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• W4313454633 abstract "Immune checkpoint inhibitors (ICIs) have become one important therapeutic strategy for advanced non-small-cell lung cancer (NSCLC). It remains imperative to identify reliable and convenient biomarkers to predict both the efficacy and toxicity of immunotherapy, and tumor-associated autoantibodies (TAAbs) are recognized as one of the promising candidates for this.This study enrolled 97 advanced NSCLC patients with ICI-based immunotherapy treatment, who were divided into a training cohort (n = 48) and a validation cohort (n = 49), and measured for the serum level of 35 TAAbs. According to the statistical association between the serum positivity and clinical outcome of each TAAb in the training cohort, a TAAb panel was developed to predict the progression-free survival (PFS), and further examined in the validation cohort and in different subgroups. Similarly, another TAAb panel was derived to predict the occurrence of immune-related adverse events (irAEs).In the training cohort, a 7-TAAb panel composed of p53, CAGE, MAGEA4, GAGE7, UTP14A, IMP2, and PSMC1 TAAbs was derived to predict PFS (median PFS [mPFS] 9.9 vs. 4.3 months, p = 0.043). The statistical association between the panel positivity and longer PFS was confirmed in the validation cohort (mPFS 11.1 vs. 4.8 months, p = 0.015) and in different subgroups of patients. Moreover, another 4-TAAb panel of BRCA2, MAGEA4, ZNF768, and PARP TAAbs was developed to predict the occurrence of irAEs, showing higher risk in panel-positive patients (71.43% vs. 28.91%, p = 0.0046).Collectively, our study developed and validated two TAAb panels as valuable prognostic biomarkers for immunotherapy." @default.
• W4313454633 created "2023-01-06" @default.
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• W4313454633 date "2023-01-02" @default.
• W4313454633 modified "2023-09-25" @default.
• W4313454633 title "The development of a t<scp>umor‐associated</scp> autoantibodies panel to predict clinical outcomes for immune checkpoint i<scp>nhibitor‐based</scp> treatment in patients with advanced n<scp>on‐small</scp>‐cell lung cancer" @default.
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• W4313454633 doi "https://doi.org/10.1111/1759-7714.14772" @default.
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• W4313454633 hasPublicationYear "2023" @default.
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