Brain Metastases Of Lung Adenocarcinoma Research Articles

P3.03H.05 AKAP12 Deficiency Leads to Blood-Brain Barrier Disruption and Serves as a Crucial Diagnostic Marker for Brain Metastasis in Lung Adenocarcinoma

P3.03H.05 AKAP12 Deficiency Leads to Blood-Brain Barrier Disruption and Serves as a Crucial Diagnostic Marker for Brain Metastasis in Lung Adenocarcinoma

Epigenetic Regulation of RNF135 by LSD1 Promotes Stemness Maintenance and Brain Metastasis in LungAdenocarcinoma.

RING finger protein 135 (RNF135) is identified as a regulator in certain cancer types. However, its role and molecular mechanisms in lung adenocarcinoma (LUAD) are still unclear. Herein, we investigated the level of RNF135 in tumor tissues of LUAD patients using the UALCAN database and confirmed the data by real-time PCR and western blot analysis. The effects of RNF135 on stemness maintenance and migration/invasion capability of LUAD cells were investigated by sphere formation, flow cytometry, wound healing, and transwell assay. Limiting dilution xenograft assay and intracardiac injection of LUAD cells were applied to assess the implications of RNF135 in tumorigenesis and brain metastasis. Our results revealed that RNF135 was upregulated in tumor tissues of LUAD patients and was positively correlated with poor prognosis. Knockdown of RNF135 suppressed cancer stem cells (CSCs)-like properties, and migration/invasion capability of A549 and NCI-H1975 cells. Conversely, overexpression of RNF135 augmented CSCs-like traits and migration/invasion ability of LUAD cells. Limiting dilution xenograft assay demonstrated that RNF135 was required for the self-renewal of CSCs to initiate LUAD development. Overexpression of RNF135 in A549 cells increased their ability to metastasize to the brain in vivo. Mechanistically, the transcriptional activation of RNF135 by LSD1 involved H3K9me2 demethylation at the promoter region of RNF135. Reexpression of RNF135 in LSD1-silenced A549 cells was able to reverse LSD1-mediated stemness maintenance and migration/invasion capability. Overall, our results implied that targeting of LSD1/RNF135 axis might be a feasible method to suppress tumorigenesis and brain metastasis of LUAD patients.

Proteomics shows that brain metastases of lung adenocarcinoma overexpress ribosomal proteins in response to gamma knife radiosurgery

Gamma knife radiosurgery (GKRS) is recommended as the first-line treatment for brain metastases of lung adenocarcinoma (LUAD) in many guidelines, but its specific mechanism is unclear. We aimed to study the changes in the proteome of brain metastases of LUAD in response to the hyperacute phase of GKRS and further explore the mechanism of differentially expressed proteins (DEPs). Cancer tissues were collected from a clinical trial for neoadjuvant stereotactic radiosurgery before surgical resection of large brain metastases (ChiCTR2000038995). Five brain metastasis tissues of LUAD were collected within 24 h after GKRS. Five brain metastasis tissues without radiotherapy were collected as control samples. Proteomics analysis showed that 163 proteins were upregulated and 25 proteins were downregulated. GO and KEGG enrichment analyses showed that the DEPs were closely related to ribosomes. Fifty-three of 70 ribosomal proteins were significantly overexpressed, while none of them were underexpressed. The risk score constructed from 7 upregulated ribosomal proteins (RPL4, RPS19, RPS16, RPLP0, RPS2, RPS26 and RPS25) was an independent risk factor for the survival time of LUAD patients. Overexpression of ribosomal proteins may represent a desperate response to lethal radiotherapy. We propose that targeted inhibition of these ribosomal proteins may enhance the efficacy of GKRS.

The Effect of Intracranial Control After Intracranial Local Therapy on the Prognosis of Patients with Brain Metastasis of Lung Adenocarcinoma.

