An enterococcal phage-derived enzyme suppresses graft-versus-host disease.

Changes in the gut microbiome have pivotal roles in the pathogenesis of acute graft-versus-host disease (aGVHD) after allogenic haematopoietic cell transplantation (allo-HCT)1-6. However, effective methods for safely resolving gut dysbiosis have not yet been established. An expansion of the pathogen Enterococcus faecalis in the intestine, associated with dysbiosis, has been shown to be a risk factor for aGVHD7-10. Here we analyse the intestinal microbiome of patients with allo-HCT, and find that E. faecalis escapes elimination and proliferates in the intestine by forming biofilms, rather than by acquiring drug-resistance genes. We isolated cytolysin-positive highly pathogenic E. faecalis from faecal samples and identified an anti-E. faecalis enzyme derived from E. faecalis-specific bacteriophages by analysing bacterial whole-genome sequencing data. The antibacterial enzyme had lytic activity against the biofilm of E. faecalis in vitro and in vivo. Furthermore, in aGVHD-induced gnotobiotic mice that were colonized with E. faecalis or with patient faecal samples characterized by the domination of Enterococcus, levels of intestinal cytolysin-positive E. faecalis were decreased and survival was significantly increased in the group that was treated with the E. faecalis-specific enzyme, compared with controls. Thus, administration of a phage-derived antibacterial enzyme that is specific to biofilm-forming pathogenic E. faecalis-which is difficult to eliminate with existing antibiotics-might provide an approach to protect against aGVHD.

The tidyomics ecosystem: enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipulation standard. Here we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analyzing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas, spanning six data frameworks and ten analysis tools.

biotextgraph: graphical summarization of functional similarities from textual information.

SUMMARY: Functional interpretation of biological entities such as differentially expressed genes is one of the fundamental analyses in bioinformatics. The task can be addressed by using biological pathway databases with enrichment analysis (EA). However, textual description of biological entities in public databases is less explored and integrated in existing tools and it has a potential to reveal new mechanisms. Here, we present a new R package biotextgraph for graphical summarization of omics' textual description data which enables assessment of functional similarities of the lists of biological entities. We illustrate application examples of annotating gene identifiers in addition to EA. The results suggest that the visualization based on words and inspection of biological entities with text can reveal a set of biologically meaningful terms that could not be obtained by using biological pathway databases alone. The results suggest the usefulness of the package in the routine analysis of omics-related data. The package also offers a web-based application for convenient querying. AVAILABILITY AND IMPLEMENTATION: The package, documentation, and web server are available at: https://github.com/noriakis/biotextgraph.

ggkegg: analysis and visualization of KEGG data utilizing the grammar of graphics.

SUMMARY: The Kyoto Encyclopedia of Genes and Genomes (KEGG) database serves as a valuable systems biology resource and is widely utilized in diverse research fields. However, existing software does not allow flexible visualization and network analyses of the vast and complex KEGG data. We developed ggkegg, an R package that integrates KEGG information with ggplot2 and ggraph. ggkegg enables enhanced visualization and network analyses of KEGG data. We demonstrate the utility of the package by providing examples of its application in single-cell, bulk transcriptome, and microbiome analyses. ggkegg may empower researchers to analyze complex biological networks and present their results effectively. AVAILABILITY AND IMPLEMENTATION: The package and user documentation are available at: https://github.com/noriakis/ggkegg.

Preemptive Intravenous Human Immunoglobulin G Suppresses BK Polyomavirus Replication and Spread of Infection In Vitro.

