scRNA-seq in medulloblastoma shows cellular heterogeneity and lineage expansion support resistance to SHH inhibitor therapy.
Jennifer Karin OcasioBenjamin R BabcockDaniel MalawskySeth J WeirLipin LooJeremy M SimonMark J ZylkaDuhyeong HwangTaylor DismukeMarina SokolskyElias P RosenRajeev VibhakarJiao ZhangOlivier SaulnierMaria VladoiuIbrahim El-HamamyLincoln D SteinMichael D TaylorKyle S SmithPaul A NorthcottAlejandro ColaneriKirk C WilhelmsenTimothy R GershonPublished in: Nature communications (2019)
Targeting oncogenic pathways holds promise for brain tumor treatment, but inhibition of Sonic Hedgehog (SHH) signaling has failed in SHH-driven medulloblastoma. Cellular diversity within tumors and reduced lineage commitment can undermine targeted therapy by increasing the probability of treatment-resistant populations. Using single-cell RNA-seq and lineage tracing, we analyzed cellular diversity in medulloblastomas in transgenic, medulloblastoma-prone mice, and responses to the SHH-pathway inhibitor vismodegib. In untreated tumors, we find expected stromal cells and tumor-derived cells showing either a spectrum of neural progenitor-differentiation states or glial and stem cell markers. Vismodegib reduces the proliferative population and increases differentiation. However, specific cell types in vismodegib-treated tumors remain proliferative, showing either persistent SHH-pathway activation or stem cell characteristics. Our data show that even in tumors with a single pathway-activating mutation, diverse mechanisms drive tumor growth. This diversity confers early resistance to targeted inhibitor therapy, demonstrating the need to target multiple pathways simultaneously.
Keyphrases
- single cell
- rna seq
- basal cell carcinoma
- stem cells
- high throughput
- induced apoptosis
- big data
- gene expression
- transcription factor
- type diabetes
- machine learning
- cell therapy
- cell proliferation
- electronic health record
- spinal cord
- cell death
- adipose tissue
- endoplasmic reticulum stress
- mesenchymal stem cells
- artificial intelligence
- oxidative stress
- high fat diet induced
- cell fate
- bone marrow
- spinal cord injury
- deep learning