Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility

Stem-cell states converge in multistage cutaneous squamous cell carcinoma development

Stem cells play a critical role in cancer development by contributing to cell heterogeneity, lineage plasticity, and drug resistance. We created gene expression networks from hundreds of mouse tissue samples (both normal and tumor) and integrated these with lineage tracing and single-cell RNA-seq, to identify convergence of cell states in premalignant tumor cells expressing markers of lineage plasticity and drug resistance. Two of these cell states representing multilineage plasticity or proliferation were inversely correlated, suggesting a mutually exclusive relationship. Treatment of carcinomas in vivo with chemotherapy repressed the proliferative state and activated multilineage plasticity whereas inhibition of differentiation repressed plasticity and potentiated responses to cell cycle inhibitors. Manipulation of this cell state transition point may provide a source of potential combinatorial targets for cancer therapy.

deltaXpress (ΔXpress): a tool for mapping differentially correlated genes using single-cell qPCR data

BACKGROUND

High-throughput experiments provide deep insight into the molecular biology of different species, but more tools need to be developed to handle this type of data. At the transcriptomics level, quantitative Polymerase Chain Reaction technology (qPCR) can be affordably adapted to produce high-throughput results through a single-cell approach. In addition to comparative expression profiles between groups, single-cell approaches allow us to evaluate and propose new dependency relationships among markers. However, this alternative has not been explored before for large-scale qPCR-based experiments.

RESULTS

Herein, we present deltaXpress (ΔXpress), a web app for analyzing data from single-cell qPCR experiments using a combination of HTML and R programming languages in a friendly environment. This application uses cycle threshold (Ct) values and categorical information for each sample as input, allowing the best pair of housekeeping genes to be chosen to normalize the expression of target genes. ΔXpress emulates a bulk analysis by observing differentially expressed genes, but in addition, it allows the discovery of pairwise genes differentially correlated when comparing two experimental conditions. Researchers can download normalized data or use subsequent modules to map differentially correlated genes, perform conventional comparisons between experimental groups, obtain additional information about their genes (gene glossary), and generate ready-to-publication images (600 dots per inch).

CONCLUSIONS

ΔXpress web app is freely available to non-commercial users at https://alexismurillo.shinyapps.io/dXpress/ and can be used for different experiments in all technologies involving qPCR with at least one housekeeping region.

Gene networks reveal stem-cell state convergence during preneoplasia and progression to malignancy in multistage skin carcinogenesis

Adult mammalian stem cells play critical roles in normal tissue homeostasis, as well as in tumor development, by contributing to cell heterogeneity, plasticity, and development of drug resistance. The relationship between different types of normal and cancer stem cells is highly controversial and poorly understood. Here, we carried out gene expression network analysis of normal and tumor samples from genetically heterogeneous mice to create network metagenes for visualization of stem-cell networks, rather than individual stem-cell markers, at the single-cell level during multistage carcinogenesis. We combined this approach with lineage tracing and single-cell RNASeq of stem cells and their progeny, identifying a previously unrecognized hierarchy in which Lgr6+ stem cells from tumors generate progeny that express a range of other stem-cell markers including Sox2, Pitx1, Foxa1, Klf5, and Cd44. Our data identify a convergence of multiple stem-cell and tumor-suppressor pathways in benign tumor cells expressing markers of lineage plasticity and oxidative stress. This same single-cell population expresses network metagenes corresponding to markers of cancer drug resistance in human tumors of the skin, lung and prostate. Treatment of mouse squamous carcinomas in vivo with the chemotherapeutic cis-platin resulted in elevated expression of the genes that mark this cell population. Our data have allowed us to create a simplified model of multistage carcinogenesis that identifies distinct stem-cell states at different stages of tumor progression, thereby identifying networks involved in lineage plasticity, drug resistance, and immune surveillance, providing a rich source of potential targets for cancer therapy.

Notch dimerization and gene dosage are important for normal heart development, intestinal stem cell maintenance, and splenic marginal zone B-cell homeostasis during mite infestation

Cooperative DNA binding is a key feature of transcriptional regulation. Here we examined the role of cooperativity in Notch signaling by CRISPR-mediated engineering of mice in which neither Notch1 nor Notch2 can homo- or heterodimerize, essential for cooperative binding to sequence-paired sites (SPS) located near many Notch-regulated genes. Although most known Notch-dependent phenotypes were unaffected in Notch1/2 dimer-deficient mice, a subset of tissues proved highly sensitive to loss of cooperativity. These phenotypes include heart development, compromised viability in combination with low gene dose, and the gut, developing ulcerative colitis in response to 1% dextran sulfate sodium (DSS). The most striking phenotypes-gender imbalance and splenic marginal zone B-cell lymphoma-emerged in combination with gene dose reduction or when challenged by chronic fur mite infestation. This study highlights the role of the environment in malignancy and colitis and is consistent with Notch-dependent anti-parasite immune responses being compromised in Notch dimer-deficient animals.

