Tumor Vaccines for Solid Tumors

Fudan University

Status

Enrolling

Conditions

Solid Tumor

Glioma

Treatments

Radiation: Radiotherapy

Procedure: Surgery

Drug: Chemotherapy

Biological: tumor vaccine

Study type

Observational

Funder types

Other

Identifiers

NCT06102837

KY2023-846

2022YFC3401605 (Other Grant/Funding Number)

2022YFC3401600 (Other Grant/Funding Number)

Details and patient eligibility

About

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.

Enrollment

340 estimated patients

Sex

All

Volunteers

No Healthy Volunteers

Inclusion criteria

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.

Exclusion criteria

Patients who meet any of the following criteria will not be included in this study: