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Review

Matrix Metalloproteases in Pancreatic Ductal Adenocarcinoma: Key Drivers of Disease Progression?

by
Etienne J. Slapak
1,2,3,
JanWillem Duitman
1,2,
Cansu Tekin
1,2,3,
Maarten F. Bijlsma
2,3 and
C. Arnold Spek
1,2,*
1
Center of Experimental and Molecular Medicine, University of Amsterdam, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
2
Laboratory for Experimental Oncology and Radiobiology, Cancer Center Amsterdam, University of Amsterdam, Amsterdam UMC, 1105 AZ Amsterdam, The Netherlands
3
Oncode Institute, 1105 AZ Amsterdam, The Netherlands
*
Author to whom correspondence should be addressed.
Biology 2020, 9(4), 80; https://doi.org/10.3390/biology9040080
Submission received: 26 March 2020 / Revised: 15 April 2020 / Accepted: 15 April 2020 / Published: 18 April 2020
(This article belongs to the Special Issue Proteases—From Basic Structure to Function to Drug Design as Targeted Therapy)
Browse Figure
Versions Notes

Abstract

:
Pancreatic cancer is a dismal disorder that is histologically characterized by a dense fibrotic stroma around the tumor cells. As the extracellular matrix comprises the bulk of the stroma, matrix degrading proteases may play an important role in pancreatic cancer. It has been suggested that matrix metalloproteases are key drivers of both tumor growth and metastasis during pancreatic cancer progression. Based upon this notion, changes in matrix metalloprotease expression levels are often considered surrogate markers for pancreatic cancer progression and/or treatment response. Indeed, reduced matrix metalloprotease levels upon treatment (either pharmacological or due to genetic ablation) are considered as proof of the anti-tumorigenic potential of the mediator under study. In the current review, we aim to establish whether matrix metalloproteases indeed drive pancreatic cancer progression and whether decreased matrix metalloprotease levels in experimental settings are therefore indicative of treatment response. After a systematic review of the studies focusing on matrix metalloproteases in pancreatic cancer, we conclude that the available literature is not as convincing as expected and that, although individual matrix metalloproteases may contribute to pancreatic cancer growth and metastasis, this does not support the generalized notion that matrix metalloproteases drive pancreatic ductal adenocarcinoma progression.

1. Introduction

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with the worst survival outcome of any cancer [1]. Its incidence, which is around 10 per 100,000 individuals, is rising in developed countries [2,3], with 458 thousand new cases and 432 thousand deaths in 2018 worldwide [4]. The 5-year survival rate is around 9%, and the 10-year mortality is approaching 99% [5]. Progress towards improving survival has been slow, and current treatment options are inadequate. The only significant progress that has been made is in the form of lower mortality rates for patients eligible for resections, and a slight prolongation and improved quality of life in patients with inoperable disease with the use of chemotherapeutic agents. Single-agent gemcitabine treatment has been the standard of care for inoperable PDAC for many years, although the observed benefits are small in daily practice [6,7,8,9] and seem restricted to patients with a good performance status [10]. More recently, nanoparticle albumin-bound paclitaxel was shown to exert superior antitumor activity compared to gemcitabine monotherapy, thereby establishing nab-paclitaxel and gemcitabine combination therapy as first-line chemotherapy regimens in PDAC [11]. In patients with a good performance status, combination therapy with folinic acid, fluorouracil, irinotecan and oxaliplatin (FOLFIRINOX) is superior over other treatments [12] and FOLFIRINOX is consequently emerging as the new standard of care for relatively fit patients [13]. Importantly however, even in the specific group of patients eligible for FOLFIRINOX treatment, the survival benefit is limited [14].

1.1. Tumor Microenvironment of PDAC

PDAC is characterized by a strong desmoplastic reaction, which results in an archetypal tumor microenvironment, consisting of a dense stroma surrounding the tumor cells [15,16]. The stroma forms the bulk of the tumor, taking up to 90% of the total tumor mass and consists of many cellular and acellular components like (myo)fibroblasts, macrophages, blood vessels and extracellular matrix components such as, among others, collagen I, collagen IV, laminin and fibronectin. In the stroma, the extracellular matrix has traditionally been considered to be a stable structure that mainly plays a supportive role in maintaining tissue morphology. Nowadays, however, it is evident that the extracellular matrix forms a dynamic and versatile milieu that affects the fundamental processes of the surrounding cells [17,18]. Accordingly, the loss of extracellular matrix homeostasis and integrity is considered one of the hallmarks of cancer and typically defines transitional events, resulting in cancer progression and metastasis [19]. Moreover, the loss of extracellular matrix homeostasis due to stromal depletion aggravates pancreatic cancer progression in preclinical animal models [20,21,22].

1.2. Matrix Metalloproteases in the Tumor Microenvironment

The desmoplastic PDAC stroma contains many different proteases that play a key role in the crosstalk between tumor and stromal cells. An intriguing group of proteases in the tumor microenvironment consist of matrix metalloproteases (MMPs), which are primarily known for their ability to degrade extracellular matrix components. Altered expression and/or activity of MMPs in the tumor microenvironment is likely to lead to the loss of homeostasis of the extracellular matrix, thereby driving PDAC progression. Based upon this notion, MMPs are considered important contributors to PDAC progression and experimental PDAC studies frequently use MMPs as surrogate markers for treatment responses. Decreased MMP levels are, nowadays, considered as important signs of the anti-tumorigenic potential of the gene/compound/miRNA under study. In the current review, we address whether the literature supports the concept that MMPs drive PDAC progression and if decreased MMP levels under experimental settings are indicative of the treatment response. To this end, we performed a systematic review of patient and experimental animal studies, focusing on MMPs in PDAC.

1.3. Overview of Matrix Metalloproteases

MMPs are calcium-dependent zinc-containing endopeptidases of the metzincin protease superfamily. They typically contain an N-terminal propeptide of approximately 80–90 amino acids, with a conserved PRCGXPD motif that is responsible for maintaining latency via the binding of the cysteine residue to the zinc atom in the active site [23]. After the proteolytic removal of the propeptide, the active form of MMP contains a calcium-dependent catalytic domain of around 200 amino acids, which contains a hydrophobic S1′-pocket that determines substrate specificity, proceeded by a linker region of variable length, and the C-terminal hemopexin-like domain, which spans approximately 200 amino acids. The hemopexin-like domain, which is absent in some MMP family members, plays a functional role in substrate binding and/or in interactions with tissue inhibitors of metalloproteases (TIMPs), a family of specific MMP protein inhibitors [24].
Since the identification of a diffusible collagenolytic factor in living amphibian tissue that is capable of degrading undenatured calf skin collagen [25], a total of 24 MMPs have been identified in humans [26]. According to their substrate specificity, MMPs are classified into subfamilies: (1) collagenases, (2) gelatinases, (3) stromelysins, (4) matrilysins, (5) membrane-type MMPs and (6) others. Despite the general acceptance of the classification system based on extracellular matrix substrates, MMPs are rather promiscuous in substrate recognition and also proteolytically cleave substrates beyond extracellular matrix proteins.

2. Methods

To provide a comprehensive overview of the role of MMPs in PDAC, a systematic PubMed search without restrictions was performed. A combination of the search terms “pancreatic cancer” and every individual MMP (both using the official gene name and the common name; see Supplementary Materials Table S1) was used to retrieve papers published up to 1 March 2020. All papers were independently screened by their title and abstract, followed by full text assessment to include papers that contained MMP expression analysis in PDAC patients and papers that contained animal experiments that targeted (either genetically or pharmacologically) MMPs in pancreatic cancer models. The excluded papers were those that contained in vitro data only, papers that assayed MMP levels in experimental animal models without interventions or genetic modifications, or papers that did not focus on PDAC.

3. Results

We retrieved 64 papers focusing on collagenases, 642 papers focusing on gelatinases, 51 papers focusing on stromelysins, 93 papers focusing on matrilysins, 66 papers focusing on transmembrane MMPs and 21 papers focusing on other MMPs (Figure 1). After the removal of duplicates, 816 eligible studies were identified and were vigorously screened to obtain those that contained patient data and/or animal experiments in which MMPs were targeted. This resulted in the inclusion of 14 papers focusing on collagenases, 60 on gelatinases, 11 on stromelysins, 21 on matrilysins, 12 on transmembrane-type MMPs and five on the so-called “other” MMPs. As several of the eligible papers contained data on multiple MMPs, the total number of papers including patient/experimental animal data selected for the review was 91.

3.1. Collagenases in PDAC

Despite the general notion that collagenases (MMP1, MMP8 and MMP13) are key players in cancer biology [27,28,29], relatively little is known about collagenases in PDAC. Although MMP-1 is consistently shown to be overexpressed in PDAC patients compared to healthy controls [30,31,32,33,34,35,36], its effects on cancer progression are inconsistent (Table 1). For example, MMP1 overexpression has been reported as being associated with both a poor prognosis [30] and prolonged survival [37], although no correlations with tumor size, differentiation status and lymph node involvement have been observed [30,36,38]. Despite an elegant recent study showing that MMP1-dependent protease activated receptor (PAR)-1 drives PDAC cell migration and perineural invasion [33], the important role of MMP1 in PDAC is not supported by the experimental data. Besides MMP1 overexpression, MMP8 [36,39] and MMP13 [34,40] are also overexpressed in PDAC patients compared to healthy controls. The relevance of increased MMP expression is not well documented and only a single study showed that MMP-13 expression is associated with lymph node metastasis and the tumor’s pathological stage [41]. Interestingly however, MMP13 overexpression significantly promoted the invasion of the PDAC cells in vitro, whereas MMP13 inhibition blocked leptin-mediated PDAC cell invasion [41], while CD40 agonist-dependent resolution of fibrosis and enhanced chemotherapy efficacy were diminished by MMP13 inhibition [42].

3.2. Gelatinases in PDAC

The most studied MMPs in PDAC are, without a doubt, the gelatinases (MMP2 and MMP9; see Figure 1). The vast majority of studies show that both MMP2 [34,35,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62] and MMP9 [34,36,39,48,49,53,54,59,62,63,64,65,66,67] are upregulated in PDAC patients (Table 1), while a minority of studies fail to show a difference in expression between PDAC and the controls [36,38,52,60,61,68,69,70,71]. The potential clinical relevance is less pronounced, as just half of the studies reported associations between increased MMP2 or MMP9 levels with clinical characteristics such as survival, metastasis or tumor stage [43,46,47,48,50,51,53,56,57,58,61,63,65,67,68,72,73], whereas in the other half of the studies no such correlations were observed (Table 2). Despite the rather diverse observations in patients, initial preclinical experimental animal experiments showed promising results (Table 3). Batimastat treatment of mice harboring orthotopic pancreatic cancers reduced cancer growth, metastasis and death compared to control-treated mice, while also potentiating gemcitabine sensitivity [74,75,76,77]. Batimastat was also shown to reduce metastasis and death when PDAC cells were directly injected into the spleen of recipient mice, in order to mimic liver metastasis in PDAC [78]. Although batimastat is not specific to MMP2 and MMP9 and also inhibits MMP1, MMP3, MMP7, MMP8 and several ADAM family members, based on the gelatin zymography of tumor samples before and after treatment, it was hypothesized that the tumor-inhibiting effect of batimastat was dependent on MMP2 and, to a lesser extent, MMP9. The potential importance of MMP2 and MMP9 in PDAC progression is further supported by studies using more specific inhibitors like MMI-166, RO28-2653 and OPB-3206. Indeed, the selective MMP2, MMP9 and MMP14 inhibitor MMI-166 inhibited PDAC growth in both mice and Syrian hamsters [79,80], whereas RO28-2653 and OPB-3206 (both also selective MMP2, MMP9 and MMP14 inhibitors) reduced chemically induced pancreatic carcinogenesis in Syrian hamsters [81,82]. Finally, treatment with the selective MMP2 and MMP9 inhibitor SB-3CT reduced the lung metastasis of subcutaneously implanted PDAC cells [83].
The most conclusive evidence of the role of MMP2 in PDAC progression comes from subcutaneous models, in which the injection of shMMP2-silenced PANC1 cells resulted in smaller tumors compared to the injection of control shRNA transduced cells [84], whereas treatment with MMP2-blocking peptides limited tumor growth and angiogenesis [85].
In a similar way to the inconclusive association studies in patients (see above and Table 2), experimental animal experiments specifically targeting MMP9 show inconsistent results (Table 3). Orthotopic injections of MMP9-overexpressing Panc02 cells led to bigger tumors than injections of their control counterparts, but the absence/presence of MMP9 did not affect metastasis [86]. Treatment with a MMP9-blocking antibody did not affect the tumor growth of subcutaneously implanted PDAC cells, but did enhance gemcitabine and nab-paclitaxel sensitivity when PDAC cells were injected into the peritoneal cavity [87]. Doxycycline treatment, suggested to specifically target MMP9, reduced the growth of subcutaneously injected Capan-1 cells [88]. Finally, subcutaneous or orthotopic implantation of PDAC cells in MMP9-deficient mice diminished tumor take, tumor growth, angiogenesis and metastasis [83,89] but tumor progression and metastasis increased in MMP9-deficient mice on the Kras(G12D)/Tp53 background [90].

3.3. Stromelysins in PDAC

Clinical studies do not support the general role of stromelysins (MMP3, MMP10 and MMP11) in PDAC (Table 1). Although MMP11 is consistently upregulated and associated with clinical characteristics in PDAC patients [35,36,91,92,93], the data for MMP3 is more controversial. Only half of the studies focusing on MMP3 suggest its expression is increased in PDAC patients compared to control tissue [34,35,94,95], and only a single study suggests that MMP3 is associated with patient survival [95]. Besides clinical studies, preclinical animal models also do not support an important role for stromelysins in PDAC progression. Apart from a study which suggests, but does not prove, that MMP10 drives the invasion and metastasis of PDAC [96], it has only been shown that MMP3 overexpression on the Kras(G12D) background increases neoplastic alterations in pancreatic acinar cells [94]. These premalignant morphological changes were accompanied by the recruitment of infiltrating immune cells and the expression of smooth muscle actin and collagen, indicating that MMP3 is not only a coconspirator of Kras in inducing tumorigenic changes in epithelial cells, but also that it promotes the establishment of a tumorigenic microenvironment. Though it has been suggested that MMP3 may play a role in PDAC initiation, the actual importance of endogenous MMP3 (as opposed to overexpressed MMP3) in PDAC progression and its potential clinical relevance remains elusive.

3.4. Matrilysins in PDAC

MMP7 and MMP26 are the only two members of the matrilysin subfamily. A large number of studies have compared MMP7 expression in PDAC patients with pancreatitis patients and/or healthy controls and have consistently shown that MMP7 levels are elevated in PDAC patients (Table 1) [34,35,36,54,69,91,97,98,99,100,101,102,103,104]. More importantly, MMP7 levels correlate with metastasis and/or survival in most, but not all, studies. Based upon these reports, it is suggested that MMP7 is an important regulator of tumor formation. In line with this notion, preclinical experimental animal models show that MMP7 expression is intimately linked with acinar-to-ductal metaplasia and that pancreatic duct ligation-dependent acinar cell loss, caspase-3 activation, and subsequent metaplasia is significantly reduced in MMP7-deficient mice (Table 3) [98]. The effect of MMP7 on acinar-to-ductal metaplasia seems model-specific, however, as MMP7 deficiency did not affect pancreatitis driven-PanIN development in Pfta1-Cre Kras(G12D) mice [105]. In addition to PDAC initiation, MMP7 also seems to drive PDAC progression. Using several genetic Kras-driven PDAC models, it was shown that both tumor size and metastasis were significantly reduced by MMP7 deficiency. The percentage of mice with lymph node metastasis reduced from around 60 in MMP7-proficient mice to 0 in MMP7-deficient mice, whereas the percentage of mice with liver metastasis dropped from 67% to 13% due to MMP7 deficiency [105]. In line with these findings, the metastasis of MMP7-silenced PANC1 cells was largely reduced compared to control PANC1 cells, whereas pharmacological MMP7 inhibition with sulfur-2-(4-chlorine-3-trifluoromethyl phenyl)-sulfonamido-4-phenylbutyric acid (SCTPSPA) also significantly reduced the metastasis of PANC1 cells [101]. MMP26 expression was also induced in PDAC patients compared to the controls and, intriguingly, MMP26 was expressed significantly more often in tumors with lymph node involvement. Although this is suggestive of the general role of matrilysins in PDAC progression, experimental data confirming the pro-tumorigenic role of MMP26 in PDAC is lacking and it remains to be established whether MMP26 is indeed a driver of disease progression or merely acts as a marker of PDAC metastasis [106].

3.5. Membrane-Type MMPs in PDAC

Seven membrane-bound MMPs have been described so far: the transmembrane members MMP14, MMP15, MMP16, MMP23 and MMP24, and the GPI-anchored members MMP17 and MMP25. Of the membrane-bound MMPs, MMP14 seems most relevant in the setting of PDAC (Table 1, Table 2 and Table 3). Indeed, the overexpression of MMP14 in mice expressing an activating Kras(G12D) mutation led to more large, dysplastic mucin-containing papillary lesions compared to the control Kras(G12D) mice (Table 3) [107]. Using subcutaneous models, MMP14 overexpression in cancer cells seems to reduce the cytotoxic effect of gemcitabine [108], whereas MMP14 inhibition in pancreatic stellate cells limits tumor growth [84]. Moreover, the cancer cell-specific overexpression of membrane-type 1 matrix metalloproteinase cytoplasmic tail binding protein-1 (MTCBP-1; MMP14 binding protein inhibiting its activity) restricts metastasis in orthotopic PDAC models, further suggesting that MMP14 may enhance tumor progression [109]. However, clinical data do not support the important role of MMP14 in PDAC progression (Table 1 and Table 2). Although MMP14 may be overexpressed in PDAC [44,110], MMP14 does not correlate with clinical characteristics such as tumor differentiation, tumor size, lymph node status, or patient survival [31,37,111].

3.6. Other MMPs in PDAC

The so-called other MMPs (i.e., MMP12, MMP19, MMP20, MMP21, MMP27 and MMP28) are not very well characterized in PDAC. Although some members seem to be overexpressed in PDAC [106,111,112] and may be associated with tumor stage and patients survival (Table 1) [111,112,113], no preclinical studies have addressed the role of these MMPs in PDAC (Table 2). Therefore, their actual importance remains to be established.

3.7. Clinical Trials with MMP Inhibitors in PDAC

Only two phase 3 trials focusing on MMP inhibition in PDAC have been published [114,115]. One trial showed that the addition of marimastat (a broad-spectrum MMP inhibitor targeting MMP1, MMP2, MMP7, MMP9 and MMP14) to gemcitabine in a double-blind placebo-controlled, randomized study was well-tolerated but did not show clinical benefits in PDAC patients [114]. The overall response rates (11% and 16% with and without the addition of marimastat, respectively), progression-free survival and time to treatment failure were similar in both treatment arms. Another phase 3 trial showed that BAY 12-9566 (tanomastat; MMP2, MMP3 and MMP9 inhibitor) treatment was also well tolerated by PDAC patients but was inferior to gemcitabine, with median survival times of 3.74 and 6.59 months for the BAY 12-9566 and gemcitabine arm, respectively [115]. Median progression-free survival and quality-of-life analyses also favored gemcitabine, arguing against MMP inhibition in the setting of PDAC.
The fact that there are no clinical benefits obtained through MMP inhibition does not imply that MMPs do not contribute to PDAC progression. As elegantly discussed [116,117], the disappointing clinical trial results may be due to several reasons, of which the inclusion of advanced stage disease seems most relevant. Broad spectrum MMP inhibitors may also lack efficacy as they could block the potential tumor inhibitory activities of specific MMPs. As indicated above, MMP9 deficiency on the Kras(G12D) background enhanced tumor progression and invasive growth [90], supporting this notion and providing an alternative explanation for the negative marimastat and BAY 12-9566 results in PDAC patients. Finally, the poor clinical efficacy of MMP inhibitors could also be explained by the overestimation of the role of MMPs in PDAC progression based on preclinical models that do not fully capture the complexity of human disease.

4. Conclusions

The potential clinical relevance of MMPs in PDAC has largely been addressed using patient-derived tumor material. These studies show a rather consistent picture with respect to MMP overexpression in tumors compared to control sections, although almost 25% of the studies do not show significant differences between patients and controls. However, the association of MMP overexpression with clinical characteristics is not as convincing as suggested in the literature. Half of the studies show that high MMP levels are associated with (lymph node) metastasis and reduced survival, whereas the other half of the studies do not show any correlation with clinical characteristics. Patient-derived data do not, therefore, seem to allow firm conclusions that MMP expression levels (in general) are associated with PDAC progression and poor prognosis to be drawn, especially when considering that publication bias may have resulted in negative studies not being published.
Initial preclinical experimental animal models using broad spectrum MMP inhibitors are more in line with the general role of MMPs in PDAC progression, as different inhibitors limit tumor growth and metastasis in subcutaneous, orthotopic and spontaneous PDAC models. The contribution of individual MMPs in PDAC progression is, however, not very well established. Only MMP2, MMP7 and MMP14 are shown to potentiate tumor growth and/or metastasis in multiple independent papers. For others, the literature is conflicting or missing and no clear conclusions can be drawn. Importantly, however, conflicting results do not indicate that the individual MMPs have no effect in PDAC. The biology of PDAC and MMP is complex and MMPs may act in a context-dependent manner, with both tumor-promoting and tumor-inhibiting effects. The conflicting role of MMP9 serves as an excellent example for this notion. The data rather convincingly show that tumor MMP9 expression drives PDAC progression, but systemic MMP9 ablation triggers invasive growth and metastasis by blocking MMP9-dependent tumor-inhibiting effects in the bone marrow.
Despite the presence of a large range of MMP-deficient animals and the relative ease of generating MMP deficient cells with CRISPR technology, the majority of MMPs have not been studied in preclinical PDAC animal models. To fully appreciate the importance of individual MMPs in PDAC progression and to assess their potential clinical relevance, we have to await studies that combine (pharmacological inhibition in) genetic Kras-driven spontaneous models with subcutaneous and/or orthotopic models, in which MMPs are specifically depleted in stromal or tumor cells. In particular, experiments that address pharmacological treatment with specific MMP inhibitors after tumors could turn out to be invaluable for establishing the context-dependent role of individual MMPs in PDAC. Before such studies have been performed, we should be careful not to generalize the available literature.
Although broad spectrum MMP inhibitors limit PDAC progression in preclinical animal models [73,74,75,76,77,78,79,80,81,82], they seem to lack efficacy in a clinical setting [115,116]. This disparity between preclinical data and clinical trials can be attributed to several factors—for instance, differences in pharmacokinetics, pharmacodynamics and metabolism and the failure to accurately model the tumor microenvironment [128]. In particular, xenograft models, which lack a functional immune system, show a reduced complexity and cellular diversity compared to human disease models. Moreover, the degree of aneuploidy in human tumors results in great variety within inter-tumoral gene modifications, in a different manner compared to how it occurs in mice [129,130]. All of these species-related differences limit the capacity of preclinical mouse models to accurately predict the response of MMP inhibitors in PDAC patients.
In conclusion, based on our systematic review on the role of matrix metalloproteases in PDAC, we conclude that the available literature is not as consistent as envisioned and that, although individual matrix metalloproteases seem to contribute to PDAC growth and metastasis, our review does not support the generalized notion that matrix metalloproteases drive PDAC progression.

Supplementary Materials

The following are available online at https://www.mdpi.com/2079-7737/9/4/80/s1, Table S1: Search terms used and number of papers retrieved.

Funding

This research was funded by grants from the Dutch Cancer Foundation (UVA 2017-11174 and UVA 2014-6782) and the Netherlands Organization for Scientific Research (VENI grant 016.186.046).

Conflicts of Interest

The authors declare no conflict of interest. M.F.B. has acted as a consultant to Servier, and received research funding from Celgene.

