Potential Synthetic Lethal Interactions Research Articles

Synthetic lethality and the minimal genome size problem.

Gene knockout studies suggest that ~300 genes in a bacterial genome and ~1,100 genes in a yeast genome cannot be deleted without loss of viability. These single-gene knockout experiments do not account for negative genetic interactions, when two or more genes can each be deleted without effect, but their joint deletion is lethal. Thus, large-scale single-gene deletion studies underestimate the size of a minimal gene set compatible with cell survival. In yeast Saccharomyces cerevisiae, the viability of all possible deletions of gene pairs (2-tuples), and of some deletions of gene triplets (3-tuples), has been experimentally tested. To estimate the size of a yeast minimal genome from that data, we first established that finding the size of a minimal gene set is equivalent to finding the minimum vertex cover in the lethality (hyper)graph, where the vertices are genes and (hyper)edges connect k-tuples of genes whose joint deletion is lethal. Using the Lovász-Johnson-Chvatal greedy approximation algorithm, we computed the minimum vertex cover of the synthetic-lethal 2-tuples graph to be 1,723 genes. We next simulated the genetic interactions in 3-tuples, extrapolating from the existing triplet sample, and again estimated minimum vertex covers. The size of a minimal gene set in yeast rapidly approaches the size of the entire genome even when considering only synthetic lethalities in k-tuples with small k. In contrast, several studies reported successful experimental reductions of yeast and bacterial genomes by simultaneous deletions of hundreds of genes, without eliciting synthetic lethality. We discuss possible reasons for this apparent contradiction.IMPORTANCEHow can we estimate the smallest number of genes sufficient for a unicellular organism to survive on a rich medium? One approach is to remove genes one at a time and count how many of such deletion strains are unable to grow. However, the single-gene knockout data are insufficient, because joint gene deletions may result in negative genetic interactions, also known as synthetic lethality. We used a technique from graph theory to estimate the size of minimal yeast genome from partial data on synthetic lethality. The number of potential synthetic lethal interactions grows very fast when multiple genes are deleted, revealing a paradoxical contrast with the experimental reductions of yeast genome by ~100 genes, and of bacterial genomes by several hundreds of genes.

VRK1 Is a Synthetic-Lethal Target in VRK2-Deficient Glioblastoma.

A paralog synthetic-lethal interaction between VRK1 and VRK2 sensitizes VRK2-methylated glioblastoma to perturbation of VRK1 kinase activity, supporting VRK1 as a drug discovery target in this disease.

Abstract LB131: Genome-wide CRISPR-Cas9 screen parallel with transcriptome RNAseq to identify synthetic lethal drug targets to cisplatin/doxorubicin in triple-negative breast cancer

Abstract Triple-negative breast cancer (TNBC) accounts for 15-20% of cases yet disproportional accounts for 35% of breast cancer deaths. Chemotherapy remains the first-line treatment for TNBC. Despite the great research efforts, above half of TNBC patients have developed drug resistance after chemotherapies. Thus, the study of chemo-resistance and identification of novel targets are critical to improving TNBC treatment. In our study, we compared genomic profiles between TNBC cell lines and patients' samples and selected the most representative one, MDA-MB-231,for TNBC chemotherapy-poor responders. Then, Genome-wide CRISPR-Cas9 screen and RNAseq were performed in MDA-MB-231 to identify potential synthetic lethal targets to Cisplatin/Doxorubicin. To identify cell lines that correspond to poor responder patients, we selected genomic profiles of 17 good responders, 36 poor responders, and 21 TNBC cell lines from GEO database. We used Hierarchical clustering analysis, Spearman's rank correlation, and GSEA analysis to determine the representative cell lines in gene expression level and pathway level. With the results from our analysis, MDA-MB-231 is most representative among 21 TNBC cell lines. To identify essential genes and pathways for cell survival under Cisplatin/Doxorubicin treatment, we performed genome-wide CRISPR-Cas9 knockout screens in MDA-MB-231 and introduced CRISPR library TKOV3 into cells by lentivirus. After puromycin selection, the surviving cells were treated with Cisplatin/Doxorubicin for 21 days and sgRNAs were sequenced at ~80 million reads per sample to achieve a 600x coverage over the TKOV3 library. To accurate the CRISPR-Cas9 screen results and capture the transcriptomic changes during the Cisplatin/Doxorubicin treatment, we performed RNAseq from MDA-MD-231 after treating in same drug conditions matched with the CRISPR screen. By the MAGeCK algorithm, we generated the list of candidate genes that can form a synthetic lethal partnership with Cisplatin/Doxorubicin. Our negative selection screen confirmed that loss of essential genes from DNA damage repair and regulation of DNA replication pathways, such as BCL2L1, ATM, CDC25B, NBN, sensitizes cells to Cisplatin/Doxorubicin, which has been reported in DNA damage drug synthetic lethal studies. Meanwhile, our analysis also revealed hundreds of unrecognized genes involved in the G2/M DNA damage checkpoint, AMPK signaling pathway, mTOR signaling pathway, and Hsp90-mediated pathways. In addition, the pathways related to transcriptomic response to Cisplatin/Doxorubicin from RNAseq data show many differences with essential pathways shown in the CRISPR screen, which proposed a complex regulation system in cell response to DNA damage drug. In general, Genome-wide CRISPR-Cas9 screen along with transcriptome RNAseq is efficient to identify essential genes that have potential synthetic lethal interaction with Cisplatin/Doxorubicin. This provides new opportunities for combination therapies in TNBC chemo-resistant patients. Citation Format: Shuai Shao, Shan Tang, Xue Wu, Yue Zhao, Huo Yang, Lijun Cheng, Lang Li. Genome-wide CRISPR-Cas9 screen parallel with transcriptome RNAseq to identify synthetic lethal drug targets to cisplatin/doxorubicin in triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB131.

