• Cadherins
• Cancer
• Catenins
• Claudins
• Connexins
• Junctional adhesion molecules
• Zona occludens

• Humans
• Neoplasms/metabolism
• Neoplasms/pathology
• Intercellular Junctions/metabolism
• Intercellular Junctions/pathology
• Animals

• BCL2i
• chronic lymphocytic leukemia
• clinical trials
• drug resistance
• venetoclax

• Humans
• Leukemia, Lymphocytic, Chronic, B-Cell/drug therapy
• Leukemia, Lymphocytic, Chronic, B-Cell/metabolism
• Leukemia, Lymphocytic, Chronic, B-Cell/therapy
• Leukemia, Lymphocytic, Chronic, B-Cell/genetics
• Leukemia, Lymphocytic, Chronic, B-Cell/pathology
• Drug Resistance, Neoplasm/drug effects
• Proto-Oncogene Proteins c-bcl-2/metabolism
• Proto-Oncogene Proteins c-bcl-2/antagonists & inhibitors
• Bridged Bicyclo Compounds, Heterocyclic/therapeutic use
• Bridged Bicyclo Compounds, Heterocyclic/pharmacology
• Sulfonamides/therapeutic use
• Sulfonamides/pharmacology
• Antineoplastic Agents/therapeutic use
• Antineoplastic Agents/pharmacology

• Apoptosis
• Colorectal cancer
• Epigenetic
• Long Non-coding RNA
• miRNA

• Active components
• Castration-resistant prostate cancer
• Network pharmacology
• QiLing decoction
• Signaling pathways
• Tumor growth

• Cancer stem cells
• cancer
• drug resistance
• epigenetics

• Drug Resistance, Neoplasm/genetics
• Epigenesis, Genetic/genetics
• Epithelial-Mesenchymal Transition/genetics
• Humans
• Neoplasm Recurrence, Local/pathology
• Neoplastic Stem Cells/pathology
• Signal Transduction/genetics
• Tumor Microenvironment/genetics

• Animals
• Autophagy
• Female
• Genes, Tumor Suppressor/physiology
• Humans
• Mice
• Phosphatidylinositol 3-Kinases/metabolism
• Signal Transduction
• ras Proteins/metabolism

• P50 CA083639 NCI NIH HHS
• R01 CA135354 NCI NIH HHS

• apoptosis
• cancer
• chromatin modifying enzymes
• epigenetic drugs
• evasion
• therapy

The underlying causes of esophageal cancer (EC) are unknown. To explore the molecular mechanisms that lead to EC, gene expression profiles of large cohorts of patients with EC were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases (GSE5364, GSE20347 and GSE23400). The present study identified 83 upregulated and 22 downregulated genes between EC and normal tissue using R statistical software and the GEO2R web tool. The Database for Annotation, Visualization and Integrated Discovery was used to identify the associated pathways, and for functional annotation of the differentially expressed genes (DEGs). Protein-protein interactions of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database, and hub genes were visualized using Cytoscape software. An online Kaplan-Meier plotter survival analysis tool was utilized to evaluate the prognostic value of hub gene expression in patients with EC. Further analysis of an additional dataset from GEO (GSE21293) revealed that these genes were associated with infiltration and metastasis in EC. In addition, the Gene Expression Profiling Interactive Analysis tool was used to evaluate expression levels of hub genes in patients with EC for different pathological stages. The Ualcan analysis tool was used to evaluate the expression levels of hub genes for different histological types. Overall, ubiquitin conjugating enzyme E2 C, cyclin dependent kinase inhibitor 3, CDC28 protein kinase regulatory subunit 2, kinesin family member 20A (KIF20A) and RAD51 associated protein 1 (RAD51AP1) were upregulated in EC tissues compared with normal tissues, and upregulation of these genes was a poor prognostic factor for patients with EC, indicating that these genes may mediate EC cell infiltration and metastasis. Among the hub genes, KIF-20A had potential value for predicting the pathological stage of EC. KIF20A and RAD51AP1 were more informative biomarkers of esophageal squamous cell carcinoma. Further studies are required to explore the value of these genes in the treatment of EC.

