Johan Staaf

Bio: Johan Staaf is an academic researcher from Lund University. The author has contributed to research in topics: Breast cancer & Lung cancer. The author has an hindex of 46, co-authored 153 publications receiving 8416 citations. Previous affiliations of Johan Staaf include University College Cork.

Landscape of somatic mutations in 560 breast cancer whole-genome sequences

Abstract: We analysed whole-genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. We found that 93 protein-coding cancer genes carried probable driver mutations. Some non-coding regions exhibited high mutation frequencies, but most have distinctive structural features probably causing elevated mutation rates and do not contain driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed twelve base substitution and six rearrangement signatures. Three rearrangement signatures, characterized by tandem duplications or deletions, appear associated with defective homologous-recombination-based DNA repair: one with deficient BRCA1 function, another with deficient BRCA1 or BRCA2 function, the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operating, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures

Abstract: Approximately 1-5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction. Herein we used a lasso logistic regression model to identify six distinguishing mutational signatures predictive of BRCA1/BRCA2 deficiency. A weighted model called HRDetect was developed to accurately detect BRCA1/BRCA2-deficient samples. HRDetect identifies BRCA1/BRCA2-deficient tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline BRCA1 or BRCA2 mutation, allowed us to identify an additional 22 tumors with somatic loss of BRCA1 or BRCA2 and 47 tumors with functional BRCA1/BRCA2 deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring BRCA1/BRCA2 deficiency (up to 22%) than hitherto appreciated (∼1-5%) who could have selective therapeutic sensitivity to PARP inhibition.

GOBO: Gene Expression-Based Outcome for Breast Cancer Online.

Abstract: Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo), allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1) rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2) identification of co-expressed genes for creation of potential metagenes, 3) association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Recurrent gross mutations of the PTEN tumor suppressor gene in breast cancers with deficient DSB repair

Abstract: Basal-like breast cancer (BBC) is a subtype of breast cancer with poor prognosis1, 2, 3 Inherited mutations of BRCA1, a cancer susceptibility gene involved in double-strand DNA break (DSB) repair, lead to breast cancers that are nearly always of the BBC subtype3, 4, 5; however, the precise molecular lesions and oncogenic consequences of BRCA1 dysfunction are poorly understood Here we show that heterozygous inactivation of the tumor suppressor gene Pten leads to the formation of basal-like mammary tumors in mice, and that loss of PTEN expression is significantly associated with the BBC subtype in human sporadic and BRCA1-associated hereditary breast cancers In addition, we identify frequent gross PTEN mutations, involving intragenic chromosome breaks, inversions, deletions and micro copy number aberrations, specifically in BRCA1-deficient tumors These data provide an example of a specific and recurrent oncogenic consequence of BRCA1-dependent dysfunction in DNA repair and provide insight into the pathogenesis of BBC with therapeutic implications These findings also argue that obtaining an accurate census of genes mutated in cancer will require a systematic examination for gross gene rearrangements, particularly in tumors with deficient DSB repair

Molecular subtypes of breast cancer are associated with characteristic DNA methylation patterns

Abstract: Introduction: Five different molecular subtypes of breast cancer have been identified through gene expression profiling. Each subtype has a characteristic expression pattern suggested to partly depend on cellular origin. We aimed to investigate whether the molecular subtypes also display distinct methylation profiles. Methods: We analysed methylation status of 807 cancer-related genes in 189 fresh frozen primary breast tumours and four normal breast tissue samples using an array-based methylation assay. Results: Unsupervised analysis revealed three groups of breast cancer with characteristic methylation patterns. The three groups were associated with the luminal A, luminal B and basal-like molecular subtypes of breast cancer, respectively, whereas cancers of the HER2-enriched and normal-like subtypes were distributed among the three groups. The methylation frequencies were significantly different between subtypes, with luminal B and basal-like tumours being most and least frequently methylated, respectively. Moreover, targets of the polycomb repressor complex in breast cancer and embryonic stem cells were more methylated in luminal B tumours than in other tumours. BRCA2-mutated tumours had a particularly high degree of methylation. Finally, by utilizing gene expression data, we observed that a large fraction of genes reported as having subtype-specific expression patterns might be regulated through methylation. Conclusions: We have found that breast cancers of the basal-like, luminal A and luminal B molecular subtypes harbour specific methylation profiles. Our results suggest that methylation may play an important role in the development of breast cancers.

Comprehensive molecular portraits of human breast tumours

Abstract: We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.

Integrative analysis of 111 reference human epigenomes

Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Patterns of Somatic Mutation in Human Cancer Genomes

Abstract: AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore PL02-05 All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

The biogenesis, biology and characterization of circular RNAs.

Abstract: Circular RNAs (circRNAs) are covalently closed, endogenous biomolecules in eukaryotes with tissue-specific and cell-specific expression patterns, whose biogenesis is regulated by specific cis-acting elements and trans-acting factors. Some circRNAs are abundant and evolutionarily conserved, and many circRNAs exert important biological functions by acting as microRNA or protein inhibitors ('sponges'), by regulating protein function or by being translated themselves. Furthermore, circRNAs have been implicated in diseases such as diabetes mellitus, neurological disorders, cardiovascular diseases and cancer. Although the circular nature of these transcripts makes their detection, quantification and functional characterization challenging, recent advances in high-throughput RNA sequencing and circRNA-specific computational tools have driven the development of state-of-the-art approaches for their identification, and novel approaches to functional characterization are emerging.

Comprehensive molecular characterization of urothelial bladder carcinoma

Abstract: Urothelial carcinoma of the bladder is a common malignancy that causes approximately 150,000 deaths per year worldwide. To date, no molecularly targeted agents have been approved for the disease. As part of The Cancer Genome Atlas project, we report here an integrated analysis of 131 urothelial carcinomas to provide a comprehensive landscape of molecular alterations. There were statistically significant recurrent mutations in 32 genes, including multiple genes involved in cell Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#termsThis paper is distributed under the terms of the Creative Commons. Attribution-Non-Commercial-Share Alike license, and the online version of the paper is freely available to all readers.