Background/Aims Transmembrane 4 L six family member 1 (TM4SF1) is highly expressed and contributes to the progression of various malignancies. However, how it modulates hepatocellular carcinoma (HCC) progression and senescence remains to be elucidated.
Methods TM4SF1 expression in HCC samples was evaluated using immunohistochemistry and flow cytometry. Cellular senescence was assessed through SA-β-gal activity assays and Western blot analysis. TM4SF1-related protein interactions were investigated using immunoprecipitation-mass spectrometry, co-immunoprecipitation, bimolecular fluorescence complementation, and immunofluorescence. Tumor-infiltrating immune cells were analyzed by flow cytometry. The HCC mouse model was established via hydrodynamic tail vein injection.
Results TM4SF1 was highly expressed in human HCC samples and murine models. Knockdown of TM4SF1 suppressed HCC proliferation both in vitro and in vivo, inducing non-secretory senescence through upregulation of p16 and p21. TM4SF1 enhanced the interaction between AKT1 and PDPK1, thereby promoting AKT phosphorylation, which subsequently downregulated p16 and p21. Meanwhile, TM4SF1-mediated AKT phosphorylation enhanced PD-L1 expression while reducing major histocompatibility complex class I level on tumor cells, leading to impaired cytotoxic function of CD8+ T cells and an increased proportion of exhausted CD8+ T cells. In clinical HCC samples, elevated TM4SF1 expression was associated with resistance to anti-PD-1 immunotherapy. Targeting TM4SF1 via adeno-associated virus induced tumor senescence, reduced tumor burden and synergistically enhanced the efficacy of anti-PD-1 therapy.
Conclusions Our results revealed that TM4SF1 regulated tumor cell senescence and immune evasion through the AKT pathway, highlighting its potential as a therapeutic target in HCC, particularly in combination with first-line immunotherapy.
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Results In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM).
Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.
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