Neuro-oncology advances最新文献

Background: Current standard management in adult grades 2-4 gliomas includes maximal safe resection followed by adjuvant radiotherapy (RT) and chemotherapy. Radiation-induced lymphopenia (RIL) has been shown to possibly affect treatment outcomes adversely. Proton beam therapy (PBT) may reduce the volume of the normal brain receiving moderate radiation doses, and consequently RIL. Our aim was to evaluate the incidence and severity of RIL during proton beam therapy (PBT).

Methods: We identified patients with grades 2-4 glioma treated with PBT at our center between January 2019 and December 2021. We evaluated the incidence and severity of RIL from weekly complete blood count (CBC) data collected during PBT and compared it to the patients who were treated with photon-based RT (XRT) at our center during the same time.

Results: The incidence of any degree of lymphopenia (48% in PBT, vs. 81.2% in XRT, P value = .001) and severe lymphopenia (8% in PBT, vs. 24.6% in XRT, P value = .093) were both significantly lesser in patients who received PBT. Severe RIL in patients receiving PBT was seen in only CNS WHO Gr-4 tumors. Mean whole brain V20GyE and V25GyE inversely correlated to nadir ALC and were both significantly lower with PBT. Patients with lymphopenia during PBT showed a trend toward poorer progression-free survival (P = .053) compared to those with maintained lymphocyte counts.

Conclusions: Proton therapy seems to have a superior sparing of normal brain to moderate dose radiation than photon-based RT and reduces the incidence of lymphopenia. Glioma patients with lymphopenia possibly have worse outcomes than the ones with maintained lymphocyte counts.

Background: Meningiomas are the most common primary brain tumors. While most are benign (WHO grade 1) and have a favorable prognosis, up to one-fourth are classified as higher-grade, falling into WHO grade 2 or 3 categories. Recently, an integrated risk score (IRS) pertaining to tumor biology was developed and its prognostic relevance was validated in a large, multicenter study. We hypothesized imaging data to be reflective of the IRS. Thus, we assessed the potential of a machine learning classifier for its noninvasive prediction using preoperative magnetic resonance imaging (MRI).

Methods: In total, 160 WHO grade 2 and 3 meningioma patients from 2 university centers were included in this study. All patients underwent surgery with histopathological workup including methylation analysis. Preoperative MRI scans were automatically segmented, and radiomic parameters were extracted. Using a random forest classifier, 3 machine learning classifiers (1 multiclass classifier for IRS and 2 binary classifiers for low-risk and high-risk prediction, respectively) were developed in a training set (120 patients) and independently tested in a hold-out test set (40 patients).

Results: Multiclass IRS classification had a test set area under the curve (AUC) of 0.7, mostly driven by the difficulties in clearly separating medium-risk from high-risk patients. Consequently, a classifier predicting low-risk IRS versus medium-/high-risk showed a very high test accuracy of 90% (AUC 0.88). In particular, "sphericity" was associated with low-risk IRS classification.

Conclusion: The IRS, in particular molecular low-risk, can be predicted from imaging data with high accuracy, making this important prognostic classification accessible by imaging.

Background: Based on preclinical studies showing that IDH-mutant (IDHm) gliomas could be vulnerable to PARP inhibition we launched a multicenter phase 2 study to test the efficacy of olaparib monotherapy in this population.

Methods: Adults with recurrent IDHm high-grade gliomas (HGGs) after radiotherapy and at least one line of alkylating chemotherapy were enrolled. The primary endpoint was a 6-month progression-free survival rate (PFS-6) according to response assessment in neuro-oncology criteria. Pre-defined threshold for study success was a PFS-6 of at least 50%.

Results: Thirty-five patients with recurrent IDHm HGGs were enrolled, 77% at ≥ 2nd recurrence. Median time since diagnosis and radiotherapy were 7.5 years and 33 months, respectively. PFS-6 was 31.4% (95% CI [16.9; 49.3%]). Two patients (6%) had an objective response and 14 patients (40%) had a stable disease as their best response. Median PFS and median overall survival were 2.05 and 15.9 months, respectively. Oligodendrogliomas (1p/19q codeleted) had a higher PFS-6 (53.4% vs. 15.7%, P = .05) than astrocytomas while an initial diagnosis of grade 4 astrocytoma tended to be associated with a lower PFS-6 compared to grade 2/3 gliomas (0% vs 31.4%, P = .16). A grade 2 or 3 treatment-related adverse event was observed in 15 patients (43%) and 5 patients (14%), respectively. No patient definitively discontinued treatment due to side effects.

Conclusions: Although it did not meet its primary endpoint, the present study shows that in this heavily pretreated population, olaparib monotherapy was well tolerated and resulted in some activity, supporting further PARP inhibitors evaluation in IDHm HGGs, especially in oligodendrogliomas.

Genomic ascertainment is the inversion of the traditional phenotype-first approach; with a "genome-first" approach, a cohort linked to electronic health records (EHR) undergoes germline sequencing (array, panel, exome, and genome) and deleterious variation of interest in a gene (or set of genes) are identified. Phenotype is then queried from the linked EHR and from call-back investigation and estimates of variant prevalence, disease penetrance, and phenotype can be determined. This should permit a better estimate of the full phenotypic spectrum, severity, and penetrance linked to a deleterious variant. For now, given the modest size, limited EHR, and age of participants in sequenced cohorts, genomic ascertainment approaches to investigate cancer in children and young adults will likely be restricted to descriptive studies and complement traditional phenotype-first work. Another issue is the ascertainment of the cohort itself: Participants need to survive long enough to enroll. Not accounting for this may lead to bias and incorrect estimates of variant prevalence. Adult-focused cohorts with EHR extending back into childhood, linked to cancer registries, and/or studies that permit recontact with participants may facilitate genomic ascertainment in pediatric cancer research. In summary, genomic ascertainment in pediatric primary brain cancer research remains largely untapped and merits further investigation.