Analyzing the Functional Roles and Immunological Features of Chemokines in COAD.

Chemokines are key proteins that regulate cell migration and immune responses and are essential for modulating the tumor microenvironment. Despite their close association with colon cancer, the expression patterns, prognosis, immunity, and specific roles of chemokines in colon cancer are still not fully understood. In this study, we investigated the mutational features, differential expression, and immunological characteristics of chemokines in colon cancer (COAD) by analyzing the Tumor Genome Atlas (TCGA) database. We clarified the biological functions of these chemokines using Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. By univariate and multivariate COX regression analyses, we developed chemokine-based prognostic risk models. In addition, using Gene Set Enrichment Analysis (GSEA) and Gene Set Variant Analysis (GSVA), we analyzed the differences in immune responses and signaling pathways among different risk groups. The results showed that the mutation rate of chemokines was low in COAD, but 25 chemokines were significantly differentially expressed. These chemokines function in several immune-related biological processes and play key roles in signaling pathways including cytokine-cytokine receptor interactions, NF-kappa B, and IL-17. Prognostic risk models based on CCL22, CXCL1, CXCL8, CXCL9, and CXCL11 performed well. GSEA and GSVA analyses showed significant differences in immune responses and signaling pathways across risk groups. In conclusion, this study reveals the potential molecular mechanisms of chemokines in COAD and proposes a new prognostic risk model based on these insights.

BRD4L cooperates with MYC to block local tumor invasion via suppression of S100A10.

Targeted therapy based on BRD4 and MYC shows promise due to their well-researched oncogenic functions in cancer, but their tumor-suppressive roles are less understood. In this study, we employ a systematic approach to delete exons that encode the low-complexity domain (LCD) of BRD4L in cells by using CRISPR-Cas9. In particular, the deletion of exon 14 (BRD4-E14) results in cellular morphological changes towards spindle-shaped and loosely packed. BRD4-E14 deficient cells show increased cell migration and reduced cell adhesion. The expression of S100A10 was significantly increased in cells lacking E14. BRD4L binds with MYC via the E14-encoded region of the LCD to inhibit the expression of S100A10. In cancer tissues, there is a positive correlation between BRD4 and MYC, while both of these proteins are negatively associated with S100A10 expression. Finally, knocking out the BRD4-E14 region or MYC promotes tumor growth in vivo. Together, these data support a tumor-suppressive role of BRD4L and MYC in some contexts. This discovery emphasizes the significance of a discreetly design and precise patient recruitment in clinical trials that testing cancer therapy based BRD4 and MYC.

Identifying a locus in super-enhancer and its resident NFE2L1/MAFG as transcriptional factors that drive PD-L1 expression and immune evasion.

Although the transcriptional regulation of the programmed death ligand 1 (PD-L1) promoter has been extensively studied, the transcription factor residing in the PD-L1 super-enhancer has not been comprehensively explored. Through saturated CRISPR-Cas9 screening of the core region of the PD-L1 super-enhancer, we have identified a crucial genetic locus, referred to as locus 22, which is essential for PD-L1 expression. Locus 22 is a potential binding site for NFE2:MAF transcription factors. Although genetic silencing of NRF2 (NFE2L2) did not result in a reduction of PD-L1 expression, further analysis reveals that MAFG and NFE2L1 (NRF1) play a critical role in the expression of PD-L1. Importantly, lipopolysaccharides (LPS) as the major component of intratumoral bacteria could greatly induce PD-L1 expression, which is dependent on the PD-L1 super-enhancer, locus 22, and NFE2L1/MAFG. Mechanistically, genetic modification of locus 22 and silencing of MAFG greatly reduce BRD4 binding and loop formation but have minimal effects on H3K27Ac modification. Unlike control cells, cells with genetic modification of locus 22 and silencing of NFE2L1/MAFG failed to escape T cell-mediated killing. In breast cancer, the expression of MAFG is positively correlated with the expression of PD-L1. Taken together, our findings demonstrate the critical role of locus 22 and its associated transcription factor NFE2L1/MAFG in super-enhancer- and LPS-induced PD-L1 expression. Our findings provide new insight into understanding the regulation of PD-L1 transcription and intratumoral bacteria-mediated immune evasion.

A novel dictionary learning-based approach for Ultrasound Elastography denoising.

Ultrasound Elastography is a late-model Ultrasound imaging technique mainly used to diagnose tumors and diffusion diseases that can't be detected by traditional Ultrasound imaging. However, artifact noise, speckle noise, low contrast and low signal-to-noise ratio in images make disease diagnosing a challenging task. Medical images denoising, as the first step in the follow-up processing of medical images, has been concerned by many people. With the widespread use of deep learning technique in the research field, dictionary learning method are once again receiving attention. Dictionary learning, as a traditional machine learning method, requires less sample size, has high training efficiency, and can describe images well. In this work, we present a novel strategy based on K-clustering with singular value decomposition (K-SVD) and principal component analysis (PCA) to reduce noise in Ultrasound Elastography images. At this stage of dictionary training, we implement a PCA method to transform the way dictionary atoms are updated in K-SVD. Finally, we reconstructed the image based on the dictionary atoms and sparse coefficients to obtain the denoised image. We applied the presented method on datasets of clinical Ultrasound Elastography images of lung cancer from Nanjing First Hospital, and compared the results of the presented method and the original method. The experimental results of subjective and objective evaluation demonstrated that presented approach reached a satisfactory denoising effect and this research provides a new technical reference for computer aided diagnosis.

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas.

Objective: Although the expression of long noncoding RNAs (lncRNAs) and N6-methyladenosine (M6A) is correlated with different tumors, it remains unclear how M6A-related lncRNA functioning affects the initiation and progression of oral squamous cell carcinoma (OSCC). Materials and Methods: Gene expression and clinical data were retrieved from The Cancer Genome Atlas. The prognostic value of M6A-related lncRNAs was determined using univariate Cox regression analyses. Gene set enrichment analysis of OSCC patient clusters revealed the pathways that elucidate the mechanism. Furthermore, a risk-based model was established. The difference in the overall survival (OS) between groups, including low-/high-risk groups, was determined by Kaplan-Meier analysis. Relationships among immune cells, clusters, clinicopathological characteristics, and risk scores were explored. Results: Among 1,080 M6A-related lncRNAs, 36 were prognosis-related. Patients with OSCC were divided into two clusters. T stage and the pathological grade were noticeably lower in cluster 2 than in cluster 1. Epithelial-mesenchymal transition showed greater enrichment in cluster 1. Nine hub M6A-related lncRNAs were identified for the model of risk score for predicting OSCC prognosis. The OS was longer in patients with a low-risk score than in patients with a high-risk score. The risk score was an independent prognostic factor of OSCC and was associated with the infiltration of different immune cells. T stages and the American Joint Committee on Cancer (AJCC) stages were more advanced in the high-risk score group than in the low-risk score group. Finally, expression correlation analysis showed that the risk score is associated with the expression of oxidative stress markers. Conclusion: M6A-related lncRNAs play an important role in OSCC progression. Immune cell infiltration was related to the risk score model in OSCC and could accurately predict OSCC prognosis.

Rosuvastatin Regulates Odontoblast Differentiation by Suppressing NF-κB Activation in an Inflammatory Environment.

Rosuvastatin is a synthetic statin of 3-hydroxy-methyl-3-glutamyl coenzyme A reductase inhibitor. It has pleiotropic characteristics including hepatic selectivity, minimal metabolism, inhibition of inflammation, and induction of osteoblast differentiation. In this study, dental pulp stem cells (DPSCs) were treated with lipopolysaccharide alone or with rosuvastatin. Then, we examined the accelerative effects of rosuvastatin on odontoblast differentiation and mineralized nodule formation by real-time polymerase chain reaction (RT-PCR), western blot, alizarin red S staining, and alkaline phosphatase staining. The extent of anti-inflammation was determined by RT-PCR and analysis of the expression of tumor necrosis factor α, interleukin 1ß (IL-1ß), and IL-6. Furthermore, the activation of nuclear factor kappa B (NF-κB) was determined by western blot. This study demonstrates that rosuvastatin may speed up odontoblast differentiation and rescue inflammatory reaction by suppressing the NF-κB signaling pathway. It is believed that our findings provide novel perceptions on odontogenic differentiation of DPSCs.

CKIP-1 suppresses odontoblastic differentiation of dental pulp stem cells via BMP2 pathway and can interact with NRP1.

AIM: Casein kinase 2 interacting protein-1 (CKIP-1) is a recently discovered intracellular regulator of bone formation, muscle cell differentiation, and tumor cell proliferation. Our study aims to identify the inhibition of BMP2-Smad1/5 signaling by CKIP-1 in odontoblastic differentiation of human dental pulp stem cells (DPSCs). MATERIALS AND METHODS: DPSCs infected CKIP-1 siRNA or transfected CKIP-1 full-length plasmid were cultured in odontoblastic differentiation medium or added noggin (200 ng/mL) for 21 days. We examined the effects of CKIP-1 on odontoblastic differentiation, mineralized nodules formation, and interaction by western blot, real-time polymerase chain reaction (RT-PCR), alkaline phosphatase (ALP) staining, alizarin red S staining, and immunoprecipitation. RESULTS: Firstly, we have demonstrated that CKIP-1 expression markedly decreased time-dependently along with cell odontoblastic differentiation. Indeed, the silence of CKIP-1 upregulated odontoblastic differentiation via BMP2-Smad1/5 signaling, while CKIP-1 over-expression had a negative effect on odontoblastic differentiation of DPSCs. Furthermore, CKIP-1 could interact with Neuropilin-1 (NRP1). CONCLUSIONS: This work provides data that advocates a novel perception on odontoblastic differentiation of DPSCs. Therefore, inhibiting the expression of CKIP-1 may be of great significance to the development of dental caries.

Wedelolactone Enhances Odontoblast Differentiation by Promoting Wnt/ß-Catenin Signaling Pathway and Suppressing NF-κB Signaling Pathway.

Wedelolactone is a multitarget natural plant compound with many pharmacological activities, including anti-inflammatory, anticancer, and antiosteoporosis. In this study, dental pulp stem cells (DPSCs) were treated with or without wedelolactone. We found that wedelolactone stimulated odontoblast differentiation and mineralization. At the molecular level, wedelolactone directly promoted the nuclear accumulation of ß-catenin, and thereafter stimulated the expression of odontoblast-related marker genes containing dentin matrix protein-1 (DMP1), dentin sialophosphoprotein (DSPP), and runt-related transcription factor 2 (Runx2). Furthermore, wedelolactone upregulated the expression of IκBα and inhibited phosphonation and nuclear migration of p65. As a result, wedelolactone remarkably induced odontoblast differentiation through semaphorin 3A (Sema3A)/neuropilin-1 (NRP1) pathway-mediated ß-catenin activation and nuclear factor kappa B (NF-κB) pathway inhibition. Our findings provide novel perceptions on odontogenic differentiation of DPSCs.

The Role of Neuropilin-1-FYN Interaction in Odontoblast Differentiation of Dental Pulp Stem Cells.

Abnormal odontoblast differentiation of dental pulp stem cells (DPSCs) caused by inflammation is closely related to the development of dental caries. Neuropilin-1 (NRP1) is one of the members of neuropilin family. It can combine with disparate ligands involved in regulating cell differentiation. FYN belongs to the protein-tyrosine kinase family, which has been implicated in the control of cell growth, and the effect can be further strengthened by inflammatory factors. In our studies, we verified that NRP1 can form complexes with FYN and have the correlation changes in odontoblast differentiation of DPSCs. Therefore, we surmise that in the progress of dental caries, NRP1 interacts with FYN, by expanding inflammation and inhibition of odontoblast differentiation of DPSCs through nuclear factor kappa B (NF-κB) signaling pathway. In this subject, we first investigated the expression and interaction of NRP1 and FYN in DPSCs. And then, we researched the effect of this complex controlling downstream signal pathway in normal or inflammation stimulated DPSCs. Finally, we analyzed the relationship between this role and odontoblast differentiation of DPSCs. This research will provide the molecular mechanism of inflammation factors of dental caries through activating NF-κB signal regulating odontoblast differentiation in DPSCs for finding new potential drug targets for the clinical treatment of dental caries.