scholarly journals Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Yingrong Chen ◽  
Zhihong Ma ◽  
Lishan Min ◽  
Hongwei Li ◽  
Bin Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Pathway Analysis ◽  
Area Under The Curve ◽  
Sphingolipid Metabolism ◽  
Cytokeratin 19 ◽  
Tumor Biomarker ◽  
Diagnostic Model ◽  
Roc Curve Analysis ◽  
Metabolic Alterations ◽  
Specificity And Sensitivity

Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top altered pathways for analysis and visualization. We constructed a diagnostic model using potential serum biomarkers from patients with lung cancer. We assessed their specificity and sensitivity according to the area under the curve of the receiver operator characteristic (ROC) curves, which could be used to distinguish patients with lung cancer from normal subjects. The pathway analysis indicated that sphingolipid metabolism was the top altered pathway in lung cancer. ROC curve analysis indicated that glycerophospho-N-arachidonoyl ethanolamine (GpAEA) and sphingosine were potential sensitive and specific biomarkers for lung cancer diagnosis and prognosis. Compared with the traditional lung cancer diagnostic biomarkers carcinoembryonic antigen and cytokeratin 19 fragment, GpAEA and sphingosine were as good or more appropriate for detecting lung cancer. We report our identification of potential metabolic diagnostic and prognostic biomarkers of lung cancer and clarify the metabolic alterations in lung cancer.

scholarly journals Circulating miRNAs as a Predictive Biomarker of the Progression from Prediabetes to Diabetes: Outcomes of a 5-Year Prospective Observational Study

2020 ◽  
Vol 9 (7) ◽  
pp. 2184 ◽  
Author(s):  
Iwona Sidorkiewicz ◽  
Magdalena Niemira ◽  
Katarzyna Maliszewska ◽  
Anna Erol ◽  
Agnieszka Bielska ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Mirna Target ◽  
Target Genes ◽  
Quantitative Polymerase Chain Reaction ◽  
Area Under The Curve ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Circulating Mirnas ◽  
Serum Samples ◽  
Roc Curve Analysis

Due to a global increase in the prevalence of type 2 diabetes mellitus (T2DM), there is an urgent need for early identification of prediabetes, as these people have the highest risk of developing diabetes. Circulating miRNAs have shown potential as progression biomarkers in other diseases. This study aimed to conduct a baseline comparison of serum-circulating miRNAs in prediabetic individuals, with the distinction between those who later progressed to T2DM and those who did not. The expression levels of 798 miRNAs using NanoString technology were examined. Spearman correlation, receiver operating characteristic (ROC) curve analysis, and logistic regression modeling were performed. Gene ontology (GO) and canonical pathway analysis were used to explore the biological functions of the miRNA target genes. The study revealed that three miRNAs were upregulated in the serum samples of patients who later progressed to T2DM. Pathway analysis showed that the miRNA target genes were mainly significantly enriched in neuronal NO synthase (nNOS) signaling in neurons, amyloid processing, and hepatic cholestasis. ROC analysis demonstrated that miR-491-5p, miR-1307-3p, and miR-298 can be introduced as a diagnostic tool for the prediction of T2DM (area under the curve (AUC) = 94.0%, 88.0%, and 84.0%, respectively). Validation by real-time quantitative polymerase chain reaction (qRT-PCR) confirmed our findings. The results suggest that circulating miRNAs can potentially be used as predictive biomarkers of T2DM in prediabetic patients.

scholarly journals SAA4 is a Diagnostic Marker to Enhance Detection Forrheumatoid Arthritis Combined with Anti-CCP

2022 ◽  
Author(s):  
Jiahui Li ◽  
Haina Liu ◽  
Bingbing Dai ◽  
Zhijun Fan ◽  
Qiao Wang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Area Under The Curve ◽  
Density Lipoprotein ◽  
Serum Levels ◽  
Diagnostic Model ◽  
Diagnostic Efficiency ◽  
Combined Model ◽  
Specificity And Sensitivity ◽  
Diagnostic Models ◽  
In Series

Abstract Objective Serum amyloid A4 (SAA4) is an apolipoprotein that is associated with high-density lipoprotein (HDL) in plasma. In this present investigation, we appraised the potential of SAA4 as a novel diagnostic biomarker for rheumatoid arthritis (RA) combined with other established RA biomarkers, including anticitrullinated protein antibody (anti-CCP), rheumatoid factor (RF)，and C-reactive protein (CRP). Based on the correlative measures of the biomarkers, we developed a diagnostic model of RA by integrating serum levels of SAA4 with these clinical parameters. Methods A number of 316 patients were recruited in the current research. The serum levels of SAA4 were assessed by quantitative ELISA. The specificity and sensitivity of biomarkers were evaluated by using a receiver-operator curve (ROC) analysis to determine their diagnostic efficiency. Univariate and multivariate logistic regression analyses were used to screen and construct the diagnostic models for RA , consisting of diagnostic biomarkers and clinical data. A diagnostic nomogram was then generated based on logistic regression analysis results. Results The serum levels of SAA4 were considerably greatest in RA patients in comparison to other control subjects (P<0.001). Compared with anti-CCP, RF and CRP respectively, SAA4 had the highest specificity (88.60%) for diagnosing RA. The combination of SAA4 with anti-CCP could have the highest diagnostic accuracy when paired together, with highest sensitivity (91.14%) in parallel and highest specificity(98.10) in series. We successfully developed two diagnostic models: the combined model of SAA4 and anti-CCP (model A), and the combined model of SAA4, CRP, anti-CCP, RF and history of diabetes (model B). Both models showed a great area under the curve of ROC for either the training cohort or the validation cohort. The data indicated that the novel RA diagnostic models possessed an advantageous discrimination capacity and application potential. Conclusion Serum SAA4 has utility as a biomarker for RA’s diagnosis and can enhance the detection of RA when combined with anti-CCP.

Usefulness of Serum Anti-p53 Antibody Assay for Lung Cancer Diagnosis

2011 ◽  
Vol 135 (12) ◽  
pp. 1570-1575 ◽  
Author(s):  
Yongjung Park ◽  
Yoonjung Kim ◽  
Jong-Han Lee ◽  
Eun Young Lee ◽  
Hyon-Suk Kim
Keyword(s):  
Lung Cancer ◽  
Receiver Operating Characteristic ◽  
Tumor Markers ◽  
Operating Characteristic ◽  
Area Under The Curve ◽  
Control Group ◽  
Cytokeratin 19 ◽  
Characteristic Analysis ◽  
Serum Samples ◽  
Receiver Operating

Context.—Some tumor markers, including carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA 21-1), are used for the detection of lung cancer; however, their use is limited because of low sensitivities and high false-positive rates. Objectives.—To investigate the usefulness of an anti-p53 assay in detecting lung cancer and to compare the anti-p53 to CEA and CYFRA 21-1 tumor markers. Design.—Serum samples were collected from 82 patients with lung cancer. Sera were also collected from 79 patients with or without benign pulmonary disease for the control group. All 161 specimens were assayed for CEA, CYFRA 21-1, and anti-p53. The diagnostic performances of these markers were compared using receiver operating characteristic analysis. Results.—The receiver operating characteristic area under the curve values of CYFRA 21-1, CEA, and anti-p53 for discriminating lung cancers from benign or healthy conditions were 0.79, 0.81, and 0.79, respectively. Area under the curve for the 3 markers in combination was 0.90. The sensitivities of those markers for lung cancer detection were respectively 39.0%, 53.7%, and 34.1% at 94.9% specificity, and the cutoff levels at those sensitivities and specificities were 4.5 ng/mL for CYFRA 21-1, 5.4 ng/mL for CEA, and 2.7 U/mL for anti-p53. We found 79.3% positive results for patients with lung cancer by any of the 3 markers, and 12.2% were positive only for anti-p53. All patients without cancer had negative results for 2 or all 3 markers. Conclusions.—Anti-p53 combined with other conventional markers is helpful in increasing the sensitivity and specificity for detecting lung cancer.

A randomized cross-over trial in patients suspected of PAD on diagnostic accuracy of ankle-brachial index by Doppler-based versus four-point oscillometry based measurements

VASA ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 516-522 ◽  
Author(s):  
Verena Mayr ◽  
Mirko Hirschl ◽  
Peter Klein-Weigel ◽  
Luka Girardi ◽  
Michael Kundi
Keyword(s):  
Diagnostic Accuracy ◽  
Ankle Brachial Index ◽  
Area Under The Curve ◽  
High Volume ◽  
Epidemiologic Studies ◽  
Lower Sensitivity ◽  
Oscillometric Device ◽  
Specificity And Sensitivity ◽  
Time Requirements ◽  
Peripheral Arterial

Summary. Background: For diagnosis of peripheral arterial occlusive disease (PAD), a Doppler-based ankle-brachial-index (dABI) is recommended as the first non-invasive measurement. Due to limitations of dABI, oscillometry might be used as an alternative. The aim of our study was to investigate whether a semi-automatic, four-point oscillometric device provides comparable diagnostic accuracy. Furthermore, time requirements and patient preferences were evaluated. Patients and methods: 286 patients were recruited for the study; 140 without and 146 with PAD. The Doppler-based (dABI) and oscillometric (oABI and pulse wave index – PWI) measurements were performed on the same day in a randomized cross-over design. Specificity and sensitivity against verified PAD diagnosis were computed and compared by McNemar tests. ROC analyses were performed and areas under the curve were compared by non-parametric methods. Results: oABI had significantly lower sensitivity (65.8%, 95% CI: 59.2%–71.9%) compared to dABI (87.3%, CI: 81.9–91.3%) but significantly higher specificity (79.7%, 74.7–83.9% vs. 67.0%, 61.3–72.2%). PWI had a comparable sensitivity to dABI. The combination of oABI and PWI had the highest sensitivity (88.8%, 85.7–91.4%). ROC analysis revealed that PWI had the largest area under the curve, but no significant differences between oABI and dABI were observed. Time requirement for oABI was significantly shorter by about 5 min and significantly more patients would prefer oABI for future testing. Conclusions: Semi-automatic oABI measurements using the AngER-device provide comparable diagnostic results to the conventional Doppler method while PWI performed best. The time saved by oscillometry could be important, especially in high volume centers and epidemiologic studies.

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.

Clinical value of tumor-associated antigens and autoantibody panel combination detection in the early diagnostic of lung cancer

2021 ◽  
pp. 1-9
Author(s):  
Renren Ouyang ◽  
Shiji Wu ◽  
Bo Zhang ◽  
Ting Wang ◽  
Botao Yin ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Disease ◽  
Cytokeratin 19 ◽  
Healthy Controls ◽  
Control Groups ◽  
Clinical Value ◽  
Tumor Associated Antigens ◽  
Pathological Subtype ◽  
Positive Rate ◽  
Diagnosis Of Lung Cancer

BACKGROUND: This study aimed to investigate the efficiency of combining tumor-associated antigens (TAAs) and autoantibodies in the diagnosis of lung cancer. METHODS: The serum levels of TAAs and seven autoantibodies (7-AABs) were detected from patients with lung cancer, benign lung disease and healthy controls. The performance of a new panel by combing TAAs and 7-AABs was evaluated for the early diagnosis of lung cancer. RESULTS: The positive rate of 7-AABs was higher than the single detection of antibody. The positive rate of the combined detection of 7-AABs in lung cancer group (30.2%) was significantly higher than that of healthy controls (16.8%), but had no statistical difference compared with that of benign lung disease group (20.8%). The positive rate of 7-AABs showed a tendency to increase in lung cancer patients with higher tumor-node-metastasis (TNM) stages. For the pathological subtype analysis, the positive rate of 7-AABs was higher in patients with squamous cell carcinoma and small cell lung cancer than that of adenocarcinoma. The levels of carcinoembryonic antigen (CEA) and cytokeratin 19 fragment 211 (CYFRA 211) were significantly higher than that of benign lung disease and healthy control groups. An optimal model was established (including 7-AABs, CEA and CYFRA21-1) to distinguish lung cancer from control groups. The performance of this model was superior than that of single markers, with a sensitivity of 52.26% and specificity of 77.46% in the training group. Further assessment was studied in another validation group, with a sensitivity of 44.02% and specificity of 83%. CONCLUSIONS: The diagnostic performance was enhanced by combining 7-AABs, CEA and CYFRA21-1, which has critical value for the screening and early detection of lung cancer.

Evaluation of the Clinical Role of Strain Elastography in Patients Diagnosed With Congenital Torticollis

2021 ◽  
pp. 875647932098324
Author(s):  
Elif Özyazici Özkan ◽  
Mehmet Burak Ozkan ◽  
İshak Abdurrahman İsik
Keyword(s):  
Area Under The Curve ◽  
Muscle Group ◽  
Receiver Operating Curve ◽  
Control Group ◽  
Clinical Role ◽  
Congenital Muscular Torticollis ◽  
Cutoff Value ◽  
Strain Elastography ◽  
Specificity And Sensitivity ◽  
Muscular Torticollis

Objective: The objective of this study was to determine the elasticity of sternocleidomastoid muscle (SCM) in patients with congenital muscular torticollis (CMT). Methods: In all, 41 patients and 22 controls were included in the study, and the elasticity of the patients’ SCM was measured. Echogenicity, thickness, and strain values of the SCM were also obtained. Results: The thickness and strain values of the SCM were higher in the patient group than in the control group ( P = .02 and P = .15). For median values, there was no difference in echogenicity and strain. In the strain elastography evaluation of the receiver operating curve (ROC) for muscle echogenicity in the isoechoic muscle group, the specificity and sensitivity were determined to be 100% and 22%, respectively, for the area under the curve (AOC) value of 0.558 (95% confidence interval [CI], 0.424–0.6686), and the cutoff value was <1.4. In the hyperechoic muscle group, the ROC for AUC values was found to be 0.542 (95% CI, 0.411–0.6686), and the cutoff value was >1.4 with 100% sensitivity and 20.75 specificity. Conclusions: The strain elastography technique can be used in the diagnosis of CMT.

scholarly journals Identification of an optimal prolactin threshold to determine prolactinoma size using receiver operating characteristic analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bianca M. Leca ◽  
Maria Mytilinaiou ◽  
Marina Tsoli ◽  
Andreea Epure ◽  
Simon J. B. Aylwin ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Tumour Size ◽  
Area Under The Curve ◽  
Serum Prolactin ◽  
Pituitary Neoplasms ◽  
Characteristic Analysis ◽  
Roc Curve Analysis ◽  
Baseline Serum ◽  
Receiver Operating

AbstractProlactinomas represent the most common type of secretory pituitary neoplasms, with a therapeutic management that varies considerably based on tumour size and degree of hyperprolactinemia. The aim of the current study was to evaluate the relationship between serum prolactin (PRL) concentrations and prolactinoma size, and to determine a cut-off PRL value that could differentiate micro- from macro-prolactinomas. A retrospective cohort study of 114 patients diagnosed with prolactinomas between 2007 and 2017 was conducted. All patients underwent gadolinium enhanced pituitary MRI and receiver operating characteristic (ROC) analyses were performed. 51.8% of patients in this study were men, with a mean age at the time of diagnosis of 42.32 ± 15.04 years. 48.2% of the total cohort were found to have microadenomas. Baseline serum PRL concentrations were strongly correlated to tumour dimension (r = 0.750, p = 0.001). When performing the ROC curve analysis, the area under the curve was 0.976, indicating an excellent accuracy of the diagnostic method. For a value of 204 μg/L (4338 mU/L), sensitivity and specificity were calculated at 0.932 and 0.891, respectively. When a cut off value of 204 μg/L (4338 mU/L) was used, specificity was 93.2%, and sensitivity 89.1%, acceptable to reliably differentiate between micro- and macro- adenomas.

scholarly journals Carboplatin and Paclitaxel in Combination With Either Vorinostat or Placebo for First-Line Therapy of Advanced Non–Small-Cell Lung Cancer

2010 ◽  
Vol 28 (1) ◽  
pp. 56-62 ◽  
Author(s):  
Suresh S. Ramalingam ◽  
Michael L. Maitland ◽  
Paul Frankel ◽  
Athanassios E. Argiris ◽  
Marianna Koczywas ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Response Rate ◽  
Area Under The Curve ◽  
Progression Free Survival ◽  
Small Cell ◽  
Controlled Study ◽  
Small Cell Lung ◽  
Anticancer Effects

Purpose Vorinostat, a histone deacetylase inhibitor, exerts anticancer effects by both histone and nonhistone–mediated mechanisms. It also enhances the anticancer effects of platinum compounds and taxanes in non–small-cell lung cancer (NSCLC) cell lines. This phase II randomized, double-blinded, placebo-controlled study evaluated the efficacy of vorinostat in combination with carboplatin and paclitaxel in patients with advanced-stage NSCLC. Patients and Methods Patients with previously untreated stage IIIB (ie, wet) or IV NSCLC were randomly assigned (2:1) to carboplatin (area under the curve, 6 mg/mL × min) and paclitaxel (200 mg/m2 day 3) with either vorinostat (400 mg by mouth daily) or placebo. Vorinostat or placebo was given on days 1 through 14 of each 3-week cycle to a maximum of six cycles. The primary end point was comparison of the response rate. Results Ninety-four patients initiated protocol therapy. Baseline patient characteristics were similar between the two arms. The median number of cycles was four for both treatment arms. The confirmed response rate was 34% with vorinostat versus 12.5% with placebo (P = .02). There was a trend toward improvement in median progression-free survival (6.0 months v 4.1 months; P = .48) and overall survival (13.0 months v 9.7 months; P = .17) in the vorinostat arm. Grade 4 platelet toxicity was more common with vorinostat (18% v 3%; P < .05). Nausea, emesis, fatigue, dehydration, and hyponatremia also were more frequent with vorinostat. Conclusion Vorinostat enhances the efficacy of carboplatin and paclitaxel in patients with advanced NSCLC. HDAC inhibition is a promising therapeutic strategy for treatment of NSCLC.

scholarly journals Convolutional Neural Networks Promising in Lung Cancer T-Parameter Assessment on Baseline FDG-PET/CT

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
Margarita Kirienko ◽  
Martina Sollini ◽  
Giorgia Silvestri ◽  
Serena Mognetti ◽  
Emanuele Voulaz ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Fdg Pet ◽  
Area Under The Curve ◽  
Ct Images ◽  
Tnm System ◽  
Positron Emission ◽  
Pet Ct ◽  
Test Sets ◽  
Fdg Pet Ct

Aim. To develop an algorithm, based on convolutional neural network (CNN), for the classification of lung cancer lesions as T1-T2 or T3-T4 on staging fluorodeoxyglucose positron emission tomography (FDG-PET)/CT images. Methods. We retrospectively selected a cohort of 472 patients (divided in the training, validation, and test sets) submitted to staging FDG-PET/CT within 60 days before biopsy or surgery. TNM system seventh edition was used as reference. Postprocessing was performed to generate an adequate dataset. The input of CNNs was a bounding box on both PET and CT images, cropped around the lesion centre. The results were classified as Correct (concordance between reference and prediction) and Incorrect (discordance between reference and prediction). Accuracy (Correct/[Correct + Incorrect]), recall (Correctly predicted T3-T4/[all T3-T4]), and specificity (Correctly predicted T1-T2/[all T1-T2]), as commonly defined in deep learning models, were used to evaluate CNN performance. The area under the curve (AUC) was calculated for the final model. Results. The algorithm, composed of two networks (a “feature extractor” and a “classifier”), developed and tested achieved an accuracy, recall, specificity, and AUC of 87%, 69%, 69%, and 0.83; 86%, 77%, 70%, and 0.73; and 90%, 47%, 67%, and 0.68 in the training, validation, and test sets, respectively. Conclusion. We obtained proof of concept that CNNs can be used as a tool to assist in the staging of patients affected by lung cancer.

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