Flexible Axial Shielding Strategy for Improving Ethylene (Co)polymerization with 8-Cycloalkylnaphthyl α-Diimine Catalysts.

8-aryl or alkyl-naphthyl substituents are widely used as an effective axial shielding strategy for the suppression of chain transfer in late-transition metal-catalyzed ethylene (co)polymerization to yield high molecular weight polyethylene and copolymers. In this study, two 8-cycloalkylnaphthyl acenaphthene-based α-diimine ligands and the corresponding four nickel and palladium complexes were designed and synthesized to explore the effect of axial flexible shielding on ethylene (co)polymerization. In ethylene polymerization, the nickel complexes displayed high activities (up to 1.99 × 106 g mol-1 h-1) and generated lightly branched (34-54/1000 C) polyethylenes with high molecular weights (up to Mn = 1075 kg/mol), whereas the corresponding palladium complexes exhibited moderate activities (level of 104 g mol-1 h-1), producing highly branched (111-125/1000 C) polyethylenes with high molecular weights (up to Mn = 37.6 kg/mol). Highly branched (110-123/1000 C) E-MA copolymers with moderate insertion ratios (1.97-5.56 mol %) were produced by these palladium complexes in ethylene/methyl acrylate (MA) copolymerization. In addition, the size of the 8-cycloalkyl ring in these α-diimine catalysts strongly influences the ethylene (co)polymerization. Compared to cyclopentyl groups, cyclohexyl groups are more effective in suppressing chain transfer reactions in the polymerization of ethylene and the copolymerization of ethylene and MA, leading to higher molecular weight polyethylene and E-MA copolymers. Most interestingly, compared to the reported rigid planar 8-arylnaphthyl catalysts, the flexible 8-cyclohexylnaphthyl catalysts exhibited higher activity and produced higher molecular weight polyethylene in ethylene polymerization. Moreover, in nickel-catalyzed ethylene polymerization, the cyclohexyl catalyst produced significantly reduced branched polyethylene, while in palladium-catalyzed ethylene (co)polymerization, the cyclohexyl catalyst produced more highly branched polyethylene and copolymers. In contrast to the previously reported flexible 8-butylnaphthyl nickel catalysts, the 8-cycloalkylnaphthyl catalysts reported in this work yielded polyethylene with narrow unimodal molecular weight distributions.

Development and validation of a combined ferroptosis and immune prognostic signature for lung adenocarcinoma.

Background: Studies have shown that the regulation of ferroptosis could be a new approach to cancer treatment and abnormal ferroptosis is closely associated with a dysregulated immune response. However, a combined signature with ferroptosis-related genes (FRGs) and immune-related genes (IRGs) is necessary to be constructed for predicting prognoses and guiding individualized precision therapy of lung adenocarcinoma (LUAD) patients. Methods: In this study, based on the Cancer Genome Atlas (TCGA) cohort, prognosis-related FRGs and IRGs were first identified and incorporated into the Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression model to generate a combined signature of ferroptosis- and immune-related genes (CSFI) values to predict the overall survivals (OSs) of LUAD patients. And patients with LUAD from the Gene Expression Omnibus (GEO) database were applied for the validation set. Nomogram was constructed based on multivariate Cox regression analysis. Subsequently, ferroptosis, immunity, and gene mutation status of patients between the CSFI-high and -low groups were compared. Additionally, the enrichment pathways in CSFI-high and -low groups were explored by Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) and Gene Set Enrichment Analysis (GSEA) analyses. Results: As a result, the CSFI-low group showed a good prognosis instead of the CSFI-high group. CSFI was identified to be an independent prognosis factor for LUAD. In general, there were ferroptosis- and immune-suppressive states in CSFI-high patients. Notably, the mutation frequencies of TP53 were higher in CSFI-high patients. Conclusions: In LUAD, CSFI which served as a novel classifier was offered for predicting the prognoses of patients and contributing to guiding personalized targeted therapy of patients. Therefore, based on these findings, it was believed that a synergistic treatment of ferroptosis and immunity would be more effective on LUAD patients with low CSFI values.

Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC.

Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P<0.001) in the MSKCC cohort and progression-free survival (PFS; P<0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.

Association of ATRX mutations with immunologically active characteristics in patients with MSI-prone tumors.

OBJECTIVES: The role of DNA damage repair deficiency in improving immune checkpoint inhibitors (ICIs) efficacy has been widely recognized. Studies have confirmed the association of gene mutations in homologous recombination (HR) with an immune-activated microenvironment. Given the crucial role of the tumor microenvironment in ICIs response, our study aimed to identify specific HR gene mutations that influence the tumor microenvironment and thus serve as potential biomarkers for ICIs in tumors that are prone to occur with microsatellite instability (MSI) events (MSI-prone tumors). METHODS: The multi-omics and clinical data of MSI-prone tumors were extracted from ICIs-treated and non-ICIs-treated cohorts. We depicted the mutation landscape of HR genes in MSI-prone tumors and identified the prognosis related HR gene mutations. We integrated multiple immunotherapy-related indicators by bioinformatics methods to characterize the anti-tumor immunity and tumor microenvironment. RESULTS: ATRX, ARID1A, BRCA2 and ATM were the common top four frequently mutated HR genes in MSI-prone tumors, among which ATRX mutations were identified to have prognostic value for ICIs treatment. The bioinformatics analyses suggested that patients with ATRX mutilations (ATRX-mt) have enhanced anti-tumor immunity and inflamed tumor microenvironment in MSI-prone tumors. MSI-stratified analyses revealed the immunologically active features in both microsatellite instability-high (MSI-H) and non-MSI-H populations. There may exist a synergistic effect between ATRX mutations and MSI-H status in immune activation. CONCLUSIONS: Our work found the association of ATRX mutations with immunologically active characteristics in MSI-prone tumors. The combined use of ATRX mutations and MSI-H status might have potential clinical utility for ICIs selection in MSI-prone tumors.

Neurotransmitter release cycle-related genes predict the prognosis of lung adenocarcinoma.

Because of the limitations of therapeutic approaches, patients suffering from lung adenocarcinoma (LUAD) have unsatisfactory prognoses. Studies have shown that neurotransmitters participated in tumorigenesis and development. In LUAD, the expression of neurotransmitter release cycle-related genes (NRCRGs) has been reported to be disordered. This study aimed to study the correlation between NRCRGs and LUAD. In this study, based on the Cancer Genome Atlas cohort, consensus clustering analyses were performed on ten neurotransmitter release cycle-related (NRCR) differentially expressed genes. Neurotransmitter release cycle (NRC) scores were derived by the Least Absolute Shrinkage and Selection Operator-Cox regression model constituted by 3 NRCRGs. Univariate and multivariate Cox regression analyses were performed to evaluate the prognosis value of the NRC score. In addition, single-Sample Gene Set Enrichment Analysis and CIBERSORT were conducted in the Cancer Genome Atlas cohort. Finally, gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses were also performed. As a result, the NRC-low group showed a good prognosis instead of the NRC-high group. NRC score was identified to be an independent prognosis factor for LUAD. In general, the NRC score based on the prognostic model was found to be closely correlated with immunotherapy-related anti-cancer immunity and inflamed tumor microenvironment. Functional enrichment results demonstrated that differentially expressed genes between 2 NRC groups were closely correlated with DNA replication, cell-substrate adhesion, Golgi vesicle transport, MAPK signal pathway, and many others. Novel biomarkers were offered for predicting the prognoses of LUAD patients. The NRC score might contribute to guiding LUAD patients with immunotherapy selection.

The association of sex-biased ATRX mutation in female gastric cancer patients with enhanced immunotherapy-related anticancer immunity.

BACKGROUND: Genetic alterations have been proven to be the promising biomarkers for ICI response. However, sex biases in genetic alterations have been often ignored in the field of immunotherapy, which might specially influence the anticancer immunity and immunotherapy efficacy in male or female patients. Here, we have systematically evaluated the effect of the sex biases in somatic mutation of gastric cancer (GC) patients on the anticancer immunity and clinical benefit to immunotherapy. METHODS: Genomic and transcriptomic data of gastric cancer were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). We also obtained the genomic and clinical data of a MSKCC ICI-treated cohort from cbioportal database. GC male and female-derived tumor somatic mutation profiles were compared by maftools R package. Single sample gene set enrichment analysis (ssGSEA) was conducted to calculate the score of the anticancer immunity indicators including IFN-γ signaling, cytolytic activity (CYT) and antigen presenting machinery (APM). RESULTS: ATRX was found to mutate more frequently in female GC patients compared to male patients (FDR = 0.0108). Female GC patients with ATRX mutation manifested significantly more MSI-high subtypes, increased TMB and PDL1 expression as well as higher scores of IFN-γ signaling, CYT and APM. Gene set enrichment analysis (GSEA) has shown that ATRX mutation might enhance the immunogenicity and anticancer immunity through affecting DNA damage repair pathways. In the ICI-treated cohort from MSKCC, GC patients with ATRX mutation were associated with prolonged overall survival. When stratifying the entire ICI-treated cohort by sex, female patients with ATRX mutation obtained significantly better survival benefits than that of ATRX mutant male patients (Female patients, HR of ATRX MT vs WT = 0.636, 95%CI = 0.455-0.890, P = 0.023; Male patients, HR of ATRX MT vs WT = 0.929, 95%CI = 0.596-1.362, P = 0.712). CONCLUSIONS: ATRX mutation might serve as a potential predictive biomarker for favorable clinical benefit to ICI in female GC patients. ATRX mutation could be applied in combination with other biomarkers of ICI response to better identify the female GC patients who will derive greater benefits from ICI therapy.

Role of endothelin receptor type B (EDNRB) in lung adenocarcinoma.

BACKGROUND: The five-year survival rate of lung adenocarcinoma patients (LUAD) is very low,and the methods of predicting survival are a great obstacle for LUAD therapies. Endothelin receptor type B (EDNRB) gene is associated with tumorigenesis. In this study, we aimed to evaluate the predictive value of EDNRB on LUAD. METHODS: Survival analyses was performed to assess the correlation between EDNRB expression and survival of LUAD patients from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) datasets. Gene set enrichment analysis (GSEA) was conducted to illustrate possible biological functions of EDNRB. Laboratory methods were used to verify the function of EDNRB in LUAD. RESULTS: The TCGA results showed that a low expression of EDNRB was found in LUAD patients which led to poor outcome and worse survival, compared with the high expression in GSEA results which suggested that expression of EDNRB might be associated with regulation of the ERK pathway. Laboratory results suggested that EDNRB could inhibit the proliferation and migration of LUAD H1299 cells. CONCLUSIONS: EDNRB is a potential prognostic marker for LUAD patients and might exert its functions by regulating the ERK pathway in LUAD.

Weighted Gene Co-Expression Network Analysis Identifies Hub Genes Associated with Occurrence and Prognosis of Oral Squamous Cell Carcinoma.

BACKGROUND The aim of this study was to identify biomarkers closely related to the pathogenesis and prognosis of oral squamous cell carcinoma (OSCC) by using weighted gene co-expression network analysis (WGCNA) based on integrative transcriptome datasets. MATERIAL AND METHODS Gene expression profiles of OSCC were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained and we then performed with Gene ontology (GO) and pathway enrichment analysis as well as protein-protein interactions (PPI) network analysis. WGCNA was used to construct the co-expression network. Multipart results were intersected to acquire the candidate genes, and survival analysis was used to identify the hub genes. RESULTS A total of 568 DEGs, including 272 upregulated genes and 296 downregulated genes, were identified. GO and pathway analyses revealed that these DEGs were mainly enriched in extracellular matrix (ECM), ECM organization, structural constituent of muscle, and ECM-receptor interaction. The PPI network of DEGs was established, comprising 428 nodes and 1944 edges. In the co-expression network, pink module was the key module, in which 34 genes with high connectivity were identified. After the intersection of multipart results, 24 common genes were chosen as the candidate genes, among which 7 hub genes (PLAU, SERPINE1, LAMC2, ITGA5, TGFBI, FSCN1, and HLF) were identified using survival analysis. CONCLUSIONS Seven potential biomarkers were identified as being closely related with the initiation and prognosis of OSCC and might serve as potential targets for early diagnosis and personalized therapy of OSCC.

The nationwide distribution and trends of hepatitis C virus genotypes in mainland China.

Comprehensive data on hepatitis C virus (HCV) genotypes distribution is critical for treatment regimen selection, vaccine design, and drug development. This study aimed to understand the dynamic distribution of HCV genotypes in Mainland China. Three hundred sixty-two studies published from January 1993 to December 2017 involving 64 891 samples (5133 injecting drug users, 2748 volunteer blood donors, 1509 former paid plasma donors, 160 sexually encounters, and 1992 human immunodeficiency virus (HIV)/HCV coinfection patients) were eligible for the quantitative synthesis estimation. Pooled proportion of HCV genotypes (and 95% confidence intervals [CIs]) was estimated through the Freeman-Tukey double arcsine transformation by period, region, and risk group. A sharp decline of the subtype 1b was observed in all regions except in northwestern and central regions. The genotypes 3 and 6 showed an obvious increase in southern and southwestern regions and have already spread nationwide. After 2010, subtype 1b was the most dominant variant in all regions and risk groups, accounting for 54.0% (95% CI, 51.9-56.1) of all national infections. Subtype 2a was the second most prevalent strain in all regions except in the south and southwest, with 15.4% (95% CI, 13.1-17.8) national infections. The subtype 6a in southern region and 3b and 3a in southwestern region had a higher proportion of infections than that in other regions. In addition, the genotypes 3 and 6 are already prevalent in almost all risk groups. The distribution of HCV genotypes were sharply shifting in China in the past three decades. The HCV subtype 1b posed a sharp decline, whereas genotypes 3 and 6 played an increasing role in the regional and populational HCV pandemic.

Novel catalytic micromotor of porous zeolitic imidazolate framework-67 for precise drug delivery.

Micromotors hold promise as drug carriers for targeted drug delivery owing to the characteristics of self-propulsion and directional navigation. However, several defects still exist, including high cost, short movement life, low drug loading and slow release rate. Herein, a novel catalytic micromotor based on porous zeolitic imidazolate framework-67 (ZIF-67) synthesized by a greatly simplified wet chemical method assisted with ultrasonication is described as an efficient anticancer drug carrier. These porous micromotors display effective autonomous motion in hydrogen peroxide and long durable movement life of up to 90 min. Moreover, the multifunctional micromotor ZIF-67/Fe3O4/DOX exhibits excellent performance in precise drug delivery under external magnetic field with high drug loading capacity of fluorescent anticancer drug DOX up to 682 µg mg-1 owing to its porous nature, high surface area and rapid drug release based on dual stimulus of catalytic reaction and solvent effects. Therefore, these porous ZIF-67-based catalytic micromotors combine the domains of metal-organic frameworks (MOFs) and micomotors, thus developing potential resources for micromotors and holding great potential as label-free and precisely controlled high-quality candidates of drug delivery systems for biomedical applications.