Identification and validation of a genetic risk signature associated with prognosis in clear-cell renal cell carcinoma patients.

Clear-cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC), which exhibits great variability in the prognosis of patients. Endoplasmic reticulum stress (ERS) is a persistent state triggered by disruption of endoplasmic reticulum (ER) homeostasis, which has been shown to control multiple pro-tumor-associated pathways in malignant cells while dynamically reprogramming immune cell function. This study aimed to identify ERS-related genetic risk signatures (ERSGRS) to ameliorate survival prediction in ccRCC patients. In this study, we adopted differentially expressed genes (DEGs) from the Cancer Genome Atlas (TCGA) and constructed ERSGRS with independent prognostic significance by least absolute shrinkage and selection operator (LASSO) regression. After separation of patients based on risk score, survival analysis showed that low-risk patients had longer overall survival (OS) than high-risk patients, and receiver operating characteristic (ROC) curve analysis confirmed the strong predictive ability of ERSGRS. Meanwhile, the tumor microenvironment (TME) of the high-risk group demonstrated an immunosuppressive phenotype, with more infiltration of regulatory T cells (Tregs) and macrophages. The TME in the low-risk group had a stronger potential for anti-tumor immunity. Overall, the ERSGRS could be a valuable predictive tool for ccRCC prognosis.

Integration analysis of single-cell and spatial transcriptomics reveal the cellular heterogeneity landscape in glioblastoma and establish a polygenic risk model.

Background: Glioblastoma (GBM) is adults' most common and fatally malignant brain tumor. The heterogeneity is the leading cause of treatment failure. However, the relationship between cellular heterogeneity, tumor microenvironment, and GBM progression is still elusive. Methods: Integrated analysis of single-cell RNA sequencing (scRNA-seq) and spatial transcriptome sequencing (stRNA-seq) of GBM were conducted to analyze the spatial tumor microenvironment. We investigated the subpopulation heterogeneity of malignant cells through gene set enrichment analyses, cell communications analyses, and pseudotime analyses. Significantly changed genes of the pseudotime analysis were screened to create a tumor progress-related gene risk score (TPRGRS) using Cox regression algorithms in the bulkRNA-sequencing(bulkRNA-seq) dataset. We combined the TPRGRS and clinical characteristics to predict the prognosis of patients with GBM. Furthermore, functional analysis was applied to uncover the underlying mechanisms of the TPRGRS. Results: GBM cells were accurately charted to their spatial locations and uncovered their spatial colocalization. The malignant cells were divided into five clusters with transcriptional and functional heterogeneity, including unclassified malignant cells and astrocyte-like, mesenchymal-like, oligodendrocytes-progenitor-like, and neural-progenitor-like malignant cells. Cell-cell communications analysis in scRNA-seq and stRNA-seq identified ligand-receptor pairs of the CXCL, EGF, FGF, and MIF signaling pathways as bridges implying that tumor microenvironment may cause malignant cells' transcriptomic adaptability and disease progression. Pseudotime analysis showed the differentiation trajectory of GBM cells from proneural to mesenchymal transition and identified genes or pathways that affect cell differentiation. TPRGRS could successfully divide patients with GBM in three datasets into high- and low-risk groups, which was proved to be a prognostic factor independent of routine clinicopathological characteristics. Functional analysis revealed the TPRGRS associated with growth factor binding, cytokine activity, signaling receptor activator activity functions, and oncogenic pathways. Further analysis revealed the association of the TPRGRS with gene mutations and immunity in GBM. Finally, the external datasets and qRT-PCR verified high expressions of the TPRGRS mRNAs in GBM cells. Conclusion: Our study provides novel insights into heterogeneity in GBM based on scRNA-seq and stRNA-seq data. Moreover, our study proposed a malignant cell transition-based TPRGRS through integrated analysis of bulkRNA-seq and scRNA-seq data, combined with the routine clinicopathological evaluation of tumors, which may provide more personalized drug regimens for GBM patients.

Tumour-derived small extracellular vesicles contribute to the tumour progression through reshaping the systemic immune macroenvironment.

BACKGROUND: Tumour-derived small extracellular vesicles (sEVs) play a crucial role in cancer immunomodulation. In addition to tumour immune microenvironment, the peripheral immune system also contributes significantly to cancer progression and is essential for anticancer immunity. However, a comprehensive definition of which and how peripheral immune lineages are regulated by tumour-derived sEVs during cancer development remains incomplete. METHODS: In this study, we used mass cytometry with extensive antibody panels to comprehensively construct the systemic immune landscape in response to tumour development and tumour-derived sEVs. RESULTS: Systemic immunity was dramatically altered by tumour growth and tumour-derived sEVs. Tumour-derived sEVs significantly and extensively affected immune cell population composition as well as intracellular pathways, resulting in an immunosuppressive peripheral and tumour immune microenvironment, characterised by increased myeloid-derived suppressor cells and decreased Ly6C+CD8 T cells. These sEVs largely promoted hematopoietic recovery and accelerate the differentiation towards myeloid-derived suppressor cells. The knockdown of Rab27a reduced sEV secretion from tumour cells and delayed tumour growth and metastasis in vivo. CONCLUSIONS: These results highlight that tumour-derived sEVs function as a bridge between peripheral immunity regulation and the tumour microenvironment, and contribute to cancer progression through altering the composition and function of the global immune macroenvironment.

Melanoma-derived small extracellular vesicles remodel the systemic onco-immunity via disrupting hematopoietic stem cell proliferation and differentiation.

Hematopoiesis and the immune system beyond the tumor microenvironment are typically dysregulated in cancer. Tumor-derived small extracellular vesicles (sEVs) containing exosomes are emerging contributors to tumor progression and immunomodulation. However, a comprehensive definition of how tumor-derived sEVs impacts systemic immunity is lacking. In this study, we used mass cytometry with extensive antibody panels to determine the expression of 24 immune cell markers, eight intracellular proteins, and seven immune checkpoint proteins in systemic immune cell lineages. The systemic immune landscape in response to tumor-derived sEVs across three immune organs in a melanoma mouse model was then characterized. Melanoma-derived sEVs significantly and extensively influenced the composition and intracellular pathways of immune lineage and T cells. An immunosuppressive immune system with decreased natural killer and CD8 T cells in the spleen and bone marrow (BM), increased regulatory T cells in lymph nodes, and increased polymorphonuclear myeloid-derived suppressor cells (PMN-MDSC) in the BM, was induced by melanoma-derived sEVs. Additionally, melanoma-derived sEVs significantly enhanced the PD-1/PD-L1 axis in CD4 T cells and myeloid cell subsets. These sEVs largely promoted the proliferation of multiple hematopoietic stem and progenitor cell subsets and accelerated their differentiation towards MDSCs in naive mice and mice undergoing hematopoietic reconstruction. Moreover, melanoma-derived sEVs directly promoted the survival and activation of MDSCs in vitro. Collectively, our work examines the effects of tumor-derived sEVs on the systemic onco-immune macroenvironments and highlights the contribution of these sEVs to the dysregulation of hematopoiesis and systemic immune landscape in cancer.

Endocytic pathway inhibition attenuates extracellular vesicle-induced reduction of chemosensitivity to bortezomib in multiple myeloma cells.

Extracellular vesicles (EVs), including exosomes and microvesicles, derived from bone marrow stromal cells (BMSCs) have been demonstrated as key factors in the progression and drug resistance of multiple myeloma (MM). EV uptake involves a variety of mechanisms which largely depend on the vesicle origin and recipient cell type. The aim of the present study was to identify the mechanisms involved in the uptake of BMSC-derived small EVs (sEVs) by MM cells, and to evaluate the anti-MM effect of targeting this process. Methods: Human BMSC-derived sEVs were identified by transmission electron microscopy, nanoparticle tracking analysis, and western blot. The effects of chemical inhibitors and shRNA-mediated knockdown of endocytosis-associated genes on sEV uptake and cell apoptosis were analyzed by flow cytometry. The anti-MM effect of blocking sEV uptake was evaluated in vitro and in a xenograft MM mouse model. Results: sEVs derived from BMSC were taken up by MM cells in a time- and dose-dependent manner, and subsequently promoted MM cell cycling and reduced their chemosensitivity to bortezomib. Chemical endocytosis inhibitors targeting heparin sulphate proteoglycans, actin, tyrosine kinase, dynamin-2, sodium/proton exchangers, or phosphoinositide 3-kinases significantly reduced MM cell internalization of BMSC-derived sEVs. Moreover, shRNA-mediated knockdown of endocytosis-associated proteins, including caveolin-1, flotillin-1, clathrin heavy chain, and dynamin-2 in MM cells suppressed sEV uptake. Furthermore, an endocytosis inhibitor targeting dynamin-2 preferentially suppressed the uptake of sEV by primary MM cells ex vivo and enhanced the anti-MM effects of bortezomib in vitro and in a mouse model. Conclusion: Clathrin- and caveolin-dependent endocytosis and macropinocytosis are the predominant routes of sEV-mediated communication between BMSCs and MM cells, and inhibiting endocytosis attenuates sEV-induced reduction of chemosensitivity to bortezomib, and thus enhances its anti-MM properties.

Loading of metal isotope-containing intercalators for mass cytometry-based high-throughput quantitation of exosome uptake at the single-cell level.

Nanometer-sized exosomes are being widely studied as cell-to-cell communicators and versatile drug vehicles. Characterizations of the biodistribution of these exosomes are essential for the evaluation of their biological functions and drug delivery efficacy. However, current technologies for exosome tracking rely on fluorescence and have the disadvantages of being low throughput due to the limited number of available channels and spectral spillover. Here, we reported the development of an engineering approach that involves loading of metal isotope-containing intercalators into exosomes to quantify exosome uptake at the single-cell level. We demonstrate that mass cytometry in conjunction with highly multivariate cellular phenotyping enables high-throughput identification of the in vivo fate of exosomes. Inspired by these insights into cellular distribution, we optimized the administration methods for exosome-based drug delivery, verifying the anticancer efficacy of these exosomes in a mouse model of breast cancer. The evaluation of exosome's fate in vivo at the single-cell level provides valuable insights into the functions of exosomes in vivo and facilitates the improvement of exosome-based therapy.