Maria Savino

MYH9-related disease: May-Hegglin anomaly, Sebastian syndrome, Fechtner syndrome, and Epstein syndrome are not distinct entities but represent a variable expression of a single illness

May-Hegglin anomaly, Sebastian syndrome, Fechtner syndrome, and Epstein syndrome are autosomal dominant macrothrombocytopenias distinguished by different combinations of clinical and laboratory signs, such as sensorineural hearing loss, cataract, nephritis, and polymorphonuclear Döhle-like bodies. Mutations in the MYH9 gene encoding for the nonmuscle myosin heavy chain IIA (NMMHC-IIA) have been identified in all these syndromes. To understand the role of the MYH9 mutations, we report the molecular defects in 12 new cases, which together with our previous works represent a cohort of 19 families. Since no genotype-phenotype correlation was established, we performed an accurate clinical and biochemical re-evaluation of patients. In addition to macrothrombocytopenia, an abnormal distribution of NMMHC-IIA within leukocytes was observed in all individuals, including those without Döhle-like bodies. Selective, high-tone hearing deficiency and cataract was diagnosed in 83% and 23%, respectively, of patients initially referred as having May-Hegglin anomaly or Sebastian syndrome. Kidney abnormalities, such as hematuria and proteinuria, affected not only patients referred as Fechtner syndrome and Epstein syndrome but also those referred as May-Hegglin anomaly and Sebastian syndrome. These findings allowed us to conclude that May-Hegglin anomaly, Sebastian syndrome, Fechtner syndrome, and Epstein syndrome are not distinct entities but rather a single disorder with a continuous clinical spectrum varying from mild macrothrombocytopenia with leukocyte inclusions to a severe form complicated by hearing loss, cataracts, and renal failure. For this new nosologic entity, we propose the term “MHY9-related disease,” which better interprets the recent knowledge in this field and identifies all patients at risk of developing renal, hearing, or visual defects.

Spontaneous functional correction of homozygous Fanconi anaemia alleles reveals novel mechanistic basis for reverse mosaicism

Somatic mosaicism due to reversion of a pathogenic allele to wild type has been described in several autosomal recessive disorders. The best known mechanism involves intragenic mitotic recombination or gene conversion in compound heterozygous patients, whereby one allele serves to restore the wild-type sequence in the other. Here we document for the first time functional correction of a pathogenic microdeletion, microinsertion and missense mutation in homozygous Fanconi anaemia (FA) patients resulting from compensatory secondary sequence alterations in cis. The frameshift mutation 1615delG in FANCA was compensated by two additional single base-pair deletions (1637delA and 1641delT); another FANCA frameshift mutation, 3559insG, was compensated by 3580insCGCTG; and a missense mutation in FANCC (1749T→G, Leu496Arg) was altered by 1748C→T, creating a cysteine codon. Although in all three cases the predicted proteins were different from wild type, their cDNAs complemented the characteristic hypersensitivity of FA cells to crosslinking agents, thus establishing a functional correction to wild type.

Heterogeneous spectrum of mutations in the Fanconi anaemia group A gene

Fanconi anaemia (FA) is a genetically heterogeneous autosomal recessive disorder associated with chromosomal fragility, bone-marrow failure, congenital abnormalities and cancer. The gene for complementation group A (FAA), which accounts for 60–65% of all cases, has been cloned, and is composed of an open reading frame of 4.3xa0kb, which is distributed among 43 exons. We have investigated the molecular pathology of FA by screening the FAA gene for mutations in a panel of 90 patients identified by the European FA research group, EUFAR. A highly heterogeneous spectrum of mutations was identified, with 31 different mutations being detected in 34 patients. The mutations were scattered throughout the gene, and most are likely to result in the absence of the FAA protein. A surprisingly high frequency of intragenic deletions was detected, which removed between 1 and 30 exons from the gene. Most microdeletions and insertions occurred at homopolymeric tracts or direct repeats within the coding sequence. These features have not been observed in the other FA gene which has been cloned to date (FAC) and may be indicative of a higher mutation rate in FAA. This would explain why FA group A is much more common than the other complementation groups. The heterogeneity of the mutation spectrum and the frequency of intragenic deletions present a considerable challenge for the molecular diagnosis of FA. A scan of the entire coding sequence of the FAA gene may be required to detect the causative mutations, and scanning protocols will have to include methods which will detect the deletions in compound heterozygotes.

On the statistical assessment of classifiers using DNA microarray data.

