Clinical Cancer Research Meeting Calendar Advances in Breast Cancer
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Langer, R.
Right arrow Articles by Höfler, H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Langer, R.
Right arrow Articles by Höfler, H.
Clinical Cancer Research Vol. 11, 7462-7469, October 15, 2005
© 2005 American Association for Cancer Research


Cancer Therapy: Clinical

Association of Pretherapeutic Expression of Chemotherapy-Related Genes with Response to Neoadjuvant Chemotherapy in Barrett Carcinoma

Rupert Langer1, Katja Specht1, Karen Becker1, Philipp Ewald1, Melitta Bekesch1, Mario Sarbia1, Raymonde Busch2, Marcus Feith3, Hubert J. Stein3, Jörg-Rüdiger Siewert3 and Heinz Höfler1,4

Authors' Affiliations: 1 Institutes of Pathology and 2 Medical Statistics and Epidemiology and 3 Department of Surgery, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany and 4 Institutes of Pathology, GSF National Research Center for Environment and Health, Neuherberg, Germany

Requests for reprints: Heinz Hoefler, Institute of Pathology, Klinikum Rechts der Isar, Technische Universität München Trogerstrasse 18, D-81675 München, Germany. Phone: 49-89-414-04160; Fax: 49-89-414-04865; E-mail: Hoefler{at}lrz.tu-muenchen.de.


    Abstract
 Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 
Purpose: We analyzed pretherapeutic gene expression patterns of patients with locally advanced adenocarcinomas of the esophagus with regard to response to neoadjuvant chemotherapy.

Experimental Design: Pretherapeutic, paraffin-embedded, formalin-fixed endoscopic esophageal tumor biopsies of 38 patients with locally advanced esophageal adenocarcinomas (Barrett adenocarcinoma) were included. All patients underwent two cycles of cisplatin and 5-fluorouracil (5-FU) therapy with or without additional paclitaxel followed by abdominothoracal esophagectomy. RNA expression levels of 5-FU metabolism-associated genes thymidylate synthase, thymidine phosphorylase, dihydropyrimidine dehydrogenase, methylenetetrahydrofolate reductase, MAP7, and ELF3, of platinum- and taxane-related genes caldesmon, ERCC1, ERCC4, HER-2/neu, and GADD45, and of multidrug resistance gene MRP1 were determined using real-time reverse transcriptase-PCR. Expression levels were correlated with response to chemotherapy, histopathologically assessed in surgically resected specimens.

Results: Responding patients showed significantly higher pretherapeutic expression levels of MTHFR (P = 0.012), caldesmon (P = 0.016), and MRP1 (P = 0.007). In addition, patients with high pretherapeutic MTHFR and MRP1 levels had a survival benefit after surgery (P = 0.013 and P = 0.015, respectively). Additionally, investigation of intratumoral heterogeneity of gene expression of relevant genes (MTHFR, caldesmon, HER-2/neu, ERCC4, and MRP1), verified in nine untreated Barrett adenocarcinomas by examination of five distinct tumor areas, revealed no significant heterogeneity in gene expression indicating that expression profiles obtained from biopsy material may yield a representative genetic expression profile of total tumor tissue.

Conclusions: Our results indicate that determination of mRNA levels of few genes may be useful for the prediction of the success of neoadjuvant chemotherapy in individual cancer patients with locally advanced Barrett adenocarcinoma.


Multimodal treatment protocols are being increasingly employed to improve the survival of patients with locally advanced adenocarcinoma of the esophagus. Neoadjuvant chemotherapy, mainly based on 5-fluorouracil (5-FU) and cisplatin, has been shown to induce tumor remission, and there seems to be a survival advantage for patients who respond to preoperative therapy compared with surgical treatment alone. However, in the majority of the patients, no objective response is achieved and the prognosis for patients with nonresponding tumors seems even worse than for patients treated by surgery only (1, 2). This is probably due to therapy-induced side effects, selection of chemotherapy-resistant, more aggressive tumor cell clones, and delay of surgery. Thus, there is a need for diagnostic methods that allow prediction of chemotherapy response and enable a pretherapeutic discrimination of treatment responders and nonresponders.

Several molecular markers have been investigated as potential response predictors to anticancer drugs. The expression of thymidylate synthase (TS), the target enzyme for 5-FU, has been shown to be significantly associated with response to 5-FU-based therapy in gastrointestinal tumors (3). In addition, an association between the gene expression of catabolic and inactivating enzymes, like thymidine phosphorylase (TP) and dihydopyrimidine dehydrogenase (DPD), and the response to 5-FU treatment has been described (4, 5). Furthermore, a correlation between the activity of methylenetetrahydrofolate reductase (MTHFR), an inhibitor of TS, and the response to 5-FU has been reported recently (6, 7).

The excision repair cross-complementing (ERCC) gene family prevents damage to DNA caused by agents such as cisplatin (8) and low expression of ERCC1 correlates with response to this drug (9, 10). Furthermore, an association between the expression of the HER-2 receptor and resistance to several anticancer drugs, including taxanes, cisplatin, and 5-FU, has been described (11), although the role of HER-2 in drug sensitivity is still uncertain.

Finally, chemotherapy resistance may be due to overexpression of multidrug resistance proteins, belonging to the ATP-binding cassette drug transporter family. These carrier proteins cause an efflux of drugs through an energy (ATP) consuming process. Among others, multidrug resistance protein 1 (MRP1), a member of this family have been shown to be responsible for resistance to a number of chemotherapeutics, among them both cisplatin and taxanes (12, 13).

In this study, we analyzed the expression of chemotherapy response–associated genes in pretreatment biopsies of locally advanced esophageal adenocarcinoma and correlated their expression with response to neoadjuvant chemotherapy. Genes for which an association with chemotherapy resistance has already been shown in several types of gastrointestinal tumors were TS, TP, DPD, MTHFR, ERCC1, ERCC4, GADD45, HER-2/neu, and MRP1. In addition, genes recently reported to predict chemosensitivity in a panel of cell lines [i.e., the microtubule-associated protein E-MAP 115 (MAP7), the ETS transcription factor family member ESE-1B (ELF3), and the actinomyosin regulatory protein caldesmon] were also included (14, 15).

Because clinical response evaluation after neoadjuvant therapy for esophageal cancer is known to be highly inaccurate (16), gene expression was correlated with histopathologically determined tumor regression (17) as well as with overall survival.

To verify the significance of gene expression obtained from biopsy material, intratumoral gene expression heterogeneity was additionally examined in tumor tissue of untreated, locally advanced Barrett adenocarcinomas and compared with the corresponding biopsies.


    Materials and Methods
 Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 
Tissue samples. We selected 38 patients with locally advanced (uT3N1) esophageal adenocarcinoma who underwent neoadjuvant chemotherapy between 1994 and 2002 in the Department of Surgery of the Technische Universität Munich, from whom both preoperative biopsy and surgical resection material (formalin-fixed, paraffin-embedded tissue) was available. The patients must have gotten two full cycles of neoadjuvant chemotherapy. Patients with therapy abort due to disease progress during chemotherapy or with severe toxic side effects of chemotherapy were excluded as well as patients that were additionally treated with radiotherapy.

The formalin-fixed and paraffin wax–embedded tissue blocks used in the present study were historical material obtained from surgical resection specimens. All patients gave consent at the time of their original operation. The use of these human tissue samples was approved by the local ethical committee.

Preoperative chemotherapy. Preoperative therapy consisted of two cycles of combination chemotherapy, each of 36 days' duration. On day 1, cisplatin at a dose of 50 mg/m2 body surface area was given as an i.v. infusion over a period of 1 hour. Thereafter, patients received leucovorin dose of 500 mg/m2 body surface area over a period of 2 hours followed by a 5-FU dose of 2 g/m2 body surface area over a period of 24 hours. Treatment with cisplatin was repeated on days 15 and 29. Infusion of leucovorin and 5-FU was repeated on days 8, 15, 22, 29, and 36. Sixteen of the patients were additionally treated with a paclitaxel dose of 80 mg/m2 body surface area over a period of 3 hours, 1 day before infusion of cisplatin. Surgical resection of the tumor (transhiatal or abdominothorakal esophagectomy) was scheduled 3 to 4 weeks after completion of chemotherapy.

Histopathologic analysis of resected tumors. To assess histopathologic tumor regression in response to chemotherapy, the resected tumors were evaluated by a pathologist (K.B.) according to a three-grade score established by Becker et al. (17). The entire macroscopic identifiable tumor or the area of scarring indicating the site of the previous tumor (the tumor bed) was cross-sectioned serially at 0.5-cm intervals and evaluated histologically. The grading of tumor regression was based on an estimation of the percentage of vital tumor tissue in relation to the tumor bed. Patients with no or <10% residual tumor cells (tumor regression score 1) were classified as responders. All other tumors (tumor regression score 2: 10-50% residual tumor cells and tumor regression score 3: >50% residual tumor cells) were classified as nonresponders.

Real-time quantitative reverse transcriptase-PCR. Microdissection, RNA extraction, cDNA synthesis, and reverse transcriptase-PCR was done as described previously with minor modifications (18). Pooled tumor tissue from at least two biopsies per case was analyzed: a minimum of 2,000 cells of defined carcinoma areas (verified by H.H.) was scraped off using a sterile blade and transferred into a sterile 1.5-mL tube containing RNA lysis buffer. Lysis was carried out at 60°C for 24 hours until the tissue was completely solubilized.

RNA was purified by phenol and chloroform extractions followed by precipitation with an equal volume of isopropanol in the presence of 20 µL of 2 mol/L sodium acetate (pH 4.0) and 2 µL of 10 mg/mL of carrier glycogen at –20°C. The RNA pellet was washed once in 70% ethanol, dried, and resuspended in 20 µL of RNase-free water.

Ten microliters of RNA were transcribed into cDNA using Superscript II reverse transcriptase (Invitrogen, Karlsruhe, Germany) and 250 ng of random hexamers (Roche, Penzberg, Germany) following the manufacturer's recommendations in a final volume of 20 µL. PCR reactions were done in at least two replicates with the Taqman Universal PCR Master Mix (15 µL, Applied Biosystems, Darmstadt, Germany) using 5 µL of diluted cDNA, 1 µL 200 nmol/L of the labeled probe, and 1 µL 300 nmol/L of primers in a 30-µL final reaction mixture for TS, TP, DPD, ERCC1, ERCC4, HER-2/neu, GADD45, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). For MTHFR, caldesmon, ELF3, MAP7, and MRP1 each, 1.5-µL predeveloped primer probe sets (Applied Biosystems, Assays-on-Demand Gene Expression Assay Mix) were used. Primers and probes for GADD45 were synthesized according to previously published data (19). Primer and probe sequences are available from the authors upon request.

Relative expression levels of target genes were determined by the relative standard curve method. Standard curves and line equations were generated using a standard cDNA solution from SW 480 colon carcinoma cell line (fresh frozen), which was serially 5-fold diluted and analyzed in duplicates for the genes of interest and GAPDH as a normalizing housekeeping gene (20). Based on the CT value and the corresponding standard curve, the mRNA quantity of each sample was calculated by determining the ratio between the amounts of the gene of interest and GAPDH.

Intratumoral heterogeneity. To study a possible interfering effect of i.t. heterogeneity of gene expression, we investigated nine cases of non-pretreated, surgically resected Barrett adenocarcinomas (Unio Internationale Contra Cancrum stage III) determining mRNA gene expression levels of MTHFR, ERCC4, caldesmon, MRP1, and HER-2/neu in relation to GAPDH in different tumor areas. Topographical fractional microdissection of tissue was carried out under microscopic control from five distinct tumor areas of each case (see Fig. 4). Gene expression levels were compared with the corresponding expression levels revealed from preoperative biopsies of the same case.



View larger version (8K):
[in this window]
[in a new window]
[Download PPT slide]
 
Fig. 4. Graphic illustration of sites of tumor tissue microdissection within each of the nine cases of advanced Barrett carcinoma: 1 and 3, superficial tumor periphery; 2, tumor center; 4 and 5, deep tumor periphery.

 
Statistical analysis. Statistical analysis was done using nonparametric methods. Comparisons between the two groups of responders and nonresponders were made using the Mann-Whitney U test. The diagnostic accuracy of the gene expression profile to predict subsequent response was evaluated by receiver operating characteristic analysis. The optimum cutoff value for differentiation of responding and nonresponding tumors was defined by the point of the receiver operating characteristic curve with maximum Youden index = sensitivity + specificity – 100% (21, 22). In addition, survival rates were estimated according to Kaplan-Meier. Statistical comparisons between the different subgroups of patients were done with a log-rank test.

For analyzing i.t. heterogeneity of gene expression, the Friedman test was used to determine significant differences of the gene expression levels in view of the various areas. To compare gene expression levels of postoperative tumor tissue with those of corresponding preoperative biopsy specimen, the Wilcoxon sign rank test was used. The significance level was set to 5%, two sided.


    Results
 Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 
Demographics and patients available for response and survival evaluation. With consideration of the criteria mentioned above, a total of 38 patients was included in this study. It consisted of four females (10.5%) and 34 males (89.5%) with a median age of 57 years (range, 36-72 years) reflecting the typical age and sex distribution of Barrett carcinoma. Survival data were available for all patients.

All 38 patients received 5-FU/cisplatin combination therapy and 16 patients were additionally treated with paclitaxel. According to histopathologic criteria as described above, 16 patients were classified as responders and 22 as nonresponders. Additional paclitaxel treatment did not influence response behavior or clinical outcome (data not shown).

Responding patients showed a benefit in survival compared with nonresponding patients (P = 0.025, log-rank test; Fig. 1).



View larger version (16K):
[in this window]
[in a new window]
[Download PPT slide]
 
Fig. 1. Kaplan-Meier survival curves for responders to neoadjuvant chemotherapy versus nonresponders.

 
Gene expression analysis. Expression of the 12 genes was detectable in all 38 biopsy samples. For MTHFR, caldesmon, and MRP1, significant differences in gene expression was noted between responders and nonresponders. In addition, responders had higher ERCC4 albeit these differences were not statistically significant. No significant difference between responders and nonresponders was observed for TS, TP, DPD, ELF3, ERCC1, ERCC4, MAP7, HER-2/neu, and GADD45 (Mann-Whitney U test; Table 1).


View this table:
[in this window]
[in a new window]

 
Table 1. Reverse transcriptase-PCR analysis: median gene expression levels (gene/GAPDH) of responding and nonresponding patients

 
Optimum cutoff values for discrimination of responding and nonresponding tumors were then calculated for MTHFR, ERCC4, caldesmon, and MRP1 and correlated with patients' survival.

MTHFR. The median MTHFR/GAPDH in tumor biopsies was 2.13 (range, 0.48-5.28). For responding patients, median MTHFR/GAPDH was 2.61 compared with 1.55 for nonresponding patients (P = 0.012, Mann-Whitney U test). All 16 responding patients had MTHFR/GAPDH > 1.48 compared with 11 of 22 nonresponders (sensitivity, 100%; specificity, 50%; Fig. 2A). MTHFR mRNA expression also correlated with survival; patients with MTHFR/GAPDH ratios > 1.48 had a median survival time of 45.2 months after surgery, whereas patients with MTHFR/GAPDH ratios < 1.48 had a median survival of 7.2 months (P = 0.015, log-rank test; Fig. 3A).



View larger version (16K):
[in this window]
[in a new window]
[Download PPT slide]
 
Fig. 2. A, tumor MTHFR mRNA levels (MTHFR/GAPDH) versus histopathologic response to neoadjuvant chemotherapy. B, tumor caldesmon mRNA levels (caldesmon/GAPDH) versus histopathologic response to neoadjuvant chemotherapy. C, tumor MRP1 mRNA levels (MRP1/GAPDH) versus histopathologic response to neoadjuvant chemotherapy. D, tumor ERCC4 mRNA levels (ERCC4/GAPDH) versus histopathologic response to neoadjuvant chemotherapy.

 


View larger version (13K):
[in this window]
[in a new window]
[Download PPT slide]
 
Fig. 3. A, Kaplan-Meier survival curves for patients with high-MTHFR versus low-MTHFR mRNA expression levels (cutoff, 1.48). B, Kaplan-Meier survival curves for patients with high-MRP1 versus low-MRP1 mRNA expression levels (cutoff, 0.91).

 
Caldesmon. Median caldesmon/GAPDH was 1.28 (range, 0.16-6.56). The median caldesmon/GAPDH for responding patients was 1.65 compared with 0.96 for nonresponding patients (P = 0.016, Mann-Whitney U test). Fourteen of 16 responding patients had high caldesmon/GAPDH ratios (> 0.90) compared with 11 of 22 nonresponders (sensitivity, 87.5%; specificity, 50%; Fig. 2B). In addition, there seems a trend for patients with high caldesmon/GAPDH showing prolonged survival, although this was statistically not significant (P = 0.23, log-rank test).

MRP1 (ABCC1). The median MRP1/GAPDH was 1.11 (range, 0.31-6.00). Responding patients had higher median MRP1/GAPDH than nonresponding patients (1.39 and 0.85, respectively; P = 0.007, Mann-Whitney U test). One of the 16 responding patients had MRP1/GAPDH < 0.91 compared with 14 of 22 nonresponders. (sensitivity, 93.8%; specificity, 63.6%; Fig. 2C). Patients with high MRP1 mRNA expression also showed prolonged survival (e.g., with a probability of survival of 0.73 at 24 months compared with 0.19 for patients with low MRP1 levels; P = 0.017, log-rank test; Fig. 3B).

ERCC4. Median ERCC4/GAPDH was 1.33 (range, 0.64-6.35). There was no significant difference in expression levels between responders and nonresponders, although there was a trend for median ERCC4/GAPDH to be higher in responding patients (2.57) than in nonresponding patients (1.82; P = 0.11, Mann-Whitney U test). However, 13 of 16 responding patients showed high ERCC4/GAPDH (> 2.0) compared with 9 of the 22 nonresponders (data not shown). A correlation between survival and ERCC4 expression was not found.

HER-2/neu. The median HER-2/neu/GAPDH was 3.83 (range, 1.4-111.6), and no significant difference in expression levels between responders and nonresponders could be found. However, five patients (13.2%; two responders and three nonresponders) showed a HER-2/neu overexpression defined as a 5.0-fold higher expression level compared with the median HER-2/neu level.

Intratumoral heterogeneity. To assess gene expression heterogeneity, MTHFR, ERCC4, caldesmon, MRP1, and HER-2/neu were examined in tumor tissue of nine patients with untreated, locally advanced Barrett carcinoma. From each case, five samples of tumor tissue from the primary tumor (superficial tumor periphery, deep tumor periphery, and tumor center), and in addition, tissue from the corresponding diagnostic biopsy were examined (Fig. 4).

Using the Friedman test for none of the investigated genes, significant i.t. heterogeneity was observed (Table 2A and B).


View this table:
[in this window]
[in a new window]

 
Table 2. Intratumoral heterogeneity in nine patients with primary resected Barrett carcinoma in biopsy and tumor tissue

 
Gene expression in biopsy material and whole tumor tissue. Comparison between gene expression measured in biopsy material and the median expression levels of the surgical resection material (each from the five separately investigated tumor areas) revealed the constant observation that the expression levels measured in biopsy material were higher than levels measured in resection material. For ERCC4, HER-2/neu, and MRP1, this difference was significant (P = 0.011, P = 0.011, and P = 0.038, respectively, Mann-Whitney U test). However, no significant difference in the ranking of patients' gene expression levels of biopsy and resection material was observed; that is, patients with higher gene expression levels in the biopsy had also higher median gene expression levels in the whole tumor and vice versa (Mann-Whitney U test).


