The prognostic value of morphometry in advanced epithelial ovarian cancers

Regulation of signal transduction by spatial parameters: a case in NF-κB oscillation

NF-κB is a transcription factor regulating expression of more than 500 genes, and its dysfunction leads to the autoimmune and inflammatory diseases. In malignant cancer cells, NF-κB is constitutively activated. Thus the elucidation of mechanisms for NF-κB regulation is important for the establishment of therapeutic treatment caused by incorrect NF-κB responses. Cytoplasmic NF-κB translocates to the nucleus by the application of extracellular stimuli such as cytokines. Nuclear NF-κB is known to oscillate with the cycle of 1.5-4.5 h, and it is thought that the oscillation pattern regulates the expression profiles of genes. In this review, first we briefly describe regulation mechanisms of NF-κB. Next, published computational simulations on the oscillation of NF-κB are summarised. There are at least 60 reports on the computational simulation and analysis of NF-κB oscillation. Third, the importance of a 'space' for the regulation of oscillation pattern of NF-κB is discussed, showing altered oscillation pattern by the change in spatial parameters such as diffusion coefficient, nuclear to cytoplasmic volume ratio (N/C ratio), and transport through nuclear membrane. Finally, simulations in a true intracellular space (TiCS), which is an intracellular 3D space reconstructed in a computer with organelles such as nucleus and mitochondria are discussed.

Regulation of nuclear NF-κB oscillation by a diffusion coefficient and its biological implications

The transcription factor NF-κB shuttles between the cytoplasm and the nucleus, and nuclear NF-κB is known to oscillate with a cycle of 1.5-2.5 h following the application of external stimuli. Oscillation pattern of NF-κB is implicated in regulation of the gene expression profile. In a previous report, we found that the oscillation pattern of nuclear NF-κB in a computational 3D spherical cell was regulated by spatial parameters such as nuclear to cytoplasmic volume ratio, nuclear transport, locus of protein synthesis, and diffusion coefficient. Here we report analyses and a biological implication for the regulation of oscillation pattern by diffusion coefficient. Our analyses show that the “reset” of nuclear NF-κB, defined as the return of nuclear NF-κB to the initial level or lower, was crucial for the oscillation; this was confirmed by the flux analysis. In addition, we found that the distant cytoplasmic location from the nucleus acted as a “reservoir” for storing newly synthesized IκBα. When the diffusion coefficient of proteins was large (≥10⁻¹¹ m²/s), a larger amount of IκBα was stored in the “reservoir” with a large flux by diffusion. Subsequently, stored IκBα diffused back to the nucleus, where nuclear NF-κB was “reset” to the initial state. This initiated the next oscillation cycle. When the diffusion coefficient was small (≤10⁻¹³ m²/s), oscillation of nuclear NF-κB was not observed because a smaller amount of IκBα was stored in the “reservoir” and there was incomplete “reset” of nuclear NF-κB. If the diffusion coefficient for IκBα was increased to 10⁻¹¹ m²/s keeping other proteins at 10⁻¹³ m²/s, the oscillation was rescued confirming the “reset” and “reservoir” hypothesis. Finally, we showed altered effective value of diffusion coefficient by diffusion obstacles. Thus, organelle crowding seen in stressed cells possibly changes the oscillation pattern by controlling the effective diffusion coefficient.

Roles of spatial parameters on the oscillation of nuclear NF-κB: computer simulations of a 3D spherical cell

