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Standard treatment of patients with glioblastoma includes surgical resection of the tumor. The extent of resection (EOR) achieved during surgery significantly impacts prognosis and is used to stratify patients in clinical trials. In this study, we developed a U-Net-based deep-learning model to segment contrast-enhancing tumor on post-operative MRI exams taken within 72â h of resection surgery and used these segmentations to classify the EOR as either maximal or submaximal. The model was trained on 122 multiparametric MRI scans from our institution and achieved a mean Dice score of 0.52 ± 0.03 on an external dataset (n = 248), a performance -on par with the interrater agreement between expert annotators as reported in literature. We obtained an EOR classification precision/recall of 0.72/0.78 on the internal test dataset (n = 462) and 0.90/0.87 on the external dataset. Furthermore, Kaplan-Meier curves were used to compare the overall survival between patients with maximal and submaximal resection in the internal test dataset, as determined by either clinicians or the model. There was no significant difference between the survival predictions using the model's and clinical EOR classification. We find that the proposed segmentation model is capable of reliably classifying the EOR of glioblastoma tumors on early post-operative MRI scans. Moreover, we show that stratification of patients based on the model's predictions offers at least the same prognostic value as when done by clinicians.
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AIMS: The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter region is essential in evaluating the prognosis and predicting the drug response in patients with glioblastoma. In this study, we evaluated the utility of using nanopore long-read sequencing as a method for assessing methylation levels throughout the MGMT CpG-island, compared its performance to established techniques and demonstrated its clinical applicability. METHODS: We analysed 165 samples from CNS tumours, focusing on the MGMT CpG-island using nanopore sequencing. Oxford Nanopore Technologies (ONT) MinION and PromethION flow cells were employed for single sample or barcoded assays, guided by a CRISPR/Cas9 protocol, adaptive sampling or as part of a whole genome sequencing assay. Methylation data obtained through nanopore sequencing were compared to results obtained via pyrosequencing and methylation bead arrays. Hierarchical clustering was applied to nanopore sequencing data for patient stratification. RESULTS: Nanopore sequencing displayed a strong correlation (R2 = 0.91) with pyrosequencing results for the four CpGs of MGMT analysed by both methods. The MGMT-STP27 algorithm's classification was effectively reproduced using nanopore data. Unsupervised hierarchical clustering revealed distinct patterns in methylated and unmethylated samples, providing comparable survival prediction capabilities. Nanopore sequencing yielded high-confidence results in a rapid timeframe, typically within hours of sequencing, and extended the analysis to all 98 CpGs of the MGMT CpG-island. CONCLUSIONS: This study presents nanopore sequencing as a valid and efficient method for determining MGMT promotor methylation status. It offers a comprehensive view of the MGMT promoter methylation landscape, which enables the identification of potentially clinically relevant subgroups of patients. Further exploration of the clinical implications of patient stratification using nanopore sequencing of MGMT is warranted.
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Metilação de DNA , Sequenciamento por Nanoporos , Regiões Promotoras Genéticas , Humanos , Sequenciamento por Nanoporos/métodos , Regiões Promotoras Genéticas/genética , Ilhas de CpG/genética , Proteínas Supressoras de Tumor/genética , Metilases de Modificação do DNA/genética , Enzimas Reparadoras do DNA/genética , Neoplasias Encefálicas/genética , Feminino , Masculino , Glioblastoma/genética , IdosoRESUMO
PURPOSE: Glioblastoma (GBM) is an aggressive brain tumor in which primary therapy is standardized and consists of surgery, radiotherapy (RT), and chemotherapy. However, the optimal time from surgery to start of RT is unknown. A high-grade glioma cancer patient pathway (CPP) was implemented in Norway in 2015 to avoid non-medical delays and regional disparity, and to optimize information flow to patients. This study investigated how CPP affected time to RT after surgery and overall survival. METHODS: This study included consecutive GBM patients diagnosed in South-Eastern Norway Regional Health Authority from 2006 to 2019 and treated with RT. The pre CPP implementation group constituted patients diagnosed 2006-2014, and the post CPP implementation group constituted patients diagnosed 2016-2019. We evaluated timing of RT and survival in relation to CPP implementation. RESULTS: A total of 1212 patients with GBM were included. CPP implementation was associated with significantly better outcomes (p < 0.001). Median overall survival was 12.9 months. The odds of receiving RT within four weeks after surgery were significantly higher post CPP implementation (p < 0.001). We found no difference in survival dependent on timing of RT below 4, 4-6 or more than 6 weeks (p = 0.349). Prognostic factors for better outcomes in adjusted analyses were female sex (p = 0.005), younger age (p < 0.001), solitary tumors (p = 0.008), gross total resection (p < 0.001), and higher RT dose (p < 0.001). CONCLUSION: CPP implementation significantly reduced time to start of postoperative RT. Survival was significantly longer in the period after the CPP implementation, however, timing of postoperative RT relative to time of surgery did not impact survival.
