Establishment of a Prognostic Model for Hepatocellular Carcinoma Based on Bioinformatics and the Role of NR6A1 in the Progression of HCC

Abstract

Background and Aims: Generally acceptable prognostic models for hepatocellular carcinoma (HCC) are not available. This study aimed to establish a prognostic model for HCC by identifying immune-related differentially expressed genes (IR-DEGs) and to investigate the potential role of NR6A1 in the progression of HCC. Methods: Bioinformatics analysis using The Cancer Genome Atlas and ImmPort databases was used to identify IR-DEGs. Lasso Cox regression and multivariate Cox regression analysis were used to establish a prognostic model of HCC. Kaplan-Meier analysis and the receiver operating characteristic (ROC) curves were used to evaluate the performance of the prognostic model, which was further verified in the International Cancer Genome Consortium (ICGC) database. Gene set enrichment analysis was used to explore the potential pathways of NR6A1. Cell counting kit 8, colony formation, wound healing, and Transwell migration assays using Huh7 cells, and tumor formation models in nude mice were conducted. Results: A prognostic model established based on ten identified IR-DEGs including HSPA4, FABP6, MAPT, NDRG1, APLN, IL17D, LHB, SPP1, GLP1R, and NR6A1, effectively predicted the prognosis of HCC patients, was confirmed by the ROC curves and verified in ICGC database. NR6A1 expression was significantly up-regulated in HCC patients, and NR6A1 was significantly associated with a low survival rate. Gene set enrichment analysis showed the enrichment of cell cycle, mTOR, WNT, and ERBB signaling pathways in patients with high NR6A1 expression. NR6A1 promoted cell proliferation, invasiveness, migration, and malignant tumor formation and growth in vitro and in vivo. Conclusions: An effective prognostic model for HCC, based on a novel signature of 10 immune-related genes, was established. NR6A1 was up-regulated in HCC and was associated with a poor prognosis of HCC. NR6A1 promoted cell proliferation, migration, and growth of HCC, most likely through the cell cycle, mTOR, WNT, and ERBB signaling pathways.

Integrated analysis of histone lysine lactylation (Kla)-specific genes suggests that NR6A1, OSBP2 and UNC119B are novel therapeutic targets for hepatocellular carcinoma

“…In HCC, NR6A1 was identified as a prognostic marker, and associated with sorafenib resistance in HCC patients 27 . Lin et al showed that NR6A1 might inhibit the HCC immune response 28 and activate the WNT signaling pathway as well as MTOR-signaling pathway 29 , which were similar to our study. On the other hand, NR6A1 could enhance HCC proliferation and invasion in vitro and vivo 29 , which indicated that NR6A1 showed promise as a novel immune therapeutic target for HCC.…”

“…Lin et al showed that NR6A1 might inhibit the HCC immune response 28 and activate the WNT signaling pathway as well as MTOR-signaling pathway 29 , which were similar to our study. On the other hand, NR6A1 could enhance HCC proliferation and invasion in vitro and vivo 29 , which indicated that NR6A1 showed promise as a novel immune therapeutic target for HCC. OSBP2 was first served as a cytosolic protein 30 , and had a high affinity for oxysterols 31 .…”

Machine Learning-Based Identification of B4GALNT1 as a Key Player in Hepatocellular Carcinoma: A Comprehensive Bioinformatics and Structural Analysis

“…DGE (Differential gene expression) analysis was performed on the whole dataset, and 36 PC genes were identified to be differentially expressed from ML identified genes (Figure 3(F)) . After that using lasso penalized coz regression analysis theses 55 PC genes were reduced to 13 genes SEMA3F [51], B4GALNT1 [7], COLEC10 [52], CEP131 [53], APLN [54], GBA [55], SCAMP3 [56], TOMM40L [57], PYGO2 [58] and PLVAP [59] has been reported in literature while CAPN11, SPTY2D1OS and C14orf180 is not so far has been studied in LIHC. Additionally, these 13 genes from survival analysis predicted to be prognostic genes for OS of LIHC cases.…”