Development of the CNS TAP tool for the selection of precision medicine therapies in neuro-oncology

Quantifying the Growth of Glioblastoma Tumors Using Multimodal MRI Brain Images

Predicting the eventual volume of tumor cells, that might proliferate from a given tumor, can help in cancer early detection and medical procedure planning to prevent their migration to other organs. In this work, a new statistical framework is proposed using Bayesian techniques for detecting the eventual volume of cells expected to proliferate from a glioblastoma (GBM) tumor. Specifically, the tumor region was first extracted using a parallel image segmentation algorithm. Once the tumor region was determined, we were interested in the number of cells that could proliferate from this tumor until its survival time. For this, we constructed the posterior distribution of the tumor cell numbers based on the proposed likelihood function and a certain prior volume. Furthermore, we extended the detection model and conducted a Bayesian regression analysis by incorporating radiomic features to discover those non-tumor cells that remained undetected. The main focus of the study was to develop a time-independent prediction model that could reliably predict the ultimate volume a malignant tumor of the fourth-grade severity could attain and which could also determine if the incorporation of the radiomic properties of the tumor enhanced the chances of no malignant cells remaining undetected.

Upfront Biology-Guided Therapy in Diffuse Intrinsic Pontine Glioma: Therapeutic, Molecular, and Biomarker Outcomes from PNOC003

PURPOSE

PNOC003 is a multicenter precision medicine trial for children and young adults with newly diagnosed diffuse intrinsic pontine glioma (DIPG).

PATIENTS AND METHODS

Patients (3-25 years) were enrolled on the basis of imaging consistent with DIPG. Biopsy tissue was collected for whole-exome and mRNA sequencing. After radiotherapy (RT), patients were assigned up to four FDA-approved drugs based on molecular tumor board recommendations. H3K27M-mutant circulating tumor DNA (ctDNA) was longitudinally measured. Tumor tissue and matched primary cell lines were characterized using whole-genome sequencing and DNA methylation profiling. When applicable, results were verified in an independent cohort from the Children's Brain Tumor Network (CBTN).

RESULTS

Of 38 patients enrolled, 28 patients (median 6 years, 10 females) were reviewed by the molecular tumor board. Of those, 19 followed treatment recommendations. Median overall survival (OS) was 13.1 months [95% confidence interval (CI), 11.2-18.4] with no difference between patients who followed recommendations and those who did not. H3K27M-mutant ctDNA was detected at baseline in 60% of cases tested and associated with response to RT and survival. Eleven cell lines were established, showing 100% fidelity of key somatic driver gene alterations in the primary tumor. In H3K27-altered DIPGs, TP53 mutations were associated with worse OS (TP53mut 11.1 mo; 95% CI, 8.7-14; TP53wt 13.3 mo; 95% CI, 11.8-NA; P = 3.4e-2), genome instability (P = 3.1e-3), and RT resistance (P = 6.4e-4). The CBTN cohort confirmed an association between TP53 mutation status, genome instability, and clinical outcome.

CONCLUSIONS

Upfront treatment-naïve biopsy provides insight into clinically relevant molecular alterations and prognostic biomarkers for H3K27-altered DIPGs.

Clinical Utility of Precision Medicine in Pediatric Oncology: A Systematic Review

PURPOSE

Precision medicine uses advanced molecular techniques to guide the use of targeted therapeutic drugs and is an emerging paradigm in pediatric oncology. Clinical evidence related to the efficacy of many novel targeted drugs, however, is currently very limited given the rarity of pediatric cancer and the lack of published evidence for the use of these drugs in children. This systematic review aimed to evaluate the existing evidence for the feasibility and clinical efficacy of precision medicine in pediatric oncology.

METHODS

A systematic review was conducted using the PubMed, Medline, and Embase databases. Clinical trials and observational studies, which used molecular assays such as whole-exome sequencing to identify molecular targets that guided the allocation of targeted cancer drugs and reported clinical outcomes, were included in this review.

RESULTS

Twenty-one clinical trials and observational studies were identified, collectively enrolling 1,408 pediatric patients across nine countries. Therapeutic targets were found in 647 patients (46.0%); however, only 175 of these patients (27.0%) received a targeted drug. Objective responses were recorded for 73 (41.7%) of these 175 patients, only 5.2% of the total sample. Inconsistent outcome reporting and limited comparison with conventional treatment hindered evaluation of the clinical utility of precision medicine.

CONCLUSION

Precision medicine can feasibly identify molecular targets in a clinical setting. However, the inaccessibility of targeted drugs is a significant barrier, restricting the exploration of its therapeutic potential in pediatric oncology. Future clinical trials should endeavor to link the molecular testing results with access to targeted drugs and standardize outcome reporting to advance understanding of the benefits of this novel paradigm in improving patient outcomes.

Panobinostat penetrates the blood-brain barrier and achieves effective brain concentrations in a murine model

PURPOSE

Panobinostat, an orally bioavailable pan-HDAC inhibitor, has demonstrated potent activity in multiple malignancies, including pediatric brain tumors such as DIPG, with increased activity against H3K27M mutant cell lines. Given limited evidence regarding the CNS penetration of panobinostat, we sought to characterize its BBB penetration in a murine model.

METHODS

Panobinostat 15 mg/kg was administered IV to 12 CD-1 female mice. At specified time points, mice were euthanized, blood samples were collected, and brains were removed. LC-MS was performed to quantify panobinostat concentrations. C_max and AUC were estimated and correlated with previously published pharmacokinetic analyses and reports of IC-50 values in DIPG cell lines.

RESULTS

Mean panobinostat plasma concentrations (ng/mL) were 27.3 ± 2.5 at 1 h, 7.56 ± 1.8 at 2 h, 1.48 ± 0.56 at 4 h, and 2.33 ± 1.18 at 7 h. Mean panobinostat brain concentrations (ng/g) were 60.5 ± 6.1 at 1 h, 42.9 ± 5.4 at 2 h, 33.2 ± 6.1 at 4 h, and 28.1 ± 4.3 at 7 h. Brain-to-plasma ratio at 1 h was 2.22 and the brain to plasma AUC ratio was 2.63. Based on the published human pharmacokinetic data, the anticipated C_max in humans is expected to be significantly higher than the IC-50 identified in DIPG models.

CONCLUSION

It is expected that panobinostat would be effective in CNS tumors where the IC-50 is in the low nanomolar range. Thus, our data demonstrate panobinostat crosses the BBB and achieves concentrations above the IC-50 for DIPG and other brain tumors and should be explored further for clinical efficacy.

Enhanced childhood diseases treatment using computational models: Systematic review of intelligent experiments heading to precision medicine

INTRODUCTION

Precision or personalized Medicine (PM) is used for the prevention and treatment of diseases by considering a huge amount of information about individuals variables. Due to high volume of information, AI-based computational models are required. A large set of studies conducted to examine the PM approach to improve childhood clinical outcomes. Thus, the main goal of this study was to review the application of health information technology and especially artificial intelligence (AI) methods for the treatment of childhood disease using PM.

METHODS

PubMed, Scopus, Web of Science, and EMBASE databases were searched up to December 18, 2019. Articles that focused on informatics applications for childhood disease PM included in this study. Included papers were classified for qualitative analysis and interpreting results. The results were analyzed using Microsoft Excel 2019.

RESULTS

From 341 citations, 62 papers met our inclusion criteria. The number of published papers that used AI methods to apply for PM in childhood diseases increased from 2010 to 2019. Our results showed that most applied methods were related to machine learning discipline. In terms of clinical scope, the largest number of clinical articles are devoted to oncology. Besides, the analysis showed that genomics was the most PM approach used regarding childhood disease.

CONCLUSION

This systematic review examined papers that used AI methods for applying PM approaches in childhood diseases from medical informatics perspectives. Thus, it provided new insight to researchers who are interested in knowing research needs in this field.

Trametinib-based Treatment of Pediatric CNS Tumors: A Single Institutional Experience

MEK inhibitors are an emerging therapy with increasing use in mitogen-activated protein kinase-driven central nervous system (CNS) tumors. There is limited data regarding efficacy and toxicity in pediatric patients. We report our clinical experience with trametinib-based therapy for the treatment of 14 consecutive pediatric patients with recurrent low-grade glioma (N=11) or high-grade CNS tumors (N=3) with MAP kinase pathway mutations. Patients received trametinib as monotherapy (N=9) or in combination (N=5) with another antineoplastic agent. Nine patients (64%) were progression free during treatment. Five patients showed a partial response, while 4 had stable disease. Two patients (14%) progressed on therapy. All partial responses were in patients with low-grade tumors. The remaining 3 patients were not evaluable due to toxicity limiting duration of therapy. Two of 3 patients with low-grade glioma with leptomeningeal dissemination showed radiographic treatment response. Five patients reported improved clinical symptoms while on trametinib. Adverse events on trametinib-based therapy included dermatologic, mouth sores, fever, gastrointestinal, infection, neutropenia, headache, and fatigue, and were more common in patients using combination therapy. Trametinib-based therapy demonstrated signals of efficacy in our single institutional cohort of pediatric patients with mitogen-activated protein kinase-driven CNS tumors. Our observations need to be confirmed in a clinical trial setting.

Clinical Impact of Next-generation Sequencing in Pediatric Neuro-Oncology Patients: A Single-institutional Experience

The implementation of next-generation sequencing (NGS) in pediatric neuro-oncology may impact diagnosis, prognosis, therapeutic strategies, clinical trial enrollment, and germline risk. We retrospectively analyzed 58 neuro-oncology patients (31 boys, 27 girls, average age 7.4 years) who underwent NGS tumor profiling using a single commercially available platform on paraffin-embedded tissue obtained at diagnosis (20 low-grade gliomas, 12 high-grade gliomas, 11 embryonal tumors, four ependymal tumors, three meningeal tumors, and eight other CNS tumors) from May 2014 to December 2016. NGS results were analyzed for actionable mutations, variants of unknown significance and clinical impact. Seventy-four percent of patients (43 of 57) had actionable mutations; 26% had only variants of uncertain significance (VUS). NGS findings impacted treatment decisions in 55% of patients; 24% were given a targeted treatment based on NGS findings. Seven of eight patients with low-grade tumors treated with targeted therapy (everolimus, trametinib, or vemurafenib) experienced partial response or stable disease. All high-grade tumors had progressive disease on targeted therapy. Forty percent of patients had a revision or refinement of their diagnosis, and nine percent of patients were diagnosed with a previously unconfirmed cancer predisposition syndrome. Turnaround time between sample shipment and report generation averaged 13.4 ± 6.4 days. One sample failed due to insufficient DNA quantity. Our experience highlights the feasibility and clinical utility of NGS in the management of pediatric neuro-oncology patients. Future prospective clinical trials using NGS are needed to establish efficacy.

Successful treatment of a TSC2-mutant glioblastoma with everolimus

A 14-year-old boy with familial Li-Fraumeni syndrome presented with diplopia. Brain MRI revealed a right temporoparietal rim-enhancing mass. Following surgical resection and diagnosis of a gigantocellular-type glioblastoma multiforme (GBM), his family wished to avoid cytotoxic chemotherapy given the amplified risk of secondary malignancy. As such, we performed whole exome and transcriptome sequencing, which revealed germline TP53 and somatic TSC2 mutations. On completion of adjuvant radiotherapy, he was started on maintenance therapy with everolimus per recommendations from our multi-institutional brain tumour precision medicine tumour board. He has achieved a complete remission with resolution of visual symptoms and remains on everolimus therapy with concurrent electromagnetic field therapy, now 33 months from diagnosis. Our data highlight the benefit of precision medicine in children with GBM and offer insight into a targetable pathway that may be involved in similar cases.