Transport properties of pancreatic cancer describe gemcitabine delivery and response

Abstract

Background: The therapeutic resistance of pancreatic ductal adenocarcinoma (PDAC) is partly ascribed to ineffective delivery of chemotherapy to cancer cells. We hypothesized that physical properties at vascular, extracellular, and cellular scales influence delivery of and response to gemcitabine-based therapy.

Methods: We developed a method to measure mass transport properties during routine contrast-enhanced CT scans of individual human PDAC tumors. Additionally, we evaluated gemcitabine infusion during PDAC resection in 12 patients, measuring gemcitabine incorporation into tumor DNA and correlating its uptake with human equilibrative nucleoside transporter (hENT1) levels, stromal reaction, and CT-derived mass transport properties. We also studied associations between CT-derived transport properties and clinical outcomes in patients who received preoperative gemcitabine-based chemoradiotherapy for resectable PDAC.

Results: Transport modeling of 176 CT scans illustrated striking differences in transport properties between normal pancreas and tumor, with a wide array of enhancement profiles. Reflecting the interpatient differences in contrast enhancement, resected tumors exhibited dramatic differences in gemcitabine DNA incorporation, despite similar intravascular pharmacokinetics. Gemcitabine incorporation into tumor DNA was inversely related to CT-derived transport parameters and PDAC stromal score, after accounting for hENT1 levels. Moreover, stromal score directly correlated with CT-derived parameters. Among 110 patients who received preoperative gemcitabine-based chemoradiotherapy, CT-derived parameters correlated with pathological response and survival.

Conclusion: Gemcitabine incorporation into tumor DNA is highly variable and correlates with multiscale transport properties that can be derived from routine CT scans. Furthermore, pretherapy CT-derived properties correlate with clinically relevant endpoints.

Trial registration: Clinicaltrials.gov NCT01276613.

Funding: Lustgarten Foundation (989161), Department of Defense (W81XWH-09-1-0212), NIH (U54CA151668, KCA088084).

Figures

Figure 1. Deriving transport properties of pancreatic tumors from routine CT scans.

(A) Measurement technique. The pancreatic protocol involved well-timed scans in relation to contrast injection: precontrast, arterial phase, and portal venous phase (dashed lines denote representative measurement area). Systematic measurements of the pancreatic tumor and normal pancreas were recorded, and a model was developed to derive transport properties from these measurements. The model function can be integrated with time to derive AUC, and a simple piecewise linear function can be used to estimate AUC. (B) Scans from 2 patients with different enhancement patterns in the normal pancreas and pancreatic tumor are shown. The density changed with time due to intravasation of contrast into the tissues. Modeled density changes are shown, demonstrating that the model provides transport parameters for each patient’s normal tissue (blue line) and cancer (red line). (C) AUC representing the time integral of enhancement in the tissue of interest. The model was validated by comparing tissue-derived parameters with the enhancement in the aorta at the level of the celiac axis, which should reflect enhancement in the tissues. The graph for all 176 patients with pancreatic protocol CTs in this study shows how normal pancreas closely reflected aortic enhancement, whereas pancreatic tumors had higher variability. (D) Distributions of the parameter AUC from CT scans of 176 patients, grouped by pancreatic tissue type. Significant differences in the distribution of transport parameters were evident between normal pancreas and pancreatic tumor, with tumors exhibiting worsened transport properties.

Figure 2. Clinical trial of intraoperative gemcitabine.

(A) Trial design. Patients were evaluated for appropriateness for resection before infusion of gemcitabine. Gemcitabine infusion was initiated at the start of resection (asterisk; 50–100 minutes prior to specimen removal, with time dependent on drug dose) and infused at a fixed rate (see Methods). Pathological analysis and quantitative assessment of gemcitabine incorporation were then performed. (B) Immediately after tumor resection, specimens were collected using standard surgical pathology techniques, and punch biopsies of the tumor and normal pancreas were taken to measure gemcitabine incorporation into DNA. (C) Blood samples were collected at regular intervals during the intraoperative infusion of gemcitabine, so that drug concentration could be measured by HPLC and intravascular pharmacokinetics could be analyzed. The similar slopes of the lines and the tight distribution of serum gemcitabine concentrations at each time point indicate that the infusion conditions were similar for all 12 trial patients. (D) DNA was extracted from tumor biopsy samples and analyzed for gemcitabine incorporation (measured relative to deoxyguanosine) into the DNA of pancreatic tumor cells. A positive value indicates more gemcitabine incorporation into the tumor compared with normal pancreas; a negative value indicates less. Marked variability was observed in the amount of gemcitabine incorporated for the 12 trial patients.

Figure 3. Correlations between transport properties and gemcitabine incorporation.

(A) Normalized gemcitabine incorporation for each patient on the clinical trial of intraoperative gemcitabine infusion during PDAC resection, measured using specimens obtained directly from the tumor (see Figure 2B). Surgical specimens were scored for hENT1 staining (see Supplemental Table 6). A significant difference was observed in the normalized gemcitabine incorporation when divided by hENT1 score (2-tailed t test; mean and SD indicated by short and long lines, respectively). (B) Stroma amount was scored independently by a pathologist, and gemcitabine incorporation in the tumor and normal pancreas were measured. After accounting for hENT1 score, a significant inverse correlation was seen with normalized gemcitabine incorporation (linear regression). (C) Pretherapy CTs of each patient in the clinical trial of intraoperative gemcitabine infusion during PDAC resection were derived, and the normalized CT-derived parameter AUC was plotted against the stromal scores from surgical pathology for the corresponding patient. A direct linear correlation was observed. (D) Normalized AUC was plotted against the measured gemcitabine (dFdC) incorporation into pancreatic tumor cell DNA (expressed relative to deoxyguanosine [dG]). A significant inverse correlation was observed (linear regression), in agreement with the inverse correlation found for the stromal score (B), which directly correlated with the normalized CT parameter AUC (C). The equation indicates how the CT parameter may be used to predict gemcitabine incorporation in future clinical trials.

Figure 4. Correlations between transport properties and response.

(A) Representative histology, CT profiles, and normalized AUC values for patients with excellent (trace viable tumor cells) and minimal (approximately 70% viable tumor cells) responses to therapy. The patient with an excellent response had higher normalized AUC than the patient with a minimal response. (B) Normalized AUC was measured from the pretherapy CT scans of the patients who underwent surgery for potentially resectable PDAC in 2 phase 2 clinical trials of preoperative gemcitabine-based regimens (19, 20). The pathological response to therapy was scored by a pathologist. Higher normalized AUC appeared to correlate with better pathological response (linear regression). Notably, Spearman rank-order correlation was also significant (–0.30; 95% CI, –0.51 to –0.05; P = 0.02).

Figure 5. Correlations between transport properties and survival.

(A) Using a partitioning analysis for all 110 patients who received gemcitabine-based therapy in 2 published phase II trials for potentially resectable PDAC (19, 20), a cutoff of 0.6 was identified for normalized AUC (values greater than 0.6 were considered high; all others were low). This designation separated patients with a good prognosis from those with a poor prognosis on univariate and multivariate analyses (see Supplemental Table 9). (B) Of the initial 110 patients who received gemcitabine-based therapies for potentially resectable PDAC, 80 underwent curative-intent surgery. When the same cutoff of 0.6 for normalized AUC was applied to these 80 patients, patients with good prognosis were again separated from those with poor prognosis. This finding was significant on univariate and multivariate analyses (see Supplemental Table 10).

Figure 6. Multiscale transport model of response to therapy.

(i) The CT-derived parameters describe vascular tissue transport qualities (Figure 1) and also reflect underlying histopathology (Figure 3). (ii) The clinical trial demonstrated highly variable drug delivery (Figure 2) and showed that more stroma led to less gemcitabine incorporation (Figure 3). (iii) The clinical trial also illustrated how hENT1 expression can influence gemcitabine incorporation (Figure 3). (iv) The response to and outcome after therapy correlated with the CT-derived parameters (Figures 4 and 5 and Tables 1 and 2). CDA, cytidine deaminase; DCK, deoxycytidine kinase; dFdU, 2′,2′ difluorodeoxyuridine; dFdCTP, 2′,2′ difluorodeoxycytidine triphosphate.