MAGCN: A Multiple Attention Graph Convolution Networks for Predicting Synthetic Lethality.

Synthetic lethality (SL) is a potential cancer therapeutic strategy and drug discovery. Computational approaches to identify synthetic lethality genes have become an effective complement to wet experiments which are time consuming and costly. Graph convolutional networks (GCN) has been utilized to such prediction task as be good at capturing the neighborhood dependency in a graph. However, it is still a lack of the mechanism of aggregating the complementary neighboring information from various heterogeneous graphs. Here, we propose the Multiple Attention Graph Convolution Networks for predicting synthetic lethality (MAGCN). First, we obtain the functional similarity features and topological structure features of genes from different data sources respectively, such as Gene Ontology data and Protein-Protein Interaction. Then, graph convolutional network is utilized to accumulate the knowledge from neighbor nodes according to synthetic lethal associations. Meanwhile, we propose a multiple graphs attention model and construct a multiple graphs attention network to learn the contribution factors of different graphs to generate embedded representation by aggregating these graphs. Finally, the generated feature matrix is decoded to predict potential synthetic lethal interaction. Experimental results show that MAGCN is superior to other baseline methods. Case study demonstrates the ability of MAGCN to predict human SL gene pairs.

Abstract 549: Genome-wide CRISPR-Cas9 screen and RNAseq analysis identify new candidate synthetic lethality partners to PARP inhibitor in triple-negative breast cancer

Abstract As monotherapy, Poly (ADP-ribose) polymerase inhibitors (PARPi) have achieved remarkable success in treating tumors with germline BRCA1/2 mutation due to the synthetic lethality in DNA damage response. The efficacy of PARPi in combination with other therapeutic agents is still under investigation. However, BRCA mutant tumors constitute only 5-10% of total breast cancer diagnoses. Therefore, to extend the benefit of PARPi beyond BRCA mutant tumors, it is imperative to identify other genetic determinants that also contribute to PARPi sensitivity. Such knowledge also provides valuable insight into the development of combination therapies involving PARPi. To identify genes and pathways that are essential for cell survival under PARPi treatment, we performed genome-wide CRISPR-Cas9 knockout screens in a BRCA-functional, triple-negative breast cancer cell line MDA-MB-231 treated with talazoparib at a low dose (IC20, 20nM). Toronto CRISPR human knockout library TKOV3 was introduced into cells using lentivirus at MOI of 0.3~0.4. After puromycin selection, the surviving cells were treated with talazoparib or DMSO for 20 days before harvesting. The sgRNAs were sequenced at ~30 million reads per sample to achieve a 300x coverage over the TKOV3 library. To increase the accuracy of the CRISPR-Cas9 screen result, and to capture the transcriptomic changes during a relative long-term PARPi treatment as used in the screening process, we also did RNAseq profiling in MDA-MD-231 cells cultured in the conditions matched with the CRISPR-Cas9 screen. Using mRNA level as a filter to remove non-expressed genes, we were able to generate a list of candidate genes that have the potential to form synthetic lethal partnership with talazoparib. Our negative selection screen confirmed that loss of key components of DNA damage repair and DNA replication pathways such as ATM, RNASEH2C, ESCO2, EME1, and several components of Fanconi Anemia (FA) core complex sensitizes cells to talazoparib, as has been reported in similar screens using other PARP inhibitors. Meanwhile, our analysis also revealed several previously unrecognized partner genes involved in subcellular trafficking, RNA splicing, and microRNA biogenesis. In addition, the RNAseq profile depicted a transcriptomic response to long-term talazoparib treatment that has many distinctions from the essential pathways shown in the CRISPR-Cas9 screen, suggesting a complex, multi-layer regulation system in cell response to PARP inhibition. Our study identified a set of genes that have potential synthetic lethal interaction with PARPi. The status of these genes can be used to identify subset of triple-negative breast cancer patients who could potentially benefit from PARPi treatment. Strategies targeting these genes represent new opportunities for PARPi combination therapies. Citation Format: Xue Wu, Yue Zhao, Xiaoyu Xie, Xiaoling Xuei, Yunlong Liu, Lijun Cheng, Lang Li. Genome-wide CRISPR-Cas9 screen and RNAseq analysis identify new candidate synthetic lethality partners to PARP inhibitor in triple-negative breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 549.

Predicting synthetic lethal interactions in human cancers using graph regularized self-representative matrix factorization

BackgroundSynthetic lethality has attracted a lot of attentions in cancer therapeutics due to its utility in identifying new anticancer drug targets. Identifying synthetic lethal (SL) interactions is the key step towards the exploration of synthetic lethality in cancer treatment. However, biological experiments are faced with many challenges when identifying synthetic lethal interactions. Thus, it is necessary to develop computational methods which could serve as useful complements to biological experiments.ResultsIn this paper, we propose a novel graph regularized self-representative matrix factorization (GRSMF) algorithm for synthetic lethal interaction prediction. GRSMF first learns the self-representations from the known SL interactions and further integrates the functional similarities among genes derived from Gene Ontology (GO). It can then effectively predict potential SL interactions by leveraging the information provided by known SL interactions and functional annotations of genes. Extensive experiments on the synthetic lethal interaction data downloaded from SynLethDB database demonstrate the superiority of our GRSMF in predicting potential synthetic lethal interactions, compared with other competing methods. Moreover, case studies of novel interactions are conducted in this paper for further evaluating the effectiveness of GRSMF in synthetic lethal interaction prediction.ConclusionsIn this paper, we demonstrate that by adaptively exploiting the self-representation of original SL interaction data, and utilizing functional similarities among genes to enhance the learning of self-representation matrix, our GRSMF could predict potential SL interactions more accurately than other state-of-the-art SL interaction prediction methods.

Biomarkers Predicting Venetoclax Sensitivity and Strategies for Venetoclax Combination Treatment

BCL2 is an antiapoptotic protein commonly expressed in hematologic malignancies. Overexpression of BCL-2 is a poor prognostic factor in acute myeloid leukemia (AML). Venetoclax (ABT-199) is a highly selective BCL2 inhibitor that can induce cell death in multiple leukemia cell lines. Recently, venetoclax received an FDA breakthrough therapy designation for use in combination with hypomethylating agents in treatment-naive patients with AML who are unfit for intensive chemotherapy. However, venetoclax was only modestly effective as monotherapy in relapsed/refractory AML (19% CR/CRi). The aim of the current study is to integrate genomic and functional screen data to identify biomarkers to predict venetoclax sensitivity and resistance in AML, and to identify potential venetoclax combination treatment strategies. In this study, we investigated approximately 200 AML patient samples and correlated clinical parameters, whole exome sequence data, and RNAseq gene expression data with in vitro drug screening data (drug area under the curve (AUC)) to identify subsets of AML samples with sensitivity or resistance to venetoclax alone and in combinations with 10 small molecular inhibitors (Array-382, dasatinib, JQ-1, idelalisib, quizartinib, palbociclib, panobinostat, ruxolitinib, sorafenib, and trametinib). For gene expression, we observed that venetoclax correlated with 3 gene expression clusters (coefficient frequency: 0.94, 0.80 and 0.71 respectively) among 21 gene expression clusters in AML, associated with innate immune system, neutrophil degranulation, and interleukin-10 signaling. Among the BCL2 gene family, venetoclax AUC positively correlated with BCL2A1 (r=0.59, p In summary, we have identified that CD14 and/or CLEC7A could be used as biomarkers to predict venetoclax sensitivity in AML, and we propose to combine venetoclax and palbociclib to treat patients with a venetoclax resistant profile (high CD14/CLEC7A expression or high BCL2A1 expression, or presence of KRAS mutations). Disclosures Druker:Beta Cat: Membership on an entity9s Board of Directors or advisory committees; Fred Hutchinson Cancer Research Center: Research Funding; McGraw Hill: Patents & Royalties; Vivid Biosciences: Membership on an entity9s Board of Directors or advisory committees; Oregon Health & Science University: Patents & Royalties; Bristol-Meyers Squibb: Research Funding; GRAIL: Consultancy, Membership on an entity9s Board of Directors or advisory committees; ARIAD: Research Funding; Third Coast Therapeutics: Membership on an entity9s Board of Directors or advisory committees; Gilead Sciences: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Monojul: Consultancy; Novartis Pharmaceuticals: Research Funding; Millipore: Patents & Royalties; Leukemia & Lymphoma Society: Membership on an entity9s Board of Directors or advisory committees, Research Funding; ALLCRON: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Aileron Therapeutics: Consultancy; Patient True Talk: Consultancy; Cepheid: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Henry Stewart Talks: Patents & Royalties; Celgene: Consultancy; Amgen: Membership on an entity9s Board of Directors or advisory committees; MolecularMD: Consultancy, Equity Ownership, Membership on an entity9s Board of Directors or advisory committees; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity9s Board of Directors or advisory committees; Aptose Therapeutics: Consultancy, Equity Ownership, Membership on an entity9s Board of Directors or advisory committees. Majeti:BioMarin: Consultancy; Forty Seven, Inc: Consultancy, Equity Ownership, Membership on an entity9s Board of Directors or advisory committees. Tyner:Incyte: Research Funding; AstraZeneca: Research Funding; Janssen: Research Funding; Takeda: Research Funding; Leap Oncology: Equity Ownership; Seattle Genetics: Research Funding; Genentech: Research Funding; Gilead: Research Funding; Syros: Research Funding; Aptose: Research Funding; Agios: Research Funding.

Abstract 4484: Synthetic essentiality of chromatin remodeling factor CHD1 in PTEN-deficient cancer

Abstract Background: Prostate cancer (PCa) is the second leading cause of cancer death for men in the United States. Up to 70% of primary prostate tumors show loss of heterozygosity (LOH) at the PTEN locus, and loss of PTEN is a key initiation event in PCa development. Synthetic and collateral lethality have provided conceptual frameworks to identify cancer-specific vulnerabilities. Here, we explored an approach to identify potential synthetic lethal interactions through screening mutually exclusive deletion patterns in cancer genomes. Methods: We sought to identify ‘synthetic essential' genes, which might be occasionally deleted in some cancers but almost always retained in the context of a specific tumor suppressor deficiency, and posited that such synthetic essential genes would be therapeutic targets in cancers harboring specific tumor suppressor deficiencies. Results: In addition to known synthetic lethal interactions, this approach uncovered the chromatin helicase DNA-binding factor CHD1 as a putative synthetic essential gene in PTEN-deleted cancers. In PTEN-deleted prostate and breast cancers, the functional analysis showed that CHD1 depletion profoundly and specifically suppressed cell proliferation, survival, and tumorigenic potential. Mechanistically, functional PTEN stimulates GSK3β-mediated phosphorylation of CHD1 degron domains, which promotes CHD1 degradation via β-TrCP-mediated ubiquitination-proteasome pathway. Conversely, PTEN deficiency results in CHD1 protein stabilization, which in turn engages the H3K4me3 mark to activate transcription of the pro-tumorigenic TNFα/NF-κB gene network. In addition, we found CHD1 depletion significantly inhibits the progression of Pten-deficient prostate cancer genetic engineered mouse model. Conclusions: Together, this study identifies CHD1 as a novel downstream effector in PTEN pathway, and verifies CHD1 as a novel therapeutic target in PTEN deficient prostate cancer and breast cancer. Additionally, this study provides a framework for the discovery of trackable targets in cancers harboring specific tumor suppressor deficiencies. Citation Format: Di Zhao. Synthetic essentiality of chromatin remodeling factor CHD1 in PTEN-deficient cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4484.

Abstract A25: Synthetic lethal CRISPR-Cas9 screen imply an oncogenic role for FBXW7 mutations in colon cancer

Abstract Mutations in tumour suppressors and un-druggable oncogenes dominate the landscape of cancer driver genes. Only a minority of colon cancers have mutations in druggable cancer drivers, such as PIK3CA. Conversely, mutations in tumour suppressors such as APC and TP53 are frequent, as are mutations in the notoriously difficult to drug KRAS target. There is an urgent need for new therapeutics to target tumours driven by these mutations: immune checkpoint approaches are likely to only prove effective in the fraction of patients whose tumours bear high mutation loads, which is colon cancer may be restricted to the minority of mismatch repair deficient cancers. The concepts of non-oncogene addiction and synthetic lethality provide a conceptual framework for finding therapeutic targets in these cancers. We have used arrayed siRNA and pooled CRISPR-Cas9 libraries to screen a panel of isogenic and non-isogenic colon cancer cell lines under conditions designed to increase the cells dependency on oncogenic pathways. This panel contains cell lines with mutations in TP53, APC, KRAS, PIK3CA and/or FBXW7 for which we are aiming to identify co-dependencies that consistently segregate with genotype. Our screens have identified a number of novel targets for which reduced expression imposes specific fitness defects on cells with mutant PIK3CA, mutant TP53 or mutant FBXW7. Few of these targets were identified by both siRNA and CRISPR-Cas9 approaches. Furthermore, isogenic pairs of cell lines have not proved helpful for identifying synthetic lethal targets in the KRAS or PIK3CA genotypes. However, we believe the increased penetrance of the CRIPSR-Cas9 approach has uncovered novel candidate synthetic lethal genes that were not found by RNA interference. Although our current screens are not saturating, we have confirmed several previously reported genetic interactions including the requirements for expression of MDM2 in TP53 wild-type cancers and HK2 in colon cancer lines with KRAS mutations. The screens in the FBXW7 genotype were particularly interesting: in addition to identifying a potential synthetic lethal interaction with a target for which a drug has recently entered the clinic, we also found that FBXW7 itself seemed to be required in many of the colon cancers with FBXW7 mutations. This suggests that FBXW7 may sometimes act as an oncogene, rather than as a tumour suppressor in cancer initiation or progression. Finally, we have attempted to validate some of the candidate synthetic lethal genes identified by RNA interference via ultra-deep CRISPR-CAS9 pooled screening, extending the approach of the Vakoc lab (Nature Biotech. 33, 661-667, 2015). We can confirm this method can highlight functional domains of particular significance to a protein's function, but note that many-fold drop outs of sgRNAs can also occur where they target multiple sites in the genome, presumably via a DNA damage response. Citation Format: Jonathan D. Moore, Chantelle Hudson, Paul Russell, Gaganpreet Tiwana, David Walter, Ceri M. Wiggins, Joanne Yarker. Synthetic lethal CRISPR-Cas9 screen imply an oncogenic role for FBXW7 mutations in colon cancer [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr A25.

Abstract 4974: Pharmacogenomic interactions in glioblastoma cell line models

Abstract Glioblastoma (GBM) is the most common and malignant brain tumor. These tumors display a uniform and very short survival time even with treatment, but are highly heterogeneous at the histological and genomic level. To identify effective treatments and dependencies, we profiled the sensitivity of a panel of cancer cell lines to a small molecules and integrated this with systematic analysis of genetic and non-genetic determinants associated with chemical response. Methods. We profiled 381 drugs described in the Cancer Therapeutics Response Portal (CTRP) at 16 different duplicated concentrations across 78 GBM cell lines belonging to two different models: Patient-Derived GBM Cell Lines (PDGCL) and Long-Term GBM Cell Lines (LTGCL) previously included in the Cancer Cell Line Encyclopedia (CCLE). Cell lines were deeply characterized as to genotype and phenotype. As non-genomic determinants we considered: model, growth rate, behavior, stem cell and differentiation markers. Genomic determinants included mutations and somatic copy number alterations (SCNA) computed from whole exome sequencing. Each of these were integrated to determine oncogene and tumor suppressor gene pathway disruption (p53, RB and RTK signaling). At transcriptomic level we considered expression of 20.647 genes and patters described in GBMs (proneural, neural, classical, mesenchymal). Overall we correlated 10,859,643 pharmacogenomic features to discover associations with drug sensitivity. Summary. We developed a brain tumor living tissue bank as platform for preclinical pharmacogenomics analysis. Large-scale phenotypic characterization of GBM models showed increased cellular and molecular heterogeneity among PDGCLs compared to LTGCLs. PDGCLs better recapitulated patient GBM copy-number profiles. GBM cell lines exhibited all major driver mutations in human GBMs, except IDH1. PDGCLs and LTGCLs enriched for proneural and mesenchymal phenotypes, respectively. We identified NAMPT inhibitors as among the compounds with highest activity across cell lines. Integrative pharmacogenomic analyses showed MDM2/4 inhibitors were able to effectively suppress TP53 wild type GBM models, being CDKN1A (p21) expression a robust predictor of drug response in vitro and in vivo. Overall drug resistance across the screen in lines was highly associated with TP53 mutation, however a specific subset of TP53 mutant cell lines bearing simultaneous CDKN2A/B deletions were sensitive to CHK1/2 inhibitors, revealing a potential synthetic lethal interaction of clinical significance in these highly refractory cells. Analysis identified genetic alterations associated with vulnerabilities targeted by small molecules. About 85% of GBM patients display p53 pathway disruption, our results suggest independent pharmacological strategies for two genetic subtypes of GBM determined by TP53 and CDKN1A status. Our analyses provide molecular insights to drive targeted therapies in the new era of precision medicine. Citation Format: Ruben Ferrer-Luna, Shakti H. Ramkissoon, Karl H. Olausson, Lori A. Ramkissoon, Steven Schumacher, Rebecca Lamothe, Jaime H. Cheah, Kristine Pellton, Sam Haidar, Yun J. Kang, Brenton R. Paolella, Cecile Maire, Wenyu Song, Alice Meng, Ahmed Idbaih, Mikael L. Rinne, David A. Reardon, Patrick Y. Wen, Paul A. Clemons, Stuart L. Schreiber, Alykhan F. Shamji, Rameen Beroukhim, Keith L. Ligon. Pharmacogenomic interactions in glioblastoma cell line models [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 4974. doi:10.1158/1538-7445.AM2017-4974

NAMPT inhibition is a novel synthetic lethal therapeutic approach exploiting nuclear-mitochondrial crosstalk in ERCC1-deficient populations.

e23159 Background: ERCC1 (Excision Repair Cross-Complementation group 1) deficiency is the most frequent DNA repair defect in non-small cell lung cancers (NSCLC), making this enzyme an attractive therapeutic target for synthetic lethal (SL) approaches. Previous data support that DNA damage response is involved in regulation of metabolic homeostasis. We hypothesized that ERCC1 deficiency resulted in metabolic reprogramming of cancer cells that in turn generated specific vulnerabilities. Methods: High-throughput proteomic SILAC (stable isotope labeling by aminoacids in cell culture) and metabolomic (LC-MS, GC-MS, LC-QTOF) profiling were performed on a in-house generated NSCLC model of ERCC1 deficiency. Nicotinamide phosphoribosyltransferase (NAMPT) was selected as main hit and revalidated in low-throughput. Sensitivity to NAMPT inhibition was assessed in several NSCLC models. Potential SL interactions were investigated using functional DNA repair and metabolic assays, and transmission electronic microscopy (TEM). Results: We found marked metabolic rewiring in ERCC1-deficient populations, including decreased NAMPT and NAD+ levels and defects in the tricarboxylic acid cycle. These caused exquisite selective sensitivity to NAMPT inhibition in several in vitro and in vivoNSCLC models; these effects were reversed by the restoration of a functional ERCC1 isoform, establishing a causal link with the ERCC1 defective state. TEM, functional DNA repair and metabolic studies revealed structural and functional defects in the mitochondria of ERCC1-deficient cells, and allowed us to propose a model for this nuclear-mitochondrial SL link. A correlation between NAMPT expression and ERCC1 expression was observed in NSCLC patient samples. Conclusions: These findings open novel therapeutic opportunities that exploit a previously undescribed nuclear/mitochondrial SL link between ERCC1 deficiency and NAMPT inhibition in NSCLC. This highlights the potential for targeting DNA repair / metabolic crosstalk for cancer therapy, and support the evaluation of NAMPT inhibitors in ERCC1-deficient tumors.

Isocitrate Dehydrogenase 1 Mutant Cancers Are Metabolically Vulnerable to Inhibition of Acetyl CoA Carboxylase Via a 2-Hydroxyglutarate Independent Mechanism

Introduction: Mutations substituting arginine 132 of isocitrate dehydrogenase 1 (IDH1) are recurrent in acute myeloid leukemia (AML) and several other cancers, resulting in the aberrant production of the onco-metabolite, R-2-hydroxyglutarate (2-HG), as well as an inability to convert cytoplasmic alpha-ketoglutarate to isocitrate via reductive carboxylation. Currently, small molecules that effectively inhibit the neomorphic enzyme and abrogate the production of 2-HG, such as AG-120, are in clinical trials with promising results. However, these inhibitors have not proven to be curative in most AML cases, indicating a need for additional targeted therapies. We have previously investigated synthetic lethal vulnerabilities in IDH1-mutated AML and identified an interaction with BCL2 leading to increased susceptibility to ABT-199 (Chan et al, 2015). Synthetic lethal approaches targeting 2-HG independent metabolic vulnerabilities conferred by mutant IDH1 may complement IDH1 mutant inhibitors. Using a novel computational method (MiSL) based on Boolean implication (if-then rules) mining of pan-cancer data, we identified acetyl CoA carboxylase (ACACA) as a potential druggable target in IDH1-mutated AML. ACACA is the rate-limiting step in the de novo synthesis of fatty acids, and mutant IDH1 leads to a reduction in malonyl-CoA, a key building block for fatty acids, in a 2-HG independent manner. This finding led us to investigate a potential synthetic lethal interaction between mutant IDH1 and ACACA based on the hypothesis that the combination causes marked inhibition of fatty acid synthesis required for cell growth.Methods: Boolean implications (MiSL) were used to identify candidate synthetic lethal interactions with mutant IDH1 by isolating genes deleted only in the absence of the mutation and with differential gene expression within pan-cancer TCGA data. Validation was performed using THP-1 cells transduced with doxycycline-inducible wildtype and R132H mutant IDH1 lentiviral vectors, and primary patient IDH1-mutant and wildtype AML samples, using both shRNAs and a targeted pharmacologic inhibitor of ACACA. Metabolomics was performed using semi-targeted mass spectrometry and liquid chromatography. Finally, primary AML samples and IDH1-mutant and wildtype cancer cell lines (HT-1080, U118, U87) were transduced with validated shRNA and engrafted into NSG mice.Results: Our computational method found that IDH1 mutation and ACACA deletions were mutually exclusive in pan-cancer TCGA data, ACACA deletions resulted in lowered expression of ACACA, and ACACA was differentially over-expressed in IDH1-mutant AML compared to IDH1-wildtypeAML. Pharmacologic inhibition of ACACA with 2 uM TOFA caused a marked reduction in cell growth in the presence of IDH1 R132H (+ dox), but not in its absence (- dox; p = 0.0001). Similarly, knockdown of ACACA with independent shRNAs caused a defect in viable cell growth in the presence of IDH1 R132H (+ dox), but not in its absence (- dox) or with scrambled shRNA (p=0.009, shRNA #1 vs. scrambled; p=0.01, shRNA #2 vs. scrambled). Primary IDH1 R132 mutated purified AML blasts were selectively sensitive to TOFA treatment compared to IDH1 wildtype normal karyotype blasts (IC50 0.6 uM vs 6 uM, p=0.009) in viable growth assays. Furthermore, when transduced with lentivirus encoding shRNA to ACACA, primary IDH1-mutant AML cells exhibited markedly reduced engraftment of RFP-positive human CD45+CD33+ leukemic cells compared to scrambled non-targeting shRNA (p < 0.05, Mann-Whitney U). As predicted, IDH1-mutant AML blasts pre-treated with 10uM AG-120 (sufficient to inhibit production of detectable 2-HG) remained susceptible to ACACA inhibition in vitro. Strikingly, in vivo models of IDH1 R132C mutated, but not wildtype, sarcoma cell lines exhibited a dramatic decrease in cell growth after ACACA inhibition that was not reversible by treatment with AG-120. Finally, metabolomic profiling revealed a major perturbation in multiple phospholipid fatty acid species and decreased malonyl-CoA conferred by IDH1 R132H, consistent with our proposed mechanism.Conclusion: We have identified de novo lipogenesis through ACACA as a critical metabolic vulnerability linked to IDH1 mutation in AML and provide evidence that therapeutic inhibition of ACACA with small molecules may be beneficial in AML, as well as in other cancers with IDH1 mutations. DisclosuresMajeti:Forty Seven Inc.: Consultancy, Equity Ownership, Membership on an entity’s Board of Directors or advisory committees, Patents & Royalties.

Abstract C88: Genomics, advocacy, and emerging therapeutics to address triple-negative breast cancer (TNBC) outcome disparities.

