delete extraneous refs

-@article{huIdentificationDNACleavage2015,

- title = {Identification of {{DNA}} Cleavage- and Recombination-Specific {{hnRNP}} Cofactors for Activation-Induced Cytidine Deaminase},

- author = {Hu, Wenjun and Begum, Nasim A. and Mondal, Samiran and Stanlie, Andre and Honjo, Tasuku},

- date = {2015-05-05},

- journaltitle = {Proceedings of the National Academy of Sciences},

- volume = {112},

- number = {18},

- pages = {5791--5796},

- publisher = {Proceedings of the National Academy of Sciences},

- doi = {10.1073/pnas.1506167112},

- url = {https://www.pnas.org/doi/full/10.1073/pnas.1506167112},

- urldate = {2022-10-04}

-}

-

-@article{huiNovelFunctionalRole2003,

- title = {Novel Functional Role of {{CA}} Repeats and {{hnRNP L}} in {{RNA}} Stability},

- author = {Hui, Jingyi and Reither, Gregor and Bindereif, Albrecht},

- date = {2003-01-08},

- journaltitle = {RNA},

- shortjournal = {RNA},

- volume = {9},

- number = {8},

- eprint = {12869704},

- eprinttype = {pmid},

- pages = {931--936},

- publisher = {Cold Spring Harbor Lab},

- issn = {1355-8382, 1469-9001},

- doi = {10.1261/rna.5660803},

- url = {http://rnajournal.cshlp.org/content/9/8/931},

- urldate = {2022-09-28},

- abstract = {CA dinucleotide repeat sequences are very common in the human genome. We have recently demonstrated that the polymorphic CA repeats in intron 13 of the human endothelial nitric oxide synthase (eNOS) gene function as an unusual, length-dependent splicing enhancer. The CA repeat enhancer requires for its activity specific binding of hnRNP L. Here we show that in the absence of bound hnRNP L, the pre-mRNA is cleaved directly upstream of the CA repeats. The addition of recombinant hnRNP L restores RNA stability. CA repeats are both necessary and sufficient for this specific cleavage in the 5′ adjacent RNA sequence. We conclude that—in addition to its role as a splicing activator—hnRNP L can act in vitro as a sequence-specific RNA protection factor. Based on the wide abundance of CA repetitive sequences in the human genome, this may represent a novel, generally important role of this abundant hnRNP protein.},

- langid = {english},

- keywords = {hnRNP L,Repetitive sequence,RNA stability,splicing}

-}

-

-@article{hungDiverseRolesHnRNP2008,

- title = {Diverse Roles of {{hnRNP L}} in Mammalian {{mRNA}} Processing: {{A}} Combined Microarray and {{RNAi}} Analysis},

- shorttitle = {Diverse Roles of {{hnRNP L}} in Mammalian {{mRNA}} Processing},

- author = {Hung, Lee-Hsueh and Heiner, Monika and Hui, Jingyi and Schreiner, Silke and Benes, Vladimir and Bindereif, Albrecht},

- date = {2008-01-02},

- journaltitle = {RNA},

- shortjournal = {RNA},

- volume = {14},

- number = {2},

- eprint = {18073345},

- eprinttype = {pmid},

- pages = {284--296},

- publisher = {Cold Spring Harbor Lab},

- issn = {1355-8382, 1469-9001},

- doi = {10.1261/rna.725208},

- url = {http://rnajournal.cshlp.org/content/14/2/284},

- urldate = {2022-10-04},

- abstract = {Alternative mRNA splicing patterns are determined by the combinatorial control of regulator proteins and their target RNA sequences. We have recently characterized human hnRNP L as a global regulator of alternative splicing, binding to diverse C/A-rich elements. To systematically identify hnRNP L target genes on a genome-wide level, we have combined splice-sensitive microarray analysis and an RNAi-knockdown approach. As a result, we describe 11 target genes of hnRNP L that were validated by RT-PCR and that represent several new modes of hnRNP L-dependent splicing regulation, involving both activator and repressor functions: first, intron retention; second, inclusion or skipping of cassette-type exons; third, suppression of multiple exons; and fourth, alternative poly(A) site selection. In sum, this approach revealed a surprising diversity of splicing-regulatory processes as well as poly(A) site selection in which hnRNP L is involved.},

- langid = {english},

- keywords = {alternative splicing hnRNP,microarray,polyadenylation,splicing}

-}

-

-@article{hunterOPTIMALOPTimizedImaging2023,

- title = {{{OPTIMAL}}: {{An OPTimized Imaging Mass}} Cytometry {{AnaLysis}} Framework for Benchmarking Segmentation and Data Exploration},

- shorttitle = {{{OPTIMAL}}},

- author = {Hunter, Bethany and Nicorescu, Ioana and Foster, Emma and McDonald, David and Hulme, Gillian and Fuller, Andrew and Thomson, Amanda and Goldsborough, Thibaut and Hilkens, Catharien M. U. and Majo, Joaquim and Milross, Luke and Fisher, Andrew and Bankhead, Peter and Wills, John and Rees, Paul and Filby, Andrew and Merces, George},

- date = {2023-09-26},

- journaltitle = {Cytometry. Part A: The Journal of the International Society for Analytical Cytology},

- shortjournal = {Cytometry A},

- eprint = {37750225},

- eprinttype = {pmid},

- issn = {1552-4930},

- doi = {10.1002/cyto.a.24803},

- abstract = {Analysis of imaging mass cytometry (IMC) data and other low-resolution multiplexed tissue imaging technologies is often confounded by poor single-cell segmentation and suboptimal approaches for data visualization and exploration. This can lead to inaccurate identification of cell phenotypes, states, or spatial relationships compared to reference data from single-cell suspension technologies. To this end we have developed the "OPTimized Imaging Mass cytometry AnaLysis (OPTIMAL)" framework to benchmark any approaches for cell segmentation, parameter transformation, batch effect correction, data visualization/clustering, and spatial neighborhood analysis. Using a panel of 27 metal-tagged antibodies recognizing well-characterized phenotypic and functional markers to stain the same Formalin-Fixed Paraffin Embedded (FFPE) human tonsil sample tissue microarray over 12 temporally distinct batches we tested several cell segmentation models, a range of different arcsinh cofactor parameter transformation values, 5 different dimensionality reduction algorithms, and 2 clustering methods. Finally, we assessed the optimal approach for performing neighborhood analysis. We found that single-cell segmentation was improved by the use of an Ilastik-derived probability map but that issues with poor segmentation were only really evident after clustering and cell type/state identification and not always evident when using "classical" bivariate data display techniques. The optimal arcsinh cofactor for parameter transformation was 1 as it maximized the statistical separation between negative and positive signal distributions and a simple Z-score normalization step after arcsinh transformation eliminated batch effects. Of the five different dimensionality reduction approaches tested, PacMap gave the best data structure with FLOWSOM clustering out-performing phenograph in terms of cell type identification. We also found that neighborhood analysis was influenced by the method used for finding neighboring cells with a "disc" pixel expansion outperforming a "bounding box" approach combined with the need for filtering objects based on size and image-edge location. Importantly, OPTIMAL can be used to assess and integrate with any existing approach to IMC data analysis and, as it creates .FCS files from the segmentation output and allows for single-cell exploration to be conducted using a wide variety of accessible software and algorithms familiar to conventional flow cytometrists.},

- langid = {english},

- keywords = {image analysis,image cytometry,imaging mass cytometry,tissue segmentation}

-}

-

-@article{huSplicingFactorHnRNPA2B12017,

- title = {Splicing Factor {{hnRNPA2B1}} Contributes to Tumorigenic Potential of Breast Cancer Cells through {{STAT3}} and {{ERK1}}/2 Signaling Pathway},

- author = {Hu, Ying and Sun, Zihan and Deng, Jinmu and Hu, Baoquan and Yan, Wenting and Wei, Hongyi and Jiang, Jun},

- date = {2017-03-01},

- journaltitle = {Tumor Biology},

- shortjournal = {Tumour Biol.},

- volume = {39},

- number = {3},

- pages = {1010428317694318},

- publisher = {SAGE Publications Ltd STM},

- issn = {1010-4283},

- doi = {10.1177/1010428317694318},

- url = {https://doi.org/10.1177/1010428317694318},

- urldate = {2022-10-04},

- abstract = {Increasing evidence has indicated that the splicing factor hnRNPA2B1 plays a direct role in cancer development, progression, gene expression, and signal transduction. Previous studies have shown that knocking down hnRNPA2B1 in breast cancer cells induces apoptosis, but the mechanism and other functions of hnRNPA2B1 in breast cancer are unknown. The goal of this study was to investigate the biological function, clinical significance, and mechanism of hnRNPA2B1 in breast cancer. The expression of hnRNPA2B1 in 92 breast cancer and adjacent normal tissue pairs was analyzed by immunohistochemical staining. Stable clones exhibiting knockdown of hnRNPA2B1 via small hairpin RNA expression were generated using RNA interference technology in breast cancer cell lines. The effects of hnRNPA2B1 on cell proliferation were examined by MTT and EdU assay, and cellular apoptosis and the cell cycle were examined by flow cytometry. A nude mouse xenograft model was established to elucidate the function of hnRNPA2B1 in tumorigenesis in vivo. The role of hnRNPA2B1 in signaling pathways was investigated in vitro. Our data revealed that hnRNPA2B1 was overexpressed in breast cancer tissue specimens and cell lines. Knockdown of hnRNPA2B1 reduced breast cancer cell proliferation, induced apoptosis, and prolonged the S phase of the cell cycle in vitro. In addition, hnRNPA2B1 knockdown suppressed subcutaneous tumorigenicity in vivo. On a molecular level, hnRNPA2B1 knockdown decreased signal transducer and activator of transcription 3 and extracellular-signal-regulated kinase 1/2 phosphorylation. We concluded that hnRNPA2B1 promotes the tumorigenic potential of breast cancer cells, MCF-7 and MDA-MB-231, through the extracellular-signal-regulated kinase 1/2 or signal transducer and activator of transcription 3 pathway, which may serve as a target for future therapies.},

- langid = {english}

-}

-

-@article{husseyIdentificationMRNPComplex2011,

- title = {Identification of an {{mRNP}} Complex Regulating Tumorigenesis at the Translational Elongation Step},

- author = {Hussey, George S. and Chaudhury, Arindam and Dawson, Andrea E. and Lindner, Daniel J. and Knudsen, Charlotte R. and Wilce, Matthew C. J. and Merrick, William C. and Howe, Philip H.},

