Faculty Bibliography

Intraoperative diagnosis is essential for providing safe and effective care during cancer surgery¹. The existing workflow for intraoperative diagnosis based on hematoxylin and eosin staining of processed tissue is time, resource and labor intensive^2,3. Moreover, interpretation of intraoperative histologic images is dependent on a contracting, unevenly distributed, pathology workforce⁴. In the present study, we report a parallel workflow that combines stimulated Raman histology (SRH)^5-7, a label-free optical imaging method and deep convolutional neural networks (CNNs) to predict diagnosis at the bedside in near real-time in an automated fashion. Specifically, our CNNs, trained on over 2.5 million SRH images, predict brain tumor diagnosis in the operating room in under 150 s, an order of magnitude faster than conventional techniques (for example, 20-30 min)². In a multicenter, prospective clinical trial (n = 278), we demonstrated that CNN-based diagnosis of SRH images was noninferior to pathologist-based interpretation of conventional histologic images (overall accuracy, 94.6% versus 93.9%). Our CNNs learned a hierarchy of recognizable histologic feature representations to classify the major histopathologic classes of brain tumors. In addition, we implemented a semantic segmentation method to identify tumor-infiltrated diagnostic regions within SRH images. These results demonstrate how intraoperative cancer diagnosis can be streamlined, creating a complementary pathway for tissue diagnosis that is independent of a traditional pathology laboratory.

Tumors of the pineal region comprise several different entities with distinct clinical and histopathological features. Whereas some entities predominantly affect adults, pineoblastoma (PB) constitutes a highly aggressive malignancy of childhood with a poor outcome. PBs mainly arise sporadically, but may also occur in the context of cancer predisposition syndromes including DICER1 and RB1 germline mutation. With this study, we investigate clinico-pathological subgroups of pineal tumors and further characterize their biological features. We performed genome-wide DNA methylation analysis in 195 tumors of the pineal region and 20 normal pineal gland controls. Copy-number profiles were obtained from DNA methylation data; gene panel sequencing was added for 93 tumors and analysis was further complemented by miRNA sequencing for 22 tumor samples. Unsupervised clustering based on DNA methylation profiling separated known subgroups, like pineocytoma, pineal parenchymal tumor of intermediate differentiation, papillary tumor of the pineal region and PB, and further distinct subtypes within these groups, including three subtypes within the core PB subgroup. The novel molecular subgroup Pin-RB includes cases of trilateral retinoblastoma as well as sporadic pineal tumors with RB1 alterations, and displays similarities with retinoblastoma. Distinct clinical associations discriminate the second novel molecular subgroup PB-MYC from other PB cases. Alterations within the miRNA processing pathway (affecting DROSHA, DGCR8 or DICER1) are found in about two thirds of cases in the three core PB subtypes. Methylation profiling revealed biologically distinct groups of pineal tumors with specific clinical and molecular features. Our findings provide a foundation for further clinical as well as molecular and functional characterization of PB and other pineal tumors, including the role of miRNA processing defects in oncogenesis.

Molecular studies have identified distinct genomic drivers providing insights in biology of brain tumors. Advances in genetic and epigenetic analysis, as well as development of mutation-specific antibodies enable more accurate classification of histologically indistinguishable tumors. Compared with histopathologic grading, molecular biomarkers are also superior in predicting natural behavior of tumors and therapeutic response. Diffuse gliomas can be separated in astrocytoma and oligodendroglioma based on IDH1/2, ATRX, and TP53 mutational status. Pediatric gliomas are molecularly distinct from adult tumors and molecular drivers include histone H3 genes and fusions involving the MAPK pathway. Using genetic and epigenetic profiling, ependymal tumors, medulloblastomas, and atypical teratoid/rhabdoid tumors can be separated in biologically and clinically distinct entities. Identification of novel gene fusions and matched DNA methylation signatures enable accurate diagnosis of primitive neuroectodermal tumors, which were previously misdiagnosed. Genomic classification of central nervous system tumors is being readily translated into the clinical practice and will enable molecularly based patient management and clinical trials.

PURPOSE/OBJECTIVE:Molecular subgroups of pediatric brain tumors associated with divergent biological, clinical, and prognostic features have been identified. However, data regarding the impact of subgroup affiliation on the outcome of children with malignant brain tumors treated with radiation-sparing protocol is limited. We report long-term clinical outcomes and the molecular subgroups of malignant brain tumors in young children whose first-line treatment was high-dose chemotherapy without irradiation. METHODS:Tumor subclassification was performed using the Illumina HumanMethylation450 BeadChip (450k) genome-wide methylation array profiling platform. Clinical information was obtained from chart review. RESULTS:Methylation array profiling yielded information on molecular subgroups in 22 children. Median age at surgery was 26 months (range 1-119 months). Among medulloblastomas (MB), all 6 children in the infant sonic hedgehog (SHH) subgroup were long-term survivors, whereas all 4 children in subgroup 3 MB died. There was one long-term survivor in subgroup 4 MB. One out of five children with ependymoma was a long-term survivor (RELPOS). Both children with primitive neuroectodermal tumors died. One child with ATRT TYR and one child with choroid plexus carcinoma were long-term survivors. CONCLUSIONS:The efficacy of high-dose chemotherapy radiation-sparing treatment appears to be confined to favorable molecular subgroups of pediatric brain tumors, such as infant SHH MB. Identification of molecular subgroups that benefit from radiation-sparing therapy will aid in the design of prospective, "precision medicine"-driven clinical trials.

Congenital tumors account for 2% to 4% of all pediatric central nervous system tumors. Glioblastoma multiforme (GBM) represents a small subset of these tumors. Despite harboring histologic features similar to older patients, infants with GBM exhibit improved survival and respond more favorably to surgery and chemotherapy. To highlight this tumor's unique behavior, we report the case of a survivor of infantile GBM who developed a recurrent tumor in the surgical bed 6 months after diagnosis. The tumor was ultimately resected and was a ganglioglioma. This case shows both a favorable clinical outcome to an infantile GBM and this tumor's natural history.