bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 510: Selective and potent CDK8 inhibitors enhance NK cell activity and promote tumor surveillance
Authors: Hofmann Marco H. , Mani Rajeswaran , Engelhardt Harald , Impagnatiello Maria A. , Carotta Sebastian , Kerenyi Marc A. , Lorenzo-Herrero Seila , Boettcher Jark , Scharn Dirk , Arnhof Heribert , Zoephel Andreas , Schnitzer Renate , Gerstberger Thomas , Rajgolikar Girish , Goswami Swagata , Vasu Sumithira , Ettmayer Peter , Gonzalez Segundo R. , Pearson Mark , McConnell Darryl B. , Kraut Norbert , Muthusamy Natarajan , Moll Juergen 
Published: August 2019

Abstract
Natural killer (NK) cells play a pivotal role in controlling cancer. Activation of NK cells is tightly regulated by multiple extracellular receptors and internal signaling nodes. The production of perforin and granzyme B, key NK cytolytic molecules, is regulated by the suppressive signaling intermediate Cyclin Dependent Kinase 8 (CDK8) through phosphorylation and inhibition of STAT1S727.
We identified highly potent and selective CDK8 inhibitors, including BI-9811 and BI-1347, that we previously reported as valuable probe compounds (Hofmann M.H. et al., AACR Annual Meeting 2017, Abstract 4630). CDK8 inhibition promoted activation of NK cells but had no direct cytotoxic activity on the majority of cancer cell lines tested. Single agent treatment with the CDK8 inhibitor BI-1347 increased the survival of mice bearing melanoma and breast cancer allografts. In addition to this, treatment with BI-1347 resulted in enhanced NK-cell mediated lysis of myeloid leukaemia and lymphoma cells.
We evaluated whether increased efficacy could be observed upon activation of both the innate and the adaptive immune system by combining the CDK8 inhibitor with a SMAC mimetic. SMAC mimetic treatment enhanced T-cell activity and increased NK cell number in the murine EMT6 breast cancer model. Increased survival upon combination treatment was dependent on a pulsatile schedule of the CDK8 inhibitor BI-1347, which permitted activation of NK cells but avoided a hypo-responsive steady state. These results demonstrate that CDK8 inhibitors could be used either as a single agent in hematological cancers or be combined with modulators of the adaptive immune system to inhibit the growth of solid tumors.
Citation Format: Marco H. Hofmann, Rajeswaran Mani, Harald Engelhardt, Maria A. Impagnatiello, Sebastian Carotta, Marc A. Kerenyi, Seila Lorenzo-Herrero, Jark Boettcher, Dirk Scharn, Heribert Arnhof, Andreas Zoephel, Renate Schnitzer, Thomas Gerstberger, Girish Rajgolikar, Swagata Goswami, Sumithira Vasu, Peter Ettmayer, Segundo R. Gonzalez, Mark Pearson, Darryl B. McConnell, Norbert Kraut, Natarajan Muthusamy, Juergen Moll. Selective and potent CDK8 inhibitors enhance NK cell activity and promote tumor surveillance [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 510.
Abstract 5102: Deep learning method for the classification of CNV based on the next generation target sequencing
Authors: Lang Jidong , Tian Geng 
Published: August 2019

Abstract
Background: Copy number variations (CNVs) are of great importance to many cancers. Recently, the next-generation sequencing has made detecting CNV by sequencing possible. Traditional CNV determination methods involve expensive experiments, which is costly. Recently, several algorithms were proposed the detection of CNV, but none of them could utilize only the coverage information at a specific gene to make the determination of CNV at the gene.
Methods: We collected 1132 samples with 51 mesenchymal-epithelial transition factor (MET) CNV samples and 1081 samples with no CNVs. We split the exons of MET to multiple 50-bp windows with the stride of 40-bp. At each window the supporting reads were counted, and reads numbers at each exons were piled up, generating a matrix. The training set containing 38 CNV-positive matrices and 38 CNV-negative matrices were extracted from all the matrices, leaving the others as the test set. The deep learning network, convolutional neural network (CNN) were applied to distinguish between the CNV-positive matrices and the CNV-negative matrices. For comparison, logistic regression model was also applied for the classification task.
Results: The training set were split into 5 pieces containing 15 samples each and 5-fold cross validation were run for the CNN or the logistic regression model. After running 10 5-fold cross validation, we got an accuracy of 85.73 ± 9.24% for CNN and the average accuracy of 87.07 ± 8.99% for the logistic regression model. We chose 3 best models in both CNN and logistic regression models for the determination of the test set. The CNN models gained the accuracy of 71.84 ± 2.19% while the logistic regression models gained the accuracy of 69.70 ± 2.56%. Furthermore, the Area Under Curve (AUC) of the CNN models were 0.6335 ± 0.0124, higher than that of the logistic regression models which was 0.5666 ± 0.0115.
Conclusions: We proposed a method to determine the samples with CNV by using the convolutional neural network with only the coverage information within the specific region. It provides the possibility of CNV detection for cancer patients using only the next generation sequencing data.
Citation Format: Jidong Lang, Geng Tian. Deep learning method for the classification of CNV based on the next generation target sequencing [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 5102.
Abstract 5118: TIDE-E: an online evaluator of tumor immune-suppressive function of gene sets
Authors: Fu Jingxin , Zhang Wubing , Jiang Peng , Liu Xiaole S. 
Published: August 2019

Abstract
Recent immunotherapy studies have generated a diverse collection of datasets, covering different aspects of cancer immune evasion. However, to the best of our knowledge, there are no public tools that can systematically rank genes regarding their function on tumor immune evasion and comprehensively evaluate biomarkers across multiple clinical cohorts. Therefore, we presented the TIDE-E (evaluator) website for users to evaluate their gene sets across a large panel of data cohorts (http://tide.dfci.harvard.edu). The website integrated two categories of data resources, human clinical datasets from public immunotherapy studies, TCGA, PRECOG, and METABRIC databases, as well as functional genomics datasets from CRISPR screens in preclinical models. For a user-defined gene set, the web application can test its performance as immunotherapy response biomarkers across multiple clinical studies, and rank the gene members according to their relevance in promoting tumor immune evasion.
Citation Format: Jingxin Fu, Wubing Zhang, Peng Jiang, Xiaole S. Liu. TIDE-E: an online evaluator of tumor immune-suppressive function of gene sets [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 5118.
Abstract 5131: Breast cancer with insertion or deletion exhibits the immunogenic phenotype
Authors: Yuan Peng , Wang Xue , Zhang Yuzi , Zhao Jing , Cai Shangli , Yin Yongmei 
Published: August 2019

Abstract
Background: Although immunotherapy has been proven to be effective in a wide range of malignant tumors, breast cancer remains to be one of poorly immunogenic tumors and only a small subset of patients with breast cancer achieved benefits from immunotherapy. Therefore, identification of better predictive biomarkers to guide patient selection is highly desirable. It has been reported that insertion or deletion (indels) could create a novel open reading frame and generate more neoantigen which may mediate response to immunotherpay. However, the pattern of indels mutations in breast cancer is still unclear.
Methods: Whole-exome sequencing data, RNA-Seq data and clinical data of 1096 breast tumors from The Cancer Genome Altas (TCGA) database were used to analyze the pattern of indels in breast cancer. Next generation sequencing (NGS) data of 81 breast tumors from clinical dataset were also used to validate the indels mutation pattern in different molecular subtype.
Results: 81.7% (895/1096) of breast tumors in TCGA dataset harbored at least one indels mutation. Hormonal receptor (HR) negative tumors were associated with higher burden of indels mutations than HR positive tumors in both TCGA dataset (P = 0.05) and NGS-clinical dataset (P = 0.003). Indels were significantly correlated with higher TMB and neoantigen level in TCGA cohort (P &lt; 0.0001). In addition, tumors with at least eight indels mutations (cut off as 80% percentile) exhibited even higher TMB (P &lt; 0.0001) and neoantigen (P &lt; 0.0001) level. Among 45 immune related genes, the mRNA expression of 22 genes were significantly higher in tumors with indels mutations, such as LAG3, IL18, IL6, CTLA4 and PDCD1. Indels group also showed a high levels of genome instability in terms of HRD-LOH (P = 0.004), NtAI (P = 0.000), wGII (P = 0.001) and LST (P =0.014).
Conclusions: Breast tumors with indels mutations exhibited the immunogenic phenotype. Further studies are warranted to investigate the potential value of indels as a predictive biomarker for immunotherapy in breast cancer.
Note: This abstract was not presented at the meeting.
Citation Format: Peng Yuan, Xue Wang, Yuzi Zhang, Jing Zhao, Shangli Cai, Yongmei Yin. Breast cancer with insertion or deletion exhibits the immunogenic phenotype [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 5131.
Abstract 5135: Genome-wide CRISPR-based screening reveals ABCG2 as a novel drug resistance gene in pancreatic cancer
Authors: Ramaker Ryne C. , Hardigan Andrew A. , Gordon Emily R. , Myers Richard M. , Cooper Sara J. 
Published: August 2019

Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most deadly cancers and incidence is increasing due to the increase in risk factors such as diabetes and obesity. One reason for the high mortality rate associated with this cancer is the high rate of resistance to commonly used chemotherapies. Our previous work showed a link between patient survival and expression of drug resistance genes, thus we undertook genome-wide CRISPR knockout and activation screens to identify genes conferring resistance to cytotoxic chemotherapies in two pancreatic cancer cell lines. Our screen revealed hundreds of genes with potential roles in drug resistance, many of which have expression levels that correlate with patient survival. We have validated our top candidates by stably expressing individual guide RNAs in each of three pancreatic cell lines, Panc-1, BxPC-3 and MiaPaCa-2 and screening for viability following treatment with three chemotherapeutic agents, oxaliplatin, gemcitabine, and irinotecan. ABCG2, an ABC transporter, was revealed as our top hit, conferring resistance to multiple drugs in multiple cell lines. Our results would suggest that repression of ABCG2 might improve sensitivity to cytotoxic chemotherapies. We test this hypothesis using an ABCG2 inhibitor and demonstrate the effect of this inhibitor on cell viability, drug sensitivity and transcriptomic profiles in the context of cell lines with variable ABCG2 expression.
Note: This abstract was not presented at the meeting.
Citation Format: Ryne C. Ramaker, Andrew A. Hardigan, Emily R. Gordon, Richard M. Myers, Sara J. Cooper. Genome-wide CRISPR-based screening reveals ABCG2 as a novel drug resistance gene in pancreatic 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 5135.
Abstract 5136: Adapting long read sequencing technologies for targeted and single cell applications
Authors: Iyer Shruti , Goodwin Sara , McCombie W. Richard 
Published: August 2019

Abstract
Structural variations (SV), a hallmark of genomic instability in cancer, include insertions, deletions, duplications, inversions, or translocations that can either activate oncogenes or inactivate tumor suppressor genes. These variants contribute to the complexity of the cancer genome but have not been successfully resolved yet. While short-read sequencing has aided cancer genomics, it has performed poorly in SV detection, with false positive and false negative rates of 50% or more. Long-read sequencing generates reads that are &gt;10 kb long and has helped identify thousands of genomic features pertinent to cancer that were previously missed by short-read sequencing. Long reads can span SV with a single continuous read, giving a clearer idea of the variation, its position, and size. Currently, long-read sequencing methods are greatly limited by the DNA preparation step, with fragment lengths and yield often compromised by standard extraction methods. The potential to generate reads at the megabase level relies greatly on library preps using large amounts (several μg) of DNA input, which prevents its application to samples like patient tumors that are often limited in DNA. Our overarching goal is to develop a targeted approach that generates large contiguous reads from moderate to low input DNA masses. To this end, we use different extraction, amplification, fragmentation, and enrichment strategies to efficiently target and resolve complex regions of the genome that are often associated with disease conditions. Development of a targeted long-read sequencing strategy using low DNA input would give us the potential to explore the landscape of genetic variation across several individuals and heterogeneous cell populations. We are currently employing and adapting CRISPR-based targeting techniques to enrich for specific regions of the genome from intact cells and/or high-molecular-weight DNA.
Citation Format: Shruti Iyer, Sara Goodwin, W. Richard McCombie. Adapting long read sequencing technologies for targeted and single cell applications [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 5136.
Abstract 5138: Inhibition of kPNB1 and NUPR1 binding increase the anti-cancer drug sensitivity
Authors: Park Chan Hee , Ham Seung Wook , Shin HyeKyoung , Oh Kyung Soo 
Published: August 2019

Abstract
Karyopherin beta 1 (KPNB1, known as importin beta 1) is carrier protein, it is known as transporter of protein from cytoplasm to nucleus through nuclear pore complexes (NPCs) using KPNAs as an adapters. The nuclear protein-1 (NUPR1, known as p8/Com-1) is identified as a transcription factor and it is showed multifunctional mechanisms related to cellular stress response such as serum-starvation, oxidative stress and drug stimulation. In this study, we investigated protein-protein interaction between NUPR1 and KPNB1, it might be a new target for cancer therapy.For the evaluation of binding affinity between protein and inhibition effect by compound 1, we processed the single molecule binding assay. Cytotoxicity of combination treatment with doxorubicin and compound 1 were validated several cancer cell lines such as MDA-MB-231, PC-3, SK-OV-3, and SiHa. Gene expression patterns were analyzed RNA-Seq and validated with qRT-PCR and western-blotting. KPNB1 bind to NUPR1 as a high affinity compare to KPNB1 single treatment assay and there was no difference according to concentration of NUPR1. KPNB1 and NUPR1 protein-protein interaction was inhibited by compound 1 according to concentration of compound 1 showed 71%, 44%, and 31% of inhibition rate with 50nM, 10nM, 2.5nM of compound 1, respectively. In doxorubicin single treatment, NUPR1 move to nucleus more than 90% of cells compare to non-treated MDA-MB-231 cells. Otherwise, NUPR1 was exist both nucleus and cytoplasm more than 90% cells, which is indicate that translocation of NUPR1 to the nucleus was blocked by compound 1 treatment. And combination treatment showed synergistic effect of cytotoxicity in various cancer cells such as such as MDA-MB-231, SiHa, PC-3, and SK-OV-3 (1.4 ~ 6 fold). Additionally, NUPR1 related genes were showed change of gene expression in compound 1 combination compared to doxorubicin single treatment. In these results suggest that translocation mechanism of NUPR1 into nucleus bind to KPNB1 and this binding was inhibited by compound 1 which is new candidate drug combination method for cancer therapy.
Citation Format: Chan Hee Park, Seung Wook Ham, HyeKyoung Shin, Kyung Soo Oh. Inhibition of kPNB1 and NUPR1 binding increase the anti-cancer drug sensitivity [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 5138.
Abstract 5141: T-cell receptor repertoire analysis by next-generation sequencing peripheral blood mononuclear cells from multiple myeloma or smoldering multiple myeloma patients
Authors: Zhang Yong , Petrovskaya Svetlana , Scott Emma C. , Santana-Quintero Luis , Ghazanchyan Tigran , Rosenburg Amy , Rao V. Ashutosh , Blumenthal Gideon M. , Theoret Marc , Pazdur Richard , Beaver Julia A. , Kazandjian Dickran 
Published: August 2019

