Single-cell and spatial transcriptome sequencing uncover a platinum-resistant cluster overexpressed TACSTD2 in high-grade serous ovarian cancer.

Purpose: Platinum-based chemotherapy is effective but limited by resistance in high-grade serous ovarian cancer (HGSOC). Single-cell RNA sequencing (scRNA-seq) can reveal tumour cell heterogeneity and subclonal differentiation. We aimed to analyze resistance mechanisms and potential targets in HGSOC using scRNA-seq. Methods: We performed 10× genomics scRNA-seq sequencing on tumour tissues from 3 platinum-sensitive and 3 platinum-resistant HGSOC patients. We analyzed cell subcluster communication networks and spatial distribution using cellchat. We performed RNA-seq analysis on TACSTD2, a representative resistance gene in the E0 subcluster, to explore its molecular mechanism. Results: Epithelial cells, characterized by distinct chemotherapy resistance traits and highest gene copy number variations, revealed a specific cisplatin-resistant cluster (E0) associated with poor prognosis. E0 exhibited malignant features related to resistance, fostering growth through communication with fibroblasts and endothelial cells. Spatially, E0 promoted fibroblasts to protect tumour cells and impede immune cells infiltration. Furthermore, TACSTD2 was identified as a representative gene of the E0 subcluster, elucidating its role in platinum resistance through the Rap1/PI3K/AKT pathway. Conclusions: Our study reveals a platinum-resistant epithelial cell subcluster E0 and its association with TACSTD2 in HGSOC, uncovers new insights and evidence for the platinum resistance mechanism, and provides new ideas and targets for the development of therapeutic strategies against TACSTD2+ epithelial cancer cells.

Resting State Brain Networks under Inverse Agonist versus Complete Knockout of the Cannabinoid Receptor 1.

The cannabinoid receptor 1 (CB1) is famous as the target of Δ9-tetrahydrocannabinol (THC), which is the active ingredient of marijuana. Suppression of CB1 is frequently suggested as a drug target or gene therapy for many conditions (e.g., obesity, Parkinson's disease). However, brain networks affected by CB1 remain elusive, and unanticipated psychological effects in a clinical trial had dire consequences. To better understand the whole brain effects of CB1 suppression we performed in vivo imaging on mice under complete knockout of the gene for CB1 (cnr1-/-) and also under the CB1 inverse agonist rimonabant. We examined white matter structural changes and brain function (network activity and directional uniformity) in cnr1-/- mice. In cnr1-/- mice, white matter (in both sexes) and functional directional uniformity (in male mice) were altered across the brain but network activity was largely unaltered. Conversely, under rimonabant, functional directional uniformity was not altered but network activity was altered in cortical regions, primarily in networks known to be altered by THC (e.g., neocortex, hippocampal formation). However, rimonabant did not alter many brain regions found in both our cnr1-/- results and previous behavioral studies of cnr1-/- mice (e.g., thalamus, infralimbic area). This suggests that chronic loss of cnr1 is substantially different from short-term suppression, subtly rewiring the brain but largely maintaining the network activity. Our results help explain why pathological mutations in CB1 (e.g., chronic pain) do not always provide insight into the side effects of CB1 suppression (e.g., clinical depression), and thus urge more preclinical studies for any drugs that suppress CB1.

BMP2-ERK-ATF4 Axis-Based 6-methoxybenzofuran Compound I-9 Acts as Candidate Drug for Bone Formation and Anti-Osteoporosis.

As the global population ages, the number of patients with osteoporosis is rapidly rising. The existing first-line clinical drugs are bone resorption inhibitors that have difficulty restoring the bone mass of elderly patients to the safe range. The range and period of use of existing peptides and monoclonal antibodies are limited, and small-molecule bone formation-promoting drugs are urgently required. We established an I-9 synthesis route with high yield, simple operation, and low cost that was suitable for future large-scale production. I-9 administration promoted bone formation and increased bone mass in mice with low bone mass in an aged C57 mouse model. Our findings revealed a hitherto undescribed pathway involving the BMP2-ERK-ATF4 axis that promotes osteoblast differentiation; I-9 has favorable biosafety in mice. This study systematically investigated the efficacy, safety, and mechanism of I-9 for treating osteoporosis and positions this drug for preclinical research in the future. Thus, this study has promoted the development of small-molecule bone-promoting drugs.

Multi-Omics Research Accelerates the Clarification of the Formation Mechanism and the Influence of Leaf Color Variation in Tea (Camellia sinensis) Plants.

Tea is a popular beverage with characteristic functional and flavor qualities, known to be rich in bioactive metabolites such as tea polyphenols and theanine. Recently, tea varieties with variations in leaf color have been widely used in agriculture production due to their potential advantages in terms of tea quality. Numerous studies have used genome, transcriptome, metabolome, proteome, and lipidome methods to uncover the causes of leaf color variations and investigate their impacts on the accumulation of crucial bioactive metabolites in tea plants. Through a comprehensive review of various omics investigations, we note that decreased expression levels of critical genes in the biosynthesis of chlorophyll and carotenoids, activated chlorophyll degradation, and an impaired photosynthetic chain function are related to the chlorina phenotype in tea plants. For purple-leaf tea, increased expression levels of late biosynthetic genes in the flavonoid synthesis pathway and anthocyanin transport genes are the major and common causes of purple coloration. We have also summarized the influence of leaf color variation on amino acid, polyphenol, and lipid contents and put forward possible causes of these metabolic changes. Finally, this review further proposes the research demands in this field in the future.

Design and synthesis of dabigatran etexilate derivatives with inhibiting thrombin activity for hepatocellular carcinoma treatment.

Hepatocellular carcinoma (HCC) is one of the most fatal solid malignancies worldwide. Evidence suggests that thrombin stimulates tumor progression via fibrin formation and platelet activation. Meanwhile, we also found a correlation between thrombin and HCC through bioinformatics analysis. Dabigatran is a selective, direct thrombin inhibitor that reversibly binds to thrombin. Dabigatran was used as the lead agent in this study, and 19 dabigatran derivatives were designed and synthesized based on docking mode. The thrombin-inhibitory activity of the derivative AX-2 was slightly better than that of dabigatran. BX-2, a prodrug of AX-2, showed a fairly strong inhibitory effect on thrombin-induced platelet aggregation, and effectively antagonized proliferation of HCC tumor cells induced by thrombin at the cellular level. Furthermore, BX-2 reduced tumor volume, weight, lung metastasis, and secondary tumor occurrence in nude mouse models. BX-2 combined with sorafenib increased sorafenib efficacy. This study lays the foundation for discovering new anti-HCC mechanism based on thrombin. BX-2 can be used as an anti-HCC drug lead for further research.

Association of maternal hypertension during pregnancy with brain structure and behavioral problems in early adolescence.

Emerging evidence suggests an association between maternal hypertension during pregnancy and mental health in the offspring. However, less is known about the role of hypertensive pregnancy in behavioral symptoms and brain structures of the offspring as well as in their developmental changes. Here, we utilized neuroimaging and behavioral data from 11,878 participants aged 9-10 years and their 2-year follow-up from the Adolescent Brain Cognitive Development (ABCD) study to investigate the long-term effects of maternal hypertension during pregnancy on early adolescent behavior and brain anatomy. Specifically, adolescents born of mothers with maternal hypertension are at risk of long-lasting behavioral problems, as manifested by higher externalizing and internalizing behavior scores at both 9-10 years and 11-12 years. These participants additionally presented with a higher cortical thickness, particularly in the fronto-parieto-temporal areas at 9-10 years. Four regions, including the left parahippocampus, left lateral orbitofrontal lobe, right superior temporal lobe and right temporal pole, remained thicker 2 years later. These findings were partially validated in rats modeled with Nω-nitro-L-arginine methyl ester (L-NAME) preeclampsia. Therefore, clinicians and women who experience hypertension during pregnancy should be warned of this risk, and healthcare providers should recommend appropriate clinical interventions for pregnancy-induced hypertension.

Single-cell transcriptomics in ovarian cancer identify a metastasis-associated cell cluster overexpressed RAB13.

BACKGROUND: Metastasis, the leading cause of cancer-related death in patients diagnosed with ovarian cancer (OC), is a complex process that involves multiple biological effects. With the continuous development of sequencing technology, single-cell sequence has emerged as a promising strategy to understand the pathogenesis of ovarian cancer. METHODS: Through integrating 10 × single-cell data from 12 samples, we developed a single-cell map of primary and metastatic OC. By copy-number variations analysis, pseudotime analysis, enrichment analysis, and cell-cell communication analysis, we explored the heterogeneity among OC cells. We performed differential expression analysis and high dimensional weighted gene co-expression network analysis to identify the hub genes of C4. The effects of RAB13 on OC cell lines were validated in vitro. RESULTS: We discovered a cell subcluster, referred to as C4, that is closely associated with metastasis and poor prognosis in OC. This subcluster correlated with an epithelial-mesenchymal transition (EMT) and angiogenesis signature and RAB13 was identified as the key marker of it. Downregulation of RAB13 resulted in a reduction of OC cells migration and invasion. Additionally, we predicted several potential drugs that might inhibit RAB13. CONCLUSIONS: Our study has identified a cell subcluster that is closely linked to metastasis in OC, and we have also identified RAB13 as its hub gene that has great potential to become a new therapeutic target for OC.

