Prognostic signature related to the immune environment of oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) prognosis remains poor. Here we aimed to identify an effective prognostic signature for predicting the survival of patients with OSCC. Gene-expression and clinical data were obtained from the Cancer Genome Atlas database. Immune microenvironment-associated genes w...
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Gespeichert in:

Autor*in:	Hua Yingjie [verfasserIn] Sun Xuehui [verfasserIn] Luan Kefeng [verfasserIn] Wang Changlei [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	oral cancer subtype risk score prognosis survival

Übergeordnetes Werk:	In: Open Life Sciences - De Gruyter, 2015, 17(2022), 1, Seite 1135-1147
Übergeordnetes Werk:	volume:17 ; year:2022 ; number:1 ; pages:1135-1147

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1515/biol-2022-0467

Katalog-ID:	DOAJ032252668

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520			\|a Oral squamous cell carcinoma (OSCC) prognosis remains poor. Here we aimed to identify an effective prognostic signature for predicting the survival of patients with OSCC. Gene-expression and clinical data were obtained from the Cancer Genome Atlas database. Immune microenvironment-associated genes were identified using bioinformatics. Subtype and risk-score analyses were performed for these genes. Kaplan–Meier analysis and immune cell infiltration level were explored in different subtypes and risk-score groups. The prognostic ability, independent prognosis, and clinical features of the risk score were assessed. Furthermore, immunotherapy response based on the risk score was explored. Finally, a conjoint analysis of the subtype and risk-score groups was performed to determine the best prognostic combination. We found 11 potential prognostic genes and constructed a risk-score model. The subtype cluster 2 and a high-risk group showed the worst overall survival; differences in survival status might be due to the different immune cell infiltration levels. The risk score showed good performance, independent prognostic value, and valuable clinical application. Higher risk scores showed higher Tumor Immune Dysfunction and Exclusion scores, indicating that patients with a high-risk score were less likely to benefit from immunotherapy. Finally, conjoint analysis for the subgroups and risk groups showed the best predictive ability.
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language	English
source	In Open Life Sciences 17(2022), 1, Seite 1135-1147 volume:17 year:2022 number:1 pages:1135-1147
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authorswithroles_txt_mv	Hua Yingjie @@aut@@ Sun Xuehui @@aut@@ Luan Kefeng @@aut@@ Wang Changlei @@aut@@
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callnumber-first	Q - Science
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topic_title	QH301-705.5 Prognostic signature related to the immune environment of oral squamous cell carcinoma oral cancer subtype risk score prognosis survival
topic	misc QH301-705.5 misc oral cancer misc subtype misc risk score misc prognosis misc survival misc Biology (General)
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title	Prognostic signature related to the immune environment of oral squamous cell carcinoma
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title_full	Prognostic signature related to the immune environment of oral squamous cell carcinoma
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title_sort	prognostic signature related to the immune environment of oral squamous cell carcinoma
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title_auth	Prognostic signature related to the immune environment of oral squamous cell carcinoma
abstract	Oral squamous cell carcinoma (OSCC) prognosis remains poor. Here we aimed to identify an effective prognostic signature for predicting the survival of patients with OSCC. Gene-expression and clinical data were obtained from the Cancer Genome Atlas database. Immune microenvironment-associated genes were identified using bioinformatics. Subtype and risk-score analyses were performed for these genes. Kaplan–Meier analysis and immune cell infiltration level were explored in different subtypes and risk-score groups. The prognostic ability, independent prognosis, and clinical features of the risk score were assessed. Furthermore, immunotherapy response based on the risk score was explored. Finally, a conjoint analysis of the subtype and risk-score groups was performed to determine the best prognostic combination. We found 11 potential prognostic genes and constructed a risk-score model. The subtype cluster 2 and a high-risk group showed the worst overall survival; differences in survival status might be due to the different immune cell infiltration levels. The risk score showed good performance, independent prognostic value, and valuable clinical application. Higher risk scores showed higher Tumor Immune Dysfunction and Exclusion scores, indicating that patients with a high-risk score were less likely to benefit from immunotherapy. Finally, conjoint analysis for the subgroups and risk groups showed the best predictive ability.
abstractGer	Oral squamous cell carcinoma (OSCC) prognosis remains poor. Here we aimed to identify an effective prognostic signature for predicting the survival of patients with OSCC. Gene-expression and clinical data were obtained from the Cancer Genome Atlas database. Immune microenvironment-associated genes were identified using bioinformatics. Subtype and risk-score analyses were performed for these genes. Kaplan–Meier analysis and immune cell infiltration level were explored in different subtypes and risk-score groups. The prognostic ability, independent prognosis, and clinical features of the risk score were assessed. Furthermore, immunotherapy response based on the risk score was explored. Finally, a conjoint analysis of the subtype and risk-score groups was performed to determine the best prognostic combination. We found 11 potential prognostic genes and constructed a risk-score model. The subtype cluster 2 and a high-risk group showed the worst overall survival; differences in survival status might be due to the different immune cell infiltration levels. The risk score showed good performance, independent prognostic value, and valuable clinical application. Higher risk scores showed higher Tumor Immune Dysfunction and Exclusion scores, indicating that patients with a high-risk score were less likely to benefit from immunotherapy. Finally, conjoint analysis for the subgroups and risk groups showed the best predictive ability.
abstract_unstemmed	Oral squamous cell carcinoma (OSCC) prognosis remains poor. Here we aimed to identify an effective prognostic signature for predicting the survival of patients with OSCC. Gene-expression and clinical data were obtained from the Cancer Genome Atlas database. Immune microenvironment-associated genes were identified using bioinformatics. Subtype and risk-score analyses were performed for these genes. Kaplan–Meier analysis and immune cell infiltration level were explored in different subtypes and risk-score groups. The prognostic ability, independent prognosis, and clinical features of the risk score were assessed. Furthermore, immunotherapy response based on the risk score was explored. Finally, a conjoint analysis of the subtype and risk-score groups was performed to determine the best prognostic combination. We found 11 potential prognostic genes and constructed a risk-score model. The subtype cluster 2 and a high-risk group showed the worst overall survival; differences in survival status might be due to the different immune cell infiltration levels. The risk score showed good performance, independent prognostic value, and valuable clinical application. Higher risk scores showed higher Tumor Immune Dysfunction and Exclusion scores, indicating that patients with a high-risk score were less likely to benefit from immunotherapy. Finally, conjoint analysis for the subgroups and risk groups showed the best predictive ability.
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title_short	Prognostic signature related to the immune environment of oral squamous cell carcinoma
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Prognostic signature related to the immune environment of oral squamous cell carcinoma

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