Abstract
Multiple myeloma (MM) is a hematological malignancy mostly assessed by bone marrow involvement, so it is attractive to develop a method using peripheral blood. We hypothesized that peripheral blood mononuclear cells (PBMCs) may replace tedious and invasive bone marrow biopsies as a biomarker. In this study, we aimed to investigate if T-cell receptor (TCR) repertoire has clinical significance in MM or Smoldering MM (SMM) diagnosis or prognosis. Using baseline genomic DNA (PBMC) from 24 patients with SMM and 31 patients with MM, we performed next-generation sequencing on the Illumina NextSeq 500 platform by immunoSEQ TCRB Kits from Adaptive Biotechnology to quantitatively assay the complementarity determining region 3 (CDR3) of human T-cell receptor β (TCRβ) gene. To evaluate T-cell diversity and clonality, we performed pipeline analysis by ImmunoAnalyzer from Adaptive Technology, and downloaded sequencing data with manual analysis by JMP13 software. Compared to TCRB data from 280 normal control (Age &gt; 40) PBMCs (Nat Genet. 2017, 49(5):659-665), we found less TCR templates from both MM and SMM baseline based on size of TCRB repertoire, and less TCR rearrangements or unique clonotypes based on structure of TCRB repertoires. Only MM baseline showed higher maximum clonotype frequency. No difference of T-cell clonality was found from MM and SMM. Furthermore, we performed the same sequencing on 18 SMM patients at different treatment time points including chemotherapy after cycle 8, 20, and 32. Our results showed patient samples after cycle 8 had less TCR templates and TCR rearrangements compared to those from the other three time points although no significant difference were found in maximum clonotype frequency or T-cell clonality. TCR overlap analysis will be further performed to track potential clonotype changes. Thus, we identified TCR repertoire analysis may have potential clinical significance as biomarker assay for MM and SMM patients.
Citation Format: Yong Zhang, Svetlana Petrovskaya, Emma C. Scott, Luis Santana-Quintero, Tigran Ghazanchyan, Amy Rosenburg, V. Ashutosh Rao, Gideon M. Blumenthal, Marc Theoret, Richard Pazdur, Julia A. Beaver, Dickran Kazandjian. T-cell receptor repertoire analysis by next-generation sequencing peripheral blood mononuclear cells from multiple myeloma or smoldering multiple myeloma patients [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 5141.
Abstract 5146: ATP-binding cassette transporter, ABCG2, activation is responsible for chemo-resistant, SIK3 low expressed ovarian cancer
Authors: Hsu Keng-Fu , Liang Yu-Ling , Wu Chin-Han , Shih Neng-Yao 
Published: August 2019

Abstract
Background: Epithelial ovarian cancer (EOC) has a high tumor-associated mortality rate among the gynecological cancers because of chemo-resistant development.
Materials and Method: The human EOC cell lines, SKOV3, OVRCA4, were obtained from the American Type Culture Collection (ATCC). For determine ATP-binding cassette transporters and SIK3 expression, Western blot and Quantitative real-time polymerase chain reaction (qRT-PCR) were used. We used a lentiviral small-hairpin RNA (shRNA) system to knock down SIK3 in the ovarian cancer cell lines. Microarray data derived from SKOV3, OVRCA4 cells expressing sh-luc, sh-SIK3 (01), and sh-SIK3 (63) were analyzed by MetaCore and Ingenuity Pathways Analysis (IPA). Top 10 up-and down-regulated genes and other metastasis-related genes and 5 most highly enriched networks were identified. For determining cell viability when cells treated with cisplatin and Taxol, WST-1 assay was used. Immunohistochemistry and quantification of ABCG2 and SIK3 were performed in EOC tissues. Statistical analysis of OS and PFS were performed using SPSS statistical software (Version 22.0; IBM Corp, Armonk, NY). Survival curves were generated using the Kaplan-Meier method, and differences in survival were assessed using the log-rank test.
Results: Knockdown SIK3 expression upregulates ABCG2 expression, activity as well as resistance to chemotherapeutic agents. The ABCG2 and SIK3 expression levels in 204 EOC patient were mutually reversed. In all stages of the disease, high expression of SIK3 (SIK3-H) was associated with a significant better OS, PFS, compared with low expression of SIK3 (SIK3-L) (127.0 vs 46.0 months, 66.0 months vs 26.0 months respectively). Patients with SIK3-L and ABCG2-H carried the worst prognosis.
Conclusion: (1) High expression of SIK3 indicates a better prognosis in primary ovarian cancer and serous type disease, especially in advanced serous disease. (2) Ovarian cancer patients with SIK3-L and ABCG2-H expression carried the worst prognosis due to chemoresistance
Citation Format: Keng-Fu Hsu, Yu-Ling Liang, Chin-Han Wu, Neng-Yao Shih. ATP-binding cassette transporter, ABCG2, activation is responsible for chemo-resistant, SIK3 low expressed ovarian 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 5146.