Mutated b-catenin Gene Signature to Identify CTNNB1-mutated and Immune Checkpoint Resistant Hepatocellular Cancers

Background & Aims: Patients with beta-catenin (encoded by CTNNB1)-mutated hepatocellular carcinoma (HCC) have demonstrated limited clinical benefit to first-line immunotherapy (IO). Animal models of HCC expressing mutant-beta-catenin and additional aberrations via hydrodynamic tail vein injection with sleeping beauty transposon/transposase (SB-HDTVI) represent clinically relevant human HCC subsets. Here, we perform transcriptomic analysis on multiple beta-catenin-mutated and non-mutated HCC animal models to identify Mutated beta-catenin Gene Signature (MBGS) for HCC patient stratification for CTNNB1-mutations and IO response. Methods: We co-expressed in mice mutant-NFE2L2 and hMET +- mutant-CTNNB1 via SB-HDTVI and monitored for HCC development. Bulk RNA-sequencing was assessed for transcriptional differences between various beta-catenin-mutated and non-mutated models. MBGS was generated for predictive ability of CTNNB1 mutations and IO resistance in multiple HCC patient cohorts. Results: Co-expression of S45Y-beta-catenin + G31A-NFE2L2 + hMet (beta-N-M) resulted in HCC development by 4.5 weeks while co-expression of G31A-NFE2L2 + hMet (N-M) led to HCC by 14 weeks with tumors being positive for expected targets by immunohistochemistry (IHC). Bulk RNA-sequencing comparing beta-catenin-driven versus non-beta-catenin driven models yielded 95 common upregulated genes. Differential gene expression analysis of the common genes comparing CTNNB1-mutated vs non-mutated TCGA patients narrowed the gene panel to 13-(or 10-) genes. This MBGS predicted CTNNB1-mutation status in TCGA (n=374) and French (n=398) patient cohorts (with ROC AUC of 0.90 and 0.94). High MBGS expression was also associated with no overall and progression-free survival benefit when comparing atezolizumab + bevacizumab versus sorafenib arms in IMbrave150 cohort implying fewer treatment effects. Conclusions: In an era of patient molecular stratification for HCC, MBGS may aid in optimally selecting patients for IO through diagnosis of a molecular subset which lacks optimal response.