Oxidative Metabolism Drives Immortalization of Neural Stem Cells during Tumorigenesis.

Metabolic reprogramming is a key feature of many cancers, but how and when it contributes to tumorigenesis remains unclear. Here we demonstrate that metabolic reprogramming induced by mitochondrial fusion can be rate-limiting for immortalization of tumor-initiating cells (TICs) and trigger their irreversible dedication to tumorigenesis. Using single-cell transcriptomics, we find that Drosophila brain tumors contain a rapidly dividing stem cell population defined by upregulation of oxidative phosphorylation (OxPhos). We combine targeted metabolomics and in vivo genetic screening to demonstrate that OxPhos is required for tumor cell immortalization but dispensable in neural stem cells (NSCs) giving rise to tumors. Employing an in vivo NADH/NAD+ sensor, we show that NSCs precisely increase OxPhos during immortalization. Blocking OxPhos or mitochondrial fusion stalls TICs in quiescence and prevents tumorigenesis through impaired NAD+ regeneration. Our work establishes a unique connection between cellular metabolism and immortalization of tumor-initiating cells.

N6-methyladenine DNA Modification in Glioblastoma.

Genetic drivers of cancer can be dysregulated through epigenetic modifications of DNA. Although the critical role of DNA 5-methylcytosine (5mC) in the regulation of transcription is recognized, the functions of other non-canonical DNA modifications remain obscure. Here, we report the identification of novel N6-methyladenine (N6-mA) DNA modifications in human tissues and implicate this epigenetic mark in human disease, specifically the highly malignant brain cancer glioblastoma. Glioblastoma markedly upregulated N6-mA levels, which co-localized with heterochromatic histone modifications, predominantly H3K9me3. N6-mA levels were dynamically regulated by the DNA demethylase ALKBH1, depletion of which led to transcriptional silencing of oncogenic pathways through decreasing chromatin accessibility. Targeting the N6-mA regulator ALKBH1 in patient-derived human glioblastoma models inhibited tumor cell proliferation and extended the survival of tumor-bearing mice, supporting this novel DNA modification as a potential therapeutic target for glioblastoma. Collectively, our results uncover a novel epigenetic node in cancer through the DNA modification N6-mA.

Brain and other central nervous system tumor statistics, 2021.

Brain and other central nervous system (CNS) tumors are among the most fatal cancers and account for substantial morbidity and mortality in the United States. Population-based data from the Central Brain Tumor Registry of the United States (a combined data set of the National Program of Cancer Registries [NPCR] and Surveillance, Epidemiology, and End Results [SEER] registries), NPCR, National Vital Statistics System and SEER program were analyzed to assess the contemporary burden of malignant and nonmalignant brain and other CNS tumors (hereafter brain) by histology, anatomic site, age, sex, and race/ethnicity. Malignant brain tumor incidence rates declined by 0.8% annually from 2008 to 2017 for all ages combined but increased 0.5% to 0.7% per year among children and adolescents. Malignant brain tumor incidence is highest in males and non-Hispanic White individuals, whereas the rates for nonmalignant tumors are highest in females and non-Hispanic Black individuals. Five-year relative survival for all malignant brain tumors combined increased between 1975 to 1977 and 2009 to 2015 from 23% to 36%, with larger gains among younger age groups. Less improvement among older age groups largely reflects a higher burden of glioblastoma, for which there have been few major advances in prevention, early detection, and treatment the past 4 decades. Specifically, 5-year glioblastoma survival only increased from 4% to 7% during the same time period. In addition, important survival disparities by race/ethnicity remain for childhood tumors, with the largest Black-White disparities for diffuse astrocytomas (75% vs 86% for patients diagnosed during 2009-2015) and embryonal tumors (59% vs 67%). Increased resources for the collection and reporting of timely consistent data are critical for advancing research to elucidate the causes of sex, age, and racial/ethnic differences in brain tumor occurrence, especially for rarer subtypes and among understudied populations.

Management of glioblastoma: State of the art and future directions.

Glioblastoma is the most common malignant primary brain tumor. Overall, the prognosis for patients with this disease is poor, with a median survival of <2 years. There is a slight predominance in males, and incidence increases with age. The standard approach to therapy in the newly diagnosed setting includes surgery followed by concurrent radiotherapy with temozolomide and further adjuvant temozolomide. Tumor-treating fields, delivering low-intensity alternating electric fields, can also be given concurrently with adjuvant temozolomide. At recurrence, there is no standard of care; however, surgery, radiotherapy, and systemic therapy with chemotherapy or bevacizumab are all potential options, depending on the patient's circumstances. Supportive and palliative care remain important considerations throughout the disease course in the multimodality approach to management. The recently revised classification of glioblastoma based on molecular profiling, notably isocitrate dehydrogenase (IDH) mutation status, is a result of enhanced understanding of the underlying pathogenesis of disease. There is a clear need for better therapeutic options, and there have been substantial efforts exploring immunotherapy and precision oncology approaches. In contrast to other solid tumors, however, biological factors, such as the blood-brain barrier and the unique tumor and immune microenvironment, represent significant challenges in the development of novel therapies. Innovative clinical trial designs with biomarker-enrichment strategies are needed to ultimately improve the outcome of patients with glioblastoma.

Increased HOXA5 expression provides a selective advantage for gain of whole chromosome 7 in IDH wild-type glioblastoma.

Glioblastoma is the most frequently occurring and invariably fatal primary brain tumor in adults. The vast majority of glioblastomas is characterized by chromosomal copy number alterations, including gain of whole chromosome 7 and loss of whole chromosome 10. Gain of whole chromosome 7 is an early event in gliomagenesis that occurs in proneural-like precursor cells, which give rise to all isocitrate dehydrogenase (IDH) wild-type glioblastoma transcriptional subtypes. Platelet-derived growth factor A (PDGFA) is one gene on chromosome 7 known to drive gliomagenesis, but, given its location near the end of 7p, there are likely several other genes located along chromosome 7 that select for its increased whole-chromosome copy number within glioblastoma cells. To identify other potential genes that could select for gain of whole chromosome 7, we developed an unbiased bioinformatics approach that identified homeobox A5 (HOXA5) as a gene whose expression correlated with gain of chromosome 7 and a more aggressive phenotype of the resulting glioma. High expression of HOXA5 in glioblastoma was associated with a proneural gene expression pattern and decreased overall survival in both human proneural and PDGF-driven mouse glioblastoma. Furthermore, HOXA5 overexpression promoted cellular proliferation and potentiated radioresistance. We also found enrichment of HOXA5 expression in recurrent human and mouse glioblastoma at first recurrence after radiotherapy. Overall, this study implicates HOXA5 as a chromosome 7-associated gene-level locus that promotes selection for gain of whole chromosome 7 and an aggressive phenotype in glioblastoma.

The oncological role of resection in newly diagnosed diffuse adult-type glioma defined by the WHO 2021 classification: a Review by the RANO resect group.

Glioma resection is associated with prolonged survival, but neuro-oncological trials have frequently refrained from quantifying the extent of resection. The Response Assessment in Neuro-Oncology (RANO) resect group is an international, multidisciplinary group that aims to standardise research practice by delineating the oncological role of surgery in diffuse adult-type gliomas as defined per WHO 2021 classification. Favourable survival effects of more extensive resection unfold over months to decades depending on the molecular tumour profile. In tumours with a more aggressive natural history, supramaximal resection might correlate with additional survival benefit. Weighing the expected survival benefits of resection as dictated by molecular tumour profiles against clinical factors, including the introduction of neurological deficits, we propose an algorithm to estimate the oncological effects of surgery for newly diagnosed gliomas. The algorithm serves to select patients who might benefit most from extensive resection and to emphasise the relevance of quantifying the extent of resection in clinical trials.

Clinical and biological landscape of constitutional mismatch-repair deficiency syndrome: an International Replication Repair Deficiency Consortium cohort study.

BACKGROUND: Constitutional mismatch repair deficiency (CMMRD) syndrome is a rare and aggressive cancer predisposition syndrome. Because a scarcity of data on this condition contributes to management challenges and poor outcomes, we aimed to describe the clinical spectrum, cancer biology, and impact of genetics on patient survival in CMMRD. METHODS: In this cohort study, we collected cross-sectional and longitudinal data on all patients with CMMRD, with no age limits, registered with the International Replication Repair Deficiency Consortium (IRRDC) across more than 50 countries. Clinical data were extracted from the IRRDC database, medical records, and physician-completed case record forms. The primary objective was to describe the clinical features, cancer spectrum, and biology of the condition. Secondary objectives included estimations of cancer incidence and of the impact of the specific mismatch-repair gene and genotype on cancer onset and survival, including after cancer surveillance and immunotherapy interventions. FINDINGS: We analysed data from 201 patients (103 males, 98 females) enrolled between June 5, 2007 and Sept 9, 2022. Median age at diagnosis of CMMRD or a related cancer was 8·9 years (IQR 5·9-12·6), and median follow-up from diagnosis was 7·2 years (3·6-14·8). Endogamy among minorities and closed communities contributed to high homozygosity within countries with low consanguinity. Frequent dermatological manifestations (117 [93%] of 126 patients with complete data) led to a clinical overlap with neurofibromatosis type 1 (35 [28%] of 126). 339 cancers were reported in 194 (97%) of 201 patients. The cumulative cancer incidence by age 18 years was 90% (95% CI 80-99). Median time between cancer diagnoses for patients with more than one cancer was 1·9 years (IQR 0·8-3·9). Neoplasms developed in 15 organs and included early-onset adult cancers. CNS tumours were the most frequent (173 [51%] cancers), followed by gastrointestinal (75 [22%]), haematological (61 [18%]), and other cancer types (30 [9%]). Patients with CNS tumours had the poorest overall survival rates (39% [95% CI 30-52] at 10 years from diagnosis; log-rank p<0·0001 across four cancer types), followed by those with haematological cancers (67% [55-82]), gastrointestinal cancers (89% [81-97]), and other solid tumours (96% [88-100]). All cancers showed high mutation and microsatellite indel burdens, and pathognomonic mutational signatures. MLH1 or MSH2 variants caused earlier cancer onset than PMS2 or MSH6 variants, and inferior survival (overall survival at age 15 years 63% [95% CI 55-73] for PMS2, 49% [35-68] for MSH6, 19% [6-66] for MLH1, and 0% for MSH2; p<0·0001). Frameshift or truncating variants within the same gene caused earlier cancers and inferior outcomes compared with missense variants (p<0·0001). The greater deleterious effects of MLH1 and MSH2 variants as compared with PMS2 and MSH6 variants persisted despite overall improvements in survival after surveillance or immune checkpoint inhibitor interventions. INTERPRETATION: The very high cancer burden and unique genomic landscape of CMMRD highlight the benefit of comprehensive assays in timely diagnosis and precision approaches toward surveillance and immunotherapy. These data will guide the clinical management of children and patients who survive into adulthood with CMMRD. FUNDING: The Canadian Institutes for Health Research, Stand Up to Cancer, Children's Oncology Group National Cancer Institute Community Oncology Research Program, Canadian Cancer Society, Brain Canada, The V Foundation for Cancer Research, BioCanRx, Harry and Agnieszka Hall, Meagan's Walk, BRAINchild Canada, The LivWise Foundation, St Baldrick Foundation, Hold'em for Life, and Garron Family Cancer Center.

A novel ARHGAP family gene signature for survival prediction in glioma patients.

ARHGAP family genes are often used as glioma oncogenic factors, and their mechanism of action remains unexplained. Our research entailed a thorough examination of the immune microenvironment and enrichment pathways across various glioma subtypes. A distinctive 6-gene signature was developed employing the CGGA cohort, leading to insights into the disparities in clinical characteristics, mutation patterns, and immune cell infiltration among distinct risk categories. Additionally, a unique nomogram was established, grounded on ARHGAPs, with DCA curves illustrating the model's prospective clinical utility in guiding therapeutic strategies. Emphasizing the role of ARHGAP30, integral to our model, its impact on glioma severity and the credibility of our risk assessment model were substantiated through RT-qPCR, Western blot analysis, and cellular functional assays. We identified 6 ARHGAP family genes associated with glioma prognosis. Analysis using the Kaplan-Meier method indicated a correlation between elevated risk levels and adverse outcomes in glioma patients. The risk score, linked with tumour staging and IDH mutation status, emerged as an independent factor predicting prognosis. Patients in the high-risk category exhibited increased immune cell infiltration, enhanced tumour mutational burden, more pronounced expression of immune checkpoint genes, and a better response to ICB therapy. A nomogram, integrating the risk score with the pathological features of glioma patients, was developed. DCA analysis and cellular studies confirmed the model's potential to improve clinical treatment outcomes for patients. A novel ARHGAP family gene signature reveals the prognosis of glioma.

