RESUMEN
Motivation: Spatial transcriptomics enables the analysis of cell crosstalk in healthy and diseased organs by capturing the transcriptomic profiles of millions of cells within their spatial contexts. However, spatial transcriptomics approaches also raise new computational challenges for the multidimensional data analysis associated with spatial coordinates. Results: In this context, we introduce a novel analytical framework called CellsFromSpace based on independent component analysis (ICA), which allows users to analyze various commercially available technologies without relying on a single-cell reference dataset. The ICA approach deployed in CellsFromSpace decomposes spatial transcriptomics data into interpretable components associated with distinct cell types or activities. ICA also enables noise or artifact reduction and subset analysis of cell types of interest through component selection. We demonstrate the flexibility and performance of CellsFromSpace using real-world samples to demonstrate ICA's ability to successfully identify spatially distributed cells as well as rare diffuse cells, and quantitatively deconvolute datasets from the Visium, Slide-seq, MERSCOPE, and CosMX technologies. Comparative analysis with a current alternative reference-free deconvolution tool also highlights CellsFromSpace's speed, scalability and accuracy in processing complex, even multisample datasets. CellsFromSpace also offers a user-friendly graphical interface enabling non-bioinformaticians to annotate and interpret components based on spatial distribution and contributor genes, and perform full downstream analysis. Availability and implementation: CellsFromSpace (CFS) is distributed as an R package available from github at https://github.com/gustaveroussy/CFS along with tutorials, examples, and detailed documentation.
RESUMEN
The potential of immune checkpoint inhibitors (ICI) may be limited in situations where immune cell fitness is impaired. Here, we show that the efficacy of cancer immunotherapies is compromised by the accumulation of senescent cells in mice and in the context of therapy-induced senescence (TIS). Resistance to immunotherapy is associated with a decrease in the accumulation and activation of CD8 T cells within tumors. Elimination of senescent cells restores immune homeostasis within the tumor micro-environment (TME) and increases mice survival in response to immunotherapy. Using single-cell transcriptomic analysis, we observe that the injection of ABT263 (Navitoclax) reverses the exacerbated immunosuppressive profile of myeloid cells in the TME. Elimination of these myeloid cells also restores CD8 T cell proliferation in vitro and abrogates immunotherapy resistance in vivo. Overall, our study suggests that the use of senolytic drugs before ICI may constitute a pharmacological approach to improve the effectiveness of cancer immunotherapies.
