Virtual multi-institutional tumor board: a strategy for personalized diagnoses and management of rare CNS tumors.

PURPOSE: Multidisciplinary tumor boards (MTBs) integrate clinical, molecular, and radiological information and facilitate coordination of neuro-oncology care. During the COVID-19 pandemic, our MTB transitioned to a virtual and multi-institutional format. We hypothesized that this expansion would allow expert review of challenging neuro-oncology cases and contribute to the care of patients with limited access to specialized centers. METHODS: We retrospectively reviewed records from virtual MTBs held between 04/2020-03/2021. Data collected included measures of potential clinical impact, including referrals to observational or therapeutic studies, referrals for specialized neuropathology analysis, and whether molecular findings led to a change in diagnosis and/or guided management suggestions. RESULTS: During 25 meetings, 32 presenters discussed 44 cases. Approximately half (n = 20; 48%) involved a rare central nervous system (CNS) tumor. In 21% (n = 9) the diagnosis was changed or refined based on molecular profiling obtained at the NIH and in 36% (n = 15) molecular findings guided management. Clinical trial suggestions were offered to 31% (n = 13), enrollment in the observational NCI Natural History Study to 21% (n = 9), neuropathology review and molecular testing at the NIH to 17% (n = 7), and all received management suggestions. CONCLUSION: Virtual multi-institutional MTBs enable remote expert review of CNS tumors. We propose them as a strategy to facilitate expert opinions from specialized centers, especially for rare CNS tumors, helping mitigate geographic barriers to patient care and serving as a pre-screening tool for studies. Advanced molecular testing is key to obtaining a precise diagnosis, discovering potentially actionable targets, and guiding management.

MetaWise: Combined Feature Selection and Weighting Method to Link the Serum Metabolome to Treatment Response and Survival in Glioblastoma.

Glioblastoma (GBM) is a highly malignant and devastating brain cancer characterized by its ability to rapidly and aggressively grow, infiltrating brain tissue, with nearly universal recurrence after the standard of care (SOC), which comprises maximal safe resection followed by chemoirradiation (CRT). The metabolic triggers leading to the reprogramming of tumor behavior and resistance are an area increasingly studied in relation to the tumor molecular features associated with outcome. There are currently no metabolomic biomarkers for GBM. Studying the metabolomic alterations in GBM patients undergoing CRT could uncover the biochemical pathways involved in tumor response and resistance, leading to the identification of novel biomarkers and the optimization of the treatment response. The feature selection process identifies key factors to improve the model's accuracy and interpretability. This study utilizes a combined feature selection approach, incorporating both Least Absolute Shrinkage and Selection Operator (LASSO) and Minimum Redundancy-Maximum Relevance (mRMR), alongside a rank-based weighting method (i.e., MetaWise) to link metabolomic biomarkers to CRT and the 12-month and 20-month overall survival (OS) status in patients with GBM. Our method shows promising results, reducing feature dimensionality when employed on serum-based large-scale metabolomic datasets (University of Florida) for all our analyses. The proposed method successfully identified a set of eleven serum biomarkers shared among three datasets. The computational results show that the utilized method achieves 96.711%, 92.093%, and 86.910% accuracy rates with 48, 46, and 33 selected features for the CRT, 12-month, and 20-month OS-based metabolomic datasets, respectively. This discovery has implications for developing personalized treatment plans and improving patient outcomes.

MGMT ProFWise: Unlocking a New Application for Combined Feature Selection and the Rank-Based Weighting Method to Link MGMT Methylation Status to Serum Protein Expression in Patients with Glioblastoma.

