Systems biology analysis of the lung cancer‑related secretome

  • Authors:
    • Lin Feng
    • Yikun Yang
    • Min Li
    • Jie Song
    • Yanning Gao
    • Shujun Cheng
    • Ting Xiao
  • View Affiliations

  • Published online on: June 20, 2018     https://doi.org/10.3892/or.2018.6509
  • Pages: 1103-1118
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Abstract

Tumorigenesis is closely and highly associated with developmental biology. The present study aimed to discover and identify marker proteins strongly associated with the occurrence and development of non‑small cell lung cancer (NSCLC) in humans and to provide new ideas for investigating lung cancer markers by combining biological analyses of embryonic development. We established primary cultures for samples of tumor and control tissues from 9 patients with NSCLC and collected conditioned medium (CM). Subsequently, we used liquid chromatography and linear ion trap (LTQ) mass spectrometry to isolate and identify proteins in CM samples. Data mining of free proteins was conducted using the analogous analysis strategy in systems biology to obtain important lung cancer‑associated proteins (plasma markers). Proteins with significant plasma enrichment in lung cancer patients were detected via enzyme‑linked immunosorbent assay (ELISA). We identified 987 high‑confidence proteins and established a primary database of free proteins associated with lung cancer. Furthermore, 511 high‑confidence proteins were present in CM from primary tissue cultures from at least 2 of the 9 examined cases of lung cancer. Analysis using Gene Set Enrichment Analysis (GSEA) software revealed significant enrichment for 197 proteins from the CM of lung cancer samples in maternal‑placental interface expression profiles for a mid‑term placenta with strong invasiveness relative to RNA expression profiles for a human full‑term placenta after delivery. ELISA results demonstrated that hypoxanthine phosphoribosyltransferase 1 (HPRT1) was associated with worse rates of disease‑free survival (DFS) and overall survival (OS). The biological behaviors of embryonic implantation are similar to those of tumor invasion and metastasis, and the information obtained regarding developmental biology could facilitate the interpretation of tumor invasion and metastasis. Therefore, similar biological behaviors combined with analyses at different molecular levels from the perspective of systems biology will provide new ideas for tumor research.

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 (57). 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.

Table I.

Demographic features of primary culture tissue samples.

Table I.

Demographic features of primary culture tissue samples.

No.SexAgeHistopathological typesTNM stagingPathological stagingDifferentiation degree
25Female75ADCT2N0M0IBModerately
26Male68ADCT2N2M0IIIAModerately
27Male73SCCT2N0M0IBModerate-poorly
29Male65LCLCT3N1M0IIIAPoorly
30Male52SCCT2N1M0IIBModerately
31Male37SCCT4N2M0IIIBModerately
33Female61SCCT2N1M0IIBPoorly
34Male58SCCT3N2M0IIIAWell
38Male45ADCT3N1M0IIIAModerate-poorly

[i] ADC, lung adenocarcinoma; ASC, adenosquamous carcinoma of the lung; SCC, squamous cell carcinoma; SCLC, small cell lung cancer; LCLC, large cell lung carcinoma.

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 II.

Seventy-eight proteins with increased expression in the CM of primary cultures of lung cancer.

IPI accession no.Gene symbolGene descriptionFold change (T/N)Cover (%)
IPI00012165.3MUC5BMucin 5B, oligomeric mucus/gel-forming16.590.47
IPI00031564.1C7orf24Chromosome 7 open reading frame 248.3820.74
IPI00009943.2TPT1Tumor protein, translationally-controlled 15.4915.43
IPI00171834.3KRT19Keratin 194.4551.43
IPI00550640.2IGHG4 4.2715.64
IPI00024638.3LOC100133623 4.1817.03
IPI00549574.2OTUB1OTU domain, ubiquitin aldehyde binding 14.1118.45
IPI00419384.1PRKCSHProtein kinase C substrate 80 K-H4.084.36
IPI00386327.1MUC5ACMucin 5AC, oligomeric mucus/gel-forming4.073.73
IPI00604523.1MRCL3Myosin regulatory light chain MRCL33.9421.47
IPI00022792.3MFAP4 Microfibrillar-associated protein 43.8417.25
IPI00025110.3MSLNMesothelin3.6515.92
IPI00477225.1PLS3Plastin 3 (T isoform)3.568.13
IPI00396378.3HNRNPA2B1Heterogeneous nuclear ribonucleoprotein A2/B13.4920.11
IPI00295386.6CBR1Carbonyl reductase 13.3410.51
IPI00472610.2IGHM 3.1421.34
IPI00100160.3CAND1Cullin-associated and neddylation-dissociated 13.0314.15
IPI00215747.4FABP7Fatty acid binding protein 7, brain363.36
IPI00012887.1CTSL1Cathepsin L12.9710.51
IPI00027341.1CAPGCapping protein (actin filament), gelsolin-like2.867.18
IPI00465248.4ENO1Enolase 1, (alpha)2.8632.56
IPI00555616.1SOD2Superoxide dismutase 2, mitochondrial2.8119.37
IPI00001639.2KPNB1Karyopherin (importin) beta 12.789.36
IPI00514931.1THBS2Thrombospondin 22.699.47
IPI00478493.1HPHaptoglobin2.6714.78
IPI00219219.2LGALS1Lectin, galactoside-binding, soluble, 1 (galectin 1)2.6523.13
IPI00552325.1HLA-CMajor histocompatibility complex, class I, C2.5919.95
IPI00329200.4RANBP5RAN binding protein 52.558.68
IPI00012007.5AHCY S-adenosylhomocysteine hydrolase2.5317.40
IPI00013933.1DSPDesmoplakin2.464.18
IPI00219018.5GAPDH Glyceraldehyde-3-phosphate dehydrogenase2.4522.09
IPI00216746.1HNRPKHeterogeneous nuclear ribonucleoprotein K2.437.54
IPI00215911.2APEX1APEX nuclease (multifunctional DNA repair enzyme) 12.4111.04
IPI00413112.2ANXA8Annexin A82.3826.20
IPI00169383.2PGK1Phosphoglycerate kinase 12.3620.91
IPI00383237.3PKM2Pyruvate kinase, muscle2.3411.32
IPI00102821.3MGC29506Hypothetical protein MGC295062.3128.04
IPI00105407.1AKR1B10Aldo-keto reductase family 1, member B10 (aldose reductase)2.349.05
IPI00031008.1TNCTenascin C (hexabrachion)2.324.35
IPI00186290.5EEF2Eukaryotic translation elongation factor 22.338.39
IPI00025512.2HSPB1Heat shock 27 kDa protein 12.361.95
IPI00009342.1IQGAP1IQ motif containing GTPase activating protein 12.2831.80
IPI00418262.3ALDOCAldolase C, fructose-bisphosphate2.2825.34
IPI00008527.1RPLP1Ribosomal protein, large, P12.2451.75
IPI00479191.1HNRPH1Heterogeneous nuclear ribonucleoprotein H1 (H)2.2111.65
IPI00019502.1MYH9Myosin, heavy chain 9, non-muscle2.2111.33
IPI00215901.1AK2Adenylate kinase 22.2128.03
IPI00216691.4PFN1Profilin 12.211.51
IPI00024466.1UGCGL1UDP-glucose ceramide glucosyltransferase-like 12.196.11
IPI00018352.1UCHL1Ubiquitin carboxyl-terminal esterase L1 (ubiquitin thiolesterase)2.1338.57
IPI00024067.1CLTCClathrin, heavy chain (Hc)2.1310.81
IPI00028091.1ACTR3ARP3 actin-related protein 3 homolog (yeast)2.1210.53
IPI00183626.7PTBP1Polypyrimidine tract binding protein 12.1119.21
IPI00219525.9PGDPhosphogluconate dehydrogenase2.0915.56
IPI00382428.4FBLN5Fibulin 52.068.07
IPI00219025.2GLRXGlutaredoxin (thioltransferase)2.0611.43
IPI00216171.2ENO2Enolase 2 (gamma, neuronal)1.9925.87
IPI00107831.3PTPRFProtein tyrosine phosphatase, receptor type, F1.992.27
IPI00218836.1DBIDiazepam binding inhibitor (GABA receptor modulator, acyl-Coenzyme A binding protein)1.9934.62
IPI00465028.5TPI1Triosephosphate isomerase 11.9842.17
IPI00399265.1TPD52L2Tumor protein D52-like 21.9827.51
IPI00003881.3HNRPFHeterogeneous nuclear ribonucleoprotein F1.9620.00
IPI00060715.1KCTD12Potassium channel tetramerisation domain containing 121.9515.08
IPI00000875.5EEF1GEukaryotic translation elongation factor 1 gamma1.9416.28
IPI00465430.4XRCC6X-ray repair complementing defective repair in Chinese hamster cells 6 (Ku autoantigen, 70 kDa)1.9210.18
IPI00514090.1LTA4HLeukotriene A4 hydrolase1.9125.93
IPI00010303.1SERPINB4Serpin peptidase inhibitor, clade B (ovalbumin), member 41.9141.28
IPI00011937.1PRDX4Peroxiredoxin 41.99.23
IPI00550363.1TAGLN2Transgelin 21.8925.63
IPI00008524.1PABPC1Poly(A) binding protein, cytoplasmic 11.8913.68
IPI00005969.1CAPZA1Capping protein (actin filament) muscle Z-line, alpha 11.8923.08
IPI00003269.1DKFZp686D0972Similar to RIKEN cDNA 4732495G21 gene1.8716.49
IPI00395676.1UGP2UDP-glucose pyrophosphorylase 21.8617.71
IPI00294578.1TGM2Transglutaminase 2 (C polypeptide, protein-glutamine-gamma-glutamyltransferase)1.8610.19
IPI00020672.3DPP3 Dipeptidyl-peptidase 31.8310.05
IPI00479733.1ERO1LERO1-like (S. cerevisiae)1.7813.86
IPI00007423.1ANP32BAcidic (leucine-rich) nuclear phosphoprotein 32 family, member B1.7620.32
IPI00023648.3ISLRImmunoglobulin superfamily containing leucine-rich repeat1.627.01

