ncRNADrug: a database for validated and predicted ncRNAs associated with drug resistance and targeted by drugs.

Drug resistance is a major barrier in cancer treatment and anticancer drug development. Growing evidence indicates that non-coding RNAs (ncRNAs), especially microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), play pivotal roles in cancer progression, therapy, and drug resistance. Furthermore, ncRNAs have been proven to be promising novel therapeutic targets for cancer treatment. Reversing dysregulated ncRNAs by drugs holds significant potential as an effective therapeutic strategy for overcoming drug resistance. Therefore, we developed ncRNADrug, an integrated and comprehensive resource that records manually curated and computationally predicted ncRNAs associated with drug resistance, ncRNAs targeted by drugs, as well as potential drug combinations for the treatment of resistant cancer. Currently, ncRNADrug collects 29 551 experimentally validated entries involving 9195 ncRNAs (2248 miRNAs, 4145 lncRNAs and 2802 circRNAs) associated with the drug resistance of 266 drugs, and 32 969 entries involving 10 480 ncRNAs (4338 miRNAs, 6087 lncRNAs and 55 circRNAs) targeted by 965 drugs. In addition, ncRNADrug also contains associations between ncRNAs and drugs predicted from ncRNA expression profiles by differential expression analysis. Altogether, ncRNADrug surpasses the existing related databases in both data volume and functionality. It will be a useful resource for drug development and cancer treatment. ncRNADrug is available at http://www.jianglab.cn/ncRNADrug.

DRdriver: identifying drug resistance driver genes using individual-specific gene regulatory network.

Drug resistance is one of principal limiting factors for cancer treatment. Several mechanisms, especially mutation, have been validated to implicate in drug resistance. In addition, drug resistance is heterogeneous, which makes an urgent need to explore the personalized driver genes of drug resistance. Here, we proposed an approach DRdriver to identify drug resistance driver genes in individual-specific network of resistant patients. First, we identified the differential mutations for each resistant patient. Next, the individual-specific network, which included the genes with differential mutations and their targets, was constructed. Then, the genetic algorithm was utilized to identify the drug resistance driver genes, which regulated the most differentially expressed genes and the least non-differentially expressed genes. In total, we identified 1202 drug resistance driver genes for 8 cancer types and 10 drugs. We also demonstrated that the identified driver genes were mutated more frequently than other genes and tended to be associated with the development of cancer and drug resistance. Based on the mutational signatures of all driver genes and enriched pathways of driver genes in brain lower grade glioma treated by temozolomide, the drug resistance subtypes were identified. Additionally, the subtypes showed great diversity in epithelial-mesenchyme transition, DNA damage repair and tumor mutation burden. In summary, this study developed a method DRdriver for identifying personalized drug resistance driver genes, which provides a framework for unlocking the molecular mechanism and heterogeneity of drug resistance.

Estimating Metastatic Risk of Pancreatic Ductal Adenocarcinoma at Single-Cell Resolution.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by intra-tumoral heterogeneity, and patients are always diagnosed after metastasis. Thus, finding out how to effectively estimate metastatic risk underlying PDAC is necessary. In this study, we proposed scMetR to evaluate the metastatic risk of tumor cells based on single-cell RNA sequencing (scRNA-seq) data. First, we identified diverse cell types, including tumor cells and other cell types. Next, we grouped tumor cells into three sub-populations according to scMetR score, including metastasis-featuring tumor cells (MFTC), transitional metastatic tumor cells (TransMTC), and conventional tumor cells (ConvTC). We identified metastatic signature genes (MSGs) through comparing MFTC and ConvTC. Functional enrichment analysis showed that up-regulated MSGs were enriched in multiple metastasis-associated pathways. We also found that patients with high expression of up-regulated MSGs had worse prognosis. Spatial mapping of MFTC showed that they are preferentially located in the cancer and duct epithelium region, which was enriched with the ductal cells' associated inflammation. Further, we inferred cell-cell interactions, and observed that interactions of the ADGRE5 signaling pathway, which is associated with metastasis, were increased in MFTC compared to other tumor sub-populations. Finally, we predicted 12 candidate drugs that had the potential to reverse expression of MSGs. Taken together, we have proposed scMetR to estimate metastatic risk in PDAC patients at single-cell resolution which might facilitate the dissection of tumor heterogeneity.

