Emerging insights into cuproptosis and copper metabolism: implications for age-related diseases and potential therapeutic strategies.

The expanding geriatric population, whose predisposition toward disabling morbidities and age-related diseases (ARD) is well-documented, has become a paramount social issue, exerting an onerous burden on both the healthcare industry and wider society. ARD manifest as the progressive deterioration of bodily tissues and organs, eventually resulting in the failure of these vital components. At present, no efficacious measures exist to hinder the onset of ARD. Copper, an essential trace element, is involved in a wide range of physiological processes across different cell types. In recent research, a novel variant of copper-dependent cell death, termed cuproptosis, has been identified. This mode of cellular demise stands apart from previously recognized types of cell death. Cuproptosis occurs when copper binds with acyl-CoA synthetase in the tricarboxylic acid (TCA) cycle, resulting in protein aggregation and protein toxicity stress, ultimately leading to cell death. In this paper, we provide a concise overview of the current understanding concerning the metabolism of copper, copper-related diseases, the hallmarks of copper toxicity, and the mechanisms that regulate copper toxicity. Additionally, we discuss the implications of cuproptosis mutations in the development of ARD, as well as the potential for targeting cuproptosis as a treatment for ARD.

Keratin 6A (KRT6A) promotes radioresistance, invasion, and metastasis in lung cancer via p53 signaling pathway.

BACKGROUND: It is reported that the incidence rate and mortality of lung cancer are very high. Therefore, early diagnosis and identification of specific biomarkers are crucial for the clinical treatment of lung cancer. This study aims to comprehensively investigate the prognostic significance of KRT6A in human lung cancer. METHODS: The GEO2R online tool was utilized to analyze the differential expression of mRNA between lung carcinoma tissues and radioresistant tissues in the GSE73095 and GSE197236 datasets. DAVID database was used to perform GO and KEGG enrichment analyses on target genes. The Kaplan-Meier plotter tool was used to analyze the impact of key messenger ribonucleic acid on the survival status of lung cancer. In addition, quantitative real-time polymerase chain reaction (qPCR) was used to investigate the impact of key genes on the phenotype of lung cancer cells. After the knockout, we conducted cell migration and CCK-8 experiments to detect their effects on cell proliferation and invasion. RESULTS: 40 differentially expressed genes (DEGs) were chosen from GSE73095 and 118 DEGs were chosen from GSE197236. Kaplan-Meier map analysis showed that the overall cancer survival rate of the high-expression KRT6A group was higher than that of the low-expression group (P < 0.05). Besides, cell experiments have shown that when the KRT6A gene is downregulated, the proliferation and invasion ability of lung cancer cells is weakened. CONCLUSIONS: Our research concluded that KRT6A may take part in the radioresistance and progression of lung cancer and can be a potential biomarker for lung cancer patients.

The combination of body mass index and fasting plasma glucose is associated with type 2 diabetes mellitus in Japan: a secondary retrospective analysis.

Background: Body mass index (BMI) and fasting plasma glucose (FPG) are known risk factors for type 2 diabetes mellitus (T2DM), but data on the prospective association of the combination of BMI and FPG with T2DM are limited. This study sought to characterize the association of the combination of BMI and FPG (ByG) with T2DM. Methods: The current study used the NAGALA database. We categorized participants by tertiles of ByG. The association of ByG with T2DM was expressed with hazard ratios (HRs) with 95% confidence intervals (CIs) after adjustment for potential risk factors. Results: During a median follow-up of 6.19 years in the normoglycemia cohort and 5.58 years in the prediabetes cohort, the incidence of T2DM was 0.75% and 7.79%, respectively. Following multivariable adjustments, there were stepwise increases in T2DM with increasing tertiles of ByG. After a similar multivariable adjustment, the risk of T2DM was 2.57 (95% CI 2.26 - 2.92), 1.97 (95% CI 1.53 - 2.54) and 1.50 (95% CI 1.30 - 1.74) for a per-SD change in ByG in all populations, the normoglycemia cohort and the prediabetes cohort, respectively. Conclusion: ByG was associated with an increased risk of T2DM in Japan. The result reinforced the importance of the combination of BMI and FPG in assessing T2DM risk.

Source-Free Active Domain Adaptation via Augmentation-Based Sample Query and Progressive Model Adaptation.

Active domain adaptation (ADA), which enormously improves the performance of unsupervised domain adaptation (UDA) at the expense of annotating limited target data, has attracted a surge of interest. However, in real-world applications, the source data in conventional ADA are not always accessible due to data privacy and security issues. To alleviate this dilemma, we introduce a more practical and challenging setting, dubbed as source-free ADA (SFADA), where one can select a small quota of target samples for label query to assist the model learning, but labeled source data are unavailable. Therefore, how to query the most informative target samples and mitigate the domain gap without the aid of source data are two key challenges in SFADA. To address SFADA, we propose a unified method SQAdapt via augmentation-based Sample Query and progressive model Adaptation. In specific, an active selection module (ASM) is built for target label query, which exploits data augmentation to select the most informative target samples with high predictive sensitivity and uncertainty. Then, we further introduce a classifier adaptation module (CAM) to leverage both the labeled and unlabeled target data for progressively calibrating the classifier weights. Meanwhile, the source-like target samples with low selection scores are taken as source surrogates to realize the distribution alignment in the source-free scenario by the proposed distribution alignment module (DAM). Moreover, as a general active label query method, SQAdapt can be easily integrated into other source-free UDA (SFUDA) methods, and improve their performance. Comprehensive experiments on multiple benchmarks have shown that SQAdapt can achieve superior performance and even surpass most of the ADA methods.

A U-shaped association between the triglyceride to high-density lipoprotein cholesterol ratio and the risk of incident type 2 diabetes mellitus in Japanese men with normal glycemic levels: a population-based longitudinal cohort study.

Background: Several studies have verified that a high baseline TG/HDL-C ratio is a risk factor for incident type 2 diabetes mellitus (T2DM). However, for low baseline TG/HDL-C levels, the findings were inconsistent with ours. In addition, the association between baseline TG/HDL-C ratio and the risk of incident T2DM in Japanese men with normal glycemic levels is unclear. As a result, our study further investigated the relationship between baseline TG/HDL-C and the risk of incident T2DM in Japanese men with normal glycemic levels. Methods: This was a secondary longitudinal cohort study. We selected 7,684 male participants between 2004 and 2015 from the NAGALA database. A standardized Cox regression model and two piecewise Cox regression models were used to explore the relationship between the baseline high-density lipoprotein cholesterol ratio (TG/HDL-C) and incident T2DM. Results: During a median follow-up of 2,282 days, 162 men developed incident T2DM. In the adjusted model, the baseline TG/HDL-C ratio was strongly associated with the risk of incident T2DM, and no dose-dependent positive association was observed between the baseline TG/HDL-C ratio and incidence of T2DM throughout the baseline TG/HDL-C quartiles. Two-piecewise linear regression analysis showed a U-shaped association between baseline TG/HDL-C ratio and incidence of incident T2DM. A baseline TG/HDL-C ratio below 1.188 was negatively associated with incident T2DM (H.R. = 0.105, 95% CI = 0.025, 0.451; P = 0.002). In contrast, a baseline TG/HDL-C ratio >1.188 was positively associated with incident T2DM (H.R. = 1.248, 95% CI = 1.113, 1.399; P<0.001). The best TG/HDL-C threshold for predicting incident T2DM was 1.8115 (area under the curve, 0.6837). Conclusion: A U-shaped relationship between baseline TG/HDL-C ratio and incident T2DM in Japanese men with normal glycemic levels was found.

Relationship between lipid accumulation product and new-onset diabetes in the Japanese population: a retrospective cohort study.

Background: Diabetes has become a global public health problem. Obesity has been established as a risk factor for diabetes. However, it remains unclear which of the obesity indicators (BMI, WC, WhtR, ABSI, BRI, LAP, VAI) is more appropriate for monitoring diabetes. Therefore, the objective of this investigation is to compare the strength of the association of these indicators and diabetes and reveal the relationship between LAP and diabetes. Methods: 15,252 people took part in this research. LAP was quartered and COX proportional risk model was applied to explore the relationship between LAP and new-onset diabetes. Smooth curve fitting was employed to investigate the non-linear link between LAP and diabetes mellitus. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the aforementioned indicators for diabetes. Results: After adjusting for confounding factors, multiple linear regression analysis showed that each unit increase in LAP was associated with a 76.8% increase in the risk of developing diabetes (HR=1.768, 95% CI: 1.139 to 2.746, P=0.011). In addition, LAP predicted new-onset diabetes better than other indicators, and the AUC was the largest [HR: 0.713, 95% CI: 0.6806-0.7454, P<0.001, in women; HR: 0.7922, 95% CI: 0.7396-0.8447; P<0.001, in men]. When LAP was used as a lone predictor, its AUC area was largest both men and women. However, after adding classical predictors (FPG, HbA1c, SBP, exercise, age) to the model, the LAP is better than the ABSI, but not better than the other indicators when compared in pairs. Conclusions: High levels of LAP correlate very strongly with diabetes and are an important risk factor for diabetes, especially in women, those with fatty liver and current smokers. LAP was superior to other indicators when screening for diabetes susceptibility using a single indicator of obesity, both in men and in women. However, when obesity indicators were added to the model together with classical predictors, LAP did not show a significant advantage over other indicators, except ABSI.

High expression of serine protease 2 (PRSS2) associated with invasion, metastasis, and proliferation in gastric cancer.

BACKGROUND: Accumulating evidence indicates that the occurrence and development of tumors are related to the activation of oncogenes and the inactivation of tumor suppressor genes caused by epigenetic mechanisms. However, the function of serine protease 2 (PRSS2) in gastric cancer (GC) is still unknown. Our study aimed to find a regulation network involved in GC. METHODS: The mRNA data (GSE158662 and GSE194261) of GC and normal tissues were downloaded from the Gene Expression Omnibus (GEO) dataset. Differential expression analysis was performed using R software, and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted by using Xiantao software. Besides, we used Quantitative Real-time PCR (qPCR) to verify our conclusions. After gene knockdown, cell migration and CCK-8 experiment were carried out to detect the effect of gene on cell proliferation and invasion. RESULTS: Totally, 412 differentially expressed genes (DEGs) were identified from GSE158662 and 94 DEGs were identified from GSE196261. Km-plot database results indicated that PRSS2 exhibited high diagnosis worth for GC. Gene functional annotation enrichment analysis revealed that these hub mRNAs were mainly taken part in the process of tumorigenesis and development. Besides, vitro experiments showed that down-regulation of PRSS2 gene reduced the proliferation and invasion ability of GC cells. CONCLUSIONS: Our results indicated that PRSS2 may play vital roles in the carcinogenesis and progression of GC and can be potential biomarkers for patients with GC.

DANet: Semi-supervised differentiated auxiliaries guided network for video action recognition.

Video Action Recognition (ViAR) aims to identify the category of the human action observed in a given video. With the advent of Deep Learning (DL) techniques, noticeable performance breakthroughs have been achieved in this study. However, the success of most existing DL-based ViAR methods heavily relies on the existence of a large amount of annotated data, i.e., videos with corresponding action categories. In practice, obtaining such a desired number of annotations is often difficult due to expensive labeling costs, which may lead to significant performance degradation for these methods. To address this issue, we propose an end-to-end semi-supervised Differentiated Auxiliary guided Network (DANet) to best use a few annotated videos. Except for the common supervised learning on a few annotated videos, the DANet also involves the knowledge of multiple pre-trained auxiliary networks to optimize the ViAR network in a self-supervised way on the unannotated data by removing the annotations. Considering the tight connection between video action recognition and classical static image-based visual tasks, the abundant knowledge from the pre-trained static image-based models can be used for training the ViAR model. Specifically, the DANet is a two-branch architecture, which includes a target branch of the ViAR network, and an auxiliary branch of multiple auxiliary networks (i.e., referring to diverse off-the-shelf models of relevant image tasks). Given a limited number of annotated videos, we train the target ViAR network end-to-end in a semi-supervised way, namely, with both the supervised cross-entropy loss on annotated videos, and the per-auxiliary weighted self-supervised contrastive losses on the same videos but without using annotations. Besides, we further explore different weighted guidance of the auxiliary networks to the ViAR network to better reflect different relationships between the image-based models and the ViAR model. Finally, we conduct extensive experiments on several popular action recognition benchmarks in comparison with existing state-of-the-art methods, and the experimental results demonstrate the superiority of DANet over most of the compared methods. In particular, the DANet obviously suppresses state-of-the-art ViAR methods even with very fewer annotated videos.

DRNet: Double Recalibration Network for Few-Shot Semantic Segmentation.

