Anna Lokshin

PhD

UPMC Hillman Cancer Center

Professor

PLCO (Learn more about this study)

2020-1020

Dec 22, 2020

Development of improved pre-diagnostic biomarker-based screening algorithms for ovarian cancer

Ovarian cancer (OC) is the most lethal of all gynecological cancer affecting over 24,000 women every year with approximately 14,000 deaths each year. The 5-year survival rate for patients with clinically advanced OC is only 15–20%, although the cure rate for stages I-IIB disease is approximately 80%. However, currently, there is no screening modality allowing detection of OC in early stages. A first-line biomarker-based screening test must achieve a specificity of 98%, to avoid a high burden of false positive diagnoses. Molecular and mathematical modeling of progression of the most aggressive type of OC, high-grade serous carcinoma (HGSC), indicated that to be able to catch HGSC in its earlier stages with better response surgical or therapeutic treatment, biomarkers should be able to detect the disease 0.5-6 years earlier than current symptoms-based diagnosis (Years To Diagnosis, YTD). Unfortunately, based on our published study, the sensitivity (SN) of CA125 in these pre-diagnostic samples is very low varying from 10% in samples collected 0.5-1.5 YTD to 3% in samples collected 1.5-7 YTD. The same study has reported that the SN of another strong OC biomarker, HE4, is 20% is samples collected 0.5-1.5 YTD and is 10% in samples collected 1.5-7 YTD. Therefore, discovery of new biomarkers with high sensitivity in pre-diagnostic samples is warranted.
We have interrogated the pre-diagnostic PLCO samples with assays for several promising candidate biomarkers and have developed two multimarker algorithms. The first algorithm was comprised of FSH/HE4/TTR/ADAMTS13 and offered 71%SN at 95%SP in HGSC samples collected 0.5-1.5 YTD. The second algorithm consisted of HE4/FBG/PF4/APOA1 with 62%SN at 95%SP for OC samples collected 18-84 MTD. Both multimarker algorithms offered clear advantage to CA125 and HE4. However, the SN needs to be further improved.
We have demonstrated that tumor-associated auto-autoantibodies (AAb) against TRIM21, NYESO1, and TP53 can predict recurrence in platinum-sensitive OC patients before CA125 rise. We have additionally developed a unique methodology for analysis of circulating AAbs with high analytical SN.
Our goal is to improve SN of our two multimarker algorithms for both 0.5-1.5 and 1.5-7 YTD intervals. We hypothesize that combining our multimarker algorithms with AAbs and covariate data collected by PLCO in pre-diagnostic PLCO samples could improve the SN by 5-10% making them clinically useful for OC screening.
We utilize a Curiox modification of Luminex method that allows to use 5-fold less sample volume. In our case, analysis of FSH, HE4, FBG, PF4, TTR, APOA1, ADAMTS13, and AAbs in a multiplex format will require <25 microL of serum for all biomarkers.