Letter to the Editor: clinical utility of urine DNA for noninvasive detection and minimal residual disease monitoring in urothelial carcinoma

Development and validation of the utLIFE-PC algorithm for noninvasive detection of prostate cancer in urine: A prospective, observational study

Overbiopsy is a serious health issue in prostate cancer (PCa) diagnostics. We have developed a urine tumor DNA multidimensional bioinformatic algorithm, utLIFE, to avoid unnecessary biopsy. The objective is to recognize all or clinically significant PCa. Of the 801 participants recruited in our study, 630 are selected for subsequent analysis. In the training cohort (n = 237), utLIFE-PC gets an area under the receiver operating characteristic curve (AUC) of 0.967 and a sensitivity of 85.57% at 95% specificity. In the independent prospective validation cohort (n = 343), utLIFE-PC has an AUC of 0.929, sensitivity of 84.24%, and specificity of 93.26%. Notably, in patients with ≥grade group (GG)2 and ≥GG3, the assay's sensitivity is still excellent (85.33% and 87.10%, respectively). The model shows better performance than prostate-specific antigen (PSA) (p < 0.001) or the single-dimensional biomarkers (methylation, p < 0.001; copy-number variations [CNVs], p < 0.001; mutation, p < 0.001). The utLIFE-PC model can potentially optimize the PCa diagnostic process and avoid unnecessary biopsies. This study was registered at Chinese Clinical Trial Registry: ChiCTR2300071837.

Large-scale Prospective Validation Study of a Multiplex RNA Urine Test for Noninvasive Detection of Upper Tract Urothelial Carcinoma

BACKGROUND

Current approaches for diagnosis and monitoring of upper tract urothelial carcinoma (UTUC) are often invasive, costly, and not efficient for early-stage and low-grade tumors.

OBJECTIVE

To validate a noninvasive urine-based RNA test for accurate UTUC diagnosis.

DESIGN, SETTING, AND PARTICIPANTS

Urine samples were prospectively collected from 61 patients with UTUC and 99 controls without urothelial carcinomas, in five clinical centers between October 2022 and August 2023 prior to any invasive test (cystoscope or ureteroscope) or treatment. All samples were analyzed with a urine-based RNA test composed of eight genes (CA9, CCL18, ERBB2, IGF2, MMP12, PPP1R14D, SGK2, and SWINGN). The test results were presented with a risk score for each participant, which was applied to categorize patients into low- or high-risk groups.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The diagnosis of UTUC was based mainly on preoperative radiological examination criteria and confirmed by postoperative pathological results. The recursive feature elimination and support vector machine algorithms, χ2, and Student t test were used.

RESULTS AND LIMITATIONS

The eight-gene urine test accurately detected UTUC patients and controls with an area under the curve (AUC) of 0.901 in a single-center testing cohort (n = 93) and an AUC of 0.926 in a multicenter clinical validation cohort (n = 66). In the merged validation cohort, the eight-gene urine test achieved high sensitivity of 90.16%, specificity of 88.89%, and overall accuracy of 89.38%. Remarkably, excellent performance was achieved in 11 low-grade UTUC patients with accuracy of 100%. However, this study collected the urine of UTUC patients only at a single preoperative time point and did not perform continuous tests during the pathological process of UTUC in the surveillance population.

CONCLUSIONS

Our results demonstrated that the eight-gene urine test can differentiate accurately between UTUC and other urological diseases with high sensitivity and specificity. In clinical practice, it may be used for identifying UTUC patients effectively, leading to reduced reliance on ureteroscopy and blind surgery.

PATIENT SUMMARY

In this study, we investigated a multiplex RNA urine test for noninvasive upper tract urothelial carcinoma (UTUC) diagnosis before treatment. We found that the risk scores derived from the multiplex RNA urine test differed significantly between UTUC patients and corresponding controls.

Precision medicine for urothelial carcinoma: An international perspective

The treatment landscape of urothelial cancers has evolved in the last decade with the approval of chemotherapy, immune checkpoint inhibitors, targeted therapies, and antibody drug conjugates. Although improvements in response and survival have been achieved with these strategies, in some scenarios their benefit is still questionable. Current efforts to identify prognostic and predictive biomarkers are crucial for better patient selection and treatment outcomes. In this paper we will review the most promising biomarkers under investigation, such as molecular classifiers, genomic alterations, programmed cell death ligand 1 expression, tumor mutational burden, circulating tumor DNA, urinary biomarkers among others, for muscle invasive bladder cancer and metastatic urothelial cancers. Deeper understanding of these biomarkers will aid clinical decision-making and help tailor treatment strategies.

A Novel Urine DNA Predictor for Noninvasive Early Diagnosis and Monitoring Minimal Residual Disease of Upper Tract Urothelial Carcinoma

BACKGROUND

For early detection and postoperative monitoring of upper tract urothelial carcinoma (UTUC), the traditional detection method was limited to its invasiveness and insufficient sensitivity. We aim to use urine tumour DNA (utDNA) for detecting minimal residual disease (MRD), early diagnosis and perioperative monitoring in UTUC.

METHOD

We previously established a utDNA multidimensional bioinformatic valuation model, named utLIFE, using low-coverage whole-genome sequencing and targeted deep sequencing. This prospective cohort enrolled 93 patients diagnosed with UTUC without metastasis. We collected morning urine samples on the day of surgery and the discharge day after the operation for utLIFE testing. In addition, we also enrolled 80 healthy controls to further validate the specificity of the utLIFE model in the study.

RESULTS

The utLIFE of preoperative samples could discriminate UTUC with high specificity (96.25%, 77/80), and high sensitivity (96.77%, 90/93) regardless of stage and grade. The sensitivity of utLIFE was significantly higher than urine cytology (p < 0.001) and fluorescence in situ hybridisation (FISH) (p < 0.001) (N = 19), especially in early-stage and low-grade UTUC. Postoperative utLIFE scores were significantly decreased compared with those of preoperative samples (79 vs. 36, p < 0.001), indicating its association with tumour burden. For special pathology types, utLIFE performed less well in sensitivity and perioperative alteration.

CONCLUSION

In conclusion, we established a bioinformatic utDNA valuation model, utLIFE, which was validated to be a rapid and noninvasive approach with high sensitivity for early detection and MRD monitoring for UTUC.

Integrative nomogram model based on anoikis-related genes enhances prognostic evaluation in colorectal cancer

Background

Revealing the role of anoikis resistance plays in CRC is significant for CRC diagnosis and treatment. This study integrated the CRC anoikis-related key genes (CRC-AKGs) and established a novel model for improving the efficiency and accuracy of the prognostic evaluation of CRC.

Methods

CRC-ARGs were screened out by performing differential expression and univariate Cox analysis. CRC-AKGs were obtained through the LASSO machine learning algorithm and the LASSO Risk-Score was constructed to build a nomogram clinical prediction model combined with the clinical predictors. In parallel, this work developed a web-based dynamic nomogram to facilitate the generalization and practical application of our model.

Results

We identified 10 CRC-AKGs and a risk-related prognostic Risk-Score was calculated. Multivariate COX regression analysis indicated that the Risk-Score, TNM stage, and age were independent risk factors that significantly associated with the CRC prognosis(p < 0.05). A prognostic model was built to predict the outcome with satisfied accuracy (3-year AUC = 0.815) for CRC individuals. The web interactive nomogram (https://yuexiaozhang.shinyapps.io/anoikisCRC/) showed strong generalizability of our model. In parallel, a substantial correlation between tumor microenvironment and Risk-Score was discovered in the present work.

Conclusion

This study reveals the potential role of anoikis in CRC and sets new insights into clinical decision-making in colorectal cancer based on both clinical and sequencing data. Also, the interactive tool provides researchers with a user-friendly interface to input relevant clinical variables and obtain personalized risk predictions or prognostic assessments based on our established model.

MicroRNA-145-5p suppresses cell proliferation, migration, and invasion in upper tract urothelial carcinoma by targeting 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase

Upper tract urothelial carcinoma (UTUC), including renal, pelvic, and ureteral carcinoma, has a high incidence rate in Taiwan, which is different from that in Western countries. Therefore, it is imperative to elucidate the mechanisms underlying UTUC growth and metastasis. To explore the function of miR-145-5p in UTUC, we transfected the BFTC909 cell line with miR-145-5p mimics and analyzed the differences in protein levels by performing two-dimensional polyacrylamide gel electrophoresis. Real-time polymerase chain reaction and Western blot analysis were used to analyze 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/inositol monophosphate cyclohydrolase (ATIC) messenger RNA and protein levels. A dual-luciferase assay was performed to identify the target of miR-145-5p in ATIC. The effects of miR-145-5p and ATIC expression by cell transfection on cell proliferation, migration, and invasion were also assessed. miR-145-5p downregulated ATIC protein expression. High ATIC expression is associated with tumor stage, metastasis, recurrence, and a poor prognosis in patients with UTUC. Cell function assays revealed that ATIC knockdown inhibited the proliferation, migration, and invasive abilities of UTUC cells. In contrast, miR-145-5p affected the proliferation, migration, and invasive abilities of UTUC cells by directly targeting the 3'-untranslated regions of ATIC. Furthermore, we used RNA sequencing and Ingenuity Pathway Analysis to identify possible downstream genes regulated by ATIC and found that miR-145-5p regulated the protein levels of fibronectin 1, Slug, cyclin A2, cyclin B1, P57, and interferon-induced transmembrane 1 via ATIC. ATIC may be a valuable predictor of prognosis and a potential therapeutic target for UTUC.