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The Hall effect has played a vital role in unraveling the intricate properties of electron transport in solid materials. Here, we report on a crystal symmetry-dependent in-plane Hall effect (CIHE) observed in a CuPt/CoPt ferromagnetic heterostructure. Unlike the planar Hall effect (PHE), the CIHE in CuPt/CoPt strongly depends on the current flowing direction (ÏI) with respect to the crystal structure. It reaches its maximum when the current is applied along the low crystal-symmetry axes and vanishes when applied along the high crystal-symmetry axes, exhibiting an unconventional angular dependence of cos(3ÏI). Utilizing a symmetry analysis based on the Invariant Theory, we demonstrate that the CIHE can exist in magnetic crystals possessing C3v symmetry. Using a tight-binding model and realistic first-principles calculations on the metallic heterostructure, we find that the CIHE originates from the trigonal warping of the Fermi surface. Our observations highlight the critical role of crystal symmetry in generating new types of Hall effects.
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BACKGROUND: Sunitinib has emerged as the primary treatment for advanced or metastatic clear cell renal cell carcinoma (ccRCC) due to its significant improvement in patients' average survival time. However, drug resistance and adverse effects of sunitinib pose challenges to its clinical benefits. METHODS: The differentially expressed genes (DEGs) associated with sunitinib sensitivity and resistance in ccRCC were investigated. Cell counting kit-8, plate colony formation, flow cytometry and subcutaneous xenograft tumor model assays were employed to explore the effects of PDZK1 on ccRCC. Further research on the molecular mechanism was conducted through western blot, co-immunoprecipitation, immunofluorescence co-localization and immunohistochemical staining. RESULTS: We elucidated that PDZK1 is significantly downregulated in sunitinib-resistant ccRCC specimens, and PDZK1 negatively regulates the phosphorylation of PDGFR-ß and the activation of its downstream pathways through interaction with PDGFR-ß. The dysregulated low levels of PDZK1 contribute to inadequate inhibition of cell proliferation, tumor growth, and insensitivity to sunitinib treatment. Notably, our preclinical investigations showed that miR-15b antagomirs enhance sunitinib cytotoxic effects against ccRCC cells by upregulating PDZK1 levels, suggesting their potential in overcoming sunitinib resistance. CONCLUSIONS: Our findings establish the miR-15b/PDZK1/PDGFR-ß axis as a promising therapeutic target and a novel predictor for ccRCC patients' response to sunitinib treatment.
Subject(s)
Carcinoma, Renal Cell , Drug Resistance, Neoplasm , Kidney Neoplasms , Receptor, Platelet-Derived Growth Factor beta , Sunitinib , Sunitinib/pharmacology , Sunitinib/therapeutic use , Carcinoma, Renal Cell/drug therapy , Carcinoma, Renal Cell/genetics , Carcinoma, Renal Cell/pathology , Carcinoma, Renal Cell/metabolism , Humans , Receptor, Platelet-Derived Growth Factor beta/metabolism , Receptor, Platelet-Derived Growth Factor beta/genetics , Kidney Neoplasms/drug therapy , Kidney Neoplasms/pathology , Kidney Neoplasms/genetics , Kidney Neoplasms/metabolism , Animals , Drug Resistance, Neoplasm/genetics , Mice , Cell Line, Tumor , Cell Proliferation/drug effects , Xenograft Model Antitumor Assays , MicroRNAs/genetics , Signal Transduction/drug effects , Antineoplastic Agents/pharmacology , Antineoplastic Agents/therapeutic use , Female , Gene Expression Regulation, Neoplastic/drug effects , Male , Mice, Nude , Membrane Proteins/genetics , Membrane Proteins/metabolismABSTRACT
Metabolic/bariatric surgery as a treatment for obesity and related diseases, such as type 2 diabetes mellitus (T2DM), has been increasingly recognised in recent years. However, compared with conventional pharmacologic therapy, the long-term effect (≥ 5 years) of metabolic surgery in T2DM patients is still unclear. This study aimed to evaluate the diabetes remission rate, incidence of diabetic microvascular complications, incidence of macrovascular complications, and mortality in T2DM patients who received metabolic surgery versus pharmacologic therapy more than 5 years after the surgery. Searching the database, including PubMed, Embase, Web of Science, and Cochrane Library from the inception to recent (2024), for randomised clinical trials (RCTs) or cohort studies comparing T2DM patients treated with metabolic surgery versus pharmacologic therapy reporting on the outcomes of the diabetes remission rate, diabetic microvascular complications, macrovascular complications, or mortality over 5 years or more. A total of 15 articles with a total of 85,473 patients with T2DM were eligible for review and meta-analysis in this study. There is a significant long-term increase in diabetes remission for metabolic surgery compared with conventional medical therapy in the overall pooled estimation and RCT studies or cohort studies separately (overall: OR = 4.58, 95% CI: 1.89-11.07, P < 0.001). Significant long-term decreases were found in the pooled results of microvascular complications incidence (HR = 0.57, 95% CI: 0.41-0.78, P < 0.001), macrovascular complications incidence (HR = 0.59, 95% CI: 0.50-0.70, P < 0.001) and mortality (HR = 0.53, 95% CI: 0.53-0.79, P = 0.0018). Metabolic surgery showed more significant long-term effects than pharmacologic therapy on diabetes remission, macrovascular complications, microvascular complications incidence, and all-cause mortality in patients with T2DM using currently available evidence. More high-quality evidence is needed to validate the long-term effects of metabolic surgery versus conventional treatment in diabetes management.
Subject(s)
Bariatric Surgery , Diabetes Mellitus, Type 2 , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/surgery , Diabetes Mellitus, Type 2/complications , Humans , Bariatric Surgery/methods , Hypoglycemic Agents/therapeutic use , Obesity/complications , Obesity/surgery , Prognosis , Treatment OutcomeABSTRACT
Biomedical relation extraction has long been considered a challenging task due to the specialization and complexity of biomedical texts. Syntactic knowledge has been widely employed in existing research to enhance relation extraction, providing guidance for the semantic understanding and text representation of models. However, the utilization of syntactic knowledge in most studies is not exhaustive, and there is often a lack of fine-grained noise reduction, leading to confusion in relation classification. In this paper, we propose an attention generator that comprehensively considers both syntactic dependency type information and syntactic position information to distinguish the importance of different dependency connections. Additionally, we integrate positional information, dependency type information, and word representations together to introduce location-enhanced syntactic knowledge for guiding our biomedical relation extraction. Experimental results on three widely used English benchmark datasets in the biomedical domain consistently outperform a range of baseline models, demonstrating that our approach not only makes full use of syntactic knowledge but also effectively reduces the impact of noisy words.
Subject(s)
Natural Language Processing , Semantics , Data Mining/methods , Algorithms , HumansABSTRACT
Due to the magnetoelastic coupling, the magnetic properties of many flexible magnetic films (such as Fe, Co, and Ni) are sensitive to mechanical stress, which deteriorates the performance of flexible magnetoelectronic devices. We show that by stacking Co and Pt alternatively to form multilayers with strong perpendicular magnetic anisotropy (PMA), both magnetic hysteresis and magnetic domain measurements reveal robust PMA against external stress. As the PMA weakens at increased Co thickness, the magnetic anisotropy is vulnerable to external stress. These results were understood based on a micromagnetic model, which suggests that the strength of magnetoelastic anisotropy with respect to initial effective magnetic anisotropy affects the stress-stability of the film. Although the stress coefficient of magnetoelastic anisotropy is enhanced at reduced Co thickness, the concomitant increase of initial effective magnetic anisotropy guarantees a robust PMA against external stress. Our results provide a route to constructing flexible magnetoelectronic devices with enhanced stress stability.