The aim of the present study was to assess the clinical outcomes and prognostic factors of lung adenocarcinoma patients with brain metastases (BMs) after intracranial local therapy. A total of 83 lung adenocarcinoma patients with BMs who underwent craniotomy combined with radiotherapy or intracranial radiotherapy alone were retrospectively analyzed. The intracranial tumor response was determined according to the Response Assessment in Neuro-Oncology of Brain Metastases (RANO-BM) criteria. The median overall survival (OS), intracranial progression-free survival (iPFS), and related prognostic factors were analyzed with the Kaplan‒Meier estimator method and Cox proportional hazards regression model. Among 83 patients, 20 patients received craniotomy combined with radiotherapy, and 63 patients received intracranial radiotherapy alone. Following intracranial local therapy, 11 patients (13.3%) achieved complete response (CR); among them, 8 patients underwent neurosurgical resection. In addition, 32 patients (38.55%) achieved partial response (PR), 32 patients (38.55%) experienced stable disease (SD), and 8 (9.6%) experienced progressive disease (PD). The median follow-up period was 25.4 months (range 0.8-49.6 months). The median follow-up time for the iPFS was 16.2 months (range 0.6-41.2 months). The median OS, iPFS were 28.2 months and 24.7 months. Epidermal growth factor receptor (EGFR) / anaplastic lymphoma kinase (ALK) mutations (HR 3.216, 95% confidence interval (CI) 1.269-8.150, p = 0.014) and iPFS (HR 0.881, 95% CI 0.836-0.929, p < 0.001) were found to be beneficial factors for OS. An intracranial-tumor CR was associated with a longer iPFS (PR: HR 0.052, 95% CI 0.009-0.297, p = 0.001; SD: HR 0.081, 95% CI 0.025-0.259, p < 0.001; PD: HR 0.216, 95% CI 0.077-0.606, p = 0.004). Prolonged iPFS was associated with better OS in lung adenocarcinoma patients with BMs following intracranial local therapy, and mutations of EGFR / ALK or an intracranial-tumor CR are independent prognostic factors for prolonged survival.

IL-34 and its receptors as predictors of brain metastasis and prognosis in lung adenocarcinoma: Unveiling insights through bioinformatic and immunohistochemical investigations

BackgroundBrain metastasis (BM) is a prevalent form of metastasis in lung adenocarcinoma (LUAD), necessitating investigations into the underlying mechanisms. Interleukin 34 (IL-34) and its receptors, macrophage colony-stimulating factor-1 receptor (CSF-IR), Syndecan-1 (SDC-1), and protein-tyrosine phosphatase zeta receptor (PTPRZ1), are known to play pivotal roles in the metastasis of malignant tumors, thereby holding promise as potential biomarkers for studying BM in LUAD. MethodsWe performed immunohistochemistry to analyze the expression of IL-34, CSF-1R, SDC-1, and PTPRZ1 in 10 pairs of LUAD primary tissues and BMs, along with 96 unpaired primary tissues and 68 unpaired BMs. Subsequently, we evaluated the association between protein expression and the occurrence of BM. Furthermore, Kaplan-Meier survival curve analysis was conducted on both network and clinical data to explore the association between protein expression and patient prognosis and survival. ResultsAt the protein level, the expression of IL-34 and its receptors showed significant variation between paired primary tumors and BMs in 10 LUAD patients. The levels of IL-34, CSF-1R, and SDC-1 expression are typically elevated in brain metastatic lesions of LUAD compared to primary LUAD tumors. Furthermore, patients with high CSF-1R expression in primary LUAD are at a greater risk of developing brain metastases. High expression of IL-34 and CSF-1R in primary LUAD lesions indicated poor disease-free survival (DFS) and overall survival (OS), while high expression of SDC-1 indicated poor OS. Cox multivariate analysis further revealed that CSF-1R and IL-34+CSF-1R positivity independently affected LUAD OS. These findings were further substantiated in unpaired samples. ConclusionsOur results indicate significant alterations in the expression of IL-34 and its receptors, CSF-1R and SDC-1, between LUAD primary lesions and BMs, with increased expression observed in BMs. LUAD patients with positive CSF-1R expression in primary lesions exhibited a higher likelihood of developing BM, and high expression of IL-34, CSF-1R, and SDC-1 correlated with poor prognosis. These findings contribute novel insights towards identifying potential treatment or diagnostic targets for metastatic LUAD.

Genetic characteristics of cerebrospinal fluid-derived circulating tumor DNA in brain metastases of lung adenocarcinoma.

