Lung Cancer Brain Metastases Research Articles

Immunotherapy and brain metastasis in lung cancer: connecting bench side science to the clinic.

Brain metastases (BMs) are the most common form of intracranial malignant neoplasms in adults, with a profound impact on quality of life and traditionally associated with a dismal prognosis. Lung cancer accounts for approximately 40%-50% of BM across different tumors. The process leading to BMs is complex and includes local invasion, intravasation, tumor cells circulation into the bloodstream, disruption of the blood-brain barrier, extravasation of tumor cells into the brain parenchyma, and interaction with cells of the brain microenvironment, among others. Once the tumor cells have seeded in the brain parenchyma, they encounter different glial cells of the brain, as well as immune cells. The interaction between these cells and tumor cells is complex and is associated with both antitumoral and protumoral effects. To overcome the lethal prognosis associated with BMs, different treatment strategies have been developed, such as immunotherapy with immune checkpoint inhibitors, particularly inhibitors of the PD-1/PD-L1 axis, which have demonstrated to be an effective treatment in both non-small cell lung cancer and small cell lung cancer. These antibodies have shown to be effective in the treatment of BM, alone or in combination with chemotherapy or radiotherapy. However, many unsolved questions remain to be answered, such as the sequencing of immunotherapy and radiotherapy, the optimal management in symptomatic BMs, the role of the addition of anti-CTLA-4 antibodies, and so forth. The complexity in the management of BMs in the era of immunotherapy requires a multidisciplinary approach to adequately treat this devastating event. The aim of this review is to summarize evidence regarding epidemiology of BM, its pathophysiology, current approach to treatment strategies, as well as future perspectives.

Incidence and Risk Factors for Brain Metastases in Patients with Lung Cancer: A Systematic Review and Meta-Analysis

Brain metastases (BM) are a very common metastatic site in lung cancer, but the exact rate of metastasis is still controversial. Risk factors for BM development are also largely lacking, hampering personalized treatment strategies. This study aimed to identify the incidence and possible risk factors for BM in lung cancer. A systematic review, based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guide-lines, was conducted using PubMed, Medline databases and Cochrane Library databases from inception until February 2023. Two investigators independently searched and selected literature, included in randomized controlled trials and cohort studies. Heterogeneity was assessed using the χ2 test and the I2 statistic. Significant heterogeneity was indicated by P <0.05 in Cochrane Q tests and a ratio greater than 40% in I2 statistics. The review is registered on PROSPERO, number: CRD42022370173. Forty-nine studies were included in the meta-analysis. The results showed that the incidence rate of BM in non-small cell lung cancer (NSCLC) was 0.24 (95% confidence interval [CI]: 0.23-0.25; I2 = 97.1%). The incidence rate in early NSCLC was 0.11 (95% CI: 0.10-0.13), locally advanced NSCLC was 0.32 (95% CI: 0.29-0.34), and advanced NSCLC was 0.37 (95% CI: 0.35-0.38). Lung adenocarcinoma was more prone to BM in NSCLC (risk ratio [RR] = 3.59, 95% CI: 1.97-6.54; P<0.001). The BM rate of NSCLC with EGFR mutation was also higher (hazard ratio [HR] = 1.49, 95% CI: 1.14-1.94; P = 0.004). Sex and smoking had no significant effect on the incidence of BM in NSCLC. Prophylactic Cranial Irradiation (PCI) could significantly reduce BM in NSCLC (HR = 0.36, 95% CI: 0.23-0.56; P<0.001), but chemotherapy had no obvious effect on decreasing the rate of BM (HR = 0.91, 95% CI: 0.54-1.54; P = 0.73). The incidence rate of BM in small cell lung cancer (SCLC) was 0.28 (95% CI: 0.27-0.30; I2 = 95.9%), and 0.23 (95% CI: 0.20-0.25) in the limited-stage SCLC. Older age (≥65) (HR = 0.70, 95% CI: 0.54-0.92; P = 0.01) were associated with less BM in SCLC. A higher T stage (≥T3) (HR = 1.72, 95% CI: 1.16-2.56; P = 0.007) was a significant risk factor for BM, while sex, smoking dose were not. PCI could also significantly decreased BM in SCLC (HR = 0.47, 95% CI: 0.38-0.58; P<0.001). This study is the first meta-analysis of BM incidence rate in lung cancer, and further explores the factors affecting BM, providing some suggestions for clinical decision-making of BM prevention in patients with lung cancer.

Intracranial Control with Combined Dual Immune-Checkpoint Blockade and SRS for Melanoma and NSCLC Brain Metastases

It is unknown whether the use of dual immune-checkpoint inhibition (D-ICI) combined with stereotactic radiosurgery (SRS) affects local control of brain metastases (BMs). We sought to characterize the efficacy of SRS and D-ICI in patients with BMs in a large, single-institution cohort. Patients with melanoma and non-small cell lung cancer (NSCLC) BMs treated with SRS from January 1, 2016 to August 1, 2022 were evaluated. Patients were stratified by treatment with D-ICI versus single ICI (S-ICI). Concurrent ICI was defined as ICI given within four weeks of SRS. Local recurrence (LR), intracranial progression (IP), and overall survival (OS) were estimated using competing risk and Kaplan-Meier analyses. IP included both local and distant intracranial recurrence. One thousand seven hundred four SRS-treated BMs from 288 patients met inclusion criteria. 55% of patients were symptomatic from their BMs at presentation. Median age, KPS, number of lesions, and SRS courses were 64 (Q1Q3:56-70.5), 90 (80-90), 2 (1-4), and 1 (1-2), respectively. One hundred twenty-eight (44%) melanoma and 160 (56%) NSCLC patients were included. 82 (28.5%), 129 (44.8%), and 77 (26.7%) patients were treated with D-ICI, S-ICI, or SRS alone. Median SRS dose, fractions, and PTV were 20 (Q1Q3:20-25), 1 (1-5), and 0.3cc3 (0.1-1.2). The median follow-up was 14.3 months. One hundred twenty-seven (7.45%) BMs recurred post-SRS and the median time to LR was 4.8 months (Q1Q3:3.0-9.2). On competing risk analysis, LR was significantly reduced with D-ICI (HR: 0.452, p = 0.0024), but not with S-ICI (HR: 0.693, p = 0.0596) compared to SRS alone. The 1-year LR was 3.77% (95% CI = 2.19-6.00), 6.8% (5.19-8.70), and 8.96% (6.48-11.93) with D-ICI, S-ICI, and SRS alone. The median time to IP was 4.1 months (Q1Q3 = 2.9-9.5). On competing risk analysis, IP was significantly reduced with D-ICI (HR = 0.638, p = 0.031), but not with S-ICI (HR = 0.756, p = 0.106) compared to SRS alone. 1-year IP was 40.05% (95% CI = 29.14-50.70), 51.86% (42.78-60.19), and 58.49% (46.30-68.84) with D-ICI, S-ICI, and SRS alone. Concurrent delivery of D-ICI and SRS significantly reduced IP (HR = 0.463, p = 0.0071), whereas other combinations of timing and ICI did not reach significance. Median OS was 11.9 months after SRS. On Kaplan Meier analysis, OS was significantly improved with D-ICI (HR = 0.616, 95% CI = 0.412-0.923, p = 0.019), but not with S-ICI (HR = 0.877, 95% CI = 0.633-1.217, p = 0.433) compared to SRS alone. Hospitalizations (p = 0.021) and immune-related adverse events (irAEs) (p<0.001) were increased with D-ICI. Any grade radiation necrosis (RN) was also increased with D-ICI (p = 0.013), but neurologic adverse events were comparable across cohorts (p = 0.572). D-ICI combined with SRS was associated with improved local control, intracranial control, and overall survival compared to SRS alone, whereas S-ICI was not associated with an improvement in these outcomes. However, D-ICI was also associated with increased risks of irAEs and RN.

Comparative proteomic profiling of plasma exosomes in lung cancer cases of liver and brain metastasis

BackgroundMetastases within liver or the brain are the most common causes of mortality from lung cancer (LC). Predicting liver or brain metastases before having evidence from imaging of the tumors is challenging but important for early patient intervention. According to mounting evidence, exosomes circulating within blood may facilitate cancer spread by transporting certain proteins for target cells.MethodsUsing liquid chromatography–MS/MS, we investigated the plasma exosomes’ proteomic profiles derived from 42 metastatic LC patients [16 solitary liver metastasis (LM), together with 26 solitary brain metastasis (BM)] and 25 local advanced (LA) lung cancer cases without metastasis, together with five healthy controls (HC), assessing the LM and BM pathogenesis and find potential novel organ-designated proteomic biomarkers. Using ELISA assay, we verified the expression levels of three plasma exosomal protein biomarkers in 110 LC patients, including 40 solitary LM, 32 solitary BM and 38 LA, and 25 HC.ResultsIn total, 143 and 120 differentially expressed exosome-based proteins (DEEPs) were found to be dysregulated in LM and BM of lung cancer (LM-DEEPs, BM-DEEPs), compared for LA lung cancer samples, respectively. The bioinformatics analyses indicated the heterogeneity and homogeneity in LM-DEEPs and BM-DEEPs. They were primarily engaged within proteomic triggering cascade, ECM-receptor interaction, and the collagen-containing extracellular matrix. Regarding heterogeneity, LM-DEEPs primarily consisted of proteoglycans, lipoprotein, integrin, and heat shock protein, whereas the BM-DEEPs consisted of calcium-dependent/S100 proteins. Furthermore, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC)-plasma-stemming exosome proteomics showed heterogeneity, which helped to explain some of the differences between SCLC and NSCLC's metastatic features. We also found that SELL and MUC5B could be used as diagnostic markers of BM, while APOH, CD81, and CCT5 could help diagnose LM in LC patients. Additionally, we demonstrated in a validation cohort that MUC5B and SELL could serve as biomarkers for diagnosing BM, and APOH could be a novel potential diagnostic biomarker of LM.ConclusionWe presented the comprehensive and comparative plasma-stemming exosomes’ proteomic profiles from cases of LC who had isolated liver and brain metastases for the first time. We also suggested several possible biomarkers and pathogenic pathways that might be a great starting point for future research on LC metastasis.

Bevacizumab reduces peritumoral brain edema in lung cancer brain metastases after radiotherapy.

The aim of this study was to investigate the efficacy of bevacizumab (Bev) in reducing peritumoral brain edema (PTBE) after stereotactic radiotherapy (SRT) for lung cancer brain metastases. A retrospective analysis was conducted on 44 patients with lung cancer brain metastases (70 lesions) who were admitted to our oncology and Gamma Knife center from January 2020 to May 2022. All patients received intracranial SRT and had PTBE. Based on treatment with Bev, patients were categorized as SRT + Bev and SRT groups. Follow-up head magnetic resonance imaging was performed to calculate PTBE and tumor volume changes. The edema index (EI) was used to assess the severity of PTBE. Additionally, the extent of tumor reduction and intracranial progression-free survival (PFS) were compared between the two groups. The SRT + Bev group showed a statistically significant difference in EI values before and after radiotherapy (p = 0.0115), with lower values observed after treatment, but there was no difference in the SRT group (p = 0.4008). There was a difference in the distribution of EI grades in the SRT + Bev group (p = 0.0186), with an increased proportion of patients at grades 1-2 after radiotherapy, while there was no difference in the SRT group (p > 0.9999). Both groups demonstrated a significant reduction in tumor volume after radiotherapy (p < 0.05), but there was no difference in tumor volume changes between the two groups (p = 0.4089). There was no difference in intracranial PFS between the two groups (p = 0.1541). Bevacizumab significantly reduces the severity of PTBE after radiotherapy for lung cancer. However, its impact on tumor volume reduction and intracranial PFS does not reach statistical significance.

Genetic Intratumor Heterogeneity Remodels the Immune Microenvironment and Induces Immune Evasion in Brain Metastasis of Lung Cancer

IntroductionBrain metastasis, with the highest incidence in patients with lung cancer, significantly worsens prognosis and poses challenges to clinical management. To date, how brain metastasis evades immune elimination remains unknown. MethodsWhole-exome sequencing and RNA sequencing were performed on 30 matched brain metastasis, primary lung adenocarcinoma, and normal tissues. Data from The Cancer Genome Atlas primary lung adenocarcinoma cohort, including multiplex immunofluorescence, were used to support the findings of bioinformatics analysis. ResultsOur study highlights the key role of intratumor heterogeneity of genomic alterations in the metastasis process, mainly caused by homologous recombination deficiency or other somatic copy number alteration–associated mutation mechanisms, leading to increased genomic instability and genomic complexity. We further proposed a selection model of brain metastatic evolution in which intratumor heterogeneity drives immune remodeling, leading to immune escape through different mechanisms under local immune pressure. ConclusionsOur findings provide novel insights into the metastatic process and immune escape mechanisms of brain metastasis and pave the way for precise immunotherapeutic strategies for patients with lung cancer with brain metastasis.

P20.01.A CLINICAL APPLICATION OF RELATIONSHIP BETWEEN GENETIC ALTERATION AND INTRAOPERATIVE FLUORESCENCE ACTIVITY OF 5-AMINOLEVULINIC ACID IN BRAIN METASTASIS OF NON-SMALL CELL LUNG CANCER

Abstract BACKGROUND Distant metastasis into major organ is a major cause of death in cancer patients. Especially, metastasis to brain is known to duplicate the mortality of cancer patients because brain metastasis makes patients neurologically independent in daily activities. Despite surgical resection of brain metastasis is a core strategy for management, it is not possible for all brain metastasis due to eloquent location, multiple lesions, or clinical condition of patient. With advancement of technology in brain tumor surgery, fluorescence image, such as 5-aminolevulinic acid (5-ALA), can help detect the residual tumor during surgery. Recently, genetic alteration of cancer is additionally considered as prognostic factor with being added into traditional prognostic system, such as GPA scoring system. The primary objective of this study is to examine the fluorescence patterns of 5-ALA in brain metastasis surgery and investigate the results of genetic alteration in brain metastasis using next generation sequencing technique. MATERIAL AND METHODS Medical records of patients with brain metastasis of non-small cell lung cancer at our center from January 2017 to June 2022. Among them, the patients who were treated with surgical resection under 5-ALA fluorescence image and had NGS results were included in the analysis. RESULTS Total 72 patients were eligible for analysis. Mean follow-up duration was 12.36 months. Recurrence occurred in 28 (38.9%) patients and 46 (63.9%) patients succumbed to NSCLC. Mean recurrence-free survival (RFS) was 14.57 months and mean overall survival (OS) was 16.29 months. Strong fluorescence was obtained in 56 (77.8%) patients during surgery. In the NGS data of brain metastasis, genetic alteration of cell cycle regulation, DNA repair, tumorigenesis, proliferation, epigenetic regulation, and cancer immunology were detected in 73.6%, 44.4%, 56.9%, 66.7%, 30.6%, and 2.8%, respectively. In multivariate analysis, KPS, RPA class, extent of resection, modality of adjuvant treatment, genetic alteration of cell cycle regulation and cellular proliferation were associated with RFS. Additionally, age, KPS, status of NSCLC, RPA class, GPA score, modality of adjuvant treatment, genetic alteration of cell cycle regulation and cellular proliferation were associated with OS. CONCLUSION The presenting study suggested that microscopic complete resection with assist of fluorescence image could improve clinical outcome, and strong fluorescence image could reflect the genetic alteration of cell cycle regulation and cellular proliferation which are poor prognostic factors.

Whole-tumor histogram analysis of multi-parametric MRI for differentiating brain metastases histological subtypes in lung cancers: relationship with the Ki-67 proliferation index.

This study aims to investigate the predictive value of preoperative whole-tumor histogram analysis of multi-parametric MRI for histological subtypes in patients with lung cancer brain metastases (BMs) and explore the correlation between histogram parameters and Ki-67 proliferation index. The preoperative MRI data of 95 lung cancer BM lesions obtained from 73 patients (42 men and 31 women) were retrospectively analyzed. Multi-parametric MRI histogram was used to distinguish small-cell lung cancer (SCLC) from non-small cell lung cancer (NSCLC), and adenocarcinoma (AC) from squamous cell carcinoma (SCC), respectively. The T1-weighted contrast-enhanced (T1C) and apparent diffusion coefficient (ADC) histogram parameters of the volumes of interest (VOIs) in all BMs lesions were extracted using FireVoxel software. The following histogram parameters were obtained: maximum, minimum, mean, standard deviation (SD), variance, coefficient of variation (CV), skewness, kurtosis, entropy, and 1st-99th percentiles. Then investigated their relationship with the Ki-67 proliferation index. The skewness-T1C, kurtosis-T1C, minimum-ADC, mean-ADC, CV-ADC and 1st - 90th ADC percentiles were significantly different between the SCLC and NSCLC groups (all p < 0.05). When the 10th-ADC percentile was 668, the sensitivity, specificity, and accuracy (90.80%, 76.70% and 86.32%, respectively) for distinguishing SCLC from NSCLC reached their maximum values, with an AUC of 0.895 (0.824 - 0.966). Mean-T1C, CV-T1C, skewness-T1C, 1st - 50th T1C percentiles, maximum-ADC, SD-ADC, variance-ADC and 75th - 99th ADC percentiles were significantly different between the AC and SCC groups (all p < 0.05). When the CV-T1C percentiles was 3.13, the sensitivity, specificity and accuracy (75.00%, 75.60% and 75.38%, respectively) for distinguishing AC and SCC reached their maximum values, with an AUC of 0.829 (0.728-0.929). The 5th-ADC and 10th-ADC percentiles were strongly correlated with the Ki-67 proliferation index in BMs. Multi-parametric MRI histogram parameters can be used to identify the histological subtypes of lung cancer BMs and predict the Ki-67 proliferation index.

Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer.

The aim of this study was to investigate the feasibility of developing a deep learning (DL) algorithm for classifying brain metastases from non-small cell lung cancer (NSCLC) into epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement groups and to compare the accuracy with classification based on semantic features on imaging. Data set of 117 patients was analysed from 2014 to 2018 out of which 33 patients were EGFR positive, 43 patients were ALK positive and 41 patients were negative for either mutation. Convolutional neural network (CNN) architecture efficient net was used to study the accuracy of classification using T1 weighted (T1W) magnetic resonance imaging (MRI) sequence, T2 weighted (T2W) MRI sequence, T1W post contrast (T1post) MRI sequence, fluid attenuated inversion recovery (FLAIR) MRI sequences. The dataset was divided into 80% training and 20% testing. The associations between mutation status and semantic features, specifically sex, smoking history, EGFR mutation and ALK rearrangement status, extracranial metastasis, performance status and imaging variables of brain metastasis were analysed using descriptive analysis [chi-square test (χ2)], univariate and multivariate logistic regression analysis assuming 95% confidence interval (CI). In this study of 117 patients, the analysis by semantic method showed 79.2% of the patients belonged to ALK positive were non-smokers as compared to double negative groups (P = 0.03). There was a 10-fold increase in ALK positivity as compared to EGFR positivity in ring enhancing lesions patients (P = 0.015) and there was also a 6.4-fold increase in ALK positivity as compared to double negative groups in meningeal involvement patients (P = 0.004). Using CNN Efficient Net DL model, the study achieved 76% accuracy in classifying ALK rearrangement and EGFR mutations without manual segmentation of metastatic lesions. Analysis of the manually segmented dataset resulted in improved accuracy of 89% through this model. Both semantic features and DL model showed comparable accuracy in classifying EGFR mutation and ALK rearrangement. Both methods can be clinically used to predict mutation status while biopsy or genetic testing is undertaken.

CD44+ lung cancer stem cell-derived pericyte-like cells cause brain metastases through GPR124-enhanced trans-endothelial migration

Brain metastasis of lung cancer causes high mortality, but the exact mechanisms underlying the metastasis remain unclear. Here we report that vascular pericytes derived from CD44+ lung cancer stem cells (CSCs) in lung adenocarcinoma (ADC) potently cause brain metastases through the G-protein-coupled receptor 124 (GPR124)-enhanced trans-endothelial migration (TEM). CD44+ CSCs in perivascular niches generate the majority of vascular pericytes in lung ADC. CSC-derived pericyte-like cells (Cd-pericytes) exhibit remarkable TEM capacity to effectively intravasate into the vessel lumina, survive in the circulation, extravasate into the brain parenchyma, and then de-differentiate into tumorigenic CSCs to form metastases. Cd-pericytes uniquely express GPR124 that activates Wnt7-β-catenin signaling to enhance TEM capacity of Cd-pericytes for intravasation and extravasation, two critical steps during tumor metastasis. Furthermore, selective disruption of Cd-pericytes, GPR124, or the Wnt7-β-catenin signaling markedly reduces brain and liver metastases of lung ADC. Our findings uncover an unappreciated cellular and molecular paradigm driving tumor metastasis.

Genomic analysis and clinical correlations of non-small cell lung cancer brain metastasis

Up to 50% of patients with non-small cell lung cancer (NSCLC) develop brain metastasis (BM), yet the study of BM genomics has been limited by tissue access, incomplete clinical data, and a lack of comparison with paired extracranial specimens. Here we report a cohort of 233 patients with resected and sequenced (MSK-IMPACT) NSCLC BM and comprehensive clinical data. With matched samples (47 primary tumor, 42 extracranial metastatic), we show CDKN2A/B deletions and cell cycle pathway alterations to be enriched in the BM samples. Meaningful clinico-genomic correlations are noted, namely EGFR alterations in leptomeningeal disease (LMD) and MYC amplifications in multifocal regional brain progression. Patients who developed early LMD frequently have had uncommon, multiple, and persistently detectable EGFR driver mutations. The distinct mutational patterns identified in BM specimens compared to other tissue sites suggest specific biologic underpinnings of intracranial progression.

Warburg effect enhanced by AKR1B10 promotes acquired resistance to pemetrexed in lung cancer-derived brain metastasis

BackgroundResistance to pemetrexed (PEM), a rare chemotherapeutic agent that can efficiently cross the blood-brain barrier, limits the therapeutic efficacy for patients with lung cancer brain metastasis (BM). Aldo-keto reductase family 1 B10 (AKR1B10) was recently found to be elevated in lung cancer BM. The link between AKR1B10 and BM-acquired PEM is unknown.MethodsPEM drug-sensitivity was assessed in the preclinical BM model of PC9 lung adenocarcinoma cells and the BM cells with or without AKR1B10 interference in vitro and in vivo. Metabolic reprogramming of BM attributed to AKR1B10 was identified by chromatography-mass spectrometry (GC-MS) metabolomics, and the mechanism of how AKR1B10 mediates PEM chemoresistance via a way of modified metabolism was revealed by RNA sequencing as well as further molecular biology experimental approaches.ResultsThe lung cancer brain metastatic subpopulation cells (PC9-BrM3) exhibited significant resistance to PEM and silencing AKR1B10 in PC9-BrM3 increased the PEM sensitivity in vitro and in vivo. Metabolic profiling revealed that AKR1B10 prominently facilitated the Warburg metabolism characterized by the overproduction of lactate. Glycolysis regulated by AKR1B10 is vital for the resistance to PEM. In mechanism, AKR1B10 promoted glycolysis by regulating the expression of lactate dehydrogenase (LDHA) and the increased lactate, acts as a precursor that stimulates histone lactylation (H4K12la), activated the transcription of CCNB1 and accelerated the DNA replication and cell cycle.ConclusionsOur finding demonstrates that AKR1B10/glycolysis/H4K12la/CCNB1 promotes acquired PEM chemoresistance in lung cancer BM, providing novel strategies to sensitize PEM response in the treatment of lung cancer patients suffering from BM.

Retraction Note: N6-methyladenosine induced mir-143-3p promotes the brain metastasis of lung cancer via regulation of VASH1

Retraction Note: N6-methyladenosine induced mir-143-3p promotes the brain metastasis of lung cancer via regulation of VASH1

A 3-month survival model after Gamma Knife surgery in patients with brain metastasis from lung cancer with Karnofsky performance status ≤ 70

Gamma Knife surgery (GKS) for brain metastasis (BM) has been generally advocated for patients with a Karnofsky performance status (KPS) scale of ≥ 70. However, some patients with a poor KPS scale of < 70 are recoverable after GKS and show durable survival. A purpose of this study is to devise a 3-month survival prediction model to screen patients with BM with a KPS of ≤ 70 in whom GKS is needed. A retrospective analysis of 67 patients with a KPS scale of 60–70 undergoing GKS for BM of non-small cell lung cancer (NSCLC) from 2016 to 2020 in our institute was performed. Univariate and multivariate logistic regression analyses were performed to investigate factors related to survival for more than 3 months after GKS. The probability (P) prediction model was designed by giving a weight corresponding to the odds ratio of the variables. The overall survival was 9.9 ± 12.7 months (range 0.2–53.2), with a 3-month survival rate of 59.7% (n = 40). In multivariate logistic regression analysis, extracranial disease (ECD) control (p = .033), focal neurological deficit (FND) (p = .014), and cumulative tumor volume (∑ TV) (p = .005) were associated with 3-month survival. The prediction model of 3-month survival (Harrell’s C index = 0.767) was devised based on associated factors. In conclusion, GKS for BMs is recommended in selected patients, even if the KPS scale is ≤ 70.

