Genomic copy number alterations with transcriptional deregulation at 6p identify an aggressive HCC phenotype

Construction and validation of a novel IGFBP3-related signature to predict prognosis and therapeutic decision making for Hepatocellular Carcinoma

Background

IGFBP3 plays a pivotal role in carcinogenesis by being anomalously expressed in some malignancies. However, the clinical value of IGFBP3 and the role of IGFBP3-related signature in HCC remain unclear.

Methods

Multiple bioinformatics methods were used to determine the expression and diagnostic values of IGFBP3. The expression level of IGFBP3 was validated by RT-qPCR and IHC. A IGFBP3-related risk score (IGRS) was built via correlation analysis and LASSO Cox regression analysis. Further analyses, including functional enrichment, immune status of risk groups were analyzed, and the role of IGRS in guiding clinical treatment was also evaluated.

Results

IGFBP3 expression was significantly downregulated in HCC. IGFBP3 expression correlated with multiple clinicopathological characteristics and demonstrated a powerful diagnostic capability for HCC. In addition, a novel IGRS signature was developed in TCGA, which exhibited good performance for prognosis prediction and its role was further validated in GSE14520. In TCGA and GSE14520, Cox analysis also confirmed that the IGRS could serve as an independent prognostic factor for HCC. Moreover, a nomogram with good accuracy for predicting the survival of HCC was further formulated. Additionally, enrichment analysis showed that the high-IGRS group was enriched in cancer-related pathways and immune-related pathways. Additionally, patients with high IGRS exhibited an immunosuppressive phenotype. Therefore, patients with low IGRS scores may benefit from immunotherapy.

Conclusions

IGFBP3 can act as a new diagnostic factor for HCC. IGRS signature represents a valuable predictive tool in the prognosis prediction and therapeutic decision making for Hepatocellular Carcinoma.

Genomic Profiling of Combined Hepatocellular Cholangiocarcinoma Reveals Genomics Similar to Either Hepatocellular Carcinoma or Cholangiocarcinoma

PURPOSE

Combined hepatocellular cholangiocarcinoma (cHCC-CCA) is a rare, aggressive primary liver carcinoma, with morphologic features of both hepatocellular carcinomas (HCC) and liver cholangiocarcinomas (CCA).

METHODS

The genomic profiles of 4,975 CCA, 1,470 HCC, and 73 cHCC-CCA cases arising from comprehensive genomic profiling in the course of clinical care were reviewed for genomic alterations (GA), tumor mutational burden, microsatellite instability status, genomic loss of heterozygosity, chromosomal aneuploidy, genomic ancestry, and hepatitis B virus status.

RESULTS

In cHCC-CCA, GA were most common in TP53 (65.8%), TERT (49.3%), and PTEN (9.6%), and 24.6% cHCC-CCA harbored potentially targetable GA. Other GA were predominantly associated with either HCC or CCA, including, but not limited to, TERT, FGFR2, IDH1, and presence of hepatitis B virus. On the basis of these features, a machine learning (ML) model was trained to classify a cHCC-CCA case as CCA-like or HCC-like. Of cHCC-CCA cases, 16% (12/73) were ML-classified as CCA-like and 58% (42/73) cHCC-CCA were ML-classified as HCC-like. The ML model classified more than 70% of cHCC-CCA as CCA-like or HCC-like on the basis of genomic profiles, without additional clinico-pathologic input.

CONCLUSION

These findings demonstrate the use of ML for classification as based on a targeted exome panel used during routine clinical care. Classification of cHCC-CCA by genomic features alone creates insights into the biology of the disease and warrants further investigation for relevance to clinical care.

Somatic copy number profiling from hepatocellular carcinoma circulating tumor cells

Somatic copy number alterations (SCNAs) are important genetic drivers of many cancers. We investigated the feasibility of obtaining SCNA profiles from circulating tumor cells (CTCs) as a molecular liquid biopsy for hepatocellular carcinoma (HCC). CTCs from ten HCC patients underwent SCNA profiling. The Cancer Genome Atlas (TCGA) SCNA data were used to develop a cancer origin classification model, which was then evaluated for classifying 44 CTCs from multiple cancer types. Sequencing of 18 CTC samples (median: 4 CTCs/sample) from 10 HCC patients using a low-resolution whole-genome sequencing strategy (median: 0.88 million reads/sample) revealed frequent SCNAs in previously reported HCC regions such as 8q amplifications and 17p deletions. SCNA profiling revealed that CTCs share a median of 80% concordance with the primary tumor. CTCs had SCNAs not seen in the primary tumor, some with prognostic implications. Using a SCNA profiling model, the tissue of origin was correctly identified for 32/44 (73%) CTCs from 12/16 (75%) patients with different cancer types.

