bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2399: LAG-3/PD-L1 mAb2 can overcome PD-L1-mediated compensatory upregulation of LAG-3 induced by single-agent checkpoint blockade
Authors: Faroudi Mustapha , Kraman Matthew , Fosh Natalie , Reader Claire , Gliddon Daniel , Seal Claire , Lucas Christa , Koers Alexander , Wydro Mateusz , Morrow Michelle , Brewis Neil 
Published: August 2019

Abstract
FS118, currently tested in Phase I clinical trial in patients with advanced malignancies (NCT03440437), is a first-in-class bispecific antagonistic antibody (known as mAb2) targeting LAG-3 (Lymphocyte-Activation Gene 3) and PD-L1 (Programmed Death-Ligand 1), two immune checkpoint molecules that promote tumour escape from immune surveillance. Resistance to anti-PD-1 treatment is associated with upregulation of other checkpoint inhibitor receptors such as LAG-3. Dual targeting in immune checkpoint blockade (ICB) using bispecific monoclonal antibodies could potentially overcome this resistance, further increase the clinical benefit of ICB therapy and prevent relapse or resistance after immunotherapy. In a syngeneic model we used a surrogate mAb2 of FS118 (blocking both mPD-L1 and mLAG-3 binding to their receptors) to determine the effect of dual checkpoint blockade on tumour growth and to elucidate the modulation of the underlying immune mechanisms following treatment with the mAb2. Dual blockade of LAG-3 and PD-L1 with the surrogate mAb2 in the MC38 tumour-bearing mice model resulted in an increased anti-tumour activity comparable to a combination of the single agents targeting LAG-3 and PD-L1. Moreover, the mAb2 and single agent combination resulted in distinct modulations of LAG-3 and PD-L1 cell surface expression within the spleen and tumour microenvironment (TME). While both the mAb2 and combination therapy significantly reduced the number of free PD-L1 binding sites on CD4+ and CD8+ T cells in spleen and TME, total LAG-3 cell surface expression increased following treatment with the combination, whereas it reduced with mAb2 treatment. In addition, analysis of serum samples collected at various timepoints confirmed evidence of drug target engagement with increasing levels of both soluble LAG-3 (sLAG-3) and soluble PD-L1 (sPD-L1) in the mAb2 treated animals. Modulation of sPD-L1 levels in the serum of treated animals was also observed in cynomolgus monkeys treated with FS118. These data provide a strong rationale for investigating both cell surface and soluble LAG-3 and PD-L1 levels as potential pharmacodynamic biomarkers in further clinical development.
Citation Format: Mustapha Faroudi, Matthew Kraman, Natalie Fosh, Claire Reader, Daniel Gliddon, Claire Seal, Christa Lucas, Alexander Koers, Mateusz Wydro, Michelle Morrow, Neil Brewis. LAG-3/PD-L1 mAb2 can overcome PD-L1-mediated compensatory upregulation of LAG-3 induced by single-agent checkpoint blockade [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 2399.
Abstract 24: Novel STAT3 & HDAC inhibitors that selectively target triple-negative breast cancer cell
Authors: Wu Bocheng 
Published: August 2019

Abstract
Signal transducer and activator of transcription 3 (STAT3) is an oncogenetic transcriptional factor which can modulate cancer cells apoptosis. Stimulation of cancer cells by cytokines such as IL-6, INF-a, etc., can induce phosphorylation of STAT3, resulting in the translocation of p-STAT3 into the nucleus where it facilitates the expression of anti-apoptosis genes. This p-STAT3 anti-apoptotic activity is one drug resistance mechanism developed by cancer cells against chemotherapies including histone deacetylase inhibitors (HDACi). Pyrimethamine has been reported to inhibit STAT3 phosphorylation, mRNA transcriptional level, and STAT3-dependent cell viabilities. In this presentation, we disclosed novel pyrimethamine-based bifunctional STAT3-HDAC inhibitors as potential therapeutic agents for p-STAT3-dependent cancers. We will describe the design, synthesis and biological activities of STAT3-HDAC inhibitors. We will show that these bifunctional agents inhibit HDAC deacetylase activity and STAT3 phosphorylation. A subset of these compounds is more cytotoxic to MDA-MB-231, a triple-negative breast cancer cell line that is highly dependent on STAT3.
Citation Format: Bocheng Wu. Novel STAT3 & HDAC inhibitors that selectively target triple-negative breast cancer cell [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 24.
Abstract 240: Therapeutic targeting of protein kinase ck2 in mycn-driven neuroblastoma
Authors: Lian Haiwei , Shen Ning , Zhou Yun , Li Dun , Feng Hui 
Published: August 2019

