Recurrent chromosome aberrations in cancer

Chimeric RNAs generated by intergenic splicing in normal and cancer cells

A hallmark of many neoplasias is chromosomal rearrangement, an event that commonly results in the fusion of two separate genes. The RNA and protein resulting from these gene fusions often play critical roles in cancer development, maintenance, and progression. Traditionally, these fusion products are thought to be produced solely due to DNA level changes and are therefore considered unique to cancer. Recent advances in microarray and deep-sequencing have revealed many more fusion transcripts. Surprisingly, some are without detectable rearrangement at the DNA level. Reports have demonstrated that at least some of these chimeric RNAs are generated via intergenic splicing. In this review, we highlight three examples of these noncanonical chimeric transcripts that are formed by trans-splicing or cis-splicing of adjacent genes and summarize the knowledge we have regarding these noncanonical fusions. We discuss the implications of the chimeric RNAs in both cancer and normal physiology, as some of these fusion transcripts are found in normal, noncancerous cells with sequences identical to those generated by canonical chromosomal translocation found in cancer cells. Finally, we present methods that are currently being used to discover additional chimeric RNAs.

Gene expression identifies heterogeneity of metastatic behavior among high-grade non-translocation associated soft tissue sarcomas

Background

The biologic heterogeneity of soft tissue sarcomas (STS), even within histological subtypes, complicates treatment. In earlier studies, gene expression patterns that distinguish two subsets of clear cell renal carcinoma (RCC), serous ovarian carcinoma (OVCA), and aggressive fibromatosis (AF) were used to separate 73 STS into two or four groups with different probabilities of developing metastatic disease (PrMet). This study was designed to confirm our earlier observations in a larger independent data set.

Methods

We utilized these gene sets, hierarchical clustering (HC), and Kaplan-Meier analysis, to examine 309 STS, using Affymetrix chip expression profiling.

Results

HC using the combined AF-, RCC-, and OVCA-gene sets identified subsets of the STS samples. Analysis revealed differences in PrMet between the clusters defined by the first branch point of the clustering dendrogram (p = 0.048), and also among the four different clusters defined by the second branch points (p < 0.0001). Analysis also revealed differences in PrMet between the leiomyosarcomas (LMS), dedifferentiated liposarcomas (LipoD), and undifferentiated pleomorphic sarcomas (UPS) (p = 0.0004). HC of both the LipoD and UPS sample sets divided the samples into two groups with different PrMet (p = 0.0128, and 0.0002, respectively). HC of the UPS samples also showed four groups with different PrMet (p = 0.0007). HC found no subgroups of the LMS samples.

Conclusions

These data confirm our earlier studies, and suggest that this approach may allow the identification of more than two subsets of STS, each with distinct clinical behavior, and may be useful to stratify STS in clinical trials and in patient management.

Chromosome 19 rearrangements in ovarian carcinomas: zinc finger genes are particularly targeted

Chromosome 19 is frequently rearranged in ovarian carcinomas, but the pathogenetic consequences of this are not clearly understood. We performed microarray gene expression analysis on 12 ovarian carcinomas that carry a rearranged chromosome 19 in their karyotype. These aberrant chromosomes have previously been microdissected and analyzed by array-based CGH. In the current study, we wanted to explore whether the genomic alterations thus detected correlated with changes in gene expression. The microarray gene expression analysis gave information on 407 genes mapping in gained genomic regions on chromosome 19, of which 92 showed association between DNA gain and upregulated expression. Of the genes showing this association, 39 (42%) showed gain in at least two samples. The majority of these 39 genes of interest (n = 24, 62%) encode zinc finger proteins, which otherwise make up only 15% of the approximately 1,400 genes on chromosome 19. The strongest association was found for ZNF223 which was upregulated in samples with genomic gain compared with samples without gain. We suggest that DNA copy number changes brought about by rearrangements of chromosome 19 contribute to ovarian carcinogenesis by leading to upregulation of ZNF223 and other zinc finger genes. © 2014 Wiley Periodicals, Inc.

The gene regulatory network for breast cancer: integrated regulatory landscape of cancer hallmarks

In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of 351 patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO) analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome 21 is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

Identification of the transforming STRN-ALK fusion as a potential therapeutic target in the aggressive forms of thyroid cancer

Thyroid cancer is a common endocrine malignancy that encompasses well-differentiated as well as dedifferentiated cancer types. The latter tumors have high mortality and lack effective therapies. Using a paired-end RNA-sequencing approach, we report the discovery of rearrangements involving the anaplastic lymphoma kinase (ALK) gene in thyroid cancer. The most common of these involves a fusion between ALK and the striatin (STRN) gene, which is the result of a complex rearrangement involving the short arm of chromosome 2. STRN-ALK leads to constitutive activation of ALK kinase via dimerization mediated by the coiled-coil domain of STRN and to a kinase-dependent, thyroid-stimulating hormone-independent proliferation of thyroid cells. Moreover, expression of STRN-ALK transforms cells in vitro and induces tumor formation in nude mice. The kinase activity of STRN-ALK and the ALK-induced cell growth can be blocked by the ALK inhibitors crizotinib and TAE684. In addition to well-differentiated papillary cancer, STRN-ALK was found with a higher prevalence in poorly differentiated and anaplastic thyroid cancers, and it did not overlap with other known driver mutations in these tumors. Our data demonstrate that STRN-ALK fusion occurs in a subset of patients with highly aggressive types of thyroid cancer and provide initial evidence suggesting that it may represent a therapeutic target for these patients.

