Candidate Driver Research Articles

Genome-Informed Targeted Therapy for Osteosarcoma.

Osteosarcoma is a highly aggressive cancer for which treatment has remained essentially unchanged for more than 30 years. Osteosarcoma is characterized by widespread and recurrent somatic copy-number alterations (SCNA) and structural rearrangements. In contrast, few recurrent point mutations in protein-coding genes have been identified, suggesting that genes within SCNAs are key oncogenic drivers in this disease. SCNAs and structural rearrangements are highly heterogeneous across osteosarcoma cases, suggesting the need for a genome-informed approach to targeted therapy. To identify patient-specific candidate drivers, we used a simple heuristic based on degree and rank order of copy-number amplification (identified by whole-genome sequencing) and changes in gene expression as identified by RNA sequencing. Using patient-derived tumor xenografts, we demonstrate that targeting of patient-specific SCNAs leads to significant decrease in tumor burden, providing a road map for genome-informed treatment of osteosarcoma. SIGNIFICANCE: Osteosarcoma is treated with a chemotherapy regimen established 30 years ago. Although osteosarcoma is genomically complex, we hypothesized that tumor-specific dependencies could be identified within SCNAs. Using patient-derived tumor xenografts, we found a high degree of response for "genome-matched" therapies, demonstrating the utility of a targeted genome-informed approach.This article is highlighted in the In This Issue feature, p. 1.

Prediction of Driver Modules via Balancing Exclusive Coverages of Mutations in Cancer Samples.

Mutual exclusivity of cancer driving mutations is a frequently observed phenomenon in the mutational landscape of cancer. The long tail of rare mutations complicates the discovery of mutually exclusive driver modules. The existing methods usually suffer from the problem that only few genes in some identified modules cover most of the cancer samples. To overcome this hurdle, an efficient method UniCovEx is presented via identifying mutually exclusive driver modules of balanced exclusive coverages. UniCovEx first searches for candidate driver modules with a strong topological relationship in signaling networks using a greedy strategy. It then evaluates the candidate modules by considering their coverage, exclusivity, and balance of coverage, using a novel metric termed exclusive entropy of modules, which measures how balanced the modules are. Finally, UniCovEx predicts sample‐specific driver modules by solving a minimum set cover problem using a greedy strategy. When tested on 12 The Cancer Genome Atlas datasets of different cancer types, UniCovEx shows a significant superiority over the previous methods. The software is available at: https://sourceforge.net/projects/cancer‐pathway/files/.

Identifying Driver Interfaces Enriched for Somatic Missense Mutations in Tumors.

Human cancers often harbor large numbers of somatic mutations. However, only a small proportion of these mutations are expected to contribute to tumor growth and progression. Therefore, determining causal driver mutations and the genes they target is becoming an important challenge in cancer genomics. Here we describe an approach for mapping somatic mutations onto 3D structures of human proteins in complex to identify "driver interfaces." Our strategy relies on identifying protein-interaction interfaces that are unexpectedly biased toward nonsynonymous mutations, which suggests that these interfaces are subject to positive selection during tumorigenesis, implicating the interacting proteins as candidate drivers.

Identification of Jun loss promotes resistance to histone deacetylase inhibitor entinostat through Myc signaling in luminal breast cancer

BackgroundBased on promising phase II data, the histone deacetylase inhibitor entinostat is in phase III trials for patients with metastatic estrogen receptor-positive breast cancer. Predictors of sensitivity and resistance, however, remain unknown.MethodsA total of eight cell lines and nine mouse models of breast cancer were treated with entinostat. Luminal cell lines were treated with or without entinostat at their IC50 doses, and MMTV/Neu luminal mouse tumors were untreated or treated with entinostat until progression. We investigated these models using their gene expression profiling by microarray and copy number by arrayCGH. We also utilized the network-based DawnRank algorithm that integrates DNA and RNA data to identify driver genes of resistance. The impact of candidate drivers was investigated in The Cancer Genome Atlas and METABRIC breast cancer datasets.ResultsLuminal models displayed enhanced sensitivity to entinostat as compared to basal-like or claudin-low models. Both in vitro and in vivo luminal models showed significant downregulation of Myc gene signatures following entinostat treatment. Myc gene signatures became upregulated on tumor progression in vivo and overexpression of Myc conferred resistance to entinostat in vitro. Further examination of resistance mechanisms in MMTV/Neu tumors identified a portion of mouse chromosome 4 that had DNA copy number loss and low gene expression. Within this region, Jun was computationally identified to be a driver gene of resistance. Jun knockdown in cell lines resulted in upregulation of Myc signatures and made these lines more resistant to entinostat. Jun-deleted samples, found in 17–23% of luminal patients, had significantly higher Myc signature scores that predicted worse survival.ConclusionsEntinostat inhibited luminal breast cancer through Myc signaling, which was upregulated by Jun DNA loss to promote resistance to entinostat in our models. Jun DNA copy number loss, and/or high MYC signatures, might represent biomarkers for entinostat responsiveness in luminal breast cancer.

Prognostic Impact of Circulating Tumor DNA Status Post-Allogeneic Hematopoietic Stem Cell Transplantation in Acute Myeloid Leukemia and Myelodysplastic Syndrome

Background: Allogeneic hematopoietic stem cell transplantation (alloSCT) is the only curative option for patients with high risk acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). Whereas, relapse is the main event in therapeutic failure for these patients. We previously reported the utility of residual circulating tumor DNA (ctDNA) status for identifying patients with AML and MDS at high risk for relapse post myeloablative alloSCT (Nakamura et al, ASH. 2017). However, it remains to be elucidated whether persistent mutation status in serum and bone marrow (BM) have comparable ability to identify patients at high risk for relapse. Additionally, recent reports indicated mutation persistence (MP) in BM based on three genes regarding clonal hematopoiesis, DNMT3A, TET2, and ASXL1 (DTA), was not informative for relapse prediction of patients with AML in the setting of chemotherapy (Jongen-Lavrencic et al, N Engl J Med. 2018). Therefore, the prognostic impact of residual ctDNA status based on DTA genes should also be tested.Methods: To address these questions, we retrospectively collected tumor and matched serum samples at diagnosis and 1 and 3 months post-alloSCT from 53 patients with AML and MDS. Cell-free DNA was extracted from serum samples. We subjected tumor DNA, extracted from BM or peripheral blood, and buccal swab DNA, to next-generation sequencing (NGS), identifying candidate driver mutations. After identifying driver mutations, we designed droplet digital PCR (ddPCR) assay. The primary endpoint was the cumulative incidence of relapse (CIR) rate, and the secondary endpoint was the overall survival (OS) rate. We used DeLong's test to compare the performance between two assays based on the area under the curve (AUC) of receiver operating characteristics (ROC) curves.Results: Driver mutations were identified in 51 of 53 patients by NGS, and our cohort consisted of 37 patients with AML and 14 patients with MDS. The median age of the patients was 53 years. The conventional cytogenetic risk category was an adverse or high risk in 39.2% of patients, and 49.0% were in relapse or refractory disease status at alloSCT, and all patients received myeloablative conditioning; in most cases, the stem cell source was cord blood. The most frequent mutations found involved epigenetic regulators (DNMT3A/TET2/ASXL1, mutated in 32.1%), followed by signal transduction proteins (NRAS/FLT3, 31.4%). We could design at least one representative ddPCR assay for 51 patients. There was a clear correlation of variant allele frequency measurement between diagnostic ctDNA and matched tumor DNA (r2 = 0.67; P < 0.0001). Sixteen patients relapsed after a median of 7 months post-alloSCT. Both MP in BM at 1 and 3 months post-alloSCT and corresponding ctDNA persistence (CP) in serum (MP1 and MP3; CP1 and CP3, respectively) were comparably associated with higher 3-year CIR rates and inferior OS rates [3-year CIR (3-year OS): MP1 vs. non-MP1: 72.9 (50.0)% vs. 13.8 (88.0)%; P = 0.0012 (.0304) (Figure 1A); CP1 vs. non-CP1: 65.6 (45.8)% vs. 9.0 (91.7)%; P = 0.0002 (.0014) (Figure 1B); MP3 vs. non-MP3; 80.0 (30.0)% vs. 11.6 (94.1)%; P = 0.0002 (.0007); CP3 vs. non-CP3: 71.4 (53.4)% vs. 8.4 (92.5)%; P < 0.0001 (.0021)]. We next tested whether CP based on DTA could also be helpful in relapse prediction, we performed a subset analysis of patients with DTA based ddPCR assays (n=12). As a result, CP based on DTA genes also had the prognostic impact on CIR (Figure 1C). Finally, we compared the discriminatory ability of CP with those of MP. There was no significant difference between either CP and MP (Figure 1D). Additionally, when CP1 was compared with CP3, CP3 was found to be a better indicator of CIR and OS.Conclusions: In summary, we, for the first time, demonstrated that non-invasive serum ctDNA-testing, regardless of DTA genes, had comparable utility to molecular MRD testing of BM with regard to identifying patients at high risk for relapse in AML and MDS undergoing myeloablative alloSCT. Although prospective large-scale analyses are needed to confirm our findings, such non-invasive ctDNA-testing might allow for rapid clinical decision-making and, ultimately, subsequent risk-adapted therapeutic interventions post-alloSCT in AML and MDS.Figure 1. CIR based on the 1 month (A) MP and (B) CP status. (C) CIR based on the 1month CP status according to DTA subset. (D) Comparison of ROC curves for relapse prediction between 1 month CP and MP. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Comprehensive Genomic Analysis of Primary Mediastinal B-Cell Lymphoma

