Molecular Biology of Brain Metastases

Precision radiotherapy with molecular-profiling of CNS tumours

Diagnoses of CNS malignancies in the primary and metastatic setting have significantly advanced in the last decade with the advent of molecular pathology. Using a combination of immunohistochemistry, next-generation sequencing, and methylation profiling integrated with traditional histopathology, patient prognosis and disease characteristics can be understood to a much greater extent. This has recently manifested in predicting response to targeted drug therapies that are redefining management practices of CNS tumours. Radiotherapy, along with surgery, still remains an integral part of treating the majority of CNS tumours. However, the rapid advances in CNS molecular diagnostics have not yet been effectively translated into improving CNS radiotherapy. We explore several promising strategies under development to integrate molecular oncology into radiotherapy, and explore future directions that can serve to use molecular diagnostics to personalize radiotherapy. Evolving the management of CNS tumours with molecular profiling will be integral to supporting the future of precision radiotherapy.

Multimodal radiomics-based methods using deep learning for prediction of brain metastasis in non-small cell lung cancer with18F-FDG PET/CT images

Objective. Approximately 57% of non-small cell lung cancer (NSCLC) patients face a 20% risk of brain metastases (BMs). The delivery of drugs to the central nervous system is challenging because of the blood-brain barrier, leading to a relatively poor prognosis for patients with BMs. Therefore, early detection and treatment of BMs are highly important for improving patient prognosis. This study aimed to investigate the feasibility of a multimodal radiomics-based method using 3D neural networks trained on18F-FDG PET/CT images to predict BMs in NSCLC patients.Approach. We included 226 NSCLC patients who underwent18F-FDG PET/CT scans of areas, including the lung and brain, prior to EGFR-TKI therapy. Moreover, clinical data (age, sex, stage, etc) were collected and analyzed. Shallow lung features and deep lung-brain features were extracted using PyRadiomics and 3D neural networks, respectively. A support vector machine (SVM) was used to predict BMs. The receiver operating characteristic (ROC) curve and F1 score were used to assess BM prediction performance.Main result. The combination of shallow lung and shallow-deep lung-brain features demonstrated superior predictive performance (AUC = 0.96 ± 0.01). Shallow-deep lung-brain features exhibited strong significance (P < 0.001) and potential predictive performance (coefficient > 0.8). Moreover, BM prediction by age was significant (P < 0.05).Significance. Our approach enables the quantitative assessment of medical images and a deeper understanding of both superficial and deep tumor characteristics. This noninvasive method has the potential to identify BM-related features with statistical significance, thereby aiding in the development of targeted treatment plans for NSCLC patients.

Non-neoplastic astrocytes: key players for brain tumor progression

Astrocytes are highly plastic cells whose activity is essential to maintain the cerebral homeostasis, regulating synaptogenesis and synaptic transmission, vascular and metabolic functions, ions, neuro- and gliotransmitters concentrations. In pathological conditions, astrocytes may undergo transient or long-lasting molecular and functional changes that contribute to disease resolution or exacerbation. In recent years, many studies demonstrated that non-neoplastic astrocytes are key cells of the tumor microenvironment that contribute to the pathogenesis of glioblastoma, the most common primary malignant brain tumor and of secondary metastatic brain tumors. This Mini Review covers the recent development of research on non-neoplastic astrocytes as tumor-modulators. Their double-edged capability to promote cancer progression or to represent potential tools to counteract brain tumors will be discussed.

Current Treatment of Melanoma Brain Metastases

Melanoma is a type of skin cancer in which there is a strong correlation between its occurrence and exposure to ultraviolet radiation. Although it is not the most common skin cancer, it has the highest mortality rate of all skin cancers. The prognosis of patients is significantly worsened by melanoma metastasis to the brain, which often occurs in patients with advanced disease. The formation and development of melanoma metastases to the brain involve a very complex process, and their mechanisms are not fully understood. One of the ways for metastatic melanoma cells to survive and develop cancer in the brain environment is the presence of oncogenic BRAF mutation, which occurs in up to 50% of metastatic melanoma cases. Before discovering new methods of treating metastases, the overall survival of patients with this disease was 6 months. Currently, research is being conducted on new drugs using immunotherapy (immune checkpoint inhibitors: anti-PD-1, anti-CTLA-4) and targeted therapy (BRAF and MEK inhibitors) to improve the prognosis of patients. In this article, we summarize the current state of knowledge about the results of treating brain metastases with new systemic therapies.