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全部共 21 篇
临床队列临床研究Nature

Divergent genomic evolution in astrocytomas and oligodendrogliomas.

0 次引用趋势数据不足

一项发表于《自然》的研究利用全基因组和全外显子组测序,对胶质瘤纵向分析联盟收集的183例IDH突变型胶质瘤患者的纵向肿瘤标本进行了分析,多数原发手术样本组织学分级为2级(星形细胞瘤73%,少突胶质细胞瘤93%)。研究验证了肿瘤进展的已知基因组标志物,包括超突变及CDKN2A/B纯合缺失,并发现星形细胞瘤与少突胶质细胞瘤的演化轨迹存在差异:复发性少突胶质细胞瘤新获得PI3K和NOTCH1突变,与肿瘤突变负荷增加相关;复发性星形细胞瘤则获得局灶性癌基因扩增和CDKN2A/B纯合缺失,与染色体失衡增加相关,并伴随染色体碎裂和全基因组加倍等标志。两类肿瘤均出现获得性改变与全基因组变化的趋同及患者预后恶化,提示治疗难治性克隆被选择。替莫唑胺治疗与SBS11和SBS119突变特征相关,放疗相关ID8特征仅在星形细胞瘤中增加。研究表明,两类肿瘤基因组以不同方式适应肿瘤进展和治疗的选择压力。

为什么值得关注

编辑短评

该研究基于183例IDH突变胶质瘤纵向标本,通过全基因组/外显子测序揭示星形细胞瘤与少突胶质细胞瘤在进展和治疗压力下的基因组演化差异,并验证已知进展标志物。样本量较大、纵向设计及治疗相关突变特征分析增强了发现的可信度。但摘要未报告具体效应量、统计显著性及独立验证队列,结论的普适性仍需进一步确认。

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完整作者

Tamrin Chowdhury、C Mircea S Tesileanu、Emre Kocakavuk、Kevin C Johnson、Joo Ho Lee、Zeynep Erson-Omay、Chaewon Heo、Kenneth Aldape、Samirkumar B Amin、Kevin J Anderson、David M Ashley、Floris P Barthel、Jill S Barnholtz-Sloan、Daniel J Brat、Andrew R Brodbelt、Ana Valeria Castro、Elizabeth B Claus、Jennifer M Connelly、Joseph F Costello、Indrani Datta、Carol Elliott、Gaetano Finocchiaro、Pim J French、Hui K Gan、Luciano Garofano、Padmaja L Ghospurkar、Anna Golebiewska、Pranav S Gundla、Beth Hermes、Chibo Hong、Youri Hoogstrate、Craig Horbinski、Jason T Huse、Antonio Iavarone、Cihat Karadag、Mustafa Khasraw、Mathilde C M Kouwenhoven、Peter S LaViolette、Kay Li、Allison Lowman、Katy McCortney、Hyo-Eun Moon、Nader Sanai、MacLean P Nasrallah、H K Ng、D Ryan Ormond、Bethany Kwan、Marta Padovan、Sun Ha Paek、Laila M Poisson、Sushant Puri、Erica Shen、Shwetal Mehta、Andrew E Sloan、Wies R Vallentgoed、Erwin G Van Meir、Rachael Vaubel、Taylor E Wade、Annemiek M E Walenkamp、Colin Watts、Tobias Weiss、Michael Weller、Pieter Wesseling、Kerryn Westcott、Bart A Westerman、Gordon Y Ye、W K Alfred Yung、GLASS Consortium、Frederick S Varn、Roel G W Verhaak

