Significance of Bladder Neck Involvement in Risk Substratification of Intermediate-Risk Non-muscle-invasive Bladder Cancer

Near-infrared photoimmunotherapy targeting Nectin-4 in a preclinical model of bladder cancer

Enfortumab vedotin (EV), an antibody-drug conjugate (ADC) that targets Nectin-4, has shown promising results in the treatment of bladder cancer. However, multiple resistance mechanisms that are unique to ADCs limit the therapeutic potential of EV in clinical practice. Here, we developed and tested a Nectin-4-targeted near-infrared photoimmunotherapy (NIR-PIT) that utilizes the same target as EV but utilizes a distinct cytotoxic and immunotherapeutic pathway in preclinical models of bladder cancer. NIR-PIT was effective in vitro against luminal subtype human bladder cancer cell lines (RT4, RT112, MGH-U3, SW780, and HT1376-luc), but not against other subtype cell lines (UMUC3 and T24). In vivo, the tumor site was clearly visible by Nectin-4-IR700 fluorescence 24 h after its administration, suggesting the potential as an intraoperative imaging modality. NIR-PIT significantly suppressed tumor growth and prolonged survival in SW780 and RT112 xenograft models. Weekly treatment with NIR-PIT further improved tumor control in RT112 xenograft models. The effectiveness of NIR-PIT was also confirmed in HT1376-luc orthotopic xenograft models. Histological analysis verified that NIR-PIT induced a significant pathologic response. Taken together, Nectin-4-targeted NIR-PIT shows promise as a treatment for luminal subtype bladder cancers.

Cancer-Specific Survival of Patients with Non-Muscle-Invasive Bladder Cancer: A Population-Based Analysis

BACKGROUND AND PURPOSE

Non-muscle-invasive bladder cancer (NMIBC) constitutes a heterogeneous group of tumors with different prognoses. This population-based study aimed to report real-world cancer-specific survival (CSS) of NMIBC and create a prognostic nomogram based on the identified risk factors.

METHODS

The Surveillance, Epidemiology, and End Results database was searched for patients diagnosed with NMIBC from 2004 to 2015, who underwent transurethral resection of the bladder tumor. The dataset was divided into development and validation cohorts. Factors associated with CSS were identified using Cox proportional hazards and used to develop a prognostic nomogram.

RESULTS

In total, 98,238 patients with NMIBC were included. At the median follow-up of 124 months (IQR 81-157 months), cancer-specific mortality (CSM) was highest for T1HG (19.52%), followed by Tis (15.56%), similar for T1LG and TaHG (10.88% and 9.23%, respectively), and lowest for TaLG (3.76%). Multivariable Cox regression for CSS prediction was utilized to develop a nomogram including the following risk factors: tumor T category and grade, age, tumor size and location, histology type, primary character, race, income, and marital status. In the validation cohort, the model was characterized by an AUC of 0.824 and C-index that reached 0.795.

CONCLUSIONS

To conclude, NMIBC is associated with a significant risk of long-term CSM especially, but not only, in patients with T1HG. Rarely diagnosed TaHG and T1LG tumors should be regarded as high-risk due to approximately 10% CSM. T category, grading, and age remain the most powerful determinants of CSS in NMIBC, but sociodemographic factors might also influence its prognosis.

Preoperative CT features to predict risk stratification of non-muscle invasive bladder cancer

PURPOSE

To investigate whether preoperative CT features can be used to predict risk stratification of non-muscle invasive bladder cancer (NMIBC).

METHODS

The 168 patients with pathologically confirmed NMIBC who underwent preoperative CT urography were retrospectively analyzed and were divided into training (n = 117) and testing (n = 51) sets. According to the European Association of Urology Guidelines, patients were classified into low-risk (n = 50), medium-risk (n = 23), and high-risk (n = 95) groups. A random over-sample was performed to handle the offset caused by the unbalanced groups. We measured some CT features that may help stratify which for modeling were determined using an F-test-based feature selection with a tenfold cross-validation procedure, and the Gaussian Naive Bayes model was trained on the entire training set. In the testing set, the performance of the model was evaluated.

RESULTS

The selected CT features were the maximum and the minimum diameter of the largest tumor, whether the largest tumor is located at the trigone, and tumor number. In the testing set, the model reached a macro- and micro- AUC of 0.783 and 0.745 with an accuracy of 0.529. As for the one-vs-rest problem, the model was most effective in identifying low-risk individuals, with an AUC, accuracy, sensitivity, and specificity of 0.870, 0.647, 1.000, and 0.438, respectively; the medium-risk group reached 0.814, 0.882, 0.250, and 0.936, respectively; the identification of the high-risk group was harder, going 0.665, 0.529, 0.250, and 0.870, respectively.

