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Immunometabolism:a new dimension in immunotherapy resistance

Frontiers of Medicine 2023年第4期17卷 585-616页

作者： Chaoyue Xiao Wei Xiong Yiting Xu Ji’an Zou Yue Zeng Junqi Liu Yurong Peng Chunhong Hu Fang Wu Department of Oncology The Second Xiangya HospitalCentral South UniversityChangsha 410011China NHC Key Laboratory of Carcinogenesis and Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education Cancer Research InstituteCentral South UniversityChangsha 410078China Xiangya School of Medicine Central South UniversityChangsha 410013China Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre Changsha 410011China Hunan Key Laboratory of Early Diagnosis and Precision Therapy in Lung Cancer The Second Xiangya HospitalCentral South UniversityChangsha 410011China Hunan Key Laboratory of Tumor Models and Individualized Medicine The Second Xiangya HospitalCentral South UniversityChangsha 410011China

Immune checkpoint inhibitors(ICIs)have demonstrated unparalleled clinical responses and revolutionized the paradigm of tumor treatment,while substantial patients remain unresponsive or develop resistance to ICIs as a single agent,which is traceable to cellular metabolic *** dysregulated metabolism has long been adjudged as a hallmark of tumor,it is now increasingly accepted that metabolic reprogramming is not exclusive to tumor cells but is also characteristic of ***,people used to pay more attention to the effect of tumor cell metabolism on immunocytes,but in practice immunocytes interact intimately with their own metabolic function in a way that has never been realized before during their activation and differentiation,which opens up a whole new frontier called *** metabolic intervention for tumor-infiltrating immunocytes could offer fresh opportunities to break the resistance and ameliorate existing ICI immunotherapy,whose crux might be to ascertain synergistic combinations of metabolic intervention with ICIs to reap synergic benefits and facilitate an adjusted anti-tumor immune ***,we elaborate potential mechanisms underlying immunotherapy resistance from a novel dimension of metabolic reprogramming in diverse tumor-infiltrating immunocytes,and related metabolic intervention in the hope of offering a reference for targeting metabolic vulnerabilities to circumvent immunotherapeutic resistance.

关键词： immune cell immunometabolism metabolic reprogramming immunotherapy resistance tumor microenvironment immune checkpoint inhibitor

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P4.15D.04 Association Between Emotional Distress and Immunotherapy Response in Advanced NSCLC (STRESS-LUNG-1): Biomarkers Exploratory Analyses

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Journal of Thoracic Oncology 2024年第10期19卷 S417-S417页

作者： F. Wu Y. Zeng J. Zhou Z. Qiu C. Deng F. Ma C. Xia A. Liang Y. Peng S. Wang S. Yao J. Liu Y. Zhang X. Zhang X. Wang X. Liu C. Hu The Second Xiangya Hospital of Central South University Changsha/CN Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre Changsha/CN Hunan Key Laboratory of Tumor Models and Individualized Medicine The Second Xiangya Hospital Central South University Changsha/CN Hunan Key Laboratory of Early Diagnosis and Precision Therapy in Lung Cancer The Second Xiangya Hospital Central South University Changsha/CN

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P4.07E.10 The Impact of PD-1/PD-L1 Inhibitor on GGN Lesion: An Exploratory and Retrospective Study

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Journal of Thoracic Oncology 2024年第10期19卷 S382-S383页

作者： F. Wu J. Liu L. He X. Liu Y. Zeng S. Shi Y. Peng The Second Xiangya Hospital of Central South University Changsha/CN Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre Changsha/CN Hunan Key Laboratory of Tumor Models and Individualized Medicine The Second Xiangya Hospital Central South University Changsha/CN Hunan Key Laboratory of Early Diagnosis and Precision Therapy in Lung Cancer The Second Xiangya Hospital Central South University Changsha/CN Graduate School of Peking Union Medical College Chinese Academy of Medical Sciences Beijing/CN

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The role of 4D flow MRI in deep vein thrombosis research

