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Liang J, Li Y, Wan P, Zhang W, Han J, Zhang M, Li B, Jin T. CYP19A1 polymorphisms and bladder cancer risk in the Chinese Han population. Expert Rev Mol Diagn 2024:1-10. [PMID: 39086208 DOI: 10.1080/14737159.2024.2387652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 07/20/2024] [Accepted: 07/22/2024] [Indexed: 08/02/2024]
Abstract
BACKGROUND The expression of CYP19A1 has implications for the prognosis of female bladder cancer. However, this study aimed to explore the association between single nucleotide polymorphisms (SNPs) in CYP19A1 and bladder cancer risk, as no prior research has addressed this association. RESEARCH DESIGN AND METHODS We selected and genotyped five CYP19A1 SNPs (rs4646, rs6493487, rs1062033, rs17601876, and rs3751599) in 217 patients and 550 controls using the Agena MassARRAY system. Logistic regression analysis was employed to calculate the odds ratio (OR) and 95% confidence intervals (CIs). Bioinformatics predicted SNP functions and CYP19A1 involving pathways. RESULTS Our study revealed a significant association between bladder cancer risk and four SNPs (rs4646 (AC vs. CC: OR = 1.71, FDR-p = 0.005), rs6493487 (G vs. A: OR = 0.68, FDR-p = 0.011), rs1062033 (G vs. C: OR = 0.36, FDR-p < 0.001), and rs17601876 (GA vs. GG: OR = 1.66, FDR-p = 0.008)) in CYP19A1. The three SNPs (rs4646, rs1062033, and rs17601876) were significantly correlated with CYP19A1 expression levels in normal whole blood (p < 0.05). Moreover, CYP19A1 was found to primarily participate in the steroid hormone biosynthesis and metabolic pathways. CONCLUSIONS Consequently, CYP19A1 gene polymorphisms may play a crucial role in the genetic susceptibility to bladder cancer.
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Affiliation(s)
- Jing Liang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
| | - Yongfei Li
- Department of Clinical Medicine, Jining Medical University, Jining, Shandong, China
| | - Panpan Wan
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
| | - Wenjing Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
| | - Junhui Han
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
| | - Man Zhang
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
| | - Bin Li
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
| | - Tianbo Jin
- Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
- Provincial Key Laboratory of Biotechnology of Shaanxi Province, Northwest University, Xi'an, Shaanxi, China
- School of Life Sciences, Northwest University, Xi'an, Shaanxi, China
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Khadhouri S, Hramyka A, Gallagher K, Light A, Ippoliti S, Edison M, Alexander C, Kulkarni M, Zimmermann E, Nathan A, Orecchia L, Banthia R, Piazza P, Mak D, Pyrgidis N, Narayan P, Abad Lopez P, Nawaz F, Tran TT, Claps F, Hogan D, Gomez Rivas J, Alonso S, Chibuzo I, Gutierrez Hidalgo B, Whitburn J, Teoh J, Marcq G, Szostek A, Bondad J, Sountoulides P, Kelsey T, Kasivisvanathan V. Machine Learning and External Validation of the IDENTIFY Risk Calculator for Patients with Haematuria Referred to Secondary Care for Suspected Urinary Tract Cancer. Eur Urol Focus 2024:S2405-4569(24)00093-2. [PMID: 38906722 DOI: 10.1016/j.euf.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 05/24/2024] [Accepted: 06/08/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND The IDENTIFY study developed a model to predict urinary tract cancer using patient characteristics from a large multicentre, international cohort of patients referred with haematuria. In addition to calculating an individual's cancer risk, it proposes thresholds to stratify them into very-low-risk (<1%), low-risk (1-<5%), intermediate-risk (5-<20%), and high-risk (≥20%) groups. OBJECTIVE To externally validate the IDENTIFY haematuria risk calculator and compare traditional regression with machine learning algorithms. DESIGN, SETTING, AND PARTICIPANTS Prospective data were collected on patients referred to secondary care with new haematuria. Data were collected for patient variables included in the IDENTIFY risk calculator, cancer outcome, and TNM staging. Machine learning methods were used to evaluate whether better models than those developed with traditional regression methods existed. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The area under the receiver operating characteristic curve (AUC) for the detection of urinary tract cancer, calibration coefficient, calibration in the large (CITL), and Brier score were determined. RESULTS AND LIMITATIONS There were 3582 patients in the validation cohort. The development and validation cohorts were well matched. The AUC of the IDENTIFY risk calculator on the validation cohort was 0.78. This improved to 0.80 on a subanalysis of urothelial cancer prevalent countries alone, with a calibration slope of 1.04, CITL of 0.24, and Brier score of 0.14. The best machine learning model was Random Forest, which achieved an AUC of 0.76 on the validation cohort. There were no cancers stratified to the very-low-risk group in the validation cohort. Most cancers were stratified to the intermediate- and high-risk groups, with more aggressive cancers in higher-risk groups. CONCLUSIONS The IDENTIFY risk calculator performed well at predicting cancer in patients referred with haematuria on external validation. This tool can be used by urologists to better counsel patients on their cancer risks, to prioritise diagnostic resources on appropriate patients, and to avoid unnecessary invasive procedures in those with a very low risk of cancer. PATIENT SUMMARY We previously developed a calculator that predicts patients' risk of cancer when they have blood in their urine, based on their personal characteristics. We have validated this risk calculator, by testing it on a separate group of patients to ensure that it works as expected. Most patients found to have cancer tended to be in the higher-risk groups and had more aggressive types of cancer with a higher risk. This tool can be used by clinicians to fast-track high-risk patients based on the calculator and investigate them more thoroughly.