- date = {2011-02-18},

- journaltitle = {Molecular cell},

- shortjournal = {Mol Cell},

- volume = {41},

- number = {4},

- eprint = {21329880},

- eprinttype = {pmid},

- pages = {419--431},

- issn = {1097-2765},

- doi = {10.1016/j.molcel.2011.02.003},

- url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3061437/},

- urldate = {2022-09-28},

- abstract = {Transcript-selective translational regulation of epithelial-mesenchymal transition (EMT) by transforming growth factor-β (TGFβ) is directed by the hnRNP E1-containing TGFβ-activated-translational (BAT) mRNP complex. Herein, eukaryotic elongation factor-1 A1 (eEF1A1) is identified as an integral component of the BAT complex. Translational silencing of Dab2 and ILEI, two EMT-transcripts, is mediated by binding of hnRNP E1 and eEF1A1 to their 3′-UTR BAT element, whereby hnRNP E1 stalls translational elongation by inhibiting the release of eEF1A1 from the ribosomal A site. TGFβ-mediated hnRNP E1 phosphorylation, through Akt2, disrupts the BAT complex, thereby restoring translation of target EMT-transcripts. Attenuation of hnRNP E1 expression in two non-invasive breast epithelial cells (NMuMG and MCF-7) induced not only EMT, but also enabled cells to form metastatic lesions in vivo. Thus, translational regulation by TGFβ, at the elongation stage, represents a critical checkpoint coordinating the expression of EMT-transcripts required during development and in tumorigenesis and metastatic progression.},

- pmcid = {PMC3061437}

-}

-

-@article{huTherapeuticSiRNAState2020,

- title = {Therapeutic {{siRNA}}: State of the Art},

- shorttitle = {Therapeutic {{siRNA}}},

- author = {Hu, Bo and Zhong, Liping and Weng, Yuhua and Peng, Ling and Huang, Yuanyu and Zhao, Yongxiang and Liang, Xing-Jie},

- date = {2020-06-19},

- journaltitle = {Signal Transduction and Targeted Therapy},

- shortjournal = {Sig Transduct Target Ther},

- volume = {5},

- number = {1},

- pages = {1--25},

- publisher = {Nature Publishing Group},

- issn = {2059-3635},

- doi = {10.1038/s41392-020-0207-x},

- url = {https://www.nature.com/articles/s41392-020-0207-x},

- urldate = {2022-10-05},

- abstract = {RNA interference (RNAi) is an ancient biological mechanism used to defend against external invasion. It theoretically can silence any disease-related genes in a sequence-specific manner, making small interfering RNA (siRNA) a promising therapeutic modality. After a two-decade journey from its discovery, two approvals of siRNA therapeutics, ONPATTRO® (patisiran) and GIVLAARI™ (givosiran), have been achieved by Alnylam Pharmaceuticals. Reviewing the long-term pharmaceutical history of human beings, siRNA therapy currently has set up an extraordinary milestone, as it has already changed and will continue to change the treatment and management of human diseases. It can be administered quarterly, even twice-yearly, to achieve therapeutic effects, which is not the case for small molecules and antibodies. The drug development process was extremely hard, aiming to surmount complex obstacles, such as how to efficiently and safely deliver siRNAs to desired tissues and cells and how to enhance the performance of siRNAs with respect to their activity, stability, specificity and potential off-target effects. In this review, the evolution of siRNA chemical modifications and their biomedical performance are comprehensively reviewed. All clinically explored and commercialized siRNA delivery platforms, including the GalNAc (N-acetylgalactosamine)–siRNA conjugate, and their fundamental design principles are thoroughly discussed. The latest progress in siRNA therapeutic development is also summarized. This review provides a comprehensive view and roadmap for general readers working in the field.},

- issue = {1},

- langid = {english},

- keywords = {Drug delivery,Gene therapy,Nucleic-acid therapeutics,Oligo delivery}

-}

-@article{irishBcellSignalingNetworks2010,

- title = {B-Cell Signaling Networks Reveal a Negative Prognostic Human Lymphoma Cell Subset That Emerges during Tumor Progression},

- author = {Irish, Jonathan M and Myklebust, June H and Alizadeh, Ash A and Houot, Roch and Sharman, Jeff P and Czerwinski, Debra K and Nolan, Garry P and Levy, Ronald},

- date = {2010-07},

- volume = {107},

- number = {29},

- pages = {12747--12754}

-}

-

-@article{irizarrySummariesAffymetrixGeneChip2003,

- title = {Summaries of {{Affymetrix GeneChip}} Probe Level Data},

- author = {Irizarry, Rafael A. and Bolstad, Benjamin M. and Collin, Francois and Cope, Leslie M. and Hobbs, Bridget and Speed, Terence P.},

- date = {2003-02-15},

- journaltitle = {Nucleic Acids Research},

- shortjournal = {Nucleic Acids Res.},

- volume = {31},

- number = {4},

- eprint = {12582260},

- eprinttype = {pmid},

- pages = {e15},

- issn = {1362-4962},

- doi = {10.1093/nar/gng015},

- abstract = {High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays are the most popular. In this technology each gene is typically represented by a set of 11-20 pairs of probes. In order to obtain expression measures it is necessary to summarize the probe level data. Using two extensive spike-in studies and a dilution study, we developed a set of tools for assessing the effectiveness of expression measures. We found that the performance of the current version of the default expression measure provided by Affymetrix Microarray Suite can be significantly improved by the use of probe level summaries derived from empirically motivated statistical models. In particular, improvements in the ability to detect differentially expressed genes are demonstrated.},

- langid = {english},

- pmcid = {PMC150247},

- keywords = {Central Nervous System,DNA Probes,Gene Expression Profiling,Humans,Liver,Oligonucleotide Array Sequence Analysis,Reproducibility of Results,RNA Messenger,Software}

-}

-

-@article{ishiiRoleAuf1Elimination2015,

- title = {Role of {{Auf1}} in Elimination of Oxidatively Damaged Messenger {{RNA}} in Human Cells},

- author = {Ishii, Takashi and Hayakawa, Hiroshi and Sekiguchi, Takeshi and Adachi, Noritaka and Sekiguchi, Mutsuo},

- date = {2015-02},

- journaltitle = {Free Radical Biology \& Medicine},

- shortjournal = {Free Radic Biol Med},

- volume = {79},

- eprint = {25486179},

- eprinttype = {pmid},

- pages = {109--116},

- issn = {1873-4596},

- doi = {10.1016/j.freeradbiomed.2014.11.018},

- abstract = {In aerobically growing cells, in which reactive oxygen species are produced, the guanine base of RNA is oxidized to 8-oxo-7,8-dihydroguanine, which induces alterations in gene expression. Here we show that the human Auf1 protein, also called HNRNPD, binds specifically to RNA containing this oxidized base and may be involved in cellular processes associated with managing the problems caused by RNA oxidation. Auf1-deficient cells were constructed from human HeLa and Nalm-6 lines using two different targeting procedures. Both types of Auf1-deficient cells are viable, but exhibit growth retardation. The stability of messenger RNA for four different housekeeping genes was determined in Auf1-deficient and -proficient cells, treated with or without hydrogen peroxide. The level of oxidized messenger RNA was considerably higher in Auf1-deficient cells than in Auf1-proficient cells. Auf1 may play a role in the elimination of oxidized RNA, which is required for the maintenance of proper gene expression under conditions of oxidative stress.},

- langid = {english},

- keywords = {8-Oxo-78-dihydroguanine,Auf1 protein,Cell Line,Free radicals,Heterogeneous Nuclear Ribonucleoprotein D0,Heterogeneous-Nuclear Ribonucleoprotein D,Humans,Oxidative stress,Oxidative Stress,Oxidized RNA,RNA degradation,RNA Messenger}

-}

-@article{islamUncoveringNovelMutational2022,

- title = {Uncovering Novel Mutational Signatures by de Novo Extraction with {{SigProfilerExtractor}}},

- author = {Islam, S. M. Ashiqul and Díaz-Gay, Marcos and Wu, Yang and Barnes, Mark and Vangara, Raviteja and Bergstrom, Erik N. and He, Yudou and Vella, Mike and Wang, Jingwei and Teague, Jon W. and Clapham, Peter and Moody, Sarah and Senkin, Sergey and Li, Yun Rose and Riva, Laura and Zhang, Tongwu and Gruber, Andreas J. and Steele, Christopher D. and Otlu, Burçak and Khandekar, Azhar and Abbasi, Ammal and Humphreys, Laura and Syulyukina, Natalia and Brady, Samuel W. and Alexandrov, Boian S. and Pillay, Nischalan and Zhang, Jinghui and Adams, David J. and Martincorena, Iñigo and Wedge, David C. and Landi, Maria Teresa and Brennan, Paul and Stratton, Michael R. and Rozen, Steven G. and Alexandrov, Ludmil B.},

- date = {2022-11-09},

- journaltitle = {Cell Genomics},

- shortjournal = {Cell Genomics},

- volume = {2},

- number = {11},

- pages = {100179},

- issn = {2666-979X},

- doi = {10.1016/j.xgen.2022.100179},

- url = {https://www.sciencedirect.com/science/article/pii/S2666979X22001240},

- urldate = {2023-12-18},

- abstract = {Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5\% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20\% and~50\% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.},

- keywords = {cancer genomics,genomics,mutagenesis,mutational signatures}

-}

-

-@article{itoCanineLymphomaComparative2014,

- title = {Canine Lymphoma as a Comparative Model for Human Non-{{Hodgkin}} Lymphoma: Recent Progress and Applications},

- shorttitle = {Canine Lymphoma as a Comparative Model for Human Non-{{Hodgkin}} Lymphoma},

- author = {Ito, Daisuke and Frantz, Aric M. and Modiano, Jaime F.},

- date = {2014-06-15},

- journaltitle = {Veterinary Immunology and Immunopathology},

- shortjournal = {Veterinary Immunology and Immunopathology},

- series = {Special {{Issue}}: {{Dual Purpose}} with {{Dual Benefit Research Models}} in {{Veterinary}} and {{Biomedical Research}}},

- volume = {159},

- number = {3},

- pages = {192--201},

- issn = {0165-2427},

- doi = {10.1016/j.vetimm.2014.02.016},

- url = {https://www.sciencedirect.com/science/article/pii/S016524271400052X},

- urldate = {2021-05-13},

- abstract = {The term “lymphoma” describes a heterogeneous group of disorders involving monoclonal proliferation of malignant lymphocytes. As a group, lymphomas are among the most common tumors of dogs. Yet our enumeration and understanding of the many subtypes of lymphoma have been relatively slow, perhaps in part because for many years lymphoma was treated as a singular entity rather than a group of distinct diseases. The recognition that the full spectrum of lymphoid malignancies seen in humans also occurs in dogs, and that these tumors retain not only morphologic similarities and biological behavior but also synonymous driver molecular abnormalities, sets an ideal stage for dual-purpose research that can accelerate progress for these diseases in both species. Specifically, dogs represent exceptional models for defining causality, understanding progression, and developing new treatments for lymphoma in comparatively brief windows of time. Unique advantages of canine models include (1) spontaneous disease occurring without an isogenic background or genetic engineering; (2) chronology of disease adapted to lifespan, (3) shared environment and societal status that allows dogs to be treated as “patients,” while at the same time being able to ethically explore translational innovations that are not possible in human subjects; and (4) organization of dogs into breeds with relatively homogeneous genetic backgrounds and distinct predisposition for lymphomas. Here, we will review recent studies describing intrinsic and extrinsic factors that contribute to the pathogenesis of canine and human lymphomas, as well as newly developed tools that will enhance the fidelity of these models to improve diagnosis and develop new treatments.},

- langid = {english}

-}

-

-@article{iwanagaHeterogeneousNuclearRibonucleoprotein2005,

- title = {Heterogeneous Nuclear Ribonucleoprotein {{B1}} Protein Impairs {{DNA}} Repair Mediated through the Inhibition of {{DNA-dependent}} Protein Kinase Activity},

- author = {Iwanaga, Kentaro and Sueoka, Naoko and Sato, Akemi and Hayashi, Shinichiro and Sueoka, Eisaburo},

- date = {2005-08-05},

- journaltitle = {Biochemical and Biophysical Research Communications},

- shortjournal = {Biochemical and Biophysical Research Communications},

- volume = {333},

- number = {3},

- pages = {888--895},

- issn = {0006-291X},

- doi = {10.1016/j.bbrc.2005.05.180},

- url = {https://www.sciencedirect.com/science/article/pii/S0006291X05011897},

- urldate = {2022-10-04},

- abstract = {Heterogeneous nuclear ribonucleoprotein B1, an RNA binding protein, is overexpressed from the early stage of lung cancers; it is evident even in bronchial dysplasia, a premalignant lesion. We evaluated the proteins bound with hnRNP B1 and found that hnRNP B1 interacted with DNA-dependent protein kinase (DNA-PK) complex, and recombinant hnRNP B1 protein dose-dependently inhibited DNA-PK activity in vitro. To test the effect of hnRNP B1 on DNA repair, we performed comet assay after irradiation, using normal human bronchial epithelial (HBE) cells treated with siRNA for hnRNP A2/B1: reduction of hnRNP B1 treated with siRNA for hnRNP A2/B1 induced faster DNA repair in normal HBE cells. Considering these results, we assume that overexpression of hnRNP B1 occurring in the early stage of carcinogenesis inhibits DNA-PK activity, resulting in subsequent accumulation of erroneous rejoining of DNA double-strand breaks, causing tumor progression.},

- langid = {english},

- keywords = {DNA double-strand break repair,DNA-dependent protein kinase,hnRNP B1,Lung cancer,RNA binding protein,RNA splicing}

-}

-

-@article{jacksonSinglecellPathologyLandscape2020,

- title = {The Single-Cell Pathology Landscape of Breast Cancer},

- author = {Jackson, Hartland W. and Fischer, Jana R. and Zanotelli, Vito R. T. and Ali, H. Raza and Mechera, Robert and Soysal, Savas D. and Moch, Holger and Muenst, Simone and Varga, Zsuzsanna and Weber, Walter P. and Bodenmiller, Bernd},

- date = {2020-02},

- journaltitle = {Nature},

- volume = {578},

- number = {7796},

- pages = {615--620},

- publisher = {Nature Publishing Group},

- issn = {1476-4687},

- doi = {10.1038/s41586-019-1876-x},

- url = {https://www.nature.com/articles/s41586-019-1876-x},

- urldate = {2022-02-03},

- abstract = {Single-cell analyses have revealed extensive heterogeneity between and within human tumours1–4, but complex single-cell phenotypes and their spatial context are not at present reflected in the histological stratification that is the foundation of many clinical decisions. Here we use imaging mass cytometry5 to simultaneously quantify 35 biomarkers, resulting in 720 high-dimensional pathology images of tumour tissue from 352 patients with breast cancer, with long-term survival data available~for 281 patients. Spatially resolved, single-cell analysis identified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity, and enabled the cellular architecture of breast cancer tissue to be characterized on the basis of cellular composition and tissue organization. Our analysis reveals multicellular features of the tumour microenvironment and novel subgroups of breast cancer that are associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intratumour phenotypic heterogeneity in a disease-relevant manner, with the potential to inform patient-specific diagnosis.},

- issue = {7796},

- langid = {english},

- keywords = {Breast cancer,Imaging,Systems biology,Tumour heterogeneity}

-}

-

-@article{jainNanoporeSequencingAssembly2018,

- title = {Nanopore Sequencing and Assembly of a Human Genome with Ultra-Long Reads},

- author = {Jain, Miten and Koren, Sergey and Miga, Karen H and Quick, Josh and Rand, Arthur C and Sasani, Thomas A and Tyson, John R and Beggs, Andrew D and Dilthey, Alexander T and Fiddes, Ian T and Malla, Sunir and Marriott, Hannah and Nieto, Tom and O'Grady, Justin and Olsen, Hugh E and Pedersen, Brent S and Rhie, Arang and Richardson, Hollian and Quinlan, Aaron R and Snutch, Terrance P and Tee, Louise and Paten, Benedict and Phillippy, Adam M and Simpson, Jared T and Loman, Nicholas J and Loose, Matthew},

- date = {2018},

- journaltitle = {Nature Biotechnology},

- volume = {36},

- number = {4},

- eprint = {29431738},

- eprinttype = {pmid},

- pages = {338},

- issn = {1546-1696},

- doi = {10.1038/nbt.4060},

- url = {http://dx.doi.org/10.1038/nbt.4060},

- abstract = {We report the sequencing and assembly of a reference genome for the human GM12878 Utah/Ceph cell line using the MinION (Oxford Nanopore Technologies) nanopore sequencer. 91.2 Gb of sequence data, representing ∼30× theoretical coverage, were produced. Reference-based alignment enabled detection of large structural variants and epigenetic modifications. De novo assembly of nanopore reads alone yielded a contiguous assembly (NG50 ∼3 Mb). We developed a protocol to generate ultra-long reads (N50 {$>$} 100 kb, read lengths up to 882 kb). Incorporating an additional 5× coverage of these ultra-long reads more than doubled the assembly contiguity (NG50 ∼6.4 Mb). The final assembled genome was 2,867 million bases in size, covering 85.8\% of the reference. Assembly accuracy, after incorporating complementary short-read sequencing data, exceeded 99.8\%. Ultra-long reads enabled assembly and phasing of the 4-Mb major histocompatibility complex (MHC) locus in its entirety, measurement of telomere repeat length, and closure of gaps in the reference human genome assembly GRCh38.}

-}

-

-@article{jainRulesRNASpecificity2017,

- title = {Rules of {{RNA}} Specificity of {{hnRNP A1}} Revealed by Global and Quantitative Analysis of Its Affinity Distribution},

- author = {Jain, Niyati and Lin, Hsuan-Chun and Morgan, Christopher E. and Harris, Michael E. and Tolbert, Blanton S.},

- date = {2017-02-28},

- journaltitle = {Proceedings of the National Academy of Sciences},

- volume = {114},

- number = {9},

- pages = {2206--2211},

- publisher = {Proceedings of the National Academy of Sciences},

- doi = {10.1073/pnas.1616371114},

- url = {https://www.pnas.org/doi/10.1073/pnas.1616371114},

- urldate = {2022-09-26}

-}

-

-@article{jangSIRT1ExpressionAssociated,

- title = {{{SIRT1}} Expression Is Associated with Poor Prognosis of Diffuse Large {{B-cell}} Lymphoma.},

- author = {Jang, Kyu Yun and Hwang, Sung Ho and Kwon, Keun Sang and Kim, Kyung Ryoul and Choi, Ha Na and Lee, Na-Ri and Kwak, Jae-Yong and Park, Byung-Hyun and Park, Ho Sung and Chung, Myoung Ja and Kang, Myoung Jae and Lee, Dong Geun and Kim, Hun Soo and Shim, Hyeok and Moon, Woo Sung},

- journaltitle = {The American journal of surgical pathology},

- volume = {32},

- number = {10},

- pages = {1523--1531}

-}

-@article{jean-philippeHnRNPA1Swiss2013,

- title = {{{hnRNP A1}}: {{The Swiss Army Knife}} of {{Gene Expression}}},

- shorttitle = {{{hnRNP A1}}},

- author = {Jean-Philippe, Jacques and Paz, Sean and Caputi, Massimo},

- date = {2013-09},

- journaltitle = {International Journal of Molecular Sciences},

- volume = {14},

- number = {9},

- pages = {18999--19024},

- publisher = {Multidisciplinary Digital Publishing Institute},

- issn = {1422-0067},

- doi = {10.3390/ijms140918999},

- url = {https://www.mdpi.com/1422-0067/14/9/18999},

- urldate = {2022-10-05},

- abstract = {Eukaryotic cells express a large variety of RNA binding proteins (RBPs), with diverse affinities and specificities towards target RNAs. These proteins play a crucial role in almost every aspect of RNA biogenesis, expression and function. The heterogeneous nuclear ribonucleoproteins (hnRNPs) are a complex and diverse family of RNA binding proteins. hnRNPs display multiple functions in the processing of heterogeneous nuclear RNAs into mature messenger RNAs. hnRNP A1 is one of the most abundant and ubiquitously expressed members of this protein family. hnRNP A1 plays multiple roles in gene expression by regulating major steps in the processing of nascent RNA transcripts. The transcription, splicing, stability, export through nuclear pores and translation of cellular and viral transcripts are all mechanisms modulated by this protein. The diverse functions played by hnRNP A1 are not limited to mRNA biogenesis, but extend to the processing of microRNAs, telomere maintenance and the regulation of transcription factor activity. Genomic approaches have recently uncovered the extent of hnRNP A1 roles in the development and differentiation of living organisms. The aim of this review is to highlight recent developments in the study of this protein and to describe its functions in cellular and viral gene expression and its role in human pathologies.},

- issue = {9},

- langid = {english},

- keywords = {hnRNP,miRNA,mRNA,splicing,telomere,transcription,translation}

-}

-

-@article{jeltschCleavageRoquinRegnase12014,

- title = {Cleavage of Roquin and Regnase-1 by the Paracaspase {{MALT1}} Releases Their Cooperatively Repressed Targets to Promote {{TH17}} Differentiation},

- author = {Jeltsch, Katharina M and Hu, Desheng and Brenner, Sven and Zöller, Jessica and Heinz, Gitta A and Nagel, Daniel and Vogel, Katharina U and Rehage, Nina and Warth, Sebastian C and Edelmann, Stephanie L and Gloury, Renee and Martin, Nina and Lohs, Claudia and Lech, Maciej and Stehklein, Jenny E and Geerlof, Arie and Kremmer, Elisabeth and Weber, Achim and Anders, Hans-Joachim and Schmitz, Ingo and Schmidt-Supprian, Marc and Fu, Mingui and Holtmann, Helmut and Krappmann, Daniel and Ruland, Jürgen and Kallies, Axel and Heikenwalder, Mathias and Heissmeyer, Vigo},

- date = {2014-10},

- journaltitle = {Nat Immunol},

- volume = {15},

- number = {11},

- pages = {1079--1089}

-}

-

-@article{jinInferenceAnalysisCellcell2021,

- title = {Inference and Analysis of Cell-Cell Communication Using {{CellChat}}},

- author = {Jin, Suoqin and Guerrero-Juarez, Christian F. and Zhang, Lihua and Chang, Ivan and Ramos, Raul and Kuan, Chen-Hsiang and Myung, Peggy and Plikus, Maksim V. and Nie, Qing},

- date = {2021-02-17},

- journaltitle = {Nature Communications},

- shortjournal = {Nat Commun},

- volume = {12},

- number = {1},

- eprint = {33597522},

- eprinttype = {pmid},

- pages = {1088},

- issn = {2041-1723},

- doi = {10.1038/s41467-021-21246-9},

- abstract = {Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. We construct a database of interactions among ligands, receptors and their cofactors that accurately represent known heteromeric molecular complexes. We then develop CellChat, a tool that is able to quantitatively infer and analyze intercellular communication networks from single-cell RNA-sequencing (scRNA-seq) data. CellChat predicts major signaling inputs and outputs for cells and how those cells and signals coordinate for functions using network analysis and pattern recognition approaches. Through manifold learning and quantitative contrasts, CellChat classifies signaling pathways and delineates conserved and context-specific pathways across different datasets. Applying CellChat to mouse and human skin datasets shows its ability to extract complex signaling patterns. Our versatile and easy-to-use toolkit CellChat and a web-based Explorer ( http://www.cellchat.org/ ) will help discover novel intercellular communications and build cell-cell communication atlases in diverse tissues.},

- langid = {english},

- pmcid = {PMC7889871},

- keywords = {Algorithms,Animals,Cell Communication,Computational Biology,Gene Expression Profiling,Humans,Internet,Mice,Models Theoretical,Sequence Analysis RNA,Signal Transduction,Single-Cell Analysis,Skin,Software}

-}

-@article{junEfficientScalableAnalysis2015,

- title = {An Efficient and Scalable Analysis Framework for Variant Extraction and Refinement from Population-Scale {{DNA}} Sequence Data},

- author = {Jun, Goo and Wing, Mary Kate and Abecasis, Gonçalo R. and Kang, Hyun Min},

- date = {2015-06},

- journaltitle = {Genome Research},

- shortjournal = {Genome Res.},

- volume = {25},

- number = {6},

- eprint = {25883319},

- eprinttype = {pmid},

- pages = {918--925},

- issn = {1549-5469},

- doi = {10.1101/gr.176552.114},

- abstract = {The analysis of next-generation sequencing data is computationally and statistically challenging because of the massive volume of data and imperfect data quality. We present GotCloud, a pipeline for efficiently detecting and genotyping high-quality variants from large-scale sequencing data. GotCloud automates sequence alignment, sample-level quality control, variant calling, filtering of likely artifacts using machine-learning techniques, and genotype refinement using haplotype information. The pipeline can process thousands of samples in parallel and requires less computational resources than current alternatives. Experiments with whole-genome and exome-targeted sequence data generated by the 1000 Genomes Project show that the pipeline provides effective filtering against false positive variants and high power to detect true variants. Our pipeline has already contributed to variant detection and genotyping in several large-scale sequencing projects, including the 1000 Genomes Project and the NHLBI Exome Sequencing Project. We hope it will now prove useful to many medical sequencing studies.},

- langid = {english},

- pmcid = {PMC4448687},

- keywords = {Computational Biology,Databases Genetic,Exome,Genetics Population,Genome Human,Haplotypes,High-Throughput Nucleotide Sequencing,Humans,Polymorphism Single Nucleotide,Sequence Alignment,Sequence Analysis DNA,Software}

-}

-@article{kachaevInterplayMRNACapping2020,

- title = {Interplay of {{mRNA}} Capping and Transcription Machineries},

- author = {Kachaev, Zaur M. and Lebedeva, Lyubov A. and Kozlov, Eugene N. and Shidlovskii, Yulii V.},

- date = {2020-01-24},

- journaltitle = {Bioscience Reports},

- shortjournal = {Biosci Rep},

- volume = {40},

- number = {1},

- eprint = {31904821},

- eprinttype = {pmid},

- pages = {BSR20192825},

- issn = {0144-8463},

- doi = {10.1042/BSR20192825},

- url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981093/},

- urldate = {2022-10-06},

- abstract = {Early stages of transcription from eukaryotic promoters include two principal events: the capping of newly synthesized mRNA and the transition of RNA polymerase II from the preinitiation complex to the productive elongation state. The capping checkpoint model implies that these events are tightly coupled, which is necessary for ensuring the proper capping of newly synthesized mRNA. Recent findings also show that the capping machinery has a wider effect on transcription and the entire gene expression process. The molecular basis of these phenomena is discussed.},

- pmcid = {PMC6981093}

-}

-@article{kaneVelcadeFDAApproval2003,

- title = {Velcade: {{U}}.{{S}}. {{FDA}} Approval for the Treatment of Multiple Myeloma Progressing on Prior Therapy},

- shorttitle = {Velcade},

- author = {Kane, Robert C. and Bross, Peter F. and Farrell, Ann T. and Pazdur, Richard},

- date = {2003},

- journaltitle = {The Oncologist},

- shortjournal = {Oncologist},

- volume = {8},

- number = {6},

- eprint = {14657528},

- eprinttype = {pmid},

- pages = {508--513},

- issn = {1083-7159},

- doi = {10.1634/theoncologist.8-6-508},

- abstract = {Bortezomib (formerly PS-341), a promising new drug for the treatment of multiple myeloma, recently received accelerated approval from the U.S. Food and Drug Administration (FDA) for the therapy of patients with progressive myeloma after previous treatment. Two phase II studies of bortezomib used the same schedule of twice-weekly i.v. dosing for the first 2 weeks of each 3-week cycle. In a randomized study of 54 patients, two doses were compared (1.0 and 1.3 mg/m2) and objective responses occurred at both dose levels (23\% versus 35\%), including one complete response in each arm. In the other phase II study, 202 heavily pretreated patients (median of six prior therapies) all received the same schedule at 1.3 mg/m2. Of 188 evaluable patients, complete responses occurred in five (3\%) and partial responses occurred in 47 (25\%). The median duration of response was 365 days. The most clinically relevant adverse events were asthenic conditions, nausea, vomiting, diarrhea, thrombocytopenia, and a peripheral neuropathy that often was painful. This report highlights the FDA analysis supporting the accelerated approval.},

