A Study of Chromosomal Abnormalities as a Predictor of Staging and Prognosis in Patients With Liver Cancer

Overview

Liver cancer is one of the most common malignant tumors worldwide with high morbidity and mortality, and hepatocellular carcinoma (HCC) is the main histological subtype. So far, liver resection is the most effective treatment but the postoperative recurrence rate is high at five years, and the prognosis is difficult to estimate. Microvascular invasion (MVI) and postoperative minimal residual disease (MRD) are crucial prognostic factors for patients undergoing hepatectomy. Although many laboratory and imaging methods have been established to estimate the recurrence risk, their stability and accuracy are still not high. To date, no unified conclusion is achieved. It's eagerly to screen out a batch of individualized staging and prognosis-related biological indicators for early warning and prediction of prognosis, having good stability and high precision. Circulating cell-free DNA (cfDNA) molecular detection technology is an emerging detection technology of tumor gene profiling in recent years, which can be used to predict and monitor tumor recurrence. In this study, by detecting genomic chromosomal abnormalities in plasma and tumor tissues of patients before and after surgery, the investigators hope to construct a preoperative MVI prediction model and a postoperative MRD monitoring model, so as to provide reference for the precise treatment of HCC.

MVI and MRD confirmed by postoperative pathology are important prognostic factors for recurrence after liver resection, but current assessment methods have low sensitivity and specificity. cfDNA refers to the partially degraded endogenous DNA in the circulating blood that is free from the extracellular part of the body. When derived from dead and lysed tumor cells, it is called ctDNA, having a high chromosomal instability and relating to the tumor subtype and process. By low coverage whole genome sequencing, cfDNA and ctDNA in plasma were extracted and sequenced and chromosomal instability analysis is realized through UCAD pipeline. Therefore, the investigators can predict the trend of tumor by detecting cfDNA in patients, indicate MVI and MRD, carry out individualized staging of patients, predict recurrence and prognosis, and verify the prediction efficiency through follow-up, so as to establish corresponding prediction models.