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1.
Front Mol Biosci ; 10: 1141994, 2023.
Article in English | MEDLINE | ID: mdl-37056723

ABSTRACT

The incidence of brain metastases (BrM) has become a growing concern recently. It is a common and often fatal manifestation in the brain during the end-stage of many extracranial primary tumors. Increasing BrM diagnoses can be attributed to improvements in primary tumor treatments, which have extended patients' lifetime, and allowed for earlier and more efficient detection of brain lesions. Currently, therapies for BrM encompass systemic chemotherapy, targeted therapy, and immunotherapy. Systemic chemotherapy regimens are controversial due to their associated side effects and limited efficacy. Targeted and immunotherapies have garnered significant attention in the medical field: they target specific molecular sites and modulate specific cellular components. However, multiple difficulties such as drug resistance and low permeability of the blood-brain barrier (BBB) remain significant challenges. Thus, there is an urgent need for novel therapies. Brain microenvironments consist of cellular components including immune cells, neurons, endothelial cells as well as molecular components like metal ions, nutrient molecules. Recent research indicates that malignant tumor cells can manipulate the brain microenvironment to change the anti-tumoral to a pro-tumoral microenvironment, both before, during, and after BrM. This review compares the characteristics of the brain microenvironment in BrM with those in other sites or primary tumors. Furthermore, it evaluates the preclinical and clinical studies of microenvironment-targeted therapies for BrM. These therapies, due to their diversity, are expected to overcome drug resistance or low permeability of the BBB with low side effects and high specificity. This will ultimately lead to improved outcomes for patients with secondary brain tumors.

2.
Mol Cancer ; 21(1): 201, 2022 10 19.
Article in English | MEDLINE | ID: mdl-36261831

ABSTRACT

Chimeric antigen receptor (CAR) T cell (CAR-T cell) therapy based on gene editing technology represents a significant breakthrough in personalized immunotherapy for human cancer. This strategy uses genetic modification to enable T cells to target tumor-specific antigens, attack specific cancer cells, and bypass tumor cell apoptosis avoidance mechanisms to some extent. This method has been extensively used to treat hematologic diseases, but the therapeutic effect in solid tumors is not ideal. Tumor antigen escape, treatment-related toxicity, and the immunosuppressive tumor microenvironment (TME) limit their use of it. Target selection is the most critical aspect in determining the prognosis of patients receiving this treatment. This review provides a comprehensive summary of all therapeutic targets used in the clinic or shown promising potential. We summarize CAR-T cell therapies' clinical trials, applications, research frontiers, and limitations in treating different cancers. We also explore coping strategies when encountering sub-optimal tumor-associated antigens (TAA) or TAA loss. Moreover, the importance of CAR-T cell therapy in cancer immunotherapy is emphasized.


Subject(s)
Neoplasms , Receptors, Chimeric Antigen , Humans , Receptors, Chimeric Antigen/genetics , Immunotherapy, Adoptive/methods , Neoplasms/genetics , Tumor Microenvironment , Antigens, Neoplasm/genetics , Cell- and Tissue-Based Therapy
3.
Front Oncol ; 11: 732196, 2021.
Article in English | MEDLINE | ID: mdl-34722274

ABSTRACT

Imaging diagnosis is crucial for early detection and monitoring of brain tumors. Radiomics enable the extraction of a large mass of quantitative features from complex clinical imaging arrays, and then transform them into high-dimensional data which can subsequently be mined to find their relevance with the tumor's histological features, which reflect underlying genetic mutations and malignancy, along with grade, progression, therapeutic effect, or even overall survival (OS). Compared to traditional brain imaging, radiomics provides quantitative information linked to meaningful biologic characteristics and application of deep learning which sheds light on the full automation of imaging diagnosis. Recent studies have shown that radiomics' application is broad in identifying primary tumor, differential diagnosis, grading, evaluation of mutation status and aggression, prediction of treatment response and recurrence in pituitary tumors, gliomas, and brain metastases. In this descriptive review, besides establishing a general understanding among protocols, results, and clinical significance of these studies, we further discuss the current limitations along with future development of radiomics.

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