mabs lag 3 Search Results


94
Bio-Techne corporation lag3
Expression of IC by CD3 + TILs from CRC tumors according to the microsatellite status. For each figure, data were analyzed according to the MSS/MSI status, with MSS tumors shown in pale green and MSI tumors in dark blue. ( A ) Representative histograms showing the expression of PD-1, TIGIT, Tim-3, <t>Lag3</t> and NKG2A on CD3 + TILs from an MSS patient (upper panels) or from an MSI patient (lower panels). Results were expressed as positive cells and median fluorescence intensity (MFI). Isotypic controls are overlaid in grey. ( B ) Frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test (* p < 0.05; ** p < 0.01). ( C ) Pairwise frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3). ( D ) Expression level (MFI, scale in log2) of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on positive IC CD3 + TILs (n = 32, cohorts 2 and 3); Mann–Whitney test (* p < 0.05). ( E ) Principal component analysis of tumors from cohorts 2 and 3 (n = 32) based on the frequency and MFI of the 5 ICs on CD3 + TILs. ( F ) Proportion of CD4 + and CD8 + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test.
Lag3, supplied by Bio-Techne corporation, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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90
MacroGenics inc mg14.99 (macrogenics, anti-lag-3 mab)
Expression of IC by CD3 + TILs from CRC tumors according to the microsatellite status. For each figure, data were analyzed according to the MSS/MSI status, with MSS tumors shown in pale green and MSI tumors in dark blue. ( A ) Representative histograms showing the expression of PD-1, TIGIT, Tim-3, <t>Lag3</t> and NKG2A on CD3 + TILs from an MSS patient (upper panels) or from an MSI patient (lower panels). Results were expressed as positive cells and median fluorescence intensity (MFI). Isotypic controls are overlaid in grey. ( B ) Frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test (* p < 0.05; ** p < 0.01). ( C ) Pairwise frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3). ( D ) Expression level (MFI, scale in log2) of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on positive IC CD3 + TILs (n = 32, cohorts 2 and 3); Mann–Whitney test (* p < 0.05). ( E ) Principal component analysis of tumors from cohorts 2 and 3 (n = 32) based on the frequency and MFI of the 5 ICs on CD3 + TILs. ( F ) Proportion of CD4 + and CD8 + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test.
Mg14.99 (Macrogenics, Anti Lag 3 Mab), supplied by MacroGenics inc, 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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90
LabCorp monoclonal lag-3 antibody 17b4
Expression of IC by CD3 + TILs from CRC tumors according to the microsatellite status. For each figure, data were analyzed according to the MSS/MSI status, with MSS tumors shown in pale green and MSI tumors in dark blue. ( A ) Representative histograms showing the expression of PD-1, TIGIT, Tim-3, <t>Lag3</t> and NKG2A on CD3 + TILs from an MSS patient (upper panels) or from an MSI patient (lower panels). Results were expressed as positive cells and median fluorescence intensity (MFI). Isotypic controls are overlaid in grey. ( B ) Frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test (* p < 0.05; ** p < 0.01). ( C ) Pairwise frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3). ( D ) Expression level (MFI, scale in log2) of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on positive IC CD3 + TILs (n = 32, cohorts 2 and 3); Mann–Whitney test (* p < 0.05). ( E ) Principal component analysis of tumors from cohorts 2 and 3 (n = 32) based on the frequency and MFI of the 5 ICs on CD3 + TILs. ( F ) Proportion of CD4 + and CD8 + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test.
Monoclonal Lag 3 Antibody 17b4, supplied by LabCorp, 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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93
ProSci Incorporated monoclonal antibody mab
Expression of IC by CD3 + TILs from CRC tumors according to the microsatellite status. For each figure, data were analyzed according to the MSS/MSI status, with MSS tumors shown in pale green and MSI tumors in dark blue. ( A ) Representative histograms showing the expression of PD-1, TIGIT, Tim-3, <t>Lag3</t> and NKG2A on CD3 + TILs from an MSS patient (upper panels) or from an MSI patient (lower panels). Results were expressed as positive cells and median fluorescence intensity (MFI). Isotypic controls are overlaid in grey. ( B ) Frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test (* p < 0.05; ** p < 0.01). ( C ) Pairwise frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3). ( D ) Expression level (MFI, scale in log2) of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on positive IC CD3 + TILs (n = 32, cohorts 2 and 3); Mann–Whitney test (* p < 0.05). ( E ) Principal component analysis of tumors from cohorts 2 and 3 (n = 32) based on the frequency and MFI of the 5 ICs on CD3 + TILs. ( F ) Proportion of CD4 + and CD8 + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test.
Monoclonal Antibody Mab, supplied by ProSci Incorporated, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 93 stars, based on 1 article reviews
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90
Abyntek Biopharma SL anti-lag3 mab
( A ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / <t>LAG3</t> expression and lymphoid infiltrates in a total number of 12159 samples distributed on TCGA cancers. ( B ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and non-lymphoid infiltrates in a total number of 12159 samples distributed on TCGA cancers.
Anti Lag3 Mab, supplied by Abyntek Biopharma SL, 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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Danaher Inc anti beta iii tubulin βiii
High glucose-induced SC-derived exosomes inhibited the neurite outgrowth of NG108-15 cells in high glucose (A) Expression of AKT1, DNMT3A, and GAP43 in NG108-15 was detected by PCR, and AKT signaling pathway and neurite outgrowth-related factors (DNMT3A and GAP43) were inhibited in NG108-15 cells treated with H-EXO compared to L-EXO (n = 10 samples; t-test: ∗∗∗p < 0.001 versus the L-EXO group). (B and C) Western blot (B) was used to detect the protein expression of p -AKT, t-AKT, DNMT3A, and GAP43 in NG108-15 cells, the results had the same trend as the PCR results. (C) Gray value statistics of Western blot (n = 4 samples, nonparametric tests: ∗p < 0.05 of p -AKT/AKT, Bcl2/Bax and C-cas3/GAPDH versus the L-EXO group). (D and E) Immunocytochemistry staining (D) of <t>beta</t> <t>III</t> <t>Tubulin</t> (red) to observe neurite outgrowth, H-EXO significantly reduced neurite outgrowth in NG108-15 cells compared to L-EXO. Scale bar: 25 μm. (E) Neurite length quantification (n = 10 fields of view per group, t-test: ∗∗∗p < 0.001 versus the L-EXO group). For the above, data are represented as mean ± SD.
Anti Beta Iii Tubulin βiii, supplied by Danaher Inc, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Average 99 stars, based on 1 article reviews
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96
Cell Signaling Technology Inc anti lag3 rabbit polyclonal antibody
Obesity was associated with repression of immune checkpoints. ( A ) The expression of various immune checkpoints in obesity and normal groups. ( B ) The expression of <t>LAG3</t> and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. ( C ) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. ( D ) The correlation matrix of each immune checkpoint in obesity and normal group. ( * p <0.05, ** p <0.01).
Anti Lag3 Rabbit Polyclonal Antibody, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mabs+lag+3/PD-1+XP+Rabbit+mAb/pmc07762486-236-18-25
Average 96 stars, based on 1 article reviews
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90
Enzo Biochem anti-lag-3 mab (17b4
Obesity was associated with repression of immune checkpoints. ( A ) The expression of various immune checkpoints in obesity and normal groups. ( B ) The expression of <t>LAG3</t> and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. ( C ) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. ( D ) The correlation matrix of each immune checkpoint in obesity and normal group. ( * p <0.05, ** p <0.01).
Anti Lag 3 Mab (17b4, supplied by Enzo Biochem, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mabs+lag+3/anti+lag3+antibody+17b4/pm17785792-49-20-24
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86
Bristol Myers anti lag 3 monoclonal antibody called bms
Obesity was associated with repression of immune checkpoints. ( A ) The expression of various immune checkpoints in obesity and normal groups. ( B ) The expression of <t>LAG3</t> and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. ( C ) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. ( D ) The correlation matrix of each immune checkpoint in obesity and normal group. ( * p <0.05, ** p <0.01).
Anti Lag 3 Monoclonal Antibody Called Bms, supplied by Bristol Myers, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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95
Cell Signaling Technology Inc h lag 3
Obesity was associated with repression of immune checkpoints. ( A ) The expression of various immune checkpoints in obesity and normal groups. ( B ) The expression of <t>LAG3</t> and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. ( C ) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. ( D ) The correlation matrix of each immune checkpoint in obesity and normal group. ( * p <0.05, ** p <0.01).
H Lag 3, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mabs+lag+3/LAG3+XP+Rabbit+mAb/pmc11196727-263-62-65
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92
Cell Signaling Technology Inc rabbit anti lag3 igg monoclonal antibody d2g40
Obesity was associated with repression of immune checkpoints. ( A ) The expression of various immune checkpoints in obesity and normal groups. ( B ) The expression of <t>LAG3</t> and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. ( C ) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. ( D ) The correlation matrix of each immune checkpoint in obesity and normal group. ( * p <0.05, ** p <0.01).
Rabbit Anti Lag3 Igg Monoclonal Antibody D2g40, supplied by Cell Signaling Technology Inc, used in various techniques. Bioz Stars score: 92/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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93
Proteintech anti lag3 monoclonal antibody
Single-gene analysis of <t>LAG3</t> in CD8 + T cell-associated genes. The expression and correlation with CD8 + T cells for LAG3 ( A ), DUSP4 ( B ), and FXYD2 ( C ) in the TCGA–KIRC cohort. Correlation of LAG3 with tumor mutation burden ( D ) and responsiveness to immune checkpoint inhibitors ( E ). Correlation of DUSP4 with tumor mutation burden ( F ) and responsiveness to immune checkpoint inhibitors ( G ). IC 50 of sunitinib ( H ) and sorafenib ( I ) in different LAG3 expression subgroups. ( J ) LAG3 stemness score. ( K ) Relevance of LAG3 to immune-related genes
Anti Lag3 Monoclonal Antibody, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/mabs+lag+3/LAG-3+Antibody/pmc10825992-77-24-34
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Image Search Results


Expression of IC by CD3 + TILs from CRC tumors according to the microsatellite status. For each figure, data were analyzed according to the MSS/MSI status, with MSS tumors shown in pale green and MSI tumors in dark blue. ( A ) Representative histograms showing the expression of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on CD3 + TILs from an MSS patient (upper panels) or from an MSI patient (lower panels). Results were expressed as positive cells and median fluorescence intensity (MFI). Isotypic controls are overlaid in grey. ( B ) Frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test (* p < 0.05; ** p < 0.01). ( C ) Pairwise frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3). ( D ) Expression level (MFI, scale in log2) of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on positive IC CD3 + TILs (n = 32, cohorts 2 and 3); Mann–Whitney test (* p < 0.05). ( E ) Principal component analysis of tumors from cohorts 2 and 3 (n = 32) based on the frequency and MFI of the 5 ICs on CD3 + TILs. ( F ) Proportion of CD4 + and CD8 + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test.

Journal: Cancers

Article Title: Defining the Immune Checkpoint Landscape in Human Colorectal Cancer Highlights the Relevance of the TIGIT/CD155 Axis for Optimizing Immunotherapy

doi: 10.3390/cancers14174261

Figure Lengend Snippet: Expression of IC by CD3 + TILs from CRC tumors according to the microsatellite status. For each figure, data were analyzed according to the MSS/MSI status, with MSS tumors shown in pale green and MSI tumors in dark blue. ( A ) Representative histograms showing the expression of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on CD3 + TILs from an MSS patient (upper panels) or from an MSI patient (lower panels). Results were expressed as positive cells and median fluorescence intensity (MFI). Isotypic controls are overlaid in grey. ( B ) Frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test (* p < 0.05; ** p < 0.01). ( C ) Pairwise frequency of PD-1 + , TIGIT + , Tim-3 + , Lag3 + and NKG2A + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3). ( D ) Expression level (MFI, scale in log2) of PD-1, TIGIT, Tim-3, Lag3 and NKG2A on positive IC CD3 + TILs (n = 32, cohorts 2 and 3); Mann–Whitney test (* p < 0.05). ( E ) Principal component analysis of tumors from cohorts 2 and 3 (n = 32) based on the frequency and MFI of the 5 ICs on CD3 + TILs. ( F ) Proportion of CD4 + and CD8 + cells among CD3 + TILs (n = 40, cohorts 1, 2 and 3); Mann–Whitney test.

Article Snippet: The following primary antibodies were used: CD3 (Agilent Technologies, polyclonal rabbit anti-human, RRID:AB_2335677), CD8 (Agilent Technologies, monoclonal mouse anti-human clone C8/144B, RRID:AB_2075537), PD-1 (Abcam, Cambridge, UK, monoclonal mouse anti-human clone NAT105, RRID:AB_881954), TIGIT (Cell Signaling Technology, Danvers, MA, USA; monoclonal rabbit anti-human clone ESY1W, RRID:AB_2922806), Tim-3 (Bio-Techne, Minneaoplis, MN, USA, polyclonal goat anti-human, RRID:AB_355235), Lag3 (Novus, Bio-Techne, monoclonal mouse anti-human clone 17B4, RRID:AB_11162489), CD94 (Diaclone, Besançon, France; monoclonal mouse anti-human clone B-D49, RRID:AB_2922808), PD-L1 (Programmed death-ligand 1) (Cell Signaling Technology, monoclonal rabbit anti-human clone E1L3N, RRID:AB_2687655), CD155 (Cell Signaling Technology, monoclonal mouse anti-human clone D8A5G, RRID:AB_2799970), galectin-9 (Abcam, polyclonal rabbit anti-human, RRID:AB_1268942), HLA-DR (Abcam, monoclonal mouse anti-human clone SPM289, RRID:AB_444051) and HLA-E (Bio-Rad, Marnes-la-Coquette, France; monoclonal mouse anti-human clone MEM-E/02, RRID:AB_324025).

Techniques: Expressing, Fluorescence, MANN-WHITNEY

Identification of 14 CD8 + TIL clusters based on differential expression of ICs. ( A ) FlowSOM tree of CD8 + TILs from cohort 2 tumors (n = 20). The background coloring represents meta-clustering and the legends of the star plot and meta-clustering are shown on the right side. ( B ) Heatmap of the MFI of the PD-1, TIGIT, Tim-3, Lag3 and NKG2A markers expressed, or not expressed, by the 14 clusters identified in the CD8 + TIL population generated from cohort 2 tumors (n = 20). ( C ) Cell frequency in each CD4 + TIL cluster generated from cohort 2 tumors (n = 20). ( D ) Cell frequency in each CD4 + TIL cluster generated from cohort 2 and 3 tumors (n = 32) according to the MSS/MSI status (pale green and dark blue, respectively). The clusters of the two cohorts were merged and the cluster numbering from cohort 2 was retained; Mann–Whitney tests. ( E ) Principal component analysis of tumors from cohorts 2 and 3 based on cell frequencies in each generated CD8 + TIL cluster, with MSS tumors are in pale green triangles and MSI tumors in dark blue circles. Ellipses were drawn to highlight two new groups of colorectal tumors: the IC high group (in dark blue) and the IC low group (in pale green).

Journal: Cancers

Article Title: Defining the Immune Checkpoint Landscape in Human Colorectal Cancer Highlights the Relevance of the TIGIT/CD155 Axis for Optimizing Immunotherapy

doi: 10.3390/cancers14174261

Figure Lengend Snippet: Identification of 14 CD8 + TIL clusters based on differential expression of ICs. ( A ) FlowSOM tree of CD8 + TILs from cohort 2 tumors (n = 20). The background coloring represents meta-clustering and the legends of the star plot and meta-clustering are shown on the right side. ( B ) Heatmap of the MFI of the PD-1, TIGIT, Tim-3, Lag3 and NKG2A markers expressed, or not expressed, by the 14 clusters identified in the CD8 + TIL population generated from cohort 2 tumors (n = 20). ( C ) Cell frequency in each CD4 + TIL cluster generated from cohort 2 tumors (n = 20). ( D ) Cell frequency in each CD4 + TIL cluster generated from cohort 2 and 3 tumors (n = 32) according to the MSS/MSI status (pale green and dark blue, respectively). The clusters of the two cohorts were merged and the cluster numbering from cohort 2 was retained; Mann–Whitney tests. ( E ) Principal component analysis of tumors from cohorts 2 and 3 based on cell frequencies in each generated CD8 + TIL cluster, with MSS tumors are in pale green triangles and MSI tumors in dark blue circles. Ellipses were drawn to highlight two new groups of colorectal tumors: the IC high group (in dark blue) and the IC low group (in pale green).

Article Snippet: The following primary antibodies were used: CD3 (Agilent Technologies, polyclonal rabbit anti-human, RRID:AB_2335677), CD8 (Agilent Technologies, monoclonal mouse anti-human clone C8/144B, RRID:AB_2075537), PD-1 (Abcam, Cambridge, UK, monoclonal mouse anti-human clone NAT105, RRID:AB_881954), TIGIT (Cell Signaling Technology, Danvers, MA, USA; monoclonal rabbit anti-human clone ESY1W, RRID:AB_2922806), Tim-3 (Bio-Techne, Minneaoplis, MN, USA, polyclonal goat anti-human, RRID:AB_355235), Lag3 (Novus, Bio-Techne, monoclonal mouse anti-human clone 17B4, RRID:AB_11162489), CD94 (Diaclone, Besançon, France; monoclonal mouse anti-human clone B-D49, RRID:AB_2922808), PD-L1 (Programmed death-ligand 1) (Cell Signaling Technology, monoclonal rabbit anti-human clone E1L3N, RRID:AB_2687655), CD155 (Cell Signaling Technology, monoclonal mouse anti-human clone D8A5G, RRID:AB_2799970), galectin-9 (Abcam, polyclonal rabbit anti-human, RRID:AB_1268942), HLA-DR (Abcam, monoclonal mouse anti-human clone SPM289, RRID:AB_444051) and HLA-E (Bio-Rad, Marnes-la-Coquette, France; monoclonal mouse anti-human clone MEM-E/02, RRID:AB_324025).

Techniques: Expressing, Generated, MANN-WHITNEY

( A ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and lymphoid infiltrates in a total number of 12159 samples distributed on TCGA cancers. ( B ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and non-lymphoid infiltrates in a total number of 12159 samples distributed on TCGA cancers.

Journal: EMBO Molecular Medicine

Article Title: PD-1/LAG-3 co-signaling profiling uncovers CBL ubiquitin ligases as key immunotherapy targets

doi: 10.1038/s44321-024-00098-y

Figure Lengend Snippet: ( A ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and lymphoid infiltrates in a total number of 12159 samples distributed on TCGA cancers. ( B ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and non-lymphoid infiltrates in a total number of 12159 samples distributed on TCGA cancers.

Article Snippet: Then, 100 µg of anti-PD-1 mAb (RPMI-14, BioXCell), 100 µg of anti-LAG3 mAb (C9B7W, Abyntek) were administered intraperitoneally (i.p) following the scheme described in the figures.

Techniques: Expressing

( A ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 and LAG3 co-expression in the tumor-immune infiltration estimation of a total number of 12159 samples distributed on the indicated TCGA cancers. ( B ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and selected immune genes including IFN, IL, TCR signaling, CD28 co-stimulatory family and MHCII antigen presentation in the tumor-immune infiltration estimation of a total number of 12159 samples distributed on the indicated TCGA cancers. Detailed information and statistical significance for each specific gene associated to the PDCD1 / LAG3 gene signature is shown in Dataset . ( C ) Predicted network describing the potential molecular interactions for the T-cell exhaustion pathway signaling and TCR downregulation associated to both PD-1 and LAG-3 co-upregulation. QIAGEN IPA algorithms were applied on data from curated publicly available datasets of RNA-seq, small RNA-seq, metabolomics, proteomics, microarrays including miRNA and SNP, and small-scale experiments (accessed on 2024). The specific legends to inter-nodal relationships are described in IPA ( Ingenuity Pathway Analysis | QIAGEN Digital Insights ). Key nodes are shown, and inter-nodal lines represent potential functional relationships between nodes. In red, upregulated input molecules as indicated (PD-1 and LAG-3). Blue lines, predicted inhibition; orange lines, predicted activation; grey indicates a predicted relationship with a non-predicted effect, and yellow lines, predicted relationship findings inconsistent with the state of the downstream molecule. ( D ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and a selection of genes regulating cell cycle, gene expression and signaling in the tumor-immune infiltration estimation of a total number of 12,159 samples distributed on the indicated TCGA cancers. Detailed information and statistical significance for each specific gene associated to the PDCD1 / LAG3 gene signature is shown in Dataset . .

Journal: EMBO Molecular Medicine

Article Title: PD-1/LAG-3 co-signaling profiling uncovers CBL ubiquitin ligases as key immunotherapy targets

doi: 10.1038/s44321-024-00098-y

Figure Lengend Snippet: ( A ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 and LAG3 co-expression in the tumor-immune infiltration estimation of a total number of 12159 samples distributed on the indicated TCGA cancers. ( B ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and selected immune genes including IFN, IL, TCR signaling, CD28 co-stimulatory family and MHCII antigen presentation in the tumor-immune infiltration estimation of a total number of 12159 samples distributed on the indicated TCGA cancers. Detailed information and statistical significance for each specific gene associated to the PDCD1 / LAG3 gene signature is shown in Dataset . ( C ) Predicted network describing the potential molecular interactions for the T-cell exhaustion pathway signaling and TCR downregulation associated to both PD-1 and LAG-3 co-upregulation. QIAGEN IPA algorithms were applied on data from curated publicly available datasets of RNA-seq, small RNA-seq, metabolomics, proteomics, microarrays including miRNA and SNP, and small-scale experiments (accessed on 2024). The specific legends to inter-nodal relationships are described in IPA ( Ingenuity Pathway Analysis | QIAGEN Digital Insights ). Key nodes are shown, and inter-nodal lines represent potential functional relationships between nodes. In red, upregulated input molecules as indicated (PD-1 and LAG-3). Blue lines, predicted inhibition; orange lines, predicted activation; grey indicates a predicted relationship with a non-predicted effect, and yellow lines, predicted relationship findings inconsistent with the state of the downstream molecule. ( D ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and a selection of genes regulating cell cycle, gene expression and signaling in the tumor-immune infiltration estimation of a total number of 12,159 samples distributed on the indicated TCGA cancers. Detailed information and statistical significance for each specific gene associated to the PDCD1 / LAG3 gene signature is shown in Dataset . .

Article Snippet: Then, 100 µg of anti-PD-1 mAb (RPMI-14, BioXCell), 100 µg of anti-LAG3 mAb (C9B7W, Abyntek) were administered intraperitoneally (i.p) following the scheme described in the figures.

Techniques: Expressing, RNA Sequencing Assay, Functional Assay, Inhibition, Activation Assay, Selection

( A ) Identified enriched canonical pathways and upstream regulators for the upregulation of PD-1/LAG-3 and combinations. ( B ) Identified enriched molecular and cellular functions for the upregulation of PD-1/LAG-3 and combinations. ( C ) Identified enriched diseases and disorders for the upregulation of PD-1/LAG-3 and combinations. ( D ) Predicted regulatory interactomes and associated networks with the indicated PD-1 and LAG-3 signatures. Key nodes are shown, and inter-nodal lines represent functional relationships between nodes. In red, upregulated input molecules as indicated (PD-1 and LAG-3). In blue, downregulated input molecules as indicated (PD-1 and LAG-3). Blue lines, predicted inhibition; orange lines, predicted activation; grey indicates a predicted relationship with a non-predicted effect, and yellow lines, predicted relationship findings inconsistent with the state of the downstream molecule. ( E ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and a selection of genes regulating identified by IPA of a total number of 12159 samples distributed on the indicated TCGA cancers. Data information: For ( A – D ), QIAGEN IPA algorithms were used (accessed on 2024), applied on data from curated publicly available datasets of RNA-seq, small RNA-seq, metabolomics, proteomics, microarrays including miRNA and SNP, and small-scale experiments. IPA utilizes two scores for inference; P -values from a Fisher’s exact test to obtain an enrichment score, and a Z-score to assess the match of observed and predicted regulation patterns.

Journal: EMBO Molecular Medicine

Article Title: PD-1/LAG-3 co-signaling profiling uncovers CBL ubiquitin ligases as key immunotherapy targets

doi: 10.1038/s44321-024-00098-y

Figure Lengend Snippet: ( A ) Identified enriched canonical pathways and upstream regulators for the upregulation of PD-1/LAG-3 and combinations. ( B ) Identified enriched molecular and cellular functions for the upregulation of PD-1/LAG-3 and combinations. ( C ) Identified enriched diseases and disorders for the upregulation of PD-1/LAG-3 and combinations. ( D ) Predicted regulatory interactomes and associated networks with the indicated PD-1 and LAG-3 signatures. Key nodes are shown, and inter-nodal lines represent functional relationships between nodes. In red, upregulated input molecules as indicated (PD-1 and LAG-3). In blue, downregulated input molecules as indicated (PD-1 and LAG-3). Blue lines, predicted inhibition; orange lines, predicted activation; grey indicates a predicted relationship with a non-predicted effect, and yellow lines, predicted relationship findings inconsistent with the state of the downstream molecule. ( E ) Heatmap of partial purity-adjusted Spearman’s correlates calculated with TIMER 2.0. between PDCD1 / LAG3 expression and a selection of genes regulating identified by IPA of a total number of 12159 samples distributed on the indicated TCGA cancers. Data information: For ( A – D ), QIAGEN IPA algorithms were used (accessed on 2024), applied on data from curated publicly available datasets of RNA-seq, small RNA-seq, metabolomics, proteomics, microarrays including miRNA and SNP, and small-scale experiments. IPA utilizes two scores for inference; P -values from a Fisher’s exact test to obtain an enrichment score, and a Z-score to assess the match of observed and predicted regulation patterns.

Article Snippet: Then, 100 µg of anti-PD-1 mAb (RPMI-14, BioXCell), 100 µg of anti-LAG3 mAb (C9B7W, Abyntek) were administered intraperitoneally (i.p) following the scheme described in the figures.

Techniques: Functional Assay, Inhibition, Activation Assay, Expressing, Selection, RNA Sequencing Assay

( A ) Single-cell sequencing analysis of biopsies from non-small cell lung cancer (NSCLC) patients. Panels indicate the expression of PDCD1 , LAG3 and CBLB and CBLC analyzed from the single-cell lung cancer extended atlas (LuCA) (Salcher et al, ) repository as indicated. ( B ) Dot plot with the percentage of CD4 and CD8 T-cells that co-express PD-1 and LAG-3 after ex vivo activation, from healthy donors ( n = 8) and NSCLC patients ( n = 10). Statistical comparisons were performed by the Mann–Whitney test. Error bars correspond to ±SD ( C ) CBL-B expression by mean fluorescent intensities in CD4 and CD8 T-cells from a sample of non-responder NSCLC patients ( n = 4), activated ex vivo in the presence of the indicated treatments. Shown data from total CD4 and CD8 gated populations. Statistical comparisons were carried out by a two-way ANOVA to eliminate inter-patient variability followed by pair-wise Tukey tests. Box and whiskers with min to max values are plotted, computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest. ( D ) Same as ( C ) but for C-CBL expression. Box and whiskers with min to max values are plotted, computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest. ( E ) Percentage of proliferating CD4 T cells (left) and CD8 T cells (right) from a sample of high PD-1/LAG-3 co-expression patients before starting immunotherapy, activated ex vivo by A549-SC3 cells in the presence of the indicated antibodies. Statistical comparisons were carried out by a two-way ANOVA to eliminate inter-patient variability followed by pair-wise Tukey tests ( n = 5). Box and whiskers with min to max values are plotted, computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest. ( F ) Flow cytometry histograms of SATB1, Phospho SMAD 2/3, LCK and ZAP70 expression. Gates were established according to unstained controls in T-cells from a sample of non-responder NSCLC patients. Percentage of expression and Mean Fluorescence Intensity values are indicated. Data information: Statistical comparisons are shown in the graph as indicated in Methods. Briefly, for ( B ) statistical comparisons were performed by the Mann–Whitney test. For ( C – E ), statistical comparisons were carried out by a two-way ANOVA to eliminate inter-patient variability followed by pair-wise Tukey tests. Error bars correspond to ±SD. **, ***, ****, indicate P < 0.01, P < 0.001 and P < 0.0001 differences. .

Journal: EMBO Molecular Medicine

Article Title: PD-1/LAG-3 co-signaling profiling uncovers CBL ubiquitin ligases as key immunotherapy targets

doi: 10.1038/s44321-024-00098-y

Figure Lengend Snippet: ( A ) Single-cell sequencing analysis of biopsies from non-small cell lung cancer (NSCLC) patients. Panels indicate the expression of PDCD1 , LAG3 and CBLB and CBLC analyzed from the single-cell lung cancer extended atlas (LuCA) (Salcher et al, ) repository as indicated. ( B ) Dot plot with the percentage of CD4 and CD8 T-cells that co-express PD-1 and LAG-3 after ex vivo activation, from healthy donors ( n = 8) and NSCLC patients ( n = 10). Statistical comparisons were performed by the Mann–Whitney test. Error bars correspond to ±SD ( C ) CBL-B expression by mean fluorescent intensities in CD4 and CD8 T-cells from a sample of non-responder NSCLC patients ( n = 4), activated ex vivo in the presence of the indicated treatments. Shown data from total CD4 and CD8 gated populations. Statistical comparisons were carried out by a two-way ANOVA to eliminate inter-patient variability followed by pair-wise Tukey tests. Box and whiskers with min to max values are plotted, computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest. ( D ) Same as ( C ) but for C-CBL expression. Box and whiskers with min to max values are plotted, computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest. ( E ) Percentage of proliferating CD4 T cells (left) and CD8 T cells (right) from a sample of high PD-1/LAG-3 co-expression patients before starting immunotherapy, activated ex vivo by A549-SC3 cells in the presence of the indicated antibodies. Statistical comparisons were carried out by a two-way ANOVA to eliminate inter-patient variability followed by pair-wise Tukey tests ( n = 5). Box and whiskers with min to max values are plotted, computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest. ( F ) Flow cytometry histograms of SATB1, Phospho SMAD 2/3, LCK and ZAP70 expression. Gates were established according to unstained controls in T-cells from a sample of non-responder NSCLC patients. Percentage of expression and Mean Fluorescence Intensity values are indicated. Data information: Statistical comparisons are shown in the graph as indicated in Methods. Briefly, for ( B ) statistical comparisons were performed by the Mann–Whitney test. For ( C – E ), statistical comparisons were carried out by a two-way ANOVA to eliminate inter-patient variability followed by pair-wise Tukey tests. Error bars correspond to ±SD. **, ***, ****, indicate P < 0.01, P < 0.001 and P < 0.0001 differences. .

Article Snippet: Then, 100 µg of anti-PD-1 mAb (RPMI-14, BioXCell), 100 µg of anti-LAG3 mAb (C9B7W, Abyntek) were administered intraperitoneally (i.p) following the scheme described in the figures.

Techniques: Sequencing, Expressing, Ex Vivo, Activation Assay, MANN-WHITNEY, Flow Cytometry, Fluorescence

( A ) Real-Time Quantitative Cell Analysis (RTCA) of Lung adenocarcinoma (Lacun3) cells incubated for 70 h with growing concentrations of CBL-B inhibitor (CBL-Bi) as indicated. Error bars correspond to ±SD. Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests ( n = 3 independent cultures). ( B ) Mean tumor size following the indicated treatments (left). Tumor volumes 10 days after treatment initiation (right). Error bars correspond to ±SEM (left) and box and whiskers with min to max values (right), computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest ( n = 6 mice per group). Briefly, BALB/c female mice were randomly allocated and subcutaneously injected with 2 × 10 6 Lung adenocarcinoma (Lacun3) cells per animal. When tumor growth reached an average diameter of 3.5 mm (day 0), 100 µg of anti-PD-1 mAb and 100 µg of anti-LAG3 mAb were administered intraperitoneally (i.p) at days 0, 5 and 13. Control mice received the same volume of saline. Some groups of mice received 30 mg/kg of CBL-bi at days −1, 2, 4, 6, 8, 10 and 12. As negative control, the same volume of saline was injected. Mice were humanely sacrificed at day 14. Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. ( C ) Tumor growth of individual mice in the indicated treatment groups ( n = 6 mice per group). ( D ) Schematic design of the experiment. BALB/c female mice were randomly allocated and subcutaneously injected with 2 × 10 6 Lung adenocarcinoma (Lacun3) cells per animal. When tumor growth reached an average diameter of 3.5 mm (day 0), 100 µg of anti-PD-1 and 100 µg of anti-LAG3 were administered intraperitoneally at days 0, 5, 13, 16, 20, 25 and 29. Control mice received the same volume of saline. Some groups of mice received 10 mg/kg, 20 mg/kg and 30 mg/kg of CBL-Bi at days −1, 2, 4, 6, 8, 10, 12, 14, 16 and 18. As negative control, the same volume of saline was injected. The two perpendicular tumor diameters were measured every two days. Mice were humanely sacrificed when tumor size reached ~150–200 mm 2 , or when tumor ulceration or discomfort were observed. ( E ) Evolution of mean tumor size following the indicated treatments (left). Tumor volumes 14 days after treatment initiation (right). Error bars correspond to ±SEM (left) and box and whiskers with min to max values (right), computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest ( n = 6 mice per group). Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. ( F ) Kaplan–Meier survival plot of mice under the indicated treatments (percent). Statistical significance was tested with the Log-rank test. ( G ) Tumor growth of individual mice in the indicated treatment groups ( n = 6 mice per group). Data information: Statistical comparisons are shown in the graph as indicated in Methods. Briefly, for ( A , B , E ), statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. For ( F ), Survival was represented by Kaplan–Meier plots and analyzed by log-rank test. *, **, ****, indicate P < 0.05, P < 0.01 and P < 0.0001 differences. .

Journal: EMBO Molecular Medicine

Article Title: PD-1/LAG-3 co-signaling profiling uncovers CBL ubiquitin ligases as key immunotherapy targets

doi: 10.1038/s44321-024-00098-y

Figure Lengend Snippet: ( A ) Real-Time Quantitative Cell Analysis (RTCA) of Lung adenocarcinoma (Lacun3) cells incubated for 70 h with growing concentrations of CBL-B inhibitor (CBL-Bi) as indicated. Error bars correspond to ±SD. Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests ( n = 3 independent cultures). ( B ) Mean tumor size following the indicated treatments (left). Tumor volumes 10 days after treatment initiation (right). Error bars correspond to ±SEM (left) and box and whiskers with min to max values (right), computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest ( n = 6 mice per group). Briefly, BALB/c female mice were randomly allocated and subcutaneously injected with 2 × 10 6 Lung adenocarcinoma (Lacun3) cells per animal. When tumor growth reached an average diameter of 3.5 mm (day 0), 100 µg of anti-PD-1 mAb and 100 µg of anti-LAG3 mAb were administered intraperitoneally (i.p) at days 0, 5 and 13. Control mice received the same volume of saline. Some groups of mice received 30 mg/kg of CBL-bi at days −1, 2, 4, 6, 8, 10 and 12. As negative control, the same volume of saline was injected. Mice were humanely sacrificed at day 14. Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. ( C ) Tumor growth of individual mice in the indicated treatment groups ( n = 6 mice per group). ( D ) Schematic design of the experiment. BALB/c female mice were randomly allocated and subcutaneously injected with 2 × 10 6 Lung adenocarcinoma (Lacun3) cells per animal. When tumor growth reached an average diameter of 3.5 mm (day 0), 100 µg of anti-PD-1 and 100 µg of anti-LAG3 were administered intraperitoneally at days 0, 5, 13, 16, 20, 25 and 29. Control mice received the same volume of saline. Some groups of mice received 10 mg/kg, 20 mg/kg and 30 mg/kg of CBL-Bi at days −1, 2, 4, 6, 8, 10, 12, 14, 16 and 18. As negative control, the same volume of saline was injected. The two perpendicular tumor diameters were measured every two days. Mice were humanely sacrificed when tumor size reached ~150–200 mm 2 , or when tumor ulceration or discomfort were observed. ( E ) Evolution of mean tumor size following the indicated treatments (left). Tumor volumes 14 days after treatment initiation (right). Error bars correspond to ±SEM (left) and box and whiskers with min to max values (right), computing the minimum, maximum, median and quartiles. The box extends from the 25th to 75th percentiles. The whiskers go down to the smallest value and up to the largest ( n = 6 mice per group). Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. ( F ) Kaplan–Meier survival plot of mice under the indicated treatments (percent). Statistical significance was tested with the Log-rank test. ( G ) Tumor growth of individual mice in the indicated treatment groups ( n = 6 mice per group). Data information: Statistical comparisons are shown in the graph as indicated in Methods. Briefly, for ( A , B , E ), statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. For ( F ), Survival was represented by Kaplan–Meier plots and analyzed by log-rank test. *, **, ****, indicate P < 0.05, P < 0.01 and P < 0.0001 differences. .

Article Snippet: Then, 100 µg of anti-PD-1 mAb (RPMI-14, BioXCell), 100 µg of anti-LAG3 mAb (C9B7W, Abyntek) were administered intraperitoneally (i.p) following the scheme described in the figures.

Techniques: Cell Analysis, Incubation, Injection, Control, Saline, Negative Control

( A ) Schematic design of the experiment. BALB/c female mice were randomly allocated and subcutaneously injected with 2 × 10 6 Lung adenocarcinoma (Lacun3) cells per animal. 100 µg of anti-PD-1, 100 µg of anti-LAG3, 30 mg/kg of CBL-Bi and the corresponding depletion antibodies were administered intraperitoneally at days 0, 2, 6, 9, 13 and 15 as indicated in the figure. NK, CD4, and CD8 T‐cell depletions were carried out by intraperitoneal administration of 100 μg of anti‐mouse CD8a, CD4 or NK1.1 antibody. Mice were humanely sacrificed when tumor size reached ~150–200 mm 2 , or when tumor ulceration or discomfort were observed. ( B ) Kaplan–Meier survival plot of mice under the indicated treatments or depletion (percent). Statistical significance was tested with the Log-rank test. ( C ) Evolution of mean tumor size following the indicated treatments (left). Tumor volumes 9 days after treatment initiation (right). Error bars correspond to ±SEM (left) and box and whiskers with min to max values (right), computing the minimum, maximum, median and quartiles for 25th and 75th percentiles. The whiskers go down to the smallest value and up to the largest ( n = 6 mice per group). Data information: Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. ( D ) Tumor growth of individual mice in the indicated treatment groups ( n = 6 mice per group). Statistical comparisons are shown in the graph as indicated in Methods. Data information: Briefly, for ( B ), survival was represented by Kaplan–Meier plots and analyzed by log-rank test. For ( C ), statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. *, **, ****, indicate P < 0.05, P < 0.01, and P < 0.0001 differences. .

Journal: EMBO Molecular Medicine

Article Title: PD-1/LAG-3 co-signaling profiling uncovers CBL ubiquitin ligases as key immunotherapy targets

doi: 10.1038/s44321-024-00098-y

Figure Lengend Snippet: ( A ) Schematic design of the experiment. BALB/c female mice were randomly allocated and subcutaneously injected with 2 × 10 6 Lung adenocarcinoma (Lacun3) cells per animal. 100 µg of anti-PD-1, 100 µg of anti-LAG3, 30 mg/kg of CBL-Bi and the corresponding depletion antibodies were administered intraperitoneally at days 0, 2, 6, 9, 13 and 15 as indicated in the figure. NK, CD4, and CD8 T‐cell depletions were carried out by intraperitoneal administration of 100 μg of anti‐mouse CD8a, CD4 or NK1.1 antibody. Mice were humanely sacrificed when tumor size reached ~150–200 mm 2 , or when tumor ulceration or discomfort were observed. ( B ) Kaplan–Meier survival plot of mice under the indicated treatments or depletion (percent). Statistical significance was tested with the Log-rank test. ( C ) Evolution of mean tumor size following the indicated treatments (left). Tumor volumes 9 days after treatment initiation (right). Error bars correspond to ±SEM (left) and box and whiskers with min to max values (right), computing the minimum, maximum, median and quartiles for 25th and 75th percentiles. The whiskers go down to the smallest value and up to the largest ( n = 6 mice per group). Data information: Statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. ( D ) Tumor growth of individual mice in the indicated treatment groups ( n = 6 mice per group). Statistical comparisons are shown in the graph as indicated in Methods. Data information: Briefly, for ( B ), survival was represented by Kaplan–Meier plots and analyzed by log-rank test. For ( C ), statistical comparisons were carried out by a two-way ANOVA followed by pair-wise Tukey tests. *, **, ****, indicate P < 0.05, P < 0.01, and P < 0.0001 differences. .

Article Snippet: Then, 100 µg of anti-PD-1 mAb (RPMI-14, BioXCell), 100 µg of anti-LAG3 mAb (C9B7W, Abyntek) were administered intraperitoneally (i.p) following the scheme described in the figures.

Techniques: Injection

High glucose-induced SC-derived exosomes inhibited the neurite outgrowth of NG108-15 cells in high glucose (A) Expression of AKT1, DNMT3A, and GAP43 in NG108-15 was detected by PCR, and AKT signaling pathway and neurite outgrowth-related factors (DNMT3A and GAP43) were inhibited in NG108-15 cells treated with H-EXO compared to L-EXO (n = 10 samples; t-test: ∗∗∗p < 0.001 versus the L-EXO group). (B and C) Western blot (B) was used to detect the protein expression of p -AKT, t-AKT, DNMT3A, and GAP43 in NG108-15 cells, the results had the same trend as the PCR results. (C) Gray value statistics of Western blot (n = 4 samples, nonparametric tests: ∗p < 0.05 of p -AKT/AKT, Bcl2/Bax and C-cas3/GAPDH versus the L-EXO group). (D and E) Immunocytochemistry staining (D) of beta III Tubulin (red) to observe neurite outgrowth, H-EXO significantly reduced neurite outgrowth in NG108-15 cells compared to L-EXO. Scale bar: 25 μm. (E) Neurite length quantification (n = 10 fields of view per group, t-test: ∗∗∗p < 0.001 versus the L-EXO group). For the above, data are represented as mean ± SD.

Journal: iScience

Article Title: Schwann cells-derived exosomal miR-21 participates in high glucose regulation of neurite outgrowth

doi: 10.1016/j.isci.2022.105141

Figure Lengend Snippet: High glucose-induced SC-derived exosomes inhibited the neurite outgrowth of NG108-15 cells in high glucose (A) Expression of AKT1, DNMT3A, and GAP43 in NG108-15 was detected by PCR, and AKT signaling pathway and neurite outgrowth-related factors (DNMT3A and GAP43) were inhibited in NG108-15 cells treated with H-EXO compared to L-EXO (n = 10 samples; t-test: ∗∗∗p < 0.001 versus the L-EXO group). (B and C) Western blot (B) was used to detect the protein expression of p -AKT, t-AKT, DNMT3A, and GAP43 in NG108-15 cells, the results had the same trend as the PCR results. (C) Gray value statistics of Western blot (n = 4 samples, nonparametric tests: ∗p < 0.05 of p -AKT/AKT, Bcl2/Bax and C-cas3/GAPDH versus the L-EXO group). (D and E) Immunocytochemistry staining (D) of beta III Tubulin (red) to observe neurite outgrowth, H-EXO significantly reduced neurite outgrowth in NG108-15 cells compared to L-EXO. Scale bar: 25 μm. (E) Neurite length quantification (n = 10 fields of view per group, t-test: ∗∗∗p < 0.001 versus the L-EXO group). For the above, data are represented as mean ± SD.

Article Snippet: After treatment with SC exosomes for 3 days, NG108-15 cells cultured in a 35 mm confocal dish were fixed with ice-cold 4% paraformaldehyde (PFA; 158,127 Sigma-Aldrich) for 20 min, permeabilized with 0.5% Triton X-100 (X100 Sigma-Aldrich) for 15 min and blocked with 10% goat serum (G9023 Sigma-Aldrich) for 1 h. Anti-beta III Tubulin (βIII) (rabbit monoclonal 1:2000; Abcam ab1 8207 ) was used as the primary antibody over-night at 4°C, and goat anti-rabbit Alexa Fluor 555 (1:1,000; Invitrogen A27039) was used as the secondary antibody 2 h at room temperature.

Techniques: Derivative Assay, Expressing, Western Blot, Immunocytochemistry, Staining

SC-derived exosomes rich in miR-21 accelerated the neurite outgrowth of NG108-15 cells under high glucose conditions (A) Expression of AKT1, DNMT3A, and GAP43 in NG108-15 was detected by PCR, and AKT signaling pathway and neurite outgrowth-related factors (DNMT3A, GAP43) were enhanced in NG108-15 cells treated with miR-21-EXO compared to MC-EXO (n = 10 samples, t-test: ∗∗∗p < 0.001 versus the MC-EXO group). (B and C) Western blot (B) was used to detect the protein expression of p -AKT, t-AKT, DNMT3A, and GAP43 in NG108-15 cells, the results had the same trend as the PCR results. (C) Gray value statistics of Western blot (n = 6 samples, nonparametric tests: ∗p < 0.05 of p -AKT/AKT/GAP43/GAPDH, ∗∗p < 0.01 of DNMT3A/GAPDH versus the MC-EXO group). (D and E) Immunocytochemistry staining (D) of beta III Tubulin (red) to observe neurite outgrowth. Scale bar: 25 μm. (E) Neurite length quantification (n = 10 fields of view per group, t-test: ∗∗∗p < 0.001 versus the MC-EXO group). For the above, data are represented as mean ± SD.

Journal: iScience

Article Title: Schwann cells-derived exosomal miR-21 participates in high glucose regulation of neurite outgrowth

doi: 10.1016/j.isci.2022.105141

Figure Lengend Snippet: SC-derived exosomes rich in miR-21 accelerated the neurite outgrowth of NG108-15 cells under high glucose conditions (A) Expression of AKT1, DNMT3A, and GAP43 in NG108-15 was detected by PCR, and AKT signaling pathway and neurite outgrowth-related factors (DNMT3A, GAP43) were enhanced in NG108-15 cells treated with miR-21-EXO compared to MC-EXO (n = 10 samples, t-test: ∗∗∗p < 0.001 versus the MC-EXO group). (B and C) Western blot (B) was used to detect the protein expression of p -AKT, t-AKT, DNMT3A, and GAP43 in NG108-15 cells, the results had the same trend as the PCR results. (C) Gray value statistics of Western blot (n = 6 samples, nonparametric tests: ∗p < 0.05 of p -AKT/AKT/GAP43/GAPDH, ∗∗p < 0.01 of DNMT3A/GAPDH versus the MC-EXO group). (D and E) Immunocytochemistry staining (D) of beta III Tubulin (red) to observe neurite outgrowth. Scale bar: 25 μm. (E) Neurite length quantification (n = 10 fields of view per group, t-test: ∗∗∗p < 0.001 versus the MC-EXO group). For the above, data are represented as mean ± SD.

Article Snippet: After treatment with SC exosomes for 3 days, NG108-15 cells cultured in a 35 mm confocal dish were fixed with ice-cold 4% paraformaldehyde (PFA; 158,127 Sigma-Aldrich) for 20 min, permeabilized with 0.5% Triton X-100 (X100 Sigma-Aldrich) for 15 min and blocked with 10% goat serum (G9023 Sigma-Aldrich) for 1 h. Anti-beta III Tubulin (βIII) (rabbit monoclonal 1:2000; Abcam ab1 8207 ) was used as the primary antibody over-night at 4°C, and goat anti-rabbit Alexa Fluor 555 (1:1,000; Invitrogen A27039) was used as the secondary antibody 2 h at room temperature.

Techniques: Derivative Assay, Expressing, Western Blot, Immunocytochemistry, Staining

Obesity was associated with repression of immune checkpoints. ( A ) The expression of various immune checkpoints in obesity and normal groups. ( B ) The expression of LAG3 and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. ( C ) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. ( D ) The correlation matrix of each immune checkpoint in obesity and normal group. ( * p <0.05, ** p <0.01).

Journal: Aging (Albany NY)

Article Title: Colon cancer combined with obesity indicates improved survival- research on relevant mechanism

doi: 10.18632/aging.103972

Figure Lengend Snippet: Obesity was associated with repression of immune checkpoints. ( A ) The expression of various immune checkpoints in obesity and normal groups. ( B ) The expression of LAG3 and PD-1 in healthy bowel tissues, colon cancer derived from normal (non-obesity) patients and obesity patients was confirmed by immunohistochemistry. ( C ) The association of drug sensitiveness and gene expression (LAG3 and PD-1) analyzed by Genomics of Drug Sensitivity in Cancer (GDSC) database. ( D ) The correlation matrix of each immune checkpoint in obesity and normal group. ( * p <0.05, ** p <0.01).

Article Snippet: The slices were then soaked in 10% BSA to inhibit endogenous peroxidase activity and incubated with anti-PD-1 or anti-LAG3 rabbit polyclonal antibody (1:100; Cat: 86163&15372, Cell Signaling Tech, Boston, MA USA) at 4°C overnight.

Techniques: Expressing, Derivative Assay, Immunohistochemistry, Gene Expression

Single-gene analysis of LAG3 in CD8 + T cell-associated genes. The expression and correlation with CD8 + T cells for LAG3 ( A ), DUSP4 ( B ), and FXYD2 ( C ) in the TCGA–KIRC cohort. Correlation of LAG3 with tumor mutation burden ( D ) and responsiveness to immune checkpoint inhibitors ( E ). Correlation of DUSP4 with tumor mutation burden ( F ) and responsiveness to immune checkpoint inhibitors ( G ). IC 50 of sunitinib ( H ) and sorafenib ( I ) in different LAG3 expression subgroups. ( J ) LAG3 stemness score. ( K ) Relevance of LAG3 to immune-related genes

Journal: European Journal of Medical Research

Article Title: Single-cell combined bioinformatics analysis: construction of immune cluster and risk prognostic model in kidney renal clear cells based on CD8 + T cell-associated genes

doi: 10.1186/s40001-024-01689-8

Figure Lengend Snippet: Single-gene analysis of LAG3 in CD8 + T cell-associated genes. The expression and correlation with CD8 + T cells for LAG3 ( A ), DUSP4 ( B ), and FXYD2 ( C ) in the TCGA–KIRC cohort. Correlation of LAG3 with tumor mutation burden ( D ) and responsiveness to immune checkpoint inhibitors ( E ). Correlation of DUSP4 with tumor mutation burden ( F ) and responsiveness to immune checkpoint inhibitors ( G ). IC 50 of sunitinib ( H ) and sorafenib ( I ) in different LAG3 expression subgroups. ( J ) LAG3 stemness score. ( K ) Relevance of LAG3 to immune-related genes

Article Snippet: The tissue sections were incubated at 121 °C in an autoclave for 5 min to extract the antigen, following which these were incubated with anti-LAG3-monoclonal antibody at 4 °C overnight, and the bound antibody (Proteintech) was incubated at 37 °C for 30 min.

Techniques: Expressing, Mutagenesis

Cell population expression and pathway analysis of LAG3 in single-cell analysis. A LAG3 UMAP plot in CD8 + T cell-associated subgroups. B Expression of LAG3 in different cell populations in normal kidney and renal cancer tissues. C – F Analysis of potential signaling pathway of LAG3 by GESA. G – I Analysis of the enrichment of LAG3 using the GSVA algorithm

Journal: European Journal of Medical Research

Article Title: Single-cell combined bioinformatics analysis: construction of immune cluster and risk prognostic model in kidney renal clear cells based on CD8 + T cell-associated genes

doi: 10.1186/s40001-024-01689-8

Figure Lengend Snippet: Cell population expression and pathway analysis of LAG3 in single-cell analysis. A LAG3 UMAP plot in CD8 + T cell-associated subgroups. B Expression of LAG3 in different cell populations in normal kidney and renal cancer tissues. C – F Analysis of potential signaling pathway of LAG3 by GESA. G – I Analysis of the enrichment of LAG3 using the GSVA algorithm

Article Snippet: The tissue sections were incubated at 121 °C in an autoclave for 5 min to extract the antigen, following which these were incubated with anti-LAG3-monoclonal antibody at 4 °C overnight, and the bound antibody (Proteintech) was incubated at 37 °C for 30 min.

Techniques: Expressing, Single-cell Analysis

Validation of LAG3 as a key oncogene in KIRC in in vitro experiments. A Validation of LAG3 expression in renal cancer cell lines. B Knock-down efficiency of LAG3 , respectively, in 786-O and ACHN cell lines. C LAG3 clone tests in 786-O and ACHN cell lines. D LAG3 scratch tests in 786-O and ACHN cell lines. E LAG3 migration and invasion assays in 786-O and ACHN cell lines using a 24-well plate. F LAG3 CCK8 assay in 786-O and ACHN cell lines

Journal: European Journal of Medical Research

Article Title: Single-cell combined bioinformatics analysis: construction of immune cluster and risk prognostic model in kidney renal clear cells based on CD8 + T cell-associated genes

doi: 10.1186/s40001-024-01689-8

Figure Lengend Snippet: Validation of LAG3 as a key oncogene in KIRC in in vitro experiments. A Validation of LAG3 expression in renal cancer cell lines. B Knock-down efficiency of LAG3 , respectively, in 786-O and ACHN cell lines. C LAG3 clone tests in 786-O and ACHN cell lines. D LAG3 scratch tests in 786-O and ACHN cell lines. E LAG3 migration and invasion assays in 786-O and ACHN cell lines using a 24-well plate. F LAG3 CCK8 assay in 786-O and ACHN cell lines

Article Snippet: The tissue sections were incubated at 121 °C in an autoclave for 5 min to extract the antigen, following which these were incubated with anti-LAG3-monoclonal antibody at 4 °C overnight, and the bound antibody (Proteintech) was incubated at 37 °C for 30 min.

Techniques: Biomarker Discovery, In Vitro, Expressing, Knockdown, Migration, CCK-8 Assay

LAG3 is highly expressed in the KIRC tissue

Journal: European Journal of Medical Research

Article Title: Single-cell combined bioinformatics analysis: construction of immune cluster and risk prognostic model in kidney renal clear cells based on CD8 + T cell-associated genes

doi: 10.1186/s40001-024-01689-8

Figure Lengend Snippet: LAG3 is highly expressed in the KIRC tissue

Article Snippet: The tissue sections were incubated at 121 °C in an autoclave for 5 min to extract the antigen, following which these were incubated with anti-LAG3-monoclonal antibody at 4 °C overnight, and the bound antibody (Proteintech) was incubated at 37 °C for 30 min.

Techniques: