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. Author manuscript; available in PMC: 2011 Jan 1.
Published in final edited form as: Br J Haematol. 2009 Oct 28;148(2):256–267. doi: 10.1111/j.1365-2141.2009.07954.x

Laboratory Correlates for a Phase II Trial of Romidepsin in Cutaneous and Peripheral T-Cell Lymphoma

Susan E Bates 1,*, Zhirong Zhan 1, Kenneth Steadman 1, Tomasz Obrzut 1, Victoria Luchenko 1, Robin Frye 1, Robert W Robey 1, Maria Turner 2, Erin R Gardner 3, William D Figg 4, Seth M Steinberg 5, Alex Ling 6, Tito Fojo 1, Kin Wah To 1, Richard L Piekarz 1
PMCID: PMC2838427  NIHMSID: NIHMS180087  PMID: 19874311

SUMMARY

Since romidepsin has shown promise in the treatment of T-cell lymphomas, we evaluated molecular endpoints gathered from 61 patients enrolled on a phase II trial of romidepsin in cutaneous and peripheral T-cell lymphoma at the National Institutes of Health. The endpoints included histone H3 acetylation and ABCB1 gene expression in peripheral blood mononuclear cells (PBMCs); ABCB1 gene expression in tumor biopsy samples; and blood fetal hemoglobin levels (HbF), all of which were increased following romidepsin treatment. The fold increase in histone acetylation in PBMCs at 24 h was weakly to moderately well correlated with the pharmacokinetic parameters Cmax and AUClast (ρ =0.37, p=0.03 and ρ =0.36, p=0.03 respectively) and inversely associated with clearance (ρ =−0.44; p=0.03). Histone acetylation in PBMCs at 24 h was associated with response (p = 0.026) as was the increase in fetal hemoglobin (p = 0.014); this latter association may be due to the longer on-study duration for patients with disease response. Together, these results suggest that pharmacokinetics may be an important determinant of response to HDIs – the association with histone acetylation in PBMCs at 24 h is consistent with a hypothesis that potent HDIs are needed for a critical threshold of drug exposure and durable activity.

Keywords: histone deacetylase inhibitor, romidepsin, p-glycoprotein, fetal hemoglobin, T-cell lymphoma

INTRODUCTION

Romidepsin (formerly depsipeptide, FK228 or FR901228), like other histone deacetylase inhibitors (HDIs), has been found to alter gene expression patterns in a variety of cell types, including breast, lung, colon, lymphoblastic leukemia, and bladder cancer consistent with a more differentiated phenotype. HDIs have been shown to mediate increased expression of cell cycle regulators such as p21 and p27 (Archer, et al 1998, Piekarz, et al 2004, Richon, et al 2000, Sandor, et al 2000b); cell type-specific differentiation genes such as those encoding the sodium iodide (Na/I) symporter in thyroid carcinoma cells and fetal hemoglobin in erythroblasts (Cao and Stamatoyannopoulos 2006, Kitazono, et al 2001, Lea, et al 2007, Munster, et al 2001, Murphy, et al 1990, Piekarz, et al 2004, Svechnikova, et al 2008); tumor antigens such as MAGE-3 and NYESO-1 in lung cancer cell lines (Weiser, et al 2001a, Weiser, et al 2001b); and genes encoding pro-apoptotic proteins such as Fas, FasL, TRAIL, DR-5 and TNF-alpha (Imai, et al 2003, Insinga, et al 2005, Klisovic, et al 2003, Rosato, et al 2006, Sutheesophon, et al 2005). HDIs are believed to upregulate the expression of some genes by inducing chromatin relaxation through acetylation of the positively charged lysine tails of the histone proteins that form the octomeric core of chromatin (Lin, et al 2006, Marks, et al 2000). Post-translational modifications of these histone proteins are understood to create an epigenetic code that controls gene expression and silencing (Lin, et al 2006, Marks, et al 2000). However, the role of altered gene expression in HDI-induced cell death has not been elucidated. Indeed, there is evidence that competing activities may in some cases result in drug resistance. This particularly may apply to the p21 induction leading to G1 arrest. Experiments in which the G1 arrest has been abrogated, as in p21 knockout cells, or through flavopiridol-mediated escape from p21-mediated cell cycle inhibition, have shown increased cell death following HDI therapy (Nguyen, et al 2004, Sandor, et al 2000a).

The modulation of gene expression patterns — the so-called markers of differentiation — offers the possibility of exploiting HDIs in combination therapy in malignant and nonmalignant disease (Kitazono, et al 2001, Lea, et al 2007, Munster, et al 2001, Murphy, et al 1990, Piekarz, et al 2004, Svechnikova, et al 2008). For example, induction of the Na/I symporter results in increased uptake of radioiodine in cell lines in vitro (Kitazono, et al 2001), suggesting a therapeutic strategy for increasing radioactive iodine uptake in thyroid carcinoma cells in patients. Similarly, increased expression of CD25 in T-cell lymphoma cell lines has been demonstrated, resulting in increased in vitro sensitivity to CD25-targeted therapy (Chen, et al 2009, Piekarz, et al 2004, Shao, et al 2002). The earlier use of butyrates and more recently more potent HDIs to induce fetal hemoglobin is a strategy that has been proposed for treatment of sickle cell anemia and other hemoglobin disorders (Cao and Stamatoyannopoulos 2006, Skarpidi, et al 2003). Finally, although it is difficult to identify a therapeutic goal for induction of ABCB1, the induction of this gene by HDIs has been found to be as reliable a marker as the induction of p21 (Jin and Scotto 1998, Mickley, et al 1989, Robey, et al 2006).

