An integrated multigene expression panel to predict long-term survival after curative hepatectomy in patients with hepatocellular carcinoma

Abstract

Hepatocellular carcinoma (HCC) frequently recurs even after curative hepatectomy. To develop an integrated multigene expression panel, 144 patients were randomly assigned to either discovery or validation set in a 1:2 ratio. Using surgically resected HCC specimens, expression levels of 12 candidate molecular markers were determined using quantitative reverse-transcriptase PCR. In the discovery set, an expression panel was developed according to the concordance index (C-index) values for overall survival from all 4095 combinations of the 12 candidate molecular markers. Expression scores was determined with weighting according to the coefficient in a Cox regression, and patients were classified into grade 1, 2 and 3. Reproducibility was then tested in the validation set. A panel consisting of four markers, PRMT5, MAGED4, DPYSL3 and AJAP1 was selected as the optimal and most well-balanced set with a C-index value of 0.707. Patient prognosis was clearly stratified by the expression grade using this panel. In the validation set, both overall and disease-free survival rates decreased incrementally with as the grade increased. Higher grades were significantly associated with tumor multiplicity and vessel invasion. The prevalence of extrahepatic recurrences was increased in grade 3 patients. The integrated multigene expression panel clearly stratified HCC patients into low, intermediate and high risk.

Integrated multigene expression panel to prognosticate patients with gastric cancer

“…The subpopulation index was used to optimize the number of markers included in the panel, and inclusion of four markers was found to be the most objectively balanced system. To maximize performance of the expression panel, a weighting using the coefficient of each constituent was employed to determine the expression index for all patients [ 19 ]. Thereafter, patients were stratified based on their expression score (1 to 3) according to the expression index, which was a more straightforward patient stratification method compared with using continuous numeric variables.…”

“…The larger the number of markers included in the panel, the greater the number of subpopulations that patients were clustered into with a corresponding decrease in the minimal number of patients in a subpopulation. Thus, third, we used the subpopulation index, calculated as number of constituents × the minimal patient number in a subpopulation, for each number of combinations to determine the most well-balanced number of markers to be included in the expression panel [ 19 ]. Fourth, the expression index was determined with weighting according to the coefficient in a Cox regression of each constituent.…”

Targeting PRMT5 Activity Inhibits the Malignancy of Hepatocellular Carcinoma by Promoting the Transcription of HNF4α

“…Among these inhibitors, the SAM-uncompetitive PRMT5 inhibitor EPZ015666 has displayed effective anti-tumor activity in MCL xenograft animal models 25. Recent studies suggested that PRMT5 is upregulated in patient HCCs and may play a role in hepatocarcinogenesis 26-28, suggesting that targeting PRMT5 may have therapeutic effects on HCC. Nevertheless, effect of PRMT5 inhibitors on HCC remains unclear.…”