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ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-27489GSE27554
PROVIDER: PRJNA141791 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:SCREENING STUDY TO IDENTIFY DIAGNOSTIC MARKERS FOR LUNG CANCER IN ENDOBRONCHIAL LINING FLUID
| PRJNA141751 | ENA
Project description:Screening study to identify diagnostic markers for lung cancer in endobronchial lining fluid
2015-08-17 | E-GEOD-27489 | ExpressionAtlas
Project description:We investigated whether biomarker analysis in endobronchial epithelial lining fluid (ELF) collected by bronchoscopic microsampling may be useful for a definitive preoperative diagnosis. Therefore we compared ELF samples close to nodule and from the contralateral site from patients with malignant or benign diagnosis.
2011-12-31 | GSE27553 | GEO
Project description:We investigated whether biomarker analysis in endobronchial epithelial lining fluid (ELF) collected by bronchoscopic microsampling may be useful for a definitive preoperative diagnosis. Therefore we compared ELF samples close to nodule and from the contralateral site from patients with malignant or benign diagnosis.
2011-12-31 | GSE27489 | GEO
Project description:We investigated whether biomarker analysis in endobronchial epithelial lining fluid (ELF) collected by bronchoscopic microsampling may be useful for a definitive preoperative diagnosis. Therefore we compared ELF samples close to nodule and from the contralateral site from patients with malignant or benign diagnosis. ELF samples have been derived from early stage NSCLC patients and controls. Wilcox Test was performed to identify differentially expressed genes associated to a malignant diagnosis. key words: disease subtype analysis
2011-12-31 | E-GEOD-27553 | biostudies-arrayexpress
Project description:We investigated whether biomarker analysis in endobronchial epithelial lining fluid (ELF) collected by bronchoscopic microsampling may be useful for a definitive preoperative diagnosis. Therefore we compared ELF samples close to nodule and from the contralateral site from patients with malignant or benign diagnosis. ELF samples have been derived from early stage NSCLC patients and controls. LIMMA analysis was performed to identify differentially expressed genes associated to a malignant diagnosis. keywords: disease subtype analysis
2011-12-31 | E-GEOD-27489 | biostudies-arrayexpress
Project description:Background: There is a paucity of non-invasive markers for early detection of brain metastasis (BM) in patients with non-small cell lung cancer (NSCLC). Secretory proteomic approach based on quantitative tandem mass tag is believed to offer bright prospects for screening potential serum biomarkers for diseases. Methods: We used the secretory proteomics to identify up-regulated proteins in the highly brain metastatic cell line compared to the parental lung cancer cell line. Enzyme linked immunoassay and immunohistochemistry were performed on non-small cell lung cancer patients with brain metastasis and control samples from each cohort to verify the expression levels of candidate proteins. A logistic regression model was used to develop a biomarker panel composed of Cathepsin F (CTSF) and Fibulin-1 (FBLN1), and then an independent validation data set was used for verification. The diagnostic accuracy was evaluated by receiver operating characteristic (ROC) curve analysis. Changes in serum CTSF levels of patients were tracked to monitor the effect of treatment, and progression-free survival (PFS) and overall survival (OS) were analyzed to assess their prognostic relevance. Results: CTSF and FBLN1 levels were specifically upregulated in sera and tissues of patients with NSCLC BM. Importantly, the combined diagnostic performance of CTSF and FBLN1 was superior to their individual diagnostic performance (sensitivity and specificity). CTSF serum changes were found to reflect the therapeutic response of patients with NSCLC BM and the trends of resistance and progression were detected earlier than the MRI changes. Elevated expression of CTSF in NSCLC BM tissues was associated with poor PFS. Moreover, CTSF tissue expression was found to be an independent prognostic factor. Conclusions: CTSF and FBLN1 are potential novel and specific serum markers for early diagnosis of BM in patients with NSCLC. CTSF can also be used as a biomarker for monitoring therapeutic efficacy and prognostic assessment.
2022-08-12 | PXD023721 | Pride
Project description:Individuals who present with premalignant endobronchial lesions are considered at high risk of lung cancer. Nonetheless, premalignant lesions behave erratically and only a minority progresses towards lung cancer. Therefore, biomarkers need to be discovered that can aid in assessing an individual’s risk for subsequent cancer to better tailor treatment choices and avoid unnecessary follow-up procedures. We recently proposed a classifier of DNA copy number alterations (CNAs) at 3p26.3-p11.1, 3q26.2-29, and 6p25.3-24.3 as risk predictor for endobronchial cancer. The current study was set out to validate the classifier among an independent series of premalignant endobronchial lesions with various histological grades. A series of 36 endobronchial premalignant lesions (8 squamous metaplasia, and 28 various grades of dysplasia) identified during autofluorescence bronchoscopy of 12 case subjects who had carcinoma in situ or carcinoma (≥CIS) during follow-up bronchoscopy at the initial site and 24 control subjects who remained cancer-free, was subjected to array Comparative Genomic Hybridization (arrayCGH). DNA copy number profiles were related to lesion outcome. Prediction accuracy of the previously defined molecular classifier to predict endobronchial cancer in this series was determined. Unsupervised hierarchical clustering analysis revealed a significant association between cluster assignment and lesion outcome (p< 0.001), independent of histological grade, with quiescent profiles in controls (24/24) and aberrant profiles in the majority of cases (9/12). Our pre-defined classifier demonstrated 92% accuracy for predicting cancer outcome in the current sample series. Our validated classifier holds great promise for stratification of patients with premalignant endobronchial lesions for risk of subsequent cancer. Fresh frozen specimens of 36 premalignant endobronchial biopsies. Test samples were compared to an external pool of normal male/female reference DNA.
2013-12-03 | E-GEOD-45287 | biostudies-arrayexpress
Project description:Individuals who present with premalignant endobronchial lesions are considered at high risk of lung cancer. Nonetheless, premalignant lesions behave erratically and only a minority progresses towards lung cancer. Therefore, biomarkers need to be discovered that can aid in assessing an individual’s risk for subsequent cancer to better tailor treatment choices and avoid unnecessary follow-up procedures. We recently proposed a classifier of DNA copy number alterations (CNAs) at 3p26.3-p11.1, 3q26.2-29, and 6p25.3-24.3 as risk predictor for endobronchial cancer. The current study was set out to validate the classifier among an independent series of premalignant endobronchial lesions with various histological grades. A series of 36 endobronchial premalignant lesions (8 squamous metaplasia, and 28 various grades of dysplasia) identified during autofluorescence bronchoscopy of 12 case subjects who had carcinoma in situ or carcinoma (≥CIS) during follow-up bronchoscopy at the initial site and 24 control subjects who remained cancer-free, was subjected to array Comparative Genomic Hybridization (arrayCGH). DNA copy number profiles were related to lesion outcome. Prediction accuracy of the previously defined molecular classifier to predict endobronchial cancer in this series was determined. Unsupervised hierarchical clustering analysis revealed a significant association between cluster assignment and lesion outcome (p< 0.001), independent of histological grade, with quiescent profiles in controls (24/24) and aberrant profiles in the majority of cases (9/12). Our pre-defined classifier demonstrated 92% accuracy for predicting cancer outcome in the current sample series. Our validated classifier holds great promise for stratification of patients with premalignant endobronchial lesions for risk of subsequent cancer.
2013-12-03 | GSE45287 | GEO