Meta-Radiology

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Meta-Radiology 2025年第1期3卷

作者： Li, Meizhi Wu, Shangjie Liang, Xiao Gao, Chuanqi Hu, Muhua Chen, Zhu He, Pei Jia, Tingting Xiong, Li Department of Pulmonary and Critical Care Medicine The Second Xiangya Hospital of Central South University Changsha China Department of Medical Administration The Second Xiangya Hospital of Central South University Changsha China Clinical Medical Research Center for Pulmonary and Critical Care Medicine in Hunan Province Changsha China Hunan Research Centre for Evidence-based Medicine The Second Xiangya Hospital of Central South University Changsha China Department of Biomedical Engineering School of Basic Medical Science Central South University Changsha China Department of Radiology Second Xiangya Hospital Central South University Changsha China Hunan Key Laboratory for Super Microstructure and Ultrafast Process School of Physics and Electronics Central South University Changsha China National Engineering Research Center for Medical Big Data Application Technology and Big Data Institute Central South University Changsha China General Surgery Department of Second Xiangya Hospital Central South University Changsha China General Surgery Intelligent Healthcare Division of Clinical Medical Research Center of Hunan Province Changsha China

Four-dimensional (4D) flow Magnetic Resonance Imaging (MRI) technology has emerged as a valuable tool in angiography, offering unique insights into the hemodynamics and flow patterns. This research aims to explore the role of 4D flow MRI in advancing our understanding of Deep Vein Thrombosis (DVT), covering its applications in diagnosing, characterizing and mechanism of DVT, as well as its potential for guiding treatment strategies. The qualitative and quantitative information provided by 4D flow MRI enables a comprehensive assessment of blood flow in different vascular regions, shedding light on the relationship between hemodynamic changes and the onset and progression of vascular diseases. Nevertheless, most quantitative research findings for 4D hemodynamic indicators are lacking, and their use is mainly limited to examining arterial conditions. More exploration will be necessary to determine their applicability in studying venous vessels. © 2025 The Authors

关键词： 4D flow MRI Deep vein thrombosis Image analysis algorithms Noninvasive imaging

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101P Circulating tumor DNA minimal residual disease predicts the risk of progression after long-term response to first-line immunotherapy in advanced NSCLC

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Annals of Oncology 2024年 35卷 S254-S254页

作者： F. Wu Y. Peng Y. Zeng Z. Qiu F. Ma L. Zhu C. Zhou X. Pu L. Zhang Y. Zhou J. Weng S. Zengmei J. Yu Z. Zhou R. Meng Q. Bu P. Liu J. Li S. Chen L. Cui Department of Oncology The Second Xiangya Hospital Central South University Changsha China Department of Radiation Oncology Stanford University Stanford CA USA Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre Changsha China Pneumology The Second Xiangya Hospital of Central South University Changsha China Respiratory Medicine State Key Laboratory of Respiratory Diseases - The First Affiliated Hospital of Guangzhou Medical University Guangzhou China Thoracic Medicine Department Hunan Cancer Hospital Changsha China Thoracic Department Hunan Cancer Hospital Changsha China Department of Respiratory and Critical Care Medicine The Third Xiangya Hospital Central South University Changsha China Department of Oncology Yueyang 1st People's Hospital Yueyang China Department of Hematology and Oncology The Third Hospital of Changsha Changsha China Department of Oncology Zhangjiajie People's Hospital Zhangjiajie China Department of Oncology The Second People's Hospital of Huaihua Huaihua China Department of Oncology Cancer Center Union Hospital Tongji Medical College Huazhong University of Science and Technology (HUST) Institute of Radiation Oncology Union Hospital Tongji Medical College HUST Hubei Key Laboratory of Precision Radiation Oncology Wuhan China Department of Oncology The First Affiliated Hospital of Guangxi Medical University Nanning China Respiratory Medicine The First Hospital of Changsha City Changsha China Department of Oncology Xiangya Changde Hospital Changde People’s Republic of China Changde China Department of Oncology Loudi Central Hospital Loudi China Medicine Geneplus-Beijing Institute Beijing China

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DPHL:A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery

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Genomics, Proteomics & Bioinformatics 2020年第2期18卷 104-119页

作者： Tiansheng Zhu Yi Zhu Yue Xuan Huanhuan Gao Xue Cai Sander R.Piersma Thang V.Pham Tim Schelfhorst Richard R.G.D.Haas Irene V.Bijnsdorp Rui Sun Liang Yue Guan Ruan Qiushi Zhang Mo Hu Yue Zhou Winan J.Van Houdt Tessa Y.S.Le Large Jacqueline Cloos Anna Wojtuszkiewicz Danijela Koppers-Lalic Franziska Bottger Chantal Scheepbouwer Ruud H.Brakenhoff Geert J.L.H.van Leenders Jan N.M.Ijzermans John W.M.Martens Renske D.M.Steenbergen Nicole C.Grieken Sathiyamoorthy Selvarajan Sangeeta Mantoo Sze S.Lee Serene J.Y.Yeow Syed M.F.Alkaff Nan Xiang Yaoting Sun Xiao Yi Shaozheng Dai Wei Liu Tian Lu Zhicheng Wu Xiao Liang Man Wang Yingkuan Shao Xi Zheng Kailun Xu Qin Yang Yifan Meng Cong Lu Jiang Zhu Jin'e Zheng Bo Wang Sai Lou Yibei Dai Chao Xu Chenhuan Yu Huazhong Ying Tony K.Lim Jianmin Wu Xiaofei Gao Zhongzhi Luan Xiaodong Teng Peng Wu Shi'ang Huang Zhihua Tao Narayanan G.Iyer Shuigeng Zhou Wenguang Shao Henry Lam Ding Ma Jiafu Ji Oi L.Kon Shu Zheng Ruedi Aebersold Connie R.Jimenez Tiannan Guo Zhejiang Provincial Laboratory of Life Sciences and Biomedicine Westlake UniversityHangzhou 310024China Key Laboratory of Structural Biology of Zhejiang Province School of Life SciencesWestlake UniversityHangzhou 310024China Institute of Basic Medical Sciences Westlake Institute for Advanced StudyHangzhou 310024China School of Computer Science Shanghai Key Laboratory of Intelligent Information ProcessingFudan UniversityShanghai 200433China Thermo Fisher Scientific(BREMEN)GmbH Bremen 28195Germany OncoProteomics Laboratory Department of Medical OncologyVU University Medical CenterVU UniversityAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamUrologyCancer Center AmsterdamAmsterdam 1011The Netherlands Thermo Fisher Scientific Shanghai 201206China The Netherlands Cancer Institute Surgical OncologyAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamSurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamPediatric Oncology/HematologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamHematologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamMedical OncologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamNeurosurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamPathologyCancer Center AmsterdamAmsterdam 1011The Netherlands Amsterdam UMC Vrije Universiteit AmsterdamOtolaryngology/Head and Neck SurgeryCancer Center AmsterdamAmsterdam 1011The Netherlands Erasmus MC University Medical Center PathologyRotterdam 1016LVThe Netherlands Erasmus MC University Medical Center SurgeryRotterdam 1016LVThe Netherlands Erasmus MC University Medical Center Medical OncologyRotterdam 1016LVThe Netherlands Department of Anatomical Pathology Singapore General HospitalSingapore 169608Singapore Division of Medical Scie

To address the increasing need for detecting and validating protein biomarkers in clinical specimens,mass spectrometry(MS)-based targeted proteomic techniques,including the selected reaction monitoring(SRM),parallel reaction monitoring(PRM),and massively parallel dataindependent acquisition(DIA),have been *** optimal performance,they require the fragment ion spectra of targeted peptides as prior *** this report,we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue *** build the spectral resource,we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on *** then applied the workflow to generate DPHL,a comprehensive DIA pan-human library,from 1096 data-dependent acquisition(DDA)MS raw files for 16 types of cancer *** extensive spectral resource was then applied to a proteomic study of 17 prostate cancer(PCa)***,PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was *** a second application,the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma(DLBCL)patients and 18 healthy control *** expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by *** data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker *** is freely accessible at https://***/page/***?id=IPX0001400000.

关键词： data-independent acquisition Parallel reaction monitoring Spectral library Prostate cancer Diffuse large B cell lymphoma

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