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Supplementary Material 1

Supplementary Material 2

Supplementary Material 3

Additional file 3.

Additional file 1: Table 1: qPCR primer sequences. Table 2: ShRNA and siRNA sequences. Table 3: Major clusters with biological functions regulated by A1542 compounds. Table 4. RNAseq data for expression of 67 genes regulated by A1542 in HEL cells treated for 24 h with A1542 (1 μM).

Additional file 2: Figure 1: Structure of A1541-A1543 and cedrelone compounds and their biological activity in culture. Figure 2: Induction of the cholesterol biosynthesis genes by A1542. Q-RT-PCR analysis of expression of the indicated genes in HEL cells treated with DMSO or A1542 (1 μM) for 24 h. Figure 3: Induction of the cholesterol biosynthesis genes by A1543. Q-RT-PCR analysis of expression of the indicated genes in HEL cells treated with DMSO or A1543 (1 μM) for 24 h. Figure 4: Induction of the cholesterol biosynthesis genes by A1542 in SREBP1 knockdown cells. a-f Expression of the indicated genes in HEL cells treated with DMSO or A1542 (1 μM) for 24 h by Q-RT-PCR. Figure 5. Network map of genes interacts with EGR1 using STRING database. Figure 6: Suppression of the cholesterol biosynthesis genes induced by A1542 by AP1 inhibitor Tanshinone. Q-RT-PCR analysis of expression of the indicated genes in HEL cells treated with DMSO, A1542 (1 μM), Tanshinone (Tan IIA, 10 μM) and A1542 + Tan IIA for 24 h.

In order to obtain better anti-cancer compounds, nine glycosylated derivatives were designed and synthe-sized using diosgenin as starting material. Their structures were confirmed by 1H NMR, 13C NMR and MS spectra. The anti-cancer activities of intermediate compounds 5a—5i and the target compounds 6a—6i were investigated against human leukemia HEL, K562, HL60 and melanoma WM9 cell lines via MTT method. The bioassay results show that these derivatives possess good inhibitory activities against the four cancer cell lines. Furthermore, these derivatives show better inhibitory activities against K562 than against other cell lines, and most derivatives show better inhibitory activities than the parental material. Moreover, compounds 6a—6i are more active than their inter-mediates 5a—5i when against these cells. The above results demonstrate the effects of glycosylation on 3-OH of di-osgenin and acetylation of the sugar moiety on their antitumor activities.

Figure S1. Growth inhibition of HEL cells by the compounds. (A) HEL cells were treated with the indicated concentration of the compounds and percentage of inhibition was determined by MTT assay 3 days after drug treatment. (B) Microscopic images of the cells after 2 days treatment with the indicated compounds (magnification × 40). P

Figure S1. Overview of breast cancer (BC) datasets, cohorts and groups used in this project, and subgrouping analysis. (A) The 1302 BC dataset, which includes 205 triple-negative breast cancers (TNBC) with matched mRNA and miRNA data from EGAS00000000122, was used as training cohort. Six subgroups of all BC or TNBC were randomly divided to correlate expression of PTEN and miRNAs. The 207 BC dataset, which contained 44 TNBC with matched mRNA and miRNA data from GSE22220, was used as validation cohort. 205 related TNBC with copy number alteration (CNA) data and 185 related TNBC with gene mutation data from EGAS00001001753 were used to confirm genomic changes of PTEN-miRNA co-expression profile. (B) Kaplan-Meier survival analysis on PAM50 classification of all 1302 breast cancers (BC), and examples of subgroups 2A-651 BC and 2B-651 BC. (C) Heatmap of correlation coefficient (r) between PTEN and miRNAs for most positive or negative correlation in BC (left) or TNBC (right). Figure S2. DNA sequence variations in TNBC subgroups. (A) Heatmaps of Copy Number Alteration (CNA) of 93 protein-coding cancer genes among the different subgroups in 31 PTEN(-) TNBC. (B) Mutational landscape of 74 genes that have at least one mutated gene among the TNBC subgroups in 28 PTEN(-) TNBC.. Figure S3. Significant changes in copy number alterations (CNA) in protein-coding cancer genes among TNBC subgroups. CNA of total gain (1 + 2) and loss (-1 + -2) in TNBC subgroups and CNA changes of CUX1, DNMT3A, GATA3, MMLLT4, MYC, PBRM1, PTEN and ZNF217. Figure S4. Low EGFR pathway activity in PTEN-deficient TNBC including subgroup ‘a’ as compared to PTEN+ tumors. Figure S5. mRNA expression and CNA of Wnt/β-catenin signaling related genes in PTEN-low/miRs-low (subgroup ‘a’) TNBC versus other TNBC. Figure S6. mRNA expression and CNA of Wnt/β-catenin signaling related genes in PTEN(-)/β-catenin(+) TNBC versus other TNBC. Figure S7. Mutation in PTEN/β-catenin(+) TNBC versus other TNBC. 173 gene mutation data were compared and 135 genes with at least one mutation are shown in order of the number of mutated genes. Figure S8. CRNDE mRNA expression level and distribution in 1292 BC in EGAS00000000083. (A) Expression level of CRNDE mRNA in high (> 1), medium (1 to 0) and low (