Proteomics for discovery of candidate colorectal cancer biomarkers

Precision medicine in colorectal cancer: Leveraging multi-omics, spatial omics, and artificial intelligence

Colorectal cancer (CRC) is a leading cause of cancer-related deaths. Recent advancements in genomic technologies and analytical approaches have revolutionized CRC research, enabling precision medicine. This review highlights the integration of multi-omics, spatial omics, and artificial intelligence (AI) in advancing precision medicine for CRC. Multi-omics approaches have uncovered molecular mechanisms driving CRC progression, while spatial omics have provided insights into the spatial heterogeneity of gene expression in CRC tissues. AI techniques have been utilized to analyze complex datasets, identify new treatment targets, and enhance diagnosis and prognosis. Despite the tumor's heterogeneity and genetic and epigenetic complexity, the fusion of multi-omics, spatial omics, and AI shows the potential to overcome these challenges and advance precision medicine in CRC. The future lies in integrating these technologies to provide deeper insights and enable personalized therapies for CRC patients.

Immune-like sandwich multiple hotspots SERS biosensor for ultrasensitive detection of NDKA biomarker in serum

Developing the rapid, specific, and sensitive tumor marker NDKA biosensor has become an urgent need in the field of early diagnosis of colorectal cancer (CRC). Surface-enhanced Raman spectroscopy (SERS) with the advantages of high sensitivity, high resolution as well as providing sample fingerprint, enables rapid and sensitive detection of tumor markers. However, many SERS biosensors rely on boosting the quantity of Raman reporter molecules on individual nanoparticle surfaces, which can result in nanoparticle agglomeration, diminishing the stability and sensitivity of NDKA detection. Here, we proposed an immune-like sandwich multiple hotspots SERS biosensor for highly sensitive and stable analysis of NDKA in serum based on molecularly imprinted polymers and NDKA antibody. The SERS biosensor employs an array of gold nanoparticles, which are coated with a biocompatible polydopamine molecularly imprinted polymer as a substrate to specifically capture NDKA. Then the biosensor detects NDKA through Raman signals as a result of the specific binding of NDKA to the SERS nanotag affixed to the capture substrate along with the formation of multiple hotspots. This SERS biosensor not only avoids the aggregation of nanoparticles but also presents a solution to the obstacles encountered in immune strategies for certain proteins lacking multiple antibody or aptamer binding sites. Furthermore, the practical application of the SERS biosensor is validated by the detection of NDKA in serum with the lower limit of detection (LOD) of 0.25 pg/mL, meanwhile can detect NDKA of 10 ng/mL in mixed proteins solution, illustrating high sensitivity and specificity. This immune-like sandwich multiple hotspots biosensor makes it quite useful for the early detection of CRC and also provides new ideas for cancer biomarker sensing strategy in the future.

Carbon-Based Nanomaterials as Drug Delivery Agents for Colorectal Cancer: Clinical Preface to Colorectal Cancer Citing Their Markers and Existing Theranostic Approaches

Colorectal cancer (CRC) is one of the universally established cancers with a higher incidence rate. Novel progression toward cancer prevention and cancer care among countries in transition should be considered seriously for controlling CRC. Hence, several cutting edge technologies are ongoing for high performance cancer therapeutics over the past few decades. Several drug-delivery systems of the nanoregime are relatively new in this arena compared to the previous treatment modes such as chemo- or radiotherapy to mitigate cancer. Based on this background, the epidemiology, pathophysiology, clinical presentation, treatment possibilities, and theragnostic markers for CRC were revealed. Since the use of carbon nanotubes (CNTs) for the management of CRC has been less studied, the present review analyzes the preclinical studies on the application of carbon nanotubes for drug delivery and CRC therapy owing to their inherent properties. It also investigates the toxicity of CNTs on normal cells for safety testing and the clinical use of carbon nanoparticles (CNPs) for tumor localization. To conclude, this review recommends the clinical application of carbon-based nanomaterials further for the management of CRC in diagnosis and as carriers or therapeutic adjuvants.

Investigation of the Effects of Glabridin on the Proliferation, Apoptosis, and Migration of the Human Colon Cancer Cell Lines SW480 and SW620 and Its Mechanism Based on Reverse Virtual Screening and Proteomics

Colon cancer is a relatively common malignant tumor of the digestive tract. Currently, most colon cancers originate from adenoma carcinogenesis. By screening various licorice flavonoids with anticancer effects, we found that glabridin (GBN) has a prominent anticolon cancer effect. First, we initially explored whether GBN can inhibit proliferation, migration, and invasion and induce apoptosis in SW480 and SW620 cells. Next, we exploited reverse virtual and proteomics technologies to screen out closely related target pathways on the basis of a drug and target database. At the same time, we constructed the structure of the GBN target pathway in colon cancer. We predicted that GBN can regulate the phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT)-mammalian target of the rapamycin pathway (mTOR) pathway to fight colon cancer. Finally, through Western blot analysis and qRT-PCR, we verified that the expression levels of the PI3K, AKT, and mTOR proteins and genes in this pathway were significantly reduced after GBN administration. In short, the promising discovery of the anticolon cancer mechanism of GBN provides a reliable experimental basis for subsequent new drug development.

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.

Personalized Therapy and Liquid Biopsy-A Focus on Colorectal Cancer

(1) Background: Resistance mechanisms represent a barrier to anti-cancer therapies. Liquid biopsies would allow obtaining additional information in order to develop targeted therapies to thwart the resistance phenomena but also to follow in time real response to treatment and be able to adapt it the most quickly possible way in case of resistance. (2) Methods: herein we summarize the different liquid biopsies which are currently under research; we then review the literature and focalize on one of their potential roles: the theranostic one and especially in the cases of colorectal cancers. (3) Results: few studies targeting liquid biopsy as a potential tool to adapt cancer treatments are present in the literature and encompass few patients. (4) Conclusions: further research is needed to prove the efficiency of LB. Indeed, it seems a promising tool to guide treatment by targeting actionable mutations with detection of resistant mutations.

Multitarget Stool mRNA Test for Detecting Colorectal Cancer Lesions Including Advanced Adenomas

Current approved non-invasive screening methods for colorectal cancer (CRC) include FIT and DNA-FIT testing, but their efficacy for detecting precancerous lesions that are susceptible to progressing to CRC such as advanced adenomas (AA) remains limited, thus requiring further options to improve the detection of CRC lesions at earlier stages. One of these is host mRNA stool testing. The aims of the present study were to identify specific stool mRNA targets that can predict AA and to investigate their stability under a clinical-like setting. A panel of mRNA targets was tested on stool samples obtained from 102 patients including 78 CRC stage I-III and 24 AA as well as 32 healthy controls. Area under the receiver operating characteristic (ROC) curves were calculated to establish sensitivities and specificities for individual and combined targets. Stability experiments were performed on freshly obtained specimens. Six of the tested targets were found to be specifically increased in the stools of patients with CRC and three in the stools of both AA and CRC patients. After optimization for the choice of the 5 best markers for AA and CRC, ROC curve analysis revealed overall sensitivities of 75% and 89% for AA and CRC, respectively, for a ≥95% specificity, and up to 75% and 95% for AA and CRC, respectively, when combined with the FIT score. Targets were found to be stable in the stools up to 3 days at room temperature. In conclusion, these studies show that the detection of host mRNA in the stools is a valid approach for the screening of colorectal cancerous lesions at all stages and is applicable to a clinical-like setup.

Colorectal cancer screening and diagnosis: omics-based technologies for development of a non-invasive blood-based method

Introduction: Colorectal cancer (CRC) is one of the most important health problems in the Western world. In order to reduce the burden of the disease, two strategies are proposed: screening and prompt detection in symptomatic patients. Although diagnosis and prevention are mainly based on colonoscopy, fecal hemoglobin detection has been widely implemented as a noninvasive strategy. Various studies aiming to discover blood-based biomarkers have recently emerged.Areas covered: The burgeoning omics field provides diverse high-throughput approaches for CRC blood-based biomarker discovery. In this review, we appraise the most robust and commonly used technologies within the fields of genomics, transcriptomics, epigenomics, proteomics, and metabolomics, together with their targeted validation approaches. We summarize the transference process from the discovery phase until clinical translation. Finally, we review the best candidate biomarkers and their potential clinical applicability.Expert opinion: Some available biomarkers are promising, especially in the field of epigenomics: DNA methylation and microRNA. Transference requires the joint collaboration of basic researchers, intellectual property experts, technology transfer officers and clinicians. Blood-based biomarkers will be selected not only based on their diagnostic accuracy and cost but also on their reliability, applicability to clinical analysis laboratories and their acceptance by the population.

Comparison of Proteomic Technologies for Blood-Based Detection of Colorectal Cancer

Blood-based protein biomarkers are increasingly being explored as supplementary or efficient alternatives for population-based screening of colorectal cancer (CRC). The objective of the current study was to compare the diagnostic potential of proteins measured with different proteomic technologies. The concentrations of protein biomarkers were measured using proximity extension assays (PEAs), liquid chromatography/multiple reaction monitoring-mass spectrometry (LC/MRM-MS) and quantibody microarrays (QMAs) in plasma samples of 56 CRC patients and 99 participants free of neoplasms. In another approach, proteins were measured in serum samples of 30 CRC cases and 30 participants free of neoplasm using immunome full-length functional protein arrays (IpAs). From all the measurements, 9, 6, 35 and 14 protein biomarkers overlapped for comparative evaluation of (a) PEA and LC/MRM-MS, (b) PEA and QMA, (c) PEA and IpA, and (d) LC/MRM-MS and IpA measurements, respectively. Correlation analysis was performed, along with calculation of the area under the curve (AUC) for assessing the diagnostic potential of each biomarker. DeLong's test was performed to assess the differences in AUC. Evaluation of the nine biomarkers measured with PEA and LC/MRM-MS displayed correlation coefficients >+0.6, similar AUCs and DeLong's p-values indicating no differences in AUCs for biomarkers like insulin-like growth factor binding protein 2 (IGFBP2), matrix metalloproteinase 9 (MMP9) and serum paraoxonase lactonase 3 (PON3). Comparing six proteins measured with PEA and QMA showed good correlation and similar diagnostic performance for only one protein, growth differentiation factor 15 (GDF15). The comparison of 35 proteins measured with IpA and PEA and 14 proteins analyzed with IpA and LC/MRM-MS revealed poor concordance and comparatively better AUCs when measured with PEA and LC/MRM-MS. The comparison of different proteomic technologies suggests the superior performance of novel technologies like PEA and LC/MRM-MS over the assessed array-based technologies in blood-protein-based early detection of CRC.

Serum proteomic analysis of novel predictive serum proteins for neurological prognosis following cardiac arrest

Early prognostication of neurological outcome in comatose patients after cardiac arrest (CA) is vital for clinicians when assessing the survival time of sufferers and formulating appropriate treatment strategies to avoid the withdrawal of life‐sustaining treatment (WLST) from patients. However, there is still a lack of sensitive and specific serum biomarkers for early and accurate identification of these patients. Using an isobaric tag for relative and absolute quantitation (iTRAQ)‐based proteomic approach, we discovered 55 differentially expressed proteins, with 39 up‐regulated secreted serum proteins and 16 down‐regulated secreted serum proteins between three comatose CA survivors with good versus poor neurological recovery. Then, four proteins were selected and were validated via an enzyme‐linked immunosorbent assay (ELISA) approach in a larger‐scale sample containing 32 good neurological outcome patients and 46 poor neurological outcome patients, and it was confirmed that serum angiotensinogen (AGT) and alpha‐1‐antitrypsin (SERPINA1) were associated with neurological function and prognosis in CA survivors. A prognostic risk score was developed and calculated using a linear and logistic regression model based on a combination of AGT, SERPINA1 and neuron‐specific enolase (NSE) with an area under the curve of 0.865 (P < .001), and the prognostic risk score was positively correlated with the CPC value (R = 0.708, P < .001). We propose that the results of the risk score assessment not only reveal changes in biomarkers during neurological recovery but also assist in enhancing current therapeutic strategies for comatose CA survivors.

Exosomes: The protagonists in the tale of colorectal cancer?

Exosomes, which facilitate intercellular communication, antigen presentation and shuttling of biological agents, were initially thought as the cell's garbage cargo but today, after about 40 years of their discovery, we are now beginning to understand their potential role in diagnosis and therapy of several diseases including cancers. Various studies over the decades have signified the role of exosomes in different stages of cancer. Exosomes play a key role in colorectal cancer initiation (CRC), promotion of anti- apoptotic signaling pathways, regulating tumor microenvironment, enhancing tumorigenicity, promotion of angiogenesis, stem cell proliferation and endothelial cell migration, establishment of immune suppressive environment, formation of pre- metastatic niche and metastasis. Exosomes also elicits drug resistance. Since, they have the ability to cross the biological barrier, exosomes are now being explored as an efficient target specific drug delivery system that facilitates the shipping of different biomolecules and therapeutic drugs. However, cautious and strong investigative approaches are required before approving exosomes as therapeutics or drug delivery systems. In this review, we summarize the role of exosomes in different stages of CRC and also elaborate on the applications of exosomes in diagnosis and therapy with respect to CRC.

Computational advances of tumor marker selection and sample classification in cancer proteomics

Cancer proteomics has become a powerful technique for characterizing the protein markers driving transformation of malignancy, tracing proteome variation triggered by therapeutics, and discovering the novel targets and drugs for the treatment of oncologic diseases. To facilitate cancer diagnosis/prognosis and accelerate drug target discovery, a variety of methods for tumor marker identification and sample classification have been developed and successfully applied to cancer proteomic studies. This review article describes the most recent advances in those various approaches together with their current applications in cancer-related studies. Firstly, a number of popular feature selection methods are overviewed with objective evaluation on their advantages and disadvantages. Secondly, these methods are grouped into three major classes based on their underlying algorithms. Finally, a variety of sample separation algorithms are discussed. This review provides a comprehensive overview of the advances on tumor maker identification and patients/samples/tissues separations, which could be guidance to the researches in cancer proteomics.

Proteomics analysis of colon cancer progression

Background

The aim of this pilot study was to identify proteins associated with advancement of colon cancer (CC).

Methods

A quantitative proteomics approach was used to determine the global changes in the proteome of primary colon cancer from patients with non-cancer normal colon (NC), non-adenomatous colon polyp (NAP), non-metastatic tumor (CC NM) and metastatic tumor (CC M) tissues, to identify up- and down-regulated proteins. Total protein was extracted from each biopsy, trypsin-digested, iTRAQ-labeled and the resulting peptides separated using strong cation exchange (SCX) and reverse-phase (RP) chromatography on-line to electrospray ionization mass spectrometry (ESI-MS).

Results

Database searching of the MS/MS data resulted in the identification of 2777 proteins which were clustered into groups associated with disease progression. Proteins which were changed in all disease stages including benign, and hence indicative of the earliest molecular perturbations, were strongly associated with spliceosomal activity, cell cycle division, and stromal and cytoskeleton disruption reflecting increased proliferation and expansion into the surrounding healthy tissue. Those proteins changed in cancer stages but not in benign, were linked to inflammation/immune response, loss of cell adhesion, mitochondrial function and autophagy, demonstrating early evidence of cells within the nutrient-poor solid mass either undergoing cell death or adjusting for survival. Caveolin-1, which decreased and Matrix metalloproteinase-9, which increased through the three disease stages compared to normal tissue, was selected to validate the proteomics results, but significant patient-to-patient variation obfuscated interpretation so corroborated the contradictory observations made by others.

Conclusion

Nevertheless, the study has provided significant insights into CC stage progression for further investigation.

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.

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.

Exosomes and their importance in metastasis, diagnosis, and therapy of colorectal cancer

Extracellular vesicles are known as actual intermediaries of intercellular communications, such as biological signals and cargo transfer between different cells. A variety of cells release the exosomes as nanovesicular bodies. Exosomes contain different compounds such as several types of nucleic acids and proteins. In this study, we focused on exosomes in colorectal cancer as good tools that can be involved in various cancer-related processes. Furthermore, we summarize the advantages and disadvantages of exosome extraction methods and review related studies on the role of exosomes in colorectal cancer. Finally, we focus on reports available on relations between mesenchymal stem cell-derived exosomes and colorectal cancer. Several cancer-related processes such as cancer progression, metastasis, and drug resistance of colorectal cancer are related to the cargoes of exosomes. A variety of molecules, especially proteins, microRNAs, and long noncoding RNAs, play important roles in these processes. The microenvironment features, such as hypoxia, also have very important effects on the properties of the origin cell-derived exosomes. On the other hand, exosomes derived from colorectal cancer cells also interfere with cancer chemoresistance. Furthermore, today it is known that exosomes and their contents can likely be very effective in noninvasive colorectal cancer diagnosis and therapy. Thus, exosomes, and especially their cargoes, play different key roles in various aspects of basic and clinical research related to both progression and therapy of colorectal cancer.

Interplay between post-translational cyclooxygenase-2 modifications and the metabolic and proteomic profile in a colorectal cancer cohort

BACKGROUND

Colorectal cancer (CRC) is the second most common cause of cancer death worldwide. It is broadly described that cyclooxygenase-2 (COX-2) is mainly overexpressed in CRC but less is known regarding post-translational modifications of this enzyme that may regulate its activity, intracellular localization and stability. Since metabolic and proteomic profile analysis is essential for cancer prognosis and diagnosis, our hypothesis is that the analysis of correlations between these specific parameters and COX-2 state in tumors of a high number of CRC patients could be useful for the understanding of the basis of this cancer in humans.

AIM

To analyze COX-2 regulation in colorectal cancer and to perform a detailed analysis of their metabolic and proteomic profile.

METHODS

Biopsies from both healthy and pathological colorectal tissues were taken under informed consent from patients during standard colonoscopy procedure in the University Hospital of Bellvitge (Barcelona, Spain) and Germans Trias i Pujol University Hospital (Campus Can Ruti) (Barcelona, Spain). Western blot analysis was used to determine COX-2 levels. Deglycosylation assays were performed in both cells and tumor samples incubating each sample with peptide N-glycosidase F (PNGase F). Prostaglandin E₂ (PGE₂) levels were determined using a specific ELISA. ¹H high resolution magic angle spinning (HRMAS) analysis was performed using a Bruker AVIII 500 MHz spectrometer and proteomic analysis was performed in a nano-liquid chromatography-tandem mass spectrometer (nano LC-MS/MS) using a QExactive HF orbitrap MS.

RESULTS

Our data show that COX-2 has a differential expression profile in tumor tissue of CRC patients vs the adjacent non-tumor area, which correspond to a glycosylated and less active state of the protein. This fact was associated to a lesser PGE₂ production in tumors. These results were corroborated in vitro performing deglycosylation assays in HT29 cell line where COX-2 protein profile was modified after PNGase F incubation, showing higher PGE₂ levels. Moreover, HRMAS analysis indicated that tumor tissue has altered metabolic features vs non-tumor counterparts, presenting increased levels of certain metabolites such as taurine and phosphocholine and lower levels of lactate. In proteomic experiments, we detected an enlarged number of proteins in tumors that are mainly implicated in basic biological functions like mitochondrial activity, DNA/RNA processing, vesicular trafficking, metabolism, cytoskeleton and splicing.

CONCLUSION

In our colorectal cancer cohort, tumor tissue presents a differential COX-2 expression pattern with lower enzymatic activity that can be related to an altered metabolic and proteomic profile.

Gene screening of colorectal cancers via network analysis

AIM

Identifying crucial genes related to colorectal cancers via protein-protein interaction (PPI) network analysis is the aim of this study.

BACKGROUND

colorectal cancer as major reason of mortality is evaluated by genetic and proteomic approaches to find suitable biomarkers. Chromosomal instability plays crucial role in CRC. Expression change of large numbers of genes is reported.

METHODS

Differentially expressed genes related to CRCs which obtained from different proteomic methods were extracted from a review article of Paula Álvarez-Chaver et al. The genes interacted by Cytoscape software via STRING database. The central nodes determined and were enriched for biological terms by ClueGO. Action map for central genes was illustrated by CluePedia. The critical genes in CRC were introduced.

RESULTS

Among 123 query genes, 114 one recognized by software and were included in the network. SRC, EGFR, PCNA, IL8, CTNNB1, TIMP1, CDH1, and HSPD1 were determined as central genes. After gene ontology analysis SRC, EGFR, and CDH1 were identified as critical genes related to CRC.

CONCLUSION

It seems that SRC, EGFR, and CDH1 and the related pathways are possible biomarkers for CRC.

Early diagnosis of colorectal cancer via plasma proteomic analysis of CRC and advanced adenomatous polyp

AIM

This paper aimed to identify new candidate biomarkers in blood for early diagnosis of CRC.

BACKGROUND

Colorectal cancer (CRC) is the third most widespread malignancies increasing globally. The high mortality rate associated with colorectal cancer is due to the delayed diagnosis in an advanced stage while the metastasis has occurred. For better clinical management and subsequently to reduce mortality of CRC, early detection biomarkers are in high demand.

METHODS

A 2D-PAGE separation of proteins was performed followed by tandem mass Spectrometry (MALDI-TOF-TOF) to discover potential plasma protein markers for CRC and AA (advanced adenomas). Furthermore, western blot method was used to confirm a part of the results in colorectal tissue samples.

RESULTS

The significantly altered proteins including HPR, HP, ALB, KRT1, APOA1, FGB, IGJ and C4A were down-regulated in polyp relative to normal, and CRC compare to polyp surprisingly, and inversely, ORM2 was up-regulated with the fold change ≥ 2 and p-value ≤ 0.05. We also surveyed APOA1, FGB, and C4A for further confirmation of their expression changes by western blotting. All three of them showed a decreasing trend from normal toward CRC tissue samples as it mentioned before, but just changes of FGB and C4A were significant.

CONCLUSION

The results demonstrated that plasma proteins can be less invasive markers for the detection of CRC. FGB and C4A can be considered as plasma potential biomarkers to early diagnosis of CRC patients and understanding the underlying procedures in tumorigenesis. Undoubtedly, the additional study must be conducted on large scale cohorts to verify the results.

Probing the colorectal cancer proteome for biomarkers: Current status and perspectives

Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide. Biomarkers that can facilitate better clinical management of CRC are in high demand to improve patient outcome and to reduce mortality. In this regard, proteomic analysis holds a promising prospect in the hunt of novel biomarkers for CRC and in understanding the mechanisms underlying tumorigenesis. This review aims to provide an overview of the current progress of proteomic research, focusing on discovery and validation of diagnostic biomarkers for CRC. We will summarize the contributions of proteomic strategies to recent discoveries of protein biomarkers for CRC and also briefly discuss the potential and challenges of different proteomic approaches in biomarker discovery and translational applications.

Glycan analysis of colorectal cancer samples reveals stage-dependent changes in CEA glycosylation patterns

Background

Carcinoembryonic antigen (CEA) is a glycoprotein associated with colorectal cancer (CRC). While the functions of its gene and protein have been fully characterized, its post-translational modifications in the context of CRC development remain undefined.

Methods

To show the correlation between the different stages of CRC development and changes in the glycosylation patterns of CEA, we analyzed CEA in tumor tissues (CEA-T) and paired tumor-adjacent normal tissues (CEA-A) from 53 colorectal cancer patients using a high-density lectin microarray containing 56 plant lectins.

Results

We detected higher expression levels of fucose, mannose and Thomsen–Friedenreich antigen, and lower expression levels of N-acetylgalactosamine, N-acetylglucosamine, galactose, branched and bisecting N-glycans on CEA in the tumor tissues relative to the tumor-adjacent normal tissues. Furthermore, a combinatorial assessment of 9 lectins is sufficient to distinguish CRC tumor tissues from tumor-adjacent normal tissues with 83% sensitivity and ~ 90% specificity. Moreover, the levels of N-acetylgalactosamine, mannose, galactose, N-acetylglucosamine on CEA showed a downward trend after first experiencing an increase at Stage II with the stages of CRC.

Conclusions

Our insights into the changing CEA glycosylation patterns and their role in the development of CRC highlight the importance of glycan variants on CEA for early clinical detection and staging of CRC.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9182-4) contains supplementary material, which is available to authorized users.

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review

Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8-20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10-20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20-14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image.

Mass Spectrometry Analyses of Multicellular Tumor Spheroids

Multicellular tumor spheroids (MCTS) are a powerful biological in vitro model, which closely mimics the 3D structure of primary avascularized tumors. Mass spectrometry (MS) has established itself as a powerful analytical tool, not only to better understand and describe the complex structure of MCTS, but also to monitor their response to cancer therapeutics. The first part of this review focuses on traditional mass spectrometry approaches with an emphasis on elucidating the molecular characteristics of these structures. Then the mass spectrometry imaging (MSI) approaches used to obtain spatially defined information from MCTS is described. Finally the analysis of primary spheroids, such as those present in ovarian cancer, and the great potential that mass spectrometry analysis of these structures has for improved understanding of cancer progression and for personalized in vitro therapeutic testing is discussed.

Quantitative mass spectrometry analysis reveals a panel of nine proteins as diagnostic markers for colon adenocarcinomas

Adenocarcinomas are cancers originating from the gland forming cells of the colon and rectal lining, and are known to be the most common type of colorectal cancers. The current diagnosis strategies for colorectal cancers include biopsy, laboratory tests, and colonoscopy which are time consuming. Identification of protein biomarkers could aid in the detection of colon adenocarcinomas (CACs). In this study, tissue proteome of colon adenocarcinomas (n = 11) was compared with the matched control specimens (n = 11) using isobaric tags for relative and absolute quantitation (iTRAQ) based liquid chromatography-mass spectrometry (LC-MS/MS) approach. A list of 285 significantly altered proteins was identified in colon adenocarcinomas as compared to its matched controls, which are associated with growth and malignancy of the tumors. Protein interaction analysis revealed the association of altered proteins in colon adenocarcinomas with various transcription factors and their targets. A panel of nine proteins was validated using multiple reaction monitoring (MRM). Additionally, S100A9 was also validated using immunoblotting. The identified panel of proteins may serve as potential biomarkers and thereby aid in the detection of colon adenocarcinomas.

Proteome Heterogeneity in Colorectal Cancer

Tumor heterogeneity is an important feature of colorectal cancer (CRC) manifested by dynamic changes in gene expression, protein expression, and availability of different tumor subtypes. Recent publications in the past 10 years have revealed proteome heterogeneity between different colorectal tumors and within the same tumor site. This paper reviews recent research works on the proteome heterogeneity in CRC, which includes the heterogeneity within a single tumor (intratumor heterogeneity), between different anatomical sites at the same organ, and between primary and metastatic sites (intertumor heterogeneity). The potential use of proteome heterogeneity in precision medicine and its implications in biomarker discovery and therapeutic outcomes will be discussed. Identification of the unique proteome landscape between and within individual tumors is imperative for understanding cancer biology and the management of CRC patients.

Proteomic analysis of stromal proteins in different stages of colorectal cancer establishes Tenascin-C as a stromal biomarker for colorectal cancer metastasis

Tumor microenvironment is crucial to tumor development and metastasis. Little is known about the roles of stromal proteins in colorectal carcinogenesis. In this study, we used a combination of laser capture microdissection (LCM), iTRAQ labeling and two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS) to compare stromal proteomes in different stages of colorectal cancer. A total of 1966 proteins were identified, and 222 proteins presenting a significant fold change were quantified in different stages. Differentially expressed proteins (DEPs) were subjected to cluster and pathway analyses. We confirmed the differential expression of Tenascin-C and S100A9 using immunohistochemical analysis, and found that the expression levels of S100A9 and Tenascin-C were correlated with TNM stages and metastasis. In addition, our results showed that Tenascin-C was abundantly secreted by the colon cancer cells with high metastatic potential, and highly expressed in lymph nodes with metastasis. Our studies not only shed light on the mechanism by which stromal proteins contributed to colorectal carcinogenesis, but also identified Tenascin-C as a potential stromal biomarker for colorectal cancer metastasis.

Proteomic Profiling for Colorectal Cancer Biomarker Discovery

Nowadays, the ideal biomarker for colorectal cancer (CRC) has not been found. Two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) are suitable techniques for searching new biomarkers. In this chapter, we describe methodology for biomarker discovery based on a proteomic approach. In addition, special attention is given to the sample preparation, including protein extraction, fractionation, and cleanup, as we consider this a critical step. Comparing the proteomic profile of tumor and mucosa, we identified the nucleoside diphosphate kinase A (NDKA) protein as a candidate biomarker for CRC. Finally, we validated NDKA with an ELISA kit using serum samples from individuals of a screening cohort. Our results suggest that serum NDKA is a potential biomarker for screening of CRC and premalignant advanced adenomas (AA).

A Proteomics Analysis Reveals 9 Up-Regulated Proteins Associated with Altered Cell Signaling in Colon Cancer Patients

Colorectal cancer is the second most common cancer in women and third most common cancer in men. Cell signaling alterations in colon cancer, especially in aggressive metastatic tumors, require further investigations. The present study aims to compare the expression pattern of proteins associated with cell signaling in paired tumor and non-tumor samples of patients with colon cancer, as well as to define the cluster of proteins to differentiate patients with non-metastatic (Dukes' grade B) and metastatic (Dukes' grade C&D) colon cancer. Frozen tumor and non-tumor samples were collected after tumor resection from 19 patients with colon cancer. The Panorama™ Antibody Microarray-Cell Signaling kits were used for the analyses. The expression ratios of paired tumor/non-tumor samples were calculated for the each protein. We employed R packages 'samr', 'gplots', 'supclust' (pelora, wilma algorithms), 'glmnet' for the differential expression analysis, supervised clustering and penalized logistic regression. Significance analysis of microarrays revealed 9 significantly up-regulated proteins, including protein kinase C gamma, c-Myc, MDM2, pan cytokeratin, and 1 significantly down-regulated protein (GAP1) in tumoral mucosa. Pan-cytokeratin and APP were up-regulated in tumor versus non-tumor tissue, and were selected in the predictive cluster to discriminate colon cancer type. Higher levels of S-100b and phospho-Tau-pSer199/202 were confirmed as the predictors of non-metastatic colon cancer by all employed regression/clustering methods. Deregulated proteins in colon cancer are involved in oncogenic signal transduction, cell cycle control, and regulation of cytoskeleton/transport. Further studies are needed to validate potential protein markers of colon cancer development and metastatic progression.

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.

Towards personalized medicine of colorectal cancer

Efforts in colorectal cancer (CRC) research aim to improve early detection and treatment for metastatic stages which could translate into better prognosis of this disease. One of the major challenges that hinder these efforts is the heterogeneous nature of CRC and involvement of diverse molecular pathways. New large-scale 'omics' technologies are making it possible to generate, analyze and interpret biological data from molecular determinants of CRC. The developments of sophisticated computational analyses would allow information from different omics platforms to be integrated, thus providing new insights into the biology of CRC. Together, these technological advances and an improved mechanistic understanding might allow CRC to be clinically managed at the level of the individual patient. This review provides an account of the current challenges in CRC management and an insight into how new technologies could allow the development of personalized medicine for CRC.

Expression of NIBP and its clinical significance in human early colorectal cancer

AIM

To investigate the expression of NIBP and its clinical significance in early colorectal cancer.

PATIENTS AND METHODS

With immunohistochemistry, the expression of NIBP was detected in 23 patients of early colorectal cancer tissues, 102 patients of invasive colorectal cancer tissues, 32 patients of adenoma and 20 patients of normal tissues. The relationship between NIBP expression and clinicopathological characteristic of colorectal cancer were also analyzed.

RESULT

We found that the positive rates of NIBP was higher in early colorectal cancer tissues (82.6%, 19/23) than those in adenomas and normal tissues (x²=29.07, P<0.05), but not significant than those in invasive colorectal cancer (x²=1.79, P>0.05). Positivity for T1N0M0, T2N0M0, II, III and IV was 82.6% (19/23), 80.0% (4/5), 78.0% (32/41), 63.6% (21/33), 56.5% (13/23), respectively. With the increase in TNM stage, the positive rate of NIBP decreased, the positive rate of T1N0M0 is highest than other TNM stages, but no statistically significant (P>0.05).

CONCLUSION

These results suggested that NIBP is highly expressed in human early colorectal cancer tissues. NIBP might involve in the tumorigenesis and probably serve as a new marker for human early colorectal cancer.

Novel proteins from proteomic analysis of the trunk disease fungus Lasiodiplodia theobromae (Botryosphaeriaceae)

Many basic science questions remain regarding protein functions in the pathogen: host interaction, especially in the trunk disease fungi family, the Botryosphaeriaceae, which are a global problem for economically important plants, especially fruiting trees. Proteomics is a highly useful technology for studying protein expression and for discovering novel proteins in unsequenced and poorly annotated organisms. Current fungal proteomics approaches involve 2D SDS-PAGE and extensive, complex, protein extraction methodologies. In this work, a modified Folch extraction was applied to protein extraction to perform both de novo peptide sequencing and peptide fragmentation analysis/protein identification of the plant and human fungal pathogen Lasiodiplodia theobromae. Both bioinformatics approaches yielded novel peptide sequences from proteins produced by L. theobromae in the presence of exogenous triglycerides and glucose. These proteins and the functions they may possess could be targeted for further functional characterization and validation efforts, due to their potential uses in biotechnology and as new paradigms for understanding fungal biochemistry, such as the finding of allergenic enolases, as well as various novel proteases, including zinc metalloproteinases homologous to those found in snake venom. This work contributes to genomic annotation efforts, which, hand in hand with genomic sequencing, will help improve fungal bioinformatics databases for future studies of Botryosphaeriaceae. All data, including raw data, are available via the ProteomeXchange data repository with identifier PXD005283. This is the first study of its kind in Botryosphaeriaceae.

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.

Proteomic Profiling of Serial Prediagnostic Serum Samples for Early Detection of Colon Cancer in the U.S. Military

Background: Serum proteomic biomarkers offer a promising approach for early detection of cancer. In this study, we aimed to identify proteomic profiles that could distinguish colon cancer cases from controls using serial prediagnostic serum samples.Methods: This was a nested case-control study of active duty military members. Cases consisted of 264 patients diagnosed with colon cancer between 2001 and 2009. Controls were matched to cases on age, gender, race, serum sample count, and collection date. We identified peaks that discriminated cases from controls using random forest data analysis with a 2/3 training and 1/3 validation dataset. We then included epidemiologic data to see whether further improvement of model performance was obtainable. Proteins that corresponded to discriminatory peaks were identified.Results: Peaks with m/z values of 3,119.32, 2,886.67, 2,939.23, and 5,078.81 were found to discriminate cases from controls with a sensitivity of 69% and a specificity of 67% in the year before diagnosis. When smoking status was included, sensitivity increased to 76% while histories of other cancer and tonsillectomy raised specificity to 76%. Peaks at 2,886.67 and 3,119.32 m/z were identified as histone acetyltransferases while 2,939.24 m/z was a transporting ATPase subunit.Conclusions: Proteomic profiles in the year before cancer diagnosis have the potential to discriminate colon cancer patients from controls, and the addition of epidemiologic information may increase the sensitivity and specificity of discrimination.Impact: Our findings indicate the potential value of using serum prediagnostic proteomic biomarkers in combination with epidemiologic data for early detection of colon cancer. Cancer Epidemiol Biomarkers Prev; 26(5); 711-8. ©2016 AACR.

Protein content and functional characteristics of serum-purified exosomes from patients with colorectal cancer revealed by quantitative proteomics

Tumor cells of colorectal cancer (CRC) release exosomes into the circulation. These exosomes can mediate communication between cells and affect various tumor-related processes in their target cells. We present a quantitative proteomics analysis of the exosomes purified from serum of patients with CRC and normal volunteers; data are available via ProteomeXchange with identifier PXD003875. We identified 918 proteins with an overlap of 725 Gene IDs in the Exocarta proteins list. Compared with the serum-purified exosomes (SPEs) of normal volunteers, we found 36 proteins upregulated and 22 proteins downregulated in the SPEs of CRC patients. Bioinformatics analysis revealed that upregulated proteins are involved in processes that modulate the pretumorigenic microenvironment for metastasis. In contrast, differentially expressed proteins (DEPs) that play critical roles in tumor growth and cell survival were principally downregulated. Our study demonstrates that SPEs of CRC patients play a pivotal role in promoting the tumor invasiveness, but have minimal influence on putative alterations in tumor survival or proliferation. According to bioinformatics analysis, we speculate that the protein contents of exosomes might be associated with whether they are involved in premetastatic niche establishment or growth and survival of metastatic tumor cells. This information will be helpful in elucidating the pathophysiological functions of tumor-derived exosomes, and aid in the development of CRC diagnostics and therapeutics.

Determining protein biomarkers for DLBCL using FFPE tissues from HIV negative and HIV positive patients

DLBCL is the most common lymphoma subtype occurring in older populations as well as in younger HIV infected patients. The current treatment options for DLBCL are effective for most patients yet the relapse rate is high. While many biomarkers for DLBCL exist, they are not in clinical use due to low sensitivity and specificity. In addition, these biomarkers have not been studied in the HIV context. Therefore, the identification of new biomarkers for HIV negative and HIV positive DLBCL, may lead to a better understanding of the disease pathology and better therapeutic design. Protein biomarkers for DLBCL were determined using MALDI imaging mass spectrometry (IMS) and characterised using LC-MS. The expression of one of the biomarkers, heat shock protein (Hsp) 70, was confirmed on a separate cohort of samples using immunohistochemistry. The biomarkers identified in the study consisted of four protein clusters including glycolytic enzymes, ribosomal proteins, histones and collagen. These proteins could differentiate between control and tumour tissue, and the DLBCL immunohistochemical subtypes in both cohorts. The majority (41/52) of samples in the confirmation cohort were negative for Hsp70 expression. The HIV positive DLBCL cases had a higher percentage of cases expressing Hsp70 than their HIV negative counterparts. The non-GC subtype also frequently overexpressed Hsp70, confirming MALDI IMS data. The expression of Hsp70 did not correlate with survival in both the HIV negative and HIV positive cohort. This study identified potential biomarkers for HIV negative and HIV positive DLBCL from FFPE tissue sections. These may be used as diagnostic and prognostic markers complementary to current clinical management programmes for DLBCL.

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.

Dissecting characteristics and dynamics of differentially expressed proteins during multistage carcinogenesis of human colorectal cancer

AIM: To discover novel biomarkers for early diagnosis, prognosis or treatment of human colorectal cancer.

METHODS: iTRAQ 2D LC-MS/MS analysis was used to identify differentially expressed proteins (DEPs) in the human colonic epithelial carcinogenic process using laser capture microdissection-purified colonic epithelial cells from normal colon, adenoma, carcinoma in situ and invasive carcinoma tissues.

RESULTS: A total of 326 DEPs were identified, and four DEPs (DMBT1, S100A9, Galectin-10, and S100A8) with progressive alteration in the carcinogenic process were further validated by immunohistochemistry. The DEPs were involved in multiple biological processes including cell cycle, cell adhesion, translation, mRNA processing, and protein synthesis. Some of the DEPs involved in cellular process such as “translation” and “mRNA splicing” were progressively up-regulated, while some DEPs involved in other processes such as “metabolism” and “cell response to stress” was progressively down-regulated. Other proteins with up- or down-regulation at certain stages of carcinogenesis may play various roles at different stages of the colorectal carcinogenic process.

CONCLUSION: These findings give insights into our understanding of the mechanisms of colorectal carcinogenesis and provide clues for further investigation of carcinogenesis and identification of biomarkers.

Mining the Human Proteome: Biomarker Discovery for Human Cancer and Metastases

As our knowledge of the mechanisms underlying cancer development and progression has increased, so too have more effective, less toxic, and targeted therapies begun to reach the clinic. However, the full impact of these clinical advances and the practical success of the emerging field of precision medicine are dependent on the discovery and validation of sensitive and accurate biomarkers that can enable appropriate and rigorous sample type and patient selection, reliable longitudinal monitoring of therapeutic efficacy, and even risk assessment and early detection. Within the context of this review, we examine state-of-the-art approaches to the discovery and validation of noninvasive cancer biomarkers, with a specific emphasis on those that are protein or protein-associated ones. We also review sample selection strategies, currently utilized proteomic approaches for both discovery and validation requirements, and data analysis standards. Finally, we provide examples of these elements of biomarker discovery and validation from our own biomarker research.

What gastric cancer proteomic studies show about gastric carcinogenesis?

Gastric cancer is a complex, heterogeneous, and multistep disease. Over the past decades, several studies have aimed to determine the molecular factors that lead to gastric cancer development and progression. After completing the human genome sequencing, proteomic technologies have presented rapid progress. Differently from the relative static state of genome, the cell proteome is dynamic and changes in pathologic conditions. Proteomic approaches have been used to determine proteome profiles and identify differentially expressed proteins between groups of samples, such as neoplastic and nonneoplastic samples or between samples of different cancer subtypes or stages. Therefore, proteomic technologies are a useful tool toward improving the knowledge of gastric cancer molecular pathogenesis and the understanding of tumor heterogeneity. This review aimed to summarize the proteins or protein families that are frequently identified by using high-throughput screening methods and which thus may have a key role in gastric carcinogenesis. The increased knowledge of gastric carcinogenesis will clearly help in the development of new anticancer treatments. Although the studies are still in their infancy, the reviewed proteins may be useful for gastric cancer diagnosis, prognosis, and patient management.

Quantitative proteomics analysis to identify diffuse axonal injury biomarkers in rats using iTRAQ coupled LC-MS/MS

Diffuse axonal injury (DAI) is fairly common during a traumatic brain injury (TBI) and is associated with high mortality. Making an early diagnosis, appropriate therapeutic decisions, and an accurate prognostic evaluation of patients with DAI still pose difficulties for clinicians. The detailed mechanisms of axonal injury after head trauma have yet to be clearly defined and no reliable biomarkers are available for early DAI diagnosis. Therefore, this study employed an established DAI animal model in conjunction with an isobaric tag for relative and absolute quantification (iTRAQ)-based protein identification/quantification approach. Alterations in rat cerebral protein expression were quantified using iTRAQ coupled LC-MS/MS, with differentially expressed proteins between the control groups, sham and sham-injured, and the injury groups, animals that died immediately post-injury and those sacrificed at 1h, 6h, 1d, 3d and 7d post-injury, identified. A total of 1858 proteins were identified and quantified and comparative analysis identified ten candidate proteins that warranted further examination. Of the ten candidate DAI biomarkers, four proteins, citrate synthase (CS), synaptosomal-associated protein 25 (Snap25), microtubule-associated protein 1B (MAP1B) and Rho-associated protein kinase 2 (Rock2), were validated by subsequent Western blot and immunohistochemistry analyses. Our studies not only identified several novel biomarkers that may provide insight into the pathophysiological mechanisms of DAI, but also demonstrated the feasibility of iTRAQ-based quantitative proteomic analysis in cerebral tissue research.

Vascular endothelial growth factor -2578C/A polymorphism and colorectal cancer risk: A meta-analysis

BACKGROUND

The effects of the vascular endothelial growth factor (VEGF) gene -2578C/A polymorphism on colorectal cancer (CRC) risk have been investigated in some studies; however, the results of these studies were conflicting and ambiguous. Therefore, we aimed to do a meta-analysis to investigate the association of VEGF -2578C/A polymorphisms with CRC risk from all eligible case-control studies published to date.

MATERIALS AND METHODS

An electronic search of the PubMed, Embase and Medline was performed. Retrieve terms were utilized as following: ("VEGF a" [MeSH Terms]) and ("polymorphism, genetic" [MeSH Terms]) and ("colorectal neoplasms" [MeSH Terms]). The association between VEGF -2578C/A polymorphisms with CRC risk was calculated with odds ratios (ORs) and their corresponding 95% of confidence intervals (CIs), and stratified analysis was also conducted with respect to ethnicity.

RESULTS

A comprehensive meta-analysis of eight studies, including 2312 cases and 2308 controls was performed in this work. Combined analysis revealed that a significant association between the VEGF -2578C/A polymorphism with CRC risk was identified in three comparison models including C allele versus A allele (OR = 0.85, 95% CI 0.75-0.97, P = 0.02), AA versus CA + CC (OR = 1.28, 95% CI 1.09-1.51, P = 0.003), and AA versus CC (OR = 0.77, 95% CI 0.64-0.93, P = 0.006). Moreover, a similar result was obtained in the subgroup analysis that comparison models of C allele versus. A allele (OR = 0.85, 95% CI 0.76-0.95, P = 0.004), AA versus CA + CC (OR = 1.31, 95% CI 1.09-1.57, P = 0.004), and AA versus CC (OR = 0.73, 95% CI 0.59-0.90, P = 0.004) was confirmed to be associated with CRC risk in Caucasian.

CONCLUSION

It has been proved that the C allele versus A allele, AA versus CA + CC, and AA versus CC comparison models of VEGF -2578C/A polymorphism might be risk factors for CRC, but further studies with larger sample sizes are required to make a better assessment of above association.

Evaluation of a 5-Marker Blood Test for Colorectal Cancer Early Detection in a Colorectal Cancer Screening Setting

PURPOSE

In initial studies that included colorectal cancer patients undergoing diagnostic colonoscopy, we had identified a serum marker combination able to detect colorectal cancer with similar diagnostic performance as fecal immunochemical test (FIT). In this study, we aimed to validate the results in participants of a large colorectal cancer screening study conducted in the average-risk, asymptomatic screening population.

EXPERIMENTAL DESIGN

We tested serum samples from 1,200 controls, 420 advanced adenoma patients, 4 carcinoma in situ patients, and 36 colorectal cancer patients with a 5-marker blood test [carcinoembryonic antigen (CEA)+anti-p53+osteopontin+seprase+ferritin]. The diagnostic performance of individual markers and marker combinations was assessed and compared with stool test results.

RESULTS

AUCs for the detection of colorectal cancer and advanced adenomas with the 5-marker blood test were 0.78 [95% confidence interval (CI), 0.68-0.87] and 0.56 (95% CI, 0.53-0.59), respectively, which now is comparable with guaiac-based fecal occult blood test (gFOBT) but inferior to FIT. With cutoffs yielding specificities of 80%, 90%, and 95%, the sensitivities for the detection of colorectal cancer were 64%, 50%, and 42%, and early-stage cancers were detected as well as late-stage cancers. For osteopontin, seprase, and ferritin, the diagnostic performance in the screening setting was reduced compared with previous studies in diagnostic settings while CEA and anti-p53 showed similar diagnostic performance in both settings.

CONCLUSIONS

Performance of the 5-marker blood test under screening conditions is inferior to FIT even though it is still comparable with the performance of gFOBT. CEA and anti-p53 could contribute to the development of a multiple marker blood-based test for early detection of colorectal cancer.

Applying Genomics and Proteomics in Translational Surgical Oncology Research

BACKGROUND

Translational surgical research can range from investigating clinically oriented basic pathophysiological research via the correlation of molecular findings with a patient's clinical outcome to conducting treatment response studies. Herein, the specialist's opinion as a 'surgeon scientist' plays a pivotal role, e.g. in planning experimental setups focusing on the clinically most relevant needs. SUMMARY AND KEY MESSAGES: This review provides a survey of genomic and proteomic technologies and gives an up-to-date overview of those studies applying these technologies exemplarily in colorectal cancer-based biomarker research. Although current results are promising, future validation studies within multicenter networks are required to promote the translation of 'omics' from bench to bedside. In this endeavor, departments of surgery and institutes of experimental surgery together should play a fundamental role. The program for 'clinician scientists' recently launched by the German Research Society (DFG) could be one tool to promote interdisciplinary networks and surgeons' impact on translational research.

Molecular biomarkers in colorectal carcinoma

Colorectal cancer is a tumor with increasing incidence which represents one of the first leading causes of death worldwide. Gene alterations described for colorectal cancer include genome instability (microsatellite and chromosomal instability), CpG islands methylator phenotype, microRNA, histone modification, protein biomarkers, gene mutations (RAS, BRAF, PI3K, TP53, PTEN) and polymorphisms (APC, CTNNB1, DCC). In this article, biomarkers with prognostic value commonly found in colorectal cancer will be reviewed.