bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract B33: Integration of genome-wide datasets identifies SOX10 as a lineage-specific genetic dependency in melanoma
Authors: Wong Terence C. , Johannessen Cory M. , Garraway Levi A. 
Published: May 2015

Abstract
Melanoma accounts for less than 5% of skin cancers, but a majority of skin cancer deaths. Genomic studies have firmly established the role of recurrent somatic alterations in the pathogenesis of melanoma, including mutations in BRAF, NRAS, TP53, PTEN, and CDKN2A. While the discovery of activating mutations in BRAF in over 60% of melanomas has led to the development of FDA-approved BRAF and MEK inhibitors that induce dramatic responses in BRAF V600-mutant melanomas, the inevitable resistance to BRAF/MEK inhibitors necessitates a greater understanding of melanoma biology and genetics. By integrating genome-wide functional genomic and expression data, we have identified SOX10 as a lineage-specific genetic dependency in melanoma. SOX10 dependency is highly correlated with SOX10 gene expression in melanoma. Subsequent functional in vitro experiments have confirmed the role of SOX10 in the cellular proliferation and growth of melanoma cell lines. The combination of SOX10 depletion with current FDA-approved targeted therapies for melanoma hold promise for the delay or prevention of resistance to these therapeutics and may lead to more durable control of melanoma in human patients.
Citation Format: Terence C. Wong, Cory M. Johannessen, Levi A. Garraway. Integration of genome-wide datasets identifies SOX10 as a lineage-specific genetic dependency in melanoma. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr B33.
Abstract B46: Epigenetic alterations associated with platinum resistance in an ovarian cancer cell model
Authors: Samudio-Ruiz Sabrina L. , Granados Michaela L. , Hudson Laurie G. 
Published: May 2015

Abstract
Platinum resistance in ovarian cancer continues to be an impediment to clinical effectiveness. While multiple alterations associated with platinum resistance have been proposed, mechanisms responsible for those alterations, particularly epigenetic alterations, are still under investigation. Epigenetic alterations, specifically epigenetic silencing induced by DNA methylation, to genes involved in drug response is a common occurrence in platinum resistance. We have previously published that activation of the Epidermal Growth Factor Receptor (EGFR) in ovarian cancer cells increases activity of DNA methyltransferases (DNMTs) and extended EGFR activation can also increase global DNA methylation. In a concurrent abstract, we show that acute cisplatin treatment activates the EGFR and increases DNMT activity. Our overarching hypothesis for this work is that the EGFR is a key player in the development of platinum resistance by its ability to regulate DNMT activity and DNA methylation and thereby could be a therapeutic target for preventing acquisition of platinum resistance during chemotherapeutic treatment. Here, we show data obtained using a cellular model of platinum resistance that we have generated in the lab. We show that OVCA 433 cells treated repeatedly with increasing doses of cisplatin acquire resistance and demonstrate resistance in a 3D model which is more indicative of the ovarian cancer cell microenvironment. These cisplatin resistant cells (CPR) also display significantly increased DNMT activity compared to passage control (non-resistant) cells, with modest increases in global DNA methylation. While hyperactivation of the EGFR is not observed in this chronic model of cisplatin treatment, we do see a significant decrease in Copper transporter 1 (CTR1) levels in CPR cells. CTR1 is particularly important in cisplatin drug uptake, thus we believe that platinum resistance in CPR cells is due to downregulation of CTR1 potentially by DNA methylation. Current studies are evaluating DNA methylation of CTR1 and other genes that may be contributing to the development of platinum resistance. Future studies inhibiting the EGFR during cisplatin treatment will be imperative in linking cisplatin induced EGFR activation to the changes in DNMT activity and methylation that we are observing in our model of platinum resistance. This work implicates EGFR driven alterations to DNMT activity and DNA methylation as a novel mechanism for development of platinum resistance.
Citation Format: Sabrina L. Samudio-Ruiz, Michaela L. Granados, Laurie G. Hudson. Epigenetic alterations associated with platinum resistance in an ovarian cancer cell model. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr B46.
Abstract B49: Investigating kinase inhibitor resistance mechanisms through quantitative network mapping of the human kinase interactome
Authors: Cheng Feixiong , Zhao Zhongming 
Published: May 2015