Table III.

Sixty-five proteins with significantly decreased expression in the CM of the tumor tissue culture.

Table III.

Sixty-five proteins with significantly decreased expression in the CM of the tumor tissue culture.

IPI accession no.Gene symbolGene descriptionFold change (T/N)Cover (%)
IPI00001508.1INSInsulin precursor0.5525.45
IPI00179357.1TTNTitin0.540.08
IPI00299155.5PSMA4Proteasome subunit alpha type 40.5317.62
IPI00020091.1ORM2Alpha-1-acid glycoprotein 2 precursor0.5212.94
IPI00008164.1PREPProlyl endopeptidase0.504.93
IPI00401264.5TXNDC4Thioredoxin domain containing protein 4 precursor0.5016.50
IPI00004656.1B2M Beta-2-microglobulin precursor0.5026.89
IPI00006114.4SERPINF1Pigment epithelium-derived factor precursor0.4915.31
IPI00293867.6DDTD-dopachrome tautomerase0.4817.95
IPI00292936.4CXCL5Small inducible cytokine B5 precursor0.4610.53
IPI00298406.3HADH3-hydroxyacyl-CoA dehydrogenase, isoform 20.4613.33
IPI00219682.5STOMErythrocyte band 7 integral membrane protein0.4612.54
IPI00014572.1SPARCSPARC precursor0.4625.74
IPI00472112.1LOC730410Splice Isoform 2 of HLA class I histocompatibility antigen, A-11 alpha chain precursor0.458.36
IPI00024993.4ECHS1Enoyl-CoA hydratase, mitochondrial precursor0.4519.31
IPI00556607.1PSMB4Proteasome (Prosome, macropain) subunit, beta type, 40.4417.42
IPI00479877.3ALDH9A1 4-trimethylaminobutyraldehyde dehydrogenase0.445.67
IPI00003818.1KYNUKynureninase0.4216.99
IPI00218323.1TPD52N8 protein long isoform0.4210.08
IPI00012119.1DCNSplice Isoform A of Decorin precursor0.4120.61
IPI00295400.1WARSTryptophanyl-tRNA synthetase0.4114.86
IPI00008561.1MMP1Interstitial collagenase precursor0.418.96
IPI00218163.1MUC1Splice Isoform 2 of Mucin-1 precursor0.402.22
IPI00219910.1BLVRBFlavin reductase0.4018.01
IPI00027463.1S100A6Calcyclin0.4051.11
IPI00024284.4HSPG2Basement membrane-specific heparan sulfate proteoglycan core protein precursor0.403.83
IPI00395488.2VASNVasorin0.398.02
IPI00304840.3COL6A2Splice Isoform 2C2 of Collagen alpha 2(VI) chain precursor0.392.45
IPI00299738.1PCOLCEProcollagen C-proteinase enhancer protein precursor0.384.68
IPI00413959.2CLSTN1Calsyntenin-1 precursor0.3711.01
IPI00183508.2TWF1Twinfilin isoform 10.3611.46
IPI00031030.1APLP2Splice Isoform 1 of Amyloid-like protein 2 precursor0.354.33
IPI00003590.1QSOX1Quiescin Q60.359.37
IPI00032293.1CST3Cystatin C precursor0.3425.34
IPI00555841.1H2AFVH2A histone family, member V isoform 1 variant0.3415.33
IPI00102165.1H2AFJHypothetical protein FLJ109030.3318.06
IPI00166866.3IGHV3OR16-13MGC27165 protein0.3313.43
IPI00015102.1ALCAMCD166 antigen precursor0.337.38
IPI00218816.6HBBHemoglobin beta chain0.3287.76
IPI00007047.1S100A8Calgranulin A0.3120.43
IPI00465260.1GARSGARS protein0.314.79
IPI00026944.1NID1Nidogen precursor0.303.53
IPI00022078.3NDRG1NDRG1 protein0.3020.56
IPI00216138.5TAGLNTransgelin0.2826.00
IPI00007427.1AGR2Anterior gradient protein 2 homolog precursor0.2822.29
IPI00298237.4TPP1Splice Isoform 1 of Tripeptidyl-peptidase I precursor0.287.99
IPI00410714.2HBA1Alpha 2 globin variant0.2530.28
IPI00305461.2ITIH2Inter-alpha-trypsin inhibitor heavy chain H2 precursor0.257.29
IPI00022463.1TFSerotransferrin precursor0.2513.47
IPI00299547.2LCN2Lipocalin 20.2424.50
IPI00297646.2COL1A1AlphA 1 type I collAgen preproprotein0.242.80
IPI00020986.2LUMLumican precursor0.2320.71
IPI00006663.1ALDH2Aldehyde dehydrogenase, mitochondrial precursor0.208.51
IPI00465084.5DESDesmin0.1914.71
IPI00029723.1FSTL1Follistatin-related protein 1 precursor0.1611.36
IPI00027782.1MMP3Stromelysin-1 precursor0.1512.58
IPI00216644.3GSTA1Glutathione S-transferase A10.1548.87
IPI00400826.1CLUClusterin isoform 10.1413.57
IPI00176193.5COL14A1Splice Isoform 1 of Collagen alpha 1(XIV) chain precursor0.147.41
IPI00025426.1PZPPregnancy zone protein precursor0.122.83
IPI00218414.4CA2Carbonic anhydrase II0.1013.51
IPI00478003.1A2M Alpha-2-macroglobulin precursor0.106.24
IPI00025465.1OGNMimecan precursor0.088.72
IPI00550991.1SERPINA3 Alpha-1-antichymotrypsin precursor0.0426.12
IPI00019038.1LYZLysozyme C precursor0.0331.08
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.

Table IV.

One hundred and ninety-seven free proteins enriched in tumor tissue CM based on the midterm maternal-placental interface expression profile.

