An individualized prognostic signature and multi-omics distinction for early stage hepatocellular carcinoma patients with surgical resection

Abstract

Previously reported prognostic signatures for predicting the prognoses of postsurgical hepatocellular carcinoma (HCC) patients are commonly based on predefined risk scores, which are hardly applicable to samples measured by different laboratories. To solve this problem, using gene expression profiles of 170 stage I/II HCC samples, we identified a prognostic signature consisting of 20 gene pairs whose within-sample relative expression orderings (REOs) could robustly predict the disease-free survival and overall survival of HCC patients. This REOs-based prognostic signature was validated in two independent datasets. Functional enrichment analysis showed that the patients with high-risk of recurrence were characterized by the activations of pathways related to cell proliferation and tumor microenvironment, whereas the low-risk patients were characterized by the activations of various metabolism pathways. We further investigated the distinct epigenomic and genomic characteristics of the two prognostic groups using The Cancer Genome Atlas samples with multi-omics data. Epigenetic analysis showed that the transcriptional differences between the two prognostic groups were significantly concordant with DNA methylation alternations. The signaling network analysis identified several key genes (e.g. TP53, MYC) with epigenomic or genomic alternations driving poor prognoses of HCC patients. These results help us understand the multi-omics mechanisms determining the outcomes of HCC patients.

Evaluating hepatocellular carcinoma cell lines for tumour samples using within‐sample relative expression orderings of genes

“…Using the REOs of HCC‐specific gene pairs from comparisons with the six cancer types, we found that eight of 24 HCC cell lines collected from the Cancer Cell Line Encyclopedia (CCLE) resemble HCC tumours well, whereas the other 16 HCC cell lines are closer to at least one of the six cancer types than to HCC itself. In addition, we showed that all of the confirmed eight HCC cell lines are likely to be metastatic, based on a REO‐based prognostic signature for early stage HCC patients . In short, this study provides a helpful guide to select proper HCC cell lines as models for HCC.…”

Signature consist of nine differentially methylated gene pairs to predict the prognosis for stage II colorectal cancer patients

“…Here, we applied RMOs procedure in the construction of the prognosis methylation signature. The prognostic signature base on RMOs is robust against experimental batch effects and data normalization, and can be easily applied at the individual level to sample which are measured in different laboratories [13]. We performed Cox regression variable analyses to further investigate the association between RFS with candidate gene pairs and the 9-gene-pair signature.…”

“…Besides, the prognosis ability of this score is better than any individual candidate gene pair. This further emphasized the importance of developing a comprehensive signature for cancers [13]. We also performed multivariable Cox regression to estimate the association between RFS and the signature.…”

“…To our best knowledge, the prognostic signatures based on gene-specific DNA methylation for CRC patients are still lacking. Moreover, gene expression files are prone to systematic measurement biases, which normally caused by batch effects in experiment procedures [11][12][13]. Thus, a signature, which takes into consideration data normalization and batch effects, is highly required to be generally used to independent datasets [13].…”

“…Moreover, gene expression files are prone to systematic measurement biases, which normally caused by batch effects in experiment procedures [11][12][13]. Thus, a signature, which takes into consideration data normalization and batch effects, is highly required to be generally used to independent datasets [13]. Furthermore, it has been emphasized that patients in different stage of CRC should be treated differently [2].…”