Immune Infiltration Subtypes Characterization and Identification of Prognosis-Related lncRNAs in Adenocarcinoma of the Esophagogastric Junction

Hu, Xin; Wu, Liuxing; Liu, Ben; Chen, Kexin

doi:10.3389/fimmu.2021.651056

Cited by 16 publications

(16 citation statements)

References 44 publications

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“…Signaling pathways related to the IL(R)-based signature were analyzed through Gene Set Enrichment Analysis (GSEA). GSEA is commonly used to evaluate the distribution trend of genes in a predefined gene set, which has been widely reported to investigate the biological process difference between subtypes ( 20 , 21 ).…”

Section: Methodsmentioning

confidence: 99%

Clinical Significance and Immunologic Landscape of a Five-IL(R)-Based Signature in Lung Adenocarcinoma

et al. 2021

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Interleukins (ILs) and interleukin receptors (ILRs) play important role in the antitumor immune response. However, the expression signature and clinical characteristics of the IL(R) family in lung adenocarcinoma (LUAD) remains unclear. The main purpose of this study was to explore the expression profile of IL(R) family genes and construct an IL(R)-based prognostic signature in LUAD. Five public datasets of 1,312 patients with LUAD were enrolled in this study. Samples from The Cancer Genome Atlas (TCGA) were used as the training set, and samples from the other four cohorts extracted from Gene Expression Omnibus (GEO) database were used as the validation set. Additionally, the profile of IL(R) family signature was explored, and the association between this signature and immunotherapy response was also analyzed. Meanwhile, the prognostic value was compared between this IL(R)-based signature and different immunotherapy markers. A signature based on five identified IL(R)s (IL7R, IL5RA, IL20RB, IL11, IL22RA1) was constructed using the TCGA dataset through univariate/multivariable Cox proportional hazards regression and least absolute shrinkage and selection operator (LASSO) Cox analysis. These cases with LUAD were stratified into high- and low-risk group according to the risk score. This signature showed a strong prognostic ability, which was verified by the five independent cohorts and clinical subtypes. The IL(R)-based models presented unique characteristics in terms of immune cell infiltration and immune inflammation profile in tumor microenvironment (TME). Biological pathway analysis confirmed that high-risk patients showed significant T- and B-cell immunosuppression and rapid tumor cell proliferation. More importantly, we researched the relationship between this IL(R)-based signature and immune checkpoints, tumor mutation burden (TMB), tumor purity and ploidy, and tumor immune dysfunction and exclusion (TIDE) score, which confirmed that this signature gave the best prognostic value. We first provided a robust prognostic IL(R)-based signature, which had the potential as a predictor for immunotherapy response to realize individualized treatment of LUAD.

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Section: Methodsmentioning

confidence: 99%

Clinical Significance and Immunologic Landscape of a Five-IL(R)-Based Signature in Lung Adenocarcinoma

et al. 2021

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“…The expression profile data of breast cancer patients (n = 998) with complete clinical information were downloaded from TCGA database. The patients were divided into PRMT1 high-and low-expression groups according to the optimal cutoff value calculated using the "survminer" package (https://CRAN.R-project.org/package=survminer, accessed on 11 July 2021) [22,23]. The Kaplan-Meier method was used to assess the efficiency of disease-specific survival (DSS) in high-and low-expression patients.…”

Section: Disease Specific Survival Analysismentioning

confidence: 99%

Arginine Methyltransferase PRMT1 Regulates p53 Activity in Breast Cancer

Tang

et al. 2021

Life

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The protein p53 is one of the most important tumor suppressors, responding to a variety of stress signals. Mutations in p53 occur in about half of human cancer cases, and dysregulation of the p53 function by epigenetic modifiers and modifications is prevalent in a large proportion of the remainder. PRMT1 is the main enzyme responsible for the generation of asymmetric-dimethylarginine, whose upregulation or aberrant splicing has been observed in many types of malignancies. Here, we demonstrate that p53 function is regulated by PRMT1 in breast cancer cells. PRMT1 knockdown activated the p53 signal pathway and induced cell growth-arrest and senescence. PRMT1 could directly bind to p53 and inhibit the transcriptional activity of p53 in an enzymatically dependent manner, resulting in a decrease in the expression levels of several key downstream targets of the p53 pathway. We were able to detect p53 asymmetric-dimethylarginine signals in breast cancer cells and breast cancer tissues from patients, and the signals could be significantly weakened by silencing of PRMT1 with shRNA, or inhibiting PRMT1 activity with a specific inhibitor. Furthermore, PRMT1 inhibitors significantly impeded cell growth and promoted cellular senescence in breast cancer cells and primary tumor cells. These results indicate an important role of PRMT1 in the regulation of p53 function in breast tumorigenesis.

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“…The clusters showed a low correlation. When K = 2, the CDF curve is flat, revealing the correct K ( Wilkerson and Hayes, 2010 ; Senbabaoglu et al, 2014 ; Hu et al, 2021 ). The maximum Calinski-Harabasz (CH) index indicated that K = 2 was the optimal number of clusters ( Supplementary Figure S2 ).…”

Section: Resultsmentioning

confidence: 99%

Identification of an m6A Regulators-Mediated Prognosis Signature For Survival Prediction and Its Relevance to Immune Infiltration in Melanoma

Dai

et al. 2021

Front. Cell Dev. Biol.

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Despite robust evidence for the role of m6A in cancer development and progression, its association with immune infiltration and survival outcomes in melanoma remains obscure. Here, we aimed to develop an m6A-related risk signature to improve prognostic and immunotherapy responder prediction performance in the context of melanoma. We comprehensively analyzed the m6A cluster and immune infiltration phenotypes of public datasets. The TCGA (n = 457) and eleven independent melanoma cohorts (n = 758) were used as the training and validation datasets, respectively. We identified two m6A clusters (m6A-clusterA and m6A-clusterB) based on the expression pattern of m6A regulators via unsupervised consensus clustering. IGF2BP1 (7.49%), KIAA1429 (7.06%), and YTHDC1 (4.28%) were the three most frequently mutated genes. There was a correlation between driver genes mutation statuses and the expression of m6A regulators. A significant difference in tumor-associated immune infiltration between two m6A clusters was detected. Compared with m6A-clusterA, the m6A-clusterB was characterized by a lower immune score and immune cell infiltration but higher mRNA expression-based stemness index (mRNAsi). An m6A-related risk signature consisting of 12 genes was determined via Cox regression analysis and divided the patients into low- and high-risk groups (IL6ST, MBNL1, NXT2, EIF2A, CSGALNACT1, C11orf58, CD14, SPI1, NCCRP1, BOK, CD74, PAEP). A nomogram was developed for the prediction of the survival rate. Compared with the high-risk group, the low-risk group was characterized by high expression of immune checkpoints and immunophenoscore (IPS), activation of immune-related pathways, and more enriched in immune cell infiltrations. The low-risk group had a favorable prognosis and contained the potential beneficiaries of the immune checkpoint blockade therapy and verified by the IMvigor210 cohort (n = 298). The m6A-related signature we have determined in melanoma highlights the relationships between m6A regulators and immune cell infiltration. The established risk signature was identified as a promising clinical biomarker of melanoma.

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Immune Infiltration Subtypes Characterization and Identification of Prognosis-Related lncRNAs in Adenocarcinoma of the Esophagogastric Junction

Cited by 16 publications

References 44 publications

Clinical Significance and Immunologic Landscape of a Five-IL(R)-Based Signature in Lung Adenocarcinoma

Clinical Significance and Immunologic Landscape of a Five-IL(R)-Based Signature in Lung Adenocarcinoma

Arginine Methyltransferase PRMT1 Regulates p53 Activity in Breast Cancer

Identification of an m6A Regulators-Mediated Prognosis Signature For Survival Prediction and Its Relevance to Immune Infiltration in Melanoma

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