Proteomic Classification of Breast Cancer

Kamel, Dalia; Brady, Bernadette; Tabchy, Adel; Mills, Gordon B.; Hennessy, Bryan T.

doi:10.2174/138945012803530080

Cited by 14 publications

(9 citation statements)

References 55 publications

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“…However, the number of distinct subtypes is increasing steadily as multiple data types are integrated. Integration of genome copy number and transcriptional profiles defines 10 subtypes [3], and adding mutation status [4], methylation pattern [5], pattern of splice variants [6], protein and phosphoprotein expression [7] and microRNA expression and pathway activity [8] may define still more subtypes. The Cancer Genome Atlas (TCGA) project and other international genomics efforts were founded to improve our understanding of the molecular landscapes of most major tumor types with the ultimate goal of increasing the precision with which individual cancers are managed.…”

Section: Introductionmentioning

confidence: 99%

Modeling precision treatment of breast cancer

et al. 2013

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BackgroundFirst-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets.ResultsWe used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples.ConclusionsThese results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

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Section: Introductionmentioning

confidence: 99%

Modeling precision treatment of breast cancer

et al. 2013

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“…In fact recently, patient data from the cancer genome atlas project (TCGA) presented the differential methylation status of Rab25 between luminal and basal subtypes of breast cancer with significant increase in methylation in the latter group (unpublished). Furthermore, with the reevaluation of molecular features of intrinsic subtypes of breast cancer and emergence of the new “claudin low” group within the basal category (exemplified by the MDA MB231 cell line), we find that Rab25 levels are concomitantly undetectable along with low claudin levels in these mesenchymal breast cancer subtypes, clinically closest to metaplastic breast cancers 22,23 . So it is safe to conclude that in breast cancers, the oncogenic role of Rab25 is context dependent.…”

Section: 0 Context Dependent Role Of Rab25 In Cancer: Oncogene or Tmentioning

confidence: 84%

“…It is important to note that breast cancer is a highly heterogeneous disease, populated by diverse cells types 22,23 . Each molecular subtype has distinct gene expression profiles and overall outcome.…”

Section: 0 Context Dependent Role Of Rab25 In Cancer: Oncogene or Tmentioning

confidence: 99%

Rab25 in cancer: a brief update

Mitra

Cheng

Mills

2012

Biochemical Society Transactions

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Derailed endocytosis is a hallmark of cancer. The endocytic pathway, as demonstrated by our laboratory, is a frequent target of genomic aberrations in cancer and plays a critical role in the maintenance of cellular polarity, stem cell function, bioenergetics, proliferation, motility, invasion, metastasis, apoptosis and autophagy. The Rab GTPases, along with their effectors, are critical regulators of this endocytic machinery and can have a huge impact on the cellular itinerary of growth and metabolism. Rab25 is an epithelial-cell-specific member of the Rab GTPase superfamily, sharing close homology with Rab11a, the endosomal recycling Rab GTPase. RAB25 has been implicated in various cancers, with reports presenting it as both an oncogene and a tumour-suppressor gene. At the cellular level, Rab25 was shown to contribute to invasiveness of cancer cells by regulating integrin trafficking. Recently, our laboratory uncovered a critical role for Rab25 in cellular energetics. Assimilating all of the existing evidence, in the present review, we give an updated overview of the complex and often context-dependent role of Rab25 in cancer.

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“…We crossed HER2/neu-overexpressing (MMTV-neu-IRES-cre, or NIC) mice with PTEN fl/fl mice (PTEN −/− / NIC), which developed highly aggressive neu-overexpressing/PTEN-deficient and trastuzumab-resistant mammary tumors with median survival of 45 days [13]. We applied a quantitative proteomics approach of reverse phase protein array (RPPA, containing > 150 antibodies) [18] on lysates of mammary tumors from the PTEN −/− / NIC mice and compared it to the PTEN +/+ /NIC (PTEN wild type) tumors. As with patient tumors, tumors of the PTEN −/− /NIC mice had activation of not only the PI3K Figure 1C) [19].…”

Section: Biomarker Analyses Denote Activation Of Multiple Erbb2 Downsmentioning

confidence: 99%

Biomarker-guided sequential targeted therapies to overcome therapy resistance in rapidly evolving highly aggressive mammary tumors

et al. 2014

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Combinatorial targeted therapies are more effective in treating cancer by blocking by-pass mechanisms or inducing synthetic lethality. However, their clinical application is hampered by resistance and toxicity. To meet this important challenge, we developed and tested a novel concept of biomarker-guided sequential applications of various targeted therapies using ErbB2-overexpressing/PTEN-low, highly aggressive breast cancer as our model. Strikingly, sustained activation of ErbB2 and downstream pathways drives trastuzumab resistance in both PTEN-low/ trastuzumab-resistant breast cancers from patients and mammary tumors with intratumoral heterogeneity from genetically-engineered mice. Although lapatinib initially inhibited trastuzumab-resistant mouse tumors, tumors bypassed the inhibition by activating the PI3K/mTOR signaling network as shown by the quantitative protein arrays. Interestingly, activation of the mTOR pathway was also observed in neoadjuvant lapatinib-treated patients manifesting lapatinib resistance. Trastuzumab + lapatinib resistance was effectively overcome by sequential application of a PI3K/mTOR dual kinase inhibitor (BEZ235) with no significant toxicity. However, our p-RTK array analysis demonstrated that BEZ235 treatment led to increased ErbB2 expression and phosphorylation in genetically-engineered mouse tumors and in 3-D, but not 2-D, culture, leading to BEZ235 resistance. Mechanistically, we identified ErbB2 protein stabilization and activation as a novel mechanism of BEZ235 resistance, which was reversed by subsequent treatment with lapatinib + BEZ235 combination. Remarkably, this sequential application of targeted therapies guided by biomarker changes in the tumors rapidly evolving resistance doubled the life-span of mice bearing exceedingly aggressive tumors. This fundamentally novel approach of using targeted therapies in a sequential order can effectively target and reprogram the signaling networks in cancers evolving resistance during treatment.

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Proteomic Classification of Breast Cancer

Cited by 14 publications

References 55 publications

Modeling precision treatment of breast cancer

Modeling precision treatment of breast cancer

Rab25 in cancer: a brief update

Biomarker-guided sequential targeted therapies to overcome therapy resistance in rapidly evolving highly aggressive mammary tumors

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