scholarly journals Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jia-You Lin ◽  
Bao-Rong Juo ◽  
Yu-Hsuan Yeh ◽  
Shu-Hsuan Fu ◽  
Yi-Ting Chen ◽  
...  

Abstract Background Early detection of bladder cancer remains challenging because patients with early-stage bladder cancer usually have no incentive to take cytology or cystoscopy tests if they are asymptomatic. Our goal is to find non-invasive marker candidates that may help us gain insight into the metabolism of early-stage bladder cancer and be examined in routine health checks. Results We acquired urine samples from 124 patients diagnosed with early-stage bladder cancer or hernia (63 cancer patients and 61 controls). In which 100 samples were included in our marker discovery cohort, and the remaining 24 samples were included in our independent test cohort. We obtained metabolic profiles of 922 compounds of the samples by gas chromatography-mass spectrometry. Based on the metabolic profiles of the marker discovery cohort, we selected marker candidates using Wilcoxon rank-sum test with Bonferroni correction and leave-one-out cross-validation; we further excluded compounds detected in less than 60% of the bladder cancer samples. We finally selected eight putative markers. The abundance of all the eight markers in bladder cancer samples was high but extremely low in hernia samples. Moreover, the up-regulation of these markers might be in association with sugars and polyols metabolism. Conclusions In the present study, comparative urine metabolomics selected putative metabolite markers for the detection of early-stage bladder cancer. The suggested relations between early-stage bladder cancer and sugars and polyols metabolism may create opportunities for improving the detection of bladder cancer.

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Mengchan Fang ◽  
Fan Liu ◽  
Lingling Huang ◽  
Liqing Wu ◽  
Lan Guo ◽  
...  

A urine metabolomics study based on gas chromatography-mass spectrometry (GC-MS) and multivariate statistical analysis was applied to distinguish rat bladder cancer. Urine samples with different stages were collected from animal models, i.e., the early stage, medium stage, and advanced stage of the bladder cancer model group and healthy group. After resolving urea with urease, the urine samples were extracted with methanol and, then, derived with N, O-Bis(trimethylsilyl) trifluoroacetamide and trimethylchlorosilane (BSTFA + TMCS, 99 : 1, v/v), before analyzed by GC-MS. Three classification models, i.e., healthy control vs. early- and middle-stage groups, healthy control vs. advanced-stage group, and early- and middle-stage groups vs. advanced-stage group, were established to analyze these experimental data by using Random Forests (RF) algorithm, respectively. The classification results showed that combining random forest algorithm with metabolites characters, the differences caused by the progress of disease could be effectively exhibited. Our results showed that glyceric acid, 2, 3-dihydroxybutanoic acid, N-(oxohexyl)-glycine, and D-turanose had higher contributions in classification of different groups. The pathway analysis results showed that these metabolites had relationships with starch and sucrose, glycine, serine, threonine, and galactose metabolism. Our study results suggested that urine metabolomics was an effective approach for disease diagnosis.


2019 ◽  
Vol 35 (S1) ◽  
pp. 17-17
Author(s):  
Andrew Sutton ◽  
John Lamont ◽  
R. Evans ◽  
Kate Williamson ◽  
Declan O'Rourke ◽  
...  

IntroductionThe Institute of Health Economics offers a suite of analyses that provide developers an understanding of the expected commercial viability of an early stage health technology. In combination, these analyses form the Value-Engineered Translation framework. These methods incorporate innovative methods to manage uncertainty in early economic evaluations, in particular, moving beyond current stochastic assessments of headroom to account for inter-market variability in value hurdles, as well as incorporating social value premia considerations. An illustration of these methods is demonstrated using the example of a non-invasive diagnostic test (called DCRSHP) at an early stage of development, compared to current practice of cystoscopy in the diagnosis of bladder cancer.MethodsCompeting technologies were identified to inform the headroom assessment based on price and effectiveness. Then, a model-based cost-effectiveness analysis was undertaken incorporating headroom analysis, stochastic one-way sensitivity analysis, and value of information analysis using data from secondary sources.ResultsCurrently there are a number of non-invasive tests available, but none have sufficient test accuracy to be suitable for bladder cancer diagnosis alone. From the headroom analysis, DCRSHP can be priced at up to CAD 790 (i.e. USD 588) and still be cost-effective compared to the current practice of cystoscopy. Interestingly this price can be increased for patient groups that have lower levels of bladder cancer prevalence.ConclusionsThe requirements of economic evaluations depend on the stage of technology development, and analysis approaches must reflect this. The results here indicate that DCRSHP clears the value hurdle in terms of being cost-effective, and thus provides the opportunity to make a commercial return on future investment. Future analysis of DCRSHP could consider the cost drivers for development of the technology, including the regulatory pathways, costs associated with the intellectual asset management for the technology, and alternative manufacturing costs. All of which contribute to the research-to-practice continuum.


Cancers ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 870 ◽  
Author(s):  
Riccardo Vago ◽  
Alessandro Ravelli ◽  
Arianna Bettiga ◽  
Silvana Casati ◽  
Giovanni Lavorgna ◽  
...  

Due to the involvement of the endocannabinoid system (ECS) in cancer onset and progression and the less studied connection between ECS and bladder cancer, here an evaluation of the ECS modifications associated with bladder cancer is reported. Urine samples were collected from healthy volunteers and patients with bladder cancer at different grades. Endocannabinoids (ECs) and N-acylethanolamides (NAEs) were quantified by HPLC-MS/MS and results normalized for creatinine content. An increase in the urine concentrations of four ECs and NAEs analyzed was observed with a statistically significant increase in the arachidonoylethanolamide (AEA) and stearoylethanoamide (SEA) associated with bladder cancer. Receiver operating characteristic curves built with AEA and SEA data allowed the selection of 160 pg/mL for SEA (area under the curve (AUC) = 0.91, Selectivity (SE) 94%, Specificity (SP) 45%) and 8 pg/mL for AEA (AUC = 0.85, SE 94%, SP 61%) as the best cut-off values. Moreover, data from bladder cancer samples at different grades were derived from The Cancer Genome Atlas, and the expressions of thirteen different components of the “endocannabinoidome” were analyzed. Statistical analysis highlights significant variations in the expression of three enzymes involved in EC and NAE turnover in bladder cancer.


Metabolites ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 199
Author(s):  
Joana Pinto ◽  
Ângela Carapito ◽  
Filipa Amaro ◽  
Ana Rita Lima ◽  
Carina Carvalho-Maia ◽  
...  

Timely diagnosis is crucial to improve the long-term survival of bladder cancer (BC) patients. The discovery of new BC biomarkers based in urine analysis is very attractive because this biofluid is in direct contact with the inner bladder layer, in which most of the neoplasms develop, and is non-invasively collected. Hence, this work aimed to unveil alterations in the urinary volatile profile of patients diagnosed with BC compared with cancer-free individuals, as well as differences among patients diagnosed at different tumor stages, to identify candidate biomarkers for non-invasive BC diagnosis and staging. Urine analysis was performed by headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS). The results unveiled that BC patients have a distinct urinary volatile profile characterized by higher levels of several alkanes and aromatic compounds, and lower levels of aldehydes, ketones and monoterpenes. Seventeen significantly altered volatiles were used to evaluate the performance for overall BC detection, disclosing 70% sensitivity, 89% specificity and 80% accuracy. Moreover, distinct urinary volatile profiles were found among patients diagnosed at different tumor stages (Ta/Tis, T1 and ≥T2). This work identified distinct urinary volatile signatures of BC patients with potential for non-invasive detection and staging of bladder cancer.


Author(s):  
Muhammad Nadeem Ashraf ◽  
Muhammad Hussain ◽  
Zulfiqar Habib

Diabetic Retinopathy (DR) is a major cause of blindness in diabetic patients. The increasing population of diabetic patients and difficulty to diagnose it at an early stage are limiting the screening capabilities of manual diagnosis by ophthalmologists. Color fundus images are widely used to detect DR lesions due to their comfortable, cost-effective and non-invasive acquisition procedure. Computer Aided Diagnosis (CAD) of DR based on these images can assist ophthalmologists and help in saving many sight years of diabetic patients. In a CAD system, preprocessing is a crucial phase, which significantly affects its performance. Commonly used preprocessing operations are the enhancement of poor contrast, balancing the illumination imbalance due to the spherical shape of a retina, noise reduction, image resizing to support multi-resolution, color normalization, extraction of a field of view (FOV), etc. Also, the presence of blood vessels and optic discs makes the lesion detection more challenging because these two artifacts exhibit specific attributes, which are similar to those of DR lesions. Preprocessing operations can be broadly divided into three categories: 1) fixing the native defects, 2) segmentation of blood vessels, and 3) localization and segmentation of optic discs. This paper presents a review of the state-of-the-art preprocessing techniques related to three categories of operations, highlighting their significant aspects and limitations. The survey is concluded with the most effective preprocessing methods, which have been shown to improve the accuracy and efficiency of the CAD systems.


Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2510
Author(s):  
Konrad Górny ◽  
Piotr Kuwałek ◽  
Wojciech Pietrowski

The article proposes a proprietary approach to the diagnosis of induction motors allowing increasing the reliability of electric vehicles. This approach makes it possible to detect damage in the form of an inter-turn short-circuit at an early stage of its occurrence. The authors of the article describe an effective diagnostic method using the extraction of diagnostic signal features using an Enhanced Empirical Wavelet Transform and an algorithm based on the method of Ensemble Bagged Trees. The article describes in detail the methodology of the carried out research, presents the method of extracting features from the diagnostic signal and describes the conclusions resulting from the research. Phase current waveforms obtained from a real object as well as simulation results based on the field-circuit model of an induction motor were used as a diagnostic signal in the research. In order to determine the accuracy of the damage classification, simple metrics such as accuracy, sensitivity, selectivity, precision as well as complex metrics weight F1 and macro F1 were used.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Weimei Ruan ◽  
Xu Chen ◽  
Ming Huang ◽  
Hong Wang ◽  
Jiaxin Chen ◽  
...  

Abstract Background Current non-invasive tests have limited sensitivities and lack capabilities of pre-operative risk stratification for bladder cancer (BC) diagnosis. We aimed to develop and validate a urine-based DNA methylation assay as a clinically feasible test for improving BC detection and enabling pre-operative risk stratifications. Methods A urine-based DNA methylation assay was developed and validated by retrospective single-center studies in patients of suspected BC in Cohort 1 (n = 192) and Cohort 2 (n = 98), respectively. In addition, a prospective single-center study in hematuria patient group (Cohort 3, n = 174) was used as a second validation of the model. Results The assay with a dual-marker detection model showed 88.1% and 91.2% sensitivities, 89.7% and 85.7% specificities in validation Cohort 2 (patients of suspected BC) and Cohort 3 (patients of hematuria), respectively. Furthermore, this assay showed improved sensitivities over cytology and FISH on detecting low-grade tumor (66.7–77.8% vs. 0.0–22.2%, 0.0–22.2%), Ta tumor (83.3% vs. 22.2–41.2%, 44.4–52.9%) and non-muscle invasive BC (NMIBC) (80.0–89.7% vs. 51.5–52.0%, 59.4–72.0%) in both cohorts. The assay also had higher accuracies (88.9–95.8%) in diagnosing cases with concurrent genitourinary disorders as compared to cytology (55.6–70.8%) and FISH (72.2–77.8%). Meanwhile, the assay with a five-marker stratification model identified high-risk NMIBC and muscle invasive BC with 90.5% sensitivity and 86.8% specificity in Cohort 2. Conclusions The urine-based DNA methylation assay represents a highly sensitive and specific approach for BC early-stage detection and risk stratification. It has a potential to be used as a routine test to improve diagnosis and prognosis of BC in clinic.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Imteyaz Ahmad Khan ◽  
Safoora Rashid ◽  
Nidhi Singh ◽  
Sumaira Rashid ◽  
Vishwajeet Singh ◽  
...  

