Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although standard-of-care chemotherapeutics are sufficient for most ALL cases, there are subsets of patients with poor response who relapse in disease. The biology underlying differences between subtypes and their response to therapy has only partially been explained by genetic and transcriptomic profiling. Here, we perform comprehensive multi-omic analyses of 49 readily available childhood ALL cell lines, using proteomics, transcriptomics, and pharmacoproteomic characterization. We connect the molecular phenotypes with drug responses to 528 oncology drugs, identifying drug correlations as well as lineage-dependent correlations. We also identify the diacylglycerol-analog bryostatin-1 as a therapeutic candidate in the MEF2D-HNRNPUL1 fusion high-risk subtype, for which this drug activates pro-apoptotic ERK signaling associated with molecular mediators of pre-B cell negative selection. Our data is the foundation for the interactive online Functional Omics Resource of ALL (FORALL) with navigable proteomics, transcriptomics, and drug sensitivity profiles at https://proteomics.se/forall .

Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis.

MOTIVATION: Analysis of relationships of drug structure to biological response is key to understanding off-target and unexpected drug effects, and for developing hypotheses on how to tailor drug therapies. New methods are required for integrated analyses of a large number of chemical features of drugs against the corresponding genome-wide responses of multiple cell models. RESULTS: In this article, we present the first comprehensive multi-set analysis on how the chemical structure of drugs impacts on genome-wide gene expression across several cancer cell lines [Connectivity Map (CMap) database]. The task is formulated as searching for drug response components across multiple cancers to reveal shared effects of drugs and the chemical features that may be responsible. The components can be computed with an extension of a recent approach called Group Factor Analysis. We identify 11 components that link the structural descriptors of drugs with specific gene expression responses observed in the three cell lines and identify structural groups that may be responsible for the responses. Our method quantitatively outperforms the limited earlier methods on CMap and identifies both the previously reported associations and several interesting novel findings, by taking into account multiple cell lines and advanced 3D structural descriptors. The novel observations include: previously unknown similarities in the effects induced by 15-delta prostaglandin J2 and HSP90 inhibitors, which are linked to the 3D descriptors of the drugs; and the induction by simvastatin of leukemia-specific response, resembling the effects of corticosteroids. AVAILABILITY AND IMPLEMENTATION: Source Code implementing the method is available at: http://research.ics.aalto.fi/mi/software/GFAsparse. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Break-induced replication repair of damaged forks induces genomic duplications in human cells.

In budding yeast, one-ended DNA double-strand breaks (DSBs) and damaged replication forks are repaired by break-induced replication (BIR), a homologous recombination pathway that requires the Pol32 subunit of DNA polymerase delta. DNA replication stress is prevalent in cancer, but BIR has not been characterized in mammals. In a cyclin E overexpression model of DNA replication stress, POLD3, the human ortholog of POL32, was required for cell cycle progression and processive DNA synthesis. Segmental genomic duplications induced by cyclin E overexpression were also dependent on POLD3, as were BIR-mediated recombination events captured with a specialized DSB repair assay. We propose that BIR repairs damaged replication forks in mammals, accounting for the high frequency of genomic duplications in human cancers.

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs.

BACKGROUND: Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile. RESULTS: Integrated analysis of both the chemical and biological space was more informative than either dataset alone in predicting drug similarity as measured by shared protein targets. We identified ten major components that link distinct VolSurf chemical features across multiple compounds to specific cellular responses. For example, component 2 (hydrophobic properties) strongly linked to DNA damage response, while component 3 (hydrogen bonding) was associated with metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides. CONCLUSIONS: In summary, our approach identified several novel links between specific chemical structure properties and distinct biological responses in cells incubated with these drugs. Importantly, the analysis focused on chemical-biological properties that emerge across multiple drugs. The decoding of such systematic relationships is necessary to build better models of drug effects, including unanticipated types of molecular properties having strong biological effects.

Classification of unknown primary tumors with a data-driven method based on a large microarray reference database.

We present a new method to analyze cancer of unknown primary origin (CUP) samples. Our method achieves good results with classification accuracy (88% leave-one-out cross validation for primary tumors from 56 categories, 78% for CUP samples), and can also be used to study CUP samples on a gene-by-gene basis. It is not tied to any a priori defined gene set as many previous methods, and is adaptable to emerging new information.

Alignment of gene expression profiles from test samples against a reference database: New method for context-specific interpretation of microarray data.

