相关实验视频

Updated: Sep 13, 2025

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Microfluidic Co-Culture Models for Dissecting the Immune Response in in vitro Tumor Microenvironments

Published on: April 30, 2021

ImmuProgML:在瘤进展过程中基于机器学习的癌症-免疫动态剖析,以改善免疫治疗

Hanxiao Zhou^1,2, Lan Mei¹, Qianyi Lu¹

¹College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.

Journal of translational medicine

|July 27, 2025

概括

本研究介绍了ImmuProgML,这是一种机器学习框架,集成了多omics和网络分析,以预测癌症进展和免疫治疗反应,确定关键的临界点和个性化治疗的潜在治疗目标.

科学领域:

计算生物学和生物信息学
癌症研究和免疫学
机器学习在医学中的应用

背景情况:

癌症的进展是一个多阶段的过程,受瘤免疫动态的影响.
目前的免疫疗法生物标志物不能完全整合癌症-免疫相互作用或进展动态.
机器学习为分析这些动态提供了一条途径,以改善免疫疗法预测.

研究的目的:

开发一个全面的机器学习框架,ImmuProgML,用于分析癌症进展和预测免疫治疗反应.
确定关键阶段和关键途径驱动癌症进展和免疫逃避.
发现针对个性化癌症免疫治疗的新型治疗点和候选药物.

主要方法:

集成的多omics数据与动态网络生物标志物 (DNB) 分析.
开发了DNEX评分,结合表达变化和免疫疗法驱动的网络拓.
采用机器学习来预测预后和免疫治疗反应,包括用于目标识别的分子对接.

主要成果:

在黑色素瘤 (第三阶段) 和NSCLC (第二阶段) 中确定了关键的临界点,与加速进展和免疫反应有关.
该DNEX得分与免疫相关途径相关,并预测了免疫疗法预后,优于现有的签名.
发现了四种强效的蛋白-药物对 (例如,CXCR4-PIK-93),具有高结合亲和力.

结论:

ImmuProgML提供了一个新的机器学习框架,用于理解瘤与免疫相互作用.
这种方法促进了个性化的癌症免疫疗法选择.
该框架有助于识别关键进展点和潜在的治疗干预措施.

关键词:

动态网络生物标志物分析预测免疫疗法反应的预测.机器学习机器学习分子对接是分子对接.

更多相关视频

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors

Published on: June 7, 2018

相关概念视频

Tumor Immunotherapy

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.

Tumor Progression

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...