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Prognostic value of the association between MHC class I downregulation and PD-L1 upregulation in head and neck squamous cell carcinoma patients

Cited 34 time in Web of Science Cited 36 time in Scopus
Authors

Yoo, Shin Hye; Keam, Bhumsuk; Ock, Chan-Young; Kim, Sehui; Han, Buhm; Kim, Ji-Won; Lee, Keun-Wook; Jeon, Yoon Kyung; Jung, Kyeong Cheon; Chung, Eun-Jae; Kwon, Seong Keun; Ahn, Soon-Hyun; Sung, Myung-Whun; Heo, Dae Seog

Issue Date
2019-05-22
Publisher
Nature Publishing Group
Citation
Scientific Reports, Vol.9 No.1, p. 7680
Abstract
The purpose of this study was to evaluate the prognostic impact of major histocompatibility complex (MHC) class I expression and programmed death-ligand 1 (PD-L1) expression in patients with head and neck squamous cell carcinoma (HNSCC). A total of 158 patients with HNSCC were evaluated retrospectively. The expression of MHC class I and PD-L1 was analyzed in tumor specimens using immunohistochemistry. The association between MHC class I/PD-L1 expression and clinical outcome was evaluated by Kaplan-Meier and Cox regression analyses. Among 158 patients, 103 (65.2%) showed positive PD-L1 expression, and 20 (12.7%) showed no detectable expression of MHC class I. The frequency of PD-L1 positive expression with concomitant MHC class I loss was 7.0%. In the PD-L1-positive group, MHC class I loss was associated with a significantly worse survival compared with MHC class I positivity (median overall survival 39.3 months vs. not reached; P= 0.005), whereas MHC class I status provided no prognostic impact in the PD-L1 negative group. Neither PD-L1 nor MHC class I alone showed a significant difference in overall survival. The loss of MHC class I expression in PD-L1-positive HNSCC was associated with a poor clinical outcome. This suggested that MHC class I expression status might be useful for the prognosis of tumor progression in HNSCC when combined with PD-L1 expression status. External validation with enough numbers of participants in such subgroup should be needed for validation.
ISSN
2045-2322
URI
https://hdl.handle.net/10371/191504
DOI
https://doi.org/10.1038/s41598-019-44206-2
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  • College of Medicine
  • Department of Medicine
Research Area Bioinformatics, Computational Biology, Genomics, Human Leukocyte Antigen, Statistical Genetics

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