Cell line drug screening datasets can be utilized for a range of different drug discovery applications from drug biomarker discovery to building translational models of drug response. Previously, we described three separate methodologies to (1) correct for general levels of drug sensitivity to enable drug-specific biomarker discovery, (2) predict clinical drug response in patients and (3) associate these predictions with clinical features to perform in vivo drug biomarker discovery. Here, we unite and update these methodologies into one R package (oncoPredict) to facilitate the development and adoption of these tools. This new OncoPredict R package can be applied to various in vitro and in vivo contexts for drug and biomarker discovery.

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Therapy for pediatric central nervous system (CNS) malignancies can be toxic, and outcomes are suboptimal. Immunotherapy holds promise as a therapeutic avenue, but one of the challenges in its application is the poorly understood microenvironment of pediatric CNS tumors. The Children’s Brain Tumor Network released the Pediatric Brain Tumor Atlas, containing the expression profile of nearly 700 primary CNS tumors. To study the immune microenvironment, a classification from The Cancer Genome Atlas project is applied. High-grade lesions are predominantly lymphocyte deplete (C4, 80%) or immunologically quiet (C5, 7.6%). Low-grade lesions are more mixed with 43% C4, 26% C5, and a higher proportion of inflammatory subtype (C3, 28%). For survival parameters, immune subtype and tumor grade are associated. Using a multivariate cox regression model, the hazard ratio is 2.2 (0.86 – 5.4, p = 0.102) and 3.6 (1.2 – 10.9, p = 0.02) for C4 and C5, respectively. Deconvolution of immune cell gene signatures provides insight into the phenotype of lymphocyte infiltrate, which averages 8.6% (IQR 5.4% – 9.8%) across all samples. For high-grade samples, greater than median expression of T cell-, monocyte-, macrophage-, and B cell-gene signatures are each associated with decreased survival (p < 0.05). Microglia gene signatures have decreased relative expression in high-grade samples compared to low-grade samples (p < 0.001). It is hypothesized that the expression of inhibitory immunomodulators contributes to a pro-tumorigenic microenvironment and represent potential therapeutic targets. In the absence of normal samples in the data set, differential gene expression experiments between disease states can reveal upregulated immunomodulators. Focusing on diffuse midline glioma, immunologic pathways are downregulated. Furthermore, 9 inhibitory immunomodulators, including KDM1A, EZH2, CD276, and VTCN1, are significantly expressed relative to midline low-grade glioma with equivalent immune subtype. Overall, our analysis contributes to the understanding of the immune microenvironment and mechanisms of immune escape for pediatric CNS malignancies.

Therapy for pediatric central nervous system (CNS) malignancies can be toxic, and outcomes are suboptimal. Immunotherapy holds promise as a therapeutic avenue, but the poorly understood microenvironment limits its application. The Children’s Brain Tumor Network (CBTN) released the Pediatric Brain Tumor Atlas, containing expression profiles of nearly 700 primary CNS tumors. To study the immune microenvironment, a classification from The Cancer Genome Atlas project is applied. High-grade lesions are predominantly lymphocyte deplete (C4, 81%) or immunologically quiet (C5, 11%). Low-grade lesions are more mixed with 46% C4, 21% C5, and a higher proportion of inflammatory subtype (C3, 31%). For survival parameters, adjusting for tumor grade and extent of resection, the hazard ratio is 2.2 (0.78 – 6.3), p = 0.13) and 2.4 (0.6 – 10.0, p = 0.24) for C4 and C5, respectively. With no events among low-grade tumors, progression-free survival will be another useful metric and released by CBTN in April. Deconvolution of immune cell gene signatures among C4 samples reveals decreased abundance of T cells (OR 0.26, 0.1 – 0.5) yet increasing T-cell abundance is associated with decreased survival time in high-grade samples (HR 3.7, 1.4 – 10.1). Additionally, there are increased macrophage and decreased microglia signatures among high-grade samples and the C4 and C5 subtypes. It is hypothesized that expression of inhibitory immunomodulators contributes to a pro-tumorigenic microenvironment and represent potential therapeutic targets. In lieu of normal tissue in the data set, differential gene expression experiments between disease states reveals upregulated immunomodulators. Conventional immunomodulators, e.g. PDL1 and CTLA4, are expressed in low-grade samples with C3 subtype, which is abundant in craniopharyngioma. Alternative inhibitory immunomodulators, e.g. KDM1A, EZH2, CD276, are significantly expressed in high-grade samples including diffuse midline glioma. Overall, our analysis contributes to the understanding of the immune microenvironment and identifies potential mechanisms of immune escape among pediatric CNS tumors.