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Human embryonic stem cells (hESCs) have the capacity for self-renewal and multilineage differentiation, which are of clinical importance for regeneration medicine. Despite the significant progress of hESC study, the complete hESC proteome atlas, especially the surface protein composition, awaits delineation. According to the latest release of neXtProt database (January 17, 2018; 19 658 PE1, 2, 3, and 4 human proteins), membrane proteins present the major category (1047; 48%) among all 2186 missing proteins (MPs). We conducted a deep subcellular proteomics analysis of hESCs to identify the nuclear, cytoplasmic, and membrane proteins in hESCs and to mine missing membrane proteins in the very early cell status. To our knowledge, our study achieved the largest data set with confident identification of 11 970 unique proteins (1% false discovery rate at peptide, protein, and PSM levels), including the most-comprehensive description of 6 138 annotated membrane proteins in hESCs. Following the HPP guideline, we identified 26 gold (neXtProt PE2, 3, and 4 MPs) and 87 silver (potential MP candidates with a single unique peptide detected) MPs, of which 69 were membrane proteins, and the expression of 21 gold MPs was further verified either by multiple reaction monitoring mass spectrometry or by matching synthetic peptides in the Peptide Atlas database. Functional analysis of the MPs revealed their potential roles in the pluripotency-related pathways and the lineage- and tissue-specific differentiation processes. Our proteome map of hESCs may provide a rich resource not only for the identification of MPs in the human proteome but also for the investigation on self-renewal and differentiation of hESC. All mass spectrometry data were deposited in ProteomeXchange via jPOST with identifier PXD009840.

The natural course of early HCC is unknown, and its progression to intermediate and advanced HCC can be diverse. Some early stage HCC patients enjoy prolonged disease-free survival, whereas others suffer aggressive relapse to stage IV metastatic cancer within a year. Comparative proteomics of HCC tumor tissues was carried out using 2D-DIGE and MALDI-TOF/TOF MS to identify proteins that can distinguish these two groups of stage I HCC patients. Twelve out of 148 differentially regulated protein spots were found to differ by approximately 2-fold for the relapse versus nonrelapse patient tissues. Four proteins, namely, heat shock 70 kDa protein 1, argininosuccinate synthase, isoform 2 of UTP-glucose-1-phosphate uridylyltransferase, and transketolase, were shown to have the potential to differentiate metastatic relapse (MR) from nonrelapse (NR) HCC patients after validation by western blotting and immunohistochemical assays. Subsequent TMA analysis revealed a three marker panel of HSP70, ASS1, and UGP2 to be statistically significant in stratifying the two groups of HCC patients. This combination panel achieved high levels of sensitivity and specificity, which has potential for clinical use in identifying HCC tumors prone to MR. This stratification will allow development of clinical management, including close follow-up and possibly treatment options, in the near future.

Traditional proteomics analysis is plagued by the use of arbitrary thresholds resulting in large loss of information. We propose here a novel method in proteomics that utilizes all detected proteins. We demonstrate its efficacy in a proteomics screen of 5 and 7 liver cancer patients in the moderate and late stage, respectively. Utilizing biological complexes as a cluster vector, and augmenting it with submodules obtained from partitioning an integrated and cleaned protein–protein interaction network, we calculate a Proteomics Signature Profile (PSP) for each patient based on the hit rates of their reported proteins, in the absence of fold change thresholds, against the cluster vector. Using this, we demonstrated that moderate- and late-stage patients segregate with high confidence. We also discovered a moderate-stage patient who displayed a proteomics profile similar to other poor-stage patients. We identified significant clusters using a modified version of the SNet approach. Comparing our results against the Proteomics Expansion Pipeline (PEP) on which the same patient data was analyzed, we found good correlation. Building on this finding, we report significantly more clusters (176 clusters here compared to 70 in PEP), demonstrating the sensitivity of this approach. Gene Ontology (GO) terms analysis also reveals that the significant clusters are functionally congruent with the liver cancer phenotype. PSP is a powerful and sensitive method for analyzing proteomics profiles even when sample sizes are small. It does not rely on the ratio scores but, rather, whether a protein is detected or not. Although consistency of individual proteins between patients is low, we found the reported proteins tend to hit clusters in a meaningful and informative manner. By extracting this information in the form of a Proteomics Signature Profile, we confirm that this information is conserved and can be used for (1) clustering of patient samples, (2) identification of significant clusters based on real biological complexes, and (3) overcoming consistency and coverage issues prevalent in proteomics data sets.

Gastric cancer is the second leading cause of cancer deaths worldwide, and currently, there are no clinically relevant biomarkers for gastric cancer diagnosis or prognosis. In this study, we applied a 2D-LC-MS/MS based approach, in combination with iTRAQ labeling, to study the secretomes of the gastric cancer cell lines AGS and MKN7. By performing a comparative analysis between the conditioned media and the whole cell lysates, our workflow allowed us to differentiate the bona fide secreted proteins from the intracellular contaminants within the conditioned media. Ninety proteins were found to have higher abundance in the conditioned media as compared to the whole cell lysates of AGS and MKN7 cells. Using a signal peptide and nonclassical secretion prediction tool and an online exosome database, we demonstrated that up to 92.2% of these 90 proteins can be exported out of the cells by classical or nonclassical secretory pathways. We then performed quantitative comparisons of the secretomes between AGS and MKN7, identifying 43 differentially expressed secreted proteins. Among them, GRN was found to be frequently expressed in gastric tumor tissues, but not in normal gastric epithelia by immunohistochemistry. Sandwich ELISA assay also showed elevation of serum GRN levels in gastric cancer patients, particularly those with early gastric cancer. Receiver operating characteristic (ROC) curves analysis confirmed that serum GRN can provide diagnostic discriminations for gastric cancer patients.

Metastasis accounts largely for the high mortality rate of colorectal cancer (CRC) patients. In this study, we performed comparative proteome analysis of primary CRC cell lines HCT-116 and its metastatic derivative E1 using 2-D DIGE. We identified 74 differentially expressed proteins, many of which function in transcription, translation, angiogenesis signal transduction, or cytoskeletal remodeling pathways, which are indispensable cellular processes involved in the metastatic cascade. Among these proteins, stathmin-1 (STMN1) was found to be highly up-regulated in E1 as compared to HCT-116 and was thus selected for further functional studies. Our results showed that perturbations in STMN1 levels resulted in significant changes in cell migration, invasion, adhesion, and colony formation. We further showed that the differential expression of STMN1 correlated with the cells' metastatic potential in other paradigms of CRC models. Using immunohistochemistry, we also showed that STMN1 was highly expressed in colorectal primary tumors and metastatic tissues as compared to the adjacent normal colorectal tissues. Furthermore, we also showed via tissue microarray analyses of 324 CRC tissues and Kaplan-Meier survival plot that CRC patients with higher expression of STMN1 have poorer prognosis.

Current limitations in proteome analysis by high-throughput mass spectrometry (MS) approaches have sometimes led to incomplete (or inconclusive) data sets being published or unpublished. In this work, we used an iTRAQ reference data on hepatocellular carcinoma (HCC) to design a two-stage functional analysis pipeline to widen and improve the proteome coverage and, subsequently, to unveil the molecular changes that occur during HCC progression in human tumorous tissue. The first involved functional cluster analysis by incorporating an expansion step on a cleaned integrated network. The second used an in-house developed pathway database where recovery of shared neighbors was followed by pathway enrichment analysis. In the original MS data set, over 500 proteins were detected from the tumors of 12 male patients, but in this paper we reported an additional 1000 proteins after application of our bioinformatics pipeline. Through an integrative effort of network cleaning, community finding methods, and network analysis, we also uncovered several biologically interesting clusters implicated in HCC. We established that HCC transition from a moderate to poor stage involved densely connected clusters that comprised of PCNA, XRCC5, XRCC6, PARP1, PRKDC, and WRN. From our pathway enrichment analyses, it appeared that the HCC moderate stage, unlike the poor stage, is enriched in proteins involved in immune responses, thus suggesting the acquisition of immuno-evasion. Our strategy illustrates how an original oncoproteome could be expanded to one of a larger dynamic range where current technology limitations prevent/limit comprehensive proteome characterization., Comprehensive proteome coverage by mass spectrometry remains a challenge. We used an integrated analysis pipeline to improve proteome coverage and functional analysis of hepatocellular carcinoma progression. The expanded proteome includes low abundant proteins involved in transcription and signaling. With that we established that HCC transition from moderate to poor involved densely connected clusters, which implicates DNA repair and immune dysregulation.

Following an official announcement of the Chromosome-centric Human Proteome Project (C-HPP), the Chromosome 12 (Ch12) Consortium has been established by five representative teams from five Asian countries including Thailand (Siriraj Hospital, Mahidol University), Singapore (National University of Singapore), Taiwan (Academia Sinica), Hong Kong (The Chinese University of Hong Kong), and India (Institute of Bioinformatics). We have worked closely together to extensively and systematically analyze all missing and known proteins encoded by Ch12 for their tissue/cellular/subcellular localizations. The target organs/tissues/cells include kidney, brain, gastrointestinal tissues, blood/immune cells, and stem cells. In the later phase, post-translational modifications and functional significance of Ch12-encoded proteins as well as their associations with human diseases (i.e., immune diseases, metabolic disorders, and cancers) will be defined. We have collaborated with other chromosome teams, Human Kidney and Urine Proteome Project (HKUPP), AOHUPO Membrane Proteomics Initiative, and other existing HUPO initiatives in the Biology/Disease-Based Human Proteome Project (B/D-HPP) to delineate functional roles and medical implications of Ch12-encoded proteins. The data set to be obtained from this multicountry consortium will be an important piece of the jigsaw puzzle to fulfill the missions and goals of the C-HPP and the global Human Proteome Project (HPP).

Palm oil is a highly versatile commodity with wide applications in the food, cosmetics, and biofuel industries. Storage oil in the oil palm mesocarp can make up a remarkable 80% of its dry mass, making it the oil crop with the richest oil content in the world. As such, there has been an ongoing interest in understanding the mechanism of oil production in oil palm fruits. To identify the proteome changes during oil palm fruit maturation and factors affecting oil yield in oil palm fruits, we examined the proteomic profiles of oil palm mesocarps at four developing stages--12, 16, 18, and 22 weeks after pollination--by 8-plex iTRAQ labeling coupled to 2D-LC and MALDI-TOF/TOF MS. It was found that proteins from several important metabolic processes, including starch and sucrose metabolism, glycolysis, pentose phosphate shunt, fatty acid biosynthesis, and oxidative phosphorylation, were differentially expressed in a concerted manner. These increases led to an increase in carbon flux and a diversion of resources such as ATP and NADH that are required for lipid biosynthesis. The temporal proteome profiles between the high-oil-yielding (HY) and low-oil-yielding (LY) fruits also showed significant differences in the levels of proteins involved in the regulation of the TCA cycle and oxidative phosphorylation. In particular, the expression level of the β subunit of the ATP synthase complex (complex IV of the electron transport chain) was found to be increased during fruit maturation in HY but decreased in the LY during the fruit maturation. These results suggested that increased energy supply is necessary for augmented oil yield in the HY oil palm trees.

Troglitazone, a first-generation thiazolidinedione of antihyperglycaemic properties, was withdrawn from the market due to unacceptable idiosyncratic hepatotoxicity. Despite intensive research, the underlying mechanism of troglitazone-induced liver toxicity remains unknown. Here we report the use of the Sod2(+/-) mouse model of silent mitochondrial oxidative-stress-based and quantitative mass spectrometry-based proteomics to track the mitochondrial proteome changes induced by physiologically relevant troglitazone doses. By quantitative untargeted proteomics, we first globally profiled the Sod2(+/-) hepatic mitochondria proteome and found perturbations including GSH metabolism that enhanced the toxicity of the normally nontoxic troglitazone. Short- and long-term troglitazone administration in Sod2(+/-) mouse led to a mitochondrial proteome shift from an early compensatory response to an eventual phase of intolerable oxidative stress, due to decreased mitochondrial glutathione (mGSH) import protein, decreased dicarboxylate ion carrier (DIC), and the specific activation of ASK1-JNK and FOXO3a with prolonged troglitazone exposure. Furthermore, mapping of the detected proteins onto mouse specific protein-centered networks revealed lipid-associated proteins as contributors to overt mitochondrial and liver injury when under prolonged exposure to the lipid-normalizing troglitazone. By integrative toxicoproteomics, we demonstrated a powerful systems approach in identifying the collapse of specific fragile nodes and activation of crucial proteome reconfiguration regulators when targeted by an exogenous toxicant.

In this study, we aim to identify biomarkers for gastric cancer metastasis using a quantitative proteomics approach. The proteins extracted from a panel of 4 gastric cancer cell lines, two derived from primary cancer (AGS, FU97) and two from lymph node metastasis (AZ521, MKN7), were labeled with iTRAQ (8-plex) reagents and analyzed by 2D-LC-MALDI-TOF/TOF MS. In total, 641 proteins were identified with at least a 95% confidence. Using cutoff values of1.5 and0.67, 19 proteins were found to be up-regulated and 34 were down-regulated in the metastatic versus primary gastric cancer cell lines respectively. Several of these dysregulated proteins, including caldesmon, were verified using Western blotting. It was found that caldesmon expression was decreased in the two metastasis-derived cell lines, and this was confirmed by further analysis of 7 gastric cancer cell lines. Furthermore, immunohistochemical staining of 9 pairs of primary gastric cancer and the matched lymph node metastasis tissue also corroborated this observation. Finally, knockdown of caldesmon using siRNA in AGS and FU97 gastric cancer cells resulted in an increase in cell migration and invasion, while the overexpression of caldesmon in AZ521 cells led to a decrease in cell migration and invasion. This study has thus established the potential role of caldesmon in gastric cancer metastasis, and further functional studies are underway to delineate the underlying mechanism of action of this protein.

Butyrate and its analogues have long been investigated as potential chemotherapeutic agents. Our previous structure-activity relationship studies of butyrate analogues revealed that 4-benzoylbutyrate had comparable in vitro effects to butyrate when used to treat HT29 and HCT116 colorectal cancer cell lines. The aim of this study was to identify potential mechanisms associated with the antitumorigenic effects of 4-benzoylbutyrate. In this study, butyrate, 3-hydroxybutyrate and 4-benzoylbutyrate were also investigated for their effects on histone deacetylase (HDAC) activity and histone H4 acetylation in HT29 and HCT116 cells. The biological effects of these analogues on HT29 cells were further investigated using quantitative proteomics to determine the proteins potentially involved in their apoptotic and antiproliferative effects. Because 3-hydroxybutyrate had minimal to no effect on apoptosis, proliferation or HDAC activity, this analogue was used to identify differentially expressed proteins that were potentially specific to the apoptotic effects of butyrate and/or 4-benzoylbutyrate. Butyrate treatment inhibited HDAC activity and induced H4 acetylation. 4-Benzoylbutyrate inhibited HDAC activity but failed to enhance H4 acetylation. Proteomic analysis revealed 20 proteins whose levels were similarly altered by both butyrate and 4-benzoylbutyrate. Proteins that showed common patterns of differential regulation in the presence of either butyrate or 4-benzoylbutyrate included c-Myc transcriptional targets, proteins involved in ER homeostasis, signal transduction pathways and cell energy metabolism. Although an additional 23 proteins were altered by 4-benzoylbutyrate uniquely, further work is required to understand the mechanisms involved in its apoptotic effects. Refereed/Peer-reviewed

This study compared the whole cell proteome profiles of two isogenic colorectal cancer (CRC) cell lines (primary SW480 cell line and its lymph node metastatic variant SW620), as an in vitro metastatic model, to gain an insight into the molecular events of CRC metastasis. Using iTRAQ (isobaric tags for relative and absolute quantitation) based shotgun proteomics approach, we identified 1140 unique proteins, out of which 147 were found to be significantly altered in the metastatic cell. Ingenuity pathway analysis with those significantly altered proteins, revealed cellular organization and assembly as the top-ranked altered biological function. Differential expression pattern of 6 candidate proteins were validated by Western blot. Among these, the low expression level of β-catenin combined with the up-regulation of CacyBP (Calcyclin binding Protein), a β-catenin degrading protein, in the metastatic cell provided a rational guide for the downstream functional assays. The relative expression pattern of these two proteins was further validated in three other CRC cells by Western blot and quantitative immunofluorescence studies. Overexpression of CacyBP in three different primary CRC cell lines showed significant reduction in adhesion characteristics as well as cellular β-catenin level as confirmed by our experiments, indicating the possible involvement of CacyBP in CRC metastasis. In short, this study demonstrates successful application of a quantitative proteomics approach to identify novel key players for CRC metastasis, which may serve as biomarkers and/or drug targets to improve CRC therapy.