Download Proteomic analysis of expressed differentially proteins involved in

Proteomic analysis of expressed differentially proteins involved in human
colorectal cancer、adenoma and normal colonic mucosa
Lei Hi, MD, Tao Deng, MD, Shi-Yun Tan, MD
Address correspondence and reprint request to: Dr. Lei He, Department of
Gastroenterology, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan
430060, P.R.China. Tel. +86(27)88041911. Fax. +86(27)88042292.
E-mail: [email protected]
ABSTRACT
Objectives: To study the differentially expressed proteins in colorectal carcinoma
tissues, colorectal adenoma tissues and the normal colonic mucosa by proteomics
techniques.
Methods: Tissue samples from colorectal carcinoma patients、colorectal adenoma
patients and healthy controls were analyzed by SELDI-TOF-MS using WCX
magnetic beads(MB-WCX). The resulting SELDI-TOF-MS spectral data were
analyzed using the Biomarker WizardTM to find differential proteins. The differential
proteins were identified by searching the Swiss-Prot and TrEMBL.
Results: A total of 16 mass peaks were identified. The levels of five peaks at mass:
charge ratios(m/z) of 4904、7602、7705、14990 and 15708 were significantly higher
in the patients with colorectal carcinoma than that in patients with colorectal adenoma
and healthy controls(P﹤0.01); Compared with healthy controls, the level of peaks at
mass: charge ratios(m/z) of 4904 in patients with colorectal adenoma was statistically
significant, while the others were not(P﹥0.05). Database search revealed that the five
peaks corresponded to Carcinoembryonic antigen (CEA), p53R2, HCG2020031,
Kallikrein-11 (hk11) and CD99 respectively. As we know, CEA is a commonly used
tumor marker in clinic. Other four kinds of differential proteins might have the
potential as a new tumor marker.
Conclusion: Proteomic analysis can identify the proteins with variance among
colorectal carcinoma, colorectal adenoma tissues and normal colonic mucosa as well
as providing probable new biomarkers correlated with biological behavior of
colorectal carcinoma.
Colorectal cancer is a very common malignant tumor in China, the morbidity and
mortality has increased gradually in recent years (1, 2). Colorectal carcinogenesis is a
well-known multistep process. Colorectal adenoma is now recognized as the most
important precancerous lesion, and the carcinogenic process often need 10 to 15 years,
if the main premalignant lesion-adenoma is detected and removed before invasion
occurs, colorectal cancer might be effectively controlled (3, 4).
To make progress in cancer biology, it is important to explore the differential
protein expression pattern between tumor and paired normal tissue. Such proteomic
study not only contributes to elucidating the underlying molecular carcinogenesis but
also provides a robust tool to identify novel biomarkers in cancer. Traditional
proteomics is based on two-dimensional gel electrophoresis (2D-PAGE) and mass
spectrometry as the representative technology roadmap. Because of the complicated
detection process, large samples and low lever of distinguish small molecular protein,
the application of which is limited (5, 6). However, SELDI-TOF-MS technology, also
known as protein fingerprint technology, can make up above disadvantages, it does
not need dissolve and stain, high sensitivity, and not limited by protein solubility and
Ph value (7, 8), so which is widely used in proteomics research gradually.
In this study, we used SELDI-TOF-MS technology to screen different proteins
among tissues of colorectal cancer, adenoma and normal colorectal mucosa, in order
to search new targeting markers for diagnosis and therapy of colorectal cancer.
Materials and Methods. Tissue Samples. We collected 21 colorectal cancers patients,
which were surgical resection and diagnosed by pathologic manifestations at the
general surgery department of Renmin Hospital of Wuhan University between March
2011 and December 2012. There were 13 males and 8 females, age from 51 to 78,
median age was 64. None had received preoperative radiochemotherapy. According to
the TNM classification, stage Ⅰ-Ⅱ were 16 cases, Ⅲ and Ⅳ were 5 cases.
Normal colorectal mucosa was taken from adjacent tissue (at least 10 cm) as control
group. Colorectal adenoma tissues were endoscopic resected and diagnosed by
histopathology from the digestive endoscopy center of Renmin Hospital of Wuhan
University. There were 17 samples (14 males and 3 females, age from 25 to 72,
median age was 41.7) in this study. All samples were kept at -80℃. The present study
was approved by the Ethics Committee of Wuhan University. Consent was received
from all patients and all clinical investigations were performed according to the
principles of the Declaration of Helsinki.
Reagent. Carbamide, acetonitrile, Tris-HCL, CHAPS, DTT, NaAc, HPLC H2O,
and sinapinic acid (SPA) were obtained from Sigma; MB-WCX was obtained from
Beijing Biock Bio-Technology Co., Ltd; Protein Chip Biomarker SystemⅡc (PBS-Ⅱ
c) mass spectrometry was purchased from Ciphergen; BCA protein assay kit was
purchased from Beyotime institute of biotechnology.
Process of samples. Taken 50 mg tissue of each sample to grind to powder under
liquid nitrogen, then added 400 µl lysate and mixed, hatched 1h at 37 centigrade,
centrifugalized (14000 r/min) 3 min at 4 centigrade, draw supernatant which was total
protein (9), then used BCA protein assay kit to detect the concentration of protein.
Magnetic beads and Elution. Add 100 µl handled samples into centrifuge tube
which had installed MB-WCX, hatched 30 min in magnetic beads processor, then
remove the liquid. Add 100 µl MB binding buffer (50 mmol/L NaAc, Ph 4.0~4.3) into
centrifuge tube with installed MB-WCX, hatched 2 min in magnetic beads processor,
remove the liquid, repeat twice. 10µl 5% TFA eluant was added, after 2 min, draw 5µl
supernate into another centrifuge tube, and then 5 µL SPA saturated solution was
added and mixed well, draw 1µl mixed solution on Au chip, then detected when it’s
dry (10).
Data collection. Magnetic beads which had handled above were implanted into
protein fingerprint apparatus (type PBS-Ⅱc) to proteome analysis. Before reading
data, we use NP20 chip with all-in-one protein marker to revise protein fingerprint
apparatus to make sure molecular weight error < 0.1%. Setting main parameters as
follows: strength of laser 150, sensitivity 8, molecular weight range 1500~20000Da.
Range of data acquisition 20~80, collection point 100. Setting program of film
reading with Ciphergen ProteinChip 3.2, computer can map up protein mass spectrum
according to primary data accurately. Y-axis was intensity of peaks (the relative
contents of protein) and X-axis was mass-to-charge ratio (M/Z) (the relative
molecular weight of protein).
Mass-to-charge ratio of protein. Protein combined SPA was ionized by laser in
SELDI-TOF-MS helium-neon laser lasers. In the action of accelerating field, the
flight time of different mass-to-charge ratio of protein was different in vacuum tube,
the mass-to-charge ratio of protein is in proportion to the square of ions of the time of
flight. E=UZ=1/2mv2 and t=L/A can deduce M/Z=Kt2=(2U/L2)×t2. Z represents
number of ionic charge, U represents voltage, V as flight time, L as accelerated flight
of electric field voltage, K as constant.
Relative molecular weight. The protein ion beam with positive charge arrive at
the detector, electron multiplier will generate transient current, which are conversed
into the relative molecular weight of protein.
Repeatability test. Repeat 8 spot test in same sample at same time and select 3
peaks randomly, calculating the coefficient of variation of peak, if coefficient of
variation< 10%, indicates protein pattern has well repeatability.
Statistical analysis. All data were presented as the mean±SD. Results from
Biomarker Wizard (Ciphergen) were analyzed by SPSS version 17.0 (SPSS, Inc.,
Chicago, IL, USA) and one-way ANOVA (multiple comparisons) and t-tests (two
groups comparisons) were performed accordingly. P﹤0.05 was considered to indicate
a statistically significant difference.
Results. Screening differential protein. All magnetic beads were read on
SELDI-TOF-MS (type PBS- Ⅱ c), the results showed that the peak pattern of
mass-to-charge ratio was distinctly different among tissue of colorectal carcinoma,
adenoma and normal colorectal mucosa. We screen 16 differential proteins by
Biomarker Wizard. M/Z of 3398 and 9187 expressed higher in normal colorectal
mucosa, and other 14 differential proteins low expressed compared with tissue of
colorectal cancer. Compared with the normal colorectal mucosa, the expression is
higher at 4904 in colorectal adenoma. In addition, the protein peak intensity at M/Z of
4904, 7602, 7705, 14990 and 15708 in colorectal cancer is significantly higher than
colorectal adenoma and normal colorectal mucosa (Table 1).
Table 1- Differential expressed proteins among colorectal cancer、adenoma and
normal colonic mucosa.
Control
Colorectal adenoma
Colorectal cancer
M/Z
P value
Mean SD
Mean
SD
Mean
SD
3398
11.92 0.01
4.86
0.02
1.54
0.06
0.004
3576
3.44
0.07
0.82
0.01
23.79
0.05
0.009
3973
4.62
0.05
1.9
0.03
32.72
0.01
0.004
4904
0.46
0.03
5.04
0.03
25.31
0.02
0.008
5126
4.07
0.04
4.37
0.06
12.32
0.09
0.007
5498
0.27
0.04
0.93
0.07
11.21
0.06
0.005
7602
13.42 0.01
19.4
0.02
49.18
0.07
0.005
7705
3.33
0.06
3.95
0.04
9.89
0.03
0.006
7969
8.12
0.05
6.33
0.05
19.56
0.03
0.004
9514
0.27
0.09
0.75
0.01
5.45
0.05
0.003
9187
12.64 0.01
5.87
0.03
4.31
0.04
0.007
10075
3.24
0.02
2.45
0.03
9.702
0.02
0.008
10808
0.79
0.02
2.25
0.05
22.55
0.01
0.003
14990
16.09 0.04
23.26
0.02
61.02
0.05
0.002
15181
5.34
0.03
6.31
0.04
19.52
0.07
0.001
15708
7.96
0.05
8.74
0.03
23.28
0.01
0.001
Database retrieval. Input peak mass-to-charge ratios of 16 marked differential
proteins to protein data banks (http://web.expasy.org/tagident), retrieval conditions:
OS/OC/OX: homo sapiens, eukaryote, 9606; error range of M/Z <0.01; database
selection: Swiss-Prot and TrEMBL. Finally, we retrieve 5 proteins which may be
related to peak mass-to-charge ratios, the M/Z is 4904, 7602, 7705, 14990 and 15708,
respectively, and the corresponding proteins were CEA, p53R2, HCG2020031,
Kallikrein-11(hk11) and CD99 (Table 2, Fig.1).
Table 2- Five different proteins information based on database retrieval.
M/Z
4904
7602
7705
14990
15708
Swiss-Prot/TrEMBL ID
Q14081
Q7LG56
Q8WYR6
Q9UBX7
Q8TCZ2
Gene names
Protein names
Carcinoembryonic antigen(CEA)
P53R2
p53R2
hcG_2020031 HCG2020031
KLK11
Kallikrein-11（hk11）
CD99L2
CD99
Figure 1- Retrieved protein profiles of the five different proteins.
Discussion. Colorectal cancer is one common digestive cancer, In the process of
development, invasion and metastasis, the mutation, abnormal transcription and
translation can lead to abnormal protein expression. Proteomics has become a new
channel to research pathogenesis, early diagnosis, treatment and prognosis of
colorectal cancer (11). Gao et al had screened out multiple abnormal expressed
protein in the local lymphatic metastasis of colorectal cancer using SELDI-TOF-MS
technology, and preliminary build classification tree model, which can identify
whether local lymphatic metastasis or not in colorectal cancer patients (12).
In this study, we detected 16 differential proteins, 14 of which express highly in
tissue of colorectal cancer, the mass-to-charge ratios were 3576, 3973, 4904, 5126,
5498, 7602, 7705, 7969, 9514, 10075, 10808, 14990, 15181 and 15708. On the
contrary, at mass-to-charge ratio of 3398 and 9187, the mass peak of which high
expresses in normal tissue of colorectal mucosa and low in tissue of colorectal
carcinoma and adenoma. Most differential proteins modest lever express in tissue of
colorectal adenoma, it indicate that differential proteins may play an important role in
carcinogenic process.
Swiss-Prot and TrEMBL databases are the most universal protein sequence
databases. In this study, we detected 5 proteins that might relate to the development
and progression of colorectal cancer through the expert protein analysis system
(ExPASy). Mass-to-charge ratio of 4904 is CEA, a common tumor marker in
colorectal carcinoma. M/Z of 15708 is CD99, one cellular adhesion molecule, which
participates in cell adhesion, apoptosis, cell invasion and metastasis and plays an
important role in tumor generation (13). It reported that CD99 express anomaly in
various cancers, such as gastric cancer, glioma (14) and small cell lung cancer (15),
but it does not reported in colorectal carcinoma. Yamada et al found 3 tumor antigen
genes, which encoded products HCG2020031 express highly in HLA-24+ lung cancer
patients, indicated that HCG2020031 is a candidate protein of cancer vaccine (16).
We also found HCG2020031 expressed in colorectal carcinoma, but not significant.
Yu et al discovered the expression of hk11 is higher than control group in 126 rectal
cancer patients (17). It inferred that hk11 can be as a prognosis biomarker of low
rectal cancer. Similarly, in this study, the hk11 expressed higher in tissue of colorectal
carcinoma than colorectal adenoma or normal colorectal mucosa. In addition, p53R2
is a subtribe of human ribonucleotide reductase (RR). It plays an important role in
DNA repair, mtDNA synthesis, protecting against oxidative and so on (18). Liu et al
(19, 20) discovered that p53R2 expressed high in tissue of colorectal carcinoma and
inhibition cell invasion, it has be association with prognosis of the patients with
colorectal cancer, in this study, the result is in line with the above report, which
further validated our speculation.
Proteomic technology provides an effective method to study tumor-related
proteins. This study screens 5 potential proteins in relation to colorectal cancer
through proteomic fingerprint and database retrieval. Except CEA, the other 4
proteins may be act a new targeting marker for diagnosis and therapy of colorectal
cancer.
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