Supplemental Figure 1 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

FGFR3 knockdown reduces MMP-1 and MMP-10 mRNA expression in RT112 cells.</p

Supplemental Figure 2 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

FGFR3 siRNA and R3Mab diminish MMP-1 and MMP-10 mRNA leves in UMUC-14 cells.</p

Supplemental Figure 4 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

R3Mab reduces MMP protein secretion in the conditioned medium by UMUC-14 cells.</p

Supplemental Table 2 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

List of patient information in the phase I study.</p

Supplemental Figure 5 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

R3Mab attenuates xenograft growth of UMUC-14 tumors.</p

Supplemental Figure 3 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

FGFR3 knockdown in RT112 cells reduces total MMP-10 protein level in conditioned medium.</p

Supplemental Figures 6 and 7 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

R3Mab reduces serum levels of human MMP-1 and pro-MMP-10 in mice bearing bladder tumor xenografts.</p

Supplemental Table 1 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

Contains a list of genes regulated by FGFR3 shRNA in RT112 cells.</p

Supplemental Figure 8 from MMP-1 and Pro-MMP-10 as Potential Urinary Pharmacodynamic Biomarkers of FGFR3-Targeted Therapy in Patients with Bladder Cancer

Lack of effect of R3Mab on serum pro-MMP-10 levels in mice with SW780 tumors.</p

Blood transcriptomic signature in type-2 biomarker low severe asthma and asthma control.

BackgroundPatients with Type-2 (T2) cytokine-low severe asthma often have persistent symptoms despite suppression of T2-inflammation with corticosteroids (CS).ObjectivesTo analyze whole blood transcriptome from 738 samples in T2-biomarker high/low severe asthma patients to relate transcriptomic signatures to T2-biomarkers and asthma symptom scores.MethodsBulk RNAseq data were generated for blood samples (baseline, Week24, Week48) from 301 participants recruited to a randomized clinical trial of CS optimization in severe asthma. Unsupervised clustering, differential gene expression analysis, and pathway analysis were performed. Patients were grouped by T2-biomarker status and symptoms. Associations between clinical characteristics and differentially expressed genes (DEGs) associated with biomarker and symptom levels were investigated.ResultsUnsupervised clustering identified two clusters; Cluster 2 patients were blood eosinophil low/symptom high and more likely to be receiving oral CS (OCS). Differential gene expression analysis of these clusters, with and without stratification for OCS, identified 2,960 and 4,162 DEGs respectively. 627/2,960 genes remained after adjusting for OCS by subtracting OCS signature genes. Pathway analysis identified dolichyl-diphosphooligosaccharide biosynthesis and assembly of RNA polymerase I complex as significantly enriched pathways. No stable DEGs were associated with high symptoms in T2-biomarker low patients, but numerous associated with elevated T2-biomarkers, including 15 that were up-regulated at all time-points irrespective of symptom level.ConclusionsOCS have a considerable effect on whole blood transcriptome. DEG analysis demonstrates a clear T2-biomarker transcriptomic signature, but no signature was found in association with T2-biomarker low patients, including those with a high symptom burden