VAV2 signaling promotes regenerative proliferation in both cutaneous and head and neck squamous cell carcinoma

Regenerative proliferation capacity and poor differentiation are histological features usually linked to poor prognosis in head and neck squamous cell carcinoma (hnSCC). However, the pathways that regulate them remain ill-characterized. Here, we show that those traits can be triggered by the RHO GTPase activator VAV2 in keratinocytes present in the skin and oral mucosa. VAV2 is also required to maintain those traits in hnSCC patient-derived cells. This function, which is both catalysis- and RHO GTPase-dependent, is mediated by c-Myc- and YAP/TAZ-dependent transcriptomal programs associated with regenerative proliferation and cell undifferentiation, respectively. High levels of VAV2 transcripts and VAV2-regulated gene signatures are both associated with poor hnSCC patient prognosis. These results unveil a druggable pathway linked to the malignancy of specific SCC subtypes.

The Rho signalling pathway is frequently activated in squamous carcinomas. Here, the authors find that the Rho GEF VAV2 is over expressed in both cutaneous and head and neck squamous cell carcinomas and that at the molecular level VAV2 promotes a pro-tumorigenic stem cell-like signalling programme.

Analysis of chromatin accessibility in human epidermis identifies putative barrier dysfunction-sensing enhancers

To identify putative gene regulatory regions that respond to epidermal injury, we mapped chromatin dynamics in a stratified human epidermis during barrier maturation and disruption. Engineered skin substitutes (ESS) cultured at the air-liquid interface were used as a model of developing human epidermis with incomplete barrier formation. The epidermal barrier stabilized following engraftment onto immunocompromised mice, and was compromised again upon injury. Modified formaldehyde-assisted isolation of regulatory elements (FAIRE) was used to identify accessible genomic regions characteristic of monolayer keratinocytes, ESS in vitro, grafted ESS, and tape-stripped ESS graft. We mapped differentiation- and maturation-associated changes in transcription factor binding sites enriched at each stage and observed overrepresentation of AP-1 gene family motifs in barrier-deficient samples. Transcription of TSLP, an important effector of immunological memory in response to allergen exposure, was dramatically elevated in our barrier-deficient samples. We identified dynamic DNA elements that correlated with TSLP induction and may contain enhancers that regulate TSLP. Two dynamic regions were located near the TSLP promoter and overlapped with allergy-associated SNPs rs17551370 and rs2289877, strongly implicating these loci in the regulation of TSLP expression in allergic disease. Additional dynamic chromatin regions ~250kb upstream of the TSLP promoter were found to be in high linkage disequilibrium with allergic disease SNPs. Taken together, these results define dynamic chromatin accessibility changes during epidermal development and dysfunction.

Molecular and genetic inflammation networks in major human diseases

It has been well-recognized that inflammation alongside tissue repair and damage maintaining tissue homeostasis determines the initiation and progression of complex diseases. Albeit with the accomplishment of having captured the most critical inflammation-involved molecules, genetic susceptibilities, epigenetic factors, and environmental factors, our schemata on the role of inflammation in complex diseases remain largely patchy, in part due to the success of reductionism in terms of research methodology per se. Omics data alongside the advances in data integration technologies have enabled reconstruction of molecular and genetic inflammation networks which shed light on the underlying pathophysiology of complex diseases or clinical conditions. Given the proven beneficial role of anti-inflammation in coronary heart disease as well as other complex diseases and immunotherapy as a revolutionary transition in oncology, it becomes timely to review our current understanding of the molecular and genetic inflammation networks underlying major human diseases. In this review, we first briefly discuss the complexity of infectious diseases and then highlight recently uncovered molecular and genetic inflammation networks in other major human diseases including obesity, type II diabetes, coronary heart disease, late onset Alzheimer's disease, Parkinson's disease, and sporadic cancer. The commonality and specificity of these molecular networks are addressed in the context of genetics based on genome-wide association study (GWAS). The double-sword role of inflammation, such as how the aberrant type 1 and/or type 2 immunity leads to chronic and severe clinical conditions, remains open in terms of the inflammasome and the core inflammatome network features. Increasingly available large Omics and clinical data in tandem with systems biology approaches have offered an exciting yet challenging opportunity toward reconstruction of more comprehensive and dynamic molecular and genetic inflammation networks, which hold great promise in transiting network snapshots to video-style multi-scale interplays of disease mechanisms, in turn leading to effective clinical intervention.

Association between genetic variants in the promoter region of a novel antisense long noncoding RNA RP11-392P7.6 and colorectal cancer risk

There is a widespread occurrence of antisense transcripts' regulation on cancer-related genes in cancer biology. RP11-392P7.6 is antisense to the coding region of cancer-related gene GPRC5D, which has been found recently. The aim of this study was to investigate the associations of tagSNPs in the promoter region of RP11-392P7.6 with the risk of colorectal cancer. We conducted a two-stage case-control study, with a discovery set (320 cases and 319 controls) and a validation set (501 cases and 538 controls). Four tagSNPs (rs1531970, rs1642199, rs4763903, and rs10845671) were selected based on 1000 Genomes Project data and genotyped by using the Sequenom MassARRAY genotyping platform. In the discovery set, three tagSNPs (rs1642199, rs4763903, and rs10845671) were revealed promising associations with the risk of colorectal cancer, among which the rs10845671 variants were further replicated in the validation set (OR = 1.47, 95% CI = 1.10-1.20 in heterozygote codominant model; OR = 1.38, 95% CI = 1.04-1.83 in dominant model). When combined the two sets, the above positive associations remained unchanged. Rs10845671 was found to be associated with an increased risk of colorectal cancer (OR = 1.43, 95% CI = 1.14-1.81 in heterozygote codominant model; OR = 1.35, 95% CI = 1.08-1.69 in dominant model). These findings indicate that rs10845671 may contribute to the susceptibility to colorectal cancer and be a candidate biomarker for colorectal cancer risk prediction. Environ. Mol. Mutagen. 58:434-442, 2017. © 2017 Wiley Periodicals, Inc.

Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer

Background

Body mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity.

Methods

In order to gain insight into the genetic factors linking BMI and cancer, we performed chemical carcinogenesis on a genetically heterogeneous cohort of interspecific backcross mice ((Mus Spretus × FVB/N) F1 × FVB/N). Using this cohort, we performed quantitative trait loci (QTL) analysis to identify regions linked to BMI. We then performed an integrated analysis incorporating gene expression, sequence comparison between strains, and gene expression network analysis to identify candidate genes influencing both tumor development and BMI.

Results

Analysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network. Pre-treatment Panx3 gene expression levels in normal skin are associated with tumor susceptibility and inhibition of Panx function strongly influences inflammation.

Conclusions

These studies have identified several genetic loci that influence both BMI and carcinogenesis and implicate Panx3 as a candidate gene that links these phenotypes through its effects on inflammation and lipid metabolism.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0334-8) contains supplementary material, which is available to authorized users.

Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer

Inherited germline polymorphisms can cause gene expression levels in normal tissues to differ substantially between individuals. We present an analysis of the genetic architecture of normal adult skin from 470 genetically unique mice, demonstrating the effect of germline variants, skin tissue location, and perturbation by exogenous inflammation or tumorigenesis on gene signaling pathways. Gene networks related to specific cell types and signaling pathways, including sonic hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins, differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for expression quantitative trait loci (eQTL) network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules.

Expression quantitative trait analysis reveals fine germline transcript regulation in mouse lung tumors

Gene expression modulates cellular functions in both physiologic and pathologic conditions. Herein, we carried out a genetic linkage study on the transcriptome of lung tumors induced by urethane in an (A/J x C57BL/6)F4 intercross population, whose individual lung tumor multiplicity (Nlung) is linked to the genotype at the Pulmonary adenoma susceptibility 1 (Pas1) locus. We found that expression levels of 1179 and 1579 genes are modulated by an expression quantitative trait locus (eQTL) in cis and in trans, respectively (LOD score > 5). Of note, the genomic area surrounding and including the Pas1 locus regulated 14 genes in cis and 857 genes in trans. In lung tumors of the same (A/J x C57BL/6)F4 mice, we found 1124 genes whose transcript levels associated with Nlung (FDR < 0.001). The expression levels of about a third of these genes (n = 401) were regulated by the genotype at the Pas1 locus. Pathway analysis of the sets of genes associated with Nlung and regulated by Pas1 revealed a set of 14 recurrently represented genes that are components or targets of the Ras-Erk and Pi3k-Akt signaling pathways. Altogether our results illustrate the architecture of germline control of gene expression in mouse lung cancer: they highlight the importance of Pas1 as a tumor-modifier locus, attribute to it a novel role as a major regulator of transcription in lung tumor nodules and strengthen the candidacy of the Kras gene as the effector of this locus.

