Liver cancer with concomitant TP53 and CTNNB1 mutations: a case report

Hepatocellular Carcinomas with Concomitant Mutations of TERT, TP53, and CTNNB1: Is There a Role for Artificial Intelligence?

TP53, CTNNB1, and TERT-promoter mutations are the most common driver mutations in hepatocellular carcinoma (HCC). The morphological and genetical HCC heterogeneities are difficult to discriminate by the eye of the pathologist. Here, we describe two rare cases of HCC with simultaneous co-mutation of all three of genes, which represent a poorly described occurrence in the literature. In these two cases, areas with different tumor grade and different β-catenin and Glutamine Synthetase expression (performed by automated immunohistochemistry) were observed. NGS analysis was performed in these different areas, to check for potential diversity of mutation burden on the different regions, but no differences were found: all micro-areas analyzed showed the co-presence of mutations in TP53, CTNNB1, and TERT. The evidence that all mutations were found in all the different areas analyzed by NGS leads to hypothesize that the tumor is not composed of different clones harboring different mutations. All the variants are harbored by the same neoplastic clone, albeit leading to different phenotypes. Mutation prediction Artificial Intelligence models could help the morpho-genetic classification of HCC in the future, since they can find variabilities not obvious to the human eye, with increased sensitivity, specificity and reproducibility.

Multi-omics subtyping of hepatocellular carcinoma patients using a Bayesian network mixture model

Comprehensive molecular characterization of cancer subtypes is essential for predicting clinical outcomes and searching for personalized treatments. We present bnClustOmics, a statistical model and computational tool for multi-omics unsupervised clustering, which serves a dual purpose: Clustering patient samples based on a Bayesian network mixture model and learning the networks of omics variables representing these clusters. The discovered networks encode interactions among all omics variables and provide a molecular characterization of each patient subgroup. We conducted simulation studies that demonstrated the advantages of our approach compared to other clustering methods in the case where the generative model is a mixture of Bayesian networks. We applied bnClustOmics to a hepatocellular carcinoma (HCC) dataset comprising genome (mutation and copy number), transcriptome, proteome, and phosphoproteome data. We identified three main HCC subtypes together with molecular characteristics, some of which are associated with survival even when adjusting for the clinical stage. Cluster-specific networks shed light on the links between genotypes and molecular phenotypes of samples within their respective clusters and suggest targets for personalized treatments.

Combined effect of recombinant human adenovirus p53 and curcumin in the treatment of liver cancer

The development of an effective therapeutic intervention for liver cancer is a worldwide challenge that remains to be adequately addressed. Of note, TP53, which encodes the p53 protein, is an important tumor suppressor gene, 61% of TP53 is functionally inactivated in liver cancer. Recombinant human adenovirus p53 (rAd-p53) is the first commercial product that has been used for gene therapy. In the present study, the combined mechanistic effects of rAd-p53 and curcumin, a naturally occurring compound with previously reported anti-inflammatory, antioxidant and anti-cancer properties, were assessed in liver cancer cells, using HepG2 cells as the model cell line. The administration of either curcumin or rAd-p53 promoted apoptosis, suppressed epithelial-mesenchymal transition (EMT) and blocked G2/M phase progression in HepG2 cells, which were potentiated further when both agents were applied together. Combined rAd-p53 and curcumin treatment resulted in higher p53 (P<0.01) and p21 (P<0.01) expression compared with rAd-p53 or curcumin were added alone, suggesting an additive effect on TP53 expression. Additionally, curcumin and rAd-p53 were demonstrated to regulate the activation of mitogen-activated protein kinases (MAPKs) ERK1/2, p38 MAPK and JNK. These results indicated that the combination of rAd-p53 with curcumin synergistically potentiates apoptosis and inhibit EMT compared with either rAd-p53 or curcumin treatment alone via the regulation of TP53 regulation. Mechanistically, this effect on TP53 expression may involve the ERK1/2, p38 MAPK and JNK signaling pathways. The current study provides new insights that can potentially advance the development of therapeutic strategies for liver cancer treatment.

Characterization of HCC Mouse Models: Towards an Etiology-Oriented Subtyping Approach

Murine liver tumors often fail to recapitulate the complexity of human hepatocellular carcinoma (HCC), which might explain the difficulty to translate preclinical mouse studies into clinical science. The aim of this study was to evaluate a subtyping approach for murine liver cancer models with regard to etiology-defined categories of human HCC, comparing genomic changes, histomorphology, and IHC profiles. Sequencing and analysis of gene copy-number changes [by comparative genomic hybridization (CGH)] in comparison with etiology-dependent subsets of HCC patients of The Cancer Genome Atlas (TCGA) database were conducted using specimens (75 tumors) of five different HCC mouse models: diethylnitrosamine (DEN) treated wild-type C57BL/6 mice, c-Myc and AlbLTαβ transgenic mice as well as TAK1^LPC-KO and Mcl-1^Δhep mice. Digital microscopy was used for the assessment of morphology and IHC of liver cell markers (A6-CK7/19, glutamine synthetase) in mouse and n = 61 human liver tumors. Tumor CGH profiles of DEN-treated mice and c-Myc transgenic mice matched alcohol-induced HCC, including morphologic findings (abundant inclusion bodies, fatty change) in the DEN model. Tumors from AlbLTαβ transgenic mice and TAK1^LPC-KO models revealed the highest overlap with NASH-HCC CGH profiles. Concordant morphology (steatosis, lymphocyte infiltration, intratumor heterogeneity) was found in AlbLTαβ murine livers. CGH profiles from the Mcl-1^Δhep model displayed similarities with hepatitis-induced HCC and characteristic human-like phenotypes (fatty change, intertumor and intratumor heterogeneity). IMPLICATIONS: Our findings demonstrate that stratifying preclinical mouse models along etiology-oriented genotypes and human-like phenotypes is feasible. This closer resemblance of preclinical models is expected to better recapitulate HCC subgroups and thus increase their informative value.

Decreased long intergenic noncoding RNA P7 predicts unfavorable prognosis and promotes tumor proliferation via the modulation of the STAT1-MAPK pathway in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common neoplasm and is a leading cause of cancer-related death. Despite advances in the diagnosis and management of HCC, its prognosis remain unfavorable. Accumulating evidence has shown that long intergenic noncoding RNAs (lincRNAs) play central roles in the development of HCC. In this study, we identified a long intergenic noncoding RNA referred to as lincRNA P7 in HCC and explored its clinical significance and biological functions in HCC. The expression level of lincRNA P7 was significantly aberrantly deceased in HCC cancer tissues and cells lines. Gain- and loss-of-function experiments revealed that overexpression of lincRNA P7 significantly inhibited the proliferation of HCC-derived cancer cells, whereas lincRNA P7 knockdown promoted cell growth. Mechanistically, lincRNA P7 blocked Erk1/2 signaling and repressed activation of the STAT1 pathway. In nude mouse models, we show that overexpression of lincRNA P7 effectively repressed HCC xenograft tumor growth in vivo. Moreover, a clinical investigation demonstrated that down-regulated lincRNA P7 expression correlated with liver cirrhosis, Hepatitis B virus (HBV) infection, clinical stage of the tumor and recurrence. A Kaplan-Meier survival analysis showed that the expression of lincRNA P7 was significantly related to overall survival (P = 0.003) and recurrence-free survival (P = 0.031). Collectively, our findings suggested that the down-regulation of lincRNA P7 predicts poor clinical outcomes for HCC patients and might be a powerful candidate prognostic biomarker and target in HCC.

Circumventing intratumoral heterogeneity to identify potential therapeutic targets in hepatocellular carcinoma

BACKGROUND & AIMS

Identifying target genetic mutations in hepatocellular carcinoma (HCC) for therapy is made challenging by intratumoral heterogeneity. Circulating cell-free DNAs (cfDNA) may contain a more complete mutational spectrum compared to a single tumor sample. This study aimed to identify the most efficient strategy to identify all the mutations within heterogeneous HCCs.

METHODS

Whole exome sequencing (WES) and targeted deep sequencing (TDS) were carried out in 32 multi-regional tumor samples from five patients. Matched preoperative cfDNAs were sequenced accordingly. Intratumoral heterogeneity was measured using the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Profiling efficiencies of single tumor specimen and cfDNA were compared. The strategy with the highest performance was used to screen for actionable mutations.

RESULTS

Variable levels of heterogeneity with branched and parallel evolution patterns were observed. The heterogeneity decreased at higher sequencing depth of TDS compared to measurements by WES (28.1% vs. 34.9%, p<0.01) but remained unchanged when additional samples were analyzed. TDS of single tumor specimen identified an average of 70% of the total mutations from multi-regional tissues. Although genome profiling efficiency of cfDNA increased with sequencing depth, an average of 47.2% total mutations were identified using TDS, suggesting that tissue samples outperformed it. TDS of single tumor specimen in 66 patients and cfDNAs in four unresectable HCCs showed that 38.6% (26/66 and 1/4) of patients carried mutations that were potential therapeutic targets.

CONCLUSIONS

TDS of single tumor specimen could identify actionable mutations targets for therapy in HCC. cfDNA may serve as secondary alternative in profiling HCC genome.

LAY SUMMARY

Targeted deep sequencing of single tumor specimen is a more efficient method to identify mutations in hepatocellular carcinoma made from mixed subtypes compared to circulating cell-free DNA in blood. cfDNA may serve as secondary alternative in profiling HCC genome. Identifying mutations may help clinicians choose targeted therapy for better individual treatments.

The significance of low levels of LINC RP1130-1 expression in human hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common neoplasms. Little progress has been made in the diagnosis and treatment of HCC and its prognosis remains poor. Studies have increasingly found that long non-coding RNA (lncRNA) is involved in the regulation of the occurrence and development of HCC. To investigate the diagnostic and prognostic value of lncRNA in HCC, the current study examined 25 lncRNAs with differing levels of expression (according to the fold change) in microarray databases. Expression of LINC RP1130-1 was found to be markedly down-regulated in 51 HCC tissues compared to matching adjacent non-tumor liver tissues. The pattern of expression and clinical significance of LINC RP1130-1 were examined in HCC. The area under the receiver operating characteristic (ROC) curve was 0.74 for LINC RP1130-1. The expression of LINC RP1130-1 was associated with clinical stage, the number of tumors, portal vein tumor thrombus (PVTT), and microvascular invasion (MVI). More importantly, patients with a low level of LINC RP1130-1 expression had a shorter recurrence-free survival (RFS) (n = 51, p < 0.05) than those with a high level of LINC RP1130-1 expression. Taken together, these findings indicate that a low level of LINC RP1130-1 expression in patients with HCC may be a powerful tumor biomarker, with potential clinical use in diagnosing and predicting the prognosis for patients with HCC.