Gene expression profiling towards the prediction of oral cancer reoccurrence

In this work we perform gene expression profiling on tissue specimen obtained from patients with oral squamous cell carcinoma with a twofold aim: i) to identify a limited number of genes that capture perturbations at molecular level dictating the development of a potential disease relapse after remission, and ii) to employ these genes in order to build a classifier that is able to calculate the probability of disease reoccurrence for new patients, subsequently discriminating patients into high and low risk groups based on reoccurrence probability. The proposed analysis yielded 94% overall accuracy, 100% sensitivity and 89% specificity, for discriminating patients with and without a disease relapse.

Genomics of AML: clinical applications of next-generation sequencing

In the past decade, a series of technological advances have revolutionized our ability to interrogate cancer genomes, culminating in whole-genome sequencing, which provides genome-wide coverage at a single base-pair resolution. As sequencing technologies improve and costs decrease, it is likely that whole-genome sequencing of cancer cells will become commonplace in the diagnostic workup of patients with acute myelogenous leukemia (AML) and other cancers. The unprecedented molecular characterization provided by whole-genome sequencing offers the potential for an individualized approach to treatment in AML, bringing us one step closer to personalized medicine. In this chapter, we discuss how next-generation sequencing is being used to study cancer genomes. Recent publications of whole-genome sequencing in AML are reviewed and current limitations of whole-genome sequencing are examined, as well as current and potential future clinical applications of whole-genome sequencing.

Insertional engineering of chromosomes with Sleeping Beauty transposition: an overview

Novel genetic tools and mutagenesis strategies based on the Sleeping Beauty (SB) transposable element are currently under development with a vision to link primary DNA sequence information to gene functions in vertebrate models. By virtue of its inherent capacity to insert into DNA, the SB transposon can be developed into powerful tools for chromosomal manipulations. Mutagenesis screens based on SB have numerous advantages including high throughput and easy identification of mutated alleles. Forward genetic approaches based on insertional mutagenesis by engineered SB transposons have the advantage of providing insight into genetic networks and pathways based on phenotype. Indeed, the SB transposon has become a highly instrumental tool to induce tumors in experimental animals in a tissue-specific -manner with the aim of uncovering the genetic basis of diverse cancers. Here, we describe a battery of mutagenic cassettes that can be applied in conjunction with SB transposon vectors to mutagenize genes, and highlight versatile experimental strategies for the generation of engineered chromosomes for loss-of-function as well as gain-of-function mutagenesis for functional gene annotation in vertebrate models.

Proteomic changes resulting from gene copy number variations in cancer cells

Along the transformation process, cells accumulate DNA aberrations, including mutations, translocations, amplifications, and deletions. Despite numerous studies, the overall effects of amplifications and deletions on the end point of gene expression—the level of proteins—is generally unknown. Here we use large-scale and high-resolution proteomics combined with gene copy number analysis to investigate in a global manner to what extent these genomic changes have a proteomic output and therefore the ability to affect cellular transformation. We accurately measure expression levels of 6,735 proteins and directly compare them to the gene copy number. We find that the average effect of these alterations on the protein expression is only a few percent. Nevertheless, by using a novel algorithm, we find the combined impact that many of these regional chromosomal aberrations have at the protein level. We show that proteins encoded by amplified oncogenes are often overexpressed, while adjacent amplified genes, which presumably do not promote growth and survival, are attenuated. Furthermore, regulation of biological processes and molecular complexes is independent of general copy number changes. By connecting the primary genome alteration to their proteomic consequences, this approach helps to interpret the data from large-scale cancer genomics efforts.

In the course of cancer development, cells lose regulation of the cell cycle and quality control of DNA replication. As a result, many genomic alterations accumulate, among them amplifications and deletions of chromosomal regions of varying sizes. Oncogenes that drive transformation often reside in amplified regions, while tumor suppressors are deleted, yet for thousands of genes the effect of altering gene copy number is unknown. Since only genomic alterations that ultimately affect protein levels can have functional importance, a global proteomic approach that directly measures such changes is desirable. Here, we examined output of chromosomal alterations on the proteins in a system-wide manner. We analyzed the global protein expression of cancer cells compared to normal cells using mass-spectrometry–based quantitative proteomics and quantified a large part of the expressed proteome. We compared the protein data to genomic data and matched changes in gene copy number to protein expression level changes for each gene. Overall, gene copy number changes explain only a few percent of observed protein expression changes. Knowledge of when genomic and proteomic changes correlate may help in a better understanding of regulatory mechanisms in tumor development.

Identification of methylated genes associated with aggressive bladder cancer

Approximately 500,000 individuals diagnosed with bladder cancer in the U.S. require routine cystoscopic follow-up to monitor for disease recurrences or progression, resulting in over $2 billion in annual expenditures. Identification of new diagnostic and monitoring strategies are clearly needed, and markers related to DNA methylation alterations hold great promise due to their stability, objective measurement, and known associations with the disease and with its clinical features. To identify novel epigenetic markers of aggressive bladder cancer, we utilized a high-throughput DNA methylation bead-array in two distinct population-based series of incident bladder cancer (n = 73 and n = 264, respectively). We then validated the association between methylation of these candidate loci with tumor grade in a third population (n = 245) through bisulfite pyrosequencing of candidate loci. Array based analyses identified 5 loci for further confirmation with bisulfite pyrosequencing. We identified and confirmed that increased promoter methylation of HOXB2 is significantly and independently associated with invasive bladder cancer and methylation of HOXB2, KRT13 and FRZB together significantly predict high-grade non-invasive disease. Methylation of these genes may be useful as clinical markers of the disease and may point to genes and pathways worthy of additional examination as novel targets for therapeutic treatment.

Cancer biomarker discovery: the entropic hallmark

Background

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

Methodology/Principal Findings

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

Conclusions/Significance

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

Errors in delivery of cancer genetics services: implications for practice

Advances in genetics have prompted recommendations that all healthcare providers perform genetic counseling and testing. Some experts are concerned about potential negative outcomes from cancer genetic testing performed without genetic counseling by certified genetics professionals. We report a national series of cases illustrating negative outcomes of cancer genetic testing performed without counseling by a qualified provider. Three major patterns emerged from analysis of these cases: 1) Wrong genetic test ordered, 2) Genetic test results misinterpreted, and 3) Inadequate genetic counseling. Negative outcomes included unnecessary prophylactic surgeries, unnecessary testing, psychosocial distress, and false reassurance resulting in inappropriate medical management.

CONCLUSION

With the complexities of cancer genetic counseling and testing, it may be unrealistic to expect all clinicians to provide these services. A more realistic approach is better provider education and a framework in which healthcare providers identify patients who would benefit from a referral to a certified genetic counselor or experienced cancer genetics professional.

Signal transduction in the human thyrocyte and its perversion in thyroid tumors

The study of normal signal transduction pathways regulating the proliferation and differentiation of a cell type allows to predict and to understand the perversions of these pathways which lead to tumorigenesis. In the case of the human thyroid cell, three cascades are mostly involved in tumorigenesis: The pathways and genetic events affecting them are described. Caveats in the use of models and the interpretation of results are formulated and the still pending questions are outlined.

Rearrangements of NTRK1 gene in papillary thyroid carcinoma

TRK oncogenes are observed in a consistent fraction of papillary thyroid carcinoma (PTC); they arise from the fusion of the 3' terminal sequences of the NTRK1/NGF receptor gene with 5' terminal sequences of various activating genes, such as TPM3, TPR and TFG. TRK oncoproteins display constitutive tyrosine-kinase activity, leading to in vitro and in vivo transformation. In this review studies performed during the last 20 years will be summarized. The following topics will be illustrated: (a) frequency of TRK oncogenes and correlation with radiation and tumor histopathological features; (b) molecular mechanisms underlying NTRK1 oncogenic rearrangements; (c) molecular and biochemical characterization of TRK oncoproteins, and their mechanism of action; (d) role of activating sequences in the activation of TRK oncoproteins.

A human functional protein interaction network and its application to cancer data analysis

BACKGROUND

One challenge facing biologists is to tease out useful information from massive data sets for further analysis. A pathway-based analysis may shed light by projecting candidate genes onto protein functional relationship networks. We are building such a pathway-based analysis system.

RESULTS

We have constructed a protein functional interaction network by extending curated pathways with non-curated sources of information, including protein-protein interactions, gene coexpression, protein domain interaction, Gene Ontology (GO) annotations and text-mined protein interactions, which cover close to 50% of the human proteome. By applying this network to two glioblastoma multiforme (GBM) data sets and projecting cancer candidate genes onto the network, we found that the majority of GBM candidate genes form a cluster and are closer than expected by chance, and the majority of GBM samples have sequence-altered genes in two network modules, one mainly comprising genes whose products are localized in the cytoplasm and plasma membrane, and another comprising gene products in the nucleus. Both modules are highly enriched in known oncogenes, tumor suppressors and genes involved in signal transduction. Similar network patterns were also found in breast, colorectal and pancreatic cancers.

CONCLUSIONS

We have built a highly reliable functional interaction network upon expert-curated pathways and applied this network to the analysis of two genome-wide GBM and several other cancer data sets. The network patterns revealed from our results suggest common mechanisms in the cancer biology. Our system should provide a foundation for a network or pathway-based analysis platform for cancer and other diseases.

Second generation sequencing of the mesothelioma tumor genome

The current paradigm for elucidating the molecular etiology of cancers relies on the interrogation of small numbers of genes, which limits the scope of investigation. Emerging second-generation massively parallel DNA sequencing technologies have enabled more precise definition of the cancer genome on a global scale. We examined the genome of a human primary malignant pleural mesothelioma (MPM) tumor and matched normal tissue by using a combination of sequencing-by-synthesis and pyrosequencing methodologies to a 9.6X depth of coverage. Read density analysis uncovered significant aneuploidy and numerous rearrangements. Method-dependent informatics rules, which combined the results of different sequencing platforms, were developed to identify and validate candidate mutations of multiple types. Many more tumor-specific rearrangements than point mutations were uncovered at this depth of sequencing, resulting in novel, large-scale, inter- and intra-chromosomal deletions, inversions, and translocations. Nearly all candidate point mutations appeared to be previously unknown SNPs. Thirty tumor-specific fusions/translocations were independently validated with PCR and Sanger sequencing. Of these, 15 represented disrupted gene-encoding regions, including kinases, transcription factors, and growth factors. One large deletion in DPP10 resulted in altered transcription and expression of DPP10 transcripts in a set of 53 additional MPM tumors correlated with survival. Additionally, three point mutations were observed in the coding regions of NKX6-2, a transcription regulator, and NFRKB, a DNA-binding protein involved in modulating NFKB1. Several regions containing genes such as PCBD2 and DHFR, which are involved in growth factor signaling and nucleotide synthesis, respectively, were selectively amplified in the tumor. Second-generation sequencing uncovered all types of mutations in this MPM tumor, with DNA rearrangements representing the dominant type.

Inhibition of c-Jun N-terminal kinase by SP600125: a cDNA microarray analysis

BACKGROUND

In a previous investigation, we showed that the janus kinase (JNK) inhibitor SP600125 induced several phenotypic and genomic changes in leukemia cells. However, the molecular mechanisms that sustain these changes remain unknown. The purpose of the present study was to examine gene expression changes in THP-1 leukemia cells treated with SP600125.

MATERIALS AND METHODS

Gene expression levels were investigated using Affymetrix hybridization technology and quantitative reverse transcriptase polymerase chain reaction.

