Single-cell analysis reveals immune landscape in kidneys of patients with chronic transplant rejection

Epithelial cell states associated with kidney and allograft injury

The kidney epithelium, with its intricate arrangement of highly specialized cell types, constitutes the functional core of the organ. Loss of kidney epithelium is linked to the loss of functional nephrons and a subsequent decline in kidney function. In kidney transplantation, epithelial injury signatures observed during post-transplantation surveillance are strong predictors of adverse kidney allograft outcomes. However, epithelial injury is currently neither monitored clinically nor addressed therapeutically after kidney transplantation. Several factors can contribute to allograft epithelial injury, including allograft rejection, drug toxicity, recurrent infections and postrenal obstruction. The injury mechanisms that underlie allograft injury overlap partially with those associated with acute kidney injury (AKI) and chronic kidney disease (CKD) in the native kidney. Studies using advanced transcriptomic analyses of single cells from kidney or urine have identified a role for kidney injury-induced epithelial cell states in exacerbating and sustaining damage in AKI and CKD. These epithelial cell states and their associated expression signatures are also observed in transplanted kidney allografts, suggesting that the identification and characterization of transcriptomic epithelial cell states in kidney allografts may have potential clinical implications for diagnosis and therapy.

Gefitinib metabolism-related lncRNAs for the prediction of prognosis, tumor microenvironment and drug sensitivity in lung adenocarcinoma

The complete compound of gefitinib is effective in the treatment of lung adenocarcinoma. However, the effect on lung adenocarcinoma (LUAD) during its catabolism has not yet been elucidated. We carried out this study to examine the predictive value of gefitinib metabolism-related long noncoding RNAs (GMLncs) in LUAD patients. To filter GMLncs and create a prognostic model, we employed Pearson correlation, Lasso, univariate Cox, and multivariate Cox analysis. We combined risk scores and clinical features to create nomograms for better application in clinical settings. According to the constructed prognostic model, we performed GO/KEGG and GSEA enrichment analysis, tumor immune microenvironment analysis, immune evasion and immunotherapy analysis, somatic cell mutation analysis, drug sensitivity analysis, IMvigor210 immunotherapy validation, stem cell index analysis and real-time quantitative PCR (RT-qPCR) analysis. We built a predictive model with 9 GMLncs, which showed good predictive performance in validation and training sets. The calibration curve demonstrated excellent agreement between the expected and observed survival rates, for which the predictive performance was better than that of the nomogram without a risk score. The metabolism of gefitinib is related to the cytochrome P450 pathway and lipid metabolism pathway, and may be one of the causes of gefitinib resistance, according to analyses from the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Immunological evasion and immunotherapy analysis revealed that the likelihood of immune evasion increased with risk score. Tumor microenvironment analysis found most immune cells at higher concentrations in the low-risk group. Drug sensitivity analysis found 23 sensitive drugs. Twenty-one of these drugs exhibited heightened sensitivity in the high-risk group. RT-qPCR analysis validated the characteristics of 9 GMlncs. The predictive model and nomogram that we constructed have good application value in evaluating the prognosis of patients and guiding clinical treatment.

Single-Cell RNA Sequencing in Organ and Cell Transplantation

Single-cell RNA sequencing is a high-throughput novel method that provides transcriptional profiling of individual cells within biological samples. This method typically uses microfluidics systems to uncover the complex intercellular communication networks and biological pathways buried within highly heterogeneous cell populations in tissues. One important application of this technology sits in the fields of organ and stem cell transplantation, where complications such as graft rejection and other post-transplantation life-threatening issues may occur. In this review, we first focus on research in which single-cell RNA sequencing is used to study the transcriptional profile of transplanted tissues. This technology enables the analysis of the donor and recipient cells and identifies cell types and states associated with transplant complications and pathologies. We also review the use of single-cell RNA sequencing in stem cell implantation. This method enables studying the heterogeneity of normal and pathological stem cells and the heterogeneity in cell populations. With their remarkably rapid pace, the single-cell RNA sequencing methodologies will potentially result in breakthroughs in clinical transplantation in the coming years.

A transfer learning framework to elucidate the clinical relevance of altered proximal tubule cell states in kidney disease

The application of single-cell technologies in clinical nephrology remains elusive. We generated an atlas of transcriptionally defined cell types and cell states of human kidney disease by integrating single-cell signatures reported in the literature with newly generated signatures obtained from 5 patients with acute kidney injury. We used this information to develop kidney-specific cell-level information ExtractoR (K-CLIER), a transfer learning approach specifically tailored to evaluate the role of cell types/states on bulk RNAseq data. We validated the K-CLIER as a reliable computational framework to obtain a dimensionality reduction and to link clinical data with single-cell signatures. By applying K-CLIER on cohorts of patients with different kidney diseases, we identified the most relevant cell types associated with fibrosis and disease progression. This analysis highlighted the central role of altered proximal tubule cells in chronic kidney disease. Our study introduces a new strategy to exploit the power of single-cell technologies toward clinical applications.

Construction of an immune predictive model and identification of TRIP6 as a prognostic marker and therapeutic target of CRC by integration of single-cell and bulk RNA-seq data

BACKGROUND

Investigations elucidating the complex immunological mechanisms involved in colorectal cancer (CRC) and accurately predicting patient outcomes via bulk RNA-Seq analysis have been notably limited. This study aimed to identify the immune status of CRC patients, construct a prognostic model, and identify prognostic signatures via bulk RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq).

METHODS

The scRNA-seq data of CRC were downloaded from Gene Expression Omnibus (GEO). The UCSC Xena database was used to obtain bulk RNA-seq data. Differentially expressed gene (DEG), functional enrichment, and random forest analyses were conducted in order to identify core genes associated with colorectal cancer (CRC) that were relevant to prognosis. A molecular immune prediction model was developed using logistic regression after screening features using the least absolute shrinkage and selection operator (LASSO). The differences in immune cell infiltration, mutation, chemotherapeutic drug sensitivity, cellular senescence, and communication between patients who were at high and low risk of CRC according to the predictive model were investigated. The prognostic genes that were closely associated with CRC were identified by random survival forest (RSF) analysis. The expression levels and clinical significance of the hub genes were analyzed in vitro. The LoVo cell line was employed to ascertain the biological role of thyroid hormone receptor-interacting protein 6 (TRIP6).

RESULTS

A total of seven main cell subtypes were identified by scRNA-seq analysis. A molecular immune predictive model was constructed based on the risk scores. The risk score was significantly associated with OS, stage, mutation burden, immune cell infiltration, response to immunotherapy, key pathways, and cell-cell communication. The functions of the six hub genes were determined and further utilized to establish a regulatory network. Our findings unequivocally confirmed that TRIP6 upregulation was verified in the CRC samples. After knocking down TRIP6, cell proliferation, migration, and invasion of LoVo cells were inhibited, and apoptosis was promoted.

CONCLUSIONS

The molecular predictive model reliably distinguished the immune status of CRC patients. We further revealed that TRIP6 may act as an oncogene in CRC, making it a promising candidate for targeted therapy and as a prognostic marker for CRC.

Relationship between blood and tissue-based rejection-related transcripts in heart transplantation

BACKGROUND

The purpose of the study is to investigate the relationship between blood and tissue-derived rejection-related transcripts from blood gene expression profiling (GEP) and molecular microscope in the setting of allograft rejection in heart transplant.

METHODS

All heart transplant patients from August 2021 to May 2022 with both circulating blood GEP (AlloMap) and endomyocardial biopsy with molecular microscope diagnostic system (MMDx) within 4 weeks were included (N = 173 samples). We obtained individual blood GEP-based messenger RNA transcript expression levels of the 11 target genes from CareDx. Student's t-test was performed to compare blood GEP transcript expression levels between no rejection and rejection as assessed by MMDx. A Scatter plot with Spearman correlation analysis was performed to compare the relationship between transcript expression levels from AlloMap and MMDx, with and without allograft rejection.

RESULTS

There were 52 samples (30.1%) with antibody-mediated rejection (ABMR) and 15 samples (8.7%) with T-cell-mediated rejection (TCMR), as assessed by MMDx. Expression of one of the blood ITGA4 (Integrin alpha 4) expression level was elevated in ABMR, compared to no ABMR (4,607.5 vs 4,217.5; p = 0.019). Most tissue rejection-associated transcript expression levels were elevated in ABMR, and tissue ROBO4 expression correlated with the blood ITGA4 expression with moderate or greater effect size in all samples (Spearman's R = 0.31; p < 0.001). There was also a positive correlation between blood ITGA4 and tissue ROBO4 expression in samples without ABMR (Spearman's R = 0.33; p < 0.001), but no correlation between blood ITGA4 and tissue ROBO4 expression in samples with ABMR (Spearman's R = 0.009; p = 0.513).

CONCLUSIONS

Circulating blood ITGA4 expression is elevated in antibody-mediated rejection (AMR) and correlates with myocardial expression of ROBO4. The knowledge of individual transcript expression levels in blood and in tissue may provide insights into various disease processes in heart transplant patients. Taken together, the results of our study reveal an overlap between 2 objective post-heart transplant rejection surveillance methods, identify potential novel markers for ABMR, and reveal the need for a deeper understanding of molecular mechanisms underlying allograft rejection.

Unlocking the potential of T-cell metabolism reprogramming: Advancing single-cell approaches for precision immunotherapy in tumour immunity

As single-cell RNA sequencing enables the detailed clustering of T-cell subpopulations and facilitates the analysis of T-cell metabolic states and metabolite dynamics, it has gained prominence as the preferred tool for understanding heterogeneous cellular metabolism. Furthermore, the synergistic or inhibitory effects of various metabolic pathways within T cells in the tumour microenvironment are coordinated, and increased activity of specific metabolic pathways generally corresponds to increased functional activity, leading to diverse T-cell behaviours related to the effects of tumour immune cells, which shows the potential of tumour-specific T cells to induce persistent immune responses. A holistic understanding of how metabolic heterogeneity governs the immune function of specific T-cell subsets is key to obtaining field-level insights into immunometabolism. Therefore, exploring the mechanisms underlying the interplay between T-cell metabolism and immune functions will pave the way for precise immunotherapy approaches in the future, which will empower us to explore new methods for combating tumours with enhanced efficacy.

Immune landscape of the kidney allograft in response to rejection

Preventing kidney graft dysfunction and rejection is a critical step in addressing the nationwide organ shortage and improving patient outcomes. While kidney transplants (KT) are performed more frequently, the overall number of patients on the waitlist consistently exceeds organ availability. Despite improved short-term outcomes in KT, comparable progress in long-term allograft survival has not been achieved. Major cause of graft loss at 5 years post-KT is chronic allograft dysfunction (CAD) characterized by interstitial fibrosis and tubular atrophy (IFTA). Accordingly, proactive prevention of CAD requires a comprehensive understanding of the immune mechanisms associated with either further dysfunction or impaired repair. Allograft rejection is primed by innate immune cells and carried out by adaptive immune cells. The rejection process is primarily facilitated by antibody-mediated rejection (ABMR) and T cell-mediated rejection (TCMR). It is essential to better elucidate the actions of individual immune cell subclasses (e.g. B memory, Tregs, Macrophage type 1 and 2) throughout the rejection process, rather than limiting our understanding to broad classes of immune cells. Embracing multi-omic approaches may be the solution in acknowledging these intricacies and decoding these enigmatic pathways. A transition alongside advancing technology will better allow organ biology to find its place in this era of precision and personalized medicine.

Research progress on CD8+ T cell immune regulation in allogenic transplantation

With advances in tissue typing, organ preservation techniques, and clinical surgery, organ transplantation has gained popularity as a treatment option for various end-stage diseases. Allogeneic transplantation has been widely adopted and extensively researched in clinical practice. Despite significant breakthroughs and progress in immunosuppression, this procedure is still associated with several adverse reactions and complications. Therefore, there is a continuing need to explore new immunological approaches to provide fresh insights and guidance for clinical transplantation. CD8+ T cells, traditionally known for their cytotoxic function and their ability to recognize transplanted organs as "non-self" entities, display cytotoxicity. However, recent studies have unveiled that CD8+ T cells have various subtypes and functions that extend beyond conventional cytotoxicity. These CD8+ T cell subtypes include Effector CD8+ T cells, Memory CD8+ T cells, and CD8Treg cells. This review examines the immune regulatory mechanisms of CD8+ T cells in allogeneic transplantation and discusses the potential applications of CD8+ T cells in treating tumors in transplant recipients who are receiving immunosuppressive therapy. These findings offer theoretical guidance for reducing post-transplant rejection reactions and improving adverse prognoses, offering new hope for improved clinical survival rate.

Single cell and spatial transcriptomics analysis of kidney double negative T lymphocytes in normal and ischemic mouse kidneys

T cells are important in the pathogenesis of acute kidney injury (AKI), and TCR+CD4-CD8- (double negative-DN) are T cells that have regulatory properties. However, there is limited information on DN T cells compared to traditional CD4+ and CD8+ cells. To elucidate the molecular signature and spatial dynamics of DN T cells during AKI, we performed single-cell RNA sequencing (scRNA-seq) on sorted murine DN, CD4+, and CD8+ cells combined with spatial transcriptomic profiling of normal and post AKI mouse kidneys. scRNA-seq revealed distinct transcriptional profiles for DN, CD4+, and CD8+ T cells of mouse kidneys with enrichment of Kcnq5, Klrb1c, Fcer1g, and Klre1 expression in DN T cells compared to CD4+ and CD8+ T cells in normal kidney tissue. We validated the expression of these four genes in mouse kidney DN, CD4+ and CD8+ T cells using RT-PCR and Kcnq5, Klrb1, and Fcer1g genes with the NIH human kidney precision medicine project (KPMP). Spatial transcriptomics in normal and ischemic mouse kidney tissue showed a localized cluster of T cells in the outer medulla expressing DN T cell genes including Fcer1g. These results provide a template for future studies in DN T as well as CD4+ and CD8+ cells in normal and diseased kidneys.

Intragraft regulatory T cells in the modern era: what can high-dimensional methods tell us about pathways to allograft acceptance?

Replacement of diseased organs with transplanted healthy donor ones remains the best and often only treatment option for end-stage organ disease. Immunosuppressants have decreased the incidence of acute rejection, but long-term survival remains limited. The broad action of current immunosuppressive drugs results in global immune impairment, increasing the risk of cancer and infections. Hence, achievement of allograft tolerance, in which graft function is maintained in the absence of global immunosuppression, has long been the aim of transplant clinicians and scientists. Regulatory T cells (Treg) are a specialized subset of immune cells that control a diverse array of immune responses, can prevent allograft rejection in animals, and have recently been explored in early phase clinical trials as an adoptive cellular therapy in transplant recipients. It has been established that allograft residency by Tregs can promote graft acceptance, but whether intragraft Treg functional diversification and spatial organization contribute to this process is largely unknown. In this review, we will explore what is known regarding the properties of intragraft Tregs during allograft acceptance and rejection. We will summarize recent advances in understanding Treg tissue residency through spatial, transcriptomic and high-dimensional cytometric methods in both animal and human studies. Our discussion will explore properties of intragraft Tregs in mediating operational tolerance to commonly transplanted solid organs. Finally, given recent developments in Treg cellular therapy, we will review emerging knowledge of whether and how these adoptively transferred cells enter allografts in humans. An understanding of the properties of intragraft Tregs will help lay the foundation for future therapies that will promote immune tolerance.

Prognostic value analysis of cholesterol and cholesterol homeostasis related genes in breast cancer by Mendelian randomization and multi-omics machine learning

Introduction

The high incidence of breast cancer (BC) prompted us to explore more factors that might affect its occurrence, development, treatment, and also recurrence. Dysregulation of cholesterol metabolism has been widely observed in BC; however, the detailed role of how cholesterol metabolism affects chemo-sensitivity, and immune response, as well as the clinical outcome of BC is unknown.

Methods

With Mendelian randomization (MR) analysis, the potential causal relationship between genetic variants of cholesterol and BC risk was assessed first. Then we analyzed 73 cholesterol homeostasis-related genes (CHGs) in BC samples and their expression patterns in the TCGA cohort with consensus clustering analysis, aiming to figure out the relationship between cholesterol homeostasis and BC prognosis. Based on the CHG analysis, we established a CAG_score used for predicting therapeutic response and overall survival (OS) of BC patients. Furthermore, a machine learning method was adopted to accurately predict the prognosis of BC patients by comparing multi-omics differences of different risk groups.

Results

We observed that the alterations in plasma cholesterol appear to be correlative with the venture of BC (MR Egger, OR: 0.54, 95% CI: 0.35-0.84, p<0.006). The expression patterns of CHGs were classified into two distinct groups(C1 and C2). Notably, the C1 group exhibited a favorable prognosis characterized by a suppressed immune response and enhanced cholesterol metabolism in comparison to the C2 group. In addition, high CHG score were accompanied by high performance of tumor angiogenesis genes. Interestingly, the expression of vascular genes (CDH5, CLDN5, TIE1, JAM2, TEK) is lower in patients with high expression of CHGs, which means that these patients have poorer vascular stability. The CAG_score exhibits robust predictive capability for the immune microenvironment characteristics and prognosis of patients(AUC=0.79). It can also optimize the administration of various first-line drugs, including AKT inhibitors VIII Imatinib, Crizotinib, Saracatinib, Erlotinib, Dasatinib, Rapamycin, Roscovitine and Shikonin in BC patients. Finally, we employed machine learning techniques to construct a multi-omics prediction model(Risklight),with an area under the feature curve (AUC) of up to 0.89.

