AUTHOR=Xia Minqi , Wang Shuo , Ye Yingchun , Tu Yi , Huang Tiantian , Gao Ling 

TITLE=Effect of the m6ARNA gene on the prognosis of thyroid cancer, immune infiltration, and promising immunotherapy

JOURNAL=Frontiers in Immunology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2022.995645

DOI=10.3389/fimmu.2022.995645

ISSN=1664-3224

ABSTRACT=Backgrounds: Accumulating evidence suggests that N6-methyladenosine (m6A) RNA methylation plays an important role in tumor proliferation and growth. However, its effect on clinical prognosis, immune infiltration, and immune checkpoint of thyroid cancer patients have not been investigated in detail.
Methods: Clinical data and RNA expression profiles of thyroid cancer were extracted from TCGA. By consensus clustering, we pre-processed the samples from TCGA-THCA. The risk model was constructed based on Differentially expressed genes (DEGs) using lasso and cox regression analysis. The associations between risk score and clinical traits, immune infiltration, biological processes (BP), cellular components (CC), molecular function (MF), pathways, outcomes, GSEA (Gene Set Enrichment Analysis), immune infiltration, and immune checkpoint were assessed. Immunohistochemistry was used to substantiate the clinical characteristics of our samples.
Results: Gene expression analysis showed that 17 genes, except YHTDF2, had significant differences (vs. health control, P <0.001). Consensus clustering yielded 2 clusters according to their clinical features and estimated a poorer prognosis for cluster 1 (p=0.03). Heat-map between 2 clusters showed differences in T (P <0.01), N (P <0.001) and stage (P <0.01). Based on univariate COX and Lasso regression, a risk model consisting of three high-risk genes (KIAA1429, RBM15, FTO) was established and the expression difference between cancer tissues and cancer adjacent tissues of three genes was confirmed by immunohistochemical results of our clinical samples. KEGG and GESA analysis showed that risk DEGs are mainly related to proteolysis, immune response, and cancer pathways. The levels of immune infiltration in the high /low-risk group were mainly different in iDCs（p<0.05）, NK cells （p<0.05）, and Type-INF-II (p<0.001). Immune checkpoints CD160 and CD28 were significantly different in the high-risk and low-risk groups (P<0.001).  
Conclusions: Our risk model can act as an independent marker for the malignancy of thyroid cancer and provides promising immunotherapy targets for its treatment.