首页|Ningbo Medical Center Lihuili Hospital Reports Findings in Machine Learning (Development of a novel lncRNA-derived immune gene score using machine learning-based ensembles for predicting the survival of HCC)
Ningbo Medical Center Lihuili Hospital Reports Findings in Machine Learning (Development of a novel lncRNA-derived immune gene score using machine learning-based ensembles for predicting the survival of HCC)
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NETL
NSTL
Springer Nature
New research on Machine Learning is the subject of a report. According to news reporting originating in Ningbo, People’s Republic of China, by NewsRx journalists, research stated, “Long noncoding RNAs (lncRNAs) are implicated in the tumor immunology of hepatocellular carcinoma (HCC). HCC mRNA and lncRNA expression profiles were used to extract immune-related genes with the ImmPort database, and immune-related lncRNAs with the ImmLnc algorithm.” Financial support for this research came from Ningbo special support program for high-level personnel recruitment. The news reporters obtained a quote from the research from Ningbo Medical Center Lihuili Hospital, “The MOVICS package was used to cluster immune-related mRNA, immune-related lncRNA, gene mutation and methylation data on HCC from the TCGA. GEO and ICGC datasets were used to validate the model. Data from single-cell sequencing was used to determine the expression of genes from the model in various immune cell types. With this model, the area under the curve (AUC) for 1-, 3- and 5-year survival of HCC patients was 0.862, 0.869 and 0.912, respectively. Single-cell sequencing showed EREG was significantly expressed in a variety of immune cell types. Knockdown of the EREG target gene resulted in significant anti-apoptosis, pro-proliferation and pro-migration effects in HepG2 and HUH7 cells. Moreover, serum and liver tissue EREG levels in HCC patients were significantly higher than those of healthy control patients. We built a prognostic model with good accuracy for predicting HCC patient survival.”
NingboPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesGeneticsMachine Learning
NETL
NSTL
Springer Nature