Abstract
The human kinases have become one of the most important classes of drug targets in the pharmaceutical industry. More than 20 drugs targeting one or more kinases have been approved for clinical use in a variety of cancers, including lung, breast, melanoma, colorectal, pancreatic, and prostate cancers. However, patients treated with those kinase inhibitors eventually develop resistance, and their prolong survivals are typically only a few months. So far, no general model has emerged to address the kinase inhibitor resistance. In this study, we constructed a systems biology-based framework to catalogue the human kinome (kinases and their interactions), including 538 kinase genes, in the broader context of the human interactome. Specifically, we constructed three networks: a kinase-substrate interaction network containing 7,346 pairs connecting 379 kinases to 36,576 phosphorylation sites in 1,961 substrates, a protein-protein interaction network (PPIN) containing 92,699 pairs, and an atomic resolution PPIN containing 4,278 pairs. We identified the conserved regulatory phosphorylation motifs (e.g., Ser/Thr-Pro) using a sequence logo analysis. We found the typical anticancer target selection strategy that uses network hubs as drug targets might lead to a high adverse drug reaction risk. Furthermore, we found the distinct network centrality of kinases creates a high anticancer drug resistance risk by feedback or crosstalk mechanisms within cellular networks. This notion is supported by the systematic network and pathway analyses that anticancer drug resistance genes are significantly enriched as hubs and heavily participate in multiple signaling pathways. Collectively, this comprehensive human kinome map sheds light on anticancer drug resistance mechanisms and provides an innovative resource for rational kinase inhibitor design.
Note: This abstract was not presented at the conference.
Citation Format: Feixiong Cheng, Zhongming Zhao. Investigating kinase inhibitor resistance mechanisms through quantitative network mapping of the human kinase interactome. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr B49.
Abstract B51: Image-based classification of cancer drug combination response surfaces
Authors: Liu Manway , Horn Thomas , Greene Matthew , Lehar Joseph 
Published: May 2015

Abstract
Recent advances in targeted chemotherapy have dramatically improved the survival odds of patients suffering from specific molecular subtypes of cancer. Nonetheless, while a fortunate few enjoy a durable and lasting response to treatment, the majority will eventually relapse after some grace period in remission due to the emergence of drug-resistant cancer cells.
Acquired resistance is a complex phenomenon that likely involves intra-tumoral heterogeneity, tumor-stromal interactions, and natural selection due to the pressure of chemotherapy. One promising approach to overcome resistance involves utilization of two or more drug compounds in combination, where each compound targets a different member of a signaling pathway important in the disease. By targeting more proteins, the hope is that the probability of any particular cancer cell failing to respond will decrease as the barrier to survival increases.
While drug combinations are an exciting and promising direction for chemotherapeutic research, such studies present additional challenges and opportunities. Interpretation of synergistic and efficacious drug combinations is not always straightforward and pairs of drugs may interact in surprising ways that deviate from expectation based on the molecular pathway relationships between their targets. Moreover, the question of which drugs to prioritize for testing in combination is an important one to which there is currently no standard solution. The brute force approach is not cost-effective due to the factorial growth in the number of possible higher-order drug combinations.
In this work, we present and describe an algorithmic approach to (1) predict synergistic and efficacious drug combinations based on pathway relationships between their targets and (2) classify drug combination response surfaces into canonical archetypes of greatest pharmaceutical interest. Our approach borrows from classical work in image analysis and recognition. We trained and tested our algorithm on two publicly available datasets of drug combinations. We further trained on a private dataset of cancer drug combination data and made predictions that were later experimentally validated in vitro. To our knowledge, our approach is the first proof-of-concept algorithm that utilizes the actual shapes of response surfaces to categorize and prioritize drug combinations for further testing.
Citation Format: Manway Liu, Thomas Horn, Matthew Greene, Joseph Lehar. Image-based classification of cancer drug combination response surfaces. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr B51.
Abstract B52: A novel personalized therapeutic management in multiple myeloma
Authors: Krishnan Rajeev S. , Luk Frederick , Brown R. D. , Kwan Y. L. , Bebawy Mary 
Published: May 2015

