Exploring the oncogenic potential of circSOD2 in clear cell renal cell carcinoma: a novel positive feedback loop.

BACKGROUND: Existing studies have found that circular RNAs (circRNAs) act as sponges for micro RNAs (miRNAs) to control downstream genes. However, the specific functionalities and mechanisms of circRNAs in human clear cell renal cell carcinoma (ccRCC) have yet to be thoroughly investigated. METHODS: Patient cohorts from online databases were used to screen candidate circRNAs, while another cohort from our hospital was obtained for validation. CircSOD2 was identified as a potential oncogenic target, and its relevant characteristics were investigated during ccRCC progression through various assays. A positive feedback loop containing downstream miRNA and its target gene were identified using bioinformatics and validated by luciferase reporter assays, RNA pull-down, and high-throughput sequencing. RESULTS: CircSOD2 expression was elevated in tumor samples and significantly correlated with overall survival (OS) and the tumor stage of ccRCC patients, which appeared in the enhanced proliferation, invasion, and migration of tumor cells. Through competitive binding to circSOD2, miR-532-3p can promote the expression of PAX5 and the progression of ccRCC, and such regulation can be salvaged by miR-532-3p inhibitor. CONCLUSION: A novel positive feedback loop, PAX5/circSOD2/miR-532-3p/PAX5 was identified in the study, indicating that the loop may play an important role in the diagnosis and prognostic prediction in ccRCC patients.

A new thinking: extended application of genomic selection to screen multiomics data for development of novel hypoxia-immune biomarkers and target therapy of clear cell renal cell carcinoma.

Increasing evidences show the clinical significance of the interaction between hypoxia and immune in clear cell renal cell carcinoma (ccRCC) microenvironment. However, reliable prognostic signatures based on a combination of hypoxia and immune have not been well established. Moreover, many studies have only used RNA-seq profiles to screen the prognosis feature of ccRCC. Presently, there is no comprehensive analysis of multiomics data to mine a better one. Thus, we try and get it. First, t-SNE and ssGSEA analysis were used to establish tumor subtypes related to hypoxia-immune, and we investigated the hypoxia-immune-related differences in three types of genetic or epigenetic characteristics (gene expression profiles, somatic mutation, and DNA methylation) by analyzing the multiomics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct a satisfying prognostic model, with average 1-year, 3-year and 5-year areas under the curve (AUCs) equal to 0.806, 0.776 and 0.837. Comparing it with other nine known prognostic biomarkers and clinical prognostic scoring algorithms, the multiomics-based signature performs better. Then, we verified the gene expression differences in two external databases (ICGC and SYSU cohorts). Next, eight hub genes were singled out and seven hub genes were validated as prognostic genes in SYSU cohort. Furthermore, it was indicated high-risk patients have a better response for immunotherapy in immunophenoscore (IPS) analysis and TIDE algorithm. Meanwhile, estimated by GDSC and cMAP database, the high-risk patients showed sensitive responses to six chemotherapy drugs and six candidate small-molecule drugs. In summary, the signature can accurately predict the prognosis of ccRCC and may shed light on the development of novel hypoxia-immune biomarkers and target therapy of ccRCC.

m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer.

BACKGROUND: N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. METHODS: Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan-Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated. RESULTS: Totally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan-Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib. CONCLUSIONS: An m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer.

A panel of eight autophagy-related long non-coding RNAs is a good predictive parameter for clear cell renal cell carcinoma.

Clear-cell renal cell carcinoma (ccRCC) carries a variable prognosis. Prognostic biomarkers can stratify patients according to risk, and can provide crucial information for clinical decision-making. We screened for an autophagy-related long non-coding lncRNA (lncRNA) signature to improve postoperative risk stratification in The Cancer Genome Atlas (TCGA) database. We confirmed this model in ICGC and SYSU cohorts as a significant and independent prognostic signature. Western blotting, autophagic-flux assay and transmission electron microscopy were used to verify that regulation of expression of 8 lncRNAs related to autophagy affected changes in autophagic flow in vitro. Our data suggest that 8-lncRNA signature related to autophagy is a promising prognostic tool in predicting the survival of patients with ccRCC. Combination of this signature with clinical and pathologic parameters could aid accurate risk assessment to guide clinical management, and this 8-lncRNAs signature related to autophagy may serve as a therapeutic target.

circCHST15 is a novel prognostic biomarker that promotes clear cell renal cell carcinoma cell proliferation and metastasis through the miR-125a-5p/EIF4EBP1 axis.

BACKGROUND: Circular RNAs (circRNAs) have been indicated as potentially critical mediators in various types of tumor progression, generally acting as microRNA (miRNA) sponges to regulate downstream gene expression. However, the aberrant expression profile and dysfunction of circRNAs in human clear cell renal cell carcinoma (ccRCC) need to be further investigated. This study mined key prognostic circRNAs and elucidates the potential role and molecular mechanism of circRNAs in regulating the proliferation and metastasis of ccRCC. METHODS: circCHST15 (hsa_circ_0020303) was identified by mining two circRNA microarrays from the Gene Expression Omnibus database and comparing matched tumor versus adjacent normal epithelial tissue pairs or matched primary versus metastatic tumor tissue pairs. These results were validated by quantitative real-time polymerase chain reaction and agarose gel electrophoresis. We demonstrated the biological effect of circCHST15 in ccRCC both in vitro and in vivo. To test the interaction between circCHST15 and miRNAs, we conducted a number of experiments, including RNA pull down assay, dual-luciferase reporter assay and fluorescence in situ hybridization. RESULTS: The expression of circCHST15 was higher in ccRCC tissues compared to healthy adjacent kidney tissue and higher in RCC cell lines compared to normal kidney cell lines. The level of circCHST15 was positively correlated with aggressive clinicopathological characteristics, and circCHST15 served as an independent prognostic indicator for overall survival and progression-free survival in patients with ccRCC after surgical resection. Our in vivo and in vitro data indicate that circCHST15 promotes the proliferation, migration, and invasion of ccRCC cells. Mechanistically, we found that circCHST15 directly interacts with miR-125a-5p and acts as a microRNA sponge to regulate EIF4EBP1 expression. CONCLUSIONS: We found that sponging of miR-125a-5p to promote EIF4EBP1 expression is the underlying mechanism of hsa_circ_0020303-induced ccRCC progression. This prompts further investigation of circCHST15 as a potential prognostic biomarker and therapeutic target for ccRCC.

Contrast-enhanced transrectal ultrasound can reduce collection of unnecessary biopsies when diagnosing prostate cancer and is predictive of biochemical recurrence following a radical prostatectomy in patients with localized prostate cancer.

BACKGROUND: To investigate the value of using contrast-enhanced transrectal ultrasound (CETRUS) to reduce unnecessary collection of biopsies during prostate cancer diagnosis and its utility in predicting biochemical recurrence in patients with localized prostate cancer. METHODS: This was a prospective study of suspected prostate cancer patients who were evaluated with CETRUS followed by a prostate biopsy. Prostate blood flow via CETRUS was graded using a 5-point scale. The relationship between CETRUS score and biopsy outcome was then analyzed for all patients; univariate and multi-variate analyses were used to determine the probable prognostic factors for biochemical recurrence in patients with localized prostate cancer that underwent a radical prostatectomy. RESULTS: A total of 347 patients were enrolled in the study. Prostate cancer was found in 164 patients. A significant positive correlation (r = 0.69, p < 0.001) was found between CETRUS scores and prostate cancer incidence. Using CETRUS scores ≥2 as the threshold for when to biopsy could have safely reduced the number of biopsies taken overall by 12.1% (42/347) and spared 23.0% (42/183) of patients from undergoing an unnecessary biopsy. 77 patients with localized prostate cancer underwent a radical prostatectomy. The median follow-up time was 30 months (range: 8-56 months) and 17 of these 77 patients exhibited biochemical recurrence during the follow-up period. 3-year biochemical recurrence-free survival rates were 86% for patients with low CETRUS scores (≤ 3) and 59% for patients with high scores (> 3; p = 0.015). Multivariate Cox regression analysis indicated that CETRUS score was an independent predictor of biochemical recurrence (HR: 7.02; 95% CI: 2.00-24.69; p = 0.002). CONCLUSIONS: CETRUS scores may be a useful tool for reducing the collection unnecessary biopsy samples during prostate cancer diagnosis and are predictive of biochemical recurrence in patients with localized prostate cancer following a radical prostatectomy.

Predictive value of single-nucleotide polymorphism signature for recurrence in localised renal cell carcinoma: a retrospective analysis and multicentre validation study.

BACKGROUND: Identification of high-risk localised renal cell carcinoma is key for the selection of patients for adjuvant treatment who are at truly higher risk of reccurrence. We developed a classifier based on single-nucleotide polymorphisms (SNPs) to improve the predictive accuracy for renal cell carcinoma recurrence and investigated whether intratumour heterogeneity affected the precision of the classifier. METHODS: In this retrospective analysis and multicentre validation study, we used paraffin-embedded specimens from the training set of 227 patients from Sun Yat-sen University (Guangzhou, Guangdong, China) with localised clear cell renal cell carcinoma to examine 44 potential recurrence-associated SNPs, which were identified by exploratory bioinformatics analyses of a genome-wide association study from The Cancer Genome Atlas (TCGA) Kidney Renal Clear Cell Carcinoma (KIRC) dataset (n=114, 906 600 SNPs). We developed a six-SNP-based classifier by use of LASSO Cox regression, based on the association between SNP status and patients' recurrence-free survival. Intratumour heterogeneity was investigated from two other regions within the same tumours in the training set. The six-SNP-based classifier was validated in the internal testing set (n=226), the independent validation set (Chinese multicentre study; 428 patients treated between Jan 1, 2004 and Dec 31, 2012, at three hospitals in China), and TCGA set (441 retrospectively identified patients who underwent resection between 1998 and 2010 for localised clear cell renal cell carcinoma in the USA). The main outcome was recurrence-free survival; the secondary outcome was overall survival. FINDINGS: Although intratumour heterogeneity was found in 48 (23%) of 206 cases in the internal testing set with complete SNP information, the predictive accuracy of the six-SNP-based classifier was similar in the three different regions of the training set (areas under the curve [AUC] at 5 years: 0·749 [95% CI 0·660-0·826] in region 1, 0·734 [0·651-0·814] in region 2, and 0·736 [0·649-0·824] in region 3). The six-SNP-based classifier precisely predicted recurrence-free survival of patients in three validation sets (hazard ratio [HR] 5·32 [95% CI 2·81-10·07] in the internal testing set, 5·39 [3·38-8·59] in the independent validation set, and 4·62 [2·48-8·61] in the TCGA set; all p<0·0001), independently of patient age or sex and tumour stage, grade, or necrosis. The classifier and the clinicopathological risk factors (tumour stage, grade, and necrosis) were combined to construct a nomogram, which had a predictive accuracy significantly higher than that of each variable alone (AUC at 5 years 0·811 [95% CI 0·756-0·861]). INTERPRETATION: Our six-SNP-based classifier could be a practical and reliable predictor that can complement the existing staging system for prediction of localised renal cell carcinoma recurrence after surgery, which might enable physicians to make more informed treatment decisions about adjuvant therapy. Intratumour heterogeneity does not seem to hamper the accuracy of the six-SNP-based classifier as a reliable predictor of recurrence. The classifier has the potential to guide treatment decisions for patients at differing risks of recurrence. FUNDING: National Key Research and Development Program of China, National Natural Science Foundation of China, Guangdong Provincial Science and Technology Foundation of China, and Guangzhou Science and Technology Foundation of China.

Overexpression of EIF5A2 in upper urinary tract urothelial carcinoma is a new independent prognostic marker of survival.

Aim: To study the expression of EIF5A2 in urinary tract urothelial carcinoma and its clinicopathological features and prognosis. Methods: EIF5A2 expression was detected via immunohistochemistry in 101 patients. Results: Kaplan-Meier analysis showed that the EIF5A2 low expression group had significantly longer overall survival (OS; p < 0.001) and progression-free survival (PFS; p < 0.001) than the EIF5A2 high expression group. The high expression of EIF5A2 significantly predict poor OS and PFS in the subset patients (p < 0.05). EIF5A2 was an independent prognostic factor for OS and PFS (p = 0.003 and p = 0.001). The established nomogram model and its calibration curve predicted the probability of survival accurately. Conclusion: EIF5A2 is a potential molecular marker of poor prognosis in urinary tract urothelial carcinoma.

RIN1 promotes renal cell carcinoma malignancy by activating EGFR signaling through Rab25.

We previously identified the important role of RIN1 expression in the prognosis of clear cell renal cell carcinoma (ccRCC). The role of RIN1 in ccRCC malignancy and underlying molecular mechanisms remain unclear. Here we report that ccRCC cells and tissues expressed more RIN1 than normal controls. Gain-of-function and loss-of-function studies demonstrated that RIN1 enhanced ccRCC cell growth, migration and invasion abilities in vitro and promoted tumor growth and metastasis in vivo. Mechanistic studies revealed that RIN1 has an activating effect on EGFR signaling in ccRCC. In addition, we unveil Rab25, a critical GTPase in ccRCC malignancy, as a functional RIN1 interacting partner. Knockdown of Rab25 eliminated the augmentation of carcinoma cell proliferation, migration and invasion by ectopic RIN1. We also confirmed that RIN1 and Rab25 expression correlates with the overall-survival of ccRCC patients from TCGA. These findings suggest that RIN1 plays an important oncogenic role in ccRCC malignancy by activation of EGFR signaling through interacting with Rab25, and RIN1 could be employed as an effective therapeutic target for ccRCC.

Prognostic and predictive value of a microRNA signature in stage II colon cancer: a microRNA expression analysis.

BACKGROUND: Current staging methods do not accurately predict the risk of disease recurrence and benefit of adjuvant chemotherapy for patients who have had surgery for stage II colon cancer. We postulated that expression patterns of multiple microRNAs (miRNAs) could, if combined into a single model, improve postoperative risk stratification and prediction of chemotherapy benefit for these patients. METHOD: Using miRNA microarrays, we analysed 40 paired stage II colon cancer tumours and adjacent normal mucosa tissues, and identified 35 miRNAs that were differentially expressed between tumours and normal tissue. Using paraffin-embedded specimens from a further 138 patients with stage II colon cancer, we confirmed differential expression of these miRNAs using qRT-PCR. We then built a six-miRNA-based classifier using the LASSO Cox regression model, based on the association between the expression of every miRNA and the duration of individual patients' disease-free survival. We validated the prognostic and predictive accuracy of this classifier in both the internal testing group of 138 patients, and an external independent group of 460 patients. FINDINGS: Using the LASSO model, we built a classifier based on the six miRNAs: miR-21-5p, miR-20a-5p, miR-103a-3p, miR-106b-5p, miR-143-5p, and miR-215. Using this tool, we were able to classify patients between those at high risk of disease progression (high-risk group), and those at low risk of disease progression (low-risk group). Disease-free survival was significantly different between these groups in every set of patients. In the initial training group of patients, 5-year disease-free survival was 89% (95% CI 77·3-94·4) for the low-risk group, and 60% (46·3-71·0) for the high-risk group (hazard ratio [HR] 4·24, 95% CI 2·13-8·47; p<0·0001). In the internal testing set of patients, 5-year disease-free survival was 85% (95% CI 74·3-91·8) for the low-risk group, and 57% (42·8-68·5) for the high-risk group (HR 3·63, 1·86-7·01; p<0·0001), and in the independent validation set of patients, was 85% (79·6-89·0) for the low-risk group and 54% (46·4-61·1) for the high-risk group (HR 3·70, 2·56-5·35; p<0·0001). The six-miRNA-based classifier was an independent prognostic factor for, and had better prognostic value than, clinicopathological risk factors and mismatch repair status. In an ad-hoc analysis, the patients in the high-risk group were found to have a favourable response to adjuvant chemotherapy (HR 1·69, 1·17-2·45; p=0·0054). We developed two nomograms for clinical use that integrated the six-miRNA-based classifier and four clinicopathological risk factors to predict which patients might benefit from adjuvant chemotherapy after surgery for stage II colon cancer. CONCLUSION: Our six-miRNA-based classifier is a reliable prognostic and predictive tool for disease recurrence in patients with stage II colon cancer, and might be able to predict which patients benefit from adjuvant chemotherapy. It might facilitate patient counselling and individualise management of patients with this disease. FUNDING: Natural Science Foundation of China.

A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.

Single-cell and spatial transcriptomics reveal 5-methylcytosine RNA methylation regulators immunologically reprograms tumor microenvironment characterizations, immunotherapy response and precision treatment of clear cell renal cell carcinoma.

Clear cell Renal Cell Carcinoma (ccRCC) is a highly heterogeneous disease, making it challenging to predict prognosis and therapy efficacy. In this study, we aimed to explore the role of 5-methylcytosine (m5C) RNA modification in ccRCC and its potential as a predictor for therapy response and overall survival (OS). We established a novel 5-methylcytosine RNA modification-related gene index (M5CRMRGI) and studied its effect on the tumor microenvironment (TME) using single-cell sequencing data for in-depth analysis, and verified it using spatial sequencing data. Our results showed that M5CRMRGI is an independent predictor of OS in multiple datasets and exhibited outstanding performance in predicting the OS of ccRCC. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in TME were observed between high- and low-M5CRMRGI groups. Single-cell/spatial transcriptomics revealed that M5CRMRGI could reprogram the distribution of tumor-infiltrating immune cells. Moreover, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade therapy of the high-risk group. We also predicted six potential drugs binding to the core target of the M5CRMRGI signature via molecular docking. Real-world treatment cohort data proved once again that high-risk patients were appropriate for immune checkpoint blockade therapy, while low-risk patients were appropriate for Everolimus. Our study shows that the m5C modification landscape plays a role in TME distribution. The proposed M5CRMRGI-guided strategy for predicting survival and immunotherapy efficacy, we reported here, might also be applied to more cancers other than ccRCC.

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma.

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort. Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package "Seurat" was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the "ssGSEA" algorithm. In order to develop possible medications for patients with high-risk ccRCC, the "pRRophetic" package is employed. Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature's biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications. Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient's prognosis for ccRCC and reflect the disease's complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

LZTFL1 inhibits kidney tumor cell growth by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway.

LZTFL1 is a tumor suppressor located in chromosomal region 3p21.3 that is deleted frequently and early in various cancer types including the kidney cancer. However, its role in kidney tumorigenesis remains unknown. Here we hypothesized a tumor suppressive function of LZTFL1 in clear cell renal cell carcinoma (ccRCC) and its mechanism of action based on extensive bioinformatics analysis of patients' tumor data and validated it using both gain- and loss-functional studies in kidney tumor cell lines and patient-derive xenograft (PDX) model systems. Our studies indicated that LZTFL1 inhibits kidney tumor cell proliferation by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway and inducing cell cycle arrest at G1. Clinically, we found that LZTFL1 is frequently deleted in ccRCC. Downregulation of LZTFL1 is associated with a poor ccRCC outcome and may be used as prognostic maker. Furthermore, we show that overexpression of LZTFL1 in PDX via lentiviral delivery suppressed PDX growth, suggesting that re-expression of LZTFL1 may be a therapeutic strategy against ccRCC.

Multimodal recurrence scoring system for prediction of clear cell renal cell carcinoma outcome: a discovery and validation study.

BACKGROUND: Improved markers for predicting recurrence are needed to stratify patients with localised (stage I-III) renal cell carcinoma after surgery for selection of adjuvant therapy. We developed a novel assay integrating three modalities-clinical, genomic, and histopathological-to improve the predictive accuracy for localised renal cell carcinoma recurrence. METHODS: In this retrospective analysis and validation study, we developed a histopathological whole-slide image (WSI)-based score using deep learning allied to digital scanning of conventional haematoxylin and eosin-stained tumour tissue sections, to predict tumour recurrence in a development dataset of 651 patients with distinctly good or poor disease outcome. The six single nucleotide polymorphism-based score, which was detected in paraffin-embedded tumour tissue samples, and the Leibovich score, which was established using clinicopathological risk factors, were combined with the WSI-based score to construct a multimodal recurrence score in the training dataset of 1125 patients. The multimodal recurrence score was validated in 1625 patients from the independent validation dataset and 418 patients from The Cancer Genome Atlas set. The primary outcome measured was the recurrence-free interval (RFI). FINDINGS: The multimodal recurrence score had significantly higher predictive accuracy than the three single-modal scores and clinicopathological risk factors, and it precisely predicted the RFI of patients in the training and two validation datasets (areas under the curve at 5 years: 0·825-0·876 vs 0·608-0·793; p<0·05). The RFI of patients with low stage or grade is usually better than that of patients with high stage or grade; however, the RFI in the multimodal recurrence score-defined high-risk stage I and II group was shorter than in the low-risk stage III group (hazard ratio [HR] 4·57, 95% CI 2·49-8·40; p<0·0001), and the RFI of the high-risk grade 1 and 2 group was shorter than in the low-risk grade 3 and 4 group (HR 4·58, 3·19-6·59; p<0·0001). INTERPRETATION: Our multimodal recurrence score is a practical and reliable predictor that can add value to the current staging system for predicting localised renal cell carcinoma recurrence after surgery, and this combined approach more precisely informs treatment decisions about adjuvant therapy. FUNDING: National Natural Science Foundation of China, and National Key Research and Development Program of China.

Hemangioma of the prostate with retrograde ejaculation - a case report.

INTRODUCTION AND IMPORTANCE: Hemangioma of the prostate is rarely reported. We here describe a hemangioma of the prostate in a 31-year-old man. CASE PRESENTATION: The history, imaging characteristics, treatment and one year follow-up results were well documented. The chief complaint was retrograde ejaculation. A 3.1 cm × 2.9 cm mass in the prostate was detected by ultrasound. Transurethral resection of the prostate (TURP) was performed. CLINICAL DISCUSSION: Pathological examination revealed the mass was hemangioma. Immunohistochemical study found the tissue was SMA, CD34, CD31 positive, but D2-40 negative. Imaging feature combined with pathological result suggests the diagnosis of hemangioma of the prostate. One year follow-up revealed the patient was infertile. CONCLUSION: We suggest TURP should be performed to remove the hemangioma. Combined treatment is necessary to resolve the patient's infertility.

TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types.

Immunotherapy with checkpoint inhibitors, such as PD-1/PD-L1 blockage, is becoming standard of practice for an increasing number of cancer types. However, the response rate is only 10%-40%. Thus, identifying biomarkers that could accurately predict the ICI-therapy response is critically important. We downloaded somatic mutation data for 46,697 patients and tumor-infiltrating immune cells levels data for 11070 patients, then combined TP53 and BRAF mutation status into a biomarker model and found that the predict ability of TP53/BRAF mutation model is more powerful than some past models. Commonly, patients with high-TMB status have better response to ICI therapy than patients with low-TMB status. However, the genotype of TP53MUTBRAFWT in high-TMB status cohort have poorer response to ICI therapy than the genotype of BRAFMUTTP53WT in low-TMB status (Median, 18 months vs 47 month). Thus, TP53/BRAF mutation model can add predictive value to TMB in identifying patients who benefited from ICI treatment, which can enable more informed treatment decisions.