We first reported that romidepsin had marked efficacy in patients diagnosed with peripheral (PTCL) or cutaneous T-cell lymphoma (CTCL)(Piekarz, et al 2004) and subsequently opened a phase II trial in these diseases. One objective of the Phase II trial of romidepsin in cutaneous and peripheral T-cell lymphoma was to evaluate the molecular effects of HDIs. First, we evaluated the increased global histone acetylation that follows HDAC inhibition in peripheral blood mononuclear cells (PBMCs) using an immuno-dot blot method. Second, we evaluated ABCB1 gene induction as a measure romidepsin effect and a possible marker of drug resistance since P-glycoprotein (encoded by the ABCB1/MDR-1 gene) is known to transport romidepsin (Lee, et al 1994, Piekarz, et al 2004, Robey, et al 2006, Xiao, et al 2005, Yamada, et al 2006). Finally, we utilized the clinical laboratory assay for fetal hemoglobin induction and monitored the persistence of romidepsin biological effects over time.

MATERIALS AND METHODS

Patient population

The patients included in this report are those who were enrolled at the NIH Clinical Center on a phase II trial of romidepsin entitled “Phase II Trial of Depsipeptide in Patients with Cutaneous and Relapsed Peripheral T-Cell Lymphoma” (trial number NCT00020436), conducted as a multi-institutional trial with the NCI Center for Cancer Research serving as the coordinating center. This study was approved by the NCI Institutional Review Board and all patients were required to give informed consent before study participation. Sixty-one patients are the subject of this report; 21 diagnosed with PTCL and 40 with CTCL. At protocol initiation, romidepsin was administered at 18 mg/m2 on days 1 and 5 of a 21 day cycle. To improve tolerability, the schedule was changed by amendment to 14 mg/m2 romidepsin on days 1, 8, and 15 of a 4 week schedule.

Patient samples

Peripheral blood mononuclear cells (PBMCs) were isolated by density gradient separation and viably frozen until analysis. Cells were obtained prior to treatment and then at 4, 24 and 48 h after the start of infusion. Tumor biopsies (core biopsies or skin biopsies) were obtained pretreatment and at off-study time points and were snap frozen until ready for use. Blood samples for HbF measurement were drawn along with other clinical laboratory samples and were generally obtained at least three times per cycle: prior to study enrollment, during the screening visit and then again on several different days following treatment. Pharmacokinetic sample collection and analysis were performed as reported previously (Piekarz, et al 2009, in press).

Histone acetylation analysis by immuno-dot blot

Viably frozen PBMCs were thawed, washed in PBS, resuspended in lysis buffer [Tris 0.02M (Biorad, Hercules, CA), Triton X-100 (Promega, Madison, WI), 0.2 mM, β-Mercaptoethanol 0.02% (Sigma, St Louis, Mo) and aprotinin 2000 U/mL (Sigma, St Louis, Mo)], and then subjected to 30 seconds of sonication. Protein concentrations were measured using the BCA™ Protein Assay Reagent kit (Pierce, Rockford, IL). After denaturing 20 µg protein in 50% guanidine isothiocyanate (GTC) solution [4M guanidine isothiocyanate, 50mM Tris-HCl (pH 7.5), 25 mM EDTA) (Invitrogen Carlsbad, CA)] and 50% PBS, the protein was serially diluted 1:1 with 50% GTC/50% PBS solution. Next, 100 µL protein solution was applied to a vacuum manifold and filtered through two 0.22-micron nitrocellulose membranes. The top membrane was washed twice in TBS (0.1M Tris, 0.154 M NaCl), blocked with 5% dry milk/TBS and probed with anti-GAPDH antibody (American Research Products, Belmont, MA; 1:500 in 5% dry milk/TBS) overnight at 4ºC. Subsequently, the blot was washed in TTBS (0.1M Tris, 0.154 M NaCl, 0.025% Tween) and incubated with anti-mouse HRP (Amersham, Piscataway, NJ; 1:1000 in 5% dry milk/TBS) for 50 minutes at room temperature before detection with ECL Western Blotting Substrate (Pierce, Rockford, IL) by autoradiography. The blot was stripped using ReBlot™ Plus Solution (Chemicon, Billerica, MA) and staining was repeated using anti-acetylated histone H3 antibody (Upstate, Charlottesville, VA, 1:2200). Multiple exposures of autoradiograms were obtained for histone acetylation and GAPDH to obtain a signal in the linear range and densitometry was performed. The relative increase in histone acetylation upon romidepsin treatment was determined after normalization by GAPDH.

Since the immuno-dot blot assay had a narrow linear range, a systematic method was developed to determine histone acetylation for data analysis. Signals from the dot blot for each serially diluted sample were multiplied by their respective dilution factors and the averages between two successive serially diluted samples obtained. The greatest of these averages was chosen for data analysis because it represents the most linear region. Replicate experiments demonstrated relative standard deviation (RSD) ≤ 30% (data not shown).

RT-PCR analysis of MDR-1/ABCB1 expression

Total RNA was isolated from peripheral blood mononuclear cells or patient tissue biopsies with the RNeasy Fibrous Tissue Mini Kit and subjected to on-column DNA digestion as outlined in the manufacturer’s instructions (Qiagen, Germantown, MD). Reverse transcription of 1 µg total RNA using random primers (Invitrogen, Carlsbad, CA) was performed for 1 h at 37°C. The samples were then heated at 95°C for 5 min to terminate the reverse transcription. The resulting cDNA was diluted 1:8 in water (i.e. 62.5 ng of RNA) and amplified by PCR using primers specific for ABCB1. PCR reactions contained 2.5 mM MgCl2, 200 µM dNTPs, 50 pmol of each of the 5’ and 3’ primers, and 1.5 units of Taq polymerase (Applied Biosystems, Foster City, CA). Primers used for detection of ABCB1 were as follows: 5’ (410–441 bp); 3’ (664–695 bp) of the ABCB1 gene (Chen, et al 1986). Expression of ABCB1 was normalized to ribosomal RNA (rRNA) (forward primer: AAACTCTGGTGGAGGTCCGT, reverse primer: CTTACCAAAAGTGGCCCACTA). The temperature program for the PCR was 1 cycle of 95°C for 6 min; 30 cycles of 94°C for 1 min 15 s, 55°C for 1 min 15 s, and 72°C for 2 min; and finally 1 cycle of 10 min at 72°C. PCR products were subject to electrophoresis on 1% agarose gels and stained with 2 µg/mL ethidium bromide. Band intensity was quantitated by using the APP Collage PPC v 4.0 analysis software program. Experimental precision, expressed as percent RSD of 10 assays, was ≤ 36% (data not shown).

Measurement of fetal hemoglobin (HbF)

Hemoglobin F values were obtained from the clinical hematology service, Warren G. Magnuson Clinical Center. The VARIANT™ ß-thalassemia Short Program (Bio-Rad Laboratories, Inc., Hercules, CA) uses the principles of cation-exchange high-performance liquid chromatography (HPLC) to separate the most frequently occurring hemoglobins based on their characteristic retention times through an analytical cartridge. A dual-wavelength filter photometer (415 and 690 nm) monitors the hemoglobin elution. Changes in absorbance are displayed as chromatograms that are then analyzed. The normal adult HbF value is typically less than 1% of total hemoglobin. The validated reportable range for HbF is 1–40%, with a limit of detection of 0.2%. In analyses that required a baseline, all reported values equal to or below 0.2% were assigned a value of 0.2%. To calculate a baseline, an average was obtained from up to three values obtained less than 14 days prior to or within 7 days after initiation of treatment. Peak values after initiation were obtained by averaging the highest two to three values obtained in close proximity and available over the patient’s treatment course, usually within an individual cycle. Zero baseline values were analyzed as 0, or these values were reassigned a value of 0.2% or 1%. Results using all three possible baseline values are included in this report.

Statistical Methods

Correlations between continuous parameters were performed using Spearman correlation analysis. A correlation coefficient, ρ, was determined such that |ρ | > 0.70 would be interpreted as being a strong correlation; 0.5 < |ρ | < 0.7 would be moderately strong; 0.3 < |ρ | < 0.5 would be weak to moderately strong, and if |ρ | < 0.3, the correlation would be considered to be weak. Comparisons of continuous parameters between two response categories were performed using a Wilcoxon rank sum test. All p-values are two-tailed and presented without adjustment for multiple comparisons. Comparisons of continuous parameters across the four ordered response categories (PD, SD, PD, CR) were performed using the Jonckheere-Terpstra test for trend. In view of the nature of the analyses and the number of exploratory analyses performed, we will consider results with p values < 0.05 to be statistically significant but to be hypothesis-generating, requiring further validation.

RESULTS

Romidepsin causes histone acetylation in patient PBMCs

Previous studies have shown that increased histone acetylation is observed in patient PBMCs following treatment with HDIs (de Bono, et al 2008, Kelly, et al 2005, Kummar, et al 2007, Robey, et al 2006, Sandor, et al 2002, Steele, et al 2008). While we previously used immunoblot analysis to measure histone acetylation (Robey, et al 2006), we developed an immuno-dot blot assay to improve quantitation, shown in Figure 1. PBMCs obtained from 3 patients showed higher acetylated histone levels at the 4-hour time point, with the highest induction noted for patient 2 (Figure 1). Levels at the 24 and 48 h time points varied. Changes in acetylated histone H3 levels were evaluated in 47 patients, 29 with CTCL and 18 with PTCL. Results are summarized in Figure 2A, Table 1 and Supplemental Table 1. As shown in Table 1, 39% of patients have a 2-fold or greater increase at the 48 hr time point. At the 4-hour time point, the median increase was 3.0-fold, dropping to 1.85-fold at 24 h and 1.46-fold at 48 h (Supplemental Table 1). Thus, although the median increase in histone acetylation was lower at the later time points, histone acetylation nonetheless remained higher compared to pretreatment levels. These results show that romidepsin rapidly induces robust histone acetylation in PBMCs obtained from patients treated at 14 mg/m2 on a day 1, 8, and 15 schedule.

