Molecular Subtypes Defined by Cuproptosis-Associated Genes, Prognostic Model Development, and Tumor Immune Microenvironment Characterization in Adrenocortical Carcinoma.

Introduction: This study aims to explore the role of cuproptosis-related genes in ACC, utilizing data from TCGA and GEO repositories, and to develop a predictive model for patient stratification. Methods: A cohort of 123 ACC patients with survival data was analyzed. RNA-seq data of 17 CRGs were examined, and univariate Cox regression identified prognostic CRGs. A cuproptosis-related network was constructed to show interactions between CRGs. Consensus clustering classified ACC into three subtypes, with transcriptional and survival differences assessed by PCA and survival analysis. Gene set variation analysis (GSVA) and ssGSEA evaluated functional and immune infiltration characteristics across subtypes. Differentially expressed genes (DEGs) were identified, and gene clusters were established. A risk score (CRG_score) was generated using LASSO and multivariate Cox regression, validated across datasets. Tumor microenvironment, stem cell index, mutation status, drug sensitivity, and hormone synthesis were examined in relation to the CRG_score. Protein expression of key genes was validated, and functional studies on ASF1B and NDRG4 were performed. Results: Three ACC subtypes were identified with distinct survival outcomes. Subtype B showed the worst prognosis, while subtype C had the best. We identified 214 DEGs linked to cell proliferation and classified patients into three gene clusters, confirming their prognostic value. The CRG_score predicted patient outcomes, with high-risk patients demonstrating worse survival and possible resistance to immunotherapy. Drug sensitivity analysis suggested higher responsiveness to doxorubicin and etoposide in high-risk patients. Conclusion: This study suggests the potential prognostic value of CRGs in ACC. The CRG_score model provides a robust tool for risk stratification, with implications for treatment strategies.

Disulfidptosis-related subtype and prognostic signature in prostate cancer.

BACKGROUND: Disulfidptosis refers to cell death caused by the accumulation and bonding of disulfide in the cytoskeleton protein of SLC7A11-high level cells under glucose deprivation. However, the role of disulfidptosis-related genes (DRGs) in prostate cancer (PCa) classification and regulation of the tumor microenvironment remains unclear. METHODS: Firstly, we analyzed the expression and mutation landscape of DRGs in PCa. We observed the expression levels of SLC7A11 in PCa cells through in vitro experiments and assessed the inhibitory effect of the glucose transporter inhibitor BAY-876 on SLC7A11-high cells using CCK-8 assay. Subsequently, we performed unsupervised clustering of the PCa population and analyzed the differentially expressed genes (DEGs) between clusters. Using machine learning techniques to select a minimal gene set and developed disulfidoptosis-related risk signatures for PCa. We analyzed the tumor immune microenvironment and the sensitivity to immunotherapy in different risk groups. Finally, we validated the accuracy of the prognostic signatures genes using single-cell sequencing, qPCR, and western blot. RESULTS: Although SLC7A11 can increase the migration ability of tumor cells, BAY-876 effectively suppressed the viability of prostate cancer cells, particularly those with high SLC7A11 expression. Based on the DRGs, PCa patients were categorized into two clusters (A and B). The risk label, consisting of a minimal gene set derived from DEGs, included four genes. The expression levels of these genes in PCa were initially validated through in vitro experiments, and the accuracy of the risk label was confirmed in an external dataset. Cluster-B exhibited higher expression levels of DRG, representing lower risk, better prognosis, higher immune cell infiltration, and greater sensitivity to immune checkpoint blockade, whereas Cluster A showed the opposite results. These findings suggest that DRGs may serve as targets for PCa classification and treatment. Additionally, we constructed a nomogram that incorporates DRGs and clinical pathological features, providing clinicians with a quantitative method to assess the prognosis of PCa patients. CONCLUSION: This study analyzed the potential connection between disulfidptosis and PCa, and established a prognostic model related to disulfidptosis, which holds promise as a valuable tool for the management and treatment of PCa patients.

Liquid-liquid phase separation-related genes associated with prognosis, tumor microenvironment characteristics, and tumor cell features in bladder cancer.

OBJECTIVE: This study aimed to explore the Liquid-liquid phase separation (LLPS)-related genes associated with the prognosis of bladder cancer (BCa) and assess the potential application of LLPS-related prognostic signature for predicting prognosis in BCa patients. METHODS: Clinical information and transcriptome data of BCa patients were extracted from the Cancer Genome Atlas-BLCA (TCGA-BLCA) database and the GSE13507 database. Furthermore, 108 BCa patients who received treatment at our institution were subjected to a retrospective analysis. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an LLPS-related prognostic signature for BCa. The CCK8, wound healing and Transwell assays were performed. RESULTS: Based on 62 differentially expressed LLPS-related genes (DELRGs), three DELRGs were screened by LASSO analysis including kallikrein-related peptidase 5 (KLK5), monoacylglycerol O-acyltransferase 2 (MOGAT2) and S100 calcium-binding protein A7 (S100A7). Based on three DELRGs, a novel LLPS-related prognostic signature was constructed for individualized prognosis assessment. Kaplan-Meier curve analyses showed that LLPS-related prognostic signature was significantly correlated with overall survival (OS) of BCa. ROC analyses demonstrated the LLPS-related prognostic signature performed well in predicting the prognosis of BCa patients in the training group (the area under the curve (AUC) = 0.733), which was externally verified in the validation cohort 1 (AUC = 0.794) and validation cohort 2 (AUC = 0.766). Further experiments demonstrated that inhibiting KLK5 could affect the proliferation, migration, and invasion of BCa cells. CONCLUSIONS: In this study, a novel LLPS-related prognostic signature was successfully developed and validated, demonstrating strong performance in predicting the prognosis of BCa patients.

Machine learning-based autophagy-related prognostic signature for personalized risk stratification and therapeutic approaches in bladder cancer.

OBJECTIVE: Bladder cancer (BCa) is a highly lethal urological malignancy characterized by its notable histological heterogeneity. Autophagy has swiftly emerged as a diagnostic and prognostic biomarker in diverse cancer types. Nonetheless, the currently accessible autophagy-related signature specific to BCa remains limited. METHODS: A refined autophagy-related signature was developed through a 10-fold cross-validation framework, incorporating 101 combinations of machine learning algorithms. The performance of this signature in predicting prognosis and response to immunotherapy was thoroughly evaluated, along with an exploration of potential drug targets and compounds. In vitro and in vivo experiments were conducted to verify the regulatory mechanism of hub gene. RESULTS: The autophagy-related prognostic signature (ARPS) has exhibited superior performance in predicting the prognosis of BCa compared to the majority of clinical features and other developed markers. Higher ARPS is associated with poorer prognosis and reduced sensitivity to immunotherapy. Four potential targets and five therapeutic agents were screened for patients in the high-ARPS group. In vitro and vivo experiments have confirmed that FKBP9 promotes the proliferation, invasion, and metastasis of BCa. CONCLUSIONS: Overall, our study developed a valuable tool to optimize risk stratification and decision-making for BCa patients.

Environmental explanation of prostate cancer progression based on the comprehensive analysis of polychlorinated biphenyls.

OBJECTIVE: Polychlorinated biphenyls (PCBs) have caused great environmental concerns. The study aims to investigate underlying molecular mechanisms between PCBs exposure and prostate cancer (PCa). METHODS: To investigate the association between PCBs exposure and prostate cancer by using CTD, TCGA, and GEO datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore pathways associated with PCBs-related genes (PRGs). Using Lasso regression analysis, a novel PCBs-related prognostic model was developed. Both internal and external validations were conducted to assess the model's validity. Molecular docking was utilized to assess the binding capacity of PCBs to crucial genes. At last, preliminary experimental validations were conducted to confirm the biological roles of Aroclor 1254 in PCa cells. RESULTS: The GO enrichment analysis of PRGs revealed that the biological processes were most enriched in the regulation of transcription from the RNA polymerase II promoter and signal transduction. The KEGG enrichment analysis showed that of the pathways in cancer is the most significantly enriched. Next, a PCBs-related model was constructed. In the training, test, GSE70770, and GSE116918 cohorts, the biochemical recurrences free survival of the patients with high-risk scores was considerably lower. The AUCs at 5 years were 0.691, 0.718, 0.714, and 0.672 in the four cohorts, demonstrating the modest predictive ability. A nomogram that incorporated clinical characteristics was constructed. The results of the anti-cancer drug sensitivity analysis show chemotherapy might be more beneficial for patients at low risk. The molecular docking analysis demonstrated PCBs' ability to bind to crucial genes. PCa cells exposed to Aroclor 1254 at a concentration of 1 µM showed increased proliferation and invasion capabilities. CONCLUSIONS: This study provides new insights into the function of PCBs in PCa and accentuates the need for deeper exploration into the mechanistic links between PCBs exposure and PCa progression.

Magnetic resonance imaging-based radiomics nomogram for the evaluation of therapeutic responses to neoadjuvant chemohormonal therapy in high-risk non-metastatic prostate cancer.

PURPOSE: The aim of this study was to assess the potential application of a radiomics features-based nomogram for predicting therapeutic responses to neoadjuvant chemohormonal therapy (NCHT) in patients with high-risk non-metastatic prostate cancer (PCa). METHODS: Clinicopathologic information was retrospectively collected from 162 patients with high-risk non-metastatic PCa receiving NCHT and radical prostatectomy at our center. The postoperative pathological findings were used as the gold standard for evaluating the efficacy of NCHT. The least absolute shrinkage and selection operator (LASSO) was conducted to develop radiomics signature. Multivariate logistic regression analyses were conducted to identify the predictors of a positive pathological response to NCHT, and a nomogram was constructed based on these predictors. RESULTS: Sixty-three patients (38.89%) experienced positive pathological response to NCHT. Receiver operating characteristic analyses showed that the area under the curve (AUC) of periprostatic fat (PPF) radiomics signature was 0.835 (95% CI, 0.754-0.898), while the AUC of intratumoral radiomics signature was 0.822 (95% CI, 0.739-0.888). Multivariate logistic regression analysis revealed that PSA level, PPF radiomics signature and intratumoral radiomics signature were independent predictors of positive pathological response. A nomogram based on these three predictors was constructed. The AUC was 0.908 (95% CI, 0.839-0.954). The Hosmer-Lemeshow goodness-of-fit test showed that the nomogram was well calibrated. Decision curve analysis revealed the favorable clinical practicability of the nomogram. The nomogram was successfully validated in the validation cohort. Kaplan-Meier analyses showed that nomogram and positive pathological response were significantly related with survival of PCa. CONCLUSION: The radiomics-clinical nomogram based on mpMRI radiomics features exhibited superior predictive ability for positive pathological response to NCHT in high-risk non-metastatic PCa.

A Novel Classification System of Renal Hilar Tumors for Surgical Guidance: Technique, Outcome, and Safety.

BACKGROUND: This study was designed to develop an innovative classification and guidance system for renal hilar tumors and to assess the safety and effectiveness of robot-assisted partial nephrectomy (RAPN) for managing such tumors. METHODS: A total of 179 patients undergoing RAPN for renal hilar tumors were retrospectively reviewed. A novel classification system with surgical techniques was introduced and the perioperative features, tumor characteristics, and the efficacy and safety of RAPN were compared within subgroups. RESULTS: We classified the tumors according to our novel system as follows: 131 Type I, 35 Type II, and 13 Type III. However, Type III had higher median R.E.N.A.L., PADUA, and ROADS scores compared with the others (all p < 0.001), indicating increased operative complexity and higher estimated blood loss [180.00 (115.00-215.00) ml]. Operative outcomes revealed significant disparities between Type III and the others, with longer operative times [165.00 (145.00-200.50) min], warm ischemia times [24.00 (21.50-30.50) min], tumor resection times [13.00 (12.00-15.50) min], and incision closure times [22.00 (20.00-23.50) min] (all p < 0.005). Postoperative outcomes also showed significant differences, with longer durations of drain removal (77.08 ± 18.16 h) and hospitalization for Type III [5.00 (5.00-6.00) d] (all p < 0.05). Additionally, Type I had a larger tumor diameter than the others (p = 0.009) and pT stage differed significantly between the subtypes (p = 0.020). CONCLUSIONS: The novel renal hilar tumor classification system is capable of differentiating the surgical difficulty of RAPN and further offers personalized surgical steps tailored to each specific classification. It provides a meaningful tool for clinical practice.

Revealing the potential of solute carrier family 31 (copper transporters), member 1: Insights into its role in bladder cancer progression and therapeutic implications.

Introduction: Bladder cancer represents a significant public health concern with diverse genetic alterations influencing disease onset, progression, and therapy response. In this study, we explore the multifaceted role of Solute Carrier Family 31 Member 1 (SLC31A1) in bladder cancer, a pivotal gene involved in copper homeostasis. Methods: Our research involved analyzing the SLC31A1 gene expression via RT-qPCR, promoter methylation via targeted bisulfite sequencing, and mutational status via Next Generation Sequencing (NGS) using the clinical samples sourced by the local bladder cancer patients. Later on, The Cancer Genome Atlas (TCGA) datasets were utilized for validation purposes. Moreover, prognostic significance, gene enrichment terms, and therapeutic drugs of SLC31A1 were also explored using KM Plotter, DAVID, and DrugBank databases. Results: We observed that SLC31A1 was significantly up-regulated at both the mRNA and protein levels in bladder cancer tissue samples, suggesting its potential involvement in bladder cancer development and progression. Furthermore, our investigation into the methylation status revealed that SLC31A1 was significantly hypomethylated in bladder cancer tissues, which may contribute to its overexpression. The ROC analysis of the SLC31A1 gene indicated promising diagnostic potential, emphasizing its relevance in distinguishing bladder cancer patients from normal individuals. However, it is crucial to consider other factors such as cancer stage, metastasis, and recurrence for a more accurate evaluation in the clinical context. Interestingly, mutational analysis of SLC31A1 demonstrated only benign mutations, indicating their unknown role in the SLC31A1 disruption. In addition to its diagnostic value, high SLC31A1 expression was associated with poorer overall survival (OS) in bladder cancer patients, shedding light on its prognostic relevance. Gene enrichment analysis indicated that SLC31A1 could influence metabolic and copper-related processes, further underscoring its role in bladder cancer. Lastly, we explored the DrugBank database to identify potential therapeutic agents capable of reducing SLC31A1 expression. Our findings unveiled six important drugs with the potential to target SLC31A1 as a treatment strategy. Conclusion: Our comprehensive investigation highlights SLC31A1 as a promising biomarker for bladder cancer development, progression, and therapy.

Identification macrophage signatures in prostate cancer by single-cell sequencing and machine learning.

BACKGROUND: The tumor microenvironment (TME) encompasses a variety of cells that influence immune responses and tumor growth, with tumor-associated macrophages (TAM) being a crucial component of the TME. TAM can guide prostate cancer in different directions in response to various external stimuli. METHODS: First, we downloaded prostate cancer single-cell sequencing data and second-generation sequencing data from multiple public databases. From these data, we identified characteristic genes associated with TAM clusters. We then employed machine learning techniques to select the most accurate TAM gene set and developed a TAM-related risk label for prostate cancer. We analyzed the tumor-relatedness of the TAM-related risk label and different risk groups within the population. Finally, we validated the accuracy of the prognostic label using single-cell sequencing data, qPCR, and WB assays, among other methods. RESULTS: In this study, the TAM_2 cell cluster has been identified as promoting the progression of prostate cancer, possibly representing M2 macrophages. The 9 TAM feature genes selected through ten machine learning methods and demonstrated their effectiveness in predicting the progression of prostate cancer patients. Additionally, we have linked these TAM feature genes to clinical pathological characteristics, allowing us to construct a nomogram. This nomogram provides clinical practitioners with a quantitative tool for assessing the prognosis of prostate cancer patients. CONCLUSION: This study has analyzed the potential relationship between TAM and PCa and established a TAM-related prognostic model. It holds promise as a valuable tool for the management and treatment of PCa patients.

Ubiquitin-specific protease 5 promotes bladder cancer progression through stabilizing Twist1.

Aberrant activation of the epithelial-mesenchymal transition (EMT) pathway drives the development of solid tumors, which is precisely regulated by core EMT-related transcription factors, including Twist1. However, the expression pattern and regulatory mechanism of Twist1 in the progression of bladder cancer is still unclear. In this study, we explore the role of Twist1 in the progression of bladder cancer. We discovered that the EMT regulon Twist1 protein, but not Twist1 mRNA, is overexpressed in bladder cancer samples using RT-qPCR, western blot and immunohistochemistry (IHC). Mechanistically, co-immunoprecipitation (Co-IP) coupled with liquid chromatography and tandem mass spectrometry identified USP5 as a binding partner of Twist1, and the binding of Twist1 to ubiquitin-specific protease 5 (USP5) stabilizes Twist through its deubiquitinase activity to activate the EMT. Further studies found that USP5 depletion reduces cell proliferation, invasion and the EMT in bladder cancer cells, and ectopic expression of Twist1 rescues the adverse effects of USP5 loss on cell invasion and the EMT. A xenograft tumor model was used to reconfirmed the inhibitor effect of silencing USP5 expression on tumorigenesis in vivo. In addition, USP5 protein levels are significantly elevated and positively associated with Twist1 levels in clinical bladder cancer samples. Collectively, our study revealed that USP5-Twist1 axis is a novel regulatory mechanism driving bladder cancer progression and that approaches targeting USP5 may become a promising cancer treatment strategy.

Fatty acid metabolism-related molecular subtypes and a novel model for predicting prognosis in bladder cancer patients.

This study aims to develop fatty acid metabolism-related molecular subtypes and construct a fatty acid metabolism-related novel model for bladder cancer (BCa) by bioinformatic profiling. Genome RNA-seq expression data of BCa samples from the TCGA database and GEO database were downloaded. We then conducted consensus clustering analysis to identify fatty acid metabolism-related molecular subtypes for BCa. Univariate and multivariate Cox regression analysis were performed to identify a novel prognostic fatty acid metabolism-related prognostic model for BCa. Finally, we identified a total of three fatty acid metabolismrelated molecular subtypes for BCa. These three molecular subtypes have significantly different clinical characteristics, PD-L1 expression levels, and tumor microenvironments. Also, we developed a novel fatty acid metabolism-related prognostic model. Patients with low-risk score have significantly preferable overall survival compared with those with high-risk score in the training, testing, and validating cohorts. The area under the ROC curve (AUC) for overall survival prediction was 0.746, 0.681, and 0.680 in the training, testing and validating cohorts, respectively. This model was mainly suitable for male, older, high-grade, cluster 2-3, any TCGA stage, any N-stage, and any T-stage patients. Besides, we selected FASN as a hub gene for BCa and further qRT-PCR validation was successfully conducted. In conclusion, we developed and successfully validated a novel fatty acid metabolism-related prognostic model for predicting outcome for BCa patients.

A computed tomography-based comprehensive standardized adrenal tumor scoring model for predicting the perioperative outcomes of retroperitoneal laparoscopic adrenal surgery.

Background: Many imaging scoring models have been developed for tumor surgery to provide critical guidance for the selection of surgical methods. However, little research has been aimed at developing scoring models for adrenal tumors and retroperitoneal laparoscopic adrenal surgery (RLAS), which has become the primary technique for treating adrenal tumors. The study set out to establish a computed tomography (CT)-based adrenal tumor scoring model for predicting perioperative outcomes in patients with adrenal tumors who have undergone RLAS. Methods: The retrospective analysis included 306 patients with adrenal tumors diagnosed by preoperative unenhanced or enhanced CT from January 2014 to August 2018 in the First Affiliated Hospital of Fujian Medical University. CT images were used to quantify the tumor location and size; the relationships of the tumors with the surrounding organs and tissues, the large abdominal blood vessels, and the upper poles of the kidneys and renal hila; the adhesion of periadrenal fat (PF); and the tumor CT enhancement value. We conducted multivariate ordinal logistic regression analysis to screen variables and performed principal component analysis to construct a novel scoring model for RLAS. The perioperative outcomes of RLAS were evaluated according to postoperative length of stay, operative time (OT), intraoperative blood loss (IBL), and postoperative complications. Results: The final scoring model included tumor size; the relationships of the tumors with the surrounding organs and tissues, the large abdominal blood vessels, and the upper poles of the kidneys and renal hila; the tumor CT enhancement value; the adhesion of the PF; and the functional status of adrenal tumors. The total score had positive correlations with the OT (rs=0.431), IBL (rs=0.446), and postoperative length (rs=0.180) (all P values <0.001). Compared to any single metric, the total score provided better prediction of OT and IBL. The grading system for RLAS based on the scoring model also performed well in predicting the complexity and difficulty of RLAS. The coincidence rate for these factors was good (all P values <0.001). Conclusions: The developed model is feasible and repeatable in the prediction of the perioperative outcomes, complexity, and difficulty of RLAS.

ND630 controls ACACA and lipid reprogramming in prostate cancer by regulating the expression of circKIF18B_003.

BACKGROUND: ND630 is believed to be a new therapy pharmacologic molecule in targeting the expression of ACACA and regulating the lipid metabolism. However, the function of ND630 in prostate cancer remains unknown. KIF18B, as an oncogene, plays a vital role in prostate cancer progression. circKIF18B_003 was derived from oncogene KIF18B and was markedly overexpressed in prostate cancer tissues. We speculated that oncoprotein KIF18B-derived circRNA circKIF18B_003 might have roles in prostate cancer promotion. The aim of this study was to validate whether ND630 could control ACACA and lipid reprogramming in prostate cancer by regulating the expression of circKIF18B_003. METHODS: RT-qPCR was used to analyze the expression of circKIF18B_003 in prostate cancer cell lines and prostate cancer samples. circKIF18B_003 expression was modulated in prostate cancer cells using circKIF18B_003 interference or overexpression plasmid. We examined the function and effects of circKIF18B_003 in prostate cancer cells using CCK-8, colony formation, wound healing, and Transwell invasion assays and xenograft models. Fluorescence in situ hybridization (FISH) was performed to evaluate the localization of circKIF18B_003. RNA immunoprecipitation (RIP), RNA pull down, and luciferase reporter assay were performed to explore the potential mechanism of circKIF18B_003. RESULTS: The function of ND630 was determined in this study. circKIF18B_003 was overexpressed in prostate cancer tissues, and overexpression of circKIF18B_003 was associated with poor survival outcome of prostate cancer patients. The proliferation, migration, and invasion of prostate cancer cells were enhanced after up-regulation of circKIF18B_003. circKIF18B_003 is mainly located in the cytoplasm of prostate cancer cells, and the RIP and RNA pull down assays confirmed that circKIF18B_003 could act as a sponge for miR-370-3p. Further study demonstrated that up-regulation of circKIF18B_003 increased the expression of ACACA by sponging miR-370-3p. The malignant ability of prostate cancer cells enhanced by overexpression of circKIF18B_003 was reversed by the down-regulation of ACACA. We found that overexpression of circKIF18B_003 was associated with lipid metabolism, and a combination of ND-630 and docetaxel markedly attenuated tumor growth. CONCLUSION: ND630 could control ACACA and lipid reprogramming in prostate cancer by regulating the expression of circKIF18B_003. ND630 and circKIF18B_003 may represent a novel target for prostate cancer.

Head-to-head comparisons of enhanced CT, 68Ga-PSMA-11 PET/CT and 18F-FDG PET/CT in identifying adverse pathology of clear-cell renal cell carcinoma: a prospective study

ABSTRACT Objectives: Accurate preoperative prediction of adverse pathology is crucial for treatment planning of renal cell carcinoma (RCC). Previous studies have emphasized the potential of prostate-specific membrane antigen positron emission tomography / computed tomography (PSMA PET/CT) in differentiating between benign and malignant localized renal tumors. However, there is a scarcity of case reports elucidating the identification of aggressive pathological features using PET/CT. Our study was designed to prospectively compare the diagnostic value of enhanced CT, 68Ga-PSMA-11 and 18F-fluorodeoxyglucose (18F-FDG) PET/CT in clear-cell renal cell carcinoma (ccRCC) with necrosis or sarcomatoid or rhabdoid differentiation. Materials and Methods: A prospective case series of patients with a newly diagnosed renal mass who underwent enhanced CT, 68Ga-PSMA-11 and 18F-FDG PET/CT within 30 days prior to nephrectomy was included. Complete preoperative and postoperative clinicopathological data were recorded. Patients who received neoadjuvant targeted therapy, declined enhanced CT or PET/CT scanning, refused surgical treatment or had non-ccRCC pathological indications were excluded. Radiological parameters were compared within subgroups of pathological characteristics. Bonferroni corrections were used to adjust for multiple testing and statistical significance was set at a p-value less than 0.017. Results: Seventy-two patients were available for the final analysis. Enhanced CT demonstrated poor performance in identifying necrosis, sarcomatoid or rhabdoid differentiation and adverse pathology (all P > 0.05). The maximum standardized uptake value (SUVmax) of 68Ga-PSMA-11 PET/CT was more effective than 18F-FDG PET/CT in identifying tumor necrosis and adverse pathology, with an area under the curve (AUC) of 0.85 (cutoff value=25.26, p<0.001; Delong test z=2.709, p=0.007) for tumor necrosis and AUC of 0.90 (cutoff value=25.26, p<0.001; Delong test z=3.433, p<0.001) for adverse pathology. However, no significant statistical difference was found between 68Ga-PSMA-11 and 18F-FDG PET/CT in predicting sarcomatoid or rhabdoid feature (AUC of 0.91 vs.0.75, Delong test z=1.998, p=0.046). Subgroup analyses based on age, sex, tumor location, maximal diameter, stage and WHO/ISUP grade demonstrated that 68Ga-PSMA-11 PET/CT SUVmax had a significant predictive value for adverse pathology. Enhanced CT value and SUVmax demonstrated strong reliability [intraclass correlation coefficient (ICC) > 0.80], indicating a robust correlation. Conclusions: 68Ga-PSMA-11 PET/CT demonstrates distinct advantages in identifying aggressive pathological features of primary ccRCC when compared to enhanced CT and 18F-FDG PET/CT. Further research and assessment are warranted to fully establish the clinical utility of 68Ga-PSMA-11 PET/CT in ccRCC.

Exploring Novel Genome Instability-associated lncRNAs and their Potential Function in Pan-Renal Cell Carcinoma.

OBJECTIVE: Genomic instability can drive clonal evolution, continuous modification of tumor genomes, and tumor genomic heterogeneity. The molecular mechanism of genomic instability still needs further investigation. This study aims to identify novel genome instabilityassociated lncRNAs (GI-lncRNAs) and investigate the role of genome instability in pan-Renal cell carcinoma (RCC). MATERIALS AND METHODS: A mutator hypothesis was employed, combining the TCGA database of somatic mutation (SM) information, to identify GI-lncRNAs. Subsequently, a training cohort (n = 442) and a testing cohort (n = 439) were formed by randomly dividing all RCC patients. Based on the training cohort dataset, a multivariate Cox regression analysis lncRNAs risk model was created. Further validations were performed in the testing cohort, TCGA cohort, and different RCC subtypes. To confirm the relative expression levels of lncRNAs in HK-2, 786-O, and 769-P cells, qPCR was carried out. Functional pathway enrichment analyses were performed for further investigation. RESULTS: A total of 170 novel GI-lncRNAs were identified. The lncRNA prognostic risk model was constructed based on LINC00460, AC073218.1, AC010789.1, and COLCA1. This risk model successfully differentiated patients into distinct risk groups with significantly different clinical outcomes. The model was further validated in multiple independent patient cohorts. Additionally, functional and pathway enrichment analyses revealed that GI-lncRNAs play a crucial role in GI. Furthermore, the assessments of immune response, drug sensitivity, and cancer stemness revealed a significant relationship between GI-lncRNAs and tumor microenvironment infiltration, mutational burden, microsatellite instability, and drug resistance. CONCLUSIONS: In this study, we discovered four novel GI-lncRNAs and developed a novel signature that effectively predicted clinical outcomes in pan-RCC. The findings provide valuable insights for pan-RCC immunotherapy and shed light on potential underlying mechanisms.

The effect of body mass index on quality of life in modified single stoma cutaneous ureterostomy or ileal conduit after radical cystectomy.

OBJECTIVE: To explore the influence of postoperative body mass index (BMI) change on postoperative quality of life (QOL) in patients undergoing radical cystectomy (RC) plus modified single stoma cutaneous ureterostomy (MSSCU) or ileal conduit (IC). METHODS: Patients were divided into two groups according to different BMI change patterns: patients experiencing an elevated postoperative BMI level, along with a clinically significant increase in their BMI (an increase of more than 10%) were categorized as Group 1, while patients experiencing a decrease postoperative BMI level, along with a clinically significant reduction in their BMI (a decrease of more than 5%) were categorized as Group 2. Spearman correlation analysis was used to examine the correlations between quality-of-life scores and postoperative clinical parameters. RESULTS: Spearman correlation analysis showed that postoperative BMI, late complications and catheter-free state were significantly associated with postoperative global QoL and symptom scale in MSSCU and postoperative global QoL and physical scale in IC patients. Additionally, postoperative BMI, catheter-free state and the use of adjuvant therapy were associated with bad performance in many scales of QoL like body image, future perspective, social scale, future perspective (MSSCU), and abdominal bloating (IC) (Table 2, p<0.05). Patients in Group 2 with significant weight loss had a better Global QoL, a lower rate of stomal stricture and a higher catheter-free state compared with those in Group 1 in both IC and MSSCU patients. MSSCU patients in Group 2 could achieve a comparable Global QoL as to IC patients in Group 1. CONCLUSION: Controlling the substantial increase in body weight after surgery contributes to improving QoL, reducing the occurrence of stomal stricture, and ensuring a postoperative catheter-free state in BCa patients undergoing MSSCU.

A novel CD8+ T cell-related gene signature for predicting the prognosis and immunotherapy efficacy in bladder cancer.

OBJECTIVE: To identify CD8+ T cell-related molecular clusters and establish a novel gene signature for predicting the prognosis and efficacy of immunotherapy in bladder cancer (BCa). METHODS: Transcriptome and clinical data of BCa samples were obtained from the Cancer Genome Atlas (TCGA) and GEO databases. The CD8+ T cell-related genes were screened through the CIBERSORT algorithm and correlation analysis. Consensus clustering analysis was utilized to identified CD8+ T cell-related molecular clusters. A novel CD8+ T cell-related prognostic model was developed using univariate Cox regression analysis and Lasso regression analysis. Internal and external validations were performed and the validity of the model was validated in a real-world cohort. Finally, preliminary experimental verifications were carried out to verify the biological functions of SH2D2A in bladder cancer. RESULTS: A total of 52 CD8+ T cell-related prognostic genes were screened and two molecular clusters with notably diverse immune cell infiltration, prognosis and clinical features were developed. Then, a novel CD8+ T cell-related prognostic model was constructed. The patients with high-risk scores exhibited a significantly worse overall survival in training, test, whole TCGA and validating cohort. The AUC was 0.766, 0.725, 0.739 and 0.658 in the four cohorts sequentially. Subgroup analysis suggested that the novel prognostic model has a robust clinical application for selecting high-risk patients. Finally, we confirmed that patients in the low-risk group might benefit more from immunotherapy or chemotherapy, and validated the prognostic model in a real-world immunotherapy cohort. Preliminary experiment showed that SH2D2A was capable of attenuating proliferation, migration and invasion of BCa cells. CONCLUSIONS: CD8+ T cell-related molecular clusters were successfully identified. Besides, a novel CD8+ T cell-related prognostic model with an excellent predictive performance in predicting survival rates and immunotherapy efficacy of BCa was developed.

Head-to-head comparisons of enhanced CT, 68Ga-PSMA-11 PET/CT and 18F-FDG PET/CT in identifying adverse pathology of clear-cell renal cell carcinoma: a prospective study.

