Advances in Pancreatic Cancer Detection

ADVANCES IN CLINICAL CHEMISTRY, VOL. 51

ADVANCES IN PANCREATIC CANCER DETECTION Cristiana Pistol Tanase,* Monica Neagu,* Radu Albulescu,*,† and Mihail Eugen Hinescu*,‡ *‘Victor Babes’ National Institute of Pathology, Splaiul Independentei, Bucharest, Romania † National Institute for Chemical Pharmaceutical Research and Development, Calea Vitan, Bucharest, Romania ‡ ‘Carol Davila’ University of Medicine and Pharmacy, B-dul Eroilor Sanitari, Bucharest, Romania

1. Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Conventional Markers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. CEA, CA 19-9, MUC. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. p53, p21, p16, p27, K-ras, Ki-67 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Candidates in Biomarker Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Sample Type-Related Biomarkers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Signaling Pathway Biomarkers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Apoptosis-Related Biomarkers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Therapy-Related Biomarkers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Antiangiogenic Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Antisignaling Therapy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Genomics/Transcriptomics/Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1. Genomics/Transcriptomics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2. Proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

145 146 147 147 147 148 148 155 158 159 159 159 160 163 164 167 168

1. Abstract Pancreatic cancer represents a major challenge for research studies and clinical management. No specific tumor marker for the diagnosis of pancreatic cancer exists. Therefore, extensive genomic, transcriptomic, and proteomic studies are being developed to identify candidate markers for use 145 0065-2423/10 $35.00 DOI: 10.1016/S0065-2423(10)51006-0

Copyright 2010, Elsevier Inc. All rights reserved.

146

TANASE ET AL.

in high-throughput systems capable of large cohort screening. Understandably, the complex pathophysiology of pancreatic cancer requires sensitive and specific biomarkers that can improve both early diagnosis and therapeutic monitoring. The lack of a single diagnostic marker makes it likely that only a panel of biomarkers is capable of providing the appropriate combination of high sensitivity and specificity. Biomarker discovery using novel technology can improve prognostic upgrading and pinpoint new molecular targets for innovative therapy.

2. Introduction Due to the increased incidence and aggressiveness of pancreatic cancer, there has been an urgent need to identify new and more specific biomarkers for this disease state. Pancreatic cancer is one of the most devastating types of cancer worldwide and its very high mortality reflects its overwhelming aggressive nature [1–3]. Diagnosis is difficult due to the lack of specific symptoms and often takes place after the tumor has spread to other organs. Pancreatic cancer is resistant to conventional radiation and/or chemotherapy with surgery being the only solution for recovery [4–6]. This one-dimensional approach, however, is typically associated with high morbidity. The early detection of pancreatic cancer is essential for the success of clinical evolution and therapies. Thus, combined efforts are needed to identify appropriate markers for this disease [7, 8]. Elucidation of mechanisms that trigger pancreatic carcinogenesis is imperative and can directly lead to the discovery of biomarkers for early detection, prognosis, and potentially new therapeutic targets [9]. Development of noninvasive tests for cancer detection at its earliest, that is, surgically resectable stages, can substantially decrease mortality and improve survival [8], along with screening high-risk patients for pancreatic ductal adenocarcinoma (PDAC) [7]. Novel biomarkers should distinguish between chronic pancreatitis and pancreatic cancer and indicate patients with an increased risk of developing the neoplastic disease [10]. The need extends to biomarkers for therapeutic monitoring as well [1]. Although many molecular markers have been identified, the general opinion is that a set of tests investigating soluble and/or tissue-related markers would be more appropriate for diagnosis, prognosis, and therapy monitoring in pancreatic cancer [11]. Without being exhaustive, this chapter intends to review possible candidate biomarkers, either soluble or tissue related, individual or belonging to a panel, that may contribute to improved diagnostics/prognostics and therapeutic monitoring. Several recent reviews have focused on biomarkers for

ADVANCES IN PANCREATIC CANCER

147

pancreatic cancer [1, 4, 5, 8, 12–15, 106], but due to the high complexity of the disease the need to establish a hierarchy based on their relevance in early diagnosis still exists. Lately, proteomics and genomics studies have been developed with the specific goal of finding new candidate markers in PDAC [10].

3. Conventional Markers Validated tests for diagnosis and prognosis in PDAC comprise several serum markers, oncogenes, biochemical, and immunohistochemical markers. Although many of these markers have been investigated in pancreatic cancer, none appear adequate for accurate preoperative diagnosis. 3.1. CEA, CA 19-9, MUC Several classical markers have been used in pancreatic cancer diagnostic: carcinoembryonic (CEA), carbohydrate antigen (CA 19-9), and mucin (MUC) family, the last one being most commonly used in PDAC [16–18]. Although CA 19-9 has been used as a marker for many years, there have been several recent reports examining its prognostic value [19–21]. Other studies have reported that its sensitivity is inadequate as an early diagnostic marker, however, it may be helpful when used in conjunction with imaging modalities, such as computerized tomography (CT) and endoscopic ultrasonography [8, 22]. The diagnostic value (sensitivity and specificity) of CA 19-9 in pancreatic cancer increases when combined with other biomarkers such as CA 242, CA 50, CEA, CAM 17.1/WGA (mucin antibody sandwich assay) [17, 23], tissue polypeptide specific (TPS) antigen, VEGF, and CEA [24]. MUC1 and MUC4, two main members of the MUC family, are associated with pancreatic cancer [14]. Despite being an ‘‘older’’ biomarker, MUC1 is the only one superior to CA 19-9 as recently described in a novel immunoassay application [5, 25]. Both Singh et al. and Jiang et al. have suggested that mucin expression profile is important for PDAC diagnosis [26–28]. We anticipate these widely used classical biomarkers will be combined with new markers in the future to enhance their diagnostic and prognostic value. 3.2. P53, P21, P16, P27, K-RAS, KI-67 More than 20 years ago, various oncogenes and proliferation markers including Ki-67, p53, and bcl-2 were used in evaluating pancreatic cancer [28, 29]. Despite initial expectations of p53 as a single molecular marker in PDAC, its usefulness has been proven association with other mutations (p21)

148

TANASE ET AL.

for identifying good chemotherapy responders. p21 is the downstream target of p53 activation and induces G1 arrest thus enabling DNA repair mechanisms to take place. Despite the reported loss of p21 activity in tumor specimens, its role in survival rates remains to be established [30–33]. The loss of p16 appears to be a relatively early event in the progression of pancreatic cancer; it seems to be a probable prognostic indicator of survival [30, 34]. The loss of p27 expression was reported in several cases of pancreatic cancers and there is some evidence that p27 mutations may influence survival [35, 36]. In a high number of pancreatic cancer specimens, it was reported that GaT, cGT, and GcT K-ras mutations correlated with shorter median survival time versus other mutations [37]. Ploidy and cell cycle analysis of pancreatic carcinoma cells have been used for predicting tumor progression [29]. Lately, investigators have used a combined marker strategy in an attempt to improve the molecular diagnosis of pancreatic cancer. Their marker panel included mutant K-ras, methylated p16, p53 mutation, and allelic losses at 9p and 18q. This panel was considered to have a good correlation with the clinical evolution of PDAC [8, 11, 38]. It is unlikely that a single tumor marker exists for the reliable diagnosis of pancreatic cancer. Furthermore, it is difficult to extrapolate future usefulness of classical markers pending additional studies in the detection and staging of pancreatic cancer.

4. Candidates in Biomarker Discovery Due to the complex nature of pancreatic cancer, its aggressiveness and high metastatic potential, widespread efforts have been made across many scientific disciplines including genomics, proteomics, transcriptomics, and epigenomics [39]. These efforts have involved the use of blood, tissue, pancreatic, and cystic fluids in the search for angiogenesis-related proteins, growth factors, cellular signaling proteins, genes, and mutations that were found to be significantly altered in pancreatic cancer (Table 1).

4.1. SAMPLE TYPE-RELATED BIOMARKERS Biomarkers detected in various sample types can be common, namely molecules related to tissue neoplastic transformation can be shed into circulation and thus found in serum and/or pancreatic juice.

TABLE 1 CANDIDATES FOR BIOMARKERS IN PANCREATIC CANCER—CORRELATION WITH CLINICOPATHOLOGICAL FEATURES, PROGNOSIS, AND POSSIBLE THERAPY TARGETS No.

Biomarker

Specimen

1

VEGF

Serum/plasma

2

sVEGF/sVEGFR-1

Serum/plasma

3

bFGF

Serum/plasma

4

MIC-1

Tissue/Serum

5 6 7 8 9

M2-PK CEACAM1 HSP27 alpha4GnT K-ras

10

PDX-1

Plasma/Feces Serum Serum Blood Blood/Pancreatic juice Tissue

11

Maspin

Tissue

12

FAP

Tissue

13

Cav-1

Tissue

14

TG2

Tissue/Cell lines

Comments – – – – – – – – – – – – – – – –

Disease stage and metastases Predicting tumor progression Therapy targets Prognostic factor Survival rate Disease stage and metastases Predicting tumor progression Clinical diagnostic Differentiating cancer versus normal Early detection marker Monitoring diseases Differentiating cancer versus normal Differentiating cancer versus normal Differentiating cancer versus normal Accurate diagnostic Tumor progression

– – – – – – – – – – – – –

Tumor size, histological grade, lymph node metastasis Prognostic factor Survival rate Invasiveness Prognostic factor Survival rate Prognostic factor Therapy target Tumor size, histological grade Survival rate Prognostic factor Survival rate Prognostic factor

References [4, 38, 40–46]

[47] [38, 40, 41, 45, 56] [5, 14, 48–54]

[57–61] [14, 62] [63] [14, 64] [8] [65–68]

[69–71]

[72] [6, 73–75]

[76, 77]

(continues)

TABLE 1 (Continued) No.

Biomarker

Specimen

15

KOC

Tissue

16 17 18 19 20

Pancreatic juice Pancreatic juice Pancreatic juice Pancreatic juice Tissue

21 22

MMP-9 DJ-1 A1BG HIP/PAP-I HIF1a, bFGF, VEGF, PDGFA genes CXCR2 and RET genes SGLT1

23

S100P

Tissue/pancreatic juice

24

Sp1

Tissue

25 26 27

MDM2, p16, p27, p73 genes Pim-1 CLDN18, ANXA8 genes

Tissue Tissue Tissue

28

Cyclin D2, DABI, ppENK, FOXE1, NPTX2, p16, RELN, SOCS1, SPARC, TFPI2, TSLC1 genes UHRF1, ATP7A, AOX1 SAA, A1AT, ACT, ITI, APOE APOA2, APOA1, TTR TBX4

29 30 31 32

Comments

Tissue/pancreatic juice

– – – – – – – – – –

Invasiveness Differentiating benign versus malign Diagnosis and screening Diagnosis and screening Diagnosis and screening Diagnosis and screening Survival rate Differentiation therapy Cancer progression Aggressiveness Prognostic factor Differentiation cancer versus normal or chronic pancreatitis Early detection Metastasis Survival rate Prognostic factor Prognostic factor Prognostic factor Differentiating cancer versus normal Therapeutic targets Differentiating cancer versus normal Early detection

Tissue Serum Serum Tissue

– – – –

Differentiating cancer versus normal Differentiating cancer versus normal Differentiating cancer versus normal Differentiating cancer versus normal

Tissue Tissue

– – – – – – – – – – – –

References [5, 78, 79] [7] [7] [7] [4, 80] [81] [82] [83] [84]

[85]

[86] [87] [88] [8, 89]

[90–92] [93, 94] [95] [96]

ADVANCES IN PANCREATIC CANCER

151

4.1.1. Serum Biomarkers Serum has been an important sample for biomarker discovery because the tumor and all other related antigens can be shed into blood circulation. Serum can be easily obtained and safely collected and as such is readily available from tumor bearing patients [14]. Consequently, PDAC biomarkers discovery has focused primarily on serum-based analytes. A number of angiogenesis-related proteins, growth factors, heat-shock proteins, enzymes, and cytokines were found as potential pancreatic tumor markers in serum. Despite this progress, biomarker discovery is still searching for the best molecule or combination thereof for use in pancreatic cancer detection and prognosis [6, 18, 23, 41, 78, 90]. 4.1.1.1. Angiogenesis and Growth Factors. The neoangiogenesis process is enhanced in pancreatic tumors. Intratumoral microvessel density was found to be increased and reported as an independent prognostic factor for survival [4, 97]. Among the factors involved in angiogenesis, several have received attention in pancreatic cancer. These are epidermal growth factor receptor (EGFR), proangiogenic agents including vascular endothelial growth factor (VEGF) and IL-8 [4]. Several studies have found increased VEGF serum levels in patients with pancreatic cancer [42, 98, 99]. Moreover, VEGF serum level has correlated with disease stage, cancer progression, and metastases [43, 44]. Because it has been established that VEGF is an important biomarker in pancreatic cancer, its level has to be quantified when antineoplastic therapy is used, especially when antiangiogenetic drugs are involved [42, 98, 99]. In order to enhance the predictive power of VEGF analysis, a combination of multiple angiogenic factors is required. We have proven that increased serum VEGF and bFGF in pancreatic cancer patients was correlated with a disease stage and tumor progression. The simultaneous increase of soluble VEGF and bFGF could be explained by their closely related downstream signaling pathways [41]. Similar results were previously obtained using tissue samples [45]. Moreover, the EGFR pathway upregulated both VEGF and bFGF, thus enhancing angiogenesis [45, 46]. Published data has indicated that VEGF and bFGF qualify as markers for prognosis and therapeutic control in pancreatic cancer. The ratio of VEGF to its specific receptor (VEGFR-1) has been described as an independent prognostic factor for survival in pancreatic cancer and as an assessment marker for antiangiogenic therapy [47]. Although lacking pancreatic cancer specificity, angiogenic soluble factors can be considered suitable biomarker candidates for pancreatic cancer when considered within a panel. Transforming growth factors (TGF-b), widely studied in various cancers [100, 101], has received attention in pancreatic cancer as well. A member of TGF-b family, macrophage inhibitory cytokine-1 (MIC-1) [14], was

152

TANASE ET AL.

associated with several types of carcinoma [47, 48] and was found to be overexpressed [49, 50], along with other proteins [52] in primary pancreatic cancers and increased in the serum of patients with pancreatic cancers. Investigating several markers (CA 19-9, HIP, TIMP-1, osteopontin, and MIC-1) in normal, chronic pancreatitis, and pancreatic cancer patients, MIC-1 was demonstrated to be a relevant biomarker for this type of cancer. Among all the studied markers, MIC-1 had the highest sensitivity (90%) and the second ranking specificity (94%) for pancreatic cancer versus normal, but poorer when discriminating pancreatic cancer from chronic pancreatitis [51, 52]. MIC-1 is constitutively overexpressed in many tumors [53], its overexpression being probably induced by p53 activation pathway, as demonstrated both in vitro and in vivo. The activation of the p53 pathway [102] was proven by the high levels of circulating MIC-1. Overall, MIC-1 serum levels can have a clinical diagnostic and/or monitoring potential in pancreatic cancer [54, 55] and can be an early detection marker for pancreatic cancer in high-risk populations [56]. 4.1.1.2. Other Serum Markers. Various new serum biomarkers got attention in the last years regarding pancreatic cancer. Thus, tumor M2 pyruvate kinase (M2-PK), detectable in plasma, was proven to have at least equal sensitivity in pancreatic compared to other types of cancers [57– 59]. When compared with the standard tumor marker CA 19-9, M2-PK showed similar or even improved diagnostic sensitivity and specificity for pancreatic carcinoma. A combination of both parameters might even be an interesting option for primary screening [60, 61]. Carcinoembryonic antigen-related cell adhesion molecule (CEACAM1) was recently described as a superior biomarker compared to CA 19-9 in terms of distinguishing cancer serum samples from normal ones. Serum CEACAM1 can be a useful indicator for the appearance of pancreatic cancer and its combination with CA 19-9 was proven to be superior to the individual biomarker [14, 62]. Recently, another serum protein, the heat-shock protein 27 (HSP27) was identified in pancreatic cancer patients, proving high sensitivity and a good specificity [103]. 4.1.1.3. Circulating tumor cells and DNA/RNA markers. Recently, in many types of cancers, the detection of circulating tumor cells (CTCs) has been a goal for biomarker research. However, CTCs are in very low concentrations in the peripheral blood of cancer patients, that is, approximately one CTC per 10 million blood cells. Therefore, CTC detection is difficult, especially at early disease stages when tumor mass is low. As such, amplification methods, that is, PCR-based (DNA or RNA), are generally the only analytical option with the sensitivity to detect a statistically significant number of CTCs. It was reported that when measuring the levels of a-1,

ADVANCES IN PANCREATIC CANCER

153

4-acetyl-glucosaminyltransferase (alpha4GnT) mRNA extracted from peripheral blood mononuclear cells, PDAC could be diagnosed with a sensitivity of 76% and a specificity of 83% [14, 64]. Another circulating marker related to tumor cells, angiogenin mRNA, has been associated with shorter survival in patients with pancreatic tumors [103]. Interestingly, mutant K-ras has been found in the blood of patients with pancreatic cancer and has been related to advanced tumor stage [8, 104, 105]. Mutant K-ras was present in
90% of PDAC and is therefore an important marker of this disease. As in other cancer types, peripheral blood CTCs, detected by RNA/DNAbased methods, can be reliable markers for cancer detection, including pancreatic. 4.1.2. Tissue Biomarkers Valuable information regarding biomarker discovery can be obtained from cancer-related molecules that reside within the cancer tissue itself. Numerous studies with respect to these tissue-based biomarkers have been published. In this review, we present those markers most comprehensively researched in PDAC. 4.1.2.1. Angiogenic factors: EGF, VEGF, heparanase, thrombospondin, cathepsins. Overexpression of EGF in pancreatic cancer has been correlated to advanced tumor stage. When coexpressed with its receptor (EGFR), the possible prognostic information becomes more important, although not clearly linked to overall survival [30, 106, 107]. The combination of tissue EGFR, VEGF, bFGF with matrix metalloproteinase 7 (MMP7) has been reported as growth promoters in PDAC [38, 40]. Several reports have shown that heparanase expression was linked to decreased postresection survival. Heparanase increased growth factor (bFGF and heparin sulphate) release and therefore could stimulate growth and angiogenesis [108, 109]. One of the thrombospondin (TSP) members, TSP-1 has been found to be highly expressed in the stroma of surrounding tumor cells in human pancreatic cancer and its expression has been inversely correlated with microvessel density [110, 111]. Increased expression of TSP-1 is also a favorable prognostic indicator in PDAC [112]. Although cathepsins were considered overexpressed and linked to the malignant progression of pancreatic cancer, their possible application as prognostic biomarkers is still a matter of debate [113]. 4.1.2.2. MMP, uPA, CD44. A common finding in pancreatic cancer is increased MMP expression has been correlated with a poor prognosis, a shorter survival time and/or the presence of local invasion or distant metastases. A combination of MMPs expression can increase their power in survival prediction [30]. Therefore, the urokinase plasminogen activator (uPA) activates precursors of MMPs, fact that can lead to extensive degradation of the extracellular matrix (ECM). uPA and its receptor are reported

154

TANASE ET AL.

to be increased in pancreatic cancer tissue, and correlated with shorter survival time [114]. CD44v6, involved in cell–cell and cell–matrix interaction, is the isoform studied in relation to pancreatic cancer and showed a statistically significant correlation with a decreased survival rate [115]. 4.1.2.3. FAP. FAP (fibroblast activation protein) is highly expressed in PDAC, mainly in the tissue immediately adjacent to the tumor and its increased levels are associated with poor clinical outcome. FAP inhibitors may be considered promising therapeutic agents against pancreatic cancer [72]. 4.1.2.4. Cav-1. Cav-1 (caveolin-1) expression is increased in PDAC and correlates with the tumor size, histological grade, conventional tumor markers, and postresection decreased survival rates [6, 73, 74] therefore, being an independent unfavorable prognostic factor [73]. Additional studies have shown that Cav-1 cooperates with fatty acid synthase (FASN) in pancreatic tumorigenesis, and as such, may be a good candidate for prognostic biomarker [75]. Cav-1 might be used in a putative panel of biomarkers for pancreatic cancer aggressiveness detection and as therapeutic target [74, 75]. The gene encoding Cav-1 was recently annotated as possible genomic marker for PDAC [116]. 4.1.2.5. Maspin. Maspin (SerpinB5), as a tumor suppressor gene, may be a prognostic tumor marker in pancreatic cancer. 90% of PDAC tumors were classified as highly expressing maspin [69, 70, 117] and its overexpression is associated with low postoperative survival, especially in patients having tumors with diffuse pattern of maspin. The absence of maspin expression was associated with an improved survival rate and a reduced invasiveness [70, 71]. Maspin was reported as useful in differentiating chronic pancreatitis from pancreatic cancer [69]. 4.1.2.6. TG2. TG2 (tissue transglutaminase 2) overexpression was demonstrated in several cancers, including PDAC. Elevated levels of TG2 in PDAC tumors and cell lines are inversely correlated with PTEN expression and/or PTEN phosphorylation. Thus, TG2 is considered a relevant prognostic factor for patient survival, independent of the tumor stage [76, 77]. The TG2 expression was found to be correlated with drug resistance [77]. 4.1.2.7. PDX-1. PDX-1 (pancreatic and duodenal homeobox-1), normally expressed in islet cells, is elevated in pancreatic cancer tissues and it is correlated with histological grade, tumor size, and lymph node metastasis. Actually, PDX-1 is a dedifferentiation marker and can pinpoint aggressive pancreatic cancer [65]. Consequently, PDX-1 can be a good candidate as an independent survival factor [66, 67, 118]. In experimental cellular models, PDX-1 overexpression resulted in the significant increase of cell proliferation and invasion. Moreover, silencing huPDX-1 expression in pancreatic cell lines can inhibit proliferation and suppresses tumor growth in vivo [68].

ADVANCES IN PANCREATIC CANCER

155

Overall, downregulation of PDX-1 expression inhibits pancreatic cancer cell growth in various experimental models, implying its use as a potential therapeutic target. 4.1.2.8. KOC. An auspicious novel candidate to serve as a molecular marker of pancreatic malignancy is the K homology domain containing protein overexpressed in cancer (KOC). KOC is strongly overexpressed in pancreatic cancer and strong KOC staining patterns were observed in invasive pancreatic tissues carcinomas, while weak or absent staining was found in all benign cells and tissues. Recent studies demonstrated a high sensitivity and specificity of this marker in differentiating PDAC from benign ductal epithelium [78, 119]. Several important studies have underscored that tissue biomarkers could also be used to increase the sensitivity of the fine needle aspiration (FNA) analysis [5, 78, 79, 119]. 4.1.2.9. Cyclin D1. Although a marker related to cell cycle and intracellular signaling, cyclin D1 is frequently investigated in tissue samples. The target gene of b-catenin, cyclin D1, was identified in pancreatic cancer, and its overexpression could be driven by nuclear accumulation of b-catenin [120]. Studies agree that cyclin D1 expression in correlation with b-catenin nuclear/cytoplasmic accumulation is associated with tumor differentiation and poor prognosis in pancreatic cancer [121–123]. 4.1.3. Pancreatic Juice Pancreatic juice is an exceptionally rich source of proteins released from pancreatic cancer cells and therefore an ideal specimen for biomarkers discovery [4]. Recent studies, regarding proteomic analysis of pancreatic juice, have revealed the presence of 14 upregulated and 10 downregulated proteins. The analysis identified MMP-9, DJ-1, and A1BG proteins as being elevated in the pancreatic juice from PDAC patients, suggesting their further utility in diagnosis and screening [7]. Other studies have identified HIP/PAP-I (hepatocarcinoma–intestine–pancreas/pancreatitis-associated protein I) in pancreatic juice as a biomarker for PDAC [80]. 4.2. SIGNALING PATHWAY BIOMARKERS Signaling pathways involved in complex processes like aberrant proliferation, resistance to apoptosis signals, increased invasiveness, and metastatic potential can offer good candidate markers for PDAC diagnosis/prognosis. Deciphering the signaling pathways has created new expectations concerning biomarker discovery in pancreatic cancer and suggested new therapeutic approaches [4, 124].

156

TANASE ET AL.

Downstream effector pathways that are disturbed in pancreatic cancer are Raf-MAP kinase, and PI3 kinase-AKT [125, 126], pathways associated with enhanced cell growth, proliferation, and survival. The multiple control pathways of cell cycle are making this complex machinery a very interesting pool for biomarkers discovery, although finding efficient therapies focusing on ‘‘single targets’’ within cell cycle regulators remains uncertain. 4.2.1. MAPK and ERK Pathway In signaling pathways, multiple proteins are in an activated form and proven to be associated with pancreatic carcinogenesis, proteins that are members of the ERK, PKB/AKT, mTOR, and STAT3 pathways [125]. The activation of distinct mitogenic pathways in pancreatic tumor cells, including NFkB, PI3K/Akt, and MAPK cascades, can be partially responsible for the uncontrolled proliferative and antiapoptotic effects mediated by certain growth factor receptors. MAPK cascade provided MAP4K4 protein and has been reported as playing an important role in transformation, invasiveness, adhesion, and cell migration. Overexpression of this signaling protein was reported to be associated with bad prognosis and a prognostic marker for stage II PDAC [126]. Several intracellular signaling pathways intermingle between the individual molecular pathways underlying the pathology of pancreatic malignancy [126, 127]. MAPK pathway interferes with EGFR signaling network, interference that can have critical roles in various cancers [128]. EGFR is known to be overexpressed in pancreatic cancer and in several other solid tumors and might be a poor prognostic factor [124]. The discovery of specific agents targeting EGFR (tyrosine kinase inhibitors) would be extremely valuable for pancreatic cancer therapy [4]. 4.2.2. TGFb Signaling Pathway The main TGFb pathway involves three isoformes (TGFb1, 2, and 3), TGFb being a family of membrane receptors that express serine/threonine kinase functions and use intracellular transduction molecules from the SMAD family [129]. During tumor development and progression, TGFb signaling often switches from being tumor suppressive to promoting tumor invasion and metastasis. This change can be a result of Smad4 loss leading to aberrant activation of STAT3. STAT3 inhibition requires a prolonged and Smad4-dependent activation of ERKs [130, 131]. Such alterations, leading to aberrant cell cycle regulation were demonstrated in about 60% of pancreatic cancer patients [132]. It is commonly agreed that a sequence of molecular alterations involving mutational activation of K-ras and loss of the p16/ARF, SMAD4, and p53

ADVANCES IN PANCREATIC CANCER

157

tumor suppressors in pancreatic cancer [133–135]. Among all the reported defects, K-ras has a relatively unique character in relation to pancreatic cancer, as p53 loss is not specific for this type of cancer. In experimental models, knockdown of K-ras in pancreatic cancer cells inhibits growth [136]. K-ras-mediated transformation is not always associated with constitutive ERK or AKT pathway activation [137], but involved in the invasion and metastasis in vivo [138]. In the early stages of pancreatic tumorigenesis, TGFbs act as tumor suppressors (as in normal epithelium) [139]. In cultivated pancreatic tumor cells, an attenuation of TGF-growth inhibition has been recorded [140]. In cancer cell lines, epithelial–mesenchymal transition (EMT) mediated by TGFb was associated with increased levels of vimentin and decreased levels of expression for b-catenin and E-cadherin. In later stages of tumor progression, TGF expression characterizes a more aggressive phenotype. Presumably, alteration in TGFb signaling contributes to resistance to the growth inhibition. The overexpression of TGFb correlates with pancreatic progression, advanced stage, and poor survival of PDAC patients [141]. The use of TGFb inhibitors seems reasonable for the treatment of pancreatic cancer [142]. 4.2.3. Hedgehog, Wnt, and Notch Signaling Pathways In the normal development of epithelial cells, Notch and Hedgehog signaling pathways are highly involved. In the neoplastic transformation, aberrant reactivation of developmental signaling pathways, such as Notch, Hedgehog, and Wnt take place. Various interactions between these pathways might play a major role in the pancreatic cancer initiation and progression [4, 143]. Increased Hedgehog signaling demonstrated in pancreatic tumors can be explained by silencing the Hedgehog interactive protein 1 gene [4]. Wnt/b-catenin pathway is involved in pancreatic cancer progression implying various molecules, among them SDF-1/CXCR4 signaling was reported to regulate the metastatic process [144]. Recent work has demonstrated that the Wnt pathway is constitutively active in primary pancreatic tumors, and pancreatic cancer cell lines [145]. In various cell lines using transfection with an inhibitor of b-catenin or a siRNA construct specific for b-catenin a reduced cell proliferation and a significant increase in apoptosis were obtained [145]. Researchers are still looking for the mechanisms by which Wnt pathway disruption can directly promote apoptosis or enhance sensitivity to agents inducing apoptosis. Hedgehog signaling appears involved in tumor invasiveness, angiogenesis, and metastasis [146, 147]. Sonic hedgehog homolog (SHH) is one of the three proteins in the hedgehog signaling pathway, and is constitutively active in pancreatic cancer [148]. The first evidence of its involvement in PDAC came

158

TANASE ET AL.

from the demonstration that invasive pancreatic adenocarcinomas express the SHH ligand [149, 150]. In cell lines, analogs of cyclopamine, a chemical inhibitor of the hedgehog pathway, has induced growth inhibition and cell death [150], with still unclear mechanisms. SHH has been detected in the pancreatic juice of pancreatic cancer patients and proven to discriminate neoplastic disease from chronic pancreatitis patients [151]. Another highly studied intracellular signaling pathway, Notch, is involved in pancreatic cancer development and progression [152]. Recently, when using siRNA-mediated inhibition of the Notch pathway, apoptosis could be induced in pancreatic cancer cells [153]. There is a demonstrated link between Notch pathway activation and NFkB in pancreatic cancer cells [154]. These pathways are prone to biomarkers discovery in targeted therapy. Therefore, developing strategies to identify hedgehog-dependent pancreatic cancers, finding pathway inhibitors and pursuing clinical trials could be a proper future therapeutic approach.

4.3. APOPTOSIS-RELATED BIOMARKERS 4.3.1. Bcl-2, Bax, Survivin, NFkB Early studies regarding Bcl-2 expression (an antiapoptotic gene) in primary pancreatic tumors showed that Bcl-2 is expressed in well-differentiated tumors [155, 156]. Increased expression is associated with lower rates of spontaneous apoptosis [157], finding that it is sustained by the demonstration that NFkB is one of the transcription factors that drives Bcl-xl expression in pancreatic cancer cells. Bcl-2 expression was reported as displaying a positive correlation with survival following pancreatic cancer resection, although there are studies that reported the opposite, namely either no correlation or a negative relationship [158–161]. Proapoptotic members of the Bcl-2 family, like Bax, show a correlation between the loss of expression and poor survival [162, 163]. Members of inhibitor of apoptosis proteins (IAPs) like XIAP and survivin, are upregulated in pancreatic primary cancer [164]. Survivin was found in 60–80% of pancreatic tumor specimens [165, 166] and was demonstrated to correlate with the clinical stage, the histological grade, and with the proliferation index of pancreatic cancer [166, 167]. Some of the authors studying survivin show that it can be an independent prognostic indicator of overall survival [165]. Death receptors are generally upregulated in pancreatic cancers [168], perhaps due to the inflammatory tumoral microenvironment [169]. NFkB is constitutively active in a majority of human pancreatic cancer cell lines and primary tumors [170]; NFkB inhibitors can sensitize pancreatic cancer cells to chemotherapy-induced apoptosis [171].

ADVANCES IN PANCREATIC CANCER

159

5. Therapy-Related Biomarkers In pancreatic cancer, the therapeutic impact of novel biomarkers has a double requirement: as therapy targets and as treatment efficiency monitoring. There is a great need for new therapeutic modalities for patients. A great number of novel therapies targeting the mechanisms of pancreatic tumor development are under investigation [4]. 5.1. ANTIANGIOGENIC THERAPY Because pancreatic carcinomas display strong neoangiogenesis and are highly vascularized, that is, due to VEGF/VEGFR2 overexpression, antiangiogenic therapies are under exploration. The antiangiogenic therapies including anti-VEGF agent, anti-Raf/VEGFR2 agent, MMP inhibitors were acknowledged [4, 172]. Though there are no proven predictive biomarkers for anti-VEGF therapy in clinical practice, VEGF itself may be a useful tool in monitoring antiangiogenic therapy. Novel biomarkers are needed to identify patients who may respond to antiangiogenic compounds. To identify these markers, assays of ligand activation/signaling, detection of circulating endothelial cells and precursors, and dynamic imaging strategy are underway [13, 173, 174]. 5.2. ANTISIGNALING THERAPY New and effective chemotherapeutic agents to target multiple signaling pathways, inducing responsiveness of pancreatic cancer cells to death signals are also considered. Therapeutic strategies targeting important tandems, as EGF–EGFR (monoclonal antibodies against EGFR) can be monitored through EGFR level predicting individual response to EGFR-targeted therapy. The efficacy of anti-EGFR therapy was nevertheless evaluated during a series of clinical trials with encouraging results [175, 176]. The first NFkB inhibitor to enter clinical trials was the proteasome inhibitor. In preclinical stages, the drug inhibited the growth of some pancreatic cancer xenografts, associated with the induction of apoptosis and inhibition of angiogenesis [177, 178]. Curcumin, a natural NFkB inhibitor used in a recent Phase II trial in patients with advanced pancreatic cancer, showed that only 8% of the patients had a clear evidence of clinical biological activity [179]. Agonistic anti-TRAIL receptor antibodies are currently being evaluated for a combined therapy with NFkB inhibitors, like curcumin [133]. NFB downregulation using a member of the enediyne family could play a positive role in relevant targeted chemotherapy for pancreatic cancer. Another

160

TANASE ET AL.

novel therapeutic approach in pancreatic tumor can be downregulating Notch signaling by curcumin, thus lowering Notch-dependent activation of NFkB [4]. Recently, new inhibitors of the hedgehog signaling pathway were published along with one that acts downstream of SMO (Smoothened—7 membrane spanning receptor) [180, 181]. Pharmacologically altering molecular targets in the PI3K–PKB pathway also appears to be a useful therapeutic approach in pancreatic cancer models [4]. The combined use of tyrosine kinase inhibitors targeting FGF-R1 and VEGF-R2 signaling pathways can be a therapeutic solution in inoperable cancer patients [4]. Other therapeutic combination such as selective EGFRTK inhibitor and protein tyrosine kinase inhibitors could lead to inhibition of cell growth in pancreatic cancer [182]. All clinical trials using known kinase inhibitors in monotherapy or in combination with chemotherapeutic drugs did not improve statistically significant the survival of patients with pancreatic cancer. Recently, screening the human kinome to define a ‘‘survival kinase’’ catalogue for pancreatic cells, 56 kinases with potential therapeutic targets in pancreatic cancer have drawn attention. The combined inhibition of PAK7, MAP3K7, and CK2 survival kinases showed a cumulative effect on apoptosis induction proving specificity for pancreatic cancer cells [183]. CD75s-1- and iso-CD75s-1-gangliosides, potential markers for poor differentiation in pancreatic tumors, are targets for adjuvant treatment using CD75s-specific antitumor drug rViscumin. This drug has successfully passed clinical phase I trials and provides an important prospect for treating pancreatic cancer [184]. One of the most important goals for ongoing laboratory research is to validate preclinical models, at molecular and biological levels, in order to be used as screening tools to predict drug activity in patients [133]. To date, results have summarized biomarkers that individually or as a member of a more complex panel bring new tools for improving PDAC patient’s clinical management (Table 2). In the treatment of pancreatic cancer, besides identifying new molecular markers for therapeutic effectiveness, candidates for new therapeutic strategies are an essential issue in the management of pancreatic cancer.

6. Genomics/Transcriptomics/Proteomics Starting with the last decade, ‘‘omics’’ can be considered the emergent generation of scientific tools in the life sciences. Cancer research has integrated bioinformatics and molecular biology specific technology in the already known

TABLE 2 ACCURACY OF CLASSICAL AND CANDIDATE BIOMARKERS FOR PANCREATIC CANCER

Biomarker

Receiver Operating Curve/ Area Under Curve

Sensitivity (%)

Selectivity (%)

Classical biomarkers CA 19-9

0.716

86

73

Serum

ELISA

76

91

Tissue

IHC

85 90 88.9 58.8 47.1 82

98 62 71.4 34.6 69.2 100

Serum Serum Serum Pancreatic juice Serum Serum Tissue

Multiplex IHC

Serum Pancreatic juice

ELISA RT-PCR

P53 CEA CEACAM-1 MIC-1 MUC1 MMP 9 TIMP 1 K-ras

0.747

TPS S100P

0.822 0.837

0.50 0.64

New candidate biomarkers KOC

A1BG DNA methylation Span-1 DUPAN-2 PAM4 Alpha4GnT SP1

Sample

Technology

RT-PCR ELISA ELISA PCR

79

100

Tissue

IHC

82 81–94 48–80 77 76 77

100 75 75–85 95 93 100

Serum Pancreatic juice Pancreatic juice Pancreatic juice Pancreatic juice Pancreatic juice Tissue

AB arrayþMALDI PCR IHC IHC IHC IHC IHC

0.998

Relevance

References

Prognosis—survival and therapeutic response Survival, aggressiveness Survival Diagnostics Prognosis, Diagnostics Survival Survival Diagnostics malignancy Diagnostics Diagnostics

[185–188]

Diagnostics (malignant vs. benign) Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics Diagnostics

[119]

[189] [24, 190] [62] [51, 191] [192] [185] [185] [193] [194] [84]

[185] [89, 191] [191] [191] [191] [191] [85] (continues)

TABLE 2 (Continued)

Biomarker

Receiver Operating Curve/ Area Under Curve

Sensitivity (%)

Selectivity (%)

87.1 75

55.6 87

HIF1a HIP Protein signatures CA 19-9 and protein signatures (1211, 7903, 3359, 1802 Da) SAA

0.935

0.691

34.7

Haptoglobin

0.792

Sample

Technology

Relevance

References

Tissue Pancreatic juice

RT-PCR SELDI

Diagnostics Diagnostics

[81] [80]

Serum

ElisaþSELDI-TOF

Diagnostics

[195, 196]

90.2

Serum

MS

[197]

82.7

71.1

Serum

MS

SAA, haptoglobin, CA 19-9

81.3

95.5

Serum

MS

Serum amyloid A, a-1-antitrypsin, a1-antichymotrypsin, inter-a-trypsin inhibitor Apolipoprotein A-II, transthyretin, apolipoprotein A-I Protein signatures (13 proteins) Protein signatures (eight proteins) Protein signatures (12 proteins)

88

75

Serum

MALDI

Diagnostics (malignant vs. benign) Diagnostics (malignant vs. benign) Diagnostics (malignant vs. benign) Diagnostics

83

77

Serum

SELDI

Diagnostics

[95]

0.64–0.85

77.4

84.1

Tissue

SELDI

[198]

0.67–0.8

83.9

78.9

Tissue

SELDI

0.64–0.81

58.1

90.5

Tissue

SELDI

Diagnostics (PC vs. pancreatitis) Diagnostics (PC vs. benign) Diagnostics (PC vs. normal)

[197]

[197]

[94]

[195] [195]

Table reproduced with permission from Informa Healthcare from the paper: Tanase, Neagu, Albulescu, Codorean, Dima, Biomarkers in the diagnosis, and early detection of pancreatic cancer, Expert Opin. Mol. Diagn. (2009), 3(5): 1–14.

ADVANCES IN PANCREATIC CANCER

163

‘‘omics’’ field. Two forces drove forward biomarker research in cancer: genomics (including the related field of transcriptomics) and proteomics. 6.1. GENOMICS/TRANSCRIPTOMICS In the majority of cases, in the neoplastic transformation, the normal cell undergoes an array of processes driven by the accumulation of genetic alterations that finally leads to the appearance of an atypical cell. As well as in other cancer types, in pancreatic cancer too, were detected point mutations, genomic imbalances, aberrant methylation patterns, gene expression changes, alteration at mRNA, and/or protein levels. All these changes were detected in various samples such as pancreatic tissue, serum, pancreatic juice, FNA biopsies, and brush cytologies [39]. Novel molecular genetic markers can improve diagnosis and establish high-risk groups [78]. Genetic evaluation was mainly focused on genes related to angiogenesis, cell physiology, cell cycle, and epigenetics. Besides the proteins involved in angiogenesis, as prior mentioned, the genes that encode these proteins were paid attention. Thus, H1F1a, bFGF, VEGF, and PDGFA gene expressions, as well as their interrelationships, were evaluated. When comparing their expression with patient’s clinical parameters, good correlation was obtained with survival probability and, moreover, these genetic markers could stratify patients for a specific therapy [81]. Genes that regulate angiogenesis-induced growth factors are involved in pancreatic cancer as well. Therefore, CXCR2 and RET were found to be upregulated in pancreatic cancer [82]. Most of the genes that regulate cell physiology were thoroughly investigated in PDAC. Therefore, high SGLT1 (sodium-dependent glucose cotransporter 1) expression in primary tumors was correlated with aggressiveness, namely with high Bcl-2 expression. Recently, it has been reported that SGLT1 and Bcl-2 coexpression might be prognostic markers in pancreatic cancer [83]. Another gene highly involved in cell physiology is S100P and has recently been reported to be overexpressed in PDAC compared to normal pancreas and chronic pancreatitis. This gene could serve as a novel reliable early marker of malignancy. mRNA for S100P was detected in FNAB and pancreatic juice, proving that the gene encoding for S100P can be a sensitive, specific marker for pancreatic neoplasia [84]. Sp1, a common transcription factor for cell growth genes, was associated with increased probability of cancer metastasis and low overall survival. Tissue Sp1 could be a marker identifying aggressive PDAC and could be used as a prognostic factor for metastasis [85]. Neoplastic transformation is associated with cell cycle deregulation, therefore cell cycle genes MDM2, p16, p27, and p73 polymorphisms were reported to be promising markers for patients with pancreatic cancer [86]. Pim-1, a

164

TANASE ET AL.

novel proto-oncogene involved in cell survival, differentiation, and proliferation, was found significantly increased in PDAC at both mRNA and protein level. Moreover, Pim-1 expression can be enhanced by tumorinduced hypoxia, thus having a prognostic value [87]. For the evaluation of pancreatic cancer therapy, genetic markers were reported. Therefore, genes involved in invasiveness like Claudin 18— CLDN18 and annexin A8—ANXA8 were found to be overexpressed in tumor samples compared to normal tissue. Authors do not rule out that, besides their diagnostic/screening power, they may stand for therapeutic targets as well [88]. Polymorphic variations of DNA damage response genes can influence the efficacy of gemcitabine/radiation therapy [199]. Epigenetic transformation was recently evaluated with respect to pancreatic cancer. For several genes, aberrant methylation (e.g., Cyclin D2, DABI, ppENK, FOXE1, NPTX2, p16, RELN, SOCS1, SPARC, TFPI2, TSLC1) was observed in tissue and pancreatic juice during pancreatic cancer development. These epigenetic alterations were rarely detected in normal pancreatic tissue; therefore, they can be useful for early detection [8, 89]. Recently, miRNA alteration in correlation with susceptibility of pancreatic cancer development and early detection were discovered. The expression profiles of miRNAs may provide better insights on pancreatic tumorigenesis and are potential relevant diagnostic markers [200]. A set of 10 miRNAs can be used to distinguish endocrine from acinar pancreatic tumors [201]. MiR-21 overexpression was found as strongly associated with both a high Ki67 proliferation index and the presence of liver metastasis. An aberrant expression of 26 miRNAs was demonstrated in PDAC [201, 202]. There are data regarding the importance of miRNA specific patterns in pancreatic cancer and their use as molecular biomarkers for tumor diagnosis, identification of risk populations of patients, disease prognosis, prevention of cancer, and prediction of therapeutic responses [203]. The use of high-throughput DNA sequencing strategies led to the identification of several cancer causing mutations, but not pancreatic cancer. This approach will probably lead to the identification of new mutated genes in pancreatic cancer, which could serve as targets for early detection [8]. Future genomics will probably focus on the detection of mitochondrial mutations, as well as on miRNA alteration in correlation with susceptibility of pancreatic cancer development and early detection. 6.2. PROTEOMICS Proteomics technology, like mass spectrometry, 2DGE protein array, MS imagery, etc. was recently put in use for biomarker discovery in PDAC [91–93, 204].

ADVANCES IN PANCREATIC CANCER

165

A novel technology, SELDI-TOF MS, was suitable to analyze protein profiling in various body fluids, such as serum and pancreatic juice and/or tissue. This technology was applied for the discovery of candidate biomarkers [90, 91] and the new proteins found were even better than the classical ones [94, 196]. The main advantage of using SELDI as a discovery platform is that many patient samples can be profiled in single experiments. SELDI has discovered a large number of proteins, found to be differentially expressed in chronic pancreatitis and PDAC when compared with normal pancreas. From a total of 102 proteins, 30 showed significant deregulation in PDAC compared to normal tissue. Authors report that UHRF1, ATP7A, and aldehyde oxidase 1—AOX1, individually or in combination, could be potential biomarkers candidates [92]. Recently, using the same SELDI platform HIP/PAP-I was identified in pancreatic juice and reported its biomarker value [4, 80]. Another mass spectrometric approach, MALDI (matrix associated laser desorption ionization), was used to identify pancreatic cancer proteins in serum [94] where only acute phase response proteins (serum amyloid A— SAA, alpha-1-antitrypsin—A1AT, alpha-1-antichymotrypsin—ACT, interalpha-trypsin inhibitor—ITI) were significantly different compared to normal. Results were confirmed when using a combination of DIGE and MALDI/TOF/TOF. Thus, in the serum of PDAC patients, 24 unique proteins were upregulated concomitantly with 17 unique proteins downregulated compared to normal serum profiling, having among them apolipoprotein E (APOE) [68]. For quantitative proteomic profiling of pancreatic cancer and normal tissues, isotope-coded affinity tag technology and tandem mass spectrometry were used for more accurate quantitation. In this complex study, several proteins were found to be differentially expressed in pancreatic cancer, among them there were proteins associated to ECM that are known to be involved in tumor growth, migration, angiogenesis, invasion, metastasis, and immunologic escape [91]. Later, apolipoprotein A-II— APOA2, A-I—APOA1, transthyretin—TTR from the serum were confirmed as markers in pancreatic cancer by a combined SELDI approach, followed by MALDI techniques [95]. When using enhanced proteomic technology, MALDI–TOF–TOF and 2-DE, 30 different tissue proteins were found as possible candidates for biomarkers in pancreatic cancer. Among them, only TBX4 was identified as a differentiation-related protein of PDAC [96]. In a recent proteomic technology, MALDI was associated with an imaging system. Thus, MALDI-imaging mass spectrometry (MALDI-IMS) can determine the distribution of unknown compounds in a single measurement and enable the acquisition of cellular expression profiles while maintaining the cellular and molecular integrity. Several types of cancers were investigated using MALDI-IMS, including pancreatic cancer [205].

166

TANASE ET AL.

Pancreatic juice profiling was performed using a combination of proteomic methods (difference gel electrophoresis—DIGE, tandem mass spectrometry—MS/MS, Western blot, immunohistochemistry, ELISA). Using this combination MMP-9, oncogene DJ1, and A1BG was demonstrated as upregulated in correlation to PDAC [7]. The mass spectrometry analysis, like SELDI-TOF and MALDI-TOF, present the advantage of the high-throughput approach. In the basic approach, ‘‘integral’’ protein complexes from tissue or body fluids may be resolved by TOF MS with high reproducibility and accuracy. Depending on sample characteristics, major proteins that are not relevant or specific to the disease need to be removed, in order to unmask potential biomarkers. More sophisticated surface chemistries made possible on chip protein fractionation and enrichment, thus enhancing the resolving power of MALDI/SELDI analysis [206]. However, these technologies have some shortcomings: bias from artifacts related to the clinical sample collection and storage, the inherent qualitative nature of mass spectrometers, failure to identify wellestablished cancer biomarkers, bias when identifying high-abundance molecules within the serum, and disagreement between peaks generated by different research laboratories [207]. One major limitation in the development of diagnostics solutions based on TOF MS resides in the sensitivity (usually situated in the fmol range). Even if samples are depleted of major proteins and surface chemistry favors sample enrichment, the abundance of target proteins need an appropriate signal strength to be detected. This may represent a considerable problem for early diagnostics, and a more practical approach for screening/early detection would be the development of other detection techniques (such as xMAP or other protein arrays) for a set confirmed biomarkers [8]. In the ‘‘pros and cons’’ battle, in the last few years, both methods have proved their power in ‘‘biomarker mining,’’ yet their area is limited to research or biomarker discovery but not as diagnostics systems. Quantitative proteomic profiling of body fluids, tissues, or other biological samples used to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers in the early diagnosis, therapeutic targets and disease response markers [90]. Even though several important research groups handling advanced proteomic technology identified markers in pancreatic cancers by protein profiling, results were not as encouraging as expected and there is still a need to prove their usefulness as diagnostic, prognostic, or therapeutic biomarkers for pancreatic carcinoma. Help in biomarker discovery can come from multiple platform technologies and complementary strategy for

ADVANCES IN PANCREATIC CANCER

167

discovering clinically useful pancreatic cancer biomarkers. The proteomic approach can be helpful from several points of view: confirming intracellular/ tissue markers, adding new candidates for soluble markers and contributing to high-throughput systems for large cohort screening.

7. Conclusions Due to the complex nature of pancreatic cancer in terms of aggressiveness, and resistance to standard therapy, identification of sensitive and specific diagnostic/prognostic markers is essential in detecting early pancreatic cancers. Markers, as screening tools, obtained from developing proteomics and genomics research, namely proteins and nucleic acids, got attention in the last years and await validation to be put in use in clinical management of the pancreatic patients. Soluble markers detected from serum, FNA specimen, pancreatic juice, and cystic fluids are important clinical indicators for pancreatic cancer evolution. As early stages of pancreatic cancer lack in symptomatology, established screening programs can beneficiate from highly sensitive, specific, cost-effective diagnostic procedures. We believe that, for early diagnosis improvement, only a panel of soluble biomarkers could provide the appropriate combination between high sensitivity and specificity. In this panel of biomarkers, future studies will elucidate whether signaling pathway molecules that mediate intra- and intercellular interactions within the tumor could stand for valuable biomarkers. In this respect, tumor stem cells in human pancreatic cancer were recently identified and these cells express several components of various important signaling pathways. The role in controlling cell renewal or proliferation is still to be established and probably in the near future stem-cell-related markers will contribute to the biomarkers panel in PDAC. For accurate staging, prognosis and therapy monitoring along with soluble markers, tissue-related ones, can shed light on pancreatic cancer pathophysiology. Therefore, tumor types/subtypes accurate classification would be the beneficiary of multiple marker quantification at tissue level pinpointing at members of the cellular genome, transcriptome, or proteome. The currently used combination of imaging analysis, cytology, and validated biomarkers will have to enlarge with more sensitive and specific biomarkers tools to diagnose PDAC. The panel of new biomarkers will cover protein and gene profiling from various body fluids and tissues that will contribute to the diagnostic/prognostic array. We predict a genetic evaluation by means of ‘‘lab-on-a-chip’’ methods that could screen high-risk patients.

168

TANASE ET AL.

Genomics, transcriptomics, and proteomics provide dual outputs. One consists in the identification and validation of individual biomarkers or sets of biomarkers. The other one addresses to the paradigm of systems biology, namely the acquisition of a huge amount of information from simultaneous/ quantitative measurement of multiple biological components and their rigorous integration by mathematical models. All the presented possible molecular markers will be the subject of further research in order to gain their viability in clinics. Using the state-of-the-art technology, gene microarray and mass spectrometry, multiple genetic and protein can be measured in pancreatic tissue, pancreatic juice, sera, and further correlate them for acknowledging a specific molecular signature that could be used to diagnose pancreatic tumors. We believe that the discovered tissue/serum biomarker panels using highthroughput technology are capable to fulfill the characteristic of molecular signatures in diagnostic. Moreover, serum biomarkers, due to sample availability, offer both early detection of the disease and noninvasive testing. The chapter is far from being exhaustive but, all the up-to-date gathered data point out the continuous need for thorough investigation of pancreatic cancer development-related molecules and genes in order to improve early diagnosis and discover innovative therapeutic approaches. ACKNOWLEDGMENTS We appreciated the help of researchers Eleonora Codorean, Elena Raducan, Daniela Popescu, Lucian Albulescu, Maria-Linda Cruceru for their valuable input in this chapter. The authors thank Irina Radu for technical assistance.

REFERENCES [1] M.W. Saif, Translational research in pancreatic cancer. Highlights from the ‘‘44th ASCO Annual Meeting’’. Chicago, IL, USA. May 30–June 3, 2008, JOP 9 (4) (2008) 398–402. [2] F.H. Sarkar, S. Banerjee, Y. Li, Pancreatic cancer: pathogenesis, prevention and treatment, Toxicol. Appl. Pharmacol. (3) (2007) 326–336 PMCID: 2094388. [3] A. Jemal, R. Siegel, E. Ward, T. Murray, J. Xu, C. Smigal, et al., Cancer statistics, 2006, CA Cancer J. Clin. 56 (2) (2006) 106–130. [4] M. Diamantidis, G. Tsapournas, J. Kountouras, C. Zavos, New aspects of regulatory signaling pathways and novel therapies in pancreatic cancer, Curr. Mol. Med. 8 (1) (2008) 12–37. [5] T. Grote, C.D. Logsdon, Progress on molecular markers of pancreatic cancer, Curr. Opin. Gastroenterol. 23 (5) (2007) 508–514. [6] C.P. Tanase, Caveolin-1: a marker for pancreatic cancer diagnosis, Expert Rev. Mol. Diagn. 8 (4) (2008) 395–404. [7] M. Tian, Y.Z. Cui, G.H. Song, M.J. Zong, X.Y. Zhou, Y. Chen, et al., Proteomic analysis identifies MMP-9, DJ-1 and A1BG as overexpressed proteins in pancreatic juice from pancreatic ductal adenocarcinoma patients, BMC Cancer 8 (2008) 241.

ADVANCES IN PANCREATIC CANCER

169

[8] M. Goggins, Identifying molecular markers for the early detection of pancreatic neoplasia, Semin. Oncol. 34 (4) (2007) 303–310. [9] H. Algul, R.M. Schmid, Pancreatic cancer: a plea for good and comprehensive morphological studies, Eur. J. Gastroenterol. Hepatol. 20 (8) (2008) 713–715. [10] V.M. Faca, K.S. Song, H. Wang, Q. Zhang, A.L. Krasnoselsky, L.F. Newcomb, et al., A mouse to human search for plasma proteome changes associated with pancreatic tumor development, PLoS Med. 5 (6) (2008) e123 PMCID: 2504036. [11] C. Salek, L. Benesova, M. Zavoral, V. Nosek, L. Kasperova, M. Ryska, et al., Evaluation of clinical relevance of examining K-ras, p16 and p53 mutations along with allelic losses at 9p and 18q in EUS-guided fine needle aspiration samples of patients with chronic pancreatitis and pancreatic cancer, World J. Gastroenterol. 13 (27) (2007) 3714–3720. [12] A. Jimeno, M. Hidalgo, Molecular biomarkers: their increasing role in the diagnosis, characterization, and therapy guidance in pancreatic cancer, Mol. Cancer Ther. 5 (4) (2006) 787–796. [13] G. El Maalouf, C. Le Tourneau, G.N. Batty, S. Faivre, E. Raymond, Markers involved in resistance to cytotoxics and targeted therapeutics in pancreatic cancer, Cancer Treat Rev. 35 (2) (2009) 167–174. [14] J.J. Liang, E.T. Kimchi, K.F. Staveley-O’Carroll, D. Tan, Diagnostic and prognostic biomarkers in pancreatic carcinoma, Int. J. Clin. Exp. Pathol. 2 (1) (2009) 1–10 PMCID: 2491391. [15] C.P. Tanase, M. Neagu, R. Albulescu, E. Codorean, S.O. Dima, Biomarkers in the diagnosis and early detection of pancreatic cancer, Expert Opin. Med. Diagn. 175300593 (5) (2009) 533–546 Informa Healthcare. [16] S. Fujioka, T. Misawa, T. Okamoto, T. Gocho, Y. Futagawa, Y. Ishida, et al., Preoperative serum carcinoembryonic antigen and carbohydrate antigen 19-9 levels for the evaluation of curability and resectability in patients with pancreatic adenocarcinoma, J. Hepatobiliary Pancreat Surg. 14 (6) (2007) 539–544. [17] K.S. Goonetilleke, A.K. Siriwardena, Systematic review of carbohydrate antigen (CA 19-9) as a biochemical marker in the diagnosis of pancreatic cancer, Eur. J. Surg. Oncol. 33 (3) (2007) 266–270. [18] D.E. Misek, T.H. Patwa, D.M. Lubman, D.M. Simeone, Early detection and biomarkers in pancreatic cancer, J. Natl. Compr. Canc. Netw. 5 (10) (2007) 1034–1041. [19] C.R. Ferrone, D.M. Finkelstein, S.P. Thayer, A. Muzikansky, C. Fernandez-delCastillo, A.L. Warshaw, Perioperative CA19-9 levels can predict stage and survival in patients with resectable pancreatic adenocarcinoma, J. Clin. Oncol. 24 (18) (2006) 2897–2902. [20] T. Grote, D.R. Siwak, H.A. Fritsche, C. Joy, G.B. Mills, D. Simeone, et al., Validation of reverse phase protein array for practical screening of potential biomarkers in serum and plasma: accurate detection of CA19-9 levels in pancreatic cancer, Proteomics 8 (15) (2008) 3051–3060. [21] M. Kilic, E. Gocmen, M. Tez, T. Ertan, M. Keskek, M. Koc, Value of preoperative serum CA 19-9 levels in predicting resectability for pancreatic cancer, Can. J. Surg. 49 (4) (2006) 241–244. [22] D.A. Tessler, A. Catanzaro, V. Velanovich, S. Havstad, S. Goel, Predictors of cancer in patients with suspected pancreatic malignancy without a tissue diagnosis, Am. J. Surg. 191 (2) (2006) 191–197. [23] Q. Liao, Y.P. Zhao, Y.C. Yang, L.J. Li, X. Long, S.M. Han, Combined detection of serum tumor markers for differential diagnosis of solid lesions located at the pancreatic head, Hepatobiliary Pancreat. Dis. Int. 6 (6) (2007) 641–645.

170

TANASE ET AL.

[24] G. Sandblom, S. Granroth, I.C. Rasmussen, TPS, CA 19-9, VEGF-A, and CEA as diagnostic and prognostic factors in patients with mass lesions in the pancreatic head, Ups. J. Med. Sci. 113 (1) (2008) 57–64. [25] A.P. Singh, N. Moniaux, S.C. Chauhan, J.L. Meza, S.K. Batra, Inhibition of MUC4 expression suppresses pancreatic tumor cell growth and metastasis, Cancer Res. 64 (2) (2004) 622–630. [26] K. Nagata, M. Horinouchi, M. Saitou, M. Higashi, M. Nomoto, M. Goto, et al., Mucin expression profile in pancreatic cancer and the precursor lesions, J. Hepatobiliary Pancreat Surg. 14 (3) (2007) 243–254. [27] Z.M. Jiang, D.R. Xie, Q. Yang, D.L. Chen, Z.F. Bi, Diagnostic performance of MUC1 for pancreatic ductal adenocarcinoma: a meta-analysis, 2008 ASCO Annual Meeting Proceedings (Post-Meeting Edition)J. Clin. Oncol. 26 (15 Suppl.) (2008) 15680. [28] S. Jeong, D.H. Lee, J.I. Lee, J.W. Lee, K.S. Kwon, P.S. Kim, et al., Expression of Ki-67, p53, and K-ras in chronic pancreatitis and pancreatic ductal adenocarcinoma, World J. Gastroenterol. 11 (43) (2005) 6765–6769. [29] K.J. Stanton, R.A. Sidner, G.A. Miller, O.W. Cummings, C.M. Schmidt, T.J. Howard, et al., Analysis of Ki-67 antigen expression, DNA proliferative fraction, and survival in resected cancer of the pancreas, Am. J. Surg. 186 (5) (2003) 486–492. [30] G. Garcea, C.P. Neal, C.J. Pattenden, W.P. Steward, D.P. Berry, Molecular prognostic markers in pancreatic cancer: a systematic review, Rev. Eur. J. Cancer 41 (2005) 2213–2236. [31] Y. Xiong, G.J. Hannon, H. Zhang, D. Casso, R. Kobayashi, D. Beach, et al., p21 is a universal inhibitor of cyclin kinases, Nature 366 (6456) (1993) 701–704. [32] Y. Hashimoto, Y. Nio, S. Sumi, T. Toga, H. Omori, M. Itakura, et al., Correlation between TGFbeta 1 and p21 (WAFI/CIP1) expression and prognosis in resectable invasive ductal carcinoma of the pancreas, Pancreas 22 (2001) 341–371. [33] A.V. Biankin, A.L. Morey, C. Lee, J.G. Kench, S.A. Biankin, H.C. Hook, et al., DPC4/ Smad4 expression and outcome in pancreatic ductal adenocarcinoma, J. Clin. Oncol. 20 (2002) 4531–4542. [34] S. Sasaki, H. Yamamoto, H. Kaneto, I. Ozeki, Y. Adachi, H. Takagi, et al., Differential roles of alterations of p53, p16, and SMAD4 expression in the progression of intraductal papillary-mucinous tumors of the pancreas, Oncol. Rep. 10 (1) (2003) 21–25. [35] A. Juuti, S. Nordling, J. Louhimo, J. Lundin, K. von Boguslawski, C. Haglund, et al., Loss of p27 expression is associated with poor prognosis in stage I–II pancreatic cancer, Oncology 65 (2003) 371–377. [36] R.M. Feakins, A.J. Ghaffar, p27 Kip expression is reduced in pancreatic carcinoma but of limited prognostic value, Hum. Pathol. 34 (2003) 385–390. [37] A. Kawesha, P. Ghaneh, A. Andren-Sandberg, D. Ograed, R. Skar, S. Dawiskiba, et al., K-ras oncogene subtype mutations are associated with survival but not expression of p53, p16(INK4A), p21(WAF-1), cyclin D1, erbB-2 and erbB-3 in resected pancreatic ductal adenocarcinoma, Int. J. Cancer 89 (6) (2000) 469–474. [38] G. Tonini, F. Pantano, B. Vincenzi, A. Gabbrielli, R. Coppola, D. Santini, Molecular prognostic factors in patients with pancreatic cancer, Expert Opin. Ther. Targets 11 (12) (2007) 1553–1569. [39] L. Yan, C. McFaul, N. Howes, J. Leslie, G. Lancaster, T. Wong, et al., Molecular analysis to detect pancreatic ductal adenocarcinoma in high-risk groups, Gastroenterology 128 (7) (2005) 2124–2130. [40] J. Itakura, T. Ishiwata, B. Shen, M. Kornmann, M. Korc, Concomitant over-expression of vascular endothelial growth factor and its receptors in pancreatic cancer, Int. J. Cancer 85 (1) (2000) 27–34.

ADVANCES IN PANCREATIC CANCER

171

[41] C. Tanase, E. Raducan, S. Dima, L. Albulescu, I. Alina, P. Marius, et al., Assessment of soluble angiogenic markers in pancreatic cancer, Biomarkers Med. 55 (5) (2008) 447. [42] A. Kobayashi, T. Yamaguchi, T. Ishihara, T. Ohshima, T. Baba, Y. Shirai, et al., Usefulness of plasma vascular endothelial growth factor in the diagnosis of pancreatic carcinoma: differential diagnosis, tumor progression, and patient survival, Pancreas 31 (1) (2005) 74–78. [43] S. Fredriksson, J. Horecka, O.T. Brustugun, J. Schlingemann, A.C. Koong, R. Tibshirani, et al., Multiplexed proximity ligation assays to profile putative plasma biomarkers relevant to pancreatic and ovarian cancer, Clin. Chem. 54 (3) (2008) 582–589. [44] A.J. Karayiannakis, H. Bolanaki, K.N. Syrigos, B. Asimakopoulos, A. Polychronidis, S. Anagnostoulis, et al., Serum vascular endothelial growth factor levels in pancreatic cancer patients correlate with advanced and metastatic disease and poor prognosis, Cancer Lett. 194 (1) (2003) 119–124. [45] C.H. Baker, C.C. Solorzano, I.J. Fidler, Blockade of vascular endothelial growth factor receptor and epidermal growth factor receptor signaling for therapy of metastatic human pancreatic cancer, Cancer Res. 62 (7) (2002) 1996–2003. [46] K. Kuwahara, T. Sasaki, Y. Kuwada, M. Murakami, S. Yamasaki, K. Chayama, Expressions of angiogenic factors in pancreatic ductal carcinoma: a correlative study with clinicopathologic parameters and patient survival, Pancreas 26 (4) (2003) 344–349. [47] Y.T. Chang, M.C. Chang, S.C. Wei, Y.W. Tien, C. Hsu, P.C. Liang, et al., Serum vascular endothelial growth factor/soluble vascular endothelial growth factor receptor 1 ratio is an independent prognostic marker in pancreatic cancer, Pancreas 37 (2) (2008) 145–150. [48] P. Buckhaults, C. Rago, B. St. Croix, K.E. Romans, S. Saha, L. Zhang, et al., Secreted and cell surface genes expressed in benign and malignant colorectal tumors, Cancer Res. 61 (19) (2001) 6996–7001. [49] J.B. Welsh, L.M. Sapinoso, S.G. Kern, D.A. Brown, T. Liu, A.R. Bauskin, et al., Largescale delineation of secreted protein biomarkers overexpressed in cancer tissue and serum, Proc. Natl. Acad. Sci. USA 100 (6) (2003) 3410–3415 PMCID: 152306. [50] J. Koopmann, P. Buckhaults, D.A. Brown, M.L. Zahurak, N. Sato, N. Fukushima, et al., Serum macrophage inhibitory cytokine 1 as a marker of pancreatic and other periampullary cancers, Clin. Cancer Res. 10 (7) (2004) 2386–2392. [51] J. Koopmann, C.N. Rosenzweig, Z. Zhang, M.I. Canto, D.A. Brown, M. Hunter, et al., Serum markers in patients with resectable pancreatic adenocarcinoma: macrophage inhibitory cytokine 1 versus CA19-9, Clin. Cancer Res. 12 (2) (2006) 442–446. [52] J. Koopmann, N.S. Fedarko, A. Jain, A. Maitra, C. Iacobuzio-Donahue, A. Rahman, et al., Evaluation of osteopontin as biomarker for pancreatic adenocarcinoma, Cancer Epidemiol. Biomark. Prev. 13 (3) (2004) 487–491. [53] A.R. Bauskin, D.A. Brown, T. Kuffner, H. Johnen, X.W. Luo, M. Hunter, et al., Role of macrophage inhibitory cytokine-1 in tumorigenesis and diagnosis of cancer, Cancer Res. 66 (10) (2006) 4983–4986. [54] D.A. Brown, C. Stephan, R.L. Ward, M. Law, M. Hunter, A.R. Bauskin, et al., Measurement of serum levels of macrophage inhibitory cytokine 1 combined with prostate-specific antigen improves prostate cancer diagnosis, Clin. Cancer Res. 12 (1) (2006) 89–96. [55] D.A. Brown, R.L. Ward, P. Buckhaults, T. Liu, K.E. Romans, N.J. Hawkins, et al., MIC1 serum level and genotype: associations with progress and prognosis of colorectal carcinoma, Clin. Cancer Res. 9 (7) (2003) 2642–2650. [56] M.I. Canto, M. Goggins, R.H. Hruban, G.M. Petersen, F.M. Giardiello, C. Yeo, et al., Screening for early pancreatic neoplasia in high-risk individuals: a prospective controlled study, Clin. Gastroenterol. Hepatol. 4 (6) (2006) 766–781.

