Highly expressed of BID indicates poor prognosis and mediates different tumor microenvironment characteristics in clear cell renal cell carcinoma.

BACKGROUND: Studies have found that BH3 interacting domain death agonist (BID) is closely related to the occurrence and development of many kinds of tumors. However, little attention has been paid to the situation of BID in clear cell renal cell carcinoma (ccRCC). So, our aim was to explore the effect of BID in ccRCC. METHODS: Survival analysis, ROC curve, correlation analysis and Cox regression analysis were executed to analyze the prognostic value and clinical correlation of BID in ccRCC. The risk prognosis model was constructed in the training cohort and further validated in the internal testing cohort, ICGC cohort, and GEO cohort. Transcriptome sequencing and immunohistochemical staining of clinical specimens were used to validate the results of bioinformatics analysis. The GSEA, ESTIMATE algorithm, CIBERSORT algorithm, ssGSEA, TIDE score, correlation and difference analysis were used to analyze the effects of BID on immune infiltration in tumor microenvironment (TME). RESULTS: BID was highly expressed in ccRCC tissues, which was verified by transcriptome sequencing and immunohistochemical staining of clinical specimens. Patients with high expression of BID had a worse prognosis. BID is an independent prognostic factor for ccRCC. The prognostic model based on BID can accurately predict the prognosis of patients in different cohorts. In addition, the expression levels of BID was closely related to immunomodulatory molecules such as PD-1, LAG3, and CTLA4. Enrichment analysis indicated that BID was significantly enriched in immune-related responses and cancer-related pathways. The change of BID expression mediates different characteristics of immune infiltration in TME. CONCLUSIONS: BID is highly expressed in ccRCC, which is a reliable biomarker of ccRCC prognosis. It is closely related to TME, and may be a potential target for immunotherapy in patients with ccRCC.

YOLOv8-PD: an improved road damage detection algorithm based on YOLOv8n model.

Road damage detection is an crucial task to ensure road safety. To tackle the issues of poor performance on multi-scale pavement distresses and high costs in detection task, this paper presents an improved lightweight road damage detection algorithm based on YOLOv8n, named YOLOv8-PD (pavement distress). Firstly, a BOT module that can extract global information of road damage images is proposed to adapt to the large-span features of crack objects. Secondly, the introduction of the large separable kernel attention (LKSA) mechanism enhances the detection accuracy of the algorithm. Then, a C2fGhost block is constructed in the neck network to strengthen the feature extraction of complex road damages while reducing the computational load. Furthermore, we introduced lightweight shared convolution detection head (LSCD-Head) to improve feature expressiveness and reduce the number of parameters. Finally, extensive experiments on the RDD2022 dataset yield a model with parametric and computational quantities of 2.3M and 6.1 GFLOPs, which are only 74.1% and 74.3% of the baseline, and the mAP reaches an improvement of 1.4 percentage points from the baseline. In addition, experimental results on the RoadDamage dataset show that the mAP increased by 4.2% and this algorithm has good robustness. This method can provide a reference for the automatic detection method of pavement distress.

Construction and validation of a chromatin regulator-related gene signature for prognostic and therapeutic significance of clear cell renal cell carcinoma.

Background: Epigenetic alterations driven by chromatin regulators (CRs) are well-recognized cancer hallmarks. Growing evidence suggests that the imbalance of CRs may lead to the occurrence of various diseases including tumors. However, the role and prognostic value of CRs in clear cell renal cell carcinoma (ccRCC) remain undefined. Methods: Consensus clustering analysis was used to identify different subtypes. Univariate and multivariate Cox regression analysis were performed to identify prognosis-related CRs and constructed a risk model. Transcriptome sequencing was used to verify gene expression levels. Kaplan-Meier survival analysis was used to compare overall survival (OS) between high- and low-risk groups. The area under the curve (AUC) value of the receiver operating characteristic (ROC) curve was used to evaluate the performance of the model. The ESTIMATE algorithm and single-sample gene set enrichment analysis (ssGSEA) were executed to evaluate the immune characteristics of samples. Correlation analysis was used to assess the relationship between risk score and immune checkpoint genes, the relationship between expression levels of CRs and immune cell infiltration and drug therapeutic response. Finally, we also compared differences in drug sensitivity between low- and high-risk groups. Results: We identified three CRs-related subtypes with different characteristics. A prognostic model was built with four CRs and can precisely predict the OS of patients in different risk groups. The model has good stability and applicability and was further verified in the internal and external dataset. The transcriptomic levels of the four CRs were also validated, and the risk score was an independent prognostic factor for ccRCC. Obvious differences in the immune microenvironment and the expression levels of immune checkpoints were observed in low- and high-risk group. Higher immune activity and immune cell infiltration were found in the high-risk group. Besides, the expression levels of CRs were associated with drug therapeutic response. Patients with high-risk score may be more sensitive to gemcitabine, vinblastine, paclitaxel, axitinib, sunitinib, and temsirolimus. Conclusions: CRs were strongly associated with the occurrence and development of ccRCC. Targeting CRs may become a new therapeutic strategy for ccRCC. Besides, CRs-related gene signature can predict the prognosis and therapeutic significance of ccRCC, which provides an important reference for clinical decision-making.

Identification of pyroptosis-related subtypes and comprehensive analysis of characteristics of the tumor microenvironment infiltration in clear cell renal cell carcinoma.

Pyroptosis is a kind of programmed cell death triggered by the inflammasome. Growing evidence has revealed the crucial utility of pyroptosis in tumors. However, the potential mechanism of pyroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear. In this research, we systematically analyze the genetic and transcriptional alterations of pyroptosis-related genes (PRGs) in ccRCC, identify pyroptosis-related subtypes, analyze the clinical and microenvironmental differences among different subtypes, develop a corresponding prognostic model to predict the prognosis of patients, and interpret the effect of pyroptosis on ccRCC microenvironment. This study provides a new perspective for a comprehensive understanding of the role of pyroptosis in ccRCC and its impact on the immune microenvironment, and a reliable scoring system was established to predict patients' prognosis.

Construction and validation of programmed cell death-based molecular clusters for prognostic and therapeutic significance of clear cell renal cell carcinoma.

As the dominant histological subtype of kidney cancer, clear cell renal cell carcinoma (ccRCC) poorly responds to conventional chemotherapy and radiotherapy. Although novel immunotherapies such as immune checkpoint inhibitors could have a durable effect in treating ccRCC patients, the limited availability of dependable biomarkers has restricted their application in clinic. In the study of carcinogenesis and cancer therapies, there has been a recent emphasis on researching programmed cell death (PCD). In the current study, we discovered the enriched and prognostic PCD in ccRCC utilizing gene set enrichment analysis (GSEA) and investigate the functional status of ccRCC patients with different PCD risks. Then, genes related to PCD that had prognostic value in ccRCC were identified for the conduction of non-negative matrix factorization to cluster ccRCC patients. Next, the tumor microenvironment, immunogenicity, and therapeutic response in different molecular clusters were analyzed. Among PCD, apoptosis and pyroptosis were enriched in ccRCC and correlated with prognosis. Patients with high PCD levels were related to poor prognosis and a rich but suppressive immune microenvironment. PCD-based molecular clusters were identified to differentiate the clinical status and prognosis of ccRCC. Moreover, the molecular cluster with high PCD levels may correlate with high immunogenicity and a favorable therapeutic response to ccRCC. Furthermore, a simplified PCD-based gene classifier was established to facilitate clinical application and used transcriptome sequencing data from clinical ccRCC samples to validate the applicability of the gene classifier. We thoroughly extended the understanding of PCD in ccRCC and constructed a PCD-based gene classifier for differentiation of the prognosis and therapeutic efficacy in ccRCC.

An investigation on graphite behavior and coating properties in the molten pool based on different powder particle sizes.

This paper aims to explore the influence mechanism of powder particle sizes on the microstructure and properties of coatings and identify the effect of powder particle size difference on the coating graphite phase. NbC-reinforced Ni-based coatings were in-situ synthesized by laser cladding to investigate the impact of powder particle sizes on the morphology, structure, and properties of coatings. The results indicate that increasing powder particle size enlarges the coating area and decreases the coating width and dilution ratio. Meanwhile, the defect ratio first increases and then decreases. The XRD test suggests that the coating mainly consists of NbC, solid solution (Fe, Ni), B4C, Cr2C, and CrB2. Different powder particle sizes do not change the phase composition of coatings but affect the graphite phase morphology. The morphology transforms from spherical to flocculent as the powder size varies from micrometer to nanometer. The hardness of coatings gradually increases, and the friction and wear properties decrease with the growth of powder particle size. The dispersed graphite phase in the nano coating plays a self-lubricating role in the friction and wear process. This research provides a reference and theoretical basis for selecting powder particle size in laser cladding.

Identification of a basement membrane-based risk scoring system for prognosis prediction and individualized therapy in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) belongs to one of the 10 most frequently diagnosed cancers worldwide and has a poor prognosis at the advanced stage. Although multiple therapeutic agents have been proven to be curative in ccRCC, their clinical application was limited due to the lack of reliable biomarkers. Considering the important role of basement membrane (BM) in tumor metastasis and TME regulation, we investigated the expression of BM-related genes in ccRCC and identified prognostic BM genes through differentially expression analysis and univariate cox regression analysis. Then, BM-related ccRCC subtypes were recognized through consensus non-negative matrix factorization based on the prognostic BM genes and evaluated with regard to clinical and TME features. Next, utilizing the differentially expressed genes between the BM-related subtypes, a risk scoring system BMRS was established after serial analysis of univariate cox regression analysis, lasso regression analysis, and multivariate cox regression analysis. Time-dependent ROC curve revealed the satisfactory prognosis predictive capacity of BMRS with internal, and external validation. Multivariate analysis proved the independent predictive ability of BMRS and a BMRS-based nomogram was constructed for clinical application. Some featured mutants were discovered through genomic analysis of the BMRS risk groups. Meanwhile, the BMRS groups were found to have distinct immune scores, immune cell infiltration levels, and immune-related functions. Moreover, with the help of data from The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC), the potential of BMRS in predicting therapeutic response was evaluated and some possible therapeutic compounds were proposed through ConnectivityMap (CMap). For the practicability of BMRS, we validated the expression of BMRS-related genes in clinical samples. After all, we identified BM-related ccRCC subtypes with distinct clinical and TME features and constructed a risk scoring system for the prediction of prognosis, therapeutic responses, and potential therapeutic agents of ccRCC. As ccRCC systemic therapy continues to evolve, the risk scoring system BMRS we reported may assist in individualized medication administration.

Microstructures and Properties of NbC-Reinforced Ni-Based Coatings Synthesized In Situ by Ultrasonic Vibration-Assisted Laser Cladding.

This paper aims to explore the mechanism of an ultrasonic applied field on the microstructures and properties of coatings, and clarify the evolution of the molten pool under different ultrasonic frequencies. The Taguchi experimental design method was adopted in this paper. NbC-reinforced Ni-based coatings were in situ synthesized by laser cladding to investigate the effects of ultrasonic vibration process parameters on the microstructure, pore area, microhardness, and wear resistance of the cladding layer. The results show that the pore area decreases first and then increases as ultrasonic power increases from 600 to 900 W and ultrasonic frequency from 23 to 40 kHz. On the contrary, the hardness and wear resistance increase at first and then decrease. The pore area is minimized at 800 W ultrasonic power and 32 kHz ultrasonic frequency, and the hardness is maximized at 600 W ultrasonic power and 40 kHz ultrasonic frequency. Meanwhile, the highest wear resistance can be obtained when ultrasonic power is 700 W and ultrasonic frequency is 32 kHz. Based on the phase structure analysis, the cladding layer mainly consists of FeNi3, NbC, B4C, and CrB2. Ultrasonic vibration will not change the phase composition of the layer. Combined with the varying G/R value and cooling rate, the reasons for the change in grain morphology in different areas were analyzed to reveal the evolution mechanism of the molten pool under the influence of ultrasound.

Integrative Analysis of the Genomic and Immune Microenvironment Characteristics Associated With Clear Cell Renal Cell Carcinoma Progression: Implications for Prognosis and Immunotherapy.

Unlike early clear cell renal cell carcinoma (ccRCC), locally advanced and metastatic ccRCC present poor treatment outcomes and prognosis. As immune checkpoint inhibitors have achieved favorable results in the adjuvant treatment of metastatic ccRCC, we aimed to investigate the immunogenomic landscape during ccRCC progression and its potential impact on immunotherapy and prognosis. Using multi-omics and immunotherapy ccRCC datasets, an integrated analysis was performed to identify genomic alterations, immune microenvironment features, and related biological processes during ccRCC progression and evaluate their relevance to immunotherapy response and prognosis. We found that aggressive and metastatic ccRCC had higher proportions of genomic alterations, including SETD2 mutations, Del(14q), Del(9p), and higher immunosuppressive cellular and molecular infiltration levels. Of these, the Del(14q) might mediate immune escape in ccRCC via the VEGFA-VEGFR2 signaling pathway. Furthermore, immune-related pathways associated with ccRCC progression did not affect the immunotherapeutic response to ccRCC. Conversely, cell cycle pathways not only affected ccRCC progression and prognosis, but also were related to ccRCC immunotherapeutic response resistance. Overall, we described the immunogenomic characteristics of ccRCC progression and their correlations with immunotherapeutic response and prognosis, providing new insights into their prediction and the development of novel therapeutic strategies.

ICH-LR2S2: a new risk score for predicting stroke-associated pneumonia from spontaneous intracerebral hemorrhage.

PURPOSE: We develop a new risk score to predict patients with stroke-associated pneumonia (SAP) who have an acute intracranial hemorrhage (ICH). METHOD: We applied logistic regression to develop a new risk score called ICH-LR2S2. It was derived from examining a dataset of 70,540 ICH patients between 2015 and 2018 from the Chinese Stroke Center Alliance (CSCA). During the training of ICH-LR2S2, patients were randomly divided into two groups - 80% for the training set and 20% for model validation. A prospective test set was developed using 12,523 patients recruited in 2019. To further verify its effectiveness, we tested ICH-LR2S2 on an external dataset of 24,860 patients from the China National Stroke Registration Management System II (CNSR II). The performance of ICH-LR2S2 was measured by the area under the receiver operating characteristic curve (AUROC). RESULTS: The incidence of SAP in the dataset was 25.52%. A 24-point ICH-LR2S2 was developed from independent predictors, including age, modified Rankin Scale, fasting blood glucose, National Institutes of Health Stroke Scale admission score, Glasgow Coma Scale score, C-reactive protein, dysphagia, Chronic Obstructive Pulmonary Disease, and current smoking. The results showed that ICH-LR2S2 achieved an AUC = 0.749 [95% CI 0.739-0.759], which outperforms the best baseline ICH-APS (AUC = 0.704) [95% CI 0.694-0.714]. Compared with the previous ICH risk scores, ICH-LR2S2 incorporates fasting blood glucose and C-reactive protein, improving its discriminative ability. Machine learning methods such as XGboost (AUC = 0.772) [95% CI 0.762-0.782] can further improve our prediction performance. It also performed well when further validated by the external independent cohort of patients (n = 24,860), ICH-LR2S2 AUC = 0.784 [95% CI 0.774-0.794]. CONCLUSION: ICH-LR2S2 accurately distinguishes SAP patients based on easily available clinical features. It can help identify high-risk patients in the early stages of diseases.

Oncolytic Viro-Immunotherapy: An Emerging Option in the Treatment of Gliomas.

The prognosis of malignant gliomas remains poor, with median survival fewer than 20 months and a 5-year survival rate merely 5%. Their primary location in the central nervous system (CNS) and its immunosuppressive environment with little T cell infiltration has rendered cancer therapies mostly ineffective, and breakthrough therapies such as immune checkpoint inhibitors (ICIs) have shown limited benefit. However, tumor immunotherapy is developing rapidly and can help overcome these obstacles. But for now, malignant gliomas remain fatal with short survival and limited therapeutic options. Oncolytic virotherapy (OVT) is a unique antitumor immunotherapy wherein viruses selectively or preferentially kill tumor cells, replicate and spread through tumors while inducing antitumor immune responses. OVTs can also recondition the tumor microenvironment and improve the efficacy of other immunotherapies by escalating the infiltration of immune cells into tumors. Some OVTs can penetrate the blood-brain barrier (BBB) and possess tropism for the CNS, enabling intravenous delivery. Despite the therapeutic potential displayed by oncolytic viruses (OVs), optimizing OVT has proved challenging in clinical development, and marketing approvals for OVTs have been rare. In June 2021 however, as a genetically engineered OV based on herpes simplex virus-1 (G47Δ), teserpaturev got conditional and time-limited approval for the treatment of malignant gliomas in Japan. In this review, we summarize the current state of OVT, the synergistic effect of OVT in combination with other immunotherapies as well as the hurdles to successful clinical use. We also provide some suggestions to overcome the challenges in treating of gliomas.

A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction. METHODS: The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature. RESULTS: Consequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8+ T cells, resting mast cells, and naïve B cells were significantly correlated with the signature. CONCLUSION: Therefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.

In vitro and in vitro toxicity study of diesel exhaust particles using BEAS-2B cell line and the nematode Caenorhabditis elegans as biological models.

It is well accepted that diesel exhaust particles (DEPs) are highly associated with improper function of organ systems. In this study, DEP toxicity was performed by using in vitro human BEAS-2B cell line and in vivo animal model, namely, Caenorhabditis elegans (C. elegans). The potential toxicity of DEP was assessed by the apical endpoints of BEAS-2B cell line and reflections of C. elegans under exposure scenarios of 0~50 µg mL-1 DEP. With the increase of DEP exposure concentration, microscopic accumulations in the cytoplasm of cell line and intestine of C. elegans were observed. Such invasion of DEP impaired the behaviors of C. elegans as well as its un-exposed offspring and caused significant impeded locomotion. Moreover, the disorders of dopaminergic function were observed simultaneously under DEP exposure, specifically manifested by the decreased transcriptional expression of dat-1. The stress responses instructed by the expression of hsp-16.2 were also increased sharply in TJ375 strain of C. elegans at DEP concentrations of 1 and 10 µg mL-1. In the case of cellular reactions to DEP exposure, the injuries of membrane integrity and the decreased viability of cell line were simultaneously identified, and reactive oxygen species (ROS), damaged DNA fragment, and upregulated apoptosis were monotonically elevated in cell lines with the increase of DEP concentrations. This study provided a systematic insight into toxicity of DEP both in vivo and vitro, demonstrating that DEP exposure could disturb the stability of cell system and further threat the stability of organism.

Identifying 4 Novel lncRNAs as Potential Biomarkers for Acute Rejection and Graft Loss of Renal Allograft.

Acute rejection (AR) after kidney transplant is one of the major obstacles to obtain ideal graft survival. Reliable molecular biomarkers for AR and renal allograft loss are lacking. This study was performed to identify novel long noncoding RNAs (lncRNAs) for diagnosing AR and predicting the risk of graft loss. The several microarray datasets with AR and nonrejection specimens of renal allograft downloaded from Gene Expression Omnibus database were analyzed to screen differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). Univariate and multivariate Cox regression analyses were used to identify optimal prognosis-related DElncRNAs for constructing a risk score model. 39 common DElncRNAs and 185 common DEmRNAs were identified to construct a lncRNA-mRNA regulatory relationship network. DElncRNAs were revealed to regulate immune cell activation and proliferation. Then, 4 optimal DElncRNAs, ATP1A1-AS1, CTD-3080P12.3, EMX2OS, and LINC00645, were selected from 17 prognostic DElncRNAs to establish the 4-lncRNA risk score model. In the training set, the high-risk patients were more inclined to graft loss than the low-risk patients. Time-dependent receiver operating characteristics analysis revealed the model had good sensitivity and specificity in prediction of 1-, 2-, and 3-year graft survival after biopsy (AUC = 0.891, 0.836, and 0.733, respectively). The internal testing set verified the result well. Gene set enrichment analysis which expounded NOD-like receptor, the Toll-like receptor signaling pathways, and other else playing important role in immune response was enriched by the 4 lncRNAs. Allograft-infiltrating immune cells analysis elucidated the expression of 4 lncRNAs correlated with gamma delta T cells and eosinophils, etc. Our study identified 4 novel lncRNAs as potential biomarkers for AR of renal allograft and constructed a lncRNA-based model for predicting the risk of graft loss, which would provide new insights into mechanisms of AR.

Effects of carbon sources on the removal of ammonium, nitrite and nitrate nitrogen by the red yeast Sporidiobolus pararoseus Y1.

Heterotrophic nitrification and aerobic denitrification (HN-AD), which is primarily performed by bacteria rather than fungi, is an attractive approach for nitrogen removal. In this study, a red yeast, Sporidiobolus pararoseus Y1, was isolated and shown to exhibit optimal growth and nitrogen removal efficiency on glucose, followed by citrate, sucrose, acetate and starch. The nitrogen removal efficiency increased with increasing initial concentrations of NH4+-N, NO2--N and NO3--N from 14 to 140 mg·L-1. At an initial nitrogen concentration of 140 mg·L-1, the maximum removal efficiencies of NH4+-N, NO2--N and NO3--N were 98.67%, 97.13% and 83.51% after 72 h incubation, while those of corresponding total nitrogen were 88.89%, 81.31% and 70.18%, respectively. The nitrification (amoA) and denitrification genes (nirK and napA) were amplified from Y1. These results suggest that yeast are also capable of HN-AD, which can be used to remove nitrogen in wastewater systems.

Phocea, Pseudoflavonifractor and Lactobacillus intestinalis: Three Potential Biomarkers of Gut Microbiota That Affect Progression and Complications of Obesity-Induced Type 2 Diabetes Mellitus.

PURPOSE: The purpose of this study was to explore the difference and association between intestinal microbiota and plasma metabolomics between type 2 diabetes mellitus (T2DM) and normal group and to identify potential microbiota biomarkers that contribute the most to the difference in metabolites. METHODS: Six male ZDF model (fa/fa) rats were fed by a Purina #5008 Lab Diet (crude protein 23.5%, crude fat 6.5%) for 3 weeks and their age-matched 6 ZDF control (fa/+) rats were fed by normal rodent diet. Their stool and blood samples were collected at 12 weeks. To analyze the microbial populations in these samples, we used a 16S rRNA gene sequencing approach. Liquid chromatography-mass spectrometry (LC-MS) followed by multivariate statistical analysis was applied to the plasma metabolites profiling. Correlation analysis of them was calculated by Pearson statistical method. RESULTS: Twelve potential biomarkers of intestinal microbial flora and 357 differential metabolites were found in ZDF fa/fa rats, among which there are three flora that contributed the most to the perturbation of metabolites, including genus Phocea, Pseudoflavonifractor and species Lactobacillus intestinalis. CONCLUSION: Our study demonstrates the alterations of the abundance and diversity of the intestinal microbiota and the perturbation of metabolites in ZDF rats (fa/fa). We found three potential biomarkers of intestinal microbiota that may lead to perturbation in plasma metabolites. This may prompt new pathogenesis of obesity-related T2DM, but we also need to study further about the causal relationship between intestinal microbe and T2DM, so as to find the target of T2DM treatment or preventive measures.

Adjuvant radiotherapy and chemotherapy for patients with breast phyllodes tumors: a systematic review and meta-analysis.

BACKGROUND: As the efficacy of radiotherapy and chemotherapy for treatment of phyllodes tumors (PTs) remains unclear, this study aimed to review all available data and evaluate the roles of radiotherapy and chemotherapy in PT treatment. METHODS: We performed a comprehensive search of databases, including PubMed, Web of Science and the Cochrane Library. The outcomes of interest included the local recurrence (LR) rate, metastasis rate, disease-free survival rate and overall survival rate. RESULTS: Seventeen studies enrolling 696 patients were included in this random effect meta-analysis. Subgroup analysis and meta-regression were also conducted to determine study heterogeneity. A pooled local recurrence rate of 8% (95% CI: 1-22%) was observed with a statistical heterogeneity of I2 = 86.6% (p < 0.01) for radiotherapy. This was lower than the recurrence rate of 12% for simple surgical treatment (95% CI: 7-18%). Meta-regression analysis found that surgical margin status was the main source of heterogeneity (p = 0.04). The metastasis rate of 4% (95% CI: 0-11%) for patients receiving radiotherapy without significant heterogeneity was also lower than the rate for the simple surgery group (8, 95% CI: 3-15%). The available data for chemotherapy were too limited to support meta-analysis. Accordingly, we offer a pure review of these data. CONCLUSION: Our findings suggest that radiotherapy is effective in achieving local disease control and preventing metastasis.

LncRNA NKILA suppresses TGF-ß-induced epithelial-mesenchymal transition by blocking NF-κB signaling in breast cancer.

TGF-ß plays a central role in mediating epithelial-mesenchymal transition (EMT) by activating the Smad pathway. In addition, accumulating evidence suggests that TGF-ß-induced EMT is NF-κB-dependent in various cancer types. However, it is largely unclear if NF-κB mediates TGF-ß-induced EMT in breast cancer, and if this mediation occurs, the regulatory mechanisms are unknown. In our study, we found that TGF-ß activates the NF-κB pathway. Inhibition of NF-κB signaling markedly abrogates TGF-ß-induced EMT. By studying the regulatory mechanism of TGF-ß-induced NF-κB signaling, we found that lncRNA NKILA was upregulated by TGF-ß and was essential for the negative feedback regulation of the NF-κB pathway. Accordingly, overexpression of NKILA significantly reduced TGF-ß-induced tumor metastasis in vivo. Consistent with the results from mice, the expression of NKILA was negatively correlated with EMT phenotypes in clinical breast cancer samples. Collectively, our study indicated that the NKILA-mediated negative feedback affects TGF-ß-induced NF-κB activation and that NKILA may be a therapeutic molecule in breast cancer metastasis via inhibition of EMT.

miR-200b regulates epithelial-mesenchymal transition of chemo-resistant breast cancer cells by targeting FN1.

Chemotherapy is a cornerstone treatment for early and advanced stage breast cancer patients. However, resistance to chemotherapy remains a major obstacle, resulting in disease relapse and progression. Emerging studies demonstrated that miRNAs regulate chemotherapy-induced epithelial-mesenchymal transition (EMT) and drug resistance, but the underlying mechanisms remain unclear. Here we established a doxorubicin-resistant breast cancer cell line MCF-7/Adr, and found these cells exhibited an EMT phenotype featured by a fibroblast-like morphology, increased the capacity of migration and invasion, and underwent the changes of molecular markers of EMT including E-cadherin, N-cadherin, and vimentin. We then compared the miRNA expression profiles between MCF-7/Adr and parental MCF-7 by miRNA microarray, and identified miR-200b as the most dramatically down-regulated miRNA. Overexpression of miR-200b in chemo-resistant cells reversed the EMT phenotype and increased sensitivity to doxorubicin. Inhibition of miR-200b in parental cells induced EMT and resistance to doxorubicin. Furthermore, we characterized the target gene of miR-200b, and showed that overexpression of miR-200b down-regulated FN1 expression and the luciferase activity. Compared with the parental cells, FN1 was significantly elevated in MCF-7/Adr cells. Knockdown of FN1 reversed mesenchymal morphology, inhibited cell migration and invasion, and sensitized cells to doxorubicin. Our data suggest that miR-200b regulates EMT of chemo-resistant breast cancer cells by targeting FN1. miR-200b-based therapy may be an effective strategy in treating advanced breast cancer patients.

Novel chimeric transcript RRM2-c2orf48 promotes metastasis in nasopharyngeal carcinoma.

Recently, chimeric transcripts have been found to be associated with the pathogenesis and poor prognosis of malignant tumors. Through our preliminary experiment, a novel chimeric transcript called chimeric transcript RRM2-c2orf48 was detected in C666-1, a classical cell line of human nasopharyngeal carcinoma (NPC). Therefore, the objective of this study was to demonstrate the existence and expression of novel chimeric transcript RRM2-c2orf48 and to explore the main functions and mechanisms of RRM2-c2orf48 in NPC. In this study, the expression of RRM2-c2orf48 was evaluated in NPC cells and specimens. Effects of RRM2-c2orf48 on migration and invasive capacities were detected in vivo and vitro. Moreover, ways in which RRM2-c2orf48 increases the invasive capacities of NPC were explored. As a result, the presence of novel chimeric transcript RRM2-c2orf48 was confirmed in C666-1 by RT-PCR and sequencing, and it was a read-through between RRM2 and c2orf48 through the transcription of interchromosome. Higher expressions of novel RRM2-c2orf48 were detected in NPC cell lines and NPC tissue specimens relative to the controls and its expression was be statistically relevant to TNM staging. High level of RRM2-c2orf48 could increase the migration and invasive capacities of NPC cells, potentially as a result of NPC cell epithelial-mesenchymal transition. RRM2-c2orf48 could also enhance resistance of chemotherapy. In vivo, RRM2-c2orf48 could enhance lung and lymph node metastasis in nude mice. These results demonstrate that high levels of RRM2-c2orf48 expression may be a useful predictor of NPC patients of metastatic potency, presenting potential implications for NPC diagnosis and therapy.