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Supporting data for "Integrated multiomics analysis reveals the single-cell spatial landscape and immunosuppression mechanism in nasopharyngeal carcinoma"

posted on 14.04.2022, 03:54 by Lanqi GongLanqi Gong

Nasopharyngeal carcinoma (NPC) is a type of squamous cell carcinoma endemic in East and Southeast Asia. But the incidence is highly affected by epidemiological features and genetic susceptibility. Moreover, the NPC progression is primarily driven by the pstein–Barr virus (EBV) infection by inducing genomic instability and tumor microenvironment (TME) remodeling. In the past decade, NPC mortality has been reduced, because of improved healthcare awareness, large-scale screening of EBV, and optimization of chemo-radiotherapy, but the survival of advanced and chemoradiotherapy-resistant NPC patients has not been improved. According to the recent clinical trials, more than 30% of the most advanced NPC patients progress despite receiving the best chemo-radiotherapy available. For these patients, immunotherapy has emerged as a promising strategy. Nevertheless, recent clinical trials have exhibited that the PD-1 monotherapy only generated a <30% partial response rate in NPC patients. Hence, there is an unmet clinical need for deepening our understanding of microenvironmental landscape and immunosuppression mechanism to improve treatment response.

The TME of NPC is a highly heterogeneous and immunosuppressive ecosystem that facilitates tumor escape from immune surveillance. Previous studies utilizing bulk RNA sequencing, flow cytometry and immunohistochemistry (IHC) staining, remain insufficient to delineate characteristics of NPC. Thus, we aim to decipher the microenvironmental landscape in NPC patients and reveal tumor-specific features associated with prognosis and immunotherapeutic response via single-cell and spatial transcriptome sequencing (scRNA-seq and spatial-seq). Since 2019, 5’ scRNA-seq coupled with T cell receptor (TCR)/B cell receptor (BCR) profiling has been applied to clinical samples collected from 11 NPC patients and 3 NPI patients. We have initially characterized the enrichment of suppressive dysfunctional subtypes and in the TME, including FOXP3+ regulatory T cells (Tregs), HAVCR2+/TOX+ exhausted T cells (TEX), double-negative B (DN-B) cells and myeloid-derived suppressor cells (MDSCs). We applied spatial-seq to 7 primary NPC frozen tissue to construct a 2-dimensional landscape for analysis of cell-cell interactions. Particularly, we found the tumor core was highly infiltrated with Tregs and DN-B cells, but excluded effector T cells and plasma B cells, demonstrating how NPC progresses in a highly inflamed microenvironment. 

We further identify that Tregs are the primary source of immunosuppression in the NPC microenvironment. To comprehensively understand how Tregs inhibit immunotherapeutic efficacy in NPC, we establish a multi-center cohort containing 357,206 cells from 50 patients, and subsequently uncover that NPC cells promote Treg suppression via CD70-CD27 interaction, further leading to impaired anti-tumor immunity. CD70 inhibition reverted Treg development and suppression, and revitalized CD8+ T cell functioning. The anti-CD70 + anti-PD-1 therapy evaluated in NPC organoids shows an enhanced response compared to monotherapies. Mechanistically, CD70 knockout inhibited a collective lipid signaling network in co-cultured Tregs. Furthermore, the assay for transposase-accessible chromatin using sequencing (ATAC-seq) reveals that CD70 overexpression is transcriptionally regulated by NFKB2 via an EBV-dependent epigenetic modification. Altogether, our findings delineate CD70-CD27 signaling as a metabolic switch that enforces lipid-driven functional specialization and homeostasis of Tregs in the TME, and prospectively demonstrate that CD70 inhibition can synergistically work with anti-PD-1 treatment to reinvigorate anti-tumor immunity.      


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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE150825 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE200310 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?&acc=GSE200315