Exosomes Derived from Pancreatic Cancer Cells Induce Osteoclast Differentiation Through the miR125a-5p/TNFRSF1B Pathway

Zhou, Yandong; Zhu, Yi; Dong, Xin; Cao, Guodong; Li, Yongzhou; Fan, Yiqun; Chen, Qing; Cai, Haolei; Wu, Yulian

doi:10.2147/ott.s282319

Cited by 16 publications

(7 citation statements)

References 37 publications

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“…YAPC-Tacedinaline network is a small network. It is not significantly enriched for any pathways other than Osteoclast differentiation which is recently shown to be induced in pancreatic cancer-derived exosomes 61 . In contrast, the A375-Tacedinaline network is enriched in several critical signaling pathways such as MAPK, ErbB, FoxO, TGF-beta, and TNF signaling pathways (Fig.…”

Section: Resultsmentioning

confidence: 91%

Functional stratification of cancer drugs through integrated network similarity

Unsal-Beyge

Tunçbağ

2022

npj Syst Biol Appl

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Drugs not only perturb their immediate protein targets but also modulate multiple signaling pathways. In this study, we explored networks modulated by several drugs across multiple cancer cell lines by integrating their targets with transcriptomic and phosphoproteomic data. As a result, we obtained 236 reconstructed networks covering five cell lines and 70 drugs. A rigorous topological and pathway analysis showed that chemically and functionally different drugs may modulate overlapping networks. Additionally, we revealed a set of tumor-specific hidden pathways with the help of drug network models that are not detectable from the initial data. The difference in the target selectivity of the drugs leads to disjoint networks despite sharing a similar mechanism of action, e.g., HDAC inhibitors. We also used the reconstructed network models to study potential drug combinations based on the topological separation and found literature evidence for a set of drug pairs. Overall, network-level exploration of drug-modulated pathways and their deep comparison may potentially help optimize treatment strategies and suggest new drug combinations.

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Section: Resultsmentioning

confidence: 91%

Functional stratification of cancer drugs through integrated network similarity

Unsal-Beyge

Tunçbağ

2022

npj Syst Biol Appl

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“…In mouse models of colorectal cancer, it has been reported that bone mass and trabecular number in the distal femur are reduced, along with a decrease in body weight, skeletal muscle, and fat mass (27). It has also been reported that in a mouse model of pancreatic cancer, the expression of the osteoclast-specific markers NFAT2, TRAP, CTSK, and MMP-9 is increased, and bone mass and trabecular thickness in the distal femur are reduced (28). In a mouse model of breast cancer, the use of doxorubicin has been reported to decrease bone mass, and anti-TGFβ antibodies prevent bone loss (29).…”

Section: Discussionmentioning

confidence: 99%

Effects of Soft Tissue Sarcoma and Doxorubicin on Bone Metabolism in Mice

Tsuchie

Nagasawa

Hongo

et al. 2023

In Vivo

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Background/Aim: This study aimed to evaluate the effects of doxorubicin (Dox) on bone microstructure and metabolism in a mouse model of soft tissue sarcoma. Materials and Methods: CCRF S-180Ⅱ cells (2-4×10 5 cells/0.2 ml) were injected subcutaneously into the back of mice. The mice were divided into four groups according to tumor and treatment status and were reared and sacrificed after 2 or 4 weeks. Micro-computed tomography (CT) was performed to calculate the architecture of the femoral bone. The proximal tibia was double stained with tartrate-resistant acid phosphatase (TRACP) and alkaline phosphatase (ALP), and bone morphometry was performed. Results: Trabecular bone mass was significantly reduced in the Sarcoma and Sarcoma+Dox groups. Cortical bone thickness was reduced in the DOX group, with a stronger effect observed in the Sarcoma+Dox group. In bone morphometry, osteoclast number at the bone surface (Oc.N/BS) was significantly lower in the Dox, Sarcoma, and Sarcoma+Dox groups than in the Control group at 2 weeks. The osteoblast surface at the bone surface (Ob.S/BS) was significantly lower in the Dox and Sarcoma groups than in the Control group at 2 weeks. At 4 weeks, the differences were smaller for both Oc.N/BS and Ob.S/BS. Conclusion: The use of doxorubicin alone worsened the cortical bone structure; however, the presence of both soft-tissue sarcoma and doxorubicin use worsened both cortical and trabecular bone structures from an early stage.

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“…It is demonstrated that HOXA10-AS/miR-340-3p/HTR1D ceRNA axis promotes the adverse outcome of pancreatic cancer through the PI3K-AKT signaling pathway [ 34 ]. In addition, exosomes from pancreatic cancer cells have also been proven to induce osteoclast differentiation via the miR125a-5p/TNFRSF1B pathway [ 35 ]. Our findings on Human papillomavirus infection and ECM-receptor interaction are consistent with previous pancreatic cancer studies [ 36 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

Developing and validating a survival prediction model based on blood exosomal ceRNA network in patients with PAAD

Wang

Zhu

et al. 2022

BMC Med Genomics

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Background Among the most lethal cancers, pancreatic adenocarcinoma (PAAD) is an essential component of digestive system malignancies that still lacks effective diagnosis and treatment methods. As exosomes and competing endogenous RNA (ceRNA) regulatory networks in tumors go deeper, we expect to construct a ceRNA regulatory network derived from blood exosomes of PAAD patients by bioinformatics methods and develop a survival prediction model based on it. Methods Blood exosome sequencing data of PAAD patients and normal controls were downloaded from the exoRbase database, and the expression profiles of exosomal mRNA, lncRNA, and circRNA were differentially analyzed by R. The related mRNA, circRNA, lncRNA, and their corresponding miRNA prediction data were imported into Cytoscape software to visualize the ceRNA network. Then, we conducted GO and KEGG enrichment analysis of mRNA in the ceRNA network. Genes that express differently in pancreatic cancer tissues compared with normal tissues and associate with survival (P < 0.05) were determined as Hub genes by GEPIA. We identified optimal prognosis-related differentially expressed mRNAs (DEmRNAs) and generated a risk score model by performing univariate and multivariate Cox regression analyses. Results 205 DEmRNAs, 118 differentially expressed lncRNAs (DElncRNAs), and 98 differentially expressed circRNAs (DEcircRNAs) were screened out. We constructed the ceRNA network, and a total of 26 mRNA nodes, 7 lncRNA nodes, 6 circRNA nodes, and 16 miRNA nodes were identified. KEGG enrichment analysis showed that the DEmRNAs in the regulatory network were mainly enriched in Human papillomavirus infection, PI3K-Akt signaling pathway, Osteoclast differentiation, and ECM-receptor interaction. Next, six hub genes (S100A14, KRT8, KRT19, MAL2, MYO5B, PSCA) were determined through GEPIA. They all showed significantly increased expression in cancer tissues compared with control groups, and their high expression pointed to adverse survival. Two optimal prognostic-related DEmRNAs, MYO5B (HR = 1.41, P < 0.05) and PSCA (HR = 1.10, P < 0.05) were included to construct the survival prediction model. Conclusion In this study, we successfully constructed a ceRNA regulatory network in blood exosomes from PAAD patients and developed a two-gene survival prediction model that provided new targets which shall aid in diagnosing and treating PAAD.

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Exosomes Derived from Pancreatic Cancer Cells Induce Osteoclast Differentiation Through the miR125a-5p/TNFRSF1B Pathway

Cited by 16 publications

References 37 publications

Functional stratification of cancer drugs through integrated network similarity

Functional stratification of cancer drugs through integrated network similarity

Effects of Soft Tissue Sarcoma and Doxorubicin on Bone Metabolism in Mice

Developing and validating a survival prediction model based on blood exosomal ceRNA network in patients with PAAD

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