BackgroundIn this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia – Italy. The data set is made up of normal (22) and tumor (25) specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data.ResultsWe estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA) classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045) as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS) and Support Vector Machines (SVM) classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035) and e = 18% (p = 0.037) respectively. Moreover, the error rate decreases as the training set size increases, reaching its best performances with 35 training examples. In this case, RLS and SVM have error rates of e = 14% (p = 0.027) and e = 11% (p = 0.019). Concerning the number of genes, we found about 6000 genes (p < 0.05) correlated with the pathology, resulting from the signal-to-noise statistic. Moreover the performances of RLS and SVM classifiers do not change when 74% of genes is used. They progressively reduce up to e = 16% (p < 0.05) when only 2 genes are employed. The biological relevance of a set of genes determined by our statistical analysis and the major roles they play in colorectal tumorigenesis is discussed.ConclusionsThe method proposed provides statistically significant answers to precise questions relevant for the diagnosis and prognosis of cancer. We found that, with as few as 15 examples, it is possible to train statistically significant classifiers for colon cancer diagnosis. As for the definition of the number of genes sufficient for a reliable classification of colon cancer, our results suggest that it depends on the accuracy required.

Mutations of the Fanconi anemia group A gene (FAA) in Italian patients.

Fanconi anemia (FA) is an autosomal recessive disease characterized by progressive pancytopenia, congenital malformations, and predisposition to acute myeloid leukemia. At least five complementation groups (FA-A-FA-E) have been identified. The relative prevalence of FA-A has been estimated at an average of approximately 65% but may widely vary according to ethnic background. In Italy, 11 of 12 patients analyzed by cell-fusion studies were assigned to group FA-A, suggesting an unusually high relative prevalence of this FA subtype in patients of Italian ancestry. We have screened the 43 exons of the FAA gene and their flanking intronic sequences in 38 Italian FA patients, using RNA-SSCP. Ten different mutations were detected: three nonsense and one missense substitutions, four putative splice mutations, an insertion, and a duplication. Most of the mutations are expected to cause a premature termination of the FAA protein at various sites throughout the molecule. Four protein variants were also found, three of which were polymorphisms. The missense mutation D1359Y, not found in chromosomes from healthy unrelated individuals, was responsible for a local alteration of hydrophobicity in the FAA protein, and it was likely to be pathogenic. Thus, the mutations so far encountered in the FAA gene are essentially all different. Since screening based on the analysis of single exons by genomic DNA amplification apparently detects only a minority of the mutations, methods designed to detect alterations in the genomic structure of the gene or in the FAA polypeptide may be helpful in the identification of FAA mutations.

Epstein syndrome: another renal disorder with mutations in the nonmuscle myosin heavy chain 9 gene

Abstract. Epstein syndrome (EPTS) is an autosomal dominant disease characterized by nephritis, mild hearing loss, and thrombocytopenia with giant platelets. Renal and hearing abnormalities are indistinguishable from those observed in Fechtner syndrome (FTNS), an Alport-like variant. EPTS macrothrombocytopenia is similar to that described in FTNS, May-Hegglin anomaly (MHA), and Sebastian syndrome (SBS), three disorders caused by mutations in the nonmuscle heavy chain myosin IIA (MYH9). Unlike FTNS, MHA, and SBS, EPTS does not show inclusion bodies in the leukocytes. The clinical features of EPTS and the chromosomal localization of the respective gene in the same region as MYH9 suggest that this disorder is allelic with the other giant platelet disorders. We identified a MYH9 missense mutation in two EPTS familial cases. In both families, an R702H substitution was found, probably inducing conformational changes to the myosin head. A different amino acid substitution at the same codon (R702C) has been previously identified in FTNS. On the basis of predictions from molecular modeling of the X-ray crystallographic structure of chick smooth muscle myosin, the mutated thiol reactive group of R702C may lead to intermolecular disulfide bridges, with the consequent formation of the inclusions typical of FTNS. On the contrary, the R702H mutation does not allow the protein to aggregate and thus to generate Döhle-like bodies, which are indeed absent in EPTS. In conclusion, our results extend the allelic heterogeneity of MYH9 mutations to another clinical syndrome and contribute to the clarification of the pathogenesis of the various inherited giant platelet disorders.

Mutational screening of thrombopoietin receptor gene (c-mpl) in patients with congenital thrombocytopenia and absent radii (TAR)

Thrombocytopenia with absent radii (TAR) is a rare autosomal recessive disease characterized by hypomegakaryocytic thrombocytopenia and bilateral radial aplasia. We performed mutational screening of coding and promoter regions of the c‐mpl gene, encoding thrombopoietin (TPO) receptor, by sequence analysis in four unrelated patients affected by TAR syndrome. Our results indicate that c‐mpl gene mutations are not a common cause of thrombocytopenia in TAR syndrome.

Comparison between real-time quantitative PCR detection of HER2 mRNA copy number in peripheral blood and ELISA of serum HER2 protein for determining HER2 status in breast cancer patients

Background: The development of non-invasive procedure to determine HER2 status may represent a powerful method for monitoring disease progression and response to the treatment. Methods: Serum samples and RNA from peripheral blood were evaluated in 85 breast cancer patients (49 HER2 positive and 36 HER2 negative) and 22 healthy controls. HER2 mRNA levels were measured by real-time quantitative PCR (QPCR) and serum HER2 protein by immunoenzimatic assay (EIA). ROC curve analyses were used to determine the optimal cut off values. Results: A statistically significant difference was detected for both QPCR and EIA in HER2 positive patients as compared with both healthy controls and HER2 negative tumours. QPCR showed a 91% (CI95%: 84%–98%) specificity and a 78% (CI95%: 68%–88%) sensitivity for an optimal cut off value of 4.74. The optimal cut off value for EIA was 22 ng/ml yielding a 95% (CI95%: 90%–100%) specificity and a 59% (CI95%: 48%–70%) sensitivity. The QPCR assay was slightly less specific than EIA in discriminating HER2 positive breast cancers from HER2 negative tumours (78% CI95%: 69%–87% versus 86% CI95%: 79%–93%), but it was more sensitive (76% CI95%: 67%–85% versus 55% CI95%: 44%–66%). Conclusions: Our results indicate that QPCR performs better than EIA in the determination of HER2 status of breast cancer patients and could be useful in monitoring the disease during follow up.

Role of CYP2D6 Polymorphisms in the Outcome of Postoperative Pain Treatment.

OBJECTIVEnTo investigate the role of CYP2D6 phenotype in the outcome of postoperative (PO) pain (POP) treatment.nnnDESIGNnLongitudinal cohort study. Open-label trial with post hoc analysis.nnnSETTINGnGeneral Hospital Surgery and Recovery Units.nnnPATIENTSnNinety unrelated Caucasians submitted to abdominal/thoracic surgery.nnnINTERVENTIONSnStandard multimodal POP treatment including opioids (tramadol) and nonsteroidal anti-inflammatory drugs (ketoprofen) at different dosages and infusion rates according to the predicted mild, moderate, or severe POP.nnnOUTCOME MEASURESnPain (Numeric Rating Scale-NRS) and sedation (Ramsay Sedation Scale-RSS) up to 24 hours after surgery. By genotyping 16 CYP2D6 alleles, the four CYP2D6 phenotypes poor metabolizer (PM), intermediate metabolizers (IM), extensive metabolizers (EM) and ultrarapid metabolizers (UM) were predicted.nnnRESULTSnAs compared with the CYP2D6-EM phenotype, in the early PO time (30 min) a higher RSS mean score in IM was observed (Pu2009=u20090.035). A suggestion towards higher mean score in PM (Pu2009=u20090.091) and a minor mean score in UM (Pu2009=u20090.091) was also detected. No difference in the outcome of pain across the CYP2D6 phenotypes was observed.nnnCONCLUSIONSnIn respect to the normal CYP2D6 phenotype, our results suggested that slowly metabolizers (IMs and PMs) might have a major sedation, whereas more rapid metabolizers (UM) a minor sedation, in the early time after surgery. A minor role of CYP2D6 phenotype in PO analgesia may be suggested.

Linkage analysis of Fanconi anaemia in Italy and mapping of the complementation group A gene.

Abstract Fanconi anaemia (FA) is an autosomal recessive disease characterised by genetic heterogeneity, with at least five complementation groups (FA-A to FA-E). The FAC gene has been cloned and localised to 9q22.3. The most frequent defective gene, FAA, was recently mapped to chromosome 16q24.3, in a region of 10 cM between D16S498 and the telomere. Eleven FA-A and 16 unclassified Italian families were analysed by microsatellite markers. To define the localisation of the FAA locus further, microsatellites were analysed at 16q24. All the families were consistent with linkage, the highest lod score being observed with D16S1320. Evidence for common haplotypes was obtained in two genetic isolates from the Brenta basin and the Naples region. Autozygosity mapping and haplotype analysis suggest that the FAA locus is distal to D16S305.