The BRCAPRO 5.0 model is a useful tool in genetic counseling and clinical management of male breast cancer cases

No study has evaluated the performance of BRCA1/2 mutations prediction models in male breast cancer (MBC) series. Although rare, MBC deserves attention because male and female breast cancers share many characteristics, including the involvement of genetic predisposition factors such as BRCA1/BRCA2 mutations. Indeed, the occurrence of MBC is a commonly used criterion to select families for BRCA mutation testing. We evaluated the performance and clinical effectiveness of four different predictive models in a population-based series of 102 Italian MBC patients characterized for BRCA1/2 mutations. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for each risk model at the 10% threshold. The area under the ROC (AUC) curves and its corresponding asymptotic 95% CIs were calculated as a measure of the accuracy. In our study, the BRCAPRO version 5.0 had the highest combination of sensitivity, specificity, NPV and PPV for the combined probability and for the discrimination of BRCA2 mutations. In individuals with negative breast–ovarian cancer family history, BRCAPRO 5.0 reached a high discriminatory capacity (AUC=0.92) in predicting BRCA2 mutations and showed values of sensitivity, specificity, NPV and PPV of 0.5, 0.98, 0.97 and 0.67, respectively, for the combined probability. BRCAPRO version 5.0 can be particularly useful in dealing with non-familial MBC, a circumstance that often represents a challenging situation in genetic counseling.     

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories.This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.     

Peptides modulating conformational changes in secreted chaperones: From in silico design to preclinical proof of concept

Blocking conformational changes in biologically active proteins holds therapeutic promise. Inspired by the susceptibility of viral entry to inhibition by synthetic peptides that block the formation of helix–helix interactions in viral envelope proteins, we developed a computational approach for predicting interacting helices. Using this approach, which combines correlated mutations analysis and Fourier transform, we designed peptides that target gp96 and clusterin, 2 secreted chaperones known to shift between inactive and active conformations. In human blood mononuclear cells, the gp96-derived peptide inhibited the production of TNFα, IL-1β, IL-6, and IL-8 induced by endotoxin by >80%. When injected into mice, the peptide reduced circulating levels of endotoxin-induced TNFα, IL-6, and IFNγ by >50%. The clusterin-derived peptide arrested proliferation of several neoplastic cell lines, and significantly enhanced the cytostatic activity of taxol in vitro and in a xenograft model of lung cancer. Also, the predicted mode of action of the active peptides was experimentally verified. Both peptides bound to their parent proteins, and their biological activity was abolished in the presence of the peptides corresponding to the counterpart helices. These data demonstrate a previously uncharacterized method for rational design of protein antagonists.     

Validation of a prediction rule to maximize curative (R0) resection of early-stage pancreatic adenocarcinoma

Background:

The surgeon''s contribution to patients with localized pancreatic adenocarcinoma (PAC) is a margin negative (R0) resection. We hypothesized that a prediction rule based on pre-operative imaging would maximize the R0 resection rate while reducing non-therapeutic intervention.

Methods:

The prediction rule was developed using computed tomography (CT) and endoscopic ultrasound (EUS) data from 65 patients with biopsy-proven PAC who underwent attempted resection. The rule classified patients as low or high risk for non-R0 outcome and was validated in 78 subsequent patients.

Results:

Model variables were: any evidence of vascular involvement on CT; EUS stage and EUS size dichotomized at 2.6 cm. In the validation cohort, 77% underwent resection and 58% achieved R0 status. If only patients in the low-risk group underwent surgery, the prediction rule would have increased the resection rate to 92% and the R0 rate to 73%. The R0 rate was 40% higher in low-risk compared with high-risk patients (P < 0.001). High risk was associated with a 67% rate of non-curative surgery (unresectable disease and metastases).

Conclusion:

The prediction rule identified patients most likely to benefit from resection for PAC using pre-operative CT and EUS findings. Model predictions would have increased the R0 rate and reduced non-therapeutic interventions.     

三种临床评分方法对急性肺栓塞预测价值的比较

目的 以CT肺血管造影(CTPA)为金标准,评价临床普遍应用的三种国外急性肺栓塞评分方法 的预测效能,探讨适用于我国人群的评分方法.方法 连续纳入570例(男321例,女249例,年龄18～75岁,平均55岁)行CTPA检查的临床疑似急性肺栓塞的住院或门诊患者.分别采用Wells、Geneva和改良Geneva评分法评价每例患者,并预测其急件肺栓塞发生的可能性.先由2名中年资影像学医师分别独立盲法评价CTPA,评价结果 不一致时由1名高年资医师决定.应用受试者工作特征曲线分析评价二种评分方法 的预测价值.结果 570例中169例患者确诊为急性肺栓塞.三种临床评分方法 两两一致性榆验结果 显示K值为0.269～0.374,P<0.05;其中Geneva评分和改良Geneva评分的一致度较好.三种评分方法 两两存在正相关关系,Geneva评分和改良Geneva评分之间的相关关系较密切.Wells评分、Geneva评分和改良Geneva评分对评估APE的评估的阳性预测值分别为83.8%、53.3%和61.3%,阴性预测值分别为85.0%、80.6%和80.0%.三者的受试者工作特征曲线下面积分别为:Wells评分0.823,Geneva评分0.677,改良Geneva评分0.661,三者比较,除了Geneva评分和改良Geneva评分相比差异无统计学意义(u=0.352,P>0.05)外,其余两两之间的差异均有统计学意义(u=3.535,4.285,均P<0.01).结论 三种临床评分方法 均可以对急性肺栓塞作出较为准确的预测,但是Wells评分的预测价值最高,比较适合于我国人群.     

Computational Modeling of Kinase Inhibitor Selectivity

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PAMI评分法在急性ST段抬高心肌梗死介入治疗中的临床价值验证与改良

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Patterns of antibodies against latent and lytic antigens of human herpesvirus 8 in an endemic population and patients with Kaposi's sarcoma in Mozambique

The patterns of antibodies against latent and lytic antigens of human herpesvirus 8 (HHV‐8) were assessed using immunofluorescence assays of samples from 155 persons seropositive for HHV‐8 seen at public health centers and 24 patients with Kaposi's sarcoma (KS) from Mozambique. Of the 155 persons without KS, 48 (31%) had antibodies against latent antigens only, 29 (18.7%) had antibodies against lytic antigens only, and 78 (50.3%) had antibodies against both types of antigen. The HHV‐8 antibody titer tended to increase with age until age 40, after which it began to decrease. High titers of antibodies against latent and lytic antigens of HHV‐8 were detected mostly in persons co‐infected with HIV, and these increased titers could have a predictive value. All patients with KS except four patients who were seronegative for HHV‐8 had elevated titers of HHV‐8 antibodies, predominantly against latent antigens. The data suggest the potential for an increase in the development of KS in this endemic area for HHV‐8. J. Med. Virol. 82:1576–1581, 2010. © 2010 Wiley‐Liss, Inc.     

A critical appraisal of prognostic and predictive factors for common lung cancers

The outlook for patients with lung cancer remains poor despite advances in the understanding of the pathology and biology of this disease. To optimize treatment protocols prognostic data are essential. The current era with molecular research on mRNA expression analysis and proteomics will lead to a plethora of new molecular markers, which are likely to be correlated, at least in part, with each other and with disease activity, progression and survival. However, although the number of prognostic factors analysed in published systematic reviews on lung cancer is large, the scope of these factors in individual studies is often narrow. In daily practice prognostic factors other than general TNM staging are not implemented. To assess the efficacy of new prognostic factors for the management of individual patients with non-small cell lung cancer, studies with clinically relevant modelling are required. In this review arguments are provided to use a model combining radiological and histopathological growth rate, histopathological diagnosis and molecular characteristics as markers for metastatic capacity, tumour volume doubling time and expected response to targeted therapy. This may reveal time-related predictive information useful for treatment guidance of the individual patient.