Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors.

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Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors. / Cifani, Paolo; Kirik, Ufuk; Waldemarson, Sofia; James, Peter.

In: Journal of Proteome Research, Vol. 14, No. 7, 2015, p. 2819-2827.

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Cifani, Paolo ; Kirik, Ufuk ; Waldemarson, Sofia ; James, Peter. / Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors. In: Journal of Proteome Research. 2015 ; Vol. 14, No. 7. pp. 2819-2827.

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TY - JOUR

T1 - Molecular Portrait of Breast-Cancer-Derived Cell Lines Reveals Poor Similarity with Tumors.

AU - Cifani, Paolo

AU - Kirik, Ufuk

AU - Waldemarson, Sofia

AU - James, Peter

PY - 2015

Y1 - 2015

N2 - Breast-cancer-derived cell lines are an important sample source for cancer proteomics and can be classified on the basis of transcriptomic analysis into subgroups corresponding to the molecular subtypes observed in mammary tumors. This study describes a tridimensional fractionation method that allows high sequence coverage and proteome-wide estimation of protein expression levels. This workflow has been used to conduct an in-depth quantitative proteomic survey of five breast cancer cell lines matching all major cancer subgroups and shows that despite their different classification, these cell lines display a very high level of similarity. A proteome-wide comparison with the RNA levels observed in the same samples showed very little to no correlation. Finally, we demonstrate that the proteomes of in vitro models of breast cancer display surprisingly little overlap with those of clinical samples.

AB - Breast-cancer-derived cell lines are an important sample source for cancer proteomics and can be classified on the basis of transcriptomic analysis into subgroups corresponding to the molecular subtypes observed in mammary tumors. This study describes a tridimensional fractionation method that allows high sequence coverage and proteome-wide estimation of protein expression levels. This workflow has been used to conduct an in-depth quantitative proteomic survey of five breast cancer cell lines matching all major cancer subgroups and shows that despite their different classification, these cell lines display a very high level of similarity. A proteome-wide comparison with the RNA levels observed in the same samples showed very little to no correlation. Finally, we demonstrate that the proteomes of in vitro models of breast cancer display surprisingly little overlap with those of clinical samples.

U2 - 10.1021/acs.jproteome.5b00375

DO - 10.1021/acs.jproteome.5b00375

M3 - Article

VL - 14

SP - 2819

EP - 2827

JO - Journal of Proteome Research

T2 - Journal of Proteome Research

JF - Journal of Proteome Research

SN - 1535-3893

IS - 7

ER -