bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 156: Visfatin induces LOX expression and promotes tumor metastasis through the Src/Akt signaling pathway in human chondrosarcoma cells
Authors: Yu Cheng-Chieh , Lin Chih-Yang , Tang Chih-Hsin 
Published: August 2019

Abstract
Chondrosarcoma, a common primary bone malignancy that affects the joints and bones, is associated with metastases in the lung, especially in cases of high-grade chondrosarcoma. The protein lysyl oxidase (LOX) can contribute to tumor growth and metastasis, while the adipokine visfatin is pro-angiogenic and facilitates tumorigenesis as well as metastasis. However, it is unclear as to whether any association exists between visfatin and LOX expression in human chondrosarcoma metastasis. We have discovered that visfatin induces the migration, invasion and increased expression of LOX mRNA and protein in human chondrosarcoma cell lines (JJ012 and SW1353). Pretreatment of these cell lines with Src and Akt inhibitors, or transfecting them with small interfering RNAs (siRNAs), inhibited visfatin-induced chondrosarcoma metastasis and LOX expression. Thus, visfatin promotes chondrosarcoma metastasis by inducing LOX expression via the Src/Akt signaling pathway in the JJ012 cell line. microRNA analysis revealed that visfatin-induced Src/Akt signaling is responsible for downregulating mature miR-26b-5p, which targets the 3' untranslated region (3`UTR) of LOX but does not affect primary and precursor miR-26b-5p expression. This downregulation of miR-26b-5p expression by visfatin was dose-dependent. Pretreatment with Src and Akt inhibitors or transfection with siRNA reversed miR-26b-5p expression. The migration and invasion ability of JJ012 cells was reduced when they were transfected with the miR-26b-5p mimic. In summary, our data demonstrate that visfatin induces LOX expression and promotes chondrosarcoma cell migration and invasion through the Src/Akt signaling pathway, by inhibiting miR-26b-5p.
Citation Format: Cheng-Chieh Yu, Chih-Yang Lin, Chih-Hsin Tang. Visfatin induces LOX expression and promotes tumor metastasis through the Src/Akt signaling pathway in human chondrosarcoma cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 156.
Abstract 1583: Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development
Authors: Li Yafang , Xiao Xiangjun , Gorlov Ivan , Han Younghun , Hung Rayjean , Amos Christopher 
Published: August 2019

Abstract
The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43(OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. We further explored the impact of identified genetic interactions on the expression of involved cancer-related genes using the lung eQTL dataset including a total of 409 subjects with both genotyping and gene expression data. In the study between TSPAN8 gene and rs1882898:rs1705235 SNP pair, we identified decreased gene expression in individuals with reduced lung cancer risk which supports the oncogene function of TSPAN8. In the gene expression analysis between SYNE1 and rs10515157:rs1554783 SNP pair, we also identified consistent evidence between gene expression and lung cancer risk. Finally, we conducted gene set enrichment analysis to reveal potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play important roles in lung tumorigenesis. Epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.
Citation Format: Yafang Li, Xiangjun Xiao, Ivan Gorlov, Younghun Han, Rayjean Hung, Christopher Amos. Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1583.
Abstract 1586: ADAM32 is amplified in a wide range of malignancy
Authors: Rajan Aditya , Tonk Vijay , Bhende Kishore , Singh Sharda , Tonk Sahil , Awasthi Sanjay 
Published: August 2019

