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  • 1
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    Abstract LB-317: Interactive pipeline for reproducible genomics analyses
    American Association for Cancer Research (AACR) ; 2014
    In:  Cancer Research Vol. 74, No. 19_Supplement ( 2014-10-01), p. LB-317-LB-317
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 74, No. 19_Supplement ( 2014-10-01), p. LB-317-LB-317
    Abstract: Automated Genomics Analysis (AGA) is a program to analyze high-throughput genomic data sets, such as Affymetrix gene expression arrays. The software implements an easy to use, point and click, guided pipeline to combine, define and compare datasets, and customize their outputs. Batch correction techniques are implemented to combine data sets. Options to save plots, tables and data are available throughout the analysis, and log files containing the R script run are also generated to facilitate reproducible analyses. The software has been applied to gene expression measurements from head and neck squamous cell carcinoma (HNSCC). It has batch corrected several public domain microarray HNSCC datasets, facilitating accurate comparison of subtypes such as HPV status. Moreover, current extensions enable users to interactively perform reproducible genomics analysis using clinical covariates in RNA sequencing data from TCGA. Citation Format: Michael Considine, Hilary S. Parker, Yingying Wei, Xiao X. Xia, Leslie Cope, Michael F. Ochs, Elana J. Fertig. Interactive pipeline for reproducible genomics analyses. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr LB-317. doi:10.1158/1538-7445.AM2014-LB-317
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2014-LB-317
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2014
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  • 2
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    NF‐κB and stat3 transcription factor signatures differentiate HPV ‐positive and HPV ‐negative head and neck squamous cell carcinoma
    Wiley ; 2015
    In:  International Journal of Cancer Vol. 137, No. 8 ( 2015-10-15), p. 1879-1889
    Details
    In: International Journal of Cancer, Wiley, Vol. 137, No. 8 ( 2015-10-15), p. 1879-1889
    Abstract: What's new? Changes in transcription factor (TF) expression contribute to genetic and epigenetic abnormalities in cancer. In order to capitalize on those changes and advance diagnostic and therapeutic strategies for cancer, researchers must first find a way to detect and quantify changes in TF activity. Here, TF activity was estimated globally in primary head and neck squamous cell carcinoma (HNSCC) using a novel inferential approach that accounted for gene silencing and loss of heterozygosity and homozygosity. Top‐scoring pair biomarkers were identified and linked to human papillomavirus (HPV) status, enabling HPV+ and HPV‐ HNSCC to be distinguished based on TF activity.
    Type of Medium: Online Resource
    ISSN: 0020-7136 , 1097-0215
    URL: Issue
    URL: Article
    DOI: 10.1002/ijc.v137.8
    DOI: 10.1002/ijc.29558
    RVK:
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    Language: English
    Publisher: Wiley
    Publication Date: 2015
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  • 3
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    Abstract 3100: MicroRNA profiling reveals miR-205 upregulation is associated with head and neck squamous cell carcinoma and modulates E2F1 signaling.
    American Association for Cancer Research (AACR) ; 2013
    In:  Cancer Research Vol. 73, No. 8_Supplement ( 2013-04-15), p. 3100-3100
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 73, No. 8_Supplement ( 2013-04-15), p. 3100-3100
    Abstract: Introduction: Based on our previous screen of miRNAs in head and neck squamous cell carcinoma (HNSCC), we sought to functionally evaluate candidate transcripts that could modify Rb/E2F signaling. Thus, we chose to investigate miR-205 as a putative HNSCC oncogene and regulator of E2F1 protein expression. Methods: miRNAs were isolated from 29 newly diagnosed HNSCC tumors (HPV-positive: 14, HPV-negative: 15) and 4 normal mucosa samples using the PureLink RNA Isolation Kit (Invitrogen). miRNA was analyzed using the ABI Megaplex protocol without pre-amplification (Applied Biosystems). Reactions were run using the miRNA Reverse Transcription Kit and Megaplex RT Human Pool A primers, then analyzed by TaqMan Low-Density Array (TLDA) cards. miRNA data was normalized to MammU6 expression, with undetectable transcripts assigned a Ct value of 40. Empirical Bayes moderated t-statistics were used to assess miRNA differential expression and the Benjamini- Hotchberg correction was applied to these p-values to account for multiple hypothesis testing. miR-205 expression was then transiently modified (Dharmacon) in an HPV-positive and -negative HNSCC cell line. These cells were characterized by Western blot and assayed for changes in proliferation utilizing two- and three-dimensional growth assays. Results: HNSCC miRNA expression was characterized by a general upregulation of individual transcripts and miRNA families compared to normal mucosa. This difference in expression was independent of HPV-status, with only two miRNAs demonstrating differential expression between HPV-positive and -negative tumors: miR-449a and miR-129-3p. miR-205, a transcript upregulated in both subtypes, was able to modulate proliferation and E2F1 expression levels in 93VU147T (HPV+), but not UM-SCC-15 (HPV-). Further Western blot analysis concluded modulations in Rb-phosphorylation status and apoptotic signaling factors may explain these E2F1-mediated effects. Conclusions: While significant differences are evident in the miRNA profiles of HNSCC compared to normal mucosa, a striking degree of similarity exists between HPV-positive and -negative miRNA deregulation. A functional evaluation of miR-205 determined this transcript is capable of modulating HNSCC growth in the genetic context of p16 expression and proapoptotic signaling. Citation Format: Jason D. Howard, Haixia Cheng, Elena Ratner, Elana J. Fertig, Jimena Perez, Harry Quon, Michael Considine, Michael Ochs, Joanne Weidhaas, Christine H. Chung. MicroRNA profiling reveals miR-205 upregulation is associated with head and neck squamous cell carcinoma and modulates E2F1 signaling. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3100. doi:10.1158/1538-7445.AM2013-3100
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2013-3100
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2013
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  • 4
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    Abstract 3577: Splice expression variation analysis (SEVA) for differential gene isoform usage in cancer
    American Association for Cancer Research (AACR) ; 2017
    In:  Cancer Research Vol. 77, No. 13_Supplement ( 2017-07-01), p. 3577-3577
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 3577-3577
    Abstract: Alternative splicing events (ASE) are a significant component of expression alterations in cancer, and have been demonstrated to be critically important in the development of malignant phenotypes in a variety of tumors. These alternative gene isoforms alter cell-signaling networks and serve as a hidden source of tumor-driving alterations not identified in multi-omics analyses. Recent studies have demonstrated that reads from RNA-seq data can infer gene isoforms expressed in a single sample. Therefore, RNA-seq data of tumors offers the opportunity to systematically evaluate expressed gene isoforms and identify splicing events in cancer samples. To characterize a cancer specific ASEs landscape, it is essential to perform differential splice variant expression analysis to identify isoform variants that are unique to tumor samples compared to normal tissue. In spite of the breadth of ASE algorithms, few have been validated in primary tumor samples. Current methods for differential splice variant analysis compare mean expression of gene isoforms in sample groups. Because these variants are tumor-specific, ASEs are expected to have more variable exon junction expression than normal samples. Therefore, current differential ASE analysis algorithms from RNA-seq may not account for heterogeneous gene isoform usage in tumors. To address this, we introduce Splice Expression Variability Analysis (SEVA) to detect differential splice variation usage in tumor and normal samples and accounts for tumor heterogeneity. This algorithm compares the degree of variability of junction expression profiles within a population of normal samples relative to that in tumor samples. The performance of SEVA was compared with two existing algorithms, EBSeq and DiffSplice, in simulated and real RNA-seq data. Simulated data suggest that SEVA is robust and computationally efficient relative to EBSeq and DiffSplice. In contrast to EBSeq and DiffSplice, SEVA was able to identify alternative splicing events independent of overall gene expression differences. Finally, additional validation was performed using RNA-seq data for primary tumor data from HPV-positive oropharynx squamous cell carcinoma (OPSCC) tumors and normal samples from both TCGA and an independent tumor cohort of 46 OPSCC tumors and 25 normal samples. In these tumor samples, SEVA finds cancer-specific ASEs in genes that are independent of their differential expression status. Moreover, SEVA finds approximately hundreds of splice variant candidates, manageable for experimental validation in contrast to the thousands of candidates found with EBSeq or DiffSplice. These candidates include experimentally validated splice variants in HNSCC from a previous microarray study. Based on performance in both simulated and real data, SEVA represents a robust algorithm that is well suited for differential ASE analysis, particularly in RNA-sequencing data from heterogeneous primary tumor samples. Citation Format: Bahman Afsari, Theresa Guo, Michael Considine, Dylan Kelley, Emily Flam, Liliana Florea, Patrick Ha, Donald Geman, Michael F. Ochs, Joseph A. Califano, Daria A. Gaykalova, Alexander V. Favorov, Elana J. Fertig. Splice expression variation analysis (SEVA) for differential gene isoform usage in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3577. doi:10.1158/1538-7445.AM2017-3577
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2017-3577
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 5
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    Abstract 5206: Role of super-enhancers in HPV+ head and neck squamous cell carcinoma
    American Association for Cancer Research (AACR) ; 2019
    In:  Cancer Research Vol. 79, No. 13_Supplement ( 2019-07-01), p. 5206-5206
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 5206-5206
    Abstract: Head and neck squamous cell carcinomas (HNSCC) are the sixth leading cause of cancer worldwide with different incidences, mortalities, and prognosis for different subsites. Infection by Human Papilloma Viral (HPV) can cause the development of HPV+ HNSCC, the most rapidly growing population of cancer patients. The molecular biology of HPV+ HNSCC is related to abnormal transcriptional regulation. Super-enhancers (SEs) were recently identified as critical regulators of gene expression during cell differentiation and disease development. SEs are long clusters of enhancers that recruit master transcription factors (TFs) and coactivators to regulate the expression of target genes. We have recently developed a new whole-genome analytical pipeline to optimize ChIP-Seq procedures on primary surgical samples, and this protocol helped us to define the whole-genome distribution of H3K27ac, the hallmark of SEs, in HPV+ HNSCC samples. To detect SEs, we used a novel LILY algorithm that corrects the ChIP-Seq signal for copy number variation and CpG density. The analysis revealed that HPV+ HNSCC-specific SEs regulate genes critical for head and neck cancer development, such as EGFR, TP63, JAG1, IRF6, SMAD3, MAP4K2, SNAI1, TNFAIP3, ANO2, and TNFRSF1A. These genes are located in the vicinity of HNSCC-specific SEs, and the expression of those genes was altered by JQ1, the inhibitor of BRD4, the main component of SE machinery, supporting the role of SE in their regulation. The following Cistrome analysis allowed us to elucidate the TF composition of the SE machinery. Thus, we have found out that P63, P53, SOX2, FOSL1, SMAD3, and SNAI2 are TFs that are the most overrepresented in the HPV+ HNSCC-specific SEs. These comprehensive analyses have revealed novel insight into the HPV+ HNSCC biology and paved the basis for the implications for epigenetic therapeutics for this tumor types, and potentially other virus-related malignancies. Citation Format: Fernando T. Zamuner, Ilya Vorontsov, Emily Flam, Vera Mukhina, Ludmila Danilova, Tingting Ou, Elena Stavrovskaya, Theresa Guo, Eric Windsor, Dylan Z. Kelley, Michael Parfenov, Michael Considine, Elana J. Fertig, Alexander Favorov, Daria A. Gaykalova. Role of super-enhancers in HPV+ head and neck squamous cell carcinoma [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 5206.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2019-5206
    RVK:
    XA 36000
    RVK:
    XA 10000
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
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  • 6
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    Abstract 05: Untangling the gene-epigenome networks: Timing of epigenetic regulation of gene expression in acquired cetuximab resistance gene programs
    American Association for Cancer Research (AACR) ; 2017
    In:  Clinical Cancer Research Vol. 23, No. 23_Supplement ( 2017-12-01), p. 05-05
    Details
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 23, No. 23_Supplement ( 2017-12-01), p. 05-05
    Abstract: The current study performs time course RNA-seq and DNA methylation profiling to determine the complex interactions between gene expression and epigenetic changes in acquired therapeutic resistance. The genomics era provides widespread characterization of the genomic landscape of tumors and has enabled precision treatment strategies. Currently, epidermal growth factor receptor (EGFR) inhibitors are the only FDA-approved targeted therapy for clinical use in head and neck squamous cell carcinoma (HNSCC). EGFR inhibitors are only effective in a subset of each of these tumors. Moreover, patients with de novo sensitivity to EGFR inhibitors often subsequently acquire resistance and succumb to their tumors. Numerous genetic and epigenetic alterations occur in tumors with acquired resistance. However, their timing and function remain unknown. Therefore, we develop new computational techniques to find gene programs associated with the acquisition of resistance. High-throughput transcriptional profiling enables unprecedented characterization of individual genes during cancer treatment. However, identifying and targeting mechanisms of EGFR resistance from these high-throughput data requires novel systems biology techniques that can discriminate altered cellular signaling pathways in response to cancer treatment. Therefore, we developed a new bioinformatics algorithm Coordinated Gene Activity in Pattern Sets (CoGAPS) to quantify multiplexed regulation and gene reuse in oncogenic signaling. To test this algorithm, we modified the HaCaT keratinocyte cell line model of premalignancy to simulate cancer cells with constitutive overexpression of wild-type EGFR and with activating mutations in HRAS and PIK3CA in a controlled genetic background. We apply CoGAPS to gene expression data