Hypermethylated TAGMe as a universal-cancer-only methylation marker and its application in diagnosis and recurrence monitoring of urothelial carcinoma.

BACKGROUND: Urothelial carcinoma (UC) is the second most common urological malignancy. Despite numerous molecular markers have been evaluated during the past decades, no urothelial markers for diagnosis and recurrence monitoring have shown consistent clinical utility. METHODS: The methylation level of tissue samples from public database and clinical collected were analyzed. Patients with UC and benign diseases of the urinary system (BUD) were enrolled to establish TAGMe (TAG of Methylation) assessment in a training cohort (n = 567) using restriction enzyme-based bisulfite-free qPCR. The performance of TAGMe assessment was further verified in the validation cohort (n = 198). Urine samples from 57 UC patients undergoing postoperative surveillance were collected monthly for six months after surgery to assess the TAGMe methylation. RESULTS: We identified TAGMe as a potentially novel Universal-Cancer-Only Methylation (UCOM) marker was hypermethylated in multi-type cancers and investigated its application in UC. Restriction enzyme-based bisulfite-free qPCR was used for detection, and the results of which were consistent with gold standard pyrosequencing. Importantly, hypermethylated TAGMe showed excellent sensitivity of 88.9% (95% CI: 81.4-94.1%) and specificity of 90.0% (95% CI: 81.9-95.3%) in efficiently distinguishing UC from BUD patients in urine and also performed well in different clinical scenarios of UC. Moreover, the abnormality of TAGMe as an indicator of recurrence might precede clinical recurrence by three months to one year, which provided an invaluable time window for timely and effective intervention to prevent UC upstaging. CONCLUSION: TAGMe assessment based on a novel single target in urine is effective and easy to perform in UC diagnosis and recurrence monitoring, which may reduce the burden of cystoscopy. Trial registration ChiCTR2100052507. Registered on 30 October 2021.

Isolation and Identification of a Urinary Biomarker for Lung Cancer: 27-Nor-5ß-Cholestane-3α,7α,12α,24R,25S Pentol Glucuronide and Its Deuterated Analog.

An untargeted metabolomic study identified four potential lung cancer diagnostic biomarkers in human urine. One of the potential biomarkers was an unidentified feature possessing a m/z value of 561+. "561+" was isolated from human urine and tentatively identified as 27-nor-5ß-cholestane-3α,7α,12α,24,25 pentol glucuronide with unknown C24,25 stereochemistry using 1H NMR and mass spectrometry. In a prior report, the C24,25 stereochemistry of the aglycone, 27-nor-5ß-cholestane-3α,7α,12α,24,25 pentol, was found to be 24S,25R through GC analysis of the acetonide-TMS derivative. An authentic sample was prepared and found not to have the same stereochemistry as "561+". To identify the C24,25 stereochemistry, four C24,C25 diastereoisomeric alcohols of 27-nor-5ß-cholestane-3α,7α,12α,24,25 pentol were prepared from chiral amino acids. Using an LCMS method, the C24,C25 stereochemistry of the "561+" aglycone was determined to be 24R,25S. With the correct aglycone in hand, it was coupled with glucuronic acid to complete the first reported synthesis of 27-nor-5ß-cholestane-3α,7α,12α,24R,25S pentol glucuronide. Deuterium labeled 27-nor-5ß-cholestane-3α,7α,12α,24R,25S pentol was also synthesized for use as an internal standard for MS quantitation.

Prostate cancer reshapes the secreted and extracellular vesicle urinary proteomes.

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

Re: Use of TP4303 to identify prostate cancer cells in voided urine samples.

