Challenges and opportunities for cell line secretomes in cancer proteomics

An Introduction to Analytical Challenges, Approaches, and Applications in Mass Spectrometry-Based Secretomics

The active release of proteins into the extracellular space and the proteolytic cleavage of cell surface proteins are key processes that coordinate and fine-tune a multitude of physiological functions. The entirety of proteins that fulfill these extracellular tasks are referred to as the secretome and are of special interest for the investigation of biomarkers of disease states and physiological processes related to cell-cell communication. LC-MS-based proteomics approaches are a valuable tool for the comprehensive and unbiased characterization of this important subproteome. This review discusses procedures, opportunities, and limitations of mass spectrometry-based secretomics to better understand and navigate the complex analytical landscape for studying protein secretion in biomedical science.

Secreted Pyruvate Kinase M2 Promotes Lung Cancer Metastasis through Activating the Integrin Beta1/FAK Signaling Pathway

Cancer cell-derived secretomes have been documented to play critical roles in cancer progression. Intriguingly, alternative extracellular roles of intracellular proteins are involved in various steps of tumor progression, which can offer strategies to fight cancer. Herein, we identify lung cancer progression-associated secretome signatures using mass spectrometry analysis. Among them, PKM2 is verified to be highly expressed and secreted in lung cancer cells and clinical samples. Functional analyses demonstrates that secreted PKM2 facilitates tumor metastasis. Furthermore, mass spectrometry analysis and functional validation identify integrin β1 as a receptor of secreted PKM2. Mechanistically, secreted PKM2 directly bound to integrin β1 and subsequently activated the FAK/SRC/ERK axis to promote tumor metastasis. Collectively, our findings suggest that PKM2 is a potential serum biomarker for diagnosing lung cancer and that targeting the secreted PKM2-integrin β1 axis can inhibit lung cancer development, which provides evidence of a potential therapeutic strategy in lung cancer.

Clinical Implications of Extracellular HMGA1 in Breast Cancer

The unconventional secretion of proteins is generally caused by cellular stress. During the tumorigenesis, tumor cells experience high levels of stress, and the secretion of some theoretically intracellular proteins is activated. Once in the extracellular space, these proteins play different paracrine and autocrine roles and could represent a vulnerability of cancer. One of these proteins is the high mobility group A1 (HMGA1), which is frequently overexpressed in tumors and presents a low expression in normal adult tissues. We have recently described that HMGA1 establishes an autocrine loop in invasive triple-negative breast cancer (TNBC) cells. The secretion of HMGA1 and its binding to the receptor for advanced glycation end products (RAGE) mediates the migration, invasion, and metastasis of TNBC cells and predicts the onset of metastasis in these patients. In this review, we summarized different strategies to exploit the novel tumorigenic phenotype mediated by extracellular HMGA1. We envisioned future clinical applications where the association between its change in subcellular localization and breast cancer progression could be used to predict tumor aggressiveness and guide treatment decisions. Furthermore, we proposed that targeting extracellular HMGA1 as monotherapy using monoclonal antibodies, or in combination with chemotherapy and other targeted therapies, could bring new therapeutic options for TNBC patients.

Cellular Interactions in the Tumor Microenvironment: The Role of Secretome

Over the past years, it has become evident that cancer initiation and progression depends on several components of the tumor microenvironment, including inflammatory and immune cells, fibroblasts, endothelial cells, adipocytes, and extracellular matrix. These components of the tumor microenvironment and the neoplastic cells interact with each other providing pro and antitumor signals. The tumor-stroma communication occurs directly between cells or via a variety of molecules secreted, such as growth factors, cytokines, chemokines and microRNAs. This secretome, which derives not only from tumor cells but also from cancer-associated stromal cells, is an important source of key regulators of the tumorigenic process. Their screening and characterization could provide useful biomarkers to improve cancer diagnosis, prognosis, and monitoring of treatment responses.

Oncoproteomics: Current status and future opportunities

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.

Extracellular HMGA1 Promotes Tumor Invasion and Metastasis in Triple-Negative Breast Cancer

PURPOSE

The study of the cancer secretome suggests that a fraction of the intracellular proteome could play unanticipated roles in the extracellular space during tumorigenesis. A project aimed at investigating the invasive secretome led us to study the alternative extracellular function of the nuclear protein high mobility group A1 (HMGA1) in breast cancer invasion and metastasis.

EXPERIMENTAL DESIGN

Antibodies against HMGA1 were tested in signaling, adhesion, migration, invasion, and metastasis assays using breast cancer cell lines and xenograft models. Fluorescence microscopy was used to determine the subcellular localization of HMGA1 in cell lines, xenograft, and patient-derived xenograft models. A cohort of triple-negative breast cancer (TNBC) patients was used to study the correlation between subcellular localization of HMGA1 and the incidence of metastasis.

RESULTS

Our data show that treatment of invasive cells with HMGA1-blocking antibodies in the extracellular space impairs their migration and invasion abilities. We also prove that extracellular HMGA1 (eHMGA1) becomes a ligand for the Advanced glycosylation end product-specific receptor (RAGE), inducing pERK signaling and increasing migration and invasion. Using the cytoplasmic localization of HMGA1 as a surrogate marker of secretion, we showed that eHMGA1 correlates with the incidence of metastasis in a cohort of TNBC patients. Furthermore, we show that HMGA1 is enriched in the cytoplasm of tumor cells at the invasive front of primary tumors and in metastatic lesions in xenograft models.

CONCLUSIONS

Our results strongly suggest that eHMGA1 could become a novel drug target in metastatic TNBC and a biomarker predicting the onset of distant metastasis.

Gaining insights into cancer biology through exploration of the cancer secretome using proteomic and bioinformatic tools

INTRODUCTION

Tumor-associated proteins released by cancer cells and by tumor stroma cells, referred as 'cancer secretome', represent a valuable resource for discovery of potential cancer biomarkers. The last decade was marked by a great increase in number of studies focused on various aspects of cancer secretome including, composition and identification of components externalized by malignant cells and by the components of tumor microenvironment. Areas covered: Here, we provide an overview of achievements in the proteomic analysis of the cancer secretome, elicited through the tumor-associated interstitial fluid recovered from malignant tissues ex vivo or the protein component of conditioned media obtained from cultured cancer cells in vitro. We summarize various bioinformatic tools and approaches and critically appraise their outcomes, focusing on problems and challenges that arise when applied for the analysis of cancer secretomic databases. Expert commentary: Recent achievements in the omics- analysis of structural and metabolic aspects of altered cancer secretome contribute greatly to the various hallmarks of cancer including the identification of clinically significant biomarkers and potential targets for therapeutic intervention.

Proteomic approaches to decipher cancer cell secretome

In this review, we give an overview of the actual proteomic approaches used in the study of cancer cells secretome. In particular, we describe the proteomic strategies to decipher cancer cell secretome initially focusing on the different aspects of sample preparation. We examine the issues related to the presence of low abundant proteins, the analysis of secreted proteins in the conditioned media with or without the removal of fetal bovine serum and strategies developed to reduce intracellular protein contamination. As regards the identification and quantification of secreted proteins, we described the different proteomic approaches used, i.e. gel-based, MS-based (label-based and label-free), and the antibody and array-based methods, together with some of the most recent applications in the field of cancer research. Moreover, we describe the bioinformatics tools developed for the in silico validation and characterization of cancer cells secretome. We also discuss the most important available tools for protein annotation and for prediction of classical and non-classical secreted proteins. In summary in this review advances, concerns and challenges in the field of cancer secretome analysis are discussed.

Identification of Filamin-A and -B as potential biomarkers for prostate cancer

Aim:

A novel strategy for prostate cancer (PrCa) biomarker discovery is described.

Materials & methods:

In vitro perturbation biology, proteomics and Bayesian causal analysis identified biomarkers that were validated in in vitro models and clinical specimens.

Results:

Filamin-B (FLNB) and Keratin-19 were identified as biomarkers. Filamin-A (FLNA) was found to be causally linked to FLNB. Characterization of the biomarkers in a panel of cells revealed differential mRNA expression and regulation. Moreover, FLNA and FLNB were detected in the conditioned media of cells. Last, in patients without PrCa, FLNA and FLNB blood levels were positively correlated, while in patients with adenocarcinoma the relationship is dysregulated.

Conclusion:

These data support the strategy and the potential use of the biomarkers for PrCa.

The goal of this study was to use a novel strategy that combines biological outputs with Bayesian network learning to identify potential biomarkers for prostate cancer (PrCa). This methodology identified two proteins, filamin B and keratin-19, as potential biomarkers for PrCa. The network map also identified a direct linkage between filamin B and filamin A, which is a protein that has previously been identified as playing a role in PrCa etiology. The identified proteins were then validated by examining their levels in a panel of PrCa cell lines and in human plasma samples.

Urinary proteomics and metabolomics studies to monitor bladder health and urological diseases

Background

Assays of molecular biomarkers in urine are non-invasive compared to other body fluids and can be easily repeated. Based on the hypothesis that the secreted markers from the diseased organs may locally release into the body fluid in the vicinity of the injury, urine-based assays have been considered beneficial to monitoring bladder health and urological diseases. The urine proteome is much less complex than the serum and tissues, but nevertheless can contain biomarkers for diagnosis and prognosis of diseases. The urine metabolome has a much higher number and concentration of low-molecular metabolites than the serum or tissues, with a far lower lipid concentration, yet informs directly about dietary and microbial metabolism.

Discussion

We here discuss the use of mass spectrometry-based proteomics and metabolomics for urine biomarker assays, specifically with respect to the underlying mechanisms that trigger the pathological condition.

Conclusion

Molecular biomarker profiles, based on proteomics and metabolomics studies, reliably distinguish patients from healthy controls, stratify sub-populations with respect to treatment options, and predict therapeutic response of patients with urological disease.