Mononuclear phagocyte system-related multi-omics features yield head and neck squamous cell carcinoma subtypes with distinct overall survival, drug, and immunotherapy responses.
J Cancer Res Clin Oncol
; 150(2): 37, 2024 Jan 27.
Article
em En
| MEDLINE
| ID: mdl-38279056
ABSTRACT
BACKGROUND:
Recent research reported that mononuclear phagocyte system (MPS) can contribute to immune defense but the classification of head and neck squamous cell carcinoma (HNSCC) patients based on MPS-related multi-omics features using machine learning lacked.METHODS:
In this study, we obtain marker genes for MPS through differential analysis at the single-cell level and utilize "similarity network fusion" and "MoCluster" algorithms to cluster patients' multi-omics features. Subsequently, based on the corresponding clinical information, we investigate the prognosis, drugs, immunotherapy, and biological differences between the subtypes. A total of 848 patients have been included in this study, and the results obtained from the training set can be verified by two independent validation sets using "the nearest template prediction".RESULTS:
We identified two subtypes of HNSCC based on MPS-related multi-omics features, with CS2 exhibiting better predictive prognosis and drug response. CS2 represented better xenobiotic metabolism and higher levels of T and B cell infiltration, while the biological functions of CS1 were mainly enriched in coagulation function, extracellular matrix, and the JAK-STAT signaling pathway. Furthermore, we established a novel and stable classifier called "getMPsub" to classify HNSCC patients, demonstrating good consistency in the same training set. External validation sets classified by "getMPsub" also illustrated similar differences between the two subtypes.CONCLUSIONS:
Our study identified two HNSCC subtypes by machine learning and explored their biological difference. Notably, we constructed a robust classifier that presented an excellent classifying prediction, providing new insight into the precision medicine of HNSCC.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Multiômica
/
Neoplasias de Cabeça e Pescoço
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article