Journal: OncoTargets and therapy

Article Title: Secretory Pathway Kinase FAM20C , a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma

doi: 10.2147/OTT.S275452

Figure Lengend Snippet: The development of secretory pathway kinase or kinase-like proteins (SPKKPs) gene signature stratifies the IDH wild type (wt) GBM as two groups with distinct survival. ( A ) The coefficient profiles of 13 SPKKPs genes with the gradual increase of lambda by LASSO regression (TCGA GBM RNA-seq, IDH wt, n = 142). ( B ) LASSO regression analysis with cross-validation method identified a SPKKPs gene signature including 3 members in this family ( FAM20A, FAM20A , and C3orf58 ) with prognostic value in IDH wt GBM (TCGA, n = 142). ( C ) Heatmap showing the association of 13 SPKKPs gene expression with clinicopathologic features in low- and high-risk GBM groups defined by the secretory pathway kinase related gene signature (TCGA GBM RNA-seq: low risk: n = 71, high risk: n = 71, Chi-square test). ( D ) Kaplan–Meier curves describing the survival of IDH wt GBM in low- and high-risk groups defined by secretory pathway-related gene signature (TCGA GBM RNA-seq: low risk: n = 71, high risk: n = 71, Log rank test, P = 0.0312). ( E ) The expression of SPKKPs member genes in different WHO grades of glioma (TCGA RNA-seq: grade II: n = 260, grade III: n = 267, GBM: n = 168, one-way ANOVA). ( F ) The expression of SPKKPs member genes in GBM with different IDH status (TCGA GBM RNA-seq: IDH mutant (mut): n = 11, IDH wt: n = 144, t -test). ( G ) The expression of SPKKPs member genes in all low-grade gliomas (LGG) and IDH -mut LGG with different 1p/19q codeletion (codel) status (TCGA RNA-seq: LGG 1p19q codel: n = 160, LGG 1p19q non-codel: n = 317; LGG with IDH mut 1p19q codel: n = 160, LGG with IDH mut 1p19q non-codel: n = 230, t -test). (ns P > 0.05, * P < 0.05, *** P < 0.001, and **** P < 0.0001).

Article Snippet: Figure 4 FAM20C knockdown suppresses the migration, invasion, and colony formation of GBM cells. ( A ) GSEA with TCGA GBM RNA-seq dataset disclosed a significant enrichment of cell adhesion- and immune response-related phenotypes in GBM patients with high FAM20C expression. ( B ) Heat maps describing the association between FAM20C expression and cell adhesion and negative immune-regulation‐related genes in TCGA GBM RNA-seq dataset (Chi-square test). ( C ) KEGG analysis was performed on genes with a correlation coefficient greater than 0.3 (Spearman analysis) with FAM20C in TCGA GBM RNA-seq dataset. ( D ) qPCR analyses of FAM20C, MMP2, and MMP9 mRNA expression in LN229 cells transfected with siRNA targeting FAM20C or a non-targeting control (n = 4, t -test). ( E ) Transwell assays demonstrating FAM20C knock-down inhibited the migration (upper panel) and invasion (lower panel) capabilities of LN229 cells (n = 10, t -test). ( ) The colony formation assay showing FAM20C knock-down significantly inhibited the colony formation capability of LN229 cells. (n = 6, t -test). (* P < 0.05, *** P < 0.001, and **** P < 0.0001).

Techniques: RNA Sequencing, Biomarker Discovery, Gene Expression, Expressing, Mutagenesis

Journal: OncoTargets and therapy

Article Title: Secretory Pathway Kinase FAM20C , a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma

doi: 10.2147/OTT.S275452

Figure Lengend Snippet: Integrative transcriptomic analyses identify FAM20C as the core member of secretory pathway kinase or kinase-like proteins (SPKKPs) family in glioma. ( A ) The protein interaction analysis among SPKKPs member genes with STRING ( https://string-db.org ). Dark green and pink lines represent known interactions. Green, red, and blue lines represent predicted interactions. Light green, black and gray lines represent other interactions. ( B and C ) Spearman correlation ( B ), the circle size represents correlation strength, and the color represents the positive (orange) or negative (blue) correlation and the univariate Cox regression analyses ( C ) of secretory pathway-related genes in TCGA glioma RNA-seq dataset. ( D ) Oncomine analysis of FAM20C expression in indicated cancers (The number in red represents the number of datasets demonstrating elevated FAM20C expression in indicated cancers. The number in blue represents the number of datasets showing decreased FAM20C expression in indicated cancers. The intensity of the color means the level of P value).