from these models. This algorithm quantified relative changes in cellular signaling pathway activity in these data, not accessible to standard gene comparisons. Increases in CoGAPS pathway signatures from HRAS also occurred in gene expression data from the cetuximab resistant HNSCC cell line (1CC8) relative to its parental, sensitive cell line (UMSCC1). Investigation of the mechanisms of acquired resistance has previously been limited by reliance on case-control comparisons between sensitive and resistant cells, such as the UMSCC1 and 1CC8 cell lines. Since activity in cellular signaling pathways evolves during cetuximab resistance, it is essential to extend these case-control paradigms to quantify the dynamics responsible for resistance. Therefore, we developed a novel time course analysis to determine the molecular mechanisms of acquired cetuximab resistance in HNSCC. Specifically, we treated the cetuximab sensitive SCC25 HNSCC cell line over generations with both cetuximab and PBS. This long-term treatment protocol models the progression of acquired therapeutic resistance, including controls for clonal selection unrelated to treatment. Overexpression of the previous HRAS gene program also occurs in gene expression data measured during acquired cetuximab resistance in SCC25. We also measure DNA methylation during this time course to find the driver of this aberrant signaling associated with resistance. We apply CoGAPS analysis to the time course data for both DNA methylation and gene expression. This analysis distinguished early gene expression changes from cetuximab treatment from longer-term epigenetic alterations to gene expression during acquired resistance. Epigenetic regulation of FGFR1 expression emerged as the dominant mechanism of acquired therapeutic resistance in this system. Thus, our integration of time course DNA methylation and gene expression data enables unprecedented inference of the timing of targetable gene-epigenome programs responsible for acquired resistance. Citation Format: Genevieve Stein-O'Brien, Luciane T. Kagohara, Sijia Li, Manjusha Thakar, Ruchira Ranaweera, Michael Considine, Ludmila V. Danilova, Hiroyuki Ozawa, Joseph A. Califano, Daria A. Gaykalova, Michael F. Ochs, Christine H. Chung, Elana J. Fertig. Untangling the gene-epigenome networks: Timing of epigenetic regulation of gene expression in acquired cetuximab resistance gene programs [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; April 23-25, 2017; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(23_Suppl):Abstract nr 05.
    Type of Medium: Online Resource
    ISSN: 1078-0432 , 1557-3265
    URL: Article
    DOI: 10.1158/1557-3265.AACRAHNS17-05
    RVK:
    XA 36791
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 7
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    Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction
    Oxford University Press (OUP) ; 2014
    In:  Bioinformatics Vol. 30, No. 19 ( 2014-10-01), p. 2757-2763
    Details
    In: Bioinformatics, Oxford University Press (OUP), Vol. 30, No. 19 ( 2014-10-01), p. 2757-2763
    Abstract: Motivation: Sample source, procurement process and other technical variations introduce batch effects into genomics data. Algorithms to remove these artifacts enhance differences between known biological covariates, but also carry potential concern of removing intragroup biological heterogeneity and thus any personalized genomic signatures. As a result, accurate identification of novel subtypes from batch-corrected genomics data is challenging using standard algorithms designed to remove batch effects for class comparison analyses. Nor can batch effects be corrected reliably in future applications of genomics-based clinical tests, in which the biological groups are by definition unknown a priori. Results: Therefore, we assess the extent to which various batch correction algorithms remove true biological heterogeneity. We also introduce an algorithm, permuted-SVA (pSVA), using a new statistical model that is blind to biological covariates to correct for technical artifacts while retaining biological heterogeneity in genomic data. This algorithm facilitated accurate subtype identification in head and neck cancer from gene expression data in both formalin-fixed and frozen samples. When applied to predict Human Papillomavirus (HPV) status, pSVA improved cross-study validation even if the sample batches were highly confounded with HPV status in the training set. Availability and implementation: All analyses were performed using R version 2.15.0. The code and data used to generate the results of this manuscript is available from https://sourceforge.net/projects/psva . Contact:  ejfertig@jhmi.edu Supplementary information:  Supplementary data are available at Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1367-4811 , 1367-4803
    URL: Article
    DOI: 10.1093/bioinformatics/btu375
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2014
    detail.hit.zdb_id: 1468345-3
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  • 8
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    Correction: Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines
    Springer Science and Business Media LLC ; 2020
    In:  British Journal of Cancer Vol. 123, No. 10 ( 2020-11-10), p. 1582-1583
    Details
    In: British Journal of Cancer, Springer Science and Business Media LLC, Vol. 123, No. 10 ( 2020-11-10), p. 1582-1583
    Type of Medium: Online Resource
    ISSN: 0007-0920 , 1532-1827
    URL: Article
    DOI: 10.1038/s41416-020-0998-0
    RVK:
    XA 33500
    RVK:
    XA 10000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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  • 9
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    Differentially Methylated Super-Enhancers Regulate Target Gene Expression in Human Cancer
    Springer Science and Business Media LLC ; 2019
    In:  Scientific Reports Vol. 9, No. 1 ( 2019-10-21)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2019-10-21)
    Abstract: Current literature suggests that epigenetically regulated super-enhancers (SEs) are drivers of aberrant gene expression in cancers. Many tumor types are still missing chromatin data to define cancer-specific SEs and their role in carcinogenesis. In this work, we develop a simple pipeline, which can utilize chromatin data from etiologically similar tumors to discover tissue-specific SEs and their target genes using gene expression and DNA methylation data. As an example, we applied our pipeline to human papillomavirus-related oropharyngeal squamous cell carcinoma (HPV + OPSCC). This tumor type is characterized by abundant gene expression changes, which cannot be explained by genetic alterations alone. Chromatin data are still limited for this disease, so we used 3627 SE elements from public domain data for closely related tissues, including normal and tumor lung, and cervical cancer cell lines. We integrated the available DNA methylation and gene expression data for HPV + OPSCC samples to filter the candidate SEs to identify functional SEs and their affected targets, which are essential for cancer development. Overall, we found 159 differentially methylated SEs, including 87 SEs that actively regulate expression of 150 nearby genes (211 SE-gene pairs) in HPV + OPSCC. Of these, 132 SE-gene pairs were validated in a related TCGA cohort. Pathway analysis revealed that the SE-regulated genes were associated with pathways known to regulate nasopharyngeal, breast, melanoma, and bladder carcinogenesis and are regulated by the epigenetic landscape in those cancers. Thus, we propose that gene expression in HPV + OPSCC may be controlled by epigenetic alterations in SE elements, which are common between related tissues. Our pipeline can utilize a diversity of data inputs and can be further adapted to SE analysis of diseased and non-diseased tissues from different organisms.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-019-51018-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
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  • 10
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    Entinostat Decreases Immune Suppression to Promote Antitumor Responses in a HER2+ Breast Tumor Microenvironment
    American Association for Cancer Research (AACR) ; 2022
    In:  Cancer Immunology Research Vol. 10, No. 5 ( 2022-05-03), p. 656-669
    Details
    In: Cancer Immunology Research, American Association for Cancer Research (AACR), Vol. 10, No. 5 ( 2022-05-03), p. 656-669
    Abstract: Therapeutic combinations to alter immunosuppressive, solid tumor microenvironments (TME), such as in breast cancer, are essential to improve responses to immune checkpoint inhibitors (ICI). Entinostat, an oral histone deacetylase inhibitor, has been shown to improve responses to ICIs in various tumor models with immunosuppressive TMEs. The precise and comprehensive alterations to the TME induced by entinostat remain unknown. Here, we employed single-cell RNA sequencing on HER2-overexpressing breast tumors from mice treated with entinostat and ICIs to fully characterize changes across multiple cell types within the TME. This analysis demonstrates that treatment with entinostat induced a shift from a protumor to an antitumor TME signature, characterized predominantly by changes in myeloid cells. We confirmed myeloid-derived suppressor cells (MDSC) within entinostat-treated tumors associated with a less suppressive granulocytic (G)-MDSC phenotype and exhibited altered suppressive signaling that involved the NFκB and STAT3 pathways. In addition to MDSCs, tumor-associated macrophages were epigenetically reprogrammed from a protumor M2-like phenotype toward an antitumor M1-like phenotype, which may be contributing to a more sensitized TME. Overall, our in-depth analysis suggests that entinostat-induced changes on multiple myeloid cell types reduce immunosuppression and increase antitumor responses, which, in turn, improve sensitivity to ICIs. Sensitization of the TME by entinostat could ultimately broaden the population of patients with breast cancer who could benefit from ICIs.
    Type of Medium: Online Resource
    ISSN: 2326-6066 , 2326-6074
    URL: Article
    DOI: 10.1158/2326-6066.CIR-21-0170
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
    detail.hit.zdb_id: 2732517-9
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