Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma

Tong, Yalin; Peng, Mengle; Li, Jinbei; Niu, Yingjie

doi:10.1155/2022/4235305

Cited by 4 publications

(5 citation statements)

References 54 publications

(48 reference statements)

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“…Moreover, the TME related signatures analysis revealed that CD8 T cell effector and immune checkpoint associated pathway genes were higher in the low‐risk group than in the high‐risk group (Figure 5C). Previous studies revealed that colon adenocarcinoma patients with a higher immune score and more infiltration of antitumor immune cells have a better survival outcome 17–19 . Therefore, we speculated that the better prognosis of the low‐risk group might be related to the more favorable antitumor immune microenvironment.…”

Section: Resultsmentioning

confidence: 90%

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Novel prognostic model predicts overall survival in colon cancer based on RNA splicing regulation gene expression

Luo

Chen

et al. 2022

Cancer Science

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Colon cancer is the third most common cancer and the second leading cause of cancer‐related death worldwide. Dysregulated RNA splicing factors have been reported to be associated with tumorigenesis and development in colon cancer. In this study, we interrogated clinical and RNA expression data of colon cancer patients from The Cancer Genome Atlas (TCGA) dataset and the Gene Expression Omnibus (GEO) database. Genes regulating RNA splicing correlated with survival in colon cancer were identified and a risk score model was constructed using Cox regression analyses. In the risk model, RNA splicing factor peroxisome proliferator‐activated receptor‐γ coactivator‐1α (PPARGC1) is correlated with a good survival outcome, whereas Cdc2‐like kinase 1(CLK1), CLK2, and A‐kinase anchor protein 8‐like (AKAP8L) with a bad survival outcome. The risk model has a good performance for clinical prognostic prediction both in the TCGA cohort and the other two validation cohorts. In the tumor microenvironment (TME) analysis, the immune score was higher in the low‐risk group, and TME‐related pathway gene expression was also higher in low‐risk group. We further verified the mRNA and protein expression levels of these four genes in the adjacent nontumor, tumor, and liver metastasis tissues of colon cancer patients, which were consistent with bioinformatics analysis. In addition, knockdown of AKAP8L can suppress the proliferation and migration of colon cancer cells. Animal studies have also shown that AKAP8L knockdown can inhibit tumor growth in colon cancer in vivo. We established a prognostic risk model for colon cancer based on genes related to RNA splicing regulation and uncovered the role of AKAP8L in promoting colon cancer progression.

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Section: Resultsmentioning

confidence: 90%

“…Previous studies revealed that colon adenocarcinoma patients with a higher immune score and more infiltration of antitumor immune cells have a better survival outcome. 17 , 18 , 19 Therefore, we speculated that the better prognosis of the low‐risk group might be related to the more favorable antitumor immune microenvironment.…”

Section: Resultsmentioning

confidence: 99%

Novel prognostic model predicts overall survival in colon cancer based on RNA splicing regulation gene expression

Luo

Chen

et al. 2022

Cancer Science

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“…In our current work, we found that there was a clear link between the hypoxia score and the amount of COPZ1 in several cancers. Previous studies revealed that a higher immune score was correlated with better survival outcomes [ 45 , 46 ]. We further discovered that the infiltration of antitumor immune cells was higher in the patients with low COPZ1 expression, such as B cells, Neutrophil, CD8+T cells, CD4+T cells and M1 macrophages.…”

Section: Discussionmentioning

confidence: 99%

A Comprehensive Pan-Cancer Analysis of the Regulation and Prognostic Effect of Coat Complex Subunit Zeta 1

Hong

Xia

Sun

et al. 2023

Genes

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The Coatomer protein complex Zeta 1 (COPZ1) has been reported to play an essential role in maintaining the survival of some types of tumors. In this study, we sought to explore the molecular characteristics of COPZ1 and its clinical prognostic value through a pan-cancers bioinformatic analysis. We found that COPZ1 was extremely prevalent in a variety of cancer types, and high expression of COPZ1 was linked to poor overall survival in many cancers, while low expression in LAML and PADC was correlated with tumorigenesis. Besides, the CRISPR Achilles’ knockout analysis revealed that COPZ1 was vital for many tumor cells’ survival. We further demonstrated that the high expression level of COPZ1 in tumors was regulated in multi-aspects, including abnormal CNV, DNA-methylation, transcription factor and microRNAs. As for the functional exploration of COPZ1, we found a positive relationship between COPZ1’s expression and stemness and hypoxia signature, especially the contribution of COPZ1 on EMT ability in SARC. GSEA analysis revealed that COPZ1 was associated with many immune response pathways. Further investigation demonstrated that COPZ expression was negatively correlated with immune score and stromal score, and low expression of COPZ1 has been associated to more antitumor immune cell infiltration and pro-inflammatory cytokines. The further analysis of COPZ1 expression and anti-inflammatory M2 cells showed a consistent result. Finally, we verified the expression of COPZ1 in HCC cells, and proved its ability of sustaining tumor growth and invasion with biological experiments. Our study provides a multi-dimensional pan-cancer analysis of COPZ and demonstrates that COPZ1 can serve as both a prospective target for the treatment of cancer and a prognostic marker for a variety of cancer types.

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“…Considering the complex TME in GBM, the connections between 22 immune cells activity and the prognostic signature were investigated using the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) analysis ( 28 ). Moreover, the immune score, Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) score, and stromal score were calculated by the ESTIMATE algorithm ( 29 ).…”

Section: Methodsmentioning

confidence: 99%

A new prognostic model for glioblastoma multiforme based on coagulation-related genes

Zhou,

Deng,

et al. 2023

Transl Cancer Res

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Background Glioblastoma multiforme (GBM) is the most aggressive, common, and lethal type of primary brain tumor. Multiple cancers have been associated with abnormalities in the coagulation system that facilitate tumor invasion and metastasis. In GBM, the prognostic value and underlying mechanism of coagulation-related genes (CRGs) have not been explored. Methods RNA sequencing (RNA-seq) and clinical information on GBM were obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), respectively. Following the identification of differentially expressed CRGs (DECRGs) between GBM and control samples, the survival-related DECRGs were selected via univariate and multivariate Cox regression analyses to establish a prognostic signature. The prognostic performance and clinical utility of the prognostic signature were assessed by the Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC) curve analysis, and a nomogram was constructed. The signature genes-related underlying mechanisms were analyzed according to gene set enrichment analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-cell analysis. Finally, the difference in immune cell infiltration, stromal score, immune score, and Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) score were compared between different risk groups. Results A 5-gene prognostic signature ( PLAUR, GP6, C5AR1, SERPINA5, F2RL2 ) was established for overall survival (OS) prediction of GBM patients. The predicted efficiency of the prognostic signature was confirmed in TGGA-GBM dataset and validated in the CGGA-GBM dataset, revealing that it could differentiate GBM patients from controls well, and high risk score was accompanied with poor prognosis. Moreover, biological process (BP) and signaling pathway analyses showed that signature genes were mainly enriched in the functions of blood coagulation and tumor invasion and metastasis. Moreover, high-risk patients exhibited higher levels of immune cell infiltration, stromal score, immune score, and ESTIMATE score than that of low-risk patients. Conclusions An analysis of coagulation-related prognostic signatures was conducted in this study, as well as how signature genes may affect GBM progress, providing information that might provide new ideas for the development of GBM-related molecular targeted therapies.

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Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma

Cited by 4 publications

References 54 publications

Novel prognostic model predicts overall survival in colon cancer based on RNA splicing regulation gene expression

Novel prognostic model predicts overall survival in colon cancer based on RNA splicing regulation gene expression

A Comprehensive Pan-Cancer Analysis of the Regulation and Prognostic Effect of Coat Complex Subunit Zeta 1

A new prognostic model for glioblastoma multiforme based on coagulation-related genes

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