Tyrosine Kinase Inhibitor Treatment Response Research Articles

Evaluating the Potential of Delta Radiomics for Assessing Tyrosine Kinase Inhibitor Treatment Response in Non-Small Cell Lung Cancer Patients.

Our study aimed to harness the power of CT scans, observed over time, in predicting how lung adenocarcinoma patients might respond to a treatment known as EGFR-TKI. Analyzing scans from 322 advanced stage lung cancer patients, we identified distinct image-based patterns. By integrating these patterns with comprehensive clinical information, such as gene mutations and treatment regimens, our predictive capabilities were significantly enhanced. Interestingly, the precision of these predictions, particularly related to radiomics features, diminished when data from various centers were combined, suggesting that the approach requires standardization across facilities. This novel method offers a potential pathway to anticipate disease progression in lung adenocarcinoma patients treated with EGFR-TKI, laying the groundwork for more personalized treatments. To further validate this approach, extensive studies involving a larger cohort are pivotal.

Early Prediction and Monitoring of Treatment Response in Gastrointestinal Stromal Tumors by Means of Imaging: A Systematic Review.

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal neoplasms. Tyrosine kinase inhibitor (TKI) therapy is currently part of routine clinical practice for unresectable and metastatic disease. It is important to assess the efficacy of TKI treatment at an early stage to optimize therapy strategies and eliminate futile ineffective treatment, side effects and unnecessary costs. This systematic review provides an overview of the imaging features obtained from contrast-enhanced (CE)-CT and 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT to predict and monitor TKI treatment response in GIST patients. PubMed, Web of Science, the Cochrane Library and Embase were systematically screened. Articles were considered eligible if quantitative outcome measures (area under the curve (AUC), correlations, sensitivity, specificity, accuracy) were used to evaluate the efficacy of imaging features for predicting and monitoring treatment response to various TKI treatments. The methodological quality of all articles was assessed using the Quality Assessment of Diagnostic Accuracy Studies, v2 (QUADAS-2) tool and modified versions of the Radiomics Quality Score (RQS). A total of 90 articles were included, of which 66 articles used baseline [18F]FDG-PET and CE-CT imaging features for response prediction. Generally, the presence of heterogeneous enhancement on baseline CE-CT imaging was considered predictive for high-risk GISTs, related to underlying neovascularization and necrosis of the tumor. The remaining articles discussed therapy monitoring. Clinically established imaging features, including changes in tumor size and density, were considered unfavorable monitoring criteria, leading to under- and overestimation of response. Furthermore, changes in glucose metabolism, as reflected by [18F]FDG-PET imaging features, preceded changes in tumor size and were more strongly correlated with tumor response. Although CE-CT and [18F]FDG-PET can aid in the prediction and monitoring in GIST patients, further research on cost-effectiveness is recommended.

High dimensionality reduction by matrix factorization for systems pharmacology.

The extraction of predictive features from the complex high-dimensional multi-omic data is necessary for decoding and overcoming the therapeutic responses in systems pharmacology. Developing computational methods to reduce high-dimensional space of features in in vitro, in vivo and clinical data is essential to discover the evolution and mechanisms of the drug responses and drug resistance. In this paper, we have utilized the matrix factorization (MF) as a modality for high dimensionality reduction in systems pharmacology. In this respect, we have proposed three novel feature selection methods using the mathematical conception of a basis for features. We have applied these techniques as well as three other MF methods to analyze eight different gene expression datasets to investigate and compare their performance for feature selection. Our results show that these methods are capable of reducing the feature spaces and find predictive features in terms of phenotype determination. The three proposed techniques outperform the other methods used and can extract a 2-gene signature predictive of a tyrosine kinase inhibitor treatment response in the Cancer Cell Line Encyclopedia.

Predicting Tyrosine Kinase Inhibitor Treatment Response in Stage IV Lung Adenocarcinoma Patients With EGFR Mutation Using Model-Based Deep Transfer Learning.

BackgroundFor stage IV patients harboring EGFR mutations, there is a differential response to the first-line TKI treatment. We constructed three-dimensional convolutional neural networks (CNN) with deep transfer learning to stratify patients into subgroups with different response and progression risks.Materials and MethodsFrom 2013 to 2017, 339 patients with EGFR mutation receiving first-line TKI treatment were included. Progression-free survival (PFS) time and progression patterns were confirmed by routine follow-up and restaging examinations. Patients were divided into two subgroups according to the median PFS (<=9 months, > 9 months). We developed a PFS prediction model and a progression pattern classification model using transfer learning from a pre-trained EGFR mutation classification 3D CNN. Clinical features were fused with the 3D CNN to build the final hybrid prediction model. The performance was quantified using area under receiver operating characteristic curve (AUC), and model performance was compared by AUCs with Delong test.ResultsThe PFS prediction CNN showed an AUC of 0.744 (95% CI, 0.645–0.843) in the independent validation set and the hybrid model of CNNs and clinical features showed an AUC of 0.771 (95% CI, 0.676–0.866), which are significantly better than clinical features-based model (AUC, 0.624, P<0.01). The progression pattern prediction model showed an AUC of 0.762(95% CI, 0.643–0.882) and the hybrid model with clinical features showed an AUC of 0.794 (95% CI, 0.681–0.908), which can provide compensate information for clinical features-based model (AUC, 0.710; 95% CI, 0.582–0.839).ConclusionThe CNN exhibits potential ability to stratify progression status in patients with EGFR mutation treated with first-line TKI, which might help make clinical decisions.

Co-occurring Alterations in the RAS-MAPK Pathway Limit Response to MET Inhibitor Treatment in MET Exon 14 Skipping Mutation-Positive Lung Cancer.

Although patients with advanced-stage non-small cell lung cancers (NSCLC) harboring MET exon 14 skipping mutations (METex14) often benefit from MET tyrosine kinase inhibitor (TKI) treatment, clinical benefit is limited by primary and acquired drug resistance. The molecular basis for this resistance remains incompletely understood. Targeted sequencing analysis was performed on cell-free circulating tumor DNA obtained from 289 patients with advanced-stage METex14-mutated NSCLC. Prominent co-occurring RAS-MAPK pathway gene alterations (e.g., in KRAS, NF1) were detected in NSCLCs with METex14 skipping alterations as compared with EGFR-mutated NSCLCs. There was an association between decreased MET TKI treatment response and RAS-MAPK pathway co-occurring alterations. In a preclinical model expressing a canonical METex14 mutation, KRAS overexpression or NF1 downregulation hyperactivated MAPK signaling to promote MET TKI resistance. This resistance was overcome by cotreatment with crizotinib and the MEK inhibitor trametinib. Our study provides a genomic landscape of co-occurring alterations in advanced-stage METex14-mutated NSCLC and suggests a potential combination therapy strategy targeting MAPK pathway signaling to enhance clinical outcomes.

502P - Epidermal growth factor receptor tyrosine kinase inhibitor treatment response in advanced non-small cell lung cancer with uncommon mutations: A multicenter observational study

BackgroundTreatment with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) is the standard therapy for advanced non-small cell lung cancer (NSCLC) with common EGFR mutations. However, the efficacy of EGFR-TKIs in patients with uncommon EGFR mutations remains unclear. MethodsWe retrospectively surveyed a consecutive database of patients with NSCLC with EGFR mutations. We analyzed the data of patients with NSCLC with uncommon mutations, including single or compound mutations, who were treated with EGFR-TKIs between May 2016 and October 2018. ResultsData from 543 patients were collected from five institutions, among whom 23 had EGFR uncommon mutations. Twenty-one patients who were treated with any EGFR-TKIs were analyzed in this study, 18 of whom were treated with EGFR-TKIs as first-line therapy (gefitinib 5, erlotinib 3, afatinib 10 patients). In contrast, three patients underwent cytotoxic chemotherapy as first-line therapy and were treated with EGFR-TKIs as second- and third-line therapy (gefitinib 1, erlotinib 1, afatinib 1 patient). According to the Response Evaluation Criteria in Solid Tumors, the overall response rate was 56%, and the disease control rate was 78%. The median progression-free survival (PFS) was 14.0 months in all patients with uncommon mutations. The median PFS of patients who were treated with first and second generation EGFR-TKIs were 14.0 months (n = 10) and 7.3 months (n = 11), respectively. Moreover, the PFS of patients with the G719X mutation (n = 12, median PFS: 32.9 months) was longer than that of patients with the L861Q mutation (n = 4, median PFS: 11.1) and compound mutations (n = 4, median PFS 7.3 months). ConclusionsFirst and second generation EGFR-TKIs are effective treatments for patients with NSCLC with uncommon mutations. Notably, a greater favorable response was observed in patients with G719X mutations than those with L861Q and compound mutations. Clinical trial identificationUMIN000028989. Legal entity responsible for the studyFumio Imamura. FundingAstraZeneca. DisclosureF. Imamura: Honoraria (self), Advisory / Consultancy, Research grant / Funding (institution): AstraZeneca. All other authors have declared no conflicts of interest.

Tyrosine kinase inhibitor sensitive PDGFRΑ mutations in GIST: Two cases and review of the literature.

Gastrointestinal stromal tumors (GISTs) are rare mesenchymal malignancies of the gastrointestinal tract. Most GISTs harbor a c-KIT (80%) or a PDGFRα (10%) mutation that leads to constitutive activation of the tyrosine kinase receptor. Response to treatment with tyrosine kinase inhibitors (TKIs) is dependent on mutational status of the tumor. The most common mutation in PDGFRα, D842V, is known to be imatinib resistant. Almost all other PDGFRα mutations are imatinib sensitive. We describe two patients with a PDGFRα exon 18 mutated GIST responding to treatment with TKIs. One of these patients has a p.M844_S847 deletion, not previously described in relation with TKI treatment response. Mutations in circulating tumor DNA were detectable with digital droplet PCR in serial plasma samples taken during treatment and correlated with treatment response of both patients. Computer 3D-modeling of the PDGFRα kinase domain of these two variants revealed no direct interference in imatinib or sunitinib binding and no effect in its activity in contrast to the reported structure of the imatinib resistant D842V mutation.An overview is given of the literature regarding the evidence of patients with different PDGFRα mutated GISTs on response to TKIs. The findings emphasize the use of mutational analysis in GIST to provide patients personalized treatment. Detection of mutations in plasma is feasible and can provide real-time information concerning treatment response. We suggest to register GIST patients with these uncommon mutations in a prospective international database to understand the tumor biology and obtain more evidence of such mutations to predict treatment response.

Quantification of BCR-ABL transcripts in peripheral blood cells and plasma of chronic myeloid leukemia patients at different stages of tyrosine kinase inhibitor treatment response

Purpose : To investigate the feasibility of using peripheral blood plasma samples as surrogates for blood cell sampling for quantification of breakpoint cluster region-Abelson oncogene (BCR-ABL) transcript levels to monitor treatment responses in chronic myeloid leukemia (CML) patients. Methods : Peripheral blood samples were collected from 20 healthy individuals and 165 CML patients at various stages of treatment response. Level of BCR-ABL mutation gene transcripts were determined by RNA extraction and quantitative real time polymerase chain reaction (RT-PCR). Results : The ratio of BCR-ABL transcripts/ABL transcripts in blood cells was significantly higher (p < 0.05) than in plasma for untreated and treated patients. Patients who received tyrosine kinase inhibitor (TKI) therapy and achieved major molecular response during treatment had the lowest mean ratio detected in blood cells (0.06 ± 0.0 %) and the ratio was below the detectable limit in plasma samples. Unlike plasma samples, BCR-ABL/ABL transcript ratios in blood cell samples strongly correlated with white cell counts in CML patients undergoing all types of treatment responses. Conclusion : Blood cell sampling is more sensitive than plasma sampling in diagnosis and evaluation of CML treatment response. Keywords : Chronic myeloid leukemia, Peripheral blood cells, Plasma RNA, Treatment response, Tyrosine kinase inhibitors

Abstract B71: Circulating PD-1+CD8+T cells reflect response to epidermal growth factor receptor tyrosine kinase inhibitors in non-small cell lung cancer patients

Abstract The programmed death-1 (PD-1)/programmed cell death-1 ligand (PD-L1) pathway plays a crucial role in tumor evasion. Alteration in Epidermal Growth Factor Receptor (EGFR) and KRAS are oncogenic drivers in lung cancer and activation of this pathway is a critical event during lung tumorigenesis. However, how this oncogenic signaling influences immunity in the tumor microenvironment is just beginning to be understood. According to other report, expression of mutant EGFR in bronchial epithelial cells induces PD-L1 and PD-L1 expression is reduced by EGFR inhibitors in lung cancer cell lines with activated EGFR mutation. Thus, we evaluated the levels of PD-1+ T cells in peripheral blood according to the response of EGFR Tyrosine Kinase Inhibitors (TKIs) in Non-small Cell Lung Cancer (NSCLC) patients. Blood samples of NSCLC patients were obtained at baseline and after EGFR TKI treatment. Flow cytometry was used to detect PD-1 expressing CD4 or CD8 T cells. Total 53 patients were enrolled in the study. 17 patients had EGFR mutation and treated with EGFR TKIs. The expression of PD-1+CD8+ T cells in peripheral blood are increased according to their clinical stage. The expression levels of PD-1+CD8+ T cells significantly decreased after EGFR TKIs treatment (pretreatment vs. post-treatment 0.93±1.25% vs. 0.43±0.59%, P=0.006). Post/pre EGFR TKIs treatment ratio of PD-1+CD8+ T cells was lower in partial response group than stable disease group (0.19±0.17 vs. 0.9±0.68, P=0.017). So this result showed that PD-1+CD8+ T cells was more decreased in good responder group. EGFR mutant lung tumor inhibited antitumor immunity by activating PD-1 and PD-1 expression was reduced by EGFR TKI, which was proportional to treatment response. In conclusion, the change of PD-1+CD8+ T cell in peripheral blood may be a surrogate marker to predict EGFR TKIs treatment response. Citation Format: Sung Yong Lee, Sungjong Lee, Jee Youn Oh, Kyung Hoon Min, Gyu Young Hur, Jae Jeong Shim, Kyung Ho Kang. Circulating PD-1+CD8+T cells reflect response to epidermal growth factor receptor tyrosine kinase inhibitors in non-small cell lung cancer patients. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr B71.

Abstract 2039: Exploring the longitudinal transcriptomic landscape of tyrosine kinase inhibitor treatment response in chronic myeloid leukemia patients

Abstract The interpretation and implementation of large-scale genetic profiles into clinical practice remains a challenge despite substantial growth in our understanding of genetic contributors to drug response. Most current omic studies focus on identifying genetic features that are distinct between normal and tumor samples, but fail to capture the dynamics of association between omic profiles, treatment response and disease progression over time. The focus of this research is to analyze the longitudinal transcriptomic profile of chronic myeloid leukemia patients (CML) in context of tyrosine kinase inhibitor (TKI) treatment and clinical status. The main objectives were to compare a series of post-TKI treatment transcriptome profiles to their baseline levels, and characterize the impact of TKI treatment and CML disease status on the individual's transcriptome over time. Our ultimate goal is to develop TKI response predictors using the longitudinal expression data collected over the treatment course. Peripheral blood samples, buccal swabs and detailed clinical data were collected from each study participant (screened for BCR-ABL1 translocation) for a period of 6 months, in addition to pre-therapy baseline. RNA was extracted from granulocytes isolated from peripheral blood samples, and profiled using RNA sequencing. RNAseq profiles over TKI treatment course were compared to baseline, as well as against hematologic response (complete blood count), cytogenetic response (FISH), and clinical disease progression. We investigated dynamic trends in RNAseq profiles associated TKI response, as well as with the clinical status of the patient over time. We identified genetic features that were either 1) Differentially expressed between baseline and post-TKI time points; 2) Showed non-random spikes in expression levels at specific time points; 3) Associated with hematological and clinical phenotypes, including white blood cell count, percentage granulocytes and percentage cells with BCR-ABL1 translocation; 4) Demonstrated highly correlated patterns of expression over time. Through clustering and enrichment analysis of the selected transcripts, we identified several pathways and molecular features associated with TKI-response, and altered disease state. Of note, we found mTOR signaling, and pro-apoptotic pathways to be significantly altered between baseline and TKI-responding individuals. In addition, we observed significant changes in transcription regulatory network of several transcription factors, notably AP-1, over the treatment time course. To our knowledge, this is the first study to establish the utility of comprehensive longitudinal multiple transcriptome profile analysis of TKI-response in CML. We believe this study will pave way for future large-scale longitudinal omic profiling of CML and other cancer-types. Citation Format: Aritro Nath, Fan Wang, Divya Lenkala, Bonnie LaCroix, Nancy Glavin, Kristen Kipping-Johnson, Paul Geeleher, Michael Thirman, Lucy Godley, Gordana Raca, Richard Larson, R. Stephanie Huang. Exploring the longitudinal transcriptomic landscape of tyrosine kinase inhibitor treatment response in chronic myeloid leukemia patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2039.

Simultaneous EGFR mutation detection and copy number assessment in circulating tumour DNA (ctDNA) to inform molecular methods of therapy resistance and plasma ctDNA content in lung adenocarcinoma.

e23027Background: EGFR circulating tumour DNA (ctDNA) is a dynamic blood-borne marker predictive of EGFR tyrosine kinase inhibitor treatment response and disease progression. Microdroplet digital P...

Comparison of uncommon EGFR exon 21 L858R compound mutations with single mutation.

Non-small-cell lung cancer with epidermal growth factor receptor (EGFR) mutation is sensitive to EGFR tyrosine kinase inhibitors (TKIs). But little is known about the response to EGFR TKIs and the prognostic role of compound mutations. This study compared the uncommon EGFR exon 21 L858R compound mutations with single mutation to characterize EGFR compound mutations and investigated their response to EGFR TKI treatment. We retrospectively screened 799 non-small-cell lung cancer patients from August 1, 2009 to June 1, 2012 by EGFR mutation testing. EGFR mutations were detected in 443 patients, with 22 (4.97%) compound mutations. Subsequently, six patients with EGFR exon 21 L858R compound mutations and 18 paired patients with single L858R mutation were well characterized. Finally, we also analyzed the EGFR TKI treatment response and patients’ outcomes of compound or single L858R mutations. There was no differential treatment effect on the disease control rate and objective response rate between the L858R compound mutations and single mutation groups. No significant difference in overall survival or progression-free survival of these two groups was found by log-rank test. In conclusion, we demonstrated that no significant difference was detected in the response to EGFR TKIs and patients’ outcomes in the compound and single mutation groups.

Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor Treatment Response in Advanced Non-Small Cell Lung Cancer with G719X/L861Q/S768I Mutations

ABSTRACT Aim: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are very effective for lung cancers with classical sensitive EGFR mutations; however, their role in tumors with uncommon mutations, such as G719X, L861Q and S768I, is still not clear. Previous studies are limited by their small sample size. Taiwan Lung Cancer Society, in conjunction with Taiwan Lung Cancer Clinical Trial Consortium, initiated a study to evaluate the clinical effectiveness of EGFR-TKI in patients with advanced non-small cell lung carcinoma (NSCLC) bearing EGFR G719X, L861Q and/or S768I mutations. Methods: Patients were eligible if they had stage IIIB or IV NSCLC bearing G719X, L861Q or S768I mutations, had been treated by gefitinib or erlotinib, and did not receive other anti-tumor therapy during EGFR-TKI treatment. Patients with tumors that had concomittant classical sensitive (exon 19 deletions and L858R mutation) or resistant (T790M and exon 20 insertions) mutations were excluded. Results: Totally 226 cases were screened from 18 institutes throughout Taiwan. One hundred and sixty-one cases were eligible and all were adenocarcinomas. Among them, 56.5% were female, 68.8% were never smokers, 95.7% were stage IV, 76.4% were PS 0-1, and 78.9% were treatment-naive. EGFR mutation status were G719X of 78 cases, L861Q of 58, S768I of 7, G719X + L861Q of 8, and G719X + S768I of 10. One hundred and twenty-seven patients were treated by gefitinib and 34 by erlotinib. Four hundred and eighty-three patients who had classical sensitive EGFR mutations and were treated by EGFR-TKI were served as the control. EGFR-TKI treatment outcomes are summarized in the Table. Patients with G719X/L861Q/S768I mutations had inferior response rate and shorter progression free survival than patients with exon 19 deletions or L858R mutations (both P ORR DCR PFS G719X/L861Q/S768I (n = 161) 40.5% 75.8% 7.7m L858R mutations (n = 253) 67.6% 95.7% 10.4m exon 19 deletions (n = 223) 64.5% 94.6% 14.1m Conclusions: Patients with advanced lung adenocarcinomas of EGFR G719X/L861Q/S768I mutations had suboptimal treatment outcome to EGFR-TKI. Prospective randomized trials are warranted to decide the most appropriate therapy for patients with these uncommon mutations. Disclosure: C. Chiu: I have received honorarium from AstraZeneca, Boehringer Ingelheim and Roche. All other authors have declared no conflicts of interest.

Multi-scale agent-based brain cancer modeling and prediction of TKI treatment response: Incorporating EGFR signaling pathway and angiogenesis

BackgroundThe epidermal growth factor receptor (EGFR) signaling pathway and angiogenesis in brain cancer act as an engine for tumor initiation, expansion and response to therapy. Since the existing literature does not have any models that investigate the impact of both angiogenesis and molecular signaling pathways on treatment, we propose a novel multi-scale, agent-based computational model that includes both angiogenesis and EGFR modules to study the response of brain cancer under tyrosine kinase inhibitors (TKIs) treatment.ResultsThe novel angiogenesis module integrated into the agent-based tumor model is based on a set of reaction–diffusion equations that describe the spatio-temporal evolution of the distributions of micro-environmental factors such as glucose, oxygen, TGFα, VEGF and fibronectin. These molecular species regulate tumor growth during angiogenesis. Each tumor cell is equipped with an EGFR signaling pathway linked to a cell-cycle pathway to determine its phenotype. EGFR TKIs are delivered through the blood vessels of tumor microvasculature and the response to treatment is studied.ConclusionsOur simulations demonstrated that entire tumor growth profile is a collective behaviour of cells regulated by the EGFR signaling pathway and the cell cycle. We also found that angiogenesis has a dual effect under TKI treatment: on one hand, through neo-vasculature TKIs are delivered to decrease tumor invasion; on the other hand, the neo-vasculature can transport glucose and oxygen to tumor cells to maintain their metabolism, which results in an increase of cell survival rate in the late simulation stages.

Influence of Chemotherapy on EGFR Mutation Status Among Patients With Non–Small-Cell Lung Cancer

EGFR mutation is a predictor of epidermal growth factor receptor-tyrosine kinase inhibitor treatment response in patients with non-small-cell lung cancer (NSCLC). However, it remains unclear whether chemotherapy affects EGFR mutation status in NSCLC. We investigated the influence of chemotherapy on EGFR mutations in plasma and tumor tissues from patients with NSCLC. Samples were derived from three cohorts: one, 264 patients with advanced NSCLC who received first-line chemotherapy with matched pre- and postchemotherapy blood samples; two, 63 patients with stages IIb to IIIb disease with pre- and post-neoadjuvant chemotherapy tumor tissues; and three, 79 patients with advanced NSCLC who underwent palliative surgery. EGFR mutation status was determined and analyzed to reveal potential impact of chemotherapy. In the first cohort, EGFR mutations were detected in 34.5% of the prechemotherapy plasma samples (91 of 264) but in only 23.1% of the postchemotherapy plasma samples (61 of 264). The decrease in EGFR mutation rate was statistically significant (P < .001). Patients whose EGFR mutations switched from positive to negative after chemotherapy had a better partial response (PR) than patients with a reverse change (P = .037). A similar decrease in EGFR mutation rate was observed in tissues after neoadjuvant chemotherapy in the second cohort (34.9% [22 of 63] v 19.0% [12 of 63]; P = .013). In the third cohort, 38.0% of the tumors (30 of 79) showed an intratumor heterogeneity of EGFR mutation, whereas 62.0% (49 of 79) were homogeneous, either with EGFR mutation or no mutation. Our results suggest that chemotherapy may reduce EGFR mutation frequency in patients with NSCLC, likely the result of a preferential response of subclones with EGFR mutations in tumors with heterogeneous tumor cell populations.

Pretreatment Epidermal Growth Factor Receptor (EGFR) T790M Mutation Predicts Shorter EGFR Tyrosine Kinase Inhibitor Response Duration in Patients With Non–Small-Cell Lung Cancer

Patients with non-small-cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR)-activating mutations have excellent response to EGFR tyrosine kinase inhibitors (TKIs), but T790M mutation accounts for most TKI drug resistance. This study used highly sensitive methods to detect T790M before and after TKI therapy and investigated the association of T790M and its mutation frequencies with clinical outcome. Direct sequencing, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and next-generation sequencing (NGS) were used to assess T790M in the following two cohorts of patients with NSCLC: TKI-naive patients (n = 107) and TKI-treated patients (n = 85). Results were correlated with TKI treatment response and survival. MALDI-TOF MS was highly sensitive in detecting and quantifying the frequency of EGFR-activating mutations and T790M (detection limits, 0.4% to 2.2%). MALDI-TOF MS identified more T790M than direct sequencing in TKI-naive patients with NSCLC (27 of 107 patients, 25.2% v three of 107 patients, 2.8%, respectively; P < .001) and in TKI-treated patients (before TKI: 23 of 73 patients, 31.5% v two of 73 patients, 2.7%, respectively; P < .001; and after TKI: 10 of 12 patients, 83.3% v four of 12 patients, 33.3%, respectively; P = .0143). The EGFR mutations and their frequencies were confirmed by NGS. T790M was an independent predictor of decreased progression-free survival (PFS) in patients with NSCLC who received TKI treatment (P < .05, multivariate Cox regression). T790M may not be a rare event before or after TKI therapy in patients with NSCLC with EGFR-activating mutations. The pretreatment T790M mutation was associated with shorter PFS with EGFR TKI therapy in patients with NSCLC.

Quantitative Multiplex Measurement of BCR-ABL1 Expression on the International Scale Using the BCR/ABL1 Quant™ RUO Reagents and the LightCycler® 480

Abstract 4430 Introduction:BCR-ABL1 e13a2 or e14a2 fusion transcripts corresponding to the translocation (9;22) are present in >95% of chronic myeloid leukemia (CML) patients. This molecular signature is thus useful to monitor tumor burden and tyrosine kinase inhibitor treatment response in CML. The e1a2 variant is found in about 5% of children with acute lymphoblastic leukemia (ALL) and 20–35% of adult ALL. Growing evidence indicates that the e1a2 variant is associated with inferior outcome and higher risk of relapse in CML. It is therefore also important to study e1a2 expression levels in these individuals. The objective of this study was to evaluate the use of a single multiplex assay (BCR/ABL1 Quant™ RUO) for the quantitative detection of e1a2, e13a2, and e14a2 fusion transcripts. These reagents were initially optimized for use with the ABI 7500 series of instruments (Brown et al., Blood Cancer Journal 2011). Here we investigated their compatibility and performance on the LightCycler® 480 System (LC480). Method:Control RNAs containing or lacking BCR-ABL1 transcripts were obtained from commercial sources. The kit's Calibrator standard curve samples and the ARQ IS Calibrator Panel were both prepared by heat lysis prior to reverse transcription (RT). The RNA was then reverse transcribed and then amplified by multiplex, real-time quantitative PCR on the ABI 7500 Fast Dx or LC480 using target-specific primers for e1a2, e13a2, e14a2, and ABL1 as an endogenous internal control. Runs on the LC480 used a ramp rate of 1.6 degrees/second to mimic that of the ABI 7500. Also, color compensation reagents (positive simplex reactions) were used on the LC480 per manufacturer's recommendations to generate a color compensation profile to enhance the performance of the multiplex reactions. Four-point standard curves were generated in each run using the included multiplex ARQ Calibrators (each calibrator sample contains each target: BCR/ABL1, ABL1, and BCR/ABL1 Quant Norm, an exogenous internal control). Fusion transcript identity was determined by capillary electrophoresis on an ABI 3130xl series instrument with 36 cm capillaries using POP7. Data were analyzed using either instrument's software (SDS v1.4 for the ABI 7500 Fast Dx and LightCycler software v1.5 for the LC480) or proprietary Excel-based software developed by Arista Molecular. Result:Analytical performance assessed using cell line dilutions showed a lower limit of detection equivalent to at least one translocation-positive cell in 100,000 normal cells. Linearity of >5 logs was observed with these samples. Breakpoints e13a2, e14a2, and e1a2 were all detected with various control materials. Negative specimens did not generate signal. ANOVA of multiple independent runs of controls sample replicates in randomly assigned plate locations on the LC480 showed excellent inter- and intra-run reproducibility and no detectable spatial bias across the plate. Side-by-side runs of the samples on both the 7500 and LC480 showed excellent correspondence of the results. Finally, testing of residual clinical specimens and prototype secondary IS reference materials (ARQ IS Calibrator Panel) linked to the WHO 1st International Genetic Reference Panel for the quantitation of BCR-ABL translocation indicated that the assay has the performance required to report on the International Scale (IS) when performed on the LC480. Conclusion:The BCR/ABL1 Quant RUO reagents are compatible with use on the LC480 instrument. They have the advantage of both quantifying and distinguishing e1a2, e13a2, and e14a2 fusion transcripts in a single reaction. Streamlined reagent formulation, multiplex assay format, and inclusion of ARQ calibrators improve the workflow and increase the number of specimens that can be tested per run. Our results suggest that this research assay has the performance required for reporting on the IS. Further evaluation with a larger set of clinical specimens is warranted. Disclosures:Brown:Asuragen: Employment. Laosinchai-Wolf:Asuragen: Employment. Labourier:Asuragen: Employment.

Sensitivity to Imatinib In BCR-ABL1-Positive Chronic Myeloid Leukemia Cells Depends on the Presence of Normal ABL1.

AbstractAbstract 3405 Background:BCR-ABL1 encoding for oncogenic tyrosine kinase results from t(9;22)(q34;q11) reciprocal translocation or variants generating the Philadelphia chromosome (Ph), which initiates chronic myeloid leukemia in chronic phase (CML-CP). The second (wild-type) ABL1 and BCR alleles in CML-CP cells remain intact on the non-rearranged homologues of chromosome 9 and 22, respectively. Accordingly, CML-CP cells at early stages express both forms of the ABL1 kinase, oncogenic BCR-ABL1 and normal ABL1. ABL1 tyrosine kinase inhibitors (TKIs) such as imatinib, dasatinib and nilotinib revolutionized the treatment of CML-CP, but they do not eradicate leukemia. Patients who do achieve complete cytogenetic remission (CCyR) may eventually stop responding and acquire resistance to TKIs, which may lead to disease relapse and malignant progression. Mutations in the sequence encoding BCR-ABL1 kinase have been detected in approximately 50% of CML-CP patients resistant to TKIs, but other factors contributing to this phenomenon are poorly characterized. Results:Here, we identified a novel mechanism of TKI resistance: loss of the remaining normal ABL1 allele resulting from cryptic deletion in the 9q34 region in the normal chromosome 9 [del(9)(q34)]. Using bacterial artificial chromosome probes (BACs) for dual color/dual probe fluorescent in situ hybridization (D-FISH), and oligonucleotide array comparative genomic hybridization (aCGH) we show that genomic deletion of ABL1 allele in non-translocated chromosome 9 acquired during TKI therapy in CML-CP patients was associated with resistance to imatinib and dasatinib. del(9)(q34) was detected in approximately 10% of the patients who initially failed to achieve CCyR within 12 months of TKI treatment. Moreover, BCR-ABL1-positive Abl1-/- murine leukemia cells were refractory to imatinib in comparison to BCR-ABL1–positive Abl1+/+ counterparts as indicated by persistent BCR-ABL1 –mediated tyrosine phosphorylation, lack of BCR-ABL1 protein degradation, increased cell survival and clonogenic activity. Expression of exogenous ABL1 kinase in BCR-ABL1–positive Abl1-/- cells restored their sensitivity to imatinib. These results provide direct evidence that Abl1 plays a crucial role in regulation of the sensitivity of BCR-ABL1-positive leukemia cells to imatinib. ABL1 is regarded as a cell cycle regulatory and pro-apoptotic protein, thus antagonistic to BCR-ABL1. The cell cycle inhibitory activity is independent of ABL1 kinase, whereas the pro-apoptotic function is dependent on its kinase activity. However, acquired resistance to TKIs caused by a loss of the wild-type ABL1 kinase does not appear to depend directly on the lack of ABL1-induced cell cycle arrest and/or apoptosis. In contrast to BCR-ABL1 –positive Abl1+/+ leukemia cells, imatinib exerted only modest effect on BCR-ABL1 kinase-dependent tyrosine phosphorylation and did not downregulate BCR-ABL1 protein in Abl1-/- leukemia cells, suggesting the role of Abl1 in cellular uptake of the drug and/or BCR-ABL1 degradation. Expression of imatinib cellular importer Oct-1 and cellular exporters Abcb1 and Abcg2 does not appear to favor the resistance to TKI in BCR-ABL1-positive Abl1-/- cells, but the impact of ABL1 on intracellular metabolism of imatinib cannot be excluded. In addition, expression of chaperone protein Hsp90, which protects BCR-ABL1 from proteasomal degradation, is not affected by Abl1. However, >3-fold downregulation of cathepsin B may be responsible for lack of degradation of BCR-ABL1 protein in imatinib-treated Abl1-/- cells. Conclusions:Altogether, it can be postulated that loss of expression of ABL1 kinase plays an important role in TKI resistance in CML. It can be achieved by interstitial deletion in chromosome 9 [del(9)(q34)] causing loss of normal ABL1 allele, which could be eventually combined with epigenetic silencing of the alternative ABL1 promoter retained in the CpG island of the BCR-ABL1 gene in t(9;22)(q34:q11). Detection of the del(9)(q34) is beyond the resolution of conventional karyotyping currently used to monitor TKI treatment response. In contrast, D-FISH using commercially available probes can identify such loss in both quiescent and dividing cells. In summary, downregulation of ABL1 caused by del(9)(q34) may serve as an important prognostic factor and have a significant impact on CML treatment. Disclosures:No relevant conflicts of interest to declare.