Additional file 1 of Specific chromatin landscapes and transcription factors couple breast cancer subtype with metastatic relapse to lung or brain
Creators: name: Cai, Wesley
name: Greer, Celeste
name: Chen, Jocelyn
name: Arnal-Estapé, Anna
name: Cao, Jian
name: Yan, Qin
name: Nguyen, Don
Publisher: name: figshare
Year: 2020
Subjects: subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Neuroscience
subject: Developmental Biology
subject: Cancer
subject: Hematology
subject: Infectious Diseases
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 1: Figure S1. Gene expression associated with promoter and enhancer changes. (A-B) Distribution of significant gene expression changes (RNA log2FC) associated with promoter H3K4me3 peaks either significantly decreased or increased in LM2 vs Par (A) or BrM2 vs Par (B). (C-D) Distribution of significantly gene expression changes (RNA log2FC) linked with either significantly increased or decreased enhancer H3K27ac peaks in LM2 vs Par (C, left) or BrM2 vs Par (D, left). Linkages determined using HiChIP. Shuffle indicates the same plot after randomly shuffling the linkages. P values were calculated using Wilcox U-test. Figure S2. Common promoter and enhancer activation in metastatic cells. (A) Genome track view of the promoter region of PLCB1 demonstrating shared H3K4me3 changes in metastatic sub-populations. (B) Genome track view of APOBEC3G demonstrating shared enhancer H3K27ac changes in metastatic sub-populations. Promoter-enhancer linkage was determined by HiChIP. Figure S3. metATAC workflow and ontology. (A) Schematic of how the TCGA cohort data and cell line ATAC data were integrated and analyzed. MDA-MB-231 lines were processed using the same method as indicated in Corces et al. [37], and top differentially accessible chromatin regions were used to generate the metATAC signature. Each patient in the TCGA cohort (n = 69) was then assigned a score based on their open chromatin similarity to Par or metastatic sub-populations (common metATAC score). Significantly different regions defined by p &lt; 5e-5, as determined by DESeq2 and BH correction. (B) GREAT gene ontology results associated with increased (up) and decreased (down) peaks in the signature. (C) Distribution of metATAC score between ER positive and negative patients as determined by IHC. P-value determined using Wilcoxon rank sum test. (D) Kaplan-Meier plots of patients separated into ER positive (left) and negative (right) as determined by IHC. metATAC quantile was assigned before splitting the patient into the two groups. Figure S4. Scheme for regulatory motif prediction. Scheme for identification of TFs associated with differentially expressed genes between each metastatic sub-population and Par. Reproducible linkages between ATAC peaks were first determined using HiChIP data and subsequently annotated to be either distal or proximal (promoter) to the TSS of each gene. Gene expression is then used to determine significantly up- or down-regulated genes. ATAC peaks that are linked to these gene modules (both distal and proximal) and also follow the same direction of signal change are elected as regulatory regions. Hypergeometric tests are then performed on regulatory regions using all regions as background to determine enriched TF motif clusters (based on RSAT). Motif clusters are finally re-assigned to transcription factors that fall within each respective cluster. Figure S5. Regulatory motifs and associated transcription factors. (A) TFs associated with motif clusters enriched in regions of increased accessibility (gained) in either LM2 compared to Par, BrM2 compared to Par, or both. TFs names are color-coded to indicate membership in the respective motif cluster. (B) Same as (A) but with motif clusters enriched in regions of decreased accessibility (lost) in the indicated comparison. Figure S6. Subtype specificity of metATAC score and transcription factor expression. (A-B) Distribution of LM2- (A) or BrM2-specific (B) metATAC score across PAM50 subtypes. (C-D) Expression of the indicated transcription factors across subtypes. (E) Kaplan-Meier curve of SMAD1 expression and brain metastasis-free survival. (F) Expression of SMAD1 across subtypes. (G) Kaplan-Meier curve of NRBF2 expression and brain metastasis-free survival. (H) Expression of NRBF2 across subtypes. NS non-significant. Figure S7. Subtype specificity of metATAC score and transcription factor expression. (A) Kaplan-Meier curve of RUNX2 and lung metastasis-free survival within basal-like patients. (B) Kaplan-Meier curve of JUN and brain metastasis-free survival within basal-like patients. N = 38.