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GE-based biomarkers in CML
Gene expression profiles and mutations: ‘seed and soil’ revisited
As described above, it will be important to develop CML models that integrate the interaction between genetic and epigenetic factors in driving drug resistance and disease transformation. In this respect, the effects of specific mutations may be cell-context dependent, with differential effects on GE and function depending on the cell type being examined. This is particularly the case for mutations affecting transcription factors, for which cell states, and their attendant chromatin accessibility profile, determine whether the mutated transcription factor has access to its target genes.
To integrate contributions from both the above fea- tures, we propose a model in which the cell of origin, with its attendant epigenetic and transcriptional program, determines the ability of specific mutations to contribute to biological and clinical outcomes (Figure 2). This model is a derivative of the ‘seed and soil’ hypothesis of cancer initiation.82 The model will be useful for hypothesis test- ing, and likely explains an important feature of BCR- ABL1 itself. It has been shown in murine models that only when expressed in HSC, but not more committed progenitors, can BCR-ABL1 induce a myeloproliferative disorder. This is likely because BCR-ABL1 is incapable of conferring self-renewal capacity upon committed progen- itors, indicating that CML cells rely on BCR-ABL1-inde- pendent mechanisms for stemness programs. These find- ings are in contrast to those for other leukemia fusion genes (e.g., MLL-ENL, MLL-AF9, MOZ-TIF2) which are capable of conferring self-renewal and transform progen- itor cells.83 Relatedly, the model may also explain a natu- rally occurring phenomenon whereby normal individuals found to carry the BCR-ABL1 fusion in their peripheral blood mononuclear cells apparently never develop CML.84 Here, the model would posit that the BCR-ABL1 fusion is occurring in a long-lived progenitor without self- renewal function.
Analogous to the situation regarding cancer initiation by leukemia fusion genes, mutations devoid of self- renewal function may only confer an increased risk of BC transformation when they occur in a target cell that already possesses physiological self-renewal function. According to this model, mutations in RUNX1 that are sufficient to induce BC-like disease in mice (Table 3) may be deemed a ‘strong’ biological seed that can transform many cell types within the hematopoietic hierarchy. Such mutations would be expected to induce disease progres- sion in the majority of patients who harbor such muta- tions, which is indeed the case.37 However, a minority of CP patients with RUNX1 mutations continue to enjoy sustained deep maolecular responses,57 suggesting the existence of other important factors that modulate RUNX1 function. Along the same lines, ASXL1 was recently identified as the most frequently mutated gene at diagnosis in nine patients, the majority (n=6) of whom eventually developed BC, while a minority (n=2) achieved a MMR.14
In contrast to the above examples, the prognostic impact of ‘weak’ seeds is much less clear. In a study by Kim et al., at least four different patterns were observed for TET2 mutations.57 One pattern is seen in patients with TKI resistance when both TET2 and ABL1 variant allele frequencies increased following TKI therapy, while
another is seen when the TET2 variant allele frequency reduces after TKI treatment in patients with disease pro- gression. In other cases, TET2 mutations were also detect- ed within Philadelphia chromosome-negative cells, and here, patients showed complex outcomes following TKI therapy, with some achieving MMR and others showing TKI resistance. These observations suggest that the effect of TET2 mutations are highly contextual.
Challenges ahead but room for optimism
As described above, the discovery of a limited and tractable set of genes that is prognostic across a majority of CML patients has been challenging for clinical, biolog- ical, and technical reasons. Nevertheless, there is room for optimism. In the setting of breast cancer, GE panels com- prising 21 genes that encompass various aspects of breast cancer biology have been found to be predictive of thera- peutic response, and minimized the use of additional therapy without compromising survival.85 Among liquid tumors, a recent study in acute myeloid leukemia demon- strated that a parsimonious 17-gene GE score, derived from a larger set of stemness-conferring genes, predicts resistance to initial therapy.86 Interestingly, this score was independent of cytogenetic and mutational risk factors, and suggests that biological factors (e.g., stemness) tran- scend traditional genetics-based groupings.87
Encouragingly in CML, two recent reports suggest that it is possible, using peripheral blood samples taken at diagnosis or 3 months after diagnosis, to predict deep molecular responses and also sustained treatment-free remissions. In the first study, the Adelaide group showed that the rate of decline of BCR-ABL1 transcripts during first-line TKI therapy (calculated from baseline and 3- month BCR-ABL1 transcript levels) predicts success of treatment-free remission.88 The time taken for BCR-ABL1 transcripts to halve was the strongest independent predic- tor of sustained treatment-free remission: 80% in patients with a halving time of <9.35 days versus 4% if the halving time was >21.85 days (P<0.001). In a separate study, Radich et al. reported that GE signatures from peripheral blood taken prior to TKI initiation can distinguish indi- viduals who will achieve a deep molecular response (MR4.5) at 5 years from those who will have suboptimal responses.89 Thus, biological information encoded in GE data can predict very long-term clinical outcomes in CML, and it is therefore conceivable that GE-based data will be able to identify patients in whom TKI therapy can be safely discontinued. More importantly, these early reports suggest that despite the likely existence of diverse resistance mechanisms within the study populations, final common paths, readout either as dynamic measures of BCR-ABL1 transcript levels, or peripheral blood GE sig- natures are indeed discoverable.
Stages in developing gene expression-based risk assessment
The stages of developing GE-based tests has been out- lined in recent reviews and consensus statements, and comprise at least three phases that assess: analytical validity (reliably measuring the genotype of interest), clinical validity (ability to segregate patients into biologi-
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