Journal: Biological Psychiatry Global Open Science

Article Title: Regional Molecular Changes in Chronic Lipopolysaccharide-Induced Neuroinflammation

doi: 10.1016/j.bpsgos.2025.100515

Figure Lengend Snippet: Circulating inflammatory cytokines and brain tissue expression of inflammatory and apoptotic markers. Serum concentrations of IL-1β (A) , TNF-α (B) , and IL-6 (C) in the ST- and LT-LPS and CON groups. (D–K) Heatmaps of real-time polymerase chain reaction results showing the effect of ST- and LT-LPS treatment on the mRNA expression of inflammatory markers in the Hyp, Pfc, Str, Hip, Mdb, Ctx, and Cbm. (G–I, K) Heatmaps of the sagittal plane of the rat brain showing upregulated or downregulated mRNA expression in the different brain regions as a result of LPS administration. LPS (1 mg/kg, i.p.; ST, n = 8; LT, n = 9) and saline (0.1 mL, i.p.; ST, n = 10; LT, n = 10) were administered once off (ST; n = 18) and once a week for 4 weeks (LT; n = 19). Data are presented as mean ± SD relative to the housekeeping gene Tbp . Data were analyzed using a 2-way analysis of variance followed by a Tukey’s post hoc test, and heatmaps are represented as expression values ( z scores) for differentially expressed genes. (A–C) p < .05 ( ∗ ), p < .01 ( ∗∗ ), p < .0001 ( ∗∗∗∗ ). (D–F, J) a ST-CON vs. ST-LPS; b ST-LPS vs. LT-LPS; c LT-CON vs. LT-LPS. p < .05 (a, b, c), p < .01 (aa, bb, cc), p < .001 (aaa, bbb, ccc), p < .0001 (aaaa, bbbb, cccc). Cbm, cerebellum; CON, control; Ctx, cortex; Hip, hippocampus; Hyp, hypothalamus; IFN-γ, interferon gamma; IL, interleukin; i.p., intraperitoneally; LPS, lipopolysaccharide; LT, long-term; Mdb, midbrain; mRNA, messenger RNA; Pfc, prefrontal cortex; ST, short-term; Str, striatum; TNF-α, tumor necrosis factor α.

Article Snippet: Heatmaps of gene expression z scores (see for additional information) for ST- and LT-CON and LPS-groups were generated in GraphPad Prism version 10 (GraphPad Software).

Techniques: Expressing, Real-time Polymerase Chain Reaction, Saline, Control

Journal: Biological Psychiatry Global Open Science

Article Title: Regional Molecular Changes in Chronic Lipopolysaccharide-Induced Neuroinflammation

doi: 10.1016/j.bpsgos.2025.100515

Figure Lengend Snippet: Brain tissue expression of apoptotic markers and H&E stained sections of rat sagittal hippocampus. (A) Heatmap of real-time polymerase chain reaction results showing the effect of ST- and LT-LPS treatment on the mRNA expression of apoptotic markers in the Hyp, Pfc, Str, Hip, Mdb, Ctx, and Cbm. (B) Heatmaps of the sagittal plane of the rat brain showing upregulated or downregulated mRNA expression in the different brain regions as a result of LPS. LPS (1 mg/kg, i.p.; ST, n = 8; LT, n = 9) and saline (0.1 mL, i.p.; ST, n = 10; LT, n = 10) were administered once off (ST; n = 18) and once a week for 4 weeks (LT; n = 19). Data are presented as mean ± SD relative to the housekeeping gene Tbp . Data were analyzed using a 2-way analysis of variance followed by a Tukey’s post hoc test, and heatmaps are represented as expression values ( z scores) for differentially expressed genes. (A) a ST-CON vs. ST-LPS; b ST-LPS vs. LT-LPS; c LT-CON vs. LT-LPS. p < .05 (a, b, c), p < .01 (aa, bb, cc), p < .001 (aaa, bbb, ccc), p < .0001 (aaaa, bbbb, cccc). (C, D) H&E staining of rat sagittal hippocampus (scale bars = 50 μm) after treatment with (C) saline (0.1 mL, i.p.) CON showing the normal structure, (D) LPS (1 mg/kg, i.p.) showing vacuolated cells (black arrows) and immune cell infiltration (blue arrows). Bax, Bcl-2-associated X protein; Bcl2, B-cell leukemia/lymphoma 2 protein; Cbm, cerebellum; CON, control; Ctx, cortex; H&E, hematoxylin and eosin; Hip, hippocampus; Hyp, hypothalamus; i.p., intraperitoneally; LPS, lipopolysaccharide; LT, long-term; Mdb, midbrain; mRNA, messenger RNA; Pfc, prefrontal cortex; ST, short-term; Str, striatum.

Article Snippet: Heatmaps of gene expression z scores (see for additional information) for ST- and LT-CON and LPS-groups were generated in GraphPad Prism version 10 (GraphPad Software).

Techniques: Expressing, Staining, Real-time Polymerase Chain Reaction, Saline, Control

Journal: Biological Psychiatry Global Open Science

Article Title: Regional Molecular Changes in Chronic Lipopolysaccharide-Induced Neuroinflammation

doi: 10.1016/j.bpsgos.2025.100515

Figure Lengend Snippet: Brain tissue mRNA expression of neurotrophic factors and associations of molecular and behavioral outcomes in LPS treatment. Heatmaps of real-time polymerase chain reaction results showing the effect of ST- and LT-LPS treatment on the mRNA expression of Creb (B, F) and neurotrophic markers (A, C, D, E, G, H) in the Hyp, Pfc, Str, Hip, Mdb, Ctx, and Cbm. (E–H) Heatmaps of the sagittal plane of the rat brain showing the upregulated or downregulated mRNA expression in the different brain regions as a result of LPS. LPS (1 mg/kg, i.p.; ST, n = 8; LT, n = 9) and saline (0.1 mL, i.p.; ST, n = 10; LT, n = 10) were administered once off (ST; n = 18) and once a week for 4 weeks (LT; n = 19). Data are presented as mean ± SD relative to the housekeeping gene Tbp . Data were analyzed using a 2-way analysis of variance followed by a Tukey’s post hoc test, and heatmaps are presented as expression values ( z scores) for differentially expressed genes. ( A – D ) a ST-CON vs. ST-LPS; b ST-LPS vs. LT-LPS; c LT-CON vs. LT-LPS. p < .05 (a, b, c), p < .01 (aa, bb, cc), p < .001 (aaa, bbb, ccc), p < .0001 (aaaa, bbbb, cccc). (I) Volcano plot of all behavioral and molecular data with filtering criteria of |log 2 FC| > 1.3 and p < .05, and (J) Pearson’s correlation coefficient matrix heatmap of all molecular and behavioral analysis; p < .05. B dnf , brain-derived neurotrophic factor; Cbm, cerebellum; CON, control; C reb , cyclic-AMP response-element binding protein; Ctx, cortex; FC, fold change; Hip, hippocampus; Hyp, hypothalamus; I fn -γ, interferon gamma; I l , interleukin; i.p., intraperitoneally; LPS, lipopolysaccharide; LT, long-term; Mdb, midbrain; mRNA, messenger RNA; N gf , nerve growth factor; Pfc, prefrontal cortex; ST, short-term; Str, striatum.

Article Snippet: Heatmaps of gene expression z scores (see for additional information) for ST- and LT-CON and LPS-groups were generated in GraphPad Prism version 10 (GraphPad Software).

Techniques: Expressing, Real-time Polymerase Chain Reaction, Saline, Derivative Assay, Control, Binding Assay

Journal: Scientific Reports

Article Title: Uncovering drug repurposing candidates for head and neck cancers: insights from systematic pharmacogenomics data analysis

doi: 10.1038/s41598-021-03418-1

Figure Lengend Snippet: Identification of biomarker of response for osimertinib. ( A ) The mean logFC from the PRISM primary screen for osimertinib in HNSCC is comparable with NSCLC with EGFR mutations ( P = 0.4180). Both the clinically responsive subset (NSCLC with EGFR mutation) ( P = 0.0005) and unselected HNSCC ( P < 0.0001) have mean logFC that are significantly lower than the subset of NSCLC without EGFR mutation. ( B ) Pearson’s correlation of EGFR ligands (AREG, TGFA, EPGN, EREG and HBEGF) or EGFR gene expression with osimertinib sensitivity in 28 HNSCC cell lines (each row is a cell line). ( C ) Average EGFR ligands expression (Z-score) is significantly correlated with osimertinib sensitivity (logFC) (Pearson’s R = -0.4949, P = 0.0087). ( D ) Gene set enrichment analysis (GSEA) reveal significant upregulation of the TGF-beta signalling pathway among the osimertinib-resistant cell lines. ( E ) Gene expression heatmap from GSEA, showing the up-regulated genes within the TGF-beta signalling pathway. ( A ) to ( C ) were plotted using GraphPad Prism software 8.0.2. ( D ) and ( E ) were figures generated from running the GSEA modules from GenePattern 2 ( https://www.genepattern.org/ ).

Article Snippet: Both the clinically responsive subset (NSCLC with EGFR mutation) ( P = 0.0005) and unselected HNSCC ( P < 0.0001) have mean logFC that are significantly lower than the subset of NSCLC without EGFR mutation. ( B ) Pearson’s correlation of EGFR ligands (AREG, TGFA, EPGN, EREG and HBEGF) or EGFR gene expression with osimertinib sensitivity in 28 HNSCC cell lines (each row is a cell line). ( C ) Average EGFR ligands expression (Z-score) is significantly correlated with osimertinib sensitivity (logFC) (Pearson’s R = -0.4949, P = 0.0087). ( D ) Gene set enrichment analysis (GSEA) reveal significant upregulation of the TGF-beta signalling pathway among the osimertinib-resistant cell lines. ( E ) Gene expression heatmap from GSEA, showing the up-regulated genes within the TGF-beta signalling pathway. ( A ) to ( C ) were plotted using GraphPad Prism software 8.0.2. ( D ) and ( E ) were figures generated from running the GSEA modules from GenePattern 2 ( https://www.genepattern.org/ ).

Techniques: Biomarker Assay, Mutagenesis, Expressing, Software, Generated

Journal: Scientific Reports

Article Title: Uncovering drug repurposing candidates for head and neck cancers: insights from systematic pharmacogenomics data analysis

doi: 10.1038/s41598-021-03418-1

Figure Lengend Snippet: Uncovering candidate biomarkers of response and possible mechanism of intrinsic resistance towards MEKi. ( A ) Heatmap (generated using Morpheus tool: https://software.broadinstitute.org/morpheus/ ) with hierarchical clustering showing the drug sensitivity profile of 28 HNSCC cell lines towards all 20 MEKi. Some subclusters (in red) consisting of eight MEK inhibitors showed a largely similar pattern of sensitivity. ( B ) Volcano plot of differentially expressed genes between MEKi-sensitive and MEKi-resistant HNSCC. ( C ) STRING network analysis of 136 significantly upregulated genes among the MEKi-sensitive cell lines, revealed enrichment of REACTOME pathway (HSA-1280215-“Cytokines signalling in immune system” [highlighted in red]. A total of 24 genes were in this Reactome pathway (unconnected nodes are hidden). ( D ) Pearson’s correlation between the gene expression of six cytokines (IL1A, SAA1, LCN2, CSF2, IL1B and CXCL1) with significant correlation with the average potential drug sensitivity against MEKi (n = 28). Graph was plotted using GraphPad Prism software 8.0.2. ( E ) GSEA analysis of MEKi-sensitive and MEKi-resistant cell lines, with immune-related hallmark pathways being enriched among MEKi-sensitive HNSCC; While in MEKi-resistant HNSCC, hallmarks that are enriched are proliferation or cell cycle-related pathways. ( F ) Comparison of enriched hallmarks among the MEKi-resistant HNSCC, from GDSCv2 and Lepikhova datasets. The hallmarks of E2F_Targets, MYC_Targets_V2, G2M_checkpoint and spermatogenesis are consistently associated with MEKi resistance.

Article Snippet: Both the clinically responsive subset (NSCLC with EGFR mutation) ( P = 0.0005) and unselected HNSCC ( P < 0.0001) have mean logFC that are significantly lower than the subset of NSCLC without EGFR mutation. ( B ) Pearson’s correlation of EGFR ligands (AREG, TGFA, EPGN, EREG and HBEGF) or EGFR gene expression with osimertinib sensitivity in 28 HNSCC cell lines (each row is a cell line). ( C ) Average EGFR ligands expression (Z-score) is significantly correlated with osimertinib sensitivity (logFC) (Pearson’s R = -0.4949, P = 0.0087). ( D ) Gene set enrichment analysis (GSEA) reveal significant upregulation of the TGF-beta signalling pathway among the osimertinib-resistant cell lines. ( E ) Gene expression heatmap from GSEA, showing the up-regulated genes within the TGF-beta signalling pathway. ( A ) to ( C ) were plotted using GraphPad Prism software 8.0.2. ( D ) and ( E ) were figures generated from running the GSEA modules from GenePattern 2 ( https://www.genepattern.org/ ).

Techniques: Generated, Software, Expressing