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Partek normalized rnaseq data
Neuroendocrine SCLC express fewer factors that are inhibitory to NK cells. ( A ) Immunofluorescent staining of NCAM1 and MHC-class I proteins in SCLC tissues of a tumor microarray (NCAM1 = red, MHC-class I = white, DAPI = blue). Images representing tumor cases that are POS for NCAM1 and NEG for MHC-class I; double POS for NCAM1 and MHC-class I; NCAM1 NEG/MHC-class I POS; and double NEG for NCAM1 and MHC-class I. ( B ) Quantification of 80 SCLC tumors scored based on positivity for NCAM1 and MHC-class I expression. ( C ) Immunofluorescent staining of ASCL1, NEUROD1, POU2F3, YAP1, and MHC-class I in SCLC tissues of a tumor microarray (ASCL1 = turquoise, NEUROD1 = green, POU2F3 = pink, YAP1 = red, MHC-class I = white, DAPI = blue). Images representing a tumor classified as each of the four subtypes of SCLC. ( D ) Quantification of 79 evaluable tumors based on the predominant transcription factor expression and MHC-class I within each case. ( E ) SCLC tissues of a tumor microarray were analyzed by RNA in situ hybridization for the presence of NK cells. Representative image depicting RNA in situ hybridization staining of CD49b mRNA (pink) and NCR3 mRNA (NKp30, green). ( F ) Quantification displays the number of NK cells per 1000 DAPI POS cells within a standardized ROI; analysis completed on ASCL1 POS MHC-class I NEG , ASCL1 POS MHC-class I POS , NEUROD1 POS , POU2F3 POS (n = 5 tissues each), and YAP1 POS (n = 2 tissues). *p < 0.05 by one-way ANOVA with Tukey’s multiple comparison post-test. ( G ) Heatmap expression of ASCL1, NEUROD1, POU2F3, YAP1, and genes relevant to NK activity in 88 SCLC tumor biopsies obtained from 62 patients <t>with</t> <t>metastatic</t> SCLC previously analyzed by <t>RNAseq</t> analysis (NE = grey, non-NE = black, ASCL1 = purple, NEUROD1 = orange, POU2F3 = blue, YAP1 = green). ( H ) Heatmap of expression of selected NK activating and NK inhibitory ligand genes as determined by quantitative reverse transcription PCR across a panel of SCLC cell lines (NE = neuroendocrine; non-NE = non-neuroendocrine). Values illustrated correspond to log 2 -transformed gene expression relative to the control gene GAPDH in each cell line. ( I ) Neuroendocrine (DMS79, H69) and non-neuroendocrine (DMS114, H841) SCLC cells were assayed for susceptibility to NK cells at an E:Tratio of 10:1 in a 24-hour assay. **** p < 0.0001 comparing NE versus non-NE by unpaired t test. Data illustrated are representative of n = 8 healthy NK donors. #, number; ANOVA, analysis of variance; DAPI, ′,6-diamidino-2-phenylindole; E:T, effector-to-target; NE, neuroendocrine; NEG, negative; NK, natural killer; PCR, polymerase chain reaction; POS, positive; ROI, region of interest.
Normalized Rnaseq Data, supplied by Partek, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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1) Product Images from "An Interleukin-15 Superagonist Enables Antitumor Efficacy of Natural Killer Cells Against All Molecular Variants of SCLC"

Article Title: An Interleukin-15 Superagonist Enables Antitumor Efficacy of Natural Killer Cells Against All Molecular Variants of SCLC

