AUTHOR=Jiang Linlin , Wang Peng , Su Mu , Yang Lili , Wang Qingbo 

TITLE=Identification of mRNA Signature for Predicting Prognosis Risk of Rectal Adenocarcinoma

JOURNAL=Frontiers in Genetics

VOLUME=13

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.880945

DOI=10.3389/fgene.2022.880945

ISSN=1664-8021

ABSTRACT=<p><bold>Background:</bold> The immune system plays a crucial role in rectal adenocarcinoma (READ). Immune-related genes may help predict READ prognoses.</p><p><bold>Methods:</bold> The Cancer Genome Atlas dataset and GSE56699 were used as the training and validation datasets, respectively, and differentially expressed genes (DEGs) were identified. The optimal DEG combination was determined, and the prognostic risk model was constructed. The correlation between optimal DEGs and immune infiltrating cells was evaluated.</p><p><bold>Results:</bold> Nine DEGs were selected for analysis. Moreover, <italic>ADAMDEC1</italic> showed a positive correlation with six immune infiltrates, most notably with B cells and dendritic cells. <italic>F13A1</italic> was also positively correlated with six immune infiltrates, particularly macrophage and dendritic cells, whereas <italic>LGALS9C</italic> was negatively correlated with all immune infiltrates except B cells. Additionally, the prognostic risk model was strongly correlated with the actual situation. We retained only three prognosis risk factors: age, pathologic stage, and prognostic risk model. The stratified analysis revealed that lower ages and pathologic stages have a better prognosis with READ. Age and mRNA prognostic factors were the most important factors in determining the possibility of 3- and 5-year survival.</p><p><bold>Conclusion:</bold> In summary, we identified a nine-gene prognosis risk model that is applicable to the treatment of READ. Altogether, characteristics such as the gene signature and age have a strong predictive value for prognosis risk.</p>