AKT2S128/CCTαS315/319/323-positive cancer-associated fibroblasts (CAFs) mediate focal adhesion kinase (FAK) inhibitors resistance via secreting phosphatidylcholines (PCs).

Abnormal metabolism is regarded as an oncogenic hallmark related to tumor progression and therapeutic resistance. Present study employed multi-omics, including phosphoproteomics, untargeted metabolomics and lipidomics, to demonstrate that the pAKT2 Ser128 and pCCTα Ser315/319/323-positive cancer-associated fibroblasts (CAFs) substantially release phosphatidylcholines (PCs), contributing to the resistance of focal adhesion kinase (FAK) inhibitors in esophageal squamous cell carcinoma (ESCC) treatment. Additionally, we observed extremely low levels of FAK Tyr397 expression in CAFs, potentially offering no available target for FAK inhibitors playing their anti-growth role in CAFs. Consequently, FAK inhibitor increased the intracellular concentration of Ca2+ in CAFs, promoting the formation of AKT2/CCTα complex, leading to phosphorylation of CCTα Ser315/319/323 sites and eventually enhancing stromal PC production. This activation could stimulate the intratumoral Janus kinase 2 (JAK2)/Signal transducer and activator of transcription 3 (STAT3) pathway, triggering resistance to FAK inhibition. Analysis of clinical samples demonstrated that stromal pAKT2 Ser128 and pCCTα Ser315/319/323 are related to the tumor malignancy and reduced patient survival. Pseudo-targeted lipidomics and further validation cohort quantitatively showed that plasma PCs enable to distinguish the malignant extent of ESCC patients. In conclusion, inhibition of stroma-derived PCs and related pathway could be possible therapeutic strategies for tumor therapy.

Prediction of immune infiltration and prognosis for patients with cholangiocarcinoma based on a cuproptosis-related lncRNA signature.

Objective: Cholangiocarcinoma (CHOL) is a malignant disease that affects the digestive tract, and it is characterized by a poor prognosis. This research sought to explore the involvement of cuproptosis-related lncRNAs (CRLs) in the prognostic prediction and immune infiltration of cholangiocarcinoma. Methods: The expression profiles and clinical data of CHOL patients were acquired from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and CRLs were defined via co-expression analysis. Two molecular clusters distinguished by cuproptosis-related genes (CRGs) were produced. Then a risk signature consisted by four CRLs was formed, and all samples were separated into low- and high-risk groups using a risk score. Kaplan-Meier survival analysis, principal component analysis, differentially expressed analysis, immune cell infiltration analysis, and sensitivities analysis of chemotherapy drugs were conducted between the two groups. Simultaneously, the expression values of four lncRNAs confirmed by real-time PCR in our own 20 CHOL samples were brought into the risk model. Results: The CHOL samples could be differentiated into two molecular clusters, which displayed contrasting survival times. Additionally, patients with higher risk scores had significantly worse prognosis compared to those in the low-risk group. Furthermore, both immune infiltration and enrichment analysis revealed significant discrepancies in the tumor immune microenvironment (TIME) between different risk groups. Moreover, the predictive power and the correlation with CA19-9 and CEA of risk signature were validated in our own samples. Conclusion: We developed a risk signature which could serve as an independent prognostic factor and offer a promising prediction for not only prognosis but also TIME in CHOL patients.

Integrated Controller Design and Application for CNC Machine Tool Servo Systems Based on Model Reference Adaptive Control and Adaptive Sliding Mode Control.

In order to reduce the effect of nonlinear friction and time-varying factors on the servo system of a computer numerical control (CNC) machine tool and improve its motion control accuracy, this paper uses an adaptive sliding mode control (ASMC) method based on model reference adaptive control (MRAC). The method adopts ASMC in the control outer loop and obtains the optimal control parameters by making the sliding mode control (SMC) law continuous and adaptively estimating the control parameters. At the same time, MRAC is used in the control inner loop to enhance the "invariance" of the controlled object so that the switching gain of SMC can satisfy the disturbance matching condition even under lesser conditions. Simulation and experimental results show that compared with the traditional SMC, the ASMC based on MRAC proposed in this paper effectively reduces the influence of nonlinear friction on the system performance, and the reduction in following error reaches 71.2%, which significantly improves the motion control accuracy of the control system. The spectral analysis of the following errors shows that the maximum magnitude reduction rate of the high-frequency chattering is 89.02%, which significantly reduces the effect of the high-frequency chattering and effectively improves the stability performance of the control system.

Combined radiomics of primary tumour and bone metastasis improve the prediction of EGFR mutation status and response to EGFR-TKI therapy for NSCLC.

PURPOSE: To develop radiomics models of primary tumour and spinal metastases to predict epidermal growth factor receptor (EGFR) mutations and therapeutic response to EGFR-tyrosine kinase inhibitor (TKI) in patients with metastatic non-small-cell lung cancer (NSCLC). METHODS: We enrolled 203 patients with spinal metastases between December 2017 and September 2021, classified as patients with the EGFR mutation or EGFR wild-type. All patients underwent thoracic CT and spinal MRI scans before any treatment. Radiomics analysis was performed to extract features from primary tumour and metastases images and identify predictive features with the least absolute shrinkage and selection operator. Radiomics signatures (RS) were constructed based on primary tumour (RS-Pri), metastases (RS-Met), and in combination (RS-Com) to predict EGFR mutation status and response to EGFR-TKI. Receiver operating characteristic (ROC) curve analysis with 10-fold cross-validation was applied to assess the performance of the models. RESULTS: To predict the EGFR mutation status, the RS based on the combination of primary tumour and metastases improved the prediction AUCs compared to those based on the primary tumour or metastasis alone in the training (RS-Com-EGFR: 0.927) and validation (RS-Com-EGFR: 0.812) cohorts. To predict response to EGFR-TKI, the developed RS based on combined primary tumour and metastasis generated the highest AUCs in the training (RS-Com-TKI: 0.880) and validation (RS-Com-TKI: 0.798) cohort. CONCLUSIONS: Primary NSCLC and spinal metastases can provide complementary information to predict the EGFR mutation status and response to EGFR-TKI. The developed models that integrate primary lesions and metastases may be potential imaging markers to guide individual treatment decisions.

Delivery of Small-Molecule Drugs and Protein Drugs by Injectable Acid-Responsive Self-Assembled COF Hydrogels for Combinatorial Lung Cancer Treatment.

Covalent organic frameworks (COFs) have revealed enormous application prospects for cancer therapeutics recently, but their assembly systems face considerable challenges, such as the codelivery of hydrophobic and hydrophilic protein drugs with different physicochemical properties for in vivo delivery and release, as well as endosomal/lysosomal escape of protein drugs. To address these issues, we leveraged the high specific surface area, lipotropism, and structural tunability of boronate ester-linked COFs (COF-1) for the construction of advanced drug delivery systems. We first encapsulated the small-molecule drug doxorubicin (DOX) into a lipophilic COF (COF-1@DOX) and immobilized the functional protein drug ribonuclease A (RNase A) on the surface of the COF (RNase A-COF-1@DOX). We then created a novel composite delivery system (RNase A-COF-1@DOX gel) by cross-linking an albumin-oxygenated hydrogel (gel) network into the pores of COFs, allowing targeted codelivery of protein and small-molecule drugs in vivo. Using in-living body and multichannel fluorescence imaging, we analyzed the in vivo codelivery of protein and small-molecule drugs in a Lewis lung carcinoma (LLC) model. Finally, we applied the RNase A-COF-1@DOX gel to treat lung cancer in mice. This study paves an avenue for constructing COF-based drug delivery systems for lung cancer treatment and holds the potential to be extended to other types of cancer for more effective and targeted therapeutic treatments.

Analysis of cuproptosis-related lncRNA signature for predicting prognosis and tumor immune microenvironment in pancreatic cancer.

Pancreatic cancer (PC) is a highly malignant digestive tract tumor, with a dismal 5-year survival rate. Recently, cuproptosis was found to be copper-dependent cell death. This work aims to establish a cuproptosis-related lncRNA signature which could predict the prognosis of PC patients and help clinical decision-making. Firstly, cuproptosis-related lncRNAs were identified in the TCGA-PAAD database. Next, a cuproptosis-related lncRNA signature based on five lncRNAs was established. Besides, the ICGC cohort and our samples from 30 PC patients served as external validation groups to verify the predictive power of the risk signature. Then, the expression of CASC8 was verified in PC samples, scRNA-seq dataset CRA001160, and PC cell lines. The correlation between CASC8 and cuproptosis-related genes was validated by Real-Time PCR. Additionally, the roles of CASC8 in PC progression and immune microenvironment characterization were explored by loss-of-function assay. As showed in the results, the prognosis of patients with higher risk scores was prominently worse than that with lower risk scores. Real-Time PCR and single cell analysis suggested that CASC8 was highly expressed in pancreatic cancer and related to cuproptosis. Additionally, gene inhibition of CASC8 impacted the proliferation, apoptosis and migration of PC cells. Furthermore, CASC8 was demonstrated to impact the expression of CD274 and several chemokines, and serve as a key indicator in tumor immune microenvironment characterization. In conclusion, the cuproptosis-related lncRNA signature could provide valuable indications for the prognosis of PC patients, and CASC8 was a candidate biomarker for not only predicting the progression of PC patients but also their antitumor immune responses.

Immunosuppression, immune escape, and immunotherapy in pancreatic cancer: focused on the tumor microenvironment.

Pancreatic ductal adenocarcinoma (PDAC), the most common type of pancreatic cancer, is characterized by poor treatment response and low survival time. The current clinical treatment for advanced PDAC is still not effective. In recent years, the research and application of immunotherapy have developed rapidly and achieved substantial results in many malignant tumors. However, the translational application in PDAC is still far from satisfactory and needs to be developed urgently. To carry out the study of immunotherapy, it is necessary to fully decipher the immune characteristics of PDAC. This review summarizes the recent progress of the tumor microenvironment (TME) of PDAC and highlights its link with immunotherapy. We describe the molecular cues and corresponding intervention methods, collate several promising targets and progress worthy of further study, and put forward the importance of integrated immunotherapy to provide ideas for future research of TME and immunotherapy of PDAC.

Exploitation and Verification of a Stroma- and Metastasis-Associated Risk Prognostic Signature in Pancreatic Adenocarcinoma.

Pancreatic adenocarcinoma (PAAD), one of the most malignant tumors, not only has abundant mesenchymal components, but is also characterized by an extremely high metastatic risk. The purpose of this study was to construct a model of stroma- and metastasis-associated prognostic signature, aiming to benefit the existing clinical staging system and predict the prognosis of patients. First, stroma-associated genes were screened from the TCGA database with the ESTIMATE algorithm. Subsequently, transcriptomic data from clinical tissues in the RenJi cohort were screened for metastasis-associated genes. Integrating the two sets of genes, we constructed a risk prognostic signature by Cox and LASSO regression analysis. We then obtained a risk score by a quantitative formula and divided all samples into high- and low-risk groups based on the scores. The results demonstrated that patients with high-risk scores have a worse prognosis than those with low-risk scores, both in the TCGA database and in the RenJi cohort. In addition, tumor mutation burden, chemotherapeutic drug sensitivity and immune infiltration analysis also exhibited significant differences between the two groups. In exploring the potential mechanisms of how stromal components affect tumor metastasis, we simulated different matrix stiffness in vitro to explore its effect on EMT key genes in PAAD cells. We found that cancer cells stimulated by high matrix stiffness may trigger EMT and promote PAAD metastasis.

Characteristic Synthesis of a Covalent Organic Framework and Its Application in Multifunctional Tumor Therapy.

For decades, covalent organic frameworks (COFs) have attracted wide biomedical interest due to their unique properties including ease of synthesis, porosity, and adjustable biocompatibility. Versatile COFs can easily encapsulate various therapeutic drugs due to their extremely high payload and porosity. COFs with abundant functional groups can be surface-modified to achieve active targeting and enhance biocompatibility. In this paper, the latest developments of COFs in the biomedical field are summarized. First, the classification and synthesis of COFs are discussed. Cancer diagnosis and treatment based on COFs are studied, and the advantages and limitations of each method are discussed. Second, the specific preparation methods to obtain specific therapeutic properties are summarized. Finally, based on the combination and modification of COFs with various components, this review system summarizes different combination therapies. In addition, the main challenges faced in COF research and prospects for applying COFs to cancer diagnosis and treatment are evaluated. This review provides enlightening insights into the interdisciplinary research on COFs and applications in biomedicine, which highlight the great expectations for their further clinical transformation.