Article Snippet: Figure 4 FAM20C knockdown suppresses the migration, invasion, and colony formation of GBM cells. ( A ) GSEA with TCGA GBM RNA-seq dataset disclosed a significant enrichment of cell adhesion- and immune response-related phenotypes in GBM patients with high FAM20C expression. ( B ) Heat maps describing the association between FAM20C expression and cell adhesion and negative immune-regulation‐related genes in TCGA GBM RNA-seq dataset (Chi-square test). ( C ) KEGG analysis was performed on genes with a correlation coefficient greater than 0.3 (Spearman analysis) with FAM20C in TCGA GBM RNA-seq dataset. ( D ) qPCR analyses of FAM20C, MMP2, and MMP9 mRNA expression in LN229 cells transfected with siRNA targeting FAM20C or a non-targeting control (n = 4, t -test). ( E ) Transwell assays demonstrating FAM20C knock-down inhibited the migration (upper panel) and invasion (lower panel) capabilities of LN229 cells (n = 10, t -test). ( ) The colony formation assay showing FAM20C knock-down significantly inhibited the colony formation capability of LN229 cells. (n = 6, t -test). (* P < 0.05, *** P < 0.001, and **** P < 0.0001).

Techniques: RNA Sequencing, Expressing

Journal: OncoTargets and therapy

Article Title: Secretory Pathway Kinase FAM20C , a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma

doi: 10.2147/OTT.S275452

Figure Lengend Snippet: FAM20C is associated with progressive malignancy and unfavorable prognosis in glioma. ( A ) Representative immunohistochemical images of FAM20C staining in clinical glioma samples (Scale bar, 50 μm; grade II: n = 3, grade III: n = 7, grade IV: n=28). ( B ) Kaplan–Meier curve evaluating the correlation between FAM20C protein expression and GBM patients’ survival (FAM20C low vs high, low n = 11, high n = 17, P = 0.0241; Log rank test). ( C ) The analyses of FAM20C expression in non-tumor and different grade glioma samples (TCGA glioma RNA-seq: non-tumor, n = 5; grade II: n = 130; grade III: n = 133; GBM: n = 80, one-way ANOVA). ( D ) Kaplan–Meier curves of FAM20C expression and the survival of different grade glioma in TCGA. (left panel: grade II, low n = 130, high n = 130, P = 0.710; middle panel: grade III, low n = 133, high n = 134, P = 0.0069; right panel: GBM, low n = 80, high n = 80, P = 0.0013, Log rank test). ( E ) The analysis of FAM20C expression in non-tumor and GBM samples using data from Clinical Proteomic Tumor Analysis Consortium (CPTAC, non-tumor, n = 10; GBM, n = 100, P < 0.0001, t -test). ( F ) Kaplan–Meier curves of FAM20C expression and GBM patients’ survival in CPTAC. (high: n = 46, low: n = 47, P = 0.0032, Log rank test) ( G ) The analysis of FAM20C expression in different regions of GBM with data from the IVY GBM Altas Project ( http://glioblastoma.alleninstitute.org/ ). ( H ) Representative immunohistochemical images of FAM20C staining in peri-necrotic region of GBM. (Scale bar, 50 μm). ( I ) The analyses of FAM20C expression in different subtypes GBM (TCGA GBM RNA-seq: classical n = 48; mesenchymal n = 65; proneural n = 18, one-way ANOVA). ( J ) The receiver operator characteristic (ROC) curve describing the sensitivity and specificity of FAM20C as a marker for mesenchymal (n = 65) vs other subtypes (classical n = 48, and proneural n = 18) in TCGA. ( K ) FAM20C expression analysis in GBM with different IDH status (TCGA GBM RNA-seq: IDH mut, n = 11; IDH wt, n = 143, P < 0.0001, t -test). ( L ) Kaplan‐Meier curve describing the association between FAM20C expression and GBM IDH wt patients’ 2-year survival (TCGA, low n = 71, high n = 71, P = 0.0288, Log rank test). ( M ) The ROC curves comparing the sensitivity and specificity of FAM20C as a prognostic marker for glioma patients in TCGA (left panel: 3‐year; right: 5‐year). ( N and O ) Kaplan–Meier curves describing the association between FAM20C expression and TCGA GBM patients’ survival with or without radiation ( N ) or chemotherapy ( O ) (N: low without radiation n = 39, low with radiation n = 43; high without radiation n = 32, high with radiation n = 50; ( O ) low without chemotherapy n = 22, low with chemotherapy n = 61; high without chemotherapy n = 18, high with chemotherapy n = 66, Log rank test). (ns P > 0.05, * P < 0.05, ** P < 0.01, *** P < 0.001, and **** P < 0.0001).

