Expression of ADAM Proteases in Bladder Cancer Patients with BCG Failure: A Pilot Study.
Renate PichlerAndrea Katharina LindnerGeorg SchäferGennadi TulchinerNina StaudacherMartin MayrEva ComperatJacob J OrmeGert SchachtnerMartin ThurnherPublished in: Journal of clinical medicine (2021)
Although Bacillus Calmette Guérin (BCG) remains a mainstay of adjuvant treatment in high-risk, non-muscle-invasive bladder cancer, BCG failure occurs in up to 40% of patients, with radical cystectomy (RC) as the inevitable therapeutic consequence. Current data suggest that PD-L1 immunosuppressive signaling is responsible for BCG failure, supporting the therapeutic rationale of combining checkpoint inhibitors with BCG. To address the immune cascade in 19 RC specimens obtained after BCG failure, we applied a small immunohistochemical (IHC) panel consisting of selected markers (PD-L1, GATA-3, a disintegrin and metalloproteinase (ADAM) proteases, IL-10/IL-10R). A modified quick score was used for IHC semi-quantification of these markers in tumor cells (TC) and immune cells (IC) within two different regions: muscle-invasive bladder cancer (MIBC) and primary/concurrent carcinoma in situ (CIS). Contrary to expectation, PD-L1 was consistently low, irrespective of tumor region and cell type. Intriguingly, expression of ADAM17, which has been reported to release membrane-bound PD-L1, was high in both tumor regions and cell types. Moreover, expression of GATA3, IL-10, and IL-10R was also increased, indicative of a generally immunosuppressive tumor microenvironment in BCG failure. ADAM10 expression was associated with advanced tumor disease at RC. Our findings raise the possibility that ADAM proteases may cleave PD-L1 from the surface of bladder TC and possibly also from IC. Therefore, IHC assessment of PD-L1 expression seems to be insufficient and should be supplemented by ADAM10/17 in patients with BCG failure.
Keyphrases
- muscle invasive bladder cancer
- poor prognosis
- transcription factor
- binding protein
- long non coding rna
- dna damage
- radiation therapy
- early stage
- squamous cell carcinoma
- single cell
- cell proliferation
- cell cycle
- machine learning
- oxidative stress
- artificial intelligence
- electronic health record
- locally advanced
- big data
- bacillus subtilis
- fine needle aspiration