Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors

Single-nucleus RNA sequencing and deep tissue proteomics reveal distinct tumour microenvironment in stage-I and II cervical cancer

BACKGROUND

Cervical cancer (CC) is the 3rd most common cancer in women and the 4th leading cause of deaths in gynaecological malignancies, yet the exact progression of CC is inconclusive, mainly due to the high complexity of the changing tumour microenvironment (TME) at different stages of tumorigenesis. Importantly, a detailed comparative single-nucleus transcriptomic analysis of tumour microenvironment (TME) of CC patients at different stages is lacking.

METHODS

In this study, a total of 42,928 and 29,200 nuclei isolated from the tumour tissues of stage-I and II CC patients and subjected to single-nucleus RNA sequencing (snRNA-seq) analysis. The cell heterogeneity and functions were comparatively investigated using bioinformatic tools. In addition, label-free quantitative mass spectrometry based proteomic analysis was carried out. The proteome profiles of stage-I and II CC patients were compared, and an integrative analysis with the snRNA-seq was performed.

RESULTS

Compared with the stage-I CC (CCI) patients, the immune response relevant signalling pathways were largely suppressed in various immune cells of the stage-II CC (CCII) patients, yet the signalling associated with cell and tissue development was enriched, as well as metabolism for energy production suggested by the upregulation of genes associated with mitochondria. This was consistent with the quantitative proteomic analysis that showed the dominance of proteins promoting cell growth and intercellular matrix development in the TME of CCII group. The interferon-α and γ responses appeared the most activated pathways in many cell populations of the CCI patients. Several collagens, such as COL12A1, COL5A1, COL4A1 and COL4A2, were found significantly upregulated in the CCII group, suggesting their roles in diagnosing CC progression. A novel transcript AC244205.1 was detected as the most upregulated gene in CCII patients, and its possible mechanistic role in CC may be investigated further.

CONCLUSIONS

Our study provides important resources for decoding the progression of CC and set the foundation for developing novel approaches for diagnosing CC and tackling the immunosuppressive TME.

Single-cell RNA-seq integrated with multi-omics reveals SERPINE2 as a target for metastasis in advanced renal cell carcinoma

Tumor growth, metastasis and therapeutic response are believed to be regulated by the tumor and its microenvironment (TME) in advanced renal cell carcinoma (RCC). However, the mechanisms underlying genomic, transcriptomic and epigenetic alternations in RCC progression have not been completely defined. In this study, single-cell RNA-sequencing (scRNA-seq) data were obtained from eight tissue samples of RCC patients, including two matched pairs of primary and metastatic sites (lymph nodes), along with Hi-C, transposable accessible chromatin by high-throughput (ATAC-seq) and RNA-sequencing (RNA-seq) between RCC (Caki-1) and human renal tubular epithelial cell line (HK-2). The identified target was verified in clinical tissue samples (microarray of 407 RCC patients, TMA-30 and TMA-2020), whose function was further validated by in vitro and in vivo experiments through knockdown or overexpression. We profiled transcriptomes of 30514 malignant cells, and 14762 non-malignant cells. Comprehensive multi-omics analysis revealed that malignant cells and TME played a key role in RCC. The expression programs of stromal cells and immune cells were consistent among the samples, whereas malignant cells expressed distinct programs associated with hypoxia, cell cycle, epithelial differentiation, and two different metastasis patterns. Comparison of the hierarchical structure showed that SERPINE2 was related to these NNMF expression programs, and at the same time targeted the switched compartment. SERPINE2 was highly expressed in RCC tissues and lowly expressed in para-tumor tissues or HK-2 cell line. SERPINE2 knockdown markedly suppressed RCC cell growth and invasion, while SERPINE2 overexpression dramatically promoted RCC cell metastasis both in vitro and in vivo. In addition, SERPINE2 could activate the epithelial-mesenchymal transition pathway. The above findings demonstrated that the role of distinct expression patterns of malignant cells and TME played a distinct role in RCC progression. SERPINE2 was identified as a potential therapeutic target for inhibiting metastasis in advanced RCC.

Renal interstitial cells promote nephron regeneration by secreting prostaglandin E2

In organ regeneration, progenitor and stem cells reside in their native microenvironment, which provides dynamic physical and chemical cues essential to their survival, proliferation, and differentiation. However, the types of cells that form the native microenvironment for renal progenitor cells (RPCs) have not been clarified. Here, single-cell sequencing of zebrafish kidney reveals fabp10a as a principal marker of renal interstitial cells (RICs), which can be specifically labeled by GFP under the control of fabp10a promoter in the fabp10a:GFP transgenic zebrafish. During nephron regeneration, the formation of nephrons is supported by RICs that form a network to wrap the RPC aggregates. RICs that are in close contact with RPC aggregates express cyclooxygenase 2 (Cox2) and secrete prostaglandin E2 (PGE2). Inhibiting PGE2 production prevents nephrogenesis by reducing the proliferation of RPCs. PGE2 cooperates with Wnt4a to promote nephron maturation by regulating β-catenin stability of RPC aggregates. Overall, these findings indicate that RICs provide a necessary microenvironment for rapid nephrogenesis during nephron regeneration.

Single-cell transcriptomics: A new tool for studying diabetic kidney disease

The kidney is a complex organ comprising various functional partitions and special cell types that play important roles in maintaining homeostasis in the body. Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease and is an independent risk factor for cardiovascular diseases. Owing to the complexity and heterogeneity of kidney structure and function, the mechanism of DKD development has not been fully elucidated. Single-cell sequencing, including transcriptomics, epigenetics, metabolomics, and proteomics etc., is a powerful technology that enables the analysis of specific cell types and states, specifically expressed genes or pathways, cell differentiation trajectories, intercellular communication, and regulation or co-expression of genes in various diseases. Compared with other omics, RNA sequencing is a more developed technique with higher utilization of tissues or samples. This article reviewed the application of single-cell transcriptomics in the field of DKD and highlighted the key signaling pathways in specific tissues or cell types involved in the occurrence and development of DKD. The comprehensive understanding of single-cell transcriptomics through single-cell RNA-seq and single-nucleus RNA-seq will provide us new insights into the pathogenesis and treatment strategy of various diseases including DKD.

Single-Cell and Transcriptome-Based Immune Cell-Related Prognostic Model in Clear Cell Renal Cell Carcinoma

Traditional studies mostly focus on the role of single gene in regulating clear cell renal cell carcinoma (ccRCC), while it ignores the impact of tumour heterogeneity on disease progression. The purpose of this study is to construct a prognostic risk model for ccRCC by analysing the differential marker genes related to immune cells in the single-cell database to provide help in clinical diagnosis and targeted therapy. Single-cell data and ligand-receptor relationship pair data were downloaded from related publications, and ccRCC phenotype and expression profile data were downloaded from TCGA and CPTAC. Based on the DEGs of each cluster acquired from single-cell data, immune cell marker genes, and ligand-receptor gene data, we constructed a multilayer network. Then, the genes in the network and the genes in TCGA were used to construct the WGCNA network, which screened out prognosis-associated genes for subsequent analysis. Finally, a prognostic risk scoring model was obtained, and CPTAC data showed that the effectiveness of this model was good. A nomogram based on the predictive model for predicting the overall survival was established, and internal validation was performed well. Our findings suggest that the predictive model built and based on the immune cell scRNA-seq will enable us to judge the prognosis of patients with ccRCC and provide more accurate directions for basic relevant research and clinical practice.

