LBA2 Analytical and clinical validation of a ctDNA-based assay for multi-cancer detection

Early cancer detection is essential to achieve better treatment outcomes and reduce mortality. However, most current screening methods test for a single cancer type or some of them are invasive, resulting in a low accessibility rate. To overcome such clinical challenges, we previously developed a multimodal liquid biopsy-based assay named Screening for the Presence of Tumor by Methylation And Size (SPOT-MAS) to detect the five most common types of cancer in Vietnam (liver, breast, colorectal, gastric, and lung cancer). Herein, we launched a large-scale study, named K-DETEK, to assess the feasibility and clinical performance of SPOT-MAS in a multi-center clinical trial setting. A prospective cohort study (ClinicalTrials.gov identifier: NCT05227261) was conducted at 13 major hospitals and one research institute in Vietnam. Our study recruited asymptomatic participants aged 40 years or older and followed up for 6 and 12 months. Analytical sensitivity of our assay was assessed by using our healthy and cancer-standard samples with known tumor fraction. The clinical performance was assessed by computing the positive predictive value (PPV), the negative predictive value (NPV) and accuracy in detecting tumor tissue-of-origin (TOO). We established a clinical limit of detection (LOD) value of 0.038 (95% CI:0.035-0.042) and did not observe any noticeable impact of potential inferences (hemolysis rate, genomic DNA) on our assay performance. Furthermore, our analysis of 9,024 eligible participants demonstrated its ability to detect cancers in asymptomatic individuals with a PPV of 57.14%, a NPV of 99.92% and an accuracy of 80.00% in detecting tumor location. Our study provides analytical and clinical evidence to support SPOT-MAS as a multi-cancer blood test for early detection in a low- and middle-income country, especially in Vietnam, where a nationwide cancer screening program is urgently needed but currently not available. Beyond detecting cancer signals, our test predicted the tumor location, allowing clinicians to fast-track the follow-up diagnostic and guide any necessary treatment.