HZE Radiation Non-Targeted Effects on the Microenvironment That Mediate Mammary Carcinogenesis

Clear mechanistic understanding of the biological processes elicited by radiation that increase cancer risk can be used to inform prediction of health consequences of medical uses, such as radiotherapy, or occupational exposures, such as those of astronauts during deep space travel. Here, we review the current concepts of carcinogenesis as a multicellular process during which transformed cells escape normal tissue controls, including the immune system, and establish a tumor microenvironment. We discuss the contribution of two broad classes of radiation effects that may increase cancer: radiation targeted effects that occur as a result of direct energy deposition, e.g., DNA damage, and non-targeted effects (NTE) that result from changes in cell signaling, e.g., genomic instability. It is unknown whether the potentially greater carcinogenic effect of high Z and energy (HZE) particle radiation is a function of the relative contribution or extent of NTE or due to unique NTE. We addressed this problem using a radiation/genetic mammary chimera mouse model of breast cancer. Our experiments suggest that NTE promote more aggressive cancers, as evidenced by increased growth rate, transcriptomic signatures, and metastasis, and that HZE particle NTE are more effective than reference γ-radiation. Emerging evidence suggest that HZE irradiation dampens antitumor immunity. These studies raise concern that HZE radiation exposure not only increases the likelihood of developing cancer but also could promote progression to more aggressive cancer with a greater risk of mortality.

Belief propagation in genotype-phenotype networks

Graphical models have proven to be a valuable tool for connecting genotypes and phenotypes. Structural learning of phenotype-genotype networks has received considerable attention in the post-genome era. In recent years, a dozen different methods have emerged for network inference, which leverage natural variation that arises in certain genetic populations. The structure of the network itself can be used to form hypotheses based on the inferred direct and indirect network relationships, but represents a premature endpoint to the graphical analyses. In this work, we extend this endpoint. We examine the unexplored problem of perturbing a given network structure, and quantifying the system-wide effects on the network in a node-wise manner. The perturbation is achieved through the setting of values of phenotype node(s), which may reflect an inhibition or activation, and propagating this information through the entire network. We leverage belief propagation methods in Conditional Gaussian Bayesian Networks (CG-BNs), in order to absorb and propagate phenotypic evidence through the network. We show that the modeling assumptions adopted for genotype-phenotype networks represent an important sub-class of CG-BNs, which possess properties that ensure exact inference in the propagation scheme. The system-wide effects of the perturbation are quantified in a node-wise manner through the comparison of perturbed and unperturbed marginal distributions using a symmetric Kullback-Leibler divergence. Applications to kidney and skin cancer expression quantitative trait loci (eQTL) data from different mus musculus populations are presented. System-wide effects in the network were predicted and visualized across a spectrum of evidence. Sub-pathways and regions of the network responded in concert, suggesting co-regulation and coordination throughout the network in response to phenotypic changes. We demonstrate how these predicted system-wide effects can be examined in connection with estimated class probabilities for covariates of interest, e.g. cancer status. Despite the uncertainty in the network structure, we demonstrate the system-wide predictions are stable across an ensemble of highly likely networks. A software package, geneNetBP, which implements our approach, was developed in the R programming language.

Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers

Human tumors show a high level of genetic heterogeneity, but the processes that influence the timing and route of metastatic dissemination of the subclones are unknown. Here we have used whole-exome sequencing of 103 matched benign, malignant and metastatic skin tumors from genetically heterogeneous mice to demonstrate that most metastases disseminate synchronously from the primary tumor, supporting parallel rather than linear evolution as the predominant model of metastasis. Shared mutations between primary carcinomas and their matched metastases have the distinct A-to-T signature of the initiating carcinogen dimethylbenzanthracene, but non-shared mutations are primarily G-to-T, a signature associated with oxidative stress. The existence of carcinomas that either did or did not metastasize in the same host animal suggests that there are tumor-intrinsic factors that influence metastatic seeding. We also demonstrate the importance of germline polymorphisms in determining allele-specific mutations, and we identify somatic genetic alterations that are specifically related to initiation of carcinogenesis by Hras or Kras mutations. Mouse tumors that mimic the genetic heterogeneity of human cancers can aid our understanding of the clonal evolution of metastasis and provide a realistic model for the testing of novel therapies.

Statistical thermodynamics of transcription profiles in normal development and tumorigeneses in cohorts of patients

Experimental biology is providing the distribution of numerous different biological molecules inside cells and in body fluids of patients. Statistical methods of analysis have very successfully examined these rather large databases. We seek to use a thermodynamic analysis to provide a physical understanding and quantitative characterization of human cancers and other pathologies within a molecule-centered approach. The key technical development is the introduction of a Lagrangian. By imposing constraints the minimal value of the Lagrangian defines a thermodynamically stable state of the cellular system. The minimization also allows using experimental data measured at a number of different conditions to evaluate the steady-state distribution of biomolecules such as messenger RNAs. Thereby the number of effectively accessible quantum states of biomolecules is determined from the experimentally measured expression levels. With the increased resolution provided by the minimization of the Lagrangian one can differentiate between normal and diseased patients and further between disease subtypes. Each such refinement corresponds to imposing an additional constraint of biological origin. The constraints are the unbalanced ongoing biological processes in the system. MicroRNA expression level data for control and diseased lung cancer patients are analyzed as an example.

