相关实验视频

Updated: Jul 24, 2025

Predictive Immune Modeling of Solid Tumors

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

基因表达分类器的构建和验证,以预测初级三阴性乳腺癌中免疫治疗反应

Miquel Ensenyat-Mendez¹, Javier I J Orozco², Pere Llinàs-Arias¹

¹Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Health Research Institute of the Balearic Islands (IdISBa), Palma, Spain.

Communications medicine

|July 10, 2023

概括

一个新的37基因分类器,TNBC-ICI,准确地预测了对免疫检查点抑制剂 (ICI) 以及三阴性乳腺癌 (TNBC) 化疗的反应. 这个工具有助于选择患者进行有效的ICI治疗.

科学领域:

在瘤学瘤学.
免疫治疗是一种免疫疗法.
基因组学就是基因组学.

背景情况:

免疫检查点抑制剂 (ICI) 为三阴性乳腺癌 (TNBC) 患者提供了更好的结果,但响应预测仍然具有挑战性.
已知生物标志物如PD-L1和瘤突变负担在TNBC中显示出有限的预测价值.

研究的目的:

开发和验证基于机器学习的基因表达分类器,用于预测初级TNBC中ICI的反应.
将新型分类器的性能与现有的分子签名进行比较.

主要方法:

机器学习模型被训练在TNBC,HR+/HER2-乳腺和其他固体瘤的ICI前基因表达特征.
一个37基因分类器 (TNBC-ICI) 已经开发和验证在独立的队列.

主要成果:

在TNBC中,TNBC-ICI分类器在预测病理完整反应 (pCR) 中获得了0.86的AUC.
TNBC-ICI的表现优于PD-1/PD-L1基因表达特征 (AUC 0.67),并且在HR+/HER2-乳腺癌中表现出适度的准确性 (AUC 0.72-0.75).
该分类器在非乳腺固体瘤中表现不佳 (中位数AUC为0.67).

结论:

在TNBC-ICI分类器有效预测PCR到ICI加化学疗法在初级TNBC.
该分类器可以指导临床研究,并帮助TNBC患者的治疗决策.
需要进一步验证,以建立TNBC免疫治疗的全面预测小组.

更多相关视频

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

Studying Triple Negative Breast Cancer Using Orthotopic Breast Cancer Model

Published on: March 20, 2020

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Orthotopic Transplantation of Breast Tumors as Preclinical Models for Breast Cancer

Published on: May 18, 2020

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.