BSBM-16 HLA CLASS-I ANTIGEN PRESENTATION MACHINERY AND IFN-γ PATHWAY ALTERATIONS IN LUNG CANCER BRAIN METASTASES

Abstract BACKGROUND Immune checkpoint inhibitors (ICI) can have activity in lung cancer brain metastases (LBM). However, the duration of responses is limited and most patients with LBM do not benefit from these therapies. Alterations in HLA class-I antigen presentation machinery via beta-2 microglobulin (B2M) downregulation and disruption of IFN-γ sensing were identified as mechanisms of immune evasion and ICI resistance in solid tumors. However, the expression and clinical significance of these pathways in LBM are poorly understood. METHODS Using multiplex quantitative immunofluorescence we measured the localized expression of B2M protein; and the IFN-γ pathway markers phospho-STAT1 (pSTAT1), and Interferon Regulatory Factor 1 (IRF-1) in 67 immunotherapy naïve LBM and 45 primary lung tumors (PLT), including 15 patients with paired samples represented in a tissue microarray. The markers were selectively measured in cytokeratin + tumor cells and in cytokeratin- stromal cells. Associations between the markers, PD-L1, TILs and clinicopathologic variables were compared between LBM and PLT. RESULTS LBM showed lower levels of B2M in both tumor and stroma compartments compared to PLT. In contrast, high tumor and stromal levels of pSTAT1 were observed in LBM and comparable levels of IRF-1 were found between both tumor sites. Consistently across LBM and PLT samples, pSTAT1 and IRF1 were strongly correlated, and a positive but weaker association was observed with B2M and TILs. Only in PLT high tumor-cell PD-L1 expression was associated with high levels of IRF-1. No statistically significant association was observed between the markers and clinicopathologic variables. Tumor B2M downregulation in PLT was associated with worse survival. CONCLUSION LBM show distinct immunomodulatory properties relative to PLT, characterized by reduced HLA class-I antigen presentation machinery, elevated IFN-γ signaling and reduced local adaptive immune responses. These results support differences in immune evasion mechanisms in LBM compared with the PLT, which may have biological and clinical implications.

BSBM-11 COMBINING IMMUNOTHERAPY AND WHOLE-BRAIN RADIATION THERAPY IN A NOVEL SYNGENEIC LUNG CANCER BRAIN METASTASIS PRECLINICAL MODEL: DOES TIMING OF ADMINISTRATION MATTER?

Abstract Approximately 50% of all brain metastasis cases originate from primary lung tumors. Whole-brain radiation therapy (WBRT) is a common treatment for patients with multiple brain metastases, but patients rarely survive longer than one year after diagnosis. Recent studies demonstrate improved outcomes with combinatorial radiotherapy and immunotherapy, but the optimal timing of immunotherapy administration is unclear. Eliciting a robust immune response post-immunotherapy is vital for therapeutic efficacy. Our work shows that the BBB is disrupted and proinflammatory cytokines are increased in the brain 12 hours post-WBRT in immunocompetent but not immunocompromised mice. Additionally, efflux transporter activity is decreased at this time point. This study utilizes a novel Lewis Lung Carcinoma cell line, LLC-Br, which was developed in our laboratory to preferentially metastasize to the brain. Mice were treated with immune checkpoint inhibitors (ICIs) before or after WBRT then we evaluated tumor progression, survival, and blood-tumor barrier (BTB) permeability. We hypothesized administration of ICI following WBRT would increase survival, decrease tumor burden, and increase BTB permeability in our preclinical syngeneic lung cancer brain metastasis model.

Immune checkpoint inhibitors for the treatment of non-small cell lung cancer brain metastases.

Lung cancer has the highest risk of brain metastasis (BM) among all solid carcinomas. The emergence of BM has a significant impact on the selection of oncologic treatment for patients. Immune checkpoint inhibitors (ICIs) are the most promising treatment option for patients without druggable mutations and have been shown to improve survival in patients with non-small cell lung cancer (NSCLC) BM in clinical trials with good safety. Moreover, ICI has shown certain effects in NSCLC BM, and the overall intracranial efficacy is comparable to extracranial efficacy. However, a proportion of patients showed discordant responses in primary and metastatic lesions, suggesting that multiple mechanisms may exist underlying ICI activity in BM. According to studies pertaining to tumor immune microenvironments, ICIs may be capable of provoking immunity in situ. Meanwhile, systematic immune cells activated by ICIs can migrate into the central nervous system and exert antitumor effects. This review summarizes the present evidence for ICI treatment efficacy in NSCLC BM and proposes the possible mechanisms of ICI treatment for NSCLC BMs based on existing evidence.

Expression of pannexin1 in lung cancer brain metastasis and immune microenvironment.

Brain metastases are the most common central nervous system malignancy, and the leading cause of cancer-related deaths. Non-small cell lung carcinomas (NSCLC) comprise the most common cell of origin. Immunotherapy, particularly checkpoint inhibitors, has emerged as the standard of care for many patients with advanced lung cancer. Pannexin1 (PANX1) is a transmembrane glycoprotein that forms large-pore channels and has been reported to promote cancer metastasis. However, the roles of PANX1 in lung cancer brain metastases and tumor immune microenvironment have not been characterized. 42 patient-matched formalin-fixed paraffin-embedded tissue samples from lung carcinomas and the subsequent brain metastases were constructed into three tissue microarrays (TMAs). PANX1 and markers of tumor-infiltrating immune cells (CD3, CD4, CD8, CD68, and TMEM119) were assessed using immunohistochemistry and digital image analysis. The expression of PANX1 was significantly higher in brain metastases than in their paired primary lung carcinoma. The high levels of PANX1 in lung carcinoma cells in the brain inversely correlated with infiltration of peripheral blood-derived macrophages. Our findings highlight the role of PANX1 in the progression of metastatic NSCLC, and the potential therapeutic approach of targeting PANX1 enhances the efficacy of immune checkpoint inhibitors in brain metastasis.

18F-FDG PET/CT radiomics predicts brain metastasis in I-IIIA resected Non-Small cell lung cancer

ObjectiveTo establish 18F-FDG PET/CT radiomics model for predicting brain metastasis in non-small cell lung cancer (NSCLC) patients. MethodsThis research comprised 203 NSCLC patients who had received surgical therapy at two institutions. To identify independent predictive factors of brain metastasis, metabolic indicators, CT features, and clinical features were investigated. A prediction model was established by incorporating radiomics signature and clinicopathological risk variables. The suggested model’s performance was assessed from the perspective of discrimination, calibration, and clinical application. ResultsThe C-indices of the PET/CT radiomics model in the training, internal validation, and external validation cohorts were 0.911, 0.825 and 0.800, respectively. According to the multivariate analysis, neuron-specific enolase (NSE) and air bronchogram were independent risk factors for brain metastasis (BM). Furthermore, the combined model integrating radiomics and clinicopathological characteristics related to brain metastasis performed better in terms of prediction, with C-indices of 0.927, 0.861, and 0.860 in the training, internal validation, and external validation cohorts, respectively. The decision curve analysis (DCA) suggested that the PET/CT nomogram was clinically beneficial. ConclusionsA predictive algorithm based on PET/CT imaging information and clinicopathological features may accurately predict the probability of brain metastasis in NSCLC patients following surgery. This presented doctors with a unique technique for screening NSCLC patients at high risk of brain metastasis.

Magnetic resonance imaging characteristics of brain metastases in small cell lung cancer.

Lung is the most common primary site of brain metastases (BMs). For different pathological types of BMs have some similar characteristics, it is still a challenge to confirm the origin based on their characteristics directly. BMs of small cell lung cancer (SCLC) have favorable therapeutic expectations due to their high sensitivity to radiotherapy. This study sought to identify unique characteristics of BMs in SCLC, aiming to assist in clinical decision-making. Patients diagnosed with BMs of lung cancer who received radiotherapy from January 2017 to January 2022 were reviewed (N = 284). Definitive diagnosis of BMs of SCLC was reached for 36 patients. All patients underwent head examination using magnetic resonance imaging. The number, size, location, and signal characteristics of lesions were analyzed. There were 7 and 29 patients with single focus and non-single focus, respectively. Ten patients had diffuse lesions, and the remaining 26 patients had a total of 90 lesions. These lesions were divided into three groups according to size: <1, 1-3, and >3 cm (43.33%, 53.34%, and 3.33%, respectively). Sixty-six lesions were located in the supratentorial area, primarily including cortical and subcortical lesions (55.56%) and deep brain lesions (20%). Moreover, 22 lesions were located in the infratentorial area. According to diffusion-weighted imaging and T1-weighted contrast enhancement, the imaging characteristics were classified into six patterns. Hyperintensity in diffusion-weighted imaging and homogeneous enhancement was the most common pattern of BMs in SCLC (46.67%), while partial lesions showed hyperintensity in diffusion-weighted imaging without enhancement (7.78%). The manifestations of BMs in SCLC were multiple lesions (diameter: 1-3 cm), hyperintensity in diffusion-weighted imaging, and homogeneous enhancement. Interestingly, hyperintensity in diffusion-weighted imaging without enhancement was also one of the characteristics.