RESULTS

Affymetrix technology showed that the expression of 1,038 genes with a biological process description well known in gene ontology was modulated. Fifteen genes were related to kinases or phosphatases, 20 genes were involved in the cell cycle regulation, and 23 genes were involved in apoptosis. A network of 15 correlated genes was obtained showing a primordial role for the myelocytomatosis viral oncogene homolog (MYC).

CONCLUSION

These findings show that SP600125 exhibits cytostatic and cytolytic activities through MYC gene modulation.

Breast cancer relapse prediction based on multi-gene RT-PCR algorithm

BACKGROUND

Breast cancer is very heterogeneous disease at both the clinical and molecular levels. Most research is based on analysis of a single gene, but only complex investigation of genes involved in different cell processes such as apoptosis or signal transduction can help to better understand the biology of this type of tumour. Novel techniques such as microarrays and real-time RT-PCR allow performance of such complex research. Only this kind of approach can improve cancer treatment through individualisation of disease cases with different molecular backgrounds.

MATERIAL/METHODS

We performed quantitative RT-PCR to analyze levels of expression of 10 genes in 119 patient samples: 4 with known good prognosis signature (WWOX, ESR1, CDH, BAX) and 6 previously reported as bad prognosis markers of breast cancer (KRT5, KRT14, KRT17, CCNE1, BCL2, BIRC5).

RESULTS

The algorithm composed of 10 genes distinguishes 2 statistically significant groups of patients with different rates of disease-free survival. However, when patients were divided into 2 groups according to estrogen receptor status, this algorithm could be applied only for a group with estrogen receptor negative breast cancer. High algorithm value is a good prognostic factor of disease-free survival for patients with estrogen negative breast cancers (HR=0.26; p=0.0039), but not for patients with ER positive tumors (p>0.05).

CONCLUSIONS

The presented multigene algorithm may be used for outcome evaluation for estrogen receptor-negative breast cancer patients.

Signatures of mutation and selection in the cancer genome

The cancer genome is moulded by the dual processes of somatic mutation and selection. Homozygous deletions in cancer genomes occur over recessive cancer genes, where they can confer selective growth advantage, and over fragile sites, where they are thought to reflect an increased local rate of DNA breakage. However, most homozygous deletions in cancer genomes are unexplained. Here we identified 2,428 somatic homozygous deletions in 746 cancer cell lines. These overlie 11% of protein-coding genes that, therefore, are not mandatory for survival of human cells. We derived structural signatures that distinguish between homozygous deletions over recessive cancer genes and fragile sites. Application to clusters of unexplained homozygous deletions suggests that many are in regions of inherent fragility, whereas a small subset overlies recessive cancer genes. The results illustrate how structural signatures can be used to distinguish between the influences of mutation and selection in cancer genomes. The extensive copy number, genotyping, sequence and expression data available for this large series of publicly available cancer cell lines renders them informative reagents for future studies of cancer biology and drug discovery.

Recurrent copy number alterations in BRCA1-mutated ovarian tumors alter biological pathways

Array CGH was used to identify recurrent copy number alterations (RCNA) characteristic of either BRCA1-related or sporadic ovarian cancer. After preprocessing, both groups of patients were modeled using a recurrent Hidden Markov Model to detect RCNA. RCNA with a probability higher than 80% were called. After removing RCNA present in both groups, the genes present in the remaining RCNA were investigated for enrichment of pathways from external databases. More RCNA were observed in the BRCA1 group, and they display more losses than gains compared to the sporadic group. When focusing on the type of RCNA, no significant difference in length was seen for the gains, but there was a statistically significant difference for the losses. In the sporadic group, a great proportion of the altered regions contain genes known to have a function in cell adhesion and complement activation, whereas the BRCA1 samples are characterized by alterations in the HOX genes, metalloproteinases, tumor suppressor genes, and the estrogen-signaling pathways. We conclude that BRCA1 ovarian tumors present a different type, number, and length of RCNA; a huge amount of the genome is lost, resulting in important genomic instability. Moreover, important biological pathways are altered differentially when compared to the sporadic group.

A comprehensive catalogue of somatic mutations from a human cancer genome

All cancers carry somatic mutations. A subset of these somatic alterations, termed driver mutations, confer selective growth advantage and are implicated in cancer development, whereas the remainder are passengers. Here we have sequenced the genomes of a malignant melanoma and a lymphoblastoid cell line from the same person, providing the first comprehensive catalogue of somatic mutations from an individual cancer. The catalogue provides remarkable insights into the forces that have shaped this cancer genome. The dominant mutational signature reflects DNA damage due to ultraviolet light exposure, a known risk factor for malignant melanoma, whereas the uneven distribution of mutations across the genome, with a lower prevalence in gene footprints, indicates that DNA repair has been preferentially deployed towards transcribed regions. The results illustrate the power of a cancer genome sequence to reveal traces of the DNA damage, repair, mutation and selection processes that were operative years before the cancer became symptomatic.

Ultradeep sequencing of a human ultraconserved region reveals somatic and constitutional genomic instability

Ultradeep sequencing of genomes permits the detection of very low-level genomic instability in non-neoplastic tissues of patients with the most common form of inherited colorectal cancer.

Early detection of cancer-associated genomic instability is crucial, particularly in tumour types in which this instability represents the essential underlying mechanism of tumourigenesis. Currently used methods require the presence of already established neoplastic cells because they only detect clonal mutations. In principle, parallel sequencing of single DNA filaments could reveal the early phases of tumour initiation by detecting low-frequency mutations, provided an adequate depth of coverage and an effective control of the experimental error. We applied ultradeep sequencing to estimate the genomic instability of individuals with hereditary non-polyposis colorectal cancer (HNPCC). To overcome the experimental error, we used an ultraconserved region (UCR) of the human genome as an internal control. By comparing the mutability outside and inside the UCR, we observed a tendency of the ultraconserved element to accumulate significantly fewer mutations than the flanking segments in both neoplastic and nonneoplastic HNPCC samples. No difference between the two regions was detectable in cells from healthy donors, indicating that all three HNPCC samples have mutation rates higher than the healthy genome. This is the first, to our knowledge, direct evidence of an intrinsic genomic instability of individuals with heterozygous mutations in mismatch repair genes, and constitutes the proof of principle for the development of a more sensitive molecular assay of genomic instability.

In hereditary non-polyposis colorectal cancer (HNPCC), a germline mutation in one allele of a gene responsible for repairing DNA damage predisposes the host to cancer, because subsequent somatic inactivation of the one wild-type allele leads to genomic instability that favours tumourigenesis. Nonneoplastic tissues of HNPCC individuals are believed to repair DNA normally, as they are heterozygous and thus are thought to be genomically stable. However, methods used to date are known to be incapable of detecting very low levels of genome instability. Here, we present a more sensitive procedure based on the resequencing of a HNPCC genomic region using next-generation sequencing technology. With this approach, we show that genomic instability is in fact detectable in nonneoplastic tissues of HNPCC patients compared with healthy donors. This constitutional instability may predispose them to acquiring the second somatic mutation event needed for cancer development.

Endometrial cancer side-population cells show prominent migration and have a potential to differentiate into the mesenchymal cell lineage

Cancer stem-like cell subpopulations, referred to as "side-population" (SP) cells, have been identified in several tumors based on their ability to efflux the fluorescent dye Hoechst 33342. Although SP cells have been identified in the normal human endometrium and endometrial cancer, little is known about their characteristics. In this study, we isolated and characterized the SP cells in human endometrial cancer cells and in rat endometrial cells expressing oncogenic human K-Ras protein. These SP cells showed i) reduction in the expression levels of differentiation markers; ii) long-term proliferative capacity of the cell cultures; iii) self-renewal capacity in vitro; iv) enhancement of migration, lamellipodia, and uropodia formation; and v) enhanced tumorigenicity. In nude mice, SP cells formed large, invasive tumors, which were composed of both tumor cells and stromal-like cells with enriched extracellular matrix. The expression levels of vimentin, alpha-smooth muscle actin, and collagen III were enhanced in SP tumors compared with the levels in non-SP tumors. In addition, analysis of microdissected samples and fluorescence in situ hybridization of Hec1-SP-tumors showed that the stromal-like cells with enriched extracellular matrix contained human DNA, confirming that the stromal-like cells were derived from the inoculated cells. Moreober, in a Matrigel assay, SP cells differentiated into alpha-smooth muscle actin-expressing cells. These findings demonstrate that SP cells have cancer stem-like cell features, including the potential to differentiate into the mesenchymal cell lineage.

Zoom-in array comparative genomic hybridization (aCGH) to detect germline rearrangements in cancer susceptibility genes

Disease predisposing germline mutations in cancer susceptibility genes may consist of large genomic rearrangements, including deletions or duplications that are challenging, to detect and characterize using standard PCR-based mutation screening methods. Such rearrangements range from single exons up to hundreds of kilobases of sequence in size. Array-based comparative genomic hybridization (aCGH) has evolved as a powerful technique to detect copy number alterations on a genome-wide scale. However, the conventional genome-wide approach of aCGH still provides only limited information about copy number status for individual exons. Custom-designed aCGH arrays focused on only a few target regions (zoom-in aCGH) may circumvent this drawback. Benefits of zoom-in aCGH include the possibility to target almost any region in the genome, and an unbiased coverage of exonic and intronic sequence facilitating convenient design of primers for sequence determination of the breakpoints. Furthermore, zoom-in aCGH can be streamlined for a particular application, for example, focusing on breast cancer susceptibility genes, with increased capacity using multiformat design.

[Gastrointestinal stromal tumours: clinico-morphological features, pathogenesis and modern treatment strategies]

Gastrointestinal stromal tumours (GIST) are the commonest mesenchymal tumours of gastrointestinal organs accounting for 1-3% of all gastrointestinal neoplasms and almost 5% of all soft tissue sarcomas. Most GIST (95%) express transmembrane receptor KIT or CD117, CD34 (70%), vimentin (80%), specific smooth muscle and neurogenic markers (with different frequency). Up to 85% of the stromal tumours have mutations in the KIT gene (exones 9, 11, 13, 17) and 3-18% in the PDGFRA (platelet-derived growth factor receptor-alpha) gene (exones 12, 14, 18). Mutations are absent in 5% of KITand PDGFRA genes. Mutational status, mitotic index, size and location of the tumour are the most informative criteria for the choice of treatment strategy and prognosis of the disease.

Cholesterol homeostasis in two commonly used human prostate cancer cell-lines, LNCaP and PC-3

BACKGROUND

Recently, there has been renewed interest in the link between cholesterol and prostate cancer. It has been previously reported that in vitro, prostate cancer cells lack sterol-mediated feedback regulation of the major transcription factor in cholesterol homeostasis, sterol-regulatory element binding protein 2 (SREBP-2). This could explain the accumulation of cholesterol observed in clinical prostate cancers. Consequently, perturbed feedback regulation to increased sterol levels has become a pervasive concept in the prostate cancer setting. Here, we aimed to explore this in greater depth.

METHODOLOGY/PRINCIPAL FINDINGS

After altering the cellular cholesterol status in LNCaP and PC-3 prostate cancer cells, we examined SREBP-2 processing, downstream effects on promoter activity and expression of SREBP-2 target genes, and functional activity (low-density lipoprotein uptake, cholesterol synthesis). In doing so, we observed that LNCaP and PC-3 cells were sensitive to increased sterol levels. In contrast, lowering cholesterol levels via statin treatment generated a greater response in LNCaP cells than PC-3 cells. This highlighted an important difference between these cell-lines: basal SREBP-2 activity appeared to be higher in PC-3 cells, reducing sensitivity to decreased cholesterol levels.

CONCLUSION/SIGNIFICANCE

Thus, prostate cancer cells are sensitive to changing sterol levels in vitro, but the extent of this regulation differs between prostate cancer cell-lines. These results shed new light on the regulation of cholesterol metabolism in two commonly used prostate cancer cell-lines, and emphasize the importance of establishing whether or not cholesterol homeostasis is perturbed in prostate cancer in vivo.

Analysis of the association between CIMP and BRAF in colorectal cancer by DNA methylation profiling

A CpG island methylator phenotype (CIMP) is displayed by a distinct subset of colorectal cancers with a high frequency of DNA hypermethylation in a specific group of CpG islands. Recent studies have shown that an activating mutation of BRAF (BRAF^V600E) is tightly associated with CIMP, raising the question of whether BRAF^V600E plays a causal role in the development of CIMP or whether CIMP provides a favorable environment for the acquisition of BRAF^V600E. We employed Illumina GoldenGate DNA methylation technology, which interrogates 1,505 CpG sites in 807 different genes, to further study this association. We first examined whether expression of BRAF^V600E causes DNA hypermethylation by stably expressing BRAF^V600E in the CIMP-negative, BRAF wild-type COLO 320DM colorectal cancer cell line. We determined 100 CIMP-associated CpG sites and examined changes in DNA methylation in eight stably transfected clones over multiple passages. We found that BRAF^V600E is not sufficient to induce CIMP in our system. Secondly, considering the alternative possibility, we identified genes whose DNA hypermethylation was closely linked to BRAF^V600E and CIMP in 235 primary colorectal tumors. Interestingly, genes that showed the most significant link include those that mediate various signaling pathways implicated in colorectal tumorigenesis, such as BMP3 and BMP6 (BMP signaling), EPHA3, KIT, and FLT1 (receptor tyrosine kinases) and SMO (Hedgehog signaling). Furthermore, we identified CIMP-dependent DNA hypermethylation of IGFBP7, which has been shown to mediate BRAF^V600E-induced cellular senescence and apoptosis. Promoter DNA hypermethylation of IGFBP7 was associated with silencing of the gene. CIMP-specific inactivation of BRAF^V600E-induced senescence and apoptosis pathways by IGFBP7 DNA hypermethylation might create a favorable context for the acquisition of BRAF^V600E in CIMP+ colorectal cancer. Our data will be useful for future investigations toward understanding CIMP in colorectal cancer and gaining insights into the role of aberrant DNA hypermethylation in colorectal tumorigenesis.

Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data

Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA), which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE), Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS), Gradient based Leave-one-out Gene Selection (GLGS). To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II) breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC) is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and AUC errors.

Synthetic lethal genetic interactions that decrease somatic cell proliferation in Caenorhabditis elegans identify the alternative RFC CTF18 as a candidate cancer drug target

Somatic mutations causing chromosome instability (CIN) in tumors can be exploited for selective killing of cancer cells by knockdown of second-site genes causing synthetic lethality. We tested and statistically validated synthetic lethal (SL) interactions between mutations in six Saccharomyces cerevisiae CIN genes orthologous to genes mutated in colon tumors and five additional CIN genes. To identify which SL interactions are conserved in higher organisms and represent potential chemotherapeutic targets, we developed an assay system in Caenorhabditis elegans to test genetic interactions causing synthetic proliferation defects in somatic cells. We made use of postembryonic RNA interference and the vulval cell lineage of C. elegans as a readout for somatic cell proliferation defects. We identified SL interactions between members of the cohesin complex and CTF4, RAD27, and components of the alternative RFC(CTF18) complex. The genetic interactions tested are highly conserved between S. cerevisiae and C. elegans and suggest that the alternative RFC components DCC1, CTF8, and CTF18 are ideal therapeutic targets because of their mild phenotype when knocked down singly in C. elegans. Furthermore, the C. elegans assay system will contribute to our knowledge of genetic interactions in a multicellular animal and is a powerful approach to identify new cancer therapeutic targets.