Physicochemical and digestive properties of corn starch nanoparticles incorporated different polyphenols.

The corn starch nanoparticles were prepared by incorporating three kinds of polyphenols, including quercetin, proanthocyanidins and tannin acid. The physicochemical and digestive properties of corn starch nanoparticles were researched. The quercetin showed a higher complexation index than proanthocyanidins and tannin acid when they complexed with corn starch. The mean size of corn starch quercetin, proanthocyanidins and tannin acid were 168.5 nm, 179.1 nm and 188.6 nm, respectively. XRD results indicated that all the corn starch-polyphenols complex showed V-type crystalline structure, the crystallinity of corn starch-quercetin complex was 19.31 %, which showed more formation of amylose-quercetin single helical formed than the other two starch-polyphenol complexes. In vitro digestion revealed that polyphenols could resist digestion and quercetin increased the content of resistant starch from 23.32 % to 35.24 % and polyphenols can form complexes with starch through hydrophobic interactions or hydrogen bonding. This study indicated the hydrophobic polyphenols had a more significant effect on the digestibility of corn starch. And the cell toxicity assessments demonstrated that all nanoparticles were nontoxic and biocompatible.

CD274 (PD-L1) negatively regulates M1 macrophage polarization in ALI/ARDS.

Background: Acute lung injury (ALI)/severe acute respiratory distress syndrome (ARDS) is a serious clinical syndrome characterized by a high mortality rate. The pathophysiological mechanisms underlying ALI/ARDS remain incompletely understood. Considering the crucial role of immune infiltration and macrophage polarization in the pathogenesis of ALI/ARDS, this study aims to identify key genes associated with both ALI/ARDS and M1 macrophage polarization, employing a combination of bioinformatics and experimental approaches. The findings could potentially reveal novel biomarkers for the diagnosis and management of ALI/ARDS. Methods: Gene expression profiles relevant to ALI were retrieved from the GEO database to identify co-upregulated differentially expressed genes (DEGs). GO and KEGG analyses facilitated functional annotation and pathway elucidation. PPI networks were constructed to identify hub genes, and differences in immune cell infiltration were subsequently examined. The expression of hub genes in M1 versus M2 macrophages was evaluated using macrophage polarization datasets. The diagnostic utility of CD274 (PD-L1) for ARDS was assessed by receiver operating characteristic (ROC) analysis in a validation dataset. Experimental confirmation was conducted using two LPS-induced M1 macrophage models and an ALI mouse model. The role of CD274 (PD-L1) in M1 macrophage polarization and associated proinflammatory cytokine production was further investigated by siRNA-mediated silencing. Results: A total of 99 co-upregulated DEGs were identified in two ALI-linked datasets. Enrichment analysis revealed that these DEGs were mainly involved in immune-inflammatory pathways. The following top 10 hub genes were identified from the PPI network: IL-6, IL-1ß, CXCL10, CD274, CCL2, TLR2, CXCL1, CCL3, IFIT1, and IFIT3. Immune infiltration analysis revealed a significantly increased abundance of M1 and M2 macrophages in lung tissue from the ALI group compared to the control group. Subsequent analysis confirmed that CD274 (PD-L1), a key immunological checkpoint molecule, was highly expressed within M1 macrophages. ROC analysis validated CD274 (PD-L1) as a promising biomarker for the diagnosis of ARDS. Both in vitro and in vivo experiments supported the bioinformatics analysis and confirmed that the JAK-STAT3 pathway promotes CD274 (PD-L1) expression on M1 macrophages. Importantly, knockdown of CD274 (PD-L1) expression potentiated M1 macrophage polarization and enhanced proinflammatory cytokines production. Conclusion: This study demonstrates a significant correlation between CD274 (PD-L1) and M1 macrophages in ALI/ARDS. CD274 (PD-L1) functions as a negative regulator of M1 polarization and the secretion of proinflammatory cytokines in macrophages. These findings suggest potential new targets for the diagnosis and treatment of ALI/ARDS.

