Seven Genes Associated With Lymphatic Metastasis in Thyroid Cancer That Is Linked to Tumor Immune Cell Infiltration

Abstract

ObjectiveSince there are few studies exploring genes associated with lymphatic metastasis of thyroid carcinoma (THCA), this study was conducted to explore genes associated with lymphatic metastasis of THCA and to investigate the relationship with immune infiltration.MethodsDifferentially expressed genes associated with THCA lymphatic metastasis were analyzed based on The Cancer Genome Atlas Program (TCGA) database; a protein-protein interaction(PPI)network was constructed to screen for pivotal genes. Based on the identified hub genes, their expression in THCA with and without lymphatic metastasis were determined. Functional enrichment analysis was performed. The correlation between the identified genes and immune cell infiltration was explored. LASSO logistic regression analysis was performed to determine the risk score of the most relevant gene constructs and multifactor COX regression analysis based on genes in the risk score formula.ResultsA total of 115 genes were differentially expressed in THCA with and without lymphatic metastasis, including 28 upregulated genes and 87 downregulated genes. The PPI network identified seven hub genes (EVA1A, TIMP1, SERPINA1, FAM20A, FN1, TNC, MXRA8); the expression of all seven genes was upregulated in the group with lymphatic metastasis; Immuno-infiltration analysis showed that all seven genes were significantly positively correlated with macrophage M1 and NK cells and negatively correlated with T-cell CD4+ and myeloid dendritic cells. LASSO logistic regression analysis identified the five most relevant genes (EVA1A, SERPINA1, FN1, TNC, MXRA8), and multi-factor COX regression analysis showed EVA1A, SERPINA1 and FN1 as independent prognostic factors.ConclusionSeven genes were associated with lymphatic metastasis of THCA and with tumor immune cell infiltration.

Screening of ulcerative colitis biomarkers and potential pathways based on weighted gene co-expression network, machine learning and ceRNA hypothesis

“…This may be related to the fact that TIMP 1 antagonizes the overexpression of MMPs in UC and inhibits the involvement of MMPs in the shaping of the inflammatory microenvironment in UC [ 52 ]. In terms of immune cells, Wu believes that TIMP1 is a key gene involved in the infiltration of immune cells in thyroid cancer lymphatic metastasis [ 53 ]. TIMP1 potently inhibits the polarization of NK cells toward a decidual-like phenotype [ 54 ] and increases hepatic neutrophil infiltration [ 55 ].…”

Bioinformatics Analysis of Inflammation Gene Signature in Indicating Cholangiocarcinoma Prognosis

“…CCL2, also known as the inflammation-associated expression signature, was mostly derived from cancer-associated fibroblasts, which were components of the cholangiocarcinoma tumor microenvironment. [ 16 , 17 ] Its risk score in the total population was significantly related to OS (HR = 3.144, 95% CI = 1.908–5.178, P < 0.001). Multivariate Cox analysis demonstrated that the risk score remained an independent predictor of OS after controlling for additional confounding variables (HR = 2.792, 95% CI = 1.651–4.721, P < 0.001).…”

ERBB2 as a prognostic biomarker correlates with immune infiltrates in papillary thyroid cancer

“…In our study, the expression of ERBB2 was found to be positively correlated with VEGF-associated genes of VEGFA , FLT , KDR , and FLT4 ( Shibuya, 2011 ), vascular endothelial cell markers of PECAM1 and VWF ( Bauer et al, 2015 ), and vascular support-related genes of TEK , ANGPT1 , ANGPT2 , CDH5 , CLDN5 , and JAM2 ( Oshi et al, 2021 ). Furthermore, the expression of ERBB2 was positively correlated with lymph node metastatic signature genes such as EVA1A , TIMP1 , SERPINA1 , FAM20A , FN1 , TNC , and MXRA8 ( Wu et al, 2021 ), and distant metastatic signature genes of MMP2 , PTTG1 , VEGFC , CXCR4 , and FGF2 ( Liang et al, 2011 ). Besides, ERBB2 expression was also positively correlated with proliferation-related genes, such as MKI67 , PCNA , and MCM2 ( Juríková et al, 2016 ).…”

“…Co-expression heat map assesses the correlation between the expression of ERBB2 and gene sets, including the iodine metabolism-related gene set of TSHR , SLC5A8 , SLC26A4 , and TPO ( Portulano et al, 2013 ), the tumor angiogenesis gene set of VEGFA , FLT1 , KDR , FLT4 , PECAM1 , VWF , TIE1 , TEK , ANGPT1 , ANGPT2 , CDH5 , and CLDN5 ( Smith et al, 2010 ; Haibe et al, 2020 ), Lymph node metastasis gene set of EVA1A , TIMP1 , SERPINA1 , FAM20A , FN1 , TNC , and MXRA8 ( Wu et al, 2021 ), distant metastatic gene sets of MMP2 , PTTG1 , VEGFC , CXCR4 , and FGF2 , tumor cell proliferation set of MKI67 , PCNA , and MCM2 ) ( Liang et al, 2011 ), and MEKi resistance marker gene set of SPRY2 , SPRY4 , ETV4 , ETV5 , DUSP4 , DUSP6 , CCND1 , EPHA2 , and EPHA4 ( Mazzoni et al, 2019 ; Degirmenci et al, 2021 ).…”