Abstract
The capecitabine and temozolomide (CAPTEM) regimen is active in the treatment of metastatic pancreatic neuroendocrine tumors (pNETs), with response rates ranging from 30 to 70%. Small retrospective studies suggest that O6-methylguanine DNA methyltransferase (MGMT) deficiency predicts response to temozolomide. High tumor proliferative activity is also commonly perceived as a significant predictor of response to cytotoxic chemotherapy. It is unclear whether chromosomal instability (CIN), which correlates with alternative lengthening of telomeres (ALT), is a predictive factor. In this study, we evaluated 143 patients with advanced pNET who underwent treatment with CAPTEM for radiographic and biochemical response. MGMT expression (n=52), grade (n=128) and ALT activation (n=46) were investigated as potential predictive biomarkers. Treatment with CAPTEM was associated with an overall response rate (ORR) of 54% by RECIST 1.1. Response to CAPTEM was not influenced by MGMT expression, proliferative activity or ALT pathway activation. Based on these results, no biomarker-driven selection criteria for use of the CAPTEM regimen can be recommended at this time.
Introduction
Chemotherapy regimens containing the oral alkylating agent temozolomide are active in the treatment of metastatic pancreatic neuroendocrine tumors (pNETs), with response rates ranging from 30 to 70% (Kulke et al. 2006, Strosberg et al. 2011, Chan et al. 2012, Fine et al. 2013). The cytotoxic activity of temozolomide is related to its ability to induce DNA alkylation/methylation at the O6 and N7 positions of guanine, ultimately resulting in DNA mismatch and tumor cell death. The suicide enzyme O6-methylguanine DNA methyltransferase (MGMT) repairs DNA by removing the O6-alkylguanine adducts. High levels of MGMT expression contribute to chemoresistance by counteracting the therapeutic effect of alkylating agents (Gerson 2004). Among patients with either advanced glioblastoma or melanoma treated with temozolomide, loss of tumoral MGMT is associated with improved survival (Middleton et al. 1998, Hegi et al. 2005, Chinot et al. 2007). In pNET patients, conflicting results have been reported so far (Ekeblad et al. 2007, Kulke et al. 2009, Schmitt et al. 2014, Walter et al. 2015), and it is still unclear whether MGMT deficiency is predictive for clinical benefit from temozolomide.
Tumor grade, measured by mitotic rate or Ki-67 proliferative index, is often regarded as a significant predictor of response to chemotherapy in pNET patients (Falconi et al. 2012, Öberg et al. 2012). However, no studies have formally investigated the correlation between proliferative activity and tumor response. Clinically aggressive pNETs are also characterized by chromosomal instability (CIN) (Jonkers et al. 2005), which has been recently associated with loss of DAXX/ATRX and activation of the alternative lengthening of telomeres (ALT), a telomerase-independent mechanism of telomere maintenance (Marinoni et al. 2014). Although patients with fast-growing, bulky, highly mutated pNETs are deemed to be ideal candidates for chemotherapy (Kunz et al. 2015), it is unclear whether DAXX/ATRX loss and ALT activation, as surrogate marker of CIN, predicts response to temozolomide.
In an era in which the therapeutic landscape of pNETs is rapidly evolving and multiple treatment options are available (Cives & Strosberg 2014), providers are faced with the challenge of treatment sequencing. As a result, there is a clear need for identification of predictive biomarkers to enable selection of patients who are likely to benefit from specific therapies. In this study, we investigated MGMT expression, tumor proliferation, DAXX/ATRX status and ALT activation as potential predictors of response to capecitabine/temozolomide (CAPTEM) chemotherapy in patients with advanced pNETs.
Patients and methods
Patients, treatment and tumor response evaluation
Approval for data collection and analysis was obtained from the Institutional Review Board of the University of South Florida (Tampa, FL, USA). We retrospectively examined 143 consecutive patients with unresectable pNET who received CAPTEM chemotherapy at our institution between 2005 and 2014 and were assessable for radiographic response. Demographic, clinical and pathological information including tumor grade by World Health Organization (WHO) 2010 criteria (Rindi et al. 2010), mitotic rate and Ki-67 labeling index were obtained by review of patient medical records. The chemotherapy regimen consisted of oral capecitabine, 750mg/m2 twice daily for 14days (days 1–14), and oral temozolomide, 200mg/m2 once daily for 5days (days 10–14), every 28days, as described previously (Strosberg et al. 2011).