Targeting TYK2 alleviates Rab27A-induced malignant progression of non-small cell lung cancer via disrupting IFNα-TYK2-STAT-HSPA5 axis.

Rab27A is a small GTPase-mediating exosome secretion, which participates in tumorigenesis of multiple cancer types. Understanding the biological role of Rab27A in non-small cell lung cancer (NSCLC) is of great importance for oncological research and clinical treatment. In this study, we investigate the function and internal mechanism of Rab27A in NSCLC. Results show that Rab27A is overexpressed in NSCLC, and regulates the tumor proliferation, migration, invasion, and cell motility in vitro and in vivo, and is negatively regulated by miR-124. Further research reveals that upregulated Rab27A can induce the production of IFNα in the medium by mediating exosome secretion. Then IFNα activates TYK2/STAT/HSPA5 signaling to promote NSCLC cell proliferation and metastasis. This process can be suppressed by TYK2 inhibitor Cerdulatinib. These results suggest that Rab27A is involved in the pathogenesis of NSCLC by regulating exosome secretion and downstream signaling, and inhibitors targeting this axis may become a promising strategy in future clinical practice.

CADM + : Confusion-Based Learning Framework With Drift Detection and Adaptation for Real-Time Safety Assessment.

Real-time safety assessment (RTSA) of dynamic systems holds substantial implications across diverse fields, including industrial and electronic applications. However, the complexity and rapid flow nature of data streams, coupled with the expensive label cost and pose significant challenges. To address these issues, a novel confusion-based learning framework, termed confusion-and-detection method plus (CADM + ), is proposed in this article. When drift occurs, the model is updated with uncertain samples, which may cause confusion between existing and new concepts, resulting in performance differences. The cosine similarity is used to measure the degree of such conceptual confusion in the model. Furthermore, the change of standard deviation within a fixed-size cosine similarity window is introduced as an indicator for drift detection. Theoretical demonstrations show the asymptotic increase of cosine similarity. In addition, the approximate independence of the change in standard deviation with the number of trained samples is indicated. Finally, the extreme value theory (EVT) is applied to determine the threshold of judging drifts. Several experiments are conducted to verify its effectiveness. Experimental results prove that the proposed framework is more suitable for RTSA tasks compared with state-of-the-art algorithms. The source code is available at https://github.com/THUFDD/CADM-plus.

Two-dimensional inverse problem of fire location in the closed goaf of coal mine based on optical fiber sensors.

Monitoring the temperature to determine the fire source locations is essential for controlling the spontaneous combustion in the goaf. Optical fiber sensors are employed to measure the temperature distribution in the goaf. However, due to changes in the geological conditions and the influence of the falling rocks in the goaf, only sensors on the upper side of the uncompacted goaf, due to inclination and coal pillar, may remain. Unilateral sensors are located on the upper side of the goaf, while fire occurs in the center. To investigate the issue with linear unilateral sensors, a two-dimensional inverse method has been developed to determine the location of fire sources by considering heat transfer after a fire inside the goaf. The equations were theoretically solved using Green's function method to obtain the internal temperature distribution of the physical model of the goaf. Sensitivity analysis identified the most crucial parameters in the process of spontaneous heating at different temperature. The fire source location can be determined using a loop method based on the model calculations. We considered a case to validate the model. Accurately identifying the fire source location in the goaf using the unilateral sensors has an essential theoretical and practical significance for fire prevention and fighting.

Construction of CoNi2S4/Co9S8@Co4S3 nanocubes derived from Ni-Co prussian blue analogues@cobalt carbonate hydroxide core-shell heterostructure for asymmetric supercapacitor.

