bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 42: Target inhibitory networks and drug response modeling
Authors: Shankavaram Uma , Camphausen Kevin 
Published: May 2016

Abstract
Cancer is a complex disease caused by multiple factors, which hamper effective drug discovery. Drug combination or multi target agents provide an alternate way to effectively modify disease networks. Synergistic drug pairs have special potential for treatment since they allow a desired effect to be achieved with lower total dose of administered medicine and usually with fewer side effects. However, the major challenge has been the prediction of chemotherapeutic efficacy based on the biological profile of the tumor.
Because of the lack of gene expression data treated with drug combinations, in this study, we present a computational approach to identify effective drug combinations by exploiting high throughput data. We constructed tissue specific network pharmacology based on large-scale screening data on drug treatment efficacies of 130 drugs under clinical and preclinical investigation and drug-target binding affinities. We evaluated CNS cancer subset and applied logic based network algorithm to predict effective drug combinations based on drug-target interactions and single drug sensitivity profiles.
Cancer cell based target inhibition network analysis in two case studies using glioma cell lines, (U87 and U251) identified distinct cell line survival pathways (p &lt; 0.001), including cell proliferation, adhesion and growth factor signaling. We estimated pairwise drug synergy scores for all the target genes and identified several synergistic pairs with potential clinical relevance. Target inhibition modeling allowed systematic exploration of functional interactions between drugs and their targets to maximally inhibit multiple survival pathways.
Citation Format: Uma Shankavaram, Kevin Camphausen. Target inhibitory networks and drug response modeling. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 42.
Abstract 47: Nucleophosmin/B23 (NPM/B23) and estrogen receptor alpha (ER alpha) in endometrial cancer
Authors: Lin Chiao Yun , Chao Angel , Wang Tzu-Hao , Lai Chyong-Huey 
Published: May 2016

Abstract
Purpose: Unopposed estrogen exposure is an important factor in the tumorigenesis of endometrial cancer. We aim to investigate the regulatory role of NPM/B23 in estrogen signaling in endometrial cancer.
Methods: To elucidate the underlying mechanism, we performed RT-qPCR, western blotting, promoter assay, immunoprecipitation, proliferation assay, protein stability assay, and ubiquitination assay in endometrial cancer cell lines.
Results: NPM/B23 was required for estrogen-induced endometrial proliferation, and the increase in NPM/B23 was estrogen receptor alpha (ER alpha)-dependent. Furthermore, estrogen increased NPM/B23 protein levels by repressing its ubiquitination and subsequently stabilizing the protein. The overexpression of alternate reading frame (ARF) suppressed the estrogen-induced increase in the NPM/B23 protein levels, indicating that ARF inhibited the observed estrogen-mediated NPM/B23 stabilization. Suppression of the NPM/B23-ARF interfered with the interaction and the subsequent increase in NPM/B23 protein levels.
Conclusions: Characterization of NPM/B23 in estrogen-mediated cell proliferation may extend our understanding of the tumorigenesis of endometrial cancers. Targeting B23 with hormonal therapy can be further explored for the treatment of endometrial cancer.
Citation Format: Chiao Yun Lin, Angel Chao, Tzu-Hao Wang, Chyong-Huey Lai. Nucleophosmin/B23 (NPM/B23) and estrogen receptor alpha (ER alpha) in endometrial cancer. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 47.
Abstract 54: TOMA OS-seq: A high efficiency targeted re-sequencing strategy for detecting gene amplifications, rearrangements, indels and point mutations in tumor DNA isolated from FFPE solid tumors and plasma
Authors: Bouhlal Yosr , McKenzie Alexander , So Austin P. 
Published: May 2016

Abstract
Critical genetic errors, namely specific mutations, are required for the development and maintenance of cancer. Molecular diagnostics that leverage the breadth of next-generation sequencing (NGS) to identify this mutational landscape are therefore becoming an important clinical tool in the precision treatment of cancer. However, widespread adoption of NGS technologies in the clinic is hampered by the complexity of the NGS workflow, and the resulting limits in analytical capabilities arising from noise introduced by poor step-wise yields and bias from extensive application of PCR. To address these deficiencies, we introduce TOMA OS-Seq, a complete targeted resequencing workflow designed specifically for the requirements of the clinical laboratory. Based on oligo-selective sequencing (OS-seq), a panel of 96 genes - each with diagnostic or prognostic value - can be sequenced end-to-end from as little as 1 ng of input material, enabling the analysis of DNA purified from fine-needle aspirates and plasma. Utilizing a minimal number of high efficiency processing steps to create a targeted library, this simple workflow minimizes the requirement for PCR amplification, preserving the quantitative relationship among the loci interrogated in the original sample. TOMA OS-Seq is therefore capable of detecting copy number alterations, in addition to rearrangements/fusions, insertions/deletions, and single nucleotide variants.
Citation Format: Yosr Bouhlal, Alexander McKenzie, Austin P. So. TOMA OS-seq: A high efficiency targeted re-sequencing strategy for detecting gene amplifications, rearrangements, indels and point mutations in tumor DNA isolated from FFPE solid tumors and plasma. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 54.
Abstract IA02: Precision medicine in acute lymphoblastic leukemia
Authors: Mullighan Charles G. 
Published: May 2016

Abstract
Acute lymphoblastic leukemia (ALL) is the commonest childhood tumor. Despite overall favorable treatment outcomes in children, relapsed ALL remains a leading cause of cancer death in young people. Current treatment regiments are mostly non-targeted and accompanied by significant toxicities, and new treatments tailored to patient-specific tumor vulnerabilities are required to further improve treatment outcomes. ALL has long been known to be genetically diverse. Recent genomic sequencing efforts have provided multiple new insights into the classification and genetic basis of ALL. ALL is now known to comprise multiple subtypes that have distinct constellations of chromosomal rearrangements, DNA copy number alterations and sequence mutations that perturb a limited number of key cellular pathways including lymphoid development, Ras and kinase signaling, tumor suppression drug metabolism and epigenetic regulation. These findings have several implications for precision medicine approaches.
First, different subtypes have distinct associations with relapse risk that will enable tailoring of the intensity of therapy, the requirement for intensive treatment approaches such as transplantation, and the potential for pathway-directed approaches such as BCL2 inhibitors, PI3K inhibitors and Ras inhibitors. Secondly, several subtypes have genetic alterations that are logical candidates for genomic testing and individualized targeted therapy. An important recent advance has been the identification of Ph-like ALL, a common high risk subtype of leukemia characterized by a range of genetic alterations activating cytokine receptor and kinase signaling amenable to ABL-class and JAK-STAT inhibitors. Large precision medicine trials identifying Ph-like ALL, the underlying genetic alterations, and directing patients to targeted kinase inhibitor therapy are currently in development. Thirdly, studies sequencing sequential samples obtained during therapy have identified several genes and pathways selectively mutated at relapse, including epigenetic regulators, that are logical targets for therapeutic intervention. Finally, genome sequencing is being used to develop highly sensitive approaches to detect and track response to treatment. Examples of each of these paradigms will be presented that highlight the potential of precision medicine to further improve treatment outcomes in ALL.
Citation Format: Charles G. Mullighan. Precision medicine in acute lymphoblastic leukemia. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr IA02.
Abstract IA04: Functional genomics for discovery of pathogenic mechanisms of disease and novel therapies for hematologic malignancies
Authors: Tyner Jeffrey W. 
Published: May 2016

Abstract
Our ability to quickly and cost-effectively decode cancer genomes and identify somatic mutations has been revolutionized by deep sequencing technologies. In some instances, the identification of these somatic driver mutations has resulted in implementation of more effective therapeutic strategies for patients. However, in many instances knowledge of somatic drivers has not resulted in new therapeutic strategies. In some cases, these driver mutations are gain-of-function and targeted drugs have not yet been developed, such that further drug development will bridge the translational gap between genomic knowledge and clinical translation. However, in many cases the somatic driver mutations are not directly targetable because the mutations result in loss-of-function of the mutated gene. In these cases, we face a critical knowledge gap between understanding of the identity of molecular drivers of disease and understanding of the dysregulated signaling pathways that result from these loss-of-function genetic events. It will be important to close this knowledge gap in order to better understand the targeted therapies that can be effective for all somatic driver events, such that all cancer patients can receive effective, individually tailored therapies. My lab has developed ex vivo, functional screening platforms that can be applied directly to primary specimens from patients with hematologic malignancies. These assays are based on panels of drugs and can deliver information about the specific drugs (or combinations of drugs) to which a patient's tumor cells are hypersensitive. Integration of these functional data with genomic information about each patient's tumor cells has allowed us to accelerate the process by which we discover actionable therapeutic strategies that correlate with tumor genotypes. In addition, these assays are completed in a clinically relevant time frame of three days, such that the data from these assays can be used to directly inform therapeutic strategies, even in the absence of genomic information. In this lecture, I will provide an overview of these functional screening platforms, I will illustrate strategies of data integration that have enabled rapid discovery and translation of new targeted therapy strategies, and I will discuss our experience to date with direct clinical implementation of findings from these functional screening data.
Citation Format: Jeffrey W. Tyner. Functional genomics for discovery of pathogenic mechanisms of disease and novel therapies for hematologic malignancies. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr IA04.
Abstract IA05: Clinical genomics alters care, informs new science
Authors: Taylor Barry S. 
Published: May 2016

Abstract
Broad-based prospective sequencing has begun to inform the care of individual cancer patients. Such genomically driven cancer medicine is facilitating the use of mechanism-based therapeutic approaches in patients. In addition to the value of such data to inform the treatment of individual patients under active clinical care, over time these accrue as unprecedented datasets of integrated genomic, clinical, and treatment response data that can inform translational cancer research. Here, we present preliminary results of our efforts to combine both large-scale retrospective and prospective sequencing data in cancer to drive translational cancer biology. We will report on our efforts to develop a computational oncology framework to mine these data not only for new treatment hypotheses that can be tested clinically and the preliminary results from those studies, but also how this is driving new approaches to understand so-called long tail mutations both biologically and clinically. These efforts lie at the interface of retrospective and prospective studies to inform precision oncology through new tools that move beyond enumerating individual genetic vulnerabilities toward interpreting their biological and clinical interpretation for the benefit of patients.
Citation Format: Barry S. Taylor. Clinical genomics alters care, informs new science. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr IA05.
Abstract IA17: Delivering on the promise of personalized medicine
Authors: Mills Gordon B. 
Published: May 2016

Abstract
The realization of the promise of personalized molecular medicine requires efficient development and implementation of novel targeted therapeutics linked to molecular markers able to identify patients most likely to benefit. An efficient integration of DNA, RNA and protein information content will be needed to identify patients likely to respond to particular therapies. The plethora of aberrations present in each tumor, the need to distinguish drivers from passengers, and the combinatorial effects of aberrations on critical cellular functions represent key challenges. The overall likelihood of response to therapy represents the interaction between predictors of sensitivity and predictors of resistance. Resistance can be pre-existing, adaptive, or acquired. Resistance can also occur through heterogeneity of molecular changes within the tumor and metastases. Adaptive resistance, which is the consequence of activation of homeostatic loops and phylogenetically conserved stress responses, provides a potential therapeutic liability that can be leveraged for rational combinatorial therapy. Thus a comprehensive analysis of patient tumors before, during and after treatment should become the standard of practice. Testing these precepts will require the development and implementation of novel trial designs. It is likely that we will need to increase the size of phase I and II trials to allow the identification and validation of molecular markers at the same time as the initial evaluation the toxicity and efficacy of targeted therapeutics. This will come with the advantage much smaller phase III trials of patients selected for the likelihood to respond accelerating the approval of effective targeted therapeutics.
Citation Format: Gordon B. Mills. Delivering on the promise of personalized medicine. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr IA17.
Abstract A023: The clinical utility of the modified Glasgow Prognostic Score in patients undergoing potentially curative colorectal cancer resection
Authors: Park James H. , Roxburgh Campbell SD , Horgan Paul G. , McMillan Donald C. 
Published: May 2016

Abstract
The aim of the present study was to examine the clinical utility of assessment of the systemic inflammatory response, using the modified Glasgow Prognostic Score (mGPS), in combination with TNM stage in 1000 consecutive patients undergoing potentially curative colorectal cancer resection in a single institution. An mGPS of 0 (CRP&lt;10mg/L), 1 (CRP&gt;10mg/L/ albumin&lt;35g/L) and 2 (CRP&gt;10mg/L/ albumin&lt;35g/L) was observed in 63%, 21% and 16% of patients respectively. The mGPS was associated with reduced cancer-specific survival (P&lt;0.01), independent of TNM stage; the combination of TNM stage and mGPS stratified five-year survival from 97% (TNM I, mGPS=0) to 32% (TNM III, mGPS=2) (P&lt;0.001). Furthermore, in patients undergoing elective resection of TNM III colon cancer, mGPS stratified survival of patients who received adjuvant chemotherapy from 91% (mGPS=0) to 56% (mGPS=2) (P=0.001). Indeed, the mGPS is routinely available and, in combination with TNM-based staging, provides additional prognostic information following potentially curative colorectal cancer resection.
Citation Format: James H. Park, Campbell SD Roxburgh, Paul G. Horgan, Donald C. McMillan. The clinical utility of the modified Glasgow Prognostic Score in patients undergoing potentially curative colorectal cancer resection. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A023.
Abstract A027: A phase I open-label, non-randomized study of recombinant compound interferon (rSIFN-co) in patients with advanced solid tumors
Authors: Choo Su Pin , Tai Wai Meng , Macapagal Maria , Ahmad Aziah , Li Greg , Goh Mui Leng , Ng Matthew , Tan Tira , Tan Shao Weng , Lim Wan Teck 
Published: May 2016

Abstract
Background: Recombinant compound interferon (rSIFN-co) is a new class of interferon derived from altering the spatial structure and configuration of the basic interferon protein. rSIFN-co displayed greater anti-tumor activity in solid tumors compared to interferon α-2b in pre-clinical studies.
Methods: Patients with advanced malignancies were enrolled to determine the safety, tolerability, recommended phase II dose (RP2D), pharmacodynamics (PD) and preliminary anti-tumor activities in a 3+3 dose escalation design. Two pre-defined dose levels were planned. rSIFN-co was dosed 3 times a week via subcutaneous injection for 21 days followed by 7 days rest. This was preceded by a lead in phase. PD studies comprised of FDG-PET, pre- and post treatment changes in plasma cytokine profile and tumor repressive/ enhancing genes as well as 2'5'-oligoadenylate synthetase levels.
Results: Results presented are based on preliminary data collected as of Jan. 27, 2015. 22 patients (median age 65.5 years, 14 male and 8 female) have been enrolled with 21 evaluable for safety and 15 amenable to efficacy analysis. 10 hepatocellular carcinoma (HCC), 6 non-small cell lung cancer (NSCLC), 4 colorectal cancer (CRC), 1 melanoma and 1 nasopharyngeal carcinoma patients (pts) were dosed at 2 dose levels. The RP2D was 24μg 3x/week for 21days followed by 7 days rest. No dose limiting toxicities were encountered. Most adverse events (92%) were CTCAE grade 1 and 2. The most frequent grade 1/2 treatment related adverse events (trAEs) were flu-like symptoms (90%), anorexia (33%), fatigue (33%), weight loss (33%), nausea (29%), thrombocytopenia (29%), and diarrhea (24%). Grade 3/4 trAEs were fever (2 pts), leucopenia (2 pts), transaminitis (2 pts), weight loss (1 pt), fatigue (1 pt), afebrile neutropenia (1 pt) and syncope (1 pt). 11 patients had stable disease (SD) and 4 patients had progressive disease (PD). 4 patients (2 HCC, 1 NSCLC and 1 CRC) had prolonged stable disease (&gt;16 weeks). Detailed PD data will be presented for all cohorts.
Conclusion: The RP2D was 24μg three times a week for 21days followed by 7 days rest with a lead in phase. Modest activity was seen in heavily pre-treated advanced solid tumor patients.
Citation Format: Su Pin Choo, Wai Meng Tai, Maria Macapagal, Aziah Ahmad, Greg Li, Mui Leng Goh, Matthew Ng, Tira Tan, Shao Weng Tan, Wan Teck Lim. A phase I open-label, non-randomized study of recombinant compound interferon (rSIFN-co) in patients with advanced solid tumors. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A027.
Abstract A058: GITRL-Fc, an immunotherapeutic agent that stimulates T-cell-mediated antitumor immune response
Authors: Axelrod Fumiko , Jie Hyun-Bae , Mayes Erin , Monteon Jorge , Srivastava Minu , Yun Rui , Park Inkyung Angie , Gurney Austin 
Published: May 2016

Abstract
GITRL, (Glucocorticoid-Induced Tumor Necrosis Factor Receptor Ligand, TNFSF18) is a member of the TNF family of ligands and naturally exists as a membrane-anchored type II protein that self assembles as a trimer. GITRL activates the co-stimulatory receptor GITR. A novel single-gene linkerless GITRL trimer was shown to be functional when fused to either the N- or C-terminus of an immunoglobulin Fc domain, offering a flexible strategy that may also be amenable to the production of bispecific agents. GITRL-Fc activated GITR signaling more effectively than prototype GITR agonist antibody DTA-1. GITRL-Fc promoted a robust anti-tumor immune response in several murine tumor graft models, including the apparent total regression of some treated tumors. GITRL-Fc potentiated tumor specific T-cell responses, particularly of the Th1 type, increased antigen-specific CD8 response, and promoted a reduction in Treg-mediated immune-suppressive activity.
Citation Format: Fumiko Axelrod, Hyun-Bae Jie, Erin Mayes, Jorge Monteon, Minu Srivastava, Rui Yun, Inkyung Angie Park, Austin Gurney. GITRL-Fc, an immunotherapeutic agent that stimulates T-cell-mediated antitumor immune response. [abstract]. In: Proceedings of the CRI-CIMT-EATI-AACR Inaugural International Cancer Immunotherapy Conference: Translating Science into Survival; September 16-19, 2015; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(1 Suppl):Abstract nr A058.