A Proteomics Based Approach for the Identification of Gastric Cancer Related Markers

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A Proteomics Based Approach for the Identification of Gastric Cancer Related Markers

Ishfaq A. Sheikh

¹

, Zeenat Mirza

¹

, Ashraf Ali

¹

, Gjumrakch Aliev

^2,3,4

and Ghulam Md Ashraf

^1,

*

1

King Fahd Medical Research Center, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia;

2

GALLY International Biomedical Research Consulting LLC., 7733 Louis Pasteur Drive, #330, San Antonio, TX, 78229, USA;

³

School of Health Science and Healthcare Administration, University of Atlanta, E. Johns Crossing,

#175, Johns Creek, GA, 30097, USA;

⁴

Institute of Physiologically Active Compounds Russian Academy of Sciences, Chernogolovka, 142432, Russia

Abstract: Gastric cancer (GC) is the amongst the most common cancer types causing second largest number of cancer related deaths globally. GC is characterized as an aggressive malignancy which is very tough to be detected at an early stage. GC has been defined as a complex, multistep process involving multiple genetic and epigenetic alterations leading to aberrant expression of key regulating factors. GC according to WHO has been defined as malignant epithelial tumors of the gastric mucosa with glandular differentiation. About one half of the GCs are located

in the lower stomach, and remaining is located in the corpus and fundus of the stomach (20%), lesser curvature (20%), cardia (10%) and greater curvature (3%). GC has been classified into intestinal and diffuse types based on epidemiological and clinico- and histo- pathological features. The etiology of GC is multifactorial and includes dietary as well as non-dietary factors. Despite a lot of research ef- forts, GC remains to be the cancer without clear symptoms at onset, poor prognosis, with metastasis and recurrence. Thus, there is an ur- gent need for identifying novel and diagnostic GC biomarkers and techniques with high sensitivity and specificity. In the present review, we provide a synopsis of proteomics based GC biomarkers discovered from various cancerous specimens such as blood, gastric fluid, tissues, cells and H. pylori infected cancer cell lines. The advent of proteomics based GC biomarkers will be a great asset for the early detection and treatment of GC.

Keywords: Gastric cancer, proteomics, blood, H. pylori, diagnosis.

INTRODUCTION

Gastric cancer (GC), also called stomach cancer, is one of the deadliest and most common cancers across the world. Currently, it is ranked second in terms of global cancer-related mortality [1, 2].

Due to advancement in various genomic and proteomic techniques, the incidence and mortality have reduced dramatically over the last 50 years in many countries. GC is the fourth most in terms of incidence, which varies among various ethnic population and regions of the world [3]. GC is considered as aggressive malignancy, which is difficult to detect at an early stage [4]. A recent assessment based on a national survey reported GC as the second most common fatal cancer in India with a mortality rate of 12.6% [5]. In India, its presence varies across different zones, with GC being is more prevalent in the southern and north-eastern states with Mizoram recording an age-adjusted rate of 50.6 and 23.3 for men and women, respectively [6, 7]. In middle east, GC occurrence varies considerably in different countries. Its occurrence is very high in Iran (around 26.1/10

⁵

), low in Israel (12.5/10

⁵

) and very low in Egypt (3.4/10

⁵

) [8]. Among GCC, GC has been reported to be higher in Oman than in all other nations (Bahrain, Kuwait, Qatar, Saudi Arabia, and UAE) [9]. The literature evidences of GC in Saudi Arabia is still in nascent stage with some reports from regions of western [10] and southern Saudi Arabia [11].

The development of GC is a complex, multistep process which involves several parameters. Involvement of various genetic and epigenetic factors, such as activation and alteration of oncogenes, tumor suppressor genes, DNA repair genes, cell cycle regulators, and signaling molecules leads to aberrant expression of key factors regulating cell cycle progression, apoptosis, senescence, and

*

Address correspondence to this author at the King Fahd Medical Research Center, King Abdulaziz University, P. O. Box 80216, Jeddah 21589, Saudi Arabia; Tel: +966593594931; E-mail: [email protected]

[email protected]

differentiation [12]. WHO has defined GC as “malignant epithelial tumors of the gastric mucosa with glandular differentiation” [13].

Uncontrolled growth in the lining of stomach can lead to incidence of gastric tumors, which can later invade adjoining normal tissues and can further spread to other parts of the body to cause cancer.[14]. Overall 50% of the GCs are located in the lower part of stomach (pyloris and antrum), 20% are located in the corpus and fundus (body) of the stomach, 20% are in the part of lesser curvature, 10% at the cardia and 3% at the greater curvature [15].

Accumulating evidence has confirmed the role of H. pylori infection in the pathogenesis of GC besides other factors. H. pylori causes chronic gastritis, the precursor to all the pathophysiological abnormal characteristic of gastric carcinogenesis [16, 17]. Antican- cer research has proclaimed many novel target molecules and techniques [18-21]. However, these precursor lesions only develop in a proportion of infected subjects, and do not necessarily progress into invasive cancers. GC is a cancer without clear symptoms at onset, poor prognosis, and metastasis and recurrence [22, 23]. Early diagnosis of GC urgently requires novel biomarkers and techniques with high sensitivity and specificity.

PATHOLOGICAL CLASSIFICATION OF GC

Based on epidemiological, clinical and histo-pathological features GC can be classified into intestinal and diffuse types [24, 25].

The intestinal type of GC display components of glandular, solid or intestinal architecture as well as tubular structures [26]. In contrast to intestinal variant, diffuse variant displays single cells or poorly cohesive cluster of cells that infiltrate the gastric wall, often leading to widespread thickening and rigidity of the gastric wall, known as linitus plastica [27]. Histologically, intestinal-type is well differen- tiated while diffuse-type is poorly differentiated. Intestinal-type occurs more commonly in older patients, while diffuse-type is more prevalent in younger patients [28]. Diffuse-type is not well differen- tiated with infiltrating, non-cohesive cells and occurs mostly in

Ghulam Md Ashraf

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younger patients [29]. Adenocarcinoma, which accounts for 90% to 95% of all gastric malignancies, is the major histological type of GC [28]. The method used to predict prognosis and direct therapeu- tic decisions of patients with GC across the world is considered as TNM (Tumor Node Metastasis) staging system [30].

ETIOLOGY OF GC

There are several factors, dietary and non-dietary, which con- tribute in the etiology of GC [6]. Factors such as H. pylori infection, increase in obesity, certain dietary factors, such as higher intake of salty foods and smoked meats, consumption of food preserved with nitrites or nitrates, smoking and alcohol abuse is responsible for intestinal-type of GC. It is believed to arise through a long term multistep progression from chronic gastritis to chronic atrophy to intestinal metaplasia to dysplasia [6]. The diffuse-type of GC is more likely to have a genetic cause. The primary genetic etiology, known as hereditary diffuse GC (HDGC), is mainly due to the E- cadherin (CDH1) germline mutation [26, 31]. Studies of GC during last few decades have shown that the etiolology results from the complex interactions between gene and environment [32, 33]. New high-throughput techniques, such as NGS, have revealed its hetero- geneous milieu, such as alterations of many genes, deregulation of signaling pathways, aberrant DNA methylation patterns, and chro- mosomal imbalances [29]. Although there is vast advancement in diagnosis and treatment, the survival rate of GC in five years has been found to be only 20 per cent [6, 34].

GC BIOMARKERS

In order to improve the understanding and behavior of GC and to diagnose it early, a lot of work has been done to search tumor biomarkers. The aim is to improve cure rates by early detection and diagnosis of such tumors. The biomarkers are defined as biological variables that correlate well with clinico-biological outcome. The current cancer biomarker discovery targets are abnormally expressed proteins, and now they are becoming increasingly popular [35]. Carcino-embryonic antigen, CA 19-9, CA 50 and CA 72-4 are presently used biomarkers, but, the sensitivity and specificity of these biomarkers are not sufficient to detect early stage GT. The disadvantages of these biomarkers are that their specificity is not strong and they have low positive rate [36]. To enhance the diagnostic sensitivity and specificity, few studies have simultaneously evaluated more than one candidate biomarker, leading to the belief that no single biomarker is likely to prove complete prediction [37, 38]. Discovered markers may also define a subset of networked causal proteins that regulate disease phenotype [39]. Regardless of the method and protocol and data's quality, it is possible that some discovered biomarkers may behave as false positives. Therefore, it is must to validate identified biomarkers against definitive biomedical ground to make them more authentic. Validation of biomarker can be executed by number of ways. They can be validated on bench-side in traditional labs, and web based electronic resources such as text-mining, gene ontology, and clinical trials [40].

Advancement in genomics and proteomics technologies have revolutionized the biomarker discovery. Several recent studies re- veal that genomics and proteomics are powerful tools for tumor identification and classification. Identification of genes or proteins expressed in different cancers may serve as predictive, diagnostic, or prognostic biomarkers [41, 42]. Overall, molecular phenotyping of GC is still in its infancy and the search for novel diagnostic, prognostic and predictive biomarkers continues [43]. Identifying single discriminating biomarker (e.g. COX-2, c-myc, p27 or p53) cannot have a major impact, as a single biomarker is likely insuffi- cient for confirmed diagnosis or for making clinical decisions. Dis- covery of miRNA has provided landmark in cancer research.

Analysis of cancer tissues has revealed the importance of miRNAs as molecular markers for cancer classification, prognosis, and drug- response prediction. As a circulating markers, miRNAs can help in

early diagnosis and follow-up investigations in cancer biomarker discovery [44]. Thanks to high stability and the availability of assays able to quantify their level, miRNAs could be added to the panel of potential biomarkers [45, 46]. Cancer cells act cleverly as they employ multiple and diverse survival pathways, so there is need to define a battery of biomarkers (complex signatures that define multiple outcomes) which can identify those abrupted signaling pathways [47]. Such signatures (battery of biomarkers) may more appropriately represent the breadth of molecular diversity inherent in different cancers. They can pave the pathway to under- stand the impact of both nature and nurture on the molecular genetics of gastric carcinogenesis. In the coming era of personalized medicine, genomic and proteomic profiling attempts for mining novel biomarkers of GC may provide significant basis for individu- alized treatment to cancer patients.

PROTEOMICS BASED GC BIOMARKERS

According to report produced by WHO in 2008 around 7.6 million people across world die of cancer each year, and it is as- sumed that by 2030, the deaths from cancer will rise to more than 11 million [48, 49]. Based on 2008-2012 data, the number of GC cases increased to 7.4 per 100,000 men and women per year and the number of deaths being 3.4 per 100,000 men and women per year [50]. Consumption of nitrate- or nitrite-rich food (grilled and baked food, salted, or pickled foods) are some of the major well known GC causing factors [51]. Presence of H. pylori infection [52], age (>60 years), a history of earlier stomach disorders [53] are the other causative factors. Proteomics based biomarkers can help in the accurate diagnosis and distinction of GC patients from healthy individuals or patients without GC [54, 55]. Several advanced proteomics techniques are used to identify potential target proteins that can act as novel GC biomarkers. Various proteomics techniques such as 2-DE, Gel Electrophoresis, SDS PAGE, iTRAQ, ICAT, Protein Chip array, hydrophilic interaction liquid chromatography (HILIC), LC-MS, GC-MS, HPLC, affinity chromatography and 2- D LC etc were used for identification of cancer biomarkers [56].

The identity of the separated proteins is then confirmed by Mass Spectrometry techniques [57]. Other latest techniques like western blotting and immunohistochemistry (IHC), is used to validate such isolated compounds [58]. Our previous publications have estab- lished galectins as an important proteomics based GC biomarkers with significant changes in their expression during malignancies including GC [59-66]. In the present review, we have tried to ex- plore the recent progress made in biomarker discovery for Gastric Cancer. We have tried to give idea of various proteomics tools used in biomarker discovery. Our aim is to provide a useful guide that predicts the future direction of the advancement of proteomic tech- nology in cancer biomarker discovery.

SPECIMENS USED FOR IDENTIFICATION OF GC BIO- MARKERS

Cancerous Blood Samples

As blood is an easily accessible and easy-to-use clinical speci-

men for most diseases, it is also used for identification of GC bio-

marker. Due to easy accessibility compared to tissue and gastric

fluid, it can be used as useful source for discovering a highly effec-

tive screening biomarker for GC. The prime objective of proteomic

researchers is to identify blood based GC biomarkers using several

advanced proteome technologies. [67]. For initial and advanced

stage analysis of serum ES-MS, MALDI-TOF MS, GC MS and 2-

DE techniques are utilized [68], besides using other sophisticated

techniques like iTRAQ and liquid chromatography techniques (LC-

MS/MS) for plasma analysis at different stages of gastric cancers

[69]. The identified expected biomarkers were compared with se-

rum protein profiles of other types of cancer, to check its specificity

in gastric carcinogenesis. Their cross reactivity with other known

biomarkers were also checked [70, 71]. MKN45 and SC-M1 mouse

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xenograft models have been used to check the progression of Gas- tric Carcinogenesis by analyzing their protein profiling [69, 72].

Several proteomics approaches like SELDI-TOF-MS, Protein Chip array HPLC-ESI-MS, hydrophilic interaction liquid chromatogra-

phy (HILIC), and 2-D LC (LC-MS) etc has been combined for the

search of future biomarkers with high sensitivity and high specificity [73-77]. All potential blood based biomarkers identified by different proteomics technologies for gastric carcinogenesis can be categorized into future diagnostic biomarker [78]. Some of the probable GC biomarkers obtained by proteomics technology are,

apolipoprotein C-I (apoC-I) and apoC-III [77], thrombin light chain

A [79], and three protein masses with 1468, 3935, and 7560m/z [74]. These potential blood based biomarkers have high sensitivity (>89.9%) and high specificity (>71%). Other biomarkers have lesser specificity such as MIF [80] and a 2209-Da peptide [81], can also be considered as future blood biomarkers for GC (>28% sensitivity and >83.3% specificity). C9 [69] (sensitivity: 90%; specificity: 74%) and IPO-38 [70] (sensitivity: 56.7%; specificity: 93.3%) are additional biomarkers specific for different stages of Gastric Carcinogenesis. Thus, above findings show that blood and serum based biomarkers isolated through different proteomics approaches can be successfully applied to biomarker based drug discovery, using latest diagnostic tools having bigger clinical sample size.

Table 1 shows potential GC biomarkers identified from cancerous blood specimens.

Cancerous Gastric Fluid Specimens

Gastric fluid, which help in food digestion, and provide protec- tion against different infections, can also be used for biomarker discovery particularly in gastric carcinogenesis [82]. Several proteomics techniques like Mass Spectrometry (ESI-MS, GC-MS, LC- MS) has been used to separate proteins from gastric fluid [83].

Some interesting results were observed when data from gastric fluid is compared with healthy individual. Patients with gastric ulcers and GC have higher protein concentrations in their gastric juice compared to healthy individuals, but their concentration is lower in patients with duodenal ulcers, than those in healthy individuals [84]. Some of the important GC markers discovered from gastric juice are pepsin-related proteins such as pepsinogen C [83], pepsin

A [83], 1-antitrypsin [84], and pepsinogen II [85], which have been found altered in GC. It can be interpreted that the activation of proteolytic enzymes in gastric juice can have significant implication in GC. Table 2 shows potential GC biomarkers identified from cancerous gastric fluid specimens.

Cancerous Tissue Specimens

Tissue biopsies are major specimen to confirm cases of different carcinogenesis. Patients with suspected tumors go to surgery, so paired tissues of gastric tumors and surrounding noncancerous gastric mucosa obtained after surgical resection are main source of GC confirmation. These samples are usually analyzed by 2-DE combined with MALDI-TOF [80, 86], besides other proteomic techniques such as ProteinChip arrays [87] and SELDI-TOF-MS [88].

These profiling helps to differentiate tumor from normal tissues or early stages from advanced stages of GC. The primary goal of tissue profiling by different proteomics techniques is to discover useful therapeutic targets against such diseases. In previous studies, it was observed that expected tissue biomarkers are over expressed in tumor tissues and it is easier to detect individuals with GC from healthy individuals. The biomarkers discovered from tissue specimen include HER2 (sensitivity: 65%; specificity: 92%) [86], human neutrophil peptides 1–3 (HNPs 1–3), and MIF (P<0.05) [89].

Among them HER2 has been found to be associated with gastric as well as breast cancers [90] and obvious therapeutic target in both cases. The result provides possibility of proteomics technology in identification of such markers which can potentially applied to identification of another cancer. It can check whether known biomarkers in one type of cancer can acts as novel biomarkers for other types of cancers. The expression profiling of proteomics biomarkers like, chloride intracellular channel 1 (CLIC1; low expression correlated with a high 5-year survival rate) [91] in combination with a patient's survival rate and IHC assay results may have a high prognostic value. In brief, the application of different proteomic tools can help in identification and verification of different biomarkers which can provide more robust clinical evaluation of patients with GC. Table 3 shows potential GC biomarkers identified from cancerous tissue specimens.

Table 1. Potential GC biomarkers identified from cancerous blood specimens.

Potential Biomarker Detection Method Verification Method Expression Level References

CF1 2-DE, MALDI-TOF-MS Western blot Down [97]

C9 iTRAQ LC-MS/MS Western blot Up [69]

IPO-38 Antibody microarray ELISA Up [70]

ITIH3 iTRAQ Western blot Up [69]

SLeX HILIC, off-line 2-D LC 2-DE, 2-D DIGE Up [76]

ApoC-I and ApoC-III C8-reverse phase LC-MS/MS ELISA Down [77]

FPA Serum pretreatment with C8 magnetic beads, MALDI-TOF-MS

ELISA Unclear [98]

Thrombin light chain A SELDI-TOF-MS Immunoprecipitation Down [79]

MIF ELISA - Up [80]

a 2209-Da peptide MALDI-TOF-MS Western blot Unclear [81]

Peaks at 1468, 3935, and 7560 m/z

SELDI-TOF-MS, ProteinChip arrays

- Unclear [74]

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Cancerous Cells/Cell Line Specimens

Various proteomics and transcriptomics strategy has been applied to discover the molecular details of diseases. Altered protein expression in cell-cell interactions, cell-extracellular matrix adhe- sion, cell motility, proliferation, and tumor immunity, have been explored to solve the puzzle of different cancers [92]. Among them

MET (an oncogene) is found to be involved in the growth and survival of gastric tumor cells [93, 94]. Other proteins such as Vimentin and galectin 1 found in metastatic cells [92] and - enolase (ENO1) in GKN 1-overexpressing cells [95]. These molecules can be used as therapeutic targets for GC detection Table 2. Potential GC biomarkers identified from cancerous gastric fluid specimens.

Potential Biomarkers Detection Method Verification Method References

PGC, pepsin A, -defensin ProteinChip arrays, SELDI-TOF-MS ELISA [83]

1-antitrypsin precursor 2-DE MALDI-TOFMS [84]

GKN1, trefoil factor 1, 1-antitryspin, pepsinogen II 2-DE, MALDI LC-MS/MS Western blot [85]

Table 3. Potential GC biomarkers identified from cancerous tissue specimens.

Potential Biomarkers Detection Method Verification Method Expression Level References

Selenium-binding protein 1 2-DE, MALDI-TOF-MS RT-PCR, Western blot, IHC Down [80]

ENO1, GRP78, GRP94, PPIA, PRDX1, PTEN

2-DE, MALDI-TOF-MS Western blot, IHC Down [12]

MAWD-binding protein 2-DE, MALDI-TOF-MS Western blot, Real-Time PCR Down [99]

MAD1L1, HSP27, CYR61 2-DE, MALDI-TOF-MS, YR61 IHC Unclear [100]

CLIC1 2-DE, MALDI-TOF-MS Real-Time PCR, Western blot Up [91]

Cathepsin B 2-DE, MALDI-TOF-MS Western blot, IHC Up [79]

AMP-18 2-DE, MALDI-TOF-MS 2-D Immunoblots Unclear [101]

HSP27 2-DE, MALDI-TOF-MS IHC Up [102]

ATP-dependent RNA helicase DDX39

2-D DIGE, LC-MS/MS Western blot, IHC Unclear [103]

LDHA 2-DE, GC-TOF-MS Real-Time PCR, Western blot Down [88]

PDHB 2-DE, GC-TOF-MS Real-Time PCR, Western blot Up [88]

T3, HIF and fumarate 2-DE, ESI-Q-TOF-MS/MS RT-PCR, Western blot Unclear [104]

CRIP1, HNP-1, S100A6 MALDI imaging MS IHC Unclear [86]

-defensin-1, -defensin-2, S100A8, S100A9

MALDI-TOF-MS HPLC, LC-MS/MS Unclear [88]

PGC ProteinChip arrays, SELDI-TOF-MS IHC Down [87]

HNPs 1–3 and macrophage migration inhibitory factor

ProteinChip arrays, SELDI-TOF-MS LC-MS/MS, IHC Up [89]

Galectin-2 ICAT, LC-MS IHC Unclear [98]

Apo-A1 iTRAQ LC-MS Western blot Down [69]

S100P NanoLC-MS IHC Down [105]

Laminin gamma 2 chain monomer IHC 2-D Immunoblots Up [106]

HER2 IHC, Fluorescence in situ hybridization Imaging mass spectrometry Up [86]

Glycolipid TLC immunostaining GC-MS Down [107]

GM2 TLC immunostaining GC-MS Up [107]

Galectin-2 ICAT, LC-MS Western blot, IHC Down [108]

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Table 4. Potential GC biomarkers identified from cancerous cells/cell line specimens.

Cell Line Potential Biomarker Detection Verification Method Expression Level References MkN-1, MkN-

45,KATOIII

GRP78 2-DE, MALDI-TOF/TOF- MS, Western blot, Im-

munoreactions

IHC Unclear [71]

SC-M1, TMC-1 Vimentin, galectin 1 2-D LC-MS/MS, cICAT, Microarray

Western blot, semi- quantitative RT-PCR

Unclear [92]

SNU5 Mitochondrial MET iTRAQ-MS/MS (MET inhibitor treatment)

Western blot Up [109]

GTL16 IL-8, GRO, uPAR, IL-6

Protein arrays (MET inhibitor treatment)

ELISA Unclear [110]

SGC ENO1 2-DE, MALDI-TOF-MS Western blot, Flow cytometry Down [95]

MKN7, MKN45, HFE145

CTSS iTRAQ-MS/MS IHC, Tissue microarray Up [111]

SNU5, SNU1, AGS, YCC1, KatoIII

phospho-p53 LC-MS/MS Protein antibody array Unclear [109]

SGC7901 15-PGDH 2-DE, Western Blot Unclear [104]

SC-M1 14-3-3 MALDI-TOF-MS IHC Up [112]

SGC and tissues 14-3-3 2-DE Western blot up [113]

RGM-1, AGS Ubiquinol-cytochrome c reductase, mitochondrial

short-chain enoyl- coenzyme A hydratase-

1, HSP60 and EF-Tu

MALDI-TOF-TOF (5-FU treatment) 2-DE, LC-

MS/MS 2-DE

ELISA Western blot

Up [114]

GES-1, SGC7901 Sorcin iTRAQ IHC Up [115]

Table 5. Potential GC biomarkers identified from H. pylori-infected cancerous specimens

1 Potential Biomarker Detection Method Verification Method References

Serum, H. pylori GroES 2-D Immunoblots, Nano LC- MS/MS

Serologic study [96]

Serum, H. pylori 17 antigens 2-D Immunoblots No [116]

Serum, H. pylori 30 antigens 2-D Immunoblots, MALDI-TOF- MS

No [117]

Cells Annexin A2 ProteinChips, SELDI-TOF-MS Western Blot [118]

Cells Serine arginine-rich (SR) proteins (regulation of alternative splicing)

SILAC, phosphoprotein enrich- ment, 2-DE, MALDI TOF/TOF-

MS

No [119]

Cells 140 transcripts, 190 protein species 2-DE, MALDI-TOF-MS, cDNA expression array

No [120]

Tissue Annexin A4 2-DE, MALDI-TOF-MS Western blot [121]

H. pylori antioxidant protein group (SodB, KatA, AphC/TsaA, TrxA, Pfr), tricarboxylic

acid cycle proteins (Idh, FrdA, FrdB, FldA, AcnB) and heat shock proteins

(GroEL and ClpB)

2-D DIGE, MALDI-TOF-MS Real-time PCR, DNA microarray

[122]

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and treatment. However, for these identified predictive cell bio- markers to be used in clinical settings, rigorous in vivo evaluation of these markers in clinical specimens is necessary. Table 4 shows potential GC biomarkers identified from cancerous cells/cell line specimens.

H. pylori-Infected Cancerous Specimens

Chronic infection with H. pylori is considered a high risk for GC development [52]. For detecting H. pylori-related target pro- teins, H. pylori-infected specimens and H. pylori strains isolated from patients have been used as a source to establish an H. pylori- associated proteomic profile. GroES is considered as H. pylori spe- cific antigen for GC identified by immunoproteomics [96]. Com- parative immunoproteomics can be effective clinical diagnostic tools for H. pylori-infected GC patients. Table 5 shows potential GC biomarkers identified from H. pylori-infected cancerous speci- mens.

CONCLUSION

GC remains to be one of the leading causes of mortality worldwide. Hence due to the high toll of deaths occurring every year, there has always been a compelling need and quest for exploring new ways of diagnosis and treatment. Present work is an attempt to provide an in depth information in an easy and understandable lan- guage about the GC. Although advancements in proteomic research contributed a lot in identifying novel biomarkers for GC diagnosis, but mining miRNAs as biomarkers has been the area of focus in present time. Diagnosing GC using single biomarker does not seem to be sufficient. Although, so far individually large number of biomarkers have been reported, but defining the set of biomarkers could be quite useful in diagnosis and prediction. This review article gives the full coverage of biomarkers from different sources and assays used for their diagnosis and could be quite useful for clini- cians. This would be helpful in bridging the gap between theoretical knowledge and the experimental assays used in prediction and diagnosis of GC.

CONFLICTS OF INTEREST

The authors confirm that this article content has no conflict of interest.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the research facilities provided by King Fahd Medical Research Center, King Abdulaziz University, Jeddah, Saudi Arabia.

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A Proteomics Based Approach for the Identification of Gastric Cancer Related Markers

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