Significant Down-Regulation of Urea Cycle Generates Clinically

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Significant Down-regulation of Urea Cycle Generates Clinically Relevant Proteomic Signature in Hepatocellular Carcinoma Patients with Macrovascular Invasion Yin Cao, WenWen Ding, Jingzi Zhang, Qi Gao, HaoXiang Yang, Wangsen Cao, Zhongxia Wang, Lei Fang, and Ronghui Du J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.8b00921 • Publication Date (Web): 22 Mar 2019 Downloaded from http://pubs.acs.org on March 22, 2019

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Journal of Proteome Research

Significant Down-regulation of Urea Cycle Generates Clinically Relevant Proteomic Signature in Hepatocellular Carcinoma Patients with Macrovascular Invasion Yin Cao1,2‡, WenWen Ding1‡, JingZi Zhang1‡, Qi Gao1, HaoXiang Yang1, WangSen Cao1, ZhongXia Wang2*, Lei Fang1*, RongHui Du1* 1

Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, 22

Hankou Road, Gulou District, Nanjing 210093, China 2

Department of Hepatobiliary Surgery, the Affiliated Drum Tower Hospital of Nanjing

University Medical School, 321 Zhongshan Road, Gulou District, Nanjing 210008, China

*Correspondence should be addressed to Dr. RongHui Du ([email protected]), Dr. Lei Fang ([email protected]) and Dr. ZhongXia Wang ([email protected]).

Abstract: Vascular invasion is considered as the critical risk factors of hepatocellular carcinoma (HCC). To reveal the molecular mechanisms underlying macrovascular invasion (MaVI) in HCC, we performed an iTRAQ based proteomic study to identify notably dysregulated proteins from 8 HCC patients with differential vascular invasion and further confirmed them in the other 53 HCC patients. 47 proteins were found significantly down-regulated in HCC with MaVi. More importantly, 30 of them were not changed in HCC without MaVI. Gene ontology analysis of these 47 proteins shows the top 3 enriched biological processes are urea cycle, gluconeogenesis and arginine biosynthetic process. We validated 9 remarkably dysregulated candidates in HCC patients with MaVI by Western blot, including 8 down-regulated proteins (CPS1, ASS1, ASL,

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ARG1, BHMT, DMGDH, Annexin A6 and CES1) and 1 up-regulated protein (CKAP4). Furthermore, dysregulation of CPS1, ASL and ARG1, key enzymes involved in urea cycle, together with Annexin A6 and CES1, major proteins in regulating cholesterol homeostasis and fatty acid ester metabolism were verified using immunohistochemical staining. The significant down-regulation of urea cycle generates clinically relevant proteomic signature in HCC patients with macrovascular invasion, which may provide possible insights into the molecular mechanisms of metastasis and new therapeutic targets of HCC.

Keywords: HCC; macorvascular invasion; iTRAQ; urea cycle; proteomic signature; molecular mechanisms.

Introduction Hepatocellular carcinoma (HCC) represents the third most common cause of cancer-related death worldwide, leading to about 600,000 deaths annually (1, 2). Curative hepatectomy is now widely considered as the first choice of therapy for HCC with well liver functional reserve, particularly early-stage HCC (3). Unfortunately, approximately 70% of HCC patients have a recurrence within the 5 years after curative hepatectomy (4). Vascular invasion is generally considered as an important risk factor for the prognosis of HCC patients after the hepatectomy (5). The invasion of hepatic vasculature of HCC could be further divided into microvascular or macrovascular invasion. Microvascular invasion (MiVI) is defined as tumor identifiable only under microscopy within vascular spaces surrounded by endothelium, while macrovascular


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invasion (MaVI) refers to gross tumor invasion into main trunk or branches of portal vein or hepatic vein (6, 7). MiVI and MaVI may represent the stepwise process of vascular invasion that finally lead to intrahepatic dissemination and distal metastasis of HCC (8, 9). Multiple studies have revealed that vascular invasion, including both MiVI and MaVI, was inversely correlated with the survival of HCC patients. Patients with MiVI may benefit from anatomical liver resection, transcatheter therapy and radiotherapy (10-13). Despite recent diagnosis and treatment options improved, the prognosis of HCC with MaVI remains dismal. It has been reported that the median survival of HCC patients with MaVI is only between 2-6 months with supportive care (7, 14, 15). MaVI is traditionally considered as a contraindication for surgical resection (16-18) though several inconsistent studies reported survival of HCC with MaVI was improved by radical surgical procedures. International guidelines including the Barcelona Clinic Liver Cancer system, the European Association for the Study of Liver Disease and the Asian Pacific Association for the Study of the Liver recommend sorafenib as the only option for advanced HCC with MaVI (7, 18). However, sorafenib can only slightly improve the survival by 1-3 months (7, 17, 19). MaVI of the hepatic and/or portal vein is present in about 10-40% of patients at diagnosis (15, 20, 21). Lower rates of MaVI are reported when HCC is diagnosed early (20) while MaVI is seen in up to 44% of patients with end-stage HCC (22). To find more promising biomarkers to diagnose the vascular invasion of HCC at early stage is urgent and necessary. Meanwhile, current evidence on the molecular mechanism of MaVI is rather limited. Thus, it is of great significance to shed light on the underlying mechanism of MaVI in HCC, which may lead to the innovation of novel therapy to improve the prognosis of this deadly disease.


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In this study, we collected surgical specimens of HCC patients with MiVI(-) (without microvascular invasion), MiVI(+) or MaVI, and performed an iTRAQ based proteomic study to identify significantly dysregulated proteins in paired tumor versus adjacent para-tumor tissues. A great number of differentially expressed proteins involved in urea cycle, gluconeogenesis, arginine biosynthetic, fatty acid metabolism and cancer cell motility/invasion were revealed in HCC patients with MaVI. More importantly, the expression of these proteins specifically changed in MaVI are not affected in HCC patients with MiVI(-) and MiVI(+), which may represent clinically relevant proteomic signatures of MaVI and provide potential therapeutic targets for further investigation. Materials and Methods Tissue samples preparation of HCC patients Table 1. Patient demographics and clinical characteristics.

a

AFP, alpha-fetoprotein, AFP value > 10 is positive through the manufacturer's introduction.


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This study was approved by the Ethics Committee of the Affiliated Drum Tower Hospital of Nanjing University Medical School. All tissues of HCC patients were obtained from Department of Hepatobiliary Surgery, the Affiliated Drum Tower Hospital of Nanjing University Medical School. The general and clinical information of all participated patients were well documented and recorded by experienced pathologists. We totally collected surgical specimens of 61 HCC patients with MiVI(-) (n=23), MiVI(+) (n=23) or MaVI (n=15) for proteomic study and further validation using Western blot and Immunohistochemical (IHC) staining (Table 1). All the patients acknowledged and consent the use of their tissue samples for this study. The liver tissues were snap frozen in liquid nitrogen and stored at -80 °C for further analysis. For iTRAQ experiments, HCC patients with MaVI (4 patients: A, B, C, D), MiVI(+) (2 patient: E, F) and MiVI(-) (2 patients: G, H) were selected by two experienced pathologists based on the common clinical and histopathologic features, and also taking into account their age and gender. (Table 2). Both pathologically confirmed liver tumor tissues and adjacent para-tumor liver tissues from the same patient were collected. Table 2. Information of 8 patients selected for iTRAQ experiments

b

F: female, M: male.


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Protein isolation, digestion and labeling with iTRAQ reagents 100mg tissue of tumor and adjacent para-tumor from HCC patients was used for protein isolation. Briefly, the tissues were first homogenized in RIPA lysis buffer (50 mM Tris-HCl, 0.5% NP-40, 0.25% Na-deoxycholate, 1 mM EDTA and 1% Protease Inhibitor Cocktail III and V, 1 mM PMSF, 1 mM Na3VO4, 1 mM NaF, pH 7.4), incubated for 30 min on ice, then followed by non-contact ultrasonic decomposition at 4 °C using Bioruptor Plus sonication device (Diagenode, Belgium). The supernatant was collected and cell debris was removed by centrifugation at 12,000 rpm for 30 min. The protein concentration was determined with the Pierce™ BCA Protein Assay Kit (Thermo Scientific, USA) and further confirmed by Coomassie brilliant blue staining. For on-filter protein digestion, an aliquot of total protein (100 μg) was diluted to 100 μl with 0.5 M TEAB, reduced with 5 mM TCEP for 1 h at 55 °C, and then alkylated with 6.25 mM MMTS for 30 min at room temperature in darkness. The obtained protein was then transferred to 10K filter (Vivacon, USA) followed by centrifugation at 12,000 rpm for 30 min to remove solvent and washed 3 times with 100 μl 0.5 M TEAB by repeating centrifugation. Finally, trypsin (Promega, USA) was added onto the filter at 1:50 trypsin-to-protein mass ratio for the first digestion overnight, and 1:100 trypsin-to-protein mass ratio for a second 4 h-digestion at 37 °C. The resultant peptides were collected and labeled with iTRAQ Reagent-8 plex Multiplex Kit (AB SCIEX) according to the manufacturer’s instructions. The samples were labeled as shown in Table 3: In iTRAQ experiment I, four HCC para-tumor samples (P) from patient A-D were labeled with iTRAQ tag 113, 115, 117 or 119, and four HCC tumor samples (T) from patient AD were labeled with iTRAQ tag 114, 116, 118 or 121. In iTRAQ experiment II, four HCC para-


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tumor samples (P) from patient E-H were labeled with iTRAQ tag 113, 115, 117 or 119, and four HCC tumor samples (T) from patient E-H were labeled with iTRAQ tag 114, 116, 118 or 121. For each iTRAQ experiment, all labeled peptides were mixed together, speedvac dried and fractionated into 48 fractions using high-performance liquid chromatography (HPLC) system (SHIMADZU) with a Durashell C18 column (5 μm, 100 Å, 4.6 × 250 mm). Finally, 16 samples were obtained by pooling every 16 fractions, e.g. pool fraction 1, 17, 33 as sample 1, fraction 2, 18, 34, as sample 2, until fraction 16, 32, 48 as sample 16. After desalting and speedvac drying, 16 samples were resuspended in 3% (v/v), formic acid 2% (v/v) acetonitrile for LC-MS/MS analysis. Table 3. iTRAQ labeling information iTRAQ experiment I

iTRAQ experiment II


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LC-MS/MS analysis MS data acquisition was performed with a NanoLC.2D (Eksigent Technologies) coupled with a TripleTOF 5600+ System (AB SCIEX). Samples were chromatographed using a 60 min gradient from 2–80% (mobile phase A 0.1% (v/v) formic acid, 2% (v/v) acetonitrile; mobile phase B 0.1% (v/v) formic acid, 98% (v/v) acetonitrile) after direct injection onto a nanoLC Column, 3C18-CL, 75 μm*15 cm (Eksigent Technologies). The gradient was comprised of an increase from 2% to 25% solvent B over 35 min, 25% to 50% B in 9 min and climbing to 80% B in 6 min then holding at 80% B for the last 6 min, all at a constant flow-rate of 300 nL/min. MS spectra were collected in the range 350–1,500 m/z for 250 ms. The 50 most intense precursors with charge state 2–5 were selected for fragmentation, and MS/MS spectra were collected in the range 100– 2,000 m/z for 100 ms; precursor ions were excluded from reselection for 15 s. Database searching The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (23, 24) partner repository with the dataset identifier PXD011846. Submission details: Project Name: Clinically Relevant Proteomic Signature in Hepatocellular Carcinoma Patients with Macrovascular Invasion. Project accession: PXD011846; Project DOI: Not applicable. Reviewer account details: Username: [email protected]; Password: WbyoQjLY. The original MS/MS data were submitted to ProteinPilot Software (version 4.5, AB Sciex) for data analysis and searched against Homo sapiens in UniProt database (April 9, 2016, containing 160,566 sequences, http://www.uniprot.org/proteomes/UP000005640). The following search parameters were used: the instrument was TripleTOF 5600, iTRAQ quantification, trypsin digestion, cysteine modified with MMTS; thorough ID, quantitate, bias correction and


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background correction were checked for protein quantification and normalization. An automatic decoy database search strategy was used to estimate FDR (false discovery rate) using the PSPEP (Proteomics System Performance Evaluation Pipeline Software) algorithm. Only proteins with a valid p value were selected for further analysis. For identification of differentially expressed proteins in tumor/para-tumor, we specifically defined protein with fold change  1.2, p value < 0.05 as up-regulated, and fold change  0.8, p value < 0.05 as down-regulated. Bioinformatics analysis Further bioinformatics analyses were carried out with R studio and other requisite softwares. For quality control and overview of mass spectrometry data, principal component analysis (PCA) (the R package “ggplot2”) and whole-proteome heatmap (the R package “pheatmap”) was performed to demonstrate the similarity or heterogeneity in all tumor and para-tumor tissues from four patients in each iTRAQ experiment. Then, the overall dynamic changes of protein expression between tumor and para-tumor tissues (T/P) per patient were displayed using volcano plot with the R package “ggplot2” (the cutoff value of statistical significance was p < 0.05, fold change was  1.2 or  0.8). And the reproducibility of potential differentially expressed proteins among each patient group was performed by the R package “VennDiagram”. For in-depth information, the stable differentially expressed proteins in T/P were displayed by heatmap (the R package “pheatmap”) and classified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and

Genomes

(KEGG)

pathway

annotation

using

DAVID

online

tools

(http://david.abcc.ncifcrf.gov). The GO and KEGG pathway with a corrected p-value < 0.05 is considered as significant. For each category, a two-tailed Fisher’s exact test was employed to test the enrichment of the differentially expressed protein against all identified proteins (Prism 6 software); KEGG database was used to map the differentially expressed protein at concerned


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metabolic pathways (https://www.kegg.jp); and protein-protein interaction network analysis (PPI) was performed via STRING online tools (http://string-db.org), and manually reorganized. Western blot analysis Tumor and adjacent para-tumor tissues were homogenized in RIPA lysis buffer containing all necessary protease and phosphatase inhibitors. 100 g of protein from each sample was separated by 12% SDS-PAGE gel and transferred to PVDF membrane (Merck Millipore, Germany). The membrane was blocked with 5% non-fat milk in Tris-buffered saline (TBS) and incubated overnight at 4°C with the primary antibody in TBS containing 0.1% Tween-20 (TBST). The following antibodies were used: carbamoyl-phosphate synthetase 1 (CPS1,1:2500, 18703-1-AP, Proteintech), argininosuccinate synthetase 1 (ASS1, 1:5000, 16210-1-AP, Proteintech), argininosuccinate lyase (ASL, 1:800, 16645-1-AP, Proteintech), arginase 1 (ARG1, 1:2500,16001-1-AP, Proteintech), betaine-homocysteine methyltransferase (BHMT, 1:2000, 15965-1-AP, Proteintech), dimethylglycine dehydrogenase (DMGDH, 1:5000, 24813-1-AP, Proteintech), carboxylesterase 1 (CES1, 1:2500, 14587-1-AP, Proteintech), annexin A6(Annexin A6, 1:1000, 12542-1-AP, Proteintech) and cytoskeleton-associated protein 4 (CKAP4, 1:8000, 16686-1-AP, Proteintech). After washing with TBST, the membrane was incubated with a horseradish peroxidase (HRP)-conjugated secondary antibody for 1 h at room temperature and developed using a chemiluminescent HRP substrate (Merck Millipore, Germany). Signal intensities were quantified using Image J software and protein levels were normalized to GAPDH. Immunohistochemical staining


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Immunohistochemical (IHC) staining was performed on liver tissues from HCC patients with differential vascular invasion to validate the proteomic results. In brief, consecutive sections (5 m thickness) of formalin-fixed, paraffin-embedded specimens from HCC patients were stained with various antibodies. IHC staining was performed using specific antibodies against CPS1 (1:50), ASL (1:250), BHMT1 (1:100), Annexin A6 (1:250) and CES1 (1:40) from Proteintech. After rinsing with washing buffer, the slides were incubated with appropriate HRP conjugated secondary antibody. The intensities and percentages of the stained sections were graded by experienced liver pathologists，and the staining intensity was scored as negative (0, less than 5% of cells staining), weak positive (1+, 5-30% of cell staining), moderate positive (2+, 31-60% of cells staining), and strong positive (3+, greater than 60% of cells staining). The IHC score was finally obtained by multiplying intensity (0, 1+, 2+, 3+) and distribution percentage. Statistical analysis All of the data were processed using SPSS 12.0 (SPSS Inc., Chicago, IL). When the data were analyzed nonparametric distribution was assumed, therefore the Wilcoxon matched paired test or Kruskal–Wallis test was used, initially with Dunn’s post-test for ANOVA analysis. Results were considered significant when p < 0.05. Results and Discussion A schematic workflow of screening MaVI specific proteins from HCC patients The extremely poor prognosis of HCC patients is largely due to the high frequency of disease recurrence or distant metastasis after surgical resection (25). Macrovascular invasion has been considered as a critical risk factor (8, 9). Identification of MaVI specific dysregulated proteins


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will benefit the elucidation of underlying mechanism of HCC progression, providing new therapeutic targets of HCC with MaVI. However, comprehensive proteomic profile of HCC patients with MaVI has not been well established.

Figure 1. A schematic workflow of screening MaVI specific proteins from HCC patients using iTRAQ based strategy. Briefly, we collected tumor and para-tumor liver tissues from totally 8 HCC patients, including 4 MaVI (Patient A-D), 2 MiVI(+) (Patient E, F) and 2 MiVI(-) (Patient G, H) patients. After protein extraction and trypsin digestion, two independent iTRAQ labeling experiments were performed separately as described in


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Materials and Methods. For both iTRAQ experiments, the labeled peptides were then pooled together for HPLC fractionation and subject to LC-MS/MS analysis. Database searching and intensive bioinformatics analyses were performed to identify potential MaVI specific HCC biomarkers.

In this study, we have developed an efficient workflow to screen MaVI specific dysregulated proteins from HCC patients (Fig. 1). Briefly, we collected tumor and para-tumor liver tissues from totally 8 HCC patients, including 4 MaVI (Patient A-D), 2 MiVI(+) (Patient E, F) and 2 MiVI(-) (Patient G, H) patients. After protein extraction and trypsin digestion, two independent iTRAQ labeling experiments were performed separately as described in Materials and Methods (Table 1). For both iTRAQ experiments, the labeled peptides were then pooled together for HPLC fractionation and subject to LC-MS/MS analysis. Database searching and intensive bioinformatics analyses were performed to identify potential MaVI specific HCC biomarkers. These potential biomarkers were further confirmed and validated by Western blot and IHC staining in large patient cohort. Protein identification and quantification overview In patients with MaVI, totally 4,258 proteins were identified in the iTRAQ experiment. Among these 4,258 proteins, 2,450 proteins were quantified with a valid p value, which were preserved for further analysis (Fig. 2A). In patients without MaVI, a total of 3,650 proteins were identified, and 2,950 proteins were quantified. To have an overview of all proteins quantified across 8 samples in patients with MaVI or MiVI(+)/(-), principal component analysis (PCA) was performed using prcomp. 2D scatter PCA score plots were visualized by ggplot2 to determine which PCs best separated the para-tumor versus tumor tissues. The PCA explains 46.9% of the variance in MaVI Group (Fig. 2B: PC1 = 27.4%, PC2 = 19.5%) and 41.6% of the variance in MiVI(+)/(-) Group (Fig. 2C: PC1=23.7%, PC2=17.9%). The results demonstrated that para-


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tumor tissues and tumor tissues could be separated into two distinct groups in both iTRAQ experiments, indicating there was remarkable heterogeneity between these two tissue types (Fig. 2B, 2C). However, in iTRAQ experiment I, although all 4 para-tumor tissues were tightly grouped, tumor tissues A, B and C were grouped more closely than tumor tissue D, implying tumor tissue D was more heterogeneous. Similarly, in iTRAQ experiment II, tumor tissues E, G and H were more tightly grouped than tumor tissue F. Heatmap was further generated to clearly demonstrate the distinct protein expression pattern between HCC tumor tissue (T) and its corresponding para-tumor tissue (P) (Fig. 2D, 2E). Interestingly, the para-tumor tissues from patients A-D had very similar protein expression pattern, whereas tumor tissues from the same 4 patients showed remarkably differential protein expression pattern, especially in patient D, indicating that protein expression in tumor tissues were dysregulated among different patients, which could be caused by individual variance of patient.