172

TANASE ET AL.

[57] H.R. Hathurusinghe, K.S. Goonetilleke, A.K. Siriwardena, Current status of tumor M2 pyruvate kinase (tumor M2-PK) as a biomarker of gastrointestinal malignancy, Ann. Surg. Oncol. 14 (10) (2007) 2714–2720. [58] I. Novotny, P. Dite, M. Dastych, A. Za´kova´, J. Trna, H. Novotna´, et al., Tumor marker M2-pyruvate-kinase in differential diagnosis of chronic pancreatitis and pancreatic cancer, Hepatogastroenterology 55 (85) (2008) 1475–1477. [59] M. Ventrucci, A. Cipolla, C. Racchini, R. Casadei, P. Simoni, L. Gullo, Tumor M2pyruvate kinase, a new metabolic marker for pancreatic cancer, Dig. Dis. Sci. 49 (7–8) (2004) 1149–1155. [60] P.D. Hardt, N. Ewald, Tumor M2 pyruvate kinase: a tumor marker and its clinical application in gastrointestinal malignancy, Expert Rev. Mol. Diagn. 8 (5) (2008) 579–585. [61] Y. Kumar, K. Gurusamy, V. Pamecha, B.R. Davidson, Tumor M2-pyruvate kinase as tumor marker in exocrine pancreatic cancer a meta-analysis, Pancreas 35 (2) (2007) 114–119. [62] D.M. Simeone, B. Ji, M. Banerjee, T. Arumugam, D. Li, M.A. Anderson, et al., CEACAM1, a novel serum biomarker for pancreatic cancer, Pancreas 34 (4) (2007) 436–443. [63] C. Melle, G. Ernst, N. Escher, D. Hartmann, B. Schimmel, A. Bleul, et al., Protein profiling of microdissected pancreas carcinoma and identification of HSP27 as a potential serum marker, Clin. Chem. 53 (4) (2007) 629–635. [64] S. Ishizone, K. Yamauchi, S. Kawa, T. Suzuki, F. Shimizu, O. Harada, et al., Clinical utility of quantitative RT-PCR targeted to alpha1, 4-N-acetylglucosaminyltransferase mRNA for detection of pancreatic cancer, Cancer Sci. 97 (2) (2006) 119–126. [65] M. Koizumi, R. Doi, E. Toyoda, T. Masui, S.S. Tulachan, Y. Kawaguchi, et al., Increased PDX-1 expression is associated with outcome in patients with pancreatic cancer, Surgery 134 (2) (2003) 260–266. [66] K. Quint, S. Stintzing, B. Alinger, C. Hauser-Kronberger, O. Dietze, S. Gahr, et al., The expression pattern of PDX-1, SHH, Patched and Gli-1 is associated with pathological and clinical features in human pancreatic cancer, Pancreatology 9 (1–2) (2009) 116–126. [67] X.P. Wang, Z.J. Li, J. Magnusson, F.C. Brunicardi, Tissue MicroArray analyses of pancreatic duodenal homeobox-1 in human cancers, World J. Surg. 29 (3) (2005) 334–338. [68] S. Liu, N. Ballian, N.S. Belaguli, S. Patel, M. Li, N.S. Templeton, et al., PDX-1 acts as a potential molecular target for treatment of human pancreatic cancer, Pancreas 37 (2) (2008) 210–220. [69] J.W. Nash, A. Bhardwaj, P. Wen, W.L. Frankel, Maspin is useful in the distinction of pancreatic adenocarcinoma from chronic pancreatitis: a tissue microarray based study, Appl. Immunohistochem. Mol. Morphol. 15 (1) (2007) 59–63. [70] N. Ohike, N. Maass, C. Mundhenke, M. Biallek, M. Zhang, W. Jonat, et al., Clinicopathological significance and molecular regulation of maspin expression in ductal adenocarcinoma of the pancreas, Cancer Lett. 199 (2) (2003) 193–200. [71] D. Cao, Q. Zhang, L.S. Wu, S.N. Salaria, J.W. Winter, R.H. Hruban, et al., Prognostic significance of maspin in pancreatic ductal adenocarcinoma: tissue microarray analysis of 223 surgically resected cases, Mod. Pathol. 20 (5) (2007) 570–578. [72] S.J. Cohen, R.K. Alpaugh, I. Palazzo, N.J. Meropol, A. Rogatko, Z. Xu, et al., Fibroblast activation protein and its relationship to clinical outcome in pancreatic adenocarcinoma, Pancreas 37 (2) (2008) 154–158. [73] M. Suzuoki, M. Miyamoto, K. Kato, K. Hiraoka, T. Oshikiri, Y. Nakakubo, et al., Impact of caveolin-1 expression on prognosis of pancreatic ductal adenocarcinoma, Br. J. Cancer 87 (10) (2002) 1140–1144. [74] C.P. Tanase, S. Dima, M. Mihai, E. Raducan, M.I. Nicolescu, L. Albulescu, et al., Caveolin-1 overexpression correlates with tumour progression markers in pancreatic ductal adenocarcinoma, J. Mol. Histol. 40 (1) (2009) 23–29.

ADVANCES IN PANCREATIC CANCER

173

[75] A.K. Witkiewicz, K.H. Nguyen, A. Dasgupta, E.P. Kennedy, C.J. Yeo, M.P. Lisanti, et al., Co-expression of fatty acid synthase and caveolin-1 in pancreatic ductal adenocarcinoma: implications for tumor progression and clinical outcome, Cell Cycle 7 (19) (2008) 3021–3025. [76] K. Mehta, J. Fok, F.R. Miller, D. Koul, A.A. Sahin, Prognostic significance of tissue transglutaminase in drug resistant and metastatic breast cancer, Clin. Cancer Res. 10 (23) (2004) 8068–8076. [77] A. Verma, S. Guha, H. Wang, J.Y. Fok, D. Koul, J. Abbruzzese, et al., Tissue transglutaminase regulates focal adhesion kinase/AKT activation by modulating PTEN expression in pancreatic cancer cells, Clin. Cancer Res. 14 (7) (2008) 1997–2005. [78] M. Buchholz, H. Kestler, T.M. Gress, Differential diagnosis of pancreatic tumors by molecular analysis of clinical specimens, Pancreatology 8 (6) (2008) 551–557. [79] H. Zhao, D. Mandich, R.W. Cartun, S. Ligato, Expression of K homology domain containing protein overexpressed in cancer in pancreatic FNA for diagnosing adenocarcinoma of pancreas, Diagn. Cytopathol. 35 (11) (2007) 700–704. [80] C. Rosty, L. Christa, S. Kuzdzal, W.M. Baldwin, M.L. Zahurak, F. Carnot, et al., Identification of hepatocarcinoma-intestine-pancreas/pancreatitis-associated protein I as a biomarker for pancreatic ductal adenocarcinoma by protein biochip technology, Cancer Res. 62 (6) (2002) 1868–1875. [81] A.C. Hoffmann, R. Mori, D. Vallbohmer, J. Brabender, E. Klein, U. Drebber, et al., High expression of HIF1a is a predictor of clinical outcome in patients with pancreatic ductal adenocarcinomas and correlated to PDGFA, VEGF, and bFGF, Neoplasia 10 (7) (2008) 674–679. [82] T.R. Donahue, O.J. Hines, CXCR2 and RET single nucleotide polymorphisms in pancreatic cancer, World J. Surg. 33 (4) (2009) 710–715. [83] V.F. Casneuf, P. Fonteyne, N. Van Damme, P. Demetter, P. Pauwels, B. de Hemptinne, et al., Expression of SGLT1, Bcl-2 and p53 in primary pancreatic cancer related to survival, Cancer Invest. 26 (8) (2008) 852–859. [84] K. Ohuchida, K. Mizumoto, T. Egami, H. Yamaguchi, K. Fujii, H. Konomi, et al., S100P is an early developmental marker of pancreatic carcinogenesis, Clin. Cancer Res. 12 (18) (2006) 5411–5416. [85] N.Y. Jiang, B.A. Woda, B.F. Banner, G.F. Whalen, K.A. Dresser, D. Lu, et al., A new biomarker that identifies a subset of aggressive pancreatic ductal adenocarcinoma, Cancer Epidemiol. Biomark. Prev. 17 (7) (2008) 1648–1652. [86] J. Chen, D. Li, A.M. Killary, S. Sen, C.I. Amos, D.B. Evans, et al., Polymorphisms of p16, p27, p73, and MDM2 modulate response and survival of pancreatic cancer patients treated with preoperative chemoradiation, Ann. Surg. Oncol. 16 (2) (2009) 431–439. [87] C. Reiser-Erkan, M. Erkan, Z. Pan, S. Bekasi, N.A. Giese, S. Streit, et al., Hypoxiainducible proto-oncogene Pim-1 is a prognostic marker in pancreatic ductal adenocarcinoma, Cancer Biol. Ther. 7 (9) (2008) 1352–1359. [88] Z.E. Karanjawala, P.B. Illei, R. Ashfaq, J.R. Infante, K. Murphy, A. Pandey, et al., New markers of pancreatic cancer identified through differential gene expression analyses: claudin 18 and annexin A8, Am. J. Surg. Pathol. 32 (2) (2008) 188–196. [89] H. Matsubayashi, M. Canto, N. Sato, A. Klein, T. Abe, K. Yamashita, et al., DNA methylation alterations in the pancreatic juice of patients with suspected pancreatic disease, Cancer Res. 66 (2) (2006) 1208–1217. [90] R. Chen, S. Pan, T.A. Brentnall, R. Aebersold, Proteomic profiling of pancreatic cancer for biomarker discovery, Mol. Cell. Proteomics 4 (4) (2005) 523–533.

174

TANASE ET AL.

[91] R. Chen, E.C. Yi, S. Donohoe, S. Pan, J. Eng, K. Cooke, et al., Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape, Gastroenterology 129 (4) (2005) 1187–1197. [92] T. Crnogorac-Jurcevic, R. Gangeswaran, V. Bhakta, G. Capurso, S. Lattimore, M. Akada, et al., Proteomic analysis of chronic pancreatitis and pancreatic adenocarcinoma, Gastroenterology 129 (5) (2005) 1454–1463. [93] K.H. Yu, A.K. Rustgi, I.A. Blair, Characterization of proteins in human pancreatic cancer serum using differential gel electrophoresis and tandem mass spectrometry, J. Proteome Res. 4 (5) (2005) 1742–1751. [94] J.M. Koomen, L.N. Shih, K.R. Coombes, D. Li, L.C. Xiao, I.J. Fidler, et al., Plasma protein profiling for diagnosis of pancreatic cancer reveals the presence of host response proteins, Clin. Cancer Res. 11 (3) (2005) 1110–1118. [95] M. Ehmann, K. Felix, D. Hartmann, M. Schnolzer, M. Nees, S. Vorderwulbecke, et al., Identification of potential markers for the detection of pancreatic cancer through comparative serum protein expression profiling, Pancreas 34 (2) (2007) 205–214. [96] T. Qi, J. Han, Y. Cui, M. Zong, X. Liu, B. Zhu, Comparative proteomic analysis for the detection of biomarkers in pancreatic ductal adenocarcinomas, J. Clin. Pathol. 61 (1) (2008) 49–58. [97] X. Zhang, E. Galardi, M. Duquette, J. Lawler, S. Parangi, Antiangiogenic treatment with three thrombospondin-1 type 1 repeats versus gemcitabine in an orthotopic human pancreatic cancer model, Clin. Cancer Res. 11 (15) (2005) 5622–5630. [98] G. Bellone, A. Novarino, I. Chiappino, C. Gramigni, A. Carbone, A. Addeo, et al., Circulating vascular endothelial growth factor and interferon-gamma-inducible protein10 levels in pancreatic cancer during chemotherapy, Anticancer Res. 25 (5) (2005) 3287–3291. [99] Y. Seo, H. Baba, T. Fukuda, M. Takashima, K. Sugimachi, High expression of vascular endothelial growth factor is associated with liver metastasis and a poor prognosis for patients with ductal pancreatic adenocarcinoma, Cancer 88 (10) (2000) 2239–2245. [100] R. Derynck, J.A. Jarrett, E.Y. Chen, D.H. Eaton, J.R. Bell, R.K. Assoian, et al., Human transforming growth factor-beta complementary DNA sequence and expression in normal and transformed cells, Nature 316 (6030) (1985) 701–705. [101] E. Glynne-Jones, M.E. Harper, L. Goddard, C.L. Eaton, P.N. Matthews, K. Griffiths, Transforming growth factor beta 1 expression in benign and malignant prostatic tumors, Prostate 25 (4) (1994) 210–218. [102] H. Yang, Z. Filipovic, D. Brown, S.N. Breit, L.T. Vassilev, Macrophage inhibitory cytokine-1: a novel biomarker for p53 pathway activation, Mol. Cancer Ther. 2 (10) (2003) 1023–1029. [103] S. Shimoyama, F. Gansuage, S. Gansauge, G. Negri, T. Oohara, H.G. Beger, Increased angiogenin expression in pancreatic cancer is related to cancer aggressiveness, Cancer Res. 56 (2003) 2703–2706. [104] H.E. Mulcahy, J. Lyautey, C. Lederrey, X. qi Chen, P. Anker, E.M. Alstead, et al., A prospective study of K-ras mutations in the plasma of pancreatic cancer patients, Clin. Cancer Res. 4 (2) (1998) 271–275. [105] T. Yamada, S. Nakamori, H. Ohzato, S. Oshima, T. Aoki, N. Higaki, et al., Detection of K-ras gene mutations in plasma DNA of patients with pancreatic adenocarcinoma: correlation with clinicopathological features, Clin. Cancer Res. 4 (6) (1998) 1527–1532. [106] J. Heidemann, D.G. Binion, W. Domschke, T. Kucharzik, Antiangiogenic therapy in human gastrointestinal malignancies, Gut. 55 (2006) 1497–1511. [107] P. Bu¨chler, H.A. Reber, M.W. Bu¨chler, H. Friess, O.J. Hines, VEGF-RII influences the prognosis of pancreatic cancer, Ann. Surg. 236 (2002) 738–749.

