Uncovering the Bronchoalveolar Single-Cell Landscape of Patients With Pulmonary Tuberculosis With Human Immunodeficiency Virus Type 1 Coinfection.

BACKGROUND: Coinfection of human immunodeficiency virus type 1 (HIV-1) is the most significant risk factor for tuberculosis (TB). The immune responses of the lung are essential to restrict the growth of Mycobacterium tuberculosis and avoid the emergence of the disease. Nevertheless, there is still limited knowledge about the local immune response in people with HIV-1-TB coinfection. METHODS: We employed single-cell RNA sequencing (scRNA-seq) on bronchoalveolar lavage fluid from 9 individuals with HIV-1-TB coinfection and 10 with pulmonary TB. RESULTS: A total of 19 058 cells were grouped into 4 major cell types: myeloid cells, T/natural killer (NK) cells, B cells, and epithelial cells. The myeloid cells and T/NK cells were further divided into 10 and 11 subsets, respectively. The proportions of dendritic cell subsets, CD4+ T cells, and NK cells were lower in the HIV-1-TB coinfection group compared to the TB group, while the frequency of CD8+ T cells was higher. Additionally, we identified numerous differentially expressed genes between the CD4+ and CD8+ T-cell subsets between the 2 groups. CONCLUSIONS: HIV-1 infection not only affects the abundance of immune cells in the lungs but also alters their functions in patients with pulmonary TB.

An invasive zone in human liver cancer identified by Stereo-seq promotes hepatocyte-tumor cell crosstalk, local immunosuppression and tumor progression.

Dissecting and understanding the cancer ecosystem, especially that around the tumor margins, which have strong implications for tumor cell infiltration and invasion, are essential for exploring the mechanisms of tumor metastasis and developing effective new treatments. Using a novel tumor border scanning and digitization model enabled by nanoscale resolution-SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we identified a 500 µm-wide zone centered around the tumor border in patients with liver cancer, referred to as "the invasive zone". We detected strong immunosuppression, metabolic reprogramming, and severely damaged hepatocytes in this zone. We also identified a subpopulation of damaged hepatocytes with increased expression of serum amyloid A1 and A2 (referred to collectively as SAAs) located close to the border on the paratumor side. Overexpression of CXCL6 in adjacent malignant cells could induce activation of the JAK-STAT3 pathway in nearby hepatocytes, which subsequently caused SAAs' overexpression in these hepatocytes. Furthermore, overexpression and secretion of SAAs by hepatocytes in the invasive zone could lead to the recruitment of macrophages and M2 polarization, further promoting local immunosuppression, potentially resulting in tumor progression. Clinical association analysis in additional five independent cohorts of patients with primary and secondary liver cancer (n = 423) showed that patients with overexpression of SAAs in the invasive zone had a worse prognosis. Further in vivo experiments using mouse liver tumor models in situ confirmed that the knockdown of genes encoding SAAs in hepatocytes decreased macrophage accumulation around the tumor border and delayed tumor growth. The identification and characterization of a novel invasive zone in human cancer patients not only add an important layer of understanding regarding the mechanisms of tumor invasion and metastasis, but may also pave the way for developing novel therapeutic strategies for advanced liver cancer and other solid tumors.

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.

Single-cell transcriptomic landscape identifies the expansion of peripheral blood monocytes as an indicator of HIV-1-TB co-infection.

Certain circulating cell subsets are involved in immune dysregulation in human immunodeficiency virus type 1 (HIV-1) and tuberculosis (TB) co-infection; however, the characteristics and role of these subclusters are unknown. Peripheral blood mononuclear cells (PBMCs) of patients with HIV-1 infection alone (HIV-pre) and those with HIV-1-TB co-infection without anti-TB treatment (HIV-pre & TB-pre) and with anti-TB treatment for 2 weeks (HIV-pre & TB-pos) were subjected to single-cell RNA sequencing (scRNA-seq) to characterize the transcriptome of different immune cell subclusters. We obtained > 60,000 cells and identified 32 cell subclusters based on gene expression. The proportion of immune-cell subclusters was altered in HIV-1-TB co-infected individuals compared with that in HIV-pre-group, indicating immune dysregulation corresponding to different disease states. The proportion of an inflammatory CD14+CD16+ monocyte subset was higher in the HIV-pre & TB-pre group than in the HIV-pre group; this was validated in an additional cohort (n = 80) via a blood cell differential test, which also demonstrated a good discriminative performance (area under the curve, 0.8046). These findings depicted the atlas of immune PBMC subclusters in HIV-1-TB co-infection and demonstrate that monocyte subsets in peripheral blood might serve as a discriminating biomarker for diagnosis of HIV-1-TB co-infection.

Comprehensive landscape of epigenetic-dysregulated lncRNAs reveals a profound role of enhancers in carcinogenesis in BC subtypes.

Aberrant expression of long non-coding RNAs (lncRNA) is associated with altered DNA methylation and histone modifications during carcinogenesis. However, identifying epigenetically dysregulated lncRNAs and characterizing their functional mechanisms in different cancer subtypes are still major challenges for cancer studies. In this study, we systematically analyzed the epigenetic alterations of lncRNAs at important regulatory elements in three breast cancer subtypes. We identified 87, 691, and 1,197 epigenetically dysregulated lncRNAs in luminal, basal, and claudin-low subtypes of breast cancer, respectively. The landscape of epigenetically dysregulated lncRNAs at enhancer elements revealed that epigenetic changes of the majority of lncRNAs occurred in a subtype-specific manner and contributed to subtype-specific biological functions. We identified six acetylation of lysine 27 on histone H3 (H3K27ac)-dysregulated lncRNAs and three DNA methylation-dysregulated lncRNAs (CTC-303L1.2, RP11-738B7.1, and SLC26A4-AS1) as prognostic biomarkers of basal subtype. These lncRNAs were involved in immune response-related biological functions. Treatment of the basal breast cancer cell line MDA-MB-468 with CREBBP/EP300 bromodomain inhibitors downregulated H3K27 acetylation levels and caused a decrease in the expression of five H3K27ac-dysregulated lncRNAs (LINC00393, KB-1836B5.1, RP1-140K8.5, AC005162.1, and AC020916.2) and inhibition of the growth of breast cancer cells. One epigenetically dysregulated lncRNA (LINC01983) and four lncRNA regulators (UCA1, RP11-221J22.2, RP11-221J22.1, and RP1-212P9.3) were identified as prognostic biomarkers of the luminal molecular subtype of breast cancer by controlling the tumor necrosis factor (TNF) signaling pathway, T helper (Th)17 cell differentiation, and T cell migration. Finally, our results highlighted a profound role of enhancer-related H3K27ac-dysregulated lncRNAs, DNA methylation-dysregulated lncRNAs, and lncRNA regulators in breast cancer subtype carcinogenesis and their potential prognostic value.

LncTarD: a manually-curated database of experimentally-supported functional lncRNA-target regulations in human diseases.

Long non-coding RNAs (lncRNAs) are associated with human diseases. Although lncRNA-disease associations have received significant attention, no online repository is available to collect lncRNA-mediated regulatory mechanisms, key downstream targets, and important biological functions driven by disease-related lncRNAs in human diseases. We thus developed LncTarD (http://biocc.hrbmu.edu.cn/LncTarD/ or http://bio-bigdata.hrbmu.edu.cn/LncTarD), a manually-curated database that provides a comprehensive resource of key lncRNA-target regulations, lncRNA-influenced functions, and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD offers (i) 2822 key lncRNA-target regulations involving 475 lncRNAs and 1039 targets associated with 177 human diseases; (ii) 1613 experimentally-supported functional regulations and 1209 expression associations in human diseases; (iii) important biological functions driven by disease-related lncRNAs in human diseases; (iv) lncRNA-target regulations responsible for drug resistance or sensitivity in human diseases and (v) lncRNA microarray, lncRNA sequence data and transcriptome data of an 11 373 pan-cancer patient cohort from TCGA to help characterize the functional dynamics of these lncRNA-target regulations. LncTarD also provides a user-friendly interface to conveniently browse, search, and download data. LncTarD will be a useful resource platform for the further understanding of functions and molecular mechanisms of lncRNA deregulation in human disease, which will help to identify novel and sensitive biomarkers and therapeutic targets.