Selection Of Tyrosine Kinase Inhibitors Research Articles

FLT3 activating mutations display differential sensitivity to multiple tyrosine kinase inhibitors.

Fms-like tyrosine kinase-3 (FLT3) is a receptor tyrosine kinase that normally functions in hematopoietic cell survival, proliferation and differentiation. Constitutively activating mutations of FLT3 map predominately to the juxtamembrane domain (internal tandem duplications; ITD) or the activation loop (AL) of the kinase domain and are detected in about 1/3 of de novo acute myeloid leukemia (AML) patients. Small molecule tyrosine kinase inhibitors (TKI) effectively target FLT3/ITD mutations, but some activating mutations, particularly those on the AL, are relatively resistant to many FLT3 TKI. We reproduced many of the AL or other non-ITD activating mutations and tested 13 FLT3 TKI for their activity against these and wild-type FLT3. All 13 TKI tested inhibited BaF3/ITD cell proliferation in a concentration-dependent manner as reported, but most TKI exhibited a wide range of differential activity against AL and other point mutants. Western blotting results examining inhibition of FLT3 autophosphorylation and signaling pathways indicate that many AL mutations reduce TKI binding. Most FLT3 TKI effectively target wild-type FLT3 signaling. As a demonstration of this differential activity, treatment of BaF3 D835Y cells transplanted in BALB/c mice with sorafenib showed no effect in vivo against this mutant whereas lestaurtinib proved effective at reducing disease burden. Thus, while FLT3 TKI have been selected based on their ability to inhibit FLT3/ITD, the selection of appropriate TKI for AML patients with FLT3 AL and other activating point mutations requires personalized consideration.

Clinical Application of Artificial Intelligence in Patients with Chronic Myeloid Leukemia in Chronic Phase

▪IntroductionArtificial intelligence (AI) has been applied to a wide range of daily activities to assist in decision-making. Randomized clinical trials can compare the efficacy of treatment between patient groups. However, the best treatment decision for each individual patient, with their own clinical and biological features, and in the context of comparable treatment options, is more difficult to predict. The integrated consideration of various prognostic features can reach the point beyond human recognition. An AI-assisted approach may help with decision-making in complex clinical situations. The aim of this study is to introduce a prototype of AI to predict outcome such as achievement of major molecular response (MMR) within 1 year of the start of tyrosine kinase inhibitor (TKI).MethodsResponse data for 630 patients with newly diagnosed CML-CP in consecutive prospective clinical trials of frontline imatinib (n=73; NCT00048672), high-dose imatinib (n=208; NCT00038469 and NCT00050531), nilotinib (n=148; NCT00129740), dasatinib (n=150; NCT00254423), and ponatinib (n=51; NCT01570868) were analyzed. After multiple imputation for missing variables, neural network analysis with a multilayer perceptron model using the statistically significant variables by stepwise multivariate analysis was performed to predict the cumulative incidence of MMR within 1 year. The hyperbolic tangent and softmax activation function were used to create the architecture of hidden layers and output layers, respectively. Batch training with scaled conjugate gradient optimization algorithm with learning parameters (initial Lambda of 0.0000005, initial Sigma of 0.00005, interval center of 0, and interval offset of ±0.5) was used to train the neural network. To evaluate the accuracy of prediction, the entire cohort was randomly divided into training dataset (70%) and test dataset (30%). The correct prediction in the test dataset was repeatedly assessed 1,000 times to validate this approach. The whole cohort was subsequently used to create the AI model for MMR prediction, and was divided into two cohorts based on the prediction by the AI; AI-predicted response, and AI-predicted nonresponse. Hypothetical choice of TKI was assumed to rank the selection of TKI among imatinib 400 mg/day, imatinib 800 mg/day, dasatinib, nilotinib, and ponatinib to calculate the estimated percentage of MMR within 1 year for each patient. The Kaplan-Meier method with a log-rank test was used for failure-free survival (FFS), transformation-free survival (TFS), event-free survival (EFS), and overall survival (OS). To balance baseline patient characteristics between cohorts, propensity score matching after propensity score calculation by logistic regression was performed with nearest neighbor matching method with a caliper of 0.20. Exact matching was used for the type of cytogenetic, transcript, and TKI.ResultsOf 630 patients treated, 464 (74%) achieved MMR within 1 year. The stepwise multivariate analysis identified the selection of TKI, type of transcript, white blood cell count, albumin, and spleen size at diagnosis were the predictors for MMR within 1 year. Neural network analysis with a multilayer perceptron model is shown in figure 1. Through repeated random selection for training set (70%) and test set (30%), the mean correct prediction for MMR within 1 year was 77.4% (95% confidence interval [CI], 74.2-80.5), and 76.9% (95% CI, 71.4-82.3), respectively. Of 630 patients, the neural network model predicted 539 patients (86%) as responders, and 91 patients (14%) as nonresponders (table 1). Before propensity score matching, the AI-response cohort had higher rates of CCyR, MMR, MR4, MR4.5, and CMR as well as FFS, TFS, EFS, and OS compared to those of the AI-nonresponse cohort (figure 2). After propensity score matching, 25 patients in each cohort were identified, and the baseline differences were minimized (table 1). The AI-response cohort had higher rates of MMR, MR4, and FFS than those of AI-non-response cohort (figure 2).ConclusionAI with a multilayer perceptron model can predict target outcome. Incorporation of additional clinical and biological variables may improve the prediction rates to suggest the best treatment option in each patient with CML-CP. Such strategy is ongoing. [Display omitted] [Display omitted] [Display omitted] DisclosuresKantarjian:ARIAD: Research Funding; Bristol-Myers Squibb: Research Funding; Amgen: Research Funding; Pfizer Inc: Research Funding; Delta-Fly Pharma: Research Funding; Novartis: Research Funding. Jabbour:ARIAD: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Research Funding; BMS: Consultancy. Ravandi:BMS: Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding. Konopleva:AbbVie: Research Funding; Genentech: Research Funding. Wierda:Novartis: Research Funding; Abbvie: Research Funding; Acerta: Research Funding; Gilead: Research Funding; Genentech: Research Funding. Daver:Pfizer: Consultancy, Research Funding; Kiromic: Research Funding; BMS: Research Funding; Otsuka: Consultancy, Honoraria; Sunesis: Consultancy, Research Funding; Karyopharm: Honoraria, Research Funding; Ariad: Research Funding.

Severe Adverse Events By First Line Tyrosine Kinase Inhibitors Decrease Survival Rate in Patients with Newly Diagnosed Chronic Phase Chronic Myeloid Leukemia

Background: Chronic phase chronic myeloid leukemia (CML-CP) has become a manageable disease for most patients treated with tyrosine kinase inhibitors (TKIs). However, all TKIs have broad spectrum of toxic effects, and have to be managed by cessation, reduction and supportive care. The objective of this study is to analyze the adverse events (AEs) with different TKIs used as initial therapy for CML and their impact on outcome.Methods: We retrospectively evaluated a total of 494 patients with CML who received at least one TKI, imatinib, dasatinib, nilotinib and bosutinib in a practice setting between 2004 and 2014 at multicenter participating in the Hokkaido hematology study group.Results: Of the 494 patients (315 males and 179 females), with a median age of 59.5 years (range 2-93), imatinib, dasatinib or nilotinib were prescribed as the first line TKI in 283 (62.3%), 109 (24%) and 102 (22.5%) patients, respectively. Disease status at primary diagnosis was composed of chronic phase (450), accelerated phase (21) and blastic phase (23). With a median follow-up of 4.7 years in patients with CML-CP, the 5-year overall survival (OS), event-free survival (EFS) were 94.5% and 92.3%, respectively. The patients with complication or organ dysfunction (61/450, 13.6%) and age >60 (227/450, 50.4%) at diagnosis had significantly inferior OS (p= 0.0089 and p= 0.0012). The patients achieved higher rates of major molecular response (MMR) at 6 and 12 months after initial treatment with dasatinib, nilotinib vs imatinib (41.5%, 42.6% vs 12.5% and 54.3%, 54.5% vs 41.5%, p<.0001 and p<.0001), but final MMR rates were similar in dasatinib, nilotinib vs imatinib (70.2%, 70.3% vs 63.9%, p=0.179). Moreover, there were no significant differences in EFS and OS for specific TKIs (p= 0.345 and p= 0.458). Of the 450 patients with CML-CP, 312 treatment modifications after the first line TKI treatment were carried out: 144 (46.2%) TKI changes or definitive discontinuations, 60 (19.2%) dose reductions, 36 (11.5%) temporary discontinuations and 72 (23.3%) dose reductions after temporary discontinuation. The main reasons for the 312 treatment modifications were 254 AEs (81.4%) and 41 failure or progression (13.1%). After initial TKI treatment, 272 (60.4%), 118 (26.2%), 37 (8.2%) and 23 (5.1%) patients had no, 1, 2 and 3 TKI changes, respectively. However, the number of TKI changes was not related to OS and EFS (p= 0.574 and p= 0.267). In the first line TKI treatment, grade I-II and III-IV AEs occurred in 185 (41.1%) and 123 (27.3%) patients. AEs resulting in treatment modifications occurred in 142 (55.5%) patients for imatinib, 53 (53.5%) for nilotinib and 59 (62.1%) for dasatinib. Grade III-IV AEs in the first line TKI treatment was significantly correlated to inferior OS and EFS as compared with grade 0-II AEs (p= 0.00612 and p= 0.0014). Multivariate analyses confirmed the fact that grade III-IV AEs significantly predicted for inferior EFS and OS, HR=3.311, 95% CI 1.34-8.175 (p= 0.0094) and HR=3.096, 95% CI 1.4560-6.587 (p= 0.0033), respectively.Conclusions: Although long-term outcomes were similar in each TKI regardless of the first line TKI selection, severe AEs in the first line TKI treatment decreased survival rate of the patients with CML-CP. We need the personalized or some specialized treatment for elderly patients or patients with frailty. Early change of TKIs is recommended, when encountered with severe AEs of specific TKIs. DisclosuresNo relevant conflicts of interest to declare.

Evaluation of a tyrosine kinase peptide microarray for tyrosine kinase inhibitor therapy selection in cancer.

Personalized cancer medicine aims to accurately predict the response of individual patients to targeted therapies, including tyrosine kinase inhibitors (TKIs). Clinical implementation of this concept requires a robust selection tool. Here, using both cancer cell lines and tumor tissue from patients, we evaluated a high-throughput tyrosine kinase peptide substrate array to determine its readiness as a selection tool for TKI therapy. We found linearly increasing phosphorylation signal intensities of peptides representing kinase activity along the kinetic curve of the assay with 7.5–10 μg of lysate protein and up to 400 μM adenosine triphosphate (ATP). Basal kinase activity profiles were reproducible with intra- and inter-experiment coefficients of variation of <15% and <20%, respectively. Evaluation of 14 tumor cell lines and tissues showed similar consistently high phosphorylated peptides in their basal profiles. Incubation of four patient-derived tumor lysates with the TKIs dasatinib, sunitinib, sorafenib and erlotinib primarily caused inhibition of substrates that were highly phosphorylated in the basal profile analyses. Using recombinant Src and Axl kinase, relative substrate specificity was demonstrated for a subset of peptides, as their phosphorylation was reverted by co-incubation with a specific inhibitor. In conclusion, we demonstrated robust technical specifications of this high-throughput tyrosine kinase peptide microarray. These features required as little as 5–7 μg of protein per sample, facilitating clinical implementation as a TKI selection tool. However, currently available peptide substrates can benefit from an enhancement of the differential potential for complex samples such as tumor lysates. We propose that mass spectrometry-based phosphoproteomics may provide such an enhancement by identifying more discriminative peptides.