CircME1 promotes aerobic glycolysis and sunitinib resistance of clear cell renal cell carcinoma through cis-regulation of ME1.

Circular RNAs (circRNAs) play critical roles in clear cell renal cell carcinoma (ccRCC). However, their involvement in sunitinib resistance remains largely unknown. Herein, we identified a novel circRNA, named circME1, which contributes to sunitinib resistance development in ccRCC. CircME1 also promoted proliferation, migration, and invasion of ccRCC cells. Further mechanism analysis showed that circME1 interacted with U1 snRNP at the promoter of its parental gene ME1, thereby upregulating the expression of ME1, enhancing aerobic glycolysis of ccRCC, and promoting its malignant phenotype. Furthermore, ME1 specific inhibitor could effectively repress the oncogenic functions of circME1. Taken together, our study demonstrates that the circME1/ME1 pathway is involved in ccRCC progression and sunitinib resistance development, which may be exploited for anticancer therapy.

Circular RNA circSNX6 promotes sunitinib resistance in renal cell carcinoma through the miR-1184/GPCPD1/ lysophosphatidic acid axis.

Sunitinib resistance is a major challenge in systemic therapy for renal cell carcinoma (RCC). The role of circular RNAs (circRNAs) in regulating sunitinib resistance of RCC is largely unknown. We established sunitinib-resistant RCC cell lines in vivo. Through RNA-sequencing, we identified circSNX6, whose expression is upregulated in sunitinib-resistant cells compared with their parental cells. High circSNX6 expression was correlated with sunitinib resistance and worse oncologic outcomes in a cohort of 81 RCC patients. In vitro and in vivo experiments confirmed that circSNX6 could promote sunitinib resistance in RCC. circSNX6 acts as a molecular "sponge" to relieve the suppressive effect of microRNA (miR)-1184 on its target gene, glycerophosphocholine phosphodiesterase 1 (GPCPD1), which increases intracellular lysophosphatidic acid (LPA) levels and, ultimately, promotes sunitinib resistance in RCC cells. Our findings demonstrated that the circSNX6/miR-1184/GPCPD1 axis had a critical role in regulation of intracellular LPA levels and sunitinib resistance in RCC; they also provide a novel prognostic indicator and promising therapeutic targets.

Positive feedback regulation of lncRNA PVT1 and HIF2α contributes to clear cell renal cell carcinoma tumorigenesis and metastasis.

Long noncoding RNAs (lncRNAs) have been reported to exert important roles in tumors, including clear cell renal cell carcinoma (ccRCC). PVT1 is an important oncogenic lncRNA which has critical effects on onset and development of various cancers, however, the underlying mechanism of PVT1 functioning in ccRCC remains largely unknown. VHL deficiency-induced HIF2α accumulation is one of the major factors for ccRCC. Here, we identified the potential molecular mechanism of PVT1 in promoting ccRCC development by stabilizing HIF2α. PVT1 was significantly upregulated in ccRCC tissues and high PVT1 expression was associated with poor prognosis of ccRCC patients. Both gain-of-function and loss-of function experiments revealed that PVT1 enhanced ccRCC cells proliferation, migration, and invasion and induced tumor angiogenesis in vitro and in vivo. Mechanistically, PVT1 interacted with HIF2α protein and enhanced its stability by protecting it from ubiquitination-dependent degradation, thereby exerting its biological significance. Meanwhile, HIF2α bound to the enhancer of PVT1 to transactivate its expression. Furthermore, HIF2α specific inhibitor could repress PVT1 expression and its oncogenic functions. Therefore, our study demonstrates that the PVT1/ HIF2α positive feedback loop involves in tumorigenesis and progression of ccRCC, which may be exploited for anticancer therapy.