bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 1969: Inhibition of poly(ADP-ribose) polymerase downregulates BRCA1 and RAD51 in a pathway mediated by E2F4 and p130
Authors: Hegan Denise C. , Lu Yuhong , Stachelek Gregory C. , Crosby Meredith E. , Bindra Ranjit S. , Glazer Peter M. 
Published: February 2011

Abstract
Inhibitors of poly(ADP-ribose) polymerase (PARP) are in clinical trials for cancer therapy based on the role of PARP in recruitment of base excision repair (BER) factors to sites of damage. Here we show that PARP inhibition to block BER is toxic to hypoxic cancer cells, in which homology-dependent repair (HDR) is known to be down-regulated. However, we also report the unexpected finding that disruption of PARP, itself, either via chemical PARP inhibitors or siRNAs targeted to PARP-1, can inhibit HDR by suppressing expression of BRCA1 and RAD51, key factors in HDR of DNA breaks. Mechanistically, PARP inhibition was found to cause increased occupancy of the BRCA1 and RAD51 promoters by repressive E2F4/p130 complexes, a pathway prevented by expression of HPV E7, which disrupts p130 activity, or by siRNAs to knock down p130 expression. Functionally, disruption of p130 by E7 expression or by siRNA knockdown also reverses the cytotoxicity and radiosensitivity associated with PARP inhibition, suggesting that the down-regulation of BRCA1 and RAD51 is central to these effects. Direct measurement of HDR using a GFP-based assay demonstrates reduced HDR in cells treated with PARP inhibitors. This work identifies a novel mechanism by which PARP regulates DNA repair and suggests new strategies for combination cancer therapies.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1969.
Abstract 1976: The discovery of mechanisms of resistance to SMO antagonists and the therapeutic implications
Authors: Dorsch Marion , Buonamici Silvia , Williams Juliet , Wang Anlai , Guo Ribo , Vattay Anthony , Hsiao Kathy , Yuan Jing , Ostrom Lance , Fordjour Paul , Anderson Dustin , Morrissey Michael , Monahan John , Kelleher Joseph , Peukert Stefan , Pan Shifeng , Wu Xu , Maira Sauver-Michel , Garcia-Echeverria Carlos , Briggs Kimberly , Watkins Neil , Yao Yung-mae , Lengauer Christoph , Warmuth Markus , Sellers William 
Published: February 2011

Abstract
Smoothened (Smo) is a G-protein coupled receptor (GPCR)-like molecule that activates the Hedgehog (Hh) signal transduction pathway. In the resting state, the 12-pass transmembrane protein Patched (Ptch) inhibits Smo activity. When Ptch inhibition is attenuated, Smo signals via a cytosolic complex of proteins leading to activation of the Gli family of transcription factors. Genetic activation of the Hh pathway at or upstream of Smo is linked to tumorigenesis in several cancers. In particular, somatic mutations in Ptch and Smo leading to constitutive pathway activation are found in sporadic medulloblastoma (MB) and basal cell carcinoma (BCC). Evidence suggests that antagonists of Smo may abrogate the tumorigenic phenotype engendered by Ptch inactivation.
NVP-LDE225 is a potent and selective orally available Smo antagonist that robustly inhibits Smo-dependent signaling in vitro and in vivo. NVP-LDE225 exerted dose-related anti-tumor activity in vivo in several genetically defined MB models that are driven by mutations in Ptch leading to near complete tumor regression and Hh pathway inhibition. However, following long-term continuous dosing of NVP-LDE225 in medulloblastoma allograft models, evidence of resistance to NVP-LDE225 was observed. Here, we describe our efforts to proactively identify mechanisms of resistance to targeted therapy of Smo. Genome-wide DNA- and RNA-profiling of resistant tumors revealed distinct resistance mechanisms allowing tumors to evade the inhibitory effects of Smo antagonists. Chromosomal amplification of Gli2, a downstream effector of Hh signaling, was identified as one mechanism leading to restoration of pathway signaling despite adequate drug exposure. Additional mining of the gene expression data for pathway signatures that are selectively deregulated in resistant tumors identified increased phosphatidylinositol-3-kinase (PI3K) signaling as another potential resistance mechanism. Probing the functional relevance of increased PI3K signaling, we showed that the combination of NVP-LDE225 with the dual PI3K/mTor inhibitor NVP-BEZ235 markedly delayed the development of resistance. Our findings have important clinical implications for future treatment strategies in medulloblastoma.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1976.
Abstract 1979: Algebraic factorization of gene expression profiles reveals subtype-specific drug sensitivities among 54 breast cancer cell lines
Authors: Gibb William J. , Collisson Eric , Korkola James , Heiser Laura , Sadanandam Anguraj , Kuo Wen-Lin , Hu Zhi , Mao Jian-Hua , Wang Nicholas , Bayani Nora , Billig Jessica , Ziyad Safiyyah , Lewis Sophi , Feiler Heidi , Jakkula Lakshmi , Wolf Denise , Lenburg Marc , Spellman Paul , Gray Joe 
Published: February 2011

