Leveraging of single molecule sequencing methods for less invasive cancer detection

In the field of paediatric neuro-oncology, the positions of tumours within the central nervous system of the patients makes the acquisition of solid tumour biopsies risky. For many tumour types, monitoring of treatment response is restricted to Magnetic Resonance Imaging (MRI), or cerebrospinal fluid (CSF) cytology in the cases with leptomeningeal dissemination. Both of these lack sensitivity, leaving room for improvement. Recent advances in molecular barcoding sensitivity and error suppression have made the sequencing of DNA derived from liquid biopsies possible. Liquid biopsies offer an alternative to solid biopsies, since the collection of bodily fluids is much less invasive by comparison, and liquid biopsies contain cell-free DNA (cfDNA). In cancer patients, it has been shown that a fraction of the cfDNA in multiple liquid biopsies, such as plasma and CSF, harbour the genetic alterations present within the tumour. This circulating tumour DNA (ctDNA) can be used as a biomarker for diagnosis, stratification, and surveillance of the tumour. The monitoring of treatment response, and the detection of minimal residual disease, is of particular importance in paediatric brain tumours, given the low sensitivity of existing methods. This project created a versatile system, utilising molecular barcoding, which was able to detect Single Nucleotide Variants (SNVs), Insertions/Deletions and Copy-Number Variants in a single assay. A wet-lab workflow was created and iteratively improved, such that it could handle a diverse range of liquid biopsy types, including plasma, cystic fluid and CSF. This workflow was coupled with a bioinformatic pipeline, designed to process the data for all three variant calling processes simultaneously. For SNV calling, a custom variant caller was created to aid in the suppression of errors in barcoded sequencing, and the system was used in the first documented tracking of Adamantinomatous Craniopharyngioma treatment response using cystic fluid liquid biopsies

Ultraaccurate genome sequencing and haplotyping of single human cells.

Accurate detection of variants and long-range haplotypes in genomes of single human cells remains very challenging. Common approaches require extensive in vitro amplification of genomes of individual cells using DNA polymerases and high-throughput short-read DNA sequencing. These approaches have two notable drawbacks. First, polymerase replication errors could generate tens of thousands of false-positive calls per genome. Second, relatively short sequence reads contain little to no haplotype information. Here we report a method, which is dubbed SISSOR (single-stranded sequencing using microfluidic reactors), for accurate single-cell genome sequencing and haplotyping. A microfluidic processor is used to separate the Watson and Crick strands of the double-stranded chromosomal DNA in a single cell and to randomly partition megabase-size DNA strands into multiple nanoliter compartments for amplification and construction of barcoded libraries for sequencing. The separation and partitioning of large single-stranded DNA fragments of the homologous chromosome pairs allows for the independent sequencing of each of the complementary and homologous strands. This enables the assembly of long haplotypes and reduction of sequence errors by using the redundant sequence information and haplotype-based error removal. We demonstrated the ability to sequence single-cell genomes with error rates as low as 10-8 and average 500-kb-long DNA fragments that can be assembled into haplotype contigs with N50 greater than 7 Mb. The performance could be further improved with more uniform amplification and more accurate sequence alignment. The ability to obtain accurate genome sequences and haplotype information from single cells will enable applications of genome sequencing for diverse clinical needs

Detecting very low allele fraction variants using targeted DNA sequencing and a novel molecular barcode-aware variant caller

The supplementary materials include supplementary methods, supplementary figures, and supplementary tables. (PDF 706 kb

Applications and data analysis of next-generation sequencing

Over the past 6 years, next-generation sequencing (NGS) has been established as a valuable high-throughput method for research in molecular genetics and has successfully been employed in the identification of rare and common genetic variations. Although the high expectations regarding the discovery of new diagnostic targets and an overall reduction of cost have been achieved, technological challenges in instrument handling, robustness of the chemistry, and data analysis need to be overcome. Each workflow and sequencing platform have their particular problems and caveats, which need to be addressed. Regarding NGS, there is a variety of different enrichment methods, sequencing devices, or technologies as well as a multitude of analyzing software products available. In this manuscript, the authors focus on challenges in data analysis when employing different target enrichment methods and the best applications for each of the

Bioinformatics and computational tools for next-generation sequencing analysis in clinical genetics

Clinical genetics has an important role in the healthcare system to provide a definitive diagnosis for many rare syndromes. It also can have an influence over genetics prevention, disease prognosis and assisting the selection of the best options of care/treatment for patients. Next-generation sequencing (NGS) has transformed clinical genetics making possible to analyze hundreds of genes at an unprecedented speed and at a lower price when comparing to conventional Sanger sequencing. Despite the growing literature concerning NGS in a clinical setting, this review aims to fill the gap that exists among (bio)informaticians, molecular geneticists and clinicians, by presenting a general overview of the NGS technology and workflow. First, we will review the current NGS platforms, focusing on the two main platforms Illumina and Ion Torrent, and discussing the major strong points and weaknesses intrinsic to each platform. Next, the NGS analytical bioinformatic pipelines are dissected, giving some emphasis to the algorithms commonly used to generate process data and to analyze sequence variants. Finally, the main challenges around NGS bioinformatics are placed in perspective for future developments. Even with the huge achievements made in NGS technology and bioinformatics, further improvements in bioinformatic algorithms are still required to deal with complex and genetically heterogeneous disorders

Spatially resolved clonal copy number alterations in benign and malignant tissue

Publisher Copyright: © 2022, The Author(s).Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.Peer reviewe

Spatially resolved clonal copy number alterations in benign and malignant tissue

Publisher Copyright: © 2022, The Author(s).Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.Peer reviewe