Additional file 1: Table S1. of A Fucus vesiculosus extract inhibits estrogen receptor activation and induces cell death in female cancer cell lines

248 genes analyzed for expression profiling (Nanostring™ nCounter®) and 6 housekeeping reference genes. Figure S1. Assays of toxicity. (A) FVE effects on membrane permeability and mitochondrial ATP. (B) Digitonin used as positive control for primary necrosis. (C) CCCP used as positive control for mitochondrial toxicity. Figure S2. Morphological alterations. (A) FVE-untreated and (B) -treated cells with 1.0 % FVE, 48 hr. Figure S3. Heatmap of differential mRNA expression following FVE treatment at 0.25 % and 1.0 % (4 hr) in MCF-7, T47D, MDA-MB-231, HEC-1-B, RL95-2 and OVCAR-3 cell lines; significance level, p <0.05. Figure S4. Treatment of MCF-7, MDA-MB-231, HEC-1-B, MES-SA, AN3-CA, OVCAR-3 and Caov-3 cells with apoptosis (VAD) and autophagy (3MA) inhibitors; *indicates significant difference with FVE without inhibitor (p <0.05). Figure S5. FVE-induced apoptosis via caspase3/7-mediated PARP cleavage in MDA-MB-231 cells; *p <0.05, **p <0.01 compared to controls. Figure S6. FVE down-regulates PI3K/Akt/mTOR signaling in MCF-7 cells. (A) FVE reduced Akt phosphorylation at Ser473 and Thr308, (B) decreased PI3K, 4-EB-P1 and p70S6K phosphorylation, and (C) promoted accumulation of phospho-Beclin-1 and LC3B II. Data are from >3 independent Western blots normalized by β-actin levels; *p <0.05, **p <0.01 compared to controls. Figure S7. FVE down-regulates PI3K/Akt/mTOR signaling in MDA-MB-231 cells. (A) FVE reduced Akt phosphorylation at Ser473 and Thr308, (B) decreased PI3K, 4-EB-P1 and p70S6K phosphorylation, and (C) promoted phospho-Beclin-1 and LC3B II accumulation. Data are from >3 independent Western blots normalized by β-actin levels; *p <0.05, **p < 0.01 compared to controls. Figure S8. Fucoidan up-regulates phosphor-Akt. (A) Fucoidan increased Akt phosphorylation at Ser473 in MCF-7 cells in a concentration-dependent manner; no change in Akt phosphorylation at Thr308. (B) Fucoidan increased Akt phosphorylation at Ser473 in MDA-MB-231 cells in a concentration- and time-dependent manner; no changes observed in Akt phosphorylation at Thr308. (PDF 11350 kb

MOESM3 of Tumor specific liposomes improve detection of pancreatic adenocarcinoma in vivo using optoacoustic tomography

Additional file 3: Figure S3.   Representative locations of organs on MSOT at both 46 and 49 mm. Organs are noted PT = Pancreas tumor, S = Spleen, L = Liver, BV = Blood vessel, K = Kidney

MOESM1 of Tumor specific liposomes improve detection of pancreatic adenocarcinoma in vivo using optoacoustic tomography

Additional file 1: Figure S1.   Structures of the lipids used for control and Sdc1-tagged liposome synthesis

MOESM2 of Tumor specific liposomes improve detection of pancreatic adenocarcinoma in vivo using optoacoustic tomography

Additional file 2: Figure S2. Absorption spectrum for CF-750 encapsulated Sdc1 liposomes. The liposomes demonstrated fluorescence activity with peak absorbance at 750 nm. Encapsulating the CF-750 dye within the Sdc1 liposomes did not change the optical activity of the dye

AR negative triple negative or “quadruple negative” breast cancers in African American women have an enriched basal and immune signature

<div><p>There is increasing evidence that Androgen Receptor (AR) expression has prognostic usefulness in Triple negative breast cancer (TNBC), where tumors that lack AR expression are considered “Quadruple negative” Breast Cancers (“QNBC”). However, a comprehensive analysis of AR expression within all breast cancer subtypes or stratified by race has not been reported. We assessed AR mRNA expression in 925 tumors from The Cancer Genome Atlas (TCGA), and 136 tumors in 2 confirmation sets. AR protein expression was determined by immunohistochemistry in 197 tumors from a multi-institutional cohort, for a total of 1258 patients analyzed. Cox hazard ratios were used to determine correlations to PAM50 breast cancer subtypes, and TNBC subtypes. Overall, AR-negative patients are diagnosed at a younger age compared to AR-positive patients, with the average age of AA AR-negative patients being, 49. AA breast tumors express AR at lower rates compared to Whites, independent of ER and PR expression (p<0.0001). AR-negative patients have a (66.60; 95% CI, 32–146) odds ratio of being basal-like compared to other PAM50 subtypes, and this is associated with an increased time to progression and decreased overall survival. AA “QNBC” patients predominately demonstrated BL1, BL2 and IM subtypes, with differential expression of E<i>2F1</i>, <i>NFKBIL2</i>, <i>CCL2</i>, <i>TGFB3</i>, <i>CEBPB</i>, <i>PDK1</i>, <i>IL12RB2</i>, <i>IL2RA</i>, and <i>SOS1</i> genes compared to white patients. Immune checkpoint inhibitors PD-1, PD-L1, and CTLA-4 were significantly upregulated in both overall “QNBC” and AA “QNBC” patients as well. Thus, AR could be used as a prognostic marker for breast cancer, particularly in AA “QNBC” patients.</p></div

Expression heatmap showing comparison between PAM50 genes subtypes the AR-positive vs AR-negative tumors.

Heat Map using PAM50 gene signature compared to AR status. Genes that are enriched in ER and AR-negative subtypes (blue bar) show complete absence of expression in a subset of the AR-positive subtypes that is traditionally categorized as ‘unclassified’ subtypes (blue arrow). Genes enriched in the Hormone Receptor (HR) subtypes are typically decreased in the AR-negative subtype (red bar), including some samples that would normally considered ‘unclassified’ or HR-positive.</p

AR-associated genes.

<p>A. Genes most highly associated <i>(bivariate cutoff 1</i>.<i>0E-07)</i> with AR expression across the TCGA dataset were used to determined novel gene expression signatures associated with AR tumor status. Distinct subgroups of genes with shared expression trends were identified using K-means cluster analysis and separated into 5 nodes of genes with expression trends that are either upregulated or downregulated in the AR-negative tumors. B. A subset of genes related to the Immunomodulatory TNBC subtype display statistically significant differences in expression between AA vs White patients when comparing expression in AR-high and AR-low categories.</p

Patient characteristics of TCGA population.

<p>The TCGA invasive breast cancer dataset had the largest patient set of RNA-seq data (primary breast cancers for 180 AAs and 745 Whites) was used to quantify distributions of AR expression across patient groups in order to calculate a suitable threshold to stratify the entire dataset/population as AR-positive or AR-negative categories, based on highest and lowest tertiles, exclusively.</p

AR tumor status is associated with younger ages and AR-negative patients have a significantly higher rate of disease progression.

(A). Density plot of ages for each AR status. The mean age of AR positive subtypes is 59, and the mean age of AR negative subtypes is 56. (B). Sub-stratifying ages by race groups indicates that there is a significant difference in the age for AR negative AA (p = 0.034) as compared to AR positive category. (C). AR negative patients compared AR positive patients have a higher rate of disease progression as determined by cumulative survival analysis. (D) AR negative AA patients with basal subtypes have a higher rate of disease progression, even compared to whites with the same tumor subtype. Log-Rank test was used to calculate P values, and significance was determined p<0.05. (E). Kaplan Meier plot shows the overall survival probability in AR-positive and AR-negative patients. (F). Kaplan Meier plot shows the overall survival probability in Whites and African American AR-negative patients.</p

AR status is significantly different between race groups and among molecular subtypes.

<p>(A). AA women have more AR-negative tumor types in each molecular subtype. (B). Within the AR-negative subtypes, there are significantly higher proportions of TNBC basal-like. (C). All TNBC samples were subjected to “Vanderbilt” subtypes. AAs, compared to White AR-negative QNBC patients, had more BL1 (24% v 17%), BL2 (16% v 12%), and IM (24% v 19%) subtypes. Inversely, AR-negative White QNBC patients had more mesenchymal (M) (25% v 20%), mesenchymal stem-like (MSL) (12% v 8%), and unstable (UNS) (14% vs 8%) subtypes compared to AR-negative QNBC AA TNBC patients.</p