bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 3558: Src regulation of peroxisome proliferator-activated receptor gamma (PPARγ) in lipid metabolism of lung cancer
Authors: Hua Tuyen N. M. , Phan Ai N. H. , Jeong Yangsik 
Published: July 2017

Abstract
Metabolic reprogramming, recently becoming one of the cancer hallmarks, is linked to oncogenic signal transduction to find a better solution for cancer therapy. As one of key mediators in oncogenic signal transduction, non-receptor tyrosine kinase Src is known to drive cancer progression by promoting cell proliferation, metastasis, and drug resistance. Although previous studies reported that Src promotes fat accumulation and suppresses browning of white adipocytes, little is known about the mechanistic role of Src in cancer metabolism. Here we report that Src mediates lipid mobilization by suppressing transcriptional activity of PPARγ, a key regulator of lipid metabolism. Firstly, we found Src suppression of PPARγ activity which, interestingly, turned out to be independent of Src kinase domain or a known Src phosphorylation site of PPARγ at tyrosine 78. Since the treatment of Src inhibitor (e.g., SU6656, PP2) could rescue Src-driven PPARγ suppression by possibly changing Src conformation, we might suggest the involvement of Src-PPARγ interaction in the regulatory mechanism. Mechanistically, further in vitro experiment showed Src inhibitor treatment recovered expression of PPARγ target genes such as fatty acid binding protein 4 (FABP4) and cluster of differentiation 36 (CD36) in a subset of non-small cell lung cancer cell lines. The increase of FABP4 and CD36 expression was associated with the reduction of lipid droplets, suggesting the role of Src regulation of PPARγ in lipid mobilization. Collectively, this finding provides better understandings about the role of Src in cancer lipid metabolism, and an insight into therapeutic combination of targeting oncogenic signal transduction and lipid metabolism to treat cancer.
Note: This abstract was not presented at the meeting.
Citation Format: Tuyen N. M. Hua, Ai N. H. Phan, Yangsik Jeong. Src regulation of peroxisome proliferator-activated receptor gamma (PPARγ) in lipid metabolism of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3558. doi:10.1158/1538-7445.AM2017-3558
Abstract 3562: A novel TGF-β signaling pathway promotes a slow growing phenotype of cancer cells in response to glutamine insufficiency
Authors: He Dan , Yin Chengqian , Qie Shuo , Chen Shuyang , Sang Nianli 
Published: July 2017

Abstract
Glutamine is a critical nutrient for proliferating cells and most tumor cells. Glutamine addiction as one of the dramatic tumor cell adaptive metabolisms is characterized by increased glutaminolysis. To better understand how tumor cells respond to glutamine deficiency, we cultured Hep3B cells in glutamine free media supplemented with ammonia, and isolated survival clones (MM01). These clones are capable of perpetual survival in glutamine free media with ammonia, but assume a slow growing phenotype, which represents the model adapted to long-term glutamine insufficiency. Comparing MM01 and Hep3B by microarray-based genome-wide gene expression profiling, we identified functional activation of Smad2/3 in MM01 cells, suggesting that long-term glutamine insufficiency activates a TGF-β signaling pathway. We have validated that glutamine insufficiency triggers Samd2 phosphorylation, which in turn, stimulates the expression of p15INK4B, providing a link to the slow growing phenotype. To elucidate how glutamine insufficiency triggers TGF-β signaling, we examined the effects of glutamine insufficiency on the expression levels of TGF-β family ligands, and found that Inhibin-βE, a newly discovered inhibin subunit isoform in the TGF-β superfamily, is up-regulated at both mRNA and protein levels in MM01. Luciferase assays demonstrate that glutamine insufficiency enhances the activity of Inhibin-βE promoter. Furthermore, we show that overexpressing Inhibin-βE is sufficient to induce Smad2/3 activation and growth inhibition in Hep3B cells. Taken together, our data suggest that Inhibin-βE likely plays a crucial role in cell adaptation to metabolic stress, facilitating cancer cell survival by slowing down biosynthesis and proliferation. A better understanding of the novel Inhibin-βE-triggered TGF-β signaling pathway may provide potential new therapeutic targets for cancer treatment.
Citation Format: Dan He, Chengqian Yin, Shuo Qie, Shuyang Chen, Nianli Sang. A novel TGF-β signaling pathway promotes a slow growing phenotype of cancer cells in response to glutamine insufficiency [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3562. doi:10.1158/1538-7445.AM2017-3562
Abstract 3569: Comparative RNA-seq analysis reveals dys-regulation of major canonical pathways in ERG-inducible LNCaP cell progression model of prostate cancer
Authors: Kumar Parameet , Chakraborty Joyeeta , Chatterjee Raghunath , Sukumar Gauthaman , Dalgard Clifton L. , Babcock Kevin , Dobi Albert , Sreenath Taduru L. , Biswas Roopa 
Published: July 2017

