PhD Scientific Days 2022

Pathology and Oncology I. (Poster discussion will take place in the Aula during the Coffee Break)

Molecular Analysis of Urothelial Carcinoma to Predict the Efficacy of Immune Checkpoint Inhibitor Therapy

Text of the abstract

Introduction: Immune checkpoint inhibitors (ICIs) have become available for systemic treatment of advanced urothelial carcinoma. PD-(L)1 inhibitor therapies have resulted in durable therapeutic effect in a subset of platinum-resistant or ineligible patients. The molecular background of the large individual heterogeneity regarding the response to ICIs is poorly understood.
Aims: The aim of our research is to elucidate individual differences in ICI therapy efficacy by molecular analyses of the tumour and to develop a prediction model that combines clinical and molecular data for the prediction of efficacy of ICIs.
Methods: Our research involves the collection of clinical data, serum, stool, and tumour samples from urothelial cancer patients who received ICI treatment. Clinical and follow-up data from more than 200 patients have been collected and formalin-fixed paraffin-embedded tissue samples from 41 patients have been analysed. We assessed the gene expression pattern of 770 immune-related genes using the NanoString technology. In addition, a 60-gene panel was used to determine the molecular subtypes according to various classification systems. Prognostic genes were further tested in silico in the transcriptome data of the IMvigor 210 study.
Result: Gene expression analyses have been performed on samples of 41 ICI-treated patients. Presence of liver metastasis (p=0.009), age ≤68 years (p=0.032) and worse ECOG PS (p=0.002), proved to be independently associated with shorter overall survival. Among immune-related genes, 44 were found to correlate with overall survival. These were further investigated in the transcriptome data from the IMvigor 210 study, which confirmed the prognostic value of 7 genes (CXCL13, p=0.020; CTLA4, p=0.046; BTLA, p=0.031; ERAP1, p=0.011; APOBEC3B, p=0.046; CRP, p=0.019; and KIR3DL2, p=0.028). Assessing the correlation of molecular subgroups with radiographic response, the luminal (MDA), luminal-infiltrated (TCGA), urothelial (Lund) and stroma-rich (consensus) subgroups showed the highest sensitivity to the ICI therapy.
Conclusion: Our results demonstrate different ICI sensitivity for certain molecular subtypes. In addition, 7 potentially ICI predictive single markers could be identified in our institutional cohort and validated in an independent dataset. However, current interim results are rather preliminary due to low number of cases.