- langid = {english},

- keywords = {Antineoplastic Agents,Boronic Acids,Bortezomib,Drug Approval,Humans,Multiple Myeloma,Pyrazines,Randomized Controlled Trials as Topic,United States,United States Food and Drug Administration}

-}

-

-@article{karczewskiMutationalConstraintSpectrum2020,

- title = {The Mutational Constraint Spectrum Quantified from Variation in 141,456 Humans},

- author = {Karczewski, Konrad J. and Francioli, Laurent C. and Tiao, Grace and Cummings, Beryl B. and Alföldi, Jessica and Wang, Qingbo and Collins, Ryan L. and Laricchia, Kristen M. and Ganna, Andrea and Birnbaum, Daniel P. and Gauthier, Laura D. and Brand, Harrison and Solomonson, Matthew and Watts, Nicholas A. and Rhodes, Daniel and Singer-Berk, Moriel and England, Eleina M. and Seaby, Eleanor G. and Kosmicki, Jack A. and Walters, Raymond K. and Tashman, Katherine and Farjoun, Yossi and Banks, Eric and Poterba, Timothy and Wang, Arcturus and Seed, Cotton and Whiffin, Nicola and Chong, Jessica X. and Samocha, Kaitlin E. and Pierce-Hoffman, Emma and Zappala, Zachary and O’Donnell-Luria, Anne H. and Minikel, Eric Vallabh and Weisburd, Ben and Lek, Monkol and Ware, James S. and Vittal, Christopher and Armean, Irina M. and Bergelson, Louis and Cibulskis, Kristian and Connolly, Kristen M. and Covarrubias, Miguel and Donnelly, Stacey and Ferriera, Steven and Gabriel, Stacey and Gentry, Jeff and Gupta, Namrata and Jeandet, Thibault and Kaplan, Diane and Llanwarne, Christopher and Munshi, Ruchi and Novod, Sam and Petrillo, Nikelle and Roazen, David and Ruano-Rubio, Valentin and Saltzman, Andrea and Schleicher, Molly and Soto, Jose and Tibbetts, Kathleen and Tolonen, Charlotte and Wade, Gordon and Talkowski, Michael E. and Consortium, Genome Aggregation Database (gnomAD) and Neale, Benjamin M. and Daly, Mark J. and MacArthur, Daniel G.},

- date = {2020-04-08},

- journaltitle = {bioRxiv},

- pages = {531210},

- publisher = {Cold Spring Harbor Laboratory},

- doi = {10.1101/531210},

- url = {https://www.biorxiv.org/content/10.1101/531210v4},

- urldate = {2020-04-27},

- abstract = {{$<$}p{$>$}Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organism9s function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes. Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved human mutation rate model, we classify human protein-coding genes along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.{$<$}/p{$>$}},

- langid = {english}

-}

-@article{kaufmannMEDICC2WholegenomeDoubling2021,

- title = {{{MEDICC2}}: Whole-Genome Doubling Aware Copy-Number Phylogenies for Cancer Evolution},

- shorttitle = {{{MEDICC2}}},

- author = {Kaufmann, Tom L. and Petkovic, Marina and Watkins, Thomas BK and Colliver, Emma C. and Laskina, Sofya and Thapa, Nisha and Minussi, Darlan C. and Navin, Nicholas and Swanton, Charles and Loo, Peter Van and Haase, Kerstin and Tarabichi, Maxime and Schwarz, Roland F.},

- date = {2021-09-06},

- pages = {2021.02.28.433227},

- publisher = {bioRxiv},

- doi = {10.1101/2021.02.28.433227},

- url = {https://www.biorxiv.org/content/10.1101/2021.02.28.433227v2},

- urldate = {2022-02-01},

- abstract = {Chromosomal instability (CIN) and somatic copy-number alterations (SCNA) play a key role in the evolutionary process that shapes cancer genomes. SC-NAs comprise many classes of clinically relevant events, such as localised amplifications, gains, losses, loss-of-heterozygosity (LOH) events, and recently discovered parallel evolutionary events revealed by multi-sample phasing. These events frequently appear jointly with whole genome doubling (WGD), a transformative event in tumour evolution involving tetraploidization of genomes preceded or followed by individual chromosomal copy-number changes and associated with an overall increase in structural CIN. While SCNAs have been leveraged for phylogeny reconstruction in the past, existing methods do not take WGD events into account and cannot model parallel evolution. They frequently make use of the infinite sites assumption, do not model horizontal dependencies between adjacent genomic loci and can not infer ancestral genomes. Here we present MEDICC2, a new phylogeny inference algorithm for allele-specific SCNA data that addresses these shortcomings. MEDICC2 dispenses with the infinite sites assumption, models parallel evolution and accurately identifies clonal and subclonal WGD events. It times SCNAs relative to each other, quantifies SCNA burden in single-sample studies and infers phylogenetic trees and ancestral genomes in multi-sample or single-cell sequencing scenarios with thousands of cells. We demonstrate MEDICC2’s ability on simulated data, real-world data of 2,778 single sample tumours from the Pan-cancer analysis of whole genomes (PCAWG), 10 bulk multi-region prostate cancer patients and two recent single-cell datasets of triple-negative breast cancer comprising several thousands of single cells.},

- langid = {english}

-}