Biomedical subjects
Publications and source records attributed to Beatrice Susil.
This summary of the findings of investigations of the changing transcriptional profile of human endometrium during the menstrual cycle shows that it is possible to classify the menstrual cycle based on the global gene expression profile, and identifies groups of known and novel genes that may be associated with different biological processes that occur in the endometrium such as implantation and menstruation.
Endometrial cancer is the most common gynaecological malignancy in the developed world. The majority of cases can be divided into two broad categories based on clinico-pathological and molecular characteristics; Type I oestrogen-dependent with endometrioid morphology and Type II non-oestrogen-dependent with serous papillary or clear cell morphology. As has been described for other malignancies, such as colorectal carcinoma, the transition from normal endometrium to carcinoma is thought to involve a stepwise accumulation of alterations in cellular regulatory pathways leading to dysfunctional cell growth. This article reviews the current knowledge of the molecular changes commonly associated with endometrial cancer and presents possible progression models.
Endometrium is a dynamic tissue that undergoes cyclic changes each month, under the overall control of estrogen and progesterone. The aims of this study were to investigate the changing global gene expression profile of human endometrium during the menstrual cycle using microarray technology and to determine the correlation between histopathological evaluation and molecular profile of the samples. Standard two-colour cDNA microarrays were performed on the 43 samples against a common reference, using a 10.5 K cDNA glass slide microarray. The results were validated using real-time PCR. Analysis of expression data was carried out using parametric analysis of variance with Benjamini-Hochberg correction. Hierarchical clustering reveals a strong relationship between histopathology and transcriptional profile of the samples. The study identified 1452 genes that showed significant changes in expression (P< or =0.05) across the menstrual cycle, with 425 genes having changes that are at least 2-fold. The data were also independently analysed by a CSIRO algorithm called GeneRaVE that identified a small subset of genes whose expression profiles could be used to classify nearly all the biopsies into their correct cycle stage. We also identified and validated three genes [(natural cytotoxicity triggering receptor (NCR)3, fucosyl transferase (FUT)4 and Fyn-binding protein (FYB)] that had not been shown to have significant cyclic changes in the human endometrium, previously. We have shown for the first time that endometrial cycle stage prediction is possible based on global gene expression profile.
In 32 patients with stage 1 or 2 cervical cancer, preoperative magnetic resonance imaging (MRI) images were compared with corresponding linear measurements made on fresh histopathology specimens. Their clinical tumor diameters recorded as a part of Federation of International Gynecologists and Obstetricians (FIGO) staging were also correlated with the MRI-derived tumor volumes. The locations of neoplastic lesions within the cervix and uterus were identified accurately by MRI as verified in subsequent histopathology examinations. The examination under anesthesia (EUA) diameter (tumor size) was not related to the MRI-derived tumor diameter. Pathologic tumor diameter correlated well with the corresponding diameter in T2-weighted MRI. Tumor volume as measured by MRI was an accurate representation of the local extent of the disease and can be used as an objective measure of cervical cancer at the primary site. Substituting MRI-derived volume in place of clinical tumor diameter in the FIGO staging system will help refine its prognostic significance in patients with both operable and nonoperable cervical cancer.