Significant transcriptional changes in mature daughter Varroa destructor mites during infestation of different developmental stages of honeybees

Background: Varroa destructor is considered a major cause of honeybee (Apis mellifera) colony losses worldwide. Although V. destructor mites exhibit preference behavior for certain honeybee lifecycle stages, the mechanism underlying host finding and preference remains largely unknown. Results: By using a de novo transcriptome assembly strategy, we sequenced the mature daughter V. destructor mite transcriptome during infestation of different stages of honeybees (brood cells, newly emerged bees and adult bees). A total of 132 779 unigenes were obtained with an average length of 2745 bp and N50 of 5706 bp. About 63.1% of the transcriptome could be annotated based on sequence homology to the predatory mite Metaseiulus occidentalis proteins. Expression analysis revealed that mature daughter mites had distinct transcriptome profiles after infestation of different honeybee stages, and that the majority of the differentially expressed genes (DEGs) of mite infesting adult honeybees were down-regulated compared to that infesting the sealed brood cells. Gene ontology and KEGG pathway enrichment analyses showed that a large number of DEGs were involved in cellular process and metabolic process, suggesting that Varroa mites undergo metabolic adjustment to accommodate the cellular, molecular and/or immune response of the honeybees. Interestingly, in adult honeybees, some mite DEGs involved in neurotransmitter biosynthesis and transport were identified and their levels of expression were validated by quantitative polymerase chain reaction (qPCR). Conclusion: These results provide evidence for transcriptional reprogramming in mature daughter Varroa mites during infestation of honeybees, which may be relevant to understanding the mechanism underpinning adaptation and preference behavior of these mites for honeybees. © 2020 Society of Chemical Industry

Common Core Genes Play Vital Roles in Gastric Cancer With Different Stages

Background: Owing to complex molecular mechanisms in gastric cancer (GC) oncogenesis and progression, existing biomarkers and therapeutic targets could not significantly improve diagnosis and prognosis. This study aims to identify the key genes and signaling pathways related to GC oncogenesis and progression using bioinformatics and meta-analysis methods.Methods: Eligible microarray datasets were downloaded and integrated using the meta-analysis method. According to the tumor stage, GC gene chips were classified into three groups. Thereafter, the three groups’ differentially expressed genes (DEGs) were identified by comparing the gene data of the tumor groups with those of matched normal specimens. Enrichment analyses were conducted based on common DEGs among the three groups. Then protein–protein interaction (PPI) networks were constructed to identify relevant hub genes and subnetworks. The effects of significant DEGs and hub genes were verified and explored in other datasets. In addition, the analysis of mutated genes was also conducted using gene data from The Cancer Genome Atlas database.Results: After integration of six microarray datasets, 1,229 common DEGs consisting of 1,065 upregulated and 164 downregulated genes were identified. Alpha-2 collagen type I (COL1A2), tissue inhibitor matrix metalloproteinase 1 (TIMP1), thymus cell antigen 1 (THY1), and biglycan (BGN) were selected as significant DEGs throughout GC development. The low expression of ghrelin (GHRL) is associated with a high lymph node ratio (LNR) and poor survival outcomes. Thereafter, we constructed a PPI network of all identified DEGs and gained 39 subnetworks and the top 20 hub genes. Enrichment analyses were performed for common DEGs, the most related subnetwork, and the top 20 hub genes. We also selected 61 metabolic DEGs to construct PPI networks and acquired the relevant hub genes. Centrosomal protein 55 (CEP55) and POLR1A were identified as hub genes associated with survival outcomes.Conclusion: The DEGs, hub genes, and enrichment analysis for GC with different stages were comprehensively investigated, which contribute to exploring the new biomarkers and therapeutic targets

Multidisciplinary treatment for locally advanced gastric cancer: A systematic review and network meta-analysis

Introduction: This study aimed to evaluate the efficacy of multidisciplinary treatment for patients with locally advanced gastric cancer (LAGC) who underwent radical gastrectomy. Patients and Methods: Randomised controlled trials (RCTs) comparing the effectiveness of surgery alone, adjuvant chemotherapy (CT), adjuvant radiotherapy (RT), adjuvant chemoradiotherapy (CRT), neoadjuvant CT, neoadjuvant RT, neoadjuvant CRT, perioperative CT and hyperthermic intraperitoneal chemotherapy (HIPEC) for LAGC were searched. Overall survival (OS), disease-free survival (DFS), recurrence and metastasis, long-term mortality, adverse events (grade ≥3), operative complications and R0 resection rate were used as outcome indicators for meta-analysis. Results: Forty-five RCTs with 10077 participants were finally analysed. Adjuvant CT had higher OS (hazard ratio [HR] = 0.74, 95% credible interval [CI] = 0.66–0.82) and DFS (HR = 0.67, 95% CI = 0.60–0.74) than surgery-alone group. Perioperative CT (odds ratio [OR] = 2.56, 95% CI = 1.19–5.50) and adjuvant CT (OR = 0.48, 95% CI = 0.27–0.86) both had more recurrence and metastasis than HIPEC + adjuvant CT, while adjuvant CRT tended to have less recurrence and metastasis than adjuvant CT (OR = 1.76, 95% CI = 1.29–2.42) and even adjuvant RT (OR = 1.83, 95% CI = 0.98–3.40). Moreover, the incidence of mortality in HIPEC + adjuvant CT was lower than that in adjuvant RT (OR = 0.28, 95% CI = 0.11–0.72), adjuvant CT (OR = 0.45, 95% CI = 0.23–0.86) and perioperative CT (OR = 2.39, 95% CI = 1.05–5.41). Analysis of adverse events (grade ≥3) showed no statistically significant difference between any two adjuvant therapy groups. Conclusion: A combination of HIPEC with adjuvant CT seems to be the most effective adjuvant therapy, which contributes to reducing tumour recurrence, metastasis and mortality – without increasing surgical complications and adverse events related to toxicity. Compared with CT or RT alone, CRT can reduce recurrence, metastasis and mortality but increase adverse events. Moreover, neoadjuvant therapy can effectively improve the radical resection rate, but neoadjuvant CT tends to increase surgical complications