Construction of Prussian blue analogues (PBAs) with heterostructure is beneficial to preparing PBAs derivatives with superior electrochemical performance. In this work, the core-shell nanostructured nanocubes composed of nickel hexacyanocobalt PBA (NiCo-PBA)@cobalt carbonate hydroxide (CCH) are synthesized through an in-situ epitaxial growth strategy, and the formation mechanisms of coating are carefully validated and specifically discussed. Then, the precursors are successfully transformed into hierarchical CoNi2S4/Co9S8@Co4S3 via the gas-phase vulcanization method. Benefiting from the intriguing heterostructure and multicomponent sulfides, the CoNi2S4/Co9S8@Co4S3-80 electrode exhibits a high specific capacity of 799 ± 16C/g (specific capacitance of 1595 ± 31F/g) at 1 A/g, ultra-high capacity retention of 80 % at a high current density of 20 A/g. The assembled asymmetric supercapacitor (ASC) device delivers a high energy density of 43.3 Wh kg-1 at a power density of 899 W kg-1 and exhibits superior cycling stability with the capacity retention of 88 % after 5,000 cycles. Subsequently, the fabricated all-solid-state ASC device shows an excellent energy density of 36.4 Wh kg-1 with a power density of 824 W kg-1. This work proposing rational design of combining multicomponent sulfides and core-shell heterostructure based on PBA nanocubes opens up a novel route for developing asymmetric supercapacitor electrode materials with superior performance.

Lead-Free Chiral Perovskite for High Degree of Circularly Polarized Light Emission and Spin Injection.

We report a zero-dimensional (0D) lead-free chiral perovskite (S-/R-MBA)4Bi2I10 with a high degree of circularly polarized light (CPL) emission. Our 0D lead-free chiral perovskite exhibits an average degree of circular polarization (DOCP) of 19.8% at 78 K under linearly polarized laser excitation, and the maximum DOCP can reach 25.8%, which is 40 times higher than the highest DOCP of 0.5% in all reported lead-free chiral perovskites to the best of our knowledge. The high DOCP of (S-/R-MBA)4Bi2I10 is attributed to the free exciton emission with a Huang-Rhys factor of 2.8. In contrast, all the lead-free chiral perovskites in prior reports are dominant by self-trapped exciton in which the spin relaxation reduces DOCP dramatically. Moreover, we realize the manipulation of the valley degree of freedom of monolayer WSe2 by using the spin injection of the 0D chiral lead-free perovskites. Our results provide a new perspective to develop lead-free chiral perovskite devices for CPL light source, spintronics, and valleytronics.

Dynamic Submodular-Based Learning Strategy in Imbalanced Drifting Streams for Real-Time Safety Assessment in Nonstationary Environments.

The design of real-time safety assessment (RTSA) approaches in nonstationary environments is meaningful to reduce the possibility of significant losses. However, several challenging problems are needed to be well considered. The performance of existing approaches will be negatively affected in the settings of imbalanced drifting streams. In this case, the model design with the incremental update should also be explored. Furthermore, the query strategy should also be well-designed. This article investigates a dynamic submodular-based learning strategy to address such issues. Specifically, an efficient incremental update procedure is designed with the structure of the broad learning system (BLS), which is beneficial to the detection of concept drift. Furthermore, a novel dynamic submodular-based annotation with an activation interval strategy is proposed to select valuable samples in imbalanced drifting streams. The lower bound of annotation value is also proven theoretically with a novel drift adaption mechanism. Numerous experiments are conducted with the realistic data of JiaoLong deep-sea manned submersible. The experimental results show that the proposed approach can achieve better assessment accuracy than typical existing approaches.

Dynamic Model Interpretation-Guided Online Active Learning Scheme for Real-Time Safety Assessment.

Chunk-level real-time safety assessment of dynamic systems is a critical component of industrial processes, which is essential to prevent hazards and reduce the risk of injury or damage to equipment and facilities, especially in nonstationary environments. In this context, multiple real and complex concept drifts are inevitable in industrial settings, making it crucial to understand their detection and adaptation processes. The incremental learning scheme should also be well considered. However, existing methods have certain limitations in dealing with such issues. In this article, a dynamic model interpretation-guided online active learning scheme, termed a dynamic model interpretation-guided learning scheme (DMI-LS), is proposed. Specifically, the model update strategy with chunk data is designed based on the implementation of the broad learning system. A novel query strategy is then investigated to consider the ranking preference difference, which relies on the interpretation generated by the explainable artificial intelligence method. Several experiments based on the JiaoLong deep-sea manned submersible data are conducted to verify the effects of the proposed DMI-LS. The results show that it outperforms the other advanced existing approaches with different settings in most scenarios.

FTO facilitates cancer metastasis by modifying the m6A level of FAP to induce integrin/FAK signaling in non-small cell lung cancer.

BACKGROUND: Emerging evidence suggests the critical roles of N6-methyladenosine (m6A) RNA modification in tumorigenesis and tumor progression. However, the role of m6A in non-small cell lung cancer (NSCLC) is still unclear. This study aimed to explore the role of the m6A demethylase fat mass and obesity-associated protein (FTO) in the tumor metastasis of NSCLC. METHODS: A human m6A epitranscriptomic microarray analysis was used to identify downstream targets of FTO. Quantitative real-time PCR (qRT‒PCR) and western blotting were employed to evaluate the expression levels of FTO and FAP in NSCLC cell lines and tissues. Gain-of-function and loss-of-function assays were conducted in vivo and in vitro to assess the effects of FTO and FAP on NSCLC metastasis. M6A-RNA immunoprecipitation (MeRIP), RNA immunoprecipitation (RIP), luciferase reporter assays, and RNA stability assays were used to explore the mechanism of FTO action. Co-immunoprecipitation (co-IP) assays were used to determine the mechanism of FAP in NSCLC metastasis. RESULTS: FTO was upregulated and predicted poor prognosis in patients with NSCLC. FTO promoted cell migration and invasion in NSCLC, and the FAK inhibitor defactinib (VS6063) suppressed NSCLC metastasis induced by overexpression of FTO. Mechanistically, FTO facilitated NSCLC metastasis by modifying the m6A level of FAP in a YTHDF2-dependent manner. Moreover, FTO-mediated metastasis formation depended on the interactions between FAP and integrin family members, which further activated the FAK signaling. CONCLUSION: Our current findings provided valuable insights into the role of FTO-mediated m6A demethylation modification in NSCLC metastasis. FTO was identified as a contributor to NSCLC metastasis through the activation of the FAP/integrin/FAK signaling, which may be a potential therapeutic target for NSCLC. Video Abstract.

Emerging evidence suggests the crucial roles of N⁶-methyladenosine (m⁶A) RNA modification in tumorigenesis and progression. Nonetheless, the role of m⁶A in NSCLC remains unclear. The purpose of this study was to investigate the role of m⁶A demethylase fat mass and obesity-associated protein (FTO) in the tumor metastasis of non-small cell lung cancer (NSCLC). Results illustrated that FTO was upregulated and predicted poor prognosis in NSCLC patients. FTO promoted cell migration and invasion in NSCLC, and the FAK inhibitor defactinib (VS6063) suppressed NSCLC metastasis induced by overexpression of FTO. Mechanistically, FTO facilitated NSCLC metastasis by modifying the m⁶A level of FAP in a YTHDF2-dependent manner. Moreover, FTO-mediated metastasis formation depended on the interactions between FAP and integrin family members, which further activated the FAK signaling. Our current findings provided valuable insights into the role of FTO-mediated m⁶A demethylation modification in NSCLC metastasis. FTO was identified as a contributor to NSCLC metastasis through the activation of the FAP/integrin/FAK signaling, which may be a potential therapeutic target for NSCLC.

Corrigendum: Advanced NSCLC patients with EGFR T790M harbouring TP53 R273C or KRAS G12V cannot benefit from osimertinib based on a clinical multicentre study by tissue and liquid biopsy.

[This corrects the article DOI: 10.3389/fonc.2021.621992.].

Coral-like Fe-doped MoO2/C heterostructures with rich oxygen vacancies for efficient electrocatalytic N2 reduction.

Molybdenum (Mo) is one of the most important constituent elements in natural nitrogenase and theoretical calculation results show that Mo-based materials can be used as potential NRR electrocatalysts. The design of advanced catalysts with a special structure is very essential for promoting the development of electrocatalytic N2 into NH3. In this paper, Fe-doped MoO2/C heterostructured nanoparticles with rich oxygen vacancies (Vo) are designed and they exhibit highly efficient catalytic activity for artificial N2 fixation in neutral electrolytes under ambient conditions. The influence of the atomic ratio of the Fe source to the Mo source and the NaBH4 ethanol solution treatment on the structure and electrocatalytic performance are systematically investigated. The Vo-Fe-MoO2/C (1 : 50) catalyst with rich oxygen vacancies shows a satisfactory electrocatalytic N2 reduction reaction (e-NRR) activity in 0.1 M Na2SO4 with a high ammonia yield rate of 15.87 ± 0.3 µg h-1 mg-1 at -0.5 V versus the reversible hydrogen electrode (vs. the RHE) and a FE of 13.4% at -0.3 V (vs. the RHE). According to the results of DFT calculations, the active center of the electro-catalytic nitrogen reduction reaction is the molybdenum atom between the iron atom and the O vacancy. Oxygen vacancies can not only reduce the energy barrier of the RDS but also facilitate the desorption of ammonia and the first step hydrogenation of nitrogen. The doping of Fe will change the electronic state of the Mo atom in MoO2.

Forkhead box L2 is a target of miR-133b and plays an important role in the pathogenesis of non-small cell lung cancer.

BACKGROUND: Forkhead box L2 (FOXL2) has been recognized as a transcription factor in the progression of many malignancies, but its role in non-small cell lung cancer (NSCLC) remains unclear. This research clarified on the role of FOXL2 and the specific molecular mechanism in NSCLC. METHODS: RNA and protein levels were detected by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting assays. Cell proliferation was examined by cell counting kit-8 (CCK-8) and clonogenic assays. Transwell and wound healing assays were used to detect cell invasion and migration. Cell cycle alterations were assessed by flow cytometry. The relationship between FOXL2 and miR-133b was verified by dual-luciferase reporter assays. In vivo metastasis was monitored in the tail vein-injected mice. RESULTS: FOXL2 was upregulated in NSCLC cells and tissues. Downregulation of FOXL2 restrained cell proliferation, migration, and invasion and arrested the cell cycle of NSCLC cells. Moreover, FOXL2 promoted the epithelial-mesenchymal transition (EMT) process of NSCLC cells by inducing the transforming growth factor-ß (TGF-ß)/Smad signaling pathway. miR-133b directly targeted the 3'-UTR of FOXL2 and negatively regulated FOXL2 expression. Knockdown of FOXL2 blocked metastasis in vivo. CONCLUSIONS: miR-133b downregulates FOXL2 by targeting the 3'-UTR of FOXL2, thereby inhibiting cell proliferation, EMT and metastasis induced by the TGF-ß/Smad signaling pathway in NSCLC. FOXL2 may be a potential molecular target for treating NSCLC.

Numerical and experimental study on monitoring coal cracks with PZT sensor.

The rupture of coal pillar can lead to spontaneous combustion or collapse of goaf, which endangers the safety of workers. To explore the relationship between the crack depth of the coal structure and the signal received by the piezoelectric ceramic sensor, the output data of coal samples were analyzed by using the piezoelectric effect, combined with the experiment and ABAQUS simulation. Based on the signal amplitude, the output signal characteristics of the coal model with different crack depths were analyzed, and the evaluation index of coal crack cracking degree (Dc) was defined. The results show that the piezoelectric fluctuation method can effectively identify the local cracks of coal. When the distance between the lead Piezoelectric Transducer (PZT) patch and crack position is constant, the amplitude of the PZT patch output signal will decay with the deepening of the crack depth, while the value of increases with the increase of crack depth. This study provides a theoretical basis for mine disaster prevention and control.

An Online Active Broad Learning Approach for Real-Time Safety Assessment of Dynamic Systems in Nonstationary Environments.

Real-time safety assessment of the complex dynamic systems in nonstationary environments is of great significance for avoiding the potential hazards. In this case, the update procedure with high assessment accuracy and training speed is crucial and meaningful in the dynamic streaming setting. Generally, the performance of most online learning approaches will be negatively affected by limited annotated samples in such a setting. Moreover, the time cost of advanced conventional methods with retaining procedures is relatively high, constraining their practicality. In this article, a novel online active broad learning approach, termed OABL, is proposed. In detail, the effectiveness of the broad learning system in the framework of online active learning is first revealed and verified. A reasonable dynamic asymmetric query strategy is then designed with a limited annotation budget to actively annotate the relatively valuable samples, which is beneficial to mitigating the negative effects of class imbalance. In this context, the advantage of the human-in-the-loop characteristic is also effectively used to control the evolution direction of the learner during the incremental update, which makes it better able to adapt to complex and nonstationary environments. Several related experiments are conducted with the realistic data of JiaoLong deep-sea manned submersible. Results show the effectiveness and practicality of the proposal compared with the existing advanced approaches.

TIF1γ inhibits lung adenocarcinoma EMT and metastasis by interacting with the TAF15/TBP complex.

The molecular underpinnings of lung adenocarcinoma (LUAD) metastasis remain poorly defined. Here, using human LUAD cell lines, we find that transcriptional intermediary factor 1 γ (TIF1γ) binds to TATA box binding protein (TBP) in competition with TBP-associated factor 15 (TAF15) and impedes TAF15/TBP-mediated interleukin 6 (IL-6) transactivation. TIF1γ modifies TAF15 through multi-mono-ubiquitylation and drives nuclear export of TAF15. Functionally, TAF15 accelerates epithelial-mesenchymal transition (EMT) and metastasis of LUAD cells, acting in just the opposite way as TIF1γ. Low TIF1γ or high TAF15 expression levels are shown in metastatic LUAD specimens and correlate with poor survival of individuals with LUAD. Our findings suggest that the TAF15/TBP complex is required for IL-6 activation-induced EMT and invasion, which are inhibited by TIF1γ. This study highlights the crucial interaction between TIF1γ and the TAF15/TBP complex for regulating EMT and metastasis in LUAD.

ChemistGA: A Chemical Synthesizable Accessible Molecular Generation Algorithm for Real-World Drug Discovery.

Many deep learning (DL)-based molecular generative models have been proposed to design novel molecules. These models may perform well on benchmarks, but they usually do not take real-world constraints into account, such as available training data set, synthetic accessibility, and scaffold diversity in drug discovery. In this study, a new algorithm, ChemistGA, was proposed by combining the traditional heuristic algorithm with DL, in which the crossover of the traditional genetic algorithm (GA) was redefined by DL in conjunction with GA, and an innovative backcrossing operation was implemented to generate desired molecules. Our results clearly show that ChemistGA not only retains the strength of the traditional GA but also greatly enhances the synthetic accessibility and success rate of the generated molecules with desired properties. Calculations on the two benchmarks illustrate that ChemistGA achieves impressive performance among the state-of-the-art baselines, and it opens a new avenue for the application of generative models to real-world drug discovery scenarios.

Circ_0039908/miR-let-7c/RRM2 axis was identified played an important role in lung adenocarcinoma by integrated analysis.

Background: Circular RNAs (circRNAs) are shown to play a significant role in cancer initiation and progression by interacting on microRNAs (miRNAs) which act as one kind of competing endogenous RNAs (ceRNAs) for the regulation effect on target gene expressions. This study was performed to explore the prognosis-related circRNAs in lung adenocarcinoma (LUAD) patients by integrated analysis and find the mechanism it worked. Methods: The miRNAs and mRNAs, accompanied with circRNAs expressions were obtained through The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, The cytoHubba app of Cytoscape was used to identify hubgenes. Quantitative real-time PCR (q-RT PCR) was performed to identify the expression of circRNA, miRNA and mRNA, Cell Counting Kit-8 (CCK-8) and clone formation assays were used to evaluate the proliferation ability of different kinds of cells in vitro. Transwell assays were utilized to assess the motility of tumor cells. Results: Finally, circRNA_0039908/let7c-5p/RRM2 axis was identified in our research, it can play an important role in the LUAD pathogenesis progression and we found that the proliferation, invasion and migration abilities of LUAD cells can be suppressed after knockdown of circRNA_0039908. This work indicates that circRNA_0039908/let7c-5p/RRM2 axis may be a promising target in the prognosis and treatment of LUAD patients. Conclusions: Circ_0039908/miR-let-7c/RRM2 axis can promote the ability of proliferation, migration and invasion of LUAD cells.

Finding Asymptomatic Spreaders in a COVID-19 Transmission Network by Graph Attention Networks.

In the COVID-19 epidemic the mildly symptomatic and asymptomatic infections generate a substantial portion of virus spread; these undetected individuals make it difficult to assess the effectiveness of preventive measures as most epidemic prevention strategies are based on the detected data. Effectively identifying the undetected infections in local transmission will be of great help in COVID-19 control. In this work, we propose an RNA virus transmission network representation model based on graph attention networks (RVTR); this model is constructed using the principle of natural language processing to learn the information of gene sequence and using a graph attention network to catch the topological character of COVID-19 transmission networks. Since SARS-CoV-2 will mutate when it spreads, our approach makes use of graph context loss function, which can reflect that the genetic sequence of infections with close spreading relation will be more similar than those with a long distance, to train our model. Our approach shows its ability to find asymptomatic spreaders both on simulated and real COVID-19 datasets and performs better when compared with other network representation and feature extraction methods.

LINC02535/miR-30a-5p/GALNT3 axis contributes to lung adenocarcinoma progression via the NF- κ B signaling pathway.

Long non-coding RNAs (LncRNA) play important roles in multiple types of cancers. We addressed the role of LINC02535 by regulating the miR-30a-5p /GalNAc Transferase 3 (GALNT3) axis to promote the proliferation, migration, and invasion in lung adenocarcinoma (LUAD) cells. The Cancer Genome Atlas (TCGA) database screened differentially expressed lncRNAs. Quantitative real-time PCR analysis (qRT-PCR) confirmed that LINC02535 is highly expressed in LUAD tissues and cells. In vitro experiments showed that LINC02535 promotes the proliferation, migration, and invasion of LUAD cells. A xenograft mouse model was used to show that LINC02535 promotes tumor growth in vivo. RNA immunoprecipitation (RIP) and Dual-luciferase reporter assay results confirmed that LINC02535 targets miR-30a-5p. The Vicia villosa lectin (VVA) pull-down assay indicated that MUC1 is the glycosylation target of GALNT3, and western blot verified that NF-κB is the downstream signaling pathway of MUC1. We found that LINC02535 was increased in LUAD tissues and cells, and LINC02535 was correlated with the poor prognosis of LUAD patients. miR-30a-5p acts as a tumor suppressor in LUAD by targeting GALNT3. We also demonstrated that LINC02535 might function as the sponge of miR-30a-5p to up-regulate GALNT3, and consequently promote the proliferation and metastasis of LUAD. LINC02535 acts as a competing endogenous RNA (ceRNA) to interact with miR-30a-5p, thereby upregulating the expression of GALNT3, enhancing the function of MUC1, and activating the NF-κB signaling pathway, promoting the malignant progression of LUAD cells.Abbreviations: LncRNA:long non-coding RNA; LUAD: lung adenocarcinoma; TCGA: The Cancer Genome Atlas; GALNT3: GalNAc Transferase 3; qRT-PCR: quantitative real-time PCR analysis; RIP: RNA immunoprecipitation; SPF: specific pathogen-free; VVA: Vicia villosa lectin; ceRNA: competing endogenous RNA; MiRNAs: microRNAs; FBS: fetal bovine serum; PBS: Phosphate buffered saline; CCK-8: Cell Counting Kit-8; NSCLC: non-small cell lung cancer; OC: ovarian cancer; HCC: hepatocellular carcinoma.