Ras/ERK and PI3K/AKT signaling differentially regulate oncogenic ERG mediated transcription in prostate cells

Strittmatter, Brady G.; Jerde, Travis J.; Hollenhorst, Peter C.

doi:10.1371/journal.pgen.1009708

Cited by 8 publications

(5 citation statements)

References 47 publications

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“…By applying functional annotation on a network, they find Ras protein signal transduction is one of the important signaling pathways in prostate cancer. Also in 2021, Strittmatter et al [ 32 ] show the change in ERG expression gene by Ras/ERK and PI3K/AKT signaling pathways, promoting prostate tumor.…”

Section: Resultsmentioning

confidence: 99%

DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues

Mahdi-Esferizi,

Haji Molla Hoseyni,

Mehrpanah

et al. 2023

BMC Bioinformatics

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Background P4 medicine (predict, prevent, personalize, and participate) is a new approach to diagnosing and predicting diseases on a patient-by-patient basis. For the prevention and treatment of diseases, prediction plays a fundamental role. One of the intelligent strategies is the design of deep learning models that can predict the state of the disease using gene expression data. Results We create an autoencoder deep learning model called DeeP4med, including a Classifier and a Transferor that predicts cancer's gene expression (mRNA) matrix from its matched normal sample and vice versa. The range of the F1 score of the model, depending on tissue type in the Classifier, is from 0.935 to 0.999 and in Transferor from 0.944 to 0.999. The accuracy of DeeP4med for tissue and disease classification was 0.986 and 0.992, respectively, which performed better compared to seven classic machine learning models (Support Vector Classifier, Logistic Regression, Linear Discriminant Analysis, Naive Bayes, Decision Tree, Random Forest, K Nearest Neighbors). Conclusions Based on the idea of DeeP4med, by having the gene expression matrix of a normal tissue, we can predict its tumor gene expression matrix and, in this way, find effective genes in transforming a normal tissue into a tumor tissue. Results of Differentially Expressed Genes (DEGs) and enrichment analysis on the predicted matrices for 13 types of cancer showed a good correlation with the literature and biological databases. This led that by using the gene expression matrix, to train the model with features of each person in a normal and cancer state, this model could predict diagnosis based on gene expression data from healthy tissue and be used to identify possible therapeutic interventions for those patients.

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Section: Resultsmentioning

confidence: 99%

DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues

Mahdi-Esferizi,

Haji Molla Hoseyni,

Mehrpanah

et al. 2023

BMC Bioinformatics

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“…Ras is an important protein that links PI3K/MAPK signaling [32]. Ras is overexpressed in many cancers and is involved in cancer growth and metastasis through the activation of PI3K/MAPK, making it a potential target for cancer therapy [33]. Ras is known to activate ERK1/2 in the MAPK signaling pathway [34], and it is therefore suggested that the reduction of Ras expression by nanaomycin K may be one of the mechanisms by which it inhibits the activation of the MAPK signaling pathway.…”

Section: Discussionmentioning

confidence: 99%

Growth and Migration Blocking Effect of Nanaomycin K, a Compound Produced by Streptomyces sp., on Prostate Cancer Cell Lines In Vitro and In Vivo

Hirata

Shigemura

Moriwaki

et al. 2023

Cancers

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Since castration-resistant prostate cancer (CRPC) acquires resistance to molecularly targeted drugs, discovering a class of drugs with different mechanisms of action is needed for more efficient treatment. In this study, we investigated the anti-tumor effects of nanaomycin K, derived from “Streptomyces rosa subsp. notoensis” OS-3966. The cell lines used were LNCaP (non-CRPC), PC-3 (CRPC), and TRAMP-C2 (CRPC). Experiments included cell proliferation analysis, wound healing analysis, and Western blotting. In addition, nanaomycin K was administered intratumorally to TRAMP-C2 carcinoma-bearing mice to assess effects on tumor growth. Furthermore, immuno-histochemistry staining was performed on excised tissues. Nanaomycin K suppressed cell proliferation in all cell lines (p < 0.001) and suppressed wound healing in TRAMP-C2 (p = 0.008). Nanaomycin K suppressed or showed a tendency to suppress the expression of N-cadherin, Vimentin, Slug, and Ras in all cell lines, and suppressed the phosphorylation of p38, SAPK/JNK, and Erk1/2 in LNCaP and TRAMP-C2. In vivo, nanaomycin K safely inhibited tumor growth (p = 0.001). In addition, suppression of phospho-Erk1/2 and increased expression of E-cadherin and cleaved-Caspase3 were observed in excised tumors. Nanaomycin K inhibits tumor growth and suppresses migration by inhibiting epithelial-mesenchymal transition in prostate cancer. Its mechanism of action is related to the inhibition of phosphorylation of the MAPK signaling pathway.

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“…Research on the RAS-ERK signaling pathway has been increasing in recent years. For example, tumorigenic Sergi-mediated transcription in prostate cells could be adjusted by RAS-ERK and PI3K-AKT signaling pathways differentially [33]. Vemurafenib significantly reduced the proliferation of melanocyte nevus by targeting the RAS-ERK pathway [34].…”

Section: Discussionmentioning

confidence: 99%

IPO5 Mediates EMT and Promotes Esophageal Cancer Development through the RAS-ERK Pathway

Li¹,

Li²,

Chen³

et al. 2022

Oxidative Medicine and Cellular Longevity

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Objective. In the development of many tumors, IPO5, as a member of the nuclear transporter family, exerts a significant function. Also, IPO5 is used as a therapeutic target for tumors based on some reports. By studying IPO5 expression in esophageal cancer tissues, the mechanism associated with IPO5 improving esophageal cancer development was explored in this study. Methods. To gain differentially expressed genes, this study utilized mRNA microarray and TCGA database for comprehensive analysis of esophageal cancer tissues and normal esophageal cancer tissues, and then the differentially expressed gene IPO5 was screened by us. To assess esophageal cancer patients’ prognosis, this study also applied the Kaplan-Meier analysis, and we also conducted the GSEA enrichment analysis to investigate IPO5-related signaling pathways. This study performed TISIDB and TIMER online analysis tools to study the correlation between IPO5 and immune regulation and infiltration. We took specimens of esophageal cancer from patients and detected the expression of IPO5 in tumor and normal tissues by immunohistochemistry. The IPO5 gene-silenced esophageal cancer cell model was constructed by lentivirus transfection. Through the Transwell invasion assay, CCK-8 assay, and cell scratch assay, this study investigated the effects of IPO5 on cell propagation, invasion, and transfer. What is more, we identified the influences of IPO5 on the cell cycle through flow cytometry and established a subcutaneous tumor-forming model in nude mice. Immunohistochemistry was used to verify the expression of KI-67, and this study detected the modifications of cell pathway-related proteins using Western blot and applied EMT-related proteins to explain the mechanism of esophageal cancer induced by IPO5. Results. According to database survival analysis, IPO5 high-expression patients had shorter disease-free survival than IPO5 low-expression patients. Compared to normal tissues, the IPO5 expression in cancer tissues was significantly higher in clinical trials ( P < 0.05 ). Through TISIDB and TIMER database studies, we found that IPO5 could affect immune regulation, and the age of IPO5 expression grows with the increase of immune infiltration level. The IPO5 expression in esophageal cancer cells was higher than normal, especially in ECA109 and OE33 cells ( P < 0.01 ). After knocking out IPO5 gene expression, cell proliferation capacity and invasion capacity were reduced ( P < 0.05 ) and decreased ( P < 0.01 ) in the IPO5-interfered group rather than the negative control group. The growth cycle of esophageal carcinoma cells was arrested in the G2/M phase after IPO5 gene silencing ( P < 0.01 ). Tumor-forming experiments in nude mice confirmed that after IPO5 deletion, the tumor shrank, the expression of KI67 decreased, the downstream protein expression level of the RAS pathway decreased after sh-IPO5 interference ( P < 0.01 ), and the level of EMT marker delined ( P < 0.05 ). Conclusion. In esophageal cancer, IPO5 is highly expressed and correlates with survival rate. Esophageal cancer cell growth and migration were significantly affected by the inhibition of IPO5 in vitro and in vivo. IPO5 mediates EMT using the RAS-ERK signaling pathway activation and promotes esophageal cancer cell development in vivo and in vitro.

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Ras/ERK and PI3K/AKT signaling differentially regulate oncogenic ERG mediated transcription in prostate cells

Cited by 8 publications

References 47 publications

DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues

DeeP4med: deep learning for P4 medicine to predict normal and cancer transcriptome in multiple human tissues

Growth and Migration Blocking Effect of Nanaomycin K, a Compound Produced by Streptomyces sp., on Prostate Cancer Cell Lines In Vitro and In Vivo

IPO5 Mediates EMT and Promotes Esophageal Cancer Development through the RAS-ERK Pathway

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