The gene signature of tertiary lymphoid structures within ovarian cancer predicts the prognosis and immunotherapy benefit

Autor: Yue Hou, Sijing Qiao, Miao Li, Xue Han, Xuan Wei, Yingxin Pang, Hongluan Mao
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Frontiers in Genetics, Vol 13 (2023)
Druh dokumentu: article
ISSN: 1664-8021
DOI: 10.3389/fgene.2022.1090640
Popis: Ovarian cancer (OC) has the lowest survival rate among gynecologic malignancies. Ectopic lymphocyte aggregates, namely tertiary lymphoid structures (TLSs), have been reported as positive biomarkers for tumor prognosis. However, the related gene signature of tertiary lymphoid structure in ovarian cancer was less understood. Therefore, this study first exhibited the organizational patterns of tertiary lymphoid structure by H&E staining and immunohistochemistry (IHC), and confirmed the improved survival values of tertiary lymphoid structure and quantified tumor-infiltrating lymphocytes (CD20+ B cells and CD8+ T cells) in ovarian cancer patients. Secondly, we collected the genes involved in tertiary lymphoid structure from databases. By the univariate regression analysis, the tertiary lymphoid structure gene signature (CETP, CCR7, SELL, LAMP3, CCL19, CXCL9, CXCL10, CXCL11, and CXCL13) with prognostic value, characteristically of ovarian cancer, was constructed in the TCGA dataset and validated in the GSE140082 dataset. Thirdly, by performing CIBERSORT and Tumor Immune Dysfunction and Exclusion (TIDE) analysis, we found that the high expression of this gene signature was positively correlated with developed immune infiltration and reduced immune escape. The improved IPS score and application in the IMvigor210 dataset received PD-L1 proved the predictive value of immunotherapy for this gene signature. Furthermore, this signature showed a better correlation between tumor mutation burden and classical checkpoint genes. In conclusion, Tertiary lymphoid structure plays important role in tumor immunity and the gene signature can be evaluated as a biomarker for predicting prognosis and guiding immunotherapy in ovarian cancer.
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