IDMIR: identification of dysregulated miRNAs associated with disease based on a miRNA-miRNA interaction network constructed through gene expression data.

Micro ribonucleic acids (miRNAs) play a pivotal role in governing the human transcriptome in various biological phenomena. Hence, the accumulation of miRNA expression dysregulation frequently assumes a noteworthy role in the initiation and progression of complex diseases. However, accurate identification of dysregulated miRNAs still faces challenges at the current stage. Several bioinformatics tools have recently emerged for forecasting the associations between miRNAs and diseases. Nonetheless, the existing reference tools mainly identify the miRNA-disease associations in a general state and fall short of pinpointing dysregulated miRNAs within a specific disease state. Additionally, no studies adequately consider miRNA-miRNA interactions (MMIs) when analyzing the miRNA-disease associations. Here, we introduced a systematic approach, called IDMIR, which enabled the identification of expression dysregulated miRNAs through an MMI network under the gene expression context, where the network's architecture was designed to implicitly connect miRNAs based on their shared biological functions within a particular disease context. The advantage of IDMIR is that it uses gene expression data for the identification of dysregulated miRNAs by analyzing variations in MMIs. We illustrated the excellent predictive power for dysregulated miRNAs of the IDMIR approach through data analysis on breast cancer and bladder urothelial cancer. IDMIR could surpass several existing miRNA-disease association prediction approaches through comparison. We believe the approach complements the deficiencies in predicting miRNA-disease association and may provide new insights and possibilities for diagnosing and treating diseases. The IDMIR approach is now available as a free R package on CRAN (https://CRAN.R-project.org/package=IDMIR).

PathwayTMB: A pathway-based tumor mutational burden analysis method for predicting the clinical outcome of cancer immunotherapy.

Immunotherapy has become one of the most promising therapy methods for cancer, but only a small number of patients are responsive to it, indicating that more effective biomarkers are urgently needed. This study developed a pathway analysis method, named PathwayTMB, to identify genomic mutation pathways that serve as potential biomarkers for predicting the clinical outcome of immunotherapy. PathwayTMB first calculates the patient-specific pathway-based tumor mutational burden (PTMB) to reflect the cumulative extent of mutations for each pathway. It then screens mutated survival benefit-related pathways to construct an immune-related prognostic signature based on PTMB (IPSP). In a melanoma training set, IPSP-high patients presented a longer overall survival and a higher response rate than IPSP-low patients. Moreover, the IPSP showed a superior predictive effect compared with TMB. In addition, the prognostic and predictive value of the IPSP was consistently validated in two independent validation sets. Finally, in a multi-cancer dataset, PathwayTMB also exhibited good performance. Our results indicate that PathwayTMB could identify the mutation pathways for predicting immunotherapeutic survival, and their combination may serve as a potential predictive biomarker for immune checkpoint inhibitor therapy.

A pathway-based mutation signature to predict the clinical outcomes and response to CTLA-4 inhibitors in melanoma.

Immune checkpoint inhibitor (ICI) therapy has become a powerful clinical strategy for treating melanoma. The relationship between somatic mutations and the clinical benefits of immunotherapy has been widely recognized. However, the gene-based predictive biomarkers are less stable due to the heterogeneity of cancer at the individual gene level. Recent studies have suggested that the accumulation of gene mutations in biological pathways may activate antitumor immune responses. Herein, a novel pathway mutation signature (PMS) was constructed to predict the survival and efficacy of ICI therapy. In a dataset of melanoma patients treated with anti-CTLA-4, we mapped the mutated genes into the pathways and then identified seven significant mutation pathways associated with survival and immunotherapy response, which were used to construct the PMS model. According to the PMS model, the patients in the PMS-high group showed better overall survival (hazard ratio (HR) = 0.37; log-rank test, p < 0.0001) and progression-free survival (HR = 0.52; log-rank test, p = 0.014) than those in the PMS-low group. The PMS-high patients also showed a significantly higher objective response rate to anti-CTLA-4 therapy than the PMS-low patients (Fisher's exact test, p = 0.0055), and the predictive power of the PMS model was superior to that of TMB. Finally, the prognostic and predictive value of the PMS model was validated in two independent validation sets. Our study demonstrated that the PMS model can be considered a potential biomarker to predict the clinical outcomes and response to anti-CTLA-4 therapy in melanoma patients.

Identification of comutation in signaling pathways to predict the clinical outcomes of immunotherapy.

BACKGROUND: Immune checkpoint blockades (ICBs) have emerged as a promising treatment for cancer. Recently, tumour mutational burden (TMB) and neoantigen load (NAL) have been proposed to be potential biomarkers to predict the efficacy of ICB; however, they were limited by difficulties in defining the cut-off values and inconsistent detection platforms. Therefore, it is critical to identify more effective predictive biomarkers for screening patients who will potentially benefit from immunotherapy. In this study, we aimed to identify comutated signaling pathways to predict the clinical outcomes of immunotherapy. METHODS: Here, we comprehensively analysed the signaling pathway mutation status of 9763 samples across 33 different cancer types from The Cancer Genome Atlas (TCGA) by mapping the somatic mutations to the pathways. We then explored the comutated pathways that were associated with increased TMB and NAL by using receiver operating characteristic (ROC) curve analysis and multiple linear regressions. RESULTS: Our results revealed that comutation of the Spliceosome (Sp) pathway and Hedgehog (He) signaling pathway (defined as SpHe-comut+) could be used as a predictor of increased TMB and NAL and was associated with increased levels of immune-related signatures. In seven independent immunotherapy cohorts, we validated that SpHe-comut+ patients exhibited a longer overall survival (OS) or progression-free survival (PFS) and a higher objective response rate (ORR) than SpHe-comut- patients. Moreover, a combination of SpHe-comut status with PD-L1 expression further improved the predictive value for ICB therapy. CONCLUSION: Overall, SpHe-comut+ was demonstrated to be an effective predictor of immunotherapeutic benefit in seven independent immunotherapy cohorts and may serve as a potential and convenient biomarker for the clinical application of ICB therapy.

A novel pathway mutation perturbation score predicts the clinical outcomes of immunotherapy.

The link between tumor genetic variations and immunotherapy benefits has been widely recognized. Recent studies suggested that the key biological pathways activated by accumulated genetic mutations may act as an effective biomarker for predicting the efficacy of immune checkpoint inhibitor (ICI) therapy. Here, we developed a novel individual Pathway Mutation Perturbation (iPMP) method that measures the pathway mutation perturbation level by combining evidence of the cumulative effect of mutated genes with the position of mutated genes in the pathways. In iPMP, somatic mutations on a single sample were first mapped to genes in a single pathway to infer the pathway mutation perturbation score (PMPscore), and then, an integrated PMPscore profile was produced, which can be used in place of the original mutation dataset to identify associations with clinical outcomes. To illustrate the effect of iPMP, we applied it to a melanoma cohort treated with ICIs and identified seven significant perturbation pathways, which jointly constructed a pathway-based signature. With the signature, patients were classified into two subgroups with significant distinctive overall survival and objective response rate to immunotherapy. Moreover, the pathway-based signature was consistently validated in two independent melanoma cohorts. We further applied iPMP to two non-small cell lung cancer cohorts and also obtained good performance. Altogether, the iPMP method could be used to identify the significant mutation perturbation pathways for constructing the pathway-based biomarker to predict the clinical outcomes of immunotherapy. The iPMP method has been implemented as a freely available R-based package (https://CRAN.R-project.org/package=PMAPscore).

Effects of Ginsenoside Rg1 on the Biological Activity of Human Periodontal Ligament Cells.

, Objective. To investigate the effect of ginsenoside Rg1 on the biological activity of primary cultured human periodontal ligament cells (PDLC). Methods. The effects of ginsenoside Rg1 on the proliferation activity, protein synthesis, and alkaline phosphatase (ALP) activity of primary cultured human periodontal ligament cells were investigated by thiazole blue (MTT) colorimetric method, Coomassie brilliant blue method, and enzyme kinetics method. The effect of ginsenoside Rg1 on cell cycle was detected by flow cytometry, and the cells were labeled with calcium ion-sensitive fluorescent probe Fluo3/AM, and the effect of ginsenoside Rg1 on intracellular free calcium concentration was detected by laser scanning confocal microscope. Results. Compared with the control group, the experimental groups of ginsenoside Rg1 at various concentrations could significantly promote cell proliferation, and the effect time was the longest in the concentration range of 0.01-0.05 µmol/L;, Rg1 0.01umol/L and 0.05umol/L. The protein content in the 72-hour cell culture medium of the µmol/L group was significantly higher than that of the control group; the ALP activity in the 72-hour cell culture medium of the Rg1 0.01 µmol/L, 0.05 µmol/L, and 0.1 µmol/L groups was significantly higher than that of the control group; FCM assay showed that after 0.1 µmol/L Rg1 for 48 hours, compared with the control group, the proportion of cells in the early stage of DNA synthesis (G1%) of PDLC was significantly reduced, while the proportion of cells in the DNA synthesis stage (S%) and the value of cell proliferation index PrI (S + G2M)% were significantly increased; Rg1 increased intracellular calcium in PDLC cells at first and then decreased and finally maintained at a slightly higher resting calcium level than before drug addition. Conclusion. Ginsenoside Rg1 can increase the proliferation activity, protein synthesis, and alkaline phosphatase activity of periodontal ligament cells within a certain concentration range; Rg1 reduces the cells in G1 phase and increases cells in S phase of periodontal ligament fibroblasts. Change the concentration of free calcium ions in cells and promote more cells to enter a proliferative state.

Pan-cancer analysis reveals sex-specific signatures in the tumor microenvironment.

The processes of cancer initiation, progression, and response to therapy are affected by the sex of cancer patients. Immunotherapy responses largely depend on the tumor microenvironment (TME), but how sex may shape some TME features, remains unknown. Here, we analyzed immune infiltration signatures across 19 cancer types from 1771 male and 1137 female patients in The Cancer Genome Atlas to evaluate how sex may affect the tumor mutational burden (TMB), immune scores, stromal scores, tumor purity, immune cells, immune checkpoint genes, and functional pathways in the TME. Pan-cancer analyses showed higher TMB and tumor purity scores, as well as lower immune and stromal scores in male patients as compared to female patients. Lung adenocarcinoma, lung squamous carcinoma, kidney papillary carcinoma, and head and neck squamous carcinoma showed the most significant sex biases in terms of infiltrating immune cells, immune checkpoint gene expression, and functional pathways. We further focused on lung adenocarcinoma samples in order to identify and validate sex-specific immune cell biomarkers with prognostic potential. Overall, sex may affect the tumor microenvironment, and sex-specific TME biomarkers may help tailor cancer immunotherapy in certain cancer types.

DrugSim2DR: systematic prediction of drug functional similarities in the context of specific disease for drug repurposing.

BACKGROUND: Traditional approaches to drug development are costly and involve high risks. The drug repurposing approach can be a valuable alternative to traditional approaches and has therefore received considerable attention in recent years. FINDINGS: Herein, we develop a previously undescribed computational approach, called DrugSim2DR, which uses a network diffusion algorithm to identify candidate anticancer drugs based on a drug functional similarity network. The innovation of the approach lies in the drug-drug functional similarity network constructed in a manner that implicitly links drugs through their common biological functions in the context of a specific disease state, as the similarity relationships based on general states (e.g., network proximity or Jaccard index of drug targets) ignore disease-specific molecular characteristics. The drug functional similarity network may provide a reference for prediction of drug combinations. We describe and validate the DrugSim2DR approach through analysis of data on breast cancer and lung cancer. DrugSim2DR identified some US Food and Drug Administration-approved anticancer drugs, as well as some candidate drugs validated by previous studies in the literature. Moreover, DrugSim2DR showed excellent predictive performance, as evidenced by receiver operating characteristic analysis and multiapproach comparisons in various cancer datasets. CONCLUSIONS: DrugSim2DR could accurately assess drug-drug functional similarity within a specific disease context and may more effectively prioritize disease candidate drugs. To increase the usability of our approach, we have developed an R-based software package, DrugSim2DR, which is freely available on CRAN (https://CRAN.R-project.org/package=DrugSim2DR).

Development and Validation of a Three-Gene Prognostic Signature Based on Tumor Microenvironment for Gastric Cancer.

Gastric cancer (GC), which has high morbidity and low survival rate, is one of the most common malignant tumors in the world. The increasing evidences show that the tumor microenvironment (TME) is related to the occurrence and progression of tumors and the prognosis of patients. In this study, we aimed to develop a TME-based prognostic signature for GC. We first identified the differentially expressed genes (DEGs) related to the TME using the Wilcoxon rank-sum test in a training set of GC. Univariate Cox regression analysis was used to identify prognostic-related DEGs. To decrease the overfitting, we performed the least absolute shrinkage and selection operator (LASSO) regression to reduce the number of signature genes and obtained three genes (LPPR4, ADAM12, NOX4). Next, the multivariate Cox regression was performed to construct the risk score model, and a three-gene prognostic signature was developed. According to the signature, patients were classified into high-risk and low-risk groups with significantly different survival. The signature was then applied to three independent validated sets and obtained the same results. We conducted the time-dependent Receiver Operating Characteristic (ROC) curve analysis to evaluate our signature. We further evaluated the differential immune characters between high-risk and low-risk patients to reveal the potential immune mechanism of the impact on the prognosis of the model. Overall, we identified a three-gene prognostic signature based on TME to predict the prognosis of patients with GC and facilitate the development of a precise treatment strategy.

Cadmium Induces Acute Liver Injury by Inhibiting Nrf2 and the Role of NF-κB, NLRP3, and MAPKs Signaling Pathway.

Acute Cadmium (Cd) exposure usually induces hepatotoxicity. It is well known that oxidative stress and inflammation causes Cd-induced liver injury. However, the effect of nuclear factor erythroid 2-related factor 2 (Nrf2) in Cd-induced liver injury is not completely understood. In this study, we observed Cd-induced liver damage and the potential contribution of Nrf2, nuclear factor-κB (NF-κB), Nod-like receptor 3 (NLRP3), and mitogen-activated protein kinases (MAPKs) signaling pathways. Changes in serum transaminases and proinflammatory cytokines expression showed that Cd could induce acute hepatotoxicity. Moreover, Nrf2 and its downstream heme oxygenase 1 (HO-1) were inhibited by Cd exposure, and Kelch-like ECH-associated protein 1 (Keap1), the inhibitory protein of Nrf2, was increased. Furthermore, NF-κB, NLRP3, and MAPKs signaling pathways were all activated by Cd intoxication. In conclusion, the inhibition of Nrf2, HO-1, and the activation of NF-κB, NLRP3, and MAPKs all contribute to Cd-induced liver injury.

Construction of vascularized tissue-engineered bone with polylysine-modified coral hydroxyapatite and a double cell-sheet complex to repair a large radius bone defect in rabbits.

In this study, the potential of vascularized tissue-engineered bone constructed by a double cell-sheet (DCS) complex and polylysine (PLL)-modified coralline hydroxyapatite (CHA) to repair large radius bone defects was investigated in rabbits. Firstly, the DCS complex was obtained after rabbit adipose-derived mesenchymal stem cell (ADSC) culture was induced. Secondly, PLL-CHA composite scaffolds with different concentrations of PLL were prepared by the soaking and vacuum freeze-drying methods, and then the scaffolds were characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, compression performance testing and cytocompatibility evaluation. Thirdly, DCS-PLL-CHA vascularized tissue-engineered bone was constructed in vitro and transplanted into a large radius bone defect model in rabbits. Finally, the potential of the DCS-PLL-CHA vascularized tissue-engineered bone to repair the large bone defect was evaluated through general observations, laser speckle imaging, scanning electron microscopy (SEM), histological staining, radiography observations and RT-PCR. The in vitro experimental results showed that the DCS complex provided a very large cell reserve, which carried a large number of osteoblasts and vascular endothelial cells that were induced in vitro. When the DCS complex was combined with the PLL-CHA scaffold in vitro, the effects of PLL on cell adhesion, proliferation and differentiation led to a situation similar to the chemotaxis of the body, making the combined complex more conducive to graft cellularization than the DCS complex alone. The in vivo experiments showed blood supply on the surface of the callus in each group, and the amount of blood perfusion on the surface of the defect area was almost equal among the groups. At 12 weeks, the surface of the DCS-PLL-CHA group was completely wrapped by bone tissue and osteoids, the cortical bone image was basically continuous, and the medullary cavity was mainly perforated. A large amount of well-arranged lamellar bone was formed, a small amount of undegraded CHA exhibited a linear pattern, and a large amount of bone filling could be seen in the pores. At 12 weeks, the expression levels of BGLAP, SPP1 and VEGF were similar in each group, but PECAM1 expression was higher in the DCS-PLL-CHA group than in the autogenous bone group and CHA group. The results showed that PLL could effectively promote the adhesion, proliferation and differentiation of ADSCs and that DCS-PLL-CHA vascularized tissue-engineered bone has potential for bone regeneration and bone reconstruction and can be used to repair large bone defects. STATEMENT OF SIGNIFICANCE: 1. PLL-CHA composite scaffolds with different concentrations of PLL were prepared by the soaking and vacuum freeze-drying methods. 2. The vascularized tissue-engineered bone was constructed by the double cell sheet (DCS) complex combined with PLL-CHA scaffolds. 3. The DCS-PLL-CHA vascularized tissue-engineered bone has potential for bone regeneration and bone reconstruction and can be used to repair large bone defects.

[Causes of re-emergence of Oncomelania snails in hardened ditches].

OBJECTIVE: To understand the impact factors of the re-emergence of Oncomelania snails in hardened ditches so as to find out the measures to improve the effect of snail eradication. METHODS: Thirteen infected townships from Jingmen City were randomly selected and investigated with the retrospective method and the field survey. All the data were analyzed for evaluating the effect of the hardened ditches on snail eradication and finding out the causes of the re-emergence of snails in hardened ditches RESULTS: After on-site investigation of 151 hardened ditches, the eradication rate of snail areas was 78.79%, and 71 ditches were founded with snails and the re-emergence rate was 47.02%. The major factors of the snail re-emergence were the spread of the snails from the upstream, the dilapidation of the hardened ditches, no using molluscicides before the hardened ditches, and the snails being brought by the engineering construction. CONCLUSIONS: The only hardened ditches can not eradicate the snails. We should manage an overall plan when processing the ditches hardening project, implementation with molluscicides before the project and strengthen the maintenance of the hardened ditches.

Narrow bandpass tunable terahertz filter based on photonic crystal cavity.

We have fabricated a very narrow bandpass tunable terahertz (THz) filter based on a one-dimensional photonic crystal cavity. Since the filter consists of silicon wafers and air spacers, it has a very high quality factor of about 1500. The full width at half maximum (FWHM) of the passband is only about 200 MHz, and the peak transmission is higher than -4 dB. Besides, the central frequency can be tuned rapidly over the entire bandgap with the length of cavity adjusted by a motorized linear stage. Further analytical calculations indicate that a high-Q tunable filter with both high peak transmission and wide tunable range is possible if thinner silicon layers are used.