Dataset Information

Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA).

ABSTRACT: Rational: LDCT screening can identify early-stage lung cancers yet introduces excessive false positives and it remains a great challenge to differentiate malignant tumors from benign solitary pulmonary nodules, which calls for better non-invasive diagnostic tools. Methods: We performed DNA methylation profiling by high throughput DNA bisulfite sequencing in tissue samples (nodule size < 3 cm in diameter) to learn methylation patterns that differentiate cancerous tumors from benign lesions. Then we filtered out methylation patterns exhibiting high background in circulating tumor DNA (ctDNA) and built an assay for plasma sample classification. Results: We first performed methylation profiling of 230 tissue samples to learn cancer-specific methylation patterns which achieved a sensitivity of 92.7% (88.3% - 97.1%) and a specificity of 92.8% (89.3% - 96.3%). These tissue-derived DNA methylation markers were further filtered using a training set of 66 plasma samples and 9 markers were selected to build a diagnostic prediction model. From an independent validation set of additional 66 plasma samples, this model obtained a sensitivity of 79.5% (63.5% - 90.7%) and a specificity of 85.2% (66.3% - 95.8%) for differentiating patients with malignant tumor (n = 39) from patients with benign lesions (n = 27). Additionally, when tested on gender and age matched asymptomatic normal individuals (n = 118), our model achieved a specificity of 93.2% (89.0% - 98.3%). Specifically, our assay is highly sensitive towards early-stage lung cancer, with a sensitivity of 75.0% (55.0%-90.0%) in 20 stage Ia lung cancer patients and 85.7% (57.1%-100.0%) in 7 stage Ib lung cancer patients. Conclusions: We have developed a novel sensitive blood based non-invasive diagnostic assay for detecting early stage lung cancer as well as differentiating lung cancers from benign pulmonary nodules.

SUBMITTER: Liang W

PROVIDER: S-EPMC6485294 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA).

Liang Wenhua W Zhao Yue Y Huang Weizhe W Gao Yangbin Y Xu Weihong W Tao Jinsheng J Yang Meng M Li Lequn L Ping Wei W Shen Hui H Fu Xiangning X Chen Zhiwei Z Laird Peter W PW Cai Xuyu X Fan Jian-Bing JB He Jianxing J

Theranostics 20190406 7

<b>Rational:</b> LDCT screening can identify early-stage lung cancers yet introduces excessive false positives and it remains a great challenge to differentiate malignant tumors from benign solitary pulmonary nodules, which calls for better non-invasive diagnostic tools. <b>Methods:</b> We performed DNA methylation profiling by high throughput DNA bisulfite sequencing in tissue samples (nodule size < 3 cm in diameter) to learn methylation patterns that differentiate cancerous tumors from benign ...[more]

PMID: 31037156

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Project description:Background:Hepatocellular carcinoma (HCC) includes cryptogenic hepatocellular carcinomas (CR-HCC) that lack a defined cause. Specific DNA methylation patterns and comparisons of the aberrant alterations in DNA methylation between CR-HCC and adjacent peritumor tissues (APTs) have not yet been reported. Methods:The SureSelectXT Methyl-Seq Target Enrichment System was used to sequence targeted DNA methylation in three paired CR-HCC tissues and APTs. Gene Ontology (GO) enrichment and KEGG pathway analysis were performed to investigate the DNA methylation mechanism of CR-HCC. The mRNA expression levels of HOXB-AS3, HOXB6, HOXB3, USP18, MAP3K6, TIRAP, TNNI2, SHC3, CTTN, and TFAP2A, selected from the identified signaling pathways, were evaluated by quantitative real-time PCR (qPCR). Results:A total of 1728 differentially methylated regions (DMRs) were identified in tumor tissues compared with non-tumor tissues, of which 868 DMRs were hypermethylated and 860 were hypomethylated. The DMRs were mapped within 2091 DMR-associated genes (DMGs). The mRNA expression of HOXB-AS3, HOXB3, and MAP3K6 was downregulated in CR-HCC tissues compared to the APTs. However, the mRNA expression of TIRAP, SHC3, and CTTN was upregulated in the CR-HCC tissues. Differences between the mRNA expression of HOXB6, USP18, TNNI2, and TFAP2A in the CR-HCC and APTS tissues were not statistically significant. GO analysis showed that the molecular functions of "binding", "protein binding", and "cytoskeletal protein binding" were the main categories for the hypermethylated DMGs. The hypomethylated DMGs were mostly enriched in the molecular functions "binding", "protein binding", "calcium ion binding", among others. KEGG pathway analysis showed that the hypermethylated DMGs were enriched in several pathways such as "estrogen signaling pathway", while hypomethylated DMGs were enriched in several pathways such as "proteoglycans in cancer", suggesting that epigenetic modifications play important roles in the cryptogenic hepatocarcinogenesis. Conclusion:These results provide useful information for future work to characterize the functions of epigenetic mechanisms on CR-HCC.

Project description:Background: Safe and sensitive methods for glioblastoma diagnosis and disease monitoring are urgently needed. Exosomes are nano-sized extracellular vesicles that contain molecules characteristic of their cell-of-origin, including microRNA. Exosomes released by glioblastoma tumors cross the blood-brain-barrier ino the peripheral circulation. Methods: Serum exosomal-microRNA isolated from IDH-wildtype glioblastoma (n=12) and IDH-mutant glioma grades II-III (n=10) were analyzed using small-RNA next generation sequencing and compared to age- and gender-matched healthy controls. Differentially expressed miRNAs (|fold change|³2 and p-value ≤ 0.05 in three statistical tests, Fischer-exact, t-test, and Wilcoxon) were identified and the predictive power of individual and subsets of miRNAs were tested using univariate (logistic regression) and multivariate (Random Forest) analyses. Additional glioblastoma sera (n=4) and independent sets of healthy (n=9) and non-glioma (n=10) controls were used to further test the predictive power of our glioblastoma miRNA signature. Results: Twenty-six miRNAs were differentially expressed in glioblastoma relative to healthy controls. Seven miRNAs (miR-182-5p, miR-328-3p, miR-339-5p, miR-340-5p, miR-485-3p, miR-486-5p and miR-543) were the most stable for classifying glioblastoma, achieving a predictive power of 91.7%. Strikingly, the combined expressions of miR-182-5p, miR-328-3p miR-485-3p miR-486-5p distinguished glioblastoma patients from controls with perfect accuracy. This miRNA panel was able to correctly classify all specimens in validation cohorts (n=23). An analogous approach was used to identify 23 dysregulated miRNAs in IDH-mutant gliomas, including a distinct subset of stable miRNAs for classifying patients with lower-grade IDH-mutant gliomas. Conclusions: Our serum exosomal-miRNA signature can accurately diagnose glioblastoma preoperatively. These findings have significant scope to revolutionize glioblastoma tumor diagnosis and disease monitoring. IMPORTANCE OF STUDY: There is a real need for accurate biomarkers that can measure glioblastoma disease activity and treatment response in a safe and timely manner. This study demonstrates that exosome-associated microRNAs have exceptional utility as blood-based biomarkers in glioma patients. This work also shows the potential for exosomal microRNA profiles to be used for glioma subtyping, grading and determining mutational states. The development of specific, sensitive and non-invasive screening tests would have significant clinical benefit by reducing costs of treatment monitoring, improving accessibility and quality-of-life measures. Moreover, such tests have the potential to provide objectively measured surrogate endpoints to allow clinical trial protocols to be more dynamic and adaptive.

Dataset Information

Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA).

Publications

Non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA).

Similar Datasets

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