Cancer cell adaptation to chemotherapy
- Federica Di Nicolantonio1,
- Stuart J Mercer1,
- Louise A Knight1,
- Francis G Gabriel1,
- Pauline A Whitehouse1,
- Sanjay Sharma1,
- Augusta Fernando1,
- Sharon Glaysher1,
- Silvana Di Palma1,
- Penny Johnson1,
- Shaw S Somers2,
- Simon Toh2,
- Bernie Higgins3,
- Alan Lamont4,
- Tim Gulliford5,
- Jeremy Hurren2,
- Constantinos Yiangou2 and
- Ian A Cree1Email author
© Di Nicolantonio et al; licensee BioMed Central Ltd. 2005
Received: 23 November 2004
Accepted: 18 July 2005
Published: 18 July 2005
Tumor resistance to chemotherapy may be present at the beginning of treatment, develop during treatment, or become apparent on re-treatment of the patient. The mechanisms involved are usually inferred from experiments with cell lines, as studies in tumor-derived cells are difficult. Studies of human tumors show that cells adapt to chemotherapy, but it has been largely assumed that clonal selection leads to the resistance of recurrent tumors.
Cells derived from 47 tumors of breast, ovarian, esophageal, and colorectal origin and 16 paired esophageal biopsies were exposed to anticancer agents (cisplatin; 5-fluorouracil; epirubicin; doxorubicin; paclitaxel; irinotecan and topotecan) in short-term cell culture (6 days). Real-time quantitative PCR was used to measure up- or down-regulation of 16 different resistance/target genes, and when tissue was available, immunohistochemistry was used to assess the protein levels.
In 8/16 paired esophageal biopsies, there was an increase in the expression of multi-drug resistance gene 1 (MDR1) following epirubicin + cisplatin + 5-fluorouracil (ECF) chemotherapy and this was accompanied by increased expression of the MDR-1 encoded protein, P-gp. Following exposure to doxorubicin in vitro, 13/14 breast carcinomas and 9/12 ovarian carcinomas showed >2-fold down-regulation of topoisomerase IIα (TOPOIIα). Exposure to topotecan in vitro, resulted in >4-fold down-regulation of TOPOIIα in 6/7 colorectal tumors and 8/10 ovarian tumors.
This study suggests that up-regulation of resistance genes or down-regulation in target genes may occur rapidly in human solid tumors, within days of the start of treatment, and that similar changes are present in pre- and post-chemotherapy biopsy material. The molecular processes used by each tumor appear to be linked to the drug used, but there is also heterogeneity between individual tumors, even those with the same histological type, in the pattern and magnitude of response to the same drugs. Adaptation to chemotherapy may explain why prediction of resistance mechanisms is difficult on the basis of tumor type alone or individual markers, and suggests that more complex predictive methods are required to improve the response rates to chemotherapy.
Tumor resistance to chemotherapy is a well-known clinical phenomenon that is now yielding its secrets to investigation at the molecular level in biopsy material. Studies in cell lines do not always correlate well with results from tumor tissue , which may consist largely of non-neoplastic cells that support and modify the biology of neoplastic cells. Thus it is important to validate the mechanisms important in vitro with the situation in the patient. Nevertheless, cell line studies and immunohistochemical studies of tumors suggest that resistance is a selective process: only those cells that survive a drug-induced insult will re-grow.
We have previously shown development of such resistance to combination chemotherapy in tumor-derived cells from matched biopsies collected from breast cancer patients before and after administration of doxorubicin-containing chemotherapy . In this study we show similar results in patients with esophageal cancer from biopsies obtained prior to and several months after chemotherapy. Two cycles of the combination of epirubicin, cisplatin and 5-FU (ECF) are given to these patients prior to resection, allowing studies to be performed with paired samples before and after chemotherapy. We have used real-time quantitative RT-PCR (qRT-PCR) and immunohistochemistry (IHC) to assess targets known to be of importance to resistance to these agents.
The mechanisms involved in resistance to chemotherapy usually involve up-regulation of resistance mechanisms, or down-regulation of target genes. Examples of the former include drug efflux pump molecules such as multi-drug resistance gene 1/P-glycoprotein (MDR1/P-gp), while the latter include topoisomerases (TOPOs), targets of drugs such as etoposide and doxorubicin. Many papers attest to the importance of clonal selection in this process: it is for instance possible to expose cell lines to low concentrations of drugs and, over time, to produce highly resistant sub-clones . However, there is another potential mechanism that does not require clonal selection: cells may be able to adapt by regulation of expression of resistance or target molecules individually if they survive the initial exposure to the drug. This could be a more rapid process and would require changes in molecular expression, possibly due to epigenetic change, rather than genetic mechanisms such as mutation . As a result, resistance may therefore arise rapidly following treatment with chemotherapy.
Recent studies have shown that the expression of MDR1/P-gp is up-regulated within hours of anti-cancer drug treatment in vivo in patient samples [5–8], although this effect was not observed in all patients. We therefore wished to examine how quickly and in how many cases these resistance molecules were up-regulated in tumor-derived cells from several tumor types. We have used selective short-term cell culture (6 days) to examine the changes in expression that occur following exposure to chemotherapy compared to medium-only control cells from the same samples. Our short-term culture system employs a serum-free medium and polypropylene 96 'U' well microplates. This inhibits the proliferation and survival of normal cells and allows selective survival of a neoplastic cell population . The short incubation period also limits the possibility of selection of clones or sub-populations in vitro. However, the presence of non-neoplastic cells for most of the incubation period allows the interaction between stromal cells and neoplastic cells, a factor that appears to be important to maintain the chemosensitivity profile .
