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Cytotoxic innate lymphoid cells sense cancer cell-expressed interleukin-15 to suppress human and murine malignancies (vol 23, pg 904, 2022)

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NATURE IMMUNOLOGY 2022年第8期23卷 1285-1285页

作者： Kansler, Emily R. Dadi, Saida Krishna, Chirag Nixon, Briana G. Stamatiades, Efstathios G. Liu, Ming Kuo, Fengshen Zhang, Jing Zhang, Xian Capistrano, Kristelle Blum, Kyle A. Weiss, Kate Kedl, Ross M. Cui, Guangwei Ikuta, Koichi Chan, Timothy A. Leslie, Christina S. Hakimi, A. Ari Li, Ming O. Immunology Program Memorial Sloan Kettering Cancer Center New York NY USA Louis V. Gerstner Jr. Graduate School of Biomedical Sciences Memorial Sloan Kettering Cancer Center New York NY USA Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Immunology and Microbial Pathogenesis Graduate Program Weill Cornell Graduate School of Medical Sciences Cornell University New York NY USA Human Oncology and Pathogenesis Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Immunology and Microbiology University of Colorado Anschutz Medical Campus Aurora CO USA Laboratory of Immune Regulation Department of Virus Research Institute for Frontier Life and Medical Sciences Kyoto University Kyoto Japan Department of Urology Memorial Sloan Kettering Cancer Center New York NY USA

Malignancy can be suppressed by the immune system. However, the classes of immunosurveillance responses and their mode of tumor sensing remain incompletely understood. Here, we show that although clear cell renal cell carcinoma (ccRCC) was infiltrated by exhaustion-phenotype CD8+ T cells that negatively correlated with patient prognosis, chromophobe RCC (chRCC) had abundant infiltration of granzyme A-expressing intraepithelial type 1 innate lymphoid cells (ILC1s) that positively associated with patient survival. Interleukin-15 (IL-15) promoted ILC1 granzyme A expression and cytotoxicity, and IL-15 expression in chRCC tumor tissue positively tracked with the ILC1 response. An ILC1 gene signature also predicted survival of a subset of breast cancer patients in association with IL-15 expression. Notably, ILC1s directly interacted with cancer cells, and IL-15 produced by cancer cells supported the expansion and anti-tumor function of ILC1s in a murine breast cancer model. Thus, ILC1 sensing of cancer cell IL-15 defines an immunosurveillance mechanism of epithelial malignancies.

关键词： Immunosurveillance Innate lymphoid cells Biomedicine general Immunology Infectious Diseases

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Publisher Correction: Ageing limits stemness and tumorigenesis by reprogramming iron homeostasis

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Nature 2025年 1页

作者： Xueqian Zhuang Simon Joost Zhuxuan Li Melissa Blum Klavdija Krause Selena Ding Matthew J. Bott Tuomas Tammela Qing Wang David T. Humphreys Yuna Landais Emily S. Wong Alexander Ferrena Deyou Zheng Yingqian Zhan Richard P. Koche Yang Zhao Ronan Chaligne Joo-Hyeon Lee Sebastian E. Carrasco Umeshkumar K. Bhanot Pekka Katajisto Yadira M. Soto-Feliciano Thomas Pisanic Tiffany Thomas Cancer Biology and Genetics Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Graduate School of Medical Science Weill Cornell Medicine New York NY USA Victor Chang Cardiac Research Institute Sydney New South Wales Australia School of Biotechnology and Biomolecular Sciences UNSW Sydney New South Wales Australia Institute for Clinical and Translational Research Albert Einstein College of Medicine New York NY USA Departments of Genetics Neurology and Neuroscience Albert Einstein College of Medicine New York NY USA Center for Epigenetics Research Memorial Sloan Kettering Cancer Center New York NY USA Department of Biomedical Engineering Johns Hopkins University Baltimore MD USA Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York NY USA Wellcome–MRC Cambridge Stem Cell Institute Jeffrey Cheah Biomedical Centre University of Cambridge Cambridge UK Department of Physiology Development and Neuroscience University of Cambridge Cambridge UK Laboratory of Comparative Pathology Weill Cornell Medicine Memorial Sloan Kettering Cancer Center and Rockefeller University New York NY USA Pathology Core Facility Department of Pathology Memorial Sloan Kettering Cancer Center New York NY USA Institute of Biotechnology HiLIFE University of Helsinki Helsinki Finland Department of Cell and Molecular Biology Karolinska Institute Stockholm Sweden Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland David H. Koch Institute for Integrative Cancer Research Massachusetts Institute of Technology Cambridge MA USA Department of Biology Massachusetts Institute of Technology Cambridge MA USA Institute for NanoBioTechnology Department of Oncology–Cancer Genetics and Epigenetics Johns Hopkins University Baltimore MD USA Department of Pathology and Cell Biology Columbia University College of Physicians and Surgeons New

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Improving protein-RNA interface prediction by combining sequence homology based method with a naive bayes classifier: Preliminary results 11

Improving protein-RNA interface prediction by combining sequ...

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2011 ACM Conference on Bioinformatics, computational biology and Biomedicine, ACM-BCB 2011

作者： Xue, Li C. Walia, Rasna EL-Manzalawy, Yasser Dobbs, Drena Honavar, Vasant Bioinformatics and Computational Biology Program Iowa State University Ames IA 50011 United States Department of Genetics Development and Cell Biology Iowa State University Ames IA 50011 United States Department of Computer Science Iowa State University Ames IA 50011 United States Department of Systems and Computer Engineering Al-Azhar University Cairo Egypt

ISBN: (纸本)9781450307963

Protein-RNA interactions play important roles in cellular processes like protein synthesis, RNA processing, and gene expression regulation. Reliable identification of the interfaces involved in RNA-protein interactions is essential for comprehending the mechanisms and the functional implications of these interactions and provides a valuable guide for rational drug discovery and design. Because the determination of 3D structures of protein-RNA complexes has various technical limitations and is typically costly, reliable in silico interface prediction methods that require only the sequence information are urgently needed. We present HomPRIP, a homologous sequence based method for predicting protein-RNA interfaces, based on our conservation analysis of protein-RNA interfaces. We test Hom-PRIP on a benchmark dataset of 199 proteins and compare it with the state-of-the-art protein-RNA interface prediction methods. Our results show that HomPRIP can reliably identify protein-RNA interface residues in 71% of test proteins with at least one putative sequence homolog passing the similarity thresholds of HomPRIP. Moreover, to facilitate predictions for proteins with no identified homologs, we develop HomPRIP-NB, a method combining the HomPRIP predictor and a Naive Bayes (NB) classifier trained using evolutionary information derived from alignments against the NCBI nr database. Our results suggest that HomPRIP-NB significantly outperforms the state-of-the-art machine learning methods for predicting protein-RNA interface residues. Copyright © 2011 ACM.

关键词： Proteins

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Microbial cancer immunotherapy reprograms hematopoiesis to enhance myeloid-driven anti-tumor immunity

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cancer Cell 2025年

作者： Andrew W. Daman Anthony C. Antonelli Gil Redelman-Sidi Lucinda Paddock Shireen Khayat Mythili Ketavarapu Jin Gyu Cheong Leonardo F. Jurado Anna Benjamin Song Jiang Dughan Ahimovic Victoria R. Lawless Michael J. Bale Oleg Loutochin Victor A. McPherson Maziar Divangahi Rachel E. Niec Dana Pe’er Eugene Pietzak Steven Z. Josefowicz Michael S. Glickman Immunology and Microbial Pathogenesis Program Graduate School of Medical Sciences Weill Cornell Medicine New York NY USA Department of Pathology and Laboratory Medicine Division of Cell and Cancer Pathobiology Weill Cornell Medicine New York NY USA Immunology Program Sloan Kettering Institute New York NY USA Infectious Diseases Service Department of Medicine Memorial Sloan Kettering Cancer Center New York NY USA Howard Hughes Medical Institute Chevy Chase MD USA Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York NY USA Pharmacology Program Weill Cornell Medicine Graduate School of Medical Sciences New York NY USA Department of Medicine Department of Pathology Department of Microbiology & Immunology McGill University Health Centre McGill International TB Centre Meakins-Christie Laboratories McGill University Montreal QC Canada Urology Service Department of Surgery Memorial Sloan Kettering Cancer Center New York NY USA Department of Urology Jewish General Hospital McGill University Montreal QC Canada Human Oncology and Pathogenesis Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York NY USA

Mycobacterium bovis Bacillus Calmette-Guérin (BCG) is the vaccine against tuberculosis and an immunotherapy for bladder cancer. When administered intravenously, BCG reprograms bone marrow hematopoietic stem and progenitor cells (HSPCs), leading to heterologous protection against infections. Whether HSPC reprogramming contributes to the anti-tumor effects of BCG administered into the bladder is unknown. We demonstrate that BCG administered in the bladder colonizes the bone marrow and, in both mice and humans, reprograms HSPCs to alter and amplify myelopoiesis. BCG-reprogrammed HSPCs are sufficient to confer augmented anti-tumor immunity through production of neutrophils, monocytes, and dendritic cells that broadly remodel the tumor microenvironment, drive T cell-dependent anti-tumor responses, and synergize with checkpoint blockade. We conclude that bladder BCG acts systemically through hematopoiesis, highlighting the broad potential of HSPC reprogramming to enhance the innate drivers of T cell-dependent tumor immunity.

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Review: Precision medicine and driver mutations: computational methods, functional assays and conformational principles for interpreting cancer drivers (vol 15, e1006658, 2019)

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PLOS computational biology 2019年第6期15卷 e1006658-e1006658页

作者： Nussinov, Ruth Jang, Hyunbum Tsai, Chung-Jung Cheng, Feixiong Computational Structural Biology Section Basic Science Program Frederick National Laboratory for Cancer Research National Cancer Institute Frederick Maryland United States of America Department of Human Molecular Genetics and Biochemistry Sackler School of Medicine Tel Aviv University Tel Aviv Israel Genomic Medicine Institute Lerner Research Institute Cleveland Clinic Cleveland Ohio United States of America Department of Molecular Medicine Cleveland Clinic Lerner College of Medicine Case Western Reserve University Cleveland Ohio United States of America

At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor’s genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses—all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community.

关键词： INDIVIDUALIZED medicine cancer genetics MUTATION (biology) ONCOLOGY cancer treatment EXOMES PHARMACOLOGY TUMOR genetics

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Tegavivint triggers TECR-dependent nonapoptotic cancer cell death

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Nature chemical biology 2025年 2025 May 26页

作者： Logan Leak Ziwei Wang Alby J Joseph Brianna Johnson Alyssa A Chan Cassandra M Decosto Leslie Magtanong Pin-Joe Ko Weaverly Colleen Lee Joan Ritho Sophia Manukian Alec Millner Shweta Chitkara Jennifer J Salinas Rachid Skouta Matthew G Rees Melissa M Ronan Jennifer A Roth Chad L Myers Jason Moffat Charles Boone Steven J Bensinger David A Nathanson G Ekin Atilla-Gokcumen Everett J Moding Scott J Dixon Department of Biology Stanford University Stanford CA USA. Department of Radiation Oncology Stanford University School of Medicine Stanford CA USA. Department of Chemistry University at Buffalo The State University of New York Buffalo NY USA. Department of Molecular and Medical Pharmacology University of California Los Angeles Los Angeles CA USA. Department of Chemistry University of Massachusetts Amherst Amherst MA USA. Department of Biology University of Massachusetts Amherst Amherst MA USA. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Computer Science and Engineering Bioinformatics and Computational Biology Graduate Program University of Minnesota-Twin Cities Minneapolis MN USA. Program in Genetics & Genome Biology The Hospital for Sick Children Toronto Ontario Canada. Department of Molecular Genetics University of Toronto Toronto Ontario Canada. Donnelly Centre University of Toronto Toronto Ontario Canada. RIKEN Center for Sustainable Resource Science Saitama Japan. Department of Microbiology Immunology and Molecular Genetics University of California Los Angeles Los Angeles CA USA. UCLA Lipidomics Laboratory University of California Los Angeles Los Angeles CA USA. Jonsson Comprehensive Cancer Center David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA. Department of Biology Stanford University Stanford CA USA. sjdixon@stanford.edu.

Small molecules that induce nonapoptotic cell death are of fundamental mechanistic interest and may be useful to treat certain cancers. Here we report that tegavivint, a drug candidate undergoing human clinical trials, can activate a unique mechanism of nonapoptotic cell death in sarcomas and other cancer cells. This lethal mechanism is distinct from ferroptosis, necroptosis and pyroptosis and requires the lipid metabolic enzyme trans-2,3-enoyl-CoA reductase (TECR). TECR is canonically involved in the synthesis of very-long-chain fatty acids but appears to promote nonapoptotic cell death in response to CIL56 and tegavivint via the synthesis of the saturated long-chain fatty acid palmitate. These findings outline a lipid-dependent nonapoptotic cell death mechanism that can be induced by a drug candidate currently being tested in humans.

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Counteracting lineage-specific transcription factor network finely tunes lung adeno-to-squamous transdifferentiation through remodeling tumor immune microenvironment

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National Science Review 2023年第4期10卷 37-55页

作者： Shijie Tang Yun Xue Zhen Qin Zhaoyuan Fang Yihua Sun Chongzhe Yuan Yunjian Pan Yue Zhao Xinyuan Tong Jian Zhang Hsinyi Huang Yuting Chen Liang Hu Dasong Huang Ruiqi Wang Weiguo Zou Yuan Li Roman K.Thomas Andrea Ventura Kwok-Kin Wong Haiquan Chen Luonan Chen Hongbin Ji State Key Laboratory of Cell Biology Shanghai Institute of Biochemistry and Cell BiologyCenter for Excellence in Molecular Cell ScienceChinese Academy of Sciences College of Life Sciences University of Chinese Academy of Sciences Zhejiang University-University of Edinburgh Institute Zhejiang University School of Medicine The Second Affiliated Hospital Zhejiang University School of Medicine Department of Thoracic Surgery Fudan University Shanghai Cancer Center Department of Oncology Shanghai Medical CollegeFudan University School of Life Science and Technology Shanghai Tech University Department of Mathematics Shanghai University Department of Translational Genomics Center of Integrated Oncology Cologne-BonnMedical FacultyUniversity of Cologne Department of Pathology University Hospital Cologne Cancer Biology and Genetics Program Memorial Sloan Kettering Cancer Center Laura and Isaac Perlmutter Cancer Center New York University Langone Medical Center Key Laboratory of Systems Biology Shanghai Institutes for Biological SciencesChinese Academy of Sciences School of Life Science Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of Sciences

Human lung adenosquamous cell carcinoma(LUAS), containing both adenomatous and squamous pathologies, harbors strong plasticity and is significantly associated with poor prognosis. We established an up-to-date comprehensive genomic and transcriptomic landscape of LUAS in 109 Chinese specimens and demonstrated LUAS development via adeno-to-squamous transdifferentiation. Unsupervised transcriptomic clustering and dynamic network biomarker analysis identified an inflammatory subtype as the critical transition stage during LUAS development. Dynamic dysregulation of the counteracting lineage-specific transcription factors(TFs), containing adenomatous TFs NKX2-1 and FOXA2, and squamous TFs TP63 and SOX2, finely tuned the lineage transition via promoting CXCL3/5-mediated neutrophil infiltration. Genomic clustering identified the most malignant subtype featured with STK11-inactivation, and targeting LSD1 through genetic deletion or pharmacological inhibition almost eradicated STK11-deficient lung tumors. These data collectively uncover the comprehensive molecular landscape, oncogenic driver spectrum and therapeutic vulnerability of Chinese LUAS.

关键词： LUAS ALK fusion counteracting TF regulatory network CXCL3/CXCL5 LSD1

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HBO1 functions as an epigenetic barrier to hepatocyte plasticity and reprogramming during liver injury

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Cell Stem Cell 2025年

作者： Wei-Chien Yuan Andrew S. Earl Sai Ma Karel Alcedo Jacquelyn O. Russell Fabiana M. Duarte Yen-Ting Chu Pei-Chi Chang Hsin-Yi Chen Hsin-Hui Chi Qian Zhu Alejo E. Rodriguez-Fraticelli Sachin H. Patel Yu-Ru Lee Jason D. Buenrostro Fernando D. Camargo Stem Cell Program Boston Children’s Hospital Boston MA 02115 USA Department of Stem Cell and Regenerative Biology Harvard University Cambridge MA 02138 USA Department of Life Sciences and Institute of Genome Sciences National Yang Ming Chiao Tung University Taipei 112304 Taiwan Cancer and Immunology Research Center National Yang Ming Chiao Tung University Taipei 112304 Taiwan Broad Institute of MIT and Harvard Cambridge MA 02142 USA Department of Biology Massachusetts Institute of Technology Cambridge MA 02142 USA Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY 10026 USA Institute of Biomedical Sciences Academia Sinica Taipei 115201 Taiwan Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health Boston MA 02215 USA Lester Sue Smith Breast Center Department of Molecular and Human Genetics 1 Baylor Plaza Houston TX 77030 USA

Hepatocytes can reprogram into biliary epithelial cells (BECs) during liver injury, but the underlying epigenetic mechanisms remain poorly understood. Here, we define the chromatin dynamics of this process using single-cell ATAC-seq and identify YAP/TEAD activation as a key driver of chromatin remodeling. An in vivo CRISPR screen highlights the histone acetyltransferase HBO1 as a critical barrier to reprogramming. HBO1 is recruited by YAP to target loci, where it promotes histone H3 lysine 14 acetylation (H3K14ac) and engages the chromatin reader zinc-finger MYND-type containing 8 (ZMYND8) to suppress YAP/TEAD-driven transcription. Loss of HBO1 accelerates chromatin remodeling, enhances YAP binding, and enables a more complete hepatocyte-to-BEC transition. Our findings position HBO1 as an epigenetic brake that restrains YAP-mediated reprogramming, suggesting that targeting HBO1 may enhance hepatocyte plasticity for liver regeneration.

关键词： HBO1 Hippo-YAP epigenetic regulation hepatocyte reprogramming in vivo CRISPR screen

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Retraction notice to "Efficacy of Sunitinib and Radiotherapy in Genetically Engineered Mouse Model of Soft-Tissue Sarcoma" Int J Radiat Oncol Biol Phys, 2009;74(4), pp 1207-1216

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International journal of radiation oncology, biology, physics 2025年第2期122卷 524页

作者： Sam S Yoon Lars Stangenberg Yoon-Jin Lee Courtney Rothrock Jonathan M Dreyfuss Kwan-Hyuck Baek Peter R Waterman G Petur Nielsen Ralph Weissleder Umar Mahmood Peter J Park Tyler Jacks Rebecca D Dodd Carolyn J Fisher Sandra Ryeom David G Kirsch Department of Surgery Division of Surgical Oncology Massachusetts General Hospital and Harvard Medical School Boston MA. Center for Molecular Imaging Research Department of Radiology Massachusetts General Hospital and Harvard Medical School Boston MA. Harvard-Partners Center for Genetics and Genomics Brigham and Women's Hospital and Harvard Medical School Boston MA. Vascular Biology Program and Department of Surgery Boston Children's Hospital and Harvard Medical School Boston MA. Center for Molecular Imaging Research Department of Radiology Massachusetts General Hospital and Harvard Medical School Boston MA Center for Systems Biology Massachusetts General Hospital and Harvard Medical School Boston MA. Department of Pathology Massachusetts General Hospital and Harvard Medical School Boston MA. Center for Cancer Research Department of Biology and Howard Hughes Medical Institute Massachusetts Institute of Technology Boston MA. Departments of Radiation Oncology and Pharmacology and Cancer Biology Duke University School of Medicine Durham NC.

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Evaluating methods for the prediction of cell-type-specific enhancers in the mammalian cortex

Cell Genomics

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Cell Genomics 2025年 100879页

作者： Nelson J. Johansen Niklas Kempynck Nathan R. Zemke Saroja Somasundaram Seppe De Winter Marcus Hooper Deepanjali Dwivedi Ruchi Lohia Fabien Wehbe Bocheng Li Darina Abaffyová Ethan J. Armand Julie De Man Eren Can Ekşi Nikolai Hecker Gert Hulselmans Vasilis Konstantakos David Mauduit John K. Mich Gabriele Partel Trygve E. Bakken Allen Institute for Brain Science Seattle WA 98109 USA VIB Center for AI & Computational Biology VIB-KU Leuven Center for Brain and Disease Research & KU Leuven Department of Human Genetics Leuven Belgium Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA 92093 USA Physiology Department and Donnelly Centre for Cellular and Biomolecular Research University of Toronto Toronto ON Canada Maisonneuve-Rosemont Hospital Research Centre University of Montreal Montreal QC Canada School of Life Sciences Westlake University Hangzhou Zhejiang China Bioinformatics and Systems Biology Program University of California San Diego La Jolla CA 92093 USA

Identifying cell-type-specific enhancers is critical for developing genetic tools to study the mammalian brain. We organized the “Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics” to evaluate machine learning and feature-based methods for nominating enhancer sequences targeting mouse cortical cell types. Methods were assessed using in vivo data from hundreds of adeno-associated virus (AAV)-packaged, retro-orbitally delivered enhancers. Open chromatin was the strongest predictor of functional enhancers, while sequence models improved prediction of non-functional enhancers and identified cell-type-specific transcription factor codes to inform in silico enhancer design. This challenge establishes a benchmark for enhancer prioritization and highlights computational and molecular features critical for identifying functional cortical enhancers, advancing efforts to map and manipulate gene regulation in the mammalian cortex.

关键词： enhancer-AAV DNA sequence model TF codes single-cell multiomics cortex prediction benchmark cross-species ATAC-seq

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