Review of molecular classification and treatment implications of pediatric brain tumors.

PURPOSE OF REVIEW: Brain tumors are the most common solid tumors and leading cause of cancer-related death in children. The advent of large-scale genomics has resulted in a plethora of profiling studies that have mapped the genetic and epigenetic landscapes of pediatric brain tumors, ringing in a new era of precision diagnostics and targeted therapies. In this review, we highlight the most recent findings, focusing on studies published after 2015, and discuss how new evidence is changing the care of children with brain tumors. RECENT FINDINGS: Genome-wide and epigenome-wide profiling data have revealed distinct tumor entities within, virtually, all pediatric brain tumor groups including medulloblastoma; ependymoma; high-grade and low-grade gliomas; atypical teratoid/rhabdoid tumors; and other embryonal tumors, previously called CNS primitive neuroectodermal tumors. Whenever integrated with clinical information, many molecular alterations emerge as powerful prognostic markers and should thus be used to stratify patients and tailor therapies. SUMMARY: Optimal integration of this newly emerging knowledge in a timely and meaningful way into clinical care is a remarkable task and a matter of active debate. The historical morphology-based classification of tumors is being replaced by a genetic-based classification, and the first generation of molecularly informed clinical trials is underway.

New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs.

Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein, we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs, we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated "CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)," "CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)," "CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)," and "CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)," will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors.

Generating prior probabilities for classifiers of brain tumours using belief networks.

BACKGROUND: Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. METHODS: The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. RESULTS: Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET), germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. CONCLUSION: Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.

Endolymphatic sac tumours.

This review article surveys clinical and pathological literature on endolymphatic sac tumours (ELST) and summarizes characteristics that describe the entity. ELST are rare neuroectodermal neoplasms in the petrous bone, originating from inner ear structures. They can be encountered sporadically or in von Hippel-Lindau disease. The most prominent symptom is sensorineural deafness. Historically, nomenclature of invasive adenoid tumours in the petrous bone has been divergent, the term papillary adenocarcinoma used most frequently. Histologically, they have a follicular or papillary and adenoid pattern that can be easily confused with various other neoplastic conditions including metastatic carcinoma. It remains to be verified whether similar tumours (papillary adenocarcinomas) can originate from the middle ear. Middle ear adenomas have a similar appearance but probably originate from neural crest cells in the middle ear. ELST can express a variety of epitopes (including cytokeratin and neuroectodermal markers) which can be detected immunohistochemically. In cases in von Hippel-Lindau disease the cerebello-pontine angle should be included in routine radiological examinations to detect ELST before the tumours lead to deafness. In apparently sporadic cases of ELST, genetic testing for von Hippel-Lindau disease should be considered. Correct distinction of ELST from metastatic carcinoma prevents futile searches for unknown primary tumours.

Pediatric brain tumors: diagnosis and management.

Pediatric brain tumors are the most common solid tumor and the second most common neoplasm in childhood. Confirmation of diagnosis is made by visualization of the tumor on a computed tomographic or magnetic resonance imaging scan. Treatment includes surgery followed by observation or chemotherapy and/or radiation therapy, depending on the amount of tumor removed and its histological characteristics. Recent advances in neuroradiology, neurosurgical techniques, and neuro-oncology have begun to impact the length and quality of survival of children diagnosed with brain tumors. A multidisciplinary approach in the treatment of these children is necessary with the nurses and/or nurse practitioners as the consistent members of the team often coordinating the care.

A monoclonal antibody to a cytoskeletal protein selectively recognizing malignant neuroectodermal tumors.

Fusion of myeloma (P3X63-Ag 8.653) cells with spleen cells from BALB/c mice immunized with human neuroblastoma (SK-N-SH) cells yielded a hybridoma clone, referred to as 3XB7, with a unique pattern of reactivity to malignant neuroectodermal tumors except gliomas of low-grade malignancy. Indirect immunofluorescence staining under different conditions and Western blot analysis indicate that the 3XB7 MAb recognizes an intracellular cytoskeletal protein of M(r) 52K. Immunohistochemical studies with cryostat and paraffin-embedded sections from tumor biopsies revealed that the 3XB7 MAb specifically recognizes malignant neuroectodermal tumors and reacts negatively with other epithelial and mesenchymal tumors, e.g., carcinomas, lymphomas, and sarcomas as well as with normal adult and fetal brain tissues. Negative reaction was also observed with other small round cell tumors of childhood. Thus the 3XB7 antigen can be used for diagnosis of all stages of neuroblastomas, and its specific expression in gliomas with high-grade malignancy (grades III and IV) confer on it additional prognostic value.

Negative 123-meta-iodobenzyl-guanidine imaging in Ewing's sarcoma of bone.

The role of radiolabeled meta-iodobenzyl-guanidine (mIBG) is established in the detection and the staging of neuroblastoma. We designed a study of mIBG scanning for patients with Ewing's sarcoma, a tumor for which a neuroectodermic origin has been proposed. We explored 15 children with round cell sarcoma of bone by a whole body scan carried out 24 hours after injection of 123-I mIBG. No patient demonstrated significant uptake either at the site of the primary or at the sites of metastases. These results suggest that despite its neural histogenesis Ewing's sarcoma is a member of the nonneuroblastoma neural crest tumors, which does not produce or store adrenergic metabolites.