bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 5068: Genomic regulation of the cell cycle as a function of ARID1A occupancy in breast epithelial cells
Authors: Jdeed Sham , Balint Balint L. , Uray Iván P.
Published: August 2019

The idea of chemoprevention introduced a new concept both in clinical practice and experimental approaches. While single agent ER-independent chemopreventive therapy based on RXR-selective retinoids and other agents has produced promising results, even minor toxicity remains an obstacle to their clinical use. We performed unbiased high throughput screening to identify synergistic growth suppressive combinations of agents in normal mammary epithelial cells. A RXR-selective agonist and a beta-adrenergic inhibitor, as a candidate combination, at low concentrations demonstrated marked cancer preventive activity in a mouse model of Her2-induced ER-negative breast cancer. To elucidate the molecular mechanisms of this chemopreventive activity proteomic analyses of the candidate drug combination ensued. These revealed increased levels and phosphorylation of the DNA damage sensor ATM, along with elevated levels of the ARID1A subunit of the SWI/SNF chromatin remodeler in normal breast epithelial cells, but not in in situ breast carcinoma cells. Thus, we hypothesized that the maintenance of genomic integrity through ARID1A is a critical factor in the effectiveness of cancer preventive agents and helps reduce the odds of transformation. Genomic regions of increased accessibility are mapped by high throughput sequencing enabling multidimensional assays of the regulatory chromatin regions. Enhancers identified through chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) for H3K27 acetyl complemented with histones H3K4 will be discussed. We propose that ARID1A may mediate antiproliferative effects through genome-wide pausing of transcription of cell cycle regulatory genes. These results will help establish a role for the crosstalk of rexinoid and adrenergic signaling in the maintenance of a conserved chromatin remodeling mechanism and thus, premalignancy in breast epithelial cells.

Citation Format: Sham Jdeed, Balint L. Balint, Iván P. Uray. Genomic regulation of the cell cycle as a function of ARID1A occupancy in breast epithelial 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 5068.
Abstract 5070: Sulforaphane is a novel inhibitor of breast cancer-induced osteolytic bone resorption
Authors: Pore Subrata K. , Latoche Joseph D. , Anderson Carolyn J. , Adamik Juraj , Galson Deborah L. , Weiss Kurt R. , Lee Boeun , Watters Rebecca J. , Kumta Prashant N. , Singh Shivendra V.
Published: August 2019

Bone is the preferred site for metastatic spread in women with advanced breast cancer, and skeletal complications is associated with high morbidity and mortality. Nearly 70% of luminal-type breast cancer patients with metastases to bone experience skeletal complications due to enhanced osteoclastogenesis (osteoclast activation) that increases bone resorption, pain, pathological fractures, spinal cord compression, and hypercalcemia. The present study was designed to determine the effect of a cruciferous vegetable component (Sulforaphane; SFN) on breast cancer-induced osteoclastogenesis. Osteoclast differentiation in mouse bone marrow monocytes (BMM) was inhibited significantly upon the addition of 10% conditioned-media (CM) from SFN-treated breast cancer cells belonging to different subtypes, including MDA-MB-231, MCF-7, and SK-BR-3, in comparison with corresponding control. PCR-based gene expression profiling identified a common set of genes downregulated by SFN treatment compared to vehicle-treated control in MDA-MB-231, MCF-7, and SK-BR-3 cells, including osteoclastogenesis promoting transcription factors (RUNX2, NF-κB, and SOX-9) and certain soluble molecules (MMP9, TNFα, and Cathepsin K). Many of these gene expression changes were confirmed in MDA-MB-231, MCF-7, and SK-BR-3 cells by RT-PCR or western blotting. To determine the in vivo efficacy, SFN was administrated orally (1 mg per mouse; three times/week) to athymic mice intracardially injected with MDA-MB-231-Luc cells. SFN administration significantly inhibited the multiplicity of bone metastases and increased the bone volume relative to total volume. SFN-mediated prevention of osteoclastogenesis was associated with a significant decrease in TRAP-positive osteoclasts in bones and the levels of Cathepsin K, IL-8, and RANKL in serum. Altogether, this study demonstrates, for the first time to the best of our knowledge, that SFN is a potent inhibitor of breast cancer-induced osteoclastogenesis and bone resorption in vitro and in vivo. This study was partly funded by a pilot project grant from the UPMC Hillman Cancer (NCI grant P30 CA047904; Robert L. Ferris- Principal Investigator) and RO1 CA142604 and CA129347 awarded by the National Cancer Institute (Shivendra Singh- Principal Investigator).

Citation Format: Subrata K. Pore, Joseph D. Latoche, Carolyn J. Anderson, Juraj Adamik, Deborah L. Galson, Kurt R. Weiss, Boeun Lee, Rebecca J. Watters, Prashant N. Kumta, Shivendra V. Singh. Sulforaphane is a novel inhibitor of breast cancer-induced osteolytic bone resorption [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 5070.
Abstract 5081: Leelamine is a novel inhibitor of fatty acid synthesis in prostate cancer
Authors: Singh Krishna B. , Singh Shivendra V.
Published: August 2019

Increased beta-oxidation of fatty acids to meet energy demand is a rather unique characteristic of a subset of human prostate cancers. A safe and effective intervention for inhibition of fatty acid synthesis is still a clinically unmet need. We have shown previously that leelamine (LLM), a phytochemical derived from pine tree bark, suppresses expression and activity of full-length androgen receptor (AR) and its splice variants in vitro and in vivo in preclinical models of prostate cancer. Because AR is implicated in regulation of fatty acid metabolism, the present study was undertaken to determine the effect of LLM on this metabolic pathway. Treatment of a castration-resistant (22Rv1) as well as an androgen-responsive (LNCaP) human prostate cancer cell line with LLM (2.5 and 5 µmol/L) resulted in downregulation of key fatty acid synthesis enzyme proteins including ATP citrate lyase (ACLY), acetyl-CoA carboxylase 1 (ACC1), fatty acid synthase (FASN), and sterol regulatory element-binding protein 1 (SREBP1). LLM treatment also decreased intracellular levels of total free fatty acids and neutral lipid droplets in LNCaP and 22Rv1 cells. Consistent with the in vitro results, we also observed a significant decrease in ACLY and SREBP1 protein expression and number of neutral lipid droplets in vivo in tumor tissue sections of 22Rv1 xenografts after intraperitoneal administration of LLM (9.1 mg/kg bw/ day, 5 times/week) compared to controls. Studies are in progress to determine if overexpression of AR and/or SREBP1 confers protection against fatty acid synthesis inhibition by LLM. In conclusion, it is reasonable to postulate that suppression of AR-SREBP1 regulated fatty acid metabolism is an important mechanism in prostate cancer inhibition by LLM. This study was supported by the grant RO1 CA101753 awarded by the National Cancer Institute.

Citation Format: Krishna B. Singh, Shivendra V. Singh. Leelamine is a novel inhibitor of fatty acid synthesis in prostate 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 5081.
Abstract 5086: Acetyl-L-carnitine (ALCAR) inhibits angiogenesis, migration and macrophage recruitment in prostatic cancer cells
Authors: Albini Adriana , Bruno Antonino , Baci Denisa , Gallazzi Matteo , Tramacere Matilde
Published: August 2019

Many efforts have been addressed on the identification of novel active compounds from natural sources, endowed with anti-proliferative, anti-oxidant, chemopreventive properties, and their ability to target the tumour microenvironment (TME). Through metabolomics approaches we previously found that in serum samples from prostate cancer (PCa) patients, three carnitine family members were significantly decreased, suggesting a potential protective role of carnitine against PCa. Acetyl-L-carnitine(ALCAR) is an aceticacid ester of carnitine with high bioavailability and is involved in the transportof fatty acids across the inner mitochondrial membrane. We have showed that ALCAR was able reduce angiogenesis in vitro, acting on the VEGF/VEGFR2 and CXCR4/CXCL12 axes. We also found that ALCAR inhibits inflammatory angiogenesis in vivo, by reducing endothelial cells and macrophage recruitment in the matrigel plugs. Here we investigated the ability of ALCAR to interfere with key functional steps of prostate carcinogenesis and identified the molecular mechanisms involved. The effects of ALCAR on PCa cells were investigated in vitro by functional assays (adhesion, migration and invasion assays), molecular and biochemical approaches (RT-PCR, FACS, Byoplex and western blot). We found that ALCAR reduces apoptosis on PCa cells (PC3, Du-145, LNcap) and inhibits crucial tumorigenic steps such as adhesion, migration and invasion. We than confirmed the results from functional assays at molecular levels, and we found that ALCAR blocks CXCR4/CXCL12 axes, a key regulator of malignant migratory/aggressive phenotype. In accordance with our published paper, we confirmed the anti-angiogenic and ant-inflammatory properties of ALCAR, that we found to lower VEGF and CXCL8 production in PCa cell lines. Furthermore, we found a significantly reduced expression of inflammatory-related chemokines/cytokines involved macrophage recruitment such as CCL2, IL-6 and TNFα in PCa cells. Our results highlight the angio/chemopreventive and anti-inflammatory properties of ALCAR and allow the identification of multiple and overlapping mechanisms of action through which ALCAR inhibits PCa progression / metastasis. Our findings provide the rational for the employment of ALCAR, as a possible supplement for approaches of chemoprevention in subjects at high risk to develop cancer.

Citation Format: Adriana Albini, Antonino Bruno, Denisa Baci, Matteo Gallazzi, Matilde Tramacere. Acetyl-L-carnitine (ALCAR) inhibits angiogenesis, migration and macrophage recruitment in prostatic cancer 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 5086.
Abstract 5094: SCOPE: A normalization and copy number estimation method for single-cell DNA sequencing
Authors: Wang Rujin , Lin Danyu , Jiang Yuchao
Published: August 2019

Whole genome single-cell DNA sequencing (scDNA-seq) enables characterization of copy number profiles at the cellular level. This circumvents the averaging effects associated with bulk-tissue sequencing and has increased resolution yet decreased ambiguity in deconvolving cancer subclones and elucidating cancer evolutionary history. ScDNA-seq data is, however, sparse, noisy, and highly variable even within a homogeneous cell population, due to the biases and artifacts that are introduced during the library preparation and sequencing procedure. Here, we propose SCOPE, a normalization and copy number estimation method for scDNA-seq data. The distinguishing features of SCOPE include: (i) utilization of cell-specific Gini coefficients for quality controls and for identification of normal/diploid cells, which are further used as negative control samples in a Poisson latent factor model for normalization; (ii) modeling of GC content bias using an expectation-maximization algorithm embedded in the Poisson generalized linear models, which accounts for the different copy number states along the genome; (iii) a cross-sample iterative segmentation procedure to identify breakpoints that are shared across cells from the same genetic background. We evaluate performance of SCOPE on real scDNA-seq data sets from cancer genomic studies. Compared to existing methods, SCOPE more accurately estimates subclonal copy number aberrations and is shown to have higher correlation with array-based copy number profiles of purified bulk samples from the same patient. We further demonstrate SCOPE on three recently released data sets using the 10X Genomics single-cell CNV pipeline and show that it can reliably recover 1% of the cancer cells from a background of normal and recover the cancer subclonal compositions of 10,000 breast cancer cells.

Citation Format: Rujin Wang, Danyu Lin, Yuchao Jiang. SCOPE: A normalization and copy number estimation method for single-cell DNA 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 5094.
Abstract 5095: Statistical modeling of transcriptional regulatory states in single-cell RNA-Seq data of tumor and infiltrated immune cells
Authors: Wan Changlin , Chang Wennan , Lu Xiaoyu , Sun Yifan , So Kaman , Cao Sha , Lu Xiongbin , Zhang Chi
Published: August 2019

Single-cell RNA-seq of tumor tissue has greatly strengthened our understanding of tumor development as well as the heterogeneous tissue micro-environment. Many models are dedicated to detect deferentially expressed genes among single cells of different conditions, or to discover (novel) sub-cell types via various clustering methods. However, current statistical models often neglect the zero/low expressions, and use one single modality to fit the rest of the non-zero ones. We believe that zero and low expressions are observed partly due to limited experimental resolution; on the other hand, occasionally, low expressions are falsely observed as non-zero due to the existence of incompletely degraded mRNA. In addition, the severe heterogeneity and fast dynamics of single cells makes it invalid to fit their expressions in one single modality. Here, we propose a left truncated mixture Gaussian (LTMG) distribution to uncover the multimodality in single cells’ gene expression while properly handling the zero and low expressions. LTMG is motivated by the kinetic relationships among the mRNA abundance, transcriptional regulatory signals (TRSs), and mRNA metabolism in a cell. Specifically, observations of a gene’s expression are fitted as mixture Gaussian distributions which assumes zero and low expressions as left censored data. By treating each mixing component as one state of the transcriptional regulators, we combined our LTMG model and our in-house bi-clustering algorithm to infer modules of genes co-regulated by certain (unknown) transcriptional regulatory signal, which is only shared by a subset of all the single cells. Application of the method to three high quality single-cell RNA-seq data sets of T cells extracted from liver, colon and lung cancer micro-environments, identified varied transcriptional regulations specific to subclasses of T cells.

Citation Format: Changlin Wan, Wennan Chang, Xiaoyu Lu, Yifan Sun, Kaman So, Sha Cao, Xiongbin Lu, Chi Zhang. Statistical modeling of transcriptional regulatory states in single-cell RNA-Seq data of tumor and infiltrated immune 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 5095.
Abstract 5104: Pan-cancer classification on gene expression data by neural network
Authors: Yu Kijin , Kim Bong-Hyun , Lee Peter Chang Whan
Published: August 2019

Cancer classification based on molecular signatures such as gene expression profiles has been provided insights on causes of the disease or provided guidance for selecting patient’s treatment regimen. We developed a cancer classifier that can identify 13 different types of cancers or a normal tissue based on bulk RNA-seq data as well as single cell RNA-seq data. Training was performed with 6,483 samples from 13 cancer tissues and 640 samples from tumor-adjacent normal tissues in The Cancer Genome Atlas based on 300 most significant genes for the binary classification of each cancer. Then, we compared Neural network, Support vector machine, Naïve Bayes and Random Forest methods. Neural network performed consistently better than other methods, even it took shorter time to train. We further applied our approach to bulked single cell data that is generated from single cell RNA-seq and found our model successfully classified cancer types and normal samples. Gene set enrichment analysis comparing cancer types found genes in cell cycle-related pathways, which highlights the differences between cancer types might be in their abilities to grow in different conditions. We also found genes that expressed in multiple cancers that can be novel biomarkers and therapeutic targets.

