A Global Phosphorylation Atlas of Proteins Within Pathological Site of Rotator Cuff Tendinopathy

DEWNA: dynamic entropy weight network analysis and its application to the DNA-binding proteome in A549 cells with cisplatin-induced damage

Cisplatin is one of the most commonly used chemotherapy drugs for treating solid tumors. As a genotoxic agent, cisplatin binds to DNA and forms platinum-DNA adducts that cause DNA damage and activate a series of signaling pathways mediated by various DNA-binding proteins (DBPs), ultimately leading to cell death. Therefore, DBPs play crucial roles in the cellular response to cisplatin and in determining cell fate. However, systematic studies of DBPs responding to cisplatin damage and their temporal dynamics are still lacking. To address this, we developed a novel and user-friendly stand-alone software, DEWNA, designed for dynamic entropy weight network analysis to reveal the dynamic changes of DBPs and their functions. DEWNA utilizes the entropy weight method, multiscale embedded gene co-expression network analysis and generalized reporter score-based analysis to process time-course proteome expression data, helping scientists identify protein hubs and pathway entropy profiles during disease progression. We applied DEWNA to a dataset of DBPs from A549 cells responding to cisplatin-induced damage across 8 time points, with data generated by data-independent acquisition mass spectrometry (DIA-MS). The results demonstrate that DEWNA can effectively identify protein hubs and associated pathways that are significantly altered in response to cisplatin-induced DNA damage, and offer a comprehensive view of how different pathways interact and respond dynamically over time to cisplatin treatment. Notably, we observed the dynamic activation of distinct DNA repair pathways and cell death mechanisms during the drug treatment time course, providing new insights into the molecular mechanisms underlying the cellular response to DNA damage.

Macroporous Granular Hydrogels Functionalized with Aligned Architecture and Small Extracellular Vesicles Stimulate Osteoporotic Tendon-To-Bone Healing

Osteoporotic tendon-to-bone healing (TBH) after rotator cuff repair (RCR) is a significant orthopedic challenge. Considering the aligned architecture of the tendon, inflammatory microenvironment at the injury site, and the need for endogenous cell/tissue infiltration, there is an imminent need for an ideal scaffold to promote TBH that has aligned architecture, ability to modulate inflammation, and macroporous structure. Herein, a novel macroporous hydrogel comprising sodium alginate/hyaluronic acid/small extracellular vesicles from adipose-derived stem cells (sEVs) (MHA-sEVs) with aligned architecture and immunomodulatory ability is fabricated. When implanted subcutaneously, MHA-sEVs significantly improve cell infiltration and tissue integration through its macroporous structure. When applied to the osteoporotic RCR model, MHA-sEVs promote TBH by improving tendon repair through macroporous aligned architecture while enhancing bone regeneration by modulating inflammation. Notably, the biomechanical strength of MHA-sEVs is approximately two times higher than the control group, indicating great potential in reducing postoperative retear rates. Further cell-hydrogel interaction studies reveal that the alignment of microfiber gels in MHA-sEVs induces tenogenic differentiation of tendon-derived stem cells, while sEVs improve mitochondrial dysfunction in M1 macrophages (Mφ) and inhibit Mφ polarization toward M1 via nuclear factor-kappaB (NF-κb) signaling pathway. Taken together, MHA-sEVs provide a promising strategy for future clinical application in promoting osteoporotic TBH.

Gypenosides ameliorate high-fat diet-induced nonalcoholic fatty liver disease in mice by regulating lipid metabolism

Gypenosides (GP), extracted from the traditional Chinese herb Gynostemma pentaphyllum (Thunb.) Makino, have been used to treat metabolic disorders, including lipid metabolism disorders and diabetes. Although recent studies have confirmed their beneficial effects in nonalcoholic fatty liver disease (NAFLD), the underlying therapeutic mechanism remains unclear. In this study, we explored the protective mechanism of GP against NAFLD in mice and provided new insights into the prevention and treatment of NAFLD. Male C57BL6/J mice were divided into three experimental groups: normal diet, high-fat diet (HFD), and GP groups. The mice were fed an HFD for 16 weeks to establish an NAFLD model and then treated with GP for 22 weeks. The transcriptome and proteome of the mice livers were profiled using RNA sequencing and high-resolution mass spectrometry, respectively. The results showed that GP decreased serum lipid levels, liver index, and liver fat accumulation in mice. Principal component and heatmap analyses indicated that GP significantly modulated the changes in the expression of genes associated with HFD-induced NAFLD. The 164 differentially expressed genes recovered using GP were enriched in fatty acid and steroid metabolism pathways. Further results showed that GP reduced fatty acid synthesis by downregulating the expression of Srebf1, Fasn, Acss2, Acly, Acaca, Fads1, and Elovl6; modulated glycerolipid metabolism by inducing the expression of Mgll; promoted fatty acid transportation and degradation by inducing the expression of Slc27a1, Cpt1a, and Ehhadh; and reduced hepatic cholesterol synthesis by downregulating the expression of Tm7sf2, Ebp, Sc5d, Lss, Fdft1, Cyp51, Nsdhl, Pmvk, Mvd, Fdps, and Dhcr7. The proteomic data further indicated that GP decreased the protein expression levels of ACACA, ACLY, ACSS2, TM7SF2, EBP, FDFT1, NSDHL, PMVK, MVD, FDPS, and DHCR7 and increased those of MGLL, SLC27A1, and EHHADH. In conclusion, GP can regulate the key genes involved in hepatic lipid metabolism in NAFLD mice, providing initial evidence for the mechanisms underlying the therapeutic effect of GP in NAFLD.

Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Background

Advances in our understanding of the tumor microenvironment have radically changed the cancer field, highlighting the emerging need for biomarkers of an active, favorable tumor immune phenotype to aid treatment stratification and clinical prognostication. Numerous immune-related gene signatures have been defined; however, their prognostic value is often limited to one or few cancer types. Moreover, the area of non-coding RNA as biomarkers remains largely unexplored although their number and biological roles are rapidly expanding.

Methods

We developed a multi-step process to identify immune-related long non-coding RNA signatures with prognostic connotation in multiple TCGA solid cancer datasets.

Results

Using the breast cancer dataset as a discovery cohort we found 2988 differentially expressed lncRNAs between immune favorable and unfavorable tumors, as defined by the immunologic constant of rejection (ICR) gene signature. Mapping of the lncRNAs to a coding-non-coding network identified 127 proxy protein-coding genes that are enriched in immune-related diseases and functions. Next, we defined two distinct 20-lncRNA prognostic signatures that show a stronger effect on overall survival than the ICR signature in multiple solid cancers. Furthermore, we found a 3 lncRNA signature that demonstrated prognostic significance across 5 solid cancer types with a stronger association with clinical outcome than ICR. Moreover, this 3 lncRNA signature showed additional prognostic significance in uterine corpus endometrial carcinoma and cervical squamous cell carcinoma and endocervical adenocarcinoma as compared to ICR.

Conclusion

We identified an immune-related 3-lncRNA signature with prognostic connotation in multiple solid cancer types which performed equally well and in some cases better than the 20-gene ICR signature, indicating that it could be used as a minimal informative signature for clinical implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03654-7.