Prognostic Value of Programmed Death Ligand-1 Expression on Tumor-Infiltrating Immune Cells in Patients Treated with Cisplatin-Based Combination Adjuvant Chemotherapy Following Radical Cystectomy for Muscle-Invasive Bladder Cancer: A Retrospective Cohort Study

Programmed Cell Death-Ligand-1 expression in Bladder Schistosomal Squamous Cell Carcinoma – There’s room for Immune Checkpoint Blockage?

Schistosoma haematobium, the causative agent of urogenital schistosomiasis, is a carcinogen type 1 since 1994. It is strongly associated with bladder squamous-cell carcinoma in endemic regions, where it accounts for 53-69% of bladder-carcinoma cases. This histological subtype is associated with chronic inflammation being more aggressive and resistant to conventional chemo and radiotherapy. Immune-Checkpoint-Blockage (ICB) therapies targeting the Programmed-Cell-Death-Protein-1(PD-1)/Programmed-Cell-Death-Ligand-1(PD-L1) axis showed considerable success in treating advanced bladder urothelial carcinoma. PD-L1 is induced by inflammatory stimuli and expressed in immune and tumor cells. The binding of PD-L1 with PD-1 modulates immune response leading to T-cell exhaustion. PD-L1 presents in several isoforms and its expression is dynamic and can serve as a companion marker for patients’ eligibility, allowing the identification of positive tumors that are more likely to respond to ICB therapy. The high PD-L1 expression in bladder-urothelial-carcinoma and squamous-cell carcinoma may affect further ICB-therapy application and outcomes. In general, divergent histologies are ineligible for therapy. These treatments are expensive and prone to auto-immune side effects and resistance. Thus, biomarkers capable of predicting therapy response are needed. Also, the PD-L1 expression assessment still needs refinement. Studies focused on squamous cell differentiation associated with S. haematobium remain scarce. Furthermore, in low and middle-income-regions, where schistosomiasis is endemic, SCC biomarkers are needed. This mini-review provides an overview of the current literature regarding PD-L1 expression in bladder-squamous-cell-carcinoma and schistosomiasis. It aims to pinpoint future directions, controversies, challenges, and the importance of PD-L1 as a biomarker for diagnosis, disease aggressiveness, and ICB-therapy prognosis in bladder-schistosomal-squamous-cell carcinoma.

Expression and Prognostic Implication of PD-L1 in Patients with Urothelial Carcinoma with Variant Histology (Squamous Differentiation or Micropapillary) Undergoing Radical Cystectomy

The expression and prognostic role of programmed death ligand-1 (PD-L1) on tumor-infiltrating immune cells (TICs) has not been determined in urothelial carcinoma (UC) with variant histology. We retrospectively reviewed 90 patients (44 with micropapillary variant of UC (MPUC) and 46 with UC with squamous differentiation (UCSD)) who underwent radical cystectomy between January 2013 and December 2019. The expression of PD-L1 in TICs was measured using the VENTANA (SP-142) immunohistochemistry assay and dichotomized using a 5% cutoff value (positive ≥ 5%). Kaplan–Meier survival analysis was used to estimate recurrence-free survival (RFS), and multivariable Cox proportional hazard models were used to identify factors predicting tumor recurrence. Overall, positive PD-L1 expression in TICs was confirmed in 50 of 90 (55.6%) patients (40.1% (18/44) of MPUC and 69.9% (32/46) of UCSD). RFS was significantly shorter in patients with positive PD-L1 expression in TICs than in those with negative PD-L1 expression both in MPUC (p = 0.005) and UCSD (p = 0.046). Positive PD-L1 expression in TICs was significantly associated with an increased risk of tumor recurrence in both MPUC (HR = 1.85; 95% CI: 1.323–2.672; p = 0.017) and UCSD (HR = 1.58; 95% CI: 1.162–2.780; p = 0.032). In conclusion, positive PD-L1 expression in TICs was significantly associated with poorer RFS in both MPUC and UCSD patients. Our results support the use of adjuvant immunotherapy in these patients if they test positive for PD-L1 in their TICs.

Tumor-Associated Macrophages in Bladder Cancer: Biological Role, Impact on Therapeutic Response and Perspectives for Immunotherapy

Tumor-associated macrophages (TAMs) are one of the most abundant infiltrating immune cells of solid tumors. Despite their possible dual role, i.e., pro- or anti-tumoral, there is considerable evidence showing that the accumulation of TAMs promotes tumor progression rather than slowing it. Several strategies are being developed and clinically tested to target these cells. Bladder cancer (BCa) is one of the most common cancers, and despite heavy treatments, including immune checkpoint inhibitors (ICIs), the overall patient survival for advanced BCa is still poor. TAMs are present in bladder tumors and play a significant role in BCa development. However, few investigations have analyzed the effect of targeting TAMs in BCa. In this review, we focus on the importance of TAMs in a cancerous bladder, their association with patient outcome and treatment efficiency as well as on how current BCa treatments impact these cells. We also report different strategies used in other cancer types to develop new immunotherapeutic strategies with the aim of improving BCa management through TAMs targeting.

Prognostic Role of Programmed Death Ligand-1 on Tumor-Infiltrating Immune Cells in "High-Risk" Patients Following Radical Cystectomy: A Retrospective Cohort Study

Purpose

The aim of this study is to investigate the prognostic role of programmed death ligand-1 (PD-L1) on tumor-infiltrating immune cells (TIICs) in patients after radical cystectomy (RC) for bladder cancer (BCa).

Materials and Methods

We retrospectively reviewed 92 “high-risk” (≥pT3a and/or pN+) patients who underwent RC for BCa, without adjuvant chemotherapy (AC), between April 2014 and December 2019. PD-L1 on TIICs was measured only using the VENTANA (SP-142) immunohistochemistry assay. Patients were categorized into three groups based to the percentage of the tumor area covered by PD-L1 on TIICs: IC0 (<1%), IC1 (≥1% and <5%), and IC2/3 (≥5%). Positive PD-L1 was defined as IC2/3 (≥5%). Kaplan–Meier survival analysis was used to illustrate recurrence-free survival (RFS), and Cox proportional hazard models were used to identify predictive factors of tumor recurrence.

Results

Within the cohort, the proportions of PD-L1 IC0, IC1, and IC2/3 were 21.7%, 23.9%, and 54.4%, respectively. At follow-up (mean 31.3 months), tumor recurrence was identified in 49 patients (53.3%). Using multivariable analysis, tumor stage (pT4; P=0.005), positive lymph nodes (P=0.021), and positive PD-L1 on TIICs (P=0.010) were independent predictors of tumor recurrence. The 2- and 3-year RFS rates were 67.7% and 64.2% in negative PD-L1 on TIICs, while 27.8% and 22.3% in positive PD-L1 on TIICs, respectively.

Conclusions

Positive PD-L1 on TIICs was significantly associated with poorer RFS in “high-risk” patients after RC without AC. Our results support the use of adjuvant immunotherapy in “high-risk” patients with positive PD-L1 on TIICs after RC.

A nomogram combined with radiomics features, albuminuria, and metabolic syndrome to predict the risk of myometrial invasion of bladder cancer

Background

To establish a preoperative prediction model of myometrial invasion of bladder cancer (BC) based on the radiomics characteristics of multi-parameter thin-slice enhanced computed tomography (CT) imaging.

Methods

Data from 100 patients with BC were analyzed retrospectively. The patients were divided into two groups: muscular invasive BC and non-muscular invasive BC. The tumor region was segmented from enhanced CT images (arterial- and venous-phase calibration maps) of all patients using Slicer-3D software. We extracted 1,223 texture features from tumor image data based on the shape and gray-level co-occurrence matrix, gray size region matrix, gray run-length matrix, adjacent gray difference matrix, and gray correlation matrix. The patients were randomly divided into a training group (n=70) and a verification group (n=30) in a 7:3 ratio. Interclass correlation coefficients >0.75, least absolute shrinkage, and selection operator regression were used for feature selection. The prediction model was established by combining Rad-score, independent clinical factors, and support vector machine (SVM), and a radiomics nomogram was constructed. The nomogram was tested using the consistency index, calibration curve, time-dependent receiver operating characteristic curve, and clinical decision curve to predict the myometrial invasion of the bladder preoperatively.

Results

Six radiomics features that were significantly related to myometrial invasion of BC were selected to construct a predictive model. The area under the curve (AUC) values of training group and verification group based on SVM were 0.898 (95% CI: 0.820–0.976) and 0.702 (95% CI: 0.495–0.909), respectively. Single factor and multiple factor analysis showed that albuminuria (95% CI: 0.243–2.206, P=0.0014) and metabolic syndrome (95% CI: 0.850–2.935, P<0.001) were independent influencing factors of BC myometrial invasion. Clinical factors and 11 radiomics features were used to construct a comprehensive model for predicting the pathological grade of BC (radiomics + clinical). After a comprehensive comparison, we found that the overall effectiveness of the model (radiomics + clinical) was the highest (AUC =0.8457).

Conclusions

Based on the multi-parameter thin-layer enhanced CT radiomics feature can be used as a potential independent predictor of BC myometrial invasion, the model based on parameters can initially quantitatively characterize the risk of myometrial invasion, and has excellent potential for predicting myometrial invasion of BC.