The mutational landscape of phosphorylation signaling in cancer

Somatic mutations in cancer genomes include drivers that provide selective advantages to tumor cells and passengers present due to genome instability. Discovery of pan-cancer drivers will help characterize biological systems important in multiple cancers and lead to development of better therapies. Driver genes are most often identified by their recurrent mutations across tumor samples. However, some mutations are more important for protein function than others. Thus considering the location of mutations with respect to functional protein sites can predict their mechanisms of action and improve the sensitivity of driver gene detection. Protein phosphorylation is a post-translational modification central to cancer biology and treatment, and frequently altered by driver mutations. Here we used our ActiveDriver method to analyze known phosphorylation sites mutated by single nucleotide variants (SNVs) in The Cancer Genome Atlas Research Network (TCGA) pan-cancer dataset of 3,185 genomes and 12 cancer types. Phosphorylation-related SNVs (pSNVs) occur in ~90% of tumors, show increased conservation and functional mutation impact compared to other protein-coding mutations, and are enriched in cancer genes and pathways. Gene-centric analysis found 150 known and candidate cancer genes with significant pSNV recurrence. Using a novel computational method, we predict that 29% of these mutations directly abolish phosphorylation or modify kinase target sites to rewire signaling pathways. This analysis shows that incorporation of information about protein signaling sites will improve computational pipelines for variant function prediction.

Understanding spatial organizations of chromosomes via statistical analysis of Hi-C data

Understanding how chromosomes fold provides insights into the transcription regulation, hence, the functional state of the cell. Using the next generation sequencing technology, the recently developed Hi-C approach enables a global view of spatial chromatin organization in the nucleus, which substantially expands our knowledge about genome organization and function. However, due to multiple layers of biases, noises and uncertainties buried in the protocol of Hi-C experiments, analyzing and interpreting Hi-C data poses great challenges, and requires novel statistical methods to be developed. This article provides an overview of recent Hi-C studies and their impacts on biomedical research, describes major challenges in statistical analysis of Hi-C data, and discusses some perspectives for future research.

Dissecting karyotypic patterns in non-hyperdiploid multiple myeloma: an overview on the karyotypic evolution

BACKGROUND

Multiple myeloma (MM) is a plasma cell disorder characterized by the presence of specific genetic and cytogenetic aberrations that define unique subgroups with different outcomes. On the basis of the ploidy status, MM can be subdivided into hyperdiploid MM (H-MM) and non-hyperdiploid MM (NH-MM). NH-MM is an entity that encompasses hypodiploid, pseudodiploid, and near tetraploid MM and is associated with a higher number of immunoglobulin heavy-chain (IgH) translocations.

MATERIALS AND METHODS

We have systematically analyzed the structure of the karyotypic evolution in NH-MM and identified several genetic features of their complex karyotypic patterns.

RESULTS

On the basis of statistical models used in complex karyotypes, we were able to identify the temporal order in which the genetic aberrations occur in NH-MM. In this analysis, whole chromosome losses and IgH translocations were commonly seen, and -13/13q- and t14q32 were defined as early genetic events in the karyotypic evolution of NH-MM. Furthermore, chromosome 1 and 17 abnormalities were associated with a late karyotypic phase of evolution consistent with the recognized pattern of acquired events deemed to be associated with these type of genetic aberrations.

CONCLUSION

Accumulation of genetic aberrations in NH-MM above a threshold results in malignant transformation.

Sarcoma diagnosis in the age of molecular pathology

Mesenchymal neoplasia presents numerous challenges to pathologic classification. Histologic features can be deceiving, and traditional immunohistochemical markers of differentiation may be of little use in narrowing the diagnosis. Fortunately, great strides have been made in unraveling the genetic and genomic alterations associated with both sarcomagenesis and benign neoplasia. In turn, these advances have led to an expansion of the available diagnostic toolkit for sarcoma pathology. In order to assist the practicing pathologist in integrating these tools into their repertoire, this article will discuss some of the latest advances in sarcoma diagnosis, including an update on translocation-associated sarcomas, and will review a number of sarcoma-specific immunohistochemical studies developed over the past decade. Some of the potential uses and pitfalls of commonly used tests will be addressed. Finally, the discussion will briefly touch upon the impact that advances in molecular technologies, particularly targeted gene expression analysis, may have on altering the face of diagnostic pathology.

ToP: a trend-of-disease-progression procedure works well for identifying cancer genes from multi-state cohort gene expression data for human colorectal cancer

Significantly expressed genes extracted from microarray gene expression data have proved very useful for identifying genetic biomarkers of diseases, including cancer. However, deriving a disease related inference from a list of differentially expressed genes has proven less than straightforward. In a systems disease such as cancer, how genes interact with each other should matter just as much as the level of gene expression. Here, in a novel approach, we used the network and disease progression properties of individual genes in state-specific gene-gene interaction networks (GGINs) to select cancer genes for human colorectal cancer (CRC) and obtain a much higher hit rate of known cancer genes when compared with methods not based on network theory. We constructed GGINs by integrating gene expression microarray data from multiple states--healthy control (Nor), adenoma (Ade), inflammatory bowel disease (IBD) and CRC--with protein-protein interaction database and Gene Ontology. We tracked changes in the network degrees and clustering coefficients of individual genes in the GGINs as the disease state changed from one to another. From these we inferred the state sequences Nor-Ade-CRC and Nor-IBD-CRC both exhibited a trend of (disease) progression (ToP) toward CRC, and devised a ToP procedure for selecting cancer genes for CRC. Of the 141 candidates selected using ToP, ∼50% had literature support as cancer genes, compared to hit rates of 20% to 30% for standard methods using only gene expression data. Among the 16 candidate cancer genes that encoded transcription factors, 13 were known to be tumorigenic and three were novel: CDK1, SNRPF, and ILF2. We identified 13 of the 141 predicted cancer genes as candidate markers for early detection of CRC, 11 and 2 at the Ade and IBD states, respectively.

Aneuploidy in health, disease, and aging

Aneuploidy, an aberrant number of chromosomes, has been recognized as a feature of human malignancies for over a century, but compelling evidence for causality was largely lacking until mouse models for chromosome number instability were used. These in vivo studies have not only uncovered important new insights into the extremely complex aneuploidy-cancer relationship but also into the molecular mechanisms underlying proper and aberrant chromosome segregation. A series of diverse mouse models for the mitotic checkpoint protein BubR1 has provided evidence for a provocative novel link between aneuploidization and the development of age-related pathologies.