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Neoplasias Encefálicas , Glioblastoma , Tempo para o Tratamento , Humanos , Glioblastoma/radioterapia , Glioblastoma/mortalidade , Glioblastoma/cirurgia , Masculino , Feminino , Pessoa de Meia-Idade , Neoplasias Encefálicas/mortalidade , Neoplasias Encefálicas/radioterapia , Idoso , Tempo para o Tratamento/estatística & dados numéricos , Noruega/epidemiologia , Adulto , Taxa de Sobrevida , Estudos de Coortes , Prognóstico , Procedimentos Clínicos , Estudos Retrospectivos , Adulto Jovem , SeguimentosRESUMO
BACKGROUND: Surveillance of incidence and survival of central nervous system tumors is essential to monitor disease burden and epidemiological changes, and to allocate health care resources. Here, we describe glioma incidence and survival trends by histopathology group, age, and sex in the Norwegian population. MATERIAL AND METHODS: We included patients with a histologically verified glioma reported to the Cancer Registry of Norway from 2002 to 2021 (N = 7,048). Population size and expected mortality were obtained from Statistics Norway. Cases were followed from diagnosis until death, emigration, or 31 December 2022, whichever came first. We calculated age-standardized incidence rates (ASIR) per 100,000 person-years and age-standardized relative survival (RS). Results: The ASIR for histologically verified gliomas was 7.4 (95% CI: 7.3-7.6) and was higher for males (8.8; 95% CI: 8.5-9.1) than females (6.1; 95% CI: 5.9-6.4). Overall incidence was stable over time. Glioblastoma was the most frequent tumor entity (ASIR = 4.2; 95% CI: 4.1-4.4). Overall, glioma patients had a 1-year RS of 63.6% (95% CI: 62.5-64.8%), and a 5-year RS of 32.8% (95% CI: 31.6-33.9%). Females had slightly better survival than males. For most entities, 1- and 5-year RS improved over time (5-year RS for all gliomas 29.0% (2006) and 33.1% (2021), p < 0.001). Across all tumor types, the RS declined with increasing age at diagnosis. INTERPRETATION: The incidence of gliomas has been stable while patient survival has increased over the past 20 years in Norway. As gliomas represent a heterogeneous group of primary CNS tumors, regular reporting from cancer registries at the histopathology group level is important to monitor disease burden and allocate health care resources in a population.
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Glioma , Masculino , Feminino , Humanos , Incidência , Estudos de Coortes , Glioma/epidemiologia , Sistema de Registros , Noruega/epidemiologiaRESUMO
Glioblastoma (GBM) is an aggressive and highly heterogeneous primary brain tumor. Glioma stem cells represent a subpopulation of tumor cells with stem cell traits that are presumed to be the cause of tumor relapse. There exists complex tumor heterogeneity in drug sensitivity patterns between glioma stem cell (GSC) cultures derived from different patients. Here, we describe that heterogeneity also exists between GSC cultures derived from multiple biopsies within a single tumor. From biopsies harvested within spatially distinct regions representing the entire tumor mass, we established seven GSC cultures and compared their stem cell properties, mutations, gene expression profiles, and drug sensitivity patterns against 115 different anticancer drugs. The results were compared to 14 GSC cultures derived from other patients. Between the multiregional-derived GSC cultures, we observed only minor differences in their phenotype, proliferative capacity, and global gene expression. Further, they displayed intratumoral heterogeneity in mutational profiles and sensitivity patterns to anticancer drugs. This heterogeneity, however, did not exceed the extensive heterogeneity found between GSC cultures derived from other GBM patients. Our results suggest that the use of GSC cultures from one single focal biopsy may underestimate the overall complexity of the GSC population and display the importance of including GSC cultures reflecting the entire tumor mass in drug screening strategies.