Article Snippet: Figure 4 FAM20C knockdown suppresses the migration, invasion, and colony formation of GBM cells. ( A ) GSEA with TCGA GBM RNA-seq dataset disclosed a significant enrichment of cell adhesion- and immune response-related phenotypes in GBM patients with high FAM20C expression. ( B ) Heat maps describing the association between FAM20C expression and cell adhesion and negative immune-regulation‐related genes in TCGA GBM RNA-seq dataset (Chi-square test). ( C ) KEGG analysis was performed on genes with a correlation coefficient greater than 0.3 (Spearman analysis) with FAM20C in TCGA GBM RNA-seq dataset. ( D ) qPCR analyses of FAM20C, MMP2, and MMP9 mRNA expression in LN229 cells transfected with siRNA targeting FAM20C or a non-targeting control (n = 4, t -test). ( E ) Transwell assays demonstrating FAM20C knock-down inhibited the migration (upper panel) and invasion (lower panel) capabilities of LN229 cells (n = 10, t -test). ( ) The colony formation assay showing FAM20C knock-down significantly inhibited the colony formation capability of LN229 cells. (n = 6, t -test). (* P < 0.05, *** P < 0.001, and **** P < 0.0001).

Techniques: Immunohistochemical staining, Staining, Expressing, RNA Sequencing, Marker

Journal: OncoTargets and therapy

Article Title: Secretory Pathway Kinase FAM20C , a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma

doi: 10.2147/OTT.S275452

Figure Lengend Snippet: FAM20C knockdown suppresses the migration, invasion, and colony formation of GBM cells. ( A ) GSEA with TCGA GBM RNA-seq dataset disclosed a significant enrichment of cell adhesion- and immune response-related phenotypes in GBM patients with high FAM20C expression. ( B ) Heat maps describing the association between FAM20C expression and cell adhesion and negative immune-regulation‐related genes in TCGA GBM RNA-seq dataset (Chi-square test). ( C ) KEGG analysis was performed on genes with a correlation coefficient greater than 0.3 (Spearman analysis) with FAM20C in TCGA GBM RNA-seq dataset. ( D ) qPCR analyses of FAM20C, MMP2, and MMP9 mRNA expression in LN229 cells transfected with siRNA targeting FAM20C or a non-targeting control (n = 4, t -test). ( E ) Transwell assays demonstrating FAM20C knock-down inhibited the migration (upper panel) and invasion (lower panel) capabilities of LN229 cells (n = 10, t -test). ( F ) The colony formation assay showing FAM20C knock-down significantly inhibited the colony formation capability of LN229 cells. (n = 6, t -test). (* P < 0.05, *** P < 0.001, and **** P < 0.0001).

Article Snippet: Figure 4 FAM20C knockdown suppresses the migration, invasion, and colony formation of GBM cells. ( A ) GSEA with TCGA GBM RNA-seq dataset disclosed a significant enrichment of cell adhesion- and immune response-related phenotypes in GBM patients with high FAM20C expression. ( B ) Heat maps describing the association between FAM20C expression and cell adhesion and negative immune-regulation‐related genes in TCGA GBM RNA-seq dataset (Chi-square test). ( C ) KEGG analysis was performed on genes with a correlation coefficient greater than 0.3 (Spearman analysis) with FAM20C in TCGA GBM RNA-seq dataset. ( D ) qPCR analyses of FAM20C, MMP2, and MMP9 mRNA expression in LN229 cells transfected with siRNA targeting FAM20C or a non-targeting control (n = 4, t -test). ( E ) Transwell assays demonstrating FAM20C knock-down inhibited the migration (upper panel) and invasion (lower panel) capabilities of LN229 cells (n = 10, t -test). ( ) The colony formation assay showing FAM20C knock-down significantly inhibited the colony formation capability of LN229 cells. (n = 6, t -test). (* P < 0.05, *** P < 0.001, and **** P < 0.0001).

Techniques: Knockdown, Migration, RNA Sequencing, Expressing, Transfection, Control, Colony Assay

Journal: OncoTargets and therapy

Article Title: Secretory Pathway Kinase FAM20C , a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma

doi: 10.2147/OTT.S275452

Figure Lengend Snippet: The screening of FAM20C substrates in GBM distinguishes FN1 as the key substrate interacting with it. ( A ) The analyses of protein interactions between FAM20C and its substrates by STRING webtool ( https://string-db.org ). ( B ) The univariate Cox regression analyses of FAM20C substrates in TCGA GBM RNA-seq dataset. ( C ) Pearson correlation analysis between FAM20C and its substrates (TCGA GBM RNA-seq dataset: circle size represents the correlation strength, and color represents the positive (orange) or negative (blue) correlation). ( D ) Pearson correlation analysis between FAM20C and FN1 in TCGA GBM RNA-seq dataset. ( E ) Three-dimensional binding pattern of FAM20C and FN1 protein obtained by molecular docking simulation. ( F ) The interaction site between FAM20C and FN1.

Article Snippet: Figure 4 FAM20C knockdown suppresses the migration, invasion, and colony formation of GBM cells. ( A ) GSEA with TCGA GBM RNA-seq dataset disclosed a significant enrichment of cell adhesion- and immune response-related phenotypes in GBM patients with high FAM20C expression. ( B ) Heat maps describing the association between FAM20C expression and cell adhesion and negative immune-regulation‐related genes in TCGA GBM RNA-seq dataset (Chi-square test). ( C ) KEGG analysis was performed on genes with a correlation coefficient greater than 0.3 (Spearman analysis) with FAM20C in TCGA GBM RNA-seq dataset. ( D ) qPCR analyses of FAM20C, MMP2, and MMP9 mRNA expression in LN229 cells transfected with siRNA targeting FAM20C or a non-targeting control (n = 4, t -test). ( E ) Transwell assays demonstrating FAM20C knock-down inhibited the migration (upper panel) and invasion (lower panel) capabilities of LN229 cells (n = 10, t -test). ( ) The colony formation assay showing FAM20C knock-down significantly inhibited the colony formation capability of LN229 cells. (n = 6, t -test). (* P < 0.05, *** P < 0.001, and **** P < 0.0001).

