Prognostic Value of Liquid-Biopsy-Based Biomarkers in Upper Tract Urothelial Carcinoma.

Currently, there are no reliable prognostic factors to determine which upper tract urothelial carcinoma (UTUC) patients will progress after radical nephroureterectomy (RNU). We aim to evaluate whether liquid-biopsy-based biomarkers (circulating tumor cells (CTCs), cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA)) were able to predict clinical outcomes in localized UTUC patients undergoing RNU. Twenty patients were prospectively enrolled between 2021 and 2023. Two blood samples were collected before RNU and three months later. CTCs and cfDNA were isolated and evaluated using the IsoFlux system and Quant-iT PicoGreen dsDNA kit, respectively. Droplet digital PCR was performed to determine ctDNA status. Cox regression analysis was performed on CTCs, cfDNA, and ctDNA at two different follow-up time points to examine their influence on tumor progression and cancer-specific survival (CSS). During a median follow-up of 18 months, seven (35%) patients progressed and three (15%) died. Multivariate analysis demonstrated that cfDNA levels three months after RNU are a significant predictor of tumor progression (HR = 1.085; p = 0.006) and CSS (HR = 1.168; p = 0.029). No associations were found between CTC enumeration and ctDNA status with any of the clinical outcomes evaluated. The evaluation of cfDNA levels in clinical practice could improve the disease management of UTUC patients.

Tumor-Agnostic Circulating Tumor DNA Testing for Monitoring Muscle-Invasive Bladder Cancer.

Circulating tumor DNA (ctDNA) has recently emerged as a real-time prognostic and predictive biomarker for monitoring cancer patients. Here, we aimed to ascertain whether tumor-agnostic ctDNA testing would be a feasible strategy to monitor disease progression and therapeutic response in muscle-invasive bladder cancer (MIBC) patients after radical cystectomy (RC). Forty-two MIBC patients who underwent RC were prospectively included. Blood samples from these patients were collected at different follow-up time points. Two specific mutations (TERT c.1-124C>T and ATM c.1236-2A>T) were analyzed in the patients' plasma samples by droplet digital PCR to determine their ctDNA status. During a median follow-up of 21 months, 24% of patients progressed in a median of six months. ctDNA status was identified as a prognostic biomarker of tumor progression before RC and 4 and 12 months later (HR 6.774, HR 3.673, and HR 30.865, respectively; p < 0.05). Lastly, dynamic changes in ctDNA status between baseline and four months later were significantly associated with patient outcomes (p = 0.045). In conclusion, longitudinal ctDNA analysis using a tumor-agnostic approach is a potential tool for monitoring MIBC patients after RC. The implementation of this testing in a clinical setting could improve disease management and patients' outcomes.

Assessment of aggressive bladder cancer mutations in plasma cell-free DNA.

Background and aims: The spatial and temporal genetic heterogeneity of bladder cancer (BC) makes challenging to find specific drivers of metastatic disease, thus preventing to determine those BC patients at high risk of tumor progression. Our aim was to identify DNA mutations providing aggressive behavior to bladder tumors and analyze them in patients' cell-free DNA (cfDNA) during their follow-up after radical cystectomy (RC) in order to monitor tumor evolution. Methods: Six BC patients who underwent RC and presented disease progression during their follow-up were included. Next-generation sequencing was used to determine somatic mutations in several primary tumor and metastatic specimens from each patient. Shared DNA mutations between primary bladder tumor and metastatic sites were identified in cfDNA samples through droplet digital PCR. Results: Besides BC genetic heterogeneity, specific mutations in at least one of these genes -TERT, ATM, RB1, and FGFR3- were found in primary tumors and their metastases in all patients. These mutations were also identified in the patients' cfDNA at different follow-up time points. Additionally, the dynamic changes of these mutations in cfDNA allowed us to determine tumor evolution in response to treatment. Conclusion: The analysis of BC mutations associated with poor prognosis in plasma cfDNA could be a valuable tool to monitor tumor evolution, thus improving the clinical management of BC patients.

Cell-Free DNA as a Prognostic Biomarker for Monitoring Muscle-Invasive Bladder Cancer.

Cell-free DNA (cfDNA) has recently emerged as a real-time biomarker for diagnosis, monitoring and prediction of therapy response in tumoral disease. Here, we evaluated cfDNA as a prognostic biomarker for monitoring muscle-invasive bladder cancer (MIBC) patients at different follow-up time points. Blood samples from 37 MIBC patients who underwent radical cystectomy (RC) were collected at cystectomy and 1, 4, 12 and 24 months later. Plasma cfDNA amount and fragmentation patterns were determined. Four mutations were analyzed in cfDNA to detect circulating tumor DNA (ctDNA) during patient follow-up. During a median follow-up of 36 months, 46% of patients progressed; median time to progression was 10 months. cfDNA levels and ctDNA status four months after RC were identified as independent prognostic biomarkers of tumor progression (HR 5.290; p = 0.033) and cancer-specific survival (HR 4.199; p = 0.038), respectively. Furthermore, ctDNA clearance four months after RC was significantly associated with patients' clinical outcomes. In conclusion, cfDNA levels and ctDNA status four months after RC have prognostic implications in MIBC patients. In addition, cfDNA monitoring is useful to predict patient outcomes after RC. cfDNA analysis in the clinical setting could greatly improve MIBC patient management.

Multicentric validation of diagnostic tests based on BC-116 and BC-106 urine peptide biomarkers for bladder cancer in two prospective cohorts of patients.

BACKGROUND: Non-invasive urine-based biomarkers can potentially improve current diagnostic and monitoring protocols for bladder cancer (BC). Here we assess the performance of earlier published biomarker panels for BC detection (BC-116) and monitoring of recurrence (BC-106) in combination with cytology, in two prospectively collected patient cohorts. METHODS: Of the 602 patients screened for BC, 551 were found eligible. For the primary setting, 73 patients diagnosed with primary BC (n = 27) and benign urological disorders, including patients with macroscopic haematuria, cystitis and/or nephrolithiasis (n = 46) were included. In total, 478 patients under surveillance were additionally considered (83 BC recurrences; 395 negative for recurrence). Urine samples were analysed with capillary electrophoresis-mass spectrometry. The biomarker score was estimated via support vector machine-based software. RESULTS: Validation of BC-116 biomarker panel resulted in 89% sensitivity and 67% specificity (AUCBC-116 = 0.82). A diagnostic score based on cytology and BC-116 resulted in good (AUCNom116 = 0.85) but not significantly better performance (P = 0.5672). A diagnostic score including BC-106 and cytology was evaluated (AUCNom106 = 0.82), significantly outperforming both cytology (AUCcyt = 0.72; P = 0.0022) and BC-106 (AUCBC-106 = 0.67; P = 0.0012). CONCLUSIONS: BC-116 biomarker panel is a useful test for detecting primary BC. BC-106 classifier integrated with cytology showing >95% negative predictive value, might be useful for decreasing the number of cystoscopies during surveillance.

Prognostic Gene Expression-Based Signature in Clear-Cell Renal Cell Carcinoma.

The inaccuracy of the current prognostic algorithms and the potential changes in the therapeutic management of localized ccRCC demands the development of an improved prognostic model for these patients. To this end, we analyzed whole-transcriptome profiling of 26 tissue samples from progressive and non-progressive ccRCCs using Illumina Hi-seq 4000. Differentially expressed genes (DEG) were intersected with the RNA-sequencing data from the TCGA. The overlapping genes were used for further analysis. A total of 132 genes were found to be prognosis-related genes. LASSO regression enabled the development of the best prognostic six-gene panel. Cox regression analyses were performed to identify independent clinical prognostic parameters to construct a combined nomogram which includes the expression of CERCAM, MIA2, HS6ST2, ONECUT2, SOX12, TMEM132A, pT stage, tumor size and ISUP grade. A risk score generated using this model effectively stratified patients at higher risk of disease progression (HR 10.79; p < 0.001) and cancer-specific death (HR 19.27; p < 0.001). It correlated with the clinicopathological variables, enabling us to discriminate a subset of patients at higher risk of progression within the Stage, Size, Grade and Necrosis score (SSIGN) risk groups, pT and ISUP grade. In summary, a gene expression-based prognostic signature was successfully developed providing a more precise assessment of the individual risk of progression.

Prognostic implication of TERT promoter mutation and circulating tumor cells in muscle-invasive bladder cancer.

PURPOSE: Current clinical prognostic factors are not accurate enough to identify and monitor those muscle-invasive bladder cancer (MIBC) patients at high risk of progression after radical cystectomy (RC). Here, we determined genetic alterations in the tumor and circulating tumor cell (CTC) enumeration to find biomarkers useful for the management of MIBC after RC. METHODS: Thirty-nine MIBC patients undergoing RC were included. Tumoral tissue DNA was analyzed by next generation sequencing. CTCs were isolated from blood collected before RC and one, four and 12 months later. RESULTS: Sixteen (41%) patients progressed in a median time of 8.5 months and 11 (69%) of these patients harbored the TERT c.-124C > T mutation. All progressive patients harboring the TERT c.-124C > T mutation presented a significant increase in CTC number 12 months after RC compared to those without the mutation. Additionally, CTC number at 12 months was identified as an independent prognostic biomarker for tumor progression and cancer specific survival (CSS). Ten (63%) progressive patients showed an increment of CTC number with a median anticipation period of four months compared with imaging techniques. CONCLUSIONS: The TERT c.-124C > T mutation could be considered a biomarker of aggressivity. CTC enumeration is a useful tool for identifying MIBC patients at high risk of progression and CSS after RC and for detecting tumor progression earlier than imaging techniques.

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma.

The probability of tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC) is highly variable, underlining the lack of predictive accuracy of the current clinicopathological factors. To develop an accurate prognostic classifier for these patients, we analyzed global gene expression patterns in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 4000. Expression levels of 22 selected differentially expressed genes (DEG) were assessed by nCounter analysis in an independent series of 71 ccRCCs. A clinicopathological-molecular model for predicting tumor progression was developed and in silico validated in a total of 202 ccRCC patients using the TCGA cohort. A total of 1202 DEGs were found between progressive and non-progressive intermediate/high-risk ccRCC in RNAseq analysis, and seven of the 22 DEGs selected were validated by nCounter. Expression of HS6ST2, pT stage, tumor size, and ISUP grade were found to be independent prognostic factors for tumor progression. A risk score generated using these variables was able to distinguish patients at higher risk of tumor progression (HR 7.27; p < 0.001), consistent with the results obtained from the TCGA cohort (HR 2.74; p < 0.002). In summary, a combined prognostic algorithm was successfully developed and validated. This model may aid physicians to select high-risk patients for adjuvant therapy.

Differential gene expression profile between progressive and de novo muscle invasive bladder cancer and its prognostic implication.

This study aimed to ascertain gene expression profile differences between progressive muscle-invasive bladder cancer (MIBC) and de novo MIBC, and to identify prognostic biomarkers to improve patients' treatment. Retrospective multicenter study in which 212 MIBC patients who underwent radical cystectomy between 2000 and 2019 were included. Gene expression profiles were determined in 26 samples using Illumina microarrays. The expression levels of 94 genes were studied by quantitative PCR in an independent set of 186 MIBC patients. In a median follow-up of 16 months, 46.7% patients developed tumor progression after cystectomy. In our series, progressive MIBC patients show a worse tumor progression (p = 0.024) and cancer-specific survival (CSS) (p = 0.049) than the de novo group. A total of 480 genes were found to be differently expressed between both groups. Differential expression of 24 out of the 94 selected genes was found in an independent cohort. RBPMC2 and DSC3 were found as independent prognostic biomarkers of tumor progression and CALD1 and LCOR were identified as prognostic biomarkers of CSS between both groups. In conclusion, progressive and de novo MIBC patients show different clinical outcome and gene expression profiles. Gene expression patterns may contribute to predict high-risk of progression to distant metastasis or CSS.

