Tissue culture-based breast cancer biomarker discovery platform

Analysis of Cancer Cell Line Secretomes: A Complementary Source of Disease-Specific Protein Biomarkers

Various types of cancer cells enrich or condition the medium that they are cultured in by secreting or shedding proteins and small molecules. These secreted or shed factors are involved in key biological processes, including cellular communication, proliferation, and migration, and are represented by protein families, including cytokines, growth factors, and enzymes. The rapid development of high-resolution mass spectrometry and shotgun strategies for proteome analysis facilitates the identification of these factors in biological models and elucidation of their potential roles in pathophysiology. Hence, the following protocol provides details on how to prepare proteins present in conditioned media for mass spectrometry analysis.

Phosphorylated Proteins from Serum: A Promising Potential Diagnostic Biomarker of Cancer

Cancer is a fatal disease worldwide. Each year ten million people are diagnosed around the world, and more than half of patients eventually die from it in many countries. A majority of cancer remains asymptomatic in the earlier stages, with specific symptoms appearing in the advanced stages when the chances of adequate treatment are low. Cancer screening is generally executed by different imaging techniques like ultrasonography (USG), mammography, CT-scan, and magnetic resonance imaging (MRI). Imaging techniques, however, fail to distinguish between cancerous and non-cancerous cells for early diagnosis. To confirm the imaging result, solid and liquid biopsies are done which have certain limitations such as invasive (in case of solid biopsy) or missed early diagnosis due to extremely low concentrations of circulating tumor DNA (in case of liquid biopsy). Therefore, it is essential to detect certain biomarkers by a noninvasive approach. One approach is a proteomic or glycoproteomic study which mostly identifies proteins and glycoproteins present in tissues and serum. Some of these studies are approved by the Food and Drug Administration (FDA). Another non-expensive and comparatively easier method to detect glycoprotein biomarkers is by ELISA, which uses lectins of diverse specificities. Several of the FDA approved proteins used as cancer biomarkers do not show optimal sensitivities for precise diagnosis of the diseases. In this regard, expression of phosphoproteins is associated with a more specific stage of a particular disease with high sensitivity and specificity. In this review, we discuss the expression of different serum phosphoproteins in various cancers. These phosphoproteins are detected either by phosphoprotein enrichment by immunoprecipitation using phosphospecific antibody and metal oxide affinity chromatography followed by LC-MS/MS or by 2D gel electrophoresis followed by MALDI-ToF/MS analysis. The updated knowledge on phosphorylated proteins in clinical samples from various cancer patients would help to develop these serum phophoproteins as potential diagnostic/prognostic biomarkers of cancer.

Application of metabolomics in the diagnosis of breast cancer: a systematic review

Breast cancer (BC) remains the most frequent type of cancer in females worldwide. However, the pathogenesis of BC is still under the cloud, along with the huge challenge of early diagnosis, which is widely acknowledged as the key to a successful therapy. Metabolomics, a newborn innovative technique in recent years, has demonstrated great potential in cancer-related researches. The aim of this review is to look back on clinical and cellular metabolomic studies in the diagnosis of BC over the past decade, and provide a systematic summary of metabolic biomarkers and pathways related to BC diagnosis.

Novel secretome-to-transcriptome integrated or secreto-transcriptomic approach to reveal liquid biopsy biomarkers for predicting individualized prognosis of breast cancer patients

Background

Presently, a 50-gene expression model (PAM50) serves as a breast cancer (BC) subtype classifier that is insufficient to distinguish, within each single PAM50-classified subtype, patient subpopulations having different prognosis. There is a pressing need for inexpensive and minimally invasive biomarker tests to easily and accurately predict individuals’ clinical outcomes and response to treatments. Although quantitative proteomic approaches have been developed to identify/profile proteins secreted (secretome) from various cancer cell lines in vitro, missing are the clinicopathological relevance and the associated prognostic value of these secretomic identifications.

Methods

To discover biomarkers to predict individualized prognosis we introduce a new multi-omics (secreto-transcriptomics) method that identifies, in their oncogenically secreted states, candidate markers of BC subtypes whose genes bear patient-specific mRNA expression alterations of prognostic significance. First, we used label-free quantitative (LFQ) proteomics to identify the proteins showing BC-subtypic secretion from a series of BC cell lines representing major BC-subtypes. To determine and externally validate the prognostic value of these secreted proteins, we developed a secreto-transcriptomic approach that discovered a PAM50-subtypic Secretion-Correlated mRNA Expression Pattern (SeCEP) wherein the PAM50-subtypic secretion of select proteins statistically correlated with cis-mRNA expression of their encoding genes in patients of the corresponding PAM50-subtypes. Kaplan-Meier analysis of SeCEP genes was used to identify new liquid biopsy biomarkers for predicting individualized prognosis.

Results

The mRNA expression-to-secretion correlation (SeCEP) pinpointed multiple genes that are fully translated into the oncogenically active secretome in a PAM50-subtypic manner. Further, multiple SeCEP genes in distinct combinations or panels of multiple SeCEP genes were identified as ‘systems prognostic markers’ that showed mRNA co-overexpression patterns in the distinct subpopulations of PAM50-subtypic patients with poor prognosis or high-risk of relapse. Thus, our secreto-transcriptomic approach statistically linked BC subtypic secretome genes with patient-specific information about their mRNA expression alterations and significantly improved the sensitivity and specificity in patient stratification in the context of clinical outcomes or prognosis.

Conclusions

By combining LFQ secretome screening with proteo-transcriptomic retrospective analysis of patient data our integrated multi-omics approach bypasses costly, tedious, genome-wide fishing and predictive modeling that are commonly required to distinguish a few prognostically altered genes from thousands of other non-BC related genes in a genome.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0530-7) contains supplementary material, which is available to authorized users.

The use of cell culture platforms to identify novel markers of bone and dentin resorption

OBJECTIVES

1) To test the hypothesis that there would be proteomic differences in the composition of exosomes isolated from osteoclasts and odontoclasts and 2) to determine the clinical usefulness of these in vitro biomarker candidates.

MATERIALS AND METHODS

Mouse bone marrow-derived precursors were cultured on either dentin or bone slices and allowed to mature and begin resorption. Exosomes were isolated from cell culture media and characterized by mass spectrometry. The proteomic data obtained from this in vitro study were compared with the data obtained from human samples in our previous work.

RESULTS

There was a difference in the proteomic composition of exosomes from osteoclasts and odontoclasts. A total of 40 exosomal proteins were only present in osteoclast media, whereas six unique exosomal proteins were identified in odontoclast supernatants. Approximately 50% of exosomal proteins released by clastic cells in vitro can be found in oral fluids.

CONCLUSION

Our data suggest that the mineralized matrix type plays a role in the final phenotypic characteristics of mouse clastic cells. Many in vitro biomarker candidates of bone and dentin resorption can also be found in human oral fluids, thus indicating that this approach may be a viable alternative in biomarker discovery.

In-depth analysis of secretome and N-glycosecretome of human hepatocellular carcinoma metastatic cell lines shed light on metastasis correlated proteins

Cancer cell metastasis is a major cause of cancer fatality. But the underlying molecular mechanisms remain incompletely understood, which results in the lack of efficient diagnosis, therapy and prevention approaches. Here, we report a systematic study on the secretory proteins (secretome) and secretory N-glycoproteins (N-glycosecretome) of four human hepatocellular carcinoma (HCC) cell lines with different metastatic potential, to explore the molecular mechanism of metastasis and supply the clues for effective measurement of diagnosis and therapy. Totally, 6242 unique gene products (GPs) and 1637 unique N-glycosites from 635 GPs were confidently identified. About 4000 GPs on average were quantified in each of the cell lines, 1156 of which show differential expression (p<0.05). Ninety-nine percentage of the significantly altered proteins were secretory proteins and proteins correlated to cell movement were significantly activated with the increasing of metastatic potential of the cell lines. Twenty-three GPs increased both in the secretome and the N-glycosecretome were chosen as candidates and verified by western blot analysis, and 10 of them were chosen for immunohistochemistry (IHC) analysis. The cumulative survival rates of the patients with candidate (FAT1, DKK3) suggested that these proteins might be used as biomarkers for HCC diagnosis. In addition, a comparative analysis with the published core human plasma database (1754 GPs) revealed that there were 182 proteins not presented in the human plasma database but identified by our studies, some of which were selected and verified successfully by western blotting in human plasma.

Proteomic Analysis of Exosomes and Exosome-Free Conditioned Media From Human Osteosarcoma Cell Lines Reveals Secretion of Proteins Related to Tumor Progression

Osteosarcomas are the most prevalent bone tumors in pediatric patients, but can also occur later in life. Bone tumors have the potential to metastasize to lung and occasionally other vital organs. To understand how osteosarcoma cells interact with their micro-environment to support bone tumor progression and metastasis, we analyzed secreted proteins and exosomes from three human osteosarcoma cell lines. Exosome isolation was validated by transmission electron microscopy (TEM) and immuno-blotting for characteristic biomarkers (CD63, CD9, and CD81). Exosomal and soluble proteins (less than 100 kDa) were identified by mass spectrometry analysis using nanoLC-MS/MS and classified by functional gene ontology clustering. We identified a secretome set of >3,000 proteins for both fractions, and detected proteins that are either common or unique among the three osteosarcoma cell lines. Protein ontology comparison of proteomes from exosomes and exosome-free fractions revealed differences in the enrichment of functional categories associated with different biological processes, including those related to tumor progression (i.e., angiogenesis, cell adhesion, and cell migration). The secretome characteristics of osteosarcoma cells are consistent with the pathological properties of tumor cells with metastatic potential. J. Cell. Biochem. 118: 351-360, 2017. © 2016 Wiley Periodicals, Inc.

Systems biology study of mucopolysaccharidosis using a human metabolic reconstruction network

Mucopolysaccharidosis (MPS) is a group of lysosomal storage diseases (LSD), characterized by the deficiency of a lysosomal enzyme responsible for the degradation of glycosaminoglycans (GAG). This deficiency leads to the lysosomal accumulation of partially degraded GAG. Nevertheless, deficiency of a single lysosomal enzyme has been associated with impairment in other cell mechanism, such as apoptosis and redox balance. Although GAG analysis represents the main biomarker for MPS diagnosis, it has several limitations that can lead to a misdiagnosis, whereby the identification of new biomarkers represents an important issue for MPS. In this study, we used a system biology approach, through the use of a genome-scale human metabolic reconstruction to understand the effect of metabolism alterations in cell homeostasis and to identify potential new biomarkers in MPS. In-silico MPS models were generated by silencing of MPS-related enzymes, and were analyzed through a flux balance and variability analysis. We found that MPS models used approximately 2286 reactions to satisfy the objective function. Impaired reactions were mainly involved in cellular respiration, mitochondrial process, amino acid and lipid metabolism, and ion exchange. Metabolic changes were similar for MPS I and II, and MPS III A to C; while the remaining MPS showed unique metabolic profiles. Eight and thirteen potential high-confidence biomarkers were identified for MPS IVB and VII, respectively, which were associated with the secondary pathologic process of LSD. In vivo evaluation of predicted intermediate confidence biomarkers (β-hexosaminidase and β-glucoronidase) for MPS IVA and VI correlated with the in-silico prediction. These results show the potential of a computational human metabolic reconstruction to understand the molecular mechanisms this group of diseases, which can be used to identify new biomarkers for MPS.

Proteomics in the Assessment of the Therapeutic Response of Antineoplastic Drugs: Strategies and Practical Applications

Uncovering unknown pathological mechanisms and body response to applied medication are the driving forces toward personalized medicine. In this post-genomic era, all eyes are turned to the proteomics field, searching for answers and explanations by investigating the gene end point functional units-proteins and their proteoforms. The development of cutting-edge mass spectrometric technologies and bioinformatics tools have allowed the life-science community to discover disease-specific proteins as biomarkers, which are often concealed by high sample complexity and dynamic range of abundance. Currently, there are several proteomics-based approaches to investigate the proteome. This chapter focuses on gold standard proteomics strategies and related issues toward candidate biomarker discovery, which may have diagnostic/prognostic as well as mechanistic utility in cancer drug resistance.

Identification of Circulating Biomarker Candidates for Hepatocellular Carcinoma (HCC): An Integrated Prioritization Approach

Hepatocellular carcinoma (HCC) is the world's third most widespread cancer. Currently available circulating biomarkers for this silently progressing malignancy are not sufficiently specific and sensitive to meet all clinical needs. There is an imminent and pressing need for the identification of novel circulating biomarkers to increase disease-free survival rate. In order to facilitate the selection of the most promising circulating protein biomarkers, we attempted to define an objective method likely to have a significant impact on the analysis of vast data generated from cutting-edge technologies. Current study exploits data available in seven publicly accessible gene and protein databases, unveiling 731 liver-specific proteins through initial enrichment analysis. Verification of expression profiles followed by integration of proteomic datasets, enriched for the cancer secretome, filtered out 20 proteins including 6 previously characterized circulating HCC biomarkers. Finally, interactome analysis of these proteins with midkine (MDK), dickkopf-1 (DKK-1), current standard HCC biomarker alpha-fetoprotein (AFP), its interacting partners in conjunction with HCC-specific circulating and liver deregulated miRNAs target filtration highlighted seven novel statistically significant putative biomarkers including complement component 8, alpha (C8A), mannose binding lectin (MBL2), antithrombin III (SERPINC1), 11β-hydroxysteroid dehydrogenase type 1 (HSD11B1), alcohol dehydrogenase 6 (ADH6), beta-ureidopropionase (UPB1) and cytochrome P450, family 2, subfamily A, polypeptide 6 (CYP2A6). Our proposed methodology provides a swift assortment process for biomarker prioritization that eventually reduces the economic burden of experimental evaluation. Further dedicated validation studies of potential putative biomarkers on HCC patient blood samples are warranted. We hope that the use of such integrative secretome, interactome and miRNAs target filtration approach will accelerate the selection of high-priority biomarkers for other diseases as well, that are more amenable to downstream clinical validation experiments.

Galectin-3 Binding Protein Secreted by Breast Cancer Cells Inhibits Monocyte-Derived Fibrocyte Differentiation

To metastasize, tumor cells often need to migrate through a layer of collagen-containing scar tissue which encapsulates the tumor. A key component of scar tissue and fibrosing diseases is the monocyte-derived fibrocyte, a collagen-secreting profibrotic cell. To test the hypothesis that invasive tumor cells may block the formation of the fibrous sheath, we determined whether tumor cells secrete factors that inhibit monocyte-derived fibrocyte differentiation. We found that the human metastatic breast cancer cell line MDA-MB-231 secretes activity that inhibits human monocyte-derived fibrocyte differentiation, whereas less aggressive breast cancer cell lines secrete less of this activity. Purification indicated that Galectin-3 binding protein (LGALS3BP) is the active factor. Recombinant LGALS3BP inhibits monocyte-derived fibrocyte differentiation, and immunodepletion of LGALS3BP from MDA-MB 231 conditioned media removes the monocyte-derived fibrocyte differentiation-inhibiting activity. LGALS3BP inhibits the differentiation of monocyte-derived fibrocytes from wild-type mouse spleen cells, but not from SIGN-R1(-/-) mouse spleen cells, suggesting that CD209/SIGN-R1 is required for the LGALS3BP effect. Galectin-3 and galectin-1, binding partners of LGALS3BP, potentiate monocyte-derived fibrocyte differentiation. In breast cancer biopsies, increased levels of tumor cell-associated LGALS3BP were observed in regions of the tumor that were invading the surrounding stroma. These findings suggest LGALS3BP and galectin-3 as new targets to treat metastatic cancer and fibrosing diseases.

