Abstract
Simple SummaryPrecise identification and annotation of mutations are of utmost importance in clinical oncology. Insights of the DNA sequence can provide meaningful knowledge to unravel the underlying genetics of disease. Hence, tailoring of personalized medicine often relies on specific genomic alteration for treatment efficacy. The aim of this review is to highlight that sequencing harbors much more than just four nucleotides. Moreover, the gradual transition from first to second generation sequencing technologies has led to awareness for choosing the most appropriate bioinformatic analytic tools based on the aim, quality and demand for a specific purpose. Thus, the same raw data can lead to various results reflecting the intrinsic features of different datamining pipelines. Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.
Highlights
Insights into the sequence of DNA can provide meaningful knowledge to unravel the genetics of disease
In that regard, growing databases of variants and putatively beneficial drug molecular targeting are in constant development and can be useful tools to assist guidance, such as the Catalogue Of Somatic Mutations In Cancer (COSMIC) [29,30], ClinVar [31,32] and Precision Oncology Knowledge Base (OncoKB) [33]
The advent of next-generation sequencing (NGS) greatly improved the study of genetics, as well as the diagnosis and treatment of genetic diseases
Summary
Insights into the sequence of DNA can provide meaningful knowledge to unravel the genetics of disease This approach has propelled diagnostic and treatment strategies to a new level, where personalized medicine is gradually becoming adopted in the clinic. That demand was shortly followed by the development of a plethora of devised NGS bioinformatic tools, each serving its own purpose. Most computational tools such as Bowtie2 [2], Burrows–Wheeler Aligner (BWA) [3], Mutect2 [4] and Strelka2 [5] are freely available for processing NGS data in the scopes of (i) sequence mapping, (ii) base calling and (iii) variant calling. We focused on the many factors that influence data interpretation and its application in oncology This covers sequencing technologies, data output from sequencing, pitfalls and bioinformatics concerns. We discussed the increasing clinical demand for the implementation of NGS
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