OBJECTIVES: Accurate preoperative prediction of adverse pathology is crucial for treatment planning of renal cell carcinoma (RCC). Previous studies have emphasized the potential of prostate-specific membrane antigen positron emission tomography / computed tomography (PSMA PET/CT) in differentiating between benign and malignant localized renal tumors. However, there is a scarcity of case reports elucidating the identification of aggressive pathological features using PET/CT. Our study was designed to prospectively compare the diagnostic value of enhanced CT, 68Ga-PSMA-11 and 18F-fluorodeoxyglucose (18F-FDG) PET/CT in clear-cell renal cell carcinoma (ccRCC) with necrosis or sarcomatoid or rhabdoid differentiation. MATERIALS AND METHODS: A prospective case series of patients with a newly diagnosed renal mass who underwent enhanced CT, 68Ga-PSMA-11 and 18F-FDG PET/CT within 30 days prior to nephrectomy was included. Complete preoperative and postoperative clinicopathological data were recorded. Patients who received neoadjuvant targeted therapy, declined enhanced CT or PET/CT scanning, refused surgical treatment or had non-ccRCC pathological indications were excluded. Radiological parameters were compared within subgroups of pathological characteristics. Bonferroni corrections were used to adjust for multiple testing and statistical significance was set at a p-value less than 0.017. RESULTS: Seventy-two patients were available for the final analysis. Enhanced CT demonstrated poor performance in identifying necrosis, sarcomatoid or rhabdoid differentiation and adverse pathology (all P > 0.05). The maximum standardized uptake value (SUVmax) of 68Ga-PSMA-11 PET/CT was more effective than 18F-FDG PET/CT in identifying tumor necrosis and adverse pathology, with an area under the curve (AUC) of 0.85 (cutoff value=25.26, p<0.001; Delong test z=2.709, p=0.007) for tumor necrosis and AUC of 0.90 (cutoff value=25.26, p<0.001; Delong test z=3.433, p<0.001) for adverse pathology. However, no significant statistical difference was found between 68Ga-PSMA-11 and 18F-FDG PET/CT in predicting sarcomatoid or rhabdoid feature (AUC of 0.91 vs.0.75, Delong test z=1.998, p=0.046). Subgroup analyses based on age, sex, tumor location, maximal diameter, stage and WHO/ISUP grade demonstrated that 68Ga-PSMA-11 PET/CT SUVmax had a significant predictive value for adverse pathology. Enhanced CT value and SUVmax demonstrated strong reliability [intraclass correlation coefficient (ICC) > 0.80], indicating a robust correlation. CONCLUSIONS: 68Ga-PSMA-11 PET/CT demonstrates distinct advantages in identifying aggressive pathological features of primary ccRCC when compared to enhanced CT and 18F-FDG PET/CT. Further research and assessment are warranted to fully establish the clinical utility of 68Ga-PSMA-11 PET/CT in ccRCC.

A tumor-associated macrophages related model for predicting biochemical recurrence and tumor immune environment in prostate cancer.

OBJECTIVE: To identify tumor-associated macrophages (TAMs) related molecular subtypes and develop a TAMs related prognostic model for prostate cancer (PCa). METHODS: Consensus clustering analysis was used to identify TAMs related molecular clusters. A TAMs related prognostic model was developed using univariate and multivariate Cox analysis. RESULTS: Three TAMs related molecular clusters were identified and were confirmed to be associated with prognosis, clinicopathological characteristics, PD-L1 expression levels and tumor microenvironment. A TAMs related prognostic model was constructed. Patients in low-risk group all showed a more appreciable biochemical recurrence-free survival (BCRFS) than patients in high-risk group in train cohort, test cohort, entire TCGA cohort and validation cohort. SLC26A3 attenuated progression of PCa and prevented macrophage polarizing to TAMs phenotype, which was initially verified. CONCLUSIONS: We successfully identified molecular clusters related to TAMs. Additionally, we developed a prognostic model involving TAMs that exhibits excellent predictive performance for biochemical recurrence-free survival in PCa.

Subtype and prognostic analysis of immunogenic cell death-related gene signature in prostate cancer.

Background: Immunogenic cell death (ICD) plays a vital role in tumor progression and immune response. However, the integrative role of ICD-related genes and subtypes in the tumor microenvironment (TME) in prostate cancer (PCa) remains unknown. Materials and methods: The sample data were obtained from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Memorial Sloan Kettering Cancer Center (MSKCC) prostate cancer-related databases. We first divided the subtypes based on ICD genes from 901 PCa patients and then identified the prognosis- related genes (PRGs) between different ICD subtypes. Subsequently, all the patients were randomly split into the training and test groups. We developed a risk signature in the training set by least absolute shrinkage and selection operator (LASSO)-Cox regression. Following this, we verified this prognostic signature in both the training test and external test sets. The relationships between the different subgroups and clinical pathological characteristics, immune infiltration characteristics, and mutation status of the TME were examined. Finally, the artificial neural network (ANN) and fundamental experiment study were constructed to verify the accuracy of the prognostic signature. Results: We identified two ICD clusters with immunological features and three gene clusters composed of PRGs. Additionally, we demonstrated that the risk signature can be used to evaluate tumor immune cell infiltration, prognostic status, and an immune checkpoint inhibitor. The low-risk group, which has a high overlap with group C of the gene cluster, is characterized by high ICD levels, immunocompetence, and favorable survival probability. Furthermore, the tumor progression genes selected by the ANN also exhibit potential associations with risk signature genes. Conclusion: This study identified individuals with high ICD levels in prostate cancer who may have more abundant immune infiltration and revealed the potential effects of risk signature on the TME, immune checkpoint inhibitor, and prognosis of PCa.