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Original Articles

Precision Medicine and Pancreatic Cancer

A Gemcitabine Pathway Approach

Farrell, James J. MD; Moughan, Jennifer MS; Wong, Jonathan L. BS; Regine, William F. MD, FACR, FACRO; Schaefer, Paul MD; Benson, Al B. III MD, FACP, FASCO; Macdonald, John S. MD; Liu, Xiyong MD, PhD; Yen, Yun MD, PhD; Lai, Raymond MD, PhD; Zheng, Zhong MD, PhD; Bepler, Gerold MD, PhD; Guha, Chandan MD, PhD; Elsaleh, Hany MD, PhD

Author Information
doi: 10.1097/MPA.0000000000000710

Abstract

The availability of both gemcitabine-based and non–gemcitabine-based treatment regimens for pancreatic cancer and the overall poor dismal prognosis associated with this disease necessitate the validation of predictive markers of treatment response in this disease to facilitate precision medicine options.1–3 Radiation Therapy Oncology Group (RTOG) 9704 is a phase III randomized postoperative adjuvant study in patients with pancreatic cancer comparing prechemoradiation and postchemoradiation 5-fluorouracil (5-FU) with prechemoradiation and postchemoradiation gemcitabine and represents an ideal study for evaluating predictive markers of gemcitabine treatment response.4 Using it, we previously showed the protein expression of human equilibrative nucleoside transporter 1 (hENT1), the predominant transmembrane transporter for gemcitabine, as a possible treatment predictive marker in the adjuvant setting for pancreatic cancer,5 which was further validated by several subsequent studies (Supplementary Table 1, https://links.lww.com/MPA/A527).6–13

There are several reasons why there are conflicting data about the predictive value of other markers involved with gemcitabine metabolism (deoxycytidine kinase [DCK],7,14,15 ribonucleotide reductase 1 [RRM1],7,9,16–18 RRM2,17,19 and p53R2),20–22 some of which are being used in routine clinical practice to make decisions about precision medicine options for patients. First, several gene expression studies have been performed without the appropriate microdissection of the tumor tissue to separate it from the stromal tissue. This suggests that the protein-based markers by immunohistochemistry (IHC) represent the most reproducible methodology for these types of studies. Second, several studies used a heterogeneous collection of data, disease stages, and nonprospective and nonrandomized treatment regimens often involving multiple drug regimens. Finally, different antibodies and IHC scoring systems have been used across several studies.

In view of the appropriate design and prospective tissue collection of the RTOG 9704 study and its initial use in validating hENT1 as a promising predictive marker, we decided to use this study to analyze DCK, RRM1, RRM2 and p53R2 protein expressions, correlate them with treatment outcome, and compare our results with current existing published data to assess the predictive value of these markers for guiding precision medicine options with gemcitabine treatment.

MATERIALS AND METHODS

Patient Selection and Consent

The RTOG tissue bank received tumor blocks from a total of 229 of the 538 patients who had undergone surgical resection and was entered in the RTOG 9704 prospective adjuvant treatment trial. Permission to perform this study was obtained by the institutional review board.23 A tissue microarray (TMA), which was also used for the original hENT1 study, was constructed using tissue core samples from the patients enrolled in the RTOG 9704 study, using 3 cores from different areas of a patient's tumor.

IHC and Scoring

Rabbit polyclonal antibodies were raised against a synthetic human DCK peptide, and tissue IHC was performed per a previous study.24 Semiquantitative scoring of tumoral cytoplasmic staining was used for the evaluation of DCK protein expression by a single pathologist (R.L.). Staining of DCK protein was assigned a score from 0 to 2 based on staining intensity (no staining, 0; weakly positive staining, 1; and strongly positive staining, 2). A final score (0–200) was determined by multiplying the intensity score and the percentage of the positive cells in the specimen, as described previously.15 The mean score of triplicate tissues from each patient was used for analysis, and the scores were dichotomized into low and high DCKs based on the median score of all the cytoplasmic means per patient data in the 3 TMAs.

Immunofluorescence combined with AQUA, using antiserum to RRM1 that was generated from rabbits, was used to assess in situ expression of nuclear RRM1, as described previously.25 The final slides were scanned with SpotGrabber (HistoRx, New Haven, CT), and images were analyzed with AQUA (version 1.6, PM-2000; HistoRx) by a pathologist with experience in RRM1 staining (Z.Z.). The AQUA scores ranged from 0 (no expression) to 3000 (maximal observed expression) for the triplicate TMA tissues for each patient. The median value of the RRM1 expression levels was used to divide the patients into high and low RRM1 levels.

The tumoral protein expression of hRRM2 was performed using a mouse polyclonal antibody against hRRM2 (Convance, Princeton, NJ), as previously described.26 Two independent scorers (Y.Y. and X.L.) experienced with RRM2 IHC assessed and scored the cytoplasmic RRM2 immunostaining intensities, ranging from 0 (no staining) to 3 (maximum staining), with a consensus score being agreed upon if there was initial discordance between the 2 scorers.26 The mean cytoplasmic RRM2 score was assessed per patient, and the RRM2 cytoplasmic score was also categorized as “low RRM2” expression (mean cytoplasmic score, <1.5 [<mean + 1 SD]) and “high RRM2” expression (mean cytoplasmic score, ≥1.5 [≥mean + 1 SD]).

Because of nonspecific targeting of commercial p53R2 antibody, a new highly specific p53R2 antirabbit antibody was used.27 Details of the de-paraffinization protocol and IHC were described in a previous publication.28 Each sample was scored by 2 independent investigators in a double-blind manner (X.L. and Y.Y.), with a consensus score being agreed upon if there was initial discordance between the 2 scorers. Cytoplasmic staining of p53R2 protein was assigned a score from 0 to 2 based on staining intensity (no staining, 0; weakly positive staining, 1; and strongly positive staining, 2) per a previous study.27 The percentage of adenocarcinoma cells stained at each intensity level was recorded for each, resulting in weighted scores ranging between 0 and 200. For the purposes of statistical analysis, the scores were dichotomized into low and high p53R2 based on the median score.

IHC Biomarker Statistical Analysis

The DCK, RRM1, RRM2, and p53R2 (gemcitabine pathway biomarkers) IHC scores were submitted to the RTOG Statistical Department for an analysis without knowledge of patient demographics, treatment arm randomization, or outcome. A statistical comparison to assess whether missing data were associated with dichotomized baseline characteristics (pathological T stage [T1 and T2 vs T3 and T4], American Joint Committee on Cancer stage [I and II vs III and IV], primary tumor location [head vs everything else]) was carried out using the χ2 test for each of the markers.

Associations between the gemcitabine pathway biomarkers' protein expressions, dichotomized (“low” vs “high”) with tumor demographic details and treatment outcomes (overall survival [OS], disease-free survival [DFS]), were sought using the χ2 test and the Cox proportional hazards model. Both treatment arms of the study were analyzed. Overall survival and DFS were estimated using the Kaplan-Meier method, and the biomarkers were compared using the log-rank test. The following variables were included in the multivariate analyses based on an analysis of the original trial: age, sex, race, treatment arm (when appropriate), nodal involvement (no vs yes), tumor diameter (<3 vs ≥ 3 cm), Karnofsky Performance Score (100 and 90 vs 60, 70, and 80), and surgical margin status (negative vs positive and negative vs unknown). Results were expressed as hazard ratios (HRs) (HR > 1 denoting an increased risk of death) and considered significant at a P value of 0.05.

Literature Search

A systematic literature search up to December 2014 was performed in MEDLINE and EMBASE to identify relevant studies. An initial search study using recognized search terms ([hENT1 or DCK or RRM1 or RRM2 or p53R2] and [Pancreatic Cancer or Pancreatic Carcinoma] and [Gemcitabine]) was conducted. Studies were considered eligible for comparison with the current study if they were performed using IHC and in the adjuvant setting.

RESULTS

DCK Protein Expression

Of the 229 patient tumor samples evaluated, 186 had analyzable DCK immunostaining. There were no positive statistical associations between baseline characteristics and missing and determined DCK protein expressions (Supplementary Tables 2 and 3, https://links.lww.com/MPA/A527). For cytoplasm mean across 3 TMAs, the median score was 125.00 (min-max, 0.00–200.00) to dichotomize the results into low and high DCKs. High DCK expression was seen in 50 of 88 patients in the gemcitabine treatment arm and in 44 of 98 patients randomized to the 5-FU treatment arm.

Univariate and multivariate analyses for dichotomized DCK—low DCK versus high DCK—were performed for all patients (Table 1). By multivariate analysis, DCK expression was independently and significantly associated with OS despite adjusting for baseline characteristics in these multivariate models for the overall treatment group (HR, 0.71; P = 0.044) (Table 1, Fig. 1A), but this was not seen with DFS. Deoxycytidine kinase protein expression was not significantly associated with OS or DFS among those patients randomized to the gemcitabine treatment arm on the multivariate analysis (Table 1, Fig. 1B). However, the multivariate analysis confirmed an improved OS when comparing all patients with high DCK with patients with low DCK (HR, 0.50; P = 0.0026) (Table 1, Fig. 1C), but no association was seen for DFS in the 5-FU treatment arm.

T1-20
TABLE 1:
Overall Survival and DFS for hENT1, DCK, RRM1, RRM2, and p53R2 (Univariate and Multivariate Analysis)
F1-20
FIGURE 1:
Overall survival for DCK protein expression: a multivariate analysis. A, All patients. B, Gemcitabine treatment arm. C, 5-FU treatment arm.

RRM1 Protein Expression

Of the 229 patient tumor samples evaluated, 196 had analyzable RRM1 immunostaining. There were no positive statistical associations between baseline characteristics and missing and determined RRM1 protein expressions (Supplementary Tables 4 and 5, https://links.lww.com/MPA/A527). For nucleus staining maximum of the triplicate tissues from a single patient, the median of the mean of all TMAs was 971.38 (min-max, 27.14–3370.34), which was used as the cutoff to divide patients into “low RRM1” and “high RRM1.” High RRM1 staining was seen in 44 of 92 patients in the gemcitabine treatment arm and in 54 of 104 patients randomized to the 5-FU treatment arm.

Univariate and multivariate analyses for dichotomized RRM1—low RRM1 versus high RRM1—were performed for all patients (Table 1). Ribonucleotide reductase 1 expression was independently and significantly associated with OS (HR, 0.71; P = 0.031), but not DFS (HR, 0.84; P = 0.26), despite adjusting for baseline characteristics in these multivariate models for the overall treatment group (Table 1, Fig. 2A). We observed statistically significant prolonged OS (HR, 0.51; P = 0.0021) and DFS (HR, 0.65; P = 0.036) for patients with high RRM1 as compared with patients with low RRM1, for all patients treated with 5-FU (Table 1, Fig. 2C). No association between RRM1 protein expression and OS and DFS was seen in the gemcitabine-treated group (Table 1, Fig. 2B).

F2-20
FIGURE 2:
Overall survival for RRM1 protein expression: a multivariate analysis. A, All patients. B, Gemcitabine treatment arm. C, 5-FU treatment arm.

RRM2 Protein Expression

Of the 229 patient tumor samples evaluated, 189 had analyzable RRM2 immunostaining. There were no positive statistical associations between baseline characteristics and missing and determined RRM2 protein expressions (Supplementary Tables 6 and 7, https://links.lww.com/MPA/A527). High RRM2 staining was seen in 9 of 88 patients in the gemcitabine treatment arm and in 12 of 101 patients randomized to the 5-FU treatment arm.

Univariate and multivariate analyses for dichotomized RRM2—low RRM2 versus high RRM2—were performed for all patients (Table 1). Ribonucleotide reductase 2 expression was independently and significantly associated with DFS despite adjusting for baseline characteristics in these multivariate models for the overall treatment group (HR, 1.62 [95% confidence interval, 1.01–2.60]; P = 0.045) (Table 1, Fig. 3A). We observed prolonged DFS, which approached statistical significance for patients with low RRM2 as compared with patients with high RRM2, for all patients treated with gemcitabine (HR, 2.24 [95% confidence interval, 1.08–4.68]; P = 0.031) (Table 1, Fig. 3B). No association between RRM2 protein expression and OS was seen in the gemcitabine-treated group. In the 5-FU treatment arm, RRM2 expression was not significantly associated with OS or DFS after adjusting for baseline characteristics in these multivariate models (Table 1, Fig. 3C).

F3-20
FIGURE 3:
Overall survival for RRM2 protein expression: a multivariate analysis. A, All patients. B, Gemcitabine treatment arm. C, 5-FU treatment arm.

P53R2 Protein Expression

Of the 229 patient tumor samples evaluated, 163 had analyzable p53R2 immunostaining. There were no positive statistical associations between baseline characteristics and missing and determined p53R2 protein expressions (Supplementary Tables 8 and 9, https://links.lww.com/MPA/A527). For cytoplasm mean, the median is 1.3 (min-max, 0.00–2.00) to dichotomize the results into low and high p53R2. High p53R2 expression was seen in 44 of 74 patients in the gemcitabine treatment arm and in 55 of 89 patients randomized to the 5-FU treatment arm.

Univariate and multivariate analyses for dichotomized p53R2—low p53R2 versus high p53R2—were performed for all patients. p53R2 (Table 1) expression was not significantly associated with OS (HR, 1.07; P = 0.71) or DFS (HR, 1.01; P = 0.97) despite adjusting for baseline characteristics in these multivariate models for the overall treatment group (Table 1, Fig. 4A). Again, p53R2 protein expression was not significantly associated with OS or DFS among those patients randomized to either the gemcitabine treatment arm (OS: HR, 1.36, P = 0.25; DFS: HR, 1.62, P = 0.06) or the 5-FU treatment arm (OS: HR, 0.98, P = 0.92; DFS: HR, 0.76, P = 0.23) on the multivariate analysis (Table 1; Figs. 4B, C).

F4-20
FIGURE 4:
Overall survival for p53R2 protein expression: a multivariate analysis. A, All patients. B, Gemcitabine treatment arm. C, 5-FU treatment arm.

DISCUSSION

Several lessons were learned from the initial RTOG 9704 study of hENT1, which supported its role as a promising predictive marker of treatment response for precision medicine in pancreatic cancer and its subsequent validation in other studies.5 First, the importance of disease stage and treatment setting is important when discussing the predictive value of a possible marker. The studies supporting hENT1 are all in the adjuvant setting,6–13 with no strong evidence to support its role in the advanced or metastatic stage12,29 and unclear significance in the neoadjuvant setting.30,31 In addition, the methodology for quantitating the marker is important. It is important to know whether protein or RNA is being measured, what type of antibody is being used, whether a TMA to increase tumor representation is used, and the marker scoring system used including marker location (eg, cytoplasm vs nuclear location) and appropriate cutoffs. For example, if messenger RNA (mRNA) is being measured, then microdissection of tumor is important.32,33 Finally, the availability of well-characterized prospectively treated patients with both gemcitabine and nongemcitabine treatment arms is important to formally assess the predictive value of a marker, rather than only the prognostic value.5,11,12 Hence, this study aimed to validate other non-hENT1 gemcitabine-related markers using the RTOG 9704 tissue in the adjuvant setting and using a previously standardized IHC methodology.

Deoxycytidine kinase is the enzyme responsible for the rate-limiting step, which converts the prodrug gemcitabine to its active monophosphorylated form.34 One study correlated high DCK mRNA levels with prolonged DFS in patients with pancreatic cancer receiving palliative gemcitabine,33 and another study showed no correlation at all.32 Our data do not support the predictive role for tumoral cytoplasmic DCK protein to determine outcome response to gemcitabine in the adjuvant setting in pancreatic cancer. This is in contradistinction to other IHC studies, which have suggested DCK as a gemcitabine predictive marker (Table 2).7,14,15 Although these studies used a similar antibody and DCK cytoplasmic scoring system, two are small retrospective studies that did not use TMA analysis or did not include heterogeneous treatment groups.14,15 The more recent large study in the adjuvant setting is complicated by its retrospective tissue and data collection methodology and the absence of a randomized nongemcitabine treatment arm.7 Interestingly, our current study did seem to support an association between high levels of DCK and OS for the entire study group (both treatment arms) likely because of the effect seen in the 5-FU treatment arm. There are some preclinical cell data supporting the association between high DCK levels and 5-FU sensitivity, but very little is known about the precise mechanism.35 Similarly, cell data have shown that RRM1 significantly contributes to the induction of DNA damage by 5-FU possibly related to RAD51 focus formation.36 It is possible that it reflects an increased sensitivity of proliferating cells to 5-FU, with DCK and possibly RRM1 being the key enzymes of DNA synthesis.

T2-20
TABLE 2:
DCK, RRM1, and RRM2 Expressions by IHC in Pancreatic Cancer

Ribonucleotide reductase 1, a multimeric enzyme that converts ribonucleotides to deoxyribonucleosides, has been reported as a predictive marker of gemcitabine treatment response in pancreatic cancer in several preclinical studies.37,38 Several very small clinical studies in pancreatic cancer have demonstrated an association between low RRM1 expression (as determined by quantitative reverse transcription polymerase chain reaction37,39 or IHC16). In the study showing an association with survival in a gemcitabine-treated cohort and low RRM1 protein expression, only nuclear expression was measured, and the association was not seen for patients with a high expression of RRM1. Similar to our larger study, there are also several other large RNA-based and IHC studies that do not demonstrate the predictive value of RRM1 (Table 2).7,17,18,32,40 Two studies have demonstrated the predictive value of combining low RRM1 and high hENT1 to predict improved survival with or without the expression of other markers such as RRM2 and DCK.9,33

We demonstrated an association between high tumor RRM2 protein expression and decreased DFS in patients with pancreatic cancer receiving adjuvant therapy in a prospective randomized trial. This effect was not seen in patients treated with 5-FU alone, suggesting that tumor RRM2 protein levels may function as a predictive marker of response to treatment with gemcitabine. This is in keeping with previous nonpancreatic cancer data, which associated high levels of RRM2 expression (either by protein or gene expression) with gemcitabine chemoresistance and worse survival.27,41 The importance of the ribonucleotidase redcutase RRM2 enzyme in cancer prognosis, and as a potential predictive marker for response to gemcitabine treatment, has been reported in several preclinical cancer models including lung cancer25,42–44 and pancreatic cancer.32,34,37,45–47 However, the other clinical data supporting the role for RRM2 as a predictive marker of gemcitabine response are conflicting. Lower pretreatment RRM2 mRNA expression of endoscopic ultrasound–guided fine-needle aspiration biopsy specimens from patients with pancreatic cancer was associated with improved median survival and overall response rate after gemcitabine treatment.45 However, in a larger study of both RRM1 and RRM2 gene expressions in laser microdissected pancreatic surgical or biopsy specimens, there was no association between gene expression and pancreatic cancer disease survival after treatment with gemcitabine.32 A recent retrospective non-TMA RRM2 protein expression study in the adjuvant setting with pancreatic cancer supports the concept of high RRM2 expression corresponding with worse OS and DFS in the overall patient group, as well as the 74 patients receiving adjuvant therapy (Table 2).

The p53-inducible p53R2 gene also plays an important role in DNA repair and synthesis after DNA damage.48–50 The expression of p53R2 has been variably correlated with an overall prognosis in patients with esophageal squamous cell carcinoma, early-stage non–small cell lung cancer, and colon cancer.27,41 To date, there has been no study of p53R2 in pancreatic cancer, as either a prognostic or predictive biomarker. This current study does not favor p53R2 to be either prognostic or predictive of treatment response in the adjuvant pancreatic cancer setting.

In conclusion, our current study does not support the predictive roles of DCK, RRM1, or p53R2 in the precision medicine guided treatment of pancreatic cancer with gemcitabine in the adjuvant setting but does support the possible predictive value of RRM2. Although our study did not combine multiple markers, as has been conducted in other studies, it is unlikely to have proven of benefit in this particular study. For now, efforts should focus on hENT1 as a valid predictive marker of the treatment response of gemcitabine in pancreatic cancer.

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Keywords:

pancreatic cancer; precision medicine; hENT1; DCK; RRM1; RRM2

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