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pmid:34888229

Identification of Hypoxia-Related Molecular Classification and Associated Gene Signature in Oral Squamous Cell Carcinoma.

Chen Li · Xin Chen · Xiaolin Ren · Jia-Lin Chen · Hao Chen · Jing-Jia Yu · Qiu-Chi Ran · Shuang Kang · Xi-Meng Chen · Zhen-Jin Zhao

Frontiers in oncology · 2021 doi:10.3389/fonc.2021.709865

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

Execution evidence has not yet been added to this .science file. Explore its methods, data and open questions to plan the next step.
Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:34888229
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science-record
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title
Identification of Hypoxia-Related Molecular Classification and Associated Gene Signature in Oral Squamous Cell Carcinoma.
doi
10.3389/fonc.2021.709865
pmid
34888229
authors array · 10 items
[0]
Chen Li
[1]
Xin Chen
[2]
Xiaolin Ren
[3]
Jia-Lin Chen
[4]
Hao Chen
[5]
Jing-Jia Yu
[6]
Qiu-Chi Ran
[7]
Shuang Kang
[8]
Xi-Meng Chen
[9]
Zhen-Jin Zhao
journal
Frontiers in oncology
year
2021
abstract
The high heterogeneity of oral squamous cell carcinoma (OSCC) is the main obstacle for individualized treatment. Recognizing the characteristics of different subtypes and investigating the promising strategies for each subclass are of great significance in precise treatment. In this study, we systematically evaluated hypoxia-mediated patterns together with immune characteristics of 309 OSCC patients in the TCGA training set and 97 patients in the GSE41613 testing set. We further identified two different hypoxia subtypes with distinct immune microenvironment traits and provided treatment programs for the two subclasses. In order to assess hypoxia level individually, we finally constructed a hypoxia-related risk score, which could predict the clinical outcome and immunotherapy response of OSCC patients. In summary, the recognition of different hypoxia patterns and the establishment of hypoxia-related risk score might enhance our understanding of the tumor microenvironment of OSCC and provide more personalized treatment strategies in the future.
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Then, the “glmnet” R package was performed to filter the prognosis-related hypoxia genes by LASSO Cox regression analysis with a 10-fold cross-validation.
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sections[11] "Development and Validation of Predictive Risk Score" paragraph 2
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Then, the “glmnet” R package was performed to filter the prognosis-related hypoxia genes by LASSO Cox regression analysis with a 10-fold cross-validation.
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The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.
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The paper identified two hypoxia-associated OSCC subtypes with distinct immune microenvironment traits and constructed a hypoxia-related risk score that could predict clinical outcome and immunotherapy response.
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We further identified two different hypoxia subtypes with distinct immune microenvironment traits and provided treatment programs for the two subclasses.
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sections[0] "Abstract" paragraph 1
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In order to assess hypoxia level individually, we finally constructed a hypoxia-related risk score, which could predict the clinical outcome and immunotherapy response of OSCC patients.
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The paper identified two hypoxia-associated OSCC subtypes with distinct immune microenvironment traits and constructed a hypoxia-related risk score that could predict clinical outcome and immunotherapy response.
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A 13-gene signature prognostic of HPV-negative OSCC: discovery and external validation
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usters estimated by Cibersort algorithm. (C) EPIC algorithm revealed 7 immune cells difference
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Recognizing the characteristics of different subtypes and investigating the promising strategies for each subclass are of great significance in precise treatment. In this study, we systematically evaluated hypoxia-mediated patterns together with immune characteristics of 309 OSCC patients in the TCGA training set and 97 patients in the GSE41613 testing set. We further identified two different hypoxia subtypes with distinct immune microenvironment traits and provided treatment programs for the two subclasses. In order to assess hypoxia level individually, we finally constructed a hypoxia-related risk score, which could predict the clinical outcome and immunotherapy response of OSCC patients. 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