Dataset Information

Circulating and local nuclear expression of survivin and fibulin-3 genes in discriminating benign from malignant respiratory diseases: correlation analysis.

ABSTRACT: Survivin is an inhibitor of apoptosis as well as a promoter of cell proliferation. Fibulin-3 is a matrix glycoprotein that displays potential for tumor suppression or propagation. The present study aimed to validate the expression levels of survivin and fibulin-3 in benign and malignant respiratory diseases. This case-control study included 219 patients categorized into five groups. Group A included 63 patients with lung cancer, group B included 63 patients with various benign lung diseases, group D included 45 patients with malignant pleural mesothelioma (MPM), and group E included 48 patients with various benign pleural diseases. Group C included 60 healthy individuals (control group). Serum survivin and fibulin-3 levels were measured by ELISA, whereas their nuclear expressions in the lung and pleura were assessed via Western blot analysis. The results showed significantly higher survivin serum levels and significantly lower fibulin-3 levels in group A compared with in group B and controls (P<0.001). There were significantly higher serum levels of survivin and fibulin-3 in group D compared with in group E and controls (P<0.001), consistent with observed nuclear survivin and fibulin-3 expression levels. Fibulin-3 was determined to have higher value than survivin in discriminating lung cancer from MPM (P<0.05). Survivin and fibulin-3 could be useful diagnostic markers for lung and pleural cancers, and fibulin-3 expression was particularly useful in differentiating lung cancer from MPM.

SUBMITTER: Hassan MH

PROVIDER: S-EPMC7789905 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Circulating and local nuclear expression of survivin and fibulin-3 genes in discriminating benign from malignant respiratory diseases: correlation analysis.

Hassan Mohammed H MH Abuhamdah Sawsan S Abdel-Bary Mohamed M Wahman Mohammed M Abd-Elhamid Tarek Hamdy TH Beshay Morris M Mosallam Karam K Elsadek Bakheet E M BEM

Bioscience reports 20210101 1

Survivin is an inhibitor of apoptosis as well as a promoter of cell proliferation. Fibulin-3 is a matrix glycoprotein that displays potential for tumor suppression or propagation. The present study aimed to validate the expression levels of survivin and fibulin-3 in benign and malignant respiratory diseases. This case-control study included 219 patients categorized into five groups. Group A included 63 patients with lung cancer, group B included 63 patients with various benign lung diseases, gro ...[more]

PMID: 33226065

Similar Datasets

Project description:ObjectivesThe use of magnetic resonance (MR) imaging in differentiation between benign and malignant adnexal masses in children and adolescents might be of great value in the diagnostic workup of sonographically indeterminate masses, since preserving fertility is of particular importance in this population. This systematic review evaluates the diagnostic value of MR imaging in children with an ovarian mass.MethodsThe review was made according to the PRISMA Statement. PubMed and EMBASE were systematically searched for studies on the use of MR imaging in differential diagnosis of ovarian masses in both adult women and children from 2008 to 2018.ResultsSixteen paediatric and 18 adult studies were included. In the included studies, MR imaging has shown good diagnostic performance in differentiating between benign and malignant ovarian masses. MR imaging techniques including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging seem to further improve the diagnostic performance.ConclusionThe addition of DWI with apparent diffusion coefficient (ADC) values measured in enhancing components of solid lesions and DCE imaging may further increase the good diagnostic performance of MR imaging in the pre-operative differentiation between benign and malignant ovarian masses by increasing specificity. Prospective age-specific studies are needed to confirm the high diagnostic performance of MR imaging in children and adolescents with a sonographically indeterminate ovarian mass.Key points• MR imaging, based on several morphological features, is of good diagnostic performance in differentiating between benign and malignant ovarian masses. Sensitivity and specificity varied between 84.8 to 100% and 20.0 to 98.4%, respectively. • MR imaging techniques like diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) imaging seem to improve the diagnostic performance. • Specific studies in children and adolescents with ovarian masses are required to confirm the suggested increased diagnostic performance of DWI and DCE in this population.

Project description:ObjectivesTo develop and test the performance of computerized ultrasound image analysis using deep neural networks (DNNs) in discriminating between benign and malignant ovarian tumors and to compare its diagnostic accuracy with that of subjective assessment (SA) by an ultrasound expert.MethodsWe included 3077 (grayscale, n = 1927; power Doppler, n = 1150) ultrasound images from 758 women with ovarian tumors, who were classified prospectively by expert ultrasound examiners according to IOTA (International Ovarian Tumor Analysis) terms and definitions. Histological outcome from surgery (n = 634) or long-term (≥ 3 years) follow-up (n = 124) served as the gold standard. The dataset was split into a training set (n = 508; 314 benign and 194 malignant), a validation set (n = 100; 60 benign and 40 malignant) and a test set (n = 150; 75 benign and 75 malignant). We used transfer learning on three pre-trained DNNs: VGG16, ResNet50 and MobileNet. Each model was trained, and the outputs calibrated, using temperature scaling. An ensemble of the three models was then used to estimate the probability of malignancy based on all images from a given case. The DNN ensemble classified the tumors as benign or malignant (Ovry-Dx1 model); or as benign, inconclusive or malignant (Ovry-Dx2 model). The diagnostic performance of the DNN models, in terms of sensitivity and specificity, was compared to that of SA for classifying ovarian tumors in the test set.ResultsAt a sensitivity of 96.0%, Ovry-Dx1 had a specificity similar to that of SA (86.7% vs 88.0%; P = 1.0). Ovry-Dx2 had a sensitivity of 97.1% and a specificity of 93.7%, when designating 12.7% of the lesions as inconclusive. By complimenting Ovry-Dx2 with SA in inconclusive cases, the overall sensitivity (96.0%) and specificity (89.3%) were not significantly different from using SA in all cases (P = 1.0).ConclusionUltrasound image analysis using DNNs can predict ovarian malignancy with a diagnostic accuracy comparable to that of human expert examiners, indicating that these models may have a role in the triage of women with an ovarian tumor. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Dataset Information

Circulating and local nuclear expression of survivin and fibulin-3 genes in discriminating benign from malignant respiratory diseases: correlation analysis.

Publications

Circulating and local nuclear expression of survivin and fibulin-3 genes in discriminating benign from malignant respiratory diseases: correlation analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets