CD8+ Cell Density Gradient across the Tumor Epithelium-Stromal Interface of Non-Muscle Invasive Papillary Urothelial Carcinoma Predicts Recurrence-Free Survival after BCG Immunotherapy

Fibroblast Activation Protein-α and the Immune Landscape: Unraveling T1 Non-muscle-invasive Bladder Cancer Progression

Background and objective

The tumor microenvironment (TME) in non-muscle-invasive bladder cancer (NMIBC) plays an important role in the anticancer response. We aimed to identify the prognostic biomarkers in the TME of patients with NMIBC for progression to ≥T2.

Methods

From our institutional database, 40 patients with T1 high-risk NMIBC who progressed were pair matched for Club Urologico Español de Tratamiento Oncologico (CUETO) progression variables with 80 patients who never progressed despite longer follow-up. Progression was defined as ≥T2 or extravesical disease. Patients were treated at least with bacillus Calmette-Guérin (BCG) induction (five or more of six doses). Immunohistochemical (IHC) markers for the TME were used on tissue at first T1 diagnosis: CD8-PanCK, GZMB-CD8-FOXP3, CD163, PD-L1 SP142/SP263, fibroblast activation protein-α (FAP), and CK5-GATA3. Full tissue slides were annotated digitally. Relative marker area (IHC-positive area/total area) or density (IHC-positive cells per area; n/mm2) was calculated, differentiating between regions of interest (ROIs; T1, Ta, and carcinoma in situ) and between compartments (stromal, epithelial, and combined). Differences in IHC variables were assessed using the t test, for continuous variables using analysis of variance and comparisons of more than two groups using Tukey's test. Conditional logistic regression for progression at 5-yr follow-up was performed with clusters based on pair matching.

Key findings and limitations

Only FAP expression (increase per 50%) in T1 (odds ratio [OR]: 1.33; 95% confidence interval [CI]: 1.04-1.70) and all ROIs combined (OR: 1.62; 95% CI: 1.14-2.29) correlated significantly with progression. None of the other clinicopathological/IHC variables correlated with progression.

Conclusions and clinical implications

FAP is a potential prognostic biomarker for progression in high-risk NMIBC. FAP is a marker for cancer-associated fibroblasts and is linked to immunosuppression and neoangiogenesis, which makes future investigation clinically relevant.

Patient summary

We found that progression of high-risk non-muscle-invasive bladder cancer to muscle-invasive disease is less in patients with lower fibroblast activation protein-α (FAP) expression, which is a marker for cancer-associated fibroblasts.

Spatial Distribution of Macrophage and Lymphocyte Subtypes within Tumor Microenvironment to Predict Recurrence of Non-Muscle-Invasive Papillary Urothelial Carcinoma after BCG Immunotherapy

Non-muscle-invasive papillary urothelial carcinoma (NMIPUC) of the urinary bladder is the most common type of bladder cancer. Intravesical Bacille Calmette-Guerin (BCG) immunotherapy is applied in patients with a high risk of recurrence and progression of NMIPUC to muscle-invasive disease. However, the tumor relapses in about 30% of patients despite the treatment, raising the need for better risk stratification. We explored the potential of spatial distributions of immune cell subtypes (CD20, CD11c, CD163, ICOS, and CD8) within the tumor microenvironment to predict NMIPUC recurrence following BCG immunotherapy. Based on analyses of digital whole-slide images, we assessed the densities of the immune cells in the epithelial-stromal interface zone compartments and their distribution, represented by an epithelial-stromal interface density ratio (IDR). While the densities of any cell type did not predict recurrence, a higher IDR of CD11c (HR: 0.0012, p-value = 0.0002), CD8 (HR: 0.0379, p-value = 0.005), and ICOS (HR: 0.0768, p-value = 0.0388) was associated with longer recurrence-free survival (RFS) based on the univariate Cox regression. The history of positive repeated TUR (re-TUR) (HR: 4.93, p-value = 0.0001) and T1 tumor stage (HR: 2.04, p-value = 0.0159) were associated with shorter RFS, while G3 tumor grade according to the 1973 WHO classification showed borderline significance (HR: 1.83, p-value = 0.0522). In a multivariate analysis, the two models with a concordance index exceeding 0.7 included the CD11c IDR in combination with either a history of positive re-TUR or tumor stage. We conclude that the CD11c IDR is the most informative predictor of NMIPUC recurrence after BCG immunotherapy. Our findings highlight the importance of assessment of the spatial distribution of immune cells in the tumor microenvironment.

Prediction of Non-Muscle Invasive Papillary Urothelial Carcinoma Relapse from Hematoxylin-Eosin Images Using Deep Multiple Instance Learning in Patients Treated with Bacille Calmette-Guérin Immunotherapy

The limited reproducibility of the grading of non-muscle invasive papillary urothelial carcinoma (NMIPUC) necessitates the search for more robust image-based predictive factors. In a cohort of 157 NMIPUC patients treated with Bacille Calmette-Guérin (BCG) immunotherapy, we explored the multiple instance learning (MIL)-based classification approach for the prediction of 2-year and 5-year relapse-free survival and the multiple instance survival learning (MISL) framework for survival regression. We used features extracted from image patches sampled from whole slide images of hematoxylin-eosin-stained transurethral resection (TUR) NPMIPUC specimens and tested several patch sampling and feature extraction network variations to optimize the model performance. We selected the model showing the best patient survival stratification for further testing in the context of clinical and pathological variables. MISL with the multiresolution patch sampling technique achieved the best patient risk stratification (concordance index = 0.574, p = 0.010), followed by a 2-year MIL classification. The best-selected model revealed an independent prognostic value in the context of other clinical and pathologic variables (tumor stage, grade, and presence of tumor on the repeated TUR) with statistically significant patient risk stratification. Our findings suggest that MISL-based predictions can improve NMIPUC patient risk stratification, while validation studies are needed to test the generalizability of our models.

Advancing Cancer Immunotherapy: From Molecular Mechanisms to Clinical Applications

In recent years, cancer immunotherapy research has made remarkable progress, completely transforming the cancer treatment landscape [...].