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Published in: Pathology & Oncology Research 3/2020

01-07-2020 | Checkpoint Inhibitors | Original Article

Unraveling LGALS1 as a Potential Immune Checkpoint and a Predictor of the Response to Anti-PD1 Therapy in Clear Cell Renal Carcinoma

Authors: Yan Li, Shouyan Yang, Honggang Yue, Dandi Yuan, Luxia Li, Jinghong Zhao, Lintao Zhao

Published in: Pathology & Oncology Research | Issue 3/2020

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Abstract

Immunotherapy base on immune checkpoint inhibitor had obtained significant progress in extending the survival of clear cell renal carcinoma (ccRCC) patients. In order to further improve the efficiency of immunotherapy, novel immune checkpoint inhibitors needed to be developed. Differentially expressed genes (DEGs) between healthy kidney tissues and ccRCC tissues had been found from GSE68417 by GEO2R online analysis tool. Correlation analysis and Kaplan–Meier survival analyses were based on UALCAN database. Analyses of the outcome of anti-PD1 treatment had been found from GSE67501 dataset. At first, 9 genes with higher expression were associated with shorter overall survival time. More importantly, higher expression of LGALS1 was correlated with a profitable outcome of anti-PD1 treatment and the combined the expression level of PD-L1 and LGALS1 together could more efficiently predict the outcome of anti-PD1 treatment than using PD-L1 alone. At last, the genes which correlated with LGALS1 expression in ccRCC patients were enriched in TNF alpha Signaling Pathway which is mainly correlated with T cell apoptosis and survival. Together, these suggest LGALS1 could be a potential immune checkpoint, which could promote tumor progression through affecting T cell survival.
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Metadata
Title
Unraveling LGALS1 as a Potential Immune Checkpoint and a Predictor of the Response to Anti-PD1 Therapy in Clear Cell Renal Carcinoma
Authors
Yan Li
Shouyan Yang
Honggang Yue
Dandi Yuan
Luxia Li
Jinghong Zhao
Lintao Zhao
Publication date
01-07-2020
Publisher
Springer Netherlands
Published in
Pathology & Oncology Research / Issue 3/2020
Print ISSN: 1219-4956
Electronic ISSN: 1532-2807
DOI
https://doi.org/10.1007/s12253-019-00710-4

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