Transcription factor NF-κB resides in the cytoplasm and translocates to the nucleus by application of extracellular stimuli. It is known that the nuclear NF-κB oscillates and different oscillation patterns lead to different gene expression. Nearly forty reports on modeling and simulation of nuclear NF-κB have been published to date. The computational models reported so far are temporal or two-dimensional, and the discussions on spatial parameters have not been involved or limited. Since spatial parameters in cancer cells such as nuclear to cytoplasmic volume (N/C) ratio are different from normal cells, it is important to understand the relationship between oscillation patterns and spatial parameters. Here we report simulations of a 3D computational model for the oscillation of nuclear NF-κB using A-Cell software. First, we found that the default biochemical kinetic constants used in the temporal model cannot replicate the experimentally observed oscillation in the 3D model. Thus, the default parameters should be changed in the 3D model. Second, spatial parameters such as N/C ratio, nuclear transport, diffusion coefficients, and the location of IκB synthesis were found to alter the oscillation pattern. Third, among them, larger N/C ratios resulted in persistent oscillation of nuclear NF-κB, and larger nuclear transport resulted in faster oscillation frequency. Our simulation results suggest that the changes in spatial parameters seen in cancer cells is one possible mechanism for alteration in the oscillation pattern of nuclear NF-κB and lead to the altered gene expression in these cells.

Clinical value of morphometric and DNA flow cytometric variables as independent predictors of survival in epithelial ovarian carcinoma: a 5-year follow-up study

The aim of this follow-up study is to validate the clinical significance of quantitative morphometric and DNA flow cytometric variables as independent prognostic factors of overall survival and progression-free survival in epithelial ovarian carcinoma. Tumor samples were collected from 135 patients with epithelial ovarian carcinoma at 3 hospitals in the Netherlands. Evaluated clinico-pathologic variables were age, histologic subtype, differentiation grade, clinical stage [International Federation of Gynecology and Obstetrics (FIGO)], presence of ascites, serum CA-125, and the completeness of debulking surgery. Morphometry and DNA flow cytometric techniques were assessed on each tumor sample to determine the mitotic activity index (MAI), volume percentage epithelium, mean nuclear area (MNA), standard deviation of MNA (SD MNA), nuclear perimeter (NP), and DNA ploidy. Univariate analysis showed that differentiation grade, FIGO stage, presence of ascites, preoperative CA-125 levels, DNA ploidy, and MAI, NP, and MNA were of significant prognostic value. After multivariate analysis (using forward Cox proportional hazard analysis), only differentiation grade and FIGO stage remained significant. From this study, we can conclude that morphometry and DNA flow cytometry are not independent prognosticators and therefore have no clinical value in predicting prognosis in ovarian carcinoma.

The prognostic value of nuclear morphometric analysis in serous ovarian carcinoma

The objective of this study was to determine whether nuclear morphometric data can predict survival, disease progression, and chemotherapeutic response in ovarian serous carcinoma. Nuclear morphometric parameters were determined from archival hematoxylin and eosin sections of 132 serous tumors. Clinicopathologic and morphometric parameters were evaluated as to their individual and independent prognostic value and prediction of chemotherapy response. Nuclear parameters were found to strongly correlate with extent of disease residuum, tumor grade, and FIGO stage. Univariate analysis revealed stage, grade, preoperative CA125, presence of ascites, extent of disease residuum, standard deviation of nuclear area (SDNA), nuclear perimeter (NP), SDNP, nuclear length (NL), nuclear breadth (NB), orthoferet, and equivalent diameter (ED) to be significant predictors of overall survival (OS) and disease-free survival (DFS). Grade, stage, extent of disease residuum, presence of ascites, SDNA, NP, NL, NB, and orthoferet were found to be significant predictors of chemotherapy response. Multivariate analysis revealed extent of disease residuum (P <or= 0.01) and ED (P = 0.002) to be significant predictors for OS. FIGO stage (P <or= 0.01) and ED (P = 0.039) were significant predictors of DFS. NL (P = 0.041) and extent of residual disease (P = 0.003) were the strongest predictors of chemotherapy response with correct classification rates of 68.8% and 70.3%, respectively. In all stages, nuclear morphometry was easy to perform and highly reproducible. Independent prognostic significance was achieved for OS and DFS analysis. Results also suggest that nuclear morphometry can provide significant information to predict chemotherapy response in platinum-treated serous ovarian cancer.