Prognostic and predictive impact of molecular tumor burden index in non-small cell lung cancer patients

分子肿瘤负荷指数对非小细胞肺癌患者的预后和预测价值

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Abstract

BACKGROUND: The biomarkers of immune checkpoint inhibitors in the treatment of non-small cell lung cancer (NSCLC) patients have limited predictive performance. In this study we aimed to investigate the feasibility of molecular tumor burden index (mTBI) in circulating tumor DNA (ctDNA) as a predictor for immunotherapy in patients with NSCLC. METHODS: From February 2017 to November 2020, pretreatment and on-treatment (3~6 weeks after first cycle of immunotherapy) dynamic plasma ctDNA samples from NSCLC patients receiving immune monotherapy or combination therapy were analyzed by targeted capture sequencing of 1021 genes. PyClone was used to infer the mTBI. The impact of pretreatment mTBI on survival outcomes was verified in the POPLAR/OAK trials. RESULTS: We found that patients without detectable baseline ctDNA had better survival outcomes (median overall survival [OS]: not reached vs. 12.8 months; hazard ratio [HR], 0.15; p = 0.035]). RB1 and SMARCA4 mutations were remarkably associated with worse survival outcomes. Furthermore, lower pretreatment mTBI was associated with superior OS (median: not reached vs. 8.1 months; HR, 0.22; p = 0.024) and PFS (median: 32.9 vs. 5.4 months; HR, 0.35; p = 0.045), but not objective response, which was validated in the POPLAR/OAK cohort, suggesting that baseline mTBI was a prognostic factor for NSCLC immunotherapy. Early dynamic changes of mTBI (ΔmTBI) significantly distinguished responsive patients, and patients with mTBI decrease to more than 68% at the final tumor evaluation had longer OS (median: 38.2 vs. 4.0 months; HR, 0.18; p = 0.017) and PFS (median: not reached vs. 2.3 months; HR, 0.24; p = 0.030). CONCLUSION: ΔmTBI had a good sensitivity to identify potential beneficial patients based on the best effect CT scans, demonstrating that mTBI dynamics were predictive of benefit from immune checkpoint blockade.

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