Identification of hydrophobic proteins as biomarker candidates for colorectal cancer

Circular RNAs and gastrointestinal cancers: Epigenetic regulators with a prognostic and therapeutic role

Both environmental and genetic factors are involved in the initiation and development of gastrointestinal cancer. Covalent closed circular RNAs (circRNAs) are produced by a mechanism called "back-splicing" from mRNAs. They are highly stable and show cell and tissue specific expression patterns. Although some functions such as "microRNA sponge" and "RNA binding protein sponge" have been reported for a small number of circRNAs, the function of thousands of other circRNAs is still unknown. Dysregulation of circRNAs has been reported in many GI cancers and are involved in metastasis and invasion. CircRNAs have been reported to be useful as prognostic markers and targets for developing new treatments. We first describe the properties and biogenesis of circRNAs. We then summarize recent reports about circRNA functions, expression status, and their potential to be used as biomarkers in GI cancers including, gastric cancer, colorectal cancer, esophageal cancer, hepatocellular carcinoma, gallbladder cancer and pancreatic cancer.

Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.

Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer

About one million people per year develop colorectal cancer (CRC) and approximately half of them die. The extent of the disease (i.e. local invasion at the time of diagnosis) is a key prognostic factor. The 5-year survival rate is almost 90% in the case of delimited CRC and 10% in the case of metastasized CRC. Hence, one of the great challenges in the battle against CRC is to improve early diagnosis strategies. Large-scale proteomic approaches are widely used in cancer research to search for novel biomarkers. Such biomarkers can help in improving the accuracy of the diagnosis and in the optimization of personalized therapy. Herein, we provide an overview of studies published in the last 5 years on CRC that led to the identification of protein biomarkers suitable for clinical application by using proteomic approaches. We discussed these findings according to biomarker application, including also the role of protein phosphorylation and cancer stem cells in biomarker discovery. Our review provides a cross section of scientific approaches and can furnish suggestions for future experimental strategies to be used as reference by scientists, clinicians and researchers interested in proteomics for biomarker discovery.

Proteomics for discovery of candidate colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers.

Improving colorectal cancer management: the potential of proteomics

Colorectal cancer (CRC) is the third most common cancer worldwide. Successful treatment is heavily dependent on tumor stage at the time of detection, but unfortunately CRC is often only detected in advanced stages. New biomarkers in the form of genes or proteins that can be used for diagnosis, prognostication, follow-up, and treatment selection and monitoring could be of great benefit for the management of CRC. Furthermore, proteins could prove valuable new targets for therapy. Therefore, clinical proteomics has gained a lot of scientific interest in this regard. To get an overall insight into the extent to which this research has contributed to a better management of CRC, we give a comprehensive overview of the results of proteomics research on CRC, focusing on expression proteomics, in other words, protein profiling studies. Furthermore, we evaluate the potential of the discriminating proteins identified in this research for clinical use as biomarkers for (early) diagnosis, prognosis and follow-up of CRC or as targets for new therapeutic regimens.

Classification of lung cancer tumors based on structural and physicochemical properties of proteins by bioinformatics models

Rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important in diagnosis of this disease. Furthermore sequence-derived structural and physicochemical descriptors are very useful for machine learning prediction of protein structural and functional classes, classifying proteins and the prediction performance. Herein, in this study is the classification of lung tumors based on 1497 attributes derived from structural and physicochemical properties of protein sequences (based on genes defined by microarray analysis) investigated through a combination of attribute weighting, supervised and unsupervised clustering algorithms. Eighty percent of the weighting methods selected features such as autocorrelation, dipeptide composition and distribution of hydrophobicity as the most important protein attributes in classification of SCLC, NSCLC and COMMON classes of lung tumors. The same results were observed by most tree induction algorithms while descriptors of hydrophobicity distribution were high in protein sequences COMMON in both groups and distribution of charge in these proteins was very low; showing COMMON proteins were very hydrophobic. Furthermore, compositions of polar dipeptide in SCLC proteins were higher than NSCLC proteins. Some clustering models (alone or in combination with attribute weighting algorithms) were able to nearly classify SCLC and NSCLC proteins. Random Forest tree induction algorithm, calculated on leaves one-out and 10-fold cross validation) shows more than 86% accuracy in clustering and predicting three different lung cancer tumors. Here for the first time the application of data mining tools to effectively classify three classes of lung cancer tumors regarding the importance of dipeptide composition, autocorrelation and distribution descriptor has been reported.

Secreted clusterin in colon tumor cell models and its potential as diagnostic marker for colorectal cancer

We studied the specific changes of the secreted protein clusterin and its cytoplasmic precursor regarding colorectal tumorigenesis, using in vitro differentiation of Caco-2 cells. In tumor-like stage, we observed an overexpression of both precursor and secreted clusterin, corroborated in the cell line SW-480. Noticeably, SW-620 cells (from a tumoral node, thus with metastatic capacity) did not show overexpression of either precursor or secreted clusterin, suggesting a downregulation related to local metastasis. We further investigated clusterin in serum, finding a significant increase in colorectal cancer patients, with 81% sensitivity, 79% specificity, and an area under the ROC curve of 0.85.

Desmin expression in colorectal cancer stroma correlates with advanced stage disease and marks angiogenic microvessels

Introduction

Biomarkers that improve stratification of colorectal cancer patients for adjuvant therapy versus resection alone, or that are predictive of response to therapeutic agents, have the potential to greatly improve patient selection for such therapies. The aim was to determine proteins differentially expressed within the malignant epithelial glands and closely associated stromal elements compared to matched normal mucosa, and to characterise the over-expression of one such protein as a potential biomarker.

Methods

Protein from laser microdissected tumor and normal mucosa was analysed by two dimensional difference gel electrophoresis (2D DIGE) and mass spectrometry to determine differentially over expressed tumor proteins. Tumor over-expression of one such protein, desmin, was quantified using immunofluorescence staining in a larger cohort. Dual staining for desmin and vimentin, or desmin and von Willebrand factor, was performed to determine the cell type of interest.

Results

Desmin expression was significantly increased between stage I and III tumors, (P < 0.0001), and stage II and III tumors, (P < 0.0001). Strong focal desmin expression was found in stroma directly adjacent to carcinomatous glands and microvessels. These cells showed co-localisation of desmin and vimentin in close association with cells expressing VWF, indicating they were pericytes. Significantly higher levels of desmin-positive pericytes were observed in late stage tumors, consistent with increased angiogenesis.

Conclusion

Pericyte coverage of vasculature is a marker of vessel maturation, hence desmin expression may have use as a marker for microvessel maturation. Clinical trials will be needed to determine its use in identifying tumors that will be less responsive to anti-angiogenic therapy.

Use of multiple reaction monitoring for multiplex analysis of colorectal cancer-associated proteins in human feces

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths worldwide with an annual incidence of almost a million cases and an annual mortality around 500,000. The fecal occult blood test is currently the first line method for CRC screening, but has unacceptably low sensitivity and specificity. Improved screening tests are therefore urgently required for early-stage CRC screening when therapy is most likely to be effective. We describe a discovery-based proteomics hypothesis using orthogonal multi-dimensional fractionation (1-D SDS-PAGE, RP-HPLC, size exclusion chromatography) to mine deep into the fecal proteome for the initial discovery process, which generated a library containing 108 human fecal proteins with the associated peptide and MS/MS data. These data were then used to develop and optimize a multiplex multiple reaction monitoring assay for 40 non-redundant human proteins present in the feces. To show proof of principal for clinical analysis, multiplex screening of these 40 proteins was carried out on fecal samples from eight CRC patient and seven normal volunteers. We identified 24 proteins consistently found in all samples and nine proteins found only in the CRC patients, showing the potential of this approach for the analysis of potential CRC biomarkers. Absolute quantitation using C-terminal isotopically labeled synthetic peptides corresponding to hemoglobin and carcinoembryonic antigen 5 was also performed.

A proteome analysis of the tetracyanonickelate (II) responses in Klebsiella oxytoca

Tetracyanonickelate (II) (TCN) has been proved to be degraded by Klebsiella oxytoca. In order to examine the physiological responses of TCN degradation by this bacterium, two-dimensional (2-DE) electrophoresis approach and Matrix-assisted laser desorption/ionization-time of flight-mass spectrometry allow us to identify 91 proteins spots that were significantly altered in the presence of 1 mM TCN in relative to that in 1 mM ammonia when K. oxytoca grown at the late-log phase. Among them, 43 proteins were successfully identified. Fractions enriched in hydrophobic proteins were obtained with a specific extraction method based on temperature-dependent phase partitioning with Triton X-114, with the successful identification of 26 proteins out of 41 differential proteins. Some proteins were related with TCN metabolism. OsmC-like protein, molecular chaperone DnaK, glutathione S-transferase, alkyl hydroperoxide reductase, DNA protection during starvation conditions and DNA binding ferritin-like protein can counteract the oxidative stress from TCN biodegradation. The nitrogenase had been suggested to participate in TCN degradation by K. oxytoca, and was upregulated in TCN-treated cells as expected. The induction of glutamine synthetase could enhance the assimilation of limited nitrogen source produced from the bioconversion of TCN into ammonia as the alternate nitrogen source for bacteria growth. These findings could provide new insights into the inducible mechanisms underlying the capacity of K. oxytoca to tolerate TCN stress.

Hydrophobic protein in colorectal cancer in relation to tumor stages and grades

AIM: To identify differentially expressed hydrophobic proteins in colorectal cancer.

METHODS: Eighteen pairs of colorectal cancerous tissues in addition to tissues from normal mucosa were analysed. Hydrophobic proteins were extracted from the tissues, separated using 2-D gel electrophoresis and analysed using Liquid Chromatography Tandem Mass Spectrometry (LC/MS/MS). Statistical analysis of the proteins was carried out in order to determine the significance of each protein to colorectal cancer (CRC) and also their relation to CRC stages, grades and patients’ gender.

RESULTS: Thirteen differentially expressed proteins which were expressed abundantly in either cancerous or normal tissues were identified. A number of these proteins were found to relate strongly with a particular stage or grade of CRC. In addition, the association of these proteins with patient gender also appeared to be significant.

CONCLUSION: Stomatin-like protein 2 was found to be a promising biomarker for CRC, especially in female patients. The differentially expressed proteins identified were associated with CRC and may act as drug target candidates.

Murine fecal proteomics: a model system for the detection of potential biomarkers for colorectal cancer

Tumor related products shed into the feces offer a potential source of biomarkers for the detection of colorectal cancer (CRC). Using SDS-PAGE followed by nanoflow reversed-phased LC-MS/MS to analyse fecal samples from Apc(Min/+) mice (that develop spontaneous multiple intestinal neoplasia with age) we have identified 336 proteins (115 proteins of murine origin, 201 from fecal bacteria, 18 associated with food intake and 2 of apparent parasitic origin). 75% of the murine proteins identified in this study are predicted to be extracellular or associated with the cell plasma membrane. Of these proteins, a number of the murine homologues of colorectal cancer associated proteins (CCAP) such as hemoglobin, haptoglobin, hemopexin, alpha-2-macroglobulin and cadherin-17 have been identified, demonstrating the potential of fecal proteomics for detecting potential biomarkers and paving the way for subsequent MS/MS based biomarker studies on similar human samples.