Mechanisms of Pinometostat (EPZ-5676) Treatment-Emergent Resistance in MLL-Rearranged Leukemia.

DOT1L is a protein methyltransferase involved in the development and maintenance of MLL-rearranged (MLL-r) leukemia through its ectopic methylation of histones associated with well-characterized leukemic genes. Pinometostat (EPZ-5676), a selective inhibitor of DOT1L, is in clinical development in relapsed/refractory acute leukemia patients harboring rearrangements of the MLL gene. The observation of responses and subsequent relapses in the adult trial treating MLL-r patients motivated preclinical investigations into potential mechanisms of pinometostat treatment-emergent resistance (TER) in cell lines confirmed to have MLL-r. TER was achieved in five MLL-r cell lines, KOPN-8, MOLM-13, MV4-11, NOMO-1, and SEM. Two of the cell lines, KOPN-8 and NOMO-1, were thoroughly characterized to understand the mechanisms involved in pinometostat resistance. Unlike many other targeted therapies, resistance does not appear to be achieved through drug-induced selection of mutations of the target itself. Instead, we identified both drug efflux transporter dependent and independent mechanisms of resistance to pinometostat. In KOPN-8 TER cells, increased expression of the drug efflux transporter ABCB1 (P-glycoprotein, MDR1) was the primary mechanism of drug resistance. In contrast, resistance in NOMO-1 cells occurs through a mechanism other than upregulation of a specific efflux pump. RNA-seq analysis performed on both parental and resistant KOPN-8 and NOMO-1 cell lines supported two unique candidate pathway mechanisms that may explain the pinometostat resistance observed in these cell lines. These results are the first demonstration of TER models of the DOT1L inhibitor pinometostat and may provide useful tools for investigating clinical resistance. Mol Cancer Ther; 16(8); 1669-79. ©2017 AACR.

Blood-based identification of non-responders to anti-TNF therapy in rheumatoid arthritis.

BACKGROUND: Faced with an increasing number of choices for biologic therapies, rheumatologists have a critical need for better tools to inform rheumatoid arthritis (RA) disease management. The ability to identify patients who are unlikely to respond to first-line biologic anti-TNF therapies prior to their treatment would allow these patients to seek alternative therapies, providing faster relief and avoiding complications of disease. METHODS: We identified a gene expression classifier to predict, pre-treatment, which RA patients are unlikely to respond to the anti-TNF infliximab. The classifier was trained and independently evaluated using four published whole blood gene expression data sets, in which RA patients (n = 116 = 44 + 15 + 30 + 27) were treated with infliximab, and their response assessed 14-16 months post treatment according to the European League Against Rheumatism (EULAR) response criteria. For each patient, prior knowledge was used to group gene expression measurements into disease-relevant biological signaling mechanisms that were used as the input features for regularized logistic regression. RESULTS: The classifier produced a substantial enrichment of non-responders (59 %, given by the cross validated test precision) compared to the full population (27 % non-responders), while identifying nearly a third of non-responders. Given this classifier performance, treatment of predicted non-responders with alternative biologics would decrease their chance of non-response by between a third and a half, substantially improving their odds of effective treatment and stemming further disease progression. The classifier consisted of 18 signaling mechanisms, which together indicated that higher inflammatory signaling mediated by TNF and other cytokines was present pre-treatment in the blood of patients who responded to infliximab treatment. In contrast, non-responders were classified by relatively higher levels of specific metabolic activities in the blood prior to treatment. CONCLUSIONS: We were able to successfully produce a classifier to identify a population of RA patients significantly enriched in anti-TNF non-responders across four different patient cohorts. Additional prospective studies are needed to validate and refine the classifier for clinical use.

Assessment of network perturbation amplitudes by applying high-throughput data to causal biological networks.

BACKGROUND: High-throughput measurement technologies produce data sets that have the potential to elucidate the biological impact of disease, drug treatment, and environmental agents on humans. The scientific community faces an ongoing challenge in the analysis of these rich data sources to more accurately characterize biological processes that have been perturbed at the mechanistic level. Here, a new approach is built on previous methodologies in which high-throughput data was interpreted using prior biological knowledge of cause and effect relationships. These relationships are structured into network models that describe specific biological processes, such as inflammatory signaling or cell cycle progression. This enables quantitative assessment of network perturbation in response to a given stimulus. RESULTS: Four complementary methods were devised to quantify treatment-induced activity changes in processes described by network models. In addition, companion statistics were developed to qualify significance and specificity of the results. This approach is called Network Perturbation Amplitude (NPA) scoring because the amplitudes of treatment-induced perturbations are computed for biological network models. The NPA methods were tested on two transcriptomic data sets: normal human bronchial epithelial (NHBE) cells treated with the pro-inflammatory signaling mediator TNFα, and HCT116 colon cancer cells treated with the CDK cell cycle inhibitor R547. Each data set was scored against network models representing different aspects of inflammatory signaling and cell cycle progression, and these scores were compared with independent measures of pathway activity in NHBE cells to verify the approach. The NPA scoring method successfully quantified the amplitude of TNFα-induced perturbation for each network model when compared against NF-κB nuclear localization and cell number. In addition, the degree and specificity to which CDK-inhibition affected cell cycle and inflammatory signaling were meaningfully determined. CONCLUSIONS: The NPA scoring method leverages high-throughput measurements and a priori literature-derived knowledge in the form of network models to characterize the activity change for a broad collection of biological processes at high-resolution. Applications of this framework include comparative assessment of the biological impact caused by environmental factors, toxic substances, or drug treatments.

Early patient stratification and predictive biomarkers in drug discovery and development: a case study of ulcerative colitis anti-TNF therapy.

The current drug discovery paradigm is long, costly, and prone to failure. For projects in early development, lack of efficacy in Phase II is a major contributor to the overall failure rate. Efficacy failures often occur from one of two major reasons: either the investigational agent did not achieve the required pharmacology or the mechanism targeted by the investigational agent did not significantly contribute to the disease in the tested patient population. The latter scenario can arise due to insufficient study power stemming from patient heterogeneity. If the subset of disease patients driven by the mechanism that is likely to respond to the drug can be identified and selected before enrollment begins, efficacy and response rates should improve. This will not only augment drug approval percentages, but will also minimize the number of patients at risk of side effects in the face of a suboptimal response to treatment. Here we describe a systems biology approach using molecular profiling data from patients at baseline for the development of predictive biomarker content to identify potential responders to a molecular targeted therapy before the drug is tested in humans. A case study is presented where a classifier to predict response to a TNF targeted therapy for ulcerative colitis is developed a priori and verified against a test set of patients where clinical outcomes are known. This approach will promote the tandem development of drugs with predictive response, patient selection biomarkers.

Rational design of memory in eukaryotic cells.

The ability to logically engineer novel cellular functions promises a deeper understanding of biological systems. Here we demonstrate the rational design of cellular memory in yeast that employs autoregulatory transcriptional positive feedback. We built a set of transcriptional activators and quantitatively characterized their effects on gene expression in living cells. Modeling in conjunction with the quantitative characterization of the activator-promoter pairs accurately predicts the behavior of the memory network. This study demonstrates the power of taking advantage of components with measured quantitative parameters to specify eukaryotic regulatory networks with desired properties.

Designing biological systems.

The design of artificial biological systems and the understanding of their natural counterparts are key objectives of the emerging discipline of synthetic biology. Toward both ends, research in synthetic biology has primarily focused on the construction of simple devices, such as transcription-based oscillators and switches. Construction of such devices should provide us with insight on the design of natural systems, indicating whether our understanding is complete or whether there are still gaps in our knowledge. Construction of simple biological systems may also lay the groundwork for the construction of more complex systems that have practical utility. To realize its full potential, biological systems design borrows from the allied fields of protein design and metabolic engineering. In this review, we describe the scientific accomplishments in this field, as well as its forays into biological part standardization and education of future biological designers.

The chloromethylketone protease inhibitor AAPF(CMK) also targets ATP-dependent helicases and SAP-domain proteins.

We have been studying a nuclear protease, which appears to be involved in cellular transformation, as well as in infections with high-risk human papillomaviruses (HPVs). This protease has a chymotrypsin-like substrate specificity and the chloromethylketone inhibitor AAPF(CMK) is a potent (and relatively selective) inhibitor of it. Recently, we have observed that AAPF(CMK) has potent effects in some model systems which appear not to be mediated by decreases in the nuclear protease. Here we show that AAPF(CMK) selectively reacts with ATP-dependent helicases as well as a limited spectrum of proteins in other DNA repair/chromatin remodeling nuclear complexes, including for example Cohesin complex components and proteins containing SAP-domains. In vitro, AAPF(CMK) selectively reacts with SV40 large T antigen, and inhibits its helicase activity.

Motion as a phenotype: the use of live-cell imaging and machine visual screening to characterize transcription-dependent chromosome dynamics.

BACKGROUND: Gene transcriptional activity is well correlated with intra-nuclear position, especially relative to the nuclear periphery, which is a region classically associated with gene silencing. Recently however, actively transcribed genes have also been found localized to the nuclear periphery in the yeast Saccharomyces cerevisiae. When genes are activated, they become associated with the nuclear pore complex (NPC) at the nuclear envelope. Furthermore, chromosomes are not static structures, but exhibit constrained diffusion in real-time, live-cell studies of particular loci. The relationship of chromosome motion with transcriptional activation and active-gene recruitment to the nuclear periphery has not yet been investigated. RESULTS: We have generated a yeast strain that enables us to observe the motion of the galactose-inducible GAL gene locus relative to the nuclear periphery in real-time under transcriptionally active and repressed conditions. Using segmented geometric particle tracking, we show that the repressed GAL locus undergoes constrained diffusive movement, and that transcriptional induction with galactose is associated with an enrichment in cells with GAL loci that are both associated with the nuclear periphery and much more constrained in their movement. Furthermore, we report that the mRNA export factor Sac3 is involved in this galactose-induced enrichment of GAL loci at the nuclear periphery. In parallel, using a novel machine visual screening technique, we find that the motion of constrained GAL loci correlates with the motion of the cognate nuclei in galactose-induced cells. CONCLUSION: Transcriptional activation of the GAL genes is associated with their tethering and motion constraint at the nuclear periphery. We describe a model of gene recruitment to the nuclear periphery involving gene diffusion and the mRNA export factor Sac3 that can be used as a framework for further experimentation. In addition, we applied to the analysis of chromosome motion a machine visual screening approach that used unbiased visual data rather than segmented geometric data. This novel analytical approach will allow for high-throughput study of processes that can be monitored via alterations in chromosome motion and connectivity with the nuclear periphery.

A protease inhibitor specifically inhibits growth of HPV-infected keratinocytes.

Protease inhibitors have been known to exhibit anticarcinogenic activity in a variety of model systems, although the biological target(s) and mechanism remain enigmatic. Human papillomavirus (HPV) is the primary etiological agent of cervical cancer. Here we show that a nuclear chymotrypsin-like protease activity (NCLPA), which appears to be involved in transformation in several different experimental models, is significantly elevated in keratinocytes infected with high-risk HPV. Further, we demonstrate a marked growth inhibition of organotypic raft cultures, which is specific for cells infected with high-risk HPV types, using a chloromethyl ketone inhibitor previously shown to be relatively selective for the NCLPA. Surprisingly, this HPV-dependent inhibitory effect is independent of any alterations in the NCLPA. This finding has clear implications for the development of novel therapeutics specifically targeted to cervical dysplasias with HPV-infected cells.

Developmentally induced changes in transcriptional program alter spatial organization across chromosomes.

Although the spatial location of genes within the nucleus has been implicated in their transcriptional status, little is known about the dynamics of gene location that accompany large-scale changes in gene expression. The mating of haploid yeast Saccharomyces cerevisiae is accompanied by a large-scale change in transcription and developmental program. We examined changes in nuclear organization that accompany stimulus by the mating pheromone alpha factor and found that most alpha-factor-induced genes become associated with components of the nuclear envelope. The myosin-like protein Mlp1, which has been implicated in mRNA export, was further shown to exhibit RNA dependence in its association with alpha-factor-induced genes. High-resolution mapping of association of chromosome III with Mlp1 revealed alpha-factor-dependent determinants of nuclear pore association, including origins of replication, specific intergenic regions, and the 3' ends of transcriptionally activated genes. Taken together, these results reveal RNA- and DNA-dependent determinants of nuclear organization as well as a detailed picture of how an entire chromosome alters its spatial conformation in response to a developmental cue.

Spontaneous transformation of an immortalized hepatocyte cell line: potential role of a nuclear protease.

In this study, we utilized an in vitro model of spontaneous transformation/progression, an SV40 large T antigen-immortalized rat hepatocyte cell line (designated CWSV14) that is very weakly tumorigenic at low-passage, but acquires a transformed phenotype upon extended passage in cell culture. Here we show that this mid-passage transformation is accompanied by development of aneuploidy and disorganization of the actin cytoskeleton, concomitant with a large increase in a chymotrypsin-like nuclear protease activity which we have previously implicated in chemical transformation of fibroblasts and ras-transformation of hepatocytes. Passage of the CWSV14 cells with AAPF(cmk), a relatively selective inhibitor of the nuclear protease activity, abrogates the acquisition of the transformed phenotype and prevents the changes in the actin cytoskeleton. We hypothesize that the nuclear protease may play a role in initiating development of genomic instability, paralleling the archetypical role of proteases in paradigms such as the SOS-type responses in bacteria and yeast.