scRNA-seq in medulloblastoma shows cellular heterogeneity and lineage expansion support resistance to SHH inhibitor therapy

Ocasio, Jennifer K.; Babcock, Benjamin; Malawsky, Daniel; Weir, Seth; Loo, Lipin; Simon, Jeremy M.; Hwang, Duhyeong; Dismuke, Taylor; Sokolsky-Papkov, Marina; Rosen, Elias P.; Vibhakar, Rajeev; Zhang, Jiao; Saulnier, Olivier; Vladoiu, Maria C.; El-Hamamy, Ibrahim; Stein, Lincoln; Taylor, Michael D.; Smith, Kyle; Northcott, Paul A.; Colaneri, Alejandro; Wilhelmsen, Kirk C.; Gershon, Timothy R.

doi:10.1038/s41467-019-13657-6

Cited by 87 publications

(148 citation statements)

References 56 publications

(72 reference statements)

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“…In neurons, STMN2 is involved with neuron development and growth (Hannan et al, 1996), and is expressed primarily in CGN sub-lineage postnatal excitatory cerebellar nuclei neurons, unipolar brush cells (UBCs) and UBC precursors in the developing murine cerebellum (Ocasio et al, 2019a;Vladoiu et al, 2019). In GP4, STMN2 expression was seen in undifferentiated progenitors (Table 1), suggesting that it marks earlier stages of neuron development than GRIA2, consistent with its reported role in developing neurons (Stein et al, 1988).…”

Section: Shh Tumors Contain a Unique Differentiated Subpopulation Thasupporting

confidence: 66%

“…Mice were raised until P15 and then tumors were harvested under general anesthesia. Tumor samples were dissociated using the Papain Dissociation System (Worthington Biochemical) as previous described (Ocasio et al, 2019a). Briefly, tumor samples were incubated in papain at 37°C for 15 min, then triturated and the suspended cells were spun through a density gradient of ovomucoid inhibitor.…”

Section: Methods For Math1-cre/smom2 Shh Gem Tumor Generation and Tumomentioning

confidence: 99%

“…The predominant differentiated GP4 subpopulation, GP4-C1 (33% of neoplastic GP4), was characterized by gene expression similar to GP3-C1, but showed higher expression of GRIA2, a component of glutamatergic lineage neurons. In developing murine cerebellum neurons, GRIA2 was identified as a marker of unipolar brush cells (UBCs) (Vladoiu et al, 2019) although also expressed in Purkinje cells and cerebellar granular neurons (CGNs) (Ocasio et al, 2019a).…”

Section: The Predominant Gp4 Mb Differentiated Subpopulation Is Distimentioning

confidence: 99%

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Neoplastic and immune single cell transcriptomics define subgroup-specific intra-tumoral heterogeneity of childhood medulloblastoma

Riemondy

Venkataraman

Willard

et al. 2020

Preprint

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Medulloblastoma (MB) is a heterogeneous disease in which neoplastic cells and associated immune cells contribute to disease progression. To better understand cellular heterogeneity in MB we profile neoplastic and immune populations in childhood MB samples using single-cell RNA sequencing, immunohistochemistry and deconvolution of transcriptomic data. Neoplastic cells cluster primarily according to individual sample of origin which is in part due to the effect of chromosomal copy number gains and losses. Harmony alignment reveals novel MB subgroup/subtype-associated subpopulations that recapitulate neurodevelopmental processes and are associated with clinical outcomes. We identify discrete photoreceptor-like cells in MB subgroups GP3 and GP4 and nodule-associated neuronally-differentiated cells in subgroup SHH. MB immune infiltrates consist of both developmentally-related neuron-pruning and antigen presenting myeloid cells. We show that this MB cellular diversity is recapitulated in genetically engineered mouse subgroup-specific models of MB. These findings advance our understanding of both the neoplastic and immune landscape of MB.

