Cancer Driver Events Research Articles

Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures.

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery of the next generation of novel drug targets. It is becoming apparent that more complex models of cancer are required to fully appreciate the contributing factors that drive tumorigenesis in vivo and increase the efficacy of novel therapies that make the transition from pre-clinical models to clinical trials.Here we present a methodology for generating uniform and reproducible tumor spheroids that can be subjected to siRNA functional screening. These spheroids display many characteristics that are found in solid tumors that are not present in traditional two-dimension culture. We show that several commonly used breast cancer cell lines are amenable to this protocol. Furthermore, we provide proof-of-principle data utilizing the breast cancer cell line BT474, confirming their dependency on amplification of the epidermal growth factor receptor HER2 and mutation of phosphatidylinositol-4,5-biphosphate 3-kinase (PIK3CA) when grown as tumor spheroids. Finally, we are able to further investigate and confirm the spatial impact of these dependencies using immunohistochemistry.

Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures

The identification of functional driver events in cancer is central to furthering our understanding of cancer biology and indispensable for the discovery of the next generation of novel drug targets. It is becoming apparent that more complex models of cancer are required to fully appreciate the contributing factors that drive tumorigenesis in vivo and increase the efficacy of novel therapies that make the transition from pre-clinical models to clinical trials. Here we present a methodology for generating uniform and reproducible tumor spheroids that can be subjected to siRNA functional screening. These spheroids display many characteristics that are found in solid tumors that are not present in traditional two-dimension culture. We show that several commonly used breast cancer cell lines are amenable to this protocol. Furthermore, we provide proof-of-principle data utilizing the breast cancer cell line BT474, confirming their dependency on amplification of the epidermal growth factor receptor HER2 and mutation of phosphatidylinositol-4,5-biphosphate 3-kinase (PIK3CA) when grown as tumor spheroids. Finally, we are able to further investigate and confirm the spatial impact of these dependencies using immunohistochemistry.

A new NFIA:RAF1 fusion activating the MAPK pathway in pilocytic astrocytoma

Pilocytic astrocytoma (PA) is one of the most common brain cancers among children and activation of the Mitogen-Activated Protein Kinase (MAPK) pathway is considered the hallmark. In the majority of cases, oncogenic BRAF fusions or BRAF V600E mutations are observed, while RAF1 or NF1 alterations are more rarely found. However, in some cases, no apparent cancer driver events can be identified. Here, we describe a novel fusion between the transcription factor nuclear factor 1A (NFIA) and Raf-1 proto-oncogene (RAF1) in a 5-year old boy with PA. The novel fusion was identified as part of a comprehensive genomic tumor profiling. We show that the NFIA:RAF1 fusion results in constitutive Raf1 kinase activity, leading to activation of downstream MEK1/2 cascade and increased proliferation of cancer cells. The NFIA:RAF1 fusion displayed distinct subcellular localization towards the plasma membrane indicative of Raf-1 activation, in contrast to both wild type NFIA and Raf-1, which were localized in the nucleus and cytoplasm, respectively. In conclusion, our data support the existence of rare oncogenic RAF1 fusions with constitutive Raf-1 activity. This highlights the need for broad genetic testing in order to refine diagnostics of PA and to unravel potential treatment options, e.g. with MEK inhibitors.

A microscopic landscape of the invasive breast cancer genome.

Histologic grade is one of the most important microscopic features used to predict the prognosis of invasive breast cancer and may serve as a marker for studying cancer driving genomic abnormalities in vivo. We analyzed whole genome sequencing data from 680 cases of TCGA invasive ductal carcinomas of the breast and correlated them to corresponding pathology information. Ten genetic abnormalities were found to be statistically associated with histologic grade, including three most prevalent cancer driver events, TP53 and PIK3CA mutations and MYC amplification. A distinct genetic interaction among these genomic abnormalities was revealed as measured by the histologic grading score. While TP53 mutation and MYC amplification were synergistic in promoting tumor progression, PIK3CA mutation was found to have alleviated the oncogenic effect of either the TP53 mutation or MYC amplification, and was associated with a significant reduction in mitotic activity in TP53 mutated and/or MYC amplified breast cancer. Furthermore, we discovered that different types of genetic abnormalities (mutation versus amplification) within the same cancer driver gene (PIK3CA or GATA3) were associated with opposite histologic changes in invasive breast cancer. In conclusion, our study suggests that histologic grade may serve as a biomarker to define cancer driving genetic events in vivo.

Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer.

The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wide profiling strategies, alterations outside the coding context entered the focus, and multiple examples highlight the role of gene deregulation as cancer-driving events. This review describes the implication of noncoding alterations in oncogenesis and provides a theoretical framework for the identification of causal somatic variants using quantitative trait loci (QTL) analysis. Assuming that functional noncoding alterations affect quantifiable regulatory processes, somatic QTL studies constitute a valuable strategy to pinpoint cancer gene deregulation. Eventually, the comprehensive identification and interpretation of coding and noncoding alterations will guide our future understanding of cancer biology.

Mining the coding and non-coding genome for cancer drivers

Progress in next-generation sequencing provides unprecedented opportunities to fully characterize the spectrum of somatic mutations of cancer genomes. Given the large number of somatic mutations identified by such technologies, the prioritization of cancer-driving events is a consistent bottleneck. Most bioinformatics tools concentrate on driver mutations in the coding fraction of the genome, those causing changes in protein products. As more non-coding pathogenic variants are identified and characterized, the development of computational approaches to effectively prioritize cancer-driving variants within the non-coding fraction of human genome is becoming critical. After a short summary of methods for coding variant prioritization, we here review the highly diverse non-coding elements that may act as cancer drivers and describe recent methods that attempt to evaluate the deleteriousness of sequence variation in these elements. With such tools, the prioritization and identification of cancer-implicated regulatory elements and non-coding RNAs is becoming a reality.

Sparse expression bases in cancer reveal tumor drivers.

We define a new category of candidate tumor drivers in cancer genome evolution: ‘selected expression regulators’ (SERs)—genes driving dysregulated transcriptional programs in cancer evolution. The SERs are identified from genome-wide tumor expression data with a novel method, namely SPARROW (SPARse selected expRessiOn regulators identified With penalized regression). SPARROW uncovers a previously unknown connection between cancer expression variation and driver events, by using a novel sparse regression technique. Our results indicate that SPARROW is a powerful complementary approach to identify candidate genes containing driver events that are hard to detect from sequence data, due to a large number of passenger mutations and lack of comprehensive sequence information from a sufficiently large number of samples. SERs identified by SPARROW reveal known driver mutations in multiple human cancers, along with known cancer-associated processes and survival-associated genes, better than popular methods for inferring gene expression networks. We demonstrate that when applied to acute myeloid leukemia expression data, SPARROW identifies an apoptotic biomarker (PYCARD) for an investigational drug obatoclax. The PYCARD and obatoclax association is validated in 30 AML patient samples.

Notch pathway inactivation is a driver event in bladder cancer

Notch pathway inactivation is a driver event in bladder cancer

104IN - Intrapatient Heterogeneity and Clonal Evolution: what Precision Medicine?

ABSTRACT Increasing evidence supports complex sub clonal relationships in solid tumours, manifested as intratumour heterogeneity. Our group and others are finding evidence for spatial heterogeneity within individual tumours and the temporal dynamics of tumour evolution. Parallel evolution of sub clones, with distinct somatic events occurring in the same gene, signal transduction pathway or protein complex, suggests constraints to tumour evolution that might be therapeutically exploitable. Drivers of tumour heterogeneity appear to change during the disease course that contribute to the temporally distinct origins of cancer driver events. Genome doubling, occurring early or late in tumour evolution, exacerbates chromosomal instability contributing to intercellular heterogeneity and poor outcome. The finding of sub clonal driver events is likely to limit the efficacy of targeted mono therapies, suggesting the need for new approaches to drug development and clinical trial design. TRACERx, a longitudinal lung cancer evolution study and DARWIN clinical trials aimed at deciphering the relevance of sub clonal driver events to therapeutic outcome, will be discussed. Disclosure: The author has declared no conflicts of interest.

Deciphering intratumor heterogeneity and temporal acquisition of driver events to refine precision medicine.

The presence of multiple subclones within tumors mandates understanding of longitudinal and spatial subclonal dynamics. Resolving the spatial and temporal heterogeneity of subclones with cancer driver events may offer insight into therapy response, tumor evolutionary histories and clinical trial design.

Targeted genomic rearrangements using CRISPR/Cas technology.

Genomic rearrangements are frequently observed in cancer cells but have been difficult to generate in a highly specific manner for functional analysis. Here we report the application of CRISPR/Cas technology to successfully generate several types of chromosomal rearrangements implicated as driver events in lung cancer, including the CD74-ROS1 translocation event and the EML4-ALK and KIF5B-RET inversion events. Our results demonstrate that Cas9-induced DNA breaks promote efficient rearrangement between pairs of targeted loci, providing a highly tractable approach for the study of genomic rearrangements.

Pheochromocytoma and paraganglioma pathogenesis: learning from genetic heterogeneity

The neuroendocrine tumours pheochromocytomas and paragangliomas carry the highest degree of heritability in human neoplasms, enabling genetic alterations to be traced to clinical phenotypes through their transmission in families. Mutations in more than a dozen distinct susceptibility genes have implicated multiple pathways in these tumours, offering insights into kinase downstream signalling interactions and hypoxia regulation, and uncovering links between metabolism, epigenetic remodelling and cell growth. These advances extend to co-occurring tumours, including renal, thyroid and gastrointestinal malignancies. Hereditary pheochromocytomas and paragangliomas are powerful models for recognizing cancer driver events, which can be harnessed for diagnostic purposes and for guiding the future development of targeted therapies.

A survey of thousands of tumor exomes and transcriptomes to expand clinical opportunities for crizotinib.

11017 Background: Cancer driver events occur as a result of chromosomal rearrangements. There are several examples where targeted inhibition of the resulting fusion produces dramatic clinical response. For example, the EML4-ALK fusion in non-small cell lung cancer (NSCLC). Other ALK fusions have been described in NSCLC and other diseases including the NPM-ALK fusion in anaplastic large cell lymphoma (ALCL). The efficacy of crizotinib and other ALK inhibitors are being investigated in these diseases. ALK is also subject to activation via mutation and sensitivity to crizotinib is reported in ALK mutation positive neuroblastoma. Finally, crizotinib has activity not only against ALK, but also against ROS1, MST1R and MET. ROS1 fusions have been found in NSCLC and glioblastoma, and MET amplification events in gastric adenocarcinoma identify additional settings that may benefit from crizotinib treatment. Methods: To further understand the full therapeutic potential of Crizotinib, we undertook a genomic survey of ALK, ROS1, MET and MST1R across 1,000’s of patients from the The Cancer Genome Atlas (TCGA) and Oncomine. Results: We confirmed the presence of EML4-ALK fusions in both lung and colorectal cancer (CRC), and also identified a novel ALK fusion in CRC. ALK hotspot mutations and focal amplifications were confined to neuroblastoma, as previously described. Our survey of ROS1 identified rare novel fusions in NSCLC and glioblastoma, and high-level amplifications in liposarcoma (2%) and rarely in breast cancer (0.2%). No fusions were identified for MET, however high-level amplifications were observed in 1-5% of papillary renal cell carcinoma, the intestinal subtype of gastric adenocarcinoma, oliogodendroglioma, glioblastoma and lung adenocarcinoma. Hotspot mutations were frequently observed in squamous head and neck (11%), and more rarely in hepatocellular carcinoma, small cell lung and ovarian cancers. Conclusions: These results leverage all available genomic profiling data to provide a broadened scope of therapeutic opportunity for inhibitors like crizotinib. With the growing availability of next-generation sequencing, such surveys can support hypothesis-driven development of targeted therapies.

Abstract 3165: Metastatic tumor evolution delineates clinically important oncogenic drivers in diffuse gastric cancer.

Abstract We conducted a detailed genetic and functional analysis of personalized tumor evolution in a case of diffuse gastric cancer. Leveraging the unique genetics of an individual with a confirmed germline mutation in the causative CDH1 tumor suppressor gene, we identified candidate drivers for a primary tumor in the stomach and a metastatic recurrence in the left ovary, referred to as a Krukenberg tumor. Using genome sequencing, we demonstrate that the primary and metastatic tumors share the majority of cancer driver events including biallelic CDH1 and TP53 mutations consistent with a common genetic origin. The primary gastric cancer displayed amplification of FGFR2, a gene that encodes the fibroblast growth factor (FGF) receptor 2 with multiple small molecule inhibitors in clinical therapy development. Tumor evolution and genetic divergence was clearly evident with the ovarian metastasis lacking the FGFR2 amplification and displaying its own subset of mutations and genomic aberrations. Namely, the metastatic tumor had unique biallelic events affecting TGFBR2, a critical gene in the TGF-β (tumor growth factor) signaling pathway that has not previously implicated in diffuse gastric cancer. To determine the independent oncogenic attributes of these separate pathways, we used a diffuse gastric cancer cell line and organoid model system to replicate and study the context of the known and candidate drivers found in the index patient's primary versus metastatic sites. We demonstrated that in the context of biallelic CDH1 and TP53 functional loss, the addition of either FGFR2 or TGFBR2 drivers independently lead to gastric cancer. This result supports the independent cancer driver roles of the FGF and TGF-β signaling pathways in metastatic tumor evolution in diffuse gastric cancer. Our study has implications regarding personalized cancer medicine approaches in patients with metastatic gastric cancer. Citation Format: Lincoln D. Nadauld, Sarah Garcia, Georges Natsoulis, John M. Bell, Erik Hopmans, Hua Xu, Reetesh K. Pai, John F. Regan, James M. Ford, Calvin J. Kuo, Hanlee Ji. Metastatic tumor evolution delineates clinically important oncogenic drivers in diffuse gastric cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3165. doi:10.1158/1538-7445.AM2013-3165

Lentiviral vector–based insertional mutagenesis identifies genes associated with liver cancer

Transposons and γ-retroviruses have been efficiently used as insertional mutagens in different tissues to identify molecular culprits of cancer. However, these systems are characterized by recurring integrations that accumulate in tumor cells, hampering the identification of early cancer-driving events amongst bystander and progression-related events. We developed an insertional mutagenesis platform based on lentiviral vectors (LVV) by which we could efficiently induce hepatocellular carcinoma (HCC) in 3 different mouse models. By virtue of LVV’s replication-deficient nature and broad genome-wide integration pattern, LVV-based insertional mutagenesis allowed identification of 4 new liver cancer genes from a limited number of integrations. We validated the oncogenic potential of all the identified genes in vivo, with different levels of penetrance. Our newly identified cancer genes are likely to play a role in human disease, since they are upregulated and/or amplified/deleted in human HCCs and can predict clinical outcome of patients.

Revealing selection in cancer using the predicted functional impact of cancer mutations. Application to nomination of cancer drivers

Every malignant tumor has a unique spectrum of genomic alterations including numerous protein mutations. There are also hundreds of personal germline variants to be taken into account. The combinatorial diversity of potential cancer-driving events limits the applicability of statistical methods to determine tumor-specific "driver" alterations among an overwhelming majority of "passengers". An alternative approach to determining driver mutations is to assess the functional impact of mutations in a given tumor and predict drivers based on a numerical value of the mutation impact in a particular context of genomic alterations.Recently, we introduced a functional impact score, which assesses the mutation impact by the value of entropic disordering of the evolutionary conservation patterns in proteins. The functional impact score separates disease-associated variants from benign polymorphisms with an accuracy of ~80%. Can the score be used to identify functionally important non-recurrent cancer-driver mutations? Assuming that cancer-drivers are positively selected in tumor evolution, we investigated how the functional impact score correlates with key features of natural selection in cancer, such as the non-uniformity of distribution of mutations, the frequency of affected tumor suppressors and oncogenes, the frequency of concurrent alterations in regions of heterozygous deletions and copy gain; as a control, we used presumably non-selected silent mutations. Using mutations of six cancers studied in TCGA projects, we found that predicted high-scoring functional mutations as well as truncating mutations tend to be evolutionarily selected as compared to low-scoring and silent mutations. This result justifies prediction of mutations-drivers using a shorter list of predicted high-scoring functional mutations, rather than the "long tail" of all mutations.

The Evolution and Impact of Subclonal Mutations in Chronic Lymphocytic Leukemia

Abstract 5The impact of clonal heterogeneity on cancer progression in chronic lymphocytic leukemia (CLL) is not well understood. We hypothesized that the evolutionary dynamics of subclonal mutations contribute to the variations in disease tempo and response to therapy that characterize CLL. We therefore carried out a large-scale analysis of subclonal and clonal point mutations and copy-number alterations in 149 CLLs, detected by whole exome sequencing (WES) and SNP arrays.We utilized a novel computational approach, which integrates purity and local ploidy information, to infer the cancer cell fraction (CCF) of each mutation from WES data, and to classify mutations as clonal or subclonal. Subclonal mutations were detected in 146/149 CLLs and were enriched with putative cancer driver events (P=0.001). Furthermore, higher numbers of subclonal mutations were associated with prior anti-leukemia therapy (P=0.017). Together, these results suggest that a strong extrinsic selection pressure, such as cytotoxic treatment, promotes the expansion of fitter subclones, driving them to above our detection threshold (CCF of ∼0.10).The order of mutation acquisition may be inferred from the aggregate frequencies at which driver events are clonal or subclonal, as clonal mutations represent earlier events and subclonal later events. Of the 149 samples, we found 3 drivers (MYD88, trisomy 12, and del(13q)) that were clonal in 80–100% of samples harboring these alterations –significantly higher than other driver events (q<0.1), suggesting that they arise earlier in typical CLL development. Other drivers (e.g., ATM, TP53 and SF3B1) were often observed at subclonal frequencies, indicating that they often arise later in leukemic development.We directly assessed the evolution of somatic mutations in 18 patients, in which data from two distant timepoints were available. Clonal evolution was observed in 11 of 18 patients (10 of 12 who received intervening treatment, but only 1 of 6 without intervening treatment, P=0.012) and confirmed that subclonal mutations (e.g., del(11q), SF3B1 and TP53) shifted towards clonality over time. Indeed, expanding subclonal mutations were enriched in putative drivers (P=0.021), suggesting that these mutations not only mark genetic evolution but also provide the fitness advantage driving it. Changes in the genetic composition of CLL cells with clonal evolution were associated with network level changes in gene expression.If treatment-associated genetic evolution leads to expansion of a fitter subclone, we would predict a shorter time to relapse in these individuals. Indeed, presence of a detectable subclonal driver mutation was associated with a shorter time to retreatment in these 18 samples (P=0.04), indicating that the presence of subclonal drivers adversely impacts clinical outcome. In the analysis of the full cohort of 149 samples, we observed that CLLs with subclonal driver mutations were associated with shorter times from diagnosis to first therapy (P=0.001) and between sample collection to treatment (P<0.001). Moreover, in the subset of 67 of 149 patients who were treated after sampling, presence of subclonal driver mutations evident in the pre-treatment sample was associated with earlier retreatment (P=0.003). Regression models adjusting for CLL prognostic factors (IGHV status, prior therapy and high risk cytogenetics) demonstrated that the presence of a subclonal driver was an independent risk factor for earlier retreatment (adjusted hazard ratio of 4.61 (CI 1.59–13.34), P=0.005). Thus, the detection of subclonal drivers(indicative of an active evolutionary process) is associated with shorter duration of remission.In conclusion, the analysis of clonal heterogeneity in CLL provides a glimpse into the past, present and future of a patient's disease. Through the cross-sectional analysis of 149 samples, we derived the number and genetic composition of clonal and subclonal mutations and thus uncovered footprints of the past history of CLL. Furthermore, we inferred a temporal order of genetic events implicated in CLL. Finally, our combined longitudinal and cross-sectional analyses revealed that knowledge of subclonal mutations anticipates the genetic composition of the future relapsing leukemia as well as the rapidity with which it will occur. These data challenge us to therapeutically address not only genetic targets but also their dynamic evolutionary landscape. Disclosures:No relevant conflicts of interest to declare.

Whole-genome reconstruction and mutational signatures in gastric cancer

BackgroundGastric cancer is the second highest cause of global cancer mortality. To explore the complete repertoire of somatic alterations in gastric cancer, we combined massively parallel short read and DNA paired-end tag sequencing to present the first whole-genome analysis of two gastric adenocarcinomas, one with chromosomal instability and the other with microsatellite instability.ResultsIntegrative analysis and de novo assemblies revealed the architecture of a wild-type KRAS amplification, a common driver event in gastric cancer. We discovered three distinct mutational signatures in gastric cancer - against a genome-wide backdrop of oxidative and microsatellite instability-related mutational signatures, we identified the first exome-specific mutational signature. Further characterization of the impact of these signatures by combining sequencing data from 40 complete gastric cancer exomes and targeted screening of an additional 94 independent gastric tumors uncovered ACVR2A, RPL22 and LMAN1 as recurrently mutated genes in microsatellite instability-positive gastric cancer and PAPPA as a recurrently mutated gene in TP53 wild-type gastric cancer.ConclusionsThese results highlight how whole-genome cancer sequencing can uncover information relevant to tissue-specific carcinogenesis that would otherwise be missed from exome-sequencing data.

Abstract 1613: High-throughput tyrosine kinase activity profiling identifies focal adhesion kinase (FAK) as a new target in Ewing sarcoma

Abstract Aberrant activation of tyrosine kinases is a frequent driver event in cancer. Nevertheless, for many tumors, the critical kinase abnormalities have yet to be discovered. Emerging technologies are enabling the rapid profiling in high-throughput format of not only kinase expression, but kinase activation. We leveraged a bead-based approach for profiling tyrosine kinase phosphorylation in Ewing sarcoma and identified focal adhesion kinase (FAK) as a top candidate. Ewing sarcoma is the second most common bone tumor diagnosed in children. Current treatment for de novo disease employs intensive cytotoxic chemotherapy in combination with radiation or surgical resection. Outcomes for metastatic and recurrent disease remain poor. One potential target in Ewing sarcoma is the EWS/FLI rearrangement. However, development of small molecule modulators of aberrant transcription factors poses a challenge. IGF1R has emerged as a tractable target with modest success in a small subset of relapsed patients treated with IGF1R antibody therapy. However, single agent IGF1R-directed therapy is unlikely to be curative. New targeted approaches are needed for treating this disease. Utilizing a fluorescent, bead-based technology, we screened six human Ewing sarcoma cell lines. This approach is based on the multiplexed coupling of 62 kinase-specific antibodies to microspheres. Protein lysates from cell lines are incubated with antibody-coupled beads and a biotinylated antiphosphotyrosine antibody and the bead complexes detected with a Luminex flow cytometer. FAK phosphorylation was detected at higher levels in Ewing sarcoma cell lines compared to a control cell line and a no lysate BSA control. Phosphorylation at the FAK Y397 activation site was confirmed in all six lines by western immunoblotting. We next addressed the functional consequences of loss of FAK in Ewing sarcoma cell lines with both genetic and pharmacological inhibition. Multiple shRNAs directed against FAK inhibited cell viability and profoundly decreased colony formation and size in methylcellulose in three Ewing sarcoma cell lines. Similarly, chemical inhibition of FAK at doses that decrease phosphorylation at the kinase activity site decreased growth of Ewing sarcoma cell lines and inhibited anchorage independent growth. Based on prior reports of a synergistic interaction of inhibiting FAK and IGF1R in epithelial tumors, we hypothesized that a similar interaction would be observed in Ewing sarcoma. Indeed, we observed enhanced effects of small molecule inhibition of FAK on shRNA-directed knockdown of IGF1R on both cell viability and colony formation. In vivo studies of FAK inhibition as a single perturbation, as well as in combination with IGF1R inhibitors, are currently underway. With FAK small molecule inhibitors already in clinical trials, these studies may have immediate translational relevance to Ewing sarcoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1613. doi:10.1158/1538-7445.AM2011-1613