Do-it-yourself genetic testing

We developed a computational screen that tests an individual's genome for mutations in the BRCA genes, despite the fact that both are currently protected by patents

Selecting a BRCA risk assessment model for use in a familial cancer clinic

<p>Abstract</p> <p>Background</p> <p>Risk models are used to calculate the likelihood of carrying a <it>BRCA1 </it>or <it>BRCA2 </it>mutation. We evaluated the performances of currently-used risk models among patients from a large familial program using the criteria of high sensitivity, simple data collection and entry and <it>BRCA </it>score reporting.</p> <p>Methods</p> <p>Risk calculations were performed by applying the BRCAPRO, Manchester, Penn II, Myriad II, FHAT, IBIS and BOADICEA models to 200 non-<it>BRCA </it>carriers and 100 <it>BRCA </it>carriers, consecutively tested between August 1995 and March 2006. Areas under the receiver operating characteristic curves (AUCs) were determined and sensitivity and specificity were calculated at the conventional testing thresholds. In addition, subset analyses were performed for low and high risk probands.</p> <p>Results</p> <p>The BRCAPRO, Penn II, Myriad II, FHAT and BOADICEA models all have similar AUCs of approximately 0.75 for <it>BRCA </it>status. The Manchester and IBIS models have lower AUCs (0. and 0.47 respectively). At the conventional testing thresholds, the sensitivities and specificities for a <it>BRCA </it>mutation were, respectively, as follows: BRCAPRO (0.75, 0.62), Manchester (0.58,0.71), Penn II (0.93,0.31), Myriad II (0.71,0.63), FHAT (0.70,0.63), IBIS (0.20,0.74), BOADICEA (0.70, 0.65).</p> <p>Conclusion</p> <p>The Penn II model most closely met the criteria we established and this supports the use of this model for identifying individuals appropriate for genetic testing at our facility. These data are applicable to other familial clinics provided that variations in sample populations are taken into consideration.</p

Efficiency of BRCAPRO and Myriad II mutation probability thresholds versus cancer history criteria alone for BRCA1/2 mutation detection

Considerable differences exist amongst countries in the mutation probability methods and thresholds used to select patients for BRCA1/2 genetic screening. In order to assess the added value of mutation probability methods, we have retrospectively calculated the BRCAPRO and Myriad II probabilities in 306 probands who had previously been selected for DNA-analysis according to criteria based on familial history of cancer. DNA-analysis identified 52 mutations (16.9%) and 11 unclassified variants (UVs, 3.6%). Compared to cancer history, a threshold ≥10% with BRCAPRO or with Myriad II excluded about 40% of the patients from analysis, including four with a mutation and probabilities <10% with both programs. All four probands had a BRCA2 mutation. BRCAPRO and Myriad II showed similar specificity at 10% threshold, overall BRCAPRO was more sensitive than Myriad II for the detection of mutations. Only two of the probands with an UV had probabilities >20% with BRCAPRO and Myriad II. In summary, BRCAPRO and Myriad II are more efficient than cancer history alone to exclude patients without a mutation. BRCAPRO performs better for the detection of BRCA1 mutations than of BRCA2 mutations. The Myriad II scores provided no additional information than the BRCAPRO scores alone for the detection of patients with a mutation. The use of thresholds excluded from analysis the majority of patients carrying an UV

Fcγ Receptor I Alpha Chain (CD64) Expression in Macrophages Is Critical for the Onset of Meningitis by Escherichia coli K1

Neonatal meningitis due to Escherichia coli K1 is a serious illness with unchanged morbidity and mortality rates for the last few decades. The lack of a comprehensive understanding of the mechanisms involved in the development of meningitis contributes to this poor outcome. Here, we demonstrate that depletion of macrophages in newborn mice renders the animals resistant to E. coli K1 induced meningitis. The entry of E. coli K1 into macrophages requires the interaction of outer membrane protein A (OmpA) of E. coli K1 with the alpha chain of Fcγ receptor I (FcγRIa, CD64) for which IgG opsonization is not necessary. Overexpression of full-length but not C-terminal truncated FcγRIa in COS-1 cells permits E. coli K1 to enter the cells. Moreover, OmpA binding to FcγRIa prevents the recruitment of the γ-chain and induces a different pattern of tyrosine phosphorylation of macrophage proteins compared to IgG2a induced phosphorylation. Of note, FcγRIa−/− mice are resistant to E. coli infection due to accelerated clearance of bacteria from circulation, which in turn was the result of increased expression of CR3 on macrophages. Reintroduction of human FcγRIa in mouse FcγRIa−/− macrophages in vitro increased bacterial survival by suppressing the expression of CR3. Adoptive transfer of wild type macrophages into FcγRIa−/− mice restored susceptibility to E. coli infection. Together, these results show that the interaction of FcγRI alpha chain with OmpA plays a key role in the development of neonatal meningitis by E. coli K1

Immunophenotypic predictive profiling of BRCA1-associated breast cancer

The immunophenotypic predictive profile of BRCA1-associated cancers including major predictive markers, i.e., PARP-1, EGFR, c-kit, HER-2, and steroid hormones (ER/PR) that may have therapeutic relevance has not yet been reported in a comprehensive study. Using immunohistochemistry, we examined the expression of these proteins in a large cohort of BRCA1-associated breast cancers. PARP-1 immunoreactivity was found in 81.9%, EGFR in 43.6%, ER/PR in 17.9%, c-kit in 14.7%, and overexpression of HER-2 in 3.6% of cancers. For all markers studied, 8.2% of tumors were negative. Expression of only one predictive marker was found in 29.7% of cancers, and most frequently, it was PARP-1 (20.8%). In 62.1% of tumors, more than one predictive marker was expressed: PARP-1 and EGFR in 30.4%, PARP-1, and hormone receptors in 13.3% and PARP-1 with c-kit in 7.5% of all tumors. Coexpression of two or more other predictive markers was rare. There were significant differences in the median age at diagnosis of BRCA1-associated cancer between patients with ER+ vs. ER− and grades 1–2 vs. grade 3 tumors. These results demonstrate that BRCA1-associated cancers differ with respect to expression of proteins that are regarded as targets for specific therapies and that 92% of patients with BRCA1-associated cancers may benefit from one or several options for specific therapy (in addition to DNA damaging agents, e.g., cisplatin). About 8% of cancers which do not express therapeutic target proteins may not respond to such therapies. Knowledge of the immunophenotypic predictive profile may help with the recruitment of patients for trials of targeted therapies