Proteomics in colorectal cancer translational research: Biomarker discovery for clinical applications

The impact of nitric oxide on HER family post-translational modification and downstream signaling in cancer

The human epidermal growth factor receptor (HER) family consists of four members, activated by two families of ligands. They are known for mediating cell-cell interactions in organogenesis, and their deregulation has been associated with various cancers, including breast and esophageal cancers. In particular, aberrant epidermal growth factor receptor (EGFR) and HER2 signaling drive disease progression and result in poorer patient outcomes. Nitric oxide (NO) has been proposed as an alternative activator of the HER family and may play a role in this aberrant activation due to its ability to induce s-nitrosation and phosphorylation of the EGFR. This review discusses the potential impact of NO on HER family activation and downstream signaling, along with its role in the efficacy of therapeutics targeting the family.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

Three-dimensional heterotypic colorectal cancer spheroid models for evaluation of drug response

Colorectal cancer (CRC) is a leading cause of death worldwide. Improved preclinical tumor models are needed to make treatment screening clinically relevant and address disease mortality. Advancements in 3D cell culture have enabled a greater recapitulation of the architecture and heterogeneity of the tumor microenvironment (TME). This has enhanced their pathophysiological relevance and enabled more accurate predictions of tumor progression and drug response in patients. An increasing number of 3D CRC spheroid models include cell populations such as cancer-associated fibroblasts (CAFs), endothelial cells (ECs), immune cells, and gut bacteria to better mimic the in vivo regulation of signaling pathways. Furthermore, cell heterogeneity within the 3D spheroid models enables the identification of new therapeutic targets to develop alternative treatments and test TME-target therapies. In this mini review, we present the advances in mimicking tumor heterogeneity in 3D CRC spheroid models by incorporating CAFs, ECs, immune cells, and gut bacteria. We introduce how, in these models, the diverse cells influence chemoresistance and tumor progression of the CRC spheroids. We also highlight important parameters evaluated during drug screening in the CRC heterocellular spheroids.

Proteomic profiling and network biology of colorectal cancer liver metastasis

INTRODUCTION

Tissue-based proteomic studies of colorectal cancer (CRC) metastasis have delivered fragmented results, with very few therapeutic targets and prognostic biomarkers moving beyond the discovery phase. This situation is likely due to the difficulties in obtaining and analyzing large numbers of patient-derived metastatic samples, the own heterogeneity of CRC, and technical limitations in proteomics discovery. As an alternative, metastatic CRC cell lines provide a flexible framework to investigate the underlying mechanisms and network biology of metastasis for target discovery.

AREAS COVERED

In this perspective, we comment on different in-depth proteomic studies of metastatic versus non-metastatic CRC cell lines. Identified metastasis-related proteins are introduced and discussed according to the spatial location in different cellular fractions, with special emphasis on membrane/adhesion proteins, secreted proteins, and nuclear factors, including miRNAs associated with liver metastasis. Moreover, we analyze the biological significance and potential therapeutic applications of the identified liver metastasis-related proteins.

EXPERT OPINION

The combination of protein discovery and functional analysis is the only way to accelerate the progress to clinical translation of the proteomic-derived findings in a relatively fast pace. Patient-derived organoids represent a promising alternative to patient tissues and cell lines, but further optimizations are still required for achieving solid and reproducible results.

Potential prognostic and predictive value of UBE2N, IMPDH1, DYNC1LI1 and HRASLS2 in colorectal cancer stool specimens

Colorectal cancer (CRC) is the most common gastrointestinal malignancy worldwide. The poor specificity and sensitivity of the fecal occult blood test has prompted the development of CRC-related genetic markers for CRC screening and treatment. Gene expression profiles in stool specimens are effective, sensitive and clinically applicable. Herein, a novel advantage of using cells shed from the colon is presented for cost-effective CRC screening. Molecular panels were generated through a series of leave-one-out cross-validation and discriminant analyses. A logistic regression model following reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry was used to validate a specific panel for CRC prediction. The panel, consisting of ubiquitin-conjugating enzyme E2 N (UBE2N), inosine monophosphate dehydrogenase 1 (IMPDH1), dynein cytoplasmic 1 light intermediate chain 1 (DYNC1LI1) and phospholipase A and acyltransferase 2 (HRASLS2), accurately recognized patients with CRC and could thus be further investigated as a potential prognostic and predictive biomarker for CRC. UBE2N, IMPDH1 and DYNC1LI1 expression levels were upregulated and HRASLS2 expression was downregulated in CRC tissues. The predictive power of the panel was 96.6% [95% confidence interval (CI), 88.1-99.6%] sensitivity and 89.7% (95% CI, 72.6-97.8%) specificity at a predicted cut-off value at 0.540, suggesting that this four-gene panel testing of stool specimens can faithfully mirror the state of the colon. On the whole, the present study demonstrates that screening for CRC or cancer detection in stool specimens collected non-invasively does not require the inclusion of an excessive number of genes, and colonic defects can be identified via the detection of an aberrant protein in the mucosa or submucosa.

Application of peptide biomarkers in life analysis based on liquid chromatography-mass spectrometry technology

Biomedicine is developing rapidly in the 21st century. Among them, the qualitative and quantitative analysis of peptide biomarkers is of considerable importance for the diagnosis and therapy of diseases and the quality evaluation of drugs and food. The identification and quantitative analysis of peptides have been going on for decades. Traditionally, immunoassays or biological assays are generally used to quantify peptides in biological matrices. However, the selectivity and sensitivity of these methods cannot meet the requirements of the application. The separation and analysis technique of liquid chromatography-mass spectrometry (LC-MS) supplies a reliable alternative. In contrast to immunoassays, LC-MS methods are capable of providing the analytical prowess necessary to satisfy the demands of peptide biomarker research in the life sciences arena. This review article provides a historical account of the in-roads made by LC-MS technology for the detection of peptide biomarkers in the past 10 years, with the focus on the qualification/quantification developments and their applications.

Machine Learning-Based Identification of Colon Cancer Candidate Diagnostics Genes

Simple Summary

We developed a predictive approach using different machine learning methods to identify a number of genes that can potentially serve as novel diagnostic colon cancer biomarkers.