Patients and tissue samples for in vitrostudies
Tumor derived cells were obtained from 17 breast cancer patients (16 primaries; 1 pre-treated with mitoxantrone and paclitaxel), 13 ovarian cancer patients (all pre-treated with a cisplatin-based regimen), 10 colorectal cancer patients (all primaries) and 7 esophageal cancer patients (3 untreated; 4 treated with ECF). Cells were grown for 6 days in serum-free medium with or without drugs, before RNA extraction and further PCR analysis.
Patients and tissue samples for in vivostudy
Thirty-four esophageal adenocarcinoma biopsies, thirty-two of which were paired samples were obtained from patients (17M:1F; median age 57, range 42–81) before and after administration of 2 cycles of ECF chemotherapy. After enzymatic digestion, tumor derived cells were centrifuged over Ficoll (Sigma Chemical Co, Poole, UK, Cat. No. 1077-1) to remove blood contaminating cells, washed in PBS, and stored in RNA later (Ambion, Huntingdon, UK) at -80°C until further molecular analysis was performed. Tissue sections from these samples were stained for GST-π, MRP1, P-gp and TS. All tumor samples were removed as part of patient treatment, with consent for tissue donation and local research ethics committee approval for use of the tissue surplus to diagnostic requirements for cellular and molecular assays. Chemosensitivity data were available for 9 patients with recurrent ovarian cancer, before treatment and on relapse, though in only one case was material available from both samples for quantitative RT-PCR.
Cisplatin, 5-fluorouracil (5-FU), epirubicin, doxorubicin, irinotecan, paclitaxel (Taxol®) and topotecan (Hycamptin®) were obtained from the pharmacy at Queen Alexandra Hospital (Portsmouth, UK). Cisplatin, 5-FU, irinotecan and paclitaxel were stored at room temperature, while all other drugs were stored at -20°C, as previously reported . Test drug concentrations (TDC) were 10.0 μM for cisplatin, 345 μM for 5-FU, 148 μM for irinotecan, 15.9 μM for paclitaxel, 2.5 μM for doxorubicin, 0.862 μM for epirubicin, and 1.64 μM for topotecan. Combinations were made up by adding two or three drugs concurrently at their 200% TDC at the beginning of the ATP-cell viability assay and diluted in a constant ratio: sequential studies were not performed.
Short-term cell culture
Briefly, tumor tissue or fluid was taken by a histopathologist or surgeon under sterile conditions, and transported to the laboratory in cell culture medium of Dulbecco's modified Eagle's medium (DMEM; Sigma Cat No. D5671) with antibiotics (100 U/ml penicillin and 100 μg/ml streptomycin, Sigma, Cat No. P0781) at 4°C. Cells were obtained from solid tumors by enzymatic dissociation, usually 0.75 mg/ml collagenase (Sigma Cat No. C-8051) overnight. Viable tumor-derived cells were purified by density centrifugation (Histopaque 1077-1, Sigma), washed, counted and resuspended to 100,000 cells/ml in case of effusions or 200,000 cells/ml for solid biopsies. In the meantime 96-well polypropylene microplates (Corning-Costar, High Wycombe, UK; Cat No. 3790) were prepared with each drug/combination at six doubling dilutions in triplicate from 200% TDC to 6.25% TDC, according to Andreotti et al. . Approximately 10,000–20,000 cells/well were added to the plates to a final volume of 200 μl/well. The plates were then incubated at 37°C in 5% CO2 for 6 days, after which the degree of cell inhibition was assessed by measurement of the remaining ATP in comparison with negative control (no drug, MO) and positive control (maximum inhibitor, MI) rows of 12 wells each. Prior to cell lysis with an ATP-extracting reagent, an aliquot of 150 μl of cell suspension were removed from each well, centrifuged, washed with phosphate buffered saline (PBS) and stored at -80°C in a GTIC-containing solution (lysis buffer RA1, Macherey-Nagel, Düren, Germany; Cat. No.740961) until further molecular analysis was carried out. The RNA was subsequently extracted from aliquots that had been exposed to a drug concentration capable of inhibiting cell growth by 40–60%. ATP was extracted from the remaining 50 μl cell suspension and measured by light output in a microplate luminometer (Berthold Diagnostic Systems GmbH, Pforzheim, Germany) following addition of luciferin-luciferase.
Cells obtained after enzymatic dissociation from endoscopic esophageal biopsies or short term cell culture were either resuspended in RNA later (Ambion, Huntingdon, UK; Cat No. 7020) or lysed with buffer RA1 and stored at -80°C until RNA extraction. Total RNA was extracted from at least 50,000 cells with a commercially available kit (NucleoSpin® RNA II mini, Macherey-Nagel; Cat No. 740955) according to the manufacturer's instructions. The protocol included a DNase digestion step to prevent carry-over of genomic DNA in further analysis.
List of primers for qRT-PCR. Sequence of primers (forward and reverse) used for qRT-PCR experiments. GenBank accession numbers for each gene are indicated in brackets. The primers were designed using an old version of the software Primer 3.0, available at the following website: http://www-genome.wi.mit.edu/cgi-bin/primer/primer3.cgi/
Sequence 5'-3' (forward and reverse primer)
GAA GGT GAA GGT CGG AGT C
GAA GAT GGT GAT GGG ATT TC
TCA GGC AGT ATA ATC CAA AGA TGG T
AGT CTG GCT TAT ATC CAA CAC TTC G
CTG CAC GAT CCC GAG ACT CT
GCT GTA TGC ACG GCT ACT GG
TGG GAA CAA GAG GGC ATC TG
CCA CCA CTG CAT CAA ATT CAT G
CAC GAA CCA CGG CAC TGA TT
TTT TCT TGC TGC CAG TCT GGA C
CAC AAC CAT TGC ATC TTG GC
GCT GCA AAG CCG TAA ATC CA
CCA AAG GCA GTA AAG CAG GAA
TCA CGA CTC CCC GTA TCG A
TGG TCA AGT GCT GGA TGA TAG A
GGT AGA AGT TGG AGT CTG TAG GA
GGG AAT TTG GCG ACG TAA TTC
GCG GAG GCT GAG GAA CAG
CGG AGA CCT CAC CCT GTA
CGC CTC ATA GTT GGT GTA GA
TGG TTC AGG TGG CTC TGG AT
CTG TAG ACA AAC GAT GAG CTA TCA CA
GGC ACA GCA TCA AAC CAA GT
GCA AGC ATG GCA AGG TCA A
CAA TGC TGT GAT GGC GAT G
GAT CCG ATT GTC TTT GCT CTT CA
TGC AGC CTC CAT AAC CAT GAG
GAT GCC TGC CAT TGG ACC TA
GAT CCC AAC TGC TCC TGC
ACT TGG CAC AGC CCA CAG
CAG CTG GCC ATC GAG ATC A
TCC AGT CTC TGA GCC TCA TGC
CCT TGG ATA AGC TGG AGT CT
CCT ACT CTG ACC CAC GAT AC
CCA GAG ATC GGG AGA CAT GG
TAC GTG AGC AGG GCG TAG CT
TOPO I (J03250)
CTC CAC AAC GAT TCC CAG AT
TTA TGT TCA CTG TTG CTA TGC TT
TOPO IIα (NM_001067)
GTA ATT TTG ATG TCC CTC CAC GA
TCA AGG TCT GAC ACG ACA CTT
TOPO IIβ (NM_001068)
GCA GCC GAA AGA CCT AAA TA
AAT CAT TAT TGT CAT CAT CAT CAT C
List of antibodies used for immunohistochemical studies.
Glutathione S-Transferase pi GST-π (polyclonal)
30 min RT
BioGenex (Distributor: Menarini Diagnostics, Wokingham, UK)
P-glycoprotein (MDR-1) (Clone JSB-1)
Pressure Cook 2 min pH 6.0
Novo Castra Newcastle-upon-Tyne, UK
Multidrug Resistant-Related Protein (MRP) (Clone MRPm6, specific for MRP-1)
Pressure Cook 2 min pH 7.0
30 min RT
Chemicon International Chandlers Ford, UK
Thymidylate Synthase TS (Clone TS 106)
Pressure Cook 2 min pH 6.0
30 min RT
Neo Markers (Distributor: Lab Vision, Newmarket, UK)
The luminometer readings obtained from the ATP-TCA were entered into an Excel 2000 spreadsheet (Microsoft) which calculated the percentage of cell inhibition for each drug concentration according to the previous published formula: 1 - [(Test - MI)/(MO - MI)]*100 . For each drug-response curve, the 50% inhibitory concentration (IC50) and the 90% inhibitory concentration (IC90) were also calculated as previously described .
Assessment of slides was done using the H-score. Staining intensity (none, 0 points; weak, 1 point; moderate, 2 points; strong, 3 points) and percentage of positive tumor cells were multiplied to achieve a score between 0 and 300. A H-score of 100 or more was regarded as positive and results less than 100 were regarded as negative. The correlation coefficients were calculated by the method of the least squares, and the correlation between the IC90 and IC50 values and immunohistochemistry indices was assessed using univariate linear regression (Statsdirect, Sale, UK).
Non-parametric statistical methods were used. The calculated and descriptive data were entered into an Access 2000 database (Microsoft) and analysed using a Wilcoxon two-tailed paired rank sum test for paired data or the Mann-Whitney U test for unpaired data, as appropriate (Statsdirect). IC50 and IC90 values for each compound were correlated to the relative mRNA levels of target genes using Spearman's rank correlation coefficient and multivariate analysis. On statistical advice, we chose not to use a Bonferroni's correction, but it should be noted that some technically statistically significant results could have arisen by chance.
Chemotherapy-induced changes in mRNA levels in biopsy material
Relative expression of mRNA levels in esophageal samples obtained from patients before and after chemotherapy (median values). The last 2 columns on the right represent values for the 12 paired biopsies. The p values have been calculated using non parametric statistics, and in detail the Mann Whitney U test for unpaired samples, and the Wilcoxon matched pairs test for paired samples.
All esophageal samples
Paired esophageal samples
Pre-chemo n = 13
Post-chemo n = 6
Pre-chemo n = 6
Post-chemo n = 6
We then determined the relative mRNA levels of enzymes that have previously been correlated with 5-FU sensitivity: dihydropyrimidine dehydrogenase (DPD), thymidine phosphorylase (TP) and thymidylate synthase (TS) . No significant difference was found for these 3 genes when we compared their expression pre- and post-chemotherapy in unpaired samples (Table 3). However, we found a modest increase of TS expression in 5/6 paired samples (Fig. 2b), 3 of which also showed a concomitant decrease in TP levels. One sample showed a paradoxical decrease in TS, indicating some heterogeneity. Although the sample size is small, the trend of increased TS levels in ECF exposed tumors is consistent with a number of previous reports that demonstrated an acute induction of TS expression in cell lines, animal models and human tumors following 5-FU treatment [18, 19].
It should be noted that these qRT-PCR results were all obtained from samples that included normal cells present in the tumor as well as neoplastic cells, and could be affected by changes in normal cells as well as malignant cells.
Chemotherapy-induced changes in protein levels in biopsy material
Median expression (range in brackets) of protein levels in paired esophageal samples (n = 16) obtained from patients before and after chemotherapy. Slides were assessed using the H-score. A H-score of 100 or more was regarded as positive and below 100 was regarded as negative.
Changes in short-term cell culture
Of the 47 solid tumor samples studied in short-term cultures, 7 were esophago-gastric, 17 were breast carcinomas, 13 were ovarian carcinomas and 10 were colorectal tumors. A total of 93 experiments were performed, as in most cases the same sample was treated with 2 or more drugs.
Doxorubicin effects in short-term cell culture
Relative expression of mRNA levels in tumor samples after ex vivo exposure to doxorubicin. The IC50 concentrations for the samples tested are shown for each drug (median and range). The p values have been calculated using non-parametric statistics, in detail the Wilcoxon matched pairs test. On statistical advice, we chose not to use a Bonferroni's correction, but it should be noted that some technically statistically significant results could have arisen by chance.
Doxorubicin IC50 = 0.828 μM (0.569–1.16)
Doxorubicin IC50 = 1.34 μM (0.310–17.7)
Topoisomerase I inhibitors effects in short-term cell culture
Relative expression of mRNA levels in tumor samples after ex vivo exposure to topotecan and irinotecan. The IC50 concentrations for the samples tested are shown for each drug (median and range). The p values have been calculated using non-parametric statistics, in detail the Wilcoxon matched pairs test. On statistical advice, we chose not to use a Bonferroni's correction, but it should be noted that some technically statistically significant results could have arisen by chance.
Topotecan IC50 = 0.754 μM (0.164–4.82)
Irinotecan IC50 = 55.4 μM (29.5–100)
No significant changes were observed in the expression of the drug efflux molecules, MDR-1, BCRP and MRP-1 (Table 6), though, as in the case of doxorubicin, considerable heterogeneity was noted. We observed an increase of BCRP levels after irinotecan or topotecan exposure in 2/7 colorectal samples and 3/9 ovarian samples.
Amongst the genes implicated in DNA repair (Table 6), the modest down-regulation of MLH1 by topotecan exposure was not found statistically significant, although it was noted in 7/10 ovarian samples. Up-regulation of ERCC1 expression was found in all 10 ovarian cancer samples exposed to topotecan (p < 0.002, Wilcoxon), and in all 7 colorectal specimens treated with irinotecan, although in this group the increase was modest (p = 0.016, Wilcoxon).
Finally, we looked at EGFR as a marker of tumor growth and progression. After topotecan exposure we found a decrease (more than 2-fold) in the expression of this growth factor in 9/10 ovarian samples (Table 6), with the median levels decreasing from 0.470 to 0.163 units (p < 0.0039, Wilcoxon).
5-FU effects in short-term cell culture
Relative expression of mRNA levels in tumor samples after ex vivo exposure to 5 FU. The IC50 concentrations for the samples tested are shown for each drug (median and range). The p values have been calculated using non-parametric statistics, in detail the Wilcoxon matched pairs test. On statistical advice, we chose not to use a Bonferroni's correction, but it should be noted that some technically statistically significant results could have arisen by chance.
Breast samples IC50 = 200 μM (86.5–363)
Colorectal samples IC50 = 112 μM (13.8–311)
Cisplatin effects in short-term cell culture
Relative expression of mRNA levels in tumor samples after ex vivo exposure to cisplatin. The IC50 concentrations for the samples tested are shown for each drug (median and range). The p values have been calculated using non-parametric statistics, in detail the Wilcoxon matched pairs test. On statistical advice, we chose not to use a Bonferroni's correction, but it should be noted that some technically statistically significant results could have arisen by chance.
Breast samples IC50 = 18.4 μM (8.9–30.9)
Ovarian samples IC50 = 17.8 μM (6.3–25.6)
There was no significant change in MGMT in tumor-derived breast or ovarian cells. However, it has previously been shown that MGMT mRNA levels begin to recover after 24 hours in the absence of drug . There was a paradoxical decrease in the copper export pump ATP7B following cisplatin exposure (Table 8), in tumor-derived breast cells (p = 0.0327, Wilcoxon matched pairs test), but not in ovarian cells. No significant changes were observed in the heavy-metal binding protein MTII, in either tumor type.
ECF effects in short-term cell culture
We were able to study tumor-derived cells from 7 esophageal cancer patients, 4 of which had already been given ECF in vivo. The results mirror those obtained from paired esophageal biopsies: we noticed increased expression of TS in the cells that had been exposed to ECF (Fig 3h). However, the expected up-regulation of MDR1 was only detected in 4/7 samples (data not shown), and may therefore be occurring in non-neoplastic cells that do not normally express MDR1, rather than in the neoplastic cells, which we found to express this molecule to the same degree pre- and post-treatment.
