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

Exploring prognostic biomarkers in pathological images of colorectal cancer patients via deep learning

Hematoxylin and eosin (H&E) whole slide images provide valuable information for predicting prognostic outcomes in colorectal cancer (CRC) patients. However, extracting prognostic indicators from pathological images is challenging due to the subtle complexities of phenotypic information. We trained a weakly supervised deep learning model on data from 640 CRC patients in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial dataset and validated it using data from 522 CRC patients in the cancer genome atlas (TCGA) dataset. We created the colorectal cancer risk score (CRCRS) to assess patient prognosis, visualized the pathological phenotype of the risk score using Grad-CAM, and employed multiomics data from the TCGA CRC cohort to investigate the potential biological mechanisms underlying the risk score. The overall survival analysis revealed that the CRCRS served as an independent prognostic indicator for both the PLCO cohort (p < 0.001) and the TCGA cohort (p < 0.001), with its predictive efficacy remaining unaffected by the clinical staging system. Additionally, satisfactory chemotherapeutic benefits were observed in stage II/III CRC patients with high CRCRS but not in those with low CRCRS. A pathomics nomogram constructed by integrating the CRCRS with the tumor-node-metastasis (TNM) staging system enhanced prognostic prediction accuracy compared with using the TNM staging system alone. Noteworthy features of the risk score were identified, such as immature tumor mesenchyme, disorganized gland structures, small clusters of cancer cells associated with unfavorable prognosis, and infiltrating inflammatory cells associated with favorable prognosis. The TCGA multiomics data revealed potential correlations between the CRCRS and the activation of energy production and metabolic pathways, the tumor immune microenvironment, and genetic mutations in APC, SMAD2, EEF1AKMT4, EPG5, and TANC1. In summary, our deep learning algorithm identified the CRCRS as a prognostic indicator in CRC, providing a significant approach for prognostic risk stratification and tailoring precise treatment strategies for individual patients.

UHPLC-HRMS-based Multiomics to Explore the Potential Mechanisms and Biomarkers for Colorectal Cancer

BACKGROUND

Understanding the metabolic changes in colorectal cancer (CRC) and exploring potential diagnostic biomarkers is crucial for elucidating its pathogenesis and reducing mortality. Cancer cells are typically derived from cancer tissues and can be easily obtained and cultured. Systematic studies on CRC cells at different stages are still lacking. Additionally, there is a need to validate our previous findings from human serum.

METHODS

Ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics and lipidomics were employed to comprehensively measure metabolites and lipids in CRC cells at four different stages and serum samples from normal control (NR) and CRC subjects. Univariate and multivariate statistical analyses were applied to select the differential metabolites and lipids between groups. Biomarkers with good diagnostic efficacy for CRC that existed in both cells and serum were screened by the receiver operating characteristic curve (ROC) analysis. Furthermore, potential biomarkers were validated using metabolite standards.

RESULTS

Metabolite and lipid profiles differed significantly among CRC cells at stages A, B, C, and D. Dysregulation of glycerophospholipid (GPL), fatty acid (FA), and amino acid (AA) metabolism played a crucial role in the CRC progression, particularly GPL metabolism dominated by phosphatidylcholine (PC). A total of 46 differential metabolites and 29 differential lipids common to the four stages of CRC cells were discovered. Eight metabolites showed the same trends in CRC cells and serum from CRC patients compared to the control groups. Among them, palmitoylcarnitine and sphingosine could serve as potential biomarkers with the values of area under the curve (AUC) more than 0.80 in the serum and cells. Their panel exhibited excellent performance in discriminating CRC cells at different stages from normal cells (AUC = 1.00).

CONCLUSIONS

To our knowledge, this is the first research to attempt to validate the results of metabolism studies of serum from CRC patients using cell models. The metabolic disorders of PC, FA, and AA were closely related to the tumorigenesis of CRC, with PC being the more critical factor. The panel composed of palmitoylcarnitine and sphingosine may act as a potential biomarker for the diagnosis of CRC, aiding in its prevention.

Current Status and Emerging Trends in Colorectal Cancer Screening and Diagnostics

Colorectal cancer (CRC) is a prevalent and potentially fatal disease categorized based on its high incidences and mortality rates, which raised the need for effective diagnostic strategies for the early detection and management of CRC. While there are several conventional cancer diagnostics available, they have certain limitations that hinder their effectiveness. Significant research efforts are currently being dedicated to elucidating novel methodologies that aim at comprehending the intricate molecular mechanism that underlies CRC. Recently, microfluidic diagnostics have emerged as a pivotal solution, offering non-invasive approaches to real-time monitoring of disease progression and treatment response. Microfluidic devices enable the integration of multiple sample preparation steps into a single platform, which speeds up processing and improves sensitivity. Such advancements in diagnostic technologies hold immense promise for revolutionizing the field of CRC diagnosis and enabling efficient detection and monitoring strategies. This article elucidates several of the latest developments in microfluidic technology for CRC diagnostics. In addition to the advancements in microfluidic technology for CRC diagnostics, the integration of artificial intelligence (AI) holds great promise for further enhancing diagnostic capabilities. Advancements in microfluidic systems and AI-driven approaches can revolutionize colorectal cancer diagnostics, offering accurate, efficient, and personalized strategies to improve patient outcomes and transform cancer management.

UHPLC-HRMS-based serum untargeted lipidomics: Phosphatidylcholines and sphingomyelins are the main disturbed lipid markers to distinguish colorectal advanced adenoma from cancer

Colorectal advanced adenoma (CAA) is a key precancerous lesion of colorectal cancer (CRC), and early diagnosis can lessen CRC morbidity and mortality. Although abnormal lipid metabolism is associated with the development of CRC, there are no studies on the biomarkers and mechanism of lipid metabolism linked to CAA carcinogenesis. Hence, we performed a lipidomics study of serum samples from 46 CAA, and 50 CRC patients by the ultra high-performance liquid chromatography tandem high resolution mass spectrometry (UHPLC-HRMS) in both electrospray ionization (ESI) modes. Differential lipids were selected by univariate and multivariate statistics analysis, and their diagnostic performance was evaluated using a receiver operating characteristic curve (ROC) analysis. Combining P < 0.05 and variable importance in projection (VIP) > 1, 59 differential lipids were obtained totally. Ten of them showed good discriminant ability for CAA and CRC (AUC > 0.900). Especially, the lipid panel consisting of PC 44:5, PC 35:6e, and SM d40:3 showed the highest selection frequency and outperformed (AUC = 0.952). Additionally, phosphatidylcholine (PC) and sphingomyelin (SM) were the main differential and high-performance lipids. In short, this is the first study to explore the biomarkers and mechanism for CAA-CRC sequence with large-scale serum lipidomics. The findings should provide valuable reference and new clues for the development of diagnostic and therapeutic strategies of CRC.

Aberrant circulating tumor DNA methylation and exosomal microRNA biomarkers for early detection of colorectal cancer

INTRODUCTION

Colorectal cancer (CRC) became the third most commonly diagnosed malignancy and the second leading cause of cancer death in 2020. However, the rates of early screening and early diagnosis for CRC remain unsatisfactory. Thus, it is essential to explore the initiating factors of CRC and strategies for its early diagnosis. Research progress in liquid biopsy has led to the finding that circulating tumor-derived DNA (ctDNA) and exosomes play vital roles in early detection of CRC. THE APPLICATIONS OF LIQUID BIOPSY FOR EARLY DETECTION OF COLORECTAL CANCER: Moreover, the increased understanding of epigenetics has highlighted the role of ctDNA methylation in CRC carcinogenesis, and the detection of aberrant ctDNA methylation markers is a feasible strategy for diagnosis of early-stage CRC. Among exosomal markers, microRNAs (miRNAs) are abundant and are the most researched. Upregulated or downregulated expression of exosome-derived miRNAs can indicate the occurrence of early-stage CRC.

FUTURE PERSPECTIVE

The current research progress on aberrant ctDNA methylation and tumor exosomal miRNA biomarkers in early detection of CRC is summarized in this review, and the advantages and shortcomings of the methods are discussed.

Occult colon cancer with liver abscess and pancreatitis as the first manifestations: A case report

INTRODUCTION

Klebsiella pneumoniae-induced liver abscess (KP-PLA) is a common type of pyogenic liver abscess, severe acute pancreatitis (SAP) has high mortality, and poor prognosis in advanced colon cancer. There have been no report of SAP complicated with colon cancer after KP-PLA as so far. In this study, we reported a case of SAP secondary to KP-PLA with colon cancer for the first time, so as to provide reference for clinical diagnosis and treatment of these diseases.

PATIENT CONCERNS AND DIAGNOSIS

A 64-year-old woman with a history of diabetes visited our hospital with abdominal pain for 5 + days. He was diagnosed with KP-PLA a month ago, which had not healed when he was admitted. He was diagnosed with SAP, and histological examination of colonic biopsy confirmed the diagnosis of moderately differentiated adenocarcinoma.

INTERVENTIONS AND OUTCOMES

He was treated with intravenous antibiotics and underwent modified endoscopic mucosal resection under colonoscopy. We conducted a 2-month follow-up, and there was no recurrence of liver abscess and pancreatitis.

CONCLUSION

Screening for intestinal tumors is necessary in patients with cryptogenic liver abscess, especially KP-PLA with diabetes.

