Biomarker Development for Diagnosis, Surveillance, and Prognosis for Adrenocortical Carcinoma (ACC)
Abstract
FY18 PRCRP Section II.A.1. Topic Area – Adrenal Cancer The adrenal glands reside above each kidney and produce a variety of hormones (including steroids such as cortisol) essential for life. Adrenal cancer (adrenocortical carcinoma, [ACC]) is an extraordinarily rare cancer of these glands, but is frequently aggressive and often deadly. In contrast to the rarity of ACC, ~10% of the general population have non-cancerous adrenal nodules (often benign tumors called adrenocortical adenomas, [ACA]) which may be incidentally discovered during routine medical imaging. It is clinically challenging to distinguish ACC from ACA, and requires many patients to undergo numerous radiological scans which may never lead to a definitive diagnosis. If, after this extensive workup, the physician still suspects a patient may have ACC, the patient will likely undergo a major surgical procedure to remove the nodule. Many of these patients will have benign ACA and in retrospect could have avoided surgery at no risk. On the other hand, surgery is the only treatment with the potential to cure often fatal ACC. However, even after surgery, up to 70% of patients with ACC will still relapse, and physicians often cannot predict which patients have a high risk of relapse and which do not. As a result, even patients who will never relapse undergo extensive radiological imaging every few months following surgery. For patients who develop metastatic adrenal cancer, treatments are limited, and <10% of patients with metastases survive 5 years after diagnosis. Tools to enable physicians to identify patients at high risk of relapse early are therefore urgently needed. Taken together, these features highlight significant gaps in the knowledge of optimal strategies for the clinical management of adrenal cancer. Recent studies from our group have uncovered several novel characteristics of ACC. ACC often secrete a unique profile of steroids in the blood that we can detect using high-resolution technology optimized by our team. We have also performed comprehensive molecular studies on ACC and identified that this cancer is not a single, homogenous disease. Instead, there are three types of ACC, each with a unique molecular fingerprint and associated with varying disease aggressiveness. Half of patients with the most aggressive ACC type experience relapse within a year of diagnosis; nearly all patients with this type relapse within 2 years. We have developed a simple test to quickly and accurately molecularly fingerprint ACC (and identify cancers belonging to this aggressive type) using tissue samples obtained from surgery. These tools enable us to use non-invasive techniques to diagnose and measure ACC, eliminating the requirement for extensive radiological scans; furthermore, our simple molecular fingerprint test performed early as the day a patient undergoes surgery can predict which patients are likely to relapse. We now propose to extend our findings to a larger group of patients with ACC, to evaluate the statistical power of our technology in diagnosing, measuring, and fingerprinting ACC, and predicting risk of relapse during routine clinical management. We will also partner with an upcoming clinical trial to determine if we can prevent relapse in patients with the aggressive ACC type when they are treated with chemotherapy shortly after surgery. During this 4-year award period, our studies will generate the robust supportive data required for our technology to be immediately incorporated into clinical management of adrenal cancer, and lead to urgently needed advances in therapies for patients fighting this devastating disease. Section II.A.2 Military Relevance Focus Area(s) – gaps in early detection/diagnosis, prognosis, treatment, and/or survivorship that may impact mission readiness and the health and well-being of military members, Veterans, their beneficiaries, and the general public. Military personnel are or may have been exposed to any number of ha
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 19, 2019
- Source ID
- W81XWH1910530
Entities
People
- Tobias Else
Organizations
- United States Army
- University of Michigan