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Figure 2. Protein identification and quantification overview. A. Total number of identified (blue bar) and quantified (yellow bar) proteins in two independent iTRAQ experiments. Group I: iTRAQ experiment I consists of T/P from 4 HCC patients with MaVI (Patient A-D), Group II: iTRAQ experiment II consists of T/P from 2 MiVI(+) (Patient E, F) and 2 MiVI(-) (Patient G, H) patients. B, C. PCA analysis of two independent iTRAQ experiments I and II, respectively. Para-tumor tissues and tumor tissues can be separated into two distinct groups in both iTRAQ experiments. Patients are named A, B, C, etc., and T indicates tumor, P indicates para-tumor. AT represents tumor of patient A, BT represents tumor of patient B, and AP represents


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para-tumor of patient etc. D, E. Heatmap shows distinct protein expression pattern of HCC tumor tissue (T) and its corresponding para-tumor tissue (P) in two independent TRAQ experiments, respectively.

Identification of stably dysregulated proteins in HCC patients with MaVI Volcano plot was used to efficiently visualize the differentially expressed proteins in tumor tissue versus para-tumor tissue (T/P) in each HCC patient. When comparing T/P for the same patient, protein with fold change  1.2 and p < 0.05 was considered as up-regulated (red dots), while fold change  0.8 and p < 0.05 was considered as down-regulated (green dots). As shown in Figure 3A-3D, a great number of dysregulated proteins were found in each patient when comparing tumor tissue to para-tumor tissue. A summary of up- and down-regulated proteins in each patient was also shown (Fig. 3E). To identify stably up- or down-regulated proteins in T/P across all 4 patients, venn diagram analysis was performed, showing totally there were 47 proteins down-regulated (Fig. 3G), while only 3 proteins were up-regulated (Fig. 3F & Fig. S1). Heatmap of 3 stably up-regulated and 47 down-regulated proteins in T/P in all 4 patients demonstrated their differential expression level across 8 samples (Fig. 3H). Considering a great number of up-regulated and down-regulated proteins each patient respectively has, the final only 3 stably up-regulated proteins in all 4 patients suggested the high heterogeneity of 4 tumor tissues, especially for up-regulated proteins. Further venn diagram analysis of up- or downregulated proteins in MiVI(-), MiVI(+) and MaVI showed that 30 out of 47 down-regulated proteins identified in MaVI were specific in HCC patient with MaVI (Fig. 3I & 3J, Fig. S2 & S3). Thus, these 47 stably down-regulated proteins in MaVI could serve as a potential pool for the identification of macrovascular invasion specific HCC biomarkers.


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Figure 3. Identification of stably dysregulated proteins in HCC patients with MaVI. A-D is volcano plot of all quantified proteins in patient A-D, respectively. When comparing T/P for the same patient, a protein with fold change  1.2 and p < 0.05 was considered as up-regulated (red dots), while fold change  0.8 and p < 0.05


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was considered as down-regulated (green dote). E. A summary of up-regulated and down-regulated proteins in 4 MaVI patients. F, G. Identification of stably up- or down-regulated proteins in T/P in 4 MaVI patients using venn diagram analysis. Totally there were 47 proteins down-regulated (F), while only 3 proteins up-regulated (G) in T/P in all 4 patients. H. Heatmap of 47 stably up-regulated and 3 down-regulated proteins in T/P in all 4 patients. I, J. Venn diagram analysis of up- (I) or down-regulated proteins (J) in MiVI(-), MiVI(+) and MaVI. 30 out of 47 down-regulated proteins are specific in HCC with MaVI.

Figure 4. Bioinformatics analysis of 47 down-regulated proteins in HCC with MaVI. A. KEGG pathway analysis. B. Gene ontology analysis showed urea cycle as top 1 enriched biological process. C. Heatmap of 5 key enzymes in urea cycle which were significantly down-regulated in HCC with MaVI.

Bioinformatics analysis of 47 stably down-regulated proteins in MaVI HCC patients Intensive bioinformatics analyses were performed for the 47 stably down-regulated proteins in T/P in MaVI patients. KEGG pathway analysis showed the most enriched pathways were valine,


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leucine and isoleucine degradation, fatty acid degradation, glycolysis/gluconeogenesis, and biosysthesis of amino acids, followed by arginine biosynthesis, alanine, aspartate and glutamate metabolism, and fatty acid metabolism (Fig. 4A). A detailed down-regulated expression profile of glucose and lipid metabolism pathways was shown in Figure S4A and S4B, and proteinprotein interaction network displayed these proteins interacted with each other (Fig. S4C). In gene ontology analysis, the top 3 enriched biological processes were urea cycle, gluconeogenesis and arginine biosynthesis process, followed by response to zinc ion, cellular response to glucagon stimulus, fatty acid beta-oxidation and response to drug (Fig. 4B). Heatmap in Figure 4C showed the expression pattern of 5 core enzymes CPS1, OTC, ASS1, ARG1 and ASL in urea cycle were significantly down-regulated in T/P in all 4 patients. Validation of potential MaVI specific biomarkers by Western blot and IHC staining To select potential biomarkers of HCC with MaVI for further validation, we setup several criteria including functional classification based on our bioinformatics analysis, previous reports on their function and their correlation with HCC. We finally validated the expression of 9 candidates including 8 down-regulated proteins (CPS1, ASS1, ASL, ARG1, BHMT, DMGDH, Annexin A6 and CES1) and 1 up-regulated protein (CKAP4) in T/P of HCC patients with MaVI by Western blot (n =15) and IHC (n=15). The expression of 6 urea cycle related enzymes (CPS1, ASS1, ASL, ARG1, BHMT and DMGDH in Fig. 5A and Fig. S5), Annexin A6 and CES1 (Fig. 5B) in all 4 paired tissue samples was markedly reduced in tumor tissues with MaVI than in the corresponding para-tumor tissues. Moreover, the intensity of these 8 proteins in 11 paired tissue samples with MaVI were quantified, normalized to loading control GAPDH, and the results demonstrated that all of them had significantly lower expression levels in tumor tissues than in the para-tumor tissues (Fig. 5 C-J). To investigate whether the dysregulation of these proteins


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was caused by aberrant gene expression, quantitative real-time PCR was performed to measure the mRNA levels of 4 urea cycle genes CPS1, ASS1, ASL, ARG1 and one other gene CKAP4 in paired P/T tissues of 11 HCC patients with MaVI (Fig. S6). The results showed similar changes in their mRNA levels compared to protein levels as observed in Western blot (Fig.5, Fig. S6). Annexin A6 is a lipid-binding protein highly expressed in the liver regulating cholesterol homeostasis and signaling pathways (26-28). Our data indicated that Annexin A6 was more than 2-fold reduced in tumor tissue compared to the adjacent para-tumor tissue in HCC with MaVI (Fig. 5B and 5I), which is consistent with Christa Buechler’s work showing that Annexin A6 is specifically reduced in HCC (29).

Figure 5. Validation of significantly dysregulated proteins in HCC patients with MaVI by Western blot. A. Western blot validated the decrease of 6 urea cycle related enzymes CPS1, ASS1, ASL, ARG1, BHMT and


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DMGDH in HCC tumor tissue (T) with MaVI, compared to corresponding para-tumor tissue (P). B. Western blot validated the decrease of Annexin A6 and CES1, and the increase of CKAP4 in T/P in HCC. T and P tissue samples from 11 MaVi patients in Table 1 (independent from those 4 patients A-D used in iTRAQ) were tested, and results of 4 representative patients were shown here. C-K. Quantification results of Western blot shown in A. GAPDH was used as loading control for normalization. The decreased expression of CPS1, ASS1, ASL, ARG1, BHMT, DMGDH, Annexin A6, CES1 and increase of CKAP4 in T/P was shown (p < 0.01), respectively.

In addition to down-regulated proteins, we also selected cytoskeleton-associated membrane protein 4 (CKAP4), one of the up-regulated proteins in iTRAQ results for validation. CKAP4, also known as P63, is a type II transmembrane protein located in the endoplasmic reticulum (30). Previous studies have shown that CKAP4 is important in maintaining the structure of the endoplasmic reticulum. It can also inhibit the proliferation of bladder cancer cells by combining its ligand anti-proliferative factor (31). Expression of CKAP4 showed obvious up-regulation in tumor tissues of MaVI when determined by Western blot (Fig.5B and 5K). To our knowledge, this is the first systematic investigation of the prognostic significance of CKAP4 in HCC, especially in HCC patients with MaVI. To further validate our MS results, 5 out of the 9 candidates were selected for IHC staining. Figure 6A showed a representative IHC staining pattern obtained from 11 paired HCC tissues with MaVI, which displayed remarkably reduced expression of the candidate proteins CPS1, ASL, BHMT, Annexin A6 and CES1 in tumor (T) compared with para-tumor tissues (P). The IHC scores from 11 HCC patients were converted into four different intensities: negative (0), weak positive (1+), moderate positive (2+) and strong positive (3+), and were represented with different colors, unambiguously demonstrating the markedly down-regulation of these 5 proteins


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in tumors with MaVI. Among them, CPS1 and CES1 were the most significantly down-regulated in all 11 tumor tissues compared with para-tumor in MaVI (Fig. 6B).

Figure 6. Detection of five biomarker candidates in HCC with MaVI by IHC staining. A. Representative IHC staining demonstrated markedly decrease of CPS1, ASL, BHMT, Annexin A6 and CES1 in T/P in HCC. The scale bar is 100 m. B. A summary of IHC staining for CPS1, ASL, BHMT, Annexin A6 and CES1 in 11 paired T/P liver tissue sections from HCC with MaVI. The IHC scores were converted into four different intensities: negative (0), weak positive (1+), moderate positive (2+), and strong positive (3+), and were represented with different colors as shown.

CPS1 is the flux generating urea cycle feeder enzyme, converting ammonium into carbamoyl phosphate (32). Patients with CPS1 deficiency exhibit lethally severe hyperammonemia in the neonatal period, because ammonia can’t be converted to carbamoyl phosphate to enter the urea cycle. Earlier studies have reported suppression of CPS1 expression in HCC due to the hypermethylation of CPS1 gene (33-36). CES1 is a highly expressed liver-specific serine esterase, a


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key drug metabolizing enzyme playing critical physiologic roles in liver. Na’s group in Korea reported that CES1 is more potent and specific than alpha-fetoprotein in distinguishing cancer from other liver diseases. They used 2D-DIGE to determine the down-regulation of CES1 in liver tissue (37, 38). They also reported that the level of liver CES1 was elevated in the plasma of HCC patients, but was remarkably down-regulated in HCC tumor tissues. To elucidate the specificity of CPS1 and CES1 down-regulation in MaVI, we determined their expression in 53 paired HCC tissues including 21 MiVI(-), 21 MiVI(+) and 11 MaVI by IHC and Western blot. As shown in Figure 7 and Figure S7, expression of CPS1 in tumor (T) with MiVI(-) and MiVI(+) didn’t stably change compared with para-tumor (P), but significantly decreased in tumor (T) with MaVI, indicating CPS1 has been precisely reduced during the progression of HCC with MiVI(-) or MiVI(+) to MaVI. Interestingly, our data demonstrated that CES1 expression was continuously decreasing in HCC tumor with the progress of vascular invasion from MiVI(-) to MiVI(+), until it was almost undetectable in HCC tumor with MaVI. This is the first report that reduced expression of CES1 is accompanying with the progression of vascular invasion in HCC. The step-wisely decreasing expression of CES1 with the exacerbation of vascular invasion from MiVI(-), MiVI(+) to MaVI could be used to diagnose the extent of vascular invasion in HCC patients .


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Figure 7. CPS1 and CES1 have distinct expression pattern during the progress of vascular invasion in HCC. A. Representative IHC staining for CPS1 and CES1 in T/P of HCC with different extents of vascular invasion. n=6 for MiVI(-), MiVI(+) and MaVI, respectively. B. Western blot analysis of CPS1 and CES1 expression in T/P of HCC with different extents of vascular invasion. Results of two representative patients were shown here and the remaining were shown in Fig. S7, n=15 for MiVI(-) and MiVI(+), and n=5 for MaVI. C. Quantitation of CPS1 and CES1 expression as shown in B. CPS1 is specifically down-regulated in HCC with MaVI, while CES1 was continuously decreasing in HCC with the progress of vascular invasion. ** indicates p < 0.01.

Urea cycle was remarkably down-regulated in HCC patients with macrovascular invasion Urea cycle is the essential metabolic pathway controlled by 5 key enzymes in the liver for detoxification of ammonia, which converts highly toxic ammonia to urea for excretion (39-41). ASS1, acting as a rate-limiting enzyme of urea cycle in hepatocytes and endothelial cells, generates argininosuccinate from citrulline and aspartate (42). Argininosuccinate is subsequently converted to arginine and fumarate by ASL, which is the downstream of ASS1 (43). Then ARG1


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is responsible for converting arginine to urea for final excretion. Several studies have reported ASS1 is absent in HCC (44, 45), and Yang et al. found ASL expression was reduced in more than 30% of HCC patients after they observed 61 cases (46). Although urea cycle has been reported to be involved in several cancers including HCC, the precise function of urea cycle in HCC with MaVI remains unclear. To thoroughly evaluate the dysregulation of urea cycle in HCC patients with MaVI, we compared T/P iTRAQ ratio of all 12 urea cycle related key enzymes, including 5 enzymes in urea cycle and 7 enzymes upstream of it in all 4 HCC patients. Besides the 5 core enzymes CPS1, OTC, ASS1, ARG1 and ASL in urea cycle, other urea cycle related enzymes such as BHMT, BHMT2, DMGDH, SARDH and GLDC were also significantly reduced in tumor tissue compared to para-tumor tissue (Fig. 8). Only 2 enzymes CHDH and ALDH7A1, which are far upstream of urea cycle, were a little down-regulated or not changed.


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Figure 8. Urea cycle is remarkably down-regulated in HCC patients with macrovascular invasion. A. The down-regulation of urea cycle and its related key enzymes in tumor tissue vs. para-tumor tissue in all 4 HCC patients with MaVI. The T/P iTRAQ ratios of all 12 urea cycle related key enzymes, including 5 enzymes in urea cycle and 7 enzymes upstream of it were shown. Besides the 5 core enzymes CPS1, OTC, ASS1, ARG1 and ASL in urea cycle, other urea cycle related enzymes such as BHMT, BHMT2, DMGDH, SARDH and GLDC were also significantly reduced in tumor tissue compared to para-tumor tissue in HCC with MaVI.

In addition to proteomic study, we also performed TCGA database analysis to investigate the correlation between mRNA level of urea cycle enzymes and HCC. Unexpectedly, among 12 urea cycle related enzymes, only mRNA level of BHMT was significantly down-regulated in HCC tumor compared to para-tumor tissue (Fig. 9, Fig. S8). Considering that HCC patients in TCGA database were not finely distinguished into MiVI(-), MiVI(+) and MaVI, these results support that down-regulation of urea cycle might not be a characteristic for tumor tissue of all HCC, but only specifically for that of HCC with MaVI. In accordance with this, we found that lower mRNA level of several urea cycle enzymes such as CPS1, OTC, ALDH7A1, BHMT, BHMT2, DMGDH and SARDH were significantly correlated with the decreased overall survival rate of HCC, but had no correlation with disease free survival rate of HCC (Fig. 9, Fig. S8). In combination with our proteomic findings that urea cycle was markedly impaired in tumor tissue of HCC with MaVI, we speculate that dysregulated urea cycle probably inhibits the overall survival rate of HCC by promoting macrovascular invasion and metastasis of HCC. Thus, the remarkably down-regulation of urea cycle and its upstream pathway in tumor tissue of HCC patients with MaVI provides valuable insight into the molecular mechanisms of HCC progression and also potential therapeutic targets of MaVI for further investigation.


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Figure 9. TCGA analysis of urea cycle and its related key enzymes in tumor tissue (n=369) compared to paratumor tissue (n=160) of HCC. A-G. The mRNA level of urea cycle related enzymes (OTC, CPS1, ALDH7A1, BHMT, BHMT2, DMGDH and SARDH) in tumor tissue of HCC (High: n=182, Low: n=182) and their correlation with overall /disease free survival rate of HCC patients were analyzed in TCGA database. Only enzymes have significant change in mRNA level in T/P in HCC, or its mRNA level is positively correlated with overall survival rate of HCC were shown. Complete analysis results can be found in Figure S8.

Conclusion Our study illustrated remarkably dysregulated proteomic profile in HCC with MaVI using iTRAQ technique. The significant down-regulation of urea cycle generates clinically relevant proteomic signature in HCC patients with macrovascular invasion. In particular, the reduction of CPS1 is MaVI specific, while CES1 is decreasing step-wisely with the exacerbation of vascular invasion, providing evidences that CPS1 and CES1 have the potential to indicate the progression of vascular invasion in HCC. These stably dysregulated proteins in MaVI, especially key enzymes in urea cycle, may represent potential therapeutic targets for further investigation and pave a way for new insights into intervention of macrovascular invasion of HCC.

Supporting Information The following supporting information is available free of charge at ACS website http://pubs.acs.org. Figure S1: The iTRAQ ratio of 3 up-regulated proteins in HCC patients with macrovascular invasion.


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Figure S2: Summary of dysregulated proteins in MiVI(+) HCC patients identified by iTRAQ. Figure S3. Summary of dysregulated proteins in MiVI(-) HCC patients identified by iTRAQ. Figure S4. Down-regulated proteins in glucose and lipid metabolic pathways in HCC patients with macrovascular invasion. Figure S5. Validation of significantly dysregulated proteins in HCC patients with MaVI (patient A-D) by Western blot. Figure S6. Evaluation of the mRNA levels of the significantly dysregulated proteins in HCC patients with MaVI by real-time qPCR. Figure S7. Western blot analysis of CPS1 and CES1 expression in T/P of HCC with MiVI(-) and MiVI(+). Figure S8. The mRNA level of urea cycle and its related key enzymes in tumor tissue (n=369) compared to para-tumor tissue (n=160) of HCC by TCGA analysis.

Corresponding Author *Correspondence should be addressed to: Dr. RongHui Du ([email protected]), 22 Hankou Road, Gulou District, Nanjing University, Nanjing, 210093, People’s Republic of China. Phone: +86-25-83596845, Fax: +86-2583596845. Dr. Lei Fang ([email protected]), 22 Hankou Road, Gulou District, Nanjing University, Nanjing, 210093, People’s Republic of China. Phone: +86-25-83596845, Fax: +86-2583596845.


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Dr. ZhongXia Wang ([email protected]), 321 Zhongshan Road, Gulou District, Nanjing, 210008, People’s Republic of China. Phone: +86-25-83596845, Fax: +86-25-83596845.


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Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. ‡These authors contributed equally. Funding Sources This work was supported by the National Natural Science Foundation of China (No. 81673430, 81602093, 31500664 and 31770838), Natural Science Foundation of Jiangsu Province (No. BK20160118 and BK20171338), the Fundamental Research Funds for the Central Universities (No. 021414380215, 021414380258, 021414380333 and 021414380334) and Provincial Undergraduate Training Programs for Innovation (No.S201810284048). Acknowledgement We thank “Translational Medicine Core Facilities of Medical School of Nanjing University” for the use of mass spectrometry facilities and bioinformatics analysis. Abbreviations HCC, hepatocellular carcinoma; MaVI, macrovascular invasion; MiVI, microvascular invasion; iTRAQ, isobaric tags for relative and absolute quantification; CPS1, carbamoyl-phosphate synthetase 1; ASS1, argininosuccinate synthetase 1; ASL, argininosuccinate lyase; ARG1, arginase 1; BHMT, betaine-homocysteine methyltransferase; DMGDH, dimethylglycine dehydrogenase; CES1, carboxylesterase 1; CKAP4, cytoskeleton-associated protein 4. Supporting Information Supplementary figures S1-S8


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