Abstract

Background: Colorectal cancer (CRC) is the third leading cause of cancer-related death and the fourth most commonly diagnosed cancer worldwide. Due to a lack of diagnostic biomarkers and understanding of the underlying molecular mechanisms, CRC’s mortality rate continues to grow. CRC occurrence and progression are dynamic processes. The expression levels of specific molecules vary at various stages of CRC, rendering its early detection and diagnosis challenging and the need for identifying accurate and meaningful CRC biomarkers more pressing. The advances in high-throughput sequencing technologies have been used to explore novel gene expression, targeted treatments, and colon cancer pathogenesis. Such approaches are routinely being applied and result in large datasets whose analysis is increasingly becoming dependent on machine learning (ML) algorithms that have been demonstrated to be computationally efficient platforms for the identification of variables across such high-dimensional datasets. Methods: We developed a novel ML-based experimental design to study CRC gene associations. Six different machine learning methods were employed as classifiers to identify genes that can be used as diagnostics for CRC using gene expression and clinical datasets. The accuracy, sensitivity, specificity, F1 score, and area under receiver operating characteristic (AUROC) curve were derived to explore the differentially expressed genes (DEGs) for CRC diagnosis. Gene ontology enrichment analyses of these DEGs were performed and predicted gene signatures were linked with miRNAs. Results: We evaluated six machine learning classification methods (Adaboost, ExtraTrees, logistic regression, naïve Bayes classifier, random forest, and XGBoost) across different combinations of training and test datasets over GEO datasets. The accuracy and the AUROC of each combination of training and test data with different algorithms were used as comparison metrics. Random forest (RF) models consistently performed better than other models. In total, 34 genes were identified and used for pathway and gene set enrichment analysis. Further mapping of the 34 genes with miRNA identified interesting miRNA hubs genes. Conclusions: We identified 34 genes with high accuracy that can be used as a diagnostics panel for CRC.

Molecular Network of Colorectal Cancer and Current Therapeutic Options

Colorectal cancer (CRC), a leading cause of cancer-related mortalities globally, results from the accumulation of multiple genetic and epigenetic alterations in the normal colonic and rectum epithelium, leading to the progression from colorectal adenomas to invasive carcinomas. Almost half of CRC patients will develop metastases in the course of the disease and most patients with metastatic CRC are incurable. Particularly, the 5-year survival rate of patients with stage 4 CRC at diagnosis is less than 10%. Although genetic understanding of these CRC tumors and paired metastases has led to major advances in elucidating early driver genes responsible for carcinogenesis and metastasis, the pathophysiological contribution of transcriptional and epigenetic aberrations in this malignancy which influence many central signaling pathways have attracted attention recently. Therefore, treatments that could affect several different molecular pathways may have pivotal implications for their efficacy. In this review, we summarize our current knowledge on the molecular network of CRC, including cellular signaling pathways, CRC microenvironment modulation, epigenetic changes, and CRC biomarkers for diagnosis and predictive/prognostic use. We also provide an overview of opportunities for the treatment and prevention strategies in this field.

A Review of HER4 (ErbB4) Kinase, Its Impact on Cancer, and Its Inhibitors

HER4 is a receptor tyrosine kinase that is required for the evolution of normal body systems such as cardiovascular, nervous, and endocrine systems, especially the mammary glands. It is activated through ligand binding and activates MAPKs and PI3K/AKT pathways. HER4 is commonly expressed in many human tissues, both adult and fetal. It is important to understand the role of HER4 in the treatment of many disorders. Many studies were also conducted on the role of HER4 in tumors and its tumor suppressor function. Mostly, overexpression of HER4 kinase results in cancer development. In the present article, we reviewed the structure, location, ligands, physiological functions of HER4, and its relationship to different cancer types. HER4 inhibitors reported mainly from 2016 to the present were reviewed as well.

Faecal Diagnostic Biomarkers for Colorectal Cancer

Simple Summary

Colorectal cancer (CRC) is a significant public health problem, being a major cause of cancer death worldwide. Hence, the identification of biomarkers able to support CRC detection is crucial. This work analyses a panel of six biomarkers, namely interleukin-6 (IL-6), tumour necrosis factor-alpha (TNF-α), matrix metalloproteinase (MMP)-2, MMP-9, haemoglobin (Hb) and M2-pyruvate kinase (M2-PK), in stool samples from patients with CRC, advanced adenomas, other lesions and healthy individuals. Our results indicate that the levels of Hb and M2-PK were increased in CRC patients in comparison to the controls. Moreover, the combination of these biomarkers increased the specificity or sensitivity for CRC detection and thus present potential for diagnosis of CRC.

Abstract

Background: Colorectal cancer (CRC) is a major cause of cancer-related death worldwide. Cancer progression, including invasion and metastasis, is a major cause of death among CRC patients. Current methods for CRC screening commonly consist of a combination of faecal immunochemical test (FIT) for stool occult blood detection and invasive procedures such as colonoscopy. Considering the slow progression of CRC, and that symptoms usually emerge at advanced stages, its early diagnostic can limit cancer’s spread and provide a successful treatment. Biomarkers have a high potential for the diagnosis of CRC in either blood or stool samples. Methods: In this study, we analysed the diagnostic value of six different biomarkers in stool samples of patients with CRC, advanced adenomas, other lesions and healthy individuals. We have also assessed the overall performance of the combination of these biomarkers for CRC detection. Results: The results indicate that haemoglobin (Hb) and M2-pyruvate kinase (M2-PK) levels were increased in CRC patients in comparison to the controls. Conversely, the concentrations of matrix metalloproteinase (MMP)-2, MMP-9, and tumour necrosis factor-alpha (TNF-α) were not significantly different between the tested groups. Conclusion: The combination of FIT-Hb with the M2-PK levels increased the specificity or sensitivity for CRC detection and thus present potential as faecal diagnostic biomarkers for CRC.

Comprehensive polar metabolomics and lipidomics profiling discriminates the transformed from the non-transformed state in colon tissue and cell lines

Colorectal cancer (CRC) is the fourth most lethal disease worldwide. Despite an urgent need for therapeutic advance, selective target identification in a preclinical phase is hampered by molecular and metabolic variations between cellular models. To foster optimal model selection from a translational perspective, we performed untargeted ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry-based polar metabolomics and lipidomics to non-transformed (CCD841-CON and FHC) and transformed (HCT116, HT29, Caco2, SW480 and SW948) colon cell lines as well as tissue samples from ten colorectal cancer patients. This unveiled metabolic signatures discriminating the transformed from the non-transformed state. Metabolites involved in glutaminolysis, tryptophan catabolism, pyrimidine, lipid and carnitine synthesis were elevated in transformed cells and cancerous tissue, whereas those involved in the glycerol-3-phosphate shuttle, urea cycle and redox reactions were lowered. The degree of glutaminolysis and lipid synthesis was specific to the colon cancer cell line at hand. Thus, our study exposed pathways that are specifically associated with the transformation state and revealed differences between colon cancer cell lines that should be considered when targeting cancer-associated pathways.