Techniques: RNA Sequencing, Binding Assay

Journal: OncoTargets and therapy

Article Title: Secretory Pathway Kinase FAM20C , a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma

doi: 10.2147/OTT.S275452

Figure Lengend Snippet: FAM20C is associated with the regulation of immune response in GBM. ( A ) Heat maps describing the expression of FAM20C negatively correlated with tumor purity, and positively correlated with immune score and stromal score (TCGA GBM RNA-seq, n = 168, Pearson correlation analysis). ( B ) The analyses of xCell (upper panel) and EPIC scores (lower panel) indicating FAM20C expression pattern in indicated cell populations (TCGA GBM RNA-seq: FAM20C low n = 84; high n = 84, t -test). ( C and D ) t-SNE map color-coded for transcript counts ( C ) and the corresponding single-cell bar plots ( D ) of FAM20C enriched in different cell subpopulations of GBM (SCP393 dataset, https://portals.broadinstitute.org/single_cell/study/SCP393/single-cell-rna-seq-of-adult-and-pediatric-glioblastoma ). ( E ) Transwell assay showing 20 μg/mL FAM20C recombinant protein significantly enhances the migration of THP1 cells. (n = 15, t -test). (ns P > 0.05, ** P < 0.01, *** P < 0.001, and **** P < 0.0001).

Article Snippet: Figure 4 FAM20C knockdown suppresses the migration, invasion, and colony formation of GBM cells. ( A ) GSEA with TCGA GBM RNA-seq dataset disclosed a significant enrichment of cell adhesion- and immune response-related phenotypes in GBM patients with high FAM20C expression. ( B ) Heat maps describing the association between FAM20C expression and cell adhesion and negative immune-regulation‐related genes in TCGA GBM RNA-seq dataset (Chi-square test). ( C ) KEGG analysis was performed on genes with a correlation coefficient greater than 0.3 (Spearman analysis) with FAM20C in TCGA GBM RNA-seq dataset. ( D ) qPCR analyses of FAM20C, MMP2, and MMP9 mRNA expression in LN229 cells transfected with siRNA targeting FAM20C or a non-targeting control (n = 4, t -test). ( E ) Transwell assays demonstrating FAM20C knock-down inhibited the migration (upper panel) and invasion (lower panel) capabilities of LN229 cells (n = 10, t -test). ( ) The colony formation assay showing FAM20C knock-down significantly inhibited the colony formation capability of LN229 cells. (n = 6, t -test). (* P < 0.05, *** P < 0.001, and **** P < 0.0001).

Techniques: Expressing, RNA Sequencing, Transwell Assay, Recombinant, Migration

Journal: Molecular Cancer

Article Title: Emerging artificial intelligence-driven precision therapies in tumor drug resistance: recent advances, opportunities, and challenges

doi: 10.1186/s12943-025-02321-x

Figure Lengend Snippet: Application of artificial intelligence in basic research on tumor drug resistance

Article Snippet: RNA-seq data from DepMap and TCGA datasets , TransCell (Self-Encoders + Migration Learning + Deep Feedforward Neural Networks) , External validation on proteomic data in CellMinerCDB and RNA-seq data in NCI60 cell line , TransCell improved drug susceptibility prediction performance by more than 50% , [ ] .

Techniques: Biomarker Discovery, Binding Assay, Fluorescence, Kinase Assay, Immunohistochemistry, Quantitative RT-PCR, Staining, Knockdown, CRISPR, Mutagenesis, Knock-Out, Activation Assay, Expressing, Reverse Transcription Polymerase Chain Reaction, Migration, Gene Expression, Plasmid Preparation, Injection, Selection, Histone Deacetylase Assay, Imaging, Cytometry

Journal: Molecular Cancer

Article Title: Emerging artificial intelligence-driven precision therapies in tumor drug resistance: recent advances, opportunities, and challenges

doi: 10.1186/s12943-025-02321-x

Figure Lengend Snippet: Available databases on tumor drug resistance

Article Snippet: RNA-seq data from DepMap and TCGA datasets , TransCell (Self-Encoders + Migration Learning + Deep Feedforward Neural Networks) , External validation on proteomic data in CellMinerCDB and RNA-seq data in NCI60 cell line , TransCell improved drug susceptibility prediction performance by more than 50% , [ ] .

Techniques: Expressing, Mutagenesis, Drug discovery, Biomarker Discovery

Journal: Cell Discovery

Article Title: Targeting a chemo-induced adaptive signaling circuit confers therapeutic vulnerabilities in pancreatic cancer

doi: 10.1038/s41421-024-00720-w

Figure Lengend Snippet: a Kaplan–Meier survival analysis of patients with 14-3-3ζ-high ( n = 114) and -low expressing ( n = 12) PDACs (log-rank test). b Kaplan–Meier survival analysis of KPC ( n = 10) and KPC -ζ fl/fl ( n = 9) mice treated with Gem (Log-Rank test). c Relative cell number of PANC-1.shCtrl/sh ζ cells 3D-cultured in the lower chambers of a Transwell unit with or without 3D-cultured hPSCs in the upper chambers of a Transwell unit treated with Gem (20 nM) for 72 h (mean ± SD, t -test, n = 3 biological repeats). d Gene set enrichment analysis (GSEA) of Yap1 signature in 14-3-3ζ-high vs 14-3-3ζ-low human PDACs in the TCGA dataset. e Western blotting (WB) analyses of cytoplasmic and nuclear Yap1, 14-3-3ζ, tubulin (a cytoplasmic protein marker, sample processing controls), and YY1 (a nuclear protein marker, sample processing controls) in 3D-cultured PACN-1.shCtrl vs PACN-1.sh ζ cells that were treated with Gem (20 nM) or vehicle for 3 h. Representative data of two independent repeats. f RPPA analysis of NIH3T3 cells treated with CM collected from Panc02 cells cultured in 10% or 0% FBS medium. g WB analysis of Cox2 and GAPDH (sample processing controls) in NIH3T3 cells treated with CM from Panc02.shCtrl or sh ζ cells treated with or without Gem (20 nM, 72 h). Representative data of two independent repeats. h Relative cell number of Panc02 cells under indicated modifications and conditions; Panc02-GFP cells and NIH3T3 cells were transfected with control or indicated siRNAs respectively, then co-cultured and treated with Gem (8.5 nM) or vehicle. Panc02:NIH3T3 = 1:9 (mean ± SD, t -test, n = 3 biological repeats). i Schematics of in vivo experiment in Fig. 1j, k. Panc02.shCtrl ind. are Panc02.doxy-inducible shCtrl cells, Panc02.sh Yap1 ind. are Panc02.doxy-inducible sh Yap1 cells. j IHC staining of Yap1 in PDACs from intrapancreatic injection of Panc02.doxy-inducible shCtrl and Panc02.doxy-inducible sh Yap1 cells. scale bar: 25 µm. k Left: Quantification of tumor volumes of doxy-treated mice bearing Panc02.doxy-inducible shCtrl or Panc02.doxy-inducible sh Yap1 tumors 1 week after the indicated treatments (mean, Mann–Whitney test). Right: Images of treated Panc02 tumors.

Article Snippet: TCGA RNA-seq data were downloaded from the Broad Institute Firehose website ( https://gdac.broadinstitute.org/ ).

Techniques: Expressing, Cell Culture, Western Blot, Marker, Transfection, Control, In Vivo, Immunohistochemistry, Injection, MANN-WHITNEY

Journal: Cell Discovery

Article Title: Targeting a chemo-induced adaptive signaling circuit confers therapeutic vulnerabilities in pancreatic cancer

doi: 10.1038/s41421-024-00720-w

Figure Lengend Snippet: a Comparison of clinicopathological features of 113 patients with pancreatic cancer (MDACC patient cohort 1) expressing different levels of 14-3-3ζ (low vs high), nuclear Yap1 (negative vs positive), and stromal Cox2 (negative vs positive). b Representative IHC images of human PDAC tumors stained with the indicated proteins. scale bar: 50 µm (14-3-3ζ), 20 µm (Yap1 and Cox2). c Multivariate logistic regression analysis of the correlation between Yap1 (nuclear) and 14-3-3ζ by adjusting for the indicated clinicopathological characteristics. Odds ratio, 95% confidence intervals, and P values are presented. d Multivariate logistic regression analysis of the correlation between Cox2 (stroma) and Yap1 (nuclear) by adjusting for the indicated clinicopathological characteristics. Odds ratio, 95% confidence intervals, and P values are presented. e Correlation analysis between Yap1 target gene signatures and Cox2 gene expression using TCGA (Left) and ICGC (Right) PDAC patient datasets.