Prostate cancer is the second most common cancer in men across the world. Prior to PSA testing, men usually presented with locally advanced disease detected on digital rectal exam or with metastatic disease. PSA ushered in the era of serum biomarkers for prostate cancer. It has taken over three decades to refine the role of PSA in prostate cancer detection. The lack of specificity has spurred research into finding better, readily obtainable biomarkers with high sensitivity and specificity. The trick is to find the prostate cancers that are a threat, not the ones that aren't. Over the last decade and more, many biomarkers have been proposed and tested (HK-2, Pro-PSA, PCA3, TMPRSS2:ERG fusion transcripts, miRNA, just to name a few) but we still await that magical combination of a readily available, reproducible, and hopefully inexpensive biomarker with high sensitivity and specificity. The authors describe the use of a peptide labeled fluorophore for the VPAC1 receptors that are expressed on malignant prostate cancer cells shed in the urine. After initial feasibility work, the authors collected urine from 318 men with lower urinary tract symptoms and a PSA > 4. The patients underwent prostate biopsy yielding Grade Group 2 or higher prostate cancer in 158 patients. One hundred fifty-four or those patients with cancer had a positive result for the biomarker. The sensitivity of the test was 100%, the specificity was 97.56%, positive predictive value was 97.47%, and negative predictive value was 100%.1 These are impressive numbers for a urine biomarker (or any biomarker). This work is certainly promising, BUT, we have seen promising early data on many biomarkers. In this study, the mean PSA in the cancer group was 34.53 ng/mL versus 9.41 in the control (negative) group. Since patients with infection were excluded, the significantly different PSA levels seemed to be selecting the cancers as well. Time and follow up will determine if the "negative biopsy" controls were truly negative. Can the technique and these results be reproduced? The true test will be how this biomarker consistently performs across a broader population of men with a lower, more homogenous PSA elevation. I will eagerly await results of continued study of this promising biomarker for prostate cancer.

Identification of a urinary CD276 fragment for detecting resectable pancreatic cancer using a C-terminal proteomics strategy.

This study aimed to confirm urinary protein fragments in relation to the presence of pancreatic ductal adenocarcinoma (PDAC) via a C-terminal proteomics strategy using exploratory and validation cohorts. Urinary fragments were examined by iTRAQ-labelling of tryptic peptides and concentrations of C-terminal fragments were evaluated. Only the urinary CD276 fragment showed a fold change (FC) of > 1.5 with a significant difference of P < 0.01 between healthy (H) and PDAC participants in both the exploratory (H, n = 42; PDAC, n = 39) and validation cohorts (H, n = 36; resectable PDAC, n = 28). The sensitivity and specificity of the CD276 fragment for diagnosing resectable PDAC were 75% and 89%, respectively, in the validation cohort. Postoperative urinary levels of the CD276 fragment were low as compared to those before surgery (n = 18, P < 0.01). Comprehensive C-terminus proteomics identified an increase in the urinary CD276 fragment level as a feature of patients with PDAC. The urinary CD276 fragment is a potential biomarker for detecting resectable PDAC.

Urine Biopsy as Dynamic Biomarker to Enhance Clinical Staging of Bladder Cancer in Radical Cystectomy Candidates.

PURPOSE: There is significant interest in identifying complete responders to neoadjuvant chemotherapy (NAC) before radical cystectomy (RC) to potentially avoid removal of a pathologically benign bladder. However, clinical restaging after NAC is highly inaccurate. The objective of this study was to develop a next-generation sequencing-based molecular assay using urine to enhance clinical staging of patients with bladder cancer. METHODS: Urine samples from 20 and 44 patients with bladder cancer undergoing RC were prospectively collected for retrospective analysis for molecular correlate analysis from two clinical trials, respectively. The first cohort was used to benchmark the assay, and the second was used to determine the performance characteristics of the test as it correlates to responder status as measured by pathologic examination. RESULTS: First, to benchmark the assay, known mutations identified in the tissue (MT) of patients from the Accelerated Methotrexate, Vinblastine, Doxorubicin, Cisplatin trial (ClinicalTrials.gov identifier: NCT01611662, n = 16) and a cohort from University of California-San Francisco (n = 4) were cross referenced against mutation profiles from urine (MU). We then determined the correlation between MU persistence and residual disease in pre-RC urine samples from a second prospective clinical trial (The pT0 trial; ClinicalTrials.gov identifier: NCT02968732). Residual MU status correlated strongly with residual disease status (pT0 trial; n = 44; P = .0092) when MU from urine supernatant and urine pellet were assessed separately and analyzed in tandem. The sensitivity, specificity, PPV, and NPV were 91%, 50%, 86%, and 63% respectively, with an overall accuracy of 82% for this second cohort. CONCLUSION: MU are representative of MT and thus can be used to enhance clinical staging of urothelial carcinoma. Urine biopsy may be used as a reliable tool that can be further developed to identify complete response to NAC in anticipation of safe RC avoidance.

Urinary PSA-ZINC biomarker outperforms standard of care in early detection of prostate cancer.

BACKGROUND: Urine is a promising biological fluid for prostate cancer (PCa) diagnostics due to its non-invasive collection and wide range of biomarkers. The aim of this study was to assess the role of urinary PSA (uPSA) and urinary Zinc (uZinc) as biomarkers for the diagnosis of PCa in combination with routine parameters of standard of care (SOC - blood PSA, abnormal DRE, age) and MRI in patients candidates for prostate biopsy. METHODS: Urine samples after prostatic massages were collected from men with suspected PCa scheduled for prostate biopsy. Quantification of uPSA was performed by ECLIA platform and confirmed by ELISA assay, while uZinc measurement was evaluated by ICP-MS and confirmed by colorimetric in vitro assay. Six multivariate logistic regression analysis were performed to assess diagnostic performance of uPSA and uZinc (urine), SOC and MRI alone, and combination of MRI+SOC, MRI+urine and SOC+MRI+urine. The discriminative power of the logistic models was assessed by calculating the area under the receiver operating characteristic (ROC) curves (AUC). RESULTS: Two hundred thirty-eight patients were included in the analysis; 145 of them were diagnosed with PCa. Urine test showed a better discrimination of HS from CP, in respect of uPSA and uZinc alone, both for PCa of any grade and Gleason Score ≥7 (4+3) (AUC 0.804 and 0.823 respectively). ROC curve combining SOC+MRI+urine showed an AUC=0.882, that is statistically different from SOC or MRI alone, or MRI+SOC (P=0.0001, P=0.0001, and P=0.008 respectively). PCa risk algorithm designed considering SOC+MRI+urine results in potential reduction of 57% of unnecessary biopsies compared to the current standard parameters. CONCLUSIONS: The loss of uPSA and Zinc production and secretion during neoplastic transformation of the prostate could potentially represent a hallmark of PCa. Its combination with age, PSA and DRE, as well as with mpMRI could represent an interesting approach to improve the diagnostic accuracy of PCa.

Multispectral 3D DNA Machine Combined with Multimodal Machine Learning for Noninvasive Precise Diagnosis of Bladder Cancer.

Extracellular vesicle (EV) molecular phenotyping offers enormous opportunities for cancer diagnostics. However, the majority of the associated studies adopted biomarker-based unimodal analysis to achieve cancer diagnosis, which has high false positives and low precision. Herein, we report a multimodal platform for the high-precision diagnosis of bladder cancer (BCa) through a multispectral 3D DNA machine in combination with a multimodal machine learning (ML) algorithm. The DNA machine was constructed using magnetic microparticles (MNPs) functionalized with aptamers that specifically identify the target of interest, i.e., five protein markers on bladder-cancer-derived urinary EVs (uEVs). The aptamers were hybridized with DNA-stabilized silver nanoclusters (DNA/AgNCs) and a G-quadruplex/hemin complex to form a sensing module. Such a DNA machine ensured multispectral detection of protein markers by fluorescence (FL), inductively coupled plasma mass spectrometry (ICP-MS), and UV-vis absorption (Abs). The obtained data sets then underwent uni- or multimodal ML for BCa diagnosis to compare the analytical performance. In this study, urine samples were obtained from our prospective cohort (n = 45). Our analytical results showed that the 3D DNA machine provided a detection limit of 9.2 × 103 particles mL-1 with a linear range of 4 × 104 to 5 × 107 particles mL-1 for uEVs. Moreover, the multimodal data fusion model exhibited an accuracy of 95.0%, a precision of 93.1%, and a recall rate of 93.2% on average, while those of the three types of unimodal models were no more than 91%. The elevated diagnosis precision by using the present fusion platform offers a perspective approach to diminishing the rate of misdiagnosis and overtreatment of BCa.

