A new 12-gene diagnostic biomarker signature of melanoma revealed by integrated microarray analysis

Experimental assessment of robust reference genes for qRT-PCR in lung cancer studies

Stable internal reference genes are crucial for quantitative real-time PCR (qRT-PCR) analyses in lung cancer studies. Widely used reference genes are mostly chosen by intuition or from pan-cancer transcriptome data and lack experimental validation by qRT-PCR in the context of lung cancer. This study evaluated the stability of candidate reference genes in lung cancer cell lines under normal homeostasis, hypoxia, and serum deprivation to screen for robust reference genes for qRT-PCR in lung cancer studies. The stability of reference gene combinations was also assessed. We found that most of the stably expressed genes from pan-cancer transcriptome analyses were not sufficiently stable under some of the tested conditions. CIAO1, CNOT4, and SNW1 were found to be the most stable reference genes under various conditions. Greater stability was achieved by combining more reference genes. We further used the hypoxia biomarker hypoxia-inducible factor (HIF)-2α to demonstrate that choosing inappropriate reference genes can lead to incorrect qRT-PCR results. We also found that the stable reference genes were irrelevant to malignancy, which may explain their stability under various conditions that cancer cells often encounter. This study provides a list of validated and stable qRT-PCR reference genes and reference gene combinations for lung cancer that may standardize qRT-PCR experiments in future lung cancer studies.

Melanoma molecular subtyping and scoring model construction based on ligand-receptor pairs

Melanoma is a malignancy of melanocytes, responsible for a high percentage of skin cancer mortality. Ligand-Receptor pairs, a type of cellular communication, are essential for tumor genesis, growth, metastasis, and prognosis. Yet, the role of Ligand-Receptor pairs in melanoma has not been fully elucidated. Our research focused on the function of Ligand-Receptor pairs in melanoma prognosis. We screened 131 melanoma prognosis corresponded ligand-receptor pairs by analyzing the TCGA data of melanoma and the 2293 LR pairs retrieved from the connectomeDB2020 database. And further developed subtypes of melanoma according to the expression of these ligand-receptor pairs by Consensus Clustering. Then we using lasso cox regression and stepwise multivariate regression analysis established a ligand-receptor pairs-based scoring model for the evaluation of melanoma prognosis. Our study demonstrated that the ligand-receptor pairs are vital to the molecular heterogeneity of melanoma, and characterized three different melanoma ligand-receptor pairs subtypes. Among them, the C3 subtype showed a better prognosis, while the C1 subtype exhibited a low prognosis state. And our analysis then found out that this could be related to the differed activation and inhabitation of the cell cycle and immune-related pathways. Using lasso cox regression and stepwise multivariate regression analysis, we further identified 9 key ligand-receptor pairs and established a scoring model that effectively correlated with the prognosis, immune pathways, and therapy of melanoma, showing that the LR.score model was a trustworthy and independent biomarker for melanoma prognosis evaluation. In sum, we found that ligand-receptor pairs are significantly associated with the prognosis and therapy of melanoma. And our ligand-receptor-based scoring model showed potential for the evaluation of melanoma prognosis and immune therapy outcome prediction, which is crucial to the survival for the patients.

Role of gene signature regulation in tumor immune microenvironment on the mechanism of uveal melanoma metastasis

BACKGROUND

Uveal melanoma (UM) is a rare but deadly cancer. The main cause of death from UM is liver metastasis. Though the metastasis mechanism remains unclear, it is closely related to the immune microenvironment and gene expression.

OBJECTIVE

This study aimed to identify the prognostic genes in primary and metastatic UM and their relationship with the immune microenvironment.

METHODS

Primary and metastatic UM data from the GEO database included GSE22138 and GSE44295 datasets. Kaplan-Meier analysis, Cox regression models, and ROC analysis were applied to screen genes in GSE22138. TIMER2.0 was employed to analyze the immune microenvironment from gene expression. Prognostic immune gene correlation was tested by Spearman. The results were validated in the independent dataset of cohort GSE44295.

RESULTS

Metastasis and primary differential gene analysis showed 107 significantly different genes associated with prognosis, and 11 of them were immune-related. ROC analysis demonstrated that our signature was predictive for UM prognosis (AUC > 0.8). Neutrophil and myeloid dendritic cells were closely associated with metastasis with scores that significantly divided patients into high-risk and low-risk groups (log-rank p< 0.05). Of these 11 genes, FABP5 and SHC4 were significantly associated with neutrophils in metastatic tumors, while ROBO1 expression was significantly correlated with myeloid dendritic cells in the primary tumors.

CONCLUSIONS

The present study constructed an 11-gene signature and established a model for risk stratification and prediction of overall survival in metastatic UM. Since FABP5 and SHC4 are related to neutrophil infiltration in metastatic UM, FABP5 and neutrophil regulation might be crucial in metastatic UM.

Biomarker Discovery for Meta-Classification of Melanoma Metastatic Progression Using Transfer Learning

Melanoma is considered to be the most serious and aggressive type of skin cancer, and metastasis appears to be the most important factor in its prognosis. Herein, we developed a transfer learning-based biomarker discovery model that could aid in the diagnosis and prognosis of this disease. After applying it to the ensemble machine learning model, results revealed that the genes found were consistent with those found using other methodologies previously applied to the same TCGA (The Cancer Genome Atlas) data set. Further novel biomarkers were also found. Our ensemble model achieved an AUC of 0.9861, an accuracy of 91.05, and an F1 score of 90.60 using an independent validation data set. This study was able to identify potential genes for diagnostic classification (C7 and GRIK5) and diagnostic and prognostic biomarkers (S100A7, S100A7, KRT14, KRT17, KRT6B, KRTDAP, SERPINB4, TSHR, PVRL4, WFDC5, IL20RB) in melanoma. The results show the utility of a transfer learning approach for biomarker discovery in melanoma.

Genome-wide promoter methylation profiling in a cellular model of melanoma progression reveals markers of malignancy and metastasis that predict melanoma survival

The epigenetic changes associated with melanoma progression to advanced and metastatic stages are still poorly understood. To shed light on the CpG methylation dynamics during melanoma development, we analyzed the methylome profiles of a four-stage cell line model of melanoma progression: non-tumorigenic melanocytes (melan-a), premalignant melanocytes (4C), non-metastatic melanoma cells (4C11−), and metastatic melanoma cells (4C11+). We identified 540 hypo- and 37 hypermethylated gene promoters that together characterized a malignancy signature, and 646 hypo- and 520 hypermethylated promoters that distinguished a metastasis signature. Differentially methylated genes from these signatures were correlated with overall survival using TCGA-SKCM methylation data. Moreover, multivariate Cox analyses with LASSO regularization identified panels of 33 and 31 CpGs, respectively, from the malignancy and metastasis signatures that predicted poor survival. We found a concordant relationship between DNA methylation and transcriptional levels for genes from the malignancy (Pyroxd2 and Ptgfrn) and metastasis (Arnt2, Igfbp4 and Ptprf) signatures, which were both also correlated with melanoma prognosis. Altogether, this study reveals novel CpGs methylation markers associated with malignancy and metastasis that collectively could improve the survival prediction of melanoma patients.

Feature selection and classification over the network with missing node observations

Jointly analyzing transcriptomic data and the existing biological networks can yield more robust and informative feature selection results, as well as better understanding of the biological mechanisms. Selecting and classifying node features over genome-scale networks has become increasingly important in genomic biology and genomic medicine. Existing methods have some critical drawbacks. The first is they do not allow flexible modeling of different subtypes of selected nodes. The second is they ignore nodes with missing values, very likely to increase bias in estimation. To address these limitations, we propose a general modeling framework for Bayesian node classification (BNC) with missing values. A new prior model is developed for the class indicators incorporating the network structure. For posterior computation, we resort to the Swendsen-Wang algorithm for efficiently updating class indicators. BNC can naturally handle missing values in the Bayesian modeling framework, which improves the node classification accuracy and reduces the bias in estimating gene effects. We demonstrate the advantages of our methods via extensive simulation studies and the analysis of the cutaneous melanoma dataset from The Cancer Genome Atlas.

A decade of checkpoint blockade immunotherapy in melanoma: understanding the molecular basis for immune sensitivity and resistance

Ten years since the immune checkpoint inhibitor ipilimumab was approved for advanced melanoma, it is time to reflect on the lessons learned regarding modulation of the immune system to treat cancer and on novel approaches to further extend the efficacy of current and emerging immunotherapies. Here, we review the studies that led to our current understanding of the melanoma immune microenvironment in humans and the mechanistic work supporting these observations. We discuss how this information is guiding more precise analyses of the mechanisms of action of immune checkpoint blockade and novel immunotherapeutic approaches. Lastly, we review emerging evidence supporting the negative impact of melanoma metabolic adaptation on anti-tumor immunity and discuss how to counteract such mechanisms for more successful use of immunotherapy.

Phenotypic plasticity of melanocytes derived from human adult skin

We previously described a novel in vitro culture technique for dedifferentiated human adult skin melanocytes. Melanocytes cultured in a defined, cholera toxin and PMA free medium became bipolar, unpigmented, and highly proliferative. Furthermore, TRP-1 and c-Kit expression disappeared and EGFR receptor and nestin expression were induced in the cells. Here, we further characterized the phenotype of these dedifferentiated cells and by comparing them to mature pigmented melanocytes we detected crucial steps in their phenotype change. Our data suggest that normal adult melanocytes easily dedifferentiate into pluripotent stem cells given the right environment. This dedifferentiation process described here for normal melanocyte is very similar to what has been described for melanoma cells, indicating that phenotype switching driven by environmental factors is a general characteristic of melanocytes that can occur independent of malignant transformation.

Phosphatidylserine-specific phospholipase A1: A friend or the devil in disguise

Various human tissues and cells express phospholipase A1 member A (PLA1A), including the liver, lung, prostate gland, and immune cells. The enzyme belongs to the pancreatic lipase family. PLA1A specifically hydrolyzes sn-1 fatty acid of phosphatidylserine (PS) or 1-acyl-lysophosphatidylserine (1-acyl-lysoPS). PS externalized by activated cells or apoptotic cells or extracellular vesicles is a potential source of substrate for the production of unsaturated lysoPS species by PLA1A. Maturation and functions of many immune cells, such as T cells, dendritic cells, macrophages, and mast cells, can be regulated by PLA1A and lysoPS. Several lysoPS receptors, including GPR34, GPR174 and P2Y10, have been identified. High serum levels and high PLA1A expression are associated with autoimmune disorders such as Graves' disease and systemic lupus erythematosus. Increased expression of PLA1A is associated with metastatic melanomas. PLA1A may contribute to cardiometabolic disorders through mediating cholesterol transportation and producing lysoPS. Furthermore, PLA1A is necessary for hepatitis C virus assembly and can play a role in the antivirus innate immune response. This review summarizes recent findings on PLA1A expression, lysoPS and lysoPS receptors in autoimmune disorders, cancers, cardiometabolic disorders, antivirus immune responses, as well as regulations of immune cells.

The Research on the Treatment of Metastatic Skin Cutaneous Melanoma by Huanglian Jiedu Decoction Based on the Analysis of Immune Infiltration Analysis

Objective

To explore the potential mechanism of Huanglian Jiedu Decoction (HJD) treatment and prevention of metastatic Cutaneous Melanoma (CM) occurrence and metastasis based on network pharmacological methods and immune infiltration analysis.

Methods

The GEO database was used to obtain metastatic CM disease targets, the TCMSP database and the HERB database were used to obtain HJD action targets, core genes were screened by protein interaction network, and the potential mechanism of HJD in the treatment of metastatic CM was explored by enrichment analysis, prognostic analysis and immune infiltration analysis.

Results

HJD treatment of metastatic CM involved 60 targets, enrichment analysis showed that HJD treatment of metastatic CM involved Chemokine signaling pathway, NF-kappa B signaling pathway, and Fluid shear stress and atherosclerosis, etc. Prognostic analysis revealed that HJD had a certain ability to improve the prognosis of metastatic CM patients. Immune infiltration analysis showed that HJD could inhibit the immune cell infiltration of metastatic CM patients by acting on related targets.

Conclusions

Our study identified the potential mechanism of HJD in the treatment of metastatic CM through network pharmacology, and revealed the mechanism of HJD in the prevention of Skin Cutaneous Melanoma metastasis through immune infiltration analysis and prognostic analysis.

Cutaneous Melanoma: Mutational Status and Potential Links to Tertiary Lymphoid Structure Formation

Recent advances in immunotherapy have enabled rapid evolution of novel interventional approaches designed to reinvigorate and expand patient immune responses against cancer. An emerging approach in cancer immunology involves the conditional induction of tertiary lymphoid structures (TLS), which are non-encapsulated ectopic lymphoid structures forming at sites of chronic, pathologic inflammation. Cutaneous melanoma (CM), a highly-immunogenic form of solid cancer, continues to rise in both incidence and mortality rate, with recent reports supporting a positive correlation between the presence of TLS in melanoma and beneficial treatment outcomes amongst advanced-stage patients. In this context, TLS in CM are postulated to serve as dynamic centers for the initiation of robust anti-tumor responses within affected regions of active disease. Given their potential importance to patient outcome, significant effort has been recently devoted to gaining a better understanding of TLS neogenesis and the influence these lymphoid organs exert within the tumor microenvironment. Here, we briefly review TLS structure, function, and response to treatment in the setting of CM. To uncover potential tumor-intrinsic mechanisms that regulate TLS formation, we have taken the novel perspective of evaluating TLS induction in melanomas impacted by common driver mutations in BRAF, PTEN, NRAS, KIT, PRDM1, and MITF. Through analysis of The Cancer Genome Atlas (TCGA), we show expression of DNA repair proteins (DRPs) including BRCA1, PAXIP, ERCC1, ERCC2, ERCC3, MSH2, and PMS2 to be negatively correlated with expression of pro-TLS genes, suggesting DRP loss may favor TLS development in support of improved patient outcome and patient response to interventional immunotherapy.

Skeletal muscle-specific over-expression of the nuclear sirtuin SIRT6 blocks cancer-associated cachexia by regulating multiple targets

BACKGROUND

During cancer cachexia, cytokines released from tumour cells can alter body's metabolism, which can lead to onset of this disease process. Biological basis of cachexia is multifactorial; hence, it is important to identify and modulate multiple targets to curtail the process of cachexia. Previously, we reported that the nuclear sirtuin, SIRT6, blocks expression of myostatin, a negative regulator of muscle growth, through modulation of the NF-κB signalling. This study was undertaken to test whether muscle-specific over-expression of SIRT6 can block the cancer-associated muscle wasting in vivo and to identify additional relevant targets of SIRT6, which can explain its ability to maintain muscle health.

METHODS

We generated a skeletal muscle-specific SIRT6 over-expressing transgenic mouse line (Sk.T6Tg) expressing SIRT6 at a moderate (two-fold to four-fold) level, compared with its control littermates. To generate a cancer-cachexia model, B16F10 mouse melanoma cells were injected subcutaneously in the flanks of mice. Gastrocnemius muscle tissues from non-tumour and tumour controls and Sk.T6Tg mice (n = 5-20) were analysed by histology, immunoblotting, and RT-qPCR. Plasma samples of mice were evaluated using cytokine arrays and ELISA in both non-tumour and tumour conditions.

RESULTS

Our results demonstrate dual benefits of muscle-specific moderate over-expression of SIRT6 in a mouse model of cancer-cachexia. In tumour-bearing mice, SIRT6 over-expression preserved muscle weight (P < 0.001) and fibre size (P < 0.005) as well as suppressed tumour growth (P < 0.05). SIRT6 over-expression significantly reduced myostatin expression and plasma free fatty acids levels but maintained plasma insulin levels in tumour-bearing mice. These positive effects of SIRT6 were associated with downregulation of the circulatory chemokine, CXCL10, and the myokine, WNT4. SIRT6 also upregulated expression of GLUT4, the major glucose transporter in the skeletal muscle. These results for the first time demonstrate that SIRT6 regulates multiple targets to limit tumour growth and cancer-associated muscle atrophy.

CONCLUSION

Given the multifactorial nature of cachexia, SIRT6, which concurrently controls multiple pathways, can be a valuable therapeutic target to overcome this debilitating syndrome.

MicroRNAs and target molecules in bladder cancer

Bladder cancer (BC) is considered as one of the most common malignant tumors in humans with complex pathogenesis including gene expression variation, protein degradation, and changes in signaling pathways. Many studies on involved miRNAs in BC have demonstrated that they could be used as potential biomarkers in the prognosis, response to treatment, and screening before the cancerous phenotype onset. MicroRNAs (miRNAs) regulate many cellular processes through their different effects on special targets along with modifying signaling pathways, apoptosis, cell growth, and differentiation. The diverse expression of miRNAs in cancerous tissues could mediate procedures leading to the oncogenic or suppressor behavior of certain genes in cancer cells. Since a specific miRNA may have multiple targets, an mRNA could also be regulated by multiple miRNAs which further demonstrates the actual role of miRNAs in cancer. In addition, miRNAs can be utilized as biomarkers in some cancers that cannot be screened in the early stages. Hence, finding blood, urine, or tissue miRNA biomarkers by novel or routine gene expression method could be an essential step in the prognosis and control of cancer. In the present review, we have thoroughly evaluated the recent findings on different miRNAs in BC which can provide comprehensive information on better understanding the role of diverse miRNAs and better decision making regarding the new approaches in the diagnosis, prognosis, prevention, and treatment of BC.

Insights Into the Albinism Mechanism for Two Distinct Color Morphs of Northern Snakehead, Channa argus Through Histological and Transcriptome Analyses

The great northern snakehead (Channa argus) is one of the most important economic and conservational fish in China. In this study, the melanocytes in the skin of two distinct color morphs C. argus were investigated and compared through employment of the microscopic analysis, hematoxylin and eosin (H&E) and Masson Fontana staining. Our results demonstrated the uneven distribution of melanocytes with extremely low density and most of them were in the state of aging or death. Meanwhile, there was no obvious pigment layer and melanocytes distribution pattern found in the albino-type (AT), while the melanocytes were evenly distributed with abundance in the bicolor-type (BT). The transcriptome analysis through Illumina HiSeq sequencing showed that a total of 34.93 Gb Clean Data was obtained, and Q30 base percentage reached 92.66%. The BT and AT northern snakeheads transcriptome data included a total of 56,039,701 and 60,410,063 clean reads (n = 3), respectively. In gene expression analyses, the sample correlation coefficients (r) were ranged between 0.92 and 1.00; the contribution of PC1 and PC2 were 50.25 and 13.73% by using PCA cluster analysis, the total number of DEGs were 1024 (559 up-regulated and 465 down-regulated), and the number of annotated DEGs was 767 (COG 172, KEGG 262, GO 288, SwissProt 548, Pfam 579 and NR 765). Additionally, 46,363 ± 873 and 44,947 ± 392 single nucleotide polymorphisms (SNPs) were compiled via genetic structure analysis, respectively. Ten key pigment-related genes were screened using qRT-PCR. And all of them revealed extremely higher expression levels in the skin of BT than those of AT. This is the first study to analyze the mechanism of albino characteristics of Channa via histology and transcriptomics, and also provide the oretical and practical support for the protection and development of germplasm resources for C. argus.

CXCL13 and Its Receptor CXCR5 in Cancer: Inflammation, Immune Response, and Beyond

It is well-established that the chemokine C-X-C motif ligand 13 (CXCL13) and its receptor, the G-protein coupled receptor (GPCR) CXCR5, play fundamental roles in inflammatory, infectious and immune responses. Originally identified as a B-cell chemoattractant, CXCL13 exerts important functions in lymphoid neogenesis, and has been widely implicated in the pathogenesis of a number of autoimmune diseases and inflammatory conditions, as well as in lymphoproliferative disorders. Current evidence also indicates that the CXCL13:CXCR5 axis orchestrates cell-cell interactions that regulate lymphocyte infiltration within the tumor microenvironment, thereby determining responsiveness to cytotoxic and immune-targeted therapies. In this review, we provide a comprehensive perspective of the involvement of CXCL13 and its receptor in cancer progression. Studies in recent years postulated novel roles for this chemokine in controlling the cancer cell phenotype, and suggest important functions in the growth and metastatic dissemination of solid tumors. Carcinogens have been found to induce CXCL13 production, and production of this chemokine within the tumor milieu has been shown to impact the proliferation, migration, and invasive properties of cancer cells. Thus, the complex networks of cellular interactions involving tumoral CXCL13 and CXCR5 integrate to promote cancer cell autonomous and non-autonomous responses, highlighting the relevance of autocrine and paracrine interactions in dictating the cancer phenotype. Dissecting the molecular and signaling events regulated by CXCL13 and how this chemokine dynamically controls the interaction between the cancer cell and the tumor microenvironment is key to identify novel effectors and therapeutic targets for cancer treatment.

Expression of Neural Crest Markers GLDC and ERRFI1 is Correlated with Melanoma Prognosis

Regulation of particular genes during the formation of neural crest (NC) cells is also described during progression of malignant melanoma. In this context, it is of paramount importance to develop neural crest models allowing the identification of candidate genes, which could be used as biomarkers for melanoma prognosis. Here, we used a human induced Pluripotent Stem Cells (iPSC)-based approach to present novel NC-associated genes, expression of which was upregulated in melanoma. A list of 8 candidate genes, based on highest upregulation, was tested for prognostic value in a tissue microarray analysis containing samples from advanced melanoma (good versus bad prognosis) as well as from high-risk primary melanomas (early metastasizing versus non or late-metastasizing). CD271, GLDC, and ERRFI1 showed significantly higher expression in metastatic patients who died early than the ones who survived at least 30 months. In addition, GLDC and TWIST showed a significantly higher immunohistochemistry (IHC) score in primary melanomas from patients who developed metastases within 12 months versus those who did not develop metastases in 30 months. In conclusion, our iPSC-based study reveals a significant association of NC marker GLDC protein expression with melanoma prognosis.

The Implication of mRNA Degradation Disorders on Human DISease: Focus on DIS3 and DIS3-Like Enzymes

RNA degradation is considered a critical posttranscriptional regulatory checkpoint, maintaining the correct functioning of organisms. When a specific RNA transcript is no longer required in the cell, it is signaled for degradation through a number of highly regulated steps. Ribonucleases (or simply RNases) are key enzymes involved in the control of RNA stability. These enzymes can perform the RNA degradation alone or cooperate with other proteins in RNA degradation complexes. Important findings over the last years have shed light into eukaryotic RNA degradation by members of the RNase II/RNB family of enzymes. DIS3 enzyme belongs to this family and represents one of the catalytic subunits of the multiprotein complex exosome. This RNase has a diverse range of functions, mainly within nuclear RNA metabolism. Humans encode two other DIS3-like enzymes: DIS3L (DIS3L1) and DIS3L2. DIS3L1 also acts in association with the exosome but is strictly cytoplasmic. In contrast, DIS3L2 acts independently of the exosome and shows a distinctive preference for uridylated RNAs. These enzymes have been shown to be involved in important cellular processes, such as mitotic control, and associated with human disorders like cancer. This review shows how the impairment of function of each of these enzymes is implicated in human disease.

Predictive genetic profiles for regional lymph node metastasis in primary cutaneous melanoma: a case-matched pilot study

Melanoma confers an estimated lifetime risk of one in 50 for 2016. Clinicopathologic staging and sentinel lymph node biopsy (SLNB) have been the standard of care for T2 and T3 lesions. Molecular biomarkers identified in the primary lesion suggestive of metastatic potential may offer a more conclusive prognosis of these lesions. Our purpose was to investigate molecular mutations in primary melanoma that were predictive for micrometastasis as defined by a positive sentinel lymph node (SLN) in a case-controlled manner: nine patients with negative SLN and nine with positive SLN. The two cohorts were statistically identical as shown by a t-test for age (P=0.17), race (P=0.18), Breslow depth (P=0.14), Clark level (P=0.33), host response (P=0.17), ulceration (P=0.50), satellite nodules (P=0.17), lymphovascular invasion (P=0.50), and mitotic activity (P=0.09). While no single gene was significantly associated with SLN status, multivariate analysis using classification and regression tree assessment revealed two unique gene profiles that completely represented regional metastases in our cohort as defined by a positive SLN: PIK3CA (+) NRAS (-) and PIK3CA (-) ERBB4 (-) TP53 (+) SMAD4 (-). These profiles were identified in 89% of the patients with positive SLN; none of these profiles were identified in the SLN-negative cohort. We identified two unique gene profiles associated with positive SLN that do not overlap other studies and highlight the genetic complexity that portends the metastatic phenotype in cutaneous melanoma.

Molecular classification and subtype-specific characterization of skin cutaneous melanoma by aggregating multiple genomic platform data

PURPOSE

Traditional classification of melanoma is widely utilized with little apparent results making the development of robust classifiers that can guide therapies an urgency. Successful seminal research on classification has provided a wider understanding of cancer from multiple molecular profiles, respectively. However, it may ignore the complementary nature of the information provided by different types of data, which motivated us to subtype melanoma by aggregating multiple genomic platform data.

METHODS

Aggregating three omics data of 328 melanoma samples, melanoma subtyping was performed by three clustering methods. Differences across subtypes were extracted by functional enrichment, epigenetically silencing, gene mutations and clinical features. Subtypes were further distinguished by putative biomarkers.

RESULTS

Functional enrichment of the subtype-specific differential expression genes endowed subtypes new designation: immune, melanin and ion, in which the first subtype was enriched for immune system, the second was characterized by melanin and pigmentation, and the third was enriched for ion-involved transmission process. Subtypes also differed in age, Breslow thickness, tumor site, mutation frequency of BRAF, PTGS2, CDKN2A, CDKN2B and incidence of epigenetically silencing for IL15RA, EPSTI1, LXN, CDKN1B genes.

CONCLUSIONS

Skin cutaneous melanoma can be robustly divided into three subtypes by SNFCC+. Compared with the TCGA classification derived from gene expression, the subtypes we presented share concordance, but new traits are excavated. Such a genomic classification offers insights to further personalize therapeutic decision-making and melanoma management.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA⁺/CDK1⁺ and CENPA⁺/CDC20⁺ were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients.

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10-4) alone remained predictive after adjusting for clinical predictors.

Repigmentation of Human Vitiligo Skin by NBUVB Is Controlled by Transcription of GLI1 and Activation of the β-Catenin Pathway in the Hair Follicle Bulge Stem Cells

Vitiligo repigmentation is a complex process in which the melanocyte-depleted interfollicular epidermis is repopulated by melanocyte precursors from hair follicle bulge that proliferate, migrate, and differentiate into mature melanocytes on their way to the epidermis. The strongest stimulus for vitiligo repigmentation is narrow-band UVB (NBUVB), but how the hair follicle melanocyte precursors are activated by UV light has not been extensively studied. To better understand this process, we developed an application that combined laser capture microdissection and subsequent whole transcriptome RNA sequencing of hair follicle bulge melanocyte precursors and compared their gene signatures to that of regenerated mature epidermal melanocytes from NBUVB-treated vitiligo skin. Using this strategy, we found up-regulation of TNC, GJB6, and THBS1 in the hair follicle bulge melanocytes and of TYR in the epidermal melanocytes of the NBUVB-treated vitiligo skin. We validated these results by quantitative real-time-PCR using NBUVB-treated vitiligo skin and untreated normal skin. We also identified that GLI1, a candidate stem cell-associated gene, is significantly up-regulated in the melanocytes captured from NBUVB-treated vitiligo bulge compared with untreated vitiligo bulge. These signals are potential key players in the activation of bulge melanocyte precursors during vitiligo repigmentation.

Interaction between miR-572 and PPP2R2C, and their effects on the proliferation, migration, and invasion of nasopharyngeal carcinoma (NPC) cells

We investigated the how miR-572 regulates PPP2R2C, and studied the effects of miR-572 and PPP2R2C on proliferation and migration as well as invasion of nasopharyngeal carcinoma (NPC) cells. NPC tissues and normal tissues were collected, and the expressions of miR-572 and PPP2R2C were detected by real-time PCR. Western blot was applied to detect the expression of PPP2R2C protein. The target relationship between miR-572 and PPP2R2C was confirmed by dual luciferase reporter gene assay. MTT assay and flow cytometry were applied to investigate the viability and apoptosis levels of NPC cells. Transwell as well as wound healing assays were used, respectively, to detect the invasiveness and migration of NPC cells. MiR-572 was highly expressed in NPC tissues as well as NPC cells, and there was lower expression of PPP2R2C in NPC tissues compared with normal samples. MiR-572 could bind to the 3' UTR of PPP2R2C and decrease its expression. Over-expressed miR-572 and decreased PPP2R2C expression could both inhibit proliferation and invasion and induce apoptosis of NPC cells. Thus, miR-572 promotes the proliferation and invasion of NPC by directly down-regulating PPP2R2C.

Quantitative comparison of the spreading and invasion of radial growth phase and metastatic melanoma cells in a three-dimensional human skin equivalent model

BACKGROUND

Standard two-dimensional (2D) cell migration assays do not provide information about vertical invasion processes, which are critical for melanoma progression. We provide information about three-dimensional (3D) melanoma cell migration, proliferation and invasion in a 3D melanoma skin equivalent (MSE) model. In particular, we pay careful attention to compare the structure of the tissues in the MSE with similarly-prepared 3D human skin equivalent (HSE) models. The HSE model is identically prepared to the MSE model except that melanoma cells are omitted. Using the MSE model, we examine melanoma migration, proliferation and invasion from two different human melanoma cell lines. One cell line, WM35, is associated with the early phase of the disease where spreading is thought to be confined to the epidermis. The other cell line, SK-MEL-28, is associated with the later phase of the disease where spreading into the dermis is expected.

METHODS

3D MSE and HSE models are constructed using human de-epidermised dermis (DED) prepared from skin tissue. Primary fibroblasts and primary keratinocytes are used in the MSE and HSE models to ensure the formation of a stratified epidermis, with a well-defined basement membrane. Radial spreading of cells across the surface of the HSE and MSE models is observed. Vertical invasion of melanoma cells downward through the skin is observed and measured using immunohistochemistry. All measurements of invasion are made at day 0, 9, 15 and 20, providing detailed time course data.

RESULTS

Both HSE and MSE models are similar to native skin in vivo, with a well-defined stratification of the epidermis that is separated from the dermis by a basement membrane. In the HSE and MSE we find fibroblast cells confined to the dermis, and differentiated keratinocytes in the epidermis. In the MSE, melanoma cells form colonies in the epidermis during the early part of the experiment. In the later stage of the experiment, the melanoma cells in the MSE invade deeper into the tissues. Interestingly, both the WM35 and SK-MEL-28 melanoma cells lead to a breakdown of the basement membrane and eventually enter the dermis. However, these two cell lines invade at different rates, with the SK-MEL-28 melanoma cells invading faster than the WM35 cells.

DISCUSSION

The MSE and HSE models are a reliable platform for studying melanoma invasion in a 3D tissue that is similar to native human skin. Interestingly, we find that the WM35 cell line, that is thought to be associated with radial spreading only, is able to invade into the dermis. The vertical invasion of melanoma cells into the dermal region appears to be associated with a localised disruption of the basement membrane. Presenting our results in terms of time course data, along with images and quantitative measurements of the depth of invasion extends previous 3D work that has often been reported without these details.

KLHL21, a novel gene that contributes to the progression of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) has very high prevalence and associated-mortality. However, targeted therapies that are currently used in clinical practice for HCC have certain limitations, in part because of the lack of reliable and clinically applicable biomarkers that can be used for diagnosis and prognosis assessments and for the surveillance of treatment effectiveness.

METHODS

Meta-analysis was used to analyze the integrated microarray data for global identification of a set of robust biomarkers for HCC. Quantitative RT-PCR (qRT-PCR) was performed to validate the expression levels of selected genes. Gene expression was inhibited by siRNA. CellTiter 96^® AQueous One Solution Cell Proliferation assays were used to determine cell proliferation, and Transwell assays were used to determine cell migration and invasion potential.

RESULTS

Meta-analysis of the expression data provided a gene expression signature from a total of 1525 patients with HCC, showing 1529 up-regulated genes and 478 down-regulated genes in cancer samples. The expression levels of genes having strong clinical significance were validated by qRT-PCR using primary HCC tissues and the paired adjacent noncancerous liver tissues. Up-regulation of VPS45, WIPI1, TTC1, IGBP1 and KLHL21 genes and down-regulation of FCGRT gene were confirmed in clinical HCC samples. KLHL21 was the most promising gene for potential use as a bioclinical marker in this analysis. Abrogating expression of it significantly inhibited cell proliferation, migration and invasion.

CONCLUSIONS

Our study suggests that KLHL21 is a potential target for therapeutic intervention. Our findings also provide novel candidate genes on a genome-wide scale, which may have significant impact on the design and execution of effective therapy of HCC patients.

Identification of novel genes that regulate androgen receptor signaling and growth of androgen-deprived prostate cancer cells

Prostate cancer progression to castration refractory disease is associated with anomalous transcriptional activity of the androgen receptor (AR) in an androgen-depleted milieu. To identify novel gene products whose downregulation transactivates AR in prostate cancer cells, we performed a screen of enzymatically-generated shRNA lenti-libraries selecting for transduced LNCaP cells with elevated expression of a fluorescent reporter gene under the control of an AR-responsive promoter. The shRNAs present in selected populations were analyzed using high-throughput sequencing to identify target genes. Highly enriched gene targets were then validated with siRNAs against selected genes, testing first for increased expression of luciferase from an AR-responsive promoter and then for altered expression of endogenous androgen-regulated genes in LNCaP cells. We identified 20 human genes whose silencing affected the expression of exogenous and endogenous androgen-responsive genes in prostate cancer cells grown in androgen-depleted medium. Knockdown of four of these genes upregulated the expression of endogenous AR targets and siRNAs targeting two of these genes (IGSF8 and RTN1) enabled androgen-independent proliferation of androgen-dependent cells. The effects of IGSF8 appear to be mediated through its interaction with a tetraspanin protein, CD9, previously implicated in prostate cancer progression. Remarkably, homozygous deletions of IGSF8 are found almost exclusively in prostate cancers but not in other cancer types. Our study shows that androgen independence can be achieved through the inhibition of specific genes and reveals a novel set of genes that regulate AR signaling in prostate cancers.

Complex network-based approaches to biomarker discovery

Many studies on biomarker discovery have been done by analyzing mutations in DNA sequences and differences in gene expression patterns. As a new branch of the latter approach, the concept of network biomarkers has been proposed, in which expression data of small subnetworks are used as markers. Furthermore, network biomarkers have been extended to dynamical network biomarkers, in which time series expression data of subnetworks are used as markers. On the other hand, the methodologies in complex networks have also been applied to biomarker discovery. For example, various centrality measures and the concept of observability have been applied. In this article, we review these new approaches for biomarker discovery with focusing on the computational/methodological aspects.

Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving Melanoma

Metastatic melanoma patients have a poor prognosis, mainly attributable to the underlying heterogeneity in melanoma driver genes and altered gene expression profiles. These characteristics of melanoma also make the development of drugs and identification of novel drug targets for metastatic melanoma a daunting task. Systems biology offers an alternative approach to re-explore the genes or gene sets that display dysregulated behaviour without being differentially expressed. In this study, we have performed systems biology studies to enhance our knowledge about the conserved property of disease genes or gene sets among mutually exclusive datasets representing melanoma progression. We meta-analysed 642 microarray samples to generate melanoma reconstructed networks representing four different stages of melanoma progression to extract genes with altered molecular circuitry wiring as compared to a normal cellular state. Intriguingly, a majority of the melanoma network-rewired genes are not differentially expressed and the disease genes involved in melanoma progression consistently modulate its activity by rewiring network connections. We found that the shortlisted disease genes in the study show strong and abnormal network connectivity, which enhances with the disease progression. Moreover, the deviated network properties of the disease gene sets allow ranking/prioritization of different enriched, dysregulated and conserved pathway terms in metastatic melanoma, in agreement with previous findings. Our analysis also reveals presence of distinct network hubs in different stages of metastasizing tumor for the same set of pathways in the statistically conserved gene sets. The study results are also presented as a freely available database at http://bioinfo.icgeb.res.in/m3db/. The web-based database resource consists of results from the analysis presented here, integrated with cytoscape web and user-friendly tools for visualization, retrieval and further analysis.

An Application of Sequential Meta-Analysis to Gene Expression Studies

Most of the discoveries from gene expression data are driven by a study claiming an optimal subset of genes that play a key role in a specific disease. Meta-analysis of the available datasets can help in getting concordant results so that a real-life application may be more successful. Sequential meta-analysis (SMA) is an approach for combining studies in chronological order while preserving the type I error and pre-specifying the statistical power to detect a given effect size. We focus on the application of SMA to find gene expression signatures across experiments in acute myeloid leukemia. SMA of seven raw datasets is used to evaluate whether the accumulated samples show enough evidence or more experiments should be initiated. We found 313 differentially expressed genes, based on the cumulative information of the experiments. SMA offers an alternative to existing methods in generating a gene list by evaluating the adequacy of the cumulative information.

Functional and protein‑protein interaction network analysis of colorectal cancer induced by ulcerative colitis

Colorectal cancer (CRC) is a well‑recognized complication of ulcerative colitis (UC), and patients with UC have a higher incidence of CRC, compared with the general population. However, the properties of CRC induced by UC have not been clarified using an interaction network to analyze and compare gene sets. In the present study, six microarray datasets of CRC and UC were extracted from the Array Express database, and gene signatures were identified using the genome‑wide relative significance (GWRS) method. Functional analysis was performed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Prediction of the genes and microRNA were performed using a hypergeometric method. A protein‑protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins, and clusters were obtained through the Molecular Complex Detection algorithm. Topological centrality and a novel analyzing method, based on the rank value of GWGS, were used to characterize the biological importance of the clusters. A total of 217 differentially expressed (DE) genes of CRC were identified, 341 DE genes were identified in UC, and 62 common genes existed in the two. Several KEGG pathways were the same in CRC and UC. Collagenase, progesterone, heparin, urokinase, nadh and adenosine drugs demonstrated potential for use in treatment of CRC and UC. In the PPI network of CRC, 210 nodes and 752 edges were observed, wheras 314 nodes and 882 edges were identified in UC. Cluster 3 in UC had the highest GWGS, while the topological centrality of Cluster 3 in UC had the lowest degree and betweenness. PPI network analysis provided an effective way to estimate and understand the likelihood of the potential connections between proteins/genes. The results obtained following the use of GWGS to analyze differences between clusters did not agree with the topological degree and betweenness centrality, which indicated that gene fold change based GWGS was controversial with degree here in CRC and UC.

The 3' to 5' Exoribonuclease DIS3: From Structure and Mechanisms to Biological Functions and Role in Human Disease

DIS3 is a conserved exoribonuclease and catalytic subunit of the exosome, a protein complex involved in the 3' to 5' degradation and processing of both nuclear and cytoplasmic RNA species. Recently, aberrant expression of DIS3 has been found to be implicated in a range of different cancers. Perhaps most striking is the finding that DIS3 is recurrently mutated in 11% of multiple myeloma patients. Much work has been done to elucidate the structural and biochemical characteristics of DIS3, including the mechanistic details of its role as an effector of RNA decay pathways. Nevertheless, we do not understand how DIS3 mutations can lead to cancer. There are a number of studies that pertain to the function of DIS3 at the organismal level. Mutant phenotypes in S. pombe, S. cerevisiae and Drosophila suggest DIS3 homologues have a common role in cell-cycle progression and microtubule assembly. DIS3 has also recently been implicated in antibody diversification of mouse B-cells. This article aims to review current knowledge of the structure, mechanisms and functions of DIS3 as well as highlighting the genetic patterns observed within myeloma patients, in order to yield insight into the putative role of DIS3 mutations in oncogenesis.

Molecular alterations in signal pathways of melanoma and new personalized treatment strategies: Targeting of Notch

Despite modern achievements in therapy of malignant melanomas new treatment strategies are welcomed in clinics for survival of patients. Now it is supposed that personalized molecular therapies for each patient are needed concerning a specificity of molecular alterations in patient's tumors. In human melanoma, Notch signaling interacts with other pathways, including MAPK, PI3K-AKT, NF-kB, and p53. This article discusses mutated genes and leading aberrant signal pathways in human melanoma which are of interest concerning to their perspective for personalized treatment strategies in melanoma. We speculate that E3 ubiquitin ligases MDM2 and MDM4 can be attractive therapeutic target for p53 and Notch signaling pathways in malignant melanoma by using small molecule inhibitors. It is possible that restoration of p53-MDM2-NUMB complexes in melanoma can restore wild type p53 function and positively modulate Notch pathway. In this review we summarize recent data about novel US Food and Drug Administration approved target drugs for metastatic melanoma treatment, and suppose model for treatment strategy by targeting Notch.

Identification of hepatocellular carcinoma-associated hub genes and pathways by integrated microarray analysis

AIMS AND BACKGROUND

Hepatocellular carcinoma (HCC) is a dismal malignancy associated with multiple molecular changes. The purpose of this study was to identify the differentially expressed genes and analyze the biological processes related to HCC.

METHODS AND STUDY DESIGN

Datasets of HCC were obtained from the NCBI Gene Expression Omnibus. Integrated analysis of differentially expressed genes was performed using the INMEX program. Then Gene Ontology enrichment analyses and pathway analysis were performed based on the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein-protein interaction network was constructed using the Cytoscape software; the netwerk served to find hub genes for HCC. Real-time RT-PCR was used to validate the microarray data for hub genes.

RESULTS

We identified 273 genes that were differentially expressed in HCC. Gene Ontology enrichment analyses revealed response to cadmium ion, cellular response to cadmium ion, and cellular response to zinc ion for these genes. Pathway analysis showed that significant pathways included fatty acid metabolism, butanoate metabolism, and PPAR signaling pathway. The protein-protein interaction network indicated that CDH1, ECHS1, ACAA1, MT2A, and MYC were important genes which participated in many interactions. Experimental validation of the role of four upregulated genes (ECHS1, ACAA1, MT2A and MYC) in the progression of HCC was carried out.

CONCLUSIONS

Our study displayed genes that were consistently differentially expressed in HCC. The biological pathways and protein-protein interaction networks associated with those genes were also identified. We predicted that CDH1, ECHS1, ACAA1, MT2A, and MYC might be target genes for diagnosing HCC.

Identification of hub subnetwork based on topological features of genes in breast cancer

The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer.

Melanocytes in the skin--comparative whole transcriptome analysis of main skin cell types

Melanocytes possess several functions besides a role in pigment synthesis, but detailed characteristics of the cells are still unclear. We used whole transcriptome sequencing (RNA-Seq) to assess differential gene expression of cultivated normal human melanocytes with respect to keratinocytes, fibroblasts and whole skin. The present results reveal cultivated melanocytes as highly proliferative cells with possible stem cell-like properties. The enhanced readiness to regenerate makes melanocytes the most vulnerable cells in the skin and explains their high risk of developing into malignant melanoma.

Identification of several hub-genes associated with periodontitis using integrated microarray analysis

The aim of the present study was to identify differentially expressed genes and biological processes associated with periodontitis. In this study, the most significant 200 differentially expressed genes associated with periodontitis were identified using integrated analysis of multiple microarray data in combination with screening for genome-wide relative significance and genome-wide global significance. Gene Ontology (GO) enrichment analysis and pathway analysis were performed using the GO website and Kyoto Encyclopedia of Genes and Genomes (KEGG). A protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins. The top 200 differentially expressed genes were found to be highly associated with periodontitis. GO enrichment analyses revealed that the identified genes were significantly enriched in terms of response to organic substance, response to wounding and cell migration. The most common term of the KEGG pathway was cytokine-cytokine receptor interaction. PPI network analysis indicated that interleukin (IL)8, IL1β, vascular endothelial growth factor A, intercellular adhesion molecule 1, PTGS2 and CXCL10 were hub genes, which formed numerous interactions with several genes. In conclusion, the present study identified numerous genes that were differentially expressed in periodontitis, as well as determined the biological pathways and PPI network associated with those genes.

Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses

OBJECTIVES

To explore the molecular mechanism of hepatitis B virus-related and hepatitis C virus-related hepatocellular carcinoma, samples from hepatitis B virus and hepatitis C virus infected patients and the normal were compared, respectively.

METHODS

In both experiments, genes with high value were selected based on a genome-wide relative significance and genome-wide global significance model. Co-expression network of the selected genes was constructed, and transcription factors in the network were identified. Molecular complex detection algorithm was used to obtain sub-networks.

RESULTS

Based on the new model, the top 300 genes were selected. Co-expression network was constructed and transcription factors were identified. We obtained two common genes FCN2 and CXCL14, and two common transcription factors RFX5 and EZH2. In hepatitis B virus experiment, cluster 1 and 3 had the higher value. In cluster 1, ten of the 17 genes and one transcription factor were all reported associated with hepatocellular carcinoma. In cluster 3, transcription factor ESR1 was reported related with hepatocellular carcinoma. In hepatitis C virus experiment, the value of cluster 3 and 4 was higher. In cluster 3, nine genes were reported to play a key role in hepatocellular carcinoma. In cluster 4, there were 5 genes in the 34 genes. To compare the relevance of a node in holding together communicating nodes, centralities based analysis was performed and we obtained some genes with high stress value.

CONCLUSION

The analysis above helped us to understand the pathogenesis of hepatitis B virus and hepatitis C virus associated hepatocellular carcinoma.

Gene expression profiling for targeted cancer treatment

INTRODUCTION

There is certain degree of frustration and discontent in the area of microarray gene expression data analysis of cancer datasets. It arises from the mathematical problem called 'curse of dimensionality,' which is due to the small number of samples available in training sets, used for calculating transcriptional signatures from the large number of differentially expressed (DE) genes, measured by microarrays. The new generation of causal reasoning algorithms can provide solutions to the curse of dimensionality by transforming microarray data into activity of a small number of cancer hallmark pathways. This new approach can make feature space dimensionality optimal for mathematical signature calculations.

AREAS COVERED

The author reviews the reasons behind the current frustration with transcriptional signatures derived from DE genes in cancer. He also provides an overview of the novel methods for signature calculations based on differentially variable genes and expression regulators. Furthermore, the authors provide perspectives on causal reasoning algorithms that use prior knowledge about regulatory events described in scientific literature to identify expression regulators responsible for the differential expression observed in cancer samples.

EXPERT OPINION

The author advocates causal reasoning methods to calculate cancer pathway activity signatures. The current challenge for these algorithms is in ensuring quality of the knowledgebase. Indeed, the development of cancer hallmark pathway collections, together with statistical algorithms to transform activity of expression regulators into pathway activity, are necessary for causal reasoning to be used in cancer research.

Dormancy of growth-stunted malignant melanoma: sustainable and smoldering patterns

The presentations of primary and metastatic cutaneous malignant melanoma (CMM) are very diverse. Evidence increasingly indicates that single CMM cells spread to distant sites quite early during cancer progression and are soon eliminated before they become clinically detectable. However bulky metastases which appear at a later stage might derive from some of these early neoplastic cells. It seems that local CMM single cell micro-metastases commonly predict sentinel lymph node involvement without overtly reflecting CMM progression to bulky visceral metastases. This study is intended to review the current understanding of the mechanisms underlying two CMM presentations. The first is the long interval, apparently disease-free, with persistent CMM dormancy, which may precede overt metastatic growth. Immunosurveillance may induce dormancy in single CMM cells disseminated in the body by blocking their proliferation cycle. The second is the so-called CMM smoldering phenomenon, which is marked by an alternate progression and regression of CMM locally with metastases that wax and wane for long periods of time over restricted skin areas. These very diverse patterns of CMM progression are likely to be ascribable to a number of biological factors, including the activation of CMM stem cells, and the combined phenotypic heterogeneity and variability in proliferative amplification in CMM cell clusters. Furthermore an adequate stimulation of CMM immune-surveillance and the induction of a specific stromal structure and vascular response are required. In this context, most early CMM tumors are in part controlled by lymphocyte-mediated responses before they become clinically detectable. However both the role of immune-surveillance and the mechanisms underlying both persistent and smoldering CMM dormancy remain unclear.

Skinomics: past, present and future for diagnostic microarray studies in dermatology

Easily accessible, skin was among the first targets analyzed using 'omics' and dermatology embraced the approaches very early. Microarrays have been used to define disease markers, identify transcriptional changes and even trace the course of treatment. Melanoma and psoriasis have been explored using microarrays. Particularly noteworthy is the multinational mapping of psoriasis susceptibility loci. The transcriptional changes in psoriasis have been identified using hundreds of biopsies. Epidermal keratinocytes have been studied because they respond to UV light, infections, inflammatory and immunomodulating cytokines, toxins and so on. Epidermal differentiation genes are being characterized and are expressed in human epidermal stem cells. Exciting discoveries defining human skin microbiomes have opened a new field of research with great medical potential. Specific to dermatology, the non-invasive skin sampling for microarray studies, using tape stripping, has been developed; it promises to advance dermatology toward 'omics' techniques directly applicable to the personalized medicine of the future.

Ectopic lymphoid-like structures in infection, cancer and autoimmunity

Ectopic lymphoid-like structures often develop at sites of inflammation where they influence the course of infection, autoimmune disease, cancer and transplant rejection. These lymphoid aggregates range from tight clusters of B cells and T cells to highly organized structures that comprise functional germinal centres. Although the mechanisms governing ectopic lymphoid neogenesis in human pathology remain poorly defined, the presence of ectopic lymphoid-like structures within inflamed tissues has been linked to both protective and deleterious outcomes in patients. In this Review, we discuss investigations in both experimental model systems and patient cohorts to provide a perspective on the formation and functions of ectopic lymphoid-like structures in human pathology, with particular reference to the clinical implications and the potential for therapeutic targeting.

Role of Tertiary Lymphoid Structures (TLS) in Anti-Tumor Immunity: Potential Tumor-Induced Cytokines/Chemokines that Regulate TLS Formation in Epithelial-Derived Cancers

Following the successes of monoclonal antibody immunotherapies (trastuzumab (Herceptin^®) and rituximab (Rituxan^®)) and the first approved cancer vaccine, Provenge^® (sipuleucel-T), investigations into the immune system and how it can be modified by a tumor has become an exciting and promising new field of cancer research. Dozens of clinical trials for new antibodies, cancer and adjuvant vaccines, and autologous T and dendritic cell transfers are ongoing in hopes of identifying ways to re-awaken the immune system and force an anti-tumor response. To date, however, few consistent, reproducible, or clinically-relevant effects have been shown using vaccine or autologous cell transfers due in part to the fact that the immunosuppressive mechanisms of the tumor have not been overcome. Much of the research focus has been on re-activating or priming cytotoxic T cells to recognize tumor, in some cases completely disregarding the potential roles that B cells play in immune surveillance or how a solid tumor should be treated to maximize immunogenicity. Here, we will summarize what is currently known about the induction or evasion of humoral immunity via tumor-induced cytokine/chemokine expression and how formation of tertiary lymphoid structures (TLS) within the tumor microenvironment may be used to enhance immunotherapy response.