Presence of onco-fetal neighborhoods in hepatocellular carcinoma is associated with relapse and response to immunotherapy.

Onco-fetal reprogramming of the tumor ecosystem induces fetal developmental signatures in the tumor microenvironment, leading to immunosuppressive features. Here, we employed single-cell RNA sequencing, spatial transcriptomics and bulk RNA sequencing to delineate specific cell subsets involved in hepatocellular carcinoma (HCC) relapse and response to immunotherapy. We identified POSTN+ extracellular matrix cancer-associated fibroblasts (EM CAFs) as a prominent onco-fetal interacting hub, promoting tumor progression. Cell-cell communication and spatial transcriptomics analysis revealed crosstalk and co-localization of onco-fetal cells, including POSTN+ CAFs, FOLR2+ macrophages and PLVAP+ endothelial cells. Further analyses suggest an association between onco-fetal reprogramming and epithelial-mesenchymal transition (EMT), tumor cell proliferation and recruitment of Treg cells, ultimately influencing early relapse and response to immunotherapy. In summary, our study identifies POSTN+ CAFs as part of the HCC onco-fetal niche and highlights its potential influence in EMT, relapse and immunotherapy response, paving the way for the use of onco-fetal signatures for therapeutic stratification.

Cross-tissue single-cell landscape of human monocytes and macrophages in health and disease.

Mononuclear phagocytes (MNPs) encompass dendritic cells, monocytes, and macrophages (MoMac), which exhibit antimicrobial, homeostatic, and immunoregulatory functions. We integrated 178,651 MNPs from 13 tissues across 41 datasets to generate a MNP single-cell RNA compendium (MNP-VERSE), a publicly available tool to map MNPs and define conserved gene signatures of MNP populations. Next, we generated a MoMac-focused compendium that revealed an array of specialized cell subsets widely distributed across multiple tissues. Specific pathological forms were expanded in cancer and inflammation. All neoplastic tissues contained conserved tumor-associated macrophage populations. In particular, we focused on IL4I1+CD274(PD-L1)+IDO1+ macrophages, which accumulated in the tumor periphery in a T cell-dependent manner via interferon-γ (IFN-γ) and CD40/CD40L-induced maturation from IFN-primed monocytes. IL4I1_Macs exhibited immunosuppressive characteristics through tryptophan degradation and promoted the entry of regulatory T cell into tumors. This integrated analysis provides a robust online-available platform for uniform annotation and dissection of specific macrophage functions in healthy and pathological states.

Single-Cell RNA-seq Reveals Angiotensin-Converting Enzyme 2 and Transmembrane Serine Protease 2 Expression in TROP2+ Liver Progenitor Cells: Implications in Coronavirus Disease 2019-Associated Liver Dysfunction.

The recent coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2. COVID-19 was first reported in China (December 2019) and is now prevalent across the globe. Entry of severe acute respiratory syndrome coronavirus 2 into mammalian cells requires the binding of viral Spike (S) proteins to the angiotensin-converting enzyme 2 receptor. Once entered, the S protein is primed by a specialized serine protease, transmembrane serine protease 2 in the host cell. Importantly, besides the respiratory symptoms that are consistent with other common respiratory virus infections when patients become viremic, a significant number of COVID-19 patients also develop liver comorbidities. We explored whether a specific target cell-type in the mammalian liver could be implicated in disease pathophysiology other than the general deleterious response to cytokine storms. Here, we used single-cell RNA-seq to survey the human liver and identified potentially implicated liver cell-type for viral ingress. We analyzed ~300,000 single cells across five different (i.e., human fetal, healthy, cirrhotic, tumor, and adjacent normal) liver tissue types. This study reports on the co-expression of angiotensin-converting enzyme 2 and transmembrane serine protease 2 in a TROP2+ liver progenitor population. Importantly, we detected enrichment of this cell population in the cirrhotic liver when compared with tumor tissue. These results indicated that in COVID-19-associated liver dysfunction and cell death, a viral infection of TROP2+ progenitors in the liver might significantly impair liver regeneration in patients with liver cirrhosis.

Onco-fetal Reprogramming of Endothelial Cells Drives Immunosuppressive Macrophages in Hepatocellular Carcinoma.

We employed scRNA sequencing to extensively characterize the cellular landscape of human liver from development to disease. Analysis of ∼212,000 cells representing human fetal, hepatocellular carcinoma (HCC), and mouse liver revealed remarkable fetal-like reprogramming of the tumor microenvironment. Specifically, the HCC ecosystem displayed features reminiscent of fetal development, including re-emergence of fetal-associated endothelial cells (PLVAP/VEGFR2) and fetal-like (FOLR2) tumor-associated macrophages. In a cross-species comparative analysis, we discovered remarkable similarity between mouse embryonic, fetal-liver, and tumor macrophages. Spatial transcriptomics further revealed a shared onco-fetal ecosystem between fetal liver and HCC. Furthermore, gene regulatory analysis, spatial transcriptomics, and in vitro functional assays implicated VEGF and NOTCH signaling in maintaining onco-fetal ecosystem. Taken together, we report a shared immunosuppressive onco-fetal ecosystem in fetal liver and HCC. Our results unravel a previously unexplored onco-fetal reprogramming of the tumor ecosystem, provide novel targets for therapeutic interventions in HCC, and open avenues for identifying similar paradigms in other cancers and disease.

Single-Cell RNA Sequencing for Precision Oncology: Current State-of-Art.

Tumors exhibit genetic and phenotypic diversity leading to intra-tumor heterogeneity (ITH). Further complex ecosystem (stromal and immune cells) of tumors contributes into the ITH. This ITH allows tumors to overcome various selection pressures such as anti-cancer therapies and metastasis at distant organs. Single-cell RNA-seq (scRNA-seq) has provided unprecedented insights into ITH and its implications in drug resistance and metastasis. As scRNA-seq technology grows and provides many new findings, new tools on different programming platforms are frequently generated. Here, we aim to provide a framework and guidelines for new entrants into the field of scRNA-seq. In this review, we discuss the current state-of-art of scRNA-seq analysis step-by-step including filtering, normalization and analysis. First, we discuss the brief history of experimental methods, followed by data processing and implications in precision oncology.