Dataset Information

Proteomic profiling identifies breast tumor metastasis-associated factors in an isogenic model.

ABSTRACT: A combination of LC and MS was applied to an isogenic breast tumor metastasis model to identify proteins associated with a cellular phenotype. Chromatofocusing followed by nonporous-RP-HPLC/ESI-TOF MS was applied to cell lysates of a pair of monoclonal cell lines from the human breast carcinoma cell line MDA-MB-435 that have different metastatic phenotypes in immune-compromised mice. This method was developed to separate proteins based on pI and hydrophobicity. The high resolution and mass accuracy of ESI-TOF measurements provided a good correlation of theoretical MW and experimental Mr values of intact proteins measured in mass maps obtained in the pH range 3.8-6.4. The isolated proteins were digested by trypsin and analyzed by MALDI-TOF MS, MALDI-QIT-TOF MS, and monolith-based HPLC/MS/MS. The unique combination of the techniques provided valuable information including quantitation and modification of proteins. We identified 89 selected proteins, of which 43 were confirmed as differentially expressed. Metastasis-associated proteins included galectin-1, whereas annexin I and annexin II were associated with the nonmetastatic phenotype. In this study, we demonstrate that combining a variety of MS tools with a multidimensional liquid-phase separation provides the ability to map cellular protein content, to search for modified proteins, and to correlate protein expression with cellular phenotype.

SUBMITTER: Kreunin P

PROVIDER: S-EPMC2663396 | biostudies-literature | 2007 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Proteomic profiling identifies breast tumor metastasis-associated factors in an isogenic model.

Kreunin Paweena P Yoo Chul C Urquidi Virginia V Lubman David M DM Goodison Steve S

Proteomics 20070101 2

A combination of LC and MS was applied to an isogenic breast tumor metastasis model to identify proteins associated with a cellular phenotype. Chromatofocusing followed by nonporous-RP-HPLC/ESI-TOF MS was applied to cell lysates of a pair of monoclonal cell lines from the human breast carcinoma cell line MDA-MB-435 that have different metastatic phenotypes in immune-compromised mice. This method was developed to separate proteins based on pI and hydrophobicity. The high resolution and mass accur ...[more]

PMID: 17205601

Similar Datasets

Project description:Breast cancer tumors are known to be highly heterogeneous and differences in their metabolic phenotypes, especially at protein level, are less well-understood. Profiling of metabolism-related proteins harbors the potential to establish new patient stratification regimes and biomarkers promoting individualized therapy. In our study, we aimed to examine the relationship between metabolism-associated protein expression profiles and clinicopathological characteristics in a large cohort of breast cancer patients.Breast cancer specimens from 801 consecutive patients, diagnosed between 2009 and 2011, were investigated using reverse phase protein arrays (RPPA). Patients were treated in accordance with national guidelines in five certified German breast centers. To obtain quantitative expression data, 37 antibodies detecting proteins relevant to cancer metabolism, were applied. Hierarchical cluster analysis and individual target characterization were performed. Clustering results and individual protein expression patterns were associated with clinical data. The Kaplan-Meier method was used to estimate survival functions. Univariate and multivariate Cox regression models were applied to assess the impact of protein expression and other clinicopathological features on survival.We identified three metabolic clusters of breast cancer, which do not reflect the receptor-defined subtypes, but are significantly correlated with overall survival (OS, p???0.03) and recurrence-free survival (RFS, p???0.01). Furthermore, univariate and multivariate analysis of individual protein expression profiles demonstrated the central role of serine hydroxymethyltransferase 2 (SHMT2) and amino acid transporter ASCT2 (SLC1A5) as independent prognostic factors in breast cancer patients. High SHMT2 protein expression was significantly correlated with poor OS (hazard ratio (HR)?=?1.53, 95% confidence interval (CI)?=?1.10-2.12, p???0.01) and RFS (HR?=?1.54, 95% CI?=?1.16-2.04, p???0.01). High protein expression of ASCT2 was significantly correlated with poor RFS (HR?=?1.31, 95% CI?=?1.01-1.71, p???0.05).Our data confirm the heterogeneity of breast tumors at a functional proteomic level and dissects the relationship between metabolism-related proteins, pathological features and patient survival. These observations highlight the importance of SHMT2 and ASCT2 as valuable individual prognostic markers and potential targets for personalized breast cancer therapy.ClinicalTrials.gov, NCT01592825 . Registered on 3 May 2012.

Project description:The initiation and progression of breast cancer from the transformation of the normal epithelium to ductal carcinoma in situ (DCIS) and invasive disease is a complex process involving the acquisition of genetic alterations and changes in gene expression, alongside microenvironmental and recognized histological alterations. Here, we sought to comprehensively characterise the genomic and transcriptomic features of the MCF10 isogenic model of breast cancer progression, and to functionally validate potential driver alterations in three-dimensional (3D) spheroids that may provide insights into breast cancer progression, and identify targetable alterations in conditions more similar to those encountered in vivo. We performed whole genome, exome and RNA sequencing of the MCF10 progression series to catalogue the copy number and mutational and transcriptomic landscapes associated with progression. We identified a number of predicted driver mutations (including PIK3CA and TP53) that were acquired during transformation of non-malignant MCF10A cells to their malignant counterparts that are also present in analysed primary breast cancers from The Cancer Genome Atlas (TCGA). Acquisition of genomic alterations identified MYC amplification and previously undescribed RAB3GAP1-HRAS and UBA2-PDCD2L expressed in-frame fusion genes in malignant cells. Comparison of pathway aberrations associated with progression showed that, when cells are grown as 3D spheroids, they show perturbations of cancer-relevant pathways. Functional interrogation of the dependency on predicted driver events identified alterations in HRAS, PIK3CA and TP53 that selectively decreased cell growth and were associated with progression from preinvasive to invasive disease only when cells were grown as spheroids. Our results have identified changes in the genomic repertoire in cell lines representative of the stages of breast cancer progression, and demonstrate that genetic dependencies can be uncovered when cells are grown in conditions more like those in vivo. The MCF10 progression series therefore represents a good model with which to dissect potential biomarkers and to evaluate therapeutic targets involved in the progression of breast cancer. © 2016 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Project description:Background:Cancer associated fibroblasts are activated in the tumor microenvironment and contribute to tumor progression, angiogenesis, extracellular matrix remodeling, and inflammation. Methods:To identify proteins characteristic for fibroblasts in colorectal cancer we used liquid chromatography-tandem mass spectrometry to derive protein abundance from whole-tissue homogenates of human colorectal cancer/normal mucosa pairs. Alterations of protein levels were determined by two-sided t test with greater than threefold difference and an FDR of < 0.05. Public available datasets were used to predict proteins of stromal origin and link protein with mRNA regulation. Immunohistochemistry confirmed the localization of selected proteins. Results:We identified a set of 24 proteins associated with inflammation, matrix organization, TGF? receptor signaling and angiogenesis mainly originating from the stroma. Most prominent were increased abundance of SerpinB5 in the parenchyme and latent transforming growth factor ?-binding protein, thrombospondin-B2, and secreted protein acidic-and-cysteine-rich in the stroma. Extracellular matrix remodeling involved collagens type VIII, XII, XIV, and VI as well as lysyl-oxidase-2. In silico analysis of mRNA levels demonstrated altered expression in the tumor and the adjacent normal tissue as compared to mucosa of healthy individuals indicating that inflammatory activation affected the surrounding tissue. Immunohistochemistry of 26 tumor specimen confirmed upregulation of SerpinB5, thrombospondin B2 and secreted protein acidic-and-cysteine-rich. Conclusions:This study demonstrates the feasibility of detecting tumor- and compartment-specific protein-signatures that are functionally meaningful by proteomic profiling of whole-tissue extracts together with mining of RNA expression datasets. The results provide the basis for further exploration of inflammation-related stromal markers in larger patient cohorts and experimental models.

Project description:Development of aromatase inhibitor resistant breast cancer among postmenopausal women continues to be a major clinical obstacle. Previously, our group demonstrated that as breast cancer cells transition from hormone-dependent to hormone-independent, they are associated with increased growth factor signaling, enhanced cellular motility, and the epithelial to mesenchymal transition (EMT). Given the complexity of cancer stem cells (CSC) and their implications on endocrine resistance and EMT, we sought to understand their contribution towards the development of aromatase inhibitor resistant breast cancer. Cells cultured three dimensionally as mammospheres are enriched for CSCs and more accurately recapitulates tumors in vivo. Therefore, a global proteomic analysis was conducted using letrozole resistant breast cancer cells (LTLT-Ca) mammospheres and compared to their adherent counterparts. Results demonstrated over 1000 proteins with quantitative abundance ratios were identified. Among the quantified proteins, 359 were significantly altered (p < 0.05), where 173 were upregulated and 186 downregulated (p < 0.05, fold change >1.20). Notably, midasin, a chaperone protein required for maturation and nuclear export of the pre-60S ribosome was increased 35-fold. Protein expression analyses confirmed midasin is ubiquitously expressed in normal tissue but is overexpressed in lobular and ductal breast carcinoma tissue as well as ER+ and ER- breast cancer cell lines. Functional enrichment analyses indicated that 19 gene ontology terms and one KEGG pathway were over-represented by the down-regulated proteins and both were associated with protein synthesis. Increased midasin was strongly correlated with decreased relapse free survival in hormone independent breast cancer. For the first time, we characterized the global proteomic signature of CSC-enriched letrozole-resistant cells associated with protein synthesis, which may implicate a role for midasin in endocrine resistance.

Dataset Information

Proteomic profiling identifies breast tumor metastasis-associated factors in an isogenic model.

Publications

Proteomic profiling identifies breast tumor metastasis-associated factors in an isogenic model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure