Implantable Nanosensor for Early-Stage Ovarian Cancer Detection
Abstract
Ovarian cancer is the fifth-leading cause of cancer-related deaths among females in the United States and first among gynecologic malignancies, resulting in 22,000 new cases and 14,000 deaths per year. For patients with advanced stages of ovarian cancer, around 70% of the cases relapse, and the 5-year survival rate is 39%. In contrast, if detected early at stage one, survival rates are over 90%. However, only about 20% of diagnosed ovarian cancers are detected at an early stage, and approximately 61% of cases are diagnosed after metastasis to distant sites, reducing survival rate to < 30%. There is currently no diagnostic screening method for early and accurate diagnosis of ovarian cancer, nor are there strategies to rapidly determine the best mode of therapy. The early detection of ovarian cancer in high-risk populations and timely measurements of disease progression and recurrence would markedly increase survival rates. Additionally, women in the military have recently been identified as a high-risk population. It is, therefore, critical to develop effective, sensitive, and robust detection strategies to reduce mortality. Conventionally, serum cancer antigen 125 (CA-125) measurements and ultrasonography have been used to detect ovarian carcinoma. Recent reports found that these methods do not result in early-stage detection and confer little survival benefit. It is now widely accepted that such methods are not justified for use in cancer screening, and the U.S. Preventative Services Task Force recommends against their use. The biomarker human epididymis protein 4 (HE4) is produced by malignant epithelial cells. However, there are significant limitations of blood-based screening. These proteins are produced in the ovaries and fallopian tubes, but they do not reach the blood in detectable levels until advanced disease stages. Thus, detection of these cancer proteins may be enhanced by measurements taken from within the uterine cavity or other locations closer to the ovaries and fallopian tube, where tumors most commonly originate. We believe that conventional/previous approaches involving serum measurements of biomarkers such as CA- 125 may be failing to detect early-stage cancer due to (1) limited specificity, as the majority of abnormal protein levels are the result of other cancers or benign gynecologic conditions and (2) the low levels of biomarkers that migrate from the location of disease to the blood. To address the challenges, we propose to develop a strategy for the detection of multiple ovarian cancer biomarkers transiently and locally, where they are produced at higher levels at earlier disease stages. We believe that long-term detection and enhanced sensitivity, via detection closer to the disease site, will allow early-stage detection of ovarian cancer. The objective of this proposal is to develop an implantable sensor platform that enables continuous/repeated monitoring the levels of a critical ovarian cancer biomarker in the uterine cavity, in high-risk patients. We will develop and test an implantable sensor capable of long-term detection of biomarkers that can continuously measure and relay information non-invasively. This work will result in revolutionary new technological developments of biomarker sensors, including an implantable sensor technology capable of long-term measurements. This technology will be the first to longitudinally detect cancer biomarkers using a minimally-invasive implantable optical sensor, and the first to detect early-stage ovarian cancer. Upon successful completion, the clinical development of the sensor will commence. This technology has the potential to change clinical practice and markedly improve detection of ovarian cancer, and this technology, to measure biomarkers over time, will be useful in the measurement of many other biomarkers and disease indications.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210563
Entities
People
- Daniel A. Heller
Organizations
- Sloan-Kettering Institute
- United States Army