Co-culturing multicellular tumor models: Modeling the tumor microenvironment and analysis techniques

Advances in two-dimensional (2D) and three-dimensional (3D) cell culture over the last 10 years have led to the development of a plethora of methods for cultivating tumor models. More recently, cellular co-cultures have become a suitable testbed. The first portion of this review focuses on co-culturing methods that have been developed in recent years utilizing the multicellular tumor spheroid model. The latter portion describes techniques that are used to analyze the proteomes of mono- or co-cultured tumor models, with a focus on mass spectrometry (MS)-based analyses. Protein profiles are important indicators of the tumor heterogeneity. Therefore, there is a specific focus within this review on analysis by MS and MS imaging methods evaluating the proteomic profiles of 2D and 3D co-cultures. While these models are incredibly important for biological research, so far, they have not been widely explored on the proteomic level. With this review, we aim to introduce these systems to an analytical audience, with the goal of highlighting MS as an underutilized tool for proteomic analysis of tumor models.

Flavokawain C exhibits anti-tumor effects on in vivo HCT 116 xenograft and identification of its apoptosis-linked serum biomarkers via proteomic analysis

Chalcones and their derivatives belong to the flavonoid family. They have been extensively studied for their anticancer properties and some have been approved for clinical use. In this study, the in vivo anti-tumor activity of flavokawain C (FKC), a naturally occurring chalcone found in Kava (Piper methysticum Forst) was evaluated in HCT 116 cells (colon carcinoma). We also attempted to identify potential biomarkers and/or molecular targets in serum with applicability in predicting treatment outcome. The anti-tumor effects and toxicity of FKC were assessed using the xenograft nude mice model. Cisplatin was used as positive control. The anti-proliferative and apoptotic activities were then evaluated in tumor tissues treated with FKC. Furthermore, two-dimensional electrophoresis (2-DE) followed by protein identification using MALDI-TOF/TOF-MS/MS was performed to compare the serum proteome profiles between healthy nude mice and nude mice bearing HCT 116 tumor treated with vehicle solution and FKC, respectively. Our results showed that FKC treatment significantly inhibited HCT 116 tumor growth. In vivo toxicity studies showed that administration of FKC did not cause damage to major organs and had no significant effect on body weight. FKC was found to induce apoptosis in tumor, and this was associated with increased expression of cleaved caspase-3 and decreased expression of Ki67 in tumor tissues. Our proteomic analysis identified five proteins that changed in abundance - Ig mu chain C region (secreted form), GRP78, hemopexin, kininogen-1 and apolipoprotein E. Overall, our findings demonstrated the potential of FKC as an anti-cancer agent for the treatment of colon carcinoma.

An Eight-CpG-based Methylation Classifier for Preoperative Discriminating Early and Advanced-Late Stage of Colorectal Cancer

Aim

To develop and validate a CpG-based classifier for preoperative discrimination of early and advanced-late stage colorectal cancer (CRC).

Methods

We identified an epigenetic signature based on methylation status of multiple CpG sites (CpGs) from 372 subjects in The Cancer Genome Atlas (TCGA) CRC cohort, and an external cohort (GSE48684) with 64 subjects by LASSO regression algorithm. A classifier derived from the methylation signature was used to establish a multivariable logistic regression model to predict the advanced-late stage of CRC. A nomogram was further developed by incorporating the classifier and some independent clinical risk factors, and its performance was evaluated by discrimination and calibration analysis. The prognostic value of the classifier was determined by survival analysis. Furthermore, the diagnostic performance of several CpGs in the methylation signature was evaluated.

Results

The eight-CpG-based methylation signature discriminated early stage from advanced-late stage CRC, with a satisfactory AUC of more than 0.700 in both the training and validation sets. This methylation classifier was identified as an independent predictor for CRC staging. The nomogram showed favorable predictive power for preoperative staging, and the C-index reached 0.817 (95% CI: 0.753–0.881) and 0.817 (95% CI: 0.721–0.913) in another training set and validation set respectively, with good calibration. The patients stratified in the high-risk group by the methylation classifier had significantly worse survival outcome than those in the low-risk group. Combination diagnosis utilizing only four of the eight specific CpGs performed well, even in CRC patients with low CEA level or at early stage.

Conclusions

Our classifier is a valuable predictive indicator that can supplement established methods for more accurate preoperative staging and also provides prognostic information for CRC patients. Besides, the combination of multiple CpGs has a high value in the diagnosis of CRC.

Proteomic Characterization of Colorectal Cancer Cells versus Normal-Derived Colon Mucosa Cells: Approaching Identification of Novel Diagnostic Protein Biomarkers in Colorectal Cancer

In the western world, colorectal cancer (CRC) is the third most common cause of cancer-related deaths. Survival is closely related to the stage of cancer at diagnosis striking the clinical need for biomarkers capable of early detection. To search for possible biological parameters for early diagnosis of CRC we evaluated protein expression for three CREC (acronym: Cab45, reticulocalbin, ERC-55, calumenin) proteins: reticulocalbin, calumenin, and ERC-55 in a cellular model consisting of a normal derived colon mucosa cell line, NCM460, and a primary adenocarcinoma cell line of the colon, SW480. Furthermore, this cellular model was analyzed by a top-down proteomic approach, 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) for novel putative diagnostic markers by identification of differentially expressed proteins between the two cell lines. A different colorectal carcinoma cell line, HCT 116, was used in a bottom-up proteomic approach with label-free quantification (LFQ) LC-MS/MS. The two cellular models gave sets of putative diagnostic CRC biomarkers. Various of these novel putative markers were verified with increased expression in CRC patient neoplastic tissue compared to the expression in a non-involved part of the colon, including reticulocalbin, calumenin, S100A6 and protein SET. Characterization of these novel identified biological features for CRC patients may have diagnostic potential and therapeutic relevance in this malignancy characterized by a still unmet clinical need.

Biomarkers in Colorectal Cancer: The Role of Translational Proteomics Research

Colorectal cancer is one of the most common cancers in the world, and it is one of the leading causes of cancer-related death. Despite recent progress in the development of screening programs and in the management of patients with colorectal cancer, there are still many gaps to fill, ranging from the prevention and early diagnosis to the determination of prognosis factors and treatment of metastatic disease, to establish a personalized approach. The genetic profile approach has been increasingly used in the decision-making process, especially in the choice of targeted therapies and in the prediction of drug response, but there are still few validated biomarkers of colorectal cancer for clinical practice. The discovery of non-invasive, sensitive, and specific biomarkers is an urgent need, and translational proteomics play a key role in this process, as they enable better comprehension of colorectal carcinogenesis, identification of potential markers, and subsequent validation. This review provides an overview of recent advances in the search for colorectal cancer biomarkers through proteomics studies according to biomarker function and clinical application.

Colorectal carcinoma screening: Established methods and emerging technology

Colorectal carcinoma screening programs have shown success in lowering both the incidence and mortality rate of colorectal carcinoma at a population level, in part because this carcinoma is relatively slow growing and has an identifiable premalignant lesion. Still, many patients do not undergo the recommended screening for colorectal carcinoma, and of those who do, a subset may be over- or under-diagnosed by the currently available testing methods. The primary purpose of this article is to review the data regarding currently available colorectal cancer screening modalities, which include fecal occult blood testing, direct colonic visualization, and noninvasive imaging techniques. In addition, readers will be introduced to a variety of biomarkers that may serve as stand-alone or adjunct tests in the future. Finally, there is a brief discussion of the current epidemiologic considerations that public health officials must address as they create population screening guidelines. The data we provide as laboratory physicians and scientists are critical to the construction of appropriate recommendations that ultimately decrease the burden of disease from colorectal carcinoma.

Oncoproteomics: Current status and future opportunities

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.

Clinical Proteomics in Colorectal Cancer, a Promising Tool for Improving Personalised Medicine

Colorectal cancer is the third most common and the fourth most lethal cancer worldwide. In most of cases, patients are diagnosed at an advanced or even metastatic stage, thus explaining the high mortality. The lack of proper clinical tests and the complicated procedures currently used for detecting this cancer, as well as for predicting the response to treatment and the outcome of a patient's resistance in guiding clinical practice, are key elements driving the search for biomarkers. In the present overview, the different biomarkers (diagnostic, prognostic, treatment resistance) discovered through proteomics studies in various colorectal cancer study models (blood, stool, biopsies), including the different proteomic techniques used for the discovery of these biomarkers, are reviewed, as well as the various tests used in clinical practice and those currently in clinical phase. These studies define the limits and perspectives related to proteomic biomarker research for personalised medicine in colorectal cancer.

Innovative methods for biomarker discovery in the evaluation and development of cancer precision therapies

The discovery of biomarkers able to detect cancer at an early stage, to evaluate its aggressiveness, and to predict the response to therapy remains a major challenge in clinical oncology and precision medicine. In this review, we summarize recent achievements in the discovery and development of cancer biomarkers. We also highlight emerging innovative methods in biomarker discovery and provide insights into the challenges faced in their evaluation and validation.

Evolving notions on immune response in colorectal cancer and their implications for biomarker development

INTRODUCTION

Colorectal cancer (CRC) still represents the third most commonly diagnosed type of cancer in men and women worldwide. CRC is acknowledged as a heterogeneous disease that develops through a multi-step sequence of events driven by clonal selections; this observation is sustained by the fact that histologically similar tumors may have completely different outcomes, including a varied response to therapy.

METHODS

In "early" and "intermediate" stage of CRC (stages II and III, respectively) there is a compelling need for new biomarkers fit to assess the metastatic potential of their disease, selecting patients with aggressive disease that might benefit from adjuvant and targeted therapies. Therefore, we review the actual notions on immune response in colorectal cancer and their implications for biomarker development.

RESULTS

The recognition of the key role of immune cells in human cancer progression has recently drawn attention on the tumor immune microenvironment, as a source of new indicators of tumor outcome and response to therapy. Thus, beside consolidated histopathological biomarkers, immune endpoints are now emerging as potential biomarkers.

CONCLUSIONS

The introduction of immune signatures and cellular and molecular components of the immune system as biomarkers is particularly important considering the increasing use of immune-based cancer therapies as therapeutic strategies for cancer patients.

Proteomics for early detection of colorectal cancer: recent updates

INTRODUCTION

Colorectal cancer (CRC) is a common type of cancer with a relatively poor survival rate. The survival rate of patients could be improved if CRC is detected early. Biomarkers associated with early stages of tumor development might provide useful tools for the early diagnosis of colorectal cancer. Areas covered: Online searches using PubMed and Google Scholar were performed using keywords and with a focus on recent proteomic studies. The aim of this review is to highlight the need for biomarkers to improve the detection rate of early CRC and provide an overview of proteomic technologies used for biomarker discovery and validation. This review will also discuss recent proteomic studies which focus on identifying biomarkers associated with the early stages of CRC development. Expert commentary: A large number of CRC biomarkers are increasingly being identified by proteomics using diverse approaches. However, the clinical relevance and introduction of these markers into clinical practice cannot be determined without a robust validation process. The size of validation cohorts remains a major limitation in many biomarker studies.

Quantitative proteomic profiling of paired cancerous and normal colon epithelial cells isolated freshly from colorectal cancer patients

PURPOSE

The heterogeneous structure in tumor tissues from colorectal cancer (CRC) patients excludes an informative comparison between tumors and adjacent normal tissues. Here, we develop and apply a strategy to compare paired cancerous (CEC) versus normal (NEC) epithelial cells enriched from patients and discover potential biomarkers and therapeutic targets for CRC.

EXPERIMENTAL DESIGN

CEC and NEC cells are respectively isolated from five different tumor and normal locations in the resected colon tissue from each patient (N = 12 patients) using an optimized epithelial cell adhesion molecule (EpCAM)-based enrichment approach. An ion current-based quantitative method is employed to perform comparative proteomic analysis for each patient.

RESULTS

A total of 458 altered proteins that are common among >75% of patients are observed and selected for further investigation. Besides known findings such as deregulation of mitochondrial function, tricarboxylic acid cycle, and RNA post-transcriptional modification, functional analysis further revealed RAN signaling pathway, small nucleolar ribonucleoproteins (snoRNPs), and infection by RNA viruses are altered in CEC cells. A selection of the altered proteins of interest is validated by immunohistochemistry analyses.

CONCLUSION AND CLINICAL RELEVANCE

The informative comparison between matched CEC and NEC enhances our understanding of molecular mechanisms of CRC development and provides biomarker candidates and new pathways for therapeutic intervention.

Mining the fecal proteome: from biomarkers to personalised medicine

INTRODUCTION

Fecal proteomics has gained increased prominence in recent years. It can provide insights into the diagnosis and surveillance of many bowel diseases by both identifying potential biomarkers in stool samples and helping identify disease-related pathways. Fecal proteomics has already shown its potential for the discovery and validation of biomarkers for colorectal cancer screening, and the analysis of fecal microbiota by MALDI-MS for the diagnosis of a range of bowel diseases is gaining clinical acceptance. Areas covered: Based on a comprehensive analysis of the current literature, we introduce the range of sensitive and specific proteomics methods which comprise the current 'Proteomics Toolbox', explain how the integration of fecal proteomics with data processing/bioinformatics has been used for the identification of potential biomarkers for both CRC and other gut-related pathologies and analysis of the fecal microbiome, outline some of the current fecal assays in current clinical practice and introduce the concept of personalised medicine which these technologies will help inform. Expert commentary: Integration of fecal proteomics with other proteomics and genomics strategies as well as bioinformatics is paving the way towards personalised medicine, which will bring with it improved global healthcare.

2017 update on the relationship between diabetes and colorectal cancer: epidemiology, potential molecular mechanisms and therapeutic implications

Worldwide deaths from diabetes mellitus (DM) and colorectal cancer increased by 90% and 57%, respectively, over the past 20 years. The risk of colorectal cancer was estimated to be 27% higher in patients with type 2 DM than in non-diabetic controls. However, there are potential confounders, information from lower income countries is scarce, across the globe there is no correlation between DM prevalence and colorectal cancer incidence and the association has evolved over time, suggesting the impact of additional environmental factors. The clinical relevance of these associations depends on understanding the mechanism involved. Although evidence is limited, insulin use has been associated with increased and metformin with decreased incidence of colorectal cancer. In addition, colorectal cancer shares some cellular and molecular pathways with diabetes target organ damage, exemplified by diabetic kidney disease. These include epithelial cell injury, activation of inflammation and Wnt/β-catenin pathways and iron homeostasis defects, among others. Indeed, some drugs have undergone clinical trials for both cancer and diabetic kidney disease. Genome-wide association studies have identified diabetes-associated genes (e.g. TCF7L2) that may also contribute to colorectal cancer. We review the epidemiological evidence, potential pathophysiological mechanisms and therapeutic implications of the association between DM and colorectal cancer. Further studies should clarify the worldwide association between DM and colorectal cancer, strengthen the biological plausibility of a cause-and-effect relationship through characterization of the molecular pathways involved, search for specific molecular signatures of colorectal cancer under diabetic conditions, and eventually explore DM-specific strategies to prevent or treat colorectal cancer.

Targeted Proteomics for Multiplexed Verification of Markers of Colorectal Tumorigenesis

Targeted proteomic methods can accelerate the verification of multiple tumor marker candidates in large series of patient samples. We utilized the targeted approach known as selected/multiple reaction monitoring (S/MRM) to verify potential protein markers of colorectal adenoma identified by our group in previous transcriptomic and quantitative shotgun proteomic studies of a large cohort of precancerous colorectal lesions. We developed SRM assays to reproducibly detect and quantify 25 (62.5%) of the 40 selected proteins in an independent series of precancerous and cancerous tissue samples (19 adenoma/normal mucosa pairs; 17 adenocarcinoma/normal mucosa pairs). Twenty-three proteins were significantly up-regulated (n = 17) or downregulated (n = 6) in adenomas and/or adenocarcinomas, as compared with normal mucosa (linear fold changes ≥ ±1.3, adjusted p value <0.05). Most changes were observed in both tumor types (up-regulation of ANP32A, ANXA3, SORD, LDHA, LCN2, NCL, S100A11, SERPINB5, CDV3, OLFM4, and REG4; downregulation of ARF6 and PGM5), and a five-protein biomarker signature distinguished neoplastic tissue from normal mucosa with a maximum area under the receiver operating curve greater than 0.83. Other changes were specific for adenomas (PPA1 and PPA2 up-regulation; KCTD12 downregulation) or adenocarcinoma (ANP32B, G6PD, RCN1, and SET up-regulation; downregulated AKR1B1, APEX1, and PPA1). Some changes significantly correlated with a few patient- or tumor-related phenotypes. Twenty-two (96%) of the 23 proteins have a potential to be released from the tumors into the bloodstream, and their detectability in plasma has been previously reported. The proteins identified in this study expand the pool of biomarker candidates that can be used to develop a standardized precolonoscopy blood test for the early detection of colorectal tumors.

Proteomic strategies in the search for novel pancreatic cancer biomarkers and drug targets: recent advances and clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers; despite a low incidence rate it is the fourth leading cause of cancer-related death in the world. Improvement of the diagnosis, prognosis and treatment remains the main focus of pancreatic cancer research. Rapid developments in proteomic technologies has improved our understanding of the pancreatic cancer proteome. Here, the authors summarise the recent proteomic strategies undertaken in the search for: novel biomarkers for early diagnosis, pancreatic cancer-specific proteins which may be used for novel targeted therapies and proteins which may be useful for monitoring disease progression post-therapy. Recent advances and findings discussed here provide great promise of having a significant clinical impact and improving the outcome of patients with this malignancy.

Typing of colon and lung adenocarcinoma by high throughput imaging mass spectrometry

In advanced tumor stages, diagnosis is frequently made from metastatic tumor tissue. In some cases, the identification of the tumor of origin may be difficult by histology alone. In this setting, immunohistochemical and molecular biological methods are often required. In a subset of tumors definite diagnosis cannot be achieved. Thus, additional new diagnostic methods are required for precise tumor subtyping. Mass spectrometric methods are of special interest for the discrimination of different tumor types. We investigated whether it is possible to discern adenocarcinomas of colon and lung using high-throughput imaging mass spectrometry on formalin-fixed paraffin-embedded tissue microarrays. 101 primary adenocarcinoma of the colon and 91 primary adenocarcinoma of the lung were used to train a Linear Discriminant Analysis model. Results were validated on an independent set of 116 colonic and 75 lung adenocarcinomas. In the validation cohort 109 of 116 patients with colonic and 67 of 75 patients with lung adenocarcinomas were correctly classified. The ability to define proteomic profiles capable to discern different tumor types promises a valuable tool in cancer diagnostics and might complement current approaches. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Integrative analysis of the colorectal cancer proteome: potential clinical impact

INTRODUCTION

Colorectal cancer (CRC) is one of the common types of cancer that affects a significant proportion of the population and is a major contributor to cancer related mortality. The relatively poor survival rate of CRC could be improved through the identification of clinically useful biomarkers. Areas covered: This review highlights the need for biomarkers and discusses recent proteomics discoveries in the aspects of CRC clinical practice including diagnosis, prognosis, therapy, screening and molecular pathological epidemiology (MPE). Studies have been evaluated in relation to biomarker target, methodology, sample selection, limitations, and potential impact. Finally, the progress in proteomic approaches is briefly discussed and the main difficulties facing the translation of proteomics biomarkers into the clinical practice are highlighted. Expert commentary: The establishment of specific guidelines, best practice recommendations and the improvement in proteomic strategies will significantly improve the prospects for developing clinically useful biomarkers.

High sensitivity isoelectric focusing to establish a signaling biomarker for the diagnosis of human colorectal cancer

BACKGROUND

The progression of colorectal cancer (CRC) involves recurrent amplifications/mutations in the epidermal growth factor receptor (EGFR) and downstream signal transducers of the Ras pathway, KRAS and BRAF. Whether genetic events predicted to result in increased and constitutive signaling indeed lead to enhanced biological activity is often unclear and, due to technical challenges, unexplored. Here, we investigated proliferative signaling in CRC using a highly sensitive method for protein detection. The aim of the study was to determine whether multiple changes in proliferative signaling in CRC could be combined and exploited as a "complex biomarker" for diagnostic purposes.

METHODS

We used robotized capillary isoelectric focusing as well as conventional immunoblotting for the comprehensive analysis of epidermal growth factor receptor signaling pathways converging on extracellular regulated kinase 1/2 (ERK1/2), AKT, phospholipase Cγ1 (PLCγ1) and c-SRC in normal mucosa compared with CRC stage II and IV. Computational analyses were used to test different activity patterns for the analyzed signal transducers.

RESULTS

Signaling pathways implicated in cell proliferation were differently dysregulated in CRC and, unexpectedly, several were downregulated in disease. Thus, levels of activated ERK1 (pERK1), but not pERK2, decreased in stage II and IV while total ERK1/2 expression remained unaffected. In addition, c-SRC expression was lower in CRC compared with normal tissues and phosphorylation on the activating residue Y418 was not detected. In contrast, PLCγ1 and AKT expression levels were elevated in disease. Immunoblotting of the different signal transducers, run in parallel to capillary isoelectric focusing, showed higher variability and lower sensitivity and resolution. Computational analyses showed that, while individual signaling changes lacked predictive power, using the combination of changes in three signaling components to create a "complex biomarker" allowed with very high accuracy, the correct diagnosis of tissues as either normal or cancerous.

CONCLUSIONS

We present techniques that allow rapid and sensitive determination of cancer signaling that can be used to differentiate colorectal cancer from normal tissue.

Proteomic indicators of oxidation and hydration state in colorectal cancer

New integrative approaches are needed to harness the potential of rapidly growing datasets of protein expression and microbial community composition in colorectal cancer. Chemical and thermodynamic models offer theoretical tools to describe populations of biomacromolecules and their relative potential for formation in different microenvironmental conditions. The average oxidation state of carbon (Z_C) can be calculated as an elemental ratio from the chemical formulas of proteins, and water demand per residue (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O) is computed by writing the overall formation reactions of proteins from basis species. Using results reported in proteomic studies of clinical samples, many datasets exhibit higher mean Z_C or \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}${\overline{n}}_{{\mathrm{H}}_{2}\mathrm{O}}$\end{document}n¯H2O of proteins in carcinoma or adenoma compared to normal tissue. In contrast, average protein compositions in bacterial genomes often have lower Z_C for bacteria enriched in fecal samples from cancer patients compared to healthy donors. In thermodynamic calculations, the potential for formation of the cancer-related proteins is energetically favored by changes in the chemical activity of H₂O and fugacity of O₂ that reflect the compositional differences. The compositional analysis suggests that a systematic change in chemical composition is an essential feature of cancer proteomes, and the thermodynamic descriptions show that the observed proteomic transformations in host tissue could be promoted by relatively high microenvironmental oxidation and hydration states.

Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer

Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers.

Mass spectrometry-based proteomics: from cancer biology to protein biomarkers, drug targets, and clinical applications

Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins--the major cellular players bringing about cellular functions--at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

Bone Marrow Stromal Antigen 2 Is a Novel Plasma Biomarker and Prognosticator for Colorectal Carcinoma: A Secretome-Based Verification Study

BACKGROUND

The cancer cell secretome has been recognized as a valuable reservoir for identifying novel serum/plasma biomarkers for different cancers, including colorectal cancer (CRC). This study aimed to verify four CRC cell-secreted proteins (tumor-associated calcium signal transducer 2/trophoblast cell surface antigen 2 (TACSTD2/TROP2), tetraspanin-6 (TSPAN6), bone marrow stromal antigen 2 (BST2), and tumor necrosis factor receptor superfamily member 16 (NGFR)) as potential plasma CRC biomarkers.

METHODS

The study population comprises 152 CRC patients and 152 controls. Target protein levels in plasma and tissue samples were assessed by ELISA and immunohistochemistry, respectively.

RESULTS

Among the four candidate proteins examined by ELISA in a small sample set, only BST2 showed significantly elevated plasma levels in CRC patients versus controls. Immunohistochemical analysis revealed the overexpression of BST2 in CRC tissues, and higher BST2 expression levels correlated with poorer 5-year survival (46.47% versus 65.57%; p = 0.044). Further verification confirmed the elevated plasma BST2 levels in CRC patients (2.35 ± 0.13 ng/mL) versus controls (1.04 ± 0.03 ng/mL) (p < 0.01), with an area under the ROC curve (AUC) being 0.858 comparable to that of CEA (0.867).

CONCLUSION

BST2, a membrane protein selectively detected in CRC cell secretome, may be a novel plasma biomarker and prognosticator for CRC.

Biomarkers of Host Response Predict Primary End-Point Radiological Pneumonia in Tanzanian Children with Clinical Pneumonia: A Prospective Cohort Study

Background

Diagnosing pediatric pneumonia is challenging in low-resource settings. The World Health Organization (WHO) has defined primary end-point radiological pneumonia for use in epidemiological and vaccine studies. However, radiography requires expertise and is often inaccessible. We hypothesized that plasma biomarkers of inflammation and endothelial activation may be useful surrogates for end-point pneumonia, and may provide insight into its biological significance.

Methods

We studied children with WHO-defined clinical pneumonia (n = 155) within a prospective cohort of 1,005 consecutive febrile children presenting to Tanzanian outpatient clinics. Based on x-ray findings, participants were categorized as primary end-point pneumonia (n = 30), other infiltrates (n = 31), or normal chest x-ray (n = 94). Plasma levels of 7 host response biomarkers at presentation were measured by ELISA. Associations between biomarker levels and radiological findings were assessed by Kruskal-Wallis test and multivariable logistic regression. Biomarker ability to predict radiological findings was evaluated using receiver operating characteristic curve analysis and Classification and Regression Tree analysis.

Results

Compared to children with normal x-ray, children with end-point pneumonia had significantly higher C-reactive protein, procalcitonin and Chitinase 3-like-1, while those with other infiltrates had elevated procalcitonin and von Willebrand Factor and decreased soluble Tie-2 and endoglin. Clinical variables were not predictive of radiological findings. Classification and Regression Tree analysis generated multi-marker models with improved performance over single markers for discriminating between groups. A model based on C-reactive protein and Chitinase 3-like-1 discriminated between end-point pneumonia and non-end-point pneumonia with 93.3% sensitivity (95% confidence interval 76.5–98.8), 80.8% specificity (72.6–87.1), positive likelihood ratio 4.9 (3.4–7.1), negative likelihood ratio 0.083 (0.022–0.32), and misclassification rate 0.20 (standard error 0.038).

Conclusions

In Tanzanian children with WHO-defined clinical pneumonia, combinations of host biomarkers distinguished between end-point pneumonia, other infiltrates, and normal chest x-ray, whereas clinical variables did not. These findings generate pathophysiological hypotheses and may have potential research and clinical utility.

Screening and identification of apolipoprotein A-I as a potential hepatoblastoma biomarker in children, excluding inflammatory factors

The aim of the present study was to identify a child hepatoblastoma serum biomarker that is unaffected by inflammatory factors, with the ultimate aim of finding an effective method for the early diagnosis of hepatoblastoma. The magnetic bead-based weak cation exchange chromatography technique was used to process serum harvested from 30 children with hepatoblastoma, 20 children with systemic inflammatory response syndrome (SIRS) and 20 healthy children. Proteins differentially expressed in SIRS were excluded from consideration as biomarkers for hepatoblastoma. Proteins differentially expressed in hepatoblastoma and healthy controls were screened using surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS). Target proteins were purified by SDS-PAGE, and matrix-assisted laser desorption/ionization (MALDI)-TOF-MS was used to determine their amino acid sequences. Protein matches were searched in the SwissProt database. Quantitative polymerase chain reaction (qPCR) and ELISA were employed to confirm the expression of target proteins. Following screening to exclude inflammatory factors, SELDI-TOF-MS revealed a protein with a mass-to-charge ratio of 9,348 Da that was expressed at significantly lower levels in the serum of children with hepatoblastoma compared with healthy controls (P<0.01). Sequence analysis identified this protein as apolipoprotein A-1 (Apo A-I). qPCR and ELISA confirmed that the expression of Apo A-I mRNA and protein were significantly lower in children with hepatoblastoma compared with healthy controls (P<0.05). These results indicate that Apo A-I is a non-inflammatory protein marker for hepatoblastoma with the potential for use in early diagnosis of hepatoblastoma. In addition, the present study demonstrates the feasibility of proteomic screening for the identification of proteins that can serve as markers for a specific tumor.

Reporting in studies of protein biomarkers of prognosis in colorectal cancer in relation to the REMARK guidelines

PURPOSE

The REMARK guidelines give authors comprehensive and specific advice on the complete and transparent reporting of studies of prognostic tumor markers. The aim of this study was to use the REMARK guidelines to evaluate the quality of reporting in a sample of studies assessing tissue-based protein markers for survival after resection of colorectal cancer.

EXPERIMENTAL DESIGN

Eighty pertinent articles were scored according to their conformity to 26 items derived from the REMARK criteria.

RESULTS

Overall, on a scale of adequacy of reporting that potentially ranged from 26 to 78, the median for these studies was 60 (interquartile range 54-64) and several criteria were adequately covered in a large proportion of studies. However, others were either not dealt with or inadequately covered, including description of the study design (35%), definition of survival endpoints (48%), adjuvant therapy (54%), follow-up procedures and time (59%), neoadjuvant therapy (63%), inclusion/exclusion criteria (73%), multivariable modeling methods and results (74%), and discussion of study limitations (85%).

CONCLUSIONS AND CLINICAL RELEVANCE

Inadequacies in presentation militate against comparability among protein marker studies and undermine the generalizability of their findings. The quality of reporting could be improved if journal editors were to require authors to ensure that their work satisfied the REMARK criteria.

Surgery in the era of the 'omics revolution

Background

Surgery is entering a new phase with the revolution in genomic technology. Cheap, mass access to next‐generation sequencing is now allowing the analysis of entire human genomes at the DNA and RNA level. These data sets are being used increasingly to identify the molecular differences that underlie common surgical diseases, and enable them to be stratified for patient benefit.

Methods

This article reviews the recent developments in the molecular biology of colorectal, oesophagogastric and breast cancer.

Results

The review specifically covers developments in genetic predisposition, next‐generation sequencing studies, biomarkers for stratification, prognosis and treatment, and other 'omics technologies such as metabolomics and proteomics.

Conclusion

There are unique opportunities over the next decade to change the management of surgical disease radically, using these technologies. The directions that this may take are highlighted, including future advances such as the 100 000 Genomes Project.

May individualize cancer treatment

Plasma clusterin as a candidate pre-diagnosis marker of colorectal cancer risk in the Florence cohort of the European Prospective Investigation into Cancer and Nutrition: a pilot study

BACKGROUND

Colorectal cancer is one of the major causes of cancer mortality world-wide. Prevention would improve if at-risk subjects could be identified. The aim of this study was to characterise plasma protein biomarkers associated with the risk of colorectal cancer in samples collected prospectively, before the disease diagnosis.

METHODS

After an exploratory study on the comprehensive plasma proteome analysis by liquid chromatography-tandem mass spectrometry from ten colorectal cancer cases enrolled at diagnosis, and ten matched controls (Phase 1), a similar preliminary study was performed on prospective plasma samples from ten colorectal cancer cases, enrolled years before disease development, and ten matched controls identified in a nested case-control study within the Florence cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC) study (Phase 2); in Phase 3 the validation of the candidate biomarkers by targeted proteomics on 48 colorectal cancer cases and 48 matched controls from the Florence-EPIC cohort, and the evaluation of the disease risk were performed.

RESULTS

Systems biology tools indicated that both in the Phase 1 and Phase 2 studies circulating protein levels differing in cases more than 1.5 times from controls, were involved in inflammation and/or immune response. Eight proteins including apolipoprotein C-II, complement C4-B, complement component C9, clusterin, alpha-2-HS-glycoprotein, mannan-binding lectin serine-protease, mannose-binding protein C, and N-acetylmuramoyl-L-alanine amidase were selected as promising candidate biomarkers. Targeted proteomics of the selected proteins in the EPIC samples showed significantly higher clusterin levels in cases than controls, but only in men (mean ± SD, 1.98 ± 0.46 and 1.61 ± 0.43 nmol/mL respectively, Mann-Whitney U, two-tailed P = 0.0173). The remaining proteins were unchanged. Using multivariate logistic models a significant positive association emerged for clusterin, with an 80% increase in the colorectal cancer risk with protein's unit increase, but only in men.

CONCLUSIONS

The results show that plasma proteins can be altered years before colorectal cancer detection. The high circulating clusterin in pre-diagnostic samples suggests this biomarker can improve the identification of people at risk of colorectal cancer and might help in designing preventive interventions.

Application of metabolomics in thyroid cancer research

Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput "omics" techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

Elevated levels of 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase identified in clinical samples from patients diagnosed with colorectal cancer

BACKGROUND

Colorectal cancer (CRC), a heterogeneous disease that is common in both men and women, continues to be one of the predominant cancers worldwide. Lifestyle, diet, environmental factors and gene defects all contribute towards CRC development risk. Therefore, the identification of novel biomarkers to aid in the management of CRC is crucial. The aim of the present study was to identify candidate biomarkers for CRC, and to develop a better understanding of their role in tumourogenesis.

METHODS

In this study, both plasma and tissue samples from patients diagnosed with CRC, together with non-malignant and normal controls were examined using mass spectrometry based proteomics and metabolomics approaches.

RESULTS

It was established that the level of several biomolecules, including serotonin, gamma enolase, pyruvate kinase and members of the 14-3-3 family of proteins, showed statistically significant changes when comparing malignant versus non-malignant patient samples, with a distinct pattern emerging mirroring cancer cell energy production.

CONCLUSION

The diagnosis and management of CRC could be enhanced by the discovery and validation of new candidate biomarkers, as found in this study, aimed at facilitating early detection and/or patient stratification together with providing information on the complex behaviour of cancer cells.

Immunohistochemical Characterization of Large Intestinal Adenocarcinoma in the Rhesus Macaque (Macaca mulatta)

In rhesus macaques, adenocarcinomas of either the ileocecal junction or colon are common spontaneous tumors in aging populations. The macaque tumors have similar gross and histologic characteristics compared with their human counterpart, but little is known regarding the immunohistochemical expression of proteins that are commonly implicated in the pathogenesis of these tumors in humans. We performed a retrospective review of 22 cases of large intestinal carcinoma in the rhesus macaque and evaluated the expression pattern of a panel of potentially prognostically significant proteins identified from human studies. Histologic characteristics of the tumors included abundant mucin deposition, transmural spread, and lymphatic invasion. All rhesus adenocarcinomas displayed altered expression of 1 or more of CD10, β-catenin, sirtuin 1, cytokeratin 17, and p53 compared with age-matched controls. Zymographic analysis of active matrix metalloproteinases 2 and 9 in the serum from 5 animals failed to reveal statistically significant differences between adenocarcinoma cases and controls. Based on the data presented herein, large intestinal carcinomas in the macaque share many histomorphologic and immunohistochemical similarities to large intestinal tumors in humans. Further validation of this animal model is considered important for the development of novel therapeutics and a better understanding of the pathogenesis.

N-glycoprotein analysis discovers new up-regulated glycoproteins in colorectal cancer tissue

Colorectal cancer is one of the leading causes of death due to cancer worldwide. Therefore, the identification of high-specificity and -sensitivity biomarkers for the early detection of colorectal cancer is urgently needed. Post-translational modifications, such as glycosylation, are known to play an important role in cancer progression. In the present work, we used a quantitative proteomic technique based on (18)O stable isotope labeling to identify differentially expressed N-linked glycoproteins in colorectal cancer tissue samples compared with healthy colorectal tissue from 19 patients undergoing colorectal cancer surgery. We identified 54 up-regulated glycoproteins in colorectal cancer samples, therefore potentially involved in the biological processes of tumorigenesis. In particular, nine of these (PLOD2, DPEP1, SE1L1, CD82, PAR1, PLOD3, S12A2, LAMP3, OLFM4) were found to be up-regulated in the great majority of the cohort, and, interestingly, the association with colorectal cancer of four (PLOD2, S12A2, PLOD3, CD82) has not been hitherto described.

Pharmacogenetics research on chemotherapy resistance in colorectal cancer over the last 20 years

During the past two decades the first sequencing of the human genome was performed showing its high degree of inter-individual differentiation, as a result of large international research projects (Human Genome Project, the 1000 Genomes Project International HapMap Project, and Programs for Genomic Applications NHLBI-PGA). This period was also a time of intensive development of molecular biology techniques and enormous knowledge growth in the biology of cancer. For clinical use in the treatment of patients with colorectal cancer (CRC), in addition to fluoropyrimidines, another two new cytostatic drugs were allowed: irinotecan and oxaliplatin. Intensive research into new treatment regimens and a new generation of drugs used in targeted therapy has also been conducted. The last 20 years was a time of numerous in vitro and in vivo studies on the molecular basis of drug resistance. One of the most important factors limiting the effectiveness of chemotherapy is the primary and secondary resistance of cancer cells. Understanding the genetic factors and mechanisms that contribute to the lack of or low sensitivity of tumour tissue to cytostatics is a key element in the currently developing trend of personalized medicine. Scientists hope to increase the percentage of positive treatment response in CRC patients due to practical applications of pharmacogenetics/pharmacogenomics. Over the past 20 years the clinical usability of different predictive markers has been tested among which only a few have been confirmed to have high application potential. This review is a synthetic presentation of drug resistance in the context of CRC patient chemotherapy. The multifactorial nature and volume of the issues involved do not allow the author to present a comprehensive study on this subject in one review.