Global molecular dysfunctions in gastric cancer revealed by an integrated analysis of the phosphoproteome and transcriptome

Dysregulation of phosphoproteins in hepatocellular carcinoma revealed via quantitative analysis of the phosphoproteome

Hepatocellular carcinoma (HCC) is one of the most frequently diagnosed types of cancer in the world. Post-translational modifications, such as phosphorylation, serve an essential role during cancer development. To identify aberrant phosphorylation in HCC, a multiplexed tandem mass tag approach combined with liquid chromatography tandem-mass spectrometry was used in the present study. The results are available via ProteomeXchange (identifier no. PXD013934). A total of 4,780 phosphorylated sites distributed on 2,209 proteins were identified and quantified, including 74 and 459 phosphorylated upregulated and downregulated proteins, respectively. Bioinformatic analysis revealed differences and similarities between HCC and normal tissues. Gene Ontology enrichment analysis provided information on biological processes, molecular functions, cellular components and sub-cellular localizations. Protein domains enrichment of differentially expressed proteins was analyzed using InterPro database. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed pathways that may potentially be involved in HCC. Integrative analysis of the functions, pathways, motifs of phosphorylated peptides, protein domains and protein interactions established a profile of the phosphoproteome of HCC, which may contribute to identify novel biomarkers for the diagnosis and prognosis of HCC, as well as novel therapeutic targets for HCC treatment.

Phosphoproteomic analysis identifies CLK1 as a novel therapeutic target in gastric cancer

BACKGROUND

Phosphorylation is an important regulatory mechanism of protein activity in cells. Studies in various cancers have reported perturbations in kinases resulting in aberrant phosphorylation of oncoproteins and tumor suppressor proteins.

METHODS

In this study, we carried out quantitative phosphoproteomic analysis of gastric cancer tissues and corresponding xenograft samples. Using these data, we employed bioinformatics analysis to identify aberrant signaling pathways. We further performed molecular inhibition and silencing of the upstream regulatory kinase in gastric cancer cell lines and validated its effect on cellular phenotype. Through an ex vivo technology utilizing patient tumor and blood sample, we sought to understand the therapeutic potential of the kinase by recreating the tumor microenvironment.

RESULTS

Using mass spectrometry-based high-throughput analysis, we identified 1,344 phosphosites and 848 phosphoproteins, including differential phosphorylation of 177 proteins (fold change cut-off ≥ 1.5). Our data showed that a subset of differentially phosphorylated proteins belonged to splicing machinery. Pathway analysis highlighted Cdc2-like kinase (CLK1) as upstream kinase. Inhibition of CLK1 using TG003 and CLK1 siRNA resulted in a decreased cell viability, proliferation, invasion and migration as well as modulation in the phosphorylation of SRSF2. Ex vivo experiments which utilizes patient's own tumor and blood to recreate the tumor microenvironment validated the use of CLK1 as a potential target for gastric cancer treatment.

CONCLUSIONS

Our data indicates that CLK1 plays a crucial role in the regulation of splicing process in gastric cancer and that CLK1 can act as a novel therapeutic target in gastric cancer.

Phospho-Protein Arrays as Effective Tools for Screening Possible Targets for Kinase Inhibitors and Their Use in Precision Pediatric Oncology

The specific targeting of signal transduction by low-molecular-weight inhibitors or monoclonal antibodies represents a very promising personalized treatment strategy in pediatric oncology. In this study, we present the successful and clinically relevant use of commercially available phospho-protein arrays for analyses of the phosphorylation profiles of a broad spectrum of receptor tyrosine kinases and their downstream signaling proteins in tumor tissue samples. Although these arrays were made for research purposes on human biological samples, they have already been used by several authors to profile various tumor types. Our study performed a systematic analysis of the advantages and pitfalls of the use of this method for personalized clinical medicine. In certain clinical cases and their series, we demonstrated the important aspects of data processing and evaluation, the use of phospho-protein arrays for single sample and serial sample analyses, and the validation of obtained results by immunohistochemistry, as well as the possibilities of this method for the hierarchical clustering of pediatric solid tumors. Our results clearly show that phospho-protein arrays are apparently useful for the clinical consideration of druggable molecular targets within a specific tumor. Thus, their potential validation for diagnostic purposes may substantially improve the personalized approach in the treatment of relapsed or refractory solid tumors.

High-Throughput Assessment of Kinome-wide Activation States

Aberrant kinase activity has been linked to a variety of disorders; however, methods to probe kinase activation states in cells have been lacking. Until now, kinase activity has mainly been deduced from either protein expression or substrate phosphorylation levels. Here, we describe a strategy to directly infer kinase activation through targeted quantification of T-loop phosphorylation, which serves as a critical activation switch in a majority of protein kinases. Combining selective phosphopeptide enrichment with robust targeted mass spectrometry, we provide highly specific assays for 248 peptides, covering 221 phosphosites in the T-loop region of 178 human kinases. Using these assays, we monitored the activation of 63 kinases through 73 T-loop phosphosites across different cell types, primary cells, and patient-derived tissue material. The sensitivity of our assays is highlighted by the reproducible detection of TNF-α-induced RIPK1 activation and the detection of 46 T-loop phosphorylation sites from a breast tumor needle biopsy.

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Robust targeted MS assays permit observation of conserved kinome activation sites

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178 human kinases are characterized in high-throughput assays

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Kinase activation states are observed in human primary cells and needle biopsy

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Specific kinase activation states are induced during cell death and drug resistance

E2F6-mediated lncRNA CASC2 down-regulation predicts poor prognosis and promotes progression in gastric carcinoma

AIMS

To investigate the potential biological role of E2F6 and its underlying molecular mechanism in gastric carcinoma (GC) progression.

MAIN METHODS

The expressions of cancer susceptibility candidate 2 (CASC2), E2F6 and matrix metalloprotein-2 (MMP-2) were measured by quantitative real-time polymerase chain reaction and western blotting. The inhibitory effect of E2F6 on CASC2 was evaluated using luciferase reporter assay. Cell growth was assessed by colony formation assay and cell counting kit-8. Cell invasion and apoptosis were measured by transwell assay and flow cytometry assay, respectively. In vivo tumorigenicity was assessed by tumor xenografts in nude mice.

KEY FINDINGS

Our data revealed that CASC2 was downregulated while E2F6 was upregulated in GC tissues and cell lines. Remarkably, lower expression of CASC2 was associated with poor survival in GC patients. E2F6 inhibited the expression of CASC2. Subsequently, reliable data showed that downregulation of E2F6 suppressed the proliferation and invasion, and promoted the apoptosis of GC cells. Furthermore, downregulation of E2F6 decreased the expression of MMP-2 and increased the activity of caspase-3. However, these changes triggered by E2F6 knockdown could be reversed by inhibition of CASC2. Moreover, we also proved that downregulation of CASC2 reverses the effect of E2F6 knockdown on tumor growth in vivo.

SIGNIFICANCE

Our data demonstrated that E2F6 could regulate the proliferation, invasion and apoptosis of GC cells via inhibiting the expression of CASC2, suggesting that E2F6/CASC2 axis is another regulator of GC progression.

pETM: a penalized Exponential Tilt Model for analysis of correlated high-dimensional DNA methylation data

Motivation

DNA methylation plays an important role in many biological processes and cancer progression. Recent studies have found that there are also differences in methylation variations in different groups other than differences in methylation means. Several methods have been developed that consider both mean and variance signals in order to improve statistical power of detecting differentially methylated loci. Moreover, as methylation levels of neighboring CpG sites are known to be strongly correlated, methods that incorporate correlations have also been developed. We previously developed a network-based penalized logistic regression for correlated methylation data, but only focusing on mean signals. We have also developed a generalized exponential tilt model that captures both mean and variance signals but only examining one CpG site at a time.

Results

In this article, we proposed a penalized Exponential Tilt Model (pETM) using network-based regularization that captures both mean and variance signals in DNA methylation data and takes into account the correlations among nearby CpG sites. By combining the strength of the two models we previously developed, we demonstrated the superior power and better performance of the pETM method through simulations and the applications to the 450K DNA methylation array data of the four breast invasive carcinoma cancer subtypes from The Cancer Genome Atlas (TCGA) project. The developed pETM method identifies many cancer-related methylation loci that were missed by our previously developed method that considers correlations among nearby methylation loci but not variance signals.