Prognostic classifier for predicting biochemical recurrence in localized prostate cancer patients after radical prostatectomy.

OBJECTIVE: The purpose of the study was to develop an improved classifier for predicting biochemical recurrence (BCR) in clinically localized PCa patients after radical prostatectomy. METHODS AND MATERIALS: Retrospective study including 122 PCa patients who attended our department between 2000 and 2007. Gene expression patterns were analyzed in 21 samples from 7 localized, 6 locally advanced, and 8 metastatic PCa patients using Illumina microarrays. Expression levels of 41 genes were validated by quantitative PCR in 101 independent PCa patients who underwent radical prostatectomy. Logistic regression analysis was used to identify individual predictors of BCR. A risk score for predicting BCR including clinicopathological and gene expression variables was developed. Interaction networks were built by GeneMANIA Cytoscape plugin. RESULTS: A total of 37 patients developed BCR (36.6%) in a median follow-up of 120 months. Expression levels of 7,930 transcripts differed between clinically localized and locally advanced-metastatic PCa groups (FDR < 0.1). We found that expression of ASF1B and MCL1 as well as Gleason score, extracapsular extension, seminal vesicle invasion, and positive margins were independent prognostic factors of BCR. A risk score generated using these variables was able to discriminate between 2 groups of patients with a significantly different probability of BCR (HR 6.24; CI 3.23-12.4, P< 0.01), improving the individual discriminative performance of each of these variables on their own. Direct interactions between the 2 genes of the model were not found. CONCLUSION: Combination of gene expression patterns and clinicopathological variables in a robust, easy-to-use, and reliable classifier may contribute to improve PCa risk stratification.

Urine cytology suspicious for urothelial carcinoma: Prospective follow-up of cases using cytology and urine biomarker-based ancillary techniques.

BACKGROUND: Urine cytology results that are suspicious for urothelial carcinoma (UC) are challenging. The objective of this study was to elucidate the clinical significance of such results in patients who have a negative cystoscopy. METHODS: In this prospective study, 83 patients who had urine cytology that was suspicious of UC and a negative cystoscopy underwent a second cystoscopy and urine evaluation by cytology, UroVysion fluorescence in situ hybridization (FISH) assay, FGFR3 (fibroblast growth factor receptor 3) and TERT (telomerase reverse transcriptase) mutations and an 8-gene expression classifier (GEC). Results from all techniques were compared with patients' clinical outcomes. RESULTS: The presence of tumor was identified in 41% of patients; of these, 82% had tumors identified at their second evaluation (76% high-grade [HG] tumors), and 18% had tumors identified at a later follow-up (50% were HG tumors). After The Paris System for Reporting urinary Cytology (TPS) reclassification, 53 cytology results still had an indeterminate diagnosis (13 were suspicious for HGUC, and 40 had atypical urothelial cells (AUCs)]. Complete results from second evaluations using urine cytology, cytology-TPS, FISH, and GEC were available for 6 cases that were suspicious for HGUC and 34 cases that had AUCs. The sensitivity of these techniques to detect HG tumors in cases that were suspicious for HGUC was 100%, except for cytology-TPS, for which the sensitivity was 50%. The sensitivity of cytology and cytology-TPS to detect HG tumors in cases with AUCs was 33%, whereas the sensitivity of fluorescence in situ hybridization and GEC in these cases was 83% and 75%, respectively, to detect HG tumors at the second evaluation. CONCLUSIONS: The current results indicate the relevant clinical significance of indeterminate urine cytology findings and strongly suggest the use of complementary evaluations by urine biomarker-based, ancillary techniques to elucidate their significance.

Urine Gene Expression Profiles in Bladder Pain Syndrome Patients Treated with Triamcinolone.

BACKGROUND: The pathogenesis of bladder pain syndrome (BPS) remains incompletely defined, and there is no standard treatment for BPS as yet. OBJECTIVE: To gain detailed insight into the disease pathobiology of BPS through comparative gene expression analysis of urine from BPS patients versus control individuals and, furthermore, to determine the efficacy of triamcinolone treatment in BPS patients in terms of the gene expression profiles in urine. DESIGN, SETTING, AND PARTICIPANTS: A prospective pilot study including 21 urine samples from patients with Hunner's lesions (n=6) and controls (n=9) between January and August 2017. INTERVENTION: Triamcinolone treatment of BPS patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Urine samples from BPS patients were collected before (pretreatment group) and 2 wk after triamcinolone treatment (post-treatment group). Gene expression of urine sediment was analyzed using RNA sequencing. Pathways and biological processes in which differentially expressed genes are involved were analyzed. RESULTS AND LIMITATIONS: A total of 3745 genes were found to be differentially expressed between the three groups tested. Gene expression differences between controls and BPS samples (630 differentially expressed genes) were more pronounced than the differences between pre- and post-treatment BPS samples (197 differentially expressed genes). Gen Set Enrichment Analysis showed that differentially expressed genes in BPS patients (pretreatment), compared with controls, were enriched for some functional gene networks associated with several metabolic processes and ribosome biogenesis. The limited number of patients included may not accurately represent the BPS population. CONCLUSIONS: Gene expression profiles of urine sediment are able to discriminate between BPS and control patients. Moreover, we show that triamcinolone induces changes in urine gene expression profiles. PATIENT SUMMARY: In this report, we looked at gene expression profiles of urine sediment from patients with Hunner's lesions, before and after triamcinolone treatment, and control individuals. We found that urine gene expression profiles are able to discriminate Hunner's lesions patients from controls. Furthermore, we report, for the first time, that triamcinolone treatment of patients with Hunner's lesions induces changes in bladder gene expression profiles that can be observed in urine samples.

Ability of a urine gene expression classifier to reduce the number of follow-up cystoscopies in bladder cancer patients.

This study aimed to improve our previous urine gene expression classifiers focusing on the detection of non-high-risk non-muscle-invasive bladder cancer (NMIBC), and develop a new classifier able to decrease the frequency of cystoscopies during bladder cancer (BC) patients' surveillance. A total of 597 urines from BC patients, controls and patients in follow-up for BC (PFBC) were included. The study has 3 phases. In the urinary biomarker discovery phase, 84 urines from BC and control patients were retrospectively included and analyzed by Ribonucleic Acid (RNA) sequencing. In the classifier development phase, a total of 132 selected genes from previous phase were evaluated by nCounter in 214 prospectively collected urines from PFBC (98 with tumor). A diagnostic classifier was generated by logistic regression. Finally, in the classifier validation phase, a multicentric and international cohort of 248 urines (134 BC and 114 nonrecurrent PFBC) was used to validate classifier performance. A total of 521 genes were found differentially expressed between non-high-risk NMIBC samples and all other groups (P < 0.05). An 8-gene diagnostic classifier with an area under curve (AUC) of 0.893 was developed. Validation of this classifier in a cohort of PFBC achieved an overall sensitivity (SN) and a negative predictive value (NPV) of 96% and 97%, respectively (AUC = 0.823). Notably, this accuracy was maintained in non-high-risk NMIBC group (SN = 94%; NPV = 98%). In conclusion, this 8-gene expression classifier has high SN and NPV in a real clinical scenario. The use of this classifier can reduce the number of follow-up cystoscopies in PFBC, although assessing its final place in clinical setting is necessary.

Urine cell-based DNA methylation classifier for monitoring bladder cancer.

Background: Current standard methods used to detect and monitor bladder cancer (BC) are invasive or have low sensitivity. This study aimed to develop a urine methylation biomarker classifier for BC monitoring and validate this classifier in patients in follow-up for bladder cancer (PFBC). Methods: Voided urine samples (N = 725) from BC patients, controls, and PFBC were prospectively collected in four centers. Finally, 626 urine samples were available for analysis. DNA was extracted from the urinary cells and bisulfite modificated, and methylation status was analyzed using pyrosequencing. Cytology was available from a subset of patients (N = 399). In the discovery phase, seven selected genes from the literature (CDH13, CFTR, NID2, SALL3, TMEFF2, TWIST1, and VIM2) were studied in 111 BC and 57 control samples. This training set was used to develop a gene classifier by logistic regression and was validated in 458 PFBC samples (173 with recurrence). Results: A three-gene methylation classifier containing CFTR, SALL3, and TWIST1 was developed in the training set (AUC 0.874). The classifier achieved an AUC of 0.741 in the validation series. Cytology results were available for 308 samples from the validation set. Cytology achieved AUC 0.696 whereas the classifier in this subset of patients reached an AUC 0.768. Combining the methylation classifier with cytology results achieved an AUC 0.86 in the validation set, with a sensitivity of 96%, a specificity of 40%, and a positive and negative predictive value of 56 and 92%, respectively. Conclusions: The combination of the three-gene methylation classifier and cytology results has high sensitivity and high negative predictive value in a real clinical scenario (PFBC). The proposed classifier is a useful test for predicting BC recurrence and decrease the number of cystoscopies in the follow-up of BC patients. If only patients with a positive combined classifier result would be cystoscopied, 36% of all cystoscopies can be prevented.

Prognostic value of circulating microRNAs in upper tract urinary carcinoma.

The identification of upper tract urinary carcinoma (UTUC) prognostic biomarkers is urgently needed to predict tumour progression. This study aimed to identify serum microRNAs (miRNAs) that may be useful as minimally invasive predictive biomarkers of tumour progression and survival in UTUC patients. To this end, 33 UTUC patients who underwent radical nephroureterectomy at the Hospital Clinic of Barcelona were prospectively included. Expression of 800 miRNAs was evaluated in serum samples from these patients using nCounter® miRNA Expression Assays. The study was divided into an initial discovery phase (n=12) and a validation phase (n=21). Cox regression analysis was used for survival analysis. The median follow-up (range) of the series was 42 months (9-100 months). In the discovery phase, 38 differentially expressed miRNAs were identified between progressing and non-progressing UTUC patients (p<0.05). Validation of these 38 miRNAs in an independent set of UTUC patients confirmed the differential expression in 18 of them (p<0.05). Cox Regression analysis showed miR-151b and pathological stage as significant prognostic factors for tumour progression (HR=0.33, p<0.001 and HR=2.62, p=0.006, respectively) and cancer specific survival (HR=0.25, p<0.001 and HR=3.98, p=0.003, respectively). Survival curves revealed that miR-151b is able to discriminate between two groups of UTUC patients with a highly significant different probability of tumour progression (p=0.006) and cancer specific survival (p=0.034). Although the data needs to be externally validated, miRNA analysis in serum appears to be a valuable prognostic tool in UTUC patients. Particularly, differential expression of miR-151b in serum may serve as a minimally invasive prognostic tool in UTUC.

Prognostic microRNAs in upper tract urothelial carcinoma: multicenter and international validation study.

OBJECTIVE: To validate previously discovered miRNAs (miR-31-5p and miR-149-5p) as prognostic factors for UTUC in an independent cohort of UTUC patients. PATIENTS AND METHODS: Multicenter, international and retrospective study of formalin-fixed paraffin-embedded tissue samples from 103 UTUC patients (45 progressing and 58 non-progressing) who underwent radical nephroureterectomy. Total RNA was isolated and reverse transcribed. The expression of target miRNAs (miR-31-5p and miR-149-5p) and the endogenous control miR-218-5p was evaluated in all samples by reverse transcription quantitative PCR. Normalized miRNA expression values were evaluated by multivariate forward stepwise Cox regression analysis. Kaplan Meier curves were used to discriminate between two groups of patients with a different probability of tumour progression. RESULTS: The mean age (range) of the series was 67 (33-94) years. Overall, 45 patients (43.7%) developed tumour progression and 32 patients (31.2%) died, 20 of these (62.5%) due to their UTUC, after a median follow-up of 36 months. The mean time for tumour progression and cancer-specific survival were 15 and 20 months, respectively. Five year tumour progression free survival and cancer-specific survival were 58% for ≤ pT2, 36% for pT3 and 0% for pT4 and 67.8% for ≤ pT2, 50.6% for pT3 and 0% for pT4, respectively. In the multivariate analysis, expression of miR-31-5p was found to be an independent prognostic factor of tumour progression (HR 1.1; 95% CI 1.039-1.273; p=0.02). Kaplan Meier curve shows that miR-31-5p expression values are able to discriminate between two groups of UTUC patients with a different probability of tumour progression (p=0.007). CONCLUSIONS: We have been able to validate our previous results in an independent multicentre international cohort of UTUC patients, suggesting that miRNA-31-5p could be a useful prognostic marker of UTUC progression. The application of miRNA expression values to clinical practice could refine the currently used clinicopathological-based approach for predicting UTUC patients' outcome.

Urinary cell microRNA-based prognostic classifier for non-muscle invasive bladder cancer.

Current prognostic tools for non-muscle invasive bladder cancer (NMIBC) do not have enough discriminative capacity to predict the risk of tumour progression. This study aimed to identify urinary cell microRNAs that may be useful as non-invasive predictive biomarkers of tumour progression in NMIBC patients. To this end, 210 urine samples from NMIBC patients were included in the study. RNA was extracted from urinary cells and expression of 8 microRNAs, previously described by our group, was analysed by quantitative PCR. A tumour progression predicting model was developed by Cox regression analysis and validated by bootstrapping. Regression analysis identified miR-140-5p and miR-92a-3p as independent predictors of tumour progression. The risk score derived from the model containing these two microRNAs was able to discriminate between two groups with a highly significant different probability of tumour progression (HR, 5.204; p<0.001) which was maintained when patients were stratified according to tumour risk. The algorithm was also able to identify two groups with different cancer-specific survival (HR, 3.879; p=0.021). Although the data needs to be externally validated, miRNA analysis in urine appears to be a valuable prognostic tool in NMIBC patients.

A five-gene expression signature to predict progression in T1G3 bladder cancer.

OBJECTIVE: The aim of this study was to analyze tumour gene expression profiles of progressive and non-progressive T1G3 bladder cancer (BC) patients to develop a gene expression signature to predict tumour progression. METHODS: Retrospective, multicenter study of 96 T1G3 BC patients without carcinoma in situ (CIS) who underwent a transurethral resection. Formalin-fixed paraffin-embedded tissue samples were collected. Global gene expression patterns were analyzed in 21 selected samples from progressive and non-progressive T1G3 BC patients using Illumina microarrays. Expression levels of 94 genes selected based on microarray data and based on literature were studied by quantitative polymerase chain reaction (qPCR) in an independent series of 75 progressive and non-progressive T1G3 BC patients. Univariate logistic regression was used to identify individual predictors. A variable selection method was used to develop a multiplex biomarker model. Discrimination of the model was measured by area under the receiver-operating characteristic curve. Interaction networks between the genes of the model were built by GeneMANIA Cytoscape plugin. RESULTS: A total of 1294 genes were found differentially expressed between progressive and non-progressive patients. Differential expression of 15 genes was validated by qPCR in an additional set of samples. A five-gene expression signature (ANXA10, DAB2, HYAL2, SPOCD1, and MAP4K1) discriminated progressive from non-progressive T1G3 BC patients with a sensitivity of 79% and a specificity of 86% (AUC = 0.83). Direct interactions between the five genes of the model were not found. CONCLUSIONS: Progressive and non-progressive T1G3 bladder tumours have shown different gene expression patterns. To identify T1G3 BC patients with a high risk of progression, a five-gene expression signature has been developed.

Using gene expression from urine sediment to diagnose prostate cancer: development of a new multiplex mRNA urine test and validation of current biomarkers.

BACKGROUND: Additional accurate non-invasive biomarkers are needed in the clinical setting to improve prostate cancer (PCa) diagnosis. Here we have developed a new and improved multiplex mRNA urine test to detect prostate cancer (PCa). Furthermore, we have validated the PCA3 urinary transcript and some panels of urinary transcripts previously reported as useful diagnostic biomarkers for PCa in our cohort. METHODS: Post-prostatic massage urine samples were prospectively collected from PCa patients and controls. Expression levels of 42 target genes selected from our previous studies and from the literature were studied in 224 post-prostatic massage urine sediments by quantitative PCR. Univariate logistic regression was used to identify individual PCa predictors. A variable selection method was used to develop a multiplex biomarker model. Discrimination was measured by ROC curve AUC for both, our model and the previously published biomarkers. RESULTS: Seven of the 42 genes evaluated (PCA3, ELF3, HIST1H2BG, MYO6, GALNT3, PHF12 and GDF15) were found to be independent predictors for discriminating patients with PCa from controls. We developed a four-gene expression signature (HIST1H2BG, SPP1, ELF3 and PCA3) with a sensitivity of 77% and a specificity of 67% (AUC = 0.763) for discriminating between tumor and control urines. The accuracy of PCA3 and previously reported panels of biomarkers is roughly maintained in our cohort. CONCLUSIONS: Our four-gene expression signature outperforms PCA3 as well as previously reported panels of biomarkers to predict PCa risk. This study suggests that a urinary biomarker panel could improve PCa detection. However, the accuracy of the panels of urinary transcripts developed to date, including our signature, is not high enough to warrant using them routinely in a clinical setting.

Gene expression test for the non-invasive diagnosis of bladder cancer: A prospective, blinded, international and multicenter validation study.

OBJECTIVE: This study aimed to validate, in a prospective, blinded, international and multicenter cohort, our previously reported four non-invasive tests for bladder cancer (BC) diagnosis based on the gene expression patterns of urine. METHODS: Consecutive voided urine samples from BC patients and controls were prospectively collected in five European centres (n=789). Finally, 525 samples were successfully analysed. Gene expression values were quantified using TaqMan Arrays and previously reported diagnostic algorithms were applied to gene expression data. Results from the most accurate gene signature for BC diagnosis were associated with clinical parameters using analysis of variance test. RESULTS: High diagnostic accuracy for the four gene signatures was found in the independent validation set (area under curve [AUC]=0.903-0.918), with the signature composed of two genes (GS_D2) having the best performance (sensitivity: 81.48%; specificity: 91.26%; AUC: 0.918). The diagnostic accuracy of GS_D2 was not affected by the number of tumours (p=0.58) but was statistically associated with tumour size (p=0.008). Also, GS_D2 diagnostic accuracy increases with increasing BC tumour risk. We found no differences in the performance of the GS_D2 test among the populations and centres in detecting tumours (p=0.7) and controls (p=0.2). CONCLUSIONS: Our GS_D2 test is non-invasive, non-observer dependent and non-labour-intensive, and has demonstrated diagnostic accuracy in an independent, international and multicenter study, equal or superior to the current gold standard (cystoscopy combined with cytology). Additionally, it has higher sensitivity than cytology while maintaining its specificity. Consequently, it meets the requirements for consideration as a molecular test applicable to clinical practice in the management of BC.