Proteomic identification of potential prognostic biomarkers in resectable pancreatic ductal adenocarcinoma

Correlation of the tumor escape phenotype with loss of PRELP expression in melanoma

BACKGROUND

Despite immunotherapies having revolutionized the treatment of advanced cutaneous melanoma, effective and durable responses were only reported in a few patients. A better understanding of the interaction of melanoma cells with the microenvironment, including extracellular matrix (ECM) components, might provide novel therapeutic options. Although the ECM has been linked to several hallmarks of cancer, little information is available regarding the expression and function of the ECM protein purine-arginine-rich and leucine-rich protein (PRELP) in cancer, including melanoma.

METHODS

The structural integrity, expression and function of PRELP, its correlation with the expression of immune modulatory molecules, immune cell infiltration and clinical parameters were determined using standard methods and/or bioinformatics.

RESULTS

Bioinformatics analysis revealed a heterogeneous, but statistically significant reduced PRELP expression in available datasets of skin cutaneous melanoma when compared to adjacent normal tissues, which was associated with reduced patients' survival, low expression levels of components of the MHC class I antigen processing machinery (APM) and interferon (IFN)-γ signal transduction pathway, but increased expression of the transforming growth factor (TGF)-β isoform 1 (TFGB1) and TGF-β receptor 1 (TGFBR1). In addition, a high frequency of intra-tumoral T cells directly correlated with the expression of MHC class I and PRELP as well as the T cell attractant CCL5 in melanoma lesions. Marginal to low PRELP expression levels were found in the 47/49 human melanoma cell lines analysis. Transfection of PRELP into melanoma cell lines restored MHC class I surface expression due to transcriptional upregulation of major MHC class I APM and IFN-γ pathway components. In addition, PRELP overexpression is accompanied by high CCL5 secretion levels in cell supernatant, an impaired TGF-β signaling as well as a reduced cell proliferation, migration and invasion of melanoma cells.

CONCLUSIONS

Our findings suggest that PRELP induces the expression of MHC class I and CCL5 in melanoma, which might be involved in an enhanced T cell recruitment and immunogenicity associated with an improved patients' outcome. Therefore, PRELP might serve as a marker for predicting disease progression and its recovery could revert the tumorigenic phenotype, which represents a novel therapeutic option for melanoma.

Proteogenomic insights into the biology and treatment of pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with poor prognosis. Proteogenomic characterization and integrative proteomic analysis provide a functional context to annotate genomic abnormalities with prognostic value.

METHODS

We performed an integrated multi-omics analysis, including whole-exome sequencing, RNA-seq, proteomic, and phosphoproteomic analysis of 217 PDAC tumors with paired non-tumor adjacent tissues. In vivo functional experiments were performed to further illustrate the biological events related to PDAC tumorigenesis and progression.

RESULTS

A comprehensive proteogenomic landscape revealed that TP53 mutations upregulated the CDK4-mediated cell proliferation process and led to poor prognosis in younger patients. Integrative multi-omics analysis illustrated the proteomic and phosphoproteomic alteration led by genomic alterations such as KRAS mutations and ADAM9 amplification of PDAC tumorigenesis. Proteogenomic analysis combined with in vivo experiments revealed that the higher amplification frequency of ADAM9 (8p11.22) could drive PDAC metastasis, though downregulating adhesion junction and upregulating WNT signaling pathway. Proteome-based stratification of PDAC revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Immune clustering defined a metabolic tumor subset that harbored FH amplicons led to better prognosis. Functional experiments revealed the role of FH in altering tumor glycolysis and in impacting PDAC tumor microenvironments. Experiments utilizing both in vivo and in vitro assay proved that loss of HOGA1 promoted the tumor growth via activating LARP7-CDK1 pathway.

CONCLUSIONS

This proteogenomic dataset provided a valuable resource for researchers and clinicians seeking for better understanding and treatment of PDAC.

Proteomic Analysis Reveals Molecular Differences in the Development of Gastric Cancer

Gastric cancer (GC) is the 3rd leading cause of death from cancer and the 5th most common cancer worldwide. The detection rate of GC among Tibetans is significantly higher than that in Han Chinese, probably due to differences in their living habits, dietary structure, and environment. Despite such a high disease burden, the epidemiology of gastric cancer has not been studied in this population. Molecular markers are required to aid the diagnosis and treatment of GC. In this study, we collected gastric tissue samples from patients in Tibet with chronic nonatrophic gastritis (CNAG) (n = 6), chronic atrophic gastritis (CAG) (n = 7), gastric intraepithelial neoplasia (GIN) (n = 4), and GC (n = 5). The proteins in each group were analyzed using coupled label-free mass spectrometry. In addition, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein interaction networks were used to analyze the differentially expressed proteins (DEPs) among groups. DEPs were quantified in comparisons of GC versus CNAG (223), GC versus GIN (100), and GIN versus CNAG (341). GO and KEGG analyses showed that the DEPs were mainly associated with immunity (GC versus CNAG) and cancer proliferation and metastasis (GC versus GIN, and GIN versus CNAG). Furthermore, the expression levels of cell proliferation and cytoskeleton-related proteins increased consistently during cancer development, such as ITGA4, DDC, and CPT1A; thus, they are potential diagnostic markers. These results obtained by proteomics analysis could improve our understanding of cancer biology in GC and provide a rich resource for data mining and discovering potential immunotherapy targets.

