Gene Expression Analysis in Ovarian Cancer – Faults and Hints from DNA Microarray Study

The introduction of microarray techniques to cancer research brought great expectations for finding biomarkers that would improve patients’ treatment; however, the results of such studies are poorly reproducible and critical analyses of these methods are rare. In this study, we examined global gene expression in 97 ovarian cancer samples. Also, validation of results by quantitative RT-PCR was performed on 30 additional ovarian cancer samples. We carried out a number of systematic analyses in relation to several defined clinicopathological features. The main goal of our study was to delineate the molecular background of ovarian cancer chemoresistance and find biomarkers suitable for prediction of patients’ prognosis. We found that histological tumor type was the major source of variability in genes expression, except for serous and undifferentiated tumors that showed nearly identical profiles. Analysis of clinical endpoints [tumor response to chemotherapy, overall survival, disease-free survival (DFS)] brought results that were not confirmed by validation either on the same group or on the independent group of patients. CLASP1 was the only gene that was found to be important for DFS in the independent group, whereas in the preceding experiments it showed associations with other clinical endpoints and with BRCA1 gene mutation; thus, it may be worthy of further testing. Our results confirm that histological tumor type may be a strong confounding factor and we conclude that gene expression studies of ovarian carcinomas should be performed on histologically homogeneous groups. Among the reasons of poor reproducibility of statistical results may be the fact that despite relatively large patients’ group, in some analyses one has to compare small and unequal classes of samples. In addition, arbitrarily performed division of samples into classes compared may not always reflect their true biological diversity. And finally, we think that clinical endpoints of the tumor probably depend on subtle changes in many and, possibly, alternative molecular pathways, and such changes may be difficult to demonstrate

Zagrożenia zdrowotne wśród dzieci i młodzieży. T. 3

Praca recenzowana / Peer-reviewed pape

The Clinical and Biochemical Predictors of Bone Mass in Preterm Infants.

Metabolic bone disease of prematurity still occurs in preterm infants, although a significant improvement in neonatal care has been observed in recent decades. Dual-energy X-ray absorptiometry (DXA) is the precise technique for assessing bone mineral content (BMC) in preterm infants, but is not widely available.To investigate the clinical and biochemical parameters, including bone metabolism markers as potential predictors of BMC, in preterm infants up to 3 months corrected age (CA).Ca-P homeostasis, iPTH, 25-hydroxyvitamin D, osteocalcin, N-terminal propeptide, cross-linked C-telopeptide and amino-terminal pro C-type natriuretic peptide and the DXA scans were prospectively performed in 184 preterm infants (≤ 34 weeks' gestation) between term age and 3 mo CA. Lower bone mass was defined as BMC below or equal to respective median value for the whole study group, rounded to the nearest whole number.The appropriate quality DXA scans were available for 160 infants (87%) examined at term and for 130 (71%) tested at 3 mo CA. Higher iPTH level was the only independent predictor of lower BMC at term, whereas lower BMC at 3 mo CA was associated both with lower urinary phosphate excretion and higher serum osteocalcin level. ROC analysis showed that iPTH >43.6 pg/mL provided 40% sensitivity and 88% specificity in identification of preterm infants with lower BMC at term. In turn, urinary phosphate excretion (TRP>97% or UP/Cr ≤0.74 mg/mg) and serum osteocalcin >172 ng/mL provided 40% sensitivity and 93% specificity in identification of infants with decreased BMC at 3 mo CA.Serum iPTH might to be a simple predictor of reduced BMC in preterm infants at term age, but urinary phosphate excretion and serum osteocalcin might predict reduced BMC at 3 mo CA. These results represent a promising diagnostic tool based on simple, widely available biochemical measurements for bone mass assessment in preterm infants