Scientific publications

Mutations in circulating tumor DNA predict primary resistance to systemic therapies in advanced hepatocellular carcinoma. Scientific Publication

Oct 23, 2020 | Magazine: Oncogene

Johann von Felden  1   2 , Amanda J Craig  2 , Teresa Garcia-Lezana  2 , Ismail Labgaa  2   3 , Philipp K Haber  2 , Delia D'Avola  2   4 , Amon Asgharpour  2 , Douglas Dieterich  2 , Antoinette Bonaccorso  5 , Miguel Torres-Martin  2 , Daniela Sia  2 , Max W Sung  6 , Parissa Tabrizian  5 , Myron Schwartz  5 , Josep M Llovet  2   7   8 , Augusto Villanueva  9   10


Abstract

Little is known about the mutational landscape of advanced hepatocellular carcinoma (HCC), and predictive biomarkers of response to systemic therapies are lacking.

We aimed to describe the mutational landscape of advanced HCC and to identify predictors of primary resistance to systemic therapies using circulating tumor DNA (ctDNA). We prospectively enrolled 121 patients between October 2015 and January 2019.

We performed targeted ultra-deep sequencing of 25 genes and Digital Droplet PCR of TERT promoter, including sequential samples throughout treatment. Primary endpoint was progression-free survival (PFS) stratified by mutation profiles in ctDNA. Secondary endpoints were overall survival and objective response rate.

The most frequent mutations in ctDNA of advanced HCC were TERT promoter (51%), TP53 (32%), CTNNB1 (17%), PTEN (8%), AXIN1, ARID2, KMT2D, and TSC2 (each 6%). TP53 and CTNNB1 mutations were mutually exclusive. Patients with mutations in the PI3K/MTOR pathway had significantly shorter PFS than those without these mutations after tyrosine kinase inhibitors (2.1 vs 3.7 months, p < 0.001), but not after immune checkpoint inhibition (CPI). WNT pathway mutations were not associated with PFS, overall survival, or objective response after CPI. Serial profiling of ctDNA in a subset correlated with treatment response.

Mutation profiling of ctDNA in advanced HCC shows similar mutation frequencies for known HCC drivers compared to early stages and identifies predictive biomarkers of response to systemic therapies.

CITATION Oncogene. 2020 Oct 23.doi: 10.1038/s41388-020-01519-1

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