Novel Breast Cancer Biomarkers Identified by Integrative Proteomic and Gene Expression Mapping

Ou, Keli; Yu, Kun; Kesuma, Djohan; Hooi, Michelle; Huang, Na; Chen, Wei; Lee, Suet Ying; Goh, Xin Pei; Tan, Lay Keng; Liu, Jia; Soon, Sou Yen; Rashid, Suhaimi Bin Abdul; Putti, Thomas Choudary; Jikuya, Hiroyuki; Ichikawa, Tetsuo; Nishimura, Osamu; Salto-Tellez, Manuel; Tan, Patrick

doi:10.1021/pr700820g

Cited by 48 publications

(39 citation statements)

References 51 publications

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“…Conventional validation assays such as RT-PCR, ELISA and Western blots are prohibitively resource and time-intensive [45]. To relieve the bottleneck between the discovery and validation phrase, efforts are being made to integrate both proteomic and genomic platforms to discover biomarkers [24,46]. In line with these efforts, we first used a SILAC proteomic approach to identify differentially expressed proteins in Her2/neu-positive cells, followed by validation at the mRNA level and in silico analysis of published microarray data.…”

Section: Identification Of Novel Biomarkersmentioning

confidence: 99%

“…In addition to gene expression profiling studies [9][10][11][12], various published proteomic studies have been published that have investigated the proteomic profile of either HER2-positive mammary tissues [13][14][15][16][17][18][19] or HER2-expressing cell lines [20][21][22][23][24][25][26]. Here, we report a quantitative proteomics investigation of a Her2-overexpressing epithelial cell line (H6O5), isolated from a primary mammary tumor of MMTV-Her2/neu transgenic mice.…”

Section: Introductionmentioning

confidence: 99%

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Proteomic characterization of Her2/neu‐overexpressing breast cancer cells

Chen¹,

Pimienta²,

Gu³

et al. 2011

Proteomics Clinical Apps

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The receptor tyrosine kinase HER2 is an oncogene amplified in invasive breast cancer and its overexpression in mammary epithelial cell lines is a strong determinant of a tumorigenic phenotype. Accordingly, HER2-overexpressing mammary tumors are commonly indicative of a poor prognosis in patients. Several quantitative proteomic studies have employed two-dimensional gel electrophoresis in combination with tandem mass spectrometry, which provides only limited information about the molecular mechanisms underlying HER2/neu signaling. In the present study, we used a SILAC-based approach to compare the proteomic profile of normal breast epithelial cells with that of Her2/neu-overexpressing mammary epithelial cells, isolated from primary mammary tumors arising in MMTV-Her2/neu transgenic mice. We identified 23 proteins with relevant annotated functions in breast cancer, showing a substantial differential expression. This included overexpression of creatine kinase, retinol-binding protein 1, thymosin beta 4 and tumor protein D52, which correlated with the tumorigenic phenotype of Her2-overexpressing cells. The differential expression pattern of two genes, gelsolin and retinol binding protein 1, was further validated in normal and tumor tissues. Finally, an in silico analysis of published cancer microarray datasets revealed a 23-gene signature which can be used to predict the probability of metastasis-free survival in breast cancer patients.

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Section: Identification Of Novel Biomarkersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Proteomic characterization of Her2/neu‐overexpressing breast cancer cells

Chen¹,

Pimienta²,

Gu³

et al. 2011

Proteomics Clinical Apps

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“…To date, this issue has been addressed by analysis of molecular profiles associated with hormone response and disease state in breast cancer cells. Gene expression profiling (28 -30) and quantitative proteomics analyses (31,32) provided a blueprint of the effects of estrogen and other ER ligands in hormoneresponsive cancer cells, revealing a complexity of ER-induced cellular responses that suggests the likelihood that ERs exist in the cell in multiple functional conformations. Indeed, the already mentioned ability of ligand-activated ERs to form multiple complexes with key intracellular regulatory molecules represents a well known mechanism to explain their multifaceted effects in key processes such as signal transduction and transcriptional regulation (2,6).…”

mentioning

confidence: 99%

Identification of a Hormone-regulated Dynamic Nuclear Actin Network Associated with Estrogen Receptor α in Human Breast Cancer Cell Nuclei