Few-shot segmentation aims at learning to segment query images guided by only a few annotated images from the support set. Previous methods rely on mining the feature embedding similarity across the query and the support images to achieve successful segmentation. However, these models tend to perform badly in cases where the query instances have a large variance from the support ones. To enhance model robustness against such intra-class variance, we propose a Double Recalibration Network (DRNet) with two recalibration modules, i.e., the Self-adapted Recalibration (SR) module and the Cross-attended Recalibration (CR) module. In particular, beyond learning robust feature embedding for pixel-wise comparison between support and query as in conventional methods, the DRNet further exploits semantic-aware knowledge embedded in the query image to help segment itself, which we call 'self-adapted recalibration'. More specifically, DRNet first employs guidance from the support set to roughly predict an incomplete but correct initial object region for the query image, and then reversely uses the feature embedding extracted from the incomplete object region to segment the query image. Also, we devise a CR module to refine the feature representation of the query image by propagating the underlying knowledge embedded in the support image's foreground to the query. Instead of foreground global pooling, we refine the response at each pixel in the query feature map by attending to all foreground pixels in the support feature map and taking the weighted average by their similarity; meanwhile, feature maps of the query image are also added back to weighted feature maps as a residual connection. Our DRNet can effectively address the intra-class variance under the few-shot setting with such two recalibration modules, and mine more accurate target regions for query images. We conduct extensive experiments on the popular benchmarks PASCAL- 5i and COCO- 20i . The DRNet with the best configuration achieves the mIoU of 63.6% and 64.9% on PASCAL- 5i and 44.7% and 49.6% on COCO- 20i for 1-shot and 5-shot settings respectively, significantly outperforming the state-of-the-arts without any bells and whistles. Code is available at: https://github.com/fangzy97/drnet.

2, 5-dichloro-1, 4-benuinone exposure to zebrafish embryos/larvae causes neurodevelopmental toxicity.

2, 5-dichloro-1, 4-benuinone (2, 5-DCBQ) is an emerging disinfection by-product belonging to the class of halobenzoquinones (HBQs). However, there is limited evidence regarding the neurotoxic effects of 2, 5-DCBQ. To better understand the toxicological mechanisms of aquatic organisms, zebrafish embryos were exposed to 0.2 mg/L, 0.4 mg/L, and 0.6 mg/L of 2, 5-DCBQ from 4 h post-fertilization (hpf) to 120 hpf. Developmental defects, such as reduced body length, decreased heart rate, decreased pigmentation, and abnormal motor axon structure was observed. In particular, the locomotor activity of zebrafish larvae reduced with exposure to increasing 2, 5-DCBQ concentrations, and this effect was more pronounced under dark stimulation. The results indicated that the genes associated with neuronal development (gfap, mbp, syn2a, elavl3, ache, and a1-tubulin) were significantly downregulated after treatment with 2, 5-DCBQ. Furthermore, the KEGG result showed the neuroactive ligand-receptor interaction and apoptosis pathways were visibly disrupted, and we found acetylcholinesterase activity was also affected. In summary, the disinfection by-product, 2, 5-DCBQ, exhibits neurodevelopmental toxicity in zebrafish embryos, providing novel evidence for comprehensive analyses of its toxicity.

miRNA-142-3p functions as a potential tumor suppressor directly targeting FAM83D in the development of ovarian cancer.

BACKGROUND: FAM83D (family with sequence similarity 83, member D) is of particular interest in tumorigenesis and tumor progression. Ovarian cancer is the leading cause of cancer-related death in women all over the world. This study aims to research the association between FAM83D and ovarian cancer (OC). METHODS: The gene expression data of OC and normal samples (GSE81873 and GSE27651) was downloaded from Gene Expression Omnibus (GEO) dataset. The bioinformatics analysis was performed to distinguish two differentially expressed genes (DEGs), prognostic candidate genes and functional enrichment pathways. Immunohistochemistry (IHC), Quantitative Real-time PCR (qPCR), and luciferase reporter assays were utilized for further study. RESULTS: There were 56 DEMs and 63 DEGs in cancer tissues compared to normal tissues. According to the km-plot software, hsa-miR-142-3p and FAM83D were associated with the overall survival of patients with OC. Besides, Multivariate analysis included that hsa-miR-142-3p and FAM83D were independent risk factors for OC patients. Furthermore, qPCR demonstrated that miRNA-142-3p and FAM83D were differentially expressed in normal ovarian tissues (NOTs) and ovarian cancer tissues (OCTs). IHC results indicated that FAM83D was overexpressed in OCTs compared with NOTs. Last but not least, luciferase reporter assays verified that FAM83D was a direct target of hsa-miRNA-142-3p in OC cells. CONCLUSIONS: The prognostic model based on the miRNA-mRNA network could provide predictive significance for the prognosis of OC patients, which would be worthy of clinical application. Our results concluded that miR-142-3p and its targets gene FAM83D may be potential diagnostic and prognostic biomarkers for patients with OC.

Photothermal combined with intratumoral injection of annonaceous acetogenin nanoparticles for breast cancer therapy.

ACGs (annonaceous acetogenins) possess excellent antitumor activity, but their serious accompanying toxicity has prevented their application in the clinic. To address this problem, we therefore constructed an intratumoral drug delivery system integrating chemotherapy and photothermal therapy. The PEGylation of polydopamine nanoparticles (PDA-PEG NPs) possessed an excellent biocompatibility with size of 70.96 ± 2.55 nm, thus can be used as good photothermal materials in the body. Moreover, PDA-PEG NPs can kill half of cancer cells under NIR (near-infrared) laser irradiation, and the survival rate of 4T1 cells is only 1% when ACG NPs and PDA-PEG NPs are combined. In vivo distribution studies showed that the 0.1 mg/kg ACGs NPs + PDA-PEG NPs + NIR group had the highest tumor inhibition rate, which was significantly superior to that of the 0.1 mg/kg ACGs NPs intratumoral injection group (82.65% vs. 59.08%). Altogether, the combination of PDA-PEG NPs + NIR with chemotherapy drugs may provide a feasible and effective strategy for the treatment of superficial tumors.

Identification and verification of microRNA signature and key genes in the development of osteosarcoma with lung metastasis.

BACKGROUND: Osteosarcoma (OS) is a heterogeneous malignant spindle cell tumor in children under the age of 20. This study aims to research the association between Solute Carrier Family 7 Member 8 (SLC7A8) as well as related genes and OS. METHOD: OS and normal samples (GSE38698 and GSE85537) were downloaded from Gene Expression Omnibus dataset. The bioinformatics analysis was performed to distinguish 2 differentially expressed genes, prognostic candidate genes and functional enrichment pathway. Immunohistochemistry and quantitative real-time PCR were utilized for further study. RESULTS: There were 5 DEMs and 10 differentially expressed genes in cancer tissues compared to normal tissues. According to the km-plot software, ARHGEF3, BSN, PQLC3, and SLC7A8 were significantly related to the overall survival of patients with OS. Furthermore, Multivariate analysis included that SLC7A8 was independent risk factors for OS patients. Furthermore, immunohistochemistry and quantitative real-time PCR outcomes indicated that the expression level of SLC7A8 and hsa-miR-506 was differentially expressed in lung metastasis OS tissues and non-metastasis tissues. CONCLUSION: The prognostic model based on the miRNA-mRNA network could provide predictive significance for prognosis of OS patients, which would be worthy of clinical application. Our results concluded that SLC7A8 may play a key role in the development of OS.

Serglycin promotes proliferation, migration, and invasion via the JAK/STAT signaling pathway in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is a common disease in the world, and its pathogenesis is still unclear. This study aims to identify the key genes that promote the proliferation, invasion, and metastasis of osteosarcoma cells. METHOD: GSE124768 and GSE126209 were downloaded from the Gene Expression Omnibus (GEO) database. The gene ontology and enrichment pathway were analyzed by FunRich software. qPCR and Western blot were used to detect the gene expression. After gene knockdown, Transwell and wound healing assays were conducted on osteosarcoma cells to detect whether the genes were defined before enhancing the invasion of osteosarcoma. RESULTS: Totally, 341 mRNAs were found to be regulated differentially in osteosarcoma cells compared to osteoblasts. In addition, the expression level of Serglycin (SRGN) in osteosarcoma cells was higher than that in human osteoblasts. The invasion and proliferation ability of osteosarcoma cells with upregulated Serglycin was significantly increased, and on the contrary, decreased after Serglycin knockdown. Moreover, we preliminarily found that Serglycin may associate with the JAK/STAT signaling pathway. CONCLUSIONS: By using microarray and bioinformatics analyses, differently expressed mRNAs were identified and a complete gene network was constructed. To our knowledge, we describe for the first time Serglycin as a potential biomarker.

Vincristine-doxorubicin co-loaded artificial low-density lipoproteins towards solid tumours.

To construct an artificial low-density lipoprotein (aLDL) that highly mimics low-density lipoprotein (LDL) in vivo, and deliver vincristine (VCR) - doxorubicin (DOX) simultaneously, the 100 nm and 35 nm DOX-VCR-aLDLs (DV-aLDLs) were constructed, then the physicochemical characteristics were evaluated. Through in vitro inverse gravity diffusion experiment, the tumour cake and sphere model experiment, draw a conclusion that the diffusion of 35 nm DV-aLDLs was stronger than 100 nm DV-aLDLs, and the tumour retention of 35 nm DV-aLDLs was better than the DV-solution. In addition, the three-dimension (3D) in vivo distribution imaging of aLDLs was performed on HepG-2 tumour-bearing nude mice, followed by the biodistribution and therapeutic efficacy on these xenograft models. Taking advantage of better diffusion capacity in tumour tissue, as well as the synergistic effect of VCR and DOX, the 35 nm DV-aLDL had the strongest efficacy and the lowest toxicity. High entrapment efficiency and stability, both active and passive targeting, making aLDL a potential carrier for tumour-targeted therapy at the same time.

ARHGEF3 Associated with Invasion, Metastasis, and Proliferation in Human Osteosarcoma.

BACKGROUND: Osteosarcoma is a malignant bone tumor composed of mesenchymal cells producing osteoid and immature bone. This study is aimed at developing novel potential prognostic biomarkers and constructing a miRNA-mRNA network for progression in osteosarcoma. METHOD: GSE70367 and GSE70414 were obtained in the Gene Expression Omnibus (GEO) database. GEO software and the GEO2R calculation method were used to analyze two gene profiles. The coexpression of differentially expressed miRNAs (DEMs) and genes (DEGs) was identified and searched for in the FunRich database for pathway and ontology analysis. Cytoscape was utilized to construct the mRNA-miRNA network. Survival analysis of identified miRNAs and mRNAs was performed by utilizing the Kaplan-Meier Plotter. Besides, expression levels of DEMs and target mRNAs were verified by performing quantitative real-time PCR (qRT-PCR) and Western blot (WB). RESULTS: Six differentially expressed microRNAs (DEMs) were identified, and 8 target genes were selected after screening. By using the KM Plotter software, miRNA-124 and ARHGEF3 were obviously associated with the overall survival of patients with osteosarcoma. Furthermore, ARHGEF3 was found downregulated in osteosarcoma cells by performing qRT-PCR and WB experiments. Results also showed that downregulated ARHGEF3 may associate with invasion, metastasis, and proliferation. CONCLUSIONS: By using microarray and bioinformatics analysis, DEMs were selected, and a complete miRNA-mRNA network was constructed. ARHGEF3 may act as a therapeutic and prognostic target of osteosarcoma.

Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis.

BACKGROUND: Because its metastasis to the lymph nodes are closely related to poor prognosis, miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of colorectal cancer (CRC). This study aimed to identify novel gene signatures in the lymph node metastasis of CRC. METHODS: GSE56350, GSE70574, and GSE95109 datasets were downloaded from the Gene Expression Omnibus (GEO) database, while data from 569 colorectal cancer cases were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated using R programming language (Version 3.6.3), while gene ontology and enrichment analysis of target mRNAs were performed using FunRich ( http://www.funrich.org ). Furthermore, the mRNA-miRNA network was constructed using Cytoscape software (Version 3.8.0). Gene expression levels were verified using the GEO datasets. Similarly, quantitative real-time PCR (qPCR) was used to examine expression profiles from 20 paired non-metastatic and metastatic lymph node tissue samples obtained from patients with CRC. RESULTS: In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering the results. Moreover, two key miRNAs (hsa-miR-99a, hsa-miR-100) and one gene (heparan sulfate-glucosamine 3-sulfotransferase 2 [HS3ST2]) were identified. The GEO datasets analysis and qPCR results showed that the expression of key miRNA and genes were consistent with that obtained from the bioinformatic analysis. A novel miRNA-mRNA network capable of predicting the prognosis and confirmed experimentally, hsa-miR-99a-HS3ST2-hsa-miR-100, was found after expression analysis in metastasized lymph node tissue from CRC samples. CONCLUSION: In summary, miRNAs and genes with potential as biomarkers were found and a novel miRNA-mRNA network was established for CRC lymph node metastasis by systematic bioinformatic analysis and experimental validation. This network may be used as a potential biomarker in the development of lymph node metastatic CRC.

HS3ST2 and Its Related Molecules as Potential Biomarkers for Predicting Lymph Node Metastasis in Patients with Colorectal Cancer.

BACKGROUND: Lymph node metastasis is a major cause of cancer-related death in patients with colorectal cancer (CRC), but current strategies are limited to predicting this clinical behavior. Our study aims to establish a lymph node metastasis prediction model based on miRNA and mRNA to improve the accuracy of prediction. METHODS: GSE56350, GSE70574, and GSE95109 were downloaded from the Gene Expression Omnibus (GEO) database and 569 colorectal cancer statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs were calculated by using R software. Besides, gene ontology and enriched pathway analysis of target mRNAs were analyzed by using FunRich. Furthermore, the mRNA-miRNA network was constructed using Cytoscape software. Gene expression level was also detected by performing qRT-PCR (quantitative real-time PCR) in colorectal cancer and lymph node tissues. RESULTS: In total, 5 differentially expressed miRNAs were selected, and 34 mRNAs were identified after filtering. The research of KEGG indicated that mRNAs are enriched in many cancer pathways. Differentially expressed miRNAs were most enriched in the cytoplasm, nucleoside, transcription factor activity, and RNA binding. KEGG pathway analysis of these target genes was mainly enriched in 5 pathways including fatty acid elongation, MAPK signaling pathway, autophagy, signaling pathways regulating pluripotency of stem cells, and Th17 cell differentiation. The results of qRT-PCR indicated that hsa-miR-100 and hsa-miR-99a were differentially expressed in lymph node metastatic colorectal cancer tissues and lymph node non-metastasis tissues which all target HS3ST2. Besides, we also found they have a significant difference in colorectal cancer tissues compared with normal tissues. CONCLUSION: By using microarray and bioinformatics analyses, differentially expressed miRNAs were identified and a complete gene network was constructed. To our knowledge, HS3ST2 and related molecules including hsa-miR-100 and hsa-miR-99a were firstly identified as potential biomarkers in the development of lymph node metastatic colorectal cancer.

The Prognostic Significance of Hsp70 in Patients with Colorectal Cancer Patients: A PRISMA-Compliant Meta-Analysis.

BACKGROUND: Hsp70 (heat shock protein 70) plays a key role in carcinogenesis and cancer progression. However, the relationship between the Hsp70 expression level and the colorectal cancer patient survival is unknown. This study is aimed at investigating the relationship between Hsp70 and the prognosis of colorectal carcinoma patients. METHODS: PubMed, Web of Science, and Embase were used for systematic computer literature retrieval. Stata SE14.0 software was used for quantitative meta-analysis. Besides, data was extracted from selected articles. Relationships between Hsp70 expression level and prognosis were further studied. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) were also computed. RESULTS: A total of 11 potentially eligible studies with 2269 patients were identified in 10 tumors from PubMed, Web of Science, and Embase. Hsp70 overexpression was associated with poor overall survival (OS) and disease-free survival (DFS) in colorectal carcinoma patients (HRs, 0.65 (95% CI: 0.52-0.78) and 0.77 (95% CI: 0.23-1.32), respectively). CONCLUSIONS: Hsp70 overexpression can predict poor survival in colorectal cancer patients.

Identification of Key miRNAs in the Treatment of Dabrafenib-Resistant Melanoma.

Dabrafenib resistance is a significant problem in melanoma, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism of drug resistance of dabrafenib and to explore the key genes and pathways that mediate drug resistance in melanoma. GSE117666 was downloaded from the Gene Expression Omnibus (GEO) database and 492 melanoma statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Besides, differentially expressed miRNAs (DEMs) were identified by taking advantage of the R software and GEO2R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) and FunRich was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify potential pathways and functional annotations linked with melanoma chemoresistance. 9 DEMs and 872 mRNAs were selected after filtering. Then, target genes were uploaded to Metascape to construct protein-protein interaction (PPI) network. Also, 6 hub mRNAs were screened after performing the PPI network. Furthermore, a total of 4 out of 9 miRNAs had an obvious association with the survival rate (P < 0.05) and showed a good power of risk prediction model of over survival. The present research may provide a deeper understanding of regulatory genes of dabrafenib resistance in melanoma.