Copy Number Variation in Tumor Cells and Extracellular DNA in Patients with Lung Adenocarcinoma

Кутилин, Денис С.; Айрапетова, Т Г; Anistratov, Pavel A.; Pyltsin, Sergey P.; Leyman, Igor A.; Karnaukhov, Nikolay S.; Kit, Oleg I.

doi:10.1007/s10517-019-04620-y

Cited by 19 publications

(6 citation statements)

References 8 publications

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“…Our finding showed that CASP8 was downregulated in tumor tissues and suggested its negative association with the occurrence of LUAD. Our finding is not in conformity with that in a study undertaken by Kutilin et al, [ 22 ] who found that the proportion of gene copy numbers for CASP8 was not significantly different between tumor cells and normal lung cells. In this study, we identified CASP8 as an independent risk factor for overall mortality in LUAD patients, which is in concordance with Liu et al’s conclusion.…”

Section: Discussioncontrasting

confidence: 99%

Establishment of a prognostic signature for lung adenocarcinoma by integration of 7 pyroptosis-related genes and cross-validation between the TCGA and GEO cohorts: A comprehensive bioinformatics analysis

Zhang

Wan

et al. 2022

Medicine

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Pyroptosis-related genes (PRGs) have been reported to be associated with prognosis of lung adenocarcinoma (LUAD). Until now, the relationship of PRGs to the prognosis of LUAD patients and its underlying mechanisms have been poorly elucidated. Using The Cancer Genome Atlas (TCGA) LUAD cohort, a prior bioinformatics analysis constructed a prognostic signature incorporating 5 PRGs (NLRP7, NLRP1, NLRP2, NOD1, and CASP6) for predicting prognosis of LUAD patients. However, it has not been validated by the Gene Expression Omnibus (GEO) LUAD cohort yet. We implemented a modified bioinformatics analysis to, respectively, construct one prognostic signature with the TCGA cohort and with the GEO cohort and attempted to perform cross-validations by the GEO cohort and the TCGA cohort alternately in turn. Univariate and multivariate Cox regression analysis screened PRGs and constructed 2 prognostic signatures with the TCGA and GEO cohorts. All LUAD samples were classified into high- and low-risk groups according to the median risk score that was generated by regression formula. Kaplan-Meier survival analysis compared the overall survival rate between the 2 risk groups, and receiver operating characteristic curve analysis evaluated predictive performance of the 2 signatures. Additionally, risk score, combined with clinicopathological features, was subjected to multivariate Cox regression analysis, to evaluate independent prognostic value of the 2 signatures. Finally, the 2 signatures received cross-validations by the GEO and TCGA cohorts, alternately. The TCGA cohort yielded a 3-gene signature (PYCARD, NLRP1, and NLRC4), whereas the GEO cohort built a 7-gene signature (SCAF11, NOD1, NLRP2, NLRP1, GPX4, CASP8, and AIM2) for predicting the prognosis of LUAD patients. Multivariate analysis proved independent prognostic value of risk score in the TCGA cohort (hazard ratio, = 1.939,; P = 8.43 × 10−4) and the GEO cohort (hazard ratio, = 2.291,; P = 4.34 × 10−9). Cross-validations confirmed prognostic value for the 7-gene signature from the GEO cohort by the TCGA cohort but not for the 3-gene signature from the TCGA cohort by the GEO cohort. We develop and validate a 7-gene prognostic signature (SCAF11, NOD1, NLRP2, NLRP1, GPX4, CASP8, and AIM2) with independent prognostic value for patients with LUAD.

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Section: Discussioncontrasting

confidence: 99%

Establishment of a prognostic signature for lung adenocarcinoma by integration of 7 pyroptosis-related genes and cross-validation between the TCGA and GEO cohorts: A comprehensive bioinformatics analysis

Zhang

Wan

et al. 2022

Medicine

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“…In addition, the study demonstrated the potential clinical utility of urine cfDNAs in predicting treatment response and monitoring disease progression. Kutilin et al analyzed CNVs for 30 genes in patients with lung cancer [156]. CNVs were detected for genes responsible for apoptosis regulation (BAX, P53, and CASP3), proliferation (SOX2), DNA reparation (XRCC1), oxidative phosphorylation (HV2), EGFR signaling pathway (GRB2, SOS1, MAPK1, STAT1, and BRAF), and for mir3678.…”

Section: Copy-number Variations (Cnvs)mentioning

confidence: 99%

Properties and Application of Cell-Free DNA as a Clinical Biomarker

Miranda

Baraúna

Santos

et al. 2021

IJMS

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Biomarkers are valuable tools in clinical practice. In 2001, the National Institutes of Health (NIH) standardized the definition of a biomarker as a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention. A biomarker has clinical relevance when it presents precision, standardization and reproducibility, suitability to the patient, straightforward interpretation by clinicians, and high sensitivity and/or specificity by the parameter it proposes to identify. Thus, serum biomarkers should have advantages related to the simplicity of the procedures and to the fact that venous blood collection is commonplace in clinical practice. We described the potentiality of cfDNA as a general clinical biomarker and focused on endothelial dysfunction. Circulating cell-free DNA (cfDNA) refers to extracellular DNA present in body fluid that may be derived from both normal and diseased cells. An increasing number of studies demonstrate the potential use of cfDNA as a noninvasive biomarker to determine physiologic and pathologic conditions. However, although still scarce, increasing evidence has been reported regarding using cfDNA in cardiovascular diseases. Here, we have reviewed the history of cfDNA, its source, molecular features, and release mechanism. We also show recent studies that have investigated cfDNA as a possible marker of endothelial damage in clinical settings. In the cardiovascular system, the studies are quite new, and although interesting, stronger evidence is still needed. However, some drawbacks in cfDNA methodologies should be overcome before its recommendation as a biomarker in the clinical setting.

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“…As regards SOX2 gene, SOX2 gene is the most important gene among all the SOX family of genes, due to its ability to reprogram somatic cells into induced pluripotent stem cells [ 16 ]. Kutilin D, et al found a significant increase in SOX2 CNV in 50% of lung tissue samples and it was 3.6 times higher in plasma samples compared to controls [ 25 ]. Another study demonstrated increase in the CNV of SOX2 gene by fluorescence in situ hybridization (FISH) using tissues resected from NSCLC patients.…”

Section: Discussionmentioning

confidence: 99%

HOXA9 gene promotor methylation and copy number variation of SOX2 and HV2 genes in cell free DNA: A potential diagnostic panel for non-small cell lung cancer

et al. 2023

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Background Most cases of lung cancer are diagnosed at advanced stage. Detection of genetic and epigenetic markers in cell-free DNA (cfDNA) is a promising tool for the diagnosis of lung cancer at an early stage. The aim of this study was to identify non-invasive diagnostic markers in cell free DNA (cfDNA) for non-small cell lung cancer (NSCLC) as it is the most common type of lung cancer. Methods We investigated the cfDNA HOXA9 gene promotor methylation by pyrosequencing. Copy number variation of SOX2 and HV2 genes were detected by real-time PCR in cfDNA extracted from plasma samples of 25 newly diagnosed NSCLC patients and 25 age and sex matched controls. Results Methylation level of HOXA9 was significantly higher in NSCLC patients than controls (p > 0.001). SOX2 showed significantly higher CNV and HV2 showed lower CNV in patients than controls (p > 0.001, p = 0.001 respectively). Receiver Operating Characteristic (ROC) curve analysis for HOXA9 methylation, SOX2 CNV and HV2 CNV showed a discrimination power of 79.4%, 80% and 77.5% respectively and the area under the curve for the combined analysis of the three genes was 0.958 with 88% sensitivity and 100% specificity. Conclusions In this study, we suggest a potentially diagnostic panel that may help in detection of lung cancer with high sensitivity and specificity using cell free DNA. This Panel included HOXA9 gene methylation and the CNV of SOX2 and HV2 genes.

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Copy Number Variation in Tumor Cells and Extracellular DNA in Patients with Lung Adenocarcinoma

Cited by 19 publications

References 8 publications

Establishment of a prognostic signature for lung adenocarcinoma by integration of 7 pyroptosis-related genes and cross-validation between the TCGA and GEO cohorts: A comprehensive bioinformatics analysis

Establishment of a prognostic signature for lung adenocarcinoma by integration of 7 pyroptosis-related genes and cross-validation between the TCGA and GEO cohorts: A comprehensive bioinformatics analysis

Properties and Application of Cell-Free DNA as a Clinical Biomarker

HOXA9 gene promotor methylation and copy number variation of SOX2 and HV2 genes in cell free DNA: A potential diagnostic panel for non-small cell lung cancer

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