Current approaches to the management of brain metastases

Brain-tumor-seeking and serpin-inhibiting outer membrane vesicles restore plasmin-mediated attacks against brain metastases

Many chemotherapeutic and molecular targeted drugs have been used to treat brain metastases, e.g., anti-angiogenic vandetanib. However, the blood-brain barrier and brain-specific resistance mechanisms make these systemic therapeutic approaches inefficacious. Brain metastatic cancer cells could mimic neurons to upregulate multiple serpins and secrete them into the extracellular environment to reduce local plasmin production to promote L1CAM-mediated vessel co-option and resist anti-angiogenesis therapy. Here, we developed brain-tumor-seeking and serpin-inhibiting outer membrane vesicles (DE@OMVs) to traverse across the blood-brain barrier, bypass neurons, and specially enter metastatic cancer cells via targeting GRP94 and vimentin. Through specific delivery of dexamethasone and embelin, reduced serpin secretion, restored plasmin production, significant L1CAM inactivation and tumor cell apoptosis were specially found in intracranial metastatic regions, leading to delayed tumor growth and prolonged survival in mice with brain metastases. By combining the brain-tumor-seeking properties with the regulation of the serpin/plasminogen activator/plasmin/L1CAM axis, this study provides a potent and highly-selective systemic therapeutic option for brain metastases.

Cognitive dysfunction induced by cranial radiotherapy: mechanisms and therapeutic methods

Cranial radiotherapy can damage normal brain tissues, inducing cognitive dysfunction in patients. Radiotherapy-induced cognitive dysfunction is associated with hippocampal injury, white matter damage and microvascular injury. In this study, the mechanisms of cognitive dysfunction induced by cranial radiotherapy and combined chemoradiotherapy are reviewed, and the advances in therapeutic methods for radiotherapy-induced brain injury are summarized. The mechanisms of radiotherapy-induced brain injury include a decline of neurogenesis, impairment of neurons and glial cells, vascular injury, oxidative stress and DNA damage, cell death, and inflammatory response. Disruption of the bloodbrain barrier (BBB) increases the exposure of the brain to chemotherapeutic agents, thus exacerbating radiotherapy-induced brain damage. The current methods used to prevent radiotherapy-induced brain injury mainly include precision radiotherapy, stem cell transplantation, and treatment with neuroprotective drugs. The combined application of precision radiotherapy and neuroprotective drugs, including antioxidants, anti-inflammatory agents and other drugs, might exert better neuroprotective effects. To resolve the issues of neuroprotective drugs, such as difficulty in crossing the BBB, nanoenzymes and drug delivery nano-systems could be applied in the future.

Antibody-Drug Conjugates for the Treatment of Non-Small Cell Lung Cancer with Central Nervous System Metastases

Antibody-drug conjugates (ADCs) represent an emerging class of targeted anticancer agents that have demonstrated impressive efficacy in numerous cancer types. In non-small cell lung cancer (NSCLC), ADCs have become a component of the treatment armamentarium for a subset of patients with metastatic disease. Emerging data suggest that some ADCs exhibit impressive activity even in central nervous system (CNS) metastases, a disease site that is difficult to treat and associated with poor prognosis. Herein, we describe and summarize the existing evidence surrounding ADCs in NSCLC with a focus on CNS activity.

The value of nomogram based on MRI functional imaging in differentiating cerebral alveolar echinococcosis from brain metastases

OBJECTIVE

This study aims to evaluate the effectiveness of a nomogram model constructed using Diffusion Kurtosis Imaging (DKI) and 3D Arterial Spin Labeling (3D-ASL) functional imaging techniques in distinguishing between cerebral alveolar echinococcosis (CAE) and brain metastases (BM).

METHODS

Prospectively collected were 24 cases (86 lesions) of patients diagnosed with CAE and 16 cases (69 lesions) of patients diagnosed with BM at the affiliated hospital of Qinghai University from 2018 to 2023, confirmed either pathologically or through comprehensive diagnosis. Both patient groups underwent DKI and 3D-ASL scanning. DKI parameters (Kmean, Dmean, FA, ADC) and cerebral blood flow (CBF) were analyzed for the parenchymal area, edema area, and symmetrical normal brain tissue area in both groups. There were 155 lesions in total in the two groups of patients. We used SPSS to randomly select 70% as the training set (108 lesions) and the remaining 30% as the test set (47 lesions) and performed a difference analysis between the two groups. The independent factors distinguishing CAE from BM were identified using univariate and multivariate logistic regression analyses. Based on these factors, a diagnostic model was constructed and expressed as a nomogram.

RESULT

Univariate and multivariate logistic regression analyses identified nDmean1 and nCBF1 in the lesion parenchyma area, as well as nKmean2 and nDmean2 in the edema area, as independent factors for distinguishing CAE from BM. The model's performance, measured by the area under the ROC curve (AUC), had values of 0.942 and 0.989 for the training and test sets, respectively. Calibration curves demonstrated that the predicted probabilities were highly consistent with the actual values, and DCA confirmed the model's high clinical utility.

CONCLUSION

The nomogram model, which incorporates DKI and 3D-ASL functional imaging, effectively distinguishes CAE from BM. It offers an intuitive, accurate, and non-invasive method for differentiation, thus providing valuable guidance for subsequent clinical decisions.

Brain Metastases from Genito-Urinary Cancers in the Canton of Geneva (Switzerland): Study of Incidence, Management and Outcomes

BACKGROUND

Incidence of brain metastases is precisely unknown and there is no clear consensus on their management. We aimed to determine the incidence of brain metastases among patients with genito-urinary primaries, present patients' characteristics and identify prognostic factors.

METHOD

We identified 51 patients treated in Geneva University Hospitals between January 1992 and December 2019. We retrospectively correlated their overall survival with 23 variables. We repeated a multivariate analysis with significant variables.

RESULTS

Overall incidence of Brain Metastases (BMs) among Genito-Urinary (GU) patients is estimated to be 1.76% (range per primary GU tumour type: 0.00-6.65%). BMs originate from germ cell tumours in two cases (3.92%), from urothelial cell carcinoma in 15 cases (29.41%), from prostate cancer in 13 cases (25.49%), and from renal cell carcinoma in 21 cases (41.18%); there are no BMs from penile cancer in our cohort. The median age at BM diagnosis is 67 years old (range: 25-92). Most patients (54%) have a stage IV disease at initial diagnosis and 11 patients (22%) have BM at initial diagnosis. Only six patients (12%) are asymptomatic at BM diagnosis. The median Overall Survival (OS) from BM diagnosis is 3 months (range: 0-127). Five patients (10%) are long survivors (OS > 24 months). OS is significantly influenced by patient performance status and administration of systemic treatment. In the absence of meningeal carcinomatosis, OS is influenced by systemic treatment and stereotactic radiosurgery. We also apply the Graded Prognostic Assessment (GPA) score to our cohort and note significant differences between groups.

CONCLUSION

Brain metastases from solid tumours is not a uniform disease, with a prognosis varying a lot among patients. The optimal management for patients with genito-urinary malignancies with brain metastases remain unclear and further research is needed.

A novel metastatic tumor segmentation method with a new evaluation metric in clinic study

Background

Brain metastases are the most common brain malignancies. Automatic detection and segmentation of brain metastases provide significant assistance for radiologists in discovering the location of the lesion and making accurate clinical decisions on brain tumor type for precise treatment.

Objectives

However, due to the small size of the brain metastases, existing brain metastases segmentation produces unsatisfactory results and has not been evaluated on clinic datasets.

Methodology

In this work, we propose a new metastasis segmentation method DRAU-Net, which integrates a new attention mechanism multi-branch weighted attention module and DResConv module, making the extraction of tumor boundaries more complete. To enhance the evaluation of both the segmentation quality and the number of targets, we propose a novel medical image segmentation evaluation metric: multi-objective segmentation integrity metric, which effectively improves the evaluation results on multiple brain metastases with small size.

Results

Experimental results evaluated on the BraTS2023 dataset and collected clinical data show that the proposed method has achieved excellent performance with an average dice coefficient of 0.6858 and multi-objective segmentation integrity metric of 0.5582.

Conclusion

Compared with other methods, our proposed method achieved the best performance in the task of segmenting metastatic tumors.