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Section: Shh Tumors Contain a Unique Differentiated Subpopulation Thasupporting

confidence: 66%

Section: Methods For Math1-cre/smom2 Shh Gem Tumor Generation and Tumomentioning

confidence: 99%

Section: The Predominant Gp4 Mb Differentiated Subpopulation Is Distimentioning

confidence: 99%

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Neoplastic and immune single cell transcriptomics define subgroup-specific intra-tumoral heterogeneity of childhood medulloblastoma

Riemondy

Venkataraman

Willard

et al. 2020

Preprint

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“…A single-cell RNA-seq performed to analyze cellular diversity in MB show that even in tumors with a single pathway-activating mutation, diverse mechanisms drive tumor growth. This diversity confers early resistance to vismodegib, demonstrating the need to target multiple pathways simultaneously [210].…”

Section: Expert Opinionmentioning

confidence: 99%

The SHH/GLI signaling pathway: a therapeutic target for medulloblastoma

Severini

Ghirga

Bufalieri

et al. 2020

Expert Opinion on Therapeutic Targets

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Introduction: Medulloblastoma (MB) is a heterogeneous tumor of the cerebellum that is divided into four main subgroups with distinct molecular and clinical features. Sonic Hedgehog MB (SHH-MB) is the most genetically understood and occurs predominantly in childhood. Current therapies consist of aggressive and non-targeted multimodal approaches that are often ineffective and cause long-term complications. These problems intensify the need to develop molecularly targeted therapies to improve outcome and reduce treatment-related morbidities. In this scenario, Hedgehog (HH) signaling, a developmental pathway whose deregulation is involved in the pathogenesis of several malignancies, has emerged as an attractive druggable pathway for SHH-MB therapy. Areas covered: This review provides an overview of the advancements in the HH antagonist research field. We place an emphasis on Smoothened (SMO) and glioma-associated oncogene homolog (GLI) inhibitors and immunotherapy approaches that are validated in preclinical SHH-MB models and that have therapeutic potential for MB patients. Literature from Pubmed and data reported on ClinicalTrial. gov up to August 2020 were considered. Expert opinion: Extensive-omics analysis has enhanced our knowledge and has transformed the way that MB is studied and managed. The clinical use of SMO antagonists has yet to be determined, however, future GLI inhibitors and multitargeting approaches are promising.

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“…The focus of our analysis is on evaluating if the proposed BC-t-SNE method provides a robust data representation, which is successful at removing batch effects without affecting biological information of interest; see Ocasio et al (2019) for an analysis involving cell-annotations on the same dataset.…”

Section: Sil Kbet Lisi Pcregmentioning

confidence: 99%

Projected t-SNE for batch correction

et al. 2020

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Motivation: Low-dimensional representations of high-dimensional data are routinely employed in biomedical research to visualize, interpret and communicate results from different pipelines. In this article, we propose a novel procedure to directly estimate t-SNE embeddings that are not driven by batch effects. Without correction, interesting structure in the data can be obscured by batch effects.The proposed algorithm can therefore significantly aid visualization of high-dimensional data.Results: The proposed methods are based on linear algebra and constrained optimization, leading to efficient algorithms and fast computation in many high-dimensional settings. Results on artificial single-cell transcription profiling data show that the proposed procedure successfully removes multiple batch effects from t-SNE embeddings, while retaining fundamental information on cell types. When applied to single-cell gene expression data to investigate mouse medulloblastoma, the proposed method successfully removes batches related with mice identifiers and the date of the experiment, while preserving clusters of oligodendrocytes, astrocytes, and endothelial cells and microglia, which are expected to lie in the stroma within or adjacent to the tumors.Availability: Source code implementing the proposed approach in R and Julia is available at the link https://github.com/emanuelealiverti/BC tSNE, including a tutorial to reproduce the simulation studies.

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scRNA-seq in medulloblastoma shows cellular heterogeneity and lineage expansion support resistance to SHH inhibitor therapy

Cited by 87 publications

References 56 publications

Neoplastic and immune single cell transcriptomics define subgroup-specific intra-tumoral heterogeneity of childhood medulloblastoma

Neoplastic and immune single cell transcriptomics define subgroup-specific intra-tumoral heterogeneity of childhood medulloblastoma

The SHH/GLI signaling pathway: a therapeutic target for medulloblastoma

Projected t-SNE for batch correction

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