Equalizer reduces SNP bias in Affymetrix microarrays

BACKGROUND

Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans.

RESULTS

By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings.

CONCLUSIONS

The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.

Genomic landscape of carcinogen-induced and genetically induced mouse skin squamous cell carcinoma

Mouse models of cancers are routinely used to study cancer biology. However, it remains unclear whether carcinogenesis in mice is driven by the same spectrum of genomic alterations found in humans. Here we conducted a comprehensive genomic analysis of 9,10-dimethyl-1,2-benzanthracene (DMBA)-induced skin cancer, the most commonly used skin cancer model, which appears as benign papillomas that progress into squamous cell carcinomas (SCCs). We also studied genetically induced SCCs that expressed G12D mutant Kras (Kras G12D) but were deficient for p53. Using whole-exome sequencing, we uncovered a characteristic mutational signature of DMBA-induced SCCs. We found that the vast majority of DMBA-induced SCCs presented recurrent mutations in Hras, Kras or Rras2 and mutations in several additional putative oncogenes and tumor-suppressor genes. Similar genes were recurrently mutated in mouse and human SCCs that were from different organs or had been exposed to different carcinogens. Invasive SCCs, but not papillomas, presented substantial chromosomal aberrations, especially in DMBA-induced and genetically induced Trp53-mutated SCCs. Metastasis occurred through sequential spreading, with relatively few additional genetic events. This study provides a framework for future functional cancer genomic studies in mice.

The developing story of Sprouty and cancer

Sprouty proteins are evolutionarily conserved modulators of MAPK/ERK pathway. Through interacting with an increasing number of effectors, mediators, and regulators with ultimate influence on multiple targets within or beyond ERK, Sprouty orchestrates a complex, multilayered regulatory system and mediates a crosstalk among different signaling pathways for a coordinated cellular response. As such, Sprouty has been implicated in various developmental and physiological processes. Evidence shows that ERK is aberrantly activated in malignant conditions. Accordingly, Sprouty deregulation has been reported in different cancer types and shown to impact cancer development, progression, and metastasis. In this article, we have tried to provide an overview of the current knowledge about the Sprouty physiology and its regulatory functions in health, as well as an updated review of the Sprouty status in cancer. Putative implications of Sprouty in cancer biology, their clinical relevance, and their proposed applications are also revisited. As a developing story, however, role of Sprouty in cancer remains to be further elucidated.

Systematic genetic analysis identifies Cis-eQTL target genes associated with glioblastoma patient survival

Prior expression quantitative trait locus (eQTL) studies have demonstrated heritable variation determining differences in gene expression. The majority of eQTL studies were based on cell lines and normal tissues. We performed cis-eQTL analysis using glioblastoma multiforme (GBM) data sets obtained from The Cancer Genome Atlas (TCGA) to systematically investigate germline variation's contribution to tumor gene expression levels. We identified 985 significant cis-eQTL associations (FDR<0.05) mapped to 978 SNP loci and 159 unique genes. Approximately 57% of these eQTLs have been previously linked to the gene expression in cell lines and normal tissues; 43% of these share cis associations known to be associated with functional annotations. About 25% of these cis-eQTL associations are also common to those identified in Breast Cancer from a recent study. Further investigation of the relationship between gene expression and patient clinical information identified 13 eQTL genes whose expression level significantly correlates with GBM patient survival (p<0.05). Most of these genes are also differentially expressed in tumor samples and organ-specific controls (p<0.05). Our results demonstrated a significant relationship of germline variation with gene expression levels in GBM. The identification of eQTLs-based expression associated survival might be important to the understanding of genetic contribution to GBM cancer prognosis.

Hair follicle disruption facilitates pathogenesis to UVB-induced cutaneous inflammation and basal cell carcinoma development in Ptch(+/-) mice

Hairless mice carrying homozygous mutations in hairless gene manifest rudimentary hair follicles (HFs), epidermal cysts, hairless phenotype, and enhanced susceptibility to squamous cell carcinomas. However, their susceptibility to basal cell carcinomas (BCCs), a neoplasm considered originated from HF-localized stem cells, is unknown. To demonstrate the role of HFs in BCC development, we bred Ptch(+/-)/C57BL6 with SKH-1 hairless mice, followed by brother-sister cross to get F2 homozygous mutant (hairless) or wild-type (haired) mice. UVB-induced inflammation was less pronounced in shaved haired than in hairless mice. In hairless mice, inflammatory infiltrate was found around the rudimentary HFs and epidermal cysts. Expression of epidermal IL1f6, S100a8, vitamin D receptor, repetin, and major histocompatibility complex II, biomarkers depicting susceptibility to cutaneous inflammation, was also higher. In these animals, HF disruption altered susceptibility to UVB-induced BCCs. Tumor onset in hairless mice was 10 weeks earlier than in haired littermates. The incidence of BCCs was significantly higher in hairless than in haired animals; however, the magnitude of sonic hedgehog signaling did not differ significantly. Overall, 100% of hairless mice developed >12 tumors per mouse after 32 weeks of UVB therapy, whereas haired mice developed fewer than three tumors per mouse after 44 weeks of long-term UVB irradiation. Tumors in hairless mice were more aggressive than in haired littermates and manifested decreased E-cadherin and enhanced mesenchymal proteins. These data provide novel evidence that disruption of HFs in Ptch(+/-) mice enhances cutaneous susceptibility to inflammation and BCCs.

Systems biology perspectives on the carcinogenic potential of radiation

This review focuses on recent experimental and modeling studies that attempt to define the physiological context in which high linear energy transfer (LET) radiation increases epithelial cancer risk and the efficiency with which it does so. Radiation carcinogenesis is a two-compartment problem: ionizing radiation can alter genomic sequence as a result of damage due to targeted effects (TE) from the interaction of energy and DNA; it can also alter phenotype and multicellular interactions that contribute to cancer by poorly understood non-targeted effects (NTE). Rather than being secondary to DNA damage and mutations that can initiate cancer, radiation NTE create the critical context in which to promote cancer. Systems biology modeling using comprehensive experimental data that integrates different levels of biological organization and time-scales is a means of identifying the key processes underlying the carcinogenic potential of high-LET radiation. We hypothesize that inflammation is a key process, and thus cancer susceptibility will depend on specific genetic predisposition to the type and duration of this response. Systems genetics using novel mouse models can be used to identify such determinants of susceptibility to cancer in radiation sensitive tissues following high-LET radiation. Improved understanding of radiation carcinogenesis achieved by defining the relative contribution of NTE carcinogenic effects and identifying the genetic determinants of the high-LET cancer susceptibility will help reduce uncertainties in radiation risk assessment.

Are all granzymes cytotoxic in vivo?

Granzymes are serine proteases mainly found in cytotoxic lymphocytes. The most-studied member of this group is granzyme B, which is a potent cytotoxin that has set the paradigm that all granzymes are cyototoxic. In the last 5 years, this paradigm has become controversial. On one hand, there is a plethora of sometimes contradictory publications showing mainly caspase-independent cytotoxic effects of granzyme A and the so-called orphan granzymes in vitro. On the other hand, there are increasing numbers of reports of granzymes failing to induce cell death in vitro unless very high (potentially supra-physiological) concentrations are used. Furthermore, experiments with granzyme A or granzyme M knock-out mice reveal little or no deficit in their cytotoxic lymphocytes’ killing ability ex vivo, but indicate impairment in the inflammatory response. These findings of non-cytotoxic effects of granzymes challenge dogma, and thus require alternative or additional explanations to be developed of the role of granzymes in defeating pathogens. Here we review evidence for granzyme cytotoxicity, give an overview of their non-cytotoxic functions, and suggest technical improvements for future investigations.

Transcriptome analysis of psoriasis in a large case-control sample: RNA-seq provides insights into disease mechanisms

To increase our understanding of psoriasis, we utilized RNA-seq to assay the transcriptomes of lesional psoriatic and normal skin. We sequenced polyadenylated RNA-derived cDNAs from 92 psoriatic and 82 normal punch biopsies, generating an average of ~38 million single-end 80-bp reads per sample. Comparison of 42 samples examined by both RNA-seq and microarray revealed marked differences in sensitivity, with transcripts identified only by RNA-seq having much lower expression than those also identified by microarray. RNA-seq identified many more differentially expressed transcripts enriched in immune system processes. Weighted gene co-expression network analysis (WGCNA) revealed multiple modules of coordinately expressed epidermal differentiation genes, overlapping significantly with genes regulated by the long non-coding RNA TINCR, its target gene, staufen-1 (STAU1), the p63 target gene ZNF750, and its target KLF4. Other coordinately expressed modules were enriched for lymphoid and/or myeloid signature transcripts and genes induced by IL-17 in keratinocytes. Dermally-expressed genes were significantly down-regulated in psoriatic biopsies, most likely due to expansion of the epidermal compartment. These results demonstrate the power of WGCNA to elucidate gene regulatory circuits in psoriasis, and emphasize the influence of tissue architecture in both differential expression and co-expression analysis.

