Another surprising role for exosomes? Improving next-generation sequencing-based cancer diagnostics in liquid biopsies

AbstractBackgroundNon-small cell lung cancer (NSCLC) patients benefit from targeted therapies both in first- and second-line treatment. Nevertheless, molecular profiling of lung cancer tumors after first disease progression is seldom performed. The analysis of circulating tumor DNA (ctDNA) enables not only non-invasive biomarker testing but also monitoring tumor response to treatment. Digital PCR (dPCR), although a robust approach, only enables the analysis of a limited number of mutations. Next-generation sequencing (NGS), on the other hand, enables the analysis of significantly greater numbers of mutations.MethodsA total of 54 circulating free DNA (cfDNA) samples from 52 NSCLC patients and two healthy donors were analyzed by NGS using the Oncomine™ Lung cfDNA Assay kit and dPCR.ResultsLin’s concordance correlation coefficient and Pearson’s correlation coefficient between mutant allele frequencies (MAFs) assessed by NGS and dPCR revealed a positive and linear relationship between the two data sets (ρc = 0.986; 95% confidence interval [CI] = 0.975–0.991; r = 0.987; p < 0.0001, respectively), indicating an excellent concordance between both measurements. Similarly, the agreement between NGS and dPCR for the detection of the resistance mutation p.T790M was almost perfect (K = 0.81; 95% CI = 0.62–0.99), with an excellent correlation in terms of MAFs (ρc = 0.991; 95% CI = 0.981–0.992 and Pearson’s r = 0.998; p < 0.0001). Importantly, cfDNA sequencing was successful using as low as 10 ng cfDNA input.ConclusionsMAFs assessed by NGS were highly correlated with MAFs assessed by dPCR, demonstrating that NGS is a robust technique for ctDNA quantification using clinical samples, thereby allowing for dynamic genomic surveillance in the era of precision medicine.

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Abstract 3602: Validation and implementation of next-generation sequencing in liquid biopsies by a novel NGS platform: Focus on non-small cell lung cancer

10.1158/1538-7445.am2018-3602 ◽

2018 ◽

Author(s):

Atil Bisgin ◽

Ozge Sonmezler ◽

Ibrahim Boga

Keyword(s):

Lung Cancer ◽

Next Generation Sequencing ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Small Cell ◽

Next Generation ◽

Small Cell Lung ◽

Liquid Biopsies ◽

Generation Sequencing

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Power and Promise of Next-Generation Sequencing in Liquid Biopsies and Cancer Control

Cancer Control ◽

10.1177/1073274820934805 ◽

2020 ◽

Vol 27 (3) ◽

pp. 107327482093480

Author(s):

Ting-Miao Wu ◽

Ji-Bin Liu ◽

Yu Liu ◽

Yi Shi ◽

Wen Li ◽

...

Keyword(s):

Next Generation Sequencing ◽

Treatment Plan ◽

Genetic Mutations ◽

Specific Gene ◽

Specific Situation ◽

Next Generation ◽

Early Screening ◽

Liquid Biopsies ◽

Cancer Management ◽

Generation Sequencing

Traditional methods of cancer treatment are usually based on the morphological and histological diagnosis of tumors, and they are not optimized according to the specific situation. Precision medicine adjusts the existing treatment regimen based on the patient’s genomic information to make it most suitable for patients. Detection of genetic mutations in tumors is the basis of precise cancer medicine. Through the analysis of genetic mutations in patients with cancer, we can tailor the treatment plan for each patient with cancer to maximize the curative effect, minimize damage to healthy tissues, and optimize resources. In recent years, next-generation sequencing technology has developed rapidly and has become the core technology of precise targeted therapy and immunotherapy for cancer. From early cancer screening to treatment guidance for patients with advanced cancer, liquid biopsy is increasingly used in cancer management. This is as a result of the development of better noninvasive, repeatable, sensitive, and accurate tools used in early screening, diagnosis, evaluation, and monitoring of patients. Cell-free DNA, which is a new noninvasive molecular pathological detection method, often carries tumor-specific gene changes. It plays an important role in optimizing treatment and evaluating the efficacy of different treatment options in clinical trials, and it has broad clinical applications.

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P2.14-29 Clinical Impact of Next-Generation Sequencing (NGS) in Blood Liquid Biopsies for Treatment Decisions in Advanced NSCLC

Journal of Thoracic Oncology ◽

10.1016/j.jtho.2019.08.1814 ◽

2019 ◽

Vol 14 (10) ◽

pp. S840-S841

Author(s):

M. Garcia Pardo ◽

I. Martinez Delfrade ◽

I. Aparicio Salcedo ◽

M. Arregui Valles ◽

M. Alva Bianchi ◽

...

Keyword(s):

Next Generation Sequencing ◽

Advanced Nsclc ◽

Treatment Decisions ◽

Clinical Impact ◽

Next Generation ◽

Liquid Biopsies ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

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RNA Analysis as a Tool to Determine Clinically Relevant Gene Fusions and Splice Variants

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2017-0134-ra ◽

2018 ◽

Vol 142 (4) ◽

pp. 474-479 ◽

Cited By ~ 5

Author(s):

Cristina Teixidó ◽

Ana Giménez-Capitán ◽

Miguel Ángel Molina-Vila ◽

Vicente Peg ◽

Niki Karachaliou ◽

...

Keyword(s):

Next Generation Sequencing ◽

Cancer Patients ◽

Splice Variants ◽

Treatment Options ◽

Diagnostic Process ◽

Gene Fusions ◽

Next Generation ◽

Liquid Biopsies ◽

Rna Analysis ◽

Generation Sequencing

Context.— Technologic advances have contributed to the increasing relevance of RNA analysis in clinical oncology practice. The different genetic aberrations that can be screened with RNA include gene fusions and splice variants. Validated methods of identifying these alterations include fluorescence in situ hybridization, immunohistochemistry, reverse transcription–polymerase chain reaction, and next-generation sequencing, which can provide physicians valuable information on disease and treatment of cancer patients. Objective.— To discuss the standard techniques available and new approaches for the identification of gene fusions and splice variants in cancer, focusing on RNA analysis and how analytic methods have evolved in both tissue and liquid biopsies. Data Sources.— This is a narrative review based on PubMed searches and the authors' own experiences. Conclusions.— Reliable RNA-based testing in tissue and liquid biopsies can inform the diagnostic process and guide physicians toward the best treatment options. Next-generation sequencing methodologies permit simultaneous assessment of molecular alterations and increase the number of treatment options available for cancer patients.

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Automated Workflow for Somatic and Germline Next Generation Sequencing Analysis in Routine Clinical Cancer Diagnostics

Cancers ◽

10.3390/cancers11111691 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1691

Author(s):

Muscarella ◽

Fabrizio ◽

De Bonis ◽

Mancini ◽

Balsamo ◽

...

Keyword(s):

Next Generation Sequencing ◽

Scale Up ◽

Cancer Diagnostics ◽

Sequencing Analysis ◽

Library Preparation ◽

Next Generation ◽

High Quality ◽

High Coverage ◽

Dna Recovery ◽

Generation Sequencing

Thanks to personalized medicine trends and collaborations between industry, clinical research groups and regulatory agencies, next generation sequencing (NGS) is turning into a common practice faster than one could have originally expected. When considering clinical applications of NGS in oncology, a rapid workflow for DNA extraction from formalin-fixed paraffin-embedded (FFPE) tissue samples, as well as producing high quality library preparation, can be real challenges. Here we consider these targets and how applying effective automation technology to NGS workflows may help improve yield, timing and quality-control. We firstly evaluated DNA recovery from archived FFPE blocks from three different manual extraction methods and two automated extraction workstations. The workflow was then implemented to somatic (lung/colon panel) and germline (BRCA1/2) library preparation for NGS analysis exploiting two automated workstations. All commercial kits gave good results in terms of DNA yield and quality. On the other hand, the automated workstation workflow has been proven to be a valid automatic extraction system to obtain high quality DNA suitable for NGS analysis (lung/colon Ampli-seq panel). Moreover, it can be efficiently integrated with an open liquid handling platform to provide high-quality libraries from germline DNA with more reproducibility and high coverage for targeted sequences in less time (BRCA1/2). The introduction of automation in routine workflow leads to an improvement of NGS standardization and increased scale up of sample preparations, reducing labor and timing, with optimization of reagents and management.

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Next-generation sequencing of microbial cell-free DNA for rapid noninvasive diagnosis of infectious diseases in immunocompromised hosts

F1000Research ◽

10.12688/f1000research.19766.1 ◽

2019 ◽

Vol 8 ◽

pp. 1194

Author(s):

Jose F. Camargo ◽

Asim A. Ahmed ◽

Martin S. Lindner ◽

Michele I. Morris ◽

Shweta Anjan ◽

...

Keyword(s):

Next Generation Sequencing ◽

Noninvasive Diagnosis ◽

Cell Transplant ◽

Next Generation ◽

Liquid Biopsies ◽

Cell Free Dna ◽

Hematopoietic Stem ◽

Free Dna ◽

Immunocompromised Hosts ◽

Generation Sequencing

Background: Cell-free DNA (cfDNA) sequencing has emerged as an effective laboratory method for rapid and noninvasive diagnosis in prenatal screening testing, organ transplant rejection screening, and oncology liquid biopsies. Methods: Here we report our experience using next-generation sequencing (NGS) for detection of microbial cfDNA in a cohort of ten immunocompromised patients with febrile neutropenia or deep-seated infection. Results: Among five hematological malignancy patients, for whom a microbiological diagnosis was established, pathogen identification by cfDNA NGS demonstrated 100% positive agreement with conventional diagnostic laboratory methods. Further, cfDNA identified the etiological agent in two patients with culture negative sepsis who had undergone hematopoietic stem cell transplant. Conclusion: These data support the clinical utility of measurement of microbial cfDNA sequencing from peripheral blood for rapid noninvasive diagnosis of infections in immunocompromised hosts. Larger studies are needed.

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Performance analysis of SiRe next-generation sequencing panel in diagnostic setting: focus on NSCLC routine samples

Journal of Clinical Pathology ◽

10.1136/jclinpath-2018-205386 ◽

2018 ◽

Vol 72 (1) ◽

pp. 38-45 ◽

Cited By ~ 17

Author(s):

Francesco Pepe ◽

Caterina De Luca ◽

Riccardo Smeraglio ◽

Pasquale Pisapia ◽

Roberta Sgariglia ◽

...

Keyword(s):

Next Generation Sequencing ◽

Progression Free Survival ◽

Outcome Evaluation ◽

Read Length ◽

Next Generation ◽

Liquid Biopsies ◽

Tissue Samples ◽

Sample Mean ◽

Technical Parameters ◽

Generation Sequencing

AimsFollowing the development for liquid biopsies of the SiRe next-generation sequencing (NGS) panel that covers 568 clinical relevant mutations in EGFR, KRAS, NRAS, BRAF, cKIT and PDGFRa genes, in this current study, we apply this small NGS panel on tissue samples of lung cancer.MethodsA total of 322 specimens were prospectively tested. Technical parameters were analysed on both cytological and histological samples. In a subset of 75 samples, the EGFR SiRe results were compared with those generated by the European Community (CE)–IVD EGFR assay on Idylla platform. Clinical outcomes of 11 patients treated, on the basis of SiRe results, were also evaluated.ResultsOnly 28 (8.7%) specimens failed to produce a library; out of the 294 remaining samples, a total of 168 somatic mutations were found. In nearly all instances (74/75–99%), the EGFR SiRe results were confirmed by Idylla. In general, SiRe analytical parameters were excellent. However, histological and cytological specimens differed in relation to average reads for sample, mean number of mapped reads, median read length and average reads for amplicon. Treatment outcome evaluation in 11 patients showed a partial response in 82 % (9/11) patients with a median progression-free survival of 340 days.ConclusionsThe small gene panel SiRe is a clinically relevant tool useful to widespread the adoption of NGS in predictive molecular pathology laboratories.

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A statistical approach for tracking clonal dynamics in cancer using longitudinal next-generation sequencing data

10.1101/2020.01.20.913236 ◽

2020 ◽

Author(s):

Dimitrios V. Vavoulis ◽

Anthony Cutts ◽

Jenny C. Taylor ◽

Anna Schuh

Keyword(s):

Next Generation Sequencing ◽

Longitudinal Data ◽

Darwinian Evolution ◽

Next Generation Sequencing Data ◽

Model Parameters ◽

Next Generation ◽

Sequencing Data ◽

Sample Collection ◽

Liquid Biopsies ◽

Generation Sequencing

ABSTRACTTumours are composed of genotypically and phenotypically distinct cancer cell populations (clones), which are subject to a process of Darwinian evolution in response to changes in their local micro-environment, such as drug treatment. In a cancer patient, this process of continuous adaptation can be studied through next-generation sequencing of multiple tumour samples combined with appropriate bioinformatics and statistical methodologies. One family of statistical methods for clonal deconvolution seeks to identify groups of mutations and estimate the prevalence of each group in the tumour, while taking into account its purity and copy number profile. These methods have been used in the analysis of cross-sectional data, as well as for longitudinal data by discarding information on the timing of sample collection. Two key questions are how (in the case of longitudinal data) can we incorporate such information in our analyses and if there is any benefit in doing so. Regarding the first question, we incorporated information on the temporal spacing of longitudinally collected samples into standard non-parametric approaches for clonal deconvolution by modelling the time dependence of the prevalence of each clone as a Gaussian process. This permitted reconstruction of the temporal profile of the abundance of each clone continuously from several sparsely collected samples and without any strong prior assumptions on the functional form of this profile. Regarding the second question, we tested various model configurations on a range of whole genome, whole exome and targeted sequencing data from patients with chronic lymphocytic leukaemia, on liquid biopsy data from a patient with melanoma and on synthetic data. We demonstrate that incorporating temporal information in our analysis improves model performance, as long as data of sufficient volume and complexity are available for estimating free model parameters. We expect that our approach will be useful in cases where collecting a relatively long sequence of tumour samples is feasible, as in the case of liquid cancers (e.g. leukaemia) and liquid biopsies. The statistical methodology presented in this paper is freely available at github.com/dvav/clonosGP.

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