Macrophage polarization-related gene signature for risk stratification and prognosis of survival in gliomas.

Macrophage polarization plays an essential role in tumour immune cell infiltration and tumour growth. In this study, we selected a series of genes distinguishing between M1 and M2 macrophages and explored their prognostic value in gliomas. A total of 170 genes were included in our study. The CGGA database was used as the training cohort and the TCGA database as the validation cohort. The biological processes and functions were identified by GO and KEGG analysis. Kaplan-Meier analysis was used to compare survival differences between groups. Importantly, we built a risk score model using Cox regression analysis based on the CGGA and verified it in the TCGA database and our sequencing data. Patients with gliomas in the high-risk group were associated with high pathologic grade, IDH WT status, MGMT promoter unmethylation, 1p19q non-codeletion and prone to have a poor outcome. GEPIA results revealed that CD300C, CNRIP1 and MYO1F are the most related genes of immune infiltrations. The differential expression of these genes between low-grade gliomas and glioblastomas was confirmed by q-RT-PCR. Macrophage polarization-related gene signatures can predict the malignancy and outcome of patients with gliomas and might act as a promising target for glioma immunotherapy in the future.

Machine learning-based identification of a cell death-related signature associated with prognosis and immune infiltration in glioma.

Accumulating evidence suggests that a wide variety of cell deaths are deeply involved in cancer immunity. However, their roles in glioma have not been explored. We employed a logistic regression model with the shrinkage regularization operator (LASSO) Cox combined with seven machine learning algorithms to analyse the patterns of cell death (including cuproptosis, ferroptosis, pyroptosis, apoptosis and necrosis) in The Cancer Genome Atlas (TCGA) cohort. The performance of the nomogram was assessed through the use of receiver operating characteristic (ROC) curves and calibration curves. Cell-type identification was estimated by using the cell-type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) and single sample gene set enrichment analysis methods. Hub genes associated with the prognostic model were screened through machine learning techniques. The expression pattern and clinical significance of MYD88 were investigated via immunohistochemistry (IHC). The cell death score represents an independent prognostic factor for poor outcomes in glioma patients and has a distinctly superior accuracy to that of 10 published signatures. The nomogram performed well in predicting outcomes according to time-dependent ROC and calibration plots. In addition, a high-risk score was significantly related to high expression of immune checkpoint molecules and dense infiltration of protumor cells, these findings were associated with a cell death-based prognostic model. Upregulated MYD88 expression was associated with malignant phenotypes and undesirable prognoses according to the IHC. Furthermore, high MYD88 expression was associated with poor clinical outcomes and was positively related to CD163, PD-L1 and vimentin expression in the in-horse cohort. The cell death score provides a precise stratification and immune status for glioma. MYD88 was found to be an outstanding representative that might play an important role in glioma.

Comprehensive analysis of lncRNA-associated ceRNA network reveals novel potential prognostic regulatory axes in glioblastoma multiforme.

Deciphering the lncRNA-associated competitive endogenous RNA (ceRNA) network is essential in decoding glioblastoma multiforme (GBM) pathogenesis by regulating miRNA availability and controlling mRNA stability. This study aimed to explore novel biomarkers for GBM by constructing a lncRNA-miRNA-mRNA network. A ceRNA network in GBM was constructed using lncRNA, mRNA and miRNA expression profiles from the TCGA and GEO datasets. Seed nodes were identified by protein-protein interaction (PPI) network analysis of deregulated-mRNAs (DEmRNAs) in the ceRNA network. A lncRNA-miRNA-seed network was constructed by mapping the seed nodes into the preliminary ceRNA network. The impact of the seed nodes on the overall survival (OS) of patients was assessed by the GSCA database. Functional enrichment analysis of the deregulated-lncRNAs (DElncRNA) in the ceRNA network and genes interacting with OS-related genes in the PPI network were performed. Finally, the positive correlation between seed nodes and their associated lncRNAs and the expression level of these molecules in GBM tissue compared with normal samples was validated using the GEPIA database. Our analyzes revealed that three novel regulatory axes AL161785.1/miR-139-5p/MS4A6A, LINC02611/miR-139-5p/MS4A6A and PCED1B-AS1/miR-433-3p/MS4A6A may play essential roles in GBM pathogenesis. MS4A6A is upregulated in GBM and closely associated with shorter survival time of patients. We also identified that MS4A6A expression positively correlates with genes related to tumour-associated macrophages, which induce macrophage infiltration and immune suppression. The functional enrichment analysis demonstrated that DElncRNAs are mainly involved in neuroactive ligand-receptor interaction, calcium/MAPK signalling pathway, ribosome, GABAergic/Serotonergic/Glutamatergic synapse and immune system process. In addition, genes related to MS4A6A contribute to immune and inflammatory-related biological processes. Our findings provide novel insights to understand the ceRNA regulation in GBM and identify novel prognostic biomarkers or therapeutic targets.