Radiological assessment of tumor responses was separately and independently performed by two investigators (M C and J S) and all discrepancies in response assessment were adjudicated by a radiologist (B M). The nearest pretreatment computed tomography or magnetic resonance imaging scan was used as baseline and compared with subsequent scans, obtained as part of routine clinical care. The Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 (Eisenhauer et al. 2009) was used for evaluation of radiographic response. Biochemical response was measured based on baseline chromogranin A (CgA) levels obtained before initiation of the temozolomide-based regimen.
Immunohistochemistry
Immunohistochemistry (IHC) was used to evaluate the expression of MGMT, DAXX and ATRX. Sections of 5µm in thickness were cut from archival paraffin-embedded pathology specimens and subjected to MGMT staining protocol using the Ventana Discovery XT automated system (Ventana Medical Systems, Tucson, AZ, USA) as per manufacturer’s protocol with proprietary reagents. Immunolabeling for DAXX and ATRX was performed as described previously (Jiao et al. 2011). The mouse mAb against MGMT (MS-470-P1; Thermo Scientific) was used at a 1:20 concentration, whereas the rabbit polyclonal antibodies anti-DAXX (HPA008736; Sigma‐Aldrich) or anti-ATRX (HPA001906; Sigma‐Aldrich) were used at 1:150 and 1:400 dilution, respectively. After 1h of incubation at room temperature, the primary antibodies were detected by 16 (MGMT) and 30min (DAXX, ATRX) of incubation with the respective HRP-labeled secondary antibody. Tissue sections were developed using 3,3′-diaminobenzidine (Sigma-Aldrich) as a substrate and then counterstained with hematoxylin.
The immunostained sections were examined under a light microscope by two independent pathologists (M G and M B) who were blinded to the patient clinical outcome. In case of disagreement, a consensus was reached after joint review at a multihead microscope. MGMT expression was evaluated by three different systems of interpretation (Allred et al. 1993, Ekeblad et al. 2007, Kulke et al. 2009). Criteria for MGMT deficiency determination are listed in Supplementary Table 1, see section on supplementary data given at the end of this article. For DAXX and ATRX, only nuclear labeling was evaluated. Tumors were scored as positive when there was nuclear labeling in at least 50% of tumor cells. Non-neoplastic cells (endothelial cells, stromal cells and islets of Langerhans) served as an internal positive control in all tissue sections. Cases lacking positive immunostaining in benign elements were considered to be uninformative.
Telomere-specific FISH
Telomere-specific FISH was performed and interpreted as described previously (Heaphy et al. 2011). Briefly, deparaffinized slides were hydrated, steamed for 20min in citrate buffer, dehydrated and hybridized with a Cy3-labeled peptide nucleic acid (PNA) probe complementary to the mammalian telomere repeat sequence ([N-terminus to C-terminus] CCCTAACCCTAACCCTAA). As a positive control for hybridization efficiency, a FITC-labeled PNA probe having specificity for human centromeric DNA repeats (ATTCGTTGGAAACGGGA; CENP-B binding sequence) was also included in the hybridization solution. Following post-hybridization washes, nuclear counterstaining with 4′,6-diamidino-2-phenylindole (DAPI) was conducted. Slides were imaged with a Nikon 50i epifluorescence microscope equipped with X-Cite series 120 illuminator (EXFO Photonics Solutions Inc, Ontario, Canada) and appropriate excitation/emission filters. Gray-scale images were captured using Nikon NIS-Elements software and an attached Photometrics CoolSNAP EZ digital camera, pseudo-colored and merged.
The FISH slides were assessed by A K M Large, ultra-bright telomere repeat DNA aggregates are unique to ALT-positive cell populations and are significantly larger and brighter than the FISH signals emanating from normal telomeres in the same cell population. pNETs were classified as ALT-positive if they met the following criteria: (i) the presence of ultra-bright, intranuclear foci of telomere FISH signals and (ii) ALT-associated telomeric DNA foci in ≥1% of neoplastic cells. Tumor samples lacking ALT-associated telomeric foci were considered ALT-negative. In all cases, areas exhibiting necrosis were excluded from consideration.
Statistical analysis
Expression of MGMT, proliferative activity, activation of the ALT pathway and tumor mutational status were correlated with the patients’ radiographic or biochemical response using the χ2 test or Fisher’s exact test, as appropriate. The Cohen’s kappa coefficient was used to assess the degree of correlation between the different systems adopted for MGMT status interpretation. All time-to-event functions were estimated by the Kaplan–Meier method and compared by the log-rank test. Progression-free survival (PFS) was calculated from initiation of chemotherapy until the date of first progressive disease or death due to any cause. Overall survival (OS) was defined as the time from start of treatment until death as a result of any cause, with patients censored at the date of last follow-up if still alive. Time-to-treatment failure (TTF) was defined as the time from treatment initiation until discontinuation for any reason. Exact 95% CI were calculated for each proportion of interest. All tests were two sided and statistical significance was declared at P<0.05. Statistical analysis was performed using MedCal statistical software 12.7 (MedCalc Software bvba, Ostend, Belgium).
Results
Demographics and tumor characteristics
Demographic variables and clinicopathological characteristics of 143 patients enrolled in the study are listed in Table 1. At treatment onset, median age of the patient population was 59 (28–82) years. The majority (91/143) of patients were males, and more than three quarters (115/143) had grade 1 or 2 pNETs. No large cell or small cell neuroendocrine carcinomas were included in the study. Twenty-seven patients had hormonally functioning tumors, including 11 patients with gastrinoma syndrome, 8 patients with glucagonoma or insulinoma syndrome, 6 patients with VIPoma syndrome, 1 patient with carcinoid syndrome and 1 patient with ectopic ACTH secretion. Tumors were metastatic in 133 patients and locally advanced in 10 patients. Most patients (117/143) were treatment naïve or had received only one prior line of systemic therapy; 59 received prior octreotide long-acting repeatable (LAR), 24 received prior cytotoxic chemotherapy (including etoposide/cisplatin, streptozotocin, gemcitabine and radiosensitizing capecitabine), 11 had prior everolimus, 6 had prior sunitinib, 2 had prior peptide receptor radionuclide therapy (PRRT) and 9 had prior investigational agents (including pasireotide, bevacizumab and ganitumab). The median time from diagnosis until CAPTEM initiation was 12 (1–204) months.
Patient demographics and clinical characteristics.
Characteristics | n of patients (=143) | % |
---|---|---|
Age (years) | ||
Median | 59 | |
Range | 28–82 | |
Gender | ||
Male | 91 | 64 |
Female | 52 | 36 |
Race | ||
White | 117 | 82 |
Black | 17 | 12 |
Hispanic | 5 | 3 |
Asian | 4 | 3 |
Time from diagnosis (months) | ||
Median | 12 | |
Range | 1–204 | |
Genetic syndrome | ||
No | 140 | 98 |
Yes | 3 | 2 |
VHL | 2 | 1 |
MEN1 | 1 | 1 |
Tumor grade (WHO 2010) | ||
G1 | 78 | 55 |
G2 | 37 | 26 |
G3 | 13 | 9 |
Not available | 15 | 10 |
Tumor functionality | ||
No | 116 | 81 |
Yes | 27 | 19 |
Gastrinoma syndrome | 11 | 7 |
VIPoma syndrome | 6 | 4 |
Glucagonoma syndrome | 4 | 3 |
Insulinoma syndrome | 4 | 3 |
Cushing’s syndrome | 1 | 1 |
Carcinoid syndrome | 1 | 1 |
Sites of metastases | ||
Locally advanced | 10 | 7 |
Liver | 128 | 89 |
Lymph nodes | 37 | 26 |
Bone | 16 | 11 |
Lung | 5 | 3 |
Othersa | 7 | 5 |
Elevated baseline chromogranin A (>ULN) | ||
Yes | 89 | 62 |
No | 54 | 38 |
Baseline chromogranin A (nl <15ng/mL) | ||
Median | 27 | |
Mean | 340 | |
Range | (1–8000) | |
Prior lines of systemic therapy | ||
0 | 61 | 43 |
1 | 56 | 39 |
2 | 16 | 11 |
3 | 8 | 6 |
4 | 2 | 1 |
Previous systemic therapy | ||
Octreotide LARc | 59 | 41 |
Chemotherapyb | 24 | 17 |
Everolimus | 11 | 8 |
Sunitinib | 6 | 4 |
PRRT | 2 | 1 |
Investigational agents | 9 | 6 |
Concurrent octreotide LAR | ||
Yes | 32 | 22 |
No | 111 | 78 |
No. of temozolomide/capecitabine cycles | ||
Median | 9 | |
Range | 1–28 |
Including kidneys, adrenal glands, breasts, adnexa, spleen and peritoneum; bIncluding etoposide/cisplatin (21/143), streptozotocin (1/143), gemcitabine (1/143) and capecitabine (1/143); cOctreotide LAR was the only prior therapy in 39 patients (27%).