Glioblastoma (GBM) is a fatal brain tumor with limited treatment options. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is the central molecular biomarker linked to both the response to temozolomide, the standard chemotherapy drug employed for GBM, and to patient survival. However, MGMT status is captured on tumor tissue which, given the difficulty in acquisition, limits the use of this molecular feature for treatment monitoring. MGMT protein expression levels may offer additional insights into the mechanistic understanding of MGMT but, currently, they correlate poorly to promoter methylation. The difficulty of acquiring tumor tissue for MGMT testing drives the need for non-invasive methods to predict MGMT status. Feature selection aims to identify the most informative features to build accurate and interpretable prediction models. This study explores the new application of a combined feature selection (i.e., LASSO and mRMR) and the rank-based weighting method (i.e., MGMT ProFWise) to non-invasively link MGMT promoter methylation status and serum protein expression in patients with GBM. Our method provides promising results, reducing dimensionality (by more than 95%) when employed on two large-scale proteomic datasets (7k SomaScan® panel and CPTAC) for all our analyses. The computational results indicate that the proposed approach provides 14 shared serum biomarkers that may be helpful for diagnostic, prognostic, and/or predictive operations for GBM-related processes, given further validation.

Glioblastoma cells have increased capacity to repair radiation-induced DNA damage after migration to the olfactory bulb.

BACKGROUND: The invasive nature of GBM combined with the diversity of brain microenvironments creates the potential for a topographic heterogeneity in GBM radioresponse. Investigating the mechanisms responsible for a microenvironment-induced differential GBM response to radiation may provide insights into the molecules and processes mediating GBM radioresistance. METHODS: Using a model system in which human GBM stem-like cells implanted into the right striatum of nude mice migrate throughout the right hemisphere (RH) to the olfactory bulb (OB), the radiation-induced DNA damage response was evaluated in each location according to γH2AX and 53BP1 foci and cell cycle phase distribution as determined by flow cytometry and immunohistochemistry. RNAseq was used to compare transcriptomes of tumor cells growing in the OB and the RH. Protein expression and neuron-tumor interaction were defined by immunohistochemistry and confocal microscopy. RESULTS: After irradiation, there was a more rapid dispersal of γH2AX and 53BP1 foci in the OB versus in the RH, indicative of increased double strand break repair capacity in the OB and consistent with the OB providing a radioprotective niche. With respect to the cell cycle, by 6 h after irradiation there was a significant loss of mitotic tumor cells in both locations suggesting a similar activation of the G2/M checkpoint. However, by 24 h post-irradiation there was an accumulation of G2 phase cells in the OB, which continued out to at least 96 h. Transcriptome analysis showed that tumor cells in the OB had higher expression levels of DNA repair genes involved in non-homologous end joining and genes related to the spindle assembly checkpoint. Tumor cells in the OB were also found to have an increased frequency of soma-soma contact with neurons. CONCLUSION: GBM cells that have migrated to the OB have an increased capacity to repair radiation-induced double strand breaks and altered cell cycle regulation. These results correspond to an upregulation of genes involved in DNA damage repair and cell cycle control. Because the murine OB provides a source of radioresistant tumor cells not evident in other experimental systems, it may serve as a model for investigating the mechanisms mediating GBM radioresistance.

Hierarchical Voting-Based Feature Selection and Ensemble Learning Model Scheme for Glioma Grading with Clinical and Molecular Characteristics.

Determining the aggressiveness of gliomas, termed grading, is a critical step toward treatment optimization to increase the survival rate and decrease treatment toxicity for patients. Streamlined grading using molecular information has the potential to facilitate decision making in the clinic and aid in treatment planning. In recent years, molecular markers have increasingly gained importance in the classification of tumors. In this study, we propose a novel hierarchical voting-based methodology for improving the performance results of the feature selection stage and machine learning models for glioma grading with clinical and molecular predictors. To identify the best scheme for the given soft-voting-based ensemble learning model selections, we utilized publicly available TCGA and CGGA datasets and employed four dimensionality reduction methods to carry out a voting-based ensemble feature selection and five supervised models, with a total of sixteen combination sets. We also compared our proposed feature selection method with the LASSO feature selection method in isolation. The computational results indicate that the proposed method achieves 87.606% and 79.668% accuracy rates on TCGA and CGGA datasets, respectively, outperforming the LASSO feature selection method.

Avelumab, a PD-L1 Inhibitor, in Combination with Hypofractionated Radiotherapy and the Abscopal Effect in Relapsed Refractory Multiple Myeloma.

LESSONS LEARNED: Despite the initial optimism for using immune checkpoint inhibition in the treatment of multiple myeloma, subsequent clinical studies have been disappointing. Preclinical studies have suggested that priming the immune system with various modalities in addition to checkpoint inhibition may overcome the relative T-cell exhaustion or senescence; however, in this small data set, radiotherapy with checkpoint inhibition did not appear to activate the antitumor immune response. BACKGROUND: Extramedullary disease (EMD) is recognized as an aggressive subentity of multiple myeloma (MM) with a need for novel therapeutic approaches. We therefore designed a proof-of-principle pilot study to evaluate the synergy between the combination of the anti-PD-L1, avelumab, and concomitant hypofractionated radiotherapy. METHODS: This was a single-arm phase II Simon two-stage single center study that was prematurely terminated because of the COVID-19 pandemic after enrolling four patients. Key eligibility included patients with relapsed/refractory multiple myeloma (RRMM) who had exhausted or were not candidates for standard therapy and had at least one lesion amenable to radiotherapy. Patients received avelumab until progression or intolerable toxicity and hypofractionated radiotherapy to a focal lesion in cycle 2. Radiotherapy was delayed until cycle 2 to allow the avelumab to reach a study state, given the important observation from previous studies that concomitant therapy is needed for the abscopal effect. RESULTS: At a median potential follow-up of 10.5 months, there were no objective responses, one minimal response, and two stable disease as best response. The median progression-free survival (PFS) was 5.3 months (95% confidence interval [CI]: 2.5-7.1 months), and no deaths occurred. There were no grade ≥3 and five grade 1-2 treatment-related adverse events. CONCLUSION: Avelumab in combination with radiotherapy for patients with RRMM and EMD was associated with very modest systemic clinical benefit; however, patients did benefit as usual from local radiotherapy. Furthermore, the combination was very well tolerated compared with historical RRMM treatment regimens.

Detection of metabolic change in glioblastoma cells after radiotherapy using hyperpolarized 13 C-MRI.

Dynamic nuclear polarization (DNP) of 13 C-labeled substrates enables the use of magnetic resonance imaging (MRI) to monitor specific enzymatic reactions in tumors and offers an opportunity to investigate these differences. In this study, DNP-MRI chemical shift imaging with hyperpolarized [1-13 C] pyruvate was conducted to evaluate the metabolic change in glycolytic profiles after radiation of two glioma stem-like cell-derived gliomas (GBMJ1 and NSC11) and an adherent human glioblastoma cell line (U251) in an orthotopic xenograft mouse model. The DNP-MRI showed an increase in Lac/Pyr at 6 and 16 h after irradiation (18% ± 4% and 14% ± 3%, respectively; mean ± SEM) compared with unirradiated controls in GBMJ1 tumors, whereas no significant change was observed in U251 and NSC11 tumors. Metabolomic analysis likewise showed a significant increase in lactate in GBMJ1 tumors at 16 h. An immunoblot assay showed upregulation of lactate dehydrogenase-A expression in GBMJ1 following radiation exposure, consistent with DNP-MRI and metabolomic analysis. In conclusion, our preclinical study demonstrates that the DNP-MRI technique has the potential to be a powerful diagnostic method with which to evaluate GBM tumor metabolism before and after radiation in the clinical setting.

Synthesis of [1-13 C-5-12 C]-alpha-ketoglutarate enables noninvasive detection of 2-hydroxyglutarate.

Isocitrate dehydrogenase 1 (IDH1) mutations that generate the oncometabolite 2-hydroxyglutarate (2-HG) from α-ketoglutarate (α-KG) have been identified in many types of tumors and are an important prognostic factor in gliomas. 2-HG production can be determined by hyperpolarized carbon-13 magnetic resonance spectroscopy (HP-13 C-MRS) using [1-13 C]-α-KG as a probe, but peak contamination from naturally occurring [5-13 C]-α-KG overlaps with the [1-13 C]-2-HG peak. Via a newly developed oxidative-Stetter reaction, [1-13 C-5-12 C]-α-KG was synthesized. α-KG metabolism was measured via HP-13 C-MRS using [1-13 C-5-12 C]-α-KG as a probe. [1-13 C-5-12 C]-α-KG was synthesized in high yields, and successfully eliminated the signal from C5 of α-KG in the HP-13 C-MRS spectra. In HCT116 IDH1 R132H cells, [1-13 C-5-12 C]-α-KG allowed for unimpeded detection of [1-13 C]-2-HG. 12 C-enrichment represents a novel method to circumvent spectral overlap, and [1-13 C-5-12 C]-α-KG shows promise as a probe to study IDH1 mutant tumors and α-KG metabolism.

Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.

Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at the forefront of large-scale data acquisition and well positioned towards both the production and analysis of large-scale oncologic data with the potential for clinically driven endpoints and advancement of patient outcomes. Neuro-oncology is comprised of malignancies that often carry poor prognosis and significant neurological sequelae. The analysis of radiation therapy mediated treatment and the potential for computationally mediated analyses may lead to more precise therapy by employing large scale data. We analysed the state of the literature pertaining to large scale data, computational analysis, and the advancement of molecular biomarkers in neuro-oncology with emphasis on radiation oncology. We aimed to connect existing and evolving approaches to realistic avenues for clinical implementation focusing on low grade gliomas (LGG), high grade gliomas (HGG), management of the elderly patient with HGG, rare central nervous system tumors, craniospinal irradiation, and re-irradiation to examine how computational analysis and molecular science may synergistically drive advances in personalised radiation therapy (RT) and optimise patient outcomes.

Translation Initiation Machinery as a Tumor Selective Target for Radiosensitization.

Towards improving the efficacy of radiotherapy, one approach is to target the molecules and processes mediating cellular radioresponse. Along these lines, translational control of gene expression has been established as a fundamental component of cellular radioresponse, which suggests that the molecules participating in this process (i.e., the translational machinery) can serve as determinants of radiosensitivity. Moreover, the proteins comprising the translational machinery are often overexpressed in tumor cells suggesting the potential for tumor specific radiosensitization. Studies to date have shown that inhibiting proteins involved in translation initiation, the rate-limiting step in translation, specifically the three members of the eIF4F cap binding complex eIF4E, eIF4G, and eIF4A as well as the cap binding regulatory kinases mTOR and Mnk1/2, results in the radiosensitization of tumor cells. Because ribosomes are required for translation initiation, inhibiting ribosome biogenesis also appears to be a strategy for radiosensitization. In general, the radiosensitization induced by targeting the translation initiation machinery involves inhibition of DNA repair, which appears to be the consequence of a reduced expression of proteins critical to radioresponse. The availability of clinically relevant inhibitors of this component of the translational machinery suggests opportunities to extend this approach to radiosensitization to patient care.

DiscoverSL: an R package for multi-omic data driven prediction of synthetic lethality in cancers.

SUMMARY: Synthetic lethality is a state when simultaneous loss of two genes is lethal to a cancer cell, while the loss of the individual genes is not. We developed an R package DiscoverSL to predict and visualize synthetic lethality in cancers using multi-omic cancer data. Mutation, copy number alteration and gene expression data from The Cancer Genome Atlas project were combined to develop a multi-parametric Random Forest classifier. The effects of selectively targeting the predicted synthetic lethal genes is tested in silico using shRNA and drug screening data from cancer cell line databases. The clinical outcome in patients with mutation in primary gene and over/under-expression in the synthetic lethal gene is evaluated using Kaplan-Meier analysis. The method helps to identify new therapeutic approaches by exploiting the concept of synthetic lethality. AVAILABILITY AND IMPLEMENTATION: DiscoverSL package with user manual and sample workflow is available for download from github url: https://github.com/shaoli86/DiscoverSL/releases/tag/V1.0 under GNU GPL-3. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detection of glioblastoma intratumor heterogeneity in radiosensitivity using patient-derived neurosphere cultures.

PURPOSE: Glioblastoma (GBM) is characterized by extensive clonal diversity suggesting the presence of tumor cells with varying degrees of treatment sensitivity. Radiotherapy is an integral part of glioblastoma treatment. Whether GBMs are comprised of spatially distinct cellular populations with uniform or varying degrees of radiosensitivity has not been established. METHODS: Spatially distinct regions of three GBMs (J3, J7 and J14) were resected and unique cell lines were derived from each region. DNA from cell lines, corresponding tumor fragments, and patient blood was extracted for whole exome sequencing. Variants, clonal composition, and functional implications were compared and analyzed with superFreq and IPA. Limiting dilution assays were performed on cell lines to measure intrinsic radiosensitivity. RESULTS: Based on WES, cell lines generated from different regions of the same tumor were more closely correlated with their tumor of origin than the other GBMs. Variant and clonal composition comparisons showed that cell lines from distinct tumors displayed increasing levels of ITH with J3 and J14 having the lowest and highest, respectively. The radiosensitivities of the cell lines generated from the J3 tumor were similar as were those generated from the J7 tumor. However, the radiosensitivities of the 2 cell lines generated from the J14 tumor (J14T3 and J14T6) were significantly different with J14T6 being more sensitive than J14T3. CONCLUSION: Data suggest a tumor dependent ITH in radiosensitivity. The existence of ITH in radiosensitivity may impact not only the initial therapeutic response but also the effectiveness of retreatment protocols.

The prevalence of altered body image in patients with primary brain tumors: an understudied population.

PURPOSE: Body image (BI) is an important issue for cancer patients, as patients with BI concerns are susceptible to depression, anxiety, difficulty coping, and poor quality of life (QoL). While this concern has been documented in patients with other malignancies, no data exists of this QoL issue in patients with primary brain tumors (PBT). METHODS: A cross-sectional survey of 100 PBT patients was conducted on an IRB approved prospective protocol using structured questionnaires. Participants completed the body image scale (BIS), Appearance Scheme Inventory Revised (ASI-R), MD Anderson Symptom Inventory Brain Tumor (MDASI-BT), and Patient-Reported Outcomes Measurement Information System (PROMIS) Depression, Anxiety, and Psychosocial Impact Positive measures. RESULTS: The prevalence of clinically significant body image dissatisfaction (BIS ≥ 10) was 28% (95% CI 19-37%), median BIS score was 5 (range 0-27). The median ASI-R composite score was 2.9 (range 1.5-4.7). BIS was significantly correlated with the ASI-R (r = 0.53, 95% CI 0.37 to 0.65). The mean PROMIS Depression score was 48.4 (SD = 8.9), PROMIS Anxiety score was 49.4 (SD = 9.9), and PROMIS Psychosocial Illness Impact Positive score was 48.9 (SD = 9.7). BIS was significantly correlated with age, and trended with BMI and sex. The PROMIS Psychosocial Illness Impact Positive and PROMIS Anxiety scores were the most strongly related to BIS. CONCLUSIONS: This study, the first to explore altered body image in PBT patients, revealed clinically significant body image dissatisfaction in nearly 1/3 of patients, similar to other malignancies. These findings underscore the potential contribution of disease and treatment-related body image concerns on psychosocial wellbeing in patients with PBT.

A phase I trial of lenalidomide and radiotherapy in children with diffuse intrinsic pontine gliomas or high-grade gliomas.

PURPOSE: This study was performed to determine the maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D) of the immunomodulatory agent, lenalidomide, when administered daily during 6 weeks of radiation therapy to children with newly diagnosed diffuse intrinsic pontine glioma (DIPG) or high-grade glioma (HGG) PATIENTS & METHODS: Children and young adults < 22 years of age with newly diagnosed disease and no prior chemotherapy or radiation therapy were eligible. Children with HGG were required to have an inoperable or incompletely resected tumor. Eligible patients received standard radiation therapy to a prescription dose of 54-59.4 Gy, with concurrent administration of lenalidomide daily during radiation therapy in a standard 3 + 3 Phase I dose escalation design. Following completion of radiation therapy, patients had a 2-week break followed by maintenance lenalidomide at 116 mg/m2/day × 21 days of a 28-day cycle. RESULTS: Twenty-nine patients (age range 4-19 years) were enrolled; 24 were evaluable for dose finding (DIPG, n = 13; HGG, n = 11). The MTD was not reached at doses of lenalidomide up to 116 mg/m2/day. Exceptional responses were noted in DIPG and malignant glioma (gliomatosis cerebri) notably at higher dose levels and at higher steady state plasma concentrations. The primary toxicity was myelosuppression. CONCLUSION: The RP2D of lenalidomide administered daily during radiation therapy is 116 mg/m2/day. Children with malignant gliomas tolerate much higher doses of lenalidomide during radiation therapy compared to adults. This finding is critical as activity was observed primarily at higher dose levels suggesting a dose response.

Combining precision radiotherapy with molecular targeting and immunomodulatory agents: a guideline by the American Society for Radiation Oncology.

The practice of radiation oncology is primarily based on precise technical delivery of highly conformal, image-guided external beam radiotherapy or brachytherapy. However, systematic research efforts are being made to facilitate individualised radiation dose prescriptions on the basis of gene-expressssion profiles that reflect the radiosensitivity of tumour and normal tissue. This advance in precision radiotherapy should complement those benefits made in precision cancer medicine that use molecularly targeted agents and immunotherapies. The personalisation of cancer therapy, predicated largely on genomic interrogation, is facilitating the selection of therapies that are directed against driver mutations, aberrant cell signalling, tumour microenvironments, and genetic susceptibilities. With the increasing technical power of radiotherapy to safely increase local tumour control for many solid tumours, it is an opportune time to rigorously explore the potential benefits of combining radiotherapy with molecular targeted agents and immunotherapies to increase cancer survival outcomes. This theme provides the basis and foundation for this American Society for Radiation Oncology guideline on combining radiotherapy with molecular targeting and immunotherapy agents.

Differentiating pseudoprogression from true progression: analysis of radiographic, biologic, and clinical clues in GBM.

INTRODUCTION: Pseudoprogression (PsP) is a diagnostic dilemma in glioblastoma (GBM) after chemoradiotherapy (CRT). Magnetic resonance imaging (MRI) features may fail to distinguish PsP from early true progression (eTP), however clinical findings may aid in their distinction. METHODS: Sixty-seven patients received CRT for GBM between 2003 and 2016, and had pre- and post-treatment imaging suitable for retrospective evaluation using RANO criteria. Patients with signs of progression within the first 12-weeks post-radiation (P-12) were selected. Lesions that improved or stabilized were defined as PsP, and lesions that progressed were defined as eTP. RESULTS: The median follow up for all patients was 17.6 months. Signs of progression developed in 35/67 (52.2%) patients within P-12. Of these, 20/35 (57.1%) were subsequently defined as eTP and 15/35 (42.9%) as PsP. MRI demonstrated increased contrast enhancement in 84.2% of eTP and 100% of PsP, and elevated CBV in 73.7% for eTP and 93.3% for PsP. A decrease in FLAIR was not seen in eTP patients, but was seen in 26.7% PsP patients. Patients with eTP were significantly more likely to require increased steroid doses or suffer clinical decline than PsP patients (OR 4.89, 95% CI 1.003-19.27; p = 0.046). KPS declined in 25% with eTP and none of the PsP patients. CONCLUSIONS: MRI imaging did not differentiate eTP from PsP, however, KPS decline or need for increased steroids was significantly more common in eTP versus PsP. Investigation and standardization of clinical assessments in response criteria may help address the diagnostic dilemma of pseudoprogression after frontline treatment for GBM.

Optimizing the Benefit of CNS Radiation Therapy in the Pediatric Population-PART 1: Understanding and Managing Acute and Late Toxicities.

Radiation therapy continues to be a key component in the management of pediatric malignancies. Increasing the likelihood of cure while minimizing late treatment toxicity in these young patients remains the primary goal. Within the realm of central nervous system neoplasms, efforts to further improve the efficacy of radiation therapy continue, while balancing risks of damage to uninvolved tissue. Radiation therapy can result in second malignancies, as well as cerebrovascular, neurotoxic, neurocognitive, endocrine, psychosocial, and quality-of-life effects. In this article we describe these acute and late effects and their implications, and we highlight strategies that have emerged to reduce both the volume of tissue that is irradiated and the radiation dose delivered. The feasibility, efficacy, and risks of these newer approaches to radiation therapy continue to be evaluated and monitored; robust outcome data are needed.

Optimizing the Benefit of CNS Radiation Therapy in the Pediatric Population-PART 2: Novel Methods of Radiation Delivery.

Newer approaches in the field of radiation therapy have raised the bar in the treatment of central nervous system (CNS) malignancies, with recognized advances that have aimed to increase the therapeutic index by improving conformality of the radiation dose to the planned target volume. Beyond these advances, the continued evolution of more effective systems for delivery of radiation to the CNS may offer further benefit not only to adults but also to pediatric patients, a cohort of the population that may be more sensitive to the long-term effects of radiation. This article describes several novel irradiation techniques under investigation that hold promise in the pediatric population. These include newer approaches to intensity-modulated radiation therapy; stereotactic radiosurgery and radiation therapy; particle therapy, most notably proton therapy, which may be of particular benefit in enabling young patients to avoid radiation-related adverse effects; and radioimmunotherapy strategies that spare healthy tissue from radiotoxicity by delivering therapy directly to tumor tissue. Although emerging strategies for the delivery of radiation therapy hold promise for improved outcomes in pediatric patients, there must be rigorous long-term evaluation of consequences associated with the various techniques employed, to weigh risks, benefits, and impact on quality of life.

A prospective study of mediastinal gray-zone lymphoma.

Mediastinal B-cell lymphomas present in the mediastinum and are most frequent in young patients. Nodular sclerosis Hodgkin lymphoma (NSHL) and primary mediastinal B-cell lymphoma (PMBL) are the common types, whereas mediastinal gray-zone lymphoma (MGZL) is extremely rare and has pathological features intermediate between NSHL and PMBL. The indeterminate pathobiology of MGZL has led to uncertainty regarding therapeutic strategy, and its clinical characteristics and treatment have not been characterized. We conducted a prospective study of infusional dose-adjusted etoposide, doxorubicin, and cyclophosphamide with vincristine, prednisone, and rituximab (DA-EPOCH-R) and filgrastim in untreated MGZL. We analyzed biomarkers of outcome and compared their clinical and biological characteristics to PMBL. Twenty-four MGZL patients had a median age of 33 years (range, 14 to 59 years), and 46% had mediastinal masses ≥10 cm. At 59 months median follow-up, the event-free survival and overall survival were 62% and 74%, respectively. The serum absolute lymphocyte count, the presence of tumor-infiltrating dendritic cells, CD15 expression on the malignant cells, and tumor morphology were biomarkers of outcome in MGZL. Compared with PMBL, MGZL patients were more likely to be male, express CD15, have lower expression of CD20, and have a worse outcome. DA-EPOCH-R alone is effective in MGZL. The trial was registered at ClinicalTrials.gov (NCT00001337).

A phase I trial of cabozantinib and gemcitabine in advanced pancreatic cancer.

Background Cabozantinib and gemcitabine improve tumor control in pancreatic ductal adenocarcinoma (PDAC) in preclinical models through c-Met inhibition. We sought to determine the maximum tolerated dose (MTD) of this combination in patients with advanced PDAC. Methods Patients with ≤1 prior treatment and adequate performance status were eligible. Cabozantinib was given orally once daily, beginning day (-)7 and continued with gemcitabine given intravenously on days 1, 8, and 15 every 28 days. Dose level was assigned using Time to Event Continual Reassessment Method (TITE-CRM). Primary endpoint was MTD, defined as the highest dose level at which ≤25 % of patients incurred a dose-limiting toxicity (DLT). Secondary endpoints included response rate, progression-free survival (PFS), overall survival (OS) and urinary biomarker assessment. Results Twelve patients were enrolled and treated with 10 patients evaluable for DLT. The probability of DLT was >25 % for all dose levels tested, and thus an MTD was not determined. DLTs included grade 3 ALT/AST elevations and thrombocytopenia. Three patients had partial responses, but each discontinued therapy due to toxicity. Median PFS and OS were 4.7 (95 % CI: 1.4-9.7) and 10.1 months (95 % CI: 3.6-20.6). Exploratory biomarker analysis showed correlation of c-Met and VEGF levels with response. Conclusions An MTD for the combination was not established. Cabozantinib and gemcitabine appear impractical for further development due to DLT at low doses and continuing toxicities with ongoing therapy. Acknowledging the small sample size, responses were seen suggesting further investigation of c-Met inhibition in PDAC may be warranted.