期刊
CANCERS
卷 13, 期 19, 页码 -出版社
MDPI
DOI: 10.3390/cancers13194839
关键词
triple-negative breast neoplasms; neoadjuvant therapy; immunotherapy; biomarkers; tumor microenvironment
类别
资金
- AstraZeneca
- Susan Komen Leadership Grant [SAC160076]
- Investigator Award from the Breast Cancer Research Foundation
- Morgan Welch Inflammatory Breast Cancer Research Program
- State of Texas Rare and Aggressive Breast Cancer Research Program grant
- National Institutes of Health/National Cancer Institute award [1R01CA205043-01A1]
- NCI through Cancer Center Support Grant [CA016672]
The study confirmed a novel 27-gene immuno-oncology signature for predicting the pathologic complete response of primary triple-negative breast cancer to neoadjuvant immunotherapy. Combining this signature with PD-L1 immunohistochemistry enhanced the predictive power. Further analysis in a larger cohort is warranted.
Simple Summary Through analysis of specimens from patients with primary triple-negative breast cancer (TNBC) enrolled in a neoadjuvant clinical trial assessing durvalumab with chemotherapy, we confirmed a novel 27-gene immuno-oncology (IO) signature that generates an IO score to predict the pathologic complete response (pCR) of primary TNBC to neoadjuvant immunotherapy with the PD-L1 blocker durvalumab with chemotherapy. Combining the 27-gene IO signature with PD-L1 immunohistochemistry strengthened the model's predictive power of the pCR. Furthermore, the comprehensive computational analysis revealed that the 27-gene IO signature corresponded with an immunogenic tumor microenvironment. A precise predictive biomarker for TNBC response to immunochemotherapy is urgently needed. We previously established a 27-gene IO signature for TNBC derived from a previously established 101-gene model for classifying TNBC. Here we report a pilot study to assess the performance of a 27-gene IO signature in predicting the pCR of TNBC to preoperative immunochemotherapy. We obtained RNA sequencing data from the primary tumors of 55 patients with TNBC, who received neoadjuvant immunochemotherapy with the PD-L1 blocker durvalumab. We determined the power and accuracy in predicting pCR for the immunomodulatory (IM) subtype identified by the 101-gene model, the 27-gene IO signature, and PD-L1 expression by immunohistochemistry (IHC). The pCR rate was 45% (25/55). The odds ratios for pCR were as follows: IM subtype by 101-gene model, 3.14 (p = 0.054); 27-gene IO signature, 4.13 (p = 0.012); PD-L1 expression by IHC, 2.63 (p = 0.106); 27-gene IO signature in combination with PD-L1 expression by IHC, 6.53 (p = 0.003). The 27-gene IO signature has the potential to predict the pCR of primary TNBC to neoadjuvant immunochemotherapy. Further analysis in a large cohort is needed.
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