Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer

Zhao, Xiaojuan; Liu, Jianzhong; Liu, Shuzhen; Yang, Fangfang; Chen, Erfei

doi:10.3390/cancers11111722

Cited by 20 publications

(19 citation statements)

References 37 publications

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“…Subsequently, the risk signature using three genes (GF2BP1 + IGF2BP2 + METTL3) was shown to be an independent prognostic marker of NPC. Accumulating studies showed that the tumor immune microenvironment plays a vital role in the progression and prognosis of various cancers (35). NPC is characterized as a highly immunogenic tumor characterized by high rates of tumorinfiltrating lymphocytes (TILs) (36,37).…”

Section: Discussionmentioning

confidence: 99%

Gene Signatures and Prognostic Values of m6A Genes in Nasopharyngeal Carcinoma

Xiao

et al. 2020

Front. Oncol.

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Nasopharyngeal carcinoma (NPC) is a malignant tumor with a high rate of local invasion and early distant metastasis. Accumulating studies suggest that N6-methyladenosine methylation (m 6 A) is closely related to tumorigenesis. However, the relationship between m 6 A-related genes and prognosis of NPC is poorly understood. Our research aims to discover the prognostic value of m 6 A RNA methylation genes in NPC. In this study, we analyzed the differentially expressed m 6 A-related genes between NPC samples and normal control samples and found that two upregulated genes (YTHDF3 and IGF2BP2) and one downregulated gene (METTL3) were overlapped in GSE68799 and GSE53819. Next, we found that high expression of IGF2BP1 and low expression of METTL3 and YTHDF3 in NPC patients showed poor progression-free survival (PFS). Subsequently, the four m 6 A genes were selected for consensus cluster analysis, and risk models were established. The risk signature, using three genes (GF2BP1 + IGF2BP2 + METTL3), was an independent prognostic factor and predicts the clinicopathological features of NPC. Additionally, the GO, KEGG analysis, and CIBERSORT algorithm revealed that the risk signature was closely associated to immune infiltration in NPC. Finally, the expression and clinical significance of METTL3 were successfully validated in NPC tissues using immunohistochemical techniques. In conclusion, our finding revealed the potential role of m 6 A modification in NPC, providing novel insight into NPC prognosis and therapeutic strategies.

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Section: Discussionmentioning

confidence: 99%

Gene Signatures and Prognostic Values of m6A Genes in Nasopharyngeal Carcinoma

Xiao

et al. 2020

Front. Oncol.

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“…FASLG (Fas ligand), a core gene involved in lymphocyte apoptosis and Tcell development, was down-regulated, which meant partial loss of self-regulation in tumor immunity. In recent years, various immunoscore models, based on TILs' proportion, ratio of immune cells, and expression of prognostic genes, have been developed and verified to assess prognosis (51)(52)(53). Though current studies showed relatively good probability of prognostic assessment in part, they focus on the overall distribution of immune cells and total gene expression difference between samples.…”

Section: Discussionmentioning

confidence: 99%

Evaluating Distribution and Prognostic Value of New Tumor-Infiltrating Lymphocytes in HCC Based on a scRNA-Seq Study With CIBERSORTx

Shen

Zhou

et al. 2020

Front. Med.

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Hepatocellular carcinoma (HCC) is a commonly diagnosed cancer with high mortality rates. The immune response plays an important role in the progression of HCC. Immunotherapies are becoming an increasingly promising tool for treating cancers. Advancements in scRNA-seq (single-cell RNA sequencing) have allowed us to identify new subsets in the immune microenvironment of HCC. Yet, distribution of these new cell types and their potential prognostic value in bulk samples from large cohorts remained unclear. This study aimed to investigate the tumor-infiltration and prognostic value of new cell subsets identified by a previous scRNA-seq study in a TCGA HCC cohort using CIBERSORTx, a machine learning method to estimate cell proportion and infer cell-type-specific gene expression profiles. We observed different distributions of tumor-infiltrating lymphocytes between tumor and normal cells. Among these, the CD4-GZMA cell subset showed association with prognosis (log-rank test, p < 0.05). We further analyzed CD4-GZMA cell specific gene expression with CIBERSORTx, and found 19 prognostic genes (univariable cox regression, p < 0.05). Finally, we applied Least absolute shrinkage and selection operator (LASSO) Cox regression to construct an immune risk score model and performed a prognostic assessment of our model in TCGA and ICGC cohorts. Taken together, the immune landscape in HCC bulk samples may be more complex than assumed, with heterogeneity and different tumor-infiltration relative to scRNA-seq results. Additionally, CD4-GZMA cells and their characteristics may yield therapeutic benefits in the immune treatment of HCC.

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“…The cBio Cancer Genomics database (https://www.cbioportal.org/) was used to investigate the genetic alteration information of 13 m 6 A methylation regulators [20]. Univariate Cox regression analysis was performed to exp lore the relationships between the expression of m 6 A RNA methylation regulators and patients' survival [21]. Then, these 13 m 6 A methylation regulators were entered into a LASSO regression analysis [15].…”

Section: Construction Of Prognostic Gene Signaturementioning

confidence: 99%

Identification and validation of a novel prognostic index based on m6A RNA methylation regulators in esophageal carcinoma

Yang¹,

Duan²,

Zhao³

et al. 2020

Preprint

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Background The incidence and mortality rate of esophageal carcinoma (ESCA) remains high. This study proposed to explore the promising prognostic markers based on m6A RNA methylation regulators, and finally to improve the prognostic assessment for ESCA patients. Methods The RNA sequencing and relevant clinical data of ESCA and normal tissues were obtained from The Cancer Genome Atlas (TCGA) database. Then, we evaluated the expression pattern of 13 m6A methylation regulators in ESCA and normal samples. Two groups of ESCA were divided by the consensus clustering analysis. STRING database and R package were used to construct the protein-protein interaction network and conduct correlation analysis, respectively. Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to develop the multiple-gene risk signature. Kaplan-Meier method and receiver operating characteristic (ROC) curves were used to assess the accuracy of the model. The clinical nomogram combining clinicpathological factors and gene signature was built to predict survival rate of ESCA patients. Gene set enrichment analysis (GSEA) and networks prediction analysis were conducted to explore the signaling pathways that related to the risk genes. Results Eight m6A methylation regulators (HNRNPC, YTHDF1, METTL3, YTHDF2, WTAP, YTHDC1, KIAA1429, and RBM15) were significantly upregulated in ESCA. Two clusters of ESCA with obvious differences in tumor stage were identified via the consensus clustering analysis. A two-gene signature, ALKBH5 and HNRNPC, was established for predicting the prognosis of ESCA patients. Kaplan-Meier curves illustrated that the overall survival of patients in low-risk group was obviously longer than that of patients in high-risk group (P = 1.411e-02). Importantly, risk score and tumor stage were identified as the independent prognostic indicators. The testing dataset GSE13898 showed that the nomogram had a good capacity to assess the prognosis of ESCA patients. Cell cycle, mTOR pathway, and p53 signaling pathway were found to be related to the dysregulation of risk genes. Conclusions m6A RNA methylation regulators ALKBH5 and HNRNPC could act as prognostic indicators and therapeutic targets for prognostic analysis and cancer treatment of ESCA.

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Construction and Validation of an Immune-Related Prognostic Model Based on TP53 Status in Colorectal Cancer

Cited by 20 publications

References 37 publications

Gene Signatures and Prognostic Values of m6A Genes in Nasopharyngeal Carcinoma

Gene Signatures and Prognostic Values of m6A Genes in Nasopharyngeal Carcinoma

Evaluating Distribution and Prognostic Value of New Tumor-Infiltrating Lymphocytes in HCC Based on a scRNA-Seq Study With CIBERSORTx

Identification and validation of a novel prognostic index based on m6A RNA methylation regulators in esophageal carcinoma

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