Whole blood gene expression can distinguish benign from malignant lung nodules transitioning from microarrays to a nanostring platform
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ABSTRACT:
PROVIDER: PRJNA423293 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Development of a non-invasive, whole blood microarray gene expression signature that accurately distinguishes malignant from benign lung nodules detected by LDCT and the successful transition of that signature to a custom NanoString panel with no loss of accuracy.
2018-12-20 | GSE108375 | GEO
Project description:A serum miRNA combination could be a favourable classifier to differentiate malignant pulmonary nodules from benign pulmonary nodules.
2023-08-27 | GSE157074 | GEO
Project description:BACKGROUND: Following fine needle aspiration, 15-30% of thyroid nodules are not clearly benign or malignant. These cytologically indeterminate nodules are often referred for diagnostic surgery, though most prove benign. A novel diagnostic test measuring the expression of 167 genes has shown promise in improving pre-operative risk assessment. We evaluated this test in a prospective, multicenter study. METHODS: Over 19 months, we performed a prospective study at 49 clinical sites enrolling 3,789 patients and collecting 4,812 samples from thyroid nodules >1cm requiring evaluation. We obtained 577 cytologically indeterminate aspirates with corresponding histopathology of excised lesions on 413. Central blinded histopathologic review served as the reference (“gold”) standard. After applying inclusion criteria, gene expression classifier results were obtained for 265 indeterminate nodules used in this analysis, and performance was calculated. RESULTS: 85 of 265 indeterminate nodules were malignant. The gene expression classifier correctly identified 78 of 85 as ‘suspicious’ (92% sensitivity, [84%-97%] 95% CI). Specificity was 52%, [44%-59%]. The negative predictive value was 95%, 94%, and 85%, respectively, for aspirates with AUS/FLUS, FN/SFN, or ‘suspicious’ cytology. Analysis of 7 false negative cases revealed 6 with a paucity of thyroid follicular cells, suggesting that insufficient sampling of the nodule had occurred. CONCLUSIONS: Though individualized clinical care is recommended, these data support consideration of a conservative approach for most patients with indeterminate FNA cytology and benign gene expression classifier results.
2012-06-25 | GSE34289 | GEO
Project description:BACKGROUND: Following fine needle aspiration, 15-30% of thyroid nodules are not clearly benign or malignant. These cytologically indeterminate nodules are often referred for diagnostic surgery, though most prove benign. A novel diagnostic test measuring the expression of 167 genes has shown promise in improving pre-operative risk assessment. We evaluated this test in a prospective, multicenter study. METHODS: Over 19 months, we performed a prospective study at 49 clinical sites enrolling 3,789 patients and collecting 4,812 samples from thyroid nodules >1cm requiring evaluation. We obtained 577 cytologically indeterminate aspirates with corresponding histopathology of excised lesions on 413. Central blinded histopathologic review served as the reference (“gold”) standard. After applying inclusion criteria, gene expression classifier results were obtained for 265 indeterminate nodules used in this analysis, and performance was calculated. RESULTS: 85 of 265 indeterminate nodules were malignant. The gene expression classifier correctly identified 78 of 85 as ‘suspicious’ (92% sensitivity, [84%-97%] 95% CI). Specificity was 52%, [44%-59%]. The negative predictive value was 95%, 94%, and 85%, respectively, for aspirates with AUS/FLUS, FN/SFN, or ‘suspicious’ cytology. Analysis of 7 false negative cases revealed 6 with a paucity of thyroid follicular cells, suggesting that insufficient sampling of the nodule had occurred. CONCLUSIONS: Though individualized clinical care is recommended, these data support consideration of a conservative approach for most patients with indeterminate FNA cytology and benign gene expression classifier results. 265 cytologically indetermine samples, 47 cytologically benign and 55 cytologically malignant samples
2012-06-24 | E-GEOD-34289 | biostudies-arrayexpress
Project description:Background: Fine needle aspiration biopsy (FNAB) is the gold-standard procedure for diagnosing malignant thyroid nodules. Indeterminate cytology is identified in 10-40% of cases and molecular testing may guide management in this setting. Current commercial options are expensive, and are either sensitive or specific. The aim of this study was to utilize next generation sequencing (NGS) technology to identify informative diversities in the microRNA (miRNA) expression profile of benign versus malignant thyroid nodules. Methods: Ex-vivo FNAB samples were obtained from thyroid specimens of patients that underwent thyroidectomy at a referral center. miRNA levels were determined using NGS and multiplexing technologies. Statistical analyses identified differences between normal and malignant samples and miRNA expression profiles that associate with malignancy were established. The accuracy of the miRNA signature in predicting histological malignancy was validated using a group of patient specimens with indeterminate cytology results. Results: 274 samples were obtained from 102 patients undergoing thyroidectomy. Of these samples, 71% were benign and 29% were malignant. Nineteen miRNAs were identified as statistically different between benign and malignant samples and were used to classify 35 additional nodules with indeterminate cytology (validation). The miRNA panel’s sensitivity, specificity, negative and positive predictive values and overall accuracy were 91%, 100%, 87%, 100% and 94%, respectively. Conclusion: Using NGS technology we identified a panel of 19 miRNAs that may be utilized to distinguish benign from malignant thyroid nodules with indeterminate cytology. Impact: Our panel may classify indeterminate thyroid nodules at higher accuracy than commercially available molecular tests.
2018-12-21 | GSE116196 | GEO
Project description:We identified candidate protein biomarkers to distinguish lung adenocarcinomas from benign nodules. We employed shotgun proteomics using a multidimensional peptide separation approach coupled to tandem mass spectrometry (LC-MS/MS) to characterize proteomes of a collection of 34 benign lung nodules. The benign lung nodule inventories were compared to inventories from early stage lung adenocarcinomas, from 24 patients with non-adjuvant treatment following the resection, and to inventories from normal tissue collected from 10 patients as bronchial and alveolar epithelium to identify biomarkers.We developed PRM assays to quantify a subset of 43 candidate biomarker proteins via 170 tryptic peptides in a single LC-PRM-MS run using a validation cohort of 20 benign nodules, 20 adenocarcinoma, and 20 normal lung tissues.
2016-10-09 | MSV000080236 | MassIVE
Project description:<p><strong>BACKGROUND:</strong> Novel biomarkers are urgently needed to distinguish between benign and malignant thyroid nodules and detect thyroid cancer in the early stage. The associations between serum IgG N-glycosylation and thyroid cancer risk have been revealed. We aimed to explore the potential of IgG N-glycan traits as biomarkers in the differential diagnosis of thyroid cancer.</p><p><strong>METHODS:</strong> Plasma IgG N-glycome analysis was applied to a discovery cohort followed by independent validation. IgG N-glycan profiles were obtained using a robust quantitative strategy based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. IgG N-glycans were relatively quantified, and classification performance was evaluated based on directly detected and derived glycan traits.</p><p><strong>RESULTS: </strong>Four directly detected glycans were significantly changed in thyroid cancer patients compared to that in non-cancer controls. Derived glycan traits and a classification glycol-panel were generated based on the directly detected glycan traits. In the discovery cohort, derived trait BN (bisecting type neutral N-glycans) and the glyco-panel showed potential in distinguishing between thyroid cancer and non-cancer controls with AUCs of 0.920 and 0.917, respectively. The diagnostic potential was further validated. Derived trait BN and the glycol-panel displayed “accurate” performance (AUC>0.8) in discriminating thyroid cancer from benign thyroid nodules and healthy controls in the validation cohort. Meanwhile, derived trait BN and the glycol-panel also showed diagnostic potential in detecting early-stage thyroid cancer.</p><p><strong>CONCLUSIONS:</strong> IgG N-glycome analysis revealed N-glycomic differences that allow classification of thyroid cancer from non-cancer controls. Our results suggested that derived trait BN and the classification glyco-panel rather than single N-glycans may serve as candidate biomarkers for further validation.</p>
2021-09-01 | MTBLS2935 | MetaboLights
Project description:Genetic and methylation profiles distinguish benign, malignant and spitzoid melanocytic tumors
| EGAS00001006205 | EGA
Project description:Given the pressing clinical problem of making decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPN), then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis, twelve differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of the DEPs were validated in two independent validation cohorts. The results showed that the level of three candidate proteins (PRDX2, PON1, APOC3) were lower in the plasma of LUAD than BPN. The three candidate proteins were combined with three promising computed tomography (CT) indicators (Spiculation, Vascular Notch Sign, Lobulation) and three traditional markers (CEA, CA125, CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with AUC of 0.904, sensitivity of 81.44% and specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity and accuracy of 0.868, 65.63%, 90.14% and 82.52%, respectively. This model maybe a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity.
2024-01-26 | PXD046731 | Pride
Project description:We hypothesized that distinct protein expression features of benign and malignant pulmonary nodules may reveal novel candidate biomarkers for the early detection of lung cancer. We performed proteome profiling by liquid chromatography-tandem mass spectrometry to characterize 34 resected benign lung nodules, 24 untreated lung adenocarcinomas (ADCs), and biopsies of bronchial epithelium. Group comparisons identified 65 proteins that differentiate nodules from ADCs and normal bronchial epithelium and 66 proteins that differentiate ADCs from nodules and normal bronchial epithelium. We developed a multiplexed parallel reaction monitoring (PRM) assay to quantify a subset of 43 of these candidate biomarkers in an independent cohort of 20 benign nodules, 21 ADCs, and 20 normal bronchial biopsies. PRM analyses confirmed significant nodule-specific abundance of 10 proteins including ALOX5, ALOX5AP, CCL19, CILP1, COL5A2, ITGB2, ITGAX, PTPRE, S100A12, and SLC2A3 and significant ADC-specific abundance of CEACAM6, CRABP2, LAD1, PLOD2, and TMEM110-MUSTN1. Immunohistochemistry analyses for seven selected proteins performed on an independent set of tissue microarrays confirmed nodule-specific expression of ALOX5, ALOX5AP, ITGAX, and SLC2A3 and cancer-specific expression of CEACAM6. These studies illustrate the value of global and targeted proteomics in a systematic process to identify and qualify candidate biomarkers for noninvasive molecular diagnosis of lung cancer.
| S-EPMC6339813 | biostudies-literature