Abstract
Cytogenetic analysis using karyotyping and fluorescence in-situ hybridization (FISH) has been the method of choice for identifying chromosomal abnormalities in cancer and other diseases. FISH is a powerful tool enabling detection the amplification or deletion of specific genes of interest using specific fluorescent labelled DNA probes. It has high sensitivity and specificity and enables detection of chromosomal abnormalities present in many genetic disorders. Unfortunately, FISH is labor intensive, gives information only regarding chromosomal changes specifically designated by the nucleotide sequence of the probes. Recently, DNA microarray techniques have allowed the simultaneous detection of vast number of chromosomal abnormalities including deletions, amplifications and translocations. These assays are suitable for large scale screening to discovery previously unknown associations of chromosomal lesions with many types of cancer. In present studies, we performed a retrospective analyses on anonymized data from the Constitutional v3 Array from the Texas Tech University Cytogenetics Lab (Children’s Oncology Group reference lab) on 198 sequential patients to determine the frequency of chromosomal aberrations and their disease associations. The patient population included children and adults. The majority of patients had malignancy, but some had pancytopenia or immune deficiency. We found chromosomal rearrangements, amplifications or deletions at 794 loci. The most commonly affected loci were 8p11.21-8p11.22, 15q11.1-15q11.2, 14q11.2, 14q32.33, 9p24 and 9p13. The 8p11.2 locus was amplified in 81 cases and deleted in 17 cases, an amplification/deletion ratio greater than any other locus. At this locus, the KAT6A, ADAM32 and TACC1 genes are known to associate with cancer, while no associations of GPAT4 and TM2D2 have been reported. The ADAM32 gene amplification, previously identified only in breast cancer, was also found in hepatocellular carcinoma, T-cell Lymphoma, acute lymphoblastic leukemia, acute myelogenous leukemia, Wilm’s Tumor, neuroblastoma, rhabdomyosarcoma, fibromatosis, chondroblastoma, enchondroma, and giant cell tumor of the bone. An oncogenic role of ADAM32 should be investigated in a broad spectrum of pediatric and adult malignancy.
Citation Format: Aditya Rajan, Vijay Tonk, Kishore Bhende, Sharda Singh, Sahil Tonk, Sanjay Awasthi. ADAM32 is amplified in a wide range of malignancy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1586.
Abstract 1588: Germline variation in DNA repair genes and risk of Barrett's esophagus and esophageal adenocarcinoma
Authors: Buas Matthew F. , Yan Li , Peng Xuan , Qi Qianya , Chen Jianhong , Thrift Aaron , He Qianchuan , Onstad Lynn , Gharahkhani Puya , MacGregor Stuart , Vaughan Thomas L. , Madeleine Margaret M. 
Published: August 2019

Abstract
Incidence of esophageal adenocarcinoma (EA) has risen substantially in Western countries over recent decades. Established risk factors for EA and its precursor lesion, Barrett’s esophagus (BE), include reflux, obesity, and tobacco smoking. Inherited genetic variation also influences disease risk, although only a limited number of susceptibility loci have been identified. Genomic analyses of EA tumors have revealed a distinctive mutational signature, high mutational burden, and extensive somatic chromosome alterations, features also observed in high-risk BE tissue. To explore whether germline variation in DNA repair-related genes may be associated with altered disease susceptibility, we analyzed data from a recent meta-analysis of genome-wide association studies (GWAS) encompassing 4,112 EA cases, 6,167 BE cases, and 17,159 controls, representing the largest sample size assembled for these conditions. Using a gene-based testing approach (VEGAS2), we assessed 263 DNA repair-related genes and found that variation in NEIL2, a mediator of base excision repair (BER), was significantly associated with risk of BE (P=1.4×10-5, q&lt;0.05). No other gene-level associations with BE or EA survived correction for multiple comparisons. SNP-level analysis of 239 polymorphisms at the NEIL2 locus revealed six variants strongly associated with altered risk of BE (P&lt;5×10-5, q&lt;0.01), with the index SNP classified as an intronic eQTL for NEIL2 in esophageal tissue. Four of these SNPs were also associated with risk of EA (P&lt;0.05), with odds ratios in the same direction and of similar magnitude. Our results provide evidence that germline genetic variation in a DNA glycosylase enzyme (NEIL2) may influence risk of BE/EA, and suggest a potential novel biological role for altered BER in BE/EA pathogenesis.
Citation Format: Matthew F. Buas, Li Yan, Xuan Peng, Qianya Qi, Jianhong Chen, Aaron Thrift, Qianchuan He, Lynn Onstad, Puya Gharahkhani, Stuart MacGregor, Thomas L. Vaughan, Margaret M. Madeleine. Germline variation in DNA repair genes and risk of Barrett's esophagus and esophageal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1588.
Abstract 159: Chemokine receptor expression profiling of lymph node invasive versus lymph node non-invasive melanomas
Authors: Bushhouse David Z. , Hargadon Kristian M. 
Published: August 2019

Abstract
Regional lymph nodes are one of the first sites of melanoma metastasis during tumor progression, and lymph node invasion by tumor cells is a poor prognostic factor in melanoma patients. We have employed models of lymph node invasive and lymph node non-invasive murine melanomas to investigate the potential role of chemokine/chemokine receptor signaling pathways in the regulation of tumor cell trafficking to regional lymph nodes. PCR array analyses identified several differentially expressed chemokine and chemokine receptor genes in the lymph node invasive B16-F1 melanoma versus the lymph node non-invasive D5.1G4 melanoma. Among these differentially expressed genes, Cxcr3, Cxcr6, Cxcr7, Cx3cr1, Cxcl10, and Cx3cl1 were all significantly upregulated at the RNA level in B16-F1 melanoma. We are currently validating these differential gene expression data at the protein level, and these findings will provide key insights into the potential role of these chemokines and chemokine receptors in the metastasis of melanoma cells to regional lymph nodes.
Citation Format: David Z. Bushhouse, Kristian M. Hargadon. Chemokine receptor expression profiling of lymph node invasive versus lymph node non-invasive melanomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 159.
Abstract 1592: Genome-wide meta-analysis of keratinocytic cancers identifies 26 novel risk loci
Authors: Liyanage Upekha E. , Law Matthew H. , Han Xikun , An Jiyuan , Ong Jue-Sheng , Gharahkhani Puya , Iles Mark M. , Neale Rachel E. , Olsen Catherine , Macgregor Stuart , Whiteman David C. 
Published: August 2019

Abstract
Background: Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) (collectively referred to as keratinocytic skin cancers (KC)) are the most common forms of cancer in fair-skinned people. KCs account for the highest expenditure of any cancer type in the Australian healthcare system. Knowledge about the genetic architecture of skin cancer may help elucidate the biology of the disease.
Methods: We conducted a genome-wide meta-analysis of KC, including 28248 cases and 353855 controls from United Kingdom, United States and Australian populations. We performed LD score regression to determine the genetic correlation between KC, BCC, SCC, and melanoma.
Results: We identified 41 independent genome-wide significant SNPs associated with KC risk, 16 of which have not been reported previously. A further 10 loci were implicated using gene-based tests. New loci included common variants in BRCA2 (rare variants increase risk of various cancers) and CTLA4 (immune response; antibodies targeting CTLA-4 are used to treat melanoma). We found a strong genetic correlation between BCC and SCC, 0.93 (95% confidence interval [CI] 0.71 - 1.16). The genetic correlation between melanoma and BCC was 0.66 (95% CI: 0.41 - 0.91). Comparatively lower genetic correlations were identified between melanoma and SCC 0.43 (95% CI: 0.12 - 0.74), and melanoma and KC 0.52 (95% CI: 0.27 - 0.76).
Conclusions: We have identified novel genetic loci associated with KC risk which will lead to a greater understanding of the biology of KC. Future work will leverage the genetic correlations between BCC, SCC and melanoma to further advance our understanding of these cancers.
Citation Format: Upekha E. Liyanage, Matthew H. Law, Xikun Han, Jiyuan An, Jue-Sheng Ong, Puya Gharahkhani, Mark M. Iles, Rachel E. Neale, Catherine Olsen, Stuart Macgregor, David C. Whiteman. Genome-wide meta-analysis of keratinocytic cancers identifies 26 novel risk loci [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1592.
Abstract 1595: Functional genomic analysis of 18q21.1 locus identifies potential functional variants and genes for colorectal cancer
Authors: Wang Jifeng , Guo Xingyi , Qu Shimian , Bauer Joshua A. , Long Jirong , Zheng Wei , Cai Qiuyin 
Published: August 2019

Abstract
Colorectal cancer (CRC) is one of the most commonly diagnosed cancers in the world. Genome-wide association studies have identified approximately 50 genetic risk loci for CRC. We have previously identified SNP rs7229639, located in the second intronic region of the SMAD7 gene at locus 18q21.1, in relation to CRC risk in Asians. In this study, we performed functional genomic analysis to identify potential functional variants and target genes for this association. Functional annotation analysis using epigenetic data from ENCODE and Roadmap projects showed functional evidence of promoter and/or enhancer activities for four highly correlated potential functional SNPs, including rs7229639, rs77544449, rs112540150 and rs57668004. Using in vitro luciferase reporter assays in colon cancer HCT116 and PKO cells, we showed that the risk alleles of rs7229639 and rs77544449 increase promoter or enhancer activities, compared to reference alleles. The risk alleles of both SNPs also affect the ability of interacting with nuclear proteins in the electrophoretic mobility shift assays, compared to reference alleles. To identify candidate target genes for this risk locus, we performed cis-expression quantitative trait loci (eQTL) analysis using transcriptome data from the Genotype-Tissue Expression (GTEx) project, The Cancer Genome Atlas (TCGA) and Colonmics. We identified putative target gene LIPG, located 500 kb downstream of rs7229639, in all three datasets. No associations were observed for SMAD7, or eight other genes in the region, via eQTL analysis. To investigate the biological functions of LIPG gene in colorectal cancer, we knock-downed LIPG gene expression using siRNA in HCT116 and PKO cells, which resulted in a significant decrease in cell proliferation, colony formation, migration and invasion in both HCT116 and PKO cells. These results suggest that LIPG gene plays a significant role in colorectal tumorigenesis via disruption of cell behaviors. Taken together, results from our study suggest that the association between the rs7229639/18q21.1 locus and CRC risk may be mediated through SNPs that regulate expression of the LIPG gene.
Citation Format: Jifeng Wang, Xingyi Guo, Shimian Qu, Joshua A. Bauer, Jirong Long, Wei Zheng, Qiuyin Cai. Functional genomic analysis of 18q21.1 locus identifies potential functional variants and genes for colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1595.
Abstract 1596: Genome-wide gene-environmental interaction and random survival forest analyses: Insulin resistance and breast cancer risk
Authors: Jung Su Yon , Yu Herbert , Pellegrini Matteo , Papp Jeanette , Sobel Eric , Zhang Zuo-Feng 
Published: August 2019

Abstract
Purpose: Obesity–insulin connections have been considered potential risk factors for postmenopausal breast cancer, and the association between insulin resistance (IR) genotypes and phenotypes can be modified by obesity-lifestyle factors, affecting breast cancer risk. We explored the role of IR in those pathways at the genome-wide level. With identified IR genetic factors and selected lifestyles, we further generated risk profiles for breast cancer risk.
Methods: Using large-scale cohort data from postmenopausal women in the Women’s Health Initiative Database for Genotypes and Phenotypes Study, our previous genome-wide association gene–behavior interaction study identified 58 loci for associations with IR phenotypes (homeostatic model assessment–IR, hyperglycemia, and hyperinsulinemia). We evaluated those single-nucleotide polymorphisms (SNPs) and additional 31 lifestyles in relation to breast cancer risk by conducting a two-stage multimodal random survival forest analysis.
Results: We identified the most predictive genetic and lifestyle variables in overall and subgroup analyses (stratified by body mass index [BMI], exercise, and dietary fat intake). Two SNPs (LINC00460 rs17254590 and MKLN1 rs117911989), endogenous and exogenous factors related to lifetime cumulative exposure to estrogen, BMI, and dietary alcohol intake were the most common influential factors across the analyses. Individual SNPs did not have significant associations with breast cancer, but the combined SNPs and lifestyles synergistically increased the risk of breast cancer in a dose-dependent manner. In subgroup analysis, we further stratified women by the two strongest variables (durations of oral contraceptive [OC] and opposed estrogen use). Shorter-duration OC and ever-opposed estrogen users with both risks of genotypes and lifestyles had greater risk (2.5 times and 6.3 times, respectively) than their counterparts without risks in both. This indicates the combined effect of SNPs and lifestyles and the joint effect with OC use and opposed estrogen on breast cancer risk.
Conclusions: Our findings may contribute to more accurate prediction of breast cancer and suggest intervention strategies for those women with genetic risk to reduce their breast cancer risk.
Citation Format: Su Yon Jung, Herbert Yu, Matteo Pellegrini, Jeanette Papp, Eric Sobel, Zuo-Feng Zhang. Genome-wide gene-environmental interaction and random survival forest analyses: Insulin resistance and breast cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1596.
Abstract 1640: Deep learning classification of neuro-oncology medical documents
Authors: Wells Michael , Sabedot Thais , Malta Tathiane , Snyder James , Poisson Laila , Noushmehr Houtan 
Published: August 2019

Abstract
Introduction
Precision medicine and big data for cancer discovery requires well curated indexed critical health care data, however to date limited resources exist that successfully parse out unstructured clinical data in neuro-oncology. Current practice relies on time consuming manual extraction by researchers or clinicians resulting in data inconsistency and limitation in data set volume. Rule-based natural language processing algorithms could be used for simple consistent text, but medical documents are created longitudinally by multiple people across long periods of time resulting in inconsistencies and semantic heterogeneity that render rule-based techniques insufficient.
Methods
We applied a deep learning text classification method to multiple clinical document categories including clinical pathology reports and a text based clinical database spanning 17 years of clinical narratives with approximately 4000 unique cases. For this study we identified clinically relevant molecular criteria for glioma outlined in the WHO 2016 CNS classification of tumors including IDH mutation, MGMT methylation, and 1p19q co-deletion status. Using a convolutional neural network with two densely connected layers of 30 rectified linear nodes we were able to classify patients into their respected molecular cohort with an accuracy of 98%.
Conclusion
Parsing of unstructured text based clinical narratives and pathology reports using convolutional neural networks is a promising method to extract heterogeneous molecular data in neuro-oncology for large scale data analysis.
Citation Format: Michael Wells, Thais Sabedot, Tathiane Malta, James Snyder, Laila Poisson, Houtan Noushmehr. Deep learning classification of neuro-oncology medical documents [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1640.