Abnormal levels of heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) in tumour tissue and blood samples from patients diagnosed with lung cancer

Lung cancer is the second most common type of cancer in the world and is the most common cause of cancer-related death in both men and women. Research into causes, prevention and treatment of lung cancer is ongoing and much progress has been made recently in these areas, however survival rates have not significantly improved. Therefore, it is essential to develop biomarkers for early diagnosis of lung cancer, prediction of metastasis and evaluation of treatment efficiency, as well as using these molecules to provide some understanding about tumour biology and translate highly promising findings in basic science research to clinical application. In this investigation, two-dimensional difference gel electrophoresis and mass spectrometry were initially used to analyse conditioned media from a panel of lung cancer and normal bronchial epithelial cell lines. Significant proteins were identified with heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1), pyruvate kinase M2 isoform (PKM2), Hsc-70 interacting protein and lactate dehydrogenase A (LDHA) selected for analysis in serum from healthy individuals and lung cancer patients. hnRNPA2B1, PKM2 and LDHA were found to be statistically significant in all comparisons. Tissue analysis and knockdown of hnRNPA2B1 using siRNA subsequently demonstrated both the overexpression and potential role for this molecule in lung tumorigenesis. The data presented highlights a number of in vitro derived candidate biomarkers subsequently verified in patient samples and also provides some insight into their roles in the complex intracellular mechanisms associated with tumour progression.

Mass spectrometry-based proteomics in molecular diagnostics: discovery of cancer biomarkers using tissue culture

Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

Identificationof potential lung cancer biomarkers by liquid chromatography tandem mass spectrometry-based proteomics analysis of secretomes of two lung cancer cell lines

A label-free nano-liquid chromatography tandem mass spectrometry proteomics analysis on the conditioned media (CM) of two lung cancer cell lines of different histological backgrounds to identify secreted or membrane-bound proteins as novel lung cancer biomarkers was performed. Five hundred and seventy seven proteins were identified and 38% of them were classified as extracellular or membrane-bound. For the search of potential biomarkers of lung cancer a series of selection criteria were proposed. We detected known or putative lung cancer markers. In addition, 40 novel proteins were identified, whose role as biomarkers of lung cancer should be explored further.

Proteomic signatures of the desmoplastic invasion front reveal collagen type XII as a marker of myofibroblastic differentiation during colorectal cancer metastasis

Cancer-associated fibroblasts (CAFs), represent a pivotal compartment of solid cancers (desmoplasia), and are causatively implicated in cancer development and progression. CAFs are recruited by growth factors secreted by cancer cells and they present a myofibroblastic phenotype, similar to the one obtained by resident fibroblasts during wound healing. Paracrine signaling between cancer cells and CAFs results in a unique protein expression profile in areas of desmoplastic reaction, which is speculated to drive metastasis. In an attempt to decipher large-scale proteomic profiles of the cancer invasive margins, we developed an in vitro coculture model system, based on tumor-host cell interactions between colon cancer cells and CAFs. Proteomic analysis of conditioned media derived from these cocultures coupled to mass spectrometry and bioinformatic analysis was performed to uncover myofibroblastic signatures of the cancer invasion front. Our analysis resulted in the identification and generation of a desmoplastic protein dataset (DPD), consisting of 152 candidate proteins of desmoplasia. By using monoculture exclusion datasets, a secretome algorithm and gene-expression meta-analysis in DPD, we specified a 22-protein “myofibroblastic signature” with putative importance in the regulation of colorectal cancer metastasis. Of these proteins, we investigated collagen type XII by immunohistochemistry, a fibril-associated collagen with interrupted triple helices (FACIT), whose expression has not been reported in desmoplastic lesions in any type of cancer. Collagen type XII was highly expressed in desmoplastic stroma by and around alpha-smooth muscle actin (α-SMA) positive CAFs, as well as in cancer cells lining the invasion front, in a small cohort of colon cancer patients. Other stromal markers, such as collagen type III, were also expressed in stromal collagen, but not in cancer cells. In a complementary fashion, gene expression meta-analysis revealed that COL12A1 is also an upregulated gene in colorectal cancer. Our proteomic analysis identified previously documented markers of tumor invasion fronts and our DPD could serve as a pool for future investigation of the tumor microenvironment. Collagen type XII is a novel candidate marker of myofibroblasts, and/or cancer cells undergoing dedifferentiation.

