Hepatocellular carcinoma screening is associated with survival benefit in silico but needs confirmation in an in vivo analysis

MRI is the most commonly used imaging modality for HCC screening at a tertiary care transplant center

PURPOSE

In this study, we describe the patterns of hepatocellular carcinoma (HCC) screening with imaging and factors associated with imaging modality selection in a tertiary care transplant center.

METHODS

This was a retrospective study where all adult patients with cirrhosis and/or chronic hepatitis B virus infection referred for HCC screening with ultrasound (US), CT or MRI were identified during 2017. The association between imaging methods, demographic/clinical data were analyzed by uni- and multivariate analysis.

RESULTS

A total of 1437 patients were included (median age 61y, 59% male, median BMI 27.5 kg/m², median AFP 3.4 ng/mL, 37% with HCV and 87% with cirrhosis). Index screening imaging method utilization included MRI (51%), US (33%) and CT (16%). Use of US as the index imaging modality for screening was significantly associated with race/ethnicity [Odds Ratio (OR) 1.71-2.01, all p < 0.05] in multivariate analysis. Presence of cirrhosis (OR 0.29, p < 0.001) and referral by a hepatologist (OR 0.23, p < 0.001) were associated with screening with MRI in the multivariate analysis; while gender, age, BMI, etiology and income at ZIP code of residence were not significantly associated with imaging modality selection. HCC was observed in 62 patients (prevalence 4.3%). Rate of HCC detection was significantly higher with MRI vs US (5.9% vs. 1.5%, p = 0.001).

CONCLUSION

MRI was the most frequently used modality (> 50%) for HCC screening in our tertiary care center, in contrast with the current practice guidelines. Race/ethnicity, cirrhosis and referral by a hepatologist were associated with the imaging method used for HCC screening.

Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer and has poor outcomes. However, the potential molecular biological process underpinning the occurrence and development of HCC is still largely unknown. The purpose of this study was to identify the core genes related to HCC and explore their potential molecular events using bioinformatics methods. HCC-related expression profiles GSE25097 and GSE84005 were selected from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) between 306 HCC tissues and 281 corresponding noncancerous tissues were identified using GEO2R online tools. The protein-protein interaction network (PPIN) was constructed and visualized using the STRING database. Gene Ontology (GO) and KEGG pathway enrichment analyses of the DEGs were carried out using DAVID 6.8 and KOBAS 3.0. Additionally, module analysis and centrality parameter analysis were performed by Cytoscape. The expression differences of key genes in normal hepatocyte cells and HCC cells were verified by quantitative real-time fluorescence polymerase chain reaction (qRT-PCR). Additionally, survival analysis of key genes was performed by GEPIA. Our results showed that a total of 291 DEGs were identified including 99 upregulated genes and 192 downregulated genes. Our results showed that the PPIN of HCC was made up of 287 nodes and 2527 edges. GO analysis showed that these genes were mainly enriched in the molecular function of protein binding. Additionally, KEGG pathway analysis also revealed that DEGs were mainly involved in the metabolic, cell cycle, and chemical carcinogenesis pathways. Interestingly, a significant module with high centrality features including 10 key genes was found. Among these, CDK1, NDC80, HMMR, CDKN3, and PTTG1, which were only upregulated in HCC patients, have attracted much attention. Furthermore, qRT-PCR also confirmed the upregulation of these five key genes in the normal human hepatocyte cell line (HL-7702) and HCC cell lines (SMMC-7721, MHCC-97L, and MHCC-97H); patients with upregulated expression of these five key genes had significantly poorer survival and prognosis. CDK1, NDC80, HMMR, CDKN3, and PTTG1 can be used as molecular markers for HCC. This finding provides potential strategies for clinical diagnosis, accurate treatment, and prognosis analysis of liver cancer.