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Phenotypic differences among cancers with the same origin may be associated with chemotherapy response. CHFR silencing associated with DNA methylation has been suggested to be predictive of taxane sensitivity in diverse tumor types. However, the use of microsatellite instability (MSI:unstable--MSS:stable) as a predictive marker for therapeutic effect has had conflicting results. We examined these molecular alterations as predictors of chemotherapy sensitivity in colorectal cancer (CRC). Differential sensitivity to docetaxel and gemcitabine was compared to potential predictive biomarkers CHFR methylation and MSI status. Cell lines that were MSI-H/CHFR-methylated, MSS/CHFR-methylated, and MSS/CHFR-unmethylated were assessed for in vivo sensitivity of CRC cell line xenografts to docetaxel and/or gemcitabine. We observed increased sensitivity in vitro to gemcitabine in cell lines with MSI and docetaxel in cell lines with CHFR inactivation via DNA methylation. In vivo treatment of human xenografts confirmed differential sensitivity, with the MSI-H/CHFR-methylated line RKO having tumor growth inhibition to each agent, and at least additive tumor growth inhibition with combination therapy. The MSS-CHFR-unmethylated line, CACO2, was resistant to single and combination therapy, while COLO205, the MSS/CHFR-methylated line, showed tumor growth inhibition with docetaxel, but not gemcitabine, therapy. CHFR methylation in CRC cell lines predicted for sensitivity in vitro and in vivo to docetaxel, while MSI-H cell lines were more sensitive to gemcitabine. These data suggest that a subset of CRC patients would be selectively sensitive to a novel combination of gemcitabine and docetaxel, and are the basis for an ongoing clinical trial of this combination in a biomarker-selected patient population.
In 2010 there were approximately 53,221 colorectal cancer (CRC) related deaths in the United States. CRC is the second most diagnosed cancer and the second leading cause of cancer related deaths in the US.1 Currently there are at most three lines of standard chemotherapy available for metastatic CRC.2 Treatment of CRC with 5-fluorouracil (5FU) in combination with oxaliplatin or irinotecan and targeted agents such as bevacizumab and anti-epidermal growth factor-receptor (anti-EGFR) antibodies has increased the overall survival of metastatic patients from 10 to approaching 24 months.3 KRAS mutational status is the only clinically used biomarker in CRC, and predicts for resistance to EGFR inhibitors.4
Drug development has moved over the past decade to target subsets of patients to best assess clinical activity of new therapies. Previously, agents were tested in unselected patients without tailoring therapy to a patient’s tumor unique molecular characteristics. This potentially resulted in some drugs being discarded for inactivity due to not being tested in an optimal patient population. This would be particularly a problem for therapies that would be active in only a small subset of a particular malignancy. For example, sixty percent of CRC patients are wild-type for KRAS and would be predicted to be responsive to anti-EGFR therapy; accordingly anti-EGFR agents still demonstrated activity and received FDA approval even though they were initially tested in an unselected group of patients.5 Alternatively, ALK mutation is only present in approximately 5% of non-small cell lung cancer, and emphasis on selecting patients with ALK overexpression has been pivotal to the successful drug development strategy of ALK inhibitors.6
Colorectal cancer has distinct molecular phenotypes that may have impact on treatment response. CRC can be subdivided in to microsatellite unstable (MSI) or microsatellite stable (MSS) based upon mutations or DNA methylation of genes in mismatch repair (MMR) machinery.7 MSI is further divided in to two phenotypes, MSI-high (MSI-H) and MSI-low (MSI-L) based on distinct clinicopathological features. MSI-H colorectal tumors have defects in MMR genes, while MSI-L tumors are similar to MSS tumors and arise from chromosomal instability. One percent of CRC is linked to genomic mutations in MMR genes, and another 15% of CRC patients will have MSI from silencing of these genes due to hypermethylation.7, 8 Preclinical and clinical studies assessing the relative chemosensitivity of MSI versus MSS colon cancer have yielded mixed results. In vitro studies have demonstrated that MSI cell lines have less cytotoxicity with 5FU than MSS cell lines.9 In addition, differential sensitivity between MSI and MSS colorectal cancer cell lines has been reported for irinotecan, where MSI cell lines were shown to be more sensitive than MSS cell lines.10 However, clinical studies have reported mixed results, with some studies suggesting that patients with MSI receive less benefit from 5FU based therapy, while other studies suggesting that these patients do receive benefit from 5FU and oxaliplatin treatment, the present standard for care for adjuvant and metastatic CRC treatment.11 Previous studies also have reported that the MSI phenotype is associated with increased sensitivity to nucleoside analogues, including gemcitabine, due to the cells inability to tolerate DNA damage associated with this class of agents.12 Since the most common cause of MSI in sporadic CRC is via MLH1 promoter region methylation,13 this suggests that epigenetic changes may alter chemotherapy sensitivity.
An association between microsatellite instability and a hypermethylator phenotype has been well described,14, 15 with this subset of colon cancer having increased epigenetic silencing of tumor suppressor genes.16–19 As is true for mutational changes, the methylation status of genes can be used as predictive marker for drug sensitivity. One example is MGMT, where hypermethylation of this gene is associated with better response to alkylating agents and radiation treatment in glioblastoma.20, 21 Another potentially relevant alteration involves the CHFR (checkpoint with forkhead and RING finger domains) gene, which encodes a protein that is involved in G2/M checkpoint by delaying the entry in to metaphase,22 inhibiting polo-like kinase-1 by and thus delaying G2 to M transition.23 CHFR functions as a checkpoint to delay entry of cells in the mitotic phase of the cell cycle when alterations of the mitotic spindle occur. Thus, when cells are treated with microtubule inhibitors or other agents which alter the mitotic spindle, loss of CHFR leads to mitotic catastrophe and apoptosis.22 Methylation resulting in silencing of CHFR would then be a possible biomarker of sensitivity to taxanes, and previous preclinical and clinical studies in multiple histologies have suggested this correlation.24–27 We have previously reported CHFR methylation in a subset of colon cancer (~30%) as well as a high concordance between CHFR methylation and MSI.28 However, since taxanes have not been used for the treatment of patients with colorectal cancer, no association of CHFR function or silencing has been carried out in colorectal cancer.
We hypothesized that CHFR methylation or MSI may render subsets of colon cancer sensitive to docetaxel or gemcitabine, respectively. Furthermore, as we have previously reported a high concordance between these two potential biomarkers, we further theorized that there may be increased antitumor effect from combination therapy in colon cancer with both CHFR methylation and MSI.
Five MSI cell lines (RKO, SW48, LOVO, HCT116, DLD1) and five MSS cell lines (SW480, SW620, COLO205, CACO2 and HT29) were obtained from ATCC. Cells were maintained in McCoys 5A media with 10% fetal bovine serum and 1% penicillin- streptomycin at 37c in 5% CO2.
Total RNA was extracted from the cell lines using a Qiagen RNA extraction kit and the concentration was measured using a NanoDrop spectrophotometer. The extracted RNA, approximately 1µ g, was reverse transcribed to first strand cDNA by High Capacity cDNA Reverse Transcription kit (Applied Biosystems). Prior to cDNA preparation, DNA was degraded in the extracted RNA samples by DNAase I enzyme (Invitrogen).
First strand cDNA prepared from RNA was used for quantifying the CHFR mRNA in cell lines. The forward primer for the CHFR gene is GGCAACCAGAGGTTTGACAT and reverse primer is AGTCAGGACGGGATGTTACG. Primers were designed using Primer 3 software and ordered from IDT. The cDNA was amplified using IQ3 quantitative PCR detection system from Bio-Rad. PCR was done in triplicates for each cell line sample: 1µ l of cDNA product, 12.5µ l of SYBR green PCR master mix (Bio-Rad), 1µ l of forward and reverse primers combined, to a total volume of 25µ l with sterile water was used per PCR. PCR was carried at the following conditions, initial incubation at 95c for 5mins, denaturation at 95c for 30 seconds, annealing at 55c for 30 seconds, and finally extension step at 72c for 30 seconds. Denaturation, annealing and extension steps were repeated for 40 cycles followed by melting curve analysis. CHFR expression levels were normalized to their respective β-actin levels for each cell line and calculated relative to the RKO cell line using the ΔΔCt method. Primers for B-actin are: forward: TTCTACAATGAGCTGCGTGTG and reverse: GGGGTGTTGAAGGTCTCAAA.
cDNA was prepared from isolated RNA (Qiagen RNeasy kit) using the iScript cDNA synthesis kit (Bio-Rad). qPCR was performed using SsoAdvanced SYBR Green Supermix and the “My iQ iCycler” thermal cycler (Bio-Rad). PCR was performed in triplicate for each sample: 1µ l of cDNA product, 7.5µ l of SsoAdvanced SYBR Green master mix, 0.6µ l of combined forward and reverse primers (10 µM each), and up to a total volume of 15µ l with sterile water per PCR reaction. PCR was performed with an initial incubation step at 95c for 3 minutes followed by 40 cycles at 95c for 30 seconds and 57c for 30 seconds. These 40 cycles were followed by melting curve analysis. Forward primer for MDR1 gene is CTGGTTTGATGTGCACGATGTTGG and reverse primer is TGCCAAGACCTCTTCAGCTACTG. Each cell line sample was normalized to its own GAPDH control using the following primers (IDT) to amplify GAPDH in the samples: forward GAAGGTCGGAGTCAACGGATTT and reverse ATGGGTGGAATCATATTGGAAC. Calculations were made using the ΔΔCt method. Correlation between MDR1 expression and sensitivity to taxanes in cell lines were analyzed using a two-tailed paired t-test.
Expression of mRNA for cytidine deaminase (CDD), human concentrative nucleoside transporter (HCNT1), human equilibrative nucleoside transporter (HENT1) and deoxycytidine kinase (DCK) genes was tested using qualitative PCR in the 10 cell lines. The cDNA obtained from reverse transcription (as above) was amplified using HotStar TaqPlus DNA polymerase (Qiagen). PCR was performed in 20µ l of total volume containing 10µ l of PCR master mix, 1µ l of template DNA, 1µ l of forward and reverse primers each with sterile water to make up the volume. For CDD: initial activation temperature at 95c for 5 minutes, followed by 95c for 30 seconds, 65c for 45 seconds, and 72c for 80 seconds (35 cycles). Final extension step was carried for 10 minutes at 72c. The following primers were used for CDD gene; forward TGAAGCCTGAGTGTGTCCAG and reverse TAGCAATTGCCCTGAAATCC. For HCNT1: initial activation temperature at 94c for 3 minutes, followed by 94c for 20 seconds, 58c for 20 seconds, and 72c for 20 seconds (40 cycles). Final extension step was carried for 10minutes at 72c. The following primers were used for HCNT1 gene; forward TCTGTGGATTTGCCAATTTCAG and reverse CGGAGCACTATCTGGGAGAAGT. For HENT1 and DCK, initial activation temperature at 94c for 3 minutes, followed by 94c for 20 seconds, 60c for 20 seconds, and 72c for 20 seconds (40 cycles). Final extension step was carried for 10minutes at 72c. The following primers were used for HENT1 gene; forward GCTGGGTCTGACCGTTGTAT and reverse CTGTACAGGGTGCATGATGG. The following primers were used for DCK gene; forward AAACCTGAACGATGGTCTTTTACC and reverse CTTTGAGCTTGCCATTCAGAGA.
Genomic DNA was extracted using a QIAamp DNA Mini kit (Qiagen). The extracted DNA was quantified using a NanoDrop spectrophotometer and up to 1µ g of extracted genomic DNA was used for bisulfite treatment. Bisulfite conversion was done using EZ DNA Methylation kit (Zymo Research). CHFR gene promoter methylation status was determined by using primers previously published.28 The primers are methylated upper primer, 5’-GTTATTTTCGTGATTCGTAGGCGAC-3’, methylated downstream primer, 5’-CGAAACCGAAAATAACCCGCG-3’and unmethylated upper primer, 5’-GATTGTAGTTATTTTTGTGATTTGTAGGTGAT-3’, and unmethylated downstream primer, 5’-AACTAAAACAAAACCAAAAATAACCCACA-3’. PCR was performed in a 25µ l reaction volume containing 0.5µ l of Red Taq DNA polymerase (Sigma), 1µ l of template DNA and 35 cycles were used at 57°C annealing temperature.
Cytotoxicity of the drugs was determined by MTS assay (Promega). Drugs tested were gemcitabine, irinotecan, oxaliplatin, docetaxel, cyclophosphamide, pemetrexed, and 5-flourouracil. In brief, 4000 cells were plated in each well of 96 well plates 24 hours prior to the addition of drugs. After 24 hours, drug was added in increasing concentrations, except docetaxel; each drug concentration was done in triplicate and allowed to incubate for two days. After two days, 20µ l of the MTS reagent was added and read after 2hrs at 490nm absorbance. For docetaxel drug response, drug was added 24 hours after plating the cells. After 24 hours drug was replaced with fresh media and later incubated for two days. At the end MTS assay was done as described before for determining the cell viability. Raw absorbance values were background subtracted with wells containing only media. Cell viability was calculated by the following formula (absorbance of treated well/absorbance of mock*100) for each drug concentration. Cell viability was plotted against drug concentrations and the concentration at which 50% of the cells are viable is taken as IC50. Correlation between cytotoxicity of cell lines to CHFR methylation, microsatellite instability, and other tested markers was calculated using a two-tailed Fisher’s exact test unless otherwise stated.
We analyzed 145 samples of colorectal carcinoma from the Cancer Genome Atlas project (TCGA)29 that had both DNA methylation and mRNA expression data. TCGA used Illumina Infinium HumanMethylation27 BeadChip (Illumina) for DNA methylation profiling and Agilent G4502A microarray for mRNA expression profiling. Using these data, we calculated the Spearman's rank correlation coefficient for CHFR promoter DNA methylation and mRNA expression with the help of R software30 (Supplementary Figure 2).
SW480, COLO205, RKO, and HCT116 were maintained as above but without the addition of penicillin-streptomycin. Cell lines were treated on the same schedule with 500 nM 5-azacitidine (Sigma) twice weekly with splitting into drug-free media twice weekly. Untreated cell lines were similarly maintained and passaged. Docetaxel cytotoxicity assays were performed using MTS reagent. For these assays, 3000 (SW480) or 4000 (COLO205, RKO, HCT116) cells were plated per well into 96-well plates 24 hours prior to docetaxel (Hospira) addition. Each drug concentration was performed in replicates of five. On the day of plating, additional samples of these azacitidine-treated and untreated cells were pelleted, frozen on dry ice, and stored at −80 C for molecular studies. After 48 hours of incubation with docetaxel, the MTS in vitro cytotoxic assays were performed.
Nucleic acid from the frozen cell pellets corresponding to each MTS assay was isolated using the ZR-Duet DNA/RNA MiniPrep kit (Zymo Research). DNA bisulfite conversion was performed using the EZ DNA Methylation kit and MSP was performed as described above but with 1.0 µ l of Jumpstart RedTaq DNA polymerase and annealing at 59°C.28 cDNA was prepared from the isolated RNA using the iScript cDNA synthesis kit. For CHFR expression analysis, qPCR was performed using SsoAdvanced SYBR Green Supermix as described above with the CHFR primer sequences listed above. PCR was performed in triplicate for each sample.PCR was performed with an initial incubation step at 95c for 3 minutes followed by 40 cycles of denaturation at 95c for 30 seconds plus annealing at 57c for 30 seconds. These 40 cycles were then followed by melting curve analysis. Each cell line sample was normalized to its own GAPDH control using the primers described above and calculations were made using the ΔΔCt method. At least two separate docetaxel cytotoxicity assays- each with their corresponding CHFR qPCR expression analyses- were performed for each cell line with representative data shown in Figure 3.
Antitumor activity of the chemotherapeutic drugs as single agents and their combination was evaluated in xenograft models. Colorectal cancer cells with media and matrigel in the ratio of 1:1 were injected subcutaneously in to the two flanks of mice. All xenograft studies were conducted using homozygous female athymic nude mice which were purchased from Simonson Laboratories,CA. Five mice were used for each experimental condition. Docetaxel drug was administered intraperitoneally once a week, and gemcitabine was also given intraperitoneally twice weekly, both at 20 mg/kg. The mice were treated only until the time point when the mock animals were sacrificed due to tumor volume. Length (L) and width (W) of tumors were measured with a caliper until the tumors reached 2cm. Tumor volume (TV) was calculated with the following formula TV=1/2*(Length*width2). Matrigel for xenograft studies was obtained from BD Pharmingen. Chemotherapeutic drugs docetaxel and gemcitabine hydrochloride for xenograft studies was obtained from Sigma and the Johns Hopkins pharmacy, respectively. Docetaxel was dissolved In DMSO and gemcitabine hydrochloride was dissolved in saline for xenograft studies.
To test our hypothesis that CHFR methylation of CRC cell lines correlates with sensitivity to docetaxel treatment, CHFR promoter methylation was determined for ten colorectal cancer cell lines using MSP. Methylation status of these cell lines were correlated to the degree of cytotoxicity of the lines to docetaxel using MTS assay. RKO, SW48, HCT116, COLO205 and DLD1 cell lines were found to be completely methylated. HT29, LOVO, and CACO2 cell lines were partially methylated and SW620 and SW480 cell lines were fully unmethylated (Figure 1A). CHFR mRNA was then quantified using real time PCR. CHFR mRNA levels were absent in RKO, SW48, HCT116, DLD1, and COLO205, correlating with their methylation status (Figure 1B). Cell lines with unmethylated CHFR (SW480 and SW620), and those with partial methylation (HT29, LOVO and CACO2) all expressed CHFR, with two of the partially methylated cell lines having lower relative expression (HT29 and LOVO). These results suggest that loss of expression in these cell lines correlates with promoter region DNA methylation.
Next we examined sensitivity of these cell lines to docetaxel treatment. Cell lines with methylated and silenced CHFR (RKO, SW48, HCT116 and COLO205) were most sensitive to docetaxel (IC50 1.2–3nm; Figure 2A; Table 1). The two partially methylated cell lines with modest CHFR expression (LOVO and HT29) had intermediate sensitivity to docetaxel (IC50 7–10nM). In contrast, the three cell lines with high levels of CHFR expression (SW620, SW480, CACO2) were significantly more resistant to docetaxel (IC50 50–100nm). Aside from DLD1, CACO2 was the least sensitive to docetaxel treatment (IC50 100nm), and had the highest level of CHFR expression. As previously described in the literature,31 DLD1 displayed a resistant phenotype to all agents tested (docetaxel, gemcitabine, pemetrexed, cyclophosphamide, and 5-fluorouracil), though it was CHFR silent (not shown). CHFR expressing lines (unmethylated and partially methylated) were compared to CHFR silenced lines; the correlation between CHFR expression and resistance to docetaxel was statistically significant (p = 0.033). We also noted the significant overlap of CHFR methylation and MSI, as observed previously by ourselves and others.28 All MSI cell lines were CHFR methylated (one partially) while 4 of 5 MSS cell lines were unmethylated/partially methylated with CHFR expression noted.
MDR/ABC transporters have also been implicated as resistance factors to taxane therapy. Cell lines were profiled for their expression of MDR1 by qPCR (Supplemental Figure 1) but there was no correlation between the expression level of MDR1 and taxane resistance in these cell lines (p= 0.482). We also examined CHFR methylation and MDR expression in primary colorectal cancers using The Cancer Genome Atlas. We found similar prevalence of CHFR methylation and silenced CHFR expression in this data set (~30%, Supplemental Figure 2). There was minimal variation in MDR expression across colorectal cancers and there was no correlation between tumors with CHFR methylation.
To assess if CHFR re-expression results in decreased sensitivity to docetaxel, we treated multiple cell lines with a low-dose of the demethylating agent 5-azacitidine which allows for gene demethylation while minimizing the cytotoxic activity of 5-azacitidine (Figure 3). 5-azacitidine-treated versus untreated cells were then exposed to increasing concentrations of docetaxel. Cells lines with silenced CHFR expression that demonstrated increased CHFR re-expression with 5-azacitidine treatment showed decreased sensitivity to docetaxel. Cell lines with silenced CHFR that did not have significant CHFR re-expression showed no change in sensitivity to docetaxel. Specifically, SW480, with fully unmethylated CHFR and the greatest baseline expression of CHFR (approximately 50 fold greater than any silenced cell line) was the most resistant to docetaxel and showed no significant shift in docetaxel resistance with 5-azacitidine treatment, though CHFR expression did increase. COLO205 had low baseline expression of CHFR but did re-express CHFR following demethylation with 5-azacitidine treatment and demonstrated a corresponding decrease in sensitivity to docetaxel. RKO also had relatively low baseline expression of CHFR but demonstrated demethylation following 5-azacitidine treatment with a small amount of CHFR re-expression and a corresponding small decrease in docetaxel sensitivity. HCT116, which had extremely low baseline expression of CHFR, did not significantly re-express CHFR in 5-azacitidine, despite some demethylation, and demonstrated similar sensitivity regardless of 5-azacitidine treatment.
There are conflicting reports regarding patients with microsatellite instability and their response to accepted chemotherapy for colon cancer.32–34 No preclinical studies have assessed for differential sensitivity in colorectal cell lines to other chemotherapeutic drugs that are not commonly used to treat colorectal cancer. We tested multiple agents, as described above, for any association between microsatellite stability status and sensitivity of the cell lines to these drugs. 5FU was tested as a second pyrimidine analog that is known to have activity in colon cancer. Only two cell lines (RKO and HCT116) were sensitive to 5FU (IC50 4µm) in physiologically attainable ranges; the IC50 ranged from 40µm to 64µm for the remaining cell lines. All of the cell lines which we tested with cyclophosphamide were resistant in physiologically attainable ranges, except RKO (IC50 110µm). Pemetrexed had IC50 ranging from 50µm to 200µm with no clear association between microsatellite stability and sensitivity.
However, using the same panel of ten colorectal cancer cell lines (five MSI and five MSS), we found that MSI-H cell lines RKO, SW48, HCT116, and LOVO and were exquisitely sensitive to gemcitabine (IC50 80–350 nM; Figure 2B; Table 1). MSS cell lines COLO205, HT29, CAC02 SW620, and SW480were resistant to gemcitabine (IC501250nM – not reached>6500 nM). DLD1 again was resistant to all drugs tested (not shown). The correlation between MSI and sensitivity to gemcitabine was statistically significant (p = 0.048). The transporters HCNT1 and HENT1 have both been shown to be important for gemcitabine uptake into cells whereas cytidine deaminase (CDD) and deoxycytidine kinase (DCK) are critical for metabolism of gemcitabine.35 Thus, we evaluated for the presence of CDD, HCNT1, HENT1, and DCK expression, to investigate a possible mechanism for the differential sensitivity we observed. We did not find any significant correlation between mRNA levels in the cell lines and their gemcitabine sensitivity (p = 0.52 for CDD, p = 1.0 for HCNT1, HENT1, and DCK, data not shown). CDD was expressed in all the lines except RKO, with possibly lower levels in CACO2, LOVO, HT29, and SW48. HCNT1 was expressed in all the cell lines except SW480 and SW48. HENT1 and DCK were each expressed similarly in all the cell lines.
The sensitivity of cell lines to gemcitabine and/or docetaxel with in vitro testing suggests the ability to select therapy based upon molecular phenotypes. To test this approach in vivo, using docetaxel and gemcitabine individually and in combination, we treated human xenografts in mice based upon methylation of CHFR and microsatellite stability status. Three lines were chosen that represented each phenotype. CACO2, with the highest expression of the CHFR gene product and as a MSS cell line, was predicted to be resistant to both docetaxel and gemcitabine; the xenograft model confirmed this prediction (Figure 4A), with minimal activity of either drug or the combination. COLO205, which is completely methylated for CHFR and MSS, was predicted to be sensitive to docetaxel but resistant to gemcitabine. Indeed, the COLO205 xenograft was highly sensitive to docetaxel alone but resistant to gemcitabine and the addition of gemcitabine to docetaxel provided minimal benefit to docetaxel treatment alone (Figure 4B). RKO has a completely methylated and silent CHFR gene and is also MSI-H; this would be predicted to be sensitive to both docetaxel and gemcitabine. The RKO xenografts growth was the fastest of any cell line tested. The RKO xenografts still showed sensitivity to both agents and marked sensitivity to combination therapy with both drugs (Figure 4C). No MSI cell line tested had unmethylated CHFR, consistent with published literature indicating these biomarkers are often associated. Importantly, as all xenografts groups were only treated until the mock group was sacrificed, the animals received only 3 (COLO205) or 4 weekly doses (CACO2 and RKO) of docetaxel and gemcitabine; sustained tumor control was noted even after drug treatment had ceased in COLO205 and RKO xenografts.
Biomarker use to help predict treatment response for mCRC patients first began in 2008, when KRAS mutation was found to predict for lack of benefit to anti-EGFR agents. Presently, in mCRC, we now only have two lines of therapy for the 40% of patients that have KRAS mutation, and KRAS wild-type patients have three regimens. The main goal of this study was to find additional drug combinations that might have activity and which are traditionally not used in treatment of CRC; moreover, we aimed to identify the patients which might benefit most from these repurposed regimens.
Docetaxel has proven activity in many solid tumors including breast, prostate, gastric and lung cancers but early studies in unselected colon cancer patients were disappointing.36–39 The EORTC phase II study of docetaxel in metastatic colon cancer showed a 9% response rate, with one complete response noted, while Pazdur et al. reported 2 minor responses not reaching criteria for a partial response in another phase II study of the agent. Our data showed differential sensitivity based on CHFR expression, as regulated by methylation, in CRC cell lines. Considering the mechanism of CHFR as an important checkpoint protein causing cellular arrest, this suggests that treatment with an anti-microtubule agent would result in increased cytotoxicity if CHFR is not available. We and others have previously reported that there is a subset of colon cancer tumors, approximately 31%, that have CHFR methylation.28, 40 Using the highly purified TCGA sample data, we confirmed this prevalence in a larger cohort of primary tumors.
It has been previously shown in gastric cancer that CHFR methylated cell lines lead to absence of gene expression for that gene and are sensitive to microtubule inhibitors such as paclitaxel and docetaxel,27 though a retrospective study in advanced and recurrent gastric cancer did not find the same association.41 An association between taxane response and CHFR methylation was also reported in a preclinical study of endometrial cancer where endometrial cell lines with CHFR methylation were more sensitive to paclitaxel and this sensitivity was reversed with re-expression of CHFR by demethylation of the gene.42 Similarly, CHFR methylation predicted for sensitivity to taxanes in cervical adenocarcinoma cell lines also reversed with demethylation of the gene.24 Our study is the first report of the impact of CHFR methylation status on chemosensitivity in CRC. Recent work has suggested a potential prognostic value for the biomarker as well, with Tanaka et al. reporting that CHFR gene methylation is associated with disease recurrence in locally advanced colon cancer.43
Previous work has demonstrated that ectopic expression of CHFR in CHFR-null cells results in taxane resistance.22 These reports are consistent with our findings that re-expression of CHFR using 5-azacitidine in methylated cell lines does shift the dose-response curve of docetaxel towards resistance. This is particularly meaningful as treatment with a second cytotoxic agent would be expected to show more cytotoxicity, not less. Since CHFR is a densely methylated gene, we were not able to induce sufficient demethylation in all cell lines with our lower dose of 5-azacitidine as was seen in HCT116. In cell lines where CHFR was not able to be re-expressed (HCT116) or is already unmethylated and expressed highly at baseline (SW480), there was no change in sensitivity to docetaxel following 5-azatidine treatment. This experiment is limited due to the non-specific demethylating activity of 5-azacitidine but lends support to the hypothesis that CHFR itself may be the cause of increased resistance to taxanes.
Our data also support the use of gemcitabine in MSI-H CRC patients, approximately 15% of the CRC population. In the original phase I study of the agent, one of two responders was a colon cancer patient,44 but the phase II trial of gemcitabine in unselected CRC patients reported minimal activity.45 Our work demonstrates that MSI status predicts sensitivity to gemcitabine. The ability of microsatellite status to predict sensitivity to chemotherapy has been controversial in regards to 5FU-based treatments.9, 11, 46, 47 Data supporting that MSI status may predict for improved prognosis has been more consistent.48 In this paper, we found that MSI cell lines were significantly more sensitive to gemcitabine than MSS cell lines. DLD1 was resistant to all agents tested. Previous studies have also reported that DLD1 is resistant to agents to which other MSI cell lines are susceptible; as DLD1 has a loss of hMSH6,33 it has a less microsatellite unstable phenotype and may be the reason why we and others did not see the same response as other MSI cell lines. The mechanism of increased sensitivity of MSI cell lines to gemcitabine in our experiments is unknown; silencing of the mismatch repair genes themselves are not likely the cause of increased gemcitabine sensitivity, as gemcitabine-related DNA repair is usually repaired through other DNA repair pathways. We did not find any correlation with gemcitabine sensitivity and gemcitabine-transporter or metabolizing protein expression. There has been difficulty elucidating the mechanism for differential sensitivity seen of MSI cell lines to other agents such as irinotecan and 5FU previously.32–34 MSI-H cell lines likely have some other molecular abnormality common between them, for which MSI-H is a surrogate biomarker, perhaps just overall genomic instability. Takahashi et al. reported that there was increased in vitro sensitivity of a MLH1-deficient/MSI when compared to MLH1 introduced MSI colon cancer to DNA polymerase inhibitors such as gemcitabine and hydroxyurea.12
In our study, there were some inherent challenges in assessing the contributions of the MSI vs. CHFR-methylated phenotype to drug sensitivity due to the overlap between CHFR methylation and MSI. Our work attempted to tease out these differences using candidate cell lines that express MSI or CHFR exclusively as well as those with both biomarkers, as would be found in a standard patient population. The selected cell lines were very rapid growing cell lines; this rapid growth did make post-treatment effects of treatment difficult to interpret. Still, during active treatment, there was clearly differential activity of each agent and the combination predicted by biomarker presence or absence. Moreover, after active treatment of the mice ceased (at the time of sacrifice of mock group), we noted sustained growth inhibition in the combination treated group compared to docetaxel alone for COLO205 and RKO (Figure 4B–C).
Our data support the possibility that CHFR methylation and MSI may be predictive biomarkers for docetaxel and/or gemcitabine treatment for subsets of colon cancer patients. For this work, we chose 10 cell lines that are commonly used in preclinical work for colorectal cancer, and which provided a group of cell lines with differential MSI and CHFR methylation status. We feel this was an adequate, albeit limited, sample size to test our hypothesis. The overlap between MSI and CHFR methylation as well as MSI and the hypermethylator phenotype (CIMP) creates great opportunities for combination treatment with a taxane plus gemcitabine regimen for ~15% of CRC, a regimen that would be predicted to have at least additive benefit for these CHFR-methylated, MSI patients. In addition, another 15% of patients with only CHFR methylation or MSI would be predicted to benefit from monotherapy with either a taxane or gemcitabine. A phase II trial to test this hypothesis in a biomarker-driven patient metastatic CRC population has recently been activated. More broadly, oncologic drug testing based on epigenetic biomarkers may be an important piece of the drug development paradigm to appropriately select therapy for cancer patients of all tumor types.
We have previously reported that CHFR methylation occurs in a subset of CRC tumors and has high concordance with the MSI phenotype. Here we report that CHFR methylation predicts for docetaxel sensitivity and MSI status predicts for gemcitabine sensitivity in CRC cell lines. We have confirmed these findings in xenograft models and our results form the basis of a phase II study of this novel combination in patients based on MSI and CHFR methylation status.
We thank Dr. Scott Kern for helpful comments and suggestions.
FINANCIAL DISCLOSURES/ CONFLICTS OF INTEREST
JGH receives consulting fees and research support from MDxHealth. Under a licensing agreement between the Johns Hopkins University and this company, the methylation-specific PCR assay was licensed to MDxHealth, and the university is entitled to a share of the royalties received by the company from sales of the licensed technology.