Journal: Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer

doi: 10.1016/j.jtho.2022.11.008

Neuroendocrine SCLC express fewer factors that are inhibitory to NK cells. ( A ) Immunofluorescent staining of NCAM1 and MHC-class I proteins in SCLC tissues of a tumor microarray (NCAM1 = red, MHC-class I = white, DAPI = blue). Images representing tumor cases that are POS for NCAM1 and NEG for MHC-class I; double POS for NCAM1 and MHC-class I; NCAM1 NEG/MHC-class I POS; and double NEG for NCAM1 and MHC-class I. ( B ) Quantification of 80 SCLC tumors scored based on positivity for NCAM1 and MHC-class I expression. ( C ) Immunofluorescent staining of ASCL1, NEUROD1, POU2F3, YAP1, and MHC-class I in SCLC tissues of a tumor microarray (ASCL1 = turquoise, NEUROD1 = green, POU2F3 = pink, YAP1 = red, MHC-class I = white, DAPI = blue). Images representing a tumor classified as each of the four subtypes of SCLC. ( D ) Quantification of 79 evaluable tumors based on the predominant transcription factor expression and MHC-class I within each case. ( E ) SCLC tissues of a tumor microarray were analyzed by RNA in situ hybridization for the presence of NK cells. Representative image depicting RNA in situ hybridization staining of CD49b mRNA (pink) and NCR3 mRNA (NKp30, green). ( F ) Quantification displays the number of NK cells per 1000 DAPI POS cells within a standardized ROI; analysis completed on ASCL1 POS MHC-class I NEG , ASCL1 POS MHC-class I POS , NEUROD1 POS , POU2F3 POS (n = 5 tissues each), and YAP1 POS (n = 2 tissues). *p < 0.05 by one-way ANOVA with Tukey’s multiple comparison post-test. ( G ) Heatmap expression of ASCL1, NEUROD1, POU2F3, YAP1, and genes relevant to NK activity in 88 SCLC tumor biopsies obtained from 62 patients with metastatic SCLC previously analyzed by RNAseq analysis (NE = grey, non-NE = black, ASCL1 = purple, NEUROD1 = orange, POU2F3 = blue, YAP1 = green). ( H ) Heatmap of expression of selected NK activating and NK inhibitory ligand genes as determined by quantitative reverse transcription PCR across a panel of SCLC cell lines (NE = neuroendocrine; non-NE = non-neuroendocrine). Values illustrated correspond to log 2 -transformed gene expression relative to the control gene GAPDH in each cell line. ( I ) Neuroendocrine (DMS79, H69) and non-neuroendocrine (DMS114, H841) SCLC cells were assayed for susceptibility to NK cells at an E:Tratio of 10:1 in a 24-hour assay. **** p < 0.0001 comparing NE versus non-NE by unpaired t test. Data illustrated are representative of n = 8 healthy NK donors. #, number; ANOVA, analysis of variance; DAPI, ′,6-diamidino-2-phenylindole; E:T, effector-to-target; NE, neuroendocrine; NEG, negative; NK, natural killer; PCR, polymerase chain reaction; POS, positive; ROI, region of interest.
Figure Legend Snippet: Neuroendocrine SCLC express fewer factors that are inhibitory to NK cells. ( A ) Immunofluorescent staining of NCAM1 and MHC-class I proteins in SCLC tissues of a tumor microarray (NCAM1 = red, MHC-class I = white, DAPI = blue). Images representing tumor cases that are POS for NCAM1 and NEG for MHC-class I; double POS for NCAM1 and MHC-class I; NCAM1 NEG/MHC-class I POS; and double NEG for NCAM1 and MHC-class I. ( B ) Quantification of 80 SCLC tumors scored based on positivity for NCAM1 and MHC-class I expression. ( C ) Immunofluorescent staining of ASCL1, NEUROD1, POU2F3, YAP1, and MHC-class I in SCLC tissues of a tumor microarray (ASCL1 = turquoise, NEUROD1 = green, POU2F3 = pink, YAP1 = red, MHC-class I = white, DAPI = blue). Images representing a tumor classified as each of the four subtypes of SCLC. ( D ) Quantification of 79 evaluable tumors based on the predominant transcription factor expression and MHC-class I within each case. ( E ) SCLC tissues of a tumor microarray were analyzed by RNA in situ hybridization for the presence of NK cells. Representative image depicting RNA in situ hybridization staining of CD49b mRNA (pink) and NCR3 mRNA (NKp30, green). ( F ) Quantification displays the number of NK cells per 1000 DAPI POS cells within a standardized ROI; analysis completed on ASCL1 POS MHC-class I NEG , ASCL1 POS MHC-class I POS , NEUROD1 POS , POU2F3 POS (n = 5 tissues each), and YAP1 POS (n = 2 tissues). *p < 0.05 by one-way ANOVA with Tukey’s multiple comparison post-test. ( G ) Heatmap expression of ASCL1, NEUROD1, POU2F3, YAP1, and genes relevant to NK activity in 88 SCLC tumor biopsies obtained from 62 patients with metastatic SCLC previously analyzed by RNAseq analysis (NE = grey, non-NE = black, ASCL1 = purple, NEUROD1 = orange, POU2F3 = blue, YAP1 = green). ( H ) Heatmap of expression of selected NK activating and NK inhibitory ligand genes as determined by quantitative reverse transcription PCR across a panel of SCLC cell lines (NE = neuroendocrine; non-NE = non-neuroendocrine). Values illustrated correspond to log 2 -transformed gene expression relative to the control gene GAPDH in each cell line. ( I ) Neuroendocrine (DMS79, H69) and non-neuroendocrine (DMS114, H841) SCLC cells were assayed for susceptibility to NK cells at an E:Tratio of 10:1 in a 24-hour assay. **** p < 0.0001 comparing NE versus non-NE by unpaired t test. Data illustrated are representative of n = 8 healthy NK donors. #, number; ANOVA, analysis of variance; DAPI, ′,6-diamidino-2-phenylindole; E:T, effector-to-target; NE, neuroendocrine; NEG, negative; NK, natural killer; PCR, polymerase chain reaction; POS, positive; ROI, region of interest.

Techniques Used: Staining, Microarray, Expressing, RNA In Situ Hybridization, Comparison, Activity Assay, Reverse Transcription, Transformation Assay, Gene Expression, Control, Polymerase Chain Reaction



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A heatmap of gene expression of adaptive immune resistance markers in PDAC patients from <t>TCGA</t> (n=152). Please also see Supplementary Fig. S2, Supplementary Table S1). Genes included in the heatmap are PD-L1 (CD274), IDO1, CTLA4, LAG3, CD276 (B7-H3), V-set domain containing T-cell activation inhibitor 1 (VTCN1; also known as B7-H4), CD70, Hepatitis A virus cellular receptor 2 (HAVCR2; also known as T-cell immunoglobulin and mucin-domain containing-3 (TIM-3)), CD40, CD47, tumor necrosis factor receptor superfamily member 18 (TNFRSF18I; also known as glucocorticoid-induced TNFR-related protein (GITR)), TIGIT, or LIGHT (also known as tumor necrosis factor superfamily member 14 (TNFSF14)). Each column is a sample.
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Image Search Results


Expression patterns of the ZDHHC enzymes in major human cell types. Heatmaps showing human single-cell RNAseq expression data for the ZDHHC enzymes, downloaded from the Human Protein Atlas. 76 major cell types were identified within 15 cell type clusters. Heatmaps are grouped according to cell type cluster to view relative expression. Heatmap units: TPM. All data available for download on CellPalmSeq.

Journal: Frontiers in Physiology

Article Title: CellPalmSeq: A curated RNAseq database of palmitoylating and de-palmitoylating enzyme expression in human cell types and laboratory cell lines

doi: 10.3389/fphys.2023.1110550

Figure Lengend Snippet: Expression patterns of the ZDHHC enzymes in major human cell types. Heatmaps showing human single-cell RNAseq expression data for the ZDHHC enzymes, downloaded from the Human Protein Atlas. 76 major cell types were identified within 15 cell type clusters. Heatmaps are grouped according to cell type cluster to view relative expression. Heatmap units: TPM. All data available for download on CellPalmSeq.

Article Snippet: For Human Protein Atlas, normalized single-cell RNAseq data collated from 26 datasets ( www.proteinatlas.org/download/rna_single_cell_type.tsv.zip ) were directly downloaded from ( www.proteinatlas.org/about/download ) and data were extracted (nTPM) for the genes that regulate S -palmitoylation.

Techniques: Expressing

Expression patterns of the ZDHHC accessory proteins and depalmitoylating enzymes in major human cell types. Heatmaps showing human single-cell RNAseq expression data for the ZDHHC accessory proteins and depalmitoylating enzymes, downloaded from the Human Protein Atlas. 76 major cell types were identified within 15 cell type clusters. Heatmaps are grouped according to cell type cluster to view relative expression. Heatmap units: Transcripts per million (TPM). All data available for download on CellPalmSeq.

Journal: Frontiers in Physiology

Article Title: CellPalmSeq: A curated RNAseq database of palmitoylating and de-palmitoylating enzyme expression in human cell types and laboratory cell lines

doi: 10.3389/fphys.2023.1110550

Figure Lengend Snippet: Expression patterns of the ZDHHC accessory proteins and depalmitoylating enzymes in major human cell types. Heatmaps showing human single-cell RNAseq expression data for the ZDHHC accessory proteins and depalmitoylating enzymes, downloaded from the Human Protein Atlas. 76 major cell types were identified within 15 cell type clusters. Heatmaps are grouped according to cell type cluster to view relative expression. Heatmap units: Transcripts per million (TPM). All data available for download on CellPalmSeq.

Article Snippet: For Human Protein Atlas, normalized single-cell RNAseq data collated from 26 datasets ( www.proteinatlas.org/download/rna_single_cell_type.tsv.zip ) were directly downloaded from ( www.proteinatlas.org/about/download ) and data were extracted (nTPM) for the genes that regulate S -palmitoylation.

Techniques: Expressing

Expression of the genes that regulate palmitoylation from CCLE cancer cell lines. (A) Heatmap showing RNAseq expression data for the genes that regulate S -palmitoylation, downloaded from CCLE and averaged according to ‘Primary Disease’. Data are included from 1406 cell lines, averaged into 30 primary disease types. (B) Expression data for selected human cell lines that are commonly used for basic research. All data were extracted from the CCLE dataset, except the H9 cell line which was found only in the CMP dataset, and HEK-293 that was found in the HPA cell line dataset. Heatmap units: Transcripts per million (TPM). All data available for download on CellPalmSeq.

Journal: Frontiers in Physiology

Article Title: CellPalmSeq: A curated RNAseq database of palmitoylating and de-palmitoylating enzyme expression in human cell types and laboratory cell lines

doi: 10.3389/fphys.2023.1110550

Figure Lengend Snippet: Expression of the genes that regulate palmitoylation from CCLE cancer cell lines. (A) Heatmap showing RNAseq expression data for the genes that regulate S -palmitoylation, downloaded from CCLE and averaged according to ‘Primary Disease’. Data are included from 1406 cell lines, averaged into 30 primary disease types. (B) Expression data for selected human cell lines that are commonly used for basic research. All data were extracted from the CCLE dataset, except the H9 cell line which was found only in the CMP dataset, and HEK-293 that was found in the HPA cell line dataset. Heatmap units: Transcripts per million (TPM). All data available for download on CellPalmSeq.

Article Snippet: For Human Protein Atlas, normalized single-cell RNAseq data collated from 26 datasets ( www.proteinatlas.org/download/rna_single_cell_type.tsv.zip ) were directly downloaded from ( www.proteinatlas.org/about/download ) and data were extracted (nTPM) for the genes that regulate S -palmitoylation.

Techniques: Expressing

Correlation between RNA and protein expression using cancer cell line data. (A) Diagram illustrating how expression values were converted to z-scores and then correlation values calculated, using CCLE RNAseq and proteomic data. (B) Graph of Spearman correlation values calculated from expression z-scores across available CCLE cell lines, for RNA vs. protein. Number on each bar represents the number of cell lines (in which both RNA and protein were detected) used for each correlation calculation. (C) Heatmap showing enrichments of both RNA and protein across cancer type clusters for selected palmitoylating and depalmitoylating enzymes. Heatmap units: z-score.

Journal: Frontiers in Physiology

Article Title: CellPalmSeq: A curated RNAseq database of palmitoylating and de-palmitoylating enzyme expression in human cell types and laboratory cell lines

doi: 10.3389/fphys.2023.1110550

Figure Lengend Snippet: Correlation between RNA and protein expression using cancer cell line data. (A) Diagram illustrating how expression values were converted to z-scores and then correlation values calculated, using CCLE RNAseq and proteomic data. (B) Graph of Spearman correlation values calculated from expression z-scores across available CCLE cell lines, for RNA vs. protein. Number on each bar represents the number of cell lines (in which both RNA and protein were detected) used for each correlation calculation. (C) Heatmap showing enrichments of both RNA and protein across cancer type clusters for selected palmitoylating and depalmitoylating enzymes. Heatmap units: z-score.

Article Snippet: For Human Protein Atlas, normalized single-cell RNAseq data collated from 26 datasets ( www.proteinatlas.org/download/rna_single_cell_type.tsv.zip ) were directly downloaded from ( www.proteinatlas.org/about/download ) and data were extracted (nTPM) for the genes that regulate S -palmitoylation.

Techniques: Expressing

Expression of the genes that regulate S-palmitoylation in selected commonly used non-human cell lines. (A) Heatmap of RNAseq expression data for the genes that regulate S -palmitoylation in control/untreated samples from mouse NIH/3T3 cell line, downloaded from selected datasets on GEO (labelled with GEO accession numbers). N = 1–3 control samples per dataset. Units = Transcripts per million (TPM). (B) As A but for Rat PC12 cell line samples. N = 3 samples per cell dataset. (C) As A but for dog MDCK cell line samples. N = 3–12 samples per dataset.

Journal: Frontiers in Physiology

Article Title: CellPalmSeq: A curated RNAseq database of palmitoylating and de-palmitoylating enzyme expression in human cell types and laboratory cell lines

doi: 10.3389/fphys.2023.1110550

Figure Lengend Snippet: Expression of the genes that regulate S-palmitoylation in selected commonly used non-human cell lines. (A) Heatmap of RNAseq expression data for the genes that regulate S -palmitoylation in control/untreated samples from mouse NIH/3T3 cell line, downloaded from selected datasets on GEO (labelled with GEO accession numbers). N = 1–3 control samples per dataset. Units = Transcripts per million (TPM). (B) As A but for Rat PC12 cell line samples. N = 3 samples per cell dataset. (C) As A but for dog MDCK cell line samples. N = 3–12 samples per dataset.

Article Snippet: For Human Protein Atlas, normalized single-cell RNAseq data collated from 26 datasets ( www.proteinatlas.org/download/rna_single_cell_type.tsv.zip ) were directly downloaded from ( www.proteinatlas.org/about/download ) and data were extracted (nTPM) for the genes that regulate S -palmitoylation.

Techniques: Expressing, Control

Neuroendocrine SCLC express fewer factors that are inhibitory to NK cells. ( A ) Immunofluorescent staining of NCAM1 and MHC-class I proteins in SCLC tissues of a tumor microarray (NCAM1 = red, MHC-class I = white, DAPI = blue). Images representing tumor cases that are POS for NCAM1 and NEG for MHC-class I; double POS for NCAM1 and MHC-class I; NCAM1 NEG/MHC-class I POS; and double NEG for NCAM1 and MHC-class I. ( B ) Quantification of 80 SCLC tumors scored based on positivity for NCAM1 and MHC-class I expression. ( C ) Immunofluorescent staining of ASCL1, NEUROD1, POU2F3, YAP1, and MHC-class I in SCLC tissues of a tumor microarray (ASCL1 = turquoise, NEUROD1 = green, POU2F3 = pink, YAP1 = red, MHC-class I = white, DAPI = blue). Images representing a tumor classified as each of the four subtypes of SCLC. ( D ) Quantification of 79 evaluable tumors based on the predominant transcription factor expression and MHC-class I within each case. ( E ) SCLC tissues of a tumor microarray were analyzed by RNA in situ hybridization for the presence of NK cells. Representative image depicting RNA in situ hybridization staining of CD49b mRNA (pink) and NCR3 mRNA (NKp30, green). ( F ) Quantification displays the number of NK cells per 1000 DAPI POS cells within a standardized ROI; analysis completed on ASCL1 POS MHC-class I NEG , ASCL1 POS MHC-class I POS , NEUROD1 POS , POU2F3 POS (n = 5 tissues each), and YAP1 POS (n = 2 tissues). *p < 0.05 by one-way ANOVA with Tukey’s multiple comparison post-test. ( G ) Heatmap expression of ASCL1, NEUROD1, POU2F3, YAP1, and genes relevant to NK activity in 88 SCLC tumor biopsies obtained from 62 patients with metastatic SCLC previously analyzed by RNAseq analysis (NE = grey, non-NE = black, ASCL1 = purple, NEUROD1 = orange, POU2F3 = blue, YAP1 = green). ( H ) Heatmap of expression of selected NK activating and NK inhibitory ligand genes as determined by quantitative reverse transcription PCR across a panel of SCLC cell lines (NE = neuroendocrine; non-NE = non-neuroendocrine). Values illustrated correspond to log 2 -transformed gene expression relative to the control gene GAPDH in each cell line. ( I ) Neuroendocrine (DMS79, H69) and non-neuroendocrine (DMS114, H841) SCLC cells were assayed for susceptibility to NK cells at an E:Tratio of 10:1 in a 24-hour assay. **** p < 0.0001 comparing NE versus non-NE by unpaired t test. Data illustrated are representative of n = 8 healthy NK donors. #, number; ANOVA, analysis of variance; DAPI, ′,6-diamidino-2-phenylindole; E:T, effector-to-target; NE, neuroendocrine; NEG, negative; NK, natural killer; PCR, polymerase chain reaction; POS, positive; ROI, region of interest.

Journal: Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer

Article Title: An Interleukin-15 Superagonist Enables Antitumor Efficacy of Natural Killer Cells Against All Molecular Variants of SCLC

doi: 10.1016/j.jtho.2022.11.008

Figure Lengend Snippet: Neuroendocrine SCLC express fewer factors that are inhibitory to NK cells. ( A ) Immunofluorescent staining of NCAM1 and MHC-class I proteins in SCLC tissues of a tumor microarray (NCAM1 = red, MHC-class I = white, DAPI = blue). Images representing tumor cases that are POS for NCAM1 and NEG for MHC-class I; double POS for NCAM1 and MHC-class I; NCAM1 NEG/MHC-class I POS; and double NEG for NCAM1 and MHC-class I. ( B ) Quantification of 80 SCLC tumors scored based on positivity for NCAM1 and MHC-class I expression. ( C ) Immunofluorescent staining of ASCL1, NEUROD1, POU2F3, YAP1, and MHC-class I in SCLC tissues of a tumor microarray (ASCL1 = turquoise, NEUROD1 = green, POU2F3 = pink, YAP1 = red, MHC-class I = white, DAPI = blue). Images representing a tumor classified as each of the four subtypes of SCLC. ( D ) Quantification of 79 evaluable tumors based on the predominant transcription factor expression and MHC-class I within each case. ( E ) SCLC tissues of a tumor microarray were analyzed by RNA in situ hybridization for the presence of NK cells. Representative image depicting RNA in situ hybridization staining of CD49b mRNA (pink) and NCR3 mRNA (NKp30, green). ( F ) Quantification displays the number of NK cells per 1000 DAPI POS cells within a standardized ROI; analysis completed on ASCL1 POS MHC-class I NEG , ASCL1 POS MHC-class I POS , NEUROD1 POS , POU2F3 POS (n = 5 tissues each), and YAP1 POS (n = 2 tissues). *p < 0.05 by one-way ANOVA with Tukey’s multiple comparison post-test. ( G ) Heatmap expression of ASCL1, NEUROD1, POU2F3, YAP1, and genes relevant to NK activity in 88 SCLC tumor biopsies obtained from 62 patients with metastatic SCLC previously analyzed by RNAseq analysis (NE = grey, non-NE = black, ASCL1 = purple, NEUROD1 = orange, POU2F3 = blue, YAP1 = green). ( H ) Heatmap of expression of selected NK activating and NK inhibitory ligand genes as determined by quantitative reverse transcription PCR across a panel of SCLC cell lines (NE = neuroendocrine; non-NE = non-neuroendocrine). Values illustrated correspond to log 2 -transformed gene expression relative to the control gene GAPDH in each cell line. ( I ) Neuroendocrine (DMS79, H69) and non-neuroendocrine (DMS114, H841) SCLC cells were assayed for susceptibility to NK cells at an E:Tratio of 10:1 in a 24-hour assay. **** p < 0.0001 comparing NE versus non-NE by unpaired t test. Data illustrated are representative of n = 8 healthy NK donors. #, number; ANOVA, analysis of variance; DAPI, ′,6-diamidino-2-phenylindole; E:T, effector-to-target; NE, neuroendocrine; NEG, negative; NK, natural killer; PCR, polymerase chain reaction; POS, positive; ROI, region of interest.

