Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma

Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis

PURPOSE

To perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC).

METHODS

Thirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation.

RESULTS

There were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data.

CONCLUSIONS

The findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas.

Biochemical pharmacology of adenylyl cyclases in cancer

Globally, despite extensive research and pharmacological advancement, cancer remains one of the most common causes of mortality. Understanding the signaling pathways involved in cancer progression is essential for the discovery of new drug targets. The adenylyl cyclase (AC) superfamily comprises glycoproteins that regulate intracellular signaling and convert ATP into cyclic AMP, an important second messenger. The present review highlights the involvement of ACs in cancer progression and suppression, broken down for each specific mammalian AC isoform. The precise mechanisms by which ACs contribute to cancer cell proliferation and invasion are not well understood and are variable among cancer types; however, AC overactivation, along with that of downstream regulators, presents a potential target for novel anticancer therapies. The expression patterns of ACs in numerous cancers are discussed. In addition, we highlight inhibitors of AC-related signaling that are currently under investigation, with a focus on possible anti-cancer strategies. Recent discoveries with small molecules regarding more direct modulation AC activity are also discussed in detail. A more comprehensive understanding of different components in AC-related signaling could potentially lead to the development of novel therapeutic strategies for personalized oncology and might enhance the efficacy of chemoimmunotherapy in the treatment of various cancers.

CommPath: An R package for inference and analysis of pathway-mediated cell-cell communication chain from single-cell transcriptomics

Single-cell transcriptomics offers opportunities to investigate ligand-receptor (LR) interactions between heterogeneous cell populations within tissues. However, most existing tools for the inference of intercellular communication do not allow prioritization of functional LR associations that provoke certain biological responses in the receiver cells. In addition, current tools do not enable the identification of the impact on the downstream cell types of the receiver cells. We present CommPath, an open-source R package and webserver, to analyze and visualize the LR interactions and pathway-mediated intercellular communication chain with single-cell transcriptomic data. CommPath curates a comprehensive signaling pathway database to interpret the consequences of LR associations and therefore infers functional LR interactions. Furthermore, CommPath determines cell-cell communication chain by considering both the upstream and downstream cells of user-defined cell populations. Applying CommPath to human hepatocellular carcinoma dataset shows its ability to decipher complex LR interaction patterns and the associated intercellular communication chain, as well as their changes in disease versus homeostasis.

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.

Targeting Adenylate Cyclase Family: New Concept of Targeted Cancer Therapy

The adenylate cyclase (ADCY) superfamily is a group of glycoproteins regulating intracellular signaling. ADCYs act as key regulators in the cyclic adenosine monophosphate (cAMP) signaling pathway and are related to cell sensitivity to chemotherapy and ionizing radiation. Many members of the superfamily are detectable in most chemoresistance cases despite the complexity and unknownness of the specific mechanism underlying the role of ADCYs in the proliferation and invasion of cancer cells. The overactivation of ADCY, as well as its upstream and downstream regulators, is implicated as a major potential target of novel anticancer therapies and markers of exceptional responders to chemotherapy. The present review focuses on the oncogenic functions of the ADCY family and emphasizes the possibility of the mediating roles of deleterious nonsynonymous single nucleotide polymorphisms (nsSNPs) in ADCY as a prognostic therapeutic target in modulating resistance to chemotherapy and immunotherapy. It assesses the mediating roles of ADCY and its counterparts as stress regulators in reprogramming cancer cell metabolism and the tumor microenvironment. Additionally, the well-evaluated inhibitors of ADCY-related signaling, which are under clinical investigation, are highlighted. A better understanding of ADCY-induced signaling and deleterious nsSNPs (p.E1003K and p.R1116C) in ADCY6 provides new opportunities for developing novel therapeutic strategies in personalized oncology and new approaches to enhance chemoimmunotherapy efficacy in treating various cancers.

Association Between FSIP2 Mutation and an Improved Efficacy of Immune Checkpoint Inhibitors in Patients With Skin Cutaneous Melanoma

Background

Immune checkpoint inhibitors (ICIs) have shown remarkable success in treating skin cutaneous melanoma (SKCM); however, the response to treatment varies greatly between patients. Considering that the efficacy of ICI treatment is influenced by many factors, we selected the Fibrosheath interacting protein 2 (FSIP2) gene and systematically analyzed its potential to predict the efficacy of ICI treatment.

