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Review
. 2010 Dec;4(6):496-510.
doi: 10.1016/j.molonc.2010.09.001. Epub 2010 Sep 16.

Cancer secretomics reveal pathophysiological pathways in cancer molecular oncology

George S Karagiannis  1 , Maria P Pavlou, Eleftherios P Diamandis
Affiliations
Review

Cancer secretomics reveal pathophysiological pathways in cancer molecular oncology

George S Karagiannis et al. Mol Oncol. 2010 Dec.

Abstract

Emerging proteomic tools and mass spectrometry play pivotal roles in protein identification, quantification and characterization, even in complex biological samples. The cancer secretome, namely the whole collection of proteins secreted by cancer cells through various secretory pathways, has only recently been shown to have significant potential for diverse applications in oncoproteomics. For example, secreted proteins might represent putative tumor biomarkers or therapeutic targets for various types of cancer. Consequently, many proteomic strategies for secretome analysis have been extensively deployed over the last few years. These efforts generated a large amount of information awaiting deeper mining, better understanding and careful interpretation. Distinct sub-fields, such as degradomics, exosome proteomics and tumor-host cell interactions have been developed, in an attempt to provide certain answers to partially elucidated mechanisms of cancer pathobiology. In this review, advances, concerns and challenges in the field of secretome analysis as well as possible clinical applications are discussed.

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Figures

Figure 1
Figure 1
Heterotypic overview of the cancer secretome. All the microenvironmental, secreted proteins may originate either from cancer cells or from associated stromal cells and their secretion may be triggered by paracrine or autocrine actions between them. Proteomic approaches to capture the tumor microenvironment should focus on identifying proteins secreted by all associated cells, not just the cancer cells. Arrows initiating from cells and pointing in molecules represent secretion; the opposite represents the paracrine or autocrine action of the secreted molecules on the cell types.
Figure 2
Figure 2
Bioinformatics tools for prediction of protein secretion pathways. The classical protein secretory pathway is ER/Golgi‐dependent and involves the presence of the signal peptide that directs translocation of these proteins to the ER. Protcomb, SignalP, SPD and Sig‐Pred are some of the widely used programs for prediction of proteins secreted through the classical secretory pathway. The non‐classical protein secretion pathway is ER/Golgi‐independent and is associated with absence of signal peptide. SecretomeP has been used for prediction of proteins secreted through non‐classical secretion pathways. Proteolytic events in the extracellular space might also result in shedding of membrane‐bound proteins/particles. Although this is not a protein secretion pathway, but an extracellular proteolytic event, software, such as TMHMM and TMpred is being used for the prediction of membrane and membrane‐bound proteins. Finally, a database of exosome‐secreted proteins, called ExoCarta has been recently generated as a distinct database the proteins secreted as such. ER, endoplasmic reticulum; ILVs, intralumenal vesicles; MVBs, multivesicular bodies; SPD, secreted protein database; SIG‐Pred, signal peptide prediction; TMHMM, transmembrane prediction with hidden Markov models; TMpred, prediction of transmembrane regions and orientation. Arrows indicate protein secretion or vesicle processing/movement. Blue boxes indicate software and their applications.
Figure 3
Figure 3
Cell‐biological programs, activated during the metastatic cascade, that could be investigated with mass spectrometry‐based secretome analysis. The metastatic cascade begins with an initial step of localized invasiveness, which enables in situ carcinoma cells that have undergone epithelial‐to‐mesenchymal transition, to breach the basement membrane. Thereafter, they enter into lymphatic or blood microvessels via a process called intravasation. The latter may transport these cancer cells to distant anatomical sites, where they are actually trapped and subsequently they invade into the neighboring tissue via a counter‐related process, called extravasation. This process enables them to form dormant micrometastases, which eventually may acquire the ability to successfully colonize the tissue and form a macroscopic metastasis. Throughout this process, the cancer cells deploy specific cell‐biological programs involving significant alterations in their proteome and secretome profiles to overcome various biological barriers; proteomic investigations have revealed metastasis‐associated proteins with specific roles within the metastatic cascade. EMT, epithelial‐to‐mesenchymal transition; ECM, extracellular matrix.
Figure 4
Figure 4
Schematic view of the region represented with an asterisk in Fig. 3, showing a distinct network of proteolytic relationships during cancer cell migration within the stroma. Kallikrein‐related peptidases, many of which are secreted by cancer cells, have been found capable of activating pro‐uPA (produced abundantly by stromal cells) and generate active uPA. In turn, uPA binds to its receptor, uPAR, present in the plasma membrane of the cancer cells, and converts plasminogen into active plasmin. Once plasmin is activated, it may, in turn, proceed to activate several inactive pro‐MMPs and generate active enzymes (MMPs). The latter are mainly responsible for ECM degradation. In addition, KLKs (e.g. KLK1) may be able to directly activate MMPs and also cleave constituents of the ECM themselves. uPA, urokinase‐type plasminogen activator; pro‐uPA, proform of uPA; uPAR, uPA receptor; MMPs, matrix metalloproteinases; pro‐MMPs, proform of MMPs; KLKs, kallikreins; ECM, extracellular matrix. Arrows between two molecules represent activation; arrows initiating from a molecule and pointing out in arrows represent enzymatic interaction; arrows initiating from cell interior and pointing in molecules represent secretion.
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