Prediction of early-stage hepatocellular carcinoma using OncoScan chromosomal copy number aberration data

AIM

To identify chromosomal copy number aberrations (CNAs) in early-stage hepatocellular carcinoma (HCC) and analyze whether they are correlated with patient prognosis.

METHODS

One hundred and twenty patients with early-stage HCC were enrolled in our study, with the collection of formalin fixed, paraffin-embedded (FFPE) specimens and clinicopathological data. Tumor areas were marked by certified pathologists on a hematoxylin and eosin-stained slide, and cancer and adjacent non-cancerous tissues underwent extraction of DNA, which was analyzed with the Affymetrix OncoScan platform to assess CNAs and loss of heterozygosity (LOH). Ten individuals with nonmalignant disease were used as the control group. Another cohort consisting of 40 patients with stage I/II HCC were enrolled to analyze gene expression and to correlate findings with the OncoScan data.

RESULTS

Copy number amplifications occurred at chromosomes 1q21.1-q44 and 8q12.3-24.3 and deletions were found at 4q13.1-q35.2, 8p 23.2-21.1, 16q23.3-24.3, and 17p13.3-12, while LOH commonly occurred at 1p32.3, 3p21.31, 8p23.2-21.1, 16q22.1-24.3, and 17p 13.3-11 in early-stage HCC. Using Cox regression analysis, we also found that a higher percentage of genome change (≥ 60%) was an independent factor for worse prognosis in early-stage HCC (P = 0.031). Among the 875 genes in the OncoScan GeneChip, six were independent predictors of worse disease-free survival, of which three were amplified (MYC, ELAC2, and SYK) and three were deleted (GAK, MECOM, and WRN). Further, patients with HCC who exhibited ≥ 3 CNAs involving these six genes have worse outcomes compared to those who had < 3 CNAs (P < 0.001). Similarly, Asian patients with stage I HCC from The Cancer Genome Atlas harboring CNAs with these genes were also predicted to have poorer outcomes.

CONCLUSION

Patients with early-stage HCC and increased genome change or CNAs involving MYC, ELAC2, SYK, GAK, MECOM, or WRN are at risk for poorer outcome after resection.

Integrative analysis of genomic and epigenomic regulation of the transcriptome in liver cancer

Hepatocellular carcinoma harbors numerous genomic and epigenomic aberrations of DNA copy numbers and DNA methylation. Transcriptomic deregulation by these aberrations plays key driver roles in heterogeneous progression of cancers. Here, we profile DNA copy numbers, DNA methylation, and messenger RNA expression levels from 64 cases of hepatocellular carcinoma specimens. We find that the frequencies of the aberrancies of the DNA copy-number-correlated (CNVcor) expression genes and the methylation-correlated expression (METcor) genes are co-regulated significantly. Multi-omics integration of the CNVcor and METcor genes reveal three prognostic subtypes of hepatocellular carcinoma, which can be validated by an independent data. The most aggressive subtype expressing stemness genes has frequent BAP1 mutations, implying its pivotal role in the aggressive tumor progression. In conclusion, our integrative analysis of genomic and epigenomic regulation provides new insights on the multi-layered pathobiology of hepatocellular carcinoma, which might be helpful in developing precision management for hepatocellular carcinoma patients.Hepatocellular carcinoma is known to harbour numerous genomic and epigenomic aberrations, driving transcriptomic deregulation. Here, the authors integrate genomic, epigenomic, and expression data to reveal three prognostic subtypes, providing insight to the pathobiology of hepatocellular carcinoma.

Precision medicine for hepatocellular carcinoma: driver mutations and targeted therapy

Hepatocellular carcinoma (HCC) is the third most frequent cause of tumor-related mortality and there are an estimated approximately 850,000 new cases annually. Most HCC patients are diagnosed at middle or advanced stage, losing the opportunity of surgery. The development of HCC is promoted by accumulated diverse genetic mutations, which confer selective growth advantages to tumor cells and are called "driver mutations". The discovery of driver mutations provides a novel precision medicine strategy for late stage HCC, called targeted therapy. In this review, we summarized currently discovered driver mutations and corresponding signaling pathways, made an overview of identification methods of driver mutations and genes, and classified targeted drugs for HCC. The knowledge of mutational landscape deepen our understanding of carcinogenesis and promise future precision medicine for HCC patients.

