morpheus heatmapping software  (Broad Institute Inc)

Journal: Clinical & Translational Immunology

Article Title: Robust immunity to influenza vaccination in haematopoietic stem cell transplant recipients following reconstitution of humoral and adaptive immunity

doi: 10.1002/cti2.1456

Figure Lengend Snippet: Multivariant analyses of HR‐HSCT and LR‐HSCT groups. (a) Levels of influenza‐specific antibodies separated for HC, LR‐HSCT and HR‐HSCT. Raw MFI data were standardised using z ‐score before generating the heatmap. Value closer to 1 (i.e. hotter colour) indicates that the level of antibody was higher than other individuals, whereas value closer to −1 (blue) indicates lower antibody level (b–e) partial least squares discriminant analysis (PLS‐DA), loadings plot and principal component analysis (PCA) on antibody levels at dose 1 (b) or baseline (d) for LR‐HSCT and HR‐HSCT groups (10‐fold cross‐validation). PCA was performed with four and five selected features, respectively, to validate their importance in separating groups. (c , e) Direct comparisons of features are shown in loadings plots. Bars indicate median and interquartile range. Significance between the two groups was determined using the Mann–Whitney test (* P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001). (f–i) Correlations matrix (f) between pre‐vaccination and post‐vaccination influenza‐specific antibodies and B cells and (g, h) correlations of key features. (i) Correlations between A/Switzerland (H3N2) HA IgG and months after HSCT. Correlation was determined with Spearman's correlation. n HC = 14, n HSCT‐LR = 7, n HSCT‐HR = 8. Technical replicates were not performed due to limited patient samples.

Article Snippet: Heatmaps for visualisation were generated using the online Morpheus heatmap software ( https://software.broadinstitute.org/morpheus ; the Broad Institute, MA, USA).

Techniques: Biomarker Discovery, MANN-WHITNEY

Journal: Clinical & Translational Immunology

Article Title: Robust immunity to influenza vaccination in haematopoietic stem cell transplant recipients following reconstitution of humoral and adaptive immunity

doi: 10.1002/cti2.1456

Figure Lengend Snippet: Humoral responses in HSCT recipients following two IIV doses. (a, b) Pooled analyses of HAI titre and influenza‐specific B‐cell frequency. Bars indicate the median and interquartile range. Significance was determined using the Friedman test followed by Dunn's multiple comparisons test ( n = 8; ** P < 0.01). (c) HAI antibody landscapes against 12 A/H3N2 strains of HSCT recipients that received two IIV doses. Vertical and horizontal dotted lines indicate the vaccine strain and the seroprotective HAI titre at 40 respectively. Solid lines indicate titre landscapes across strains estimated using GAMs and shadings indicate 95% CI for the model. Colour dots show individual participant titres against each antigen. (d) HAI titre and (e) influenza‐specific B‐cell frequency against the vaccine strains of each individual who received two IIV doses. (f) Heatmap of isotype distribution and Fc gamma receptor binding ability of influenza‐specific antibodies for each HSCT recipient that received two IIV doses. MFI values were standardised using z ‐score. A value closer to 1 (i.e. a hotter colour) indicates that the level of antibody was higher than other individuals/time points. Note that participant HSCT01 had a documented influenza B virus infection between the administration of the second vaccine dose and the last blood drawing. Technical replicates were not performed due to limited patient samples.

Article Snippet: Heatmaps for visualisation were generated using the online Morpheus heatmap software ( https://software.broadinstitute.org/morpheus ; the Broad Institute, MA, USA).

Techniques: Binding Assay, Virus, Infection

Journal: Nature Communications

Article Title: SARS-CoV-2 infection results in immune responses in the respiratory tract and peripheral blood that suggest mechanisms of disease severity

doi: 10.1038/s41467-022-30088-y

Figure Lengend Snippet: a ELISA titration curves against the SARS-CoV-2 receptor-binding domain (RBD) for IgM, IgG, and IgA in COVID-19 respiratory and paired plasma samples and non-COVID-19 respiratory samples as negative controls. Dotted lines within each graph indicates the cut-off used to determine end-point titres. b End-point titres of SARS-CoV-2 RBD antibodies between top left panel: respiratory samples of COVID-19 and non-COVID-19 patients, top right panel: respiratory and paired plasma samples of COVID-19 patients, and bottom panel: endotracheal tube aspirate (ETA), sputum, or bronchoalveolar lavage (BAL) and paired plasma samples of COVID-19 patients. Top left panel: Bars indicate median with interquartile range. Dotted line indicates the detection level. n ETA = 15, n Sputum = 20, n BAL = 6, n Non-COVID-19 ETA = 5, n Non-COVID-19 sputum = 1. Top right panel: Dotted lines connect the most closely matched plasma and respiratory samples from each patient. Bottom panel: Bars indicate the median. Statistical significance was determined with a two-sided Mann-Whitney test. n ETA = 15, n ETA matched plasma = 14, n Sputum = 20, n Sputum matched plasma = 19, n BAL = 6, n BAL matched plasma = 3. c Heatmap of percentage (%) inhibition tested by surrogate virus neutralization test (sVNT), anti-RBD ELISA titres and days post disease onset. d Correlation between anti-RBD antibody titres and (%) sVNT inhibition. Correlation was determined with a two-tailed Spearman’s correlation. e Number of samples and patients with seroconverted anti-RBD IgM, IgG, IgA and positive % sVNT inhibition. Red curved lines surrounding the donut graphs indicate the samples/patients with seroconverted IgM and IgG. Earliest samples were used for each patient when determining seroconversion which was defined as average titre + 2×SD of non-COVID-19 respiratory samples. Positive % sVNT inhibition was defined as % sVNT inhibition ≥ 20%. f Correlation of anti-RBD ELISA titres and % sVNT inhibition between respiratory samples (ETA, sputum, and BAL) and paired plasma samples collected at the closest timepoint for each patient. Correlation was determined with a two-tailed Spearman’s correlation. n ETA = 15, n ETA matched plasma = 14, n Sputum = 20, n Sputum matched plasma = 19, n BAL = 6, n BAL matched plasma = 3. Source data are provided as a Source Data file.

Article Snippet: Correlations were assessed using two-tailed Spearman’s correlation coefficient ( r s ) and visualized in R v3.6.2 as heatmaps using the corrplot package or using the online Morpheus heatmap software ( https://software.broadinstitute.org/morpheus ; the Broad Institute, MA, USA) and p-values of correlations were corrected for multiple comparisons by FDR in R v3.6.2.

Techniques: Enzyme-linked Immunosorbent Assay, Titration, Binding Assay, Clinical Proteomics, MANN-WHITNEY, Inhibition, Virus, Neutralization, Two Tailed Test

Journal: Molecular cancer research : MCR

Article Title: TGFβ and Hippo pathways cooperate to enhance sarcomagenesis and metastasis through the hyaluronan mediated motility receptor (HMMR)

doi: 10.1158/1541-7786.MCR-19-0877

Figure Lengend Snippet: TGFβ and YAP1 cooperatively regulate RHAMM via NF-κB signaling pathway. (A) Broad institute Morpheus software heatmap based on gene expression from microarray analysis of KP230 cells treated with DMSO or SAHA (2 µM)/JQ1 (0.5 µM) for 48 hrs. (B) qRT-PCR of HT-1080 and (C) KP230 cells treated as in A. *P <0.01. n=3. (D) Western blot of HT-1080 (E) KP230 and (F) KIA treated as in A. (G) qRT-PCR of KP cells p65/Rela shRNA, *P <0.01. n=3. (H) Western blot of KP cells expressing Rela shRNA.

Article Snippet: We conclude that RHAMM expression is regulated by the YAP1-NF-κB axis in addition to TGFβ signaling. fig ft0 fig mode=article f1 fig/graphic|fig/alternatives/graphic mode="anchored" m1 Open in a separate window Figure 4. caption a7 TGFβ and YAP1 cooperatively regulate RHAMM via NF-κB signaling pathway. ( A) Broad institute Morpheus software heatmap based on gene expression from microarray analysis of KP230 cells treated with DMSO or SAHA (2 μM)/JQ1 (0.5 μM) for 48 hrs. ( B ) qRT-PCR of HT-1080 and ( C ) KP230 cells treated as in A.

Techniques: Software, Gene Expression, Microarray, Quantitative RT-PCR, Western Blot, shRNA, Expressing