Treatment outcomes
Patients received a median of nine 28-day treatment cycles. Reasons for discontinuation included radiographic tumor progression (n=47), maximal response or chemotherapy break (at physician’s discretion; n=66), unacceptable toxicity (n=20) and patient decision (n=2). Eight patients remained on treatment at the time of data analysis. Toxicities leading to CAPTEM discontinuation included thrombocytopenia (n=11), fatigue (n=5), palmoplantar erythrodysesthesia (n=3) and neutropenia (n=1).
All 143 patients were assessable for radiographic response. When best response to therapy was evaluated, 54% (77/143) of patients experienced partial response according to RECIST criteria, whereas 35% (50/143) had stable disease and 11% (16/143) experienced progressive disease. The waterfall plot analysis (Fig. 1A) showed some degree of tumor shrinkage in 78% (112/143) of evaluable patients and continued tumor growth in 22% (31/143) of the cohort. Among 89 patients with baseline-elevated (>ULN) serum CgA levels, 54 patients (61%) experienced major reductions (>50%) or normalization of the tumor marker. This biochemical response was observed within 3months of treatment initiation in 28 patients (31%). Differences between the median baseline CgA concentration and its lowest and 3-month value following initiation of treatment were statistically significant (P<0.0001 and P=0.0004, respectively; Fig. 1B).
At the time of data cutoff, 54 patients had died and 89 patients were alive, with median follow-up duration of 34months (range: 4–113months). As depicted in Fig. 2A, the median OS was 73.2months (95% CI, 51.9–81.1months), and the 5-year survival rate was 58.6% (±4.9%). The median PFS was 17months (95% CI: 15–25months; Fig. 2B). At 1 and 2years, estimated rates of PFS were 70.6% (±4.6%) and 41.8% (±6.9%), respectively. Among responding patients, the median duration of response was 19months (95% CI: 9–28months). The median TTF was 9months (95% CI: 7.8–10.2months).
MGMT expression as a predictor of response
MGMT expression was evaluated in 65 pNET patients with available tissue. The IHC staining was not interpretable in 13 cases because of lack of positive internal controls or paucity of tumor cells. Among 52 assessable cases, 15 (29%) were MGMT deficient, when the deficiency was defined by the complete absence of staining in all tumor cells (Kulke et al. 2009). When MGMT deficiency was defined by the lack of nuclear staining in ≥10% of tumor cells (Ekeblad et al. 2007) or by an Allred score <4 (Allred et al. 1993), we interpreted as deficient 20 (38%) and 19 (36%) cases, respectively. Interobserver agreement rate was 77%. By Cohen’s test, there was a high degree of correlation between the two latter methods of MGMT staining interpretation (κ=0.96 ± 0.04). The concordance rates between the interpretation system proposed by Kulke et al. (2009) and the other two methods were slightly lower (κ=0.49±0.12 and κ=0.53±0.12, respectively). As detailed in Table 2, patients harboring MGMT-intact or MGMT-deficient pNETs exhibited similar overall response rates (ORR) following CAPTEM treatment. MGMT expression by IHC had no significant influence on biochemical response rate, OS or PFS.
Candidate biomarkers in pNETs.
Criteria of stratification | Interpretable cases (n) | ORR (%) | P | Major biochemical response (%) | P | PFS, 95% CI (months) | P | OS, 95% CI (months) | P |
---|---|---|---|---|---|---|---|---|---|
MGMT (intact: nuclear staining in any tumor cells) | 52 | 0.10 | 0.66 | 0.25 | 0.40 | ||||
MGMT intact | 65 | 67 | 16.8 (14.5–16.8) | NR | |||||
MGMT deficient | 40 | 50 | 14.5 (6.2–14.5) | 81.1 (73.2–81.1) | |||||
MGMT (intact: nuclear staining in ≥10% of tumor cells) | 52 | 0.37 | 0.56 | 0.62 | 0.41 | ||||
MGMT intact | 63 | 47 | 14.5 (12.6–24.3) | 73.2 (36.4–73.2) | |||||
MGMT deficient | 50 | 35 | 16.6 (15.4–17.4) | 81.1 (48.7–81.1) | |||||
MGMT (intact: Allred score ≥4) | 52 | 0.25 | 0.57 | 0.54 | 0.27 | ||||
MGMT intact | 64 | 45 | 17.4 (12.6–24.3) | 73.2 (36.4–73.2) | |||||
MGMT deficient | 47 | 37 | 16.6 (15.4–16.6) | 81.1 (39.2–81.1) | |||||
Grade | 128 | 0.29 | 0.7 | 0.83 | 0.84 | ||||
Low grade | 65 | 64 | 16.8 (15.4–24.3) | 72.1 (48.6–81.1) | |||||
Intermediate grade | 52 | 72 | 14.5 (10–14.5) | 67.4 (35.2–73.2) | |||||
High grade | 69 | 78 | 24.6 (22.6–24.6) | 76.2 (17.8–76.2) | |||||
Mitotic count/10 HPF | 96 | 0.93 | 0.03 | 0.58 | 0.007 | ||||
<2 | 54 | 64 | 17.4 (15.4–24.3) | 74.8 (36.4–81.1) | |||||
2 <MC<20 | 50 | 74 | 16.8 (9.8–24.6) | 73.2 (31.5–73.2) | |||||
>20 | 50 | 100 | NR | 14.6 (11.4–14.6) | |||||
Ki-67 labeling index | 80 | 0.38 | 0.74 | 0.27 | 0.61 | ||||
<3% | 65 | 90 | NR | 35.2 (33.6–35.7) | |||||
Between 3 and 20% | 50 | 67 | NR | 73.2 (42.2–81.1) | |||||
>20% | 42 | 71 | 14.5 (10–24.6) | 76.2 (17.9–76.2) | |||||
ALT status | 46 | 0.37 | 0.66 | 0.38 | 0.02 | ||||
ALT-positive | 63 | 77 | NR | NR | |||||
ALT-negative | 47 | 70 | 14.5 (10.2–16.8) | 36.4 (30.1–81.1) | |||||
DAXX/ATRX status | 31 | 0.34 | 0.27 | 0.35 | 0.13 | ||||
DAXX/ATRX-positive | 52 | 53 | 16.3 (14.5–16.8) | 48.7 (34.5–48.7) | |||||
DAXX/ATRX-negative | 69 | 75 | NR | NR |
NR, not reached.
Tumor proliferation as a predictor of response
Tumor grade, mitotic rate and Ki-67 labeling index were assessable in up to 128/143 patients. As detailed in Table 2, response to CAPTEM in patients with pNETs was not significantly influenced by tumor proliferation, even when the lower Ki-67% threshold was set up at 5, 10 or 55%. High mitotic rate (>20mitoses/10 high-power fields) was associated with poor prognosis.
ALT activation as a predictor of response
Among 61 pNET samples analyzed by telomeric FISH to detect ALT activation, 15 were not interpretable due to nonspecific background staining or paucity of tumor cells. Twenty-seven (59%) tumors had ultra-bright telomere FISH signals, a nearly universal feature of ALT (Fig. 3). Histomorphologically, ALT-positive samples were characterized by atypical cytology, defined as chromatin density heterogeneity and variation in nuclear size. ALT activation did not predict response to CAPTEM but was associated with improved survival (P=0.02; Table 2). Given the reported association between ALT activation and DAXX/ATRX loss (Heaphy et al. 2011, Marinoni et al. 2014), we evaluated using IHC the expression of both proteins in pNETs. In ALT-positive tumors, DAXX/ATRX were deficient in 16 (59%) cases, positive in 1 (4%) and unevaluable in 10 (37%) tumors because of the lack of positive internal controls. In ALT-negative tumors, we observed the loss of DAXX or ATRX in 4 (21%) tumors. Overall, there was an inverse correlation between ALT activation and loss of DAXX/ATRX (P<0.0001). The expression of DAXX/ATRX was neither predictive of response to CAPTEM, nor affected patient prognosis (Table 2). The overall cohort and the cohorts evaluated in MGMT expression, tumor proliferation and ALT status were not different in terms of baseline characteristics, nor therapeutic outcomes.
Discussion
This is the largest reported cohort of pNET patients treated with CAPTEM chemotherapy. We observed an ORR of 54%, a median OS of 73.2months and a median PFS of 17months. We also found that MGMT expression as measured by IHC, proliferative activity and ALT pathway activation did not predict response to CAPTEM.
There remains considerable controversy regarding the optimal method of MGMT detection in tumor samples. In pNETs, both methyl-specific PCR and pyrosequencing have been used to evaluate MGMT promoter methylation status as a surrogate of MGMT activity (Schmitt et al. 2014, Walter et al. 2015). Direct measurement of MGMT protein expression by IHC is the most convenient technique to measure MGMT status in the clinical setting, despite pitfalls in the interpretation of the staining that have been described (Kulke et al. 2009, Walter et al. 2015). In the absence of formal recommendations or uniformly used criteria for the interpretation of MGMT immunostaining (Ekeblad et al. 2007, Kulke et al. 2009, Schmitt et al. 2014, Walter et al. 2015), we defined the MGMT status according to different systems and found that MGMT was undetectable in 29–38% of tumors. These rates are slightly lower than previously reported for pNETs (36–66%) (Ekeblad et al. 2007, Kulke et al. 2009, Schmitt et al. 2014, Walter et al. 2015). Sample bias, sampling issues, interobserver variability and/or IHC technical differences (including the use of different antibodies against MGMT) might account for this difference. Although small studies have identified MGMT deficiency by IHC as a predictor of response to temozolomide in pNETs (Kulke et al. 2009, Walter et al. 2015), this biomarker was neither predictive nor prognostic in our series. A possible explanation is that concurrent capecitabine may counteract MGMT-associated resistance to temozolomide (Fine et al. 2013). Alternatively, variations in quality of tissue samples and in interpretation of IHC data may have attenuated the predictive power of this assay. High proliferative activity and rapid pace of disease progression are commonly regarded as major determinants of sensitivity to cytotoxic drugs in patients with pNETs. However, no correlation between tumor grade, mitotic rate or Ki-67 labeling index and tumor response to CAPTEM was observed in our series. This finding might be related to the fact that the cytotoxic activity of temozolomide is not confined to mitosis, but spans the whole cell cycle (Gerson 2004). Moreover, it emphasizes the concept that tumor proliferative activity, measured on needle biopsy or resected primary tumor specimen, may not always reflect the clinical aggressiveness of a metastatic pNET.
Consistent with previous studies (Heaphy et al. 2011, Marinoni et al. 2014), we found that 59% of analyzed pNETs were ALT-positive. ALT activation was negatively associated with DAXX/ATRX expression (P<0.0001) and prognostic for improved survival (P=0.02) in a population of patients with advanced/metastatic pNETs. This association has been observed in other series of metastatic pNETs (Jiao et al. 2011). Both ALT status and DAXX/ATRX expression, as surrogate markers of CIN (Marinoni et al. 2014), were not able to predict response to CAPTEM.
Limitations of this study included its retrospective design and paucity of tissue in a large fraction of cases. Tissue limitations precluded assessment of MGMT promoter methylation assays and other potential molecular biomarkers and reduced our ability to detect meaningful differences in the tested potential predictors. Moreover, it is important to emphasize that even though mitotic rate and Ki-67 index were not predictive of response in this series, nearly all tumors were clinically aggressive (i.e. symptomatic, rapidly progressive or widespread). Thus, the response rates observed in this series should not be assumed to reflect the activity of CAPTEM in patients with indolent, low-grade pNETs.
In conclusion, CAPTEM is associated with very encouraging treatment outcomes and survival durations in patients with advanced pNETs. Although MGMT status has been postulated to be a predictive factor for response based on small retrospective studies and has been used in clinical practice, we have not observed any correlation between protein expression and radiographic response in this series of patients treated with CAPTEM. Moreover, despite the common perception that chemotherapy is particularly active in highly proliferative tumors, we were unable to observe any correlation between mitotic activity or Ki-67 index and response. Although we cannot recommend any biomarker-driven selection criterion for use of the CAPTEM regimen, future studies, including a prospective randomized trial of temozolomide alone or in combination with capecitabine (Nbib1824875), may provide further insight into the predictive validity of MGMT promoter methylation, among other assays.
Supplementary data
This is linked to the online version of the paper at http://dx.doi.org/10.1530/ERC-16-0147.
Declaration of interest
Dr Strosberg has performed consultation for Novartis and Ipsen within institutional conflict of interest payment guidelines. All remaining authors have declared no conflicts of interest.
Funding
This work was supported by Moffitt Cancer Center patients’ donations.
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