Abstract
Prostate Cancer (CaP) is the most common non-cutaneous form of cancer in men and is the second leading cause of cancer mortality in men in the USA. In human CaP, gene fusion between androgen responsive regulatory elements at the 5' untranslated region of TMPRSS2 and ETS-related genes (ERG) is present in at least 50% of the prostate tumors. To identify and investigate the underlying mechanisms of ERG-associated CaP, we developed ERG-inducible LNCaP cell system. In this present study, we investigated the unique cellular transcriptome associated with over-expressed ERG in CaP cells. Our data from comprehensive transcriptome analyses, illustrate a distinct signature that distinguishes ERG-dependent and ERG-independent CaP. The data highlight the significant heterogeneity among the transcript. Out of the 527 differentially expressed genes, 232 genes were up-regulated and 295 genes were down-regulated in response to ERG. Subsequent, in silico analyses indicate that these differentially expressed genes were associated with many pathways and functions. The most significantly differentially expressed genes were associated with cell cycle regulation. The top-ranked biological functions affected by ERG over-expression include Cell Cycle (p &lt; 1.42E-04), Cellular Growth and Proliferation (p &lt; 1.23E-04), Cellular Development (p &lt;1.23E-04), Cell Death and Survival (p &lt; 1.37E-04), and Cellular Assembly and Organization (p &lt; 1.42E-04). Further analyses indicate a strong association with known cancer networks. The top-ranked canonical pathways enriched in ERG-positive compared to ERG-negative LNCaP cells include, Cell Cycle Control of Chromosomal Replication (p=2.69E-16), Role of CHK Proteins in Cell Cycle Checkpoint Control (p=3.16E-11), Cell Cycle: G2/M DNA Damage Checkpoint Regulation (p=1.34E-09), Role of BRCA1 in DNA Damage Response (p=4.05E-08) and Estrogen-mediated S-phase Entry (p =5.51E-08). These findings indicate new insights into the complexity of TMPRESS2-ERG gene fusion, and may help understand mechanistic pathways which promote growth and progression of CaP.
Citation Format: Parameet Kumar, Joyeeta Chakraborty, Raghunath Chatterjee, Gauthaman Sukumar, Clifton L. Dalgard, Kevin Babcock, Albert Dobi, Taduru L. Sreenath, Roopa Biswas. Comparative RNA-seq analysis reveals dys-regulation of major canonical pathways in ERG-inducible LNCaP cell progression model of prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3569. doi:10.1158/1538-7445.AM2017-3569
Abstract 3570: Germline structural variant detection with variation graphs
Authors: Dawson Eric T. , Garrison Erik , Novak Adam , Paten Benedict , Eizinga Jordan , Hickey Glenn , Chanock Stephen , Durbin Richard 
Published: July 2017

Abstract
Structural variants play a major role in many cancers. However, classical methods of detection rely on searching for mapping signatures and a perpetual “rediscovering” of variants relative to the reference. A more efficient technique would be to map directly against known variants. We present a novel method for detecting known structural variants in next-generation sequencing data using variation graphs. Variation graphs are reference-like structures that succinctly encode the variation present within a population. Existing tools enable reads to be efficiently mapped against this graph structure. We are able to speed up queries for the presence or absence of variants by reducing the operation to a simple lookup in an external index. The current implementation of our variation graph approach is open source and publically available as part of the variation graph toolkit (https://github.com/vgteam/vg). Our method of variant typing on variation graphs has great potential to model and assess the complexity of cancer genomes while remaining efficient enough to make analysis tractable.
Citation Format: Eric T. Dawson, Erik Garrison, Adam Novak, Benedict Paten, Jordan Eizinga, Glenn Hickey, Stephen Chanock, Richard Durbin. Germline structural variant detection with variation graphs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3570. doi:10.1158/1538-7445.AM2017-3570
Abstract 3580: GATK CNV: copy-number variation discovery from coverage data
Authors: Babadi Mehrtash , Benjamin David I. , Lee Samuel K. , Smirnov Andrey , Chevalier Aaron , Lichtenstein Lee , Rubio Valentin Ruano 
Published: July 2017