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Affiliation(s)
- Sinan Khadhouri
- School of Medicine, University of St Andrews, St Andrews, UK; British Urological Researchers in Surgical Training (BURST), London, UK.
| | - Artsiom Hramyka
- School of Computer Science, University of St Andrews, St Andrews, UK
| | - Kevin Gallagher
- British Urological Researchers in Surgical Training (BURST), London, UK; Institute of Cancer and Genetics, University of Edinburgh, Edinburgh, UK; Division of Surgery and Interventional Science, University College London, London, UK
| | - Alexander Light
- British Urological Researchers in Surgical Training (BURST), London, UK; Department of Surgery and Cancer, Imperial College London, London, UK
| | - Simona Ippoliti
- British Urological Researchers in Surgical Training (BURST), London, UK; Department of Paediatric Surgery, Hull Royal Infirmary, Hull University Teaching Hospitals, Hull, UK
| | - Marie Edison
- British Urological Researchers in Surgical Training (BURST), London, UK; Department of Urology, Chelsea and Westminster Hospital, London, UK
| | - Cameron Alexander
- British Urological Researchers in Surgical Training (BURST), London, UK; Luton and Dunstable University Hospital, Luton, UK
| | - Meghana Kulkarni
- British Urological Researchers in Surgical Training (BURST), London, UK; Department of Urology, St George's University Hospitals NHS Foundation Trust, London, UK
| | - Eleanor Zimmermann
- British Urological Researchers in Surgical Training (BURST), London, UK; Department of Urology, Southmead Hospital, Bristol, UK
| | - Arjun Nathan
- British Urological Researchers in Surgical Training (BURST), London, UK; Division of Surgery and Interventional Science, University College London, London, UK
| | - Luca Orecchia
- AOU Policlinico Tor Vergata University Hospital of Rome, Rome, Italy
| | - Ravi Banthia
- University Hospital Coventry Warwickshire, Coventry, UK
| | - Pietro Piazza
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - David Mak
- Royal Wolverhampton Hospitals, Wolverhampton, UK
| | | | | | | | - Faisal Nawaz
- University Hospitals of Derby and Burton, Derby, UK
| | - Trung-Thanh Tran
- Department of Surgery, Hanoi Medical University, Hanoi, Vietnam; Department of Urology, Hanoi Medical University Hospital, Hanoi, Vietnam
| | | | | | | | | | | | | | | | - Jeremy Teoh
- S.H. Ho Urology Centre, Department of Surgery, The Chinese University of Hong Kong, Hong Kong
| | - Gautier Marcq
- Urology Department, Claude Huriez Hospital, CHU Lille, Lille, France; CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, UMR9020-U1277 - CANTHER - Cancer Heterogeneity Plasticity and Resistance to Therapies, University Lille, Lille, France
| | - Alexandra Szostek
- Urology Department, Claude Huriez Hospital, CHU Lille, Lille, France
| | - Jasper Bondad
- Southend University Hospital, Southend-on-Sea, Essex, UK
| | - Petros Sountoulides
- Department of Urology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Tom Kelsey
- School of Computer Science, University of St Andrews, St Andrews, UK
| | - Veeru Kasivisvanathan
- British Urological Researchers in Surgical Training (BURST), London, UK; University College London, London, UK
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Tan WS, Ahmad A, Zhou Y, Nathan A, Ogunbo A, Gbolahan O, Kallam N, Smith R, Khalifeh M, Tan WP, Cohen D, Volanis D, Walter FM, Sasieni P, Kamat AM, Kelly JD. Hematuria Cancer Risk Score with Ultrasound Informs Cystoscopy Use in Patients with Hematuria. Eur Urol Oncol 2024:S2588-9311(24)00134-2. [PMID: 38811250 DOI: 10.1016/j.euo.2024.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 04/04/2024] [Accepted: 05/07/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND Hematuria is a cardinal symptom of urinary tract cancer and would require further investigations. OBJECTIVE To determine the ability of renal bladder ultrasound (RBUS) with the Hematuria Cancer Risk Score (HCRS) to inform cystoscopy use in patients with hematuria. DESIGN, SETTING, AND PARTICIPANTS The development cohort comprised 1984 patients with hematuria from 40 UK hospitals (DETECT 1; ClinicalTrials.gov: NCT02676180) who received RBUS. An independent validation cohort comprised 500 consecutive patients referred to secondary care for a suspicion of bladder cancer. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Sensitivity and true negative of the HCRS and RBUS were assessed. RESULTS AND LIMITATIONS A total of 134 (7%) and 36 (8%) patients in the development and validation cohorts, respectively, had a diagnosis of urinary tract cancer. Validation of the HCRS achieves good discrimination with an area under the receiver operating characteristic curve of 0.727 (95% confidence interval 0.648-0.800) in the validation cohort with sensitivity of 95% for the identification of cancer. Utilizing the cutoff of 4.500 derived from the HCRS in combination with RBUS in the development cohort, 680 (34%) patients would have been spared cystoscopy at the cost of missing a G1 Ta bladder cancer and a urinary tract cancer patient, while 117 (25%) patients would have avoided cystoscopy at the cost of missing a single patient of G1 Ta bladder cancer with sensitivity for the identification of cancer of 97% in the validation cohort. CONCLUSIONS The HCRS with RBUS offers good discriminatory ability in identifying patients who would benefit from cystoscopy, sparing selected patient cohorts from an invasive procedure. PATIENT SUMMARY The hematuria cancer risk score with renal bladder ultrasound allows for the triage of patients with hematuria who would benefit from visual examination of the bladder (cystoscopy). This resulted in 25% of patients safely omitting cystoscopy, which is an invasive procedure, and would lead to health care cost savings.
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Affiliation(s)
- Wei Shen Tan
- Department of Urology, University of Texas MD Anderson Cancer Centre, Houston, TX, USA; Division of Surgery and Interventional Science, University College London, London, UK.
| | - Amar Ahmad
- Division of Surgery and Interventional Science, University College London, London, UK; Cancer Intelligence, Cancer Research UK, London, UK
| | - Yin Zhou
- Department of Public health and Primary Care, University of Cambridge, Cambridge, UK; Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Arjun Nathan
- Department of Urology, University of Texas MD Anderson Cancer Centre, Houston, TX, USA; Department of Urology, Royal Free Hospital, London, UK
| | | | | | - Neha Kallam
- Department of Urology, Royal Free Hospital, London, UK
| | - Rebecca Smith
- Department of Urology, Royal Free Hospital, London, UK
| | - Maen Khalifeh
- Department of Urology, Royal Free Hospital, London, UK
| | - Wei Phin Tan
- Department of Urology, New York University Langone Health, New York City, NY, USA
| | - Daniel Cohen
- Department of Urology, Royal Free Hospital, London, UK
| | | | - Fiona M Walter
- Department of Public health and Primary Care, University of Cambridge, Cambridge, UK; Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Peter Sasieni
- Faculty of Life Sciences & Medicine, School of Cancer & Pharmaceutical Sciences, Innovation Hub, Guys Cancer Centre, Guys Hospital, King's College London, London, UK
| | - Ashish M Kamat
- Division of Surgery and Interventional Science, University College London, London, UK
| | - John D Kelly
- Division of Surgery and Interventional Science, University College London, London, UK; Department of Urology, University College London Hospitals, London, UK
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Bajeot AS, Roumiguié M. Point de vue de l’urologue : apport de la cytologie urinaire dans le diagnostic et la prise en charge des tumeurs urothéliales. Ann Pathol 2024; 44:183-187. [PMID: 38653657 DOI: 10.1016/j.annpat.2024.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 04/05/2024] [Accepted: 04/08/2024] [Indexed: 04/25/2024]
Affiliation(s)
- A-S Bajeot
- Département d'urologie, CHU de Rangueil/IUCT oncopole, Toulouse, France.
| | - M Roumiguié
- Département d'urologie, CHU de Rangueil/IUCT oncopole, Toulouse, France
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Toribio-Vázquez C, Gómez Rivas J, Amigo F, Carrión DM, Yebes Á, Alonso-Bartolomé M, Ayllon H, Aguilera A, Martinez-Piñeiro L, Antón-Juanilla M, Crespo-Atín V, Otaola-Arca H, Herranz-Yague JA, Munoz Rivero MV, MacKenzie KR, Shah TT, Gao C, Zimmermann E, Jefferies M, Nambiar A, Gallagher KM, Khadhouri S, Kasivisvanathan V. Prevalence of urinary tract cancer in the Spanish cohort of the IDENTIFY study. Actas Urol Esp 2024; 48:228-237. [PMID: 37574012 DOI: 10.1016/j.acuroe.2023.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 06/12/2023] [Accepted: 06/14/2023] [Indexed: 08/15/2023]
Abstract
INTRODUCTION Malignant tumors of the urinary tract are associated with high morbidity and mortality, and their prevalence can vary worldwide. Recently, the IDENTIFY study has published results on the prevalence of urinary tract cancer at a global level. This study evaluates the prevalence of cancer within the Spanish cohort of the IDENTIFY study to determine whether the published results can be extrapolated to our population. PATIENTS AND METHODS An analysis of the data from the Spanish cohort of patients in the IDENTIFY study was performed. This is a prospective cohort of patients referred to secondary care with suspected cancer, predominantly due to hematuria. Patients were recruited between December 2017 and December 2018. RESULTS A total of 706 patients from 9 Spanish centers were analyzed. Of these, 277 (39.2%) were diagnosed with cancer: 259 (36.7%) bladder cancer, 10 (1.4%) upper tract urothelial carcinoma, 9 (1.2%) renal cancer and 5 (0.7%) prostate cancer. Increasing age (OR 1.05 (95% CI 1.03-1.06; P < 0.001)), visible hematuria (VH) OR 2.19 (95% CI 1.13-4.24; P = 0.02)) and smoking (ex-smokers: OR 2.11(95% CI 1.30-3.40; P = 0.002); smokers: OR 2.36 (95% CI 1.40-3.95; P = 0.001)) were associated with higher probability of bladder cancer. CONCLUSION This study highlights the risk of bladder cancer in patients with VH and smoking habits. Bladder cancer presented the highest prevalence; higher than the prevalence reported in previous series and presented in the IDENTIFY study. Future work should evaluate other associated factors that allow us to create cancer prediction models to improve the detection of cancer in our patients.
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Affiliation(s)
- C Toribio-Vázquez
- Servicio de Urología, Hospital Universitario La Paz, Madrid, Spain; Universidad Autónoma de Madrid, Madrid, Spain.
| | - J Gómez Rivas
- Servicio de Urología, Hospital Universitario Clínico San Carlos, Madrid, Spain
| | - F Amigo
- Institut Hospital del Mar d''Investigacions Mèdiques, Barcelona, Spain
| | - D M Carrión
- Servicio de Urología, Hospital Universitario La Paz, Madrid, Spain
| | - Á Yebes
- Servicio de Urología, Hospital Universitario La Paz, Madrid, Spain
| | | | - H Ayllon
- Servicio de Urología, Hospital Universitario La Paz, Madrid, Spain
| | - A Aguilera
- Servicio de Urología, Hospital Universitario La Paz, Madrid, Spain; Universidad Autónoma de Madrid, Madrid, Spain
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Rival PM, Ooi L, Lim H, Varughese A, Pandey M, Dowling C, Sengupta S. Reliability of the IDENTIFY calculator in stratifying risk of urothelial carcinoma in patients with haematuria: An initial evaluation at an Australian centre. BJUI COMPASS 2024; 5:173-177. [PMID: 38371206 PMCID: PMC10869655 DOI: 10.1002/bco2.291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/26/2023] [Accepted: 08/26/2023] [Indexed: 02/20/2024] Open
Affiliation(s)
- Paul M. Rival
- Department of UrologyEastern HealthMelbourneVictoriaAustralia
- Eastern Health Clinical School, Faculty of Medicine, Nursing and Health SciencesMonash UniversityMelbourneVictoriaAustralia
| | - Lucas Ooi
- Department of UrologyEastern HealthMelbourneVictoriaAustralia
| | - Hyun Lim
- Department of UrologyEastern HealthMelbourneVictoriaAustralia
| | | | - Monika Pandey
- Department of UrologyEastern HealthMelbourneVictoriaAustralia
| | - Caroline Dowling
- Department of UrologyEastern HealthMelbourneVictoriaAustralia
- Eastern Health Clinical School, Faculty of Medicine, Nursing and Health SciencesMonash UniversityMelbourneVictoriaAustralia
| | - Shomik Sengupta
- Department of UrologyEastern HealthMelbourneVictoriaAustralia
- Eastern Health Clinical School, Faculty of Medicine, Nursing and Health SciencesMonash UniversityMelbourneVictoriaAustralia
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Su Y, Chen L, Yang J. Network pharmacology and in vitro experiments reveal sophoridine-induced apoptosis and G 1 phase arrest via ROS-dependent PI3K/Akt/FoxO3a pathway activation in human bladder cancer cells. Chem Biol Drug Des 2024; 103:e14476. [PMID: 38346772 DOI: 10.1111/cbdd.14476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 12/07/2023] [Accepted: 12/27/2023] [Indexed: 02/15/2024]
Abstract
Bladder cancer (BLCA), a common primary malignancy, exhibits resistance to conventional chemotherapeutic agents. Sophoridine (SR) is a quinoline alkaloid derived from the traditional Chinese herb Sophora alopecuroides L., which belongs to the legume family Sophoraceae. SR is reported to exert growth-inhibitory effects against several cancers. However, the mechanisms underlying the growth-inhibitory effects of SR on BLCA have not been elucidated. This study performed molecular and cellular experiments to verify the growth-inhibitory effects of SR on BLCA and the underlying mechanisms. SR inhibited cell proliferation and promoted apoptosis and G1-phase arrest through the PI3K/AKT/FoxO3a signaling pathway. More interestingly, the effects of SR can be attributed to the accumulation of reactive oxygen species (ROS) in vivo. ROS may be the upstream factor of this pathway. Additionally, SR inhibited the migration and invasion of BLCA cells in a concentration-dependent or time-dependent manner. This is the first study to demonstrate the ROS-dependent PI3K/AKT/FoxO3a pathway-mediated anticancer effect of SR and the anticancer mechanism of SR in BLCA. The correlation between SR-induced ROS-dependent cell proliferation inhibition, apoptosis, cell cycle arrest, and PI3K/AKT/FoxO3a suggests that SR is a promising novel therapeutic for BLCA.
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Affiliation(s)
- Yao Su
- College of Pharmacy, Chengdu University, Chengdu, Sichuan, China
| | - Lin Chen
- Department of Urology Surgery, Affiliated Hospital and Clinical Medical College of Chengdu University, Chengdu, Sichuan, China
| | - Jin Yang
- Department of Urology Surgery, Affiliated Hospital and Clinical Medical College of Chengdu University, Chengdu, Sichuan, China
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Salari K, Sundi D, Lee JJ, Wu S, Wu CL, DiFiore G, Yan QR, Pienkny A, Lee CK, Oberlin D, Barme G, Piser J, Kahn R, Collins E, Phillips KG, Caruso VM, Goudarzi M, Garcia-Ransom M, Lentz PS, Evans-Holm ME, MacBride AR, Fischer DS, Haddadzadeh IJ, Mazzarella BC, Gray JW, Koppie TM, Bicocca VT, Levin TG, Lotan Y, Feldman AS. Development and Multicenter Case-Control Validation of Urinary Comprehensive Genomic Profiling for Urothelial Carcinoma Diagnosis, Surveillance, and Risk-Prediction. Clin Cancer Res 2023; 29:3668-3680. [PMID: 37439796 PMCID: PMC10502470 DOI: 10.1158/1078-0432.ccr-23-0570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 04/25/2023] [Accepted: 07/11/2023] [Indexed: 07/14/2023]
Abstract
PURPOSE Urinary comprehensive genomic profiling (uCGP) uses next-generation sequencing to identify mutations associated with urothelial carcinoma and has the potential to improve patient outcomes by noninvasively diagnosing disease, predicting grade and stage, and estimating recurrence risk. EXPERIMENTAL DESIGN This is a multicenter case-control study using banked urine specimens collected from patients undergoing initial diagnosis/hematuria workup or urothelial carcinoma surveillance. A total of 581 samples were analyzed by uCGP: 333 for disease classification and grading algorithm development, and 248 for blinded validation. uCGP testing was done using the UroAmp platform, which identifies five classes of mutation: single-nucleotide variants, copy-number variants, small insertion-deletions, copy-neutral loss of heterozygosity, and aneuploidy. UroAmp algorithms predicting urothelial carcinoma tumor presence, grade, and recurrence risk were compared with cytology, cystoscopy, and pathology. RESULTS uCGP algorithms had a validation sensitivity/specificity of 95%/90% for initial cancer diagnosis in patients with hematuria and demonstrated a negative predictive value (NPV) of 99%. A positive diagnostic likelihood ratio (DLR) of 9.2 and a negative DLR of 0.05 demonstrate the ability to risk-stratify patients presenting with hematuria. In surveillance patients, binary urothelial carcinoma classification demonstrated an NPV of 91%. uCGP recurrence-risk prediction significantly prognosticated future recurrence (hazard ratio, 6.2), whereas clinical risk factors did not. uCGP demonstrated positive predictive value (PPV) comparable with cytology (45% vs. 42%) with much higher sensitivity (79% vs. 25%). Finally, molecular grade predictions had a PPV of 88% and a specificity of 95%. CONCLUSIONS uCGP enables noninvasive, accurate urothelial carcinoma diagnosis and risk stratification in both hematuria and urothelial carcinoma surveillance patients.
