Tissue proteomics in pancreatic cancer study: discovery, emerging technologies, and challenges

The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

Identification of differentially expressed proteins in the locoregional recurrent esophageal squamous cell carcinoma by quantitative proteomics

Background

This study aimed to identify potential biomarkers associated with locoregional recurrence in patients with esophageal squamous cell carcinoma (ESCC) after radical resection.

Methods

We performed a quantitative proteomics analysis using isobaric tags for relative and absolute quantification (iTRAQ) with reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) to identify differential expression proteins (DEPs) between a locoregional recurrence group and good prognosis group of ESCC after radical esophagectomy. The bioinformatics analysis was performed with ingenuity pathway analysis software (IPA) and Gene Ontology (GO) database using the software of MAS 3.0. Kaplan-Meier (KM) Plotter Online Tool (http://www.kmplot.com) was used to evaluate the relationship between the differential expression of proteins and survival in patients with ESCC.

Results

More than 400 proteins were quantitated of which 27 proteins had upregulated expression and 55 proteins had downregulated expression in the locoregional recurrence group compared to the good prognosis group. These 82 DEPs were associated with biological procession of cancer development including cellular movement, cellular assembly and organization, cellular function and maintenance, cellular growth and proliferation, cell death and survival, DNA replication recombination and repair, and so on. Of these DEPs, SPTAN1 and AGT proteins were identified to be associated with RFS in ESCC. SPTAN1 was positively associated with RFS and AGT was negatively associated with RFS. Expression of SPTAN1 tended to have favorable OS while expression of AGT tended to have poor OS.

Conclusions

Our results demonstrated that quantitative proteomics is an effective discovery tool to identify biomarkers for prognosis prediction in ESCC. However, it needs more studies with large populations of ESCC to validate these potential biomarkers.

Integrated proteomics and phosphoproteomics reveal perturbed regulative pathways in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis largely owing to its inefficient diagnosis, rapid progress, and tenacious drug resistance. Here, we aimed to analyze the expressive patterns of proteins and phosphorylation in PDAC tissue samples and compare them to normal pancreatic tissue to investigate the underlying mechanisms and to reveal potential protein targets for diagnosis and drug development. Liquid chromatography coupled to mass spectrometry (LC-MS) based proteomics and phosphoproteomics analyses were performed using 20 pairs of patient-derived PDAC tissue and normal pancreatic tissue samples. Protein identification and quantification were conducted using MaxQuant software. Bioinformatics analysis was used to retrieve PDAC-relevant pathways and gene ontology (GO) terms. 4985 proteins and 3643 phosphoproteins were identified with high confidence; of these, 322 proteins and 235 phosphoproteins were dysregulated in PDAC. Several pathways, including several extracellular matrix-related pathways, were found to be strongly associated with PDAC. Further, the expression levels of filamin A (FLNA), integrin alpha-V (ITGAV), thymidine phosphorylase (TYMP), medium-chain specific acyl-CoA dehydrogenase, mitochondrial (ACADM), short-chain specific acyl-CoA dehydrogenase, mitochondrial (ACADS), and acetyl-CoA acetyltransferase, mitochondrial (ACAT1) were examined through western blot and immunohistochemistry analysis, and the results confirmed the validity of the proteomics analysis results. These findings provide comprehensive insight into the dysregulated regulative networks in PDAC tissue samples at the protein and phosphorylation levels, and they provide clues for further pathological studies and drug-target development.

Stromal expression of hemopexin is associated with lymph-node metastasis in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most aggressive types of cancer. Certain proteins in the tumor microenvironment have attracted considerable attention owing to their association with tumor invasion and metastasis. Here, we used proteomics to identify proteins associated with lymph-node metastasis, which is one of the prognostic factors. We selected lymph node metastasis-positive and -negative patients (n = 5 each) who underwent pancreatectomy between 2005 and 2015 and subjected to comprehensive proteomic profiling of tumor stroma. A total of 490 proteins were detected by mass spectrometry. Software analysis revealed that nine of these proteins were differentially expressed between the two patient groups. We focused on hemopexin and ferritin light chain based on immunohistochemistry results. We assessed the clinicopathological data of 163 patients and found that hemopexin expression was associated with UICC N2 (p = 0.0399), lymph node ratio (p = 0.0252), venous invasion (p = 0.0096), and lymphatic invasion (p = 0.0232). Notably, in vitro assays showed that hemopexin promotes invasion of the pancreatic cancer cells. Our findings suggest that hemopexin is a lymph node metastasis-associated protein that could potentially serve as a useful therapeutic target or biomarker of pancreatic ductal adenocarcinoma.

A Comparative Analysis of Tumors and Plasma Circulating Tumor DNA in 145 Advanced Cancer Patients Annotated by 3 Core Cellular Processes

Matched-targeted and immune checkpoint therapies have improved survival in cancer patients, but tumor heterogeneity contributes to drug resistance. Our study categorized gene mutations from next generation sequencing (NGS) into three core processes. This annotation helps decipher complex biologic interactions to guide therapy. We collected NGS data on 145 patients who have failed standard therapy (2016 to 2018). One hundred and forty two patients had data for tissue (Caris MI/X) and plasma cell-free circulating tumor DNA (Guardant360) platforms. The mutated genes were categorized into cell fate (CF), cell survival (CS), and genome maintenance (GM). Comparative analysis was performed for concordance and discordance, unclassified mutations, trends in TP53 alterations, and PD-L1 expression. Two gene mutation maps were generated to compare each NGS platform. Mutated genes predominantly matched to CS with concordance between Guardant360 (64.4%) and Caris (51.5%). TP53 alterations comprised a significant proportion of the mutation pool in Caris and Guardant360, 14.7% and 13.1%, respectively. Twenty-six potentially actionable gene alterations were detected from matching ctDNA to Caris unclassified alterations. The CS core cellular process was the most prevalent in our study population. Clinical trials are warranted to investigate biomarkers for the three core cellular processes in advanced cancer patients to define the next best therapies.

Proteome alterations in pancreatic ductal adenocarcinoma

Proteins are the essential functional biomolecules profoundly implicated in all aspects of pancreatic tumorigenesis and its progression. While common genomic factors, such as KRAS, TP53, SMAD4, and CDKN2A have been well recognized in association of pancreatic ductal adenocarcinoma (PDAC), our understanding of functional changes at the proteome level merits further investigation. Malignance associated proteome alterations can be attributed to the convoluted outcomes from genetic, epigenetic and environmental factors in initiating and progressing PDAC, and may reflect on changes in protein expressional level, structure, localization, as well as post-translational modifications (PTMs) status. The study of localized or systemic proteome alterations in PDAC, as well as its precursor lesions, such as pancreatic intraepithelial neoplasia (PanIN) and mucinous pancreatic cystic neoplasm, would provide unique perspectives in elucidating functional molecular events underlying PDAC. While efforts have been made, challenges still exist to comprehensively integrate much of the proteomic discovery to the perspectives gained from genomic studies in the context of biomarker discovery. Novel approaches and data from well-defined longitudinal clinical studies and experimental models are needed to facilitate the study of PDAC and precursor lesions for early detection and intervention.

Omics Approaches in Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal—around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.

Oncoproteomics: Current status and future opportunities

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.

Impact of proteomics investigations on gastric cancer treatment and diagnosis

Gastric cancer is one of the epidemics diseases with a high mortality rate in different countries. It causes many health problems in the world every year. It affects the digestive tract, and in advanced cases, its treatment has many difficulties. Early detection of cancer in different parts of the gastrointestinal tract can be accompanied by inexpensive treatment. As cancer cells make different biomarkers during different stages of the disease, researchers are looking for different biomarkers for gastrointestinal cancers detection. On the other hand, with the advent of advanced techniques such as proteomics and the discovery of a large number of proteins related to gastrointestinal cancer, finding the role of these proteins is essential. Indeed, the function of large amounts of these proteins has remained unknown. Data from databases such as genes and proteins associated with gastrointestinal cancers were collected and the proteomic data of these databases were analyzed to find a clear perspective of the impact of proteomics in gastric cancer management. The role of heat shock proteins, metabolic proteins, membrane binding proteins, galectins, prohibitins, S100 proteins, and many different types of proteins in gastric cancer was highlighted. This article reviewed proteomic researches in cancer-related areas of the gastric cancer in order to evaluate the findings of researchers.

Proteomics Profiling of Pancreatic Cancer and Pancreatitis for Biomarkers Discovery

Pancreatic cancer is one of the most aggressive malignancies with an increase in incidence predicted, particularly in African Americans. Pancreatic cancer is considered a silent disease with poor prognosis and a lack of early biomarkers for detection. Proteomics has been applied in many diseases for identifying or discovering biomarkers. It has long been suggested that chronic pancreatitis may be a risk factor for developing pancreatic cancer. This study identified proteins that are altered in expression in pancreatic cancer and pancreatitis compared to normal using proteomic technology. Proteins were extracted from laser captured micro-dissected tissues and separated in 2-DPAGE and imaged. The protein profiles of pancreatic cancer and pancreatitis are similar but differed with the protein profile of normal adjacent tissues. Representative proteins, overexpressed in tumor and pancreatitis but not normal tissues, were excised from gels, subjected to in-gel digestion, and analyzed by MALDI-TOF mass spectrometry. Proteins identified included transferrin, ER-60 protein, proapolipoprotein, tropomyosin 1, alpha 1 actin precursor, ACTB protein, and gamma 2 propeptide, aldehyde dehydrogenase 1A1, pancreatic lipase and annexin A1. Several proteins, which were shown in pancreatic cancer, were also observed in pancreatitis samples. Understanding the role of these specific proteins and their mechanistic action will give insights into their involvement in pancreatic cancers.

A Comparative Quantitative LC-MS/MS Profiling Analysis of Human Pancreatic Adenocarcinoma, Adjacent-Normal Tissue, and Patient-Derived Tumour Xenografts

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers worldwide; it develops in a relatively symptom-free manner, leading to rapid disease progression and metastasis, leading to a 5-year survival rate of less than 5%. A lack of dependable diagnostic markers and rapid development of resistance to conventional therapies are among the problems associated with management of the disease. A better understanding of pancreatic tumour biology and discovery of new potential therapeutic targets are important goals in pancreatic cancer research. This study describes the comparative quantitative LC-MS/MS proteomic analysis of the membrane-enriched proteome of 10 human pancreatic ductal adenocarcinomas, 9 matched adjacent-normal pancreas and patient-derived xenografts (PDXs) in mice (10 at F1 generation and 10 F2). Quantitative label-free LC-MS/MS data analysis identified 129 proteins upregulated, and 109 downregulated, in PDAC, compared to adjacent-normal tissue. In this study, analysing peptide MS/MS data from the xenografts, great care was taken to distinguish species-specific peptides definitively derived from human sequences, or from mice, which could not be distinguished. The human-only peptides from the PDXs are of particular value, since only human tumour cells survive, and stromal cells are replaced during engraftment in the mouse; this list is, therefore, enriched in tumour-associated proteins, some of which might be potential therapeutic or diagnostic targets. Using human-specific sequences, 32 proteins were found to be upregulated, and 113 downregulated in PDX F1 tumours, compared to primary PDAC. Differential expression of CD55 between PDAC and normal pancreas, and expression across PDX generations, was confirmed by Western blotting. These data indicate the value of using PDX models in PDAC research. This study is the first comparative proteomic analysis of PDAC which employs PDX models to identify patient tumour cell-associated proteins, in an effort to find robust targets for therapeutic treatment of PDAC.

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.

Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

Chemical composition and the potential for proteomic transformation in cancer, hypoxia, and hyperosmotic stress

The changes of protein expression that are monitored in proteomic experiments are a type of biological transformation that also involves changes in chemical composition. Accompanying the myriad molecular-level interactions that underlie any proteomic transformation, there is an overall thermodynamic potential that is sensitive to microenvironmental conditions, including local oxidation and hydration potential. Here, up- and down-expressed proteins identified in 71 comparative proteomics studies were analyzed using the average oxidation state of carbon (Z_C) and water demand per residue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O), calculated using elemental abundances and stoichiometric reactions to form proteins from basis species. Experimental lowering of oxygen availability (hypoxia) or water activity (hyperosmotic stress) generally results in decreased Z_C or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O of up-expressed compared to down-expressed proteins. This correspondence of chemical composition with experimental conditions provides evidence for attraction of the proteomes to a low-energy state. An opposite compositional change, toward higher average oxidation or hydration state, is found for proteomic transformations in colorectal and pancreatic cancer, and in two experiments for adipose-derived stem cells. Calculations of chemical affinity were used to estimate the thermodynamic potentials for proteomic transformations as a function of fugacity of O₂ and activity of H₂O, which serve as scales of oxidation and hydration potential. Diagrams summarizing the relative potential for formation of up- and down-expressed proteins have predicted equipotential lines that cluster around particular values of oxygen fugacity and water activity for similar datasets. The changes in chemical composition of proteomes are likely linked with reactions among other cellular molecules. A redox balance calculation indicates that an increase in the lipid to protein ratio in cancer cells by 20% over hypoxic cells would generate a large enough electron sink for oxidation of the cancer proteomes. The datasets and computer code used here are made available in a new R package, canprot.

Proteomic strategies in the search for novel pancreatic cancer biomarkers and drug targets: recent advances and clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers; despite a low incidence rate it is the fourth leading cause of cancer-related death in the world. Improvement of the diagnosis, prognosis and treatment remains the main focus of pancreatic cancer research. Rapid developments in proteomic technologies has improved our understanding of the pancreatic cancer proteome. Here, the authors summarise the recent proteomic strategies undertaken in the search for: novel biomarkers for early diagnosis, pancreatic cancer-specific proteins which may be used for novel targeted therapies and proteins which may be useful for monitoring disease progression post-therapy. Recent advances and findings discussed here provide great promise of having a significant clinical impact and improving the outcome of patients with this malignancy.

Glycoproteins and glycoproteomics in pancreatic cancer

Aberrations in protein glycosylation and polysaccharides play a pivotal role in pancreatic tumorigenesis, influencing cancer progression, metastasis, immuno-response and chemoresistance. Abnormal expression in sugar moieties can impact the function of various glycoproteins, including mucins, surface receptors, adhesive proteins, proteoglycans, as well as their effectors and binding ligands, resulting in an increase in pancreatic cancer invasiveness and a cancer-favored microenvironment. Recent advance in glycoproteomics, glycomics and other chemical biology techniques have been employed to better understand the complex mechanism of glycosylation events and how they orchestrate molecular activities in genomics, proteomics and metabolomics implicated in pancreatic adenocarcinoma. A variety of strategies have been demonstrated targeting protein glycosylation and polysaccharides for diagnostic and therapeutic development.

Mining the Human Proteome: Biomarker Discovery for Human Cancer and Metastases

As our knowledge of the mechanisms underlying cancer development and progression has increased, so too have more effective, less toxic, and targeted therapies begun to reach the clinic. However, the full impact of these clinical advances and the practical success of the emerging field of precision medicine are dependent on the discovery and validation of sensitive and accurate biomarkers that can enable appropriate and rigorous sample type and patient selection, reliable longitudinal monitoring of therapeutic efficacy, and even risk assessment and early detection. Within the context of this review, we examine state-of-the-art approaches to the discovery and validation of noninvasive cancer biomarkers, with a specific emphasis on those that are protein or protein-associated ones. We also review sample selection strategies, currently utilized proteomic approaches for both discovery and validation requirements, and data analysis standards. Finally, we provide examples of these elements of biomarker discovery and validation from our own biomarker research.

Differential Proteomic Analysis of Human Saliva using Tandem Mass Tags Quantification for Gastric Cancer Detection

Novel biomarkers and non-invasive diagnostic methods are urgently needed for the screening of gastric cancer to reduce its high mortality. We employed quantitative proteomics approach to develop discriminatory biomarker signatures from human saliva for the detection of gastric cancer. Salivary proteins were analyzed and compared between gastric cancer patients and matched control subjects by using tandem mass tags (TMT) technology. More than 500 proteins were identified with quantification, and 48 of them showed significant difference expression (p < 0.05) between normal controls and gastric cancer patients, including 7 up-regulated proteins and 41 down-regulated proteins. Five proteins were selected for initial verification by ELISA and three were successfully verified, namely cystatin B (CSTB), triosephosphate isomerase (TPI1), and deleted in malignant brain tumors 1 protein (DMBT1). All three proteins could differentiate gastric cancer patients from normal control subjects, dramatically (p < 0.05). The combination of these three biomarkers could reach 85% sensitivity and 80% specificity for the detection of gastric cancer with accuracy of 0.93. This study provides the proof of concept of salivary biomarkers for the non-invasive detection of gastric cancer. It is highly encouraging to turn these biomarkers into an applicable clinical test after large scale validation.

Molecular detection of pancreatic neoplasia: Current status and future promise

Pancreatic cancer is usually diagnosed at an advanced stage and curative resection is feasible in only a small minority of patients at the time of diagnosis. Diagnosis at an early stage is unequivocally associated with better long-term survival. Several candidate molecular markers for early detection are currently under investigation in different phases of discovery and validation. Recent advances in the technology for whole genome, methylome, ribonucleome, and proteome interrogation has enabled rapid advancements in the field of biomarker discovery. In this review we discuss the current status of molecular markers for detection of pancreatic cancer in blood, pancreatic cyst fluid, pancreatic juice and stool and briefly highlight some promising preliminary results of new approaches that have the potential of advancing this field in the near future.

Proteomics analysis of bodily fluids in pancreatic cancer

Proteomics study of pancreatic cancer using bodily fluids emphasizes biomarker discovery and clinical application, presenting unique prospect and challenges. Depending on the physiological nature of the bodily fluid and its proximity to pancreatic cancer, the proteomes of bodily fluids, such as pancreatic juice, pancreatic cyst fluid, blood, bile, and urine, can be substantially different in terms of protein constitution and the dynamic range of protein concentration. Thus, a comprehensive discovery and specific detection of cancer-associated proteins within these varied fluids is a complex task, requiring rigorous experiment design and a concerted approach. While major challenges still remain, fluid proteomics studies in pancreatic cancer to date have provided a wealth of information in revealing proteome alterations associated with pancreatic cancer in various bodily fluids.

The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science

In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment.

Proteomic identification of potential prognostic biomarkers in resectable pancreatic ductal adenocarcinoma

Pancreatic cancer is a devastating disease with a mortality rate almost identical with its incidence. In this context, the investigation of the pancreatic cancer proteome has gained considerable attention because profiles of proteins may be able to identify disease states and progression more accurately. Therefore, our objective was to investigate the changes in the proteome of patients suffering from pancreatic ductal adenocarcinoma (PDAC) by a comprehensive quantitative approach. Comparative proteomic profiling by label-free LC-MS/MS analysis of nine matched pairs of tumor and nontumor pancreas samples was used to identify differences in protein levels characteristic for PDAC. In this analysis, 488 proteins were quantified by at least two peptides of which 99 proteins displayed altered levels in PDAC (p < 0.01, fold change >1.3). Screening of data revealed a number of molecules that had already been related to PDAC such as galectin-1 (LEG1), major vault protein, adenylyl cyclase-associated protein 1 (CAP1), but also a potential new prognostic biomarker prolargin (PRELP). The Kaplan-Meier survival analysis revealed a significant correlation of protein abundance of PRELP with postoperative survival of patients with PDAC. For selected proteins the findings were verified by targeted proteomics (SRM), validated by immunohistochemistry and Western blotting and their value as candidate biomarkers is discussed.

Biomarkers for pancreatic cancer: promising new markers and options beyond CA 19-9

Pancreatic adenocarcinoma accounts for nearly 90-95% of exocrine malignant tumors of the pancreas. Traditionally, overexpressed proteins/epitopes such as CA 19-9, CA-50, CEA, and many others were being used as pancreatic cancer tumor markers. The main utility of these biomarkers was in the diagnosis of pancreatic cancer as well as to assess response to chemotherapy and to determine prognosis and to predict tumor recurrence. However, these markers had significant limitations such as lack of sensitivity, false-negative results in certain blood groups, as well as false-positive elevation in the presence of obstructive jaundice. To circumvent these limitations, an extraordinary amount of research is being performed to identify an accurate tumor marker or a panel of markers that could aid in the management of the pancreatic cancer. Although this research has identified a large number and different variety of biomarkers, few hold future promise as a preferred marker for pancreatic cancer. This review provides an insight into exciting new areas of pancreatic biomarker research such as salivary, pancreatic juice, and stool markers that can be used as a noninvasive test to identify pancreatic cancer. This manuscript also provides a discussion on newer biomarkers, the role of microRNAs, and pancreatic cancer proteomics, which have the potential to identify a preferred tumor marker for pancreatic adenocarcinoma. This review further elaborates on important genetic changes associated with the development and progression of pancreatic cancer that holds the key for the identification of a sensitive biomarker and which could also serve as a therapeutic target.

Cancer metabolism and mass spectrometry-based proteomics

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

Altered sphingolipid metabolism in patients with metastatic pancreatic cancer

Although numerous genetic mutations and amplifications have been identified in pancreatic cancer, much of the molecular pathogenesis of the disease remains undefined. While proteomic and transcriptomic analyses have been utilized to probe and characterize pancreatic tumors, lipidomic analyses have not been applied to identify perturbations in pancreatic cancer patient samples. Thus, we utilized a mass spectrometry-based lipidomic approach, focused towards the sphingolipid class of lipids, to quantify changes in human pancreatic cancer tumor and plasma specimens. Subgroup analysis revealed that patients with positive lymph node metastasis have a markedly higher level of ceramide species (C16:0 and C24:1) in their tumor specimens compared to pancreatic cancer patients without nodal disease or to patients with pancreatitis. Also of interest, ceramide metabolites, including phosphorylated (sphingosine- and sphinganine-1-phosphate) and glycosylated (cerebroside) species were elevated in the plasma, but not the pancreas, of pancreatic cancer patients with nodal disease. Analysis of plasma level of cytokine and growth factors revealed that IL-6, IL-8, CCL11 (eotaxin), EGF and IP10 (interferon inducible protein 10, CXCL10) were elevated in patients with positive lymph nodes metastasis, but that only IP10 and EGF directly correlated with several sphingolipid changes. Taken together, these data indicate that sphingolipid metabolism is altered in human pancreatic cancer and associated with advanced disease. Assessing plasma and/or tissue sphingolipids could potentially risk stratify patients in the clinical setting.

Quantitative proteomic analysis of differentially expressed proteins in pancreatic cancer stem cells

AIM: To screen and identify differentially expressed proteins in pancreatic cancer stem cells.

METHODS: MIA-PaCa2 (TIC^high) and BxPc-3 (TIC^low) were used in the study. Differentially expressed proteins between MIA-PaCa2 (TIC^high) and BxPc-3 (TI^Clow) cells were isolated and screened by 2D-DIGE analysis. Protein identification was performed by peptide mass fingerprinting with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/TOF). Western blot was performed to verify the differential expression of TRIM28.

RESULTS: Fluorescent differential protein expression patterns were obtained between MIA-PaCa2 (TIC^high) and BxPc-3 (TIC^low) cells. Analyses with DeCyder v6.5 software showed a total of 23 differentially expressed protein spots (>1.5 folds), and these protein spots were identified by mass spectrometry as 19 proteins, which are involved in cell communication and signal transduction, immune response, transcription and cell cycle regulation, adipocyte differentiation and lipid droplet formation, cytoskeletal formation, cell adhesion, transport, and translation. Western blot analysis revealed that TRIM28 was highly expressed in MIA-PaCa2 (TIC^high) cells but not expressed in BxPc-3 (TIC^low) cells. Among the 19 identified proteins, 8 were up-regulated and 11 down-regulated in MIA-PaCa2 (TIC^high) cells.

CONCLUSION: The identified differentially expressed proteins, such as TRIM28, are associated with the genesis, development and regulation of pancreatic cancer stem cells. They may become new therapeutic targets for pancreatic cancer.