Nonlinear tumor evolution from dysplastic nodules to hepatocellular carcinoma

Dysfunction of CCT3-associated network signals for the critical state during progression of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors and is a serious threat to human health; thus, early diagnosis and adequate treatment are essential. However, there are still great challenges in identifying the tipping point and detecting early warning signals of early HCC. In this study, we aimed to identify the tipping point (critical state) of and key molecules involved in hepatocarcinogenesis based on time series transcriptome expression data of HCC patients. The phase from veHCC (very early HCC) to eHCC (early HCC) was identified as the critical state in HCC progression, with 143 genes identified as key candidate molecules by combining the DDRTree (dimensionality reduction via graph structure learning) and DNB (dynamic network biomarker) methods. Then, we ranked the candidate genes to verify their mRNA levels using the diethylnitrosamine (DEN)-induced HCC mouse model and identified five early warning signals, namely, CCT3, DSTYK, EIF3E, IARS2 and TXNRD1; these signals can be regarded as the potential early warning signals for the critical state of HCC. We identified CCT3 as an independent prognostic factor for HCC, and functions of CCT3 involving in the "MYCtargets_V1" and "E2F-Targets" are closely related to the progression of HCC. The predictive method combining the DDRTree and DNB methods can not only identify the key critical state before cancer but also determine candidate molecules of critical state, thus providing new insight into the early diagnosis and preemptive treatment of HCC.

Identification of chromosomal instability-associated genes as hepatocellular carcinoma progression-related biomarkers to guide clinical diagnosis, prognosis and therapy

Hepatocellular carcinoma (HCC) is a type of cancer characterized by high heterogeneity and a complex multistep progression process. Significantly-altered biomarkers for HCC need to be identified. Differentially expressed genes and weighted gene co-expression network analyses were used to identify progression-related biomarkers. LASSO-Cox regression and random forest algorithms were used to construct the progression-related prognosis (PRP) score. Three chromosomal instability-associated genes (KIF20A, TOP2A, and TTK) have been identified as progression-related biomarkers. The robustness of the PRP scores were validated using four independent cohorts. Immune status was observed using the single-sample gene set enrichment analysis (ssGSEA). Comprehensive analysis showed that the patients with high PRP score had wider genomic alterations, more malignant phenotypes, and were in a state of immunosuppression. The diagnostic models constructed via logistic regression based on the three genes showed satisfactory performances in distinguishing HCC from cirrhotic tissues or dysplastic nodules. The nomogram combining PRP scores with clinical factors had a better performance in predicting prognosis than the tumor node metastasis classification (TNM) system. We further confirmed that KIF20A, TOP2A, and TTK were highly expressed in HCC tissues than in cirrhotic tissues. Downregulation of all three genes aggravated chromosomal instabilities in HCC and suppressed HCC cells viability both in vitro and in vivo. Overall, our study highlights the important roles of chromosomal instability-associated genes during the progression of HCC and their potential clinical diagnosis and prognostic value and provides promising new ideas for developing therapeutic strategies to improve the outcomes of HCC patients.

Characterisation of dysplastic liver nodules using low-pass DNA sequencing and detection of chromosome arm-level abnormalities in blood-derived cell-free DNA

High-grade dysplasia carries significant risk of transformation to hepatocellular carcinoma (HCC). Despite this, at the current standard of care, all non-malignant hepatic nodules including high-grade dysplastic nodules are managed similarly. This is partly related to difficulties in distinguishing high-risk pathology in the liver. We aimed to identify chromosome arm-level somatic copy number alterations (SCNAs) that characterise the transition of liver nodules along the cirrhosis-dysplasia-carcinoma axis. We validated our findings on an independent cohort using blood-derived cell-free DNA. A repository of non-cancer DNA sequences obtained from patients with HCC (n = 389) was analysed to generate cut-off thresholds aiming to minimise false-positive SCNAs. Tissue samples representing stages from the multistep process of hepatocarcinogenesis (n = 184) were subjected to low-pass whole genome sequencing. Chromosome arm-level SCNAs were identified in liver cirrhosis, dysplastic nodules, and HCC to assess their discriminative capacity. Samples positive for 1q+ or 8q+ arm-level duplications were likely to be either HCC or high-grade dysplastic nodules as opposed to low-grade dysplastic nodules or cirrhotic tissue with an odds ratio (OR) of 35.5 (95% CI 11.5-110) and 16 (95% CI 6.4-40.2), respectively (p < 0.0001). In an independent cohort of patients recruited from Nottingham, UK, at least two out of four alterations (1q+, 4q-, 8p-, and 8q+) were detectable in blood-derived cell-free DNA of patients with HCC (n = 22) but none of the control patients with liver cirrhosis (n = 9). Arm-level SCNAs on 1q+ or 8q+ are associated with high-risk liver pathology. These can be detected using low-pass sequencing of cell-free DNA isolated from blood, which may be a future early cancer screening tool for patients with liver cirrhosis. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

The landscape of gene mutations in cirrhosis and hepatocellular carcinoma

Chronic liver disease and primary liver cancer are a massive global problem, with a future increase in incidences predicted. The most prevalent form of primary liver cancer, hepatocellular carcinoma, occurs after years of chronic liver disease. Mutations in the genome are a causative and defining feature of all cancers. Chronic liver disease, mostly at the cirrhotic stage, causes the accumulation of progressive mutations which can drive cancer development. Within the liver, a Darwinian process selects out dominant clones with selected driver mutations but also leaves a trail of passenger mutations which can be used to track the evolution of a tumour. Understanding what causes specific mutations and how they combine with one another to form cancer is a question at the heart of understanding, preventing and tackling liver cancer. Herein, we review the landscape of gene mutations in cirrhosis, especially those paving the way toward hepatocellular carcinoma development, that have been characterised by recent studies capitalising on technological advances in genomic sequencing. With these insights, we are beginning to understand how cancers form in the liver, particularly on the background of chronic liver disease. This knowledge may soon lead to breakthroughs in the way we detect, diagnose and treat this devastating disease.

Genomic structures of dysplastic nodule and concurrent hepatocellular carcinoma

Although high-grade dysplastic nodule (HGDN) is a preneoplastic lesion that precedes hepatocellular carcinoma (HCC), the genomic structures of HGDN in conjunction with HCC remain elusive. The objective of this study was to identify genomic alterations of HGDN and its difference from HCC that may drive HGDN progression to HCC. We analyzed 16 regions of paired HGDN and HCC from 6 patients using whole-exome sequencing to find somatic mutation and copy number alteration (CNA) profiles of HGDN and HCC. The numbers of mutations, driver mutations, and CNAs of HGDNs were not significantly different from those of HCCs. We identified that the CNA gain of 1q25.3-1q42.13 was predominant in the HCCs compared with that in the HGDNs. Two cases (one nodule-in-nodule case and another case with closely attached HCC and HGDN) showed several overlapped driver mutations (CTNNB1 and CEBPA) and CNAs (losses of CDKN2A, RB1, and TP53) between HGDNs and HCCs, suggesting their roles in the early HCC development. The other 4 cases with spatially separated HCCs and HGDNs showed few overlapped alterations between the paired HCCs and HGDNs. Mutations in ERBB2 and CCND1, and CNAs (gains of CTNNB1, MET, and SMO and losses of PTEN, TP53, and SETD2) were identified as "HCC predominant," suggesting their roles in the progression of HGDN to HCC. Our data show that HCCs are direct descendants of HGDNs in some cases, but there is no direct evidence of such relationship in spatially separated cases. Genomic features of HGDN identified in this study provide a useful resource for dissecting clues for the genetic diagnosis of HGDN and HCC.

Polymorphisms and expression pattern of circular RNA circ-ITCH contributes to the carcinogenesis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks the sixth most common cancer and the third cause of cancer-related mortality worldwide. Recent studies identified that circ-ITCH Suppresses mutiple cancers proliferation via inhibiting the Wnt/beta-Catenin pathway. In current study, conducted a genetic association study together with epidemiological follow-up study to delineate the role of circ-ITCH in the development and progression of HCC. we found rs10485505 (adjusted OR =1.18; 95% CI=1.06-1.31; P value =3.1×10^-3) and rs4911154 (adjusted OR =1.27; 95% CI=1.14-1.43; P value =3.7×10^-5) were significantly associated with increased HCC risk. The expression level of circ-ITCH was significantly lower in HCC tissues, compared with that in adjacent tissues (P value < 0.001). Cox regression analysis indicated that high expression of circ-ITCH was associated with favorable survival of HCC (HR=0.45; 95% CI=0.29-0.68; P value < 0.001). These results indicate that circ-ITCH may have an inhibitory effect on HCC, and could serve as susceptibility and prognostic biomarkers for HCC patients.

The evolution of tumour phylogenetics: principles and practice

Rapid advances in high-throughput sequencing and a growing realization of the importance of evolutionary theory to cancer genomics have led to a proliferation of phylogenetic studies of tumour progression. These studies have yielded not only new insights but also a plethora of experimental approaches, sometimes reaching conflicting or poorly supported conclusions. Here, we consider this body of work in light of the key computational principles underpinning phylogenetic inference, with the goal of providing practical guidance on the design and analysis of scientifically rigorous tumour phylogeny studies. We survey the range of methods and tools available to the researcher, their key applications, and the various unsolved problems, closing with a perspective on the prospects and broader implications of this field.