Citation Format: Kijin Yu, Bong-Hyun Kim, Peter Chang Whan Lee. Pan-cancer classification on gene expression data by neural network [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 5104.
Abstract 5107: Putative biomarkers for tumor sample purity prediction based on gene expression data
Authors: Li Yuanyuan
Published: August 2019

Tumor purity is the percent of cancer cells present in a sample of tumor tissue. The non-cancerous cells (immune cells, fibroblasts, etc.) have an important role in tumor biology. We applied a supervised machine learning method, XGBoost, to data from 33 TCGA tumor types to predict tumor purity using RNA-seq gene expression data. Across the 33 tumor types, the median correlation between observed and predicted tumor-purity ranged from 0.75 to 0.87 with small root mean square errors, suggesting that tumor purity can be accurately predicted using expression data. We further confirmed that a ten-gene set (CSF2RB, RHOH, C1S, CCDC69, CCL22, CYTIP, POU2AF1, FGR, CCL21, and IL7R) whose expression levels alone were predictive of tumor purity regardless of tumor type. We tested the predicative power of the ten-gene set on an independent dataset that was not from TCGA and showed that the expression levels of the ten genes can accurately predict the cancer cell proportions in those independent samples. The correlation coefficient between the predicted and experimentally obtained tumor purity was 0.88. Our analyses suggested that the ten-gene set may serve as a biomarker for tumor purity prediction using gene expression data.

Citation Format: Yuanyuan Li. Putative biomarkers for tumor sample purity prediction based on gene expression 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 5107.
Abstract 5111: HuPharm: An interactive data analysis platform for preclinical studies
Authors: Mao Binchen , Guol Sheng , Li Qixiang
Published: August 2019

Background: Preclinical studies, the first stage of the drug development process, must always have proper planning, execution, analysis and reporting in order to preserve scientific integrity. The decision to advance to human clinical trials depends heavily on results of these studies. For To facilitateing in vivo pharmacology data analysis and interpretation, we developed a web platform (HuPharm) that automates statistical pipelines and report generation. Its intuitive and interactive interface will greatly help researchers, who more often than not are non-statisticians, on data validation, exploratory data analysis and statistical analysis.

Methods: We use RStudio’s shiny package to build an interactive web application (HuPharm), and we use knitr and rmarkdown packages to generate a highly informative data analysis report. HuPharm is deployed on the web using Shinyapps.io developed by RStudio. Based on the distribution of input data, HuPharm will automatically performs parametric tests such as ANOVA and Welch’s t-test or non-parametric tests such as Kruskal-Wallis test and Mann-Whitney U test. Additionally, HuPharm is capable of conducting survival analysis, including both non-parametric Kaplan-Meier analysis and Ccox regression. Aside from classical tests, we have also implemented a number of state-of-the-art analytics on HuPharm, such as multilevel/hierarchical linear models, frailty analysis and joint modeling of longitudinal and survival data. Last by not the least, power analysis module in HuPharm can help researchers with their study design by power and sample size calculation.

Results: Based upon user inputs, HuPharm will dynamically generate a series of tables and figures to facilitate preclinical data analysis, such as tumor volume summary statistic table and plots, tumor growth curves, omnibus group comparison plots, all pairwise group comparison table and post hoc analysis results table. In addition, HuPharm can generate one nicely formatted study report including all those aforementioned figures and tables in both html and pdf format. Powered by shiny server’s interactive design, users can easily adjust the parameters to explore their data in a highly flexible and responsive way.

Conclusions: HuPharm is a convenient and powerful tool to aid researchers in the field of preclinical trials studies for their study design and data analysis. It will help to add rigor and improve the quality of preclinical studies.

Citation Format: Binchen Mao, Sheng Guol, Qixiang Li. HuPharm: An interactive data analysis platform for preclinical 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 5111.
Abstract 5113: A flexible pipeline for precision medicine biomarker detection and prediction of treatment response
Authors: Hughitt V Keith , Gorjifard Sayeh , Michalowski Aleksandra M. , Simmons John K. , Dale Ryan , Polley Eric C. , Keats Jonathan J. , Mock Beverly A.
Published: August 2019

Recent years have seen an explosion in the availability of paired molecular profiling and drug screen data, providing an unprecedented opportunity for the development of targeted therapies based on an individual’s genetic background. Despite a number of recent successes in diseases ranging from cystic fibrosis to cancer, significant hurdles remain in our ability to accurately predict treatments based on molecular profiling data. In particular, few such tools exist that allow the integration of heterogeneous data types (e.g. genomic, transcriptomic, and somatic mutations), along with high-throughput drug screen data to make predictions about treatment efficacy. Here, we describe a generalized open-source pipeline developed for the analysis of precision medicine data, Pharmacogenomics Prediction Pipeline, or “P3”. The modular design of P3 enables the inclusion of arbitrary input data types and the selection from multiple alternative machine learning algorithms, while automated statistical and visualization reporting steps incorporated throughout the pipeline assist in parameter tuning and early detection of problematic data components. Molecular profiling data is further enriched by the incorporation of external biological information in the form of pathway and gene set annotations such and Gene Ontology (GO) and The Molecular Signatures Database (MSigDB). To demonstrate the use of P3 for preclinical biomarker prediction, we applied P3 to an unpublished multiple myeloma dataset consisting of exome, RNA-Seq, CNV, and drug screen data for 1,912 compounds across 47 tumor cell lines. Specifically, P3 was used to predict molecular features associated with response to treatment for all drugs where a differential response to treatment was observed across patients. Furthermore, molecular profiling and drug screen data for 267 drugs and over a thousand cell lines spanning multiple cancer types from the Genomics of Drug Sensitivity in Cancer (GDSC) project were analyzed using P3, providing insights into shared mechanisms of drug sensitivity and resistance across different cancer and treatment types.

