Hwee Tong Tan

Serum autoantibodies as biomarkers for early cancer detection

Autoantibodies against autologus tumor‐associated antigens have been detected in the asymptomatic stage of cancer and can thus serve as biomarkers for early cancer diagnosis. Moreover, because autoantibodies are found in sera, they can be screened easily using a noninvasive approach. Consequently, many studies have been initiated to identify novel autoantibodies relevant to various cancer types. To facilitate autoantibody discovery, approaches that allow the simultaneous identification of multiple autoantibodies are preferred. Five such techniques – SEREX, phage display, protein microarray, SERPA and MAPPing – are discussed here. In the second part of this review, we discussed autoantibodies found in the five most common cancers (lung, breast, colorectal, stomach and liver). The discovery of panels of tumor‐associated antigens and autoantibody signatures with high sensitivity and specificity would aid in the development of diagnostics, prognostics and therapeutics for cancer patients.

Membrane proteins and membrane proteomics

Biological membranes form an essential barrier between living cells and their external environments, as well as serve to compartmentalize intracellular organelles within eukaryotes. The latter includes membranes that envelope the nucleus, the outer and inner membranes of the mitochondria, membrane cisternae complex of the ER, Golgi apparatus, as well as lysosomes and secretory vesicles. Depending on their localizations in the whole organism and also within the cell, these membranes have different, highly specialized functions. Although 30% of naturally occurring proteins are predicted to be embedded in biological membranes, membrane proteomics is traditionally understudied due to difficulties in solubilizing, separating, and identifying membrane proteins. Given the importance of membrane proteins in the various cellular processes listed in this review, as well as the roles they play in diseases and their potential as drug targets, it is imperative that this class of proteins be better studied. With the recent advancement in technology, it is expected that some of the difficulties in membrane proteomics will be overcome, yielding new data on membrane proteins.

Quantitative and Temporal Proteome Analysis of Butyrate-treated Colorectal Cancer Cells

Colorectal cancer is one of the most common cancers in developed countries, and its incidence is negatively associated with high dietary fiber intake. Butyrate, a short-chain fatty acid fermentation by-product of fiber induces cell maturation with the promotion of growth arrest, differentiation, and/or apoptosis of cancer cells. The stimulation of cell maturation by butyrate in colonic cancer cells follows a temporal progression from the early phase of growth arrest to the activation of apoptotic cascades. Previously we performed two-dimensional DIGE to identify differentially expressed proteins induced by 24-h butyrate treatment of HCT-116 colorectal cancer cells. Herein we used quantitative proteomics approaches using iTRAQ (isobaric tags for relative and absolute quantitation), a stable isotope labeling methodology that enables multiplexing of four samples, for a temporal study of HCT-116 cells treated with butyrate. In addition, cleavable ICAT, which selectively tags cysteine-containing proteins, was also used, and the results complemented those obtained from the iTRAQ strategy. Selected protein targets were validated by real time PCR and Western blotting. A model is proposed to illustrate our findings from this temporal analysis of the butyrate-responsive proteome that uncovered several integrated cellular processes and pathways involved in growth arrest, apoptosis, and metastasis. These signature clusters of butyrate-regulated pathways are potential targets for novel chemopreventive and therapeutic drugs for treatment of colorectal cancer.

Identification of Key Players for Colorectal Cancer Metastasis by iTRAQ Quantitative Proteomics Profiling of Isogenic SW480 and SW620 Cell Lines

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.

Subcellular fractionation methods and strategies for proteomics.

Developments in subcellular fractionation strategies have provided the means to profile and analyze the protein composition of organelles and cellular structures by proteomics. Here, we review the application of classical (e.g. density gradient centrifugation) and emerging sophisticated techniques (fluorescent‐assisted organelle sorting) in the fractionation, and statistical/bioinformatics tools for the prediction of protein localization in subcellular proteomics. We also review the validation methods currently used (such as microscopy, RNA interference and multiple reaction monitoring) and discuss the importance of verification of the results obtained in subcellular proteomics. Finally, the numerous challenges facing subcellular proteomics including the dynamics of organelles are being examined. However, complementary approaches such as modern statistics, bioinformatics and large‐scale integrative analysis are beginning to emerge as powerful tools to proteomics for analyzing subcellular organelles and structures.

Mining the Gastric Cancer Secretome: Identification of GRN as a Potential Diagnostic Marker for Early Gastric Cancer

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.

Enhancing gold recovery from electronic waste via lixiviant metabolic engineering in Chromobacterium violaceum

Conventional leaching (extraction) methods for gold recovery from electronic waste involve the use of strong acids and pose considerable threat to the environment. The alternative use of bioleaching microbes for gold recovery is non-pollutive and relies on the secretion of a lixiviant or (bio)chemical such as cyanide for extraction of gold from electronic waste. However, widespread industrial use of bioleaching microbes has been constrained by the limited cyanogenic capabilities of lixiviant-producing microorganisms such as Chromobacterium violaceum. Here we show the construction of a metabolically-engineered strain of Chromobacterium violaceum that produces more (70%) cyanide lixiviant and recovers more than twice as much gold from electronic waste compared to wild-type bacteria. Comparative proteome analyses suggested the possibility of further enhancement in cyanogenesis through subsequent metabolic engineering. Our results demonstrated the utility of lixiviant metabolic engineering in the construction of enhanced bioleaching microbes for the bioleaching of precious metals from electronic waste.

Identification and Functional Validation of Caldesmon as a Potential Gastric Cancer Metastasis-associated Protein

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 of >1.5 and <0.67, 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.

Novel proteomic biomarker panel for prediction of aggressive metastatic hepatocellular carcinoma relapse in surgically resectable patients.

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.

Analysis of colorectal cancer glyco-secretome identifies laminin β-1 (LAMB1) as a potential serological biomarker for colorectal cancer

The high mortality rate in colorectal cancer is mostly ascribed to metastasis, but the only clinical biomarker available for disease monitoring and prognosis is the carcinoembryonic antigen (CEA). However, the prognostic utility of CEA remains controversial. In an effort to identify novel biomarkers that could be potentially translated for clinical use, we collected the secretomes from the colon adenocarcinoma cell line HCT‐116 and its metastatic derivative, E1, using the hollow fiber culture system, and utilized the multilectin affinity chromatography approach to enrich for the secreted glycoproteins (glyco‐secretome). The HCT‐116 and E1 glyco‐secretomes were compared using the label‐free quantitative SWATH‐MS technology, and a total of 149 glycoproteins were differentially secreted in E1 cells. Among these glycoproteins, laminin β‐1 (LAMB1), a glycoprotein not previously known to be secreted in colorectal cancer cells, was observed to be oversecreted in E1 cells. In addition, we showed that LAMB1 levels were significantly higher in colorectal cancer patient serum samples as compared to healthy controls when measured using ELISA. ROC analyses indicated that LAMB1 performed better than CEA at discriminating between colorectal cancer patients from controls. Moreover, the diagnostic performance was further improved when LAMB1 was used in combination with CEA.