Multi-Omics Analyses Revealed Transcriptional Regulators associated with Immune Checkpoint Inhibitor Treatment in Advanced Bladder Cancer

Author(s): Feng Xu, Zuheng Wang, Dian Fu, Xiuquan Shi, Jie Huang, Yuhao Chen, Jianping Da, Tingling Zhang, Jingping Ge, Xiaofeng Xu, Wen Cheng

Abstract Background: Urothelial Bladder Cancer (UBC) is one of the most lethal cancers worldwide, the 5-year survival rate remains poor with platinum-based chemotherapy regimens as the standard of cancer treatment protocol. Recent FDA approval of a programmed death ligand-1 (PD-L1) inhibitor, atezolizumab, in advanced UBC patients is changing the therapeutic landscape. Although the response to anti-PD-L1 is correlated to PD-L1 expression and tumor mutation burden, the molecule determinants of responsiveness or non-responsiveness to Immune Checkpoint Inhibitor (ICI) is largely unknown.

Methods: R package maftools was used for genomic characterization and differential mutational analysis. EdgeR and DysRegSig algorithm were used for differential gene expression and dysregulator analysis. ConcensusTME algorithm was used for deconvolution of cell types within tumor microenvironment from bulk RNAseq data.

Result: A published immunotherapy cohort with whole exome sequencing, RNAseq and clinic outcome data for 29 metastatic urothelial cancer patients was used, paralleled with The Cancer Genome Altas (TCGA) Bladder Cancer cohort, GSE78220 cohort and MSKCC-bladder cancer cohort. Genomic mutational profiling, mutational signature, a panel genes in antigen presentation and interferon signaling in bladder cancer were delineated with potential correlation with Durable Clinic Benefit (DCB) or non-DCB of PD-L1 inhibitor treatment. Characterized immune-responsive or resistant associated genes showed differentially expressed between DCB group and non-DCB group. Furthermore, transcriptional signature and transcriptional regulators between DCB and non- DCB were identified from transcriptomic data.

Conclusion: Our exploratory analyses provide multidimensional view of complexity of molecular determinants of immune responsiveness and suggest the influences of transcriptional reprogram in i