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. 2016 Jul 28;37(10):13595–13606. doi: 10.1007/s13277-016-5275-8

Identification of aldolase A as a potential diagnostic biomarker for colorectal cancer based on proteomic analysis using formalin-fixed paraffin-embedded tissue

Tetsushi Yamamoto 1, Mitsuhiro Kudo 2, Wei-Xia Peng 2, Hideyuki Takata 2,3, Hideki Takakura 1, Kiyoshi Teduka 2, Takenori Fujii 2, Kuniko Mitamura 1, Atsushi Taga 1, Eiji Uchida 3, Zenya Naito 2,
PMCID: PMC5097088  PMID: 27468721

Abstract

Colorectal cancer (CRC) is one of the most common cancers worldwide, and many patients are already at an advanced stage when they are diagnosed. Therefore, novel biomarkers for early detection of colorectal cancer are required. In this study, we performed a global shotgun proteomic analysis using formalin-fixed and paraffin-embedded (FFPE) CRC tissue. We identified 84 candidate proteins whose expression levels were differentially expressed in cancer and non-cancer regions. A label-free semiquantitative method based on spectral counting and gene ontology (GO) analysis led to a total of 21 candidate proteins that could potentially be detected in blood. Validation studies revealed cyclophilin A, annexin A2, and aldolase A mRNA and protein expression levels were significantly higher in cancer regions than in non-cancer regions. Moreover, an in vitro study showed that secretion of aldolase A into the culture medium was clearly suppressed in CRC cells compared to normal colon epithelium. These findings suggest that decreased aldolase A in blood may be a novel biomarker for the early detection of CRC.

Keywords: Colorectal cancer, Shotgun proteomics, Formalin-fixed paraffin-embedded tissue, Aldolase A

Introduction

Colorectal cancer (CRC) is one of the most common cancers worldwide. If the tumor is limited to the mucosa or submucosa, CRC can be completely cured by endoscopic or surgical therapy; however, many patients are already at an advanced stage when they are diagnosed. Therefore, an early detection method is needed. Diagnostic blood tests based on detection of carcinoembryonic antigen (CEA) are now widely used for CRC, but the sensitivity of this biomarker in early-stage cancer is only 5–10 % [1, 2]. The identification of novel candidate molecules that are secreted by cancer cells may lead to the development of early detection methods and improved prognosis.

Formalin-fixed and paraffin-embedded (FFPE) tissues are archived in hospitals, together with detailed clinical information such as disease history, clinical examination results, and drug responses. FFPE tissues are routinely used in the diagnosis and research of diseases, including cancers, by conventional staining, immunohistochemistry (IHC), and in situ hybridization [35]. Previously, FFPE tissues were considered unsuitable for proteomic analysis. However, methods to isolate protein from FFPE tissues for proteomic analysis have been developed, and various FFPE tissues have been used in proteomic studies [617]. Thus, archived FFPE tissues may be useful for identifying new biomarkers.

In this study, we performed shotgun liquid chromatography (LC)/mass spectrometry (MS)-based global proteomic analysis using proteins from FFPE CRC tissue to identify proteins whose expression levels are modified in cancer regions. We identified aldolase A as a candidate protein with potential as a novel biomarker for early detection of CRC.

Materials and methods

Materials

The following materials were purchased from Wako Pure Chemical Industries (Osaka, Japan): guanidine hydrochloride, DTT, Tris, tris (2-carboxyethyl) phosphine hydrochloride (TCEP), and iodoacetamide (IAA). All other chemicals and reagents were purchased from Sigma Chemical Corp. (St. Louis, MO, USA).

Patients and tissue specimens

The tissues used in this study were from 45 patients who underwent surgical resection for CRC at Nippon Medical School Hospital between October 2007 and August 2014. None of the patients received chemotherapy or radiation therapy prior to surgery and none had inflammatory colorectal disease such as colitis or infectious diseases. The pathological diagnosis and clinicopathological stage were determined according to the criteria of the World Health Organization [18]. After a histopathological analysis, 10 of these 45 cases were selected for proteomic analysis. Immunohistochemical analyses were performed on all 45 cases. Paraffin-embedded specimens were prepared for proteomic and immunohistochemical analyses. This study was carried out in accordance with the principles embodied in the Declaration of Helsinki, 2013, and the Japanese Society of Pathology Ethics Committee. Informed consent for the use of colorectal tissues was obtained from all patients.

Protein extraction from FFPE tissue

FFPE CRC tissues from ten patients were used for proteomic analysis. Pathological and clinical information are shown in Table 1. Following histological examination of hematoxylin and eosin (H&E) sections, we separated the cancer regions from the non-cancer regions, which maintained normal structures. Sections (10 μm) were deparaffinized in xylene and rehydrated through a series of graded alcohols (100, 90, 80, and 70 %). After staining with Mayer’s hematoxylin for 5 min, cancer and non-cancer regions were manually dissected under a microscope (Fig. 1). Proteins were extracted from both cancer and non-cancer regions using lysis buffer (6 M guanidine-HCl, 40 mM Tris-HCl pH 8.2, and 65 mM DTT) according to a previous report [17]. Protein concentration was measured by the Bradford method.

Table 1.

Clinical and pathological data of patients with CRC that contributed tissues for proteomic analysis

Patient No. Age (year) Gender pTNM pStaging Tumor location Number of identified proteins
Cancer region Non-cancer region
1 63 M T3N0M0 Stage IIA S 49 26
2 53 M T3N0M0 Stage IIA S 38 38
3 77 F T3N0M0 Stage IIA S 50 34
4 53 M T3N0M0 Stage IIA S 69 52
5 76 F T3N0M0 Stage IIA S 52 22
6 51 M T3N0M0 Stage IIA A 22 4
7 67 F TisN0M0 Stage 0 A 44 28
8 52 M T3N0M0 Stage IIA Ra 52 50
9 69 M T3N0M0 Stage IIA T 65 16
10 69 F T3N0M0 Stage IIA S 19 35

M male, F female, A ascending colon, T transverse colon, S sigmoid colon, Ra upper rectum

Fig. 1.

Fig. 1

Manual dissection of FFPE colon tissue. Representative image shows non-cancer and cancer regions before (a and b, respectively) and after (c and d, respectively) dissection. Sections were stained with hematoxylin

In-solution trypsin digestion

A gel-free digestion was performed according to the protocol described by Bluemlein et al. [19], with slight modifications. Briefly, 10 μg of protein was extracted from each sample, reduced with 45 mM DTT and 20 mM TCEP, and then alkylated using 100 mM IAA. After alkylation, samples were digested with proteomics-grade trypsin (Agilent Technologies Inc., Santa Clara, CA, USA) at 37 °C for 24 h. Digests were purified using PepClean C-18 Spin Columns (Thermo, Rockford, IL, USA) according to the manufacturer’s protocol.

LC-MS/MS analysis for protein identification

Approximately 2 μg of purified peptide samples were injected onto a peptide L-trap column (Chemicals Evaluation and Research Institute, Tokyo, Japan) using an HTS PAL autosampler (CTC Analytics, Zwingen, Switzerland) and further separated thorough an Advance-nano UHPLC (AMR Inc., Tokyo, Japan) using a reverse-phase C18-column (Zaplous column α, 3-μm diameter gel particles and 100 Å pore size, 0.1 × 150 mm; AMR). The mobile phase consisted of solution A (0.1 % formic acid in water) and solution B (acetonitrile). The flow rate was 500 nL/min, with a concentration gradient of acetonitrile from 5 % B to 35 % B over 120 min. Gradient-eluted peptides were analyzed using an amaZon ETD ion-trap mass spectrometer (Bruker Daltonics, Billerica, MA, USA). Data were acquired in a data-dependent manner, in which MS/MS fragmentation was performed on the ten most intense peaks of every full MS scan.

All MS/MS spectra data were searched against the SwissProt Homo sapiens database with Mascot (version_2.3.01; Matrix Science, London, UK). Search criteria were as follows: enzyme, trypsin; allowance of up to two missed cleavage peptides; mass tolerance ±0.5 Da and MS/MS tolerance ±0.5 Da; and modifications of cysteine carbamidomethylation, methionine oxidation, and N-formylation including formyl (K), formyl (R), and formyl (N terminus).

Spectral counting analysis of identified proteins

To compare protein expression across all tissue samples, we used the spectral counting method. In this analysis, when not specific spectral peak could be identified, the expression level of that protein was taken as zero, as described in a previous report [20]. Fold-changes of expressed proteins in the base 2 logarithmic scale were calculated with Rsc based upon spectral counting [21]. Relative amounts of identified proteins were also calculated with the normalized spectral abundance factor (NSAF) [22]. Candidate proteins with modified expression levels in the cancer region were chosen to ensure that the Rsc satisfied >1 or <−1, which corresponded to fold changes of >2 or <0.5.

Bioinformatics

Functional annotations for the identified proteins with modified expression levels in the cancer region were processed using the Database for annotation, visualization, and integrated discovery (DAVID) version 6.7 (http://david.abcc.ncifcrf.gov/home.jsp) [2325].

Quantitative RT-PCR

Total RNA was extracted from FFPE CRC tissue with the RNeasy FFPE Kit (QIAGEN, Valencia, CA, USA) and from CRC cell lines with the GenElute Mammalian Total RNA Miniprep Kit (Sigma). cDNA was synthesized using the SuperScript VILO cDNA Synthesis Kit for FFPE tissue and the High Capacity cDNA Reverse Transcription kit for the CRC cell line according to the manufacturer’s protocols (Life Technologies Japan, Tokyo, Japan). To measure expression of aldolase A, cyclophilin A, and annexin A2 mRNA, quantitative reverse transcription PCR (qRT-PCR) was performed with the 7500 system (Applied Biosystems, Foster City, CA, USA). Primers and TaqMan probes for aldolase A (Hs00765620_m1), cyclophilin A (Hs04194521_s1), annexin A2 (Hs00743063_s1), and 18S rRNA (Hs03928990_g1) were used with the TaqMan Gene Expression Assay. qRT-PCR results were expressed relative to an internal standard concentration as a ratio of target/18S rRNA. Gene expression was measured in triplicate.

Immunohistochemistry

FFPE CRC tissues from 46 patients were used for a validation analysis. Pathological and clinical information are shown in Table 2. Paraffin-embedded tissue sections (3 μm) were subjected to immunostaining using a Histofine Simple Stain MAX-PO (R) kit (Nichirei, Tokyo, Japan) for identifying aldolase A, annexin A2, and cyclophilin A. After deparaffinization, sections were pretreated in an autoclave at 121 °C for 15 min in 10 mM citrate buffer (pH 6.0) for cyclophilin A. Endogenous peroxidase activity was blocked by incubation for 30 min with 0.3 % hydrogen peroxide in methanol. Tissue sections were then incubated with the anti-ALDOA antibody (1:150 dilution; Atlas Antibodies, Stockholm, Sweden) for aldolase A, anti-cyclophilin A antibody (1:150 dilution; Novus Biologicals, Littleton, CO, USA), or anti-annexin A2 antibody (1:400 dilution; Cell Signaling Technology, Inc., Danvers, MA, USA) in phosphate-buffered saline containing 1 % bovine serum albumin for 16 h at 4 °C. Bound antibodies were detected with the Simple Stain MAX-PO (R) with diaminobenzidine tetrahydrochloride as the substrate. Sections were then counterstained with Mayer’s hematoxylin. Two investigators (TY and HT) evaluated all the sections separately in a blinded manner. Sections were scored for both intensity (0, no stain; 1, weak; 2, moderate; and 3, strong) and percentage of epithelial cells that stained positive (0, 0–5 %; 1, 6–25 %; 2, 26–50 %; 3, 51–75 %; and 4, 76–100 %). Scores were derived from the sum of the intensity and percentage of immunoreactive cells [15].

Table 2.

Clinical and pathological data of patients with CRC that contributed tissues for immunohistochemical analysis

Patient No. Age(year) Gender pTNM pStaging Tumor location
1 67 F TisN0M0 Stage 0 A
2 66 F TisN0M0 Stage 0 D
3 61 F TisN0M0 Stage 0 S
4 70 M TisN0M0 Stage 0 T
5 64 F TisN0M0 Stage 0 T
6 63 M T2N0M0 Stage I Rb
7 58 F T2N0M0 Stage I Rb
8 45 F T2N0M0 Stage I Rb
9 67 F T2N0M0 Stage I Ra
10 87 F T2N0M0 Stage I Ra
11 67 F T2N0M0 Stage I S
12 70 M T1N0M0 Stage I S
13 75 F T1N0M0 Stage I T
14 82 M T1N0M0 Stage I T
15 63 M T3N0M0 Stage IIA S
16 53 M T3N0M0 Stage IIA S
17 77 F T3N0M0 Stage IIA S
18 53 M T3N0M0 Stage IIA S
19 76 F T3N0M0 Stage IIA S
20 51 M T3N0M0 Stage IIA A
21 52 M T3N0M0 Stage IIA Ra
22 69 M T3N0M0 Stage IIA T
23 69 F T3N0M0 Stage IIA S
24 92 M T3N0M0 Stage IIA T
25 64 M T2N1aM0 Stage IIIA Ra
26 73 F T2N1bM0 Stage IIIA Ra
27 64 M T3N1aM0 Stage IIIB Ra
28 50 F T3N1bM0 Stage IIIB S
29 51 M T3N1bM0 Stage IIIB A
30 64 M T3N1aM0 Stage IIIB S
31 64 F T3N1bM0 Stage IIIB Ra
32 78 F T3N1aM0 Stage IIIB A
33 72 F T4aN1AM0 Stage IIIB C
34 52 M T3N1bM0 Stage IIIB Ra
35 85 F T4bN1aM0 Stage IIIC A
36 70 M T4aN2aM0 Stage IIIC S
37 81 F T4aN0M1a Stage IVA T
38 71 F T4aN2aM1a Stage IVA A
39 49 M T3N2aM1a Stage IVA C
40 78 M T3N1bM1a Stage IVA Ra
41 77 M T4aN2aM1a Stage IVA T
42 57 M T3N2bM1b Stage IVB Ra
43 72 F T4aN0M1b Stage IVB D
44 71 F T4bN2bM1b Stage IVB C
45 70 M T3N0M1b Stage IVB S

M male, F female, A ascending colon, T transverse colon, S sigmoid colon, Ra upper rectum, Rb lower rectum, D descending colon, C cecum

CRC cell lines

CRC cell lines DLD-1, SW480, and SW620 and normal human colon epithelial cell line CCD 841 CoN were purchased from the American Type Culture Collection (Manassas, VA, USA). All cells were cultured in RPMI 1640 medium supplemented with 10 % fetal bovine serum (FBS) (Gibco, Carlsbad, CA, USA) in an atmosphere containing 5 % CO2.

Protein preparation

CRC cells were plated at a density of 5 × 105 cells per dish in a 100-mm dish and grown in culture medium. After 72 h, cells were solubilized in urea lysis buffer (7 M urea, 2 M thiourea, 5 % CHAPS, and 1 % Triton X-100). To quantify secreted protein, the culture medium of CRC cells was collected after 72 h.

Western blot analysis

The cell extract, culture medium, and commercial human normal serum (ImmunoBioScience Corp., Mukilteo, WA) were subjected to SDS-PAGE under reducing conditions. The separated proteins were transferred to polyvinylidene fluoride transfer membranes. Membranes were incubated with an anti-annexin A2 rabbit monoclonal antibody, anti-aldolase A rabbit monoclonal antibody, or anti-cyclophilin A antibody (Cell Signaling Technology Inc., Beverly, MA, USA) at 4 °C overnight. Membranes were then washed and incubated with HRP-conjugated anti-rabbit IgG antibody (American Qualex, San Clemente, CA). After washing, blots were visualized by enhanced chemiluminescence and detected using a myECL Imager system (ThermoFisher Scientific). The same membranes were reprobed with anti-β-actin antibody (Sigma) to confirm equal loading of the proteins. All Western blot analyses were performed three times.

Statistical analysis

All data are presented as the mean ± standard error of the mean. Data between two groups were compared with the unpaired t test. Values of *P < 0.05 and **P < 0.001 were considered significant in all analyses. Computations were performed with GraphPad Prism version 5 (GraphPad Software, La Jolla, CA, USA).

Results

Protein identification and profiles in cancer and non-cancer regions of CRC tissue

To investigate the molecular profile of proteins expressed in relation to cancer progression, we performed shotgun proteomic analysis using FFPE CRC tissue. We used manual dissection to separate the cancer regions and non-cancer regions from FFPE CRC tissues and examined the protein expression not only in cells but also in the stromal tissue surrounding cells (Fig. 1). We successfully identified proteins in both cancer and non-cancer regions of FFPE tissues (Table 1). Figure 2 shows the Venn map for the proteins identified.

Fig. 2.

Fig. 2

Venn map of proteins identified from FFPE colorectal cancer tissue. We identified 204 proteins in the cancer regions and 142 in the non-cancer regions

Semiquantitative comparison of proteins identified in cancer and non-cancer regions of CRC tissue

We next performed a label-free semiquantitative method based on spectral counting to identify proteins with modified expression levels in the cancer region. The Rsc value was plotted against the corresponding protein (x-axis) in increasing order from left to right for proteins identified in the cancer and non-cancer regions. Positive and negative Rsc values indicate increased and decreased expression, respectively, in the cancer region. In Fig. 3, the NSAF value (bar) was plotted against the corresponding protein (x-axis) and the NSAF values of the cancer regions (black bar) and non-cancer regions (gray bar). Proteins are indicated above and below the x-axis. Proteins with either a high positive or negative Rsc value were considered as potential early detection markers for CRC.

Fig. 3.

Fig. 3

Semiquantitative comparison of proteins identified in FFPE colon tissue. Rsc and normalized spectral abundance factor (NSAF) values calculated for the proteins identified (x-axis). Comparison of protein expression in cancer versus non-cancer tissue. Proteins highly expressed in either cancer or non-cancer regions were plotted near the right or left side of the x-axis

A total of 84 differentially expressed proteins were identified in the cancer regions (Table 3). Representative proteins that were upregulated included known tumor markers such as 60 kDa heat shock protein (HSP60) and carcinoembryonic antigen-related cell adhesion molecule 5 (CEAM5, also known as CEA). By contrast, expression levels of housekeeping proteins such as β-actin and histone H4 did not change.

Table 3.

Differentially expressed proteins in cancer region of CRC samples

No. ID Accession number and description No. of amino acids Spectral counting
Non-cancer Cancer Fold change (Rsc)
1 FCGBP_HUMAN (Q9Y6R7) IgGFc-binding protein 5405 15 1 −3.307086
2 K1C10_HUMAN (P13645) Keratin, type I cytoskeletal 10 584 7 0 −3.163409
3 H3C_HUMAN (Q6NXT2) Histone H3.3C 135 12 1 −3.006964
4 CO1A1_HUMAN (P02452) Collagen alpha-1(I) chain 1464 6 0 −2.975121
5 K22E_HUMAN (P35908) Keratin, type II cytoskeletal 2 epidermal 639 5 0 −2.759125
6 K2C6B_HUMAN (P04259) Keratin, type II cytoskeletal 6B 564 5 0 −2.759125
7 H2B1A_HUMAN (Q96A08) Histone H2B type 1-A 127 9 1 −2.630943
8 K1C14_HUMAN (P02533) Keratin, type I cytoskeletal 14 472 4 0 −2.505717
9 K1C17_HUMAN (Q04695) Keratin, type I cytoskeletal 17 432 4 0 −2.505717
10 K2C5_HUMAN (P13647) Keratin, type II cytoskeletal 5 590 4 0 −2.505717
11 CRIP1_HUMAN (P50238) Cysteine-rich protein 1 77 3 0 −2.198995
12 MUC2_HUMAN (Q02817) Mucin-2 5179 3 0 −2.198995
13 ATPA_HUMAN (P25705) ATP synthase subunit alpha, mitochondrial 553 6 1 −2.125742
14 K2C1B_HUMAN (Q7Z794) Keratin, type II cytoskeletal 1b 578 13 4 −1.887275
15 LMNA_HUMAN (P02545) Prelamin-A/C 664 10 3 −1.84682
16 K1C9_HUMAN (P35527) Keratin, type I cytoskeletal 9 623 15 5 −1.827612
17 ACTN4_HUMAN (O43707) Alpha-actinin-4 911 2 0 −1.810107
18 GLUC_HUMAN (P01275) Glucagon 180 2 0 −1.810107
19 RS7_HUMAN (P62081) 40S ribosomal protein S7 194 2 0 −1.810107
20 K2C1_HUMAN (P04264) Keratin, type II cytoskeletal 1 644 39 18 −1.541287
21 CLCA1_HUMAN (A8K7I4) Calcium-activated chloride channel regulator 1 914 7 3 −1.393723
22 CAH1_HUMAN (P00915) Carbonic anhydrase 1 261 1 0 −1.277731
23 GSLG1_HUMAN (Q92896) Golgi apparatus protein 1 1179 1 0 −1.277731
24 LAMB3_HUMAN (Q13751) Laminin subunit beta-3 1172 1 0 −1.277731
25 MK15_HUMAN (Q8TD08) Mitogen-activated protein kinase 15 544 1 0 −1.277731
26 RS30_HUMAN (P62861) 40S ribosomal protein S30 59 1 0 −1.277731
27 ZHANG_HUMAN (Q9NS37) CREB/ATF bZIP transcription factor 354 1 0 −1.277731
28 ZN408_HUMAN (Q9H9D4) Zinc finger protein 408 720 1 0 −1.277731
29 PGBM_HUMAN (P98160) Basement membrane-specific heparan sulfate proteoglycan core protein 4391 1 0 −1.277731
30 DPYL2_HUMAN (Q16555) Dihydropyrimidinase-related protein 2 572 1 0 −1.277731
31 RL31_HUMAN (P62899) 60S ribosomal protein L31 125 1 0 −1.277731
32 HNRPL_HUMAN (P14866) Heterogeneous nuclear ribonucleoprotein L 589 1 0 −1.277731
33 FLNA_HUMAN (P21333) Filamin-A 2647 1 0 −1.277731
34 CO6A2_HUMAN (P12110) Collagen alpha-2(VI) chain 1019 1 0 −1.277731
35 ARPC5_HUMAN (O15511) Actin-related protein 2/3 complex subunit 5 151 1 0 −1.277731
36 RS23_HUMAN (P62266) 40S ribosomal protein S23 143 1 0 −1.277731
37 MYH14_HUMAN (Q7Z406) Myosin-14 1995 1 0 −1.277731
38 EF2_HUMAN (P13639) Elongation factor 2 858 1 0 −1.277731
39 ECHB_HUMAN (P55084) Trifunctional enzyme subunit beta, mitochondrial 474 1 0 −1.277731
40 FA48A_HUMAN (Q8NEM7) Protein FAM48A 779 1 0 −1.277731
41 SETX_HUMAN (Q7Z333) Probable helicase senataxin 2677 1 0 −1.277731
42 GFAP_HUMAN (P14136) Glial fibrillary acidic protein 432 1 0 −1.277731
43 PERI_HUMAN (P41219) Peripherin 470 1 0 −1.277731
44 POTEE_HUMAN (Q6S8J3) POTE ankyrin domain family member E 1075 1 0 −1.277731
45 TTHY_HUMAN (P02766) Transthyretin 147 1 0 −1.277731
46 CAH2_HUMAN (P00918) Carbonic anhydrase 2 260 1 0 −1.277731
47 ENPL_HUMAN (P14625) Endoplasmin 803 1 0 −1.277731
48 HS71L_HUMAN (P34931) Heat shock 70 kDa protein 1-like 641 1 0 −1.277731
49 CBR1_HUMAN (P16152) Carbonyl reductase [NADPH] 1 277 1 0 −1.277731
50 SPTA2_HUMAN (Q13813) Spectrin alpha chain, brain 2472 1 0 −1.277731
51 HNRCL_HUMAN (O60812) Heterogeneous nuclear ribonucleoprotein C-like 1 293 1 0 −1.277731
52 UGGG1_HUMAN (Q9NYU2) UDP-glucose:glycoprotein glucosyltransferase 1 1555 1 0 −1.277731
53 OST48_HUMAN (P39656) Dolichyl-diphosphooligosaccharide--protein glycosyltransferase 48 kDa subunit 456 1 0 −1.277731
54 ACTA_HUMAN (P62736) Actin, aortic smooth muscle 377 40 23 −1.238478
55 AGR2_HUMAN (O95994) Anterior gradient protein 2 homolog 175 4 2 −1.124439
56 TBB2C_HUMAN (P68371) Tubulin beta-2C chain 445 12 7 −1.124173
57 KCRB_HUMAN (P12277) Creatine kinase B-type 381 8 5 −1.001492
58 HSP7C_HUMAN (P11142) Heat shock cognate 71 kDa protein 643 1 5 1.051122
59 PPIA_HUMAN (P62937) Peptidyl-prolyl cis-trans isomerase A 165 1 5 1.051122
60 SBP1_HUMAN (Q13228) Selenium-binding protein 1 472 1 5 1.051122
61 G3P_HUMAN (P04406) Glyceraldehyde-3-phosphate dehydrogenase 335 6 19 1.0692919
62 ANXA2_HUMAN (P07355) Annexin A2 339 1 6 1.2666356
63 MDHM_HUMAN (P40926) Malate dehydrogenase, mitochondrial 338 1 6 1.2666356
64 ALDOA_HUMAN (P04075) Fructose-bisphosphate aldolase A 364 0 3 1.3418115
65 LDHA_HUMAN (P00338) L-lactate dehydrogenase A chain 332 0 3 1.3418115
66 RL7_HUMAN (P18124) 60S ribosomal protein L7 248 0 3 1.3418115
67 S10A8_HUMAN (P05109) Protein S100-A8 93 0 3 1.3418115
68 RL12_HUMAN (P30050) 60S ribosomal protein L12 165 0 3 1.3418115
69 TBB1_HUMAN (Q9H4B7) Tubulin beta-1 chain 451 0 3 1.3418115
70 TAGL2_HUMAN (P37802) Transgelin-2 199 0 3 1.3418115
71 LDHA_HUMAN (P00338) L-lactate dehydrogenase A chain 332 0 3 1.3418115
72 DHSA_HUMAN (P31040) Succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial 664 0 3 1.3418115
73 S10A9_HUMAN (P06702) Protein S100-A9 114 0 3 1.3418115
74 TBA1A_HUMAN (Q71U36) Tubulin alpha-1 A chain 451 0 3 1.3418115
75 FIBA_HUMAN (P02671) Fibrinogen alpha chain 866 0 4 1.6480523
76 CEAM5_HUMAN (P06731) Carcinoembryonic antigen-related cell adhesion molecule 5 702 0 4 1.6480523
77 RL1D1_HUMAN (O76021) Ribosomal L1 domain-containing protein 1 490 0 4 1.6480523
78 1433B_HUMAN (P31946) 14–3-3 protein beta/alpha 246 0 5 1.9009786
79 ACTN1_HUMAN (P12814) Alpha-actinin-1 892 1 10 1.9060767
80 DEF1_HUMAN (P59665) Neutrophil defensin 1 94 1 13 2.2513044
81 CH60_HUMAN (P10809) 60 kDa heat shock protein, mitochondrial 573 2 23 2.5000084
82 H2B1C_HUMAN (P62807) Histone H2B type 1-C/E/F/G/I 126 0 9 2.620238
83 H31_HUMAN (P68431) Histone H3.1 136 0 13 3.1011611
84 TBB5_HUMAN (P07437) Tubulin beta chain 444 0 13 3.1011611

Expression levels of these 84 proteins were more than two-fold higher or lower in cancer regions compared to non-cancer regions of CRC samples

Functional annotation of differentially expressed proteins in cancer regions of CRC tissue

DAVID was used to perform GO analyses for the differentially expressed proteins identified for each cellular component (Fig. 4). Functional annotations were counted by normalizing to the total number of identified proteins. Based on the cellular component classification, we focused on 21 proteins classified in the extracellular region, which could potentially be detected in the blood of patients with CRC (Table 4).

Fig. 4.

Fig. 4

Analysis of GO cellular components of identified proteins. Protein assignments to GO cellular component categories are shown only for significant categories (p < 0.05)

Table 4.

Proteins categorized as extracellular region proteins

No. Accession number and description Fold change (Rsc)
1 (Q9Y6R7) IgGFc-binding protein −3.3070855
2 (P02452) Collagen alpha-1(I) chain −2.9751214
3 (Q02817) Mucin-2 −2.1989951
4 (O43707) Alpha-actinin-4 −1.8101074
5 (P01275) Glucagon −1.8101074
6 (A8K7I4) Calcium-activated chloride channel regulator 1 −1.3937233
7 (Q13751) Laminin subunit beta-3 −1.2777305
8 (Q8TD08) Mitogen-activated protein kinase 15 −1.2777305
9 (P98160) Basement membrane-specific heparan sulfate proteoglycan core protein −1.2777305
10 (P21333) Filamin-A −1.2777305
11 (P12110) Collagen alpha-2(VI) chain −1.2777305
12 (P02766) Transthyretin −1.2777305
13 (P00918) Carbonic anhydrase 2 −1.2777305
14 (O95994) Anterior gradient protein 2 homolog −1.1244392
15 (P62937) Peptidyl-prolyl cis-trans isomerase A 1.05112197
16 (P07355) Annexin A2 1.26663565
17 (P04075) Fructose-bisphosphate aldolase A 1.34181152
18 (P02671) Fibrinogen alpha chain 1.64805231
19 (P12814) Alpha-actinin-1 1.90607666
20 (P59665) Neutrophil defensin 1 2.25130442
21 (P10809) 60 kDa heat shock protein, mitochondrial 2.50000843

Twenty-one proteins that were differentially expressed in cancer regions of CRC samples were classified as extracellular region proteins by gene ontology analysis

qRT-PCR analysis of aldolase A, cyclophilin A, and annexin A2 in cancer and non-cancer regions of CRC tissue

Fructose-bisphosphate aldolase A (aldolase A), peptidyl-prolyl cis-trans isomerase A (also known as cyclophilin A), and annexin A2 were upregulated in cancer regions (Table 3) and consequently selected as candidate diagnostic biomarkers. To confirm the higher expression levels of the candidate proteins in cancer regions compared to non-cancer regions, we performed qRT-PCR analysis. Expression levels of the mRNAs for these proteins were significantly higher in cancer compared to non-cancer regions (Fig. 5a–c).

Fig. 5.

Fig. 5

qPCR analysis of spectral counting results. Aldolase A, cyclophilin A, and annexin A2 were selected for confirmation. Expression levels of aldolase A, cyclophilin A, and annexin A2 mRNA were significantly higher in cancer compared to non-cancer regions (ac). *p < 0.05, **p < 0.001

IHC analysis of aldolase A, cyclophilin A, and annexin A2 in cancer and non-cancer regions of CRC tissue

We next performed IHC analysis of the three candidate proteins for validation with tissues from 45 CRC cases (Table 2). IHC analysis revealed that expression levels of all three proteins were significantly higher in cancer regions compared to non-cancer regions (Fig. 6).

Fig. 6.

Fig. 6

IHC validation of spectral counting results. Expression levels of aldolase A, cyclophilin A, and annexin A2 were validated by IHC. Representative images of non-cancer regions (a, d, and g) and cancer regions (b, e, and h). Graphs of IHC scores are shown in (c), (f), and (i). Cancer regions showed significantly stronger expression of these three proteins, which is consistent with spectral counting data. *p < 0.05; **p < 0.001. Original magnification, 100×; insets, 400×

Expression of aldolase A, cyclophilin A, and annexin A2 in CRC cell lines

To investigate whether the candidate proteins were suitable as biomarkers, their mRNA and protein expression levels in CRC cell lines were determined by qRT-PCR analysis and western blotting. All tested cell lines expressed the three candidate proteins, and their expression levels in CRC cells tended to be higher than in normal colon epithelial cells (Fig. 7a–d). Aldolase A was not detected in the culture medium of the three CRC cell lines, but it was detected in normal colon epithelial cells (Fig. 7e, upper panel). Cyclophilin A was not detected in the culture medium of any cell lines (Fig. 7e, middle panel). The level of annexin A2 in the culture medium appeared to depend on the level of annexin A2 in the cell extract for each cell line (Fig. 7e, lower panel). Finally, we detected aldolase A in normal human serum and confirmed that the level depended on the loaded serum volume (Fig. 7f, lane 1–3).

Fig. 7.

Fig. 7

Expression of the three candidate proteins in CRC cell lines. Expression levels of aldolase A, cyclophilin A, and annexin A2 were examined by qRT-PCR and western blot. Expression levels of aldolase A (a), cyclophilin A (b), and annexin A2 (c) mRNA in CRC cells were almost all significantly higher than in normal colon epithelium. *p < 0.05; **p < 0.001. Expression levels of the three candidate proteins in cell extracts from CRC cell lines were similar to mRNA expression levels (d). Aldolase A was only detected in the culture medium of normal colon epithelium (e, upper panel). Cyclophilin A was not detected in any of the examined culture medium samples (e, middle panel). The level of annexin A2 in the culture medium appeared to depend on the level in the cell extract for each cell line (e, lower panel). Aldolase A was detected in human normal serum, and the level of aldolase A detected depended on the volume of serum loaded (f, lane 1, 10 μg serum; lane 2, 20 μg serum; lane 3, 30 μg serum)

Discussion

In this study, we used a gel-free LC-MS-based proteomics approach to identify potential biomarkers for cancer in FFPE CRC tissues. We used semiquantitative methods based on spectral counting to detect 84 proteins in which expression levels were altered >2-fold in cancer compared to non-cancer regions of CRC tissue (Table 3). CEA, a known tumor marker used in diagnostic blood tests for CRC, was among these proteins. Thus, the approach used in this study could potentially be used to identify novel biomarker candidates.

To identify early detection markers for CRC that can be detected by diagnostic blood tests, we focused on proteins in the “extracellular region” category of cellular components based on the results of GO analysis (Table 4). These proteins are secreted into the extracellular space and thus may potentially be detected in blood. These criteria led us to select aldolase A, cyclophilin A, and annexin A2 as candidates. We did not include HSP60, neutrophil defensin1, or alpha-actinin-1, because previous reports had already suggested that these proteins might be biomarkers for CRC [2629].

Validation studies revealed that mRNA and protein expression levels of the three candidate proteins were significantly higher in the cancer region compared to non-cancer regions (Figs. 5 and 6). Moreover, to evaluate whether these proteins were useful as biomarkers, we also investigated their mRNA and protein expression levels in CRC cell lines and secretion of the proteins into the medium. Cyclophilin A was not secreted into the culture medium of all tested CRC cell lines (Fig. 7e). Thus, cyclophilin A is not suitable as a diagnostic blood tumor marker. On the other hand, annexin A2 expression in SW480 cells derived from the primary tumor site of a CRC patient was higher than expression in SW620 cells that were established from a metastatic site in the same patient (Fig. 7c–e). Decreased annexin A2 expression in cancer cells could play a role in the progression and metastasis of CRC and may be useful for predicting metastasis.

Although mRNA and protein expression of aldolase A were detected in all tested cell lines (Fig. 7a and d), aldolase A protein was not detected in the culture medium of the three CRC cell lines, while it was clearly detected in the culture medium of normal colon epithelial cells (Fig. 7e). Moreover, aldolase A was detected in normal human serum (Fig. 7f). These results suggest that secretion of aldolase A may be suppressed by dysfunction of aldolase A due to accumulated genetic mutations during the carcinogenesis process of CRC. Therefore, decreased aldolase A levels in blood may be useful as a biomarker for the early diagnosis of CRC.

Aldolase A is a glycolytic enzyme and contributes to various cellular functions related to muscle maintenance, cell shape and mobility regulation, striated muscle contraction, actin filament organization, and ATP biosynthesis [3040]. There are several reports of elevated expression of aldolase A in the serum of patients with malignant tumors, such as those with lung and renal cancer [41, 42]. However, the expression kinetics and functions of aldolase A in CRC are not well understood. To our knowledge, this is the first report of decreased secretion of aldolase A in CRC. Thus, further studies are necessary to clarify the decrease in aldolase A levels in the blood of CRC patients in order to determine if this protein can be used as an early detection biomarker for CRC.

Conclusion

In conclusion, we identified 248 proteins from FFPE CRC tissues using global shotgun proteomics. A label-free semiquantitative method based on spectral counting and GO identified 21 candidate early detection biomarkers for CRC that could potentially be detected in blood. Validation studies revealed that cyclophilin A, annexin A2, and aldolase A expression levels were significantly higher in cancer compared to non-cancer regions. In vitro studies showed that secretion of aldolase A into the culture medium was clearly suppressed in CRC cancer cells to normal colon epithelium. Finally, aldolase A may play an important role in the carcinogenesis process of CRC and may be useful as an early detection biomarker for CRC.

Acknowledgments

We thank Mr. K. Teduka and Mr. T. Fujii for technical assistance (Department of Integrated Diagnostic Pathology). This work was supported by a Grant-in-Aid for Scientific Research (C, No. 15 K09054 to T. Yamamoto) and also in part by the MEXT-Supported Program of the Strategic Research Foundation at Private Universities (2014-2018) (S1411037).

Compliance with ethical standards

Conflicts of interest

None.

References

  • 1.Kuusela P, Jalanko H, Roberts P, Sipponen P, Mecklin JP, Pitkanen R, Makela O. Comparison of CA 19-9 and carcinoembryonic antigen (CEA) levels in the serum of patients with colorectal diseases. Br J Cancer. 1984;49:135–139. doi: 10.1038/bjc.1984.25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Zamcheck N, Pusztaszeri G. CEA, AFP and other potential tumor markers. CA Cancer J Clin. 1975;25:204–214. doi: 10.3322/canjclin.25.4.204. [DOI] [PubMed] [Google Scholar]
  • 3.Shi SR, Cote RJ, Taylor CR. Antigen retrieval immunohistochemistry: past, present, and future. The journal of histochemistry and cytochemistry: official journal of the Histochemistry Society. 1997;45:327–343. doi: 10.1177/002215549704500301. [DOI] [PubMed] [Google Scholar]
  • 4.Tourtellotte WW, Verity AN, Schmid P, Martinez S, Shapshak P. Covalent binding of formalin fixed paraffin embedded brain tissue sections to glass slides suitable for in situ hybridization. J Virol Methods. 1987;15:87–99. doi: 10.1016/0166-0934(87)90052-8. [DOI] [PubMed] [Google Scholar]
  • 5.Zhao J, Wu R, Au A, Marquez A, Yu Y, Shi Z. Determination of HER2 gene amplification by chromogenic in situ hybridization (CISH) in archival breast carcinoma. Modern pathology: an official journal of the United States and Canadian Academy of Pathology, Inc. 2002;15:657–665. doi: 10.1038/modpathol.3880582. [DOI] [PubMed] [Google Scholar]
  • 6.D.A. Prieto, B.L. Hood, M.M. Darfler, T.G. Guiel, D.A. Lucas, T.P. Conrads, T.D. Veenstra, D.B. Krizman, Liquid tissue: proteomic profiling of formalin-fixed tissues. BioTechniques Suppl. 2005. 32–35. [DOI] [PubMed]
  • 7.Hood BL, Darfler MM, Guiel TG, Furusato B, Lucas DA, Ringeisen BR, Sesterhenn IA, Conrads TP, Veenstra TD, Krizman DB. Proteomic analysis of formalin-fixed prostate cancer tissue. Molecular & cellular proteomics: MCP. 2005;4:1741–1753. doi: 10.1074/mcp.M500102-MCP200. [DOI] [PubMed] [Google Scholar]
  • 8.Hood BL, Conrads TP, Veenstra TD. Unravelling the proteome of formalin-fixed paraffin-embedded tissue. Briefings in functional genomics & proteomics. 2006;5:169–175. doi: 10.1093/bfgp/ell017. [DOI] [PubMed] [Google Scholar]
  • 9.Hood BL, Conrads TP, Veenstra TD. Mass spectrometric analysis of formalin-fixed paraffin-embedded tissue: unlocking the proteome within. Proteomics. 2006;6:4106–4114. doi: 10.1002/pmic.200600016. [DOI] [PubMed] [Google Scholar]
  • 10.Guo T, Wang W, Rudnick PA, Song T, Li J, Zhuang Z, Weil RJ, DeVoe DL, Lee CS, Balgley BM. Proteome analysis of microdissected formalin-fixed and paraffin-embedded tissue specimens. The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society. 2007;55:763–772. doi: 10.1369/jhc.7A7177.2007. [DOI] [PubMed] [Google Scholar]
  • 11.Kislinger T, Cox B, Kannan A, Chung C, Hu P, Ignatchenko A, Scott MS, Gramolini AO, Morris Q, Hallett MT, Rossant J, Hughes TR, Frey B, Emili A. Global survey of organ and organelle protein expression in mouse: combined proteomic and transcriptomic profiling. Cell. 2006;125:173–186. doi: 10.1016/j.cell.2006.01.044. [DOI] [PubMed] [Google Scholar]
  • 12.Nirmalan NJ, Harnden P, Selby PJ, Banks RE. Mining the archival formalin-fixed paraffin-embedded tissue proteome: opportunities and challenges. Mol BioSyst. 2008;4:712–720. doi: 10.1039/b800098k. [DOI] [PubMed] [Google Scholar]
  • 13.Scicchitano MS, Dalmas DA, Boyce RW, Thomas HC, Frazier KS. Protein extraction of formalin-fixed, paraffin-embedded tissue enables robust proteomic profiles by mass spectrometry. The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society. 2009;57:849–860. doi: 10.1369/jhc.2009.953497. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Sprung RW, Jr, Brock JW, Tanksley JP, Li M, Washington MK, Slebos RJ, Liebler DC. Equivalence of protein inventories obtained from formalin-fixed paraffin-embedded and frozen tissue in multidimensional liquid chromatography-tandem mass spectrometry shotgun proteomic analysis. Molecular & cellular proteomics: MCP. 2009;8:1988–1998. doi: 10.1074/mcp.M800518-MCP200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Naidoo K, Jones R, Dmitrovic B, Wijesuriya N, Kocher H, Hart IR, Crnogorac-Jurcevic T. Proteome of formalin-fixed paraffin-embedded pancreatic ductal adenocarcinoma and lymph node metastases. J Pathol. 2012;226:756–763. doi: 10.1002/path.3959. [DOI] [PubMed] [Google Scholar]
  • 16.Paulo JA, Lee LS, Banks PA, Steen H, Conwell DL. Proteomic analysis of formalin-fixed paraffin-embedded pancreatic tissue using liquid chromatography tandem mass spectrometry. Pancreas. 2012;41:175–185. doi: 10.1097/MPA.0b013e318227a6b7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Jiang X, Feng S, Tian R, Ye M, Zou H. Development of efficient protein extraction methods for shotgun proteome analysis of formalin-fixed tissues. J Proteome Res. 2007;6:1038–1047. doi: 10.1021/pr0605318. [DOI] [PubMed] [Google Scholar]
  • 18.Hamilton SR, Aaltonen LA. Pathology and genetics of tumours of the digestive system. In: Kleihues P, Sobin LH, editors. World health organization classification of tumours. Lyon: IARCPress; 2000. [Google Scholar]
  • 19.Bluemlein K, Ralser M. Monitoring protein expression in whole-cell extracts by targeted label- and standard-free LC-MS/MS. Nat Protoc. 2011;6:859–869. doi: 10.1038/nprot.2011.333. [DOI] [PubMed] [Google Scholar]
  • 20.Kawamura T, Nomura M, Tojo H, Fujii K, Hamasaki H, Mikami S, Bando Y, Kato H, Nishimura T. Proteomic analysis of laser-microdissected paraffin-embedded tissues: (1) stage-related protein candidates upon non-metastatic lung adenocarcinoma. J Proteome. 2010;73:1089–1099. doi: 10.1016/j.jprot.2009.11.011. [DOI] [PubMed] [Google Scholar]
  • 21.Old WM, Meyer-Arendt K, Aveline-Wolf L, Pierce KG, Mendoza A, Sevinsky JR, Resing KA, Ahn NG. Comparison of label-free methods for quantifying human proteins by shotgun proteomics. Molecular & cellular proteomics : MCP. 2005;4:1487–1502. doi: 10.1074/mcp.M500084-MCP200. [DOI] [PubMed] [Google Scholar]
  • 22.Zybailov B, Coleman MK, Florens L, Washburn MP. Correlation of relative abundance ratios derived from peptide ion chromatograms and spectrum counting for quantitative proteomic analysis using stable isotope labeling. Anal Chem. 2005;77:6218–6224. doi: 10.1021/ac050846r. [DOI] [PubMed] [Google Scholar]
  • 23.Dennis G, Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003;4:P3. doi: 10.1186/gb-2003-4-5-p3. [DOI] [PubMed] [Google Scholar]
  • 24.da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4:44–57. doi: 10.1038/nprot.2008.211. [DOI] [PubMed] [Google Scholar]
  • 25.da Huang W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37:1–13. doi: 10.1093/nar/gkn923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Hamelin C, Cornut E, Poirier F, Pons S, Beaulieu C, Charrier JP, Haidous H, Cotte E, Lambert C, Piard F, Ataman-Onal Y, Choquet-Kastylevsky G. Identification and verification of heat shock protein 60 as a potential serum marker for colorectal cancer. The FEBS journal. 2011;278:4845–4859. doi: 10.1111/j.1742-4658.2011.08385.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.van den Broek I, Sparidans RW, Engwegen JY, Cats A, Depla AC, Schellens JH, Beijnen JH. Evaluation of human neutrophil peptide-1, -2 and -3 as serum markers for colorectal cancer. Cancer biomarkers : section A of Disease markers. 2010;7:109–115. doi: 10.3233/CBM-2010-0153. [DOI] [PubMed] [Google Scholar]
  • 28.Kemik O, Kemik AS, Sumer A, Begenik H, Purisa S, Tuzun S. Human neutrophil peptides 1, 2 and 3 (HNP 1-3): elevated serum levels in colorectal cancer and novel marker of lymphatic and hepatic metastasis. Human & experimental toxicology. 2013;32:167–171. doi: 10.1177/0960327111412802. [DOI] [PubMed] [Google Scholar]
  • 29.Thorsen K, Sorensen KD, Brems-Eskildsen AS, Modin C, Gaustadnes M, Hein AM, Kruhoffer M, Laurberg S, Borre M, Wang K, Brunak S, Krainer AR, Torring N, Dyrskjot L, Andersen CL, Orntoft TF. Alternative splicing in colon, bladder, and prostate cancer identified by exon array analysis. Molecular & cellular proteomics : MCP. 2008;7:1214–1224. doi: 10.1074/mcp.M700590-MCP200. [DOI] [PubMed] [Google Scholar]
  • 30.Kusakabe T, Motoki K, Hori K. Mode of interactions of human aldolase isozymes with cytoskeletons. Arch Biochem Biophys. 1997;344:184–193. doi: 10.1006/abbi.1997.0204. [DOI] [PubMed] [Google Scholar]
  • 31.Harris SJ, Winzor DJ. Enzyme kinetic evidence of active-site involvement in the interaction between aldolase and muscle myofibrils. Biochim Biophys Acta. 1987;911:121–126. doi: 10.1016/0167-4838(87)90279-2. [DOI] [PubMed] [Google Scholar]
  • 32.Carr D, Knull H. Aldolase-tubulin interactions: removal of tubulin C-terminals impairs interactions. Biochem Biophys Res Commun. 1993;195:289–293. doi: 10.1006/bbrc.1993.2043. [DOI] [PubMed] [Google Scholar]
  • 33.St-Jean M, Izard T, Sygusch J. A hydrophobic pocket in the active site of glycolytic aldolase mediates interactions with Wiskott-Aldrich syndrome protein. J Biol Chem. 2007;282:14309–14315. doi: 10.1074/jbc.M611505200. [DOI] [PubMed] [Google Scholar]
  • 34.Arnold H, Pette D. Binding of glycolytic enzymes to structure proteins of the muscle. European journal of biochemistry/FEBS. 1968;6:163–171. doi: 10.1111/j.1432-1033.1968.tb00434.x. [DOI] [PubMed] [Google Scholar]
  • 35.Walsh JL, Knull HR. Heteromerous interactions among glycolytic enzymes and of glycolytic enzymes with F-actin: effects of poly (ethylene glycol) Biochim Biophys Acta. 1988;952:83–91. doi: 10.1016/0167-4838(88)90104-5. [DOI] [PubMed] [Google Scholar]
  • 36.Clarke FM, Masters CJ. On the association of glycolytic enzymes with structural proteins of skeletal muscle. Biochim Biophys Acta. 1975;381:37–46. doi: 10.1016/0304-4165(75)90187-7. [DOI] [PubMed] [Google Scholar]
  • 37.Knull HR, Walsh JL. Association of glycolytic enzymes with the cytoskeleton. Curr Top Cell Regul. 1992;33:15–30. doi: 10.1016/B978-0-12-152833-1.50007-1. [DOI] [PubMed] [Google Scholar]
  • 38.Walsh JL, Keith TJ, Knull HR. Glycolytic enzyme interactions with tubulin and microtubules. Biochim Biophys Acta. 1989;999:64–70. doi: 10.1016/0167-4838(89)90031-9. [DOI] [PubMed] [Google Scholar]
  • 39.Tochio T, Tanaka H, Nakata S, Hosoya H. Fructose-1,6-bisphosphate aldolase a is involved in HaCaT cell migration by inducing lamellipodia formation. J Dermatol Sci. 2010;58:123–129. doi: 10.1016/j.jdermsci.2010.02.012. [DOI] [PubMed] [Google Scholar]
  • 40.Lu M, Holliday LS, Zhang L, Dunn WA, Jr, Gluck SL. Interaction between aldolase and vacuolar H + −ATPase: evidence for direct coupling of glycolysis to the ATP-hydrolyzing proton pump. J Biol Chem. 2001;276:30407–30413. doi: 10.1074/jbc.M008768200. [DOI] [PubMed] [Google Scholar]
  • 41.Asaka M, Kimura T, Meguro T, Kato M, Kudo M, Miyazaki T, Alpert E. Alteration of aldolase isozymes in serum and tissues of patients with cancer and other diseases. J Clin Lab Anal. 1994;8:144–148. doi: 10.1002/jcla.1860080306. [DOI] [PubMed] [Google Scholar]
  • 42.Takashi M, Zhu Y, Nakano Y, Miyake K, Kato K. Elevated levels of serum aldolase a in patients with renal cell carcinoma. Urol Res. 1992;20:307–311. doi: 10.1007/BF00300265. [DOI] [PubMed] [Google Scholar]

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