Cellular heterogeneity and stem cells of vascular endothelial cells in blood vessel formation and homeostasis: Insights from single-cell RNA sequencing

Vascular endothelial cells (ECs) that constitute the inner surface of blood vessels are essential for new vessel formation and organ homeostasis. ECs display remarkable phenotypic heterogeneity across different organs and the vascular tree during angiogenesis and homeostasis. Recent advances in single cell RNA sequencing (scRNA-seq) technologies have allowed a new understanding of EC heterogeneity in both mice and humans. In particular, scRNA-seq has identified new molecular signatures for arterial, venous and capillary ECs in different organs, as well as previously unrecognized specialized EC subtypes, such as the aerocytes localized in the alveolar capillaries of the lung. scRNA-seq has also revealed the gene expression profiles of specialized tissue-resident EC subtypes that are capable of clonal expansion and contribute to adult angiogenesis, a process of new vessel formation from the pre-existing vasculature. These specialized tissue-resident ECs have been identified in various different mouse tissues, including aortic endothelium, liver, heart, lung, skin, skeletal muscle, retina, choroid, and brain. Transcription factors and signaling pathways have also been identified in the specialized tissue-resident ECs that control angiogenesis. Furthermore, scRNA-seq has also documented responses of ECs in diseases such as cancer, age-related macular degeneration, Alzheimer's disease, atherosclerosis, and myocardial infarction. These new findings revealed by scRNA-seq have the potential to provide new therapeutic targets for different diseases associated with blood vessels. In this article, we summarize recent advances in the understanding of the vascular endothelial cell heterogeneity and endothelial stem cells associated with angiogenesis and homeostasis in mice and humans, and we discuss future prospects for the application of scRNA-seq technology.

Identification of ARMH4 and WIPF3 as human podocyte proteins with potential roles in immunomodulation and cytoskeletal dynamics

The podocyte is a specialized cell type critically involved in maintaining the selective filtration barrier of the kidney. Podocytes are primary or secondary targets for a multitude of kidney diseases. Despite intense investigation, the transcriptome and proteome of human podocytes remain incompletely characterized. Here, we analyzed publicly available RNA-Seq data from human kidneys (n = 85) to computationally identify potential novel podocyte markers. For confirmation, we used an online histology resource followed by in-house staining of human kidneys and biochemical fractionation of glomeruli. Initial characterization of the novel podocyte transcripts was performed using viral overexpression and mRNA silencing. Several previously unrecognized gene products were identified that correlated to established podocyte markers on the RNA level and that were histologically localized to podocytes. ARMH4 (a.k.a. UT2 or C14orf37) and WIPF3 (a.k.a CR16) were among the hits. We show that these transcripts increase in response to overexpression of the podocyte transcription factor LMX1B. Overexpression of ARMH4 from low endogenous levels in primary kidney epithelial cells reduced the release of the inflammatory mediators IL-1B and IL-8 (CXCL8). The opposite effect was seen in mature human podocytes when ARMH4 was silenced. Overexpression of WIPF3 stabilized N-WASP, known to be required for maintenance of podocyte foot processes, and increased cell motility as shown using a scratch assay. Moreover, data from normal and diseased human kidneys showed that ARMH4 was downregulated in glomerular pathologies, while WIPF3 remained constantly expressed. ARMH4 and WIPF3 are new potential markers of human podocytes, where they may modulate inflammatory insults by controlling cytokine release and contribute to cytoskeletal dynamics, respectively.

New insights into fibrotic signaling in renal cell carcinoma

Fibrotic signaling plays a pivotal role in the development and progression of solid cancers including renal cell carcinoma (RCC). Intratumoral fibrosis (ITF) and pseudo-capsule (PC) fibrosis are significantly correlated to the disease progression of renal cell carcinoma. Targeting classic fibrotic signaling processes such as TGF-β signaling and epithelial-to-mesenchymal transition (EMT) shows promising antitumor effects both preclinically and clinically. Therefore, a better understanding of the pathogenic mechanisms of fibrotic signaling in renal cell carcinoma at molecular resolution can facilitate the development of precision therapies against solid cancers. In this review, we systematically summarized the latest updates on fibrotic signaling, from clinical correlation and molecular mechanisms to its therapeutic strategies for renal cell carcinoma. Importantly, we examined the reported fibrotic signaling on the human renal cell carcinoma dataset at the transcriptome level with single-cell resolution to assess its translational potential in the clinic.

A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data

MOTIVATION

Single-cell multimodal assays allow us to simultaneously measure two different molecular features of the same cell, enabling new insights into cellular heterogeneity, cell development and diseases. However, most existing methods suffer from inaccurate dimensionality reduction for the joint-modality data, hindering their discovery of novel or rare cell subpopulations.

RESULTS

Here, we present VIMCCA, a computational framework based on variational-assisted multi-view canonical correlation analysis to integrate paired multimodal single-cell data. Our statistical model uses a common latent variable to interpret the common source of variances in two different data modalities. Our approach jointly learns an inference model and two modality-specific non-linear models by leveraging variational inference and deep learning. We perform VIMCCA and compare it with 10 existing state-of-the-art algorithms on four paired multi-modal datasets sequenced by different protocols. Results demonstrate that VIMCCA facilitates integrating various types of joint-modality data, thus leading to more reliable and accurate downstream analysis. VIMCCA improves our ability to identify novel or rare cell subtypes compared to existing widely used methods. Besides, it can also facilitate inferring cell lineage based on joint-modality profiles.

AVAILABILITY AND IMPLEMENTATION

The VIMCCA algorithm has been implemented in our toolkit package scbean (≥0.5.0), and its code has been archived at https://github.com/jhu99/scbean under MIT license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Single-cell analysis of multiple cancer types reveals differences in endothelial cells between tumors and normal tissues

Endothelial cells (ECs) play an important role in tumor progression. Currently, the main target of anti-angiogenic therapy is the vascular endothelial growth factor (VEGF) pathway. Some patients do benefit from anti-VEGF/VEGFR therapy; however, a large number of patients do not have response or acquire drug resistance after treatment. Moreover, anti-VEGF/VEGFR therapy may lead to nephrotoxicity and cardiovascular-related side effects due to its action on normal ECs. Therefore, it is necessary to identify targets that are specific to tumor ECs and could be applied to various cancer types. We integrated single-cell RNA sequencing data from six cancer types and constructed a multi-cancer EC atlas to decode the characteristic of tumor ECs. We found that tip-like ECs mainly exist in tumor tissues but barely exist in normal tissues. Tip-like ECs are involved in the promotion of tumor angiogenesis and inhibition on anti-tumor immune responses. Moreover, tumor cells, myeloid cells, and pericytes are the main sources of pro-angiogenic factors. High proportion of tip-like ECs is associated with poor prognosis in multiple cancer types. We also identified that prostate-specific membrane antigen (PSMA) is a specific marker for tip-like ECs in all the cancer types we studied. In summary, we demonstrate that tip-like ECs are the main differential EC subcluster between tumors and normal tissues. Tip-like ECs may promote tumor progression through promoting angiogenesis while inhibiting anti-tumor immune responses. PSMA was a specific marker for tip-like ECs, which could be used as a potential target for the diagnosis and treatment of non-prostate cancers.

Single-cell RNA sequencing revealed the liver heterogeneity between egg-laying duck and ceased-laying duck

BACKGROUND

In the late phase of production, ducks untimely cease laying, leading to a lower feed conversion. Liver plays a vital role in the synthesis and transport of yolk materials during egg formation in birds. However, the molecular mechanism of liver in ceased-laying duck is far from clear, higher resolution and deeper analysis is needed. Sing-cell RNA-sequencing of 10 × Genomics platform can help to map the liver single cell gene expression atlas of Shaoxing duck and provide new insights into the liver between egg-laying and ceased-laying ducks.

RESULTS

About 20,000 single cells were profiled and 22 clusters were identified. All the clusters were identified as 6 cell types. The dominant cell type is hepatocyte, accounted for about 60% of all the cells. Of note, the heterogeneity of cells between egg-laying duck and ceased-laying duck mainly occurred in hepatocytes. Cells of cluster 3 and 12 were the unique hepatocyte states of egg-laying ducks, while cells of cluster 0 and 15 were the unique hepatocyte states of ceased-laying ducks. The expression mode of yolk precursor transporters, lipid metabolizing enzymes and fibrinogens were different in hepatocytes between egg-laying duck and ceased-laying duck. APOV1, VTG2, VTG1, APOB, RBP, VTDB and SCD might be activated in egg-laying ducks, while APOA1, APOA4, APOC3, FGB and FGG might be activated in ceased-laying ducks.

CONCLUSIONS

Our study further proofs that APOV1 and APOB play key roles in egg production, rather than APOA1 and APOA4. It is also the first to detect a correlation between the higher expression of APOC3, FGB, FGG and ceased-laying in duck.

Dynamic partitioning of branched-chain amino acids-derived nitrogen supports renal cancer progression

Metabolic reprogramming is critical for tumor initiation and progression. However, the exact impact of specific metabolic changes on cancer progression is poorly understood. Here, we integrate multimodal analyses of primary and metastatic clonally-related clear cell renal cancer cells (ccRCC) grown in physiological media to identify key stage-specific metabolic vulnerabilities. We show that a VHL loss-dependent reprogramming of branched-chain amino acid catabolism sustains the de novo biosynthesis of aspartate and arginine enabling tumor cells with the flexibility of partitioning the nitrogen of the amino acids depending on their needs. Importantly, we identify the epigenetic reactivation of argininosuccinate synthase (ASS1), a urea cycle enzyme suppressed in primary ccRCC, as a crucial event for metastatic renal cancer cells to acquire the capability to generate arginine, invade in vitro and metastasize in vivo. Overall, our study uncovers a mechanism of metabolic flexibility occurring during ccRCC progression, paving the way for the development of novel stage-specific therapies.

scDSSC: Deep Sparse Subspace Clustering for scRNA-seq Data

Single cell RNA sequencing (scRNA-seq) enables researchers to characterize transcriptomic profiles at the single-cell resolution with increasingly high throughput. Clustering is a crucial step in single cell analysis. Clustering analysis of transcriptome profiled by scRNA-seq can reveal the heterogeneity and diversity of cells. However, single cell study still remains great challenges due to its high noise and dimension. Subspace clustering aims at discovering the intrinsic structure of data in unsupervised fashion. In this paper, we propose a deep sparse subspace clustering method scDSSC combining noise reduction and dimensionality reduction for scRNA-seq data, which simultaneously learns feature representation and clustering via explicit modelling of scRNA-seq data generation. Experiments on a variety of scRNA-seq datasets from thousands to tens of thousands of cells have shown that scDSSC can significantly improve clustering performance and facilitate the interpretability of clustering and downstream analysis. Compared to some popular scRNA-deq analysis methods, scDSSC outperformed state-of-the-art methods under various clustering performance metrics.

Microbiota-host crosstalk in the newborn and adult rumen at single-cell resolution

BACKGROUND

The rumen is the hallmark organ of ruminants, playing a vital role in their nutrition and providing products for humans. In newborn suckling ruminants milk bypasses the rumen, while in adults this first chamber of the forestomach has developed to become the principal site of microbial fermentation of plant fibers. With the advent of single-cell transcriptomics, it is now possible to study the underlying cell composition of rumen tissues and investigate how this relates the development of mutualistic symbiosis between the rumen and its epithelium-attached microbes.

RESULTS

We constructed a comprehensive cell landscape of the rumen epithelium, based on single-cell RNA sequencing of 49,689 high-quality single cells from newborn and adult rumen tissues. Our single-cell analysis identified six immune cell subtypes and seventeen non-immune cell subtypes of the rumen. On performing cross-species analysis of orthologous genes expressed in epithelial cells of cattle rumen and the human stomach and skin, we observed that the species difference overrides any cross-species cell-type similarity. Comparing adult with newborn cattle samples, we found fewer epithelial cell subtypes and more abundant immune cells, dominated by T helper type 17 cells in the rumen tissue of adult cattle. In newborns, there were more fibroblasts and myofibroblasts, an IGFBP3+ epithelial cell subtype not seen in adults, while dendritic cells were the most prevalent immune cell subtype. Metabolism-related functions and the oxidation-reduction process were significantly upregulated in adult rumen epithelial cells. Using 16S rDNA sequencing, fluorescence in situ hybridization, and absolute quantitative real-time PCR, we found that epithelial Desulfovibrio was significantly enriched in the adult cattle. Integrating the microbiome and metabolome analysis of rumen tissues revealed a high co-occurrence probability of Desulfovibrio with pyridoxal in the adult cattle compared with newborn ones while the scRNA-seq data indicated a stronger ability of pyroxidal binding in the adult rumen epithelial cell subtypes. These findings indicate that Desulfovibrio and pyridoxal likely play important roles in maintaining redox balance in the adult rumen.

CONCLUSIONS

Our integrated multi-omics analysis provides novel insights into rumen development and function and may facilitate the future precision improvement of rumen function and milk/meat production in cattle.

Mapping single-cell transcriptomes in the intra-tumoral and associated territories of kidney cancer

Tumor behavior is intricately dependent on the oncogenic properties of cancer cells and their multi-cellular interactions. To understand these dependencies within the wider microenvironment, we studied over 270,000 single-cell transcriptomes and 100 microdissected whole exomes from 12 patients with kidney tumors, prior to validation using spatial transcriptomics. Tissues were sampled from multiple regions of the tumor core, the tumor-normal interface, normal surrounding tissues, and peripheral blood. We find that the tissue-type location of CD8+ T cell clonotypes largely defines their exhaustion state with intra-tumoral spatial heterogeneity that is not well explained by somatic heterogeneity. De novo mutation calling from single-cell RNA-sequencing data allows us to broadly infer the clonality of stromal cells and lineage-trace myeloid cell development. We report six conserved meta-programs that distinguish tumor cell function, and find an epithelial-mesenchymal transition meta-program highly enriched at the tumor-normal interface that co-localizes with IL1B-expressing macrophages, offering a potential therapeutic target.

Secuer: Ultrafast, scalable and accurate clustering of single-cell RNA-seq data

Identifying cell clusters is a critical step for single-cell transcriptomics study. Despite the numerous clustering tools developed recently, the rapid growth of scRNA-seq volumes prompts for a more (computationally) efficient clustering method. Here, we introduce Secuer, a Scalable and Efficient speCtral clUstERing algorithm for scRNA-seq data. By employing an anchor-based bipartite graph representation algorithm, Secuer enjoys reduced runtime and memory usage over one order of magnitude for datasets with more than 1 million cells. Meanwhile, Secuer also achieves better or comparable accuracy than competing methods in small and moderate benchmark datasets. Furthermore, we showcase that Secuer can also serve as a building block for a new consensus clustering method, Secuer-consensus, which again improves the runtime and scalability of state-of-the-art consensus clustering methods while also maintaining the accuracy. Overall, Secuer is a versatile, accurate, and scalable clustering framework suitable for small to ultra-large single-cell clustering tasks.

Impact of the Human Cell Atlas on medicine

Single-cell atlases promise to provide a 'missing link' between genes, diseases and therapies. By identifying the specific cell types, states, programs and contexts where disease-implicated genes act, we will understand the mechanisms of disease at the cellular and tissue levels and can use this understanding to develop powerful disease diagnostics; identify promising new drug targets; predict their efficacy, toxicity and resistance mechanisms; and empower new kinds of therapies, from cancer therapies to regenerative medicine. Here, we lay out a vision for the potential of cell atlases to impact the future of medicine, and describe how advances over the past decade have begun to realize this potential in common complex diseases, infectious diseases (including COVID-19), rare diseases and cancer.

