scholarly journals Integrated genomic and DNA methylation analysis of patients with advanced non-small cell lung cancer with brain metastases

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Yanjun Xu ◽  
Zhiyu Huang ◽  
Xiaoqing Yu ◽  
Kaiyan Chen ◽  
Yun Fan
Keyword(s):  
Dna Methylation ◽  
Brain Metastasis ◽  
Advanced Nsclc ◽  
Lung Tumor ◽  
Small Cell Lung ◽  
Methylation Analysis ◽  
Cns Metastasis ◽  
Tumor Tissues ◽  
Primary Lung Tumor ◽  
Dna Methylation Analysis

Abstract Background Brain metastasis is a common and lethal complication of non-small cell lung cancer (NSCLC). It is mostly diagnosed only after symptoms develop, at which point very few treatment options are available. Therefore, patients who have an increased risk of developing brain metastasis need to be identified early. Our study aimed to identify genomic and epigenomic biomarkers for predicting brain metastasis risk in NSCLC patients. Methods Paired primary lung tumor tissues and either brain metastatic tissues or cerebrospinal fluid (CSF) samples were collected from 29 patients with treatment-naïve advanced NSCLC with central nervous system (CNS) metastases. A control group comprising 31 patients with advanced NSCLC who died without ever developing CNS metastasis was also included. Somatic mutations and DNA methylation levels were examined through capture-based targeted sequencing with a 520-gene panel and targeted bisulfite sequencing with an 80,672 CpG panel. Results Compared to primary lung lesions, brain metastatic tissues harbored numerous unique copy number variations. The tumor mutational burden was comparable between brain metastatic tissue (P = 0.168)/CSF (P = 0.445) and their paired primary lung tumor samples. Kelch-like ECH-associated protein (KEAP1) mutations were detected in primary lung tumor and brain metastatic tissue samples of patients with brain metastasis. KEAP1 mutation rate was significantly higher in patients with brain metastasis than those without (P = 0.031). DNA methylation analysis revealed 15 differentially methylated blocks between primary lung tumors of patients with and without CNS metastasis. A brain metastasis risk prediction model based on these 15 differentially methylated blocks had an area under the curve of 0.94, with 87.1% sensitivity and 82.8% specificity. Conclusions Our analyses revealed 15 differentially methylated blocks in primary lung tumor tissues, which can differentiate patients with and without CNS metastasis. These differentially methylated blocks may serve as predictive biomarkers for the risk of developing CNS metastasis in NSCLC. Additional larger studies are needed to validate the predictive value of these markers.

scholarly journals Epigenome-wide DNA methylation analysis of small cell lung cancer cell lines suggests potential chemotherapy targets

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Julia Krushkal ◽  
Thomas Silvers ◽  
William C. Reinhold ◽  
Dmitriy Sonkin ◽  
Suleyman Vural ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Dna Methylation ◽  
Small Cell Lung Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Small Cell ◽  
Lung Cancer Cell ◽  
Small Cell Lung ◽  
Methylation Analysis ◽  
Dna Methylation Analysis

scholarly journals Genomewide DNA Methylation Analysis Identifies Novel Methylated Genes in Non–Small-Cell Lung Carcinomas

2013 ◽  
Vol 8 (5) ◽  
pp. 562-573 ◽  
Author(s):  
Rejane Hughes Carvalho ◽  
Jun Hou ◽  
Vanja Haberle ◽  
Joachim Aerts ◽  
Frank Grosveld ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Small Cell ◽  
Small Cell Lung ◽  
Methylation Analysis ◽  
Lung Carcinomas ◽  
Dna Methylation Analysis

196 Checkpoint blockade therapy for brain-metastatic non-small cell lung cancer: a comparative effectiveness analysis of national data

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A211-A211
Author(s):  
Nayan Lamba ◽  
Bryan Iorgulescu
Keyword(s):  
Brain Metastasis ◽  
Brain Metastases ◽  
Advanced Nsclc ◽  
Small Cell ◽  
Second Line ◽  
Newly Diagnosed ◽  
Small Cell Lung ◽  
Survival Analyses ◽  
Stage 4 ◽  
Insured Patients

BackgroundManagement of advanced non-small cell lung carcinoma (NSCLC) has been transformed by PD-1/PD-L1 immune checkpoint inhibitors (ICI), with FDA approvals in 2015 (second-line) and 2016 (first-line). Despite ~40% of NSCLC patients developing brain metastases, these patients were disproportionately excluded from the pioneering ICI trials. Thus herein we evaluate the overall survival (OS) associated with ICI in NSCLC brain metastases nationally.MethodsPatients newly-diagnosed with stage 4 NSCLC, including brain metastases, from 2010–2016 were identified from the National Cancer Database (comprising >70% of all newly-diagnosed cancers in the U.S.) Landmark survival analysis was used to address immortal time bias. Post-approval, median time from diagnosis to ICI was 58 days, and this timepoint was selected for all landmark survival analyses (OS estimated by Kaplan-Meier technique, and compared by logrank test and multivariable Cox regression) and for multivariable logistic regression to identify predictors of ICI utilization.Results50,858 patients presented with advanced NSCLC that involved the brain: representing 27.6% of all newly-diagnosed stage 4 cases. Following initial FDA approvals in 2015, ICI use in brain metastasis patients rose from 7.2% in 2015 to 12.7% in 2016. OS for NSCLC brain metastasis patients diagnosed post-approval (i.e. 2015, median 6.3 months, 95% [confidence interval] CI: 6.0–6.6) was substantially better than those diagnosed pre-approval (median 5.5 months, 95%CI: 5.4–5.7, p<0.001) and, in fact, than those diagnosed in 2014 (median 5.9 months, 95%CI: 5.6–6.1, p=0.002). Among patients diagnosed post-approval (in 2015, n=7,431), ICI receipt demonstrated substantially improved OS in landmark survival analyses (median 13.8 months, 95%CI: 12.2–15.1; vs. 8.5 months, 95%CI: 8.3–8.9, p<0.001) – benefits which persisted in multivariable landmark survival analyses (hazard ratio [HR] 0.83, 95%CI: 0.71–0.96, p=0.02), independent of patient characteristics, other therapies, and extracranial disease. For patients diagnosed post-approval, who reached the landmark timepoint, ICI receipt was independent of patient demographics, socioeconomic status, and hospital type—with the exception of Medicaid-insured patients, who were less likely than privately insured patients to receive ICI (OR 0.77, 95%CI: 0.60–0.97, p=0.03).ConclusionsNationally, the use of ICI for NSCLC brain metastasis patients is increasing, generally without significant socioeconomic barriers. Brain metastasis patients diagnosed in the post-approval second-line ICI era (2015) demonstrated significantly better OS than patients diagnosed pre-approval and even than patients diagnosed only in 2014. ICI was associated with a >60% relative increase in median OS. Together our findings from a real-world population demonstrate that the dramatic OS benefits of ICIs for advanced NSCLC also extended to brain metastasis patients.

scholarly journals P46.03 DNA Methylation Analysis in Smokers and Non-Smokers (Passive and ex-Smokers)

2021 ◽  
Vol 16 (3) ◽  
pp. S490
Author(s):  
D.M. Aguilar-Beltrán ◽  
A.G. Alcázar-Ramos ◽  
A.L. Vega-Rodríguez ◽  
D.G. García-Gutiérrez ◽  
A.D. Bertadillo-Jilote ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Methylation Analysis ◽  
Dna Methylation Analysis

scholarly journals DNA Methylation in Solid Tumors: Functions and Methods of Detection

2021 ◽  
Vol 22 (8) ◽  
pp. 4247
Author(s):  
Andrea Martisova ◽  
Jitka Holcakova ◽  
Nasim Izadi ◽  
Ravery Sebuyoya ◽  
Roman Hrstka ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Solid Tumors ◽  
Epigenetic Modification ◽  
Single Gene ◽  
Restriction Enzymes ◽  
Methylation Analysis ◽  
Cpg Dinucleotides ◽  
Sequencing Technologies ◽  
Genome Level ◽  
Dna Methylation Analysis

DNA methylation, i.e., addition of methyl group to 5′-carbon of cytosine residues in CpG dinucleotides, is an important epigenetic modification regulating gene expression, and thus implied in many cellular processes. Deregulation of DNA methylation is strongly associated with onset of various diseases, including cancer. Here, we review how DNA methylation affects carcinogenesis process and give examples of solid tumors where aberrant DNA methylation is often present. We explain principles of methods developed for DNA methylation analysis at both single gene and whole genome level, based on (i) sodium bisulfite conversion, (ii) methylation-sensitive restriction enzymes, and (iii) interactions of 5-methylcytosine (5mC) with methyl-binding proteins or antibodies against 5mC. In addition to standard methods, we describe recent advances in next generation sequencing technologies applied to DNA methylation analysis, as well as in development of biosensors that represent their cheaper and faster alternatives. Most importantly, we highlight not only advantages, but also disadvantages and challenges of each method.

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