MYC regulation of a "poor-prognosis" metastatic cancer cell state - PubMed (original) (raw)

. 2010 Feb 23;107(8):3698-703.

doi: 10.1073/pnas.0914203107. Epub 2010 Feb 4.

Ben S Wittner, Daniel Irimia, Richard J Flavin, Mathieu Lupien, Ruwanthi N Gunawardane, Clifford A Meyer, Eric S Lightcap, Pablo Tamayo, Jill P Mesirov, X Shirley Liu, Toshi Shioda, Mehmet Toner, Massimo Loda, Myles Brown, Joan S Brugge, Sridhar Ramaswamy

Affiliations

MYC regulation of a "poor-prognosis" metastatic cancer cell state

Anita Wolfer et al. Proc Natl Acad Sci U S A. 2010.

Abstract

Gene expression signatures are used in the clinic as prognostic tools to determine the risk of individual patients with localized breast tumors developing distant metastasis. We lack a clear understanding, however, of whether these correlative biomarkers link to a common biological network that regulates metastasis. We find that the c-MYC oncoprotein coordinately regulates the expression of 13 different "poor-outcome" cancer signatures. In addition, functional inactivation of MYC in human breast cancer cells specifically inhibits distant metastasis in vivo and invasive behavior in vitro of these cells. These results suggest that MYC oncogene activity (as marked by "poor-prognosis" signature expression) may be necessary for the translocation of poor-outcome human breast tumors to distant sites.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.

Fig. 1.

Molecular regulation of 13 poor-outcome human cancer signatures. (A) Thirteen different signatures (designated s1–s13), correlated with different biological processes associated with metastatic progression, reported to be prognostic in different tumor types (green). To simplify the analysis, we first created two “metagenes” by separately averaging up-regulated and down-regulated genes from each multigene poor-outcome cancer signature (s1–s13). (B_–_J) Plots displaying UP and DOWN metagenes derived from each signature in standard deviation units after (B) 17β-estradiol stimulation (red circles) versus control (blue diamonds) in MCF7 cells, (C) ERBB2 overexpression (red circles) versus control (blue diamonds) in MCF10A cells, (D) EGF stimulation (red circles) versus control (blue diamonds) in MCF10A cells, (E) DHT stimulation (red circles) versus control (blue diamonds) in LNCaP cells, (F) 17β-estradiol stimulation and CHX treatment (red circles) versus CHX treatment alone (blue diamonds) in MCF7 cells, (G) overexpression of MYC (red circles) versus vector control (blue diamonds) in MCF7 cells, (H) overexpression of ZIP (red circles) versus vector control (blue diamonds) in MCF7 cells, (I) siRNA knockdown of endogenous MYC (red circles) versus vector control (blue diamonds) in MCF7 cells, and (J) siRNA knockdown of endogenous MYC (red circles) versus vector control (blue diamonds) in MDA-MB-231 cells. Circles and diamonds represent independent replicates. s2, s7, and s9 are unidirectional signatures that have only up-regulated genes.

Fig. 2.

Fig. 2.

MYC-centered core interactome. (A) Venn diagram illustrating derivation of the core gene set. (B) A highly connected network of the 20 genes in the core gene set (orange) and 13 associated genes identified using the IPA algorithm (17). MYC is highlighted in red. (C) Statistical analysis of genome-wide MYC-binding site data obtained from MCF7 cells after stimulation with 17β-estradiol, generated using ChIP-Chip (chromatin immunoprecipitation and tiling microarrays spanning the entire nonrepetitive human genome) (26). UP and DOWN poor-outcome signature genes with at least one MYC binding site within ± 5 kb of their transcription start site (orange) versus the same for all other genes on the tiling array (green).

Fig. 3.

Fig. 3.

MDA-MB-231 primary tumorigenesis and metastasis in vivo with stable MYC knockdown. (A) Western blot for MYC protein after stable, lentiviral-mediated knockdown with two different MYC hairpins (HP1 and HP2) compared with pLKO empty vector control after serial passage in MDA-MB-231 cells. (B) Proliferation curves for empty vector control (pLKO), HP1, and HP2 cells after serial passage over 4 days, showing absorbance as a measure of cell number (n = 3, 95% CI). (C) Tumor growth of control (pLKO) and HP1 cell xenografts in NOD/SCID mice (pLKO, n = 9; HP1, n = 7; 95% CI). (D) Boxplot of the number of lung metastases per mouse in control and MYC HP1 knockdown tumor-bearing mice (pLKO, n = 9; MYC HP1, n = 7; P value calculated from the two-sided, two-sample Wilcoxon test). (E) Representative immunohistochemistry for MYC protein expression in primary and metastatic tumor sections from the outlier animal in the MYC HP1 knockdown group. (F) Representative light microscopy (H&E) and immunohistochemistry (MKI67, TUNEL, vimentin, and e-cadherin) in pLKO control and MYC HP1 knockdown primary tumors. (Scale bars: 20 μm.)

Fig. 4.

Fig. 4.

MDA-MB-231 invasion and migration in vitro with stable MYC knockdown. (A) Representative light microscopy images of control (pLKO) and MYC knockdown (MYC HP1) MDA-MB-231 breast cancer cells migrating through Matrigel-filled microcapillaries. (B) Position of individual pLKO and MYC HP1 cells invading through Matrigel-filled microcapillaries over 24 h plotted against time. (C) Bar plot representing the average invasion speed through Matrigel for pLKO and MYC HP1 cells, 13.9 ± 1.1 μm/h for pLKO (n = 33) and 9.1 ± 0.9 μm/h for MYC HP1 (n = 31) and 10.9 ± 0.7 μm/h for MYC HP2 (n = 33). P values were computed by the two-sided Walsh t test. (D) Representative light microscopy images of pLKO and MYC HP1 MDA-MB-231 breast cancer cells migrating through collagen IV–coated microcapillaries. (E) Position of individual pLKO and MYC HP1 cells migrating along collagen IV–coated microcapillaries over 12 h plotted against time. (F) Bar plot representing the average migration speed through collagen-coated microcapillaries for pLKO and MYC HP1 knockdown cells, 82.5 ± 7.5 μm/h for pLKO (n = 17) and 70.4 ± 6.4 μm/h for MYC HP1 (n = 21). P values were computed by the two-sided Walsh t test. Also see

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