bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 1982: Analyzing TCGA data: A novel, systems-oriented method for diagnosing batch effects and adjusting for them
Authors: Zhang Nianxiang , Akbani Rehan , Zhang Li , Broom Bradley , Baggerly Keith A. , Mills Gordon B. , Yung W.K. Alfred , Weinstein John N. 
Published: February 2011

Abstract
The Cancer Genome Atlas (TCGA) project aims at multi-faceted molecular characterization of up to 25 different types of clinical cancers over the next 5 years. Included are profiles of single-nucleotide mutations, indels, loss of heterozygosity, DNA copy number, DNA methylation, mRNA expression, and microRNA expression. For each type of measurement, an absolutely critical initial question is whether the batches of tumors obtained from different sources and/or processed at different times show batch effects that might confound our ability to draw valid conclusions about the biology or about clinical outcomes. As PIs and members of a newly designated TCGA Genome Data Analysis Center B, we have developed and applied a novel, systems-oriented approach to the problem of batch differences. The method is based on a scalar quantity that we call the “correlation of correlations” (CR). CR reflects the difference between batches, not in terms of characteristics of the individual genes but in a more systems-oriented way based on the pattern of relationships among the various genes in the data set. If two batches of samples are identical, CR = 1; if they are randomly related to each other in their properties, CR = 0. To assess the statistical robustness (i.e., p-value) of any apparent difference between two batches, we apply a permutation test, keeping the batch sizes constant. That analysis is complemented by principal component analysis and hierarchical clustering. In addition to diagnosing batch effects, we have tested five different algorithms (empirical Bayes with parametric and non-parametric prior, median polish, batch-wise median polish, ANOVA, and ANOVA with variance shrinkage) to correct in part for any batch effects that do exist. We first applied the new approach to TCGA Affymetrix U133A mRNA expression data on 237 high-grade serous ovarian cancers. One batch (designated # 9) out of 6 stood out as different from the others, particularly from batch #14 (permutation test two-tail p &lt;0.001). Of the 5 adjustment methods, batch-wise median polish produced the greatest uniformity of the final data set and the greatest decrease in hierarchical clustering batch effects (Fisher's exact p &lt;0.0001). Similar analysis of 327 TCGA glioblastoma samples showed batch #4 to be the most statistically significant outlier out of 10 batches, with batch #3 also significantly different. We are using the same methods to assess global similarities and differences among disparate classes of data, for example mRNA and microRNA expression.
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 1982.
Abstract 1984: A novel logistic regression model for microRNA microarray normalization
Authors: Wang Bin , Howell Paul , Wang Xiaofeng , Qian Xuemin , Huang Kun , Riker Adam , Ju Jingfang , Xi Yaguang 
Published: February 2011

Abstract
MicroRNA (miRNA) is a set of newly discovered non-coding small RNA molecules. It regulates gene expression at the translational level through binding to the 3′-UTR of the target gene. Its significant effects have contributed to a number of critical biological events including cell proliferation, apoptosis, development as well as tumorigenesis. High throughput genomic discovery platforms (e.g. microarray) have been employed to evaluate the important roles of miRNAs by analyzing their expression profiling. However, because of the small total number of miRNAs and the absence of well known endorse controls, the traditional normalization methods for messenger RNA (mRNA) profiling analysis could not offer a suitable normalization solution for miRNA analysis. The establishment of new adaptive normalization methods has come to the forefront. In this study, Locked Nucleic Acid (LNA) based miRNA array was employed to profile miRNAs using colorectal cancer cell lines HCT116 under different drug treatments (5FU, CPT-11, and oxaliplatin). We randomly selected approximate 10% of total microRNAs from the microarray (37 miRNAs) and determined their expression patterns using quantitive real-time PCR (qRT-PCR), which has become the gold standard for relative gene expression analysis and one of the major validation methods after high throughput discovery. Then, a logistic regression model was built to normalize the miRNA expression data from miRNA array, by utilizing the results from qRT-PCR and some auxiliary variables. Twenty additional miRNAs were selected to validate the predicted results by the novel model. The result shows that the consistency between the qRT-PCR and array results was significantly improved with the new normalization method. Compared to other popularly used normalization methods, the logistic regression model efficiently calibrates the variance across arrays and improves miRNA microarray discovery accuracy.
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 1984.
Abstract 1985: Identification of differentially expressed genes using annealing control primer (ACP)-based GeneFishing PCR technique in serous ovarian carcinoma of Korean women
Authors: Choi Dae Han , Bae Sumi , Kim Jeong Shick , Bae Dong Han , Baek Kwang-Hyun , Ahn Woong Shick 
Published: February 2011

Abstract
Object : Ovarian cancer is the most lethal among gynecologic neoplasmas in women more than 60% of ovarian cancer is serous cystadenocarcinoma. The aim of this study is to discover different genes expression profiles between serous cystadenocarcinoma of ovary in Korean women and normal ovarian tissue.
Methods : Twenty ovarian serous cystadenocarcinoma specimens were obtained from the Department of Obstetrics and Gynecology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea. We used a common reference as a control Stratagene (www.stratagene.com). The profiles of expressed genes were discovered from the ovarian cancer using annealing control primer (ACP)-based GeneFishing polymerase chain reaction (www.seegene.co.kr), screened by a BLAST search, and confirmed by quantitative reverse transcription-PCR (qRT-PCR).
Results : In the study, about 173 differential expressed genes were identified between normal and ovarian serous cystadenocarcinoma samples, 105 of differentially expressed genes were identified more than 2-folds, 68 up-regulated and 37 down-regulated genes were sequenced. Up-regulated genes were DC_UbP, mitochondrial respiratory proteins, secretoglobin, gelsolin, actinin, cox2, sarcoglycan, VTCN1, DYNEIN, S100 A10, IFI27, EIF4A1, IFITM1, B-cell translocation protein 1, PPA1, NDRG1, HLA-DRA, COL11A1, BAZ2B, RAD54L, PRDX1, SMAD5, ELF3, SSBP1, HSBP1, TFG, SP3 etc. and down-regulated genes were MYH11, TIMP1, CYP21A2, Myo15, complement component1(C1S), FOXP1, Ku etc. Among 105 clones selected by ACP-based GeneFishing PCR, 57 genes (46 up-regulated and 11 down-regulated genes) with different expression patterns were determined and all these were confirmed by quantitative real time RT-PCR. Especially qRT-PCR analysis showed that SSBP1, HSBP1, TFG and SP3 genes were up expressed, and C1S gene was down expressed in 100% (20/20) patients with serous ovarian carcinoma.
Conclusion : We identified the five highly expressed genes in serous ovarian adenocarcinoma using ACP-based GeneFishing PCR technique in Korean women. The detail functions of those genes and their products remain to be determined, the genes will provide insights into mechanisms of carcinogenesis or tumor progression in serous ovarian carcinoma in Korean women.
Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend.
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 1985.
Abstract 1986: RAS signaling is the key factor determining differential response to PI3K and MAPK targeting compounds in a panel of breast cancer cell lines
Authors: Feldman Igor , Zhang Theresa , Nebozhyn Michael , Ayers Mark , Paweletz Cloud , Lynch Bethany , Arthur Bill , Roberts Brian , Strack Peter , Shumway Stuart , Chen Albert , Chastain Mike , Huang Pearl , Dai Hongyue , Watters James , Loboda Andrey 
Published: February 2011

Abstract
We have tested PI3K and MAPK targeting compounds in a panel of 69 breast cancer cell lines. Following the molecular stratification of breast cancer tumors, we have used ER and HER2 biomarkers to stratify cell lines into HER2 positive (HER2+), ER positive (ER+), and triple negative (TN; ER-, PR- and HER2-) subgroups. Both gene expression and response to compounds showed significant differences among the subtypes. Response to mTOR and AKT inhibition was the greatest in ER+ and HER2+ groups (86%, 85% for mTORi and 64%, 77% for AKTi response rates, respectively), whereas TN cell lines showed preferential sensitivity to MEK inhibition (30%). The combination of AKT plus MEK and mTOR plus MEK inhibitors showed synergy in TN tumors (56% and 80% response rates, respectively), particularly in the epithelial subgroup. We believe that RAS pathway deregulation, as reported by a gene expression signature of RAS activation, is the key latent variable that explains the difference in responses. This conclusion is based on pathway activation differences between subtypes. We observe that the TN group has both elevated PI3K and MAPK signaling, evident by high levels of RAS, pERK, and pMEK signatures, whereas the ER+/GGI+ group only has high levels of PI3K signaling. Thus, mTOR, AKT, or MEK alone is insufficient to inhibit the TN lines, whereas the combos are very effective. Finally, we have assessed the prevalence of the EMT and RAS signatures across subtypes of breast tumors. Similar to cell lines, the RAS signature is markedly higher in TN compared to ER+/GGI+ and, to a lesser extent, compared to HER2+ tumors. The EMT signature on the other hand is not significantly different among subtypes. This would suggest that the response patterns observed in ER+/GGI+ and TN/E subtypes of this breast panel will be applicable to a substantial subpopulation of breast tumors (∼38%). Importantly, these breast subtypes represent the largest unmet need and are a high priority for the clinical oncology.
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 1986.
Abstract 1988: In silico estimates of cell components in cancer tissue based on expression profiling data
Authors: Wang Yipeng , Xia XiaoQin , Jia Zhenyu , Sawyers Anne , Yao HuaZhen , Wang-Rodriquez Jessica , Mercola Dan , McClelland Michael 
Published: February 2011

Abstract
Cancer gene expression profiling studies often measure samples that vary widely in the mixtures of cell types they contain. Such variation could confound efforts to correlate expression with clinical parameters. In principle, the proportion of each major tissue type can be estimated from the profiling data and used to triage samples before using the data to study correlations with disease parameters. Four large gene expression microarray data sets from prostate tissue whose cell components were estimated by pathologists were used to test the performance of in silico prediction of tissue components. Multi-variate linear regression models were developed for in silico prediction of major cell components of prostate cancer tissue. 10-fold cross-validation within each data set gave average differences between the pathologist and in silico predictions of 8∼14% for the tumor component and 13∼17% for stroma component. Across data sets that used similar platforms and fresh frozen samples, the average differences were 11∼12% for tumor and 12∼17% for stroma. Prediction models were applied to expression data on the same platform from 219 other tumor-enriched prostate cancer samples for which tissue proportions were not known. The tumor “enriched” samples were predicted to have a wide range of tumor percentages; 0 to 87%. Furthermore, there was a 10.5% difference in the average predicted tumor percentages between 37 recurrent and 42 non-recurrent cancer patients. This systematic difference in tumor content would likely cause tissue-specific gene changes to falsely appear to be correlated with recurrence unless some samples were excluded to remove this bias or unless tissue percentages were incorporated into the prediction model. Similar circumstances may arise in other sets of clinical samples. A web service, CellPred, has been designed for the in silico prediction of prostate cancer sample cell components. While this site is currently based on microarray data, it could equally well use high-throughput sequencing data. The approach presented here can be generalized to other tissue mixtures once data on both tissue content and expression profiles are obtained for a training set. CellPred is freely available at http://www.webarraydb.org/.
Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend.
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 1988.
Abstract 1989: Gene expression signature of the non-cancerous liver tissue associated with the early recurrence of hepatocellular carcinoma
Authors: Tanaka Shinji , Mogushi Kaoru , Yasen Mahmut , Noguchi Norio , Irie Takumi , Kudo Atsushi , Nakamura Noriaki , Inazawa Johji , Tanaka Hiroshi , Arii Shigeki 
Published: February 2011