Citation Format: V Keith Hughitt, Sayeh Gorjifard, Aleksandra M. Michalowski, John K. Simmons, Ryan Dale, Eric C. Polley, Jonathan J. Keats, Beverly A. Mock. A flexible pipeline for precision medicine biomarker detection and prediction of treatment response [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 5113.
Abstract 5117: Comprehensive structural analysis of cancer genomes by genome mapping
Authors: Lam Ernest , Delpu Yannick
Published: August 2019

Tumors are often comprised of heterogeneous populations of cells, with certain cancer-driving mutations at low allele fractions in early stages of cancer development. Effective detection of such variants is critical for diagnosis and targeted treatment. However, typical short sequence reads are limited in their ability to span across repetitive regions of the genome and to facilitate structural variant (SV) analysis. Based on specific labeling and mapping of ultra-high molecular weight (UHMW) DNA, we developed a single-molecule platform that has the potential to detect disease-relevant SVs and give a high-resolution view of tumor heterogeneity.

We developed a DNA isolation and sample preparation workflow that preserves the DNA integrity and conserves structural variation information from blood, cells and preserved tissue. Single molecules are labeled at specific motifs and analyzed in massively parallel nanochannels. The single-molecule maps are used in a bioinformatics pipeline that effectively detects structural variants at low allele fractions. It includes single-molecule based SV calling and fractional copy number analysis. Preliminary analyses using simulated and well-characterized cancer samples showed high sensitivity for variants of different types at as low as 5% allele fractions. The candidate variants are then annotated and further prioritized based on control data and publicly available annotations. The data are imported into a graphical user interface tool that includes new visualization tools (such as Circos diagrams) for real-time interactive visualization and curation.

Bionano offers sample preparation, DNA imaging and genomic data analysis technologies combined into one streamlined workflow that enables high-throughput genome mapping on the Bionano Saphyr system. Together, these components allows for efficient analysis of any genome of interest.

Citation Format: Ernest Lam, Yannick Delpu. Comprehensive structural analysis of cancer genomes by genome mapping [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 5117.
Abstract 513: Investigating the expression of indolamine deoxygenase I (IDO1) and other immune markers in tissue microarrays
Authors: Cerezo Ana , Hoyo Gloria Martinez-del , Peregrina Sandra , Mondejar Tamara , Caleiras Eduardo , Gonzalez Patricia , Lospitao Eva , Hernandez-Tiedra Sonia , Diezma Laura , Casas Estela , Dorsey Frank , Benhadji Karim , Gilmour Raymond , Geeganage Sandaruwan , Velasco Susana
Published: August 2019

Purpose of the study: To gain insight to the proportion of solid tumors that express IDO1, CD73 and PD-L1 in lung cancer, colon adenocarcinoma, renal cell carcinoma (RCC) and melanoma, and the correlation between expression of these immune checkpoints and immune cell infiltration within the tumor.

Experimental procedures: Using a battery of properly validated antibodies, we have performed an in situ analysis of IDO1, CD73 and PD-L1 expression by immunohistochemistry in a panel of colon cancer (n=68), lung cancer (n=36), RCC (n=67) and melanoma (n=48) tissue microarray samples. Tumor infiltrating T cells, CD3+ and CD8+, were also detected by IHC and counted in serial sections for each sample. We search for a possible a correlation between the expression of these immunosuppressor proteins and the number of infiltrating CD3+ and CD8+ T cells as well as their expression in the different tumor components: tumor cells, stroma and endothelium.

Results: Our IHC analysis allowed us to classify the analyzed samples into two main groups: those with expression of IDO1, CD73 and PD-L1, which were also the ones with a high presence of immune cells within the tumors, “hot tumors”, and those that showed to be negative for all three proteins, and that correlated with lower infiltration of T cells, “cold tumors”. We also analyzed the location of the proteins within the tumors, and found an effect between endothelial expression of Ido1 and reduced infiltration in lung and RCC tumors.

Conclusions: The response to combined immune checkpoint and IDO1 therapy could depend on the proper stratification of patients; therefore, it is of significant interest to determine the proportion of solid tumors that express IDO1, CD73 and PD-L1, and the correlation of the expression of these three immune check points to immune cell infiltration within the tumor. Thus, proper patient stratification based on the expression of these immune checkpoints may improve the efficacy of IDO1 inhibitor based immune therapies.

Citation Format: Ana Cerezo, Gloria Martinez-del Hoyo, Sandra Peregrina, Tamara Mondejar, Eduardo Caleiras, Patricia Gonzalez, Eva Lospitao, Sonia Hernandez-Tiedra, Laura Diezma, Estela Casas, Frank Dorsey, Karim Benhadji, Raymond Gilmour, Sandaruwan Geeganage, Susana Velasco. Investigating the expression of indolamine deoxygenase I (IDO1) and other immune markers in tissue microarrays [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 513.
Abstract 5145: A new discovering motif on SOS1 PR domain clues Grb2-SOS1 association
Authors: Liao Tsung-Jen , Jang Hyunbum , Nussinov Ruth , Fushman David
Published: August 2019

Grb2 is an adaptor protein that recruits Ras-specific guanine nucleotide exchange factor (GEF), such as Son of sevenless 1 (SOS1), to the plasma membrane. SOS1 exchanges GDP by GTP, activating Ras. Grb2 consists of an SH2 domain in the middle and flanks nSH3/cSH3 domains at both ends. Both nSH3/cSH3 domains bind to SOS1’s C-terminal proline rich (PR) domain and have the preference for interacting with the PXXPXR motif. Our NMR data suggest that the arginine residue, followed by prolines in the PXXPXR motif, is responsible for the SH3-SOS1 association, yielding large chemical shift perturbations (CSPs) on the binding interface of SH3. The SOS1’s PR motif, PVPPPVPPRRRP, exhibits the strongest binding affinity to both SH3 domains. Using comprehensive techniques involving molecular dynamics (MD) simulation and NMR measurement, we uncover a new SOS1’s PR motifs, PKLPPKTYKREH, which shows strong binding to cSH3 but exhibits very weak affinity to nSH3. Unlike the arginine residue in the PXXPXR motif, the lysine residue in the PXXPPKXXKR motif induces weak interaction with cSH3. However, high affinity interaction is mainly derived from the hydrophobic interaction between the PXXP motif and cSH3, indicating the different binding modes of interaction. Our results suggest that Grb2 nSH3/cSH3 bind to SOS1 at distinct locations and provide atomic detailed models of Grb2-SOS1 association. Recent Grb2 targeted therapy reveals that peptide inhibitors, which interrupt Grb2-SOS1 interaction, effectively prevent the migration of breast cancer cell. The mechanism of Grb2-SOS1 interaction may enlighten the promising drug treatment development.

Citation Format: Tsung-Jen Liao, Hyunbum Jang, Ruth Nussinov, David Fushman. A new discovering motif on SOS1 PR domain clues Grb2-SOS1 association [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 5145.
Abstract 5232: PES1 is highly expressed and its biological function in gastrointestinal tumor
Authors: Feng Qin , Lian Shenyi , Wang Ping , Wang Yue , Li Zhongwu , Shou Chengchao , Ren Tingting , Lin Dongmei
Published: August 2019

Nucleolus, one of the most important organelles in cell nuclear of eukaryotic cells, is made of rRNA, rDNA and nucleoproteins. Its main function is rRNA synthetic. PES1 is part of nucleolar protein, and was identified in the mutational study of the embryonic development of Zebrafish. Its main biological functions include forming nucleolus, promoting cell proliferation and regulating cell cycle. A few researches indicate the close relationship between PES1 and tumorigenesis.

The purpose of this study is to explore the role of PES1 in tumorigenesis and the possible mechanism. Three specific monoclonal antibodies against PES1 were made through hybridoma technique. Using these antibodies, it is found that PES1 had significantly higher expression in gastric and colon carcinoma than in tumor-adjacent and -distant tissues. Immunohistochemical assay on gastric carcinoma specimens and colon carcinoma specimens indicated that PES1 had significantly higher expression in carcinoma than in tumor-adjacent tissues. Moreover, we demonstrated the localization of PES1 was changed from nucleolus to nucleoplasm significantly under the stimulation of chemotherapeutic drugs and UV. The phenomenon of PES1 translocation in nucleus was weaken in drug-resistant cancer cell lines. These results suggest that the translocation of PES1 in nucleus might be related to DNA damage repair and drug resistance mechanism of cancer cells.

In summary, PES1 expression is significantly higher in gastric and colon carcinoma tissue. And dynamic changes of PES1 localization in the cell nucleus is an important biological function and is worth further research.

Note: This abstract was not presented at the meeting.

Citation Format: Qin Feng, Shenyi Lian, Ping Wang, Yue Wang, Zhongwu Li, Chengchao Shou, Tingting Ren, Dongmei Lin. PES1 is highly expressed and its biological function in gastrointestinal tumor [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 5232.
Abstract 5236: A qualitative change in transcriptome during MDCKII 3D epithelial morphogenesis is linked to intracellular trafficking
Authors: Wang Tianfang , Zhao Shaying , Cheng Shi-Yuan
Published: August 2019

The majority of human cancers are derived from epithelial tissues. Understanding epithelial morphogenesis is hence important in cancer research. Madin-Darby canine kidney II (MDCKII) cells, cultured in 3D and 2D conditions, are used extensively as a model for studying cell polarity, epithelial morphogenesis and carcinogenesis. Like other cell differentiation systems, gene expression plays a key role in MDCKII epithelial morphogenesis.

To better understand the change in the transcriptome, we performed a time course RNA-seq analysis of MDCKII 3D cytogenesis, along with fully polarized 2D cells for comparison. Surprisingly, our study reveals that the change is not linear, but rather clearly biphasic. Specifically, about 3,000 genes are significantly up- or down-regulated between 24 hour and day 3 after seeding, when the lumen is forming, compared to < 120 such genes during other time intervals. Because previous studies have shown that Rab11-coordinated intracellular trafficking plays an essential role in MDCKII lumen formation, we hypothesize this qualitative change in the transcriptome is linked to intracellular trafficking. To test this hypothesis, we used knockdown clones of AVL9 and DENND5A, both interacting with Rab11 and participating in trafficking. Knockdown cells have altered cell polarity and defective trafficking, but not as significant changes in transcriptome as wild type cells, supporting our hypothesis. We then focused on β-catenin to better understand the mechanism. Our study reveals that in wild type cells, following the first cell division, β-catenin is depleted from the nucleus and enriched in cell-cell junction. This results in MYC transcriptional silencing (supported by ATAC-seq analysis), which in turn initiated down-regulation of numerous MYC target genes. These observations are however not observed in knockdown cells.

Our study supports the qualitative change (“switch on-off”) model, rather than the quantitative (gradual) change model, in transcriptome remodeling during epithelial cell differentiation. Moreover, our work supports that intracellular trafficking likely initiates this quantitative change in transcriptome.

Citation Format: Tianfang Wang, Shaying Zhao, Shi-Yuan Cheng. A qualitative change in transcriptome during MDCKII 3D epithelial morphogenesis is linked to intracellular trafficking [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 5236.
Abstract 5242: To investigate the molecular mechanism and therapeutic roles of PSF-1 in leukemia
Authors: Hsieh Han-Yun , Jia Wei-Zhen , Takakura Nobuyuki
Published: August 2019

Recently, DNA replication protein PSF-1 gets more and more attention on the research field, PSF-1 not only plays the critical role in normal cell DNA replication but also involves in cancer cell proliferation and anti-apoptosis. PSF1 highly expressed in many types of cancers, such as non-small lung cancer, breast cancer, and colon carcinoma. However, the role and mechanism of PSF1 in leukemia are still uncleared. Compared to the human normal peripheral blood mononuclear cells (PBMCs), the expression level of PSF1 was significantly increased in several types of leukemia, including acute and chronic type leukemia. We also found that PSF1 participate in leukemic cell proliferation and anti-apoptosis. Since PSF1 presents in many types of leukemia, PSF-1 might act as a potential therapeutic target of pan-leukemia. However, in order to enhance the therapeutic effect of leukemia, against its recurrence and metastasis, leukemic stem cells (LSCs) become the novel therapeutic research target. Previous studies indicated that PSF-1 is essential for stem cell proliferation. Based on the study, we selected PSF-1 as the candidate. In this research, we would like to investigate the role of PSF-1 in leukemia and its cancer stem cell niche. Further to establish the new therapeutic method of LSC-specific clinical treatment.

Citation Format: Han-Yun Hsieh, Wei-Zhen Jia, Nobuyuki Takakura. To investigate the molecular mechanism and therapeutic roles of PSF-1 in leukemia [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 5242.
Abstract 5247: Overexpression of methylenetetrahydrofolate dehydrogenase 1 like (MTHFD1L) in bladder cancer: A potential therapeutic target
Authors: Eich Marie-Lisa , Pena Maria D. Rodriguez , Chandrashekar Darshan S. , Gordetsky Jennifer B. , Netto George J. , Varambally Sooryanarayana
Published: August 2019

Introduction: Methylenetetrahydrofolate dehydrogenase 1 (MTHFD1L) is a mitochondrial enzyme involved in the folate cycle by catalyzing the reaction of formyl-tetrahydrofolate to format and tetrahydrofolate (THF). THF is crucial for de novo purine and thymidylate synthesis and is also involved in the regeneration of methionine. Cancer cells rely on purines derived from the de novo pathway for the nucleotides whereas normal cells favor the salvage pathway. Thus, MTHFD1L could be a valuable therapeutic target for anticancer drug design. This study aimed to examine MTHFD1L expression in bladder cancer (BLCA).

Material and Methods: Applying the publicly available cancer transcriptome database UALCAN, we searched for overexpressed genes in bladder cancer associated with survival probability. These in silico analyses indicated a high expression of MTHFD1L in bladder cancer. Furthermore, MTHFD1L expression was analyzed in different molecular subtypes, stage and race groups. Survival probability in MTHFD1L low-and high-expressing tumors was also assessed using UALCAN. Additionally, by searching the publicly available data base Human Protein Atlas we analyzed MTHFD1L immunostaining patterns in bladder cancer.

Results: We analyzed data for 19 normal bladder tissues and 408 primary bladder cancers from the TCGA dataset. MTHFD1L was significantly (p<0.0001) overexpressed in tumorous tissue compared to normal. This overexpression was observed independent of stage, race and age. Furthermore, we found a higher number of MTHFD1L mRNA transcripts in tumors belonging to the basal/squamous and in the neuronal TCGA subtype. Kaplan-Meier survival analysis indicated a poorer survival in patients with high MTHFD1L expression (p=0.05). Evaluation of immunohistochemistry staining pattern in bladder cancer using the Human Protein Atlas database showed a differential expression among human bladder cancer tissues. We are performing in vitro studies to evaluate the role of MTHFD1L in bladder cancer initiation and progression.

Conclusions: Our preliminary findings on MTHFD1L suggest that its overexpression is associated with poor patient survival in bladder cancer. These results suggest that MTHFD1L could be important in the biology of BLCA and a potential target for therapy. Future studies will investigate the functional significance of MTHFD1L and its regulation in bladder cancer.

