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Published in: Breast Cancer Research 1/2015

Open Access 01-12-2015 | Research article

HDAC6 activity is a non-oncogene addiction hub for inflammatory breast cancers

Authors: Preeti Putcha, Jiyang Yu, Ruth Rodriguez-Barrueco, Laura Saucedo-Cuevas, Patricia Villagrasa, Eva Murga-Penas, Steven N. Quayle, Min Yang, Veronica Castro, David Llobet-Navas, Daniel Birnbaum, Pascal Finetti, Wendy A. Woodward, François Bertucci, Mary L. Alpaugh, Andrea Califano, Jose Silva

Published in: Breast Cancer Research | Issue 1/2015

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Abstract

Introduction

Inflammatory breast cancer (IBC) is the most lethal form of breast cancers with a 5-year survival rate of only 40 %. Despite its lethality, IBC remains poorly understood which has greatly limited its therapeutic management. We thus decided to utilize an integrative functional genomic strategy to identify the Achilles’ heel of IBC cells.

Methods

We have pioneered the development of genetic tools as well as experimental and analytical strategies to perform RNAi-based loss-of-function studies at a genome-wide level. Importantly, we and others have demonstrated that these functional screens are able to identify essential functions linked to certain cancer phenotypes. Thus, we decided to use this approach to identify IBC specific sensitivities.

Results

We identified and validated HDAC6 as a functionally necessary gene to maintain IBC cell viability, while being non-essential for other breast cancer subtypes. Importantly, small molecule inhibitors for HDAC6 already exist and are in clinical trials for other tumor types. We thus demonstrated that Ricolinostat (ACY1215), a leading HDAC6 inhibitor, efficiently controls IBC cell proliferation both in vitro and in vivo. Critically, functional HDAC6 dependency is not associated with genomic alterations at its locus and thus represents a non-oncogene addiction. Despite HDAC6 not being overexpressed, we found that its activity is significantly higher in IBC compared to non-IBC cells, suggesting a possible rationale supporting the observed dependency.

Conclusion

Our finding that IBC cells are sensitive to HDAC6 inhibition provides a foundation to rapidly develop novel, efficient, and well-tolerated targeted therapy strategies for IBC patients.
Appendix
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Literature
1.
go back to reference Hance KW, Anderson WF, Devesa SS, Young HA, Levine PH. Trends in inflammatory breast carcinoma incidence and survival: the surveillance, epidemiology, and end results program at the National Cancer Institute. J Natl Cancer Inst. 2005;97(13):966–75.CrossRefPubMed Hance KW, Anderson WF, Devesa SS, Young HA, Levine PH. Trends in inflammatory breast carcinoma incidence and survival: the surveillance, epidemiology, and end results program at the National Cancer Institute. J Natl Cancer Inst. 2005;97(13):966–75.CrossRefPubMed
2.
go back to reference Matro JM, Li T, Cristofanilli M, Hughes ME, Ottesen RA, Weeks JC, et al. Inflammatory Breast Cancer Management in the National Comprehensive Cancer Network: The Disease, Recurrence Pattern, and Outcome. Clin Breast Cancer. 2014. Matro JM, Li T, Cristofanilli M, Hughes ME, Ottesen RA, Weeks JC, et al. Inflammatory Breast Cancer Management in the National Comprehensive Cancer Network: The Disease, Recurrence Pattern, and Outcome. Clin Breast Cancer. 2014.
3.
go back to reference van Uden DJ, van Laarhoven HW, Westenberg AH, de Wilt JH, Blanken-Peeters CF. Inflammatory breast cancer: an overview. Crit Rev Oncol Hematol. 2015;93(2):116–26.CrossRefPubMed van Uden DJ, van Laarhoven HW, Westenberg AH, de Wilt JH, Blanken-Peeters CF. Inflammatory breast cancer: an overview. Crit Rev Oncol Hematol. 2015;93(2):116–26.CrossRefPubMed
4.
go back to reference Dawood S, Ueno NT, Cristofanilli M. The medical treatment of inflammatory breast cancer. Semin Oncol. 2008;35(1):64–71.CrossRefPubMed Dawood S, Ueno NT, Cristofanilli M. The medical treatment of inflammatory breast cancer. Semin Oncol. 2008;35(1):64–71.CrossRefPubMed
6.
go back to reference Weinstein IB, Joe AK. Mechanisms of disease: Oncogene addiction--a rationale for molecular targeting in cancer therapy. Nat Clin Pract Oncol. 2006;3(8):448–57.CrossRefPubMed Weinstein IB, Joe AK. Mechanisms of disease: Oncogene addiction--a rationale for molecular targeting in cancer therapy. Nat Clin Pract Oncol. 2006;3(8):448–57.CrossRefPubMed
7.
go back to reference Houchens NW, Merajver SD. Molecular determinants of the inflammatory breast cancer phenotype. Oncology (Williston Park). 2008;22(14):1556–61. discussion 1561, 1565-1558, 1576. Houchens NW, Merajver SD. Molecular determinants of the inflammatory breast cancer phenotype. Oncology (Williston Park). 2008;22(14):1556–61. discussion 1561, 1565-1558, 1576.
8.
go back to reference Bertucci F, Finetti P, Vermeulen P, Van Dam P, Dirix L, Birnbaum D, et al. Genomic profiling of inflammatory breast cancer: a review. Breast. 2014;23(5):538–45.CrossRefPubMed Bertucci F, Finetti P, Vermeulen P, Van Dam P, Dirix L, Birnbaum D, et al. Genomic profiling of inflammatory breast cancer: a review. Breast. 2014;23(5):538–45.CrossRefPubMed
9.
go back to reference Silva JM, Li MZ, Chang K, Ge W, Golding MC, Rickles RJ, et al. Second-generation shRNA libraries covering the mouse and human genomes. Nat Genet. 2005;37(11):1281–8.CrossRefPubMed Silva JM, Li MZ, Chang K, Ge W, Golding MC, Rickles RJ, et al. Second-generation shRNA libraries covering the mouse and human genomes. Nat Genet. 2005;37(11):1281–8.CrossRefPubMed
10.
go back to reference Paddison PJ, Silva JM, Conklin DS, Schlabach M, Li M, Aruleba S, et al. A resource for large-scale RNA-interference-based screens in mammals. Nature. 2004;428(6981):427–31.CrossRefPubMed Paddison PJ, Silva JM, Conklin DS, Schlabach M, Li M, Aruleba S, et al. A resource for large-scale RNA-interference-based screens in mammals. Nature. 2004;428(6981):427–31.CrossRefPubMed
11.
go back to reference Silva JM, Ezhkova E, Silva J, Heart S, Castillo M, Campos Y, et al. Cyfip1 is a putative invasion suppressor in epithelial cancers. Cell. 2009;137(6):1047–61.CrossRefPubMedPubMedCentral Silva JM, Ezhkova E, Silva J, Heart S, Castillo M, Campos Y, et al. Cyfip1 is a putative invasion suppressor in epithelial cancers. Cell. 2009;137(6):1047–61.CrossRefPubMedPubMedCentral
12.
go back to reference Silva JM, Marran K, Parker JS, Silva J, Golding M, Schlabach MR, et al. Profiling essential genes in human mammary cells by multiplex RNAi screening. Science. 2008;319(5863):617–20.CrossRefPubMedPubMedCentral Silva JM, Marran K, Parker JS, Silva J, Golding M, Schlabach MR, et al. Profiling essential genes in human mammary cells by multiplex RNAi screening. Science. 2008;319(5863):617–20.CrossRefPubMedPubMedCentral
13.
go back to reference Rodriguez-Barrueco R, Marshall N, Silva JM. Pooled shRNA screenings: experimental approach. Methods Mol Biol. 2013;980:353–70.CrossRefPubMed Rodriguez-Barrueco R, Marshall N, Silva JM. Pooled shRNA screenings: experimental approach. Methods Mol Biol. 2013;980:353–70.CrossRefPubMed
14.
go back to reference Yu J, Putcha P, Califano A, Silva JM. Pooled shRNA screenings: computational analysis. Methods Mol Biol. 2013;980:371–84.CrossRefPubMed Yu J, Putcha P, Califano A, Silva JM. Pooled shRNA screenings: computational analysis. Methods Mol Biol. 2013;980:371–84.CrossRefPubMed
15.
go back to reference Marcotte R, Brown KR, Suarez F, Sayad A, Karamboulas K, Krzyzanowski PM, et al. Essential gene profiles in breast, pancreatic, and ovarian cancer cells. Cancer Discov. 2012;2(2):172–89.CrossRefPubMed Marcotte R, Brown KR, Suarez F, Sayad A, Karamboulas K, Krzyzanowski PM, et al. Essential gene profiles in breast, pancreatic, and ovarian cancer cells. Cancer Discov. 2012;2(2):172–89.CrossRefPubMed
16.
go back to reference Brough R, Frankum JR, Sims D, Mackay A, Mendes-Pereira AM, Bajrami I, et al. Functional viability profiles of breast cancer. Cancer Discov. 2011;1(3):260–73.CrossRefPubMedPubMedCentral Brough R, Frankum JR, Sims D, Mackay A, Mendes-Pereira AM, Bajrami I, et al. Functional viability profiles of breast cancer. Cancer Discov. 2011;1(3):260–73.CrossRefPubMedPubMedCentral
17.
go back to reference Lord CJ, McDonald S, Swift S, Turner NC, Ashworth A. A high-throughput RNA interference screen for DNA repair determinants of PARP inhibitor sensitivity. DNA Repair (Amst). 2008;7(12):2010–9.CrossRef Lord CJ, McDonald S, Swift S, Turner NC, Ashworth A. A high-throughput RNA interference screen for DNA repair determinants of PARP inhibitor sensitivity. DNA Repair (Amst). 2008;7(12):2010–9.CrossRef
18.
go back to reference Kawaguchi Y, Kovacs JJ, McLaurin A, Vance JM, Ito A, Yao TP. The deacetylase HDAC6 regulates aggresome formation and cell viability in response to misfolded protein stress. Cell. 2003;115(6):727–38.CrossRefPubMed Kawaguchi Y, Kovacs JJ, McLaurin A, Vance JM, Ito A, Yao TP. The deacetylase HDAC6 regulates aggresome formation and cell viability in response to misfolded protein stress. Cell. 2003;115(6):727–38.CrossRefPubMed
19.
go back to reference Matthias P, Yoshida M, Khochbin S. HDAC6 a new cellular stress surveillance factor. Cell Cycle. 2008;7(1):7–10.CrossRefPubMed Matthias P, Yoshida M, Khochbin S. HDAC6 a new cellular stress surveillance factor. Cell Cycle. 2008;7(1):7–10.CrossRefPubMed
20.
go back to reference Boyault C, Zhang Y, Fritah S, Caron C, Gilquin B, Kwon SH, et al. HDAC6 controls major cell response pathways to cytotoxic accumulation of protein aggregates. Genes Dev. 2007;21(17):2172–81.CrossRefPubMedPubMedCentral Boyault C, Zhang Y, Fritah S, Caron C, Gilquin B, Kwon SH, et al. HDAC6 controls major cell response pathways to cytotoxic accumulation of protein aggregates. Genes Dev. 2007;21(17):2172–81.CrossRefPubMedPubMedCentral
21.
go back to reference Santo L, Hideshima T, Kung AL, Tseng JC, Tamang D, Yang M, et al. Preclinical activity, pharmacodynamic, and pharmacokinetic properties of a selective HDAC6 inhibitor, ACY-1215, in combination with bortezomib in multiple myeloma. Blood. 2012;119(11):2579–89.CrossRefPubMedPubMedCentral Santo L, Hideshima T, Kung AL, Tseng JC, Tamang D, Yang M, et al. Preclinical activity, pharmacodynamic, and pharmacokinetic properties of a selective HDAC6 inhibitor, ACY-1215, in combination with bortezomib in multiple myeloma. Blood. 2012;119(11):2579–89.CrossRefPubMedPubMedCentral
22.
go back to reference Sims D, Mendes-Pereira AM, Frankum J, Burgess D, Cerone MA, Lombardelli C, et al. High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing. Genome Biol. 2011;12(10):R104.CrossRefPubMedPubMedCentral Sims D, Mendes-Pereira AM, Frankum J, Burgess D, Cerone MA, Lombardelli C, et al. High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing. Genome Biol. 2011;12(10):R104.CrossRefPubMedPubMedCentral
23.
go back to reference Bassik MC, Lebbink RJ, Churchman LS, Ingolia NT, Patena W, LeProust EM, et al. Rapid creation and quantitative monitoring of high coverage shRNA libraries. Nat Methods. 2009;6(6):443–5.CrossRefPubMedPubMedCentral Bassik MC, Lebbink RJ, Churchman LS, Ingolia NT, Patena W, LeProust EM, et al. Rapid creation and quantitative monitoring of high coverage shRNA libraries. Nat Methods. 2009;6(6):443–5.CrossRefPubMedPubMedCentral
24.
go back to reference Fellmann C, Zuber J, McJunkin K, Chang K, Malone CD, Dickins RA, et al. Functional identification of optimized RNAi triggers using a massively parallel sensor assay. Mol Cell. 2011;41(6):733–46.CrossRefPubMedPubMedCentral Fellmann C, Zuber J, McJunkin K, Chang K, Malone CD, Dickins RA, et al. Functional identification of optimized RNAi triggers using a massively parallel sensor assay. Mol Cell. 2011;41(6):733–46.CrossRefPubMedPubMedCentral
25.
go back to reference Baldi P, Long AD. A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes. Bioinformatics. 2001;17(6):509–19.CrossRefPubMed Baldi P, Long AD. A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes. Bioinformatics. 2001;17(6):509–19.CrossRefPubMed
26.
go back to reference Chang CW, Cheng WC, Chen CR, Shu WY, Tsai ML, Huang CL, et al. Identification of human housekeeping genes and tissue-selective genes by microarray meta-analysis. PLoS One. 2011;6(7):e22859.CrossRefPubMedPubMedCentral Chang CW, Cheng WC, Chen CR, Shu WY, Tsai ML, Huang CL, et al. Identification of human housekeeping genes and tissue-selective genes by microarray meta-analysis. PLoS One. 2011;6(7):e22859.CrossRefPubMedPubMedCentral
27.
go back to reference Stouffer SA, Suchman EA, DeVinney LC, Star SA, Williams RMJ. Adjustment During Army Life, vol. 1. Princeton: Princeton University Press; 1949. Stouffer SA, Suchman EA, DeVinney LC, Star SA, Williams RMJ. Adjustment During Army Life, vol. 1. Princeton: Princeton University Press; 1949.
28.
go back to reference da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.CrossRef da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.CrossRef
29.
go back to reference Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545–50.CrossRefPubMedPubMedCentral Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545–50.CrossRefPubMedPubMedCentral
30.
go back to reference Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R, et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics. 2006;7 Suppl 1:S7.CrossRefPubMed Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R, et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics. 2006;7 Suppl 1:S7.CrossRefPubMed
31.
go back to reference Cancer Genome Atlas N. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70.CrossRef Cancer Genome Atlas N. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70.CrossRef
32.
go back to reference Cancer Genome Atlas Research N. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511(7511):543–50.CrossRef Cancer Genome Atlas Research N. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 2014;511(7511):543–50.CrossRef
33.
go back to reference Cancer Genome Atlas N. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330–7.CrossRef Cancer Genome Atlas N. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330–7.CrossRef
34.
go back to reference Piovan E, Yu J, Tosello V, Herranz D, Ambesi-Impiombato A, Da Silva AC, et al. Direct reversal of glucocorticoid resistance by AKT inhibition in acute lymphoblastic leukemia. Cancer Cell. 2013;24(6):766–76.CrossRefPubMed Piovan E, Yu J, Tosello V, Herranz D, Ambesi-Impiombato A, Da Silva AC, et al. Direct reversal of glucocorticoid resistance by AKT inhibition in acute lymphoblastic leukemia. Cancer Cell. 2013;24(6):766–76.CrossRefPubMed
35.
go back to reference Lefebvre C, Rajbhandari P, Alvarez MJ, Bandaru P, Lim WK, Sato M, et al. A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers. Mol Syst Biol. 2010;6:377.CrossRefPubMedPubMedCentral Lefebvre C, Rajbhandari P, Alvarez MJ, Bandaru P, Lim WK, Sato M, et al. A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers. Mol Syst Biol. 2010;6:377.CrossRefPubMedPubMedCentral
36.
go back to reference Carro MS, Lim WK, Alvarez MJ, Bollo RJ, Zhao X, Snyder EY, et al. The transcriptional network for mesenchymal transformation of brain tumours. Nature. 2010;463(7279):318–25.CrossRefPubMed Carro MS, Lim WK, Alvarez MJ, Bollo RJ, Zhao X, Snyder EY, et al. The transcriptional network for mesenchymal transformation of brain tumours. Nature. 2010;463(7279):318–25.CrossRefPubMed
37.
go back to reference Efron B, Tibshirani R. On Testing the Significance of Sets of Genes. Ann Appl Stat. 2007;1(1):107–29.CrossRef Efron B, Tibshirani R. On Testing the Significance of Sets of Genes. Ann Appl Stat. 2007;1(1):107–29.CrossRef
38.
go back to reference Rodriguez-Barrueco R, Yu J, Saucedo-Cuevas LP, Olivan M, Llobet-Navas D, Putcha P, et al. Inhibition of the autocrine IL-6-JAK2-STAT3-calprotectin axis as targeted therapy for HR-/HER2+ breast cancers. Genes Dev. 2015.Genes Dev. 2015;1;29(15):1631-48. doi: 10.1101/gad.262642.115. Epub 2015 Jul. Rodriguez-Barrueco R, Yu J, Saucedo-Cuevas LP, Olivan M, Llobet-Navas D, Putcha P, et al. Inhibition of the autocrine IL-6-JAK2-STAT3-calprotectin axis as targeted therapy for HR-/HER2+ breast cancers. Genes Dev. 2015.Genes Dev. 2015;1;29(15):1631-48. doi: 10.​1101/​gad.​262642.​115. Epub 2015 Jul.
39.
go back to reference Wang T, Wei JJ, Sabatini DM, Lander ES. Genetic screens in human cells using the CRISPR-Cas9 system. Science. 2014;343(6166):80–4.CrossRefPubMed Wang T, Wei JJ, Sabatini DM, Lander ES. Genetic screens in human cells using the CRISPR-Cas9 system. Science. 2014;343(6166):80–4.CrossRefPubMed
40.
go back to reference Schlabach MR, Luo J, Solimini NL, Hu G, Xu Q, Li MZ, et al. Cancer proliferation gene discovery through functional genomics. Science. 2008;319(5863):620–4.CrossRefPubMedPubMedCentral Schlabach MR, Luo J, Solimini NL, Hu G, Xu Q, Li MZ, et al. Cancer proliferation gene discovery through functional genomics. Science. 2008;319(5863):620–4.CrossRefPubMedPubMedCentral
41.
go back to reference Scholl C, Frohling S, Dunn IF, Schinzel AC, Barbie DA, Kim SY, et al. Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells. Cell. 2009;137(5):821–34.CrossRefPubMed Scholl C, Frohling S, Dunn IF, Schinzel AC, Barbie DA, Kim SY, et al. Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells. Cell. 2009;137(5):821–34.CrossRefPubMed
42.
go back to reference Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 2006;10(6):515–27.CrossRefPubMedPubMedCentral Neve RM, Chin K, Fridlyand J, Yeh J, Baehner FL, Fevr T, et al. A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell. 2006;10(6):515–27.CrossRefPubMedPubMedCentral
43.
go back to reference Luo B, Cheung HW, Subramanian A, Sharifnia T, Okamoto M, Yang X, et al. Highly parallel identification of essential genes in cancer cells. Proc Natl Acad Sci U S A. 2008;105(51):20380–5.CrossRefPubMedPubMedCentral Luo B, Cheung HW, Subramanian A, Sharifnia T, Okamoto M, Yang X, et al. Highly parallel identification of essential genes in cancer cells. Proc Natl Acad Sci U S A. 2008;105(51):20380–5.CrossRefPubMedPubMedCentral
44.
go back to reference Hubbert C, Guardiola A, Shao R, Kawaguchi Y, Ito A, Nixon A, et al. HDAC6 is a microtubule-associated deacetylase. Nature. 2002;417(6887):455–8.CrossRefPubMed Hubbert C, Guardiola A, Shao R, Kawaguchi Y, Ito A, Nixon A, et al. HDAC6 is a microtubule-associated deacetylase. Nature. 2002;417(6887):455–8.CrossRefPubMed
45.
go back to reference De Vreese R, Verhaeghe T, Desmet T, D’Hooghe M. Potent and selective HDAC6 inhibitory activity of N-(4-hydroxycarbamoylbenzyl)-1,2,4,9-tetrahydro-3-thia-9-azafluorenes as novel sulfur analogues of Tubastatin A. Chem Commun. 2013;49(36):3775–7.CrossRef De Vreese R, Verhaeghe T, Desmet T, D’Hooghe M. Potent and selective HDAC6 inhibitory activity of N-(4-hydroxycarbamoylbenzyl)-1,2,4,9-tetrahydro-3-thia-9-azafluorenes as novel sulfur analogues of Tubastatin A. Chem Commun. 2013;49(36):3775–7.CrossRef
46.
go back to reference Klopp AH, Lacerda L, Gupta A, Debeb BG, Solley T, Li L, et al. Mesenchymal stem cells promote mammosphere formation and decrease E-cadherin in normal and malignant breast cells. PLoS One. 2010;5(8):e12180.CrossRefPubMedPubMedCentral Klopp AH, Lacerda L, Gupta A, Debeb BG, Solley T, Li L, et al. Mesenchymal stem cells promote mammosphere formation and decrease E-cadherin in normal and malignant breast cells. PLoS One. 2010;5(8):e12180.CrossRefPubMedPubMedCentral
47.
go back to reference Alpaugh ML, Tomlinson JS, Shao ZM, Barsky SH. A novel human xenograft model of inflammatory breast cancer. Cancer Res. 1999;59(20):5079–84.PubMed Alpaugh ML, Tomlinson JS, Shao ZM, Barsky SH. A novel human xenograft model of inflammatory breast cancer. Cancer Res. 1999;59(20):5079–84.PubMed
48.
go back to reference Xiao Y, Ye Y, Yearsley K, Jones S, Barsky SH. The lymphovascular embolus of inflammatory breast cancer expresses a stem cell-like phenotype. Am J Pathol. 2008;173(2):561–74.CrossRefPubMedPubMedCentral Xiao Y, Ye Y, Yearsley K, Jones S, Barsky SH. The lymphovascular embolus of inflammatory breast cancer expresses a stem cell-like phenotype. Am J Pathol. 2008;173(2):561–74.CrossRefPubMedPubMedCentral
49.
go back to reference Bekhouche I, Finetti P, Adelaide J, Ferrari A, Tarpin C, Charafe-Jauffret E, et al. High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes. PLoS One. 2011;6(2):e16950.CrossRefPubMedPubMedCentral Bekhouche I, Finetti P, Adelaide J, Ferrari A, Tarpin C, Charafe-Jauffret E, et al. High-resolution comparative genomic hybridization of inflammatory breast cancer and identification of candidate genes. PLoS One. 2011;6(2):e16950.CrossRefPubMedPubMedCentral
50.
go back to reference Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A. Reverse engineering of regulatory networks in human B cells. Nat Genet. 2005;37(4):382–90.CrossRefPubMed Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A. Reverse engineering of regulatory networks in human B cells. Nat Genet. 2005;37(4):382–90.CrossRefPubMed
51.
go back to reference Aytes A, Mitrofanova A, Lefebvre C, Alvarez MJ, Castillo-Martin M, Zheng T, et al. Cross-species regulatory network analysis identifies a synergistic interaction between FOXM1 and CENPF that drives prostate cancer malignancy. Cancer Cell. 2014;25(5):638–51.CrossRefPubMedPubMedCentral Aytes A, Mitrofanova A, Lefebvre C, Alvarez MJ, Castillo-Martin M, Zheng T, et al. Cross-species regulatory network analysis identifies a synergistic interaction between FOXM1 and CENPF that drives prostate cancer malignancy. Cancer Cell. 2014;25(5):638–51.CrossRefPubMedPubMedCentral
52.
53.
go back to reference Bertucci F, Finetti P, Rougemont J, Charafe-Jauffret E, Cervera N, Tarpin C, et al. Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res. 2005;65(6):2170–8.CrossRefPubMed Bertucci F, Finetti P, Rougemont J, Charafe-Jauffret E, Cervera N, Tarpin C, et al. Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res. 2005;65(6):2170–8.CrossRefPubMed
54.
go back to reference Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–52.CrossRefPubMed Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–52.CrossRefPubMed
55.
go back to reference Yan J. Interplay between HDAC6 and its interacting partners: essential roles in the aggresome-autophagy pathway and neurodegenerative diseases. DNA Cell Biol. 2014;33(9):567–80.CrossRefPubMed Yan J. Interplay between HDAC6 and its interacting partners: essential roles in the aggresome-autophagy pathway and neurodegenerative diseases. DNA Cell Biol. 2014;33(9):567–80.CrossRefPubMed
56.
go back to reference Ron D, Walter P. Signal integration in the endoplasmic reticulum unfolded protein response. Nat Rev Mol Cell Biol. 2007;8(7):519–29.CrossRefPubMed Ron D, Walter P. Signal integration in the endoplasmic reticulum unfolded protein response. Nat Rev Mol Cell Biol. 2007;8(7):519–29.CrossRefPubMed
58.
go back to reference Lee JY, Nagano Y, Taylor JP, Lim KL, Yao TP. Disease-causing mutations in parkin impair mitochondrial ubiquitination, aggregation, and HDAC6-dependent mitophagy. J Cell Biol. 2010;189(4):671–9.CrossRefPubMedPubMedCentral Lee JY, Nagano Y, Taylor JP, Lim KL, Yao TP. Disease-causing mutations in parkin impair mitochondrial ubiquitination, aggregation, and HDAC6-dependent mitophagy. J Cell Biol. 2010;189(4):671–9.CrossRefPubMedPubMedCentral
60.
go back to reference Shokolenko I, Venediktova N, Bochkareva A, Wilson GL, Alexeyev MF. Oxidative stress induces degradation of mitochondrial DNA. Nucleic Acids Res. 2009;37(8):2539–48.CrossRefPubMedPubMedCentral Shokolenko I, Venediktova N, Bochkareva A, Wilson GL, Alexeyev MF. Oxidative stress induces degradation of mitochondrial DNA. Nucleic Acids Res. 2009;37(8):2539–48.CrossRefPubMedPubMedCentral
61.
go back to reference Evan GI, Vousden KH. Proliferation, cell cycle and apoptosis in cancer. Nature. 2001;411(6835):342–8.CrossRefPubMed Evan GI, Vousden KH. Proliferation, cell cycle and apoptosis in cancer. Nature. 2001;411(6835):342–8.CrossRefPubMed
62.
63.
go back to reference Chen S, Zhang Y, Zhou L, Leng Y, Lin H, Kmieciak M, et al. A Bim-targeting strategy overcomes adaptive bortezomib resistance in myeloma through a novel link between autophagy and apoptosis. Blood. 2014;124(17):2687–97.CrossRefPubMedPubMedCentral Chen S, Zhang Y, Zhou L, Leng Y, Lin H, Kmieciak M, et al. A Bim-targeting strategy overcomes adaptive bortezomib resistance in myeloma through a novel link between autophagy and apoptosis. Blood. 2014;124(17):2687–97.CrossRefPubMedPubMedCentral
64.
go back to reference Hideshima T, Richardson PG, Anderson KC. Mechanism of action of proteasome inhibitors and deacetylase inhibitors and the biological basis of synergy in multiple myeloma. Mol Cancer Ther. 2011;10(11):2034–42.CrossRefPubMedPubMedCentral Hideshima T, Richardson PG, Anderson KC. Mechanism of action of proteasome inhibitors and deacetylase inhibitors and the biological basis of synergy in multiple myeloma. Mol Cancer Ther. 2011;10(11):2034–42.CrossRefPubMedPubMedCentral
65.
go back to reference Kekatpure VD, Dannenberg AJ, Subbaramaiah K. HDAC6 modulates Hsp90 chaperone activity and regulates activation of aryl hydrocarbon receptor signaling. J Biol Chem. 2009;284(12):7436–45.CrossRefPubMedPubMedCentral Kekatpure VD, Dannenberg AJ, Subbaramaiah K. HDAC6 modulates Hsp90 chaperone activity and regulates activation of aryl hydrocarbon receptor signaling. J Biol Chem. 2009;284(12):7436–45.CrossRefPubMedPubMedCentral
66.
go back to reference Qian DZ, Kachhap SK, Collis SJ, Verheul HM, Carducci MA, Atadja P, et al. Class II histone deacetylases are associated with VHL-independent regulation of hypoxia-inducible factor 1 alpha. Cancer Res. 2006;66(17):8814–21.CrossRefPubMed Qian DZ, Kachhap SK, Collis SJ, Verheul HM, Carducci MA, Atadja P, et al. Class II histone deacetylases are associated with VHL-independent regulation of hypoxia-inducible factor 1 alpha. Cancer Res. 2006;66(17):8814–21.CrossRefPubMed
67.
go back to reference Hurst DR, Mehta A, Moore BP, Phadke PA, Meehan WJ, Accavitti MA, et al. Breast cancer metastasis suppressor 1 (BRMS1) is stabilized by the Hsp90 chaperone. Biochem Biophys Res Commun. 2006;348(4):1429–35.CrossRefPubMedPubMedCentral Hurst DR, Mehta A, Moore BP, Phadke PA, Meehan WJ, Accavitti MA, et al. Breast cancer metastasis suppressor 1 (BRMS1) is stabilized by the Hsp90 chaperone. Biochem Biophys Res Commun. 2006;348(4):1429–35.CrossRefPubMedPubMedCentral
68.
go back to reference Bali P, Pranpat M, Bradner J, Balasis M, Fiskus W, Guo F, et al. Inhibition of histone deacetylase 6 acetylates and disrupts the chaperone function of heat shock protein 90: a novel basis for antileukemia activity of histone deacetylase inhibitors. J Biol Chem. 2005;280(29):26729–34.CrossRefPubMed Bali P, Pranpat M, Bradner J, Balasis M, Fiskus W, Guo F, et al. Inhibition of histone deacetylase 6 acetylates and disrupts the chaperone function of heat shock protein 90: a novel basis for antileukemia activity of histone deacetylase inhibitors. J Biol Chem. 2005;280(29):26729–34.CrossRefPubMed
69.
go back to reference Fernandez SV, Robertson FM, Pei J, Aburto-Chumpitaz L, Mu Z, Chu K, et al. Inflammatory breast cancer (IBC): clues for targeted therapies. Breast Cancer Res Treat. 2013;140(1):23–33.CrossRefPubMedPubMedCentral Fernandez SV, Robertson FM, Pei J, Aburto-Chumpitaz L, Mu Z, Chu K, et al. Inflammatory breast cancer (IBC): clues for targeted therapies. Breast Cancer Res Treat. 2013;140(1):23–33.CrossRefPubMedPubMedCentral
70.
go back to reference Tinoco G, Warsch S, Gluck S, Avancha K, Montero AJ. Treating breast cancer in the 21st century: emerging biological therapies. J Cancer. 2013;4(2):117–32.CrossRefPubMedPubMedCentral Tinoco G, Warsch S, Gluck S, Avancha K, Montero AJ. Treating breast cancer in the 21st century: emerging biological therapies. J Cancer. 2013;4(2):117–32.CrossRefPubMedPubMedCentral
71.
go back to reference Marcus AI, Zhou J, O’Brate A, Hamel E, Wong J, Nivens M, et al. The synergistic combination of the farnesyl transferase inhibitor lonafarnib and paclitaxel enhances tubulin acetylation and requires a functional tubulin deacetylase. Cancer Res. 2005;65(9):3883–93.CrossRefPubMedPubMedCentral Marcus AI, Zhou J, O’Brate A, Hamel E, Wong J, Nivens M, et al. The synergistic combination of the farnesyl transferase inhibitor lonafarnib and paclitaxel enhances tubulin acetylation and requires a functional tubulin deacetylase. Cancer Res. 2005;65(9):3883–93.CrossRefPubMedPubMedCentral
Metadata
Title
HDAC6 activity is a non-oncogene addiction hub for inflammatory breast cancers
Authors
Preeti Putcha
Jiyang Yu
Ruth Rodriguez-Barrueco
Laura Saucedo-Cuevas
Patricia Villagrasa
Eva Murga-Penas
Steven N. Quayle
Min Yang
Veronica Castro
David Llobet-Navas
Daniel Birnbaum
Pascal Finetti
Wendy A. Woodward
François Bertucci
Mary L. Alpaugh
Andrea Califano
Jose Silva
Publication date
01-12-2015
Publisher
BioMed Central
Published in
Breast Cancer Research / Issue 1/2015
Electronic ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-015-0658-0

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