Back

Targeted KRAS(G12V) degradation elicits efficient and durable lung adenocarcinoma regression in vivo

Martin, A.; Garcia-Perez, I. M.; San Jose, S.; Rojo, P.; Riego-Mejias, C.; Teodosio, C.; Barbosa, B. M.; Sanchez-Zarzalejo, C.; Folch-I-Casanovas, I.; Odena Caballol, A.; Jario, S.; Entrialgo, R.; Nokin, M.-J.; Loa, D.; Guruceaga, E.; Stephan-Otto Attolini, C.; Ambrogio, C.; Villanueva, A.; Vicent, S.; Riera, A.; Santamaria, D.; Mayor-Ruiz, C.

2024-12-15 cancer biology
10.1101/2024.12.13.627539 bioRxiv
Show abstract

Recent drug discovery breakthroughs led to the approval of KRASG12C inhibitors in lung adenocarcinoma (LUAD). Unfortunately, clinical responses remain limited due to rapid resistance onset. Proteolysis-targeting chimeras (PROTACs) have emerged as promising alternatives to traditional inhibition. However, there is limited mechanistic understanding of KRAS degradation in vivo. Here, we developed a preclinical LUAD mouse model and demonstrated that targeted oncogenic KRAS degradation induces rapid tumor regression. Transcriptional, histological, and immunophenotypic analyses revealed a substantial remodeling of the tumor microenvironment. Notably, disease relapse observed during long-term degrader treatment stems from proteolysis machinery dysregulation, indicating resistance mechanisms distinct from those reported upon KRAS inhibition. Our findings highlight the therapeutic potential of KRAS degradation in LUAD, offering insights into cell-intrinsic and extrinsic mechanisms driving durable antitumor responses and supporting further clinical exploration. SIGNIFICANCEGiven the short duration of the clinical responses to KRAS inhibitors, complementary therapies are a dire medical need. Our preclinical findings endorse KRAS degradation as a therapeutic alternative in LUAD, where cell-intrinsic and extrinsic mechanisms drive tumor regression and durable therapeutic responses.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.