Noninvasive, Accurate Diagnosis of Chronic Liver Diseases Using Whole-Transcriptome Profiling of Platelets

Abstract Background: Hepatocellular carcinoma (HCC) is the most serious tumor in the world. It generally undergoes a series of processes from HBV infection, chronic hepatitis, cirrhosis, and HCC from early to late stages. Patients could benefit from early detection of chronic liver diseases (CLD). Tumor-Educated Platelets play an important role in tumor progression, which maybe a potential biomarker for CLD early diagnosis. Here, we developed a noninvasive liquid biopsy technique using platelet RNA for the early screening of patients with liver diseases. Methods: This study included a total of 163 individuals, including 50 healthy individuals, 39 chronic hepatitis B (CHB) patients, 40 liver cirrhosis (LC) and 34 patients with HCC. Blood was collected before initiation of treatment. Platelet RNA-Seq combined with Support Vector Machine (SVM), was used for the first time to distinguish the different stages of CLD in Asian patients. Results: Developed diagnostic model could distinguished with 92.4% accuracy between 34 HCC and 50 healthy, 89.92% accuracy between 34 patients HCC and 129 non-cancer individuals, and 83.67% between 50 healthy and 113 CLD. Across four different individual types, the accuracy of distinction (healthy/chronic hepatitis B/liver cirrhosis/hepatocellular carcinoma) was 65.31%. This model was internally validated, resulting in optimism-corrected AUC's of 86.8%. Conclusions: Our data indicate that the developed platelet RNA-Seq is a valuable platform for the diagnosis of CLD, providing an effective solution for its diagnosis.