RUNX1, FUS, and ELAVL1-induced circPTPN22 promote gastric cancer cell proliferation, migration, and invasion through miR-6788-5p/PAK1 axis-mediated autophagy.

BACKGROUND: An increasing number of studies have demonstrated the association of circular RNAs (circRNAs) with the pathological processes of various diseases and their involvement in the onset and progression of multiple cancers. Nevertheless, the functional roles and underlying mechanisms of circRNAs in the autophagy regulation of gastric cancer (GC) have not been fully elucidated. METHODS: We used transmission electron microscopy and the mRFP-GFP-LC3 dual fluorescent autophagy indicator to investigate autophagy regulation. The cell counting kit-8 assay, colony formation assay, 5-ethynyl-2'-deoxyuridine incorporation assay, Transwell assay, and Western blot assay were conducted to confirm circPTPN22's influence on GC progression. Dual luciferase reporter assays validated the binding between circPTPN22 and miR-6788-5p, as well as miR-6788-5p and p21-activated kinase-1 (PAK1). Functional rescue experiments assessed whether circPTPN22 modulates PAK1 expression by competitively binding miR-6788-5p, affecting autophagy and other biological processes in GC cells. We investigated the impact of circPTPN22 on in vivo GC tumors using a nude mouse xenograft model. Bioinformatics tools predicted upstream regulatory transcription factors and binding proteins of circPTPN22, while chromatin immunoprecipitation and ribonucleoprotein immunoprecipitation assays confirmed the binding status. RESULTS: Upregulation of circPTPN22 in GC has been shown to inhibit autophagy and promote cell proliferation, migration, and invasion. Mechanistically, circPTPN22 directly binds to miR-6788-5p, subsequently regulating the expression of PAK1, which activates protein kinase B (Akt) and extracellular signal-regulated kinase (Erk) phosphorylation. This modulation ultimately affects autophagy levels in GC cells. Additionally, runt-related transcription factor 1 (RUNX1) negatively regulates circPTPN22 expression, while RNA-binding proteins such as FUS (fused in sarcoma) and ELAVL1 (recombinant ELAV-like protein 1) positively regulate its expression. Inhibition of the autophagy pathway can increase FUS expression, further upregulating circPTPN22 in GC cells, thereby exacerbating the progression of GC. CONCLUSION: Under the regulation of the transcription factor RUNX1 and RNA-binding proteins FUS and ELAVL1, circPTPN22 activates the phosphorylation of Akt and Erk through the miR-6788-5p/PAK1 axis, thereby modulating autophagy in GC cells. Inhibition of autophagy increases FUS, which in turn upregulates circPTPN22, forming a positive feedback loop that ultimately accelerates the progression of GC.

m6A-modified circRNAs: detections, mechanisms, and prospects in cancers.

Circular RNAs (circRNAs) have become a research hotspot in recent years with their universality, diversity, stability, conservativeness, and spatiotemporal specificity. N6-methyladenosine (m6A), the most abundant modification in the eukaryotic cells, is engaged in the pathophysiological processes of various diseases. An increasing amount of evidence has suggested that m6A modification is common in circRNAs and is associated with their biological functions. This review summarizes the effects of m6A modification on circRNAs and their regulation mechanisms in cancers, providing some suggestions of m6A-modified circRNAs in cancer therapy.

Controlling the stability of Pickering emulsions by pH-responsive nanoparticles.

Electrostatic dissipative particle dynamics simulations were conducted to model the interactions between emulsion droplets stabilized by pH-sensitive polyelectrolyte-grafted nanoparticles. Using a steered molecular dynamics approach, a mechanistic study of forced coalescence was performed to probe the resistance between two particle-covered droplets. The degree of ionization of the grafted polyelectrolytes was adjusted to capture the pH responsiveness. The maximal resistance forces were measured to quantitatively discriminate the efficacy of particles in stabilizing emulsions at different degrees of ionization. Through analyzing droplet dynamics, resistance force variation, and electric field, we discovered that the resistance is attributed to direct electrostatic repulsion, the image charge effect near the water-oil interface, and steric hindrance among extended polymers. When the particle density on the droplet surface is relatively low, the increasing resistance forces at higher degrees of ionization can effectively prevent droplet coalescence. Oppositely, the ionization compromises emulsion stability when the particle surface coverage is high. Substantial desorption of particles from the interface was triggered as the degree of ionization increases. This in turn reduces resistance force and facilitates coalescence. Moreover, the nanoparticles prevent coalescence at high surface coverages by forming dense layers at individual interfaces, while the particle bridges straddling two interfaces were found at low surface coverages, which can also keep the droplets apart.

