HEXIM1 as a Robust Pharmacodynamic Marker for Monitoring Target Engagement of BET Family Bromodomain Inhibitors in Tumors and Surrogate Tissues

Reversible lysine acetylation has emerged as a central regulatory mechanism for chromosome remodeling, gene transcription, and other biological processes (1, 2). The bromodomain and extraterminal domain (BET) family of proteins (BRD2, BRD3, BRD4, and BRDT) interacts with acetylated histone tails through their bromodomains (3). Once bound to acetylated histones, BET family proteins activate transcription by recruiting the positive transcription elongation factor complex (pTEFb) that is essential for transcription elongation (4, 5). BET family proteins control diverse transcriptional programs that are important for cancer pathogenesis (6, 7). In particular, recent studies have shown that BRD4 is highly enriched in large clusters of enhancers that supercharge the expression of genes critical for cancer initiation and maintenance (8–10). The potential of targeting BET family proteins for cancer therapy has been substantiated using small-molecule inhibitors, such as JQ1, iBET, and OTX015 (11–13). Significant in vitro and in vivo activities of JQ1 and iBET have been reported in preclinical models of NUT midline carcinoma (NMC), acute myeloid leukemia (AML), multiple myeloma, acute lymphoblastic leukemia, non-Hodgkin lymphoma (NHL), non–small cell lung carcinoma (NSCLC), glioblastoma, small-cell lung carcinoma, breast cancer, neuroblastoma, pancreatic cancer, and prostate cancer (11, 14–31). Clinical responses to OTX015 have been observed in AML, NHL, multiple myeloma, and NMC patients (32–34). Thrombocytopenia and gastrointestinal events have presented as dose-limiting toxicities of OTX015, and clinical responses to OTX015 are often short lived at the recommended therapeutic dose, which raises the question on whether BET proteins are sufficiently inhibited at the recommended therapeutic dose before and at relapse (33, 34). It has been reported that initial attempts to address this question using literature-described putative pharmacodynamic markers, such as c-Myc, Bcl-2, CCND1, NF-κB, BRD2, BRD3, and BRD4, in bone marrow cells at baseline and after 1 week of treatment failed to detect any pharmacodynamic marker modulation in AML patients treated at active dose and those with clinical responses (33). Therefore, a more careful analysis of well-characterized pharmacodynamic markers will likely be required to better understand the efficacy and tolerability implications of targeting BET family proteins in the clinical setting. ABBV-075 is a potent and selective BET inhibitor that is under phase I clinical investigation (ClinicalTrials.gov identifier: NCT02391480). It binds to protein constructs containing both bromodomains of BRD2, BRD4, or BRDT with similar affinities (K_i of 1–2.2 nmol/L) but exhibits roughly 10-fold weaker potency toward the tandem bromodomain construct of BRD3 (12.2 nmol/L). Extensive in vitro and in vivo characterization of ABBV-075 demonstrated broad activity across cancer cell lines and xenograft tumors (35). Herein, we report the identification and characterization of HEXIM1 as a robust pharmacodynamic marker for monitoring target engagement of ABBV-075 and other BET inhibitors in tumors and surrogate tissues.

All compounds were synthesized at AbbVie. Binding affinities of BET inhibitors to BRD4 were determined by a time-resolved fluorescence resonance energy transfer (TR-FRET) assay using florescent-conjugated MS417 as a probe and protein constructs containing both bromodomains of BRD4.

All cancer cell lines were obtained from commercial sources, such as ATCC and DSMZ, between 2010 and 2012 and maintained by a core cell line facility that performed routine mycoplasma testing and STR authentication analysis using the Gene Print10 Kit (Promega). NSCLC cell lines NCI-H1299, NCI-H460, and NCI-H1975, colorectal cancer cell lines DLD-1 and GEO, multiple myeloma cell line OPM-2, AML cell line MV4:11, and NHL cell line Ramos were cultured in RPMI1640 supplemented with 10% FBS (Invitrogen). Breast cancer cell lines MDA-MB-231 and MX-1 and pancreatic cancer cell lines MiaPaCa-2 and HPAC were cultured in DMEM supplemented with 10% FBS. Prostate cancer cell line PC-3M was cultured in F-12K supplemented with 10% FBS. All cell lines were cultured in a humidified incubator at 37°C containing 5% CO₂. Freshly isolated human peripheral blood mononuclear cells (PBMC) were obtained from Bioreclamation and plated in 96-well tissue culture plates in RPMI1640/10% FBS (Invitrogen) for compound treatment. For proliferation assays, cells were incubated with different concentrations of BET inhibitors in 96-well tissue culture plates for 3 days, followed by viability determination using the CellTiter-Glo assay according to the manufacturer's recommendations (Promega). The percentage inhibition of luciferase signal was normalized to control cells treated with DMSO, and IC₅₀s were calculated by nonlinear regression analysis using GraphPad PRISM software.

