Under normal conditions, insulin promotes hepatic de novo lipogenesis (DNL). However, during insulin resistance (IR), when insulin signalling is blunted and accompanied by hyperinsulinaemia, the promotion of hepatic DNL continues unabated and hepatic steatosis increases. Here, we show that WD40 repeat-containing protein 6 (WDR6) promotes hepatic DNL during IR. Mechanistically, WDR6 interacts with the beta-type catalytic subunit of serine/threonine-protein phosphatase 1 (PPP1CB) to facilitate PPP1CB dephosphorylation at Thr316, which subsequently enhances fatty acid synthases transcription through DNA-dependent protein kinase and upstream stimulatory factor 1. Using molecular dynamics simulation analysis, we find a small natural compound, XLIX, that inhibits the interaction of WDR6 with PPP1CB, thus reducing DNL in IR states. Together, these results reveal WDR6 as a promising target for the treatment of hepatic steatosis.

Background: Proliferative hepatocellular carcinomas (HCCs) is a class of aggressive tumors with poor prognosis. We aimed to construct a computed tomography (CT)-based radiomics nomogram to predict proliferative HCC, stratify clinical outcomes and explore the tumor microenvironment. Methods: Patients with pathologically diagnosed HCC following a hepatectomy were retrospectively collected from two medical centers. A CT-based radiomics nomogram incorporating radiomics model and clinicoradiological features to predict proliferative HCC was constructed using the training cohort (n = 184), and validated using an internal test cohort (n = 80) and an external test cohort (n = 89). The predictive performance of the nomogram for clinical outcomes was evaluated for HCC patients who underwent surgery (n = 201) or received transarterial chemoembolization (TACE, n = 104). RNA sequencing data and histological tissue slides from The Cancer Imaging Archive database were used to perform transcriptomics and pathomics analysis. Results: The areas under the receiver operating characteristic curve of the radiomics nomogram to predict proliferative HCC were 0.84, 0.87, and 0.85 in the training, internal test, and external test cohorts, respectively. The radiomics nomogram could stratify early recurrence-free survivals in the surgery outcome cohort (hazard ratio [HR] = 2.25; P < 0.001) and progression-free survivals in the TACE outcome cohort (HR = 2.21; P = 0.03). Transcriptomics and pathomics analysis indicated that the radiomics nomogram was associated with carbon metabolism, immune cells infiltration, TP53 mutation, and heterogeneity of tumor cells. Conclusion: The CT-based radiomics nomogram could predict proliferative HCC, stratify clinical outcomes, and measure a pro-tumor microenvironment.