Computer simulations of the signalling network in FLT3 +-acute myeloid leukaemia - indications for an optimal dosage of inhibitors against FLT3 and CDK6

Interplay of mutations, alternate mechanisms, and treatment breaks in leukaemia: Understanding and implications studied with stochastic models

Bcr-Abl1 kinase domain mutations are the most prevalent cause of treatment resistance in chronic myeloid leukaemia (CML). Alternate resistance pathways nevertheless exist, and cell line experiments show certain patterns in the gain, and loss, of some of these alternate adaptations. These adaptations have clinical consequences when the tumour develops mechanisms that are beneficial to its growth under treatment, but slow down its growth when not treated. The results of temporarily halting treatment in CML have not been widely discussed in the clinic and there is no robust theoretical model that could suggest when such a pause in therapy can be tolerated. We constructed a dynamic model of how mechanisms such as Bcr-Abl1 overexpression and drug transporter upregulation evolve to produce resistance in cell lines, and investigate its behaviour subject to different treatment schedules, in particular when the treatment is paused ('drug holiday'). Our study results suggest that the presence of additional resistance mechanisms creates an environment which favours mutations that are either preexisting or occur late during treatment. Importantly, the results suggest the existence of tumour drug addiction, where cancer cells become dependent on the drug for (optimal) survival, which could be exploited through a treatment holiday. All simulation code is available at https://github.com/Sandalmoth/dual-adaptation.

Combination strategies to overcome drug resistance in FLT+ acute myeloid leukaemia

BACKGROUND

Acute myeloid leukaemia (AML) remains difficult to treat despite the development of novel formulations and targeted therapies. Activating mutations in the FLT3 gene are common among patients and make the tumour susceptible to FLT3 inhibitors, but resistance to such inhibitors develops quickly.

METHODS

We examined combination therapies aimed at FLT3+-AML, and studied the development of resistance using a newly developed protocol. Combinations of FLT3, CDK4/6 and PI3K inhibitors were tested for synergism.

RESULTS

We show that AML cells express CDK4 and that the CDK4/6 inhibitors palbociclib and abemaciclib inhibit cellular growth. PI3K inhibitors were also effective in inhibiting the growth of AML cell lines that express FLT3-ITD. Whereas resistance to quizartinib develops quickly, the combinations overcome such resistance.

CONCLUSIONS

This study suggests that a multi-targeted intervention involving a CDK4/6 inhibitor with a FLT3 inhibitor or a pan-PI3K inhibitor might be a valuable therapeutic strategy for AML to overcome drug resistance. Moreover, many patients cannot tolerate high doses of the drugs that were studied (quizartinib, palbociclib and PI3K inhibitors) for longer periods, and it is therefore of high significance that the drugs act synergistically and lower doses can be used.

The molecular mechanisms behind activation of FLT3 in acute myeloid leukemia and resistance to therapy by selective inhibitors

Acute myeloid leukemia is an aggressive cancer, which, in spite of increasingly better understanding of its genetic background remains difficult to treat. Mutations in the FLT3 gene are observed in ≈30% of the patients. Most of these mutations are internal tandem duplications (ITDs) of a sequence within the protein coding region, an activation mechanism that is almost non-existent with other genes and cancers. As patients each carry their own unique set of mutations, it is challenging to understand how ITDs activate the protein, and ascertain the risk for each individual patient. Available treatment options are limited due to development of drug resistance. Here, recent studies are reviewed that help to better understand the molecular mechanism behind activation of the FLT3 protein due to mutations. It is argued that difference in mutation sequences and especially location might be coupled to prognosis. When it comes to FLT3 inhibitors, key differences between them can be attributed to the mode of inhibition (type-1 and type-2 inhibitors), effective inhibitory coefficient in the blood plasma and off-target binding. Accounting for the position and length of insertions may in the future be used to predict prognosis and rationalise treatment. Development of new inhibitors must take into account the potential for resistance mutations. Inhibitors aimed at multiple specific targets are currently being developed. These, and as well as combination therapies will hopefully lead to longer periods during which targeted FLT3 therapy will remain effective.

Dexamethasone Induces Changes in Osteogenic Differentiation of Human Mesenchymal Stromal Cells via SOX9 and PPARG, but Not RUNX2

Despite the huge body of research on osteogenic differentiation and bone tissue engineering, the translation potential of in vitro results still does not match the effort employed. One reason might be that the protocols used for in vitro research have inherent pitfalls. The synthetic glucocorticoid dexamethasone is commonly used in protocols for trilineage differentiation of human bone marrow mesenchymal stromal cells (hBMSCs). However, in the case of osteogenic commitment, dexamethasone has the main pitfall of inhibiting terminal osteoblast differentiation, and its pro-adipogenic effect is well known. In this work, we aimed to clarify the role of dexamethasone in the osteogenesis of hBMSCs, with a particular focus on off-target differentiation. The results showed that dexamethasone does induce osteogenic differentiation by inhibiting SOX9 expression, but not directly through RUNX2 upregulation as it is commonly thought. Rather, PPARG is concomitantly and strongly upregulated, leading to the formation of adipocyte-like cells within osteogenic cultures. Limiting the exposure to dexamethasone to the first week of differentiation did not affect the mineralization potential. Gene expression levels of RUNX2, SOX9, and PPARG were simulated using approximate Bayesian computation based on a simplified theoretical model, which was able to reproduce the observed experimental trends but with a different range of responses, indicating that other factors should be integrated to fully understand how dexamethasone influences cell fate. In summary, this work provides evidence that current in vitro differentiation protocols based on dexamethasone do not represent a good model, and further research is warranted in this field.

Combating drug resistance in acute myeloid leukaemia by drug rotations: the effects of quizartinib and pexidartinib

BACKGROUND

Acute myeloid leukaemia (AML) is an aggressive blood cancer. In approximately 30% of the cases, driver mutations in the FLT3 gene are identified. FLT3 inhibitors are used in treatment of such patients together with cytotoxic drugs or (in refractory AML) as single agents. Unfortunately, resistance to FLT3 inhibitors limits their efficacy. Resistance is often due to secondary mutations in the gene encoding the molecular target. The gatekeeper mutation F691L confers resistance to specific FLT3 inhibitors such as quizartinib, but pexidartinib is much less resistance to this mutation. Pexidartinib alone is however sensitive to many other resistance mutations. In chronic myeloid leukaemia (CML), it has been suggested that rotation between drugs with a different landscape of resistance mutations might postpone the emergence of resistance.

METHODS

We studied the effect of quizartinib and pexidartinib in AML cell lines that express FLT3 (MOLM-14 and MV4-11). Using a rotation protocol, we further examined whether the emergence of resistance could be postponed. Computational modelling was used to analyse the onset of resistance and suggest which mutations are most likely to occur in a quantitative fashion.

RESULTS

The cells were sensitive to both inhibitors but quickly developed resistance that could be inherited, suggesting a genetic origin. Rotation protocols were not useful to postpone the emergence of resistance, which implies that such protocols, or changing from pexidartinib to quizartinib (or vice-versa) should not be used in patients. The computational modelling led to similar conclusions and suggested that F691L is the most common mutation to occur with quizartinib, and also when both drugs are used in rotation.

CONCLUSIONS

AML patients are not likely to benefit from a quizartinib/pexidartinib rotation protocol. A combination of tyrosine kinase inhibitors (with different molecular targets) might be more useful in the future. Development of specific FLT3 inhibitors that are less sensitive to resistance mutations might also lead to a better outcome.

Pattern and Dynamics of FLT3 Duplications

FMS-like tyrosine kinase 3 (FLT3) is mutated in ∼30% of patients that suffer from acute myeloid leukemia (AML). In about 25% of all AML patients, in-frame insertions are observed in the sequence. Most of those insertions are internal tandem duplications (ITDs) of a sequence from the protein. The characteristics of such mutations in terms of length, sequence, and location were hitherto studied in different populations, but not in a comprehensive mutation database. Here, in-frame insertions into the FLT3 gene were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. These were analyzed with respect to the length, location, and sequence of the mutations. Furthermore, characteristic strings (sequences) of different lengths were identified. Mutations were shown to occur most often in the juxtamembrane zipper (JM-Z) domain of FLT3, followed by the hinge domain and first tyrosine kinase domain (TKD1), upstream of the phosphate-binding loop (P-loop). Interestingly, there are specific hot spot residues where insertions are more likely to occur. The insertions vary in length between one and 67 amino acids, with the largest insertions spanning the phosphate binding loop. Insertions that occur downstream of the P-loop are shorter. Our analysis further shows that acidic and aromatic residues are enriched in the insertions. Finally, molecular dynamics simulations were run for FLT3 with ITD insertions in the hinge and tyrosine kinase domains. On the basis of the findings, a mechanism is proposed for activation by ITDs, according to which there is no direct coupling between the length of the insertion and the activity of the mutated protein. The effect of insertions on the sensitivity of FLT3 to kinase inhibitors is discussed based on our findings.

The effects of combination treatments on drug resistance in chronic myeloid leukaemia: an evaluation of the tyrosine kinase inhibitors axitinib and asciminib

BACKGROUND

Chronic myeloid leukaemia is in principle a treatable malignancy but drug resistance is lowering survival. Recent drug discoveries have opened up new options for drug combinations, which is a concept used in other areas for preventing drug resistance. Two of these are (I) Axitinib, which inhibits the T315I mutation of BCR-ABL1, a main source of drug resistance, and (II) Asciminib, which has been developed as an allosteric BCR-ABL1 inhibitor, targeting an entirely different binding site, and as such does not compete for binding with other drugs. These drugs offer new treatment options.

METHODS

We measured the proliferation of KCL-22 cells exposed to imatinib-dasatinib, imatinib-asciminib and dasatinib-asciminib combinations and calculated combination index graphs for each case. Moreover, using the median-effect equation we calculated how much axitinib can reduce the growth advantage of T315I mutant clones in combination with available drugs. In addition, we calculated how much the total drug burden could be reduced by combinations using asciminib and other drugs, and evaluated which mutations such combinations might be sensitive to.

RESULTS

Asciminib had synergistic interactions with imatinib or dasatinib in KCL-22 cells at high degrees of inhibition. Interestingly, some antagonism between asciminib and the other drugs was present at lower degrees on inhibition. Simulations revealed that asciminib may allow for dose reductions, and its complementary resistance profile could reduce the risk of mutation based resistance. Axitinib, however, had only a minor effect on T315I growth advantage.

CONCLUSIONS

Given how asciminib combinations were synergistic in vitro, our modelling suggests that drug combinations involving asciminib should allow for lower total drug doses, and may result in a reduced spectrum of observed resistance mutations. On the other hand, a combination involving axitinib was not shown to be useful in countering drug resistance.

Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations

BACKGROUND

Network inference is an important aim of systems biology. It enables the transformation of OMICs datasets into biological knowledge. It consists of reverse engineering gene regulatory networks from OMICs data, such as RNAseq or mass spectrometry-based proteomics data, through computational methods. This approach allows to identify signalling pathways involved in specific biological functions. The ability to infer causality in gene regulatory networks, in addition to correlation, is crucial for several modelling approaches and allows targeted control in biotechnology applications.

METHODS

We performed simulations according to the approximate Bayesian computation method, where the core model consisted of a steady-state simulation algorithm used to study gene regulatory networks in systems for which a limited level of details is available. The simulations outcome was compared to experimentally measured transcriptomics and proteomics data through approximate Bayesian computation.

RESULTS

The structure of small gene regulatory networks responsible for the regulation of biological functions involved in biomining were inferred from multi OMICs data of mixed bacterial cultures. Several causal inter- and intraspecies interactions were inferred between genes coding for proteins involved in the biomining process, such as heavy metal transport, DNA damage, replication and repair, and membrane biogenesis. The method also provided indications for the role of several uncharacterized proteins by the inferred connection in their network context.

CONCLUSIONS

The combination of fast algorithms with high-performance computing allowed the simulation of a multitude of gene regulatory networks and their comparison to experimentally measured OMICs data through approximate Bayesian computation, enabling the probabilistic inference of causality in gene regulatory networks of a multispecies bacterial system involved in biomining without need of single-cell or multiple perturbation experiments. This information can be used to influence biological functions and control specific processes in biotechnology applications.