Full Dissolution of the Whole Lithium Sulfide Family (Li2 S8 to Li2 S) in a Safe Eutectic Solvent for Rechargeable Lithium-Sulfur Batteries.

The lithium-sulfur battery is an attractive option for next-generation energy storage owing to its much higher theoretical energy density than state-of-the-art lithium-ion batteries. However, the massive volume changes of the sulfur cathode and the uncontrollable deposition of Li2 S2 /Li2 S significantly deteriorate cycling life and increase voltage polarization. To address these challenges, we develop an ϵ-caprolactam/acetamide based eutectic-solvent electrolyte, which can dissolve all lithium polysulfides and lithium sulfide (Li2 S8 -Li2 S). With this new electrolyte, high specific capacity (1360 mAh g-1 ) and reasonable cycling stability are achieved. Moreover, in contrast to conventional ether electrolyte with a low flash point (ca. 2 °C), such low-cost eutectic-solvent-based electrolyte is difficult to ignite, and thus can dramatically enhance battery safety. This research provides a new approach to improving lithium-sulfur batteries in aspects of both safety and performance.

Structure and Dynamics of Stimuli-Responsive Nanoparticle Monolayers at Fluid Interfaces.

Stimuli-responsive nanoparticles at fluid interfaces offer great potential for realizing on-demand and controllable self-assembly that can benefit various applications. Here, we conducted electrostatic dissipative particle dynamics simulations to provide a fundamental understanding of the microstructure and interfacial dynamics of responsive nanoparticle monolayers at a water-oil interface. The model nanoparticle is functionalized with polyelectrolytes to render the pH sensitivity, which permits further manipulation of the monolayer properties. The monolayer structure was analyzed in great detail through the density and electric field distributions, structure factor, and Voronoi tessellation. Even at a low surface coverage, a continuous disorder-to-order phase transition was observed when the particle's degree of ionization increases in response to pH changes. The six-neighbor particle fraction and bond orientation order parameter quantitatively characterize the structural transition induced by long-range electrostatic interactions. Adding salt can screen the electrostatic interactions and offer additional control on the monolayer structure. The detailed dynamics of the monolayer in different states was revealed by analyzing mean-squared displacements, in which different diffusion regimes were identified. The self-diffusion of individual particles and the collective dynamics of the whole monolayer were probed and correlated with the structural transition. Our results provide deeper insight into the dynamic behavior of responsive nanoparticle surfactants and lay the groundwork for bottom-up synthesis of novel nanomaterials, responsive emulsions, and microdroplet reactors.

Drying mediated orientation and assembly structure of amphiphilic Janus particles.

Amphiphilic Janus particles demonstrate unique assembly structures when dried on a hydrophilic substrate. Particle orientations are influenced by amphiphilicity and Janus balance. A three-stage model is developed to describe the process. Simulation further indicates the dominant force is capillary attraction due to the interface pinning at rough Janus boundaries.

Interfacial adsorption of pH-responsive polymers and nanoparticles.

Using dissipative particle dynamics (DPD), we model the interfacial adsorption of pH-responsive polyelectrolytes and polyelectrolyte-grafted nanoparticles (PNPs) at a planar water-oil interface. The electrostatic interactions in the presence of the dielectric discontinuity across the interface are modeled by exploiting the Groot method, which uses an iterative method to solve the Poisson equation on a uniform grid with distributed charge. We reveal the effects of the pH and salinity of the aqueous solution and the length of the polyelectrolyte on the adsorption behavior of weak polyelectrolytes. The adsorption kinetics is monitored via the trajectory of the center of mass of the polyelectrolyte in the direction normal to the interface. The residence time at the interface and the pair correlation function between the polyelectrolyte and the oil are measured to quantitatively characterize the adsorption. Similar to the weak polyelectrolytes, the influences of pH, salinity and grafted chain length on the adsorption of an individual PNP are explored. Our results show that by grafting polyelectrolytes, the interfacial behavior of the nanoparticles can be tuned by changing the pH and salinity of the solution, which is dictated by the contact angle, the pair correlation function between the particles and the oil, the desorption energy, and the particle morphology at the interface. We also observe that the electrostatic-driven variations in the interfacial activity and morphology of the PNPs are not sensitive to the length of the grafted polyelectrolytes.

CircBRIP1: a plasma diagnostic marker for non-small-cell lung cancer.

BACKGROUND: Circular RNA (circRNA), which has been demonstrated in studies to be abundantly prevalent in tumor cells and bodily fluids and to play a significant role in tumors, has the potential for biological markers to be used to assist tumor diagnosis. This study mainly discusses the potential of circBRIP1 as a biomarker for diagnosing non-small-cell lung cancer (NSCLC). METHODS: First, high-throughput sequencing screened the differentially expressed circBRIP1, and real-time fluorescence quantitative PCR (qRT-PCR) verified its expression in NSCLC. Next, sanger sequencing, agarose gel electrophoresis, RNase R assay, and fluorescence in situ hybridization (FISH) were used to verify its molecular characteristics. The diagnostic value was analyzed by the subject operating characteristic curve (ROC), and the cardinality test was analyzed for correlation with clinicopathological parameters. Finally, we tentatively predicted the downstream miRNA- or RNA-binding protein that may bind to circBRIP1. RESULTS: CircBRIP1 is highly expressed in NSCLC tissues, cells and plasma with good specificity and stability. CircBRIP1 not only can well-distinguish NSCLC patients from benign pulmonary diseases (BPD) patients, healthy individuals and small cell lung cancer (SCLC) patients, but it also has some potential for dynamic monitoring. Combined with the analysis of clinicopathological data, the high level of circRNA expression was related to the degree of tumor differentiation, TNM stage, T stage, lymph node metastasis and distal metastasis in NSCLC patients. In addition, circBRIP1 has a high diagnostic value. CONCLUSIONS: Plasma circBRIP1 is significantly overexpressed in NSCLC patients. It can be used as a sensitive biomarker with unique value for early diagnosis, tumor development and prognosis detection.

Associations of clinical subtypes and bile acid levels of intrahepatic cholestasis of pregnancy with pregnancy outcomes.

Intrahepatic cholestasis of pregnancy (ICP) can lead to many adverse pregnancy outcomes, and the influencing factors remain unclear at present. This study retrospectively analyzed clinical data from 1815 pregnant women with ICP and evaluated the relationship between ICP subtypes, gestational age at onset, and pregnancy outcomes. The results of this study show that during pregnancy, the levels of biochemical indicators (TBA, DBIL and ALT) in the serum of pregnant women initially diagnosed with subtypes of ICP were noted to constantly change, and the subtype of ICP and its severity also changed. The incidence of adverse pregnancy outcomes [meconium-stained amniotic fluid (MSAF), NICU transfer, Apgar score ≤ 7 at 1 min, and preterm birth] in patients with ICP1 (icteric type) was significantly higher than for patients with ICP2, ICP3 or ICP4. The preterm birth rate of early-onset ICP was higher than that of late-onset ICP in ICP1 and ICP3 subtypes. In conclusion, the outcome of pregnancy in women with ICP is closely related to the serum TBA level and ICP subtype, which should be recognized in the clinic.

Circulating circular RNA hsa_circ_0023179 acts as a diagnostic biomarker for non-small-cell lung cancer detection.

BACKGROUND: Lung cancer, the most prevalent cancer-related death worldwide, still lacks the means for early diagnosis. Because of the unique properties of the loop that make it stable in body fluids, circular RNAs (circRNAs) as a biomarker becomes a possibility. This research purposed to explore whether hsa_circ_0023179 can be applied as a possible biomarker for the early diagnosis and prognosis of non-small cell lung cancer (NSCLC). METHODS: hsa_circ_0023179 was screened by high-throughput sequencing of three pairs of NSCLC tissues and their surrounding tissues. Agarose gel electrophoresis (AGE), Sanger sequencing, exonuclease digestion assay, and actinomycin D were used to affirm the molecular properties of circRNA. Precision determination was performed by placement at room temperature and multiple freeze-thawing test for methodological evaluation. The expression of hsa_circ_0023179 in tissues, serum, and cells was determined by quantitative real-time polymerase chain reaction (qRT-PCR) to establish the receiver operating characteristic (ROC) curve to assess the diagnostic efficacy of hsa_circ_0023179. RESULTS: hsa_circ_0023179 conforms to the basic properties of circRNA, and the detection method of hsa_circ_0023179 has good stability and repeatability. Its expression was connected to histological type, TNM stage, lymph node metastasis, and distal metastasis in NSCLC tissues, serum, and cells. Compared with traditional tumor markers with higher sensitivity and specificity. A combined diagnosis can significantly improve the diagnostic value. The decrease in postoperative expression level suggests some potential for dynamic monitoring. CONCLUSION: hsa_circ_0023179 might be a promising novel serum marker for the detection and prediction of NSCLC.

Construction of amidoxime-functionalized magnetic hydroxyapatite with enhanced uranium extraction performance from aqueous solution and seawater.

A novel amidoxime-functionalized magnetic hydroxyapatite (AFNH) was successfuly fabricated to extract uranium from aqueous solution and seawater. The introduction of amidoxime group not only increased the number of active site of AFNH to speed up the adsorption rate and increase the extraction capacity, but also adjusted the optimal extraction pH from 4 to 8, which was beneficial for capturing uranium from seawater. The maximum adsorption capacity and adsorption efficiency at pH 8 were 945.2 mg g-1 and 99.2%, respectively. AFNH still had good removal efficiency (above 90%) after five cycles, indicating the good regeneration of AFNH. After uranium adsorption, AFNH could be easily recycled by magnetic separation due to its magnetism. In simulated seawater, AFNH also showed excellent uranium removal performance with high adsorption efficiency (84.9%) and adsorption capacity (1.70 mg g-1). Furthermore, the 14-day uranium extraction capacity of AFNH in natural seawater could reach 5.93 mg g-1. The SEM, FTIR, XRD and XPS analyses showed that the enhanced uranium extraction performance of AFNH was mainly attributed to electrostatic interaction, complexation and co-precipitation. In conclusion, AFNH was expected to be a candidate as adsorbent with great potential in extracting uranium from seawater.

Efficient separation of uranium(VI) from aqueous solution using magnetic Co/Al layered double oxides coated with carbon dots.

Herein, magnetic layered double oxides coated with carbon dots (MLCs) were synthesized through introducing sodium dodecylbenzene sulfonate and FeCl2 into Co/Al LDH for capturing uranium from aqueous solution. When the molar ratio of Co to Al was 4 : 1, the MLC composite possessed the strongest affinity to uranium(VI) in solution with short equilibrium time (<160 min), high adsorption efficiency (94.31%) and large removal capacity (513.85 mg g-1). The adsorption behavior of MLCs for uranium(VI) was well fitted with Langmuir and pseudo-second-order models, suggesting that the monolayer chemical adsorption was the rate-limiting step. Besides, MLC-3 could be reused by using 0.15 mol L-1 ethylene diamine tetraacetic acid as an eluent and the removal percentage still remained at a high level (>83.3%) after 5 adsorption/desorption cycles. Redox reaction, chemical complexation and electrostatic attraction were proved to play significant roles in uranium(VI) separation. Therefore, MLC-3 could be used as a potential adsorbent in uranium(VI)-containing wastewater treatment due to its excellent adsorption performance for uranium(VI).

Fabrication of phosphoric-crosslinked chitosan@g-C3N4 gel beads for uranium(VI) separation from aqueous solution.

In this work, a novel g-C3N4 filled, phosphoric-crosslinked chitosan gel bead (P-CS@CN) was successfully prepared to adsorb U(VI) from water. The separation performance of chitosan was improved by introducing more functional groups. At pH 5 and 298 K, the adsorption efficiency and adsorption capacity could reach 98.0 % and 416.7 mg g-1, respectively. After adsorption, the morphological structure of P-CS@CN did not change and adsorption efficiency remained above 90 % after 5 cycles. P-CS@CN exhibited an excellent applicability in water environment based on dynamic adsorption experiments. Thermodynamic analyses demonstrated the value of ΔG, manifesting the spontaneity of U(VI) adsorption process on P-CS@CN. The positive values of ΔH and ΔS showed that the U(VI) removal behavior of P-CS@CN was an endothermic reaction, indicating that the increase of temperature was great benefit to the removal. The adsorption mechanism of P-CS@CN gel bead could be summarized as the complexation reaction with the surface functional groups. This study not only developed an efficient adsorbent for the treatment of radioactive pollutants, but also provided a simple and feasible strategy for the modification of chitosan-based adsorption materials.

Decoding Optical Responses of Contact-Printed Arrays of Thermotropic Liquid Crystals Using Machine Learning: Detection and Reporting of Aqueous Amphiphiles with Enhanced Sensitivity and Selectivity.

Surfactants and other amphiphilic molecules are used extensively in household products, industrial processes, and biological applications and are also common environmental contaminants; as such, methods that can detect, sense, or quantify them are of great practical relevance. Aqueous emulsions of thermotropic liquid crystals (LCs) can exhibit distinctive optical responses in the presence of surfactants and have thus emerged as sensitive, rapid, and inexpensive sensors or reporters of environmental amphiphiles. However, many existing LC-in-water emulsions require the use of complicated or expensive instrumentation for quantitative characterization owing to variations in optical responses among individual LC droplets. In many cases, the responses of LC droplets are also analyzed by human inspection, which can miss subtle color or topological changes encoded in LC birefringence patterns. Here, we report an LC-based surfactant sensing platform that takes a step toward addressing several of these issues and can reliably predict concentrations and types of surfactants in aqueous solutions. Our approach uses surface-immobilized, microcontact-printed arrays of micrometer-scale droplets of thermotropic LCs and hierarchical convolutional neural networks (CNNs) to automatically extract and decode rich information about topological defects and color patterns available in optical micrographs of LC droplets to classify and quantify adsorbed surfactants. In addition, we report computational capabilities to determine relevant optical features extracted by the CNN from LC micrographs, which can provide insights into surfactant adsorption phenomena at LC-water interfaces. Overall, the combination of microcontact-printed LC arrays and machine learning provides a convenient and robust platform that could prove useful for developing high-throughput sensors for on-site testing of environmentally or biologically relevant amphiphiles.

Hsa_circ_0000437 promotes pathogenesis of gastric cancer and lymph node metastasis.

Cellular communication between gastric cancer (GC) cells with different metastatic potentials and microenvironments and resultant cancer progression is not fully understood. Circular RNAs (circRNAs) and exosomal circRNAs are known to play extremely important regulatory roles in GC occurrence and progression. Here, we revealed significant differences in coronin-like actin-binding protein 1C (CORO1C) derived circRNA hsa_circ_0000437 between GC and para-cancer tissues. Hsa_circ_0000437 regulated GC cell proliferation, invasion, migration and apoptosis by targeting Ser/Arg-rich splicing factor 3 (SRSF3) and inhibiting programmed cell death 4 (PDCD4). The ectopic expression of hsa_circ_0000437 dramatically promoted tumor growth in nude mice in vivo. Furthermore, both gain-of-function and loss-of-function experiments demonstrated that hsa_circ_0000437 promoted human lymphatic endothelial cells (HLECs) invasion, migration, and tube formation in vitro and also promoted lymphangiogenesis and lymph node metastasis (LNM) in popliteal LNM model in vivo, when it was enriched in GC-secreted exosomes and transferred into HLECs. Mechanistically, exosomal hsa_circ_0000437 induced LNM via HSPA2-ERK signaling pathway independent of VEGF-C. Clinical data showed that exosomal hsa_circ_0000437 was enriched in the serum of GC patients, which was associated with LNM. In summary, these findings highlight the potential role of hsa_circ_0000437 as an outcome biomarker in GC patients with LNM, which may provide a novel target for GC therapy.

Natural Rubber Blend Optimization via Data-Driven Modeling: The Implementation for Reverse Engineering.

Natural rubber formulation methodologies implemented within industry primarily implicate a high dependence on the formulator's experience as it involves an educated guess-and-check process. The formulator must leverage their experience to ensure that the number of iterations to the final blend composition is minimized. The study presented in this paper includes the implementation of blend formulation methodology that targets material properties relevant to the application in which the product will be used by incorporating predictive models, including linear regression, response surface method (RSM), artificial neural networks (ANNs), and Gaussian process regression (GPR). Training of such models requires data, which is equal to financial resources in industry. To ensure minimum experimental effort, the dataset is kept small, and the model complexity is kept simple, and as a proof of concept, the predictive models are used to reverse engineer a current material used in the footwear industry based on target viscoelastic properties (relaxation behavior, tanδ, and hardness), which all depend on the amount of crosslinker, plasticizer, and the quantity of voids used to create the lightweight high-performance material. RSM, ANN, and GPR result in prediction accuracy of 90%, 97%, and 100%, respectively. It is evident that the testing accuracy increases with algorithm complexity; therefore, these methodologies provide a wide range of tools capable of predicting compound formulation based on specified target properties, and with a wide range of complexity.

Design of Multifunctional Nanopore Using Polyampholyte Brush with Composition Gradient.

Molecular organizations and charge patterns inside biological nanopores are optimized by evolution to enhance ionic and molecular transport. Inspired by the nuclear pore complex that employs asymmetrically arranged disordered proteins for its gating, we here design an artificial nanopore coated by an asymmetric polyampholyte brush as a model system to study the asymmetric mass transport under nanoconfinement. A nonequilibrium steady-state molecular theory is developed to account for the intricate charge regulation effect of the weak polyampholyte and to address the coupling between the polymer conformation and the external electric field. On the basis of this state-of-the-art theoretical method, we present a comprehensive theoretical description of the stimuli-responsive structural behaviors and transport properties inside the nanopore with all molecular details considered. Our model demonstrates that by incorporating a gradient of pH sensitivity into the polymer coatings of the nanopore, a variety of asymmetric charge patterns and functional structures can be achieved, in a pH-responsive manner that allows for multiple functions to be implemented into the designed system. The asymmetric charge pattern inside the nanopore leads to an electrostatic trap for major current carriers, which turns the nanopore into an ionic rectifier with a rectification factor above 1000 at optimized pH and salt concentration. Our theory further predicts that the nanopore design behaves like a double-gated nanofluidic device with pH-triggered opening of the gates, which can serve as an ion pump and pH-responsive molecular filter. These results deepen our understanding of asymmetric transport in nanoconfined systems and provide guidelines for designing polymer-coated smart nanopores.

Predicting Critical Micelle Concentrations for Surfactants Using Graph Convolutional Neural Networks.

Surfactants are amphiphilic molecules that are widely used in consumer products, industrial processes, and biological applications. A critical property of a surfactant is the critical micelle concentration (CMC), which is the concentration at which surfactant molecules undergo cooperative self-assembly in solution. Notably, the primary method to obtain CMCs experimentally-tensiometry-is laborious and expensive. In this study, we show that graph convolutional neural networks (GCNs) can predict CMCs directly from the surfactant molecular structure. In particular, we developed a GCN architecture that encodes the surfactant structure in the form of a molecular graph and trained it using experimental CMC data. We found that the GCN can predict CMCs with higher accuracy on a more inclusive data set than previously proposed methods and that it can generalize to anionic, cationic, zwitterionic, and nonionic surfactants using a single model. Molecular saliency maps revealed how atom types and surfactant molecular substructures contribute to CMCs and found this behavior to be in agreement with physical rules that correlate constitutional and topological information to CMCs. Following such rules, we proposed a small set of new surfactants for which experimental CMCs are not available; for these molecules, CMCs predicted with our GCN exhibited similar trends to those obtained from molecular simulations. These results provide evidence that GCNs can enable high-throughput screening of surfactants with desired self-assembly characteristics.

LncRNA HCP5 : A Potential Biomarker for Diagnosing Gastric Cancer.

BACKGROUND: It has been reported that long non-coding RNAs (lncRNAs) can be regarded as a biomarker and had particular clinical significance for early screening and gastric cancer (GC) diagnosis. Therefore, this study aimed to investigate whether serum HCP5 could be a new diagnostic biomarker. METHODS: Filtered out the HCP5 from the GEO database. The specificity of HCP5 was verified by real-time fluorescence quantitative PCR (qRT-PCR), and then the stability of HCP5 was verified by room temperature storage and repeated freeze-thaw experiments. Meanwhile, the accuracy of HCP5 was verified by agarose gel electrophoresis (AGE) and Sanger sequencing. Simultaneously, the expression level of serum HCP5 was detected by qRT-PCR in 98 patients with primary gastric cancer, 21 gastritis patients, 82 healthy donors, and multiple cancer types. Then, the methodology analysis was carried on. Moreover, receiver operating characteristic (ROC) was used to evaluate its diagnostic efficiency. RESULTS: qRT-PCR method had good repeatability and stability in detecting HCP5. The expression level of HCP5 in the serum of gastric cancer patients was remarkably higher than that of healthy controls, and it could distinguish gastritis patients from healthy donors. Besides, the expression of HCP5 was increased dramatically in MKN-45 and MGC-803. The FISH assay showed that HCP5 was mainly distributed in the cytoplasm of MKN-45 and BGC-823 cells. When HCP5 was combined with existing tumor markers, the diagnostic efficiency of HCP5 was the best, and the combined diagnosis of carcinoembryonic antigen (CEA), carbohydrate antigen199 (CA199), and HCP5 can significantly improve the diagnostic sensitivity. Besides, compared with the expression levels of thyroid cancer (THCA), colorectal cancer (CRC), and breast cancer (BRCA), serum HCP5 in gastric cancer was the most specific. Moreover, the high expression of serum HCP5 was related to differentiation, lymph node metastasis, and nerve invasion. The term of serum HCP5 after the operation was significantly lower than that of patients with primary gastric cancer. CONCLUSION: Serum HCP5 can be used as a potential biomarker of non-invasive fluid biopsy, which had a unique value in the early diagnosis, development, and prognosis of gastric cancer.

CAM-DR: Mechanisms, Roles and Clinical Application in Tumors.

Despite the continuous improvement of various therapeutic techniques, the overall prognosis of tumors has been significantly improved, but malignant tumors in the middle and advanced stages still cannot be completely cured. It is now evident that cell adhesion-mediated resistance (CAM-DR) limits the success of cancer therapies and is a great obstacle to overcome in the clinic. The interactions between tumor cells and extracellular matrix (ECM) molecules or adjacent cells may play a significant role in initiating the intracellular signaling pathways that are associated with cell proliferation, survival upon binding to their ligands. Recent studies illustrate that these adhesion-related factors may contribute to the survival of cancer cells after chemotherapeutic therapy, advantageous to resistant cells to proliferate and develop multiple mechanisms of drug resistance. In this review, we focus on the molecular basis of these interactions and the main signal transduction pathways that are involved in the enhancement of the cancer cells' survival. Furthermore, therapies targeting interactions between cancer cells and their environment to enhance drug response or prevent the emergence of drug resistance will also be discussed.