Conclusion

With the help of CAG_score and Risklight, we reveal the signature of cholesterol homeostasis-related genes for angiogenesis, immune responses, and the therapeutic response in breast cancer, which contributes to precision medicine and improved prognosis of BC.

Advances in the study of B cells in renal ischemia-reperfusion injury

Renal ischemia-reperfusion injury (IRI) is a non-negligible clinical challenge for clinicians in surgeries such as renal transplantation. Functional loss of renal tubular epithelial cell (TEC) in IRI leads to the development of acute kidney injury, delayed graft function (DGF), and allograft rejection. The available evidence indicates that cellular oxidative stress, cell death, microvascular dysfunction, and immune response play an important role in the pathogenesis of IRI. A variety of immune cells, including macrophages and T cells, are actively involved in the progression of IRI in the immune response. The role of B cells in IRI has been relatively less studied, but there is a growing body of evidence for the involvement of B cells, which involve in the development of IRI through innate immune responses, adaptive immune responses, and negative immune regulation. Therefore, therapies targeting B cells may be a potential direction to mitigate IRI. In this review, we summarize the current state of research on the role of B cells in IRI, explore the potential effects of different B cell subsets in the pathogenesis of IRI, and discuss possible targets of B cells for therapeutic aim in renal IRI.

Single-nuclei RNA-seq reveals skin cell responses to Aeromonas hydrophila infection in Chinese longsnout catfish Leiocassis longirostris

As the primary natural barrier that protects against adverse environmental conditions, the skin plays a crucial role in the innate immune response of fish, particularly in relation to bacterial infections. However, due to the diverse functionality and intricate anatomical and cellular composition of the skin, deciphering the immune response of the host is a challenging task. In this study, single nuclei RNA-sequencing (snRNA-seq) was performed on skin biopsies obtained from Chinese longsnout catfish (Leiocassis longirostris), comparing Aeromonas hydrophila-infected subjects to healthy control subjects. A total of 19,581 single nuclei cells were sequenced using 10x Genomics (10,400 in the control group and 9,181 in the treated group). Based on expressed unique transcriptional profiles, 33 cell clusters were identified and classified into 12 cell types including keratinocyte (KC), fibroblast (FB), endothelial cells (EC), secretory cells (SC), immune cells, smooth muscle cells (SMC), and other cells such as pericyte (PC), brush cell (BC), red blood cell (RBC), neuroendocrine cell (NDC), neuron cells (NC), and melanocyte (MC). Among these, three clusters of KCs, namely, KC1, KC2, and KC5 exhibited significant expansion after A. hydrophila infection. Analysis of pathway enrichment revealed that KC1 was primarily involved in environmental signal transduction, KC2 was primarily involved in endocrine function, and KC5 was primarily involved in metabolism. Finally, our findings suggest that neutrophils may play a crucial role in combating A. hydrophila infections. In summary, this study not only provides the first detailed comprehensive map of all cell types present in the skin of teleost fish but also sheds light on the immune response mechanism of the skin following A. hydrophila infection in Chinese longsnout catfish.

The role of regulatory T cells in the pathogenesis of acute kidney injury

The incidence of acute kidney injury (AKI) is on the rise and is associated with high mortality; however, there are currently few effective treatments. Moreover, the relationship between Tregs and other components of the immune microenvironment (IME) in the pathogenesis of AKI remains unclear. We downloaded four publicly accessible AKI datasets, GSE61739, GSE67401, GSE19130, GSE81741, GSE19288 and GSE106993 from the gene expression omnibus (GEO) database. Additionally, we gathered two kidney single-cell sequencing (scRNA-seq) samples from the Department of Organ Transplantation at Zhujiang Hospital of Southern Medical University to investigate chronic kidney transplant rejection (CKTR). Moreover, we also collected three samples of normal kidney tissue from GSE131685. By analysing the differences in immune cells between the AKI and Non-AKI groups, we discovered that the Non-AKI group contained a significantly greater number of Tregs than the AKI group. Additionally, the activation of signalling pathways, such as inflammatory molecules secretion, immune response, glycolytic metabolism, NOTCH, FGF, NF-κB and TLR4, was significantly greater in the AKI group than in the Non-AKI group. Additionally, analysis of single-cell sequencing data revealed that Tregs in patients with chronic kidney rejection and in normal kidney tissue have distinct biology, including immune activation, cytokine production, and activation fractions of signalling pathways such as NOTCH and TLR4. In this study, we found significant differences in the IME between AKI and Non-AKI, including differences in Tregs cells and activation levels of biologically significant signalling pathways. Tregs were associated with lower activity of signalling pathways such as inflammatory response, inflammatory molecule secretion, immune activation, glycolysis.

Single-Cell Heterogeneity Restorative Chimeric Engineering Nanoparticles for Alleviating Antibody-Mediated Allograft Injury

Disturbance of single-cell transcriptional heterogeneity is an inevitable consequence of persistent donor-specific antibody (DSA) production and allosensitization. However, identifying and efficiently clearing allospecific antibody repertoires to restore single-cell transcriptional profiles remain challenging. Here, inspired by the high affinity of natural bacterial proteins for antibodies, a genetic engineered membrane-coated nanoparticle termed as DSA trapper by the engineering chimeric gene of protein A/G with phosphatidylserine ligands for macrophage phagocytosis was reported. It has been shown that DSA trappers adsorbed alloreactive antibodies with high saturation and activated the heterophagic clearance of antibody complexes, alleviating IgG deposition and complement activation. Remarkably, DSA trappers increased the endothelial protective lineages by 8.39-fold, reversed the highly biased cytotoxicity, and promoted the proliferative profiles of Treg cells, directly providing an obligate immune tolerant niche for single-cell heterogeneity restoration. In the mice of allogeneic transplantation, the DSA trapper spared endothelial from inflammatory degenerative rosette, improved the glomerular filtration rate, and prolonged the survival of allogeneic mice from 23.6 to 78.3 days. In general, by identifying the lineage characteristics of rejection-related antibodies, the chimeric engineered DSA trapper realized immunoadsorption and further phagocytosis of alloantibody complexes to restore the single-cell genetic architecture of the allograft, offering a promising prospect for the treatment of alloantibody-mediated immune injury.

Single-cell RNA sequencing reveals the transcriptomic landscape of kidneys in patients with ischemic acute kidney injury

BACKGROUND

Ischemic acute kidney injury (AKI) is a common syndrome associated with considerable mortality and healthcare costs. Up to now, the underlying pathogenesis of ischemic AKI remains incompletely understood, and specific strategies for early diagnosis and treatment of ischemic AKI are still lacking. Here, this study aimed to define the transcriptomic landscape of AKI patients through single-cell RNA sequencing (scRNA-seq) analysis in kidneys.

METHODS

In this study, scRNA-seq technology was applied to kidneys from two ischemic AKI patients, and three human public scRNA-seq datasets were collected as controls. Differentially expressed genes (DEGs) and cell clusters of kidneys were determined. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, as well as the ligand-receptor interaction between cells, were performed. We also validated several DEGs expression in kidneys from human ischemic AKI and ischemia/reperfusion (I/R) injury induced AKI mice through immunohistochemistry staining.

RESULTS

15 distinct cell clusters were determined in kidney from subjects of ischemic AKI and control. The injured proximal tubules (PT) displayed a proapoptotic and proinflammatory phenotype. PT cells of ischemic AKI had up-regulation of novel pro-apoptotic genes including USP47 , RASSF4 , EBAG9 , IER3 , SASH1 , SEPTIN7 , and NUB1 , which have not been reported in ischemic AKI previously. Several hub genes were validated in kidneys from human AKI and renal I/R injury mice, respectively. Furthermore, PT highly expressed DEGs enriched in endoplasmic reticulum stress, autophagy, and retinoic acid-inducible gene I (RIG-I) signaling. DEGs overexpressed in other tubular cells were primarily enriched in nucleotide-binding and oligomerization domain (NOD)-like receptor signaling, estrogen signaling, interleukin (IL)-12 signaling, and IL-17 signaling. Overexpressed genes in kidney-resident immune cells including macrophages, natural killer T (NKT) cells, monocytes, and dendritic cells were associated with leukocyte activation, chemotaxis, cell adhesion, and complement activation. In addition, the ligand-receptor interactions analysis revealed prominent communications between macrophages and monocytes with other cells in the process of ischemic AKI.

CONCLUSION

Together, this study reveals distinct cell-specific transcriptomic atlas of kidney in ischemic AKI patients, altered signaling pathways, and potential cell-cell crosstalk in the development of AKI. These data reveal new insights into the pathogenesis and potential therapeutic strategies in ischemic AKI.

Single-cell transcriptomics reveals that tumor-infiltrating natural killer cells are activated by localized ablative immunotherapy and share anti-tumor signatures induced by immune checkpoint inhibitors

Rationale

Natural killer (NK) cells provide protective anti-cancer immunity. However, the cancer therapy induced activation gene signatures and pathways in NK cells remain unclear.

Methods

We applied a novel localized ablative immunotherapy (LAIT) by synergizing photothermal therapy (PTT) with intra-tumor delivering of the immunostimulant N-dihydrogalactochitosan (GC), to treat breast cancer using a mammary tumor virus-polyoma middle tumor-antigen (MMTV-PyMT) mouse model. We performed single-cell RNA sequencing (scRNAseq) analysis to unveil the cellular heterogeneity and compare the transcriptional alterations induced by PTT, GC, and LAIT in NK cells within the tumor microenvironment (TME).

Results

ScRNAseq showed that NK subtypes, including cycling, activated, interferon-stimulated, and cytotoxic NK cells. Trajectory analysis revealed a route toward activation and cytotoxicity following pseudotime progression. Both GC and LAIT elevated gene expression associated with NK cell activation, cytolytic effectors, activating receptors, IFN pathway components, and cytokines/chemokines in NK subtypes. Single-cell transcriptomics analysis using immune checkpoint inhibitor (ICI)-treated animal and human samples revealed that ICI-induced NK activation and cytotoxicity across several cancer types. Furthermore, ICI-induced NK gene signatures were also induced by LAIT treatment. We also discovered that several types of cancer patients had significantly longer overall survival when they had higher expression of genes in NK cells that were also specifically upregulated by LAIT.

Conclusion

Our findings show for the first time that LAIT activates cytotoxicity in NK cells and the upregulated genes positively correlate with beneficial clinical outcomes for cancer patients. More importantly, our results further establish the correlation between the effects of LAIT and ICI on NK cells, hence expanding our understanding of mechanism of LAIT in remodeling TME and shedding light on the potentials of NK cell activation and anti-tumor cytotoxic functions in clinical applications.

Allograft tissue under the microscope: only the beginning

PURPOSE OF REVIEW

To review novel modalities for interrogating a kidney allograft biopsy to complement the current Banff schema.

RECENT FINDINGS

Newer approaches of Artificial Intelligence (AI), Machine Learning (ML), digital pathology including Ex Vivo Microscopy, evaluation of the biopsy gene expression using bulk, single cell, and spatial transcriptomics and spatial proteomics are now available for tissue interrogation.

SUMMARY

Banff Schema of classification of allograft histology has standardized reporting of tissue pathology internationally greatly impacting clinical care and research. Inherent sampling error of biopsies, and lack of automated morphometric analysis with ordinal outputs limit its performance in prognostication of allograft health. Over the last decade, there has been an explosion of newer methods of evaluation of allograft tissue under the microscope. Digital pathology along with the application of AI and ML algorithms could revolutionize histopathological analyses. Novel molecular diagnostics such as spatially resolved single cell transcriptomics are identifying newer mechanisms underlying the pathologic diagnosis to delineate pathways of immunological activation, tissue injury, repair, and regeneration in allograft tissues. While these techniques are the future of tissue analysis, costs and complex logistics currently limit their clinical use.

Single-Cell Transcriptome Identifies the Renal Cell Type Tropism of Human BK Polyomavirus

BK polyomavirus (BKPyV) infection is the main factor affecting the prognosis of kidney transplant recipients, as no antiviral agent is yet available. A better understanding of the renal-cell-type tropism of BKPyV can serve to develop new treatment strategies. In this study, the single-cell transcriptomic analysis demonstrated that the ranking of BKPyV tropism for the kidney was proximal tubule cells (PT), collecting duct cells (CD), and glomerular endothelial cells (GEC) according to the signature of renal cell type and immune microenvironment. In normal kidneys, we found that BKPyV infection-related transcription factors P65 and CEBPB were PT-specific transcription factors, and PT showed higher glycolysis/gluconeogenesis activities than CD and GEC. Furthermore, in the BKPyV-infected kidneys, the percentage of late viral transcripts in PT was significantly higher than in CD and GEC. In addition, PT had the smallest cell-cell interactions with immune cells compared to CD and GEC in both normal and BKPyV-infected kidneys. Subsequently, we indirectly demonstrated the ranking of BKPyV tropism via the clinical observation of sequential biopsies. Together, our results provided in-depth insights into the renal cell-type tropism of BKPyV in vivo at single-cell resolution and proposed a novel antiviral target.

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.

A Machine Learning Analysis of Prognostic Genes Associated With Allograft Tolerance After Renal Transplantation

In this study, we aimed to identify transplantation tolerance (TOL)-related gene signature and use it to predict the different types of renal allograft rejection performances in kidney transplantation. Gene expression data were obtained from the Gene Expression Omnibus (GEO) database, differently expressed genes (DEGs) were performed, and the gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were also conducted. The machine learning methods were combined to analyze the feature TOL-related genes and verify their predictive performance. Afterward, the gene expression levels and predictive performances of TOL-related genes were conducted in the context of acute rejection (AR), chronic rejection (CR), and graft loss through heatmap plots and the receiver operating characteristic (ROC) curves, and their respective immune infiltration results were also performed. Furthermore, the TOL-related gene signature for graft survival was conducted to discover gene immune cell enrichment. A total of 25 TOL-related DEGs were founded, and the GO and KEGG results indicated that DEGs mainly enriched in B cell-related functions and pathways. 7 TOL-related gene signature was constructed and performed delightedly in TOL groups and different types of allograft rejection. The immune infiltration analysis suggested that gene signature was correlated with different types of immune cells. The Kaplan-Meier (KM) survival analysis demonstrated that BLNK and MZB1 were the prognostic TOL-related genes. Our study proposed a novel gene signature that may influence TOL in kidney transplantation, providing possible guidance for immunosuppressive therapy in kidney transplant patients.

Integration of artificial intelligence and multi-omics in kidney diseases

Kidney disease is a leading cause of death worldwide. Currently, the diagnosis of kidney diseases and the grading of their severity are mainly based on clinical features, which do not reveal the underlying molecular pathways. More recent surge of ∼omics studies has greatly catalyzed disease research. The advent of artificial intelligence (AI) has opened the avenue for the efficient integration and interpretation of big datasets for discovering clinically actionable knowledge. This review discusses how AI and multi-omics can be applied and integrated, to offer opportunities to develop novel diagnostic and therapeutic means in kidney diseases. The combination of new technology and novel analysis pipelines can lead to breakthroughs in expanding our understanding of disease pathogenesis, shedding new light on biomarkers and disease classification, as well as providing possibilities of precise treatment.

Revisiting transplant immunology through the lens of single-cell technologies

Solid organ transplantation (SOT) is the standard of care for end-stage organ disease. The most frequent complication of SOT involves allograft rejection, which may occur via T cell- and/or antibody-mediated mechanisms. Diagnosis of rejection in the clinical setting requires an invasive biopsy as there are currently no reliable biomarkers to detect rejection episodes. Likewise, it is virtually impossible to identify patients who exhibit operational tolerance and may be candidates for reduced or complete withdrawal of immunosuppression. Emerging single-cell technologies, including cytometry by time-of-flight (CyTOF), imaging mass cytometry, and single-cell RNA sequencing, represent a new opportunity for deep characterization of pathogenic immune populations involved in both allograft rejection and tolerance in clinical samples. These techniques enable examination of both individual cellular phenotypes and cell-to-cell interactions, ultimately providing new insights into the complex pathophysiology of allograft rejection. However, working with these large, highly dimensional datasets requires expertise in advanced data processing and analysis using computational biology techniques. Machine learning algorithms represent an optimal strategy to analyze and create predictive models using these complex datasets and will likely be essential for future clinical application of patient level results based on single-cell data. Herein, we review the existing literature on single-cell techniques in the context of SOT.

Into the multi-omics era: Progress of T cells profiling in the context of solid organ transplantation

T cells are the common type of lymphocyte to mediate allograft rejection, remaining long-term allograft survival impeditive. However, the heterogeneity of T cells, in terms of differentiation and activation status, the effector function, and highly diverse T cell receptors (TCRs) have thus precluded us from tracking these T cells and thereby comprehending their fate in recipients due to the limitations of traditional detection approaches. Recently, with the widespread development of single-cell techniques, the identification and characterization of T cells have been performed at single-cell resolution, which has contributed to a deeper comprehension of T cell heterogeneity by relevant detections in a single cell - such as gene expression, DNA methylation, chromatin accessibility, surface proteins, and TCR. Although these approaches can provide valuable insights into an individual cell independently, a comprehensive understanding can be obtained when applied joint analysis. Multi-omics techniques have been implemented in characterizing T cells in health and disease, including transplantation. This review focuses on the thesis, challenges, and advances in these technologies and highlights their application to the study of alloreactive T cells to improve the understanding of T cell heterogeneity in solid organ transplantation.

Applications of Transcriptomics in the Research of Antibody-Mediated Rejection in Kidney Transplantation: Progress and Perspectives

Antibody-mediated rejection (ABMR) is the major cause of chronic allograft dysfunction and loss in kidney transplantation. The immunological mechanisms of ABMR that have been featured in the latest studies indicate a highly complex interplay between various immune and nonimmune cell types. Clinical diagnostic standards have long been criticized for being arbitrary and the lack of accuracy. Transcriptomic approaches, including microarray and RNA sequencing of allograft biopsies, enable the identification of differential gene expression and the continuous improvement of diagnostics. Given that conventional bulk transcriptomic approaches only reflect the average gene expression but not the status at the single-cell level, thereby ignoring the heterogeneity of the transcriptome across individual cells, single-cell RNA sequencing is rising as a powerful tool to provide a high-resolution transcriptome map of immune cells, which allows the elucidation of the pathogenesis and may facilitate the development of novel strategies for clinical treatment of ABMR.

Uncover diagnostic immunity/hypoxia/ferroptosis/epithelial mesenchymal transformation-related CCR5, CD86, CD8A, ITGAM, and PTPRC in kidney transplantation patients with allograft rejection

The aim of this study was to identify predictive immunity/hypoxia/ferroptosis/epithelial mesenchymal transformation (EMT)-related biomarkers, pathways and new drugs in allograft rejection in kidney transplant patients. First, gene expression data were downloaded followed by identification of differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis. Second, diagnostic model was construction based on key genes, followed by correlation analysis between immune/hypoxia/ferroptosis/EMT and key diagnostic genes. Finally, drug prediction of diagnostic key genes was carried out. Five diagnostic genes were further identified, including CCR5, CD86, CD8A, ITGAM, and PTPRC, which were positively correlated with allograft rejection after the kidney transplant. Highly infiltrated immune cells, highly expression of hypoxia-related genes and activated status of EMT were significantly positively correlated with five diagnostic genes. Interestingly, suppressors of ferroptosis (SOFs) and drivers of ferroptosis (DOFs) showed a complex regulatory relationship between ferroptosis and five diagnostic genes. CD86, CCR5, and ITGAM were respectively drug target of ABATACEPT, MARAVIROC, and CLARITHROMYCIN. PTPRC was drug target of both PREDNISONE and EPOETIN BETA. In conclusion, the study could be useful in understanding changes in the microenvironment within transplantation, which may promote or sustain the development of allograft rejection after kidney transplantation.

The Value of Single-cell Technologies in Solid Organ Transplantation Studies

Single-cell technologies open up new opportunities to explore the behavior of cells at the individual level. For solid organ transplantation, single-cell technologies can provide in-depth insights into the underlying mechanisms of the immunological processes involved in alloimmune responses after transplantation by investigating the role of individual cells in tolerance and rejection. Here, we review the value of single-cell technologies, including cytometry by time-of-flight and single-cell RNA sequencing, in the context of solid organ transplantation research. Various applications of single-cell technologies are addressed, such as the characterization and identification of immune cell subsets involved in rejection or tolerance. In addition, we explore the opportunities for analyzing specific alloreactive T- or B-cell clones by linking phenotype data to T- or B-cell receptor data, and for distinguishing donor- from recipient-derived immune cells. Moreover, we discuss the use of single-cell technologies in biomarker identification and risk stratification, as well as the remaining challenges. Together, this review highlights that single-cell approaches contribute to a better understanding of underlying immunological mechanisms of rejection and tolerance, thereby potentially accelerating the development of new or improved therapies to avoid allograft rejection.

Molecular typing and prognostic model of lung adenocarcinoma based on cuprotosis-related lncRNAs

Background

Previous research has shown the heterogeneity of lung adenocarcinoma (LUAD) accounts for the different effects and prognoses of the same treatment. Cuprotosis is a newly discovered form of programmed cell death involved in the development of tumors. Therefore, it is important to study the long non-coding RNAs (lncRNAs) that regulate cuprotosis to identify molecular subtypes and predict survival of LUAD.

Methods

The expression profile, clinical, and mutation data of LUAD were downloaded from The Cancer Genome Atlas (TCGA), and the "ConsensusClusterPlus" package was used to cluster LUADs based on cuprotosis-related lncRNAs (CR-lncRNAs). The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were used to construct a prognostic model. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were used for assessing immune cells infiltration and immune function. The tumor microenvironment (TME) score was calculated by ESTIMATE, and the tumor mutational burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) were used to evaluate the efficacy of immunotherapy.

Results

Firstly, 501 CR-lncRNAs were identified based on the co-expression relationship of 19 cuprotosis genes. And univariate Cox further obtained 34 prognosis-related CR-lncRNAs. The unsupervised consensus clustering divided LUAD samples into cluster A and cluster B, and showed cluster A had better prognosis, more immune cells infiltration, stronger immune function, and a higher TME score. Subsequently, we used Lasso Cox regression to construct a prognostic model, and univariate and multivariate Cox analyses showed the risk score could be an independent prognostic indicator. Immune cells infiltration, immune function, and TME score were increased markedly in the low-risk group, while TMB and TIDE suggested the efficacy of immunotherapy might be increased in high-risk group.

Conclusions

Our research identified two new molecular subtypes and constructed a novel prognostic model of LUAD which could provide new direction for its diagnosis, treatment, and prognosis.

Single-Cell RNA sequencing reveals immune cell dynamics and local intercellular communication in acute murine cardiac allograft rejection

Rationale: Transplant rejection is a major impediment to long-term allograft survival, in which the actions of immune cells are of fundamental importance. However, the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection are not completely clear.

Methods: Here we performed single-cell RNA sequencing on CD45⁺ immune cells isolated from cardiac grafts and spleens in a model of murine heterotopic heart transplantation. Moreover, we applied unsupervised clustering, functional enrichment analysis, cell trajectory construction and intercellular communication analysis to explore the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection at single-cell level. The effect of CXCR3 antagonist and neutralizing antibody against its ligand on allograft rejection and T cell function was evaluated in murine heart transplantation model.

Results: We presented the immune cell landscape of acute murine cardiac allograft rejection at single-cell resolution, and uncovered the functional characteristics and differentiation trajectory of several alloreactive cell subpopulations, including Mki67^hi CTLs, Ccl5^hi CTLs, activated Tregs and alloreactive B cells. We demonstrated local intercellular communication and revealed the upregulation of CXCR3 and its ligands in cardiac allografts. Finally, CXCR3 blockade significantly suppressed acute cardiac allograft rejection and inhibited the alloreactive T cell function.

Conclusions: These results provide a new insight into the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection, and suggest CXCR3 pathway may serve as a potential therapeutic target for transplant rejection.

Understanding Mammalian Hair Follicle Ecosystems by Single-Cell RNA Sequencing

Simple Summary

Single-cell sequencing technology can reflect cell population heterogeneity at the single-cell level, leading to a better understanding of the role of individual cells in the microenvironment. Over the past few years, single-cell sequencing technology has not only made more new discoveries in the study of cellular heterogeneity of other rare cells such as stem cells, but has also become the most powerful research method for embryonic development, organ differentiation, cancer occurrence, and cell mapping. In this review, we outline the use of scRNA-seq in hair follicles. In particular, by focusing on landmark studies and the recent discovery of novel subpopulations of hair follicles, we summarize the phenotypic diversity of hair follicle cells and their links to hair follicle morphogenesis. Enhancing our understanding of the progress of hair follicle research will help to elucidate the regulatory mechanisms that determine the fate of different types of cells in the hair follicle, thereby guiding hair loss treatment and hair-producing economic animal breeding research.

Abstract

Single-cell sequencing technology can fully reflect the heterogeneity of cell populations at the single cell level, making it possible for us to re-recognize various tissues and organs. At present, the sequencing study of hair follicles is transiting from the traditional ordinary transcriptome level to the single cell level, which will provide diverse insights into the function of hair follicle cells. This review focuses on research advances in the hair follicle microenvironment obtained from scRNA-seq studies of major cell types in hair follicle development, with a special emphasis on the discovery of new subpopulations of hair follicles by single-cell techniques. We also discuss the problems and current solutions in scRNA-seq observation and look forward to its prospects.

Identification of a Prognostic Model Based on Immune Cell Signatures in Clear Cell Renal Cell Carcinoma

Background. Accumulating evidence substantiated that the immune cells were intricately intertwined with the prognosis and therapy of clear cell renal cell carcinoma (ccRCC). We aimed to construct an immune cell signatures (ICS) score model to predict the prognosis of ccRCC patients and furnish guidance for finding appropriate treatment strategies. Methods. Based on The Cancer Genome Atlas (TCGA) database, the normalized enrichment score (NES) of 184 ICSf was calculated using single-sample gene set enrichment analysis (ssGSEA). An ICS score model was generated in light of univariate Cox regression and Least absolute shrinkage and selection operator (Lasso)-Cox regression, which was independently validated in ArrayExpress database. In addition, we appraised the predictive power of the model via Kaplan-Meier (K-M) curves and time-dependent receiver operating characteristic (ROC) curves. Eventually, immune infiltration, genomic alterations and immunotherapy were analyzed between high and low ICS score groups. Results. Initially, we screened 11 ICS with prognostic impact based on 515 ccRCC patients. K-M curves presented that the high ICS score group experienced a poorer prognosis ( $P<0.001$ ). In parallel, ROC curves revealed a satisfactory reliability of model to predict individual survival at 1, 3, and 5 years, with area under the curves (AUCs) of 0.744, 0.713, and 0.742, respectively. In addition, we revealed that the high ICS score group was characterized by increased infiltration of immune cells, strengthened BAP1 mutation frequency, and enhanced expression of immune checkpoint genes. Conclusion. The ICS score model has higher predictive power for patients’ prognosis and can instruct ccRCC patients in seeking suitable treatment.

Cancer Risk and Mutational Patterns Following Organ Transplantation

The rapid development of medical technology and widespread application of immunosuppressive drugs have improved the success rate of organ transplantation significantly. However, the use of immunosuppressive agents increases the frequency of malignancy greatly. With the prospect of “precision medicine” for tumors and development of next-generation sequencing technology, more attention has been paid to the application of high-throughput sequencing technology in clinical oncology research, which is mainly applied to the early diagnosis of tumors and analysis of tumor-related genes. All generations of cancers carry somatic mutations, meanwhile, significant differences were observed in mutational signatures across tumors. Systematic sequencing of cancer genomes from patients after organ transplantation can reveal DNA damage and repair processes in exposed cancer cells and their precursors. In this review, we summarize the application of high-throughput sequencing and organoids in the field of organ transplantation, the mutational patterns of cancer genomes, and propose a new research strategy for understanding the mechanism of cancer following organ transplantation.

FibROAD: a manually curated resource for multi-omics level evidence integration of fibrosis research

Organ fibrosis represents a vital health threat that substantially contributes to yearly mortality rates. While a considerable amount of research has been conducted on fibrosis, these reports have only focused on specific organs as affected within distinct disorders. Accordingly, results from such studies have been unable to provide a comprehensive understanding of the pathological processes involved. Here, we describe the development of FibROAD, an open-access database that integrates evidence from fibrosis-associated disorders as obtained from both the literature and multi-omics data. This resource will greatly assist both researchers and clinicians in the comprehension and treatment of this condition. FibROAD currently involves an assembly of 232 strong evidence-based fibrosis-related genes (FRGs) as garnered from 909 PubMed publications and contains lists of multi-omics data from > 4000 samples including RNA-seq, single-cell RNA-seq, miRNA-seq, ChIP-seq, ATAC-seq MeDIP-seq and MBD-seq as obtained from 17 different organs in 5 species. Results from integrative analyses as obtained using FibROAD have demonstrated that FRGs can be indicators for a wide range of organ fibrosis and reveal potential pro-fibrotic candidate genes for fibrosis research. In conclusion, FibROAD serves as a convenient platform where researchers can acquire integrated evidence and a more comprehensive understanding of fibrosis-related disorders.

Database URL  https://www.fibroad.org

Antigen presentation and interferon signatures in B cells driven by localized ablative cancer immunotherapy correlate with extended survival

Rationale: B cells have emerged as key regulators in protective cancer immunity. However, the activation pathways induced in B cells during effective immunotherapy are not well understood. Methods: We used a novel localized ablative immunotherapy (LAIT), combining photothermal therapy (PTT) with intra-tumor delivery of the immunostimulant N-dihydrogalactochitosan (GC), to treat mice bearing mouse mammary tumor virus-polyoma middle tumor-antigen (MMTV-PyMT). We used single-cell RNA sequencing to compare the transcriptional changes induced by PTT, GC and PTT+GC in B cells within the tumor microenvironment (TME). Results: LAIT significantly increased survival in the tumor-bearing mice, compared to the treatment by PTT and GC alone. We found that PTT, GC and PTT+GC increased the proportion of tumor-infiltrating B cells and induced gene expression signatures associated with B cell activation. Both GC and PTT+GC elevated gene expression associated with antigen presentation, whereas GC elevated transcripts that regulate B cell activation and GTPase function and PTT+GC induced interferon response genes. Trajectory analysis, where B cells were organized according to pseudotime progression, revealed that both GC and PTT+GC induced the differentiation of B cells from a resting state towards an effector phenotype. The analyses confirmed upregulated interferon signatures in the differentiated tumor-infiltrating B cells following treatment by PTT+GC but not by GC. We also observed that breast cancer patients had significantly longer survival time if they had elevated expression of genes in B cells that were induced by PTT+GC therapy in the mouse tumors. Conclusion: Our findings show that the combination of local ablation and local application of immunostimulant initiates the activation of interferon signatures and antigen-presentation in B cells which is associated with positive clinical outcomes for breast cancer. These findings broaden our understanding of LAIT's regulatory roles in remodeling TME and shed light on the potentials of B cell activation in clinical applications.

New insights on the monitoring of solid-organ allografts based on immune cell signatures

Attaining a fair long-term allograft survival remains a challenge for allogeneic transplantation worldwide. Although the emergence of immunosuppressants has caused noticeable progress in the management of immunologic rejection, proper application of these therapeutics and dose adjustments require delicate and real-time monitoring of recipients. Nevertheless, the majority of conventional allograft monitoring approaches are based on organ damage or functional tests that render them unable to predict the rejection events in early time points before the establishment of a functional alloimmune response. On the other hand, biopsy-based methods include invasive practices and are accompanied by serious complications. In recent years, there have been a myriad of attempts on the discovery of reliable and non-invasive approaches for the monitoring of allografts that regarding a close relationship between allografts and hosts' immune system, most of the attempts have been devoted to the studies on the immune response-associated biomarkers. The discovery of gene and protein expression patterns in immune cells along with their phenotypic characterization and secretome analysis as well as tracking the immune responses in allograft tissues and clinical specimens are among the notable attempts taken to discover the non-invasive predictive markers with a proper coincidence to the pathologic condition. Collectively, these studies suggest a list of candidate biomarkers with ideal potentials for early and non-invasive prediction of allograft rejection and shed light on the way towards developing more standardized and reproducible approaches for monitoring the allograft rejection.

Single-Cell Transcriptomic Analysis of Peripheral Blood Reveals a Novel B-Cell Subset in Renal Allograft Recipients With Accommodation

Background: Kidney transplantation (KTx) is a preeminent treatment for end-stage renal disease (ESRD). After the application of immunosuppressants (IS), renal allograft recipients could reach a state called accommodation which means they are neither rejected nor infected. This study aimed to describe the details of this immune accommodation and reveal a novel mechanism of IS on immune cell subpopulations.

Methods: We analyzed multiple cell subgroups and their gene expression of peripheral T, B, myeloid, and NK cells from renal allograft recipients with accommodation and healthy control (HC) by single-cell transcriptomics sequencing (scRNA-seq) and flow cytometry.

Results: A total of 8,272 cells were isolated and sequenced from three individuals, including 2,758 cells from HC, 2,550 cells from ESRD patient, and 2,964 cells from KTx patient, as well as 396 immune response–related genes were detected during sequencing. 5 T-cell, 4 NK-cell, 5 myeloid, and 4 B-cell clusters were defined. Among them, a B-cell subset (CD19⁺IGLC3^lowIGKC^highTCL1A^-CD127⁺) of renal transplant recipients with accommodation was significantly lower than that of HC and verified by flow cytometry, and this B-cell subset showed an activated potential because of its high expression of CD127. Furthermore, we found that IL32 might be the key cytokine to induce the differentiation of this B-cell cluster.

Conclusion: We found a novel B-cell subset (CD19⁺IGLC3^lowIGKC^highTCL1A^-CD127⁺) which was inhibited and decreased in renal allograft recipients with accommodation. This study might reveal the effect of commonly used IS in clinical practice on B-cell subsets and related mechanism.

The Role of Myeloid Cells in Acute Kidney Injury and Kidney Repair

AKI remains highly prevalent, yet no optimal therapy is available to prevent it or promote recovery after initial insult. Experimental studies have demonstrated that both innate and adaptive immune responses play a central role during AKI. In response to injury, myeloid cells are first recruited and activated on the basis of specific signals from the damaged microenvironment. The subsequent recruitment and activation state of the immune cells depends on the stage of injury and recovery, reflecting a dynamic and diverse spectrum of immunophenotypes. In this review, we highlight our current understanding of the mechanisms by which myeloid cells contribute to injury, repair, and fibrosis after AKI.

Studying Kidney Diseases at the Single-Cell Level

BACKGROUND

The kidney is a highly complex organ that performs diverse functions that are essential for health. Kidney disease occurs when the kidneys are damaged and fail to function properly. Single-cell analysis is a powerful technology that provides unprecedented insights into normal and abnormal kidney cell types and will transform our understanding of the mechanism underlying common kidney diseases.

SUMMARY

Our understanding of kidney disease pathogenesis is limited by the incomplete molecular characterization of cell types responsible for kidney functions. Application of single-cell technologies for the study of the kidney has revealed cellular heterogeneity, gene expression signatures, and molecular dynamics during the onset and development of kidney diseases. Single-cell analyses of kidney organoids and allograft tissues offer new insights into kidney organogenesis, disease mechanisms, and therapeutic outcomes. Collectively, a better understanding of kidney cell heterogeneity and the molecular dynamics of kidney diseases will improve diagnostic accuracy and facilitate the identification of novel treatment strategies in nephrology.

KEY MESSAGE

In this review article, we summarize recent single-cell studies on kidney diseases and discuss the impact of single-cell technology on both basic and clinical nephrology research.

Single-Cell Analysis Reveals Spatial Heterogeneity of Immune Cells in Lung Adenocarcinoma

The impacts of the tumor microenvironment (TME) on tumor evolvability remain unclear. A challenge for nearly all cancer types is spatial heterogeneity, providing substrates for the emergence and evolvability of drug resistance and leading to unfavorable prognosis. Understanding TME heterogeneity among different tumor sites would provide deeper insights into personalized therapy. We found 9,992 cell profiles of the TME in human lung adenocarcinoma (LUAD) samples at a single-cell resolution. By comparing different tumor sites, we discovered high TME heterogeneity. Single-sample gene set enrichment analysis (ssGSEA) was utilized to explore functional differences between cell subpopulations and between the core, middle and edge of tumors. We identified 8 main cell types and 27 cell subtypes of T cells, B cells, fibroblasts and myeloid cells. We revealed CD4+ naive T cells in the tumor core that express high levels of immune checkpoint molecules and have a higher activity of immune-exhaustion signaling. CD8+ T cell subpopulations in the tumor core correlate with the upregulated activity of transforming growth factor-β (TGF-β) and fibroblast growth factor receptor (FGFR) signaling and downregulated T cell activity. B cell subtypes in the tumor core downregulate cytokine production. In this study, we revealed that there was immunological heterogeneity in the TME of patients with LUAD that have different ratios of immune cells and stromal cells, different functions, and various degrees of activation of immune-related pathways in different tumor parts. Therefore, clarifying the spatial heterogeneity of the tumor in the immune microenvironment can help clinicians design personalized treatments.

Advances in single-cell sequencing: insights from organ transplantation

Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.

Current Methodological Challenges of Single-Cell and Single-Nucleus RNA-Sequencing in Glomerular Diseases

Single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) allow transcriptomic profiling of thousands of cells from a renal biopsy specimen at a single-cell resolution. Both methods are promising tools to unravel the underlying pathophysiology of glomerular diseases. This review provides an overview of the technical challenges that should be addressed when designing single-cell transcriptomics experiments that focus on glomerulopathies. The isolation of glomerular cells from core needle biopsy specimens for single-cell transcriptomics remains difficult and depends upon five major factors. First, core needle biopsies generate little tissue material, and several samples are required to identify glomerular cells. Second, both fresh and frozen tissue samples may yield glomerular cells, although every experimental pipeline has different (dis)advantages. Third, enrichment for glomerular cells in human tissue before single-cell analysis is challenging because no effective standardized pipelines are available. Fourth, the current warm cell-dissociation protocols may damage glomerular cells and induce transcriptional artifacts, which can be minimized by using cold dissociation techniques at the cost of less efficient cell dissociation. Finally, snRNA-seq methods may be superior to scRNA-seq in isolating glomerular cells; however, the efficacy of snRNA-seq on core needle biopsy specimens remains to be proven. The field of single-cell omics is rapidly evolving, and the integration of these techniques in multiomics assays will undoubtedly create new insights in the complex pathophysiology of glomerular diseases.

Dissecting the human kidney allograft transcriptome: single-cell RNA sequencing

PURPOSE OF REVIEW

Single-cell RNA sequencing (scRNA-seq) has provided opportunities to interrogate kidney allografts at a hitherto unavailable molecular level of resolution. Understanding of this technology is essential to better appreciate the relevant biomedical literature.

RECENT FINDINGS

Sequencing is a technique to determine the order of nucleotides in a segment of RNA or DNA. RNA-seq of kidney allograft tissues has revealed novel mechanistic insights but does not provide information on individual cell types and cell states. scRNA-seq enables to study the transcriptome of individual cells and assess the transcriptional differences and similarities within a population of cells. Initial studies on rejecting kidney allograft tissues in humans have identified the transcriptional profile of the active players of the innate and adaptive immune system. Application of scRNA-seq in a preclinical model of kidney transplantation has revealed that allograft-infiltrating myeloid cells follow a trajectory of differentiation from monocytes to proinflammatory macrophages and exhibit distinct interactions with kidney allograft parenchymal cells; myeloid cell expression of Axl played a major role in promoting intragraft myeloid cell and T-cell differentiation.

SUMMARY

The current review discusses the technical aspects of scRNA-seq and summarizes the application of this technology to dissect the human kidney allograft transcriptome.

Single-Cell RNA Sequencing Reveals the Immunological Profiles of Renal Allograft Rejection in Mice

Allograft rejection is a common immunological feature in renal transplantation and is associated with reduced graft survival. A mouse renal allograft rejection model was induced and single-cell RNA sequencing (scRNA-seq) data of CD45+ leukocytes in kidney allografts on days 7 (D7) and 15 (D15) after operation was analyzed to reveal a full immunological profiling. We identified 20 immune cell types among 10,921 leukocytes. Macrophages and CD8+ T cells constituted the main populations on both timepoints. In the process from acute rejection (AR) towards chronic rejection (CR), the proportion of proliferating and naïve CD8+ T cells dropped significantly. Both B cells and neutrophils decreased by about 3 folds. On the contrary, the proportion of macrophages and dendritic cells (DCs) increased significantly, especially by about a 4.5-fold increase in Ly6cloMrc1+ macrophages and 2.6 folds increase in Ly6cloEar2+ macrophages. Moreover, myeloid cells harbored the richest ligand and receptor (LR) pairs with other cells, particularly for chemokine ligands such as Cxcl9, Cxcl10, Cxcl16 and Yars. However, macrophages with weak response to interferon gamma (IFNg) contributed to rejection chronicization. To conclude, reduction in CD8 T cells, B cells and neutrophils while increasing in Ly6cloMrc1+ macrophages and Ly6cloEar2+ macrophages, may contribute significantly to the progress from AR towards CR.

Acidosis and alkali therapy in patients with kidney transplant is associated with transcriptional changes and altered abundance of genes involved in cell metabolism and acid-base balance

BACKGROUND

Metabolic acidosis occurs frequently in patients with kidney transplant and is associated with higher risk for and accelerated loss of graft function. To date, it is not known whether alkali therapy in these patients improves kidney function and whether acidosis and its therapy is associated with altered expression of proteins involved in renal acid-base metabolism.

METHODS

We collected retrospectively kidney biopsies from 22 patients. Of these patients, 9 had no acidosis, 9 had metabolic acidosis (plasma HCO3- < 22 mmol/l), and 4 had acidosis and received alkali therapy. We performed transcriptome analysis and immunohistochemistry for proteins involved in renal acid-base handling.

RESULTS

We found the expression of 40 transcripts significantly changed between kidneys from non-acidotic and acidotic patients. These genes are mostly involved in proximal tubule amino acid and lipid metabolism and energy homeostasis. Three transcripts were fully recovered by alkali therapy: the Kir4.2 K+-channel, an important regulator of proximal tubule HCO3--metabolism and transport, ACADSB and SHMT1, genes involved in beta-oxidation and methionine metabolism. Immunohistochemistry showed reduced staining for the proximal tubule NBCe1 HCO3- transporter in kidneys from acidotic patients that recovered with alkali therapy. In addition, the HCO3-exchanger pendrin was affected by acidosis and alkali therapy.

CONCLUSIONS

Metabolic acidosis in kidney transplant recipients is associated with alterations in the renal transcriptome that are partly restored by alkali therapy. Acid-base transport proteins mostly from proximal tubule were also affected by acidosis and alkali therapy suggesting that the downregulation of critical players contributes to metabolic acidosis in these patients.

Single-Cell Profiling Reveals Transcriptional Signatures and Cell-Cell Crosstalk in Anti-PLA2R Positive Idiopathic Membranous Nephropathy Patients

Idiopathic membranous nephropathy (IMN) is an organ-specific autoimmune disease of the kidney glomerulus. It may gradually progress to end-stage renal disease (ESRD) characterized by increased proteinuria, which leads to serious consequences. Although substantial advances have been made in the understanding of the molecular bases of IMN in the last 10 years, certain questions remain largely unanswered. To define the transcriptomic landscape at single-cell resolution, we analyzed kidney samples from 6 patients with anti-PLA2R positive IMN and 2 healthy control subjects using single-cell RNA sequencing. We then identified distinct cell clusters through unsupervised clustering analysis of kidney specimens. Identification of the differentially expressed genes (DEGs) and enrichment analysis as well as the interaction between cells were also performed. Based on transcriptional expression patterns, we identified all previously described cell types in the kidney. The DEGs in most kidney parenchymal cells were primarily enriched in genes involved in the regulation of inflammation and immune response including IL-17 signaling, TNF signaling, NOD-like receptor signaling, and MAPK signaling. Moreover, cell-cell crosstalk highlighted the extensive communication of mesangial cells, which infers great importance in IMN. IMN with massive proteinuria displayed elevated expression of genes participating in inflammatory signaling pathways that may be involved in the pathogenesis of the progression of IMN. Overall, we applied single-cell RNA sequencing to IMN to uncover intercellular interactions, elucidate key pathways underlying the pathogenesis, and identify novel therapeutic targets of anti-PLA2R positive IMN.

Tackling Chronic Kidney Transplant Rejection: Challenges and Promises

Despite advances in post-transplant management, the long-term survival rate of kidney grafts and patients has not improved as approximately forty percent of transplants fails within ten years after transplantation. Both immunologic and non-immunologic factors contribute to late allograft loss. Chronic kidney transplant rejection (CKTR) is often clinically silent yet progressive allogeneic immune process that leads to cumulative graft injury, deterioration of graft function. Chronic active T cell mediated rejection (TCMR) and chronic active antibody-mediated rejection (ABMR) are classified as two principal subtypes of CKTR. While significant improvements have been made towards a better understanding of cellular and molecular mechanisms and diagnostic classifications of CKTR, lack of early detection, differential diagnosis and effective therapies continue to pose major challenges for long-term management. Recent development of high throughput cellular and molecular biotechnologies has allowed rapid development of new biomarkers associated with chronic renal injury, which not only provide insight into pathogenesis of chronic rejection but also allow for early detection. In parallel, several novel therapeutic strategies have emerged which may hold great promise for improvement of long-term graft and patient survival. With a brief overview of current understanding of pathogenesis, standard diagnosis and challenges in the context of CKTR, this mini-review aims to provide updates and insights into the latest development of promising novel biomarkers for diagnosis and novel therapeutic interventions to prevent and treat CKTR.

The Role of RNA-Sequencing as a New Genetic Diagnosis Tool

Purpose of Review

Whole exome sequencing (WES) and whole-genome sequencing (WGS) are frontline approaches for the genetic diagnosis of rare diseases. However, WES/WGS fails in up to 75% of cases. Transcriptomics via RNA-sequencing (RNA-Seq) is a novel approach that aims to increase the diagnostic yield in rare diseases.

Recent Findings

Recent publications focus on the success of RNA-Seq for increasing diagnosis rates in WES/WGS-negative patients in up to 36% of cases, across a range of different diseases, sample sizes, and tissue types.

Summary

RNA-Seq is beneficial for aiding prioritisation of causative variants currently not detected or often overlooked by WES/WGS alone. An improvement in diagnostic yields has been demonstrated using multiple source tissues, with muscle and fibroblasts being the most representative, but the more accessible blood still demonstrating diagnostic success, particularly in neuromuscular disorders. The introduction of RNA-Seq to the genetic diagnosis toolbox promises to be a useful complementary tool to WES/WGS for improving genetic diagnosis in patients with rare disease.

Single-Cell Profiling of Kidney Transplant Recipients With Immunosuppressive Treatment Reveals the Dynamic Immune Characteristics

Kidney transplantation is currently the first choice of treatment for various types of end-stage renal failure, but there are major limitations in the application of immunosuppressive protocols after kidney transplantation. When the dose of immunosuppressant is too low, graft rejection occurs easily, while a dose that is too high can lead to graft loss. Therefore, it is very important to explore the immune status of patients receiving immunosuppressive agents after kidney transplantation. To compare the immune status of the recipient’s whole peripheral blood before and after receipt of immunosuppressive agents, we used single-cell cytometry by time-of-flight (CyTOF) to detect the peripheral blood immune cells in five kidney transplant recipients (KTRs) from the Department of Organ Transplantation of Zhujiang Hospital of Southern Medical University before and after receiving immunosuppressive agents. Based on CyTOF analysis, we detected 363,342 live single immune cells. We found that the immune cell types of the KTRs before and after receipt of immunosuppressive agents were mainly divided into CD4+ T cells, CD8+ T cells, B cells, NK cells/γδ T cells, monocytes/macrophages, granulocytes, and dendritic cells (DCs). After further reclustering of the above cell types, it was found that the immune cell subclusters in the peripheral blood of patients underwent major changes after receipt of immunosuppressants. After receiving immunosuppressive therapy, the peripheral blood of KTRs had significantly increased levels of CD57+NK cells and significantly decreased levels of central memory CD4+ T cells, follicular helper CD4+ T cells, effector CD8+ T cells, effector memory CD8+ T cells and naive CD8+ T cells. This study used CyTOF to classify immune cells in the peripheral blood of KTRs before and after immunosuppressive treatment, further compared differences in the proportions of the main immune cell types and immune cell subgroups before and after receipt of immunosuppressants, and provided relatively accurate information for assessment and treatment strategies for KTRs.

Crosstalk Between the MSI Status and Tumor Microenvironment in Colorectal Cancer

Colorectal cancer (CRC) patients, especially those with deficient mismatch repair (dMMR)/microsatellite instability-high (MSI-H) tumors, whose sensitivity to immune checkpoint inhibitors (ICIs) is significantly higher than that of patients with microsatellite-stable (MSS)/microsatellite instability-low (MSI-L) tumors, have derived clinical benefits from immunotherapy. Most studies have not systematically evaluated the immune characteristics and immune microenvironments of MSI-H and MSS/MSI-L CRCs. We analyzed the relationship between the MSI status and prognosis of ICI treatment in an immunotherapy cohort. We further used mutation data for the immunotherapy and The Cancer Genome Atlas (TCGA)-CRC [colon adenocarcinoma (COAD) + rectum adenocarcinoma (READ)] cohorts. For mRNA expression, mutation data analysis of the immune microenvironment and immunogenicity under different MSI statuses was performed. Compared with CRC patients with MSS/MSI-L tumors, those with MSI-H tumors significantly benefited from ICI treatment. MSI-H CRC had more immune cell infiltration, higher expression of immune-related genes, and higher immunogenicity than MSS/MSI-L CRC. The MANTIS score, which is used to predict the MSI status, was positively correlated with immune cells, immune-related genes, and immunogenicity. In addition, subtype analysis showed that COAD and READ might have different immune microenvironments. MSI-H CRC may have an inflammatory tumor microenvironment and increased sensitivity to ICIs. Unlike those of MSI-H READ, the immune characteristics of MSI-H COAD may be consistent with those of MSI-H CRC.