• CDC28 protein kinase regulatory subunit 2
• RAD51 associated protein 1
• cyclin dependent kinase inhibitor 3
• esophageal cancer
• expression profiling data
• hub genes
• kinesin family member 20A
• ubiquitin conjugating enzyme E2 C

• autophagy
• cell survival
• oncogene
• tumor necrosis factor α (TNFα)
• tumor necrosis factor α-inducing protein 8 (TNFAIP8)

• Animals
• Apoptosis
• Apoptosis Regulatory Proteins/chemistry
• Apoptosis Regulatory Proteins/genetics
• Apoptosis Regulatory Proteins/physiology
• Autophagy
• Cell Transformation, Neoplastic/pathology
• Drosophila melanogaster
• Drug Resistance, Neoplasm
• Humans
• Intracellular Signaling Peptides and Proteins/physiology
• Mice
• Neoplasm Metastasis
• Neoplasms/genetics
• Neoplasms/metabolism
• Neoplasms/pathology
• Neoplasms, Experimental
• Oncogenes
• Signal Transduction
• Transplantation, Heterologous
• Tumor Necrosis Factor-alpha/metabolism

• R01 MD012767 NIMHD NIH HHS
• U01 CA194730 NCI NIH HHS
• U54 MD012392 NIMHD NIH HHS

• Malignancy
• Oncogenesis
• Treatment
• UCHs

Tumor necrosis factor-α-induced protein-8 (TNFAIP8) is the earliest discovered component of TNFAIP8 family [tumor necrosis factor-α-induced protein-8 like (TIPE) family]. TNFAIP8 contains a putative death effector domain (DED) homologous to DED II in FLIP (Fas-associated death domain-like interleukin-1β-converting enzyme-inhibitory protein), which may affect cell survival/death process. Recently, it has been demonstrated that TNFAIP8 could inhibit apoptosis and autophagy in various types of cells. Moreover, TNFAIP8 level fluctuated evidently in patients with inflammatory, malignant, and autoimmune diseases, indicating that it might be an anti-apoptotic and oncogenetic protein. Herein we will review the discovery, gene/protein structure, pathophysiological functions, and clinical significance of TNFAIP8 together with its potential regulatory mechanism.

• Apoptosis
• Autophagy
• Immune Response
• Inflammation
• Tumor
• Tumor Necrosis Factor-α Induced Protein-8

Secreted Protein Acidic and Rich in Cysteine (SPARC) is a matricellular glycoprotein that is implicated in myriad physiological and pathological conditions characterized by extensive remodeling and plasticity. The functions and disease association of SPARC in cancer is being increasingly appreciated as it plays multi-faceted contextual roles depending on the cancer type, cell of origin and the unique cancer milieu at both primary and metastatic sites. Herein we will review our current knowledge of the role of SPARC in the multistep cascades of urinary bladder carcinogenesis, progression and metastasis from preclinical models and clinical data and shine the light on its prognostic and therapeutic potentials.

• SPARC
• carcinogenesis
• cell cycle
• inflammation
• urinary bladder

• Cancer
• Cancer therapy
• DNA double-strand breaks
• DNA repair
• Genome stability
• Homologous recombination
• RAD51AP1
• Replication

• Animals
• Carcinogenesis/metabolism
• Carrier Proteins/metabolism
• DNA-Binding Proteins/metabolism
• Humans
• Mice
• Nuclear Proteins/metabolism
• RNA-Binding Proteins
• Recombinational DNA Repair

• T32 OD012201 NIH HHS
• R56 ES021454 NIEHS NIH HHS
• R01 CA220123 NCI NIH HHS
• R01 ES021454 NIEHS NIH HHS
• R01 CA168635 NCI NIH HHS

The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks in a wide spectrum of biological systems.

In the current era of cancer research, stimulated by the release of the entire human genome, it has become increasingly clear that to understand cancer we need to understand how the many thousands of genes and proteins involved interact. Modern techniques have enabled the collection of unprecedented amounts of high quality data describing the state of these molecules during cancer development. In cancer research particularly, this strategy has been particularly successful, leading to the discovery of new drugs able to target key factors promoting cancer growth. However, a large body of research suggests that in complex organs, the interaction between cancer and its surrounding environment is an essential part of the biology of both diseased and healthy tissues, therefore it is of paramount importance that this process is further investigated. Here we report a strategy designed to reveal communication signals between cancer cells and adjacent cell types. We apply the strategy to prostate cancer and find that normal cells surrounding the tumour do exert an anti-tumour activity on prostate cancer cells. By using a statistical model which integrates multiple levels of genetic data, we show that cell-to-cell communication genes are controlled by DNA alterations and have potential prognostic value.

• Bayes Theorem
• Cell Communication
• Cell Line
• Cell Line, Tumor
• Coculture Techniques
• Computational Biology
• Epithelial Cells/metabolism
• Gene Expression Profiling
• Gene Regulatory Networks
• Humans
• Male
• Models, Biological
• Prostate/cytology
• Prostate/metabolism
• Prostatic Neoplasms/genetics
• Prostatic Neoplasms/metabolism
• Prostatic Neoplasms/pathology
• Signal Transduction/genetics

• P30 CA016672 NCI NIH HHS
• Cancer Research UK
• National Institutes of Health

• cancer biology
• enhancer of zeste homolog 2
• hepatocellular carcinoma
• histone methylation
• overall survival
• polycomb
• prognostic factor
• serine/threonine-protein kinase PAK 6 (PAK6)

• DNA methylation
• differentiation
• epigenetics
• haematopoietic stem cells
• progenitor cells

• Biomarkers, Tumor/genetics
• Biomarkers, Tumor/metabolism
• Carcinoma, Squamous Cell/pathology
• Cell Transformation, Neoplastic/genetics
• Disease Progression
• Female
• Gene Expression Regulation, Neoplastic/genetics
• Human papillomavirus 16/isolation & purification
• Humans
• Keratinocytes/metabolism
• Papillomavirus Infections/genetics
• Phosphoglycerate Dehydrogenase/genetics
• Phosphoglycerate Dehydrogenase/metabolism
• Tissue Array Analysis
• Uterine Cervical Neoplasms/genetics
• Uterine Cervical Neoplasms/pathology
• Uterine Cervical Dysplasia/genetics

PAKs 4, 5 and 6 are members of the group B family of p21-activated kinases. Among this group, PAK4 has been most extensively studied. While it has essential roles in embryonic development, in adults high levels of PAK4 are frequently associated with cancer. PAK4 is overexpressed in a variety of cancers, and the Pak4 gene is amplified in some cancers. PAK4 overexpression is sufficient to cause oncogenic transformation in cells and in mouse models. The tight connection between PAK4 and cancer make it a promising diagnostic tool as well as a potential drug target. The group B PAKs also have important developmental functions. PAK4 is important for many early developmental processes, while PAK5 and PAK6 play roles in learning and memory in mice. This chapter provides an overview of the roles of the group B PAKs in cancer as well as development, and includes a discussion of PAK mediated signaling pathways and cellular functions.

• neurobiology
• oncogenesis
• p21-activated kinases
• pak
• protein kinases
• substrates

• (R)-bicalutamide
• Hormone-resistance
• Mitochondrial fission
• MtDNA
• Prostate cancer

• Androgens/pharmacology
• Anilides/pharmacology
• Animals
• COS Cells
• Cell Line, Tumor
• Cell Survival/drug effects
• Chlorocebus aethiops
• Clone Cells
• DNA, Mitochondrial/metabolism
• Drug Resistance, Neoplasm/drug effects
• Dynamins
• GTP Phosphohydrolases/genetics
• GTP Phosphohydrolases/metabolism
• Gene Expression Profiling
• Gene Expression Regulation, Neoplastic/drug effects
• Genome, Mitochondrial/genetics
• Humans
• Male
• Microtubule-Associated Proteins/genetics
• Microtubule-Associated Proteins/metabolism
• Mitochondrial Dynamics/drug effects
• Mitochondrial Dynamics/genetics
• Mitochondrial Proteins/genetics
• Mitochondrial Proteins/metabolism
• Nitriles/pharmacology
• Prostatic Neoplasms/genetics
• Prostatic Neoplasms/pathology
• Prostatic Neoplasms/ultrastructure
• Tosyl Compounds/pharmacology
• Transcription, Genetic/drug effects

• Actin cytoskeleton
• Apoptosis
• Cell invasion
• Cell survival
• LIM kinase
• Metastasis
• p-21-activated kinase

Genes with altered DNA methylation can be used as biomarkers for cancer detection and assessment of prognosis. Here we analyzed the methylation status of a colorectal cancer biomarker panel (CNRIP1, FBN1, INA, MAL, SNCA, and SPG20) in 97 cancer cell lines, derived from 17 different cancer types. Interestingly, the genes were frequently methylated also in hematological cancer types and were therefore subjected to analyses in primary tumor samples from the major types of non-Hodgkin lymphomas (NHL) and in healthy controls. In total, the genes CNRIP1, FBN1, INA, MAL, SNCA, and SPG20 were methylated in 53%, 23%, 52%, 69%, 97%, and 92% of the tumor samples, respectively, and were unmethylated in all healthy controls. With the exception of a single tumor sample, a correct prediction of lymphoma or normal sample was made in a blinded analysis of the validation series using a combination of SNCA and SPG20. The combined ROC-curve analysis of these genes resulted in an area under the curve of 0.999 (P = 4.2 × 10⁻¹⁸), and a sensitivity and specificity of 98% and 100%, respectively, across the test and validation series. Interestingly, the promoter methylation of CNRIP1 was associated with decreased overall survival in diffuse large B-cell lymphoma (DLBCL) (P = 0.03).

In conclusion, our results demonstrate that SNCA and SPG20 methylation might be suitable for early detection and monitoring of NHL. Furthermore, CNRIP1 could potentially be used as a prognostic factor in DLBCL.

• CNRIP1
• MAL
• SNCA
• SPG20
• biomarker
• diagnosis
• epigenetic
• lymphoma
• methylation
• prognosis

• angiogenesis
• dormancy
• histone modification
• methylation
• ovarian cancer
• recurrence

Long chain alkylphenols are man-made compounds still present in industrial and agricultural processes. Their main use is domestic and they are widespread in household products, cleansers and cosmetics, leading to a global environmental and human contamination. These molecules are known to exert estrogen-like activities through binding to classical estrogen receptors. In vitro, they can also interact with the G-protein coupled estrogen receptor. Testicular germ cell tumor etiology and progression are proposed to be stimulated by lifelong estrogeno-mimetic exposure. We studied the transduction signaling pathways through which an alkyphenol mixture triggers testicular cancer cell proliferation in vitro and in vivo. Proliferation assays were monitored after exposure to a realistic mixture of 4-tert-octylphenol and 4-nonylphenol of either TCam-2 seminoma derived cells, NT2/D1 embryonal carcinoma cells or testis tumor in xenografted nude mice. Specific pharmacological inhibitors and gene-silencing strategies were used in TCam-2 cells in order to demonstrate that the alkylphenol mix triggers CREB-phosphorylation through a rapid, ERα36-PI3kinase non genomic pathway. Microarray analysis of the mixture target genes revealed that this pathway can modulate the expression of the DNA-methyltransferase-3 (Dnmt3) gene family which is involved in DNA methylation control. Our results highlight a key role for ERα36 in alkylphenol non genomic signaling in testicular germ cell tumors. Hence, ERα36-dependent control of the epigenetic status opens the way for the understanding of the link between endocrine disruptor exposure and the burden of hormone sensitive cancers.

Most gain of function mutations of tyrosine kinase receptors in human tumours are hemizygous. Gastrointestinal stromal tumours (GIST) with homozygous mutations have a worse prognosis. We aimed to identify genes differentially regulated by hemizygous and heterozygous KIT mutations.

Expression of 94 genes and 384 miRNA was analysed with low density arrays in five NIH3T3 cell lines expressing the full-length human KIT cDNA wild-type (WT), hemizygous KIT mutation with del557-558 (D6) or del564-581 (D54) and heterozygous WT/D6 or WT/D54. Expression of 5 of these genes and 384 miRNA was then analysed in GISTs samples.