BK polyomavirus (BKPyV) infection causes various diseases in immunocompromised patients. Cells from human lung and kidney were infected with BKPyV and treated with commercially available intravenous immunoglobulin G (IVIG). Its effects on BKPyV replication and spread of infection were investigated, focusing on administration timing. IVIG treatment 3 hours after infection suppressed BKPyV replication assessed by real-time PCR and expression of the viral capsid protein 1 and large T-antigen. IVIG effectively reduced the number of BKPyV-infected cells 2 weeks after infection in an antibody titer-dependent manner. Virus release in the culture supernatants was not influenced by IVIG treatment 6-80 hours and 3-9 days after infection. Collectively, IVIG did not affect viral release from infected cells but inhibited the spread of infection by neutralizing the released virus and blocking the new infected cell formation, indicating greater efficacy in early localized infection. BKPyV replication resumed in IVIG-treated cultures at 7 days after IVIG removal. Early prophylactic administration of IVIG is expected to reduce the growth and spread of BKPyV infection, resulting in the reduction of infected cell lesions and prevention of BKPyV-associated diseases.

CBNplot: Bayesian network plots for enrichment analysis.

SUMMARY: When investigating gene expression profiles, determining important directed edges between genes can provide valuable insights in addition to identifying differentially expressed genes. In the subsequent functional enrichment analysis (EA), understanding how enriched pathways or genes in the pathway interact with one another can help infer the gene regulatory network (GRN), important for studying the underlying molecular mechanisms. However, packages for easy inference of the GRN based on EA are scarce. Here, we developed an R package, CBNplot, which infers the Bayesian network (BN) from gene expression data, explicitly utilizing EA results obtained from curated biological pathway databases. The core features include convenient wrapping for structure learning, visualization of the BN from EA results, comparison with reference networks, and reflection of gene-related information on the plot. As an example, we demonstrate the analysis of bladder cancer-related datasets using CBNplot, including probabilistic reasoning, which is a unique aspect of BN analysis. We display the transformability of results obtained from one dataset to another, the validity of the analysis as assessed using established knowledge and literature, and the possibility of facilitating knowledge discovery from gene expression datasets. AVAILABILITY AND IMPLEMENTATION: The library, documentation and web server are available at https://github.com/noriakis/CBNplot. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Individual health-disease phase diagrams for disease prevention based on machine learning.

Early disease detection and prevention methods based on effective interventions are gaining attention worldwide. Progress in precision medicine has revealed that substantial heterogeneity exists in health data at the individual level and that complex health factors are involved in chronic disease development. Machine-learning techniques have enabled precise personal-level disease prediction by capturing individual differences in multivariate data. However, it is challenging to identify what aspects should be improved for disease prevention based on future disease-onset prediction because of the complex relationships among multiple biomarkers. Here, we present a health-disease phase diagram (HDPD) that represents an individual's health state by visualizing the future-onset boundary values of multiple biomarkers that fluctuate early in the disease progression process. In HDPDs, future-onset predictions are represented by perturbing multiple biomarker values while accounting for dependencies among variables. We constructed HDPDs for 11 diseases using longitudinal health checkup cohort data of 3,238 individuals, comprising 3,215 measurement items and genetic data. The improvement of biomarker values to the non-onset region in HDPD remarkably prevented future disease onset in 7 out of 11 diseases. HDPDs can represent individual physiological states in the onset process and be used as intervention goals for disease prevention.

Use of proton pump inhibitors and macrolide antibiotics and risk of acute kidney injury: a self-controlled case series study.

BACKGROUND: Proton pump inhibitors (PPIs) are widely used for the treatment of gastrointestinal disorders such as peptic ulcer disease and dyspepsia. However, several studies have suggested that PPI use increases the risk of acute kidney injury (AKI). PPIs are often concomitantly used with antibiotics, such as macrolides and penicillins for Helicobacter pylori eradication. Although macrolide antibiotics are considered to have relatively low nephrotoxicity, they are well known to increase the risk of AKI due to drug-drug interactions. In this study, we aimed to investigate the association between PPI use and the development of AKI. We also evaluated the effect of concomitant use of PPIs and macrolide antibiotics on the risk of AKI. METHODS: This self-controlled case series study was conducted using electronic medical records at Kyoto University Hospital. We identified patients who were prescribed at least one PPI and macrolide antibiotic between January 2014 and December 2019 and underwent blood examinations at least once a year. An adjusted incident rate ratio (aIRR) of AKI with PPI use or concomitant use macrolide antibiotics with PPIs was estimated using a conditional Poisson regression model controlled for the estimated glomerular filtration rate at the beginning of observation and use of potentially nephrotoxic antibiotics. RESULTS: Of the 3,685 individuals who received PPIs and macrolide antibiotics, 766 patients with episodes of stage 1 or higher AKI were identified. Any stage of AKI was associated with PPI use (aIRR, 1.80 (95% confidence interval (CI) 1.60 to 2.04)). Stage 2 or higher AKI was observed in 279 cases, with an estimated aIRR of 2.01 (95% CI 1.57 to 2.58, for PPI use). For the period of concomitant use of macrolide antibiotics with PPIs compared with the period of PPIs alone, an aIRR of stage 1 or higher AKI was estimated as 0.82 (95% CI 0.60 to 1.13). CONCLUSIONS: Our findings added epidemiological information for the association between PPI use and an increased risk of stage 1 or higher AKI. However, we did not detect an association between the concomitant use of macrolide antibiotics and an increased risk of AKI in PPI users.

Metagenomic profiling of gut microbiome in early chronic kidney disease.

BACKGROUND: The relationship between chronic kidney disease (CKD) and the gut microbiome, which interact through chronic inflammation, uraemic toxin production and immune response regulation, has gained interest in the development of CKD therapies. However, reports using shotgun metagenomic analysis of the gut microbiome are scarce, especially for early CKD. Here we characterized gut microbiome differences between non-CKD participants and ones with early CKD using metagenomic sequencing. METHODS: In total, 74 non-CKD participants and 37 participants with early CKD were included based on propensity score matching, controlling for various factors including dietary intake. Stool samples were collected from participants and subjected to shotgun sequencing. Bacterial and pathway abundances were profiled at the species level with MetaPhlAn2 and HUMAnN2, respectively, and overall microbiome differences were determined using Bray-Curtis dissimilarities. Diabetic and non-diabetic populations were analysed separately. RESULTS: For diabetic and non-diabetic participants, the mean estimated glomerular filtration rates of the CKD group were 53.71 [standard deviation (SD) 3.87] and 53.72 (SD 4.44), whereas those of the non-CKD group were 72.63 (SD 7.72) and 76.10 (SD 9.84), respectively. Alpha and beta diversities were not significantly different between groups. Based on taxonomic analysis, butyrate-producing species Roseburia inulinivorans, Ruminococcus torques and Ruminococcus lactaris were more abundant in the non-CKD group, whereas Bacteroides caccae and Bacteroides coprocora were more abundant in the non-diabetic CKD group. CONCLUSIONS: Although gut microbiome changes in individuals with early CKD were subtle, the results suggest that changes related to producing short-chain fatty acids can already be observed in early CKD.

[Determination of Endograft Size in Thoracic Endovascular Aortic Repair for Blunt Thoracic Aortic Injury:Report of a Case].

Although the efficacy of thoracic endovascular aortic repair( TEVAR) for blunt thoracic aortic injury (BTAI) has been reported, the determination of the proper endograft size for TEVAR in BTAI cases is yet to be established. The management of BTAI by TEVAR may not be effective if a wrong endograft size is selected, possibly leading to fatal outcomes. In this case report, a hemodynamically unstable patient with BTAI was saved by TEVAR, and the preoperative and postoperative changes in the aortic diameter were compared. In TEVAR for BTAI, the effects of hemodynamic instability should be considered and the appropriate device size should be determined based on blood pressure, pulse, and inferior vena cava diameter.

Simultaneous scanning near-field optical and X-ray diffraction microscopy for correlative nanoscale structure-property characterization.

A multimodal imaging instrument has been developed that integrates scanning near-field optical microscopy with nanofocused synchrotron X-ray diffraction imaging. The instrument allows for the simultaneous nanoscale characterization of electronic/near-field optical properties of materials together with their crystallographic structure, facilitating the investigation of local structure-property relationships. The design, implementation and operating procedures of this instrument are reported. The scientific capabilities are demonstrated in a proof-of-principle study of the insulator-metal phase transition in samarium sulfide (SmS) single crystals induced by applying mechanical pressure via a scanning tip. The multimodal imaging of an in situ tip-written region shows that the near-field optical reflectivity can be correlated with the heterogeneously transformed structure of the near-surface region of the crystal.

Anti-inflammatory and morphologic effects of pitavastatin on carotid arteries and thoracic aorta evaluated by integrated backscatter trans-esophageal ultrasound and PET/CT: a prospective randomized comparative study with pravastatin (EPICENTRE study).

BACKGROUND: We sought to evaluate the effects of a strong lipophilic statin (pitavastatin) on plaque components and morphology assessed by transesophageal echocardiography (TEE) and transthoracic echocardiography (TTE), as well as plaque inflammation assessed by 18F-fluorodeoxyglucose (FDG) PET/CT in the thoracic aorta and the carotid artery. Furthermore, we compared the effects of pitavastatin with those of mild hydrophilic statin (pravastatin). METHODS: We examined atherosclerotic plaques in the thoracic aorta by TEE and those in the carotid artery by integrated backscatter (IBS)-TTE and PET/CT. We identified the target plaque, where there was macrophage infiltration and inflammation, by strong FDG uptake in the thoracic aorta and carotid arteries and measured maximum standard uptake values (max SUV) by PET/CT. We measured the intima-media thickness (IMT) and the corrected IBS (cIBS) values in the intima-media complex by TEE and TTE at the same site of FDG accumulation by PET/CT. RESULTS: Patients were randomly divided into two treatment groups: a pitavastatin group (PI group: n =10, 68.4 ± 5.1 years) and a pravastatin group (PR group: n =10, 63.9 ± 11.2 years). The same examinations were performed after six months at the same site in each patient. We used calculated target-to-background ratio (TBR) to measure max SUV of plaques and evaluated percent change of TBR. There was no significant difference in low density lipoprotein-cholesterol, TBR, IMT and cIBS values in plaques at baseline between the PI and PR groups. After treatment, there was greater improvement in TBR, cIBS values and IMT in the PI group than the PR group. CONCLUSIONS: The pravastatin treatment was less effective on plaque inflammation than pitavastatin treatment. This trend was the same in the carotid arteries and the thoracic aorta. Pitavastatin not only improved the atherosis as measured by IMT and cIBS values but also attenuated inflammation of plaques as measured by max SUV at the same site. The present study indicated that pitavastatin has stronger effects on the regression and stabilization of plaques in the thoracic aorta and carotid arteries compared with pravastatin.

Outcomes of thoracic endovascular aortic repair using fenestrated stent grafts in patients with thoracic aortic distal arch aneurysms.

OBJECTIVES: Thoracic endovascular aortic repair (TEVAR) for aortic arch aneurysms is challenging because of anatomical restrictions and the presence of cervical branches. Revascularization of the cervical branch is required when conventional commercial stent grafts are used. TEVAR using fenestrated stent grafts (FSG) often does not require additional procedures to revascularize cervical branches. This study aimed to evaluate the features and initial and midterm outcomes of TEVAR using fenestrated stent grafts. METHODS: From April 2007 to December 2016, 101 consecutive patients underwent TEVAR using fenestrated stent grafts for distal aortic arch aneurysms at a single centre. Technical success, complications, freedom from aneurysm-related death, secondary intervention and aneurysm progression were retrospectively investigated. RESULTS: All the patients underwent TEVAR using fenestrated stent grafts. The 30-day mortality rate was zero. Cerebral infarction, access route problems and spinal cord injury occurred in 4, 3 and 2 patients, respectively. Each type of endoleak was observed in 38 of the 101 patients during the course of the study; 20/38 patients had minor type 1 endoleaks at the time of discharge. The endoleak disappeared in 2 patients and showed no significant change in 8 patients; however, the aneurysm expanded over time in 10 patients. Additional treatment was performed in 8 of the 10 patients with type 1 endoleaks and dilatation of the aneurysm. The rate of freedom from aneurysm-related death during the observation period was 98%. CONCLUSIONS: TEVAR with FSG is a simple procedure, with few complications. Additional treatment has been observed to reduce aneurysm-related deaths, even in patients with endoleaks and enlarged aneurysms. Based on this study, the outcomes of endovascular repair of aortic arch aneurysms using a fenestrated stent graft seem acceptable.

Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy.

BACKGROUND: Acute kidney injury (AKI) is a critical complication of immune checkpoint inhibitor therapy. Since the etiology of AKI in patients undergoing cancer therapy varies, clarifying underlying causes in individual cases is critical for optimal cancer treatment. Although it is essential to individually analyze immune checkpoint inhibitor-treated patients for underlying pathologies for each AKI episode, these analyses have not been realized. Herein, we aimed to individually clarify the underlying causes of AKI in immune checkpoint inhibitor-treated patients using a new clustering approach with Shapley Additive exPlanations (SHAP). METHODS: We developed a gradient-boosting decision tree-based machine learning model continuously predicting AKI within 7 days, using the medical records of 616 immune checkpoint inhibitor-treated patients. The temporal changes in individual predictive reasoning in AKI prediction models represented the key features contributing to each AKI prediction and clustered AKI patients based on the features with high predictive contribution quantified in time series by SHAP. We searched for common clinical backgrounds of AKI patients in each cluster, compared with annotation by three nephrologists. RESULTS: One hundred and twelve patients (18.2%) had at least one AKI episode. They were clustered per the key feature, and their SHAP value patterns, and the nephrologists assessed the clusters' clinical relevance. Receiver operating characteristic analysis revealed that the area under the curve was 0.880. Patients with AKI were categorized into four clusters with significant prognostic differences (p = 0.010). The leading causes of AKI for each cluster, such as hypovolemia, drug-related, and cancer cachexia, were all clinically interpretable, which conventional approaches cannot obtain. CONCLUSION: Our results suggest that the clustering method of individual predictive reasoning in machine learning models can be applied to infer clinically critical factors for developing each episode of AKI among patients with multiple AKI risk factors, such as immune checkpoint inhibitor-treated patients.

Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information.

Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findings from 206 patients with IPF and 36 controls. Differential protein expression analysis was also performed by edgeR and incorporated into the constructed network. We have successfully visualized the relationship between biomolecules and clinical findings with this approach. The IPF-specific network included modules associated with TGF-ß signaling (TGFB1 and LRC32), fibrosis-related (A2MG and PZP), myofibroblast and inflammation (LRP1 and ITIH4), complement-related (SAA1 and SAA2), as well as serum markers, and clinical symptoms (KL-6, SP-D and fine crackles). Notably, it identified SAA2 associated with lymphocyte counts and PSPB connected with the serum markers KL-6 and SP-D, along with fine crackles as clinical manifestations. These results contribute to the elucidation of the pathogenesis of IPF and potential therapeutic targets.

The tidyomics ecosystem: Enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. Here, we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning, and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.

Quantum critical state in a magnetic quasicrystal.

Quasicrystals are metallic alloys that possess long-range, aperiodic structures with diffraction symmetries forbidden to conventional crystals. Since the discovery of quasicrystals by Schechtman et al. in 1984, there has been considerable progress in resolving their geometric structure. For example, it is well known that the golden ratio of mathematics and art occurs over and over again in their crystal structure. However, the characteristic properties of the electronic states--whether they are extended as in periodic crystals or localized as in amorphous materials--are still unresolved. Here we report the first observation of quantum (T = 0) critical phenomena of the Au-Al-Yb quasicrystal--the magnetic susceptibility and the electronic specific heat coefficient arising from strongly correlated 4f electrons of the Yb atoms diverge as T→0. Furthermore, we observe that this quantum critical phenomenon is robust against hydrostatic pressure. By contrast, there is no such divergence in a crystalline approximant, a phase whose composition is close to that of the quasicrystal and whose unit cell has atomic decorations (that is, icosahedral clusters of atoms) that look like the quasicrystal. These results clearly indicate that the quantum criticality is associated with the unique electronic state of the quasicrystal, that is, a spatially confined critical state. Finally we discuss the possibility that there is a general law underlying the conventional crystals and the quasicrystals.

Home-based cardiac rehabilitation decreases red cell distribution width in chronic heart failure.

OBJECTIVE: Red cell distribution width (RDW) is a measure of variation in the volume of circulating erythrocytes and has recently emerged as a powerful prognostic marker in heart failure. We studied the effect of 5-month, home-based cardiac rehabilitation on RDW. METHODS AND RESULTS: Sixty-two patients (age: median 67 years, IQR 63-74) with chronic heart failure caused by reduced left ventricular systolic function were enrolled. Exercise time and physical activity levels out of the hospital were determined by a single-axial accelerometer. Baseline RDW values were: median 13.6, IQR 12.8-14.4%, with 13 patients (21.0%) showing values above the upper normal limit. RDW values were decreased significantly after training in the 13 patients with elevated baseline RDW values (P < 0.01), but not in the remaining 49 patients with normal baseline RDW values. There was a highly significant correlation between baseline RDW and changes in RDW after exercise training (P = 0.0001, r2 = 0.628, n = 62). The time spent for moderate (> 3 METs) exercise was: median 9.0, IQR 3.0-18.8 minutes per day. CONCLUSIONS: Relatively low intensity, home-based cardiac rehabilitation was associated with decreased RDW in heart failure patients with abnormal RDW.

Definition of a Dietary Pattern Expressing the Intake of Vegetables and Fruits and Its Association with Intestinal Microbiota.

Daily dietary habits directly or indirectly influence the intestinal microbiota, and the resulting changes in its composition and metabolic activity alter the health conditions of the host. Although many studies have analyzed the association between individual nutrients/food items and intestinal microbiota, the assessment of the diet and intestinal microbiota from a macroscopic perspective has not yet been performed in Japan. Therefore, we focused on vegetables and fruits and aimed to identify dietary patterns of high intake of these foods and to examine their relationship with the intestinal microbiota. This cross-sectional study included 1019 healthy individuals aged ≥20 years in a rural area in northern Japan. Six dietary patterns were detected by factor analysis using the brief-type self-administered diet history questionnaire (BDHQ) data to identify the "vege pattern", which was the dietary pattern rich in vegetables and fruits. Permutational multivariate analysis of variance revealed changes in ß-diversity according to dietary patterns. In multivariable-adjusted models, the adherence to the vege pattern was positively correlated with α-diversity. This is the first study to reveal a correlation between intestinal microbiota and dietary habits rich in vegetables and fruits in a rural area of Japan.

Exploring the mechanism of BK polyomavirus-associated nephropathy through consensus gene network approach.

BK polyomavirus-associated nephropathy occurs in kidney transplant recipients under immunosuppressive treatment. BK polyomavirus is implicated in cancer development and invasion, and case reports of renal cell carcinoma and urothelial carcinoma possibly associated with BK polyomavirus has been reported. Further, it has been suggested that the immune responses of KT-related diseases could play a role in the pathogenesis and progression of renal cell carcinoma. Thus, we thought to examine the relationship between BK polyomavirus-associated nephropathy and renal cell carcinoma in terms of gene expression. To identify the common and specific immune responses involved in kidney transplantation-related diseases with a specific focus on BK polyomavirus-associated nephropathy, we performed consensus weighted gene co-expression network analysis on gene profile datasets of renal biopsy samples from different institutions. After the identification of gene modules and validation of the obtained network by immunohistochemistry of the marker across kidney transplantation-related diseases, the relationship between prognosis of renal cell carcinoma and modules was assessed. We included the data from 248 patients and identified the 14 gene clusters across the datasets. We revealed that one cluster related to the translation regulating process and DNA damage response was specifically upregulated in BK polyomavirus-associated nephropathy. There was a significant association between the expression value of hub genes of the identified cluster including those related to cGAS-STING pathway and DNA damage response, and the prognosis of renal cell carcinoma. The study suggested the potential link between kidney transplantation-related diseases, especially specific transcriptomic signature of BK polyomavirus associated nephropathy and renal cell carcinoma.