Journal for immunotherapy of cancer · 2025
Gene-expression signature predicts autoimmune toxicity in metastatic melanoma.
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Mallardo Domenico, Fordellone Mario, Bailey Michael, White Andrew, Simeone Ester, Festino Lucia, Vanella Vito, Trojaniello Claudia, Vitale Maria Grazia, Ottaviano Margaret, Capone Mariaelena, Costa Caterina, Ingenito Maria, Sparano Francesca, Facchini Bianca Arianna, Cavalcanti Ernesta, De Filippi Rosaria, Caracò Corrado, Cesano Alessandra, Warren Sarah, Chiodini Paolo, Budillon Alfredo, Ascierto Paolo A
Аннотация
OBJECTIVES: To identify predictive gene-expression signatures for immune-related adverse events (irAEs) in patients with melanoma treated with anti-PD-1 inhibitors, in the adjuvant therapy (AT) and first-line therapy (FLT).
METHODS: This retrospective study analyzed baseline whole-blood gene expression profile from 161 patients with resected stage III or unresectable stage III-IV melanoma treated with anti-PD-1 inhibitors. RNA was extracted from baseline peripheral blood samples and profiled using the NanoString nCounter PanCancer IO 360 panel. Gene-expression signatures were identified and validated using cross-validated sparse partial least squares modeling and principal component analysis, then correlated with toxicity occurrence.
RESULTS: A total of 223 and 186 irAEs were observed in the AT and FLT groups, respectively, including arthralgia, colitis, and headache. Distinct gene-expression signatures significantly predicted toxicity occurrence, with variation across therapy settings. Arthralgia was predicted by immune-related and apoptotic gene signatures (eg, SMAD5, FASLG in FLT; ICOS, TGFB2 in AT), while colitis was linked to inflammatory and adhesion-related pathways. In the AT group, headache was associated with genes involved in interferon and adhesion signaling. Across both cohorts, specific signatures predicted overall irAE risk and timing. No events were observed in patients with low-risk signatures over the follow-up period. In the FLT cohort, arthralgia and cutaneous toxicities were positively associated with ORR, while arthralgia, asthenia, colitis, fatigue, and skin-related toxicities correlated with improved disease control rate. No significant association between irAEs and relapse risk was observed in the adjuvant cohort.
CONCLUSIONS: Whole-blood gene-expression profiling enables early identification of patients at high risk for irAEs during anti-PD-1 therapy. These predictive biomarkers may guide personalized toxicity monitoring in melanoma treatment.
METHODS: This retrospective study analyzed baseline whole-blood gene expression profile from 161 patients with resected stage III or unresectable stage III-IV melanoma treated with anti-PD-1 inhibitors. RNA was extracted from baseline peripheral blood samples and profiled using the NanoString nCounter PanCancer IO 360 panel. Gene-expression signatures were identified and validated using cross-validated sparse partial least squares modeling and principal component analysis, then correlated with toxicity occurrence.
RESULTS: A total of 223 and 186 irAEs were observed in the AT and FLT groups, respectively, including arthralgia, colitis, and headache. Distinct gene-expression signatures significantly predicted toxicity occurrence, with variation across therapy settings. Arthralgia was predicted by immune-related and apoptotic gene signatures (eg, SMAD5, FASLG in FLT; ICOS, TGFB2 in AT), while colitis was linked to inflammatory and adhesion-related pathways. In the AT group, headache was associated with genes involved in interferon and adhesion signaling. Across both cohorts, specific signatures predicted overall irAE risk and timing. No events were observed in patients with low-risk signatures over the follow-up period. In the FLT cohort, arthralgia and cutaneous toxicities were positively associated with ORR, while arthralgia, asthenia, colitis, fatigue, and skin-related toxicities correlated with improved disease control rate. No significant association between irAEs and relapse risk was observed in the adjuvant cohort.
CONCLUSIONS: Whole-blood gene-expression profiling enables early identification of patients at high risk for irAEs during anti-PD-1 therapy. These predictive biomarkers may guide personalized toxicity monitoring in melanoma treatment.