Skip to content

Advertisement

  • Research article
  • Open Access
  • Open Peer Review

The inflammatory milieu within the pancreatic cancer microenvironment correlates with clinicopathologic parameters, chemoresistance and survival

  • 1,
  • 1,
  • 2,
  • 2,
  • 1, 3,
  • 1, 3,
  • 1,
  • 1,
  • 4,
  • 5,
  • 1,
  • 2 and
  • 1Email author
BMC Cancer201515:783

https://doi.org/10.1186/s12885-015-1820-x

  • Received: 4 May 2015
  • Accepted: 16 October 2015
  • Published:
Open Peer Review reports

Abstract

Background

The tumor microenvironment impacts pancreatic cancer (PC) development, progression and metastasis. How intratumoral inflammatory mediators modulate this biology remains poorly understood. We hypothesized that the inflammatory milieu within the PC microenvironment would correlate with clinicopathologic findings and survival.

Methods

Pancreatic specimens from normal pancreas (n = 6), chronic pancreatitis (n = 9) and pancreatic adenocarcinoma (n = 36) were homogenized immediately upon resection. Homogenates were subjected to multiplex analysis of 41 inflammatory mediators.

Results

Twenty-three mediators were significantly elevated in adenocarcinoma specimens compared to nonmalignant controls. Increased intratumoral IL-8 concentrations associated with larger tumors (P = .045) and poor differentiation (P = .038); the administration of neoadjuvant chemotherapy associated with reduced IL-8 concentrations (P = .003). Neoadjuvant therapy was also associated with elevated concentrations of Flt-3 L (P = .005). Elevated levels of pro-inflammatory cytokines IL-1β (P = .017) and TNFα (P = .033) were associated with a poor histopathologic response to neoadjuvant therapy. Elevated concentrations of G-CSF (P = .016) and PDGF-AA (P = .012) correlated with reduced overall survival. Conversely, elevated concentrations of FGF-2 (P = .038), TNFα (P = .031) and MIP-1α (P = .036) were associated with prolonged survival.

Conclusion

The pancreatic cancer microenvironment harbors a unique inflammatory milieu with potential diagnostic and prognostic value.

Keywords

  • Inflammation
  • Cytokines
  • Chemokines
  • Growth factors
  • Pancreatic cancer
  • Tumor microenvironment

Background

Pancreatic adenocarcinoma (PC) is the fourth leading cause of cancer deaths in the United States, due in part to nearly universal resistance to cytotoxic chemotherapy. Gemcitabine-based therapies achieve clinical benefit in approximately 24 % of patients with PC [1], but the overall survival advantages are sobering, ranging from a few weeks to months [13]. Complete surgical resection offers patients with PC the greatest survival benefit. However, this is achievable in fewer than 20 % of patients presenting with PC [4]. As a result, PC is projected to be the second leading cause of cancer deaths by 2030 [5]. There is a tremendous need to discover novel biomarker (s) or panels of biomarkers that can aid in detecting PC earlier, improving prognostic evaluation and predicting response to chemotherapy.

Inflammation within the PC microenvironment has been mechanistically linked to tumor progression and chemoresistance through NF-κB, IL-6, toll-like receptor and TGF-β signaling pathways [610]. However, the diagnostic and prognostic value of the inflammatory milieu within the PC microenvironment remains essentially undefined. While survival gains from immune cell infiltration into the tumor microenvironment have been conclusively demonstrated in colorectal and ovarian cancer [1113], similar investigations have not yielded consistent results in PC [14, 15]. Patients with chronic pancreatitis are 5–15 times more likely to develop PC [16] and insights into the association between inflammation and PC stems from investigations of chronic pancreatitis. Potential environmental sequelae of pancreatitis such as hypoxia, the presence of reactive oxygen species, and acidosis may influence the development of PC [17]. Additionally, numerous soluble mediators, including TNF-α [18], TGF-α [19], TGF-β [20], IL-1β [21], IL-1α [22], IL-6 [23, 24], IL-8 [25], VEGF [26], and others have been implicated in PC carcinogenesis, tumor progression, and treatment resistance. However, the relationship between the inflammatory milieu and the spectrum of disease from normal pancreas to pancreatitis to pancreatic cancer has not yet been characterized. Therefore, the translational relevance of the microenvironmental inflammatory milieu to PC development and progression remains speculative.

We examined the inflammatory milieu present in the PC microenvironment from 36 freshly resected tumor specimens using a forty-one-item panel of cytokines, chemokines and growth factors to test the hypothesis that expression levels of these mediators harbor diagnostic and prognostic value. We first compared the inflammatory milieu of PC to that of pancreatitis (n = 9) and normal pancreas (n = 6). Inflammatory mediators were further evaluated in relation to prognostic clinicopathologic parameters, administration of neoadjuvant therapy, treatment resistance and patient survival. These data bring the field one step closer to the identification of biomarker panels that can aid in detecting disease earlier and classifying patients with respect to response to chemotherapy and most importantly, prognosis.

Materials and methods

Patient cohorts

A prospectively maintained database approved by the Institutional Review Board at the University of Florida (353–2007) was utilized for sample selection. Written informed consent was obtained from all participants. In total, 51 samples were included in this study. Using pathologically verified diagnoses, samples were placed into one of three experimental groups: normal pancreas (n = 6), chronic pancreatitis (n = 9) and pancreatic carcinoma (n = 36). Indications for resection of ‘normal’ pancreata included duodenal adenomas (n = 3), remotely located neuroendocrine tumors (n = 2) and a ductal squamoid cyst (n = 1). Of the 36 patients with pathologically confirmed pancreatic adenocarcinoma, all underwent resection with curative intent, 10 whom completed gemcitabine/abraxane-based neoadjuvant chemotherapy. Pathologic response to neoadjuvant chemotherapy was graded by clinical pathologists upon resection using a validated scale [27]. Briefly, histopathologic response to neoadjuvant therapy was broadly grouped into complete (>90 % of tumor cells destroyed), moderate (10–90 % of tumor cells destroyed) and poor (<10 % of tumor cells destroyed). All 36 patients had at least 6 months of clinical follow-up for survival analysis.

Pancreatic tissue harvest

Resected pancreatic tissue was immediately weighed and placed in cell lysis buffer (Cell Signaling Technologies, Danvers, MA) with a protease inhibitor cocktail (Sigma-Aldrich, St. Louis, MO). Immediately adjacent tissues were preserved in formalin for histologic verification of pathology. Tissues were dissociated mechanically and further homogenized using the FastPrep-24 system according to the manufacturer’s protocol (MP Biomedicals, Santa Ana, CA). Homogenates were stored at −80 °C until soluble mediator analysis could be performed.

Soluble mediator analysis

Homogenates were then probed for soluble mediators using the Milliplex® Premixed 41-Plex Immunology Multiplex Assay (Merck Millipore, Darmstadt, Germany) according to the manufacturer’s protocol. Specifically, supernatants from tissue homogenates were incubated in filter bottom microtiter plates (EMD Millipore, San Jose, CA) with beads coated with primary antibodies overnight at 4C. After washing, PE- conjugated anti-cytokine antibodies were added and incubated for additional 2 h at room temperature. Following washing, data was acquired on a Luminex 200 (EMD Millipore, San Jose, CA) and analyzed with Milliplex Software (EMD Millipore, San Jose, CA). Concentrations were quantified using a standard curve and 5 parameter logistics to determine pg/mL concentrations.

All cytokine concentrations were normalized to total protein concentrations using detergent compatible protein quantification (Bio-Rad, Hercules, CA). Soluble mediator concentrations were then converted to pg/mg of tissue as follows: pg/ml divided by mg/ml of total protein.

Statistical analysis

All statistical analysis was performed using SPSS version 22.0 (IBM SPSS Statistics for Windows; IBM Corp). For each normalized tissue cytokine concentration, represented in picograms per milligram of total protein (pg/mg protein), normality was assessed using the Shapiro-Wilk test. Since all normalized cytokine concentrations did not display normal distributions (P < 0.05), non-parametric testing was employed to evaluate differences. In this manner, the Mann Whitney U test was incorporated for binomial categorical variables, and P < 0.05 was considered statistically significant. Additionally, Spearman’s rank correlation coefficients were employed to determine significant associations between continuous variables. Overall survival was calculated using the following formula: Number of days from date of surgery to death or the date of last follow-up, whichever came first, divided by 365.25 (accounting for leap years), multiplied by 12 to obtain the time in months. Kaplan-Meier survival curves were generated using median intratumoral concentration to dichotomize PC specimens into cytokinehigh and cytokinelow groups. The log-rank (Mantel-Cox) test was used to evaluate statistical significance. Additionally, a univariate Cox proportional hazards model was used to generate hazard ratios. Each soluble mediator was then incorporated into a multivariate proportional hazards model with the degree of lymphatic metastasis, as this was the only clinicopathologic parameter demonstrating a significant correlation with survival (P < .05) on univariate analysis.

Results

Pancreatic adenocarcinoma has a distinct intratumoral inflammatory milieu

Establishing the diagnosis of PC remains a significant clinical problem that delays initiation of therapy, impacts enrollment in clinical trials, and mandates that patients undergo major surgical procedures in the absence of definitive findings. In order to determine whether the intratumoral inflammatory milieu may have diagnostic value, we measured the concentrations of 41 cytokines, chemokines and growth factors in 51 freshly homogenized pancreatic surgical samples. We found no significant differences in any of the normalized cytokine concentrations when comparing normal pancreatic tissue (n = 6) to that of chronic pancreatitis (n = 9). Thus, pairwise comparisons between nonmalignant tissue (n = 15) and adenocarcinoma (n = 36) as well as between pancreatitis alone (n = 9) and adenocarcinoma (n = 36) were performed (Table 1). Of the 41-protein-panel of cytokines, chemokines and growth factors evaluated, the concentrations of 23 emerged as significantly higher in pancreatic cancer compared to nonmalignant tissue. The most significant differences (P < .001) were observed for Eotaxin, IP-10, MCP1, MCP3, MDC, IL-1α, IL-1RA, IL-7, and IL-8. Interestingly, all but 3 (FGF-2, RANTES and IL1β) of the 23 mediators that emerged as significant when comparing pancreatic cancer to nonmalignant tissue also emerged as significant when comparing pancreatic cancer to pancreatitis. Together these data suggest that pancreatic adenocarcinoma has a distinct inflammatory milieu when compared to that of nonmalignant pancreatic tissues, including that of chronic pancreatitis.
Table 1

Inflammatory milieu within pancreatic tissue is predictive of malignancy

 

Normal pancreas (n = 6)

Pancreatitis (n = 9)

Pancreatic cancer (n = 36)

P value nonmalignant vs. Pancreatic cancer

P value pancreatitis vs. Pancreatic cancer

Growth factors

     

FGF-2

761 (221)

951 (187)

1674 (177)

.009

.063

PDGF-BB

117 (46)

102 (48)

244 (63)

.026

.022

VEGF

151 (46)

76 (20)

252 (59)

.119

.046

Chemokines

     

Eotaxin

21.8 (12.8)

21.4 (12.9)

90.4 (16.3)

<.001

.002

Fractalkine

55.1 (12.8)

43.0 (9.4)

71.1 (3.6)

.010

.009

Gro

163 (67)

463 (296)

531 (87)

.007

.043

IP-10

69 (33)

70 (32)

620 (148)

<.001

<.001

MCP1

437 (136)

378 (104)

1615 (302)

<.001

<.001

MCP3

4.7 (1.9)

2.5 (0.8)

16.6 (2.8)

<.001

<.001

MDC

27 (11)

70 (36)

143 (17)

<.001

.009

MIP-1α

14.3 (4.9)

16.9 (7.6)

37.9 (4.6)

.001

.009

MIP-1β

22.1 (9.4)

14.3 (5.0)

38.4 (6.1)

.007

.008

RANTES

766 (261)

1066 (228)

1929 (235)

.032

.178

Cytokines

     

GM-CSF

4.1 (2.0)

1.4 (0.3)

14.0 (3.9)

<.001

<.001

IFNα2

13.0 (2.7)

8.7 (2.3)

19.9 (2.4)

.013

.012

IL-1α

1.8 (0.5)

3.2 (0.6)

12.2 (2.0)

<.001

.003

IL-1RA

157 (144)

46 (21)

500 (96)

<.001

<.001

IL-1β

0.6 (0.1)

0.9 (0.1)

1.3 (0.2)

.032

.262

IL-6

13.3 (5.3)

5.8 (2.1)

71.8 (23.3)

<.001

<.001

IL-7

3.9 (1.0)

4.5 (1.0)

10.4 (0.8)

<.001

<.001

IL-8

160 (154)

61 (37)

848 (161)

<.001

.002

IL-15

1.7 (0.2)

2.0 (0.3)

3.5 (0.4)

.001

.021

TNFα

1.6 (0.7)

1.4 (0.4)

3.3 (0.4)

.002

.010

Concentrations expressed as mean (SE) in units of pg/mg protein. All significant comparisons are shown for which P < 0.05 using the Mann Whitney U test

Elements of the intratumoral inflammatory milieu strongly associate with the administration of neoadjuvant cytotoxic chemotherapy

Dynamic changes accompanying the administration of cytotoxic chemotherapy within the PC microenvironment remain poorly described. In order to determine whether differences within intratumoral inflammatory milieu associate with the administration of cytotoxic chemotherapy, patients were dichotomized into groups based on the administration of neoadjuvant therapy. Indeed, significantly lower levels of intratumoral IL-8 were observed in PC specimens from patients treated with neoadjuvant gemcitabine-based regimens compared to those from treatment naïve patients (median concentration 1129 pg/mg protein vs. 114 pg/mg protein; P = .003) (Table 2). Conversely, high intratumoral concentrations of Flt-3 L and IL-2 correlated with the administration of neoadjuvant chemotherapy. Together these data suggest that the administration of cytotoxic chemotherapy alters the inflammatory microenvironment in PC.
Table 2

Intratumoral milieu correlates with the administration of cytotoxic chemotherapy

 

Neoadjuvant Chemotherapy

 
 

No (n = 26)

Yes (n = 10)

P value

Flt3L

15.9 (1.6)

24.0 (3.5)

.005

IL-1α

15.0 (2.6)

5.0 (0.9)

.006

IL-8

1129 (197)

114 (35)

.003

All significant comparisons are shown for which P < 0.05 using the Mann Whitney U test

Poor histopathologic response to neoadjuvant chemotherapy appears to associate with poor clinical outcomes, although this phenomenon continues to be debated [2830]. In order to determine if the intratumoral milieu could offer insights into the degree of clinical response to cytotoxic chemotherapy, histopathologic response to neoadjuvant chemotherapy was correlated to soluble mediator concentrations. Clinically, resected PC specimens with a poor histopathologic response to neoadjuvant therapy represent a group of treatment-resistant tumors. Indeed, significantly higher levels of the pro-inflammatory cytokines IL-1β and TNFα were observed in tumors from this population compared to tumors displaying a moderate to complete pathologic response to cytotoxic chemotherapy (Fig. 1). These preliminary data provide rationale for the continued evaluation of potential biologic mechanisms within the tumor microenvironment by which resistance to cytotoxic chemotherapy is maintained.
Fig. 1
Fig. 1

Th1-associated cytokines within the tumor microenvironment correlate with treatment resistance in PC. Distributions are displayed comparing intratumoral concentrations of a IL-1β and b TNFα in homogenates of pancreatic adenocarcinoma with histopathologic response to neoadjuvant chemotherapy. Bars represent mean values with standard error of the mean. *P < 0.05 for each association using the Mann Whitney U test

Variations within the intratumoral inflammatory milieu correlate with clinicopathologic features

In order to determine whether patterns of soluble mediator concentrations could offer further insights into the biology of PC, the inflammatory milieu was evaluated with respect to commonly used clinicopathologic parameters, such as positive lymph node ratio, serum CA 19–9 concentrations, tumor grade and tumor size. In our analysis of lymphatic metastasis using positive lymph node ratio, elevated intratumoral EGF concentrations associated with a high degree of lymphatic metastasis (ρ = 0.332, P = .048), while high concentrations of IL-4 displayed the opposite trend, correlating with reduced lymphatic metastasis (ρ = −0.377; P = .023) (Table 3). Additionally, IFN-γ (ρ = 0.391; P = .022) and RANTES (ρ = 0.475; P = .005) demonstrated significant positive correlations with serum CA 19–9 levels. High levels of IL-8 and IP-10 associated with larger tumors (ρ = 0.336; P = .042 and ρ = 0.373; P = .023 with respect to tumor size in cm). The inflammatory milieu was then correlated with the degree of tumor differentiation observed in malignant tissue. Significant associations between poor tumor differentation and high concentrations of GM-CSF, IL-15 and IL-8 were observed (Fig. 2). While these patterns provide insights into potential relationships between aspects of clinicopathological parameters and inflammation, these parameters do not always correlate with outcome.
Table 3

Inflammatory milieu within the tumor microenvironment correlates with clinicopathologic parameters in PC specimens

Clinical parameter

Ligand

Spearman coefficient

P value

Positive Lymph Node Ratio

EGF

.332

.048

IL-4

-.377

.023

CA 19–9 (U/mL)

IFN-ɤ

.391

.022

RANTES

.475

.005

Tumor Size (cm)

IL-8

.336

.045

IP-10

.357

.033

All significant comparisons are shown for which P < 0.05

Fig. 2
Fig. 2

Inflammatory milieu within the tumor microenvironment correlates with tumor grade. Intratumoral concentrations of a GM-CSF, b IL-8 and c IL-15 demonstrated significant correlations with high tumor grade. *P < 0.05 for each association using the Mann Whitney U test

We therefore aimed to determine if these known clinicopathologic predictors of outcome correlated with survival in our cohort. One commonly used predictor of overall survival in resected pancreatic cancer is the ratio of lymph nodes containing malignancy to the total number of lymph nodes resected and examined [31]. Indeed in our cohort, elevated positive lymph node ratios correlated strongly with reduced overall survival (HR 55.8; P = .002) (Table 4). This population therefore confirms the predictive nature of lymphatic metastasis. However, associations between survival and other commonly used prognostic parameters such as microscopically positive resection margins and poor tumor differentiation were not statistically significant in this cohort (HR 1.96; P = .12 and HR 2.28; P = .053, respectively) (Table 4).
Table 4

Univariate analysis of overall survival

 

HR

95 % CI

P value

Age (y)

1.01

0.98–1.05

.556

Neoadjuvant Therapy

1.08

0.43–2.68

.870

CA 19–9 (kU/mL)

1.38

0.83–2.29

.215

Major Vascular Resection

2.66

0.85–8.30

.093

R1 Resection

1.96

0.84–4.53

.118

Positive Lymph Node Ratio

55.8

4.35–714

.002*

Poor Tumor Differentiation

2.28

0.99–5.23

.053

Tumor Size (cm)

1.06

0.89–1.28

.506

Clinicopathologic parameters were analyzed in a Cox proportional hazards model for 36 patients with surgically resected pancreatic adenocarcinoma. Abbreviations: HR hazard ratio, CI confidence interval, y years, R1 resection denotes a microscopically positive margin; Positive lymph node ratio refers to the number of lymph nodes positive for malignancy divided by the total number of lymph nodes examined; cm centimeters. *, P < .05

Variations in the inflammatory milieu within the tumor microenvironment correlate with patient survival

Since the common clinicopathological data were poor at predicting outcome, we next hypothesized that elements within the inflammatory milieu harbor superior prognostic value. The intratumoral milieu was correlated with overall survival in all 36 patients with PC who underwent surgical resection with curative intent. All patients had at least 6 months of clinical follow-up. Associations between the intratumoral milieu and overall survival were evaluated using both Kaplan-Meier and Cox proportional hazards models. Soluble mediators were first dichotomized using median concentrations and evaluated by log-rank test in a Kaplan-Meier model. FGF-2, MDC, IL-4 and Flt-3 L significantly correlated with prolonged survival upon dichotomization (Table 5, Fig. 3). Due to the potential bias introduced from the artificial categorization of values dichotomized at the median, a proportional hazards model was employed, allowing for direct correlation of intratumoral mediator concentration and survival. In this manner, high levels of both G-CSF and PDGF-AA correlated with reduced survival (HR 1.03; P = .016 and HR 3.51; P = .012, respectively) (Table 5).
Table 5

Soluble mediators detected within the PC microenvironment correlate with prognosis

 

Dichotomized at median concentration

Univariate PH model

Multivariate PH model

 

Median OS (Low)

Median OS (High)

P value

HR (95 % CI)

P value

HR (95 % CI)

P value

EGF

10.4

11.0

.165

1.23 (0.98–1.54)

.078

1.10 (.86–1.42)

.439

G-CSF

18.3

7.5

.064

1.03 (1.01–1.06)

.016*

1.02 (1.00–1.05)

.071

PDGF-AA

18.7

8.9

.170

3.51 (1.32–9.31)

.012*

2.72 (1.00–7.40)

.050*

IL-6

11.0

10.4

.500

12.0 (0.85–172)

.066

6.10 (0.39–96.13)

.198

FGF-2

7.1

20.7

.010*

0.60 (0.37–0.97)

.038*

0.59 (0.37–0.93)

.024*

TNFα

7.5

18.3

.085

0.78 (0.63–0.98)

.031*

0.79 (0.64–0.97)

.027*

MIP-1α

10.4

14.9

.352

0.98 (0.96–1.00)

.036*

0.98 (0.97–1.00)

.029*

IL-4

7.6

20.7

.008*

0.85 (0.70–1.04)

.112

0.26 (0.75–1.08)

.902

Flt-3 L

7.1

18.7

.037*

0.95 (0.88–1.01)

.103

0.94 (0.86–1.02)

.113

MDC

7.6

20.7

.049*

0.01 (0–1.37)

.065

0.01 (0–2.24)

.098

Eotaxin

7.5

18.7

.055

0.03 (0–15.2)

.263

0.09 (0–47.9)

.454

Soluble mediators were dichotomized at median concentrations and survival was evaluated using Kaplan-Meier analysis with P values determined using the log-rank test (left). Associations between soluble mediator concentrations and survival were then evaluated in a continuous fashion using a Cox proportional hazards model (middle). Finally, concentrations were evaluated in a multivariate Cox proportional hazards model with positive lymph node ratio (right). Abbreviations: PH proportional hazards, OS overall survival, HR hazard ratio, CI confidence interval. *, P < .05

Fig. 3
Fig. 3

Elements of the inflammatory milieu within the tumor microenvironment have prognostic value. Kaplan-Meier curves are plotted for a FGF-2, b MDC, c Flt-3 L and d IL-4 based on cutoffs at median cytokine concentrations in 36 pancreatic adenocarcinoma specimens. The log-rank test was used to compare differences. Significance was considered for those in which P < 0.05

Anecdotal observations of interest included: Four patients with tumors which demonstrated distinctly high PDGF-AA concentrations, at least double that of any other PC specimen, recurred within 6 months postoperatively. Further, two patients with tumors containing G-CSF concentrations over 5 times that of any other also recurred within 6 months, with one of these patients showing evidence of metastatic disease as soon as two months postoperatively. Conversely, two patients with tumors with undetectable MIP-1α recurred within 6 months and three patients whose tumors had the highest intratumoral MIP-1α concentrations were recurrence-free between one and three years postoperatively. Further, the patient with the highest intratumoral TNFα concentration remains recurrence-free 34 months postoperatively.

Discussion

Due to the dismal clinical outcomes associated with pancreatic adenocarcinoma and the continued debate surrounding therapeutic interventions, there is a tremendous need for the development of tools that can supplement current diagnostic and prognostic efforts. The extent of genetic and phenotypic heterogeneity specific to PC represents a major obstacle to the clinical application of developing biomarkers in PC. Efforts to further understand clinical observations regarding pathologic signaling within the tumor microenvironment have provided a novel focus that have led to major breakthroughs. Examples include therapeutic successes following Nab-paclitaxel infusion that is dependent upon SPARC expression in desmoplastic tumor-associated stroma [32, 33], and consistent observations that partial responses achieved from CD40 agonists led to the infiltration of tumoricidal macrophages into the local microenvironment [34, 35]. In order to further understand clinically important paracrine signaling pathways within this local microenvironment, the work presented here has detected a unique inflammatory signature within pancreatic adenocarcinoma that is distinct from that of chronic, benign inflammation. Further, several members of this panel of markers were associated with specific clinicopathologic parameters, response to cytotoxic chemotherapy, and overall survival.

The almost universal development of treatment resistance and disease relapse following systemic cytotoxic or targeted therapies has made survival in PC achievable in only a small minority of patients. Mechanistically, chemoresistant phenotypes have been reproduced in vitro. However, the relevance of these findings to clinical practice remains unclear. For example, gemcitabine resistance has been linked to the expression of gemcitabine-metabolizing proteins and DNA repair enzymes as well as the downregulation of nucleoside transporters. However, the clinical value of identifying these markers in resected PC specimens has yielded conflicting results [36]. Here we demonstrate that not only is the exposure to gemcitabine-based therapy associated with a different inflammatory milieu within the tumor, but also that differences in the milieu associate with the degree of clinical response, whereby increased levels of intratumoral IL1-β and TNF-α are associated with poor histopathologic response to neoadjuvant therapy. These findings further support a wealth of investigations linking downstream NF-κB signaling to tumor progression and chemoresistance [37].

The observation that EGF levels correlated with the degree of lymph node metastasis is consistent with widespread evidence implicating EGF signaling in cancer progression and metastasis, culminating in a phase three trial employing EGFR inhibition in pancreatic cancer [3]. Conversely, high intratumoral concentrations of IL-4 displayed the opposite trend, correlating with reduced lymphatic metastasis, whereby patients with tumors high in IL-4 concentrations displayed roughly triple the survival of those with tumors expressing low levels of IL-4. In light of this finding it is important to note that direct stimulation of cancer cells with IL-4 generally results in augmented growth and proliferation [3840]. However, this finding must be interpreted within the context of IL-4 signaling within the microenvironment. Indeed, constitutive IL-4 expressing cancers have demonstrated reduced growth in vivo due to the induction of a robust antitumor immune response [41]. Similarly, intratumoral levels of IL-8 and GM-CSF were predictive of tumor grade while IL-8 levels were also positively associated with tumor size. Again this is consistent with previous findings that suggest that IL-8 and GM-CSF produced in the tumor microenvironment promote immune evasion in PC [4244]. Interestingly, the administration of cytotoxic chemotherapy was strongly associated with significantly lower intratumoral IL-8 concentrations. The investigation of the intratumoral inflammatory milieu has therefore revealed consistent correlations between IL-8 concentrations, histopathologic findings and the administration of chemotherapy.

As alluded to above, several of these mediators could also be used to predict survival. For instance, high intratumoral G-CSF levels correlated with reduced overall survival, which is supported in literature relating myeloid-derived suppressor cell infiltration to tumor progression and angiogenesis [45]. Of particular interest is the prolonged survival observed in patients with high intratumoral FGF-2, known to stimulate fibroblast migration, wound healing and generally thought to be a growth factor which supports growing tumors. However, it is generally accepted that FGF-2 is abundant in most tissues, concentrated in basement membranes and at cell surfaces in inactive forms. Tissue injury leads to FGF-2 activation and subsequent promotion of wound healing processes known to promote tumor growth, invasion and angiogenesis [46]. In this context, reduced FGF-2 concentrations in tissue homogenates may paradoxically reflect increased FGF-2 activation, which would lead to the expected findings of reduced survival.

The inability to follow the intratumoral inflammatory milieu over time represents a significant limitation to this type of analysis, as this information will be critical to elucidating the relationship between local inflammation and treatment strategies in PC. In addition, stratification of long-term survival into treatment-naïve and treatment-exposed tumors will be essential in validating these relationships. However, this analysis currently lacks the power to dichotomize in this fashion. While grouping mediators into functionally relevant categories may address our current lack of power, the pleiotropic nature of these soluble mediators may lead to improper interpretations in the absence of functional analyses. Further, it has not escaped our notice that VEGF demonstrated no correlation with survival in this analysis. The extensive body of work associating VEGF signaling with angiogenesis and tumor progression has led many groups to investigate potential correlations between VEGF expression and survival in PC. Subsequent analyses have yielded conflicting results [4749]. Importantly, this is not the first clinical cohort to demonstrate a nonsignificant correlation between intratumoral VEGF levels and overall survival in PC.

Conclusions

In summary, pancreatic adenocarcinoma is a devastating malignancy with an extremely poor prognosis. High ratios of tumor stroma to cancer cells plague the sensitivity of cytologic diagnosis of PC; In fact, even direct pathologic analysis of PC biopsies can yield inconsistent results with high interobserver variability [50]. Highly specific, reliable biochemical signatures obtained from these small samples that improve diagnostic sensitivity could dramatically improve the clinical care of PC patients. Further, treatment algorithms for PC in the absence of metastasis are currently anatomic based and lack attention to variations in biology. Thus, there is further need to develop accurate biomarkers capable of predicting response to systemic therapies or the futility of surgical or radiation therapy. Unfortunately, the current literature is characterized by marked variability between individual studies as to the relative prognostic impact of several biomarkers in PC. Here, in contrast to studies that evaluated these properties using a single or a couple biomarkers, we have identified novel relationships between tissue examination and clinical outcome by quantitatively evaluating the milieu of the tumor microenvironment utilizing fresh pancreatic surgical specimens. It is important to note that even though some of these associations are counterintuitive based on the currently understood biology, the greater context and complexity of the tumor microenvironment in PC is not currently appreciated. Thus, these data combined with a better understanding of the context-dependence of inflammatory signaling, may eventually offer the opportunity to identify patterns that improve interpretations in cancer and emphasize the importance of investigating the tumor microenvironment as a whole. Nonetheless, results presented here exhibit a high degree of reproducibility and provide rationale to prospectively evaluate these markers as diagnostic and prognostic tools.

Declarations

Acknowledgements

This research was supported by funding from the NIH (NCI 5T32CA106493-09) as well as the Cracchiolo Foundation.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Surgery, College of Medicine, University of Florida Health Science Center, Room 6116, Shands Hospital, 1600 SW Archer Rd, Gainesville, FL 32610, USA
(2)
Department of Oral Biology, College of Dentistry, University of Florida Health Science Center, Gainesville, FL 32610, USA
(3)
North Florida/South Georgia Veterans Health System, Department of Surgery, University of Florida College of Medicine, Gainesville, FL 32610, USA
(4)
Department of Pathology, College of Medicine, University of Florida Health Science Center, Gainesville, FL 32610, USA
(5)
Department of Medicine, College of Medicine, University of Florida Health Science Center, Gainesville, FL 32610, USA

References

  1. Burris 3rd HA, Moore MJ, Andersen J, Green MR, Rothenberg ML, Modiano MR, et al. Improvements in survival and clinical benefit with gemcitabine as first-line therapy for patients with advanced pancreas cancer: a randomized trial. J Clin Oncol. 1997;15(6):2403–13.PubMedGoogle Scholar
  2. Conroy T, Desseigne F, Ychou M, Bouche O, Guimbaud R, Becouarn Y, et al. FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer. N Engl J Med. 2011;364(19):1817–25.View ArticlePubMedGoogle Scholar
  3. Moore MJ, Goldstein D, Hamm J, Figer A, Hecht JR, Gallinger S, et al. Erlotinib plus gemcitabine compared with gemcitabine alone in patients with advanced pancreatic cancer: a phase III trial of the National Cancer Institute of Canada Clinical Trials Group. J Clin Oncol. 2007;25(15):1960–6.View ArticlePubMedGoogle Scholar
  4. Wolf AM, Pucci MJ, Gabale SD, McIntyre CA, Irizarry AM, Kennedy EP, et al. Safety of perioperative aspirin therapy in pancreatic operations. Surgery. 2014;155(1):39–46.View ArticlePubMedGoogle Scholar
  5. Rahib L, Smith BD, Aizenberg R, Rosenzweig AB, Fleshman JM, Matrisian LM. Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer Res. 2014;74(11):2913–21.View ArticlePubMedGoogle Scholar
  6. Muerkoster S, Wegehenkel K, Arlt A, Witt M, Sipos B, Kruse ML, et al. Tumor stroma interactions induce chemoresistance in pancreatic ductal carcinoma cells involving increased secretion and paracrine effects of nitric oxide and interleukin-1beta. Cancer Res. 2004;64(4):1331–7.View ArticlePubMedGoogle Scholar
  7. Hausmann S, Kong B, Michalski C, Erkan M, Friess H. The role of inflammation in pancreatic cancer. Adv Exp Med Biol. 2014;816:129–51.View ArticlePubMedGoogle Scholar
  8. Kadaba R, Birke H, Wang J, Hooper S, Andl CD, Di Maggio F, et al. Imbalance of desmoplastic stromal cell numbers drives aggressive cancer processes. J Pathol. 2013;230(1):107–17.View ArticlePubMedPubMed CentralGoogle Scholar
  9. Vonlaufen A, Joshi S, Qu C, Phillips PA, Xu Z, Parker NR, et al. Pancreatic stellate cells: partners in crime with pancreatic cancer cells. Cancer Res. 2008;68(7):2085–93.View ArticlePubMedGoogle Scholar
  10. Koay EJ, Truty MJ, Cristini V, Thomas RM, Chen R, Chatterjee D, et al. Transport properties of pancreatic cancer describe gemcitabine delivery and response. J Clin Invest. 2014;124(4):1525–36.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pages C, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science. 2006;313(5795):1960–4.View ArticlePubMedGoogle Scholar
  12. Zhang L, Conejo-Garcia JR, Katsaros D, Gimotty PA, Massobrio M, Regnani G, et al. Intratumoral T cells, recurrence, and survival in epithelial ovarian cancer. N Engl J Med. 2003;348(3):203–13.View ArticlePubMedGoogle Scholar
  13. Naito Y, Saito K, Shiiba K, Ohuchi A, Saigenji K, Nagura H, et al. CD8+ T cells infiltrated within cancer cell nests as a prognostic factor in human colorectal cancer. Cancer Res. 1998;58(16):3491–4.PubMedGoogle Scholar
  14. Chatterjee D, Katz MH, Rashid A, Estrella JS, Wang H, Varadhachary GR, et al. Pancreatic intraepithelial neoplasia and histological changes in non-neoplastic pancreas associated with neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma. Histopathology. 2013;63(6):841–51.View ArticlePubMedGoogle Scholar
  15. Fukunaga A, Miyamoto M, Cho Y, Murakami S, Kawarada Y, Oshikiri T, et al. CD8+ tumor-infiltrating lymphocytes together with CD4+ tumor-infiltrating lymphocytes and dendritic cells improve the prognosis of patients with pancreatic adenocarcinoma. Pancreas. 2004;28(1):e26–31.View ArticlePubMedGoogle Scholar
  16. Bang UC, Benfield T, Hyldstrup L, Bendtsen F, Beck Jensen JE. Mortality, cancer, and comorbidities associated with chronic pancreatitis-a Danish nationwide matched-cohort study. Gastroenterology. 2013;146(4):989–94.View ArticlePubMedGoogle Scholar
  17. Gillies RJ, Verduzco D, Gatenby RA. Evolutionary dynamics of carcinogenesis and why targeted therapy does not work. Nat Rev Cancer. 2012;12(7):487–93.View ArticlePubMedPubMed CentralGoogle Scholar
  18. Chopra M, Lang I, Salzmann S, Pachel C, Kraus S, Bauerlein CA, et al. Tumor necrosis factor induces tumor promoting and anti-tumoral effects on pancreatic cancer via TNFR1. PLoS One. 2013;8(9):e75737.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Means AL, Meszoely IM, Suzuki K, Miyamoto Y, Rustgi AK, Coffey Jr RJ, et al. Pancreatic epithelial plasticity mediated by acinar cell transdifferentiation and generation of nestin-positive intermediates. Development. 2005;132(16):3767–76.View ArticlePubMedGoogle Scholar
  20. Ellenrieder V, Hendler SF, Ruhland C, Boeck W, Adler G, Gress TM. TGF-beta-induced invasiveness of pancreatic cancer cells is mediated by matrix metalloproteinase-2 and the urokinase plasminogen activator system. Int J Cancer. 2001;93(2):204–11.View ArticlePubMedGoogle Scholar
  21. Greco E, Basso D, Fogar P, Mazza S, Navaglia F, Zambon CF, et al. Pancreatic cancer cells invasiveness is mainly affected by interleukin-1beta not by transforming growth factor-beta1. Int J Biol Markers. 2005;20(4):235–41.PubMedGoogle Scholar
  22. Melisi D, Niu J, Chang Z, Xia Q, Peng B, Ishiyama S, et al. Secreted interleukin-1alpha induces a metastatic phenotype in pancreatic cancer by sustaining a constitutive activation of nuclear factor-kappaB. Mol Cancer Res. 2009;7(5):624–33.View ArticlePubMedPubMed CentralGoogle Scholar
  23. Miyamoto Y, Hosotani R, Doi R, Wada M, Ida J, Tsuji S, et al. Interleukin-6 inhibits radiation induced apoptosis in pancreatic cancer cells. Anticancer Res. 2001;21(4A):2449–56.PubMedGoogle Scholar
  24. Bellone G, Smirne C, Mauri FA, Tonel E, Carbone A, Buffolino A, et al. Cytokine expression profile in human pancreatic carcinoma cells and in surgical specimens: implications for survival. Cancer Immunol Immunother. 2006;55(6):684–98.View ArticlePubMedGoogle Scholar
  25. Takamori H, Oades ZG, Hoch OC, Burger M, Schraufstatter IU. Autocrine growth effect of IL-8 and GROalpha on a human pancreatic cancer cell line, Capan-1. Pancreas. 2000;21(1):52–6.View ArticlePubMedGoogle Scholar
  26. Rhim AD, Oberstein PE, Thomas DH, Mirek ET, Palermo CF, Sastra SA, et al. Stromal Elements Act to Restrain, Rather Than Support, Pancreatic Ductal Adenocarcinoma. Cancer Cell. 2014;25(6):735–47.View ArticlePubMedPubMed CentralGoogle Scholar
  27. Evans DB, Rich TA, Byrd DR, Cleary KR, Connelly JH, Levin B, et al. Preoperative chemoradiation and pancreaticoduodenectomy for adenocarcinoma of the pancreas. Arch Surg. 1992;127(11):1335–9.View ArticlePubMedGoogle Scholar
  28. Breslin TM, Hess KR, Harbison DB, Jean ME, Cleary KR, Dackiw AP, et al. Neoadjuvant chemoradiotherapy for adenocarcinoma of the pancreas: treatment variables and survival duration. Ann Surg Oncol. 2001;8(2):123–32.View ArticlePubMedGoogle Scholar
  29. Le Scodan R, Mornex F, Partensky C, Mercier C, Valette PJ, Ychou M, et al. Histopathological response to preoperative chemoradiation for resectable pancreatic adenocarcinoma: the French Phase II FFCD 9704-SFRO Trial. Am J Clin Oncol. 2008;31(6):545–52.View ArticlePubMedGoogle Scholar
  30. White RR, Xie HB, Gottfried MR, Czito BG, Hurwitz HI, Morse MA, et al. Significance of histological response to preoperative chemoradiotherapy for pancreatic cancer. Ann Surg Oncol. 2005;12(3):214–21.View ArticlePubMedGoogle Scholar
  31. La Torre M, Nigri G, Petrucciani N, Cavallini M, Aurello P, Cosenza G, et al. Prognostic assessment of different lymph node staging methods for pancreatic cancer with R0 resection: pN staging, lymph node ratio, log odds of positive lymph nodes. Pancreatology. 2014;14(4):289–94.View ArticlePubMedGoogle Scholar
  32. Infante JR, Matsubayashi H, Sato N, Tonascia J, Klein AP, Riall TA, et al. Peritumoral fibroblast SPARC expression and patient outcome with resectable pancreatic adenocarcinoma. J Clin Oncol. 2007;25(3):319–25.View ArticlePubMedGoogle Scholar
  33. Von Hoff DD, Ramanathan RK, Borad MJ, Laheru DA, Smith LS, Wood TE, et al. Gemcitabine plus nab-paclitaxel is an active regimen in patients with advanced pancreatic cancer: a phase I/II trial. J Clin Oncol. 2011;29(34):4548–54.View ArticleGoogle Scholar
  34. Beatty GL, Chiorean EG, Fishman MP, Saboury B, Teitelbaum UR, Sun W, et al. CD40 agonists alter tumor stroma and show efficacy against pancreatic carcinoma in mice and humans. Science. 2011;331(6024):1612–6.View ArticlePubMedPubMed CentralGoogle Scholar
  35. Luheshi N, Davies G, Legg J. Understanding the influence of the tumor microenvironment on macrophage responses to CD40 agonists. Oncoimmunology. 2014;3(1):e27615.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Costello E, Greenhalf W, Neoptolemos JP. New biomarkers and targets in pancreatic cancer and their application to treatment. Nat Rev Gastroenterol Hepatol. 2012;9(8):435–44.View ArticlePubMedGoogle Scholar
  37. Karin M. Nuclear factor-kappaB in cancer development and progression. Nature. 2006;441(7092):431–6.View ArticlePubMedGoogle Scholar
  38. Roca H, Craig MJ, Ying C, Varsos ZS, Czarnieski P, Alva AS, et al. IL-4 induces proliferation in prostate cancer PC3 cells under nutrient-depletion stress through the activation of the JNK-pathway and survivin up-regulation. J Cell Biochem. 2012;113(5):1569–80.PubMedPubMed CentralGoogle Scholar
  39. Lee SO, Pinder E, Chun JY, Lou W, Sun M, Gao AC. Interleukin-4 stimulates androgen-independent growth in LNCaP human prostate cancer cells. Prostate. 2008;68(1):85–91.View ArticlePubMedGoogle Scholar
  40. Prokopchuk O, Liu Y, Henne-Bruns D, Kornmann M. Interleukin-4 enhances proliferation of human pancreatic cancer cells: evidence for autocrine and paracrine actions. Br J Cancer. 2005;92(5):921–8.View ArticlePubMedPubMed CentralGoogle Scholar
  41. Eguchi J, Hiroishi K, Ishii S, Baba T, Matsumura T, Hiraide A, et al. Interleukin-4 gene transduced tumor cells promote a potent tumor-specific Th1-type response in cooperation with interferon-alpha transduction. Gene Ther. 2005;12(9):733–41.View ArticlePubMedGoogle Scholar
  42. Mace TA, Ameen Z, Collins A, Wojcik S, Mair M, Young GS, et al. Pancreatic cancer-associated stellate cells promote differentiation of myeloid-derived suppressor cells in a STAT3-dependent manner. Cancer Res. 2013;73(10):3007–18.View ArticlePubMedPubMed CentralGoogle Scholar
  43. Pylayeva-Gupta Y, Lee KE, Hajdu CH, Miller G, Bar-Sagi D. Oncogenic Kras-induced GM-CSF production promotes the development of pancreatic neoplasia. Cancer Cell. 2012;21(6):836–47.View ArticlePubMedPubMed CentralGoogle Scholar
  44. Xie K. Interleukin-8 and human cancer biology. Cytokine Growth Factor Rev. 2001;12(4):375–91.View ArticlePubMedGoogle Scholar
  45. Shojaei F, Wu X, Qu X, Kowanetz M, Yu L, Tan M, et al. G-CSF-initiated myeloid cell mobilization and angiogenesis mediate tumor refractoriness to anti-VEGF therapy in mouse models. Proc Natl Acad Sci. 2009;106(16):6742–7.View ArticlePubMedPubMed CentralGoogle Scholar
  46. Kato M, Wang H, Kainulainen V, Fitzgerald ML, Ledbetter S, Ornitz DM, et al. Physiological degradation converts the soluble syndecan-1 ectodomain from an inhibitor to a potent activator of FGF-2. Nat Med. 1998;4(6):691–7.View ArticlePubMedGoogle Scholar
  47. Smith RA, Tang J, Tudur-Smith C, Neoptolemos JP, Ghaneh P. Meta-analysis of immunohistochemical prognostic markers in resected pancreatic cancer. Br J Cancer. 2011;104(9):1440–51.View ArticlePubMedPubMed CentralGoogle Scholar
  48. Jamieson NB, Carter CR, McKay CJ, Oien KA. Tissue biomarkers for prognosis in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis. Clin Cancer Res. 2011;17(10):3316–31.View ArticlePubMedGoogle Scholar
  49. Ansari D, Rosendahl A, Elebro J, Andersson R. Systematic review of immunohistochemical biomarkers to identify prognostic subgroups of patients with pancreatic cancer. Br J Surg. 2011;98(8):1041–55.View ArticlePubMedGoogle Scholar
  50. Larghi A, Correale L, Ricci R, Abdulkader I, Monges G, Iglesias-Garcia J, et al. Interobserver agreement and accuracy of preoperative endoscopic ultrasound-guided biopsy for histological grading of pancreatic cancer. Endoscopy. 2014;47(4):308–14.PubMedGoogle Scholar

Copyright

© Delitto et al. 2015

Advertisement