Oncoapoptotic signaling and deregulated target genes in cancers: special reference to oral cancer

Cancer is a class of diseases characterized by uncontrolled cell growth. The development of cancer takes place in a multi-step process during which cells acquire a series of mutations that eventually lead to unrestrained cell growth and division, inhibition of cell differentiation, and evasion of cell death. Dysregulation of oncoapoptotic genes, growth factors, receptors and their downstream signaling pathway components represent a central driving force in tumor development. The detailed studies of signal transduction pathways for mechanisms of cell growth and apoptosis have significantly advanced our understanding of human cancers, subsequently leading to more effective treatments. Oral squamous cell carcinoma represents a classic example of multi-stage carcinogenesis. It gradually evolves through transitional precursor lesions from normal epithelium to a full-blown metastatic phenotype. Genetic alterations in many genes encoding crucial proteins, which regulate cell proliferation, differentiation, survival and apoptosis, have been implicated in oral cancer. As like other solid tumors, in oral cancer these genes include the ones coding for cell cycle regulators or oncoproteins (e.g. Ras, Myc, cyclins, CDKs, and CKIs), tumor suppressors (e.g. p53 and pRb), pro-survival proteins (e.g. telomerase, growth factors or their receptors), anti-apoptotic proteins (e.g. Bcl2 family, IAPs, and NF-kB), pro-apoptotic proteins (e.g. Bax and BH-3 family, Fas, TNF-R, and caspases), and the genes encoding key transcription factors or elements for signal transduction leading to cell growth and apoptosis. Here we discuss the current knowledge of oncoapoptotic regulation in human cancers with special reference to oral cancers.

Directional genomic hybridization for chromosomal inversion discovery and detection

Chromosomal rearrangements are a source of structural variation within the genome that figure prominently in human disease, where the importance of translocations and deletions is well recognized. In principle, inversions—reversals in the orientation of DNA sequences within a chromosome—should have similar detrimental potential. However, the study of inversions has been hampered by traditional approaches used for their detection, which are not particularly robust. Even with significant advances in whole genome approaches, changes in the absolute orientation of DNA remain difficult to detect routinely. Consequently, our understanding of inversions is still surprisingly limited, as is our appreciation for their frequency and involvement in human disease. Here, we introduce the directional genomic hybridization methodology of chromatid painting—a whole new way of looking at structural features of the genome—that can be employed with high resolution on a cell-by-cell basis, and demonstrate its basic capabilities for genome-wide discovery and targeted detection of inversions. Bioinformatics enabled development of sequence- and strand-specific directional probe sets, which when coupled with single-stranded hybridization, greatly improved the resolution and ease of inversion detection. We highlight examples of the far-ranging applicability of this cytogenomics-based approach, which include confirmation of the alignment of the human genome database and evidence that individuals themselves share similar sequence directionality, as well as use in comparative and evolutionary studies for any species whose genome has been sequenced. In addition to applications related to basic mechanistic studies, the information obtainable with strand-specific hybridization strategies may ultimately enable novel gene discovery, thereby benefitting the diagnosis and treatment of a variety of human disease states and disorders including cancer, autism, and idiopathic infertility.

Karyotype heterogeneity and unclassified chromosomal abnormalities

In a departure from traditional gene-centric thinking with regard to cytogenetics and cytogenomics, the recently introduced genome theory calls upon a re-focusing of our attention on karyotype analyses of disease conditions. Karyotype heterogeneity has been demonstrated to be directly involved in the somatic cell evolution process which is the basis of many common and complex diseases such as cancer. To correctly use karyotype heterogeneity and apply it to monitor system instability, we need to include many seemingly unimportant non-specific chromosomal aberrations into our analysis. Traditionally, cytogenetic analysis has been focused on identifying recurrent types of abnormalities, particularly those that have been linked to specific diseases. In this perspective, drawing on the new framework of 4D-genomics, we will briefly review the importance of studying karyotype heterogeneity. We have also listed a number of overlooked chromosomal aberrations including defective mitotic figures, chromosome fragmentation as well as genome chaos. Finally, we call for the systematic discovery/characterization and classification of karyotype abnormalities in human diseases, as karyotype heterogeneity is the common factor that is essential for somatic cell evolution.

Watching the grin fade: tracing the effects of polyploidy on different evolutionary time scales

Polyploidy, or whole-genome duplication (WGD), is a recurrent mutation both in cell lineages and over evolutionary time. By globally changing the relationship between gene copy number and other cellular entities, it can induce dramatic changes at the cellular and phenotypic level. Perhaps surprisingly, then, the insights that these events can bring to understanding other cellular features are not as well appreciated as they could be. In this review, we draw on examples of polyploidy from animals, plants and yeast to explore how investigations of polyploid cells have improved our understanding of the cell cycle, biological network complexity, metabolic phenotypes and tumor biology. We argue that the study of polyploidy across organisms, cell types, and time scales serves not only as a window into basic cell biology, but also as a basis for a predictive biology with applications ranging from crop improvement to treating cancer.

Arsenic and lead contamination in urban soils of Villa de la Paz (Mexico) affected by historical mine wastes and its effect on children's health studied by micronucleated exfoliated cells assay

Environmental geochemical and health studies were carried out in urban areas of Villa de la Paz, S.L.P. (Mexico), where mining activities have been developed for more of 200 years, leading to the pollution of surface soil by arsenic and heavy metals (Pb, Cd, Cu, Zn). The analysis of urban soils to determine total and bioaccessibility concentrations of As and Pb, demonstrated a combined contribution of the natural and anthropogenic concentrations in the site, at levels higher than the environmental guideline values that provoke a human health risk. Contour soil mapping confirmed that historical mine waste deposits without environmental control measures, are the main source of pollution soil by As and Pb in the site. Exposure (Pb in blood and As in urine) and effect (micronucleated exfoliated cells assay) biological monitoring were then carried out in the childhood population of the site and in a control site. The exposure biological monitoring demonstrated that at least 20-30 % of children presented Pb and As exposure values higher than the national and international maximum intervention values. The effect biomonitoring by MEC assay confirmed that there is a genotoxic damage in local childhood population that could be associated with the arsenic exposure in the site.

Chromosomal heterogeneity and instability characterize pediatric medulloblastoma cell lines and affect neoplastic phenotype

Chromosomal heterogeneity is a hallmark of most tumors and it can drive critical events as growth advantages, survival advantages, progression and karyotypic evolution. Medulloblastoma (MB) is the most common malignant central nervous system tumor in children. This work attempted to investigate chromosomal heterogeneity and instability profiles of two MB pediatric cell lines and their relationship with cell phenotype. We performed GTG-banding and cytokinesis-block micronucleus cytome assays, as well as morphological characterization, cell population doubling time, colony-forming efficiency, and chemo-sensitivity assays in two pediatric MB cell lines (UW402 and UW473). Both MB cells showed a high chromosomal heterogeneity. UW473 cells showed ~2 fold higher both clonal- and non-clonal chromosomal alterations than UW402 cells. Besides, UW473 showed two clonal-groups well-differentiated by ploidy level (<2n> and <4n>) and also presented a significantly higher number of chromosomal instability biomarkers. These results were associated with high morphological heterogeneity and survival advantages for UW473 and proliferation advantages for UW402 cells. Moreover, UW473 was significantly more sensitive to methotrexate, temozolomide and cisplatin while UW402 cells were more sensitive to doxorubicin. These data suggest that distinct different degrees of karyotypic heterogeneity and instability may affect neoplasic phenotype of MB cells. These findings bring new insights into cell and tumor biology.

Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers

Large-scale cancer genome sequencing has uncovered thousands of gene mutations, but distinguishing tumor driver genes from functionally neutral passenger mutations is a major challenge. We analyzed 800 cancer genomes of eight types to find single-nucleotide variants (SNVs) that precisely target phosphorylation machinery, important in cancer development and drug targeting. Assuming that cancer-related biological systems involve unexpectedly frequent mutations, we used novel algorithms to identify genes with significant phosphorylation-associated SNVs (pSNVs), phospho-mutated pathways, kinase networks, drug targets, and clinically correlated signaling modules. We highlight increased survival of patients with TP53 pSNVs, hierarchically organized cancer kinase modules, a novel pSNV in EGFR, and an immune-related network of pSNVs that correlates with prolonged survival in ovarian cancer. Our findings include multiple actionable cancer gene candidates (FLNB, GRM1, POU2F1), protein complexes (HCF1, ASF1), and kinases (PRKCZ). This study demonstrates new ways of interpreting cancer genomes and presents new leads for cancer research.

High level of chromosomal aberration in ovarian cancer genome correlates with poor clinical outcome

OBJECTIVES

Structural aberration in chromosomes characterizes almost all human solid cancers and analysis of those alterations may reveal the history of chromosomal instability. However, the clinical significance of massive chromosomal abnormality in ovarian high-grade serous carcinoma (HGSC) remains elusive. In this study, we addressed this issue by analyzing the genomic profiles in 455 ovarian HGSCs available from The Cancer Genome Atlas (TCGA).

METHODS

DNA copy number, mRNA expression, and clinical information were downloaded from the TCGA data portal. A chromosomal disruption index (CDI) was developed to summarize the extent of copy number aberrations across the entire genome. A Cox regression model was applied to identify factors associated with poor prognosis. Genes whose expression was associated with CDI were identified by a 2-stage multivariate linear regression and were used to find enriched pathways by Ingenuity Pathway Analysis.

RESULTS

Multivariate survival analysis showed that a higher CDI was significantly associated with a worse overall survival in patients. Interestingly, the pattern of DNA copy number alterations across all the chromosomes was similar between tumors with high and low CDI, suggesting they did not arise from different mechanisms. We also observed that expression of several genes was highly correlated with the CDI, even after adjusting for local copy number variation. We found that molecular pathways involving DNA damage response and mitosis were significantly enriched in these CDI-correlated genes.

CONCLUSION

Our results provide a new insight into the role of chromosomal rearrangement in the development of HGSC and the promise of applying CDI in risk-stratifying HGSC patients, perhaps for different clinical managements. The genes whose expression is correlated with CDI are worthy of further study to elucidate the mechanism of chromosomal instability in HGSC.

Microhomology directs diverse DNA break repair pathways and chromosomal translocations

Chromosomal structural change triggers carcinogenesis and the formation of other genetic diseases. The breakpoint junctions of these rearrangements often contain small overlapping sequences called “microhomology,” yet the genetic pathway(s) responsible have yet to be defined. We report a simple genetic system to detect microhomology-mediated repair (MHMR) events after a DNA double-strand break (DSB) in budding yeast cells. MHMR using >15 bp operates as a single-strand annealing variant, requiring the non-essential DNA polymerase subunit Pol32. MHMR is inhibited by sequence mismatches, but independent of extensive DNA synthesis like break-induced replication. However, MHMR using less than 14 bp is genetically distinct from that using longer microhomology and far less efficient for the repair of distant DSBs. MHMR catalyzes chromosomal translocation almost as efficiently as intra-chromosomal repair. The results suggest that the intrinsic annealing propensity between microhomology sequences efficiently leads to chromosomal rearrangements.

Cancer results from an accumulation of mutations that transform a normal cell into one that proliferates uncontrollably. DNA double-strand breaks (DSBs) can lead to genetic mutations and chromosome rearrangements, underscoring the importance of functional DNA DSB repair pathways in the maintenance of chromosome integrity and tumor suppression. Ample evidence suggests that cells possess multiple DSB repair mechanisms with distinct mutational potentials, and one or more of these pathways is likely responsible for the formation of chromosomal translocations. Importantly, at the junctions of many rearrangements, small (2–20 bp in length) overlapping sequences from each of the original sequences, termed “microhomology,” are found, and they may provide a clue as to how these rearrangements form. Here, we describe our genetic investigation into how flanking microhomology influences the type and frequency of DSB repair. We also show that microhomology-mediated repair (MHMR) efficiently induces chromosomal translocations. This research provides a basic understanding of the mechanisms that utilize microhomology for mutagenic repair.

A retrospective analysis of antitumour activity with trabectedin in translocation-related sarcomas

AIMS

Approximately 20% of soft tissue sarcomas (STS) have subtype-specific chromosomal translocations; these generate chimeric oncoproteins which can act as abnormal transcription factors. Since trabectedin can bind to DNA and displace transcription factors, antitumour activity was explored in translocation-related sarcoma (TRS) subtypes.

METHODS

The current retrospective pooled analysis includes data from 81 patients with TRS treated in 8 phase II trials.

RESULTS

TRS subtypes were: synovial sarcoma (SS, n=45), myxoid-round cell liposarcoma (MRC-L-sarcoma, n=27), alveolar soft part sarcoma (ASPS, n=4), endometrial stromal sarcoma (ESS, n=3) and clear cell sarcoma (CCS, n=2). All but one patient had received prior chemotherapy (median of 2 lines). Patients received a median of 4 trabectedin cycles (range, 1-48; median dose intensity=0.40 mg/m(2)/week). Partial responses according to Response Evaluation Criteria in Solid Tumours (RECIST) occurred in 8 patients (ORR=10%; 95% CI, 4-19%): four in MRC-L-sarcoma; three in SS and one in ESS. Tumour control rate (ORR plus stable disease) was 59% (95% CI, 48-70%). Median PFS was 4.1 months (6-month PFS rate=40%). Median overall survival was 17.4 months (survival rate at 12 months=60%). Trabectedin had a manageable safety profile.

CONCLUSION

Trabectedin demonstrates encouraging disease control in TRS. Since these promising results were generally noted in patients following chemotherapy, a phase III randomised trial in first-line is ongoing to compare trabectedin with doxorubicin-based chemotherapy in patients with TRS.

Oncogenomics methods and resources

Today, cancer is viewed as a genetic disease and many genetic mechanisms of oncogenesis are known. The progression from normal tissue to invasive cancer is thought to occur over a timescale of 5-20 years. This transformation is driven by both inherited genetic factors and somatic genetic alterations and mutations, and it results in uncontrolled cell growth and, in many cases, death. In this article, we review the main types of genomic and genetic alterations involved in cancer, namely copy-number changes, genomic rearrangements, somatic mutations, polymorphisms, and epigenomic alterations in cancer. We then discuss the transcriptomic consequences of these alterations in tumor cells. The use of "next-generation" sequencing methods in cancer research is described in the relevant sections. Finally, we discuss different approaches for candidate prioritization and integration and analysis of these complex data.

Absolute quantification of somatic DNA alterations in human cancer

We describe a computational method that infers tumor purity and malignant cell ploidy directly from analysis of somatic DNA alterations. The method, named ABSOLUTE, can detect subclonal heterogeneity and somatic homozygosity, and it can calculate statistical sensitivity for detection of specific aberrations. We used ABSOLUTE to analyze exome sequencing data from 214 ovarian carcinoma tumor-normal pairs. This analysis identified both pervasive subclonal somatic point-mutations and a small subset of predominantly clonal and homozygous mutations, which were overrepresented in the tumor suppressor genes TP53 and NF1 and in a candidate tumor suppressor gene CDK12. We also used ABSOLUTE to infer absolute allelic copy-number profiles from 3,155 diverse cancer specimens, revealing that genome-doubling events are common in human cancer, likely occur in cells that are already aneuploid, and influence pathways of tumor progression (for example, with recessive inactivation of NF1 being less common after genome doubling). ABSOLUTE will facilitate the design of clinical sequencing studies and studies of cancer genome evolution and intra-tumor heterogeneity.

New therapeutic targets in soft tissue sarcoma

Soft tissue sarcomas are an uncommon and diverse group of more than 50 mesenchymal malignancies. The pathogenesis of many of these is poorly understood, but others have begun to reveal the secrets of their underlying mechanisms. With considerable effort over recent years, soft tissue sarcomas have increasingly been classified on the basis of underlying molecular alterations. In turn, this has allowed the development and application of targeted agents in several specific, molecularly defined, sarcoma subtypes. This review will focus on the rationale for targeted therapy in sarcoma, with emphasis on the relevance of specific molecular factors and pathways in both translocation-associated sarcomas and in genetically complex tumors. In addition, we will address some of the early successes in sarcoma-targeted therapy as well as a few challenges and disappointments in this field. Finally, we will discuss several possible opportunities represented by poorly understood, but potentially promising new therapeutic targets, as well as several novel biological agents currently in preclinical and early phase I/II trials. This will provide the reader with the context for understanding the current state of this field and a sense of where it may be headed in the coming years.

Gene expression identifies heterogeneity of metastatic propensity in high-grade soft tissue sarcomas

BACKGROUND

Metastatic propensity of soft tissue sarcoma (STS) is heterogeneous and may be determined by gene expression patterns that do not correlate well with morphology. The authors have reported gene expression patterns that distinguish 2 broad classes of clear cell renal carcinoma (ccRCC-gene set), and other patterns that can distinguish heterogeneity of serous ovarian carcinoma (OVCA-gene set) and aggressive fibromatosis (AF-gene set); however, clinical follow-up data were not available for these samples.

METHODS

In the current study, gene expression patterns in 73 samples of high-grade STS were examined using spotted cDNA microarray slides that contained ∼16,000 unique UniGene clusters. Approximately 50% of the genes present in the ccRCC-, OVCA-, and AF-gene sets were also represented in the data from this chip set, and these were combined to form a composite gene set of 278 probes.

RESULTS

Hierarchical clustering using this composite gene set suggested the existence of subsets of the STS samples. Analysis revealed differences in the time to development of metastatic disease between the clusters defined by the first branch point of the clustering dendrogram (P = .005), and also among the 4 different clusters defined by the second branch points (P = .001).

CONCLUSIONS

This approach suggests the existence of >2 subsets of high-grade pleomorphic STS, each with distinct clinical behavior. A composite gene set such as that described here may be useful to stratify STS in clinical trials, and may be of practical utility in patient management.

Evolutionary mechanisms and diversity in cancer

The recently introduced genome theory of cancer evolution provides a new framework for evolutionary studies on cancer. In particular, the established relationship between the large number of individual molecular mechanisms and the general evolutionary mechanism of cancer calls upon a change in our strategies that have been based on the characterization of common cancer gene mutations and their defined pathways. To further explain the significance of the genome theory of cancer evolution, a brief review will be presented describing the various attempts to illustrate the evolutionary mechanism of cancer, followed by further analysis of some key components of somatic cell evolution, including the diversity of biological systems, the multiple levels of information systems and control systems, the two phases (the punctuated or discontinuous phase and gradual Darwinian stepwise phase) and dynamic patterns of somatic cell evolution where genome replacement is the driving force. By linking various individual molecular mechanisms to the level of genome population diversity and tumorigenicity, the general mechanism of cancer has been identified as the evolutionary mechanism of cancer, which can be summarized by the following three steps including stress-induced genome instability, population diversity or heterogeneity, and genome-mediated macroevolution. Interestingly, the evolutionary mechanism is equal to the collective aggregate of all individual molecular mechanisms. This relationship explains why most of the known molecular mechanisms can contribute to cancer yet there is no single dominant mechanism for the majority of clinical cases. Despite the fact that each molecular mechanism can serve as a system stress and initiate the evolutionary process, to achieve cancer, multiple cycles of genome-mediated macroevolution are required and are a stochastically determined event. Finally, the potential clinical implications of the evolutionary mechanism of cancer are briefly reviewed.

High-throughput resequencing of target-captured cDNA in cancer cells

The recent advent of whole exon (exome)-capture technology, coupled with second-generation sequencers, has made it possible to readily detect genomic alterations that affect encoded proteins in cancer cells. Such target resequencing of the cancer genome, however, fails to detect most clinically-relevant gene fusions, given that such oncogenic fusion genes are often generated through intron-to-intron ligation. To develop a resequencing platform that simultaneously captures point mutations, insertions-deletions (indels), and gene fusions in the cancer genome, we chose cDNA as the input for target capture and extensive resequencing, and we describe the versatility of such a cDNA-capture system. As a test case, we constructed a custom target-capture system for 913 cancer-related genes, and we purified cDNA fragments for the target gene set from five cell lines of CML. Our target gene set included Abelson murine leukemia viral oncogene homolog 1 (ABL1), but it did not include breakpoint cluster region (BCR); however, the sequence output faithfully detected reads spanning the fusion points of these two genes in all cell lines, confirming the ability of cDNA capture to detect gene fusions. Furthermore, computational analysis of the sequence dataset successfully identified non-synonymous mutations and indels, including those of tumor protein p53 (TP53). Our data might thus support the feasibility of a cDNA-capture system coupled with massively parallel sequencing as a simple platform for the detection of a variety of anomalies in protein-coding genes among hundreds of cancer specimens.

Chromosome abnormalities defined by conventional cytogenetics in plasma cell leukemia: what have we learned about its biology?

Cancer cells are characterized by having chromosomal abnormalities. The number of aberrations and the specific chromosomes affected are likely correlated with tumor progression. In this study, we analyzed the karyotype of 126 plasma cell leukemia (PCL) patients to identify the most frequently occurring imbalances and to design a model of karyotypic evolution. The Mitelman database of chromosome was searched and abnormal karyotypes were assessed. The main clones were analyzed and chromosomal gains and losses were used to design a model of genetic acquisition based on the calculation of a variable called time to occurrence. Our comprehensive study of genetic abnormalities of a large number of PCL karyotypes suggests that PCL is mainly characterized by the presence of whole chromosome losses as well as IgH rearrangements which is similar to that observed in non-hyperdiploid multiple myeloma (MM). Temporal analysis suggests that most PCL have around 10 abnormalities at diagnosis. It is possible that accumulation of abnormalities such as 17p13 (TP53) and 1p losses may trigger the extramedullary features of PCL. Our study demonstrates that cytogenetics is a valuable tool to evaluate the role of genetic imbalances on karyotypic evolution by using a mathematical model.

SKY analysis revealed recurrent numerical and structural chromosome changes in BDII rat endometrial carcinomas

Background

Genomic alterations are common features of cancer cells, and some of these changes are proven to be neoplastic-specific. Such alterations may serve as valuable tools for diagnosis and classification of tumors, prediction of clinical outcome, disease monitoring, and choice of therapy as well as for providing clues to the location of crucial cancer-related genes.

Endometrial carcinoma (EC) is the most frequently diagnosed malignancy of the female genital tract, ranking fourth among all invasive tumors affecting women. Cytogenetic studies of human ECs have not produced very conclusive data, since many of these studies are based on karyotyping of limited number of cases and no really specific karyotypic changes have yet been identified. As the majority of the genes are conserved among mammals, the use of inbred animal model systems may serve as a tool for identification of underlying genes and pathways involved in tumorigenesis in humans. In the present work we used spectral karyotyping (SKY) to identify cancer-related aberrations in a well-characterized experimental model for spontaneous endometrial carcinoma in the BDII rat tumor model.

Results

Analysis of 21 experimental ECs revealed specific nonrandom numerical and structural chromosomal changes. The most recurrent numerical alterations were gains in rat chromosome 4 (RNO4) and losses in RNO15. The most commonly structural changes were mainly in form of chromosomal translocations and were detected in RNO3, RNO6, RNO10, RNO11, RNO12, and RNO20. Unbalanced chromosomal translocations involving RNO3p was the most commonly observed structural changes in this material followed by RNO11p and RNO10 translocations.

Conclusion

The non-random nature of these events, as documented by their high frequencies of incidence, is suggesting for dynamic selection of these changes during experimental EC tumorigenesis and therefore for their potential contribution into development of this malignancy. Comparative molecular analysis of the identified genetic changes in this tumor model with those reported in the human ECs may provide new insights into underlying genetic changes involved in EC development and tumorigenesis.

Detecting copy number status and uncovering subclonal markers in heterogeneous tumor biopsies

Background

Genomic aberrations can be used to determine cancer diagnosis and prognosis. Clinically relevant novel aberrations can be discovered using high-throughput assays such as Single Nucleotide Polymorphism (SNP) arrays and next-generation sequencing, which typically provide aggregate signals of many cells at once. However, heterogeneity of tumor subclones dramatically complicates the task of detecting aberrations.

Results

The aggregate signal of a population of subclones can be described as a linear system of equations. We employed a measure of allelic imbalance and total amount of DNA to characterize each locus by the copy number status (gain, loss or neither) of the strongest subclonal component. We designed simulated data to compare our measure to existing approaches and we analyzed SNP-arrays from 30 melanoma samples and transcriptome sequencing (RNA-Seq) from one melanoma sample.

We showed that any system describing aggregate subclonal signals is underdetermined, leading to non-unique solutions for the exact copy number profile of subclones. For this reason, our illustrative measure was more robust than existing Hidden Markov Model (HMM) based tools in inferring the aberration status, as indicated by tests on simulated data. This higher robustness contributed in identifying numerous aberrations in several loci of melanoma samples. We validated the heterogeneity and aberration status within single biopsies by fluorescent in situ hybridization of four affected and transcriptionally up-regulated genes E2F8, ETV4, EZH2 and FAM84B in 11 melanoma cell lines. Heterogeneity was further demonstrated in the analysis of allelic imbalance changes along single exons from melanoma RNA-Seq.

Conclusions

These studies demonstrate how subclonal heterogeneity, prevalent in tumor samples, is reflected in aggregate signals measured by high-throughput techniques. Our proposed approach yields high robustness in detecting copy number alterations using high-throughput technologies and has the potential to identify specific subclonal markers from next-generation sequencing data.

[Dangerous liaisons in prostate cancer. Clinical and biological implications of recurrent gene fusions]

Prostate cancer is a common and clinically heterogeneous disease. Understanding the biology of prostate cancer is necessary to best determinate the risk of disease progression and develop novel therapeutic approaches to prevent or slow down disease progression. The recent discovery and subsequent characterization of recurrent gene rearrangements of ETS genes - most frequently ERG - in the majority of prostate cancers is a milestone in translational prostate cancer research. Although multiple molecular alterations have been detected in prostate cancer, a detailed understanding of gene fusion in prostate cancer should help explain the clinical and biologic diversity in addition to providing a rationale for a molecular sub-classification of the disease. This review describes the path from the identification of common ETS gene rearrangements in prostate cancer to possible applications in the treatment of patients, on to the potential scientific implications arising from their discovery.

A Boolean-based systems biology approach to predict novel genes associated with cancer: Application to colorectal cancer

Background

Cancer has remarkable complexity at the molecular level, with multiple genes, proteins, pathways and regulatory interconnections being affected. We introduce a systems biology approach to study cancer that formally integrates the available genetic, transcriptomic, epigenetic and molecular knowledge on cancer biology and, as a proof of concept, we apply it to colorectal cancer.

Results

We first classified all the genes in the human genome into cancer-associated and non-cancer-associated genes based on extensive literature mining. We then selected a set of functional attributes proven to be highly relevant to cancer biology that includes protein kinases, secreted proteins, transcription factors, post-translational modifications of proteins, DNA methylation and tissue specificity. These cancer-associated genes were used to extract 'common cancer fingerprints' through these molecular attributes, and a Boolean logic was implemented in such a way that both the expression data and functional attributes could be rationally integrated, allowing for the generation of a guilt-by-association algorithm to identify novel cancer-associated genes. Finally, these candidate genes are interlaced with the known cancer-related genes in a network analysis aimed at identifying highly conserved gene interactions that impact cancer outcome. We demonstrate the effectiveness of this approach using colorectal cancer as a test case and identify several novel candidate genes that are classified according to their functional attributes. These genes include the following: 1) secreted proteins as potential biomarkers for the early detection of colorectal cancer (FXYD1, GUCA2B, REG3A); 2) kinases as potential drug candidates to prevent tumor growth (CDC42BPB, EPHB3, TRPM6); and 3) potential oncogenic transcription factors (CDK8, MEF2C, ZIC2).

Conclusion

We argue that this is a holistic approach that faithfully mimics cancer characteristics, efficiently predicts novel cancer-associated genes and has universal applicability to the study and advancement of cancer research.

The mutator phenotype in cancer: molecular mechanisms and targeting strategies

Normal human cells replicate their DNA with exceptional accuracy. It has been estimated that approximately one error occurs during DNA replication for each 10(9) to 10(10) nucleotides polymerized. In contrast, malignant cells exhibit multiple chromosomal abnormalities and contain tens of thousands of alterations in the nucleotide sequence of nuclear DNA. To account for the disparity between the rarity of mutations in normal cells and the large numbers of mutations present in cancer, we have hypothesized that during tumor development, cancer cells exhibit a mutator phenotype. As a defining feature of cancer, the mutator phenotype remains an as-yet unexplored therapeutic target: by reducing the rate at which mutations accumulate it may be possible to significantly delay tumor development; conversely, the large number of mutations in cancer may make cancer cells more sensitive to cell killing by increasing the mutation rate. Here we summarize the evidence for the mutator phenotype hypothesis in cancer and explore how the increased frequency of random mutations during the evolution of human tumors provides new approaches for the design of cancer chemotherapy.

FusionSeq: a modular framework for finding gene fusions by analyzing paired-end RNA-sequencing data

We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including eight cancers with and without known rearrangements.

Deregulation of Aurora kinase gene expression in human testicular germ cell tumours

The Aurora kinases regulate chromosome segregation and cytokinesis, and alterations in their expression associate with cell malignant transformation. In this study, we demonstrated by qRT-PCR analysis of 14 seminomas that Aurora-A mRNA was, with respect to control tissues, augmented in five of 14 tumour tissues by 2.17 +/- 0.30 fold (P < 0.05) and reduced in 9 to 0.38 +/- 0.10 (P < 0.01). Aurora-B mRNA was increased in 11 tumour tissues by 4.33 +/- 0.82 fold (P < 0.01) and reduced in 3 to 0.41 +/- 0.11 fold. Aurora-C mRNA was reduced to 0.20 +/- 0.32 fold (P < 0.01) in 13 seminomas and up-regulated in one case. Western blot experiments, performed on protein extracts of nine seminomas and six normal testes, showed an up-regulation of Aurora-B protein by 10.14 +/- 3.51 fold (P < 0.05), while Aurora-A protein was found increased in four seminomas by 2.16 +/- 0.43 (P < 0.05), unchanged in three and reduced in two tumour tissues. Aurora-C protein was increased by 9.2 +/- 2.90 fold (P < 0.05), suggesting that post-transcriptional mechanisms modulate its expression. In conclusion, we demonstrated that expression of Aurora kinases is deregulated in seminomas, suggesting that they may play a role in the progression of testicular cancers.

Telomere disruption results in non-random formation of de novo dicentric chromosomes involving acrocentric human chromosomes

Genome rearrangement often produces chromosomes with two centromeres (dicentrics) that are inherently unstable because of bridge formation and breakage during cell division. However, mammalian dicentrics, and particularly those in humans, can be quite stable, usually because one centromere is functionally silenced. Molecular mechanisms of centromere inactivation are poorly understood since there are few systems to experimentally create dicentric human chromosomes. Here, we describe a human cell culture model that enriches for de novo dicentrics. We demonstrate that transient disruption of human telomere structure non-randomly produces dicentric fusions involving acrocentric chromosomes. The induced dicentrics vary in structure near fusion breakpoints and like naturally-occurring dicentrics, exhibit various inter-centromeric distances. Many functional dicentrics persist for months after formation. Even those with distantly spaced centromeres remain functionally dicentric for 20 cell generations. Other dicentrics within the population reflect centromere inactivation. In some cases, centromere inactivation occurs by an apparently epigenetic mechanism. In other dicentrics, the size of the α-satellite DNA array associated with CENP-A is reduced compared to the same array before dicentric formation. Extra-chromosomal fragments that contained CENP-A often appear in the same cells as dicentrics. Some of these fragments are derived from the same α-satellite DNA array as inactivated centromeres. Our results indicate that dicentric human chromosomes undergo alternative fates after formation. Many retain two active centromeres and are stable through multiple cell divisions. Others undergo centromere inactivation. This event occurs within a broad temporal window and can involve deletion of chromatin that marks the locus as a site for CENP-A maintenance/replenishment.

Endogenous human centromeres are defined by large arrays of α-satellite DNA. A portion of each α-satellite array is assembled into CENP-A chromatin, the structural and functional platform for kinetochore formation. Most chromosomes are monocentric, meaning they have a single centromere. However, genome rearrangement can produce chromosomes with two centromeres (dicentrics). In most organisms, dicentrics typically break during cell division; however, dicentric human chromosomes can be stable in mitosis and meiosis. This stability reflects centromere inactivation, a poorly understood phenomenon in which one centromere is functionally silenced. To explore molecular and genomic events that occur at the time of dicentric formation, we describe a cell-based system to create dicentric human chromosomes and monitor their behavior after formation. Such dicentrics can experience several fates, including centromere inactivation, breakage, or maintaining two functional centromeres. Unexpectedly, we also find that dicentrics with large (>20Mb) inter-centromeric distances are stable through at least 20 cell divisions. Our results highlight similarities and differences in dicentric behavior between humans and model organisms, and they provide evidence for one mechanism of centromere inactivation by centromeric deletion in some dicentrics. The ability to create dicentric human chromosomes provides a system to test other mechanisms of centromere disassembly and dicentric chromosome stability.

Chromosomal aberrations in thyroid follicular-cell neoplasia: in the search of novel oncogenes and tumour suppressor genes

Thyroid cancer derived from the follicular cell is characterised by specific gene alterations that are closely linked to the various pathological types comprising papillary, follicular and anaplastic thyroid cancer. However, the correlation between molecular biology and pathology is not absolute, since about 30% of cases do not harbour the typical gene alterations. This situation, coupled with the demonstration of genetic heterogeneity in thyroid cancer, is a strong motivation for the search of novel gene alterations. Chromosomal aberrations are a good starting point to initiate this search and therefore the current knowledge on chromosomal alterations in thyroid follicular-cell neoplasia is reviewed in this article. An overview on molecular cytogenetic approaches for this strategy is also provided. The identification of novel genetic markers in thyroid cancer will be further improved by integrative approaches combining data from genomic and expression analyses with clinical data. This approach is powerful to identify genetic markers as well as new therapeutic targets in follicular-cell thyroid cancer.

Extracting consistent knowledge from highly inconsistent cancer gene data sources

BACKGROUND

Hundreds of genes that are causally implicated in oncogenesis have been found and collected in various databases. For efficient application of these abundant but diverse data sources, it is of fundamental importance to evaluate their consistency.

RESULTS

First, we showed that the lists of cancer genes from some major data sources were highly inconsistent in terms of overlapping genes. In particular, most cancer genes accumulated in previous small-scale studies could not be rediscovered in current high-throughput genome screening studies. Then, based on a metric proposed in this study, we showed that most cancer gene lists from different data sources were highly functionally consistent. Finally, we extracted functionally consistent cancer genes from various data sources and collected them in our database F-Census.

CONCLUSIONS

Although they have very low gene overlapping, most cancer gene data sources are highly consistent at the functional level, which indicates that they can separately capture partial genes in a few key pathways associated with cancer. Our results suggest that the sample sizes currently used for cancer studies might be inadequate for consistently capturing individual cancer genes, but could be sufficient for finding a number of cancer genes that could represent functionally most cancer genes. The F-Census database provides biologists with a useful tool for browsing and extracting functionally consistent cancer genes from various data sources.

Devil Facial Tumour Disease (DFTD): Using Genetics and Genomics to Investigate Infectious Disease in an Endangered Marsupial

The Tasmanian devil (Sarcophilus harrisii), so named for its blood-curdling, nocturnal shrieks and snarls, is the largest of the carnivorous marsupials. Although once widely persecuted, concerted efforts are now being made to save the devil from extinction following the emergence of a fatal transmissible malignancy known as devil facial tumour disease (DFTD). DFTD is unusual in that the infectious agent is the cancer cell itself. This chapter discusses the aetiology and pathogenesis of DFTD as well as the profound impact the spread of DFTD has had on the devil’s conservation status. Strategies for managing DFTD and conserving the devil will be explored and the contribution of new sequencing technology to the field of conservation genetics and genomics will be examined with regard to the Tasmanian devil and DFTD.