Abstract
INTRODUCTION
The INDIGO study (NCT04164901) showed that vorasidenib, an oral, brain-penetrant, dual inhibitor of mutant isocitrate dehydrogenase (mIDH) 1/2, significantly improved ...imaging-based progression-free survival and time-to-next-intervention compared with placebo in patients with grade 2 mIDH1/2 glioma previously treated with surgery only. Given the limitations of traditional bi-dimensional measurements, evaluating volumetry and tumor growth rate (TGR) is an additional method of measuring treatment effect in these diffuse growing tumors.
METHODS
Magnetic resonance imaging (MRI) scans were performed at baseline and every 12 weeks on-treatment; up to three pre-treatment MRI scans were requested when available. Tumor volumes were derived per blinded independent review committee using a semi-automated approach. TGR was defined as percentage change in tumor volume every 6 months. Patients with evaluable baseline and ≥ 1 MRI during the corresponding period were included in the analysis. The difference in TGR in each arm was assessed by slope of tumor growth over time using a linear mixed model.
RESULTS
331 patients were randomized to vorasidenib (n=168) or placebo (n=163). Median follow-up was 14.2 months. On-treatment TGR was −2.5% (95% CI, −4.7, −0.2) with vorasidenib (n=167) and 13.9% (95% CI, 11.1, 16.8) with placebo (n=161). In patients with available imaging data, TGR pre- and post-treatment with vorasidenib (n=56) was 13.2% (95% CI, 10.3, 16.3) and −3.3% (95% CI, −5.2, −1.2), respectively, while placebo (n=67) was 18.3% (95% CI, 15.0, 21.7) and 12.2% (95% CI, 9.5, 14.9), respectively. In patients who crossed over from placebo with available imaging data (n=38), TGR pre- and post-crossover was 22.4% (95% CI, 15.7, 29.4) and 5.2% (95% CI, −3.8, 15.0), respectively.
CONCLUSIONS
Tumor growth was observed in patients with mIDH1/2 gliomas before receiving vorasidenib or placebo. Treatment with vorasidenib reduced the TGR and shrunk tumor volume, whereas continued growth in tumor volume was observed in patients receiving placebo.
Specific biological properties of those circulating cancer cells that are the origin of brain metastases (BM) are not well understood. Here, single circulating breast cancer cells were fate-tracked ...during all steps of the brain metastatic cascade in mice after intracardial injection over weeks. A novel
two-photon microscopy methodology was developed that allowed to determine the specific cellular and molecular features of breast cancer cells that homed in the brain, extravasated, and successfully established a brain macrometastasis. Those BM-initiating breast cancer cells (BMIC) were mainly originating from a slow-cycling subpopulation that included only 16% to 20% of all circulating cancer cells. BMICs showed enrichment of various markers of cellular stemness. As a proof of principle for the principal usefulness of this approach, expression profiling of BMICs versus non-BMICs was performed, which revealed upregulation of NDRG1 in the slow-cycling BMIC subpopulation in one BM model. Here, BM development was completely suppressed when NDRG1 expression was downregulated. In accordance, in primary human breast cancer, NDRG1 expression was heterogeneous, and high NDRG1 expression was associated with shorter metastasis-free survival. In conclusion, our data identify temporary slow-cycling breast cancer cells as the dominant source of brain and other metastases and demonstrates that this can lead to better understanding of BMIC-relevant pathways, including potential new approaches to prevent BM in patients. IMPLICATIONS: Cancer cells responsible for successful brain metastasis outgrowth are slow cycling and harbor stemness features. The molecular characteristics of these metastasis-initiating cells can be studied using intravital microscopy technology.
A successful therapeutic paradigm established historically in oncology involves combining agents with potentially complementary mechanisms of antitumor activity into rationally designed regimens. For ...example, cocktails of cytotoxic agents, which were carefully designed based on mechanisms of action, dose, and scheduling considerations, have led to dramatic improvements in survival including cures for childhood leukemia, Hodgkin's lymphoma, and several other complex cancers. Outcome for glioblastoma, the most common primary malignant CNS cancer, has been more modest, but nonetheless our current standard of care derives from confirmation that combination therapy surpasses single modality therapy. Immunotherapy has recently come of age for medical oncology with exciting therapeutic benefits achieved by several types of agents including vaccines, adoptive T cells, and immune checkpoint inhibitors against several types of cancers. Nonetheless, most benefits are relatively short, while others are durable but are limited to a minority of treated patients. Critical factors limiting efficacy of immunotherapeutics include insufficient immunogenicity and/or inadequate ability to overcome immunosuppressive factors exploited by tumors. The paradigm of rationally designed combinatorial regimens, originally established by cytotoxic therapy for oncology, may also prove relevant for immunotherapy. Realization of the true therapeutic potential of immunotherapy for medical oncology and neuro-oncology patients may require development of combinatorial regimens that optimize immunogenicity and target tumor adaptive immunosuppressive factors.