作者机构

  • Department of Neurosurgery, Yale University, New Haven, CT, USA.
  • Department of Hematology and Stem Cell Transplantation, West German Cancer Center (WTZ), National Center for Tumor Diseases (NCT) West, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
  • Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, South Korea.
  • Cancer Research Institute, Seoul National University College of Medicine, Seoul, South Korea.
  • National Institutes of Health, Bethesda, MD, USA.
  • The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
  • Preston Robert Tisch Brain Tumor Center at Duke University, Durham, NC, USA.
  • Translational Genomics Research Institute, Phoenix, AZ, USA.
  • National Cancer Institute, Bethesda, MD, USA.
  • Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • Walton Centre NHS Foundation Trust, Liverpool, UK.
  • Hermelin Brain Tumor Center, Department of Neurosurgery, Henry Ford Health, Detroit, MI, USA.
  • Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
  • Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA.
  • Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
  • Department of Neurosurgery, University of California, San Francisco, San Francisco, CA, USA.
  • St Joseph's Hospital and Medical Center, Phoenix, AZ, USA.
  • Department of Neurology, IRCCS Ospedale San Raffaele, Milan, Italy.
  • Department of Neurology, Erasmus University Medical Centre Rotterdam, Rotterdam, The Netherlands.
  • Cancer Therapies and Biology Laboratory, Olivia Newton-John Cancer Research Institute, Austin Health, Melbourne, Victoria, Australia.
  • Department of Public Health Sciences, Division of Biostatistics and Bioinformatics, Miller School of Medicine, University of Miami, Miami, FL, USA.
  • Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, USA.
  • NORLUX Neuro-Oncology Laboratory, Department of Cancer Research, Luxembourg Institute of Health, Luxembourg, Luxembourg.
  • Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  • University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, FL, USA.
  • Department of Neurosurgery, Duke University Medical Center, Durham, NC, USA.
  • Department of Neurology, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
  • Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, USA.
  • Department of Pathology, Prince of Wales Hospital, Hong Kong, China.
  • Department of Neurosurgery, Cancer Research Institute, Hypoxia/Ischemia Disease Institute, Seoul National University, Seoul, Republic of Korea.
  • Ivy Brain Tumor Center at the Barrow Neurological Institute, Phoenix, AZ, USA.
  • Glioblastoma Translational Center of Excellence, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Department of Neurosurgery, University of Colorado Anschutz School of Medicine, Aurora, CO, USA.
  • Department of Emergency Medicine, University of Colorado Anschutz School of Medicine, Aurora, CO, USA.
  • Advanced Institutes of Convergence Technology, Seoul National University, Suwon-si, Republic of Korea.
  • Oregon Health & Science University, Portland, OR, USA.
  • Neurological Institute, Premier Health and Wright State University School of Medicine, Dayton, OH, USA.
  • University of Alabama at Birmingham (UAB), Birmingham, AL, USA.
  • Division of Anatomic Pathology, Mayo Clinic, Rochester, MN, USA.
  • Department of Medical Oncology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Department of Cancer Genome Sciences, University of Birmingham, Birmingham, UK.
  • Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland.
  • VUmc, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
  • Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
  • Department of Neurosurgery, VUmc, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
  • University of California, San Diego, La Jolla, CA, USA.
  • Department of Neuro-Oncology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA. frederick.varn@jax.org.
  • Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, USA. frederick.varn@jax.org.
  • Institute for Systems Genomics, University of Connecticut, Storrs, CT, USA. frederick.varn@jax.org.
  • Department of Neurosurgery, Yale University, New Haven, CT, USA. roel.verhaak@yale.edu.

技术路线

['数据/样本:183例IDH突变型胶质瘤患者的纵向收集肿瘤标本(来自GLASS联盟)', '分析:全基因组测序和全外显子组测序,表征纵向标本的遗传驱动因素;验证已知进展基因组标志物(超突变、CDKN2A/B纯合缺失),发现区分星形细胞瘤与少突胶质细胞瘤演化轨迹的遗传改变;分析获得性改变、全基因组变化与患者结局的趋同;关联治疗(替莫唑胺、放疗)与突变特征', '验证:验证已知基因组标志物(超突变和CDKN2A/B纯合缺失)']

最近 5 个完整年度引用趋势

0110202102022020230202402025

不含 2026 年,仅展示最近 5 个完整年度。

数据来源:openalex更新时间:2026/10/30 06:02
公共数据库临床研究Frontiers in genetics

The immunogenicity control axis: a multi-omics framework for integrating epigenetic, DNA damage response, and immune states in cancer.

暂无引用数据

免疫治疗已改变癌症治疗格局,但治疗反应仍存在异质性,仅凭免疫相关生物标志物难以完全解释。为此,研究提出“免疫原性控制轴”(ICA)这一可检验的多组学框架,整合表观遗传调控、DNA损伤应答(DDR)与免疫活性三个互补维度。其核心假设是:表观遗传许可性影响免疫相关转录与抗原呈递,DDR相关基因组过程促进抗原变异,这些肿瘤内在特征与免疫状态相互作用,共同塑造肿瘤免疫可见性。为便于定量检验,ICA通过独立构建的表观遗传、DDR和免疫评分标准化后整合为复合ICA评分。以宫颈癌为初步疾病背景,基于TCGA-CESC数据的分析对ICA相关分子状态及预后关系进行了探索性评估,并以模拟分析说明特定分析流程。该框架进一步扩展至扰动分析,利用CMap/LINCS转录特征和网络信息优先筛选可能逆转ICA相关分子状态的候选天然化合物。上述计算分析旨在生成假设,而非生物学或临床验证。ICA提供了一个可证伪框架,用于检验表观遗传、DDR与免疫信息的协同能否捕捉超出单一分子维度的肿瘤免疫原性变异,并为后续实验验证的扰动假设提供优先级。

为什么值得关注

暂未整理

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完整作者

暂未整理

作者机构

暂未整理

技术路线

暂未整理

最近 5 个完整年度引用趋势

暂无引用数据

数据来源:暂未标注更新时间:暂无更新时间
合成生物学综述Frontiers in genome editing

Engineering next-generation CAR-NK cells for hematological malignancies: genome editing, synthetic biology, and precision immunotherapy.

暂无引用数据

嵌合抗原受体(CAR)免疫治疗已改变肿瘤治疗格局,CAR-T细胞率先取得临床成功,但其严重毒性、自体制造复杂性及抗原丢失后高复发率促使人们开发CAR-NK等替代效应平台。CAR-NK细胞兼具抗原导向细胞毒作用与自然杀伤细胞固有抗肿瘤功能,是有望更安全、更易获得的现货型治疗策略。然而,其临床疗效受限于体内持久性短、迁移与实体瘤浸润不足、对肿瘤微环境免疫抑制高度敏感及肿瘤异质性驱动的抗原逃逸等生物学障碍,并面临细胞来源差异、大规模扩增能力有限、体外功能耗竭和缺乏标准化生产方案等技术瓶颈。为此,基因组工程、系统生物学和计算建模的进展提供了解决路径。靶向抑制性检查点和持久性程序的基因组编辑策略至关重要,但增强持久性需严格保障措施以降低组成性信号或基因组不稳定性带来的毒性风险,因此下一代CAR-NK工程需平衡延长寿命、强效细胞毒性与安全性。多组学方法有助于深入表征CAR-NK功能状态及肿瘤-免疫相互作用,人工智能指导的工程可整合高维生物学与制造数据,优化受体设计、预测治疗性能并加速转化流程。这些创新共同推动CAR-NK细胞向可编程、能动态感知并响应肿瘤演变的细胞疗法发展,促进精准肿瘤学中自主化、高度可扩展且精准可控的细胞免疫治疗转型。

为什么值得关注

暂未整理

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完整作者

Ahmed Reda Bahr、Youssef Basem、Amani Alhejely、Abdel Rahman Alaa、Saifallah Mabrouk Abozeid、Amira Basem、Mohsen A Khormi、Mabrouk A Abo-Zaid

作者机构

  • Faculty of Medicine, Alexandria University, Alexandria, Egypt.
  • Medical and Pharmaceutical Industrial Biotechnology Department, College of Biotechnology, Misr University for Science and Technology (MUST), Giza, Egypt.
  • Biology Department, Darb University College, Jazan University, Jazan, Saudi Arabia.
  • Faculty of Medicine, Cairo University, Kasr AlAiny, Egypt.
  • Department of Biotechnology and Genetic Engineering, College of Science, Helwan National University, Cairo, Egypt.
  • Department of Biology, College of Science, Jazan University, Jazan, Saudi Arabia.

技术路线

暂未整理

最近 5 个完整年度引用趋势

暂无引用数据

数据来源:暂未标注更新时间:暂无更新时间
临床队列临床研究Nature medicine

A health-system-scale, episode-resolved multimodal atlas of cancer cachexia.

0 次引用趋势数据不足

《自然·医学》发表的一项研究利用纪念斯隆-凯特琳癌症中心2010至2024年间52,236例癌症患者的纵向临床基因组数据,构建了按发作解析的癌症恶病质多模态图谱。研究发现,恶病质性体重减轻发作集中于疾病进展期附近,并与几乎所有癌种的不良结局相关;不同恶性肿瘤的恶病质发作具有一致的血清学特征,即白蛋白和血红蛋白降低、肝酶升高。多种肿瘤体细胞基因型(包括多种疾病中的TP53突变)与恶病质发作更频繁相关。基于上述发现,研究者建立了多变量模型,用于预测肺癌、结直肠癌和前列腺癌患者即将发生恶病质性体重减轻的风险,并在丹娜法伯癌症研究院5,785例独立外部队列中完成验证。研究表明,常规临床基因组数据可作为癌症恶病质研究的可扩展资源。

为什么值得关注

暂未整理

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完整作者

Venise Jan Castillon、Amy X Xie、Sonia Boscenco、Ethan Tse、Neil Ruthen、Jamie Wang、Ziad Bakouny、Michele Waters、Chenlian Fu、Christopher Fong、Mustafa Saleh、Tarek Baroud、Wungki Park、Urvi A Shah、A Ari Hakimi、Puneeth Iyengar、Justin Jee、Eileen White、Alexander Gusev、Tobias Janowitz、Marcus D Goncalves、Ed Reznik

作者机构

  • Computational Oncology Service, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Dana-Farber Cancer Institute, Boston, MA, USA.
  • Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Weill Cornell Medical College, New York, NY, USA.
  • Urology Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Rutgers Cancer Institute, Rutgers University, New Brunswick, NJ, USA.
  • Ludwig Princeton Branch, Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ, USA.
  • Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Harvard Medical School, Boston, MA, USA.
  • Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
  • Northwell Health Cancer Institute, Northwell Health, New Hyde Park, NY, USA.
  • Holman Division of Endocrinology, Diabetes & Metabolism, Department of Medicine and Radiation Oncology, NYU Langone Health, New York, NY, USA.
  • Computational Oncology Service, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. reznike@mskcc.org.

技术路线

纵向临床基因组数据(MSK-IMPACT,52,236例患者,2010-2024)→定义共识性恶病质体重减轻的发作分辨轨迹并关联结局、血清学与肿瘤基因型→多变量模型预测肺癌、结直肠癌和前列腺癌的恶病质体重减轻风险→在Dana-Farber癌症研究所独立外部队列(n=5,785)中验证

最近 5 个完整年度引用趋势

0110202102022020230202402025

不含 2026 年,仅展示最近 5 个完整年度。

数据来源:openalex更新时间:2026/10/30 06:02
临床队列综述Laboratory medicine

Extending the clinical utility of exome sequencing: reanalysis, variant reclassification, and dynamic reporting in molecular diagnosis.

暂无引用数据

临床外显子组测序(ES)广泛用于疑似孟德尔病和罕见病的诊断,但许多患者初次分析后仍无法确诊,阴性或非诊断性结果并不一定排除遗传病因,因为基因组知识和患者表型会随时间演变。该叙述性综述检索PubMed/MEDLINE、Web of Science核心合集和Google Scholar,综合外显子再分析、变异重分类、动态报告及补充诊断方法的证据与实践考量。非诊断性ES结果可能反映技术和生物信息学局限、临床或家系信息不完整、基因-疾病知识演变、变异证据不确定或超出常规ES检测范围的遗传机制。结合更新表型信息、数据库、分析方法和家系证据的结构化再分析可发现额外诊断;变异重分类和动态报告更新支持纵向解读,次要发现和人工智能辅助流程需适当监管。再分析不足时,可机制导向升级至基因组测序、RNA测序、长读长测序、甲基化检测、生化检测或功能试验。结构化再分析和动态报告可将ES从一次性分子检测转变为纵向诊断过程,实施需透明的再分析标准、可追溯的解读、不确定性的适当沟通和可持续的实验室流程,以支持临床决策和精准医学。

为什么值得关注

AI 辅助短评,基于标题和摘要整理

本文为叙述性综述,系统梳理外显子组测序阴性后重分析、变异重分类与动态报告的策略,并讨论机制导向的升级检测。选题切合临床痛点,强调将ES从一次性检测转变为纵向诊断过程。但作为综述,未提供原始验证数据,重分析与动态报告的实际增益、可操作性及成本效益仍需前瞻性研究确认。

查看扩展信息

完整作者

Lupeng Ji、Xue Zhou、Jiong Gao、Lin Zhu、Hui Zhang、Yilong Tu、Shun Ge、Chao Yuan

作者机构

  • Department of Pathology, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.
  • Medical Affairs Department, Hangzhou Adicon Clinical Laboratories Co., Ltd., West Lake District, Hangzhou, China.
  • Medical Affairs Department, Shenzhen Mindray Bio-Medical Electronics Co, Ltd, Shenzhen, China.

技术路线

文献检索(PubMed/MEDLINE、Web of Science Core Collection、Google Scholar)→叙述性综述证据综合(外显子组重分析、变异重分类、动态报告及补充诊断方法)

最近 5 个完整年度引用趋势

暂无引用数据

数据来源:暂未标注更新时间:暂无更新时间
临床队列临床研究Nature

Sugar-rich foods exacerbate antibiotic-induced microbiome disruption.

