A comprehensive cellular anatomy of normal human kidney is crucial to address the cellular origins of renal disease and renal cancer. Some kidney diseases may be cell type-specific, especially renal tubular cells. To investigate the classification and transcriptomic information of the human kidney, we rapidly obtained a single-cell suspension of the kidney and conducted single-cell RNA sequencing (scRNA-seq). Here, we present the scRNA-seq data of 23,366 high-quality cells from the kidneys of three human donors. In this dataset, we show 10 clusters of normal human renal cells. Due to the high quality of single-cell transcriptomic information, proximal tubule (PT) cells were classified into three subtypes and collecting ducts cells into two subtypes. Collectively, our data provide a reliable reference for studies on renal cell biology and kidney disease.

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two long noncoding RNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC. Significance: A comprehensive analysis of gene expression and DNA regulation in ccRCC using scATAC-seq and scRNA-seq reveals the DNA regulatory programs of ccRCC at the single-cell level.

Background: Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumor heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumor-specific markers, especially single-cell RNA sequencing (scRNA-seq).Methods: We performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumor characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level.Results: Some new tumor-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumor cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC.Conclusions: Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC.

Prostate is susceptible to infection and pro-inflammatory agents in a man’s whole life. Chronic inflammation might play important roles in the development and progression of prostate cancer. Mesenchymal stem cells (MSCs) are often recruited to the tumor microenvironment due to local inflammation. We have asked whether stimulation of MSCs by pro-inflammatory cytokines could promote prostate tumor growth. The current study investigated the possible involvement of MSCs stimulated by pro-inflammatory cytokines in promotion and angiogenesis of prostate cancer through relative pathway in vitro and in vivo. A syngeneic mouse model of C57 was established. The murine prostate cancer cells (RM-1) mixing with MSCs treated with tumor necrosis factor alpha (TNF-α) and interferon gamma (IFN-γ) or vehicle were subcutaneously injected into C57 mice. Tumor volume of C57 mouse model was estimated and serum level of platelet-derived growth factor (PDGF) and vascular endothelial growth factor (VEGF) was test by Enzyme-linked Immunosorbent Assay (ELISA). A hen egg test-chorioallantoic membrane (HET-CAM) assay was applied to test the effect of conditioned media of stimulated MSCs in chorioallantoic membrane angiogenesis. Short interfering RNA (siRNA) knocked down either hypoxia-inducible factor-1alpha (HIF-1α) or nuclear factor-erythroid-2-related factor 2 (NRF2) were employed. mRNA of PDGF and VEGF in MSCs, as well as NRF2 and HIF-1α was test by Real time polymerase chain reaction (PCR) analyses. Protein expression levels of PDGF and VEGF from conditioned medium, NRF2, HIF-1α, as well as PDGF and VEGF in MSCs were detected by Western blot analysis. MSCs treated with TNF-α and IFN-γ promote tumor growth in C57 syngeneic mouse model, correlating with increased serum level of PDGF, VEGF. HET-CAM assay shows the angiogenic effect of conditioned medium of MSCs pre-treated with the pro-inflammatory cytokines. mRNA and protein levels of two pro-angiogenic factors (PDGF and VEGF) and key hypoxia regulators (HIF-1α and NRF2) in MSCs were induced after MSCs’ pretreatment. siRNA knockdown either HIF-1α or NRF2 results reduction of PDGF and VEGF expression. MSCs stimulated by pro-inflammatory cytokines increase the expression of PDGF and VEGF via the NRF2-HIF-1α pathway and accelerate prostate cancer growth in mice.

Background: The introduction of multiparameter MRI and novel biomarkers has greatly improved the prediction of clinically significant prostate cancer (csPCa). However, decision-making regarding prostate biopsy and prebiopsy examinations is still difficult. We aimed to establish a quick and economic tool to improve the detection of csPCa based on routinely performed clinical examinations through an automated machine learning platform (AutoML). Methods: This study included a multicenter retrospective cohort and two prospective cohorts with 4747 cases from 9 hospitals across China. The multimodal data, including demographics, clinical characteristics, laboratory tests, and ultrasound reports, of consecutive participants were retrieved using extract-transform-load tools. AutoML was applied to explore potential data processing patterns and the most suitable algorithm to build the Prostate Cancer Artificial Intelligence Diagnostic System (PCAIDS). The diagnostic performance was determined by the receiver operating characteristic curve (ROC) for discriminating csPCa from insignificant prostate cancer (PCa) and benign disease. The clinical utility was evaluated by decision curve analysis (DCA) and waterfall plots. Results: The random forest algorithm was applied in the feature selection, and the AutoML algorithm was applied for model establishment. The area under the curve (AUC) value in identifying csPCa was 0.853 in the training cohort, 0.820 in the validation cohort, 0.807 in the Changhai prospective cohort, and 0.850 in the Zhongda prospective cohort. DCA showed that the PCAIDS was superior to PSA or fPSA/tPSA for diagnosing csPCa with a higher net benefit for all threshold probabilities in all cohorts. Setting a fixed sensitivity of 95%, a total of 32.2%, 17.6%, and 26.3% of unnecessary biopsies could be avoided with less than 5% of csPCa missed in the validation cohort, Changhai and Zhongda prospective cohorts, respectively. Conclusions: The PCAIDS was an effective tool to inform decision-making regarding the need for prostate biopsy and prebiopsy examinations such as mpMRI. Further prospective and international studies are warranted to validate the findings of this study. Trial registration: Chinese Clinical Trial Registry ChiCTR2100048428. Registered on 06 July 2021.

Androgen deprivation (AD) as the first-line treatment for advanced prostate cancer (PCa) is insufficient for a long-term effect. Castration resistance remains the greatest obstacle in PCa clinical therapy. Mesenchymal stem cells (MSCs) can migrate into PCa tissues contributing to tumor progression, therefore, in this study we explored the effect of AD on MSC migration to PCa and elicited its importance for the emergence of castration resistance. MSC migration assay was performed in several PCa cells (LNCaP, VCaP, and 22Rv1) using in-vivo and in-vitro approaches. Reactive oxygen species generation was evaluated by fluorescence assay. IL-1β was analyzed by immunohistochemistry, and neutralization experiments were conducted using neutralization antibody. Stem markers (CD133, CD44, and SOX2) were quantified by real-time PCR analysis. The concentration of chemokine ligand 5 was measured by enzyme-linked immunosorbent assay and small hairpin RNA was used for functional analyses. AD could significantly contribute to PCa recruitment of MSCs in vivo and in vitro. AD-induced oxidative stress could promote the inflammatory response mediated by IL-1β secretion via activating the NF-κB signaling pathway. Moreover, N-acetylcysteine could significantly inhibit MSC recruitment to PCa sites when AD is performed. Furthermore, we found MSCs could increase stemness of PCa cells via promoting chemokine ligand 5 secretion in the AD condition, and consequently accelerate emergence of castration resistance. Our results suggest that castration in clinical PCa therapy may elicit oxidative stress in tumor sites, resulting in increased MSC migration and in tumor cell growth in an androgen-independent manner. Blocking MSC migration to the tumor may provide a new potential target to suppress castration-resistant PCa emergence.