(OTKA FK138696) Támogató: Hungarian National Research, Development and Innovation
Office
(STIA-KFI2021)
(H2020-739593)
(125509) Támogató: OTKA
(ÚNKP-21-3-SZTE-102)
(114-460) Támogató: OTKA
(13208) Támogató: NKFI
HCEMM TKP(TKP-2021-EGA-05) Támogató: NKFIH
HCEMM(2022-2.1.1-NL-2022-00005) Támogató: NKFIH
(POST-COVID2021-36)
While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic
melanoma, only about 50% respond, lacking reliable predictive methods. We introduce
a panel of six proteins aimed at predicting response to ICI therapy. Evaluating previously
reported proteins in two untreated melanoma cohorts, we used a published predictive
model (EaSIeR score) to identify potential proteins distinguishing responders and
non-responders. Six proteins initially identified in the ICI cohort correlated with
predicted response in the untreated cohort. Additionally, three proteins correlated
with patient survival, both at the protein, and at the transcript levels, in an independent
immunotherapy treated cohort. Our study identifies predictive biomarkers across three
melanoma cohorts, suggesting their use in therapeutic decision-making.