A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma

Song, Congkuan; Wu, Zhi‐Quan; Wang, Qingwen; Wang, Yujin; Guo, Zixin; Li, Sheng; Hu, Weidong

doi:10.3389/fcell.2021.634697

Cited by 13 publications

(15 citation statements)

References 31 publications

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“…These findings imply that low ARNTL2 expression ccRCC patients with high PBRM1 mutation rates can achieve more clinical benefits from ICI therapy. Furthermore, recent studies reported that ARNTL2 is correlated with prognosis and immune infiltration of lung adenocarcinoma [ 13 , 14 ]. These studies indicate that ARNTL2 may affect the TIME of cancer.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have explored carcinogenesis roles of ARNTL2 in human malignancies such as breast carcinoma and colorectal adenocarcinoma [ 11 , 12 ]. In addition, recent researches reported that ARNTL2 is correlated with poor survival and immune infiltration level of lung adenocarcinoma [ 13 , 14 ]. However, the potential roles of ARNTL2 in ccRCC have not been investigated so far.…”

Section: Introductionmentioning

confidence: 99%

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Upregulation of ARNTL2 is associated with poor survival and immune infiltration in clear cell renal cell carcinoma

Wang

Ying

et al. 2021

Cancer Cell Int

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Background Aryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2) is a member of the PAS superfamily. Previous studies explored the carcinogenic roles of transcription factor ARNTL2 in human malignancies. However, its roles in ccRCC have not been elucidated. This study sought to explore the roles of ARNTL2 in ccRCC and determine its correlations with tumor immunity. Methods The expression of ARNTL2 was analyzed using the GEO, TCGA and GTEx database, and verified in ccRCC tissue samples and cell lines by qRT-PCR and western blot analysis. Kaplan–Meier survival curve analysis, Cox regression analysis (including univariate and multivariate analysis) was utilized to evaluate the prognostic values of ARNTL2. Potential biological mechanisms of ARNTL2 were explored using GSEA method. Colony formation and wound healing assays were conducted to explore the oncogenic role of ARNTL2 in ccRCC. ssGSEA and xCell algorithm were used to explore the correlation between ARNTL2 expression and tumor immune microenvironment (TIME). Results ARNTL2 was significantly upregulated in ccRCC tissues and cell lines compared to normal kidney tissues and cell line. Enhanced expression of ARNTL2 was strongly linked to advanced clinical stage and unfavorable overall survival in ccRCC. ARNTL2 was determined as an independent prognostic marker through cox regression analysis. A prognostic nomogram was constructed to predict 1-, 3- and 5-year overall survival of ccRCC patients by integrating ARNTL2 expression with other clinicopathologic variables. GSEA analysis showed that focal adhesion, T cell receptor, cell cycle, and JAK-STAT signaling pathway were significantly enriched in high ARNTL2 samples. Silencing of ARNTL2 suppressed the colony formation ability and wound healing efficacy of ccRCC cell lines. xCell analysis showed that high expression level of ARNTL2 exhibited an immune infiltration status similar to CD8 + inflamed ccRCC subtype, which was characterized by high infiltration level of CD8 + T cell and high expression level of the immune escape biomarkers such as PD-L1, PD-L2, PD1 and CTLA4. Conclusion ARNTL2 is an independent adverse predictor of ccRCC patient survival. High expression level of ARNTL2 is associated with immune infiltration, and may be a novel therapeutic target in ccRCC.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Upregulation of ARNTL2 is associated with poor survival and immune infiltration in clear cell renal cell carcinoma

Wang

Ying

et al. 2021

Cancer Cell Int

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“…( 65 ) have found a positive association between the expression of the transcription factor ARNTL2 (aryl hydrocarbon receptor nuclear translocator-like 2) and the outcome of patients with LUAD. ARNTL2 is a paralog of the circadian transcription factor ARNTL and has recently been discovered to also act as a modifier of immune cell infiltration in malignancies ( 66 – 68 ). Meanwhile, the Wnt antagonist DKK1 (Dickkopf-1) has been implicated in the modulation of immune cell activities as well as the immunosuppressive microenvironment in cancers and has become a promising target for cancer immunotherapy ( 69 , 70 ).…”

Section: Discussionmentioning

confidence: 99%

Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures

et al. 2022

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Increasing evidence has implicated the modification of 7-methylguanosine (m7G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m7G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop a novel prognostic model in LUAD based on m7G-related gene signatures. The LUAD transcriptome profiling data and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus datasets. After screening, we first obtained 29 m7G-related genes, most of which were upregulated in tumor tissues and negatively associated with overall survival (OS). According to the expression similarity of m7G-related genes, the combined samples from the TCGA-LUAD and GSE68465 datasets were further classified as two clusters that exhibit distinct OS rates and genetic heterogeneity. Then, we constructed a novel prognostic model involving four genes by using 130 differentially expressed genes among the two clusters. The combined samples were randomly divided into a training cohort and an internal validation cohort in a 1:1 ratio, and the GSE72094 dataset was used as an external validation cohort. The samples were divided into high- and low-risk groups. We demonstrated that a higher risk score was an independent negative prognostic factor and predicted poor OS. A nomogram was further constructed to better predict the survival of LUAD patients. Functional enrichment analyses indicated that cell cycle and DNA replication-related biological processes and pathways were enriched in the high-risk group. More importantly, the low-risk group had greater infiltration and enrichment of most immune cells, as well as higher ESTIMATE, immune, and stromal scores. In addition, the high-risk group had a lower TIDE score and higher expressions of most immune checkpoint-related genes. We finally noticed that patients in the high-risk group were more sensitive to chemotherapeutic agents commonly used in LUAD. In conclusion, we herein summarized for the first time the alterations and prognostic role of m7G-related genes in LUAD and then constructed a prognostic model based on m7G-related gene signatures that could accurately and stably predict survival and guide individualized treatment decision-making in LUAD patients.

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“…Then, using TIMER database, we discovered that the copy number of the ARNTL2 was negatively related to the infiltration levels of B cell, CD8 + T cell, macrophage, neutrophil in LUAD. By searching Pubmed, we found that the ARNTL2-related immune process affects several types of diseases, such as LUAD [ 79 , 80 ], pancreatic cancer [ 81 ], type 1 diabetes [ 82 , 83 ]. These findings imply that ARNTL2-induced alteration may affect the tumor immune microenvironment and the progression of LUAD.…”

Section: Discussionmentioning

confidence: 99%

ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

et al. 2021

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Background Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study. Methods Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells. Results We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes. Conclusion Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

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A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma

Cited by 13 publications

References 31 publications

Upregulation of ARNTL2 is associated with poor survival and immune infiltration in clear cell renal cell carcinoma

Upregulation of ARNTL2 is associated with poor survival and immune infiltration in clear cell renal cell carcinoma

Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures

ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

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