Estimating Survival in Patients With Lung Cancer and Brain Metastases: An Update of the Graded Prognostic Assessment for Lung Cancer Using Molecular Markers (Lung-molGPA)

Validity test of small cell lung cancer (SCLC) graded prognostic assessment and proposal of a new index for patients with brain metastases from SCLC

Background and purpose

We performed a validity test of a recently-reported, small cell lung cancer (SCLC) graded prognostic assessment (GPA) system for SCLC patients with brain metastases (BMs). Thereafter, we created a new prognostic index, the SCLC Grade, for such patients.

Materials and methods

We studied 508 SCLC patients selected from among nearly 7000 consecutive patients undergoing gamma knife SRS for BMs since 1998.

Results

In the SCLC GPA, there were no median survival time (MST) differences among pairs of the neighboring subgroups. Therefore, the 508 patients were randomly divided into the two series, i.e., a test (340 patients) and a validity (168) series. In the test series, five factors were identified by univariable analyses as favoring longer survival (rounded lower 95 % CI of the HR was at least 1.3): Sex, Karnofsky Performance Status, tumor numbers, primary tumor status and extracerebral metastases. This new index is the sum of scores (0 and 1) of these five factors: SCLC-Grade 4-6 (score of 4, 5 or 6), 2-3 (2 or 3), and 0-1 (0 or 1). This new system showed highly statistically significant MST differences among subclasses. Next, this SCLC-Grade was applied to the verification series. Consistent results were obtained, i.e., there were highly statistically significant MST differences among subclasses.

Conclusions

Our validity test results for the SCLC GPA demonstrated this system to not precisely reflect the outcomes of SCLC patients with BMs. Our results suggest the herein-proposed SCLC-Grade to have superior prognostic value.

Assessing survival in non-small cell lung cancer brain metastases after stereotactic radiosurgery: before and after the start of the targetable mutation era

PURPOSE

Targeted treatment options for non-small cell lung cancer (NSCLC) brain metastases (BMs) may be combined with stereotactic radiosurgery (SRS) to optimize survival. We assessed patient outcomes after SRS for NSCLC BMs, identifying survival trajectories associated with targetable mutations.

METHODS

In this retrospective time-dependent analysis, we analyzed median overall survival of patients who received ≥ 1 SRS courses for BM from NSCLC from 2001 to 2021. We compared survival of patients with and without targetable mutations based on clinical variables and treatment.

RESULTS

Among the 213 patients included, 87 (40.8%) had targetable mutations-primarily EGFR (22.5%)-and 126 (59.2%) did not. Patients with targetable mutations were more often female (63.2%, p <.001) and nonsmokers (58.6%, p <.001); had higher initial lung-molGPA (2.0 vs. 1.5, p <.001) and lower cumulative tumor volume (3.7 vs. 10.6 cm3, p <.001); and received more concurrent (55.2% vs. 36.5%, p =.007) and total (median 3 vs. 2, p <.001) systemic therapies. These patients had lower mortality rates (74.7% vs. 91.3%, p <.001) and risk (HR 0.298 [95%CI 0.190-0.469], p <.001) and longer median overall survival (20.2 vs. 7.4 months, p <.001), including survival ≥ 3 years (p =.001). Survival was best predicted by SRS with tumor resection in patients with non-targetable mutations (HR 0.491 [95%CI 0.318-757], p =.001) and by systemic therapy with SRS for those with targetable mutations (HR 0.124 [95%CI 0.013-1.153], p =.067).

CONCLUSION

The presence of targetable mutations enhances survival in patients receiving SRS for NSCLC BM, particularly when used with systemic therapies. Survival for patients without targetable mutations was longest with SRS and surgical resection. These results inform best practices for managing patients with NSCLC BM based on driver mutation status.

Ivonescimab Plus Chemotherapy in Non-Small Cell Lung Cancer With EGFR Variant: A Randomized Clinical Trial

Importance

For patients with non-small cell lung cancer whose disease progressed while receiving EGFR tyrosine kinase inhibitor (EGFR-TKI) therapy, particularly third-generation TKIs, optimal treatment options remain limited.

Objective

To compare the efficacy of ivonescimab plus chemotherapy with chemotherapy alone for patients with relapsed advanced or metastatic non-small cell lung cancer with the epidermal growth factor receptor (EGFR) variant.

Design, Setting, and Participants

Double-blind, placebo-controlled, randomized, phase 3 trial at 55 sites in China enrolled participants from January 2022 to November 2022; a total of 322 eligible patients were enrolled.

Interventions

Participants received ivonescimab (n = 161) or placebo (n = 161) plus pemetrexed and carboplatin once every 3 weeks for 4 cycles, followed by maintenance therapy of ivonescimab plus pemetrexed or placebo plus pemetrexed.

Main Outcomes and Measures

The primary end point was progression-free survival in the intention-to-treat population assessed by an independent radiographic review committee (IRRC) per Response Evaluation Criteria in Solid Tumors version 1.1. The results of the first planned interim analysis are reported.

Results

Among 322 enrolled patients in the ivonescimab and placebo groups, the median age was 59.6 vs 59.4 years and 52.2% vs 50.9% of patients were female. As of March 10, 2023, median follow-up time was 7.89 months. Median progression-free survival was 7.1 (95% CI, 5.9-8.7) months in the ivonescimab group vs 4.8 (95% CI, 4.2-5.6) months for placebo (difference, 2.3 months; hazard ratio [HR], 0.46 [95% CI, 0.34-0.62]; P < .001). The prespecified subgroup analysis showed progression-free survival benefit favoring patients receiving ivonescimab over placebo across almost all subgroups, including patients whose disease progressed while receiving third-generation EGFR-TKI therapy (HR, 0.48 [95% CI 0.35-0.66]) and those with brain metastases (HR, 0.40 [95% CI, 0.22-0.73]). The objective response rate was 50.6% (95% CI, 42.6%-58.6%) with ivonescimab and 35.4% (95% CI, 28.0%-43.3%) with placebo (difference, 15.6% [95% CI, 5.3%-26.0%]; P = .006). The median overall survival data were not mature; at data cutoff, 69 patients (21.4%) had died. Grade 3 or higher treatment-emergent adverse events occurred in 99 patients (61.5%) in the ivonescimab group vs 79 patients (49.1%) in the placebo group, the most common of which were chemotherapy-related. Grade 3 or higher immune-related adverse events occurred in 10 patients (6.2%) in the ivonescimab group vs 4 (2.5%) in the placebo group. Grade 3 or higher vascular endothelial growth factor-related adverse events occurred in 5 patients (3.1%) in the ivonescimab group vs 4 (2.5%) in the placebo group.

Conclusions

Ivonescimab plus chemotherapy significantly improved progression-free survival with tolerable safety profile in TKI-treated non-small cell lung cancer.

Trial Registration

ClinicalTrials.gov Identifier: NCT05184712.

Characterization of the tumor microenvironment in breast cancer brain metastasis

Objective

The difference in the tumor microenvironment (TME) between primary breast cancer (PBC) and breast cancer brain metastasis (BCBM) is still unknown. Herein, we present the landscape of the TME in PBC and BCBM to better understand the process of BCBM.

Methods

The Gene Expression Omnibus (GEO) database was used to obtain suitable PBC and BCBM data. Hub genes that were differentially expressed between the two groups were searched. Gene Ontology (GO) and KEGG were used to define the gene's function. Single-cell data were also analyzed to determine the difference between PBC and BCBM.

Results

Two datasets (GSE100534 and GSE125989) were used to search for hub genes, and 79 genes were either upregulated or downregulated between the two groups. Four hub genes (COL1A1, PDGFR, MMP3 and FZD7) were related to prognosis. GO and KEGG analyses showed that extracellular matrix and focal adhesion play major roles in the metastasis process. Another two datasets (GSE176078 and GSE186344) were enrolled for single-cell analysis. Single-cell analysis demonstrated that immune cells (66.6 %) form the main part of PBC, while cancer-associated fibroblasts (CAFs) (21.7 %) are the main component of BCBM. Immune cell proportion analysis showed that CD4+/CD8+ T cells (28.9 % and 14.3 %, respectively) and macrophages(M2) accounted for the majority of cells in PBC and BCBM, respectively. Further analysis of the classification of CAFs showed that apCAFs were significantly higher in PBC.

Conclusions

This study presents the landscape of BCBM with hub gene searching and single-cell analysis. Showing the difference in the tumor/immune microenvironment of PBC and BCBM, would be beneficial to explore immunotherapy and targeted therapy for BCBM.

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

Purpose

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.

Patients and Methods

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.

Results

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).

Conclusion

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.

Tyrosine Kinase Inhibitors With and Without Up-Front Stereotactic Radiosurgery for Brain Metastases From EGFR and ALK Oncogene-Driven Non-Small Cell Lung Cancer (TURBO-NSCLC)

PURPOSE

Newer-generation tyrosine kinase inhibitors (TKIs) for non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements have demonstrated high CNS activity. The optimal use of up-front stereotactic radiosurgery (SRS) for brain metastases (BM) in patients eligible for CNS-penetrant TKIs is controversial, and data to guide patient management are limited.

MATERIALS AND METHODS

Data on TKI-naïve patients with EGFR- and ALK-driven NSCLC with BM treated with CNS-penetrant TKIs with and without up-front SRS were retrospectively collected from seven academic centers in the United States. Time-to-CNS progression and overall survival (OS) were analyzed, with multivariable adjustment in Fine & Gray and Cox proportional hazards models for clinically relevant factors.

RESULTS

From 2013 to 2022, 317 patients were identified (200 TKI-only and 117 TKI + SRS). Two hundred fifty (79%) and 61 (19%) patients received osimertinib and alectinib, respectively. Patients receiving TKI + SRS were more likely to have BM ≥1 cm (P < .001) and neurologic symptoms (P < .001) at presentation. Median OS was similar between the TKI and TKI + SRS groups (median 41 v 40 months, respectively; P = .5). On multivariable analysis, TKI + SRS was associated with a significant improvement in time-to-CNS progression (hazard ratio [HR], 0.63 [95% CI, 0.42 to 0.96]; P = .033). Local CNS control was significantly improved with TKI + SRS (HR, 0.30 [95% CI, 0.16 to 0.55]; P < .001), whereas no significant differences were observed in distant CNS control. Subgroup analyses demonstrated a greater benefit from TKI + SRS in patients with BM ≥1 cm in diameter for time-to-CNS progression and CNS progression-free survival.

CONCLUSION

The addition of up-front SRS to CNS-penetrant TKI improved time-to-CNS progression and local CNS control, but not OS, in patients with BM from EGFR- and ALK-driven NSCLC. Patients with larger BM (≥1 cm) may benefit the most from up-front SRS.

Prediction of prognosis in lung cancer using machine learning with inter-institutional generalizability: A multicenter cohort study (WJOG15121L: REAL-WIND)

OBJECTIVES

Predicting the prognosis of lung cancer is crucial for providing optimal medical care. However, a method to accurately predict the overall prognosis in patients with stage IV lung cancer, even with the use of machine learning, has not been established. Moreover, the inter-institutional generalizability of such algorithms remains unexplored. This study aimed to establish machine learning-based algorithms with inter-institutional generalizability to predict prognosis.

MATERIALS AND METHODS

This multicenter, retrospective, hospital-based cohort study included consecutive patients with stage IV lung cancer who were randomly categorized into the training and independent test cohorts with a 2:1 ratio, respectively. The primary metric to assess algorithm performance was the area under the receiver operating characteristic curve in the independent test cohort. To assess the inter-institutional generalizability of the algorithms, we investigated their ability to predict patient outcomes in the remaining facility after being trained using data from 15 other facilities.

RESULTS

Overall, 6,751 patients (median age, 70 years) were enrolled, and 1,515 (22 %) showed mutated epidermal growth factor receptor expression. The median overall survival was 16.6 (95 % confidence interval, 15.9-17.5) months. Algorithm performance metrics in the test cohort showed that the areas under the curves were 0.90 (95 % confidence interval, 0.88-0.91), 0.85 (0.84-0.87), 0.83 (0.81-0.85), and 0.85 (0.82-0.87) at 180, 360, 720, and 1,080 predicted survival days, respectively. The performance test of 16 algorithms for investigating inter-institutional generalizability showed median areas under the curves of 0.87 (range, 0.84-0.92), 0.84 (0.78-0.88), 0.84 (0.76-0.89), and 0.84 (0.75-0.90) at 180, 360, 720, and 1,080 days, respectively.

CONCLUSION

This study developed machine learning algorithms that could accurately predict the prognosis in patients with stage IV lung cancer with high inter-institutional generalizability. This can enhance the accuracy of prognosis prediction and support informed and shared decision-making in clinical settings.

Adrenergic microenvironment driven by cancer-associated Schwann cells contributes to chemoresistance in patients with lung cancer

Doublecortin (DCX)-positive neural progenitor-like cells are purported components of the cancer microenvironment. The number of DCX-positive cells in tissues reportedly correlates with cancer progression; however, little is known about the mechanism by which these cells affect cancer progression. Here we demonstrated that DCX-positive cells, which are found in all major histological subtypes of lung cancer, are cancer-associated Schwann cells (CAS) and contribute to the chemoresistance of lung cancer cells by establishing an adrenergic microenvironment. Mechanistically, the activation of the Hippo transducer YAP/TAZ was involved in the acquisition of new traits of CAS and DCX positivity. We further revealed that CAS express catecholamine-synthesizing enzymes and synthesize adrenaline, which potentiates the chemoresistance of lung cancer cells through the activation of YAP/TAZ. Our findings shed light on CAS, which drive the formation of an adrenergic microenvironment by the reciprocal regulation of YAP/TAZ in lung cancer tissues.

[First-line immunotherapy in non-small cell lung cancer diagnosed with brain metastases]

INTRODUCTION

Up to 30% patients newly diagnosed with advanced non-small cell lung cancer (NSCLC) present with brain metastases. In the absence of oncogenic addiction, first-line immunotherapy, alone or in combination with chemotherapy, is the current standard of care. This review aims to synthesize the available data regarding the efficacy of immunotherapy in these patients, and to discuss the possibility of its being coordinated with local treatments such as radiotherapy.

STATE OF THE ART

NSCLC patients with brain metastases appear to have survival benefits with immunotherapy similar to those of NSCLC patients without brain metastases. However, this finding is based on mainly prospective studies having included highly selected patients with pre-treated and stable brain metastases. Several retrospective studies and two prospective single-arm studies have confirmed the intracranial efficacy of immunotherapy, either alone or in combination with chemotherapy.

PERSPECTIVES

The indications and optimal timing for cerebral radiotherapy remain subjects of debate. To date, there exists no randomized study assessing the addition of brain radiotherapy to first-line immunotherapy. That said, a recent meta-analysis showed increased intracerebral response when radiotherapy complemented immunotherapy.

CONCLUSIONS

For NSCLC patients with brain metastases, the available data suggest a clear benefit of first-line immunotherapy, whether alone or combined with chemotherapy. However, most of these data are drawn from retrospective, non-randomized studies with small sample sizes.

Site-Specific Response and Resistance Patterns in Patients with Advanced Non-Small-Cell Lung Cancer Treated with First-Line Systemic Therapy

Patients with advanced NSCLC have heterogenous responses to immune checkpoint inhibitors (ICIs) with or without chemotherapy. In NSCLC, the impact of the distribution of metastatic sites and the response to systemic therapy combinations remain poorly understood. In a retrospective cohort study of patients with unresectable stage III/IV NSCLC who received first-line systemic therapy, we sought to assess the association between the site of metastases with patterns of response and progression. Data regarding demographics, tumour characteristics (including site, size, and volume of metastases), treatment, and outcomes were examined at two cancer care centres. The endpoints included organ site-specific response rate, objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Two-hundred and eighty-five patients were included in the analysis. In a multivariate analysis, patients with bone metastases had a reduced ORR, PFS, and OS. Primary resistance was also more likely in patients with bone metastases. Patients with bone or liver metastases had a shorter OS when receiving ICIs with or without chemotherapy, but not with chemotherapy alone, suggesting an immunological basis for therapeutic resistance. A directed assessment of the tumour microenvironment in these locations and a deeper understanding of the drivers of organ-specific resistance to immunotherapy are critical to optimise novel combination therapies and sequencing in these patients.

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.

Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study

The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparametric MRI to differentiate the pathological subtypes of brain metastasis (BM) in lung cancer patients. This retrospective analysis collected 246 patients (456 BMs) from five medical centers from July 2016 to June 2022. The BMs were from small-cell lung cancer (SCLC, n = 230) and non-small-cell lung cancer (NSCLC, n = 226; 119 adenocarcinoma and 107 squamous cell carcinoma). Patients from four medical centers were assigned to training set and internal validation set with a ratio of 4:1, and we selected another medical center as an external test set. An attention-guided residual fusion network (ARFN) model for T1WI, T2WI, T2-FLAIR, DWI, and contrast-enhanced T1WI based on the ResNet-18 basic network was developed. The area under the receiver operating characteristic curve (AUC) was used to assess the classification performance. Compared with models based on five single-sequence and other combinations, a multiparametric MRI model based on five sequences had higher specificity in distinguishing BMs from different types of lung cancer. In the internal validation and external test sets, AUCs of the model for the classification of SCLC and NSCLC brain metastasis were 0.796 and 0.751, respectively; in terms of differentiating adenocarcinoma from squamous cell carcinoma BMs, the AUC values of the prediction models combining the five sequences were 0.771 and 0.738, respectively. DL together with multiparametric MRI has discriminatory feasibility in identifying pathology type of BM from lung cancer.

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.

Predicting Survival with Brain Metastases in the Stereotactic Radiosurgery Era: are Existing Prognostic Scores Still Relevant? Or Can we do Better?

Predicting survival is essential to tailoring treatment for patients diagnosed with brain metastases. We have evaluated the performance of widely used, validated prognostic scoring systems (Graded Prognostic Assessment and diagnosis-specific Graded Prognostic Assessment) in over 1000 'real-world' patients treated with stereotactic radiosurgery to the brain, selected according to National Health Service commissioning criteria. Survival outcomes from our dataset were consistent with those predicted by the prognostic systems, but with certain cancer subtypes showing a significantly better survival than predicted. Although performance status remains the simplest tool for prediction, total brain tumour volume emerges as an independent prognostic factor, and a new, improved, prognostic scoring system incorporating this has been developed.

Comprehensive genomic and clinical analyses identify APOBEC mutational signatures as a brain metastasis risk factor in lung adenocarcinoma patients

BACKGROUND

Lung adenocarcinoma is the most common source of brain metastasis (BM), resulting in significant morbidity and mortality. We aimed to identify patients with high BM risk who possibly benefit from brain-penetrant drugs, prophylactic cranial irradiation, or close brain magnetic resonance imaging surveillance.

METHODS

Metastatic lung adenocarcinoma patients with extracranial tumor samples profiled by a next-generation sequencing panel targeting 425 tumor-related genes were retrospectively enrolled between February 2008 and July 2021. We compared BM and non-BM patients' genomic and clinical features and studied their associations with BM risk. Two external cohorts were used for result validation and molecular mechanisms investigation, respectively.

RESULTS

We included 174 eligible patients, including 90 having developed BM by the end of follow-up. Age≤60, EGFR activating mutations, and high-level apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) mutational signatures were associated with elevated BM risk. Similar findings in BM-free survival were obtained by fitting Fine-Gray subdistribution hazard models addressing competing risks. Increased BM risk related to APOBEC mutational signatures was validated in an external cohort (N = 440). RNA sequencing data analyses performed in another external cohort (N = 230) revealed that expressions of metastasis-related pathways such as transforming growth factor (TGF)β and epithelial-mesenchymal transition (EMT) were upregulated in the patients with high-level APOBEC mutational signatures.

CONCLUSION

APOBEC mutational signatures related to upregulated TGFβ and EMT, could serve as an independent risk factor for BM and BM-free survival in metastatic lung adenocarcinoma patients. Further investigations are warranted to tailor personalized treatments to improve the susceptible patient's outcomes.