    Discussion
 Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 
Neoadjuvant therapy in the treatment of Barrett carcinoma is done in an effort to improve the possibility of complete resection and to prolong overall and disease-free survival (1, 2). There are various attempts to predict the success of neoadjuvant treatment discriminating potential responders from nonresponders to avoid severe side effects of an unnecessary therapy.

In this study, we tested several molecular markers for their potential to predict therapy response. As most chemotherapy treatment regimes of both squamous cell carcinoma and adenocarcinoma of the esophagus are based on combinations of cisplatin, 5-FU, and recently also taxanes (1), we did mRNA expression profiling of genes known to be associated with these drugs.

5-FU acts by inhibiting TS, an enzyme involved in DNA synthesis. MTHFR partly controls the intracellular flux of folate derivates into the TS reaction. Thus, decreased enzyme activity of MTHFR may result in an increase of the amount of folates available for the TS reaction and the effect of TS inhibiting 5-FU might be enhanced in these individuals (23).

We found that tumors with high MTHFR levels (cutoff, 1.48) had a significantly better pathohistologic response, and patients showed a better survival than patients with low MTHFR expression in their tumor biopsies. There are no studies thus far investigating MTHFR expression and chemotherapy resistance. In contrast to our findings, a correlation between reduced MTHFR activity caused by polymorphism and favorable chemotherapy response to 5-FU therapy has been recently reported in colorectal and breast cancer (6, 24), but there are still no data concerning esophageal carcinomas. However, the regulation of the folate pool is complex, and decreased enzyme activity due to gene polymorphism may cause other effects in purine and folate metabolism than decreased or increased MTHFR expression.

In our study, no correlation between pretherapeutic levels of TS, TP, or DPD and response to neoadjuvant chemotherapy nor the survival of the patients was found.

Until now, chemotherapy resistance to 5-FU has been mainly investigated in colorectal cancer. A correlation between expression levels of TS, DPD, and TP and survival of patients has been observed in a number of studies, (4, 2528). However, most of these studies aim at the prediction of the success of adjuvant treatment of metastatic disease but not of neoadjuvant treatment. Interestingly, TS has been shown to be a prognostic marker with regard to survival rather than a predictive marker for local chemotherapy response. However, pretherapeutic TS, TP, or DPD expression levels also failed to correlate with survival in our collective.

Furthermore, we analyzed genes associated with the metabolism of platinum agents. Cisplatin is one of the most potent antitumor agents known, showing an even more pronounced activity in combination with 5-FU. Its cytotoxicity is believed to result from the formation of platinum-DNA adducts, which activate several signal transduction pathways causing the induction of apoptosis. The mechanisms implicated to be responsible for cisplatin resistance are manifold (i.e., decreased drug accumulation, increased drug inactivation, and an enhanced ability to repair and tolerate DNA damage). The ERCC gene family prevents damage to DNA by nucleotide excision and repair acting by a complex of ERCC1 with ERCC11, XPF, and ERCC4. ERCC1 has been shown to be connected to cisplatin resistance in esophageal (16), colorectal, and gastric cancer (9, 10). In our study, we could not show a significant correlation between ERCC1 expression and neoadjuvant chemotherapy response, although more responders than nonresponders showed high ERCC4 levels suggesting an important role of genes associated with nuclear excision repair in resistance to cisplatin.

Interestingly, we could identify a novel marker which already had been proposed to be connected to cisplatin resistance in cell lines (15) but not in human malignancies. The caldesmon gene was expressed significantly higher in responding than nonresponding patients. Caldesmon is a potential actinomyosin regulatory protein found in smooth muscle and nonmuscle cells. Of the two isoforms, the high molecular weight caldesmon is predominantly expressed in smooth muscle, whereas the low molecular weight form analyzed in our study is widely distributed in nonmuscle tissues (29). Nonmuscle caldesmon is a regulatory factor in the microfilament network and is thus involved in the assembly and stabilization of microfilaments. Thus, our results confirm that genes involved in cytoskeleton may also play a role in chemotherapy resistance.

Another mechanism of chemotherapy resistance involves the extrusion of anticancer agents from the tumor cells by cell membrane transporters. ATP-binding cassette transporters are a family of transporter proteins that contribute to drug resistance via ATP-dependent drug efflux pumps. At least 10 members of the ATP-binding cassette transporter family (MRPs) have been implicated to be involved in resistance to cancer therapeutics over the past years (13, 30). We investigated MRP1 and found a significant correlation between response behavior and pretherapeutic MRP1 levels. Responding patients had higher median MRP1 levels than nonresponding patients, and only 1 of the 16 responding patients had low MRP1 expression relative to 14 of 22 nonresponders. Patients with high MRP1 levels also showed prolonged survival. These data are unexpected, because they may contradict the proposal that high multidrug resistance is caused by an increased cellular efflux of drugs from tumor cells.

High expression levels of MRPs can be detected in chemotherapy-resistant tumor cells of hematologic and solid malignancies. Yet, transcription of MRPs is influenced by intrinsic and extrinsic factors (e.g., hypoxia, carcinogens, or the chemotherapeutics agents themselves), and tumors with primarily low baseline expression levels of MRPs may develop up-regulation having been exposed to chemotherapy (31, 32). Findings obtained from treated tumors represent molecular changes that are occurring after or during therapy and therefore cannot serve as basis for conclusions on pretherapeutic conditions that we investigated in our study.

HER-2/neu overexpression may also be associated with resistance to several anticancer drugs, such as taxanes, cisplatin, and 5-FU. However, other drug resistance factors of cancer cells such as MRP1 may rather be responsible for resistance to chemotherapeutics than HER-2/neu overexpression itself (11). Because in Barrett carcinoma, HER-2/neu gene amplification can be observed in about one third of the cases (33), we analyzed HER-2/neu gene expression. Five patients of our study showed an overexpression of HER-2/neu (5.0-fold higher expression level compared with the median HER-2/neu/GAPDH). However, distribution of responders was comparable with patients exhibiting normal HER-2/neu expression levels. Thus, we could not confirm an association between HER-2/neu gene expression and response to neoadjuvant chemotherapy in Barrett adenocarcinoma.

To examine response to neoadjuvant chemotherapy, pretherapeutic tissue, usually diagnostic biopsy material, has to be analyzed. Biopsies are generally restricted to the superficial, endoluminal parts of a tumor; thus, they may not accurately reflect the situation in a highly heterogeneous tumor. A number of studies have shown i.t. genetic heterogeneity in several human cancers (34, 35) including Barrett carcinoma (33, 36), however, not yet at the gene expression level. To address the question, whether gene expression analysis of biopsies can be representative for the whole tumor tissue, we analyzed nine not preoperatively treated tumors with respect to i.t. heterogeneity. The investigated genes were stable across geographic regions of the tumors. The fact that expression levels measured in whole tumor tissue was different form those measured in biopsy material may be due to the influence of formalin fixation (e.g., fixation delay or duration of formalin infiltration in resection specimen in contrast to immediate fixation of biopsy specimen; ref. 37). However, for all genes analyzed patients with higher gene expression levels in the biopsy compared with the other patients had also higher median gene expression levels in the whole tumor and vice versa. From these findings, we conclude that expression profiles obtained from biopsy material may yield a representative genetic expression profile of the total tumor tissue, at least in Barrett adenocarcinoma for the genes analyzed in this study.

In conclusion, we found an association between the response of patients with Barrett adenocarcinoma to neoadjuvant chemotherapy and the expression levels of MTHFR, caldesmon, and MRP1, in part with a sensitivity of >90% to identify responding patients. Additionally, the strength of this study is that, to our knowledge, the largest homogenous collective of patients with Barrett adenocarcinoma thus far treated with the same dose of chemotherapy was investigated and a standardized determination of tumor regression was used. Although chemotherapy resistance is highly complex and may be determined not only by pretherapeutic conditions but also be influenced by transcriptional genetic changes during therapy, our findings provide encouragement to go on developing diagnostic tools that may predict good or poor response preoperatively by analyzing routine biopsies from tumor tissue.


    Footnotes
 
Grant support: Deutsche Krebshilfe grant 70-2789-Si3.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: Neither our article nor a similar study (neither in whole nor in part) has been submitted to any other primary scientific journal.

Presented in part at the 88th Meeting of the German Society of Pathology, June 4, Rostock, Germany.

Received 1/ 7/05; revised 6/22/05; accepted 7/28/05.


    References
 Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

  1. Zacherl J, Sendler A, Stein HJ, et al. Current status of neoadjuvant therapy for adenocarcinoma of the distal esophagus. World J Surg 2003;27:1067–74.[Medline]
  2. Burak WE, Jr. Is neoadjuvant therapy the answer to adenocarcinoma of the esophagus? Am J Surg 2003;186:296–300.[CrossRef][Medline]
  3. Lenz HJ. Pharmacogenomics in colorectal cancer. Semin Oncol 2003;30:47–53.
  4. Salonga D, Danenberg KD, Johnson M, et al. Colorectal tumors responding to 5-fluorouracil have low gene expression levels of dihydropyrimidine dehydrogenase, thymidylate synthase, and thymidine phosphorylase. Clin Cancer Res 2000;6:1322–7.[Abstract/Free Full Text]
  5. Kornmann M, Schwabe W, Sander S, et al. Thymidylate synthase and dihydropyrimidine dehydrogenase mRNA expression levels: predictors for survival in colorectal cancer patients receiving adjuvant 5-fluorouracil. Clin Cancer Res 2003;9:4116–24.[Abstract/Free Full Text]
  6. Cohen V, Panet-Raymond V, Sabbaghian N, et al. Methylenetetrahydrofolate reductase polymorphism in advanced colorectal cancer: a novel genomic predictor of clinical response to fluoropyrimidine-based chemotherapy. Clin Cancer Res 2003;9:1611–5.[Abstract/Free Full Text]
  7. Kawakami K, Omura K, Kanehira E, et al. Methylenetetrahydrofolate reductase polymorphism is associated with folate pool in gastrointestinal cancer tissue. Anticancer Res 2001;21:285–9.[Medline]
  8. Larminat F, Bohr VA. Role of the human ERCC-1 gene in gene-specific repair of cisplatin-induced DNA damage. Nucleic Acids Res 1994;22:3005–10.[Abstract/Free Full Text]
  9. Shirota Y, Stoehlmacher J, Brabender J, et al. ERCC1 and thymidylate synthase mRNA levels predict survival for colorectal cancer patients receiving combination oxaliplatin and fluorouracil chemotherapy. J Clin Oncol 2001;19:4298–304.[Abstract/Free Full Text]
  10. Metzger R, Leichman CG, Danenberg KD, et al. ERCC1 mRNA levels complement thymidylate synthase mRNA levels in predicting response and survival for gastric cancer patients receiving combination cisplatin and fluorouracil chemotherapy. J Clin Oncol 1998;16:309–16.[Abstract/Free Full Text]
  11. Kim R, Tanabe K, Uchida Y, et al. The role of HER-2 oncoprotein in drug-sensitivity in breast cancer [review]. Oncol Rep 2002;9:3–9.[Medline]
  12. Kruh GD, Zeng H, Rea PA, et al. MRP subfamily transporters and resistance to anticancer agents. J Bioenerg Biomembr 2001;33:493–501.[CrossRef][Medline]
  13. Kruh GD, Belinsky MG. The MRP family of drug efflux pumps. Oncogene 2003;22:7537–52.[CrossRef][Medline]
  14. Staunton JE, Slonim DK, Coller HA, et al. Chemosensitivity prediction by transcriptional profiling. Proc Natl Acad Sci U S A 2001;98:10787–92.[Abstract/Free Full Text]
  15. Scherf U, Ross DT, Waltham M, et al. A gene expression database for the molecular pharmacology of cancer. Nat Genet 2000;24:236–44.[CrossRef][Medline]
  16. Warnecke-Eberz U, Metzger R, Miyazono F, et al. High specificity of quantitative excision repair cross-complementing 1 messenger RNA expression for prediction of minor histopathological response to neoadjuvant radiochemotherapy in esophageal cancer. Clin Cancer Res 2004;10:3794–9.[Abstract/Free Full Text]
  17. Becker K, Mueller JD, Schulmacher C, et al. Histomorphology and grading of regression in gastric carcinoma treated with neoadjuvant chemotherapy. Cancer 2003;98:1521–30.[CrossRef][Medline]
  18. Specht K, Richter T, Muller U, et al. Quantitative gene expression analysis in microdissected archival formalin-fixed and paraffin-embedded tumor tissue. Am J Pathol 2001;158:419–29.[Abstract/Free Full Text]
  19. Napieralski R, Ott K, Kremer M, et al. Combined GADD45A and thymidine phosphorylase expression levels predict response and survival of neoadjuvant-treated gastric cancer patients. Clin Cancer Res 2005;11:3025–31.[Abstract/Free Full Text]
  20. Vandesompele J, De Preter K, Pattyn F, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002;3:RESEARCH0034.[Medline]
  21. Youden WJ. Index for rating diagnostic tests. Cancer 1950;3:32–5.[CrossRef][Medline]
  22. Schisterman EF, Perkins NJ, Liu A, et al. Optimal cut-point and its corresponding Youden index to discriminate individuals using pooled blood samples. Epidemiology 2005;16:73–81.[CrossRef][Medline]
  23. Etienne MC, Ilc K, Formento JL, et al. Thymidylate synthase and methylenetetrahydrofolate reductase gene polymorphisms: relationships with 5-fluorouracil sensitivity. Br J Cancer 2004;90:526–34.[CrossRef][Medline]
  24. Toffoli G, Veronesi A, Boiocchi M, et al. MTHFR gene polymorphism and severe toxicity during adjuvant treatment of early breast cancer with cyclophosphamide, methotrexate, and fluorouracil (CMF). Ann Oncol 2000;11:373–4.[Free Full Text]
  25. Aschele C, Lonardi S, Monfardini S. Thymidylate synthase expression as a predictor of clinical response to fluoropyrimidine-based chemotherapy in advanced colorectal cancer. Cancer Treat Rev 2002;28:27–47.[CrossRef][Medline]
  26. Metzger R, Danenberg K, Leichman CG, et al. High basal level gene expression of thymidine phosphorylase (platelet-derived endothelial cell growth factor) in colorectal tumors is associated with nonresponse to 5-fluorouracil. Clin Cancer Res 1998;4:2371–6.[Abstract/Free Full Text]
  27. Adlard JW, Richman SD, Seymour MT, et al. Prediction of the response of colorectal cancer to systemic therapy. Lancet Oncol 2002;3:75–82.[CrossRef][Medline]
  28. Popat S, Matakidou A, Houlston RS. Thymidylate synthase expression and prognosis in colorectal cancer: a systematic review and meta-analysis. J Clin Oncol 2004;22:529–36.[Abstract/Free Full Text]
  29. Hayashi K, Yano H, Hashida T, et al. Genomic structure of the human caldesmon gene. Proc Natl Acad Sci U S A 1992;89:12122–6.[Abstract/Free Full Text]
  30. Scotto KW. Transcriptional regulation of ABC drug transporters. Oncogene 2003;22:7496–511.[CrossRef][Medline]
  31. Nishiyama M, Yamamoto W, Park JS, et al. Low-dose cisplatin and 5-fluorouracil in combination can repress increased gene expression of cellular resistance determinants to themselves. Clin Cancer Res 1999;5:2620–8.[Abstract/Free Full Text]
  32. Leonard GD, Fojo T, Bates SE. The role of ABC transporters in clinical practice. Oncologist 2003;8:411–24.[Abstract/Free Full Text]
  33. Walch A, Specht K, Bink K, et al. HER-2/neu gene amplification, elevated mRNA expression, and protein overexpression in the metaplasia-dysplasia-adenocarcinoma sequence of Barrett's esophagus. Lab Invest 2001;81:791–801.[Medline]
  34. Zitzelsberger H, Kulka U, Lehmann L, et al. Genetic heterogeneity in a prostatic carcinoma and associated prostatic intraepithelial neoplasia as demonstrated by combined use of laser-microdissection, degenerate oligonucleotide primed PCR and comparative genomic hybridization. Virchows Arch 1998;433:297–304.[CrossRef][Medline]
  35. Aubele M, Mattis A, Zitzelsberger H, et al. Intratumoral heterogeneity in breast carcinoma revealed by laser-microdissection and comparative genomic hybridization. Cancer Genet Cytogenet 1999;110:94–102.[CrossRef][Medline]
  36. Owonikoko T, Rees M, Gabbert HE, et al. Intratumoral genetic heterogeneity in Barrett adenocarcinoma. Am J Clin Pathol 2002;117:558–66.[Abstract/Free Full Text]
  37. Godfrey TE, Kim SH, Chavira M, et al. Quantitative mRNA expression analysis from formalin-fixed, paraffin-embedded tissues using 5' nuclease quantitative reverse transcription-polymerase chain reaction. J Mol Diagn 2000;2:84–91.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
GutHome page
K R Fareed, P Kaye, I N Soomro, M Ilyas, S Martin, S L Parsons, and S Madhusudan
Biomarkers of response to therapy in oesophago-gastric cancer
Gut, January 1, 2009; 58(1): 127 - 143.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
R. Langer, K. Ott, K. Specht, K. Becker, F. Lordick, M. Burian, K. Herrmann, A. Schrattenholz, M. A. Cahill, M. Schwaiger, et al.
Protein Expression Profiling in Esophageal Adenocarcinoma Patients Indicates Association of Heat-Shock Protein 27 Expression and Chemotherapy Response
Clin. Cancer Res., December 15, 2008; 14(24): 8279 - 8287.
[Abstract] [Full Text] [PDF]


Home page
Eur. J. Cardiothorac. Surg.Home page
D. Breen and F. Barlesi
The place of excision repair cross complementation 1 (ERCC1) in surgically treated non-small cell lung cancer
Eur. J. Cardiothorac. Surg., May 1, 2008; 33(5): 805 - 811.
[Abstract] [Full Text] [PDF]


Home page
Ann. Surg. Oncol.Home page
C. Duong, D. M. Greenawalt, A. Kowalczyk, M. L. Ciavarella, G. Raskutti, W. K. Murray, W. A. Phillips, and R. J. S. Thomas
Pretreatment Gene Expression Profiles Can Be Used to Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer.
Ann. Surg. Oncol., December 1, 2007; 14(12): 3602 - 3609.
[Abstract] [Full Text] [PDF]


Home page
Clin. Cancer Res.Home page
A. Handra-Luca, J. Hernandez, G. Mountzios, E. Taranchon, J. Lacau-St-Guily, J.-C. Soria, and P. Fouret
Excision Repair Cross Complementation Group 1 Immunohistochemical Expression Predicts Objective Response and Cancer-Specific Survival in Patients Treated by Cisplatin-Based Induction Chemotherapy for Locally Advanced Head and Neck Squamous Cell Carcinoma
Clin. Cancer Res., July 1, 2007; 13(13): 3855 - 3859.
[Abstract] [Full Text] [PDF]


Home page
JCOHome page
K. Ott, W. A. Weber, F. Lordick, K. Becker, R. Busch, K. Herrmann, H. Wieder, U. Fink, M. Schwaiger, and J.-R. Siewert
Metabolic Imaging Predicts Response, Survival, and Recurrence in Adenocarcinomas of the Esophagogastric Junction
J. Clin. Oncol., October 10, 2006; 24(29): 4692 - 4698.
[Abstract] [Full Text] [PDF]


Home page
NEJMHome page
K. A. Olaussen, A. Dunant, P. Fouret, E. Brambilla, F. Andre, V. Haddad, E. Taranchon, M. Filipits, R. Pirker, H. H. Popper, et al.
DNA repair by ERCC1 in non-small-cell lung cancer and cisplatin-based adjuvant chemotherapy.
N. Engl. J. Med., September 7, 2006; 355(10): 983 - 991.
[Abstract] [Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Langer, R.
Right arrow Articles by Höfler, H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Langer, R.
Right arrow Articles by Höfler, H.


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online