CONCLUSION

It is feasible to predict the risk stratification of NMIBC using preoperative CT features.

Preoperative Systemic Inflammatory Markers as a Significant Prognostic Factor After TURBT in Patients with Non-Muscle-Invasive Bladder Cancer

Introduction

Neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and lymphocyte/monocyte ratio (LMR) have been widely proposed to have predictive value for the patient prognosis of many malignancies, including bladder cancer. However, the predictive value of their combination in non-muscle-invasive bladder cancer (NMIBC) is unclear.

Methods

Cases of NMIBC patients who underwent transurethral resection of the bladder tumor were recruited from two tertiary public medical centers. A systemic inflammatory marker (SIM) score was calculated based on comprehensive consideration of NLR, PLR, and LMR. Recurrence-free survival (RFS) and progression-free survival (PFS) were estimated by Kaplan-Meier analysis. The Log rank test was used to compare differences between the groups. Cox regression was used to screen risk factors affecting RFS and PFS. Nomogram models were established and validated, and patients were stratified based on the model scores.

Results

The study dataset was grouped according to a 7:3 randomization, with the training cohort consisting of 292 cases and the validation cohort consisting of 124 cases. Cox regression analysis showed that SIM score is an independent predictor of RFS and PFS in NMIBC patients. The novel models were established based on the SIM score and other statistically significant clinicopathological features. The area under the curve (AUC) for predicting 1-, 2-, and 3-year RFS was 0.667, 0.689, and 0.713, respectively. The AUC for predicting 1-, 2-, and 3-year PFS was 0.807, 0.775, and 0.862, respectively. Based on the risk stratification, patients at high risk of recurrence and progression could be accurately identified. The established models were applied to the patient evaluation of the validation cohort, which proved the great performance of the novel models.

Conclusion

The novel models based on the SIM score and clinicopathological characteristics can accurately predict the survival prognosis of NMIBC patients, and the models can be used by clinicians for individualized patient assessment and to assist in clinical decision-making.

Significance of dorsal bladder neck involvement in predicting the progression of non-muscle-invasive bladder cancer

OBJECTIVES

Accurately predicting of progression is important for patients with non-muscle-invasive bladder cancer (NMIBC). We previously reported that bladder neck involvement (BNI) was significantly associated with progression of NMIBC. In this study, we evaluated the prognostic significance of the detailed BNI location in NMIBC patients.

METHODS

We retrospectively reviewed 651 patients diagnosed with primary NMIBC at a single center between 2000 and 2018. Using the detailed BNI location, patients were divided into the following three groups: dorsal BNI (BNId; 4 to 8 o'clock position), ventral BNI (BNIv; 8 to 4 o'clock but not 4 to 8 o'clock position), and non-BNI group. Both time to progression to muscle-invasive disease and distant metastasis was compared among the three groups. A prognostic model was developed and its discriminative ability was evaluated.

RESULTS

Dorsal bladder neck involvement and BNIv were observed in 43 (6.6%) and 36 (5.5%) patients, respectively. During a median follow-up of 61 months, 35 (5.4%) patients progressed. The cumulative incidence at 5 years was 12%, 0%, and 5.0% in BNId, BNIv, and non-BNI groups, respectively. On multivariate analysis, BNId was a significant and independent risk factor for progression, tumor stage pT1, and histologic grade G3. One point was assigned to each factor, and patients were classified into four well-stratified prognostic groups based on the total score.

CONCLUSION

Dorsal bladder neck involvement was an independent and significant risk factor for progression in primary NMIBC. Our simple and practical prognostic model including BNId is easy to use and may help selecting the optimal treatment and its timing.

Development and external validation of a novel nomogram model for predicting postoperative recurrence-free survival in non-muscle-invasive bladder cancer

Background

Transurethral resection of the bladder tumor with or without adjuvant intravesical instillation (IVI) has been the standard treatment for non-muscle-invasive bladder cancer (NMIBC), whereas a high percentage of patients still experience local tumor recurrence and disease progression after receiving the standard treatment modalities. Unfortunately, current relevant prediction models for determining the recurrent and progression risk of NMIBC patients are far from impeccable.

Methods

Clinicopathological characteristics and follow-up information were retrospectively collected from two tertiary medical centers between October 2018 and June 2021. The least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were used to screen potential risk factors affecting recurrence-free survival (RFS) of patients. A nomogram model was established, and the patients were risk-stratified based on the model scores. Both internal and external validation were performed by sampling the model with 1,000 bootstrap resamples.

Results

The study included 299 patient data obtained from the Affiliated Hospital of Xuzhou Medical University and 117 patient data obtained from the First Affiliated Hospital of Guangxi Medical University. Univariate regression analysis suggested that urine red blood cell count and different tumor invasion locations might be potential predictors of RFS. LASSO-Cox regression confirmed that prior recurrence status, times of IVI, and systemic immune-inflammation index (SII) were independent factors for predicting RFS. The area under the curve for predicting 1-, 2-, and 3-year RFS was 0.835, 0.833, and 0.871, respectively. Based on the risk stratification, patients at high risk of recurrence and progression could be accurately identified. A user-friendly risk calculator based on the model is deposited at https://dl0710.shinyapps.io/nmibc_rfs/.

Conclusion

Internal and external validation analyses showed that our model had excellent predictive discriminatory ability and stability. The risk calculator can be used for individualized assessment of survival risk in NMIBC patients and can assist in guiding clinical decision-making.

[Optimal surveillance intensity of cystoscopy in intermediate-risk non-muscle invasive bladder cancer]

OBJECTIVE

To determine the optimal cystoscopic frequency for intermediate-risk non-muscle invasive bladder cancer.

METHODS

Patients with intermediate-risk non-muscle invasive bladder cancer, who underwent transurethral resection of bladder tumor in Peking University People's Hospital from January 2001 to October 2019, were retrospectively analyzed. Their clinical, pathological and follow-up data were collected. In postoperative 2-year period, the patients were underwent cystoscopy every 3 to 6 months. Depending on recurrence and progression of the patients, we hypothesized three strategies of surveillance intensity in the first 2 years after surgery: model 1: 3-month intervals, model 2: 6-month intervals, and model 3: 12-month intervals. The differences in the numbers and time of delayed detection of recurrence and progression were compared among the three models.

RESULTS

A total of 185 patients were enrolled, including 144 males (77.8%) and 41 females (22.2%). The median age was 68 (59-76) years. There were 118 cases (63.8%) with single tumor and 67 cases (36.2%) with multiple tumor. Of the patients 179 (96.8%) had stage Ta and 6 (3.2%) had stage T1. There were 108 cases (58.4%) with high-grade disease and 77 cases (41.6%) with low-grade disease. During the follow-up period of the first 2 years, 52 patients (28.1%) had recurrence, 133 cases (71.9%) had no recurrence, 11 cases (5.9%) had progression and 174 cases (94.1%) had no progression. Compared with model 1, 29 (55.8%) delayed detection of recurrence in model 2 vs. 41 (78.8%) delayed detection of recurrence in model 3, and the difference was statistically significant (P=0.012). The median delayed time of detecting recurrence was 1.00 months in model 1, 1.99 months in model 2 and 4.19 months in model 3, respectively. There were statistically significant differences between mode 1 and model 3 (P=0.001), and between model 2 and model 3 (P=0.013). Compared with model 1, 5 (45.4%) delayed detection of progression in model 2 vs. 8 (72.7%) delayed detection of progression in model 3, and the difference was not statistically significant. The median delayed time of detecting progression was 1.00 month in model 1, 2.00 months in model 2 and 3.00 months in model 3, respectively. There was no statistically significant difference among them.

CONCLUSION

Although providing slightly slower detection of tumor recurrence and progression, compared with 3-month intervals of cystoscopy, 6-month intervals do not result in serious adverse outcomes and reduce cost and pain of the patients, which is feasible in intermediate-risk non-muscle invasive bladder cancer.

Near-Infrared Photoimmunotherapy (NIR-PIT) in Urologic Cancers

Near-infrared photoimmunotherapy (NIR-PIT) is a novel molecularly-targeted therapy that selectively kills cancer cells by systemically injecting an antibody-photoabsorber conjugate (APC) that binds to cancer cells, followed by the application of NIR light that drives photochemical transformations of the APC. APCs are synthesized by selecting a monoclonal antibody that binds to a receptor on a cancer cell and conjugating it to IRDye700DX silica-phthalocyanine dye. Approximately 24 h after APC administration, NIR light is delivered to the tumor, resulting in nearly-immediate necrotic cell death of cancer cells while causing no harm to normal tissues. In addition, NIR-PIT induces a strong immunologic effect, activating anti-cancer immunity that can be further boosted when combined with either immune checkpoint inhibitors or immune suppressive cell-targeted (e.g., regulatory T cells) NIR-PIT. Currently, a global phase III study of NIR-PIT in recurrent head and neck squamous cell carcinoma is ongoing. The first APC and NIR laser systems were approved for clinical use in September 2020 in Japan. In the near future, the clinical applications of NIR-PIT will expand to other cancers, including urologic cancers. In this review, we provide an overview of NIR-PIT and its possible applications in urologic cancers.