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Proteomic maps of breast cancer subtypes.

ABSTRACT: Systems-wide profiling of breast cancer has almost always entailed RNA and DNA analysis by microarray and sequencing techniques. Marked developments in proteomic technologies now enable very deep profiling of clinical samples, with high identification and quantification accuracy. We analysed 40 oestrogen receptor positive (luminal), Her2 positive and triple negative breast tumours and reached a quantitative depth of >10,000 proteins. These proteomic profiles identified functional differences between breast cancer subtypes, related to energy metabolism, cell growth, mRNA translation and cell-cell communication. Furthermore, we derived a signature of 19 proteins, which differ between the breast cancer subtypes, through support vector machine (SVM)-based classification and feature selection. Remarkably, only three proteins of the signature were associated with gene copy number variations and eleven were also reflected on the mRNA level. These breast cancer features revealed by our work provide novel insights that may ultimately translate to development of subtype-specific therapeutics.

SUBMITTER: Tyanova S

PROVIDER: S-EPMC4725767 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Proteomic maps of breast cancer subtypes.

Tyanova Stefka S Albrechtsen Reidar R Kronqvist Pauliina P Cox Juergen J Mann Matthias M Geiger Tamar T

Nature communications 20160104

Systems-wide profiling of breast cancer has almost always entailed RNA and DNA analysis by microarray and sequencing techniques. Marked developments in proteomic technologies now enable very deep profiling of clinical samples, with high identification and quantification accuracy. We analysed 40 oestrogen receptor positive (luminal), Her2 positive and triple negative breast tumours and reached a quantitative depth of >10,000 proteins. These proteomic profiles identified functional differences bet ...[more]

PMID: 26725330

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Project description:BackgroundWomen with diabetes have a worse survival after breast cancer diagnosis compared to women without diabetes. This may be due to a different etiological profile, leading to the development of more aggressive breast cancer subtypes. Our aim was to investigate whether insulin and non-insulin treated women with diabetes develop specific clinicopathological breast cancer subtypes compared to women without diabetes.Methods and findingsThis cross-sectional study included randomly selected patients with invasive breast cancer diagnosed in 2000-2010. Stratified by age at breast cancer diagnosis (≤50 and >50 years), women with diabetes were 2:1 frequency-matched on year of birth and age at breast cancer diagnosis (both in 10-year categories) to women without diabetes, to select ~300 patients with tumor tissue available. Tumor MicroArrays were stained by immunohistochemistry for estrogen and progesterone receptor (ER, PR), HER2, Ki67, CK5/6, CK14, and p63. A pathologist scored all stains and revised morphology and grade. Associations between diabetes/insulin treatment and clinicopathological subtypes were analyzed using multivariable logistic regression. Morphology and grade were not significantly different between women with diabetes (n = 211) and women without diabetes (n = 101), irrespective of menopausal status. Premenopausal women with diabetes tended to have more often PR-negative (OR = 2.44(95%CI:1.07-5.55)), HER2-negative (OR = 2.84(95%CI:1.11-7.22)), and basal-like (OR = 3.14(95%CI:1.03-9.60) tumors than the women without diabetes, with non-significantly increased frequencies of ER-negative (OR = 2.48(95%CI:0.95-6.45)) and triple negative (OR = 2.60(95%CI:0.88-7.67) tumors. After adjustment for age and BMI, the associations remained similar in size but less significant. We observed no evidence for associations of clinicopathological subtypes with diabetes in postmenopausal women, or with insulin treatment in general.ConclusionsWe found no compelling evidence that women with diabetes, treated with or without insulin, develop different breast cancer subtypes than women without diabetes. However, premenopausal women with diabetes tended to develop breast tumors that do not express hormonal receptors, which are typically associated with poor prognosis.

Project description:Depression is a highly heterogeneous disorder. Accumulating evidence suggests biological and genetic differences between subtypes of depression that are homogeneous in symptom presentation. We aimed to evaluate differences in serum protein profiles between persons with atypical and melancholic depressive subtypes, and compare these profiles with serum protein levels of healthy controls. We used the baseline data from the Netherlands Study of Depression and Anxiety on 414 controls, 231 persons with a melancholic depressive subtype and 128 persons with an atypical depressive subtype for whom the proteomic data were available. Depressive subtypes were previously established using a data-driven analysis, and 171 serum proteins were measured on a multi-analyte profiling platform. Linear regression models were adjusted for several covariates and corrected for multiple testing using false discovery rate q-values. We observed differences in analytes between the atypical and melancholic subtypes (9 analytes, q<0.05) and between atypical depression and controls (23 analytes, q<0.05). Eight of the nine markers differing between the atypical and melancholic subtype overlapped with markers from the comparison between atypical subtype and controls (mesothelin, leptin, IGFBP1, IGFBP2, FABPa, insulin, C3 and B2M), and were mainly involved in cellular communication and signal transduction, and immune response. No markers differed significantly between the melancholic subtype and controls. To conclude, although some uncertainties exist in our results as a result of missing data imputation and lack of proteomic replication samples, many of the identified analytes are inflammatory or metabolic markers, which supports the notion of atypical depression as a syndrome characterized by metabolic disturbances and inflammation, and underline the importance and relevance of subtypes of depression in biological and genetic research, and potentially in the treatment of depression.

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Proteomic maps of breast cancer subtypes.

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Proteomic maps of breast cancer subtypes.

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