1 次引用趋势数据不足

一项研究通过精确追踪173名因造血细胞移植住院患者摄入的9 419餐饮食并分析随后微生物组变化,评估饮食与肠道微生物组动态的关系。对158名有配对纵向微生物组样本患者数据应用贝叶斯推断显示,抗生素暴露期间摄入甜食和糖类可预测微生物失调加重,表现为α多样性降低和致病共生菌肠球菌更大程度扩增。小鼠实验亦表明,补充蔗糖可增加并延长抗生素诱导的肠球菌扩增。研究提示,抗生素治疗期间避免富含单糖的饮食或可减轻微生物群破坏。

为什么值得关注

编辑短评

评估了饮食(特别是甜食和糖类)与肠道微生物组动态的关系,抗生素治疗期间避免富含单糖的饮食或可减轻微生物群破坏。

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完整作者

Anqi Dai、Annamaria Ballweg、William Jogia、Madhumitha Rangesa、Peter A Adintori、Mirae Baichoo、Tyler Funnell、Teng Fei、Nicholas R Waters、Abrielle Swartz、Sukanya Sahu、Brianna Gipson、Sandeep S Raj、Eiko Hayase、Zoe Pierce、Kenton Wu、Natalie Smith、Justin Neuberger、Adam Warren、Marina Burgos da Silva、Oriana Miltiadous、Corrado Zuanelli Brambilla、Marissa Lubin Buchan、Tatanisha K Peets、Ana Gradissimo、Luigi A Amoretti、Caichen Duan、Chenzhen Zhang、Fanny Matheis、Alexis P Sullivan、John B Slingerland、Annelie G Clurman、Daniel G Brereton、Paul A Giardina、Antonio L C Gomes、Abigail J Johnson、Dan Knights、Robert R Jenq、Kate A Markey、Miguel-Angel Perales、Sergio A Giralt、Marcel R M van den Brink、Jonas Schluter、Jonathan U Peled

作者机构

  • Adult Bone Marrow Transplantation Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Institute for Systems Genetics, NYU Langone Health Grossman School of Medicine, New York, NY, USA.
  • Department of Microbiology, NYU Langone Health Grossman School of Medicine, New York, NY, USA.
  • Department of Hematology and Hematopoietic Cell Transplantation, City of Hope National Medical Center, Los Angeles, CA, USA.
  • Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Departments of Genomic Medicine and Stem Cell Transplantation Cellular Therapy, Division of Cancer Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Human Oncology & Pathogenesis Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Haematology Unit, Department of Cellular Therapy, Hematology and Laboratory Medicine, Azienda Ospedaliero-Universitaria Senese, Siena, Italy.
  • Food and Nutrition Services, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Department of Biomedical Engineering, NYU Tandon School of Engineering, New York, NY, USA.
  • Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
  • Riddet Institute, Massey University, Palmerston North, New Zealand.
  • Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA.
  • Biotechnology Institute, University of Minnesota, Saint Paul, MN, USA.
  • Translational Science and Therapeutics Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Division of Medicine, University of Washington, Seattle, WA, USA.
  • Weill Cornell Medical College, New York, NY, USA.
  • City of Hope, Duarte, CA, USA. mvandenbrink@coh.org.
  • Institute for Systems Genetics, NYU Langone Health Grossman School of Medicine, New York, NY, USA. jonas.schluter@nyulangone.org.
  • Department of Microbiology, NYU Langone Health Grossman School of Medicine, New York, NY, USA. jonas.schluter@nyulangone.org.
  • Laura and Isaac Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA. jonas.schluter@nyulangone.org.
  • Adult Bone Marrow Transplantation Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA. peledj@mskcc.org.
  • Weill Cornell Medical College, New York, NY, USA. peledj@mskcc.org.

技术路线

数据/样本:173例造血干细胞移植住院患者的9,419餐饮食记录及纵向肠道菌群样本(其中158例有配对纵向菌群样本用于贝叶斯推断);分析:贝叶斯推断评估饮食与菌群动态关系;验证:小鼠实验验证蔗糖补充对抗生素诱导肠球菌扩张的影响。

最近 5 个完整年度引用趋势

0110202102022020230202402025

不含 2026 年,仅展示最近 5 个完整年度。

数据来源:openalex更新时间:2026/10/30 06:30
临床队列临床研究Cell

Microbiome signatures linked to cancer and treatment adverse events in a real-world cohort.