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Biology 09 00080 g001 550
Figure 1. Flowchart of paper inclusion. Using the search criteria indicated in Supplementary Materials Table S1, we obtained 814 eligible papers that we screened for the presence of patient and/or matrix metalloprotease (MMP) intervention in animal models. After the exclusion of duplicate papers, we ended up with 91 papers that were included in the review.
Figure 1. Flowchart of paper inclusion. Using the search criteria indicated in Supplementary Materials Table S1, we obtained 814 eligible papers that we screened for the presence of patient and/or matrix metalloprotease (MMP) intervention in animal models. After the exclusion of duplicate papers, we ended up with 91 papers that were included in the review.
Biology 09 00080 g001
Table
Table 1. MMP expression levels in Pancreatic ductal adenocarcinoma (PDAC) patients and controls. Red indicates increased MMP levels, blue indicates no difference and green indicates decreased MMP levels in PDAC patients.
Table 1. MMP expression levels in Pancreatic ductal adenocarcinoma (PDAC) patients and controls. Red indicates increased MMP levels, blue indicates no difference and green indicates decreased MMP levels in PDAC patients.
MemberPatient NumberMethodDifferenceReference
MMP145 PC, 10 COIHCno difference[36]
MMP18 PC, 8 CORNAno difference[59]
MMP1248 PC, 216 COSerumno difference[69]
MMP146 PC, 5 COIHCup vs healthy[30]
MMP125 PCRNAup vs adjacent CO[31]
MMP110 PC, 12 CP, 5 COIHCup vs CO[32]
MMP145 PCRNAup vs adjacent CO[33]
MMP130 PCIHCup vs adjacent CO[33]
MMP1104 PC, 62 COIHCup vs CO[34]
MMP117 PC, 17 CORNAup vs CO[35]
MMP118 PC, 8 CORNAup vs healthy[36]
MMP275 PC, 10 COIHCno difference[36]
MMP218 PC, 8 CORNAno difference[36]
MMP270 PC and 10 COIHCno difference[38]
MMP292 PC, 43 CP, 91 COSerumno difference[68]
MMP235 PCRNA/IHCno difference[70]
MMP246 PC, 13 COSerumno difference[71]
MMP2104 PC, 62 COIHCup vs CO[34]
MMP217 PC, 17 CORNAupvsCO[35]
MMP2122 PCIHCup vs adjacent CO[43]
MMP218 PC, 9 CP, 9 CORNAup vs both others[44]
MMP212 PC, 11 CP, 7 COpancreatic juiceup vs both others[45]
MMP2127 PCIHCup vs CO[46]
MMP220 PC IHCup vs CO[47]
MMP232 PC, 31 CPELISA on tissueup vs CP[48]
MMP2110 PC, 24 BTPlasmaup vs BT[49]
MMP237 PC, 7 CPIHCup vs CP and CO[50]
MMP245 PCIHCup vs CO[51]
MMP251 PC, 60 COUrineup vs CO[52]
MMP244 PC, 8 COIHCup vs CO[52]
MMP230 PC, 17 COIHCup vs CO[53]
MMP229 PCIHCup vs adjacent CO[54]
MMP2127 PC, 25 CP, 25 COPlasmaup vs CP and CO[55]
MMP2106 PCRNA/WBup vs adjacent CO[56]
MMP240 PC, 10 COIHCup vs CO[57]
MMP267 PC, 20 COIHCup vs adjacent CO[58]
MMP28 PC, 8 CORNAupvsCO[59]
MMP210 PC, 3 COZGupvsCO[60]
MMP233 PC, 14 CP, 13 COZG/WBupvsCO[61]
MMP222 PC, 9 CP, 9 CORNAup vs adjacent CO[62]
MMP210 PC, 213 COSerumdown vs CO[118]
MMP345 PC, 10 COIHCno difference[36]
MMP318 PC, 8 CORNAno difference[36]
MMP38 PC, 8 CORNAno difference[59]
MMP3104 PC, 62 COIHCup vs CO[34]
MMP317 PC, 17 CORNAup vs CO[35]
MMP3140 PC, 12 COIHCup vs CO[94]
MMP3140 PC, 12 COIHCup vs CO[95]
MMP718 PC, 8 CORNAno difference[36]
MMP7104 PC, 62 COIHCup vs CO[34]
MMP717 PC, 17 CORNAup vs CO[35]
MMP745 PC, 10 COIHCup vs CO[36]
MMP729 PCIHCup vs adjacent CO[54]
MMP7248 PC, 216 COSerumup vs CO[68]
MMP744 PC, 17 CPRNAup vs CP[91]
MMP770 PCRNAup vs adjacent CO[97]
MMP732 PC, ? COIHCup vs CO[98]
MMP747 PC, 10 COIHCup vs CO[99]
MMP763 PC, 31 CPPlasmaup vs CP[100]
MMP730 PCRNAup vs adjacent CO[101]
MMP75 PC, 5 CP, 62 COIHCup vs CP and CO[102]
MMP7131 PC, 30 CP, 131 COPlasmaup vs CO[103]
MMP710 PCRNAup vs adjacent CO[104]
MMP8248 PC, 216 COSerumno difference[69]
MMP875 PC, 10 COIHCup vs CO[36]
MMP891 PC, 41 CP, 30 CORNA (PBMCs)up vs CO[39]
MMP918 PC, 8 CORNAno difference[36]
MMP970 PC, 10 COIHCno difference[38]
MMP951 PC, 60 COurineno difference[52]
MMP910 PC, 3 COZGno difference[60]
MMP933 PC, 14 CP, 13 COZG/WBno difference[61]
MMP9248 PC, 216 COSerumno difference[69]
MMP935 PCRNA/IHCno difference[70]
MMP9104 PC, 62 COIHCup vs CO[34]
MMP945 PC, 10 COIHCup vs CO[36]
MMP991 PC, 41 CP, 30 CORNA (PBMCs)up vs CP and CO[39]
MMP932 PC, 31 CPELISA on tissueup vs CP[48]
MMP9110 PC, 24 BTPlasmaup vs BT[49]
MMP930 PC, 17 COIHCup vs CO[53]
MMP929 PCIHCup vs adjacent CO[54]
MMP98 PC, 8 CORNAup vs CO[59]
MMP922 PC, 9 CP, 9 CORNAup vs adjacent CO[62]
MMP936 PCIHCup vs CO[63]
MMP99 PC, 9 COMS/MSup vs CO[64]
MMP978 PC, 45 CP, 70 COSerumup vs both[65]
MMP962 PC, 16 COIHCup vs CO[66]
MMP9103 PC, 6 COIHCup vs CO[67]
MMP1017 PC, 17 CORNAno difference[35]
MMP1117 PC, 17 CORNAup vs CO[35]
MMP1118 PC, 8 CORNAup vs CO[36]
MMP1175 PC, 10 COIHCup vs CO[36]
MMP1144 PC, 17 CPRNAup vs CP[91]
MMP1112 PC, 16 COBloodup vs CO[92]
MMP1121 PC, 9 COIHCup vs CO[93]
MMP1275 PC, 10 COIHCno difference[36]
MMP1239 PC, 13 CORNA/WB/IHCup vs CO[111]
MMP13104 PC, 62 COIHCup vs CO[34]
MMP1345 PCRNAup vs adjacent CO[40]
MMP1475 PC, 10 COIHCno difference[36]
MMP1435 PCRNA/IHCno difference[111]
MMP1418 PC, 9 CP, 9 CORNAup vs both others[44]
MMP1464 PC, 9 COIHCup vs CO[110]
MMP1518 PC, 9 CP, 9 CORNAup vs both others[44]
MMP1518 PC, 8 CORNAreduced vs CO[36]
MMP1618 PC, 9 CP, 9 CORNAno difference[44]
MMP1612 PCIHCup vs adjacent CO[119]
MMP19102 PCIHCup vs adjacent CO[112]
MMP20102 PCIHCup vs adjacent CO[112]
MMP2125 PC, 18 COIHCup vs CO[106]
MMP2625 PC, 18 COIHCup vs CO[106]
Pancreatic cancer (PC); pancreatitis (CP); healthy control (CO); benign tumor (BT); immunohistochemistry (IHC); Western blot (WB); zymography (DG).
Table
Table 2. Association between MMP expression and clinical characteristics of PDAC. Red indicates that MMP levels are associated with poor outcome, blue indicates no association and green indicates that MMP levels are associated with improved survival.
Table 2. Association between MMP expression and clinical characteristics of PDAC. Red indicates that MMP levels are associated with poor outcome, blue indicates no association and green indicates that MMP levels are associated with improved survival.
MemberPatient NumberMethodCorrelationReference
MMP145 PC, 10 COIHCno[36]
MMP170 PCIHCno[38]
MMP146 PC, 5 COIHCOS,LM, Size, Stage[30]
MMP130 PCIHCPNI[33]
MMP151 PCIHC/serumOS[37]
MMP275 PC, 10 COIHCno[36]
MMP270 PC, 10 COIHCno[38]
MMP251 PCIHC/serumno[37]
MMP232 PC, 31 CPELISA on tissueno[48]
MMP237 PC, 7 CPIHCno[50]
MMP229 PCIHCno[54]
MMP2127 PC, 25 CP, 25 COplasmano[55]
MMP235 PCRNA/IHCno[70]
MMP232 PCIHCno[120]
MMP267 PCIHCLM,PNI, OS, DF[121]
MMP2122 PCIHCOS, DF[43]
MMP2127 PCIHCOS, Stage[46]
MMP220 PC IHCLM[47]
MMP237 PC, 7 CPIHCLM, DM[50]
MMP245 PCIHCOS, LM, Stage[51]
MMP230 PC, 17 COIHCLM, Stage, Size[53]
MMP2106 PCRNA/WBDM, Stage[56]
MMP240 PC, 10 COIHCLM[57]
MMP267 PC, 20 COIHCLM, Stage, PNI[58]
MMP233 PC, 14 CP, 13 COZG/WBStage[61]
MMP292 PC, 43 CP, 91 COserumLM, DM[68]
MMP232 PCIHCVI[72]
MMP288 PCIHCOS[73]
MMP345 PC, 10 COIHCno[36]
MMP318 PC, 8 CORNAno[36]
MMP370 PCIHCno[38]
MMP3140 PC, 12 COIHCOS[95]
MMP751 PCIHC/serumno[37]
MMP729 PCIHCno[54]
MMP788 PCIHCno[73]
MMP745 PC, 10 COIHCOS,LM, DIF, Stage[36]
MMP770 PCIHCOS,Size, DIF[38]
MMP7134 PCIHCStage, PNI,OS[122]
MMP770 PCRNALM, Size[97]
MMP747 PC, 10 COIHCOS, DM[99]
MMP710 PCRNAOS[104]
MMP7101 PCserumOS[105]
MMP739 PCIHCLM, OS[123]
MMP875 PC, 10 COIHCno[36]
MMP891 PC, 41 CP, 30 CORNA (PBMCs)no[39]
MMP945 PC, 10 COIHCno[36]
MMP970 PC, 10 COIHCno[38]
MMP951 PCIHC/serumno[37]
MMP991 PC, 41 CP, 30 CORNA (PBMCs)no[39]
MMP929 PCIHCno[54]
MMP933 PC, 14 CP, 13 COZG/WBno[61]
MMP99 PC, 9 COMS/MSno[64]
MMP935 PCRNA/IHCno[70]
MMP932 PCIHCno[123]
MMP927 PCIHCno[124]
MMP962 PC, 16 COIHCPNI,LM, Stage, Size[66]
MMP963 PCIHCVI,OS, LM, DM[125]
MMP962 PCIHCLM,OS[126]
MMP932 PC, 31 CPELISA on tissueLM[48]
MMP930 PC, 17 COIHCLM, Stage, Size[53]
MMP936 PCIHCLM, DM[63]
MMP978 PC, 45 CP, 70 COserumOS[65]
MMP9103 PC, 6 COIHCOS, LM, DM, VI, Stage[67]
MMP932 PCIHCVI[72]
MMP988 PCIHCOS, DF,DM[73]
MMP1051 PCIHC/serumno[37]
MMP1175 PC, 10 COIHCOS, LM,DIF, Size[36]
MMP11not indicatedRNAOS[92]
MMP1275 PC, 10 COIHCno[36]
MMP1239 PC, 13 CORNA/WB/IHCOS,LM, Stage[111]
MMP1360 PCIHCLM[41]
MMP1470 PCIHCno[38]
MMP1475 PC, 10 COIHCno[36]
MMP1437 PCRNA/IHCno[70]
MMP1578 PCIHCOS, DF,PNI, LM, DM, Stage[127]
MMP19102 PCIHCOS, DF, PNI, Stage[112]
MMP20102 PCIHCOS, DF, Stage, PNI[112]
MMP2125 PC, 18 COIHCno[106]
MMP2625 PC, 18 COIHCLM[106]
MMP28not indicatedRNAOS[113]
Pancreatic cancer (PC); pancreatitis (CP); healthy control (CO); benign tumor (BT); immunohistochemistry (IHC); Western blot (WB); zymography (DG); overall survival (OS); disease-free survival (DF); lymph node metastasis (LM); perineural invasion (PNI); venous invasion (VI); distant metastasis (DM); differentiation (DIF).
Table
Table 3. Experimental animal models that target MMPs.
Table 3. Experimental animal models that target MMPs.
TargetModel“Treatment”ResultReference
MMP1Sciatic nerve invasion shMMP1 PANC1 cellsReduced perineural invasion[33]
MMP2/9?Orthotopic injection HPAC cellsBatimastat (day −7 till death/sacrifice)Increased gemcitabine sensitivity, No effect single treatment[74]
Orthotopic injection HPAC cellsBatimastat (day −4 till death/sacrifice)Reduced tumor growth, metastasis and death[75]
Orthotopic injection HPAC cellsBatimastat (day 7 till death/sacrifice)Reduced local invasion and death[76]
Orthotopic injection HPAC cellsBatimastat (day 7 till death/sacrifice)Reduced tumor weight[77]
Injection AsPC1 or Capan-1 cells in spleenBatimastat (day −7 till day 14)Reduced metastasis and death[78]
Subcutaneous injection SW1990 cellsMMI-166 from day 7 till sacrifice at day 28Reduced tumor growth[79]
Orthotopic injection PGHAM cells (Syrian hamster)MMI-166 (day 1 till sacrifice)Reduced tumor growth, liver metastasis and MVD[80]
BOP injections (Syrian hamster)RO28-2653 (week 6 till week 14)Reduced liver metastasis, No effect death[81]
BOP injections (Syrian hamster)OPB-3206 in diet from day 48 till sacrificeReduced invasive carcinoma[82]
Subcutaneous injection Panc02 or MIAPaca2 cellsSB-3CT (day 1 till sacrifice)Reduced lung metastasis[83]
MMP2Subcutaneous injection organoid and PSCshMMP2 PSCReduced tumor growth[84]
Subcutaneous injection PANC-1 or CFPAC-1 cellsMMP2 blocking peptides after tumor takeReduced growth and MVD[85]
MMP3Kras(G12D) miceMMP3 overexpressionIncreased neoplastic alterations[94]
MMP7Ductal ligationMMP7 deficient miceReduced ductal metaplasia[98]
Pfta1-Cre/KrasG12D miceMMP7 deficiencyNo effect acinar to ductal metaplasia[105]
Pdx1-Crelate/KrasG12D miceMMP7 deficiencyReduced tumor development[105]
Pdx1-CreLate/KrasG12D/p53f/+ miceMMP7 deficiencyReduced tumor growth and metastasis[105]
Tail vein injection PANC1 cellsshMMP7Reduced liver and lung metastasis[101]
SCTPSPA (day −2 till day 25)Reduced lung metastasis[101]
MMP9Subcutaneous injection Panc02 cellsMMP9 deficient miceReduced lung metastasis[83]
Orthotopic injection Panc02 cellsMMP9 overexpressionEnhanced tumor growth, No effect metastasis[86]
Subcutaneous injection AsPC-1 cellsaMMP9 antibody AB0046 (day 1 till day 14)No effect on tumor weight[87]
Injection AsPC-1 cells in peritoneal cavityaMMP9 antibody AB0046 (day 14 till day 56)Increased gemcitabine/nab-paclitaxel sensitivity, No effect metastasis[87]
Subcutaneous injection Capan-1 cellsDoxycycline (day 1 till day 14)Reduced growth and MVD[88]
Orthotopic injection L3.6pl cellsMMP9 deficient miceReduced tumor take, growth and MVD[89]
Pdx-1+/Cre;KrasG12D;Trp53 miceMMP9 deficiencyIncreased progression and invasive growth[90]
Intravenous injection 9801 or Panc02 cellsMMP9 deficient miceIncreased metastasis[90]
MMP14Subcutaneous injection organoid and PSCshMMP14 PSCReduced tumor growth[84]
KrasG12D miceMMP14 overexpressionIncreased number of PanIN lesions[107]
Subcutaneous injection PANC1 or HPAF-II cellsMMP14 overexpressionReduced gemcitabine sensitivity, No effect single treatment[108]
Orthotopic injection DanG or BxPc3 cellsMTCBP-1 overexpressionReduced metastasis, No effect tumor growth[109]
Note: All experiments were performed using mice unless indicated otherwise.

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Slapak, E.J.; Duitman, J.; Tekin, C.; Bijlsma, M.F.; Spek, C.A. Matrix Metalloproteases in Pancreatic Ductal Adenocarcinoma: Key Drivers of Disease Progression? Biology 2020, 9, 80. https://doi.org/10.3390/biology9040080

AMA Style

Slapak EJ, Duitman J, Tekin C, Bijlsma MF, Spek CA. Matrix Metalloproteases in Pancreatic Ductal Adenocarcinoma: Key Drivers of Disease Progression? Biology. 2020; 9(4):80. https://doi.org/10.3390/biology9040080

Chicago/Turabian Style

Slapak, Etienne J., JanWillem Duitman, Cansu Tekin, Maarten F. Bijlsma, and C. Arnold Spek. 2020. "Matrix Metalloproteases in Pancreatic Ductal Adenocarcinoma: Key Drivers of Disease Progression?" Biology 9, no. 4: 80. https://doi.org/10.3390/biology9040080

APA Style

Slapak, E. J., Duitman, J., Tekin, C., Bijlsma, M. F., & Spek, C. A. (2020). Matrix Metalloproteases in Pancreatic Ductal Adenocarcinoma: Key Drivers of Disease Progression? Biology, 9(4), 80. https://doi.org/10.3390/biology9040080

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