Preclinical and Clinical Research on Therapeutic Vaccines for Solid Tumors
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 340
- 试验地点
- 1
- 主要终点
- Proteomics
研究概览
简要总结
Glioma is the most common primary malignant intracranial tumor, characterized by limited clinical treatment options and extremely poor prognosis. There is an urgent need for the development of new technologies and clinical practice. With the advancement of immunotherapy, tumor therapeutic vaccines have emerged as a hot topic in the field of solid tumor immunotherapy. Several clinical trials have confirmed that tumor vaccines can improve the prognosis of glioma patients. Vaccines are the first systemic treatment technology in nearly 30 years that can simultaneously extend the overall survival of patients with newly diagnosed glioblastoma and recurrent glioblastoma in Phase III clinical trials. This novel approach holds significant clinical value and brings hope to large number of patients. Our team has previously developed a dendritic cell (DC) vaccine for glioma, and the phase II clinical trial has demonstrated that it can extend the prognosis of glioma patients. However, several patients benefit less from vaccine therapy. Therefore, the identification of molecular mechanisms that render patients unresponsive to vaccine treatment is critical to improving vaccine efficacy. This project aims to collect various types of clinical samples from patients, including glioma patients receiving tumor vaccine treatment, glioma patients receiving conventional clinical treatment without tumor vaccine, and non-tumor patients (hemorrhagic stroke, ischemic stroke, and traumatic brain injury). High-throughput sequencing techniques will be used to establish an immune microenvironment database, followed by bioinformatics analysis and molecular biology experiments to uncover the molecular mechanisms influencing vaccine efficacy. Artificial intelligence and deep learning technologies will be employed to extract molecular mechanisms related information from radiology images and pathology images. Ultimately, the project seeks to establish an integrated diagnostic and treatment model that combines imaging, pathology, and omics data to advance the clinical application of vaccines.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Other
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •The patients with glioma patients/non-tumor patients (hemorrhagic stroke, ischemic stroke, and traumatic brain injury) in the Department of Neurosurgery of Huashan Hospital Affiliated to Fudan University who meet the following three conditions can be enrolled:
- •They were no age limit, male and female;
- •The pathological results of frozen section during operation were gliomas or non-tumor;
- •Tissue (6 mm * 6 mm) can be used for cell sorting on the basis of not affecting clinical routine diagnosis;
- •Sign informed consent.
排除标准
- •Patients who meet any of the following criteria will not be included in this study:
- •Participants in other clinical trials;
- •Pregnant women.
研究组 & 干预措施
glioma patients receiving conventional treatment
干预措施: Chemotherapy (Drug)
glioma patients receiving tumor vaccine
干预措施: tumor vaccine (Biological)
glioma patients receiving tumor vaccine
干预措施: Radiotherapy (Radiation)
glioma patients receiving tumor vaccine
干预措施: Chemotherapy (Drug)
glioma patients receiving tumor vaccine
干预措施: Surgery (Procedure)
glioma patients receiving conventional treatment
干预措施: Radiotherapy (Radiation)
glioma patients receiving conventional treatment
干预措施: Surgery (Procedure)
non-tumor patients
干预措施: Surgery (Procedure)
结局指标
主要结局
Proteomics
时间窗: 48 months
The issues collected will be used for proteomic sequencing to measure gene expression level in protein
Transcriptomics
时间窗: 48 months
The issues collected will be used for transcriptome sequencing to measure gene expression level.
Immunomics
时间窗: 48 months
The issues collected will be used for TCR/BCR sequencing to measure clonality of lymphocytes
Genomics
时间窗: 48 months
The issues collected will be used for whole genome sequencing or whole exome sequencing to measure gene mutations.
Radiomics
时间窗: 48 months
The features from images will be extracted using algorithm of Deep-learning or Radiomics
IHC analysis
时间窗: 48 months
Different expression level of proteins (CD3,CD8,B7-H4 et.al) in Gliomas with different grades and molecular subgroups will be measured using immunohistochemical.
次要结局
未报告次要终点
