Downregulation of MTHFD2 Inhibits Proliferation and Enhances Chemosensitivity in Hepatocellular Carcinoma via PI3K/AKT Pathway.

BACKGROUND: Despite the substantial impact of methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) on cancer progression, its significance in the regulation of hepatocellular carcinoma (HCC) cell proliferation and chemosensitivity remains poorly defined. METHODS: We evaluated MTHFD2 expression in a total of 95 HCC tissues by immunohistochemistry and analyzed the association of MTHFD2 with clinicopathologic features. qRT-PCR and Western blotting were conducted to verify MTHFD2 expression levels. Bioinformatics analysis such as gene set enrichment analysis (GSEA) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were used to predict the signaling pathways involved in MTHFD2. In addition, to investigate the anti-tumor effects of MTHFD2 knockdown, Cell Counting Kit-8 (CCK-8) and EdU assays were used. RESULTS: We found that MTHFD2 was frequently upregulated in HCC, and the combination of increased expression of MTHFD2 and Ki67 was associated with poor HCC prognosis. MTHFD2 knockdown significantly inhibited HCC cell proliferation and effectively sensitized HCC cells to sorafenib and lenvatinib. PI3K/AKT pathway was involved in MTHFD2-mediated modulation of proliferation and chemosensitivity. CONCLUSIONS: These findings indicate that MTHFD2 plays an important role in proliferation and chemosensitivity of HCC, indicating that it may serve as a novel pharmacological target for improving HCC therapy.

Could the underlying biological basis of prognostic radiomics and deep learning signatures be explored in patients with lung cancer? A systematic review.

OBJECTIVES: To summarize the underlying biological correlation of prognostic radiomics and deep learning signatures in patients with lung cancer and evaluate the quality of available studies. METHODS: This study examined databases including the PubMed, Embase, Web of Science Core Collection, and Cochrane Library, for studies that elaborated on the underlying biological correlation with prognostic radiomics and deep learning signatures based on CT or PET/CT for predicting the prognosis in patients with lung cancer. Information about the patient and radiogenomic analyses was extracted for the included studies. The Radiomics Quality Score (RQS) and the Prediction Model Risk of Bias Assessment Tool were used to assess the quality of these studies. RESULTS: Twelve studies were included with 7,338 patients from 2014 to 2022. All studies except for one were retrospective. Supervised machine learning was adopted in six studies, and the remaining used unsupervised machine learning methods. Gene sequencing and histopathological data were analyzed by 83.33% and 16.67% of the included studies, respectively. Gene set enrichment analysis and correlation analysis were most used to explore the biological meaning of prognostic signatures. The median RQS for supervised learning articles was 13.5 (range 12-19) and 7.0 (range 5-14) for unsupervised learning articles. The studies included in this report were assessed to have high risk of bias overall. CONCLUSION: The biological basis for the interpretability of data-driven models mainly focused on genomics and histopathological factors, and it may improve the prognosis of lung cancer with more proper biological interpretation in the future.

CDK5 destabilizes PD-L1 via chaperon-mediated autophagy to control cancer immune surveillance in hepatocellular carcinoma.

BACKGROUND: In the past few years, immunotherapies of hepatocellular carcinoma (HCC) targeting programmed cell death protein 1 (PD-1) and its ligand programmed cell death ligand 1 (PD-L1), have achieved durable clinical benefits. However, only a fraction of HCC patients showed objective clinical response to PD-1/PD-L1 blockade alone. Despite the impact on post-translational modifications of PD-L1 being substantial, its significance in resistance to HCC immunotherapy remains poorly defined. METHODS: Cyclin-dependent kinase 5 (CDK5) expression was knocked down in HCC cells, CDK5 and PD-L1 protein levels were examined by Western blot. Coimmunoprecipitation was conducted to evaluate the interaction between proteins. Preclinical HCC mice model was constructed to evaluate the effect of CDK5 inhibitor alone or in combination with PD-1 antibody. Clinical HCC samples were used to elucidate the clinical relevance of CDK5, PD-L1, and PD-L1 T290 phosphorylation in HCC. RESULTS: We find that CDK5 deficiency upregulates PD-L1 protein expression in HCC cells and decipher a novel molecular mechanism under which PD-L1 is downregulated by CDK5, that is, CDK5 mediated PD-L1 phosphorylation at T290 promotes its binding with chaperon protein heat-shock cognate protein 70 (HSC70) and degradation through chaperon-mediated autophagy. Notably, treatment of CDK5 inhibitor, PNU112455A, effectively upregulates the tumorous PD-L1 level, promotes the response to anti-PD-1 immunotherapy,and prolongs the survival time of mice bearing HCC tumors. What is more, the T290 phosphorylation status of PD-L1 correlates with the prognosis of HCC. CONCLUSIONS: Targeting CDK5 can synergize with PD-1 blockade to suppress HCC growth, which may have clinical benefits. Our study reveals a unique regulation of the degradation of PD-L1 in HCC, and provides an attractive therapeutic target, a potential drug, and a new prognostic marker for the clinical treatment of HCC.

Design of Beta-2 Microglobulin Adsorbent Protein Nanoparticles.

Beta-2 microglobulin (B2M) is an immune system protein that is found on the surface of all nucleated human cells. B2M is naturally shed from cell surfaces into the plasma, followed by renal excretion. In patients with impaired renal function, B2M will accumulate in organs and tissues leading to significantly reduced life expectancy and quality of life. While current hemodialysis methods have been successful in managing electrolyte as well as small and large molecule disturbances arising in chronic renal failure, they have shown only modest success in managing plasma levels of B2M and similar sized proteins, while sparing important proteins such as albumin. We describe a systematic protein design effort aimed at adding the ability to selectively remove specific, undesired waste proteins such as B2M from the plasma of chronic renal failure patients. A novel nanoparticle built using a tetrahedral protein assembly as a scaffold that presents 12 copies of a B2M-binding nanobody is described. The designed nanoparticle binds specifically to B2M through protein-protein interactions with nanomolar binding affinity (~4.2 nM). Notably, binding to the nanoparticle increases the effective size of B2M by over 50-fold, offering a potential selective avenue for separation based on size. We present data to support the potential utility of such a nanoparticle for removing B2M from plasma by either size-based filtration or by polyvalent binding to a stationary matrix under blood flow conditions. Such applications could address current shortcomings in the management of problematic mid-sized proteins in chronic renal failure patients.

A diamidinatogermylene as a Z-type ligand in a nickel(0) complex.

The reaction of the phosphine functionalized chlorogermylene 1 with Ni(COD)2 (COD = 1,5-cyclooctadiene) afforded the bis-chlorogermylene ligated nickel(0) complex 2 in high yield. The dechlorination reaction of 2 with elemental potassium serendipitously yielded the diamidinatogermylene nickel(0) complex 3. Single-crystal X-ray diffraction analysis reveals that the germanium center in 3 features a pyramidalized geometry, suggesting the germylene moiety in 3 acts as a Z-type ligand, which is further supported by theoretical calculations. Complex 3 represents the first example bearing a Z-type diaminogermylene ligand.