Tyrosine Kinase Inhibitors Response Research Articles

Peripheral blood quantitation of CD26 positive leukemic stem cells as a predictor of tyrosine kinase inhibitor response in chronic myeloid leukemia.

Leukemic stem cells (LSCs) are the transcriptionally low/silent cells which are resistant to the tyrosine kinase inhibitor. These have been found to play a pivotal role in disease relapse in chronic myeloid leukemia (CML) cases. The present study evaluated the correlation of absolute CML-LSC count in the peripheral blood (PB) at diagnosis and achievement of major molecular response (MMR) at 12 months in patients of CML-CP. This was a prospective, observational, non-interventional single center study including newly diagnosed adult (>18 yrs) CML-CP patients. Absolute CD26 + CML-LSC quantification was done by multiparametric flow cytometry. Patients were treated with Imatinib treatment and subsequently monitored at 3-month intervals for BCR::ABL transcript levels. MMR was defined as a BCR::ABL1 transcript level of less than 0.1% on international scale. A total of 89 patients were enrolled in the study out of which 40.5% achieved MMR at 12 months. There was a significant difference in the median absolute CML-LSC count of the patients who achieved MMR at 12 months as compared to those who did not (58.5 vs 368.1 cells/μL; p value <0.001). Using a ROC analysis, a count of <165.69 CML LSC/μL was identified to have a sensitivity of 83.8% and specificity of 72.4%, in predicting the MMR at 12 months. Absolute CML-LSC count at diagnosis in the PB predicts the MMR achievement at 12 months. An absolute count of less than 165 cells/μL is highly predictive of achieving MMR at 12 months.

Analysis of Response and Progression Patterns of Tyrosine Kinase Inhibitors in Recurrent or Metastatic Adenoid Cystic Carcinoma: A Post Hoc Analysis of Two KCSG Phase II Trials.

In this study, we evaluated 66 patients diagnosed with adenoid cystic carcinoma (ACC) enrolled in two Korean Cancer Study Group trials to investigate the response and progression patterns in recurrent and/or metastatic ACC treated with vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFR-TKIs). We evaluated 66 patients diagnosed with ACC who were enrolled in the Korean Cancer Study Group trials. The tumor measurements, clinical data, treatment outcomes, and progression patterns of therapy were analyzed. In the 66 patients (53 receiving axitinib and 13 receiving nintedanib), the disease control rate was 61%, and 3 patients achieved partial response. The median follow-up, median progression-free survival (PFS), overall survival, and 6-month PFS rate were 27.6, 12.4, and 18.1 months and 62.1%, respectively. Among 42 patients who experienced progression, 27 (64.3%) showed target lesion progression. Bone metastasis was an independent poor prognostic factor. Overall, most patients demonstrated stable disease with prolonged PFS; however, prominent target lesion progression occurred in some patients. Thus, PFS may capture VEGFR-TKI efficacy better than the objective response rate.

Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction.

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

Tyrosine kinase inhibitor response of ABL-class acute lymphoblastic leukemia: the role of kinase type and SH3 domain

AbstractAcute lymphoblastic leukemia (ALL) with fusions of ABL-class tyrosine kinase genes other than BCR::ABL1 occurs in ∼3% of children with ALL. The tyrosine kinase genes involved in this BCR::ABL1-like (Ph-like) subtype include ABL1, PDGFRB, ABL2, and CSF1R, each of which has up to 10 described partner genes. ABL-class ALL resembles BCR::ABL1-positive ALL with a similar gene expression profile, poor response to chemotherapy, and sensitivity to tyrosine kinase inhibitors (TKIs). There is a lack of comprehensive data regarding TKI sensitivity in the heterogeneous group of ABL-class ALL. We observed variability in TKI sensitivity within and among each ABL-class tyrosine kinase gene subgroup. We showed that ALL samples with fusions for any of the 4 tyrosine kinase genes were relatively sensitive to imatinib. In contrast, the PDGFRB-fused ALL samples were less sensitive to dasatinib and bosutinib. Variation in ex vivo TKI response within the subset of samples with the same ABL-class tyrosine kinase gene was not associated with the ALL immunophenotype, 5′ fusion partner, presence or absence of Src-homology-2/3 domains, or deletions of IKZF1, PAX5, or CDKN2A/B. In conclusion, the tyrosine kinase gene involved in ABL-class ALL is the main determinant of TKI sensitivity and relevant for specific TKI selection.

The Contemporary Role of Hematopoietic Stem Cell Transplantation in the Management of Chronic Myeloid Leukemia: Is It the Same in All Settings?

Hematopoietic stem cell transplantation (HSCT) for chronic myeloid leukemia (CML) patients has transitioned from the standard of care to a treatment option limited to those with unsatisfactory tyrosine kinase inhibitor (TKI) responses and advanced disease stages. In recent years, the threshold for undergoing HSCT has increased. Most CML patients now have life expectancies comparable to the general population, and therefore, the goal of therapy is shifting toward achieving treatment-free remission (TFR). While TKI discontinuation trials in CML show potential for achieving TFR, relapse risk is high, affirming allogeneic HSCT as the sole curative treatment. HSCT should be incorporated into treatment algorithms from the time of diagnosis and, in some patients, evaluated as soon as possible. In this review, we will look at some of the recent advances in HSCT, as well as its indication in the era of aiming for TFR in the presence of TKIs in CML.

Correlation analysis of bone marrow microvessel density and miRNA expression on drug resistance in patients with chronic myelogenous leukemia after tyrosine kinase inhibitor treatment

ABSTRACT Objective: This study analyzed the relationship between bone marrow microvessel density (MVD) and the expression of four miRNAs with chronic myelogenous leukemia (CML) resistance after tyrosine kinase inhibitor (TKI) treatment. Methods: 234 CML patients were divided into resistance and non-resistance groups in terms of the results of the 5-year follow-up. Patients were divided into the Optimum response group and the Warning/Failure group based on TKI response. MVD was determined by immunohistochemistry, and the expression levels of four miRNAs (miR-106a, miR-155, miR-146a, and miR-340) in bone marrow biopsy specimens were examined by qPCR. We evaluated the association of MVD with four miRNAs and them predictive value for CML resistance after TKI treatment. Results: The MVD and the levels of miR-106a, miR-155, and miR-146a were significantly higher while the miR-340 level was lower in the resistance group than the non-resistance group. Besides, MVD had a significant correlation with the levels of miR-340 and miR-155. According to the results of survival analysis, MVD as well as miR-340 and miR-155 levels were observably correlated with 5-year survival of patients without TKI resistance. The results of the ROC curve indicated that the MVD, miR-106a, miR-340, and miR-155 had good predictive accuracy for CML resistance after TKI treatment. As for the results of multivariate analysis, disease stage, risk level (high risk), high MVD, low miR-340 expression, and high miR-155 expression were all independent risk factors for CML resistance. Conclusion: MVD and the expression of miR-340 and miR-155 are closely associated with CML resistance after TKI treatment.

Abstract C158: Predicting TKI responses in PDGFRA-mutant gastrointestinal stromal tumor

Abstract Gastrointestinal stromal tumor (GIST) is the most common sarcoma and frequently harbor oncogenic mutations in the receptor tyrosine kinases KIT or platelet derived growth factor receptor alpha (PDGFRA). Imatinib, a type II tyrosine kinase inhibitor (TKI), can successfully treat many KIT-mutant GIST. Yet, it is generally regarded as less effective against PDGFRA-mutant GIST because patients with the most common mutation, exon 18 D842V, are clinically resistant to imatinib and other GIST type II TKIs. However, there are many other PDGFRA mutations reported in GIST whose imatinib sensitivity is unknown. We curated mutation data from a large cohort of PDGFRA-mutant GIST patients, and over 80% had exon 18 mutations. Many mutations clustered around residues 840-849 and included non-D842V point mutations or complex indels. We previously biochemically profiled some of these frequently observed mutations and showed that some were imatinib sensitive, and that sensitivity was dependent on the properties of the 842-codon residue. As modeling each clinically reported mutation is not feasible, we hypothesized that imatinib sensitivity of PDGFRA exon 18 mutations could be predicted based on the 842 residue. To test our hypothesis, we created individual Ba/F3 cell lines that expressed individual PDGFRA mutant kinases, with one cell line each for every amino acid substitution at the 842 residue. Cells underwent transformation limiting dilution assays and imatinib sensitivity was determined via immunoblotting for phosphorylated and total PDGFRA. We observed that 13 out of the 20 amino acids conferred imatinib sensitivity when in the 842-codon position. 7 out of 8 hydrophobic residues conferred imatinib resistance (IC50&amp;gt;150nM) and all amino acids from other classes (polar, negative charge, positive charge, special case) conferred sensitivity (IC50&amp;lt;150nM). Alanine conferred imatinib sensitivity, despite being hydrophobic. Previous studies describe that imatinib resistance seen in D842V patients is due to PDGFRA structural changes. Therefore, we are currently performing molecular simulations and drug docking studies with our mutant kinases to understand how changes at the 842 position effect kinase structure and imatinib binding. Our predictions will identify patients that would benefit from imatinib therapy, while identifying those that require avapritinib. Avapritinib was recently FDA-approved for first-line treatment of all PDGFRA exon 18 mutation GIST, although it was initially created to target D842V. In Europe, avapritinib is only approved for D842V patients. Identifying non-D842V patients that either require avapritinib or could benefit from imatinib is crucial, as current guidelines may suggest no treatment at all. Also, eligible patients treated with imatinib first have additional treatment options if they progress, but this avenue is not available for those progressing on avapritinib. Using our work to support this paradigm shifting approach to optimize TKI treatment sequencing for PDGFRA-mutant GIST will transform patient care and clinical outcomes. Citation Format: Homma M Khosroyani, Ajia Town, Johanna Falkenhorst, Sebastian Bauer, Michael Heinrich. Predicting TKI responses in PDGFRA-mutant gastrointestinal stromal tumor [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C158.

Identification of Multivariable microRNA and Clinical Biomarkers Panels to Predict Imatinib Response in Chronic Myeloid Leukemia at Diagnosis

Imatinib Mesylate (IM) was once hailed as the magic bullet for chronic myeloid leukemia (CML) and remains a front-line therapy for CML to this day alongside other tyrosine kinase inhibitors (TKIs). However, TKI treatments are rarely curative and while they demonstrate efficacy in managing the disease, patients are often required to receive life-long treatment or risk experiencing relapse. Patients also frequently harbor innate TKI-resistance mechanisms to front-line IM therapy and without prior screening, patients can spend precious months on non-optimal treatment before transitioning to other therapeutic strategies. Thus, there is a growing interest in studying biomarkers in patients which can predict TKI response upon diagnosis. CML has unique microRNA (miRNA) expression profiles at different stages of the disease and in response to TKI-treatment. We previously generated global transcriptome profiles on treatment-naïve CD34 + CML cells with known subsequent imatinib (IM) responses and identified several differentially expressed miRNAs in IM-nonresponders as compared to IM-responders. We also reported that IM response could be predicted in treatment-naïve CD34 + cells by an in vitro colony forming cell (CFC) assay. Additionally, we previously analyzed patient data from the ENESTxtnd clinical trial to show that miRNA expression combined with CFC output data could accurately predict Nilotinib response in patients. In this study, we used a Cox Proportional Hazard (CoxPH) analysis to identify 22 out of a pool of 35 pre-validated miRNAs which were associated with IM nonresponse in CD34 + CML cells of 80 patients at diagnosis. These patients were later classified as IM-responders or IM-nonresponders based on the latest European LeukemiaNet (ELN) guidelines. Interestingly, a Welch t-test revealed 16 of these 22 IM-response associated miRNAs to be differentially expressed between IM-responders and IM-nonresponders. Between IM-responders and IM-nonresponders we also found 7 clinical parameters that were associated with IM-response of which 3 matched parameters had significantly different values including CFC assay outputs ( p=0.0015), Sokal scores ( p=0.0070) and white blood cell counts (WBC, p=0.0028). We then trained a machine learning model employing the random-forest (RF), gradient-boosting (GBM) and naïve-bayes (NB) algorithms with different combinations of the 16 miRNAs with and without the clinical parameters of these patients to identify panels with high predictive performance based on area-under-curve (AUC) values of receiver-operating-characteristic (ROC) and precision-recall (PR) curves. Notably, the multivariable panel consisting of both miRNAs and clinical features (AUC-ROC RF=0.83, GBM=0.83, NB=0.84, AUC-PR RF=0.68, GBM=0.67, NB=0.70) performed better than either miRNA (AUC-ROC RF=0.72, GBM=0.73, NB=0.78, AUC-PR RF=0.49, GBM=0.51, NB=0.4) or clinical (AUC-ROC RF=0.82, GBM=0.84, NB=0.84, AUC-PR RF=0.64, GBM=0.67, NB=0.64) panels alone. Interestingly, 2 miRNAs in this panel, miR-185 and miR-145, were also significant classifiers for our Nilotinib predictive study suggesting that expression patterns of these miRNAs may have predictive properties for multiple TKI responses. Thus, we show that predictive accuracy of biomarkers may be supplemented by inclusion of multivariable parameters, and our findings may inform future studies on developing predictive panels for more optimized treatment plans in the clinic.

The Impact of Pausing Bruton Tyrosine Kinase Inhibitor Therapy and Responsiveness of Vaccination in Blood Cancer Patients: Primary Outcome Result for the Randomised Improve Trial

Background: Patients with CLL have profound immunosuppression, higher mortality rates from COVID-19 infection and poorer responses to vaccination. Patients taking continuous Bruton Tyrosine Kinase inhibitor (BTKi) therapy demonstrate the poorest responses to vaccination, despite booster COVID-19 doses. BTKi therapy is taken continuously and is non-selective, inhibiting B cell receptor signalling in healthy B cells, as well as CLL cells. As covalent BTKi therapies have a short half-life and BTK receptor occupancy increases on stopping drug, a temporary pause in BTKi around the time of vaccination may improve immunity. Aim: To assess whether a temporary three-week pause of daily BTKi treatment around COVID-19 vaccination improves the immune response in people with Chronic Lymphocytic Leukaemia (CLL) whilst maintaining disease control. Methods: Patients with CLL in CR/stable PR taking either acalabrutinib or ibrutinib for 1 year or more were recruited to the open-label, prospective, 2-arm, parallel group, multicentre IMPROVE trial (ISRCTN 14197181) at 11 NHS UK hospital sites, prior to their COVID-19 booster vaccination. Participants were randomised (1:1) to either pause BTKi therapy for 3 weeks, starting 6 days before vaccination, or to continue BTKi therapy as usual. Researchers doing the laboratory analyses were blinded to group assignment. The primary outcome was SARS-CoV-2 Spike receptor binding domain (RBD) antibody titres 3 weeks after receiving the COVID-19 booster vaccine dose, assessed in the intention-to treat population. Results: Between Oct 10, 2022 and June 30, 2023, 99 participants with CLL were randomly assigned to continue BTKi (n=49) or pause BTKi (n=50). Mean age of participants was 70.5 years and 71/99 (72%) were male. 63/99 (64%) were on first line CLL therapy, and 51 (52%) were taking Ibrutinib, with the remaining participants taking Acalabrutinib. Participants had a median of 6 previous COVID-19 vaccinations prior to their booster (IQR 4-6). 84 (85%) were given the Bivalent Pfizer booster vaccination, 6 (6%) the Moderna Bivalent, 7 (7%) Sanofi, 1 (1%) unknown and 1 (1%) did not receive a vaccination. The proportion of participants deficient in IgG (&amp;lt;6 g/L); IgA (&amp;lt;0.8g/L) and IgM (&amp;lt;0.6g/L) were similar in both groups at baseline. At baseline, the geometric mean anti-spike RBD antibody titre was 71.6 U/mL (SD 101.3) in the suspend BTKi group and 132.9 U/mL (SD 82.2) in the continue BTKi group. The numbers of participants with no prior response to vaccination (≤ 0.4 U/mL) were 18/50 (36%) in the pause BTKi group and 14/49 (29%) in the continue BTKi group. After 3 weeks, 5/47 (11%) in the pause group and 1/48 (2%) in the continue group, seroconverted. The geometric mean anti-spike RBD antibody titre at 3 weeks was 150.4 U/mL (SD 100.9) in the suspend BTKi group and 151.8 U/mL (SD 109.6) in the continue BTKi group, with a geometric mean ratio (GMR) of 1.830 (95% CI 0.820 - 4.083; p = 0.140; mixed-effects model). There were no intervention-related serious adverse events reported. 4 patients withdrew from study. 2 patients in the pause arm and no patients in the continue arm sought NHS advice during the 3 week vaccination period. 2 patients in the pause arm and 1 patient in the continue arm commenced steroids during the 3 week period. No difference was observed in full blood count parameters between baseline and 3 weeks' in the 2 arms. LDH levels were 191.4 (SD 44.6) and 196.5 (SD 47.4) at baseline and 195.7 (SD 81.8) and 217 (SD 99.7) at 3 weeks' in continue Vs pause arm respectively. Participants self-reported no new or swollen lymph nodes at baseline in either arm, but 4 (8%) reported new or swollen lymph nodes in the pause arm compared with 0 in the continue arm. Compliance was self-reported; 48/49 in the continue group and 47/50 in suspend group confirmed compliance to allocated arm. Interpretation: A 3 week interruption in BTKi around the time of vaccination may improve seroconversion rates in people with CLL but does not boost antibody titre responses overall. Further analysis of secondary endpoints including neutralisation and cellular immunity is ongoing.

Mutation of Epigenetic Regulators at Diagnosis Is an Independent Predictor of Tyrosine Kinase Inhibitor Treatment Failure: A Report from the Residiag Study

Introduction Additional mutations at chronic myeloid leukemia (CML) diagnosis have been shown to variably affect tyrosine kinase inhibitor (TKI) response and were inconstantly detected at loss of response. Contradictory observations may have resulted from difficulties in reliably inferring CML clonal architecture from mutations quantified by NGS, BCR::ABL1 by qRT-PCR, ABL1-TK by RNA-Seq. The RESIDIAG study was designed to identify at diagnosis molecular markers predictive of TKI treatment failure and analyze the clonal dynamics using asymmetric capture sequencing (aCAP-Seq). Methods DNA samples from 60 TKI responders (median follow-up: 7.1 years) were sequenced at diagnosis by aCAP-Seq, allowing quantification and breakpoint sequencing of genomic BCR::ABL1 fusion together with 43 myeloid genes, including ABL1 with a limit of detection of ~0.1% for BCR::ABL1 and 0.5-1% for SNVs and Indels. In parallel, CML patients who experienced treatment failure (ELN 2020) were sequentially analyzed at diagnosis and at failure (n=53), at diagnosis only (n=1), and at failure only (n=3). Small deletions and BCR::ABL1 breakpoints were analyzed to search for microhomology-mediated end-joining (MMEJ) repair signatures. Mutation analysis followed strict medical standards. Results The proportion of patients receiving imatinib at diagnosis wasn't statistically different (p=0.08; Pearson's Chi-square test) between responders (70%) and the failure group (56%). At diagnosis, the number of mutations was higher (p&amp;lt;0.001, t-test with Welch correction) in the failure group (0.9±0.1) as compared with responders (0.18± 0.05). ASXL1, DNMT3A, and TET2 were more frequently mutated at diagnosis in the failure group (38.6%, p&amp;lt;0.001; 10.5%, p=0.01, and 4.3%, p=0.025 respectively; Pearson's Chi²test) as compared with responders (6.7%, 0% and 0% respectively) and the presence of a mutation in one of these genes was highly associated with a reduced failure-free survival (p&amp;lt;0.001, Log-ranked test, Figure 1). An MMEJ signature at BCR::ABL1 breakpoints was more frequent (p=0.014, Pearson's Chi² test) in the failure group (29.1%) than in the responder group (9.1%). and was significantly associated with the ELTS score (p=0.005, Pearson's Chi² test) but not the Sokal score (p=0.017, Pearson's Chi² test). At first failure, 69% of patients had additional mutations in ASXL1 (39%), ABL1-TK (38%), DNMT3A (18%), or TET2 (15%), while other genes were rarely (&amp;lt;5%) mutated. ASXL1 mutations found at diagnosis were still detectable in 18/22 patients at failure and VAF suggested that double mutant BCR::ABL1/ ASXL1 clones were driving TKI failure with or without BCR:: ABL1 tyrosine kinase domain mutation (TKD). ASXL1 mutations disappearing upon treatment were mostly at low frequency &amp;lt;5% at diagnosis and thus possibly not clonally related to CML. Furthermore, a stepwise selection of variables followed by multivariate analysis with the Fine-Gray model identified the age of patients (sdHR [95% C.I.] = 0.99 [0.97-1.00]; p=0.08) and the presence of a mutation in epigenetics regulators at diagnosis as factors affecting the onset of TKD mutations (sdHR = 3.01 [1.76-5.15]; p&amp;lt;0.001). Intriguingly, co-occurring mutations in DNMT3A and TET2 were found in five patients at TKI failure. Their allelic frequency kinetics suggested that these belonged to the same clone driving CML relapse in 4/5 CML patients, while one patient also had a TKD mutation likely involved in CML relapse. Finally, multivariate COX regression analysis identified two independent predictors of TKI failure at diagnosis: a high-risk ELTS score (p=0.001; hazard ratio=3.42 [1.62-7.22] with low-risk as baseline) and a mutation in ASXL1, DNMT3A or TET2 (p=0.002; hazard ratio=2.87 [1.49-5.51]). Conclusion Altogether these results strongly point to the contribution of epigenetic regulator mutations in the emergence of TKI failure in CML and warrant further biological studies to better understand the underlying mechanisms

New Pattern of Emerging Somatic Mutations in Optimal Responders Following Tyrosine Kinase Inhibitor Therapy in Chronic Myeloid Leukemia Patients Evidenced from Mutational Kinetic Analysis Based on Pairwise Comparison

Introduction Recent advances in genomics in chronic myeloid leukemia (CML) patients (pts) provide new insights in understanding somatic mutation (SM) and their prognostic implications following tyrosine kinase inhibitor (TKI) therapy. DNMT3A, TET2, or ASXL1 (DTA) mutations are most frequently detected following TKI therapy and have adverse prognosis. Five longitudinal patterns of changes in SM after TKI therapy were suggested with its clinical significance (Kim, Blood 2017): Pattern 1, persistent mutation burden despite optimal TKI response; Pattern 2, emerging mutation which correlates with TKI resistance/CML progression; Pattern 3, mutational clearance with mixed clinical outcomes; and Pattern 4 and 5 having some mutation in germline control as well as CML cells. Clonal evolution (CE) in Philadelphia negative (Ph -) clone is found in up to 10% of CML pts who respond to TKI therapy optimally but develop +8 or -7 changes in Ph - clone. This is diagnosed only by metaphase cytogenetic test on bone marrow samples. Alternatively, fluorescence in situ hybridization (FISH) test can be used. With recent advances in next-generation sequencing (NGS), we hypothesize that SM profiling can capture a clone carrying a SM in the Ph - population. We sequenced and analyzed mutation profiles in paired samples taken prior to TKI therapy and at longitudinal follow-up. Patients and methods The present study adopted single molecule-tagging and molecular inversion probe (smMIP)-based sequencing methods to analyze the DNA extracted from the mononuclear cell fraction of peripheral blood samples collected from CML pts at initial diagnosis and during follow-up. While conventional NGS has a relatively high intrinsic sequencing error rate and is limited in detecting mutations with a variant allele frequency (VAF) of less than 2%, smMIP-based sequencing overcomes this issue by tracking all sequence reads from a single strand and can detect mutations with a limit of detection up to 0.1%. The in-house CML-specific smMIP panel used in this study included 40 genes with 332 amplicon probes covering genes involved in epigenetic modifiers, activation signaling, myeloid transcription factor, spliceosome, tumor suppressor, cohesion, and miscellaneous functions. To evaluate kinetics of mutations, we calculated doubling time of mutations. Using the mutational VAFs from 2 time points, t1 and t2, the doubling time was calculated according to the following equation: = (-2 -1) log(2) /log(-2) - log(-1), where VAF1 and VAF2 is the VAF of the mutant at time points t1 and t2, respectively. Results We performed targeted deep sequencing on a total of 119 serial samples from 51 CML pts (median of 405.5 days following TKI therapy). 41 pts had an optimal response, 7 were non-responders, and 3 were non-evaluable for response. Pattern 2 was observed in 1 of 7 non-responders. In 12 pts pattern 3 (mutation clearance with mixed clinical outcomes) was observed. 22 pts carried 36 mutations. At baseline 9 pts had somatic mutations. Emergence of somatic mutations in optimal responders was observed in 13 out of total 51 (25%) pts, with DNMT3A (n=5), TET2 (n=4), ASXL1 (n=4), and EZH2 (n=2). While JAK2, SF3B1, U2AF1, PHF6, TP53, BRAF, and CBL were observed in one patient each (Figure 1). Particularly, those with emerging DTA mutation were all optimal responders to TKI therapy. This pattern of mutational change is novel and has never been described before. The median doubling time was 77 days (range 21-1909 days) in the group with emergence of somatic mutation in follow-up samples. The doubling time was 56.1, 93.7, 74.8 days in DNMT3A, ASXL1, and TET2 mutations, respectively. Based on kinetics of mutations (doubling time), to capture 10-fold increase (i.e. 1 log increase) of certain mutation, NGS profile can be monitored every 6-7 months. This pattern of emergence of mutations (mostly DTA mutation) in pts responding optimally to TKI therapy is new and does not fit into the five patterns mentioned in our previous paper (Kim, Blood 2017). Thus, we propose this sixth novel pattern called “Emerging mutational clones in CML pts responding optimally to TKI therapy”. Conclusion We suggest a new pattern of emerging mutations in optimal responders to TKI therapy, which could derive from expansion of Ph- clone carrying some clones with emerging mutations. Longitudinal NGS monitoring in CML patients is feasible with frequency every 6-7 months.

EXTH-82. THE ROLE OF PTEN AND EPIGENETIC KINOME PROGRAMMING IN EGFR TKI RESPONSE IN GLIOBLASTOMA

Abstract Glioblastoma (GBM) is the most common brain tumor and standard therapy only extends survival from 12 to 15 months. The receptor tyrosine kinase EGFR is altered in ~60% of GBM, resulting in aberrant activation of downstream pathways, including PI3K, that potentiate tumorigenesis. Though EGFR targeting has been successful in other cancers, clinical trials with EGFR tyrosine kinase inhibitors (TKI) have failed in GBM, in part due to resistance. Trial results suggested that the most common oncogenic EGFR variant, EGFRvIII (vIII), and negative regulator of PI3K signaling, PTEN, were biomarkers of response. To dissect the role of PTEN in GBM tumorigenesis and EGFR TKI response, we utilized vIII-expressing mouse astrocytes with and without functional Pten. Pten loss potentiated tumorigenesis in vitro and in vivo, as proliferation and stemness were significantly increased, and mouse survival was decreased upon implantation as orthoptic allografts. Both RNA-seq and proteomic analysis using multiplex inhibitor beads with mass spectrometry (MIB-MS) showed significantly altered kinome profiles. Pten deleted cells were 5-fold more sensitive to the EGFR TKI neratinib, a drug that induced Pten-dependent modulation of the kinase transcriptome over 48h. This acute transcriptional adaptation implies alteration of the epigenetic landscape. We hypothesized that disruption of enhancer dynamics via BET bromodomain inhibition would improve EGFR TKI durability. We found that cells expressing Pten were 10-fold more sensitive to multiple BET inhibitors, including JQ1, birabresib, and molibresib, and these inhibitors synergized with neratinib to reduce proliferation only in the Pten wild type model. Ongoing work is focused on defining the role of PTEN in maintenance of differential transcriptional and epigenetic programs. We will explore potential mechanistic roles of both the enzymatic and non-enzymatic functions of Pten and characterize its effect on hallmark cancer phenotypes such as proliferation, stemness/self-renewal, and tumorigenesis in the presence and absence of EGFR ± BET inhibitors.

Identification of multivariable microRNA and clinical biomarker panels to predict imatinib response in chronic myeloid leukemia at diagnosis.

Imatinib Mesylate (imatinib) was once hailed as the magic bullet for chronic myeloid leukemia (CML) and remains a front-line therapy for CML to this day alongside other tyrosine kinase inhibitors (TKIs). However, TKI treatments are rarely curative and patients are often required to receive life-long treatment or otherwise risk relapse. Thus, there is a growing interest in identifying biomarkers in patients which can predict TKI response upon diagnosis. In this study, we analyze clinical data and differentially expressed miRNAs in CD34+ CML cells from 80 patients at diagnosis who were later classified as imatinib-responders or imatinib-nonresponders. A Cox Proportional Hazard (CoxPH) analysis identified 16 miRNAs that were associated with imatinib nonresponse and differentially expressed in these patients. We also trained a machine learning model with different combinations of the 16 miRNAs with and without clinical parameters and identified a panel with high predictive performance based on area-under-curve values of receiver-operating-characteristic and precision-recall curves. Interestingly, the multivariable panel consisting of both miRNAs and clinical features performed better than either miRNA or clinical panels alone. Thus, our findings may inform future studies on predictive biomarkers and serve as a tool to develop more optimized treatment plans for CML patients in the clinic.

BCR::ABL1 kinase domain mutation testing and clinical outcome in a nationwide chronic myeloid leukemia patient population.

Acquired missense mutations in the BCR::ABL1 kinase domain (KD) may cause tyrosine kinase inhibitor (TKI) treatment failure. Based on mutation-specific in vitro derived IC50-values, alternative TKI may be selected. We assessed clinical practice of BCR::ABL1 KD mutation testing, clinical response in relation to IC50-values, and clinical outcome of tested patients. Patients from six Dutch CML reference centers and a national registry were included once a mutational analysis was performed. Reasons for testing were categorized as suboptimal TKI response, and primary or secondary TKI resistance. Four hundred twenty analyses were performed in 275 patients. Sixty-nine patients harbored at least one mutation. Most analyses were performed because of suboptimal TKI response but with low mutation incidence (4%), while most mutations were found in primary and secondary resistant patients (21% and 51%, respectively). Harboring a BCR::ABL1 mutation was associated with inferior overall survival (HR 3.2 [95% CI, 1.7-6.1; p < .001]). Clinically observed responses to TKI usually corresponded with the predicted TKI sensitivity based on the IC50-values, but a high IC50-value did not preclude a good clinical response per se. We recommend BCR::ABL1 KD mutation testing in particular in the context of primary or secondary resistance. IC50-values can direct the TKI choice for CML patients, but clinical efficacy can be seen despite adverse in vitro resistance.

Chromosomal Copy Number Variation Predicts EGFR-TKI Response and Prognosis for Patients with Non-Small Cell Lung Cancer.

Chromosomal abnormalities represent genomic signatures linked to cancer prognosis and responses to chemotherapy, immunotherapy, and drug resistance. This study aimed to investigate the impact of chromosome copy number variants (CNVs) on the efficacy of tyrosine kinase inhibitors (TKIs) in EGFR-mutated non-small cell lung cancer (NSCLC) patients, as well as its prognostic implications for progression-free survival (PFS) and overall survival (OS) in EGFR wild-type patients. A total of 110 patients with advanced NSCLC were enrolled in this study and categorized into EGFR-mutated and wild-type groups. Utilizing next-generation sequencing (NGS) technology, we assessed 24 genes and chromosome CNVs associated with lung cancer pathways in patients' tissue samples. Within the EGFR-mutated group, patients with a gain in Chr 1p13.3-p13.1 exhibited poor TKI responses, a high relapse rate, and shortened PFS (P = 0.002). Conversely, EGFR-mutated patients with a gain in 14q31.1-q31.3 demonstrated favorable TKI responses and relatively extended PFS (P = 0.005). Among EGFR wild-type patients, the presence of 7q31.1-q31.31 CNV emerged as an independent factor influencing both PFS and OS (P = 0.013, P = 0.004). Notably, patients with a gain in 7q31.1-q31.31 exhibited prolonged PFS and OS. Additionally, independent prognostic significance for OS in EGFR wild-type patients was observed for CNVs in 9q21.31-q22.2 and 11p11.11-q12.1 regions (P = 0.001). Patients with gains in these regions experienced extended OS, while losses were predictive of poorer outcomes. Our results suggested that chromosomal copy number variation is a practical indicator for predicting the response of EGFR-targeted therapy and prognosis for NSCLC patients.

Effect on outcomes of toxicity-related dose reduction in TKI monotherapy or TKI-IO combination therapy for advanced renal cell carcinoma.

4528 Background: Tyrosine kinase inhibitors (TKI) in monotherapy or TKI in combination with immunotherapeutic agents (IO) are standard of care fist-line treatment for advanced or metastatic renal cell carcinoma (RCC). Dose reduction due to toxicity is extremely frequently and represents an important clinical management issue, with frequent dose reduction, treatment suspension and change of schedule. We examined the outcomes of patient treated with TKI in monotherapy and in combination with immunotherapy (TKI-IO). Methods: We performed a retrospective analysis of clinical outcomes in patients with RCC treated with TKI (cohort 1) or TKI-IO (cohort 2) in Italian and Spanish institutions. A descriptive analysis was performed. Univariate logistic regression models were carried out to estimate the association between best response (CR or PR vs SD or PD) and type of TKI (monotherapy or combination therapy). Survival curves were estimated using the Kaplan-Meier method and were compared by the log-rank test. Cox proportional-hazard models were used to obtain hazard ratios (HRs) with 95%. Median follow-up was calculated using the reverse Kaplan-Meier method. Results: A total of 401 patients were divided in cohort 1 (329 patients) and cohort 2 (72 patients). Median Follow-up was 81.22 months in cohort 1 and 19.02 months in cohort 2. Most frequent toxicities that lead to dose reduction were mucositis (20.13%), Asthenia (16.88%) and Hand-foot syndrome (15.58%). Overall Response Rate was higher in patients that reduced dose, both in cohort 1 (48% vs 29%, p&lt;0.01) and cohort 2 (81% vs 40%, p&lt;0.01). In cohort 1 Progression Free Survival (PFS) was longer in patients with dose reduction (27.14 months vs 16.59 months) (HR 0.77 [0.6; 0.98]; p=0.04). Overall Survival (OS) was also improved (55 months vs 34.17) (HR 0.71 [0.53; 0.93]; p=0.01). In cohort 2, both PFS (39.13 months vs 41.3 months) (HR 0.63 [0.27; 1.48]; p=0.29) and OS (39.13 months vs 55.85 months) (HR 0.65 [0.26; 1.63]; p=0.29) did not statistically differ between patients that reduced dose and patients that did not reduce dose. Conclusions: TKI dose reduction due to toxicity seems to be related to improved outcomes, both in ORR and PFS/OS. ORR was statistically improved in both cohort 1 and cohort 2. PFS and OS in cohort 1 favoured patients that experienced dose reduction. PFS and OS in cohort 2 did not show a statistically significant difference, probably due to the short follow-up and small number of patients. However, outcomes seem to show a trend toward favouring patients that reduce dose.

Characterization of the bone marrow niche in patients with chronic myeloid leukemia identifies CXCL14 as a new therapeutic option

AbstractAlthough tyrosine kinase inhibitors (TKIs) are effective in treating chronic myeloid leukemia (CML), they often fail to eradicate the leukemia-initiating stem cells (LSCs), causing disease persistence and relapse. Evidence indicates that LSC persistence may be because of bone marrow (BM) niche protection; however, little is known about the underlying mechanisms. Herein, we molecularly and functionally characterize BM niches in patients with CML at diagnosis and reveal the altered niche composition and function in these patients. Long-term culture initiating cell assay showed that the mesenchymal stem cells from patients with CML displayed an enhanced supporting capacity for normal and CML BM CD34+CD38– cells. Molecularly, RNA sequencing detected dysregulated cytokine and growth factor expression in the BM cellular niches of patients with CML. Among them, CXCL14 was lost in the BM cellular niches in contrast to its expression in healthy BM. Restoring CXCL14 significantly inhibited CML LSC maintenance and enhanced their response to imatinib in vitro, and CML engraftment in vivo in NSG-SGM3 mice. Importantly, CXCL14 treatment dramatically inhibited CML engraftment in patient-derived xenografted NSG-SGM3 mice, even to a greater degree than imatinib, and this inhibition persisted in patients with suboptimal TKI response. Mechanistically, CXCL14 upregulated inflammatory cytokine signaling but downregulated mTOR signaling and oxidative phosphorylation in CML LSCs. Together, we have discovered a suppressive role of CXCL14 in CML LSC growth. CXCL14 might offer a treatment option targeting CML LSCs.

A-to-I edited miR-411-5p targets MET and promotes TKI response in NSCLC-resistant cells.

Non-small cell lung cancer (NSCLC) patients carrying an epidermal growth factor receptor (EGFR) mutation have an initial favorable clinical response to the tyrosine kinase inhibitors (TKIs). Unfortunately, rapid resistance occurs mainly because of genetic alterations, including amplification of the hepatocyte growth factor receptor (MET) and its abnormal activity. The RNA post-transcriptional modifications that contribute to aberrant expression of MET in cancer are largely under-investigated and among them is the adenosine-to-inosine (A-to-I) RNA editing of microRNAs. A reduction of A-to-I editing in position 5 of miR-411-5p has been identified in several cancers, including NSCLC. In this study, thanks to cancer-associated gene expression analysis, we assessed the effect of the edited miR-411-5p on NSCLC cell lines. We found that edited miR-411-5p directly targets MET and negatively affects the mitogen-activated protein kinases (MAPKs) pathway. Considering the predominant role of the MAPKs pathway on TKIs resistance, we generated NSCLC EGFR mutated cell lines resistant to TK inhibitors and evaluated the effect of edited miR-411-5p overexpression. We found that the edited miR-411-5p reduces proliferation and induces apoptosis, promoting EGFR TKIs response in NSCLC-resistant cells.

Structure-Guided Strategies of Targeted Therapies for Patients with EGFR-Mutant Non-Small Cell Lung Cancer.

Oncogenic mutations within the EGFR kinase domain are well-established driver mutations in non-small cell lung cancer (NSCLC). Small-molecule tyrosine kinase inhibitors (TKIs) specifically targeting these mutations have improved treatment outcomes for patients with this subtype of NSCLC. The selectivity of these targeted agents is based on the location of the mutations within the exons of the EGFR gene, and grouping mutations based on structural similarities has proved a useful tool for conceptualizing the heterogeneity of TKI response. Structure-based analysis of EGFR mutations has influenced TKI development, and improved structural understanding will inform continued therapeutic development and further improve patient outcomes. In this review, we summarize recent progress on targeted therapy strategies for patients with EGFR-mutant NSCLC based on structure and function analysis.