UHPLC-HRMS–based serum lipisdomics reveals novel biomarkers to assist in the discrimination between colorectal adenoma and cancer

The development of a colorectal adenoma (CA) into carcinoma (CRC) is a long and stealthy process. There remains a lack of reliable biomarkers to distinguish CA from CRC. To effectively explore underlying molecular mechanisms and identify novel lipid biomarkers promising for early diagnosis of CRC, an ultrahigh-performance liquid chromatography tandem high-resolution mass spectrometry (UHPLC-HRMS) method was employed to comprehensively measure lipid species in human serum samples of patients with CA and CRC. Results showed significant differences in serum lipid profiles between CA and CRC groups, and 85 differential lipid species (P &lt; 0.05 and fold change &gt; 1.50 or &lt; 0.67) were discovered. These significantly altered lipid species were mainly involved in fatty acid (FA), phosphatidylcholine (PC), and triacylglycerol (TAG) metabolism with the constituent ratio &gt; 63.50%. After performance evaluation by the receiver operating characteristic (ROC) curve analysis, seven lipid species were ultimately proposed as potential biomarkers with the area under the curve (AUC) &gt; 0.800. Of particular value, a lipid panel containing docosanamide, SM d36:0, PC 36:1e, and triheptanoin was selected as a composite candidate biomarker with excellent performance (AUC = 0.971), and the highest selected frequency to distinguish patients with CA from patients with CRC based on the support vector machine (SVM) classification model. To our knowledge, this study was the first to undertake a lipidomics profile using serum intended to identify screening lipid biomarkers to discriminate between CA and CRC. The lipid panel could potentially serve as a composite biomarker aiding the early diagnosis of CRC. Metabolic dysregulation of FAs, PCs, and TAGs seems likely involved in malignant transformation of CA, which hopefully will provide new clues to understand its underlying mechanism.

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.

Serum untargeted lipidomics by UHPLC-ESI-HRMS aids the biomarker discovery of colorectal adenoma

BACKGROUND

Colorectal adenoma (CA) is an important precancerous lesion and early screening target of colorectal cancer (CRC). Lipids with numerous physiological functions are proved to be involved in the development of CRC. However, there is no lipidomic study with large-scale serum samples on diagnostic biomarkers for CA.

METHODS

The serum lipidomics of CA patients (n = 50) and normal control (NR) (n = 50) was performed by ultra high performance liquid chromatography-high resolution mass spectrometry with electrospray ionization (UHPLC-ESI-HRMS). Univariate and multivariate statistical analyses were utilized to screen the differential lipids between groups, and combining the constituent ratio analysis and diagnostic efficiency evaluation by receiver operating characteristic (ROC) curve disclosed the potential mechanism and biomarkers for CA.

RESULTS

There were obvious differences in serum lipid profiles between CA and NR groups. Totally, 79 differential lipids were selected by criterion of P < 0.05 and fold change > 1.5 or < 0.67. Triacylglycerols (TAGs) and phosphatidylcholines (PCs) were the major differential lipids with ratio > 60%, indicating these two lipid metabolic pathways showed evident disequilibrium, which could contribute to CA formation. Of them, 12 differential lipids had good diagnostic ability as candidate biomarkers for CA (AUC ≥ 0.900) by ROC analysis.

CONCLUSIONS

To our knowledge, this is the first attempt to profile serum lipidomics and explore lipid biomarkers of CA to help early screening of CRC. 12 differential lipids are obtained to act as potential diagnostic markers of CA. PCs and fatty acids were the main dysregulated biomarkers for CA in serum.

Association of IGF-1 and IGFBP-3 levels with gastric cancer: A systematic review and meta-analysis

PURPOSE

Many studies have investigated the association between serum IGF-1 and IGFBP levels with gastric cancer (GC), but the results remained inconclusive. In this work, we performed a systematic review and meta-analysis to examine the precise association of serum levels of IGF-1 and IGFBP with GC.

METHODS

A comprehensive systematic search was carried out in PubMed/MEDLINE, SCOPUS, Web of Science, and EMBASE databases for (nested) case-control studies that reported the levels of IGF-1 and IGFBP in GC cases and healthy controls, from inception until October 2020. Weighted mean difference (WMD) was calculated for estimating combined effect size. Subgroup analysis was performed to identify the source of heterogeneity among studies.

RESULTS

We found eight and five eligible studies (with 1541 participants) which provided data for IGF-1 and IGFBP, respectively. All studies on IGFBP reported the IGFBP-3 isoform. The pooled results indicate that GC patients had significantly lower serum IGF-1 [WMD = -26.21 ng/mL (95% CI, -45.58 to -6.85; P = .008)] and IGFBP-3 [WMD = -0.41 ng/mL (95% CI, -0.80 to -0.01; P = .04; I²  = 89.9%; P < .001)] levels than those in healthy subjects. Significant heterogeneity was observed in the association, which could be attributed to the sample size of the studies.

CONCLUSIONS

In conclusion, our study reveals a significantly lower level of IGF-1 and IGFBP-3 in GC patients compared with healthy control subjects.

Molecular tissue profiling by MALDI imaging: recent progress and applications in cancer research

Matrix-assisted laser desorption/ionization (MALDI) imaging is an emergent technology that has been increasingly adopted in cancer research. MALDI imaging is capable of providing global molecular mapping of the abundance and spatial information of biomolecules directly in the tissues without labeling. It enables the characterization of a wide spectrum of analytes, including proteins, peptides, glycans, lipids, drugs, and metabolites and is well suited for both discovery and targeted analysis. An advantage of MALDI imaging is that it maintains tissue integrity, which allows correlation with histological features. It has proven to be a valuable tool for probing tumor heterogeneity and has been increasingly applied to interrogate molecular events associated with cancer. It provides unique insights into both the molecular content and spatial details that are not accessible by other techniques, and it has allowed considerable progress in the field of cancer research. In this review, we first provide an overview of the MALDI imaging workflow and approach. We then highlight some useful applications in various niches of cancer research, followed by a discussion of the challenges, recent developments and future prospect of this technique in the field.

Identification of hub genes and functional modules in colon adenocarcinoma based on public databases by bioinformatics analysis

Background

Colon adenocarcinoma (COAD) is one of the most common cancers in the world. Although an extensive effort has been made to elucidate its pathogenesis, the underlying molecular mechanisms and genetic characteristics remain elusive.

Methods

In this study, protein-coding transcript expression profiles of COAD were downloaded from the Cancer RNA-Seq Nexus (CRN) database. They were then integrated to identify the overlapping transcripts expressed in every COAD RNA sequencing (RNA-seq) subset. The functional annotation of these overlapping genes (OLGs) involved noting their biological process (BP), cellular components (CC), molecular function (MF) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway in the Database for Annotation, Visualization and Integrated Discovery (DAVID). Protein-protein interaction (PPI) networks were then constructed and analyzed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape 3.8.2.

Results

A total of 10 hub genes and 3 functional modules were screened by the plugin cytoHubba and MCODE, respectively. The plugin ClueGO and DAVID were used for the functional enrichment analyses of both hub genes and modules. The expression of hub genes was verified through the gene expression profiling interactive analysis (GEPIA) database. Survival analysis of the hub genes revealed that low expressions of ADCY5, GNG2, and PTPRC were significantly associated with an improved COAD prognosis. Furthermore, the expression level of ADCY5 in stages I/II was lower than that in stages III/IV, which seems to explain why the low expression of ADCY5 results in a better prognosis.

Conclusions

The identification of hub genes, functional modules, and pathways have the potential to improve our understanding of the causes and underlying molecular events of COAD. The hub gene ADCY5 could also be a prognostic monitoring indicator or therapeutic target in the treatment of COAD.

Management of oxidative stress and inflammation in cardiovascular diseases: mechanisms and challenges

Cardiovascular diseases (CVDs) have diverse physiopathological mechanisms with interconnected oxidative stress and inflammation as one of the common etiologies which result in the onset and development of atherosclerotic plaques. In this review, we illustrate this strong crosstalk between oxidative stress, inflammation, and CVD. Also, mitochondrial functions underlying this crosstalk, and various approaches for the prevention of redox/inflammatory biological impacts will be illustrated. In part, we focus on the laboratory biomarkers and physiological tests for the evaluation of oxidative stress status and inflammatory processes. The impact of a healthy lifestyle on CVD onset and development is displayed as well. Furthermore, the differences in oxidative stress and inflammation are related to genetic susceptibility to cardiovascular diseases and the variability in the assessment of CVDs risk between individuals; Omics technologies for measuring oxidative stress and inflammation will be explored. Finally, we display the oxidative stress-related microRNA and the functions of the redox basis of epigenetic modifications.

Potential biomarkers for inherited thrombocytopenia 2 identified by plasma proteomics

Inherited thrombocytopenia 2 (THC2) is difficult to diagnose due to the lack of specific clinical characteristics and diagnostic methods. To identify potential plasma protein biomarkers for THC2, we collected the plasma samples from a THC2 family (9 THC2 and 15 non-THC2 members), enriched the medium and low abundant proteins using Proteominer and analyzed the protein profiles using the liquid chromatography-mass spectrometry in data independent acquisition mode. Initially, we detected 784 proteins in the plasma samples of this family and identified 27 up-regulated and 36 down-regulated in the THC2 group compared to the non-THC2 group (|log₂ ratio| >1 and p-value <0.05). To improve the predictive power, top eight dysregulated proteins (B7Z2B4, LTF, HP, ERN1, IGHV1-8, A0A0X9V9C4, VH6DJ, and D3JV41) were selected by an area under the curve-based random forest process to construct a clinical model. Multivariate analysis with random forest and support vector machine showed that the prediction model provided high discrimination ability for THC2 diagnosis (AUC: 1.000 and 0.967, respectively). The potential plasma protein biomarkers will be tested in more THC2 patients and other thrombocytopenia patients to further validate their specificity and sensitivity.

Association of circulating leptin and adiponectin levels with colorectal cancer risk: A systematic review and meta-analysis of case-control studies

PURPOSE

Leptin and adiponectin are adipokines which have been commonly implicated in carcinogenesis. As such, many studies have investigated the association of circulating leptin and adiponectin levels with colorectal cancer (CRC) risk. However, the results remained inconsistent.

METHODS

In this work, we performed a systematic review and meta-analysis to precisely examine the association between circulating levels of leptin and adiponectin and CRC risk. A systematic literature search was performed in PubMed/MEDLINE, Scopus, Web of Science, and EMBASE databases from inception until October 2020. The pooled effect size was then estimated by calculating the odds ratio (OR).

RESULTS

A total of 23 records (comprising 26 studies) were included in the meta-analysis. The overall analysis found that circulating levels of leptin and adiponectin were not significantly associated with CRC risk (P > 0.05). Interestingly, subgroup analysis revealed that a higher level of adiponectin was significantly associated with an increased CRC risk among overweight individuals (OR = 1.16; 95 % CI: 1.02, 1.32), and a decreased CRC risk among normal weight individuals (OR = 0.76; 95 % CI: 0.62, 0.92). Besides, a higher level of adiponectin was also significantly associated with a decreased risk of CRC in men (OR = 0.76; 95 % CI: 0.59, 0.98).

CONCLUSIONS

In conclusion, circulating leptin level was not associated with CRC risk, but that of adiponectin was associated with CRC risk only in specific subgroups.

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.

Proteomics of Colorectal Cancer: Tumors, Organoids, and Cell Cultures-A Minireview

Proteomics, the study of the complete protein composition of a sample, is an important field for cancer research. Changes in the proteome can serve as a biomarker of cancer or lead to the development of a targeted therapy. This minireview will focus on mass spectrometry-based proteomics studies applied specifically to colorectal cancer, particularly the variety of cancer model systems used, including tumor samples, two-dimensional (2D) and three-dimensional (3D) cell cultures such as spheroids and organoids. A thorough discussion of the application of these systems will accompany the review of the literature, as each provides distinct advantages and disadvantages for colorectal cancer research. Finally, we provide conclusions and future perspectives for the application of these model systems to cancer research as a whole.

PLA-PEG nanospheres decorated with phage display selected peptides as biomarkers for detection of human colorectal adenocarcinoma

Peptide-mediated targeting to colorectal cancer can increase selectivity and specificity of this cancer diagnosis acting as biomarkers. The present work aimed to select peptides using the phage display technique and associate the peptides with polymeric nanospheres in order to evaluate their cytotoxicity and selectivity during cell interaction with Caco-2 human colon tumor cell line. Two peptides identified by phage display (peptide-1 and peptide-2) were synthesized and exhibited purity higher than 84%. Poly(lactic acid)-block-polyethylene glycol nanospheres were prepared by nanoprecipitation and double emulsion methods in order to load the two peptides. Nanoparticles ranged in size from 114 to 150 nm and peptide encapsulation efficiency varied from 16 to 32%, depending on the methodology. No cytotoxic activity was observed towards Caco-2 tumor cell line, either free or loaded peptides in concentrations up to 3 μM at incubation times of 6 and 24 h, indicating safety as biomarkers. Fluorescein isothiocyanate-labeled peptides allowed evaluating selective interactions with Caco-2 cells, where peptide-1 entrapped in nanospheres showed greater intensity of co-localized cell fluorescence, in comparison to peptide-2. Peptide-1 loaded in nanospheres revealed promising to be investigated in further studies of selectivity with other human colon rectal cells as a potential biomarker.Graphical abstract.

Comparative Proteomics and Secretomics Revealed Virulence and Antibiotic Resistance-Associated Factors in Vibrio parahaemolyticus Recovered From Commonly Consumed Aquatic Products

