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Expression and significance of PD-L1 in breast cancer tumor cells and tumor-infiltrating lymphocytes / 临床与实验病理学杂志
Chinese Journal of Clinical and Experimental Pathology ; (12): 63-67, 2017.
Article in Chinese | WPRIM | ID: wpr-513496
ABSTRACT
Purpose To investigate the expression of programmed death ligand-1 (PD-L1) in breast cancer tumor cells and stromal tumor-infiltrating lymphocyte (sTIL),and to study the relationship between the expression of PD-L1 and the clinicopathological characteristics of the patients.Method The protein expression of PD-L1 was detected by immunohistochemistry of EliVision two-step method in 68 cases of non special type of invasive breast cancer,and the relationship between the expression of PD-L1 protein and the immunohistochemistry subtypes and clinical parameters was analyzed.Results The total expression rate of PD-L1 was 35.3% in breast tumor tissue,specially in triple negative breast cancer (TNBC) which occupy the highest positive rate.The expression rates of PD-L1 in tumor tissue of the luminal subtype,HER-2 over-expression subtype and TNBC subtype were 16.1%,37.5% and 61.9% respectively,and the difference was statistically significant.The total expression rate of PD-L1 in sTIL was 51.5%,and the highest expression rate was 81.0% in TNBC.There were significant differences of PD-L1 expression in sTIL of the luminal subtype,HER-2 over-expression subtype and TNBC subtype.Expression of PD-L1 in tumor tissue and sTIL had a significant positive correlation.Conclusion PD-L1 expressed in TNBC was significantly higher than other types of breast cancer,which suggest the blocking of signal pathway of PD-1/PD-L1 may expected to become a new immunotherapy for breast cancer,especially for TNBC subtype.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Clinical and Experimental Pathology Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Clinical and Experimental Pathology Year: 2017 Type: Article