Figure 1.

Figure 1

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Increased histone H3 acetylation in peripheral blood mononuclear cells (PBMCs) obtained from patients receiving romidepsin as measured by immuno-dot blot. Protein was extracted from patient PBMCs, serially diluted and transferred to a nitrocellulose membrane with a vacuum manifold as outlined in the Materials and Methods section. The membrane was subsequently probed with an anti-acetylated histone H3 monoclonal antibody and subjected to enhanced chemiluminescence detection (top blot). The blot was then stripped and reprobed with an anti-GAPDH antibody; only the top row is shown for GAPDH (bottom blot). Results for three separate patients are shown.

Figure 2.

Figure 2

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Summary of acetylated histone H3, ABCB1 expression, and hemoglobin F levels from patients receiving romidepsin. (A) Acetylated histone H3 levels (values based on the pre sample being assigned the value of 1) were determined by immuno-dot blot before patients were treated with romidepsin (pre) or at 4 h, 24 h and 48 h after start of the romidepsin injection. (B) ABCB1 expression levels (with the pre sample assigned the value of 1) in patient PBMCs obtained pre, 4 h, 24 h and 48 h after initiation of the romidepsin infusion were determined by quantitative RT-PCR. (C) Hemoglobin F levels (expressed as percent of total hemoglobin), were determined at baseline (average of up to three values obtained prior to or within the first 7 days of treatment), peak (average of up to three values obtained in close proximity and available over the patient’s treatment course) and final (average of up to three values at time of last dose) time points. For all graphs, the line represents the median data value.

Table 1.

Fold increase in histone acetylation, ABCB1 gene expression and hemoglobin F in patient PBMC samples at different times after treatment with romidepsin: Distribution of samples by magnitude of fold increase over pre value

Fold Increase
Histone Acetylation
Timepoint n x < 2 2 ≤ x < 4 x ≥ 4
4 h 41 11 (27%) 17 (41%) 13 (32%)
24 h 37 21 (57%) 9 (24%) 7 (19%)
48 h 18 11 (61%) 2 (11%) 5 (28%)
ABCB1 gene expression
n x < 2 2 ≤ x < 4 x ≥ 4
4 h 46 20 (43%) 17 (37%) 9 (19%)
24 h 46 29 (63%) 14 (30%) 3 (7%)
48 h 20 14 (70%) 3 (15%) 3 (15%)
Hemoglobin F
n x < 2 2 ≤ x < 4 x ≥ 4
Peak 52 14 (27%) 7 (13%) 31 (60%)
Final 49 20 (41%) 9 (18%) 20 (41 %)
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Increased expression of ABCB1 in PBMCs obtained from patients receiving romidepsin

We previously demonstrated that ABCB1 expression is upregulated in PBMCs obtained from patients treated with romidepsin (Robey, et al 2006). Thus, ABCB1 gene expression was evaluated in the present study. We considered that induction of gene expression represented a downstream or distal effect of HDAC inhibition. Such gene induction would confirm the ability of romidepsin to bind HDAC enzymes and remove them from repressive transcription factor complexes. In all, changes in ABCB1 expression were measured in PBMCs obtained from 52 patients, 35 with CTCL and 17 with PTCL. Results are summarized in Figure 2B and Table 1 and Supplemental Table 1.

Expression levels of ABCB1 were generally low and in twenty patients we could not detect at least a 2-fold increase in ABCB1 mRNA levels in PBMCs 4 hours after initiation of the romidepsin infusion. Among these 20 patients, 17 also had samples available at 24 h. Twelve of these samples (71%) again showed less than a 2-fold increase (Table 1). This indicates that there was concordance in low values at 4 and 24 h in patients with CTCL with low or no ABCB1 induction. In other words, if there was no significant rise at 4 h, there was not likely to be a significant rise at 24 h.

Scatterplots of ABCB1 mRNA expression in PBMCs are shown in Figure 2B. These plots graphically depict the increased ABCB1 mRNA expression observed. The highest increase in ABCB1 expression was noted in samples collected 4 h after the start of the romidepsin infusion. As noted in the tabulated data (Supplemental Table 1), the patients with PTCL had a higher median fold increase than patients with CTCL, 2.74 vs. 1.78; however this was not statistically significant (p=0.08).

Fetal hemoglobin levels in patients are elevated after romidepsin administration

We obtained fetal hemoglobin (HbF) values during the course of therapy as a potential surrogate marker for the effect of romidepsin on normal bone marrow. Numerous samples for HbF were obtained over time, in contrast to the surrogate studies with acetylated histone H3 and ABCB1 in PBMCs, which centered on samples collected during the first cycle. Results for each patient were visually examined to identify the cluster of highest values obtained over time. These values, up to 3 in number, were identified as the peak, and the highest value of the three was identified as the “peak value”. The time to peak value was identified, as well as the fold change over baseline. Representative plots are shown in Figure 3A–D and the data are summarized in Figure 2C, Table 1 and Supplemental Table 1. Additional patient data is provided in Supplemental Figure 1. Of the 61 patients with recorded values, 26 were reported as having a value of zero at baseline, and we reassigned these values a level of 0.2% for calculation of the fold-increase. In patients with a reported baseline HbF level of < 0.2%, whether the actual reported baseline was used, or if baseline values were reassigned a value of 0.2% (the lowest reported value), or a value of 1% (the value considered lowest limit of detection in the Variant™ instruction manual), the change to peak average or high value was statistically significant with p < 0.0001 in each case. The median time to peak induction was 99 days (range 27–295 days). Among the 61 patients, 73% demonstrated a two-fold or greater induction of fetal hemoglobin (Table 1). To be certain that this was not an effect of anemia induced by romidepsin, we corrected the values for total hemoglobin and demonstrated consistent findings (data not shown). Similar results were observed in patients with CTCL or PTCL (Table 1).

Figure 3.

Figure 3

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Hemoglobin F levels in 4 separate patients receiving romidepsin. Hemoglobin F levels (g/dL) were monitored in 4 patients (A–D) over time.

Analysis of ABCB1 expression levels in biopsy samples

Biopsy samples were obtained in patients from active disease sites. For patients with cutaneous T-cell lymphoma this was involved skin, and for patients with peripheral T-cell lymphoma this was usually fine needle aspiration of an involved lymph node. For patients with Sézary syndrome, circulating cells were obtained. Total RNA was analyzed by traditional PCR, as described in the methods section, and the amount of PCR product determined by densitometry. The densitometric value was normalized to the level of expression of ABCB1 in SW620 cells that stably express ABCB1 at a low level thought to be relevant to the range found in clinical samples. Expression in the SW620 cells was assigned a value of 10; this mRNA level encodes sufficient P-glycoprotein (P-gp) to be detectable by immunoblot analysis, and by functional efflux assays (Herzog, et al 1992). “On-study” and “pre” samples were usually obtained before the first dose of romidepsin, but were occasionally collected before the start of a treatment cycle. For evaluation of gene induction in the immediate post-romidepsin period, “peak” samples were obtained on the day following treatment, except in the case of Sézary syndrome, where circulating malignant cells were obtained at 4 and 24 hours. A sample was considered “off-study” if it was obtained within 30 days of discontinuing therapy. The immediate “post” romidepsin samples were not included as off-study values. Although pre/post samples were obtained at various intervals after enrollment, most pairs were obtained in cycle 1.

Figure 4 depicts a series of scatterplots of ABCB1 values obtained as outlined above. As shown in Figure 4A, only a sight increase in median levels was observed between off-study and on study samples for all patients treated. While samples from patients with CTCL showed only a slight increase in median ABCB1 expression levels (Figure 4B), ABCB1 expression appears to be more readily increased in PTCL tumors (Figure 4C). In Figure 4D, 34 sets of pre/post samples are plotted, obtained from 24 patients. Some patients contributed to more than one entry for the pre/post treatment data; 19 entries come from cycle 1; another 15 entries come from other treatment cycles. Fourteen of the 34 sets demonstrate a greater than 50% increase in the ABCB1 expression level and eight of the samples demonstrate a two-fold or greater increase in level. These results are consistent with gene induction in the tumor samples as a downstream event from histone deacetylase inhibition, but do not suggest induction of ABCB1 as a mechanism of resistance. Data are summarized in Supplemental Table 2.

Figure 4.

Figure 4

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ABCB1 levels in biopsy samples at on study (or pre), off-study, peak, and post time points. ABCB1 expression levels (with the pre sample assigned the value of 1) in biopsy samples obtained at on-study (before romidepsin treatment), off-study (within 30 days of discontinuing romidepsin) or peak (highest value obtained for any biopsy collected while receiving romidepsin) time points were determined by quantitative RT-PCR. Values are normalized to the level of expression of ABCB1 in SW620 cells that was assigned a value of 10. (A) Results from all patients. (B) Results from patients diagnosed with CTCL. (C) Results from patients diagnosed with PTCL. For graphs A–C, the line represents the median data value (D) ABCB1 expression levels before treatment (pre) are compared to the post treatment (post) values for 34 pairs of samples from 24 patients.

Statistical analysis of clinical correlates

Possible associations between biomarkers or pharmacokinetic parameters and response were then explored. As shown in Table 2, the increase in AcH3 in PBMCs at the 24 h time point was found to be weakly to moderately well correlated with the pharmacokinetic parameters Cmax (ρ =0.37, p=0.03), AUClast (ρ =0.36, p=0.03), and inversely correlated with drug clearance (ρ =-0.44, p=0.03), as shown in Figure 5. A weak to moderate correlation was also observed between these pharmacokinetic parameters and ABCB1 expression in patient biopsy samples, again with an inverse correlation with clearance (Table 2). This effect would be somewhat less pronounced if we excluded the data from one patient whose fold increase in ABCB1 in a biopsy sample was greater than 30, while all the other such values were below 8. There were no correlations between Cmax, AUClast or clearance with the fold increase in ABCB1 in PBMCs, the fold increase in HbF, decrease in platelet count, or cycle I platelet nadir (Table 2). As seen in Table 3, among the biomarkers examined, the level of global histone acetylation at the 24 h time point in patient PBMCs was found to be associated with the fold increase in ABCB1 in PBMCs at the 4 h time point.

Table 2.

Spearman correlation analysis of pharmacokinetic parameter values with selected biomarkers. Results provided include the Spearman correlation coefficient (ρ), the p-value for a test of whether r=0 (p), and the number of observations (n).

Cmax AUClast Clearance
Fold increase in AcH3 in PBMCs
  4h ρ 0.20 0.17 0.31
p 0.23 0.31 0.12
n 38 38 26
  24h ρ 0.37 0.36 − 0.44
p 0.030 0.033 0.028
n 35 35 25
  48h ρ 0.25 0.24 − 0.26
p 0.32 0.35 0.39
n 17 17 13
Fold increase in ABCB1 in PBMCs
  4h ρ −0.23 − 0.24 0.17
p 0.13 0.12 0.38
n 44 44 29
  24h ρ −0.025 − 0.067 0.19
p 0.87 0.67 0.32
n 43 43 29
  48h ρ −0.12 − 0.15 0.30
p 0.63 0.56 0.27
n 18 18 15
Fold increase in ABCB1 in biopsy samples
  ≈24h ρ 0.44 0.45 −0.51
p 0.048 0.040 0.041
n 21 21 16
Decrease in platelet count (Day 2 – Day 1)
ρ 0.051 0.035 −0.11
p 0.72 0.80 0.49
n 53 38 38
Cycle 1 platelet nadir
ρ −0.19 − 0.21 0.059
p 0.16 0.12 0.72
n 56 40 40
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Figure 5.

Figure 5

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Correlation of change in acetylated histone H3 (24h post treatment/baseline) in PBMCs with pharmacokinetic parameters. Fold change in acetylated histone H3 was plotted versus (A) Cmax, (B) AUClast and (C) clearance. Line depicts line of best fit, based on least-squares linear regression. Correlation coefficient (ρ) and significance (p) for each parameter were: (A) ρ = 0.37, p = 0.030; (B) ρ = 0.36, p = 0.033; (C) ρ = −0.44, p = 0.028.

Table 3.

Spearman correlation analysis of acetylated histone H3 values with other biomarkers. Results provided include the Spearman correlation coefficients (ρ), the p-value for a test of whether r=0, and the number of observations (n).

AcH3 4h* AcH3 24h AcH3 48h
Fold increase in ABCB1 in PBMCs
  4h ρ 0.26 0.42 0.28
P 0.13 0.020 0.33
N 35 30 14
  24h ρ − 0.13 − 0.20 0.19
P 0.50 0.28 0.49
N 31 31 16
  48h ρ − 0.26 −0.15 0.33
P 0.39 0.60 0.27
N 14 14 13
Fold increase in ABCB1 in biopsy samples
ρ − 0.26 − 0.24 0.070
P 0.32 0.35 0.83
N 16 17 12
Decrease in platelet count (Day 2 – Day 1)
ρ 0.18 0.072 − 0.068
P 0.27 0.67 0.79
N 39 37 18
Cycle 1 platelet nadir
ρ − 0.16 − 0.082 − 0.053
P 0.31 0.63 0.84
N 41 37 18
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*

Fold Increase in AcH3 in PBMCs

We next explored whether certain parameters would be associated with patients’ disease response, classified into categories: CR/PR and PD/SD. The parameters examined included global histone acetylation in patient PBMCs at the 4, 24 and 48 h time points; ABCB1 fold expression at the 4, 24 and 48 h time points; ABCB1 levels in the on-study biopsy; fold increase in ABCB1 levels in the pre versus post sample; fold increase in ABCB1 levels in the off-study value; and HbF fold change. Among these parameters, greater acetylated histone levels in PBMCs at the 24 h time point were associated with with complete and partial response (CR/PR: median: 3.77, range: 0.04–17.45 vs. SD/PD: median: 1.62, range: 0.67–6.71; p=0.026). Greater HbF fold change also appeared to be associated with clinical response (CR/PR: median 6.50, range 1.69–23.00 vs. SD/PD: median 3.70, range: 0.95–11.50; p=0.014); however, this may have been due to increased duration of time on study for patients with response. When each of these parameters was also evaluated across the four ordered response categories, instead of between the two pooled response categories, the results were similar although to a lesser degree at least in part because of loss in power associated with performing statistical tests with smaller number of subjects per group (p=0.10 for acetylated histone levels, and p=0.04 for HbF fold changes). Time on-study and time to peak value both were weakly to moderately correlated with HbF fold change (ρ = 0.36, p=0.02). The pharmacokinetic parameters Cmax, AUClast or clearance were not associated with response (p = 0.36, 0.44 and 0.78, respectively, for tests comparing non-responders to responders). The lack of association between pharmacokinetic parameters and response may be due to the fact that depsipeptide has been shown to be a prodrug, requiring reduction of a sulfhydryl group to activate HDAC inhibitory activity (Furumai, et al 2002).

DISCUSSION

This report summarizes the exploratory endpoints collected as part of a phase II trial with romidepsin in cutaneous and peripheral T-cell lymphoma, conducted as a multi-institutional trial. Molecular endpoints were a secondary aim of the study and were analyzed in an exploratory fashion. Four types of molecular endpoints were evaluated: histone acetylation in PBMCs; ABCB1 gene expression in PBMCs; ABCB1 gene expression in biopsy samples obtained from patients; and blood fetal hemoglobin levels (HbF). Other endpoints have been reported as potential markers of efficacy for HDIs including p21 induction in PBMCs (Gojo, et al 2007), increased nuclear staining of phospho-STAT-3 (Duvic, et al 2007) and plasma IL-6 levels (Gimsing, et al 2008). In addition, tumor gene profiling yielded several potential genes that could be used as biomarkers (Ellis, et al 2008). These have also confirmed the activity of HDIs at the level of the tumor. However, no single biomarker has emerged as a predictor of clinical response to HDIs.

Using an immuno-dot blot assay, an increase in global histone acetylation was noted in the majority of patients. At 4 hours, 73% of patients had evidence of at least a 2-fold increase in global histone acetylation in circulating PBMCs, which persisted at that level or higher at 24 hours in 43% of patients. We chose to perform dot blot analysis to provide a method that would allow simultaneous detection of histone acetylation in the linear range of the assay in multiple samples despite the fact that the dot blot assay is somewhat less sensitive than conventional western blot analysis. Comparable changes in global histone acetylation have been observed in clinical trials of other HDIs, including vorinostat (Garcia-Manero, et al 2008), PXD101 (Steele, et al 2005), CI-994 (Pauer, et al 2004), MS-275 (Gojo, et al 2007, Kummar, et al 2007), and valproic acid (Atmaca, et al 2007, Munster, et al 2007). Several different methods have been used in these studies, including immunoblot analysis and flow cytometry; similar to our findings, increases of 2- to 6-fold were reported (Byrd, et al 2005, Garcia-Manero, et al 2008, Kummar, et al 2007). However, in these studies, histone acetylation was not found to correlate with response, possibly due to different time point sampling or a smaller patient population. In the present study, increased global histone acetylation at 24 hours was not only somewhat correlated with pharmacokinetic parameters, but was also associated with response (p = 0.026) when the patients were separated by major response or non-response (including patients with disease progression or stable disease). Additionally, the positive, although not particularly strong, correlation of global acetylation of histone H3 with pharmacokinetic parameters Cmax and AUC (correlation coefficients of approximately 0.36 to 0.37), and the negative correlation with clearance at about the same level (ρ =−0.43) suggests that increased drug exposure results in increased levels of global histone acetylation. The fact that correlations of this magnitude are observed only in the 24-hour time-point may reflect the requirement for increased drug exposure or more frequent treatment to yield a more lasting effect. Our confidence in this finding is strong and is corroborated by the observation of this same result in an earlier analysis of a smaller cohort of patients, using a different method of autoradiography analysis (Piekarz, et al 2008).

Compared to the findings for histone acetylation in PBMCs, a somewhat reduced proportion of patients demonstrated increased ABCB1 expression in PBMCs, with 56% of patients having ABCB1 levels 2-fold or higher than the baseline at 4 hours and 37% of patients having ABCB1 levels 2-fold or higher than the baseline at 24 hours. These levels of induction were not found to be correlated with pharmacokinetic parameters. In cell line models, ABCB1 is induced to a much greater extent following romidepsin exposure compared to the increases observed here in the patient samples (Piekarz, et al 2004, Robey, et al 2006, Xiao, et al 2005, Yamada, et al 2006). It may be that constraints in the ABCB1 gene promoter are present in the normal circulating white blood cells that prevent a greater increase. If true, circulating Sézary cells could show a higher rate of gene expression change in response to HDAC inhibition. All three patients enrolled with Sézary syndrome (with circulating Sézary levels > 1000/ul) demonstrated increased ABCB1 expression — fold-increase values of 1.77, 7.17, and 3.36 following the first romidepsin dose. Rapid loss of Sézary cells followed exposure to romidepsin.

Using circulating fetal hemoglobin levels as another surrogate for the gene expression changes resulting from HDAC inhibition, 73% of patients had a > 2-fold rise in HbF levels and 60% had a > 4-fold rise. This increase is similar to that reported for other drugs that induce HbF such as butyrate or 5-azacytidine (Coleman and Inusa 2007). This occurred over time, with a median time to peak of 99 days – compatible with a RBC half-life of 120 days under normal circumstances and the fact that HbF expression may only be modulated in erythroid progenitors found in the bone marrow that then subsequently populate the circulation. This suggests that the effect of repeated HDAC inhibition on the normal erythroid progenitor cells as occurred on the day 1, 8, and 15 schedule was cumulative. The observed decline in hemoglobin F levels that follows the peak has not been explained and serial pharmacokinetic studies would need to be performed over time to ensure that romidepsin exposure is not decreasing due to increased elimination. It is possible that upregulation of ABCB1 expression in organs results in increased drug excretion. The failure of fetal hemoglobin induction to be correlated with the first-dose pharmacokinetic parameters is not surprising, given the long timeframe over which the hemoglobin F induction is observed. This timeframe may also be the explanation for the positive correlation between response and fold change in hemoglobin F levels. Patients with stable and progressive disease as best response were on-study a shorter time than patients with complete or partial response – and hence their peak values would be expected to be smaller. This possibility was supported by the weak to moderate correlation between time on study and fold change in hemoglobin F (ρ =0.36, p=0.02).

