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Tumor Vaccines for Solid Tumors

Preclinical and Clinical Research on Therapeutic Vaccines for Solid Tumors

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06102837
Enrollment
340
Registered
2023-10-26
Start date
2023-10-31
Completion date
2027-10-31
Last updated
2023-10-26

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Glioma, Solid Tumor

Keywords

Glioma, DC vaccine, Database, Biomarker, Artificial intelligence

Brief summary

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.

Interventions

BIOLOGICALtumor vaccine

tumor vaccine produced by our team

RADIATIONRadiotherapy

conventional treatment in clincial

DRUGChemotherapy

conventional treatment in clinical

PROCEDURESurgery

conventional treatment in clinical

Sponsors

Huashan Hospital
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
OTHER

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

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: 1. They were no age limit, male and female; 2. The pathological results of frozen section during operation were gliomas or non-tumor; 3. Tissue (6 mm \* 6 mm) can be used for cell sorting on the basis of not affecting clinical routine diagnosis; 4. Sign informed consent.

Exclusion criteria

Patients who meet any of the following criteria will not be included in this study: 1. Participants in other clinical trials; 2. Pregnant women.

Design outcomes

Primary

MeasureTime frameDescription
Transcriptomics48 monthsThe issues collected will be used for transcriptome sequencing to measure gene expression level.
Immunomics48 monthsThe issues collected will be used for TCR/BCR sequencing to measure clonality of lymphocytes
Proteomics48 monthsThe issues collected will be used for proteomic sequencing to measure gene expression level in protein
Genomics48 monthsThe issues collected will be used for whole genome sequencing or whole exome sequencing to measure gene mutations.
Radiomics48 monthsThe features from images will be extracted using algorithm of Deep-learning or Radiomics
IHC analysis48 monthsDifferent expression level of proteins (CD3,CD8,B7-H4 et.al) in Gliomas with different grades and molecular subgroups will be measured using immunohistochemical.

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026