Mechanistic interrogation of mutation-independent disease modulators of RDEB identifies the small leucine-rich proteoglycan PRELP as a TGF-β antagonist and inhibitor of fibrosis

Recessive dystrophic epidermolysis bullosa (RDEB) is a genetic extracellular matrix disease caused by deficiency in type VII collagen (Col VII). The disease manifests with devastating mucocutaneous fragility leading to progressive fibrosis and metastatic squamous cell carcinomas. Although collagen VII abundance is considered the main predictor of symptom course, previous studies have revealed the existence of mutation-independent mechanisms that control disease progression. Here, to investigate and validate new molecular modifiers of wound healing and fibrosis in a natural human setting, and toward development of disease-modulating treatment of RDEB, we performed gene expression profiling of primary fibroblast from RDEB siblings with marked phenotypic variations, despite having equal COL7A1 genotype. Gene enrichment analysis suggested that severe RDEB was associated with enhanced response to TGF-β stimulus, oxidoreductase activity, and cell contraction. Consistently, we found an increased response to TGF-β, higher levels of basal and induced reactive oxygen species (ROS), and greater contractile ability in collagen lattices in RDEB fibroblasts (RDEBFs) from donors with severe RDEB vs mild RDEB. Treatment with antioxidants allowed a reduction of the pro-fibrotic and contractile phenotype. Importantly, our analyses revealed higher expression and deposition in skin of the relatively uncharacterized small leucine-rich extracellular proteoglycan PRELP/prolargin associated with milder RDEB manifestations. Mechanistic investigations showed that PRELP effectively attenuated fibroblasts' response to TGF-β1 stimulus and cell contractile capacity. Moreover, PRELP overexpression in RDEBFs enhanced RDEB keratinocyte attachment to fibroblast-derived extracellular matrix in the absence of Col VII. Our results highlight the clinical relevance of pro-oxidant status and hyper-responsiveness to TGF-β in RDEB severity and progression. Of note, our study also reveals PRELP as a novel and natural TGF-β antagonist with a likely dermo-epidermal pro-adhesive capacity.

Current State of "Omics" Biomarkers in Pancreatic Cancer

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.

A Transcriptomics-Based Meta-Analysis Combined With Machine Learning Identifies a Secretory Biomarker Panel for Diagnosis of Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is generally incurable due to the late diagnosis and absence of markers that are concordant with expression in several sample sources (i.e., tissue, blood, plasma) and platforms (i.e., Microarray, sequencing). We optimized meta-analysis of 19 PDAC (tissue and blood) transcriptome studies from multiple platforms. The key biomarkers for PDAC diagnosis with secretory potential were identified and validated in different cohorts. Machine learning approach i.e., support vector machine supported by leave-one-out cross-validation was used to build and test the classifier. We identified a 9-gene panel (IFI27, ITGB5, CTSD, EFNA4, GGH, PLBD1, HTATIP2, IL1R2, CTSA) that achieved ∼0.92 average sensitivity and ∼0.90 average specificity in distinguishing PDAC from healthy samples in five training sets using cross-validation. These markers were also validated in proteomics and single-cell transcriptomics studies suggesting their prognostic role in the diagnosis of PDAC. Our 9-gene classifier can not only clearly discriminate between better and poor survivors but can also precisely discriminate PDAC from chronic pancreatitis (AUC = 0.95), early stages of progression [Stage I and II (AUC = 0.82), IPMA and IPMN (AUC = 1), and IPMC (AUC = 0.81)]. The 9-gene marker outperformed the previously known markers in blood studies particularly (AUC = 0.84). The discrimination of PDAC from early precursor lesions in non-malignant tissue (AUC > 0.81) and peripheral blood (AUC > 0.80) may assist in an early diagnosis of PDAC in blood samples and thus will also facilitate risk stratification upon validation in clinical trials.

PRELP has prognostic value and regulates cell proliferation and migration in hepatocellular carcinoma

Purpose: Hepatocellular carcinoma (HCC) is an aggressive and prevalent tumor threatening human health. A previous study suggested low PRELP (proline/arginine-rich end leucine-rich repeat protein) expression was associated with poor patient survival in pancreatic ductal adenocarcinoma (PDAC). However, the role of PRELP in HCC has not yet been illuminated. Methods: PRELP expression analyses were carried out using transcriptomic datasets from the Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB). The correlations between PRELP expression and clinicopathological features, and prognostic analyses were performed with a tissue microarray (TMA) and immunohistochemistry (IHC). The endogenous expression and in vitro roles of PRELP were investigated in cultured HCC cell lines. The potential mechanisms were characterized by a Gene Set Enrichment Analysis (GSEA) and gene-gene correlation analyses. Results: We found that PRELP mRNA expression was dramatically decreased in HCCs in comparison with that in adjacent normal tissues (NTs) or hepatic cirrhosis. IHC staining showed that PRELP was down-regulated in HCCs, which mainly located in cytoplasm, and was also found in nuclei. The correlation analyses revealed that PRELP expression was relevant to later p-stages (p= 0.028) and tumor size (p= 0.001). The overall survival (OS) and relapse free survival (RFS) time was shorter in HCC patients with lower PRELP expression levels than that with higher PRELP expression levels. Overexpression of PRELP inhibited, while knockdown of PRELP promoted proliferation and migration of HCC cells. For potential mechanisms, PRELP may inhibit progression of HCCs by interacting with integrin family members and the extracellular microenvironment. Conclusion: Our findings demonstrated that overexpression of PRELP correlates with better patient survival and inhibits both cell proliferation and migration in HCC. Therefore, PRELP can serve as a potential prognostic biomarker and therapeutic target which deserves further investigation.

Label-free proteomics reveals serum proteins whose levels differ between pancreatic ductal adenocarcinoma patients with short or long survival

Pancreatic ductal adenocarcinoma is the most common and aggressive type of pancreatic cancer, with a 5-year survival rate that is less than 10%. New biomarkers to aid in predicting the prognosis of pancreatic ductal adenocarcinoma patients are needed. Previous proteomic studies have to a great extent focused on finding proteins of value for the diagnosis of pancreatic ductal adenocarcinoma. There is a lack of studies that have profiled the serum or plasma proteome in order to discover candidates for new prognostic biomarkers. In this study, we have used ultra-performance liquid chromatography-ultra-definition mass spectrometry to analyze the serum samples of 21 pancreatic ductal adenocarcinoma patients with short or long survival. Statistical analysis discovered 31 proteins whose expression differed significantly between pancreatic ductal adenocarcinoma patients with short or long survival. Pathway analysis discovered multiple canonical pathways enriched in this data set, with several pathways having roles in inflammation and lipid metabolism. The serum proteins identified here, which include complement components and several enzymes, could be of value as candidates for new noninvasive prognostic markers.

Mitochondrial proteomics profile points oxidative phosphorylation as main target for beauvericin and enniatin B mixture

Beauvericin (BEA) and enniatin B (EN B) are non-legislated Fusarium mycotoxins usually found in cereal and cereal-based products all around the world. By the proteomic analysis of mitochondria enriched extracts from Jurkat cells exposed for 24 h to three concentrations of BEA:EN B (0.01-0.1-0.5 μM), a number of 1821 proteins (202 mitochondrial) were identified and relatively quantified. 340 proteins (59 mitochondrial) were statistically significant altered in our samples (Anova p-value ≤ 0.05 and fold change (FC) ≥1.5). The protein mitochondrial translational release factor 1 like (MTRF1L) was the most abundant protein in the three mycotoxin exposures studied. The mycotoxins mixture exposure induced concentration dependent changes at mitochondrial proteins levels that mainly involve inner and outer membrane complexes, Electron Transport Chain (ETC) and ribosomes. These results showed alteration of proteins levels related to oxidative phosphorylation, metabolic and neurodegenerative diseases related pathways.

An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

Proteomic analyses of ECM during pancreatic ductal adenocarcinoma progression reveal different contributions by tumor and stromal cells

Pancreatic ductal adenocarcinoma (PDAC) has prominent extracellular matrix (ECM) that compromises treatments yet cannot be nonselectively disrupted without adverse consequences. ECM of PDAC, despite the recognition of its importance, has not been comprehensively studied in patients. In this study, we used quantitative mass spectrometry (MS)-based proteomics to characterize ECM proteins in normal pancreas and pancreatic intraepithelial neoplasia (PanIN)- and PDAC-bearing pancreas from both human patients and mouse genetic models, as well as chronic pancreatitis patient samples. We describe detailed changes in both abundance and complexity of matrisome proteins in the course of PDAC progression. We reveal an early up-regulated group of matrisome proteins in PanIN, which are further up-regulated in PDAC, and we uncover notable similarities in matrix changes between pancreatitis and PDAC. We further assigned cellular origins to matrisome proteins by performing MS on multiple lines of human-to-mouse xenograft tumors. We found that, although stromal cells produce over 90% of the ECM mass, elevated levels of ECM proteins derived from the tumor cells, but not those produced exclusively by stromal cells, tend to correlate with poor patient survival. Furthermore, distinct pathways were implicated in regulating expression of matrisome proteins in cancer cells and stromal cells. We suggest that, rather than global suppression of ECM production, more precise ECM manipulations, such as targeting tumor-promoting ECM proteins and their regulators in cancer cells, could be more effective therapeutically.

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.

The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics"

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

Two Functionally Deviating Type 6 Secretion Systems Occur in the Nitrogen-Fixing Endophyte Azoarcus olearius BH72

Type VI protein secretion systems (T6SSs) have been identified in many plant-associated bacteria. However, despite the fact that effector proteins may modulate host responses or interbacterial competition, only a few have been functionally dissected in detail. We dissected the T6SS in Azoarcus olearius strain BH72, a nitrogen-fixing model endophyte of grasses. The genome harbors two gene clusters encoding putative T6SSs, tss-1 and tss-2, of which only T6SS-2 shared genetic organization and functional homology with the H1-T6SS of Pseudomonas aeruginosa. While tss-2 genes were constitutively expressed, tss-1 genes were strongly up-regulated under conditions of nitrogen fixation. A comparative analysis of the wild type and mutants lacking either functional tss-1 or tss-2 allowed to differentiate the functions of both secretion systems. Abundance of Hcp in the culture supernatant as an indication for T6SS activity revealed that only T6SS-2 was active, either under aerobic or nitrogen-fixing conditions. Our data show that T6SS-2 but not T6SS-1 is post-translationally regulated by phosphorylation mediated by TagE/TagG (PpkA/PppA), and by the phosphorylation-independent inhibitory protein TagF, similar to published work in Pseudomonas. Therefore, T6SS-1 appears to be post-translationally regulated by yet unknown mechanisms. Thus, both T6SS systems appear to perform different functions in Azoarcus, one of them specifically adapted to the nitrogen-fixing lifestyle.

The Expressional Pattern of Invasion-Related Extracellular Matrix Molecules in CNS Tumors

Aim of the study: Astrocytomas are primary CNS malignancies which infiltrate the peritumoral tissue, even when they are low-grade. Schwannomas are also primary CNS tumors, however, they do not show peritumoral infiltration similarly to brain metastases which almost never invade the neighboring parts of brain. Extracellular matrix is altered in composition in various cancer types and is proposed to play an important role in the development of invasiveness of astrocytic tumors. This study aims to identify differences in the ECM composition of CNS tumors with different invasiveness.Materials and methods: The mRNA and protein levels of ECM components were measured by QRT-PCR and mass-spectrometry, respectively, in grade II astrocytoma, NSCLC brain metastasis, schwannomas, and non-tumor brain control samples. Expressional data was analyzed statistically with ANOVA and nearest neighbor search.Results: There is a significant difference in the expressional pattern of invasion-related ECM components among various CNS tumors, especially among those of different embryonic origin. Non-invasive tumors show only slight differences in the expressional pattern of ECM molecules. Tumor samples can be separated based on their expressional pattern using statistical classifiers, therefore the ECM composition seems to be typical of various cancer types.Conclusions: Differences in the expressional pattern of the ECM could be responsible for the different invasiveness of various CNS tumors.

Label-Free Quantitative Proteomics Unravels Carboxypeptidases as the Novel Biomarker in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, with a high mortality rate and poor prognosis. However, little is known concerning the molecular mechanism of PDAC at the proteomics level. Here we report a proteomics analysis of PDAC tumor and adjacent tissues by shotgun proteomics followed by label-free quantification, and in total, 3031 and 3306 proteins were identified in three pairs of PDAC tumor and adjacent tissues, respectively; 40 of them were differentially expressed for at least three-fold in PDAC tumor tissues. Ontological and interaction network analysis highlighted the dysregulation of a set of four proteins in the carboxypeptidase family: carboxypeptidase A1 (CPA1), A2 (CPA2), B1 (CPB1), and chymotrypsin C (CTRC). Western blotting confirmed the downregulation of the carboxypeptidase network in PDAC. Immunohistochemistry of tissue microarray from 90 PDAC patients demonstrated that CPB1 was downregulated 7.07-fold (P < .0001, n = 81) in tumor comparing with the peritumor tissue. Further 208 pancreatic tissues from PDAC tumor, peritumor, and pancreatis confirmed the downregulation of CPB1 in the PDAC patients. In summary, our results displayed that the expression of carboxypeptidase is significantly downregulated in PDAC tumor tissues and may be novel biomarker in the patient with PDAC.

Recent advances in proteomic profiling of pancreatic ductal adenocarcinoma and the road ahead

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers worldwide. However, there remain many unmet clinical needs, from diagnosis to treatment strategies. The inherent complexity of the molecular characteristics of PDAC has made it difficult to meet these challenges, rendering proteomic profiling of PDAC a critical area of research. Area covered: In this review, we present recent advances in mass spectrometry (MS) and its current application in proteomic studies on PDAC. In addition, we discuss future directions for research that can efficiently incorporate current MS-based technologies that address key issues of PDAC proteomics. Expert commentary: Compared with other cancer studies, little progress has been made in PDAC proteomics, perhaps attributed to the difficulty in performing in-depth and large-scale clinical studies on PDAC. However, recent advances in mass spectrometry can advance PDAC proteomics past the fundamental research stage.

Contribution of galectin-1, a glycan-binding protein, to gastrointestinal tumor progression

Gastrointestinal cancer is a group of tumors that affect multiple sites of the digestive system, including the stomach, liver, colon and pancreas. These cancers are very aggressive and rapidly metastasize, thus identifying effective targets is crucial for treatment. Galectin-1 (Gal-1) belongs to a family of glycan-binding proteins, or lectins, with the ability to cross-link specific glycoconjugates. A variety of biological activities have been attributed to Gal-1 at different steps of tumor progression. Herein, we summarize the current literature regarding the roles of Gal-1 in gastrointestinal malignancies. Accumulating evidence shows that Gal-1 is drastically up-regulated in human gastric cancer, hepatocellular carcinoma, colorectal cancer and pancreatic ductal adenocarcinoma tissues, both in tumor epithelial and tumor-associated stromal cells. Moreover, Gal-1 makes a crucial contribution to the pathogenesis of gastrointestinal malignancies, favoring tumor development, aggressiveness, metastasis, immunosuppression and angiogenesis. We also highlight that alterations in Gal-1-specific glycoepitopes may be relevant for gastrointestinal cancer progression. Despite the findings obtained so far, further functional studies are still required. Elucidating the precise molecular mechanisms modulated by Gal-1 underlying gastrointestinal tumor progression, might lead to the development of novel Gal-1-based diagnostic methods and/or therapies.

Spectral library-based glycopeptide analysis-detection of circulating galectin-3 binding protein in pancreatic cancer

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease characterized by its late diagnosis, poor prognosis and rapid development of drug resistance. Using the data-independent acquisition (DIA) technique, the authors applied a spectral library-based proteomic approach to analyze N-glycosylated peptides in human plasma, in the context of pancreatic cancer study.

EXPERIMENTAL DESIGN

The authors extended the application of DIA to the quantification of N-glycosylated peptides enriched from plasma specimens from a clinically well-defined cohort that consists of patients with early stage PDAC, chronic pancreatitis and healthy subjects.

RESULTS

The analytical platform was evaluated in light of its robustness for quantitative analysis of large-scale clinical specimens. The authors analysis indicated that the level of N-glycosylated peptides derived from galectin-3 binding proteins (LGALS3BP) were frequently elevated in plasma from PDAC patients, concurrent with the altered N-glycosylation of LGALS3BP observed in the tumor tissue.

CONCLUSION AND CLINICAL RELEVANCE

The glycosylation form of LGALS3BP influences its function in the galectin network, which profoundly involves in cancer progression, immune response and drug resistance. As one of the major binding ligands of galectin network, discovery of site specific N-glycosylation changes of LGALS3BP in association of PDAC may provide useful clues to facilitate cancer detection or phenotype stratification.

Proteins Differentially Expressed in the Pancreas of Hepatic Alcohol Dehydrogenase-Deficient Deer Mice Fed Ethanol For 3 Months

OBJECTIVES

The aim of this study was to identify differentially expressed proteins in the pancreatic tissue of hepatic alcohol dehydrogenase-deficient deer mice fed ethanol to understand metabolic basis and mechanism of alcoholic chronic pancreatitis.

METHODS

Mice were fed liquid diet containing 3.5 g% ethanol daily for 3 months, and differentially expressed pancreatic proteins were identified by protein separation using 2-dimensional gel electrophoresis and identification by mass spectrometry.

RESULTS

Nineteen differentially expressed proteins were identified by applying criteria established for protein identification in proteomics. An increased abundance was found for ribosome-binding protein 1, 60S ribosomal protein L31-like isoform 1, histone 4, calcium, and adenosine triphosphate (ATP) binding proteins and the proteins involved in antiapoptotic processes and endoplasmic reticulum function, stress, and/or homeostasis. Low abundance was found for endoA cytokeratin, 40S ribosomal protein SA, amylase 2b isoform precursor, serum albumin, and ATP synthase subunit β and the proteins involved in cell motility, structure, and conformation.

CONCLUSIONS

Chronic ethanol feeding in alcohol dehydrogenase-deficient deer mice differentially expresses pancreatic functional and structural proteins, which can be used to develop biomarker(s) of alcoholic chronic pancreatitis, particularly amylase 2b precursor, and 60 kDa heat shock protein and those involved in ATP synthesis and blood osmotic pressure.

Potential prognostic biomarkers in pancreatic juice of resectable pancreatic ductal adenocarcinoma

Despite potentially curative surgery pancreatic cancer has a dismal prognosis. Serum cancer antigen 19-9 (CA 19-9) correlates with tumor burden, resectability and survival in patients with pancreatic ductal adenocarcinoma. Identification of novel biomarkers may facilitate early diagnosis of pancreatic cancer and improve survival. Pancreatic juice is a rich source of cancer-specific proteins rendering it a promising tool for identifying biomarkers. Recent proteomic and microRNA expression analyses have identified several biomarkers of potential diagnostic and prognostic value. Tumor markers CA 19-9 and carcinoembryonic antigen (CEA) are widely used in the characterization of premalignant and malignant lesions of the pancreas. Elevated level of CEA in bile is a marker for malignancy and a predictor of hepatic recurrence. The potential value of CA 19-9, CEA and lactate dehydrogenase as prognostic biomarkers in pancreatic juice and bile is unknown. Specimens of pancreatic juice and bile can be readily collected during surgical resection of the tumor. Profiling of pancreatic juice and bile to identify novel prognostic biomarkers may improve selection of patients for adjuvant therapy with a favorable impact on overall survival in patients diagnosed with pancreatic cancer.

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.

Secretomic profiling of cells from hollow fiber bioreactor reveals PSMA3 as a potential cholangiocarcinoma biomarker

Cholangiocarcinoma (CCA), derived from the bile duct, occurs with a relatively high incidence in Northeast Thailand. Early diagnosis is still hampered by the lack of sufficient biomarkers. In recent years, biomarker discovery using secretomes has provided interesting results, including our studies on CCA secretomes, especially with three-dimensional cell cultures. Thus, cells cultured using the hollow fiber bioreactor (HFB) with 20 kDa molecular weight cut-off (MWCO) yielded higher quality and quantity of secretomes than those from conditioned media of the monolayer culture (MNC) system. In this study, we employed the HFB culture system with 5 kDa MWCO and compared conditioned media from the HFB and MNC systems using two-dimensional gel electrophoresis, followed by identifying proteins of interest by liquid chromatography and mass spectrometry (LC/MS/MS). Two out of 4 spots of NGAL or lipocalin-2 were found to show highest increase in expression of 19.93-fold and 18.79-fold in HFB compared to MNC. Interestingly, all 14 proteasome subunits including proteasome subunit α type-1 to type-7 and β type-1 to type-7 showed 2.92-fold to 12.13-fold increased expression in HFB. The protein-protein interactions of upregulated proteins were predicted, and one of the main interaction clusters involved 20S proteasome subunits. Proteasome activity in the HFB conditioned media was also found to be higher than that in MNC conditioned media. Three types of proteasome subunit were also validated by immunoblotting and showed higher expression in the HFB system compared to MNC system. Proteasome subunit α type-3 (PSMA3) showed the highest level in plasma of cholangiocarcinoma patients compared to normal and hepatocellular carcinoma patients by immunodetection, and is of interest as a potential biomarker for cholangiocarcinoma.

A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research

The fact that cancer is a leading cause of death all around the world has naturally sparked major efforts in the pursuit of novel and more efficient biomarkers that could better serve as diagnostic tools, prognostic predictors, or therapeutical targets in the battle against this type of disease. Mass spectrometry-based proteomics has proven itself as a robust and logical alternative to the immuno-based methods that once dominated the field. Nevertheless, intrinsic limitations of classic proteomic approaches such as the natural gap between shotgun discovery-based methods and clinically applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples other than plasma and serum, which are generally aimed toward prognostic markers. Interestingly, the most common type of targeted approach is based on stable isotope dilution-selected reaction monitoring protocols for quantification of the target molecules. Overall, this reinforces that notion that targeted proteomics has already started to fulfill its role as a groundbreaking strategy that may enable researchers to catapult the number of viable, effective, and validated biomarkers in cancer clinical practice.