Investigating angiogenin/ribonuclease 5 as a diagnostic biomarker for bladder cancer: In-depth analysis from a systematic review and meta-analysis.

Bladder cancer (BC) represents a prevalent malignancy in North America and Europe, posing significant health burdens. The identification of a reliable biomarker for early BC detection is imperative to enhance prognostic outcomes. Our aim for this study is to determine the diagnostic accuracy and potential clinical utility of Angiogenin/Ribonuclease 5 (ANG/RNase 5) as a biomarker for detection of BC. A systematic literature search across multiple databases up to March 20, 2024, was conducted. CMA 3.7 and Meta-disk 1.4 were used to analyze specificity, sensitivity, AUC, DOR, LR+, LR-, Q*index, and SROC for ANG as a urinary biomarker in BC patients. Publication bias was assessed using Egger's regression asymmetry and Begg's rank correlation tests. Additional diagnosing analyses were performed using Python programming language version 3.12.1. In this meta-analysis of seven case-control studies comprising 1,051 participants (576 cases and 481 controls), pooled sensitivity was 0.701 (95 % CI: 0.662-0.738), specificity was 0.787 (95 % CI: 0.752-0.819), LR + was 3.582 (95 % CI: 2.260-5.676), LR- was 0.398 (95 % CI: 0.327-0.485), and DOR was 10.637 (95 % CI: 6.106-18.529). The AUC and Q* index values were 0.823 and 0.756, respectively. Both Begg and Mazumdar Rank Correlation Test (p = 0.229) and Egger's Test of the Intercept (p = 0.135) revealed no significant evidence of publication bias. Our meta-analysis confirms ANG/RNase 5 as a reliable biomarker for early bladder cancer detection, showing strong diagnostic accuracy and no publication bias.

Urinary dipeptidase 1 and trefoil factor 1 are promising biomarkers for early diagnosis of colorectal cancer.

BACKGROUND: Currently utilized serum tumor markers and fecal immunochemical tests do not have sufficient diagnostic power for colorectal cancer (CRC) due to their low sensitivities. To establish non-invasive urinary protein biomarkers for early CRC diagnosis, we performed stepwise analyses employing urine samples from CRCs and healthy controls (HCs). METHODS: Among 474 urine samples, 363 age- and sex-matched participants (188 HCs, 175 stage 0-III CRCs) were randomly divided into discovery (16 HCs, 16 CRCs), training (110 HCs, 110 CRCs), and validation (62 HCs, 49 CRCs) cohorts. RESULTS: Of the 23 urinary protein candidates comprehensively identified from mass spectrometry in the discovery cohort, urinary levels of dipeptidase 1 (uDPEP1) and Trefoil factor1 (uTFF1) were the two most significant diagnostic biomarkers for CRC in both training and validation cohorts using enzyme-linked immunosorbent assays. A urinary biomarker panel comprising uDPEP1 and uTFF1 significantly distinguished CRCs from HCs, showing area under the curves of 0.825-0.956 for stage 0-III CRC and 0.792-0.852 for stage 0/I CRC. uDPEP1 and uTFF1 also significantly distinguished colorectal adenoma (CRA) patients from HCs, with uDPEP1 and uTFF1 increasing significantly in the order of HCs, CRA patients, and CRC patients. Moreover, expression levels of DPEP1 and TFF1 were also significantly higher in the serum and tumor tissues of CRC, compared to HCs and normal tissues, respectively. CONCLUSIONS: This study established a promising and non-invasive urinary protein biomarker panel, which enables the early detection of CRC with high sensitivity.

