Non-invasive diagnosis of endometriosis based on a combined analysis of six plasma biomarkers.

BACKGROUND: Lack of a non-invasive diagnostic test contributes to the long delay between onset of symptoms and diagnosis of endometriosis. The aim of this study was to evaluate the combined performance of six potential plasma biomarkers in the diagnosis of endometriosis. METHODS: This case-control study was conducted in 294 infertile women, consisting of 93 women with a normal pelvis and 201 women with endometriosis. We measured plasma concentrations of interleukin (IL)-6, IL-8, tumour necrosis factor-alpha, high-sensitivity C-reactive protein (hsCRP), and cancer antigens CA-125 and CA-19-9. Analyses were done using the Kruskal-Wallis test, Mann-Whitney test, receiver operator characteristic, stepwise logistic regression and least squares support vector machines (LSSVM). RESULTS: Plasma levels of IL-6, IL-8 and CA-125 were increased in all women with endometriosis and in those with minimal-mild endometriosis, compared with controls. In women with moderate-severe endometriosis, plasma levels of IL-6, IL-8 and CA-125, but also of hsCRP, were significantly higher than in controls. Using stepwise logistic regression, moderate-severe endometriosis was diagnosed with a sensitivity of 100% (specificity 84%) and minimal-mild endometriosis was detected with a sensitivity of 87% (specificity 71%) during the secretory phase. Using LSSVM analysis, minimal-mild endometriosis was diagnosed with a sensitivity of 94% (specificity 61%) during the secretory phase and with a sensitivity of 92% (specificity 63%) during the menstrual phase. CONCLUSIONS: Advanced statistical analysis of a panel of six selected plasma biomarkers on samples obtained during the secretory phase or during menstruation allows the diagnosis of both minimal-mild and moderate-severe endometriosis with high sensitivity and clinically acceptable specificity.

Distinct physiological states of Plasmodium falciparum in malaria-infected patients.

Infection with the malaria parasite Plasmodium falciparum leads to widely different clinical conditions in children, ranging from mild flu-like symptoms to coma and death. Despite the immense medical implications, the genetic and molecular basis of this diversity remains largely unknown. Studies of in vitro gene expression have found few transcriptional differences between different parasite strains. Here we present a large study of in vivo expression profiles of parasites derived directly from blood samples from infected patients. The in vivo expression profiles define three distinct transcriptional states. The biological basis of these states can be interpreted by comparison with an extensive compendium of expression data in the yeast Saccharomyces cerevisiae. The three states in vivo closely resemble, first, active growth based on glycolytic metabolism, second, a starvation response accompanied by metabolism of alternative carbon sources, and third, an environmental stress response. The glycolytic state is highly similar to the known profile of the ring stage in vitro, but the other states have not been observed in vitro. The results reveal a previously unknown physiological diversity in the in vivo biology of the malaria parasite, in particular evidence for a functional mitochondrion in the asexual-stage parasite, and indicate in vivo and in vitro studies to determine how this variation may affect disease manifestations and treatment.

Body mass index and HER-2 overexpression in breast cancer patients over 50 years of age.

PURPOSE: In breast cancer, in vitro as well as in vivo experiments have shown an inverse relationship between HER-2 and steroid hormone receptors. It is unknown whether circulating estrogens affect HER-2 expression. We hypothesize that the postmenopausal body mass index (BMI) as a surrogate marker for bio-available estrogens, is inversely associated with HER-2 over-expression. PATIENTS AND METHODS: A total of 535 women over age 50 or with known postmenopausal status, with a unilateral, not previously treated, operable breast cancer were evaluated the evening prior to surgery for body weight, height, abdominal and hip circumference over a 3 years period. Waist-to-hip ratio (WHR) and BMI were calculated. HER-2, estrogen receptor and progesterone receptor staining was done by immunohistochemistry. All tumours with DAKO 2+ staining were submitted for HER-2 detection by FISH analysis. HER-2 was defined as positive if DAKO 3+ or FISH positive. We assessed the frequency of HER-2 positivity in each of 6 quantiles for all parameters of body composition and tested for a trend in HER-2 expression across the 6 quantiles. Furthermore, we investigated whether BMI contributed, together with other known predictors for HER-2, in a standard multivariate logistic regression model that predicts HER-2 over-expression. RESULTS: There is a decrease in HER-2 over-expression per increasing quantile of BMI. In a multivariate model-including both steroid receptors-BMI remains an independent predictor for HER-2 over-expression. CONCLUSION: In women over age 50 or with known postmenopausal status with an operable breast cancer, there is an inverse association between BMI and HER-2 over-expression.

New models to predict depth of infiltration in endometrial carcinoma based on transvaginal sonography.

OBJECTIVES: Preoperative knowledge of the depth of myometrial infiltration is important in patients with endometrial carcinoma. This study aimed at assessing the value of histopathological parameters obtained from an endometrial biopsy (Pipelle de Cornier; results available preoperatively) and ultrasound measurements obtained after transvaginal sonography with color Doppler imaging in the preoperative prediction of the depth of myometrial invasion, as determined by the final histopathological examination of the hysterectomy specimen (the gold standard). METHODS: We first collected ultrasound and histopathological data from 97 consecutive women with endometrial carcinoma and divided them into two groups according to surgical stage (Stages Ia and Ib vs. Stages Ic and higher). The areas (AUC) under the receiver-operating characteristics curves of the subjective assessment of depth of invasion by an experienced gynecologist and of the individual ultrasound parameters were calculated. Subsequently, we used these variables to train a logistic regression model and least squares support vector machines (LS-SVM) with linear and RBF (radial basis function) kernels. Finally, these models were validated prospectively on data from 76 new patients in order to make a preoperative prediction of the depth of invasion. RESULTS: Of all ultrasound parameters, the ratio of the endometrial and uterine volumes had the largest AUC (78%), while that of the subjective assessment was 79%. The AUCs of the blood flow indices were low (range, 51-64%). Stepwise logistic regression selected the degree of differentiation, the number of fibroids, the endometrial thickness and the volume of the tumor. Compared with the AUC of the subjective assessment (72%), prospective evaluation of the mathematical models resulted in a higher AUC for the LS-SVM model with an RBF kernel (77%), but this difference was not significant. CONCLUSIONS: Single morphological parameters do not improve the predictive power when compared with the subjective assessment of depth of myometrial invasion of endometrial cancer, and blood flow indices do not contribute to the prediction of stage. In this study an LS-SVM model with an RBF kernel gave the best prediction; while this might be more reliable than subjective assessment, confirmation by larger prospective studies is required.

Predicting the clinical behavior of ovarian cancer from gene expression profiles.

We investigated whether prognostic information is reflected in the expression patterns of ovarian carcinoma samples. RNA obtained from seven FIGO stage I without recurrence, seven platin-sensitive advanced-stage (III or IV), and six platin-resistant advanced-stage ovarian tumors was hybridized on a complementary DNA microarray with 21,372 spotted clones. The results revealed that a considerable number of genes exhibit nonaccidental differential expression between the different tumor classes. Principal component analysis reflected the differences between the three tumor classes and their order of transition. Using a leave-one-out approach together with least squares support vector machines, we obtained an estimated classification test accuracy of 100% for the distinction between stage I and advanced-stage disease and 76.92% for the distinction between platin-resistant versus platin-sensitive disease in FIGO stage III/IV. These results indicate that gene expression patterns could be useful in clinical management of ovarian cancer.