ABSTRACT
BACKGROUND: Recently, many studies have been conducted to examine immune response modification at epigenetic level, but the candidate effect of RNA 5-methylcytosine (m5 C) modification on tumor microenvironment (TME) of acute myeloid leukemia (AML) is still unknown at present. METHODS: We assessed the patterns of m5 C modification among 417 AML cases by using nine m5 C regulators. Thereafter, we associated those identified modification patterns with TME cell infiltration features. Additionally, stepwise regression and LASSO Cox regression analyses were conducted for quantifying patterns of m5 C modification among AML cases to establish the m5 C-score. Meanwhile, we validated the expression of genes in the m5C-score model by qRT-PCR. Finally, the present work analyzed the association between m5 C-score and AML clinical characteristics and prognostic outcomes. RESULTS: In total, three different patterns of m5 C modification (m5 C-clusters) were identified, and highly differentiated TME cell infiltration features were also identified. On this basis, evaluating patterns of m5 C modification in single cancer samples was important for evaluating the immune/stromal activities in TME and for predicting prognosis. In addition, the m5 C-score was established, which showed a close relation with the overall survival (OS) of test and training set samples. Moreover, multivariate Cox analysis suggested that our constructed m5 C-score served as the independent predicting factor for the prognosis of AML (hazard ratio = 1.57, 95% confidence interval = 1.38-1.79, p < 1e-5 ). CONCLUSIONS: This study shows that m5 C modification may be one of the key roles in the formation of diversity and complexity of TME. Meanwhile, assessing the patterns of m5 C modification among individual cancer samples is of great importance, which provides insights into cell infiltration features within TME, thereby helping to develop relevant immunotherapy and predict patient prognostic outcomes.
Subject(s)
Leukemia, Myeloid, Acute , Tumor Microenvironment , Humans , Tumor Microenvironment/genetics , Leukemia, Myeloid, Acute/genetics , RNA , Cell Differentiation , MethylationABSTRACT
BACKGROUND: Currently, acute myelocytic leukemia (AML) still has a poor prognosis. As a result, gene markers for predicting AML prognosis must be identified through systemic analysis of multi-omics data. METHODS: First of all, the copy number variation (CNV), mutation, RNA-Seq, and single nucleotide polymorphism (SNP) data, as well as those clinical follow-up data, were obtained based on The Cancer Genome Atlas (TCGA) database. Thereafter, all samples (n = 229) were randomized as test set and training set, respectively. Of them, the training set was used to screen for genes related to prognosis, and genes with mutation, SNP or CNV. Then, shrinkage estimate was used for feature selection of all the as-screened genes, to select those stable biomarkers. Eventually, a prognosis model related to those genes was established, and validated within the GEO verification (n = 124 and 72) and test set (n = 127). Moreover, it was compared with the AML prognosis prediction model reported in literature. RESULTS: Altogether 832 genes related to prognosis, 23 related to copy amplification, 774 associated with copy deletion, and 189 with significant genomic variations were acquired in this study. Later, genes with genomic variations and those related to prognosis were integrated to obtain 38 candidate genes; eventually, a shrinkage estimate was adopted to obtain 10 feature genes (including FAT2, CAMK2A, TCERG1, GDF9, PTGIS, DOC2B, DNTTIP1, PREX1, CRISPLD1 and C22orf42). Further, a signature was established using these 10 genes based on Cox regression analysis, and it served as an independent factor to predict AML prognosis. More importantly, it was able to stratify those external verification, test and training set samples with regard to the risk (P < 0.01). Compared with the prognosis prediction model reported in literature, the model established in this study was advantageous in terms of the prediction performance. CONCLUSION: The signature based on 10 genes had been established in this study, which is promising to be used to be a new marker for predicting AML prognosis.
ABSTRACT
The aim of this study was to determine the association of the microRNA-146a (miR-146a) polymorphism with the risk of diffuse large B cell lymphoma (DLBCL). The genotyping of miR-146a rs2910164 polymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). The results showed that CC genotype and C alleles distribution in the DLBCL patient was significantly higher than that of the controls (p = 0.01 and p = 0.01, respectively). No significant differences were found between the two subgroups when stratified by clinical characteristics including sexual, age at admission, performance status, pathological type, Ann Arbor stage, LDH and ß2-MG value. The miR-146a expression was detected by the Taqman real-time PCR. The result showed that the miR-146a expression was notably upregulated in DLBCL patients when compared with controls (p = 0.02). In addition, the miR-146a expression of CC genotypes subgroup was drastically downregulated than that of GC/GG genotype subgroup in DLBCL patients (p = 0.0003), suggesting that this polymorphism can functionally affect the expression of miR-146a. In conclusion, it was shown that the miR-146a rs2910164 polymorphism is associated with the risk of DLBCL in the Chinese Han population.
