An integrated machine learning framework for developing and validating a prognostic risk model of gastric cancer based on endoplasmic reticulum stress-associated genes DOI
Gang Wei, Yan Wang, Ru Liu

и другие.

Biochemistry and Biophysics Reports, Год журнала: 2024, Номер 41, С. 101891 - 101891

Опубликована: Дек. 4, 2024

Язык: Английский

Immunity‐Modulating Metal‐Based Nanomaterials for Cancer Immunotherapy DOI Creative Commons

Xing Sun,

Xican Xu,

Fengying Li

и другие.

Advanced Functional Materials, Год журнала: 2025, Номер unknown

Опубликована: Март 4, 2025

Abstract Cancer immunotherapy, which leverages the body's immune system to combat cancer, offers promise of lower toxicity and higher therapeutic efficacy compared conventional treatments. However, current immunotherapeutic approaches face significant challenges including variable patient response, immune‐related adverse events, high costs, underscoring urgent need for innovative strategies. Metal‐based nanomaterials have emerged as a promising avenue in cancer immunotherapy due their unique physicochemical properties immune‐regulating capabilities. Despite potential, concerns about toxicity, incomplete understanding modulation mechanisms, early‐stage design strategies hinder clinical translation. This review summarizes recent advancements metal‐based elucidates mechanisms by they enhance antitumor immunity responses, explores potential synergistic effects combining multiple metals. We also discuss key future perspectives application, aiming provide theoretical foundation development immunotherapies promote broader application treatment.

Язык: Английский

Процитировано

0

An integrated machine learning framework for developing and validating a prognostic risk model of gastric cancer based on endoplasmic reticulum stress-associated genes DOI
Gang Wei, Yan Wang, Ru Liu

и другие.

Biochemistry and Biophysics Reports, Год журнала: 2024, Номер 41, С. 101891 - 101891

Опубликована: Дек. 4, 2024

Язык: Английский

Процитировано

0