Prognostic Factors and Impact of Therapeutic Intervention in Patients With Brain Metastases at the Initial Presentation

Background Studies investigating the normative characteristics and prognosis of patients diagnosed with brain metastases (BMs) at the onset of cancer are scarce. Therefore, we analyzed real-world treatment options. Methodology This retrospective study enrolled 112 patients newly diagnosed with BM between May 2006 and October 2021. The variables examined included patients' age, sex, recurrence split analysis, Glasgow prognostic score (GPS), number of lesions, tumor size, peripheral brain tumor edema, targeted therapy, supportive care, chemotherapy, and date of onset. Prognostic factors were assessed using recursive partitioning analysis (RPA), graded prognostic assessment (GPA) scores, and GPS scoring, with magnetic resonance imaging (MRI) and computed tomography (CT) studies. Primary treatment comprised whole-brain radiotherapy (WBRT), with regular follow-up. Results Data from 112 survivors were analyzed, revealing a median overall survival time (MST) of 7.7 months, with some patients surviving beyond 24 months post-WBRT. Univariate analysis revealed associations between MST and RPA class, GPS, and treatment modalities (including targeted therapy and chemotherapy). RPA class 2, GPS of 0, and targeted therapy were identified as predictors of better prognosis in the multivariate analysis. In the subgroup not receiving chemotherapy, no significant difference in prognosis was seen between groups with or without WBRT. Conclusions Alongside RPA, scores indicating chronic inflammatory changes, including GPS, were confirmed as crucial prognostic factors. Moreover, treatment with molecularly targeted drugs correlated with favorable prognoses. The treatment-naïve group exhibited poorer prognoses, and WBRT was not deemed a significant prognostic factor in the chemotherapy group.

Dose-Incorporated Deep Ensemble Learning for Improving Brain Metastasis Stereotactic Radiosurgery Outcome Prediction

PURPOSE

To develop a novel deep ensemble learning model for accurate prediction of brain metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS).

METHODS AND MATERIALS

A total of 114 brain metastases (BMs) from 82 patients were evaluated, including 26 BMs that developed biopsy-confirmed local failure post-SRS. The SRS spatial dose distribution (Dmap) of each BM was registered to the planning contrast-enhanced T1 (T1-CE) magnetic resonance imaging (MRI). Axial slices of the Dmap, T1-CE, and planning target volume (PTV) segmentation (PTVseg) intersecting the BM center were extracted within a fixed field of view determined by the 60% isodose volume in Dmap. A spherical projection was implemented to transform planar image content onto a spherical surface using multiple projection centers, and the resultant T1-CE/Dmap/PTVseg projections were stacked as a 3-channel variable. Four Visual Geometry Group (VGG-19) deep encoders were used in an ensemble design, with each submodel using a different spherical projection formula as input for BM outcome prediction. In each submodel, clinical features after positional encoding were fused with VGG-19 deep features to generate logit results. The ensemble's outcome was synthesized from the 4 submodel results via logistic regression. In total, 10 model versions with random validation sample assignments were trained to study model robustness. Performance was compared with (1) a single VGG-19 encoder, (2) an ensemble with a T1-CE MRI as the sole image input after projections, and (3) an ensemble with the same image input design without clinical feature inclusion.

RESULTS

The ensemble model achieved an excellent area under the receiver operating characteristic curve (AUCROC: 0.89 ± 0.02) with high sensitivity (0.82 ± 0.05), specificity (0.84 ± 0.11), and accuracy (0.84 ± 0.08) results. This outperformed the MRI-only VGG-19 encoder (sensitivity: 0.35 ± 0.01, AUCROC: 0.64 ± 0.08), the MRI-only deep ensemble (sensitivity: 0.60 ± 0.09, AUCROC: 0.68 ± 0.06), and the 3-channel ensemble without clinical feature fusion (sensitivity: 0.78 ± 0.08, AUCROC: 0.84 ± 0.03).

CONCLUSIONS

Facilitated by the spherical image projection method, a deep ensemble model incorporating Dmap and clinical variables demonstrated excellent performance in predicting BM post-SRS local failure. Our novel approach could improve other radiation therapy outcome models and warrants further evaluation.

Immunotherapy combined with cranial radiotherapy for driver-negative non-small-cell lung cancer brain metastases: a retrospective study

Background: This study assesses immune checkpoint inhibitors' efficacy for non-small-cell lung cancer (NSCLC) with brain metastases (BM) and explores the role of cranial radiation therapy (CRT) in the immunotherapy era. Methods: The retrospective analysis screened NSCLC patients with BMs from July 2018 to December 2021. Treatment involved chemotherapy combined with immune checkpoint inhibitors as the first-line, with patients divided into CRT and non-CRT groups. Overall survival (OS), progression-free survival and intracranial progression-free survival were calculated and compared. Results: Among 113 patients, 74 who received CRT had significantly better median OS (not reached vs 15.31 months), particularly among those with one to three BMs. Factors correlating with better OS included CRT, PD-L1 expression and diagnosis-specific graded prognostic assessment scores. Conclusion: Integrating CRT with anti-PD-1 therapy notably enhanced long-term survival in NSCLC patients with BMs.

MRI radiomics for predicting intracranial progression in non-small-cell lung cancer patients with brain metastases treated with epidermal growth factor receptor tyrosine kinase inhibitors

AIM

To identify clinical and magnetic resonance imaging (MRI) radiomics predictors specialised for intracranial progression (IP) after first-line epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) treatment in non-small-cell lung cancer (NSCLC) patients with brain metastases (BMs).

MATERIALS AND METHODS

Seventy EGFR-mutated NSCLC patients with a total of 212 BMs who received first-line EGFR-TKI therapy were enrolled. Radiomics features were extracted from the BM regions on the pretreatment contrast-enhanced T1-weighted images, and the radiomics score (rad-score) of each BM was established based on the selected features. Furthermore, the mean rad-score derived from the average rad-score of all included BMs in each patient was calculated. Univariate and multivariate logistic regression analyses were performed to identify potential predictors of IP. Prediction models based on different predictors and their combinations were constructed, and nomogram based on the optimal prediction model was evaluated.

RESULTS

Thirty-three (47.1 %) patients developed IP, and the remaining 37 (52.9 %) patients were IP-free. EGFR-19del mutation (OR 0.19, 95 % CI 0.05-0.69), third-generation TKI treatment (OR 0.33, 95 % CI 0.16-0.67) and mean rad-score (OR 5.71, 95 % CI 1.65-19.68) were found to be independent predictive factors. Models based on these three predictors alone and in combination (combined model) achieved AUCs of 0.64, 0.64, 0.74, and 0.86 and 0.64, 0.64, 0.75, and 0.84 in the training and validation sets, respectively, and the combined model demonstrated optimal performance for predicting IP.

CONCLUSIONS

The model integrating EGFR-19del mutation, third-generation TKI treatment and mean rad-score had good predictive value for IP after EGFR-TKI treatment in NSCLC patients with BM.

Validation of the Lung-Mol Graded Prognostic Assessment (GPA) System for the Prognosis of Patients Receiving Radiotherapy for Brain Metastasis From Non-small Cell Lung Cancer

PURPOSE

The Lung-mol graded prognostic assessment (GPA) system predicts the prognosis of patients with brain metastases (BM) from non-small cell lung cancer (NSCLC) separately for adenocarcinoma and non-adenocarcinoma. This study aimed to validate the Lung-molGPA system using a cohort of patients in our institution who received radiotherapy for BM.

MATERIALS AND METHODS

Three hundred and thirty-nine patients with NSCLC who received their first course of radiotherapy for BM were included in the analysis. Among them, 65 received their second course of radiotherapy for BM. Data on sex, age, Karnofsky performance status (KPS), extracranial metastases (ECM), number of BM, histological type, and gene mutations were collected according to the Lung-molGPA system. We examined the validity of the scores assigned to the factors included in the Lung-molGPA system, separately for adenocarcinoma and non-adenocarcinoma. In addition, we validated the Lung-molGPA system to predict survival during both the first and second courses of radiotherapy.

RESULTS

The factors in the Lung-molGPA were significantly associated with survival, except for age in non-adenocarcinoma with marginal significance. Regarding discrimination ability, the C-indices were 0.65 and 0.69 for adenocarcinoma and non-adenocarcinoma, respectively, in the first course of radiotherapy for BM, while those in the second course were 0.62 and 0.74, respectively. Survival prediction by Lung-molGPA was almost consistent with actual survival in the first course of radiotherapy, except for the score of 0-1.0 in both histologies and 2.5-3.0 in non-adenocarcinoma. In the second course of radiotherapy, median survival could be predicted for some patients with adenocarcinoma.

CONCLUSIONS

Our study confirms the validity of Lung-molGPA for the estimation of median survival based on patient characteristics at the time of initiation of radiotherapy for patients in the first course of radiotherapy and shows that it may be applicable to patients with adenocarcinoma in the second course of radiotherapy.

Prognosis versus Actual Outcomes in Stereotactic Radiosurgery of Brain Metastases: Reliability of Common Prognostic Parameters and Indices

This study aims to evaluate the clinical outcome of stereotactic radiosurgery as the sole treatment for brain metastases and to assess prognostic factors influencing survival. A total of 108 consecutive patients with 213 metastases were retrospectively analyzed. Treatment was determined with close-meshed MRI follow-up. Various prognostic factors were assessed, and several prognostic indices were compared regarding their reliability to estimate overall survival. Median overall survival was 15 months; one-year overall survival was 50.5%. Both one- and two-year local controls were 90.9%. The rate of new metastases after SRS was 49.1%. Multivariate analysis of prognostic factors revealed that the presence of extracranial metastases, male sex, lower KPI, and progressive extracranial disease were significant risk factors for decreased survival. Of all evaluated prognostic indices, the Basic Score for Brain Metastases (BSBMs) showed the best correlation with overall survival. A substantial survival advantage was found for female patients after SRS when compared to male patients (18 versus 9 months, p = 0.003). SRS of brain metastasis is a safe and effective treatment option when frequent monitoring for new metastases with MRI is performed. Common prognostic scores lack reliable estimation of survival times. Female sex should be considered as an additional independent positive prognostic factor influencing survival.

Current pharmacologic treatment of brain metastasis in non-small cell lung cancer

Lung cancer is a type of cancer that can metastasize to the lungs, brain, bones, liver, adrenal glands, and other organs; however, the occurrence of brain metastases is the most common event. Symptoms of brain metastasis include motor dysfunction, mental dysfunction, seizures, headaches, nausea, and vomiting, and significantly reduce the quality of life of cancer patients. Brain metastases are a poor prognostic factor, and controlling them is extremely important for prolonging prognosis and improving the quality of life. Currently, local surgery and radiotherapy are recommended for their treatment. However, recently, cancer treatments using molecular-targeted drugs and immune checkpoint inhibitors have been introduced, which may also be effective against brain metastases. Therefore, it is necessary to determine whether local or systemic therapy is optimal for each case. In this review, we focus on recent findings regarding drug therapy in treating brain metastases from advanced non-small cell lung cancer.

Treatment outcomes and prognostic factors in patients with driver mutant non-small cell lung cancer and de novo brain metastases

Central nervous system (CNS) metastases can be seen at a rate of 30% in advanced stages for patients with non-small cell lung cancer (NSCLC). Growing evidence indicates the predictive roles of driver gene mutations in the development of brain metastases (BM) in recent years, meaning that oncogene-driven NSCLC have a high incidence of BM at diagnosis. Today, 3rd generation targeted drugs with high intracranial efficacy, which can cross the blood-brain barrier, have made a positive contribution to survival for these patients with an increased propensity to BM. It is important to update the clinical and pathological factors reflected in the survival with real-life data. A multi-center, retrospective database of 306 patients diagnosed with driver mutant NSCLC and initially presented with BM between between November 2008 and September 2022 were analyzed. The median progression-free survival (mPFS) was 12.25 months (95% CI, 10-14.5). While 254 of the patients received tyrosine kinase inhibitor (TKI), 51 patients received chemotherapy as first line treatment. The median intracranial PFS (iPFS) was 18.5 months (95% CI, 14.8-22.2). The median overall survival (OS) was 29 months (95% CI, 25.2-33.0). It was found that having 3 or less BM and absence of extracranial metastases were significantly associated with better mOS and iPFS. The relationship between the size of BM and survival was found to be non-significant. Among patients with advanced NSCLC with de novo BM carrying a driver mutation, long-term progression-free and overall survival can be achieved with the advent of targeted agents with high CNS efficacy with more conservative and localized radiotherapy modalities.

Focused ultrasound-assisted delivery of immunomodulating agents in brain cancer

Focused ultrasound (FUS) combined with intravascularly circulating microbubbles can transiently increase the permeability of the blood-brain barrier (BBB) to enable targeted therapeutic delivery to the brain, the clinical testing of which is currently underway in both adult and pediatric patients. Aside from traditional cancer drugs, this technique is being extended to promote the delivery of immunomodulating therapeutics to the brain, including antibodies, immune cells, and cytokines. In this manner, FUS approaches are being explored as a tool to improve and amplify the effectiveness of immunotherapy for both primary and metastatic brain cancer, a particularly challenging solid tumor to treat. Here, we present an overview of the latest groundbreaking research in FUS-assisted delivery of immunomodulating agents to the brain in pre-clinical models of brain cancer, and place it within the context of the current immunotherapy approaches. We follow this up with a discussion on new developments and emerging strategies for this rapidly evolving approach.

Exploring the Molecular Tumor Microenvironment and Translational Biomarkers in Brain Metastases of Non-Small-Cell Lung Cancer

Brain metastases represent a significant clinical challenge in the treatment of non-small-cell lung cancer (NSCLC), often leading to a severe decline in patient prognosis and survival. Recent advances in imaging and systemic treatments have increased the detection rates of brain metastases, yet clinical outcomes remain dismal due to the complexity of the metastatic tumor microenvironment (TME) and the lack of specific biomarkers for early detection and targeted therapy. The intricate interplay between NSCLC tumor cells and the surrounding TME in brain metastases is pivotal, influencing tumor progression, immune evasion, and response to therapy. This underscores the necessity for a deeper understanding of the molecular underpinnings of brain metastases, tumor microenvironment, and the identification of actionable biomarkers that can inform multimodal treatment approaches. The goal of this review is to synthesize current insights into the TME and elucidate molecular mechanisms in NSCLC brain metastases. Furthermore, we will explore the promising horizon of emerging biomarkers, both tissue- and liquid-based, that hold the potential to radically transform the treatment strategies and the enhancement of patient outcomes.

Computational markers for personalized prediction of outcomes in non-small cell lung cancer patients with brain metastases

Intracranial progression after curative treatment of early-stage non-small cell lung cancer (NSCLC) occurs from 10 to 50% and is difficult to manage, given the heterogeneity of clinical presentations and the variability of treatments available. The objective of this study was to develop a mechanistic model of intracranial progression to predict survival following a first brain metastasis (BM) event occurring at a time [Formula: see text]. Data included early-stage NSCLC patients treated with a curative intent who had a BM as the first and single relapse site (N = 31). We propose a mechanistic mathematical model able to derive computational markers from primary tumor and BM data at [Formula: see text] and estimate the amount and sizes of (visible and invisible) BMs, as well as their future behavior. These two key computational markers are [Formula: see text], the proliferation rate of a single tumor cell; and [Formula: see text], the per day, per cell, probability to metastasize. The predictive value of these individual computational biomarkers was evaluated. The model was able to correctly describe the number and size of metastases at [Formula: see text] for 20 patients. Parameters [Formula: see text] and [Formula: see text] were significantly associated with overall survival (OS) (HR 1.65 (1.07-2.53) p = 0.0029 and HR 1.95 (1.31-2.91) p = 0.0109, respectively). Adding the computational markers to the clinical ones significantly improved the predictive value of OS (c-index increased from 0.585 (95% CI 0.569-0.602) to 0.713 (95% CI 0.700-0.726), p < 0.0001). We demonstrated that our model was applicable to brain oligoprogressive patients in NSCLC and that the resulting computational markers had predictive potential. This may help lung cancer physicians to guide and personalize the management of NSCLC patients with intracranial oligoprogression.

Converging survival trends in non-small cell lung cancer patients with and without brain metastasis receiving state-of-the-art treatment

INTRODUCTION

Historically, patients with brain metastasis (BM) have been excluded from clinical trials investigating treatments for non-small cell lung cancer (NSCLC) due to their unfavorable prognosis. Advanced treatments have increased survival prospects for NSCLC patients with BM. This study evaluated the life expectancy of NSCLC patients with and without BM in the context of contemporary treatments.

METHODS

Outcome data were collected for patients with advanced NSCLC attending a tertiary medical center between 2015 and 2020. Patients were stratified according to BM status and compared for overall survival (OS) using log-rank and Cox regression analyses.

RESULTS

The cohort included 360 patients with NSCLC of whom 134 (37.2%) had BM. Most (95%) of cases of BM developed within the first two years: 63% at diagnosis, 18% during the first year, 14% during the second year. There was no significant difference in OS between patients without BM and those with BM (median 23.7 vs. 22.3 months, HR = 0.97, p = 0.82); patients with BM and a targetable or non-targetable mutation (40.2 vs. 31.4 months, HR = 0.93, p = 0.84, and 20.7 vs. 19.87 months, HR = 0.95, p = 0.75, respectively); and patients with symptomatic BM (23.7 vs. 19.8 months, HR = 0.95, p = 0.78). Treatment for BM (95% of patients) consisted of stereotactic radiosurgery or tyrosine kinase inhibitors, with corresponding intracranial control rates of 90% and 86%.

CONCLUSION

The results imply that the presence of BM has no impact on the prognosis of NSCLC. The practice of excluding NSCLC patients with BM from clinical trials warrants reconsideration.

Prediction and verification of the prognostic biomarker SLC2A2 and its association with immune infiltration in gastric cancer

Gastric cancer (GC) is the fifth most common cause of cancer-associated deaths; however, its treatment options are limited. Despite clinical improvements, chemotherapy resistance and metastasis are major challenges in improving the prognosis and quality of life of patients with GC. Therefore, effective prognostic biomarkers and targets associated with immunological interventions need to be identified. Solute carrier family 2 member 2 (SLC2A2) may serve a role in tumor development and invasion. The present study aimed to evaluate SLC2A2 as a prospective prognostic marker and chemotherapeutic target for GC. SLC2A2 expression in several types of cancer and GC was analyzed using online databases, and the effects of SLC2A2 expression on survival prognosis in GC were investigated. Clinicopathological parameters were examined to explore the association between SLC2A2 expression and overall survival (OS). Associations between SLC2A2 expression and immune infiltration, immune checkpoints and IC50 were estimated using quantification of the tumor immune contexture from human RNA-seq data, the Tumor Immune Estimation Resource 2.0 database and the Genomics of Drug Sensitivity in Cancer database. Differential SLC2A2 expression and the predictive value were validated using the Human Protein Atlas, Gene Expression Omnibus, immunohistochemistry and reverse transcription-quantitative PCR. SLC2A2 expression was downregulated in most types of tumor but upregulated in GC. Functional enrichment analysis revealed an association between SLC2A2 expression and lipid metabolism and the tumor immune microenvironment. According to Gene Ontology term functional enrichment analysis, SLC2A2-related differentially expressed genes were enriched predominantly in 'chylomicron assembly', 'plasma lipoprotein particle assembly', 'high-density lipoprotein particle', 'chylomicron', 'triglyceride-rich plasma lipoprotein particle', 'very-low-density lipoprotein particle'. 'intermembrane lipid transfer activity', 'lipoprotein particle receptor binding', 'cholesterol transporter activity' and 'intermembrane cholesterol transfer activity'. In addition, 'cholesterol metabolism', and 'fat digestion and absorption' were significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Patients with GC with high SLC2A2 expression had higher levels of neutrophil and M2 macrophage infiltration and a significant inverse correlation was observed between SLC2A2 expression and MYC targets, tumor mutation burden, microsatellite instability and immune checkpoints. Furthermore, patients with high SLC2A2 expression had worse prognosis, including OS, disease-specific survival and progression-free interval. Multivariate regression analysis demonstrated that SLC2A2 could independently prognosticate GC and the nomogram model showed favorable performance for survival prediction. SLC2A2 may be a prospective prognostic marker for GC. The prediction model may improve the prognosis of patients with GC in clinical practice, and SLC2A2 may serve as a novel therapeutic target to provide immunotherapy plans for GC.

Glasgow prognostic score for assessing the efficacy of whole-brain radiation therapy in cases of recursive partitioning analysis class 2 and class 3 multiple brain metastases: a retrospective study

PURPOSE

Whole-brain radiotherapy (WBRT) may not be beneficial for patients with brain metastases (BMs). The Glasgow Prognostic Score (GPS) is a suggested prognostic factor for malignancies. However, GPS has never been assessed in patients with BMs who have undergone WBRT. The purpose of this study was to determine whether GPS can be used to identify subgroups of patients with BMs who have a poor prognosis, such as recursive partitioning analysis (RPA) Class 2 and Class 3, and who will not receive clinical prognostic benefits from WBRT.

MATERIALS AND METHODS

A total of 180 Japanese patients with BMs were treated with WBRT between May 2008 and October 2015. We examined GPS, age, Karnofsky Performance Status (KPS), RPA, graded prognostic assessment (GPA), number of lesions, tumor size, history of brain surgery, presence of clinical symptoms, and radiation doses.

RESULTS

The overall median survival time (MST) was 6.1 months. seventeen patients (9.4%) were alive more than 2 years after WBRT. In univariate analysis, KPS ≤ 70 (p = 0.0066), GPA class 0-2 (p = 0.0008), > 3 BMs (p = 0.012), > 4 BMs (p = 0.02), patients who received ≥ 3 Gy per fraction (p = 0.0068), GPS ≥ 1 (p = 0.0003), and GPS ≥ 2 (p = 0.0009) were found to significantly decrease the MST. Patients who had brain surgery before WBRT (p = 0.036) had a longer survival. On multivariate analysis, GPS ≥ 1 (p = 0.008) was found to significantly decrease MST.

CONCLUSION

Our results suggest that GPS ≥ 1 indicates a poor prognosis in patients undergoing WBRT for intermediate and poor prognosis BMs.

Risk factors for brain metastases in locally advanced non-small cell lung cancer patients treated with radical radiotherapy

Background

Brain metastases (BM) happen frequently in lung cancer patients and lead to a poor prognosis as well as a lower quality of life. The aim of this study was to identify risk factors for BM in locally advanced non-small cell lung cancer (LA-NSCLC) patients receiving radical radiotherapy, which will be useful for selecting appropriate patient population for further intervention and future trial design.

Methods

This was a retrospective cohort study. Patients with inoperable stage IIB-IIIC NSCLC were treated consecutively with definitive thoracic radiotherapy from January 2018 to December 2021, and were retrospectively reviewed and enrolled. Patients with various clinical variables were analyzed to clarify their impact on BM with competing risk models by Fine and Gray.

Results

A total of 134 patients were enrolled in this study. The median follow-up for all patients was 37 months [95% confidence interval (CI): 30.5-43.5 months]. BM occurred in 25 patients at the time of analysis. The 1-year and 3-year cumulative BM incidence were 10.5% and 19.9%, respectively. Patients with BM had worse overall survival than those without BM [stratified hazard ratio (HR) for death: 2.83; 95% CI:1.31-6.11; P<0.001]. Based on univariate analyses, non-squamous cell carcinoma (non-SCC), biological effective dose (BED) and planning target volume (PTV) were used as input variables in multivariable analysis (P<0.01). According to multivariate analysis, non-SCC (P<0.001; HR: 6.08; 95% CI: 2.26-16.37), BED <72 Gy (P=0.017; HR: 2.81; 95% CI: 1.20-6.57), and PTV >157.73 cm3 (P=0.043; HR: 2.56; 95% CI: 1.03-6.35) were independent risk factors for BM. In subgroup analysis of adenocarcinoma with known epidermal growth factor receptor (EGFR) mutation status, PTV >157.73 cm3 and positive EGFR mutation were independent predictors for BM.

Conclusions

In this retrospective study, we found that BED <72 Gy and PTV >157.73 cm3 were significantly associated with BM development and we validated that non-SCC and positive EGFR mutation were risk factors for BM. More research is required to screen the high-risk patient population.

Prognostic significance of integrating total metabolic tumor volume and EGFR mutation status in patients with lung adenocarcinoma

Background

The objective of this study was to investigate the prognostic significance of total metabolic tumor volume (TMTV) derived from baseline 18F-2-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT), in conjunction with epidermal growth factor receptor (EGFR) mutation status, among patients with lung adenocarcinoma (LUAD).

Methods

We performed a retrospective analysis on 141 patients with LUAD (74 males, 67 females, median age 67 (range 34-86)) who underwent 18F-FDG PET/CT and had their EGFR mutation status determined. Optimal cutoff points for TMTV were determined using time-dependent receiver operating characteristic curve analysis. The survival difference was compared using Cox regression analysis and Kaplan‒Meier curves.

Results

The EGFR mutant patients (n = 79, 56.0%) exhibited significantly higher 2-year progression-free survival (PFS) and overall survival (OS) rates compared to those with EGFR wild-type (n = 62, 44.0%), with rates of 74.2% vs 69.2% (P = 0.029) and 86.1% vs 67.7% (P = 0.009), respectively. The optimal cutoff values of TMTV were 36.42 cm3 for PFS and 37.51 cm3 for OS. Patients with high TMTV exhibited significantly inferior 2-year PFS and OS, with rates of 22.4% and 38.1%, respectively, compared to those with low TMTV, who had rates of 85.8% and 95.0% (both P < 0.001). In both the EGFR mutant and wild-type groups, patients exhibiting high TMTV demonstrated significantly inferior 2-year PFS and OS compared to those with low TMTV. In multivariate analysis, EGFR mutation status (hazard ratio, HR, 0.41, 95% confidence interval, CI [0.18-0.94], P = 0.034) and TMTV (HR 8.08, 95% CI [2.34-28.0], P < 0.001) were independent prognostic factors of OS, whereas TMTV was also an independent prognosticator of PFS (HR 2.59, 95% CI [1.30-5.13], P = 0.007).

Conclusion

Our study demonstrates that the integration of TMTV on baseline 18F-FDG PET/CT with EGFR mutation status improves the accuracy of prognostic evaluation for patients with LUAD.

Enhancing outcomes: neurosurgical resection in brain metastasis patients with poor Karnofsky performance score - a comprehensive survival analysis

Background

A reduced Karnofsky performance score (KPS) often leads to the discontinuation of surgical and adjuvant therapy, owing to a lack of evidence of survival and quality of life benefits. This study aimed to examine the clinical and treatment outcomes of patients with KPS < 70 after neurosurgical resection and identify prognostic factors associated with better survival.

Methods

Patients with a preoperative KPS < 70 who underwent surgical resection for newly diagnosed brain metastases (BM) between 2007 and 2020 were retrospectively analyzed. The KPS, age, sex, tumor localization, cumulative tumor volume, number of lesions, extent of resection, prognostic assessment scores, adjuvant radiotherapy and systemic therapy, and presence of disease progression were analyzed. Univariate and multivariate logistic regression analyses were performed to determine the factors associated with better survival. Survival > 3 months was considered favorable and ≤ 3 months as poor.

Results

A total of 140 patients were identified. Median overall survival was 5.6 months (range 0-58). There was no difference in the preoperative KPS between the groups of > 3 and ≤ 3 months (50; range, 20-60 vs. 50; range, 10-60, p = 0.077). There was a significant improvement in KPS after surgery in patients with a preoperative KPS of 20% (20 vs 40 ± 20, p = 0.048). In the other groups, no significant changes in KPS were observed. Adjuvant radiotherapy was associated with better survival (44 [84.6%] vs. 32 [36.4%]; hazard ratio [HR], 0.0363; confidence interval [CI], 0.197-0.670, p = 0.00199). Adjuvant chemotherapy and immunotherapy resulted in prolonged survival (24 [46.2%] vs. 12 [13.6%]; HR 0.474, CI 0.263-0.854, p = 0.013]. Systemic disease progression was associated with poor survival (36 [50%] vs. 71 [80.7%]; HR 5.975, CI 2.610-13.677, p < 0.001].

Conclusion

Neurosurgical resection is an appropriate treatment modality for patients with low KPS. Surgery may improve functional status and facilitate further tumor-specific treatment. Combined treatment with adjuvant radiotherapy and systemic therapy was associated with improved survival in this cohort of patients. Systemic tumor progression has been identified as an independent factor for a poor prognosis. There is almost no information regarding surgical and adjuvant treatment in patients with low KPS. Our paper provides novel data on clinical outcome and survival analysis of patients with BM who underwent surgical treatment.

Navigating Post-Operative Outcomes: A Comprehensive Reframing of an Original Graded Prognostic Assessment in Patients with Brain Metastases

BACKGROUND

Graded Prognostic Assessment (GPA) has been proposed for various brain metastases (BMs) tailored to the primary histology and molecular profiles. However, it does not consider whether patients have been operated on or not and does not include surgical outcomes as prognostic factors. The residual tumor burden (RTB) is a strong predictor of overall survival. We validated the GPA score and introduced "volumetric GPA" in the largest cohort of operated patients and further explored the role of RTB as an additional prognostic factor.

METHODS

A total of 630 patients with BMs between 2007 and 2020 were included. The four GPA components were analyzed. The validity of the original score was assessed using Cox regression, and a modified index incorporating RTB was developed by comparing the accuracy, sensitivity, specificity, F1-score, and AUC parameters.

RESULTS

GPA categories showed an association with survival: age (p < 0.001, hazard ratio (HR) 2.9, 95% confidence interval (CI) 2.5-3.3), Karnofsky performance status (KPS) (p < 0.001, HR 1.3, 95% CI 1.2-1.5), number of BMs (p = 0.019, HR 1.4, 95% CI 1.1-1.8), and the presence of extracranial manifestation (p < 0.001, HR 3, 95% CI 1.6-2.5). The median survival for GPA 0-1 was 4 months; for GPA 1.5-2, it was 12 months; for GPA 2.5-3, it was 21 months; and for GPA 3.5-4, it was 38 months (p < 0.001). RTB was identified as an independent prognostic factor. A cut-off of 2 cm3 was used for further analysis, which showed a median survival of 6 months (95% CI 4-8) vs. 13 months (95% CI 11-14, p < 0.001) for patients with RTB > 2 cm3 and <2 cm3, respectively. RTB was added as an additional component for a modified volumetric GPA score. The survival rates with the modified GPA score were: GPA 0-1: 4 months, GPA 1.5-2: 7 months, GPA 2.5-3: 18 months, and GPA 3.5-4: 34 months. Both scores showed good stratification, with the new score showed a trend towards better discrimination in patients with more favorable prognoses.

CONCLUSION

The prognostic value of the original GPA was confirmed in our cohort of patients who underwent surgery for BM. The RTB was identified as a parameter of high prognostic significance and was incorporated into an updated "volumetric GPA". This score provides a novel tool for prognosis and clinical decision making in patients undergoing surgery. This method may be useful for stratification and patient selection for further treatment and in future clinical trials.

Beta-Adrenergic Blockade in Advanced Non-Small Cell Lung Cancer Patients Receiving Immunotherapy: A Multicentric Study

Introduction The standard treatment of cancer has dramatically improved with immune checkpoint inhibitors (ICIs). Despite their proven advantage, many patients fail to exhibit a meaningful and lasting response. The beta-adrenergic signalling pathway may hold significant promise due to its role in promoting an immunosuppressive milieu within the tumour microenvironment. Inhibiting β-adrenergic signalling could enhance ICI activity; however, blocking this pathway for this purpose has yielded conflicting results. The primary objective of this study was to evaluate the effect of beta-blocker use on overall survival and progression-free survival during ICI therapy. Methods A multicentric, retrospective, observational study was conducted in four Portuguese institutions. Patients with advanced non-small cell lung cancer treated with ICIs between January 2018 and December 2019 were included. Those using beta blockers for non-oncological reasons were compared with non-users. Results Among the 171 patients included, 36 concomitantly received beta blockers and ICIs. No significant increase was found in progression-free survival among patients who took β-blockers (HR 0.74, 95% confidence interval (CI) 0.48-1.12, p = 0.151), and no statistically significant difference was found in overall survival. An apparent trend was observed towards better outcomes in the beta-blocker group, with a median overall survival of 9.93 months in the group not taking β-blockers versus 14.90 months in the β-blocker group (p = 0.291) and a median progression-free survival of 5.37 in the group not taking β-blockers versus 10.87 months in the β-blocker group (p = 0.151). Nine (25%) patients in the beta-blocker group and 16 (12%) in the non-beta-blocker group were progressive disease-free at the end of follow-up. This difference between the two groups is statistically significant (p = 0.047). Conclusion Our study found no statistically significant evidence that beta blockers enhance the effectiveness of immunotherapy. Using adrenergic blockade to modulate the immune system shows promise, warranting the need to develop prospective clinical studies.

Radiomics of metastatic brain tumor as a predictive image biomarker of progression-free survival in patients with non-small-cell lung cancer with brain metastasis receiving tyrosine kinase inhibitors

BACKGROUND AND OBJECTIVE

Epidermal growth factor receptor (EGFR)-targeted tyrosine kinase inhibitors (TKIs) are the first-line therapy for EGFR-mutant non-small-cell lung cancer (NSCLC). Early prediction of treatment failure in patients with brain metastases treated with EGFR-TKIs may help in making decisions for systemic drug therapy or local brain tumor control. This study examined the predictive power of the radiomics of both brain metastasis tumors and primary lung tumors. We propose a deep learning based CoxCC model based on quantitative brain magnetic resonance imaging (MRI), a prognostic index and clinical data; the model can be used to predict progression-free survival (PFS) after EGFR-TKI therapy in advanced EGFR-mutant NSCLC.

METHODS

This retrospective single-center study included 271 patients receiving first-line EGFR-TKI targeted therapy in 2018-2019. Among them, 72 patients who had brain metastases before receiving first-line EGFR-TKI treatment. Three radiomic features were extracted from pretreatment brain MRI images. A CoxCC model for the progression risk stratification of EGFR-TKI treatment was proposed on the basis of MRI radiomics, clinical features, and a prognostic index. We performed time-dependent PFS predictions to evaluate the performance of the CoxCC model.

RESULTS

The CoxCC model based on a prognostic index, clinical features, and radiomic features of brain metastasis exhibited higher performance than clinical features combined with indexes previously proposed for determining the prognosis of brain metastasis, including recursive partitioning analysis, diagnostic-specific graded prognostic assessment, graded prognostic assessment for lung cancer using molecular markers (lung-molGPA), and modified lung-molGPA, with c-index values of 0.75, 0.67, 0.66, 0.65, and 0.65, respectively. The model achieved areas under the curve of 0.88, 0.73, 0.92, and 0.90 for predicting PFS at 3, 6, 9 and 12 months, respectively. PFS significantly differed between the high- and low-risk groups (p < 0.001).

CONCLUSIONS

For patients with advanced-stage NSCLC with brain metastasis, MRI radiomics of brain metastases may predict PFS. The CoxCC model integrating brain metastasis radiomics, clinical features, and a prognostic index provided reliable multi-time-point PFS predictions for patients with advanced NSCLC and brain metastases receiving EGFR-TKI treatment.

KIF20B Correlates with LUAD Progression and Is an Independent Risk Factor

OBJECTIVE

Kinesin family proteins (KIFs) play crucial roles in human tumorigenesis and progression. This study aimed to investigate the expression and association of Kinesin family member 20B (KIF20B) with lung adenocarcinoma (LUAD).

METHODS

RNA-seq data from LUAD patients (n = 535) were extracted from TCGA. KIF20B expression was compared between tumor tissues and controls, and between different stages of the disease. Survival and Cox regression analyses were performed, as well as in vitro cellular experiments on A549 cells.

RESULTS

KIF20B is upregulated in LUAD tumor tissues compared with controls and is higher in advanced stages. Patients with high expression of KIF20B have shorter survival times. KIF20B is an independent risk factor for the prognosis of LUAD. High KIF20B expression samples were enriched in signaling pathways related to tumor progression. si-KIF20B transfection reduced migration and invasion of A549 cells and increased apoptosis. The expression of p53 and Bax proteins was upregulated by si-KIF20B, while Bcl-2 was down-regulated.

DISCUSSION

This study reveals that high KIF20B expression is an independent risk factor for the poor prognosis of LUAD. The inhibition of KIF20B might be of great value for suppressing LUAD progression.

A brain metastasis liquid biopsy: Where are we now?

Brain metastases remain a challenging and feared complication for patients with cancer and research in this area has lagged behind research into metastases to other organs. Due to their location and the risks associated with neurosurgical biopsies, the biology underpinning brain metastases response to treatment and evolution over time remains poorly understood. Liquid biopsies are proposed to overcome many of the limitations present with tissue biopsies, providing a better representation of tumor heterogeneity, facilitating repeated sampling, and providing a noninvasive assessment of tumor biology. Several different liquid biopsy approaches have been investigated including circulating tumor cells, circulating tumor DNA, extracellular vesicles, and tumor-educated platelets; however, these have generally been less effective in assessing brain metastases compared to metastases to other organs requiring improved techniques to investigate these approaches, studies combining different liquid biopsy approaches and/or novel liquid biopsy approaches. Through this review, we highlight the current state of the art and define key unanswered questions related to brain metastases liquid biopsies.

Radiotherapy in Preclinical Models of Brain Metastases: A Review and Recommendations for Future Studies

Brain metastases (BMs) frequently occur in primary tumors such as lung cancer, breast cancer, and melanoma, and are associated with notably short natural survival. In addition to surgical interventions, chemotherapy, targeted therapy, and immunotherapy, radiotherapy (RT) is a crucial treatment for BM and encompasses whole-brain radiotherapy (WBRT) and stereotactic radiosurgery (SRS). Validating the efficacy and safety of treatment regimens through preclinical models is imperative for successful translation to clinical application. This not only advances fundamental research but also forms the theoretical foundation for clinical study. This review, grounded in animal models of brain metastases (AM-BM), explores the theoretical underpinnings and practical applications of radiotherapy in combination with chemotherapy, targeted therapy, immunotherapy, and emerging technologies such as nanomaterials and oxygen-containing microbubbles. Initially, we provided a concise overview of the establishment of AM-BMs. Subsequently, we summarize key RT parameters (RT mode, dose, fraction, dose rate) and their corresponding effects in AM-BMs. Finally, we present a comprehensive analysis of the current research status and future directions for combination therapy based on RT. In summary, there is presently no standardized regimen for AM-BM treatment involving RT. Further research is essential to deepen our understanding of the relationships between various parameters and their respective effects.

Survival Predictive Nomograms for Non-Surgical Brain Metastases Patients From Non-Small Cell Lung Cancer Receiving Radiotherapy: A Population-Based Study

OBJECTIVE

A high number of Non-Small Cell Lung Cancer (NSCLC) patients with brain metastasis who have not had surgery often have a negative outlook. Radiotherapy remains a most common and effective method. Nomograms were developed to forecast the cancer-specific survival (CSS) and overall survival (OS) in NSCLC individuals with nonoperative brain metastases who underwent radiotherapy.

METHODS

Information was gathered from the Surveillance, Epidemiology, and End Results (SEER) database about patients diagnosed with NSCLC who had brain metastases not suitable for surgery. Nomograms were created and tested using multivariate Cox regression models to forecast CSS and OS at intervals of 1, 2, and 3 years.

RESULTS

The research involved 3413 individuals diagnosed with NSCLC brain metastases who had undergone radiotherapy but had not experienced surgery. These participants were randomly divided into two categories. The analysis revealed that gender, age, ethnicity, marital status, tumor location, tumor laterality, tumor grade, histology, T stage, N stage, chemotherapy, tumor size, lung metastasis, bone metastasis, and liver metastasis were significant independent predictors for OS and CSS. The C-index for the training set for predicting OS was .709 (95% CI, .697-.721), and for the validation set, it was .705 (95% CI, .686-.723), respectively. The C-index for predicting CSS was .710 (95% CI, .697-.722) in the training set and .703 (95% CI, .684-.722) in the validation set, respectively. The nomograms model, as suggested by the impressive C-index, exhibits outstanding differentiation ability. Moreover, the ROC and calibration curves reveal its commendable precision and distinguishing potential.

CONCLUSIONS

For the first time, highly accurate and reliable nomograms were developed to predict OS and CSS in NSCLC patients with non-surgical brain metastases, who have undergone radiotherapy treatment. The nomograms may assist in tailoring counseling strategies and choosing the most effective treatment method.

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.

Validation of the ALK-Brain Prognostic Index for patients with ALK-rearranged lung cancer and brain metastases

BACKGROUND

Brain metastases (BMs) are a key challenge in the management of anaplastic lymphoma kinase-rearranged non-small-cell lung cancer (ALK+ NSCLC), but prognostic scores are complicated or rely on data before the era of tyrosine kinase inhibitors (TKIs). This study aimed to validate the novel ALK-Brain Prognostic Index (ALK-BPI), which was originally proposed based on 44 TKI-treated ALK+ NSCLC patients from Karolinska University Hospital, using an external clinical cohort.

PATIENTS AND METHODS

TKI-treated ALK+ NSCLC patients with BM from Heidelberg (n = 82, cohort 1) were retrospectively analyzed alone and together with the original Karolinska cohort (n = 126, cohort 2). Cox regression models were used to determine the association of clinical variables and scores with overall survival (OS) after BM diagnosis (BM-related OS).

RESULTS

Both cohorts showed a similar median age (58 years), roughly balanced sex distributions (52%-56% females), and Eastern Cooperative Oncology Group performance status (PS) 0-2 for most patients (87%-92%) at the time of BM development, which were present already at initial diagnosis in 36%-38% of the patients. Most patients had received next-generation ALK inhibitors (54%-63%), while 55%-56% of patients did not receive any radiotherapy. The ALK-BPI identified poor-risk patients (i.e. featuring ≥ 2/3 risk factors: PS > 2, male sex, development of BM after initial diagnosis) with a significantly shorter BM-related OS than other patients in both cohorts: 32/82 in cohort 1 with 21.3 versus 62.2 months in median [hazard ratio (HR) = 2.5, P < 0.001]; 59/126 in cohort 2 with 23.1 versus 67.2 months in median (HR = 2.6, P < 0.001). The five-parameter Lung-molGPA score did not achieve statistical significance and/or clear prognostic separation in all four groups, while the Disease-Specific Graded Prognostic Assessment score did not show consistent results.

CONCLUSIONS

The ALK-BPI is a reliable tool for easy prognostic dichotomization of TKI-treated ALK+ NSCLC patients with BM in daily clinical practice, without the complexity of previous models.

Machine-Learning-Aided Prediction of Brain Metastases Development in Non-Small-Cell Lung Cancers

PURPOSE

Non-small-cell lung cancer (NSCLC) shows a high incidence of brain metastases (BM). Early detection is crucial to improve clinical prospects. We trained and validated classifier models to identify patients with a high risk of developing BM, as they could potentially benefit from surveillance brain MRI.

METHODS

Consecutive patients with an initial diagnosis of NSCLC from January 2011 to April 2019 and an in-house chest-CT scan (staging) were retrospectively recruited at a German lung cancer center. Brain imaging was performed at initial diagnosis and in case of neurological symptoms (follow-up). Subjects lost to follow-up or still alive without BM at the data cut-off point (12/2020) were excluded. Covariates included clinical and/or 3D-radiomics-features of the primary tumor from staging chest-CT. Four machine learning models for prediction (80/20 training) were compared. Gini Importance and SHAP were used as measures of importance; sensitivity, specificity, area under the precision-recall curve, and Matthew's Correlation Coefficient as evaluation metrics.

RESULTS

Three hundred and ninety-five patients compromised the clinical cohort. Predictive models based on clinical features offered the best performance (tuned to maximize recall: sensitivity∼70%, specificity∼60%). Radiomics features failed to provide sufficient information, likely due to the heterogeneity of imaging data. Adenocarcinoma histology, lymph node invasion, and histological tumor grade were positively correlated with the prediction of BM, age, and squamous cell carcinoma histology were negatively correlated. A subgroup discovery analysis identified 2 candidate patient subpopulations appearing to present a higher risk of BM (female patients + adenocarcinoma histology, adenocarcinoma patients + no other distant metastases).

CONCLUSION

Analysis of the importance of input features suggests that the models are learning the relevant relationships between clinical features/development of BM. A higher number of samples is to be prioritized to improve performance. Employed prospectively at initial diagnosis, such models can help select high-risk subgroups for surveillance brain MRI.

Development and adaptations of the Graded Prognostic Assessment (GPA) scale: a systematic review

The Graded Prognostic Assessment (GPA) score has the best accuracy among prognostic scales for patients with brain metastases (BM). A wide range of GPA-derived scales have been established to different types of primary tumor BM. However, there is a high variability between them, and their characteristics have not been described altogether yet. We aim to summarize the features of the existent GPA-derived scales and to compare their predictor factors and their uses in clinical setting. Medline was searched from inception until January 2023 to identify studies related to the development, update, or validation of GPA. The initial search yielded 1,083 results. 16 original studies and 16 validation studies were included, comprising a total of 33,348 patients. 13 different scales were assessed, including: GPA, Diagnosis-Specific GPA, Extracranial Score, Lung-molGPA, Updated Renal GPA, Updated Gastrointestinal GPA, Modified Breast GPA, Integrated Melanoma GPA, Melanoma Mol GPA, Sarcoma GPA, Hepatocellular Carcinoma GPA, Colorectal Cancer GPA, and Uterine Cancer GPA. The most prevalent prognostic predictors were age, Karnofsky Performance Status, number of BM, and presence or absence of extracranial metastases. Treatment modalities consisted of whole brain radiation therapy, stereotactic radiosurgery, surgery, cranial radiotherapy, gamma knife radiosurgery, and BRAF inhibitor therapy. Median survival rates with no treatment and with a specific treatment ranged from 6.1 weeks to 33 months and from 3.1 to 21 months, respectively. Original GPA and GPA-derived scales are valid prognostic tools, but with heterogeneous survival results when compared to each other. More studies are needed to improve scientific evidence of these scales.

GABA(A) receptor activation drives GABARAP-Nix mediated autophagy to radiation-sensitize primary and brain-metastatic lung adenocarcinoma tumors

In non-small cell lung cancer (NSCLC) treatment, targeted therapies benefit only a subset of NSCLC, while radiotherapy responses are not durable and toxicity limits therapy. We find that a GABA(A) receptor activator, AM-101, impairs viability and clonogenicity of NSCLC primary and brain metastatic cells. Employing an ex vivo 'chip', AM-101 is as efficacious as the chemotherapeutic docetaxel, which is used with radiotherapy for advanced-stage NSCLC. In vivo , AM-101 potentiates radiation, including conferring a survival benefit to mice bearing NSCLC intracranial tumors. GABA(A) receptor activation stimulates a selective-autophagic response via multimerization of GABA(A) Receptor-Associated Protein (GABARAP), stabilization of mitochondrial receptor Nix, and utilization of ubiquitin-binding protein p62. A targeted-peptide disrupting Nix binding to GABARAP inhibits AM-101 cytotoxicity. This supports a model of GABA(A) receptor activation driving a GABARAP-Nix multimerization axis triggering autophagy. In patients receiving radiotherapy, GABA(A) receptor activation may improve tumor control while allowing radiation dose de-intensification to reduce toxicity.

Highlights

Activating GABA(A) receptors intrinsic to lung primary and metastatic brain cancer cells triggers a cytotoxic response. GABA(A) receptor activation works as well as chemotherapeutic docetaxel in impairing lung cancer viability ex vivo . GABA(A) receptor activation increases survival of mice bearing lung metastatic brain tumors.A selective-autophagic response is stimulated by GABA(A) receptor activation that includes multimerization of GABARAP and Nix.Employing a new nanomolar affinity peptide that abrogates autophagosome formation inhibits cytotoxicity elicited by GABA(A) receptor activation.

Management of Brain Metastases: A Review of Novel Therapies

Brain metastases (BMs) represent the most common intracranial tumors in adults, and most commonly originate from lung, followed by breast, melanoma, kidney, and colorectal cancer. Management of BM is individualized based on the size and number of brain metastases, the extent of extracranial disease, the primary tumor subtype, neurological symptoms, and prior lines of therapy. Until recently, treatment strategies were limited to local therapies, like surgical resection and radiotherapy, the latter in the form of whole-brain radiotherapy or stereotactic radiosurgery. The next generation of local strategies includes laser interstitial thermal therapy, magnetic hyperthermic therapy, post-resection brachytherapy, and focused ultrasound. New targeted therapies and immunotherapies with documented intracranial activity have transformed clinical outcomes. Novel systemic therapies with intracranial utility include new anaplastic lymphoma kinase inhibitors like brigatinib and ensartinib; selective "rearranged during transfection" inhibitors like selpercatinib and pralsetinib; B-raf proto-oncogene inhibitors like encorafenib and vemurafenib; Kirsten rat sarcoma viral oncogene inhibitors like sotorasib and adagrasib; ROS1 gene rearrangement (ROS1) inhibitors, anti-neurotrophic tyrosine receptor kinase agents like larotrectinib and entrectinib; anti-human epidermal growth factor receptor 2/epidermal growth factor receptor exon 20 agent like poziotinib; and antibody-drug conjugates like trastuzumab-emtansine and trastuzumab-deruxtecan. This review highlights the modern multidisciplinary management of BM, emphasizing the integration of systemic and local therapies.

