Ovarian Cancer-Challenges and Innovations

Epithelial ovarian cancer (EOC) is the leading cause of gynecologic cancer death in the United States and is the fifth most common cause of US cancer mortality in women. It is estimated that 22,440 women are diagnosed with EOC and 14,080 die from the disease in the United States each year [1]. Using the Surveillance, Epidemiology and End Results 1995-2007 database, stage I,II, III, and IV EOC have 5- year survival rates that are 89%, 70%, 36%, and 17%, respectively while the 10-year survival rates are 84%, 59%, 23%, and 8%, respectively [2]. EOC is most commonly diagnosed in women in their sixth and seventh decades. The median age at diagnosis is 63. Incidence is directly proportional to age and more than 70% of patients have advanced disease at initial presentation [3].

Ovarian cancer is the fifth leading cause of cancer death in American women. The term ‘ovarian cancer’ is loosely used by laymen to refer to ovarian malignancies from all classes of ovarian tumors (sex-cord stromal, germ cell and epithelial). In this chapter, we will discuss specifically the ovarian carcinomas, derived from epithelium, historically thought to be derived from the germinal epithelium but now shown to include fallopian tube epithelium. Ovarian carcinomas constitute a diverse group of neoplasms for which this chapter will discuss: clinical features including symptoms, gross findings, tumor histology with illustrations, immunohistochemical features used in working up the pathologic diagnosis, molecular features, and prognosis.

Dualistic classifications assign tumors arising from one tissue into two broad types based on differences in histology or grade, growth parameters (e.g., hormone dependence or independence), prognosis, or expression of specific markers. Genomic analyses have allowed a more mechanistic expression of dualistic classification, so that tumor types may be founded on functional differences in the genetics of their development. This review considers the dualistic model of ovarian cancer, which is based primarily on whether or not mutations in the TP53 gene appear in the chronology of tumor progression. Type I ovarian cancers generally do not display mutations in the TP53 gene, and, according to several criteria, they have developed in the context of a relatively stable genome. In contrast, Type II ovarian cancers develop mutations in the TP53 gene early in tumorigenesis, and the resulting genome destabilization becomes a primary driver in tumorigenesis. Type I ovarian cancers generally are of lower grade and display a less malignant phenotype than Type II ovarian cancers, despite the better response of Type II ovarian cancers to certain chemotherapeutic regimens. Some reports have shown that mutation of TP53 can occur, albeit rarely late in a putative Type I progression, giving rise to an ovarian cancer with growth and survival properties similar to a Type II cancer. Future work should apply principles of dualistic cancer lineages acquired from ovarian and some other cancers (e.g., sporadic and inflammatory bowel disease-associated colorectal cancer) to produce a unified model applicable to the prognostication and development of therapeutics for all cancers.

High-grade serous carcinoma (HGSC) is the most common epithelial ovarian cancer (EOC) accounting for 60% to 80% of ovarian cancers. Its main molecular alterations are 1) mutation or non-function of TP53, 2) BRCA1 or BRCA2 germline mutations and 3) alterations in the EGFR/HER2 pathway with Her2 overexpression. Despite these well-known genetic alterations, our understanding of gene interactions in canonical pathways remains fairly rudimentary. One approach to better understand gene-biopathway interplay is using in-silico analyses of gene expression microarray databases available in the public data repositories. Minimum information about a microarray experiment (MIAME) guidelines established, as a prerequisite for the publication of microarray data, that data supporting published conclusions are made available for further analyses by other researchers. However, in spite of the availability of large, responsibly generated datasets to the public, secondary analyses are rarely performed. The purpose of this chapter is to show an example of this approach by undertaking an in-silico analysis of Public Gene Expression Omnibus (GEO) datasets comparing the gene expression between HGSC and Fallopian Tube Epithelium (FTE) and between HGSC and Ovarian Surface Epithelium (OSE), to then apply a Functional Genomics approach to study the gene interaction of HGSC in canonical pathways, in-silico activation of these pathways, and how chemotherapeutic drugs potentially affect them. We will explain step by step the methodology and results, including the datasets selection, data filtering and normalization, comparison of the gene expression between the samples using a class comparison analysis, validation by immunohistochemistry (IHC) and Functional Genomics Analysis using Ingenuity Pathway Analysis (IPA).

This chapter explores the psychological aspects of healing from ovarian cancer. Topics discussed include: i) psychological status of the patient - those with psychiatric disorders and those with secondary anxiety or depression arising after the diagnosis of cancer, ii) communication – how much and when to communicate, iii) psychological distress and demoralization, iv) complicating factors including loss of fertility, pain, fatigue and cosmetic concerns, v) caregiver burnout, vi) treatments including: depression, anxiety and talk therapy, vii) end-of-life issues including palliative and hospice care, and aid-in-dying.

This chapter explores the role of belief in healing, beginning with a brief review of western medicine’s changing foundations - initially religious and later scientific. The chapter relates to disease in general and is inclusive of ovarian cancer. Disease in ancient times was attributed to Divine cause; religious leaders served as physicians and belief played a prominent role in healing. Groundbreaking nineteenthand twentieth-century scientific discoveries, which offered physical explanations for disease and fostered the development of companion therapies, diminished appreciation of the importance of belief in the healing process. Beginning around the mid- twentieth century and continuing to this day, scientific studies have investigated treatment outcomes in relation to the beliefs of patients and healers. The power of the placebo and nocebo are discussed, and studies and comments by both conventional and ‘alternative’ modern-day healers illustrate a renewed appreciation of the importance of belief in the healing process.