Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapy

Glucose metabolism-related genes play an important role in the development and immunotherapy of many tumours, but their role in thyroid cancer is ambiguous. To investigate the role of glucose metabolism-related genes in the development of papillary thyroid cancer (PTC) and their correlation with the...

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Main Authors: Wenjun Xie, Yu Zeng, Linfei Hu, Jiaru Hao, Yuzheng Chen, Xinwei Yun, Qiang Lin, Huashui Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Immunology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2022.991656/full
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author Wenjun Xie
Wenjun Xie
Wenjun Xie
Yu Zeng
Linfei Hu
Jiaru Hao
Yuzheng Chen
Yuzheng Chen
Xinwei Yun
Qiang Lin
Qiang Lin
Huashui Li
Huashui Li
author_facet Wenjun Xie
Wenjun Xie
Wenjun Xie
Yu Zeng
Linfei Hu
Jiaru Hao
Yuzheng Chen
Yuzheng Chen
Xinwei Yun
Qiang Lin
Qiang Lin
Huashui Li
Huashui Li
author_sort Wenjun Xie
collection DOAJ
description Glucose metabolism-related genes play an important role in the development and immunotherapy of many tumours, but their role in thyroid cancer is ambiguous. To investigate the role of glucose metabolism-related genes in the development of papillary thyroid cancer (PTC) and their correlation with the clinical outcome of PTC, we collected transcriptomic data from 501 PTC patients in the Cancer Genome Atlas (TCGA). We performed nonnegative matrix decomposition clustering of 2752 glucose metabolism-related genes from transcriptome data and classified PTC patients into three subgroups (C1 for high activation of glucose metabolism, C2 for low activation of glucose metabolism and C3 for moderate activation of glucose metabolism) based on the activation of different glucose metabolism-related genes in 10 glucose metabolism-related pathways. We found a positive correlation between the activation level of glucose metabolism and the tumour mutation burden (TMB), neoantigen number, mRNA stemness index (mRNAsi), age, and tumour stage in PTC patients. Next, we constructed a prognostic prediction model for PTC using six glucose metabolism-related genes (PGBD5, TPO, IGFBPL1, TMEM171, SOD3, TDRD9) and constructed a nomogram based on the risk score and clinical parameters of PTC patients. Both the prognostic risk prediction model and nomogram had high stability and accuracy for predicting the progression-free interval (PFI) in PTC patients. Patients were then divided into high-risk and low-risk groups by risk score. The high-risk group was sensitive to paclitaxel and anti-PD-1 treatment, and the low-risk group was sensitive to sorafenib treatment. We found that the high-risk group was enriched in inflammatory response pathways and associated with high level of immune cell infiltration. To verify the accuracy of the prognostic prediction model, we knocked down PGBD5 in PTC cells and found that the proliferation ability of PTC cells was significantly reduced. This suggests that PGBD5 may be a relatively important oncogene in PTC. Our study constructed a prognostic prediction model and classification of PTC by glucose metabolism-related genes, which provides a new perspective on the role of glucose metabolism in the development and immune microenvironment of PTC and in guiding chemotherapy, targeted therapy and immune checkpoint blockade therapy of PTC.
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spelling doaj.art-4d8c4f8b449c402e835a376e683160482022-12-22T04:27:04ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-09-011310.3389/fimmu.2022.991656991656Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapyWenjun Xie0Wenjun Xie1Wenjun Xie2Yu Zeng3Linfei Hu4Jiaru Hao5Yuzheng Chen6Yuzheng Chen7Xinwei Yun8Qiang Lin9Qiang Lin10Huashui Li11Huashui Li12Department of General Surgery, Shengli Clinical Medical College, Fujian Provincial Hospital, Fuzhou, ChinaShengli Clinical Medical College, Fujian Medical University, Fuzhou, ChinaDepartment of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, ChinaDepartment of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, ChinaDepartment of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, ChinaDepartment of Gastrointestinal Cancer Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Immunology and Biotherapy, Tianjin, ChinaShengli Clinical Medical College, Fujian Medical University, Fuzhou, ChinaDepartment of Endocrinology, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, ChinaDepartment of Thyroid and Neck Tumor, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Tianjin, ChinaDepartment of General Surgery, Shengli Clinical Medical College, Fujian Provincial Hospital, Fuzhou, ChinaShengli Clinical Medical College, Fujian Medical University, Fuzhou, ChinaDepartment of General Surgery, Shengli Clinical Medical College, Fujian Provincial Hospital, Fuzhou, ChinaShengli Clinical Medical College, Fujian Medical University, Fuzhou, ChinaGlucose metabolism-related genes play an important role in the development and immunotherapy of many tumours, but their role in thyroid cancer is ambiguous. To investigate the role of glucose metabolism-related genes in the development of papillary thyroid cancer (PTC) and their correlation with the clinical outcome of PTC, we collected transcriptomic data from 501 PTC patients in the Cancer Genome Atlas (TCGA). We performed nonnegative matrix decomposition clustering of 2752 glucose metabolism-related genes from transcriptome data and classified PTC patients into three subgroups (C1 for high activation of glucose metabolism, C2 for low activation of glucose metabolism and C3 for moderate activation of glucose metabolism) based on the activation of different glucose metabolism-related genes in 10 glucose metabolism-related pathways. We found a positive correlation between the activation level of glucose metabolism and the tumour mutation burden (TMB), neoantigen number, mRNA stemness index (mRNAsi), age, and tumour stage in PTC patients. Next, we constructed a prognostic prediction model for PTC using six glucose metabolism-related genes (PGBD5, TPO, IGFBPL1, TMEM171, SOD3, TDRD9) and constructed a nomogram based on the risk score and clinical parameters of PTC patients. Both the prognostic risk prediction model and nomogram had high stability and accuracy for predicting the progression-free interval (PFI) in PTC patients. Patients were then divided into high-risk and low-risk groups by risk score. The high-risk group was sensitive to paclitaxel and anti-PD-1 treatment, and the low-risk group was sensitive to sorafenib treatment. We found that the high-risk group was enriched in inflammatory response pathways and associated with high level of immune cell infiltration. To verify the accuracy of the prognostic prediction model, we knocked down PGBD5 in PTC cells and found that the proliferation ability of PTC cells was significantly reduced. This suggests that PGBD5 may be a relatively important oncogene in PTC. Our study constructed a prognostic prediction model and classification of PTC by glucose metabolism-related genes, which provides a new perspective on the role of glucose metabolism in the development and immune microenvironment of PTC and in guiding chemotherapy, targeted therapy and immune checkpoint blockade therapy of PTC.https://www.frontiersin.org/articles/10.3389/fimmu.2022.991656/fullmetabolic genespapillary thyroid cancer classificationimmune signaturesprognosisPD-1PGBD5
spellingShingle Wenjun Xie
Wenjun Xie
Wenjun Xie
Yu Zeng
Linfei Hu
Jiaru Hao
Yuzheng Chen
Yuzheng Chen
Xinwei Yun
Qiang Lin
Qiang Lin
Huashui Li
Huashui Li
Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapy
Frontiers in Immunology
metabolic genes
papillary thyroid cancer classification
immune signatures
prognosis
PD-1
PGBD5
title Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapy
title_full Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapy
title_fullStr Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapy
title_full_unstemmed Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapy
title_short Based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti-PD-1 therapy
title_sort based on different immune responses under the glucose metabolizing type of papillary thyroid cancer and the response to anti pd 1 therapy
topic metabolic genes
papillary thyroid cancer classification
immune signatures
prognosis
PD-1
PGBD5
url https://www.frontiersin.org/articles/10.3389/fimmu.2022.991656/full
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