Plasma DNA End-Motif Profiling as a Fragmentomic Marker in Cancer, Pregnancy, and Transplantation

Plasma DNA fragmentomics is an emerging area of research covering plasma DNA sizes, end points, and nucleosome footprints. In the present study, we found a significant increase in the diversity of plasma DNA end motifs in patients with hepatocellular carcinoma (HCC). Compared with patients without HCC, patients with HCC showed a preferential pattern of 4-mer end motifs. In particular, the abundance of plasma DNA motif CCCA was much lower in patients with HCC than in subjects without HCC. The aberrant end motifs were also observed in patients with other cancer types, including colorectal cancer, lung cancer, nasopharyngeal carcinoma, and head and neck squamous cell carcinoma. We further observed that the profile of plasma DNA end motifs originating from the same organ, such as the liver, placenta, and hematopoietic cells, generally clustered together. The profile of end motifs may therefore serve as a class of biomarkers for liquid biopsy in oncology, noninvasive prenatal testing, and transplantation monitoring. SIGNIFICANCE: Plasma DNA molecules originating from the liver, HCC and other cancers, placenta, and hematopoietic cells each harbor a set of characteristic plasma DNA end motifs. Such markers carry tissue-of-origin information and represent a new class of biomarkers in the nascent field of fragmentomics.This article is highlighted in the In This Issue feature, p. 627.

Progress toward liquid biopsies in pediatric solid tumors

Pediatric solid tumors have long been known to shed tumor cells, DNA, RNA, and proteins into the blood. Recent technological advances have allowed for improved capture and analysis of these typically scant circulating materials. Efforts are ongoing to develop "liquid biopsy" assays as minimally invasive tools to address diagnostic, prognostic, and disease monitoring needs in childhood cancer care. Applying these highly sensitive technologies to serial liquid biopsies is expected to advance understanding of tumor biology, heterogeneity, and evolution over the course of therapy, thus opening new avenues for personalized therapy. In this review, we outline the latest technologies available for liquid biopsies and describe the methods, pitfalls, and benefits of the assays that are being developed for children with extracranial solid tumors. We discuss what has been learned in several of the most common pediatric solid tumors including neuroblastoma, sarcoma, Wilms tumor, and hepatoblastoma and highlight promising future directions for the field.

Upregulation of SMYD3 and SMYD3 VNTR 3/3 polymorphism increase the risk of hepatocellular carcinoma

SMYD3 (SET and MYND domain-containing protein 3) is involved in histone modification, which initiates oncogenesis by activating transcription of multiple downstream genes. To investigate associations of variable numbers of tandem repeats (VNTR) variants in the SMYD3 gene promoter, SMYD3 serum levels and SMYD3 mRNA expression in hepatitis B virus (HBV) infection and clinical progression of related liver disease. SMYD3 VNTRs were genotyped in 756 HBV patients and 297 healthy controls. SMYD3 serum levels were measured in 293 patients and SMYD3 mRNA expression was quantified in 48 pairs of hepatocellular tumor and adjacent non-tumor liver tissues. Genotype SYMD3 VNTR 3/3 was more frequent among HCC patients than in controls (Padjusted = 0.037). SMYD3 serum levels increased according to clinical progression of liver diseases (P = 0.01); HCC patients had higher levels than non-HCC patients (P = 0.04). Among patients with SMYD3 VNTR 3/3, HCC patients had higher SMYD3 levels than others (P < 0.05). SMYD3 mRNA expression was up-regulated in HCC tumor tissues compared to other tissues (P = 0.008). In conclusion, upregulation of SMYD3 correlates with the occurrence of HCC and SMYD3 VNTR 3/3 appears to increase the risk of HCC through increasing SMYD3 levels. SMYD3 may be an indicator for HCC development in HBV patients.

Disease prediction by cell-free DNA methylation

Disease diagnosis using cell-free DNA (cfDNA) has been an active research field recently. Most existing approaches perform diagnosis based on the detection of sequence variants on cfDNA; thus, their applications are limited to diseases associated with high mutation rate such as cancer. Recent developments start to exploit the epigenetic information on cfDNA, which could have substantially wider applications. In this work, we provide thorough reviews and discussions on the statistical method developments and data analysis strategies for using cfDNA epigenetic profiles, in particular DNA methylation, to construct disease diagnostic models. We focus on two important aspects: marker selection and prediction model construction, under different scenarios. We perform simulations and real data analysis to compare different approaches, and provide recommendations for data analysis.

Computational discovery of therapeutic candidates for preventing preterm birth

Few therapeutic methods exist for preventing preterm birth (PTB), or delivery before completing 37 weeks of gestation. In the US, progesterone (P4) supplementation is the only FDA-approved drug for use in preventing recurrent spontaneous PTB. However, P4 has limited effectiveness, working in only approximately one-third of cases. Computational drug repositioning leverages data on existing drugs to discover novel therapeutic uses. We used a rank-based pattern-matching strategy to compare the differential gene expression signature for PTB to differential gene expression drug profiles in the Connectivity Map database and assigned a reversal score to each PTB-drug pair. Eighty-three drugs, including P4, had significantly reversed differential gene expression compared with that found for PTB. Many of these compounds have been evaluated in the context of pregnancy, with 13 belonging to pregnancy category A or B - indicating no known risk in human pregnancy. We focused our validation efforts on lansoprazole, a proton-pump inhibitor, which has a strong reversal score and a good safety profile. We tested lansoprazole in an animal inflammation model using LPS, which showed a significant increase in fetal viability compared with LPS treatment alone. These promising results demonstrate the effectiveness of the computational drug repositioning pipeline to identify compounds that could be effective in preventing PTB.

Tumor biology and multidisciplinary strategies of oligometastasis in gastrointestinal cancers

More than 70% of gastrointestinal (GI) cancers are diagnosed with metastases, leading to poor prognosis. For some cancer patients with limited sites of metastatic tumors, the term oligometastatic disease (OMD) has been coined as opposed to systemic polymetastasis (PMD) disease. Stephan Paget first described an organ-specific pattern of metastasis in 1889, now known as the "seed and soil" theory where distinct cancer types are found to metastasize to different tumor-specific sites. Our understanding of the biology of tumor metastasis and specifically the molecular mechanisms driving their formation are still limited, in particular, as it relates to the genesis of oligometastasis. In the following review, we discuss recent advances in general understanding of this metastatic behavior including the role of specific signaling pathways, various molecular features and biomarkers, as well as the interaction of carcinoma cells with their tissue microenvironments (both primary and metastatic niches). The unique features that underlie OMD provide potential targets for localized therapy. As it relates to clinical practice, OMD is emerging as treatable with surgical resection and/or other local therapy options. Strategies currently being applied in the clinical management of OMD will be discussed including surgical, radiation-based therapy, ablation procedures, and the results of emerging clinical trials involving immunotherapy.

The Journey to Discovering a Flatworm Target of Praziquantel: A Long TRP

Infections caused by parasitic flatworms impose a considerable worldwide health burden. One of the most impactful is schistosomiasis, a disease caused by parasitic blood flukes. Treatment of schistosomiasis has relied on a single drug - praziquantel (PZQ) - for decades. The utility of PZQ as an essential medication is, however, intertwined with a stark gap in our knowledge as to how this drug works. No flatworm target has been identified that readily explains how PZQ paralyzes and damages schistosomes. Recently, a schistosome ion channel was discovered that is activated by PZQ and displays characteristics which mirror key features of PZQ action on schistosomes. Here, the journey to discovery of this target, properties of this ion channel, and remaining questions are reviewed.

A Proteotranscriptomic-Based Computational Drug-Repositioning Method for Alzheimer's Disease

Numerous clinical trials of drug candidates for Alzheimer's disease (AD) have failed, and computational drug repositioning approaches using omics data have been proposed as effective alternative approaches to the discovery of drug candidates. However, little multi-omics data is available for AD, due to limited availability of brain tissues. Even if omics data exist, systematic drug repurposing study for AD has suffered from lack of big data, insufficient clinical information, and difficulty in data integration on account of sample heterogeneity derived from poor diagnosis or shortage of qualified post-mortem tissue. In this study, we developed a proteotranscriptomic-based computational drug repositioning method named Drug Repositioning Perturbation Score/Class (DRPS/C) based on inverse associations between disease- and drug-induced gene and protein perturbation patterns, incorporating pharmacogenomic knowledge. We constructed a Drug-induced Gene Perturbation Signature Database (DGPSD) comprised of 61,019 gene signatures perturbed by 1,520 drugs from the Connectivity Map (CMap) and the L1000 CMap. Drugs were classified into three DRPCs (High, Intermediate, and Low) according to DRPSs that were calculated using drug- and disease-induced gene perturbation signatures from DGPSD and The Cancer Genome Atlas (TCGA), respectively. The DRPS/C method was evaluated using the area under the ROC curve, with a prescribed drug list from TCGA as the gold standard. Glioblastoma had the highest AUC. To predict anti-AD drugs, DRPS were calculated using DGPSD and AD-induced gene/protein perturbation signatures generated from RNA-seq, microarray and proteomic datasets in the Synapse database, and the drugs were classified into DRPCs. We predicted 31 potential anti-AD drug candidates commonly belonged to high DRPCs of transcriptomic and proteomic signatures. Of these, four drugs classified into the nervous system group of Anatomical Therapeutic Chemical (ATC) system are voltage-gated sodium channel blockers (bupivacaine, topiramate) and monamine oxidase inhibitors (selegiline, iproniazid), and their mechanism of action was inferred from a potential anti-AD drug perspective. Our approach suggests a shortcut to discover new efficacy of drugs for AD.

5-Hydroxymethylcytosine signatures in circulating cell-free DNA as diagnostic and predictive biomarkers for coronary artery disease

Background

The 5-hydroxymethylcytosine (5hmC) DNA modification is an epigenetic marker involved in a range of biological processes. Its function has been studied extensively in tumors, neurodegenerative diseases, and atherosclerosis. Studies have reported that 5hmC modification is closely related to the phenotype transformation of vascular smooth muscle cells and endothelial dysfunction. However, its role in coronary artery disease (CAD) has not been fully studied.

Results

To investigate whether 5hmC modification correlates with CAD pathogenesis and whether 5hmC can be used as a biomarker, we used a low-input whole-genome sequencing technology based on selective chemical capture (hmC-Seal) to firstly generate the 5hmC profiles in the circulating cell-free DNA(cfDNA) of CAD patients, including stable coronary artery disease (sCAD) patients and acute myocardial infarction (AMI) patients. We detected a significant difference of 5hmC enrichment in gene bodies from CAD patients compared with normal coronary artery (NCA) individuals. Our results showed that CAD patients can be well separated from NCA individuals by 5hmC markers. The prediction performance of the model established by differentially regulated 5hmc modified genes were superior to common clinical indicators for the diagnosis of CAD (AUC = 0.93) and sCAD (AUC = 0.93). Specially, we found that 5hmC markers in cfDNA showed prediction potential for AMI (AUC = 0.95), which was superior to that of cardiac troponin I, muscle/brain creatine kinase, and myoglobin.

Conclusions

Our results suggest that 5hmC markers derived from cfDNA can serve as effective epigenetic biomarkers for minimally noninvasive diagnosis and prediction of CAD.

14-CpG-Based Signature Improves the Prognosis Prediction of Hepatocellular Carcinoma Patients

BACKGROUND

Epigenetic dysregulation via alteration of DNA methylation often occurs during the development and progression of cancer, including hepatocellular carcinoma (HCC). In the past, many patterns of single-gene DNA methylation have been extensively explored in the context of HCC prognosis prediction. However, the combined model of a mixture of CpGs has rarely been evaluated. In the present study, we aimed to develop and validate a CpG-based signature model for HCC patient prognosis.

METHODS

Data from methylation profiling of GSE73003, GSE37988, and GSE57958 from the Gene Expression Omnibus (GEO) database and 371 HCC patients from the Cancer Genome Atlas (TCGA) were downloaded. The 371 HCC patients were randomly divided into a development cohort (N = 263) and a validation cohort (N = 263) and a validation cohort (.

RESULTS

Fourteen differential CpGs associated with OS were identified in HCC patients. The MSH, based on these 14 differential CpGs, could effectively divide HCC patients into two distinct subgroups with high risk or low risk of death (P < 0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56-5.90, P < 0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56-5.90, P < 0.0001) in the development cohort (26.35 vs 83.18 months, HR = 3.83, 95% CI: 2.56-5.90.

CONCLUSION

The 14-CpG-based signature is significantly associated with OS and may be used as a novel prognostic biomarker for HCC patients.

Tankyrases/β-catenin Signaling Pathway as an Anti-proliferation and Anti-metastatic Target in Hepatocarcinoma Cell Lines

Objective: The Wnt/β-catenin pathway is involved in the development of hepatocellular carcinoma (HCC) and malignant events such as the epithelial-mesenchymal transition (EMT), metastasis, and invasion. Studies have illustrated that the inhibition of tankyrases (TNKS) antagonizes Wnt/β-catenin signaling in many cancer cells. Methods: The expression levels of proteins related to the Wnt/β-catenin pathway and EMT were analyzed by immunohistochemistry in HCC tissue and paired adjacent normal tissue (n = 10), and in an analysis of The Cancer Genome Atlas (TCGA) data. Additionally, after treatment of HCC cell lines with TNKS1/2 small interfering RNA (siRNA) and a novel TNKS inhibitor (NVP-TNKS656), cell viability, cell clone formation, wound-healing, and cell invasion assays were performed. Results: Higher expression of β-catenin, TNKS, vimentin, and N-cadherin was observed in HCC tissue compared to adjacent normal tissue, but lower expression of E-cadherin was found in HCC tissue. These findings were also observed in the TCGA analysis. In addition, TNKS inhibition (using TNKS1/2 siRNA and NVP-TNKS656) not only abrogated the proliferation of the HCC cell lines but also suppressed metastasis, invasion, and EMT phenotypic features. Moreover, the mechanisms related to TNKS inhibition in HCC probably involved the stabilization of AXIN levels and the downregulation of β-catenin, which mediates EMT marker expression. Conclusion: The TNKS/β-catenin signaling pathway is a potential anti-proliferation and anti-metastatic target in HCC.

Broad-Spectrum Profiling of Drug Safety via Learning Complex Network

Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug‐gene‐adverse drug reaction (ADR) interaction network. For the first time, the drug safety was assessed in a broad landscape of 1,156 distinct ADRs. We also designed a parameter ToxicityScore to quantify the overall drug safety. Moreover, we determined association strength for every 3,807,631 gene‐ADR interactions, which clues mechanistic exploration of ADRs. For convenience, we deployed the model as a web service ADRAlert‐gene at http://www.bio-add.org/ADRAlert/. In summary, this study offers insights into prioritizing safe drug therapy. It helps reduce the attrition rate of new drug discovery by providing a reliable ADR profile in the early preclinical stage.

Evidence for novel epigenetic marks within plants

Variation in patterns of gene expression can result from modifications in the genome that occur without a change in the sequence of the DNA; such modifications include methylation of cytosine to generate 5-methylcytosine (5mC) resulting in the generation of heritable epimutation and novel epialleles. This type of non-sequence variation is called epigenetics. The enzymes responsible for generation of such DNA modifications in mammals are named DNA methyltransferases (DNMT) including DNMT1, DNMT2 and DNMT3. The later stages of oxidations to these modifications are catalyzed by Ten Eleven Translocation (TET) proteins, which contain catalytic domains belonging to the 2-oxoglutarate dependent dioxygenase family. In various mammalian cells/tissues including embryonic stem cells, cancer cells and brain tissues, it has been confirmed that these proteins are able to induce the stepwise oxidization of 5-methyl cytosine to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), and finally 5-carboxylcytosine (5caC). Each stage from initial methylation until the end of the DNA demethylation process is considered as a specific epigenetic mark that may regulate gene expression. This review discusses controversial evidence for the presence of such oxidative products, particularly 5hmC, in various plant species. Whereas some reports suggest no evidence for enzymatic DNA demethylation, other reports suggest that the presence of oxidative products is followed by the active demethylation and indicate the contribution of possible TET-like proteins in the regulation of gene expression in plants. The review also summarizes the results obtained by expressing the human TET conserved catalytic domain in transgenic plants.

Early detection of cancer using circulating tumor DNA: biological, physiological and analytical considerations

Early diagnosis of cancer improves the efficacy of curative therapies. However, due to the difficulties involved in distinguishing between small early-stage tumors and normal biological variation, early detection of cancer is an extremely challenging task and there are currently no clinically validated biomarkers for a pan-cancer screening test. It is thus of particular significance that increasing evidence indicates the potential of circulating tumor DNA (ctDNA) molecules, which are fragmented segments of DNA shed from tumor cells into adjacent body fluids and the circulatory system, to serve as molecular markers for early cancer detection and thereby allow early intervention and improvement of therapeutic and survival outcomes. This is possible because ctDNA molecules bear cancer-specific fragmentation patterns, nucleosome depletion motifs, and genetic and epigenetic alterations, as distinct from plasma DNA originating from non-cancerous tissues/cells. Compared to traditional biomarkers, ctDNA analysis therefore presents the distinctive advantage of detecting tumor-specific alterations. However, based on a thorough survey of the literature, theoretical and empirical evidence suggests that current ctDNA analysis strategies, which are mainly based on DNA mutation detection, do not demonstrate the necessary diagnostic sensitivity and specificity that is required for broad clinical implementation in a screening context. Therefore, in this review we explain the biological, physiological, and analytical challenges toward the development of clinically meaningful ctDNA tests. In addition, we explore some approaches that can be implemented in order to increase the sensitivity and specificity of ctDNA assays.

Genetically Engineered Mouse Models for Liver Cancer

Liver cancer is the fourth leading cause of cancer-related death globally, accounting for approximately 800,000 deaths annually. Hepatocellular carcinoma (HCC) is the most common type of liver cancer, comprising approximately 80% of cases. Murine models of HCC, such as chemically-induced models, xenograft models, and genetically engineered mouse (GEM) models, are valuable tools to reproduce human HCC biopathology and biochemistry. These models can be used to identify potential biomarkers, evaluate potential novel therapeutic drugs in pre-clinical trials, and develop molecular target therapies. Considering molecular target therapies, a novel approach has been developed to create genetically engineered murine models for HCC, employing hydrodynamics-based transfection (HT). The HT method, coupled with the Sleeping Beauty transposon system or the CRISPR/Cas9 genome editing tool, has been used to rapidly and cost-effectively produce a variety of HCC models containing diverse oncogenes or inactivated tumor suppressor genes. The versatility of these models is expected to broaden our knowledge of the genetic mechanisms underlying human hepatocarcinogenesis, allowing the study of premalignant and malignant liver lesions and the evaluation of new therapeutic strategies. Here, we review recent advances in GEM models of HCC with an emphasis on new technologies.

Intestinal Absorption of Bile Acids in Health and Disease

The intestinal reclamation of bile acids is crucial for the maintenance of their enterohepatic circulation. The majority of bile acids are actively absorbed via specific transport proteins that are highly expressed in the distal ileum. The uptake of bile acids by intestinal epithelial cells modulates the activation of cytosolic and membrane receptors such as the farnesoid X receptor (FXR) and G protein-coupled bile acid receptor 1 (GPBAR1), which has a profound effect on hepatic synthesis of bile acids as well as glucose and lipid metabolism. Extensive research has focused on delineating the processes of bile acid absorption and determining the contribution of dysregulated ileal signaling in the development of intestinal and hepatic disorders. For example, a decrease in the levels of the bile acid-induced ileal hormone FGF15/19 is implicated in bile acid-induced diarrhea (BAD). Conversely, the increase in bile acid absorption with subsequent overload of bile acids could be involved in the pathophysiology of liver and metabolic disorders such as fatty liver diseases and type 2 diabetes mellitus. This review article will attempt to provide a comprehensive overview of the mechanisms involved in the intestinal handling of bile acids, the pathological implications of disrupted intestinal bile acid homeostasis, and the potential therapeutic targets for the treatment of bile acid-related disorders. Published 2020. Compr Physiol 10:21-56, 2020.

A Pathway-Based Genomic Approach to Identify Medications: Application to Alcohol Use Disorder

Chronic, excessive alcohol use alters brain gene expression patterns, which could be important for initiating, maintaining, or progressing the addicted state. It has been proposed that pharmaceuticals with opposing effects on gene expression could treat alcohol use disorder (AUD). Computational strategies comparing gene expression signatures of disease to those of pharmaceuticals show promise for nominating novel treatments. We reasoned that it may be sufficient for a treatment to target the biological pathway rather than lists of individual genes perturbed by AUD. We analyzed published and unpublished transcriptomic data using gene set enrichment of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to identify biological pathways disrupted in AUD brain and by compounds in the Library of Network-based Cellular Signatures (LINCS L1000) and Connectivity Map (CMap) databases. Several pathways were consistently disrupted in AUD brain, including an up-regulation of genes within the Complement and Coagulation Cascade, Focal Adhesion, Systemic Lupus Erythematosus, and MAPK signaling, and a down-regulation of genes within the Oxidative Phosphorylation pathway, strengthening evidence for their importance in AUD. Over 200 compounds targeted genes within those pathways in an opposing manner, more than twenty of which have already been shown to affect alcohol consumption, providing confidence in our approach. We created a user-friendly web-interface that researchers can use to identify drugs that target pathways of interest or nominate mechanism of action for drugs. This study demonstrates a unique systems pharmacology approach that can nominate pharmaceuticals that target pathways disrupted in disease states such as AUD and identify compounds that could be repurposed for AUD if sufficient evidence is attained in preclinical studies.

Landscape of cancer diagnostic biomarkers from specifically expressed genes

Although there has been great progress in cancer treatment, cancer remains a serious health threat to humans because of the lack of biomarkers for diagnosis, especially for early-stage diagnosis. In this study, we comprehensively surveyed the specifically expressed genes (SEGs) using the SEGtool based on the big data of gene expression from the The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) projects. In 15 solid tumors, we identified 233 cancer-specific SEGs (cSEGs), which were specifically expressed in only one cancer and showed great potential to be diagnostic biomarkers. Among them, three cSEGs (OGDH, MUDENG and ACO2) had a sample frequency >80% in kidney cancer, suggesting their high sensitivity. Furthermore, we identified 254 cSEGs as early-stage diagnostic biomarkers across 17 cancers. A two-gene combination strategy was applied to improve the sensitivity of diagnostic biomarkers, and hundreds of two-gene combinations were identified with high frequency. We also observed that 13 SEGs were targets of various drugs and nearly half of these drugs may be repurposed to treat cancers with SEGs as their targets. Several SEGs were regulated by specific transcription factors in the corresponding cancer, and 39 cSEGs were prognosis-related genes in 7 cancers. This work provides a survey of cancer biomarkers for diagnosis and early diagnosis and new insights to drug repurposing. These biomarkers may have great potential in cancer research and application.

Drug Repurposing in the Development of Anticancer Agents

BACKGROUND

Research into repositioning known drugs to treat cancer other than the originally intended disease continues to grow and develop, encouraged in part, by several recent success stories. Many of the studies in this article are geared towards repurposing generic drugs because additional clinical trials are relatively easy to perform and the drug safety profiles have previously been established.

OBJECTIVE

This review provides an overview of anticancer drug development strategies which is one of the important areas of drug restructuring.

METHODS

Repurposed drugs for cancer treatments are classified by their pharmacological effects. The successes and failures of important repurposed drugs as anticancer agents are evaluated in this review.

RESULTS AND CONCLUSION

Drugs could have many off-target effects, and can be intelligently repurposed if the off-target effects can be employed for therapeutic purposes. In cancer, due to the heterogeneity of the disease, often targets are quite diverse, hence a number of already known drugs that interfere with these targets could be deployed or repurposed with appropriate research and development.

Nutrition and Liver Cancer Prevention

Liver cancer represents a major public health problem. Hepatocarcinogenesis is a complex process that comprises several stages and is caused by multiple factors. Both progressive genetic and epigenetic alterations are described in liver cancer development. The most effective strategy to reduce the impact of this disease is through prevention. In addition to vaccination against HBV and treatment of HCV infection, other preventive measures include avoiding ingesting aflatoxin-contaminated foods and drinking alcoholic beverages, as well as maintaining healthy body weight and practicing physical exercise. Bioactive compounds from fruits and vegetables present great potential for liver cancer chemoprevention. Among them, tea catechins, carotenoids, retinoids, β-ionone, geranylgeraniol and folic acid can be highlighted. In addition, butyric acid, tributyrin and structured lipids based on butyric acid and other fatty acids represent additional promising chemopreventive agents. These bioactive food compounds have been shown to modulate key cellular and molecular processes that are deregulated in hepatocarcinogenesis. Furthermore, combinations of different classes of bioactive food compounds or of bioactive food compounds with synthetic drugs could lead to synergistic liver cancer chemopreventive effects.

Genome-wide mapping of 5-hydroxymethylcytosines in circulating cell-free DNA as a non-invasive approach for early detection of hepatocellular carcinoma

OBJECTIVE

The lack of highly sensitive and specific diagnostic biomarkers is a major contributor to the poor outcomes of patients with hepatocellular carcinoma (HCC). We sought to develop a non-invasive diagnostic approach using circulating cell-free DNA (cfDNA) for the early detection of HCC.

DESIGN

Applying the 5hmC-Seal technique, we obtained genome-wide 5-hydroxymethylcytosines (5hmC) in cfDNA samples from 2554 Chinese subjects: 1204 patients with HCC, 392 patients with chronic hepatitis B virus infection (CHB) or liver cirrhosis (LC) and 958 healthy individuals and patients with benign liver lesions. A diagnostic model for early HCC was developed through case-control analyses using the elastic net regularisation for feature selection.

RESULTS

The 5hmC-Seal data from patients with HCC showed a genome-wide distribution enriched with liver-derived enhancer marks. We developed a 32-gene diagnostic model that accurately distinguished early HCC (stage 0/A) based on the Barcelona Clinic Liver Cancer staging system from non-HCC (validation set: area under curve (AUC)=88.4%; (95% CI 85.8% to 91.1%)), showing superior performance over α-fetoprotein (AFP). Besides detecting patients with early stage or small tumours (eg, ≤2.0 cm) from non-HCC, the 5hmC model showed high capacity for distinguishing early HCC from high risk subjects with CHB or LC history (validation set: AUC=84.6%; (95% CI 80.6% to 88.7%)), also significantly outperforming AFP. Furthermore, the 5hmC diagnostic model appeared to be independent from potential confounders (eg, smoking/alcohol intake history).

CONCLUSION

We have developed and validated a non-invasive approach with clinical application potential for the early detection of HCC that are still surgically resectable in high risk individuals.

A pharmacogenomic analysis using L1000CDS2 identifies BX-795 as a potential anticancer drug for primary pancreatic ductal adenocarcinoma cells

Pancreatic cancer is one of the leading causes of cancer death, mainly due to the absence of early diagnostic tool and effective therapeutic agents. To identify an effective therapeutic agent for pancreatic ductal adenocarcinoma cells (PDAC), we used 10 Gene Expression Omnibus (GEO) data sets and L1000CDS2 pharmacogenetic search tool and obtained chemical "perturvants" that were predicted to reverse the abnormal gene expression changes in PDAC. Among 20 initial candidates, we measured IC50 for six compounds and identified BX-795, PDK1/TBK1 inhibitor, as a therapeutic candidate. We found that BX-795 inhibits primary PDAC cell proliferation more effectively than normal cells. Following molecular analysis revealed that BX-795 down-regulates mTOR-GSK3β pathway and trigger apoptosis. Moreover, we found that BX-795 suppresses primary PDAC cell migration via downregulation of Snail and Slug. Finally, efficacy test in patient-derived xenograft model of PDAC showed BX-795 can inhibit in vivo tumor growth as efficient as gemcitabine and a combination with trametinib further suppresses tumor growth. Collectively, these results demonstrate the BX-795 as an effective therapeutic candidate for PDAC treatment.

Genomic Characteristics of Triple-Negative Breast Cancer Nominate Molecular Subtypes That Predict Chemotherapy Response

The heterogeneity of triple-negative breast cancer (TNBC) poses difficulties for suitable treatment and leads to poor outcome. This study aimed to define a consensus molecular subtype (CMS) of TNBC and thus elucidate genomic characteristics and relevant therapy. We integrated the expression profiles of 957 TNBC samples from published datasets. We identified genomic characteristics of subtype by exploring the pathway activity, microenvironment, and clinical relevance. In addition, drug response (DR) scores (n = 181) were computationally investigated using chemical perturbation gene signatures and validated in our own patient with TNBC (n = 38) who received chemotherapy and organoid biobank data (n = 64). Subsequently, cooperative functions with drugs were also explored. Finally, we classified TNBC into four CMSs: stem-like; mesenchymal-like; immunomodulatory; luminal-androgen receptor. CMSs also elucidated distinct tumor-associated microenvironment and pathway activities. Furthermore, we discovered metastasis-promoting genes, such as secreted phosphoprotein 1 by comparing with primary. Computational DR scores associated with CMS revealed drug candidates (n = 18), and it was successfully evaluated in cisplatin response of both patients and organoids. Our CMS recapitulated in-depth functional and cellular heterogeneity encompassing primary and metastatic TNBC. We suggest DR scores to predict CMS-specific DRs and to be successfully validated. Finally, our approach systemically proposes a relevant therapeutic prediction model as well as prognostic markers for TNBC. IMPLICATIONS: We delineated the genomic characteristic and computational DR prediction for TNBC CMS from gene expression profile. Our systematic approach provides diagnostic markers for subtype and metastasis verified by machine-learning and novel therapeutic candidates for patients with TNBC.

A new risk score based on twelve hepatocellular carcinoma-specific gene expression can predict the patients' prognosis

A large panel of molecular biomarkers have been identified to predict the prognosis of hepatocellular carcinoma (HCC), yet with limited clinical application due to difficult extrapolation. We here generated a genetic risk score system comprised of 12 HCC-specific genes to better predict the prognosis of HCC patients. Four genomics profiling datasets (GSE5851, GSE28691, GSE15765 and GSE14323) were searched to seek HCC-specific genes by comparisons between cancer samples and normal liver tissues and between different subtypes of hepatic neoplasms. Univariate survival analysis screened HCC-specific genes associated with overall survival (OS) in the training dataset for next-step risk model construction. The prognostic value of the constructed HCC risk score system was then validated in the TCGA dataset. Stratified analysis indicated this scoring system showed better performance in elderly male patients with HBV infection and preoperative lower levels of creatinine, alpha-fetoprotein and platelet and higher level of albumin. Functional annotation of this risk model in high-risk patients revealed that pathways associated with cell cycle, cell migration and inflammation were significantly enriched. In summary, our constructed HCC-specific gene risk model demonstrated robustness and potentiality in predicting the prognosis of HCC patients, especially among elderly male patients with HBV infection and relatively better general conditions.

Cell-Free DNA Methylation Profiling Analysis-Technologies and Bioinformatics

Analysis of circulating nucleic acids in bodily fluids, referred to as “liquid biopsies”, is rapidly gaining prominence. Studies have shown that cell-free DNA (cfDNA) has great potential in characterizing tumor status and heterogeneity, as well as the response to therapy and tumor recurrence. DNA methylation is an epigenetic modification that plays an important role in a broad range of biological processes and diseases. It is well known that aberrant DNA methylation is generalizable across various samples and occurs early during the pathogenesis of cancer. Methylation patterns of cfDNA are also consistent with their originated cells or tissues. Systemic analysis of cfDNA methylation profiles has emerged as a promising approach for cancer detection and origin determination. In this review, we will summarize the technologies for DNA methylation analysis and discuss their feasibility for liquid biopsy applications. We will also provide a brief overview of the bioinformatic approaches for analysis of DNA methylation sequencing data. Overall, this review provides informative guidance for the selection of experimental and computational methods in cfDNA methylation-based studies.

Toward the Early Detection of Cancer by Decoding the Epigenetic and Environmental Fingerprints of Cell-Free DNA

Widespread adaptation of liquid biopsy for the early detection of cancer has yet to reach clinical utility. Circulating tumor DNA is commonly detected though the presence of genetic alterations, but only a minor fraction of tumor-derived cell-free DNA (cfDNA) fragments exhibit mutations. The cellular processes occurring in cancer development mark the chromatin. These epigenetic marks are reflected by modifications in the cfDNA methylation, fragment size, and structure. In this review, we describe how going beyond DNA sequence information alone, by analyzing cfDNA epigenetic and immune signatures, boosts the potential of liquid biopsy for the early detection of cancer.

mTOR/HDAC1 Crosstalk Mediated Suppression of ADH1A and ALDH2 Links Alcohol Metabolism to Hepatocellular Carcinoma Onset and Progression in silico

Hepatocellular carcinoma (HCC) is ranked the third deadliest cancer worldwide whose molecular pathogenesis is not fully understood. Although deregulated metabolic pathways have been implicated in HCC onset and progression, the mechanisms triggering this metabolic imbalance are yet to be explored. Here, we identified a gene signature coding catabolic enzymes (Cat-GS) involved in key metabolic pathways like amino acid, lipid, carbohydrate, drug, and retinol metabolism as suppressed in HCC. A higher expression of deregulated Cat-GS is associated with good survival and less aggressive disease state in HCC patients. On the other hand, we identified mTOR signaling as a key determinant in HCC onset and progression, whose hyperactivation is found associated with poor survival and aggressive disease state in HCC patients. Next, out of Cat-GS, we established two key regulators of alcohol metabolism, alcohol dehydrogenase 1A (ADH1A) and aldehyde dehydrogenase 2 (ALDH2), as being transcriptionally suppressed by histone deacetylase 1 (HDAC1) at the downstream of mTORC1 signaling. Suppressed ADH1A and ALDH2 expression aligns well with HCC-specific molecular profile and can efficiently predict disease onset and progression, whereas higher ADH1A and ALDH2 expression is associated with good survival and less aggressive disease state in HCC patients. Overall, our in silico findings suggest that transcriptional suppression of alcohol metabolism regulators, ADH1A and ALDH2, at the downstream of mTOR signaling is, in part, responsible for triggering oncogenic transformation of hepatocytes resulting in disease onset and progression in HCC.

5-Hydroxymethylcytosines in Circulating Cell-Free DNA Reveal Vascular Complications of Type 2 Diabetes

BACKGROUND

Long-term complications of type 2 diabetes (T2D), such as macrovascular and microvascular events, are the major causes for T2D-related disability and mortality. A clinically convenient, noninvasive approach for monitoring the development of these complications would improve the overall life quality of patients with T2D and help reduce healthcare burden through preventive interventions.

METHODS

A selective chemical labeling strategy for 5-hydroxymethylcytosines (5hmC-Seal) was used to profile genome-wide 5hmCs, an emerging class of epigenetic markers implicated in complex diseases including diabetes, in circulating cell-free DNA (cfDNA) from a collection of Chinese patients (n = 62). Differentially modified 5hmC markers between patients with T2D with and without macrovascular/microvascular complications were analyzed under a case-control design.

RESULTS

Statistically significant changes in 5hmC markers were associated with T2D-related macrovascular/microvascular complications, involving genes and pathways relevant to vascular biology and diabetes, including insulin resistance and inflammation. A 16-gene 5hmC marker panel accurately distinguished patients with vascular complications from those without [testing set: area under the curve (AUC) = 0.85; 95% CI, 0.73-0.96], outperforming conventional clinical variables such as urinary albumin. In addition, a separate 13-gene 5hmC marker panel could distinguish patients with single complications from those with multiple complications (testing set: AUC = 0.84; 95% CI, 0.68-0.99), showing superiority over conventional clinical variables.

CONCLUSIONS

The 5hmC markers in cfDNA reflected the epigenetic changes in patients with T2D who developed macrovascular/microvascular complications. The 5hmC-Seal assay has the potential to be a clinically convenient, noninvasive approach that can be applied in the clinic to monitor the presence and severity of diabetic vascular complications.

DNA Methylation and Micro-RNAs: The Most Recent and Relevant Biomarkers in the Early Diagnosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a frequently encountered cancer type, and its alarming incidence is explained by genetic and epigenetic alterations. Epigenetic changes may represent diagnostic and prognostic biomarkers of HCC. In this review we discussed deoxyribonucleic acid (DNA) hypomethylation, DNA hypermethylation, and aberrant expression of small non-coding ribonucleic acid (RNA), which could be useful new biomarkers in the early diagnosis of HCC. We selected the articles on human subjects published in English over the past two years involving diagnostic markers detected in body fluids, cancer diagnosis made on histopathological exam, and a control group of those with benign liver disease or without liver disease. These biomarkers need further investigation in clinical trials to develop clinical applications for early diagnosis and management of HCC.

Mutational Profile Using Next-Generation Sequencing May Aid in the Diagnosis and Treatment of Urachal Adenocarcinoma

Objectives. The rare urachal adenocarcinoma (UAC) of the bladder has striking morphologic and immunohistochemical overlap with colorectal adenocarcinoma (CAC) and bladder adenocarcinoma (BAC). To date, the mutational status in UAC and BAC has not been well investigated. Methods. We retrospectively evaluated 34 UACs (mucinous, n = 9; intestinal, n = 3; signet ring cell, n = 1; not otherwise specified, n = 21) and 4 BACs (n = 4). Next-generation sequencing analysis of 50 cancer "hotspot" gene mutations using the Ampliseq Cancer Hotspot Panel v2 was performed. Two UAC cases did not have adequate DNA quality with poor sequencing coverage and were excluded from the study. Results. RAS mutations were identified in 16 of 32 (50%) UACs (15 KRAS; 1 NRAS) and none of the BACs (0%). TP53 mutations were found in both UACs (18/32; 56%) and BACs (4/4; 100%). GNAS (n = 4), SMAD4 (n = 3), and BRAF (n = 1) mutations were only found in UACs. In contrast, APC (n = 2) mutations were only found in BACs. The mucinous subtype of UAC contained a SMAD4 mutation in 33% of cases (3/9), which was not identified in any other subtype (0/23; 0%) (P = .0169). The only BRAF mutation was identified in the single signet ring cell subtype of UAC. There were no other differences in the mutation profile when comparing histologic subtypes of UAC. Conclusions. In summary, UAC and BAC have overlapping but distinct mutation profiles and these differences may aid in separating these 2 entities. Next-generation sequencing to identify therapeutic targets or resistance markers may aid treatment decisions.

Poly(ADP-ribose)-dependent ubiquitination and its clinical implications

ADP-ribosylation-the addition of one or multiple ADP-ribose units onto proteins-is a therapeutically important post-translational modification implicated in cancer, neurodegeneration, and infectious diseases. The protein modification regulates a broad range of biological processes, including DNA repair, transcription, RNA metabolism, and the structural integrity of nonmembranous structures. The polymeric form of ADP-ribose, poly(ADP-ribose), was recently identified as a signal for triggering protein degradation through the ubiquitin-proteasome system. Using informatics analyses, we found that these ubiquitinated substrates tend to be low abundance proteins, which may serve as rate-limiting factors within signaling networks or metabolic processes. In this review, we summarize the current literature on poly(ADP-ribose)-dependent ubiquitination (PARdU) regarding its biological mechanisms, substrates, and relevance to diseases.

Application of the High-throughput TAB-Array for the Discovery of Novel 5-Hydroxymethylcytosine Biomarkers in Pancreatic Ductal Adenocarcinoma

The clinical outcomes of pancreatic ductal adenocarcinoma (PDAC) remain dismal, with an estimated five-year survival rate less than 5%. Early detection and prognostic approaches, including robust biomarkers for PDAC are critical for improving patient survival. Our goal was to explore the biomarker potential of 5-hydroxymethylcytosines (5hmC), an emerging epigenetic marker with a distinct role in cancer pathobiology, yet under-investigated due largely to technical constraints, for PDAC. We used the TAB-Array assay, a state-of-the-art technology to directly profile 5hmC at single base resolution with the Illumina EPIC array (~850,000 cytosine modification sites) in 17 pairs of tumor/adjacent tissue samples from US patients collected at the University of Chicago Medical Center. The TAB-Array data were analyzed to explore the genomic distribution of 5hmC and evaluate whether 5hmC markers were differentially modified between tumors and adjacent tissues. We demonstrated distinctive distribution patterns of 5hmC in tissue samples from PDAC patients relative to gene regulatory elements (e.g., histone modification marks for enhancers), indicating their potential gene regulatory relevance. Substantial differences in 5hmC-modified CpG sites, involving those genes related to cancer pathobiology, were detected between tumors and adjacent tissues. The detected 5hmC-contaning marker genes also showed prognostic value for patient survival in the US patients with PDAC from the Cancer Genome Atlas Project. This study demonstrated the technical feasibility of the TAB-Array approach in cancer biomarker discovery and the biomarker potential of 5hmC for PDAC. Future studies using tissues and/or liquid biopsies may include 5hmC as potential epigenetic biomarker targets for PDAC.

5-Hydroxymethylcytosine and ten-eleven translocation dioxygenases in head and neck carcinoma

Ten-eleven translocation (TET) enzymes are implicated in DNA demethylation through dioxygenase activity, which converts 5-methylcytosine to 5-hydroxymethylcytosine (5-hmC). However, the specific roles of TET enzymes and 5-hmC levels in head and neck squamous cell carcinoma (HNSCC) have not yet been evaluated. In this study, we analyzed 5-hmC levels and TET mRNA expression in a well-characterized dataset of 117 matched pairs of HNSCC tissues and normal tissues. 5-hmC levels and TET mRNA expression were examined via enzyme-linked immunosorbent assay and quantitative real-time PCR, respectively. 5-hmC levels were evaluated according to various clinical characteristics and prognostic implications. Notably, we found that 5-hmC levels were significantly correlated with tumor stage (P = 0.032) and recurrence (P = 0.018). Univariate analysis revealed that low levels of 5-hmC were correlated with poor disease-free survival (DFS; log-rank test, P = 0.038). The expression of TET family genes was not associated with outcomes. In multivariate analysis, low levels of 5-hmC were evaluated as a significant independent prognostic factor of DFS (hazard ratio: 2.352, 95% confidence interval: 1.136-4.896; P = 0.021). Taken together, our findings showed that reduction of TET family gene expression and subsequent low levels of 5-hmC may affect the development of HNSCC.

A cell-free DNA metagenomic sequencing assay that integrates the host injury response to infection

High-throughput metagenomic sequencing offers an unbiased approach to identify pathogens in clinical samples. Conventional metagenomic sequencing, however, does not integrate information about the host, which is often critical to distinguish infection from infectious disease, and to assess the severity of disease. Here, we explore the utility of high-throughput sequencing of cell-free DNA (cfDNA) after bisulfite conversion to map the tissue and cell types of origin of host-derived cfDNA, and to profile the bacterial and viral metagenome. We applied this assay to 51 urinary cfDNA isolates collected from a cohort of kidney transplant recipients with and without bacterial and viral infection of the urinary tract. We find that the cell and tissue types of origin of urinary cfDNA can be derived from its genome-wide profile of methylation marks, and strongly depend on infection status. We find evidence of kidney and bladder tissue damage due to viral and bacterial infection, respectively, and of the recruitment of neutrophils to the urinary tract during infection. Through direct comparison to conventional metagenomic sequencing as well as clinical tests of infection, we find this assay accurately captures the bacterial and viral composition of the sample. The assay presented here is straightforward to implement, offers a systems view into bacterial and viral infections of the urinary tract, and can find future use as a tool for the differential diagnosis of infection.

Non-alcoholic fatty liver disease (NAFLD) is associated with dynamic changes in DNA hydroxymethylation

Non-alcoholic fatty liver disease (NAFLD) is now the commonest cause of liver disease in developed countries affecting 25-33% of the general population and up to 75% of those with obesity. Recent data suggest that alterations in DNA methylation may be related to NAFLD pathogenesis and progression and we have previously shown that dynamic changes in the cell lineage identifier 5-hydroxymethylcytosine (5hmC) may be important in the pathogenesis of liver disease. We used a model of diet-induced obesity, maintaining male mice on a high-fat diet (HFD) to generate hepatic steatosis. We profiled hepatic gene expression, global and locus-specific 5hmC and additionally investigated the effects of weight loss on the phenotype. HFD led to increased weight gain, fasting hyperglycaemia, glucose intolerance, insulin resistance and hepatic periportal macrovesicular steatosis. Diet-induced hepatic steatosis associated with reversible 5hmC changes at a discrete number of functionally important genes. We propose that 5hmC profiles are a useful signature of gene transcription and a marker of cell state in NAFLD and suggest that 5hmC profiles hold potential as a biomarker of abnormal liver physiology.

Screening of Drug Repositioning Candidates for Castration Resistant Prostate Cancer

Purpose: Most prostate cancers (PCs) initially respond to androgen deprivation therapy (ADT), but eventually many PC patients develop castration resistant PC (CRPC). Currently, available drugs that have been approved for the treatment of CRPC patients are limited. Computational drug repositioning methods using public databases represent a promising and efficient tool for discovering new uses for existing drugs. The purpose of the present study is to predict drug candidates that can treat CRPC using a computational method that integrates publicly available gene expression data of tumors from CRPC patients, drug-induced gene expression data and drug response activity data. Methods: Gene expression data from tumoral and normal or benign prostate tissue samples in CRPC patients were downloaded from the Gene Expression Omnibus (GEO) and differentially expressed genes (DEGs) in CRPC were determined with a meta-signature analysis by a metaDE R package. Additionally, drug activity data were downloaded from the ChEMBL database. Furthermore, the drug-induced gene expression data were downloaded from the LINCS database. The reversal relationship between the CRPC and drug gene expression signatures as the Reverse Gene Expression Scores (RGES) were computed. Drug candidates to treat CRPC were predicted using summarized scores (sRGES). Additionally, synergic effects of drug combinations were predicted with a Target Inhibition interaction using the Minimization and Maximization Averaging (TIMMA) algorithm. Results: The drug candidates of sorafenib, olaparib, elesclomol, tanespimycin, and ponatinib were predicted to be active for the treatment of CRPC. Meanwhile, CRPC-related genes, in this case MYL9, E2F2, APOE, and ZFP36, were identified as having gene expression data that can be reversed by these drugs. Additionally, lenalidomide in combination with pazopanib was predicted to be most potent for CRPC. Conclusion: These findings support the use of a computational reversal gene expression approach to identify new drug and drug combination candidates that can be used to treat CRPC.

Microenvironment of ruptured cerebral aneurysms discovered using data driven analysis of gene expression

BACKGROUND

It is well known that ruptured intracranial aneurysms are associated with substantial morbidity and mortality, yet our understanding of the genetic mechanisms of rupture remains poor. We hypothesize that applying novel techniques to the genetic analysis of aneurysmal tissue will yield key rupture-associated mechanisms and novel drug candidates for the prevention of rupture.

METHODS

We applied weighted gene co-expression networks (WGCNA) and population-specific gene expression analysis (PSEA) to transcriptomic data from 33 ruptured and unruptured aneurysm domes. Mechanisms were annotated using Gene Ontology, and gene network/population-specific expression levels correlated with rupture state. We then used computational drug repurposing to identify plausible drug candidates for the prevention of aneurysm rupture.

RESULTS

Network analysis of bulk tissue identified multiple immune mechanisms to be associated with aneurysm rupture. Targeting these processes with computational drug repurposing revealed multiple candidates for preventing rupture including Btk inhibitors and modulators of hypoxia inducible factor. In the macrophage-specific analysis, we identify rupture-associated mechanisms MHCII antigen processing, cholesterol efflux, and keratan sulfate catabolism. These processes map well onto several of highly ranked drug candidates, providing further validation.

CONCLUSIONS

Our results are the first to demonstrate population-specific expression levels and intracranial aneurysm rupture, and propose novel drug candidates based on network-based transcriptomics.

Wnt/β-Catenin Signaling in Liver Cancers

Liver cancer is among the leading global healthcare issues associated with high morbidity and mortality. Liver cancer consists of hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), hepatoblastoma (HB), and several other rare tumors. Progression has been witnessed in understanding the interactions between etiological as well as environmental factors and the host in the development of liver cancers. However, the pathogenesis remains poorly understood, hampering the design of rational strategies aiding in preventing liver cancers. Accumulating evidence demonstrates that aberrant activation of the Wnt/β-catenin signaling pathway plays an important role in the initiation and progression of HCC, CCA, and HB. Targeting Wnt/β-catenin signaling potentiates a novel avenue for liver cancer treatment, which may benefit from the development of numerous small-molecule inhibitors and biologic agents in this field. In this review, we discuss the interaction between various etiological factors and components of Wnt/β-catenin signaling early in the precancerous lesion and the acquired mechanisms to further enhance Wnt/β-catenin signaling to promote robust cancer formation at later stages. Additionally, we shed light on current relevant inhibitors tested in liver cancers and provide future perspectives for preclinical and clinical liver cancer studies.

Gene expression analysis of heat-shock proteins and redox regulators reveals combinatorial prognostic markers in carcinomas of the gastrointestinal tract

Heat shock proteins (HSPs) are a large family of ubiquitously expressed proteins with diverse functions, including protein assembly and folding/unfolding. These proteins have been associated with the progression of various gastrointestinal tumours. Dysregulation of cellular redox has also been associated with gastrointestinal carcinogenesis, however, a link between HSPs and dysregulation of cellular redox in carcinogenesis remains unclear. In this study, we analysed mRNA co-expression and methylation patterns, as well as performed survival analysis and gene set enrichment analysis, on gastrointestinal cancer data sets (oesophageal, stomach and colorectal carcinomas) to determine whether HSP activity and cellular redox dysregulation are linked. A widespread relationship between HSPs and cellular redox was identified, with specific combinatorial co-expression patterns demonstrated to significantly alter patient survival outcomes. This comprehensive analysis provides the foundation for future studies aimed at deciphering the mechanisms of cooperativity between HSPs and redox regulatory enzymes, which may be a target for future therapeutic intervention for gastrointestinal tumours.

Pharmacologic targeting of β-catenin improves fracture healing in old mice

β-catenin protein needs to be precisely regulated for effective fracture repair. The pace of fracture healing slows with age, associated with a transient increase in β-catenin during the initial phase of the repair process. Here we examined the ability of pharmacologic agents that target β-catenin to improve the quality of fracture repair in old mice. 20 month old mice were treated with Nefopam or the tankyrase inhibitor XAV939 after a tibia fracture. Fractures were examined 21 days later by micro-CT and histology, and 28 days later using mechanical testing. Daily treatment with Nefopam for three or seven days but not ten days improved the amount of bone present at the fracture site, inhibited β-catenin protein level, and increased colony forming units osteoblastic from bone marrow cells. At 28 days, treatment increased the work to fracture of the injured tibia. XAV939 had a more modest effect on β-catenin protein, colony forming units osteoblastic, and the amount of bone at the fracture site. This data supports the notion that high levels of β-catenin in the early phase of fracture healing in old animals slows osteogenesis, and suggests a pharmacologic approach that targets β-catenin to improve fracture repair in the elderly.

Stress Conditions Induced by Locoregional Therapies Stimulate Enrichment and Proliferation of Liver Cancer Stem Cells

PURPOSE

This study tested the hypothesis that stress conditions that simulated percutaneous thermal ablation (PTA), transarterial embolization (TAE), or transarterial chemoembolization stimulated enrichment of hepatocellular carcinoma (HCC) cancer stem cells (hCSCs) and that hCSC inhibitors can suppress this effect.

MATERIALS AND METHODS

Human HCC cell lines HepG2 and PLC/PRF/5 were subjected to a 46.5°C heat bath for 10 minutes or to 1% hypoxia for 72 hours without fetal bovine serum and with or without doxorubicin. Cells were then treated with a β-catenin inhibitor (FH535 or XAV939), a PI3 kinase inhibitor (Ly294002), or niclosamide, a US Food and Drug Administration-approved antihelminthic drug that acts as a mitochondrial decoupler and mixed inhibitor. Surviving cells were analyzed for hCSC markers by flow cytometry, for stemness by colony-forming assay or sphere-forming assay, and for proliferative capacity by MTT assay (where MTT is 3-(4,5-dimethylthiazol-2-Yl)-2,5-diphenyltetrazolium bromide). Expression of proteins related to CSC renewal and proliferation were analyzed by immunoblotting and immunostaining.

RESULTS

Conditions that simulated PTA, TAE, and transarterial chemoembolization resulted in an enrichment of cells bearing hCSC markers (CD133, CD44, and EpCAM). Cells surviving heat stress exhibited higher colony- or sphere-forming capacity and a greater proliferative state. These effects could be suppressed by niclosamide and inhibitors of β-catenin and PI3 kinase.

CONCLUSIONS

Stress conditions induced by locoregional therapies stimulated hCSC enrichment and proliferation, which could be suppressed by niclosamide and inhibitors of pathways important for hCSC renewal. Future studies will determine whether combining locoregional therapies with adjuvant hCSC inhibitors reduces HCC recurrence.

Kinase network dysregulation in a human induced pluripotent stem cell model of DISC1 schizophrenia

Protein kinases orchestrate signal transduction pathways involved in central nervous system functions ranging from neurodevelopment to synaptic transmission and plasticity. Abnormalities in kinase-mediated signaling are involved in the pathophysiology of neurological disorders, including neuropsychiatric disorders. Here, we expand on the hypothesis that kinase networks are dysregulated in schizophrenia. We investigated changes in serine/threonine kinase activity in cortical excitatory neurons differentiated from induced pluripotent stem cells (iPSCs) from a schizophrenia patient presenting with a 4 bp mutation in the disrupted in schizophrenia 1 (DISC1) gene and a corresponding control. Using kinome peptide arrays, we demonstrate large scale abnormalities in DISC1 cells, including a global depression of serine/threonine kinase activity, and changes in activity of kinases, including AMP-activated protein kinase (AMPK), extracellular signal-regulated kinases (ERK), and thousand-and-one amino acid (TAO) kinases. Using isogenic cell lines in which the DISC1 mutation is either introduced in the control cell line, or rescued in the schizophrenia cell line, we ascribe most of these changes to a direct effect of the presence of the DISC1 mutation. Investigating the gene expression signatures downstream of the DISC1 kinase network, and mapping them on perturbagen signatures obtained from the Library of Integrated Network-based Cellular Signatures (LINCS) database, allowed us to propose novel drug targets able to reverse the DISC1 kinase dysregulation gene expression signature. Altogether, our findings provide new insight into abnormalities of kinase networks in schizophrenia and suggest possible targets for disease intervention.

Systems pharmacology-based integration of human and mouse data for drug repurposing to treat thoracic aneurysms

Marfan syndrome (MFS) is associated with mutations in fibrillin-1 that predispose afflicted individuals to progressive thoracic aortic aneurysm (TAA) leading to dissection and rupture of the vessel wall. Here we combined computational and experimental approaches to identify and test FDA-approved drugs that may slow or even halt aneurysm progression. Computational analyses of transcriptomic data derived from the aortas of MFS patients and MFS mice (Fbn1mgR/mgR mice) predicted that subcellular pathways associated with reduced muscle contractility are key TAA determinants that could be targeted with the GABAB receptor agonist baclofen. Systemic administration of baclofen to Fbn1mgR/mgR mice validated our computational prediction by mitigating arterial disease progression at the cellular and physiological levels. Interestingly, baclofen improved muscle contraction-related subcellular pathways by upregulating a different set of genes than those downregulated in the aorta of vehicle-treated Fbn1mgR/mgR mice. Distinct transcriptomic profiles were also associated with drug-treated MFS and wild-type mice. Thus, systems pharmacology approaches that compare patient- and mouse-derived transcriptomic data for subcellular pathway-based drug repurposing represent an effective strategy to identify potential new treatments of human diseases.

Comparing progression molecular mechanisms between lung adenocarcinoma and lung squamous cell carcinoma based on genetic and epigenetic networks: big data mining and genome-wide systems identification

Non-small-cell lung cancer (NSCLC) is the predominant type of lung cancer in the world. Lung adenocarcinoma (LADC) and lung squamous cell carcinoma (LSCC) are subtypes of NSCLC. We usually regard them as different disease due to their unique molecular characteristics, distinct cells of origin and dissimilar clinical response. However, the differences of genetic and epigenetic progression mechanism between LADC and LSCC are complicated to analyze. Therefore, we applied systems biology approaches and big databases mining to construct genetic and epigenetic networks (GENs) with next-generation sequencing data of LADC and LSCC. In order to obtain the real GENs, system identification and system order detection are conducted on gene regulatory networks (GRNs) and protein-protein interaction networks (PPINs) for each stage of LADC and LSCC. The core GENs were extracted via principal network projection (PNP). Based on the ranking of projection values, we got the core pathways in respect of KEGG pathway. Compared with the core pathways, we found significant differences between microenvironments, dysregulations of miRNAs, epigenetic modifications on certain signaling transduction proteins and target genes in each stage of LADC and LSCC. Finally, we proposed six genetic and epigenetic multiple-molecule drugs to target essential biomarkers in each progression stage of LADC and LSCC, respectively.

Compilation of Modern Technologies To Map Genome-Wide Cytosine Modifications in DNA

Over the past few decades, various DNA modification detection methods have been developed; many of the high-resolution methods are based on bisulfite treatment, which leads to DNA degradation, to a degree. Thus, novel bisulfite-free approaches have been developed in recent years and shown to be useful for epigenome analysis in otherwise difficult-to-handle, but important, DNA samples, such as hmC-seal and hmC-CATCH. Herein, an overview of advances in the development of epigenome sequencing methods for these important DNA modifications is provided.

Evaluating cell lines as models for metastatic breast cancer through integrative analysis of genomic data

Cell lines are widely-used models to study metastatic cancer although the extent to which they recapitulate the disease in patients remains unknown. The recent accumulation of genomic data provides an unprecedented opportunity to evaluate the utility of them for metastatic cancer research. Here, we reveal substantial genomic differences between breast cancer cell lines and metastatic breast cancer patient samples. We also identify cell lines that more closely resemble the different subtypes of metastatic breast cancer seen in the clinic and show that surprisingly, MDA-MB-231 cells bear little genomic similarities to basal-like metastatic breast cancer patient samples. Further comparison suggests that organoids more closely resemble the transcriptome of metastatic breast cancer samples compared to cell lines. Our work provides a guide for cell line selection in the context of breast cancer metastasis and highlights the potential of organoids in these studies.