Correlation of in vitrocytotoxicity with molecular expression
Lastly, for 5-FU, doxorubicin and irinotecan, IC90 and IC50 data were obtained by measuring the ATP levels in a small aliquot of cell suspension at the end of the incubation period. This allowed a comparison to be made between drug sensitivity and the expression of putative resistance genes in the cells that had been exposed to chemotherapeutic agents. Using multivariate analysis, the IC90 of 5-FU was correlated with the median change of mRNA levels of both TS and DPD measured in 5-FU treated tumor-derived cells compared to control cells (expressed as 2-ΔΔCt) (R2 = 0.872704; p = 0.0006 for DPD; p < 0.0001 for TS). In addition, expression of ERCC1 mRNA correlated with the IC50 values determined for doxorubicin in 11 breast samples (R = 0.7204, p < 0.0124). No other correlations were noted between sensitivity to the drugs and gene expression levels.
Our results suggest that rapid adaptation to chemotherapy may result in a resistant phenotype. This is mediated by down- or up-regulation of genes that are usually correlated to the mechanism of action of the individual chemotherapeutic agent or relevant resistance mechanisms. Our data suggest that short-term cell culture of tumor-derived cells with drugs could provide a suitable model for studying resistance mechanisms. The mechanisms observed appeared to be more specific to the drug used than to the tumor type: constitutive resistance probably reflects pre-chemotherapy expression of resistance mechanisms (e.g. drug efflux molecule expression in esophageal carcinoma). Acquired resistance develops rapidly and is likely to reflect changes in gene regulation rather than mutation-dependent selection of clones. Clonal selection may be important in some rapidly growing tumors and cell lines grown in serum-containing media, but is unlikely to be the major factor in solid tumors which have relatively low doubling rates. While mutation-mediated resistance can be much more profound than that observed here, our data suggest that the functional effects may still be sufficient to render the patient's tumor resistant to treatment within one cycle of chemotherapy.
Changes in resistance and target molecules
A large proportion of the published studies on resistance to chemotherapy have investigated the development of resistance using cell lines generated in the lab after prolonged and step-wise exposure to anti-cancer drugs. These in vitro models are not necessarily representative of the in vivo situation, when patients are usually administered one cycle of chemotherapy every 3–4 weeks. There are few studies in clinical samples. Our approach allows us to expose the tumor cells to single drugs under carefully controlled conditions, even if this would be an inappropriate drug for that particular patient. We are then able to look concomitantly at cytotoxicity, and molecular markers of resistance in the same experiment.
Anthracyclines have a mechanism of action that includes TOPO IIα inhibition via DNA intercalation. Resistance to anthracyclines is thought to be mediated by a number of different mechanisms, which include mutation or alteration of its target enzyme, TOPO IIα, and up-regulation of drug efflux proteins, such as BCRP, MRP1, MVP and MDR-1 . Our data show that many of the cell line data are correct: in most solid tumors, it appears that anthracycline and topotecan exposure do lead to decreased topoisomerase II and I expression respectively, while inducing the expression of drug efflux pump molecules. The reason for the alteration in topoisomerase II expression following topotecan exposure is not clear, but topotecan does affect cell proliferation, and any reduction in proliferation would indirectly affect the expression of topoisomerase II alpha induced during S phase. However, our results also suggest that the heterogeneity of chemosensitivity between tumors is reflected by heterogeneity of molecular determinants of resistance/sensitivity.
The increased TS levels in ECF and 5-FU exposed cells is consistent with a number of previous reports. Gene amplification of TS with consequent increases in TS mRNA and protein has been observed in cell lines that are resistant to 5-FU and fluorodeoxyuridine (FUDR) [26, 27]. Treatment with 5-FU has been shown to acutely induce TS expression in cell lines, animal models and human tumors [19, 28–30]. In general there is strong evidence that the expression of DPD and TS in GI cancers is predictive of response to 5-FU. It should be noted that the concomitant measurement of both these markers markedly enhanced the ability to predict tumor response to 5-FU-based chemotherapy in a number of studies [31–34].
Gene profiling and drug response
There are few studies comparing gene expression before and after chemotherapy. A few studies have reported microarray data in biopsy material taken before and after (or even during) chemotherapy. These studies are of great interest, though normal cell effects cannot be excluded from the results. Buchholz et al.  employed cDNA microarray to measure gene expression changes during chemotherapy in 5 patients with breast cancer. Clarke et al.  studied gene expression changes in 18 rectal cancer patients undergoing therapy with Mitomycin C or 5-FU. This study reported a number of genes implicated in protein synthesis and RNA metabolism to be significantly decreased during drug treatment. These studies are not directly comparable: tumors of different types respond better to different drugs, and differences in their adaptation to these drugs are therefore expected on the basis of their innate sensitivity or resistance.
The potential for positive selection: molecular chess
It is common to show a cross-over effect with clinical trials of treatments with differing mechanisms of action, in which patients treated with one type of chemotherapy show sensitivity to the alternative regimen following failure of the one to which they were allocated. The recognition that selection of a molecular phenotype by exposure to one anti-cancer agent may leads to the expression of molecular targets for other drugs raises the possibility that it might be possible to enhance sensitivity to second-line or maintenance therapy by careful selection of patients for first-line therapy . This approach would provide patients with a "backstop" for their first-line chemotherapy. One can envisage a series of interlocking treatments using drugs with specific molecular targets, monitored by molecular assays, which would allow the oncologist to employ a form of molecular chess to defeat the tumor. This approach might overcome the inherent heterogeneity, which is likely to underlie the variable results obtained from sequential chemotherapy to date. Assessment of this process in tumors could provide predictive assays allowing the oncologist to tailor therapy to the patient and avoid the development of resistance within the tumor.
In summary, this study suggests that up-regulation of resistance genes or down-regulation in target genes may occur rapidly in human solid tumors, within days of the start of treatment, and that similar changes are present in pre- and post-chemotherapy biopsy material. The molecular processes used by each tumor appear to be linked to the drug used, but there is heterogeneity between individual tumors, even those with the same histological type, in the pattern and magnitude of response to the same drugs. Adaptation to chemotherapy may explain why prediction of resistance mechanisms is difficult on the basis of tumor type alone or individual markers, and suggests that more complex predictive methods are required to improve the response rates to chemotherapy.
List of abbreviations
Gene names were abbreviated as follows
glyceraldehyde-3 phosphate dehydrogenase
hypoxanthine phosphoribosyltransferase 1
human porphobilinogen deaminase
succinate dehydrogenase complex-subunit A
breast cancer resistance protein
- (ERCC1) gene:
excision repair cross-complementing 1
epidermal growth factor receptor
glutathione-S-transferase isoform p
multi-drug resistance gene 1
mutL homologue 1
multi-drug resistance related protein 1
multi-drug resistance related protein 2
- MT II:
major vault protein
- TOPO I:
- TOPO II:
topoisomerase IIa and ß
This project was funded by Portsmouth Hospitals NHS Trust, CanTech Ltd, the BBSRC (Ref 31/ABY14513), the Royal Navy (SJM), the European Commission (grant number BMH4-CT98-9522; FDN), and was supported by a donation from Schering Plough Ltd (LAK). We are grateful to the NHS predictive oncology programme and all the patients, oncologists and surgeons who submitted material for chemosensitivity testing to make this study possible. We thank Christine Seddon for assistance with data entry.
- Andreotti PE, Linder D, Hartmann DM, Cree IA, Pazzagli M, Bruckner HW: TCA-100 tumour chemosensitivity assay: differences in sensitivity between cultured tumour cell lines and clinical studies. J Biolumin Chemilumin. 1994, 9: 373-378.View ArticlePubMedGoogle Scholar
- Cree IA, Kurbacher CM, Untch M, Sutherland LA, Hunter EM, Subedi AM, James EA, Dewar JA, Preece PE, Andreotti PE: Correlation of the clinical response to chemotherapy in breast cancer with ex vivo chemosensitivity. Anti-Cancer Drugs. 1996, 7: 630-635.View ArticlePubMedGoogle Scholar
- Matsumoto Y, Takano H, Fojo T: Cellular adaptation to drug exposure: evolution of the drug-resistant phenotype. Cancer Res . 1997, 57: 5086-5092.PubMedGoogle Scholar
- Egger G, Liang G, Aparicio A, Jones PA: Epigenetics in human disease and prospects for epigenetic therapy. Nature. 2004, 429: 457-463.View ArticlePubMedGoogle Scholar
- Abolhoda A, Wilson AE, Ross H, Danenberg PV, Burt M, Scotto KW: Rapid activation of MDR1 gene expression in human metastatic sarcoma after in vivo exposure to doxorubicin. Clin Cancer Res. 1999, 5: 3352-3356.PubMedGoogle Scholar
- Hu XF, Slater A, Kantharidis P, Rischin D, Juneja S, Rossi R, Lee G, Parkin JD, Zalcberg JR: Altered multidrug resistance phenotype caused by anthracycline analogues and cytosine arabinoside in myeloid leukemia. Blood. 1999, 93: 4086-4095.PubMedGoogle Scholar
- Stein U, Jurchott K, Schlafke M, Hohenberger P: Expression of multidrug resistance genes MVP, MDR1, and MRP1 determined sequentially before, during, and after hyperthermic isolated limb perfusion of soft tissue sarcoma and melanoma patients. J Clin Oncol. 2002, 20: 3282-3292.View ArticlePubMedGoogle Scholar
- Tada Y, Wada M, Migita T, Nagayama J, Hinoshita E, Mochida Y, Maehara Y, Tsuneyoshi M, Kuwano M, Naito S: Increased expression of multidrug resistance-associated proteins in bladder cancer during clinical course and drug resistance to doxorubicin. Int J Cancer. 2002, 98: 630-635.View ArticlePubMedGoogle Scholar
- Andreotti PE, Cree IA, Kurbacher CM, Hartmann DM, Linder D, Harel G, Gleiberman I, Caruso PA, Ricks SH, Untch M: Chemosensitivity testing of human tumors using a microplate adenosine triphosphate luminescence assay: clinical correlation for cisplatin resistance of ovarian carcinoma. Cancer Research. 1995, 55: 5276-5282.PubMedGoogle Scholar
- Wilmanns C, Fan D, O'Brian CA, Bucana CD, Fidler IJ: Orthotopic and ectopic organ environments differentially influence the sensitivity of murine colon carcinoma cells to doxorubicin and 5-fluorouracil. Int J Cancer. 1992, 52: 98-104.View ArticlePubMedGoogle Scholar
- Hunter EM, Sutherland LA, Cree IA, Subedi AM, Hartmann D, Linder D, Andreotti PE: The influence of storage on cytotoxic drug activity in an ATP-based chemosensitivity assay. Anticancer Drugs. 1994, 5: 171-176.View ArticlePubMedGoogle Scholar
- Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology. 2002, 3: research0034.0031-research0034.0011.View ArticleGoogle Scholar
- Applied Biosystems: ABI PRISM 7700 Sequence Detection System user Bulletin #2. Relative Quantitation of Gene Expression (P/N 4303859B). 1997, 10/2001: 11-15.Google Scholar
- Cree IA: Luminescence-Based cell viability testing. Bioluminescence Methods and Protocols. Edited by: LaRossa RA. 1998, Totowa, NJ: Humana Press Inc, 169-177.View ArticleGoogle Scholar
- Kurbacher CM, Cree IA, Brenne U, Bruckner HW, Kurbacher JA, Mallmann P, Andreotti PE, Krebs D: Heterogeneity of in vitro chemosensitivity in perioperative breast cancer cells to mitoxantrone versus doxorubicin evaluated by a microplate ATP bioluminescence assay. Breast Cancer Res Treat. 1996, 41 (2): 161-70.View ArticlePubMedGoogle Scholar
- Gottesman MM, Fojo T, Bates SE: Multidrug resistance in cancer: role of ATP-dependent transporters. Nat Rev Cancer. 2002, 2: 48-58.View ArticlePubMedGoogle Scholar
- Borst P, Evers R, Kool M, Wijnholds J: A family of drug transporters: the multidrug resistance-associated proteins. J Natl Cancer Inst. 2000, 92: 1295-1302.View ArticlePubMedGoogle Scholar
- Longley DB, Harkin DP, Johnston PG: 5-fluorouracil: mechanisms of action and clinical strategies. Nat Rev Cancer. 2003, 3: 330-338.View ArticlePubMedGoogle Scholar
- Chu E, Koeller DM, Johnston PG, Zinn S, Allegra CJ: Regulation of thymidylate synthase in human colon cancer cells treated with 5-fluorouracil and interferon-gamma. Mol Pharmacol. 1993, 43: 527-533.PubMedGoogle Scholar
- Wang JC: DNA topoisomerases. Annu Rev Biochem. 1996, 65: 635-692.View ArticlePubMedGoogle Scholar
- Foglesong PD, Reckord C, Swink S: Doxorubicin inhibits human DNA topoisomerase I. Cancer Chemother Pharmacol. 1992, 30: 123-125.View ArticlePubMedGoogle Scholar
- Dabholkar M, Vionnet J, Bostick-Bruton F, Yu JJ, Reed E: Messenger RNA levels of XPAC and ERCC1 in ovarian cancer tissue correlate with response to platinum-based chemotherapy. J Clin Invest. 1994, 94: 703-708.View ArticlePubMedPubMed CentralGoogle Scholar
- Samimi G, Fink D, Varki NM, Husain A, Hoskins WJ, Alberts DS, Howell SB: Analysis of MLH1 and MSH2 expression in ovarian cancer before and after platinum drug-based chemotherapy. Clinical Cancer Research: an Official Journal of the American Association for Cancer Research. 2000, 6: 1415-1421.Google Scholar
- D'Atri S, Graziani G, Lacal PM, Nistico V, Gilberti S, Faraoni I, Watson AJ, Bonmassar E, Margison GP: Attenuation of O(6)-methylguanine-DNA methyltransferase activity and mRNA levels by cisplatin and temozolomide in jurkat cells. J Pharmacol Exp Ther. 2000, 294: 664-671.PubMedGoogle Scholar
- Beck WT, Morgan SE, Mo YY, Bhat UG: Tumor cell resistance to DNA topoisomerase II inhibitors: new developments. Drug Resist Updat . 1999, 2: 382-389.View ArticlePubMedGoogle Scholar
- Johnston PG, Drake JC, Trepel J, Allegra CJ: Immunological quantitation of thymidylate synthase using the monoclonal antibody TS 106 in 5-fluorouracil-sensitive and -resistant human cancer cell lines. Cancer Res. 1992, 52: 4306-4312.PubMedGoogle Scholar
- Copur S, Aiba K, Drake JC, Allegra CJ, Chu E: Thymidylate synthase gene amplification in human colon cancer cell lines resistant to 5-fluorouracil. Biochem Pharmacol. 1995, 49: 1419-1426.View ArticlePubMedGoogle Scholar
- Welsh SJ, Titley J, Brunton L, Valenti M, Monaghan P, Jackman AL, Aherne GW: Comparison of thymidylate synthase (TS) protein up-regulation after exposure to TS inhibitors in normal and tumor cell lines and tissues. Clin Cancer Res. 2000, 6: 2538-2546.PubMedGoogle Scholar
- Swain SM, Lippman ME, Egan EF, Drake JC, Steinberg SM, Allegra CJ: Fluorouracil and high-dose leucovorin in previously treated patients with metastatic breast cancer. J Clin Oncol. 1989, 7: 890-899.PubMedGoogle Scholar
- Peters GJ, van der Wilt CL, van Triest B, Codacci-Pisanelli G, Johnston PG, van Groeningen CJ, Pinedo HM: Thymidylate synthase and drug resistance. Eur J Cancer. 1995, 31A: 1299-1305.View ArticlePubMedGoogle Scholar
- Salonga D, Danenberg KD, Johnson M, Metzger R, Groshen S, Tsao-Wei DD, Lenz HJ, Leichman CG, Leichman L, Diasio RB, Danenberg PV: Colorectal tumors responding to 5-fluorouracil have low gene expression levels of dihydropyrimidine dehydrogenase, thymidylate synthase, and thymidine phosphorylase. Clin Cancer Res. 2000, 6: 1322-1327.PubMedGoogle Scholar
- Ishikawa Y, Kubota T, Otani Y, Watanabe M, Teramoto T, Kumai K, Takechi T, Okabe H, Fukushima M, Kitajima M: Dihydropyrimidine dehydrogenase and messenger RNA levels in gastric cancer: possible predictor for sensitivity to 5-fluorouracil. Jpn J Cancer Res. 2000, 91: 105-112.View ArticlePubMedGoogle Scholar
- Ichikawa W, Uetake H, Shirota Y, Yamada H, Nishi N, Nihei Z, Sugihara K, Hirayama R: Combination of dihydropyrimidine dehydrogenase and thymidylate synthase gene expressions in primary tumors as predictive parameters for the efficacy of fluoropyrimidine-based chemotherapy for metastatic colorectal cancer. Clin Cancer Res. 2003, 9: 786-791.PubMedGoogle Scholar
- Kornmann M, Schwabe W, Sander S, Kron M, Strater J, Polat S, Kettner E, Weiser HF, Baumann W, Schramm H, Hausler P, Ott K, Behnke D, Staib L, Beger HG, Link KH: Thymidylate synthase and dihydropyrimidine dehydrogenase mRNA expression levels: predictors for survival in colorectal cancer patients receiving adjuvant 5-fluorouracil. Clin Cancer Res. 2003, 9: 4116-4124.PubMedGoogle Scholar
- Buchholz TA, Stivers DN, Stec J, Ayers M, Clark E, Bolt A, Sahin AA, Symmans WF, Hess KR, Kuerer HM, Valero V, Hortobagyi GN, Pusztai L: Global gene expression changes during neoadjuvant chemotherapy for human breast cancer. Cancer J. 2002, 8: 461-468.View ArticlePubMedGoogle Scholar
- Clarke PA, George ML, Easdale S, Cunningham D, Swift RI, Hill ME, Tait DM, Workman P: Molecular pharmacology of cancer therapy in human colorectal cancer by gene expression profiling. Cancer Res. 2003, 63: 6855-6863.PubMedGoogle Scholar
- Kurata T, Tamura K, Kaneda H, Nogami T, Uejima H, Asai Go G, Nakagawa K, Fukuoka M: Effect of re-treatment with gefitinib ('Iressa', ZD1839) after acquisition of resistance. Ann Oncol. 2004, 15: 173-174.View ArticlePubMedGoogle Scholar
- Moniotte S, Vaerman JL, Kockx MM, Larrouy D, Langin D, Noirhomme P, Balligand JL: Real-time RT-PCR for the detection of beta-adrenoceptor messenger RNAs in small human endomyocardial biopsies. J Mol Cell Cardiol. 2001, 33: 2121-2133.View ArticlePubMedGoogle Scholar
- van den Heuvel-Eibrink MM, Wiemer EA, Prins A, Meijerink JP, Vossebeld PJ, van der Holt B, Pieters R, Sonneveld P: Increased expression of the breast cancer resistance protein (BCRP) in relapsed or refractory acute myeloid leukemia (AML). Leukemia. 2002, 16: 833-839.View ArticlePubMedGoogle Scholar
- Bieche I, Onody P, Laurendeau I, Olivi M, Vidaud D, Lidereau R, Vidaud M: Real-Time Reverse Transcription-PCR Assay for Future Management of ERBB2-based Clinical Applications. Clin Chem. 1999, 45: 1148-1156.PubMedGoogle Scholar
- Faneyte IF, Kristel PM, Maliepaard M, Scheffer GL, Scheper RJ, Schellens JH, van de Vijver MJ: Expression of the breast cancer resistance protein in breast cancer. Clin Cancer Res. 2002, 8: 1068-1074.PubMedGoogle Scholar
- Blanquicett C, Gillespie GY, Nabors LB, Miller CR, Bharara S, Buchsbaum DJ, Diasio RB, Johnson MR: Induction of thymidine phosphorylase in both irradiated and shielded, contralateral human U87MG glioma xenografts: implications for a dual modality treatment using capecitabine and irradiation. Mol Cancer Ther. 2002, 1: 1139-1145.PubMedGoogle Scholar
- Lord RV, Brabender J, Gandara D, Alberola V, Camps C, Domine M, Cardenal F, Sanchez JM, Gumerlock PH, Taron M, Sanchez JJ, Danenberg KD, Danenberg PV, Rosell R: Low ERCC1 expression correlates with prolonged survival after cisplatin plus gemcitabine chemotherapy in non-small cell lung cancer. Clin Cancer Res. 2002, 8: 2286-2291.PubMedGoogle Scholar
- Yague E, Armesilla AL, Harrison G, Elliott J, Sardini A, Higgins CF, Raguz S: P-glycoprotein (MDR1) expression in leukemic cells is regulated at two distinct steps, mRNA stabilization and translational initiation. J Biol Chem. 2003, 278: 10344-10352.View ArticlePubMedGoogle Scholar
- Taipalensuu J, Tornblom H, Lindberg G, Einarsson C, Sjoqvist F, Melhus H, Garberg P, Sjostrom B, Lundgren B, Artursson P: Correlation of gene expression of ten drug efflux proteins of the ATP-binding cassette transporter family in normal human jejunum and in human intestinal epithelial Caco-2 cell monolayers. J Pharmacol Exp Ther. 2001, 299: 164-170.PubMedGoogle Scholar
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