Non-negative matrix factorization model-based construction for molecular clustering and prognostic assessment of head and neck squamous carcinoma.
Heliyon
; 8(8): e10100, 2022 Aug.
Article
in En
| MEDLINE
| ID: mdl-35991972
Purpose: We aimed at exploring the efficacy of non-negative matrix factorization (NMF) model-based clustering for prognostic assessment of head and neck squamous carcinoma (HNSCC). Methods: The transcriptome microarray data of HNSCC samples were downloaded from The Cancer Genome Atlas (TCGA) and the Shanghai Ninth People's Hospital. R software packages were used to establish NMF clustering, from which relevant prognostic models were developed. Results: Based on NMF, samples were allocated into 2 subgroups. Predictive models were constructed using differentially expressed genes between the two subgroups. The high-risk group was associated with poor prognostic outcomes. Moreover, multi-factor Cox regression analysis revealed that the predictive model was an independent prognostic predictor. Conclusion: The NMF-based prognostic model has the potential for prognostic assessment of HNSCC.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Prognostic_studies
Language:
En
Journal:
Heliyon
Year:
2022
Document type:
Article
Affiliation country:
China
Country of publication:
United kingdom