BACKGROUND: Gene expression microarray data have been organized and made available as public databases, but the utilization of such highly heterogeneous reference datasets in the interpretation of data from individual test samples is not as developed as e.g. in the field of nucleotide sequence comparisons. We have created a rapid and powerful approach for the alignment of microarray gene expression profiles (AGEP) from test samples with those contained in a large annotated public reference database and demonstrate here how this can facilitate interpretation of microarray data from individual samples. METHODS: AGEP is based on the calculation of kernel density distributions for the levels of expression of each gene in each reference tissue type and provides a quantitation of the similarity between the test sample and the reference tissue types as well as the identity of the typical and atypical genes in each comparison. As a reference database, we used 1654 samples from 44 normal tissues (extracted from the Genesapiens database). RESULTS: Using leave-one-out validation, AGEP correctly defined the tissue of origin for 1521 (93.6%) of all the 1654 samples in the original database. Independent validation of 195 external normal tissue samples resulted in 87% accuracy for the exact tissue type and 97% accuracy with related tissue types. AGEP analysis of 10 Duchenne muscular dystrophy (DMD) samples provided quantitative description of the key pathogenetic events, such as the extent of inflammation, in individual samples and pinpointed tissue-specific genes whose expression changed (SAMD4A) in DMD. AGEP analysis of microarray data from adipocytic differentiation of mesenchymal stem cells and from normal myeloid cell types and leukemias provided quantitative characterization of the transcriptomic changes during normal and abnormal cell differentiation. CONCLUSIONS: The AGEP method is a widely applicable method for the rapid comprehensive interpretation of microarray data, as proven here by the definition of tissue- and disease-specific changes in gene expression as well as during cellular differentiation. The capability to quantitatively compare data from individual samples against a large-scale annotated reference database represents a widely applicable paradigm for the analysis of all types of high-throughput data. AGEP enables systematic and quantitative comparison of gene expression data from test samples against a comprehensive collection of different cell/tissue types previously studied by the entire research community.

The miR-15a-miR-16-1 locus is homozygously deleted in a subset of prostate cancers.

MicroRNAs (miRNAs) are small, non-coding RNAs that negatively regulate the expression of protein coding genes. In this study, we screened highly informative prostate cancer cell lines and xenografts (n = 42) for miRNA gene copy number and expression changes. The expression profiling showed distinction between cell lines and xenografts as well as between androgen sensitive and independent models. Only a few copy number alterations that were associated with expression changes were identified. Most importantly, the miR-15a-miR-16-1 locus was found to be homozygously deleted in two samples leading to the abolishment of miR-15a, but not miR-16, expression. miR-16 is also expressed from another genomic locus. Mutation screening of the miR-15a-miR-16-1 gene in the model systems as well as clinical samples (n = 50) revealed no additional mutations. In conclusion, our data indicate that putative tumor suppressors, miR-15a and miR-16-1, are homozygously deleted in a subset of prostate cancers, further suggesting that these miRNAs could be important in the development of prostate cancer.

Androgen regulation of micro-RNAs in prostate cancer.

BACKGROUND: Androgens play a critical role in the growth of both androgen dependent and castration-resistant prostate cancer (CRPC). Only a few micro-RNAs (miRNAs) have been suggested to be androgen regulated. We aim to identify androgen regulated miRNAs. METHODS: We utilized LNCaP derived model, we have established, and which overexpresses the androgen receptor (AR), the VCaP cell line, and 13 intact-castrated prostate cancer (PC) xenograft pairs, as well as clinical specimens of untreated (PC) and CRPC. The expression of miRNAs was analyzed by microarrays and quantitative RT-PCR (Q-RT-PCR). Transfection of pre-miR-141 and anti-miR-141 was also used. RESULTS: Seventeen miRNAs were > 1.5-fold up- or downregulated upon dihydrotestosterone (DHT) treatment in the cell lines, and 42 after castration in the AR-positive xenografts. Only four miRNAs (miR-10a, miR-141, miR-150*, and miR-1225-5p) showed similar androgen regulation in both cell lines and xenografts. Of those, miR-141 was found to be expressed more in PC and CRPC compared to benign prostate hyperplasia. Additionally, the overexpression of miR-141 enhanced growth of parental LNCaP cells while inhibition of miR-141 by anti-miR-141 suppressed the growth of the LNCaP subline overexpressing AR. CONCLUSIONS: Only a few miRNAs were found to be androgen-regulated in both cell lines and xenografts models. Of those, the expression of miR-141 was upregulated in cancer. The ectopic overexpression of miR-141 increased growth of LNCaP cell suggesting it may contribute to the progression of PC.

