Identification of Necroptosis-related Subtypes and Characterization of Tumor Microenvironment Infiltration in Non-small Cell Lung Cancer
Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net..
BACKGROUND: Necroptosis is correlated with the development, prognosis, and treatment of tumors. However, the function of necroptosis-associated genes (NRGs) in the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC) remains unclear.
METHODS: In this study, 1210 NSCLC samples were classified into different subtypes based on the expression of 66 NRGs by unsupervised clustering analysis, and further analyzed the TME characteristics of these subtypes. In addition, we identified common differentially expressed genes (co-DEGs) in NRG subtypes and constructed the NRG score using principal component analysis (PCA) to assess the NRG-mediated TME characteristics of patients with NSCLC.
RESULTS: Using unsupervised cluster analysis, 1210 NSCLC samples were divided into NRGcluster A and B subtypes. The NRGcluster B survived significantly better than the NRGcluster A. TME characterization revealed that NRGcluster B was upregulated in immune and stromal signaling activation, whereas NRGcluster A was upregulated in oncogenic signaling. The NRG score constructed based on co-DEGs of the two NRG-related subtypes was positively correlated with immune cell infiltration and negatively correlated with the number of cancer stem cells (CSCs) and tumor mutational burden (TMB). In addition, survival was significantly worse in the low-NRG-score group compared to the high-NRG-score group. Finally, the assessment of immunotherapeutic efficacy showed that immunotherapeutic response was significantly worse in the low-NRG-score group compared to the high- NRG-score group.
CONCLUSION: This research reveals that NRGs are associated with the complexity and diversity of TME in NSCLC. Adopting the NRG score to quantitatively assess NRG-mediated TME in individual patients with NSCLC may help in planning clinical treatment strategies.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - year:2023 |
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| Enthalten in: |
Current cancer drug targets - (2023) vom: 01. Juni |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Deng, Yan [VerfasserIn] |
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| Links: |
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| Themen: |
Immunotherapy |
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| Anmerkungen: |
Date Revised 07.08.2023 published: Print-Electronic Citation Status Publisher |
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| doi: |
10.2174/1568009623666230414140609 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM359696104 |
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| 500 | |a Date Revised 07.08.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status Publisher | ||
| 520 | |a Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net. | ||
| 520 | |a BACKGROUND: Necroptosis is correlated with the development, prognosis, and treatment of tumors. However, the function of necroptosis-associated genes (NRGs) in the tumor microenvironment (TME) of non-small cell lung cancer (NSCLC) remains unclear | ||
| 520 | |a METHODS: In this study, 1210 NSCLC samples were classified into different subtypes based on the expression of 66 NRGs by unsupervised clustering analysis, and further analyzed the TME characteristics of these subtypes. In addition, we identified common differentially expressed genes (co-DEGs) in NRG subtypes and constructed the NRG score using principal component analysis (PCA) to assess the NRG-mediated TME characteristics of patients with NSCLC | ||
| 520 | |a RESULTS: Using unsupervised cluster analysis, 1210 NSCLC samples were divided into NRGcluster A and B subtypes. The NRGcluster B survived significantly better than the NRGcluster A. TME characterization revealed that NRGcluster B was upregulated in immune and stromal signaling activation, whereas NRGcluster A was upregulated in oncogenic signaling. The NRG score constructed based on co-DEGs of the two NRG-related subtypes was positively correlated with immune cell infiltration and negatively correlated with the number of cancer stem cells (CSCs) and tumor mutational burden (TMB). In addition, survival was significantly worse in the low-NRG-score group compared to the high-NRG-score group. Finally, the assessment of immunotherapeutic efficacy showed that immunotherapeutic response was significantly worse in the low-NRG-score group compared to the high- NRG-score group | ||
| 520 | |a CONCLUSION: This research reveals that NRGs are associated with the complexity and diversity of TME in NSCLC. Adopting the NRG score to quantitatively assess NRG-mediated TME in individual patients with NSCLC may help in planning clinical treatment strategies | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Necroptosis | |
| 650 | 4 | |a immunotherapy | |
| 650 | 4 | |a non-small cell lung cancer (NSCLC) | |
| 650 | 4 | |a prognosis. | |
| 650 | 4 | |a tumor microenvironment (TME) | |
| 650 | 4 | |a unsupervised cluster analysis | |
| 700 | 1 | |a Lin, Yan |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Bin |e verfasserin |4 aut | |
| 700 | 1 | |a Jing, Qian |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Wei |e verfasserin |4 aut | |
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