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      Reciprocal inhibition between TP63 and STAT1 regulates anti-tumor immune response through interferon-γ signaling in squamous cancer

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          Abstract

          Squamous cell carcinomas (SCCs) are common and aggressive malignancies. Immune check point blockade (ICB) therapy using PD-1/PD-L1 antibodies has been approved in several types of advanced SCCs. However, low response rate and treatment resistance are common. Improving the efficacy of ICB therapy requires better understanding of the mechanism of immune evasion. Here, we identify that the SCC-master transcription factor TP63 suppresses interferon-γ (IFNγ) signaling. TP63 inhibition leads to increased CD8 + T cell infiltration and heighten tumor killing in in vivo syngeneic mouse model and ex vivo co-culture system, respectively. Moreover, expression of TP63 is negatively correlated with CD8 + T cell infiltration and activation in patients with SCC. Silencing of TP63 enhances the anti-tumor efficacy of PD-1 blockade by promoting CD8 + T cell infiltration and functionality. Mechanistically, TP63 and STAT1 mutually suppress each other to regulate the IFNγ signaling by co-occupying and co-regulating their own promoters and enhancers. Together, our findings elucidate a tumor-extrinsic function of TP63 in promoting immune evasion of SCC cells. Over-expression of TP63 may serve as a biomarker predicting the outcome of SCC patients treated with ICB therapy, and targeting TP63/STAT/IFNγ axis may enhance the efficacy of ICB therapy for this deadly cancer.

          Abstract

          TP63 is a master regulator transcription factor in squamous cell carcinomas (SCCs). Here the authors report that TP63 suppresses IFNγ signaling in SCC tumors and that its inhibition is associated with enhanced anti-tumor immunity and response to anti-PD1.

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          Most cited references68

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          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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              Comprehensive Integration of Single-Cell Data

              Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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                Author and article information

                Contributors
                dechenli@usc.edu
                yanyij@cmpt.ac.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                20 March 2024
                20 March 2024
                2024
                : 15
                : 2484
                Affiliations
                [1 ]GRID grid.9227.e, ISNI 0000000119573309, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, , Chinese Academy of Sciences, ; Hefei, 230031 China
                [2 ]University of Science and Technology of China, ( https://ror.org/04c4dkn09) Hefei, 230026 China
                [3 ]Clinical Big Data Research Center, Scientific Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, ( https://ror.org/00rfd5b88) Shenzhen, 518107 China
                [4 ]GRID grid.42505.36, ISNI 0000 0001 2156 6853, Center for Craniofacial Molecular Biology, Herman Ostrow School of Dentistry, and Norris Comprehensive Cancer Center, , University of Southern California, ; Los Angeles, CA 90033 USA
                [5 ]Department of Medicine, Samuel Oschin Cancer Center, Cedars-Sinai Medical Center, ( https://ror.org/02pammg90) Los Angeles, CA 90048 USA
                [6 ]GRID grid.506261.6, ISNI 0000 0001 0706 7839, State Key Laboratory of Molecular Oncology, Center for Cancer Precision Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, , Chinese Academy of Medical Sciences and Peking Union Medical College, ; Beijing, 100021 China
                [7 ]Institutes of Physical Science and Technology, Anhui University, ( https://ror.org/05th6yx34) Hefei, 230601 China
                [8 ]Division of Otolaryngology-Head and Neck Surgery, Department of Surgery, Samuel Oschin Cancer Center, Cedars-Sinai Medical Center, ( https://ror.org/02pammg90) Los Angeles, CA 90048 USA
                [9 ]Department of otolaryngology, Keck School of Medicine, University of Southern California, ( https://ror.org/03taz7m60) Los Angeles, CA 90033 USA
                [10 ]Department of Thoracic Surgery, The First Affiliated Hospital of Anhui Medical University, ( https://ror.org/03t1yn780) Hefei, 230022 China
                [11 ]Hefei Cancer Hospital, Chinese Academy of Sciences, ( https://ror.org/034t30j35) Hefei, 230031 China
                [12 ]Cell-Bionomics Research Unit, Innovative Integrated Bio-Research Core, Institute for Frontier Science Initiative, Kanazawa University, ( https://ror.org/02hwp6a56) Kanazawa, Ishikawa Japan
                [13 ]Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, ( https://ror.org/00nyxxr91) Beijing, 100142 China
                [14 ]Department of Cancer Epidemiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, ( https://ror.org/02drdmm93) Beijing, 100021 China
                Author information
                http://orcid.org/0000-0002-5692-8903
                http://orcid.org/0000-0001-5423-509X
                http://orcid.org/0000-0003-2078-9056
                http://orcid.org/0000-0001-5839-9913
                http://orcid.org/0000-0002-1951-367X
                http://orcid.org/0000-0002-7432-8661
                Article
                46785
                10.1038/s41467-024-46785-9
                10954759
                38509096
                613f55e4-fc25-467b-bd1b-aa83a7eab51d
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 25 June 2023
                : 11 March 2024
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Funded by: FundRef https://doi.org/10.13039/501100003995, Natural Science Foundation of Anhui Province (Anhui Provincial Natural Science Foundation);
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                © Springer Nature Limited 2024

                Uncategorized
                transcriptional regulatory elements,immunosurveillance,tumour immunology
                Uncategorized
                transcriptional regulatory elements, immunosurveillance, tumour immunology

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