<p>Supplementary Figure S1. High expression of UBA1 is associated with low levels of intratumoral CD8+ T cells and predictive of ICB resistance and poor survival in ICB cohorts.</p>
Abstract Objective To identify disease‐specific gene expression profiles in patients with rheumatoid arthritis (RA), using complementary DNA (cDNA) microarray analyses on lymphoblastoid B cell lines (LCLs) derived from RA‐discordant monozygotic (MZ) twins. Methods The cDNA was prepared from LCLs derived from the peripheral blood of 11 pairs of RA‐discordant MZ twins. The RA twin cDNA was labeled with cy5 fluorescent dye, and the cDNA of the healthy co‐twin was labeled with cy3. To determine relative expression profiles, cDNA from each twin pair was combined and hybridized on 20,000‐element microarray chips. Immunohistochemistry and real‐time polymerase chain reaction were used to detect the expression of selected gene products in synovial tissue from patients with RA compared with patients with osteoarthritis and normal healthy controls. Results In RA twin LCLs compared with healthy co‐twin LCLs, 1,163 transcripts were significantly differentially expressed. Of these, 747 were overexpressed and 416 were underexpressed. Gene ontology analysis revealed many genes known to play a role in apoptosis, angiogenesis, proteolysis, and signaling. The 3 most significantly overexpressed genes were laeverin (a novel enzyme with sequence homology to CD13), 11β‐hydroxysteroid dehydrogenase type 2 (a steroid pathway enzyme), and cysteine‐rich, angiogenic inducer 61 (a known angiogenic factor). The products of these genes, heretofore uncharacterized in RA, were all abundantly expressed in RA synovial tissues. Conclusion Microarray cDNA analysis of peripheral blood–derived LCLs from well‐controlled patient populations is a useful tool to detect RA‐relevant genes and could help in identifying novel therapeutic targets.
<p>Contains supplementary data and table titles and as well as supplementary figures with associated titles and legends. Fig. S1. Selection method for planned efficacy analysis of ONC201 in patients with H3K27MDMG. Fig. S2. Progression-free survival from diagnosis of trial patients with non-recurrent H3K27MDMG treated with ONC201. Fig. S3. Swimmers’ plot of ONC201 response by recurrence status, tumor location, and ONC201 trial. Fig. S4. ONC201 efficacy is independent of TP53 mutation status and chromosomal instability. Fig. S5. Cox proportional hazard regression to assess the effect of ONC201 after adjusting for confounders. Fig. S6. Survival of patients with H3K27M-DMG treated with ONC201 versus ONC201untreated historical controls. Fig. S7. Survival of patients with H3K27M-DMG treated with ONC201 versus ONC201untreated patients (PNOC003 or HERBY Phase II trials). Fig. S8. Molecular attributes of patients with H3K27M-DMG treated with ONC201. Fig. S9: Survival of H3K27M-DMG mice models treated with ONC201. Fig. S10. Integrative analysis of in vitro and human tumor metabolic gene expression in response to ONC201. Fig. S11. ONC201-mediated L2HG production increases H3K27me3 in H3K27M-DMG cells. Fig. S12. ONC201-induced increase in H3K27me3 is mediated by lactate dehydrogenase. Fig. S13. ONC201 alters genomic chromatin accessibility and H3K27ac distribution in H3K27M-DMG cells. Fig. S14. ONC201 increases global H3K27me3 in patient samples. Fig. S15. ONC201 does not cause hypermethylation leading to a glioma CpG island methylator phenotype.</p>
<p>Contains supplementary data and table titles and as well as supplementary figures with associated titles and legends. Fig. S1. Selection method for planned efficacy analysis of ONC201 in patients with H3K27MDMG. Fig. S2. Progression-free survival from diagnosis of trial patients with non-recurrent H3K27MDMG treated with ONC201. Fig. S3. Swimmers’ plot of ONC201 response by recurrence status, tumor location, and ONC201 trial. Fig. S4. ONC201 efficacy is independent of TP53 mutation status and chromosomal instability. Fig. S5. Cox proportional hazard regression to assess the effect of ONC201 after adjusting for confounders. Fig. S6. Survival of patients with H3K27M-DMG treated with ONC201 versus ONC201untreated historical controls. Fig. S7. Survival of patients with H3K27M-DMG treated with ONC201 versus ONC201untreated patients (PNOC003 or HERBY Phase II trials). Fig. S8. Molecular attributes of patients with H3K27M-DMG treated with ONC201. Fig. S9: Survival of H3K27M-DMG mice models treated with ONC201. Fig. S10. Integrative analysis of in vitro and human tumor metabolic gene expression in response to ONC201. Fig. S11. ONC201-mediated L2HG production increases H3K27me3 in H3K27M-DMG cells. Fig. S12. ONC201-induced increase in H3K27me3 is mediated by lactate dehydrogenase. Fig. S13. ONC201 alters genomic chromatin accessibility and H3K27ac distribution in H3K27M-DMG cells. Fig. S14. ONC201 increases global H3K27me3 in patient samples. Fig. S15. ONC201 does not cause hypermethylation leading to a glioma CpG island methylator phenotype.</p>
<p>Genomic comparison across the different metastatic sites compared to the matched primary. A. Genomic alterations across metastatic sites compared to matched primary B. Copy number variations across metastatic sites compared to matched primary</p>
