Improving high-resolution copy number variation analysis from next generation sequencing using unique molecular identifiers

On the core segmentation algorithms of copy number variation detection tools

Shotgun sequencing is a high-throughput method used to detect copy number variants (CNVs). Although there are numerous CNV detection tools based on shotgun sequencing, their quality varies significantly, leading to performance discrepancies. Therefore, we conducted a comprehensive analysis of next-generation sequencing-based CNV detection tools over the past decade. Our findings revealed that the majority of mainstream tools employ similar detection rationale: calculates the so-called read depth signal from aligned sequencing reads and then segments the signal by utilizing either circular binary segmentation (CBS) or hidden Markov model (HMM). Hence, we compared the performance of those two core segmentation algorithms in CNV detection, considering varying sequencing depths, segment lengths and complex types of CNVs. To ensure a fair comparison, we designed a parametrical model using mainstream statistical distributions, which allows for pre-excluding bias correction such as guanine-cytosine (GC) content during the preprocessing step. The results indicate the following key points: (1) Under ideal conditions, CBS demonstrates high precision, while HMM exhibits a high recall rate. (2) For practical conditions, HMM is advantageous at lower sequencing depths, while CBS is more competitive in detecting small variant segments compared to HMM. (3) In case involving complex CNVs resembling real sequencing, HMM demonstrates more robustness compared with CBS. (4) When facing large-scale sequencing data, HMM costs less time compared with the CBS, while their memory usage is approximately equal. This can provide an important guidance and reference for researchers to develop new tools for CNV detection.

A Bioinformatics Toolkit for Next-Generation Sequencing in Clinical Oncology

Next-generation sequencing (NGS) has taken on major importance in clinical oncology practice. With the advent of targeted therapies capable of effectively targeting specific genomic alterations in cancer patients, the development of bioinformatics processes has become crucial. Thus, bioinformatics pipelines play an essential role not only in the detection and in identification of molecular alterations obtained from NGS data but also in the analysis and interpretation of variants, making it possible to transform raw sequencing data into meaningful and clinically useful information. In this review, we aim to examine the multiple steps of a bioinformatics pipeline as used in current clinical practice, and we also provide an updated list of the necessary bioinformatics tools. This resource is intended to assist researchers and clinicians in their genetic data analyses, improving the precision and efficiency of these processes in clinical research and patient care.

Copy Number Variations in Hereditary Spastic Paraplegia-Related Genes: Evaluation of an Iranian Hereditary Spastic Paraplegia Cohort and Literature Review

Introduction

In human genetic disorders, copy number variations (CNVs) are considered a considerable underlying cause. CNVs are generally detected by array-based methods but can also be discovered by read-depth analysis of whole-exome sequencing (WES) data. We performed WES-based CNV identification in a cohort of 35 Iranian families with hereditary spastic paraplegia (HSP) patients.

Methods

Thirty-five patients whose routine single-nucleotide variants (SNVs) and insertion/deletion analyses from exome data were unrevealing underwent a pipeline of CNV analysis using the read-depth detection method. Subsequently, a comprehensive search about the existence of CNVs in all 84 known HSP-causing genes was carried out in all reported HSP cases, so far.

Results and Discussion

CNV analysis of exome data indicated that 1 patient harbored a heterozygous deletion in exon 17 of the SPAST gene. Multiplex ligation-dependent probe amplification analysis confirmed this deletion in the proband and his affected father. Literature review demonstrated that, to date, pathogenic CNVs have been identified in 30 out of 84 HSP-causing genes (∼36%). However, CNVs in only 17 of these genes were specifically associated with the HSP phenotype. Among them, CNVs were more common in L1CAM, PLP1, SPAST, SPG7, SPG11, and REEP1 genes. The identification of the CNV in 1 of our patients suggests that WES allows the detection of both SNVs and CNVs from a single method without additional costs and execution time. However, because of intrinsic issues of WES in the detection of large rearrangements, it may not yet be exploited to replace the CNV detection methods in standard clinical practice.

MET Amplification in Non-Small Cell Lung Cancer (NSCLC)-A Consecutive Evaluation Using Next-Generation Sequencing (NGS) in a Real-World Setting

Simple Summary

Lung cancer has a high incidence and affects both men and women. Targeted therapy options directed at certain mutant proteins, and which avoid systemic chemotherapy are already available and emerging. The gene mesenchymal epithelial transition (MET), encoding a receptor tyrosine kinase protein, is amplified in a subpopulation of lung cancer patients. The aim of our consecutive study was to assess whether next-generation sequencing (NGS) is a reliable method for the detection of MET gene copy number. Our study confirmed that NGS is able to detect cases harboring a high-level MET gene amplification but is unreliable and fails to detect the various levels of MET gene amplification. Therefore, NGS cannot replace the gold standard method of fluorescence in situ hybridization for the detection of MET gene copy number.

Abstract

In non-small cell lung cancer (NSCLC), approximately 1–3% of cases harbor an increased gene copy number (GCN) of the MET gene. This alteration can be due to de novo amplification of the MET gene or can represent a secondary resistance mechanism in response to targeted therapies. To date, the gold standard method to evaluate the GCN of MET is fluorescence in situ hybridization (FISH). However, next-generation sequencing (NGS) is becoming more relevant to optimize therapy by revealing the mutational profile of each NSCLC. Using evaluable n = 205 NSCLC cases of a consecutive cohort, this study addressed the question of whether an amplicon based NGS assay can completely replace the FISH method regarding the classification of MET GCN status. Out of the 205 evaluable cases, only n = 9 cases (43.7%) of n = 16 high-level MET amplified cases assessed by FISH were classified as amplified by NGS. Cases harboring a MET GCN > 10 showed the best concordance when comparing FISH versus NGS (80%). This study confirms that an amplicon-based NGS assessment of the MET GCN detects high-level MET amplified cases harboring a MET GCN > 10 but fails to detect the various facets of MET gene amplification in the context of a therapy-induced resistance mechanism.

cfDNA Sequencing: Technological Approaches and Bioinformatic Issues

In the era of precision medicine, it is crucial to identify molecular alterations that will guide the therapeutic management of patients. In this context, circulating tumoral DNA (ctDNA) released by the tumor in body fluids, like blood, and carrying its molecular characteristics is becoming a powerful biomarker for non-invasive detection and monitoring of cancer. Major recent technological advances, especially in terms of sequencing, have made possible its analysis, the challenge still being its reliable early detection. Different parameters, from the pre-analytical phase to the choice of sequencing technology and bioinformatic tools can influence the sensitivity of ctDNA detection.