Objectives: Hepatic carcinoma with metastasis remains incurable, and clinical diagnostic methods lacked adequate sensitivity and specificity. Therefore, seeking effectively diagnostic biomarkers is still essential for it. RHOC  was reported to be linked to metastasis of hepatic carcinoma. However, almost all of the studies used tissues as detection samples, which was not ideal for clinical course minoring. Therefore, here, it was aimed to use PBMC samples that were not only easily accessible but also minimally invasive to determine the expression and biological interaction network of RHOC  for hepatic carcinoma with metastasis.
Methods: PBMC samples were isolated. Then, RNA-seq was performed to identify the DEGs between hepatic carcinoma with metastasis and hepatic carcinoma with solitary tumor. Subsequently, q-RT-PCR was used to verify the expression level of RHOC . Finally, bioinformatic analysis was used to present the biological interaction network of RHOC  for hepatic carcinoma with metastasis in PBMC samples.
Results: The results of both RNA-seq and q-RT-PCR showed that the expression level of RHOC  was significantly higher in the PBMC samples of hepatic carcinoma with metastasis than in those of hepatic carcinoma with solitary tumor. By using variety of bioinformatic analysis platforms, in PBMCs, 18 co-expression genes with RHOC  were identified and their interaction network showed that MYL9  and RHOC  had the highest edge evidence, and were involved in some cell migration-related pathways.
Conclusion: Our results indicated that RHOC  in PBMCs could be potentially minimally invasive indicators for the diagnosis and clinical course supervision of hepatic carcinoma with metastasis, and its biological interaction network determined based on bioinformatic methods would lay a foundation for further study of the role of RHOC  in tumor invasion and metastasis.
Keywords: RHOC, hepatic carcinoma, metastasis, PBMC, diagnosis