scholarly journals Microdroplet Digital PCR: Detection and Quantitation of Biomarkers in Archived Tissue and Serial Plasma Samples in Patients with Lung Cancer

2015 ◽  
Vol 10 (1) ◽  
pp. 212-217 ◽  
Author(s):  
Fangfei Gao ◽  
Ester Pfeifer ◽  
Hassan Farah ◽  
Elena Karampini ◽  
Divyanshu Dua ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Digital Pcr ◽  
Pcr Detection ◽  
Plasma Samples

scholarly journals A CRISPR Test for Rapidly and Sensitively Detecting Circulating EGFR Mutations

Diagnostics ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 114 ◽  
Author(s):  
Jen-Hui Tsou ◽  
Qixin Leng ◽  
Feng Jiang
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Limit Of Detection ◽  
Digital Pcr ◽  
Medical Diagnostics ◽  
Egfr Mutations ◽  
Nucleic Acid Detection ◽  
Great Promise ◽  
Plasma Samples ◽  
Lung Cancer Patients

The detection of EGFR mutations in circulating cell-free DNA can enable personalized therapy for cancer. The current techniques for detecting circulating EGFR mutations are expensive and time-consuming with moderate sensitivity. Emerging CRISPR is revolutionizing medical diagnostics and showing a great promise for nucleic acid detection. This study aims to develop CRISPR-Cas12a as a simple test to sensitively detect circulating EGFR mutations in plasma. Serially diluted samples of DNA containing heterozygous EGFR mutations (L858R and T790M) in wild-type genomic DNA are concurrently tested for the mutations by a CRISPR-Cas12a system and droplet digital PCR (ddPCR). The CRISPR-Cas12a system can detect both L858R and T790M with a limit of detection of 0.005% in less than three hours. ddPCR detects the mutations with a limit of detection of 0.05% for more than five hours. Plasma samples of 28 lung cancer patients and 20 cancer-free individuals are tested for the EGFR mutations by CRISPR-Cas12a system and ddPCR. The CRISPR-Cas12a system could detect L858R in plasma of two lung cancer patients whose tissue biopsies are positive for L858R, and one plasma sample of three lung cancer patients whose tissue biopsies are positive for T790M. ddPCR detects L858R in the same two plasm samples, however, does not detect T790M in any of the plasma samples. This proof of principle study demonstrates that the CRISPR-Cas12a system could rapidly and sensitively detect circulating EGFR mutations, and thus, has potential prognostic or therapeutic implications.

scholarly journals Pan-cancer circulating tumor DNA detection in over 10,000 Chinese patients

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yongliang Zhang ◽  
Yu Yao ◽  
Yaping Xu ◽  
Lifeng Li ◽  
Yan Gong ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Circulating Tumor Dna ◽  
Small Cell ◽  
Chinese Patients ◽  
Plasma Samples ◽  
Small Cell Lung ◽  
Pan Cancer ◽  
Tumor Dna

AbstractCirculating tumor DNA (ctDNA) provides a noninvasive approach to elucidate a patient’s genomic landscape and actionable information. Here, we design a ctDNA-based study of over 10,000 pan-cancer Chinese patients. Using parallel sequencing between plasma and white blood cells, 14% of plasma cell-free DNA samples contain clonal hematopoiesis (CH) variants, for which detectability increases with age. After eliminating CH variants, ctDNA is detected in 73.5% of plasma samples, with small cell lung cancer (91.1%) and prostate cancer (87.9%) showing the highest detectability. The landscape of putative driver genes revealed by ctDNA profiling is similar to that in a tissue-based database (R2 = 0.87, p < 0.001) but also shows some discrepancies, such as higher EGFR (44.8% versus 25.2%) and lower KRAS (6.8% versus 27.2%) frequencies in non-small cell lung cancer, and a higher TP53 frequency in hepatocellular carcinoma (53.1% versus 28.6%). Up to 41.2% of plasma samples harbor drug-sensitive alterations. These findings may be helpful for identifying therapeutic targets and combined treatment strategies.

Epidermal Growth Factor Receptor Mutations in Plasma DNA Samples Predict Tumor Response in Chinese Patients With Stages IIIB to IV Non–Small-Cell Lung Cancer

2009 ◽  
Vol 27 (16) ◽  
pp. 2653-2659 ◽  
Author(s):  
Hua Bai ◽  
Li Mao ◽  
hang Shu Wang ◽  
Jun Zhao ◽  
Lu Yang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Egfr Mutation ◽  
Tumor Response ◽  
Growth Factor Receptor ◽  
Small Cell ◽  
Egfr Mutations ◽  
Plasma Samples ◽  
Plasma Dna ◽  
Small Cell Lung ◽  
Epidermal Growth

Purpose Mutations in the epidermal growth factor receptor (EGFR) kinase domain can predict tumor response to tyrosine kinase inhibitors (TKIs) in non–small-cell lung cancer (NSCLC). However, obtaining tumor tissues for mutation analysis is challenging. We hypothesized that plasma-based EGFR mutation analysis is feasible and has value in predicting tumor response in patients with NSCLC. Patients and Methods Plasma DNA samples and matched tumors from 230 patients with stages IIIB to IV NSCLC were analyzed for EGFR mutations in exons 19 and 21 by using denaturing high-performance liquid chromatography. We compared the mutations in the plasma samples and the matched tumors and determined an association between EGFR mutation status and the patients' clinical outcomes prospectively. Results In 230 patients, we detected 81 EGFR mutations in 79 (34.3%) of the patients' plasma samples. We detected the same mutations in 63 (79.7%) of the matched tumors. Sixteen plasma (7.0%) and fourteen tumor (6.1%) samples showed unique mutations. The mutation frequencies were significantly higher in never-smokers and in patients with adenocarcinomas (P = .012 and P = .009, respectively). In the 102 patients who failed platinum-based treatment and who were treated with gefitinib, 22 (59.5%) of the 37 with EGFR mutations in the plasma samples, whereas only 15 (23.1%) of the 65 without EGFR mutations, achieved an objective response (P = .002). Patients with EGFR mutations had a significantly longer progression-free survival time than those without mutations (P = .044) in plasma. Conclusion EGFR mutations can be reliably detected in plasma DNA of patients with stages IIIB to IV NSCLC and can be used as a biomarker to predict tumor response to TKIs.

scholarly journals Detection of KRAS Mutations in Circulating Tumor DNA by Digital PCR in Early Stages of Pancreatic Cancer

2016 ◽  
Vol 62 (11) ◽  
pp. 1482-1491 ◽  
Author(s):  
Nora Brychta ◽  
Thomas Krahn ◽  
Oliver von Ahsen
Keyword(s):  
Pancreatic Cancer ◽  
Early Stage ◽  
Digital Pcr ◽  
Circulating Tumor Dna ◽  
Surgical Removal ◽  
Plasma Samples ◽  
Kras Mutations ◽  
Detection Rates ◽  
Early Stages ◽  
Tumor Dna

Abstract BACKGROUND Since surgical removal remains the only cure for pancreatic cancer, early detection is of utmost importance. Circulating biomarkers have potential as diagnostic tool for pancreatic cancer, which typically causes clinical symptoms only in advanced stage. Because of their high prevalence in pancreatic cancer, KRAS proto-oncogene, GTPase [KRAS (previous name: Kirsten rat sarcoma viral oncogene homolog)] mutations may be used to identify tumor-derived circulating plasma DNA. Here we tested the diagnostic sensitivity of chip based digital PCR for the detection of KRAS mutations in circulating tumor DNA (ctDNA) in early stage pancreatic cancer. METHODS We analyzed matched plasma (2 mL) and tumor samples from 50 patients with pancreatic cancer. Early stages (I and II) were predominant (41/50) in this cohort. DNA was extracted from tumor and plasma samples and tested for the common codon 12 mutations G12D, G12V, and G12C by chip-based digital PCR. RESULTS We identified KRAS mutations in 72% of the tumors. 44% of the tumors were positive for G12D, 20% for G12V, and 10% for G12C. One tumor was positive for G12D and G12V. Analysis of the mutations in matched plasma samples revealed detection rates of 36% for G12D, 50% for G12V, and 0% for G12C. The detection appeared to be correlated with total number of tumor cells in the primary tumor. No KRAS mutations were detected in 20 samples of healthy control plasma. CONCLUSIONS Our results support further evaluation of tumor specific mutations as early diagnostic biomarkers using plasma samples as liquid biopsy.

Integration of proteomic and clinical data for the prediction of response to immune checkpoint inhibitor therapy in non-small cell lung cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e21110-e21110
Author(s):  
Yuval Shaked ◽  
Michal Harel ◽  
Coren Lahav ◽  
Eyal Jacob ◽  
Itamar Sela ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Clinical Trial ◽  
Host Response ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Resistance Mechanisms ◽  
Small Cell ◽  
Plasma Samples ◽  
Small Cell Lung ◽  
Nsclc Patients

e21110 Background: Immune checkpoint inhibitor (ICI) therapy represents one of the most promising cancer treatments to date. However, despite unprecedented rates of durable response, only a small proportion of patients benefits from this approach. Major efforts are therefore required to characterize treatment resistance mechanisms, as well as to identify reliable biomarkers for response. We have previously shown that in response to various types of cancer therapy, including ICIs, the host may induce pro-tumorigenic processes that can promote therapy resistance. Here we examined systemic host-response proteomic profiles in non-small cell lung cancer (NSCLC) patients, aiming to discover biomarkers for response to ICI therapy and to unravel underlying resistance mechanisms. Methods: As part of our ongoing PROPHETIC clinical trial (NCT04056247), plasma samples were obtained at baseline (T0) and early-on treatment (T1; following the first treatment) from 120 NSCLC patients receiving ICI therapy. Proteomic profiling of the plasma samples was performed using proximity-extension assay (PEA) technology; validation was carried out for a fraction of the samples using ELISA-based arrays. To identify a proteomic signature that predicts clinical outcome, machine learning algorithms were applied following a random separation of the cohort into a discovery set and a validation set. Results: A proteomic signature predictive of response to treatment was identified and validated. Bioinformatic analysis identified potential mechanisms of resistance based on differentially expressed proteins associated with pro-tumorigenic biological processes. Statistical analysis of the clinical data identified multiple novel differential clinical parameters between responders and non-responders, either at baseline or by comparing T0 to T1, which may suggest host-mediated effects. Conclusions: Our study demonstrates the potential clinical utility of analyzing the host response to ICI therapy, in particular for the discovery of novel predictive biomarkers for NSCLC patient stratification. Clinical trial information: NCT04056247.

scholarly journals Compared to plasma, bronchial washing fluid shows higher diagnostic yields for detecting EGFR-TKI sensitizing mutations by ddPCR in lung cancer

2020 ◽  
Author(s):  
Sang Hoon Lee ◽  
Eun Young Kim ◽  
Taehee Kim ◽  
Yoon Soo Chang
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Kinase Inhibitor ◽  
Early Stage ◽  
Digital Pcr ◽  
Study Cohort ◽  
Diagnostic Efficacy ◽  
Detection Rates ◽  
Bronchial Washing ◽  
Exon 19 Deletion

Abstract Background: The rate of diagnosis of advanced lung adenocarcinoma must be improved. In this study, we compared the detection rates of EGFR-tyrosine kinase inhibitor-sensitizing mutations (mEGFRs) in bronchial washing fluid (BWF) and the plasma of patients with lung adenocarcinoma using the tissue genotype as the standard reference. Methods: Paired blood and BWF specimens were collected from 73 patients with lung cancer. The tumor EGFR mutation status was determined by genotyping of the plasma and BWF samples using droplet digital PCR (ddPCR). Results: The study cohort included 26, 10, 10, and 27 patients with stage I, II, III, and IV disease. Of the 73 cases, 35 had a wild-type EGFR, and 19 had the L858R substitution and exon 19 deletion mutations. The areas under the receiver operator characteristic curves for sensitivity vs. specificity of ddPCR were 0.895 [95% confidence interval (CI): 0.822–0.969] for BWF and 0.686 (95% CI: 0.592–0.780) for plasma (p < 0.001). The fractional abundance was higher in BWF of the mEGFR-positive cases than in the plasma (p = 0.004), facilitating easy threshold setting and discrimination between mEGFR-positive and negative cases. When genotyping results obtained using plasma and BWF were compared for early lung cancer (stages I–IIIA), the diagnostic yields were significantly higher for BWF ddPCR, and the same tendency was observed for the advanced stages, suggesting that the BWF data may reflect the genotype status in early-stage patients. Conclusions: The mEGFR genotyping results obtained using BWF showed a higher diagnostic efficacy than did those obtained using the plasma. Thus, BWF-based genotyping may be a useful substitute for that using plasma in lung cancer.

scholarly journals Introduction of Noninvasive Prenatal Testing for Blood Group and Platelet Antigens from Cell-Free Plasma DNA Using Digital PCR

2019 ◽  
Vol 47 (4) ◽  
pp. 292-301 ◽  
Author(s):  
Marion Eryilmaz ◽  
Dennis Müller ◽  
Gabi Rink ◽  
Harald Klüter ◽  
Peter Bugert
Keyword(s):  
Pregnant Women ◽  
Blood Group ◽  
Internal Control ◽  
Prenatal Testing ◽  
Digital Pcr ◽  
Chromosomal Marker ◽  
Plasma Samples ◽  
Autosomal Snps ◽  
Allelic Discrimination ◽  
Noninvasive Prenatal Testing

Background: Noninvasive prenatal testing (NIPT) for fetal antigens is a common standard for targeted immune prophylaxis in RhD-mediated hemolytic disease of the fetus and newborn, and is most frequently done by quantitative PCR (qPCR). A similar approach is considered for other blood group and human platelet alloantigens (HPA). Because of a higher sensitivity compared to qPCR for rare molecule detection, we established and validated digital PCR (dPCR) assays for the detection of RHD exons 3, 5 and 7, KEL1, HPA-1a, and HPA-5b from cell-free DNA (cfDNA) in plasma. The dPCR assays for the Y-chromosomal marker amelogenin and autosomal SNPs were implemented as controls for the proof of fetal DNA. Methods: Validation was performed on dilution series of mixed plasma samples from volunteer donors with known genotypes. After preamplification of the target loci, two-color (FAM and VIC) TaqManTM probe chemistry and chip-based dPCR were applied. The assays for RHD included GAPDH as an internal control. For the diallelic markers KEL1/2, HPA-1a/b, HPA-5a/b, and AMEL-X/Y and 3 autosomal SNPs, the probes enabled allelic discrimination in the two fluorescence channels. The dPCR protocol for NIPT was applied to plasma samples from pregnant women. Results: The RHD exon 5 assay allowed the detection of a 0.05% RHD target in an RhD-negative background, whereas the exon 7 assay required at least a 0.25% target. The exon 3 assay showed the highest background and required at least a 2.5% RHD target for reliable detection. The dPCR assays for the diallelic markers revealed similar sensitivity and enabled the detection of at least a 0.5% target allele. The HPA-1a assay was the most sensitive and allowed target detection in plasma mixtures containing only 0.05% HPA-1a. The plasma samples from 13 pregnant women at different gestational ages showed unambiguous positive and negative results for the analyzed targets. Conclusion: Analysis of cfDNA from maternal plasma using dPCR is suitable for the detection of fetal alleles. Because of the high sensitivity of the assays, the NIPT protocol for RhD, KEL1, and HPA can also be applied to earlier stages of pregnancy.

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