Esa Pitkänen

Characterization of Uterine Leiomyomas by Whole-Genome Sequencing

BACKGROUND Uterine leiomyomas are benign but affect the health of millions of women. A better understanding of the molecular mechanisms involved may provide clues to the prevention and treatment of these lesions. METHODS We performed whole-genome sequencing and gene-expression profiling of 38 uterine leiomyomas and the corresponding myometrium from 30 women. RESULTS Identical variants observed in some separate tumor nodules suggested that these nodules have a common origin. Complex chromosomal rearrangements resembling chromothripsis were a common feature of leiomyomas. These rearrangements are best explained by a single event of multiple chromosomal breaks and random reassembly. The rearrangements created tissue-specific changes consistent with a role in the initiation of leiomyoma, such as translocations of the HMGA2 and RAD51B loci and aberrations at the COL4A5-COL4A6 locus, and occurred in the presence of normal TP53 alleles. In some cases, separate events had occurred more than once in single tumor-cell lineages. CONCLUSIONS Chromosome shattering and reassembly resembling chromothripsis (a single genomic event that results in focal losses and rearrangements in multiple genomic regions) is a major cause of chromosomal abnormalities in uterine leiomyomas; we propose that tumorigenesis occurs when tissue-specific tumor-promoting changes are formed through these events. Chromothripsis has previously been associated with aggressive cancer; its common occurrence in leiomyomas suggests that it also has a role in the genesis and progression of benign tumors. We observed that multiple separate tumors could be seeded from a single lineage of uterine leiomyoma cells. (Funded by the Academy of Finland Center of Excellence program and others.).

CTCF/cohesin-binding sites are frequently mutated in cancer

Cohesin is present in almost all active enhancer regions, where it is associated with transcription factors. Cohesin frequently colocalizes with CTCF (CCCTC-binding factor), affecting genomic stability, expression and epigenetic homeostasis. Cohesin subunits are mutated in cancer, but CTCF/cohesin-binding sites (CBSs) in DNA have not been examined for mutations. Here we report frequent mutations at CBSs in cancers displaying a mutational signature where mutations in A•T base pairs predominate. Integration of whole-genome sequencing data from 213 colorectal cancer (CRC) samples and chromatin immunoprecipitation sequencing (ChIP-exo) data identified frequent point mutations at CBSs. In contrast, CRCs showing an ultramutator phenotype caused by defects in the exonuclease domain of DNA polymerase ɛ (POLE) displayed significantly fewer mutations at and adjacent to CBSs. Analysis of public data showed that multiple cancer types accumulate CBS mutations. CBSs are a major mutational hotspot in the noncoding cancer genome.

The Glanville fritillary genome retains an ancient karyotype and reveals selective chromosomal fusions in Lepidoptera

Previous studies have reported that chromosome synteny in Lepidoptera has been well conserved, yet the number of haploid chromosomes varies widely from 5 to 223. Here we report the genome (393 Mb) of the Glanville fritillary butterfly (Melitaea cinxia; Nymphalidae), a widely recognized model species in metapopulation biology and eco-evolutionary research, which has the putative ancestral karyotype of n=31. Using a phylogenetic analyses of Nymphalidae and of other Lepidoptera, combined with orthologue-level comparisons of chromosomes, we conclude that the ancestral lepidopteran karyotype has been n=31 for at least 140 My. We show that fusion chromosomes have retained the ancestral chromosome segments and very few rearrangements have occurred across the fusion sites. The same, shortest ancestral chromosomes have independently participated in fusion events in species with smaller karyotypes. The short chromosomes have higher rearrangement rate than long ones. These characteristics highlight distinctive features of the evolutionary dynamics of butterflies and moths.

Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species

We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.

Exome sequencing reveals frequent inactivating mutations in ARID1A, ARID1B, ARID2 and ARID4A in microsatellite unstable colorectal cancer

ARID1A has been identified as a novel tumor suppressor gene in ovarian cancer and subsequently in various other tumor types. ARID1A belongs to the ARID domain containing gene family, which comprises of 15 genes involved, for example, in transcriptional regulation, proliferation and chromatin remodeling. In this study, we used exome sequencing data to analyze the mutation frequency of all the ARID domain containing genes in 25 microsatellite unstable (MSI) colorectal cancers (CRCs) as a first systematic effort to characterize the mutation pattern of the whole ARID gene family. Genes which fulfilled the selection criteria in this discovery set (mutations in at least 4/25 [16%] samples, including at least one nonsense or splice site mutation) were chosen for further analysis in an independent validation set of 21 MSI CRCs. We found that in addition to ARID1A, which was mutated in 39% of the tumors (18/46), also ARID1B (13%, 6/46), ARID2 (13%, 6/46) and ARID4A (20%, 9/46) were frequently mutated. In all these genes, the mutations were distributed along the entire length of the gene, thus distinguishing them from typical MSI target genes previously described. Our results indicate that in addition to ARID1A, other members of the ARID gene family may play a role in MSI CRC.

Integrated data analysis reveals uterine leiomyoma subtypes with distinct driver pathways and biomarkers.

Significance The clinical and scientific community widely regards uterine leiomyomas as a single entity, although evidence of genetic heterogeneity exists. The aim of this study was to explore transcriptional differences between leiomyomas harboring different genetic alterations, including high mobility group AT-hook 2 rearrangements, mediator complex subunit 12 mutations, biallelic inactivation of fumarate hydratase, and collagen, type IV, alpha 5-collagen, type IV, alpha 6 deletions. The evidence presented herein strongly suggests that specific driver mutations are the major determinants of expression changes in leiomyomas. Here we highlight subtype-specific expression differences in key driver pathways and emphasize the utility of stratification in leiomyoma research. Finally, we offer a set of candidate biomarkers that will facilitate the molecular classification of leiomyomas. Uterine leiomyomas are common benign smooth muscle tumors that impose a major burden on women’s health. Recent sequencing studies have revealed recurrent and mutually exclusive mutations in leiomyomas, suggesting the involvement of molecularly distinct pathways. In this study, we explored transcriptional differences among leiomyomas harboring different genetic drivers, including high mobility group AT-hook 2 (HMGA2) rearrangements, mediator complex subunit 12 (MED12) mutations, biallelic inactivation of fumarate hydratase (FH), and collagen, type IV, alpha 5 and collagen, type IV, alpha 6 (COL4A5-COL4A6) deletions. We also explored the transcriptional consequences of 7q22, 22q, and 1p deletions, aiming to identify possible target genes. We investigated 94 leiomyomas and 60 corresponding myometrial tissues using exon arrays, whole genome sequencing, and SNP arrays. This integrative approach revealed subtype-specific expression changes in key driver pathways, including Wnt/β-catenin, Prolactin, and insulin-like growth factor (IGF)1 signaling. Leiomyomas with HMGA2 aberrations displayed highly significant up-regulation of the proto-oncogene pleomorphic adenoma gene 1 (PLAG1), suggesting that HMGA2 promotes tumorigenesis through PLAG1 activation. This was supported by the identification of genetic PLAG1 alterations resulting in expression signatures as seen in leiomyomas with HMGA2 aberrations. RAD51 paralog B (RAD51B), the preferential translocation partner of HMGA2, was up-regulated in MED12 mutant lesions, suggesting a role for this gene in the genesis of leiomyomas. FH-deficient leiomyomas were uniquely characterized by activation of nuclear factor erythroid 2-related factor 2 (NRF2) target genes, supporting the hypothesis that accumulation of fumarate leads to activation of the oncogenic transcription factor NRF2. This study emphasizes the need for molecular stratification in leiomyoma research and possibly in clinical practice as well. Further research is needed to determine whether the candidate biomarkers presented herein can provide guidance for managing the millions of patients affected by these lesions.

Computational methods for metabolic reconstruction.

In the wake of numerous sequenced genomes becoming available, computational methods for the reconstruction of metabolic networks have received considerable attention. Here, we review recent methods and software tools useful along the reconstruction workflow, from sequence annotation and network assembly to model verification and testing against experimental data. Reconstruction methods can be divided into three categories, depending on the magnitude of network context which is taken into account in the process of assembling the metabolic model: First, each enzyme may be predicted independently by annotation transfer or machine learning methods. Second, the presence of a metabolic pathway may be detected from genome and experimental evidence, often utilizing a reference pathway database. Third, the method may attempt to directly reconstruct a consistent metabolic network without relying on predefined reference pathways. Regardless of the chosen context, all methods strive to reconstruct genome-scale metabolic reconstructions. Currently a gap exists between software platforms dedicated to genome annotation and computational tools for automatically repairing network inconsistencies and validating against measurement data. We argue that to accelerate the reconstruction efforts, computational tools need to be developed that bridge the phases of the reconstruction workflow. In particular, the goal of finding consistent metabolic models suitable for computational analysis should be taken into account already in the beginning phases of reconstruction.

Eleven Candidate Susceptibility Genes for Common Familial Colorectal Cancer

Hereditary factors are presumed to play a role in one third of colorectal cancer (CRC) cases. However, in the majority of familial CRC cases the genetic basis of predisposition remains unexplained. This is particularly true for families with few affected individuals. To identify susceptibility genes for this common phenotype, we examined familial cases derived from a consecutive series of 1514 Finnish CRC patients. Ninety-six familial CRC patients with no previous diagnosis of a hereditary CRC syndrome were included in the analysis. Eighty-six patients had one affected first-degree relative, and ten patients had two or more. Exome sequencing was utilized to search for genes harboring putative loss-of-function variants, because such alterations are likely candidates for disease-causing mutations. Eleven genes with rare truncating variants in two or three familial CRC cases were identified: UACA, SFXN4, TWSG1, PSPH, NUDT7, ZNF490, PRSS37, CCDC18, PRADC1, MRPL3, and AKR1C4. Loss of heterozygosity was examined in all respective cancer samples, and was detected in seven occasions involving four of the candidate genes. In all seven occasions the wild-type allele was lost (P = 0.0078) providing additional evidence that these eleven genes are likely to include true culprits. The study provides a set of candidate predisposition genes which may explain a subset of common familial CRC. Additional genetic validation in other populations is required to provide firm evidence for causality, as well as to characterize the natural history of the respective phenotypes.

MED12 mutation frequency in unselected sporadic uterine leiomyomas

OBJECTIVE To determine the frequency of mediator complex subunit 12 (MED12) mutations in well-documented, prospectively collected, unselected series of sporadic uterine leiomyomas to better understand the contribution of MED12 mutations in leiomyoma genesis. DESIGN Mutation analysis of two prospectively collected sample series. SETTING Department of gynecology in university hospital and medical genetics research laboratory. PATIENT(S) 164 uterine leiomyomas from 28 patients (13 consecutive and 15 unselected patients) undergoing hysterectomy. INTERVENTION(S) MED12 mutation screening by direct sequencing, and clinical data collection. MAIN OUTCOME MEASURE(S) MED12 mutation status and various clinical variables. RESULT(S) MED12 mutations were found in 73 (83.0%) of 88 and 65 (85.5%) of 76 of uterine leiomyomas from the consecutive and unselected patient series, respectively. Smaller tumor size and a larger number of tumors correlated with positive MED12 mutation status. CONCLUSION(S) The frequency of MED12 mutations in our prospectively collected uterine leiomyoma sets was higher than in previous works. This is in keeping with the concept that MED12 mutation-positive tumors tend to be smaller in size than MED12 mutation-negative tumors. The results highlight the central role of MED12 mutations in uterine leiomyoma genesis.

Whole-Genome Sequencing of Growth Hormone (GH)-Secreting Pituitary Adenomas.

CONTEXT The somatic landscape of pituitary adenomas is largely unknown. Identification of somatic alterations aims at better understanding of tumor pathology. OBJECTIVE The objective of the study was a genome-wide characterization of somatic single-nucleotide variants, structural variants, and copy-number aberrations in somatotropinomas. DESIGN AND SETTING Whole-genome sequencing and single-nucleotide polymorphism array analyses were performed on 12 fresh-frozen somatotropinomas and their corresponding blood samples. All the coding somatic variants were confirmed by Sanger sequencing. PATIENTS Studied tumors were somatotropinomas. Apart from one AIP mutation-positive patient, all cases were mutation negative for the established germline mutations associated with pituitary adenomas. INTERVENTION(S) There were no interventions. MAIN OUTCOME MEASURES Somatic variants were identified with an established computational pipeline and filtered against germline data. Somatic copy number alteration analyses were performed using segmentation-based approaches. RESULTS A genome-wide analysis revealed on average 129 somatic single-nucleotide variants per tumor. Further analysis of coding regions showed on average 2.3 single-nucleotide variants per tumor. The only recurrent somatic events were the oncogenic GNAS mutation (p.Arg201Cys) and shared chromosome losses (chromosomes 1, 6, 13, 14, 15, 16, 18, 22). Analysis of somatic structural variants revealed one tumor with a complex chromosomal rearrangement. CONCLUSIONS Somatotropinomas showed a low number of somatic genetic alterations. Whereas no novel recurrently mutated genes could be identified, the somatic landscape has potential to affect the Ca(2+) and ATP pathways known to be involved in the pituitary tumorigenesis. Further studies, eg, methylome and transcriptome analyses, are needed to investigate possible interplay between the recurrent chromosome losses and epigenetic factors.