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.

Whole transcriptome profiling of patient-derived xenograft models as a tool to identify both tumor and stromal specific biomarkers.

The tumor microenvironment is emerging as a key regulator of cancer growth and progression, however the exact mechanisms of interaction with the tumor are poorly understood. Whilst the majority of genomic profiling efforts thus far have focused on the tumor, here we investigate RNA-Seq as a hypothesis-free tool to generate independent tumor and stromal biomarkers, and explore tumor-stroma interactions by exploiting the human-murine compartment specificity of patient-derived xenografts (PDX).Across a pan-cancer cohort of 79 PDX models, we determine that mouse stroma can be separated into distinct clusters, each corresponding to a specific stromal cell type. This implies heterogeneous recruitment of mouse stroma to the xenograft independent of tumor type. We then generate cross-species expression networks to recapitulate a known association between tumor epithelial cells and fibroblast activation, and propose a potentially novel relationship between two hypoxia-associated genes, human MIF and mouse Ddx6. Assessment of disease subtype also reveals MMP12 as a putative stromal marker of triple-negative breast cancer. Finally, we establish that our ability to dissect recruited stroma from trans-differentiated tumor cells is crucial to identifying stem-like poor-prognosis signatures in the tumor compartment.In conclusion, RNA-Seq is a powerful, cost-effective solution to global analysis of human tumor and mouse stroma simultaneously, providing new insights into mouse stromal heterogeneity and compartment-specific disease markers that are otherwise overlooked by alternative technologies. The study represents the first comprehensive analysis of its kind across multiple PDX models, and supports adoption of the approach in pre-clinical drug efficacy studies, and compartment-specific biomarker discovery.

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.

The MET Inhibitor AZD6094 (Savolitinib, HMPL-504) Induces Regression in Papillary Renal Cell Carcinoma Patient-Derived Xenograft Models.

PURPOSE: Papillary renal cell carcinoma (PRCC) is the second most common cancer of the kidney and carries a poor prognosis for patients with nonlocalized disease. The HGF receptor MET plays a central role in PRCC and aberrations, either through mutation, copy number gain, or trisomy of chromosome 7 occurring in the majority of cases. The development of effective therapies in PRCC has been hampered in part by a lack of available preclinical models. We determined the pharmacodynamic and antitumor response of the selective MET inhibitor AZD6094 in two PRCC patient-derived xenograft (PDX) models. EXPERIMENTAL DESIGN: Two PRCC PDX models were identified and MET mutation status and copy number determined. Pharmacodynamic and antitumor activity of AZD6094 was tested using a dose response up to 25 mg/kg daily, representing clinically achievable exposures, and compared with the activity of the RCC standard-of-care sunitinib (in RCC43b) or the multikinase inhibitor crizotinib (in RCC47). RESULTS: AZD6094 treatment resulted in tumor regressions, whereas sunitinib or crizotinib resulted in unsustained growth inhibition. Pharmacodynamic analysis of tumors revealed that AZD6094 could robustly suppress pMET and the duration of target inhibition was dose related. AZD6094 inhibited multiple signaling nodes, including MAPK, PI3K, and EGFR. Finally, at doses that induced tumor regression, AZD6094 resulted in a dose- and time-dependent induction of cleaved PARP, a marker of cell death. CONCLUSIONS: Data presented provide the first report testing therapeutics in preclinical in vivo models of PRCC and support the clinical development of AZD6094 in this indication.

Identification of a subset of human non-small cell lung cancer patients with high PI3Kß and low PTEN expression, more prevalent in squamous cell carcinoma.

PURPOSE: The phosphoinositide 3-kinase (PI3K) pathway is a major oncogenic signaling pathway and an attractive target for therapeutic intervention. Signaling through the PI3K pathway is moderated by the tumor suppressor PTEN, which is deficient or mutated in many human cancers. Molecular characterization of the PI3K signaling network has not been well defined in lung cancer; in particular, the role of PI3Kß and its relation to PTEN in non-small cell lung cancer NSCLC remain unclear. EXPERIMENTAL DESIGN: Antibodies directed against PI3Kß and PTEN were validated and used to examine, by immunohistochemistry, expression in 240 NSCLC resection tissues [tissue microarray (TMA) set 1]. Preliminary observations were extended to an independent set of tissues (TMA set 2) comprising 820 NSCLC patient samples analyzed in a separate laboratory applying the same validated antibodies and staining protocols. The staining intensities for PI3Kß and PTEN were explored and colocalization of these markers in individual tumor cores were correlated. RESULTS: PI3Kß expression was elevated significantly in squamous cell carcinomas (SCC) compared with adenocarcinomas. In contrast, PTEN loss was greater in SCC than in adenocarcinoma. Detailed correlative analyses of individual patient samples revealed a significantly greater proportion of SCC in TMA set 1 with higher PI3Kß and lower PTEN expression when compared with adenocarcinoma. These findings were reinforced following independent analyses of TMA set 2. CONCLUSIONS: We identify for the first time a subset of NSCLC more prevalent in SCC, with elevated expression of PI3Kß accompanied by a reduction/loss of PTEN, for whom selective PI3Kß inhibitors may be predicted to achieve greater clinical benefit.

Subtypes of primary colorectal tumors correlate with response to targeted treatment in colorectal cell lines.

BACKGROUND: Colorectal cancer (CRC) is a heterogeneous and biologically poorly understood disease. To tailor CRC treatment, it is essential to first model this heterogeneity by defining subtypes of patients with homogeneous biological and clinical characteristics and second match these subtypes to cell lines for which extensive pharmacological data is available, thus linking targeted therapies to patients most likely to respond to treatment. METHODS: We applied a new unsupervised, iterative approach to stratify CRC tumor samples into subtypes based on genome-wide mRNA expression data. By applying this stratification to several CRC cell line panels and integrating pharmacological response data, we generated hypotheses regarding the targeted treatment of different subtypes. RESULTS: In agreement with earlier studies, the two dominant CRC subtypes are highly correlated with a gene expression signature of epithelial-mesenchymal-transition (EMT). Notably, further dividing these two subtypes using iNMF (iterative Non-negative Matrix Factorization) revealed five subtypes that exhibit activation of specific signaling pathways, and show significant differences in clinical and molecular characteristics. Importantly, we were able to validate the stratification on independent, published datasets comprising over 1600 samples. Application of this stratification to four CRC cell line panels comprising 74 different cell lines, showed that the tumor subtypes are well represented in available CRC cell line panels. Pharmacological response data for targeted inhibitors of SRC, WNT, GSK3b, aurora kinase, PI3 kinase, and mTOR, showed significant differences in sensitivity across cell lines assigned to different subtypes. Importantly, some of these differences in sensitivity were in concordance with high expression of the targets or activation of the corresponding pathways in primary tumor samples of the same subtype. CONCLUSIONS: The stratification presented here is robust, captures important features of CRC, and offers valuable insight into functional differences between CRC subtypes. By matching the identified subtypes to cell line panels that have been pharmacologically characterized, it opens up new possibilities for the development and application of targeted therapies for defined CRC patient sub-populations.

Transcriptional pathway signatures predict MEK addiction and response to selumetinib (AZD6244).

Selumetinib (AZD6244, ARRY-142886) is a selective, non-ATP-competitive inhibitor of mitogen-activated protein/extracellular signal-regulated kinase kinase (MEK)-1/2. The range of antitumor activity seen preclinically and in patients highlights the importance of identifying determinants of response to this drug. In large tumor cell panels of diverse lineage, we show that MEK inhibitor response does not have an absolute correlation with mutational or phospho-protein markers of BRAF/MEK, RAS, or phosphoinositide 3-kinase (PI3K) activity. We aimed to enhance predictivity by measuring pathway output through coregulated gene networks displaying differential mRNA expression exclusive to resistant cell subsets and correlated to mutational or dynamic pathway activity. We discovered an 18-gene signature enabling measurement of MEK functional output independent of tumor genotype. Where the MEK pathway is activated but the cells remain resistant to selumetinib, we identified a 13-gene signature that implicates the existence of compensatory signaling from RAS effectors other than PI3K. The ability of these signatures to stratify samples according to functional activation of MEK and/or selumetinib sensitivity was shown in multiple independent melanoma, colon, breast, and lung tumor cell lines and in xenograft models. Furthermore, we were able to measure these signatures in fixed archival melanoma tumor samples using a single RT-qPCR-based test and found intergene correlations and associations with genetic markers of pathway activity to be preserved. These signatures offer useful tools for the study of MEK biology and clinical application of MEK inhibitors, and the novel approaches taken may benefit other targeted therapies.

Identification of biomarkers in human head and neck tumor cell lines that predict for in vitro sensitivity to gefitinib.

Potential biomarkers were identified for in vitro sensitivity to the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib in head and neck cancer. Gefitinib sensitivity was determined in cell lines, followed by transcript profiling coupled with a novel pathway analysis approach. Eleven cell lines were highly sensitive to gefitinib (inhibitor concentration required to give 50% growth inhibition [GI(50)] < 1 microM), three had intermediate sensitivity (GI(50) 1-7 microM), and six were resistant (GI(50) > 7 microM); an exploratory principal component analysis revealed a separation between the genomic profiles of sensitive and resistant cell lines. Subsequently, a hypothesis-driven analysis of Affymetrix data (Affymetrix, Inc., Santa Clara, CA, USA) revealed higher mRNA levels for E-cadherin (CDH1); transforming growth factor, alpha (TGF-alpha); amphiregulin (AREG); FLJ22662; EGFR; p21-activated kinase 6 (PAK6); glutathione S-transferase Pi (GSTP1); and ATP-binding cassette, subfamily C, member 5 (ABCC5) in sensitive versus resistant cell lines. A hypothesis-free analysis identified 46 gene transcripts that were strongly differentiated, seven of which had a known association with EGFR and head and neck cancer (human EGF receptor 3 [HER3], TGF-alpha, CDH1, EGFR, keratin 16 [KRT16], fibroblast growth factor 2 [FGF2], and cortactin [CTTN]). Polymerase chain reaction (PCR) and enzyme-linked immunoabsorbant assay analysis confirmed Affymetrix data, and EGFR gene mutation, amplification, and genomic gain correlated strongly with gefitinib sensitivity. We identified biomarkers that predict for in vitro responsiveness to gefitinib, seven of which have known association with EGFR and head and neck cancer. These in vitro predictive biomarkers may have potential utility in the clinic and warrant further investigation.