Assessment of Cardiovascular Events in Chronic Myeloid Leukemia Patients Treated with Tyrosine Kinase Inhibitors

▪Introduction: Treatment with tyrosine kinase inhibitors (TKIs) has dramatically increased the overall survival of patients with chronic myeloid leukemia (CML) but second generation TKI has been associated with an increased risk of cardiovascular events.Objectives: The aim of this study was to evaluate the incidence of cardiovascular adverse events (CVE) in CML patients treated with TKIs and to correlate with the cardiovascular (CV) risk of the patients.Methods: this is a retrospective analysis of consecutive CML patients treated with TKIs between 2005 and 2013at our Institution. Baseline risk factors for CV diseases were collected at baseline and included age, arterial hypertension (AH), dyslipidemia, obesity, hypothireoidism, smoking, diabetes mellitus (DM), coronary artery disease and chronic renal failure. Cardiovascular events during TKI treatment were collected and included: myocardial infarction, unstable angina, peripheral arterial disease, stroke, arrythmia,hypertension and cardiac failure. Cardiovascular risk was calculated using the SCORE chart of the European Society of Cardiology and patients were classified in low, moderate, high and very high risk.Results: We analyzed CML patients treated with imatinib (n=117), dasatinib (n=91) and nilotinib (n=60). The median time of follow-up was 748, 519 and 851 days, respectively. Baseline risk factors: 90 patients (38,5%) had hypertension, 34 (14,5%) DM, 67 (28,6%) dyslipidemia, 51 (21,8%) obesity, 22 (9,4%) hypothyroidism, 14 (6%) coronary arterial disease, 21 (9%) systolic cardiac dysfunction, 4 (1,7%) stroke, 20 (8,5%) chronic kidney failure and 36 (15,4%) were smokers. SCORE chart classification: 106 patients (39,5%) were in the low-risk category, 70 (26%) in the moderate risk, 46 (17,2%) in the high risk, 46 (17,2%) in the very high risk group. Overall, the cumulative incidence of CVE was 4.1%. Five (5.5%) events occurred during dasatinib treatment (P=0.015), 6 (10%) events during nilotinib and no events during imatinib treatment (P=0.001). The incidence of CVE was 10.8% in the high and very high-risk groups and 0.52% in moderate and low risk group (P≤0.001). The incidence of arterial ischemic events (AIE) was 10% (n=6) in patients treated with nilotinib, 2.2% (n=2) with dasatinib and 0% with imatinib (P≤0.001). Arterial events were exclusively observed in high and very high-risk groups (8 events, 8.7%) (P≤0.001). The risk factors associated with a higher risk of CVE were hypertension (P≤0.001), dyslipidemia (P≤0.001), coronary arterial disease (P=0.003), congestive heart failure (P=0.002) and chronic renal failure (P=0.011). Disease progression was the main cause of death in all groups.Conclusions: CVE were more frequent in patients treated with second generation TKIs. AIE were more frequent in patients treated with nilotinib, in those having a high or very high risk SCORE. The CV risk stratification of CML patients before and during TKI therapy can help in TKI selection and to identify patients at high risk, in order to reduce the morbidity and mortality associated with CVE. DisclosuresPagnano:Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol Miers-Squibb: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

Diagnosing and managing advanced chronic myeloid leukemia.

Clinical staging of chronic myeloid leukemia (CML) distinguishes between chronic phase (CP-CML), accelerated phase (AP-CML), and blastic phase (BP-CML), reflecting its natural history in the absence of effective therapy. Morphologically, transformation from CP-CML to AP/BP-CML is characterized by a progressive or sudden loss of differentiation. Multiple different somatic mutations have been implicated in transformation from CP-CML to AP/BC-CML, but no characteristic mutation or combination of mutations have emerged. Gene expression profiles of AP-CML and BP-CML are similar, consistent with biphasic evolution at the molecular level. Gene expression of tyrosine kinase inhibitor (TKI)-resistant CP-CML and second CP-CML resemble AP/BP-CML, suggesting that morphology alone is a poor predictor of biologic behavior. At the clinical level, progression to AP/BP-CML or resistance to first-line TKI therapy distinguishes a good risk condition with survival close to the general population from a disease likely to reduce survival. Progression while receiving TKI therapy is frequently caused by mutations in the target kinase BCR-ABL1, but progression may occur in the absence of explanatory BCR-ABL1 mutations, suggesting involvement of alternative pathways. Identifying patients in whom milestones of TKI response fail to occur or whose disease progress while receiving therapy requires appropriate molecular monitoring. Selection of salvage TKI depends on prior TKI history, comorbidities, and BCR-ABL1 mutation status. Despite the introduction of novel TKIs, therapy of AP/BP-CML remains challenging and requires accepting modalities with substantial toxicity, such as hematopoietic stem cell transplantation (HSCT).

Response to Miller et al: resistant mutations in CML and Ph(+) ALL - role of ponatinib.

Dear editor Miller et al1 recently reviewed the role of ponatinib in chronic myeloid leukemia (CML) and Philadelphia chromosome–positive acute lymphoblastic leukemia (Ph+ ALL), yet by the omission of an approved agent within the same class of drugs, provided an inaccurate summary of the current treatment landscape for CML. The authors discussed the evolution of tyrosine kinase inhibitor (TKI) treatment, beginning with imatinib approval in 2001, followed by the introduction of second- and third-generation TKIs, including dasatinib, nilotinib (both approved in the USA in 2010), and ponatinib (approved in the USA in December 2012). However, while citing all other approved TKIs, the authors did not discuss bosutinib (Bosulif®, Pfizer Inc., New York, NY, USA), a new second-generation TKI approved in the USA, in September 2012, for the treatment of patients with Ph+ CML who are resistant or intolerant to prior therapy, and in Europe, for Ph+ CML patients previously treated with one or more TKIs and for whom imatinib, nilotinib, and dasatinib are not appropriate choices. Bosutinib has manageable toxicity and acceptable tolerability; the most frequent adverse events observed are early-onset and generally low-grade gastrointestinal events, and with appropriate monitoring, the majority of patients are able to continue on therapy.2 Due to its potency3,4 and toxicity profile distinct from other TKIs2, bosutinib is an important option for CML therapy in the second-line and beyond. Mathisen et al recently reviewed the practical aspects of TKI selection for CML and highlighted bosutinib as a viable second- or third-line treatment option with an easy to manage toxicity profile.5 In order to gain a more comprehensive understanding of the role of ponatinib in the CML treatment landscape, we strongly recommend reading the articles referenced here.

Patients with Philadelphia-Positive Leukemia with BCR-ABL Kinase Mutations before Allogeneic Transplantation Predominantly Relapse with the Same Mutation

Despite the successes of tyrosine kinase inhibitors (TKIs) in improving outcomes in patients with chronic myeloid leukemia (CML) and Philadelphia-positive acute lymphoblastic leukemia (Ph + ALL), allogeneic hematopoietic stem cell transplantation (HSCT) continues to be an important and potentially curative option for selected patients with either disease. After HSCT, TKIs are increasingly being used to treat or prevent disease relapse, and practice patterns suggest that these TKIs are often chosen empirically without regard to pre-HSCT mutation status. We investigated whether ABL kinase domain mutations persist after transplantation and, thus, whether pre-HSCT mutation status should inform the selection of post-HSCT TKIs in these patients. We retrospectively analyzed adults who underwent allogeneic HSCT for CML and Ph + ALL at our institution between 2000 and 2010, and we identified subjects who had detectable BCR-ABL transcripts by polymerase chain reaction (PCR), as well as available RNA for Sanger sequencing of the ABL kinase domain, in both the pre- and post-HSCT settings. In total, 95 CML and 20 Ph + ALL patients with positive PCR transcripts were identified, of which 10 (10.5%) and 4 (20.0%), respectively, were found to have pre-HSCT ABL kinase mutations known to confer TKI resistance. In 9 (64.2%) of these 14 patients, the same kinase mutation was also detectable at an average time of 191 days after HSCT. Seven (50.0%) of the 14 harboring mutations had relapsed/refractory disease by last follow-up, of which, in retrospect, 6 had received a predictably ineffective TKI within the first 100 days after transplantation based on our mutation analysis. These data support the idea that pre-existing mutations in the ABL kinase domain, frequently associated with resistance to TKIs and prevalent in a transplantation population, are persistently detectable in the majority of patients after transplantation. We propose that such resistance patterns should be considered when selecting TKIs in the post-HSCT setting, including clinical trials of post-HSCT TKI prophylaxis.

Baseline Characteristics Of Patients With Chronic Myeloid Leukemia In a Prospective Observational Study (SIMPLICITY)

BackgroundOral BCR-ABL tyrosine kinase inhibitors (TKIs), including imatinib (IM), dasatinib (DAS) and nilotinib (NIL), have improved survival in chronic-phase chronic myeloid leukemia (CP-CML). Few data are available that compare TKIs in daily clinical practice across multiple regions. MethodsSIMPLICITY is an ongoing observational cohort study of adult patients with newly diagnosed CP-CML receiving first-line treatment with IM, DAS or NIL in the USA and Europe (Eu) outside of clinical trials (NCT01244750). The primary objective is to assess effectiveness of these TKIs in clinical practice. The study includes three ‘prospective' cohorts of patients treated with IM, DAS or NIL since 2010 (the study opened after first-line approval of all three TKIs) and a ‘historical' cohort treated with IM since 2008. Preliminary baseline demographics are presented for prospective cohorts. Results860 prospective patients (Eu: 32%, USA: 68%) were enrolled through June 20, 2013, receiving IM (n=399), DAS (n=229) or NIL (n=232). Median age at initiation of first-line TKI was 56 years, with significant differences in pairwise comparisons between DAS and IM and NIL and IM (Table). Demographics were consistent across cohorts. Only 30% of patients had Hasford or Sokal scores recorded. ECOG performance status (PS) was available in 54% of patients. The number of baseline comorbidities per patient (mean: 3.2 + 2.7) was balanced across cohorts; 51% of patients presented with ≥3 comorbidities. Patients in the IM cohort had a higher prevalence of gastrointestinal comorbidities (P=.006 and .007 for DAS vs IM and NIL vs IM, respectively), and the NIL cohort had a higher prevalence of musculoskeletal comorbidities than the DAS cohort (P=.015). The proportions of patients with cardiovascular comorbidities were 38%, 36% and 42% in the DAS, NIL and IM cohorts, respectively, consisting primarily of hypertension (31%) and hyperlipidemia (17%) (P>.05 across cohorts). Coronary artery disease was present in 9%, cardiac arrhythmias in 6%, myocardial infarction in 3% and peripheral arterial disease in 2% of patients. The proportion of patients with diabetes was 10%. Clinicians reported effectiveness as the most common reason for TKI selection; familiarity and cost were also cited as reasons for IM selection (P<.001 vs DAS and NIL). Comorbidities were not drivers of TKI selection in this analysis. ConclusionsThis is the first report from the prospective cohorts of SIMPLICITY. Demographics were consistent across cohorts. Overall, the SIMPLICITY population is older with potentially more comorbidities than patients enrolled in first-line clinical trials with restrictive inclusion criteria (NEJM 2003 348 994; NEJM 2010 362 2260; NEJM 2010 362 2251). Initial TKI selection does not appear to be driven by baseline comorbidity, rather by perceived effectiveness, cost and familiarity. Hasford/Sokal scores were not recorded in the majority of patients prior to starting first-line TKI therapy. Outcomes data are being collected across cohorts that will inform about a multi-region population treated outside clinical trials. Disclosures:Cortes:Ariad: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Teva: Consultancy, Honoraria, Research Funding. Hehlmann:Novartis: Consultancy; Bristol-Myers Squibb: Consultancy, Research Funding. Gambacorti-Passerini:Bristol-Myers Squibb: Consultancy; Pfizer: Honoraria, Research Funding. Goldberg:Bristol-Myers Squibb: Honoraria, Research Funding, Speakers Bureau; Novartis Oncology: Honoraria, Research Funding, Speakers Bureau; Ariad: Honoraria, Research Funding, Speakers Bureau. Khoury:Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Ariad: Honoraria; Teva: Honoraria. Mauro:Novartis Oncology: Consultancy, Honoraria, Research Funding; Ariad: Consultancy, Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Speakers Bureau. Michallet:Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria, Research Funding; MSD: Consultancy, Honoraria, Research Funding; Genzyme: Consultancy, Honoraria, Research Funding. Paquette:Ariad: Consultancy; Incyte: Consultancy, Honoraria; Novartis: Consultancy. Foreman:ICON Clinical Research: Employment, My employer ICON Clinical Research receives research funding from pharmaceutical companies including manufacturers of CML drugs Other. Mohamed:Bristol-Myers Squibb: Employment. Zyczynski:Bristol-Myers Squibb: Employment. Hirji:Bristol-Myers Squibb: Employment. Davis:Bristol-Myers Squibb: Employment.

Choosing the Best Second-Line Tyrosine Kinase Inhibitor in Imatinib-Resistant Chronic Myeloid Leukemia Patients Harboring Bcr-Abl Kinase Domain Mutations: How Reliable Is the IC50?

Development of drug resistance to imatinib mesylate in chronic myeloid leukemia (CML) patients is often accompanied by selection of point mutations in the kinase domain (KD) of the Bcr-Abl oncoprotein, where imatinib binds. Several second-generation tyrosine kinase inhibitors (TKIs) have been designed rationally so as to enhance potency and retain the ability to bind mutated forms of Bcr-Abl. Since the preclinical phase of their development, most of these inhibitors have been tested in in vitro studies to assess their half maximal inhibitory concentration (IC₅₀) for unmutated and mutated Bcr-Abl-that is, the drug concentration required to inhibit the cell proliferation or the phosphorylation processes driven by either the unmutated or the mutated forms of the kinase. A number of such studies have been published, and now that two inhibitors-dasatinib and nilotinib-are available for the treatment of imatinib-resistant cases, it is tempting for clinicians to reason on the IC₅₀ values to guess, case by case, which one will work best in patients harboring specific Bcr-Abl KD mutations. Here, we discuss the pros and cons of using this approach in TKI selection.

Predictability of the response to tyrosine kinase inhibitors via in vitro analysis of Bcr-Abl phosphorylation

It would be of great value to predict the efficacy of tyrosine kinase inhibitors (TKIs) in the treatment of individual CML patients. We propose an immunoblot system for detecting the phosphorylation of Crkl, a major target of Bcr-Abl, in blood samples after in vitro incubation with TKIs. When the remaining phosphorylated Crkl after treatment with imatinib was evaluated as the “residual index (RI)”, high values were found in accordance with imatinib resistance. Moreover, RI reflected the outcome of imatinib- as well as second generation TKIs with a high sensitivity and specificity. Therefore, this system should be useful in the selection of TKIs.