Anoikis‐related signature in liver hepatocellular carcinoma defines the YBX1/SPP1 axis by machine learning strategies and valid experiments

Abstract

BackgroundLiver 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.MethodsThe 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.ResultsThe 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.ConclusionsClinical care and the treatment plan for patients with LIHC were anticipated to benefit significantly from the established Anoikis‐related score.

Y-Box Binding Protein 1: Unraveling the Multifaceted Role in Cancer Development and Therapeutic Potential

“…For instance, in liver hepatocellular carcinoma, a novel Anoikisrelated score was developed, accurately predicting immunological activity, gene alterations, and medication sensitivity. SPP1 emerged as a significant predictor for immunotherapy outcomes, influencing LIHC cell behavior, with a potential YBX1/SPP1 axis identified, offering insights for improved patient care and treatment strategies [221]. Immunityrelated GTPase M (IRGM), a critical player in immune regulation, interacts with YBX1 to facilitate PD-L1 transcription, suppressing CD8+ T cell infiltration in HCC and contributing to cancer progression [222].…”