Unsupervised and supervised hierarchical clustering of the mRNA and miRNA profiles showed that heterozygous mutants clustered with KIT WT expressing cells while hemizygous mutants were distinct. Among hemizygous cells, D6 and D54 expressing cells clustered separately. Most deregulated genes have been reported as potentially implicated in cancer and severals, as ANXA8 and FBN1, are highlighted by both, mRNA and miRNA analyses. MiRNA and mRNA analyses in GISTs samples confirmed that their expressions varied according to the mutation of the alleles. Interestingly, RGS16, a membrane protein of the regulator of G protein family, correlate with the subcellular localization of KIT mutants and might be responsible for regulation of the PI3K/AKT signalling pathway.

Patterns of mRNA and miRNA expression in cells and tumours depend on heterozygous/hemizygous status of KIT mutations, and deletion/presence of TYR568 & TYR570 residues. Thus each mutation of KIT may drive specific oncogenic pathways.

• Biomarker
• Diagnosis
• Hepatocellular carcinoma
• Methylation
• Prognosis
• Tumor suppressor gene

• Azacitidine/analogs & derivatives
• Azacitidine/pharmacology
• Carcinoma, Hepatocellular/genetics
• Carcinoma, Hepatocellular/mortality
• Carcinoma, Hepatocellular/pathology
• Cell Line, Tumor
• DNA Methylation
• Decitabine
• Humans
• Liver Neoplasms/genetics
• Liver Neoplasms/mortality
• Liver Neoplasms/pathology
• Osteonectin/analysis
• Osteonectin/genetics
• Prognosis
• RNA, Messenger/analysis

• BRCA1 Protein/metabolism
• BRCA2 Protein/metabolism
• Blotting, Western
• Cell Line, Tumor
• DNA Methylation/drug effects
• DNA Methylation/physiology
• Flow Cytometry
• Genes, Tumor Suppressor/drug effects
• Genistein/pharmacology
• Glutathione S-Transferase pi/metabolism
• Humans
• Isoflavones/pharmacology
• Male
• Phytoestrogens/pharmacology
• Promoter Regions, Genetic/drug effects
• Prostatic Neoplasms/metabolism
• Receptor, EphB2/metabolism
• Glycine max/chemistry

• sparc
• cancer
• adipogenesis

• Adipogenesis/drug effects
• Animals
• Anti-Obesity Agents/therapeutic use
• Antineoplastic Agents/therapeutic use
• Humans
• Neoplasms/drug therapy
• Obesity/drug therapy
• Osteonectin/therapeutic use

• R01 CA131294 NCI NIH HHS
• R21 CA155686 NCI NIH HHS
• R01CA131294 NCI NIH HHS

• Animals
• Cell Line, Tumor
• Collagen Type I/genetics
• CpG Islands/genetics
• DNA Methylation/genetics
• Gene Silencing
• Genes, Tumor Suppressor
• Humans
• Infant, Newborn
• Melanoma/genetics
• Melanoma/pathology
• Oligonucleotide Array Sequence Analysis
• Promoter Regions, Genetic/genetics
• RNA, Messenger/genetics
• RNA, Messenger/metabolism
• Skin Neoplasms/genetics
• Skin Neoplasms/pathology
• Thrombospondin 1/deficiency
• Thrombospondin 1/genetics
• Tumor Necrosis Factor Decoy Receptors/deficiency
• Tumor Necrosis Factor Decoy Receptors/genetics
• Ubiquitin Thiolesterase/deficiency
• Ubiquitin Thiolesterase/genetics

• Apoptosis Regulatory Proteins/genetics
• Apoptotic Protease-Activating Factor 1/genetics
• Calcium-Calmodulin-Dependent Protein Kinases/genetics
• Carcinoma, Renal Cell/ethnology
• Carcinoma, Renal Cell/genetics
• Carcinoma, Renal Cell/metabolism
• DNA Methylation
• Death-Associated Protein Kinases
• Disease Progression
• Female
• Humans
• India
• Kidney/pathology
• Kidney Neoplasms/ethnology
• Kidney Neoplasms/genetics
• Kidney Neoplasms/metabolism
• Male
• Middle Aged
• Neoplasm Staging/methods
• Osteonectin/genetics
• Promoter Regions, Genetic

The presence of cancer-specific DNA methylation patterns in epithelial colorectal cells in human feces provides the prospect of a simple, non-invasive screening test for colorectal cancer and its precursor, the adenoma. This study investigates a panel of epigenetic markers for the detection of colorectal cancer and adenomas.

Candidate biomarkers were subjected to quantitative methylation analysis in test sets of tissue samples from colorectal cancers, adenomas, and normal colonic mucosa. All findings were verified in independent clinical validation series. A total of 523 human samples were included in the study. Receiver operating characteristic (ROC) curve analysis was used to evaluate the performance of the biomarker panel.

Promoter hypermethylation of the genes CNRIP1, FBN1, INA, MAL, SNCA, and SPG20 was frequent in both colorectal cancers (65-94%) and adenomas (35-91%), whereas normal mucosa samples were rarely (0-5%) methylated. The combined sensitivity of at least two positives among the six markers was 94% for colorectal cancers and 93% for adenoma samples, with a specificity of 98%. The resulting areas under the ROC curve were 0.984 for cancers and 0.968 for adenomas versus normal mucosa.

The novel epigenetic marker panel shows very high sensitivity and specificity for both colorectal cancers and adenomas. Our findings suggest this biomarker panel to be highly suitable for early tumor detection.

• chromatin regulation
• dna methylation
• epigenetics
• gene transcription
• thrombomodulin
• mesothelioma
• thrombosis

• Aged
• Antimetabolites, Antineoplastic/pharmacology
• Azacitidine/analogs & derivatives
• Cell Line
• DNA Methylation
• Decitabine
• Epithelium/metabolism
• Epithelium/pathology
• Female
• Gene Expression Regulation, Neoplastic
• Gene Silencing
• Humans
• Male
• Mesothelioma/metabolism
• Mesothelioma/pathology
• Middle Aged
• Neoplasm Proteins/genetics
• Neoplasm Proteins/metabolism
• Poly (ADP-Ribose) Polymerase-1
• Poly(ADP-ribose) Polymerases/genetics
• Poly(ADP-ribose) Polymerases/metabolism
• Promoter Regions, Genetic
• Thrombomodulin/biosynthesis
• Thrombomodulin/genetics

With the development of high-throughput screening, a variety of genetic alterations has been found in hepatocellular carcinoma (HCC). Although previous studies on HCC methylation profiles have focused on liver tissue, studies using isolated hepatocytes are rare. The heterogeneity of liver composition may impact the genuine methylation status of HCC; therefore, it is important to clarify the methylation profile of hepatocytes to aid in understanding the process of tumorigenesis.

The global methylation profile of single hepatocytes isolated from liver tissue of hepatitis B virus (HBV) related HCC (HBHC) was analyzed using Illumina Infinium Human Methylation27 BeadChips, and combined bisulfite restriction analysis (COBRA) and bisulfite sequencing were used to validate the 20 significant hypermethylated genes identified. In this study, we found many noteworthy differences in the genome-wide methylation profiles of single hepatocytes of HBHC. Unsupervised hierarchical clustering analysis showed that hepatocyte methylation profiles could be classified according to three cell types: hepatocytes of HCC, adjacent hepatocytes and normal hepatocytes. Among the 20 most hypermethylated genes in the hepatocytes of HBHC, 7 novel genes (WNK2, EMILIN2, TLX3, TM6SF1, TRIM58, HIST1H4Fand GRASP) were found to be hypermethylated in HBHC and hypomethylated in paired adjacent liver tissues; these findings have not been reported in previous studies on tissue samples.

The genome-wide methylation profile of purified single hepatocytes of HBHC was aided in understanding the process of tumorigenesis, and a series of novel methylated genes found in this study have the potential to be biomarkers for the diagnosis and prognosis of HBHC.

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods.

Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer.

We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-througput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.

• Animals
• Biomarkers, Tumor/genetics
• Biomarkers, Tumor/metabolism
• Computational Biology/methods
• Entropy
• Gene Expression Profiling
• Genes, Neoplasm/genetics
• Humans
• Male
• Melanoma/genetics
• Melanoma/metabolism
• Melanoma/pathology
• Mice
• Neoplasms/genetics
• Neoplasms/metabolism
• Neoplasms/pathology
• Oligonucleotide Array Sequence Analysis
• Prostatic Neoplasms/genetics
• Prostatic Neoplasms/metabolism
• Prostatic Neoplasms/pathology