Proteomic profiling identifies markers for inflammation-related tumor-fibroblast interaction.
Proteomic profiling identifies markers for inflammation-related tumor-fibroblast interaction.
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蛋白质组学分析可识别炎症相关的肿瘤-成纤维细胞相互作用的标记。
DOI：
10.1186/s12014-017-9168-7
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发表时间：
2017
影响因子：
3.8
通讯作者：
Marian B
中科院分区：
文献类型：
--
作者：
Drev D;Bileck A;Erdem ZN;Mohr T;Timelthaler G;Beer A;Gerner C;Marian B
Cancer associated fibroblasts are activated in the tumor microenvironment and contribute to tumor progression, angiogenesis, extracellular matrix remodeling, and inflammation. 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. We identified a set of 24 proteins associated with inflammation, matrix organization, TGFβ receptor signaling and angiogenesis mainly originating from the stroma. Most prominent were increased abundance of SerpinB5 in the parenchyme and latent transforming growth factor β-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. 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. The online version of this article (doi:10.1186/s12014-017-9168-7) contains supplementary material, which is available to authorized users.
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影响因子：
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作者：
Chen X;Churchill MJ;Nagar KK;Tailor YH;Chu T;Rush BS;Jiang Z;Wang EB;Renz BW;Wang H;Fung MC;Worthley DL;Mukherjee S;Wang TC
通讯作者：
Wang TC
影响因子：
1.6
作者：
Cao, Dengfeng;Wilentz, Robb E.;Maitra, Anirban
通讯作者：
Maitra, Anirban
DOI：
10.1093/bioinformatics/btp101
发表时间：
2009-04-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Bindea G;Mlecnik B;Hackl H;Charoentong P;Tosolini M;Kirilovsky A;Fridman WH;Pagès F;Trajanoski Z;Galon J
通讯作者：
Galon J
影响因子：
4.1
作者：
Bornstein, Paul
通讯作者：
Bornstein, Paul
DOI：
10.1084/jem.20151193
发表时间：
2016-10-17
期刊：
The Journal of experimental medicine
影响因子：
--
作者：
Afik R;Zigmond E;Vugman M;Klepfish M;Shimshoni E;Pasmanik-Chor M;Shenoy A;Bassat E;Halpern Z;Geiger T;Sagi I;Varol C
通讯作者：
Varol C