Miika Ahdesmaki

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.

PIM Kinase Inhibitor AZD1208 for Treatment of MYC-Driven Prostate Cancer

BACKGROUND PIM1 kinase is coexpressed with c-MYC in human prostate cancers (PCs) and dramatically enhances c-MYC-induced tumorigenicity. Here we examine the effects of a novel oral PIM inhibitor, AZD1208, on prostate tumorigenesis and recurrence. METHODS A mouse c-MYC/Pim1-transduced tissue recombination PC model, Myc-CaP allografts, and human PC xenografts were treated with AZD1208 (n = 5-11 per group). Androgen-sensitive and castrate-resistant prostate cancer (CRPC) models were studied as well as the effects of hypoxia and radiation. RNA sequencing was used to analyze drug-induced gene expression changes. Results were analyzed with χ(2) test. Students t test and nonparametric Mann-Whitney rank sum U Test. All statistical tests were two-sided. RESULTS AZD1208 inhibited tumorigenesis in tissue recombinants, Myc-CaP, and human PC xenograft models. PIM inhibition decreased c-MYC/Pim1 graft growth by 54.3 ± 39% (P < .001), decreased cellular proliferation by 46 ± 14% (P = .016), and increased apoptosis by 326 ± 170% (P = .039). AZD1208 suppressed multiple protumorigenic pathways, including the MYC gene program. However, it also downregulated the p53 pathway. Hypoxia and radiation induced PIM1 in prostate cancer cells, and AZD1208 functioned as a radiation sensitizer. Recurrent tumors postcastration responded transiently to either AZD1208 or radiation treatment, and combination treatment resulted in more sustained inhibition of tumor growth. Cell lines established from recurrent, AZD1208-resistant tumors again revealed downregulation of the p53 pathway. Irradiated AZD1208-treated tumors robustly upregulated p53, providing a possible mechanistic explanation for the effectiveness of combination therapy. Finally, an AZD1208-resistant gene signature was found to be associated with biochemical recurrence in PC patients. CONCLUSIONS PIM inhibition is a potential treatment for MYC-driven prostate cancers including CRPC, and its effectiveness may be enhanced by activators of the p53 pathway, such as radiation.

AZD5153: a novel bivalent BET bromodomain inhibitor highly active against hematologic malignancies

The bromodomain and extraterminal (BET) protein BRD4 regulates gene expression via recruitment of transcriptional regulatory complexes to acetylated chromatin. Pharmacological targeting of BRD4 bromodomains by small molecule inhibitors has proven to be an effective means to disrupt aberrant transcriptional programs critical for tumor growth and/or survival. Herein, we report AZD5153, a potent, selective, and orally available BET/BRD4 bromodomain inhibitor possessing a bivalent binding mode. Unlike previously described monovalent inhibitors, AZD5153 ligates two bromodomains in BRD4 simultaneously. The enhanced avidity afforded through bivalent binding translates into increased cellular and antitumor activity in preclinical hematologic tumor models. In vivo administration of AZD5153 led to tumor stasis or regression in multiple xenograft models of acute myeloid leukemia, multiple myeloma, and diffuse large B-cell lymphoma. The relationship between AZD5153 exposure and efficacy suggests that prolonged BRD4 target coverage is a primary efficacy driver. AZD5153 treatment markedly affects transcriptional programs of MYC, E2F, and mTOR. Of note, mTOR pathway modulation is associated with cell line sensitivity to AZD5153. Transcriptional modulation of MYC and HEXIM1 was confirmed in AZD5153-treated human whole blood, thus supporting their use as clinical pharmacodynamic biomarkers. This study establishes AZD5153 as a highly potent, orally available BET/BRD4 inhibitor and provides a rationale for clinical development in hematologic malignancies. Mol Cancer Ther; 15(11); 2563–74. ©2016 AACR.

Rational selection of syngeneic preclinical tumor models for immunotherapeutic drug discovery

Murine syngeneic tumor models are used to study responses to antitumor immunotherapies. To rationalize model selection, the underlying genetic and immunologic biology of the models was analyzed, allowing parallels to be drawn between models and human disease phenotypes. Murine syngeneic tumor models are critical to novel immuno-based therapy development, but the molecular and immunologic features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Across a panel of commonly used murine syngeneic tumor models, we showed variable responsiveness to immunotherapies. We used array comparative genomic hybridization, whole-exome sequencing, exon microarray analysis, and flow cytometry to extensively characterize these models, which revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell–specific genes that suggested differences in tumor immune infiltrates between models. Further investigation using flow cytometry showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor “inflamed” and “non-inflamed” tumor immune infiltrate phenotypes. We also found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell–rich tumor immune infiltrate has been correlated with increased efficacy of immunotherapies in the clinic, and these differences could underlie the varying response profiles to immunotherapy between the syngeneic models. This characterization highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of immunotherapies as well as combinations with targeted therapies in vivo. Cancer Immunol Res; 5(1); 29–41. ©2016 AACR.

A reliable method for the detection of BRCA1 and BRCA2 mutations in fixed tumour tissue utilising multiplex PCR-based targeted next generation sequencing

BackgroundGermline mutations in BRCA1 or BRCA2 lead to a high lifetime probability of developing ovarian or breast cancer. These genes can also be involved in the development of non-hereditary tumours as somatic BRCA1/2 pathogenic variants are found in some of these cancers. Since patients with somatic BRCA pathogenic variants may benefit from treatment with poly ADP ribose polymerase inhibitors, it is important to be able to test for somatic changes in routinely available tumour samples. Such samples are typically formalin-fixed paraffin-embedded (FFPE) tissue, where the extracted DNA tends to be highly fragmented and of limited quantity, making analysis of large genes such as BRCA1 and BRCA2 challenging. This is made more difficult as somatic changes may be evident in only part of the sample, due to the presence of normal tissue.MethodsWe examined the feasibility of analysing DNA extracted from FFPE ovarian and breast tumour tissue to identify significant DNA variants in BRCA1/ BRCA2 using next generation sequencing methods that were sensitive enough to detect low level mutations, multiplexed to reduce the amount of DNA required and had short amplicon design. The utility of two GeneRead DNAseq Targeted Exon Enrichment Panels with different designs targeting only BRCA1/2 exons, and the Ion AmpliSeq BRCA community panel, followed by library preparation and adaptor ligation using the TruSeq DNA PCR-Free HT Sample Preparation Kit and NGS analysis on the MiSeq were investigated.ResultsUsing the GeneRead method, we successfully analysed over 76% of samples, with >95% coverage of BRCA1/2 coding regions and a mean average read depth of >1000-fold. All mutations identified were confirmed where possible by Sanger sequencing or replication to eliminate the risk of false positive results due to artefacts within FFPE material. Admixture experiments demonstrated that BRCA1/2 variants could be detected if present in >10% of the sample. A sample subset was evaluated using the Ion AmpliSeq BRCA panel, achieving >99% coverage and sufficient read depth for a proportion of the samples.ConclusionsDetection of BRCA1/2 variants in fixed tissue is feasible, and could be performed prospectively to facilitate optimum treatment decisions for ovarian or breast cancer patients.

An evaluation of the challenges to developing tumor BRCA1 and BRCA2 testing methodologies for clinical practice

Ovarian cancer patients with germline or somatic pathogenic variants benefit from treatment with poly ADP ribose polymerase (PARP) inhibitors. Tumor BRCA1/2 testing is more challenging than germline testing as the majority of samples are formalin‐fixed paraffin embedded (FFPE), the tumor genome is complex, and the allelic fraction of somatic variants can be low. We collaborated with 10 laboratories testing BRCA1/2 in tumors to compare different approaches to identify clinically important variants within FFPE tumor DNA samples. This was not a proficiency study but an inter‐laboratory comparison to identify common issues. Each laboratory received the same tumor DNA samples ranging in genotype, quantity, quality, and variant allele frequency (VAF). Each laboratory performed their preferred next‐generation sequencing method to report on the variants. No false positive results were reported in this small study and the majority of methods detected the low VAF variants. A number of variants were not detected due to the bioinformatics analysis, variant classification, or insufficient DNA. The use of hybridization capture or short amplicon methods are recommended based on a bioinformatic assessment of the data. The study highlights the importance of establishing standards and standardization for tBRCA testing particularly when the test results dictate clinical decisions regarding life extending therapies.

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

Prioritisation of structural variant calls in cancer genomes

Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants.

Abstract 4186: Syngenomic fingerprint: the biomic characterization of the mouse syngeneic tumor models

The pre-clinical assessment of immuno-oncology (IO) therapies can be enabled by the use of murine syngeneic tumors established in immuno-competent mice. With the aims of selecting relevant models and of minimizing animal experimentation by reducing the number of models tested, the full characterisation of syngeneic models at the transcriptomic and genomic level is a key objective for pre-clinical scientists. Model characterisation includes global aCGH, exon array analysis and FACS profiling alongside exome sequencing. The model data is undergoing hypothesis free and driven analyses which are already generating valuable insights. Comparison of in vivo tumor samples with their in vitro equivalents has highlighted enrichment for a number of immune pathways; as has the comparison of different tumor lines. The genomic, transcriptomic and ‘proteomic’ model data are being integrated to give a functional output which will act as a ‘Syngenomic Fingerprint’ for each model. The resulting Syngenomic fingerprints will help pre-clinical scientists to refine their in vivo plans through an improved understanding of the limits and advantages as well as the clinical relevance of some of our preclinical models. It is also supporting the targeted modification of models to better match specific human cancer types. Citation Format: John E. Prime, Suzanne Mosely, Jens-Oliver Koopmann, Dennis YQ Wang, Danielle Greenawalt, James Harper, Miika J. Ahdesmaki, Rebecca Leyland, Olivia Harris, Ross Stewart, Philip Brohawn, Brandon Higgs, Bryony Langford, Athula Herath, Robert Kozarski, Jane Coates-Ulrichsen, Judith Anderton, Michelle Morrow, Richard C. A Sainson, Robert W. Wilkinson. Syngenomic fingerprint: the biomic characterization of the mouse syngeneic tumor models. [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 4186.