0 次引用趋势数据不足

一项真实世界混合癌症队列研究(Mayo Clinic Cancer Microbiome)纳入1,364例癌症患者和287名健康对照,采用可校正癌症、合并症及人口学和临床变量相关非特异性微生物组关联的分析框架,在五类癌症中鉴定出341种最可能参与癌症发病的癌症相关菌种。在癌种内部,早期乳腺癌患者粪便胆汁酸及C. scindens水平较低,早期结直肠癌患者乳酸和Veillonella parvula升高;携带二氢嘧啶脱氢酶的Anaerostipes hadrus对5-氟尿嘧啶所致腹泻具有保护作用。研究提示该队列可用于发现癌症特异性微生物组特征和预测性生物标志物。

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完整作者

Lu Yang、Vaidhvi Singh、Brent J Gawey、Jason P Sinnwell、Stephen Johnson、Elle C Billings、Trena M Van Gorp、Jonathan J Harrington、Michael Q Slama、Lisa M Till、Manavjot Singh、Thoshik R Samineni、Mojun Zhu、Krishna R Kalari、Gianrico Farrugia、Jun Chen、Ruben A T Mars、Purna C Kashyap

作者机构

  • Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA; The Benioff Center for Microbiome Medicine, University of California San Francisco, San Francisco, CA, USA.
  • Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
  • Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA; Division of Gastroenterology, Mount Sinai, New York, NY, USA.
  • Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
  • Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
  • Division of Gastroenterology, Mount Sinai, New York, NY, USA.
  • Department of Oncology, Mayo Clinic, Rochester, MN, USA.
  • Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA.
  • Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA; Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA. Electronic address: chen.jun2@mayo.edu.
  • Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA; Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA. Electronic address: mars.ruben@mayo.edu.
  • Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, USA. Electronic address: kashyap.purna@mayo.edu.

技术路线

真实世界混合癌症队列(1364例癌症患者和287例健康对照)的粪便微生物组数据 → 构建校正框架以排除与合并症、人口学和临床变量的非特异性关联,鉴定出五类癌症相关的341个菌种

最近 5 个完整年度引用趋势

0110202102022020230202402025

不含 2026 年,仅展示最近 5 个完整年度。

数据来源:openalex更新时间:2026/10/30 12:53
临床队列临床研究Cell

Opposing functions of gut immunomodulatory metabolites on CAR-T therapy.

0 次引用趋势数据不足

一项研究纳入德国三个中心的129例患者,采用鸟枪法宏基因组学和靶向质谱分析发现,CAR-T细胞治疗前短链脂肪酸(尤其是戊酸)水平降低与疾病进展风险增加相关;而吲哚类代谢物(包括吲哚-3-甲醛和吲哚-3-乙酸)及支链脂肪酸异戊酸水平升高与不良结局相关。在人源和小鼠CAR-T细胞模型中的功能验证表明,补充戊酸可增强CAR-T细胞疗效,而吲哚-3-甲醛和异戊酸则损害其疗效。研究揭示了免疫调节代谢物对CAR-T细胞治疗的对立作用,对设计代谢物引导的微生物组治疗策略具有重要意义。

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完整作者

Markus Perl、Severin Guetter、Dhyani Shah、Simon Holzinger、Luisa Becker、Misbah Tariq、Philipp Menauer、Simon Delahais、Gloria Lutzny-Geier、Julian N Scherer、Sascha Göttert、Konstantin Herfeld、Paul Heinrich、Klaus Georg Kreitmeier、Claudia Gebhard、Wolfgang Herr、Marcel P Trefny、Janina Doerr、Saba Sameri、Dennis C Harrer、Kai Ziegler-Martin、Sarah Staudt、Leo Hansmann、Matthias Edinger、Daniel Wolff、Daniela Weber、Elisabeth Meedt、Alexander Denk、Andre Gessner、Ernst Holler、Tobias Wertheimer、Klaus Neuhaus、Tingting Zheng、David M Cordas Dos Santos、Sebastian Theurich、Melanie Schirmer、Karin Kleigrewe、Jonas Schluter、Marcel van den Brink、Michael Schmitt、Markus Feuerer、Christoph Heuser-Loy、Jeremy Baldwin、Luca Gattinoni、Michael Rehli、Michael Hudecek、Camille Bigenwald、Laurence Zitvogel、Marion Subklewe、Viktoria Blumenberg、Maria-Luisa Schubert、Christoph Stein-Thoeringer、Maik Luu、Sebastian Kobold、Matthias A Fante、Erik Thiele Orberg、Hendrik Poeck

作者机构

  • Department of Internal Medicine III, Hematology & Internal Oncology, University Hospital Regensburg, Regensburg, Germany; Bavarian Cancer Research Center (BZKF), Regensburg, Germany. Electronic address: markus.perl.ukr@gmail.com.
  • Department of Internal Medicine III, Hematology & Internal Oncology, University Hospital Regensburg, Regensburg, Germany; Leibniz Institute for Immunotherapy (LIT), Regensburg, Germany.
  • Department of Internal Medicine III, Hematology & Internal Oncology, University Hospital Regensburg, Regensburg, Germany.
  • Division of Clinical Pharmacology, Department of Medicine IV, University Hospital, Ludwig Maximilian University (LMU) of Munich, Munich, Germany.
  • Department of Internal Medicine 5, Hematology and Oncology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Leibniz Institute for Immunotherapy (LIT), Regensburg, Germany.
  • Lehrstuhl für Zelluläre Immuntherapie, Medizinische Klinik und Poliklinik II, Universitätsklinikum Würzburg, Würzburg, Germany.
  • Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg, Regensburg, Germany.
  • Division of Hematology and Oncology, Department of Medicine, Freiburg University, Freising, Germany.
  • Core Facility Microbiome, ZIEL - Institute for Food & Health, Technische Universität München, Freising, Germany.
  • Translational Microbiome Data Integration, School of Life Sciences, Technical University of Munich, Freising, Germany; ZIEL - Institute for Food & Health, Technische Universität München, Freising, Germany.
  • Gene Center and Department of Biochemistry, LMU Munich, Munich, Germany.
  • Department of Medicine III, Hematology/Oncology, LMU University Hospital and Gene Center, LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), Partner Site Munich, a partnership between the DKFZ and BZKF at the University Hospital of the LMU, Germany.
  • Translational Microbiome Data Integration, School of Life Sciences, Technical University of Munich, Freising, Germany; ZIEL - Institute for Food & Health, Technische Universität München, Freising, Germany; Center for Organoid Systems, Technical University Munich, Garching, Germany.
  • Bavarian Center for Biomolecular Mass Spectrometry, TUM School of Life Sciences, Technical University Munich, Freising, Germany.
  • Department of Microbiology, New York University Grossman School of Medicine, New York, NY, USA; Institute for Systems Genetics, NYU Langone Health Grossman School of Medicine, New York, NY, USA.
  • Beckman Research Institute, City of Hope, Duarte, CA, USA.
  • Department of Medicine V, Hematology, Oncology and Rheumatology, University Hospital Heidelberg, Heidelberg, Germany.
  • Leibniz Institute for Immunotherapy (LIT), Regensburg, Germany; Department of Internal Medicine III, Haematology and Oncology, University Hospital Bonn, Bonn, Germany.
  • Lehrstuhl für Zelluläre Immuntherapie, Medizinische Klinik und Poliklinik II, Universitätsklinikum Würzburg, Würzburg, Germany; Branch Cellular Immunotherapy, Fraunhofer Institute for Cell Therapy and Immunology (IZI), Würzburg, Germany.
  • Gustave Roussy Cancer Campus, Villejuif, France.
  • Department of Medicine III, Hematology/Oncology, LMU University Hospital and Gene Center, LMU Munich, Munich, Germany; Laboratory for Translational Cancer Immunology, Gene Center LMU Munich, Munich, Germany; German Cancer Consortium (DKTK), Partner Site Munich, Munich, Germany; Bavarian Cancer Research Center (BZKF), Munich, Germany.
  • Department of Internal Medicine I, University Hospital Tuebingen, Tuebingen, Germany.
  • Division of Clinical Pharmacology, Department of Medicine IV, University Hospital, Ludwig Maximilian University (LMU) of Munich, Munich, Germany; Laboratory for Translational Cancer Immunology, Gene Center LMU Munich, Munich, Germany; Bavarian Cancer Research Center (BZKF), Munich, Germany; German Center for Lung Research (DZL), Partner Site Munich, Munich, Germany.
  • Department of Internal Medicine III, Hematology & Internal Oncology, University Hospital Regensburg, Regensburg, Germany; Department of Internal Medicine II, University Hospital of Würzburg, Würzburg, Germany.
  • Department of Internal Medicine III, Hematology & Internal Oncology, University Hospital Regensburg, Regensburg, Germany; Bavarian Cancer Research Center (BZKF), Regensburg, Germany. Electronic address: erik.orberg@ukr.de.
  • Department of Internal Medicine III, Hematology & Internal Oncology, University Hospital Regensburg, Regensburg, Germany; Bavarian Cancer Research Center (BZKF), Regensburg, Germany; Leibniz Institute for Immunotherapy (LIT), Regensburg, Germany. Electronic address: hendrik.poeck@ukr.de.

技术路线

粪便宏基因组与靶向质谱(129例三中心队列)→代谢物与疾病进展关联分析→人及小鼠CAR-T细胞模型功能验证

最近 5 个完整年度引用趋势

0110202102022020230202402025

不含 2026 年,仅展示最近 5 个完整年度。

数据来源:openalex更新时间:2026/10/30 06:03
公共数据库临床研究Nucleic acids research

circRNADisease v3.0: an updated resource for high-quality, experimentally supported circRNA-disease associations.

0 次引用趋势数据不足

环状RNA(circRNA)与疾病关联的系统整合对阐明其在疾病发生中的作用及评估其生物标志物和治疗靶点潜力具有重要意义。circRNADisease v3.0是一个经过人工审编、实验支持的circRNA-疾病关联数据库的扩展升级版本,共收录15 390条circRNA-疾病条目,涉及9 168个circRNA、656个MONDO标准化疾病术语和66个物种,数据量较v2.0增加两倍以上。每条记录依据支持证据的强度和多样性赋予置信评分,证据类型包括临床证据、环状转录本身份验证、表达检测、功能实验、分子机制验证和生物信息学分析。该版本还整合了基因组坐标、亚细胞定位、实验验证方法、临床意义、数据与代码可用性及多疾病术语交叉引用。新增Circ2CNV模块(含33个TCGA癌症队列中2 962 504条circRNA-癌症队列拷贝数变异记录)和Circ2Celltype模块(含29种细胞类型的2 025条细胞类型解析证据记录),与原有Circ2Mut模块共同将文献审编的circRNA-疾病关联与基因组改变和细胞背景相连接。该数据库为circRNA研究提供了全面且以证据为导向的平台,可通过http://cgga.org.cn/circRNADisease/免费获取。

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完整作者

Chang-Lin Yang、Rui Yang、Wen-Lu Tan、Han-Xiao Zhou、Ling-Xiang Wu、Ji Shi、Fan Wu、Li-Jie Huang、Zhi-Yan Sun、Tao Jiang、Zheng Zhao

作者机构

  • Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China.
  • Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
  • Chinese Glioma Genome Atlas (CGGA) Network and Asian Glioma Genome Atlas (AGGA) Network, Beijing 100070, China.
  • Chinese Neuro-Oncology Genome Atlas (CGGA-CNS) Network, Beijing 100070, China.

技术路线

数据/样本:文献人工审编的circRNA-疾病关联,v3.0含15,390条条目(9,168个circRNA、656个MONDO标准化疾病术语、66个物种),并整合TCGA 33个癌症队列的2,962,504条circRNA-癌症队列记录(Circ2CNV模块)和2,025条细胞类型分辨证据(29种细胞类型,Circ2Celltype模块);分析:依据临床证据、circular-transcript身份验证、表达检测、功能实验、分子机制验证和生物信息学分析等支持证据的强度与多样性,为每条记录赋予置信度评分,并整合基因组坐标、亚细胞定位、实验验证方法、临床意义、数据与代码可及性及多疾病术语交叉引用;验证:原文未报告独立的实验或计算验证。

最近 5 个完整年度引用趋势

0110202102022020230202402025

不含 2026 年,仅展示最近 5 个完整年度。

数据来源:openalex更新时间:2026/10/29 12:36
AI 靶点发现研究类型未标注Chinese herbal medicines

Advancing TCM-derived active natural product drug discovery for novel drug targets: Insights from AI powered tools.

暂无引用数据

针对尚未充分探索的新型生物靶点发现天然产物至关重要,是推动多类疾病创新疗法发展的基础。随着人工智能(AI)快速发展及多组学整合、网络靶点预测、虚拟筛选、药物-靶点相互作用预测等药物发现策略的应用,中药来源活性天然产物药物发现进入新阶段,多模态高维数据可在大数据背景下整合,提升理论基础与技术能力。但AI驱动的天然产物药物发现仍面临数据与研究质量保障及实现更深入科学发现等重大挑战,需进一步创新以获得更精准且具有生物医学意义的结果。整合高维数据、网络建模与智能筛选,并置于闭环验证框架中,有望推动AI与大数据范式促进生物活性成分的精准发现,为复杂疾病的靶向治疗开辟新前沿。

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完整作者

Shangtao Wang、Jinling Zhang、Wenshuang Wang、Sihan Xu、Man Zhang、Yuanyuan Hou、Gang Bai

作者机构

  • College of Pharmacy and Tianjin Key Laboratory of Molecular Drug Research. State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300350, China.

技术路线

暂未整理

最近 5 个完整年度引用趋势

暂无引用数据

数据来源:暂未标注更新时间:暂无更新时间
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