Page 56 - Hematology_ Basic Principles and Practice ( PDFDrive )

28 Part I Molecular and Cellular Basis of Hematology

neoplasia. Similarly, monoclonal gammopathy of undetermined sig- pathophysiology of disease. Trisomy 21, for example, predisposes
nificance and monoclonal B-cell lymphocytosis are characterized by individuals to transient myeloproliferative disorders and acute mega-
clonal expansion of lymphoid clones that are usually associated with karyoblastic leukemia. Deletions at the RB1 locus encoding the reti-
multiple myeloma and chronic lymphocytic leukemia, respectively. noblastoma gene or deletions of the TP53 gene encoding the p53
Because only a minority of individuals go on to develop a clinically tumor suppressor predispose individuals to the development of solid
symptomatic neoplasm, an important goal is to identify additional cancers, although only rarely to hematologic malignancies. In a
variants that promote the development of overt malignancy. Also of landmark set of studies, it was shown that tumors from patients who
great interest is the question of the extent to which hematologic inherit a mutant copy of the retinoblastoma tumor suppressor gene
diseases (whether malignant or otherwise) are caused by germline often have deletions of the remaining allele. This process has been
genetic variation. Although it is clear that certain disorders (e.g., termed loss of heterozygosity, and the search for genetic loci showing
hemophilia) have a highly penetrant, Mendelian basis, it is less certain loss of heterozygosity in tumor samples has identified a number of
whether genetic variation substantially contributes to diseases that genes that are involved in critical cellular processes and are important
have been historically considered “sporadic” in the large majority of for cancer progression. Similarly, amplification of genomic loci can
cases, such as multiple myeloma. play an important role in oncogenesis and cancer biology. For
In contrast, mutations present in tumors but absent in the normal example, amplification of the ERBB2 (HER2) oncogene in human
cells from that individual are referred to as somatic. Somatic muta- breast cancer predicts a poor prognosis, and ERBB2 has been shown
tions are thought to be a major driver of cancer behavior. However, to be an important therapeutic target in this disease.
all somatic mutations are not causal drivers of cancer. Indeed, the The search for gains and losses of genetic material can be carried
majority of somatic mutations observed in any individual tumor are out using a number of techniques that require various levels of
likely passenger mutations—that is, they play no functional role in expertise and allow assessment of genomic integrity at various resolu-
the pathogenesis of the tumor but rather were present in a cell that tions. The first method developed to assess genomic integrity, cytoge-
subsequently acquired a driver mutation that resulted in the cell’s netic analysis, is still used today, but it allows identification only of
clonal outgrowth. The proportion of passengers to drivers differs abnormalities that encompass large regions of the genome. Neverthe-
dramatically from tumor type to tumor type. For example, tumors less, cytogenetic analysis has provided tremendous insight into the
associated with tobacco (e.g., lung cancer) or sunlight exposure (e.g., pathophysiology of disease, particularly for leukemogenesis. Cytoge-
melanoma) have very high mutation frequencies, with the majority netic analysis remains a key part of the diagnostic workup for new
of the observed mutations being “passengers.” In contrast, many cases of leukemia. It is likely, however, that over time it will be
hematologic malignancies (e.g., acute myeloid leukemia) have rela- replaced by next-generation sequencing methods that have the ability
tively low mutation rates, and some cancers such as infant leukemias to detect point mutations, deletions/insertions, copy number changes,
have extraordinarily low rates, with only a handful of protein-coding and chromosomal translocations, all at high resolution.
somatic mutations seen per patient. More recently developed methods for assessing copy number
Distinguishing passenger mutations from driver mutations is a variation include comparative genomic hybridization (CGH) and
major focus of cancer genome research. The complete delineation of high-density single-nucleotide polymorphism (SNP) arrays. Although
the biologically important mutations in cancer requires both large- CGH and SNP arrays are falling out of favor, massively parallel
scale sequencing studies (enabling the identification of recurrent genome sequencing can be used for copy number variant detection.
mutations) and the functional characterization of observed mutations. Special note should be made of the analysis of copy number data. At
the level of the individual sample (e.g., a tumor), one can easily
visualize regions of aberration using tools such as the Integrative
Point Mutations Genomics Viewer (IGV) (Fig. 3.2). Although this type of analysis
highlights those aberrations in a particular sample, it does not reflect
The most common type of genetic variants (both germline and copy number abnormalities that are commonly observed across a
somatic) are single-nucleotide variants (SNVs), also known as point collection of samples. Such recurrent copy number gains or losses tend
mutations. As more individuals are sequenced and deposited into to indicate biologically important events as opposed to copy number
databases, it is becoming possible to catalog all common SNVs in the aberrations that simply reflect genomic instability but do not con-
human population. Still, it is estimated that every individual will tribute to cancer pathogenesis (and therefore are nonrecurrent). To
harbor 50 to 100 coding mutations not present in any database. For identify statistically significant regions of copy number abnormalities,
these reasons, it is particularly important to compare the somatic algorithms such as the genomic identification of significant targets in
genome of a tumor with its matched normal germline sequence; cancer (GISTIC) method can be applied, yielding a plot of regions
otherwise, “private” germline variants may be mistaken for somatic of amplification and deletion that are commonly observed in a set of
mutations. samples (as shown in Fig. 3.3 for 24 patients with multiple myeloma).
Certain patterns of point mutation are characteristic of particular
environmental exposures. For example, G>T/C>A transversions are
characteristic of tobacco-associated lung cancer, and C>T/G>A Rearrangements
transitions are characteristic of ultraviolet radiation–associated skin
cancers. Most hematologic malignancies lack a particular pattern of Chromosomal rearrangements (including balanced and unbalanced
mutation, although B-cell lymphomas demonstrate a characteristic translocations, inversions, and more complex aberrations) are particu-
pattern of hot spots of mutations caused by activation-induced, larly important in the hematologic malignancies. Translocations were
adenosine deaminase–mediated. among the very first genomic defects to be discovered in cancer
Although not as common as point mutations, small somatic inser- because cytogenetic analysis of metaphase chromosome spreads was
tions or deletions (referred to collectively as indels) are also observed feasible for the acute leukemias long before more technically advanced
in tumors. These generally consist of the loss or gain of one or a few methods became available. Two basic types of translocations are
nucleotides that, when they occur within protein-coding regions, common: those that result in fusion proteins involving two distinct
result in translational frameshifts that generally yield loss-of-function genes and those that result in overexpression of an otherwise structur-
alleles. ally normal gene. Translocations resulting in fusion transcripts (e.g.,
ETV6/RUNX1 in acute lymphoblastic leukemia [ALL]) generally
involve chromosomal breakage within intronic regions of the two
Copy Number genes, with in-frame fusion being a result of the normal process of
RNA splicing. In contrast, translocations resulting in overexpression
Gains (amplifications) or losses (deletions) of genetic material at typically involve the juxtaposition of a coding region next to a highly
specific loci are recognized as playing an important role in the active promoter or enhancer region such as an immunoglobulin