Abstract
Amplification of the MYCN oncogene occurs in about 30-40% of advanced neuroblastoma cases and is the most reliable predictor of poor prognosis. Protein kinase CK2 (casein kinase II) is a highly conserved serine/threonine kinase that can be effectively inhibited by small molecules. In fact, CX-4945, a potent, specific, ATP-competitive CK2 inhibitor, is currently tested in clinical trials to treat multiple cancers. However, the role of CK2 in MYCN-driven neuroblastoma remains unknown. To determine the relevance of CK2 in MYCN-driven neuroblastoma pathogenesis, we analyzed published microarray data and compared the expression of the CK2 subunits in primary neuroblastoma patients samples. We found that both CK2α and CK2α’ are upregulated in neuroblastoma patients samples with MYCN amplification, compared to the ones without MYCN amplification. To determine the effect of CK2 inhibition on neuroblastoma cells, we treated a panel of human neuroblastoma cell lines with the CK2 inhibitor CX-4945 and short hairpin RNA specifically targeting CK2α. CK2 inhibitor CX-4945 suppressed human neuroblastoma cell growth, mainly through inducing apoptosis, especially in the MYCN-amplified cells. More over, CK2α knockdown also induced cell apoptosis. In-vitro assay indicated that CK2 inhibition through either genetic or pharmacological approaches effectively reduced cell growth of human neuroblastoma cells primarily through induction of apoptosis. 14 days in-vivo treatment, CX-4945 significantly decreased tumor growth in mouse xenografts by subcutaneously implanting human KELLY neuroblastoma cells, but didn’t affect their body weight. These studies characterize the role of CK2 in neuroblastoma development, and provide valuable information about the relevance of CK2 as a target in MYCN-driven neuroblastoma.
Note: This abstract was not presented at the meeting.
Citation Format: Haiwei Lian, Ning Shen, Yun Zhou, Dun Li, Hui Feng. Therapeutic targeting of protein kinase ck2 in mycn-driven neuroblastoma [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 240.
Abstract 2409: Predictive accuracy of Cox proportional hazards cure models with application in cancer studies
Authors: Han Xiaoxia , Zhang Yilong , Shao Yongzhao 
Published: August 2019

Abstract
With recent development in cancer screening, diagnosis and treatment, many early-stage cancer patients will never experience recurrence, metastasis or death due to their primary cancer, whom can be considered as clinically cured. In the era of precision medicine, it is of interest to develop predictive models for cure status as well as for survival among uncured patients. The area under the ROC curve (AUC) is commonly used for assessing discriminative accuracy for dichotomous outcome (cured/uncured). Yet the conventional AUC cannot be directly used here due to unobserved cured status. In this study, we extend the conventional AUC to Cox proportional hazards (PH) cure models for evaluating prognostic utility in the presence of latent cured patients. We develop consistent and asymptotically normal estimates with explicit formulas for sensitivity, specificity and AUC. Furthermore, we reviewed the prognostic accuracy estimators for survival time among uncured patients for Cox PH cure models. Numerical studies show that our proposed estimators perform well for finite sample size. A melanoma data is used to illustrate the utility of our proposed prognostic metrics. We also have developed an R package called evacure to efficiently compute these estimates and their confidence intervals.
Citation Format: Xiaoxia Han, Yilong Zhang, Yongzhao Shao. Predictive accuracy of Cox proportional hazards cure models with application in cancer studies [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 2409.
Abstract 2412: Development of a gene signature to predict positive or negative sentinel nodes as a prognostic marker in melanoma
Authors: Majeske Audrey J. , Geddes Timothy J. , Keidan Richard , Wilson George D. 
Published: August 2019

Abstract
In recent years, sentinel lymph node (SLN) biopsy has been adopted as a less invasive technique to assess the prognostic outcome of melanoma, whereby draining the key lymph nodes for presence of a tumor decreases unnecessary lymph node dissections and reduces the risk of developing lymphedema. However, this technique only has therapeutic value in patients with SLN-positive tumor nodes, which only represents about half of the population diagnosed with melanoma. In a pilot study, we assessed the predictive efficacy of using a commercialized multi-biomarker next-generation sequencing (NGS) assay (Illumina® Comprehensive Cancer Panel) containing selected genes which have been shown to have a prognostic impact in melanoma progression, to determine whether these can identify primary tumors which do not require SLN biopsy. We used laser capture microdissection to capture pathologist-identified areas of tumor from four groups of samples 1) skin lesions from SLN-positive patients, 2) skin lesions from SLN-negative patients, 3) node samples from SLN-positive patients and node samples from SLN-negative patients; some cases of skin lesions and nodes were matched for the same patient. Sequencing identified 14 genes containing variants in &gt;70% of the positive node samples, which were absent in samples with negative nodes. This included EGFR, PDGFR, ATM, PIK3CA, TP53 and ERBB4. Of note, variants in ERBB4 is of interest as it has been shown in the past to be a potential molecular target in the treatment of melanoma. We are currently validating these preliminary findings in a larger cohort of patients (n=31) and will report on the NGS findings of this study and the efficacy of using genetic biomarkers in skin biopsy samples as a potential prognostic marker for early stage melanoma patients who may not require SLN biopsy.
Citation Format: Audrey J. Majeske, Timothy J. Geddes, Richard Keidan, George D. Wilson. Development of a gene signature to predict positive or negative sentinel nodes as a prognostic marker in melanoma [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 2412.
Abstract 2420: The development of novel detection system for circulating tumor DNA using DNA chip system
Authors: Nakamura Noriaki , Okamura Hiroshi , Yamano Hirofumi , Ito Hiromichi , Zembutsu Hitoshi 
Published: August 2019

