Supplemental Figure S1-S8, Tables S1-S7 from A Novel MAPK–microRNA Signature Is Predictive of Hormone-Therapy Resistance and Poor Outcome in ER-Positive Breast Cancer

&lt;p&gt;Figure S1. Flowchart of study overview Figure S2. (A) gene set enrichment analysis for gene targets of microRNAs overexpressed in the hMAPK- microRNA signature. (B) gene set enrichment analysis for gene targets of microRNAs underexpressed in the hMAPK microRNA signature. The DIANA Mirpath online tool was used for gene set enrichment analyses. Figure S3. (A) MCF-7 cells stably transfected with constitutively active RAF kinase were treated with U0126 for 24 hours. miRNA expression was determined by qRT-PCR; expression given as fold change relative to DMSO treated sample. (B) MCF-7 cells stably transfected to overexpress EGFR were stimulated with EGF and harvested 8 and 24 hours later. Figure S4. (A) Expression of genes that are targets of microRNAs underexpressed in the hMAPKmicroRNA signature in ER+ cancers from TCGA dataset. (B) Expression of genes that are targets of microRNAs overexpresed in the hMAPK-microRNA signature in in ER+ cancers from TCGA dataset. (C) Expression of genes that are targets of microRNAs underexpressed in the hMAPKmicroRNA signature in all breast cancers from METABRIC dataset. (D) Expression of genes that are targets of microRNAs overexpressed in the hMAPK-microRNA signature in all breast cancers from METABRIC dataset. (E) Expression of genes that are targets of microRNAs underexpressed in the hMAPK-microRNA signature in ER+ cancers from METABRIC dataset. (F) Expression of genes that are targets of microRNAs overexpressed in the hMAPK-microRNA signature in ER+ cancers from METABRIC dataset. p-values and t-scores for student's t-test between highhMAPK-microRNA and low-hMAPK-microRNA groups are indicated. Figure S5. Comparison of protein expression of target genes of hMAPK-microRNAs between breast cancers classified as high-hMAPK and low-hMAPK by the hMAPK-microRNA signature. Figure S6. Breast cancers classified as "high hMAPK" by the hMAPK-microRNA signature are enriched for cancers that are (A) ER-negative, (B) and high tumor grade in training datasets. pvalues for chi squared test of independence and for Fisher's exact test are reported. Figure S7. Breast cancers classified as "high hMAPK" by the hMAPK-microRNA signature are enriched for cancers that are (A) ER-negative, (B) high tumor grade, (C) described by a highproliferation metric, and (D) ERBB2 positive in validation datasets. p-values for chi squared test of independence and for Fisher's exact test are reported. Figure S8. Kaplan-Meier survival analysis of patients from the Buffa dataset classified as highhMAPK or low-hMAPK by the hMAPK-microRNA recurrence signature. (left) All patients,(middle) patients with ER+ disease (right)patients with ER- disease. Kaplan-Meier curves: dashed= low-hMAPK-microRNA, solid= high-hMAPK-microRNA; logrank test p-values are indicated Table S1A. Clinical characteristics of Buffa training dataset Table S1B. Clinical characteristics of TCGA training dataset Table S1C. Clinical characteristics of Enerly training dataset Table S1D. Clinical characteristics of METABRIC training dataset Table S2. The hMAPK-microRNA signature: microRNAs that are commonly differentially expressed in tumors classified as hMAPK-mRNA vs those classified as not-hMAPK-RNA in the TCGA and Buffa training datasets. Table S3. RPPA protein expression for proteins with significant differential expression between cancers from TCGA dataset classified as hMAPK-miRNA or not-hMAPK-miRNA. T-statistic, pvalue, and permutation adjusted p-value given. Yellow= upregulated in hMAPK-miRNA; blue: downregulated in hMAPK-miRNA Table S4. The hMAPK-microRNA recurrence signature. Table S5. Multivariate analysis of hMAPK-microRNA recurrence signature in METABRIC dataset and Lyng datasets.Table S6. Multivariate analysis of hMAPK-microRNA recurrence signature in METABRIC dataset, patients stratified according to treatment status. Table S7. hMAPK-microRNA survival signature.&lt;/p&gt;

Topic: MicroRNA in disease regulation
Subfield: Cancer Research
Field: Biochemistry, Genetics and Molecular Biology
Domain: Life Sciences