Multiple factors influencing the release of hTERT mRNA from pancreatic cancer cell lines in in vitro culture

Since telomerase expression is highly prevalent in human cancers, the quantitation of serum/plasma hTERT (human telomerase reverse transcriptase) mRNA levels may be useful for early detection of PCa (pancreatic cancer). To analyse the correspondence between exhTERT (extracellular hTERT) mRNA levels and hTERT expression, we designed a cell culture system to investigate factors modulating the extracellular levels of hTERT mRNA in media conditioned by eight PCa cell lines. We found that the level of exhTERT mRNA was dependent on cell growth rate. MIAPaCa-2, PANC-1, KLM-1 and PK-9 cells expressed high levels of exhTERT mRNA, independent of cell density, whereas proliferating PK-59, BxPC-3 and PK-45H cells released low levels of exhTERT mRNA. The augmented release of mRNA by spontaneous dead MIAPaCa-2 cells was further increased at postconfluence. In Capan-1 cells, low correspondence of marker was also due to RNase secretion. Upon reaching confluence, some PCa cell lines showed down-regulation of hTERT expression. Following cell-cell adhesion, as shown by E-cadherin engagement, PK-59 cells showed levels of extracellular message below the limits of detection, a loss not due to an increase in message degradation. These results suggest that the levels of exhTERT mRNA in the medium of PCa cell lines are altered not only in response to cell growth rate and cell destruction, but are responsive to extracellular cues such as RNases and cell density. A cell-free assay for exhTERT mRNA may therefore not be useful for early detection of PCa.

Integrated proteomic profiling of cell line conditioned media and pancreatic juice for the identification of pancreatic cancer biomarkers

Pancreatic cancer is one of the leading causes of cancer-related deaths, for which serological biomarkers are urgently needed. Most discovery-phase studies focus on the use of one biological source for analysis. The present study details the combined mining of pancreatic cancer-related cell line conditioned media and pancreatic juice for identification of putative diagnostic leads. Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer, we extensively characterized the proteomes of conditioned media from six pancreatic cancer cell lines (BxPc3, MIA-PaCa2, PANC1, CAPAN1, CFPAC1, and SU.86.86), the normal human pancreatic ductal epithelial cell line HPDE, and two pools of six pancreatic juice samples from ductal adenocarcinoma patients. All samples were analyzed in triplicate. Between 1261 and 2171 proteins were identified with two or more peptides in each of the cell lines, and an average of 521 proteins were identified in the pancreatic juice pools. In total, 3479 nonredundant proteins were identified with high confidence, of which ∼ 40% were extracellular or cell membrane-bound based on Genome Ontology classifications. Three strategies were employed for identification of candidate biomarkers: (1) examination of differential protein expression between the cancer and normal cell lines using label-free protein quantification, (2) integrative analysis, focusing on the overlap of proteins among the multiple biological fluids, and (3) tissue specificity analysis through mining of publically available databases. Preliminary verification of anterior gradient homolog 2, syncollin, olfactomedin-4, polymeric immunoglobulin receptor, and collagen alpha-1(VI) chain in plasma samples from pancreatic cancer patients and healthy controls using ELISA, showed a significant increase (p < 0.01) of these proteins in plasma from pancreatic cancer patients. The combination of these five proteins showed an improved area under the receiver operating characteristic curve to CA19.9 alone. Further validation of these proteins is warranted, as is the investigation of the remaining group of candidates.

Quantitative secretome analysis reveals that COL6A1 is a metastasis-associated protein using stacking gel-aided purification combined with iTRAQ labeling

In cancer metastasis, secreted proteins play an important role in promoting cancer cell migration and invasion and thus also in the increase of cancer metastasis in the extracellular microenvironment. In this study, we developed a strategy that combined a simple gel-aided protein purification with iTRAQ labeling to quantify and discover the metastasis-associated proteins in the lung cancer cell secretome. Secreted proteins associated with lung cancer metastasis were produced using CL1-0 and CL1-5 cells with different metastatic abilities. Quantitative secretomics analysis identified a total of 353 proteins, 7 of which were considered to be metastasis-associated proteins. These included TIMP1, COL6A1, uPA, and AAT, all of which were higher in CL1-5, and AL1A1, PRDX1, and NID1, which were higher in CL1-0. Six of these metastasis-associated proteins were validated with Western blot analysis. In addition, pathway analysis was performed in building the interaction network between the identified metastasis-associated proteins. Further functional analysis of COL6A1 on the metastatic abilities of CL1 cells was also carried out. An RNA interference-based knock-down of COL6A1 suppressed the metastatic ability of CL1-5 cells; in contrast, a plasmid-transfected overexpression of COL6A1 increased the metastatic ability of CL1-0 cells. This study describes a simple and high throughput sample purification method that can be used for the quantitative secretomics analysis of metastasis-associated proteins.

Pentraxin-3 is a novel biomarker of lung carcinoma

PURPOSE

Our objective was to validate the performance of three new candidate lung cancer biomarkers, pentraxin-3 (PTX3), human kallikrein 11 (KLK11), and progranulin.

EXPERIMENTAL DESIGN

We analyzed by commercial ELISA, and with a blinded protocol, 422 samples from 203 patients with lung carcinoma, 180 individuals with high risk for lung cancer (heavy smokers), and 43 individuals with cancers other than lung. All samples were obtained from the Early Detection Research Network (Reference set A).

RESULTS

We found that progranulin and KLK11 were not informative lung cancer biomarkers, with areas under the receiver operating characteristic curve (AUC; ROC), close to 0.50. However, PTX3 was an informative lung cancer biomarker, with considerable ability to separate lung cancer patients from high-risk controls. At 90% and 80% specificity, the sensitivities versus the high-risk control group were 37% and 48%, respectively. The discriminatory ability of PTX3 was about the same with all major subtypes and histotypes of lung cancer. The AUC of the ROC curves increased according to the disease stage, from 0.64 (stage I) to 0.72 (stage IV).

CONCLUSION

PTX3, but not KLK11 or progranulin, is a new serum biomarker for lung carcinoma. Its diagnostic sensitivity and specificity is similar to other clinically used lung cancer biomarkers. More studies are needed to establish if PTX3 has clinical utility for lung cancer diagnosis and management.

Conditioned media from cell lines: a complementary model to clinical specimens for the discovery of disease-specific biomarkers

In the strictest sense, the cell secretome (conditioned media) refers to the collection of proteins that contain a signal peptide and are processed via the endoplasmic reticulum and Golgi apparatus through the classical secretion pathway. More generally, the secretome also encompasses proteins shed from the cell surface and intracellular proteins released through non-classical secretion pathway or exosomes. These secreted proteins include numerous enzymes, growth factors, cytokines and hormones or other soluble mediators. They are fundamental in the processes of cell growth, differentiation, invasion and angiogenesis by regulating cell-to-cell and cell-to-extracellular matrix interactions. The main aim of this review is to provide a synopsis of findings from the analysis of the secretome taking diabetes, cancer and neurodegenerative diseases as examples. We will also discuss the preparation of conditioned media and on the main proteomic-based methodological approaches that have been developed for the study of secreted/shed proteins.

Proteomic analysis identification of a pattern of shared alterations in the secretome of dermal fibroblasts from systemic sclerosis and nephrogenic systemic fibrosis

A proteomic analysis of the secretome of cultured dermal fibroblasts from patients with systemic sclerosis (SSc) and nephrogenic systemic fibrosis (NSF) was performed to identify proteins that reflect the fibrotic process. Confluent culture supernatants from three cell strains each of normal, SSc, and NSF dermal fibroblasts were pooled separately, and each pool was labeled with a specific fluorochrome. The three pools were electrophoresed together on two-dimension SDS gels, and protein differential expression was evaluated by quantitative fluorescence analysis. The secretome analysis identified 1694 spots per sample, among which 890 spots (52%) were differentially increased or decreased (more than twofold) in SSc fibroblasts, and 985 spots (58%) were differentially increased or decreased in NSF fibroblasts compared with normal fibroblasts. Mass spectrometry analysis was then used to identify the proteins that had increased by the greatest extent in both NSF and SSc secretomes. Three reticulocalbin family members were among the 10 most up-regulated proteins. Confocal microscopy results validated the differential increase of reticulocalbin-1 in affected SSc and NSF skin, and Western blot findings demonstrated its presence in SSc sera. The secretomes of both SSc and NSF fibroblasts display a pattern of shared changes compared with the normal fibroblast secretome. The differentially increased proteins reflect an activated fibroblast phenotype and may represent a specific "fibrosis signature" that can be used as a biomarker for fibrotic diseases.

Cancer secretomics reveal pathophysiological pathways in cancer molecular oncology

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.

Leucine-rich alpha-2-glycoprotein-1 is upregulated in sera and tumors of ovarian cancer patients

BACKGROUND

New biomarkers that replace or are used in conjunction with the current ovarian cancer diagnostic antigen, CA125, are needed for detection of ovarian cancer in the presurgical setting, as well as for detection of disease recurrence. We previously demonstrated the upregulation of leucine-rich alpha-2-glycoprotein-1 (LRG1) in the sera of ovarian cancer patients compared to healthy women using quantitative mass spectrometry.

METHODS

LRG1 was quantified by ELISA in serum from two relatively large cohorts of women with ovarian cancer and benign gynecological disease. The expression of LRG1 in ovarian cancer tissues and cell lines was examined by gene microarray, reverse-transcriptase polymerase chain reaction (RT-PCR), Western blot, immunocytochemistry and mass spectrometry.

RESULTS

Mean serum LRG1 was higher in 58 ovarian cancer patients than in 56 healthy women (89.33 ± 77.90 vs. 42.99 ± 9.88 ug/ml; p = 0.0008) and was highest among stage III/IV patients. In a separate set of 193 pre-surgical samples, LRG1 was higher in patients with serous or clear cell ovarian cancer (145.82 ± 65.99 ug/ml) compared to patients with benign gynecological diseases (82.53 ± 76.67 ug/ml, p < 0.0001). CA125 and LRG1 levels were moderately correlated (r = 0.47, p < 0.0001). LRG1 mRNA levels were higher in ovarian cancer tissues and cell lines compared to their normal counterparts when analyzed by gene microarray and RT-PCR. LRG1 protein was detected in ovarian cancer tissue samples and cell lines by immunocytochemistry and Western blotting. Multiple iosforms of LRG1 were observed by Western blot and were shown to represent different glycosylation states by digestion with glycosidase. LRG1 protein was also detected in the conditioned media of ovarian cancer cell culture by ELISA, Western blotting, and mass spectrometry.

CONCLUSIONS

Serum LRG1 was significantly elevated in women with ovarian cancer compared to healthy women and women with benign gynecological disease, and was only moderately correlated with CA125. Ovarian cancer cells secrete LRG1 and may contribute directly to the elevated levels of LRG1 observed in the serum of ovarian cancer patients. Future studies will determine whether LRG1 may serve as a biomarker for presurgical diagnosis, disease recurrence, and/or as a target for therapy.

In situ proteomic analysis of human breast cancer epithelial cells using laser capture microdissection: annotation by protein set enrichment analysis and gene ontology

Identification of molecular signatures that allow detection of the transition from normal breast epithelial cells to malignant invasive cells is a critical component in the development of diagnostic, therapeutic, and preventative strategies for human breast cancer. Substantial efforts have been devoted to deciphering breast cancer etiology at the genome level, but only a limited number of studies have appeared at the proteome level. In this work, we compared individual in situ proteome profiles of nonpatient matched nine noncancerous, normal breast epithelial (NBE) samples with nine estrogen receptor (ER)-positive (luminal subtype), invasive malignant breast epithelial (MBE) samples by combining laser capture microdissection (LCM) and quantitative shotgun proteomics. A total of 12,970 unique peptides were identified from the 18 samples, and 1623 proteins were selected for quantitative analysis using spectral index (SpI) as a measure of protein abundance. A total of 298 proteins were differentially expressed between NBE and MBE at 95% confidence level, and this differential expression correlated well with immunohistochemistry (IHC) results reported in the Human Protein Atlas (HPA) database. To assess pathway level patterns in the observed expression changes, we developed protein set enrichment analysis (PSEA), a modification of a well-known approach in gene expression analysis, Gene Set Enrichment Analysis (GSEA). Unlike single gene-based functional term enrichment analyses that only examines pathway overrepresentation of proteins above a given significance threshold, PSEA applies a weighted running sum statistic to the entire expression data to discover significantly enriched protein groups. Application of PSEA to the expression data in this study revealed not only well-known ER-dependent and cellular morphology-dependent protein abundance changes, but also significant alterations of downstream targets for multiple transcription factors (TFs), suggesting a role for specific gene regulatory pathways in breast tumorigenesis. A parallel GOMiner analysis revealed both confirmatory and complementary data to PSEA. The combination of the two annotation approaches yielded extensive biological feature mapping for in depth analysis of the quantitative proteomic data.

Magnetic particles as powerful purification tool for high sensitive mass spectrometric screening procedures

The effective isolation and purification of proteins from biological fluids is the most crucial step for a successful protein analysis when only minute amounts are available. While conventional purification methods such as dialysis, ultrafiltration or protein precipitation often lead to a marked loss of protein, SPE with small-sized particles is a powerful alternative. The implementation of particles with superparamagnetic cores facilitates the handling of those particles and allows the application of particles in the nanometer to low micrometer range. Due to the small diameters, magnetic particles are advantageous for increasing sensitivity when using subsequent MS analysis or gel electrophoresis. In the last years, different types of magnetic particles were developed for specific protein purification purposes followed by analysis or screening procedures using MS or SDS gel electrophoresis. In this review, the use of magnetic particles for different applications, such as, the extraction and analysis of DNA/RNA, peptides and proteins, is described.

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.

Integrating high-throughput technologies in the quest for effective biomarkers for ovarian cancer

Despite widespread interest, few serum biomarkers have been introduced to the clinic over the past 20 years. Each approach to ovarian cancer biomarker discovery has its own advantages and disadvantages and it seems likely that a global biomarker discovery platform that mines all possible sources for biomarkers might be more useful. Such data could be combined with information from relevant microarray data, bioinformatic analyses and literature searches. This proposed integrated systems biology approach has the potential to yield promising ovarian cancer markers for diagnosis, prognosis and monitoring of patients during therapy.

Profiling pancreatic cancer-secreted proteome using 15N amino acids and serum-free media

OBJECTIVES

A new method of determining protein turnover by labeling protein with N amino acids was used in conjunction with serum-free cell culture to profile secreted proteins that are released by MIA PaCa-2 pancreatic cancer cells in culture.

METHODS

MIA PaCa-2 cells were first cultured in Dulbecco modified Eagle medium (Gibco by Invitrogen, Carlsbad, Calif) with 10% fetal bovine serum, then in serum-free modified Eagle medium with or without 50% N algal amino acid mixture. The effect of oxythiamine chloride on secreteome was studied. Secreteome from cell culture media was analyzed by 2-dimensional (2D) gel electrophoresis. Differentially expressed proteins were detected and identified. Protein turnover rates were calculated according to the newly established method. Western blot and enzyme-linked immunosorbent assay were used to validate identified proteins.

RESULTS

Among the 14 differentially expressed proteins after oxythiamine treatment, tissue inhibitor of metalloproteases-1 and cytokeratin-10 were identified as 2 newly synthesized secreted proteins caused by substantial N incorporation. The inhibition of tissue inhibitor of metalloproteases-1 expression in MIA PaCa-2 cells by oxythiamine treatment was first demonstrated by 2D gel electrophoresis and further validated by Western blotting and enzyme-linked immunosorbent assay analyses.

CONCLUSIONS

Our method of labeling protein with N amino acids in conjunction with serum-free cell culture allows the identification of actively secreted proteins from pancreatic cancer cells and is a useful method for serum biomarker discovery.

The bottleneck in the cancer biomarker pipeline and protein quantification through mass spectrometry-based approaches: current strategies for candidate verification

BACKGROUND

Although robust discovery-phase platforms have resulted in the generation of large numbers of candidate cancer biomarkers, a comparable system for subsequent quantitative assessment and verification of all candidates is lacking. Established immunoassays and available antibodies permit analysis of small subsets of candidates; however, the lack of commercially available reagents, coupled with high costs and lengthy production and purification times, have rendered the large majority of candidates untestable.

CONTENT

Mass spectrometry (MS), and in particular multiple reaction monitoring (MRM)-MS, has emerged as an alternative technology to immunoassays for quantification of target proteins. Novel biomarkers are expected to be present in serum in the low (microg/L-ng/L) range, but analysis of complex serum or plasma digests by MS has yielded milligram per liter limits of detection at best. The coupling of prior sample purification strategies such as enrichment of target analytes, depletion of high-abundance proteins, and prefractionation, has enabled reliable penetration into the low microgram per liter range. This review highlights prospects for candidate verification through MS-based methods. We first outline the biomarker discovery pipeline and its existing bottleneck; we then discuss various MRM-based strategies for targeted protein quantification, the applicability of such methods for candidate verification, and points of concern.

SUMMARY

Although it is unlikely that MS-based protein quantification will replace immunoassays in the near future, with the expected improvements in limits of detection and specificity in instrumentation, MRM-based approaches show great promise for alleviating the existing bottleneck to discovery.

Up-regulated proteins in the fluid bathing the tumour cell microenvironment as potential serological markers for early detection of cancer of the breast

Breast cancer is by far the most common diagnosed form of cancer and the leading cause of cancer death in women today. Clinically useful biomarkers for early detection of breast cancer could lead to a significant reduction in mortality. Here we describe a detailed analysis using gel-based proteomics in combination with mass spectrometry and immunohistochemistry (IHC) of the tumour interstitial fluids (TIF) and normal interstitial fluids (NIF) collected from 69 prospective breast cancer patients. The goal of this study was to identify abundant cancer up-regulated proteins that are externalised by cells in the tumour microenvironment of most if not all these lesions. To this end, we applied a phased biomarker discovery research strategy to the analysis of these samples rather than comparing all samples among each other, with inherent inter and intra-sample variability problems. To this end, we chose to use samples derived from a single tumour/benign tissue pair (patient 46, triple negative tumour), for which we had well-matched samples in terms of epithelial cell numbers, to generate the initial dataset. In this first phase we found 110 proteins that were up-regulated by a factor of 2 or more in the TIF, some of which were confirmed by IHC. In the second phase, we carried out a systematic computer assisted analysis of the 2D gels of the remaining 68 TIF samples in order to identify TIF 46 up-regulated proteins that were deregulated in 90% or more of all the available TIFs, thus representing common breast cancer markers. This second phase singled out a set of 26 breast cancer markers, most of which were also identified by a complementary analysis using LC-MS/MS. The expression of calreticulin, cellular retinoic acid-binding protein II, chloride intracellular channel protein 1, EF-1-beta, galectin 1, peroxiredoxin-2, platelet-derived endothelial cell growth factor, protein disulfide isomerase and ubiquitin carboxyl-terminal hydrolase 5 were further validated using a tissue microarray containing 70 malignant breast carcinomas of various grades of atypia. A significant number of these proteins have already been detected in the blood/plasma/secretome by others. The next steps, which include biomarker prioritization based on the hierarchal evaluation of these markers, antibody and antigen development, assay development, analytical validation, and preliminary testing in the blood of healthy and breast cancer patients, are discussed.

Differential secreted proteome approach in murine model for candidate biomarker discovery in colon cancer

The complexity and heterogeneity of the plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. We used cell culture as a model system and identified differentially expressed, secreted proteins which may constitute serological biomarkers. A stable isotope labeling by amino acids in cell culture (SILAC) approach was used to label the entire secreted proteomes of the CT26 murine colon cancer cell line and normal young adult mouse colon (YAMC) cell line, thereby creating a stable isotope labeled proteome (SILAP) standard. This SILAP standard was added to unlabeled murine CT26 colon cancer cell or normal murine YAMC colon epithelial cell secreted proteome samples. A multidimensional approach combining isoelectric focusing (IEF), strong cation exchange (SCX) followed by reversed phase liquid chromatography was used for extensive protein and peptide separation. A total of 614 and 929 proteins were identified from the YAMC and CT26 cell lines, with 418 proteins common to both cell lines. Twenty highly abundant differentially expressed proteins from these groups were selected for liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS) analysis in sera. Differential secretion into the serum was observed for several proteins when Apc(min) mice were compared with control mice. These findings were then confirmed by Western blot analysis.

Technical and biological issues relevant to cell typing with aptamers

A number of aptamers have been selected against cell surface biomarkers or against eukaryotic tissue culture cells themselves. To determine the general utility of aptamers for assessing the cell surface proteome, we developed a standardized flow cytometry assay and carried out a comprehensive study with 7 different aptamers and 14 different cell lines. By examining how aptamers performed with a variety of cell lines, we identified difficulties in using aptamers for cell typing. While there are some aptamers that show excellent correlation between cell surface binding and the expression of a biomarker on the cell surface, other aptamers showed nonspecific binding by flow cytometry. For example, it has recently been claimed that an anti-PTK7 (protein tyrosine kinase 7) aptamer identified a new biomarker for leukemia cells, but data with the additional cell lines shows that it is possible that the aptamer instead identifies a propensity for adherence. Better understanding and controlling for the role of background and nonspecific binding to cells should open the way to using arrays of aptamers for describing and quantifying the cell surface proteome.