scholarly journals Plasma-derived candidate biomarkers for detection of gallbladder carcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ratna Priya ◽  
Vaishali Jain ◽  
Javed Akhtar ◽  
Geeta Chauhan ◽  
Puja Sakhuja ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Gallbladder Carcinoma ◽  
Poor Prognosis ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Early Stage ◽  
High Sensitivity ◽  
Advanced Stage ◽  
Associated Proteins ◽  
Clinical Verification

AbstractGallbladder carcinoma (GBC) is a major cancer of the gastrointestinal tract with poor prognosis. Reliable and affordable biomarker-based assays with high sensitivity and specificity for the detection of this cancer are a clinical need. With the aim of studying the potential of the plasma-derived extracellular vesicles (EVs), we carried out quantitative proteomic analysis of the EV proteins, using three types of controls and various stages of the disease, which led to the identification of 86 proteins with altered abundance. These include 29 proteins unique to early stage, 44 unique to the advanced stage and 13 proteins being common to both the stages. Many proteins are functionally relevant to the tumor condition or have been also known to be differentially expressed in GBC tissues. Several of them are also present in the plasma in free state. Clinical verification of three tumor-associated proteins with elevated levels in comparison to all the three control types—5′-nucleotidase isoform 2 (NT5E), aminopeptidase N (ANPEP) and neprilysin (MME) was carried out using individual plasma samples from early or advanced stage GBC. Sensitivity and specificity assessment based on receiver operating characteristic (ROC) analysis indicated a significant association of NT5E and ANPEP with advanced stage GBC and MME with early stage GBC. These and other proteins identified in the study may be potentially useful for developing new diagnostics for GBC.

The utility of six serum tumor markers in early detection of lung cancer

2019 ◽  
Author(s):  
Qingwen Jiang ◽  
Xu Zheng ◽  
Yiting Li ◽  
Weina Huang ◽  
Xinjian Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Sensitivity And Specificity ◽  
Operating Characteristic ◽  
Early Stage ◽  
High Sensitivity ◽  
Roc Curves ◽  
Serum Levels ◽  
Benign Diseases ◽  
Significant Difference ◽  
Diagnosis Of Lung Cancer

Abstract Background: Lung cancer has become the leading cause of cancer-related death in China. However, most of patients were diagnosed at advanced stage. Thus, novel lung cancer diagnostic tests, which can be used to screen individuals in early stage, are required.Methods: A total of 208 patients involving 161 cases of lung cancer and 47 cases of benign diseases were enrolled. Serum concentration of GTM, CETM, PTM, CTM, ETM and HTM were analyzed by kits according to the manufacturer’s guidelines.Results: The results showed significant difference in serum concentrations of GTM, CETM, PTM, CTM, ETM, and HTM between patients with lung cancer and benign diseases. In addition, when compared with benign diseases, higher levels of those six markers were also observed in patient with SCC and SCLC, but not for ADC. Receiver operating characteristic (ROC) curves were further suggested a high sensitivity and specificity of six markers to identify lung cancer.Conclusion: The serum levels of GTM, CETM, PTM, CTM, ETM and HTM in lung cancer were significantly higher than those of benign diseases. Moreover, these six biomarkers showed a high sensitivity and specificity to identify a patient with malignant. These findings suggested that detection of those six biomarkers in serum might be helpful for differential diagnosis of lung cancer.

miR-224 is an early-stage biomarker of hepatocellular carcinoma with miR-224 and miR-125b as prognostic biomarkers

2020 ◽  
Vol 14 (15) ◽  
pp. 1485-1500
Author(s):  
Lichao Yang ◽  
Chunmeng Wei ◽  
Yasi Li ◽  
Xiao He ◽  
Min He
Keyword(s):  
Hepatocellular Carcinoma ◽  
Systematic Review ◽  
Survival Analysis ◽  
Sensitivity And Specificity ◽  
Poor Prognosis ◽  
Early Stage ◽  
Meta Analysis ◽  
Benign Lesion ◽  
Diagnostic Efficiency ◽  
Low Expression

