Literature DB >> 35043231

Prognostic value, DNA variation and immunologic features of a tertiary lymphoid structure-related chemokine signature in clear cell renal cell carcinoma.

Chunguang Ma1, Wangrui Liu2, Aihetaimujiang Anwaier1, Wenhao Xu1, Xi Tian1, Guohai Shi1, Yuanyuan Qu3, Shiyin Wei4, Hailiang Zhang5, Dingwei Ye6.   

Abstract

BACKGROUND: The tumor microenvironment (TME) and tertiary lymphoid structures (TLS) affect the occurrence and development of cancers. How the immune contexture interacts with the phenotype of clear cell renal cell carcinoma (ccRCC) remains unclear.
METHODS: We identified and evaluated TLS clusters in ccRCC using machine learning algorithms and the 12-chemokine gene signature for TLS. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features and predictive value of CXCL13 in ccRCC were performed.
RESULTS: We found a prominently enrichment of the 12-chemokine gene signature for TLS in patients with ccRCC compared with other types of renal cell carcinoma. We identified a prognostic value of CCL4, CCL5, CCL8, CCL19 and CXCL13 expression in ccRCC. DNA deletion of the TLS gene signature significantly predicted poor outcome in ccRCC compared with amplification and wild-type gene signature. We established TLS clusters (C1-4) and observed distinct differences in survival, stem cell-like characteristics, immune cell distribution, response to immunotherapies and VEGF-targeted therapies among the clusters. We found that elevated CXCL13 expression significantly predicted aggressive progression and poor prognosis in 232 patients with ccRCC in a real-world validation cohort.
CONCLUSION: This study described a 12-chemokine gene signature for TLS in ccRCC and established TLS clusters that reflected different TME immune status and corresponded to prognosis of ccRCC. We confirmed the dense presence of TILs aggregation and TLS in ccRCC and demonstrated an oncogenic role of CXCL13 expression of ccRCC, which help develop immunotherapies and provide novel insights on the long-term management of ccRCC.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  CXCL13; Clear cell renal cell carcinoma; Machine learning algorithm; Prognosis; Tertiary lymphoid structures; Tumor microenvironment

Mesh:

Substances:

Year:  2022        PMID: 35043231     DOI: 10.1007/s00262-021-03123-y

Source DB:  PubMed          Journal:  Cancer Immunol Immunother        ISSN: 0340-7004            Impact factor:   6.630


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