Circulating microRNAs as biomarkers for stratifying different phases of liver cancer progression and response to therapy

Abstract

Hepatocellular carcinoma (HCC) is the most common liver cancer and is among the leading causes of cancer-related death worldwide. There is no reliable biomarker for the early diagnosis of HCC. Circulating microRNAs (miRNAs) have attracted attention as potential biomarkers of disease. By small-RNA next-generation sequencing, the analysis of serum miRNAs led to the identification of molecular signatures able to discriminate advanced HCC from early HCC (n = 246); advanced HCC from CIRRHOSIS (n = 299); advanced HCC from HEALTHY (n = 320); HEALTHY from early HCC (n = 343); and HEALTHY from CIRRHOSIS (n = 414). Cirrhotic patients and early HCC patients exhibited similar serum miRNA profiles, yet a small number of miRNAs (n = 57) were able to distinguish these two classes of patients. A second objective of the study was to identify serum miRNAs capable of predicting the response to therapy in patients with advanced HCC. All patients were treated with sorafenib as first-line therapy: 24 were nonresponsive and 24 responsive. Analysis of circulating miRNAs revealed a 54 miRNAs signature able to separate the two subgroups. This study suggested that circulating miRNAs could be useful biomarkers for monitoring patients with liver diseases ranging from cirrhosis to advanced HCC and possibly predicting susceptibility to first-line treatment based on sorafenib.

Keywords: Circulating biomarkers; Diagnostic biormarkers; Early diagnosis; Hepatocellular carcinoma; Next generation sequencing; Predictive biomarkers; Sorafenib; microRNA.

Figure 1

Classification of phases of human HCC. (a,b) PCA and unsupervised hierarchical clustering based on serum miRNAs selected by a multigroup analysis (ANOVA) (n = 557 miRNAs, p value < 0.01). Samples were from normal individuals (n = 11) and patients with cirrhosis (n = 14), early HCC (n = 11) or advanced HCC (n = 12). The analyses could visibly separate three groups: normal individuals (Normal), advanced HCC (HCC) and patients with cirrhosis (CE)/early HCC (HCC_early).

Figure 2

A panel of 57 serum miRNAs differentiates patients affected by early HCC or cirrhosis. The comparison between serum miRNA levels of patients affected by cirrhosis (CE) or early HCC identified a panel of 57 miRNAs (p value < 0.01, FC > 1.33 UP or DOWN) able to classify the two categories of patients, as evidenced by hierarchical clustering and PAM analyses. Albeit with variable probabilities, both analyses correctly classified 100% of the samples. The list of miRNAs is in Suppl Table 7.

Figure 3

A panel of 54 serum miRNAs predicts sorafenib response in patients with advanced HCC. (a,b) PCA and unsupervised hierarchical clustering classified the samples in two main groups, each including either R or NR patients. Overall, 23 of the 24 samples were included in the correct group. (c) Like PCA and clustering analyses, PAM confirmed the good classification prediction of the miRNAs panel, with only LG932 misclassified. Notably, sample LG932 turned out to be NR at the second clinical assessment, 4 months after start of therapy. R = responder; NR = non-responder. The list of miRNAs (p-value < 0.05, FC > 1.35 UP or DOWN) is in Suppl Table 8.

Figure 4

Validation of the 54 miRNAs signature on 48 patients with advanced HCC treated with sorafenib as first line therapy. Sera from all patients were collected at diagnosis, before the start of therapy. PCA analysis (a) and unsupervised hierarchical clustering (b) was performed by using the 54 miRNAs signature (Supplementary Table 8) on all 48 samples. The analysis identified two main clusters: one made mainly of R patients; the second mainly of NR patients: overall 41 of 48 patients grouped in the correct cluster. (C) PAM analysis also produced a correct prediction in 41 of 48 patients. Statistical performances of the analyses are shown in Table 3.