e20503 Background: Brain metastases (BM), encompassing parenchymal metastases (PM) and leptomeningeal metastases (LM), are a common and fatal complication of advanced lung adenocarcinoma (LUAD). However, the genomic disparities between PM and LM, as determined by cerebrospinal fluid (CSF)-derived circulating tumor DNA (ctDNA), and its clinical utility as a liquid biopsy medium remain unclear. Methods: We conducted a retrospective study involving 33 patients diagnosed with BM from LUAD, comprising 16 cases with PM and 17 cases with LM, at Shandong Cancer Hospital between March 2018 and June 2021. CSF and matched peripheral blood lymphocyte samples were collected from all patients, and plasma samples were collected from 25 of them. Genomic profiles of CSF and plasma in patients with PM and LM were compared. CSF-ctDNA, plasma-ctDNA, and DNA from matched peripheral blood lymphocytes underwent next-generation sequencing (NGS) based on a 769 cancer-related gene panel. Results: A total of 363 mutations were detected in CSF-ctDNA, with 90.9% (30/33) of all LUAD patients with PM or LM showing mutations. EGFR mutations were the most common, occurring in PM samples from 56.3% (9/16) of patients and in LM samples from 76.5% (13/17) of patients, followed by other frequently mutated driver genes, including TP53 in 19 (57.6%) patients, MLH1 in 9 (27.3%) patients, and KMT2C in 8 (24.2%). Notably, EGFR 19del was more prevalent as a driver mutation in patients with LM compared to those with PM in our study, particularly the p.E746_A750del mutated subtype. Furthermore, the frequency of mutations in the mismatch repair (MMR) pathway was significantly higher in patients with LM than in those with PM. Additionally, CSF exhibited a more comprehensive profile of driver genomic mutations than matched plasma in patients with any form of BM, accompanied by a higher variation burden and detection of druggable mutations. Conclusions: CSF-ctDNA sequencing revealed distinct genomic patterns in patients with BM, particularly in LM, and could potentially enhance the management of BM patients compared to plasma.

Dissecting the MUC5AC/ANXA2 signaling axis: implications for brain metastasis in lung adenocarcinoma

Non-small cell lung carcinoma (NSCLC) exhibits a heightened propensity for brain metastasis, posing a significant clinical challenge. Mucin 5ac (MUC5AC) plays a pivotal role in the development of lung adenocarcinoma (LUAD); however, its role in causing brain metastases remains unknown. In this study, we aimed to investigate the contribution of MUC5AC to brain metastasis in patients with LUAD utilizing various brain metastasis models. Our findings revealed a substantial increase in the MUC5AC level in LUAD brain metastases (LUAD-BrM) samples and brain-tropic cell lines compared to primary samples or parental control cell lines. Intriguingly, depletion of MUC5AC in brain-tropic cells led to significant reductions in intracranial metastasis and tumor growth, and improved survival following intracardiac injection, in contrast to the observations in the control groups. Proteomic analysis revealed that mechanistically, MUC5AC depletion resulted in decreased expression of metastasis-associated molecules. There were increases in epithelial-to-mesenchymal transition, tumor invasiveness, and metastasis phenotypes in tumors with high MUC5AC expression. Furthermore, immunoprecipitation and proteomic analysis revealed a novel interaction of MUC5AC with Annexin A2 (ANXA2), which activated downstream matrix metalloproteases and facilitated extracellular matrix degradation to promote metastasis. Disrupting MUC5AC-ANXA2 signaling with a peptide inhibitor effectively abrogated the metastatic process. Additionally, treatment of tumor cells with an astrocyte-conditioned medium or the chemokine CCL2 resulted in upregulation of MUC5AC expression and enhanced brain colonization. In summary, our study demonstrates that the MUC5AC/ANXA2 signaling axis promotes brain metastasis, suggesting a potential therapeutic paradigm for LUAD patients with high MUC5AC expression.

Changes in the expression of cell interaction-related pathways during brain metastasis in lung adenocarcinoma: Gene expression and immunohistochemical analysis

BackgroundBrain metastasis (BM) is a prevalent prognostic event in the development of lung adenocarcinoma (LUAD) with a poor prognosis. Alterations in gene or protein expression during various phases of BM remain unclear. MethodsWe performed gene expression and pathway analyses using a metastasis-related gene panel on 12 lung tissues from patients with confirmed BM, 12 lung tissues from patients without BM, and 12 matched brain tissues from patients with confirmed BM during follow-up after LUAD surgery. The results of the gene expression analysis were validated by immunohistochemistry. ResultsCell interaction-related pathways (such as focal adhesion, extracellular matrix-receptor interaction, and proteoglycans in cancer) showed the greatest differences among the three groups. Expression of the cell interaction-related pathway was highest in the lung sample of BM group and lowest in the matched brain tissue. Using a machine learning model, a signature of 20 genes from cell interaction-related pathways accurately predicted BM (area under the curve score of 0.792 and an accuracy rate of 0.875). Immunohistochemical analysis showed higher expression of proteins associated with cell interaction-related genes and a mesenchymal phenotype in the lung sample of BM group than in those without BM or matched brain tissue. ConclusionsLUAD acquires the characteristics of the cell interaction-related pathway that leads to the development of BM, with a significant decrease in expression following brain colonization.

ITGB4 is a prognostic biomarker and correlated with lung adenocarcinoma brain metastasis.

