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First published online 11 June 2008
doi: 10.1242/dev.019018

Development 135, 2403-2413 (2008)
Published by The Company of Biologists 2008
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Patterns of cell signaling pathway activation that characterize mammary development

Eran R. Andrechek, Seiichi Mori, Rachel E. Rempel, Jeffrey T. Chang and Joseph R. Nevins*

Duke Institute for Genome Sciences and Policy, Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, NC 27710, USA.


Figure 1
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  		Fig. 1. Mammary gland development. (A) Schematic illustrating the development of the mouse mammary gland. Each stage of the schematic is accompanied by (B) matched timepoints of mammary glands in wholemount preparations and (C) histological sections. Insets in the histological panels show (from left to right) examples of immunohistochemistry for {alpha} smooth muscle actin to highlight the cap cells (puberty), PNCA to illustrate rapid growth (pregnant) and TUNEL to illustrate regulated cell death (involution).

 

Figure 2
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  		Fig. 2. Unsupervised analysis of mouse mammary gland development. (A) The developmental dataset including virgin (V) at 10 weeks and 12 weeks of age, pregnancy (P) at 1, 2, 3, 8.5, 12.5, 14.5 and 17.5 days post coitum, lactation (Lac) at 1, 3 and 7 days following partition, and involution (Inv) samples at days 1-4 and 20 following weaning were used in unsupervised clustering. The various clusters denoting involution, lactation, early and late pregnancy that were used in a search of gene ontology are indicated on the right and are denoted A-D. (B) The pubertal dataset including samples from 3 to 7 weeks of development, as also used in unsupervised clustering.

 

Figure 3
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  		Fig. 3. Supervised clustering of mouse mammary gland development. The developmental dataset used in Fig. 2A was analyzed through supervised clustering. Virgin timepoints are measured in weeks, the remainder in days.

 

Figure 4
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  		Fig. 4. Gene set enrichment during mouse mammary development. (A) Lactation (days 1, 3 and 7) and involution (days 1-4) samples were used in GSEA. An example of the enrichment analysis is shown with the random walk for the androgen-regulated gene set as well as the heatmap of the individual genes that compose the gene set. (B) ASSESS, a version of GSEA, was applied to the same data with the normalized enrichment scores being reported on a sample-by-sample basis for each gene set. Results from selected gene sets are shown. (C) In addition, the pubertal dataset was examined, with the two phenotypic classes based on the differential sample clustering from Fig. 2B, and the normalized enrichment scores are shown for a number of gene sets.

 

Figure 5
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  		Fig. 5. Pathway activation probabilities. (A) The probability of pathway activation was examined in the developmental and pubertal datasets. STAT3 and p63, well-established mammary markers, were initially used to validate this method in the mammary development dataset. (B) In addition, a variety of genetic pathways were analyzed for their probability of activation in the developmental dataset, including MYC, β-catenin, RAS, SRC, a knockout signature for Rb, E2F1, E2F2, E2F3 and E2F4. (C) Other phenotypic and genetic pathways were also examined for the probability of their activation including TNF, RHOA, TGFβ, basal/luminal status, endotoxin infection and an immune signature. (D) In addition, the pubertal data were subjected to the same analysis and relevant results are shown.

 

Figure 6
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  		Fig. 6. Mammary outgrowth is defective in E2F mutant mice. (A) Wholemounts from wild-type, E2f1-knockout, E2f3 heterozygous and E2f4-knockout mice are shown at 4 and 8 weeks of age. (B) The extent of mammary epithelial outgrowth was quantitated at 4 weeks of development. Relative to the control, there was a significant difference in E2f1-knockout (P=0.0017), E2f3 heterozygous (P<0.0001) and E2f4-knockout (P<0.0001) mice. This outgrowth analysis was repeated at 8 weeks of age, when the E2f3-knockout and E2f4-knockout exhibit a growth delay (P=0.059 and P=0.02, respectively) relative to the control. In addition, ductal branching was quantitated at 8 weeks and was significant for each of the E2F mutant strains, except the E2f2-knockout mice [P=0.05 (E2f1), 0.00008 (E2f3 heterozygous), 0.0003 (E2f3 knockout) and 0.001 (E2f4 knockout)]. (C) Transplants of control and E2F mutant mammary epithelium in nu/nu recipients as shown in a wholemount analysis. (D) Quantitation of transplant outgrowth in E2F mutants relative to wild-type control. E2f1-knockout ductal extension was reduced (to 74% of control, P=0.046), whereas no defects were observed for E2f2 knockouts. E2f3-knockout and E2f3 heterozygous mice had 36% (P=0.014) and 78% growth (P=0.043), respectively, of wild-type growth. E2f4 knockouts were most severely affected with only 23% of control growth (P=0.010). Asterisk denotes statistical significance.

 

Figure 7
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  		Fig. 7. Apoptotic delays during involution in E2f3 mutant mice. (A) Involution in the wild-type control, E2f1-knockout and E2f3 heterozygous samples. (B) To examine apoptosis in the wild type and E2f3 mutant, a TUNEL analysis was conducted at day 2 and day 3 of involution. TUNEL-positive cells stain brown and the sections are lightly counterstained with Hematoxylin. (C) The results of the TUNEL staining were quantitated, with the day 2 and day 3 differences being significant (P<0.0001 and P=0.0073, respectively). (D) An involution signature from a wild-type mammary involution dataset was generated and the probability of fitting the signature was assessed for the wild type and E2f3 mutant at successive days of involution. Red indicates a high probability of matching the involution day 4 signature; blue indicates a high probability of matching the involution day 1 signature.

 

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