Diede Brunen

FGFR1 is a potential prognostic biomarker and therapeutic target in head and neck squamous cell carcinoma

Purpose: FGFR1 is a promising therapeutic target in multiple types of solid tumors, including head and neck squamous cell carcinoma (HNSCC). FGFR inhibitors have shown great therapeutic value in preclinical models. However, resistance remains a major setback. In this study, we have investigated the prognostic value of FGFR1 expression in HNSCC, the therapeutic relevance of targeting FGFR with AZD4547, and potential resistant mechanisms. Experimental Design: IHC and FISH were applied on tissue microarrays to investigate FGFR1 protein expression and FGFR1 gene copy numbers in 452 HNSCCs. The sensitivity of HNSCC cell lines to AZD4547, either as single or combination treatment with the EGFR inhibitor gefitinib, was assessed using long-term colony formation assays, short-term viability assays, and biochemical analysis. Results: FGFR1 protein overexpression occurred in 82% (36/44) of human papillomavirus (HPV)–positive HNSCC and 75% (294/392) of HPV-negative HNSCC and relates with poor overall survival and disease-free survival in HPV-negative HNSCC [HR, 3.07; 95% confidence interval (CI), 1.74–6.90; P = 0.001 and HR, 1.53; 95% CI, 1.04–2.39; P = 0.033]. Moreover, the FGFR1 gene was amplified in 3% (3/110) of HPV-negative HNSCC. Treatment of the high FGFR1-expressing cell line CCL30 with AZD4547 reduced cell proliferation and FGFR signaling. Two FGFR-amplified cell lines, SCC147 and BICR16, were resistant to AZD4547 treatment due to EGFR signaling. Combined AZD4547 and gefitinib treatment synergistically inhibited the proliferation of resistant cell lines. Conclusions: Here, we identify high FGFR1 expression as a candidate prognostic biomarker in HPV-negative HNSCC. Furthermore, we provide a rationale for treating FGFR1-expressing HNSCC with the FGFR inhibitor AZD4547 and for combining AZD4547 and gefitinib in FGFR inhibitor–resistant HNSCC patients. Clin Cancer Res; 22(15); 3884–93. ©2016 AACR.

Drug therapy: Exploiting synthetic lethality to improve cancer therapy

The success of cancer therapies is hampered by a paucity of suitable drug targets and the rapid development of therapy resistance. The concept of synthetic lethality provides a potential solution to these constraints via the identification of novel therapeutic vulnerabilities, as exemplified in two recent studies.

An Acquired Vulnerability of Drug-Resistant Melanoma with Therapeutic Potential

BRAF(V600E) mutant melanomas treated with inhibitors of the BRAF and MEK kinases almost invariably develop resistance that is frequently caused by reactivation of the mitogen activated protein kinase (MAPK) pathway. To identify novel treatment options for such patients, we searched for acquired vulnerabilities of MAPK inhibitor-resistant melanomas. We find that resistance to BRAF+MEK inhibitors is associated with increased levels of reactive oxygen species (ROS). Subsequent treatment with the histone deacetylase inhibitor vorinostat suppresses SLC7A11, leading to a lethal increase in the already-elevated levels of ROS in drug-resistant cells. This causes selective apoptotic death of only the drug-resistant tumor cells. Consistently, treatment of BRAF inhibitor-resistant melanoma with vorinostat in mice results in dramatic tumor regression. In a study in patients with advanced BRAF+MEK inhibitor-resistant melanoma, we find that vorinostat can selectively ablate drug-resistant tumor cells, providing clinical proof of concept for the novel therapy identified here.

Intrinsic resistance to PIM kinase inhibition in AML through p38α-mediated feedback activation of mTOR signaling

Although conventional therapies for acute myeloid leukemia (AML) and diffuse large B-cell lymphoma (DLBCL) are effective in inducing remission, many patients relapse upon treatment. Hence, there is an urgent need for novel therapies. PIM kinases are often overexpressed in AML and DLBCL and are therefore an attractive therapeutic target. However, in vitro experiments have demonstrated that intrinsic resistance to PIM inhibition is common. It is therefore likely that only a minority of patients will benefit from single agent PIM inhibitor treatment. In this study, we performed an shRNA-based genetic screen to identify kinases whose suppression is synergistic with PIM inhibition. Here, we report that suppression of p38α (MAPK14) is synthetic lethal with the PIM kinase inhibitor AZD1208. PIM inhibition elevates reactive oxygen species (ROS) levels, which subsequently activates p38α and downstream AKT/mTOR signaling. We found that p38α inhibitors sensitize hematological tumor cell lines to AZD1208 treatment in vitro and in vivo. These results were validated in ex vivo patient-derived AML cells. Our findings provide mechanistic and translational evidence supporting the rationale to test a combination of p38α and PIM inhibitors in clinical trials for AML and DLBCL.

Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer human primary tumor data

Two genes are synthetically lethal (SL) when defects in both are lethal to a cell but a single defect is non-lethal. SL partners of cancer mutations are of great interest as pharmacological targets; however, identifying them by cell line-based methods is challenging. Here we develop MiSL (Mining Synthetic Lethals), an algorithm that mines pan-cancer human primary tumour data to identify mutation-specific SL partners for specific cancers. We apply MiSL to 12 different cancers and predict 145,891 SL partners for 3,120 mutations, including known mutation-specific SL partners. Comparisons with functional screens show that MiSL predictions are enriched for SLs in multiple cancers. We extensively validate a SL interaction identified by MiSL between the IDH1 mutation and ACACA in leukaemia using gene targeting and patient-derived xenografts. Furthermore, we apply MiSL to pinpoint genetic biomarkers for drug sensitivity. These results demonstrate that MiSL can accelerate precision oncology by identifying mutation-specific targets and biomarkers.

PIM Kinases Are a Potential Prognostic Biomarker and Therapeutic Target in Neuroblastoma

The majority of high-risk neuroblastoma patients are refractory to, or relapse on, current treatment regimens, resulting in 5-year survival rates of less than 50%. This emphasizes the urgent need to identify novel therapeutic targets. Here, we report that high PIM kinase expression is correlated with poor overall survival. Treatment of neuroblastoma cell lines with the pan-PIM inhibitors AZD1208 or PIM-447 suppressed proliferation through inhibition of mTOR signaling. In a panel of neuroblastoma cell lines, we observed a marked binary response to PIM inhibition, suggesting that specific genetic lesions control responses to PIM inhibition. Using a genome-wide CRISPR-Cas9 genetic screen, we identified NF1 loss as the major resistance mechanism to PIM kinase inhibitors. Treatment with AZD1208 impaired the growth of NF1 wild-type xenografts, while NF1 knockout cells were insensitive. Thus, our data indicate that PIM inhibition may be a novel targeted therapy in NF1 wild-type neuroblastoma. Mol Cancer Ther; 17(4); 849–57. ©2018 AACR.

Abstract A27: Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer primary tumor data

Synthetic lethality, in which a single gene defect leads to dependency on a second gene that is otherwise not essential, is an attractive paradigm to identify targeted therapies for somatic mutations. Current methods to detect synthetic lethal (SL) partners for somatic mutations use large-scale shRNA screens in cell lines, combine shRNA data with tumor genomic data or use human orthologs of yeast SL interactions. These approaches are limited as they rely on cell line or yeast data, which are not representative of primary tumors. We have developed MiSL, a novel computational algorithm that utilizes large pan-cancer patient datasets (mutation, copy number and gene expression) to identify SL partners for specific mutations in specific cancer types. The underlying assumption of our approach is that, across multiple cancers, SL partners of a mutation will be amplified more frequently or deleted less frequently, with concordant changes in expression, in primary tumor samples harboring the mutation. Application of MiSL produced candidate SL partners for 30-80% of recurrent mutations in 12 cancers. Importantly, MiSL identified candidate SL partners for mutations (mut) in genes such as IDH1 that are not well-represented in existing cell lines. This is a distinct advantage over recent computational methods that combine shRNA data along with genomic data to make their predictions. Since MiSL uses only genomic and gene expression data, it allows assessment of a wide range of primary human tumors and mutations found in large primary tumor data sets such as TCGA. We validated MiSL using existing data and large-scale shRNA experiments we performed in doxycycline-inducible expression systems. We found that IDH1mut MiSL candidates in acute myeloid leukemia (AML) were enriched (p=0.004) for essential genes specific to IDH1mut but not IDH1 wildtype cells determined by a DECIPHER shRNA screen covering 9,965 human genes performed in doxycycline-inducible IDH1 (R132) THP-1 cells. Importantly, 1 out of 5 MiSL candidates was a SL partner of IDH1mut in AML cells as per the shRNA screen, indicating MiSL9s strong predictive power. Also, for multiple mutations in colorectal cancer, MiSL candidates were enriched (p Next, we used MiSL to identify novel and druggable SL partners in (i) AML and (ii) breast cancer. MiSL predicted a novel SL interaction in AML between IDH1mut and ACACA, the rate-limiting enzyme of fatty acid synthesis. Consistent with our prediction, pharmacologic or genetic blockade of ACACA prevented cell proliferation in the presence of IDH1mut, but not with IDH1 wildtype, in AML cell lines. Furthermore, when transduced with lentivirus encoding RFP-marked shRNA to ACACA, primary IDH1mut AML cells exhibited markedly reduced engraftment of RFP-positive human CD45+CD33+ leukemic cells compared to scrambled non-targeting shRNA (p In summary, MiSL is a general computational solution that finds novel SL interactions. Specifically, IDH1mut-ACACA is the first in vivo validated synthetic lethal in human tumor cells discovered purely by computational analysis of tumor genomic data. MiSL can greatly accelerate identification of pharmacologic targets associated with specific somatic mutations in specific tumor types for all kinds of mutations, thereby making it directly translatable to clinical applications. MiSL can also pinpoint predictive genetic biomarkers that can identify/extend indications for targeted therapies. Citation Format: Subarna Sinha, Daniel Thomas, Steven Chan, Yang Gao, Diede Brunen, Damoun Torabi, Andreas Reinisch, Rene Bernards, Ravindra Majeti, David L. Dill. Systematic discovery of mutation-specific synthetic lethals by mining pan-cancer primary tumor data. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Targeting the Vulnerabilities of Cancer; May 16-19, 2016; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(1_Suppl):Abstract nr A27.

Abstract LB-B07: MiSL: a method for mining synthetic lethal partners of somatic mutations identifies acetyl-CoA carboxylase as a synthetic lethal interactor of the IDH1 mutation in Leukemia

Synthetic lethality, in which a single gene defect leads to dependency on a second gene that is otherwise not essential, is an attractive paradigm to identify targeted therapies for cancer-specific mutations. Current methods to detect synthetic lethal (SL) partners for somatic mutations rely on large-scale shRNA screens in cell-lines or use human orthologs of yeast SL interactions, both of which are not necessarily representative of primary tumors and have incomplete coverage. We have developed MiSL, a novel Boolean implication-based algorithm that utilizes large pan-cancer patient datasets (mutation, copy number and gene expression) to identify SL partners for cancer mutations. The underlying assumption of our approach is that, across multiple cancers, SL partners of a mutation will be amplified more frequently or deleted less frequently, with concordant changes in expression, in primary tumor samples harboring the mutation. Pan-cancer analysis discovers robust biological relationships that are likely to be independent of cancer subtype and increases statistical power. First, we sought to validate MiSL using existing knowledge and large-scale shRNA data. Consistent with prior knowledge, MiSL candidates for BRCA1 mutation (mut) in breast cancer were enriched for DNA repair genes (p = .0.006). We also found: (1) significant overlap (p = 0.002) between leukemia IDH1mut MiSL candidates and essential genes in IDH1mut cells determined by a DECIPHER shRNA screen we performed in doxycycline-inducible IDH1 (R132) THP-1 cells, and (2) for multiple mutations in colorectal cancer, MiSL candidates were enriched (p Next, we experimentally confirmed novel SL partners that are druggable in (i) acute myeloid leukemia (AML) and (ii) breast cancer. We tested the response to 17 drugs whose targets were predicted to be SL partners of IDH1mut in AML by MiSL. For a majority of these drugs, treatment with the drug reduced cell viability selectively in the presence of the mutation in AML cell-lines, suggesting that the MiSL identifies true SL partners. Importantly, MiSL predicted a novel SL interaction in AML between IDH1mut and ACACA, the rate-limiting enzyme that controls lipid biosynthesis. Consistent with our prediction, selective inhibition of ACACA with shRNA or a small molecule inhibitor TOFA prevented cell proliferation in the presence of IDH1mut but not with IDH1 wildtype in AML cell-lines and primary blasts (n = 5/6 IDH1mut/IDH1 wt, p = 0.04). This suggests a novel role for IDH1mut in reprogramming lipid metabolism. MiSL also predicted that AKT1 is a SL partner of PIK3CAmut in breast cancer which we experimentally confirmed using 8 breast cancer lines. All four PIK3CAmut (but not wildtype) breast cancers were sensitive to AKT1 inhibition in viability and colony assays. In conclusion, MiSL is a general computational solution that finds novel SL interactions and its use can greatly accelerate novel target discovery for precision medicine in cancer. Using primary patient data allows it to capture in vivo tumor evolution in the human microenvironment, revealing SL interactions missed by existing methods. It can be widely applicable and can greatly accelerate novel target discovery for precision medicine in cancer. Citation Format: Subarna Sinha, Daniel Thomas, Yang Gao, Steven M. Chan, Diede Brunen, Rene Bernards, Ravindra Majeti, David L. Dill. MiSL: a method for mining synthetic lethal partners of somatic mutations identifies acetyl-CoA carboxylase as a synthetic lethal interactor of the IDH1 mutation in Leukemia. [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-B07.