Heterogeneity of Ovarian Cancer: Relationships Among Histological Group, Stage of Disease, Tumor Markers, Patient Characteristics, and Survival

Abstract

Epidemiological studies have established associations between various reproductive factors and risk of ovarian cancer; it has also been observed that some of these risk factors are only associated with specific histological subgroups. To investigate the correlation of genetic alterations with these risk factors, we examined a consecutive series of 158 ovarian cancer cases treated at the University of Kentucky (1990-96). Common molecular genetic alterations (LOH on chromosome 17, P53 alterations, K-RAS mutations), histological and clinical characteristics of the disease, demographic patient information and survival were evaluated. These latter data were from the Kentucky Cancer Registry. Univariate analysis showed higher frequencies of chromosome 17 loss and P53 mutations in tumors of advanced stage and grade, and in older and post-menopausal women. Non-mucinous tumors were more likely to be classified as late stage, high-grade cancers, and to have chromosome 17 loss and P53 mutations. Survival analysis indicated that stage was the only independent significant variable. When stage was the outcome variable in multiple logistic regression analysis, histology and chromosome 17 loss were significantly associated with poor survival. This case-case study provides evidence that ovarian cancers of mucinous and non-mucinous histology are significantly different with respect to clinical characteristics, survival and molecular alterations. It also lends support to the hypothesis that ovarian cancer is a heterogeneous disease with distinct etiological factors and clinical outcomes, which may require different approaches to treatment.

Validation of tissue microarray technology in ovarian carcinoma

“…23 Proportions of immunostain expression for the three markers (Ki-67:64% ER:60%, p53:58%) greatly correspond with those described in literature. 5,24,25 The final score for the whole-section analysis represents an average across different tumor areas; if we were to compare that average with the average findings from all six cores in every case, concordance would reach 100%. Validation of ovarian cancer tissue microarray DG Rosen et al Thus, regardless of the complexity of the immunohistochemical pattern in the whole section, we found strong correlations between full sections and 1-mm cores in tissue microarrays.…”

“…4 Staining for p53 and ER was graded as follows: 0, negative (no cells stained); 1, weakly positive (o10% of cells stained); 2, moderately positive (10-50% of cells stained); or 3, strongly positive (4 50% cells stained). 5 Figure 1 …”

Influence of Reproductive Factors on Mortality after Epithelial Ovarian Cancer Diagnosis

“…We considered other potential confounders, including smoking, race, education, body mass index, and family history of breast or ovarian cancer, but none of these altered the HR estimates. We also examined whether the influence of reproductive factors on ovarian cancer survival varied by age at diagnosis, stage of cancer, histologic type, or menopausal status, as previous reports have identified these as independent predictors of ovarian cancer survival (24,(26)(27)(28). We used the log likelihood ratio test of a full model containing the relevant interaction terms and a reduced model without the interaction terms.…”

Mucinous ovarian cancer: A therapeutic review

“…In contrast to HGSOC, mEOC typically demonstrates overexpression of the K-RAS oncogene. Moreover, KRAS mutations are prevalent in 43-46% of mEOC, 30% mucinous CRC and 28% non-mucinous CRC (35)(36)(37).…”

“…96%) [35], this is only limited to < 30% of mEOC cases [36]. However, a recent Australian study using whole genome sequencing of 24 tumours reported a surprisingly high rate of TP53 mutations (52%), again highlighting the heterogeneity of entities that are classified as mEOC [37].…”