Efficacy, Mechanism, and Structure-Activity Relationship of 6-Methoxy Benzofuran Derivatives as a Useful Tool for Senile Osteoporosis.

Most patients with senile osteoporosis (SOP) are severely deficient in bone mass, and treatments using bone resorption inhibitors, such as bisphosphonates, have shown limited efficacy. Small-molecule osteogenesis-promoting drugs are required to improve the treatment for this disease. Previously, we demonstrated that a compound with a benzofuran-like structure promoted bone formation by upregulating BMP-2, and it exhibited a therapeutic effect in SAMP-6 mice, glucocorticoid-induced osteoporosis rats, and ovariectomized rats. In this study, aged C57 and SAMP-6 mice models were used to investigate the therapeutic and preventive effects of compound 125 on SOP. scRNA-seq analysis showed that BMP-2 upregulation is the mechanism through which 125 accelerates bone turnover and increases the proportion of osteoblasts. We evaluated the structure-activity relationship of the candidate drugs and found that the derivative I-9 showed significantly higher efficacy than 125 and teriparatide in the zebrafish osteoporosis model. This study provides a foundation for the development of SOP drugs.

MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain.

Segmenting the fine structure of the mouse brain on magnetic resonance (MR) images is critical for delineating morphological regions, analyzing brain function, and understanding their relationships. Compared to a single MRI modality, multimodal MRI data provide complementary tissue features that can be exploited by deep learning models, resulting in better segmentation results. However, multimodal mouse brain MRI data is often lacking, making automatic segmentation of mouse brain fine structure a very challenging task. To address this issue, it is necessary to fuse multimodal MRI data to produce distinguished contrasts in different brain structures. Hence, we propose a novel disentangled and contrastive GAN-based framework, named MouseGAN++, to synthesize multiple MR modalities from single ones in a structure-preserving manner, thus improving the segmentation performance by imputing missing modalities and multi-modality fusion. Our results demonstrate that the translation performance of our method outperforms the state-of-the-art methods. Using the subsequently learned modality-invariant information as well as the modality-translated images, MouseGAN++ can segment fine brain structures with averaged dice coefficients of 90.0% (T2w) and 87.9% (T1w), respectively, achieving around +10% performance improvement compared to the state-of-the-art algorithms. Our results demonstrate that MouseGAN++, as a simultaneous image synthesis and segmentation method, can be used to fuse cross-modality information in an unpaired manner and yield more robust performance in the absence of multimodal data. We release our method as a mouse brain structural segmentation tool for free academic usage at https://github.com/yu02019.

TW-Net: Transformer Weighted Network for Neonatal Brain MRI Segmentation.

Accurate neonatal brain MRI segmentation is valuable for investigating brain growth patterns and tracking the progression of neurodevelopmental disorders. However, it is a challenging task to use intensity-based methods to segment neonatal brain structures because of small contrast differences between brain regions caused by the inherent myelination process. Although convolutional neural networks offer the potential to segment brain structures in an intensity-independent manner, they suffer from lack of in-plane long-range dependency which is essential for the segmentation. To solve this problem, we propose a novel Transformer-Weighted network (TW-Net) to incorporate in-plane long-range dependency information. TW-Net employs a conventional encoder-decoder architecture with a Transformer module in the middle. The Transformer module uses a rotate-and-flip layer to better calculate the similarity between two patches in a slice to leverage similar patterns of geometrical and texture features within brain structures. In addition, a deep supervision module and squeeze-and-excitation blocks are introduced to incorporate boundary information of brain structures. Compared with state-of-the-art deep learning algorithms, TW-Net outperforms these methods for multiple-label tasks in 2D and 2.5D configurations on two independent public datasets, demonstrating that TW-Net is a promising method for neonatal brain MRI segmentation.

Structure-based virtual screening identified novel FOXM1 inhibitors as the lead compounds for ovarian cancer.

Ovarian cancer (OC) is a gynecological tumor with possibly the worst prognosis, its 5-year survival rate being only 47.4%. The first line of therapy prescribed is chemotherapy consisting of platinum and paclitaxel. The primary reason for treatment failure is drug resistance. FOXM1 protein has been found to be closely associated with drug resistance, and inhibition of FOXM1 expression sensitizes cisplatin-resistant ovarian cancer cells. Combining existing first-line chemotherapy drugs with FOXM1 prolongs the overall survival of patients, therefore, FOXM1 is considered a potential therapeutic target in ovarian cancer. Previous research conducted by our team revealed a highly credible conformation of FOXM1 which enables binding by small molecules. Based on this conformation, the current study conducted virtual screening to determine a new structural skeleton for FOXM1 inhibitors which would enhance their medicinal properties. DZY-4 showed the highest affinity towards FOXM1, and its inhibitory effect on proliferation and migration of ovarian cancer at the cellular level was better than or equal to that of cisplatin, while its efficacy was equivalent to that of cisplatin in a nude mouse model. In this study, the anti-tumor effect of DZY-4 is reported for the first time. DZY-4 shows potential as a drug that can be used for ovarian cancer treatment, as well as a drug lead for future research.

A generalizable brain extraction net (BEN) for multimodal MRI data from rodents, nonhuman primates, and humans.

Accurate brain tissue extraction on magnetic resonance imaging (MRI) data is crucial for analyzing brain structure and function. While several conventional tools have been optimized to handle human brain data, there have been no generalizable methods to extract brain tissues for multimodal MRI data from rodents, nonhuman primates, and humans. Therefore, developing a flexible and generalizable method for extracting whole brain tissue across species would allow researchers to analyze and compare experiment results more efficiently. Here, we propose a domain-adaptive and semi-supervised deep neural network, named the Brain Extraction Net (BEN), to extract brain tissues across species, MRI modalities, and MR scanners. We have evaluated BEN on 18 independent datasets, including 783 rodent MRI scans, 246 nonhuman primate MRI scans, and 4601 human MRI scans, covering five species, four modalities, and six MR scanners with various magnetic field strengths. Compared to conventional toolboxes, the superiority of BEN is illustrated by its robustness, accuracy, and generalizability. Our proposed method not only provides a generalized solution for extracting brain tissue across species but also significantly improves the accuracy of atlas registration, thereby benefiting the downstream processing tasks. As a novel fully automated deep-learning method, BEN is designed as an open-source software to enable high-throughput processing of neuroimaging data across species in preclinical and clinical applications.

Magnetic resonance imaging (MRI) is an ideal way to obtain high-resolution images of the whole brain of rodents and primates (including humans) non-invasively. A critical step in processing MRI data is brain tissue extraction, which consists on removing the signal from the non-neural tissues around the brain, such as the skull or fat, from the images. If this step is done incorrectly, it can lead to images with signals that do not correspond to the brain, which can compromise downstream analysis, and lead to errors when comparing samples from similar species. Although several traditional toolboxes to perform brain extraction are available, most of them focus on human brains, and no standardized methods are available for other mammals, such as rodents and monkeys. To bridge this gap, Yu et al. developed a computational method based on deep learning (a type of machine learning that imitates how humans learn certain types of information) named the Brain Extraction Net (BEN). BEN can extract brain tissues across species, MRI modalities, and scanners to provide a generalizable toolbox for neuroimaging using MRI. Next, Yu et al. demonstrated BEN's functionality in a large-scale experiment involving brain tissue extraction in eighteen different MRI datasets from different species. In these experiments, BEN was shown to improve the robustness and accuracy of processing brain magnetic resonance imaging data. Brain tissue extraction is essential for MRI-based neuroimaging studies, so BEN can benefit both the neuroimaging and the neuroscience communities. Importantly, the tool is an open-source software, allowing other researchers to use it freely. Additionally, it is an extensible tool that allows users to provide their own data and pre-trained networks to further improve BEN's generalization. Yu et al. have also designed interfaces to support other popular neuroimaging processing pipelines and to directly deal with external datasets, enabling scientists to use it to extract brain tissue in their own experiments.

Synthesis and antineoplastic activity of ethylene glycol phenyl aminoethyl ether derivatives as FOXM1 inhibitors.

FOXM1 signalling pathways are highly expressed in multiple human cancers. Based on the crystal structure of the FOXM1 DNA binding domain, our preliminary research found ethylene glycol (4-benzyloxyphenyl) cyclopentylaminoethyl ether XST20, which could inhibit ovarian cancer cell proliferation and showed a medium affinity for the truncated protein FOXM1. This study intended to develop a FOXM1 inhibitor with stronger affinity and higher efficiency to be utilized as a molecular tool and drug candidate. We evaluated the optimization direction through molecular docking and systematically modified the structure of XST20. A novel class of ethylene glycol phenyl aminoethyl ether derivatives were synthesized, their anticancer activity and mechanism were evaluated, and the structure-activity relationship was summarized. Compound S2 showed a stronger affinity for FOXM1 and improved its activity with a broad-spectrum anticancer effect. S2 displayed selective antiproliferative activity against cancer cells with high expression levels of FOXM1 proteins. S2 should be a good chemobiological tool and a potential leading compound for future studies of anticancer drugs targeting FOXM1.

Self-adhesive PMIA membranes with chitosan porous beads immobilized pullulanase for efficient biological aging of beer.

A novel pulluanase@chitosan porous beads/Poly (m-phthaloyl-m-phenylenediamine) (PULL@CPB/PMIA) membrane with good separation and biocatalysis properties was prepared by a self-adhesive method by introducing an immobilized enzyme (PULL@CPB) onto the PMIA membrane. The combination of PULL@CPB and PMIA could increase the one-step refining of protoplasmic beer as well as the ability of biocatalysis to lower the alcohol-to-ester ratio. The experimental results showed that the addition of PULL@CPB and the increase in the ratio of EtOH/water in the coagulation bath both increased the load of pullulanase on the membrane surface, while excessive addition decreased the activity of pullulanase. Under the amount of PULL@CPB is 0.5 g·L-1 and the ratio of EtOH/water is 60%, the relative activity of pullulanase in PULL@CPB modified PMIA membrane was the highest, which was 91.7% of the initial activity. The interception rates of protein and macromolecular ß-glucan were 92.2% and 87.3%, respectively, under the condition of beer flux (162.3 L·m-2·h-1). At the same time, the PULL@CPB/PMIA membrane has strong antibacterial performance and thus plays a role in extending the shelf life of beer. Compared with free pullulanase, the thermal stability, pH stability, organic solvent stability, and storing stability of immobilized pullulanase were significantly improved. The effects of PULL@CPB dosage and operating temperature on biocatalysis efficiency were discussed. The immobilized pullulanase activity on the membrane remained at 70.8% after 10 continuous uses. Therefore, the PMIA membrane is an excellent carrier of pullulanase, so its bioactive membrane has a wide range of prospects in food, medicine, and other fields.

Narrative In Situ Visual Analysis for Large-Scale Ocean Eddy Evolution.

The rapid development of high-performance computing systems has led to a rapid increase in the speed of flow field simulation calculations. However, large-scale simulation output data lead to storage bottlenecks and inefficient data analysis. In this work, we used in situ visualization to process the simulation analysis of large-scale flow fields. Combined with narrative visual analysis, we designed a large-scale ocean flow field eddy evolution analysis system based on in situ visualization. Our system can generate high-precision eddy streamline structures in real time and supports eddy statistical analysis and tracking analysis at different ocean regional scales. Through the case data analysis of ocean simulation, we demonstrated the efficiency and effectiveness of the system.

The value of longitudinal clinical data and paired CT scans in predicting the deterioration of COVID-19 revealed by an artificial intelligence system.

The respective value of clinical data and CT examinations in predicting COVID-19 progression is unclear, because the CT scans and clinical data previously used are not synchronized in time. To address this issue, we collected 119 COVID-19 patients with 341 longitudinal CT scans and paired clinical data, and we developed an AI system for the prediction of COVID-19 deterioration. By combining features extracted from CT and clinical data with our system, we can predict whether a patient will develop severe symptoms during hospitalization. Complementary to clinical data, CT examinations show significant add-on values for the prediction of COVID-19 progression in the early stage of COVID-19, especially in the 6th to 8th day after the symptom onset, indicating that this is the ideal time window for the introduction of CT examinations. We release our AI system to provide clinicians with additional assistance to optimize CT usage in the clinical workflow.

EGCG Induces Pro-inflammatory Response in Macrophages to Prevent Bacterial Infection through the 67LR/p38/JNK Signaling Pathway.

Extensive studies focused on the therapeutic efficacy of epigallocatechin-3-gallate (EGCG) against bacterial infection. However, little is known about its prophylactic efficacy against bacterial infection. Herein, we found that EGCG showed an effective prophylactic efficacy against bacterial infection with a broad spectrum, including Gram-negative, Gram-positive, and drug-resistant bacteria. Pretreatment with EGCG through intraperitoneal injection, intravenous injection, or intragastric administration significantly reduced the bacterial load, inflammatory response, and mortality in mouse abdominal infection models induced by bacterial inoculation or cecal ligation and puncture. Pretreatment with EGCG by intraperitoneal injection significantly increased the numbers of neutrophils and monocytes/macrophages in the abdominal cavity and peripheral blood of mice, and depletion of neutrophils and monocytes/macrophages by specific antibodies or chemical drugs obviously increased the bacterial load in mice. Of note, EGCG did not directly induce neutrophil and macrophage migration, and it just induced phagocyte migration in the presence of macrophages in a co-cultured system, implying that EGCG-induced phagocyte migration relies on its immunoregulatory effects on macrophages. EGCG markedly induced the production of cytokines and chemokines in macrophages and mouse peritoneal lavage, including tumor necrosis factor-α (TNF-α), interleukin-1 ß (IL-1ß), IL-6, CXC chemokine ligands 1 and 2 (CXCL1 and 2), and monocyte chemotactic protein-1 (MCP-1). EGCG significantly induced the phosphorylation of p38 and JNK mitogen-activated protein kinases (MAPKs) in macrophages, and inhibition of p38 and JNK MAPKs markedly reduced EGCG-induced chemokine and cytokine production. Anti-67-kDa laminin receptor (67LR) antibody treatment significantly reduced EGCG-induced chemokine production and p38 and JNK phosphorylation in macrophages. Together, EGCG showed an obvious prophylactic efficacy against bacterial infection by inducing a pro-inflammatory response in macrophages through the 67LR/p38/JNK signaling pathway, supporting the further development of EGCG as a potent prophylaxis for bacterial infection and providing new clues to understand the healthcare function of green tea.

Structural Elucidation of Garcipaucinones A and B From Garcinia paucinervis Using Quantum Chemical Calculations.

Two tocotrienol derivatives, garcipaucinones A (1) and B (2), and a biosynthetically related known analogue (3) were isolated from the fruit of Garcinia paucinervis. Their structures including absolute configurations were unequivocally determined by spectroscopic methods complemented with electronic circular dichroism (ECD) calculations and gauge-independent atomic orbital (GIAO) NMR calculations. Compounds 1 and 2 are the first naturally occurring tocotrienol derivatives with a 3,10-dioxatricyclo-[7.3.1.02,7]tridecane skeleton incorporating an unusual γ-pyrone motif. A reasonable biosynthetic pathway for formation of the two compounds is proposed. The antiproliferative and anti-inflammatory activities of compounds 1 and 2 were also evaluated.

Novel lncRNA UPLA1 mediates tumorigenesis and prognosis in lung adenocarcinoma.

With the development of molecular biotechnology and sequencing techniques, long non-coding RNAs (lncRNAs) have been shown to play a vital role in a variety of cancers including lung cancer. In our previous study, we used RNA sequencing and high-content screening proliferation screening data to identify lncRNAs that were significantly associated with tumour biological functions such as LINC01426. Herein, based on previous work, we report a novel lncRNA UPLA1 (upregulation promoting LUAD-associated transcript-1), which has not been explored or reported in any previous studies. Our results showed that UPLA1 is highly expressed and regulates important biological functions in lung adenocarcinoma. In vitro experiments revealed that UPLA1 promoted the migration, invasion, and proliferation abilities, and is related to cell cycle arrest, in lung adenocarcinoma cells. Moreover, the upregulation of UPLA1 significantly improved the growth of tumours in vivo. We identified that UPLA1 was mainly located in the nucleus using fluorescence in situ hybridisation, and that it promoted Wnt/ß-catenin signalling by binding to desmoplakin using RNA pulldown assay and mass spectrometry. Additionally, luciferase reporter assay revealed that YY1 is the transcription factor of UPLA1 and suppressed the expression of UPLA1 as a transcriptional inhibitor. This finding provides important evidence regarding the two roles of YY1 in cancer. Furthermore, in situ hybridisation assay results showed that UPLA1 was closely related to the prognosis and tumour, node, metastasis (TNM) stage of lung adenocarcinoma. In summary, our results suggest that the novel lncRNA UPLA1 promotes the progression of lung adenocarcinoma and may be used as a prognostic marker, and thus, has considerable clinical significance.