The discovery of driver mutations in cancers has raised interest in their suitability as immunotherapeutic targets. A recent study demonstrates that a point mutation in isocitrate dehydrogenase 1 ...(IDH1R132H), expressed in gliomas and other tumors, is presented on human MHC class II and induces a mutation-specific CD4
+
antitumor T cell response in patients and a syngeneic tumor model in MHC-humanized mice.
Oligodendrogliomas are defined at the molecular level by the presence of an IDH mutation and codeletion of chromosomal arms 1p and 19q. In the past, case reports and small studies described gliomas ...with sarcomatous features arising from oligodendrogliomas, so called oligosarcomas. Here, we report a series of 24 IDH-mutant oligosarcomas from 23 patients forming a distinct methylation class. The tumors were recurrences from prior oligodendrogliomas or developed de novo. Precursor tumors of 12 oligosarcomas were histologically and molecularly indistinguishable from conventional oligodendrogliomas. Oligosarcoma tumor cells were embedded in a dense network of reticulin fibers, frequently showing p53 accumulation, positivity for SMA and CALD1, loss of OLIG2 and gain of H3K27 trimethylation (H3K27me3) as compared to primary lesions. In 5 oligosarcomas no 1p/19q codeletion was detectable, although it was present in the primary lesions. Copy number neutral LOH was determined as underlying mechanism. Oligosarcomas harbored an increased chromosomal copy number variation load with frequent
CDKN2A/B
deletions. Proteomic profiling demonstrated oligosarcomas to be highly distinct from conventional CNS WHO grade 3 oligodendrogliomas with consistent evidence for a smooth muscle differentiation. Expression of several tumor suppressors was reduced with NF1 being lost frequently. In contrast, oncogenic YAP1 was aberrantly overexpressed in oligosarcomas. Panel sequencing revealed mutations in
NF1
and
TP53
along with
IDH1/2
and
TERT
promoter mutations. Survival of patients was significantly poorer for oligosarcomas as first recurrence than for grade 3 oligodendrogliomas as first recurrence. These results establish oligosarcomas as a distinct group of IDH-mutant gliomas differing from conventional oligodendrogliomas on the histologic, epigenetic, proteomic, molecular and clinical level. The diagnosis can be based on the combined presence of (a) sarcomatous histology, (b) IDH-mutation and (c)
TERT
promoter mutation and/or 1p/19q codeletion, or, in unresolved cases, on its characteristic DNA methylation profile.
Abstract
Background
Symptom management in glioma patients remains challenging, as patients suffer from various concurrently occurring symptoms. This study aimed to identify symptom clusters and ...examine the association between these symptom clusters and patients’ functioning.
Methods
Data of the CODAGLIO project was used, including individual patient data from previously published international randomized controlled trials (RCTs) in glioma patients. Symptom prevalence and level of functioning were assessed with European Organisation for Research and Treatment of Cancer (EORTC) quality of life QLQ-C30 and QLQ-BN20 self-report questionnaires. Associations between symptoms were examined with Spearman correlation coefficients and partial correlation networks. Hierarchical cluster analyses were performed to identify symptom clusters. Multivariable regression analyses were performed to determine independent associations between the symptom clusters and functioning, adjusted for possible confounders.
Results
Included in the analysis were 4307 newly diagnosed glioma patients from 11 RCTs who completed the EORTC questionnaires before randomization. Many patients (44%) suffered from 5–10 symptoms simultaneously. Four symptom clusters were identified: a motor cluster, a fatigue cluster, a pain cluster, and a gastrointestinal/seizures/bladder control cluster. Having symptoms in the motor cluster was associated with decreased (≥10 points difference) physical, role, and social functioning (betas ranged from −11.3 to −15.9, all P < 0.001), independent of other factors. Similarly, having symptoms in the fatigue cluster was found to negatively influence role functioning (beta of −12.3, P < 0.001), independent of other factors.
Conclusions
Two symptom clusters, the fatigue and motor cluster, were frequently affected in glioma patients and were found to independently have a negative association with certain aspects of patients’ functioning as measured with a self-report questionnaire.
Purpose
The Working Group for Neuro-Oncology of the German Society for Radiation Oncology in cooperation with members of the Neuro-Oncology Working Group of the German Cancer Society aimed to define ...a practical guideline for the diagnosis and treatment of radiation-induced necrosis (RN) of the central nervous system (CNS).
Methods
Panel members of the DEGRO working group invited experts, participated in a series of conferences, supplemented their clinical experience, performed a literature review, and formulated recommendations for medical treatment of RN including bevacizumab in clinical routine.
Conclusion
Diagnosis and treatment of RN requires multidisciplinary structures of care and defined processes. Diagnosis has to be made on an interdisciplinary level with the joint knowledge of a neuroradiologist, radiation oncologist, neurosurgeon, neuropathologist, and neuro-oncologist. A multistep approach as an opportunity to review as many characteristics as possible to improve diagnostic confidence is recommended. Additional information about radiotherapy (RT) techniques is crucial for the diagnosis of RN. Misdiagnosis of untreated and progressive RN can lead to severe neurological deficits. In this practice guideline, we propose a detailed nomenclature of treatment-related changes and a multistep approach for their diagnosis.
Abstract
Pediatric brain tumor entities harbor a variety of gene fusions. Whilst other molecular parameters like somatic mutations and copy number alterations have become pivotal for brain tumor ...diagnostics, gene fusions are only less well covered by routinely applied methylation arrays or targeted next-generation sequencing of DNA. In a routine diagnostic setting we established and optimized a workflow for investigation of gene fusions in formalin-fixed paraffin-embedded (FFPE) tumor tissues by using RNA sequencing. Assessing different tools for calling fusions from raw data, we found relevant fusions in 66 out of 101 (65%) analyzed cases in a prospective cohort collected over 26 months. In 43 (43%) cases the fusions were of decisive diagnostic relevance and in 40 (40%) cases the fusion genes rendered a druggable target. Besides the relevance of pathognomonic fusions for diagnostics, especially the detection of druggable gene fusions yields direct benefit to the patients. This approach allows for an unbiased search for fusion events in the tested samples. Besides rare variants of established fusions which were not detected by prior targeted analyses, we identified previously unreported fusion events. Exemplified on KIAA1549:BRAF fusion, we in addition provide an overview of the detection accuracy of different methods, including breakpoint detection in DNA methylation array data and fusion gene detection in DNA panel sequencing data. Our data show that RNA sequencing has great diagnostic as well as therapeutic value by clinically detecting relevant alterations.
Abstract
Background
This study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and ...assesses the impact of DWI intensity normalization on model generalizability.
Methods
Radiomic features, compliant with image biomarker standardization initiative standards, were extracted from preoperative MRI of 549 patients with diffuse glioma, known IDH, and 1p19q-status. Anatomical sequences (T1, T1c, T2, FLAIR) underwent N4-Bias Field Correction (N4) and WhiteStripe normalization (N4/WS). Apparent diffusion coefficient (ADC) maps were normalized using N4 or N4/z-score. Nine machine-learning algorithms were trained for multiclass prediction of glioma types (IDH-mutant 1p/19q codeleted, IDH-mutant 1p/19q non-codeleted, IDH-wild type). Four approaches were compared: Anatomical, anatomical + ADC naive, anatomical + ADC N4, and anatomical + ADC N4/z-score. The University of California San Francisco (UCSF)-glioma dataset (n = 409) was used for external validation.
Results
Naïve-Bayes algorithms yielded overall the best performance on the internal test set. Adding ADC radiomics significantly improved AUC from 0.79 to 0.86 (P = .011) for the IDH-wild-type subgroup, but not for the other 2 glioma subgroups (P > .05). In the external UCSF dataset, the addition of ADC radiomics yielded a significantly higher AUC for the IDH-wild-type subgroup (P ≤ .001): 0.80 (N4/WS anatomical alone), 0.81 (anatomical + ADC naive), 0.81 (anatomical + ADC N4), and 0.88 (anatomical + ADC N4/z-score) as well as for the IDH-mutant 1p/19q non-codeleted subgroup (P < .012 each).
Conclusions
ADC radiomics can enhance the performance of conventional MRI-based radiomic models, particularly for IDH-wild-type glioma. The benefit of intensity normalization of ADC maps depends on the type and context of the used data.
Lay Summary
Gliomas are tumors that originate in the brain. These tumors are classified into 3 main genetic groups: IDH-mutant 1p/19q codeleted, IDH-mutant 1p/19q non-codeleted, IDH-wild type. Knowing which genetic group a glioma belongs to is important for predicting how the tumor will behave. At present, this can only be achieved through genetic testing of tissue obtained during surgery. The authors of this study aimed to determine whether the genetic group of glioma could be predicted using magnetic resonance imaging (MRI). To do this, they developed computer models that combined a special MRI sequence, which detects the movement of water in tumor cells (ADC), with standard anatomic MRI scans. They then tested their models using publicly available data. Their results show that the addition of features from the ADC sequences improved the prediction of some, but not all, genetic types of gliomas.
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