Primary mediastinal large B-cell lymphomas (PMBL) typically occur in young women who present with localized, large mediastinal masses. These tumors share certain clinical, pathomorphological and transcriptional features with classical Hodgkin lymphoma (cHL). To date, PMBL genetic analyses focused on limited sets of genes and recurrent somatic copy number alterations (SCNAs). Previously, we identified frequent 9p24.1/PD-L1/PD-L2 copy gains and increased expression of the PD-1 ligands as a genetically-defined immune escape mechanism in PMBL. The demonstrated efficacy of PD-1 blockade in relapsed/refractory PMBL led to recent FDA approval and underscored the importance of characterizing targetable genetic vulnerabilities in this disease.For these reasons, we obtained diagnostic biopsy specimens from 37 patients with PMBL (median age 34; female 70%) and performed whole exome sequencing (WES) with an expanded bait set to capture structural variants (SVs). Somatic alterations (mutations, SCNAs and SVs) were determined using established analytical pipelines including our algorithm for evaluating tumors without paired normal samples. Genes more frequently mutated than by chance, Candidate Cancer Genes (CCGs), were identified with MutSig2CV and recurrent SCNAs were defined with GISTIC2.0. SVs were characterized with a recently described 4-algorithm pipeline (Nature Medicine, 2018;24(5):679-690).First, we identified 15 CCGs (q-value <0.1) including genes with known roles in PMBL, such as IL4R and TNFAIP3 and mutational drivers in additional B-cell lymphomas (B2M, GNA13, STAT6, IKZF3, XPO1, TP53, PAX5) and other cancers (TP53, ZNF217 and XPO1). Overlaying the predicted protein changes onto available 3D protein structures highlighted the likely biological functions of specific alterations, such as mutational clustering in the STAT6 DNA-binding domain.We next analyzed the PMBL mutational signatures and identified 3 cases as hypermutators with MSI signatures, including 2 with MLH1 frameshift mutations and 1 with a nonsense PMS2 mutation. Despite the young age of the PMBL patient cohort, the majority of remaining mutations were caused by spontaneous deamination at CpGs, a genetic signature usually associated with aging. The next most prevalent mutational signatures were APOBEC and, infrequently, AID. We observed a higher median mutational density in PMBL (7.56 mutations/MB), compared to diffuse large B-cell lymphoma (DLBCL) and most solid cancers, providing a potential basis for increased neoantigen production and responsiveness to PD-1 blockade.Next, we identified 18 recurrent SCNAs, including 10 copy gains (2 focal and 8 arm level) and 8 copy losses (7 focal and 1 arm level). Copy gains of 9p24.1/PD-L1/PD-L2 were detected in 70% of cases. SVs were defined at base-pair resolution and included infrequent (2/37) tandem duplications of both PD-1 ligands and inactivating CTIIA SVs (deletions and inversions) in 10% (4/37) of cases.Although PMBL had a higher mutational density than DLBCL, the PMBL alterations involved a smaller number of median genetic drivers (9 [PMBL] vs 17 [DLBCL], respectively). Combined analyses of recurrent CCGs, SCNAs and SVs revealed that certain candidate driver genes were perturbed by multiple mechanisms. Examples include: TNFAIP3 (59% overall, 41% mutations, 24% copy loss, 6% biallelic); and B2M (51% overall, 30% mutations, 27% copy loss, 6% biallelic).Concurrent analyses of the 3 types of genetic alterations also revealed multiple bases of perturbing specific signaling pathways. In this PMBL series, 73% (27/33) of tumors exhibited one or more alterations of JAK/STAT pathway components: IL4R mutations (32%), JAK2 (9p24.1 focal copy gain [70%]) and STAT6 mutations (43%). Additionally, 59% of PMBLs had alterations of antigen presentation pathway components including B2M copy loss or mutations, copy loss of 6q21.33 (which includes the HLA class I/II loci) and SVs of CTIIA. These findings provide a genetic framework for analyzing the precise mechanism of action of PD-1 blockade in PMBL.Taken together, these findings underscore the importance of a comprehensive genomic analysis in PMBL and define additional candidate treatment targets and pathogenetic mechanisms in this disease.____BC, CS and AD contributed equally. GG and MAS contributed equally. DisclosuresRodig:Merck: Research Funding; KITE: Research Funding; Affimed: Research Funding; Bristol Myers Squibb: Research Funding. Shipp:Merck: Research Funding; AstraZeneca: Honoraria; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer: Research Funding.

Tissue-Specific cis-Regulatory Divergence Implicates eloF in Inhibiting Interspecies Mating in Drosophila

Reproductive isolation is a key component of speciation. In many insects, a major driver of this isolation is cuticular hydrocarbon pheromones, which help to identify potential intraspecific mates [1-3]. When the distributions of related species overlap, there may be strong selection on mate choice for intraspecific partners [4-9] because interspecific hybridization carries significant fitness costs [10]. Drosophila hasbeen a key model for the investigation of reproductive isolation; although both male and female mate choices have been extensively investigated [6,11-16], the genes underlying species recognition remain largely unknown. To explore the molecular mechanisms underlying Drosophila speciation, we measured tissue-specific cis-regulatory divergence using RNA sequencing (RNA-seq) in D.simulans × D.sechellia hybrids. By focusing on cis-regulatory changes specific to female oenocytes, the tissue that produces cuticular hydrocarbons, we rapidly identified a small number of candidate genes. We found that one of these, the fatty acid elongase eloF, broadly affects the hydrocarbons present on D.sechellia and D.melanogaster females, as well asthe propensity of D.simulans males to mate withthem. Therefore, cis-regulatory changes in eloF may be a major driver in the sexual isolation of D.simulans from multiple other species. Our RNA-seq approach proved to be far more efficient than quantitative trait locus (QTL) mapping in identifying candidate genes; the same framework can be used to pinpoint candidate drivers of cis-regulatory divergence in traits differing between any interfertile species.

Clonal Hematopoiesis in Older Women with Extremely Skewed, Non-Random X-Inactivation Is Associated with Previous Cardiovascular and Cerebrovascular Events

Clonal Hematopoiesis in Older Women with Extremely Skewed, Non-Random X-Inactivation Is Associated with Previous Cardiovascular and Cerebrovascular Events

Genetic Landscape of Ocular Adnexa Extranodal Marginal Zone Lymphoma

Background: Ocular adnexa lymphomas (OAL) consist of a heterogeneous group of tumors that can arise in the lacrimal gland, orbit, conjunctiva and eyelid. More than 95% of these lymphomas are of B-cell origin and extranodal marginal zone lymphoma (EMZL) of mucosa-associated lymphoid tissue is the most common subtype of OAL, accounting for 55-85% of the cases. Ocular adnexa extranodal marginal zone lymphoma (OA-EMZL) patients have a persistent risk of relapses and in 4% of the cases, the disease transforms into an aggressive lymphoma. A comprehensive list of all somatic nonsilent mutations remains currently unknown thus hampering the complete understanding of the disease and the development of new diagnostic and therapeutic approaches. Previous studies analyzed only a small number of OA-EMZL patients using gene targeted sequencing. In this study we utilized whole-exome sequencing to define the genetic landscape of 69 cases of OA-EMZL. Our data provide an unbiased identification of genetically altered genes and pathways that may play a role in the molecular pathogenesis of OA-EMZL.Methods: GATK HaplotypeCaller was used for joint variant calling on all samples, while MuTect was used to detect somatic variants in seven tumor samples with available paired normal germline DNA. We focused on variants that were exonic, not synonymous, and deleterious (CADD score > 10), while excluding any variants found with a frequency > 1% in control populations. For copy number (CN) analysis we used EXCAVATOR on each sequenced exome in pooled mode against the seven paired normal samples. The output was provided to GISTIC 2.0 to determine recurrent arm-level and gene-level CN changes.Results: We identified 125 candidate cancer driver genes with the following characteristics: 1) have genomic alteration in more than 5% of the cases, 2) are present in the list of COSMIC and DLBCL driver genes, 3) are considered essential genes or tumor suppressor genes as previously defined in a functional CRISPR screen (Reddy et al., Cell 2017). Among the most frequent alterations there were mutations and CN losses of CABIN1 (32%), inactivation of TNFAIP3 (26%) and KMT2D (22%), mutations and CN changes in CARD11 (25%), RHOA (25%), CREBBP (20%) and TBL1XR1 (23%). Gene set enrichment analysis of candidate driver genes showed statistically significant enrichment for genes involved in cell junction, adhesion, cytoskeleton regulation, chromatin organization and for genes harboring at least one highly conserved NFAT binding motif TGGAAA in their promoter. In addition, we identified recurrent lesions affecting several genes belonging to the NFkB, NOTCH and B cell receptor (BCR) signaling pathways. The most frequent alterations in the NFkB pathway included inactivation of TNFAIP3 (26%), mutations and CN alterations of CARD11 (25%), MYD88 (12%), BCL10 (10%) and CRD10 (9%). Mutations affecting NOTCH signaling were found in NOTCH3 (22%), DTX1 (12%), MAML1 (12%), MAML2 (12%), DLK1 (10%) and SPEN (9%). BCR signaling genes alterations were observed in PIK3R2 (12%), VAV1 (10%), PTPN6 (7%) and BTK (4%).CABIN1 was one of the most commonly altered genes. In T cells, CABIN1 is implicated in inhibiting calcineurin-mediated signal transduction, including NFAT activation. In reactive lymph node and tonsil tissue, CABIN1 was expressed in reactive B cells (CD20+ and CD3-) localized mainly in the mantel zone area, as demonstrated by IHC and IF. We hypothesized that it may act as a negative regulator of BCR signaling in MZL. To verify this possibility we used shRNAs to knock down CABIN1 in MZL cell lines and measured NFAT activity in response to IgM stimulation using a luciferase reporter system. IgM stimulation of CABIN1-depleted MZL cells induced a more pronounced activation of NFAT signaling compared to wild-type cells.Conclusions: The genetics of OA-EMZL is characterized by somatic alterations in NFkB, NOTCH, and BCR signaling pathways. Candidate cancer driver genes are implicated in chromatin organization, cytoskeleton regulation and in adhesion, and they are also enriched for NFAT target genes. One of the most altered candidate cancer driver genes was CABIN1, which is a calcineurin inhibitor that acts as a negative regulator of NFAT activity. CABIN1 depletion in MZL cells boosts BCR-stimulated NFAT activity. Our data suggest a widespread dysregulation of NFAT signaling cascade downstream of BCR stimulation as a possible mechanism of OA-EMZL pathogenesis. DisclosuresLossos:Affimed: Research Funding.

Gene characteristics predicting missense, nonsense and frameshift mutations in tumor samples

BackgroundBecause driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples.ResultsWe used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations– positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified.ConclusionsBy comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.

Cancer3D 2.0: interactive analysis of 3D patterns of cancer mutations in cancer subsets.

Our knowledge of cancer genomics exploded in last several years, providing us with detailed knowledge of genetic alterations in almost all cancer types. Analysis of this data gave us new insights into molecular aspects of cancer, most important being the amazing diversity of molecular abnormalities in individual cancers. The most important question in cancer research today is how to classify this diversity to identify subtypes that are most relevant for treatment and outcome prediction for individual patients. The Cancer3D database at http://www.cancer3d.org gives an open and user-friendly way to analyze cancer missense mutations in the context of structures of proteins they are found in and in relation to patients’ clinical data. This approach allows users to find novel candidate driver regions for specific subgroups, that often cannot be found when similar analyses are done on the whole gene level and for large, diverse cohorts. Interactive interface allows user to visualize the distribution of mutations in subgroups defined by cancer type and stage, gender and age brackets, patient's ethnicity or vice versa find dominant cancer type, gender or age groups for specific three-dimensional mutation patterns.

Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation.

The role of pro-inflammatory macrophage activation in cardiovascular disease (CVD) is a complex one amenable to network approaches. While an indispensible tool for elucidating the molecular underpinnings of complex diseases including CVD, the interactome is limited in its utility as it is not specific to any cell type, experimental condition or disease state. We introduced context-specificity to the interactome by combining it with co-abundance networks derived from unbiased proteomics measurements from activated macrophage-like cells. Each macrophage phenotype contributed to certain regions of the interactome. Using a network proximity-based prioritization method on the combined network, we predicted potential regulators of macrophage activation. Prediction performance significantly increased with the addition of co-abundance edges, and the prioritized candidates captured inflammation, immunity and CVD signatures. Integrating the novel network topology with transcriptomics and proteomics revealed top candidate drivers of inflammation. In vitro loss-of-function experiments demonstrated the regulatory role of these proteins in pro-inflammatory signaling.

A pan-cancer atlas of cancer hallmark-associated candidate driver lncRNAs.

Substantial cancer genome sequencing efforts have discovered many important driver genes contributing to tumorigenesis. However, very little is known about the genetic alterations of long non‐coding RNAs (lncRNAs) in cancer. Thus, there is a need for systematic surveys of driver lncRNAs. Through integrative analysis of 5918 tumors across 11 cancer types, we revealed that lncRNAs have undergone dramatic genomic alterations, many of which are mutually exclusive with well‐known cancer genes. Using the hypothesis of functional redundancy of mutual exclusivity, we developed a computational framework to identify driver lncRNAs associated with different cancer hallmarks. Applying it to pan‐cancer data, we identified 378 candidate driver lncRNAs whose genomic features highly resemble the known cancer driver genes (e.g. high conservation and early replication). We further validated the candidate driver lncRNAs involved in ‘Tissue Invasion and Metastasis’ in lung adenocarcinoma and breast cancer, and also highlighted their potential roles in improving clinical outcomes. In summary, we have generated a comprehensive landscape of cancer candidate driver lncRNAs that could act as a starting point for future functional explorations, as well as the identification of biomarkers and lncRNA‐based target therapy.

Abstract PR05: Genomic analysis of osteosarcoma reveals opportunities for targeted therapy

Abstract Osteosarcoma (OS) patients who relapse after initial therapy or present with metastatic disease have an extremely poor prognosis. Chemotherapy regimens for these patients have limited efficacy and significant toxicities. Thus, new therapeutic approaches are urgently needed. OS is characterized by numerous copy-number alterations (CNAs) and structural variations (SVs) in cancer-relevant genes. In contrast, recurrent point mutations are not seen. Thus, OS is a C-class (copy number-driven) rather than an M-class (mutation-driven) cancer. However, little is known with regards to whether copy-number alterations can be used to select therapies for aggressive cancers such as OS. The genomic heterogeneity of OS suggests that there may be different oncogenic drivers in subsets of patients. Thus, a systematic effort to identify targetable, patient-specific key driver genes (likely CNAs) is required. We established a clinically annotated patient-derived tumor xenograft (PDTX) bank of 16 OS samples obtained at diagnosis, after surgical resection, and from metastasis, thus representing the full spectrum of disease. Comparison between PDTXs with a corresponding matched primary tumor demonstrated high correlation in copy number (by WGS for 12 samples) and gene expression (by RNAseq for 13 samples), suggesting that PDTXs are faithful preclinical models for OS. To identify recurrent CNAs, we analyzed this WGS dataset together with a public dataset of OS WGS samples. With this combined dataset of 69 samples from 52 patients, we searched for recurrent CNAs across an actionable cancer gene list and identified genes amplified at least 4-fold in at least 2 samples. The two most frequently amplified genes in OS are CCNE1 and MYC. Other frequent alterations were those in the PI3K pathway (PTEN loss and/or AKT amplification), AURKB amplification, CDK4 amplification, and VEGFA amplification. Importantly, all of these CNAs were reflected in at least one PDTX model. We hypothesized that in OS some of these CNAs are key cancer drivers that can be targeted for cancer treatment. To test this hypothesis, we rank-ordered the CNAs in 9 PDTXs by the amplitude of the copy number gain. We used this simple heuristic to identify candidate drivers for individual samples. We then identified 6 drugs that could be used to target specific amplified genes and tested these drugs in corresponding CNA-matched PDTX. In all cases, we saw significant growth inhibition in matched PDTXs whereas the effect was minimal in PDTXs treated with unmatched therapies. These results support the hypothesis that specific genes within CNA serve as oncogenic drivers in OS and thus outline a feasible approach to personalized, genome-informed therapy for this disease. This work could serve as the necessary preclinical proof of principle for development of a targeted therapy basket trial for OS. In parallel to these studies and in order to further define the evolutionary trajectory of OS, we have carried out a comprehensive analysis of both spatial and temporal changes that occur in OS samples from the same patient. This has allowed us to begin defining the role of whole-genome duplication events and chromothripsis as well as loss of heterozygosity in the evolution of OS. We are directing our current efforts towards merging this evolutionary analysis with knowledge of possible targetable events to further identify key vulnerabilities that could be exploited for therapeutic benefit. Citation Format: Leanne Sayles, Marcus Breese, Amanda Koehne, Krystal Straessler, Stanley Leung, Aviv Spillinger, Doug Hawkins, Steven Dubois, Alex Lee, Bogdan Tanasa, Kim Miok, Avanthi Shah, Sheri Spunt, Neyssa Marina, Kim Hazard, Alejandro Sweet-Cordero. Genomic analysis of osteosarcoma reveals opportunities for targeted therapy [abstract]. In: Proceedings of the AACR Special Conference: Pediatric Cancer Research: From Basic Science to the Clinic; 2017 Dec 3-6; Atlanta, Georgia. Philadelphia (PA): AACR; Cancer Res 2018;78(19 Suppl):Abstract nr PR05.

Comprehensive Genomic Characterization of Parathyroid Cancer Identifies Novel Candidate Driver Mutations and Core Pathways.

ContextElucidating the genomic landscape of sporadic parathyroid carcinoma (PC) has been limited by low tumor incidence.ObjectiveIdentify driver mutations of sporadic PC and potential actionable pathways.MethodsPatients undergoing surgical resection for sporadic PC between 1980 and 2016 at MD Anderson Cancer Center were identified. Patients with sporadic PC according to World Health Organization diagnostic criteria and with available formalin-fixed, paraffin-embedded (FFPE) PC tumor tissue were included and their clinical data analyzed to assess extent of disease. Patients with parathyroid tumors of uncertain malignancy or atypical parathyroid neoplasms were excluded. Thirty-one patients meeting diagnostic criteria had available tissue for analysis. FFPE PC tumors were subjected to DNA extraction and next-generation whole-exome sequencing. All variant calls are single-algorithm only. Twenty-nine samples passed quality assurance after DNA extraction.Main Outcome MeasuresSomatic or private germline mutations present in sporadic PC and identification of pathways involved in tumorigenesis.ResultsWe identified 35 genes with considerable mutational load; only eight genes were previously identified in other PC cohorts. These genes mediate critical processes, including chromosome organization, DNA repair, and cell cycle regulations. Gene mutations involved in MAPK signaling and immune response are also heavily implicated. These findings are limited by inherent molecular artifacts in FFPE tissue analysis and the absence of matched germline DNA. Additionally, variant calls are only single algorithm and may include false-positive/negative calls.ConclusionWe identified 33 candidate driver genes of sporadic PC, in addition to previously known driver genes CDC73 and MEN1.

Abstract A037: C1orf116, a gene of unknown function, promotes tight junctions and epithelial cell phenotype in prostate cancer

Abstract While advances in the treatment of localized prostate cancer (PCa) have improved five-year survival to near 100%, metastatic disease remains incurable. Lethal metastases are the end-result of a cancer cell that escapes the primary tumor, travels through the vasculature, and eventually invades and colonizes a secondary site. Thus, in order for a cancer cell to metastasize from the primary tumor, it must move. In a critical early event of metastasis, a rare population of cells in the primary tumor undergoes a phenotype switch from a proliferating epithelial cell to gain mesenchymal cell characteristics, including high migratory capacity, during the process of epithelial-to-mesenchymal transition (EMT). Using a multistudy gene expression discovery analysis, we previously identified C1orf116 as a novel candidate driver of EMT (doi: 10.1186/s12885-017-3413-3). C1orf116 is an unnamed gene of unknown function that remains largely uncharacterized in any disease state, including cancer or EMT. To substantiate its potential role in EMT, we queried the Cancer Cell Line Encyclopedia dataset (GSE36133) and found that C1orf116 expression is associated with classical epithelial markers and inversely associated with mesenchymal markers. To specifically interrogate the role of C1orf116 in EMT, we overexpressed C1orf116 in otherwise C1orf116low PC3 cells (PC3-oe). PC3-oe cells demonstrated distinctive cobblestone epithelial cellular morphology. Correspondingly, PC3-oe cultures showed increased epithelial marker expression (including OVOL1, CDH1, ESRP), indicating that C1orf116 expression was sufficient to induce an epithelial transition. To determine whether C1orf116 influenced migration, we performed a scratch-closure assay. PC3-oe cultures showed reduced motility compared to control, suggesting that C1orf116 restricts motility. Cellular migration is influenced by many factors, including cell-ECM adhesion, “go vs. grow” switching, and cell-cell adhesion. We observed that PC-oe established cell-cell contacts more rapidly than cells in the control cultures (time-lapse photography immediately following culture seeding) and hypothesized that C1orf116 promoted cell-cell adhesion. We found that PC3-oe had increased expression of tight junction complexes (including ZO1, ZO2, ZO3). Likewise, siRNA-mediated knockdown of C1orf116 expression in C42b (C1orf116high) cells resulted in decreased expression of tight junction proteins. These findings demonstrate that C1orf116 is a novel driver of the epithelial phenotype. In particular, C1orf116 expression promotes cell-cell tight junctions, thereby restricting the active emigrant phenotype of potentially lethal metastatic cells. Citation Format: Sarah R. Amend, James Hernandez, Princy Parsana, Kenneth J. Pienta. C1orf116, a gene of unknown function, promotes tight junctions and epithelial cell phenotype in prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A037.

Association of IRS2 overexpression with disease progression in intrahepatic cholangiocarcinoma.

Insulin receptor substrate 2 (IRS2) is a candidate driver oncogene frequently amplified in cancer and is positively associated with IRS2 expression. The overexpression of IRS2 has been suggested to promote tumor metastasis. However, its function in intrahepatic cholangiocarcinoma (iCCA) has not been investigated extensively. The present study examined 86 cases of iCCA to analyze IRS2 expression and its correlation with clinicopathological characteristics using immunohistochemical assays. Three stable cell lines overexpressing IRS2 were established. The mobility potential of cells was compared in the basal condition and following manipulation using cell migration and invasion assays. Epithelial-mesenchymal transition (EMT)-associated proteins were assessed by western blotting. IRS2 was overexpressed in 29 iCCA cases (33.7%) and was significantly more frequent in cases with large tumor size (P=0.033), classified as an advanced stage by the American Joint Committee on Cancer (P=0.046). In comparison with the control cells, the three IRS2-overexpressing iCCA cell lines exhibited a statistically significant increase in mobility potential. Expression analysis of EMT markers demonstrated decreased epithelial marker levels and increased mesenchymal marker levels in IRS2-overexpressing cells compared with their corresponding control cells. The results of the present study indicate that IRS2 overexpression is characterized by a large tumor size and advanced tumor stage in iCCA, and that it may increase tumor mobility potential by regulating EMT pathways. Therefore, it is a valuable predictive indicator of metastasis and may provide a novel direction for targeted therapy in iCCA.

3137 - IL-1 Drives Clonal Hematopoiesis via Selective Induction of Growth Arrest in Normal HSC

Clonal hematopoiesis of indeterminate potential (CHIP) results from selective expansion (>0.02% VAF) of hematopoietic clones carrying loss-of-function mutations in key epigenetic and transcriptional regulators such as TET2, ASXL1 and TP53. CHIP is a critical risk factor for myeloid malignancy, coronary heart disease and all-cause mortality. CHIP occurs primarily in settings of chronic inflammation and tissue decline, suggesting that inflammation in the bone marrow (BM) may act as a selective force that favors mutant hematopoietic clones. Interleukin (IL)-1 is a pro-inflammatory cytokine commonly overproduced by senescent and/or damaged cells and may be a candidate driver of CHIP. Here, we show that chronic IL-1 beta stimulation in vivo in mice induces a growth arrest gene program, characterized by broad repression of protein synthesis, cell metabolism and proliferation pathways, and concurrent activation of cell cycle inhibitors, hence leading to LT-HSC quiescence and delayed cell cycle re-entry during chronic IL-1 exposure. Strikingly, this gene program is selectively induced in IL-1-exposed HSC expressing high protein levels of the myeloid transcription factor PU.1. Notably, we find that LT-HSC from chronic IL-1-exposed tamoxifen-inducible, hematopoietic specific SCL-CreERT::Tet2+/- and Tet2-/- (Tet2-deficient) mice incompletely activate the growth arrest program. To test whether IL-1 is required to confer a competitive advantage on Tet2-deficient cells in vivo, we generated WT:Tet2-deficient BM chimeric mice using a low-inflammation conditioning approach. Strikingly, Tet2-deficient cells exhibited preferential expansion in recipient mice exclusively in the presence of chronic IL-1 beta treatment. We are now interrogating the dependence of clonal expansion on PU.1 expression in WT cells, and whether IL-1 blockade and/or depletion of senescent cells reverses Tet2-deficient HSC expansion. Collectively, our study may provide a basis for redefining CHIP as a potentially reversible process of somatic evolution that is driven by chronic IL-1 production and BM inflammation.

Clonal Hematopoiesis in Aging.

Clonal hematopoiesis of indeterminate potential (CHIP) is a common, age-associated condition characterized by the acquisition of somatic mutations. This concise review explores our current understanding of the mechanisms that influence the development of clonality with aging and its potential malignant and non-malignant clinical implications. Aging of the hematopoietic system results in phenotypic changes that favor clonal dominance. Cell-extrinsic factors provide additional selective pressures that further shape clonal architecture. Even so, small clones with candidate driver mutations appear to be ubiquitous with age and largely benign in the absence of strong selective pressures. Benign clonal expansion may compensate for the loss of regenerative HSC capacity as we age. CHIP is a marker of aging that reflects the biologic interplay between HSC aging and cell-extrinsic factors. The clinical significance of CHIP is highly variable and dependent on clinical context. Distinguishing the causal relationships and confounding factors that regulate clonal behavior will be essential to define the mechanistic role of CHIP in aging and potentially mitigate its clinical consequences.

Abstract LB-096: A gain-of-function screen identifies drivers of drug resistance in BRAFV600E melanoma cell lines

Abstract Melanoma is the deadliest form of skin cancer, and until recently patients had few treatment options upon diagnosis. Fortunately, this lack of treatment options changed with the discovery of vemurafenib, a highly selective kinase inhibitor that specifically targets the BRAFV600E mutant protein, found in ~50% of all melanoma cases. Initially, the kinase inhibitor provided complete or partial response to over 50% of patients and prolonged progression-free survival. However, the majority of patients relapse once tumors acquire resistance to vemurafenib. Some of the genetic resistance mechanisms are known, including BRAF amplification, expression of truncated BRAF, and RAS mutation. However, a significant portion of vemurafenib resistance cases is unexplained. While drug resistance can be delayed by combining vemurafenib with cobimetinib, a MEK inhibitor, mechanisms of resistance to this drug combination are not well characterized. We performed a gain-of-function screen to identify drivers of drug resistance to vemurafenib or vemurafenib combined with cobimetinib. Briefly, A375 melanoma cells were engineered to express the hyperactive transposase SB100. These cells were then subsequently transfected with the mutagenic T2Onc3 transposon to produce a population of mutagenized A375 cells. Three weeks of vemurafenib treatment selected for cells with the acquired ability to grow in the presence of drug. Candidate driver mutations were then identified by profiling the sites of transposon insertion in drug-resistant cells to find genes that were recurrently over-expressed by transposon insertions. This led to the discovery of five genes that act as drivers of vemurafenib resistance when overexpressed in the human melanoma cell line A375. Candidate genes were then validated in multiple melanoma cell lines by assessing cell growth and viability in varying concentrations of vemurafenib. An analogous screen was performed in A375 to identify drivers of resistance to the combination of vemurafenib and cobimetinib. In addition, we are assessing the diversity of drug resistance mechanisms by performing mutagenesis in three additional human melanoma cell lines. The characterization of the novel drug resistance pathways identified here will improve treatment outcomes for patients with BRAFV600E mutant melanoma. Citation Format: Charlotte R. Feddersen, Jacob L. Schillo, Hayley R. Vaughn, Andrew P. Voigt, Eliot Y. Zhu, Lexy S. Wadsworth, Christopher S. Stipp, Adam J. Dupuy. A gain-of-function screen identifies drivers of drug resistance in BRAFV600E melanoma cell lines [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 LB-096.