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

2021 ◽  
Vol 22 (3) ◽  
pp. 1189
Author(s):  
Megha Bhardwaj ◽  
Tobias Terzer ◽  
Petra Schrotz-King ◽  
Hermann Brenner
Keyword(s):  
Colorectal Cancer ◽  
Multiple Reaction Monitoring ◽  
Area Under The Curve ◽  
Superior Performance ◽  
Blood Protein ◽  
Protein Biomarkers ◽  
Serum Samples ◽  
Functional Protein ◽  
Novel Technologies ◽  
Diagnostic Potential

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.

Multi-omics analysis to reveal the role of gut microbiome–associated serum metabolites in the detection of colorectal cancer and adenoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 3539-3539
Author(s):  
Feng Chen ◽  
Xudong Dai ◽  
Wei Cui
Keyword(s):  
Colorectal Cancer ◽  
Gut Microbiome ◽  
Early Stage ◽  
Normal Population ◽  
Area Under The Curve ◽  
Superior Performance ◽  
Integrated Analysis ◽  
Circulation System ◽  
Serum Metabolites ◽  
Diagnostic Potential

3539 Background: Gut microbiome and their metabolites have been revealed to be associated with the initiation and progression of colorectal cancer (CRC), and gut microbiome produced or associated metabolites could enter the circulation system. Methods: Integrated analysis of untargeted serum metabolomics by liquid chromatography–mass spectrometry (LS-MS) and metagenome sequencing of fecal samples derived from matched individuals were used to profile serum metabolites that are both significantly affected by CRC and co-related with the gut microbiome. Targeted LC-MS was further used to test the ability of these metabolites for discriminating CRC and adenoma from healthy individuals. Results: More than 300 gut microbiome–associated serum metabolites with significantly altered abundance in both colorectal carcinoma (CRC) and adenoma patients have been identified. A panel of eight gut microbiome–associated serum metabolites (GMSM panel) was established and accurately discriminated CRC and adenoma from normal population. The GMSM panel–based CRC and colorectal adenoma prediction model yielded an area under the curve (AUC) of 0.94 (95% confidence interval: 0.90–0.99) and AUC of 0.91 (sensitivity 82%, specificity 91%) in the training and validation set respectively. This GMSM model shows significantly superior performance to the clinical marker carcinoembryonic antigen (CEA) (AUC 0.72), and more importantly, it suggests promising diagnostic potential in detecting adenoma (AUC = 0.81) and early-stage CRC (AUC = 0.91). Conclusions: Our results indicate that gut microbiome reprogramming in CRC patients is associated with the alterations of the serum metabolome, and these gut microbiome–associated serum metabolites has potential application for the detection of earlier CRC and adenoma.

scholarly journals Identification and Evaluation of Serum Protein Biomarkers Which Differentiate Psoriatic from Rheumatoid Arthritis

2020 ◽  
Author(s):  
Angela Mc Ardle ◽  
Anna Kwasnik ◽  
Agnes Szenpetery ◽  
Melissa Jones ◽  
Belinda Hernandez ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Serum Protein ◽  
Clinical Decision Making ◽  
Multiple Reaction Monitoring ◽  
Area Under The Curve ◽  
Clinical Decision ◽  
Additional Patient ◽  
Second Phase ◽  
Protein Biomarkers ◽  
Protein Discovery

AbstractObjectivesTo identify serum protein biomarkers which might separate early inflammatory arthritis (EIA) patients with psoriatic arthritis (PsA) from those with rheumatoid arthritis (RA) to provide an accurate diagnosis and support appropriate early intervention.MethodsIn an initial protein discovery phase, the serum proteome of a cohort of patients with PsA and RA was interrogated using unbiased liquid chromatography mass spectrometry (LC-MS/MS) (n=64 patients), a multiplexed antibody assay (Luminex) for 48 proteins (n=64 patients) and an aptamer-based assay (SOMAscan) targeting 1,129 proteins (n=36 patients). Subsequently, analytically validated targeted multiple reaction monitoring (MRM) assays were developed to further evaluate those proteins identified as discriminatory during the discovery. During an initial verification phase, MRM assays were developed to a panel of 150 proteins (by measuring a total of 233 peptides) and used to re-evaluate the discovery cohort (n=60). During a second verification phase, the panel of proteins was expanded to include an additional 23 proteins identified in other proteomic discovery analyses of arthritis patients. The expanded panel was evaluated using a second, independent cohort of PsA and RA patients (n=167).ResultsMultivariate analysis of the protein discovery data revealed that it was possible to discriminate PsA from RA patients with an area under the curve (AUC) of 0.94 for nLC-MS/MS, 0.69 for Luminex based measurements; 0.73 for SOMAscan analysis. During the initial verification phase, random forest models confirmed that proteins measured by MRM could differentiate PsA and RA patients with an AUC of 0.79 and during the second phase of verification the expanded panel could segregate the two disease groups with an AUC of 0.85.ConclusionWe report a serum protein biomarker panel which can separate EIA patients with PsA from those with RA. We suggest that the routine use of such a panel in EIA patients will improve clinical decision making and with continued evaluation and refinement using additional patient cohorts will support the development of a diagnostic test for patients with PsA.

scholarly journals Novel circulating protein biomarkers for thyroid cancer determined through data-independent acquisition mass spectrometry

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9507
Author(s):  
Dandan Li ◽  
Jie Wu ◽  
Zhongjuan Liu ◽  
Ling Qiu ◽  
Yimin Zhang
Keyword(s):  
Mass Spectrometry ◽  
Area Under The Curve ◽  
High Sensitivity ◽  
Factor H ◽  
Complement Factor ◽  
Protein Biomarkers ◽  
Serum Samples ◽  
Data Independent Acquisition ◽  
Median Serum ◽  
And Control

Background Distinguishing between different types of thyroid cancers (TC) remains challenging in clinical laboratories. As different tumor types require different clinical interventions, it is necessary to establish new methods for accurate diagnosis of TC. Methods Proteomic analysis of the human serum was performed through data-independent acquisition mass spectrometry for 29 patients with TC (stages I–IV): 13 cases of papillary TC (PTC), 10 cases of medullary TC (MTC), and six cases follicular TC (FTC). In addition, 15 patients with benign thyroid nodules (TNs) and 10 healthy controls (HCs) were included in this study. Subsequently, 17 differentially expressed proteins were identified in 291 patients with TC, including 247 with PTC, 38 with MTC, and six with FTC, and 69 patients with benign TNs and 176 with HC, using enzyme-linked immunosorbent assays. Results In total, 517 proteins were detected in the serum samples using an Orbitrap Q-Exactive-plus mass spectrometer. The amyloid beta A4 protein, apolipoprotein A-IV, gelsolin, contactin-1, gamma-glutamyl hydrolase, and complement factor H-related protein 1 (CFHR1) were selected for further analysis. The median serum CFHR1 levels were significantly higher in the MTC and FTC groups than in the PTC and control groups (P < 0.001). CFHR1 exhibited higher diagnostic performance in distinguishing patients with MTC from those with PTC (P < 0.001), with a sensitivity of 100.0%, specificity of 85.08%, area under the curve of 0.93, and detection cut-off of 0.92 ng/mL. Conclusion CFHR1 may serve as a novel biomarker to distinguish PTC from MTC with high sensitivity and specificity.

scholarly journals CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice

2021 ◽  
Vol 17 (8) ◽  
pp. e1009773
Author(s):  
Deniz Koyuncu ◽  
Muhammad Khalid Khan Niazi ◽  
Thomas Tavolara ◽  
Claudia Abeijon ◽  
Melanie L. Ginese ◽  
...  
Keyword(s):  
Serum Protein ◽  
Limit Of Detection ◽  
Area Under The Curve ◽  
World Health ◽  
Protein Biomarkers ◽  
Serum Samples ◽  
Protein Biomarker ◽  
Mouse Population ◽  
Diagnostic Quality ◽  
Diversity Outbred

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, serum protein biomarkers to help diagnose TB, which afflicts millions of people in high-burden countries. However, the protein biomarker pipeline is small. Here, we used the Diversity Outbred (DO) mouse population to address this gap, identifying five protein biomarker candidates. One protein biomarker, serum CXCL1, met the World Health Organization’s Targeted Product Profile for a triage test to diagnose active TB from latent M.tb infection (LTBI), non-TB lung disease, and normal sera in HIV-negative, adults from South Africa and Vietnam. To find the biomarker candidates, we quantified seven immune cytokines and four inflammatory proteins corresponding to highly expressed genes unique to progressor DO mice. Next, we applied statistical and machine learning methods to the data, i.e., 11 proteins in lungs from 453 infected and 29 non-infected mice. After searching all combinations of five algorithms and 239 protein subsets, validating, and testing the findings on independent data, two combinations accurately diagnosed progressor DO mice: Logistic Regression using MMP8; and Gradient Tree Boosting using a panel of 4: CXCL1, CXCL2, TNF, IL-10. Of those five protein biomarker candidates, two (MMP8 and CXCL1) were crucial for classifying DO mice; were above the limit of detection in most human serum samples; and had not been widely assessed for diagnostic performance in humans before. In patient sera, CXCL1 exceeded the triage diagnostic test criteria (>90% sensitivity; >70% specificity), while MMP8 did not. Using Area Under the Curve analyses, CXCL1 averaged 94.5% sensitivity and 88.8% specificity for active pulmonary TB (ATB) vs LTBI; 90.9% sensitivity and 71.4% specificity for ATB vs non-TB; and 100.0% sensitivity and 98.4% specificity for ATB vs normal sera. Our findings overall show that the DO mouse population can discover diagnostic-quality, serum protein biomarkers of human TB.

scholarly journals piRNA-823 Is a Unique Potential Diagnostic Non-Invasive Biomarker in Colorectal Cancer Patients

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 598
Author(s):  
Norhan A. Sabbah ◽  
Wael M. Abdalla ◽  
Walid A. Mawla ◽  
Nagla AbdAlMonem ◽  
Amal F. Gharib ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Patients ◽  
Characteristic Curve ◽  
Area Under The Curve ◽  
Serum Levels ◽  
P Element ◽  
Serum Samples ◽  
Expression Levels ◽  
Non Invasive ◽  
Colorectal Cancer Patients

Early detection of colorectal cancer (CRC) is the most important factor in deciding its prognosis, so the need to develop an accurate screening test is a must. P-element induced wimpy testis (PIWI) RNA-823 (piR-823) is one of the first piRNAs recognized to be linked to malignancy. We aimed to investigate the expression levels of piR-823 in both serum and tissues of colorectal cancer patients and the ability to use its serum level as a non-invasive diagnostic biomarker to detect colorectal cancer. We determined piR-823 expression levels in 84 serum samples of CRC patients, 75 serum samples of healthy controls, and biological specimens obtained from the 84 patients with colorectal cancer from both the tumor tissues and the normal neighboring tissues using quantitative real-time reverse transcriptase-PCR. We showed that piR-823 had significantly higher serum and tissue expression levels in CRC patients compared to the controls. We observed a significant positive correlation between piR-823 serum levels and the staging of CRC, with significantly higher levels exhibiting advanced stages of CRC (III and IV). This translates into poorer differentiation and lymph node metastasis. The receiver operating characteristic curve (ROC curve) test showed 83.3% sensitivity and 89.3% specificity at a cut-off value of >5.98-fold change, with an area under the curve of 0.933 (p < 0.0001) concerning the ability of piR-823 in diagnosing patients with colorectal carcinoma. piR-823 expression is upregulated in colorectal cancer patients’ serum and tissues, and it can be used as a diagnostic noninvasive biomarker for CRC.

The Promising Signatures of Circulating microRNA-145 in Epithelial Ovarian Cancer Patients

MicroRNA ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Mariyam Zuberi ◽  
Rashid Mir ◽  
Imran Khan ◽  
Jamsheed Javid ◽  
Sameer Ahmad Guru ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Roc Curve ◽  
Histological Grade ◽  
Area Under The Curve ◽  
Lymph Node Status ◽  
P Value ◽  
Circulating Microrna ◽  
Serum Samples ◽  
Diagnostic Potential

Background:Epithelial ovarian cancer continues to be a deleterious threat to women as it is asymptomatic and is typically detected in advanced stages. Cogent non-invasive biomarkers are therefore needed which are effective in apprehending the disease in early stages. Recently, miRNA deregulation has shown a promising magnitude in ovarian cancer tumorigenesis. miRNA-145(miR- 145) is beginning to be understood for its possible role in cancer development and progression. In this study, we identified the clinicopathological hallmarks altered owing to the downexpression of serum miR-145 in EOC.Methods:70 serum samples from histopathologically confirmed EOC patients and 70 controls were collected. Total RNA from serum was isolated by Trizol method, polyadenylated and reverse transcribed into cDNA. Expression level of miR-145 was detected by miRNA qRT-PCR using RNU6B snRNA as reference.Results:The alliance of miR-145 profiling amongst patients and controls established itself to be conspicuous with a significant p-value (p<0.0001). A positive conglomeration (p=0.04) of miR-145 profiling was manifested with histopathological grade. Receiver Operating Characteristic (ROC) curve highlights the diagnostic potential and makes it imminent with a robust Area Under the curve (AUC). A positive correlation with the ROC curve was also noted for histological grade, FIGO stage, distant metastasis, lymph node status and survival.Conclusion:Our results propose that miR-145 down-regulation might be a possible touchstone for disease progression and be identified as a diagnostic marker and predict disease outcome in EOC patients.

Evaluation of a 92 multiplex protein panel in detection of colorectal cancer and high-risk adenoma in 784 symptomatic individuals

2021 ◽  
pp. 1-12
Author(s):  
Louise Rasmussen ◽  
Hans Jørgen Nielsen ◽  
Ib Jarle Christensen
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Colorectal Adenoma ◽  
Precancerous Lesions ◽  
Protein Profiling ◽  
Superior Performance ◽  
Full Potential ◽  
Protein Biomarkers ◽  
Proximity Extension Assay ◽  
Control Study

BACKGROUND: Blood-based protein biomarkers for detection of colorectal cancer (CRC) have been submitted to intense research to improve the full potential in screening for CRC. OBJECTIVE: The aim was to explore the diagnostic performance of 92 proteins related to inflammation and carcinogenesis in detection of CRC or precancerous lesions. METHODS: Blood-samples were collected from 4,698 individuals undergoing colonoscopy. An explorative unmatched case-control study was designed with 294 cases (individuals with CRC or high-risk colorectal adenoma) and 490 controls (individuals with low-risk colorectal adenoma, non-malignant findings or clean colorectum at colonoscopy). Protein profiling was performed by multiplex proximity extension assay. Statistical analyses were performed as univariate and multivariate logistic regression analyses. RESULTS: Univariably, CSF-1, MMP12 and IL8 demonstrated superior performance in discrimination of individuals with CRC. Recurrently, IL8 was included as contributor in majority of multivariate models discriminating individuals with CRC. The multivariate evaluation in discrimination of individuals with CRC demonstrated AUC=ROC 0.82, sensitivity = 0.39 at specificity = 0.80. Discrimination of individuals with late stage CRC from individuals with clean colorectum demonstrated AUC=ROC 0.90, sensitivity = 0.58 at specificity = 0.80. CONCLUSIONS: A subset of biomarker candidates, specifically IL8, investigated in the present study suggest a potential as blood-based biomarkers in screening of CRC.

scholarly journals Proteomic Characterization of Colorectal Cancer Tissue from Patients Identifies Novel Putative Protein Biomarkers

2021 ◽  
Vol 43 (2) ◽  
pp. 1043-1056
Author(s):  
Maja Ludvigsen ◽  
Louise Thorlacius-Ussing ◽  
Henrik Vorum ◽  
Mogens Tornby Stender ◽  
Ole Thorlacius-Ussing ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Expression Patterns ◽  
Cancer Tissue ◽  
Protein Biomarkers ◽  
Differential Protein Expression ◽  
Two Dimensional Gel Electrophoresis ◽  
One Dimensional ◽  
Diagnostic Potential ◽  
Liquid Chromatography Tandem Mass

Colorectal cancer (CRC) is one of the leading causes of cancer-related death over the world. There is a great need for biomarkers capable of early detection and as targets for treatment. Differential protein expression was investigated with two-dimensional gel electrophoresis (2D-PAGE) followed by identification with liquid chromatography–tandem mass spectrometry (LC-MS/MS) in CRC patient tissue from (i) the peripheral part of the tumor, (ii) the central part of the tumor as well as from (iii) a non-involved part of the colorectal tissue. The expression patterns of six identified proteins were further evaluated by one-dimensional Western blot (1D-WB) analysis of the CRC tissue. Proteins that were perturbed in expression level in the peripheral or in the central part of the tumor as compared with the non-involved part included S100A11, HNRNPF, HNRNPH1 or HNRNPH2, GSTP1, PKM and FABP1. These identified markers may have future diagnostic potential or may be novel treatment targets after further evaluation in larger patient cohorts.

scholarly journals Sphingolipid Analysis Indicate Lactosylceramide as a Potential Biomarker of Inflammatory Bowel Disease in Children

Biomolecules ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 1083
Author(s):  
Aleksandra Filimoniuk ◽  
Agnieszka Blachnio-Zabielska ◽  
Monika Imierska ◽  
Dariusz Marek Lebensztejn ◽  
Urszula Daniluk
Keyword(s):  
Inflammatory Bowel Disease ◽  
Bowel Disease ◽  
High Performance ◽  
Area Under The Curve ◽  
Study Groups ◽  
Diagnostic Value ◽  
Serum Samples ◽  
Specificity And Sensitivity ◽  
Potential Biomarker ◽  
Inflammatory Bowel

An altered ceramide composition in patients with inflammatory bowel disease (IBD) has been reported recently. The aim of this study was to evaluate the concentrations of sphingolipids in the serum of treatment-naive children with newly diagnosed IBD and to determine the diagnostic value of the tested lipids in pediatric IBD. The concentrations of sphingolipids in serum samples were evaluated using a quantitative method, an ultra-high-performance liquid chromatography-tandem mass spectrometry in children with Crohn’s disease (CD) (n=34), ulcerative colitis (UC) (n = 39), and controls (Ctr) (n = 24). Among the study groups, the most significant differences in concentrations were noted for C16:0-LacCer, especially in children with CD compared to Ctr or even to UC. Additionally, the relevant increase in C20:0-Cer and C18:1-Cer concentrations were detected in both IBD groups compared to Ctr. The enhanced C24:0-Cer level was observed only in UC, while C18:0-Cer only in the CD group. The highest area under the curve (AUC), specificity, and sensitivity were determined for C16:0-LacCer in CD diagnosis. Our results suggest that the serum LacC16-Cer may be a potential biomarker that distinguishes children with IBD from healthy controls and differentiates IBD subtypes. In addition, C20:0-Cer and C18:0-Cer levels also seem to be closely connected with IBD.

scholarly journals Retinal Vessel Segmentation by Deep Residual Learning with Wide Activation

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yuliang Ma ◽  
Xue Li ◽  
Xiaopeng Duan ◽  
Yun Peng ◽  
Yingchun Zhang
Keyword(s):  
Blood Vessel ◽  
Blood Vessels ◽  
Area Under The Curve ◽  
Retinal Vessel ◽  
Vessel Segmentation ◽  
Superior Performance ◽  
Retinal Blood Vessel ◽  
Low Contrast ◽  
Blood Vessel Segmentation ◽  
Small Vessels

Purpose. Retinal blood vessel image segmentation is an important step in ophthalmological analysis. However, it is difficult to segment small vessels accurately because of low contrast and complex feature information of blood vessels. The objective of this study is to develop an improved retinal blood vessel segmentation structure (WA-Net) to overcome these challenges. Methods. This paper mainly focuses on the width of deep learning. The channels of the ResNet block were broadened to propagate more low-level features, and the identity mapping pathway was slimmed to maintain parameter complexity. A residual atrous spatial pyramid module was used to capture the retinal vessels at various scales. We applied weight normalization to eliminate the impacts of the mini-batch and improve segmentation accuracy. The experiments were performed on the DRIVE and STARE datasets. To show the generalizability of WA-Net, we performed cross-training between datasets. Results. The global accuracy and specificity within datasets were 95.66% and 96.45% and 98.13% and 98.71%, respectively. The accuracy and area under the curve of the interdataset diverged only by 1%∼2% compared with the performance of the corresponding intradataset. Conclusion. All the results show that WA-Net extracts more detailed blood vessels and shows superior performance on retinal blood vessel segmentation tasks.

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