Mass Spectrometry in Clinical Diagnosis: A Preliminary Application in Tumor Cellular Proteomics for Biomarker Discovery

¹Instrument Technology Research Center, National Applied Research Laboratories, Hsinchu, Taiwan

²Department of Medical Research, Kaohsiung Medical University Chung-Ho Memorial Hospital, Kaohsiung, Taiwan

³Translational Research Center, Kaohsiung Medical University Chung-Ho Memorial Hospital, Kaohsiung, Taiwan

⁴Department of Obstetrics and Gynecology, Kaohsiung Medical University Chung-Ho Memorial Hospital, Kaohsiung, Taiwan

⁵School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

⁶Department of Nuclear Medicine, Kaohsiung Medical University Chung-Ho Memorial Hospital, Kaohsiung, Taiwan

⁷Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung, Taiwan

⁸Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan

⁹Department of Biochemistry, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

¹⁰National Sun Yat-sen University-Kaohsiung Medical University Joint Research Center, Kaohsiung, Taiwan

¹¹Department of Chemistry, National Sun Yat-sen University, Kaohsiung, Taiwan

¹²Center of Biomedical Engineering and System Biology, Kaohsiung Medical University, Kaohsiung, Taiwan

^†These authors contributed equally to this work as first authors

*Corresponding Author:

Prof. Yu-Chang Tyan
Department of Medical Imaging and Radiological Sciences
Kaohsiung Medical University, 100
Shi-Chuan 1^st Road, Kaohsiung 807, Taiwan
Tel: 886-7-3121101 ext 2357
E-mail: yctyan@kmu.edu.tw

Received date: January 27, 2014; Accepted date: February 19, 2014; Published date: February 21, 2014

Citation: Yang MH, Yuan SS, Chen YL, Chu PY, Jong SB, et al. (2014) Mass Spectrometry in Clinical Diagnosis: A Preliminary Application in Tumor Cellular Proteomics for Biomarker Discovery. J Anal Bioanal Tech S2:009. doi: 10.4172/2155-9872.S2-009

Copyright: © 2014 Yang MH, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Cancer is a group of diseases characterized by uncontrolled growth and spread of abnormal cells, which cause high mortality rates. The purpose of this study is to characterize the proteins secreted from the HepG2, MCF-7 and HT-29 cells, which may relate to cell differentiation and tumor metastasis. In the proteomic analysis, the secretome proteins were identified by reverse phase nano-high performance liquid chromatography/electrospray ionization tandem mass spectrometry (RP-nano-UPLC-ESI-MS/MS) followed by peptide fragmentation pattern analysis. Moreover, identifications of tumor cell protein expressions by proteomic approaches were indicated that several proteins may activate or enhance the PI3K/AKT/mTOR pathway. The PI3K/AKT/mTOR pathway has been shown to be related to the cancer cell metastasis and proliferation, and the ubiquitin C (UBC) may serve as potential protein diagnostic biomarker to be examined in further investigations.

Keywords

Proteomic; Biomarker; PI3K/AKT/mTOR pathway; Ubiquitin C; Mass spectrometry

Introduction

Cancer is a class of diseases characterized by abnormal cells with uncontrolled growth, which are able to invade other cells. The main categories of cancer include: carcinoma, sarcoma, leukemia, lymphoma, myeloma, and central nervous system cancers. Untreated cancer can cause serious illness and death [1,2].

Early detection of cancer greatly improves the chances for effective treatment and the survival rate. There are two major components of early detection of cancer: education to promote early diagnosis and cancer screening. More recently, screening for cancer with radiological imaging techniques such as X-rays, Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and ultrasound, have been suggested and used regularly in order to detect where a tumor is located and what organs may be affected. However, in some studies over 50% of trial participants had an indeterminate location [3,4]. An endoscopy procedure may also be employed to check for abnormalities inside the body.

Unfortunately, early detection strategies thus far have not shown a significant reduction in cancer specific mortality, and the overall fiveyear average survival remains less than 15%. Although many insights into the molecular pathology of malignant tumors have been achieved, additional information is critical to both our understanding of the development, and progression of these malignant tumors as well as to aid in early diagnosis [5].

“Proteome” and “proteomics” are relatively new words, coined by Wilkins et al. [6]. The proteome is the entire set of proteins expressed by the genome. Proteomic analysis means a comprehensive analysis of proteins, and proteomics is the science by which proteins are comprehensively investigated with regard to their roles as functional elements. Recently, characterization of these cellular proteins by proteomic approaches has revealed a definition of protein reactivity and the protein-protein interaction for malignant tumor related proteins.

As an alternative strategy, many investigations have focused on the development of biomarkers as a noninvasive diagnostic tool. In clinical and diagnostic proteomics, it is essential to develop a comprehensive and robust system for proteome analysis [7]. Recent advances in liquid chromatography, mass spectrometry, and data analysis software enable the direct analysis of extremely complex peptide mixtures, often referred to as shotgun proteomics or multidimensional protein identification technology (MudPIT) [8]. Although multidimensional liquid chromatography/tandem mass spectrometry (MDLC-MS/MS) systems have been recently developed as powerful tools, especially for identification of protein complexes, these systems still have some drawbacks in their application to clinical research that requires an analysis of a large number of clinical samples [9].

A driving force in proteomics is the discovery of biomarkers, proteins that change in concentration or state in association with a specific biological process or disease. Determination of concentration changes, relative or absolute, is fundamental to the discovery of valid biomarkers. The objective of this study is to present proteomics profiling data of the cell secretome obtained by RP-nano-UPLCESI- MS/MS technology. A database is formed for the diversity and relative abundance of various proteins found in the cell secretome. The database provides not only information on the nature of protein present in the cell secretome but also potential protein diagnostic markers to be examined in further investigations.

Materials and Methods

Cell culture

HepG2 (liver tumor cell), MCF-7 (breast tumor cell) and HT-29 (colorectal tumor cell) cells were maintained at 37°C and 5% CO₂ in RPMI 1640 medium (Gibco, USA) supplemented with 10% fetal bovine serum (FBS, Hyclone Laboratories, Logan, UT), 1% penicillin/ streptomycin (Gibco, Grand Island, NY, USA) and 44 mM NaHCO₃. After three days, the cells were washed with phosphate buffered saline (PBS) and the medium was replaced by serum-free RPMI 1640 medium for 12 h.

Sample preparation

After incubation with serum-free RPMI 1640 medium, the secreted proteins in the medium were centrifuged at 1500 g for 10 min at 4°C. The supernatants were filtered through 0.8 μm filters and the protein concentrations were adjusted to 1 mg/mL with 25 mM ammonium bicarbonate.

Cell secretome samples (100 μL) were transferred into 1.5 mL Eppendorf tubes and incubated at 37°C for 3 h after mixing with 25 μL of 1M dithiothreitol (DTT, USB Corporation, 15397). Then the cell secretome samples were reduced and alkylated in the dark, at room temperature, for 30 min after the addition of 25 μL of 1 M iodoacetamide (IAA, Amersham Biosciences, RPN6302V) in 25 mM ammonium bicarbonate. Approximately 10 μL of 0.1 μg/μL modified trypsin digestion buffer (Trypsin Gold, Mass Spectrometry Grade, V5280, Promega, WI, USA) in 25 mM ammonium bicarbonate were added to the cell secretome samples, which were then incubated at 37°C for at least 12 h in a water bath. Two micro liters of formic acid were added to each sample before mass spectrometric analysis for protein identification.

Proteomic analysis

The complex peptide mixtures were separated by RP-nano-UPLCESI- MS/MS. The protein tryptic digests were fractionated using a flow rate of 400 nL/min with a nano-UPLC system (nanoACQUITY UPLC, Waters, Milford, MA) coupled to an ion trap mass spectrometer (LTQ Orbitrap Discovery Hybrid FTMS, Thermo, San Jose, CA) equipped with an electrospray ionization source. For RP-nano-UPLC-ESI-MS/ MS analyses, a sample (2 μL) of the desired peptide digest was loaded into the trapping column (Symmetry C18, 5 μm, 180 μm×20 mm) by an autosampler. The RP separation was performed using a linear acetonitrile gradient from 99% buffer A (100% D.I. water/0.1% formic acid) to 85% buffer B (100% acetonitrile/0.1% formic acid) in 100 min using the micropump at a flow rate of approximately 400 nL/min. The separation was performed on a C18 microcapillary column (BEH C18, 1.7 μm, 75 μm×100 mm) using the nano separation system. As peptides were eluted from the micro-capillary column, they were electrosprayed into the ESI-MS/MS with the application of a distal 2.1 kV spraying voltage with heated capillary temperature of 200°C. Each scan cycle was contained one full-scan mass spectrum (m/z range:400-2000) and followed by three data dependent tandem mass spectra. The collision energy of MS/MS analysis was set at 35%.

Database search

For protein identification, Mascot software (Version 2.2.1, Matrix Science, London, UK) was used to search the Swiss-Prot human protein sequence database. For proteolytic cleavages, only tryptic cleavage was allowed, and the number of maximal internal (missed) cleavage sites was set to 2. Variable modifications of cysteine with carboxyamidomethylation, methionine with oxidation, and asparagine/ glutamine with deamidation were allowed. Mass tolerances of the precursor peptide ion and fragment ion were set to 10 ppm and 0.5 Da, respectively. When the MOWSE score was greater than 50, the protein identification was defined as positive and considered significant (p<0.05). All Mascot results were visually confirmed. In addition, the criterion requires a readily observable series of at least four y-ions for an identified peptide [10]. When a protein was identified by three or more unique peptides, no visual assessment of spectra was conducted and the protein was considered to be present in the sample. Proteins were initially annotated by similar search conditions using UniProtKB/ Swiss-Prot databases. The analyses of protein-protein interaction pathways were performed by String 9.1 Web software.

Results and Discussions

In decades, the major leading causes of death were malignant tumors, and the three most popular cancers were liver cancers, colorectal cancers, and breast cancers. There are many kinds of cancer types, and the severity of the cancer depends on the location, the extent of cancer cell malignant growth, and whether the occurrence of metastases. The reason for out-of-control tumor cell growth may be the proto-oncogenes which activate the cells into cancerous state. It may be mainly due to the expression of abnormal cell division proteins, such as tumor suppressor gene dysfunction. In this situation, the DNA codes of the proteins were damaged, and the proteins were therefore contained the translation errors. For normal cells to translate into cancer cells, the mutations typically are required for multiple times, or translated to process protein and gene disruption.

Hepatocellular carcinoma (HCC) is the most common malignant liver tumor. It is the most or second most common cause of cancerrelated mortality, especially in Asia and Africa, with a five-year survival rate of less than 5% without treatment [1]. HCC targets hepatocytes, the major cell type of liver, leading to the deregulation of homeostasis [11,12].

Colorectal cancer, also known as colon cancer, rectal cancer, or bowel cancer, is a cancer in the colon, rectum, or appendix. It is the second leading cancer killer in the United States. Colorectal cancer symptoms include a change in bowel habits or bleeding, but often there are no symptoms. Most colorectal cancers originate from small, noncancerous (benign) tumors called adenomatous polyps that form on the inner walls of the large intestine [13-16].

The breast cancer is the most common cancer diagnosed in women. The most common types of breast cancers are lobular carcinoma and ductal carcinoma, which begin in the lobules and the lining of the milk ducts of the breast. Breast cancer can occur in both men and women, but it’s far more common in women [17-21].

In this study, we selected the three most common kinds of tumor cells as a cancer model and used an extremely sensitive technique for identification of proteins, namely, RP-nano-UPLC-ESI-MS/MS, to characterize the secretome of tumor cells. Each RP-nano-UPLC-ESIMS/ MS analysis was typically generated about 4,000 MS/MS spectra. A total around 36,000 (4,000 scans×3 repeats×3 samples) MS/MS spectra were analyzed by the database search software SEQUEST. Only a small fraction (9.65%, 3,474) of searches produced significant matches according to the inclusion criteria that we used for this study.

These 3,474 significant matches were assigned to 2,931 peptide fragments, which gave about 81.9% duplicate in the three replicate runs. The total number of unique peptides identified in the cell secretome samples was 619 by Mascot search software. From these short sequences, the protein composition of the composite cell secretome samples can be incurred. The tryptic peptides produced were often mapped to protein sequence entries in the UniProtKB/Swiss-Prot database. The 619 unique matched peptide sequences belonged to 415 protein sequence entries. Most of them were identified at a minimal confidence level in which only one unique peptide sequence matched, whereas 52 protein identifications showed higher confidence levels with at least three unique peptide sequences matched. Figure 1 shows the typical MS/MS spectrum of the identified peptide. The MS/MS spectrum represents the amino acid sequence of tryptic peptide, which is triply charged peptide with m/z of 761.73. The amino acid sequence of the tryptic peptide is FKEIQTQNFSLINENQSLK. The peptide originated from CASP8-associated protein 2, and the interpretation of the complete y-ion and b-ion series provides the peptide sequence as shown. In the 52 identified proteins, there were 16 proteins of special interest since they may play roles in the regulation of cell proliferation and differentiation. The information of 16 protein identifications was listed in the Table 1.

Figure 1: MS/MS spectral data of peptide from the cancer cell. Interpretation of the complete y-ion and b-ion series provides the peptide sequences as shown.

Table 1: The 16 proteins identified with higher confidence level (at least three unique peptide sequences matched) in this study.

Identified proteins in this study were classified into different groups of molecular functions and biological processes, based on their functional categories in the SWISS-Port/TrEMBL and Bioinformatic Harvester EMBL protein database. We used the ExPASy Molecular Biology Server (Expert Protein Analysis System) of the Swiss Institute of Bioinformatics (SIB) to explore the known functions of the identified proteins, which had been reported in the literature (Table 2). The Swiss-Prot identifiers could be employed for linkages of proteins to a defined vocabulary of terms describing the biological processes, cellular components and molecular functions of known Gene Ontology (GO). The Gene Ontology Consortium provides annotation of each protein and structure to organize selected proteins into biologically relevant groups. These groupings can serve as the basis for identifying those areas of biology showing correlated protein changes [22-24].

Table 2: Subcellular location and protein function of 16 proteins with higher confidence levels identified in cancer.

In this study, the protein-interaction networks were analyzed by String 9.1 Web software, which showed the interacted proteins in cells. Thus, the biological significance between increase in the secretion of those proteins and tumor progression could be further studied accordingly. Utilizing the String 9.1 Web software, 12 of 16 proteins were connected by protein-protein interaction and marked in the Figure 2, respectively. In Figure 2, the identified proteins in liver (3), colorectal (5), and breast (4) cancers were showed and involved in the PI3K/AKT/mTOR pathway. Those proteins were also marked astral symbols in the Tables 1 and 2.

Figure 2: The protein-protein interaction pathways for the cancer cell secretome proteins were performed. Proteins identified in this study were marked by the red boxes, respectively. The triangle protein interaction of PI3K/AKT/mTOR pathway was marked by the blue box.

In the experimental results, the main finding was the secretome proteins of tumor cells may activate or enhance the PI3K/AKT/mTOR pathway, which may result in tumor metastasis and cell proliferation. In Figure 3, the protein-interaction network was identified and the key protein was the ubiquitin C (UBC, marked by the green arrows). The UBC can turn on the PI3K/AKT/mTOR pathway, which is responsible for the proliferation and is required for survival of the majority of cells.

Figure 3: The protein-protein interaction pathways were performed by String 9.0 Web software. The UBC can turn on the PI3K/AKT/mTOR pathway, which is responsible for the proliferation and is required for survival of the majority of cells (UBC, marked by the green arrows).

The mammalian target of rapamycin pathway (mTOR pathway, also known as FRAP, RAFT1 and RAP1 pathway) has been identified as a key kinase acting downstream of the activation of phosphoinositide- 3-kinase (PI3K) [25]. The hypothesis of the mTOR pathway is that it acts as a master switch of cellular catabolism and anabolism, thereby determining the growth and proliferation of tumor cells [26,27]. Activation of PI3K/AKT/mTOR signaling through the mutation of pathway components as well as through the activation of upstream signaling molecules, occur in a majority of cancer cells contributing to deregulation of proliferation, resistance to apoptosis, and changes in the metabolism characteristic of transforming cells [28].

Conclusion

The protein constitutively secreted by cells in vitro is referred to as the secretome. In this study, we used the mass spectrometry technique as an analytical method for determining cancer biomarkers on tumor cell secretome. The cell model was used to identify the tumor progression related proteins, which are secreted into the serum-free culture medium. Secreted proteins may coordinate various cellular processes in tumor cells, including growth, division, differentiation, apoptosis, migration, metastasis, angiogenesis and adhesion, and thereby contribute to the growth and spread of the tumor cells. Thus, the identification of secreted proteomics in tumor cells provides potential biomarkers closely related to carcinogenesis. Moreover, disease-specific protein biomarkers allow us to define the prognosis of the disease and gain deep insight into disease mechanisms by which proteins play a major role. Studies on secretome of different tumor cells may find novel biomarkers.

Our data demonstrate that the development of strategies to isolate proteins can expand the tumor cell proteomic map. With the bioinformatics analysis, the tumor related proteins may help discern the origin of proteins in cancer. This approach is a potentially powerful tool to discover new biomarkers and/or causative factors of disease-related proteins in cancer clinical studies; in addition, its sensitivity may also make it applicable to direct ultra-micro analysis of other bio-samples.

In this study, of these 16 proteins, 12 were presented that closely related to PI3K/AKT/mTOR pathway and may serve as cancer biomarkers. In addition, the correlation of UBC in the cancer cells was greatly indicated. The potential utility of UBC as an early cancer biomarkers merits study in the future. The database we generated provides information both on the identities of proteins present in tumor cells and a potential diagnostic biomarker for cancer.

Acknowledgements

The authors thank the Center of Excellence for Environmental Medicine, Kaohsiung Medical University for the assistance in protein identification, and S. Sheldon MT (ASCP, Retired) of Oklahoma University Medical Center Edmond for fruitful discussions and editorial assistance before submission. This work was supported by research grants 94-KMUH-ND-017 from Kaohsiung Medical University Hospital, NSC-102-3114-Y-492-076-023, NSC-100-2320-B-037-007- MY3 from the National Science Council, NSYSUKMU 102-P006 from NSYSUKMU Joint Research Project, and MOHW103-TD-B-111-05 from Ministry of Health and Welfare, Taiwan, Republic of China.

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