Single-cell sequencing reveals the heterogeneity of B cells and tertiary lymphoid structures in muscle-invasive bladder cancer.

BACKGROUND: Muscle-invasive bladder cancer (MIBC) is a highly aggressive disease with a poor prognosis. B cells are crucial factors in tumor suppression, and tertiary lymphoid structures (TLSs) facilitate immune cell recruitment to the tumor microenvironment (TME). However, the function and mechanisms of tumor-infiltrating B cells and TLSs in MIBC need to be explored further. METHODS: We performed single-cell RNA sequencing analysis of 11,612 B cells and 55,392 T cells from 12 bladder cancer patients and found naïve B cells, proliferating B cells, plasma cells, interferon-stimulated B cells and germinal center-associated B cells, and described the phenotype, gene enrichment, cell-cell communication, biological processes. We utilized immunohistochemistry (IHC) and immunofluorescence (IF) to describe TLSs morphology in MIBC. RESULTS: The interferon-stimulated B-cell subtype (B-ISG15) and germinal center-associated B-cell subtypes (B-LMO2, B-STMN1) were significantly enriched in MIBC. TLSs in MIBC exhibited a distinct follicular structure characterized by a central region of B cells resembling a germinal center surrounded by T cells. CellChat analysis showed that CXCL13 + T cells play a pivotal role in recruiting CXCR5 + B cells. Cell migration experiments demonstrated the chemoattraction of CXCL13 toward CXCR5 + B cells. Importantly, the infiltration of the interferon-stimulated B-cell subtype and the presence of TLSs correlated with a more favorable prognosis in MIBC. CONCLUSIONS: The study revealed the heterogeneity of B-cell subtypes in MIBC and suggests a pivotal role of TLSs in MIBC outcomes. Our study provides novel insights that contribute to the precision treatment of MIBC.

Establishment of a risk score model for bladder urothelial carcinoma based on energy metabolism-related genes and their relationships with immune infiltration.

Bladder urothelial carcinoma (BLCA) is a common malignant tumor of the human urinary system, and a large proportion of BLCA patients have a poor prognosis. Therefore, there is an urgent need to find more efficient and sensitive biomarkers for the prognosis of BLCA patients in clinical practice. RNA sequencing (RNA-seq) data and clinical information were obtained from The Cancer Genome Atlas, and 584 energy metabolism-related genes (EMRGs) were obtained from the Reactome pathway database. Cox regression analysis and least absolute shrinkage and selection operator analysis were applied to assess prognostic genes and build a risk score model. The estimate and cibersort algorithms were used to explore the immune microenvironment, immune infiltration, and checkpoints in BLCA patients. Furthermore, we used the Human Protein Atlas database and our single-cell RNA-seq datasets of BLCA patients to verify the expression of 13 EMRGs at the protein and single-cell levels. We constructed a risk score model; the area under the curve of the model at 5 years was 0.792. The risk score was significantly correlated with the immune markers M0 macrophages, M2 macrophages, CD8 T cells, follicular helper T cells, regulatory T cells, and dendritic activating cells. Furthermore, eight immune checkpoint genes were significantly upregulated in the high-risk group. The risk score model can accurately predict the prognosis of BLCA patients and has clinical application value. In addition, according to the differences in immune infiltration and checkpoints, BLCA patients with the most significant benefit can be selected for immune checkpoint inhibitor therapy.

A spatiotemporal steroidogenic regulatory network in human fetal adrenal glands and gonads.

Human fetal adrenal glands produce substantial amounts of dehydroepiandrosterone (DHEA), which is one of the most important precursors of sex hormones. However, the underlying biological mechanism remains largely unknown. Herein, we sequenced human fetal adrenal glands and gonads from 7 to 14 gestational weeks (GW) via 10× Genomics single-cell transcriptome techniques, reconstructed their location information by spatial transcriptomics. Relative to gonads, adrenal glands begin to synthesize steroids early. The coordination among steroidogenic cells and multiple non-steroidogenic cells promotes adrenal cortex construction and steroid synthesis. Notably, during the window of sexual differentiation (8-12 GW), key enzyme gene expression shifts to accelerate DHEA synthesis in males and cortisol synthesis in females. Our research highlights the robustness of the action of fetal adrenal glands on gonads to modify the process of sexual differentiation.

Molecular mechanisms, immune cell infiltration, and potential drugs for prostate cancer.

