bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 522: Histone deacetylase 6-let-7i-5p-thrombospondin-1 signaling axis suppresses CD47-dependent tumorigenic behavior of liver cancer
Authors: Yang Hee Doo , Eun Jung Woo , Shen Qingyu , Kim Hyung Seok , Kim Sang Yean , Nam Suk Woo 
Published: August 2018

Abstract
Histone deacetylase 6 (HDAC6) uniquely endows as tumor suppressor in liver tumorigenesis, but the underlying mechanisms leading to liver cancer are not fully understood. To identify the large-scale microRNA (miRNA) expression changes by HDAC6, we performed miRNA expression analysis in HDAC6-overexpressing Hep3B cells. From this, let-7i-5p was suggested as most highly associated miRNA with HDAC6 in liver cancer cells. We also found that let-7i-5p expression was up-regulated in a large cohort of HCC patients, and high expression of let-7i-5p was significantly associated with poor prognosis of HCC patients. Ectopic expression of antisense let-7i-5p (AS-let-7i-5p) caused cancer cell growth inhibition mediated by caspase-dependent cell death processing, and inhibited epithelial-mesenchymal transition (EMT) of liver cancer cells. Computational analysis suggested that thrombospondin-1 (TSP-1) is a specific target for let-7i-5p in liver cancer cells. Increased secretion of TSP1 was detected in AS-let-7i-5p transfected HCC cells. We found that partially purified TSP-1 from culture media (ppTSP-1) induced cellular death processing and simultaneously inhibited tumor angiogenesis and metastatic behavior of liver cancer cells. In addition, we observed that anti-TSP-1 antibody containing CD47 receptor binding motif (3F352) attenuated HDAC6, AS-let-7i-5p and TSP-1 effects on liver cancer cells. Furthermore, TSP-1 and ppTSP-1 treatments significantly enhanced macrophage phagocytosis through blocking CD47-dependent “Don't eat me” signal in liver cancer cells. Our findings suggest that HDAC6-let-7i-5p-TSP-1 signaling axis regulates CD47-dependent neoplastic and phagocytic behaviors of hepatocytes providing a novel target for the molecular treatment of liver malignancies.
Citation Format: Hee Doo Yang, Jung Woo Eun, Qingyu Shen, Hyung Seok Kim, Sang Yean Kim, Suk Woo Nam. Histone deacetylase 6-let-7i-5p-thrombospondin-1 signaling axis suppresses CD47-dependent tumorigenic behavior of liver cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 522.
Abstract 5244: Neratinib induced HER2 dependent and independent intracellular signaling events in human breast cancer cells and the clinical implications
Authors: Jiang W. G. , Martin Tracey A. , Owen Sioned , Xin Ling , Liu Yinhua , Ruge Fiona , Avogadri-Connors Francesca , Lalani Alshad S. , Bryce Richard P. , Davies Eleri 
Published: August 2018

Abstract
Background. Neratinib is an orally available irreversible pan-HER receptor tyrosine kinase inhibitor that has clinical benefit in patients with HER2-positive and HER2-mutated breast cancer. Neratinib also targets the other two members of the HER family, namely EGFR and HER4. However, tentative evidence suggests that neratinib may affect kinases of non-HER family. In the present study, we aimed to explore the pattern of kinases targeted by neratinib, in the context of HER2 non-amplified cancer cells and explored the potential clinical implications. Method. A panel of HER2-low/medium-expressing (MCF-7 and ZR-75-1) and HER2- negative (MDA-MB-231 and BT549) human breast cancer cells were used. The response of a panel of 304 kinases to neratinib was screened using the kinase antibody array. Cellular toxicity was quantified using a colorimetric method. Candidate neratinib-responsive kinases were subject to analyses against the survival of a breast cancer cohort as well as a public database for additional validation. The protein expression level of the kinase targets identified was also validated on tissue arrays from breast cancer by immunohistochemistry. Result. Of all the kinases tested, thirty-six were found to be influenced by neratinib, either via activation or suppression of their phosphorylation. Based on the differential responses to neratinib in HER2 negative and positive breast cancer cells, a small panel of the kinases were classified as HER2 independent. Using clinical cohorts, these kinases collectively had predictive value for the overall survival of the patients (p&lt;0.0001). We further analysed one of the candidate kinases, namely salt inducible kinase-1 (SIK1) and the SIK family in relation with HER2. HER2 expression was found significantly correlated with both SIK1 (r=0.46, p&lt;0.001) and also other two SIK family members. SIK1 protein staining in the tissue array was found to be aberrant in breast tumours. Conclusion. Neratinib has an effect on a subset of HER2 independent kinases in breast cancer cells. These kinases had a prognostic value on patient's survival and correlated with HER2 expression, as in the case of the SIK family.This finding may have important implication in understanding the biology of HER2 inhibitors such as neratinib.
Citation Format: W. G. Jiang, Tracey A. Martin, Sioned Owen, Ling Xin, Yinhua Liu, Fiona Ruge, Francesca Avogadri-Connors, Alshad S. Lalani, Richard P. Bryce, Eleri Davies. Neratinib induced HER2 dependent and independent intracellular signaling events in human breast cancer cells and the clinical implications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5244.
Abstract 5259: Cancer incidence in relation to body fatness in China: Evidence from a large population-based cohort study
Authors: Wang Lu , Jin Guangfu , Yu Canqing , Lv Jun , Guo Yu , Bian Zheng , Yang Ling , Chen Yiping , Hu Zhibin , Chen Feng , Chen Zhengming , Li Liming , Shen Hongbing 
Published: August 2018

Abstract
Body fatness has been associated with several cancers in developed countries, but little is known in China. The purpose of this study was to examine the association between body fatness and cancer incidence, with different anthropometric measures, and compare their predicting values. Between June 2004 and July 2008, the China Kadoorie Biobank (CKB) study recruited 0.5 million adults aged 30-79 years from 10 geographically diverse areas across China, and followed up until December, 2015. Body-mass index (BMI), body fat percentage (BFP), waist circumference (WC), and waist-to-hip ratio (WHR) were measured at baseline. Cox regression yielded adjusted hazard ratios (HRs) associating incidence of all cancers and 15 site-specific cancers with different anthropometric measures, adjusting for education level, marital status, annual household income, alcohol consumption, smoking status and physical activity, and stratifying by age at risk, sex, and region. We compared the ability of cancer risk prediction between different anthropometric measures through a receiver operating characteristic (ROC) analysis. Among 508,362 participants, the overall mean (SD) BMI was 23.66 (3.38) kg/m2, 31.11% of men and 34.24% of women were overweight or obesity (BMI≥25.0kg/m2), and 4.41% of men and 4.26% of women were underweight (BMI&lt;18.5kg/m2). 21,474 incident cancers were identified over an average of 8.94 years of follow-up. Each 5 kg/m2 increase in BMI was associated with an increased risk of endometrial (HR, 2.01; 95% CI, 1.72 to 2.35), postmenopausal breast (HR, 1.29; 95% CI, 1.18 to 1.40), colorectal (HR, 1.17; 95% CI, 1.10 to 1.25) and cervical (HR, 1.15; 95% CI, 1.03 to1.29) cancer, whereas it was associated with a reduced risk of oesophageal (HR, 0.73; 95% CI, 0.67 to 0.79), lung (HR, 0.78; 95% CI, 0.74 to 0.82), liver (HR, 0.85; 95% CI, 0.79 to 0.92), and stomach (HR, 0.88; 95% CI, 0.82 to 0.94) cancer. BMI was the best risk prediction measure for postmenopausal breast and endometrial cancer, whereas BFP were the best for oesophageal, lung, liver and stomach cancer, and WC and WHR did for colorectal cancer. BMI is related to the incidence of several cancers in China. Obesity and overweight, as well as underweight, contribute to the cancer incidence in China. Other anthropometric measures may add information for cancer-specific risk prediction.
Citation Format: Lu Wang, Guangfu Jin, Canqing Yu, Jun Lv, Yu Guo, Zheng Bian, Ling Yang, Yiping Chen, Zhibin Hu, Feng Chen, Zhengming Chen, Liming Li, Hongbing Shen. Cancer incidence in relation to body fatness in China: Evidence from a large population-based cohort study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5259.
Abstract 5269: Body mass index may not have causal association with thyroid cancer risk: A Mendelian randomization study
Authors: Kim Jeongseon , Lee Soo Ji , Nguyen Quy N. , Lee Jeonghee , Lee Eun Kyung , Hwangbo Yul , Sung Joohon 
Published: August 2018

Abstract
Background: Thyroid cancer (TC) is one of the endocrine tumors of which incidence rates have shown an upward trend worldwide. Obesity, another endemic health issue, has been recently reported in the association with increased TC risk. We attempted to examine if there is a causal association between body mass index (BMI) and TC using a Mendelian randomization approach.
Methods: Total 17,935 healthy individuals from the Korean Genome Epidemiology Study and 1,214 TC cases from National Cancer Center, Korea, and Seoul National University Hospital were selected with age, sex, BMI, and genetic information. Based on the thirteen previously reported single nucleotide polymorphisms associated with BMI, we constructed a genetic risk score (GRS) as a genetic instrumental variable (IV) representing BMI independent of possible confounding. IV analysis was performed using the ratio (or, Wald) method to test causal association.
Results: The odds of TC were 2.6 times higher in females than males. The cases were younger than the controls. The F-statistic from the regression of BMI on BMI GRS (IV) was 157.2 (usually, F larger than 10 indicates a strong and valid IV), and the IV explained 1.10% of the phenotypic variance for BMI. From IV analysis, genetically instrumented BMI was not associated with TC risk (causal odds ratio per 1kg/m2 increase in BMI 0.98 [0.79 - 1.20 95% confidence interval]).
Conclusion: Our analysis suggests that positive association between obesity and TC risk repeatedly reported from several meta-analyses may be null. Further investigation is needed as the incidence rates differ in different ethnicity.
Citation Format: Jeongseon Kim, Soo Ji Lee, Quy N. Nguyen, Jeonghee Lee, Eun Kyung Lee, Yul Hwangbo, Joohon Sung. Body mass index may not have causal association with thyroid cancer risk: A Mendelian randomization study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5269.
Abstract 527: Identification of novel target mRNAs of microRNA-143 in glioblastoma cells
Authors: Lozada-Delgado Eunice , Valiyeva Fatma , Marcos Maria , Vivas Pablo 
Published: August 2018

Abstract
The purpose of this study is to assess the biological role of microRNA-143 (miR-143) in Glioblastoma multiforme (GBM). In the United States, the incidence of GBM is about 17% of all primary brain tumors and about 60-75% of all Astrocytomas. Many patients recur even after therapy with a median survival rate of 15 months. MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. Deregulated miRNAs have been identified in cancer including GBM. In this study, we aim to thoroughly uncover the role of miR-143 by using GBM cell lines, mouse models, and patient samples. Previous qPCR data from FFPE samples of Puerto Rican GBM patients showed a higher relative expression of miR-143 in GBM patients compared to control individuals and paired surrounding non-cancerous tissue suggesting an oncogenic role. Moreover, in vitro data of transient transfections of a miR-143 oligonucleotide inhibitor in GBM cells showed reduced cell proliferation (clonogenic assay), increased apoptosis and cell cycle arrest in the G0/G1-S phase (flow cytometry and western blot analysis). Furthermore, we want to identify novel target mRNAs of miR-143 in GBM cells that may explain these results. Using in silico analysis tools and a qPCR analysis we identified 5 candidate genes as potential miR-143 targets. Western blot analysis of the proteins encoded by these genes using miR-143 overexpressing cells showed that the Integral membrane protein 2B (ITM2B) and Zinc transporter 8 (SLC30A8) protein levels were reduced and when miR-143 was transiently inhibited their protein levels where increased. These results suggest that miR-143 targets these mRNAs. Ongoing luciferase reporter assays will determine direct binding of miR-143 to the 3'UTR of these mRNAs in GBM cells.
Citation Format: Eunice Lozada-Delgado, Fatma Valiyeva, Maria Marcos, Pablo Vivas. Identification of novel target mRNAs of microRNA-143 in glioblastoma cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 527.
Abstract 5278: Tobacco and areca nut use among Chuukese youth in Guam
Authors: Somera Lilnabeth P. , Simsiman Brayan , Badowski Grazyna , Lee Hye-ryeon , Cassel Kevin 
Published: August 2018

Abstract
Background: Little is known regarding the tobacco use of Micronesian population in Guam. According to the Youth Risk Behavior Survey (YRBS) 2013, Micronesian youth have a higher prevalence rate of current smokers (27.2% vs. 15.7% for U.S.) and current smokeless tobacco users (39.7% vs. 8.8% for US) compared to the U.S. They also have the highest rate among all ethnic groups in Guam. This study aims to investigate tobacco use and areca nut use, which may explain high lung and bronchus cancer incidence and mortality rates among Micronesians. The survey in this study focuses on Chuukese youth, the largest group among Micronesians in Guam.
Methods: Respondent-driven sampling method (RDS) was used to recruit 364 Chuukese youth (ages 13-19) to complete the survey. YRBS question items that measured cigarette, cigar, and smokeless tobacco use were included in the survey. Measures for areca nut use were also included. Chi-square tests were performed by bivariate analysis. Only high school-level youth are included in the analysis.
Results: A total of 237 Chuukese high school students completed the survey. Fourteen percent of the participants currently smoke cigarettes, 6.4% currently smoke cigars, and 23.7% currently use smokeless tobacco. In addition, smokeless tobacco remains highest regarding daily use (11%) within the past 30 days prior the survey. Although there is high use of smokeless tobacco among participants, there are significant associations between gender and cigarette and gender and cigar use only. Boys smoke cigarettes and cigar at higher rates than girls. Among the recruited participants, 32% are areca nut users with tobacco product as an ingredient. There is significantly high association between smokeless tobacco users and areca nut with tobacco users. The majority of cigarette smokers (82.4%) have tried to quit smoking. Fifty-six percent of the smokeless tobacco users have tried to quit as well. However, only 17% of the participants are aware of the Guam Youth Quitline.
Conclusion: Results suggest the need to raise awareness among Chuukese youth on tobacco cessation programs on Guam, particularly the smoking cessation quitline. Tobacco cessation efforts should not focus on cigarette use only, but must also be expanded to include the use of smokeless tobacco products and chewing areca nut. Future studies should investigate the roles and implications of tobacco as an ingredient of areca nut chewing among Micronesian youth.
Citation Format: Lilnabeth P. Somera, Brayan Simsiman, Grazyna Badowski, Hye-ryeon Lee, Kevin Cassel. Tobacco and areca nut use among Chuukese youth in Guam [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5278.
Abstract 5294: CIMerge: A machine learning approach for merging and genotyping complex indel calls from NGS data
Authors: Zheng Tian , Li Yang , Geng Yu , Zhao Zhongmeng , Zhang Xuanping , Wang Jiayin 
Published: August 2018

Abstract
Complex insertion and deletion (complex indel) is a rare category of genomic structural variations, which is formed by inserting one or multiple DNA fragments into the genomic location where a deletion occurs. A recent study conducts a systematic analysis from over 8,000 pan-cancer cases, which reports hundreds of complex indels in cancer-associated genes, some of which are considered potentially druggable. Several approaches are proposed to detect complex indels from the new-generation sequencing data (both 2nd and 3rd generation). However, as different data-mining algorithms vary the preferences on capturing data patterns, different approaches may report the conflicted complex indel calls. Here, we propose a machine learning approach to correct the conflicted calls from different approaches and further estimate the genotype of each call. The proposed approach, implemented as CIMerge, adopts a relevance vector machine framework. For each candidate call, CIMerge first extracts a set of features on the candidate region, which includes the read depth, variant allelic frequency, number of the splitting/unmapped reads, number of the discordant paired-end reads, aligned contig, etc. CIMerge also considers another set of features on data-mining algorithm(s) that reported the candidate call, which includes the parameter settings, etc. Both sets of features are trained by the relevance vector machine framework, which outputs the probability of each candidate of the conflicted call. As a byproduct, it outputs the genotype of the candidate call with highest likelihood. We tested CIMerge on multiple datasets generated by different simulation configurations and compared it to several state-of-the-art approaches. The experiment results demonstrate that CIMerge outperforms the existing approaches. The average success rate of recognition is approaching 90%, while Pindel and Gindel are reported as 62.53% and 65.202%, respectively. The software package CIMerge is freely available for academic uses at https://github.com/xjtu712-lab/CIMerge.
Citation Format: Tian Zheng, Yang Li, Yu Geng, Zhongmeng Zhao, Xuanping Zhang, Jiayin Wang. CIMerge: A machine learning approach for merging and genotyping complex indel calls from NGS data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5294.
Abstract 5295: Toward high throughput immune infiltrate analysis from H&E stained images
Authors: Rawat Rishi R. , Ruderman Daniel , Agus David B. 
Published: August 2018

Abstract
Our appreciation of the immune system in breast cancer is rapidly evolving. New methods to quantify the composition and spatial distribution of the immune infiltrate from pathology images are urgently needed to develop better strategies to activate the anti-tumor immune response. Existing methods to quantify the immune infiltrate are tedious (manual counting) or rely on immunohistochemistry (IHC) staining to identify immune cells. While significant efforts are underway to develop machine learning tools to categorize cells based on morphologic features in hematoxylin and eosin (H&E) stained histopathology images, all approaches are limited by the scarcity of large, annotated ground truth training sets. In this work, we propose a new approach, leveraging “style-transfer” algorithms from the computer vision community to generate large quantities of training data from IHC stains. Using style transfer, we generate synthetic H&E images from IHC stains for immune markers, such as CD45, CD8 and CD4. The generated images have pixel-perfect ground truth provided by IHC, and do not need manual labeling. We investigate the impact of training on increasing numbers of synthesized images and validate our algorithms on an independent test set annotated by a pathologist (n=100 patients, 3064 identified lymphocytes). Our baseline classifier achieves a 83% accuracy, compared to the pathologist ground truth. This work provides a novel, tractable, and efficient way to train data-hungry algorithms to identify multiple cell types from H&E stained images. This work is supported by a grant from the Breast Cancer Research Foundation (BCRF-17-002)
Citation Format: Rishi R. Rawat, Daniel Ruderman, David B. Agus. Toward high throughput immune infiltrate analysis from H&E stained images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5295.
Abstract 5298: The accurate noninvasive staging of liver fibrosis using deep learning radiomics: A prospective multicenter study
Authors: Zhou Hui , Wang Kun , Tian Jie 
Published: August 2018

Abstract
Purpose: We developed the deep learning Radiomics of elastography (DLRE) as a noninvasive method to assess liver fibrosis stages,which is essential for prognosis, surveillance of chronic hepatitis B (CHB) patients.
Methods and Materials: 402 patients were prospectively enrolled from 12 hospitals, and finally 2010 images were included into analysis randomly.DLRE adopted the CNN method, one of the deep learning radiomic techniques, for the automatic analysis of 2D-SWE images. This study was conducted to assess the accuracy of DLRE in comparison with 2D-SWE, transient elastography (TE), transaminase-to-platelet ratio index (APRI), and fibrosis index based on the four factors (FIB-4), by using liver biopsy as the gold standard. Analysis of receiver operating characteristic (ROC) curve were performed to calculate optimal area under it (AUC) for cirrhosis (F4), advanced fibrosis (≥F3), and significance fibrosis (≥F2) for all diagnostic approaches.
Results: AUCs of DLRE were both 0.98 for cirrhosis (95% confidence interval [CI]: 0.95-0.99) and advanced fibrosis (95% CI: 0.94-0.99), which were significantly better than other methods, as well as 0.76 (95% CI: 0.72-0.81) for significance fibrosis (significantly better than APRI and FIB-4).
Conclusion: DLRE shows the best overall performance in predicting liver fibrosis stages comparing with 2D-SWE, TE, and serological examinations. It is valuable and practical for popularized application of noninvasive diagnosis of liver fibrosis stages in HBV infected patients.
Citation Format: Hui Zhou, Kun Wang, Jie Tian. The accurate noninvasive staging of liver fibrosis using deep learning radiomics: A prospective multicenter study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5298.