Vitiligo Signature‐Based Drug Screening Identifies Fulvestrant as a Novel Immunotherapy Combination Strategy

Immunotherapy has revolutionized cancer treatment; however, only 10-30% of patients experience durable survival benefits, while most malignancies remain resistant. In melanoma, vitiligo-like depigmentation is a frequent and generally mild immune-related adverse event, whose presence correlates positively with enhanced antitumor immune responses and prolonged patient survival. By performing comparative analyses between vitiligo and melanoma, we established a biomarker panel-designated the vitiligo signature (VGS)-that differentiates "cold" from "hot" tumors with high accuracy. Leveraging a deep learning-based efficacy prediction system (DLEPS), we identified and validated Fulvestrant as a candidate capable of enhancing anti-programmed cell death ligand 1 (PD L1) therapy in preclinical models. Single cell RNA sequencing revealed that Fulvestrant expanded cytotoxic T cell populations, while immunofluorescence and flow cytometry confirmed markedly increased CD8⁺ T cell infiltration into tumor tissue. Mechanistic investigations demonstrated that Fulvestrant activates the C─C motif chemokine 5 (CCL5), major histocompatibility complex class I (MHC I), and type II interferon (IFN II) signaling pathways, thereby potentiating antitumor immunity. Collectively, our study introduces a precision approach for patient stratification in immunotherapy and highlights Fulvestrant as a promising component of immunotherapy based combination strategies warranting clinical evaluation.

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Publication Details

Journal
Advanced Science
Published
2025-09-20
DOI
https://doi.org/10.1002/advs.202503979
Citations
1
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
1.05
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article

Vitiligo Signature‐Based Drug Screening Identifies Fulvestrant as a Novel Immunotherapy Combination Strategy

Yingjia Li, Zhengwei Xie, Weikaixin Kong, Suzhen Bi et al.
1 citations
Advanced Science
Cancer Immunotherapy and Biomarkers
1.05
article

Vitiligo Signature‐Based Drug Screening Identifies Fulvestrant as a Novel Immunotherapy Combination Strategy

Yingjia Li, Zhengwei Xie, Weikaixin Kong, Suzhen Bi, Sujie Zhu, Peipei Shan, Wanting Feng, Liting Huang, Jie Zhu
article en
1 citations

Abstract

Immunotherapy has revolutionized cancer treatment; however, only 10-30% of patients experience durable survival benefits, while most malignancies remain resistant. In melanoma, vitiligo-like depigmentation is a frequent and generally mild immune-related adverse event, whose presence correlates positively with enhanced antitumor immune responses and prolonged patient survival. By performing comparative analyses between vitiligo and melanoma, we established a biomarker panel-designated the vitiligo signature (VGS)-that differentiates "cold" from "hot" tumors with high accuracy. Leveraging a deep learning-based efficacy prediction system (DLEPS), we identified and validated Fulvestrant as a candidate capable of enhancing anti-programmed cell death ligand 1 (PD L1) therapy in preclinical models. Single cell RNA sequencing revealed that Fulvestrant expanded cytotoxic T cell populations, while immunofluorescence and flow cytometry confirmed markedly increased CD8⁺ T cell infiltration into tumor tissue. Mechanistic investigations demonstrated that Fulvestrant activates the C─C motif chemokine 5 (CCL5), major histocompatibility complex class I (MHC I), and type II interferon (IFN II) signaling pathways, thereby potentiating antitumor immunity. Collectively, our study introduces a precision approach for patient stratification in immunotherapy and highlights Fulvestrant as a promising component of immunotherapy based combination strategies warranting clinical evaluation.

Advanced ScienceVol. 12(44)
Qingdao University (CN), Peking University (CN), Affiliated Hospital of Qingdao University (CN), Institute for Molecular Medicine Finland (FI), Peking University International Hospital (CN)
Openalex Percentile: Top 18%
Cancer Immunotherapy and Biomarkers
1.05
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