Integrating spatial and single-cell transcriptomics to characterize the molecular and cellular architecture of the ischemic mouse brain.

Neuroinflammation is acknowledged as a pivotal pathological event after cerebral ischemia. However, there is limited knowledge of the molecular and spatial characteristics of nonneuronal cells, as well as of the interactions between cell types in the ischemic brain. Here, we used spatial transcriptomics to study the ischemic hemisphere in mice after stroke and sequenced the transcriptomes of 19,777 spots, allowing us to both visualize the transcriptional landscape within the tissue and identify gene expression profiles linked to specific histologic entities. Cell types identified by single-cell RNA sequencing confirmed and enriched the spatial annotation of ischemia-associated gene expression in the peri-infarct area of the ischemic hemisphere. Analysis of ligand-receptor interactions in cell communication revealed galectin-9 to cell-surface glycoprotein CD44 (LGALS9-CD44) as a critical signaling pathway after ischemic injury and identified microglia and macrophages as the main source of galectins after stroke. Extracellular vesicle-mediated Lgals9 delivery improved the long-term functional recovery in photothrombotic stroke mice. Knockdown of Cd44 partially reversed these therapeutic effects, inhibiting oligodendrocyte differentiation and remyelination. In summary, our study provides a detailed molecular and cellular characterization of the peri-infact area in a murine stroke model and revealed Lgals9 as potential treatment target that warrants further investigation.

Incidence rate and risk factors of ventilator-associated pneumonia in patients with traumatic brain injury: a systematic review and meta-analysis of observational studies.

Background: Ventilator-associated pneumonia is a common complication of traumatic brain injury (TBI) patients, causing great harm to the life, health and society of patients. It is important to understand the risk factors related to ventilator-associated pneumonia for infection monitoring and control of patients. However, there are still some controversies about the risk factors in previous studies. Therefore, the purpose of this study was to explore the incidence and risk factors of ventilator-associated pneumonia in patients with TBI. Methods: Two independent researchers selected literature collected by systematically searching databases including PubMed, Ovid, Embase, and ScienceDirect using medical subject headings. The primary end points of the included literature were extracted, and the Cochrane Q test and I2 statistic were used to evaluate the heterogeneity between studies. The random effects model based on the restricted maximum likelihood method and the fixed effects model based on the reverse variance method were used to calculate and combine the relative risk or mean difference of relevant indicators. The publication bias was evaluated with the funnel plot and Egger test. All results were considered statistically significant at P<0.05. Results: A total of 11 articles were included in this study for meta-analysis, and a total of 2,301 patients with TBI were included. The incidence of ventilator-associated pneumonia in TBI patients was approximately 42% (95% CI: 32-53%). Tracheotomy significantly increased the risk of ventilator-associated pneumonia in patients with TBI [relative risk (RR) =3.71; 95% CI: 1.48-6.94; P<0.05]; the use of prophylactic antibiotics could significantly reduce the risk of ventilator-associated pneumonia in patients with TBI. The risk of pneumonia (RR =0.53; 95% CI: 0.18-0.88; P<0.05); compared with female patients, male patients with TBI had a significantly higher risk (about 46%) of ventilator-associated pneumonia (RR =1.46; 95% CI: 1.13-1.79; P<0.05). Conclusions: The risk of ventilator-associated pneumonia in patients with TBI is about 42%. Posttracheotomy and mechanical ventilation are risk factors for ventilator-associated pneumonia, while prophylactic use of antibiotics is a protective factor in the development of ventilator-associated pneumonia.

Increased low frequency fluctuation in the brain after acupuncture treatment in CSVDCI patients: A randomized control trial study.

Background: Cerebral small vessel disease (CSVD) is one of two cognition-impairing diseases. Acupuncture (Acu) is a flexible treatment with few adverse effects and is thus widely used to treat neurological problems. Methods: We recruited a total of 60 patients and assigned them to two groups (n = 30 each group). During the study, some participants were excluded by quality control, and a total of 44 subjects (25 Acu and 19 controls) were completed to investigate the therapeutic efficacy of acupuncture on CSVD cognitive impairment (CSVDCI). The following demographic and clinical variables were compared between the two groups: gender, age, education, smoking, alcohol, Montreal cognitive assessment (MoCA), symbol digit modalities test (SDMT), verbal fluency test (VFT), digit span task (DST), Boston naming test (BNT) scores, and amplitude of low-frequency fluctuation (ALFF) under the typical band (0.01-0.08 Hz). Mixed effect analysis was utilized to test for differences between the two groups before and after the treatment. Results: Following acupuncture treatment, the Acu group scored higher on MoCA, SDMT, VFT, DST, and BNT compared to controls (P < 0.05). The brain regions showing substantially greater ALFF values in the Acu group were the right inferior temporal gyrus, left middle occipital gyrus, left superior occipital gyrus, left insula, bilateral postcentral gyrus, right superior parietal gyrus, right cerebellum, right precuneus, and right precentral gyrus (P < 0.005, no correction). The ALFF values in the right inferior temporal gyrus (P = 0.027), left middle occipital gyrus (P = 0.005), left superior occipital gyrus (P = 0.011), and right superior parietal gyrus (P = 0.043) were positively associated with MoCA. Conclusion: We found that acupuncture modulates the functional activity of temporal, occipital, and parietal regions of the brain in CSVDCI patients.

Altered brain spontaneous activity in patients with cerebral small vessel disease using the amplitude of low-frequency fluctuation of different frequency bands.

Background: Previous studies showed that cerebral small vessel disease (cSVD) is a leading cause of cognitive decline in elderly people and the development of Alzheimer's disease. Although brain structural changes of cSVD have been documented well, it remains unclear about the properties of brain intrinsic spontaneous activity in patients with cSVD. Methods: We collected resting-state fMRI (rs-fMRI) and T1-weighted 3D high-resolution brain structural images from 41 cSVD patients and 32 healthy controls (HC). By estimating the amplitude of low-frequency fluctuation (ALFF) under three different frequency bands (typical band: 0.01-0.1 Hz; slow-4: 0.027-0.073 Hz; and slow-5: 0.01-0.027 Hz) in the whole-brain, we analyzed band-specific ALFF differences between the cSVD patients and controls. Results: The cSVD patients showed uniformly lower ALFF than the healthy controls in the typical and slow-4 bands (pFWE < 0.05). In the typical band, cSVD patients showed lower ALFF involving voxels of the fusiform, hippocampus, inferior occipital cortex, middle occipital cortex, insula, inferior frontal cortex, rolandic operculum, and cerebellum compared with the controls. In the slow-4 band, cSVD patients showed lower ALFF involving voxels of the cerebellum, hippocampus, occipital, and fusiform compared with the controls. However, there is no significant between-group difference of ALFF in the slow-5 band. Moreover, we found significant "group × frequency" interactions in the left precuneus. Conclusion: Our results suggested that brain intrinsic spontaneous activity of cSVD patients was abnormal and showed a frequency-specific characteristic. The ALFF in the slow-4 band may be more sensitive to detecting a malfunction in cSVD patients.

ncFO: A Comprehensive Resource of Curated and Predicted ncRNAs Associated with Ferroptosis.

Ferroptosis is a form of regulated cell death driven by the accumulation of lipid hydroperoxides. Regulation of ferroptosis might be beneficial to cancer treatment. Non-coding RNAs (ncRNAs) are a class of RNA transcripts that generally cannot encode proteins and have been demonstrated to play critical roles in regulating ferroptosis. Herein, we developed ncFO, the ncRNA-ferroptosis association database, to document the manually curated and predicted ncRNAs that are associated with ferroptosis. Collectively, ncFO contains 90 experimentally verified entries, including 46 microRNAs (miRNAs), 21 long non-coding RNAs (lncRNAs), and 17 circular RNAs (circRNAs). In addition, ncFO also incorporates two online prediction tools based on the regulation and co-expression of ncRNA and ferroptosis genes. Using default parameters, we obtained 3260 predicted entries, including 598 miRNAs and 178 lncRNAs, by regulation, as well as 2,592,661 predicted entries, including 967 miRNAs and 9632 lncRNAs, by ncRNA-ferroptosis gene co-expression in more than 8000 samples across 20 cancer types. The detailed information of each entry includes ncRNA name, disease, species, tissue, target, regulation, publication time, and PubMed identifier. ncFO also provides survival analysis and differential expression analysis for ncRNAs. In summary, ncFO offers a user-friendly platform to search and predict ferroptosis-associated ncRNAs, which might facilitate research on ferroptosis and discover potential targets for cancer treatment. ncFO can be accessed at http://www.jianglab.cn/ncFO/.