Article Snippet: Normalized RNAseq data from 88 biopsies from a range of metastatic sites obtained from 62 patients with SCLC available from a previously published report were analyzed on Partek for expression of selected genes relevant to NK activity, including ligands for NK activating and NK inhibitory receptors ( MICA , MICB , ULBP1–3 , RAET1E , RAET1G , RAET1L , NCR3LG1 , PVR , ICAM1 , HLA-A , HLA-B , HLA-C , HLA-E ) and a 20-gene signature of NK infiltration previously reported.

Techniques: Staining, Microarray, Expressing, RNA In Situ Hybridization, Comparison, Activity Assay, Reverse Transcription, Transformation Assay, Gene Expression, Control, Polymerase Chain Reaction

A heatmap of gene expression of adaptive immune resistance markers in PDAC patients from TCGA (n=152). Please also see Supplementary Fig. S2, Supplementary Table S1). Genes included in the heatmap are PD-L1 (CD274), IDO1, CTLA4, LAG3, CD276 (B7-H3), V-set domain containing T-cell activation inhibitor 1 (VTCN1; also known as B7-H4), CD70, Hepatitis A virus cellular receptor 2 (HAVCR2; also known as T-cell immunoglobulin and mucin-domain containing-3 (TIM-3)), CD40, CD47, tumor necrosis factor receptor superfamily member 18 (TNFRSF18I; also known as glucocorticoid-induced TNFR-related protein (GITR)), TIGIT, or LIGHT (also known as tumor necrosis factor superfamily member 14 (TNFSF14)). Each column is a sample.

Journal: Cancer immunology research

Article Title: Programmed cell death ligand-1 (PD-L1) and CD8 expression profiling identify an immunologic subtype of pancreatic ductal adenocarcinomas with favorable survival

doi: 10.1158/2326-6066.CIR-18-0822

Figure Lengend Snippet: A heatmap of gene expression of adaptive immune resistance markers in PDAC patients from TCGA (n=152). Please also see Supplementary Fig. S2, Supplementary Table S1). Genes included in the heatmap are PD-L1 (CD274), IDO1, CTLA4, LAG3, CD276 (B7-H3), V-set domain containing T-cell activation inhibitor 1 (VTCN1; also known as B7-H4), CD70, Hepatitis A virus cellular receptor 2 (HAVCR2; also known as T-cell immunoglobulin and mucin-domain containing-3 (TIM-3)), CD40, CD47, tumor necrosis factor receptor superfamily member 18 (TNFRSF18I; also known as glucocorticoid-induced TNFR-related protein (GITR)), TIGIT, or LIGHT (also known as tumor necrosis factor superfamily member 14 (TNFSF14)). Each column is a sample.

Article Snippet: TCGA data RNA sequencing (RNAseq) data Level 3 RSEM normalized data for 152 pancreatic adenocarcinoma (PAAD) patients ( 20 ) from TCGA were accessed from the Broad Institute TCGA GDAC Firehose ( https://ezid.cdlib.org/id/doi:10.7908/C11G0KM9 ) and log2-transformed.

Techniques: Gene Expression, Activation Assay, Virus