Incorporating significant amino acid pairs to identify O-linked glycosylation sites on transmembrane proteins and non-transmembrane proteins

Background  

While occurring enzymatically in biological systems, O-linked glycosylation affects protein folding, localization and trafficking, protein solubility, antigenicity, biological activity, as well as cell-cell interactions on membrane proteins. Catalytic enzymes involve glycotransferases, sugar-transferring enzymes and glycosidases which trim specific monosaccharides from precursors to form intermediate structures. Due to the difficulty of experimental identification, several works have used computational methods to identify glycosylation sites.     

A comparative study of recombinant and native frutalin binding to human prostate tissues

Background  

Numerous studies indicate that cancer cells present an aberrant glycosylation pattern that can be detected by lectin histochemistry. Lectins have shown the ability to recognise these modifications in several carcinomas, namely in the prostate carcinoma, one of the most lethal diseases in man. Thus, the aim of this work was to investigate if the α-D-galactose-binding plant lectin frutalin is able to detect such changes in the referred carcinoma. Frutalin was obtained from different sources namely, its natural source (plant origin) and a recombinant source (Pichia expression system). Finally, the results obtained with the two lectins were compared and their potential use as prostate tumour biomarkers was discussed.     

Spatial partitioning of secretory cargo from Golgi resident proteins in live cells

Background  

To maintain organelle integrity, resident proteins must segregate from itinerant cargo during secretory transport. However, Golgi resident enzymes must have intimate access to secretory cargo in order to carry out glycosylation reactions. The amount of cargo and associated membrane may be significant compared to the amount of Golgi membrane and resident protein, but upon Golgi exit, cargo and resident are efficiently sorted. How this occurs in live cells is not known.     

Glycans as cancer biomarkers

Background

Non-invasive biomarkers, such as those from serum, are ideal for disease prognosis, staging and monitoring. In the past decade, our understanding of the importance of glycosylation changes with disease has evolved.

Scope of review

We describe potential biomarkers derived from serum glycoproteins for liver, pancreatic, prostate, ovarian, breast, lung and stomach cancers. Methods for glycan analysis have progressed and newly developed high-throughput platform technologies have enabled the analysis of large cohorts of samples in an efficient manner. We also describe this evolution and trends to follow in the future.

Major conclusions

Many convincing examples of aberrant glycans associated with cancer have come about from glycosylation analyses. Most studies have been carried out to identify changes in serum glycan profiles or through the isolation and identification of glycoproteins that contain these irregular glycan structures. In a majority of cancers the fucosylation and sialylation expression are found to be significantly modified. Therefore, these aberrations in glycan structures can be utilized as targets to improve existing cancer biomarkers.

General significance

The ability to distinguish differences in the glycosylation of proteins between cancer and control patients emphasizes glycobiology as a promising field for potential biomarker identification. Furthermore, the high-throughput and reproducible nature of the chromatography platform have highlighted extensive applications in biomarker discovery and allowed integration of glycomics with other -omics fields, such as proteomics and genomics, making systems glycobiology a reality. This article is part of a Special Issue entitled Glycoproteomics.     

Identification of O-Linked Glycoproteins Binding to the Lectin Helix pomatia Agglutinin as Markers of Metastatic Colorectal Cancer

Background

Protein glycosylation is an important post-translational modification shown to be altered in all tumour types studied to date. Mucin glycoproteins have been established as important carriers of O-linked glycans but other glycoproteins exhibiting altered glycosylation repertoires have yet to be identified but offer potential as biomarkers for metastatic cancer.

Methodology

In this study a glycoproteomic approach was used to identify glycoproteins exhibiting alterations in glycosylation in colorectal cancer and to evaluate the changes in O-linked glycosylation in the context of the p53 and KRAS (codon 12/13) mutation status. Affinity purification with the carbohydrate binding protein from Helix pomatia agglutinin (HPA) was coupled to 2-dimensional gel electrophoresis with mass spectrometry to enable the identification of low abundance O-linked glycoproteins from human colorectal cancer specimens.

Results

Aberrant O-linked glycosylation was observed to be an early event that occurred irrespective of the p53 and KRAS status and correlating with metastatic colorectal cancer. Affinity purification using the lectin HPA followed by proteomic analysis revealed annexin 4, annexin 5 and CLCA1 to be increased in the metastatic colorectal cancer specimens. The results were validated using a further independent set of specimens and this showed a significant association between the staining score for annexin 4 and HPA and the time to metastasis; independently (annexin A4: Chi square 11.45, P = 0.0007; HPA: Chi square 9.065, P = 0.0026) and in combination (annexin 4 and HPA combined: Chi square 13.47; P = 0.0002).

Conclusion

Glycoproteins showing changes in O-linked glycosylation in metastatic colorectal cancer have been identified. The glycosylation changes were independent of p53 and KRAS status. These proteins offer potential for further exploration as biomarkers and potential targets for metastatic colorectal cancer.     

Expression of Beclin Family Proteins Is Associated with Tumor Progression in Oral Cancer

Background

Beclin 1 and Beclin 2 are autophagy-related proteins that show similar amino acid sequences and domain structures. Beclin 1 established the first connection between autophagy and cancer. However, the role of Beclin 2 in cancer is unclear. The aims of this study were to analyze Beclin 1 and Beclin 2 expressions in oral cancer tissues and in cell lines, and to evaluate their possible roles in cancer progression.

Methods

We investigated Beclin 1 and Beclin 2 expressions by immunohistochemistry in 195 cases of oral cancer. The prognostic roles of Beclin 1 and Beclin 2 were analyzed statistically. In vitro, overexpression and knockdown of Beclin proteins were performed on an oral cancer cell line, SAS. The immunofluorescence and autophagy flux assays confirmed that Beclin proteins were involved in autophagy. The impacts of Beclin 1 and Beclin 2 on autophagy and tumor growth were evaluated by conversion of LC3-I to LC3-II and by clonogenic assays, respectively.

Results

Oral cancer tissues exhibited aberrant expressions of Beclin 1 and Beclin 2. The cytoplasmic Beclin 1 and Beclin 2 expressions were unrelated in oral cancer tissues. In survival analyses, high cytoplasmic Beclin 1 expression was associated with low disease specific survival, and negative nuclear Beclin 1 expression was associated with high recurrent free survival. Patients with either high or low cytoplasmic Beclin 2 expression had significantly lower overall survival and disease specific survival rates than those with moderate expression. In oral cancer cells, overexpression of either Beclin 1 or Beclin 2 led to autophagy activation and increased clonogenic survival; knockdown of Beclin 2 impaired autophagy and increased clonogenic survival.

Conclusions

Our results indicated that distinct patterns of Beclin 1 and Beclin 2 were associated with aggressive clinical outcomes. Beclin 1 overexpression, as well as Beclin 2 overexpression and depletion, contributed to tumor growth. These findings suggest Beclin proteins are associated with tumorigenesis.     

Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

Background  

Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes.     

Identification of N-Glycosylation in Hepatocellular Carcinoma Patients’ Serum with a Comparative Proteomic Approach

Aim

This study is to explore the different expressions of serum N-glycoproteins and glycosylation sites between hepatocellular carcinoma (HCC) patients and healthy controls.

Method

We combined high abundant proteins depletion and hydrophilic affinity method to enrich the glycoproteins. Through liquid chromatography-tandem mass spectrometry (LC-MS/MS), we extensively surveyed different expressions of glycosylation sites and glycoproteins between the two groups.

Result

This approach identified 152 glycosylation sites and 54 glycoproteins expressed differently between HCC patients and healthy controls. With the absolute values of Pearson coefficients of at least 0.8, eight proteins were identified significantly up or down regulated in HCC serum. Those proteins are supposed to be involved in several biological processes, cellular components and molecular functions of hepatocarcinogenesis. Several of them had been reported abnormally regulated in several kinds of malignant tumors, and may be promising biomarkers of HCC.

Conclusion

Our work provides a systematic and quantitative method of glycoproteomics and demonstrates some key changes in clinical HCC serum. These proteomic signatures may help to unveil the underlying mechanisms of hepatocarcinogenesis and may be useful for the exploration of candidate biomarkers.     

Characterisation and correction of signal fluctuations in successive acquisitions of microarray images

Background  

In cancer studies, it is common that multiple microarray experiments are conducted to measure the same clinical outcome and expressions of the same set of genes. An important goal of such experiments is to identify a subset of genes that can potentially serve as predictive markers for cancer development and progression. Analyses of individual experiments may lead to unreliable gene selection results because of the small sample sizes. Meta analysis can be used to pool multiple experiments, increase statistical power, and achieve more reliable gene selection. The meta analysis of cancer microarray data is challenging because of the high dimensionality of gene expressions and the differences in experimental settings amongst different experiments.     

Glycosylation site prediction using ensembles of Support Vector Machine classifiers

Background  

Glycosylation is one of the most complex post-translational modifications (PTMs) of proteins in eukaryotic cells. Glycosylation plays an important role in biological processes ranging from protein folding and subcellular localization, to ligand recognition and cell-cell interactions. Experimental identification of glycosylation sites is expensive and laborious. Hence, there is significant interest in the development of computational methods for reliable prediction of glycosylation sites from amino acid sequences.     

Prognostic Value of Malic Enzyme and ATP-Citrate Lyase in Non-Small Cell Lung Cancer of the Young and the Elderly

Background

Lung cancer is the leading cause of death among malignancies worldwide. Understanding its biology is therefore of pivotal importance to improve patient’s prognosis. In contrast to non-neoplastic tissues, cancer cells utilize glucose mainly for production of basic cellular modules ‘(i.e. nucleotides, aminoacids, fatty acids). In cancer, Malic enzyme (ME) and ATP-citrate lyase (ACLY) are key enzymes linking aerobic glycolysis and fatty acid synthesis and may therefore be of biological and prognostic significance in non-small cell lung cancer (NSCLC).

Material and Methods

ME and ACLY expression was analyzed in 258 NSCLC in correlation with clinico-pathological parameters including patient’s survival.

Results

Though, overall expression of both enzymes correlated positively, ACLY was associated with local tumor stage, whereas ME correlated with occurrence of mediastinal lymph node metastases. Young patients overexpressing ACLY and/or ME had a significantly longer overall survival. This proved to be an independent prognostic factor. This contrasts older NSCLC patients, in whom overexpression of ACLY and/or ME appears to predict the opposite.

Conclusion

In NSCLC, ME and ACLY show different enzyme expressions relating to local and mediastinal spread. Most important, we detected an inverse prognostic impact of ACLY and/or ME overexpression in young and elderly patients. It can therefore be expected, that treatment of NSCLC especially, if targeting metabolic pathways, requires different strategies in different age groups.     

Functional network of glycan-related molecules: Glyco-Net in Glycoconjugate Data Bank

Background  

Glycans are involved in a wide range of biological process, and they play an essential role in functions such as cell differentiation, cell adhesion, pathogen-host recognition, toxin-receptor interactions, signal transduction, cancer metastasis, and immune responses. Elucidating pathways related to post-translational modifications (PTMs) such as glycosylation are of growing importance in post-genome science and technology. Graphical networks describing the relationships among glycan-related molecules, including genes, proteins, lipids and various biological events are considered extremely valuable and convenient tools for the systematic investigation of PTMs. However, there is no database which dynamically draws functional networks related to glycans.     

An integrated analysis of molecular aberrations in NCI-60 cell lines

Background  

Cancer is a complex disease where various types of molecular aberrations drive the development and progression of malignancies. Large-scale screenings of multiple types of molecular aberrations (e.g., mutations, copy number variations, DNA methylations, gene expressions) become increasingly important in the prognosis and study of cancer. Consequently, a computational model integrating multiple types of information is essential for the analysis of the comprehensive data.     

A combined approach to data mining of textual and structured data to identify cancer-related targets

Background  

We present an effective, rapid, systematic data mining approach for identifying genes or proteins related to a particular interest. A selected combination of programs exploring PubMed abstracts, universal gene/protein databases (UniProt, InterPro, NCBI Entrez), and state-of-the-art pathway knowledge bases (LSGraph and Ingenuity Pathway Analysis) was assembled to distinguish enzymes with hydrolytic activities that are expressed in the extracellular space of cancer cells. Proteins were identified with respect to six types of cancer occurring in the prostate, breast, lung, colon, ovary, and pancreas.     

Estimating developmental states of tumors and normal tissues using a linear time-ordered model

Background  

Tumor cells are considered to have an aberrant cell state, and some evidence indicates different development states appearing in the tumorigenesis. Embryonic development and stem cell differentiation are ordered processes in which the sequence of events over time is highly conserved. The "cancer attractor" concept integrates normal developmental processes and tumorigenesis into a high-dimensional "cell state space", and provides a reasonable explanation of the relationship between these two biological processes from theoretical viewpoint. However, it is hard to describe such relationship by using existed experimental data; moreover, the measurement of different development states is also difficult.     

Moisture-induced solid state instabilities in α-chymotrypsin and their reduction through chemical glycosylation

Background  

Protein instability remains the main factor limiting the development of protein therapeutics. The fragile nature (structurally and chemically) of proteins makes them susceptible to detrimental events during processing, storage, and delivery. To overcome this, proteins are often formulated in the solid-state which combines superior stability properties with reduced operational costs. Nevertheless, solid protein pharmaceuticals can also suffer from instability problems due to moisture sorption. Chemical protein glycosylation has evolved into an important tool to overcome several instability issues associated with proteins. Herein, we employed chemical glycosylation to stabilize a solid-state protein formulation against moisture-induced deterioration in the lyophilized state.