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Enhancing stalk strength is a crucial strategy to reduce lodging. We identified a maize inbred line, QY1, with superior stalk mechanical strength. Comprehensive analyses of the microstructure, cell wall composition, and transcriptome of QY1 were performed to elucidate the underlying factors contributing to its increased strength. Notably, both the vascular bundle area and the thickness of the sclerenchyma cell walls in QY1 were significantly increased. Furthermore, analyses of cell wall components revealed a significant increase in cellulose content and a notable reduction in lignin content. RNA sequencing (RNA-seq) revealed changes in the expression of numerous genes involved in cell wall synthesis and modification, especially those encoding pectin methylesterase (PME). Variations in PME activity and the degree of methylesterification were noted. Additionally, glycolytic efficiency in QY1 was significantly enhanced. These findings indicate that QY1 could be a valuable resource for the development of maize varieties with enhanced stalk mechanical strength and for biofuel production.
Subject(s)
Carboxylic Ester Hydrolases , Cell Wall , Gene Expression Regulation, Plant , Plant Stems , Zea mays , Zea mays/genetics , Zea mays/metabolism , Cell Wall/metabolism , Cell Wall/genetics , Plant Stems/metabolism , Plant Stems/genetics , Carboxylic Ester Hydrolases/metabolism , Carboxylic Ester Hydrolases/genetics , Lignin/metabolism , Plant Proteins/metabolism , Plant Proteins/genetics , Cellulose/metabolism , TranscriptomeABSTRACT
BACKGROUND: Although most patients with cancer are treated with local therapy (LT), the proportion of late-phase clinical trials investigating local therapeutic interventions is unknown. The purpose of this study was to determine the proportion, characteristics, and trends of phase 3 cancer clinical trials assessing the therapeutic value of LT over time. METHODS: This was a cross-sectional analysis of interventional randomized controlled trials in oncology published from 2002 through 2020 and registered on ClinicalTrials.gov. Trends and characteristics of LT trials were compared to all other trials. RESULTS: Of 1877 trials screened, 794 trials enrolling 584,347 patients met inclusion criteria. A total of 27 trials (3%) included a primary randomization assessing LT compared with 767 trials (97%) investigating systemic therapy or supportive care. Annual increase in the number of LT trials (slope [m] = 0.28; 95% confidence interval [CI], 0.15-0.39; p < .001) was outpaced by the increase of trials testing systemic therapy or supportive care (m = 7.57; 95% CI, 6.03-9.11; p < .001). LT trials were more often sponsored by cooperative groups (22 of 27 [81%] vs. 211 of 767 [28%]; p < .001) and less often sponsored by industry (5 of 27 [19%] vs. 609 of 767 [79%]; p < .001). LT trials were more likely to use overall survival as primary end point compared to other trials (13 of 27 [48%] vs. 199 of 767 [26%]; p = .01). CONCLUSIONS: In contemporary late-phase oncology research, LT trials are increasingly under-represented, under-funded, and evaluate more challenging end points compared to other modalities. These findings strongly argue for greater resource allocation and funding mechanisms for LT clinical trials. PLAIN LANGUAGE SUMMARY: Most people who have cancer receive treatments directed at the site of their cancer, such as surgery or radiation. We do not know, however, how many trials test surgery or radiation compared to drug treatments (that go all over the body). We reviewed trials testing the most researched strategies (phase 3) completed between 2002 and 2020. Only 27 trials tested local treatments like surgery or radiation compared to 767 trials testing other treatments. Our study has important implications for funding research and understanding cancer research priorities.
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Photonic topological states, providing light-manipulation approaches in robust manners, have attracted intense attention. Connecting photonic topological states with far-field degrees of freedom (d.o.f.) has given rise to fruitful phenomena. Recently emerged higher-order topological insulators (HOTIs), hosting boundary states two or more dimensions lower than those of bulk, offer new paradigms to localize or transport light topologically in extended dimensionalities. However, photonic HOTIs have not been related to d.o.f. of radiation fields yet. Here, we report the observation of polarization-orthogonal second-order topological corner states at different frequencies on a designer-plasmonic kagome metasurface in the far field. Such phenomenon stands on two mechanisms, i.e., projecting the far-field polarizations to the intrinsic parity d.o.f. of lattice modes and the parity splitting of the plasmonic corner states in spectra. We theoretically and numerically show that the parity splitting originates from the underlying interorbital coupling. Both near-field and far-field experiments verify the polarization-orthogonal nondegenerate second-order topological corner states. These results promise applications in robust optical single photon emitters and multiplexed photonic devices.
Subject(s)
Fruit , Photons , Female , Pregnancy , HumansABSTRACT
Ultracold atoms in optical lattices form a competitive candidate for quantum computation owing to the excellent coherence properties, the highly parallel operations over spins, and the ultralow entropy achieved in qubit arrays. For this, a massive number of parallel entangled atom pairs have been realized in superlattices. However, the more formidable challenge is to scale up and detect multipartite entanglement, the basic resource for quantum computation, due to the lack of manipulations over local atomic spins in retroreflected bichromatic superlattices. In this Letter, we realize the functional building blocks in quantum-gate-based architecture by developing a cross-angle spin-dependent optical superlattice for implementing layers of quantum gates over moderately separated atoms incorporated with a quantum gas microscope for single-atom manipulation and detection. Bell states with a fidelity of 95.6(5)% and a lifetime of 2.20±0.13 s are prepared in parallel, and then connected to multipartite entangled states of one-dimensional ten-atom chains and two-dimensional plaquettes of 2×4 atoms. The multipartite entanglement is further verified with full bipartite nonseparability criteria. This offers a new platform toward scalable quantum computation and simulation.
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The noble metal-based electrochemical sensor design for efficient and stable formaldehyde(FA) detection is important ongoing research. In this paper, PtPd/Nafion/GCE is prepared by electrochemical cyclic voltammetry deposition method based on electrodepositing nanostructured platinum (Pt)-palladium (Pd) nanoparticles in Nafion film-coated glassy carbon electrode (GCE). The influence of deposition parameters and chemical composition (atomic ratio of Pt and Pd) on the electrochemical behaviour of PtPd/Nafion/GCE has been investigated. PtPd/Nafion/GCE displays a remarked electrocatalytic activity for the oxidation of FA and exhibits a linear relationship in the range of 10-5000µM, with a detection limit of 3.3µM in 0.1 M H2SO4solution. It is proved that the detection performance of PtPd/Nafion/GCE electrode is valuable for further application with low detection limit, wide linear range, favourable selectivity and high response.
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Named entity recognition is a key task in text mining. In the biomedical field, entity recognition focuses on extracting key information from large-scale biomedical texts for the downstream information extraction task. Biomedical literature contains a large amount of long-dependent text, and previous studies use external syntactic parsing tools to capture word dependencies in sentences to achieve nested biomedical entity recognition. However, the addition of external parsing tools often introduces unnecessary noise to the current auxiliary task and cannot improve the performance of entity recognition in an end-to-end way. Therefore, we propose a novel automatic dependency parsing approach, namely the ADPG model, to fuse syntactic structure information in an end-to-end way to recognize biomedical entities. Specifically, the method is based on a multilayer Tree-Transformer structure to automatically extract the semantic representation and syntactic structure in long-dependent sentences, and then combines a multilayer graph attention neural network (GAT) to extract the dependency paths between words in the syntactic structure to improve the performance of biomedical entity recognition. We evaluated our ADPG model on three biomedical domain and one news domain datasets, and the experimental results demonstrate that our model achieves state-of-the-art results on these four datasets with certain generalization performance. Our model is released on GitHub: https://github.com/Yumeng-Y/ADPG.
Subject(s)
Adenosine Diphosphate Glucose , Data Mining , Data Mining/methods , Neural Networks, Computer , SemanticsABSTRACT
Predicting relationships between biological entities can greatly benefit important biomedical problems. Previous studies have attempted to represent biological entities and relationships in Euclidean space using embedding methods, which evaluate their semantic similarity by representing entities as numerical vectors. However, the limitation of these methods is that they cannot prevent the loss of latent hierarchical information when embedding large graph-structured data into Euclidean space, and therefore cannot capture the semantics of entities and relationships accurately. Hyperbolic spaces, such as Poincaré ball, are better suited for hierarchical modeling than Euclidean spaces. This is because hyperbolic spaces exhibit negative curvature, causing distances to grow exponentially as they approach the boundary. In this paper, we propose HEM, a hyperbolic hierarchical knowledge graph embedding model to generate vector representations of bio-entities. By encoding the entities and relations in the hyperbolic space, HEM can capture latent hierarchical information and improve the accuracy of biological entity representation. Notably, HEM can preserve rich information with a low dimension compared with the methods that encode entities in Euclidean space. Furthermore, we explore the performance of HEM in protein-protein interaction prediction and gene-disease association prediction tasks. Experimental results demonstrate the superior performance of HEM over state-of-the-art baselines. The data and code are available at : https://github.com/Nan-ll/HEM.
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Knowledge , Pattern Recognition, Automated , SemanticsABSTRACT
Document-level relation extraction is designed to recognize connections between entities a cross sentences or between sentences. The current mainstream document relation extraction model is mainly based on the graph method or combined with the pre-trained language model, which leads to the relatively complex process of the whole workflow. In this work, we propose biomedical relation extraction based on prompt learning to avoid complex relation extraction processes and obtain decent performance. Particularity, we present a model that combines prompt learning with T5 for document relation extraction, by integrating a mask template mechanism into the model. In addition, this work also proposes a few-shot relation extraction method based on the K-nearest neighbor (KNN) algorithm with prompt learning. We select similar semantic labels through KNN, and subsequently conduct the relation extraction. The results acquired from two biomedical document benchmarks indicate that our model can improve the learning of document semantic information, achieving improvements in the relation F1 score of 3.1% on CDR.
Subject(s)
Algorithms , Semantics , Language , Learning , Natural Language ProcessingABSTRACT
The detection of anomalies in multivariate time-series data is becoming increasingly important in the automated and continuous monitoring of complex systems and devices due to the rapid increase in data volume and dimension. To address this challenge, we present a multivariate time-series anomaly detection model based on a dual-channel feature extraction module. The module focuses on the spatial and time features of the multivariate data using spatial short-time Fourier transform (STFT) and a graph attention network, respectively. The two features are then fused to significantly improve the model's anomaly detection performance. In addition, the model incorporates the Huber loss function to enhance its robustness. A comparative study of the proposed model with existing state-of-the-art ones was presented to prove the effectiveness of the proposed model on three public datasets. Furthermore, by using in shield tunneling applications, we verify the effectiveness and practicality of the model.
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Calcineurin is a Ca2+/calmodulin-dependent phosphatase. It is very important to study the affinity between calcineurin and its substrate or other interacting proteins. Two conserved motifs have been reported on the interactive proteins of calcineurin, namely, the PxIxIT motif and the LxVP motif. Here, we used 5(6)-carboxyfluorescein to fluorescently label the N-terminus of the short peptides derived from the two motifs and then determined the affinity between the protein and polypeptides. Microscale thermophoresis (MST) is very suitable for determining calcineurin with peptides containing the LxVP motif. The Kd values of the binding of calcineurin with NFATc1-YLAVP, NHE1-YLTVP, and A238L-FLCVK peptides were 6.72 ± 0.19 µM, 17.14 ± 0.35 µM, and 15.57 ± 0.10 µM, respectively. The GST pull-down results further confirmed the binding trend of the three peptides to calcineurin. However, fluorescently labeled PxIxIT polypeptides are not suitable for MST due to their own aggregation. We determined the binding affinity of the RCAN1-PSVVVH polypeptide to calcineurin by the fluorescence polarization (FP) method. MST and FP assays are fast and accurate in determining the affinity between protein-peptide interactions. Our research laid the foundation for screening the molecules that affect the binding between calcineurin and its substrates in the future.
Subject(s)
Calcineurin , Calmodulin , Amino Acid Motifs , Calcineurin/chemistry , Calmodulin/metabolism , Fluorescence Polarization , Protein BindingABSTRACT
Calcineurin (CN) controls the immune response by regulating nuclear factor of activated T cells (NFAT). Inhibition of CN function is an effective treatment for immune diseases. The PVIVIT peptide is an artificial peptide based on the NFAT-PxIxIT motif, which exhibits stronger binding to CN. A bioactive peptide (named pep4) that inhibits the CN/NFAT interaction was designed. Pep4 contains a segment of A238L as the linker and the LxVP motif and PVIVIT motif as CN binding sites. Pep4 has strong binding capacity to CN and inhibits CN activity competitively. 11-arginine-modified pep4 (11 R-pep4) inhibits the nuclear translocation of NFAT and reduces the expression of IL-2. 11 R-pep4 improves the pathological characteristics of asthmatic mice to a certain extent. The above results indicated that pep4 is a high-affinity CN inhibitor. These findings will contribute to the discovery of new CN inhibitors and promising immunosuppressive drugs.
Subject(s)
Asthma/drug therapy , Calcineurin/metabolism , NFATC Transcription Factors/antagonists & inhibitors , Peptides/pharmacology , Animals , Asthma/metabolism , Cells, Cultured , Disease Models, Animal , Dose-Response Relationship, Drug , HEK293 Cells , Humans , Male , Mice , Mice, Inbred BALB C , Molecular Structure , NFATC Transcription Factors/metabolism , Peptides/chemical synthesis , Peptides/chemistry , Signal Transduction/drug effects , Structure-Activity RelationshipABSTRACT
OBJECTIVE: Gut flora imbalance characterizes patients with chronic kidney disease (CKD). Although biotic supplementation has been proposed to lessen inflammation and oxidative stress and, thus, reduce the risk of progressive kidney damage and cardiovascular disease, the effects remain controversial. We conducted a meta-analysis to assess the therapeutic benefits of biotics in CKD. METHODS: PubMed, Embase, and Cochrane databases were systematically searched for randomized controlled trials that evaluated any biotic (prebiotic, probiotic, synbiotics) supplements in patients with CKD (CKD, stage 3-4 to end-stage renal disease). Primary endpoints included changes in renal function, markers of inflammation, and oxidative stress. Secondary endpoints included changes in levels of uremic toxins and variations in lipid metabolism. RESULTS: Twenty-three eligible studies included 842 participants. In a pooled-analysis, biotics did not change estimated glomerular filtration rate (mean difference [MD] = 0.08, P = .92) or serum albumin (MD = -0.01, P = .86), although prebiotics reduced serum creatinine (standardized mean difference [SMD] = -0.23, P = .009) and blood urea nitrogen (MD = -6.05, P < .00001). Biotics improved total antioxidative capacity (SMD = 0.37, P = .007) and malondialdehyde (SMD = -0.96, P = .006) and reduced the inflammatory marker interleukin-6 (SMD = -0.30, P = .01) although not C-reactive protein (SMD = -0.22, P = .20). Biotic intervention reduced some uremic toxins, including p-cresol sulfate (SMD = -2.18, P < .0001) and indoxyl sulfate (MD = -5.14, P = .0009), which decreased in dialysis-dependent patients. Another toxin, indole-3-acetic acid (MD = -0.22, P = .63), did not change. Lipids were unaffected by biotic intervention (total cholesterol: SMD = -0.01, P = .89; high-density lipoprotein: SMD = -0.08, P = .76; low-density lipoprotein: MD = 3.54, P = .28; triglyceride: MD = -2.26, P = .58). CONCLUSION: The results highlight the favorable influence of biotics on circulating markers of creatinine, oxidant stress (malondialdehyde, total antioxidative capacity), inflammation (interleukin-6), and uremic toxins (p-cresol sulfate) in patients with CKD. Biotics did not affect estimated glomerular filtration rate, albumin, indole-3-acetic acid, or lipids in either predialysis or dialysis patients.
Subject(s)
Renal Insufficiency, Chronic , Synbiotics , Humans , Prebiotics , Randomized Controlled Trials as Topic , Renal Insufficiency, Chronic/complications , Renal Insufficiency, Chronic/therapy , Uremic ToxinsABSTRACT
In recent years, although Immune Checkpoint Inhibitors (ICIs) significantly improves survival both in local advanced stage and advanced stage of non-small cell lung cancer (NSCLC), the objective response rate of ICI monotherapy is still only about 20%. Thus, to identify the mechanisms of ICI resistance is critical to increase the efficacy of ICI treatments. By bioinformatics analysis, we found that the expression of regulator of chromosome condensation 1 (RCC1) in lung adenocarcinoma was significantly higher than that in normal lung tissue in TCGA and Oncomine databases. The survival analysis showed that high expression RCC1 was associated with the poor prognosis of NSCLC. And the expression of RCC1 was inversely related to the number of immune cell infiltration. In vitro, knockdown of RCC1 not only significantly inhibited the proliferation of lung adenocarcinoma cells but also increased the expression levels of p27kip1 and PD-L1, and decreased the expression level of CDK4 and p-Rb. In vivo, knockdown of RCC1 significantly slowed down the growth rate of tumour, and further reduced the volume and weight of tumour model after treated by PD-L1 monoclonal antibody. Therefore, RCC1 could up-regulate the expression level of PD-L1 by regulating p27kip1 /CDK4 pathway and decrease the resistance to ICIs. And this study might provide a new way to increase the efficacy of PD-L1 monoclonal antibody by inhibiting RCC1.
Subject(s)
B7-H1 Antigen/metabolism , Carcinoma, Non-Small-Cell Lung/drug therapy , Cell Cycle Proteins/antagonists & inhibitors , Cyclin-Dependent Kinase 4/metabolism , Cyclin-Dependent Kinase Inhibitor p27/metabolism , Gene Expression Regulation, Neoplastic/drug effects , Guanine Nucleotide Exchange Factors/antagonists & inhibitors , Immunotherapy/methods , Nuclear Proteins/antagonists & inhibitors , Adenocarcinoma of Lung/drug therapy , Adenocarcinoma of Lung/immunology , Adenocarcinoma of Lung/metabolism , Adenocarcinoma of Lung/pathology , Adult , Aged , Animals , Apoptosis , B7-H1 Antigen/genetics , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Carcinoma, Non-Small-Cell Lung/immunology , Carcinoma, Non-Small-Cell Lung/metabolism , Carcinoma, Non-Small-Cell Lung/pathology , Cell Cycle Proteins/genetics , Cell Cycle Proteins/metabolism , Cell Movement , Cell Proliferation , Cyclin-Dependent Kinase 4/genetics , Cyclin-Dependent Kinase Inhibitor p27/genetics , Female , Guanine Nucleotide Exchange Factors/genetics , Guanine Nucleotide Exchange Factors/metabolism , Humans , Lung Neoplasms/drug therapy , Lung Neoplasms/immunology , Lung Neoplasms/metabolism , Lung Neoplasms/pathology , Male , Mice , Mice, Inbred C57BL , Middle Aged , Nuclear Proteins/genetics , Nuclear Proteins/metabolism , Prognosis , Survival Rate , Tumor Cells, Cultured , Xenograft Model Antitumor Assays , Young AdultABSTRACT
BACKGROUND: The rhomboids are a family of multi-transmembrane proteins, many of which have been implicated in facilitating tumor progression. Little is yet known, however, about rhomboid-associated biomarkers in cancers. An analysis of such biomarkers could yield important insights into the role of the rhomboids in cancer pathology. METHODS: In this study, we carried out the univariate Cox regression analysis and compared gene expression patterns of several rhomboid genes in 30 types of cancers by using The Cancer Genome Atlas (TCGA) database and the methods delineated in Gene Expression Profiling Interactive Analysis (GEPIA). We then used datasets GSE47032, GSE126964, GSE68417 and 75 paired pathological specimens to verify the influences of the rhomboid genes in cancer progression. Moreover, we carried out Weighted Gene Correlation Network Analysis (WGCNA) to investigate gene-related functions and we exploited potential correlations between rhomboid genes expression and immune cell infiltration in cancer tissues. Furthermore, we constructed gene-knockdown cancer cell lines to investigate rhomboid gene functions. RESULTS: We find that kidney renal clear cell carcinoma (KIRC) disease progression is affected by fluctuations in the expression of a number of the rhomboid family of genes and, more specifically, high levels of RHBDF2 gene expression are a good indicator of poor prognosis of the disease, as patients with high RHBDF2 expression levels exhibit less favorable survival rates compared to those with low RHBDF2 levels. Silencing of the RHBDF2 gene in KIRC cell lines leads to significantly diminished cell proliferation and migration; this is in good agreement with the identification of an enhanced presence of a number of cell growth and migration promoting signaling molecules in KIRC tumors. We found that, although high level of RHBDF2 correlated with increased infiltration of lymphocytes in cancer tissues, artificially overexpressed RHBDF2 led to an inhibition of the activity of the infiltrated immune cells through sustaining PD-L1 protein level. Furthermore, we show that RHBDF2 related cell migration and PD-L1 regulation were potentially mediated by EGFR signaling pathway. CONCLUSIONS: RHBDF2 gene functions are correlated to facilitated renal clear cell carcinoma progression and may serve as a critical prognostic biomarker for the disease.
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BACKGROUND: Type 2 diabetes has been associated with increased risk of gynecologic cancers, yet the effect of gestational diabetes mellitus (GDM) on gynecologic cancers is unclear. OBJECTIVES: To examine associations between GDM history and subsequent gynecologic cancers in parous women, and to explore whether gestational hypertension (GH) plays a role in the associations. STUDY DESIGN: The population-based cohort study included 15,941 individuals from the Swedish Twin Registry. The history of GDM and GH was ascertained based on self-reports. Incident cases of gynecologic cancers (including cancers of the cervix, uterus, ovaries and other female genitalia) were obtained from the National Patients Registry and the Swedish Cancer Registry. Generalized estimating equation models were applied to analyze associations between GDM and gynecologic cancers. Stratified analysis was used to explore whether associations between GDM and gynecologic cancers differed by GH. Additive and multiplicative interactions were calculated between GDM and GH. RESULTS: Of all participants, 350 (2.2%) had GDM, and 1762 (11.1%) had incident gynecologic cancers. No statistically significant associations were found between GDM and risks of any gynecologic cancers. However, GDM was associated with an increased risk of ovarian cancer (OR = 5.29, 95% CI: 1.63-17.19) in women with GH. Interactions between GDM and GH were observed on the additive scale (Attributable proportion due to interaction: 0.86, 95% CI 0.42-1.30, P < 0.001). CONCLUSIONS: The associations between GDM and risks of gynecologic cancers were not evident, but the effect of GDM on the risk of ovarian cancer was modified by GH. Further validation in larger cohorts is warranted.