Abstract
We propose and evaluate a novel algorithm for inferring germline and somatic copy number variation from whole exome sequencing (WES) and whole genome sequencing (WGS) data. Starting with the depth of aligned short reads from a cohort of samples, we use a Bayesian model for learning sequencing bias and simultaneously detecting CNV events using a hidden Markov model for change-point detection. A unified framework is used to call both germline and somatic CNVs. Denoising and event discovery are performed self-consistently to achieve maximum accuracy. In contrast to previous methods, our model naturally accounts for mixed sex cohorts and can detect events on sex chromosomes. Furthermore, we can detect excessively noisy samples and extract useful information within a probabilistic framework. Our implementation can also utilize Spark clusters, enabling the processing of larger cohorts and allowing for improved runtime performance.
We benchmark the new method for precision, recall, and reproducibility of both germline and somatic variants. Evaluations are performed on a cohort of WES samples from The Cancer Genome Atlas with matching WGS data. For germline variants, we use blood normal samples and compare our calls on WES data against Genome STRiP calls on WGS data. We find that GATK CNV yields remarkably higher precision and recall compared to XHMM and CODEX software packages. For somatic variants, we compare our calls against TITAN and find a remarkably high concordance.
Citation Format: Mehrtash Babadi, David I. Benjamin, Samuel K. Lee, Andrey Smirnov, Aaron Chevalier, Lee Lichtenstein, Valentin Ruano Rubio. GATK CNV: copy-number variation discovery from coverage data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3580. doi:10.1158/1538-7445.AM2017-3580
Abstract 3581: GATK ACNV: allelic copy-number variation discovery from SNPs and coverage data
Authors: Chevalier Aaron , Lichtenstein Lee , Smirnov Andrey , Lee Samuel K. , Babidi Mehrtash , Benjamin David I. , Ruano-Rubio Valentin 
Published: July 2017

Abstract
The presence of somatic copy-number alterations in tumor genomes can be used to predict both patient sensitivity to treatments as well as outcomes. The inclusion of allelic data improves statistical power to detect copy-number events and allows for discovery of copy-neutral events. We present GATK ACNV, an allelic copy-number variation method built on the Genome Analysis Toolkit. ACNV is a tool for detecting somatic copy-number activity from whole exome and whole genome sequencing data by segmenting the genome into regions of constant copy number and estimating copy ratio and minor-allele fraction in those regions.
ACNV uses a novel probabilistic model to account for reference bias (optionally using a panel of normals), which improves the estimation of minor-allele fraction. We combine this with the coverage model from GATK CNV by segmenting with a unified hidden Markov model, improving the statistical power to detect copy-number variation.
We validate ACNV using a purity series of the cell line HCC1143 and cancer samples from The Cancer Genome Atlas. Our results show that ACNV is able to discover regions of somatic copy-number activity accurately and with high resolution in both whole exome and whole genome sequencing data.
Citation Format: Aaron Chevalier, Lee Lichtenstein, Andrey Smirnov, Samuel K. Lee, Mehrtash Babidi, David I. Benjamin, Valentin Ruano-Rubio. GATK ACNV: allelic copy-number variation discovery from SNPs and coverage data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3581. doi:10.1158/1538-7445.AM2017-3581
Abstract 3595: Under-reporting of research biopsies in clinical trials in oncology
Authors: Parseghian Christine M. , Raghav Kanwal , Yao James , Ellis Lee M. , Tam Alda , Overman Michael J. 
Published: July 2017

Abstract
Purpose: Research biopsies are frequently incorporated into clinical trials in oncology, and are often a mandatory requirement for trial enrollment. However, limited information is available regarding the extent and completeness of research biopsy reporting.
Methods: We identified a cohort of therapeutic clinical trials wherein at least one image-guided non-diagnostic research biopsy was performed between 1/2005 and 10/2010 from a large interventional radiology database at MD Anderson Cancer Center. Study protocols were compared with the highest level of corresponding publication as a manuscript, registry report, or abstract.
Results: A total of 866 research biopsies were performed across 46 clinical trials (median 19 biopsies/trial). After a median follow-up time of 5.8yrs from study completion, 35 trials (76%) had published manuscripts (18 reported biopsy results), 8 (17%) had either a registry or abstract report (1 reported biopsy results), and 3 (7%) were not reported. In total, 19 trials (41%) reported biopsy results. Of these 19 trials, 6 (32%) trials under-reported the number of biopsies performed. Only 14 of 32 (42%) trials with mandatory research biopsies reported on these biopsies. Comments regarding biopsy quality/adequacy were reported in only 5 trials. Complications from these biopsies occurred in 39 pts (grade 3 in 6 pts) in 8 trials, but only 1 (13%) trial reported biopsy complications. Factors associated with better reporting of research biopsies are shown in the Table. When limited to only published manuscripts, results were unchanged. Academic sponsorship and a larger number of biopsies, especially serial biopsies, were associated with increased reporting of research biopsies.
Conclusion: Despite ethical obligations to report research biopsies, 59% of trials do not report on these biopsies. Although complications occur, they are rarely reported. Clinical trial design efforts to ensure that an adequate number of research biopsies are obtained may lead to improved reporting of research biopsy biomarker results.
VariableNTrials reporting biopsies (%)P-valueMandatory or optional biopsy1Mandatory (+/- optional)3314 (42)Optional135 (38)Total number of biopsies per trial0.002&lt;10193 (16)10-302211 (50)&gt;3055 (100)Trials with serial biopsies (No. of pts.)0.00011-5110 (0)&gt;=51813 (72)Study sponsorship0.03Industry246 (25)Academic2213 (59)Clinical trial0.77Multicenter218 (38)Single center2511 (44)Phase of clinical trial0.51I or I/II3315 (45)II or III134 (31)
Citation Format: Christine M. Parseghian, Kanwal Raghav, James Yao, Lee M. Ellis, Alda Tam, Michael J. Overman. Under-reporting of research biopsies in clinical trials in oncology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3595. doi:10.1158/1538-7445.AM2017-3595
Abstract 3596: How many tumor indications should be initially studied in clinical development of next-generation immunotherapies
Authors: Chen Cong , Deng Qiqi , He Linchen , Mehrotra Devan , Rubin Eric H. , Beckman Robert A. 
Published: July 2017

Abstract
An experimental oncology immunotherapy may have the potential to be effective in a large number of tumor indications. Once a recommended Phase II dose (RP2D) is determined, under resource constraint, a natural strategy is to conduct Phase II proof-of-concept (POC) trials in two waves. A cohort of potential tumor indications is selected for the first wave investigation and the second wave investigation in a different cohort of tumor indications is initiated only after the drug has been demonstrated to be effective in the first wave. Immunotherapy development is a dynamic environment with rapidly evolving mechanistic understanding, constant flow of new data and frequent changes in the competitive landscape. How many tumor indications should be investigated in the first wave given the uncertainties? We attempt to answer this question by maximizing a benefit-cost ratio, defined to be the expected number of effective tumor indications correctly identified in the two waves divided by the expected total sample size for the POC trials in the two waves and the total sample size for the Phase III trials triggered by those with a positive outcome in the first wave. It is found that the optimal number of the first wave POC trials is in a range of approximately three to six, which may vary with the resource constraint but is otherwise robust to the key factors we have considered. A recommendation is made on how much resource should be invested in the first wave.
Citation Format: Cong Chen, Qiqi Deng, Linchen He, Devan Mehrotra, Eric H. Rubin, Robert A. Beckman. How many tumor indications should be initially studied in clinical development of next-generation immunotherapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3596. doi:10.1158/1538-7445.AM2017-3596
Abstract 360: Leveraging a novel ITIM motif in GPCRs for targeted antibody design
Authors: Belcastro Lili T. , Jancina Anastasia , Adams Christina , Paulukinas Ryan D. , Moore Catherine C. 
Published: July 2017

Abstract
CXCR4, a chemokine GPCR, is essential for migration of neuronal, hematopoietic, and breast cancer cells during metastasis whereby CXCR4 dysregulation promotes migration and invasion. Following SDF stimulation, CXCR4 is phosphorylated on Ser/Thr residues which initiates adaptor recruitment, receptor desensitization, and trafficking to endocytic sites. Here we show that stimulation with gradient SDF, delays receptor phosphorylation and trafficking, leading to sustained signaling to a novel CXCR4-SHP2-ERK pathway. SHP2 is a tyrosine phosphatase implicated in HER2(+) and triple-negative breast cancers, whereby it transduces mitogenic and migratory signals driving hyperproliferation and invasion. SHP2 is recruited to tyrosine phosphorylated ITIM motifs (immmunoreceptor tyrosine-based inhibitory consensus motifs), a hallmark found in inhibitory immune receptors with little evidence in GPCRs. Here we identify an ITIM motif in CXCR4 that regulates both SHP2 binding and signaling. Specifically, we assessed if gradient SDF stimulation of CXCR4 1) delays receptor phosphorylation and trafficking, 2) sustains signaling to SHP2-ERK, 3) induces SHP2-dependent migration; and if CXCR4 Tyr mutation within the ITIM motif 4) maintains SDF gradient sensing ability, and 5) disrupts interaction with and signaling to SHP2. Our data demonstrate that gradient SDF delays receptor Ser/Thr phosphorylation and internalization thereby sustaining signaling to SHP2-ERK and driving SHP2-dependent migration. Furthermore, the ITIM mutant maintains SDF gradient sensing ability, but disrupts interaction with and signaling to SHP2. Our data support a working model that CXCR4 contains a functional ITIM motif which we are currently leveraging for targeted antibody design for use in migration studies of aggressive breast cancer cells with dysregulated CXCR4. These studies were supported by NIH grant GM-097718, PA Department of Health grant SAP4100057688, and the Milton Lev Memorial Faculty Research Fund.
Citation Format: Lili T. Belcastro, Anastasia Jancina, Christina Adams, Ryan D. Paulukinas, Catherine C. Moore. Leveraging a novel ITIM motif in GPCRs for targeted antibody design [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 360. doi:10.1158/1538-7445.AM2017-360