Ovarian Cancer

Ovarian cancer is the seventh most common type of cancer in women, with 58% of cases occurring in developing countries.

There are 239,000 cases of ovarian cancer diagnosed worldwide each year, and 152,000 deaths annually. In the United States, 22,000 cases of ovarian cancer are diagnosed, with 14,000 deaths each year.

Ovarian cancer is one of the most deadly cancers because it is largely symptomless and rarely diagnosed before it has spread extensively.1 Symptoms may include bloating, pelvic pain, and abdominal swelling, among others, but these symptoms are shared with a number of other conditions.2 Ovarian cancer commonly spreads to the lining of the abdomen, local lymph nodes, lungs, and liver.3

In 2012, there were 239,000 cases of ovarian cancer and 152,000 deaths worldwide. Ovarian cancer is the seventh-most common cancer and the eighth-most common cause of death from cancer in women. Ovarian cancer is more common in the developed world than in the developing world.4 There are approximately 22,000 cases of ovarian cancer annually in the US and approximately 14,000 deaths. The overall five-year survival rate in the United States is 45%.5

The risk of ovarian cancer is increased by factors that increase ovulation and obesity.1,6 The risk is decreased by factors that reduce ovulation.6 About 10% of cases are related to inherited genetic risk, and individuals who inherit mutations in the BRCA1 or BRCA2 genes have about a 50% chance of developing the disease.

95% of ovarian cancers are ovarian carcinomas. There are five main subtypes of ovarian carcinoma. The most common subtype is high-grade serous, which accounts for 70% of ovarian carcinomas. Of the remaining 30% of ovarian carcinomas, approximate one third are unclassified (10% or total), and another third are classified as mucinous. 5% of all ovarian carcinomas are classified as endometrioid, and about 3% are classified as clear cell.7

Most of the risk factors for ovarian cancer are hormonal in nature. Ovarian cancer is associated with increased age, family history of ovarian cancer, abdominal pain or distension postmenopausal bleeding and appetite loss.8 Hereditary forms of ovarian cancer can be caused by mutations in specific genes (most notably BRCA1 and BRCA2, but also in genes for hereditary non-polyposis colorectal cancer (Lynch syndrome). In addition to these hereditary factors, a large number of genetic mutations have been associated with one or more of the sub-types of ovarian cancer. These genes are mostly associated with the regulation of cell division and the cell cycle.

Signs and symptoms of ovarian cancer are frequently absent in early stages and when do appear, they can be easily mistaken for other disorders and may persist for several months or even years before being recognized and diagnosed. Most typical symptoms include bloating, abdominal or pelvic pain or discomfort, difficulty eating, indigestion, heartburn, nausea, early satiety, and possibly urinary symptoms.

The treatment of ovarian cancer usually begins with surgery, will generally include chemotherapy and may include radiation therapy. The specific course of treatment will be based the type of ovarian cancer and the extent to which it has spread. These factors will also weigh heavily on the outcome.

Animal Models of Ovarian Cancer

Pharma Models LLC offers a variety of different models for ovarian cancer. Most frequently used are the sub-cutaneous human tumor xenografts, but the majority of the cell lines used in these models can also be injected intraperitoneally into immune-compromised mice to initiate a more clinically relevant form of the disease.

Subcutaneous Xenograft Models for Human Ovarian Carcinoma

There are several cell lines that are commonly used as subcutaneous xenografts in immunocompromised mice. Several examples of typical growth curves are shown in Figure 1. In this example, three ovarian cancer cell lines were implanted subcutaneously in nude mice and the growth of the resulting tumors followed. In this model, treatment would typically begin at a mean tumor volume of 100 mm3, and continue until the negative control tumors reach a volume of 1500 mm3.

Figure 1

Figure 1: Representative growth curves for three ovarian cancer cell lines in nude mice, beginning at implantation.

Orthotopic/Metastatic Models of Ovarian Cancer

In addition to subcutaneous xenograft models of ovarian cancer, several of the cell lines can also be implanted into the peritoneum of female mice as an orthotopic model of ovarian cancer. Given a typical clinical pattern for ovarian cancer, this model also serves as a model of metastatic ovarian cancer. Pharma Models LLC has luciferase labeled human ovarian cancer cell lines that allow the progression of the tumor to be monitored during the study.

Please contact us for more information on this model.

Figure 2Figure 2: Orthotopic Ovarian Cancer in Nude Mice. Mice were implanted intraperitoneally with 1×106 luciferase expressing ovarian cancer cells. Luciferase expression was evaluated in a Bruker in vivo Xtreme imaging system on Days 7, 10, 14, 17, 21 and 28 post tumor cell implantation. Image shows luminescence overlaid on X-ray.


  1. Rossing, Mary Anne; Wicklund, Kristine G.; Cushing-Haugen, Kara L.; Weiss, Noel S. (2010-01-28). Predictive Value of Symptoms for Early Detection of Ovarian Cancer. J Natl Cancer Inst. 102 (4): 222–9.
  2. Ovarian Epithelial Cancer Treatment (PDQ®). NCI. 2014-05-12. Retrieved 1 July 2014.
  3. Ruddon, RW. Cancer biology (4th ed. ed.). Oxford: Oxford University Press. (2007).
  4. World Cancer Report 2014. World Health Organization. 2014. pp. Chapter 5.12.
  5. SEER Stat Fact Sheets: Ovary Cancer. NCI. Retrieved 18 June 2014.
  6. Ovarian Cancer Prevention (PDQ®). NCI. 2014-06-20. Retrieved 1 July 2014.
  7. Sung PL, Chang YH, Chao KC, Chuang CM. Global distribution pattern of histological subtypes of epithelial ovarian cancer: a database analysis and systematic review. Gynecol Oncol. 2014;133(2):147-54.
  8. Hippisley-Cox, J; Coupland, C (Jan 4, 2011). Identifying women with suspected ovarian cancer in primary care: derivation and validation of algorithm. BMJ 344: d8009.
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