Serum proteomic profiling for the early diagnosis of colorectal cancer

Serum Splicing Factor Proline- and Glutamine-Rich Is a Diagnostic Marker for Non-Small-Cell Lung Cancer and Other Solid Cancers

Cancer markers are measurable molecules in blood or tissues that are produced by tumor cells or immune cells in response to cancer progression. They play an important role in clinical diagnosis, prognosis, and therapy monitoring. Splicing factor proline- and glutamine-rich (SFPQ) plays an important role in cancer growth and metastasis. SFPQ is not only more highly expressed in non-small-cell lung cancer (NSCLC) cells than it is in controls, but also highly expressed in cancer cells in patients with other solid cancers. Thus, a new enzyme-linked immunosorbent assay (ELISA) for detecting SFPQ was developed, in which the SFPQ protein is trapped by the first specific mAb coated on a microplate, and then recognized by a second specific mAb. This assay allows for the specific detection of SFPQ in the serum of patients with solid cancer. Regarding NSCLC, the serum SFPQ levels distinguished the non-cancer controls from the patients with NSCLC, with an area under the curve of 0.876, a sensitivity of 87%, and a specificity of 94%. The serum SFPQ levels were significantly elevated in the patients with NSCLC or other solid cancers. In conclusion, serum SFPQ could be a promising novel diagnostic biomarker for NSCLC and other malignancies.

MALDI-TOF MS: application in diagnosis, dereplication, biomolecule profiling and microbial ecology

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized scientific research over the past few decades and has provided a unique platform in ongoing technological developments. Undoubtedly, there has been a bloom chiefly in the field of biological sciences with this emerging technology, and has enabled researchers to generate critical data in the field of disease diagnoses, drug development, dereplication. It has received well acceptance in the field of microbial identification even at strain level, as well as diversified field like biomolecule profiling (proteomics and lipidomics) has evolved tremendously. Additionally, this approach has received a lot more attention over conventional technologies due to its high throughput, speed, and cost effectiveness. This review aims to provide a detailed insight regarding the application of MALDI-TOF MS in the context of medicine, biomolecule profiling, dereplication, and microbial ecology. In general, the expansion in the application of this technology and new advancements it has made in the field of science and technology has been highlighted.

Circulating proteins as predictive and prognostic biomarkers in breast cancer

Breast cancer (BC) is the most common cancer and among the leading causes of cancer death in women. It is a heterogeneous group of tumours with numerous morphological and molecular subtypes, making predictions of disease evolution and patient outcomes difficult. Therefore, biomarkers are needed to help clinicians choose the best treatment for each patient. For the last years, studies have increasingly focused on biomarkers obtainable by liquid biopsy. Circulating proteins (from serum or plasma) can be used for inexpensive and minimally invasive determination of disease risk, early diagnosis, treatment adjusting, prognostication and disease progression monitoring. We provide here a review of the main published studies on serum proteins in breast cancer and elaborate on the potential of circulating proteins to be predictive and/or prognostic biomarkers in breast cancer.

Identification of Circulating Biomarkers of COVID-19 Using MALDI-TOF Mass Spectrometry

Matrix-assisted laser desorption/ionization source coupled with time-of-flight mass analyzer mass spectrometry (MALDI-TOF MS) is being widely used to obtain proteomic profiles for clinical purposes, as a fast, low-cost, robust, and efficient technique. Here we describe a method for biofluid analysis using MALDI-TOF MS for rapid acquisition of proteomic signatures of COVID-19 infected patients. By using solid-phase extraction, the method allows the analysis of biofluids in less than 15 min.

Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Lower Gastrointestinal Cancers: A Systematic Review and Meta-Analysis

INTRODUCTION

Lower gastrointestinal (GI) cancers are a major cause of cancer deaths worldwide. Prognosis improves with earlier diagnosis, and non-invasive biomarkers have the potential to aid with early detection. Substantial investment has been made into the development of biomarkers; however, studies are often carried out in specialist settings and few have been evaluated for low-prevalence populations.

METHODS

We aimed to identify novel biomarkers for the detection of lower GI cancers that have the potential to be evaluated for use in primary care. MEDLINE, Embase, Emcare and Web of Science were systematically searched for studies published in English from January 2000 to October 2019. Reference lists of included studies were also assessed. Studies had to report on measures of diagnostic performance for biomarkers (single or in panels) used to detect colorectal or anal cancers. We included all designs and excluded studies with fewer than 50 cases/controls. Data were extracted from published studies on types of biomarkers, populations and outcomes. Narrative synthesis was used, and measures of specificity and sensitivity were meta-analysed where possible.

RESULTS

We identified 142 studies reporting on biomarkers for lower GI cancers, for 24,844 cases and 45,374 controls. A total of 378 unique biomarkers were identified. Heterogeneity of study design, population type and sample source precluded meta-analysis for all markers except methylated septin 9 (mSEPT9) and pyruvate kinase type tumour M2 (TuM2-PK). The estimated sensitivity and specificity of mSEPT9 was 80.6% (95% CI 76.6-84.0%) and 88.0% (95% CI 79.1-93.4%) respectively; TuM2-PK had an estimated sensitivity of 81.6% (95% CI 75.2-86.6%) and specificity of 80.1% (95% CI 76.7-83.0%).

CONCLUSION

Two novel biomarkers (mSEPT9 and TuM2-PK) were identified from the literature with potential for use in lower-prevalence populations. Further research is needed to validate these biomarkers in primary care for screening and assessment of symptomatic patients.

A Meta-Analysis of Proteomic Blood Markers of Colorectal Cancer

BACKGROUND

Early diagnosis will significantly improve the survival rate of colorectal cancer (CRC); however, the existing methods for CRC screening were either invasive or inefficient. There is an emergency need for novel markers in CRC's early diagnosis. Serum proteomics has gained great potential in discovering novel markers, providing markers that reflect the early stage of cancer and prognosis prediction of CRC. In this paper, the results of proteomics of CRC studies were summarized through a meta-analysis in order to obtain the diagnostic efficiency of novel markers.

METHODS

A systematic search on bibliographic databases was performed to collect the studies that explore blood-based markers for CRC applying proteomics. The detection and validation methods, as well as the specificity and sensitivity of the biomarkers in these studies, were evaluated. Newcastle- Ottawa Scale (NOS) case-control studies version was used for quality assessment of included studies.

RESULTS

Thirty-four studies were selected from 751 studies, in which markers detected by proteomics were summarized. In total, fifty-nine proteins were classified according to their biological function. The sensitivity, specificity, or AUC varied among these markers. Among them, Mammalian STE20-like protein kinase 1/ Serine threonine kinase 4 (MST1/STK4), S100 calcium-binding protein A9 (S100A9), and Tissue inhibitor of metalloproteinases 1 (TIMP1) were suitable for effect sizes merging, and their diagnostic efficiencies were recalculated after merging. MST1/STK4 obtained a sensitivity of 68% and a specificity of 78%. S100A9 achieved a sensitivity of 72%, a specificity of 83%, and an AUC of 0.88. TIMP1 obtained a sensitivity of 42%, a specificity of 88%, and an AUC of 0.71.

CONCLUSION

MST1/STK4, S100A9, and TIMP1 showed excellent performance for CRC detection. Several other markers also presented optimized diagnostic efficacy for CRC early detection, but further verification is still needed before they are suitable for clinical use. The discovering of more efficient markers will benefit CRC treatment.

Omics technologies for improved diagnosis and treatment of colorectal cancer: Technical advancement and major perspectives

Colorectal cancer (CRC) ranks third among the most commonly occurring cancers worldwide, and it causes half a million deaths annually. Alongside mechanistic study for CRC detection and treatment by conventional techniques, new technologies have been developed to study CRC. These technologies include genomics, transcriptomics, proteomics, and metabolomics which elucidate DNA markers, RNA transcripts, protein and, metabolites produced inside the colon and rectum part of the gut. All these approaches form the omics arena, which presents a remarkable opportunity for the discovery of novel prognostic, diagnostic and therapeutic biomarkers and also delineate the underlying mechanism of CRC causation, which may further help in devising treatment strategies. This review also mentions the latest developments in metagenomics and culturomics as emerging evidence suggests that metagenomics of gut microbiota has profound implications in the causation, prognosis, and treatment of CRC. A majority of bacteria cannot be studied as they remain unculturable, so culturomics has also been strengthened to develop culture conditions suitable for the growth of unculturable bacteria and identify unknown bacteria. The overall purpose of this review is to succinctly evaluate the application of omics technologies in colorectal cancer research for improving the diagnosis and treatment strategies.

Profiling of polar urine metabolite extracts from Chinese colorectal cancer patients to screen for potential diagnostic and adverse-effect biomarkers

Background: Metabolomics has demonstrated its potential in the early diagnosis, drug safety evaluation and personalized toxicology research of various cancers. Objectives: We aim to screen for potential diagnostic and capecitabine-related adverse effect (CRAE) biomarkers from urinary endogenous metabolites in Chinese colorectal cancer (CRC) patients. Methods: The metabolic profiles of 139 CRC patients and 50 non-neoplastic controls were analyzed using ultra-high-performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry. Results: There were 41 metabolites identified between the CRC patients and the non-neoplastic controls, and 19 metabolites were identified between CRC patients with and without CRAE. Based on these identified metabolites, bioinformatic analysis and prediction model construction were completed. Most of these differential metabolites have important roles in cell proliferation and differentiation and the immune system. Based on binary logistic regression, a CRC prediction model, composed of 3-methylhistidine, N-heptanoylglycine, N1,N12-diacetylspermine and hippurate, was established, with an area under curve (AUC) of 0.980 (95% CI: 0.953-1.000; sensitivity: 94.3%; specificity: 92.0%) in the training set, and an AUC of 0.968 (95% CI: 0.933-1.000; sensitivity: 89.9%; specificity: 92.0%) in the testing set. In addition, methionine and 4-pyridoxic acid can be combined to predict hand foot syndrome, with an AUC of 0.884; ubiquinone-1 and 4-pyridoxic acid can be combined to predict anemia, with an AUC of 0.889; and 5-acetamidovalerate and 3,4-methylenesebacic acid can be combined to predict neutropenia, with an AUC of 0.882. Conclusion: The profiling of urine polar metabolites has great potential in the early detection of CRC and the prediction of CRAE.

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.

Evaluation of potential circulating biomarkers for prediction of response to chemoradiation in patients with glioblastoma

Surgery followed by chemoradiation and adjuvant chemotherapy is standard of care for patients with a glioblastoma (GBM). Due to its limited benefit, an upfront method to predict dismal outcome would prevent unnecessary toxic treatment. We searched for a predictive blood derived biomarker in a cohort of 55 patients with GBM. Increasing age (HR 1.03, 95 % CI 1.01–1.06), and postoperative tumor residue (HR 1.07, 95 % CI 1.02–1.15) were independently associated with unfavourable progression free survival (PFS) in these patients. Corticosteroid use before start of chemoradiaton was strongly predictive for outcome (HR 3.26, 95 % CI 1.67–6.39) with a mean PFS and OS in patients using corticosteroids of 7.3 and 14.6 months, versus 16.1 and 21.6 months in patients not using corticosteroids (p = 0.0005, p < 0.0067 respectively). Despite earlier reports, blood concentrations of YKL-40, Fetuin-a and haptoglobin were not predictive for response. In addition, serum peptide profiles, determined by MALDI-TOF mass spectroscopy, were not predictive as well. In conclusion, further biomarker discovery studies are needed to predict treatment outcome for patients with GBM in the near future.

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC.

Alterations of the Plasma Peptidome Profiling in Colorectal Cancer Progression

Early detection of colorectal cancer (CRC) remains a challenge. It has been highlighted that the pathological alterations within an organ and tissues might be reflected in serum or plasma proteomic/peptidic patterns. The aim of the study was to follow the changes in the plasma peptides associated to colorectal cancer progression by mass spectrometry. This study included 27 adenoma, 67 CRC (n = 33 I-II stage and n = 34 III-IV stage), 23 liver metastasis from CRC patients and 34 subjects disease-free as controls. For plasma peptides analysis, samples purification was performed on the Nanoporous Silica Chips technology followed by matrix-assisted laser desorption/ionisation-time of flight analysis. Since the high complexity of the obtained dataset, multivariate statistical analysis, and discriminant pattern recognition were performed for study groups classification. Forty-four of 88 ionic species were successfully identified as fragments of peptides and proteins physiologically circulating in the blood and belonging to immune and coagulation systems and inflammatory mediators. Many peptides clustered into sets of overlapping sequences with ladder-like truncation clearly associated to proteolytic processes of both endo- and exoproteases activity. Comparing to controls, a different median ion intensity of the group-type fragments distribution was observed. Moreover, the degradation pattern obtained by proteolytic cleavage was different into study groups. This pattern was specific and characteristic of each group: controls, colon tumour disease (including adenoma and CRC), and liver metastasis, revealing a role as biomarker in early diagnosis and prognosis. Our findings highlighted peculiar changes in protease activity characteristic of CRC progression from pre-cancer lesion to metastatic disease. J. Cell. Physiol. 231: 915-925, 2016. © 2015 Wiley Periodicals, Inc.

Biomarker Characterization by MALDI-TOF/MS

Mass spectrometric techniques frequently used in clinical diagnosis, such as gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, ambient ionization mass spectrometry, and matrix-assisted laser desorption ionization/time-of-flight mass spectrometry (MALDI-TOF/MS), are discussed. Due to its ability to rapidly detect large biomolecules in trace amounts, MALDI-TOF/MS is an ideal tool for characterizing disease biomarkers in biologic samples. Clinical applications of MS for the identification and characterization of microorganisms, DNA fragments, tissues, and biofluids are introduced. Approaches for using MALDI-TOF/MS to detect various disease biomarkers including peptides, proteins, and lipids in biological fluids are further discussed. Finally, various sample pretreatment methods which improve the detection efficiency of disease biomarkers are introduced.

Proteomic study of pilocytic astrocytoma pediatric brain tumor intracystic fluid

Liquid chromatography in coupling with high-resolution ESI-LTQ-Orbitrap mass spectrometry was applied for a proteomic study of pediatric pilocytic astrocytoma brain tumor intracystic fluid by an integrated top-down/bottom-up platform. Both of the proteomic strategies resulted complementary and support each other in contributing to a wide characterization of the protein and peptide content of the tumor fluid. Top-down approach allowed to identify several proteins and peptides involved in different biological activities together with the characterization of interesting proteoforms such as fibrinopeptide A and its truncated form, fibrinopeptide B, complement C3f fragments, β-thymosin peptides, ubiquitin, several apolipoproteins belonging to A and C families, apolipoprotein J and D, and cystatin C. Of particular interest resulted the identification of a N-terminal truncated cystatin C proteoform, likely involved in immune response mechanism modulations and the identification of oxidized and glycosylated apolipoproteins including disulfide bridge dimeric forms. The bottom-up approach confirmed some of the experimental data findings together with adding the characterization of high-molecular-mass proteins in the samples. These data could contribute to elucidate the molecular mechanisms involved in onset and progression of the disease and cyst development.

Comparative evaluation of 5-15-kDa salivary proteins from patients with different oral diseases by MALDI-TOF/TOF mass spectrometry

OBJECTIVES

The present study aimed to determine the potential use of matrix-assisted laser desorption/ionization with time-of-flight/time-of-flight mass spectrometry (MALDI-TOF/TOF MS) for analyzing specific patterns of mass signals of low-molecular-weight proteins in saliva from patients with different oral diseases.

MATERIALS AND METHODS

Unstimulated whole saliva samples were collected from healthy subjects (n = 30) and patients with oral diseases including oral cancer (n = 30), oral lichen planus (n = 30), and chronic periodontitis (n = 30). Proteomic profiles of 5,000-15,000-Da salivary proteins were evaluated by MALDI-TOF/TOF MS. Quantification of mass signals was performed by FlexAnalysis and ClinProTool software.

RESULTS

In oral cancer, the percentages of mass signals at 5,592.26 and 8,301.46 Da were significantly increased as compared with other groups (p = 0.002 and p = 0.030, respectively). In oral lichen planus, the percentages of mass signals at 12,964.55 and 13,279.08 Da were significantly increased as compared with other groups (p < 0.001, and p < 0.001, respectively). In chronic periodontitis, the percentages of mass signals at 5,835.73 and 9,801.83 Da were significantly decreased as compared with other groups (p = 0.003 and p = 0.005, respectively).

CONCLUSIONS

The present study demonstrated a potential use of MALDI-TOF/TOF as a rapid screening method to differentiate one oral disease from others by identifying specific patterns of mass signals in saliva from patients. However, MALDI-TOF/TOF has several limitations regarding the identification of the candidate mass signals.

CLINICAL RELEVANCE

MALDI-TOF/TOF MS can be used as a rapid screening method to differentiate one oral disease from others with a caution concerning peptide identity.

Overexpression of nuclear apoptosis-inducing factor 1 altered the proteomic profile of human gastric cancer cell MKN45 and induced cell cycle arrest at G1/S phase

Nuclear apoptosis-inducing factor 1 (NAIF1) was previously reported to induce apoptosis. Moreover, the expression of NAIF1 was significantly down-regulated in human gastric cancer tissues compared to adjacent normal tissues. However, the mechanism by which the NAIF1 gene induces apoptosis is not fully understood. Our results show that NAIF1 was minimally expressed in all the tested gastric cancer cell lines. Our data also demonstrates that NAIF1 is localized in the nuclei of cells as detected by monitoring the green fluorescence of NAIF1-GFP fusion protein using fluorescent confocal microscopy. Next, a comparative proteomic approach was used to identify the differential expression of proteins between gastric cancer cell lines MKN45/NAIF1 (−) and MKN45/NAIF1 (+). We found five proteins (proteasome 26S subunit 2, proteasome 26S subunit 13, NADH dehydrogenase Fe-S protein 1, chaperonin containing TCP1 subunit 3 and thioredoxin reductase 1) that were up-regulated and three proteins (ribonuclease inhibitor 1, 14-3-3 protein epsilon isoform and apolipoprotein A-I binding protein) that were down-regulated in the MKN45 cells overexpressing NAIF1. We also discovered that NAIF1 could induce cell cycle arrest at G1/S phase by altering the expression of cell cycle proteins cyclinD1, cdc2 and p21. The differentially expressed proteins identified here are related to various cellular programs involving cell cycle, apoptosis, and signal transduction regulation and suggest that NAIF1 may be a tumor suppressor in gastric cancer. Our research provides evidence that elucidates the role of how NAIF1 functions in gastric cancer.

Proteomics for discovery of candidate colorectal cancer biomarkers

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

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.