Aleksandra Markovets

Acquired EGFR C797S mutation mediates resistance to AZD9291 in non–small cell lung cancer harboring EGFR T790M

Here we studied cell-free plasma DNA (cfDNA) collected from subjects with advanced lung cancer whose tumors had developed resistance to the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) AZD9291. We first performed next-generation sequencing of cfDNA from seven subjects and detected an acquired EGFR C797S mutation in one; expression of this mutant EGFR construct in a cell line rendered it resistant to AZD9291. We then performed droplet digital PCR on serial cfDNA specimens collected from 15 AZD9291-treated subjects. All were positive for the T790M mutation before treatment, but upon developing AZD9291 resistance three molecular subtypes emerged: six cases acquired the C797S mutation, five cases maintained the T790M mutation but did not acquire the C797S mutation and four cases lost the T790M mutation despite the presence of the underlying EGFR activating mutation. Our findings provide insight into the diversity of mechanisms through which tumors acquire resistance to AZD9291 and highlight the need for therapies that are able to overcome resistance mediated by the EGFR C797S mutation.

Acquired Resistance to the Mutant-Selective EGFR Inhibitor AZD9291 Is Associated with Increased Dependence on RAS Signaling in Preclinical Models

Resistance to targeted EGFR inhibitors is likely to develop in EGFR-mutant lung cancers. Early identification of innate or acquired resistance mechanisms to these agents is essential to direct development of future therapies. We describe the detection of heterogeneous mechanisms of resistance within populations of EGFR-mutant cells (PC9 and/or NCI-H1975) with acquired resistance to current and newly developed EGFR tyrosine kinase inhibitors, including AZD9291. We report the detection of NRAS mutations, including a novel E63K mutation, and a gain of copy number of WT NRAS or WT KRAS in cell populations resistant to gefitinib, afatinib, WZ4002, or AZD9291. Compared with parental cells, a number of resistant cell populations were more sensitive to inhibition by the MEK inhibitor selumetinib (AZD6244; ARRY-142886) when treated in combination with the originating EGFR inhibitor. In vitro, a combination of AZD9291 with selumetinib prevented emergence of resistance in PC9 cells and delayed resistance in NCI-H1975 cells. In vivo, concomitant dosing of AZD9291 with selumetinib caused regression of AZD9291-resistant tumors in an EGFRm/T790M transgenic model. Our data support the use of a combination of AZD9291 with a MEK inhibitor to delay or prevent resistance to AZD9291 in EGFRm and/or EGFRm/T790M tumors. Furthermore, these findings suggest that NRAS modifications in tumor samples from patients who have progressed on current or EGFR inhibitors in development may support subsequent treatment with a combination of EGFR and MEK inhibition.

VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research

Abstract Accurate variant calling in next generation sequencing (NGS) is critical to understand cancer genomes better. Here we present VarDict, a novel and versatile variant caller for both DNA- and RNA-sequencing data. VarDict simultaneously calls SNV, MNV, InDels, complex and structural variants, expanding the detected genetic driver landscape of tumors. It performs local realignments on the fly for more accurate allele frequency estimation. VarDict performance scales linearly to sequencing depth, enabling ultra-deep sequencing used to explore tumor evolution or detect tumor DNA circulating in blood. In addition, VarDict performs amplicon aware variant calling for polymerase chain reaction (PCR)-based targeted sequencing often used in diagnostic settings, and is able to detect PCR artifacts. Finally, VarDict also detects differences in somatic and loss of heterozygosity variants between paired samples. VarDict reprocessing of The Cancer Genome Atlas (TCGA) Lung Adenocarcinoma dataset called known driver mutations in KRAS, EGFR, BRAF, PIK3CA and MET in 16% more patients than previously published variant calls. We believe VarDict will greatly facilitate application of NGS in clinical cancer research.

Osimertinib As First-Line Treatment of EGFR Mutation–Positive Advanced Non–Small-Cell Lung Cancer

Purpose The AURA study ( ClinicalTrials.gov identifier: NCT01802632) included two cohorts of treatment-naïve patients to examine clinical activity and safety of osimertinib (an epidermal growth factor receptor [EGFR] -tyrosine kinase inhibitor selective for EGFR-tyrosine kinase inhibitor sensitizing [ EGFRm] and EGFR T790M resistance mutations) as first-line treatment of EGFR-mutated advanced non-small-cell lung cancer (NSCLC). Patients and Methods Sixty treatment-naïve patients with locally advanced or metastatic EGFRm NSCLC received osimertinib 80 or 160 mg once daily (30 patients per cohort). End points included investigator-assessed objective response rate (ORR), progression-free survival (PFS), and safety evaluation. Plasma samples were collected at or after patients experienced disease progression, as defined by Response Evaluation Criteria in Solid Tumors (RECIST), to investigate osimertinib resistance mechanisms. Results At data cutoff (November 1, 2016), median follow-up was 19.1 months. Overall ORR was 67% (95% CI, 47% to 83%) in the 80-mg group, 87% (95% CI, 69% to 96%) in the 160-mg group, and 77% (95% CI, 64% to 87%) across doses. Median PFS time was 22.1 months (95% CI, 13.7 to 30.2 months) in the 80-mg group, 19.3 months (95% CI, 13.7 to 26.0 months) in the 160-mg group, and 20.5 months (95% CI, 15.0 to 26.1 months) across doses. Of 38 patients with postprogression plasma samples, 50% had no detectable circulating tumor DNA. Nine of 19 patients had putative resistance mechanisms, including amplification of MET (n = 1); amplification of EGFR and KRAS (n = 1); MEK1, KRAS, or PIK3CA mutation (n = 1 each); EGFR C797S mutation (n = 2); JAK2 mutation (n = 1); and HER2 exon 20 insertion (n = 1). Acquired EGFR T790M was not detected. Conclusion Osimertinib demonstrated a robust ORR and prolonged PFS in treatment-naïve patients with EGFRm advanced NSCLC. There was no evidence of acquired EGFR T790M mutation in postprogression plasma samples.

Acquired savolitinib resistance in non-small cell lung cancer arises via multiple mechanisms that converge on MET-independent mTOR and MYC activation

Lung cancer is the most common cause of cancer death globally with a significant, unmet need for more efficacious treatments. The receptor tyrosine kinase MET has been implicated as an oncogene in numerous cancer subtypes, including non-small cell lung cancer (NSCLC). Here we explore the therapeutic potential of savolitinib (volitinib, AZD6094, HMPL-504), a potent and selective MET inhibitor, in NSCLC. In vitro, savolitinib inhibits MET phosphorylation with nanomolar potency, which correlates with blockade of PI3K/AKT and MAPK signaling as well as MYC down-regulation. In vivo, savolitinib causes inhibition of these pathways and significantly decreases growth of MET-dependent xenografts. To understand resistance mechanisms, we generated savolitinib resistance in MET-amplified NSCLC cell lines and analyzed individual clones. We found that upregulation of MYC and constitutive mTOR pathway activation is a conserved feature of resistant clones that can be overcome by knockdown of MYC or dual mTORC1/2 inhibition. Lastly, we demonstrate that mechanisms of resistance are heterogeneous, arising via a switch to EGFR dependence or by a requirement for PIM signaling. This work demonstrates the efficacy of savolitinib in NSCLC and characterizes acquired resistance, identifying both known and novel mechanisms that may inform combination strategies in the clinic.

Abstract 4864: VarDict: A novel and versatile variant caller for next-generation sequencing in cancer research

Cancer genomes are known to harbor a wide range of mutations, including complex variants with combination of insertion and deletion (InDels). Next generation sequencing (NGS) has revolutionized our understanding of mutations in cancer. Most of current variant callers from NGS focused on single nucleotide variants (SNV) or short InDels. However, detection of complex variants remains a challenge and off limits to most current variant callers. In addition, efficient analysis of ultra-deep targeted sequencing without downsampling for low frequency mutations in heterogeneous cancer samples, which is becoming more routine, is also a challenge and not handled well by most current variant callers. Here, we describe VarDict, a novel and versatile variant caller for ultra-deep targeted deep sequencing, exome, whole genome, and RNA-seq. VarDict is designed for heterogeneous cancer genomes and is able to simultaneously call SNVs (Single-Nucleotide Variants), MNVs (Multiple-Nucleotide Variants), InDels (user-defined sizes), and complex variants (combination of aforementioned events). VarDict handles ultra-deep sequencing of runs up to mean coverage of 1M without down-sampling or significant loss of performance. It performs local realignment around InDels on the fly and rescues soft-clipped reads for more accurate estimation of allele frequencies as well as allowing calls of InDels only supported by soft-clipped reads. In addition, it performs amplicon aware variant calling for PCR-based targeted sequencing by avoiding calling variants in PCR primers, discounting primer depths, and importantly, detecting variants with amplicon-bias, a common artifact for PCR based targeted sequencing. VarDict can also be run in paired mode to identify somatic or LOH variants, as well as variants whose allele frequencies have shifted significantly. It thus enables paired DNA-seq and RNA-seq variant calling that most variant callers do not handle well. To demonstrate the value of VarDict in practice, we applied VarDict on the WGS of NA12878, and compared the result to the calls made in Genome In A Bottle (GiaB). VarDict was able to call >96% of variants in GiaB. In addition, it found many more variants likely missed by GiaB, especially complex variants, many of which were never categorized before. We further applied VarDict in the ICGC-TCGA DREAM Mutation Calling challenge (syn312572). We found it to be as sensitive as the more commonly used somatic SNP callers like MuTect, Freebayes, and VarScan in calling SNPs but more sensitive in calling InDels than an array of other variant callers, including VarScan, FreeBayes, and Scalpel. VarDict is fully open source, implemented in Perl, and uses memory efficiently, regardless of the depth, making it a HPC cluster friendly tool. VarDict has further been integrated into bcbio-nextgen, an open source framework for scalable NGS analysis for ease of deployment. VarDict is freely available in GitHub (https://github.com/AstraZeneca-NGS/VarDict). Citation Format: Zhongwu Lai, Aleksandra Markovets, Miika Ahdesmaki, Justin Johnson. VarDict: A novel and versatile variant caller for next-generation sequencing in cancer research. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4864. doi:10.1158/1538-7445.AM2015-4864

Abstract LB-249: Examination of analytical factors impacting concordance of plasma-tumor testing by next-generation sequencing (NGS)

The increased usage of circulating tumor DNA (ctDNA) sequencing for oncology clinical research demonstrates a critical need for sensitive and specific testing. While we have observed a high degree of concordance between single tumor mutations in tumor and plasma, several recent studies have highlighted a lack of concordance between plasma and tumor panel NGS gene panel testing due to biological and technical factors. To explore further these factors and benchmark ctDNA NGS testing services, a set of matched plasma, tumor, and normal samples from 24 subjects were acquired from three biobanking companies. Replicate 2 ml-plasma samples were tested by four ctDNA sequencing companies, and matching tumor/normal samples were tested by two tumor sequencing companies. Concordance was measured by comparing plasma mutations to tumor mutations as well as comparing mutations among the same plasma tested by the ctDNA companies. While our experience with NGS of matched samples from clinical trials typically identifies ~30% of patients with no detectable mutation and therefore likely not shedding tumor DNA, with the retrospectively collected commercial samples ~60% lacked detectable high confidence mutations, likely due to quality control issues with sample collection. We also found variation in the concordance of ctDNA mutation detection rates among the four vendors, due to significant differences in DNA yield and assay sensitivity. While factors such as tumor heterogeneity and timing of plasma-tumor collection can lower concordance rates, the majority of discordance in our study was due to technical rather than biological variation. Assay analytical variance and the impact of reporting false positive variants are key factors that need to be addressed as plasma-based NGS testing is more widely incorporated into translational and clinical research. Examples illustrating the complexity of the analyses and giving support for confidence in ctDNA testing results will be given. Citation Format: Daniel Stetson, Brian Dougherty, Ambar Ahmed, Tristan Lubinski, Aleksandra Markovets, Kenneth Thress, Robert McEwen, Gaia Schiavon, David Whitston, Barrett Nuttall, J. Carl Barrett. Examination of analytical factors impacting concordance of plasma-tumor testing by next-generation sequencing (NGS) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-249. doi:10.1158/1538-7445.AM2017-LB-249

Abstract 5268: Seq2C: from sequence to copy number for cancer samples

Targeted sequencing is used increasingly in clinics to guide therapeutic decisions by measuring mutations, small indels and/or rearrangements in cancer genes. An ability to use the same platform to detect additional oncogene activation (or tumor suppressor loss) through copy number changes could significantly expand the number of patients able to benefit from targeted therapies. Many currently available tools either requires a matched normal, works only for whole genome or exome sequencing, or don9t work for PCR-based targeted sequencing. In addition, no tools available to detect breakpoints within a gene from targeted sequencing. A versatile copy number analysis tool from sequencing is needed to maximize the value of the sequencing routinely applied in clinics. Here we presented a novel computational tool, Seq2C (Sequencing To Copy Number), which is versatile to handle various situations and reports aberrations at gene level ready for interpretation. Seq2C works at cohort level and does not require a matched ‘normal’, though it can optionally use one or more normal samples for small ( Another distinct feature differentiating Seq2C from other currently available tools is that Seq2C identifies breakpoints and detects one or more exon deletion or duplication rearrangements within a gene, which is common in tumor suppressors as a mechanism to lose function. In addition, it can also detect potential fusions in genes such as ALK and ERG, where a copy number change is often accompanied with the fusion and a breakpoint can thus be called by Seq2C. Furthermore, it can predict gender from exome or whole genome sequencing. We applied Seq2C to exome sequencing of CCLE cell lines, and showed that it produced gene level copy number data highly correlated to those derived from microarrays, the current gold standard. Interestingly, Seq2C identified one or more exon deletions in several common tumor suppressors, such as TP53, PTEN, CDKN2A, NF1, STK11 and RB1, in cell lines with no known aberrations. They were supported by RNA-Seq data. It also correctly called known ERG fusion in prostate cell line NCI-H660 and identified a previously un-reported EML4-ALK fusion in a pancreatic cancer cell line SNU-324, which is confirmed by RNA-Seq data, suggesting EML4-ALK is not limited to lung cancer. In conclusion, Seq2C is a versatile copy number analysis tool for sequencing and will be useful for cancer research. Seq2C is freely available in GitHub. Citation Format: Zhongwu Lai, Aleksandra Markovets, Jonathan Dry. Seq2C: from sequence to copy number for cancer samples. [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 5268.

Abstract LB-C22: Acquired resistance to the cMET inhibitor savolitinib in lung cancer models through EGFR/mTOR/MYC deregulation and adoption of PIM signaling

Lung cancer is the most common cause of cancer death globally with a significant, unmet need for more efficacious treatments. Aberrant receptor tyrosine kinase (RTK) signaling is a well-documented driver of disease onset and progression in multiple cancer types, including non-small cell lung cancer (NSCLC), where the cMET RTK contributes to tumor progression, maintenance and resistance to targeted therapies. Here, we explore the therapeutic potential of the potent and selective cMET inhibitor savolitinib (volitinib, AZD6094, HMPL-504) in NSCLC and begin to elucidate mechanisms of acquired savolitinib resistance in preclinical models. Using in vitro proliferation assays and immunoblot analysis, we determine that savolitinib rapidly inhibits cMET auto-phosphorylation/activation and reduces the viability of NSCLC cell lines NCI-H1993 and EBC-1 with a GI50 of 4.20 nM and 2.14 nM, respectively. In vivo, once daily treatment of NCI-H1993 xenografts with 3.0 mg/kg savolitinib significantly slows tumor growth, whereas treatment of EBC-1 xenografts with 30.0 mg/kg results in tumor stasis. Importantly, we observe tumor regressions in a patient-derived xenograft model of a NSCLC lymph node metastasis, HLXF-036LN, dosed with savolitinib 50.0 mg/kg once daily. Pharmacodynamic analysis of in vitro and in vivo models shows that savolitinib sensitivity correlates with blockade of PI3K/AKT and MAPK signaling, and interestingly, with cMYC (MYC) protein down-regulation. To elucidate mechanisms of acquired resistance in NSCLC, we generated savolitinib resistance in vitro using the NCI-H1993 and EBC-1 cell lines and further sub-cloned resistant NCI-H1993 cells to study the heterogeneity of resistance mechanisms. Using small-molecule screening, phospho-protein arrays and interrogation of signaling pathway activity by immunoblot, we identify 1) deregulated mTORC1/2 signaling and 2) the uncoupling of MYC expression from cMET activation as commonly contributing to resistance in all clones tested. RNA interference (siRNA) and MYC over-expression experiments confirm the novel finding that sustained MYC expression can partially drive resistance to a tyrosine kinase inhibitor such as savolitinib. Additionally, we identify clone-specific resistance mechanisms arising via a previously-described switch to EGFR dependence or by our novel finding of a de novo requirement for PIM signaling. Taken together, this work demonstrates the preclinical efficacy of savolitinib in NSCLC and provides an initial characterization of potential resistance mechanisms, identifying core resistance targets and clone-specific vulnerabilities that could be exploited to counter acquired savolitinib resistance that may emerge in the clinic. Citation Format: Ryan E. Henry, Evan R. Barry, Brendon Ladd, Aleksandra Markovets, Garry J. Beran, Yongxin Ren, Feng Zhou, Lillian Castriotta, Ammar Adam, Weiguo Qing, Weiguo Su, Edwin Clark, Celina M. D9Cruz, Alwin Schuller. Acquired resistance to the cMET inhibitor savolitinib in lung cancer models through EGFR/mTOR/MYC deregulation and adoption of PIM signaling. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr LB-C22.