Subtype and pathway specific responses to anticancer compounds in breast cancer

Heiser, Laura M.; Sadanandam, Anguraj; Kuo, Wen‐Lin; Benz, Stephen C.; Goldstein, Theodore C.; Ng, Sam; Gibb, William J.; Wang, Nicholas J.; Ziyad, Safiyyah; Tong, Frances; Bayani, Nora; Hu, Zhi; Billig, Jessica I.; Dueregger, Andrea; Lewis, Sophia; Jakkula, Lakshmi R.; Korkola, James E.; Durinck, Steffen; Pepin, FranÃ§ois; Guan, Yinghui; Purdom, Elizabeth; Neuvial, Pierre; Bengtsson, Henrik; Wood, Kenneth W.; Smith, Peter G.; Vassilev, Lyubomir T.; Hennessy, Bryan T.; Greshock, Joel; Bachman, Kurtis E.; Hardwicke, Mary Ann; Park, John W.; Marton, Laurence J.; Wolf, Denise M.; Collisson, Eric A.; Neve, Richard M.; Mills, Gordon B.; Speed, Terence P.; Feiler, Heidi S.; Wooster, Richard; Haussler, David; Stuart, Joshua M.; Gray, Joe W.; Spellman, Paul T.

doi:10.1073/pnas.1018854108

Cited by 426 publications

(577 citation statements)

References 35 publications

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“…1B) and in basal and claudin-low subtypes in the cell lines, molecularly classified using PAM50 (a breast cancer intrinsic classifier using the RT-qPCR assay for 50 genes) (Fig. S1A) (24). Finally, we measured SET mRNA expression by qPCR in a limited set of primary human breast tumor samples with patient-matched adjacent normal tissue and found that 60% of samples showed higher expression of SET in tumor compared with the matched normal (Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Interestingly, we found that CIP2A overexpression correlated with the triple negative breast cancer subtype, a result that was further supported with RNA-seq data from human breast cancer cell lines. This result is important, as the claudin-low breast cancer subtype associates highly with up-regulation of the MYC/ MYC-associated factor X network (24). This correlation suggests that CIP2A could potentially be used as a diagnostic biomarker for more malignant, MYC-driven tumor types.…”

Section: Discussionmentioning

confidence: 97%

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Targeting c-MYC by antagonizing PP2A inhibitors in breast cancer

Janghorban¹,

Farrell²,

Allen-Petersen³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

165

175

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The transcription factor c-MYC is stabilized and activated by phosphorylation at serine 62 (S62) in breast cancer. Protein phosphatase 2A (PP2A) is a critical negative regulator of c-MYC through its ability to dephosphorylate S62. By inactivating c-MYC and other key signaling pathways, PP2A plays an important tumor suppressor function. Two endogenous inhibitors of PP2A, I2PP2A, Inhibitor-2 of PP2A (SET oncoprotein) and cancerous inhibitor of PP2A (CIP2A), inactivate PP2A and are overexpressed in several tumor types. Here we show that SET is overexpressed in about 50-60% and CIP2A in about 90% of breast cancers. Knockdown of SET or CIP2A reduces the tumorigenic potential of breast cancer cell lines both in vitro and in vivo. Treatment of breast cancer cells in vitro or in vivo with OP449, a novel SET antagonist, also decreases the tumorigenic potential of breast cancer cells and induces apoptosis. We show that this is, at least in part, due to decreased S62 phosphorylation of c-MYC and reduced c-MYC activity and target gene expression. Because of the ubiquitous expression and tumor suppressor activity of PP2A in cells, as well as the critical role of c-MYC in human cancer, we propose that activation of PP2A (here accomplished through antagonizing endogenous inhibitors) could be a novel antitumor strategy to posttranslationally target c-MYC in breast cancer.breast cancer therapy | phosphatase activator T he c-MYC (MYC) oncoprotein is overexpressed in human breast cancer and this is associated with poor clinical outcome (1, 2). Expression of MYC is regulated at multiple levels, including protein stability, which is increased in several cancer types (1,3,4). MYC stability is regulated in part by sequential and interdependent phosphorylation at two conserved residues, threonine 58 (T58) and serine 62 (S62) (5). MYC is phosphorylated at S62 (pS62) through the mitogen-activated protein kinase (MAPK) pathway or cyclin-dependent kinase (CDK) activation in response to growth signals and this modification increases its stability and oncogenic activity (5-8). When growth signals cease, GSK3, in a manner dependent upon prior phosphorylation at S62, phosphorylates T58 (pT58) (5, 6). T58 phosphorylation facilitates protein phosphatase 2A (PP2A)-mediated dephosphorylation of pS62 and recruitment of the E3 ubiquitin ligase SCF Fbw7 to initiate proteasomal destruction of MYC (9, 10). This process is facilitated by AXIN1, which helps nucleate a destruction complex for MYC at target gene promoters (11, 12). Our previous work has shown that MYC stability is increased in breast cancers and that this correlates with high pS62-and low pT58-MYC (4).PP2A is a ubiquitously expressed, heterotrimeric serinethreonine (S/T) phosphatase that mediates 30-50% of cellular S/T phosphatase activity (13). Target specificity of PP2A is directed by a variable regulatory (B) subunit, and we have shown that B56α is the isoform that directs PP2A to MYC (9, 13). Human cell transformation requires inhibition of PP2A activity and, in an siRNA screen, B56α, ...

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 97%

Targeting c-MYC by antagonizing PP2A inhibitors in breast cancer

Janghorban¹,

Farrell²,

Allen-Petersen³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

165

175

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show abstract

“…These gain-of-function mutations in the PI3KCA gene are found in a broad range of cancers, and they are highly enriched in breast cancer, where they are observed in 20-25% of cases (7). In addition, breast cancers with amplified HER2, which comprise ∼20% of all breast cancers, (8) are also particularly sensitive to PI3K inhibition (9)(10)(11). However, even among patients whose cancers harbor PIK3CA mutations, a significant heterogeneity of responses has been observed to PI3K inhibitors currently being tested in clinical studies (3)(4)(5).…”

mentioning

confidence: 99%

PI3K regulates MEK/ERK signaling in breast cancer via the Rac-GEF, P-Rex1

Ebi

Costa

Faber

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

178

163

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The PI3K pathway is genetically altered in excess of 70% of breast cancers, largely through PIK3CA mutation and HER2 amplification. Preclinical studies have suggested that these subsets of breast cancers are particularly sensitive to PI3K inhibitors; however, the reasons for this heightened sensitivity are mainly unknown. We investigated the signaling effects of PI3K inhibition in PIK3CA mutant and HER2 amplified breast cancers using PI3K inhibitors currently in clinical trials. Unexpectedly, we found that in PIK3CA mutant and HER2 amplified breast cancers sensitive to PI3K inhibitors, PI3K inhibition led to a rapid suppression of Rac1/p21-activated kinase (PAK)/protein kinase C-RAF (C-RAF)/ protein kinase MEK (MEK)/ERK signaling that did not involve RAS. Furthermore, PI3K inhibition led to an ERK-dependent up-regulation of the proapoptotic protein, BIM, followed by induction of apoptosis. Expression of a constitutively active form of Rac1 in these breast cancer models blocked PI3Ki-induced down-regulation of ERK phosphorylation, apoptosis, and mitigated PI3K inhibitor sensitivity in vivo. In contrast, protein kinase AKT inhibitors failed to block MEK/ERK signaling, did not upregulate BIM, and failed to induce apoptosis. Finally, we identified phosphatidylinositol 3,4,5-trisphosphate-dependent Rac exchanger 1 (P-Rex1) as the PI(3,4,5)P3-dependent guanine exchange factor for Rac1 responsible for regulation of the Rac1/C-RAF/MEK/ERK pathway in these cells. The expression level of P-Rex1 correlates with sensitivity to PI3K inhibitors in these breast cancer cell lines. Thus, PI3K inhibitors have enhanced activity in PIK3CA mutant and HER2 amplified breast cancers in which PI3K inhibition down-regulates both the AKT and Rac1/ERK pathways. In addition, P-Rex1 may serve as a biomarker to predict response to single-agent PI3K inhibitors within this subset of breast cancers.

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“…Breast cancers are comprised of distinct subtypes which may respond differently to pathway-targeted therapies; collections of breast cancer cell lines show differential responses across cell lines and show subtype-, pathway-, and genomic aberration-specific responses [8]. These observations suggest mechanisms of response and resistance which differ across cell lines.…”

Section: Application To Rppa (Reverse Phase Protein Arrays) Data Setmentioning

confidence: 99%

“…For instance, several recent studies focus on the temporal complexity and heterogeneity of single-neuron activity in the premotor and motor cortices [3] [6] [7]. Moreover, since many current and emerging cancer treatments are designed to inhibit or stimulate a specific node (or gene) in the networks and alter signaling cascades, advancing our understanding of how the system dynamics of these networks is deregulated across cancer cells and finding subgroups of genes and conditions will ultimately lead to the more effective treatment strategies [8].…”

Section: Introductionmentioning

confidence: 99%

Disentangling Multidimensional Spatio-Temporal Data into their Common and Aberrant Responses

Chang

Korkola²,

Amin

et al. 2014

Preprint

Self Cite

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With the advent of high-throughput measurement techniques, scientists and engineers are starting to grapple with massive data sets and encountering challenges with how to organize, process and extract information into meaningful structures. Multidimensional spatio-temporal biological data sets such as time series gene expression with various perturbations over different cell lines, or neural spike trains across many experimental trials, have the potential to acquire insight across multiple dimensions. For this potential to be realized, we need a suitable representation to understand the data. Since a wide range of experiments and the unknown complexity of the underlying system contribute to the heterogeneity of biological data, we propose a method based on Robust Principal Component Analysis (RPCA), which is well suited for extracting principal components when there are corrupted observations. The proposed method provides us a new representation of these data sets in terms of a common and aberrant response. This representation might help users to acquire a new insight from data. Author SummaryOne of the most exciting trends and important themes in science and engineering involves the use of high-throughput measurement data. With different dimensions, for example, various perturbations, different doses of drug or cell lines characteristics, such multidimensional data sets enable us to understand commonalities and differences across multiple dimensions. A general question is how to organize the observed data into meaningful structures and how to find an appropriate similarity measure. A natural way of viewing these complex high dimensional data sets is to examine and analyze the large-scale features and then to focus on the interesting details. With this notion, we propose an RPCA-based method which models common variations as approximately the low-rank component and anomalies as the sparse component. We show that the proposed method is able to find distinct subtypes and classify data sets in a robust way without any prior knowledge by separating these common responses and abnormal responses.

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Subtype and pathway specific responses to anticancer compounds in breast cancer

Cited by 426 publications

References 35 publications

Targeting c-MYC by antagonizing PP2A inhibitors in breast cancer

Targeting c-MYC by antagonizing PP2A inhibitors in breast cancer

PI3K regulates MEK/ERK signaling in breast cancer via the Rac-GEF, P-Rex1

Disentangling Multidimensional Spatio-Temporal Data into their Common and Aberrant Responses

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