STIL/AURKA axis promotes cell proliferation by influencing primary cilia formation in bladder cancer.

BACKGROUND: The primary cilia (PC) is a microtubule-based and nonmotile organelle which protrudes from the surface of almost all mammalian cells. At present, PC has been found to be a deficiency or loss in multiple cancers. Restoring PC could be a novel targeting therapy strategy. Our research showed that PC was reduced in human bladder cancer (BLCA) cells, and PC deficiency promotes cell proliferation. However, the concrete mechanisms remain unknown. SCL/TAL1 interrupting locus (STIL), a PC-related protein, was screened in our previous study and could influence the cell cycle by regulating PC in tumor cells. In this study, we aimed to elucidate the function of STIL for PC to explore the underlying mechanism of PC in BLCA. METHODS: Public database analysis, western blot, and enzyme-linked immunosorbent assay (ELISA) were used to screen genes and explore gene expression alteration. Immunofluorescence and western blot were utilized to investigate PC. Wound healing assay, clone formation assay, and CCK-8 assay were used to explore cell migration, growth, and proliferation. The co-immunoprecipitation and western blot were employed to reveal the interaction of STIL and AURKA. RESULTS: We found that high STIL expression is correlated with poor outcomes of BLCA patients. Further analysis revealed that STIL overexpression could inhibit PC formation, activate SHH signaling pathways, and promote cell proliferation. In contrast, STIL-knockdown could promote PC formation, inactivate SHH signaling, and inhibit cell proliferation. Furthermore, we found that the regulatory functions of STIL for PC depend on AURKA. STIL could influence proteasome activity and maintain AURKA stabilization. AURKA-knockdown could reverse PC deficiency caused by STIL overexpression for PC in BLCA cells. We observed that co-knockdown in STIL and AURKA significantly enhanced PC assembly. CONCLUSION: In summary, our result provides a potential therapy target for BLCA based on the restoration of PC.

Antegrade flexible ureteroscopy-assisted percutaneous nephrolithotomy for staghorn calculi: a prospective randomized controlled study.

The aim is to compare the efficacy and safety between single percutaneous nephrolithotomy (sPNL) and antegrade flexible ureteroscopy-assisted percutaneous nephrolithotomy (aPNL) for the treatment of staghorn calculi. A prospective randomized controlled study was conducted at the Second Hospital of Tianjin Medical University. A total of 160 eligible patients were included, with 81 in the sPNL group and 79 in the aPNL group. The study first compared the overall differences between sPNL and aPNL. Then, the patients were divided into two subgroups: Group 1 (with less than 5 stone branches) and Group 2 (with 5 or more stone branches), and the differences between the two subgroups were further analyzed. The results showed that aPNL had a higher stone-free rate (SFR) and required fewer percutaneous tracts, with a shorter operation time compared to sPNL (P < 0.05). Moreover, aPNL significantly reduced the need for staged surgery, particularly in patients with 5 or more stone branches. Moreover, there were no significant differences in the changes of hemoglobin levels and the need for blood transfusions between the sPNL and aPNL groups, and the incidence of multiple tracts was lower in the aPNL group. The two groups showed comparable rates of perioperative complications. We concluded that aPNL resulted in a higher SFR for staghorn calculi, and required fewer multiple percutaneous tracts, reduced the need for staged surgery, and had a shorter operative time than PNL alone, especially for patients with 5 or more stone branches. Furthermore, aPNL did not increase the incidence of surgical complications.

Construction of exosome-related genes risk model in kidney cell carcinoma predicts prognosis and immune therapy response.

Renal cell carcinoma (RCC) is one of the most prevalent types of urological cancer. Exosomes are vesicles derived from cells and have been found to promote the development of RCC, but the potential biomarker and molecular mechanism of exosomes on RCC remain ambiguous. Here, we first screened differentially expressed exosome-related genes (ERGs) by analyzing The Cancer Genome Atlas (TCGA) database and exoRBase 2.0 database. We then determined prognosis-related ERGs (PRERGs) by univariate Cox regression analysis. Gene Dependency Score (gDS), target development level, and pathway correlation analysis were utilized to examine the importance of PRERGs. Machine learning and lasso-cox regression were utilized to screen and construct a 5-gene risk model. The risk model showed high predictive accuracy for the prognosis of patients and proved to be an independent prognostic factor in three RCC datasets, including TCGA-KIRC, E-MTAB-1980, and TCGA-KIRP datasets. Patients with high-risk scores showed worse outcomes in different clinical subgroups, revealing that the risk score is robust. In addition, we found that immune-related pathways are highly enriched in the high-risk group. Activities of immune cells were distinct in high-/low-risk groups. In independent immune therapeutic cohorts, high-risk patients show worse immune therapy responses. In summary, we identified several exosome-derived genes that might play essential roles in RCC and constructed a 5-gene risk signature to predict the prognosis of RCC and immune therapy response.

Development and validation of a nomogram to predict impacted ureteral stones via machine learning.

BACKGROUND: To develop and evaluate a nomogram for predicting impacted ureteral stones using some simple and easily available clinical features. METHODS: From June 2019 to July 2022, 480 patients who underwent ureteroscopic lithotripsy (URSL) for ureteral calculi were enrolled in the study. From the eligible study population between June 2019 and December 2020, a training and validation set was randomly generated in a 7:3 ratio. To further evaluate the generalization performance of the nomogram, we performed an additional validation using the data from January 2021 to July 2022. Lasso regression analysis was used to identify the most useful predictive features. Subsequently, a multivariate logistic regression algorithm was applied to select independent predictive features. The predictive performance of the nomogram was assessed using Receiver Operating Characteristic (ROC) curves, calibration curves and decision Curve Analysis (DCA). The Hosmer-Lemeshow Test was utilized to evaluate the overall goodness of fit of the nomogram. RESULTS: Multivariate logistic regression analysis showed that flank pain, hydronephrosis, stone length/width, HU below (Hounsfield unit density of the ureter center below the stone), HU above/below (HU above divided by HU below) and UWT (ureteral wall thickness) were ascertained as independent predictors of impacted ureteral stones. The nomogram showed outstanding performance within the training dataset, with the area under the curve (AUC) of 0.907. Moreover, the AUC was 0.874 in the validation dataset. The ROC curve, calibration curve, DCA curve and Hosmer-Lemeshow Test suggested that the nomogram maintains excellent clinical applicability and demonstrates commendable performance. Similar results were achieved in the test dataset as well. CONCLUSIONS: We established a nomogram that can be effectively used for preoperative diagnosis of impacted ureteral stones, which is of great significance for the treatment of this disease.

Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are found in primary and advanced tumours. They are primarily involved in tumour progression through complex mechanisms with other types of cells in the tumour microenvironment. However, essential fibroblasts-related genes (FRG) in bladder cancer still need to be explored, and there is a shortage of an ideal predictive model or molecular subtype for the progression and immune therapeutic assessment for bladder cancer, especially muscular-invasive bladder cancer based on the FRG. MATERIALS AND METHODS: CAF-related genes of bladder cancer were identified by analysing single-cell RNA sequence datasets, and bulk transcriptome datasets and gene signatures were used to characterize them. Then, 10 types of machine learning algorithms were utilised to determine the hallmark FRG and construct the FRG index (FRGI) and subtypes. Further molecular subtypes combined with CD8+ T-cells were established to predict the prognosis and immune therapy response. RESULTS: Fifty-four BLCA-related FRG were screened by large-scale scRNA-sequence datasets. The machine learning algorithm established a 3-genes FRGI. High FRGI represented a worse outcome. Then, FRGI combined clinical variables to construct a nomogram, which shows high predictive performance for the prognosis of bladder cancer. Furthermore, the BLCA datasets were separated into two subtypes - fibroblast hot and cold types. In five independent BLCA cohorts, the fibroblast hot type showed worse outcomes than the cold type. Multiple cancer-related hallmark pathways are distinctively enriched in these two types. In addition, high FRGI or fibroblast hot type shows a worse immune therapeutic response. Then, four subtypes called CD8-FRG subtypes were established under the combination of FRG signature and activity of CD8+ T-cells, which turned out to be effective in predicting the prognosis and immune therapeutic response of bladder cancer in multiple independent datasets. Pathway enrichment analysis, multiple gene signatures, and epigenetic alteration characterize the CD8-FRG subtypes and provide a potential combination strategy method against bladder cancer. CONCLUSIONS: In summary, the authors established a novel FRGI and CD8-FRG subtype by large-scale datasets and organised analyses, which could accurately predict clinical outcomes and immune therapeutic response of BLCA after surgery.

A randomized controlled study of ureteral stent extraction string on patient's quality of life and stent-related complications after percutaneous nephrolithotomy in the prone position.

To demonstrate the Tianjin Institute of Urology (TJIU) technique to place and remove the ureteral stent with extraction string after percutaneous nephrolithotomy (PCNL). Additionally, we aim to compare the pain experienced during stent removal, quality of life during stent retention, and stent-related complications between patients with and without extraction string. 65 patients were included in the final analysis in the string group constructed by the TJIU technique and 66 patients in the conventional double-J ureteral stent (non-string) group. All patients underwent the surgery in a prone position under general anesthesia. They completed the Ureteral Stent Symptom Questionnaire (USSQ) on postoperative days (POD) 7, as well as before their ureteral stent was removed. The visual analogue scale (VAS) pain score (0-10) was completed immediately after the removal of the ureteral stent. Moreover, a specialized person was responsible for recording stent-related complications. All patients completed the USSQ on POD 7, and we did not find a difference in scores in each field. However, there was a significant difference in the "sex" domain before removing the ureteral stent (4.34 vs 3.23; p = 0.01). Notably, the use of extraction string after PCNL could decrease the pain associated with stent removal significantly (mean VAS scores 1.45 vs 2.76; p < 0.01). Extraction string did not increase the incidence of stent-related complications. We concluded that placing a ureteral stent with an extraction string after PCNL reduces the pain of ureteral stent removal without increasing complications such as accidental removal of the stent, febrile urinary tract infection (UTI).

Identification of risk factors and clinical model construction of abdominal distension after radical cystectomy.

Background: The occurrence of abdominal distention after radical cystectomy (RC) is common. We sought to determine risk factors of abdominal distention after RC, and to establish a simple and reliable nomogram for clinical risk assessment. Methods: Clinical information on 139 patients who underwent RC from January 2020 to August 2021 was collected. The chi-square test, hypergeometric test, and univariate/multivariate logistic regression were utilized to explore the relationship between variables and abdominal distention after RC. A nomogram was then used to predict the probability of abdominal distension for the patients who underwent RC. Calibration and receiver operating characteristic (ROC) curves were used to evaluate the accuracy of the model. Results: We found that 35 patients (25%) occurred in abdominal distention after RC. Among the patients, 7 of them developed intestinal obstruction. Postoperative water fasting time and abdominal surgery history were independent risk factors for abdominal distension after surgery. Finally, we constructed a risk model to predict the probability of abdominal distension after surgery. This model showed good fitting and calibration and excellent diagnostic performance with an area under the curve (AUC) of 0.804. Conclusions: Postoperative water fasting time and abdominal surgery history were independent risk factors for abdominal distension after surgery. There was no significant difference in the incidence of postoperative abdominal distention between robot-assisted cystectomy and laparoscopic cystectomy.

A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma.

Necroptosis is a regulated form of cell necroptotic process, playing a pivotal role in tumors. In renal cell cancer (RCC), inhibiting necroptosis could promote the proliferation of tumor cells. However, the molecular mechanisms and prognosis prediction of necroptotic-process-related genes in RCC are still unclear. In this study, we first identified the necroptotic process prognosis-related genes (NPRGss) by analyzing the kidney renal clear cell carcinoma (KIRC) data in The Cancer Genome Atlas (TCGA, n=607). We systematically analyzed the expression alteration, clinical relevance, and molecular mechanisms of NPRGss in renal clear cell carcinoma. We constructed an NPRGs risk signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis on the basis of the expression of seven NPRGss. We discovered that the overall survival (OS) of KIRC patients differed significantly in high- or low-NPRGs-risk groups. The univariate/multivariate Cox regression revealed that the NPRGs risk signature was an independent prognosis factor in RCC. The gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the molecular mechanisms of NPRGss. Immune-/metabolism-related pathways showed differential enrichment in high-/low-NPRGs-risk groups. The E-MTAB-1980, TCGA-KIRP, GSE78220, the cohort of Alexandra et al., and IMvigor210 cohort datasets were respectively used as independent validation cohorts of NPRGs risk signature. The patients in high- or low-NPRGs-risk groups showed different drug sensitivity, immune checkpoint expression, and immune therapy response. Finally, we established a nomogram based on the NPRGs risk signature, stage, grade, and age for eventual clinical translation; the nomogram possesses an accurate and stable prediction effect. The signature could predict patients' prognosis and therapy response, which provides the foundation for further clinical therapeutic strategies for RCC patients.

STIL Acts as an Oncogenetic Driver in a Primary Cilia-Dependent Manner in Human Cancer.

SCL/TAL1 Interrupting locus (STIL) is a ciliary-related gene involved in regulating the cell cycle and duplication of centrioles in dividing cells. STIL has been found disordered in multiple cancers and driven carcinogenesis. However, the molecular mechanisms and biological functions of STIL in cancers remain ambiguous. Here, we systematically analyzed the genetic alterations, molecular mechanisms, and clinical relevance of STIL across >10,000 samples representing 33 cancer types in The Cancer Genome Atlas (TCGA) dataset. We found that STIL expression is up-regulated in most cancer types compared with their adjacent normal tissues. The expression dysregulation of STIL was affected by copy number variation, mutation, and DNA methylation. High STIL expression was associated with worse outcomes and promoted the progression of cancers. Gene Ontology (GO) enrichment analysis and Gene Set Variation Analysis (GSVA) further revealed that STIL is involved in cell cycle progression, Mitotic spindle, G2M checkpoint, and E2F targets pathways across cancer types. STIL expression was negatively correlated with multiple genes taking part in ciliogenesis and was positively correlated with several genes which participated with centrosomal duplication or cilia degradation. Moreover, STIL silencing could promote primary cilia formation and inhibit cell cycle protein expression in prostate and kidney cancer cell lines. The phenotype and protein expression alteration due to STIL silencing could be reversed by IFT88 silencing in cancer cells. These results revealed that STIL could regulate the cell cycle through primary cilia in tumor cells. In summary, our results revealed the importance of STIL in cancers. Targeting STIL might be a novel therapeutic approach for cancers.