Prediction of hepatocellular carcinoma (HCC) risk is an urgent unmet need in patients with nonalcoholic fatty liver disease (NAFLD). In cohorts of 409 patients with NAFLD from multiple global regions, we defined and validated hepatic transcriptome and serum secretome signatures predictive of long-term HCC risk in patients with NAFLD. A 133-gene signature, prognostic liver signature (PLS)–NAFLD, predicted incident HCC over up to 15 years of longitudinal observation. High-risk PLS-NAFLD was associated with IDO1 ⁺ dendritic cells and dysfunctional CD8 ⁺ T cells in fibrotic portal tracts along with impaired metabolic regulators. PLS-NAFLD was validated in independent cohorts of patients with NAFLD who were HCC naïve (HCC incidence rates at 15 years were 22.7 and 0% in high- and low-risk patients, respectively) or HCC experienced (de novo HCC recurrence rates at 5 years were 71.8 and 42.9% in high- and low-risk patients, respectively). PLS-NAFLD was bioinformatically translated into a four-protein secretome signature, PLSec-NAFLD, which was validated in an independent cohort of HCC-naïve patients with NAFLD and cirrhosis (HCC incidence rates at 15 years were 37.6 and 0% in high- and low-risk patients, respectively). Combination of PLSec-NAFLD with our previously defined etiology-agnostic PLSec-AFP yielded improved HCC risk stratification. PLS-NAFLD was modified by bariatric surgery, lipophilic statin, and IDO1 inhibitor, suggesting that the signature can be used for drug discovery and as a surrogate end point in HCC chemoprevention clinical trials. Collectively, PLS/PLSec-NAFLD may enable NAFLD-specific HCC risk prediction and facilitate clinical translation of NAFLD-directed HCC chemoprevention.

Liver cancer, primarily HCC, exhibits highly heterogeneous histological and molecular aberrations across tumors and within individual tumor nodules. Such intertumor and intratumor heterogeneities may lead to diversity in the natural history of disease progression and various clinical disparities across the patients. Recently developed multimodality, single-cell, and spatial omics profiling technologies have enabled interrogation of the intertumor/intratumor heterogeneity in the cancer cells and the tumor immune microenvironment. These features may influence the natural history and efficacy of emerging therapies targeting novel molecular and immune pathways, some of which had been deemed undruggable. Thus, comprehensive characterization of the heterogeneities at various levels may facilitate the discovery of biomarkers that enable personalized and rational treatment decisions, and optimize treatment efficacy while minimizing the risk of adverse effects. Such companion biomarkers will also refine HCC treatment algorithms across disease stages for cost-effective patient management by optimizing the allocation of limited medical resources. Despite this promise, the complexity of the intertumor/intratumor heterogeneity and ever-expanding inventory of therapeutic agents and regimens have made clinical evaluation and translation of biomarkers increasingly challenging. To address this issue, novel clinical trial designs have been proposed and incorporated into recent studies. In this review, we discuss the latest findings in the molecular and immune landscape of HCC for their potential and utility as biomarkers, the framework of evaluation and clinical application of predictive/prognostic biomarkers, and ongoing biomarker-guided therapeutic clinical trials. These new developments may revolutionize patient care and substantially impact the still dismal HCC mortality.

A select group of patients with hepatocellular carcinomas (HCC) benefit from surgical, radiologic, and systemic therapies that include a combination of anti-angiogenic and immune-checkpoint inhibitors. However, because HCC is generally asymptomatic in its early stages, this not only leads to late diagnosis, but also to therapy resistance. The nucleoside analogue 6-thio-dG (THIO) is a first-in-class telomerase-mediated telomere-targeting anticancer agent. In telomerase expressing cancer cells, THIO is converted into the corresponding 5′-triphosphate, which is efficiently incorporated into telomeres by telomerase, activating telomere damage responses and apoptotic pathways. Here, we show how THIO is effective in controlling tumor growth and, when combined with immune checkpoint inhibitors, is even more effective in a T-cell-dependent manner. We also show telomere stress induced by THIO increases both innate sensing and adaptive antitumor immunity in HCC. Importantly, the extracellular high-mobility group box 1 protein acts as a prototypical endogenous DAMP (Damage Associated Molecular Pattern) in eliciting adaptive immunity by THIO. These results provide a strong rationale for combining telomere-targeted therapy with immunotherapy.

Prediction of hepatocellular carcinoma (HCC) risk becomes increasingly important with recently emerging HCC-predisposing conditions, namely non-alcoholic fatty liver disease and cured hepatitis C virus infection. These etiologies are accompanied with a relatively low HCC incidence rate (~1% per year or less), while affecting a large patient population. Hepatitis B virus infection remains a major HCC risk factor, but a majority of the patients are now on antiviral therapy, which substantially lowers, but does not eliminate, HCC risk. Thus, it is critically important to identify a small subset of patients who have elevated likelihood of developing HCC, to optimize the allocation of limited HCC screening resources to those who need it most and enable cost-effective early HCC diagnosis to prolong patient survival. To date, numerous clinical-variable-based HCC risk scores have been developed for specific clinical contexts defined by liver disease etiology, severity, and other factors. In parallel, various molecular features have been reported as potential HCC risk biomarkers, utilizing both tissue and body-fluid specimens. Deep-learning-based risk modeling is an emerging strategy. Although none of them has been widely incorporated in clinical care of liver disease patients yet, some have been undergoing the process of validation and clinical development. In this review, these risk scores and biomarker candidates are overviewed, and strategic issues in their validation and clinical translation are discussed.

SET domain containing 5 (SETD5), a chromatin regulator involved in adipocytic differentiation, has been identified in various cancers, but its immunohistochemical expression and prognostic significance in liposarcoma remain unclear. This study examined the immunohistochemical expression and prognostic significance of SETD5 in liposarcomas. SETD5 expression was analyzed in 100 adipocytic tumors using immunohistochemistry; these 100 tumors consisted of 24 dedifferentiated liposarcomas (DDLPS), 24 atypical lipomatous tumors/well differentiated liposarcomas (WDLPS), 12 myxoid liposarcomas, 5 pleomorphic liposarcomas, and 35 benign adipocytic tumors. SETD5 expression was assessed using the immunoreactivity score and its prognostic significance was investigated. SETD5 expression was absent in normal adipose tissue and minimal in lipomas. SETD5 expression was significantly higher in WDLPS than in lipomas ( p = 0.01). Moreover, SETD5 expression was markedly elevated in the dedifferentiated component of DDLPS compared to the well‐differentiated component ( p < 0.001). Pleomorphic liposarcoma showed the highest SETD5 expression levels. In DDLPS, high SETD5 expression in the dedifferentiated component correlated with worse overall survival ( p < 0.001) but was not correlated with disease‐free survival ( p = 0.086). Immunohistochemical expression of SETD5 significantly correlates with prognosis in DDLPS and may serve as a candidate pathological factor for dedifferentiation and prognosis.