AbstractEarly-stage diagnosis of pancreatic ductal adenocarcinoma (PDAC) is difficult due to non-specific symptoms. Circulating miRNAs in body fluids have been emerging as potential non-invasive biomarkers for diagnosis of many cancers. Thus, this study aimed to assess a panel of miRNAs for their ability to differentiate PDAC from chronic pancreatitis (CP), a benign inflammatory condition of the pancreas. Next-generation sequencing was performed to identify miRNAs present in 60 FFPE tissue samples (27 PDAC, 23 CP and 10 normal pancreatic tissues). Four up-regulated miRNAs (miR-215-5p, miR-122-5p, miR-192-5p, and miR-181a-2-3p) and four down-regulated miRNAs (miR-30b-5p, miR-216b-5p, miR-320b, and miR-214-5p) in PDAC compared to CP were selected based on next-generation sequencing results. The levels of these 8 differentially expressed miRNAs were measured by qRT-PCR in 125 serum samples (50 PDAC, 50 CP, and 25 healthy controls (HC)). The results showed significant upregulation of miR-215-5p, miR-122-5p, and miR-192-5p in PDAC serum samples. In contrast, levels of miR-30b-5p and miR-320b were significantly lower in PDAC as compared to CP and HC. ROC analysis showed that these 5 miRNAs can distinguish PDAC from both CP and HC. Hence, this panel can serve as a non-invasive biomarker for the early detection of PDAC.


2020 ◽  
Vol 245 (16) ◽  
pp. 1428-1436
Author(s):  
Zhi-Jun Zhang ◽  
Xing-Guo Song ◽  
Li Xie ◽  
Kang-Yu Wang ◽  
You-Yong Tang ◽  
...  

Circulating exosomal microRNAs (ExmiRNAs) provide an ideal non-invasive method for cancer diagnosis. In this study, we evaluated two circulating ExmiRNAs in NSCLC patients as a diagnostic tool for early-stage non-small lung cancer (NSCLC). The exosomes were characterized by qNano, transmission electron microscopy, and Western blot, and the ExmiRNA expression was measured by microarrays. The differentially expressed miRNAs were verified by RT-qPCR using peripheral blood specimens from NSCLC patients ( n = 276, 0 and I stage: n = 104) and healthy donors ( n = 282). The diagnostic values were measured by receiver operating characteristic (ROC) analysis. The results show that the expression of both ExmiR-20b-5p and ExmiR-3187-5p was drastically reduced in NSCLC patients. The area under the ROC curve (AUC) was determined to be 0.818 and 0.690 for ExmiR-20b-5p and ExmiR-3187-5p, respectively. When these two ExmiRNAs were combined, the AUC increased to 0.848. When the ExmiRNAs were administered with either carcinoembryonic antigen (CEA) or cytokeratin-19-fragment (CYFRA21-1), the AUC was further improved to 0.905 and 0.894, respectively. Additionally, both ExmiR-20b-5p and ExmiR-3187-5p could be used to distinguish early stages NSCLC (0 and I stage) from the healthy controls. The ROC curves showed that the AUCs were 0.810 and 0.673, respectively. Combination of ExmiR-20b-5p and ExmiR-3187-5p enhanced the AUC to 0.838. When CEA and CYFRA21-1 were administered with the ExmiRNAs, the AUCs were improved to 0.930 and 0.928, respectively. In summary, circulating serum exosomal miR-20b-5p and miR-3187-5p could be used as effective, non-invasive biomarkers for the diagnosis of early-stage NSCLC, and the effects were further improved when the ExmiRNAs were combined. Impact statement The high mortality of non-small cell lung cancer (NSCLC) is mainly because the cancer has progressed to a more advanced stage before diagnosis. If NSCLC can be diagnosed at early stages, especially stage 0 or I, the overall survival rate will be largely improved by definitive treatment such as lobectomy. We herein validated two novel circulating serum ExmiRs as diagnostic biomarkers for early-stage NSCLC to fulfill the unmet medical need. Considering the number of specimens in this study, circulating serum exosomal miR-20b-5p and miR-3187-5p are putative NSCLC biomarkers, which need to be further investigated in a larger randomized controlled clinical trial.


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