Ambrosino

Tarallo

Bamundo

et al. 2010

Molecular & Cellular Proteomics

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Estrogen receptor ␣ (ER␣) is a modular protein of the steroid/nuclear receptor family of transcriptional regulators that upon binding to the hormone undergoes structural changes, resulting in its nuclear translocation and docking to specific chromatin sites. In the nucleus, ER␣ assembles in multiprotein complexes that act as final effectors of estrogen signaling to the genome through chromatin remodeling and epigenetic modifications, leading to dynamic and coordinated regulation of hormoneresponsive genes. Identification of the molecular partners of ER␣ and understanding their combinatory interactions within functional complexes is a prerequisite to define the molecular basis of estrogen control of cell functions. To this end, affinity purification was applied to map and characterize the ER␣ interactome in hormone-responsive human breast cancer cell nuclei. MCF-7 cell clones expressing human ER␣ fused to a tandem affinity purification tag were generated and used to purify native nuclear ERcontaining complexes by IgG-Sepharose affinity chromatography and glycerol gradient centrifugation. Purified complexes were analyzed by two-dimensional DIGE and mass spectrometry, leading to the identification of a liganddependent multiprotein complex comprising ␤-actin, myosins, and several proteins involved in actin filament organization and dynamics and/or known to participate in actin-mediated regulation of gene transcription, chromatin dynamics, and ribosome biogenesis. Time course analyses indicated that complexes containing ER␣ and actin are assembled in the nucleus early after receptor activation by ligands, and gene knockdown experiments showed that gelsolin and the nuclear isoform of myosin 1c are key determinants for assembly and/or stability of these complexes. Based on these results, we propose that the actin network plays a role in nuclear ER␣ actions in breast cancer cells, including coordinated regulation of target gene activity, spatial and functional reorganization of chromatin, and ribosome biogenesis. Molecular & Cellular Proteomics 9:1352-1367, 2010.Estrogens are potent tumor promoters for the mammary gland due to their growth-promoting actions in mammary epithelial cells (1). The mechanisms underlying stimulation of breast cell proliferation and control of the cell state by estrogens are still poorly defined despite the evident causal relationships between these hormonal actions and mammary gland carcinogenesis and cancer progression. Estrogen-responsive cells are endowed with specific estrogen receptors, ER␣ 1 and ER␤, members of the steroid/nuclear receptor superfamily of transcription factors that directly modulate the gene transcription rate (2). In addition, estrogens can trigger rapid and transient cellular responses through a mechanism(s) independent from this "genomic" pathway of steroid receptor action (3, 4). Such "extragenomic" effects include cell typespecific, rapid, and transient responses of signal transduction pathways; induction of intracellular calcium mobilization; and From the Departmen...

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“…A comparison between the proteomic and transcriptomic data generated a subset of concordant markers, which were then validated in tissue mRNA and tissue microarrays. 81 A different study highlighted the ability of characterising different subtypes of diseases, in this case hyperdiploid and nonhyperdiploid multiple myeloma, using multi-omics approaches. The integrated study elucidated differences of disease characteristics of these subtypes is not only based on early promoting events, but also manifests in differentially regulated pathway activity and alterations in genetic architecture.…”

Section: Improvements Through Data Integration?mentioning

confidence: 99%

Application of omic technologies in cancer research

et al. 2018

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Understanding the biology of health and diseases such as cancer, generating insight into the triggers and potentiators of disease and the development of therapeutic approaches to counter and treat disease requires detailed interrogation of inherited genes, and the dynamic positioning of the transcriptome and proteome. In the last 10 years, significant technological developments and increases in sample throughput capabilities have led to a dramatic increase in the size and complexity of the datasets that can be generated. A key challenge now is to develop robust approaches for analysing and interpreting these, and converting data into biologically-and clinically-relevant information. Herein, we provide an overview of approaches for acquiring, integrating and interpreting complex datasets generated using multiple omic platforms, with a focus on the field of cancer research, and highlight key successful data handling and integration applications.

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Novel Breast Cancer Biomarkers Identified by Integrative Proteomic and Gene Expression Mapping

Cited by 48 publications

References 51 publications

Proteomic characterization of Her2/neu‐overexpressing breast cancer cells

Proteomic characterization of Her2/neu‐overexpressing breast cancer cells

Identification of a Hormone-regulated Dynamic Nuclear Actin Network Associated with Estrogen Receptor α in Human Breast Cancer Cell Nuclei

Application of omic technologies in cancer research

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