Cancer Stemness-Based Prognostic Immune-Related Gene Signatures in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

Li, Na; Li, Yalin; Zheng, Peixian; Zhan, Xianquan

doi:10.3389/fendo.2021.755805

Cited by 25 publications

(17 citation statements)

References 59 publications

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“…In our investigation, patients with low logistics score had poor responses to immunotherapy, suggesting that for the selection of patients before ICI treatment, these 18 immune response-related characteristic genes may be useful. In the process of selecting patients for ICI treatment, PD-L1 expression, TMB, mRNAsi, and EREG-mRNAsi have been measured ( Li et al, 2021a ). The predictive performance of this immune feature was not related to mRNAsi.…”

Section: Discussionmentioning

confidence: 99%

Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma

Xue

Feng²,

Zhou³

et al. 2022

Front. Genet.

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Background: Immunotherapy has been a promising approach option for lung cancer.Method: All the open-accessed data was obtained from the Cancer Genome Atlas (TCGA) database. All the analysis was conducted using the R software analysis.Results: Firstly, the genes differentially expressed in lung cancer immunotherapy responders and non-responders were identified. Then, the lung adenocarcinoma immunotherapy-related genes were determined by LASSO logistic regression and SVM-RFE, respectively. A total of 18 immunotherapy response-related genes were included in our investigation. Subsequently, we constructed the logistics score model. Patients with high logistics score had a better clinical effect on immunotherapy, with 63.2% of patients responding to immunotherapy, while only 12.1% of patients in the low logistics score group responded to immunotherapy. Moreover, we found that pathways related to immunotherapy were mainly enriched in metabolic pathways such as fatty acid metabolism, bile acid metabolism, oxidative phosphorylation, and carcinogenic pathways such as KRAS signaling. Logistics score was positively correlated with NK cells activated, Mast cells resting, Monocytes, Macrophages M2, dendritic cells resting, dendritic cells activated and eosinophils, while was negatively related to Tregs, macrophages M0, macrophages M1, and mast cells activated. In addition, ERVH48-1 was screened for single-cell exploration. The expression of ERVH48-1 increased in patients with distant metastasis, and ERVH48-1 was associated with pathways such as pancreas beta cells, spermatogenesis, G2M checkpoints and KRAS signaling. The result of quantitative real-time PCR showed that ERVH48-1 was upregulated in lung cancer cells.Conclusion: Our study developed an effective signature to predict the immunotherapy response of lung cancer patients.

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Section: Discussionmentioning

confidence: 99%

Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma

Xue

Feng²,

Zhou³

et al. 2022

Front. Genet.

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“…The genetic variation of CD1B correlated with biochemical recurrence in patients with localized prostate cancer (42). An increasing body of bioinformatics analyses identi ed CD1B as prognostic biomarkers in colon cancer and lung cancer (43)(44)(45)(46). MATK has been found to phosphorylate and inhibit Src family kinases, and plays an inhibitory role in cell growth and proliferation of T-cells (47).…”

Section: Discussionmentioning

confidence: 99%

Immune checkpoints expression patterns predict prognosis and immune microenvironment remodeling in triple-negative breast cancer

Zhang

Jin

Pan³

et al. 2022

Preprint

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Targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown. Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. Molecular typings based on the ICGs expression profiled were identified and the associations between ICGs molecular typing and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs) were further explored. We identified two ICGs clusters and two ICGs-related gene clusters, which were were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We also established and ICGs Riskscore quantification system to assess the ICGs expression patterns for individuals. TNBC patients with lower ICGs Riskscore were characterized by increased immune cell infiltration, favorable clinical outcome and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict OS in TNBC and the proposed nomogram presents good performance. Genomic features analysis revealed that high ICGs-related riskscore group presented an increased tumor mutation burden compared with the low ICGs-related riskscore group. Collectively, dissecting the ICGs expression patterns not only provides a new insight of subtype of TNBC but also deepens the understanding of ICGs in tumor immune microenvironment.

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“…Li et al analyzed the role of cancer stemness in lung cancer survival data, specifically lung adenocarcinoma (n=452) and lung squamous cell carcinoma (n=363). 5,11 In their study, they reported how differentially expressed genes related to stemness origination, which then led to the dysregulation of the tumor microenvironment and abundance of infiltrating immune cells. The tumor microenvironment included "naïve B cells, B cells memory, plasma cells, T cells CD8, T cells CD4 memory resting, T cells CD4-memory activated, T cells follicular helper, Tregs, NK cells resting, NK cells activated, monocytes, macrophages M0, macrophages M1, macrophages M2, dendritic cells resting, dendritic cells activated, mast cells resting, mast cells activated, eosinophils, and neutrophils", which were profiled with CIBERSORT.…”

Section: Lung Adenocarcinoma (Luad) and Lung Squamous Cell Carcinoma ...mentioning

confidence: 99%

“…Studies on lung adenocarcinoma and lung squamous cell carcinoma, gastric cancer, hepatocellular carcinoma and glioblastoma, and other tumors of varying degrees of prognosis, have formed the focus of mRNAsi tools which ultimately lead to clinical outcome data such as overall survival (OS) and progression-free survival (PFS). 5,6,7,8,9 mRNAsi has been developed to analyze prognostic significance for immunotherapy response for cancer stemness in lung cancer, gastric cancer, hepatocellular carcinoma and glioblastoma that form the focus of this review article.…”

Section: Introductionmentioning

confidence: 99%

Clinical Tier Grading of Cancer Stem Cells According to Clinical Characteristics for Immune Checkpoint Inhibitors Guided by mRNA stemness index

Hays¹

2022

MRAJ

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Cancer stems cells are cells in tumors that have self-renewing capabilities and proliferation, and are partly responsible for tumor growth, metastasis and drug resistance, and have been associated with multidrug resistance and epithelial-mesenchymal transition. mRNA stemness index or mRNAsi is a machine learning tool that uses the application of algorithms to find associations between cancer stemness and tumor prognostic signatures. mRNAsi predicts gene mutation status and identifies tumor signaling pathways. Clinical tier grading is a common feature for stratifying the presenting features and symptoms of patients in several diseases. This study is a review article that summarizes studies in lung cancer, gastric cancer, hepatocellular carcinoma and glioblastoma that use mRNA stemness index machine learning tools to identify differentially expressed genes, characterize the tumor microenvironment and tumor mutational burden, and determine clinical endpoints. A prognostic signature is shown in this paper as determined by mRNAsi high and low values, and a clinical tier grading system is proposed that categorizes cancer stemness presenting characteristics. This clinical grading tier system demonstrates a relationship between cancer stemness and immune checkpoint inhibitor efficacy. This type of tiered system for cancer patients and the accompanying workflow proposed may prove useful to oncologists, and has not been performed before, and is unique in the literature.

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Cancer Stemness-Based Prognostic Immune-Related Gene Signatures in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

Cited by 25 publications

References 59 publications

Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma

Immunotherapy response and microenvironment provide biomarkers of immunotherapy options for patients with lung adenocarcinoma

Immune checkpoints expression patterns predict prognosis and immune microenvironment remodeling in triple-negative breast cancer

Clinical Tier Grading of Cancer Stem Cells According to Clinical Characteristics for Immune Checkpoint Inhibitors Guided by mRNA stemness index

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