Nanonets Collect Cancer Secretome from Pericellular Space

Identifying novel cancer biomarkers is important for early cancer detection as it can reduce mortality rates. The cancer secretome, the collection of all macromolecules secreted by a tumor cell, alters its composition compared to normal tissue, and this change plays an important role in the observation of cancer progression. The collection and accurate analysis of cancer secretomes could lead to the discovery of novel biomarkers, thus improving outcomes of cancer treatment. We unexpectedly discovered that enzyme-instructed self-assembly (EISA) of a D-peptide hydrogelator results in nanonets/hydrogel around cancer cells that overexpress ectophosphatases. Here we show that these nanonets are able to rapidly collect proteins in the pericellular space (i.e., near the surface) of cancer cells. Because the secretory substances are at their highest concentration near the cell surface, the use of pericellular nanonets to collect the cancer secretome maximizes the yield and quality of samples, reduces pre-analytical variations, and allows the dynamic profiling of secretome samples. Thus, this new approach has great potential in identifying the heterotypic signaling in tumor microenvironments thereby improving the understanding of tumor microenvironments and accelerating the discovery of potential biomarkers in cancer biology. Data are available via ProteomeXchange with identifier PXD003924.     

A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer

Cancer secretomes are a promising source for biomarker discovery. The analysis of cancer secretomes still faces some difficulties mainly related to the intracellular contamination, which hinders the qualification and follow-up validations. This study aimed to establish a high-quality secretome of A549 cells by using the cellular proteome as a reference and to test the merits of this refined secretome for biomarker discovery for non-small cell lung cancer (NSCLC). Using one-dimensional gel electrophoresis followed by liquid-chromatography tandem mass spectrometry, we comprehensively investigated the secretome and the concurrent cellular proteome of A549 cells. A high-quality secretome consisting of 382 proteins was refined from 889 initial secretory proteins. More than 85.3% of proteins were annotated as secreted and 76.8% as extracellular or membrane-bound. The discriminative power of the lung-cancer associated secretome was confirmed by gene expression and serum proteomic data. The elevated level of C4b-binding Protein (C4BP) in NSCLC blood was verified by enzyme-linked immunosorbent assays (ELISA, p = 6.07e-6). Moreover, the serum C4BP level in 89 patients showed a strong association with the clinical staging of NSCLC. Our reference-experiment-driven strategy is simple and widely applicable, and may facilitate the identification of novel promising biomarkers of lung cancer.     

Glioblastoma cell secretome: analysis of three glioblastoma cell lines reveal 148 non-redundant proteins

Glioblastoma multiforme (GBM) is the most aggressive among human gliomas with poor prognosis. Study of tumor cell secretome - proteins secreted by cancer cell lines, is a powerful approach to discover potential diagnostic or prognostic biomarkers. Here we report, for the first time, proteins secreted by three GBM cell lines, HNGC2, LN229 and U87MG. Analysis of the conditioned media of these cell lines by LC-MS/MS using ESI-IT mass spectrometer (LTQ) resulted in the confident identification of 102, 119 and 64 proteins, respectively. Integration of the results from all the three cell lines lead to a dataset of 148 non-redundant proteins. Subcellular classification using Genome Ontology indicated that 42% of the proteins identified belonged to extracellular or membrane proteins, viz. Vinculin, Tenascin XB, SERPIN F1 and TIMP-1. 52 proteins matched with the secretomes of 11 major cancer types reported earlier whereas remaining 96 are unique to our study. 25 protein identifications from the dataset represent proteins related to GBM or other cancer tissues as per Human Protein Atlas; at least 22 are detectable in plasma, 11 of them being reported even in cerebrospinal fluid. Our study thus provides a valuable resource of GBM cell secretome with potential for further investigation as GBM biomarkers.     

Identification of collapsin response mediator protein-2 as a potential marker of colorectal carcinoma by comparative analysis of cancer cell secretomes

The cancer cell secretome may contain many potentially useful biomarkers. We therefore sought to identify proteins in the conditioned media of colorectal carcinoma (CRC) cell lines but not in those from other cancer cell lines. The secretomes of 21 cancer cell lines derived from 12 cancer types were analyzed by SDS-PAGE combined with MALDI-TOF MS. Among the 325 proteins identified, collapsin response mediator protein-2 (CRMP-2) was chosen for evaluation as a potential CRC biomarker, since it was selectively detected in the CRC cell line secretome and has never been reported as a cancer biomarker. Immunohistochemical analysis of 169 CRC specimens showed that CRMP-2 was positively detected in 58.6% of the tumors, but weakly or not detected in >90% of the adjacent nontumor epithelial cells. Moreover, the CRMP-2-positive rate was significantly increased in earlier stage tumors and lymph node metastasis. Plasma CRMP-2 levels were significantly higher in CRC patients (N = 201) versus healthy controls (N = 201) (61.3 +/- 34.6 vs. 40.2 +/- 24.3 ng/mL, p = 0.001). Our results indicate that comparative analysis of cancer cell secretome is a feasible strategy for identifying potential cancer biomarkers, and that CRMP-2 may be a novel CRC biomarker.     

Secreted proteins as a fundamental source for biomarker discovery

The proteins secreted by various cells (the secretomes) are a potential rich source of biomarkers as they reflect various states of the cells at real time and at given conditions. To have accessible, sufficient and reliable protein markers is desirable as they mark various stages of disease development and their presence/absence can be used for diagnosis, prognosis, risk stratification and therapeutic monitoring. As direct analysis of blood/plasma, a common and noninvasive patient screening method, can be difficult for candidate protein biomarker identification, the alternative/complementary approaches are required, one of them is the analysis of secretomes in cell conditioned media in vitro. As the proteins secreted by cells as a response to various stimuli are most likely secreted into blood/plasma, the identification and pre-selection of candidate protein biomarkers from cell secretomes with subsequent validation of their presence at higher levels in serum/plasma is a promising approach. In this review, we discuss the proteins secreted by three progenitor cell types (smooth muscle, endothelial and cardiac progenitor cells) and two adult cell types (neonatal rat ventrical myocytes and smooth muscle cells) which can be relevant to cardiovascular research and which have been recently published in the literature. We found, at least for secretome studies included in this review, that secretomes of progenitor and adult cells overlap by 48% but the secretomes are very distinct among progenitor cell themselves as well as between adult cells. In addition, we compared secreted proteins to protein identifications listed in the Human Plasma PeptideAtlas and in two reports with cardiovascular-related proteins and we performed the extensive literature search to find if any of these secreted proteins were identified in a biomarker study. As expected, many proteins have been identified as biomarkers in cancer but 18 proteins (out of 62) have been tested as biomarkers in cardiovascular diseases as well.     

Mass spectrometric proteomics profiles of in vivo tumor secretomes: capillary ultrafiltration sampling of regressive tumor masses

Identification of in vivo secreted peptides/proteins (secretomes) in tumor masses has the potential to provide important biomarkers and therapeutic targets for cancer therapy. However, limitations of existing technologies have made obtaining these secretomes for analysis extremely difficult. Here we employed an in vivo sampling technique using capillary ultrafiltration (CUF) probes to collect secretomes directly from tumor masses. Mass spectrometric proteomics approaches were then used to identify the tumor secretomes. A UV-induced skin fibrosarcoma cell line (UV-2240) was subcutaneously injected into C3H/NeH mice, resulting in tumor masses that initially progressed, then regressed and eventually eradicated. We then implanted CUF probes into tumor masses at the progressive and regressive stage. Five secreted proteins (cyclophilin-A, S100A4, profilin-1, thymosin beta 4 and 10), previously associated with tumor progression, were identified from tumor masses at the progressive stage. Five secreted proteins including three protease inhibitors (fetuin-A, alpha-1 antitrypsin 1-6, and contrapsin) were identified from tumor masses at the regressive stage. The technique involving CUF probes linked to mass spectrometric proteomics reinforces systems biology studies of cell-cell interactions and is potentially applicable to the discovery of in vivo biomarkers in human disease.     

Mining the gastric cancer secretome: identification of GRN as a potential diagnostic marker for early gastric cancer

Gastric cancer is the second leading cause of cancer deaths worldwide, and currently, there are no clinically relevant biomarkers for gastric cancer diagnosis or prognosis. In this study, we applied a 2D-LC-MS/MS based approach, in combination with iTRAQ labeling, to study the secretomes of the gastric cancer cell lines AGS and MKN7. By performing a comparative analysis between the conditioned media and the whole cell lysates, our workflow allowed us to differentiate the bona fide secreted proteins from the intracellular contaminants within the conditioned media. Ninety proteins were found to have higher abundance in the conditioned media as compared to the whole cell lysates of AGS and MKN7 cells. Using a signal peptide and nonclassical secretion prediction tool and an online exosome database, we demonstrated that up to 92.2% of these 90 proteins can be exported out of the cells by classical or nonclassical secretory pathways. We then performed quantitative comparisons of the secretomes between AGS and MKN7, identifying 43 differentially expressed secreted proteins. Among them, GRN was found to be frequently expressed in gastric tumor tissues, but not in normal gastric epithelia by immunohistochemistry. Sandwich ELISA assay also showed elevation of serum GRN levels in gastric cancer patients, particularly those with early gastric cancer. Receiver operating characteristic (ROC) curves analysis confirmed that serum GRN can provide diagnostic discriminations for gastric cancer patients.     

Secretome analysis using a hollow fiber culture system for cancer biomarker discovery

Secreted proteins, collectively referred to as the secretome, were suggested as valuable biomarkers in disease diagnosis and prognosis. However, some secreted proteins from cell cultures are difficult to detect because of their intrinsically low abundance; they are frequently masked by the released proteins from lysed cells and the substantial amounts of serum proteins used in culture medium. The hollow fiber culture (HFC) system is a commercially available system composed of small fibers sealed in a cartridge shell; cells grow on the outside of the fiber. Recently, because this system can help cells grow at a high density, it has been developed and applied in a novel analytical platform for cell secretome collection in cancer biomarker discovery. This article focuses on the advantages of the HFC system, including the effectiveness of the system for collection of secretomes, and reviews the process of cell secretome collection by the HFC system and proteomic approaches to discover cancer biomarkers. The HFC system not only provides a high-density three-dimensional (3D) cell culture system to mimic tumor growth conditions in vivo but can also accommodate numerous cells in a small volume, allowing secreted proteins to be accumulated and concentrated. In addition, cell lysis rates can be greatly reduced, decreasing the amount of contamination by abundant cytosolic proteins from lysed cells. Therefore, the HFC system is useful for preparing a wide range of proteins from cell secretomes and provides an effective method for collecting higher amounts of secreted proteins from cancer cells. This article is part of a Special Issue entitled: An Updated Secretome.     

Sieving through the cancer secretome

Cancer is among the most prevalent and serious health problems worldwide. Therefore, there is an urgent need for novel cancer biomarkers with high sensitivity and specificity for early detection and management of the disease. The cancer secretome, encompassing all the proteins that are secreted by cancer cells, is a promising source of biomarkers as the secreted proteins are most likely to enter the blood circulation. Moreover, since secreted proteins are responsible for signaling and communication with the tumor microenvironment, studying the cancer secretome would further the understanding of cancer biology. Latest developments in proteomics technologies have significantly advanced the study of the cancer secretome. In this review, we will present an overview of the secretome sample preparation process and summarize the data from recent secretome studies of six common cancers with high mortality (breast, colorectal, gastric, liver, lung and prostate cancers). In particular, we will focus on the various platforms that were employed and discuss the clinical applicability of the key findings in these studies. This article is part of a Special Issue entitled: An Updated Secretome.     

Negative regulators of cell death pathways in cancer: perspective on biomarkers and targeted therapies

Cancer is a primary cause of human fatality and conventional cancer therapies, e.g., chemotherapy, are often associated with adverse side-effects, tumor drug-resistance, and recurrence. Molecularly targeted therapy, composed of small-molecule inhibitors and immunotherapy (e.g., monoclonal antibody and cancer vaccines), is a less harmful alternative being more effective against cancer cells whilst preserving healthy tissues. Drug-resistance, however, caused by negative regulation of cell death signaling pathways, is still a challenge. Circumvention of negative regulators of cell death pathways or development of predictive and response biomarkers is, therefore, quintessential. This review critically discusses the current state of knowledge on targeting negative regulators of cell death signaling pathways including apoptosis, ferroptosis, necroptosis, autophagy, and anoikis and evaluates the recent advances in clinical and preclinical research on biomarkers of negative regulators. It aims to provide a comprehensive platform for designing efficacious polytherapies including novel agents for restoring cell death signaling pathways or targeting alternative resistance pathways to improve the chances for antitumor responses. Overall, it is concluded that nonapoptotic cell death pathways are a potential research arena for drug discovery, development of novel biomarkers and targeted therapies.     

N-glycoproteome Analysis of the Secretome of Human Metastatic Hepatocellular Carcinoma Cell Lines Combining Hydrazide Chemistry,HILIC Enrichment and Mass Spectrometry

Cancer cell metastasis is a major cause of cancer death. Unfortunately, the underlying molecular mechanisms remain unknown, which results in the lack of efficient diagnosis, therapy and prevention approaches. Nevertheless, the dysregulation of the cancer cell secretome is known to play key roles in tumor transformation and progression. The majority of proteins in the secretome are secretory proteins and membrane-released proteins, and, mostly, the glycosylated proteins. Until recently, few studies have explored protein N-glycosylation changes in the secretome, although protein glycosylation has received increasing attention in the study of tumor development processes. Here, the N-glycoproteins in the secretome of two human hepatocellular carcinoma (HCC) cell lines with low (MHCC97L) or high (HCCLM3) metastatic potential were investigated with a in-depth characterization of the N-glycosites by combining two general glycopeptide enrichment approaches, hydrazide chemistry and zwitterionic hydrophilic interaction chromatography (zic-HILIC), with mass spectrometry analysis. A total of 1,213 unique N-glycosites from 611 N-glycoproteins were confidently identified. These N-glycoproteins were primarily localized to the extracellular space and plasma membrane, supporting the important role of N-glycosylation in the secretory pathway. Coupling label-free quantification with a hierarchical clustering strategy, we determined the differential regulation of several N-glycoproteins that are related to metastasis, among which AFP, DKK1, FN1, CD151 and TGFβ2 were up-regulated in HCCLM3 cells. The inclusion of the well-known metastasis-related proteins AFP and DKK1 in this list provides solid supports for our study. Further western blotting experiments detecting FN1 and FAT1 confirmed our discovery. The glycoproteome strategy in this study provides an effective means to explore potential cancer biomarkers.     

Disagreements in the therapeutic use of mesenchymal stem cell-derived secretome

In a recent article, the authors provide a detailed summary of the characteristics and biological functions of mesenchymal stem cells (MSCs), as well as a discussion on the potential mechanisms of action of MSC-based therapies. They describe the morphology, biogenesis, and current isolation techniques of exosomes, one of the most important fractions of the MSC-derived secretome. They also summarize the characteristics of MSC-derived exosomes and highlight their functions and therapeutic potential for tissue/organ regeneration and for kidney, liver, cardiovascular, neurological, and musculoskeletal diseases, as well as cutaneous wound healing. Despite the fact that MSCs are regarded as an important pillar of regenerative medicine, their regenerative potential has been demonstrated to be limited in a number of pathological conditions. The negative effects of MSC-based cell therapy have heightened interest in the therapeutic use of MSC-derived secretome. On the other hand, MSC-derived exosomes and microvesicles possess the potential to have a significant impact on disease development, including cancer. MSCs can interact with tumor cells and promote mutual exchange and induction of cellular markers by exchanging secretome. Furthermore, enzymes secreted into and activated within exosomes can result in tumor cells acquiring new properties. As a result, therapeutic applications of MSC-derived secretomes must be approached with extreme caution.     

Breast tumor microenvironment: proteomics highlights the treatments targeting secretome

Tumor secreted substances (secretome), including extracellular matrix (ECM) components, act as mediators of tumor-host communication in the breast tumor microenvironment. Proteomic analysis has emphasized the value of the secretome as a source of prospective markers and drug targets for the treatment of breast cancers. Utilizing bioinformatics, our recent studies revealed global changes in protein expression after the activation of ECM-mediated signaling in breast cancer cells. A newly designed technique integrating a capillary ultrafiltration (CUF) probe with mass spectrometry was demonstrated to dynamically sample and identify in vivo and pure secretome from the tumor microenvironment. Such in vivo profiling of breast cancer secretomes may facilitate the development of novel drugs specifically targeting secretome.     

