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pmid:37455914

Identification of SERPINA1 promoting better prognosis in papillary thyroid carcinoma along with Hashimoto's thyroiditis through WGCNA analysis.

Yihan Zhang · Xin Xie · Hong Zhou · Bingxin Li · Li Ding · Zhaogen Cai · Huaidong Song · Shuangxia Zhao · Huanbai Xu

Frontiers in endocrinology · 2023 doi:10.3389/fendo.2023.1131078

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:37455914
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science-record
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generator object · 2 fields
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paper object · 10 fields
state
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title
Identification of SERPINA1 promoting better prognosis in papillary thyroid carcinoma along with Hashimoto's thyroiditis through WGCNA analysis.
doi
10.3389/fendo.2023.1131078
pmid
37455914
authors array · 9 items
[0]
Yihan Zhang
[1]
Xin Xie
[2]
Hong Zhou
[3]
Bingxin Li
[4]
Li Ding
[5]
Zhaogen Cai
[6]
Huaidong Song
[7]
Shuangxia Zhao
[8]
Huanbai Xu
journal
Frontiers in endocrinology
year
2023
abstract
Background: Hashimoto's thyroiditis (HT) is an autoimmune thyroid disease. Papillary thyroid carcinoma (PTC) is the most common endocrine cancer. In recent years the rate of coexistence between PTC and HT has increased but the relationship between them remains unclear, meaning it is necessary to find potential biomarkers for PTC coexistence with HT to predict its potential pathways. Method: A co-expression network was constructed using the weighted gene co-expression network analysis (WGCNA) in the R package. The modules of PTC associated with HT (PTC-W) were identified from the GSE138198 dataset. Protein-protein interaction network (PPI) was used to screen the hub genes. Immunohistochemical (IHC) analysis was performed to validate the expression of the hub genes in tissues. Clinical data from The Cancer Genome Atlas (TCGA) datasets were used to analyse the prognosis of the hub genes. Gene set enrichment analysis (GSEA) was used to screen potential pathways of PTC-W. Result: The MEbrown module representing the most significant module, with 958 differentially expressed genes (DEGs), was screened in PTC-W, based on WGCNA analysis. Through PPI, SERPINA1 was identified as a hub gene. Immunostaining validated that SERPINA1 was highly expressed in PTC-W. Moreover, PTC-W expressing SERPINA1 exhibits a better prognosis than PTC without HT (PTC-WO). Conclusion: Our study demonstrates that SERPINA1 promotes the occurrence of PTC-W, and its prognosis is better than PTC-WO. SERPINA1 promotes a better prognosis for PTC-W, possibly through a tumour inhibition signalling pathway.
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sections[5] "Module and DEG identification based on weighted gene co-expression network analysis" paragraph 2
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A co-expression network was constructed using the WGCNA package from R.
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.
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The MEbrown module representing the most significant module, with 958 differentially expressed genes (DEGs), was screened in PTC-W, based on WGCNA analysis.
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The MEbrown module representing the most significant module, with 958 differentially expressed genes (DEGs), was screened in PTC-W, based on WGCNA analysis.
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The MEbrown module representing the most significant module, with 958 differentially expressed genes (DEGs), was screened in PTC-W, based on WGCNA analysis.
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title
Differentially expression profiling in Hashimoto's thyroiditis (HT), papillary thyroid carcinoma (PTC) with HT in background, PTC without HT in background, micro PTC (mPTC), and three normal thyroid samples (TN).
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work (PPI) was used to screen the hub genes. Immunohistochemical (IHC) analysis was performed to validate the
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PPI, SERPINA1 was identified as a hub gene. Immunostaining validated that SERPINA1 was highly expressed
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Complete file
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In recent years the rate of coexistence between PTC and HT has increased but the relationship between them remains unclear, meaning it is necessary to find potential biomarkers for PTC coexistence with HT to predict its potential pathways.\nMethod: A co-expression network was constructed using the weighted gene co-expression network analysis (WGCNA) in the R package. The modules of PTC associated with HT (PTC-W) were identified from the GSE138198 dataset. Protein-protein interaction network (PPI) was used to screen the hub genes. Immunohistochemical (IHC) analysis was performed to validate the expression of the hub genes in tissues. Clinical data from The Cancer Genome Atlas (TCGA) datasets were used to analyse the prognosis of the hub genes. Gene set enrichment analysis (GSEA) was used to screen potential pathways of PTC-W.\nResult: The MEbrown module representing the most significant module, with 958 differentially expressed genes (DEGs), was screened in PTC-W, based on WGCNA analysis. Through PPI, SERPINA1 was identified as a hub gene. Immunostaining validated that SERPINA1 was highly expressed in PTC-W. Moreover, PTC-W expressing SERPINA1 exhibits a better prognosis than PTC without HT (PTC-WO).\nConclusion: Our study demonstrates that SERPINA1 promotes the occurrence of PTC-W, and its prognosis is better than PTC-WO. 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