Exploration of Combinational Therapeutic Strategies for HCC Based on TCGA HCC Database

Abstract

Hepatocellular carcinoma (HCC) is one of the most deadly types of cancer. Sorafenib is currently the only available first-line molecular targeted drug approved by the FDA for HCC. However, primary and secondary resistance is often encountered with treatment with sorafenib. Genomic alterations found in HCC represent potential targets to develop new drugs or new combinational strategies against this type of cancer. Here we analyzed genomic alterations from the TCGA database of HCC samples and the corresponding targeted drugs available to the clinic to identify candidate drugs that might hold promise when used in combination with sorafenib. Our results revealed that IL6, JAK1, LEPR and RAF1 related pathways were commonly altered in HCC, which have targeted drugs available in medical practice. Fourteen genes with available targeting drugs were frequently altered in HCC. The pathways and gene targets with the respective targeted drugs warrant further evaluation in clinical trials to determine their therapeutic value in the treatment of HCC, alone or in combination with sorafenib. In summary, the analysis of TCGA, identified a series of pathways with targeted drugs available that were altered in HCC. Combination treatment with specific targeted drugs, depending on the altered pathways found in individuals may provide a better treatment strategy that will ultimately improve individual patient survival.

Exploring the metastasis-related biomarker and carcinogenic mechanism in liver cancer based on single cell technology

“…EBF1 was reported as a B cell differentiation regulatory factor, and the EBF1 can interact with the transcription factor JAK2 to inhibit the transcription of PAX5 affecting B cell functional integrality [ 84 ], the EBF1 acted as a negative regulator of AKR1B1, the induced EBF1 expression suppressed the AKR1B1 expression resulting in attenuated gastric cancer growth and invasiveness [ 85 ], meanwhile, the EBF1 also acts as a powerful repressor of B lymphocyte-induced maturation protein-1 (Blimp-1) to block B cell maturation [ 86 ], the high expression of EBF1 in triple-negative breast cancer (TNBC) has a pivotal role in tumorigenicity, while depletion of EBF1 induces significantly tumor cell mitophagy and growth inhibition [ 87 ]. Our study indicated that the EBF1 as the upstream regulator was positively correlated with NDUFA4L2 expression, suggesting the drug combination targeted EBF1 and NDUFA4L2 are benefit to cancer therapy [ 88 ], such as the combination of Mirin and Vorinostat, PLX-4720 and THR-101. The overexpression of NDUFA4L2 significantly upregulated the EBF1, which as a potential transcription factor may be promote the NDUFA4L2 expression through the positive feedback regulation mechanism, while the NDUFA4L2 as the actual metastasis-promoting factor involved in HCC metastasis.…”

A prognostic exosome-related long non-coding RNAs risk model related to the immune microenvironment and therapeutic responses for patients with liver hepatocellular carcinoma

“…The LIHC dataset containing RNA sequences and information on clinical characteristics was derived from TCGA ( http://cancergenome.nih.gov/ ) [ 19 ]. Samples were processed as follows: (1) Excised samples of primary tumors; (2) Samples with overall survival (OS) greater than 30 days; (3) Only samples with complete data of transcriptome expression and clinical prognostic information were kept.…”

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies

“…Patients without complete information were excluded. Finally, we selected 365 and 221 patients from TCGA ( 9 ) and GSE14520, respectively, and GSE14520 was used for external validation. Since data were obtained from two databases, to ensure the data can be compared and reduce batch effects, transcript per million values were log2 transformed and normalized using the R package.…”