A new risk stratification model for intravesical recurrence, disease progression, and cancer-specific death in patients with non-muscle invasive bladder cancer: the J-NICE risk tables

Miyake, Makito; Matsuyama, Hideyasu; Teramukai, Satoshi; Kinoshita, Fumie; Yokota, Isao; Matsumoto, Hiroaki; Shimada, Kaoru; Kinjyo, Mitsuru; Shimokama, Tatsuro; Okumura, Koji; Yomenori, Masaya; Enokida, Hideki; Nakagawa, Masayuki; Nakai, Yasushi; Fujimoto, Kiyohide

doi:10.1007/s10147-020-01654-5

Cited by 16 publications

(20 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Based on 20 PRSGs, we constructed a prediction model for the OS of patients with BLCA and the model achieved a good accuracy and applicability (AUC: 0.699). The construction of prediction model can assist oncologists in clinical decisionmarking, thus many previous studies have focused on the identification of prognostic biomarkers in patients with BLCA (29)(30)(31). A lot of statistical methods, such as deep learning, Cox regression and LASSO regression analysis, have been used in the identification of the prognostic factors including the clinical information (age, clinical stage, and lymphovascular invasion), laboratory examination (C-reactive protein); molecular features (competing endogenous RNA, immune infiltration) (29,30,(32)(33)(34).…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of the Prognostic Stemness Biomarkers in Bladder Cancer Bone Metastasis

et al. 2021

View full text Add to dashboard Cite

BackgroundBladder urothelial carcinoma (BLCA) is one of the most common urinary system malignancies with a high metastasis rate. Cancer stem cells (CSCs) play an important role in the occurrence and progression of BLCA, however, its roles in bone metastasis and the prognostic stemness biomarkers have not been identified in BLCA.MethodIn order to identify the roles of CSC in the tumorigenesis, bone metastasis and prognosis of BLCA, the RNA sequencing data of patients with BLCA were retrieved from The Cancer Genome Atlas (TCGA) databases. The mRNA expression-based stemness index (mRNAsi) and the differential expressed genes (DEGs) were evaluated and identified. The associations between mRNAsi and the tumorigenesis, bone metastasis, clinical stage and overall survival (OS) were also established. The key prognostic stemness-related genes (PSRGs) were screened by Lasso regression, and based on them, the predict model was constructed. Its accuracy was tested by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve and the risk score. Additionally, in order to explore the key regulatory network, the relationship among differentially expressing TFs, PSRGs, and absolute quantification of 50 hallmarks of cancer were also identified by Pearson correlation analysis. To verify the identified key TFs and PSRGs, their expression levels were identified by our clinical samples via immunohistochemistry (IHC).ResultsA total of 8,647 DEGs were identified between 411 primary BLCAs and 19 normal solid tissue samples. According to the clinical stage, mRNAsi and bone metastasis of BLCA, 2,383 stage-related DEGs, 3,680 stemness-related DEGs and 716 bone metastasis-associated DEGs were uncovered, respectively. Additionally, compared with normal tissue, mRNAsi was significantly upregulated in the primary BLCA and also associated with the prognosis (P = 0.016), bone metastasis (P < 0.001) and AJCC clinical stage (P < 0.001) of BLCA patients. A total of 20 PSRGs were further screened by Lasso regression, and based on them, we constructed the predict model with a relatively high accuracy (AUC: 0.699). Moreover, we found two key TFs (EPO, ARID3A), four key PRSGs (CACNA1E, LINC01356, CGA and SSX3) and five key hallmarks of cancer gene sets (DNA repair, myc targets, E2F targets, mTORC1 signaling and unfolded protein response) in the regulatory network. The tissue microarray of BLCA and BLCA bone metastasis also revealed high expression of the key TFs (EPO, ARID3A) and PRSGs (SSX3) in BLCA.ConclusionOur study identifies mRNAsi as a reliable index in predicting the tumorigenesis, bone metastasis and prognosis of patients with BLCA and provides a well-applied model for predicting the OS for patients with BLCA based on 20 PSRGs. Besides, we also identified the regulatory network between key PSRGs and cancer gene sets in mediating the BLCA bone metastasis.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification and Validation of the Prognostic Stemness Biomarkers in Bladder Cancer Bone Metastasis

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In clinic, the prediction model may help oncologists to make therapeutic strategy. Therefore, many previous studies have explored the biomarkers and predict the prognosis of patients with BLCA [24][25][26] . In these prediction models, various statistical methods, such as deep learning, Cox regression and LASSO regression analysis, have been used and many prognostic factors have been included, such as clinical information (age, clinical stage and metastasis), laboratory examination (in ammatory indicators); molecular features (competing endogenous RNA, immune in ltration) 24,25,27−29 .…”

Section: Discussionmentioning

confidence: 99%

Identification of the prognostic Enhancer RNA in bladder cancer bone metastasis

Hao

Yan

Zheng

et al. 2020

Preprint

View full text Add to dashboard Cite

Background Bladder urothelial carcinoma (BLCA), one of the most common urinary system malignancies, has a high morbidity and metastasis rate. The enhancer RNAs (eRNAs), are derived from enhancer regions and contribute to enhancer function, whereas their roles in BLCA tumorigenesis and bone metastasis are still unclear.Method The RNA sequencing data of patients with BLCA were retrieved from The Cancer Genome Atlas (TCGA) databases and the normalized gene expression profile of eRNA in BLCA (annotated by Ensemble ID) were downloaded from the eRic database. The differential expression eRNAs and genes were evaluated and identified between primary BLCA with and without bone metastasis. The prognostic bone metastasis-specific eRNAs (PBMSEs) were screened by Lasso regression, and based on them, the risk scores were identified and predict models were constructed. Their accuracy were tested by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve. Additionally, in order to explore the bone metastasis-specific regulation network, the relationship among key PBMSEs, differentially expressed target genes of eRNAs and signaling pathways were identified by Pearson correlation analysis. ResultsA total of 832 eRNAs were detected, with 37 PBMSEs annotated by Ensemble ID in univariate Cox regression analysis. Based on them, the first prediction model was constructed with the AUC of 0.920. Besides, we uncovered 166 DEGs between primary BLCA with and without bone metastasis. A total of 23 eRNAs and 109 target genes annotated by official gene symbol were uncovered in which31 PBMSEs and target genes revealed prognostic. Based on them, another prediction model was constructed with the AUC of 0.742. Moreover, we identified EMP1 as a PBMSE which regulated the target genes of APOLD1 and GPRC5A, and tumorigenesis-related pathways of KRAS signaling, inflammatory response, IL2-stat5 signaling and epithelial mesenchymal transition (EMT).Conclusion Our study identifies eRNAs as reliable indexes for prognosis and bone metastasis prediction in BLCA patients and provides well-applied prediction models for them. The bone metastasis-specific regulation network was also explored in which PBMSE (EMP1) could mediate target genes (APOLD1, GPRC5A) and tumorigenesis-related pathways (KRAS signaling, inflammatory response, EMT) in the tumorigenesis and bone metastasis of BLCA.

show abstract

“…To date, we have conducted several observational studies on the oncological outcomes of NMIBC patients treated using TURBT with or without intravesical treatment [1,[20][21][22][23]. Our study subjects include patients with low-or intermediate-risk NMIBC, who were treated with TURBT followed by IPIC (with no further adjuvant treatment) and who were eligible for the pilot analysis.…”

Section: Determining the Target Sample Sizementioning

confidence: 99%

Fluorescent cystoscopy-assisted en bloc transurethral resection versus conventional transurethral resection in patients with non-muscle invasive bladder cancer: study protocol of a prospective, open-label, randomized control trial (the FLEBER study)

Miyake

Nishimura

Inoue

et al. 2021

Trials

Self Cite

View full text Add to dashboard Cite

Background Transurethral resection of bladder tumor (TURBT) is an essential procedure both for the treatment and staging of bladder cancer, particularly non-muscle invasive bladder cancer (NMIBC). The dissemination of cancer cells during resection and the consequent seeding into the bladder mucosa is the main cause of post-TURBT intravesical recurrence. Although the tumor dissemination is inevitable during conventional TURBT (cTURBT), this drawback can be overcome by tumor resection in one piece with intact surrounding normal tissues, referred to as en bloc resection. We previously described the photodynamic diagnosis (PDD)-assisted en bloc TURBT (EBTUR) technique and its favorable outcomes. Based on our preliminary studies, this randomized controlled trial was designed to evaluate the superiority of PDD-EBTUR to PDD-cTURBT. Methods The FLEBER study is a single-center randomized controlled trial in NMIBC patients who require TURBT. The longest diameter of the tumor must be between 6 and 30 mm. A total of 160 eligible patients will be enrolled after screening and randomly allocated to the PDD-EBTUR (experimental) and PDD-cTURBT (control) groups in a 1:1 ratio (80 cases to 80 cases). All patients will be treated using a single, immediate postoperative intravesical chemotherapy with epirubicin. The primary endpoint of this trial is the 2-year recurrence-free survival after surgery in pathologically proven low- or intermediate-risk NMIBC. All patients will be monitored by cystoscopy and urine cytology every 3 months for 2 years. Patient data including adverse events and complications, and data from frequency volume charts, pain scales, and health-related QOL questionnaires will be collected before and after the TURBT at indicated visits. Discussion The goal of this trial is to determine the potential benefits of PDD-cTURBT and PDD-EBTUR followed by a single immediate postoperative intravesical chemotherapy in patients with low- or intermediate-risk NMIBC who undergo TURBT. Ultimately, our findings will lead to the development of better interventions and potentially change the standard of care. Trial registration This clinical trial was prospectively registered with the UMIN Clinical Trials Registry on 1 August 2020. The reference number is UMIN000041273, and the Ethics Committee of Nara Medical University Approval ID is 2702.

show abstract

A new risk stratification model for intravesical recurrence, disease progression, and cancer-specific death in patients with non-muscle invasive bladder cancer: the J-NICE risk tables

Cited by 16 publications

References 27 publications

Identification and Validation of the Prognostic Stemness Biomarkers in Bladder Cancer Bone Metastasis

Identification and Validation of the Prognostic Stemness Biomarkers in Bladder Cancer Bone Metastasis

Identification of the prognostic Enhancer RNA in bladder cancer bone metastasis

Fluorescent cystoscopy-assisted en bloc transurethral resection versus conventional transurethral resection in patients with non-muscle invasive bladder cancer: study protocol of a prospective, open-label, randomized control trial (the FLEBER study)

Contact Info

Product

Resources

About