Abstract
Gene panels covering hundreds of mutation hotspots for detection of cell-free DNA (cfDNA) have been developed for the establishment of clinically practical circulating tumor (ctDNA) detection system. Although amplicon-based or capture-based genomic profiling of genes commonly mutated in cancer using next-generation sequencing (NGS) system have been developed, they are not sufficiently sensitive nor accurate to be used for clinical diagnosis in hospital. As a result of preliminary study using 87 advanced pancreatic cancer (stage lll/lV), we observed that one or more KRAS mutation(s) could be detected in 60.9% of patients with advanced pancreatic cancer by using the amplicon-based deep sequencing system. To develop more sensitive and accurate ctDNA detection system, we optimized conditions of our DNA chip system. We firstly used 100 synthetic DNA samples, whose KRAS mutant allele frequencies were from 0.1% to 10.0%, and investigated the quantitativity of our DNA chip system. We amplified target regions by PCR to obtain 2,000 copies of synthesized DNA. The PCR product was hybridized with the probe on the DNA chip. The fluorescence ratio (mutant allele fluorescence intensity / total fluorescence intensity) of 100 synthetic DNA samples were clearly distinguished to that of negative control by using the DNA chip system. We defined an appropriate cut-off values of small quantities (0.1%) of mutations. Furthermore, to confirm the accuracy and reliability of this method, we verified our DNA chip system using 15 plasma cfDNA samples from patients with mutant KRAS (0.1~10.0%) and 15 samples from patients without mutant KRAS as negative control. 10 ng of ctDNA which extracted from blood sample is used in PCR. We observed that detected mutant status by DNA chip was completely concordant (100%) with those by amplicon-based deep sequencing system. Our data confirmed that mutant allele in cfDNA can be sensitively and accurately detected by DNA chip system. These results suggest that the ctDNA detection system developed in this study could be a novel diagnostic tool for tumor burden, and could realize the ultra-early detection of refractory tumors including pancreatic cancer.
Citation Format: Noriaki Nakamura, Hiroshi Okamura, Hirofumi Yamano, Hiromichi Ito, Hitoshi Zembutsu. The development of novel detection system for circulating tumor DNA using DNA chip system [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 2420.
Abstract 243: Differential effects of combination treatment of biochanin A and statins on glioblastoma multiforme cell proliferation and cell metabolism
Authors: Desai Vilas S. , Buchhalter Eric , Cabanzo Max , Tiwari Arushi , Kaushal Gagan , Lai James C. , Bhushan Alok 
Published: August 2019

Abstract
Glioblastoma Multiforme (GBM) is a deadly brain cancer and represents the most common central nervous system (CNS) tumors in adults. Although GBM does not metastasize, its aggressive growth and invasive nature are responsible for poor patient prognosis. The current standard therapy for newly diagnosed GBM patients involves surgical resection, followed by radiation and chemotherapy with Temozolomide. However, its rapid rate of infiltration into normal brain tissue ultimately renders the therapy ineffective. Epidemiological studies on dietary isoflavones (e.g., genistein, biochanin A) have shown their anti-cancer potential in different cancers. Though primarily used in management of hyperlipidemia and cardiovascular diseases, statins are known to exert anti-proliferative effects. We therefore hypothesized that a combination treatment of biochanin A & statins (e.g., Atorvastatin, Lovastatin, Simvastatin, Fluvastatin and Pravastatin) exerts enhanced anticancer effects on GBM U-87 MG and T98 G cells. Our studies showed statins induced differential effects on viability of GBM cells in combination with biochanin A, with U-87 MG being more susceptible than T98 G cells. The combination treatment of biochanin A and atorvastatin also decreased invasion in U-87 MG cells. Additionally, cell metabolism studies using seahorse XFp analyzer showed a switch in their metabolic phenotype with an increase in mitochondrial respiration and a decrease in glycolytic activity with the combination treatment. We also performed metabolite extraction on GBM cells for a global unbiased profiling of metabolites using a single extraction procedure and dual separation analysis by LCMS. A differential analysis of alternative GBM treatment indicated statistically significant changes in carbohydrate and amino acid metabolism as well as alterations to various degradation pathway intermediates. Together, the combination treatment-induced effects on GBM cell lines are differential and our results may have potential implications in developing combination therapies with biochanin A in vivo and support the design of new and better therapies for the treatment of a lethal cancer like GBM.
Citation Format: Vilas S. Desai, Eric Buchhalter, Max Cabanzo, Arushi Tiwari, Gagan Kaushal, James C. Lai, Alok Bhushan. Differential effects of combination treatment of biochanin A and statins on glioblastoma multiforme cell proliferation and cell metabolism [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 243.
Abstract 2443: Predicting the impact of somatic mutations on chromatin conformation using deep learning
Authors: Trieu Tuan , Khurana Ekta 
Published: August 2019

Abstract
DNA in eukaryotes is packed into hierarchical layers of loops resulting in the 3D structure of the genome. 3D genome organization plays vital roles in many biological processes of the cell such as gene regulation, cell division and stem cell differentiation and its disruption can lead to gene dysregulation and diseases, including cancer. We developed a deep learning model to predict the impact of single nucleotide variants, indels and structural variants on 3D chromatin loop structures of the genome. We first built a deep convolutional neural network to learn DNA sequence patterns of boundaries of 3D chromatin loops. The learned patterns of boundaries are then used to train another neural network to learn if two boundaries are likely boundaries of a chromatin loop given their DNA sequences. The model produces a probability indicating the likelihood of the two boundaries to form a chromatin loop (loop probability). It is trained with DNA sequence only, and therefore, it can detect effects of DNA variants on 3D chromatin loops as changes in loop probabilities. We trained our model with 80% of 3D chromatin loop from the cell line GM12878. Our model to predict boundaries of loops can distinguish DNA sequences of boundaries from random sequences with AUC of 0.96 on a balanced test-set from the cell line GM12878 and also performs well on data from the K562 cells with AUC of 0.93. Our result shows that variants in lymphoblastoid cells GM12878 do not change loop probabilities as much as variants in leukemia cells K562 do, consistent with the greater disruptive role of tumorigenic variants in the cancer cells. We next applied our model on whole-genome sequences of 240 malignant lymphoma patients to identify loop-disrupting variants that may act as drivers of cancer. We find that genes in predicted altered loops show more differential expression in tumor samples compared to genes in unchanged loops. Our method can be applied on large cohorts of patients with whole-genome sequences to analyze the chromatin conformation changes caused by somatic variants.
Citation Format: Tuan Trieu, Ekta Khurana. Predicting the impact of somatic mutations on chromatin conformation using deep learning [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 2443.
Abstract 2453: A new deconvolution algorithm for accurate assessing immune and stromal cell populations in mouse transcriptomic data
Authors: Lu Xiaoyu , Tu Szu-wei , Chang Wennan , Huo Yan , Wang Pengcheng , Zhang Yu , Zhang Chi , Cao Sha 
Published: August 2019

Abstract
Multiple deconvolution methods have been developed for investigating the heterogeneous immune and stromal (I/S) cell types in human cancer tissue by deciphering their relative abundances using transcriptomic data. However, there is a lack of a user-friendly software for mouse transcriptomic data deconvolution. Key challenges for developing such a tool include: (1) limited training data sets for available for deriving signature genes of I/S cell types in sporadic mouse data; (2) mouse models of diverse geno-/pheno-types may have varied expressions of I/S cell marker genes; (3) the transcriptomic data may be collected from mouse with certain levels of immuno-deficiency; and (4) the transcriptomic data may come from highly diverse experimental platforms. To solve these challenges, we (i) developed a novel non-parametric analysis method to derive potential I/S cell signature genes from a large collection of mouse data sets; (ii) implemented a low rank sub matrix identification method with a non-negative matrix factorization (NMF) based deconvolution method; and (iii) enabled the flexibility that certain I/S cell types may be absent if their respective cell markers do not form a significant low rank structure. The new method is applied to mouse prostate cancer data sets to infer the level of anti-cancer immune cell populations. Genes expressed by cancer cells that are negatively associated with the anti-cancer immune cells are further inferred, and compared with the results derived in human data. A user-friendly R package of the deconvolution method is released through GitHub.
Citation Format: Xiaoyu Lu, Szu-wei Tu, Wennan Chang, Yan Huo, Pengcheng Wang, Yu Zhang, Chi Zhang, Sha Cao. A new deconvolution algorithm for accurate assessing immune and stromal cell populations in mouse transcriptomic data [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 2453.