Ovarian Cancer

Collaborators:  Daniel Cramer, M.D., Sc.D. (BWH), Steven Skates, Ph.D.(MGH), Martin McIntosh, Ph.D. (Fred Hutchinson Cancer Research Center), and Rosanne Kho, M.D. (Mayo Clinic) and Garrick Wallstrom, Ph.D.

Disease Background

Who gets it?
What are the symptoms?
How do we detect it now?
How is it currently treated?
What are the current challenges?
  • Ovarian cancer is the 5th leading cause of cancer-related death in women.
  • Symptoms can include abdominal pressure, pelvic discomfort, persistent lack of energy, and lower back pain.
  • Cancer can begin in the cells on the outside of the ovaries, in egg-producing cells, or in the hormone producing cells
  • Most women are diagnosed with advanced disease, which has a poor prognosis.
  • When it is caught early, patients have a very high survival rate.
  • Detection of ovarian cancer is difficult: recent genomics data suggests that there are up to 17 years from the start of cancer development till the diagnosis.
  • Tissue biopsies, ultrasounds, and pelvic examinations are currently used in clinics to detect the cancer with varying degrees of success and specificity.
  • The available biomarkers for use in the detection of ovarian cancer fail to detect the disease early enough.
  • Current treatments include either or a combination of surgery and/or chemotherapy.
  • Current clinical methods of the early detection of ovarian cancer are extremely limited in specificity and sensitivity.
  • p53 is a tumor suppressor protein that acts like a brake preventing cancer
  • When a mutation occurs in p53 it fails to stop cancer, like cutting a brake line.
  • A large percentage of ovarian tumors harbor some kind of p53 mutation
  • If we can target this mutant gene, we may be able to detect these deadly diseases much early than current methods.


Our Approach

Ovarian CancerThe immune system creates antibodies to both foreign and self proteins, and by developing a way to detect antibodies that target mutant p53 proteins, we may be able to detect ovarian cancer early using patients’ blood. Using NAPPA, we print the most common p53 specific mutant proteins on these slides. If antibodies are made that can bind to mutant p53, our slides may detect them. By comparing healthy to benign patients, we can detect biomarkers that are only in cancerous patients. If detected early enough, these biomarkers may lead to better patient prognosis, or help to distinguish different stages or forms of cancer, which may lead to better personalized treatment.

Figure (from Anderson et al 2010): p53 autoantibodies are highly specific biomarkers in serous ovarian cancer. A, sera derived from 30 ovarian cancer patients and 30 age-matched healthy women were tested for p53-specific antibodies by RAPID ELISA. Dotted line, the cutoff value (columns, mean signal of the controls; bars, SD; 13.1 × 106). B, distribution of p53 autoantibodies in serous cases and controls. The signal intensity for serous cases (n= 60) and all controls (n = 120) are shown as a percentage of the total sera. The distribution of p53-AAb signal intensity for controls (open columns) is a unimodal distribution and the cases show a bimodal distribution (filled columns).




Anderson KS, Wong J, Vitonis A, Crum CP, Sluss PM, Labaer J, Cramer D. (2010) P53 Autoantibodies As Potential Detection And Prognostic Biomarkers In Serous Ovarian Cancer. Cancer Epidemiology, Biomarkers, and Prevention Mar;19(3):859-68. PMID: 20200435

Siufi Neto J, Kho RM, Siufi DF, Baracat EC, Anderson KS, Abrão MS. (2014) Cellular, histologic, and molecular changes associated with endometriosis and ovarian cancer. J Minim Invasive Gynecol. Jan-Feb; 21(1): 55-63. Epub 2013 Aug 17. PMID: 23962574