NCI-H1299 and MiaPaCa-2 were plated at 5 × 10⁵ per well in 6-well tissue culture plates overnight prior to compound treatment with vehicle (DMSO), MS417 (0.5 μmol/L), or C1 (10 μmol/L) for either 3 or 6 hours. Total RNA was extracted using the Qiazol lysis reagent and the RNeasy 96 Universal Tissue Kit (Qiagen). RNA purity and integrity were examined using the Agilent Bioanalyzer 2100. Microarray target preparation and hybridization were carried out using the purified RNA samples per Affymetrix protocols. The whole genomic expression profile was determined using the Affymetrix HumanGenome U133A 2.0 array with three biological replicates. Microarray data were then normalized and analyzed for fold change and P value using Rosetta Resolver software. Pathway analysis was performed using the Database for Annotation Visualization and Integrated Discovery (DAVID) software. The gene expression array data can be found at the Gene Expression Omnibus under accession numbers GSE89932, GSE89933, GSE89934, and GSE89935.

The QuantiGene Plex Assay was performed according to the manufacturer's protocol (Affymetrix). Briefly, cells, whole blood, or homogenized tumor or skin tissues were lysed in the corresponding lysis buffer recommended by Affemetrix. Lysed samples were then incubated overnight with the probe sets for genes of interest or housekeeping genes (B2M and HPRT1) and processed for signal amplification and detection according to the manufacturer's protocol. The final signal was captured using the Luminex FlexMAP 3D instrument (Luminex), and data were presented as mean fluorescent intensity (MFI). The MFI of genes of interest in each sample was first normalized to MFI of housekeeping genes and then normalized to control samples (DMSO or vehicle) to determine the fold or ratio of expression change. For dose–response experiments, the EC₅₀s were calculated by nonlinear regression analysis using GraphPad PRISM software.

RNA in situ hybridization (ISH) assay was performed using the RNAscope probes and reagents, according to the manufacturer's protocol (Advanced Cell Diagnostics). Briefly, formalin-fixed paraffin-embedded (FFPE) tissue sections (5-μm thick) were mounted on positively charged microscopic glass slides (Fisherbrand Superfrost Plus; Fisher Scientific). All steps of RNAscope staining of the slides were performed on a Leica automation system using custom software (Leica Microsystems Inc.).

All animal studies were conducted in a specific pathogen-free environment in accordance with the Internal Institutional Animal Care and Use Committee, accredited by the American Association of Laboratory Animal Care under conditions that meet or exceed the standards set by the United States Department of Agriculture Animal Welfare Act, Public Health Service Policy on Humane Care and Use of Animals, and the NIH guide on laboratory animal welfare. Overt signs of dehydration, lack of grooming, lethargy, >15% weight loss as well as tumor volume >20% of body weight were used to determine the tumor endpoint. For tumor models, a 1:1 mixture of 5 × 10⁶ cells/Matrigel (BD Biosciences) per site or 1:10 tumor brie [MX-1; in S-MEM (MEM, suspension, no calcium, no glutamine); Life Technologies Corporation] was inoculated subcutaneously into the right hind flank of female SCID/beige or female Fox Chase SCID (Charles River Laboratories) mice, respectively. Tumors were allowed to reach approximately 250 mm³, and mice were size-matched into treatment groups (n = 10 in each group). All BET inhibitors used in the current experiments were administered by oral gavage once daily.