Methods

Patient data were collected from an ICI treatment cohort (n = 120) and a The Cancer Genome Atlas (TCGA)-SKCM cohort (n = 467). The data were divided into an FSIP2-mutant (MT) group and FSIP2-wild-type (WT) group according to FSIP2 mutation status. In this study, we analyzed the patients' overall survival rate, tumor mutational burden (TMB), neoantigen load (NAL), copy number variation (CNV), cell infiltration data and immune-related genes. We used gene set enrichment analysis (GSEA) to delineate biological pathways and processes associated with the efficacy of immunotherapy.

Results

The efficacy of ICI treatment of SKCM patients with FSIP2 mutation was significantly better than that of patients without FSIP2 mutation. The patients in the FSIP2-MT group had higher tumor immunogenicity and lower regulatory T cell (Treg) infiltration. Results of GSEA showed that pathways related to tumor progression (MAPK and FGFR), immunomodulation, and IL-2 synthesis inhibition were significantly downregulated in the FSIP2-MT group.

Conclusion

Our research suggests that the FSIP2 gene has the potential to predict the efficacy of ICI treatment. The high tumor immunogenicity and low Treg levels observed may be closely related to the fact that patients with FSIP2-MT can benefit from ICI treatment.

Prediction of hepatocellular carcinoma risk in patients with chronic liver disease from dynamic modular networks

Background

Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease.

Methods

In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs.

Results

We found the total of 13 oncogenic allosteric modules (OAMs) among chronic hepatitis B (CHB), cirrhosis and HCC network used SimiNEF. We obtained the 11 highly correlated gene pairs involving 15 genes (r > 0.8, P < 0.001) from the 12 OAMs (the out-of-bag (OOB) classification error rate < 0.5) partial consistent with those in independent clinical microarray data, then a three-gene set (cyp1a2-cyp2c19-il6) was optimized to distinguish HCC from non-tumor liver tissues using random forests with an average area under the curve (AUC) of 0.973. Furthermore, we found significant inhibitory effect on the tumor growth of Bel-7402, Hep 3B and Huh7 cell lines in zebrafish treated with the compounds affected those three genes.

Conclusions

These findings indicated that the sequential AMs-based approach could detect HCC risk in the patients with chronic liver disease and might be applied to any time-dependent risk of cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02791-9.

Integrative analysis of layers of data in hepatocellular carcinoma reveals pathway dependencies

BACKGROUND

The broader use of high-throughput technologies has led to improved molecular characterization of hepatocellular carcinoma (HCC). 

AIM

To comprehensively analyze and characterize all publicly available genomic, gene expression, methylation, miRNA and proteomic data in HCC, covering 85 studies and 3355 patient sample profiles, to identify the key dysregulated genes and pathways they affect. 

METHODS

We collected and curated all well-annotated and publicly available high-throughput datasets from PubMed and Gene Expression Omnibus derived from human HCC tissue. Comprehensive pathway enrichment analysis was performed using pathDIP for each data type (genomic, gene expression, methylation, miRNA and proteomic), and the overlap of pathways was assessed to elucidate pathway dependencies in HCC.

RESULTS

We identified a total of 8733 abstracts retrieved by the search on PubMed on HCC for the different layers of data on human HCC samples, published until December 2016. The common key dysregulated pathways in HCC tissue across different layers of data included epidermal growth factor (EGFR) and β1-integrin pathways. Genes along these pathways were significantly and consistently dysregulated across the different types of high-throughput data and had prognostic value with respect to overall survival. Using CTD database, estradiol would best modulate and revert these genes appropriately.

CONCLUSION

By analyzing and integrating all available high-throughput genomic, transcriptomic, miRNA, methylation and proteomic data from human HCC tissue, we identified EGFR, β1-integrin and axon guidance as pathway dependencies in HCC. These are master regulators of key pathways in HCC, such as the mTOR, Ras/Raf/MAPK and p53 pathways. The genes implicated in these pathways had prognostic value in HCC, with Netrin and Slit3 being novel proteins of prognostic importance to HCC. Based on this integrative analysis, EGFR, and β1-integrin are master regulators that could serve as potential therapeutic targets in HCC.

The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis

Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate sample types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and individual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research.

Transcriptomic identification of HBx-associated hub genes in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies around the world. Among the risk factors involved in liver carcinogenesis, hepatitis B virus (HBV) X protein (HBx) is considered to be a key regulator in hepatocarcinogenesis. Whether HBx promotes or protects against HCC remains controversial, therefore exploring new HBx-associated genes is still important.

METHODS

HBx was overexpressed in HepG2, HepG2.2.15 and SMMC-7721 cell lines, primary mouse hepatocytes and livers of C57BL/6N mice. High-throughput RNA sequencing profiling of HepG2 cells with HBx overexpression and related differentially-expressed genes (DEGs), pathway enrichment analysis, protein-protein interaction networks (PPIs), overlapping analysis were conducted. In addition, Gene Expression Omnibus (GEO) and proteomic datasets of HBV-positive HCC datasets were used to verify the expression and prognosis of selected DEGs. Finally, we also evaluated the known oncogenic role of HBx by oncogenic array analysis.

RESULTS

A total of 523 DEGs were obtained from HBx-overexpressing HepG2 cells. Twelve DEGs were identified and validated in cells transiently transfected with HBx and three datasets of HBV-positive HCC transcription profiles. In addition, using the Kaplan-Meier plotter database, the expression levels of the twelve different genes were further analyzed to predict patient outcomes.

CONCLUSION

Among the 12 identified HBx-associated hub genes, HBV-positive HCC patients expressing ARG1 and TAT showed a good overall survival (OS) and relapse-free survival (RFS). Thus, ARG1 and TAT expression could be potential prognostic markers.

Targeting Ca2+ Signaling in the Initiation, Promotion and Progression of Hepatocellular Carcinoma

Simple Summary

Liver cancer (hepatocellular carcinoma) is a significant health burden worldwide. It is often not detected until at an advanced stage when there are few treatment options available. Changes in calcium concentrations within liver cancer cells are essential for regulating their growth, death, and migration (metastasis). Our aim was to review published papers which have identified proteins involved in calcium signaling as potential drug targets for the treatment of liver cancer. About twenty calcium signaling proteins were identified, including those involved in regulating calcium concentrations in the cytoplasm, endoplasmic reticulum and mitochondria. A few of these have turned out to be sites of action of natural products previously known to inhibit liver cancer. More systematic studies are now needed to determine which calcium signaling proteins might be used clinically for treatment of liver cancer, especially advanced stage cancers and those resistant to inhibition by current drugs.

Abstract

Hepatocellular carcinoma (HCC) is a considerable health burden worldwide and a major contributor to cancer-related deaths. HCC is often not noticed until at an advanced stage where treatment options are limited and current systemic drugs can usually only prolong survival for a short time. Understanding the biology and pathology of HCC is a challenge, due to the cellular and anatomic complexities of the liver. While not yet fully understood, liver cancer stem cells play a central role in the initiation and progression of HCC and in resistance to drugs. There are approximately twenty Ca²⁺-signaling proteins identified as potential targets for therapeutic treatment at different stages of HCC. These potential targets include inhibition of the self-renewal properties of liver cancer stem cells; HCC initiation and promotion by hepatitis B and C and non-alcoholic fatty liver disease (principally involving reduction of reactive oxygen species); and cell proliferation, tumor growth, migration and metastasis. A few of these Ca²⁺-signaling pathways have been identified as targets for natural products previously known to reduce HCC. Promising Ca²⁺-signaling targets include voltage-operated Ca²⁺ channel proteins (liver cancer stem cells), inositol trisphosphate receptors, store-operated Ca²⁺ entry, TRP channels, sarco/endoplasmic reticulum (Ca²⁺+Mg²⁺) ATP-ase and Ca²⁺/calmodulin-dependent protein kinases. However, none of these Ca²⁺-signaling targets has been seriously studied any further than laboratory research experiments. The future application of more systematic studies, including genomics, gene expression (RNA-seq), and improved knowledge of the fundamental biology and pathology of HCC will likely reveal new Ca²⁺-signaling protein targets and consolidate priorities for those already identified.

Angiosarcoma patients treated with immune checkpoint inhibitors: a case series of seven patients from a single institution

BACKGROUND

Angiosarcoma is an uncommon endothelial malignancy and a highly aggressive soft tissue sarcoma. Due to its infiltrative nature, successful management of localized angiosarcoma is often challenging. Systemic chemotherapy is used in the metastatic setting and occasionally in patients with high-risk localized disease in neoadjuvant or adjuvant settings. However, responses tend to be short-lived and most patients succumb to metastatic disease. Novel therapies are needed for patients with angiosarcomas.

METHODS

We performed a retrospective analysis of patients with locally advanced or metastatic angiosarcoma, who were treated with checkpoint inhibitors at our institution. We collected their clinical information and outcome measurements. In one patient with achieved complete response, we analyzed circulating and infiltrating T cells within peripheral blood and tumor tissue.

RESULTS

We have treated seven angiosarcoma (AS) patients with checkpoint inhibitors either in the context of clinical trials or off label [Pembrolizumab + Axitinib (NCT02636725; n = 1), AGEN1884, a CTLA-4 inhibitor (NCT02694822; n = 2), Pembrolizumab (n = 4)]. Five patients had cutaneous angiosarcoma, one primary breast angiosarcoma and one radiation-associated breast angiosarcoma. At 12 weeks, 5/7 patients (71%) had partial response of their lesions either on imaging and/or clinical exam and two (29%) had progressive disease. 6/7 patients are alive to date and, thus far, 3/7 patients (43%) have progressed (median 3.4 months)- one achieved partial response after pembrolizumab was switched to ongoing Nivolumab/Ipilimumab, one died of progressive disease at 31 weeks (primary breast angiosarcoma) and one was placed on pazopanib. One patient had a complete response (CR) following extended treatment with monotherapy AGEN1884. No patient experienced any ≥ grade 2 toxicities.

CONCLUSIONS

This case series underscores the value of targeted immunotherapy in treating angiosarcoma. It also identifies genetic heterogeneity of cutaneous angiosarcomas and discusses specific genetic findings that may explain reported benefits from immunotherapy.

Novel significant stage-specific differentially expressed genes in hepatocellular carcinoma

BACKGROUND

Liver cancer is among top deadly cancers worldwide with a very poor prognosis, and the liver is a vulnerable site for metastases of other cancers. Early diagnosis is crucial for treatment of the predominant liver cancers, namely hepatocellular carcinoma (HCC). Here we developed a novel computational framework for the stage-specific analysis of HCC.

METHODS

Using publicly available clinical and RNA-Seq data of cancer samples and controls and the AJCC staging system, we performed a linear modelling analysis of gene expression across all stages and found significant genome-wide changes in the log fold-change of gene expression in cancer samples relative to control. To identify genes that were stage-specific controlling for confounding differential expression in other stages, we developed a set of six pairwise contrasts between the stages and enforced a p-value threshold (< 0.05) for each such contrast. Genes were specific for a stage if they passed all the significance filters for that stage. The monotonicity of gene expression with cancer progression was analyzed with a linear model using the cancer stage as a numeric variable.

RESULTS

Our analysis yielded two stage-I specific genes (CA9, WNT7B), two stage-II specific genes (APOBEC3B, FAM186A), ten stage-III specific genes including DLG5, PARI, NCAPG2, GNMT and XRCC2, and 35 stage-IV specific genes including GABRD, PGAM2, PECAM1 and CXCR2P1. Overexpression of DLG5 was found to be tumor-promoting contrary to the cancer literature on this gene. Further, GABRD was found to be signifincantly monotonically upregulated across stages. Our work has revealed 1977 genes with significant monotonic patterns of expression across cancer stages. NDUFA4L2, CRHBP and PIGU were top genes with monotonic changes of expression across cancer stages that could represent promising targets for therapy. Comparison with gene signatures from the BCLC staging system identified two genes, HSP90AB1 and ARHGAP42. Gene set enrichment analysis indicated overrepresented pathways specific to each stage, notably viral infection pathways in HCC initiation.

CONCLUSIONS

Our study identified novel significant stage-specific differentially expressed genes which could enhance our understanding of the molecular determinants of hepatocellular carcinoma progression. Our findings could serve as biomarkers that potentially underpin diagnosis as well as pinpoint therapeutic targets.

Oxysterols and Gastrointestinal Cancers Around the Clock

This review focuses on the role of oxidized sterols in three major gastrointestinal cancers (hepatocellular carcinoma, pancreatic, and colon cancer) and how the circadian clock affects the carcinogenesis by regulating the lipid metabolism and beyond. While each field of research (cancer, oxysterols, and circadian clock) is well-studied within their specialty, little is known about the intertwining mechanisms and how these influence the disease etiology in each cancer type. Oxysterols are involved in pathology of these cancers, but final conclusions about their protective or damaging effects are elusive, since the effect depends on the type of oxysterol, concentration, and the cell type. Oxysterol concentrations, the expression of key regulators liver X receptors (LXR), farnesoid X receptor (FXR), and oxysterol-binding proteins (OSBP) family are modulated in tumors and plasma of cancer patients, exposing these proteins and selected oxysterols as new potential biomarkers and drug targets. Evidence about how cholesterol/oxysterol pathways are intertwined with circadian clock is building. Identified key contact points are different forms of retinoic acid receptor related orphan receptors (ROR) and LXRs. RORs and LXRs are both regulated by sterols/oxysterols and the circadian clock and in return also regulate the same pathways, representing a complex interplay between sterol metabolism and the clock. With this in mind, in addition to classical therapies to modulate cholesterol in gastrointestinal cancers, such as the statin therapy, the time is ripe also for therapies where time and duration of the drug application is taken as an important factor for successful therapies. The final goal is the personalized approach with chronotherapy for disease management and treatment in order to increase the positive drug effects.

Advances in genomic hepatocellular carcinoma research

Background

Hepatocellular carcinoma (HCC) is the cancer with the second highest mortality in the world due to its late presentation and limited treatment options. As such, there is an urgent need to identify novel biomarkers for early diagnosis and to develop novel therapies. The availability of next-generation sequencing (NGS) data from tumors of liver cancer patients has provided us with invaluable resources to better understand HCC through the integration of data from different sources to facilitate the identification of promising biomarkers or therapeutic targets.

Findings

Here, we review key insights gleaned from more than 20 NGS studies of HCC tumor samples, comprising approximately 582 whole genomes and 1,211 whole exomes mainly from the East Asian population. Through consolidation of reported somatic mutations from multiple studies, we identified genes with different types of somatic mutations, including single nucleotide variations, insertion/deletions, structural variations, and copy number alterations as well as genes with multiple frequent viral integration. Pathway analysis showed that this curated list of somatic mutations is critically involved in cancer-related pathways, viral carcinogenesis, and signaling pathways. Lastly, we addressed the future directions of HCC research as more NGS datasets become available.

Conclusions

Our review is a comprehensive resource for the current NGS research in HCC, consolidating published articles, potential gene candidates, and their related biological pathways.

Precision oncology in liver cancer

With the widespread adoption of molecular profiling in clinical oncology practice, many physicians are faced with making therapeutic decisions based upon isolated genomic alterations. For example, epidermal growth factor receptor tyrosine kinase inhibitors (TKIs) are effective in EGFR-mutant non-small cell lung cancers (NSCLC) while anti-EGFR monoclonal antibodies are ineffective in Ras-mutant colorectal cancers. The matching of mutations with drugs aimed at their respective gene products represents the current state of "precision" oncology. Despite the great expectations of this approach, only a fraction of cancers responds to 'targeted' interventions, and many early responders will ultimately develop resistance to these agents. The underwhelming success of mutation-driven therapies across all cancer types is not due to an inability to detect genetic changes in tumors; rather a deficit in functional insight into the genomic alterations that give rise to each cancer. The Achilles heel of precision oncology thus remains the lack of a robust functional understanding of an individual cancer genome that then allows prediction of the best therapy and resultant outcome for that patient. Current practice focuses on one 'actionable' mutation at a time, while solid cancers typically possess many mutations that involve different cellular sub-populations within a tumor. No method or platform currently exists to guide the interpretation of these complex data, nor to accurately predict response to treatment. This problem is particularly germane to primary liver cancers (PLC), for which only a handful of targeted therapies have been introduced. Here, we will review strategies aimed at overcoming some of these challenges in precision oncology, using liver cancer as an example.

Whole genome sequencing of matched tumor, adjacent non-tumor tissues and corresponding normal blood samples of hepatocellular carcinoma patients revealed dynamic changes of the mutations profiles during hepatocarcinogenesis

Hepatocellular carcinoma (HCC) has become the third most deadly disease worldwide and HBV is the major factor in Asia and Africa. We conducted 9 WGS (whole genome sequencing) analyses for matched samples of tumor, adjacent non-tumor tissues and normal blood samples of HCC patients from three HBV positive patients. We then validated the mutations identified in a larger cohort of 177 HCC patients. We found that the number of the unique somatic mutations (average of 59,136) in tumor samples is significantly less than that in adjacent non-tumor tissues (average 83, 633). We discovered that the TP53 R249S mutation occurred in 7.7% of the HCC patients, and it was significantly associated with poor diagnosis. In addition, we found that the L104P mutation in the VCX gene (Variable charge, X-linked) was absent in white blood cell samples, but present at 11.1% frequency in the adjacent tissues and increased to 14.6% in HCC tissues, suggesting that this mutation might be a tumor driver gene driving HCC carcinogenesis. Finally, we identified a TK1-RNU7 fusion, which would result in a deletion of 103 amino acids from its C-terminal. The frequencies of this fusion event decreased from the adjacent tissues (29.2%) to the tumors (16.7%), suggesting that a truncated thymidine Kinase1 (TK1) caused by the fusion event might be deleterious and be selected against during tumor progression. The three-way comparisons allow the identification of potential driver mutations of carcinogenesis. Furthermore, our dataset provides the research community a valuable dataset for identifying dynamic changes of mutation profiles and driver mutations for HCC.

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

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.

Interplay between circadian clock and viral infection

The circadian clock underpins most physiological conditions and provides a temporal dimension to our understanding of body and tissue homeostasis. Disruptions of circadian rhythms have been associated with many diseases, including metabolic disorders and cancer. Recent literature highlights a role for the circadian clock to regulate innate and adaptive immune functions that may prime the host response to infectious organisms. Viruses are obligate parasites that rely on host cell synthesis machinery for their own replication, survival and dissemination. Here, we review key findings on how circadian rhythms impact viral infection and how viruses modulate molecular clocks to facilitate their own replication. This emerging area of viral-clock biology research provides a fertile ground for discovering novel anti-viral targets and optimizing immune-based therapies.

The biology of Hepatocellular carcinoma: implications for genomic and immune therapies

Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is a leading cause of cancer-related death worldwide. It is highly refractory to most systemic therapies. Recently, significant progress has been made in uncovering genomic alterations in HCC, including potentially targetable aberrations. The most common molecular anomalies in this malignancy are mutations in the TERT promoter, TP53, CTNNB1, AXIN1, ARID1A, CDKN2A and CCND1 genes. PTEN loss at the protein level is also frequent. Genomic portfolios stratify by risk factors as follows: (i) CTNNB1 with alcoholic cirrhosis; and (ii) TP53 with hepatitis B virus-induced cirrhosis. Activating mutations in CTNNB1 and inactivating mutations in AXIN1 both activate WNT signaling. Alterations in this pathway, as well as in TP53 and the cell cycle machinery, and in the PI3K/Akt/mTor axis (the latter activated in the presence of PTEN loss), as well as aberrant angiogenesis and epigenetic anomalies, appear to be major events in HCC. Many of these abnormalities may be pharmacologically tractable. Immunotherapy with checkpoint inhibitors is also emerging as an important treatment option. Indeed, 82% of patients express PD-L1 (immunohistochemistry) and response rates to anti-PD-1 treatment are about 19%, and include about 5% complete remissions as well as durable benefit in some patients. Biomarker-matched trials are still limited in this disease, and many of the genomic alterations in HCC remain challenging to target. Future studies may require combination regimens that include both immunotherapies and molecularly matched targeted treatments.

Piccolo mediates EGFR signaling and acts as a prognostic biomarker in esophageal squamous cell carcinoma

The presynaptic cytomatrix protein Piccolo, encoded by PCLO, is frequently mutated and amplified in esophageal squamous cell carcinoma (ESCC), but its exact roles in ESCC remain unclear. Here we report that Piccolo expression correlates significantly with clinical stage, patient survival and tumor embolus. Functional studies demonstrate that PCLO knockdown remarkably attenuates ESCC malignancy in vitro and in vivo, and ectopic EGFR expression partially compensates for Piccolo loss. PCLO knockdown promotes ubiquitination and degradation of EGFR, which is associated with the negative regulatory effect of Piccolo on E3 ligase Siah1. An anti-Piccolo monoclonal antibody inhibited tumor proliferation in a mouse model of ESCC. These results demonstrate that Piccolo contributes to tumor aggressiveness in ESCC, likely by stabilizing EGFR and promoting EGFR-dependent signaling. Our results further suggest that Piccolo may represent a novel prognostic biomarker and therapeutic target for patients with ESCC.

Genetic alterations in hepatocellular carcinoma: An update

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. Although recent advances in therapeutic approaches for treating HCC have improved the prognoses of patients with HCC, this cancer is still associated with a poor survival rate mainly due to late diagnosis. Therefore, a diagnosis must be made sufficiently early to perform curative and effective treatments. There is a need for a deeper understanding of the molecular mechanisms underlying the initiation and progression of HCC because these mechanisms are critical for making early diagnoses and developing novel therapeutic strategies. Over the past decade, much progress has been made in elucidating the molecular mechanisms underlying hepatocarcinogenesis. In particular, recent advances in next-generation sequencing technologies have revealed numerous genetic alterations, including recurrently mutated genes and dysregulated signaling pathways in HCC. A better understanding of the genetic alterations in HCC could contribute to identifying potential driver mutations and discovering novel therapeutic targets in the future. In this article, we summarize the current advances in research on the genetic alterations, including genomic instability, single-nucleotide polymorphisms, somatic mutations and deregulated signaling pathways, implicated in the initiation and progression of HCC. We also attempt to elucidate some of the genetic mechanisms that contribute to making early diagnoses of and developing molecularly targeted therapies for HCC.

Identification of hub genes and pathways associated with hepatocellular carcinoma based on network strategy

The objective of this study was to identify hub genes and pathways associated with hepatocellular carcinoma (HCC) by centrality analysis of a co-expression network. A co-expression network based on differentially expressed (DE) genes of HCC was constructed using the Differentially Co-expressed Genes and Links (DCGL) package. Centrality analyses, for centrality of degree, clustering coefficient, closeness, stress and betweenness for the co-expression network were performed to identify hub genes, and the hub genes were combined together to overcome inconsistent results. Enrichment analyses were conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Finally, validation of hub genes was conducted utilizing reverse transcription-polymerase chain reaction (RT-PCR) analysis. In total, 260 DE genes between normal controls and HCC patients were obtained and a co-expression network with 154 nodes and 326 edges was constructed. From this, 13 hub genes were identified according to degree, clustering coefficient, closeness, stress and betweenness centrality analysis. It was found that reelin (RELN), potassium voltage-gated channel subfamily J member 10 (KCNJ10) and neural cell adhesion molecule 1 (NCAM1) were common hub genes across the five centralities, and the results of RT-PCR analysis for RELN, KCNJ10 and NCAM1 were consistent with the centrality analyses. Pathway enrichment analysis of DE genes showed that cell cycle, metabolism of xenobiotics by cytochrome P450 and p53 signaling pathway were the most significant pathways. This study may contribute to understanding the molecular pathogenesis of HCC and provide potential biomarkers for its early detection and effective therapies.

Whole exome sequencing of microdissected splenic marginal zone lymphoma: a study to discover novel tumor-specific mutations

Background

Splenic marginal zone lymphoma (SMZL) is an indolent B-cell non-Hodgkin lymphoma and represents the most common primary malignancy of the spleen. Its precise molecular pathogenesis is still unknown and specific molecular markers for diagnosis or possible targets for causal therapies are lacking.

Methods

We performed whole exome sequencing (WES) and copy number analysis from laser-microdissected tumor cells of two primary SMZL discovery cases. Selected somatic single nucleotide variants (SNVs) were analyzed using pyrosequencing and Sanger sequencing in an independent validation cohort.

Results

Overall, 25 nonsynonymous somatic SNVs were identified, including known mutations in the NOTCH2 and MYD88 genes. Twenty-three of the mutations have not been associated with SMZL before. Many of these seem to be subclonal. Screening of 24 additional SMZL for mutations at the same positions found mutated in the WES approach revealed no recurrence of mutations for ZNF608 and PDE10A, whereas the MYD88 L265P missense mutation was identified in 15 % of cases. An analysis of the NOTCH2 PEST domain and the whole coding region of the transcription factor SMYD1 in eight cases identified no additional case with a NOTCH2 mutation, but two additional cases with SMYD1 alterations.

Conclusions

In this first WES approach from microdissected SMZL tissue we confirmed known mutations and discovered new somatic variants. Recurrence of MYD88 mutations in SMZL was validated, but NOTCH2 PEST domain mutations were relatively rare (10 % of cases). Recurrent mutations in the transcription factor SMYD1 have not been described in SMZL before and warrant further investigation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1766-z) contains supplementary material, which is available to authorized users.

Biomarkers for hepatocellular carcinoma: diagnostic and therapeutic utility

Because of the high prevalence and associated-mortality of hepatocellular carcinoma (HCC), early diagnosis of the disease is vital for patient survival. In this regard, tumor size is one of the two main prognostic factors for surgical resection, which constitutes the only curative treatment for HCC along with liver transplantation. However, techniques for HCC surveillance and diagnosis that are currently used in clinical practice have certain limitations that may be inherent to the tumor development. Thus, it is important to continue efforts in the search for biomarkers that increase diagnostic accuracy for HCC. In this review, we focus on different biological sources of candidate biomarkers for HCC diagnosis. Although those biomarkers identified from biological samples obtained by noninvasive methods have greater diagnostic value, we have also considered those obtained from liver tissue because of their potential therapeutic value. To date, sorafenib is the only US Food and Drug Administration-approved antineoplastic for HCC. However, this therapeutic agent shows very low tumor response rates and frequently causes acquired resistance in HCC patients. We discuss the use of HCC biomarkers as therapeutic targets themselves, or as targets to increase sensitivity to sorafenib treatment.

Identifying prognostic features by bottom-up approach and correlating to drug repositioning

Background

Traditionally top-down method was used to identify prognostic features in cancer research. That is to say, differentially expressed genes usually in cancer versus normal were identified to see if they possess survival prediction power. The problem is that prognostic features identified from one set of patient samples can rarely be transferred to other datasets. We apply bottom-up approach in this study: survival correlated or clinical stage correlated genes were selected first and prioritized by their network topology additionally, then a small set of features can be used as a prognostic signature.

Methods

Gene expression profiles of a cohort of 221 hepatocellular carcinoma (HCC) patients were used as a training set, ‘bottom-up’ approach was applied to discover gene-expression signatures associated with survival in both tumor and adjacent non-tumor tissues, and compared with ‘top-down’ approach. The results were validated in a second cohort of 82 patients which was used as a testing set.

Results

Two sets of gene signatures separately identified in tumor and adjacent non-tumor tissues by bottom-up approach were developed in the training cohort. These two signatures were associated with overall survival times of HCC patients and the robustness of each was validated in the testing set, and each predictive performance was better than gene expression signatures reported previously. Moreover, genes in these two prognosis signature gave some indications for drug-repositioning on HCC. Some approved drugs targeting these markers have the alternative indications on hepatocellular carcinoma.

Conclusion

Using the bottom-up approach, we have developed two prognostic gene signatures with a limited number of genes that associated with overall survival times of patients with HCC. Furthermore, prognostic markers in these two signatures have the potential to be therapeutic targets.