Although there was no association observed between ABCB1 induction in biopsy samples and disease response, it may be that the phenotypic changes that have been characterized in solid tumors following exposure to romidepsin and other HDIs, such as increases in markers of differentiation like ABCB1, are a result of gene expression effects that require long exposures in the in vivo setting. The mechanism underlying the exquisite sensitivity of T-cell lymphoma to romidepsin has not been determined. The HUT-78 CTCL cell line, when treated with romidepsin in the laboratory, undergoes an early onset of apoptosis, a finding that could indicate a direct rather than indirect effect occurring through gene expression change (Piekarz, et al 2004). Cell cycle arrest due to p21 induction cannot be demonstrated in vitro in the HUT-78 cells (Piekarz, et al 2004). This observation suggests that apoptosis occurs without the need for changes in gene expression. This conjecture, if true, could explain the lack of any association between induction of ABCB1 (as a surrogate for gene expression change) in biopsy samples and response.

Finally, we sought to determine whether P-glycoprotein (encoded by the ABCB1/ABCB1 gene) would emerge as a mechanism of drug resistance during disease progression or if it would be associated with response. Although we were able to show induction of ABCB1 gene expression in the biopsy samples obtained in the immediate post-romidepsin setting, as noted above, there was not a substantial increase in ABCB1 observed at the time off-study. Some increase in the median level was noted, from 2.07 units (relative to the level for SW620 cells arbitrarily assigned a value of 10 units) on-study to 3.17 units off study, a 50% increase in level. CTCL samples (n = 36), which comprise the majority of the patient population in whom biopsies were obtained (n = 42), show similar results at 1.91 and 2.76. Findings in the PTCL samples (n = 6) revealed somewhat higher median levels at baseline and at disease progression, 3.12 and 9.4, respectively. In fact, the highest levels seen on the study were observed in patients with PTCL. The highest level, 50.9, is comparable to that found in low-level, drug-selected cancer cell lines, which have demonstrable drug efflux and drug resistance (Herzog, et al 1992). Thus, while CTCL cells did not begin with or develop Pgp-mediated drug resistance in any overt way, the higher levels of pre-existing over-expression in PTCL could be important in determining outcome.

These studies show that three surrogate markers – global histone acetylation, ABCB1 expression in circulating mononuclear cells, and blood fetal hemoglobin levels – demonstrate increases following treatment of patients with romidepsin. A fourth marker, ABCB1 expression in tumor biopsy samples, also demonstrated transient low-level increases following drug exposure, particularly in CTCL samples. Two of the markers – global histone acetylation at 24 hours, and tumor biopsy ABCB1 expression – demonstrated weak to moderately strong correlations with pharmacokinetic parameters. Interestingly, histone H3 acetylation in PBMCs at the 24 h time point was associated with response. Taken together, these results support a hypothesis that peak drug concentration (Cmax) and overall exposure (AUC) to romidepsin are important in determining the likelihood that surrogate markers of romidepsin activity will be positive. These markers of romidepsin activity, in turn, may be indicative of increased likelihood of tumor response; however, these future clinical studies will be necessary to validate the ability of the markers to predict response. The requirement for activation of romidepsin through reduction of the disulfide bond (Furumai, et al 2002) may have special implications for acetylated histone H3 as a biomarker. Further analyses are needed to determine whether a threshold exists for romidepsin exposure that will increase likelihood of disease response, such as recently described for imatinib, where a trough plasma threshold of 1002 ng/ml was associated with response in patients with chronic myelogenous leukemia (Picard, et al 2007). If confirmed, such studies would support the need for a potent HDI such as romidepsin in T-cell lymphomas.

Supplementary Material

Supplementary Table 1
Supplementary Table 2

Table 4.

Comparison of acetylated histone H3 PBMC values between responders and non-responders (using Wilcoxon rank sum test).

Response CR/PR
n Mean Std Error Minimum Median Maximum p-value1
AcH3 4hr 12 4.197 0.676 1.550 3.325 8.780 0.22
AcH3 24h 9 5.052 1.721 0.037 3.770 17.450 0.026
AcH3 48h 6 5.647 2.775 0.220 2.815 17.640 0.58
Response PD/SD
N Mean Std Error Minimum Median Maximum
AcH3 4hr 25 3.768 0.752 0.440 2.980 17.300
AcH3 24h 23 1.991 0.335 0.670 1.620 6.710
AcH3 48h 11 2.234 0.584 0.280 1.530 5.960
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1

p-values shown are for the comparison of acetylated histone H3 PBMC values for CR/PR versus PD/SD.

ACKNOWLEDGEMENTS

We appreciate the contributions of Dr. Wilfried Stein, Susan Booher, Christiane da Silva and Julian Bahr to this work. We also extend our gratitude to the patients enrolled on the clinical trial.

This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract N01-CO-12400. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government.

This work was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research.

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Associated Data

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Supplementary Materials

Supplementary Table 1
NIHMS180087-supplement-Supplementary_Table_1.doc (60KB, doc)
Supplementary Table 2
NIHMS180087-supplement-Supplementary_Table_2.doc (57.5KB, doc)

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