The development of a novel zeolite-based assay for efficient and deep plasma proteomic profiling.

Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications.

A Prognostic Model for Colon Adenocarcinoma Patients Based on Ten Amino Acid Metabolism Related Genes.

Background: Amino acid metabolism plays a vital role in cancer biology. However, the application of amino acid metabolism in the prognosis of colon adenocarcinoma (COAD) has not yet been explored. Here, we construct an amino acid metabolism-related risk model to predict the survival outcome of COAD and improve clinical decision making. Methods: The RNA-sequencing-based transcriptome for 524 patients with COAD from The Cancer Genome Atlas (TCGA) was selected as a training set. The integrated Gene Expression Omnibus (GEO) dataset with 1,430 colon cancer samples was used for validation. Differential expression of amino acid metabolism-related genes (AAMRGs) was identified for prognostic gene selection. Univariate cox regression analysis, LASSO-penalized Cox regression analysis, and multivariate Cox regression analysis were applied to construct a prognostic risk model. Moreover, the correlation between risk score and microsatellite instability, immunotherapy response, and drug sensitivity were analyzed. Results: A prognostic signature was constructed based on 10 AAMRGs, including ASPG, DUOX1, GAMT, GSR, MAT1A, MTAP, PSMD12, RIMKLB, RPL3L, and RPS17. Patients with COAD were divided into high-risk and low-risk group based on the medianrisk score. Univariate and multivariate Cox regression analysis revealed that AAMRG-related signature was an independent risk factor for COAD. Moreover, COAD patients in the low-risk group were more sensitive to immunotherapy targeting PD-1 and CTLA-4. Conclusion: Our study constructed a prognostic signature based on 10 AAMRGs, which could be used to build a novel prognosis model and identify potential drug candidates for the treatment of COAD.

Mechanical Performance of RPC and Steel-RPC Composite Structure with Different Fiber Parameters: Experimental and Theoretical Research.

This paper aims to explore the material properties of RPC and transverse-bending performance, as well as the crack-width-calculation theory of a densely reinforced steel-RPC composite structure with different fiber parameters. Two fiber types (straight fiber, hybrid fiber) and four fiber volume contents (2%, 2.5%, 3%, 3.5%) were selected to explore the mechanical properties of RPC materials, and the influences of fiber parameters on compressive strength, modulus of elasticity, flexural strength and axial tensile property were investigated. Eight steel-RPC composite plates with different design parameters (fiber type and reinforcement ratio) were conducted to study the transverse-bending performance of steel-RPC composite deck structures. The results show that the addition of 3.5% hybrid fibers to the RPC matrix leads to the optimum axial tensile and flexural properties. Furthermore, the failure mode, load-displacement curve, crack occurrence and propagation characteristics of the composite structure are analyzed in detail. Based on the experimental results, the calculation methods of reinforcement stress and crack width of densely reinforced steel-RPC composite structure are proposed. The calculated results of reinforcement stress and maximum crack width are in good agreement with the actual measured values, which can provide a reference for engineering design.

Analysis of Immune Landscape Reveals Prognostic Significance of Cytotoxic CD4+ T Cells in the Central Region of pMMR CRC.

BACKGROUND: Mismatch repair proficient colorectal cancer (pMMR CRC) lacks effective treatments and has a poor prognosis, which can be attributed to the complexity of tumor microenvironment. The coordinated function of immune cells is vital to anti-tumor immunity. However, the spatial characteristics of immune cells in the pMMR CRC immune microenvironment and their relationship with clinical prognosis are not fully understood. Meanwhile, the immune modulatory effect of neoadjuvant chemotherapy (NCT), which is the first-line treatment of pMMR CRC, needs further investigation. Therefore, this study aims to explore the spatial dynamics of immune cells and its prognostic value in pMMR CRC. METHODS: We analyzed the various immune cells in formalin-fixed, paraffin-embedded tumor tissues which were collected from 77 patients with stage II/III of pMMR CRC, including 39 non-NCT treated and 38 NCT treated patients. We used the optimized multiplex immunohistochemistry (mIHC) to identify and quantify the density, type and location of immune cells in pMMR CRC. Multivariate survival analysis was performed to assess the relationship of immune profiles and clinical prognosis of pMMR CRC patients. RESULTS: The densities of most T cell subsets, B cells and macrophages were higher in the central region of the pMMR CRC than in the invasion margin. Tumor infiltrating lymphocytes (TILs), especially the infiltration of CD4+ GzmB+ T cells in the central region of the tumor was identified to be positively correlated with the prognosis of the patients. Multivariate analysis confirmed that CD4+ GzmB+ T cells population was an independent predictor of disease-free survival (DFS) in non-NCT group. Meanwhile, NCT enhanced the infiltration of CD4+ GzmB+ T cells in the central region of the pMMR CRC, which was also identified as an independent protective factor of overall survival (OS) and DFS in NCT group. CONCLUSION: We demonstrated that the level of CD4+ GzmB+ T cells located in the center of tumor could provide great prognostic value for pMMR CRC patients. And the application of neoadjuvant chemotherapy further improves the infiltration of CD4+ GzmB+ T cells in the central compartment. Further studies into the application of CD4+ GzmB+ T cells in tumor immunotherapy are needed.

Lipid Metabolism in Tumor-Infiltrating T Cells.

T cells recognize "foreign" antigens and induce durable humoral and cellular immune responses, which are indispensable for defending pathogens, as well as maintaining the integrity and homeostasis of tissues and organs. T cells are the major immune cell population in the tumor microenvironment which play a critical role in the antitumor immune response and cancer immune surveillance. Defective immune response of tumor-infiltrating T cells is the main cause of cancer immune evasion. The antitumor response of T cells is affected by multiple factors in the tumor microenvironment, including immunosuppressive cells, immune inhibitory cytokines, tumor-derived suppressive signals like PD-L1, immnuogenicity of tumor cells, as well as metabolic factors like hypoxia and nutrient deprivation. Abundant studies in past decades have proved the metabolic regulations of the immune response of T cells and the tumor-infiltrating T cells. In this chapter, we will discuss the regulations of the antitumor response of tumor-infiltrating T cells by lipid metabolism, which is one of the main components of metabolic regulation.

Potentiating CD8+ T cell antitumor activity by inhibiting PCSK9 to promote LDLR-mediated TCR recycling and signaling.

Metabolic regulation has been proven to play a critical role in T cell antitumor immunity. However, cholesterol metabolism as a key component of this regulation remains largely unexplored. Herein, we found that the low-density lipoprotein receptor (LDLR), which has been previously identified as a transporter for cholesterol, plays a pivotal role in regulating CD8+ T cell antitumor activity. Besides the involvement of cholesterol uptake which is mediated by LDLR in T cell priming and clonal expansion, we also found a non-canonical function of LDLR in CD8+ T cells: LDLR interacts with the T-cell receptor (TCR) complex and regulates TCR recycling and signaling, thus facilitating the effector function of cytotoxic T-lymphocytes (CTLs). Furthermore, we found that the tumor microenvironment (TME) downregulates CD8+ T cell LDLR level and TCR signaling via tumor cell-derived proprotein convertase subtilisin/kexin type 9 (PCSK9) which binds to LDLR and prevents the recycling of LDLR and TCR to the plasma membrane thus inhibits the effector function of CTLs. Moreover, genetic deletion or pharmacological inhibition of PCSK9 in tumor cells can enhance the antitumor activity of CD8+ T cells by alleviating the suppressive effect on CD8+ T cells and consequently inhibit tumor progression. While previously established as a hypercholesterolemia target, this study highlights PCSK9/LDLR as a potential target for cancer immunotherapy as well.