ADVANCES IN PANCREATIC CANCER

175

[108] J. Rohloff, J. Zinke, K. Schoppmeyer, A. Tannapfel, H. Witzigmann, J. Mossner, et al., Heparanase expression is a prognostic indicator for postoperative survival in pancreatic adenocarcinoma, Br. J. Cancer 22 (2002) 1270–1275. [109] E.K. Kim, S. Xu, E.F. Hollinger, P. Gattuso, C.V. Godellas, R.A. Prinz, et al., Human heparanase-1 gene expression in pancreatic cancer, J. Gastrointest. Surg. 6 (2002) 167–172. [110] U. Kasper, M. Ebert, P. Malfertheiner, A. Roessner, C.J. Kirkpatrick, H.K. Wolf, Expression of thrombospondin-1 in pancreatic carcinoma: correlation with microvessel density, Virchows Arch. 438 (2001) 116–120. [111] X. Qian, V.L. Rothman, R.F. Nicosia, G.P. Tuszynski, Expression of thrombosponind-1 in human pancreatic adenocarcinomas: role of matrix metalloproteinase-9 production, Pathol. Oncol. Res. 7 (2001) 251–259. [112] K. Tobita, H. Kijima, S. Dowaki, Y. Oida, H. Kashiwagi, M. Ishii, Thrombospondin-1 expression as a prognostic predictor of pancreatic ductal carcinoma, Int. J. Oncol. 21 (2002) 1189–1195. [113] M. Niedergethmann, R. Hildenbrand, G. Wolf, C.S. Verbeke, A. Richter, S. Post, Angiogenesis and cathepsin expression are prognostic factors in pancreatic adenocarcinoma after curative resection, Int. J. Pancreatol. 28 (2000) 31–39. [114] S.R. Harvey, T.C. Hurd, G. Markus, M.I. Martinick, R.M. Penetrante, D. Tan, et al., Evaluation of urinary plasminogen activator, its receptor matrix metalloproteinase-9 and von Willebrand factor in pancreatic cancer, Clin. Cancer Res. 15 (2003) 4935–4943. [115] R. Tomaszewska, K. Nowak, J. Stachura, CD44 isoforms expression in intraductal and invasive pancreatic cancer and its correlation to p53 gene mutations, Pol. J. Pathol. 50 (1999) 145–153. [116] C. Tanase, CAV1 (caveolin 1, caveolae protein, 22 kDa), Atlas Genet. Cytogenet. Oncol. Haematol. (2008) December http://AtlasGeneticsOncology.org/Genes/CAV1ID932ch7q31. html. [117] K. Kashima, N. Ohike, S. Mukai, M. Sato, M. Takahashi, T. Morohoshi, Expression of the tumor suppressor gene maspin and its significance in intraductal papillary mucinous neoplasms of the pancreas, Hepatobiliary Pancreat. Dis. Int. 7 (1) (2008) 86–90. [118] T. Liu, S.M. Gou, C.Y. Wang, H.S. Wu, J.X. Xiong, F. Zhou, Pancreas duodenal homeobox-1 expression and significance in pancreatic cancer, World J. Gastroenterol. 13 (18) (2007) 2615–2618. [119] A.D. Toll, A.K. Witkiewicz, M. Bibbo, Expression of K homology domain containing protein (KOC) in pancreatic cytology with corresponding histology, Acta Cytol. 53 (2) (2009) 123–129. [120] Q. Qiao, M. Ramadani, S. Gansauge, F. Gansauge, G. Leder, H.G. Beger, Reduced membranous and ectopic cytoplasmic expression of beta-catenin correlate with cyclin D1 overexpression and poor prognosis in pancreatic cancer, Int. J. Cancer 95 (2001) 194–197. [121] Y.J. Li, X.R. Ji, Relationship between the expression of betacatenin, cyclin D1 and myc and the occurrence and biological behaviour of pancreatic cancer, Zhonghua Bing Li Xue Za Zhi 32 (2003) 238–241. [122] K. Julkunen, K. Makinen, V. Karja, V.M. Kosma, M. Eskelinen, alpha, beta and chicatenin expression in human pancreatic cancer, Anticancer Res. 23 (2003) 5043–5047. [123] A.M. Lowy, C. Fenoglio-Preiser, O.J. Kim, J. Kordich, A. Gomez, J. Knight, Dysregulation of beta-catenin expression correlates with tumour differentiation in pancreatic duct adenocarcinoma, Ann. Surg. Oncol. 10 (2003) 284–290. [124] M. Cohenuram, M.W. Saif, Epidermal growth factor receptor inhibition strategies in pancreatic cancer: past, present and the future, JOP 8 (1) (2007) 4–15.

176

TANASE ET AL.

[125] N.A. Pham, J. Schwock, V. Iakovlev, G. Pond, D.W. Hedley, M.S. Tsao, Immunohistochemical analysis of changes in signaling pathway activation downstream of growth factor receptors in pancreatic duct cell carcinogenesis, BMC Cancer 8 (2008) 43. [126] J.J. Liang, H. Wang, A. Rashid, T.H. Tan, R.F. Hwang, S.R. Hamilton, et al., Expression of MAP4K4 is associated with worse prognosis in patients with stage II pancreatic ductal adenocarcinoma, Clin. Cancer Res. 14 (21) (2008) 7043–7049. [127] M.T. Yip-Schneider, A. Lin, M.S. Marshall, Pancreatic tumor cells with mutant K-ras suppress ERK activity by MEK-dependent induction of MAP kinase phosphatase-2, Biochem. Biophys. Res. Commun. 280 (4) (2001) 992–997. [128] Z. Wang, R. Sengupta, S. Banerjee, Y. Li, Y. Zhang, K.M. Rahman, et al., Epidermal growth factor receptor-related protein inhibits cell growth and invasion in pancreatic cancer, Cancer Res. 66 (15) (2006) 7653–7660. [129] P.M. Siegel, J. Massague, Cytostatic and apoptotic actions of TGF-beta in homeostasis and cancer, Nat. Rev. Cancer 3 (11) (2003) 807–821. [130] S. Zhao, K. Venkatasubbarao, J.W. Lazor, J. Sperry, C. Jin, L. Cao, et al., Inhibition of STAT3 Tyr705 phosphorylation by Smad4 suppresses transforming growth factor betamediated invasion and metastasis in pancreatic cancer cells, Cancer Res. 68 (11) (2008) 4221–4228. [131] G. Yang, X. Yang, Smad4-mediated TGF-beta signaling in tumorigenesis, Int. J. Biol. Sci. 6 (1) (2010) 1–8. [132] E.M. Jaffee, R.H. Hruban, M. Canto, S.E. Kern, Focus on pancreas cancer, Cancer Cell 2 (1) (2002) 25–28. [133] J.N. Kloth, G.G. Kenter, H.S. Spijker, S. Uljee, W.E. Corver, E.S. Jordanova, et al., Expression of Smad2 and Smad4 in cervical cancer: absent nuclear Smad4 expression correlates with poor survival, Mod. Pathol. 21 (7) (2008) 866–875. [134] P. Ghaneh, W. Greenhalf, M. Humphreys, D. Wilson, L. Zumstein, N.R. Lemoine, et al., Adenovirus-mediated transfer of p53 and p16 (INK4a) results in pancreatic cancer regression in vitro and in vivo, Gene Ther. 8 (2001) 199–208. [135] J. Calbo, C. Serna, J. Garriga, X. Grana, A. Mazo, The fate of pancreatic tumor cell lines following p16 overexpression depends on the modulation of CDK2 activity, Cell Death Differ. 11 (2004) 1055–1065. [136] P.M. Campbell, K.M. Lee, M.M. Ouellette, H.J. Kim, A.L. Groehler, V. Khazak, et al., Ras driven transformation of human nestin-positive pancreatic epithelial cells, Methods Enzymol. 439 (2008) 451–465. [137] P.M. Campbell, A.L. Groehler, K.M. Lee, M.M. Ouellette, V. Khazak, C.J. Der, K-ras promotes growth transformation and invasion of immortalized human pancreatic cells by Raf and phosphatidylinositol 3-kinase signaling, Cancer Res. 67 (2007) 2098–2106. [138] K.H. Lim, K. O’Hayer, S.J. Adam, S.D. Kendall, P.M. Campbell, C.J. Der, et al., Divergent roles for RalA and RalB in malignant growth of human pancreatic carcinoma cells, Curr. Biol. 16 (2006) 2385–2394. [139] J. Massague, S.W. Blain, R.S. Lo, TGF beta signaling in growth control, cancer, and heritable disorders, Cell 103 (2) (2000) 295–309. [140] A. Norris, M. Korc, Smad4-TGF-b pathways in pancreatic cancer Translational Implications, in: J.P. Neoptolemos, R.A. Urrutia, J. Abbruzzese, M.W. Bu¨chler (Eds.), Pancreatic Cancer, Springer-Verlag, Berlin, Heidelberg, 2009978-0-387-77497-8, pp. 2–15 Ch. 14. [141] H. Friess, Y. Yamanaka, M. Buchler, M. Ebert, H.G. Beger, L.I. Gold, et al., Enhanced expression of transforming growth factor beta isoforms in pancreatic cancer correlates with decreased survival, Gastroenterology 105 (6) (1993) 1846–1856. [142] S.B. Jakowlew, Transforming growth factor-beta in cancer and metastasis, Cancer Metastasis Rev. 25 (3) (2006) 435–457.

ADVANCES IN PANCREATIC CANCER

177

[143] J. Lau, H. Kawahira, M. Hebrok, Hedgehog signaling in pancreas development and disease, Cell. Mol. Life Sci. 63 (6) (2006) 642–652. [144] Z. Wang, Q. Ma, Beta-catenin is a promising key factor in the SDF-1/CXCR4 axis on metastasis of pancreatic cancer, Med. Hypotheses 69 (4) (2007) 816–820. [145] M. Pasca di Magliano, A.V. Biankin, P.W. Heiser, D.A. Cano, P.J. Gutierrez, T. Deramaudt, et al., Common activation of canonical Wnt signaling in pancreatic adenocarcinoma, PLoS ONE 2 (2007) e1155. [146] P. Sanchez, A.M. Hernandez, B. Stecca, A.J. Kahler, A.M. DeGueme, A. Barrett, et al., Inhibition of prostatecancer proliferation by interference with SONIC HEDGEHOGGLI1 signaling, Proc. Natl Acad. Sci. USA 101 (34) (2004) 12561–12566. [147] J.M. Bailey, A.M. Mohr, M.A. Hollingsworth, Sonic hedgehog paracrine signaling regulates metastasis and lymphangiogenesis in pancreatic cancer, Oncogene 28 (40) (2009) 3513–3525. [148] K. Xie, J.L. Abbruzzese, Developmental biology informs cancer: the emerging role of the hedgehog signaling pathway in upper gastrointestinal cancers, Cancer Cell 4 (2003) 245–247. [149] S.P. Thayer, M. Pasca di Magliano, P.W. Heiser, C.M. Nielsen, D.J. Roberts, G.Y. Lauwers, et al., Hedgehog is an early and late mediator of pancreatic cancer tumorigenesis, Nature 425 (6960) (2003) 851–856. [150] D.M. Berman, S.S. Karhadkar, A. Maitra, R. Montes De Oca, M.R. Gerstenblith, K. Briggs, et al., Widespread requirement for Hedgehog ligand stimulation in growth of digestive tract tumours, Nature 425 (2003) 846–851. [151] K. Ohuchida, K. Mizumoto, H. Fujita, H. Yamaguchi, H. Konomi, E. Nagai, et al., Sonic hedgehog is an early developmental marker of intraductal papillary mucinous neoplasms: clinical implications of mRNA levels in pancreatic juice, J. Pathol. 210 (1) (2006) 42–48. [152] M. Mimeault, R.E. Brand, A.A. Sasson, Batra SK Recent advances on the molecular mechanisms involved in pancreatic cancer progression and therapies, Pancreas 31 (2005) 301–316. [153] Z. Wang, Y. Zhang, S. Banerjee, Y. Li, F.H. Sarkar, Notch-1 down-regulation by curcumin is associated with the inhibition of cell growth and the induction of apoptosis in pancreatic cancer cells, Cancer 106 (2006) 2503–2513. [154] Z. Wang, Y. Zhang, S. Banerjee, Y. Li, F.H. Sarkar, Inhibition of nuclear factor kappab activity by genistein is mediated via Notch-1 signaling pathwayin pancreatic cancer cells, Int. J. Cancer 118 (2006) 1930–1936. [155] K. Makinen, T. Hakala, P. Lipponen, E. Alhava, M. Eskelinen, Clinical contribution of bcl-2, p53 and Ki-67 proteins in pancreatic ductal adenocarcinoma, Anticancer Res. 18 (1998) 615–618. [156] F.A. Sinicrope, D.B. Evans, S.D. Leach, K.R. Cleary, C.J. Fenoglio, J.J. Lee, et al., bcl-2 and p53 expression in resectable pancreatic adenocarcinomas: association with clinical outcome, Clin. Cancer Res. 2 (1996) 2015–2022. [157] J. Sharma, R. Srinivasan, S. Majumdar, S. Mir, B.D. Radotra, J.D. Wig, Bcl-XL protein levels determine apoptotic index in pancreatic carcinoma, Pancreas 30 (2005) 337–342. [158] C.Y. Sun, B.L. Wang, C.Q. Hu, R.Y. Peng, Y.B. Gao, Q.Y. Gu, et al., Expression of the bcl-2 gene and its significance in human pancreatic cancer, Hepatobiliary Pancreat. Dis. Int. 1 (2002) 306–308. [159] Y. Nio, C. Iguchi, K. Yamasawa, S. Sasaki, M. Takamura, T. Toga, et al., Apoptosis and expression of Bcl-2 and Bax proteins in invasive ductal carcinoma of the pancreas, Pancreas 22 (2001) 230–239.

178

TANASE ET AL.

[160] J.D. Evans, P.A. Cornford, A. Dodson, W. Greenhalf, C.S. Foster, J.P. Neoptolemos, Detailed tissue expression of bcl-2, bax, bak and bcl-x in the normal human pancreas and chronic pancreatitis, ampullary and pancreatic ductal adenocarcinomas, Pancreatology 1 (2001) 254–262. [161] D. Campani, I. Esposito, U. Boggi, D. Cecchetti, M. Menicagli, F. De Negri, et al., Bcl-2 expression in pancreas development and pancreatic cancer progression, J. Pathol. 194 (2001) 444–450. [162] H. Friess, Z. Lu, H.U. Graber, A. Zimmermann, G. Adler, M. Korc, et al., Bax, but not bcl-2, influences the prognosis of human pancreatic cancer, Gut 43 (1998) 414–421. [163] P. Magistrelli, R. Coppola, G. Tonini, B. Vincenzi, D. Santini, D. Borzomati, et al., Apoptotic index or a combination of Bax/Bcl-2 expression correlate with survival after resection of pancreatic adenocarcinoma, J. Cell. Biochem. 97 (2006) 98–108. [164] R.B. Lopes, R. Gangeswaran, I.A. McNeish, Y. Wang, N.R. Lemoine, Expression of the IAP protein family is dysregulated in pancreatic cancer cells and is important for resistance to chemotherapy, Int. J. Cancer 120 (2007) 2344–2352. [165] K. Kami, R. Doi, M. Koizuma, E. Toyoda, T. Mori, D. Ito, et al., Survivin expression is a prognostic marker in pancreatic cancer patients, Surgery 136 (2004) 443–448. [166] J.G. Qiao, Y.Q. Zhang, Y.C. Yin, Z. Tan, Expression of survivin in pancreatic cancer and its correlation to expression of Bcl-2, World J. Gastroenterol. 10 (2004) 2759–2761. [167] A.I. Sarela, C.S. Verbeke, J. Ransdale, C.L. Davies, A.F. Markham, P.J. Guillou, et al., Expression of survivin, a novel inhibitor of apoptosis and cell cycle regulatory protein, in pancreatic adenocarcinoma, Br. J. Cancer 86 (2002) 886–892. [168] F. Ozawa, H. Friess, J. Kleeff, Z.W. Xu, A. Zimmermann, M.S. Sheikh, et al., Effects and expression of TRAIL and its apoptosis-promoting receptors in human pancreatic cancer, Cancer Lett. 163 (2001) 71–81. [169] T.L. Whiteside, The role of death receptor ligands in shaping tumor microenvironment, Immunol. Invest. 36 (2007) 25–46. [170] W. Wang, J.L. Abbruzzese, D.B. Evans, L. Larry, K.R. Cleary, P.J. Chiao, The nuclear factor-kappa B RelA transcription factor is constitutively activated in human pancreatic adenocarcinoma cells, Clin. Cancer Res. 5 (1999) 119–127. [171] A.B. Kunnumakkara, S. Guha, S. Krishnan, P. Diagaradjane, J. Gelovani, B.B. Aggarwal, Curcumin potentiates antitumor activity of gemcitabine in an orthotopic model of pancreatic cancer through suppression of proliferation, angiogenesis, and inhibition of nuclear factor-kappaB-regulated gene products, Cancer Res. 67 (2007) 3853–3861. [172] S.A. Lang, P. Schachtschneider, C. Moser, A. Mori, C. Hackl, A. Gaumann, et al., Dual targeting of Raf and VEGF receptor 2 reduces growth and metastasis of pancreatic cancer through direct effects on tumor cells, endothelial cells, and pericytes, Mol. Cancer Ther. 7 (11) (2008) 3509–3518. [173] S.E. DePrimo, C. Bello, Surrogate biomarkers in evaluating response to anti-angiogenic agents: focus on sunitinib, Ann. Oncol. (Suppl. 10) (2007) x11–x19. [174] S.E. Deprimo, C.L. Bello, J. Smeraglia, C.M. Baum, D. Spinella, B.I. Rini, et al., Circulating protein biomarkers of pharmacodynamic activity of sunitinib in patients with metastatic renal cell carcinoma: modulation of VEGF and VEGF-related proteins, J. Transl. Med. 5 (2007) 32. [175] M.S. Pino, M. Shrader, C.H. Baker, F. Cognetti, H.Q. Xiong, J.L. Abbruzzese, et al., Transforming growth factor alpha expression drives constitutive epidermal growth factor receptor pathway activation and sensitivity to gefitinib (Iressa) in human pancreatic cancer cell lines, Cancer Res. 66 (2006) 3802–3812.

ADVANCES IN PANCREATIC CANCER

179

[176] A.M. Senderowicz, J.R. Johnson, R. Sridhara, P. Zimmerman, R. Justice, R. Pazdur, et al., Erlotinib/gemcitabine for first-line treatment of locally advanced or metastatic adenocarcinoma of the pancreas, Oncology (Williston Park) 21 (2007) 1696–1706, discussion 706–709, 712, 715. [177] S.T. Nawrocki, J.S. Carew, M.S. Pino, R.A. Highshaw, K. Dunner, Jr., P. Huang, et al., Bortezomib sensitizes pancreatic cancer cells to endoplasmic reticulum stress-mediated apoptosis, Cancer Res. 65 (2005) 11658–11666. [178] A. Marten, N. Zeiss, S. Serba, S. Mehrle, M. von Lilienfeld-Toal, J. Schmidt, Bortezomib is ineffective in an orthotopic mouse model of pancreatic adenocarcinoma, Mol. Cancer Ther. 7 (2008) 3624–3631. [179] N. Dhillon, B.B. Aggarwal, R.A. Newman, R.A. Wolff, A.B. Kunnumakkara, J. L. Abbruzzese, et al., Phase II trial of curcumin in patients with advanced pancreatic cancer, Clin. Cancer Res. 14 (2008) 4491–4499. [180] S.A. Brunton, J.H. Stibbard, L.L. Rubin, L.I. Kruse, O.M. Guicherit, E.A. Boyd, et al., Potent inhibitors of the hedgehog signaling pathway, J. Med. Chem. 51 (5) (2008) 1108–1110. [181] J. Lee, X. Wu, M. Pasca di Magliano, E.C. Peters, A small-molecule antagonist of the hedgehog signaling pathway, Chembiochem 8 (16) (2007) 1916–1919. [182] J. Albanell, P. Gascon, Small molecules with EGFR-TK inhibitor activity, Curr Drug Targets 6 (3) (2005) 259–274. [183] V. Giroux, J.C. Dagorn, J.L. Iovanna, A review of kinases implicated in pancreatic cancer, Pancreatology 9 (6) (2010) 738–754. [184] U. Distler, J. Souady, M. Hulsewig, I. Drmic-Hofman, J. Haier, A. Denz, et al., Tumorassociated CD75s- and iso-CD75s-gangliosides are potential targets for adjuvant therapy in pancreatic cancer, Mol. Cancer Ther. 7 (8) (2008) 2464–2475. [185] C. Li, D.M. Simeone, D.E. Brenner, M.A. Anderson, K.A. Shedden, M.T. Ruffin, et al., Pancreatic cancer serum detection using a lectin/glyco-antibody array method, J. Proteome Res. 8 (2) (2009) 483–492. [186] C.M. Parsons, J.L. Sutcliffe, R.J. Bold, Preoperative evaluation of pancreatic adenocarcinoma, J. Hepatobiliary Pancreat Surg. 15 (2008) 429–435. [187] N. Kondo, Y. Murakami, K. Uemura, Y. Hayashidani, T. Sudo, Y. Hashimoto, et al., Prognostic impact of perioperative serum CA 19-9 levels in patients with resectable pancreatic cancer, Ann. Surg. Oncol. (2010) (Epub ahead of print). [188] W.S. Koom, J. Seong, Y.B. Kim, H.O. Pyun, S.Y. Song, CA 19-9 as a predictor for response and survival in advanced pancreatic cancer patients treated with chemoradiotherapy, Int. J. Radiat. Oncol. Biol. Phys. 73 (4) (2009) 1148–1154. [189] T. Itoi, K. Takei, A. Sofuni, F. Itokawa, T. Tsuchiya, T. Kurihara, et al., Immunohistochemical analysis of p53 and MIB-1 in tissue specimens obtained from endoscopic ultrasonography-guided fine needle aspiration biopsy for the diagnosis of solid pancreatic masses, Oncol. Rep. 13 (2) (2005) 229–234. [190] S.T. Chang, J.M. Zahn, J. Horecka, P.L. Kunz, J.M. Ford, G.A. Fisher, et al., Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis, J. Transl. Med. 7 (2009) 105. [191] S. Bussom, M.W. Saif, Methods and rationale for the early detection of pancreatic cancer, JOP J. Pancreas (online) 11 (2) (2010) 128–130. [192] T. Shimamoto, M. Tani, M. Kawai, S. Hirono, S. Ina, M. Miyazawa, et al., MUC1 is a useful molecular marker for malignant intraductal papillary mucinous neoplasms in pancreatic juice obtained from endoscopic retrograde pancreatography, Pancreas (2010) (Epub ahead of print).

180

TANASE ET AL.

[193] K. Takahashi, K. Yamao, K. Okubo, A. Sawaki, N. Mizuno, R. Ashida, et al., Differential diagnosis of pancreatic cancer and focal pancreatitis by using EUS-guided FNA, Gastrointest. Endosc. 61 (1) (2005) 76–79. [194] M.T. Joergensen, N. Bru¨nner, O.B. De Muckadell, Comparison of circulating MMP-9, TIMP-1 and CA19-9 in the detection of pancreatic cancer, Anticancer Res. 30 (2) (2010) 587–592. [195] F. Navaglia, P. Fogar, D. Basso, E. Greco, A. Padoan, L. Tonidandel, et al., Pancreatic cancer biomarkers discovery by surface-enhanced laser desorption and ionization time-offlight mass spectrometry, Clin. Chem. Lab. Med. 47 (2009) 713–723. [196] J. Koopmann, Z. Zhang, N. White, J. Rosenzweig, N. Fedarko, S. Jagannath, et al., Serum diagnosis of pancreatic adenocarcinoma using surface-enhanced laser desorption and ionization mass spectrometry, Clin. Cancer Res. 10 (3) (2004) 860–868. [197] M.A. Firpo, D.Z. Gay, S.R. Granger, C.L. Scaife, J.A. DiSario, K.M. Boucher, et al., Improved diagnosis of pancreatic adenocarcinoma using haptoglobin and serum amyloid A in a panel screen, World J. Surg. 33 (4) (2009) 716–722. [198] C.J. Scarlett, R.C. Smith, A. Saxby, A. Nielsen, J.S. Samra, S.R. Wilson, et al., Proteomic classification of pancreatic adenocarcinoma tissue using protein chip technology, Gastroenterology 130 (6) (2006) 1670–1678. [199] T. Okazaki, L. Jiao, P. Chang, D.B. Evans, J.L. Abbruzzese, D. Li, Single-nucleotide polymorphisms of DNA damage response genes are associated with overall survival in patients with pancreatic cancer, Clin. Cancer Res. 14 (7) (2008) 2042–2048. [200] E.J. Lee, Y. Gusev, J. Jiang, G.J. Nuovo, M.R. Lerner, W.L. Frankel, et al., Expression profiling identifies microRNA signature in pancreatic cancer, Int. J. Cancer 120 (2007) 1046–1054. [201] C. Roldo, E. Missiaglia, J.P. Hagan, M. Falconi, P. Capelli, S. Bersani, et al., MicroRNA expression abnormalities in pancreatic endocrine and acinar tumors are associated with distinctive pathologic features and clinical behavior, J. Clin. Oncol. 24 (2006) 4677–4684. [202] A.E. Szafranska, T.S. Davison, J. John, T. Cannon, B. Sipos, A. Maghnouj, et al., MicroRNA expression alterations are linked to tumorigenesis and non-neoplastic processes in pancreatic ductal adenocarcinoma, Oncogene 26 (2007) 4442–4452. [203] S. Rachagani, S. Kumar, K.B. Surinder, MicroRNA in pancreatic cancer: pathological, diagnostic and therapeutic implications, Cancer Lett. 292 (1) (2010) 8–16. [204] M. Gronborg, T.Z. Kristiansen, A. Iwahori, R. Chang, R. Reddy, N. Sato, et al., Biomarker discovery from pancreatic cancer secretome using a differential proteomic approach, Mol. Cell. Proteomics 5 (1) (2006) 157–171. [205] A. Walch, S. Rauser, S.O. Deininger, H. Hofler, MALDI imaging mass spectrometry for direct tissue analysis: a new frontier for molecular histology, Histochem. Cell Biol. 130 (3) (2008) 421–434. [206] L.H. Cazares, J.I. Diaz, R.R. Drake, O.J. Semmes, MALDI/SELDI protein profiling of serum for the identification of cancer biomarkers, Methods Mol. Biol. 428 (2008) 125–140. [207] V. Kulasingam, E.P. Diamandis, Strategies for discovering novel cancer biomarkers through utilization of emerging technologies, Nat. Clin. Pract. Oncol. 5 (10) (2008) 588–599.