3D assessment of intervertebral disc degeneration in zebrafish identifies changes in bone density that prime disc disease

Back pain is a common condition with a high social impact and represents a global health burden.Intervertebral disc disease(IVDD)is one of the major causes of back pain;no therapeutics are currently available to reverse this disease.The impact of bone mineral density(BMD)on IVDD has been controversial,with some studies suggesting osteoporosis as causative for IVDD and others suggesting it as protective for IVDD.Functional studies to evaluate the influence of genetic components of BMD in IVDD could highlight opportunities for drug development and repurposing.By taking a holistic 3D approach,we established an aging zebrafish model for spontaneous IVDD.Increased BMD in aging,detected by automated computational analysis,is caused by bone deformities at the endplates.However,aged zebrafish spines showed changes in bone morphology,microstructure,mineral heterogeneity,and increased fragility that resembled osteoporosis.Elements of the discs recapitulated IVDD symptoms found in humans:the intervertebral ligament(equivalent to the annulus fibrosus)showed disorganized collagen fibers and herniation,while the disc center(nucleus pulposus equivalent)showed dehydration and cellular abnormalities.We manipulated BMD in young zebrafish by mutating sp7 and cathepsin K,leading to low and high BMD,respectively.Remarkably,we detected IVDD in both groups,demonstrating that low BMD does not protect against IVDD,and we found a strong correlation between high BMD and IVDD.Deep learning was applied to high-resolution synchrotron\iCJ image data to analyze osteocyte 3D lacunar distribution and morphology,revealing a role of sp7 in controlling the osteocyte lacunar 3D profile.Our findings suggest potential avenues through which bone quality can be targeted to identify beneficial therapeutics for IVDD.

Using multi-omics analysis to explore diagnostic tool and optimize drug therapy selection for patients with glioma based on cross-talk gene signature

Background:The heterogeneity of prognosis and treatment benefits among patients with gliomas is due to tumor microenvironment characteristics.However,biomarkers that reflect microenvironmental characteristics and predict the prognosis of gliomas are limited.Therefore,we aimed to develop a model that can effectively predict prognosis,differentiate microenvironment signatures,and optimize drug selection for patients with glioma.Materials and Methods:The CIBERSORT algorithm,bulk sequencing analysis,and single-cell RNA(scRNA)analysis were employed to identify significant cross-talk genes between M2 macrophages and cancer cells in glioma tissues.A predictive model was constructed based on cross-talk gene expression,and its effect on prognosis,recurrence prediction,and microenvironment characteristics was validated in multiple cohorts.The effect of the predictive model on drug selection was evaluated using the OncoPredict algorithm and relevant cellular biology experiments.Results:A high abundance of M2 macrophages in glioma tissues indicates poor prognosis,and cross-talk between macrophages and cancer cells plays a crucial role in shaping the tumor microenvironment.Eight genes involved in the cross-talk between macrophages and cancer cells were identified.Among them,periostin(POSTN),chitinase 3 like 1(CHI3L1),serum amyloid A1(SAA1),and matrix metallopeptidase 9(MMP9)were selected to construct a predictive model.The developed model demonstrated significant efficacy in distinguishing patient prognosis,recurrent cases,and characteristics of high inflammation,hypoxia,and immunosuppression.Furthermore,this model can serve as a valuable tool for guiding the use of trametinib.Conclusions:In summary,this study provides a comprehensive understanding of the interplay between M2 macrophages and cancer cells in glioma;utilizes a cross-talk gene signature to develop a predictive model that can predict the differentiation of patient prognosis,recurrence instances,and microenvironment characteristics;and aids in optimizing the application of trametinib in glioma patients.