Vibrio parahaemolyticus is a seafoodborne pathogen that can cause severe gastroenteritis and septicemia diseases in humans and even death. The emergence of multidrug-resistant V. parahaemolyticus leads to difficulties and rising costs of medical treatment. The bacterium of environmental origins containing no major virulence genes (tdh and trh) has been reported to be associated with infectious diarrhea disease as well. Identification of risk factors in V. parahaemolyticus is imperative for assuming food safety. In this study, we obtained secretomic and proteomic profiles of V. parahaemolyticus isolated from 12 species of commonly consumed aquatic products and identified candidate protein spots by using two-dimensional gel electrophoresis and liquid chromatography tandem mass spectrometry techniques. A total of 11 common and 28 differential extracellular proteins were found from distinct secretomic profiles, including eight virulence-associated proteins: outer membrane channel TolC, maltoporin, elongation factor Tu, enolase, transaldolase, flagellin C, polar flagellin B/D, and superoxide dismutase, as well as five antimicrobial and/or heavy metal resistance-associated ABC transporter proteins. Comparison of proteomic profiles derived from the 12 V. parahaemolyticus isolates also revealed five intracellular virulence-related proteins, including aldehyde-alcohol dehydrogenase, outer membrane protein A, alkyl hydroperoxide reductase C, phosphoenolpyruvate-protein phosphotransferase, and phosphoglycerate kinase. Additionally, our data indicated that aquatic product matrices significantly altered proteomic profiles of the V. parahaemolyticus isolates with a number of differentially expressed proteins identified. The results in this study meet the increasing need for novel diagnosis candidates of the leading seafoodborne pathogen worldwide.

Analysing the nanoparticle-protein corona for potential molecular target identification

When nanoparticles are introduced into biological systems, host proteins tend to associate on the particle surface to form a protein layer termed the "protein corona" (PC). Identifying the proteins that constitute the PC can yield useful information about nanoparticle processing, bio-distribution, toxicity and clearance. Similarly, characterizing and identifying proteins within the PC from patient samples provides opportunities to probe disease proteomes and identify molecules that influence the disease process. Thus, nanoparticles represent unique probing tools for discovery of molecular targets for diseases. Here, we report a first review on target identification using nanoparticles in biological samples based on analysing physico chemical interactions. We also summarize the evolution of the PC surrounding various nano-systems, comment on PC signature, address PC complexity in fluids, and outline challenges associated with analysing the PC. In addition, the influence on PC formation of various nanoparticle parameters is summarized; nanoparticle characteristics considered include size, charge, temperature, and surface modifications for both organic and inorganic nanomaterials. We also discuss the advantages of nanotechnology, over other more invasive and laborious methods, for identifying potential diagnostic and therapeutic targets.

Identification of salivary volatile organic compounds as potential markers of stomach and colorectal cancer: A pilot study

OBJECTIVES

The purpose of the pilot study was to determine the potential diagnostic capabilities for the analysis of oxygen-containing salivary volatile organic compounds (VOCs) in stomach and colorectal cancer.

METHODS

Saliva samples of 11 patients with stomach cancer, 18 patients with colorectal cancer, and 16 healthy volunteers were analyzed through capillary gas chromatography. The levels of lipid peroxidation products and catalase activity were determined in all samples. To assess saliva diagnostic potential, we constructed a Classification and Regression Tree (CART).

RESULTS

It was shown that the use of a combination of saliva VOCs (acetaldehyde, acetone, propanol-2, and ethanol) allowed classification into Cancer/Control groups with a sensitivity and specificity of 95.7 and 90.9%, respectively. To clarify the location of the tumor, it was necessary to add a methanol level; in this case, the sensitivity for detecting stomach and colorectal cancer was 80.0% and 92.3%, respectively, while the specificity in both cases was 100%. When the lipid peroxidation product content was added to the VOC indicators, they were selected as the main factors for constructing the decision tree. For classification into Cancer/Control groups, only the triene conjugate and Schiff base content in saliva was sufficient. The combination of VOCs in saliva and lipid peroxidation indices improved the sensitivity and specificity for classification to 100%.

CONCLUSION

Preliminary data were obtained on the sensitivity and specificity of the diagnosis of stomach and colorectal cancer, which confirmed the promise of further studies on saliva VOCs for the purpose of clinical laboratory diagnostics.

Electrochemical Biosensors for Determination of Colorectal Tumor Biomarkers

The accurate determination of specific tumor markers associated with cancer with non-invasive or minimally invasive procedures is the most promising approach to improve the long-term survival of cancer patients and fight against the high incidence and mortality of this disease. Quantification of biomarkers at different stages of the disease can lead to an appropriate and instantaneous therapeutic action. In this context, the determination of biomarkers by electrochemical biosensors is at the forefront of cancer diagnosis research because of their unique features such as their versatility, fast response, accurate quantification, and amenability for multiplexing and miniaturization. In this review, after briefly discussing the relevant aspects and current challenges in the determination of colorectal tumor markers, it will critically summarize the development of electrochemical biosensors to date to this aim, highlighting the enormous potential of these devices to be incorporated into the clinical practice. Finally, it will focus on the remaining challenges and opportunities to bring electrochemical biosensors to the point-of-care testing.