IF-combined smRNA FISH reveals interaction of MCPIP1 protein with IER3 mRNA

MCPIP1 and IER3 are recently described proteins essential for maintenance of immune homeostasis. IER3 is involved in the regulation of apoptosis and differentiation and has been shown lately to protect activated T cells and macrophages from apoptosis. MCPIP1 is an RNase critical for controlling inflammation-related mRNAs. MCPIP1 interacts with and degrades a set of stem-loop-containing mRNAs (including IL-6). Our results demonstrate the involvement of MCPIP1 in the regulation of IER3 mRNA levels. A dual luciferase assay revealed that over-expression of MCPIP1 resulted in a decrease of luciferase activity in the samples co-transfected with constructs containing luciferase CDS attached to IER3 3′UTR. We identified a stem-loop structure similar to that described to be important for destabilization of the IL-6 mRNA by MCPIP1. Examination of IER3 3′UTR sequence, structure and evolutionary conservation revealed that the identified stem-loop is buried within a bigger element. Deletion of this fragment abolished the regulation of IER3 3′UTR-containing transcript by MCPIP1. Finally, using immunofluorescence-combined single-molecule RNA FISH we have shown that the MCPIP1 protein co-localizes with IER3 mRNA. By this method we also proved that the presence of the wild-type NYN/PIN-like domain of MCPIP1 correlated with the decreased level of IER3 mRNA. RNA immunoprecipitation further confirmed the interaction of MCPIP1 with IER3 transcripts in vivo.

Summary: We identify IER3 mRNA as a newly discovered MCPIP1 target using recently described IF-based procedures, and also identify a conserved element involved in MCPIP1-dependent IER3 transcript destabilization.

NUPR1, a new target in liver cancer: implication in controlling cell growth, migration, invasion and sorafenib resistance

Sorafenib, an oral multikinase inhibitor, is the only approved agent for the treatment of advanced hepatocellular carcinoma (HCC). However, its benefits are modest, and as its mechanisms of action remain elusive, a better understanding of its anticancer effects is needed. Based on our previous study results, we investigated here the implication of the nuclear protein 1 (NUPR1) in HCC and its role in sorafenib treatment. NUPR1 is a stress-inducible protein that is overexpressed in various malignancies, but its role in HCC is not yet fully understood. We found that NUPR1 expression was significantly higher in primary human HCC samples than in the normal liver. Knockdown of NUPR1 significantly increased cell sensitivity to sorafenib and inhibited the cell growth, migration and invasion of HCC cells, both in vitro and in vivo. Moreover, NUPR1 silencing influenced the expression of RELB and IER3 genes. Unsurprisingly, RELB and IER3 knockdown also inhibited HCC cell viability, growth and migration. Using gene expression profiling of HCC cells following stable NUPR1 knockdown, we found that genes functionally involved in cell death and survival, cellular response to therapies, lipid metabolism, cell growth and proliferation, molecular transport and cellular movement were mostly suppressed. Network analysis of dynamic gene expression identified NF-κB and ERK as downregulated gene nodes, and several HCC-related oncogenes were also suppressed. We identified Runt-related transcription factor 2 (RUNX2) gene as a NUPR1-regulated gene and demonstrated that RUNX2 gene silencing inhibits HCC cell viability, growth, migration and increased cell sensitivity to sorafenib. We propose that the NUPR1/RELB/IER3/RUNX2 pathway has a pivotal role in hepatocarcinogenesis. The identification of the NUPR1/RELB/IER3/RUNX2 pathway as a potential therapeutic target may contribute to the development of new treatment strategies for HCC management.

Systemic genome screening identifies the outcome associated focal loss of long noncoding RNA PRAL in hepatocellular carcinoma

Systemic analyses using large-scale genomic profiles have successfully identified cancer-driving somatic copy number variations (SCNVs) loci. However, functions of vast focal SCNVs in "protein-coding gene desert" regions are largely unknown. The integrative analysis of long noncoding RNA (lncRNA) expression profiles with SCNVs in hepatocellular carcinoma (HCC) led us to identify the recurrent deletion of lncRNA-PRAL (p53 regulation-associated lncRNA) on chromosome 17p13.1, whose genomic alterations were significantly associated with reduced survival of HCC patients. We found that lncRNA-PRAL could inhibit HCC growth and induce apoptosis in vivo and in vitro through p53. Subsequent investigations indicated that the three stem-loop motifs at the 5' end of lncRNA-PRAL facilitated the combination of HSP90 and p53 and thus competitively inhibited MDM2-dependent p53 ubiquitination, resulting in enhanced p53 stability. Additionally, in vivo lncRNA-PRAL delivery efficiently reduced intrinsic tumors, indicating its potential therapeutic application.

CONCLUSIONS

lncRNA-PRAL, one of the key cancer-driving SCNVs, is a crucial stimulus for HCC growth and may serve as a potential target for antitumor therapy.

Identification of New Players in Hepatocarcinogenesis: Limits and Opportunities of Using Tissue Microarray (TMA)

Liver tumours are among the leading causes of cancer-related death worldwide and hepatocellular carcinoma (HCC) accounts for the vast majority of liver tumours. When detected at an early stage of disease, patients might still be eligible for surgical-based curative treatments. However, currently only small portion of HCC affected patients are diagnosed at an early stage. For late stage HCC no treatment option exists beside the multi-tyrosine kinase inhibitor Sorafenib. Thus new molecular targets and treatment options for HCC are urgently needed. Nevertheless, despite some improvements in diagnosis and patient management, the biology of liver tumour remains inadequately understood, mainly because these tumours have shown to harbour a highly complex genomic landscape. In addition, one major obstacle delaying the identification of new molecular targets in biomedical research is the necessity to validate them using a large collection of tissue specimens. Tissue microarray (TMA) technology allows the prompt molecular profiling of multiple tissue specimens and is therefore ideal to analyze presumptive candidate biomarkers in a fast an effective manner. The use of TMA has substantial benefits over standard techniques and represents a significant advancement in molecular pathology. For example, TMA technology reduces laboratory work, offers a high level of experimental uniformity and provides a judicious use of precious tissue. On the other hand, one potential limitation of using TMA is that the small cores sampled may not be representative of whole tumors. This issue is very critical in particularly heterogeneous cancers such as HCC. For liver focused studies, it is ideal to evaluate the staining patters of a determined marker over the structure of an entire acinus and to define staining in as many as possible anatomical regions. In this review we analyze the limits and opportunities offered by the usage of TMA technology in HCC research. In summary, TMA has revolutionized the histopathological analysis and will be of great help to further advance the knowledge in the field of hepatocarcinogenesis research.

Target genes discovery through copy number alteration analysis in human hepatocellular carcinoma

High-throughput short-read sequencing of exomes and whole cancer genomes in multiple human hepatocellular carcinoma (HCC) cohorts confirmed previously identified frequently mutated somatic genes, such as TP53, CTNNB1 and AXIN1, and identified several novel genes with moderate mutation frequencies, including ARID1A, ARID2, MLL, MLL2, MLL3, MLL4, IRF2, ATM, CDKN2A, FGF19, PIK3CA, RPS6KA3, JAK1, KEAP1, NFE2L2, C16orf62, LEPR, RAC2, and IL6ST. Functional classification of these mutated genes suggested that alterations in pathways participating in chromatin remodeling, Wnt/β-catenin signaling, JAK/STAT signaling, and oxidative stress play critical roles in HCC tumorigenesis. Nevertheless, because there are few druggable genes used in HCC therapy, the identification of new therapeutic targets through integrated genomic approaches remains an important task. Because a large amount of HCC genomic data genotyped by high density single nucleotide polymorphism arrays is deposited in the public domain, copy number alteration (CNA) analyses of these arrays is a cost-effective way to reveal target genes through profiling of recurrent and overlapping amplicons, homozygous deletions and potentially unbalanced chromosomal translocations accumulated during HCC progression. Moreover, integration of CNAs with other high-throughput genomic data, such as aberrantly coding transcriptomes and non-coding gene expression in human HCC tissues and rodent HCC models, provides lines of evidence that can be used to facilitate the identification of novel HCC target genes with the potential of improving the survival of HCC patients.