Revamped transposon-induced hepatocellular carcinoma model reveals deep similarities of cancer-driver landscapes across mice and humans
- 1HUN-REN Biological Research Centre
Abstract
Genome-scale cancer-driver discovery is limited by statistical uncertainty in driver calling and by experimental constraints on mutations available for selection. We developed 3xfOnc3 - a three-frame Sleeping Beauty (SB) mutagenesis system designed to broaden functional perturbations and reduce integration biases of traditional SB screens - and tested it in vivo in mouse liver. Within 12 months, 60% of mice developed heterogeneous hepatocellular tumors. Tumor-selected integrations were interpreted against an empirical reference from SB-based therapeutic gene delivery to hepatocytes, enabling correction for gene targetability. Background-aware filtering prioritized 315 driver candidates, including 243 protein-coding genes. Tumors were multiclonal, and identical integration-marked lineages expanded differently across lesions, supporting context-dependent clonal expansion. SB hits within young L1 subfamily members were selectively enriched in tumors. Human orthologues of candidate drivers were enriched for Cancer Gene Census genes and protein-altering pan-cancer mutations. Together, 3xfOnc3 reveals a background-corrected driver landscape linking driver selection to clonal tumor evolution and cross-species cancer relevance.
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BibTeX
@misc{imre2026revamped,
title = {{Revamped transposon-induced hepatocellular carcinoma model reveals deep similarities of cancer-driver landscapes across mice and humans}},
author = {G. Imre and A. Mates-Nagy and M. Raya and O. O. Verebi and L. Hudoba and A. Farago and D. Latinovics and R. Karkas and P. German and P. I. Kalman and E. Migh and A. Pettko-Szandtner and O. Kolacsek and A. Furedi and P. Horvath and T. Orban and I. Nagy and L. Mates},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.31.763279},
url = {https://www.biorxiv.org/content/10.64898/2026.10.31.763279v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Revamped transposon-induced hepatocellular carcinoma model reveals deep similarities of cancer-driver landscapes across mice and humans
AU - G. Imre
AU - A. Mates-Nagy
AU - M. Raya
AU - O. O. Verebi
AU - L. Hudoba
AU - A. Farago
AU - D. Latinovics
AU - R. Karkas
AU - P. German
AU - P. I. Kalman
AU - E. Migh
AU - A. Pettko-Szandtner
AU - O. Kolacsek
AU - A. Furedi
AU - P. Horvath
AU - T. Orban
AU - I. Nagy
AU - L. Mates
PY - 2026
DA - 2026/10/31
PB - bioRxiv
DO - 10.64898/2026.10.31.763279
UR - https://www.biorxiv.org/content/10.64898/2026.10.31.763279v1
AB - Genome-scale cancer-driver discovery is limited by statistical uncertainty in driver calling and by experimental constraints on mutations available for selection. We developed 3xfOnc3 - a three-frame Sleeping Beauty (SB) mutagenesis system designed to broaden functional perturbations and reduce integration biases of traditional SB screens - and tested it in vivo in mouse liver. Within 12 months, 60% of mice developed heterogeneous hepatocellular tumors. Tumor-selected integrations were interpreted against an empirical reference from SB-based therapeutic gene delivery to hepatocytes, enabling correction for gene targetability. Background-aware filtering prioritized 315 driver candidates, including 243 protein-coding genes. Tumors were multiclonal, and identical integration-marked lineages expanded differently across lesions, supporting context-dependent clonal expansion. SB hits within young L1 subfamily members were selectively enriched in tumors. Human orthologues of candidate drivers were enriched for Cancer Gene Census genes and protein-altering pan-cancer mutations. Together, 3xfOnc3 reveals a background-corrected driver landscape linking driver selection to clonal tumor evolution and cross-species cancer relevance.
ER -