Article Snippet: TCGA RNA-seq data were downloaded from the Broad Institute Firehose website ( https://gdac.broadinstitute.org/ ).

Techniques: Comparison, Expressing, Staining, Gene Expression

Journal: Scientific Reports

Article Title: Loss of Parkinson’s susceptibility gene LRRK2 promotes carcinogen-induced lung tumorigenesis

doi: 10.1038/s41598-021-81639-0

Figure Lengend Snippet: LRRK2 -low lung adenocarcinoma is associated with poor patient survival, non-TRU expression-based molecular subtypes and worse predicted tumor differentiation. ( A ) Plot of LRRK2 mRNA levels in LUAD tumors (dichotomized into LRRK2 -low and -high expression groups) and adjacent normal lung tissue (RSEM values), from TCGA LUAD patients. ( B ) Kaplan–Meier plot of LUAD patient OS or DSS stratified by LRRK2 expression status. ( C ) Pairwise Fisher’s exact test for enrichment of expression subtype frequency within LRRK2 expression groups: TRU-like versus non-TRU type LUAD. ( D ) (Left) Standardized LRRK2 tumoral expression per sample (RSEM values), annotated for lower risk TRU-like or higher risk non-TRU type tumors or (Right) grouped by the combined status for LRRK2 expression and expression subtype (median centred boxplot of RSEM values). ( E ) Pairwise Fisher’s exact test for enrichment of smoking history within LRRK2 expression groups: TRU-like versus non-TRU type LUAD. ( F ) Correlation of LRRK2 expression with a previously published gene expression-based score representing LUAD tumor differentiation status (Spearman’s correlation coefficient − 0.59 with Holm’s adjP < 0.0001; positive scores represent increasingly poor differentiation). ( G ) Stratification of the tumoral gene expression of established markers for alveolar and bronchiolar epithelial cell types, by the combined LRRK2 and expression subtype status of LUAD tumors (median-centred boxplot of standardized RSEM values; Dunn’s test BH adjP < 0.05).

Article Snippet: The following data were downloaded from the Broad Institute TCGA Genome Data Analysis Center: Level 3 TCGA LUAD clinical data (10.7908/C19P30S6), Level 3 TCGA LUAD mutation calls (10.7908/C11G0KM9), Level 4 somatic DNA alterations (SNP6 GISTIC2 copy number analysis (10.7908/C1348JSB), Level 4 MutSig 2CV version 3.1 mutation analysis (10.7908/C17P8XT3)), Level 3 TCGA LUAD RNA-seq data (10.7908/C11G0KM9).

Techniques: Expressing, Gene Expression

Journal: Scientific Reports

Article Title: Loss of Parkinson’s susceptibility gene LRRK2 promotes carcinogen-induced lung tumorigenesis

doi: 10.1038/s41598-021-81639-0

Figure Lengend Snippet: The transcriptional landscape of LRRK2 repression in lung adenocarcinoma patients. ( A ) Heatmap depicting the hierarchical agglomerative clustering of genes differentially expressed in common between two biological contexts in TCGA LUAD tumors, each with a marked reduction of LRRK2 expression: (1) across all tumors versus normal lung and (2) in the lowest LRRK2 expressing tumors versus the highest LRRK2 expressing tumors. Columns: n = 385 DEGs with absolute fold change of median RSEM value > 2; Rows: n = 59 normal lung and n = 517 LUAD tumors, ordered by tissue, LRRK2 expression status and expression subtype. ( B ) Exemplar DEGs identified in Cluster 1, enriched for genes that act in mitotic cell cycle (Metascape algorithm; q < 0.05), stratified by tumor group (multicolour boxplots of exemplar gene expression; Dunn’s test BH adjP > 0.05). Tumor groups represent the combined sample status for LRRK2 expression and non-TRU subtype. ( C ) Exemplar DEGs identified in Cluster 2, associated with tumor purity (consensus purity estimate or CPE; Spearman’s correlation coefficient ≥ 0.5 with Holm’s corrected P < 0.0001) and enriched for immune response genes (Metascape algorithm; q < 0.05), stratified by tumor group (multicolour boxplots of exemplar gene expression; Dunn’s test BH adjP < 0.01). ( D ) Exemplar DEGs identified in Cluster 3, enriched for genes that act in surfactant metabolism (Metascape algorithm; q < 0.05), stratified by tumor group (multicolour boxplots of exemplar gene expression; Dunn’s test BH adjP < 0.001) or plotted against LRRK2 expression (multicolour scatterplots; Spearman’s correlation coefficient ≥ 0.6 with Holm’s corrected P < 0.0001; standardized RSEM Transcripts Per Million or TPM).

Article Snippet: The following data were downloaded from the Broad Institute TCGA Genome Data Analysis Center: Level 3 TCGA LUAD clinical data (10.7908/C19P30S6), Level 3 TCGA LUAD mutation calls (10.7908/C11G0KM9), Level 4 somatic DNA alterations (SNP6 GISTIC2 copy number analysis (10.7908/C1348JSB), Level 4 MutSig 2CV version 3.1 mutation analysis (10.7908/C17P8XT3)), Level 3 TCGA LUAD RNA-seq data (10.7908/C11G0KM9).

Techniques: Expressing, Gene Expression

Journal: Scientific Reports

Article Title: Loss of Parkinson’s susceptibility gene LRRK2 promotes carcinogen-induced lung tumorigenesis

doi: 10.1038/s41598-021-81639-0

Figure Lengend Snippet: Overlap of DEGs identified in the lowest LRRK2 -expressing TCGA LUAD tumors with DEGs identified in mouse lung development.

Article Snippet: The following data were downloaded from the Broad Institute TCGA Genome Data Analysis Center: Level 3 TCGA LUAD clinical data (10.7908/C19P30S6), Level 3 TCGA LUAD mutation calls (10.7908/C11G0KM9), Level 4 somatic DNA alterations (SNP6 GISTIC2 copy number analysis (10.7908/C1348JSB), Level 4 MutSig 2CV version 3.1 mutation analysis (10.7908/C17P8XT3)), Level 3 TCGA LUAD RNA-seq data (10.7908/C11G0KM9).

Techniques: Expressing

Journal: The Journal of Immunology Author Choice

Article Title: Immune Subtypes and Immune Landscape Analysis of Endometrial Carcinoma

doi: 10.4049/jimmunol.2200329

Figure Lengend Snippet: ISs in uterine corpus endometrial carcinoma (UCEC). (A and B) The CDF curve of TCGA-UCEC cohort samples (A) and CDF delta area curve of TCGA-UCEC cohort samples (B) indicated that when the cluster was selected as 3, there was a relatively stable clustering result. (C) We selected k = 3 to obtain three ISs (IS1, IS2 and IS3). (D) Kaplan–Meier curves of three ISs showed that IS3 had a good prognosis, whereas the IS1 subtypes had a poor prognosis. There was a significantly high proportion of the IS1 subtypes (E) in stage IV patients and a significantly high proportion of the IS1 subtypes (F) in G3 samples. (G) The prognosis of these three ISs also significantly differs in uterine sarcoma. (H) There were significant differences among the three ISs in different stages. (I) There was a significantly high proportion of the IS1 subtypes in the stage III and stage IV samples.

Article Snippet: CDF cumulative distribution function EC endometrial cancer FPKM fragments per kilobase million GO Gene Ontology IS immune subtype MDSC myeloid-derived suppressor cell PCA principal component PD-1 programmed cell death protein 1 qPCR quantitative PCR RNA-seq RNA sequencing TCGA The Cancer Genome Atlas TIM tumor immune microenvironment TMB tumor mutational burden UCSC University of California Santa Cruz .

Techniques: