Abstract 6088: Predicting the risk of any-type cancer in asymptomatic adults using noninvasive glycosaminoglycan profiling
Authors: Gatto Francesco 
Published: March 2024

Background: Early detection of cancers through screening can reduce mortality. However, screening excludes individuals not considered at an increased risk of developing cancer, as determined by age, sex, or tobacco use. No molecular biomarker is routinely used to predict risk. Here, we investigated urine glycosaminoglycan profiles (GAGomes) as noninvasive biomarkers for any-cancer risk prediction.

Methods: In this population-based case-control study, we included adults aged over 18 years from the Lifelines Cohort Study, Netherlands who were presumed healthy at baseline. All cases who self-reported any-type cancer or died by the 5-year study visit were confirmed in the Dutch Cancer Registry and matched 1:3 to randomly selected controls (1:1 for the interim analysis). We first developed a logistic regression reference model, including age, sex, and clinical variables to predict any-type cancer. Next, we added urine GAGomes (as a single aggregate score) to the model and assessed model improvement using the likelihood ratio test. We categorized the output of the saturated model (clinical variables plus urine GAGome score) into four groups based on bespoke specificity cut-offs: low-, moderate-, intermediate-, and high-risk. We estimated odds-ratios (ORs) for their association with any-type cancer compared to the moderate-risk group, as well as their sensitivity across subsets. Using the so-estimated OR in the high-risk group, we calculated the minimum pre-test 5-year absolute risk needed to reclassify an adult into a post-test 5-year absolute risk &gt;3.00%.

Results: In the interim analysis, we included 2054 adults (median age = 51 years, 57% females). Of them, 924 were diagnosed with any-type cancer over a 6 year-follow-up period (median time to diagnosis = 1.4 years). Urine GAGomes were found to be independent risk factors when added to the reference model, explaining 27% of the variance (Nagelkerke R2 = 0.26 vs. 0.21, p &lt; 0.0001). The ORs in the low-, intermediate-, and high-risk groups were 0.05 (95% CI: 0.02-0.13 p &lt; 0.0001), 5.31 (95% CI: 3.84-7.48, p &lt; 0.0001) and 27.6 (95% CI: 14.3 - 51.6, p &lt; 0.0001), respectively. The high-risk group detected +80% more cancers than the reference model at the same specificity (99.29%), particularly in situ and stage I (+204% and +64%) and among those aged 50-69 (+247%). Adults with a pre-test 5-year absolute risk &gt; 0.25% returning a high-risk group would be reclassified to a post-test 5-year absolute risk &gt; 3.00% for any-type cancer.

Conclusion: Implementing urine GAGomes as a strategy for risk-stratified targeted screening could identify adults with increased risk of any-type cancer who are currently excluded from screening.

Citation Format: Francesco Gatto. Predicting the risk of any-type cancer in asymptomatic adults using noninvasive glycosaminoglycan profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6088.