Astrocyte-induced Cdk5 expedites breast cancer brain metastasis by suppressing MHC-I expression to evade immune recognition

Brain metastases (BrMs) evade the immune response to develop in the brain, yet the mechanisms of BrM immune evasion remains unclear. This study shows that brain astrocytes induce the overexpression of neuronal-specific cyclin-dependent kinase 5 (Cdk5) in breast cancer-derived BrMs, which facilitates BrM outgrowth in mice. Cdk5-overexpressing BrMs exhibit reduced expression and function of the class I major histocompatibility complex (MHC-I) and antigen-presentation pathway, which are restored by inhibiting Cdk5 genetically or pharmacologically, as evidenced by single-cell RNA sequencing and functional studies. Mechanistically, Cdk5 suppresses MHC-I expression on the cancer cell membrane through the Irf2bp1-Stat1-importin α-Nlrc5 pathway, enabling BrMs to avoid recognition by T cells. Treatment with roscovitine-a clinically applicable Cdk5 inhibitor-alone or combined with immune checkpoint inhibitors, significantly reduces BrM burden and increases tumour-infiltrating functional CD8+ lymphocytes in mice. Thus, astrocyte-induced Cdk5 overexpression endorses BrM immune evasion, whereas therapeutically targeting Cdk5 markedly improves the efficacy of immune checkpoint inhibitors and inhibits BrM growth.

Lazertinib in EGFR-Variant Non-Small Cell Lung Cancer With CNS Failure to Prior EGFR Tyrosine Kinase Inhibitors: A Nonrandomized Controlled Trial

Importance

EGFR-variant non-small cell lung cancer (NSCLC) is associated with a high rate of central nervous system (CNS) metastases, even with treatment with first-generation or second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs).

Objective

To investigate CNS activity with lazertinib, a third-generation EGFR TKI.

Design, Setting, and Participants

This multicenter single-arm, phase 2 nonrandomized controlled trial was conducted in South Korea and included patients with EGFR-variant NSCLC who had asymptomatic or mildly symptomatic brain metastases after unsuccessful treatment with first-generation or second-generation EGFR TKIs. Data were collected from June 2021 to April 2022, with a data cutoff date of December 15, 2022.

Exposure

Lazertinib, 240 mg, once daily.

Main Outcomes and Measures

The primary end point was intracranial objective response rate (iORR) in the evaluable population according to the Response Evaluation Criteria in Solid Tumours version 1.1 assessed by the investigators. Secondary end points included intracranial progression-free survival (iPFS) and iORR in patients with T790M-negative disease and isolated CNS progression as well as overall ORR, duration of response, intracranial duration of response, disease control rate, overall survival, cerebrospinal fluid penetration of lazertinib, and safety.

Results

Among 40 included patients, 25 (63%) were women, and the median (range) age was 63 (29-85) years. A total of 38 patients were evaluable for tumor response, including 12 patients with leptomeningeal metastases. At data cutoff, the median (range) follow-up was 13.6 (2.9-17.7) months. The iORR for the evaluable population was 55% (21 of 38; 95% CI, 38.3-71.4); for patients with T790M-positive disease, 80% (4 of 5; 95% CI, 28.4-99.5); for patients with T790M-negative disease, 43% (9 of 21; 95% CI, 21.8-66.0); and for patients with T790M-unknown disease, 67% (8 of 12; 95% CI, 34.9-90.1). The median iPFS was 15.8 months (95% CI, 15.2-not reached) for the evaluable population, 15.2 months (95% CI, 4.2-not reached) for the T790M-positive subgroup, 15.4 months (95% CI, 7.9-not reached) for the T790M-negative subgroup, and 18.0 months (95% CI, 3.9-not reached) for the T790M-unknown subgroup. The cerebrospinal fluid penetration rate of lazertinib was 46.2% (95% CI, 10.0-49.6), providing further support for its mechanism of intracranial response. Most adverse events were grade 1 or 2.

Conclusions and Relevance

In this study, lazertinib had substantial CNS activity, regardless of T790M status, against the progression of intracranial metastases with or without leptomeningeal metastases after unsuccessful treatment with first-generation or second-generation EGFR TKIs in patients with metastatic EGFR-variant NSCLC. These results suggest that using lazertinib instead of brain local treatment could be a potential strategy in patients with EGFR-variant NSCLC whose CNS metastases progressed after prior EGFR TKI treatment.

Trial Registration

ClinicalTrials.gov Identifier: NCT05326425.

Brain Metastases in Differentiated Thyroid Cancer: Clinical Presentation, Diagnosis, and Management

Background: Brain metastases (BM) are the most common intracranial neoplasms in adults and are a significant cause of morbidity and mortality. The brain is an unusual site for distant metastases of thyroid cancer; indeed, the most common sites are lungs and bones. In this narrative review, we discuss about the clinical characteristics, diagnosis, and treatment options for patients with BM from differentiated thyroid cancer (DTC). Summary: BM can be discovered before initial therapy due to symptoms, but in most patients, BM is diagnosed during follow-up because of imaging performed before starting tyrosine kinase inhibitors (TKI) or due to the onset of neurological symptoms. Older male patients with follicular thyroid cancer (FTC), poorly differentiated thyroid cancer (PDTC), and distant metastases may have an increased risk of developing BM. The gold standard for detection of BM is magnetic resonance imaging with contrast agent administration, which is superior to contrast-enhanced computed tomography. The treatment strategies for patients with BM from DTC remain controversial. Patients with poor performance status are candidates for palliative and supportive care. Neurosurgery is usually reserved for cases where symptoms persist despite medical treatment, especially in patients with favorable prognostic factors and larger lesions. It should also be considered for patients with a single BM in a surgically accessible location, particularly if the primary disease is controlled without other systemic metastases. Additionally, stereotactic radiosurgery (SRS) may be the preferred option for treating small lesions, especially those in inaccessible areas of the brain or when surgery is not advisable. Whole brain radiotherapy is less frequently used in treating these patients due to its potential side effects and the debated effectiveness. Therefore, it is typically reserved for cases involving multiple BM that are too large for SRS. TKIs are effective in patients with progressive radioiodine-refractory thyroid cancer and multiple metastases. Conclusions: Although routine screening for BM is not recommended, older male patients with FTC or PDTC and distant metastases may be at higher risk and should be carefully evaluated for BM. According to current data, patients who are suitable for neurosurgery seem to have the highest survival benefit, while SRS may be appropriate for selected patient.

Neural Influences on Tumor Progression Within the Central Nervous System

For decades, researchers have studied how brain tumors, the immune system, and drugs interact. With the advances in cancer neuroscience, which centers on defining and therapeutically targeting nervous system-cancer interactions, both within the local tumor microenvironment (TME) and on a systemic level, the subtle relationship between neurons and tumors in the central nervous system (CNS) has been deeply studied. Neurons, as the executors of brain functional activities, have been shown to significantly influence the emergence and development of brain tumors, including both primary and metastatic tumors. They engage with tumor cells via chemical or electrical synapses, directly regulating tumors or via intricate coupling networks, and also contribute to the TME through paracrine signaling, secreting proteins that exert regulatory effects. For instance, in a study involving a mouse model of glioblastoma, the authors observed a 42% increase in tumor volume when neuronal activity was stimulated, compared to controls (p < 0.01), indicating a direct correlation between neural activity and tumor growth. These thought-provoking results offer promising new strategies for brain tumor therapies, highlighting the potential of neuronal modulation to curb tumor progression. Future strategies may focus on developing drugs to inhibit or neutralize proteins and other bioactive substances secreted by neurons, break synaptic connections and interactions between infiltrating cells and tumor cells, as well as disrupt electrical coupling within glioma cell networks. By harnessing the insights gained from this research, we aspire to usher in a new era of brain tumor therapies that are both more potent and precise.

Preoperative stereotactic radiosurgery for patients with 1-4 brain metastases: A single-arm phase 2 trial outcome analysis (NCT03398694)

Background

Stereotactic radiosurgery (SRS) following surgical resection is the standard of care for patients with symptomatic oligo brain metastasis (BM), however, it is associated with 10-15% local failure. Targeting a resection cavity is imprecise, thus preoperative radiosurgery where the target is well-defined may be superior, however, the efficacy of preoperative SRS has not yet been tested in a clinical trial.

Methods

We conducted a phase 2, single-arm trial of preoperative SRS followed by surgical resection in patients with 1-4 symptomatic oligo BMs (NCT03398694) with the primary objective of measuring 6-month local control (LC). SRS was delivered to all patients utilizing a gamma knife or linear accelerator as per RTOG-9005 dosing criteria [Shaw E, Scott C, Souhami L, et al. Single dose radiosurgical treatment of recurrent previously irradiated primary brain tumors and brain metastases: final report of RTOG protocol 90-05. Int J Radiat Oncol Biol Phys. 2000;47(2):291-298] based on tumor diameter with the exception that the largest lesion diameter treated was 5 cm with 15 Gy with all SRS treatment given in single fraction dosing.

Results

The trial screened 50 patients, 48 patients were treated under the protocol and 32 patients completed the entire follow-up period. Of all the patients who completed the follow-up period, the primary endpoint of 6-month LC was 100% (95% CI: 0.891-1.000; P = .005). Secondary endpoints, presented as medians, were overall survival (17.6 months), progression-free survival (5.3 months), distant in-brain failure (40.8% at 1 year), leptomeningeal failure (4.8% at 1 year), and radiation necrosis (7.7% at 1 year).

Conclusions

Our data confirms superior local control in patients who received preoperative SRS when compared to historical controls. Further study with a larger randomized cohort of patients is warranted to fully understand the benefits of preoperative SRS.

Metal-organic framework-edaravone nanoparticles for radiotherapy-induced brain injury treatment

Cranial radiotherapy may cause damage to normal brain tissues and induce cognitive dysfunction, so developing an effective strategy to prevent radiotherapy-induced brain injury is essential. Metal-organic frameworks (MOFs) can be used as vectors for the delivery of neuroprotective drugs due to their high drug loading capacity and low toxicity. In this study, we synthesized MIL-53(Cr) nanoparticles, which were used to deliver edaravone, and modified the surface of the nanoparticles with polyethylene glycol and Angiopep-2 (EDA@MIL-53(Cr)-P/A) to improve their oral bioavailability and ability to cross the blood-brain barrier (BBB). We confirmed that MIL-53(Cr)-P/A nanoparticles could achieve the sustained release of edaravone and enhance its ability to cross the BBB. The results of in vitro experiments showed that EDA@MIL-53(Cr)-P/A could exert radioprotective effects on HT22 and BV2 cells. We also demonstrated that EDA@MIL-53(Cr)-P/A could alleviate brain injury and cognitive dysfunction in mice receiving whole-brain irradiation. Mechanistically, EDA@MIL-53(Cr)-P/A alleviated irradiation-induced brain damage by inhibiting oxidative stress, DNA damage, apoptosis and inflammatory reactions. This study provides a new strategy for the protection against radiotherapy-induced brain injury.

Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics

Introduction: Accurate prediction of tumor dynamics following Gamma Knife radiosurgery (GKRS) is critical for optimizing treatment strategies for patients with brain metastases (BMs). Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancements in deep learning, such as autoencoders, offer the potential to enhance predictive accuracy. This study aims to evaluate the efficacy of autoencoders compared to traditional ML models in predicting tumor progression or regression after GKRS. Objectives: The primary objective of this study is to assess whether integrating autoencoder-derived features into traditional ML models can improve their performance in predicting tumor dynamics three months post-GKRS in patients with brain metastases. Methods: This retrospective analysis utilized clinical data from 77 patients treated at the "Prof. Dr. Nicolae Oblu" Emergency Clinic Hospital-Iasi. Twelve variables, including socio-demographic, clinical, treatment, and radiosurgery-related factors, were considered. Tumor progression or regression within three months post-GKRS was the primary outcome, with 71 cases of regression and 6 cases of progression. Traditional ML models, such as Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Extra Trees, Random Forest, and XGBoost, were trained and evaluated. The study further explored the impact of incorporating features derived from autoencoders, particularly focusing on the effect of compression in the bottleneck layer on model performance. Results: Traditional ML models achieved accuracy rates ranging from 0.91 (KNN) to 1.00 (Extra Trees). Integrating autoencoder-derived features generally enhanced model performance. Logistic Regression saw an accuracy increase from 0.91 to 0.94, and SVM improved from 0.85 to 0.96. XGBoost maintained consistent performance with an accuracy of 0.94 and an AUC of 0.98, regardless of the feature set used. These results demonstrate that hybrid models combining deep learning and traditional ML techniques can improve predictive accuracy. Conclusion: The study highlights the potential of hybrid models incorporating autoencoder-derived features to enhance the predictive accuracy and robustness of traditional ML models in forecasting tumor dynamics post-GKRS. These advancements could significantly contribute to personalized medicine, enabling more precise and individualized treatment planning based on refined predictive insights, ultimately improving patient outcomes.

Phase I trial of dose escalation for preoperative stereotactic radiosurgery for patients with large brain metastases

BACKGROUND

Single-session stereotactic radiosurgery (SRS) or surgical resection alone for brain metastases larger than 2 cm results in unsatisfactory local control. We conducted a phase I trial for brain metastases(>2 cm) to determine the safety of preoperative SRS at escalating doses.

METHODS

Radiosurgery dose was escalated at 3 Gy increments for 3 cohorts based on maximum tumor dimension starting at: 18 Gy for >2-3 cm, 15 Gy for >3-4 cm, and 12 Gy for >4-6 cm. Dose-limiting toxicity was defined as grade III or greater acute toxicity.

RESULTS

A total of 35 patients/36 lesions were enrolled. For tumor size >2-3 cm, patients were enrolled up to the second dose level (21 Gy); for >3-4 cm and >4-6 cm cohorts the third dose level (21 and 18 Gy, respectively) was reached. There were 2 DLTs in the >3-4 cm arm at 21 Gy. The maximum tolerated dose of SRS for >2-3 cm was not reached; and was 18 Gy for both >3-4 cm arm and >4-6 cm arm. With a median follow-up of 64.0 months, the 6- and 12-month local control rates were 85.9% and 76.6%, respectively. One patient developed grade 3 radiation necrosis at 5 months. The 2-year rate of leptomeningeal disease (LMD) was 0%.

CONCLUSIONS

Preoperative SRS with dose escalation followed by surgical resection for brain metastases greater than 2 cm in size demonstrates acceptable acute toxicity. The phase II portion of the trial will be conducted at the maximum tolerated SRS doses.

Survival Analysis, Clinical Characteristics, and Predictors of Cerebral Metastases in Patients with Colorectal Cancer

INTRODUCTION

Colorectal cancer (CRC) is the third most common cancer globally and a leading cause of cancer-related deaths. While liver metastasis is common, brain metastasis (BM) is rare, occurring in 0.1% to 14% of cases. Risk factors for BM include lung metastasis at diagnosis, rectal cancer, and mutations in RAS and KRAS genes. Due to its rarity, guidelines for BM screening and treatment are limited. The aim of this study is to identify the clinical characteristics and predictors of BM at the time of the initial diagnosis of CRC.

METHODS

We evaluated patients ≥18 years old with metastatic colorectal cancer and brain metastases at diagnosis from the SEER database (2010-2021). A retrospective cohort study was conducted to analyze overall survival and predictive factors for brain metastasis, utilizing multivariate logistic regression, Kaplan-Meier survival analysis, and the Cox proportional hazards models, with p-values < 0.05 considered significant.

RESULTS

Out of 24,703 patients with metastatic colorectal cancer (mCRC), 228 (0.92%) had brain metastasis (BM) at diagnosis. BM was more prevalent in average-onset mCRC (≥50 years) compared to early-onset (<50 years) (1% vs. 0.55%, p = 0.004). Certain factors, such as older age and adenocarcinoma subtype, were associated with BM. Additionally, Asians/Pacific-Islanders (HR 1.83 CI: 1.01-3-33, p = 0.045) and American Indians/Alaska Natives (HR 4.79 CI 1.15-19.97, p = 0.032) had higher mortality rates, while surgical treatment and chemotherapy were linked to decreased mortality. Patients with BM had significantly worse overall survival (6 months vs. 21 months, p < 0.001).

CONCLUSION

BM in mCRC is uncommon, but it is associated with significantly worse outcomes, including markedly reduced overall survival. Our study highlights several critical factors associated with the presence of BM, such as older age and specific racial/ethnic groups, which may inform risk stratification and early-detection strategies. Our findings emphasize the need for heightened awareness and screening for BM in high-risk mCRC patients, as well as the inclusion of these patients in clinical trials to explore tailored therapeutic approaches aimed at improving survival and quality of life.

Improved brain metastases segmentation using generative adversarial network and conditional random field optimization mask R-CNN

BACKGROUND

In radiotherapy, the delineation of the gross tumor volume (GTV) in brain metastases using computed tomography (CT) simulation localization is very important. However, despite the criticality of this process, a pronounced gap exists in the availability of tools tailored for the automatic segmentation of the GTV based on CT simulation localization images.

PURPOSE

This study aims to fill this gap by devising an effective tool specifically for the automatic segmentation of the GTV using CT simulation localization images.

METHODS

A dual-network generative adversarial network (GAN) architecture was developed, wherein the generator focused on refining CT images for more precise delineation, and the discriminator differentiated between real and augmented images. This architecture was coupled with the Mask R-CNN model to achieve meticulous GTV segmentation. An end-to-end training process facilitated the integration between the GAN and Mask R-CNN functionalities. Furthermore, a conditional random field (CRF) was incorporated to refine the initial masks generated by the Mask R-CNN model to ensure optimal segmentation accuracy. The performance was assessed using key metrics, namely, the Dice coefficient (DSC), intersection over union (IoU), accuracy, specificity, and sensitivity.

RESULTS

The GAN+Mask R-CNN+CRF integration method in this study performs well in GTV segmentation. In particular, the model has an overall average DSC of 0.819 ± 0.102 and an IoU of 0.712 ± 0.111 in the internal validation. The overall average DSC in the external validation data is 0.726 ± 0.128 and the IoU is 0.640 ± 0.136. It demonstrates favorable generalization ability.

CONCLUSION

The integration of the GAN, Mask R-CNN, and CRF optimization provides a pioneering tool for the sophisticated segmentation of the GTV in brain metastases using CT simulation localization images. The method proposed in this study can provide a robust automatic segmentation approach for brain metastases in the absence of MRI.

A clinically compatible in vitro drug-screening platform identifies therapeutic vulnerabilities in primary cultures of brain metastases

PURPOSE

Brain metastases represent the most common intracranial tumors in adults and are associated with a poor prognosis. We used a personalized in vitro drug screening approach to characterize individual therapeutic vulnerabilities in brain metastases.

METHODS

Short-term cultures of cancer cells isolated from brain metastasis patients were molecularly characterized using next-generation sequencing and functionally evaluated using high-throughput in vitro drug screening to characterize pharmacological treatment sensitivities.

RESULTS

Next-generation sequencing identified matched genetic alterations in brain metastasis tissue samples and corresponding short-term cultures, suggesting that short-term cultures of brain metastases are suitable models for recapitulating the genetic profile of brain metastases that may determine their sensitivity to anti-cancer drugs. Employing a high-throughput in vitro drug screening platform, we successfully screened the cultures of five brain metastases for response to 267 anticancer compounds and related drug response to genetic data. Among others, we found that targeted treatment with JAK3, HER2, or FGFR3 inhibitors showed anti-cancer effects in individual brain metastasis cultures.

CONCLUSION

Our preclinical study provides a proof-of-concept for combining molecular profiling with in vitro drug screening for predictive evaluation of therapeutic vulnerabilities in brain metastasis patients. This approach could advance the use of patient-derived cancer cells in clinical practice and might eventually facilitate decision-making for personalized drug treatment.

Sex Difference in Disease-Related Adverse Events Post-Diagnosis of Lung Cancer Brain Metastases in Medicare Individuals ≥ 66 Years of Age

Sex differences are evident in adverse events (AEs) related to brain tumors, yet sex differences in AEs specific to brain metastases (BrMs) are underexplored. Lung cancer BrMs dominate among BrM, comprising over half of cases. This study examined sex differences in AEs associated with lung cancer BrMs in individuals aged 66 or older using the SEER-Medicare dataset. Multivariable logistic regression, adjusted for demographic factors and comorbidities, stratified by histological subtype, treatment, age, and year of diagnosis were used to analyze AEs among those with BrMs from primary lung tumors. Year of diagnosis was grouped into prior/post-2013, to account for shifts in treatment paradigms. The results showed nuanced sex-specific AEs. Females diagnosed post-2013 with small-cell, squamous-cell, or other non-small-cell carcinoma BrMs had a higher headache likelihood than males. Males with adenocarcinoma post-2013 were more likely to experience brain herniation. Females aged 76 and older with small-cell BrM exhibited increased vision difficulty risk compared to males of the same age, with no significant difference in other age groups. Males treated for adenocarcinoma faced heightened hemorrhagic stroke risk. This study reveals sex-specific disparities in AEs among older individuals with lung cancer BrMs, varying by histological subtype, age, diagnosis year, and treatment.

Development of an optimized machine learning approach for assessing brain metastatic burden in preclinical models

Brain metastases (BrM) occur when malignant cells spread from a primary tumor located in other parts of the body to the brain. BrM is a deadly complication for cancer patients and currently lacks effective therapies. Due to the limited access to patient samples, preclinical models remain a valuable tool for studying metastasis development, progression, and response to therapy. Thus, reliable methods for quantifying metastatic burden in these models are crucial. Here, we describe step by step a new semi-automatic machine-learning approach to quantify metastatic burden on mouse whole-brain stereomicroscope images while preserving tissue integrity. This protocol utilizes the open-source, user-friendly image analysis software QuPath. The method is fast, reproducible, unbiased, and provides access to data points not always obtainable with other existing strategies.

Pilot study: radiomic analysis for predicting treatment response to whole-brain radiotherapy combined temozolomide in lung cancer brain metastases

Objective

The objective of this study is to assess the viability of utilizing radiomics for predicting the treatment response of lung cancer brain metastases (LCBM) to whole-brain radiotherapy (WBRT) combined with temozolomide (TMZ).

Methods

Fifty-three patients diagnosed with LCBM and undergoing WBRT combined with TMZ were enrolled. Patients were divided into responsive and non-responsive groups based on the RANO-BM criteria. Radiomic features were extracted from contrast-enhanced the whole brain tissue CT images. Feature selection was performed using t-tests, Pearson correlation coefficients, and Least Absolute Shrinkage And Selection (LASSO) regression. Logistic regression was employed to construct the radiomics model, which was then integrated with clinical data to develop the nomogram model. Model performance was evaluated using receiver operating characteristic (ROC) curves, and clinical utility was assessed using decision curve analysis (DCA).

Results

A total of 1834 radiomic features were extracted from each patient's images, and 3 features with predictive value were selected. Both the radiomics and nomogram models exhibited satisfactory predictive performance and clinical utility, with the nomogram model demonstrating superior predictive value. The ROC analysis revealed that the AUC of the radiomics model in the training and testing sets were 0.776 and 0.767, respectively, while the AUC of the nomogram model were 0.799 and 0.833, respectively. DCA curves demonstrated that both models provided benefits to patients across various thresholds.

Conclusion

Radiomic-defined image biomarkers can effectively predict the treatment response of WBRT combined with TMZ in patients with LCBM, offering potential to optimize treatment decisions for this condition.

Sodium fluorescein-guided resection of brain metastases: A needed approach or an option? A systematic review and meta-analysis

PURPOSE

Brain metastases (BM) often leave residual tumors despite having visible margins, which increases the risk of local tumor recurrence and can impact overall patient survival rates. Fluorescence-guided surgery (FGS) utilizing sodium fluorescein (FL) has been reported as an effective technique in recent studies. This study aimed to evaluate the efficacy of FL FGS in improving the extent of resection of brain metastases and its impact on overall survival.

METHODS

We conducted a systematic search following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Our primary focus was on gross total resection (GTR). Additionally, we extracted survival data and evaluated the risk of bias using a modified version of the Joanna Briggs Institute critical appraisal tool.

RESULTS

The study comprised 970 patients with brain metastases through eight different studies. The study found that patients who underwent FL-guided resection had a significantly higher rate of GTR (OR: 2.02, 95% CI: 1.14-3.56, p = 0.0156, I2 = 41.5%). Additionally, the study concluded that FL-guided resection is associated with better overall survival rates (HR: 0.61, 95%CI: 0.47 0.80, p = 0.0003, I2 = 41.5%).

CONCLUSION

Our research suggests that the use of FL is associated with a higher rate of GTR and improved overall patient survival. None of the studies we reviewed reported significant complications associated with the use of FL in patients.

The indication of palliative whole-brain radiotherapy for patients with brain metastases: a simple prognostic scoring system in the era of stereotactic radiosurgery

BACKGROUND

Stereotactic irradiation has become the mainstay treatment for brain metastases (BM), and whole-brain radiotherapy (WBRT) is often used for symptom palliation. However, the survival time of patients with BM undergoing palliative WBRT (pWBRT) is limited, making it difficult to select patients who should receive treatment.

METHODS

We collected patient data from 2016 to 2022 at the Shizuoka Cancer Center and retrospectively analyzed the factors related to survival time. Overall survival (OS) was defined as the survival time after WBRT.

RESULTS

A total of 301 patients (median age, 66 years) who underwent pWBRT were included. The primary cancers were lung, breast, gastrointestinal tract, and other cancers in 203 (67%), 38 (13%), 33 (11%), and 27 (9%) patients, respectively. Median OS of all patients was 4.1 months. In the multivariate analysis, male sex (hazard ratio [HR]:1.4), Karnofsky Performance Status (KPS) ≤ 60 (HR:1.7), presence of extracranial metastasis (ECM) (HR:1.6), neutrophil-lymphocyte ratio (NLR) ≥ 5 (HR:1.6), and lactate dehydrogenase (LDH) ≥ upper limit of normal (ULN) (HR:1.3) were significantly associated with shorter OS (all P < 0.05). To predict the OS, we created a prognostic scoring system (PSS). We gave one point to each independent prognostic factor. Median OS for patients with scores of 0-2, 3, and 4-5 were 9.0, 3.5 and 1.7 months, respectively (P < 0.001).

CONCLUSIONS

Male sex, KPS ≤ 60, presence of ECM, NLR ≥ 5, and LDH ≥ ULN were poor prognostic factors for patients with BM undergoing pWBRT. By PSS combining these factors, it may be possible to select patients who should undergo pWBRT.

Stereotactic radiotherapy vs whole brain radiation therapy in EGFR mutated NSCLC: Results & reflections from the prematurely closed phase III HYBRID trial

BACKGROUND

All known randomized trials of stereotactic radiotherapy (SRT) versus whole brain radiotherapy (WBRT) for brain metastases (BMs) comprise mixed histologies. The phase III HYBRID trial (NCT02882984) attempted to evaluate the non-inferiority of SRT vs. WBRT specifically for EGFR-mutated non-small cell lung cancer (EGFRm NSCLC) BMs.

METHODS

Inclusion criteria were ≤ 5 BMs (any size) from treatment-naïve EGFRm NSCLC. All patients started a first-generation tyrosine kinase inhibitor on the first day of WBRT (37.5 Gy/15 fractions) or SRT (25-40 Gy/5 fractions per tumor volume). The primary endpoint was 18-month intracranial progression-free survival (iPFS; intention-to-treat).

RESULTS

The trial commenced in June 2015 and was closed in April 2021 after screening 208 patients but enrolling 85 (n = 41 WBRT, n = 44 SRT; median follow-up 31 and 36 months, respectively). Respectively, 9.5 % vs. 10.2 % of patients experienced intracranial progression at 18 months, and the median iPFS was 21.4 vs. 22.3 months (p > 0.05 for all). The SRT arm experienced higher overall survival and cognitive preservation (p < 0.05 for all). The most notable reason for low enrollment was patients not wishing to risk neurocognitive decline from WBRT.

CONCLUSIONS

Although this phase III trial was underpowered, there was no evidence that SRT yielded outcome detriments compared to WBRT for EGFRm NSCLC BMs. Lessons from prematurely closed trials are valuable, as they often provide important experiential perspectives for investigators designing/executing future trials. In the current era, randomized trials involving WBRT without cognitive sparing measures may be at high risk of underaccrual; trial investigators are encouraged to carefully consider our experience when attempting to design such trials. However, trials of molecular-/biologically-stratified patients are highly recommended as the notion of "individualized medicine/oncology" continues to expand.

Comparative evaluation of outcomes amongst different radiosurgery management paradigms for patients with large brain metastasis

INTRODUCTION

This study compares four management paradigms for large brain metastasis (LMB): fractionated SRS (FSRS), staged SRS (SSRS), resection and postoperative-FSRS (postop-FSRS) or preoperative-SRS (preop-SRS).

METHODS

Patients with LBM (≥ 2 cm) between July 2017 and January 2022 at a single tertiary institution were evaluated. Primary endpoints were local failure (LF), radiation necrosis (RN), leptomeningeal disease (LMD), a composite of these variables, and distant intracranial failure (DIF). Gray's test compared cumulative incidence, treating death as a competing risk with a random survival forests (RSF) machine-learning model also used to evaluate the data.

RESULTS

183 patients were treated to 234 LBMs: 31.6% for postop-FSRS, 28.2% for SSRS, 20.1% for FSRS, and 20.1% for preop-SRS. The overall 1-year composite endpoint rates were comparable (21 vs 20%) between nonoperative and operative strategies, but 1-year RN rate was 8 vs 4% (p = 0.012), 1-year overall survival (OS) was 48 vs. 69% (p = 0.001), and 1-year LMD rate was 5 vs 10% (p = 0.052). There were differences in the 1-year RN rates (7% FSRS, 3% postop-FSRS, 5% preop-SRS, 10% SSRS, p = 0.037). With RSF analysis, the out-of-bag error rate for the composite endpoint was 47%, with identified top-risk factors including widespread extracranial disease, > 5 total lesions, and breast cancer histology.

CONCLUSION

This is the first study to conduct a head-to-head retrospective comparison of four SRS methods, addressing the lack of randomized data in LBM literature amongst treatment paradigms. Despite patient characteristic trends, no significant differences were found in LF, composite endpoint, and DIF rates between non-operative and operative approaches.

Imaging Recommendations for Diagnosis, Staging, and Management of Central Nervous System Neoplasms in Adults: CNS Metastases

Brain metastases (BMs) are the most common central nervous system (CNS) neoplasms, with an increasing incidence that is due in part to an overall increase in primary cancers, improved neuroimaging modalities leading to increased detection, better systemic therapies, and longer patient survival.

OBJECTIVE

To identify cancer patients at a higher risk of developing CNS metastases and to evaluate associated prognostic factors.

METHODS

Review of imaging referral guidelines, response criteria, interval imaging assessment, modality of choice, as well as the association of clinical, serological, and imaging findings as per various cancer societies.

RESULTS

Quantitative response assessment of target and non-target brain metastases as well as an interval imaging protocol set up based on primary histological diagnosis and therapy status are discussed as per various cancer societies and imaging programs.

CONCLUSION

Predictive factors in the primary tumor as well as independent variables of brain metastases like size, number, and response to therapy are necessary in management. The location of CNS metastases, symptomatic disease, as well as follow up imaging findings form a skeletal plan to prognosticate the disease, keeping in mind all the available new advanced therapy options of surgery, radiation, and immunotherapy that improve patient outcome significantly.

Protocol for a systematic review with prospective individual patient data meta-analysis in EGFR-mutant NSCLC with brain metastases to assess the effect of SRS+osimertinib compared to osimertinib alone: the STARLET Collaboration

BACKGROUND

Patients with advanced non-small-cell lung cancer (NSCLC) with activating mutations in the epidermal growth factor receptor (EGFR) gene are a heterogeneous population who often develop brain metastases (BM). The optimal management of patients with asymptomatic brain metastases is unclear given the activity of newer-generation targeted therapies in the central nervous system. We present a protocol for an individual patient data (IPD) prospective meta-analysis to evaluate whether the addition of stereotactic radiosurgery (SRS) before osimertinib treatment will lead to better control of intracranial metastatic disease. This is a clinically relevant question that will inform practice.

METHODS

Randomised controlled trials will be eligible if they include participants with BM arising from EGFR-mutant NSCLC and suitable to receive osimertinib both in the first-line and second-line settings (P); comparisons of SRS followed by osimertinib versus osimertinib alone (I, C) and intracranial disease control included as an endpoint (O). Systematic searches of Medline (Ovid), Embase (Ovid), Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL (EBSCO), PsychInfo, ClinicalTrials.gov and the WHO's International Clinical Trials Registry Platform's Search Portal will be undertaken. An IPD meta-analysis will be performed using methodologies recommended by the Cochrane Collaboration. The primary outcome is intracranial progression-free survival, as determined by response assessment in neuro-oncology-BM criteria. Secondary outcomes include overall survival, time to whole brain radiotherapy, quality of life, and adverse events of special interest. Effect differences will be explored among prespecified subgroups.

ETHICS AND DISSEMINATION

Approved by each trial's ethics committee. Results will be relevant to clinicians, researchers, policymakers and patients, and will be disseminated via publications, presentations and media releases.

PROSPERO REGISTRATION

CRD42022330532.

Bench-to-bedside imaging in brain metastases: a road to precision oncology

Radiology has seen tremendous evolution in the last few decades. At the same time, oncology has made great strides in diagnosing and treating cancer. Distant metastases of neoplasms are being encountered more often in light of longer patient survival due to better therapeutic strategies and diagnostic methods. Brain metastasis (BM) is a dismal manifestation of systemic cancer. In the present scenario, magnetic resonance imaging (MRI), computed tomography (CT) and positron emission tomography (PET) are playing a big role in providing molecular information about cancer. Lately, molecular imaging has emerged as a stirring arena of dynamic imaging techniques that have enabled clinicians and scientists to noninvasively visualize and understand biological processes at the cellular and molecular levels. This knowledge has impacted etiopathogenesis, detection, personalized treatment, drug development, and our understanding of carcinogenesis. This article offers insight into the molecular biology underlying brain metastasis, its pathogenesis, imaging protocols, and algorithms. It also discusses disease-specific molecular imaging features, focusing on common tumors that spread to the brain, such as lung, breast, colorectal cancer, melanoma, and renal cell carcinoma. Additionally, it covers various targeted treatment options, criteria for assessing treatment response, and the role of artificial intelligence in diagnosing, managing, and predicting prognosis for patients with brain metastases.

Mathematical modeling of brain metastases growth and response to therapies: A review

Brain metastases (BMs) are the most common intracranial tumor type and a significant health concern, affecting approximately 10% to 30% of all oncological patients. Although significant progress is being made, many aspects of the metastatic process to the brain and the growth of the resulting lesions are still not well understood. There is a need for an improved understanding of the growth dynamics and the response to treatment of these tumors. Mathematical models have been proven valuable for drawing inferences and making predictions in different fields of cancer research, but few mathematical works have considered BMs. This comprehensive review aims to establish a unified platform and contribute to fostering emerging efforts dedicated to enhancing our mathematical understanding of this intricate and challenging disease. We focus on the progress made in the initial stages of mathematical modeling research regarding BMs and the significant insights gained from such studies. We also explore the vital role of mathematical modeling in predicting treatment outcomes and enhancing the quality of clinical decision-making for patients facing BMs.

