Molecular biomarkers provide both diagnostic and prognostic results for patients with diffuse glioma, the most common primary brain tumor in adults. Here, we used a long-read nanopore-based sequencing technique to simultaneously assess IDH mutation status and MGMT methylation level in 4 human cell lines and 8 fresh human brain tumor biopsies. Currently, these biomarkers are assayed separately, and results can take days to weeks. We demonstrated the use of nanopore Cas9-targeted sequencing (nCATS) to identify IDH1 and IDH2 mutations within 36 h and compared this approach against currently used clinical methods. nCATS was also able to simultaneously provide high-resolution evaluation of MGMT methylation levels not only at the promoter region, as with currently used methods, but also at CpGs across the proximal promoter region, the entirety of exon 1, and a portion of intron 1. We compared the methylation levels of all CpGs to MGMT expression in all cell lines and tumors and observed a positive correlation between intron 1 methylation and MGMT expression. Finally, we identified single nucleotide variants in 3 target loci. This pilot study demonstrates the feasibility of using nCATS as a clinical tool for cancer precision medicine.

Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30–50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.

Neuro-oncology biobanks are critical for the implementation of a precision medicine program. In this perspective, we review our first year experience of a brain tumor biobank with integrated next generation sequencing. From our experience, we describe the critical role of the neurosurgeon in diagnosis, research, and precision medicine efforts. In the first year of implementation of the biobank, 117 patients (Female: 62; Male: 55) had 125 brain tumor surgeries. 75% of patients had tumors biobanked, and 16% were of minority race/ethnicity. Tumors biobanked were as follows: diffuse gliomas (45%), brain metastases (29%), meningioma (21%), and other (5%). Among biobanked patients, 100% also had next generation sequencing. Eleven patients qualified for targeted therapy based on identification of actionable gene mutations. One patient with a hereditary cancer predisposition syndrome was also identified. An iterative quality improvement process was implemented to streamline the workflow between the operating room, pathology, and the research laboratory. Dedicated tumor bank personnel in the department of neurosurgery greatly improved standard operating procedure. Intraoperative selection and processing of tumor tissue by the neurosurgeon was integral to increasing success with cell culture assays. Currently, our institutional protocol integrates standard histopathological diagnosis, next generation sequencing, and functional assays on surgical specimens to develop precision medicine protocols for our patients. This perspective reviews the critical role of neurosurgeons in brain tumor biobank implementation and success as well as future directions for enhancing precision medicine efforts.

Glioblastoma (GBM) is highly resistant to treatment and invasion into the surrounding brain is a cancer hallmark that leads to recurrence despite surgical resection. With the emergence of precision medicine, patient-derived 3D systems are considered potentially robust GBM preclinical models. In this study, we screened a library of 22 anti-invasive compounds (i.e., NF-kB, GSK-3-B, COX-2, and tubulin inhibitors) using glioblastoma U-251 MG cell spheroids. We evaluated toxicity and invasion inhibition using a 3D Matrigel invasion assay. We next selected three compounds that inhibited invasion and screened them in patient-derived glioblastoma organoids (GBOs). We developed a platform using available macros for FIJI/ImageJ to quantify invasion from the outer margin of organoids. Our data demonstrated that a high-throughput invasion screening can be done using both an established cell line and patient-derived 3D model systems. Tubulin inhibitor compounds had the best efficacy with U-251 MG cells, however, in ex vivo patient organoids the results were highly variable. Our results indicate that the efficacy of compounds is highly related to patient intra and inter-tumor heterogeneity. These results indicate that such models can be used to evaluate personal oncology therapeutic strategies.

Brain metastases (BM) are the most common brain tumors in adults occurring in up to 40% of all cancer patients. Multi-omics approaches allow for understanding molecular mechanisms and identification of markers with prognostic significance. In this study, we profile 130 BM using genomics and transcriptomics and correlate molecular characteristics to clinical parameters. The most common tumor origins for BM were lung (40%) followed by melanoma (21%) and breast (15%). Melanoma and lung BMs contained more deleterious mutations than other subtypes (p < 0.001). Mutational signatures suggested that the bulk of the mutations were gained before metastasis. A novel copy number event centered around the MCL1 gene was found in 75% of all samples, suggesting a broader role in promoting metastasis. Unsupervised hierarchical cluster analysis of transcriptional signatures available in 65 samples based on the hallmarks of cancer revealed four distinct clusters. Melanoma samples formed a distinctive cluster in comparison to other BM subtypes. Characteristics of molecular profiles did not correlate with survival. However, patients with self-identified black race or those who did not receive radiation correlated with poor survival. These data identify potential new drivers of brain metastatic progression. Our data also suggest further investigation of sociodemographic and clinical features is needed in BM cohorts.

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OBJECTIVES/GOALS: MGMT methylation status is used to predict the response to TMZ. However, a subpopulation of patients lacking MGMT methylation still respond to TMZ. We applied omics approaches and functional studies to a cohort of GBM patients to identify novel markers that may more accurately predict TMZ response. METHODS/STUDY POPULATION: We applied a combination of omics approaches and functional studies to a cohort of GBM patients to search for novel markers that would predict the response to TMZ treatment more accurately than traditional markers. Using a set of 47 primary and secondary GBM tumor samples, we employed comparative transcriptomics, whole exome sequencing, data independent acquisition (DIA) proteomics, and phosphoproteomics to look for DNA mutations and changes in gene expression and/or protein expression that correlated to response or non-response to TMZ. Subsequently, we performed functional studies and analyzed patient treatment data to validate our results. RESULTS/ANTICIPATED RESULTS: This study is in early stage, but we anticipate that our combination of methods may allow us to identify and validate at least one novel biomarker for TMZ response in patient GBM. For example, comparative transcriptomics or phosphoproteomics may identify a previously unrecognized gene or protein over/under-expression in a subset of patients. In this case we will validate findings using western blotting, IHC staining, and through siRNA of target gene/protein on patient derived GBM cells to examine if removal of this marker leads to TMZ sensitivity. We will further confirm prediction of marker correlation through comparison with matched patient treatment data. DISCUSSION/SIGNIFICANCE: The identification of improved biomarkers to predict response to TMZ treatment is a discovery that could rapidly become standard of care for GBM patients. It would ensure that all responders receive TMZ and avoid exposing nonresponders unnecessarily to TMZ and its potential side effects.

OBJECTIVES/GOALS: A functional precision medicine platform to identify therapeutic targets for a glioblastoma patient with Li Fraumeni syndrome was performed. Comparative transcriptomics identified druggable targets and patient derived organoids and a 3D-PREDICT drug screening assay was used to validate the pipeline and identify further therapeutic targets. METHODS/STUDY POPULATION: A comparative transcriptomics pipeline was used to identify druggable genes that are uniquely overexpressed in our patient of interest relative to a cancer compendium of 12,747 tumor RNA sequencing datasets including 200 GBMs. Mini-ring patient derived organoid-based drug viability assays were performed to validate the comparative transcriptomics data. Additionally, a spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. RESULTS/ANTICIPATED RESULTS: Using comparative transcriptomics STAT1 and STAT2 were found to be significantly overexpressed in our patient, indicating ruxolitinib, a Janus kinase 1 and 2 inhibitor, as a potential therapy. Druggable pathways predicted using comparative transcriptomics corresponded with ruxolitinib sensitivity in a panel of patient derived organoids screened with this compound. Cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. Additionally, 3D-PREDICT screening identified the mTOR inhibitor everolimus as a potential candidate. These two targeted therapies were selected for our patient and resulted in radiographic disease stability. DISCUSSION/SIGNIFICANCE: This research illustrates the use of comparative transcriptomics to identify druggable pathways irrespective of actionable DNA mutations present. Our results are promising and serve to highlight the importance of functional precision medicine in tailoring treatment regimes to specific patients.