Citation Format: Marie-Lisa Eich, Maria D. Rodriguez Pena, Darshan S. Chandrashekar, Jennifer B. Gordetsky, George J. Netto, Sooryanarayana Varambally. Overexpression of methylenetetrahydrofolate dehydrogenase 1 like (MTHFD1L) in bladder cancer: A potential therapeutic target [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 5247.
Abstract 5257: Activation of the oncogene ERG by the Ras/ERK and PI3K/AKT pathways
Authors: Strittmatter Brady G. , Hollenhorst Peter
Published: August 2019

The TMPRSS2-ERG re-arrangement occurs in ~50% of prostate cancers and results in androgen driven aberrant expression of the transcription factor ERG. ERG acts as an oncogene in the prostate and activates a transcriptional program which results in cell migration, epithelial to mesenchymal transition, and tumorigenesis. Activation of both the Ras/ERK and PI3K/AKT signaling pathways has been demonstrated to be necessary for transcription of ERG target genes and is required for ERG mediated phenotypes in the prostate, however, the exact mechanism of this requirement is not known. Recently, our lab demonstrated that ERK1/2 phosphorylation of ERG abrogates ERG’s interaction with the co-repressor EZH2 and the PRC2 and is necessary for ERG-mediated transcription of genes involved in cell migration. It has been demonstrated that ERG also requires activation of the PI3K/AKT pathway for ERG-mediated tumorigenesis in the prostate, however how the Ras/ERK and PI3K/AKT pathways cooperate in transcription of ERG target genes and ERG mediated phenotypes is not well understood. Here we use genomic and transcriptomic approaches to demonstrate that Ras/ERK and PI3K/AKT pathway requirements for ERG function differ between distinct ERG-mediated mediated gene expression programs which correlate with distinct phenotypic outputs. Overall, our results demonstrate how the Ras/ERK and PI3K/AKT pathways contribute to ERG mediated tumorigenesis in the prostate and point the way towards new therapeutic targets.

Citation Format: Brady G. Strittmatter, Peter Hollenhorst. Activation of the oncogene ERG by the Ras/ERK and PI3K/AKT pathways [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 5257.
Abstract 5274: Multi-omics integration analysis robustly predicts high grade patient survival and identified altered fatty acid metabolism in high grade bladder cancer
Authors: Vantaku Venkata Rao , Dong Jianrong , Ambati Chandrashekar R , Perera Dimuthu , Donepudi Sri Ramya , Amara Chandra Sekhar , Putluri Vasanta , Shankar Ravi Shiva , Robertson Matthew J , Piyarathna Danthasinghe Waduge Badrajee , Villanueva Mariana , Rundstedt Friedrich-Carl von , Karanam Balasubramanyam , Ballester Leomar Y , Terris Martha K. , Lerner Seth P. , Andrea Apolo B , Villanueva Hugo , Sikora Andrew , Lotan Yair , Sreekumar Arun , Coarfa Cristian , Putluri Nagireddy
Published: August 2019

Cancer metabolism varies depending on tumor grade. Currently, there is an absence of integration of multi-omics data to predict Bladder cancer (BLCA) survival. We aimed to identify a metabolic signature in high-grade BLCA by integration of unbiased metabolomics, lipidomics and transcriptomics to predict patient survival and to discover novel therapeutic targets. In the current study, using a robust mass spectrometry platform, we conducted global unbiased metabolic and lipid profiling analysis. We identified 518 differential metabolites and 19 lipids of various classes using the NIST MS metabolomics compendium and lipidblast MS/MS libraries, respectively, between low-grade and high-grade BLCA then mapped them to associated genes. Pathway analysis revealed a unique set of biochemical pathways highly deregulated in high-grade BLCA. Integromics analysis identified a molecular gene signature associated with patient poor survival. Importantly, low expression of fatty acid associated enzymes in high-grade tumors was associated with low fatty acid β- oxidation and acyl carnitines in high-grade BLCA and confirmed using tissue microarray. Our key finding is that impaired fatty acid β-oxidation (FAO) by downregulation of fatty acid associate enzymes suggests a crucial role in the progression of low grade to high grade BLCA. Using a metabolic-centered multi-omics based integrative analysis provided a system-level perspective of BLCA that would facilitate the development of novel therapeutics for high-grade BLCA.

Note: This abstract was not presented at the meeting.

Citation Format: Venkata Rao Vantaku, Jianrong Dong, Chandrashekar R Ambati, Dimuthu Perera, Sri Ramya Donepudi, Chandra Sekhar Amara, Vasanta Putluri, Ravi Shiva Shankar, Matthew J Robertson, Danthasinghe Waduge Badrajee Piyarathna, Mariana Villanueva, Friedrich-Carl von Rundstedt, Balasubramanyam Karanam, Leomar Y Ballester, Martha K. Terris, Seth P. Lerner, Apolo B Andrea, Hugo Villanueva, Andrew Sikora, Yair Lotan, Arun Sreekumar, Cristian Coarfa, Nagireddy Putluri. Multi-omics integration analysis robustly predicts high grade patient survival and identified altered fatty acid metabolism in high grade bladder 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 5274.