Anoikis-related signature in liver hepatocellular carcinoma defines the YBX1/SPP1 axis by machine learning strategies and valid experiments.
J Gene Med
; 25(10): e3516, 2023 10.
Article
en En
| MEDLINE
| ID: mdl-37118998
ABSTRACT
BACKGROUND:
Liver hepatocellular carcinoma (LIHC) remains a malignant malignancy with a low cure rate. Anoikis is a newly recognized cancer hallmark. However, an Anoikis-related model has not been clarified in LIHC.METHODS:
The Anoikis-related score in the present study was created using Survival Random Forest and least absolute shrinkage and selection operator (LASSO) machine learning algorithms. Anoikis-related scores with respect to mutation analysis, immunological analysis, function annotation, and medication prediction were all thoroughly investigated.RESULTS:
The Anoikis-related score accurately predicted the patients' immunological activity, altered genes, and medication sensitivity. SPP1 immunological analysis, function annotation, medication prediction, and immunotherapy prediction were systematically investigated. SPP1 may effectively predict the outcomes of immunotherapy. SPP1 was revealed to be a mediator of LIHC cell proliferation and migration. A putative axis in LIHC was YBX1/SPP1.CONCLUSIONS:
Clinical care and the treatment plan for patients with LIHC were anticipated to benefit significantly from the established Anoikis-related score.Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Carcinoma Hepatocelular
/
Neoplasias Hepáticas
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
J Gene Med
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA MEDICA
Año:
2023
Tipo del documento:
Article
País de afiliación:
China