Dataset Information

Fingerprinting breast cancer vs. normal mammary cells by mass spectrometric analysis of volatiles.

ABSTRACT: There is increasing interest in the development of noninvasive diagnostic methods for early cancer detection, to improve the survival rate and quality of life of cancer patients. Identification of volatile metabolic compounds may provide an approach for noninvasive early diagnosis of malignant diseases. Here we analyzed the volatile metabolic signature of human breast cancer cell lines versus normal human mammary cells. Volatile compounds in the headspace of conditioned culture medium were directly fingerprinted by secondary electrospray ionization-mass spectrometry. The mass spectra were subsequently treated statistically to identify discriminating features between normal vs. cancerous cell types. We were able to classify different samples by using feature selection followed by principal component analysis (PCA). Additionally, high-resolution mass spectrometry allowed us to propose their chemical structures for some of the most discriminating molecules. We conclude that cancerous cells can release a characteristic odor whose constituents may be used as disease markers.

SUBMITTER: He J

PROVIDER: S-EPMC5381500 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Fingerprinting breast cancer vs. normal mammary cells by mass spectrometric analysis of volatiles.

He Jingjing J Sinues Pablo Martinez-Lozano PM Hollmén Maija M Li Xue X Detmar Michael M Zenobi Renato R

Scientific reports 20140606

There is increasing interest in the development of noninvasive diagnostic methods for early cancer detection, to improve the survival rate and quality of life of cancer patients. Identification of volatile metabolic compounds may provide an approach for noninvasive early diagnosis of malignant diseases. Here we analyzed the volatile metabolic signature of human breast cancer cell lines versus normal human mammary cells. Volatile compounds in the headspace of conditioned culture medium were direc ...[more]

PMID: 24903350

Similar Datasets

Project description:INTRODUCTION: About 70% of breast cancers express oestrogen receptor alpha (ESR1/ERalpha) and are oestrogen-dependent for growth. In contrast with the highly proliferative nature of ERalpha-positive tumour cells, ERalpha-positive cells in normal breast tissue rarely proliferate. Because ERalpha expression is rapidly lost when normal human mammary epithelial cells (HMECs) are grown in vitro, breast cancer models derived from HMECs are ERalpha-negative. Currently only tumour cell lines are available to model ERalpha-positive disease. To create an ERalpha-positive breast cancer model, we have forced normal HMECs derived from reduction mammoplasty tissue to express ERalpha in combination with other relevant breast cancer genes. METHODS: Candidate genes were selected based on breast cancer microarray data and cloned into lentiviral vectors. Primary HMECs prepared from reduction mammoplasty tissue were infected with lentiviral particles. Infected HMECs were characterised by Western blotting, immunofluorescence microscopy, microarray analysis, growth curves, karyotyping and SNP chip analysis. The tumorigenicity of the modified HMECs was tested after orthotopic injection into the inguinal mammary glands of NOD/SCID mice. Cells were marked with a fluorescent protein to allow visualisation in the fat pad. The growth of the graft was analysed by fluorescence microscopy of the mammary glands and pathological analysis of stained tissue sections. Oestrogen dependence of tumour growth was assessed by treatment with the oestrogen antagonist fulvestrant. RESULTS: Microarray analysis of ERalpha-positive tumours reveals that they commonly overexpress the Polycomb-group gene BMI1. Lentiviral transduction with ERalpha, BMI1, TERT and MYC allows primary HMECs to be expanded in vitro in an oestrogen-dependent manner. Orthotopic xenografting of these cells into the mammary glands of NOD/SCID mice results in the formation of ERalpha-positive tumours that metastasise to multiple organs. The cells remain wild type for TP53, diploid and genetically stable. In vivo tumour growth and in vitro proliferation of cells explanted from tumours are dependent on oestrogen. CONCLUSION: We have created a genetically defined model of ERalpha-positive human breast cancer based on normal HMECs that has the potential to model human oestrogen-dependent breast cancer in a mouse and enables the study of mechanisms involved in tumorigenesis and metastasis.

