Gene expression profiling assigns CHEK2 1100delC breast cancers to the luminal intrinsic subtypes.

CHEK2 1100delC is a moderate-risk cancer susceptibility allele that confers a high breast cancer risk in a polygenic setting. Gene expression profiling of CHEK2 1100delC breast cancers may reveal clues to the nature of the polygenic CHEK2 model and its genes involved. Here, we report global gene expression profiles of a cohort of 155 familial breast cancers, including 26 CHEK2 1100delC mutant tumors. In line with previous work, all CHEK2 1100delC mutant tumors clustered among the hormone receptor-positive breast cancers. In the hormone receptor-positive subset, a 40-gene CHEK2 signature was subsequently defined that significantly associated with CHEK2 1100delC breast cancers. The identification of a CHEK2 gene signature implies an unexpected biological homogeneity among the CHEK2 1100delC breast cancers. In addition, all 26 CHEK2 1100delC tumors classified as luminal intrinsic subtype breast cancers, with 8 luminal A and 18 luminal B tumors. This biological make-up of CHEK2 1100delC breast cancers suggests that a relatively limited number of additional susceptibility alleles are involved in the polygenic CHEK2 model. Identification of these as-yet-unknown susceptibility alleles should be aided by clues from the 40-gene CHEK2 signature.

Development and validation of a fast and automated DNA identification line.

The importance of DNA evidence for gaining investigative leads demands a fast workflow for forensic DNA profiling performed in large volumes. Therefore, we developed software solutions for automated DNA profile analysis, contamination check, major donor inference, DNA database (DDB) comparison and reporting of the conclusions. This represents the Fast DNA IDentification Line (FIDL) and this study describes its development, validation and implementation in criminal casework at the authors' institute. This first implementation regards single donor profiles and major contributors to mixtures. The validation included testing of the software components on their own and examination of the performance of different DDB search strategies. Furthermore, end-to-end testing was performed under three conditions: (1) testing of scenarios that can occur in DNA casework practice, (2) tests using three months of previous casework data, and (3) testing in a casework production environment in parallel to standard casework practices. The same DNA database candidates were retrieved by this automated line as by the manual workflow. The data flow was correct, results were reproducible and robust, results requiring manual analysis were correctly flagged, and reported results were as expected. Overall, we found FIDL valid for use in casework practice in our institute. The results from FIDL are automatically reported within three working days from receiving the trace sample. This includes the time needed for registration of the case, DNA extraction, quantification, polymerase chain reaction and capillary electrophoresis. FIDL itself takes less than two hours from intake of the raw CE data to reporting. Reported conclusions are one of five options: (1) candidate retrieved from DDB, (2) no candidate retrieved from DDB, (3) high evidential value with regards to reference within the case, (4) results require examination of expert, or (5) insufficient amount of DNA obtained to generate a DNA profile. In our current process, the automated report is sent within three working days and a complete report, with confirmation of the FIDL results, and signed by a reporting officer is sent at a later time. The signed report may include additional analyses regarding e.g. minor contributors. The automated report with first case results is quickly available to the police enabling them to act upon the DNA results prior to receiving the full DNA report. This line enables a uniform and efficient manner of handling large numbers of traces and cases and provides high value investigative leads in the early stages of the investigation.

Distinct gene mutation profiles among luminal-type and basal-type breast cancer cell lines.

Breast cancer has for long been recognized as a highly diverse tumor group, but the underlying genetic basis has been elusive. Here, we report an extensive molecular characterization of a collection of 41 human breast cancer cell lines. Protein and gene expression analyses indicated that the collection of breast cancer cell lines has retained most, if not all, molecular characteristics that are typical for clinical breast cancers. Gene mutation analyses identified 146 oncogenic mutations among 27 well-known cancer genes, amounting to an average of 3.6 mutations per cell line. Mutations in genes from the p53, RB and PI3K tumor suppressor pathways were widespread among all breast cancer cell lines. Most important, we have identified two gene mutation profiles that are specifically associated with luminal-type and basal-type breast cancer cell lines. The luminal mutation profile involved E-cadherin and MAP2K4 gene mutations and amplifications of Cyclin D1, ERBB2 and HDM2, whereas the basal mutation profile involved BRCA1, RB1, RAS and BRAF gene mutations and deletions of p16 and p14ARF. These subtype-specific gene mutation profiles constitute a genetic basis for the heterogeneity observed among human breast cancers, providing clues for their underlying biology and providing guidance for targeted pharmacogenetic intervention in breast cancer patients.

DNAxs/DNAStatistX: Development and validation of a software suite for the data management and probabilistic interpretation of DNA profiles.

The data management, interpretation and comparison of sets of DNA profiles can be complex, time-consuming and error-prone when performed manually. This, combined with the growing numbers of genetic markers in forensic identification systems calls for expert systems that can automatically compare genotyping results within (large) sets of DNA profiles and assist in profile interpretation. To that aim, we developed a user-friendly software program or DNA eXpert System that is denoted DNAxs. This software includes features to view, infer and match autosomal short tandem repeat profiles with connectivity to up and downstream software programs. Furthermore, DNAxs has imbedded the 'DNAStatistX' module, a statistical library that contains a probabilistic algorithm to calculate likelihood ratios (LRs). This algorithm is largely based on the source code of the quantitative probabilistic genotyping system EuroForMix [1]. The statistical library, DNAStatistX, supports parallel computing which can be delegated to a computer cluster and enables automated queuing of requested LR calculations. DNAStatistX is written in Java and is accessible separately or via DNAxs. Using true and non-contributors to DNA profiles with up to four contributors, the DNAStatistX accuracy and precision were assessed by comparing the DNAStatistX results to those of EuroForMix. Results were the same up to rare differences that could be attributed to the different optimizers used in both software programs. Implementation of dye specific detection thresholds resulted in larger likelihood values and thus a better explanation of the data used in this study. Furthermore, processing time, robustness of DNAStatistX results and the circumstances under which model validations failed were examined. Finally, guidelines for application of the software are shared as an example. The DNAxs software is future-proof as it applies a modular approach by which novel functionalities can be incorporated.

Phosphatidylinositol-3-OH kinase or RAS pathway mutations in human breast cancer cell lines.

Constitutive activation of the phosphatidylinositol-3-OH kinase (PI3K) and RAS signaling pathways are important events in tumor formation. This is illustrated by the frequent genetic alteration of several key players from these pathways in a wide variety of human cancers. Here, we report a detailed sequence analysis of the PTEN, PIK3CA, KRAS, HRAS, NRAS, and BRAF genes in a collection of 40 human breast cancer cell lines. We identified a surprisingly large proportion of cell lines with mutations in the PI3K or RAS pathways (54% and 25%, respectively), with mutants for each of the six genes. The PIK3CA, KRAS, and BRAF mutation spectra of the breast cancer cell lines were similar to those of colorectal cancers. Unlike in colorectal cancers, however, mutational activation of the PI3K pathway was mutually exclusive with mutational activation of the RAS pathway in all but 1 of 30 mutant breast cancer cell lines (P = 0.001). These results suggest that there is a fine distinction between the signaling activators and downstream effectors of the oncogenic PI3K and RAS pathways in breast epithelium and those in other tissues.

BRCA1 mutation analysis of 41 human breast cancer cell lines reveals three new deleterious mutants.

Germ line mutations of the BRCA1 gene confer a high risk of breast cancer and ovarian cancer to female mutation carriers. The BRCA1 protein is involved in the regulation of DNA repair. How specific tumor-associated mutations affect the molecular function of BRCA1, however, awaits further elucidation. Cell lines that harbor BRCA1 gene mutations are invaluable tools for such functional studies. Up to now, the HCC1937 cell line was the only human breast cancer cell line with an identified BRCA1 mutation. In this study, we identified three other BRCA1 mutants from among 41 human breast cancer cell lines by sequencing of the complete coding sequence of BRCA1. Cell line MDA-MB-436 had the 5396 + 1G>A mutation in the splice donor site of exon 20. Cell line SUM149PT carried the 2288delT mutation and SUM1315MO2 carried the 185delAG mutation. All three mutations were accompanied by loss of the other BRCA1 allele. The 185delAG and 5396 + 1G>A mutations are both classified as pathogenic mutations. In contrast with wild-type cell lines, none of the BRCA1 mutants expressed nuclear BRCA1 proteins as detected with Ab-1 and Ab-2 anti-BRCA1 monoclonal antibodies. These three new human BRCA1 mutant cell lines thus seem to be representative breast cancer models that could aid in further unraveling of the function of BRCA1.

Gene expression profiles associated with treatment response in oligodendrogliomas.

Oligodendrogliomas are a specific subtype of brain tumor of which the majority responds favorably to chemotherapy. In this study, we made use of expression profiling to identify chemosensitive oligodendroglial tumors. Correlation of expression profiles to loss of heterozygosity on 1p and 19q, common chromosomal aberrations associated with response to treatment, identified 376, 64, and 60 differentially expressed probe sets associated with loss of 1p, 19q or 1p, and 19q, respectively. Correlation of expression profiles to the tumors' response to treatment identified 16 differentially expressed probe sets. Because transcripts associated with chemotherapeutic response were identified independent of common chromosomal aberrations, expression profiling may be used as an alternative approach to the tumors' 1p status to identify chemosensitive oligodendroglial tumors. Finally, we correlated expression profiles to survival of the patient after diagnosis and identified 103 differentially expressed probe sets. The observation that many genes are differentially expressed between long and short survivors indicates that the genetic background of the tumor is an important factor in determining the prognosis of the patient. Furthermore, these transcripts can help identify patient subgroups that are associated with favorable prognosis. Our study is the first to correlate gene expression with chromosomal aberrations and clinical performance (response to treatment and survival) in oligodendrogliomas. The differentially expressed transcripts can help identify patient subgroups with good prognosis and those that will benefit from chemotherapeutic treatments.

Self-induced structural switches in RNA.

Many biologically active RNAs show a switch in their secondary structure, which is accompanied by changes in their function. Such changes in secondary structure often require trans-acting factors, e.g. RNA chaperones. However, several biologically active RNAs do not require trans-acting factors for this structural switch, which is therefore indicated here as a "self-induced switch". These self-induced structural switches have several characteristics in common. They all start from a metastable structure, which is maintained for some time allowing or blocking a particular function of the RNA. Hereafter, a structural element becomes available, e.g. during transcription, triggering a rapid transition into a stable conformation, which again is accompanied by either a gain or loss of function. A further common element of this type of switches is the involvement of a branch migration or strand displacement reaction, which lowers the energy barrier of the reaction sufficiently to allow rapid refolding. Here, we review a number of these self-induced switches in RNA secondary structure as proposed for several systems. A general model for this type of switches is presented, showing its importance in the biology of functionally active RNAs.

Higher capillary electrophoresis injection settings as an efficient approach to increase the sensitivity of STR typing.

Evidentiary traces may contain low quantities of DNA, and regularly incomplete short tandem repeat (STR) profiles are obtained. In this study, higher capillary electrophoresis injection settings were used to efficiently improve incomplete STR profiles generated from low-level DNA samples under standard polymerase chain reaction (PCR) conditions. The method involves capillary electrophoresis with higher injection voltage and extended injection time. STR peak heights increased six-fold. Inherent to the analysis of low-level DNA samples, we observed stochastic amplification artifacts, mainly in the form of allele dropout and heterozygous peak imbalance. Increased stutter ratios and allele drop-in were rarely seen. Upon STR typing of 10:1 admixed samples, the profile of the major component did not become overloaded when using higher injection settings as was observed upon elevated cycling. Thereby an improved profile of the minor component was obtained. For low-level DNA casework samples, we adhere to independent replication of the PCR amplification and boosted capillary electrophoresis.

MDM2 SNP309 accelerates familial breast carcinogenesis independently of estrogen signaling.

A single nucleotide polymorphism (SNP309T>G) in the intronic promoter of MDM2 was recently found to accelerate carcinogenesis in early-onset cancer cases. This cancer acceleration presumably was due to increased SP1 binding, resulting in enhanced MDM2 transcriptional activation by estrogens. We evaluated MDM2 SNP309 in 343 familial breast cancer cases with known mutation status for CHEK2 1100delC, BRCA1 and BRCA2. Cancer acceleration was indeed observed in early-onset familial breast cancer cases (diagnosed

Exon expression arrays as a tool to identify new cancer genes.

BACKGROUND: Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10-20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. PRINCIPAL FINDINGS: As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number of candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). CONCLUSIONS: The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes.