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Fig. 5 Identifying therapeutic targets for OS patients. (A) The heatmap of ten RGPSM-related genes in the high- and low-RGPSM patients. (B) The feature plots of six high expressed genes. (C) The K-M plots of <t>PSIP1</t> in predicting the prognosis of OS patients in various cohorts. (D) The PSIP1 mRNA expression levels between normal samples (normal, N)/cells (osteoblast, OB; mesenchymal stem cell, MSC) and tumor (T)/OS cells. (E) The PSIP1 protein levels in hFOB1.19 and OS cells. *, p < 0.05; **, p < 0.01
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Fig. 5 Identifying therapeutic targets for OS patients. (A) The heatmap of ten RGPSM-related genes in the high- and low-RGPSM patients. (B) The feature plots of six high expressed genes. (C) The K-M plots of <t>PSIP1</t> in predicting the prognosis of OS patients in various cohorts. (D) The PSIP1 mRNA expression levels between normal samples (normal, N)/cells (osteoblast, OB; mesenchymal stem cell, MSC) and tumor (T)/OS cells. (E) The PSIP1 protein levels in hFOB1.19 and OS cells. *, p < 0.05; **, p < 0.01
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Fig. 5 Identifying therapeutic targets for OS patients. (A) The heatmap of ten RGPSM-related genes in the high- and low-RGPSM patients. (B) The feature plots of six high expressed genes. (C) The K-M plots of <t>PSIP1</t> in predicting the prognosis of OS patients in various cohorts. (D) The PSIP1 mRNA expression levels between normal samples (normal, N)/cells (osteoblast, OB; mesenchymal stem cell, MSC) and tumor (T)/OS cells. (E) The PSIP1 protein levels in hFOB1.19 and OS cells. *, p < 0.05; **, p < 0.01
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Fig. 5 Identifying therapeutic targets for OS patients. (A) The heatmap of ten RGPSM-related genes in the high- and low-RGPSM patients. (B) The feature plots of six high expressed genes. (C) The K-M plots of PSIP1 in predicting the prognosis of OS patients in various cohorts. (D) The PSIP1 mRNA expression levels between normal samples (normal, N)/cells (osteoblast, OB; mesenchymal stem cell, MSC) and tumor (T)/OS cells. (E) The PSIP1 protein levels in hFOB1.19 and OS cells. *, p < 0.05; **, p < 0.01

Journal: Cancer cell international

Article Title: Identifying PSIP1 as a critical R-loop regulator in osteosarcoma via machine-learning and multi-omics analysis.

doi: 10.1186/s12935-025-03775-1

Figure Lengend Snippet: Fig. 5 Identifying therapeutic targets for OS patients. (A) The heatmap of ten RGPSM-related genes in the high- and low-RGPSM patients. (B) The feature plots of six high expressed genes. (C) The K-M plots of PSIP1 in predicting the prognosis of OS patients in various cohorts. (D) The PSIP1 mRNA expression levels between normal samples (normal, N)/cells (osteoblast, OB; mesenchymal stem cell, MSC) and tumor (T)/OS cells. (E) The PSIP1 protein levels in hFOB1.19 and OS cells. *, p < 0.05; **, p < 0.01

Article Snippet: The anti-bodies used in IHC were as followed: anti-PSIP1 antibody (1:100, Cat. #25504- 1-AP, Proteintech) and anti-Ki-67 antibody (1:100, Cat. GB111499-100, Servicebio).

Techniques: Biomarker Discovery, Expressing

Fig. 6 Silencing PSIP1 inhibited proliferation, invasion and migration of OS. (A-B) CCK8 (A) and colonies plate information assays (B) were used to mea sure the effects of silencing or up-regulating PSIP1 in OS cells. (C) Transwell migration assays were used to detect the migratory ability of OS cells with silencing or up-regulating PSIP1. (D) The subcutaneous tumor morphology after knockdown of PSIP1. (E-F) The size (E) and weight (F) of tumors. (G) The HE results and IHC results of PSIP1 and Ki-67 of subcutaneous tumors

Journal: Cancer cell international

Article Title: Identifying PSIP1 as a critical R-loop regulator in osteosarcoma via machine-learning and multi-omics analysis.

doi: 10.1186/s12935-025-03775-1

Figure Lengend Snippet: Fig. 6 Silencing PSIP1 inhibited proliferation, invasion and migration of OS. (A-B) CCK8 (A) and colonies plate information assays (B) were used to mea sure the effects of silencing or up-regulating PSIP1 in OS cells. (C) Transwell migration assays were used to detect the migratory ability of OS cells with silencing or up-regulating PSIP1. (D) The subcutaneous tumor morphology after knockdown of PSIP1. (E-F) The size (E) and weight (F) of tumors. (G) The HE results and IHC results of PSIP1 and Ki-67 of subcutaneous tumors

Article Snippet: The anti-bodies used in IHC were as followed: anti-PSIP1 antibody (1:100, Cat. #25504- 1-AP, Proteintech) and anti-Ki-67 antibody (1:100, Cat. GB111499-100, Servicebio).

Techniques: Migration, Knockdown

Fig. 7 Silencing PSIP1 induced R-loop accumulation and DNA damage. (A) The fluorescence intensity of S9.6 after different treatments. (B) The relative γ-H2AX foci intensity (γ-H2AX/DAPI) after different treatments. *, p < 0.05; **, p < 0.01

Journal: Cancer cell international

Article Title: Identifying PSIP1 as a critical R-loop regulator in osteosarcoma via machine-learning and multi-omics analysis.

doi: 10.1186/s12935-025-03775-1

Figure Lengend Snippet: Fig. 7 Silencing PSIP1 induced R-loop accumulation and DNA damage. (A) The fluorescence intensity of S9.6 after different treatments. (B) The relative γ-H2AX foci intensity (γ-H2AX/DAPI) after different treatments. *, p < 0.05; **, p < 0.01

Article Snippet: The anti-bodies used in IHC were as followed: anti-PSIP1 antibody (1:100, Cat. #25504- 1-AP, Proteintech) and anti-Ki-67 antibody (1:100, Cat. GB111499-100, Servicebio).

Techniques: Fluorescence