Plasma or homogenized tumor tissue aliquots (25 μL) were combined with 25 μL of internal standard (dexamethasone, prepared in acetonitrile) and 250 μL acetonitrile in a 96-well polypropylene deep-well plate. The plates were vortexed for 30 seconds followed by centrifugation (3,500 rpm for 15 minutes, 4°C). Supernatant (100 μL) was transferred to a clean 96-well plate and diluted with 200 μL 0.1% formic acid in water. The plates were centrifuged (3,500 rpm for 15 minutes, 4°C) prior to HPLC/MS-MS analysis. Analysis was performed on a Sciex API5500 Biomolecular Mass Analyzer with a TurboIonSpray interface. Analytes were ionized in the positive ion mode. Detection was in the multiple reaction monitoring mode at m/z 460.3 → 254.1 for ABBV-075 and m/z 393.2 → 147.1 for the internal standard, dexamethasone. ABBV-075 and internal standard peak areas were determined using Sciex Analyst software.

Considering the critical involvement of BET family proteins in transcriptional regulation, we reasoned that genes whose transcription is controlled by BET family proteins could serve as mechanism-based pharmacodynamic markers for BET inhibitors. Toward this end, global gene expression profiling studies were carried out in NCI-H1299 and MiaPaCa-2 cells using a JQ1-like BET family inhibitor MS417 (36) and its inactive analogue (Supplementary Fig. S1). To minimize potential complications of second or tertiary transcriptional responses to BET inhibitors, we determined gene expression changes at the relatively early time points of 3 and 6 hours after compound treatment. The inactive compound (C1, K_i > 10 μmol/L) exerted minimal impact on gene expression compared with DMSO-treated cells. In contrast, the active BET inhibitor (MS417, K_i = 0.0235 μmol/L) caused significant up- or downregulation of many genes, with more genes affected at the 6-hour than the 3-hour time point (Fig. 1A; Supplementary Table S1). DAVID pathway analysis of 290 genes that were modulated by MS417 in both NCI-H1299 and MiaPaCa-2 cells revealed an enrichment of genes involved in transcriptional regulation and apoptosis (Supplementary Table S2). It is noteworthy that c-Myc, a well-publicized target of BET inhibitors, was not significantly regulated in NCI-H1299 or MiaPaCa-2 cells (Supplementary Table S1).

To confirm and expand on findings obtained from global expression profiling, we excluded genes with very low levels of expression from the 290 genes that were commonly regulated in NCI-H1299 and MiaPaCa-2 cells and then selected 25 genes that exhibited the largest fold changes for further study using the QuantiGene Plex Assay. We put more emphasis on upregulated genes in our selection because increase of gene expression can potentially be detected more reliably. The modulation of the majority of these 25 genes by MS417 treatment recapitulated what was observed in the profiling studies, with more substantial expression changes observed at the higher dose of MS417 (Fig. 1B; Supplementary Table S3). However, the expression of all histone variants did not increase in response to MS417, and several genes, such as RIN2, HDAC9, and AURKA, were undetectable in one or two cell lines. On the basis of both the magnitude and consistency of responses across these cell lines, we narrowed our selection to 13 of the 25 genes for characterization across 10 additional cancer cell lines. Given that the response of c-Myc to BET inhibitors was primarily reported in hematologic cancer settings, we suspected that c-Myc might be a hematologic cancer-specific marker that was not modulated in our profiling studies using cell lines originating from solid tumors. Therefore, we also included c-Myc for further characterization. Among the 14 genes examined, the expression of HEXIM1, SERP1NI1, ZCCHC24, and ZMYND8 exhibited the most consistent responses to MS417 across cancer cell lines, whereas c-Myc was significantly downregulated in only the two hematologic cell lines OPM-2 and MV4:11 (Table 1). On the basis of these results, we selected ZCCHC24, HEXIM1, SERP1NI1, ZMYND8, and c-Myc as potential pharmacodynamic markers to monitor the activities of BET inhibitors in tumors.

A series of in vitro experiments was executed to understand the concentration- and time-dependent responses of these pharmacodynamic markers to BET inhibitors. Dose–response studies using ABBV-075, a structurally distinctive BET inhibitor (Supplementary Fig. S1), and MS417 were conducted in OPM-2 cells. Both MS417 and ABBV-075 caused dose-dependent up- or downregulation of HEXIM1, c-Myc, SERP1NI1, ZCCHC24, and ZMYND8 (Fig. 2A). ABBV-075 exhibited lower EC₅₀s than MS417 in modulating these genes, which was consistent with its better biochemical potency than MS417 (K_i = 0.0015 μmol/L for ABBV-075 vs. K_i = 0.024 μmol/L for MS417 in TR-FRET assay against BRD4). More importantly, the EC₅₀s of ABBV-075 or MS417 on transcription modulation of these genes were largely consistent with the antiproliferative EC₅₀s of these compounds (Supplementary Table S4), suggesting that the responses of these potential pharmacodynamic markers can properly reflect the degree of inhibition on BET family proteins that is required to produce functional outcomes.

OPM-2 and MiaPaCa cells exhibited robust apoptosis upon exposing to BET inhibitors for 24 hours or more. To avoid complications for data interpretation, we first examined the temporal responses of pharmacodynamic markers in NCI-H1299 cells, a cell line where BET inhibitors induce significant growth inhibition without overt cell death. NCI-H1299 cells were treated with MS417 for different durations or at different time points after compound removal, and the expression of various markers was determined. Similar degrees of transcriptional modulation were observed in NCI-H1299 cells exposed to MS417 for 6 to 48 hours (Fig. 2B). Compound washout resulted in the rapid loss of transcriptional changes induced by MS417, and the expression of many of these markers reverted to the basal level 6 hours after compound removal (Fig. 2C). The responses of these markers were also rapidly reversed in cells exposed to MS417 for 72 hours before compound washout, suggesting that chronic compound exposure is unlikely to alter the temporal response of these markers to BET inhibitors (Fig. 2D). The rapid reversal of marker responses were also observed in OPM-2 cells upon compound washout after 16 hours of ABBV-075 or MS417 treatment (Supplementary Fig. S2). These results collectively suggest that the expression changes of HEXIM1, ZCCHC24, SERPINI1, ZMYND8, and c-Myc faithfully denote the activities of BET inhibitors in cancer cells.

Extensive in vivo studies were carried out to evaluate the performance of these pharmacodynamic markers in xenograft tumors. Because NCI-H1299 is not a robust in vivo model, we first examined the pharmacodynamic marker response using the OPM-2 flank tumor model. Increasing amounts of ABBV-075 were administered to mice bearing OPM-2 tumors, and both tumor and plasma samples were collected 6 hours after a single administration of ABBV-075 at various dose levels. Dose-dependent modulation of ZCCHC24, HEXIM1, SERP1N1, and c-Myc, but not ZMYND8, was observed in OPM-2 tumors (Fig. 3A). Responses of these genes in the tumor were closely correlated with the tumor concentration of ABBV-075 at each dose level (Fig. 3B; and data not shown). Time course studies further revealed that the pharmacodynamic responses peaked at 4 to 8 hours after a single administration of ABBV-075 and subsequently returned to baseline at 24 hours. This profile of time-dependent pharmacodynamic responses closely mimicked the tumor concentration of ABBV-075 at each time point (Fig. 3C and D). The pharmacodynamic responses were largely correlated with antitumor efficacy results in the OPM-2 model. For example, 0.3 mg/kg/d (mkd) of ABBV-075 induced only a moderate pharmacodynamic response in the tumor and a similar dose of 0.25 mkd did not significantly impact tumor growth. In contrast, the 1 mkd dose induced robust pharmacodynamic responses in the tumor and also produced significant antitumor efficacy in the OPM-2 tumor model (Supplementary Fig. S3). Studies using four different BET inhibitors (MS417, C2, C3, and C4; Supplementary Fig. S1) and four more tumor models further confirmed the responses of HEXIM1, SERP1N1, ZCCHC24, and ZMYND8 to BET inhibitors across tumor models (Fig. 3E–H). Similar responses of these markers to multiple structurally distinct BET inhibitors and in multiple tumor models suggesting what was observed in the OPM-2 model using ABBV-075 likely reflects common pharmacodynamic responses that are resulted from the inhibition of BET family proteins rather than from unexpected off-target activities of a specific compound. Similar to what was observed in the cell line panel, c-Myc exhibited significant response to BET inhibitors in the lymphoma model Ramos but not in solid tumor models HPAC and MX1 (c-Myc was not tested in MiaPaCa-2 tumors).

Considering potential difficulties of obtaining postdose tumor biopsy samples in clinical trials, it is highly desirable to have pharmacodynamic markers that allow monitoring of target engagement in accessible surrogate tissues, such as blood and skin. To identify genes that are modulated by BET inhibitors in blood, we determined global gene expression changes in ABBV-075–treated human PBMCs and in whole blood samples from mice treated with ABBV-075. A 28-gene panel, which primarily consisted of the best responding genes in human PBMCs with the addition of a few genes that exhibited robust responses in mouse whole blood, was then selected for further confirmation. Follow-up studies using ABBV-075–treated human PBMCs and mouse blood from C5-treated mice (Supplementary Fig. S1) revealed that HEXIM1, CIRBP, BCL2L11, and POLR2A responded to BET inhibitors in both human PBMCs and mouse blood (Supplementary Table S5). Confirmatory studies using whole blood samples from ABBV-075–treated mice revealed that Hexim1 exhibited the best response among the 4 genes (Fig. 4A). Administration of increasing amounts of ABBV-075 in mice resulted in increasingly higher levels of Hexim1 in mouse whole blood, and the increases of Hexim1 to different doses of ABBV-075 were highly correlated with the plasma concentrations of ABBV-075 (Fig. 4B and C). Similar to what was observed in tumors, Hexim1 upregulation peaked at 4 hours after a single administration of ABBV-075 and then returned to baseline at 24 hours, which is largely consistent with the plasma concentrations of ABBV-075 at various time points (Fig. 4D and E).

Skin is another commonly used surrogate tissue in cancer drug development in addition to blood. Compared with pharmacodynamic markers in the blood compartment, pharmacodynamic markers in skin are perceived to provide a better assessment of compound availability and activity in tumors. To identify potential pharmacodynamic markers for BET inhibitors in skin, we determined transcriptional alterations in skin samples from ABBV-075–treated mice. From the global expression profiling results, we selected 9 genes (Atp1b1, Fastk, Hexim1, Lrg1, Serpinf1, Ubc, Panx3, Tfec, and Trim12c) for confirmation studies, based on criteria such as the magnitude of response, baseline expression level, and the response in blood and/or tumor expression profiling studies. Among these, Panx3, Tfec, and Trim12c produced very low signal using the QuantiGene Plex Assay despite the observation that these genes appeared to express at moderate levels based on the Affymatrix microarray platform. Hexim1 and Lrg1 were significantly up- or downregulated, respectively, in skin samples from ABBV-075–treated mice (Supplementary Fig. S4). Similar to what was observed in tumor and blood, Hexim1 was upregulated by ABBV-075 at 6 hours and returned to baseline at 24 hours (Fig. 5A).

Although it is possible to obtain snap-frozen skin samples from clinical trials for expression analysis, FFPE samples are much easier to handle at the clinical site and more commonly available. Therefore, we investigated the feasibility of analyzing the response of HEXIM1 to ABBV-075 in skin FFPE samples. Mouse skin samples from vehicle or ABBV-075–treated mice were processed using the standard FFPE protocol, and total RNAs were then extracted from the FFPE skin samples for expression analysis using the QuantiGene Plex Assay. ABBV-075 treatment caused significant upregulation of Hexim1 but not the housekeeping genes B2m and Hprt1 in these FFPE samples (Fig. 5B). The response of Hexim1 to ABBV-075 in FFPE skin samples was further verified using the RNA ISH method. As shown in Fig. 5C, ABBV-075 treatment resulted in a significant increase of Hexim1 expression in the skin section. Taken together, these results indicate that HEXIM1 can serve as a reliable marker to monitor the activities of BET inhibitors, such as ABBV-075, in skin using both frozen and FFPE samples and multiple assay platforms.

Pharmacodynamic markers that allow monitoring target engagement or pathway modulation in tumor or surrogate tissues are highly valuable for cancer drug development (37, 38). Pharmacodynamic marker analysis in early-stage clinical trials can provide information on potential efficacy and toxicity associated with the pharmacological modulation of a given target and informs early clinical decisions on the development program. An increasing number of BET family protein inhibitors have recently entered clinical trials, and incorporating well-characterized pharmacodynamic markers could potentially increase the probability of success for these development programs. Here, we described the identification and characterization of potential pharmacodynamic markers for monitoring the target engagement of ABBV-075 in tumors and surrogate tissues such as whole blood and skin.

The main challenge of identifying robust BET inhibitor–responsive markers is the diversity of transcriptional programs regulated by BET inhibitors across cancer cell lines and surrogate tissues. Cross-comparison of genes that exhibited robust responses to BET inhibitors in different cancer cell lines, human PBMCs, mouse whole blood, and mouse skin revealed very limited overlap between these datasets. For example, c-Myc, one of the best characterized targets of BET inhibitors in the literature, exhibited enormous disparity in responses across cancer cell lines and surrogate tissues. Although its expression was decreased in many hematologic cancer cell lines, c-Myc was not significantly modulated by MS417 or ABBV-075 in many solid tumor cell lines, PBMCs, or mouse skin samples. Similarly, RIN2 is significantly downregulated by BET inhibitors in solid tumor cell lines but expressed at very low levels in hematologic malignancies, making it a less ideal biomarker. In addition, genes such as FGFR3 exhibited exceptionally strong responses to BET inhibitors in NCI-H1299 cells, but not in other cell lines examined. To complicate matters further, transcription programs regulated by BET proteins may sometimes occur only in a defined cell population within certain tissues, which makes it difficult to detect the response of these markers to BET inhibitors using homogenized tissue samples. For example, genes such as SERPINI1 and SAT1 exhibited strong responses to BET inhibitors in defined cell populations, such as PBMCs and keratinocytes, but failed to respond to BET inhibitors when complex samples, such as whole blood and mouse skin, were analyzed (data not shown). Therefore, to avoid logistic complexities of using different pharmacodynamic markers for different cancer indications or surrogate tissues, the ideal pharmacodynamic markers for BET inhibitors should respond consistently across tissues/tumor indications/cell types.

Our results demonstrated that HEXIM1 exhibited the most consistent response to BET inhibitors in all of the settings examined, including tumors and surrogate tissues. HEXIM1 is part of the 7SK small nuclear ribonucleoprotein that sequesters pTEFb in an inactive conformation (39, 40). It has been shown that BET inhibitors, such as JQ1, release pTEFb from the 7SK snRNP complex, and the free pTEFb activates the transcription of pTEFb-dependent genes, including HEXIM1 (41). Furthermore, it has been shown that in some cancer cell lines, upregulation of HEXIM1 by BET inhibitors is required for cell death following the treatment of BET inhibitors (42). This mechanistic understanding and the remarkable consistency of HEXIM1 upregulation by BET inhibitors across many settings indicate that HEXIM1 could be a valuable mechanism-based proximal marker for monitoring target engagement of BET inhibitors. In addition, markers such as SERPINI1, ZCCHC24, and ZMYND8 may be used to monitor target engagement of BET inhibitors in tumor biopsies along with HEXIM1. In our hands, significant responses of c-Myc to BET inhibitors are largely restricted in hematologic cancer cell lines; therefore, c-Myc may be used as a pharmacodynamic marker for some hematologic cancer indications. HEXIM1 and the tumor pharmacodynamic markers described here are currently being investigated in the clinical trials of ABBV-075 (ClinicalTrials.gov identifier: NTC02391480).

K. McDaniel has ownership interest (including patents) in AbbVie. No potential conflicts of interest were disclosed by the other authors.

Conception and design: X. Lin, X. Huang, D.H. Albert, K.F. McDaniel, Y. Shen

Development of methodology: X. Lin, X. Huang, T. Uziel

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): X. Lin, X. Huang, T. Uziel, P. Hessler, D.H. Albert, L.A. Roberts-Rapp

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): X. Lin, X. Huang, T. Uziel, P. Hessler, L.A. Roberts-Rapp, Y. Shen

Writing, review, and/or revision of the manuscript: X. Lin, X. Huang, T. Uziel, D.H. Albert, L.A. Roberts-Rapp, K.F. McDaniel, W.M. Kati, Y. Shen

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): X. Lin, X. Huang, L.A. Roberts-Rapp

Study supervision: X. Lin, D.H. Albert, Y. Shen

The authors thank Ziping Yang and Lloyd Lam for supporting confirmation studies for ABBV-075 skin pharmacodynamic markers.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.