Back

Guadecitabine plus ipilimumab in unresectable melanoma: five-year follow-up and correlation with integrated, multiomic analysis in the NIBIT-M4 trial

Noviello, T.; Di Giacomo, A. M.; Caruso, F. P.; Covre, A.; Scala, G.; Costa, M. C.; Coral, S.; Fridman, W. H.; Sautes-Fridman, C.; Mortarini, R.; Brich, S.; Pruneri, G.; Simonetti, E.; Logiego, M. F.; Bedognetti, D.; Anichini, A.; Maio, M.; Ceccarelli, M.; EPigenetic Immune-oncology Consortium AIRC (EPICA) investigators,

2023-02-10 oncology
10.1101/2023.02.09.23285227 medRxiv
Show abstract

Association of DNA hypomethylating agents (DHA) with immune-checkpoint inhibitors (ICI) is a promising strategy to improve efficacy of ICI-based therapy. Here we report the five-year clinical outcome and an integrated multi-omics analysis of pre- and on-treatment lesions from advanced melanoma patients enrolled in the phase Ib NIBIT-M4 study, a dose-escalation trial of the DHA agent guadecitabine combined with ipilimumab. With a minimum follow-up of 45 months the median OS was 25.6 months; the 5-year OS rate was 28.9% and the median DoR was 20.6 months. Specific genomic features and extent of T and B cellmediated immunity discriminated lesions of responding compared to non-responding patients. Enrichment for proliferation and EMT-related gene programs, and immune escape mechanisms characterized lesions from non-responding patients. Integration of a genetic immunoediting index (GIE) with an adaptive immunity signature (ICR) stratified patients/lesions into four distinct subsets and discriminated 5-year OS and PFS. These results suggest that coupling of immunoediting with activation of adaptive immunity is a relevant requisite for achieving long term clinical benefit by epigenetic immunomodulation in advanced melanoma patients.

Matching journals

The top 6 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.