Defining the molecular action of HDAC inhibitors and synergism with androgen deprivation in ERG-positive prostate cancer.

Gene fusions between prostate-specific, androgen responsive TMPRSS2 gene and oncogenic ETS factors, such as ERG, occur in up to 50% of all prostate cancers. We recently defined a gene signature that was characteristic to prostate cancers with ERG activation. This suggested epigenetic reprogramming, such as upregulation of histone deactylase 1 (HDAC1) gene and downregulation of its target genes. We then hypothesized that patients with ERG-positive prostate cancers may benefit from epigenetic therapy such as HDAC inhibition (HDACi), especially in combination with antiandrogens. Here, we exposed ERG-positive prostate cancer cell lines to HDAC inhibitors Trichostatin A (TSA), MS-275 and suberoylanilide hydroxamic acid (SAHA) with or without androgen deprivation. We explored the effects on cell phenotype, gene expression as well as ERG and androgen receptor (AR) signaling. When compared with 5 other prostate cell lines, ERG-positive VCaP and DuCap cells were extremely sensitive to HDACi, in particular TSA, showing synergy with concomitant androgen deprivation increasing apoptosis. Both of the HDAC inhibitors studied caused repression of the ERG-fusion gene, whereas the pan-HDAC inhibitor TSA prominently repressed the ERG-associated gene signature. Additionally, HDACi and flutamide caused retention of AR in the cytoplasm, indicating blockage of androgen signaling. Our results support the hypothesis that HDACi, especially in combination with androgen deprivation, is effective against TMPRSS2-ERG-fusion positive prostate cancer in vitro. Together with our previous in vivo observations of an "epigenetic reprogramming gene signature" in clinical ERG-positive prostate cancers, these studies provide mechanistic insights to ERG-associated tumorigenesis and suggest therapeutic paradigms to be tested in vivo.

EphB2 expression across 138 human tumor types in a tissue microarray: high levels of expression in gastrointestinal cancers.

PURPOSE: To comprehensively evaluate ephrin receptor B2 (EphB2) expression in normal and neoplastic tissues. EphB2 is a tyrosine kinase recently implicated in the deregulation of cell-to-cell communication in many tumors. EXPERIMENTAL DESIGN: EphB2 protein expression was analyzed by immunohistochemistry on tissue microarrays that included 76 different normal tissues, >4,000 samples from 138 different cancer types, and 1,476 samples of colon cancer with clinical follow-up data. RESULTS: We found most prominent EphB2 expression in the intestinal epithelium (colonic crypts) with cancer of the colorectum displaying the highest EphB2 positivity of all tumors. Positivity was found in 100% of 118 colon adenomas but in 33.3% of 45 colon carcinomas. EphB2 expression was also observed in 75 tumor categories, including serous carcinoma of the endometrium (34.8%), adenocarcinoma of the esophagus (33.3%), intestinal adenocarcinoma of the stomach (30.2%), and adenocarcinoma of the small intestine (70%). The occasional finding of strong EphB2 positivity in tumors without EphB2 positivity in the corresponding normal cells [adenocarcinoma of the lung (4%) and pancreas (2.2%)] suggests that deregulation of EphB2 signaling may involve up-regulation of the protein expression. In colon carcinoma, loss of EphB2 expression was associated with advanced stage (P < 0.0001) and was an indicator of poor overall survival (P = 0.0098). CONCLUSIONS: Our results provide an overview on the EphB2 protein expression in normal and neoplastic tissues. Deregulated EphB2 expression may play a role in several cancer types with loss of EphB2 expression serving as an indicator of the possible pathogenetic role of EphB2 signaling in the maintenance of tissue architecture of colon epithelium.

A major locus for hereditary prostate cancer in Finland: localization by linkage disequilibrium of a haplotype in the HPCX region.

BACKGROUND: Prostate cancer (PRCA) is the most common cancer in males in the western world. In Finland PRCA has an age-adjusted incidence of 81.5 per 100,000. We previously reported that in Finland, the late-onset cases in families with "no-male-to-male" (NMM) transmission of PRCA accounted for most of the linkage to the HPCX region (Xq27-28). The aim of the present study was to test for linkage disequilibrium (LD) and haplotype-sharing around marker DXS1205 between cases from hereditary prostate cancer (HPC) families and population controls. The initial allelic association was performed between 108 PRCA cases and 257 population controls genotyped for 23 markers in the Xq26-28 region. This resulted in a highly significant nominal one-sided Fisher's exact P-value of 0.0003 for allele ''180'' of marker DXS1205. Subsequently, a similar level of significance was observed for the same allele for marker DXS1205 (P=0.0002) when comparing 60 NMM cases and 257 controls. These results were still significant after Bonferroni correction for multiple testing. Fine mapping efforts included the genotyping of four additional markers D3S2390, bG82i1.9, bG82i1.1, bG82i1.0 and four single nucleotide polymorphisms (SNPs) to augment the original markers around DXS1205. RESULTS: Our major finding is that markers extending from ''D3S2390'' to ''bG82i1.0'' flank the critical locus, about 150 kb. Levin and Bertell's LD measure (delta), a guide to localization of a possible variant, was 0.42 and 0.41 for alleles of markers bG82i1.9 and DXS1205, respectively. CONCLUSIONS: In this study, the most significant haplotype comprised the three tightly linked, contiguous markers: ''cen-bG82i1.9-SNP-Hap B-bG82i1.1-tel'' [''197-2-234''] among several possible haplotypes (nominal Fisher's one-sided P=0.003). The two transcription units mapping within this interval are the LDOC1 and SPANXC genes. Positional cloning of the HPCX gene(s) is being facilitated by this exploration of the Xq26-28 region. This study represents the first report identifying a haplotype in the Xq27-28 region for an association between HPCX and X-linked prostate cancer with no-male-to-male transmission in the Finnish population.

Hereditary prostate cancer in Finland: fine-mapping validates 3p26 as a major predisposition locus.

In a recent genome-wide linkage (GWL) analysis of Finnish families at high risk for prostate cancer, we found two novel putative susceptibility loci at 3p25-p26 and 11q14. Here, we report the fine-mapping of these two critical regions at high resolution with 39 microsatellite markers in 16 families, including multiplex families that were not used in the GWL scan. The maximum multipoint HLOD was 3.39 at 3p26 and 1.42 at 11q14. The highest LOD scores were seen around markers D3S1270 and D3S4559 (alpha=0.89), covering approximately two megabases. The two known genes in this region CHL1 (cell adhesion molecule with homology to L1CAM) and CNTN6 (contactin 6) were screened for exonic mutations in the families showing the strongest linkage, but no disease-segregating sequence variants were observed. The recombination map pointed to a region proximal to the area of best linkage, suggesting that more genes may need to be investigated as candidates. These results provide strong evidence for the existence of a prostate cancer susceptibility gene at 3p26 in Finnish prostate cancer families. This locus has not been strongly linked with hereditary prostate cancer in other populations. However, the mildly positive 3p LOD scores in a recent GWL analysis of patients from the United States suggest that the locus may also be important in other populations.

BRCA2 mutations in 154 finnish male breast cancer patients.

The etiology and pathogenesis of male breast cancer (MBC) are poorly known. This is due to the fact that the disease is rare, and large-scale genetic epidemiologic studies have been difficult to carry out. Here, we studied the frequency of eight recurrent Finnish BRCA2 founder mutations in a large cohort of 154 MBC patients (65% diagnosed in Finland from 1967 to 1996). Founder mutations were detected in 10 patients (6.5%), eight of whom carried the 9346(-2) A>G mutation. Two novel mutations (4075 delGT and 5808 del5) were discovered in a screening of the entire BRCA2 coding region in 34 samples. However, these mutations were not found in the rest of the 120 patients studied. Patients with positive family history of breast and/or ovarian cancer were often BRCA2 mutation carriers (44%), whereas those with no family history showed a low frequency of involvement (3.6%; P < .0001). Finally, we found only one Finnish MBC patient with 999 del5, the most common founder mutation in Finnish female breast cancer (FBC) patients, and one that explains most of the hereditary FBC and MBC cases in Iceland. The variation in BRCA2 mutation spectrum between Finnish MBC patients and FBC patients in Finland and breast cancer patients in Iceland suggests that modifying genetic and environmental factors may significantly influence the penetrance of MBC and FBC in individuals carrying germline BRCA2 mutations in some populations.

Nonsense-mediated decay microarray analysis identifies mutations of EPHB2 in human prostate cancer.

The identification of tumor-suppressor genes in solid tumors by classical cancer genetics methods is difficult and slow. We combined nonsense-mediated RNA decay microarrays and array-based comparative genomic hybridization for the genome-wide identification of genes with biallelic inactivation involving nonsense mutations and loss of the wild-type allele. This approach enabled us to identify previously unknown mutations in the receptor tyrosine kinase gene EPHB2. The DU 145 prostate cancer cell line, originating from a brain metastasis, carries a truncating mutation of EPHB2 and a deletion of the remaining allele. Additional frameshift, splice site, missense and nonsense mutations are present in clinical prostate cancer samples. Transfection of DU 145 cells, which lack functional EphB2, with wild-type EPHB2 suppresses clonogenic growth. Taken together with studies indicating that EphB2 may have an essential role in cell migration and maintenance of normal tissue architecture, our findings suggest that mutational inactivation of EPHB2 may be important in the progression and metastasis of prostate cancer.

Are data from different gene expression microarray platforms comparable?

Many commercial and custom-made microarray formats are routinely used for large-scale gene expression surveys. Here, we sought to determine the level of concordance between microarray platforms by analyzing breast cancer cell lines with in situ synthesized oligonucleotide arrays (Affymetrix HG-U95v2), commercial cDNA microarrays (Agilent Human 1 cDNA), and custom-made cDNA microarrays from a sequence-validated 13K cDNA library. Gene expression data from the commercial platforms showed good correlations across the experiments (r = 0.78-0.86), whereas the correlations between the custom-made and either of the two commercial platforms were lower (r = 0.62-0.76). Discrepant findings were due to clone errors on the custom-made microarrays, old annotations, or unknown causes. Even within platform, there can be several ways to analyze data that may influence the correlation between platforms. Our results indicate that combining data from different microarray platforms is not straightforward. Variability of the data represents a challenge for developing future diagnostic applications of microarrays.

High-resolution analysis of gene copy number alterations in human prostate cancer using CGH on cDNA microarrays: impact of copy number on gene expression.

Identification of target genes for genetic rearrangements in prostate cancer and the impact of copy number changes on gene expression are currently not well understood. Here, we applied high-resolution comparative genomic hybridization (CGH) on cDNA microarrays for analysis of prostate cancer cell lines. CGH microarrays identified most of the alterations detected by classic chromosomal CGH, as well as a number of previously unreported alterations. Specific recurrent regions of gain (28) and loss (18) were found, and their boundaries defined with sub-megabasepair accuracy. The most common changes included copy number decreases at 13q, and gains at 1q and 5p. Refined mapping identified several sites, such as at 13q (33-44, 49-51, and 74-76 Mbp from the p-telomere), which matched with minimal regions of loss seen in extensive loss of heterozygosity mapping studies of large numbers of tumors. Previously unreported recurrent changes were found at 2p, 2q, 3p, and 17q (losses), and at 3q, 5p, and 6p (gains). Integration of genomic and transcriptomic data revealed the role of individual candidate target genes for genomic alterations as well as a highly significant (P <.0001) overall association between copy number levels and the percentage of differentially expressed genes. Across the genome, the overall impact of copy number on gene expression levels was, to a large extent, attributable to low-level gains and losses of copy number, corresponding to common deletions and gains of often large chromosomal regions.

Prognostic impact of ANX7-GTPase in metastatic and HER2-negative breast cancer patients.

PURPOSE: ANX7-GTPase located on chromosome 10q21 is significantly altered and associated with hormone-refractory metastatic prostate cancers. Therefore, we investigated whether levels of ANX7 correlate with breast cancer progression and survival EXPERIMENTAL DESIGN: A diagnostic tumor tissue microarray containing 525 human breast tissue specimens at different stages of the disease was assayed for ANX7 using immunocytochemical methods with ANX7 monoclonal antibody. A separate prognostic tumor tissue microarray containing 553 human breast tissue specimens annotated with clinicopathological parameters was assayed for ANX7, HER2, estrogen receptor, progesterone receptor, and p53 protein. RESULTS: We report here for the first time that the expression of ANX7-GTPase is significantly enhanced and associated with the presence of metastatic disease (P < 0.0001) in the 525 human breast tissue specimens analyzed. Furthermore, using a separate 553 case retrospective prognostic tumor tissue microarray, we found that increased ANX7 expression is also significantly associated with poor overall patient survival (P < 0.014). This is particularly true when restricted to patients in whom the BRE clinical grade is 2 (P < 0.001) or for whom there is a lack of HER2 expression (P < 0.002). Finally, Cox regression analysis shows that as the expression of ANX7 rises, the probability of survival decreases by more than 10-fold for those patients with HER2-negative tumors. These latter patients represented 66% of the population affected with breast cancer in this study. CONCLUSIONS: High levels of ANX7 in tumor correlate strongly with poor survival of HER2-negative patients and the most aggressive forms of breast cancer. This is the first study to demonstrate that ANX7 antibody has the potential for development into an in vivo diagnostic and therapeutic tool. This simple and reliable immunohistochemical assay may therefore become an important biomarker for metastatic breast cancer diagnosis and management of HER2-negative breast tumor patients.

Generation and analysis of melanoma SAGE libraries: SAGE advice on the melanoma transcriptome.

In this study, we generated three SAGE libraries from melanoma tissues. Using bioinformatics tools usually applied to microarray data, we identified several genes, including novel transcripts, which are preferentially expressed in melanoma. SAGE results converged with previous microarray analysis on the importance of intracellular calcium and G-protein signaling, and the Wnt/Frizzled family. We also examined the expression of CD74, which was specifically, albeit not abundantly, expressed in the melanoma libraries using a melanoma progression tissue microarray, and demonstrate that this protein is expressed by melanoma cells but not by benign melanocytes. Many genes involved in intracellular calcium and G-protein signaling were highly expressed in melanoma, results we had observed earlier from microarray studies (Bittner et al., 2000). One of the genes most highly expressed in our melanoma SAGE libraries was a calcium-regulated gene, calpain 3 (p94). Immunohistochemical analysis demonstrated that calpain 3 moves from the nuclei of non-neoplastic cells to the cytoplasm of malignant cells, suggesting activation of this intracellular proteinase. Our SAGE results and the clinical validation data demonstrate how SAGE profiles can highlight specific links between signaling pathways as well as associations with tumor progression. This may provide insights into new genes that may be useful for the diagnosis and therapy of melanoma.

CHEK2 1100delC is not a risk factor for male breast cancer population.

Genetic risk factors for male breast cancer (MBC) are poorly understood. High penetrance genes such as BRCA1 or BRCA2 account for only a small proportion of the disease. A 1100delC mutation in CHEK2 (previously known as CHK2), a cell-cycle checkpoint kinase, has been implicated in predisposition of Li-Fraumeni syndrome (LFS) and breast cancer in families suggestive of LFS. This 1100delC mutation has also been shown to confer a 2-fold increase of breast cancer risk in women and a 10-fold increase of risk in men. It was estimated to account for 1% of breast cancers in women and as much as 9% of breast cancers in men at the population level based on analysis of breast cancer families without BRCA1 or BRCA2 mutations. We wanted to evaluate the significance of CHEK2 1100delC in predisposition to MBC by assessing its frequency in a population-based material of 114 Finnish MBC patients. Two patients (1.8%) carried the 1100delC mutation. The mutation frequency among MBC cases was similar to that seen in population controls (26/1885, 1.4%). Our results indicate that CHEK2 1100delC variant does not substantially increase the risk of male breast cancer at the population level. We cannot exclude the fact that a small fraction of hereditary, family-positive male breast cancers could be attributable to CHEK2 mutations.

Genome-wide scanning for linkage in Finnish breast cancer families.

Only a proportion of breast cancer families has germline mutations in the BRCA1 or BRCA2 genes, suggesting the presence of additional susceptibility genes. Finding such genes by linkage analysis has turned out to be difficult due to the genetic heterogeneity of the disease, phenocopies and incomplete penetrance of the mutations. Isolated populations may be helpful in reducing the level of genetic heterogeneity and in providing useful starting points for further genetic analyses. Here, we report results from a genome-wide linkage analysis of 14 high-risk breast cancer families from Finland. These families tested negative for BRCA1 and BRCA2 germline mutations and showed no linkage to the 13q21 region, recently proposed as an additional susceptibility locus. Suggestive linkage was seen at marker D2S364 (2q32) with a parametric two-point LOD score of 1.61 (theta=0), and an LOD score of 2.49 in nonparametric analyses. Additional genotyping of a 40 cM chromosomal region surrounding the region of interest yielded a maximum parametric two-point LOD score of 1.80 (theta=0) at D2S2262 and a nonparametric LOD score of 3.11 at an adjacent novel marker 11291M1 in BAC RP11-67G7. A nonparametric multipoint LOD score of 3.20 was seen at 11291M1 under the assumption of dominant inheritance. While not providing proof of linkage considering the small number of families and large number of laboratory and statistical analyses performed, these results warrant further studies of the 2q32 chromosomal region as a candidate breast cancer susceptibility locus. Both linkage and association studies are likely to be useful, particularly in other isolated populations.