Unraveling Molecular Differences of Gastric Cancer by Label-Free Quantitative Proteomics Analysis

Gastric cancer (GC) has significant morbidity and mortality worldwide and especially in China. Its molecular pathogenesis has not been thoroughly elaborated. The acknowledged biomarkers for diagnosis, prognosis, recurrence monitoring and treatment are lacking. Proteins from matched pairs of human GC and adjacent tissues were analyzed by a coupled label-free Mass Spectrometry (MS) approach, followed by functional annotation with software analysis. Nano-LC-MS/MS, quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry were used to validate dysregulated proteins. One hundred forty-six dysregulated proteins with more than twofold expressions were quantified, 22 of which were first reported to be relevant with GC. Most of them were involved in cancers and gastrointestinal disease. The expression of a panel of four upregulated nucleic acid binding proteins, heterogeneous nuclear ribonucleoprotein hnRNPA2B1, hnRNPD, hnRNPL and Y-box binding protein 1 (YBX-1) were validated by Nano-LC-MS/MS, qRT-PCR, western blot and immunohistochemistry assays in ten GC patients’ tissues. They were located in the keynotes of a predicted interaction network and might play important roles in abnormal cell growth. The label-free quantitative proteomic approach provides a deeper understanding and novel insight into GC-related molecular changes and possible mechanisms. It also provides some potential biomarkers for clinical diagnosis.

Proteomic Approaches for Biomarker Panels in Cancer

Proteomic technologies remain the main backbone of biomarkers discovery in cancer. The continuous development of proteomic technologies also enlarges the bioinformatics domain, thus founding the main pillars of cancer therapy. The main source for diagnostic/prognostic/therapy monitoring biomarker panels are molecules that have a dual role, being both indicators of disease development and therapy targets. Proteomic technologies, such as mass-spectrometry approaches and protein array technologies, represent the main technologies that can depict these biomarkers. Herein, we will illustrate some of the most recent strategies for biomarker discovery in cancer, including the development of immune-markers and the use of cancer stem cells as target therapy. The challenges of proteomic biomarker discovery need new forms of cross-disciplinary conglomerates that will result in increased and tailored access to treatments for patients; diagnostic companies would benefit from the enhanced co-development of companion diagnostics and pharmaceutical companies. In the technology optimization in biomarkers, immune assays are the leaders of discovery machinery.

Quantitative Proteomic Analysis of Differentially Expressed Protein Profiles Involved in Pancreatic Ductal Adenocarcinoma

OBJECTIVES

The aim of this study was to identify differentially expressed proteins among various stages of pancreatic ductal adenocarcinoma (PDAC) by shotgun proteomics using nano-liquid chromatography coupled tandem mass spectrometry and stable isotope dimethyl labeling.

METHODS

Differentially expressed proteins were identified and compared based on the mass spectral differences of their isotope-labeled peptide fragments generated from protease digestion.

RESULTS

Our quantitative proteomic analysis of the differentially expressed proteins with stable isotope (deuterium/hydrogen ratio, ≥ 2) identified a total of 353 proteins, with at least 5 protein biomarker proteins that were significantly differentially expressed between cancer and normal mice by at least a 2-fold alteration. These 5 protein biomarker candidates include α-enolase, α-catenin, 14-3-3 β, VDAC1, and calmodulin with high confidence levels. The expression levels were also found to be in agreement with those examined by Western blot and histochemical staining.

CONCLUSIONS

The systematic decrease or increase of these identified marker proteins may potentially reflect the morphological aberrations and diseased stages of pancreas carcinoma throughout progressive developments leading to PDAC. The results would form a firm foundation for future work concerning validation and clinical translation of some identified biomarkers into targeted diagnosis and therapy for various stages of PDAC.

Effect of Concomitant Radiochemotherapy on Invasion Potential of Glioblastoma

Glioblastoma (GBM) is the most common primary brain tumor in adults with inevitable recurrence after oncotherapy. The insufficient effect of "gold standard" temozolomide-based concomitant radiochemotherapy may be due to the inability to prevent tumor cell invasion. Peritumoral infiltration depends mainly on the interaction between extracellular matrix (ECM) components and cell membrane receptors. Changes in invasive behaviour after oncotherapy can be evaluated at the molecular level by determining the RNA expression and protein levels of the invasion-related ECM components. The expression of nineteen ECM molecules was determined at both RNA and protein levels in thirty-one GBM samples. Fifteen GBM samples originated from the first surgical procedure on patients before oncotherapy, and sixteen GBM samples were collected at the second surgery due to local recurrence after concomitant chemoirradiation. RNA expressions were measured with qRT-PCR, and protein levels were determined by quantitative analysis of Western blots. Only MMP-9 RNA transcript level was reduced (p < 0.05) whereas at protein level, eight molecules showed changes concordant with RNA expression with significant decrease in brevican only. The results suggest that concomitant radiochemotherapy does not have sufficient impact on the expression of invasion-related ECM components of glioblastoma, oncotherapy does not significantly affect its invasive behavior. To avoid the spread of tumors into the brain parenchyma, supplementation of antiproliferative treatment with anti-invasive agents may be worth consideration in oncotherapy for glioblastoma.

Targeted proteomics of solid cancers: from quantification of known biomarkers towards reading the digital proteome maps

The concept of personalized medicine includes novel protein biomarkers that are expected to improve the early detection, diagnosis and therapy monitoring of malignant diseases. Tissues, biofluids, cell lines and xenograft models are the common sources of biomarker candidates that require verification of clinical value in independent patient cohorts. Targeted proteomics - based on selected reaction monitoring, or data extraction from data-independent acquisition based digital maps - now represents a promising mass spectrometry alternative to immunochemical methods. To date, it has been successfully used in a high number of studies answering clinical questions on solid malignancies: breast, colorectal, prostate, ovarian, endometrial, pancreatic, hepatocellular, lung, bladder and others. It plays an important role in functional proteomic experiments that include studying the role of post-translational modifications in cancer progression. This review summarizes verified biomarker candidates successfully quantified by targeted proteomics in this field and directs the readers who plan to design their own hypothesis-driven experiments to appropriate sources of methods and knowledge.

Expression pattern of invasion-related molecules in the peritumoral brain

OBJECTIVE

The effectiveness of therapy of intracerebral neoplasms is mainly influenced by the invasive behaviour of the tumour. The peritumoral invasion depends on the interaction between the tumour cells and the extracellular matrix (ECM) of the surrounding brain. The invading tumour cells induce change in the activity of proteases, synthases and expression of ECM-components. These alterations in the peritumoral ECM are in connection to the highly different invasiveness of gliomas and metastatic brain tumours. To understand the fairly modified invasive potential of anaplastic intracerebral tumours of different origin, the effect of tumour on the peritumoral ECM and alterations of invasion related ECM components in the peritumoral brain were evaluated.

METHODS

For this reason the mRNA expression of 19 invasion-related molecules by quantitative reverse transcriptase polymerase chain reaction was determined in normal brain tissue (Norm), in the peritumoral brain tissue of glioblastoma (peri-GBM) and of intracerebral adenocarcinoma metastasis (peri-Met). To evaluate the translational expression of the investigated molecules protein levels were determined by targeted proteomic methods.

RESULTS

Establishing the invasion pattern of the investigated tissue samples 8 molecules showed concordant difference at mRNA and protein levels in the peri-GBM and peri-Met, 11 molecules in the peri-Met and normal brain and 12 in the peri-GBM and normal brain comparison.

CONCLUSION

Our results bring some ECM molecules into focus that probably play key role in arresting tumour cell invasion around the metastatic tumour, and also in the lack of impeding tumour cell migration in case of glioblastoma.

Proteoglycan form and function: A comprehensive nomenclature of proteoglycans

We provide a comprehensive classification of the proteoglycan gene families and respective protein cores. This updated nomenclature is based on three criteria: Cellular and subcellular location, overall gene/protein homology, and the utilization of specific protein modules within their respective protein cores. These three signatures were utilized to design four major classes of proteoglycans with distinct forms and functions: the intracellular, cell-surface, pericellular and extracellular proteoglycans. The proposed nomenclature encompasses forty-three distinct proteoglycan-encoding genes and many alternatively-spliced variants. The biological functions of these four proteoglycan families are critically assessed in development, cancer and angiogenesis, and in various acquired and genetic diseases where their expression is aberrant.

Proteins associated with pancreatic cancer survival in patients with resectable pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease with a dismal prognosis. However, while most patients die within the first year of diagnosis, very rarely, a few patients can survive for >10 years. Better understanding the molecular characteristics of the pancreatic adenocarcinomas from these very-long-term survivors (VLTS) may provide clues for personalized medicine and improve current pancreatic cancer treatment. To extend our previous investigation, we examined the proteomes of individual pancreas tumor tissues from a group of VLTS patients (survival ≥10 years) and short-term survival patients (STS, survival <14 months). With a given analytical sensitivity, the protein profile of each pancreatic tumor tissue was compared to reveal the proteome alterations that may be associated with pancreatic cancer survival. Pathway analysis of the differential proteins identified suggested that MYC, IGF1R and p53 were the top three upstream regulators for the STS-associated proteins, and VEGFA, APOE and TGFβ-1 were the top three upstream regulators for the VLTS-associated proteins. Immunohistochemistry analysis using an independent cohort of 145 PDAC confirmed that the higher abundance of ribosomal protein S8 (RPS8) and prolargin (PRELP) were correlated with STS and VLTS, respectively. Multivariate Cox analysis indicated that 'High-RPS8 and Low-PRELP' was significantly associated with shorter survival time (HR=2.69, 95% CI 1.46-4.92, P=0.001). In addition, galectin-1, a previously identified protein with its abundance aversely associated with pancreatic cancer survival, was further evaluated for its significance in cancer-associated fibroblasts. Knockdown of galectin-1 in pancreatic cancer-associated fibroblasts dramatically reduced cell migration and invasion. The results from our study suggested that PRELP, LGALS1 and RPS8 might be significant prognostic factors, and RPS8 and LGALS1 could be potential therapeutic targets to improve pancreatic cancer survival if further validated.

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic-based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research.