IPI accession no.Gene symbolGene descriptionCover (%)
IPI00218914.4ALDH1A1Aldehyde dehydrogenase 1 family, member A16.40
IPI00021891.5FGGFibrinogen gamma chain7.88
IPI00297284.1IGFBP2Insulin-like growth factor binding protein 2, 36 kDa11.99
IPI00027341.1CAPGCapping protein (actin filament), gelsolin-like7.18
IPI00027350.1PRDX2Peroxiredoxin 214.65
IPI00022200.2COL6A3Collagen, type VI, alpha 35.42
IPI00014230.1C1QBPComplement component 1, q subcomponent binding protein21.63
IPI00027780.1MMP2Matrix metallopeptidase 2 (gelatinase A, 72 kDa gelatinase, 72 kDa type IV collagenase)12.58
IPI00031420.1UGDHUDP-glucose dehydrogenase8.70
IPI00028908.3NID2Nidogen 2 (osteonidogen)5.06
IPI00028564.1GBP1Guanylate binding protein 1, interferon-inducible, 67 kDa5.57
IPI00556478.1SH3BGRLSH3 domain binding glutamic acid-rich protein like12.28
IPI00029658.1EFEMP1EGF-containing fibulin-like extracellular matrix protein 18.33
IPI00465248.4ENO1Enolase 1, (alpha)32.56
IPI00218493.6HPRT1Hypoxanthine phosphoribosyltransferase 1 (Lesch-Nyhan syndrome)24.42
IPI00009802.1VCANVersican1.39
IPI00219219.2LGALS1Lectin, galactoside-binding, soluble, 1 (galectin 1)23.13
IPI00411706.1ESDEsterase D/formylglutathione hydrolase19.50
IPI00020986.2LUMLumican20.71
IPI00556088.1LGALS3Lectin, galactoside-binding, soluble, 315.66
IPI00550991.1SERPINA3Serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 326.12
IPI00219525.9PGDPhosphogluconate dehydrogenase15.56
IPI00012119.1DCNDecorin31.40
IPI00382428.4FBLN5Fibulin 58.07
IPI00027223.2IDH1Isocitrate dehydrogenase 1 (NADP+), soluble27.05
IPI00017601.1CPCeruloplasmin (ferroxidase)4.51
IPI00024284.4HSPG2Heparan sulfate proteoglycan 23.83
IPI00021000.1SPP1Secreted phosphoprotein 1 (osteopontin, bone sialoprotein I, early T-lymphocyte activation 1)19.18
IPI00400826.1CLUCLU13.57
IPI00010133.1CORO1ACoronin, actin binding protein, 1A11.71
IPI00216298.5TXNThioredoxin32.94
IPI00220362.4HSPE1Heat shock 10 kDa protein 1 (chaperonin 10)25.74
IPI00218836.1DBIDiazepam binding inhibitor (GABA receptor modulator, acyl-Coenzyme A binding protein)34.62
IPI00017696.1C1SComplement component 1, s subcomponent5.06
IPI00028091.1ACTR3ARP3 actin-related protein 3 homolog (yeast)10.53
IPI00026199.1GPX3Glutathione peroxidase 3 (plasma)13.72
IPI00295741.3CTSBCathepsin B9.14
IPI00011937.1PRDX4Peroxiredoxin 49.23
IPI00021841.1APOA1Apolipoprotein A-I15.73
IPI00024095.2ANXA3Annexin A336.34
IPI00001699.1PYCARDPYD and CARD domain containing22.46
IPI00301579.3NPC2Niemann-Pick disease, type C225.83
IPI00021033.1COL3A1Collagen, type III, alpha 1 (Ehlers-Danlos syndrome type IV, autosomal dominant)6.71
IPI00027497.4GPIGlucose phosphate isomerase5.75
IPI00021842.1APOEApolipoprotein E17.35
IPI00215911.2APEX1APEX nuclease (multifunctional DNA repair enzyme) 111.04
IPI00018219.1TGFBITransforming growth factor, beta-induced, 68 kDa18.89
IPI00027444.1SERPINB1Serpin peptidase inhibitor, clade B (ovalbumin), member 115.57
IPI00216134.2TPM1Tropomyosin 1 (alpha)13.03
IPI00018146.1YWHAQTyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, theta polypeptide10.61
IPI00021828.1CSTBCystatin B (stefin B)12.24
IPI00017292.1CTNNB1Catenin (cadherin-associated protein), beta 1, 88 kDa6.27
IPI00032292.1TIMP1TIMP metallopeptidase inhibitor 117.87
IPI00022810.1CTSCCathepsin C7.56
IPI00176903.2PTRFPolymerase I and transcript release factor11.67
IPI00217966.5LDHALactate dehydrogenase A30.42
IPI00011229.1CTSDCathepsin D5.83
IPI00304692.1RBMXRNA binding motif protein, X-linked6.91
IPI00397526.1MYH10Myosin, heavy chain 10, non-muscle2.99
IPI00465038.2FBLN2Fibulin 23.09
IPI00465315.5CYCSCytochrome c, somatic19.23
IPI00019755.3GSTO1Glutathione S-transferase omega 132.22
IPI00003817.1ARHGDIBRho GDP dissociation inhibitor (GDI) beta15.42
IPI00005161.3ARPC2Actin related protein 2/3 complex, subunit 2, 34 kDa16.00
IPI00011654.2TUBBTubulin, beta38.51
IPI00553177.1SERPINA1Serpin peptidase inhibitor, clade A (alpha-1 antiproteinase, antitrypsin), member 17.66
IPI00031812.1YBX1Y box binding protein 111.18
IPI00555616.1SOD2Superoxide dismutase 2, mitochondrial19.37
IPI00023673.1LGALS3BPLectin, galactoside-binding, soluble, 3 binding protein10.60
IPI00302592.1FLNAFilamin A, alpha (actin binding protein 280)5.25
IPI00216691.4PFN1Profilin 111.51
IPI00009904.1PDIA4Protein disulfide isomerase family A, member 48.22
IPI00299547.2LCN2Lipocalin 2 (oncogene 24p3)24.50
IPI00219217.2LDHBLactate dehydrogenase B21.02
IPI00433214.1CKAP4 Cytoskeleton-associated protein 46.70
IPI00006114.4SERPINF1Serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor), member 115.31
IPI00220301.4PRDX6Peroxiredoxin 649.78
IPI00013079.1EMILIN1Elastin microfibril interfacer 15.71
IPI00329633.5TARSThreonyl-tRNA synthetase8.02
IPI00022733.1PLTPPhospholipid transfer protein18.14
IPI00477225.1PLS3Plastin 3 (T isoform)8.10
IPI00375676.2FTLFerritin, light polypeptide13.39
IPI00015361.1PFDN5Prefoldin subunit 533.77
IPI00013508.3ACTN1Actinin, alpha 113.68
IPI00472102.1HSPD1Heat shock 60 kDa protein 1 (chaperonin)
IPI00220271.2AKR1A1Aldo-keto reductase family 1, member A1 (aldehyde reductase)23.15
IPI00024993.4ECHS1Enoyl Coenzyme A hydratase, short chain, 1, mitochondrial19.31
IPI00307162.2VCLVinculin23.02
IPI00419237.1LAP3Leucine aminopeptidase 313.10
IPI00022434.2ALBAlbumin44.84
IPI00029260.2CD14CD14 molecule30.67
IPI00298406.3HADH Hydroxyacyl-Coenzyme A dehydrogenase13.33
IPI00219018.5GAPDH Glyceraldehyde-3-phosphate dehydrogenase22.09
IPI00013976.1LAMB1Laminin, beta 17.78
IPI00554634.1CUTACutA divalent cation tolerance homolog (E. coli)32.96
IPI00028004.2PSMB3Proteasome (prosome, macropain) subunit, beta type, 316.59
IPI00289334.1FLNBFilamin B, beta (actin binding protein 278)14.24
IPI00025084.2CAPNS1Calpain, small subunit 111.80
IPI00219446.4PEBP1 Phosphatidylethanolamine binding protein 115.59
IPI00020672.3DPP3 Dipeptidyl-peptidase 310.05
IPI00514377.3HSPA1AHeat shock 70 kDa protein 1A15.29
IPI00003815.1ARHGDIARho GDP dissociation inhibitor (GDI) alpha38.24
IPI00514090.1LTA4HLeukotriene A4 hydrolase25.93
IPI00005159.2ACTR2ARP2 actin-related protein 2 homolog (yeast)18.05
IPI00007853.1IFI30Interferon, gamma-inducible protein 3032.18
IPI00032140.2SERPINH1Serpin peptidase inhibitor, clade H (heat shock protein 47), member 1, (collagen binding protein 1)33.73
IPI00012726.3PABPC4Poly(A) binding protein, cytoplasmic 4 (inducible form)6.97
IPI00027933.1PSMB10Proteasome (prosome, macropain) subunit, beta type, 1019.05
IPI00419258.3HMGB1High-mobility group box 116.36
IPI00298497.3FGBFibrinogen beta chain6.11
IPI00003590.1QSOX1Quiescin Q6 sulfhydryl oxidase 111.59
IPI00183695.6S100A10S100 calcium binding protein A1040.62
IPI00554482.1NPM1Nucleophosmin (nucleolar phosphoprotein B23, numatrin)11.41
IPI00017672.2NPNucleoside phosphorylase53.58
IPI00180675.4TUBA1ATubulin, alpha 1a7.76
IPI00026781.2FASNFatty acid synthase4.90
IPI00329200.4RANBP5RAN binding protein 5
IPI00465260.1GARSGlycyl-tRNA synthetase4.79
IPI00550073.1CALM3Calmodulin 3 (phosphorylase kinase, delta)22.45
IPI00376005.1EIF5AEukaryotic translation initiation factor 5A23.53
IPI00219622.2PSMA2Proteasome (prosome, macropain) subunit, alpha type, 217.60
IPI00005087.1TMOD3Tropomodulin 3 (ubiquitous)16.19
IPI00419262.1PPIBPeptidylprolyl isomerase B (cyclophilin B)
IPI00290279.1ADKAdenosine kinase13.81
IPI00007427.1AGR2Anterior gradient homolog 2 (Xenopus laevis)22.29
IPI00413451.1SERPINB6Serpin peptidase inhibitor, clade B (ovalbumin, member 620.00
IPI00031461.1GDI2GDP dissociation inhibitor 28.54
IPI00028931.1DSG2Desmoglein 23.13
IPI00026216.4NPEPPSAminopeptidase puromycin sensitive6.42
IPI00550363.1TAGLN2Transgelin 225.63
IPI00418262.3ALDOCAldolase C, fructose-bisphosphate25.34
IPI00008527.1RPLP1Ribosomal protein, large, P151.75
IPI00299155.5PSMA4Proteasome (prosome, macropain) subunit, alpha type, 417.62
IPI00479786.1KHSRPKH-type splicing regulatory protein (FUSE binding protein 2)4.37
IPI00303318.2FAM49BFamily with sequence similarity 49, member B28.70
IPI00555900.1FKSG30Kappa-actin12.00
IPI00176193.5COL14A1Collagen, type XIV, alpha 1 (undulin)7.47
IPI00413959.2CLSTN1Calsyntenin 111.01
IPI00021440.1ACTG1Actin, gamma 117.60
IPI00556607.1PSMB4Proteasome (prosome, macropain) subunit, beta type, 417.42
IPI00025861.2CDH1Cadherin 1, type 1, E-cadherin (epithelial)9.10
IPI00220644.6PKM2Pyruvate kinase, muscle14.75
IPI00257882.5PEPDPeptidase D11.76
IPI00106642.4SDF2L1Stromal cell-derived factor 2-like 16.46
IPI00013698.1ASAH1N-acylsphingosine amidohydrolase (acid ceramidase) 19.25
IPI00032293.1CST3Cystatin C (amyloid angiopathy and cerebral hemorrhage)25.34
IPI00298281.3LAMC1Laminin, gamma 1 (formerly LAMB2)5.97
IPI00026185.4CAPZBCapping protein (actin filament) muscle Z-line, beta24.25
IPI00298547.3PARK7Parkinson disease (autosomal recessive, early onset) 730.16
IPI00297646.2COL1A1Collagen, type I, alpha 12.80
IPI00298853.5GCGroup-specific component (vitamin D binding protein)22.36
IPI00553185.2CCT3Chaperonin containing TCP1, subunit 3 (gamma)11.38
IPI00292771.3NUMA1Nuclear mitotic apparatus protein 11.80
IPI00293867.6DDTD-dopachrome tautomerase17.95
IPI00008561.1MMP1Matrix metallopeptidase 1 (interstitial collagenase)8.96
IPI00298994.3TLN1Talin 11.65
IPI00002460.2ANXA7Annexin A79.02
IPI00297550.7F13A1Coagulation factor XIII, A1 polypeptide6.16
IPI00465439.4ALDOAAldolase A, fructose-bisphosphate7.16
IPI00004656.1B2M Beta-2-microglobulin26.89
IPI00216318.4YWHABTyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, beta polypeptide20.00
IPI00296534.1FBLN1Fibulin 114.20
IPI00003818.1KYNUKynureninase (L-kynurenine hydrolase)16.99
IPI00008223.3RAD23BRAD23 homolog B (S. cerevisiae)7.33
IPI00440493.2ATP5A1ATP synthase, H+ transporting, mitochondrial F1 complex, alpha subunit 1, cardiac muscle5.42
