Results 131 to 140 of about 512,677 (302)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Small renal cell carcinoma accompanied by extensive inferior vena cava tumor thrombus diagnosed by percutaneous transvenous biopsy

IJU Case Reports
Introduction Up to 10% of patients with renal cell carcinoma present with tumor thrombus in the inferior vena cava. We report that a case of small renal cell carcinoma with tumor thrombus extending above the diaphragm for which transvenous biopsy was ...
Hikaru Tsukada, Nozomi Hayakawa, Koichiro Aida, Shinji Wada, Tsuyoshi Morimoto, Masatomo Doi, Hidefumi Mimura, Junki Koike, Eiji Kikuchi   +8 more
doaj   +1 more source

Enhancing CAR‐T Cell Efficacy in Solid Tumors by Inhibiting CCL5/VEGF‐Mediated Angiogenesis

Advanced Science, EarlyView.
This study reveals that CAR‐T cells in solid tumors produce CCL5, which paradoxically induces VEGF and angiogenesis to promote tumor growth. Blocking CCL5/VEGF signaling—through gene knockout, or the CCR5 inhibitor maraviroc—significantly enhances the antitumor efficacy of CAR‑T therapy (the diagram was created in Biorender).
Shishuo Sun, Qihong Li, Bixi Wang, Gang Wang, Ying Xue, Yibing Liang, Chenhe Hu, Zhenyu Wang, Xiaoge Gao, Haiheng Xu, Jun Song, Hailong Li, Liantao Li, Xiaoxiao Liu, Patrick Ming‐Kuen Tang, Qing Zhang   +15 more
wiley   +1 more source

Metastatic Renal Cell Carcinoma (RCC) [PDF]

, 1991
A. V. Bono, C. Stief, D. E. Johnson, D. G. Skinner, D. H. Garfield, D. J. Fairlamb, D. W. McNichols, E. Allhoff, G. L. Rohdenburg, G. T. Hultquist, H. C. Bumpus Jr., H. E. Stephenson Jr., H. J. G. Bloom, H. J. G. Bloom, H. J. G. Bloom, H. Takatera, I. Satake, J. B. Kernion De, J. B. Kernion De, J. C. Donaldson, J. E. Montie, K. Goldenberg, L. R. Kavoussi, M. M. Mims, R. C. Klugo, R. G. Middleton, R. M. Snow, R. Schlick, S. E. Katz, S. Liedke, S. Z. Freed, T. C. Everson, U. Jonas, W. de Riese, Z. Wajsman   +34 more
core   +1 more source

Radiological evaluation of biomarkers for renal cell carcinoma [PDF]

, 2018
Role of MRI DWI sequences in the evaluation of early response to neo- angiogenesis inhibitors in metastatic renal cell carcinoma Purpose: Angiogenesis inhibitors have a potential role in treating metastatic renal cell carcinoma, but it is still not ...
Marigliano, Chiara
core   +1 more source

Fully Humanized Bispecific T Cell Engager Shows Potent Activity in Central Nervous System and Peripheral Tumors

Advanced Science, EarlyView.
This study reports the development of a fully humanized bispecific T cell engager targeting IL13RA2, a tumor‐associated antigen enriched in glioblastoma. This off‐the‐shelf immunotherapy drives potent, antigen‐dependent T cell activation and tumor killing, and prolongs survival in experimental GBM and other solid tumors models without detectable off ...
Joseph T. Duffy, Angela Martin‐Regalado, Benedikt E. Haupt, Jacob R. Pogue, Aditi Thakur, Manuel Fierro Cota, Markella Zannikou, Sol Misener, Vera P. Krymskaya, Kathleen McCortney, Jason Miska, Craig Horbinski, Dmitri Simberg, Maciej S. Lesniak, Charles D. James, Roger Stupp, Irina V. Balyasnikova   +16 more
wiley   +1 more source

Nanomedicine Meets Immunotherapy: Advancing Adoptive Cell Therapy with Nanoparticles in the Treatment of Cancer with Sustainability Perspectives

Advanced Science, EarlyView.
This review surveys nanoparticle‐based strategies to enhance adoptive cell therapy, particularly CAR‐T cell approaches, in solid tumor treatment. It describes how nanoparticles can improve tumor immunogenicity and T‐cell infiltration while reducing toxicity, and how they enable in vivo CAR‐T cell generation.
Erica Frostegård, Tatiana Bobrova, Amalie Leinebø, Thibault Leray, Shayamita Ghosh, Lorena García‐Hevia, Chiara Puccinelli, Lorenzo Riccio, Jacopo Sorani, Davide Bonifazi, Julien Caumartin, Emmanuel Donnadieu, Florence Gazeau, Roland Hischier, Else Marit Inderberg, Mónica L. Fanarraga, Maria Loustau, Bernd Nowack, Sébastien Wälchli, Cécilia Ménard‐Moyon   +19 more
wiley   +1 more source

S100A14 in Tumor‐Derived EVs Targets PIAS3 to Reprogram Astrocytes and Induce Immunosuppressive Microenvironment Promoting Brain Metastasis and Germacrone Reversal Effect

Advanced Science, EarlyView.
This study identifies S100A14 in tumor‐derived exosomes as a key driver of brain metastasis. S100A14 targets PIAS3 in astrocytes, activating STAT3 signaling and promoting immunosuppressive MDSCs recruitment via chemokine secretion. Germacrone, a natural compound, binds S100A14 to disrupt this axis, effectively inhibiting brain metastasis with low ...
Qian Feng, Xia Yang, Lin An, Xue‐Yu Wang, Ming‐Rui Wang, Zhuo‐Hong Cai, Cai‐Jun Xie, Li‐Jun Qiao, You‐Bi Shen, Xi‐Min Liang, Rong Zhang, Cai‐Yan Wang, Zhong‐Qiu Liu, Rong‐Rong Zhang   +13 more
wiley   +1 more source

Tumor‐Intrinsic ARHGEF3 Enhances Antitumor Immunity by Promoting T‐Cell Infiltration and Limiting Myeloid Cell‐Mediated Immunosuppression

Advanced Science, EarlyView.
ARHGEF3 is broadly downregulated across human cancers and correlates with patient prognosis. Tumor‐intrinsic ARHGEF3 activates the RHOA–ROCK–PTEN cascade to inhibit AKT signaling, thereby promoting chemokine‐driven T‐cell infiltration and relieving lipid‐mediated myeloid immunosuppression.
Yue Li, Lan Wang, Zihao Zhang, Chunmei Qian, Ning Li, Wei Huang, Qian Ba, Xiaojian Liu, Mayu Sun   +8 more
wiley   +1 more source

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment

Advanced Science, EarlyView.
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng, Fuze Cong, Shenbo Zhang, Rui Lv, Wenjia Zhang, Xinyi Ke, Juncheng Wu, Zhonghe Zhao, Kui Zhao, Di Dong, Ruofan Zhang, Zhengyu Jin, Max Seidensticker, Zhiwei Wang, Huanwen Wu, Xianlin Han, Nan Hong, Huadan Xue   +17 more
wiley   +1 more source