scholarly journals Diagnostic value of circulating tumor DNA in molecular characterization of glioma

Medicine ◽  
2020 ◽  
Vol 99 (33) ◽  
pp. e21196
Author(s):  
Yin Kang ◽  
Xiaohua Lin ◽  
Dezhi Kang
2018 ◽  
Vol 144 (1) ◽  
pp. 68-79 ◽  
Author(s):  
Irene Jiménez ◽  
Mathieu Chicard ◽  
Léo Colmet-Daage ◽  
Nathalie Clément ◽  
Adrien Danzon ◽  
...  

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2953-2953
Author(s):  
Nieves Garcia-Gisbert ◽  
Lierni Fernández-Ibarrondo ◽  
Concepción Fernández-Rodríguez ◽  
Laura Camacho ◽  
Anna Angona ◽  
...  

Introduction. Genetic studies in patients with Ph-negative myeloproliferative neoplasms (MPNs) are essential to establish a correct diagnosis and to optimize their management. Recently, it has been demonstrated that it is possible to detect molecular alterations present in solid tumors and hematologic neoplasms by the analysis of circulating tumor DNA in plasma samples, which is known as liquid biopsy. It has been reported that most of the circulating cell-free DNA (cfDNA) has its origin in immature hematopoietic and bone marrow cells; however, there is limited information about liquid biopsy applications in MPNs. Objective. To analyze the molecular profile of circulating tumor DNA in patients with MPNs. Patients and methods. Peripheral blood samples from 75 patients with MPNs were collected at the time of diagnosis: 21 polycythemia vera (PV), 42 essential thrombocythemia (ET), 10 primary myelofibrosis (PMF) and two non-classifiable MPNs. Cellular DNA was extracted from the granulocytic fraction isolated by density gradient centrifugation and cfDNA was obtained from 1-3ml of plasma (MagMAX Cell-Free DNA Isolation Kit, Thermo Fisher Scientific). cfDNA purity was ascertained by capillary electrophoresis (4200 TapeStation system, Agilent). Molecular characterization was performed in paired samples of granulocytes DNA and cfDNA by next generation sequencing (NGS). Libraries were prepared using a custom panel that covered the whole codifying region of 25 myeloid-associated genes (QIAseq Custom DNA Panels, Qiagen) and sequenced using Illumina technology (Miseq, Nextseq) with a 3000x minimum coverage. Results. The amount of total cfDNA/mL in plasma was significantly higher in PMF (mean 97 ng/ml) than in PV and ET (mean 18 and 23g/ml, respectively) (p = 0.003, Kruskal-Wallis). Overall, 144 mutations in driver (JAK2, CALR, MPL) and non-driver genes were detected in the granulocytic fraction with similar frequencies to what has been described for PV, ET and PMF. The most frequently mutated non-driver genes where ASXL1 (18.7%), TET2 (17.3%), DNMT3A (6.7%), SRSF2 (6.7%) and IDH2 (5.3%). Sequencing of cfDNA showed a total of 146 mutations. All mutations detected in the granulocytic fraction were also detected in the paired cfDNA sample (100% concordance); two additional mutations in MPL and ASXL1 were detected in plasma in one case. The median variant allele frequency (VAF) present in cfDNA was 29% (range 0.86 - 91.73%), which is far superior to what has been described in solid neoplasms or lymphomas (median 0.41%, range 0.03% - 97.6%). A strong correlation was observed between the VAFs of granulocytic DNA and cfDNA (r = 0.875, p < 0.001, Spearman) (Figure 1). The mutation VAFs detected in cfDNA were significantly higher than VAFs detected in granulocytes (p < 0.001, Wilcoxon). In particular, MPL mutations presented 2.5 higher VAF in cfDNA than in granulocytes (p = 0.018, Wilcoxon). This finding was confirmed and quantified by digital PCR. Interestingly, in one PMF patient the p.W515L MPL driver mutation was originally only detectable by NGS in cfDNA, but not in granulocytes. This mutation was identified by ultra-sensitive digital PCR in both cfDNA (VAF 2.30%) and granulocytes (VAF 0.16%). Conclusions. The analysis of circulating tumor DNA allows the characterization of the molecular abnormalities of patients with Ph negative myeloproliferative neoplasms. The sensitivity for mutation detection in driver and non-driver genes was equal or even superior to that obtained when studying the isolated granulocytic population. Disclosures Salar: Roche: Research Funding, Speakers Bureau; Janssen Pharmaceuticals: Consultancy, Speakers Bureau; Gilead: Consultancy, Speakers Bureau; Celgene: Consultancy. Besses:Gilead: Research Funding. Bellosillo:TermoFisher Scientific: Consultancy, Speakers Bureau; Qiagen: Consultancy, Speakers Bureau.


2019 ◽  
Author(s):  
Yulan Gu ◽  
Chuandan Wan ◽  
Jiaming Qiu ◽  
Yanhong Cui ◽  
Tingwang Jiang

AbstractThe applications of liquid biopsy have attracted much attention in biomedical research in recent years. Circulating cell-free DNA (cfDNA) in the serum may serve as a unique tumor marker in various types of cancer. Circulating tumor DNA (ctDNA) is a type of serum cfDNA found in patients with cancer and contains abundant information regarding tumor characteristics, highlighting its potential diagnostic value in the clinical setting. However, the diagnostic value of cfDNA as a biomarker in cervical cancer remains unclear. Here, we performed a meta-analysis to evaluate the applications of ctDNA as a biomarker in cervical cancer. A systematic literature search was performed using PubMed, Embase, and WANFANG MED ONLINE databases up to March 18, 2019. All literature was analyzed using Meta Disc 1.4 and STATA 14.0 software. Diagnostic measures of accuracy of ctDNA in cervical cancer were pooled and investigated. Fifteen studies comprising 1109 patients with cervical cancer met our inclusion criteria and were subjected to analysis. The pooled sensitivity and specificity were 0.52 (95% confidence interval [CI], 0.33–0.71) and 0.97 (95% CI, 0.91–0.99), respectively. The pooled positive likelihood ratio and negative likelihood ratio were 16.0 (95% CI, 5.5–46.4) and 0.50 (95% CI, 0.33–0.75), respectively. The diagnostic odds ratio was 32 (95% CI, 10–108), and the area under the summary receiver operating characteristic curve was 0.92 (95% CI, 0.90– 0.94). There was no significant publication bias observed. In the included studies, ctDNA showed clear diagnostic value for diagnosing and monitoring cervical cancer. Our meta-analysis suggested that detection of human papilloma virus ctDNA in patients with cervical cancer could be used as a noninvasive early dynamic biomarker of tumors, with high specificity and moderate sensitivity. Further large-scale prospective studies are required to validate the factors that may influence the accuracy of cervical cancer diagnosis and monitoring.


Cancers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 288
Author(s):  
Hesam Abouali ◽  
Seied Ali Hosseini ◽  
Emma Purcell ◽  
Sunitha Nagrath ◽  
Mahla Poudineh

During cancer progression, tumors shed different biomarkers into the bloodstream, including circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA). The analysis of these biomarkers in the blood, known as ‘liquid biopsy’ (LB), is a promising approach for early cancer detection and treatment monitoring, and more recently, as a means for cancer therapy. Previous reviews have discussed the role of CTCs and ctDNA in cancer progression; however, ctDNA and EVs are rapidly evolving with technological advancements and computational analysis and are the subject of enormous recent studies in cancer biomarkers. In this review, first, we introduce these cell-released cancer biomarkers and briefly discuss their clinical significance in cancer diagnosis and treatment monitoring. Second, we present conventional and novel approaches for the isolation, profiling, and characterization of these markers. We then investigate the mathematical and in silico models that are developed to investigate the function of ctDNA and EVs in cancer progression. We convey our views on what is needed to pave the way to translate the emerging technologies and models into the clinic and make the case that optimized next-generation techniques and models are needed to precisely evaluate the clinical relevance of these LB markers.


2018 ◽  
Vol 7 (2) ◽  
pp. 321-329
Author(s):  
Yan Sun ◽  
Rui Meng ◽  
Zheng-Yu Cheng ◽  
Chen Fan ◽  
Xiao-Ming Wei ◽  
...  

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