Optimal timing of hypofractionated stereotactic radiotherapy for epidermal growth factor receptor-mutated non-small-cell lung cancer patients with brain metastases

BACKGROUND

For epidermal growth factor receptor (EGFR)-mutated non-small-cell lung cancer (NSCLC) patients with limited brain metastases (BMs), who eventually receive both tyrosine kinase inhibitors (TKIs) treatment and brain radiotherapy, the optimal timing of radiotherapy is not clear. The present retrospective analysis aimed to partly solve this problem.

METHODS

In total 84 EGFR-mutated NSCLC patients with limited BMs, who received both TKI treatment and brain hypofractionated stereotactic radiotherapy (HSRT), were enrolled. Patients were divided into three groups based on whether the HSRT was administrated 2 weeks before or after the beginning of TKI treatment (upfront HSRT), when intracranial lesions stabilized after TKI treatment (consolidative HSRT), or when the intracranial disease progressed after TKI treatment (salvage HSRT). The clinical efficacy and toxicities were evaluated.

RESULTS

The median intracranial progression-free survival (iPFS) and overall PFS calculated from the initiation of HSRT (iPFS1 and PFS1) of all patients were 17.5 and 13.1 months, respectively. The median iPFS and PFS calculated from the initiation of TKI treatment (iPFS2 and PFS2) of all patients were 24.1 and 18.4 months, respectively. Compared to consolidative and salvage HSRT, upfront HSRT improved iPFS1 (not reached vs. 17.5 months vs. 11.0 months, p < 0.001) and PFS1 (18.4 months vs. 9.1 months vs. 7.9 months, p < 0.001), and reduced the initial intracranial failure rate (12.5% vs. 48.1% vs. 56%, p < 0.001). However, there were no significant differences between the three groups for iPFS2, PFS2, and overall survival. Hepatic metastases and diagnosis-specific Graded Prognostic Assessment (ds-GPA) at 2-3 were poor prognostic factors.

CONCLUSION

For patients who receive both TKI treatment and brain HSRT, the timing of HSRT does not seem to influence the eventual therapeutic effect. Further validation in prospective clinical studies is needed.

Genomic Alterations and the Incidence of Brain Metastases in Advanced and Metastatic NSCLC: A Systematic Review and Meta-Analysis

INTRODUCTION

Brain metastases (BMs) in patients with advanced and metastatic NSCLC are linked to poor prognosis. Identifying genomic alterations associated with BM development could influence screening and determine targeted treatment. We aimed to establish prevalence and incidence in these groups, stratified by genomic alterations.

METHODS

A systematic review and meta-analysis compliant with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses were conducted (PROSPERO identification CRD42022315915). Articles published in MEDLINE, EMBASE, and Cochrane Library between January 2000 and May 2022 were included. Prevalence at diagnosis and incidence of new BM per year were obtained, including patients with EGFR, ALK, KRAS, and other alterations. Pooled incidence rates were calculated using random effects models.

RESULTS

A total of 64 unique articles were included (24,784 patients with NSCLC with prevalence data from 45 studies and 9058 patients with NSCLC having incidence data from 40 studies). Pooled BM prevalence at diagnosis was 28.6% (45 studies, 95% confidence interval [CI]: 26.1-31.0), and highest in patients that are ALK-positive (34.9%) or with RET-translocations (32.2%). With a median follow-up of 24 months, the per-year incidence of new BM was 0.13 in the wild-type group (14 studies, 95% CI: 0.11-0.16). Incidence was 0.16 in the EGFR group (16 studies, 95% CI: 0.11-0.21), 0.17 in the ALK group (five studies, 95% CI: 0.10-0.27), 0.10 in the KRAS group (four studies, 95% CI: 0.06-0.17), 0.13 in the ROS1 group (three studies, 95% CI: 0.06-0.28), and 0.12 in the RET group (two studies, 95% CI: 0.08-0.17).

CONCLUSIONS

Comprehensive meta-analysis indicates a higher prevalence and incidence of BM in patients with certain targetable genomic alterations. This supports brain imaging at staging and follow-up, and the need for targeted therapies with brain penetrance.

The Impact of Time Interval on Prognosis in Patients with Non-Small Cell Lung Cancer Brain Metastases After Metastases Surgery

BACKGROUND

Non-small cell lung cancer (NSCLC) is a prominent malignancy often linked to the development of brain metastases (BM), which commonly appear at diverse time intervals (TI) following the lung cancer diagnosis. This study endeavors to determine the prognostic significance of the time interval in patients with NSCLC who undergo BM surgery. Through this investigation, we aim to improve our understanding of the factors impacting the prognosis of BM cases originating from NSCLC.

METHODS

We analyzed data from 74 patients (2011-2021) who underwent BM surgery at our institution. The relationship between various clinical, radiological, and histopathological factors, as well as TI and overall survival (OS), was examined.

RESULTS

The median TI from initial NSCLC diagnosis to BM surgery was 19 months (range: 9-36 months). Notably, a shorter TI of less than 23 months was found to be independently associated with postoperative survival (adjusted odds ratio [aOR] 2.87, 95% confidence interval [CI] 1.03-8.02, P = 0.045). Additionally, a shorter TI was independently correlated with the absence of adjuvant chemotherapy for NSCLC (aOR 0.25, 95% CI 0.07-0.83, P = 0.023) and lack of targeted therapy (aOR 0.02, 95% CI 0.00-0.16, P < 0.001). Late-onset BM (TI ≥ 36 months) was observed in 15 cases (20.3%), in this subgroup, patients aged 60 years or older at the time of lung cancer diagnosis exhibited a significant independent correlation with late-onset BM (aOR 7.24, 95% CI 1.59-32.95, P = 0.011). NSCLC patients who underwent adjuvant chemotherapy displayed a notable correlation with late-onset BM (aOR 6.46, 95% CI 1.52-27.43, P = 0.011), while those who received targeted therapy also exhibited an independent association (aOR 2.27, 95% CI 1.70-3.03, P < 0.001).

CONCLUSIONS

Multiple factors contribute to the variability in the onset interval of BM subsequent to NSCLC diagnosis. The occurrence of BM within TI < 23 months following the initial diagnosis of NSCLC was demonstrated as an independent factor associated with an unfavorable prognosis following BM surgery. Furthermore, patients with NSCLC who did not receive adjuvant chemotherapy and lacked targeted therapy were shown to have an elevated likelihood of developing BM after a long progression-free survival.

Development and validation of a nomogram for predicting the overall survival in non-small cell lung cancer patients with liver metastasis

Background

Among all metastatic lesions in non-small cell lung cancer (NSCLC), liver metastasis (LM) is the most lethal site with a median survival of less than 5 months. Few studies exclusively report on prognostic factors for these unique patients. We aimed to construct and validate a practical model to predict the prognosis of NSCLC patients with LM.

Methods

Cases of NSCLC with LM diagnosed between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and were randomly split into training and validation cohort (7:3). The overall survival (OS) was measured from diagnosis until date of death or last follow-up. Cox regression analyses were performed to identify potential predictors of the model. A nomogram incorporating those independent factors was constructed and validated by the concordance index (C-index) and calibration plots. The decision curve analysis (DCA) and a risk stratification system were used to evaluate its clinical value.

Results

A total of 2,367 cases were selected for analysis and randomized to the training cohort (n=1,677) and the validation cohort (n=690). The patients were mainly male (59.3%), married (83.1%) and White (77.3%). Apart from LM, 54.2%, 26.7%, and 36.7% of patients also present with bone, brain, and lung metastases, respectively. The median follow-up was 4.0 months for all patients and 23 months for alive cases. The median OS was 5 months [interquartile range (IQR), 2-11 months]. Sex, age, race, grade, T stage, bone metastasis, brain metastasis, surgery, and chemotherapy were identified as the independent risk factors of the OS and used to develop the nomogram. The calibration curves exhibited excellent agreement between the predicted and actual survival in both the training and validation set, with a C-index of 0.700 [95% confidence interval (CI): 0.684-0.716] and 0.677 (95% CI: 0.653-0.701), respectively. The DCA and the risk classification system further supported that the prediction model was clinically effective.

Conclusions

This is the first study to build a prediction model for NSCLC patients with LM. It aids in treatment decisions, focused care, and physician-patient communication. The global prospective data is needed to further improve this model.

Clinicogenomic factors and treatment patterns among patients with advanced non-small cell lung cancer with or without brain metastases in the United States

BACKGROUND

This retrospective, real-world study evaluated the prevalence of brain metastases, clinicodemographic characteristics, systemic treatments, and factors associated with overall survival among patients with advanced non-small cell lung cancer (aNSCLC) in the US. We also described the genomic characterization of 180 brain metastatic specimens and frequency of clinically actionable genes.

MATERIALS AND METHODS

De-identified electronic health records-derived data of adult patients diagnosed with aNSCLC between 2011 and 2017 were analyzed from a US-nationwide clinicogenomic database.

RESULTS

Of 3257 adult patients with aNSCLC included in the study, approximately 31% (n = 1018) had brain metastases. Of these 1018 patients, 71% (n = 726) were diagnosed with brain metastases at initial NSCLC diagnosis; 57% (n = 583) of patients with brain metastases received systemic treatment. Platinum-based chemotherapy combinations were the most common first-line therapy; single-agent chemotherapies, epidermal growth factor receptor tyrosine kinase inhibitors, and platinum-based chemotherapy combinations were used in second line. Patients with brain metastases had a 1.56 times greater risk of death versus those with no brain metastases. In the brain metastatic specimens (n = 180), a high frequency of genomic alterations in the p53, MAPK, PI3K, mTOR, and cell-cycle associated pathways was observed.

CONCLUSION

The frequency of brain metastases at initial clinical presentation and associated poor prognosis for patients in this cohort underscores the importance of early screening for brain metastasis in NSCLC. Genomic alterations frequently identified in this study emphasize the continued need for genomic research and investigation of targeted therapies in patients with brain metastases.