Availability and Implementation

The R package 'pETM' is publicly available through CRAN: http://cran.r-project.org .

Contact

sw2206@columbia.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Detection of post-translational modifications using solid-phase proximity ligation assay

Post-translational modifications (PTMs) regulate protein activities to help orchestrate and fine-tune cellular processes. Dysregulation of PTMs is often related with disorders and malignancies, and may serve as a precise biomarker of disease. Developing sensitive tools to measure and monitor low-abundant PTMs in tissue lysates or serum will be instrumental for opening up new PTM-based diagnostic avenues. Here, we investigate the use of solid-phase proximity ligation assay (SP-PLA) for detection of different PTMs. The assay depends on the recognition of the target protein molecule and its modification by three affinity binders. Using antibodies and lectins, we applied the method for detection of glycosylated CD44 and E-Cadherin, and phosphorylated p53 and EGFR. The assay was found to have superior dynamic range and limit of detection compared to standard ELISAs. In summary, we have established the use of SP-PLA as an appropriate method for sensitive detection of PTMs in lysates and sera, which may provide a basis for future PTM-based diagnostic and prognostic biomarkers.

Flux control through protein phosphorylation in yeast

Protein phosphorylation is one of the most important mechanisms regulating metabolism as it can directly modify metabolic enzymes by the addition of phosphate groups. Attributed to such a rapid and reversible mechanism, cells can adjust metabolism rapidly in response to temporal changes. The yeast Saccharomyces cerevisiae, a widely used cell factory and model organism, is reported to show frequent phosphorylation events in metabolism. Studying protein phosphorylation in S. cerevisiae allows for gaining new insight into the function of regulatory networks, which may enable improved metabolic engineering as well as identify mechanisms underlying human metabolic diseases. Here we collect functional phosphorylation events of 41 enzymes involved in yeast metabolism and demonstrate functional mechanisms and the application of this information in metabolic engineering. From a systems biology perspective, we describe the development of phosphoproteomics in yeast as well as approaches to analysing the phosphoproteomics data. Finally, we focus on integrated analyses with other omics data sets and genome-scale metabolic models. Despite the advances, future studies improving both experimental technologies and computational approaches are imperative to expand the current knowledge of protein phosphorylation in S. cerevisiae.

Exploiting receptor tyrosine kinase co-activation for cancer therapy

Studies over the past decade have shown that many cancers have evolved receptor tyrosine kinase (RTK) co-activation as a mechanism to drive tumour progression and limit the lethal effects of therapy. This review summarises the general principles of RTK co-activation and discusses approaches to exploit this phenomenon in cancer therapy and drug discovery. Computational strategies to predict kinase co-dependencies by integrating drug screening data and kinase inhibitor selectivity profiles will also be described. We offer a perspective on the implications of RTK co-activation on tumour heterogeneity and cancer evolution and conclude by surveying emerging computational and experimental approaches that will provide insights into RTK co-activation biology and deliver new developments in effective cancer therapies.

Differential role of Wnt signaling and base excision repair pathways in gastric adenocarcinoma aggressiveness

Aberrant activation of Wnt and base excision repair (BER) signaling pathways are implicated in tumor progression and chemotherapy resistance in gastric adenocarcinoma. This study was conducted to clarify the role of E2F6 and RhoA, components of the Wnt signaling pathway, and SMUG1, a component of the BER pathway in gastric adenocarcinoma. Expression levels and clinicopathological significance of three biomarkers, namely E2F6, RhoA, and SMUG1, as potential signaling molecules involved in tumorigenesis and aggressive behavior, were examined using tissue microarray. Our analysis showed a relative increase in the expression of E2F6 in gastric adenocarcinoma with no lymph node metastasis (χ ², P = 0.04 and OR, P = 0.08), while overexpression of RhoA and SMUG1 was found more often in the diffuse subtype of gastric adenocarcinoma as compared to the intestinal subtype (χ ², P = 0.05, OR, P = 0.08 and χ ², P = 0.001, OR, P = 0.009, respectively). Higher expression of RhoA was frequently seen in tumors with vascular invasion (χ ², P = 0.01 and OR, P = 0.01). In addition, increased expression of SMUG1 was found more often in poorly differentiated tumors (χ ², P = 0.01 and OR, P = 0.01). The distinct phenotype of E2F6^Low/SMUG1^High was more common in poorly differentiated tumors (P = 0.04) and with omental involvement (P = 0.01). The RhoA^High/SMUG1^High expression pattern was significantly more often found in diffuse subtype compared to the intestinal subtype (P = 0.001) as well as in poorly differentiated tumors (P = 0.004). The E2F6^Low/SMUG1^High and RhoA^High/SMUG1^High phenotypes can be considered as aggressive phenotypes of gastric adenocarcinoma. Our findings also demonstrated the synergistic effect of RhoA and SMUG1 in conferring tumor aggressiveness in diffuse subtype of gastric adenocarcinoma.

What gastric cancer proteomic studies show about gastric carcinogenesis?

Gastric cancer is a complex, heterogeneous, and multistep disease. Over the past decades, several studies have aimed to determine the molecular factors that lead to gastric cancer development and progression. After completing the human genome sequencing, proteomic technologies have presented rapid progress. Differently from the relative static state of genome, the cell proteome is dynamic and changes in pathologic conditions. Proteomic approaches have been used to determine proteome profiles and identify differentially expressed proteins between groups of samples, such as neoplastic and nonneoplastic samples or between samples of different cancer subtypes or stages. Therefore, proteomic technologies are a useful tool toward improving the knowledge of gastric cancer molecular pathogenesis and the understanding of tumor heterogeneity. This review aimed to summarize the proteins or protein families that are frequently identified by using high-throughput screening methods and which thus may have a key role in gastric carcinogenesis. The increased knowledge of gastric carcinogenesis will clearly help in the development of new anticancer treatments. Although the studies are still in their infancy, the reviewed proteins may be useful for gastric cancer diagnosis, prognosis, and patient management.

Helicobacter pylori infection and gastric carcinoma: Not all the strains and patients are alike

Gastric carcinoma (GC) develops in only 1%-3% of Helicobacter pylori (H. pylori) infected people. The role in GC formation of the bacterial genotypes, gene polymorphisms and host's factors may therefore be important. The risk of GC is enhanced when individuals are infected by strains expressing the oncoprotein CagA, in particular if CagA has a high number of repeats containing the EPIYA sequence in its C'-terminal variable region or particular amino acid sequences flank the EPIYA motifs. H. pylori infection triggers an inflammatory response characterised by an increased secretion of some chemokines by immunocytes and colonised gastric epithelial cells; these molecules are especially constituted by proteins composing the interleukin-1beta (IL-1β) group and tumour necrosis factor-alpha (TNF-α). Polymorphisms in the promoter regions of genes encoding these molecules, could account for high concentrations of IL-1β and TNF-α in the gastric mucosa, which may cause hypochlorhydria and eventually GC. Inconsistent results have been attained with other haplotypes of inflammatory and anti-inflammatory cytokines. Genomic mechanisms of GC development are mainly based on chromosomal or microsatellite instability (MSI) and deregulation of signalling transduction pathways. H. pylori infection may induce DNA instability and breaks of double-strand DNA in gastric mucocytes. Different H. pylori strains seem to differently increase the risk of cancer development run by the host. Certain H. pylori genotypes (such as the cagA positive) induce high degrees of chronic inflammation and determine an increase of mutagenesis rate, oxidative-stress, mismatch repair mechanisms, down-regulation of base excision and genetic instability, as well as generation of reactive oxygen species that modulate apoptosis; these phenomena may end to trigger or concur to GC development.

Anion-exchange chromatography of phosphopeptides: weak anion exchange versus strong anion exchange and anion-exchange chromatography versus electrostatic repulsion-hydrophilic interaction chromatography

Most phosphoproteomics experiments rely on prefractionation of tryptic digests before online liquid chromatography-mass spectrometry. This study compares the potential and limitations of electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) and anion-exchange chromatography (AEX). At a pH higher than 5, phosphopeptides have two negative charges per residue and are well-retained in AEX. However, peptides with one or two phosphate groups are not separated from peptides with multiple Asp or Glu residues, interfering with the identification of phosphopeptides. At a pH of 2, phosphate residues have just a single negative charge but Asp and Glu are uncharged. This facilitates the separation of phosphopeptides from unmodified acidic peptides. Singly phosphorylated peptides are retained weakly under these conditions, due to electrostatic repulsion, unless hydrophilic interaction is superimposed in the ERLIC mode. Weak anion-exchange (WAX) and strong anion-exchange (SAX) columns were compared, with both peptide standards and a HeLa cell tryptic digest. The SAX column exhibited greater retention at pH 6 than did the WAX column. However, only about 60% as many phosphopeptides were identified with SAX at pH 6 than via ERLIC at pH 2. In one ERLIC run, 12 467 phosphopeptides were identified, including 4233 with more than one phosphate. We conclude that chromatography of phosphopeptides is best performed at low pH in the ERLIC mode. Under those conditions, the performances of the SAX and WAX materials were comparable. The data have been deposited with the ProteomeXchange with identifier PXD001333.

AMPK-activated protein kinase activation by Impatiens balsamina L. is related to apoptosis in HSC-2 human oral cancer cells

Objective:

In the present study, we investigated the efficacy of a methanol extract from Impatiens balsamina L. (MEIB) against HSC-2 human oral cancer cells.

Materials and Methods:

The anti-cancer efficacies of MEIB were performed by methanethiosulfonate assay, phospho-kinase array, Western blot, 4’-6-diamidino-2-phenylindole staining, trypan blue exclusion assay and 5,5’,6,6’-tetrachloro-1,1’,3,3’-tetraethylbenzimidazolylcarbocyanine iodide assay.

Results:

MEIB decreased the cell viability of HSC-2 cells. According to phospho-kinase arrays, MEIB markedly activated AMP-activated protein kinase (AMPK) signaling, but inactivated mammalian target of rapamycin signaling. MEIB induced apoptosis as evidenced by activation of caspase-3, poly (ADP-ribose) polymerase cleavage and nuclear condensation. In addition, AMPK activation by two known activators (5-aminoimidazole-4-carboxamide-1-β-ribofuranoside and metformin) decreased cell viability and induced apoptosis. Moreover, MEIB increased the expression levels of mitochondria-related proteins (t-Bid, Bak and Bad), which contributed to the disruption of mitochondrial membrane potential, cytochrome C release and activation of caspase-9. Metformin also increased t-Bid expression and the subsequent release of cytochrome C into the cytosol.

Conclusion:

These results suggest that MEIB may be of therapeutic value for treating oral cancer and that its mechanism of action occurs through AMPK and t-Bid.

Divide and conquer: subproteomic approaches toward gastric cancer biomarker and drug target discovery

The discovery of biomarkers for early detection and treatment for gastric cancer are two important gaps that proteomics have the potential to fill. Advancements in mass spectrometry, sample preparation and separation strategies are crucial to proteomics-based discoveries and subsequent translations from bench to bedside. A great number of studies exploiting various subproteomic approaches have emerged for higher-resolution analysis (compared with shotgun proteomics) that permit interrogation of different post-translational and subcellular compartmentalized forms of the same proteins as determinants of disease phenotypes. This is a unique and key strength of proteomics over genomics. In this review, the salient features, competitive edges and pitfalls of various subproteomic approaches are discussed. We also highlight valuable insights from several subproteomic studies that have increased our understanding of the molecular etiology of gastric cancer and the findings that led to the discovery of potential biomarkers/drug targets that were otherwise not revealed by conventional shotgun expression proteomics.

Affinity-based microarrays for proteomic analysis of cancer tissues

Based on about a decade of technical developments in analysing the human proteome with antibody microarrays and experience in performing such analyses, now there are the means at hand for detailed and simultaneously global investigations of this kind. Many technical aspects have been dealt with of both the microarray format itself - such as overcoming kinetic and mass transport limitations and thus achieving accurate measurements - and ancillary processes - such as extraction procedures that provide good protein solubilisation, produce reproducible yields and preserve the native protein conformation as much as possible. The overall analysis process is robust and reproducible, highly sensitive down to the level of single-molecule detection and permits an analysis of several parameters on many molecules at a time. While the study of body liquids is widely applied, analyses of tissue proteomes are still scarce. However, conditions do exist to perform the latter at a quality level that meets the standards for clinical applications. This review highlights methodological aspects relevant for a biomedically useful analysis of cellular samples and discusses the potential of such studies, in particular, in view of personalised medicine approaches.

Genetic aspects of gastric cancer instability

Unravelling the molecular mechanisms underlying gastric carcinogenesis is one of the major challenges in cancer genomics. Gastric cancer is a very complex and heterogeneous disease, and although much has been learned about the different genetic changes that eventually lead to its development, the detailed mechanisms still remain unclear. Malignant transformation of gastric cells is the consequence of a multistep process involving different genetic and epigenetic changes in numerous genes in combination with host genetic background and environmental factors. The majority of gastric adenocarcinomas are characterized by genetic instability, either microsatellite instability (MSI) or chromosomal instability (CIN). It is believed that chromosome destabilizations occur early in tumour progression. This review summarizes the most common genetic alterations leading to instability in sporadic gastric cancers and its consequences.

Discovery of biomarkers for gastric cancer: a proteomics approach

Gastric cancer is the second leading cause of cancer-related deaths worldwide. Although many treatment options exist for patients with gastric tumors, the incidence and mortality rate of gastric cancer are on the rise. The early stages of gastric cancer are non-symptomatic, and the treatment response is unpredictable. This situation is further aggravated by a lack of diagnostic biomarkers that can aid in the early detection and prognosis of gastric cancer and in the prediction of chemoresistance. Moreover, clinical surgical specimens are rarely obtained, and traditional biomarkers of gastric cancer are not very effective. Many studies in the field of proteomics have contributed to the discovery and establishment of powerful diagnostic tools (e.g., ProteinChip array) in the management of cancer. The evolution in proteomic technologies has not only enabled the screening of a large number of samples but also enabled the identification of pathologically significant proteins, such as phosphoproteins, and the quantitation of difference in protein expression under different conditions. Multiplexed assays are used widely to accurately fractionate various complex samples such as blood, tissue, cells, and Helicobacter pylori-infected specimens to identify differentially expressed proteins. Biomarker detection studies have substantially contributed to the areas of secretome, metabolome, and phosphoproteome. Here, we review the development of potential biomarkers in the natural history of gastric cancer, with specific emphasis on the characteristics of target protein convergence.

Mitochondrial proteomic approaches for new potential diagnostic and prognostic biomarkers in cancer

Mitochondrial dysfunction and mutations in mitochondrial DNA have been implicated in a wide variety of human diseases, including cancer. In recent years, considerable advances in genomic, proteomic and bioinformatic technologies have made it possible the analysis of mitochondrial proteome, leading to the identification of over 1,000 proteins which have been assigned unambiguously to mitochondria. Defining the mitochondrial proteome is a fundamental step for fully understanding the organelle functions as well as mechanisms underlying mitochondrial pathology. In fact, besides giving information on mitochondrial physiology, by characterizing all the components of this subcellular organelle, the application of proteomic technologies permitted now to study the proteins involved in many crucial properties in cell signaling, cell differentiation and cell death and, in particular, to identify mitochondrial proteins that are aberrantly expressed in cancer cells. An improved understanding of the mitochondrial proteome could be essential to shed light on the connection between mitochondrial dysfunction, deregulation of apoptosis and tumorigenesis and to discovery new therapeutic targets for mitochondria-related diseases.

Investigation of POPX2 phosphatase functions by comparative phosphoproteomic analysis

Identifying the substrates and biochemical pathway regulated by phosphatases has always been more challenging than finding those regulated by kinases. Here, we report the use of phosphoproteomic methods to analyse the pathways regulated by POPX2 (partner of PIX 2) phosphatase. POPX2 is a serine/threonine phosphatase, found in many cancer types. The levels of the POPX2 have been found to be up-regulated in the more invasive breast cancer cells compared with non-invasive ones. Our observations also suggest that POPX2 level is positively correlated with cell motility. Thus, finding substrates or pathways regulated by POPX2 will help to elucidate the regulatory mechanism of cancer cell motility and invasiveness. We have also developed and validated a protocol using electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) to enrich the phosphopeptides followed by LC-MS/MS to allow comparison between the phosphoproteomes of control and POPX2 overexpressing cells. With this approach, we were able to identify a biochemical pathway through which POPX2 exerts its apparent cellular function: the regulation of activity of glycogen synthase kinase-3, which in turn modulates extracellular signal-regulated kinase and cell motility.