The aim of this study is to explore the prognostic value and immune signature of ITGB4 expression in lung adenocarcinoma (LUAD) brain metastasis. We comprehensively screened genes associated with LUAD brain metastasis by integrating datasets from the GEO database and TMT-based quantitative proteomics profiles. Univariable survival and Multivariate Cox analysis was used to compare several clinical characteristics with survival, and a risk model was constructed. The biological functions were explored via GO and KEGG analysis. Gene set enrichment analysis (GSEA) was performed using the TCGA dataset. In addition, we use TIMER to explore the collection of ITGB4 Expression and Immune Infiltration Level in LUAD. The ability of ITGB4 to regulate tumor metastasis was further assessed by migration, invasion assay and Western-blot in H1975-BrM4 cells. We found that ITGB4 was the only gene with high clinical diagnostic and prognostic value in LUAD. Enrichment analysis indicated that ITGB4 is associated with brain metastasis, infiltration of immune cells, and the response to immunotherapy. ITGB4 expression can effectively predict the outcomes of patients with LUAD who are receiving anti-PD-1 therapy. ITGB4 knockdown inhibited the invasion, migration of H1975-BrM4 brain metastasis cells, as well as epithelial-mesenchymal transition (EMT) abilities. The heightened expression of ITGB4 protein was shown to promote EMT and enhance the metastatic potential. ITGB4 promotes the progression in H1975-BrM4 cells via MEK/ERK signaling pathway. Our findings indicate that the expression of ITGB4 is linked to the occurrence of brain metastasis and infiltration of immune cells, suggesting that ITGB4 might be a clinical treatment target for LUAD.

The application of different machine learning models based on PET/CT images and EGFR in predicting brain metastasis of adenocarcinoma of the lung

ObjectiveTo explore the value of six machine learning models based on PET/CT radiomics combined with EGFR in predicting brain metastases of lung adenocarcinoma.MethodsRetrospectively collected 204 patients with lung adenocarcinoma who underwent PET/CT examination and EGFR gene detection before treatment from Cancer Hospital Affiliated to Shandong First Medical University in 2020. Using univariate analysis and multivariate logistic regression analysis to find the independent risk factors for brain metastasis. Based on PET/CT imaging combined with EGFR and PET metabolic indexes, established six machine learning models to predict brain metastases of lung adenocarcinoma. Finally, using ten-fold cross-validation to evaluate the predictive effectiveness.ResultsIn univariate analysis, patients with N2-3, EGFR mutation-positive, LYM%≤20, and elevated tumor markers(P<0.05) were more likely to develop brain metastases. In multivariate Logistic regression analysis, PET metabolic indices revealed that SUVmax, SUVpeak, Volume, and TLG were risk factors for lung adenocarcinoma brain metastasis(P<0.05). The SVM model was the most efficient predictor of brain metastasis with an AUC of 0.82 (PET/CT group),0.70 (CT group),0.76 (PET group).ConclusionsRadiomics combined with EGFR machine learning model as a new method have higher accuracy than EGFR mutation alone. SVM model is the most effective method for predicting brain metastases of lung adenocarcinoma, and the prediction efficiency of PET/CT group is better than PET group and CT group.

Abstract LB014: The role of genetic alterations in metastatic development insights from a large-scale genomic database

Abstract Metastasis remains a major challenge in cancer treatment, with somatic genetic alterations being a crucial feature in progression. This study harnesses the whole genome sequencing data in the Genomics England biobank (GEL), cataloging of somatic alterations in the context of cancer metastasis. Our research aims to uncover the genetic underpinnings that facilitate the spread of cancer from its primary site to secondary locations by analyzing clinicogenomic data from 3047 cancer patients with metastatic progression. In this study, we analyzed the complex relationship between somatic alterations and cancer progression to uncover significant interactions among these alterations in a broad distribution of common tumor types among well-established oncogenic and tumor suppressor genes. In our study, we employed a Bayesian network approach, enabling us to not only pinpoint crucial genetic contributors to metastasis but also to consider other clinical variables, including patient treatment, sex, age, tumor grade and cancer types. In our analysis, LILRB2 was found to directly increase metastatic risk in hematologic cancer, with prior evidence suggesting its potential as a therapeutic biomarker in colorectal cancer and adversely related to patient prognosis in lung cancer. Similarly, MYL1, initially linked to tumor metastasis and immune infiltration in head and neck squamous cell carcinoma, was also found to increase the risk of metastasis in renal cancer, while interacting with the transcription factor E2F4, marker of poor prognosis in hepatocellular carcinoma. Our study not only confirmed the numerous key somatic gene alterations significantly linked to metastatic behavior across various cancers, but also established their significant roles.Our work highlights the potential of leveraging extensive genomic databases such as GEL to enhance our understanding of cancer metastasis. GEL’s paired germline and somatic data allows us to not only identify mutations unique to cancer cells but also to uncover germline variants that are associated with an elevated risk of cancer and the presence of more aggressive tumor characteristics. By characterizing metastatic risk features, we can explore the opportunities to stratify high-risk patients in clinical trials, with similar effort has been applied to brain metastasis in lung adenocarcinoma. Although tumor heterogeneity poses a treatment challenge due to cell diversity, previous work has demonstrated value in targeting the metastatic potential. For instance, trastuzumab target HER2-positive breast cancers prone to metastasis, markedly improving patient outcomes. Similarly, vemurafenib effectively controls metastatic Melanoma progression by targeting specific mutations like BRAFV600E. Understanding the genetic basis of metastasis could help identify high risk patients and lead to personalized combination therapies addressing various tumor subpopulations. Future research based on these findings could lead to the development of personalized combination treatment strategies that improve patient outcomes. Citation Format: Songjun Xu, Danyang Yu, Shuwei Li, Christopher Moy, Julio Molineros. The role of genetic alterations in metastatic development insights from a large-scale genomic database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB014.

Machine learning-driven prediction of brain metastasis in lung adenocarcinoma using miRNA profile and target gene pathway analysis of an mRNA dataset.

Brain metastasis (BM) is common in lung adenocarcinoma (LUAD) and has a poor prognosis, necessitating predictive biomarkers. MicroRNAs (MiRNAs) promote cancer cell growth, infiltration, and metastasis. However, the relationship between the miRNA expression profiles and BM occurrence in patients with LUAD remains unclear. We conducted an analysis to identify miRNAs in tissue samples that exhibited different expression levels between patients with and without BM. Using a machine learning approach, we confirmed whether the miRNA profile could be a predictive tool for BM. We performed pathway analysis of miRNA target genes using a matched mRNA dataset. We selected 25 miRNAs that consistently exhibited differential expression between the two groups of 32 samples. The 25-miRNA profile demonstrated a strong predictive potential for BM in both Group 1 and Group 2 and the entire dataset (area under the curve [AUC] = 0.918, accuracy = 0.875 in Group 1; AUC = 0.867, accuracy = 0.781 in Group 2; and AUC = 0.908, accuracy = 0.875 in the entire group). Patients predicted to have BM, based on the 25-miRNA profile, had lower survival rates. Target gene analysis of miRNAs suggested that BM could be induced through the ErbB signaling pathway, proteoglycans in cancer, and the focal adhesion pathway. Furthermore, patients predicted to have BM based on the 25-miRNA profile exhibited higher expression of the epithelial-mesenchymal transition signature, TWIST, and vimentin than those not predicted to have BM. Specifically, there was a correlation between EGFR mRNA levels and BM. This 25-miRNA profile may serve as a biomarker for predicting BM in patients with LUAD.

Abstract 4139: Prolyl 4-hydroxylase subunit alpha 1 acts as a novel target for lung adenocarcinoma brain metastasis

Abstract Lung cancer is the most lethal cancer worldwide, with a high incidence of distant metastasis. Many lung adenocarcinoma (LUAD) patients experience brain metastasis during the disease process with unfavorable prognosis. Our previous study has discovered that P4HA1 was exclusively upregulated in brain metastatic cells. Through the analysis of single-cell RNA sequencing of LUAD samples, we found that the expression of P4HA1 in brain metastatic tumor cells is higher than that in primary tumor cells. This finding was further confirmed by immunohistochemical staining. Significantly, a strong presence of P4HA1 in primary tumors is associated with a reduced duration of disease-free survival in individuals with LUAD. Overexpression of P4HA1 in A549 and PC9 cell lines significantly increased the incidence of brain metastasis in BALB/c nude mice, whereas knockdown of P4HA1 in high brain metastatic cells significantly decreased the incidence of brain metastasis and reduced the tumor foci in brain with improved survival. Utilization of DHB, a P4HA1 inhibitor, exerts both therapeutic and preventive effects in relieving brain metastases in nude mice. Furthermore, remarkable inhibition of tumor growth by DHB was observed in patient derived xenograft (PDX) models. RNA sequencing analysis demonstrated that the reduction of P4HA1 expression had a substantial impact on cell adhesion and extracellular matrix (ECM)-receptors interactions. Western blotting analysis verified that the decrease in P4HA1 expression led to a drop in the expression of adhesion molecules ICAM1, VCAM1, NCAM1, as well as integrin molecules ITGA2 and ITGA3. Furthermore, when endothelial cells were co-cultured with conditioned medium from tumor cells, it was observed that the expression of the tight junction molecule ZO1 was reduced after co-culturing with conditioned medium from P4HA1 knockdown A549 cells. The results from the in vitro blood-brain barrier (BBB) model and in vivo biofluorescence imaging indicate that P4HA1 promoted brain metastasis of LUAD via modulating the ability of tumor cells to cross the blood-brain barrier. In conclusion, our study reveals that overexpression of P4HA1 promotes metastatic spread to the brain, and targeting P4HA1 could be a promising therapeutic strategy for the treatment of lung adenocarcinoma brain metastasis. Citation Format: Yan He, Zhenyu Luo, Yucheng Dong, Rui Wan, Xue Zhang, Hua Bai, Jie Wang. Prolyl 4-hydroxylase subunit alpha 1 acts as a novel target for lung adenocarcinoma brain metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4139.

Single-cell RNA sequencing reveals epithelial cells driving brain metastasis in lung adenocarcinoma

Brain metastases (BM) of lung adenocarcinoma (LUAD) are the most common intracranial malignancy leading to death. However, the cellular origins and drivers of BM from LUAD have not been clarified. Cellular composition was characterized by single-cell sequencing analysis of primary lung adenocarcinoma (pLUAD), BM and lymph node metastasis (LNM) samples in GSE131907. Our study briefly analyzed the tumor microenvironment (TME), focusing on the role of epithelial cells (ECs) in BM. We have discovered a population of brain metastasis-associated epithelial cells (BMAECs) expressing SPP1, SAA1, and CDKN2A, and it has been observed that this population is mainly composed of aneuploid cells from pLUAD, playing a crucial role in brain metastasis. Our study concluded that both LNM and BM in LUAD originated from pLUAD lesions, but there is currently insufficient evidence to prove a direct association between BM lesions and LNM lesions, which provides inspiration for further investigation of the TME in BM.

Proteomics-based Model for Predicting the Risk of Brain Metastasis in Patients with Resected Lung Adenocarcinoma carrying the EGFR Mutation.

Introduction: Epidermal growth factor receptor (EGFR) mutation is common in Chinese patients with lung adenocarcinoma (LUAD). Brain metastases (BMs) is high and associated with poor prognosis. Identification of EGFR-mutant patients at high risk of developing BMs is important to reduce or delay the incidence of BMs. Currently, there is no literature on the prediction and modeling of EGFR brain metastasis at the proteinomics level. Methods: We conducted a retrospective study of BMs in postoperative recurrent LUAD with EGFR mutation in the First Affiliated Hospital of Guangzhou Medical University. Tissue proteomic analysis was applied in the primary tumors of resected LUAD in this study using liquid chromatography-mass spectrometry (LC-MS/MS). To identify potential markers for predicting LUAD BM, comparative analyses were performed on different groups to evaluate proteins associated with high risk of BMs. Results: A combination of three potential marker proteins was found to discriminate well between distal metastasis (DM) and local recurrence (LR) of postoperative LUAD with EGFR mutation. Gene Ontology (GO) analysis of significantly altered proteins between BM and non-BM (NBM) indicated that lipid metabolism and cell cycle-related pathways were involved in BMs of LUAD. And the enriched pathways correlated with BMs were found to be quite different in the comparison groups of postoperative adjuvant therapy, tyrosine kinase inhibitor (TKI), and chemotherapy groups. Finally, we developed a random forest algorithm model with eight proteins (RRS1, CPT1A, DNM1, SRCAP, MLYCD, PCID2, IMPAD1 and FILIP1), which showed excellent predictive value (AUC: 0.9401) of BM in patients with LUAD harboring EGFR mutation. Conclusions: A predictive model based on protein markers was developed to accurately predict postoperative BM in operable LUAD harboring EGFR mutation.

Clinical Application of the Association between Genetic Alteration and Intraoperative Fluorescence Activity of 5-Aminolevulinic Acid during the Resection of Brain Metastasis of Lung Adenocarcinoma.

The primary objective of this study was to investigate the association of certain genetic alterations and intraoperative fluorescent activity of 5-aminolevulinic acid (ALA) in brain metastasis (BM) of lung adenocarcinoma. A retrospective cohort study was conducted among 72 patients who underwent surgical resection of BM of lung adenocarcinoma at our institute for five years. Cancer cell infiltration was estimated by the intraoperative fluorescent activity of 5-ALA, and genetic alterations were analyzed by next-generation sequencing (NGS). The sensitivity and specificity for detecting cancer cell infiltration using 5-ALA were 87.5% and 96.4%, respectively. Genes associated with cell cycle regulation (p = 0.003) and cell proliferation (p = 0.044) were significantly associated with positive fluorescence activity of 5-ALA in the adjacent brain tissue. Genetic alterations in cell cycle regulation and cell proliferation were also associated with shorter recurrence-free survival (p = 0.013 and p = 0.042, respectively) and overall survival (p = 0.026 and p = 0.042, respectively) in the multivariate analysis. The results suggest that genetic alterations in cell cycle regulation and cell proliferation are associated with positive fluorescence activity of 5-ALA in the adjacent infiltrative brain tissue and influence the clinical outcome of BM of lung adenocarcinoma.

Abstract C053: BACE1 cleaves EGFR to drive lung adenocarcinoma brain metastasis

Abstract Brain metastasis occurs in up to 40% of patients with non-small cell lung cancer (NSCLC). Considerable genomic heterogeneity exists between the primary lung tumour and respective brain metastasis; however, the identity of the genes capable of driving brain metastasis is incompletely understood. Here, we carried out an in vivo genome-wide CRISPR activation (CRISPRa) screen to identify molecular drivers of brain metastasis from a NSCLC patient-derived xenograft model. We discovered activation of the Alzheimer’s disease associated b-site amyloid precursor protein cleaving enzyme 1 (BACE1) led to a significant increase in brain metastasis. Furthermore, BACE1 knockout or inhibition with Verubecestat treatment blocked NSCLC brain metastasis. Mechanistically, we identified BACE1 cleaves an N-terminal fragment of EGFR to activate downstream signalling through MEK and ERK and drive this metastatic phenotype. Together our data highlights the power of in vivo CRISPR screening to unveil novel molecular drivers and potential therapeutic targets of NSCLC brain metastasis. Citation Format: Shawn C Chafe, Kui Zhai, Sheila K Singh. BACE1 cleaves EGFR to drive lung adenocarcinoma brain metastasis [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr C053.

IMMU-49. BETA-ADRENERGIC BLOCKADE LICENSES THE USE OF IMMUNOTHERAPY IN PRIMARY AND METASTATIC BRAIN TUMORS

Abstract Immunotherapy is less effective against intracranial metastases compared to extracranial metastases and ineffective against primary brain tumors such as glioblastoma. Brain tumors present a unique challenge to in the context of immunotherapy, as these patients are immunosuppressed not just locally at the tumor, but also outside the CNS. Importantly, systemic immunosuppression observed in brain tumor patients limits the capacity of the immune system to respond to immunotherapy. Through this work we present a novel axis of immunosuppression in patients with intracranial tumors and demonstrate that overactive adrenergic signaling is a major barrier to immunotherapeutic success.Our data indicate that combining beta-adrenergic blockade with immunotherapy provides a survival benefit in the setting of brain tumors, where immunotherapy alone has proven ineffective. We demonstrate that this survival benefit is driven by a remodeling of the tumor microenvironment with an increase in cDC1s and CD8+ T cells, as well as an increase in CD40-CD40L signaling, suggesting the immune system is poised to respond. Further, we demonstrate that beta-adrenergic blockade can overcome systemic immunosuppression to restore the capacity of T cells to respond to an immune stimulus. Further, using the SEER-Medicaid database, we retrospectively examined outcomes in patients with melanoma and lung adenocarcinoma brain metastasis who received checkpoint blockade therapy alone vs those concurrently receiving beta-blocker therapy. We found that patients receiving combination therapy showed increased overall survival compared to those receiving checkpoint blockade alone. We then validated these findings in preclinical models of glioma, demonstrating that combining immunotherapy and propranolol, a widely-prescribed FDA-approved beta-blocker, extended survival. Moving forward, we suggest that combination therapy with beta-blocker and immunotherapy, particularly checkpoint blockade, represents a promising translational treatment platform for patients with primary or metastatic intracranial malignancies.

A multi-task deep learning model for EGFR genotyping prediction and GTV segmentation of brain metastasis

BackgroundThe precise prediction of epidermal growth factor receptor (EGFR) mutation status and gross tumor volume (GTV) segmentation are crucial goals in computer-aided lung adenocarcinoma brain metastasis diagnosis. However, these two tasks present continuous difficulties due to the nonuniform intensity distributions, ambiguous boundaries, and variable shapes of brain metastasis (BM) in MR images.The existing approaches for tackling these challenges mainly rely on single-task algorithms, which overlook the interdependence between these two tasks.MethodsTo comprehensively address these challenges, we propose a multi-task deep learning model that simultaneously enables GTV segmentation and EGFR subtype classification. Specifically, a multi-scale self-attention encoder that consists of a convolutional self-attention module is designed to extract the shared spatial and global information for a GTV segmentation decoder and an EGFR genotype classifier. Then, a hybrid CNN-Transformer classifier consisting of a convolutional block and a Transformer block is designed to combine the global and local information. Furthermore, the task correlation and heterogeneity issues are solved with a multi-task loss function, aiming to balance the above two tasks by incorporating segmentation and classification loss functions with learnable weights.ResultsThe experimental results demonstrate that our proposed model achieves excellent performance, surpassing that of single-task learning approaches. Our proposed model achieves a mean Dice score of 0.89 for GTV segmentation and an EGFR genotyping accuracy of 0.88 on an internal testing set, and attains an accuracy of 0.81 in the EGFR genotype prediction task and an average Dice score of 0.85 in the GTV segmentation task on the external testing set. This shows that our proposed method has outstanding performance and generalization.ConclusionWith the introduction of an efficient feature extraction module, a hybrid CNN-Transformer classifier, and a multi-task loss function, the proposed multi-task deep learning network significantly enhances the performance achieved in both GTV segmentation and EGFR genotyping tasks. Thus, the model can serve as a noninvasive tool for facilitating clinical treatment.

The Impact of Co-Alterations on Outcomes after Local Therapy for Patients with KRAS-Mutant Lung Adenocarcinoma Brain Metastases

Brain metastases are common in NSCLC with up to 25% of patients having brain metastases (BMs) at the time of diagnosis and 30% developing BMs during their disease course. KRAS is an oncogenic driver in approximately 25% of lung adenocarcinomas. Genomic alterations co-occurring with KRAS are associated with distinct biological landscapes which may influence prognosis. Herein, we sought to identify correlations between genomic profiles, intracranial progression free survival (iPFS), and overall survival (OS). We retrospectively reviewed 156 patients with KRAS-mutant lung adenocarcinoma BM who underwent SRS for their BMs at MSKCC from 2010-2022. Each patient had at least one tumor sample profiled with MSK-IMPACT, a custom FDA-cleared next-generation sequencing. Mutations, copy number alterations, and fusions were filtered for driver alterations using OncoKB. Survival outcomes were calculated from date of MRI indicating metastatic brain disease. Of the 156 patients, 80 patients presented with BMs at diagnosis whereas 76 developed BMs during their disease course, with a median 2 lines of therapy prior to BM diagnosis. The most common KRAS mutation was G12C (n = 64; 41%), G12V (n = 26, 17%), G12D (n = 17; 11%), and G12A (n = 11; 7%). The most frequently co-altered genes were TP53 (n = 71, 46%), STK11 (n = 51, 33%), CDKN2A (n = 27, 17%), KEAP1 (n = 17, 11%), and SMARCA4 (n = 10, 6%). The presence of a KEAP1 co-occurring alteration was associated with inferior iPFS (HR 1.95, 95% CI 1.05 - 3.59, p = 0.035) and the presence of SMARCA4 was also associated with inferior iPFS (HR 2.28, 95% CI 1.05 - 4.95, p = 0.038). The presence of an STK11 mutation was associated with worse OS (HR 1.57, 95% 1.01 - 2.43, p = 0.045). In a multi-variate clinico-genomic model, KEAP1 and STK11 co-occurring alterations remained significantly associated with iPFS. Patients with KEAP1-altered tumors had an increased incidence of intracranial regional progression. The 24-month cumulative incidence of regional progression amongst KEAP1-altered tumors was 57% (95% CI, 29%-77%) compared with 37% (95% CI, 29%-46%) among KEAP1-wildtype tumors (P = 0.041). Patients with CDKN2A-altered tumors had an increased incidence of leptomeningeal disease (LMD) as a form of intracranial progression. The 24-month cumulative incidence of LMD amongst CDKN2A-altered tumors was 11% (95% CI, 2.7%-27%) compared with 4.1% (95% CI, 1.5%-8.8%) among CDKN2A-wildtype tumors (P = 0.023). In our cohort of molecularly profiled KRAS-mutant lung adenocarcinoma BM patients treated with SRS, we found that co-occurring KEAP1 and STK11 were significantly associated with worse iPFS. We also observed that CDKN2A co-altered tumors had an increased incidence of LMD. These findings have implications for future efforts to personalize brain metastasis management based on comprehensive genomic profiling.