Abstract
Recurrence of hepatocellular carcinoma (HCC) might be associated with biological aggressiveness of the cancer as well as background status of the liver. In this study, the predictive values for the early recurrence were assessed on patients with HCC after curative hepatectomy using clinicopathological factors and genome-wide gene expression signatures. Multivariate analysis of clinico-pathological factors revealed portal vein invasion (p=0.007), hepatitis C virus infection (p=0.001), and low levels of serum albumin (p=0.003) as the risk factors, yielding a ROC-plot AUC value of 0.854 with 61.5% sensitivity and 81.8% specificity. Analysis of the gene expression profiling on the cancer tissues of HCC revealed the significant differences in CD24 stem cell marker and MTSS1 metastasis suppressor molecule. The cancer six-gene signature for the prediction of recurrence yielded a ROC-plot AUC value of 0.897 with 81.8% sensitivity and 88.5% specificity. Using the non-cancerous liver tissues surrounding HCC, distinct differences were recognized by the gene expression profiling such as IGL immunoglobulin lambda light chain and MAP2K1 mitogen-activated protein kinase kinase. The non-cancer six-gene signature yielded a ROC-plot AUC value of 0.966 with 84.8% sensitivity and 88.5% specificity for the prediction of HCC recurrence. These gene expression signatures can be involved in the metastatic potentials of the invasive HCC, and the multi-centric hepatocarcinogenesis, respectively. Our results might indicate the molecular targets for prediction and/or treatment of the recurrence, as well as the super-high risk group of HCC within the patients with hepatitis.
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 1989.
Abstract 1993: Higher activity of cell proliferation is associated with poor survival in lung adenocarcinoma
Authors: Lu Jo-Yang , Hsiao Tzu-Hung , Peck Konan , Chuang Eric Y. , Lai Liang-Chuan 
Published: February 2011

Abstract
The number of patients with lung adenocarcinoma, a major histological type of lung cancer, has soared recently. Although some lung adenocarcinoma patients could be diagnosed at early stages and received surgical resection, nearly 50% of patients still died from recurrence. This phenomenon indicates that using only traditional prognostic factors, like TMN staging, is not sufficient for regimen decision. Here we proposed a bioinformatic method to evaluate the activity of cell cycle from expression profiles and proved that the activity of cell cycle can be applied as prognostic factor of lung adenocarcinoma, especially for early stages.
A gene set named as cell cycle signature (CCS), which correlated with cell cycling, was used to measure the activity of tumor proliferation. The E2F1 target genes and E2F3 target genes were also applied to measure the E2F signaling pathway activity, which was regulated by the cell cycle. The prognostic ability of these gene sets was evaluated by applying Cox hazard proportional analysis to three microarray datasets of lung adenocarcinoma.
Our result revealed that the association between high activities of cell cycle and poor survival outcomes existed in lung adenocarcinoma patients. The result of Cox hazard proportional analysis showed that the CCS and E2F1/E2F3 target genes are significant contributors to survival risk. The p-values of CCS, E2F1/E2F3 target genes were all showed significant (p&lt;0.05), and these three gene sets still gave statistical significances after the survival analysis was applied on only early stage lung adenocarcinoma. The hazard ratios of CCS, E2F1 target genes and E2F3 target genes were 5.69, 3.32, and 3.96, respectively; all p-values were smaller than 0.002.
We demonstrated that the three gene sets, which accountable for the activity of cell cycle, can be applied as prognostic factors for lung adenocarcinoma, including early stage patients. Our data inferred that tumor with higher activity of proliferation is malignant eventhough its size may still be small. This finding is valuable in predicting the survival of early stage lung adenocarcinoma patients and might be useful for making treatment decisions.
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 1993.
Abstract 1994: Mediators responsible for the invasive progression of superficial bladder cancers
Authors: Seol So-Young , Lee Sang-Yop , Kim Seong-Gi , Leem Sun-Hee , Chu In-Sun 
Published: February 2011

Abstract
Bladder cancer is seventh most prevalent type of cancer worldwide and accounts for an estimated 150,000 deaths annually. Urothelial carcinoma of the bladder accounts for more than 90% of bladder cancers. This cancer presents as a heterogeneous disease that consists of two main phenotypic groups with distinct biological behaviors and prognoses: Approximately 80% of patients have tumors that are superficial or non-muscle invasive, and the remaining 20% of tumors presents as a muscle-invasive tumor with dismal prognosis. After early treatment by surgical resection and intravesical immunotherapy, around 20% of these patients have disease progression to invasive tumors and eventually die of the disease. Current methods of predicting the clinical behavior of these tumors prospectively are unreliable. Due to the progress of superficial bladder cancer into invasive bladder cancer, a development of marker that could identify superficial cancers with a high risk of progression is needed. In our microarray analysis from 165 bladder cancer patients, supervised analysis of gene expression data revealed a gene expression signature that is strongly associated with invasive bladder tumors. Gene network analyses of the signature revealed that E2F1 and its downstream effectors EZH2 and SUZ12 could be important mediators for the invasive and metastatic progression of superficial tumors. Furthermore, we investigated how these genes may affect the invasive and metastatic progression of superficial tumors. We investigated the invasive ability by these genes in two groups of bladder cancer cell lines: One group (UC9 and UC14) has a superficial signature of bladder cancer, and the other group (EJ and UC13) has an invasive signature of bladder cancer. We examined the effects of overexpression or siRNA inhibition of these genes on cell growth, wound healing migration and invasion in bladder cancer cell lines. We will report the results estimating the roles of these genes for the invasive and metastatic progression in bladder cancer cell lines.
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 1994.
Abstract 200: Methylation of GATA4 and GATA5 transcription factor genes in gastric cancers
Authors: Akiyama Yoshimitsu , Nagasali Hiromi , Kawamoto Ayako , Herman James G. , Baylin Stephen B. , Yuasa Yasuhito 
Published: February 2011

Abstract
GATA factors comprise a small family of transcription regulatory proteins containing two conserved zinc finger DNA binding domains for the consensus sequence (WGATAR). Among the six GATA factors, GATA-1/2/3 factors are prominently expressed in the hematopoietic cell lineage, while GATA-4/5/6 factors show a partly overlapping expression pattern in the heart and endoderm-derived organs. We previously reported that GATA4 and GATA5 were silenced by their promoter hypermethylation in gastrointestinal, lung and ovarian cancers. However, it remains unknown the mechanism underlying loss of GATA transcription factors in gastric carcinogenesis. To clarify the role of GATA, we examined GATA4/5 methylation and their downstream target genes in gastric cancer (GC). By using methylation specific PCR, the methylation frequency of GATA5 (30, 39%) was significantly higher than that of GATA4 (10, 13%) in 77 GC tissues (P&lt;0.01). However, methylation of GATA6 was not observed in GCs examined. We transiently over-expressed GATA4 or GATA5 in GC cell lines lacking their expression by aberrant methylation. Both GATA4 and GATA5 suppressed colony formation and cell proliferation in MKN74 cells. After GATA4/5 over-expression in MKN74 and KATO-III cells, enhanced expression of numerous genes including ones indicating tumor-suppressive functions, such as TFF1, disabled-2 and IQGAP2, was observed by microarray and RT-PCR analyses. The target genes of GATA4 and GATA5 were closely similar in MKN74 cells. We also preformed siRNA transfection of GATA4 and GATA5 in AGS and HSC43 cells which basally expressed them. Reduced expression of above predicted GATA target genes was detected in these two cell lines after siRNA transfection. These data suggest that loss of GATA4 and GATA5 expression may contribute to gastric carcinogenesis.
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 200.