Abstract
ObjectivesThe study aims to analyze the expression of N6-methyladenosine (m6A)-modified genes in rectum adenocarcinoma (READ) and identify reliable prognostic biomarkers to predict the prognosis of READ.Materials and MethodsRNA sequence data of READ and corresponding clinical survival data were obtained from The Cancer Genome Atlas (TCGA) database. N6-methyladenosine (m6A)-modified genes in READ were downloaded from the “m6Avar” database. Differentially expressed m6A-modified genes in READ stratified by different clinicopathological characteristics were identified using the “limma” package in R. Protein-protein interaction (PPI) network and co-expression analysis of differentially expressed genes (DEGs) were performed using “STRING” and Cytoscape, respectively. Principal component analysis (PCA) was done using R. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to functionally annotate the differentially expressed genes in different subgroups. Univariate Cox regression analyses were conducted to identify the powerful independent prognostic factors in READ associated with overall survival (OS). A robust likelihood-based survival model was built using the “rbsurv” package to screen for survival-associated signature genes. The Support Vector Machine (SVM) was used to predict the prognosis of READ through the risk score of survival-associated signature genes. Correlation analysis were carried out using GraphPad prism 8.ResultsWe screened 974 differentially expressed m6A-modified genes among four types of READ samples. Two READ subgroups (group 1 and group 2) were identified by K means clustering according to the expression of DEGs. The two subgroups were significantly different in overall survival and pathological stages. Next, 118 differentially expressed genes between the two subgroups were screened and the expression of 112 genes was found to be related to the prognosis of READ. Next, a panel of 10 survival-associated signature genes including adamtsl1, csmd2, fam13c, fam184a, klhl4, olfml2b, pdzd4, sec14l5, setbp1, tmem132b was constructed. The signature performed very well for prognosis prediction, time-dependent receiver-operating characteristic (ROC) analysis displaying an area under the curve (AUC) of 0.863, 0.8721, and 0.8752 for 3-year survival rate, prognostic status, and pathological stage prediction, respectively. Correlation analysis showed that the expression levels of the 10 m6A-modified genes were positively correlated with that of m6A demethylase FTO and ALKBH5.ConclusionThis study identified potential m6A-modified genes that may be involved in the pathophysiology of READ and constructed a novel gene expression panel for READ risk stratification and prognosis prediction.
Highlights
Colorectal cancer (CRC) is one of the most common cancers and a major cause of cancer deaths worldwide
The expression pattern and the prognostic value of m6A-related genes in colorectal cancer has been previously assessed using bioinformatic methods, and the results revealed that the m6A-related genes were dysregulated in CRC suggesting that they might play a significant role in the progression of CRC [32, 33]
This data revealed that about 90% of m6A-modified genes were differentially expressed in rectum adenocarcinoma (READ)
Summary
Colorectal cancer (CRC) is one of the most common cancers and a major cause of cancer deaths worldwide. Rectal cancer accounts for about 30% to 35% of all CRC patients, of which most cases have rectum adenocarcinoma (READ) [2]. READ is defined as cancer between the dentate line and the junction of the rectosigmoid colon, easy to be diagnosed by digital rectal examination and sigmoidoscopy. The choice of an appropriate treatment strategy for the rectal cancer depends upon the pathological type, degree of differentiation, depth of tumor infiltration, the presence or absence of regional lymph node (LN) metastasis, and other factors that can predict the invasiveness and prognosis of a tumor [4]. A deep understanding of the pathological and molecular features of READ is important in predicting prognosis and formulating a clinical treatment plan
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