Project description:Previous genomic profiling of immortalized, non-tumorigenic human breast epithelial cells identified a set of 1,25-dihydroxyvitamin D3 (1,25D) regulated genes with potential relevance to breast cancer prevention. In this report, we characterized the effect of 1,25D on a subset of these genes in six cell lines derived from mammary tissue and breast cancers. Non-tumorigenic cell lines included hTERT-HME1, HME and MCF10A cells which are often used to model normal breast epithelial cells. Breast cancer cell lines included MCF7 cells (a model of early stage, estrogen-dependent disease), DCIS.com cells (a derivative of MCF10A cells that models in situ breast cancer) and Hs578T cells (a model of metastatic disease). All of these cell lines express the vitamin D receptor (VDR) and exhibit anti-cancer responses to 1,25D such as changes in proliferation, apoptosis, metabolism, or invasion. Our comparative data demonstrate highly variable responses to 1,25D (100nM, 24h) between the cell lines. In both hTERT-HME1 and HME cell lines, CYP24A1, SLC1A1 and ITGB3 were up-regulated whereas KDR, GLUL and BIRC3 were down-regulated in response to 1,25D. In contrast, no changes in SLC1A1, ITGB3 or GLUL expression were detected in 1,25D treated MCF10A cells although KDR and BIRC3 were down-regulated by 1,25D. The effects of 1,25D on these genes in the breast cancer cell lines were blunted, with the DCIS.com cells exhibiting the most similar responses to the immortalized hTERT-HME1 and HME cells. The differences in cellular responses were not due to general impairment in VDR function as robust CYP24A1 induction was observed in all cell lines. Thus, our data indicate that the genomic changes induced by 1,25D are highly cell-type specific even in model cell lines derived from the same tissue. The implication of these findings is that genomic responses to changes in vitamin D status in vivo are likely to be distinct from individual to individual, particularly in neoplastic tissue. This article is part of a Special Issue entitled '17th Vitamin D Workshop'.

Project description:Because of differences in the downstream signaling patterns of its pathways, the role of the human epidermal growth factor family of receptors (HER) in promoting cell growth and survival is cell line and context dependent. Using two model cell lines, we have studied how the regulatory interaction network among the key proteins of HER signaling pathways may be rewired upon normal to cancerous transformation. We in particular investigated how the transcription factor STAT3 and several key kinases' involvement in cancer-related signaling processes differ between normal 184A1L5 human mammary epithelial (HME) and MDA-MB-231 breast cancer epithelial cells. Comparison of the responses in these cells showed that normal-to-cancerous cellular transformation causes a major re-wiring of the growth factor initiated signaling. In particular, we found that: i) regulatory interactions between Erk, p38, JNK and STAT3 are triangulated and tightly coupled in 184A1L5 HME cells, and ii) STAT3 is only weakly associated with the Erk-p38-JNK pathway in MDA-MB-231 cells. Utilizing the concept of pathway substitution, we predicted how the observed differences in the regulatory interactions may affect the proliferation/survival and motility responses of the 184A1L5 and MDA-MB-231 cells when exposed to various inhibitors. We then validated our predictions experimentally to complete the experiment-computation-experiment iteration loop. Validated differences in the regulatory interactions of the 184A1L5 and MDA-MB-231 cells indicated that instead of inhibiting STAT3, which has severe toxic side effects, simultaneous inhibition of JNK together with Erk or p38 could be a more effective strategy to impose cell death selectively to MDA-MB-231 cancer cells while considerably lowering the side effects to normal epithelial cells. Presented analysis establishes a framework with examples that would enable cell signaling researchers to identify the signaling network structures which can be used to predict the phenotypic responses in particular cell lines of interest.

Dataset Information

Fingerprinting breast cancer vs. normal mammary cells by mass spectrometric analysis of volatiles.

Publications

Fingerprinting breast cancer vs. normal mammary cells by mass spectrometric analysis of volatiles.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets