Home Life Sciences Polymorphisms correlated with the clinical outcome of locally advanced or metastatic colorectal cancer patients treated with ALIRI vs. FOLFIRI
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Polymorphisms correlated with the clinical outcome of locally advanced or metastatic colorectal cancer patients treated with ALIRI vs. FOLFIRI

  • Ana Barcelos , Elisa Giovannetti EMAIL logo , Robert de Jonge , Mina Maftouh , Pieter Griffioen , Axel R. Hanauske and Godefridus J. Peters
Published/Copyright: May 11, 2013
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Pteridines
From the journal Pteridines Volume 24 Issue 1

Abstract

Leucovorin-modulated 5-fluorouracil (5-FU) plus irinotecan (FOLFIRI) is the most common treatment of metastatic colorectal cancer (CRC). 5-FU inhibits thymidylate synthase (TS) and irinotecan topoisomerase I, leading to inhibition of DNA replication and repair. FOLFIRI efficacy suggested that other TS inhibitors might synergize with irinotecan, and Phase I/II studies for second-line treatment showed promising results of combinations with the multitargeted antifolate pemetrexed (PMX), which exerts its effects primarily via TS inhibition. However, a randomized Phase II trial of PMX + irinotecan (ALIRI) showed similar efficacy and safety, but significantly shorter progression-free survival (PFS) compared with FOLFIRI in locally advanced or metastatic CRC. In our previous aCGH study, we evaluated genome-wide copy number variations, whereas in the current study we evaluated relationships between functional polymorphisms and PFS. Candidate polymorphisms were studied by restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR) (TSER-2R/3R) or Taqman-PCR (MTHFR-1958G>A, MTR-2756A>G, MTHFR-1298A>C, SHMT1-1420C>T, ATIC-347C>G, AMPD-134C>T, MTRR-66A>G and SLC-19A180G>A) in 84 patients (40 FOLFIRI, 44 ALIRI). The Kaplan-Meier method was used to plot PFS, and the log-rank test to compare curves. At univariate analysis the homozygous variants of both MTR-2756A>G and SHMT1-1420C>T were associated with significantly shorter PFS. Conversely, a significantly longer PFS (7.3 months) was observed when ATIC-347C>G CC+CG genotypes were grouped vs. GG. At multivariate analysis the genotypes MTR-2756A>G AA+AG, SHMT1-1420C>T TT+CT and ATIC-347C>G CC+CG emerged as significant predictors for PFS. Because MTR, SHMT1 and ATIC are all involved in folate pathways, we further explored the effect of a combination of their risk genotypes on PFS, showing that patients carrying two risk genotypes had a significantly shorter PFS (3.9 months, p<0.001). The correlations of polymorphisms in genes with clinical outcome underscore the importance of a candidate gene-based approach. Ultimately, the validation of the role of these polymorphisms in prospective multicenter trials might optimize currently available treatments in selected CRC patients (e.g., FOLFIRI) or PMX-based treatments in other tumor types.

Keywords: 5-fluorouracil; clinical outcome; colorectal cancer; pemetrexed; polymorphisms

Introduction

Colorectal cancer (CRC) is the third most common cancer and the second cause of cancer-related death in the Western world [1]. The prognosis of CRC depends on tumor stage and treatment. For more than 50 years 5-fluorouracil (5-FU)-based therapy has remained the treatment of choice in both the adjuvant and palliative setting of CRC therapy. Currently, 5-FU or its prodrug capecitabine are given as combined therapeutic regimens including oxaliplatin, leucovorin, irinotecan, cetuximab and bevacizumab, which increased responses in first-line therapy up to 40% [2]. However, the overall prognosis is still poor, and no markers can reliably predict the subset of patients who will respond to cytotoxic drugs [3]. Therefore, the main challenges in CRC chemotherapy rely both on the development of new combinations and on the identification of markers to predict drug sensitivity.

The leucovorin-modulated 5-FU plus irinotecan (FOLFIRI) is the most common chemotherapeutic regimen used for first-line treatment of metastatic CRC. In this regimen, cytotoxicity is achieved through thymidylate synthase (TS) inhibition by 5-FU, which leads to disturbance on DNA replication and repair, and through topoisomerase I inhibition by irinotecan, which leads to double-strand breaks. The efficacy of this regimen as well as capecitabine plus irinotecan suggested that other TS inhibitors might synergize with irinotecan, and Phase I/II studies for second-line treatment of CRC showed promising results of combinations with the multitargeted antifolate pemetrexed, which exerts its effects primarily through TS inhibition [4, 5]. However, a randomized Phase II trial of pemetrexed + irinotecan (ALIRI) showed similar efficacy and safety, but significantly shorter progression-free survival (PFS) compared with FOLFIRI treatment [4, 6].

These results prompted further molecular studies on key determinants of activity for different TS inhibitors (Figure 1). In particular, pemetrexed is an antifolate agent that acts by disturbing critical folate-dependent metabolic processes. Folates are required for the synthesis of thymidine and purines and also to generate methionine, which plays an important role in protein synthesis, polyamine synthesis and transmethylation, essential for cell proliferation [7].

Figure 1 Scheme showing proteins involved in Pemetrexed and 5FU activity. All the enzymes encoded by the candidate genes/polymorphisms assessed in this study are marked in red. Pemetrexed is transported into the cells through SLC19A1 and is metabolized by FPGS to its active metabolite. Pemetrexed polyglutamate forms inhibit TS, DHFR, GARFT, ATIC and MTHFD1L, fundamental for the de novo biosynthesis of thymidine and purine nucleotides. See for further explanation the text.
Figure 1

Scheme showing proteins involved in Pemetrexed and 5FU activity. All the enzymes encoded by the candidate genes/polymorphisms assessed in this study are marked in red. Pemetrexed is transported into the cells through SLC19A1 and is metabolized by FPGS to its active metabolite. Pemetrexed polyglutamate forms inhibit TS, DHFR, GARFT, ATIC and MTHFD1L, fundamental for the de novo biosynthesis of thymidine and purine nucleotides. See for further explanation the text.

Several proteins can affect pemetrexed activity (Figure 1). This drug is transported into the cells mainly through the reduced folate carrier (SLC19A1) system and the proton coupled folate transporter (PCFT). It is extensively metabolized by folylpolyglutamate synthetase to more active metabolites. In vitro studies have shown that pemetrexed polyglutamation dramatically increases its affinity to TS, dihydrofolate reductase (DHFR), and glycinamide ribonucleotide formyltransferase (GARFT), and in a lesser extent to aminoimidazole carboxamide ribonucleotide formyltransferase (ATIC) and methylenetetrahydrofolate dehydrogenase (NADP+-dependent) 1-like (MTHFD1L), thus inhibiting their enzymatic activity [8–10]. All these folate-dependent enzymes are fundamental for de novo biosynthesis of thymidine and purine nucleotides. TS catalyzes the methylation of deoxyuridylate (dUMP) to deoxythymidylate (dTMP) using 5,10-methylenetetrahydrofolate (methylene-THF) as a cofactor. This function maintains the dTMP (thymidine-5′ monophosphate) pool critical for DNA replication and repair. DHFR converts dihydrofolate into tetrahydrofolate (THF), a methyl group shuttle required for de novo synthesis of purines, dTMP and certain amino acids. The protein encoded by GARFT is a trifunctional polypeptide, which has phosphoribosylglycinamide formyltransferase, phosphoribosylglycinamide synthetase and phosphoribosylaminoimidazole synthetase activity that are also required for de novo purine biosynthesis. The ATIC gene encodes a bifunctional protein that catalyzes the last two steps of the de novo purine biosynthetic pathway. The N-terminal domain has phosphoribosylaminoimidazolecarboxamide formyltransferase activity, and the C-terminal domain has IMP cyclohydrolase activity. MTHFD1L is an enzyme involved in THF synthesis in mitochondria. One-carbon substituted forms of THF are involved in de novo synthesis of purines and thymidylate, as well as in cellular methylation reactions through the regeneration of methionine from homocysteine [11].

The identification of genetic variables that predict resistance, sensitivity or toxicity to chemotherapy is of major interest in order to determine which patients would benefit most from standard therapy in terms of safety and efficacy. Moreover, although pemetrexed is not used for the treatment of CRC, the analysis from patients treated with ALIRI is an important step for the development of clinical pharmacogenetic models to understand genetic variations influencing the impact of this TS inhibitor that might apply to other tumor types.

Gene polymorphisms of TSER, MTHFR-677C>T, MTHFR-1298A>C, MTHFD-1958G>A, MTR-2756A>G, MTRR-66A>G, SHMT-1420C>T and ATIC-347C>G have been correlated with the clinical outcome in patients receiving different chemotherapeutic agents including antifolates and TS inhibitors [12–21]. Nevertheless, few data were published relating these polymorphisms to treatment outcome in patients with CRC treated with 5-FU or pemetrexed. Similarly, although so far no data have been published relating treatment outcome to SLC-19A180G>A and AMPD-134C>T polymorphisms, these two polymorphisms also play an important role in pemetrexed transport and purine nucleotide cycle and might influence clinical outcome.

Therefore, the main aim of this study was to identify a possible relation between these polymorphisms and PFS in patients with locally advanced or metastatic CRC treated with pemetrexed and/or 5-FU based therapy. The secondary aims were to identify a possible relation of these polymorphisms with treatment toxicity or clinical response.

Materials and methods

Patients

This multicenter pharmacogenetic study involved a number of patients enrolled from February 2004 to September 2005 in Australia, Germany, Greece, The Netherlands, Spain and Russia [6]. The clinical outcome of this study (JMAZ) has been published separately [6]. Patients ≥ 18 years of age with histologically or cytologically confirmed adenocarcinoma of the colon or rectum with locally advanced or metastatic disease were enrolled. Eligible patients had at least one unidimensional measurable lesion defined by response evaluation criteria in solid tumors (RECIST) [22], a life expectancy ≥12 weeks, an Eastern Cooperative Oncology Group performance status (ECOG PS) of 0–2, and adequate marrow reserve, hepatic and renal function. No previous chemotherapy for advanced disease was allowed. Prior adjuvant therapy (except irinotecan) was allowed if given ≥12 months before enrolment. All patients provided written informed consent. The study was performed according to the Declaration of Helsinki, and the protocol was reviewed and approved by the appropriate ethical review board.

Study design and treatment

This pharmacogenetic study assessed data from patients enrolled during the Randomized Phase II Trial of Pemetrexed plus Irinotecan (ALIRI) vs. Leucovorin-modulated 5-FU plus Irinotecan (FOLFIRI) in first-line treatment of locally advanced or metastatic colorectal cancer (clinicaltrial.gov identifier NCT00079872) [6]. Eligible patients were randomized in a 1:1 manner to receive pemetrexed 500 mg/m2 and irinotecan 350 mg/m2 on day 1 of each 21-day cycle (ALIRI arm) or 5-FU (400 mg/m2 bolus and 600 mg/m2 as a 22-h infusion) and leucovorin 200 mg/m2 on days 1, 2, 15, 16, 29 and 30 of a 42-day cycle and irinotecan 180 mg/m2 on days 1, 15 and 29 (FOLFIRI arm).

Baseline and treatment assessment

Pretreatment evaluation included a complete medical examination, ECOG PS, baseline tumor measurement via magnetic resonance imaging and clinical laboratory tests. Tumor measurements were repeated before every other cycle for patients receiving ALIRI and before every cycle for patients receiving FOLFIRI. Body surface area calculations, body weight, clinical laboratory tests and toxicity assessments according to the National Cancer Institute (NCI) Common Toxicity Criteria, version 2.0, were completed before each cycle.

Candidate polymorphisms

Candidate genes/polymorphisms were selected via a functional approach in order to evaluate determinants known to modulate drug metabolism and mechanism of action (Figure 1, Table 1). Therefore, we used the following criteria: (i) that the gene was part of a pathway for which there is a credible scientific basis to support its involvement in the study of drug activity; (ii) that the gene had an established, well-documented genetic polymorphism; (iii) that the frequency of the polymorphism was high enough that its effect on clinical outcome would be meaningful; and (iv) that the polymorphism had some degree of likelihood to alter the function of the gene in a biologically relevant manner. The SLC1-19A180G>A polymorphism might affect pemetrexed transport into malignant cells [23], whereas TSER genotypes might be associated with tumoral TS level; nevertheless, their value as a predictor of response to treatment with 5-FU is still controversial [20, 24, 25]. The ATIC-347C>G polymorphism might play an important role in sensitivity to the drug and in purine biosynthesis [26], whereas the MTHFR-677C>T and 1298A>C polymorphisms might affect folate distribution either to DNA synthesis or to homocysteine remethylation [27]. Furthermore, the MTHFD1-1958G>A polymorphism might affect MTHFD expression which is involved in folate and methionine metabolism [7], whereas the MTR-2756A>G and MTRR-66A>G polymorphisms might affect the expression of MTR and MTRR, respectively, which are critical in methionine synthesis [28]. Finally, the SHMT1-1420C>T polymorphism might affect SHMT expression, which plays a pivotal role in the reversible conversion of serine and THF to glycine and methylene-THF [28], whereas AMPD catalyzes the irreversible deamination of adenosine monophosphate to inosine monophosphate [29] and plays a role in the purine nucleotide cycle.

Table 1

Clinical outcome according to polymorphisms.

PolymorphismGenotypePatients n (%)PFS month (95% CI)p-Value
TSER2R19 (24.4)7.3 (6.4–8.2)0.184
3R32 (41.0)7.2 (4.0–10.4)
2R/3R27 (34.6)6.9 (6.2–7.7)
3R+2R/3R59 (75.6)7.2 (6.3–8.1)0.795
MTHFR-677 C>TCC40 (48.2)6.8 (5.2–8.3)0.183
TT9 (10.8)9.6 (6.6–12.6)
CT34 (41.0)7.7 (6.4–8.0)
CC+CT74 (89.1)6.9 (6.1–7.7)0.065
MTHFR-1298 A>CAA41 (49.4)7.7 (6.7–8.6)0.712
CC5 (6.0)4.8 (1.6–8.0)
AC37 (44.6)6.9 (6.4–8.5)
AA+AC78 (79.0)7.3 (6.6–8.0)0.970
MTHFD-1958 G>AAA16 (19.0)7.4 (6.2–8.5)0.915
GG27 (32.1)7.3 (6.1–8.5)
GA41 (48.8)6.8 (5.0–8.5)
GG+GA68 (80.9)7.2 (6.2–8.2)0.739
MTR-2756 A>GAA50 (59.5)7.2 (6.6–7.9)0.012
GG7 (8.3)4.8 (4.0–5.6)
AG27 (32.1)9.0 (6.0–12.0)
AA+AG77 (91.7)7.3 (6.6–8.0)0.034
MTRR-66 A>GAA16 (19.5)7.3 (7.1–7.5)0.409
GG22 (26.8)5.7 (4.8–6.6)
AG44 (53.7)8.8 (6.6–11.1)
AA+AG60 (73.2)7.6 (6.5–8.8)0.205
SHMT1-1420 C>TCC39 (47.0)5.6 (4.3–7.0)0.039
TT4 (4.8)7.8 (1.4–14.1)
CT40 (48.2)8.3 (7.1–9. 6)
TT+CT44 (95.2)8.3 (7.0–9.6)0.025
SLC19A1-80 G>AAA15 (18.3)8.0 (5.6–10.4)0.326
GG24 (29.3)6.9 (4.1–9.6)
GA43 (52.4)7.2 (6.2–8.3)
GG+GA67 (81.7)7.2 (6.5–7.8)0.136
ATIC-347 C>GCC37 (44.6)7.3 (6.5–8.1)0.057
GG5 (6.0)3.9 (2.6–5.2)
CG41 (49.4)7.2 (4. 9–9.6)
CC+CG78 (94.0)7.3 (6.6–8.0)0.020
AMPD-134 C>TCC62 (74.7)7.4 (6.4–8.3)0.415
TT1 (1.2)6.7 (5.4–8.8)
CT20 (24.1)7.1 (6.4–8.0)
CC+CT82 (98.8)7.2 (6.4–8.0)0.531

Genotyping for MTHFR-1958 G>A and MTR-2756 A>G, was successfully performed in all the available blood samples, while a total of 83 samples out of the 84 patients were evaluable for MTHFR-677 C>T, MTHFR-1298 A>C, SHMT1-1420 C>T, ATIC-347 C>G and AMPD-134 C>T, 82 out of the 84 patients for MTRR-66 A>G and SLC19A1-80 G>A and 78 out of 84 patients for TSER.

Genotyping

DNA was isolated from pretreated blood samples using the QIAamp DNA mini kit (Qiagen, Venlo, the Netherlands) according to the manufacturer’s instructions, and DNA yields and integrity were checked at 260–280 nm with the NanoDrop®-1000-Detector (NanoDrop Technologies, Wilmington, DE, USA). TSER and MTHFR-677C>T polymorphisms were examined by the Laboratory of Medical Oncology (VU University Medical Center, Amsterdam, The Netherlands), whereas MTHFR-1298A>C, MTHFD1-1958G>A, MTR-2756A>G, MTRR-66A>G, SHMT1-1420 C>T, SLC-19A180G>A, ATIC-347C>G and AMPD1–34C>T polymorphisms were assessed by the Laboratory of Clinical Chemistry (Erasmus MC, Rotterdam, The Netherlands).

The TSER genotype was assessed by polymerase chain reaction (PCR) amplification of the enhancer region (5′UTR) of the TS gene using a forward primer (5′-GTG GCT CCT GCG TTT CCC CC-3′) and a reverse primer (5′-GCT CCG AGC CGG CCA CAG GCA TGG CGC GG-3′’) as described previously [14, 24].

All other polymorphisms were evaluated with Taqman® probes based assays using the ABI PRISM-7000 Sequence Detection System instrument equipped with SDS version 1.3.0 software (Applied Biosystems, Leusden, the Netherlands). These PCR reactions were performed using 1.2 μL DNA sample and 5 μL reagents, in a total reaction volume of 6.2 μL. The reaction mixture underwent the following thermocycling conditions: 95°C for 10 min, 40 amplification cycles at 92°C for 15 s followed by a final annealing and extension step at 60°C for 1 min. Details of the genetic variants, primers and probes are in Supplemental Table 1.

Statistical analysis

The primary endpoint was to investigate the association between pharmacogenetic data and PFS, whereas the secondary endpoints included the association between polymorphisms and clinical response, clinical benefit and treatment toxicity. All analyses of the samples were done in a blinded manner relative to clinical outcome.

Genotype frequencies were checked for agreement with those expected under the Hardy-Weinberg equilibrium with the web-based SNP analyzer software (http://snp.istech21.com/snpanalyzer/2.0/).

PFS was defined as the time from study enrolment to disease progression or death from any cause, as appropriate. As this study was not designed to estimate overall survival (OS), no follow-up was performed on patients after relapse and second-line therapy. The Kaplan-Meier method was used to plot PFS, and the log-rank test to compare curves.

Objective response was evaluated according to RECIST criteria. Toxicity was assessed by the NCI Common Toxicity Criteria, version 2.0.

Demographic and clinical information were compared by treatment group, using Pearson’s χ2 two-sided test. This test was also used to compare clinical information (assessed as PFS, clinical response and toxicity) across genotype. The univariate analysis included different baseline demographic and clinical characteristics, such as gender, age, PS and clinical stage. Statistical analyses were performed grouping patients according to three different genotypes for each polymorphism. Further analyses were performed: (i) collapsing the homozygous and heterozygous genotypes (for all the population) when they had the same direction of effect (e.g., both had reduced/increased PFS compared with the reference group) and (ii) combining variant alleles associated with worse outcome (risk genotype). The significant prognostic variables in the univariate analysis were included in multivariate analyses, using Cox’s proportional hazards model.

Data were analyzed using SPSS-16 software (SPSS, Inc., Chicago, IL, USA). All analyses were two-sided and a p-value< 0.05 was considered statistically significant.

As this is an exploratory study, no correction for multiple testing was performed.

Results

Genotyping analyses were performed in 84 patients. Patient age ranged from 33 to 78 years. Five of these patients had no metastatic disease, whereas ECOG PS was rated 0 for 25, 1 for 52, and 2 for 7 patients, respectively. Forty patients underwent treatment with the FOLFIRI regimen, and 44 were treated the ALIRI regimen. No significant difference in any clinical feature was observed between patients treated with these regimens, and no significant difference was observed between each regimen and PFS (Figure 2A).

Figure 2 Kaplan-Meier curves showing progression free survival according to treatment group (A) ALIRI or FOLFIRI (A); or according to (B) number of risk genotypes present.
Figure 2

Kaplan-Meier curves showing progression free survival according to treatment group (A) ALIRI or FOLFIRI (A); or according to (B) number of risk genotypes present.

Polymorphisms and outcome

Genotyping was successfully performed in the vast majority of DNA samples. All polymorphisms except TSER (p=0.04) followed the Hardy-Weinberg equilibrium. As this analysis was performed in individuals from different geographic areas (e.g., 64% from Australia and Russia), population substructure is the most likely explanation for this deviation. However, the allelic frequencies of all the studied polymorphisms are consistent with those observed in previous reports and in the NCBI and NCI-SNP500 databases (Table 1).

At univariate analysis, polymorphisms of MTR-2756A>G, SHMT1-1420C>T and ATIC-347C>G were significantly associated with PFS (Table 2). In particular, a significantly shorter PFS was observed in patients harboring the MTR-2756A>G GG genotype, who had a median PFS of 4.8 months [95% confidence interval (CI), 1.6–8.0 months], in comparison with patients carrying the AA or AG genotype (median PFS, 7.3 months; 95% CI, 6.6–8.0 months). Similarly, shorter PFS (5.6 months; 95% CI, 4.3–7.0 months) was observed in patients harboring the SHMT1-1420C>T CC genotype, in comparison with patients carrying the SHMT1-1420C>T CT+TT genotype (median PFS of 8.3 months; 95% CI, 7.0–9.6 months). Finally, a significantly longer PFS (7.3 months; 95% CI, 6.6–8.0 months) was also observed when ATIC-347C>G CC+CG genotypes were grouped vs. ATIC-347 GG.

Table 2

Polymorphisms impact on PFS according to treatment.

PolymorphismGenotypeALIRIFOLFIRI
Patients n (%)PFS monthp-ValuePatients n (%)PFS monthp-Value
TSER2R84.9 (4.4–5.3)0.027118.1 (5.8–10.4)0.304
3R169.0 (4.7–13.3)167.2 (5.3–9.0)
2R/3R135.6 (3.0–8.3)147.2 (6.4–8.0)
3R+2R/3R297.6 (5.0–10.3)0.57307.2 (6.6–7.8)0.186
MTHFR-677 C>TCC195.1 (3.9–6.3)0.121217.4 (5.7–9.0)0.704
TT511.3 (4.4–18.2)48.8 (6.2–11.5)
CT166.5 (2.8–10.1)187.8 (6.6–8.9)
CC+CT355.8 (4.3–7.2)0.055397.4 (6.7–8.0)0.553
MTHFR-1298 A>CAA227.6 (5.6–9.7)0.007197.3 (6.6–8.0)0.515
CC33.3 (1.4–5.2)26.8 (–)
AC155.6 (3.5–7.8)227.8 (5.4–10.1)
AA+AC376.5 (4.6–8.3)0.003417.8 (7.0–8.5)0.249
MTHFD-1958 G>AAA64.1 (0.5–7.8)0.626107.8 (6.4–9.1)0.984
GG115.9 (2.0–9.9)167.3 (5.6–9.0)
GA235.8 (3.9–7.6)187.2 (6.0–8.5)
GG+GA345.9 (4.8–7.1)0.374347.3 (6.5–8.1)0.866
MTR-2756 A>GAA235.6 (3.3–8.0)0.067277.8 (7.0–8.4)0.080
GG24.4 (–)55.1 (1.2–9.0)
AG159.0 (5.4–12.6)126.9 (0.0–14.1)
AA+AG386.3 (4.4–8.1)0.205397.8 (6.6–9.0)0.058
MTRR-66 A>GAA35.9 (–)0.747137.3 (7.1–7.5)0.682
GG165.6 (4.5–6.8)66.9 (3.5–10.4)
AG217.1 (0.0–15.8)238.8 (7.1–10.6)
AA+AG247.1 (2.4–11.8)0.524367.8 (6.6–8.9)0.586
SHMT1-1420 C>TCC225.1 (3.5–6.7)0.632175.7 (1.6–9.8)0.022
TT––47.8 (1.4–14.1)
CT188.0 (5.0–11.0)228.8 (7.9–9.8)
TT+CT188.0 (5.0–11.0)0.632268.8 (7.8–9.9)0.009
SLC19A1-80 G>AAA64.2 (0.0–9.0)0.53399.2 (4.4–14.1)0.076
GG116.3 (1.0–11.5)136.9 (3.9–9.9)
GA225.9 (4.8–7.1)217.8 (7.0–8.5)
GG+GA335.9 (4.8–7.0)0.359347.4 (6.7–8.0)0.048
ATIC-347 C>GCC164.9 (2.0–7.7)0.069217.4 (6.6–8.1)0.549
GG53.9 (2.6–5.2)–
CG197.1 (5.0–9.2)227.8 (4.2–11.3)
CC+CG356.5 (4.7–8.2)0.024437.8 (6.7–8.8)a
AMPD-134 C>TCC305.8 (3.8–7.8)0.643327.8 (6.5–9.0)0.316
TT––16.7 (–)
CT105.9 (3.7–8.2)107.2 (3.5–10.9)
CC+CT405.9 (4.4–7.5)a427.8 (6.7–8.8)0.250

aNo comparison analysis performed because no patients in the FOLFIRI arm have the GG genotype

At multivariate analysis the genotypes MTR-2756A>G AA+AG, SHMT1-1420C>T TT+CT and ATIC-347C>G CC+CG emerged as significant predictors for PFS (Table 3).

Table 3

Multivariate analysis.

Covariates for PFSHR (95% CI)Wald p-Value
MTR-2756AG polymorphism: AA+AG vs. GG0.4 (0.2–1.0)0.047
SHMT1-1420CT polymorphism: TT+CT vs. CC0.6 (0.4–0.9)0.031
ATIC-347CG polymorphism: CC+CG vs. GG0.3 (0.1–0.7)0.011

HR, Hazard ratio; PFS, progression free survival.

Because MTR, SHMT1 and ATIC are all involved in folate pathways, we further explored the effect of a combination of their risk genotypes on PFS. The deleterious genotypes included MTR-2756A>G GG, SHMT1-1420C>T CC and ATIC-347C>G GG, all of which were related to shorter PFS (Figure 2B). These combinations were analyzed in 81 patients, and patients carrying two risk genotypes had a significantly shorter PFS (3.9 months; 95% CI, 2.4–5.4 months; p<0.001). Patients with two risk genotypes were MTR-2756A>G GG/SHMT-1420C>T CC or SHMT-1420C>T CC/ATIC-347C>G GG carriers. However, no significant difference on PFS was observed between these two groups.

At univariate analysis by treatment group (Table 2), polymorphisms of TSER, MTHFR-1298A>C and ATIC-347C>G were associated with significantly differential PFS in the ALIRI group. In particular, the less common variant genotypes of MTHFR-1298A>C and ATIC-347C>G polymorphisms were associated with decreased PFS. However, the more common polymorphic variant of SHMT1-1420C>T and the less common variant of SLC19A180G>A were associated with significantly shorter PFS in the FOLFIRI group.

The analysis of the correlation with clinical response (Table 4) revealed a significant association with the polymorphism MTHFD-1958G>A. Patients harboring the MTHFD-1958G>A AA genotype achieved a significantly higher rate of clinical response (56%), in comparison with patients carrying the MTHFD-1958 G>A GG and GA genotypes (26% and 19.5%, respectively; p=0.025), or when compared with the grouped MTHFD-1958G>A GG+GA genotype (22%; p=0.020).

Table 4

Patients with clinical response by polymorphisms.

PolymorphismGenotypePatients n (%)p-Value
TSER2R19 (24.4)0.813
3R32 (41.0)
2R/3R27 (34.6)
3R+2R/3R59 (75.6)0.506
MTHFR-677 C>TCC40 (48.2)0.807
TT9 (10.8)
CT34 (41.0)
CC+CT74 (89.2)0.758
MTHFR-1298 A>CAA41 (49.2)0.833
CC5 (6.0)
AC37 (44.6)
AA+AC78 (94.0)0.758
MTHFD-1958 G>AAA16 (19.0)0.025
GG27 (32.1)
GA41 (48.8)
GG+GA68 (81.0)0.020
MTR-2756 A>G AAAA50 (59.5)0.106
GG7 (32.1)
AG27 (32.1)
AA+AG77 (91.7)0.823
MTRR-66 A>GAA16 (19.5)0.194
GG22 (26.8)
AG44 (53.7)
AA+AG60 (73.2)0.052
SHMT1-1420 C>TCC39 (47.0)0.139
TT4 (4.8)
CT40 (48.2)
CC+CT79 (95.2)0.592
SLC19A1-80 G>AAA15 (18.3)0.909
GG24 (29.3)
GA43 (52.4)
GG+GA67 (81.7)0.707
ATIC-347 C>GCC37 (44.6)0.833
GG5 (6.0)
CG41 (49.4)
CC+CG78 (94.0)0.758
AMPD-134 C>TCC62 (74.7)0.384
TT1 (1.2)
CT20 (24.1)
CC+CT82 (98.2)0.288

The results of the correlation with toxicity are described in Table 5, showing that the polymorphism MTHFR-677C>T was significantly associated with blood and bone marrow grade 3–4 toxicity. In particular, the patients carrying the CC genotype experienced a significantly higher frequency of blood and bone marrow grade 3–4 toxicities (50%) compared with MTHFR-677C>T TT+CT grouped genotypes (25.6%; p=0.038).

Table 5

Blood and bone marrow grade 3-4 toxicity by polymorphisms.

PolymorphismGenotypen (% within genotype)p-Value
TSER2R7 (36.8)0.955
3R12 (37.5)
2R/3R11 (40.7)
3R+2R/3R23 (39.0)0.868
MTHFR-677 C>TCC20 (50.0)0.062
TT3 (33.3)
CT8 (23.5)
TT+CT11 (25.6)0.038
MTHFR-1298 A>CAA17 (41.5)0.707
CC2 (40.0)
AC12 (32.4)
AA+AC29 (37.2)1.000
MTHFD-1958 G>AAA3 (18.8)0.209
GG10 (37.0)
GA18 (43.9)
GG+GA28 (41.2)0.166
MTR-2756 A>GAA19 (38.0)0.420
GG1 (14.3)
AG11 (40.7)
AA+AG30 (39.0)0.375
MTRR-66 A>GAA8 (50.0)0.433
GG8 (36.4)
AG14 (31.8)
GG+AG22 (33.3)0.341
SHMT1-1420 C>TCC14 (35.9)0.279
TT3 (75.0)
CT14 (35.0)
CC+CT28 (35.0)0.277
SLC19A1-80 G>AAA5 (33.3)0.912
GG9 (37.5)
GA17 (39.5)
GG+GA26 (38.8)0.920
ATIC-347 C>GCC15 (40.5)0.666
GG1 (20.0)
CG15 (36.6)
CC+CG30 (38.5)0.726
AMPD-134 C>TCC24 (38.7)0.707
TT0 (0)
CT7 (35.0)
CC+CT31 (37.3)1.000

Discussion

This study evaluated the impact of functional polymorphisms on clinical outcome in locally advanced or metastatic CRC patients treated with ALIRI and/or FOLFIRI, and to our knowledge, is the first study to suggest the role of MTR-2756A>G, SHMT1-1420C>T and ATIC-347C>G polymorphisms as possible predictive factors for PFS. It is also the first study to show the correlation of the SHMT1-1420C>T and ATIC-347C>G polymorphisms with PFS in patients treated with FOLFIRI and ALIRI regimens, respectively.

Of note, in patients evaluated for polymorphism analysis no significant difference of median PFS was observed between the two regimens. Probably due to smaller sample size, this result was different from that obtained by Underhill et al. [6] where a significant longer PFS was observed on patients submitted to the FOLFIRI regimen. However, the lack of significant differences between PFS allowed us to perform all assessments on the pooled data, except for the analysis of polymorphisms on PFS by specific treatment group.

The most important results observed in this study include: (i) the shorter PFS for MTR-2756A>G GG, SHMT-1420C>T CC and ATIC-347C>G GG polymorphisms, at univariate analysis; (ii) the significant impact of MTR-2756A>G AA+AG, SHMT1-1420C>T TT+CT and ATIC-347C>G CC+CG polymorphisms on risk of progression, as observed at multivariate analysis; and (iii) the strong combined effect on PFS for MTR-2756A>G, SHMT1-1420C>T and ATIC-347C>G polymorphisms when combined risk genotypes were analyzed. These results are in accordance with the fact that all mentioned genes have a significant role in the folate pathways and consequent DNA synthesis.

The SHMT1-1420C>T polymorphic variant “T” produces a modified protein (L474F) that, although not affecting catalytic activity, impairs SHMT1 nuclear transport and, subsequently, TS activity. This modified protein accumulates in the cytoplasm where it inhibits cellular methylation reactions by sequestering 5-methyl-THF [30]. 5-Methyl-THF is required to convert homocysteine into methionine, which is needed for the synthesis of S-adenosylmethionine (SAM). SAM plays an important role in intracellular methylation reactions, including DNA methylation, which is one of the critical molecular mechanisms for DNA stability [31]. Furthermore, the lack of 5-methyl-THF due to sequestration by L474F leads to an increase of homocysteine concentrations which has been related to increased DNA damage [32]. All these mechanisms can explain why homozygous TT carriers might be more sensitive to cytotoxic activity of TS inhibitors and antifolates, resulting in significantly longer PFS.

To date, no association was found between ATIC polymorphisms and the effect of pemetrexed in cancer. However, a correlation with the activity of MTX was hypothesized by Weisman et al., suggesting that ATIC-347C>G GG encoded for a protein causing decreased de novo purine synthesis [33]. The results obtained in the present study are in accordance with previous studies in rheumatoid arthritis and psoriasis, showing that the “C” allele was associated with lower disease activity [16, 34, 35].

When the impact of polymorphisms on PFS was assessed by treatment group, TSER-3R, MTHFR-1298A>C AA and ATIC-347C>G CC+CG polymorphisms were significantly associated with longer PFS in patients treated with ALIRI. Several studies reported controversial data about the impact of TSER polymorphisms on clinical outcome in CRC patients treated with 5-FU/capecitabine-based chemotherapy [24, 36–44], whereas recent studies did not find a correlation of this polymorphism with outcome after pemetrexed-based therapies in mesothelioma and non-small cell lung cancer (NSCLC) [12, 36].

To our knowledge, there are no data on MTHFR-1298A>C polymorphisms on CRC patients treated with pemetrexed; nevertheless, the present results are in accordance with data on advanced gastric cancer patients treated with pemetrexed, showing a favorable prognostic role of the wild-type genotype [45]. These data are also similar to the results of the clinical/pharmacogenetic study by Smit and colleagues in NSCLC patients treated with pemetrexed. In this study, homozygous mutation for MTHFR-1298A>C was shown to have a trend towards a significant association with shorter PFS when compared with wild-type or heterozygous mutations [12]. The longer PFS observed in MTHFR-1298A>C AA carriers might be explained by the role of MTHFR on methylene-THF conversion to 5-methyl-THF. The MTHFR-1298A>C polymorphism is within the regulatory region of MTHFR and is known to reduce enzyme activity leading to a decreased pool of 5-methyl-THF, which leads in turn to an increase of homocysteine concentrations that have been related to increased DNA damage [32, 46].

In the FOLFIRI group, SHMT1-1420C>T and SLC-19A180G>A polymorphisms have shown a significant association with differential PFS. Once again, the significantly longer PFS observed in SHMT1-1420C>T TT carriers might be explained by the increase of homocysteine concentration which has been related to increased DNA damage [32]. Surprisingly, the SLC-19A1180G>A GG+GA polymorphism showed a significant association with shorter PFS in patients treated with FOLFIRI, but not in the ALIRI group. A previous study suggested that 5-FU transport may be mediated by SLC22A7 [47], while it is well established that antifolates such as methotrexate and pemetrexed are actively transported into cells by SLC-19A1 [23, 47]. Furthermore, SLC-19A1-IVS4(2117)C>T, IVS5(9148)C>A and exon6(2522)C>T polymorphisms were recently correlated to survival after pemetrexed-based therapy [48]. Nevertheless, there are no data correlating SLC-19A180G>A polymorphism to pemetrexed survival or PFS [48]. A possible explanation for the significant association found in our dataset is that leucovorin, used to enhance 5-FU activity, is also transported into the cell by SLC-19A1. The protein codified by the SLC-19A180G>A AA polymorphic gene might have higher transport activity leading to an increased concentration of intracellular leucovorin resulting in an increase in 5-FU activity. Furthermore, the effect of both MTHFR and SLC-19A1 polymorphisms on PFS might be mediated by the influence on total homocysteine levels [49], which have a crucial impact on DNA damage.

To our knowledge, this is also the first study reporting a significant correlation of MTHFD-1958G>A polymorphisms with clinical response. To date, the 1958G>A transition of MTHFD1 has been linked with genetic higher risk of having a child with neural tube defects (“AA” carriers) [50] or schizophrenia (“AA” or “AG” carriers) [51]. Its association with response to cytotoxic drugs may result from the effect on de novo biosynthesis of N5-methyltetrahydrofolate and subsequent reduction of SAM concentration, favoring DNA damage.

The identification of genetic variables that predict toxicity to chemotherapy is of major interest in patient selection avoiding the use of harmful therapies, and in the present study specific polymorphisms of MTHFR were identified as significant predictors for appearance of grade 3–4 blood and bone marrow toxicity. In particular, carriers of the MTHFR-677C>T TT+CT genotypes had a significantly lower risk to experience this severe toxicity compared with patients harboring the MTHFR-677C>T CC genotype. These results are in accordance with data from a clinical investigation on advanced gastric cancer patients treated with 5-fluoropyrimidine-based chemotherapy, which reported a significant association between the TT genotype with higher treatment-related general toxicity [52]. Conversely, other studies showed that the CC genotype was associated with grade 3–4 infections and diarrhea [52, 53]. However, a few studies analyzed the role of the MTHFR-677C>T polymorphism on toxic side effects after fluoropyrimidine-based therapy in CRC, drawing inconclusive results, while no data are available on the possible correlation with pemetrexed toxicity [54], and thus further studies are warranted.

In conclusion, although the present exploratory study was limited by sample size, and no correction for multiple testing was performed, the data on the correlation of polymorphisms in genes involved in the folate pathway or in antifolate chemotherapy with clinical outcome underscore the importance of a candidate gene and pathway-based approach in a genotyping investigation. These analyses should be integrated with genome-wide analysis, as described in our previous study [55].

Ultimately, the validation of the role of these polymorphisms in prospective multicenter trials might offer new tools for treatment optimization of both currently available regimens in selected CRC patients (e.g., FOLFIRI) and of pemetrexed-based treatment in other tumor types.

Corresponding author: Elisa Giovannetti, Department of Medical Oncology, VU University Medical Center, Cancer Center Amsterdam, CCA 1.52, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands, Phone: +31-20-4442267, Fax: +31-20-4443844

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Received: 2013-2-12
Accepted: 2013-4-8
Published Online: 2013-05-11
Published in Print: 2013-06-01

©2013 by Walter de Gruyter Berlin Boston

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  1. Masthead
  2. Masthead
  3. Editorial
  4. New developments in the publication of Pteridines
  5. Chemistry
  6. First synthesis of asperopterin A, an isoxanthopterin glycoside from Aspergillus oryzae
  7. Tetrahydrobiopterin
  8. Three classes of tetrahydrobiopterin-dependent enzymes
  9. Tetrahydrobiopterin attenuates ischemia-reperfusion injury following organ transplantation by targeting the nitric oxide synthase: investigations in an animal model
  10. Inflammatory diseases
  11. Folates and antifolates in rheumatoid arthritis
  12. Immune activation and inflammation increase the plasma phenylalanine-to-tyrosine ratio
  13. Tryptophan degradation and neopterin levels by aging
  14. Spot analyses of serum neopterin, tryptophan and kynurenine levels in a random group of blood donor population
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  17. Immune activation and inflammation in patients with cardiovascular disease are associated with elevated phenylalanine-to-tyrosine ratios
  18. Malignant diseases treatment
  19. Thymidylate synthase inhibitors for thoracic tumors
  20. Polymorphisms correlated with the clinical outcome of locally advanced or metastatic colorectal cancer patients treated with ALIRI vs. FOLFIRI
  21. Folate homeostasis of cancer cells affects sensitivity to not only antifolates but also other non-folate drugs: effect of MRP expression
  22. Enzymology folates
  23. Crystal structures of thymidylate synthase from nematodes, Trichinella spiralis and Caenorhabditis elegans, as a potential template for species-specific drug design
  24. Crystal structures of complexes of mouse thymidylate synthase crystallized with N4-OH-dCMP alone or in the presence of N5,10-methylenetetrahydrofolate
  25. Enzymology pterins
  26. First insights into structure-function relationships of alkylglycerol monooxygenase
  27. Fatty aldehyde dehydrogenase, the enzyme downstream of tetrahydrobiopterin-dependent alkylglycerol monooxygenase
  28. Expression of full-length human alkylglycerol monooxygenase and fragments in Escherichia coli
  29. Enzyme occurrence and function in model organisms
  30. The diverse biological functions of glutathione S-transferase omega in Drosophila
  31. Uncommon and parallel developmental patterns of thymidylate synthase expression and localization in Trichinella spiralis and Caenorhabditis elegans
https://doi.org/10.1515/pterid-2013-0021
Keywords for this article
5-fluorouracil; clinical outcome; colorectal cancer; pemetrexed; polymorphisms
Creative Commons
BY-NC-ND 3.0

Articles in the same Issue

  1. Masthead
  2. Masthead
  3. Editorial
  4. New developments in the publication of Pteridines
  5. Chemistry
  6. First synthesis of asperopterin A, an isoxanthopterin glycoside from Aspergillus oryzae
  7. Tetrahydrobiopterin
  8. Three classes of tetrahydrobiopterin-dependent enzymes
  9. Tetrahydrobiopterin attenuates ischemia-reperfusion injury following organ transplantation by targeting the nitric oxide synthase: investigations in an animal model
  10. Inflammatory diseases
  11. Folates and antifolates in rheumatoid arthritis
  12. Immune activation and inflammation increase the plasma phenylalanine-to-tyrosine ratio
  13. Tryptophan degradation and neopterin levels by aging
  14. Spot analyses of serum neopterin, tryptophan and kynurenine levels in a random group of blood donor population
  15. Endothelial dysfunction, cardiovascular diseases
  16. Tetrahydrobiopterin protects soluble guanylate cyclase against oxidative inactivation
  17. Immune activation and inflammation in patients with cardiovascular disease are associated with elevated phenylalanine-to-tyrosine ratios
  18. Malignant diseases treatment
  19. Thymidylate synthase inhibitors for thoracic tumors
  20. Polymorphisms correlated with the clinical outcome of locally advanced or metastatic colorectal cancer patients treated with ALIRI vs. FOLFIRI
  21. Folate homeostasis of cancer cells affects sensitivity to not only antifolates but also other non-folate drugs: effect of MRP expression
  22. Enzymology folates
  23. Crystal structures of thymidylate synthase from nematodes, Trichinella spiralis and Caenorhabditis elegans, as a potential template for species-specific drug design
  24. Crystal structures of complexes of mouse thymidylate synthase crystallized with N4-OH-dCMP alone or in the presence of N5,10-methylenetetrahydrofolate
  25. Enzymology pterins
  26. First insights into structure-function relationships of alkylglycerol monooxygenase
  27. Fatty aldehyde dehydrogenase, the enzyme downstream of tetrahydrobiopterin-dependent alkylglycerol monooxygenase
  28. Expression of full-length human alkylglycerol monooxygenase and fragments in Escherichia coli
  29. Enzyme occurrence and function in model organisms
  30. The diverse biological functions of glutathione S-transferase omega in Drosophila
  31. Uncommon and parallel developmental patterns of thymidylate synthase expression and localization in Trichinella spiralis and Caenorhabditis elegans
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