Tumor Vaccines for Solid Tumors

Condition(s) studied

Investigational drug(s) / intervention(s)

tumor vaccine: tumor vaccine produced by our team

Radiotherapy: conventional treatment in clincial

Chemotherapy: conventional treatment in clinical

Surgery: conventional treatment in clinical

Study 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.

Eligibility

Primary outcome measure(s)

• Transcriptomics — 48 months
  The issues collected will be used for transcriptome sequencing to measure gene expression level.
• Immunomics — 48 months
  The issues collected will be used for TCR/BCR sequencing to measure clonality of lymphocytes
• Proteomics — 48 months
  The issues collected will be used for proteomic sequencing to measure gene expression level in protein
• Genomics — 48 months
  The issues collected will be used for whole genome sequencing or whole exome sequencing to measure gene mutations.
• Radiomics — 48 months
  The features from images will be extracted using algorithm of Deep-learning or Radiomics
• IHC analysis — 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.

Trial sites (1)

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