Identification of Clinical and Tumor Microenvironment Characteristics of Hypoxia-Related Risk Signature in Lung Adenocarcinoma

Dai, Zili; Liu, Taisheng; Liu, Guihong; Deng, Zhen; Yu, Peng; Wang, Baiyao; Cen, Bohong; Guo, Liyi; Zhang, Jian

doi:10.3389/fmolb.2021.757421

Cited by 7 publications

(6 citation statements)

References 45 publications

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“…In addition, this model was also more predictable at long-term follow-up. Although the prognostic model of LUAD established by hypoxia-related genes previously has similar predictive power to our study 38 . However, this study combined HRGs and IRGs to construct a predictive model, which could more comprehensively reflect the hypoxia and immune status of LUAD patients.…”

Section: Discussionsupporting

confidence: 75%

Development and Validation of a Combined Hypoxia and Immune Prognostic Classifier for Lung Adenocarcinoma

et al. 2022

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Lung cancer is the leading cause of cancer-related deaths worldwide. Hypoxia is a crucial microenvironmental factor in lung adenocarcinoma (LUAD). However, the prognostic value based on hypoxia and immune in LUAD remains to be further clarified. The hypoxia-related genes (HRGs) and immune-related genes (IRGs) were downloaded from the public database. The RNA-seq expression and matched complete clinical data for LUAD were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to model construction. Hypoxia expression profiles, immune cell infiltration, functional enrichment analysis, Tumor Immune Dysfunction and Exclusion (TIDE) score and the somatic mutation status were analyzed and compared based on the model. Moreover, immunofluorescence (IF) staining in human LUAD cases to explore the expression of hypoxia marker and immune checkpoint. A prognostic model of 9 genes was established, which can divide patients into two subgroups. There were obvious differences in hypoxia and immune characteristics in the two groups, the group with high-risk score value showed significantly high expression of hypoxia genes and programmed death ligand-1 (PD-L1), and maybe more sensitive to immunotherapy. Patients in the high-risk group had shorter overall survival (OS). This model has a good predictive value for the prognosis of LUAD. We constructed a new HRGs and IRGs model for prognostic prediction of LUAD. This model may benefit future immunotherapy for LUAD.

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Section: Discussionsupporting

confidence: 75%

Development and Validation of a Combined Hypoxia and Immune Prognostic Classifier for Lung Adenocarcinoma

et al. 2022

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“…In a previous study on T-cell malignancy, nuclear PFKP increased CXCR4 to induce T-ALL cell invasion and was correlated with poorer survival [30] . PD-L1 has crucial functions in cancer immune evasion [31] . PFKP can induce PD-L1 to enhance cancer immune evasion in glioblastoma [14] .…”

Section: Discussionmentioning

confidence: 99%

ZNF148/PFKP/PD-L1 axis promotes non-small cell lung cancer proliferation, migration and glycolysis

Zhu,

Chen,

Jin

et al. 2023

J Cancer Metastasis Treat

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Aim: Cancer-related deaths are primarily caused by lung cancer around the world. The prognosis and burden of lung cancer must be improved by identifying novel biomarkers for diagnosis and treatment. In non-small cell lung cancer (NSCLC), the platelet isoform of phosphofructokinase 1 (PFKP) has been identified as a tumor-promoting oncogene. The current study examined the specific role that PFKP plays in NSCLC tumorigenesis, as well as the underlying mechanism. Methods: A lung cancer dataset was obtained from the TCGA in order to examine the expression of PFKP. Using the Kaplan-Meier Plotter website, we calculated the overall survival (OS) along with the recurrence-free survivals (RFS) curves with high and low levels of PFKP in lung cancer. The mechanism by which zinc finger protein 148 (ZNF148) regulated PFKP/PD-L1 levels in NSCLC was investigated through chromatin immunoprecipitation (ChIP), qRT-PCR, and western blotting. In order to uncover ZNF148's function in NSCLC, subsequent functional studies included CCK-8, colony formation, and Transwell, along with glycolysis assays. Student’s T-test was conducted for data analysis with GraphPad Prism 9.0. Results: The expression of PFKP in NSCLC was increased, and it was linked to worse outcomes. This increased expression of PFKP in NSCLC was induced by ZNF148. Silencing ZNF148 remarkably dampened NSCLC cell proliferation, invasion, and glycolysis capacities. According to a mechanistic study, ZNF148 regulates the PFKP/PD-L1 axis, which promotes NSCLC tumorigenesis. Conclusion: It has been established that ZNF148-induced PFKP is key to the proliferation, invasion, and glycolysis abilities of NSCLC cells by regulating PD-L1 expression. Therefore, the ZNF148/PFKP/PD-L1 axis could be a potential biological signature and target for NSCLC diagnosis and treatment.

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“…Kaplan-Meier (KM) survival analysis was used to test the survival difference between the two subgroups. In addition, we utilized ROC curves to compare the effectiveness of our model with previous studies ( 16 – 19 ).…”

Section: Methodsmentioning

confidence: 99%

Construction and validation of a T cell proliferation regulator-related signature for predicting prognosis and immunotherapy response in lung adenocarcinoma

Chang

Cheng

et al. 2023

Front. Immunol.

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BackgroundAs the main executor of immunotherapy, T cells significantly affect the efficacy of immunotherapy. However, the contribution of the T cell proliferation regulator to the prognosis of lung adenocarcinoma (LUAD) and immunotherapy is still unclear.MethodsBased on T cell proliferation regulators, LUAD samples from The Cancer Genome Atlas (TCGA) were divided into two different clusters by consensus clustering. Subsequently, the T cell proliferation regulator (TPR) signature was constructed according to the prognostic T cell proliferation regulators. Combined with clinical information, a nomogram for clinical practice was constructed. The predictive ability of the signature was verified by the additional Gene Expression Omnibus (GEO) dataset. We also analyzed the differences of tumor microenvironment (TME) in different subgroups and predicted the response to immunotherapy according to the TIDE algorithm. Finally, we further explored the role of ADA (Adenosine deaminase) in the lung adenocarcinoma cell lines through the knockdown of ADA. ResultsAccording to the consensus clustering, there were differences in survival and tumor microenvironment between two different molecular subtypes. T cell proliferation regulator-related signature could accurately predict the prognosis of LUAD. The low-risk group had a higher level of immune infiltration and more abundant immune-related pathways, and its response to immunotherapy was significantly better than the high-risk group (Chi-square test, p<0.0001). The knockdown of ADA inhibited proliferation, migration, and invasion in lung adenocarcinoma cell lines.ConclusionT cell proliferation regulators were closely related to the prognosis and tumor microenvironment of LUAD patients. And the signature could well predict the prognosis of LUAD patients and their response to immunotherapy. ADA may become a new target for the treatment of LUAD.

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Identification of Clinical and Tumor Microenvironment Characteristics of Hypoxia-Related Risk Signature in Lung Adenocarcinoma

Cited by 7 publications

References 45 publications

Development and Validation of a Combined Hypoxia and Immune Prognostic Classifier for Lung Adenocarcinoma

Development and Validation of a Combined Hypoxia and Immune Prognostic Classifier for Lung Adenocarcinoma

ZNF148/PFKP/PD-L1 axis promotes non-small cell lung cancer proliferation, migration and glycolysis

Construction and validation of a T cell proliferation regulator-related signature for predicting prognosis and immunotherapy response in lung adenocarcinoma

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