Antioxidant enzymes change in different non-metastatic stages in tumoral and peritumoral tissues of colorectal cancer

Antioxidant defences and oxidative stress are related to development, progression and malignancy of colorectal cancer. However, their role in early stages of cancer remains unknown. More and more recent studies have revealed that non-tumour adjacent tissue is not a normal tissue. Thus, our aim was to analyse protein levels of MnSOD (Manganese Superoxide Dismutase), acMnSOD (Acetylated Manganese superoxide Dismutase), SIRT3 (Sirtuin 3), CuZnSOD (Cupper Zinc Superoxide Dismutase), CAT (Catalase), GPx (Glutathione Peroxidase), and GRd (Glutathione Reductase) both in tumour and non-tumour adjacent tissue from colorectal cancer patients by western blot. Non-tumour adjacent tissue seemed to have higher levels of antioxidant enzymes that detoxify hydrogen peroxide compared to tumour tissue. In contrast, tumour tissue had higher levels of MnSOD and acMnSOD. Furthermore, most of the proteins analysed showed significant differences between stage I and II in both non-tumour adjacent and tumour tissue. This could indicate that antioxidant enzymes, especially MnSOD, play a crucial role in early stages of colorectal cancer in both tissues, so they could be analysed as novel biomarkers to improve colorectal cancer diagnosis.

Image-Based Network Analysis of DNp73 Expression by Immunohistochemistry in Rectal Cancer Patients

Background: Rectal cancer is a disease characterized with tumor heterogeneity. The combination of surgery, radiotherapy, and chemotherapy can reduce the risk of local recurrence. However, there is a significant difference in the response to radiotherapy among rectal cancer patients even they have the same tumor stage. Despite rapid advances in knowledge of cellular functions affecting radiosensitivity, there is still a lack of predictive factors for local recurrence and normal tissue damage. The tumor protein DNp73 is thought as a biomarker in colorectal cancer, but its clinical significance is still not sufficiently investigated, mainly due to the limitation of human-based pathology analysis. In this study, we investigated the predictive value of DNp73 in patients with rectal adenocarcinoma using image-based network analysis.

Methods: The fuzzy weighted recurrence network of time series was extended to handle multi-channel image data, and applied to the analysis of immunohistochemistry images of DNp73 expression obtained from a cohort of 25 rectal cancer patients who underwent radiotherapy before surgery. Two mathematical weighted network properties, which are the clustering coefficient and characteristic path length, were computed for the image-based networks of the primary tumor (obtained after operation) and biopsy (obtained before operation) of each cancer patient.

Results: The ratios of two weighted recurrence network properties of the primary tumors to biopsies reveal the correlation of DNp73 expression and long survival time, and discover the non-effective radiotherapy to a cohort of rectal cancer patients who had short survival time.

Conclusion: Our work contributes to the elucidation of the predictive value of DNp73 expression in rectal cancer patients who were given preoperative radiotherapy. Mathematical properties of fuzzy weighted recurrence networks of immunohistochemistry images are not only able to show the predictive factor of DNp73 expression in the patients, but also reveal the identification of non-effective application of radiotherapy to those who had poor overall survival outcome.

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.

An omics perspective on drug target discovery platforms

The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to disease, and to evaluate the efficacy, safety and commercial potential of the target. The high-throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets (e.g. DNA, RNA, protein, metabolite), has exponentially increased the volume of scientific data available for this arduous task. Therefore, computational platforms identifying and ranking disease-relevant targets from existing biomedical data sources, including omics databases, are needed. To date, more than 30 drug target discovery (DTD) platforms exist. They provide information-rich databases and graphical user interfaces to help scientists identify putative targets and pre-evaluate their therapeutic efficacy and potential side effects. Here we survey and compare a set of popular DTD platforms that utilize multiple data sources and omics-driven knowledge bases (either directly or indirectly) for identifying drug targets. We also provide a description of omics technologies and related data repositories which are important for DTD tasks.

KRAS mutation and abnormal expression of Cripto-1 as two potential candidate biomarkers for detection of colorectal cancer development

Colorectal cancer (CRC), regardless of standard procedures of treatment and screening, is still considered one of the deadliest cancers in the Western world, and in economically developed Asian countries, especially Iran. The current study was undertaken to investigate whether changes in the level of Cripto-1 (CR-1) expression and KRAS mutations have a cumulative effect on the onset and progression of CRC. Fifty colorectal tissue samples, including 35 colorectal carcinomas with matching adjacent mucosa, and 15 colorectal adenomas, were chosen for analysis. Twenty-five CRC biopsies and 15 adenoma were analyzed for KRAS mutations by DNA sequencing (Sanger sequencing), and all 50 patients (35 CRCs and 15 adenomas) were evaluated by immunohistochemistry for the CR-1 protein expression. The inducible somatic KRAS mutation (G12D) was observed in nine (36%) of CRC patients, and in two (13.3%) of adenoma patients. The CR-1 expression level in both adenomas (P < .05) and carcinomas (P < .001), were significantly different, compared with the matching adjacent mucosa. The intensity of CR-1 staining in adenomas was less than the intensity of staining, detected in the CRCs (P < .001). The G12D KRAS mutation and CR-1 abnormalities are significantly associated as two signature biomarkers with potential clinical characteristics for the detection of CRC development.

In-Depth Characterization of Mass Spectrometry-Based Proteomic Profiles Revealed Novel Signature Proteins Associated with Liver Metastatic Colorectal Cancers

Liver metastasis is the most common form of metastatic colorectal cancers during the course of the disease. The global change in protein abundance in liver metastatic colorectal cancers and its role in metastasis establishment have not been comprehensively analyzed. In the present study, fresh-frozen tissue samples including normal colon/localized/liver metastatic CRCs from each recruited patient were analyzed by quantitative proteomics using a multiplexed TMT labeling strategy. Around 5000 protein groups were quantified from all samples. The proteomic profile of localized/metastatic CRCs varied greatly from that of normal colon tissues; differential proteins were mainly from extracellular regions and participate in immune activities, which is crucial for the chronic inflammation signaling pathways in the tumor microenvironment. Further statistical analysis revealed 47 proteins exhibiting statistical significance between localized and metastatic CRCs, of which FILI1P1 and PLG were identified for the first time in proteomic data, which were highly associated with liver metastasis in CRCs.

Plasma/serum proteomics: depletion strategies for reducing high-abundance proteins for biomarker discovery

Plasma and serum are widely used for proteomics-based biomarker discovery. However, analysis of these biofluids is highly challenging due to the complexity and wide dynamic range of their proteomes. Notably, highly abundant proteins tend to obscure the detection of potential biomarkers that are usually of lower concentrations. Among the strategies to resolve this problem are: depletion of high-abundance proteins, enrichment of low abundant proteins of interest and prefractionation. In this review, we focus on current and emerging depletion techniques used to enhance the detection and identification of the less abundant proteins in plasma and serum. We discuss the applications and contributions of these methods to proteomics analysis of plasma and serum alongside their limitations and future perspectives.

Protein Expression Profiling Identifies Key Proteins and Pathways Involved in Growth Inhibitory Effects Exerted by Guggulsterone in Human Colorectal Cancer Cells

Colorectal cancer (CRC) is a leading killer cancer worldwide and one of the most common malignancies with increasing incidences of mortality. Guggulsterone (GS) is a plant sterol used for treatment of various ailments such as obesity, hyperlipidemia, diabetes, and arthritis. In the current study, anti-cancer effects of GS in human colorectal cancer cell line HCT 116 was tested, potential targets identified using mass spectrometry-based label-free shotgun proteomics approach and key pathways validated by proteome profiler antibody arrays. Comprehensive proteomic profiling identified 14 proteins as significantly dysregulated. Proteins involved in cell proliferation/migration, tumorigenesis, cell growth, metabolism, and DNA replication were downregulated while the protein with functional role in exocytosis/tumor suppression was found to be upregulated. Our study evidenced that GS treatment altered expression of Bcl-2 mediated the mitochondrial release of cytochrome c which triggered the formation of apoptosome as well as activation of caspase-3/7 leading to death of HCT 116 cells via intrinsic apoptosis pathway. GS treatment also induced expression of p53 protein while p21 expression was unaltered with no cell cycle arrest. In addition, GS was found to inhibit NF-kB signaling in colon cancer cells by quelling the expression of its regulated gene products Bcl-2, cIAP-1, and survivin.

Sudden Cardiac Death (SCD) - risk stratification and prediction with molecular biomarkers

Sudden cardiac death (SCD) is a sudden, unexpected death that is caused by the loss of heart function. While SCD affects many patients suffering from coronary artery diseases (CAD) and heart failure (HF), a considerable number of SCD events occur in asymptomatic individuals. Certain risk factors for SCD have been identified and incorporated in different clinical scores, however, risk stratification using such algorithms is only useful for health management rather than for early detection and prediction of future SCD events in high-risk individuals. In this review, we discuss different molecular biomarkers that are used for early detection of SCD. This includes genetic biomarkers, where the majority of them are genomic variants for genes that encode for ion channels. Meanwhile, protein biomarkers often denote proteins that play roles in pathophysiological processes that lead to CAD and HF, notably (i) atherosclerosis that involves oxidative stress and inflammation, as well as (ii) cardiac tissue damage that involves neurohormonal and hemodynamic regulation and myocardial stress. Finally, we outline existing challenges and future directions including the use of OMICS strategy for biomarker discovery and the multimarker panels.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

Probing the endogenous peptidomes of cancer for biomarkers: A new endeavor

The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.