The tumor microenvironment and immune targeting therapy in pediatric renal tumors

This review highlights the role of several immunomodulating elements contributing to the tumor microenvironment of various pediatric renal tumors including Wilms tumor. The roles of innate and adaptive immune cells in renal tumors are summarized as well as immunomodulatory cytokines and other proteins. The expression and the predictive role of checkpoint modulators like PD-L1 and immunomodulating proteins like glypican-3, B7-H3, COX-2 are highlighted with a translational view toward potential therapeutic innovations. We further discuss the current state of preclinical models in advancing this field of study. Finally, examples of clinical trials of immunomodulating strategies such as monoclonal antibodies and chimeric antigen receptor T (CAR-T) cells for relapsed/refractory/progressive pediatric renal tumors are described.

Delineating the dynamic evolution from preneoplasia to invasive lung adenocarcinoma by integrating single-cell RNA sequencing and spatial transcriptomics

The cell ecology and spatial niche implicated in the dynamic and sequential process of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) have not yet been elucidated. Here, we performed an integrative analysis of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to characterize the cell atlas of the invasion trajectory of LUAD. We found that the UBE2C + cancer cell subpopulation constantly increased during the invasive process of LUAD with remarkable elevation in IAC, and its spatial distribution was in the peripheral cancer region of the IAC, representing a more malignant phenotype. Furthermore, analysis of the TME cell type subpopulation showed a constant decrease in mast cells, monocytes, and lymphatic endothelial cells, which were implicated in the whole process of invasive LUAD, accompanied by an increase in NK cells and MALT B cells from AIS to MIA and an increase in Tregs and secretory B cells from MIA to IAC. Notably, for AIS, cancer cells, NK cells, and mast cells were colocalized in the cancer region; however, for IAC, Tregs colocalized with cancer cells. Finally, communication and interaction between cancer cells and TME cell-induced constitutive activation of TGF-β signaling were involved in the invasion of IAC. Therefore, our results reveal the specific cellular information and spatial architecture of cancer cells and TME subpopulations, as well as the cellular interaction between them, which will facilitate the identification and development of precision medicine in the invasive process of LUAD from AIS to IAC.

Single-cell-resolution transcriptome map revealed novel genes involved in testicular germ cell progression and somatic cells specification in Chinese tongue sole with sex reversal

Female-to-male sex reversals (pseudomales) are common in lower vertebrates and have been found in natural populations, which is a concern under rapid changes in environmental conditions. Pseudomales can exhibit altered spermatogenesis. However, the regulatory mechanisms underlying pseudomale spermatogenesis remain unclear. Here, we characterized spermatogenesis in Chinese tongue sole (Cynoglossus semilaevis), a species with genetic and environmental sex determination, based on a high-resolution single-cell RNA-seq atlas of cells derived from the testes of genotypic males and pseudomales. We identified five germ cell types and six somatic cell types and obtained a single-cell atlas of dynamic changes in gene expression during spermatogenesis in Chinese tongue sole, including alterations in pseudomales. We detected decreased levels of Ca²⁺ signaling pathway-related genes in spermatogonia, insufficient meiotic initiation in spermatocytes, and a malfunction of somatic niche cells in pseudomales. However, a cluster of CaSR genes and MAPK signaling factors were upregulated in undifferentiated spermatogonia of pseudomales. Additionally, we revealed that Z chromosome-specific genes, such as piwil2, dhx37, and ehmt1, were important for spermatogenesis. These results improve our understanding of reproduction after female-to-male sex-reversal and provide new insights into the adaptability of reproductive strategies in lower vertebrates.

Defining the origin, evolution, and immune composition of SDH-deficient renal cell carcinoma

Succinate dehydrogenase (SDH)-deficient renal cell carcinoma represents a rare subtype of hereditary kidney cancer. Clinical diagnosis can be challenging and there is little evidence to guide systemic therapeutic options. We performed genomic profiling of a cohort of tumors through the analysis of whole genomes, transcriptomes, as well as flow cytometry and immunohistochemistry in order to gain a deeper understanding of their molecular biology. We find neutral evolution after early tumor activation with a lack of secondary driver events. We show that these tumors have epithelial derivation, possibly from the macula densa, a specialized paracrine cell of the renal juxtaglomerular apparatus. They subsequently develop into immune excluded tumors. We provide transcriptomic and protein expression evidence of a highly specific tumor marker, PAPPA2. These translational findings have implications for the diagnosis and treatment for this rare tumor subtype.

Early Molecular Events Mediating Loss of Aquaporin-2 during Ureteral Obstruction in Rats

BACKGROUND

Ureteral obstruction is marked by disappearance of the vasopressin-dependent water channel aquaporin-2 (AQP2) in the renal collecting duct and polyuria upon reversal. Most studies of unilateral ureteral obstruction (UUO) models have examined late time points, obscuring the early signals that trigger loss of AQP2.

METHODS

We performed RNA-Seq on microdissected rat cortical collecting ducts (CCDs) to identify early signaling pathways after establishment of UUO.

RESULTS

Vasopressin V2 receptor (AVPR2) mRNA was decreased 3 hours after UUO, identifying one cause of AQP2 loss. Collecting duct principal cell differentiation markers were lost, including many not regulated by vasopressin. Immediate early genes in CCDs were widely induced 3 hours after UUO, including Myc, Atf3, and Fos (confirmed at the protein level). Simultaneously, expression of NF-κB signaling response genes known to repress Aqp2 increased. RNA-Seq for CCDs at an even earlier time point (30 minutes) showed widespread mRNA loss, indicating a "stunned" profile. Immunocytochemical labeling of markers of mRNA-degrading P-bodies DDX6 and 4E-T indicated an increase in P-body formation within 30 minutes.

CONCLUSIONS

Immediately after establishment of UUO, collecting ducts manifest a stunned state with broad disappearance of mRNAs. Within 3 hours, there is upregulation of immediate early and inflammatory genes and disappearance of the V2 vasopressin receptor, resulting in loss of AQP2 (confirmed by lipopolysaccharide administration). The inflammatory response seen rapidly after UUO establishment may be relevant to both UUO-induced polyuria and long-term development of fibrosis in UUO kidneys.

Genomic Characteristics and Single-Cell Profiles After Immunotherapy in Fumarate Hydratase-Deficient Renal Cell Carcinoma

PURPOSE

Fumarate hydratase-deficient renal cell carcinoma (FHRCC) is highly malignant, but the urgent need for effective treatment remains unmet. We aimed to analyze the genomic characteristics and microenvironment of FHRCC and the cause of heterogeneous response to immune checkpoint inhibitor (ICI)-based treatment at single-cell level.

EXPERIMENTAL DESIGN

Whole-exome sequencing and IHC staining analyses were performed in 30 advanced FHRCC patients. Single-cell RNA sequencing following ICI-based treatment was conducted in 4 patients. The clinical characteristics, therapeutic effect, and follow-up data were analyzed.

RESULTS

The median tumor mutation burden was only 0.14 mutations per megabase. IHC staining showed an immune-active tumor microenvironment characterized by extensive CD8+ T-cell infiltration. ATM expression was inversely correlated with percentage of tumor-infiltrating CD8+ T cells. Trajectory analysis indicated gradually upregulated exhausted markers and an increased apoptotic trend of CD8+ T cells despite continuous exposure to ICI-based treatment. ICI-based treatment was associated with improved overall response rate (17.6% vs. 0%, P = 0.046) and disease control rate (DCR; 64.7% vs. 12.5%, P = 0.004) compared with tyrosine kinase inhibitor. Among patients with germline mutation, the ORR (16.7% vs. 0%, P = 0.086) and the DCR (66.7% vs. 14.3%, P = 0.011) were higher after ICI-based treatment.

CONCLUSIONS

Immune infiltration is frequent in FHRCC. ICI-based treatment is a promising regimen, and treatment response depends on the functional status of tumor-infiltrating lymphocytes. ICI-based treatment cannot reverse the exhaustion of CD8+ T cells in patients with progressive disease, highlighting the need for additional therapeutic strategies.

Pyroptosis-Related Gene Signature Predicts the Prognosis of ccRCC Using TCGA and Single-Cell RNA Seq Database

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal carcinoma, which is not sensitive to both radiotherapy and chemotherapy. The objective response rate of metastatic renal cancer to targeted drugs and immunotherapy is unsatisfactory. Pyroptosis, proven as an inflammatory form of programmed cell death, could be activated by some inflammasomes, while could create a tumor-suppressing environment by releasing inflammatory factors in the tumor. To explore indicators predicting the prognosis of ccRCC and the effect of antitumor therapy, we constructed a pyroptosis risk model containing 4 genes after 11 pyroptosis-related genes of 516 ccRCC cases in the TCGA database were scanned. Based on the risk score, 516 ccRCC cases were divided into two groups for functional enrichment analysis and immune profile to seek functional pathways and potential therapeutic targets. Besides, those results were verified in GSE29609 and single-cell transcriptomic data. The study suggests that the conducted pyroptosis model could predict the prognosis of ccRCC and reflect the immune microenvironment, which may help in immune checkpoint inhibitor treatment.

Cellular milieu in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is globally the most prevalent renal cancer. The cells of origin in ccRCC have been identified as proximal tubular epithelial cells (PTEC); however, the transcriptomic pathways resulting in the transition from normal to malignant PTEC state have remained unclear. Immunotherapy targeting checkpoints have revolutionized the management of ccRCC, but a sustained clinical response is achieved in only a minority of ccRCC patients. This indicates that our understanding of the mechanisms involved in the malignant transition and resistance to immune checkpoint therapy in ccRCC is unclear. This review examines recent single-cell transcriptomics studies of ccRCC to clarify the transition of PTEC in ccRCC development, and the immune cell types, states, and interactions that may limit the response to targeted immune therapy, and finally suggests stromal cells as key drivers in recurrent and locally invasive ccRCC. These and future single-cell transcriptomics studies will continue to clarify the cellular milieu in the ccRCC microenvironment, thus defining actional clinical, therapeutic, and prognostic characteristics of ccRCC.

Spatial maps of T cell receptors and transcriptomes reveal distinct immune niches and interactions in the adaptive immune response

T cells mediate antigen-specific immune responses to disease through the specificity and diversity of their clonotypic T cell receptors (TCRs). Determining the spatial distributions of T cell clonotypes in tissues is essential to understanding T cell behavior, but spatial sequencing methods remain unable to profile the TCR repertoire. Here, we developed Slide-TCR-seq, a 10-μm-resolution method, to sequence whole transcriptomes and TCRs within intact tissues. We confirmed the ability of Slide-TCR-seq to map the characteristic locations of T cells and their receptors in mouse spleen. In human lymphoid germinal centers, we identified spatially distinct TCR repertoires. Profiling T cells in renal cell carcinoma and melanoma specimens revealed heterogeneous immune responses: T cell states and infiltration differed intra- and inter-clonally, and adjacent tumor and immune cells exhibited distinct gene expression. Altogether, our method yields insights into the spatial relationships between clonality, neighboring cell types, and gene expression that drive T cell responses.

A Targetable Myeloid Inflammatory State Governs Disease Recurrence in Clear-Cell Renal Cell Carcinoma

It is poorly understood how the tumor immune microenvironment influences disease recurrence in localized clear-cell renal cell carcinoma (ccRCC). Here we performed whole-transcriptomic profiling of 236 tumors from patients assigned to the placebo-only arm of a randomized, adjuvant clinical trial for high-risk localized ccRCC. Unbiased pathway analysis identified myeloid-derived IL6 as a key mediator. Furthermore, a novel myeloid gene signature strongly correlated with disease recurrence and overall survival on uni- and multivariate analyses and is linked to TP53 inactivation across multiple data sets. Strikingly, effector T-cell gene signatures, infiltration patterns, and exhaustion markers were not associated with disease recurrence. Targeting immunosuppressive myeloid inflammation with an adenosine A2A receptor antagonist in a novel, immunocompetent, Tp53-inactivated mouse model significantly reduced metastatic development. Our findings suggest that myeloid inflammation promotes disease recurrence in ccRCC and is targetable as well as provide a potential biomarker-based framework for the design of future immuno-oncology trials in ccRCC.

SIGNIFICANCE

Improved understanding of factors that influence metastatic development in localized ccRCC is greatly needed to aid accurate prediction of disease recurrence, clinical decision-making, and future adjuvant clinical trial design. Our analysis implicates intratumoral myeloid inflammation as a key driver of metastasis in patients and a novel immunocompetent mouse model. This article is highlighted in the In This Issue feature, p. 2221.

From multitude to singularity: An up-to-date overview of scRNA-seq data generation and analysis

Single cell RNA sequencing (scRNA-seq) is today a common and powerful technology in biomedical research settings, allowing to profile the whole transcriptome of a very large number of individual cells and reveal the heterogeneity of complex clinical samples. Traditionally, cells have been classified by their morphology or by expression of certain proteins in functionally distinct settings. The advent of next generation sequencing (NGS) technologies paved the way for the detection and quantitative analysis of cellular content. In this context, transcriptome quantification techniques made their advent, starting from the bulk RNA sequencing, unable to dissect the heterogeneity of a sample, and moving to the first single cell techniques capable of analyzing a small number of cells (1-100), arriving at the current single cell techniques able to generate hundreds of thousands of cells. As experimental protocols have improved rapidly, computational workflows for processing the data have also been refined, opening up to novel methods capable of scaling computational times more favorably with the dataset size and making scRNA-seq much better suited for biomedical research. In this perspective, we will highlight the key technological and computational developments which have enabled the analysis of this growing data, making the scRNA-seq a handy tool in clinical applications.

The genetic basis of congenital anomalies of the kidney and urinary tract

During the past decades, remarkable progress has been made in our understanding of the molecular basis of kidney diseases, as well as in the ability to pinpoint disease-causing genetic changes. Congenital anomalies of the kidney and urinary tract (CAKUT) are remarkably diverse, and may be either isolated to the kidney or involve other systems, and are notorious in their variable genotype-phenotype correlations. Genetic conditions underlying CAKUT are individually rare, but collectively contribute to disease etiology in ~ 16% of children with CAKUT. In this review, we will discuss basic concepts of kidney development and genetics, common causes of monogenic CAKUT, and the approach to diagnosing and managing a patient with suspected monogenic CAKUT. Altogether, the concepts presented herein represent an introduction to the emergence of nephrogenetics, a fast-growing multi-disciplinary field that is focused on deciphering the causes and manifestations of genetic kidney diseases as well as providing the framework for managing patients with genetic forms of CAKUT.

Oncofetal reprogramming in tumour development and progression

Embryonic development is characterized by rapidly dividing cells, cellular plasticity and a highly vascular microenvironment. These features are similar to those of tumour tissue, in that malignant cells are characterized by their ability to proliferate and exhibit cellular plasticity. The tumour microenvironment also often includes immunosuppressive features. Reciprocal communication between various cellular subpopulations enables fetal and tumour tissues to proliferate, migrate and escape immune responses. Fetal-like reprogramming has been demonstrated in the tumour microenvironment, indicating extraordinary cellular plasticity and bringing an additional layer of cellular heterogeneity. More importantly, some of these features are also present during inflammation. This Perspective discusses the similarity between embryogenesis, inflammation and tumorigenesis, and describes the mechanisms of oncofetal reprogramming that enable tumour cells to escape from immune responses, promoting tumour growth and metastasis.

Accurate detection of benign and malignant renal tumor subtypes with MethylBoostER: An epigenetic marker-driven learning framework

Current gold standard diagnostic strategies are unable to accurately differentiate malignant from benign small renal masses preoperatively; consequently, 20% of patients undergo unnecessary surgery. Devising a more confident presurgical diagnosis is key to improving treatment decision-making. We therefore developed MethylBoostER, a machine learning model leveraging DNA methylation data from 1228 tissue samples, to classify pathological subtypes of renal tumors (benign oncocytoma, clear cell, papillary, and chromophobe RCC) and normal kidney. The prediction accuracy in the testing set was 0.960, with class-wise ROC AUCs >0.988 for all classes. External validation was performed on >500 samples from four independent datasets, achieving AUCs >0.89 for all classes and average accuracies of 0.824, 0.703, 0.875, and 0.894 for the four datasets. Furthermore, consistent classification of multiregion samples (N = 185) from the same patient demonstrates that methylation heterogeneity does not limit model applicability. Following further clinical studies, MethylBoostER could facilitate a more confident presurgical diagnosis to guide treatment decision-making in the future.

A transcriptional metastatic signature predicts survival in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer in adults. When ccRCC is localized to the kidney, surgical resection or ablation of the tumor is often curative. However, in the metastatic setting, ccRCC remains a highly lethal disease. Here we use fresh patient samples that include treatment-naive primary tumor tissue, matched adjacent normal kidney tissue, as well as tumor samples collected from patients with bone metastases. Single-cell transcriptomic analysis of tumor cells from the primary tumors reveals a distinct transcriptional signature that is predictive of metastatic potential and patient survival. Analysis of supporting stromal cells within the tumor environment demonstrates vascular remodeling within the endothelial cells. An in silico cell-to-cell interaction analysis highlights the CXCL9/CXCL10-CXCR3 axis and the CD70-CD27 axis as potential therapeutic targets. Our findings provide biological insights into the interplay between tumor cells and the ccRCC microenvironment.

Identification of Diagnostic Genes and Effective Drugs Associated with Osteoporosis Treatment by Single-Cell RNA-Seq Analysis and Network Pharmacology

Background

Osteoporosis is a common bone metabolic disease with increased bone fragility and fracture rate. Effective diagnosis and treatment of osteoporosis still need to be explored due to the increasing incidence of disease.

Methods

Single-cell RNA-seq was acquired from GSE147287 dataset. Osteoporosis-related genes were obtained from chEMBL. Cell subpopulations were identified and characterized by scRNA-seq, t-SNE, clusterProfiler, and other computational methods. “limma” R packages were used to identify all differentially expressed genes. A diagnosis model was build using rms R packages. Key drugs were determined by proteins-proteins interaction and molecular docking.

Results

Firstly, 15,577 cells were obtained, and 12 cell subpopulations were identified by clustering, among which 6 cell subpopulations belong to CD45+ BM-MSCs and the other subpopulations were CD45-BM-MSCs. CD45- BM-MSCs_6 and CD45+ BM-MSCs_5 were consider as key subpopulations. Furthermore, we found 7 genes were correlated with above two subpopulations, and F9 gene had highest AUC. Finally, five compounds were identified, among which DB03742 bound well to F9 protein.

Conclusions

This work discovered that 7 genes were correlated with CD45-BM-MSCs_6 and CD45+ BM-MSCs_5 subpopulations in osteoporosis, among which F9 gene had better research value. Moreover, compound DB03742 was a potential inhibitor of F9 protein.

HTCA: a database with an in-depth characterization of the single-cell human transcriptome

Single-cell RNA-sequencing (scRNA-seq) is one of the most used single-cell omics in recent decades. The exponential growth of single-cell data has immense potential for large-scale integration and in-depth explorations that are more representative of the study population. Efforts have been made to consolidate published data, yet extensive characterization is still lacking. Many focused on raw-data database constructions while others concentrate mainly on gene expression queries. Hereby, we present HTCA (www.htcatlas.org), an interactive database constructed based on ∼2.3 million high-quality cells from ∼3000 scRNA-seq samples and comprised in-depth phenotype profiles of 19 healthy adult and matching fetal tissues. HTCA provides a one-stop interactive query to gene signatures, transcription factor (TF) activities, TF motifs, receptor-ligand interactions, enriched gene ontology (GO) terms, etc. across cell types in adult and fetal tissues. At the same time, HTCA encompasses single-cell splicing variant profiles of 16 adult and fetal tissues, spatial transcriptomics profiles of 11 adult and fetal tissues, and single-cell ATAC-sequencing (scATAC-seq) profiles of 27 adult and fetal tissues. Besides, HTCA provides online analysis tools to perform major steps in a typical scRNA-seq analysis. Altogether, HTCA allows real-time explorations of multi-omics adult and fetal phenotypic profiles and provides tools for a flexible scRNA-seq analysis.

FDX1 expression predicts favourable prognosis in clear cell renal cell carcinoma identified by bioinformatics and tissue microarray analysis

Ferredoxin 1 (FDX1), an iron-sulphur protein, is responsible for electron transfer in a range of metabolic redox reactions. Clear cell renal cell carcinoma (ccRCC) is an aggressive cancer characterised by metabolic reprogramming, and FDX1 is a critical regulator of cuproptosis. However, the expression profile and prognostic value of FDX1 associated with clinicopathological features in ccRCC remain largely unelucidated. In this study, we integrated a series of public bioinformatic analysis to explore the mRNA and protein profiles of FDX1 across human cancers and cell lines and validated its expression and prognostic value, especially in ccRCC. In this study, FDX1 mRNA and protein expression were aberrantly downregulated and associated with ccRCC grade, stage, and nodal metastasis, whereas in adjacent non-tumour kidney tissue, it was abundantly expressed and cytoplasmically localised in renal tubular epithelial cells. Multivariate analysis indicated that low FDX1 expression contributed to unfavourable overall and disease-free survival. The functional enrichment of FDX1 co-expressed genes in ccRCC involved mainly mitochondrial dysfunction in various metabolic processes and biological oxidation, besides iron-sulphur cluster biogenesis. Furthermore, FDX1 modulates immunological infiltration to affect prognosis. Thus, FDX1 downregulation is mechanistically because of ccRCC tumourigenesis and is a promising prognostic biomarker to stratify patients with ccRCC.

Integrated TCR repertoire analysis and single-cell transcriptomic profiling of tumor-infiltrating T cells in renal cell carcinoma identifies shared and tumor-restricted expanded clones with unique phenotypes

Objective responses of metastatic renal cell carcinoma (RCC) associated with systemic immunotherapies suggest the potential for T-cell-mediated tumor clearance. Recent analyses associate clonally expanded T cells present in the tumor at diagnosis with responses to immune checkpoint inhibitors (ICIs). To identify and further characterize tumor-associated, clonally expanded T cells, we characterized the density, spatial distribution, T-cell receptor (TCR) repertoire, and transcriptome of tumor-infiltrating T cells from 14 renal tumors at the time of resection and compared them with T cells in peripheral blood and normal adjacent kidney. Multiplex immunohistochemistry revealed that T-cell density was higher in clear cell RCC (ccRCC) than in other renal tumor histologies with spatially nonuniform T-cell hotspots and exclusion zones. TCR repertoire analysis also revealed increased clonal expansion in ccRCC tumors compared with non-clear cell histologies or normal tissues. Expanded T-cell clones were most frequently CD8+ with some detectable in peripheral blood or normal kidney and others found exclusively within the tumor. Divergent expression profiles for chemokine receptors and ligands and the Ki67 proliferation marker distinguished tumor-restricted T-cell clones from those also present in blood suggesting a distinct phenotype for subsets of clonally expanded T cells that also differed for upregulated markers of T-cell activation and exhaustion. Thus, our single-cell level stratification of clonally expanded tumor infiltrating T-cell subpopulations provides a framework for further analysis. Future studies will address the spatial orientation of these clonal subsets within tumors and their association with treatment outcomes for ICIs or other therapeutic modalities.

Precise identification of cancer cells from allelic imbalances in single cell transcriptomes

A fundamental step of tumour single cell mRNA analysis is separating cancer and non-cancer cells. We show that the common approach to separation, using shifts in average expression, can lead to erroneous biological conclusions. By contrast, allelic imbalances representing copy number changes directly detect the cancer genotype and accurately separate cancer from non-cancer cells. Our findings provide a definitive approach to identifying cancer cells from single cell mRNA sequencing data.

The identification of cancer cells from single cell transcriptomes can be improved by detecting allelic imbalances due to copy number changes.

m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear.

Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity.

Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib.

Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.

The Extracellular Matrix Environment of Clear Cell Renal Cell Carcinoma

Simple Summary

The extracellular matrix (ECM) controls fundamental properties of tumors, including growth, blood vessel investment, and invasion. The ECM defines rigidity of tumor tissue and individual ECM proteins have distinct biological effects on tumor cells. This article reviews the composition and biological functions of the ECM of clear cell renal cell carcinoma (ccRCC). The most frequent initiating genetic mutation in ccRCC inactivates the VHL gene, which plays a direct role in organizing the ECM. This is predicted to result in local ECM modification, which promotes the growth of tumor cells and the invasion of blood vessels. Later in tumor growth, connective tissue cells are recruited, which are predicted to produce large amounts of ECM, affecting the growth and invasive behaviors of tumor cells. Strategies to therapeutically control the ECM are under active investigation and a better understanding of the ccRCC ECM will determine the applicability of ECM-modifying drugs to this type of cancer.

Abstract

The extracellular matrix (ECM) of tumors is a complex mix of components characteristic of the tissue of origin. In the majority of clear cell renal cell carcinomas (ccRCCs), the tumor suppressor VHL is inactivated. VHL controls matrix organization and its loss promotes a loosely organized and angiogenic matrix, predicted to be an early step in tumor formation. During tumor evolution, cancer-associated fibroblasts (CAFs) accumulate, and they are predicted to produce abundant ECM. The ccRCC ECM composition qualitatively resembles that of the healthy kidney cortex in which the tumor arises, but there are important differences. One is the quantitative difference between a healthy cortex ECM and a tumor ECM; a tumor ECM contains a higher proportion of interstitial matrix components and a lower proportion of basement membrane components. Another is the breakdown of tissue compartments in the tumor with mixing of ECM components that are physically separated in healthy kidney cortex. Numerous studies reviewed in this work reveal effects of specific ECM components on the growth and invasive behaviors of ccRCCs, and extrapolation from other work suggests an important role for ECM in controlling ccRCC tumor rigidity, which is predicted to be a key determinant of invasive behavior.

Extensive patient-to-patient single nucleus transcriptome heterogeneity in pheochromocytomas and paragangliomas

Pheochromocytomas (PC) and paragangliomas (PG) are rare neuroendocrine tumors with varied genetic makeup and are associated with high cardiovascular morbidity and a variable risk of malignancy. The source of the transcriptional heterogeneity of the disease and the underlying biological processes that determine the outcome of PCPG remain largely unclear. We focused on PCPG tumors with germline SDHB and RET mutations, which represent distinct prognostic groups with worse or better prognoses, respectively. We applied single-nuclei RNA sequencing (snRNA-seq) to tissue samples from 11 patients and found high patient-to-patient transcriptome heterogeneity in neuroendocrine tumor cells. The tumor microenvironment also showed heterogeneous profiles, mainly contributed by macrophages of the immune cell clusters and Schwann cells of the stroma. By performing non-negative matrix factorization, we identified common transcriptional programs active in RET and SDHB, as well as distinct modules, including neuronal development, hormone synthesis and secretion, and DNA replication. Similarities between the transcriptomes of the tumor cells and those of the chromaffin- and precursor cell types suggests different developmental stages at which PC and PG tumors appear to be arrested.

Fount, fate, features, and function of renal erythropoietin-producing cells

Renal erythropoietin (Epo)-producing (REP) cells represent a rare and incompletely understood cell type. REP cells are fibroblast-like cells located in close proximity to blood vessels and tubules of the corticomedullary border region. Epo mRNA in REP cells is produced in a pronounced "on-off" mode, showing transient transcriptional bursts upon exposure to hypoxia. In contrast to "ordinary" fibroblasts, REP cells do not proliferate ex vivo, cease to produce Epo, and lose their identity following immortalization and prolonged in vitro culture, consistent with the loss of Epo production following REP cell proliferation during tissue remodelling in chronic kidney disease. Because Epo protein is usually not detectable in kidney tissue, and Epo mRNA is only transiently induced under hypoxic conditions, transgenic mouse models have been developed to permanently label REP cell precursors, active Epo producers, and inactive descendants. Future single-cell analyses of the renal stromal compartment will identify novel characteristic markers of tagged REP cells, which will provide novel insights into the regulation of Epo expression in this unique cell type.

Intrarenal Single-Cell Sequencing of Hepatitis B Virus Associated Membranous Nephropathy

To date, the pathogenesis of hepatitis B virus (HBV)-associated membranous nephropathy (MN) remains elusive. This study aimed to decipher the etiopathogenesis of HBV-associated MN by performing single-cell RNA sequencing (scRNA-seq) of kidney biopsy specimens from a patient with HBV-associated MN and two healthy individuals. We generated 4,114 intrarenal single-cell transcriptomes from the HBV-associated MN patient by scRNA-seq. Compared to healthy individuals, podocytes in the HBV-associated MN patient showed an increased expression of extracellular matrix formation-related genes, including HSPA5, CTGF, and EDIL3. Kidney endothelial cells (ECs) in the HBV-associated MN were enriched in inflammatory pathways, including NF-kappa B signaling, IL-17 signaling, TNF signaling and NOD-like receptor signaling. Gene ontology (GO) functional enrichment analysis and Gene Set Variation Analysis (GSVA) further revealed that differentially expressed genes (DEGs) of ECs from the HBV-associated MN patients were enriched in apoptotic signaling pathway, response to cytokine and leukocyte cell-cell adhesion. The up-regulated DEGs in glomerular ECs of HBV-associated MN patients were involved in biological processes such as viral gene expression, and protein targeting to endoplasmic reticulum. We further verified that the overexpressed genes in ECs from HBV-associated MN were mainly enriched in regulation of protein targeting to endoplasmic reticulum, exocytosis, viral gene expression, IL-6 and IL-1 secretion when compared with anti-phospholipase A2 receptor (PLA2R)-positive idiopathic membranous nephropathy (IMN). The receptor-ligand crosstalk analysis revealed potential interactions between endothelial cells and other cells in HBV-associated-MN. These results offer new insight into the pathogenesis of HBV-associated MN and may identify new therapeutic targets for HBV-associated MN.

Single-cell multiomics analysis reveals regulatory programs in clear cell renal cell carcinoma

The clear cell renal cell carcinoma (ccRCC) microenvironment consists of many different cell types and structural components that play critical roles in cancer progression and drug resistance, but the cellular architecture and underlying gene regulatory features of ccRCC have not been fully characterized. Here, we applied single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) to generate transcriptional and epigenomic landscapes of ccRCC. We identified tumor cell-specific regulatory programs mediated by four key transcription factors (TFs) (HOXC5, VENTX, ISL1, and OTP), and these TFs have prognostic significance in The Cancer Genome Atlas (TCGA) database. Targeting these TFs via short hairpin RNAs (shRNAs) or small molecule inhibitors decreased tumor cell proliferation. We next performed an integrative analysis of chromatin accessibility and gene expression for CD8⁺ T cells and macrophages to reveal the different regulatory elements in their subgroups. Furthermore, we delineated the intercellular communications mediated by ligand–receptor interactions within the tumor microenvironment. Taken together, our multiomics approach further clarifies the cellular heterogeneity of ccRCC and identifies potential therapeutic targets.

Integrated single-cell transcriptomics and proteomics reveal cellular-specific response and microenvironment remodeling in aristolochic acid nephropathy

Aristolochic acid nephropathy (AAN) is characterized by acute proximal tubule necrosis and immune cell infiltration, contributing to the global burden of chronic kidney disease and urothelial cancer. Although the proximal tubule has been defined as the primary target of aristolochic acids I (AAI), the mechanistic underpinning of gross renal deterioration caused by AAI has not been explicitly explained, prohibiting effective therapeutic intervention. To this point, we employed integrated single-cell RNA-Seq, bulk RNA-Seq, and mass spectrometry–based proteomics to analyze the mouse kidney after acute AAI exposure. Our results reveal a dramatic reduction of proximal tubule epithelial cells, associated with apoptotic and inflammatory pathways, indicating permanent damage beyond repair. We found the enriched development pathways in other nephron segments, suggesting activation of reparative programs triggered by AAI. The divergent response may be attributed to the segment-specific distribution of organic anion channels along the nephron, including OAT1 and OAT3. Moreover, we observed dramatic activation and recruitment of cytotoxic T and macrophage M1 cells, highlighting inflammation as a principal contributor to permanent renal injury. Ligand-receptor pairing revealed that critical intercellular crosstalk underpins damage-induced activation of immune cells. These results provide potentially novel insight into the AAI-induced kidney injury and point out possible pathways for future therapeutic intervention.

Spatially Resolved Transcriptomes of Mammalian Kidneys Illustrate the Molecular Complexity and Interactions of Functional Nephron Segments

Available transcriptomes of the mammalian kidney provide limited information on the spatial interplay between different functional nephron structures due to the required dissociation of tissue with traditional transcriptome-based methodologies. A deeper understanding of the complexity of functional nephron structures requires a non-dissociative transcriptomics approach, such as spatial transcriptomics sequencing (ST-seq). We hypothesize that the application of ST-seq in normal mammalian kidneys will give transcriptomic insights within and across species of physiology at the functional structure level and cellular communication at the cell level. Here, we applied ST-seq in six mice and four human kidneys that were histologically absent of any overt pathology. We defined the location of specific nephron structures in the captured ST-seq datasets using three lines of evidence: pathologist's annotation, marker gene expression, and integration with public single-cell and/or single-nucleus RNA-sequencing datasets. We compared the mouse and human cortical kidney regions. In the human ST-seq datasets, we further investigated the cellular communication within glomeruli and regions of proximal tubules-peritubular capillaries by screening for co-expression of ligand-receptor gene pairs. Gene expression signatures of distinct nephron structures and microvascular regions were spatially resolved within the mouse and human ST-seq datasets. We identified 7,370 differentially expressed genes (p adj < 0.05) distinguishing species, suggesting changes in energy production and metabolism in mouse cortical regions relative to human kidneys. Hundreds of potential ligand-receptor interactions were identified within glomeruli and regions of proximal tubules-peritubular capillaries, including known and novel interactions relevant to kidney physiology. Our application of ST-seq to normal human and murine kidneys confirms current knowledge and localization of transcripts within the kidney. Furthermore, the generated ST-seq datasets provide a valuable resource for the kidney community that can be used to inform future research into this complex organ.

Adult Wilms Tumor: Genetic Evidence of Origin of a Subset of Cases From Metanephric Adenoma

The genetics of nephroblastoma (Wilms tumor) occurring in adults is largely unknown, as studies have largely been limited to isolated case reports. We, therefore, studied 14 adult Wilms tumors for genetic alterations, using expanded targeted sequencing on 11 cases. The patients ranged from 17 to 46 years of age (mean and median, 31 y), and there were 8 males and 6 females. Five Wilms tumors harbored BRAF V600E mutations. All of these had better-differentiated areas identical to metanephric adenoma, as has previously been described. In 3 such cases, microdissection studies revealed that the BRAF V600E mutation was present in both the metanephric adenoma and Wilms tumor areas; however, additional genetic alterations (including TERT promoter mutations in 2 cases, ASLX1/ATR mutations in 1 other case) were limited to the Wilms tumor component. These findings suggest that the Wilms tumor developed from the metanephric adenoma. Other adult Wilms tumors harbored genetic alterations previously reported in the more common pediatric Wilms tumors, including WT1 mutations (2 cases), ASLX1 mutations (3 additional cases), NSD2 mutation (1 additional case), and 11p loss (3 cases). In summary, a significant subset of adult Wilms tumors (specifically those of epithelial type with differentiated areas) harbor targetable BRAF V600E mutations and appear to arise from metanephric adenomas as a consequence of additional acquired genetic alterations. Other adult Wilms tumors often harbor genetic alterations found in their more common pediatric counterparts, suggesting at least some similarities in their pathogenesis.

A T cell resilience model associated with response to immunotherapy in multiple tumor types

Despite breakthroughs in cancer immunotherapy, most tumor-reactive T cells cannot persist in solid tumors due to an immunosuppressive environment. We developed Tres (tumor-resilient T cell), a computational model utilizing single-cell transcriptomic data to identify signatures of T cells that are resilient to immunosuppressive signals, such as transforming growth factor-β1, tumor necrosis factor-related apoptosis-inducing ligand and prostaglandin E2. Tres reliably predicts clinical responses to immunotherapy in melanoma, lung cancer, triple-negative breast cancer and B cell malignancies using bulk T cell transcriptomic data from pre-treatment tumors from patients who received immune-checkpoint inhibitors (n = 38), infusion products for chimeric antigen receptor T cell therapies (n = 34) and pre-manufacture samples for chimeric antigen receptor T cell or tumor-infiltrating lymphocyte therapies (n = 84). Further, Tres identified FIBP, whose functions are largely unknown, as the top negative marker of tumor-resilient T cells across many solid tumor types. FIBP knockouts in murine and human donor CD8+ T cells significantly enhanced T cell-mediated cancer killing in in vitro co-cultures. Further, Fibp knockout in murine T cells potentiated the in vivo efficacy of adoptive cell transfer in the B16 tumor model. Fibp knockout T cells exhibit reduced cholesterol metabolism, which inhibits effector T cell function. These results demonstrate the utility of Tres in identifying biomarkers of T cell effectiveness and potential therapeutic targets for immunotherapies in solid tumors.

Patient-derived renal cell carcinoma organoids for personalized cancer therapy

Background

Kidney cancer is one of the most common solid tumors. The advancement of human kidney cancer research and treatment has been hindered by a lack of research models that faithfully recapitulate the diversity of the disease.

Methods

We established an effective three‐dimensional culture system for generating kidney cancer organoids from clinical renal cell carcinoma samples. Renal cell carcinoma (RCC) organoids were characterized by H&E staining, immunofluorescence, whole‐exome sequencing, RNA sequencing and single‐cell RNA sequencing. The use of RCC organoids in personalized cancer therapy was assessed by testing their responses to treatment drugs and chimeric antigen receptor T cells.

Results

Using this organoid culture system, 33 kidney cancer organoid lines from common kidney cancer subtypes, including clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (pRCC), and chromophobe renal cell carcinoma (chRCC), were generated. RCC organoids preserved the histological architectures, mutational landscapes, and transcriptional profile of the parental tumor tissues. Single‐cell RNA‐sequencing revealed inter‐ and intra‐tumoral heterogeneity in RCC organoids. RCC organoids allowed for in vitro drug screening and provided a tool for assessing the efficacy of chimeric antigen receptor T cells.

Conclusions

Patient‐derived RCC organoids are valuable pre‐clinical models for academic research and personalized medicine.