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160 Part IV: Molecular and Cellular Hematology Chapter 11: Genomics 161

detected by hybrid capture is often limited. Single nucleotide variants of multiple read pairs on different chromosomes (“translocations”).
and short insertion/deletion variants can be detected, but copy number Insertions and inversions may result in a fusion protein by virtue of
and structural variants are difficult to detect reliably, especially if they juxtaposition of exons from two genes on either the same (inversion)
are not anticipated by the addition of specially designed probes to cap- or different (insertion) chromosomes. Translocations also can result in
ture them and by the specialized analyses required to detect them. gene fusions but involve juxtaposed exons from genes present on differ-
ent chromosomes in the germline. There are multiple examples of gene
OVERVIEW OF NEXT-GENERATION DNA fusions that result in proteins with a demonstrated role in oncogenesis. 28
Genetic susceptibility to hematologic malignancies can occur
SEQUENCING ANALYSIS either by inheritance or by de novo mutations in genes, such as BRCA1/2,
It can be easily argued that the relative ease of performing biomedi- TP53, and others. Here, variants in the germline can be identified from
cal experimentation imparted by NGS-based methods has conversely aligned sequence read data to the human reference sequence, followed
required more complicated analytical approaches to accurately interpret by annotation of the known cancer susceptibility genes. The pathoge-
25
the resulting data. As mentioned earlier, this is partly a result of the nicity of a given variant can be evaluated relative to databases of pre-
complexities of the human genome and the requirement for short reads viously catalogued variants in these genes, if available. Identification of
to be aligned to the reference sequence as a first step for data analysis. these variants typically will require consenting the patient and family
It also is a result of computational infrastructure and software pipeline members to a genetic counseling session to communicate the informa-
requirements to align and analyze data because of the sheer magnitude tion about the germline susceptibility and its possible consequences for
of data generated in a single experiment, which is exacerbated by mul- siblings and children (discussed below in “Next-Generation Sequencing
tiple samples, multiple time points, and the need to integrate data of as a Clinical Assay: Implications for the Practicing Hematologist”).
different types for the correlative analyses that are desired. There are a variety of data analyses that integrate NGS data from
Most cancer-focused analyses have as a central goal the identifi- different starting materials such as DNA and RNA from the same
cation of DNA variants that are unique to the tumor cells (“somatic”) tumor, or across large groups of tumors (either from the same or dif-
as compared to the inherited (“constitutional” or “germline”) genome. ferent disease site). One example of data integration is evaluating RNA
In practice, the desired comparison (whether the sequencing platform sequencing data to support a specific variant identified initially from
is a targeted gene panel, exome, or whole genome) is achieved by first tumor to normal DNA comparisons such as for a predicted fusion gene.
aligning sequencing reads from the tumor library and from the matched In this example, the confirmed detection of the gene fusion in RNA pro-
normal library against the human genome reference sequence as sepa- vides confidence that the structural variant algorithm has identified a
rate entities. Algorithms that have specialized logic to identify differ- true positive. Such a result can also confirm cytogenetic results from
ent types of variation (single nucleotide, or “point” mutations, small conventional diagnostic assays. Similarly, the identification of a DNA
insertions or deletions, copy number, or structural alterations) then are level mutation that appears to introduce a protein truncating variant
used to separately examine each set of read alignments and to iden- (frameshift or splice site mutation) can be evaluated by examining the
tify the specific variation type relative to the human genome reference RNA sequencing data for evidence of its transcription. Because these
sequence. Lastly, the resulting variants that are identified are compared transcripts are often subject to nonsense-mediated decay (a surveillance
between the tumor and normal datasets, to identify those variants that pathway that reduces errors in gene expression by eliminating mRNA
appear unique to the tumor. As a means of interpreting the impact of transcripts that contain premature stop codons), having RNA data to
all identified somatic variants on the sequence of amino acids in a given verify the transcript is present, and if so encodes the nonsense mutation,
gene, for example, one must secondarily apply the annotation of the or is absent, can provide important information.
human genome onto identified single nucleotide and indel (term for Hematologic malignancies have very specific considerations in
the insertion or the deletion of bases) variants that occur within the experimental design and data analysis that should be noted. In partic-
coding regions and splice sites of known genes. Somatic single nucleo- ular, while high tumor cell content is typically derived from marrow
tide variants (Chap. 10) can preserve the resulting amino acid (“synon- biopsies, and therefore a majority of cells contributing DNA to NGS
ymous”); can encode a different amino acid (“nonsynonymous”); can libraries are tumor cells, the matched normal sample can be problematic
abolish a splice site and therefore alter the gene reading frame according in the following regard. In patients with high circulating tumor cell con-
to the intronic sequences up to the next encoded stop codon (“splice tent in the blood, the use of a skin, buccal swab, or mouthwash sample
site”); and can omit (“readthrough”) or introduce a stop codon (“non- to provide the normal sample may have contaminating tumor cell con-
sense”). Indel mutations typically cause a shift in the open reading tent that will complicate the identification of somatic variants. Although
frame (“frameshift”) and result in a different amino acid sequence and consent to obtain a second normal sample once the patient achieves
length of the resulting protein, depending upon the number of added remission may be used to address this dilemma, not all patients achieve
or deleted nucleotides. If the number added or deleted is a multiple of remission, and some patients will refuse the second biopsy because of
three nucleotides, the open reading frame is preserved but the protein discomfort. Flow sorting the blood or marrow to isolate a nonmalignant
sequence is altered accordingly. cell population (often normal T cells) can provide a matched normal if
Copy number gains or losses are defined by statistically significant no alternative source is available.
variation in regional read density, and often are defined by the genes The rapid and uncontrolled growth and cell division inherent to
that lie in the altered region. 26,27 Structural variants are broadly defined cancer cells often means that not all cancer cells in a patient will have
as chromosomal segments that are inserted, inverted relative to the the same somatic alterations. This has been demonstrated for leukemias
germline sequence, or translocated relative to the germline sequence. and myelodysplastic syndromes and is referred to as genomic hetero-
Here, algorithms identify the different types of structural variants based geneity. 29–36 In essence, every cancer cell carries the same set of founder
on multiple read alignments that are spaced farther apart than expected mutations (sometimes referred to as “truncal”), but subclones can exist
defined by the insert size of the sequencing library used (“insertions”); in the tumor cell population, each of which carries additional mutations
or are spaced more closely than expected (“deletions”); or have the unique to that subclone. As yet, the importance of heterogeneity has not
incorrect orientation of read direction for the read pairs aligned to the been definitively demonstrated in the context of outcome, likelihood to
same chromosome (“inversions”); or have the forward and reverse reads relapse, resistance to therapy, or other possible clinical attributes. Tumor

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