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C H A P T E R 3

GENOMIC APPROACHES TO HEMATOLOGY

Jens G. Lohr, Birgit Knoechel, and Todd R. Golub

The publication of the initial draft sequence of the human genome to screen all kinases for the phenotype of interest. Although this is
in 2001 heralded a new era of biomedical research. Just as molecular compelling, it also comes with an important limitation—the quality
biology changed the face of research in the 1970s and 1980s, genom- of the assay for each kinase’s activity may not be uniformly high. For
ics has promised a novel perspective into the biologic basis of human example, a screen for kinase phosphorylation as a surrogate for kinase
disease. Genomics involves the systematic study of biologic systems, activity has been reported. Such an approach is limited by the sensi-
typically focusing on aspects of the genome (e.g., DNA and its tivity and specificity of kinase-directed antibodies, which can be
derivatives RNA and protein). However, a major tenet of genomic enormously variable across kinase family members.
research involves hypothesis-generating data collection as opposed to Although genomics is most commonly associated with systematic
hypothesis-testing experimentation. The latter has formed the basis of observational studies, the same principles can also be applied to per-
biomedical research, whereby existing knowledge and insight guide turbational studies (i.e., systematic modulation of proteins followed
the testing of a particular hypothesis. In contrast, genome-based by a phenotypic read-out). In this manner, all genes within a particu-
research tends to make few prior assumptions, favoring unbiased data lar class (e.g., kinases) can be mutated, knocked down (e.g. by RNA
generation and analysis as a path to discovery. Clearly, both approaches interference), or completely knocked out (e.g., by genome editing),
are powerful and essential, and both should continue at full force in and the phenotypic consequence of each can be assessed. A number
the future. Although still associated with substantial cost, sequencing of genomic perturbational technologies have been developed recently,
approaches such as whole genome and whole exome DNA sequenc- most notably the discovery of clustered regularly interspaced short
ing or whole-transcriptome RNA sequencing have become available palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-
at most academic institutions, either through in-house services or mediated genome editing, as described later. Use of these perturba-
through a number of commercial providers. Large-scale national and tional technologies in combination with high-throughput sequencing
multinational genomic profiling efforts such as The Cancer Genome will yield great insight into the biology of hematologic diseases in the
Atlas have led to the establishment of repositories of genomic variants years ahead.
for the most common malignancies. Next-generation sequencing
approaches are being integrated into clinical routine and are used as
both prognostic and predictive biomarkers. The latter are proving Importance of Sample Acquisition
particularly useful as more drugs become available that target specific
genomic variants (e.g., BRAF inhibitors targeting BRAF V600E Acquisition of the appropriate samples for a genomic experiment is
mutations). The assignment of a particular therapeutic agent to a arguably the most crucial step for the generation of a dataset expected
specific genomic finding has gained momentum over the past several to be rich with biologic information. This is particularly true for gene
years and was recently termed precision medicine. expression analysis, in which a number of processes may affect data
However, with the ability to generate data of unprecedented quality. Because gene expression is a dynamic process that can be
scale, including sequencing of the whole genome, comes the chal- affected by any type of cellular manipulation, RNA abundance
lenge of data analysis. This has driven an entirely new generation measurements are potentially complicated by changes that occur
of computer scientists to focus on new approaches to genomic data between the time that the biopsy is taken and the time that the RNA
analysis, leading to new methods of pattern recognition and large- is isolated from the specimen. In general, the highest-quality RNA is
scale data processing. Translating these data into useful knowledge obtained if, as soon as possible after harvesting a sample, cells are
that provides biologic insight and clinical utility is an ongoing dissolved in a solution such as TRIzol reagent that inactivates RNase
challenge. enzymes and the sample is stored at −80°C until RNA can be
This chapter describes the principles underlying common genomic extracted. Procedures for measuring gene expression in formalin-
approaches in the study of hematologic and other diseases, focusing fixed, paraffin-embedded (FFPE) tissues (in which messenger RNA
more on concepts than on technical detail. Undoubtedly, there will [mRNA] is degraded to less than 100 nucleotides) have been used,
be continuous acceleration of the pace of use of genomic approaches but the lack of robustness of these methods may preclude routine
in clinical research and clinical care in the years ahead. clinical implementation.
Another extremely important but complicated issue is the com-
plexity of cell types (e.g., tumor cells, normal cells of the same lineage,
PRINCIPLES OF GENOMIC APPROACHES stromal cells, immune cells) present in the sample. This may be less
of an issue for bone marrow samples taken from patients with newly
Measurements and Perturbations diagnosed leukemia, in whom the number of blasts often approaches
90% or greater. In the relapsed leukemia setting (where the percent-
A common feature of many genomic approaches is the systematic age of blast cells may be low) or in other tumor types, however, the
nature of the approach (e.g., interrogating all kinases for their poten- admixture of multiple cell types may be vexing for gene expression
tial role in a particular biologic system). A more traditional approach studies. Multiple methods are available for enrichment and selection
would be to first determine (on the basis of prior knowledge) the of cells of interest from a biopsy sample; these methods include flow
kinase (or kinases) most likely to be important and then develop cytometry, immunomagnetic bead sorting, and laser-capture micro-
highly validated assays for that particular kinase. On one hand, a dissection. All have the benefit of enrichment of the cell of interest
strength of the traditional approach is that the quality of the final but also increase the amount of processing time and sample manipu-
assay is often high, given the attention paid to the one (or a couple lation. Although in principle “contaminating,” nonmalignant cells
of) kinase(s) of interest. On the other hand, such an approach is may reflect informative aspects of the tumor environment, the high
limited by the quality of the initial hypothesis. In contrast, a genomic degree of sample-to-sample variability makes such interpretations
approach would be more systematic and comprehensive, attempting challenging. A promising new approach to the problem of cell-type

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