Urinary extracellular vesicle-derived miR-126-3p predicts lymph node invasion in patients with high-risk prostate cancer.

To investigate extracellular vesicles (EVs), biomarkers for predicting lymph node invasion (LNI) in patients with high-risk prostate cancer (HRPCa), plasma, and/or urine samples were prospectively collected from 45 patients with prostate cancer (PCa) and five with benign prostatic hyperplasia (BPH). Small RNA sequencing was performed to identify miRNAs in the EVs. All patients with PCa underwent radical prostatectomy and extended pelvic lymph node dissection. Differentially expressed miRNAs were identified in patients with and without pathologically-verified LNI. The candidate miRNAs were validated in low-risk prostate cancer (LRPCa) and BPH. Four miRNA species (e.g., miR-126-3p) and three miRNA species (e.g., miR-27a-3p) were more abundant in urinary and plasma EVs, respectively, of patients with PCa. None of these miRNA species were shared between urinary and plasma EVs. miR-126-3p was significantly more abundant in patients with HR PCa with LNI than in those without (P = 0.018). miR-126-3p was significantly more abundant in the urinary EVs of patients with HRPCa than in those with LRPCa (P = 0.017) and BPH (P = 0.011). In conclusion, urinary EVs-derived miR-126-3p may serve as a good biomarker for predicting LNI in patients with HRPCa.

Candidate prognostic biomarkers and prediction models for high-grade serous ovarian cancer from urinary proteomics.

High-grade serous ovarian cancer (HGSOC) is one of the most common histologic types of ovarian cancer. The purpose of this study was to identify potential prognostic biomarkers in urine specimens from patients with HGSOC. First, 56 urine samples with information on relapse-free survival (RFS) months were collected and classified into good prognosis (RFS ≥ 12 months) and poor prognosis (RFS < 12 months) groups. Next, data-independent acquisition (DIA)-based mass spectrometry (MS) analysis was combined with MSFragger-DIA workflow to identify potential prognostic biomarkers in a discovery set (n = 31). With the aid of parallel reaction monitoring (PRM) analysis, four candidate biomarkers (ANXA1, G6PI, SPB3, and SPRR3) were finally validated in both the discovery set and an independent validation set (n = 25). Subsequent RFS and Cox regression analyses confirmed the utility of these candidate biomarkers as independent prognostic factors affecting RFS in patients with HGSOC. Regression models were constructed to predict the 12-month RFS rate, with area under the receiver operating characteristic curve (AUC) values ranging from 0.847 to 0.905. Overall, candidate prognostic biomarkers were identified in urine specimens from patients with HGSOC and prediction models for the 12-month RFS rate constructed. SIGNIFICANCE: OC is one of the leading causes of death due to gynecological malignancies. HGSOC constitutes one of the most common histologic types of OC with aggressive characteristics, accounting for the majority of advanced cases. In cases where patients with advanced HGSOC potentially face high risk of unfavorable prognosis or disease advancement within a 12-month period, intensive medical monitoring is necessary. In the era of precision cancer medicine, accurate prediction of prognosis or 12-month RFS rate is critical for distinguishing patient groups requiring heightened surveillance. Patients could significantly benefit from timely modifications to treatment regimens based on the outcomes of clinical monitoring. Urine is an ideal resource for disease surveillance purposes due to its easy accessibility. Furthermore, molecules excreted in urine are less complex and more stable than those in other liquid samples. In the current study, we identified candidate prognostic biomarkers in urine specimens from patients with HGSOC and constructed prediction models for the 12-month RFS rate.

Identification of novel snoRNA-based biomarkers for clear cell renal cell carcinoma from urine-derived extracellular vesicles.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising. METHODS: RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models. RESULTS: An initial cluster analysis of RNA-seq expression data showed separation by the subjects' gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091). CONCLUSIONS: Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.

The value of urinary exosomal microRNA-21 in the early diagnosis and prognosis of bladder cancer.

Bladder cancer (BC) poses high morbidity and mortality, with urinary exosomal microRNA (miR)-21 showing potential value in its diagnosis and prognosis, and we probed its specific role. We prospectively selected 116 BC patients and 116 healthy volunteers as the BC and control groups, respectively. BC urinary exosomal miR-146a-5p, miR-93-5p, miR-663b, miR-21, and miR-4454 relative expression levels were assessed. The correlations between clinical indexes and urinary exosomal miR-21, prognostic value of miR-21, and diagnostic value of the five candidate miRNAs, urine cytology, and miRNA joint diagnostic panel for BC and urinary exosomal miR-21, miR-4454, and urine cytology for Ta-T1 and T2-T4 stage BC were analyzed. Urinary exosomal miR-146a-5p, miR-93-5p, miR-663b, miR-21, and miR-4454 were highly expressed in BC patients. miR-146a-5p, miR-93-5p, miR-663b, miR-21, miR-4454, miRNA combined diagnostic panel, and urine cytology had certain diagnostic value for BC, with miR-21, miR-4454, and miRNA co-diagnostic panel showing the highest diagnostic value. Collectively, urinary exosomal miR-21 was closely related to Tumor-Node-Metastasis staging and grading in BC patients. Urinary exosomal miR-21 had high diagnostic value for BC and Ta-T1 and T2-T4 stage BC, and had high predictive value for BC poor prognosis, providing an effective indicator for the occurrence, development, and prognostic assessment of BC.

Increased α2,3-sialyl N-glycosylated prostate-specific membrane antigen (PSMA) in post-DRE urine is associated with high grade group prostate cancer.

INTRODUCTION: Aberrant glycosylation of proteins is an important hallmark in multiple cancers. Prostate-specific membrane antigen (PSMA), a highly glycosylated protein with 10 N-linked glycosylation sites, is an Food and Drug Administration approved theranostic for prostate cancer. However, glycosylation changes in PSMA that are associated with prostate cancer disease progression have not been fully characterized. METHODS: We investigated whether urinary PSMA sialylation correlate with high-grade prostate cancer. Urine samples were collected from men after digital rectal examination (DRE) before prostate biopsy. Lectin-antibody enzyme-linked immunoassay was used to quantify α2,3-sialyl PSMA in post-DRE urine samples from subjects with benign prostate tumors, Grade Group 1 prostate cancer and those with Grade Group ≥2 disease. RESULTS: There are significant increases in α2,3-sialylated PSMA in patients with Grade Group ≥2 disease compared to benign (p = 0.0009) and those with Grade Group 1 disease (p = 0.0063). There were no significant differences in α2,3-sialyl PSMA levels between Grade Group 1 and benign prostate tumors (p = 0.7947). CONCLUSIONS: Our study shows that there are significant differences in the abundance of α2,3-sialylated PSMA in post-DRE urines from disease stratified prostate cancer patients, and the increase is correlated with progression and disease severity. The detection of increased PSMA sialyation in post-DRE urines from patients with higher Grade Group ≥2 disease states provides novel untapped potential for the development of prognostic biomarkers for prostate cancer. Specifically, quantitation of α2,3-sialylated PSMA shows potential for discriminating between benign to intermediate grade disease, which is a significant clinical challenge in staging and risk stratification of prostate cancer.

Long-Term Changes of Urinary Exosomal Peptide Levels After Thyroidectomy in Patients with Thyroid Cancer: A Prospective Observational Study.

Background: The recurrence rate of thyroid cancer can be as high as 30%. The purpose of this study was to examine changes of urine exosomal peptide levels after thyroidectomy in patients with thyroid cancer to determine if levels can predict the risk of recurrence. Methods: Patients >20 years old as newly diagnosed with papillary thyroid cancer who had received a thyroidectomy were recruited. Urine samples were collected at 12 months after enrollment to the study, and 1 year later. Urine exosomes containing different peptides were identified and compared. Results: A total of 70 patients were enrolled in the study, and were classified by the interval between surgery and enrollment: 42 patients with < 5 years between surgery and enrollment, 14 patients between 5-10 years, and 14 patients longer than 10 years. No recurrence was observed in any patient during the 2 years after enrollment. No significant differences were found in the levels of serum proteins or urine exosomal peptides between groups, or between intervals. Known risk factors for high-risk thyroid cancer had only a mild correlation with serum protein levels and urine exosomal peptides. Conclusion: Our study revealed the long-term basal fluctuation ranges of serum proteins and urine exosomal peptides in patients with thyroid cancer who underwent thyroidectomy. For high-risk patients after thyroidectomy, concentrations of serum proteins or urine exosomal peptides within the ranges may indicate there is a lower risk of thyroid cancer recurrence during long-term follow-up. Trial Registration: ClinicalTrials.gov: NCT03488134.

Pilot study for bladder cancer detection with volatile organic compounds using ion mobility spectrometry: a novel urine-based approach.

PURPOSE: Despite many efforts, no reliable urinary marker system has so far shown the potential to substitute cystoscopy. Measuring volatile organic compounds (VOCs) from urine is a promising alternative. VOCs are metabolic products which can be measured from the headspace of urine samples. Previous studies confirmed that the urine of bladder tumor patients has a different VOC profile than healthy controls. In this pilot study, the feasibility of discriminating VOCs from urine of bladder cancer patients from that of healthy control subjects was investigated. Aim of this study was to investigate whether VOC-based diagnosis of bladder cancer from urine samples is feasible using multicapillary column ion mobility spectrometry (MCC/IMS) and to identify potential molecular correlates to the relevant analytes. METHODS: Headspace measurements of urine samples of 30 patients with confirmed transitional cell carcinoma (TCC) and 30 healthy controls were performed using MCC/IMS. In the results of the measurements, peaks showing significant differences between both groups were identified and implemented into a decision tree with respect to achieve group separation. Molecular correlates were predicted using a pre-defined dataset. RESULTS: Eight peaks with significantly differing intensity were identified, 5 of which were highly significant. Using a six-step decision tree, MCC/IMS showed a sensitivity of 90% and specificity of 100% in group separation. CONCLUSION: VOC-based detection of bladder cancer is feasible. MCC/IMS is a suitable method for urine-based diagnosis and should be further validated. The molecular characteristics and metabolic background of the analytes require further workup.

Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer.

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

Optical biomarker analysis for renal cell carcinoma obtained from preoperative and postoperative patients using ATR-FTIR spectroscopy.

Renal cell carcinoma (RCC) is the most common malignant tumor in the urinary system, accounting for 80 % to 90 % for all renal malignancies. Traditional diagnostic methods like magnetic resonance imaging (MRI) and computed tomography (CT) lack the sensitivity and specificity as they lack specific biomarkers. These limitations impede effective monitoring of tumor recurrence. This study aims to employ Attenuated Total Reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy, an optical technology sensitive to molecular groups, to analyze the potential optical biomarkers in urine and plasma samples from RCC patients pre- and post-surgery. The results reveal distinctive spectral information from both plasma and urine samples. Post-surgery urine spectra exhibit complexity compared to plasma, showing reduced content at 1072 cm-1, 1347 cm-1 and 1654 cm-1 bands, while increased content at 1112 cm-1, 1143 cm-1, 1447 cm-1, 3334 cm-1 and 3420 cm-1 bands. Utilizing machine learning models such as eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), partial least squares (PLS), and artificial neural network (ANN), the study evaluated plasma and urine samples pre- and post-surgery. Remarkably, the XGBoost method excelled in distinguishing between tumor conditions and recovery, achieving an impressive AUC value of 0.99. These results underscore the potential of ATR-FTIR technology in identifying RCC optical biomarkers, with XGBoost showing promise as a valuable screening tool for RCC recurrence diagnosis.