The 5p12 breast cancer susceptibility locus affects MRPS30 expression in estrogen-receptor positive tumors

Genome-wide association studies have identified numerous loci linked to breast cancer susceptibility, but the mechanism by which variations at these loci influence susceptibility is usually unknown. Some variants are only associated with particular clinical subtypes of breast cancer. Understanding how and why these variants influence subtype-specific cancer risk contributes to our understanding of cancer etiology. We conducted a genome-wide expression Quantitative Trait Locus (eQTL) study in a discovery set of 287 breast tumors and 97 normal mammary tissue samples and a replication set of 235 breast tumors. We found that the risk-associated allele of rs7716600 in the 5p12 estrogen receptor-positive (ER-positive) susceptibility locus was associated with elevated expression of the nearby gene MRPS30 exclusively in ER-positive tumors. We replicated this finding in 235 independent tumors. Further, we showed the rs7716600 risk genotype was associated with decreased MRPS30 promoter methylation exclusively in ER-positive breast tumors. In vitro studies in MCF-7 cells carrying the protective genotype showed that estrogen stimulation decreased MRPS30 promoter chromatin availability and mRNA levels. In contrast, in 600MPE cells carrying the risk genotype, estrogen increased MRPS30 expression and did not affect promoter availability. Our data suggest the 5p12 risk allele affects MRPS30 expression in estrogen-responsive tumor cells after tumor initiation by a mechanism affecting chromatin availability. These studies emphasize that the genetic architecture of breast cancer is context-specific, and integrated analysis of gene expression and chromatin remodeling in normal and tumor tissues will be required to explain the mechanisms of risk alleles.

Rewiring of human lung cell lineage and mitotic networks in lung adenocarcinomas

Analysis of gene expression patterns in normal tissues and their perturbations in tumors can help to identify the functional roles of oncogenes or tumor suppressors and identify potential new therapeutic targets. Here, gene expression correlation networks were derived from 92 normal human lung samples and patient-matched adenocarcinomas. The networks from normal lung show that NKX2-1 is linked to the alveolar type 2 lineage, and identify PEBP4 as a novel marker expressed in alveolar type 2 cells. Differential correlation analysis shows that the NKX2-1 network in tumors includes pathways associated with glutamate metabolism, and identifies Vaccinia-related kinase (VRK1) as a potential drug target in a tumor-specific mitotic network. We show that VRK1 inhibition cooperates with inhibition of PARP signaling to inhibit growth of lung tumor cells. Targeting of genes that are recruited into tumor mitotic networks may provide a wider therapeutic window than that seen by inhibition of known mitotic genes.

Using a systems biology approach to understand and study the mechanisms of metastasis

Metastasis remains the main cause for cancer-related deaths due to the lack of effective therapy. The clonal selection model has long been thought to be the primary mechanism of metastatic progression but many different mechanisms have been hypothesized for the progression from tumorigenesis to the successful dissemination and expansion of tumor cells at the secondary site. MicroRNAs, germline polymorphisms in combination with the tumor microenvironment are few of the different pathways to explain the metastatic cascade. Technological advances for high-throughput screening of cells such as expression profiling, next generation sequencing, as well as global network analyses have advanced the studies of these mechanisms. Combined with new insights into the various mechanisms of metastasis a systems biology approach has also been shown to be useful in identifying metastasis-specific gene signatures as well as predicting disease outcome. Furthermore, the results of these studies have been relevant for identifying biomarkers for metastatic disease.

A network perspective on unraveling the role of TRP channels in biology and disease

Transient receptor potential (TRP) channels are a large family of non-selective cation channels that mediate numerous physiological and pathophysiological processes; however, still largely unknown are the underlying molecular mechanisms. With data generated on an unprecedented scale, network-based approaches have been revolutionizing the way in which we understand biology and disease, discover disease genes, and develop therapeutic strategies. These circumstances have created opportunities to encounter TRP channel research to data-intensive science. In this review, we provide an introduction of network-based approaches in biomedical science, describe the current state of TRP channel network biology, and discuss the future direction of TRP channel research. Network perspective will facilitate the discovery of latent roles and underlying mechanisms of TRP channels in biology and disease.

Heterogeneity of gene expression in murine squamous cell carcinoma development-the same tumor by different means

Transformation is a complex process, involving many changes in the cell. In this work, we investigated the transcriptional changes that arose during the development of squamous cell carcinoma (SCC) in mice. Using microarray analysis, we looked at gene expression during different stages in cancer progression in 31 mice. By analyzing tumor progression in each mouse separately, we were able to define the global changes that were common to all 31 mice, as well as significant changes that occurred in fewer individuals. We found that different genes can contribute to the tumorigenic process in different mice, and that there are many ways to acquire the malignant properties defined by Hanahan and Weinberg as "hallmarks of cancer". Eventually, however, all these changes lead to a very similar cancerous phenotype. The finding that gene expression is strongly heterogeneous in tumors that were induced by a standardized protocol in closely related mice underscores the need for molecular characterization of human tumors and personalized therapy.

Inflammation and Hras signaling control epithelial-mesenchymal transition during skin tumor progression

Epithelial-mesenchymal transition (EMT) is thought to be an important, possibly essential, component of the process of tumor dissemination and metastasis. About 20%-30% of Hras mutant mouse skin carcinomas induced by chemical initiation/promotion protocols have undergone EMT. Reduced exposure to TPA-induced chronic inflammation causes a dramatic reduction in classical papillomas and squamous cell carcinomas (SCCs), but the mice still develop highly invasive carcinomas with EMT properties, reduced levels of Hras and Egfr signaling, and frequent Ink4/Arf deletions. Deletion of Hras from the mouse germline also leads to a strong reduction in squamous tumor development, but tumors now acquire activating Kras mutations and exhibit more aggressive metastatic properties. We propose that invasive carcinomas can arise by different genetic and biological routes dependent on exposure to chronic inflammation and possibly from different target cell populations within the skin. Our data have implications for the use of inhibitors of inflammation or of Ras/Egfr pathway signaling for prevention or treatment of invasive cancers.

Mathematical and statistical modeling in cancer systems biology

Cancer is a major health problem with high mortality rates. In the post-genome era, investigators have access to massive amounts of rapidly accumulating high-throughput data in publicly available databases, some of which are exclusively devoted to housing Cancer data. However, data interpretation efforts have not kept pace with data collection, and gained knowledge is not necessarily translating into better diagnoses and treatments. A fundamental problem is to integrate and interpret data to further our understanding in Cancer Systems Biology. Viewing cancer as a network provides insights into the complex mechanisms underlying the disease. Mathematical and statistical models provide an avenue for cancer network modeling. In this article, we review two widely used modeling paradigms: deterministic metabolic models and statistical graphical models. The strength of these approaches lies in their flexibility and predictive power. Once a model has been validated, it can be used to make predictions and generate hypotheses. We describe a number of diverse applications to Cancer Biology, including, the system-wide effects of drug-treatments, disease prognosis, tumor classification, forecasting treatment outcomes, and survival predictions.

On a fundamental structure of gene networks in living cells

Computers are organized into hardware and software. Using a theoretical approach to identify patterns in gene expression in a variety of species, organs, and cell types, we found that biological systems similarly are comprised of a relatively unchanging hardware-like gene pattern. Orthogonal patterns of software-like transcripts vary greatly, even among tumors of the same type from different individuals. Two distinguishable classes could be identified within the hardware-like component: those transcripts that are highly expressed and stable and an adaptable subset with lower expression that respond to external stimuli. Importantly, we demonstrate that this structure is conserved across organisms. Deletions of transcripts from the highly stable core are predicted to result in cell mortality. The approach provides a conceptual thermodynamic-like framework for the analysis of gene-expression levels and networks and their variations in diseased cells.

Progressive genomic instability in the FVB/Kras(LA2) mouse model of lung cancer

Alterations in DNA copy number contribute to the development and progression of cancers and are common in epithelial tumors. We have used array Comparative Genomic Hybridization (aCGH) to visualize DNA copy number alterations across the genomes of lung tumors in the Kras(LA2) model of lung cancer. Copy number gain involving the Kras locus, as focal amplification or whole chromosome gain, is the most common alteration in these tumors and with a prevalence that increased significantly with increasing tumor size. Furthermore, Kras amplification was the only major genomic event among the smallest lung tumors, suggesting that this alteration occurs early during the development of mutant Kras-driven lung cancers. Recurring gains and deletions of other chromosomes occur progressively more frequently among larger tumors. These results are in contrast to a previous aCGH analysis of lung tumors from Kras(LA2) mice on a mixed genetic background, in which relatively few DNA copy number alterations were observed regardless of tumor size. Our model features the Kras(LA2) allele on the inbred FVB/N mouse strain, and in this genetic background, there is a highly statistically significant increase in level of genomic instability with increasing tumor size. These data suggest that recurring DNA copy alterations are important for tumor progression in the Kras(LA2) model of lung cancer and that the requirement for these alterations may be dependent on the genetic background of the mouse strain.