Plasma cell-free RNA profiling distinguishes cancer from pre-malignant conditions
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE182824 | GEO | 2022/04/25
REPOSITORIES: GEO
Similar Datasets
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
Project description:Plasma cell-free RNA profiling distinguishes cancer from pre-malignant conditions
| PRJNA758012 | ENA
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. KaplanâMeier analysis with peritoneal relapse free survival showed a significant difference between âgood signature groupâ and âpoor signature groupâ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers. Of 141 samples, 56 represented the retrospective phase and 85 represented the prospective phase.
2010-05-23 | E-GEOD-15081 | biostudies-arrayexpress
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan–Meier analysis with peritoneal relapse free survival showed a significant difference between ‘good signature group’ and ‘poor signature group’ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers.
2009-03-04 | GSE15081 | GEO
Project description:There is an unmet clinical need for improved tissue and liquid biopsy tools for cancer detection. We investigated the proteomic profile of exosomes in 426 human samples from tissue explants (TE), plasma and other bodily fluids. Among traditional exosome markers, CD9, HSPA8, ALIX, HSP90AB1 represent pan-exosomes/exomeres. Moreover, we identified novel pan-exosome/exomere markers (e.g., ACTB, MSN, RAP1B). As proof of principle that exosomes are ideal diagnostic tools, we analyzed the proteome of TE exosomes (n=151) or plasma-derived exosomes (n=120). Comparison of TE exosomes identified proteins (e.g., VCAN, TNC, THBS2) that distinguish tumors from normal tissues with 90% sensitivity/94% specificity. Machinelearning classification of plasma-derived exosomes revealed 95% sensitivity/90% specificity in identifying cancer-associated exosomes. Finally, we defined a panel of tumor-type specific exosomal proteins in TE and plasma, which may help classify tumors of unknown primary origin. Overall, exosomal proteins can serve as reliable biomarkers for cancer detection and for determining cancer type
2020-08-17 | PXD018301 | Pride
Project description:BACKGROUND Autofluorescence bronchoscopy (AFB) is a valid strategy for detecting premalignant endobronchial lesions. However, no biomarker can reliably predict lung cancer risk of subjects with AFB-visualized premalignant lesions. Our present study was set out to identify AFB-visualized squamous metaplastic lesions with malignant potential by DNA copy number profiling. METHODS Regular AFB-examinations in 474 subjects at risk of lung cancer identified 6 subjects with SqM lesions at baseline and carcinoma (in situ) at the initial SqM site at follow-up bronchoscopy. These progressive SqM lesions were compared for immunostaining pattern and arrayCGH-based chromosomal profiles to 23 SqM of subjects who remained cancer-free. Specific copy number alterations (CNAs) linked to cancer risk were identified and accuracy of CNAs to predict endobronchial cancer in this series was determined. RESULTS At baseline, p53, p63 and Ki-67 immunostaining were not predictive for a differential clinical outcome of SqM lesions. The mean number of CNAs in baseline SqM of cases was significantly higher compared to controls (p<0.01). Chromosomal regions significantly more frequently altered in SqM of cases were 3p26.3-p11.1, 3q26.2-q29, 9p13.3-p13.2, and 17p13.3-p11.2 (FWER<0.10). CNAs were specifically detected at the site of future cancer. In cases, baseline-detected CNAs persisted in subsequent biopsies taken from the initial site, and levels increased towards cancer progression. CNAs at 3p26.3-p11.1, 3q26.2-29, and 6p25.3-24.3, predicted cancer risk for AFB-visualized SqM with 97% accuracy. CONCLUSION Our data strongly suggest that the presence of specific DNA copy number alterations in endobronchial SqM lesions predict endobronchial cancer.
2011-08-02 | GSE23644 | GEO
Project description:Using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq), we analyzed methylation profiles in 93 plasma samples from 77 pediatric brain tumor patients and 16 non-neoplastic patients. Binomial GLMnet classifiers of tumor and tumor subtypes were built in training sets, and performance was evaluated in test sets. The methylation profiles from plasma cfMeDIP-seq discriminated tumor from non-tumor patients with 0.83 accuracy (precision = 0.93, sensitivity = 0.86, and specificity = 0.67). Among major tumor subtypes vs. nontumors, circumscribed astrocytic glioma showed an accuracy of 0.86 (precision = 0.88, sensitivity = 0.88, and specificity = 0.83), and glioneuronal tumors had an accuracy of 0.83 (precision, sensitivity, and specificity = 0.83). Circumscribed astrocytic glioma and glioneuronal tumors could be discriminated from other tumor subtypes with 0.79 and 0.82 accuracy, respectively.
2024-09-30 | GSE275598 | GEO
Project description:Identifying biomarkers predictive for early esophageal cancer detection is critical considering the dismal survival rates. We investigated the involvement of microRNAs (miRNAs), their utility as biomarkers, and their association with survival in esophageal cancer, including Barrett’s associated and sporadic adenocarcinoma (ADC), and squamous cell carcinoma (SCC). MiRNA expression was measured in cancerous and adjacent non-cancerous tissue pairs collected from 76 US and Japanese patients enrolled in 3 distinct cohorts. In ADC patients, miR-21, miR-194, miR-293, and miR-223 expression was elevated, while miR-375 and miR-203 expression was reduced in cancerous tissue compared to non-cancerous tissue. Increased levels of miR-192 and miR-194 were observed in Barrett’s associated compared to sporadic ADC cancerous tissue. In SCC patients, miR-21, miR-181b, miR-155, and miR-146b expression was elevated while miR-375 and miR-203 levels were reduced in cancerous tissue compared to non-cancerous tissue. Significantly, elevated mir-21 expression in non-cancerous tissue was strongly associated with worse prognosis, independent of nodal status and age. Sample classification using miRNA expression yielded accuracies as high as 86% for diagnosis and 78% for Barrett’s esophagus status. Our results highlight that miRNAs are deregulated in esophageal carcinogenesis and Barrett’s esophagus, and that their expression is associated with survival in cancer patients. Sample classification using miRNA expression demonstrates their potential utility as biomarkers for esophageal carcinoma diagnosis. MiRNA microarray expression was measured using miRNA microarray chips version 3 (Ohio State University) in 44 SCC cases and 32 ADC cases, of which 18 were also diagnosed with Barrett’s esophagus.
2010-07-09 | E-GEOD-13937 | biostudies-arrayexpress
Project description:To characterize epigenomic changes during the transformation of normal plasma cells to myeloma, we used the HELP assay to analyze the methylome of CD138+ cells from 56 subjects representing premalignant (MGUS), early and advanced stages of myeloma as well as healthy controls. Plasma cells from premalignant and early stages of myeloma were characterized by striking, widespread hypomethylation.
2013-04-03 | GSE43860 | GEO