Identification of secreted proteins that reflect autophagy dynamics within tumor cells

Macroautophagy, a catabolic process of cellular self-digestion, is an important tumor cell survival mechanism and a potential target in antineoplastic therapies. Recent discoveries have implicated autophagy in the cellular secretory process, but potential roles of autophagy-mediated secretion in modifying the tumor microenvironment are poorly understood. Furthermore, efforts to inhibit autophagy in clinical trials have been hampered by suboptimal methods to quantitatively measure tumor autophagy levels. Here, we leveraged the autophagy-based involvement in cellular secretion to identify shed proteins associated with autophagy levels in melanoma. The secretome of low-autophagy WM793 melanoma cells was compared to its highly autophagic metastatic derivative, 1205Lu in physiological 3-dimensional cell culture using quantitative proteomics. These comparisons identified candidate autophagy biomarkers IL1B (interleukin 1, β), CXCL8 (chemokine (C-X-C motif) ligand 8), LIF (leukemia inhibitory factor), FAM3C (family with sequence similarity 3, member C), and DKK3 (dickkopf WNT signaling pathway inhibitor 3) with known roles in inflammation and tumorigenesis, and these proteins were subsequently shown to be elevated in supernatants of an independent panel of high-autophagy melanoma cell lines. Secretion levels of these proteins increased when low-autophagy melanoma cells were treated with the autophagy-inducing tat-BECN1 (Beclin 1) peptide and decreased when ATG7 (autophagy-related 7) was silenced in high-autophagy cells, thereby supporting a mechanistic link between these secreted proteins and autophagy. In addition, serum from metastatic melanoma patients with high tumor autophagy levels exhibited higher levels of these proteins than serum from patients with low-autophagy tumors. These results suggest that autophagy-related secretion affects the tumor microenvironment and measurement of autophagy-associated secreted proteins in plasma and possibly in tumors can serve as surrogates for intracellular autophagy dynamics in tumor cells.     

Identification of proteins secreted by head and neck cancer cell lines using LC-MS/MS: Strategy for discovery of candidate serological biomarkers

In search of blood-based biomarkers that would enhance the ability to diagnose head and neck/oral squamous cell carcinoma (HNOSCC) in early stages or predict its prognosis, we analyzed the HNOSCC secretome (ensemble of proteins secreted and/or shed from the tumor cells) for potential biomarkers using proteomic technologies. LC-MS/MS was used to identify proteins in the conditioned media of four HNOSCC cell lines (SCC4, HSC2, SCC38, and AMOSIII); 140 unique proteins were identified on the basis of 5% global false discovery rate, 122 of which were secretory proteins, with 29 being previously reported to be overexpressed in HNOSCC in comparison to normal head and neck tissues. Of these, five proteins including α-enolase, peptidyl prolyl isomerase A/cyclophilin A, 14-3-3 ζ, heterogeneous ribonucleoprotein K, and 14-3-3 σ were detected in the sera of HNOSCC patients by Western blot analysis. Our study provides the evidence that analysis of head and neck cancer cells' secretome is a viable strategy for identifying candidate serological biomarkers for HNOSCC. In future, these biomarkers may be useful in predicting the likelihood of transformation of oral pre-malignant lesions, prognosis of HNOSCC patients and evaluate response to therapy using minimally invasive tests.     

Candidate Serological Biomarkers for Cancer Identified from the Secretomes of 23 Cancer Cell Lines and the Human Protein Atlas

Although cancer cell secretome profiling is a promising strategy used to identify potential body fluid-accessible cancer biomarkers, questions remain regarding the depth to which the cancer cell secretome can be mined and the efficiency with which researchers can select useful candidates from the growing list of identified proteins. Therefore, we analyzed the secretomes of 23 human cancer cell lines derived from 11 cancer types using one-dimensional SDS-PAGE and nano-LC-MS/MS performed on an LTQ-Orbitrap mass spectrometer to generate a more comprehensive cancer cell secretome. A total of 31,180 proteins was detected, accounting for 4,584 non-redundant proteins, with an average of 1,300 proteins identified per cell line. Using protein secretion-predictive algorithms, 55.8% of the proteins appeared to be released or shed from cells. The identified proteins were selected as potential marker candidates according to three strategies: (i) proteins apparently secreted by one cancer type but not by others (cancer type-specific marker candidates), (ii) proteins released by most cancer cell lines (pan-cancer marker candidates), and (iii) proteins putatively linked to cancer-relevant pathways. We then examined protein expression profiles in the Human Protein Atlas to identify biomarker candidates that were simultaneously detected in the secretomes and highly expressed in cancer tissues. This analysis yielded 6–137 marker candidates selective for each tumor type and 94 potential pan-cancer markers. Among these, we selectively validated monocyte differentiation antigen CD14 (for liver cancer), stromal cell-derived factor 1 (for lung cancer), and cathepsin L1 and interferon-induced 17-kDa protein (for nasopharyngeal carcinoma) as potential serological cancer markers. In summary, the proteins identified from the secretomes of 23 cancer cell lines and the Human Protein Atlas represent a focused reservoir of potential cancer biomarkers.Cancer is a major cause of mortality worldwide, accounting for 10 million new cases and more than 6 million deaths per year. In developing countries, cancer is the second most common cause of death, accounting for 23–25% of the overall mortality rate (1). Notwithstanding improvements in diagnostic imaging technologies and medical treatments, the long term survival of most cancer patients is poor. Cancer therapy is often challenging because the majority of cancers are initially diagnosed in their advanced stages. For example, the 5-year survival rate for patients with HNC¹ is less than 50%. More than 50% of all HNC patients have advanced disease at the time of diagnosis (2, 3). Enormous effort has been devoted to screening and characterizing cancer markers for the early detection of cancer. Thus far, these markers include carcinoembryonic antigen, prostate-specific antigen, α-fetoprotein, CA 125, CA 15-3, and CA 19-9. Unfortunately, most biomarkers have limited specificity, sensitivity, or both (4). Thus, there is a growing consensus that marker panels, which are more sensitive and specific than individual markers, would increase the efficacy and accuracy of early stage cancer detection (4–8). The development of novel and useful biomarker panels is therefore an urgent need in the field of cancer management.Proteomics technology platforms are promising tools for the discovery of new cancer biomarkers (9). Over the past decade, serum and plasma have been the major targets of proteomics studies aimed at identifying potential cancer biomarkers (10–13). However, the progress of these studies has been hampered by the complex nature of serum/plasma samples and the large dynamic range between the concentrations of different proteins (14). As cancer biomarkers are likely to be present in low amounts in blood samples, the direct isolation of these markers from plasma and serum samples requires a labor-intensive process involving the depletion of abundant proteins and extensive protein fractionation prior to mass spectrometric analysis (15–18). Alternatively, the secretome, or group of proteins secreted by cancer cells (19), can be analyzed to identify circulating molecules present at elevated levels in serum or plasma samples from cancer patients. These proteins have the potential to act as cancer-derived marker candidates, which are distinct from host-responsive marker candidates. We, along with other groups, have demonstrated the efficacy of secretome-based strategies in a variety of cancer types, including NPC (20), breast cancer (21, 22), lung cancer (23, 24), CRC (25, 26), oral cancer (27), prostate cancer (28, 29), ovarian cancer (30), and Hodgkin lymphoma (31). In these studies, proteins secreted from cancer cells into serum-free media were resolved by one- or two-dimensional gels followed by in-gel tryptic digestion and analysis via MALDI-TOF MS or LC-MS/MS. Alternatively, the proteins were trypsin-digested in solution and analyzed by LC-MS/MS. In general, more proteins were detected in the secretome using the LC-MS/MS method than the MALDI-TOF MS method. Advanced protein separation and identification technologies have made it possible to detect more proteins in the secretomes of cancer cells, thereby facilitating the discovery of cancer biomarkers.Although the cancer cell secretomes of various tumor types have been individually analyzed by different groups using distinct protocols, few studies have used the same protocol to compare cancer cell secretomes derived from different tumor types. We previously assessed the secretomes of 21 cancer cell lines derived from 12 cancer types (i.e. consisting of 795 protein identities and 325 non-redundant proteins) by one-dimensional gel and MALDI-TOF MS (25). Our preliminary findings revealed that different cell lines have distinct secreted protein profiles and that several putative biomarkers, such as Mac-2BP (20, 26, 27, 29) and cathepsin D (21, 23, 32), present in the secretome of a given cancer cell type are commonly shared among different cancers. These observations suggest that an in-depth comparison of secretomes derived from different tumor types may identify marker candidates common to most cancers as well as markers for specific cancer types. As an increasing number of proteins are identified in the secretomes of various cancer cell lines, scientists are faced with the challenge of quickly and efficiently narrowing down the list to candidates with higher chances of success during validation testing with precious clinical specimens.In the present study, we applied one-dimensional SDS-PAGE in conjunction with nano-LC-MS/MS (GeLC-MS/MS) (33, 34) to analyze the conditioned media of 23 cancer cell lines derived from 11 cancer types, including NPC, breast cancer, bladder cancer, cervical cancer, CRC, epidermoid carcinoma, liver cancer, lung cancer, T cell lymphoma, oral cancer, and pancreatic cancer. Within this data set, 4,584 non-redundant proteins were identified from a total of 23 cell lines, yielding an average of ∼1,300 proteins per cell line. Potential marker candidates were identified via the comparative analysis of different cell line secretomes and by putative linkages to cancer-relevant pathways. The selected proteins were further compared with the HPA (35) to generate a focused data set of proteins that are secreted or released, cancer type-specific, and highly expressed in human cancer tissues. Finally, we selectively validated four proteins as potential serological cancer markers using blood samples from cancer patients.     

Identification of secreted proteins that reflect autophagy dynamics within tumor cells

Macroautophagy, a catabolic process of cellular self-digestion, is an important tumor cell survival mechanism and a potential target in antineoplastic therapies. Recent discoveries have implicated autophagy in the cellular secretory process, but potential roles of autophagy-mediated secretion in modifying the tumor microenvironment are poorly understood. Furthermore, efforts to inhibit autophagy in clinical trials have been hampered by suboptimal methods to quantitatively measure tumor autophagy levels. Here, we leveraged the autophagy-based involvement in cellular secretion to identify shed proteins associated with autophagy levels in melanoma. The secretome of low-autophagy WM793 melanoma cells was compared to its highly autophagic metastatic derivative, 1205Lu in physiological 3-dimensional cell culture using quantitative proteomics. These comparisons identified candidate autophagy biomarkers IL1B (interleukin 1, β), CXCL8 (chemokine (C-X-C motif) ligand 8), LIF (leukemia inhibitory factor), FAM3C (family with sequence similarity 3, member C), and DKK3 (dickkopf WNT signaling pathway inhibitor 3) with known roles in inflammation and tumorigenesis, and these proteins were subsequently shown to be elevated in supernatants of an independent panel of high-autophagy melanoma cell lines. Secretion levels of these proteins increased when low-autophagy melanoma cells were treated with the autophagy-inducing tat-BECN1 (Beclin 1) peptide and decreased when ATG7 (autophagy-related 7) was silenced in high-autophagy cells, thereby supporting a mechanistic link between these secreted proteins and autophagy. In addition, serum from metastatic melanoma patients with high tumor autophagy levels exhibited higher levels of these proteins than serum from patients with low-autophagy tumors. These results suggest that autophagy-related secretion affects the tumor microenvironment and measurement of autophagy-associated secreted proteins in plasma and possibly in tumors can serve as surrogates for intracellular autophagy dynamics in tumor cells.     

The cancer secretome,current status and opportunities in the lung,breast and colorectal cancer context

Despite major improvements on the knowledge and clinical management, cancer is still a deadly disease. Novel biomarkers for better cancer detection, diagnosis and treatment prediction are urgently needed. Proteins secreted, shed or leaking from the cancer cell, collectively termed the cancer secretome, are promising biomarkers since they might be detectable in blood or other biofluids. Furthermore, the cancer secretome in part represents the tumor microenvironment that plays a key role in tumor promoting processes such as angiogenesis and invasion. The cancer secretome, sampled as conditioned medium from cell lines, tumor/tissue interstitial fluid or tumor proximal body fluids, can be studied comprehensively by nanoLC-MS/MS-based approaches. Here, we outline the importance of current cancer secretome research and describe the mass spectrometry-based analysis of the secretome. Further, we provide an overview of cancer secretome research with a focus on the three most common cancer types: lung, breast and colorectal cancer. We conclude that the cancer secretome research field is a young, but rapidly evolving research field. Up to now, the focus has mainly been on the discovery of novel promising secreted cancer biomarker proteins. An interesting finding that merits attention is that in cancer unconventional secretion, e.g. via vesicles, seems increased. Refinement of current approaches and methods and progress in clinical validation of the current findings are vital in order to move towards applications in cancer management. This article is part of a Special Issue entitled: An Updated Secretome.