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采用定量配对分析工作流程对乳腺癌分泌组进行差异蛋白质组学比较。

Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow.

机构信息

Laboratory of Toxinology, Oswaldo Cruz Institute, Fiocruz, Av. Brasil 4365, Manguinhos, Rio de Janeiro, 21040-360, Brazil.

Laboratory for Proteomics and Protein Engineering, Carlos Chagas Institute, Fiocruz, Rua Prof. Algacyr Munhoz Mader 3775, CIC, Paraná, 81350-010, Brazil.

出版信息

BMC Cancer. 2019 Apr 18;19(1):365. doi: 10.1186/s12885-019-5547-y.

Abstract

BACKGROUND

Worldwide, breast cancer is the main cause of cancer mortality in women. Most cases originate in mammary ductal cells that produce the nipple aspirate fluid (NAF). In cancer patients, this secretome contains proteins associated with the tumor microenvironment. NAF studies are challenging because of inter-individual variability. We introduced a paired-proteomic shotgun strategy that relies on NAF analysis from both breasts of patients with unilateral breast cancer and extended PatternLab for Proteomics software to take advantage of this setup.

METHODS

The software is based on a peptide-centric approach and uses the binomial distribution to attribute a probability for each peptide as being linked to the disease; these probabilities are propagated to a final protein p-value according to the Stouffer's Z-score method.

RESULTS

A total of 1227 proteins were identified and quantified, of which 87 were differentially abundant, being mainly involved in glycolysis (Warburg effect) and immune system activation (activated stroma). Additionally, in the estrogen receptor-positive subgroup, proteins related to the regulation of insulin-like growth factor transport and platelet degranulation displayed higher abundance, confirming the presence of a proliferative microenvironment.

CONCLUSIONS

We debuted a differential bioinformatics workflow for the proteomic analysis of NAF, validating this secretome as a treasure-trove for studying a paired-organ cancer type.

摘要

背景

在全球范围内,乳腺癌是女性癌症死亡的主要原因。大多数病例起源于产生乳头吸出液(NAF)的乳腺导管细胞。在癌症患者中,这种分泌组包含与肿瘤微环境相关的蛋白质。由于个体间的可变性,NAF 研究具有挑战性。我们引入了一种配对蛋白质组学 shotgun 策略,该策略依赖于单侧乳腺癌患者双侧乳房的 NAF 分析,并扩展了 PatternLab for Proteomics 软件以利用这种设置。

方法

该软件基于肽中心方法,并使用二项式分布为每个肽与疾病相关的可能性分配概率;根据 Stouffer 的 Z 分数方法,根据这些概率传播到最终蛋白质 p 值。

结果

共鉴定和定量了 1227 种蛋白质,其中 87 种丰度差异,主要涉及糖酵解(Warburg 效应)和免疫系统激活(激活的基质)。此外,在雌激素受体阳性亚组中,与胰岛素样生长因子运输和血小板脱颗粒调节相关的蛋白质显示出更高的丰度,证实了增殖性微环境的存在。

结论

我们首次推出了 NAF 蛋白质组学分析的差异生物信息学工作流程,验证了这种分泌组是研究配对器官癌症类型的宝库。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/edd5/6474050/77a74f508993/12885_2019_5547_Fig1_HTML.jpg

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