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Differential gene screening and prognostic model construction. (A) The Venn diagram shows the gene intersection obtained from four differential gene screening methods (edgeR, DESeq2, Wilcoxon, and limma), with 86 common differential genes selected. (B) Univariate Cox regression identifies significant gene‐survival correlations, with hazard ratios (HR) and p ‐values illustrated in the forest plot. (C) LASSO regression cross‐validation determines the optimal λ value, with red dots representing the mean error of cross‐validation and gray bars indicating the standard deviation. (D) The LASSO regression path plot shows the trend of regression coefficients as λ values change, with coefficients gradually shrinking to zero and ultimately retaining a few key genes. (E) Multivariate Cox regression analysis selected three key genes: VAV3, TNFRSF12A, and <t>PLA2G2A</t> , showing their hazard ratios (HR) and p ‐values.
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Differential gene screening and prognostic model construction. (A) The Venn diagram shows the gene intersection obtained from four differential gene screening methods (edgeR, DESeq2, Wilcoxon, and limma), with 86 common differential genes selected. (B) Univariate Cox regression identifies significant gene‐survival correlations, with hazard ratios (HR) and p ‐values illustrated in the forest plot. (C) LASSO regression cross‐validation determines the optimal λ value, with red dots representing the mean error of cross‐validation and gray bars indicating the standard deviation. (D) The LASSO regression path plot shows the trend of regression coefficients as λ values change, with coefficients gradually shrinking to zero and ultimately retaining a few key genes. (E) Multivariate Cox regression analysis selected three key genes: VAV3, TNFRSF12A, and PLA2G2A , showing their hazard ratios (HR) and p ‐values.

Journal: The FASEB Journal

Article Title: Lactate Metabolism‐Immune Regulation‐Related Gene Signature in Lower‐Grade Gliomas: Prognostic Model Development and Immune Characterization

doi: 10.1096/fj.202503738RR

Figure Lengend Snippet: Differential gene screening and prognostic model construction. (A) The Venn diagram shows the gene intersection obtained from four differential gene screening methods (edgeR, DESeq2, Wilcoxon, and limma), with 86 common differential genes selected. (B) Univariate Cox regression identifies significant gene‐survival correlations, with hazard ratios (HR) and p ‐values illustrated in the forest plot. (C) LASSO regression cross‐validation determines the optimal λ value, with red dots representing the mean error of cross‐validation and gray bars indicating the standard deviation. (D) The LASSO regression path plot shows the trend of regression coefficients as λ values change, with coefficients gradually shrinking to zero and ultimately retaining a few key genes. (E) Multivariate Cox regression analysis selected three key genes: VAV3, TNFRSF12A, and PLA2G2A , showing their hazard ratios (HR) and p ‐values.

Article Snippet: The antibodies listed below were employed in the experiments: β‐actin (1:20000, Affinity, Cat: AF7018), PLA2G2A (1:1000, ABclonal, Cat: A19252), E‐Cadherin (1:1000, Santa Cruz, Cat: sc‐8426), Vimentin (1:1000, ABclonal, Cat: A19607), PCNA (1:1000, Santa Cruz, Cat: sc‐53 407), H1F‐1α (1: 1000, Proteintech, Cat: 20960‐1‐AP), LDHA (1:1000, Proteintech, Cat: 19987‐1‐AP), MMP2 (1:3000, ABclonal, Cat: A6247) and MMP9 (1:1000, Santa Cruz, Cat: sc‐393 859).

Techniques: Biomarker Discovery, Standard Deviation

Construction and validation of the LMRIGs prognostic signature in LGG. (A) Distribution of survival status between high‐ and low‐risk patients. (B) ROC curves of the LMRIGs signature at 1, 3, and 5 years to evaluate predictive accuracy. (C) LGG patients stratified into high‐ and low‐risk groups based on risk scores. (D) Expression patterns of risk genes in different subgroups. (E) Heatmap of the expression of three LMRIGs genes ( VAV3, TNFRSF12A , and PLA2G2A ). (F) Kaplan–Meier survival analysis in the CGGA cohort, showing better prognosis in the low‐risk group. (G) ROC curves at 1, 3, and 5 years in the CGGA cohort. (H) Risk group classification in the CGGA validation cohort. (I) Expression patterns of risk genes in different subgroups. (J) Expression of risk genes in different subgroups of the CGGA cohort.

Journal: The FASEB Journal

Article Title: Lactate Metabolism‐Immune Regulation‐Related Gene Signature in Lower‐Grade Gliomas: Prognostic Model Development and Immune Characterization

doi: 10.1096/fj.202503738RR

Figure Lengend Snippet: Construction and validation of the LMRIGs prognostic signature in LGG. (A) Distribution of survival status between high‐ and low‐risk patients. (B) ROC curves of the LMRIGs signature at 1, 3, and 5 years to evaluate predictive accuracy. (C) LGG patients stratified into high‐ and low‐risk groups based on risk scores. (D) Expression patterns of risk genes in different subgroups. (E) Heatmap of the expression of three LMRIGs genes ( VAV3, TNFRSF12A , and PLA2G2A ). (F) Kaplan–Meier survival analysis in the CGGA cohort, showing better prognosis in the low‐risk group. (G) ROC curves at 1, 3, and 5 years in the CGGA cohort. (H) Risk group classification in the CGGA validation cohort. (I) Expression patterns of risk genes in different subgroups. (J) Expression of risk genes in different subgroups of the CGGA cohort.

Article Snippet: The antibodies listed below were employed in the experiments: β‐actin (1:20000, Affinity, Cat: AF7018), PLA2G2A (1:1000, ABclonal, Cat: A19252), E‐Cadherin (1:1000, Santa Cruz, Cat: sc‐8426), Vimentin (1:1000, ABclonal, Cat: A19607), PCNA (1:1000, Santa Cruz, Cat: sc‐53 407), H1F‐1α (1: 1000, Proteintech, Cat: 20960‐1‐AP), LDHA (1:1000, Proteintech, Cat: 19987‐1‐AP), MMP2 (1:3000, ABclonal, Cat: A6247) and MMP9 (1:1000, Santa Cruz, Cat: sc‐393 859).

Techniques: Biomarker Discovery, Expressing

Expression validation of key model genes and in vitro functional experiments of PLA2G2A. (A) Immunohistochemical results from the Human Protein Atlas (HPA) database show that the expression levels of VAV3, TNFRSF12A, and PLA2G2A are significantly higher in tumor tissues than in normal tissues. (B–D) qRT‐PCR results from clinical samples show that the mRNA levels of VAV3, TNFRSF12A , and PLA2G2A are significantly elevated in tumor tissues (* p < 0.05, *** p < 0.001, **** p < 0.0001). (E) Receiver operating characteristic curves (ROC) of PLA2G2A mRNA, TNFRSF12A mRNA, and VAV3 mRNA in subjects. (F, G) Western blot analysis of PLA2G2A protein expression in different glioma cell lines (* p < 0.05, ** p < 0.01, **** p < 0.0001). (H, I) After PLA2G2A knockdown in U251 cells using shRNA, Western blot confirmed transfection efficiency (*** p < 0.001, **** p < 0.0001). (J, K) After PLA2G2A knockdown in LN229 cells using shRNA, Western blot confirmed transfection efficiency (* p < 0.05, *** p < 0.001). (L, M) CCK‐8 assay results show that PLA2G2A downregulation significantly inhibits the proliferative ability of U251 and LN229 glioma cells (* p < 0.05, ** p < 0.01, **** p < 0.0001) (N) Immunofluorescence detection shows successful construction of stable U251 and LN229 transfected cells. (O) Transwell assay results show that PLA2G2A knockdown significantly reduces the migration and invasion abilities of U251 and LN229 tumor cells. (P) Quantitative analysis further confirms that the number of migrating and invading cells in the sh‐PLA2G2A treatment group is significantly lower than in the control group (* p < 0.05, ** p < 0.01, **** p < 0.0001).

Journal: The FASEB Journal

Article Title: Lactate Metabolism‐Immune Regulation‐Related Gene Signature in Lower‐Grade Gliomas: Prognostic Model Development and Immune Characterization

doi: 10.1096/fj.202503738RR

Figure Lengend Snippet: Expression validation of key model genes and in vitro functional experiments of PLA2G2A. (A) Immunohistochemical results from the Human Protein Atlas (HPA) database show that the expression levels of VAV3, TNFRSF12A, and PLA2G2A are significantly higher in tumor tissues than in normal tissues. (B–D) qRT‐PCR results from clinical samples show that the mRNA levels of VAV3, TNFRSF12A , and PLA2G2A are significantly elevated in tumor tissues (* p < 0.05, *** p < 0.001, **** p < 0.0001). (E) Receiver operating characteristic curves (ROC) of PLA2G2A mRNA, TNFRSF12A mRNA, and VAV3 mRNA in subjects. (F, G) Western blot analysis of PLA2G2A protein expression in different glioma cell lines (* p < 0.05, ** p < 0.01, **** p < 0.0001). (H, I) After PLA2G2A knockdown in U251 cells using shRNA, Western blot confirmed transfection efficiency (*** p < 0.001, **** p < 0.0001). (J, K) After PLA2G2A knockdown in LN229 cells using shRNA, Western blot confirmed transfection efficiency (* p < 0.05, *** p < 0.001). (L, M) CCK‐8 assay results show that PLA2G2A downregulation significantly inhibits the proliferative ability of U251 and LN229 glioma cells (* p < 0.05, ** p < 0.01, **** p < 0.0001) (N) Immunofluorescence detection shows successful construction of stable U251 and LN229 transfected cells. (O) Transwell assay results show that PLA2G2A knockdown significantly reduces the migration and invasion abilities of U251 and LN229 tumor cells. (P) Quantitative analysis further confirms that the number of migrating and invading cells in the sh‐PLA2G2A treatment group is significantly lower than in the control group (* p < 0.05, ** p < 0.01, **** p < 0.0001).

Article Snippet: The antibodies listed below were employed in the experiments: β‐actin (1:20000, Affinity, Cat: AF7018), PLA2G2A (1:1000, ABclonal, Cat: A19252), E‐Cadherin (1:1000, Santa Cruz, Cat: sc‐8426), Vimentin (1:1000, ABclonal, Cat: A19607), PCNA (1:1000, Santa Cruz, Cat: sc‐53 407), H1F‐1α (1: 1000, Proteintech, Cat: 20960‐1‐AP), LDHA (1:1000, Proteintech, Cat: 19987‐1‐AP), MMP2 (1:3000, ABclonal, Cat: A6247) and MMP9 (1:1000, Santa Cruz, Cat: sc‐393 859).

Techniques: Expressing, Biomarker Discovery, In Vitro, Functional Assay, Immunohistochemical staining, Quantitative RT-PCR, Western Blot, Knockdown, shRNA, Transfection, CCK-8 Assay, Immunofluorescence, Transwell Assay, Migration, Control

Downregulation of PLA2G2A decreases tumor lactate levels, inhibits tumor growth, and reverses EMT phenotype. (A) Subcutaneous tumorigenesis experiment in mice showing differences in tumor morphology between the Sh‐NC and Sh‐PLA2G2A groups. (B, C) Comparison of tumor volume and weight, showing significantly reduced tumor growth in the Sh‐PLA2G2A group compared to the control group (* p < 0.05). (D) Lactate levels in the Sh‐NC and Sh‐PLA2G2A groups (* p < 0.05). (E, F) Western blot analysis of protein expression in the Sh‐NC and Sh‐PLA2G2A groups. Compared to the control group, PLA2G2A and the proliferation marker PCNA were significantly downregulated, the mesenchymal marker Vimentin was decreased, and the epithelial marker E‐cadherin was upregulated. HIF‐1α, LDHA, MMP2, and MMP9 were also significantly reduced. (G, H) Protein quantification analysis further confirmed the differences, with statistical significance (**** p < 0.0001).

Journal: The FASEB Journal

Article Title: Lactate Metabolism‐Immune Regulation‐Related Gene Signature in Lower‐Grade Gliomas: Prognostic Model Development and Immune Characterization

doi: 10.1096/fj.202503738RR

Figure Lengend Snippet: Downregulation of PLA2G2A decreases tumor lactate levels, inhibits tumor growth, and reverses EMT phenotype. (A) Subcutaneous tumorigenesis experiment in mice showing differences in tumor morphology between the Sh‐NC and Sh‐PLA2G2A groups. (B, C) Comparison of tumor volume and weight, showing significantly reduced tumor growth in the Sh‐PLA2G2A group compared to the control group (* p < 0.05). (D) Lactate levels in the Sh‐NC and Sh‐PLA2G2A groups (* p < 0.05). (E, F) Western blot analysis of protein expression in the Sh‐NC and Sh‐PLA2G2A groups. Compared to the control group, PLA2G2A and the proliferation marker PCNA were significantly downregulated, the mesenchymal marker Vimentin was decreased, and the epithelial marker E‐cadherin was upregulated. HIF‐1α, LDHA, MMP2, and MMP9 were also significantly reduced. (G, H) Protein quantification analysis further confirmed the differences, with statistical significance (**** p < 0.0001).

Article Snippet: The antibodies listed below were employed in the experiments: β‐actin (1:20000, Affinity, Cat: AF7018), PLA2G2A (1:1000, ABclonal, Cat: A19252), E‐Cadherin (1:1000, Santa Cruz, Cat: sc‐8426), Vimentin (1:1000, ABclonal, Cat: A19607), PCNA (1:1000, Santa Cruz, Cat: sc‐53 407), H1F‐1α (1: 1000, Proteintech, Cat: 20960‐1‐AP), LDHA (1:1000, Proteintech, Cat: 19987‐1‐AP), MMP2 (1:3000, ABclonal, Cat: A6247) and MMP9 (1:1000, Santa Cruz, Cat: sc‐393 859).

Techniques: Comparison, Control, Western Blot, Expressing, Marker

Schematic of lactate metabolism‐immune regulation‐related genes altering the tumor microenvironment in glioma. In glioma, clustering analysis based on lactate metabolism gene sets identified PLA2G2A, TNFRSF12A, and VAV3 as differentially expressed genes included in the predictive model. PLA2G2A alters the tumor microenvironment by remodeling the ECM, promoting tumor‐associated inflammation, and activating epithelial‐to‐mesenchymal transition (EMT), thereby enhancing tumor cell proliferation and invasion, ultimately leading to poor prognosis.

Journal: The FASEB Journal

Article Title: Lactate Metabolism‐Immune Regulation‐Related Gene Signature in Lower‐Grade Gliomas: Prognostic Model Development and Immune Characterization

doi: 10.1096/fj.202503738RR

Figure Lengend Snippet: Schematic of lactate metabolism‐immune regulation‐related genes altering the tumor microenvironment in glioma. In glioma, clustering analysis based on lactate metabolism gene sets identified PLA2G2A, TNFRSF12A, and VAV3 as differentially expressed genes included in the predictive model. PLA2G2A alters the tumor microenvironment by remodeling the ECM, promoting tumor‐associated inflammation, and activating epithelial‐to‐mesenchymal transition (EMT), thereby enhancing tumor cell proliferation and invasion, ultimately leading to poor prognosis.

Article Snippet: The antibodies listed below were employed in the experiments: β‐actin (1:20000, Affinity, Cat: AF7018), PLA2G2A (1:1000, ABclonal, Cat: A19252), E‐Cadherin (1:1000, Santa Cruz, Cat: sc‐8426), Vimentin (1:1000, ABclonal, Cat: A19607), PCNA (1:1000, Santa Cruz, Cat: sc‐53 407), H1F‐1α (1: 1000, Proteintech, Cat: 20960‐1‐AP), LDHA (1:1000, Proteintech, Cat: 19987‐1‐AP), MMP2 (1:3000, ABclonal, Cat: A6247) and MMP9 (1:1000, Santa Cruz, Cat: sc‐393 859).

Techniques: