Page 57 - Read Online

Crisafulli et al. Cancer Drug Resist 2019;2:225-41 I http://dx.doi.org/10.20517/cdr.2018.008 Page 235

mutations are therapy targets of drugs already in the clinics, this is rapidly leading to the repurposing of
drugs that are already known to be effective against other tumor types. These serendipitous findings are now
leading to a research effort that promises to be effective in adding new molecular-target therapies to tumor
types often in large need of impactful treatments, such as glioblastomas and pancreatic cancer [21,27,80] .

One of the first successes of NGS in this respect was the use of WES to identify risk factors that are linked
[27]
to pancreatic cancer, such as PALB2 and ATM . Other examples are the E318K MITF variant, which as
indicated above associates to melanoma, but was subsequently found to associate to renal cancer; the POLE
and POLD1 germline variations, which are associated to colon cancer, however mutations in POLD1 also
increase endometrial cancer risk; somatic mutations in BAP1, which were first identified in mesothelioma
and uveal and cutaneous melanomas, were subsequently associated to renal cell cancer.

QUALITY CHECKS
NGS protocols require highly standardized procedures for pre-analytic, analytic, and post-analytic
processes. Such requirements follow the guidelines for clinical laboratory tests according to the Clinical
Laboratory Improvement Amendments (CLIA) (www.cdc.gov/CLIA).

Although efficient and cost-effective, NGS has the disadvantages of high error rates and short read lengths,
enrichment of rare variants, and a large proportion of missing values. A comparison of the accuracy and
completeness of variant calling for two commonly used sequencing platforms found that although both
technologies achieved a relatively high concordance (88%) for unique single-nucleotide variants, concordance
for indel detection was only 27%.

The American College of Medical Genetics and Genomics (ACMG) has correspondingly developed a
position statement for the detection of germline mutations by whole exome and genome sequencing and for
the validation of NGS methods and platforms, through monitoring NGS testing, data interpretation and
[81]
reporting . Similar quality assurance guidelines for NGS in diagnostic pathology are being established in
Europe . The ACMG and the Association for Molecular Pathology (AMP) have jointly published recent
[82]
[83]
laboratory standards and guidelines .
Accordingly, any new alteration found through NGS (WES, WGS, RNA-Seq) needs to be confirmed
[84]
through another method. The main method is Sanger sequencing . Other validation methods have been
proposed, such as orthogonal NGS, i.e., the parallel sequencing of target genomes using two different
NGS platforms [84,85] . As for clinical applications, pre-analytic sample quality, such as tumor content of
specimens, DNA integrity and yield, still are key to robust findings and must be emphasized to avoid pre-
laboratory errors. Uncertainty remains on best practices regarding identification of indels and of epigenetic
changes [86,87] , which remain technically demanding for current NGS technologies.

NGS BOTTLENECKS
As previously mentioned, storing, managing, analyzing, and interpreting genome-wide data are now rapidly
becoming the bottleneck of NGS analysis procedures. Caution is also required in data interpretation, as each
[88]
distinct NGS procedure has sequencing error biases [Supplementary Table 3] . The occurrence of CNVs, as
that of large insertions, causes inherent difficulties (suboptimal sequence coverage and mapping quality) in NGS
readings, which relate to the short-read-based nature of most NGS platforms . Recent technological advances
[88]
aim at tackling this issue. High-homology regions also lead to inappropriate alignment of the reads [84,89] , and
this is particularly important in pharmacogenetic tests for pharmacokinetics genes, as CYP isoforms share a
large sequence similarity. Also, the presence of a too high or too low GC content may affect the accessibility of
gene regions . It has been estimated that more than 12% of the human exome contains “difficult or unable to
[84]
[89]
be analyzed” regions for NGS because of the presence of multiple, highly homologous genes .