Systems biology analysis of the lung cancer‑related secretome
- Authors:
- Published online on: June 20, 2018 https://doi.org/10.3892/or.2018.6509
- Pages: 1103-1118
Abstract
Introduction
Lung cancer is also known as primary bronchogenic carcinoma and is a type of malignancy that originates in the bronchial epithelium. Lung cancer is one of the most common malignant tumors and the most deadly cancer worldwide (1). In recent years, due to population aging, smoking, environmental pollution and other factors, the incidence and mortality rates of lung cancer have tended to increase across the globe, especially in China and other developing countries (2). Biomarkers are of great significance for the diagnosis and treatment of diseases, particularly cancers. With the development of large-scale proteomic technology, especially biological mass spectrometry (MS), proteomic technology has become a mainstream technological approach in cancer biomarker discovery.
Embryos and tumors share great similarities in many respects. In 1829, French scientists, Lobstein and Recamier, first proposed the concept of an embryonic origin of tumors, that is, cancer occurs due to the continued proliferation of embryonic cells present in the body (3). In the 1970s, Pierce developed the theory of ‘cancer, a problem of developmental biology’ and noted that tumorigenesis is closely and strongly related to developmental biology (4). Due to the similarity between tumors and embryonic cells during gestation in terms of growth, invasion and immune system suppression, it has been proposed in recent years that we should think of and study tumors from an evolutionary perspective (5–7). With the development of experimental techniques and the increase in research investigations, the early hypothesis that embryonic development and tumorigenesis are closely related has increasingly been confirmed.
In our preliminary study, to eliminate the interference of high-abundance proteins in the blood and enrich lung cancer-specific markers in body fluid, we established a new primary organ culture model to detect the free proteins released by tumor cells into the bloodstream (8). In the present study, we used the research system for tumor-associated proteins in body fluid that was established in our preliminary study. We also established primary cultures of tumor and control tissue samples from non-small cell lung cancer (NSCLC) patients and collected conditioned medium (CM). We then used liquid chromatography (LC) and linear ion trap (LTQ) MS to isolate and identify the full spectrum of the total proteins in CM samples. Subsequently, we used BRB-ArrayTools (http://linus.nci.nih.gov/BRB-ArrayTools.html), ArraySVG and other programs and analyzed MS data using the spectral counts produced by label-free quantitative proteomics as the quantitative parameter. We used the Gene Set Enrichment Analysis P (GSEA-P) program to conduct enrichment analysis of the free proteins identified in tumor tissue CM based on the maternal-placental interface expression profile data at different stages. Data mining of free proteins was conducted to identify important lung cancer-associated plasma proteins.
Materials and methods
Sample collection
Tissue samples of lung cancer patients for the present study were all taken from hospitalized patients in the Department of Thoracic Surgery at the Cancer Hospital of the Chinese Academy of Medical Sciences and Peking Union Medical College. When the specimens were obtained, none of the patients had received physical or chemical treatments. We conducted a comprehensive collection of patient clinical data. The histopathological types of surgically resected tumor tissues were determined by senior pathologists based on the World Health Organization (WHO) classification of lung cancer tissue. Tumor staging was determined based on the 7th edition of the Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) staging system. During the period from September 2005 to October 2006, we collected fresh tumor and control tissue samples for primary culture from 9 patients, including 5 patients with squamous cell carcinoma (SCC), 3 patients with adenocarcinoma (ADC) and 1 patient with large cell carcinoma (LCLC). The clinical data of the patients are listed in Table I.