IPI00219445.1PSME3Proteasome (prosome, macropain) activator subunit 3 (PA28 gamma; Ki)16.48
IPI00016862.1GSRGlutathione reductase12.26
IPI00220991.2AP2B1Adaptor-related protein complex 2, beta 1 subunit
IPI00215965.1HNRNPA1Heterogeneous nuclear ribonucleoprotein A111.88
IPI00010740.1SFPQSplicing factor proline/glutamine-rich (polypyrimidine tract binding protein associated)5.08
IPI00027626.2CCT6AChaperonin containing TCP1, subunit 6A (zeta 1)6.42
IPI00398779.3PLEC1Plectin 1, intermediate filament binding protein 500 kDa0.49
IPI00027463.1S100A6S100 calcium binding protein A651.11
IPI00026087.1BANF1Barrier to autointegration factor 129.21
IPI00305969.1EEF1DEukaryotic translation elongation factor 1 delta (guanine nucleotide exchange protein)4.35
IPI00177728.3CNDP2CNDP dipeptidase 2 (metallopeptidase M20 family)26.53
IPI00021347.1UBE2L3 Ubiquitin-conjugating enzyme E2L 321.43
IPI00414676.5HSP90AB1Heat shock protein 90 kDa alpha (cytosolic), class B member 17.33
IPI00216319.2YWHAHTyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, eta polypeptide11.84
IPI00013890.1SFNStratifin41.53
IPI00556148.1CFHComplement factor H4.14
IPI00329801.10ANXA5Annexin A540.62
IPI00455315.3ANXA2Annexin A248.52
IPI00009771.4LMNB2Lamin B24.33
IPI00299000.1PA2G4 Proliferation-associated 2G4, 38 kDa16.24
IPI00297779.6CCT2Chaperonin containing TCP1, subunit 2 (beta)13.67
IPI00168184.5PPP2R1AProtein phosphatase 2 (formerly 2A), regulatorysubunit A, alpha isoform12.93
IPI00012074.2HNRNPRHeterogeneous nuclear ribonucleoprotein R4.40
IPI00018768.1TSNTranslin27.19
IPI00005614.4SPTBN1Spectrin, beta, non-erythrocytic 110.77
IPI00008524.1PABPC1Poly (A) binding protein, cytoplasmic 115.90
IPI00013895.1S100A11S100 calcium binding protein A1156.19
IPI00010796.1P4HB Procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline 4-hydroxylase), beta polypeptide18.31
IPI00100160.3CAND1Cullin-associated and neddylation-dissociated 116.38
IPI00007752.1TUBB2CTubulin, beta 2C45.17
IPI00007118.1SERPINE1Serpin peptidase inhibitor, clade E (nexin, plasminogen activator inhibitor type 1), member 123.38
IPI00451401.2TPI1Triosephosphate isomerase 142.17
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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August-2018
Volume 40 Issue 2

Print ISSN: 1021-335X
Online ISSN:1791-2431

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Copy and paste a formatted citation
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Spandidos Publications style
Feng L, Yang Y, Li M, Song J, Gao Y, Cheng S and Xiao T: Systems biology analysis of the lung cancer‑related secretome. Oncol Rep 40: 1103-1118, 2018.
APA
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., & Xiao, T. (2018). Systems biology analysis of the lung cancer‑related secretome. Oncology Reports, 40, 1103-1118. https://doi.org/10.3892/or.2018.6509
MLA
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., Xiao, T."Systems biology analysis of the lung cancer‑related secretome". Oncology Reports 40.2 (2018): 1103-1118.
Chicago
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., Xiao, T."Systems biology analysis of the lung cancer‑related secretome". Oncology Reports 40, no. 2 (2018): 1103-1118. https://doi.org/10.3892/or.2018.6509