Indirect functional connectivity does not predict overall survival in glioblastoma.

BACKGROUND: Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional connectome and using the corresponding functional maps as proxies for disconnections. However, previous studies indicated limited predictive power of this approach in behavioral deficits. We hypothesized similarly low predictiveness for overall survival (OS) in glioblastoma (GBM). METHODS: A retrospective dataset of patients with GBM was included (n = 99). Lesion masks were registered in the normative space to compute disconnectivity maps. The brain functional normative connectome consisted in data from 173 healthy subjects obtained from the Human Connectome Project. A modified version of the LNM was then applied to core regions of GBM masks. Linear regression, classification, and principal component (PCA) analyses were conducted to explore the relationship between disconnectivity and OS. OS was considered both as continuous and categorical (low, intermediate, and high survival) variable. RESULTS: The results revealed no significant associations between OS and network disconnection strength when analyzed at both voxel-wise and classification levels. Moreover, patients stratified into different OS groups did not exhibit significant differences in network connectivity patterns. The spatial similarity among the first PCA of network maps for each OS group suggested a lack of distinctive network patterns associated with survival duration. CONCLUSIONS: Compared with indirect structural measures, functional indirect mapping does not provide significant predictive power for OS in patients with GBM. These findings are consistent with previous research that demonstrated the limitations of indirect functional measures in predicting clinical outcomes, underscoring the need for more comprehensive methodologies and a deeper understanding of the factors influencing clinical outcomes in this challenging disease.

Adult epithelioid glioblastoma exhibits an extremely poor prognosis and high frequency of SWI/SNF complex mutation: Insights from a retrospective study.

Epithelioid glioblastoma (eGBM) is a rare subtype of GBM. Given the update of the definition of GBM, the understanding of the molecular characteristics and prognosis of "true" adult eGBM remains limited. Herein, we retrospectively analyzed the clinicopathological data of 39 adult eGBM cases. Adult eGBM primarily affected females, with a male-to-female ratio of 1:2.3. The average age of diagnosis was 53 years, and the tumor affected the temporal lobe in 41% of cases (16/39, 41%). Microscopically, the tumors consisted mainly or entirely of epithelioid cells. Perivascular infiltration (10/39, 25.6%) and leptomeningeal dissemination (7/39, 17.9%) were not uncommon. BRAF V600E mutation was detected in 40.9% of cases (n = 9/22). Next-generation sequencing revealed that CDKN2A/B homogeneous deletion was the most frequently mutated gene (8/10, 80%), followed by TERT promoter mutation (7/10, 70%), Cyclin-dependent kinases 4 or 6 (CDK4/6) amplification (5/10, 50%) and BRAF V600E mutation (50%, 5/10). Notably, the incidence of ARID1B mutation in eGBM was 50% (5/10), representing the first report of such a mutation in this subtype of GBM. ARID1B was known to be a subunit of the SWI/SNF chromatin remodeler. Chromosome analysis showed a 7+/10- signature in 90% (9/10) cases. Adult eGBM carried a dismal prognosis compared to GBM with IDH and H3 wild-type (typical GBM) (OS: 13.89 vs 24.30 months; P = .003) and even typical GBM without MGMT promoter methylation (OS: 13.89 vs 22.08 months; P = .036). Based on these findings, it can be concluded that adult eGBM harbors a high frequency of the 7+/10- signature and alterations in the MAPK pathway, SWI/SNF complex and cyclin-related genes and portends an extremely poor prognosis.

The systematic identification of survival-related alternative splicing events and splicing factors in glioblastoma.

Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor, making it one of the most life-threatening human cancers. Nevertheless, research on the mechanism of action between alternative splicing (AS) and splicing factor (SF) or biomarkers in GBM is limited. AS is a crucial post-transcriptional regulatory mechanism. More than 95% of human genes undergo AS events. AS can diversify the expression patterns of genes, thereby increasing the diversity of proteins and playing a significant role in the occurrence and development of tumors. In this study, we downloaded 599 clinical data and 169 transcriptome analysis data from The Cancer Genome Atlas (TCGA) database. Besides, we collected AS data about GBM from TCGA-SpliceSeq. The overall survival (OS) related AS events in GBM were determined through least absolute shrinkage and selection operator (Lasso) and Cox analysis. Subsequently, the association of these 1825 OS-related AS events with patient survival was validated using the Kaplan-Meier survival analysis, receiver operating characteristic curve, risk curve analysis, and independent prognostic analysis. Finally, we depicted the AS-SF regulatory network, illustrating the interactions between splicing factors and various AS events in GBM. Additionally, we identified three splicing factors (RNU4-1, SEC31B, and CLK1) associated with patient survival. In conclusion, based on AS occurrences, we developed a predictive risk model and constructed an interaction network between GBM-related AS events and SFs, aiming to shed light on the underlying mechanisms of GBM pathogenesis and progression.

Identification and validation of anoikis-related genes to clarify the prognosis and immune mechanisms of patients with low-grade glioma.

BACKGROUND: Low-grade glioma (LGG) has an extremely poor prognosis, and the mechanism leading to malignant development has not been determined. The aim of our study was to clarify the function and mechanism of anoikis and TIMP1 in the malignant progression of LGG. METHODS: We screened 7 anoikis-related genes from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to construct a prognostic-predicting model. The study assessed the clinical prognosis, pathological characteristics, and immune cell infiltration in both high- and low-risk groups. Additionally, the potential modulatory effects of TIMP1 on proliferation, migration, and anoikis in LGG were investigated both in vivo and in vitro. RESULTS: In this study, we identified seven critical genes, namely, PTGS2, CCND1, TIMP1, PDK4, LGALS3, CDKN1A, and CDKN2A. Kaplan‒Meier (K‒M) curves demonstrated a significant correlation between clinical features and overall survival (OS), and single-cell analysis and mutation examination emphasized the heterogeneity and pivotal role of hub gene expression imbalances in LGG development. Immune cell infiltration and microenvironment analysis further elucidated the relationships between key genes and immune cells. In addition, TIMP1 promoted the malignant progression of LGG in both in vitro and in vivo models. CONCLUSIONS: This study confirmed that TIMP1 promoted the malignant progression of LGG by inhibiting anoikis, providing insights into LGG pathogenesis and potential therapeutic targets.

Triple therapy boosts survival in NSCLC patients with brain metastases: a retrospective cohort study of chemotherapy, ICIs, and antiangiogenic agents.

BACKGROUND: Treatment of brain metastases (BMs) in non-small cell lung cancer (NSCLC) patients, especially those with non-sensitive genetic mutations, is hindered by limited drug delivery through the blood-brain barrier (BBB). This retrospective study explores the efficacy of systemic treatments during brain metastasis to radiotherapy evaluation window in improving patient survival. METHODS: In this retrospective cohort study, we evaluated 209 NSCLC patients with non-sensitive mutations and BMs, treated between 2016 and 2023 at two tertiary medical centers (Chongqing University Cancer Hospital and Guangxi Medical University Cancer Hospital). The patients were divided into three groups, namely chemotherapy alone (C; n = 95), chemotherapy plus immune checkpoint inhibitors (ICIs) (C + I; n = 62), and chemotherapy with ICIs and antiangiogenic therapy (A) (C + I + A; n = 52). Statistical analyses were performed using R software, version 4.3.3. Categorical variables were compared using Fisher's exact test, and survival curves were estimated with the Kaplan-Meier method and compared via the log-rank test. Univariate and multivariate Cox regression models were used to assess factors associated with overall survival (OS). Bayesian model averaging (BMA) was employed to address model uncertainty and improve result robustness. Subgroup analyses evaluated treatment-related mortality risk. RESULTS: From an initial cohort of 658 NSCLC patients with BMs, 209 were analyzed with a median age of 59; the majority were male (80.9%) and diagnosed with adenocarcinoma (78.9%). Univariate analysis identified significant variables influencing outcomes, including BMs radiotherapy EQD2, BMs count, local thoracic treatment, BMs radiotherapy field, intracranial response, and systemic treatment post-BMs diagnosis. The C + I + A regimen significantly improved median OS to 23.6 months compared to 11.4 months with C and 16.2 months with C + I, with a hazard ratio (HR) of 0.60 (95% CI: 0.43-0.82; P < 0.0001). The two-year OS rate was highest in the C + I + A group at 38.5%, versus 10.5% in C and 20.4% in C + I (P < 0.001). Cox regression and BMA analyses confirmed the stability of BMA in providing HR estimates, yielding area under the curve (AUC) values of 0.785 for BMA and 0.793 for the Cox model, with no significant difference in predictive performance. Subgroup analysis revealed a 71% mortality risk reduction with C + I + A (HR: 0.29; 95% CI: 0.18-0.47; P < 0.0001), showing consistent benefits regardless of patient sex, BMs count, extracranial metastases presence, and local thoracic treatments. Treatment sequence analysis indicated a median OS of 33.4 months for patients starting with A, though not statistically significant (HR: 0.59; P = 0.36). The overall incidence of radiation-induced brain injury was low at 3.3%, with rates in the C, C + I, and C + I + A groups being 3.2%, 4.8%, and 1.9%, respectively (P = 0.683). CONCLUSION: Our study demonstrates the significant benefit of the C + I + A combination therapy in improving OS and reducing mortality risk in NSCLC patients with non-sensitive gene-mutated BMs. The sequential administration of A followed by ICIs shows a promising synergistic effect with cranial radiotherapy, highlighting the potential for optimized treatment sequencing. These findings emphasize the efficacy of tailored combination therapies in complex oncological care and suggest that our approach could lead to meaningful improvements in clinical outcomes for this challenging patient population.

Clinico-pathologic factors and survival of patients with breast cancer diagnosed with de novo brain metastasis: a national cancer database analysis.

PURPOSE: Patients with Breast Cancer (BC) with Brain Metastasis (BCBM) have poor survival outcomes. We aimed to explore the clinico-pathologic and therapeutic factors predicting the survival in patients with de novo BCBM using the National Cancer Database (NCDB). PATIENTS AND METHODS: The NCDB was queried for patients with BC between 2010 and 2020. Survival analysis with Kaplan-Meier curves and log rank tests were used to find median overall survival (OS) in months (95% CI) across the different variables. A multivariate cox regression model was computed to identify significant predictors of survival. RESULTS: Out of n = 2,610,598 patients, n = 9005 (0.34%) had de novo BCBM. A trend of decreasing OS was observed with increasing age, Charlson-Deyo score (CDS), and number of extracranial metastatic sites. The highest median OS was observed in the Triple Positive and the lowest OS in the Triple Negative subgroup. Based on treatment regimen, combination of systemic therapy and local therapy achieved the highest OS. A positive trend in OS was observed in the BC subgroup analysis with targeted therapy demonstrating a survival benefit when added to systemic therapy. The multivariate cox regression model showed that age, race, ethnicity, insurance, median income, facility type, CDS, BC subtype, metastatic location sites, and treatment combinations received were significantly associated with risk of death. Receiving only local treatment for BM without systemic therapy more than doubled the risk of death compared to combining it with systemic therapy. CONCLUSIONS: This analysis suggests that treatment of systemic disease is the major factor influencing survival in patients with BCBM. Moreover, targeted therapy with anti-HER2 increased survival when added to systemic therapy explaining the highest median OS noted in the Triple Positive subgroup.

Survival analysis of patients with brain metastases at initial breast cancer diagnosis over the last decade.

PURPOSE: There have been significant advances in the treatment of metastatic breast cancer (BC) over the past years, and long-term outcomes after a diagnosis of brain metastases are lacking. We aimed to identify predictors of brain metastases at initial breast cancer diagnosis, describe overall survival (OS) in the past decade, and identify factors associated with OS after brain metastases diagnosis. METHODS: We evaluated patients with de novo stage IV BC using the Surveillance, Epidemiology and End Results database from 2010 to 2019. Multivariate logistic regression was conducted to assess predictors of brain metastases at initial breast cancer diagnosis. OS was estimated using the Kaplan-Meier method and log rank test was used to compare differences between groups. Cox regression was used to assess associations between several variables and OS. RESULTS: 1,939 patients with brain metastases at initial breast cancer diagnosis were included. Factors associated with this presentation were grade III/IV tumors, ductal histology, hormone receptor (HR)-negative/human epidermal growth factor receptor 2 (HER2)-positive subtype, and extracranial metastases. Patients with HR-positive/HER2-positive disease had the longest OS (median 18 months) and 12.2% were alive at 8 years. Factors associated with shorter OS included older age, lower income, triple-negative subtype, higher grade, and visceral metastases. CONCLUSION: Over the last decade, the median OS of patients with brain metastases at initial breast cancer diagnosis remained poor; however, a substantial minority survive 5 or more years, with rates higher in patients with HER2-positive tumors. In addition to tumor subtype, OS varied according to age, extracranial metastases, and sociodemographic factors.

A deep learning model for differentiating paediatric intracranial germ cell tumour subtypes and predicting survival with MRI: a multicentre prospective study.

BACKGROUND: The pretherapeutic differentiation of subtypes of primary intracranial germ cell tumours (iGCTs), including germinomas (GEs) and nongerminomatous germ cell tumours (NGGCTs), is essential for clinical practice because of distinct treatment strategies and prognostic profiles of these diseases. This study aimed to develop a deep learning model, iGNet, to assist in the differentiation and prognostication of iGCT subtypes by employing pretherapeutic MR T2-weighted imaging. METHODS: The iGNet model, which is based on the nnUNet architecture, was developed using a retrospective dataset of 280 pathologically confirmed iGCT patients. The training dataset included 83 GEs and 117 NGGCTs, while the retrospective internal test dataset included 31 GEs and 49 NGGCTs. The model's diagnostic performance was then assessed with the area under the receiver operating characteristic curve (AUC) in a prospective internal dataset (n = 22) and two external datasets (n = 22 and 20). Next, we compared the diagnostic performance of six neuroradiologists with or without the assistance of iGNet. Finally, the predictive ability of the output of iGNet for progression-free and overall survival was assessed and compared to that of the pathological diagnosis. RESULTS: iGNet achieved high diagnostic performance, with AUCs between 0.869 and 0.950 across the four test datasets. With the assistance of iGNet, the six neuroradiologists' diagnostic AUCs (averages of the four test datasets) increased by 9.22% to 17.90%. There was no significant difference between the output of iGNet and the results of pathological diagnosis in predicting progression-free and overall survival (P = .889). CONCLUSIONS: By leveraging pretherapeutic MR imaging data, iGNet accurately differentiates iGCT subtypes, facilitating prognostic evaluation and increasing the potential for tailored treatment.

Sarcopenia is associated with chemoradiotherapy discontinuation and reduced progression-free survival in glioblastoma patients.

PURPOSE: Sarcopenia may complicate treatment in cancer patients. Herein, we assessed whether sarcopenia measurements derived from radiation planning computed tomography (CT) were associated with complications and tumor progression during radiochemotherapy for glioblastoma. METHODS: Consecutive patients undergoing radiotherapy planning for glioblastoma between 2010 and 2021 were analyzed. Retrocervical muscle cross-sectional area (CSA) was measured via threshold-based semi-automated radiation planning CT analysis. Patients in the lowest sex-specific quartile of muscle measurements were defined as sarcopenic. We abstracted treatment characteristics and tumor progression from the medical records and performed uni- and multivariable time-to-event analyses. RESULTS: We included 363 patients in our cohort (41.6% female, median age 63 years, median time to progression 7.7 months). Sarcopenic patients were less likely to receive chemotherapy (p < 0.001) and more likely to be treated with hypofractionated radiotherapy (p = 0.005). Despite abbreviated treatment, they more often discontinued radiotherapy (p = 0.023) and were more frequently prescribed corticosteroids (p = 0.014). After treatment, they were more often transferred to inpatient palliative care treatment (p = 0.035). Finally, progression-free survival was substantially shorter in sarcopenic patients in univariable (median 5.1 vs. 8.4 months, p < 0.001) and multivariable modeling (hazard ratio 0.61 [confidence interval 0.46-0.81], p = 0.001). CONCLUSION: Sarcopenia is a strong risk factor for treatment discontinuation and reduced progression-free survival in glioblastoma patients. We propose that sarcopenic patients should receive intensified supportive care during radiotherapy and during follow-up as well as expedited access to palliative care.