Criteria and prognostic models for patients with hepatocellular carcinoma undergoing liver transplantation

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

The alcohol flushing syndrome: A risk factor for cancer

Globally, alcohol consumption is responsible for an estimated 3 million deaths annually and contributes to over 740,000 new cancer cases each year.1 Acetaldehyde, a byproduct of alcohol metabolism, has been designated as first-class carcinogens by the International Agency for Research on Cancer.2 In East Asian countries such as China, Japan and Korea, approximately 36% of the population cannot effectively metabolise alcohol due to an inherited deficiency in the enzyme aldehyde dehydrogenase 2 (ALDH2).3 This deficiency leads to the accumulation of acetaldehyde in the blood, causing alcohol flushing syndrome (AFS), characterised by facial flushing, palpitations and nausea.4 AFS is a predictor of inactive ALDH2 and is associated with a higher risk of cancer development.