Internship Presentations

Integration of Single Cell RNA-seq and Spatial Transcriptomics in Glioblastoma

Rishika Chowdary

Mentor: Dr. Nagi Ayad, Department of Oncology, Georgetown University Medical Center

Date/Time: August 22nd, 2023 at 1pm.

Abstract: The most common and aggressive primary brain tumor is glioblastoma (GBM). As the standard of treatment for GBM results in nearly universal recurrence, there is a strong need to develop new strategies to fight this cancer [1]. However, GBM’s intra and inter tumor heterogeneity wherein patient tumors differ drastically from one another, but the cells within them also vary dramatically hinders the ability to identify new effective treatments. 

GBM cells have been characterized to exist within 4 transcriptional states, representative of typical neurodevelopmental cell types including astrocyte (AC)-like, neural progenitor cell (NPC)-like, oligodendrocyte progenitor cell (OPC)-like, and mesenchymal (MES)-like states. These cell states co-exist in single patient tumors, and are affected by their spatiotemporal location and their interactions with each other and the tumor microenvironment [2]. Based on this, we hypothesized that using spatially resolved transcriptomic data of GBM tumors will help us in understanding individual cells, their cell states and how they interact in-situ, in order to inform the possible cell types that are responsive to a particular therapy. The Ayad laboratory has investigated Casein Kinase 2 as a potential druggable target in GBM. Casein Kinase 2 (CK2; CSNK2A1; CSNK2A2; CSNK2B gene) is a serine-threonine heteromeric kinase, which often plays an active role in many cancers by controlling various signaling pathways. Several clinical trials and studies in mouse models demonstrate that CK2 inhibition is needed in tumor cells as they use CK2 for survival [3]. Thus we aimed to see if CK2 inhibitors were spatially selective against certain spacial niches in GBM. The Ayad lab has previously shown that many kinase inhibitors are selective for specific GBM cell transcriptional states using single-cell RNA sequencing (scRNAseq) (Suter et. al, 2023, in revision), yet this specificity has not yet been shown at spatial resolution. To assess this, We downloaded 10X visium short-read spatial transcriptomic data as published in Ren et. al. (Nature Communications, 2023) [4],where they collected tumors from five GBM patients, five diffuse midline glioma patients, and one peritumor sample. To prepare the data for analysis of a CK2 inhibitor response signature, we first created a pipeline utilizing Seurat’s [5] anchor based integration to batch correct and normalize across all 5 of the GBM samples. This batch-corrected data was used to identify distinct clusters of spots representing unique spatiotemporal niches, which we characterized using enrichment analyses. Importantly, conserved enrichment of E2F targets or Epithelial-to-Mesenchymal transition (EMT) targets were found in distinct niches of multiple patient samples. E2F target pathways include the p53 gene (TP53), which is important since CK2 regulates p53 in glioma cells [6]. Further, CK2 is involved in EMT to mediate migration and invasion [7]. Interestingly, we observe enrichment of Notch signaling in cluster 9 suggestive of key roles of CK2 signaling within that niche [8]. These studies set the groundwork for spatial pharmacotranscriptomics analysis in GBM, to identify selectivity of drugs for specific tumor tissue niches.


1. Ostrom, Q. T. (2018). CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2011–2015. doi:10.1093/neuonc/noy131 

2. Puchalski, R. B., Shah, N., Miller, J., Dalley, R., Nomura, S. R., Yoon, J. G., Smith, K. A., Lankerovich, M., Bertagnolli, D., Bickley, K., Boe, A. F., Brouner, K., Butler, S., Caldejon, S., Chapin, M., Datta, S., Dee, N., Desta, T., Dolbeare, T., Dotson, N., … Foltz, G. D. (2018). An anatomic transcriptional atlas of human glioblastoma. Science (New York, N.Y.), 360(6389), 660–663. doi:10.1126/science.aaf2666 

3. Borgo, C. (2021). Protein kinase CK2: A potential therapeutic target for diverse human diseases. Signal Transduction and Targeted Therapy. doi:10.1038/s41392-021-00567-7

4. Ren, Y., Huang, Z., Zhou, L. et al. Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas. Nat Commun 14, 1028 (2023). doi:10.1038/s41467-023-36707-6 

5. Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W. M., 3rd, Zheng, S., Butler, A., Lee, M. J., Wilk, A. J., Darby, C., Zager, M., Hoffman, P., Stoeckius, M., Papalexi, E., Mimitou, E. P., Jain, J., Srivastava, A., Stuart, T., Fleming, L. M., Yeung, B., Rogers, A. J., … Satija, R. (2021). Integrated analysis of multimodal single-cell data. Cell, 184(13), 3573–3587.e29. doi:10.1016/j.cell.2021.04.048 

6. Dixit, D., Sharma, V., Ghosh, S. et al. Inhibition of Casein kinase-2 induces p53-dependent cell cycle arrest and sensitizes glioblastoma cells to tumor necrosis factor (TNFα)-induced apoptosis through SIRT1 inhibition. Cell Death Dis 3, e271 (2012). doi:10.1038/cddis.2012.10 

7. Kim, J., & Hwan Kim, S. (2013). CK2 inhibitor CX-4945 blocks TGF-β1-induced epithelial-to-mesenchymal transition in A549 human lung adenocarcinoma cells. PloS one, 8(9), e74342. doi:10.1371/journal.pone.0074342 

8.Zhang, S., Long, H., Yang, Y. L., Wang, Y., Hsieh, D., Li, W., Au, A., Stoppler, H. J., Xu, Z., Jablons, D. M., & You, L. (2013). Inhibition of CK2α down-regulates Notch1 signaling in lung cancer cells. Journal of cellular and molecular medicine, 17(7), 854–862. doi:10.1111/jcmm.12068
Summer 2023