Abstract
Introduction: Multiple Myeloma (MM) is an incurable hematological malignancy affecting plasma cells marked by highly heterogeneous survival rate. Relapse is a significant impediment to the successful treatment of MM clinically. One of the main causes for relapse is drug resistance to cancer chemotherapy. Currently risk stratification to MM sub -groups and categorization of complete response to therapy are assessed based on molecular, cytogenetic markers using bone marrow biopsy as available systemic markers are incompetent in this regard. We are exploring the clinical significance of our recent in vitro and in vivo findings of a novel non-genetic basis to MDR whereby tiny vesicles called microparticles (MPs) shed from cancer cell's surface transfer MDR phenotype intercellularly. MP isolated from the blood of patients who suffer from Multiple Myeloma will be phenotyped for resistance, adhesion and dissemination markers and assessed whether these characteristics are predictive of treatment outcome.
Materials and Methods: We have analysed 44 de-identified Multiple Myeloma patients. The platelet free plasma was ultracentrifuged, MM- derived microparticles were identified and quantified with flow cytometry using Annexin V450, CD138 APC, P-glycoprotein -FITC in BD TruCount tubes. Also platelet derived MPs were identified and excluded using CD41a PE and compared to age-matched healthy volunteers. Western blot analysis was conducted on microparticle lysate probing for the presence of Lung-resistance related protein (LRP).
Results: Plasma cell derived MPs were identified based on the CD138 expression from the peripheral blood plasma of MM patients. The number of systemic microparticles was found to be significantly higher in MM patients compared to the healthy volunteers. Also the systemic microparticles carried the drug resistance markers.
Conclusions: There are elevated numbers of microparticles in MM that potentially correlate with tumour aggressiveness and they carried MDR phenotypes systemically. Phenotyping MM –derived microparticles holds the potential for a non-invasive personalised systemic biomarker to predict therapeutic response.
Citation Format: Rajeev S. Krishnan, Frederick Luk, R. D. Brown, Y. L. Kwan, Mary Bebawy. A novel personalized therapeutic management in multiple myeloma. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr B52.
Abstract IA04: Using comprehensive proteomic approaches to map signaling adaptations to BRAF and BRAF/MEK inhibition
Authors: Fedorenko Inna V. , Paraiso Kim H.T. , Fang Bin , Koomen John M. , Smalley Keiran S.M. 
Published: May 2015

Abstract
Although small molecule inhibitors of BRAF have shown great promise in advanced melanoma, resistance is commonplace. Many patients with acquired BRAF and BRAF/MEK inhibitor resistance develop disease at new sites, suggesting that drug-induced selection pressure drives metastasis. Here we used mass spectrometry-based phosphoproteomic screening and network modeling to uncover two novel adaptations to BRAF inhibitor therapy. The first involved ligand-independent EphA2 signaling that led to the adoption of an invasive/metastatic phenotype. The EphA2-mediated invasion was epigenetically mediated, AKT-dependent and was readily reversible upon removal of drug as well as through PI3K or HDAC inhibition. In a human melanoma mouse xenograft model, chronic BRAF inhibition led to the development of metastases, which stained positively for EphA2. A second phosphoproteomic screen showed BRAF inhibition to enhance the survival of both melanoma cells and fibroblasts through the induction of fibronectin (FN)/integrin α5β1 signaling. Adhesion to FN amplified the adaptive EGFR, HER2 and c-MET signals required for PI3K/AKT-mediated survival when BRAF was inhibited. At the same time, BRAF inhibition led, directly and indirectly, to the paracrine release of HGF and neuregulin from fibroblasts, with TGF-β release from the melanoma cells increasing both fibroblast differentiation and survival. These effects were partly mediated through paradoxical MAPK activation in the fibroblasts and could be reversed through BRAF/MEK inhibition. Thus, we have used comprehensive phosphoproteomics to identify two key non-genetic adaptations to BRAF inhibitor therapy that offer new insights into the process of therapeutic escape.
Citation Format: Inna V. Fedorenko, Kim H.T. Paraiso, Bin Fang, John M. Koomen, Keiran S.M. Smalley. Using comprehensive proteomic approaches to map signaling adaptations to BRAF and BRAF/MEK inhibition. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr IA04.
Abstract IA11: Using genomics to study preexisting resistance
Authors: Mardis Elaine R. 
Published: May 2015

Abstract
High depth sequencing with next-generation technology permits the examination of tumor-derived DNA for evidence of pre-existing, therapy resistance-conferring alterations. Several technical challenges must be addressed to overcome the inherent limitations of assays from pre-treatment biopsies. Specific computational tools are required for accurate assessment of therapy-related alterations and changes in tumor heterogeneity. Approaches that address the assay-related difficulties and the computational analyses required for these analyses will be illustrated by several examples from our studies.
Citation Format: Elaine R. Mardis. Using genomics to study preexisting resistance. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr IA11.
Abstract PR01: Adaptive resistance of patient-derived ovarian cancer cells to PI3K/mTOR inhibition
Authors: Zervantonakis Ioannis , Chen Hsing-Yu , Muranen Taru , Liu Joyce , Drapkin Ronny , Matulonis Ursula , Brugge Joan 
Published: May 2015

Abstract
Relapse due to drug resistance remains a major challenge for successful cancer treatment despite advances in chemotherapy efficacy and the development of targeted therapies. We have previously reported a therapy-induced adaptive response that is associated with treatment resistance and are investigating whether this adaptive response program could be targeted to increase treatment efficacy (Muranen et al, Cancer Cell 2012). The PI3K pathway is amplified in high-grade serous ovarian tumor and represents an attractive target in this cancer subtype. We found that both in vitro and in vivo exposure of patient-derived ovarian cancer cells to the PI3K/mTOR dual inhibitor GNE-493 increases the levels of the anti-apoptotic Bcl-2 protein, and multiple tyrosine kinase receptors, such as EGFR and HER2. Concurrent treatment of these cancer cells with GNE-493 and ABT737 (a Bcl-2 and Bcl-xl dual inhibitor) causes a reduction in cell number and increased cell death. Ongoing studies are underway to comprehensively characterize the adaptive response signature of a panel of patient-derived ovarian cancer cells and study whether targeting multiple different upregulated proteins (e.g. EGFR) may increase PI3K/mTOR treatment efficacy.
Therapy resistance has also been associated with exposure of tumor cells to pro-survival factors secreted by supporting cells in the tumor microenvironment (Straussman et al, Nature 2012 and Wilson et al, Nature 2012). We found that the growth-factors EGF, inflammatory cytokine IL-6 and ascites fluid from ovarian cancer patients induces up-regulation of Bcl-2 as well as IGFR, which masked the adaptive response to PI3K/mTOR inhibitors. We are performing ongoing studies using orthotopic patient-derived ovarian cancer xenografts to investigate the patterns of residual disease in vivo with the ultimate goal to identify whether Bcl-2 targeted drugs will enhance the efficacy of PI3K/mTOR inhibition and whether there is differential sensitivity at distinct anatomical sites (pancreas, diaphragm, peritoneal wall).
Our studies provide a framework to identify adaptive response programs and tumor microenvironment factors in patient-derived ovarian cancer cells that limit treatment efficacy of PI3K/mTOR pathway inhibition and to develop therapies to abrogate this resistance.
Citation Format: Ioannis Zervantonakis, Hsing-Yu Chen, Taru Muranen, Joyce Liu, Ronny Drapkin, Ursula Matulonis, Joan Brugge. Adaptive resistance of patient-derived ovarian cancer cells to PI3K/mTOR inhibition. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr PR01.
Understanding the MIG6–EGFR Signaling Axis in Lung Tumorigenesis
Authors: Izumchenko Evgeny , Sidransky David 
Published: May 2015

Abstract
Summary: With multiple clinical trials under way targeting mutant EGFR in patients with lung cancer, Maity and colleagues address important aspects of a MIG6–EGFR signaling axis using genetically engineered mouse models expressing mutated EGFRs on the MIG6-deficient background. This study extends our understanding of EGFR regulation by MIG6 and reveals that MIG6 antagonizes tumor formation in mutant EGFR–driven lung adenocarcinoma. Cancer Discov; 5(5); 472–4. ©2015 AACR.
See related article by Maity et al., p. 534
The Regulatory Role of Invariant NKT Cells in Tumor Immunity
Authors: McEwen-Smith Rosanna M. , Salio Mariolina , Cerundolo Vincenzo 
Published: May 2015

AbstractInvariant natural killer T (iNKT) cells are a unique population of T lymphocytes, which lie at the interface between the innate and adaptive immune systems, and are important mediators of immune responses and tumor surveillance. iNKT cells recognize lipid antigens in a CD1d-dependent manner; their subsequent activation results in a rapid and specific downstream response, which enhances both innate and adaptive immunity. The capacity of iNKT cells to modify the immune microenvironment influences the ability of the host to control tumor growth, making them an important population to be harnessed in the clinic for the development of anticancer therapeutics. Indeed, the identification of strong iNKT-cell agonists, such as α-galactosylceramide (α-GalCer) and its analogues, has led to the development of synthetic lipids that have shown potential in vaccination and treatment against cancers. In this Masters of Immunology article, we discuss these latest findings and summarize the major discoveries in iNKT-cell biology, which have enabled the design of potent strategies for immune-mediated tumor destruction. Cancer Immunol Res; 3(5); 425–35. ©2015 AACR.
Highly multiplexed SOMAmer assays as a flexible platform for protein biomarker discovery research
Authors: Saccomano Nicholas A. , Wilcox Sheri , Zichi Dom , Kraemer Stephan , Janjic Nebojsa , Gold Larry , Ayers Deb , Bock Chris , Keeney Tracy , Brody Ed , Vaught Jon 
Published: May 2015

Abstract
SomaLogic presents a transformative proteomic biomarker discovery technology that measures ~1000 human proteins in low volumes (~15 of uL biological sample) with a high-performance, high-throughput, and economical assay. Limits of detection average 1 pM and the overall dynamic range spans 7 logs with ~5% average coefficient of variation. This technology is enabled by a new class of DNA aptamers — “SOMAmers” — that contain novel chemicallymodified nucleotides, which greatly expand the physicochemical diversity of the large combinatorial SELEX libraries from which they are selected. Proteins are measured with a process that transforms a signature of protein concentrations into a representative DNA concentration signature, which is quantified with a DNA microarray. We demonstrate the utility of this technology in a large clinical biomarker discovery study of non-small cell lung cancer, as well as in alternate biological matrices.