Purpose: Innate immunity is an indispensable arm of tumor immune surveillance, and the liver is an organ with a predominance of innate immunity, where mucosal-associated invariant T (MAIT) cells are enriched. However, little is known about the phenotype, functions, and immunomodulatory role of MAIT cells in hepatocellular carcinoma (HCC). Experimental Design: The distribution, phenotype, and function of MAIT cells in patients with HCC were evaluated by both flow cytometry (FCM) and in vitro bioassays. Transcriptomic analysis of MAIT cells was also performed. Prognostic significance of tumor-infiltrating MAIT cells was validated in four independent cohorts of patients with HCC. Results: Despite their fewer densities in HCC tumor than normal liver, MAIT cells were significantly enriched in the HCC microenvironment compared with other mucosaassociated organs. Tumor-derived MAIT cells displayed a typical CCR7 À CD45RA À CD45RO þ CD95 þ effector memory phenotype with lower costimulatory and effector capabilities. Tumor-educated MAIT cells significantly upregulated inhibitory molecules like PD-1, CTLA-4, TIM-3, secreted significantly less IFNg and IL17, and produced minimal granzyme B and perforin while shifting to produce tumor-promoting cytokines like IL8. Transcriptome sequencing confirmed that tumor-derived MAIT cells were reprogrammed toward a tumor-promoting direction by downregulating genes enriched in pathways of cytokine secretion and cytolysis effector function like NFKB1 and STAT5B and by upregulating genes like IL8, CXCL12, and HAVCR2 (TIM-3). High infiltration of MAIT cells in HCC significantly correlated with an unfavorable clinical outcome, revealed by FCM, qRT-PCR, and multiplex IHC analyses, respectively. Conclusions: HCC-infiltrating MAIT cells were functionally impaired and even reprogrammed to shift away from antitumor immunity and toward a tumor-promoting direction. See related commentary by Carbone, p. 3199

Motivation Single cell RNA-sequencing (scRNA-seq) technology enables whole transcriptome profiling at single cell resolution and holds great promises in many biological and medical applications. Nevertheless, scRNA-seq often fails to capture expressed genes, leading to the prominent dropout problem. These dropouts cause many problems in down-stream analysis, such as significant increase of noises, power loss in differential expression analysis and obscuring of gene-to-gene or cell-to-cell relationship. Imputation of these dropout values can be beneficial in scRNA-seq data analysis. Results In this article, we model the dropout imputation problem as robust matrix decomposition. This model has minimal assumptions and allows us to develop a computational efficient imputation method called scRMD. Extensive data analysis shows that scRMD can accurately recover the dropout values and help to improve downstream analysis such as differential expression analysis and clustering analysis. Availability and implementation The R package scRMD is available at https://github.com/XiDsLab/scRMD. Supplementary information Supplementary data are available at Bioinformatics online.

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Hematopoietic stem cell transplantation is an effective regenerative therapy for many malignant, inherited, or autoimmune diseases. However, our understanding of reconstituted hematopoiesis in transplant patients remains limited. Here, we uncover the reconstitution dynamics of human allogeneic hematopoietic stem and progenitor cells (HSPCs) at single-cell resolution after transplantation. Transplanted HSPCs underwent rapid and measurable changes during the first 30 days after transplantation, characterized by a strong proliferative response on the first day. Transcriptomic analysis of HSPCs enabled us to observe that immunoregulatory neutrophil progenitors expressing high levels of the S100A gene family were enriched in granulocyte colony-stimulating factor–mobilized peripheral blood stem cells. Transplant recipients who developed acute graft-versus-host disease (aGVHD) infused fewer S100A high immunoregulatory neutrophil progenitors, immunophenotyped as Lin - CD34 + CD66b + CD177 + , than those who did not develop aGVHD. Therefore, our study provides insights into the regenerative process of transplanted HSPCs in human patients and identifies a potential criterion for identifying patients at high risk for developing aGVHD early after transplant.