein machinery of DecPDL and PermPDL cells, and together, we identified a distinct molecular signature for these cell populations, including unique proteins for DecPDL and PermPDL.

Probing the colorectal cancer proteome for biomarkers: Current status and perspectives

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide. Biomarkers that can facilitate better clinical management of CRC are in high demand to improve patient outcome and to reduce mortality. In this regard, proteomic analysis holds a promising prospect in the hunt of novel biomarkers for CRC and in understanding the mechanisms underlying tumorigenesis. This review aims to provide an overview of the current progress of proteomic research, focusing on discovery and validation of diagnostic biomarkers for CRC. We will summarize the contributions of proteomic strategies to recent discoveries of protein biomarkers for CRC and also briefly discuss the potential and challenges of different proteomic approaches in biomarker discovery and translational applications.

Chemotherapy Immunophenoprofiles in Non-Small-Cell Lung Cancer by Personalized Membrane Proteomics

OBJECTIVES

No study has addressed how the immune status at the molecular level is affected by first-line pemetrexed and cisplatin (PEM-CIS) combination therapy in patients with non-small-cell lung cancer (NSCLC). Thus, we aimed to identify the immune status from membrane proteome alterations in patients with NSCLC upon PEM-CIS treatment.

METHODS

The paired peripheral blood mononuclear cells (PBMCs) were collected from four patients with lung adenocarcinoma before and after the first regimen of PEM-CIS treatment and applied quantitative membrane proteomics analysis.

RESULT

In the personalized PBMC membrane proteome profiles, 2424 proteins were identified as displaying patient-specific responsive patterns. We discovered an elevated neutrophil activity and a more suppressive T-cell phenotype with the downregulation of cytotoxic T lymphocyte antigen 4 degradation and the upregulation of type 2 T-helper and T-regulatory cells in the patient with the highest progression-free survival (PFS) of 14.5 months. Patients with a PFS of 2 months showed higher expressions of T-cell subsets, MHC class II pathways, and T-cell receptor signaling, which indicated an activated immune status.

CONCLUSION AND CLINICAL RELEVANCE

Without the additional isolation of specific immune cell populations, our study demonstrated that PEM-CIS chemotherapy altered patients' immune system in terms of neutrophils, T cells, and antigen presentation pathways.

Cell Line Secretome and Tumor Tissue Proteome Markers for Early Detection of Colorectal Cancer: A Systematic Review

Objective: In order to find low abundant proteins secretome and tumor tissue proteome data have been explored in the last few years for the diagnosis of colorectal cancer (CRC). In this review we aim to summarize the results of studies evaluating markers derived from the secretome and tumor proteome for blood based detection of colorectal cancer. Methods: Observing the preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines PubMed and Web of Science databases were searched systematically for relevant studies published up to 18 July 2017. After screening for predefined eligibility criteria a total of 47 studies were identified. Information on diagnostic performance indicators, methodological procedures and validation was extracted. Functions of proteins were identified from the UniProt database and the the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess study quality. Results: Forty seven studies meeting inclusion criteria were identified. Overall, 83 different proteins were identified, with carcinoembryonic Antigen (CEA) being by far the most commonly reported (reported in 24 studies). Evaluation of the markers or marker combinations in blood samples from CRC cases and controls yielded apparently very promising diagnostic performances, with area under the curve >0.9 in several cases, but lack of internal or external validation, overoptimism due to overfitting and spectrum bias due to evaluation in clinical setting rather than screening settings are major concerns. Conclusions: Secretome and tumor proteome-based biomarkers when validated in blood yield promising candidates. However, for discovered protein markers to be clinically applicable as screening tool they have to be specific for early stages and need to be validated externally in larger studies with participants recruited in true screening setting.

Combining membrane proteomics and computational three-way pathway analysis revealed signalling pathways preferentially regulated in human iPSCs and human ESCs

Owing to the clinical potential of human induced pluripotent stem cells (hiPSCs) in regenerative medicine, a thorough examination of the similarities and differences between hiPSCs and human embryonic stem cells (hESCs) has become indispensable. Moreover, as the important roles of membrane proteins in biological signalling, functional analyses of membrane proteome are therefore promising. In this study, a pathway analysis by the bioinformatics tool GSEA was first performed to identify significant pathways associated with the three comparative membrane proteomics experiments: hiPSCs versus precursor human foreskin fibroblasts (HFF), hESCs versus precursor HFF, and hiPSCs versus hESCs. A following three-way pathway comparison was conducted to identify the differentially regulated pathways that may contribute to the differences between hiPSCs and hESCs. Our results revealed that pathways related to oxidative phosphorylation and focal adhesion may undergo incomplete regulations during the reprogramming process. This hypothesis was supported by another public proteomics dataset to a certain degree. The identified pathways and their core enriched proteins could serve as the starting point to explore the possible ways to make hiPSCs closer to hESCs.

Omics AnalySIs System for PRecision Oncology (OASISPRO): a web-based omics analysis tool for clinical phenotype prediction

SUMMARY

Precision oncology is an approach that accounts for individual differences to guide cancer management. Omics signatures have been shown to predict clinical traits for cancer patients. However, the vast amount of omics information poses an informatics challenge in systematically identifying patterns associated with health outcomes, and no general purpose data mining tool exists for physicians, medical researchers and citizen scientists without significant training in programming and bioinformatics. To bridge this gap, we built the Omics AnalySIs System for PRecision Oncology (OASISPRO), a web-based system to mine the quantitative omics information from The Cancer Genome Atlas (TCGA). This system effectively visualizes patients' clinical profiles, executes machine-learning algorithms of choice on the omics data and evaluates the prediction performance using held-out test sets. With this tool, we successfully identified genes strongly associated with tumor stage, and accurately predicted patients' survival outcomes in many cancer types, including adrenocortical carcinoma. By identifying the links between omics and clinical phenotypes, this system will facilitate omics studies on precision cancer medicine and contribute to establishing personalized cancer treatment plans.

AVAILABILITY AND IMPLEMENTATION

This web-based tool is available at http://tinyurl.com/oasispro; source codes are available at http://tinyurl.com/oasisproSourceCode.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Comprehensive Proteomic Characterization of the Human Colorectal Carcinoma Reveals Signature Proteins and Perturbed Pathways

The global change in protein abundance in colorectal cancer (CRC) and its contribution to tumorigenesis have not been comprehensively analyzed. In this study, we conducted a comprehensive proteomic analysis of paired tumors and adjacent tissues (AT) using high-resolution Fourier-transform mass spectrometry and a novel algorithm of quantitative pathway analysis. 12380 proteins were identified and 740 proteins that presented a 4-fold change were considered a CRC proteomic signature. A significant pattern of changes in protein abundance was uncovered which consisted of an imbalance in protein abundance of inhibitory and activating regulators in key signal pathways, a significant elevation of proteins in chromatin modification, gene expression and DNA replication and damage repair, and a decreased expression of proteins responsible for core extracellular matrix architectures. Specifically, based on the relative abundance, we identified a panel of 11 proteins to distinguish CRC from AT. The protein that showed the greatest degree of overexpression in CRC compared to AT was Dipeptidase 1 (DPEP1). Knockdown of DPEP1 in SW480 and HCT116 cells significantly increased cell apoptosis and attenuated cell proliferation and invasion. Together, our results show one of largest dataset in CRC proteomic research and provide a molecular link from genomic abnormalities to the tumor phenotype.

Protein Markers Associated with an ALDH Sub-Population in Colorectal Cancer

ALDH has been shown to be a marker that denotes a sub-population of cancer stem cells in colorectal and other cancers. This sub-population of cells shows an increased risk for tumor initiation, metastasis, and resistance to chemotherapy and radiation resulting in recurrence and death. It is thus essential to identify the important signaling pathways related to ALDH1+ CSCs in colon cancer. The essential issue becomes to isolate pure sub-populations of cells from heterogeneous tissues for further analysis. To achieve this goal, tissues from colorectal cancer Stage III patients were immuno-stained with ALDH1 antibody. Target ALDH1+ and ALDH1- cells from the same tissue were micro-dissected using Laser Capture Microdissection (LCM). Captured cells were lysed and analyzed using LC-MS/MS where around 20,000 cells were available for analysis. This analysis resulted in 134 proteins which were differentially expressed between ALDH1+ and ALDH1- cells in three patient sample pairs. Based on these differentially expressed proteins an IPA pathway analysis was performed that showed two key pathways in cell to cell signaling and organismal injury and abnormalities. The IPA analysis revealed β-catenin, NFκB (p65) and TGFβ1 as important cancer-related proteins in these pathways. A TMA validation using immunofluorescence staining of tissue micro-arrays including 170 cases was used to verify that these key proteins were highly overexpressed in ALDH1+ cells in colon cancer tissues compared to ALDH1- cells.

Integrative analysis of the colorectal cancer proteome: potential clinical impact

INTRODUCTION

Colorectal cancer (CRC) is one of the common types of cancer that affects a significant proportion of the population and is a major contributor to cancer related mortality. The relatively poor survival rate of CRC could be improved through the identification of clinically useful biomarkers. Areas covered: This review highlights the need for biomarkers and discusses recent proteomics discoveries in the aspects of CRC clinical practice including diagnosis, prognosis, therapy, screening and molecular pathological epidemiology (MPE). Studies have been evaluated in relation to biomarker target, methodology, sample selection, limitations, and potential impact. Finally, the progress in proteomic approaches is briefly discussed and the main difficulties facing the translation of proteomics biomarkers into the clinical practice are highlighted. Expert commentary: The establishment of specific guidelines, best practice recommendations and the improvement in proteomic strategies will significantly improve the prospects for developing clinically useful biomarkers.

Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures

Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P < 0.0001). We further built a least absolute shrinkage and selection operator (LASSO)-Cox proportional hazards model that stratified patients into early relapse and late relapse groups (P = 0.00013). The top proteomic features indicative of platinum response were involved in ATP synthesis pathways and Ran GTPase binding. Overall, we demonstrated that proteomic profiles of ovarian serous carcinoma patients predicted platinum drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers.

Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer

Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers.

Rapid High-pH Reverse Phase StageTip for Sensitive Small-Scale Membrane Proteomic Profiling

Membrane proteins are crucial targets for cancer biomarker discovery and drug development. However, in addition to the inherent challenges of hydrophobicity and low abundance, complete membrane proteome coverage of clinical specimen is usually hindered by the requirement of large amount of starting materials. Toward comprehensive membrane proteomic profiling for small amounts of samples (10 μg), we developed high-pH reverse phase (Hp-RP) combined with stop-and-go extraction tip (StageTip) technique, as a fast (∼15 min.), sensitive, reproducible, high-resolution and multiplexed fractionation method suitable for accurate quantification of the membrane proteome. This approach provided almost 2-fold enhanced detection of peptides encompassing transmembrane helix (TMH) domain, as compared with strong anion exchange (SAX) and strong cation exchange (SCX) StageTip techniques. Almost 5000 proteins (∼60% membrane proteins) can be identified in only 10 μg of membrane protein digests, showing the superior sensitivity of the Hp-RP StageTip approach. The method allowed up to 9- and 6-fold increase in the identification of unique hydrophobic and hydrophilic peptides, respectively. The Hp-RP StageTip method enabled in-depth membrane proteome profiling of 11 lung cancer cell lines harboring different EGFR mutation status, which resulted in the identification of 3983 annotated membrane proteins. This provides the largest collection of reference peptide spectral data for lung cancer membrane subproteome. Finally, relative quantification of membrane proteins between Gefitinib-resistant and -sensitive lung cancer cell lines revealed several up-regulated membrane proteins with key roles in lung cancer progression.

Annexin A4 and cancer

Annexin A4 (Anxa4) is one of the Ca(2+)-regulated and phospholipid-binding annexin superfamily proteins. Anxa4 has a potential role in diagnosis, prognosis, and treatment of certain cancers. Studies indicate that Anxa4 up-regulation promotes the progression of tumor and chemoresistance of colorectal cancer (CRC), esophageal squamous cell carcinoma (ESCC), endometrial carcinoma (EC), gastric cancer (GC), chemoresistant lung cancer (LC), malignant mesothelioma (MM), renal cell carcinoma (RCC), ovarian clear cell carcinoma (OCCC), cholangiocarcinoma, hepatocellular carcinoma (HCC), breast cancer (BC), and laryngeal cancer. Interestingly, Anxa4 also might specifically function as a tumor suppressor for prostate cancer (PCa) and have a paradoxical role for pancreatic cancer (PCC). Differential expression of Anxa4 may distinguish major salivary gland tumor (MSGT) from thyroid cancer. In addition, its differential expression was linked to Sirt1-induced cisplatin resistance of oral squamous cell carcinoma (OSCC) and miR-7-induced migration and invasion inhibition of glioma. This current review summarizes and discusses the clinical significance of Anxa4 in cancer as well as its potential mechanisms of action. It may provide new integrative understanding for future studies on the exact role of Anxa4 in cancer.

Linking patient outcome to high throughput protein expression data identifies novel regulators of colorectal adenocarcinoma aggressiveness

A key question in cancer systems biology is how to use molecular data to predict the biological behavior of tumors from individual patients. While genomics data have been heavily used, protein signaling data are more directly connected to biological phenotype and might predict cancer phenotypes such as invasion, metastasis, and patient survival. In this study, we mined publicly available data for colorectal adenocarcinoma from the Cancer Genome Atlas and identified protein expression and signaling changes that are statistically associated with patient outcome. Our analysis identified a number of known and potentially new regulators of colorectal cancer. High levels of insulin growth factor binding protein 2 (IGFBP2) were associated with both recurrence and death, and this was validated by immunohistochemical staining of a tissue microarray for a secondary patient dataset. Interestingly, GATA binding protein 3 (GATA3) was the protein most frequently associated with death in our analysis, and GATA3 expression was significantly decreased in tumor samples from stage I-II deceased patients. Experimental studies using engineered colon cancer cell lines show that exogenous expression of GATA3 decreases three-dimensional colony growth and invasiveness of colon cancer cells but does not affect two-dimensional proliferation. These findings suggest that protein data are useful for biomarker discovery and identify GATA3 as a regulator of colorectal cancer  aggressiveness.

Quantitation of the phosphoproteome using the library-assisted extracted ion chromatogram (LAXIC) strategy

Phosphorylation is a key posttranslational modification that regulates many signaling pathways, but quantifying changes in phosphorylation between samples can be challenging due to its low stoichiometry within cells. We have introduced a mass spectrometry-based label-free quantitation strategy termed LAXIC for the analysis of the phosphoproteome. This method uses a spiked-in synthetic peptide library designed to elute across the entire chromatogram for local normalization of phosphopeptides within complex samples. Normalization of phosphopeptides by library peptides that co-elute within a small time frame accounts for fluctuating ion suppression effects, allowing more accurate quantitation even when LC-MS performance varies. Here we explain the premise of LAXIC, the design of a suitable peptide library, and how the LAXIC algorithm can be implemented with software developed in-house.

Plant-derived protease inhibitors LC-pi (Lavatera cashmeriana) inhibit human lung cancer cell proliferation in vitro

The objective of this study was to check the anticancer activity of purified protease inhibitors of Lavatera cashmeriana viz LC-pi I, II, III, and IV (Lavatera cashmeriana protease inhibitors) on A549 (lung) cell. It was found that LC-pi I and II significantly inhibited the proliferation of A549 cells with IC₅₀ value of 54 μg/ml and 38 μg/ml, respectively, whereas inhibition by LC-pi III and IV was negligible. LC-pi I and II were further found to inhibit formation of colonies in a dose-dependent manner. Also, both inhibitors were found to induce apoptosis causing chromatin condensation and DNA fragmentation, without loss of mitochondrial membrane potential. Cell cycle revealed a significant increase of subG₀/G₁ phase cells that are apoptotic cells. We also demonstrated a dose-dependent decrease in migration of A549 cells on cell migration assay by both inhibitors. Taken together, we demonstrate that LC-pi I and II inhibited proliferation through arresting cells before apoptosis, inducing apoptosis and inhibiting cell migration in human lung cancer cells, but the study warrants further investigation. Our results support the notion that plant protease inhibitors may have the potential to advance as chemopreventive agents.

Mass spectrometry-based proteomics in Chest Medicine, Gerontology, and Nephrology: subgroups omics for personalized medicine

Mass spectrometry (MS) is currently the most promising tool for studying proteomics to investigate largescale proteins in a specific proteome. Emerging MS-based proteomics is widely applied to decipher complex proteome for discovering potential biomarkers. Given its growing usage in clinical medicine for biomarker discovery to predict, diagnose and confer prognosis, MS-based proteomics can benefit study of personalized medicine. In this review we introduce some fundamental MS theory and MS-based quantitative proteomic approaches as well as several representative clinical MS-based proteomics issues in Chest Medicine, Gerontology, and Nephrology.

Proteomics for discovery of candidate colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers.

Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851.

Proteomics, genomics and transcriptomics: their emerging roles in the discovery and validation of colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cancer in females and the third in males. Since CRC is often diagnosed at an advanced stage when prognosis is poor, identification of biomarkers for early diagnosis is urgently required. Recent advances in proteomics, genomics and transcriptomics have facilitated high-throughput profiling of data generated from CRC-related genes and proteins, providing a window of information for biomarker discovery and validation. However, transfer of candidate biomarkers from bench to bedside remains a dilemma. In this review, we will discuss emerging proteomic technologies and highlight various sample types utilized for proteomics-based identification of CRC biomarkers. Moreover, recent breakthroughs in genomics and transcriptomics for the identification of CRC biomarkers, with particular emphasis on the merits of emerging methylomic and miRNAomic strategies, will be discussed. Integration of proteomics, genomics and transcriptomics will facilitate the discovery and validation of CRC biomarkers leading to the emergence of personalized medicine.

Characterization of the membrane proteome and N-glycoproteome in BV-2 mouse microglia by liquid chromatography-tandem mass spectrometry

BACKGROUND

Microglial cells are resident macrophages of the central nervous system and important cellular mediators of the immune response and neuroinflammatory processes. In particular, microglial activation and communication between microglia, astrocytes, and neurons are hallmarks of the pathogenesis of several neurodegenerative diseases. Membrane proteins and their N-linked glycosylation mediate this microglial activation and regulate many biological process including signal transduction, cell-cell communication, and the immune response. Although membrane proteins and N-glycosylation represent a valuable source of drug target and biomarker discovery, the knowledge of their expressed proteome in microglia is very limited.

RESULTS

To generate a large-scale repository, we constructed a membrane proteome and N-glycoproteome from BV-2 mouse microglia using a novel integrated approach, comprising of crude membrane fractionation, multienzyme-digestion FASP, N-glyco-FASP, and various mass spectrometry. We identified 6928 proteins including 2850 membrane proteins and 1450 distinct N-glycosylation sites on 760 N-glycoproteins, of which 556 were considered novel N-glycosylation sites. Especially, a total of 114 CD antigens are identified via MS-based analysis in normal conditions of microglia for the first time. Our bioinformatics analysis provides a rich proteomic resource for examining microglial function in, for example, cell-to-cell communication and immune responses.

CONCLUSIONS

Herein, we introduce a novel integrated proteomic approach for improved identification of membrane protein and N-glycosylation sites. To our knowledge, this workflow helped us to obtain the first and the largest membrane proteomic and N-glycoproteomic datesets for mouse microglia. Collectively, our proteomics and bioinformatics analysis significantly expands the knowledge of the membrane proteome and N-glycoproteome expressed in microglia within the brain and constitutes a foundation for ongoing proteomic studies and drug development for various neurological diseases.

Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.

An integrated proteomic and transcriptomic approach to understanding azathioprine- induced hepatotoxicity in rat primary hepatocytes

Azathioprine, an immunosuppressant, has gained a prominent position in the clinic for prevention of graft rejection in organ transplants, as well as dermatological autoimmune diseases. However, according to a number of research reports, hepatotoxicity, as one of the side effects, is a major obstacle in azathioprine therapy. In this study, an integrated toxicoproteomic and toxicotranscriptomic analysis was performed using rat primary hepatocytes, in order to gain insight into the in-depth pathway map related to azathioprine-induced hepatotoxicity. For proteomic and transcriptomic analysis, rat primary hepatocytes were exposed to azathioprine at IC20 concentration for 24 h. In particular, 2D LC-MS/MS and informatics-assisted label-free strategy for proteomic analysis were applied in order to increase the number of identified proteins and to improve the confidence of the quantitation results. Among 119 differentially identified protein species, 69 were upregulated and 50 were downregulated in the azathioprine-treated group. At the mRNA level, results of transcriptomic analysis showed increased transcription of 340 genes and decreased transcription of 63 genes in the azathioprine-treated group. Based on the analysis of transcriptomic and proteomic results using the DAVID program, drug metabolism/oxidative stress enzymes, xenobiotic metabolism by cytochrome P450, fatty acid metabolism, primary bile acid biosynthesis, contraction, inflammation metabolism, and mitogen-activated protein kinase (MAPK) kinase (ERK/JNK/p38 kinase) pathways were affected in azathioprine-treated hepatotoxicity. The effects on genes and proteins related to several important pathways were confirmed by real-time PCR and immunoblot analysis, respectively. This study is the first to report on relevant pathways related to azathioprine-induced hepatotoxicity through performance of integrated transcriptomic and proteomic analyses.

Claudins and other tight junction proteins

Epithelial transport relies on the proper function and regulation of the tight junction (TJ), other-wise uncontrolled paracellular leakage of solutes and water would occur. They also act as a fence against mixing of membrane proteins of the apical and basolateral side. The proteins determining paracellular transport consist of four transmembrane regions, intracellular N and C terminals, one intracellular and two extracellular loops (ECLs). The ECLs interact laterally and with counterparts of the neighboring cell and by this achieve a general sealing function. Two TJ protein families can be distinguished, claudins, comprising 27 members in mammals, and TJ-associated MARVEL proteins (TAMP), comprising occludin, tricellulin, and MarvelD3. They are linked to a multitude of TJ-associated regulatory and scaffolding proteins. The major TJ proteins are classified according to the physiological role they play in enabling or preventing paracellular transport. Many TJ proteins have sealing functions (claudins 1, 3, 5, 11, 14, 19, and tricellulin). In contrast, a significant number of claudins form channels across TJs which feature selectivity for cations (claudins 2, 10b, and 15), anions (claudin-10a and -17), or are permeable to water (claudin-2). For several TJ proteins, function is yet unclear as their effects on epithelial barriers are inconsistent (claudins 4, 7, 8, 16, and occludin). TJs undergo physiological and pathophysiological regulation by altering protein composition or abundance. Major pathophysiological conditions which involve changes in TJ protein composition are (1) effects of pathogens binding to TJ proteins, (2) altered TJ protein composition during inflammation and infection, and (3) altered TJ protein expression in cancers.

Prioritization of cancer marker candidates based on the immunohistochemistry staining images deposited in the human protein atlas

Cancer marker discovery is an emerging topic in high-throughput quantitative proteomics. However, the omics technology usually generates a long list of marker candidates that requires a labor-intensive filtering process in order to screen for potentially useful markers. Specifically, various parameters, such as the level of overexpression of the marker in the cancer type of interest, which is related to sensitivity, and the specificity of the marker among cancer groups, are the most critical considerations. Protein expression profiling on the basis of immunohistochemistry (IHC) staining images is a technique commonly used during such filtering procedures. To systematically investigate the protein expression in different cancer versus normal tissues and cell types, the Human Protein Atlas is a most comprehensive resource because it includes millions of high-resolution IHC images with expert-curated annotations. To facilitate the filtering of potential biomarker candidates from large-scale omics datasets, in this study we have proposed a scoring approach for quantifying IHC annotation of paired cancerous/normal tissues and cancerous/normal cell types. We have comprehensively calculated the scores of all the 17219 tested antibodies deposited in the Human Protein Atlas based on their accumulated IHC images and obtained 457110 scores covering 20 different types of cancers. Statistical tests demonstrate the ability of the proposed scoring approach to prioritize cancer-specific proteins. Top 100 potential marker candidates were prioritized for the 20 cancer types with statistical significance. In addition, a model study was carried out of 1482 membrane proteins identified from a quantitative comparison of paired cancerous and adjacent normal tissues from patients with colorectal cancer (CRC). The proposed scoring approach demonstrated successful prioritization and identified four CRC markers, including two of the most widely used, namely CEACAM5 and CEACAM6. These results demonstrate the potential of this scoring approach in terms of cancer marker discovery and development. All the calculated scores are available at http://bal.ym.edu.tw/hpa/.

Stomatin-like protein 2 is associated with the clinicopathological features of human papillary thyroid cancer and is regulated by TGF-β in thyroid cancer cells

Papillary thyroid cancer (PTC) accounts for 80-90% of all cases of thyroid malignancies. Stomatin-like protein 2 (SLP-2) is a novel member of the stomatin superfamily and is found in several types of human tumors. However, whether it is expressed in human PTC is unknown. In the present study, we aimed to explore the diagnostic value of SLP-2 in patients with PTC and to investigate whether SLP-2 expression is regulated by transforming growth factor-β (TGF-β), a cytokine which plays an important role in PTC tumorigenesis. A total of 107 patients consisting of 99 cases of classical and 8 cases of follicular variant PTC was examined. The expression of SLP-2 mRNA and protein was examined by immunohistochemistry (IHC) and qPCR, respectively. We found that SLP-2 was overexpressed in human PTC. The expression of SLP-2 was significantly associated with clinicopathological features of the PTC cases. Particularly, increased SLP-2 expression was mainly correlated with primary tumors >1 cm in size, with late stage tumors and with metastatic lymph nodes. The expression of SLP-2 was correlated with the expression of Ki-67, a cell proliferation marker, in PTC tissues as detected by IHC. SLP-2 was upregulated by TGF-β1 in PTC cells as evaluated by western blotting. The present data revealed for the first time that patients with PTC exhibited SLP-2 overexpression that was associated with clinicopathological features. The correlation between SLP-2 expression and proliferation marker Ki-67 may be characteristic of PTC and may reflect PTC progression. SLP-2 was upregulated by TGF-β1, indicating a possible role of SLP-2 in PTC tumorigenesis. Our data suggest that SLP-2 may be considered as a useful diagnostic marker and therapeutic target for PTC.

Integrative analysis of proteomic and transcriptomic data for identification of pathways related to simvastatin-induced hepatotoxicity

Hepatocytes are used widely as a cell model for investigation of xenobiotic metabolism and the toxic mechanism of drugs. Simvastatin is the first statin drug used extensively in clinical practice for control of elevated cholesterol or hypercholesterolemia. However, it has also been reported to cause adverse effects in liver due to cellular damage. In this study, for proteomic and transcriptomic analysis, rat primary hepatocytes were exposed to simvastatin at IC20 concentration for 24 h. Among a total of 607 differentially expressed proteins, 61 upregulated and 29 downregulated proteins have been identified in the simvastatin-treated group. At the mRNA level, results of transcriptomic analysis revealed 206 upregulated and 41 downregulated genes in the simvastatin-treated group. Based on results of transcriptomic and proteomic analysis, NRF2-mediated oxidative stress response, xenobiotics by metabolism of cytochrome P450, fatty acid metabolism, bile metabolism, and urea cycle and inflammation metabolism pathways were focused using IPA software. Genes (FASN, UGT2B, ALDH1A1, CYP1A2, GSTA2, HAP90, IL-6, IL-1, FABP4, and ABC11) and proteins (FASN, CYP2D1, UG2TB, ALDH1A1, GSTA2, HSP90, FABP4, and ABCB11) related to several important pathways were confirmed by real-time PCR andWestern blot analysis, respectively. This study will provide new insight into the potential toxic pathways induced by simvastatin.

Quantitative measurement of phosphoproteome response to osmotic stress in arabidopsis based on Library-Assisted eXtracted Ion Chromatogram (LAXIC)

Global phosphorylation changes in plants in response to environmental stress have been relatively poorly characterized to date. Here we introduce a novel mass spectrometry-based label-free quantitation method that facilitates systematic profiling plant phosphoproteome changes with high efficiency and accuracy. This method employs synthetic peptide libraries tailored specifically as internal standards for complex phosphopeptide samples and accordingly, a local normalization algorithm, LAXIC, which calculates phosphopeptide abundance normalized locally with co-eluting library peptides. Normalization was achieved in a small time frame centered to each phosphopeptide to compensate for the diverse ion suppression effect across retention time. The label-free LAXIC method was further treated with a linear regression function to accurately measure phosphoproteome responses to osmotic stress in Arabidopsis. Among 2027 unique phosphopeptides identified and 1850 quantified phosphopeptides in Arabidopsis samples, 468 regulated phosphopeptides representing 497 phosphosites have shown significant changes. Several known and novel components in the abiotic stress pathway were identified, illustrating the capability of this method to identify critical signaling events among dynamic and complex phosphorylation. Further assessment of those regulated proteins may help shed light on phosphorylation response to osmotic stress in plants.

Proteomic workflow for analysis of archival formalin-fixed and paraffin-embedded clinical samples to a depth of 10 000 proteins

PURPOSE

Archival formalin-fixed and paraffin-embedded clinical samples represent a very diverse source of material for proteomic investigation of diseases, often with follow-up patient information. Here, we describe an analytical workflow for analysis of laser-capture microdissected formalin-fixed and paraffin-embedded samples that allows studying proteomes to a depth of 10 000 proteins per sample.

EXPERIMENTAL DESIGN

The workflow involves lysis of tissue in SDS-containing buffer, detergent removal, and consecutive digestion of the proteins with two enzymes by the multienzyme digestion filter-aided sample preparation method. Resulting peptides are fractionated by pipette-tip based strong anion exchange into six fractions and analyzed by LC-MS/MS on a bench top quadrupole Orbitrap mass spectrometer.

RESULTS

Analysis of the data using the MaxQuant software resulted in the identification of 9502 ± 28 protein groups per a 110 nL sample of microdissected cells from human colonic adenoma. This depth of proteome analysis enables systemic insights into the organization of the adenoma cells and an estimation of the abundances of known biomarkers. It also allows the identification of proteins expressed from tumor suppressors, oncogenes, and other key players in the development and progression of the colorectal cancer.

CONCLUSION AND CLINICAL RELEVANCE

Our proteomic platform can be used for quantitative comparisons between samples representing different stages of diseases and thus can be applied to the discovery of biomarkers or drug targets.

Extensive quantitative remodeling of the proteome between normal colon tissue and adenocarcinoma

In-depth proteomic analysis of microdissected colorectal cancer identifies extensive alterations in the cell-surface and nuclear proteomes between normal mucosa and adenocarcinoma, but observes strikingly little proteomic change between cancer and metastases.

First large-scale proteomic analysis of microdissected tissue from archival formalin-fixed and paraffin-embedded material.

Quantitation of 7576 proteins between patient-matched samples of normal colonic mucosa, primary cancer, and nodal metastasis.

Expression levels of 1808 proteins changed significantly between normal and cancer tissues.

Total Protein Approach (TPA)—a new way to determine protein copy numbers per cell without protein standards.

We report a proteomic analysis of microdissected material from formalin-fixed and paraffin-embedded colorectal cancer, quantifying >7500 proteins between patient matched normal mucosa, primary carcinoma, and nodal metastases. Expression levels of 1808 proteins changed significantly between normal and cancer tissues, a much larger fraction than that reported in transcript-based studies. Tumor cells exhibit extensive alterations in the cell-surface and nuclear proteomes. Functionally similar changes in the proteome were observed comparing rapidly growing and differentiated CaCo-2 cells. In contrast, there was minimal proteomic remodeling between primary cancer and metastases, suggesting that no drastic proteome changes are necessary for the tumor to propagate in a different tissue context. Additionally, we introduce a new way to determine protein copy numbers per cell without protein standards. Copy numbers estimated in enterocytes and cancer cells are in good agreement with CaCo-2 and HeLa cells and with the literature data. Our proteomic data set furthermore allows mapping quantitative changes of functional protein classes, enabling novel insights into the biology of colon cancer.

Blockade of phospholipid scramblase 1 with its N-terminal domain antibody reduces tumorigenesis of colorectal carcinomas in vitro and in vivo

Background

Membrane-bound phospholipid scramblase 1 (PLSCR1) is involved in both lipid trafficking and cell signaling. Previously, we showed that PLSCR1 is overexpressed in many colorectal carcinomas (CRCs). In the present study, we investigated the tumorigenic role of PLSCR1 in CRC and suggest that it is a potential therapeutic target.

Methods

To identify PLSCR1 as a therapeutic target, we studied the tumorigenic properties of CRC cell lines treated with a monoclonal antibody (NP1) against the N-terminus of PLSCR1 in vitro and in vivo. We also investigated cell cycle status and epidermal growth factor receptor–related pathways and downstream effectors of PLSCR1 after blocking its function with NP1.

Results

Treating CRC cells with NP1 in vitro and in vivo decreased cell proliferation, anchorage-independent growth, migration, and invasion. Adding NP1 to the CRC cell line HT29 caused arrest at G1/S. Treating HT29 cells with NP1 significantly decreased the expression of cyclin D1 and phosphorylation levels of Src, the adaptor protein Shc, and Erks. The reduced level of cyclin D1 led to an increase in the activated form of the tumor suppressor retinoblastoma protein via dephosphorylation. These actions led to attenuation of tumorigenesis.

Conclusions

Therefore, PLSCR1 may serve as a potential therapeutic target for CRC.

Proteome profiling of tolbutamide-treated rat primary hepatocytes using nano LC-MS/MS and label-free protein quantitation

Tolbutamide is used as a first line oral antihyperglycemic drug for type 2 diabetes. One side effect of this drug, hepatotoxicity, is well recognized; however, the precise mechanisms underlying tolbutamide-induced hepatotoxicity remain unclear. In this respect, proteomics techniques were used to gain further insight into the mechanistic processes of the hepatotoxicity induced by this drug. In this study, we aimed to identify molecular pathways based on proteins responding to cellular toxicity in tolbutamide-treated primary hepatocytes, using nano UPLC-MS/MS analysis. Rat primary hepatocytes were treated with an IC(20) concentration for 24 h to study the hepatotoxic effects of tolbutamide. For high-throughput label-free quantitation, tryptic-digested peptides of proteins from cell lysates were analyzed using LC-MS/MS and quantitated using the IDEAL-Q software, in which several parameters, such as assisted sequence, elution time, and mass-to-charge ratio were included. We quantified a total of 330 distinct proteins from the tolbutamide-treated hepatocytes and identified 55 upregulated and 82 downregulated proteins with expression changes. Among these differentially expressed proteins, we focused mainly on the 18 upregulated proteins belonging to xenobiotic cytochrome P450 (CYP), drug metabolism/detoxification, oxidative stress/antioxidant response, and cell damage pathway. CYP2D1, CYP2C11, UDP-glucuronosyltransferase 2B (UGT2B), superoxide dismutase 2 (SOD2), 60 kDa heat shock protein (HSPD1), heat shock protein 90 (HSP90), and catalase (CAT) were confirmed by Western blot analysis. In addition, various xenobiotic CYP proteins upregulated in the tolbutamide-treated group, CYP2D1, CYP2C13, and CYP2C11 were confirmed by reverse transcriptase-PCR analysis. Our results offer important new insights into the molecular mechanisms of tolbutamide-induced hepatotoxicity.

Secretomic analysis identifies alpha-1 antitrypsin (A1AT) as a required protein in cancer cell migration, invasion, and pericellular fibronectin assembly for facilitating lung colonization of lung adenocarcinoma cells

Metastasis is a major obstacle that must be overcome for the successful treatment of lung cancer. Proteins secreted by cancer cells may facilitate the progression of metastasis, particularly within the phases of migration and invasion. To discover metastasis-promoting secretory proteins within cancer cells, we used the label-free quantitative proteomics approach and compared the secretomes from the lung adenocarcinoma cell lines CL1-0 and CL1-5, which exhibit low and high metastatic properties, respectively. By employing quantitative analyses, we identified 660 proteins, 68 of which were considered to be expressed at different levels between the two cell lines. High levels of A1AT were secreted by CL1-5, and the roles of A1AT in the influence of lung adenocarcinoma metastasis were investigated. Molecular and pathological confirmation demonstrated that altered expression of A1AT correlates with the metastatic potential of lung adenocarcinoma. The migration and invasion properties of CL1-5 cells were significantly diminished by reducing the expression and secretion of their A1AT proteins. Conversely, the migration and invasion properties of CL1-0 cells were significantly increased through the overexpression and secretion of A1AT proteins. Furthermore, the assembly levels of the metastasis-promoting pericellular fibronectin (FN1), which facilitates colonization of lung capillary endothelia by adhering to the cell surface receptor dipeptidyl peptidase IV (DPP IV), were higher on the surfaces of suspended CL1-5 cells than on those of the CL1-0 cells. This discovery reflects previous findings in breast cancer. In line with this finding, FN1 assembly and the lung colonization of suspended CL1-5 cells were inhibited when endogenous A1AT protein was knocked down using siRNA. The major thrust of this study is to demonstrate the effects of coupling the label-free proteomics strategy with the secretomes of cancer cells that differentially exhibit invasive and metastatic properties. This provides a new opportunity for the effective identification of metastasis-associated proteins that are secreted by cancer cells and promote experimental metastasis.

Strategy for SRM-based verification of biomarker candidates discovered by iTRAQ method in limited breast cancer tissue samples

Since LC-MS-based quantitative proteomics has become increasingly applied to a wide range of biological applications over the past decade, numerous studies have performed relative and/or absolute abundance determinations across large sets of proteins. In this study, we discovered prognostic biomarker candidates from limited breast cancer tissue samples using discovery-through-verification strategy combining iTRAQ method followed by selected reaction monitoring/multiple reaction monitoring analysis (SRM/MRM). We identified and quantified 5122 proteins with high confidence in 18 patient tissue samples (pooled high-risk (n=9) or low-risk (n=9)). A total of 2480 proteins (48.4%) of them were annotated as membrane proteins, 16.1% were plasma membrane and 6.6% were extracellular space proteins by Gene Ontology analysis. Forty-nine proteins with >2-fold differences in two groups were chosen for further analysis and verified in 16 individual tissue samples (high-risk (n=9) or low-risk (n=7)) using SRM/MRM. Twenty-three proteins were differentially expressed among two groups of which MFAP4 and GP2 were further confirmed by Western blotting in 17 tissue samples (high-risk (n=9) or low-risk (n=8)) and Immunohistochemistry (IHC) in 24 tissue samples (high-risk (n=12) or low-risk (n=12)). These results indicate that the combination of iTRAQ and SRM/MRM proteomics will be a powerful tool for identification and verification of candidate protein biomarkers.

Proteomic approach reveals FKBP4 and S100A9 as potential prediction markers of therapeutic response to neoadjuvant chemotherapy in patients with breast cancer

Although doxorubicin (Doxo) and docetaxel (Docet) in combination are widely used in treatment regimens for a broad spectrum of breast cancer patients, a major obstacle has emerged in that some patients are intrinsically resistant to these chemotherapeutics. Our study aimed to discover potential prediction markers of drug resistance in needle-biopsied tissues of breast cancer patients prior to neoadjuvant chemotherapy. Tissues collected before chemotherapy were analyzed by mass spectrometry. A total of 2,331 proteins were identified and comparatively quantified between drug sensitive (DS) and drug resistant (DR) patient groups by spectral count. Of them, 298 proteins were differentially expressed by more than 1.5-fold. Some of the differentially expressed proteins (DEPs) were further confirmed by Western blotting. Bioinformatic analysis revealed that the DEPs were largely associated with drug metabolism, acute phase response signaling, and fatty acid elongation in mitochondria. Clinical validation of two selected proteins by immunohistochemistry found that FKBP4 and S100A9 might be putative prediction markers in discriminating the DR group from the DS group of breast cancer patients. The results demonstrate that a quantitative proteomics/bioinformatics approach is useful for discovering prediction markers of drug resistance, and possibly for the development of a new therapeutic strategy.

In-depth identification of pathways related to cisplatin-induced hepatotoxicity through an integrative method based on an informatics-assisted label-free protein quantitation and microarray gene expression approach

Cisplatin is used widely for treatment of a variety of cancer diseases. Recently, however, the use of cisplatin is restricted because of its adverse effects such as hepatotoxicity. There is no study with current proteomics technology to evaluate cisplatin-induced hepatotoxicity, even if some studies have reported on the hepatotoxicity. In this study, proteomic as well as genomic analyses have been used for identification of proteins and genes that respond to cisplatin treatment in rat primary hepatocytes. To investigate the hepatotoxic effects of cisplatin, rat primary hepatocytes were treated with an IC(20) concentration for 24 h. From proteomic analysis based on label-free quantitation strategy, cisplatin induced 76 up-regulated and 19 down-regulated proteins among 325 distinct proteins. In the mRNA level, genomic analysis revealed 72 up-regulated and 385 down-regulated genes in the cisplatin-treated group. Based on these two analyses, 19 pathways were commonly altered, whereas seven pathways were identified only by proteomic analysis, and 19 pathways were identified only by genomic analysis. Overall, this study explained the mechanism of cisplatin-induced hepatotoxicity with two points of view: well known pathways including drug metabolism, fatty acid metabolism, and glycolysis/TCA cycle and little known pathways including urea cycle and inflammation metabolism, for hepatotoxicity of other toxic agents. Up-regulated proteins detected by proteomic analysis in the cisplatin-treated group: FBP1 (fructose 1,6-bisphosphatase 1), FASN (fatty acid synthase), CAT (catalase), PRDX1 (peroxiredoxin-1), HSPD1 (60-kDa heat shock protein), MDH2 (malate dehydrogenase 2), and ARG1 (arginase 1), and also down-regulated proteins in the cisplatin-treated group: TPM1 (tropomyosin 1), TPM3 (tropomyosin 3), and CTSB (cathepsin B), were confirmed by Western blot analysis. In addition, up-regulated mRNAs detected by microarray analysis in the cisplatin-treated group: GSTA2, GSTT2, YC2, TXNRD1, CYP2E1, CYP2C13, CYP2D1, ALDH17, ARG1, ARG2, and IL-6, and also down-regulated mRNAs: CYP2C12, CYP26B1, TPM1, and TPM3, were confirmed by RT-PCR analysis. In case of PRDX1, FASN, and ARG1, they were further confirmed by immunofluorescence analysis. Through the integrated proteomic and genomic approaches, the present study provides the first pathway map related to cisplatin-induced hepatotoxicity, which may provide new insight into the mechanism of hepatotoxicity.

Detection of autoantibodies against Rabphilin-3A-like protein as a potential biomarker in patient's sera of colorectal cancer

BACKGROUND

Rabphilin-3A-like (RPH3AL) protein functions in the regulation of hormone exocytosis, and mutations in the RPHA3L gene have been associated with tumorigenesis in colorectal cancer (CRC). We evaluated the potential use of anti-RPH3AL autoantibodies as a marker for CRC detection.

METHODS

Sera from 84 patients with CRC and 63 healthy controls were analysed for the presence of RPH3AL autoantibodies with a Western blotting assay.

RESULTS

The frequencies of RPH3AL autoantibodies in the early stage, advanced stage and all CRC patients were 64.7%, 78.0% and 72.6%, respectively. These values are significantly higher than the frequency of RPH3AL autoantibodies in healthy controls (15.9%, P<0.001). Although the presence of RPH3AL autoantibodies did not correlate with clinical parameters, RPH3AL autoantibodies were found in 69.4% (34/49) of CRC patients who were negative for carcinoembryonic antigen. The value of the area under the receiver operating characteristic curve of RPH3AL autoantibody was 0.84, which suggests that screening for these autoantibodies could potentially be used for CRC diagnosis.

CONCLUSION

Circulating RPH3AL autoantibodies are prevalent in patients with CRC, and detection of these autoantibodies might provide a novel non-invasive approach for CRC diagnosis.