Abstract Background: Collaborative team science provides a starting point for comprehensive change, and advocates have a unique and important role developing and engaging in transdisciplinary collaboratives that focus on new questions and new possibilities to advance the science of ethnic and medically underserved health care disparities. Participating in four areas : 1) research and programmatic support, 2) education and outreach, 3) policy and strategy, and 4) representation and advisory, the UCSF Breast Science Advocacy Core (BSAC) Program, a volunteer affiliate of the Breast Oncology Program (BOP), one of ten multidisciplinary research programs under the umbrella of the UCSF Helen Diller Comprehensive Cancer Center promotes a transformative, transdisciplinary, integrated environment to study the biological basis of the diseases that comprise breast cancer; to define the risk of developing or progressing with specific types of breast cancer; to develop novel interventions that work locally and globally to reduce morbidity and mortality from breast cancer and its treatment; and to leverage new collaborative research, education, and mentoring/training opportunities that address cancer outcome disparities. Advocates involved in KOMEN, DOD, PCORI, AND CBCRP funded research and training grants apply four core principles that forge synergy with NCI Advocacy Research Working Group Recommendations: 1)strategic innovation, 2)collaborative execution, 3)evidence based decision-making, and 4) ethical codes of conduct. Embracing transdisciplinary professionalism, researchers and advocates build on their track record as shared value partners committed to furthering the collective impact of science advocacy exchange (SAE). Study Objectives: Genomic analyses of patient tumors have unearthed an overwhelming number of recurrent somatic alterations in genes that have dramatic effects on tumor biology, patient drug responses, and clinical outcomes. In one study, high grade triple negative breast cancer (TNBC) accounts for 34% of breast cancers in African American women versus 21% in white women. A growing body of evidence has shown that African American women have biologically more aggressive disease, independent of social determinants, and suffer the highest mortality rates. While biological breakthroughs of the last decade have greatly advanced our understanding of cancer, in advanced TNBC, a poor prognosis subtype, there is an urgent need to translate this evolving patient genomic data into new therapeutic paradigms. Our study focuses on the intersection of synthetic lethal approaches, MYC driven human cancers, and immunotherapy as an “innovation agenda”. A distinct MYC vision highlights how overexpression is associated with aggressive outcomes and poor patient outcomes, and synthetic lethal strategies to target MYC (CDK inhibitors, PIM2, as well as the PDI immune pathways) have potential for addressing outcome disparities In African American Women with Triple Negative Breast Cancer (TNBC). Key Findings: We have developed a screening technique that can be used to rapidly and accurately identify potential synthetic lethal interactions in TNBC. This platform utilizes an isogenic cell line system that we have developed to model oncogene activation in TNBC. A growing body of evidence has shown that: 1) Quantitative approach maps genotype-specific drug responses in isogenic cells 2) Systematic discovery of biomarkers for cancer drugs under clinical investigation 3) Clinically actionable synthetic lethal interaction between MYC and dasatinib is discovered 4) Mechanism of dasatinib action through inhibition of LYN kinase is described Key Take-Away Message: The inclusion of advocates in convergent science settings remind academic stakeholders that research is there to benefit the patient as they attempt to spark innovation, democratize science, and support smarter interventions that expedite the incredible potential of future investments in bioscience within disparities arenas. Citation Format: Susan Samson, Alicia Y. Zhou, Maria Martins, Alexandra Corella, Dai Horiuchi, Christina Yau, Taha Rakshandehroo, John Gordan, Rebecca Levin, Jeff Johnson, John Jascur, Mike Shales, Antonio Sorrentino, Jaime Cheah, Paul Clemens, Alykhan Shamji, Stuart Schreiber, Nevan Krogan, Kevan Shokat, Frank McCormick, Sourav Bandyopadhyay, Andrei Goga. Genomics, advocacy, and emerging therapeutics to address triple-negative breast cancer (TNBC) outcome disparities. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr C88.

Dual inhibition of EGFR and MET induces synthetic lethality in triple-negative breast cancer cells through downregulation of ribosomal protein S6

Triple-negative breast cancer (TNBC) exhibits innate resistance to the EGFR inhibition despite high level expression of EGFR. Recently, we found that the proliferation of basal-like (BL) subtype TNBC cells is synergistically inhibited by combination of EGFR and PI3K/AKT inhibitors. On the contrary, TNBC cells of mesenchymal stem-like (MSL) subtype are resistant to these combinations. To identify potential synthetic lethal interaction of compounds for treatment of MSL subtype TNBC cells, we performed MTT screening of MDA-MB-231 cells with a small library of receptor tyrosine kinase inhibitors (RTKIs) in the presence of gefitinib, an EGFR inhibitor. We identified MET inhibitors as potent RTKIs that caused synthetic lethality in combination with gefitinib in MDA-MB-231 cells. We demonstrated that combination of a MET inhibitor SU11274 with various EGFR inhibitors resulted in synergistic suppression of cell viability (in MTT assay) and cell survival (in colony formation assay) of MSL subtype TNBC cells. We further demonstrated that SU11274 alone induced G2 arrest and gefitinib/SU11274 combination sustained the SU11274-induced G2 arrest in these cells. In addition, SU11274/gefitinib combination synergistically reduced the level of ribosomal protein S6 (RPS6) in MSL subtype TNBC cells. In addition, knockdown of RPS6 itself, in both HS578T and MDA-MB-231, markedly reduced the proliferation of these cells. Taken together, our data suggest that dual targeting of EGFR and MET inhibits the proliferation of MSL subtype TNBC cells through down-regulation of RPS6.

Abstract PR01: Functional characterization of breast cancer using pooled lentivirus shRNA screens

Abstract Breast cancer is the most common invasive malignancy and the second leading cause of cancer death in U.S. women. Early detection and improved therapy have led to &amp;gt;85% 5-year survival, but still, half of currently affected women will succumb from metastatic disease. This poor outcome reflects our incomplete knowledge of essential genes driving tumor proliferation for each subtype. From genomic data alone, it can be difficult to access which genetic alterations drive pathogenesis because most of these are functionally irrelevant “passenger” mutations. Even if an oncogene or tumor suppressor is identified, these often are not amenable to targeted therapy. However, unanticipated gene/pathway dependencies can arise as a consequence of these genetic abnormalities in cancer cells (“synthetic lethality”). The recent development of lentiviral-based shRNA libraries enables genome-wide screening of cultured cancer cells in a pooled format, facilitating the identification of genes necessary for cancer cell proliferation and survival in cell culture as well as potential synthetic lethal interactions. The overall objectives of this project were to identify subtype-specific targets and synthetic lethal interactions for common mutations in human breast cancer using genome-wide shRNA screens, as well as to compare “functional genomic” and genomic classification schemes. We screened a panel of &amp;gt; 75 breast cancer lines using an 80,000 lentiviral shRNA library targeting 16,000 genes in a pooled format. We identified several classes of gene “dropouts,” including general essential genes, which are required for survival or growth in more than 70% of all cell lines, irrespective of subtype. Using a newly developed scoring algorithm that allows for precise measurement of statistical significance between two groups, we also identified several “subtype-specific” genes, whose essentiality is restricted to a defined subtype. These include well-known HER2 subtype-specific genes, ERBB2, ERBB3, and TFAP2C and luminal subtype-specific gene FOXA1, SPDEF, GATA3, ESR1, and CCDN1 as well as newly identified BRD4 and CHD4. These two genes were further validated as luminal-specific and results to explain their luminal subtype-specificity will be presented. In addition, the unprecedented number of lines allows the identification of synthetic lethal interaction with common breast cancer somatic mutation such as PIK3CA and PTEN. Finally, integration of gene expression, copy number variation, and functional screening results identified potential biomarkers with common genetic changes and functional drivers. Overall, our study represents an extensive functional genetic survey of four major breast cancer subtypes, reveals complexities between genomic and functional genomic results, and uncovers several unexpected gene dependencies and potential novel therapeutic target for each subtype. This abstract is also presented as Poster A22. Citation Format: Richard Marcotte, Azin Sayad, Maliha Haider, Kevin Brown, Troy Ketela, Jason Moffat, Benjamin G. Neel. Functional characterization of breast cancer using pooled lentivirus shRNA screens. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Synthetic Lethal Approaches to Cancer Vulnerabilities; May 17-20, 2013; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(5 Suppl):Abstract nr PR01.

Abstract 5084: Functional genomic classification of breast cancer using pooled lentivirus shRNA screens

Abstract Targeted therapies for most breast cancers are lacking because our knowledge of essential genes driving tumor proliferation is still primitive for each subtype. Although ongoing intensive efforts to genetically characterize large numbers of breast tumors are providing a plethora of new data on genomic abnormalities (e.g., amplifications, deletions, somatic mutations), it can be difficult to access which of these actively drive pathogenesis. Even if an oncogene or tumor suppressor is identified, these often are not amenable to targeted therapy (eg. KRAS, c-MYC, p53, etc). However, unanticipated gene/pathway dependencies can arise as a consequence of these genetic abnormalities in cancer cells (“synthetic lethality”). The recent development of lentiviral-based shRNA libraries enables genome-wide screening of cultured cancer cells in a pooled format, facilitating the identification of genes necessary for cancer cell proliferation and survival in cell culture as well as potential synthetic lethal interactions. The overall objective of this project was to identify subtype-specific targets for human breast cancer using a genome-wide shRNA screen, as well as to compare “functional genomic” and genomic classification schemes. We screened a panel of 53 breast cancer lines using an 80,000 lentiviral shRNA library targeting 16,000 genes in a pooled format. We identified several classes of gene “dropouts,” including general essential genes, which are required for survival or growth in more than 70% of all cell lines, irrespective of subtype. Most of these were enriched in housekeeping functions, although several genes involved in cellular signal transduction also were identified, including mTORC1, RAPTOR, TGFBR2, DDR1 and DDR2. In addition, we observed several “subtype-specific” genes, whose essentiality is restricted to a defined subtype. Furthermore, unsupervised and supervised clustering of our functional screening results identified potential “drivers” unique to each subtype. These include amplified/overexpressed genes such as ERBB2, ERBB3, FOXA1, SPDEF, TFAP2C, and CCDN1 known to be specific to the luminal and HER2 subtypes, respectively. Finally, integration of gene expression, copy number variation, and functional screening results identified potential synthetic lethal interactions with common genetic changes. Our study represents an extensive functional genetic survey of three major breast cancer subtypes, reveals complexities between genomic and functional genomic results, and uncovers several unexpected gene dependencies and potential novel therapeutic target for each subtype. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5084. doi:1538-7445.AM2012-5084

Correlation of somatic mutation and expression identifies genes important in human glioblastoma progression and survival.

Cooperative dysregulation of gene sequence and expression may contribute to cancer formation and progression. The Cancer Genome Atlas (TCGA) Network recently catalogued gene sequence and expression data for a collection of glioblastoma multiforme (GBM) tumors. We developed an automated, model-free method to rapidly and exhaustively examine the correlation among somatic mutation and gene expression and interrogated 149 GBM tumor samples from the TCGA. The method identified 41 genes whose mutation status is highly correlated with drastic changes in the expression (z-score ± 2.0), across tumor samples, of other genes. Some of the 41 genes have been previously implicated in GBM pathogenesis (e.g., NF1, TP53, RB1, and IDH1) and others, while implicated in cancer, had not previously been highlighted in studies using TCGA data (e.g., SYNE1, KLF6, FGFR4, and EPHB4). The method also predicted that known oncogenes and tumor suppressors participate in GBM via drastic over- and underexpression, respectively. In addition, the method identified a known synthetic lethal interaction between TP53 and PLK1, other potential synthetic lethal interactions with TP53, and correlations between IDH1 mutation status and the overexpression of known GBM survival genes.