Abstract
Breast cancer is a heterogeneous disease, with reproducible and prognostically important subclasses. Breast cancer cell lines are widely used to study preclinical investigational agents, but the relationships, if any, between breast cancer subclass and drug response are not well understood. To help bridge this gap, we have profiled drug responses across a large panel of well-annotated breast cancer cell lines. In order to translate in vitro drug responses into clinically useful predictions, it is important that the cell line panel be organized into subtypes representative of the cancer subtype diversity found in the clinic. Recent studies have demonstrated that an algebraic clustering method known as “non-negative matrix factorization” (NMF) can be applied to gene expression profiles to resolve clinically meaningful cancer subtypes in greater detail than achievable using other clustering methods. To test whether NMF improves our ability to resolve drug sensitivities in breast cancer cell lines, we clustered pretreatment gene expression profiles of 54 breast cancer cell lines using two different methods: (1) NMF-based consensus clustering and (2) hierarchical consensus clustering. Using NMF-based consensus, we identified five robust subtypes (two Basal-A, one Basal-B and two Luminal classes). In contrast, using hierarchical consensus clustering, we could identify only three robust subtypes (one Basal-A, one Basal-B and one Luminal class). The drug response profiles were then segregated by subtype to determine whether either of the two clustering methods improves our ability to resolve drug sensitivities. Of the 67 drug compounds included in our study, the 5-subtype NMF-based classification scheme revealed three compounds (AG1024, CPT-11 and topotecan) exhibiting subtype-specific drug effects (p&lt;0.1) that are undetectable using the 3-subtype hierarchical clustering. The statistical significance of drug sensitivity was gauged using the Kruskal-Wallis rank sum test, adjusted for false discovery rate Q=0.05. In conclusion, NMF consensus clustering can be used to detect drug response patterns that would otherwise go undetected.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1979.
Abstract 1983: TP53 mutations in hepatocellular carcinoma: Association with survival and stem cell-like gene expression traits
Authors: Woo Hyun Goo , Wang Xin Wei , Budhu Anuradha , Tang Zhao-You , Sun Zongtang , Harris Curtis C. , Thorgeirsson Snorri S. 
Published: February 2011

Abstract
PURPOSE
Mutations of TP53, a tumor suppressor gene, are associated with prognosis of many cancers. However, the prognostic value of TP53 mutations in hepatocellular carcinoma (HCC) is still unclear, largely because of the enormous heterogeneity in the geographic and etiological backgrounds of the HCC patients. Here, we analyzed the prognostic values of TP53 mutations. Gene expression profiling analysis was performed to evaluate the effect of TP53 mutations at the molecular level.
PATIENTS AND METHODS
TP53 mutations were investigated in a total of 409 HCC patients including Chinese (n=336) and Caucasian (n=73) patients using direct sequencing method.
RESULTS
A total of 125 TP53 mutations were found in Chinese HCC patients (37.2 %). HCC patients harboring TP53 mutations showed shorter overall survival compared to patients with wild-type TP53 (Hazard ratio [HR], 1.86; 95% confidence interval [CI], 1.37-2.52; P&lt;0.001). The hotspot mutations at R249S and V157F were significantly associated with worse prognosis in both univariate (HR, 2.11; 95% CI, 1.51-2.94; P&lt;0.001) and multivariate analyses (HR, 1.79; 95% CI, 1.29-2.51; P&lt;0.001). In addition, gene expression profile analysis revealed the expression of stem cell-like traits in TP53 mutated tumors. This finding was validated in breast and lung cancers with TP53 mutations.
CONCLUSION
TP53 mutations, particularly hotspot mutations, are associated with poor prognosis in HCC. The acquisition of stem cell-like gene expression traits may contribute to the aggressive behavior of the TP53 mutated tumors.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1983.
Abstract 1987: RNA-seq of the bronchial airway transcriptome identifies novel gene and microRNA expression changes associated with smoking and lung cancer
Authors: Beane Jennifer , Gerrein Joseph , Vick Jessica , Gindin Yevgeniy , Anderlind Christina , Levy Shawn , Massion Pierre , Schembri Frank , Lenburg Marc , Spira Avrum 
Published: February 2011

Abstract
Prior studies have shown that cigarette smoke creates a field of molecular injury in the airway epithelium. Using microarrays, our group has previously identified gene and microRNA expression differences in bronchial airway epithelial cells that are associated with smoking and lung cancer. We hypothesize that RNA-seq of the airway transcriptome will enhance our understanding of the response to tobacco smoke exposure and lung cancer pathogenesis by identifying mRNA splice variants, non-coding RNA, and novel RNA not interrogated by microarrays.
We profiled pooled bronchial airway epithelial cell brushings (n=3 patients/pool) obtained during bronchoscopy from healthy never and current smoker volunteers and smokers with and without lung cancer undergoing surgery for suspicion of lung cancer. The high MW fraction (&gt;200 bp) was amplified using a combination of oligo d(T) and random hexamers (NuGEN, San Carlos, CA) followed by library preparation with Illumina's mRNA Seq Library Prep Kit and sequencing using Illumina's Genome Analyzer generating ∼27-30 million 36 bp reads/sample. The low MW fraction (15-40 bp) was processed using ABI's Small RNA Library Sequencing Kit and sequenced using ABI's SOLiD system generating ∼50-90 million 35 bp reads/sample. The high MW reads were aligned to rRNA (5-13%), the human genome (33-40%), and to computationally generated splice junctions (1%) using BowTie. Differential gene and isoform expression was evaluated using Cufflinks and the R package Genominator. Low MW reads were aligned using both RNA2MAP and Geospiza to a filter containing rRNA, tRNA, and repeats (4-14%), to miRBase (4-10%), and the human genome minus miRBase sequences (4-8%). Expression values were calculated for microRNAs. We compared Affymetrix Exon 1.0 ST, HGU133A2, and Invitrogen miRNA microarrays to RNA-seq and found strong correlation for genes/miRNAs interrogated by microarrays, with most smoking- and cancer related changes in transcript expression being identified by sequencing and not by arrays. Genes found differentially expressed only by sequencing were validated by RT-PCR. RNA-seq also reveals differentially expressed isoforms, potential novel miRNAs, and several isoforms of known miRNAs which are being further investigated.
RNA-seq provides a comprehensive and high-resolution view of the airway transcriptome and will provide insights into the molecular field of injury induced by smoking and the pathogenesis of smoking-related lung disease.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1987.
Abstract 2000: Biological function annotation of microarray data using correlated gene indices
Authors: Feng Bin , Sun Kathryn , Nicoletti Richard , Abraham James , Robinson Murray O. 
Published: February 2011

Abstract
Although whole-genome microarray analysis has become a routine tool in biomedical research, extracting meaningful information remains a challenge. We describe a method for assessing biological information in microarray data that relies on the observation that genes common to a biological function often exhibit correlated expression within a microarray dataset. This method comprises the identification of gene sets representing a biological process of interest, determining the subset of genes that exhibit significantly correlated/anti-correlated expression, followed by the quantitative cumulated expression of the set of correlated genes.
We applied the pathway index approach by using available gene lists, Pearson correlation, and mean of correlated gene expression values to estimate the pathway status. We then annotated a renal cancer dataset with pathway index scores of 183 canonical pathways, to identify hypoxia deregulation in Renal Cell Carcinoma samples. Using the pathway index approach, we also established a biological correlation between previously identified chromosomal instability signature and proliferation signature in human cancer, and revealed relationships between two distinct prognostic breast cancer signatures, Mammaprint, Oncotype DX, and basal subtypes within a breast tumor dataset. Our analysis indicated that both Mammaprint and Oncotype DX are good prognostic biomarkers and both biomarkers correlated with basal signature score. However, we also demonstrated that both Mammaprint and Oncotype Dx predicted patient outcome in non-basal type cohort respectively, which suggested that in addition to identify basal subtype as bad outcome group, both Mammaprint and Oncotype DX were good prognostic biomarkers in non-basal type cohort. We also applied this approach to analyze genes collinear along chromosome 7 to identify EGFR locus of chromosomal amplification using only transcriptome microarray data. Thus, gene index methodology provides a new tool to annotate microarray data with biological pathway information.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2000.
Abstract 2001: Non-negative matrix factorization (NMF) as a clinical classifier: An example with chemotherapy response in ovarian cancer
Authors: Christopher Szeto , Benz Stephen , Vaske Charles , Sanborn J. Zachary , Zhu Jing , Stuart Joshua , Haussler David 
Published: February 2011

Abstract
Large-scale whole-genome assays such as aCGH and expression profiling are providing an overabundance of data on disease states, yet much of the information is not relevant to driving the disease. There is a need for generating concise explanatory modules with powerful predictive results.
Here we describe a semi-supervised machine-learning method for classifying -omics data with associated clinical features. Using NMF a matrix of -omics data is convoluted step-wise into two matrices; a table of k “metagenes” containing coefficients for membership of each gene, and a table of prediction strengths for each patient into each k-class. Where the class of a patient is known we initially set the prediction strength for that class high, otherwise the prediction strength for each class is set equally. As the NMF algorithm progresses, the class prediction can be swapped if this is supported by the -omics data. Initially the metagene coefficients are unknown and seeded randomly. As NMF does not converge onto a unique solution, multiple metagenes were learned starting at different random coefficients. These multiple models were cross-validated as predictors against held-out sets of patients using a correlation statistic different from the one used to train the model. Where a held-out patient correlates with none of the model's k-classes they are considered members of a novel class, and can be abstained from classification a priori.
We applied our method on the TCGA ovarian serous carcinoma. In this study aCGH and expression profiles were was taken before platinum treatment and the time to relapse recorded. These -omics measurements were then integrated into inferred pathway activities using a computational model of the central dogma (DIGMA). We predicted platinum sensitivity (no relapse or relapse after 12 mo) vs. platinum resistance (relapse within 3mo) on these inferred pathway activities. Consistently, the model with the highest predictive accuracy in a cross-validation setting correctly placed patients into the correct class &gt;80% of the time. Using abstaining it is possible to achieve &gt;90% correct prediction upon a subset of the patients. These results provide useful prognostic indicators as well as indicators for which events drive disease.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2001.
Abstract 2003: Detecting clonal relationships of multifocal tumors
Authors: Fox Aleah K. , Jensen Shane T. , Snijders Antoine M. , Schmidt Brian L. , Albertson Donna G. , Maley Carlo C. 
Published: February 2011

Abstract
Understanding the development and progression of tumors is fundamental for the improvement of patient treatment and care. Proliferative verrucous leukoplakia (PVL) is a recurrent, multifocal, precancerous lesion that often transforms into oral squamous cell carcinoma (SCC). Multifocal lesions may be separated in either space (synchronous) or time (metachronous). It is essential to determine the relationship between multifocal lesions in order to properly understand the progression of the disease and treat it accordingly. It has yet to be determined whether PVL lesions arise independently or are derived from a common ancestral clone of cells. We have developed a permutation algorithm to test the null hypothesis that the tumors from the same patient share no more genetic alterations than tumors originating from different patients. The alternative hypothesis is that tumors from the same patient, though separated by time and/or space, share a greater number of chromosomal abnormalities than would be expected by chance and so likely share a common premalignant ancestor cell. This will allow us to determine if the tumors arise as independent events or share some clonal relationship. Biopsy data from nine patients, each with multiple tumors, was used to run individual BAC arrays for each lesion. The breakpoints of genetic alterations were determined using Circular Binary Segmentation (CBS) and served as input for our permutation algorithm which counts the number of shared breakpoint positions between tumors. Though many regions in the genome may be prone to gain or loss in a tumor, the exact start and stop of a breakpoint likely defines a unique event such that two or more lesions sharing this alteration can be considered a signature of clonality. We found that five of the nine patients share a significant number of genetic aberrations between their SCC lesions, leading to the conclusion that in approximately half of patients, multifocal PVL tumors are clonally related. Our algorithm for identifying clonality between multiple samples from a patient could be used on a variety of platforms including high density SNP arrays, measuring loss of heterozygosity and copy number alterations, as well as high throughput sequencing. All that is required is multiple, spatially or temporally distinct samples from each patient and multiple patients.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2003.
Abstract 2004: Search for biomarkers of oral lesion by laser microdissection and LC/MS/MS method
Authors: Yamamoto Gou , Hokazono Chie , Kawamoto Mao , Isobe Tomohide , Irie Tarou , Shintani Satoru , Tachikawa Tetsuhiko 
Published: February 2011

Abstract
When we perform profiling analysis using tissue of Homo sapiens, individual difference becomes one of large problems. We use a laser microdissection as one of the solutions for this problem and try profiling analysis from tissue section. This technique can collect the part where morphologic evidence varies from the same tissue section, and comparison in an equivalence case besides in same lesion become possible. In addition, a laser microdissection method is effective in hyperplasia, papilloma, border domain, complicated differentiation form, such as lesion difficult to obtain a cultured cell. In this study, we collected area of normal epithelium, epithelial dysplasia and squamous cell carcinoma from tissue section by using laser microdissection. Collected tissue was dissolved in lysis buffer and digested by trypsin to make samples. Each sample was analyzed and quantified by LC/MS/MS, then, obtained data was referred to the protein database (SWISS PROT). From this procedure, we found over 100 different types of protein in every area. In comparison with each protein profiling list, many already known marker of oral squamous cell carcinoma, such as keratin 17, keratin 13, lumican and CD98, was detected. Two new candidate markers of oral squamous cell carcinoma are discovered at present: one is keratin superfamily, and another is tumor related protein. About extracted new candidate markers, we perform real time PCR, immunohistochemistry and Western blot from tissue section for validation. In conclusion, Laser microdissection and LC/MS/MS were useful method to search for markers of oral squamous cell carcinoma, and detected candidate marker was thought to be effective for diagnosis.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2004.