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Affiliation(s)
- Keyan Salari
- Department of Urology, Massachusetts General Hospital, Boston, Massachusetts
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Debasish Sundi
- Department of Urology, The Ohio State University Comprehensive Cancer Center & Pelotonia Institute for Immuno-Oncology, Columbus, Ohio
| | - Jason J. Lee
- Department of Urology, Massachusetts General Hospital, Boston, Massachusetts
| | - Shulin Wu
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Chin-Lee Wu
- Department of Pathology, Massachusetts General Hospital, Boston, Massachusetts
| | - Gabrielle DiFiore
- Department of Urology, The Ohio State University Comprehensive Cancer Center & Pelotonia Institute for Immuno-Oncology, Columbus, Ohio
| | - Q. Robert Yan
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Andrew Pienkny
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Chi K. Lee
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Daniel Oberlin
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Greg Barme
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Joel Piser
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Robert Kahn
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | - Edward Collins
- Golden Gate Urology, Oakland, Berkeley and San Francisco, California
| | | | | | | | | | | | | | | | | | | | | | - Joe W. Gray
- Oregon Health & Science University, Portland, Oregon
| | - Theresa M. Koppie
- Oregon Health & Science University, Portland, Oregon
- Willamette Urology, Salem, Oregon
| | | | | | - Yair Lotan
- Department of Urology, University of Texas Southwestern Medical Center Dallas, Dallas, Texas
| | - Adam S. Feldman
- Department of Urology, Massachusetts General Hospital, Boston, Massachusetts
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Impact of COVID-19 on Uro-Oncological Patients: A Comprehensive Review of the Literature. Microorganisms 2023; 11:microorganisms11010176. [PMID: 36677468 PMCID: PMC9865028 DOI: 10.3390/microorganisms11010176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 01/03/2023] [Accepted: 01/07/2023] [Indexed: 01/12/2023] Open
Abstract
Background: The aim of this paper is to discuss the impact of COVID-19 on patients with urological malignancies (prostate cancer, bladder and upper tract urothelial cancer, kidney cancer, penile and testicular cancer) and to review the available recommendations reported in the literature. Methods: A review was performed, through the PubMed database, regarding available recommendations reported in the literature, to identify studies examining the impact of COVID-19 on treatment and clinical outcomes (including upstaging, recurrence, and mortality) for uro-oncological patients. Results: The COVID-19 pandemic dramatically changed the urological guidelines and patients' access to screening programs and follow-up visits. Great efforts were undertaken to guarantee treatments to high-risk patients although follow up was not always possible due to recurrent surges, and patients with lower risk cancers had to wait for therapies. Conclusions: Physically and mentally, uro-oncological patients paid a heavy price during the COVID-19 pandemic. Long term data on the "costs" of clinical decisions made during the COVID-19 pandemic are still to be revealed and analyzed.
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Zheng Q, Yang R, Ni X, Yang S, Xiong L, Yan D, Xia L, Yuan J, Wang J, Jiao P, Wu J, Hao Y, Wang J, Guo L, Jiang Z, Wang L, Chen Z, Liu X. Accurate Diagnosis and Survival Prediction of Bladder Cancer Using Deep Learning on Histological Slides. Cancers (Basel) 2022; 14:cancers14235807. [PMID: 36497289 PMCID: PMC9737237 DOI: 10.3390/cancers14235807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/19/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
(1) Background: Early diagnosis and treatment are essential to reduce the mortality rate of bladder cancer (BLCA). We aimed to develop deep learning (DL)-based weakly supervised models for the diagnosis of BLCA and prediction of overall survival (OS) in muscle-invasive bladder cancer (MIBC) patients using whole slide digitized histological images (WSIs). (2) Methods: Diagnostic and prognostic models were developed using 926 WSIs of 412 BLCA patients from The Cancer Genome Atlas cohort. We collected 250 WSIs of 150 BLCA patients from the Renmin Hospital of Wuhan University cohort for external validation of the models. Two DL models were developed: a BLCA diagnostic model (named BlcaMIL) and an MIBC prognostic model (named MibcMLP). (3) Results: The BlcaMIL model identified BLCA with accuracy 0.987 in the external validation set, comparable to that of expert uropathologists and outperforming a junior pathologist. The C-index values for the MibcMLP model on the internal and external validation sets were 0.631 and 0.622, respectively. The risk score predicted by MibcMLP was a strong predictor independent of existing clinical or histopathologic indicators, as demonstrated by univariate Cox (HR = 2.390, p < 0.0001) and multivariate Cox (HR = 2.414, p < 0.0001) analyses. The interpretability of DL models can help in the analysis of critical regions associated with tumors to enrich the information obtained from WSIs. Furthermore, the expression of six genes (ANAPC7, MAPKAPK5, COX19, LINC01106, AL161431.1 and MYO16-AS1) was significantly associated with MibcMLP-predicted risk scores, revealing possible potential biological correlations. (4) Conclusions: Our study developed DL models for accurately diagnosing BLCA and predicting OS in MIBC patients, which will help promote the precise pathological diagnosis of BLCA and risk stratification of MIBC to improve clinical treatment decisions.
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Affiliation(s)
- Qingyuan Zheng
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Rui Yang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Xinmiao Ni
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Song Yang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Lin Xiong
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Dandan Yan
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Lingli Xia
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jingping Yuan
- Department of Pathology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jingsong Wang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Panpan Jiao
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jiejun Wu
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Yiqun Hao
- Division of Nephrology, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Jianguo Wang
- Department of Hepatic-Biliary-Pancreatic Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Liantao Guo
- Department of Breast and Thyroid Surgery, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Zhengyu Jiang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Lei Wang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
| | - Zhiyuan Chen
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Correspondence: (Z.C.); (X.L.)
| | - Xiuheng Liu
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Institute of Urologic Disease, Renmin Hospital of Wuhan University, Wuhan 430060, China
- Correspondence: (Z.C.); (X.L.)
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Guan T, Su M, Luo Z, Peng W, Zhou R, Lu Z, Feng M, Li W, Teng Y, Jiang Y, Ou C, Chen M. Long-Term Cardiovascular Mortality among 80,042 Older Patients with Bladder Cancer. Cancers (Basel) 2022; 14:cancers14194572. [PMID: 36230496 PMCID: PMC9559628 DOI: 10.3390/cancers14194572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/14/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary We conducted a large-scale population-based study with long-term follow-up to obtain a comprehensive assessment of death causes, especially cardiovascular disease death, among 80,042 older bladder cancer patients from a national cancer registry containing 44 years of data. To our knowledge, this was the first study to report the importance of CVD-related death as a competing risk among older patients with bladder cancer. CVD-related death surpassed BC as the leading cause of death 5–10 years after diagnosis among older BC patients, especially for patients with localized-stage and low-grade tumors. Furthermore, older BC patients had a higher risk of CVD-related death than the general population. Although BC management should be the primary focus of older BC patients, our results emphasized the importance of competing risks, the most prominent being CVD. Individual follow-up and management should focus not only on primary cancer but also on CVD-related death to minimize the risk of death in older patients with bladder cancer. Abstract Background: To identify the risk of death from cardiovascular disease (CVD) in older patients with bladder cancer (BC). Methods: This population-based study included 80,042 older BC patients (≥65 years) diagnosed between 1975 and 2018, with a mean follow-up of 17.2 years. The proportion of deaths, competing risk models, standardized mortality ratio (SMR), and absolute excess risk (AER) per 10,000 person-years were applied to identify the risk of CVD-related deaths among older BC patients. Results: For older patients with BC, CVD-related death was the chief cause of death, and cumulative CVD-related mortality also exceeded primary BC as the leading cause of death mostly 5–10 years after BC diagnosis, especially in localized-stage and low-grade subgroups. The risk of short- and long-term CVD-related death in older BC patients was higher than in the general older adult population (SMR = 1.30, 95% CI 1.28–1.32; AER = 105.68). The risk of sex-specific CVD-related deaths also increased compared to the general population of older adults, including heart disease, cerebrovascular diseases, hypertension without heart disease, atherosclerosis, aortic aneurysm and dissection, and other diseases of the arteries, arterioles, and capillaries. Conclusions: CVD-related death is an important competing risk among older BC patients and has surpassed primary BC as the chief cause of death, mainly 5–10 years after BC diagnosis. The risk of CVD-related death in older patients with BC was greater than in the general population. The management of older patients with BC should focus not only on the primary cancer but also on CVD-related death.
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Affiliation(s)
- Tianwang Guan
- Laboratory of Heart Center, Department of Cardiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
- Guangdong Provincial Biomedical Engineering Technology Research Center for Cardiovascular Disease, Guangzhou 510280, China
- Sino-Japanese Cooperation Platform for Translational Research in Heart Failure, Guangzhou 510280, China
| | - Miao Su
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China
| | - Zehao Luo
- Department of Clinical Medicine, Clinical Medical School, Guangzhou Medical University, Guangzhou 510180, China
| | - Weien Peng
- Department of Clinical Medicine, Clinical Medical School, Guangzhou Medical University, Guangzhou 510180, China
| | - Ruoyun Zhou
- Department of Clinical Medicine, Clinical Medical School, Guangzhou Medical University, Guangzhou 510180, China
| | - Zhenxing Lu
- Laboratory of Heart Center, Department of Cardiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
- Guangdong Provincial Biomedical Engineering Technology Research Center for Cardiovascular Disease, Guangzhou 510280, China
- Sino-Japanese Cooperation Platform for Translational Research in Heart Failure, Guangzhou 510280, China
| | - Manting Feng
- Department of Clinical Medicine, Clinical Medical School, Guangzhou Medical University, Guangzhou 510180, China
| | - Weirun Li
- Laboratory of Heart Center, Department of Cardiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
- Guangdong Provincial Biomedical Engineering Technology Research Center for Cardiovascular Disease, Guangzhou 510280, China
- Sino-Japanese Cooperation Platform for Translational Research in Heart Failure, Guangzhou 510280, China
| | - Yintong Teng
- Laboratory of Heart Center, Department of Cardiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
- Guangdong Provincial Biomedical Engineering Technology Research Center for Cardiovascular Disease, Guangzhou 510280, China
- Sino-Japanese Cooperation Platform for Translational Research in Heart Failure, Guangzhou 510280, China
| | - Yanting Jiang
- Department of Clinical Medicine, Clinical Medical School, Guangzhou Medical University, Guangzhou 510180, China
| | - Caiwen Ou
- Laboratory of Heart Center, Department of Cardiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
- Dongguan Hospital of Southern Medical University, Southern Medical University, Dongguan 523059, China
- Correspondence: (C.O.); (M.C.)
| | - Minsheng Chen
- Laboratory of Heart Center, Department of Cardiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
- Guangdong Provincial Biomedical Engineering Technology Research Center for Cardiovascular Disease, Guangzhou 510280, China
- Sino-Japanese Cooperation Platform for Translational Research in Heart Failure, Guangzhou 510280, China
- Correspondence: (C.O.); (M.C.)
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Jarbøl DE, Hyldig N, Möller S, Wehberg S, Rasmussen S, Balasubramaniam K, Haastrup PF, Søndergaard J, Rubin KH. Can National Registries Contribute to Predict the Risk of Cancer? The Cancer Risk Assessment Model (CRAM). Cancers (Basel) 2022; 14:cancers14153823. [PMID: 35954486 PMCID: PMC9367495 DOI: 10.3390/cancers14153823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 07/31/2022] [Accepted: 08/04/2022] [Indexed: 11/22/2022] Open
Abstract
Simple Summary Early identification of individuals with an increased risk of cancer is an important challenge. Danish administrative registers may be useful in this respect because they cover the entire population and include comprehensive and consistently coded long-term data. We aimed to develop a predictive model based on Danish administrative registers to facilitate the automated identification of individuals at risk of any type of cancer. In addition to age, almost all the included factors contributed statistically significantly, but also only marginally, to the prediction models, which means that we have not overlooked obvious information available in the register. Future prediction studies should focus on specific cancer types where more precise risk estimations might be expected. It is our ultimate ambition that an effective model can be used at the point of care, integrated into electronic patient record systems to alert physicians of patients at a high risk of cancer. Abstract Purpose: To develop a predictive model based on Danish administrative registers to facilitate automated identification of individuals at risk of any type of cancer. Methods: A nationwide register-based cohort study covering all individuals in Denmark aged +20 years. The outcome was all-type cancer during 2017 excluding nonmelanoma skin cancer. Diagnoses, medication, and contact with general practitioners in the exposure period (2007–2016) were considered for the predictive model. We applied backward selection to all variables by logistic regression to develop a risk model for cancer. We applied the models to the validation cohort, calculated the receiver operating characteristic curves, and estimated the corresponding areas under the curve (AUC). Results: The study population consisted of 4.2 million persons; 32,447 (0.76%) were diagnosed with cancer in 2017. We identified 39 predictive risk factors in women and 42 in men, with age above 30 as the strongest predictor for cancer. Testing the model for cancer risk showed modest accuracy, with an AUC of 0.82 (95% CI 0.81–0.82) for men and 0.75 (95% CI 0.74–0.75) for women. Conclusion: We have developed and tested a model for identifying the individual risk of cancer through the use of administrative data. The models need to be further investigated before being applied to clinical practice.
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Affiliation(s)
- Dorte E. Jarbøl
- Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5000 Odense, Denmark
- Correspondence:
| | - Nana Hyldig
- OPEN—Open Patient Data Explorative Network, Odense University Hospital, 5000 Odense, Denmark
| | - Sören Möller
- OPEN—Open Patient Data Explorative Network, Odense University Hospital, 5000 Odense, Denmark
- Research Unit OPEN, Department of Clinical Research, University of Southern Denmark, 5230 Odense, Denmark
| | - Sonja Wehberg
- Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5000 Odense, Denmark
| | - Sanne Rasmussen
- Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5000 Odense, Denmark
| | - Kirubakaran Balasubramaniam
- Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5000 Odense, Denmark
| | - Peter F. Haastrup
- Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5000 Odense, Denmark
| | - Jens Søndergaard
- Research Unit of General Practice, Department of Public Health, University of Southern Denmark, 5000 Odense, Denmark
| | - Katrine H. Rubin
- OPEN—Open Patient Data Explorative Network, Odense University Hospital, 5000 Odense, Denmark
- Research Unit OPEN, Department of Clinical Research, University of Southern Denmark, 5230 Odense, Denmark
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