SMYD5 methylation of rpL40 links ribosomal output to gastric cancer.

Dysregulated transcription due to disruption in histone lysine methylation dynamics is an established contributor to tumorigenesis1,2. However, whether analogous pathologic epigenetic mechanisms act directly on the ribosome to advance oncogenesis is unclear. Here we find that trimethylation of the core ribosomal protein L40 (rpL40) at lysine 22 (rpL40K22me3) by the lysine methyltransferase SMYD5 regulates mRNA translation output to promote malignant progression of gastric adenocarcinoma (GAC) with lethal peritoneal ascites. A biochemical-proteomics strategy identifies the monoubiquitin fusion protein partner rpL40 (ref. 3) as the principal physiological substrate of SMYD5 across diverse samples. Inhibiting the SMYD5-rpL40K22me3 axis in GAC cell lines reprogrammes protein synthesis to attenuate oncogenic gene expression signatures. SMYD5 and rpL40K22me3 are upregulated in samples from patients with GAC and negatively correlate with clinical outcomes. SMYD5 ablation in vivo in familial and sporadic mouse models of malignant GAC blocks metastatic disease, including peritoneal carcinomatosis. Suppressing SMYD5 methylation of rpL40 inhibits human cancer cell and patient-derived GAC xenograft growth and renders them hypersensitive to inhibitors of PI3K and mTOR. Finally, combining SMYD5 depletion with PI3K-mTOR inhibition and chimeric antigen receptor T cell administration cures an otherwise lethal in vivo mouse model of aggressive GAC-derived peritoneal carcinomatosis. Together, our work uncovers a ribosome-based epigenetic mechanism that facilitates the evolution of malignant GAC and proposes SMYD5 targeting as part of a potential combination therapy to treat this cancer.

Red nucleus mGluR1 and mGluR5 facilitate the development of neuropathic pain through stimulating the expressions of TNF-α and IL-1ß.

Our previous study has identified that glutamate in the red nucleus (RN) facilitates the development of neuropathic pain through metabotropic glutamate receptors (mGluR). Here, we further explored the actions and possible molecular mechanisms of red nucleus mGluR Ⅰ (mGluR1 and mGluR5) in the development of neuropathic pain induced by spared nerve injury (SNI). Our data indicated that both mGluR1 and mGluR5 were constitutively expressed in the RN of normal rats. Two weeks after SNI, the expressions of mGluR1 and mGluR5 were significantly boosted in the RN contralateral to the nerve injury. Administration of mGluR1 antagonist LY367385 or mGluR5 antagonist MTEP to the RN contralateral to the nerve injury at 2 weeks post-SNI significantly ameliorated SNI-induced neuropathic pain. However, unilateral administration of mGluRⅠ agonist DHPG to the RN of normal rats provoked a significant mechanical allodynia, this effect could be blocked by LY367385 or MTEP. Further studies indicated that the expressions of TNF-α and IL-1ß in the RN were also elevated at 2 weeks post-SNI. Administration of mGluR1 antagonist LY367385 or mGluR5 antagonist MTEP to the RN at 2 weeks post-SNI significantly inhibited the elevations of TNF-α and IL-1ß. However, administration of mGluR Ⅰ agonist DHPG to the RN of normal rats significantly enhanced the expressions of TNF-α and IL-1ß, these effects were blocked by LY367385 or MTEP. These results suggest that activation of red nucleus mGluR1 and mGluR5 facilitate the development of neuropathic pain by stimulating the expressions of TNF-α and IL-1ß. mGluR Ⅰ maybe potential targets for drug development and clinical treatment of neuropathic pain.

The prediction of Chongqing's GDP based on the LASSO method and chaotic whale group algorithm-back propagation neural network-ARIMA model.

Accurate GDP forecasts are vital for strategic decision-making and effective macroeconomic policies. In this study, we propose an innovative approach for Chongqing's GDP prediction, combining the LASSO method with the CWOA-BP-ARIMA model. Through meticulous feature selection based on Pearson correlation and Lasso regression, we identify key economic indicators linked to Chongqing's GDP. These indicators serve as inputs for the optimized CWOA-BP-ARIMA model, demonstrating its superiority over Random Forest, MLP, GA-BP, and CWOA-BP models. The CWOA-BP-ARIMA model achieves a remarkable 95% reduction in MAE and a significant 94.2% reduction in RMSE compared to Random Forest. Furthermore, it shows substantial reductions of 80.6% in MAE and 77.8% in RMSE compared to MLP, along with considerable reductions of 77.3% in MAE and 75% in RMSE compared to GA-BP. Moreover, compared to its own CWOA-BP counterpart, the model attains an impressive 30.7% reduction in MAE and a 20.46% reduction in RMSE. These results underscore the model's predictive accuracy and robustness, establishing it as a reliable tool for economic planning and decision-making. Additionally, our study calculates GDP prediction intervals at different confidence levels, further enhancing forecasting accuracy. The research uncovers a close relationship between GDP and key indicators, providing valuable insights for policy formulation. Based on the predictions, Chongqing's GDP is projected to experience positive growth, reaching 298,880 thousand yuan in 2022, 322,990 thousand yuan in 2023, and 342,730 thousand yuan in 2024. These projections equip decision-makers with essential information to formulate effective policies aligned with economic trends. Overall, our study provides valuable knowledge and tools for strategic decision-making and macroeconomic policy formulation, showcasing the exceptional performance of the CWOA-BP-ARIMA model in GDP prediction.

On the mixed Kibria-Lukman estimator for the linear regression model.

This paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria-Lukman estimator by combining the mixed estimator and the Kibria-Lukman estimator.This new estimator is a general estimation, including OLS estimator, mixed estimator and Kibria-Lukman estimator as special cases. In addition, we discuss the advantages of the new estimator based on MSEM criterion, and illustrate the theoretical results through examples and simulation analysis.

DKK2 blockage-mediated immunotherapy enhances anti-angiogenic therapy of Kras mutated colorectal cancer.

There are limited options for targeted therapies for colorectal cancer (CRC). Anti-EGFR therapy is limited to CRC without KRAS mutations. Even worse, most of CRC are refractory to currently immune checkpoint blockade. DKK2, which is upregulated in CRC, was recently found to suppress host immune responses, and its blockage effectively impeded tumor progression in benign genetic CRC models in our previous study. Here, our recent study demonstrated that in human CRC tumor samples expressing high levels of DKK2, DKK2 blockade caused stronger activation of tumor infiltrating CD8+ T cells in ex vivo culture. Intriguingly, we observed a correlation of high DKK2 expression with increased lymph node metastasis prevalence in these CRC patients as well. Furthermore, in a mouse genetic CRC model with mutations in APC and KRAS, which more closely mimics advanced human CRC, we confirmed the tumor inhibitory effect of DKK2 blockade, which significantly retarded tumor progression and extended survival, with increased immune effector cell activation and reduced angiogenesis. Based on this, we performed a combined administration of DKK2 blockade with sub-optimal anti-VEGFR treatment and observed a synergetic effect on suppressing tumor angiogenesis and progression, as well as extending survival, better than those of every single therapy. Thus, this study provides further evidence for the potential therapeutic application of DKK2 blockade in the clinical treatment of human CRC.

DKK2 imparts tumor immunity evasion through ß-catenin-independent suppression of cytotoxic immune-cell activation.

Immunotherapy offers new options for cancer treatment, but efficacy varies across cancer types. Colorectal cancers (CRCs) are largely refractory to immune-checkpoint blockade, which suggests the presence of yet uncharacterized immune-suppressive mechanisms. Here we report that the loss of adenomatosis polyposis coli (APC) in intestinal tumor cells or of the tumor suppressor PTEN in melanoma cells upregulates the expression of Dickkopf-related protein 2 (DKK2), which, together with its receptor LRP5, provides an unconventional mechanism for tumor immune evasion. DKK2 secreted by tumor cells acts on cytotoxic lymphocytes, inhibiting STAT5 signaling by impeding STAT5 nuclear localization via LRP5, but independently of LRP6 and the Wnt-ß-catenin pathway. Genetic or antibody-mediated ablation of DKK2 activates natural killer (NK) cells and CD8+ T cells in tumors, impedes tumor progression, and enhances the effects of PD-1 blockade. Thus, we have identified a previously unknown tumor immune-suppressive mechanism and immunotherapeutic targets particularly relevant for CRCs and a subset of melanomas.

Difference-based ridge-type estimator of parameters in restricted partial linear model with correlated errors.

In this article, a generalized difference-based ridge estimator is proposed for the vector parameter in a partial linear model when the errors are dependent. It is supposed that some additional linear constraints may hold to the whole parameter space. Its mean-squared error matrix is compared with the generalized restricted difference-based estimator. Finally, the performance of the new estimator is explained by a simulation study and a numerical example.

Design, Synthesis, and Structural Optimization of Lycorine-Derived Phenanthridine Derivatives as Wnt/ß-Catenin Signaling Pathway Agonists.

Lycorine is a benzylphenethylamine-type alkaloid member of the Amaryllidaceae family. A lycorine derivative, HLY78, was previously identified as a new Wnt/ß-catenin signaling pathway agonist that targets the DAX domain of axin. Herein, the structural optimization of HLY78 and analyses of the structure-activity relationships of lycorine-derived phenanthridine derivatives as agonists of the Wnt/ß-catenin signaling pathway are presented. This research suggests that triazole groups are important pharmacophores for Wnt activation; triazole groups at C-8 and C-9 of phenanthridine compounds markedly enhanced Wnt activation. A C-11-C-12 single bond is also important for Wnt activation. On the basis of these findings, two Wnt agonists were designed and synthesized. The results for these agonists indicated that the combination of a 4-ethyldihydrophenanthridine skeleton and a triazole substituent improves Wnt activation. These compounds may be useful in further pharmacological or biological studies.

Structure-based Discovery of Novel Small Molecule Wnt Signaling Inhibitors by Targeting the Cysteine-rich Domain of Frizzled.

Frizzled is the earliest discovered glycosylated Wnt protein receptor and is critical for the initiation of Wnt signaling. Antagonizing Frizzled is effective in inhibiting the growth of multiple tumor types. The extracellular N terminus of Frizzled contains a conserved cysteine-rich domain that directly interacts with Wnt ligands. Structure-based virtual screening and cell-based assays were used to identify five small molecules that can inhibit canonical Wnt signaling and have low IC50 values in the micromolar range. NMR experiments confirmed that these compounds specifically bind to the Wnt binding site on the Frizzled8 cysteine-rich domain with submicromolar dissociation constants. Our study confirms the feasibility of targeting the Frizzled cysteine-rich domain as an effective way of regulating canonical Wnt signaling. These small molecules can be further optimized into more potent therapeutic agents for regulating abnormal Wnt signaling by targeting Frizzled.

An unbiased two-parameter estimation with prior information in linear regression model.

We introduce an unbiased two-parameter estimator based on prior information and two-parameter estimator proposed by Özkale and Kaçiranlar, 2007. Then we discuss its properties and our results show that the new estimator is better than the two-parameter estimator, the ordinary least squares estimator, and explain the almost unbiased two-parameter estimator which is proposed by Wu and Yang, 2013. Finally, we give a simulation study to show the theoretical results.