Aim: The aim was to systematically investigate the miRNA biomarkers for early diagnosis of hepatocellular carcinoma (HCC). Materials & methods: A systematic review and meta-analysis of miRNA expression in HCC were performed. Results: A total of 4903 cases from 30 original studies were comprehensively analyzed. The sensitivity and specificity of miR-224 in discriminating early-stage HCC patients from benign lesion patients were 0.868 and 0.792, which were superior to α-fetoprotein. Combined miR-224 with α-fetoprotein, the sensitivity and specificity were increased to 0.882 and 0.808. Prognostic survival analysis showed low expression of miR-125b and high expression of miR-224 were associated with poor prognosis. Conclusion: miR-224 had a prominent diagnostic efficiency in early-stage HCC, with miR-224 and miR-125b being valuable in the prognostic diagnosis.

scholarly journals Discovery of Prognostic Markers for Early-Stage High-Grade Serous Ovarian Cancer by Maldi-Imaging

Cancers ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2000
Author(s):  
Hagen Kulbe ◽  
Oliver Klein ◽  
Zhiyang Wu ◽  
Eliane T. Taube ◽  
Wanja Kassuhn ◽  
...  
Keyword(s):  
Roc Analysis ◽  
Operating Characteristic ◽  
Prognostic Markers ◽  
Early Stage ◽  
Imaging Mass Spectrometry ◽  
Maldi Imaging ◽  
High Grade ◽  
Proof Of Concept ◽  
Tissue Sections ◽  
Maldi Ims

With regard to relapse and survival, early-stage high-grade serous ovarian (HGSOC) patients comprise a heterogeneous group and there is no clear consensus on first-line treatment. Currently, no prognostic markers are available for risk assessment by standard targeted immunohistochemistry and novel approaches are urgently required. Here, we applied MALDI-imaging mass spectrometry (MALDI-IMS), a new method to identify distinct mass profiles including protein signatures on paraffin-embedded tissue sections. In search of prognostic biomarker candidates, we compared proteomic profiles of primary tumor sections from early-stage HGSOC patients with either recurrent (RD) or non-recurrent disease (N = 4; each group) as a proof of concept study. In total, MALDI-IMS analysis resulted in 7537 spectra from the malignant tumor areas. Using receiver operating characteristic (ROC) analysis, 151 peptides were able to discriminate between patients with RD and non-RD (AUC > 0.6 or < 0.4; p < 0.01), and 13 of them could be annotated to proteins. Strongest expression levels of specific peptides linked to Keratin type1 and Collagen alpha-2(I) were observed and associated with poor prognosis (AUC > 0.7). These results confirm that in using IMS, we could identify new candidates to predict clinical outcome and treatment extent for patients with early-stage HGSOC.

scholarly journals Radiomics Signatures of Computed Tomography Imaging for Predicting Risk Categorization and Clinical Stage of Thymomas

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Xihai Wang ◽  
Wei Sun ◽  
Hongyuan Liang ◽  
Xiaonan Mao ◽  
Zaiming Lu
Keyword(s):  
High Risk ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Early Stage ◽  
Clinical Stage ◽  
Advanced Stage ◽  
Enhanced Ct ◽  
Significant Difference ◽  
Risk Categorization ◽  
Radiomics Signature

Purpose. The aim of this study is to develop and compare performance of radiomics signatures using texture features extracted from noncontrast enhanced CT (NECT) and contrast enhanced CT (CECT) images for preoperative predicting risk categorization and clinical stage of thymomas. Materials and Methods. Between January 2010 and October 2018, 199 patients with surgical resection and histopathologically confirmed thymoma were enrolled in this retrospective study. We extracted 841 radiomics features separately from volume of interest (VOI) in NECT and CECT images. The features with poor reproducibility and highly redundancy were removed. Then a least absolute shrinkage and selection operator method (LASSO) logistic regression model with 10-fold cross validation was used for further feature selection and radiomics signatures build. The predictive performances of radiomics signatures were assessed by receiver operating characteristic (ROC) analysis. The areas under the receiver operating characteristic curve (AUC) between radiomics signatures were compared by using Delong test. Result. In differentiating high risk thymomas from low risk thymomas, the AUC, sensitivity, and specificity were 0.801(95% CI 0.740–0.863), 0.752 and 0.767 for radiomics signature based on NECT images, and 0.827 (95% CI 0.771 -0.884), 0.798, and 0.722 for radiomics signature based on CECT images. But there was no significant difference (p=0.365) between them. In differentiating advanced stage thymomas from early stage thymomas, the AUC, sensitivity, and specificity were 0.829 (95%CI 0.757-0.900), 0.712, and 0.806 for radiomics signature based on NECT images and 0.860 (95%CI 0.803-0.917), 0.699, and 0.889 for radiomics signature based on CECT images. There was no significant difference (p=0.069) between them. The accuracy was 0.819 for radiomics signature based on NECT images, 0.869 for radiomics signature based on CECT images, and 0.779 for radiologists. Both radiomics signatures had a better performance than radiologists. But there was significant difference (p = 0.025) only between CECT radiomics signature and radiologists. Conclusion. Radiomics signatures based on texture analysis from NECT and CECT images could be utilized as noninvasive biomarkers for differentiating high risk thymomas from low risk thymomas and advanced stage thymomas from early stage thymoma. As a quantitative method, radiomics signature can provide complementary diagnostic information and help to plan personalized treatment for patients with thymomas.

scholarly journals Semi-Automatic Signature-Based Segmentation Method for Quantification of Neuromelanin in Substantia Nigra

2019 ◽  
Vol 9 (12) ◽  
pp. 335 ◽  
Author(s):  
Gašper Zupan ◽  
Dušan Šuput ◽  
Zvezdan Pirtošek ◽  
Andrej Vovk
Keyword(s):  
Substantia Nigra ◽  
Sensitivity And Specificity ◽  
Roc Analysis ◽  
Automatic Segmentation ◽  
High Sensitivity ◽  
Segmentation Method ◽  
Surface Sensitivity ◽  
Volume Sensitivity ◽  
Segmentation Methods ◽  
The Difference

In Parkinson’s disease (PD), there is a reduction of neuromelanin (NM) in the substantia nigra (SN). Manual quantification of the NM volume in the SN is unpractical and time-consuming; therefore, we aimed to quantify NM in the SN with a novel semi-automatic segmentation method. Twenty patients with PD and twelve healthy subjects (HC) were included in this study. T1-weighted spectral pre-saturation with inversion recovery (SPIR) images were acquired on a 3T scanner. Manual and semi-automatic atlas-free local statistics signature-based segmentations measured the surface and volume of SN, respectively. Midbrain volume (MV) was calculated to normalize the data. Receiver operating characteristic (ROC) analysis was performed to determine the sensitivity and specificity of both methods. PD patients had significantly lower SN mean surface (37.7 ± 8.0 vs. 56.9 ± 6.6 mm2) and volume (235.1 ± 45.4 vs. 382.9 ± 100.5 mm3) than HC. After normalization with MV, the difference remained significant. For surface, sensitivity and specificity were 91.7 and 95 percent, respectively. For volume, sensitivity and specificity were 91.7 and 90 percent, respectively. Manual and semi-automatic segmentation methods of the SN reliably distinguished between PD patients and HC. ROC analysis shows the high sensitivity and specificity of both methods.

scholarly journals Serum Epiplakin Might Be a Potential Serodiagnostic Biomarker for Bladder Cancer

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5150
Author(s):  
Soichiro Shimura ◽  
Kazumasa Matsumoto ◽  
Yuriko Shimizu ◽  
Kohei Mochizuki ◽  
Yutaka Shiono ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Healthy Volunteers ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Early Stage ◽  
Area Under The Curve ◽  
Stone Disease ◽  
Dot Blot ◽  
Expression Levels ◽  
Clinicopathological Findings

Tumor markers that can be detected at an early stage are needed. Here, we evaluated the epiplakin expression levels in sera from patients with bladder cancer (BC). Using a micro-dot blot array, we evaluated epiplakin expression levels in 60 patients with BC, 20 patients with stone disease, and 28 healthy volunteers. The area under the curve (AUC) and best cut-off point were calculated using receiver-operating characteristic (ROC) analysis. Serum epiplakin levels were significantly higher in patients with BC than in those with stone disease (p = 0.0013) and in healthy volunteers (p < 0.0001). The AUC-ROC level for BC was 0.78 (95% confidence interval (CI) = 0.69–0.87). Using a cut-off point of 873, epiplakin expression levels exhibited 68.3% sensitivity and 79.2% specificity for BC. However, the serum epiplakin levels did not significantly differ by sex, age, pathological stage and grade, or urine cytology. We performed immunohistochemical staining using the same antibody on another cohort of 127 patients who underwent radical cystectomy. Univariate and multivariate analysis results showed no significant differences between epiplakin expression, clinicopathological findings, and patient prognoses. Our results showed that serum epiplakin might be a potential serodiagnostic biomarker in patients with BC.

scholarly journals 215 Assessment of the Diagnostic Sensitivity and Specificity of Pain Biomarkers in Cattle Using Receiver Operating Characteristic Curves

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 7-8
Author(s):  
Miriam S Martin ◽  
Michael Kleinhenz ◽  
Karen Schwartzkopf-Genswein ◽  
Johann Coetzee
Keyword(s):  
Diagnostic Accuracy ◽  
Receiver Operating Characteristic ◽  
Sensitivity And Specificity ◽  
Predictive Value ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Diagnostic Sensitivity ◽  
Diagnostic Sensitivity And Specificity ◽  
Good Diagnostic Accuracy ◽  
Receiver Operating

Abstract Biomarkers are commonly used to assess pain and analgesic drug efficacy in livestock. However, the diagnostic sensitivity and specificity of these biomarkers for different pain conditions over time have not been described. Receiver operating characteristic (ROC) curves are graphical plots that illustrate the diagnostic ability of a test as its discrimination threshold is varied. The objective of this analysis was to use area under the curve (AUC) values derived from ROC analysis to assess the predictive value of pain biomarkers at specific timepoints. The biomarkers included in the analysis were blood cortisol, salivary cortisol, hair cortisol, infrared thermography (IRT), mechanical nociceptive threshold (MNT), substance P, and outcomes from a pressure/force measurement system and visual analog scale. A total sample size of 7,992 biomarker outcomes were collected from 6 pain studies involving pain associated with castration, dehorning, lameness, and surgery were included in the analysis. Each study consisted of three treatments; pain, no pain, and analgesia. All statistics were performed using statistical software (JMP Pro 14.0, SAS Institute, Inc., Cary, NC). Results comparing analgesia verses pain yielded good diagnostic accuracy (AUC &gt; 0.7; 95% CI: 0.40 to 0.99) for blood cortisol (timepoints 1.5, 2, and 6 hours); IRT (timepoints 6, 8, 12, and 72 hours); and MNT (timepoints 6, 25, and 49 hours). These results indicate that ROC analysis can be a useful indicator of the predictive value of pain biomarkers and certain timepoints seem to yield good diagnostic accuracy while many do not.

Blood-based detection of early-stage colorectal cancer using multiomics and machine learning.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 66-66
Author(s):  
Girish Putcha ◽  
Tzu-Yu Liu ◽  
Eric Ariazi ◽  
Marvin Bertin ◽  
Adam Drake ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Machine Learning ◽  
Sensitivity And Specificity ◽  
Late Stage ◽  
Early Stage ◽  
High Sensitivity ◽  
Average Risk ◽  
Learning Platform ◽  
Pathological Subtypes ◽  
Mean Sensitivity

66 Background: Despite population screening efforts, screening rates for colorectal cancer (CRC) remain suboptimal. A non-invasive, blood-based screening test with high sensitivity and specificity in early-stage disease should improve adherence and ultimately reduce mortality; however, tests based only on tumor-derived biomarkers have limited sensitivity. Here we used a multiomic, machine learning platform to discover, refine, and combine tumor- and immune-derived signals to develop a blood test for the detection of early-stage CRC. Methods: Samples from 591 participants enrolled in a prospective study including average-risk screening and case-control cohorts (NCT03688906) were included in this analysis (CRC: n = 43; colonoscopy-confirmed CRC-negative controls: n = 548). Participants with CRC were 60% male with a mean age of 63, and controls were 55% male with a mean age of 60. Stage distribution was 54% early (I/II) and 34% late (III/IV) with 11% unknown. Plasma was analyzed by whole-genome sequencing, bisulfite sequencing, and protein quantification methods. Computational methods were used to assess and infer the performance of individual and combined assays. Results: For colorectal adenocarcinoma, which represents ~95% of all CRCs, our multiomic test achieved a mean sensitivity of 92% in early stage (n = 17) and 84% in late stage (n = 11) at a specificity of 90%. Across all CRC pathological subtypes, our test achieved a mean sensitivity of 80% in early stage (n = 19) and 83% in late stage (n = 12) at a specificity of 90%; the test detected the single squamous cell carcinoma but missed both neuroendocrine tumors. Individual assays achieved a mean sensitivity of 50% in early stage and 66% in late stage at a specificity of 90%. Conclusions: In a prospective cohort, we demonstrated high sensitivity and specificity for early-stage adenocarcinoma by combining tumor- and immune-derived signals from cfDNA, epigenetic, and protein biomarkers. While most CRCs are adenocarcinomas, detection of all pathological subtypes is required to maximize sensitivity in a screening population. Further analysis of molecular and pathological subtypes, as well as the entire ~3000 patient cohort, is underway. Clinical trial information: NCT03688906.

scholarly journals Pathfast Presepsin Assay for Early Diagnosis of Systemic Inflammatory Response Syndrome in Patients with Nephrolithiasis

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Yan-song Hou ◽  
Hua Wang ◽  
Hao Chen ◽  
Ling-feng Wu ◽  
Lin-feng Lu ◽  
...  
Keyword(s):  
Roc Analysis ◽  
Operating Characteristic ◽  
Diagnostic Marker ◽  
Early Stage ◽  
Diagnostic Value ◽  
Bacterial Sepsis ◽  
Diagnostic Ability ◽  
Highly Sensitive ◽  
Comparable Performance ◽  
Median Plasma

It is relatively difficult to diagnose bacterial sepsis in nephrolithiasis patients. The aim of the study is to evaluate the diagnostic ability of presepsin in the differential diagnosis including SIRS, infection, or sepsis and to compare its diagnostic value with other markers, mainly as CRP, procalcitonin (PCT), and white blood cell (WBC) in patients of nephrolithiasis presenting with SIRS. 39 patients of nephrolithiasis who were diagnosed as SIRS were prospectively investigated. Plasma presepsin was detected by Pathfast presepsin assay system; CRP and PCT were measured as well. Additionally, 25 nephrolithiasis patients without SIRS were included. At all timing samples, patients were classified as SIRS or non-SIRS group. Median plasma presepsin levels were significantly increased in the SIRS group compared with non-SIRS group (452 pg/mL versus 178 ng/mL,P<0.001), and presepsin was markedly elevated even in the early stage of SIRS (584 pg/mL 6 h, 660 pg/mL 24 h versus 452 pg/mL,P<0.001). According to the receiver-operating characteristic (ROC) analysis, presepsin demonstrated a high diagnostic value compared with either PCT or CRP. In the early stage of SIRS, presepsin remained a highly sensitive (74.7%) and specific (88.4%) diagnostic marker compared with either PCT, CRP, or WBC. Moreover, the areas under the curve (AUCs) of presepsin (84.6%) were also superior to those seen in either PCT (79.6%) or CRP (71.8%). Thus plasma presepsin levels have comparable performance in SIRS for patients with nephrolithiasis.

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