BACKGROUND: The molecular mechanisms involved in the prostate cancer and their relationship with immune cell infiltration are not fully understood. The prostate cancer patients undergoing standard androgen deprivation therapy eventually develop castration resistant prostate cancer (CRPC) for which there is no effective treatment currently available, and the hub genes involved in this process remain unclear. OBJECTIVE: To study prostate cancer systematically and comprehensively. METHODS: Differentially expressed genes (DEGs) of prostate cancer were screened in The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Connectivity Map (Cmap) software was applied to discover potential treatment drugs. A protein-protein interaction (PPI) analysis was performed to obtained the hub genes, and the relationship between hub genes and immune cell infiltration was investigated. Next, RNAseq data of hormone-sensitive prostate cancer samples and CRPC samples obtained from TCGA database was further analyzed to identify DEGs. Finally, a PPI analysis was performed to obtain the hub genes. RESULTS: A total of 319 DEGs were identified between prostate cancer samples and normal adjacent samples from TCGA database using comparative analysis. The KEGG pathway analysis showed significant correlations with drug metabolism, metabolism of xenobiotics by cytochrome P450, and chemical carcinogenesis. AMACR, FOLH1 and NPY, three hub genes, were found to be upregulated. FOLH1 was positively correlated with CD8+ T cell infiltration. FOLH1, AMACR, and NPY were negatively correlated with CD4+ T cell infiltration. A total of 426 DEGs were identified from RNAseq data of hormone-sensitive prostate cancer samples and CRPC samples using further comparative analysis. KEGG pathway enrichment analysis showed significant correlations with arachidonic acid metabolism, PPAR signaling pathway, AMPK signaling pathway, and metabolic pathways. The top 10 hub genes in PPI network were screened out, including PPARG, SREBF1, SCD, HMGCR, FASN, PTGS2, HMGCS2, SREBF2, FDFT1, and INSIG1. Among them, SCD and FASN are expected to be the potential therapeutic targets for CRPC. CONCLUSIONS: AMACR, FOLH1 and NPY may be effective therapeutic targets and specific diagnostic markers for prostate cancer. AMACR, FOLH1, and NPY are also closely associated with immune cell infiltration in prostate cancer. Moreover, aminoglutethimide and resveratrol were found to be the promising drugs for treating prostate cancer. The progression of hormone-sensitive prostate cancer to CRPC may be related to arachidonic acid metabolism, PPAR signaling pathway, AMPK signaling pathway, and other metabolic pathways. SCD and FASN are expected to be the potential therapeutic targets for CRPC.

Association of UCP1 polymorphisms with type 2 diabetes mellitus and their interaction with physical activity and sedentary behavior.

BACKGROUND: Uncoupling protein 1 (UCP1) has been reported to be associated with type 2 diabetes mellitus (T2DM) in different populations, however, little is reported in Chinese population. The present study aimed to explore the association between some polymorphisms of UCP1 with T2DM and the interactions between UCP1 and physical activity/sedentary behavior (PA/SB) lifestyle in Chinese population. METHODS: Three polymorphisms (rs1472268, rs3811790 and rs3811791) were genotyped in 929 T2DM patients and 1044 nondiabetic controls. The data of PA and SB were acquired. Logistic regression and linear regression were conducted to assess the association of UCP1 and T2DM and related traits. RESULTS: The CC genotype of rs3811791 was significantly associated with an increased risk of T2DM [odds ratio (OR) = 1.42, P = 0.042] and a higher level of triglyceride (TG) (ß = 0.048, P = 0.034). This association still existed in the group of SB ≥ 3 h/d (OR = 1.66, P = 0.009) and the group of PA ≥ 150 min/week and SB ≥ 3 h/d (OR = 1.60, P = 0.034). In the group of PA < 150 min/week and SB < 3h/d, CC genotype was associated with a higher level of homeostatic model assessment of insulin resistance (HOMA-IR) index, and in the group of PA < 150 min/week and SB ≥ 3 h/d, CC genotype was associated with increased level of TG and decreased high-density lipoprotein cholesterol (HDL-C). CONCLUSION: This study suggests that rs3811791 of UCP1 may be associated with T2DM and TG. Moreover, we demonstrate that SB interacted with rs3811791 of UCP1 was associated with T2DM, and PA interacted with rs3811791 of UCP1 was associated with the level of HOMA-IR, HDL-C, and TG.

Exploring the mechanism of clear cell renal cell carcinoma metastasis and key genes based on multi-tool joint analysis.

Clear cell renal cell carcinoma (ccRCC) is a highly invasive urological malignant tumor that results in shorter patient survival. At present, the mechanism of ccRCC metastasis is not clear. We explored the possible mechanisms of ccRCC metastasis by analyzing the transcriptome of ccRCC patients from the Cancer Genome Atlas (TCGA) database. Comparing the differences in transcriptome in patients with and without metastasis, we found 323 differential genes (|log2FoldChange| > 1 and P < 0.001). KEGG and GO enrichment analyses of differentially expressed genes (DEGs) suggest that the transfer mechanism of ccRCC may be related to complement and coagulation cascades and cholesterol metabolism. To explore the key genes affecting tumor metastasis, we analyzed the association of these genes with patient survival time and found that 16 genes were significantly associated (P < 0.05). We compared the differences in expression of these 16 genes between ccRCC patients and the normal population, and the results showed that TF and B4GALNT1 were overexpressed in patients. Co-expression gene analysis indicated that TF may participate in the metastasis of cancer through the complement system and mucopolysaccharide biosynthesis. B4GALNT1 may affect metastasis through focal adhesion, calcium signaling pathways, and Hippo signaling pathways. Our studies suggest that the complement system and the coagulation cascade, cholesterol metabolism, calcium pathway and iron transport may be associated in the mechanism of metastasis. TF and B4GALNT1 may be the key genes for metastasis, and they may be potential diagnostic markers and therapeutic targets for ccRCC.