Peripheral blood samples were collected from July 2007 to November 2007 from 59 NSCLC patients (38 males and 21 females; mean age, 61.8 years) who underwent surgery at the National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital of Chinese Academy of Medical Sciences and Peking Union Medical College. The cohort of the NSCLC patients included 26 patients with lung SCC and 33 patients with lung ADC. There were 40 stage I–II cases and 19 stage III cases. All patients provided written informed consent before surgery, and treatments were performed in accordance with the current ethical principles of the Independent Ethics Committee, Cancer Hospital, Chinese Academy of Medical Sciences. Peripheral blood samples were collected via venipuncture prior to surgery and preserved in EDTA-coated tubes. Samples were centrifuged at 4°C for 10 min at 1,000 × g to separate plasma from blood cells. Supernatants were collected, divided into aliquots and stored at −80°C until use. Disease-free survival (DFS) was defined as the interval between surgery and recurrence; if recurrence was not diagnosed, the date of death or last follow-up was recorded. Overall survival (OS) was defined as the interval between surgery and death. After surgery, patients were followed up for over eight years or until death. At the end of the follow-up period (11–99 months, with a mean of 74 months), tumor recurrence had been identified in 33 (55.0%) patients; 27 (45.0%) patients had died at the time of data censorship.
Primary tissue culture and CM collection
We chose different control tissues depending on pathological characteristics. For SCC, the control tissue was normal bronchial tissue from the same patient. For ADC and large cell lung cancer (LCLC), the control tissue was normal lung tissue from the same patient. In all cases, the distance between the control and tumor tissues was >3 cm. Samples of paracancerous bronchial/lung tissues and lung cancer tissues that were dissected from the body within 30 min were cut into small pieces with volumes of approximately 5 mm3 using a scalpel. Tissue pieces were placed into collagen-coated gridded dishes, and LHC-9 medium (Invitrogen; Thermo Fisher Scientific, Inc., Waltham, MA, USA) was added carefully and slowly in a dropwise manner to prevent disruption of these pieces. The dishes were placed in a culture box, which was then filled with a gas mixture of 50% N2, 45% O2 and 5% CO2. The culture box was placed on a shaker, with a shaking frequency of 8–10 times/min. CM was collected after 24 h of incubation in a 36.5°C incubator. The collected CM was added to an Amicon Ultra tube (cat no. UFC900596; Millipore; Merck KGaA, Darmstadt, Germany) and then centrifuged for 45 min at 4,000 × g and 4°C. This process was performed to desalinate and concentrate the sample.
LC-MS analysis and identification of proteins released into CM by cells
Enzyme digestion of proteins in CM
A total of 30 µg of CM proteins was dissolved in 50 µl of solution containing 8 M urea and 10 mM dithiothreitol (DTT); 100 µl of 50 mM NH4HCO3 solution was then added, and the sample was incubated in a 37°C water bath for 4 h. Subsequently, 2.5 µl of 1 M indoleacetic acid (IAA) solution was added, and protein alkylation was completed during 1 h of reaction at room temperature in the dark. Next, 40 µl of acetonitrile (ACN; a final concentration of 10%) and 30 µl of 50 mM NH4HCO3 were added to the mixture, followed by sequencing-grade trypsin at a protein-to-enzyme ratio of 100:1 and all components were well mixed. After the entire system was mixed by shaking, the mixture was incubated in a 37°C water bath for 2 h. To ensure the enzyme digestion effects, trypsin was added 2 h later in a ratio of 100:1, and the incubation was continued for a total of 16 h after mixing. The reaction solution was acidified with 5% formic acid (FA) to terminate the reaction.
SPE desalination
The desalting column was an LC-18 solid-phase extraction (SPE) column (Supelco Inc., Bellefonte, PA, USA). The desalting steps were as follows: The SPE column was activated with 2 ml of ACN and equilibrated with 2 ml of 0.1% trifluoroacetic acid (TFA) solution in water; the peptide mixture was slowly added to the column until all of the samples had entered the column matrix; 2 ml of 0.1% TFA solution in water was added for desalting; elution was conducted by adding 1.5 ml of eluent (containing 80% ACN and 0.1% TFA) and the eluate was collected, lyophilized and stored at −20°C.
LC-ESI-MS/MS separation and identification of peptide mixture
Reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) was used to analyze the peptide mixture using a Thermo Finnigan™ LTQ system (Thermo Fisher Scientific, Inc.) with an electrospray ionization (ESI) ion source and the high-throughput analysis mode. A nano-LC system (Thermo Fisher Scientific, Inc.) was run with an LC-Packing system, equipped with a Famos autosampler system, Swithos loading pump and Ultimate elution pump; the system was monitored using Dionex chromatography software. Two RP-C18 trap columns (Supelco Inc.) were connected to the ten-port valve. When samples were being loaded to one column, inverted elution was conducted on the other column, and a PicoFrit™ analytical column (BioBasic®C18, 5 µm, 75 µm i.d. × 10 cm, 15 µm i.d. spray tip; New Objective, Woburn, MA, USA) was then used. Elution chromatography was conducted on the Ultimate system (Thermo Fisher Scientific, Inc.) and the eluted components directly entered the MS instrument through the ESI ion source. The LC conditions were as follows: Mobile phase A, 5% ACN-95% water; and mobile phase B, 0.1% FA-80% ACN solution.
Database search
The tandem mass spectral database was queried using the SEQUEST engine of the Bioworks3.1 software (Thermo Fisher Scientific, Inc.). We used the International Protein Index (IPI) human protein database v3.07 in the Fasta database (ftp://ftp.ebi.ac.uk/pub/databases/IPI). The search settings for peptide amino acid sequence variable modifications were C (+57.02 Da), M (+15.99 Da), a false discovery rate (FDR) of <0.01 and a peptide mass tolerance of 1.5 Da. The reverse database was established by reversing the amino acid sequence of each protein. BuildSummary software was used to integrate and compare the Sequest search results. The data filtering parameters were set as follows: Xcorr ≥1.9, 1+; Xcorr ≥2.2, 2+; Xcorr ≥3.75, 3+; DeltCn ≥0.1; Rsp ≤4.
Bioinformatic analysis of the CM free protein database
This process used the IPI as the index for data processing. We selected all proteins with no less than two matching peptides and eliminated redundant proteins due to homology for all samples.
Gene Ontology (GO) was combined with the SWISS-PROT protein database (http://www.uniprot.org/uniprot/?query=reviewed%3Ayes) to analyze the biological processes, cellular localization and molecular functions of the proteins in the CM. BRB-ArrayTools software (http://linus.nci.nih.gov/BRB-ArrayTools.html) (9) was used for the identification, cluster analysis and enrichment analysis for differential proteins. Gene Set Enrichment Analysis (GSEA) was first proposed by Mootha et al in 2003 (10). It was later modified by Subramanian et al (11) to introduce weighted scores to replace uniform scores. GSEA-P 2.0 software was used to conduct enrichment analysis of the free proteins identified in tumor tissue CM based on the placental-maternal interface expression profiles at different stages. GSEA analysis first uses the gene expression profile data of two groups that are known to have different phenotypes, and distribution L can be obtained by sorting genes based on the correlation between gene expression profiles and phenotypes. The data to be analyzed were named S, which is a series of data with common characteristics. For example, S may be gene-coding products in the same metabolic pathway, genes located in the same chromosomal band or genes/proteins with the same functions, as indicated by GO analysis. Via GSEA analysis, we ultimately obtained the enrichment conditions of data S in the existing distribution L. The data could be either randomly distributed or enriched in data closely related to a certain phenotype. The latter may indicate biological significance.
Enzyme-linked immunosorbent assay (ELISA)
Hypoxanthine phosphoribosyltransferase 1 (HPRT1) protein concentrations in plasma were assessed using ELISA according to the manufacturer's instructions. ELISA kits for HPRT1 were purchased from Aviva Systems Biology (San Diego, CA, USA). Briefly, 100 µl of diluted plasma was added to the wells of an anti-HPRT1 microplate, which was then incubated at 37°C for 2 h. Subsequently, 100 µl of prepared biotinylated HPRT1 detector antibody was added to each well, and the microplate was incubated at 37°C for 1 h. After 3 washes, 100 µl of prepared conjugate was added to each well, and the microplate was incubated at 37°C for 1 h. After 5 washes, absorbance at 450 nm was immediately assessed using a microplate reader (Bio-Rad Laboratories, Hercules, CA, USA).
Statistical analysis
The relationships between plasma levels of the HPRT1 protein and clinical parameters were analyzed by he Mann-Whitney test, using SPSS software, version 17.0 (SPSS, Inc., Chicago, IL, USA). DFS and OS rates by plasma levels of the selected proteins were assessed by log-rank test, and the Kaplan-Meier curves. P-values <0.05 were considered statistically significant (P<0.05).
Results
Identification of free proteins in the CM of primary cultures of lung cancer and the corresponding control tissues
Identification of proteins in the CM of primary cultures
For each case of lung cancer, the CM from the primary culture was dialyzed, lyophilized, bleached, reduced, alkylated and enzyme digested to obtain mixed peptides, which were then identified and sequenced using a nanoliter LC-MS/MS (LTQ, Thermo Finnigan). Among the CM samples corresponding to 9 cases (18 samples), a total of 987 high-confidence proteins (with at least two matching peptides for each protein) were detected (data not shown).
To further elucidate the biological significance of free proteins associated with lung cancer and the identified differential free proteins, we used the GO database to conduct biological functional classification for the 987 identified proteins. GO is an integrated classification system that can systematically annotate genes at three levels, molecular function, biological process and cellular component. As an important bioinformatic tool, GO can be used to identify common molecular and biological functions shared among a massive number of proteins.
Among the 987 proteins, 232 (23.5%) are extracellular or secreted proteins, 182 (18.4%) are membrane-associated proteins and the two types of proteins together account for 41.9% of all of the identified proteins (Fig. 1). This finding confirmed that this strategy was an effective method to enrich secreted proteins.
The 987 free proteins identified in the lung cancer microenvironment are primarily involved in such important processes as cell growth and maintenance, metabolism, catalysis, extracellular matrix (ECM)-receptor signaling transduction and cell adhesion. These proteins were enriched in 15 biological processes (Fig. 2), including protein binding, hydrolase activity, calcium ion binding and cytoskeletal protein binding.
Proteins involved in biological processes such as protein binding, hydrolase activity, calcium ion binding and cytoskeletal protein binding showed significantly elevated ratios in the CM, and those involved in biological processes such as nucleic acid binding, DNA binding and transferase activity demonstrated significantly reduced ratios in the CM.
Differential CM proteins identified by label-free quantitative proteomic technology
To improve the accuracy of the data, we used the standard of appearing in at least two samples to screen the 987 proteins and obtained 657 proteins of high confidence. On this basis, we used the spectral count produced by MS/MS as the parameter and the total number of spectral counts produced by each LC-MS/MS identification for each sample as the benchmark to generate standardized data.
We used the standardized spectral counts of 18 samples as the relative quantitative parameters and used the Significance Analysis of Microarrays (SAM) algorithm to identify differential proteins between the CM from tumor tissues and the CM from paracancerous bronchial tissues. The data were randomly arranged, the calculations were performed 10,000 times and the results were corrected based on a false discovery rate (FDR) of 0.10. We identified a total of 143 proteins that demonstrated significant differences. We calculated the ratios of the average spectral counts and all the differential proteins showed abundance changes >1.5 times. A total of 78 proteins showed significantly increased expression in the CM of the tumor tissue culture (Table II). These proteins included KRT19 (Cyfra21-1) and SERPINB4 (SCC), which are the lung cancer plasma markers currently used in clinical applications. A total of 65 proteins showed significantly decreased expression in the CM of the tumor tissue culture (Table III).
Table II.Seventy-eight proteins with increased expression in the CM of primary cultures of lung cancer. |
Table III.Sixty-five proteins with significantly decreased expression in the CM of the tumor tissue culture. |
Exploration of proteins in the microenvironment associated with lung cancer invasion and metastasis from the perspective of developmental biology
Enrichment of the full spectrum of proteins in the lung cancer tissue culture CM in data from different stages of the placenta
Winn et al (12) used an Affy HG-U133A microarray and analyzed 36 placental-maternal interface specimens, including 9 specimens from placentas from full-term delivery and 27 specimens from second trimester placentas, leading to a set of differential gene expression profiles closely associated with placental invasion. In the present study, we identified 828 high-confidence proteins from the CM of the tissue culture corresponding to 9 cases of lung cancer, wherein 511 proteins were present for at least two cases and 427 proteins had corresponding gene IDs in the gene bank. We used the GSEA software to conduct enrichment analysis of the 427 proteins based on the differential gene expression profiles of specimens from the placental-maternal interface at different stages. The results indicated that these free proteins had significant enrichment in the gene expression profile of the mid-term placenta of stronger invasiveness (Fig. 3), in which 197 proteins contributed significantly to the enrichment score (ES) (P=0.031, Table IV).
Table IV.One hundred and ninety-seven free proteins enriched in tumor tissue CM based on the midterm maternal-placental interface expression profile. |
HPRT1 exhibits the most significant enrichment among the 197 enriched proteins and is associated with worse DFS and OS
Hypoxanthine-guanine phosphoribosyltransferase (HPRT) is a housekeeping gene involved in nervous system development. HPRT deficiency causes the dysregulation of many cellular functions, including cell cycle control, proliferation, RNA metabolism, DNA replication and DNA repair (13). In the present study, HPRT1 exhibited the most significant enrichment among the 197 aforementioned proteins (Table IV).
Elevated plasma levels of HPRT1 protein were associated with poor prognosis. The median HPRT1 concentration (0.50 ng/ml) was defined as a cutoff point. The patients were divided into a low HPRT1 group (n=29) and a high HPRT1 group (n=30). Comparisons of Kaplan-Meier curves revealed lower DFS and OS among patients with high HPRT1 (P=0.002 and P=0.003, respectively) (Fig. 4).
Discussion
In the present study, after a brief in vitro culture of lung cancer and normal bronchial tissues, we analyzed proteins that were released into serum-free CM (all ingredients are known). This system can accurately reflect the tumor microenvironment. We used LTQ MS with the characteristics of high scanning speed to identify the full spectrum of the total protein in CM samples and completed the initial establishment of a lung cancer-associated free protein database. The primary organ culture model eliminates the interference from high-abundance proteins, reduces the dynamic range of the full spectrum of proteins, and is suitable for label-free quantitative proteomics. Therefore, we introduced a label-free quantitative parameter, spectral count, to identify differential free proteins in the CM while obtaining the full spectrum of proteins. The use of biostatistics and bioinformatics enables us to standardize MS data, identify differential proteins and establish differential protein profiles that can correctly distinguish cancer and paracancerous normal tissues. We used protein annotation, as well as GO, network and pathway analysis, to investigate the signaling pathways underlying changes in free proteins in the lung cancer microenvironment.
In the present study, the proteins in the lung cancer CM were significantly enriched in gene clusters associated with the midterm maternal-placental interface of strong invasiveness. Similar to the trophoblast cell-mediated invasion that occurs in the maternal-placental interface, tumor invasion occurs at the boundary where the tumor and host interact, and the exchange of cytokines and related proteases between tumor cells and stromal cells further facilitates tumor cell migration (14). We identified that the full spectrum of tumor tissue CM likely reflects the dynamic change in this microenvironment. It is noteworthy that compared with the heterogeneity and multiple genetic changes in tumor occurrence and development, the individual difference in embryonic development is much smaller. It may be possible to simplify the interpretation of tumor invasion from the perspective of developmental biology.
Since Lobstein et al introduced the concept of the embryonic origin of tumors in 1829, the similarities in biological behaviors between embryo implantation and tumor invasion/metastasis have received increasing attention. Embryo implantation is under the complex regulatory network involving hormones, cytokines, the immune system and genes, and implantation is a precise physiological process with strict temporal and spatial regulation, whereas invasion is a malignant pathological life phenomenon of malignancies with deregulated temporal and spatial control. During the embryonic implantation process, ‘false malignant’ trophoblast cells of blastocysts show striking similarities with cancer cells in terms of cell proliferation and differentiation, signal transduction pathways for invasion, vascular erosion and angiogenesis, immune escape and apoptosis (15). Research on embryo implantations has revealed that during the process of embryonic implantation into the endometrium, a large number of oncogenes are expressed that are also expressed during the process of tumor formation. These oncogenes include c-Met, c-fms, c-Ki, FGF-2 and Src (15). Numerous studies have revealed that matrix metalloproteinases (MMPs), the ECM and numerous cell adhesion molecules are also involved in the implantation of early embryonic trophoblast cells into the endometrium and in the process of tumor invasion and metastasis (17,18).
Winn et al (12) used chips to analyze placental-maternal interface specimens and obtained differential gene expression profiles that were closely associated with placental invasion. We identified a total of 828 high-confidence proteins in the CM from the tumor tissue culture corresponding to 9 cases of lung cancer, wherein 511 proteins were present for at least two cases, and 427 proteins had corresponding gene IDs in the gene bank. We used the GSEA software to conduct enrichment analysis of the 427 proteins based on the differential expression profiles of placental-maternal interfaces at different stages. The results indicated that 197 free proteins had significant enrichment in the gene expression profiles of the midterm placenta. We also performed a further in-depth study of the SPP1, TIMP-1 and YWHAB expression in NSCLC. Using the lung cancer tissue microarray constructed in our laboratory, we assessed the expression of these proteins for samples corresponding to 318 cases of NSCLC. The results revealed that the expression levels of SPP1 (19), TIMP-1 and YWHAB (20) in lung tumor tissues and lymph node metastatic foci were significantly higher than those in normal lung tissues and the expression of these proteins was correlated to lymph node metastasis and clinical stage. In addition, overexpression of SPP1 promoted ECM invasion by lung cancer cells.
HPRT1 exhibited the most significant enrichment among the 197 significantly enriched proteins and was associated with worse DFS and OS for the lung cancer patients included in the present study. Several studies have demonstrated that HPRT1 mutations are associated with the exposure of lung epithelial cells to particles, which induces massive neutrophil recruitment and is correlated with tumor formation (21,22). The in vitro coincubation of rat lung epithelial cells with bronchoalveolar lavage (BAL) cells isolated from particle-treated rats increased mutation frequency in the HPRT gene (23). The downregulation of etoposide-induced p38 mitogen-activated protein kinase (MAPK)-mediated expression of excision repair cross-complementary 1 (ERCC1) could reduce significant increases in etoposide-induced HPRT gene mutation frequency and decrease the cellular ability to repair DNA damage in etoposide-exposed human NSCLC cells (24). In secondhand smoke research, human lung cancer cells exposed to sidestream smoke for 24 h exhibited significantly elevated levels of oxidative DNA damage to HPRT, which contributed to lung carcinogenesis (25).
In conclusion, embryonic development and tumor formation demonstrate similar behaviors and underlying molecular mechanisms, and tumors can be considered a special ‘organ’ due to an abnormal regulation of organ formation (26). Accordingly, the present study investigated lung cancer based on an embryonic development model and combined systems biology and developmental biology to simplify the tumor analysis model and thus identify the protein profiles associated with lung cancer invasion and metastasis.
Acknowledgements
The authors thank Professor Wantao Ying and Dr Wei Jia, for their technical support of LC-MS analysis.
Funding
The present study was funded by the CAMS Innovation Fund for Medical Sciences (CIFMS) (grant no. 2016-I2M-1-001) and the National Basic Research Program of China (grant no. 2014CBA02004).
Availability of data and materials
The datasets used during the present study are available from the corresponding author upon reasonable request.
Authors' contributions
LF and TX conceived and designed the study. LF, YY, ML and JS performed the experiments. TX and ML wrote the paper. LF, YG, JS and SC reviewed and edited the manuscript and were also involved in the conception of this study. All authors read and approved the manuscript and agree to be accountable for all aspects of the research in ensuring that the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Ethics approval and consent to participate
All patients provided written informed consent before surgery, and treatments were performed in accordance with current ethical principles of the Independent Ethics Committee, Cancer Hospital, Chinese Academy of Medical Sciences.
Patient consent for publication
Not applicable.
Competing interests
The authors state that they have no competing interests.
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