Minimally-invasive implantable device enhances brain cancer suppression

Current brain tumor treatments are limited by the skull and BBB, leading to poor prognosis and short survival for glioma patients. We introduce a novel minimally-invasive brain tumor suppression (MIBTS) device combining personalized intracranial electric field therapy with in-situ chemotherapeutic coating. The core of our MIBTS technique is a wireless-ultrasound-powered, chip-sized, lightweight device with all functional circuits encapsulated in a small but efficient "Swiss-roll" structure, guaranteeing enhanced energy conversion while requiring tiny implantation windows ( ~ 3 × 5 mm), which favors broad consumers acceptance and easy-to-use of the device. Compared with existing technologies, competitive advantages in terms of tumor suppressive efficacy and therapeutic resolution were noticed, with maximum ~80% higher suppression effect than first-line chemotherapy and 50-70% higher than the most advanced tumor treating field technology. In addition, patient-personalized therapy strategies could be tuned from the MIBTS without increasing size or adding circuits on the integrated chip, ensuring the optimal therapeutic effect and avoid tumor resistance. These groundbreaking achievements of MIBTS offer new hope for controlling tumor recurrence and extending patient survival.

Evolutionary Trend Analysis of Research on Immunotherapy for Brain Metastasis Based on Machine-Learning Scientometrics

Brain metastases challenge cancer treatments with poor prognoses, despite ongoing advancements. Immunotherapy effectively alleviates advanced cancer, exhibiting immense potential to revolutionize brain metastasis management. To identify research priorities that optimize immunotherapies for brain metastases, 2164 related publications were analyzed. Scientometric visualization via R software, VOSviewer, and CiteSpace showed the interrelationships among literature, institutions, authors, and topic areas of focus. The publication rate and citations have grown exponentially over the past decade, with the US, China, and Germany as the major contributors. The University of Texas MD Anderson Cancer Center ranked highest in publications, while Memorial Sloan Kettering Cancer Center was most cited. Clusters of keywords revealed six hotspots: 'Immunology', 'Check Point Inhibitors', 'Lung Cancer', 'Immunotherapy', 'Melanoma', 'Breast Cancer', and 'Microenvironment'. Melanoma, the most studied primary tumor with brain metastases offers promising immunotherapy advancements with generalizability and adaptability to other cancers. Our results outline the holistic overview of immunotherapy research for brain metastases, which pinpoints the forefront in the field, and directs researchers toward critical inquiries for enhanced mechanistic insight and improved clinical outcomes. Moreover, governmental and funding agencies will benefit from assigning financial resources to entities and regions with the greatest potential for combating brain metastases through immunotherapy.

Risk factors, prognostic factors, and nomograms for synchronous brain metastases of solid tumors: a population-based study

In previous literatures, we found that similar studies on the short-term prognosis of synchronous brain metastases (S-BM) from other systems are rare. Our aim was to evaluate the early mortality rate of patients with S-BM from the Surveillance, Epidemiology, and End Result (SEER) database and explore the risk factors for early mortality (≤ 1 year). We used Kaplan-Meier (KM) curves to evaluate early mortality in patients with S-BM from the SEER database. Logistic regression analyses were used to identify significant independent prognostic factors in patients with a follow-up time > 12 months. And the meaningful factors were used to construct a nomogram of overall early death. The receiver operating characteristic (ROC) curve was used to test the predictive ability of the model, while the decision curve analysis (DCA) curve was used to validate the clinical application ability of the model. A total of 47,284 patients were used for univariate and multivariate logistic regression analysis to screen variables to constructing a nomogram. In the all-cause early mortality specific model, the area under the ROC (AUC) curve of the training set was 0.764 (95% confidence interval (CI): 0.758-0.769), and the AUC of the validation set was 0.761 (95% CI: 0.752-0.770). The DCA calibration curves of the training set and validation set indicate that the 1-year early mortality rate predicted by this model is consistent with the actual situation. We found that the 1-year early mortality rate was 76.4%. We constructed a validated nomogram using these covariates to effectively predict 1-year early mortality in patients with S-BM. This nomogram can help clinical workers screen high-risk patients to develop more reasonable treatment plans.

A Phase II Trial of Bevacizumab in Patients with Recurrent/Progressive Solid Tumor Brain Metastases That Have Progressed Following Whole-Brain Radiation Therapy

Patients with solid tumor brain metastases that progress after whole-brain radiation have limited options. This prospective trial investigated the efficacy, safety, and tolerability of bevacizumab as salvage therapy in this population. Eligible patients received bevacizumab 10 mg/kg intravenously every 2 weeks until progression. The primary endpoint was radiologic response using Response Assessment in Neuro-Oncology (RANO) criteria. The secondary endpoints were progression-free survival (PFS), overall survival (OS), duration of response, and safety. Quality of life (QOL) was studied using the Functional Assessment of Cancer Therapy-Brain (FACT-Br) scale. Twenty-seven patients were enrolled, with twenty-four having evaluable data for response. The majority of histologies (n = 21, 78%) were breast cancer. The remaining histologies were non-small-cell lung cancer (n = 4, 15%), neuroendocrine cancer (n = 1, 3%), and papillary fallopian serous adenocarcinoma (n = 1, 3%). Eighteen patients had radiologic response, with two patients demonstrating partial response (8.33%) and sixteen patients demonstrating stable disease (66.7%). The median duration of response was 203 days. PFS at 6 months was 46%, median PFS was 5.3 m, and median OS was 9.5 m. Treatment was well tolerated, with six patients experiencing grade 3 lymphopenia and hypertension. There was one grade 3 thromboembolism. QOL was not negatively impacted. Bevacizumab is a safe and feasible salvage treatment with durable response and favorable overall survival for patients with progressive brain metastases after whole-brain radiation.

Invasive growth of brain metastases is linked to CHI3L1 release from pSTAT3-positive astrocytes

BACKGROUND

Compared to minimally invasive brain metastases (MI BrM), highly invasive (HI) lesions form abundant contacts with cells in the peritumoral brain parenchyma and are associated with poor prognosis. Reactive astrocytes (RAs) labeled by phosphorylated STAT3 (pSTAT3) have recently emerged as a promising therapeutic target for BrM. Here, we explore whether the BrM invasion pattern is influenced by pSTAT3+ RAs and may serve as a predictive biomarker for STAT3 inhibition.

METHODS

We used immunohistochemistry to identify pSTAT3+ RAs in HI and MI human and patient-derived xenograft (PDX) BrM. Using PDX, syngeneic, and transgenic mouse models of HI and MI BrM, we assessed how pharmacological STAT3 inhibition or RA-specific STAT3 genetic ablation affected BrM growth in vivo. Cancer cell invasion was modeled in vitro using a brain slice-tumor co-culture assay. We performed single-cell RNA sequencing of human BrM and adjacent brain tissue.

RESULTS

RAs expressing pSTAT3 are situated at the brain-tumor interface and drive BrM invasive growth. HI BrM invasion pattern was associated with delayed growth in the context of STAT3 inhibition or genetic ablation. We demonstrate that pSTAT3+ RAs secrete Chitinase 3-like-1 (CHI3L1), which is a known STAT3 transcriptional target. Furthermore, single-cell RNA sequencing identified CHI3L1-expressing RAs in human HI BrM. STAT3 activation, or recombinant CHI3L1 alone, induced cancer cell invasion into the brain parenchyma using a brain slice-tumor plug co-culture assay.

CONCLUSIONS

Together, these data reveal that pSTAT3+ RA-derived CHI3L1 is associated with BrM invasion, implicating STAT3 and CHI3L1 as clinically relevant therapeutic targets for the treatment of HI BrM.

The clinical, molecular, and therapeutic implications of time from primary diagnosis to brain metastasis in lung and breast cancer patients

PURPOSE

Lung cancer (LC) and breast cancer (BC) are the most common causes of brain metastases (BMs). Time from primary diagnosis to BM (TPDBM) refers to the time interval between initial LC or BC diagnosis and development of BM. This research aims to identify clinical, molecular, and therapeutic risk factors associated with shorter TPDBM.

METHODS

We retrospectively reviewed all diagnosed LC and BC patients with BM at Harbin Medical University Cancer Hospital from 2016 to 2020. A total of 570 patients with LC brain metastasis (LCBM) and 173 patients with breast cancer brain metastasis (BCBM) patients who met the inclusion criteria were enrolled for further analysis. BM free survival time curves were generated using Kaplan-Meier analyses. Univariate and multivariate Cox regression analyses were applied to identify risk factors associated with earlier development of BM in LC and BC, respectively.

RESULTS

The median TPDBM was 5.3 months in LC and 44.4 months in BC. In multivariate analysis, clinical stage IV and M1 stage were independent risk factors for early development of LCBM. LC patients who received chemotherapy, targeted therapy, pulmonary radiotherapy, and pulmonary surgery had longer TPDBM. For BC patients, age ≥ 50 years, Ki67 ≥ 0.3, HER2 positive or triple-negative breast cancer subtype, advanced N stage, and no mastectomy were correlated with shorter TPDBM.

CONCLUSIONS

This single-institutional study helps identify patients who have a high risk of developing BM early. For these patients, early detection and intervention could have clinical benefits.

The efficiency and safety of temozolomide and PD-1/L1 inhibitors in pretreated NSCLC with brain metastasis: a retrospective cohort

OBJECTIVE

Previous research has shown that both temozolomide (TMZ) and PD-1/L1 inhibitors (PD-1/L1) alone exhibit certain potential in the treatment of non-small cell lung cancer (NSCLC) with brain metastases (BM), in this study, we will explore combining the two in order to seek new effective treatment options for NSCLC with BM.

MATERIAL AND METHODS

During 2021.1 to 2023.12, we collected the date of these pretreated-NSCLC with BM who accept the treatment of TMZ and PD-1/L1, the objective response ratio (ORR), progression-free survival (PFS) and overall survival (OS) were set as the primary endpoint, meanwhile, the toxicity of such regimen was also recorded.

RESULTS

About 42 patients are enrolled, our primary analysis demonstrated that the ORR of such regimen toward NSCLC with BM was 26.19%, with Approximate intracranial and extracranial lesion ORR was 6% and 20% respectively, the DCR was about 64.29%, the mean PFS and OS was about 4 m and 8.5 m. Further analysis indicated that the efficiency correlated with the diagnosis-Specific Graded Prognostic Assessment (ds-GPA) score. Moreover, the toxicity can also be tolerated, indicating the application potential of such regimen against NSCLC with BM.

CONCLUSIONS

Our results exhibited that with tolerated toxicity, the combination of TMZ and PD-1/L1 shows promising efficiency against NSCLC with BM, this would be of great significance for the treatment of NSCLC with brain metastasis. However, due to the limitation of sample and retrospective property, the real value of such regimen needed to be further confirmed in the future.

Synchronous skull base and spinal metastases in a patient with treatment-resistant, high-grade serous adenocarcinoma of tubo-ovarian origin

Brain metastases (BMs) arising from ovarian cancer remain rare. Spinal cord metastases are even rarer, accounting for just 0.4% of total metastatic spinal cord compressions. In this report, we describe a case of a woman in her 70s who developed sequential brain and spinal cord metastases during her treatment for high-grade serous ovarian cancer, without a germline or somatic BRCA mutation. Following completion of neoadjuvant chemotherapy, interval debulking surgery and adjuvant chemotherapy, relapsed disease was ultimately identified as a single BM, curiously mimicking an acoustic neuroma. Subsequently, spinal cord metastases rapidly developed. Throughout, multidisciplinary team meetings guided decisions on patient management. In this report, we highlight the rarity of such a presentation and discuss the possible role of disease pathophysiology, associated systemic anticancer therapy resistance, and treatment possibilities for both cerebral and spinal metastases.

Targeting the HSP47-collagen axis inhibits brain metastasis by reversing M2 microglial polarization and restoring anti-tumor immunity

Brain metastases (BrMs) are the leading cause of death in patients with solid cancers. BrMs exhibit a highly immunosuppressive milieu and poor response to immunotherapies; however, the underlying mechanism remains largely unclear. Here, we show that upregulation of HSP47 in tumor cells drives metastatic colonization and outgrowth in the brain by creating an immunosuppressive microenvironment. HSP47-mediated collagen deposition in the metastatic niche promotes microglial polarization to the M2 phenotype via the α2β1 integrin/nuclear factor κB pathway, which upregulates the anti-inflammatory cytokines and represses CD8+ T cell anti-tumor responses. Depletion of microglia reverses HSP47-induced inactivation of CD8+ T cells and abolishes BrM. Col003, an inhibitor disrupting HSP47-collagen association restores an anti-tumor immunity and enhances the efficacy of anti-PD-L1 immunotherapy in BrM-bearing mice. Our study supports that HSP47 is a critical determinant of M2 microglial polarization and immunosuppression and that blocking the HSP47-collagen axis represents a promising therapeutic strategy against brain metastatic tumors.

Osimertinib is associated with improved outcomes in pre-treated non-small cell lung cancer leptomeningeal metastases: A systematic review and meta-analysiss

Purpose

Leptomeningeal metastasis (LM) is a severe complication of non-small cell lung cancer (NSCLC). In patients with NSCLC LM harboring epidermal growth factor receptor (EGFR) mutations, osimertinib is favored over alternative EGFR tyrosine kinase inhibitors (TKIs). However, the efficacy of osimertinib relative to other EGFR-TKIs is not well established for patients with LM. We aimed to compare the efficacy of EGFR-TKIs in EGFR-mutated NSCLC LM.

Methods

This systematic review and meta-analysis performed according to PRISMA guidelines included studies of adult patients with EGFR-mutated NSCLC and a diagnosis of LM who received an EGFR-TKI for the treatment of LM. We searched Medline ALL, Embase, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science Core Collection. The evaluation of biases was done by using the Ottawa-Newscastle scale. The hazard ratio was used as the parameter of interest for overall survival (OS) and central nervous system-specific progression-free survival (PFS).

Results

128 publications were included with 243 patients and 282 lines of EGFR-TKI for NSCLC LM that met inclusion criteria. The median PFS in patients receiving any EGFR-TKI was 9.1 months, and the median OS was 14.5 months. In univariate analyses of the entire cohort, osimertinib treatment demonstrated significantly prolonged PFS, but not OS, compared to other EGFR-TKIs. Osimertinib demonstrated significantly prolonged PFS and OS in the subset of patients who were previously treated with EGFR-TKIs, but not in EGFR-TKI naïve patients.

Conclusion

Osimertinib is associated with improved outcomes compared to other EGFR-TKIs, particularly in patients previously treated with EGFR-TKIs. An important limitation is that most patients were derived from retrospective reports. These results highlight the need for prospective studies for this difficult-to-treat patient population.

Long-Term Results of Stereotactic Radiotherapy in Patients with at Least 10 Brain Metastases at Diagnosis

PURPOSE

to evaluate an SRT approach in patients with at least 10 lesions at the time of BM initial diagnosis.

METHODS

This is a monocentric prospective cohort of patients treated by SRT, followed by a brain MRI every two months. Subsequent SRT could be delivered in cases of new BMs during follow-up. The main endpoints were local control rate (LCR), overall survival (OS), and strategy success rate (SSR). Acute and late toxicity were evaluated.

RESULTS

Seventy patients were included from October 2014 to January 2019, and the most frequent primary diagnosis was non-small-cell lung cancer (N = 36, 51.4%). A total of 1174 BMs were treated at first treatment, corresponding to a median number of 14 BMs per patient. Most of the patients (N = 51, 72.6%) received a single fraction of 20-24 Gy. At 1 year, OS was 62.3%, with a median OS of 19.2 months, and SSR was 77.8%. A cumulative number of 1537 BM were treated over time, corresponding to a median cumulative number of 16 BM per patient. At 1-year, the LCR was 97.3%, with a cumulative incidence of radio-necrosis of 2.1% per lesion. Three patients (4.3%) presented Grade 2 toxicity, and there was no Grade ≥ 3 toxicity. The number of treated BMs and the treatment volume did not influence OS or SSR (p > 0.05).

CONCLUSIONS

SRT was highly efficient in controlling the BM, with minimal side effects. In this setting, an SRT treatment should be proposed even in patients with ≥10 BMs at diagnosis.

Genomic analysis of human brain metastases treated with stereotactic radiosurgery reveals unique signature based on treatment failure

Stereotactic radiosurgery (SRS) has been shown to be efficacious for the treatment of limited brain metastasis (BM); however, the effects of SRS on human brain metastases have yet to be studied. We performed genomic analysis on resected brain metastases from patients whose resected lesion was previously treated with SRS. Our analyses demonstrated for the first time that patients possess a distinct genomic signature based on type of treatment failure including local failure, leptomeningeal spread, and radio-necrosis. Examination of the center and peripheral edge of the tumors treated with SRS indicated differential DNA damage distribution and an enrichment for tumor suppressor mutations and DNA damage repair pathways along the peripheral edge. Furthermore, the two clinical modalities used to deliver SRS, LINAC and GK, demonstrated differential effects on the tumor landscape even between controlled primary sites. Our study provides, in human, biological evidence of differential effects of SRS across BM's.

Prevalence, characteristics, and risk factors of venous thromboembolism in patients with brain tumor undergoing craniotomy: a meta-analysis

BACKGROUND

Brain tumor patients undergoing craniotomy are significantly associated with the development of venous thromboembolism (VTE), while the contributing factors remains controversial. Our study aimed to investigate the prevalence and risk factors for VTE in postoperational brain tumor patients.

METHODS

We searched the PubMed, Embase, Web of Science, Medline, and Cochrane Library databases from their inception to July 2023. Article selection, data extraction, and study quality assessment were performed independently by two reviewers. Publication bias was assessed using Egger's and Begg's tests. Stata 15.0 software was used for data analysis.

RESULTS

A total of 25 studies were considered, with a total of 49,620 brain tumor individuals. The pooled prevalence of VTE during hospitalization in postoperational brain tumor patients was 9% [95% CI: (0.08, 0.10)]. Moreover, our results demonstrated that patients with VTE were older than those without VTE [mean difference [MD] = 8.14, 95% CI: (4.97, 11.30)]. The following variables were significantly associated with VTE: prior history of VTE [OR = 7.81, 95% CI: (3.62, 16.88)], congestive heart failure [OR = 2.33, 95% CI: (1.08-5.05)], diabetes [OR = 1.87, 95% CI: (1.12-3.10)], hypertension [OR = 1.27, 95% CI: (1.07-1.50)], steroid use [OR = 1.63, 95% CI: (1.41, 1.88)], high white blood cells counts [MD = 0.32, 95% CI: (0.01, 0.63)], and high fibrinogen levels [MD = 0.19, 95% CI: (0.08, 0.30)].

CONCLUSION

This meta-analysis identified risk factors for postoperational VTE in patients with brain tumor, which can serve as a theoretical foundation for medical staff to manage and treat VTE.

TRIAL REGISTRATION

CRD42023357459.

The study of primary and acquired resistance to first-line osimertinib to improve the outcome of EGFR-mutated advanced Non-small cell lung cancer patients: the challenge is open for new therapeutic strategies

The development of targeted therapy in epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) patients has radically changed their clinical perspectives. Current first-line standard treatment for advanced disease is commonly considered third-generation tyrosine kinase inhibitors (TKI), osimertinib. The study of primary and acquired resistance to front-line osimertinib is one of the main burning issues to further improve patients' outcome. Great heterogeneity has been depicted in terms of duration of clinical benefit and pattern of progression and this might be related to molecular factors including subtypes of EGFR mutations and concomitant genetic alterations. Acquired resistance can be categorized into two main classes: EGFR-dependent and EGFR-independent mechanisms and specific pattern of progression to first-line osimertinib have been demonstrated. The purpose of the manuscript is to provide a comprehensive overview of literature about molecular resistance mechanisms to first-line osimertinib, from a clinical perspective and therefore in relationship to emerging therapeutic approaches.

Interrogation of endothelial and mural cells in brain metastasis reveals key immune-regulatory mechanisms

Brain metastasis (BrM) is a common malignancy, predominantly originating from lung, melanoma, and breast cancers. The vasculature is a key component of the BrM tumor microenvironment with critical roles in regulating metastatic seeding and progression. However, the heterogeneity of the major BrM vascular components, namely endothelial and mural cells, is still poorly understood. We perform single-cell and bulk RNA-sequencing of sorted vascular cell types and detect multiple subtypes enriched specifically in BrM compared to non-tumor brain, including previously unrecognized immune regulatory subtypes. We integrate the human data with mouse models, creating a platform to interrogate vascular targets for the treatment of BrM. We find that the CD276 immune checkpoint molecule is significantly upregulated in the BrM vasculature, and anti-CD276 blocking antibodies prolonged survival in preclinical trials. This study provides important insights into the complex interactions between the vasculature, immune cells, and cancer cells, with translational relevance for designing therapeutic interventions.

Advancement of fluorescent aminopeptidase probes for rapid cancer detection-current uses and neurosurgical applications

Surgical resection is considered for most brain tumors to obtain tissue diagnosis and to eradicate or debulk the tumor. Glioma, the most common primary malignant brain tumor, generally has a poor prognosis despite the multidisciplinary treatments with radical resection and chemoradiotherapy. Surgical resection of glioma is often complicated by the obscure border between the tumor and the adjacent brain tissues and by the tumor's infiltration into the eloquent brain. 5-aminolevulinic acid is frequently used for tumor visualization, as it exhibits high fluorescence in high-grade glioma. Here, we provide an overview of the fluorescent probes currently used for brain tumors, as well as those under development for other cancers, including HMRG-based probes, 2MeSiR-based probes, and other aminopeptidase probes. We describe our recently developed HMRG-based probes in brain tumors, such as PR-HMRG, combined with the existing diagnosis approach. These probes are remarkably effective for cancer cell recognition. Thus, they can be potentially integrated into surgical treatment for intraoperative detection of cancers.

Novel radiotherapeutic strategies in the management of brain metastases: Challenging the dogma

The role of radiation therapy in the management of brain metastasis is evolving. Advancements in machine learning techniques have improved our ability to both detect brain metastasis and our ability to contour substructures of the brain as critical organs at risk. Advanced imaging with PET tracers and magnetic resonance imaging-based artificial intelligence models can now predict tumor control and differentiate tumor progression from radiation necrosis. These advancements will help to optimize dose and fractionation for each patient's lesion based on tumor size, histology, systemic therapy, medical comorbidities/patient genetics, and tumor molecular features. This review will discuss the current state of brain directed radiation for brain metastasis. We will also discuss future directions to improve the precision of stereotactic radiosurgery and optimize whole brain radiation techniques to improve local tumor control and prevent cognitive decline without forming necrosis.

HSA-net with a novel CAD pipeline boosts both clinical brain tumor MR image classification and segmentation

Brain tumors are among the most prevalent neoplasms in current medical studies. Accurately distinguishing and classifying brain tumor types accurately is crucial for patient treatment and survival in clinical practice. However, existing computer-aided diagnostic pipelines are inadequate for practical medical use due to tumor complexity. In this study, we curated a multi-centre brain tumor dataset that includes various clinical brain tumor data types, including segmentation and classification annotations, surpassing previous efforts. To enhance brain tumor segmentation accuracy, we propose a new segmentation method: HSA-Net. This method utilizes the Shared Weight Dilated Convolution module (SWDC) and Hybrid Dense Dilated Convolution module (HDense) to capture multi-scale information while minimizing parameter count. The Effective Multi-Dimensional Attention (EMA) and Important Feature Attention (IFA) modules effectively aggregate task-related information. We introduce a novel clinical brain tumor computer-aided diagnosis pipeline (CAD) that combines HSA-Net with pipeline modification. This approach not only improves segmentation accuracy but also utilizes the segmentation mask as an additional channel feature to enhance brain tumor classification results. Our experimental evaluation of 3327 real clinical data demonstrates the effectiveness of the proposed method, achieving an average Dice coefficient of 86.85 % for segmentation and a classification accuracy of 95.35 %. We also validated the effectiveness of our proposed method using the publicly available BraTS dataset.

Exosomal microRNAs in breast cancer: towards theranostic applications

Breast cancer is one of the top two reproductive cancers responsible for high rates of morbidity and mortality among women globally. Despite the advancements in the treatment of breast cancer, its early diagnosis remains a challenge. Recent evidence indicates that despite the adroit use of numerous strategies to facilitate rapid and precision-oriented screening of breast cancer at the community level through the use of mammograms, Fine-needle aspiration cytology (FNAC) and biomarker tracking, no strategy has been unequivocally accepted as a gold standard for facilitating rapid screening for disease. This necessitates the need to identify novel strategies for the detection and triage of breast cancer lesions at higher rates of specificity, and sensitivity, whilst taking into account the epidemiologic and social-demographic features of the patients. Recent shreds of evidence indicate that exosomes could be a robust source of biomaterial for the rapid screening of breast cancer due to their high stability and their presence in body fluids. Increasing evidence indicates that the Exosomal microRNAs- play a significant role in modifying the tumour microenvironment of breast cancers, thereby potentially aiding in the proliferation, invasion and metastasis of breast cancer. In this review, we summarize the role of ExomiRs in the tumour microenvironment in breast cancer. These ExomiRs can also be used as candidate biomarkers for facilitating rapid screening and triaging of breast cancer patients for clinical intervention.

Intratumoral Delivery of Chimeric Antigen Receptor T Cells Targeting CD133 Effectively Treats Brain Metastases

PURPOSE

Brain metastases (BM) are mainly treated palliatively with an expected survival of less than 12 months after diagnosis. In many solid tumors, the human neural stem cell marker glycoprotein CD133 is a marker of a tumor-initiating cell population that contributes to therapy resistance, relapse, and metastasis.

EXPERIMENTAL DESIGN

Here, we use a variant of our previously described CD133 binder to generate second-generation CD133-specific chimeric antigen receptor T cells (CAR-T) to demonstrate its specificity and efficacy against multiple patient-derived BM cell lines with variable CD133 antigen expression.

RESULTS

Using both lung- and colon-BM patient-derived xenograft models, we show that a CD133-targeting CAR-T cell therapy can evoke significant tumor reduction and survival advantage after a single dose, with complete remission observed in the colon-BM model.

CONCLUSIONS

In summary, these data suggest that CD133 plays a critical role in fueling the growth of BM, and immunotherapeutic targeting of this cell population is a feasible strategy to control the outgrowth of BM tumors that are otherwise limited to palliative care. See related commentary by Sloan et al., p. 477.