[3H]Adenine is a suitable radioligand for the labeling of G protein-coupled adenine receptors but shows high affinity to bacterial contaminations in buffer solutions

[3H]Adenine has previously been used to label the newly discovered G protein-coupled murine adenine receptors. Recent reports have questioned the suitability of [3H]adenine for adenine receptor binding studies because of curious results, e.g. high specific binding even in the absence of mammalian protein. In this study, we showed that specific [3H]adenine binding to various mammalian membrane preparations increased linearly with protein concentration. Furthermore, we found that Tris-buffer solutions typically used for radioligand binding studies (50 mM, pH 7.4) that have not been freshly prepared but stored at 4°C for some time may contain bacterial contaminations that exhibit high affinity binding for [3H]adenine. Specific binding is abolished by heating the contaminated buffer or filtering it through 0.2-μm filters. Three different, aerobic, gram-negative bacteria were isolated from a contaminated buffer solution and identified as Achromobacter xylosoxidans, A. denitrificans, and Acinetobacter lwoffii. A. xylosoxidans, a common bacterium that can cause nosocomial infections, showed a particularly high affinity for [3H]adenine in the low nanomolar range. Structure–activity relationships revealed that hypoxanthine also bound with high affinity to A. xylosoxidans, whereas other nucleobases (uracil, xanthine) and nucleosides (adenosine, uridine) did not. The nature of the labeled site in bacteria is not known, but preliminary results indicate that it may be a high-affinity purine transporter. We conclude that [3H]adenine is a well-suitable radioligand for adenine receptor binding studies but that bacterial contamination of the employed buffer solutions must be avoided.
Introduction
Purinergic receptors play an important role in transmembrane signaling [1]. Currently, two distinct families are officially recognized by the International Union of Pharmacology (IUPHAR), i.e. receptors for the purine nucleoside adenosine (P1 or adenosine receptors) and receptors for purine and/or pyrimidine nucleotides (P2 receptors) [2–4]. Whereas the P1 receptor family comprises four subtypes, A1, A2A, A2B, and A3, all of which are G protein-coupled receptors (GPCRs), the P2 family is further subdivided into two subfamilies, P2Y (GPCRs) and P2X (ligand-gated ion channels) [2–4]. In addition to the nucleoside (adenosine) and nucleotide receptors, a receptor for the nucleobase adenine has recently been discovered by a reverse pharmacological approach identifying adenine as the natural ligand for a rat orphan GPCR [5]. A mouse orthologue (mMrgA10) of the rat adenine receptor was subsequently identified by sequence comparison [5]. Very recently, a new adenine receptor has been cloned from mice showing 82% identity in its amino acid sequence to mMrgA10 and 76% to the rat adenine receptor, indicating that the new receptor is a distinct adenine receptor subtype (Genbank nucleotide sequence accession numbers: new mouse adenine receptor, DQ386867; mMrgA10, XM_195647; rat adenine receptor, AJ311952) [6, submitted]. Both adenine receptors that have been pharmacologically characterized are coupled to the inhibition of adenylate cyclase by Gi protein [5, 6]. So far, no human receptor for adenine has been identified, although initial clues for the possible existence of human adenine receptors have been found [7]. Adenine receptors are structurally unrelated to P1 and P2 receptors and therefore constitute a new family of purinergic receptors for which we proposed the designation P0 (“P zero”) receptors [8] based on the structural relationships of the physiological agonists, adenine (P0) representing a partial structure of adenosine (P1) and adenosine again being a partial structure of adenine nucleotides (P2), such as adenosine triphosphate (ATP) or adenosine diphosphate (ADP).
Radioligand binding studies are widely used to characterize GPCRs on the protein level [9]. Adenine, the natural ligand of adenine receptors, is commercially available in tritium-labeled form ([3H]adenine) and has been used to characterize recombinant rat adenine receptors expressed in Chinese hamster ovary (CHO) cells [5] as well as natively expressed rat adenine receptors in rat brain [7, 10] using membrane preparations. The radioligand has been shown to be stable under the incubation conditions [10]. Furthermore, mouse adenine receptors natively expressed in NG108-15 (neuroblastoma × glioma hybrid) cell membranes were labeled by [3H]adenine [7]. Recently, we successfully applied [3H]adenine binding to detect the mouse adenine receptor protein recombinantly expressed in Sf21 insect cell membranes, which constitute a null background because they do not endogenously express any high affinity binding site for adenine [6].
Two recent poster presentations reported on problems with [3H]adenine binding to adenine receptors. In one study using whole rat brain membrane preparations, a high-affinity binding site was detected (apparent Ki 57.5 nM) [11]. However, a very high Bmax value was found (281 pmol/mg protein), and the binding was almost completely blocked by 10 μM of hypoxanthine and abolished in the absence of Mg2+, indicating that the detected binding site was not identical with the G protein-coupled rat adenine receptor [11]. In another study, high affinity binding of [3H]adenine was detected even in the absence of added protein, and the authors suggested that [3H]adenine bound in a highly specific manner to the glass fiber filters used in the filtration assays [12]. IC50 values were determined for five adenine derivatives and three compounds [adenine (18 nM [12]; rat: 29.9 nM [7], 18 nM [5]), 7-ethyladenine (30 μM [12]; rat: 47.3 μM [7]), 8-bromoadenine (14 μM [12]; rat: 17.3 μM [7]] showed similar IC50 values as those previously determined for the rat adenine receptor, but two compounds [5′-deoxyadenosine (725 μM [12]; rat: 0.823 μM [10]), 2-fluoroadenosine (19 μM [12]; rat: 0.62 μM [7]] had much lower affinities for the unknown binding site labeled in the absence of added protein [12] than for the rat adenine receptor as previously determined [7, 10], indicating that the unknown binding sites labeled in the absence of added rat tissue were very different. Based on their results, the IJzerman group had suggested to avoid the use of [3H]adenine as a radiolabeled probe for the adenine receptor due to its putative specific, high-affinity binding to glass fiber filters [12].
That report prompted us to carefully reanalyze radioligand binding data obtained with [3H]adenine in our laboratory with the goal to find out the reason for the problems encountered in other laboratories. As a matter of fact, we had occasionally observed unusually high counts in a few experiments, which could, however, be avoided by repeating the experiments under carefully controlled experimental conditions, including the use of freshly prepared buffer solutions. We have now performed a systematic study clearly showing that [3H]adenine is a suitable radioligand for the labeling of adenine receptors in various cells and tissues if bacterial contaminations are excluded. Furthermore, we identified three common gram-negative aerobic bacteria that grow in cold Tris buffer and express high-affinity binding sites for [3H]adenine.
Materials and methods
Chemicals
[8-3H]Adenine (27 Ci/mmol) was obtained from Amersham Biosciences (Munich, Germany). Tris was obtained from Acros Organics (Leverkusen, Germany) and dimethyl sulfoxide (DMSO) was from Fluka (Switzerland). All other chemicals and reagents were obtained from Sigma unless otherwise noted.
Cell culture
Human embryonic kidney (HEK) 293 and CHO-K1 cells were grown as monolayers at 37°C (5% CO2) in Dulbecco’s modified Eagle medium (DMEM) containing 10% fetal calf serum, 100 U/ml penicillin, 100 μg/ml streptomycin, and 2 mM L-glutamine.
Membrane preparations
Frozen rat brains were obtained from Pel Freez (Rogers, AR, USA) and thawed at 4°C. Cortex and striata were dissected, and membrane fractions were prepared as previously described [7]. Membrane preparations from CHO-K1 cells, and HEK293 cells were prepared as described [13, 14]. Membrane preparations from bacteria were obtained after growing them on agar plates and subsequent amplification of single strains in Lennox broth (LB) medium over night. Membranes were then prepared in analogy to the procedures used for mammalian-cell membranes [7, 13]. Protein concentrations were determined according to the method of Lowry [15].
[3H]Adenine binding assays
Adenine binding assays were carried out as previously described [7]; however, in the absence of Mg2+ and ethyleneglycoltetraacetic acid (EGTA), unless otherwise noted, as Mg2+ and EGTA were found to have no effect on determined Ki values (data not shown). In brief, membrane preparations (50 μg of protein, unless otherwise indicated) were incubated with 10 nM [3H]adenine in 50 mM Tris-HCl, pH 7.4 in a total volume of 200 μl. Inhibition curves were determined using six to nine different concentrations of adenine, spanning three orders of magnitude. Three separate experiments were performed, each in triplicate, unless otherwise noted. Nonspecific binding was determined in the presence of 100 μM unlabeled adenine. Incubations were carried out for 1 h at room temperature and terminated by rapid filtration through GF/B glass fiber filters (Whatman, Dassel, Germany). Filters were washed three times, 2 ml each, with freshly prepared ice-cold 50 mM Tris-HCl buffer, pH 7.4 and immediately transferred to mini vials. Scintillation cocktail (Ultima Gold, Canberra Packard, 2.5 ml) was added and after an incubation of 9 h filter-bound radioactivity was measured by liquid scintillation counting at an efficiency of 54%. In some experiments, the addition of mammalian protein was omitted and replaced by 100 μl of different buffer samples. For competition experiments with bacteria, either 100 μl of 1:100 or 1:1000 dilution of an overnight culture of the bacteria in Tris buffer, 50 mM, pH 7.4, or a membrane preparation of bacteria (containing 0.4–10 μg of protein) was used.
After isolation and classification of the bacteria from contaminated buffer solutions, experiments were performed with intact bacteria (approximately 6 × 104 bacteria/sample, which roughly equals 0.5 μg of total protein/sample), unless otherwise indicated, using the standard procedure (see above). The cell number was estimated from the optical density (OD) of the overnight culture suspension, and the assumption that  [16].
Data analysis
Data were analyzed using Prism 4.03 (Graph Pad, San Diego, CA, USA). IC50 values were determined by fitting data to sigmoidal concentration-inhibition curves. Results are presented as means ± standard error of the mean (SEM) from the number of observations.
Isolation of microorganisms from contaminated buffer solutions and classification
Microorganisms were isolated from Tris-HCl buffer, pH 7.4, by plating 300 μl of the buffer on LB agar plates. Single colonies were isolated and incubated overnight in LB medium at 37°C with constant shaking at 230 rpm. Further separation was achieved by plating bacteria from overnight cultures on plate count (Merck, Darmstadt) and blood agar (Oxoid, Wesel). Morphology of colonies was visually examined. Conventional physiological and biochemical characterization assays, including gram staining, catalase and oxidase activity, motility, and oxidation/fermentation (O/F) test were carried out and analyzed according to  Bergey’s Manual of Systematic Bacteriology using reagents from Merck (Darmstadt) [17]. In addition, the following kits and appliances were used: BBL OXI/FERM Tube II (Schwarz Pharma GmbH, Germany), API 20 NE strips and apiweb software (Biomerieux, Nürtingen, Germany), and VITEK 2 fully automated system (Biomerieux, Nürtingen, Germany).
Results
Protein dependence of [3H]adenine binding
As a first step, we reevaluated (unpublished) data obtained in initial studies that had been performed to investigate the suitability of [3H]adenine as a radioligand for labeling adenine receptors. Figure 1 shows [3H]adenine binding to different membrane preparations from (a) rat brain striatum, (b) rat brain cortex, and (c) HEK293 cells and CHO-K1 cells. For each membrane preparation, different amounts of protein were investigated (25, 50, 100, and 200 μg for striatum; 0, 25, 50, 100, and 200 μg for cortex; 50 and 100 μg for HEK and CHO cells). In all cases, we found a large, approximately linear, increase in specific binding with increasing protein concentration, whereas the increase in nonspecific binding was small. No specific binding was detected in the absence of protein (see Fig. 1b).
Fig. 1Protein dependence of [3H]adenine binding to adenine receptors in rat brain striatal membranes (a), in rat brain cortical membranes (b), and in human embryonic kidney (HEK293) cell membranes and in Chinese hamster ovary cell (CHO) membranes (c). Different amounts of protein were incubated for 60 min with 10 nM of [3H]adenine in Tris-HCl buffer, pH 7.4 (n = 3). Nonspecific binding was determined in the presence of 100 μM adenine
Microbial contaminations in buffer solutions
As a next step, we investigated whether microbial contaminations present in incubation buffers that were not freshly prepared might be responsible for high counts occasionally observed in [3H]adenine binding studies in our laboratory. We performed a systematic analysis of buffer solutions (50 mM Tris-HCl, pH 7.4) stored at different conditions (different periods of time and temperatures), in different containers (plastic, glass, different sizes) used in our laboratory. Samples of buffer solutions were taken, and radioligand binding studies were performed with [3H]adenine (10 nM) using the same procedure as for the labeling of adenine receptors, except that no tissue or cell membrane preparation was added. Most investigated buffer solutions did not show any specific [3H]adenine binding. However, one sample of Tris buffer that had been taken from a 5-l plastic container with a small orifice, stored at 4°C, exhibited high affinity binding of [3H]adenine (data not shown). In contrast, radioligands used for the labeling of adenosine receptors ([3H]2-Chloro-N6-[3H]cyclopentyladenosine (CCPA) (A1) [18], [3H][3H]3-(3-hydroxypropyl)-7-methyl-8-(m-methoxystyryl)-1-propargylxanthine (MSX)-2 (A2A) [19], [3H]8-Ethyl-4-methyl-2-phenyl-(8R)-4,5,7,8-tetrahydro-1H-imidazo[2,1 ]purin-5-one (PSB)-11 (A3) [20]), or P2Y12 receptors ([3H]2-propylthioadenosine-5′-adenylic acid (1,1-dichloro-1-phosphonomethyl-1-phosphonyl) anhydride (PSB)-0413) [21] did not show any specific binding to that buffer solution.
Figure 2 shows [3H]adenine binding determined in differently treated Tris-buffer solutions (in the absence of added protein). Freshly prepared buffer did not show any specific [3H]adenine binding. After storing the buffer for 1 day at 4°C, a small degree of [3H]adenine binding could be observed, and after 2 weeks, [3H]adenine binding was significant (562 ± 19 cpm specific binding). There was a large, exponential increase in specific [3H]adenine binding with time, and after 6 weeks at 4°C, approximately 7,000 cpm (specific binding) were measured. After the 6-week-old buffer was filtered through 0.2 μm filters, [3H]adenine binding was completely abolished. Heating of the buffer for 1 min at 80°C dramatically reduced [3H]adenine binding, whereas heating for 3 min at 80°C or heating at 121°C for 20 min in an autoclave led to complete loss of specific [3H]adenine binding.
Fig. 2[3H]Adenine binding in the absence of added protein (cells or cell membranes). Incubation buffer (Tris-HCl, pH 7.4) was kept in a 5-l plastic container at 4°C for up to 6 weeks. Differently treated buffer samples (100 μl) were tested for [3H]adenine binding. The results shown represent means of three independent experiments ± standard error of the mean
Isolation of microbial buffer contaminants
As our results indicated that adenine binding was due to microbial contaminations growing in the incubation buffer, we decided to isolate the contaminants in order to characterize and eventually identify them. The microorganisms were isolated by plating contaminated incubation buffer on agar plates. This led to identification of three bacterial strains differing in the morphology of the formed colonies. The three strains were then separately amplified in medium over night, and membrane preparations were obtained to perform homologous competition binding assays using [3H]adenine (Fig. 3a).
Fig. 3Competition curves for adenine versus 10 nM [3H]adenine obtained with membrane preparations from rat brain cortex and isolated microorganisms (contaminants 1–3) (a) and intact bacteria (b). IC50 values (a): ; ; ; contaminant 3 = 2,350 nM, (n = 1). IC50 values (b): ; ;
Membrane preparations of contaminant 1 showed a very high affinity for adenine (, n = 3), whereas membrane preparations of the other two contaminants appeared to have considerably lower affinities (contaminant 2: , n = 2; contaminant 3: IC50 = 2351 nM, n = 1). For comparison, the binding curve for adenine at rat brain cortical adenine receptors () is shown (Fig. 3a). Using amounts of membrane preparations of contaminant 1 that contained more than 1 μg protein/assay tube led to depletion of the radioligand (more than 50% of the added radioligand was bound to the protein) (data not shown).
Identification of microbial contaminants
In order to identify the contaminants, standard procedures and classification kits were used (see Table 1). Standard tests, including catalase, oxidase, fermentation, motility test, and gram staining indicated that contaminant 1 is Pseudomonas  spp. or a strain of Achromobacter spp., contaminant 2 is Achromobacter  spp., and contaminant 3 Acinetobacter spp. [17]. All three bacteria are strictly aerobic gram-negative rods. For further classification, a standardized system (Api 20 NE) for classification of bacteria was used, which combines conventional and assimilation tests for identification of gram-negative rods not belonging to the Enterobacteriaceae. It was found that contaminant 1 was positive for oxidase, nitrate reduction, glucose degradation, gluconate, caprate, adipate, maltose, citrate, and phenylacetate, whereas contaminant 2 was negative for glucose, and caprate and contaminant 3 only showed positive results for caprate, maltose, and phenylacetate. Those results confirmed contaminant 3, already presumed to belong to the species Acinetobacter, as A. lwoffii, with a probability of 98.1%, and led to the identification of contaminant 1 as A. xylosoxidans (94.5% probability) and of contaminant 2 as A. denitrificans (82.2% probability) (see Table 1). Identification of the two Achromobacter strains with the VITEK fully automated system for rapid bacterial identification and antibiotic susceptibility confirmed both as members of the Achromobacter spp. with a probability of 90% each; however, differences were found in the results for phosphate, citrate, and proline assimilation (for details, see Table 1). Table 1 summarizes selected test results, which were positive for at least one of the strains.
Table 1Summary of classification test results using standard procedures and kitsTestContaminant 1Contaminant 2Contaminant 3Morphology of colonies  FormRoundRoundRound  Diameter1–2 mm1 mm1 mm  ColorGreyBeigeWhite  BrimSmoothSmoothSmooth  SurfaceShinyShinyShiny  Cross sectionRaisedRaisedRaised  Gram stainNegativeNegativeNegativeBiochemistry  Catalase+++  Oxidase++–  O/F test–/––/––/–  Motility++–  Lysine/BBL Ox/Ferm Tube II–+n.d.  ResultAchromobacter spp. or Pseudomonas spp.Achromobacter spp.Acinetobacter spp.Api 20 NE  NO3, nitrate reduction++–  GLU, glucose+––  GNT, gluconate++–  CAP, caprate+–+  ADI, adipate++–  MLT, maltose+++  CIT, citrate++–  PAC, phenylacetate+++  OX, oxidase++–  ResultA. xylosoxidans (94.5%)A. denitrificans (82.2%)A. lwoffii (98.1%)VITEK 2  N-LGGH, γ-L-glutamyl (nutrient assimilation, NA)++n.d.  P-BPHO, bis(p-nitrophenyl)phosphate+–n.d.  C-CIT, citrate–+n.d.  C-KGA, α-acetoglutaryc acid++n.d.  N-LPROT, L-proline-NA+–n.d.  ResultAchromobacter spp. (90%)Achromobacter spp. (90%)n.d. n.d. not determined
[3H]Adenine binding assays with isolated, intact bacteria
Adenine competition binding studies were performed using isolated, intact bacteria (Fig. 3b). The IC50 value obtained with whole bacterial cells of A. xylosoxidans () was in the same concentration range as that obtained with membrane preparations of the same bacteria, previously designated contaminant 1 (). For the other two bacteria, A. denitrificans and A. lwoffii, IC50 values were 5- to 10-fold lower when determined in whole bacterial cells compared with membrane preparations. From the homologous competition experiments, KD and Bmax values were estimated for A. xylosoxidans (membranes and intact cells). For bacterial membrane preparations, a KD value of 5.84 ± 1.12 nM and a Bmax value of 266 ± 65 pmol/mg protein was calculated (n = 3). For the intact bacteria, a KD value of 11.0 ± 1.2 nM and a Bmax value of 780,000 ± 120,000 sites/cell (n = 8) was obtained.
Structure–activity relationships
Affinities for selected compounds at adenine binding sites of A. xylosoxidans were determined in competition assays using whole bacterial cells and compared with data obtained in binding studies at the rat brain adenine receptor [7]. Figure 4 shows competition curves for selected compounds, which exhibited high affinity, i.e., adenine (), hypoxanthine (), and 2-fluoroadenine (). The results for all compounds tested are summarized in Table 2. Whereas the affinity of adenine for the binding sites of A. xylosoxidans was in the same range as for the rat adenine receptor, the affinities for hypoxanthine and 2-fluoroadenine differed substantially from those determined for the rat adenine receptor. Hypoxanthine showed very low affinity for the rat adenine receptor (Ki 45,000 ± 19,400 nM), but high affinity for the bacterial [3H]adenine binding sites, with an IC50 value in the low nanomolar range (59.1 ± 2.0 nM). For 2-fluoroadenine, the opposite was true: the Ki value for rat brain cortical adenine receptor was 620 ± 140 nM [7], whereas the IC50 value for the A. xylosoxidans binding site was in the micromolar range (32,100 ± 3,000 nM).
Fig. 4Competition curves for adenine, hypoxanthine and 2-fluoroadenine versus 10 nM [3H]adenine obtained with Achromobacter xylosoxidans (intact bacteria) (; ; Table 2Comparison of affinities of adenine and selected compounds for the rat adenine receptor and bacterial binding sites determined in radioligand binding studiesCompoundAchromobacter xylosoxidans (intact bacteria)Rat brain cortical membranesIC50 ± SEM [μM]a (% inhibition ± SEM at 10 μM)Ki ± SEM [μM]a (% inhibition ± SEM at 100 μM)Adenine0.0138 ± 0.0027b0.0299 ± 0.0034c2-Fluoroadenine32.1 ± 3.00.62 ± 0.14c2-Hydroxyadenine≫10 (7 ± 15)d29.4 ± 6.42,6-Diaminopurine≫10 (3 ± 8)d4.95 ± 0.751,N6-Ethenoadenineca. 10 (53 ± 6)d34.4 ± 8.1Hypoxanthine0.0591 ± 0.019645.0 ± 19.4Uracil≫10 (6 ± 1)≫100 (−6 ± 2)Xanthine>10 (17 ± 6)>100 (23 ± 7)Uridine≫10 (5 ± 5)d≫100 (−9 ± 3)Adenosine≫10 (12 ± 9)d19.4 ± 6.3caResults are from three independent experiments performed in triplicate, unless otherwise notedbResults are from eight independent experiments performed in triplicatecKi values and % inhibition values are from [7]dResults from two independent experiments performed in triplicate
Discussion
[3H]Adenine has been successfully used by us [6, 7] and other laboratories [5, 10] to label the recently discovered rat and mouse adenine receptors. However, problems with [3H]adenine binding assays have been reported by two laboratories [11, 12]. These have led to the suggestion that [3H]adenine was not a suitable radioligand for the labeling of G protein-coupled adenine receptors [11, 12]. IJzerman and coworkers [12] reported that [3H]adenine binding was not protein dependent and that it bound with nanomolar affinity to glass fiber filters in the absence of added protein. These results, which were contradictory to our own data, prompted us to reexamine the [3H]adenine binding results that we had obtained during the past years, trying to find an explanation for the discrepancies.
In contrast to the results reported by IJzerman and coworkers [12], binding of [3H]adenine to various membrane preparations was strictly protein dependent in our hands, as expected (Fig. 1). Specific binding linearly increased with increased amounts of protein and thus increased numbers of adenine receptors. Nonspecific binding was generally low for [3H]adenine, and there was only a minor increase in nonspecific binding with increasing protein concentrations. In the absence of protein, no specific binding was observed (Fig. 1b). These results indicated that [3H]adenine was a suitable radioligand for labeling adenine receptors. In fact, we could recently perform [3H]adenine binding assays on a null background for the first time, namely, at the mouse adenine receptor heterologously expressed in Sf21 insect cells. Whereas membrane preparations of the nontransfected Sf21 cells did not exhibit any specific [3H]adenine binding, cell membranes prepared from cells infected with recombinant baculoviruses bound [3H]adenine with high affinity [6].
However, when we looked carefully at all of our previous [3H]adenine binding data, we found a few [3H]adenine binding experiments that could not be evaluated due to unusually high radioactivity counts. These occasional problems had been solved by carefully controlling the experimental conditions, e.g., by using freshly prepared buffer solutions. Stimulated by the experiences reported by the IJzerman group [12], we decided to perform a systematic study to find out the reasons for those problems, which might also be causative for erroneous [3H]adenine binding results in other laboratories [11, 12].
High affinity binding of [3H]adenine to filter paper, as suggested by IJzerman and coworkers [12], could be excluded by our experiments, as buffer solutions that were freshly prepared did not show any specific [3H]adenine binding in filtration assays using glass fiber GF/B filters, the same filters that had been used by the IJzerman group [12]. On the contrary, we discovered that bacterial contaminations, which can be present in buffer solutions, express high-affinity binding sites for [3H]adenine and therefore impede adenine receptor binding assays. When we examined different buffer solutions stored in our laboratory, we discovered high [3H]adenine binding in Tris-HCl buffer solution (pH 7.4) stored at 4°C in a 5-l plastic container. That container had only a small orifice and was therefore difficult to purify. Thus, microbial contamination in this container was carried over when new buffer solution was prepared. When the contaminated buffer was filtered through a bacteria-tight filter (0.2 μm) or heated in order to denature proteins, specific [3H]adenine binding was abolished, strongly indicating that microbial proteins were responsible for the high affinity binding of adenine. A further indication that a living organism was involved was the fact that adenine binding increased exponentially with time. Interestingly, the microorganisms grew better at 4°C than at room temperature.
Our first presumption, that the contaminants might belong to yeast, could not be proven. Saccharomyces cerevisiae was used as a control organism for binding studies but showed no [3H]adenine binding (data not shown). Three microorganisms were isolated from the contaminated Tris-buffer solution and identified using standard procedures and kits. Two of these contaminants were assigned to the genera Achromobacter and one to Acinetobacter. Both bacteria species are gram-negative rods and are strictly aerobic. They are commonly found in soil and water [17]. For healthy humans or animals, they are not pathogenic, but especially A. xylosoxidans and A. lwoffii have gained increasing importance due to their ability to cause nosocomial infections [22–32]. These bacteria are able to grow under nonoptimal conditions, such as low temperature and restricted nutrient supply [17, 24–26]. They are able to metabolize a wide variety of organic substances, such as chemical pollutants in the environment, and can therefore be used as bioreporters and for the degradation of pollutants [33–36]. This is consistent with the fact that these bacteria are able to grow in simple Tris-HCl buffer at low temperature.
Both A. lwoffii and Achromobacter spp., exhibit specific binding sites for adenine, with IC50 values as low as 13 nM for A. xylosoxidans. Thus, the detected adenine binding site in A. xylosoxidans exhibits an even higher affinity than the rat (29.9 nM [7], 18 nM [5]) or mouse (54.9 nM [6]) adenine receptor. The binding affinities for A. lwoffii and A. denitrificans were more that 70-fold lower, with affinities in the low micromolar range (1 μM and 2.4 μM, respectively) when membrane preparations were analyzed and about 20-fold lower when intact cells were investigated for binding (299 nM and 253 nM, respectively). For A. xylosoxidans, only a threefold difference was found when binding affinities for membranes were compared with those with intact cells (Fig. 3). The specific, high-affinity [3H]adenine binding site in A. xylosoxidans appeared to be expressed in extraordinarily high density, as amounts of membrane preparations that contained more than 1 μg of protein/assay tube led to depletion of the radioligand (i.e., more than 50% of the added radioligand was bound to the protein). Rough estimations of receptor densities by homologous competition assays confirmed the high expression levels.
So far, the nature of these high-affinity adenine binding sites in bacteria is not known. However, bacteria express a large number of transporters, including nucleobase transporters, in order to secure their nutrient supply (for review see [37]). Nucleobase transport in bacteria has been mainly studied in Escherichia coli and Bacillus spp., as well as in the fungi Aspergillus nidulans and Neurospora crassa [37–39]. Usually, these transporters fulfill two main functions. Firstly, purines can serve as preformed bases for nucleotide biosynthesis, and secondly, they serve as nitrogen sources [40, 41]. Distinct adenine uptake systems have been identified, e.g., in E. coli [42]. The high density of the detected [3H]adenine binding sites in A. xylosoxidans would be consistent with its function as a purine transporter and points to an important role of this protein, which appears to be upregulated when the bacteria are transferred to Tris buffer (unpublished observation), a medium poor in nutrients. Such an effect has been described for protozoa [43]: purine salvage enzymes and transporters can be dramatically up- or down-regulated according to growth stage and availability of purine sources [44]. Examples are the high-affinity hypoxanthine transporter in Trypanosoma brucei brucei, which shows a 450% increased transport rate after 24 h of purine deprivation, and the adenine transporter in Crithidia luciliae, which shows a >100-fold increase of adenine uptake after purine starvation [44, 45].
For E. coli as well as for B. subtilis, two adenine transport systems have been described: a low- and a high-affinity transport system [42, 46, 47]. The latter system is important when the concentration of adenine is low [46, 47]. Differences in adenine-binding affinity observed in our studies when intact cells were compared with membrane preparations (Fig. 3) might be explained by the existence of different transporters in the bacteria (Achromobacter and Acinetobacter). Whereas bacterial membrane preparations were obtained directly from an overnight culture grown in complete medium, binding studies at whole bacteria were performed after growing them in Tris-HCl buffer, a nutrient-poor medium, in which they may have upregulated the high-affinity transporters [42, 47].
In order to investigate the structure–activity relationships of the high-affinity adenine binding site in A. xylosoxidans, a series of compounds, including adenine derivatives, other purines, and pyrimidines (uracil, xanthine, hypoxanthine), and nucleosides (uridine, adenosine) were investigated in binding studies, and the results were compared with those obtained at the rat adenine receptor. As expected, structure–activity relationships at the rat adenine receptor were very different from those at the bacterial adenine binding site. Hypoxanthine, for example, which exhibits a low affinity for the rat adenine receptor (45,000 nM), bound to the bacterial site with 760-fold higher affinity (59.1 nM), and 2-fluoroadenine, which showed a high affinity for murine adenine receptors (620 nM), bound with a 50-fold lower affinity (32,100 nM) to the bacterial site. Several compounds that had shown affinity in the micromolar range at rat adenine receptors (adenosine, 2-hydroxyadenine, 2,6-diaminopurine) were completely inactive at Achromobacter binding sites.
Alexander had previously reported that hypoxanthine at a concentration of 10 μM completely blocked [3H]adenine binding to rat brain membranes in his experiments, the results of which were not consistent with the labeling of a G protein-coupled adenine receptor [11]. It might be speculated that he actually labeled a bacterial adenine binding site rather than the rat adenine receptor, which would explain the discrepant results. The limited number of compounds (five) investigated by IJzerman and coworkers [12] do not allow a full comparison of the structure–activity relationships, but large differences were observed for two compounds—5′-deoxyadenosine (725,000 nM [12] vs. 823 nM (rat adenine receptor) [10]) and 2-fluoroadenine (19,000 nM [12], 620 nM (rat adenine receptor) [7])—indicating the labeling of a very different, presumably a bacterial, binding site by the authors [12]. The fact that hypoxanthine exhibits high affinity for the [3H]adenine binding site in A. xylosoxidans in the same concentration range as adenine itself is another indication that the labeled protein may be a purine transporter.
Nucleobase transporters have been identified in bacteria, fungi, protozoa, algae, plants, and mammals, but only few have been cloned and analyzed in detail [37, 48]. Five basic families of nucleobase transporters have been described: the nucleobase-ascorbate transporters (NAT), which include members from archaea, eubacteria, fungi, plants, and metazoa; the purine-related transporters (PRP), which are restricted to procaryotes and fungi; the purine permeases (PUP), which are purine transporters exclusively found in plants; and the equilibrative (ENT) and concentrative (CNT) nucleoside transporters, which not only transport nucleosides but may also transport nucleobases [37, 48–52]. Bacteria have developed different transport systems for related compounds, which allow them to independently absorb those compounds. This is an advantage when growing under nutritional deprivation [46, 53]. For C. luciliae, a nucleobase transporter that recognizes adenine and hypoxanthine equally well has been described [45]. In E. coli, adenine and uracil have different, specific transport systems, as do xanthine and guanine, whereas hypoxanthine might utilize the guanine transporter [53]. For B. subtilis, specific transport systems for guanine and hypoxanthine, for guanosine and inosine, as well as three independent uptake systems for adenine, adenosine and uracil, have been identified [46].
From the described observations, we conclude that the high-affinity binding sites found in bacteria isolated from Tris-buffer solutions have not much in common with the adenine receptors found in mammals. The genomes of the bacteria A. baumannii and of several closely related bacteria, such as Pseudomonas spp. are known. Therefore, we performed a search to identify potential sequences with homology to the rat and mouse adenine receptors, which, however, yielded no hits. It appears likely that [3H]adenine labels a high-affinity nucleobase transporter for adenine and hypoxanthine in Achromobacter spp., a bacterium isolated as a contaminant from Tris-HCl buffer. The high affinity in the low nanomolar range is in fact unusual; therefore, it may be speculated that the labeled protein might belong to a new type of high-affinity bacterial nucleobase transporter.
Conclusions
In conclusion, we have demonstrated that [3H]adenine is a well-suited radioligand for the labeling of G protein-coupled adenine receptors, but precaution is advised for preparing and storing buffers used for the assays to avoid bacterial contaminations. After systematically analyzing occasionally encountered irregularities in [3H]adenine binding assays, we were able to isolate three bacteria, commonly found in soil and water, from Tris-HCl buffer. They were identified as A. lwoffii, A. xylosoxidans, and A. denitrificans and revealed high-affinity binding sites for [3H]adenine.

[3h]adenine
adenine receptor
radioligand binding studies
achromobacter
acinetobacter
nosocomial infection
purine transporter
purinergic receptor
g protein-coupled receptor
bacterial buffer contamination


Expert and construct validity of the Simbionix GI Mentor II endoscopy simulator for colonoscopy

Objectives The main objectives of this study were to establish expert validity (a convincing realistic representation of colonoscopy according to experts) and construct validity (the ability to discriminate between different levels of expertise) of the Simbionix GI Mentor II virtual reality (VR) simulator for colonoscopy tasks, and to assess the didactic value of the simulator, as judged by experts.
Training skills in endoscopy for diagnostic and therapeutic procedures is essential and requires a great deal of hands-on training [1]. Virtual reality (VR) simulators offer a promising option to train these skills extensively prior to training in real-life colonoscopy, without jeopardizing patients or causing them unnecessary discomfort [2]. The use of VR training prior to performing real flexible endoscopy on patients enables novice endoscopists to go through part of their proficiency curve before submitting patients to their relatively insufficient endoscopy skills. This might not only be advantageous for the patients undergoing endoscopy, but might also prevent complications and potential consequences resulting in medicolegal litigation. One of the simulators in the field of flexible endoscopy is the GI Mentor II (see Figure 1). VR simulators have been used extensively in different fields of expertise before applying these procedures to patients. In the United States of America simulator training is mandated by the Accreditation Council for Graduate Medical Education (ACGME) in laparoscopic procedures for surgical residents [3]. The first step is to validate the simulator construct properly and verify its didactic value, before implementing simulators in teaching programmes or developing a new curriculum for flexible endoscopy around them.
Figure 1.The GI Mentor II virtual reality simulator, the setup for training in lower endoscopy.
Some studies have already been published on this subject [4–6], but the presented outcomes lacked power due to their relatively small sample sizes. In addition, some cases did not study the validity of endoscopy, but for example only the EndoBubble module, a computer simulation skills test measuring how long it takes a person to pop 20 balloons in a virtual tunnel.
Objective
The main objectives of this study were: (1) to establish the degree of representation of real-life colonoscopy on the Simbionix GI Mentor II VR colonoscopy simulation, as judged by experts (expert validity), (2) to determine whether the GI Mentor II simulator can distinguish between various degrees of expertise in endoscopy, judged by novice, intermediate experienced, experienced and expert endoscopists performing VR colonoscopy (construct validity), and (3) to assess the didactic value of the simulator, as judged by experts.
Material and Methods
Simulator
The simulator used in this study was the Simbionix GI Mentor II (Simbionix Ltd. Israel, software version 2.7.3.0) (Figure 1). The GI Mentor II can simulate upper GI tract endoscopies such as esophagogastroduodenoscopy, endoscopic retrograde cholangiopancreatographies, and endoscopic ultrasound. The lower GI tract endoscopies it simulates are sigmoidoscopy and colonoscopy. The simulator records a range of parameters upon each exercise, which can be used to assess performance objectively. The endoscope used is a customized Pentax ECS-3840F endoscope.
Participants
Participants were allocated to four groups to assess the validity and didactic value of the GI Mentor II simulator. The first group, the novices, was defined as participants without any flexible endoscopy experience; they were all medical interns or residents. The second group was intermediate experienced, with fewer than 200 colonoscopies performed before. In the third group experienced participants all performed more than 200 colonoscopies but fewer than 1,000. The fourth group consisted of experts, all of whom had performed more than 1,000 colonoscopies. These categories were chosen based upon several other studies, the demands for Dutch accreditation for colonoscopy, and the accreditation demands of the British Society of Gastroenterology, which advocates 200 colonoscopies under supervision during training [4, 6–8]. All persons were either invited to participate within our hospital, or participated during a national congress of the Dutch Society of Gastroenterology in spring 2006.
The groups consisted of at least 28 persons to ensure sufficient statistical power [9]. A post hoc sample size calculation based on the results for time to finish the EndoBubble task showed a minimal sample of 26 participants in the novices group to achieve a power of 0.95. Originally, the intermediate experienced and experienced participants formed one group, but as the expertise level and performance within this group varied considerably, this groups was split. A schematic setup of the study design is presented in Figure 2.
Figure 2.The study design.
Questionnaire
All participants were asked to fill out a questionnaire on demographics and their general medical and endoscopy experience. It also included the number of endoscopies performed annually and number of years registered as a skilled professional endoscopist.
After the simulator run the participants were asked to answer questions about their appreciation of the realism of the colonoscopy exercises performed. Appreciation was expressed on a four-point Likert scale [10] varying from very unrealistic (1) to very realistic (4). Questions were asked about the realism of imaging, simulator setup, endoscope control and both haptic and visual feedback. Experts were asked whether the GI Mentor II could be used as a teaching device for novice endoscopists and whether experience on the simulator could be useful in practice.
Simulation modules
All participants first performed the hand–eye coordination task (EndoBubble level 1) of popping all 20 balloons in the test as quickly as possible, without touching the walls. Next, the participants performed VR case numbers 1 and 3, both from colonoscopy module 1. These cases were carefully selected for their discriminative value; both cases are straightforward colonoscopies, without any abnormalities such as polyps, tumours, or inflammation. Case number 1 is a relatively easy colonoscopy to perform, whereas case number 3 is more difficult, requiring the endoscopist to apply techniques such as straightening the endoscope during loop formation and applying torque to the endoscope shaft. The assignment given for the VR colonoscopies was to reach the cecum as quickly as possible with as little patient discomfort as possible. Patient discomfort was defined as the estimated percentage of time the virtual patient was in excessive pain and the number of times excessive local pressure was caused. Other relevant test parameters were the percentage of time spent with clear view and the number of times view of the lumen was lost. The task was considered accomplished when the cecum was reached.
Data analysis
SPSS 13.0 software was used to perform descriptive statistics and Kruskal–Wallis tests for statistic analysis of the data. A separate analysis between groups was performed using a two-tailed Mann–Whitney exact U test. A p-value of less than 0.05 was considered significant. The data showed a nonparametric distribution, therefore the median and range of performance parameters are presented as primary values.
Results
Participants
Thirty-five novices, 15 intermediates, 20 experienced, and 35 expert endoscopists participated in the study. The average number of colonoscopies performed annually by experts was 445, and their mean number of years registered as a gastroenterologist was 7.7 (range 0–35 years).
Construct validity
Data output by the simulator are presented in Tables 1 and 2. The EndoBubble task was completed faster by the experts and experienced endoscopists than by novices, with fewer wall collisions. These differences were statistically significant (Kruskal–Wallis test) (Table 1). Also the colonoscopy tasks were completed faster (p < 0,001, Kruskal–Wallis test), with less patient comfort and better visibility by experts and experienced endoscopists (Table 3). Novice endoscopists (N = 35) reached the cecum in a mean time of 29:57 (min:sec) in colonoscopy case 3, intermediate experienced (N = 15) in 5:45, experienced (N = 20) in 4:19, and experts (N = 35) in 4:56. Novices lost view of the lumen significantly more often than the other groups.
Table 1.EndoBubble hand–eye coordination taskExperienceTime to finish (min:sec)Number of times wall touchedNovice N = 35Mean6:561.9Median5:581.0Range1:24–20:250–20Intermediate N = 15Mean1:561.1Median1:410.0Range0:54–4:020–5Experienced N = 20Mean1:370.9Median1:210.0Range0:43–5:330–9Expert N = 35Mean1:240.3Median1:130.0Range0:49–3:250–2Kruskal-WallisChi- square63.1519.374Asymp. sign.0000.025Table 2.Colonoscopy module 1, cases 1 and 3ExperienceTime to reach cecum (hour:min:sec)% of time spent with clear viewLost view of lumenExcessive local pressure% of time patient was in painExcessive loop formedCase 1Novice N = 35Mean6:47960.40.513.30.83Median6:169700110Range 1:53–15:08 82–99 0–30–30–44 0–6Intermediate N = 15Mean1:36970080.6Median1:40980050Range0:55–2:5291–100000–300–3Experienced N = 20Mean1:239800.29.20.7Median1:21980081Range0:48–2:4389–10000–10–270–3Expert N = 35Mean1:23980014.51.49Median1:179800121Range0:42–3:1694–1000–100–570–10Case 3Novice N = 35Mean29:57863.23.892.24.77Median23:42853301Range4:48–1:28:1972–960–121–140–240–34Intermediate N = 15Mean5:45891.12.10.91.13Median4:21921200Range2:28–13:4178–970–40–60–40–8Experienced N = 20Mean4:19910.61.91.01.6Median3:50910101Range2:27–7:0273–990–30–80–40–9Expert N = 35Mean4:56890.91.622.51Median4:0390111Range1:38–15:3968–990–40–60–100–12Table 3.Statistics colonoscopy module 1, cases 1 and 3Time to reach cecum% of time spent with clear viewLost view of lumenExcessive local pressure% of time patient was in painExcessive loop formedCase 1Chi square69.04313.88918.41519.7837.10110.691Asymp. sig.0.0000.0030.0000.0000.0690.014Case 3Chi Square65.5596.97841.93628.7944.2844.856Asymp. sig.0.0000.0730.0000.0000.2320.183Kruskal-Wallis test
A separate analysis between groups using a Mann–Whitney exact U test demonstrated no significant difference between the intermediate, experienced and expert groups on all parameters. They all completed the task faster than the novices (see Table 4).
Table 4.Differences between groups module 1, cases 1 and 3Time to reach cecum% of time spent with clear viewEost view of lumenExcessive local pressure% of time patient was in painExcessive loop formedCase 1Novice vs. intermediate0.0000.1770.0390.0130.0700.743Intermediate vs. experienced0.1660.6171.0000.2440.3850.547Experienced vs. expert0.9620.6211.0000.0430.0770.020Intermediate vs. expert0.1410.2591.0001.0000.0180.009Case 3Novice vs. intermediate0.0000.1040.0000.0040.5840.040Intermediate vs. experienced0.2570.3940.2850.5030.7710.184Experienced vs. expert0.9690.2970.1530.9420.1540.726Intermediate vs. expert0.3260.7570.8700.4160.1110.090Mann–Whitney two-tailed test, exact significance
Expert validity
The group of expert endoscopists rated the colonoscopy simulation 2.95 on a four-point Likert scale for overall realism. Anatomical representation was rated 2.58, and the simulator setup 3.14. Endoscope control scored 3.21. Haptic feedback was rated 2.57.
Didactic value
Expert opinion was that the GI Mentor II simulator should be included in the training of novice endoscopists (3.51 on a four-point Likert scale) and that expertise gained on the simulator was considered applicable in a clinical curriculum (rated 3.29 out of 4). The simulator was not considered suitable for certification of trained endoscopists (rated 2.29 out of 4).
Discussion
This study represents the largest and most detailed study on the validity of this type of colonoscopy simulator so far. The data show that the simulator can discriminate clearly between endoscopists of different expertise levels performing different colonoscopy tasks. Differences were statistically significant using relatively large sample sizes in all three exercises, the EndoBubble task as well as cases number 1 and 3. The difference between our study and previous studies by others is that we focused on the basic aspects of navigation for colonoscopy itself, rather than on the hand–eye coordination task alone, used for example in the study by Ritter et al. [4], and that we included more participants in four separate groups with different levels of expertise [4–6, 11, 12]. in this way we were able to demonstrate that the GI Mentor II can distinguish between expertise levels up to the level of an intermediate experienced endoscopist, who has performed around 200 colonoscopies. In a similar study Sedlack et al. [5] describe a limited construct for a different simulator (AccuTouch, Immersion Medical). Felsher et al. [11] demonstrated differences between novices and experts in large sample sizes but did not compare novices to intermediate levels of expertise. In this study we have demonstrated convincing expert validity for colonoscopy on the GI Mentor II virtual simulator. This in contrast to other studies focusing on the EndoBubble task as a validation study [4] and not dealing with the subject of expert validity [4, 6, 7, 11, 12].
The colonoscopy tasks were considered as accomplished once the participants reached the cecum. Asking the participants to inspect the mucosa on the way back through the colon does not, in our opinion, provide a proper representation of the endoscopist’s skills in manoeuvring through the colon, as other aspects besides the basic navigation skills of the endoscopist could influence the performance parameters provided by the simulator considerably in this case. This might lead to very different end times depending, for example, on the carefulness of the endoscopist.
This study demonstrates that the GI Mentor II simulator offers a convincing, realistic representation of colonoscopy according to experts. The overall assessment was good. Expert opinion was that the simulator can be used as a teaching tool for novice endoscopists. The simulator’s haptic feedback is doubtful. Inexperienced residents can be trained in the skills necessary in flexible endoscopy such as steering control, straightening the endoscope during loop formation and applying torque up to a certain level.
Conclusion
The current study demonstrates that the GI Mentor II simulator offers a convincing, realistic representation of colonoscopy according to experts (expert validity) and that the simulator can discriminate up to the level of intermediate experienced endoscopists (construct validity) in colonoscopy. In the cases used the simulator could not discriminate between intermediate, experienced and expert endoscopists. The next step will be a study to determine whether novice endoscopists can develop a learning curve that will actually improve their endoscopic skills applied to real patients.

validation endoscopy simulator colonoscopy training


Discrepancies in the diagnosis of intraductal proliferative lesions of the breast and its management implications: results of a multinational survey

To measure discrepancies in diagnoses and recommendations impacting management of proliferative lesions of the breast, a questionnaire of five problem scenarios was distributed among over 300 practicing pathologists. Of the 230 respondents, 56.5% considered a partial cribriform proliferation within a duct adjacent to unequivocal ductal carcinoma in situ (DCIS) as atypical ductal hyperplasia (ADH), 37.7% of whom recommended reexcision if it were at a resection margin. Of the 43.5% who diagnosed the partially involved duct as DCIS, 28.0% would not recommend reexcision if the lesion were at a margin. When only five ducts had a partial cribriform proliferation, 35.7% considered it as DCIS, while if ≥20 ducts were so involved, this figure rose to 60.4%. When one duct with a complete cribriform pattern measured 0.5, 1.5, or 4 mm, a diagnosis of DCIS was made by 22.6, 31.3, and 94.8%, respectively. When multiple ducts with flat epithelial atypia were at a margin, 20.9% recommended reexcision. Much of these discrepancies arise from the artificial separation of ADH and low-grade DCIS and emphasize the need for combining these two under the umbrella designation of ductal intraepithelial neoplasia grade 1 (DIN 1) to diminish the impact of different terminologies applied to biologically similar lesions.
Introduction
The concept of atypical hyperplasia was introduced decades ago within the continuum of intraductal breast proliferations, a continuum which encompasses benign proliferations of usual ductal hyperplasia to high-grade ductal carcinoma in situ (DCIS) [3–5, 7, 15, 32]. The term atypical ductal hyperplasia (ADH) was used initially for a vaguely defined group lesions that had “some but not all of the requisite features of ductal carcinoma in situ” [21]. Subsequently, the qualitative similarity to low-grade DCIS (LG-DCIS) was stressed, and quantitative measures were introduced to separate ADH from DCIS [21, 31].
Totally arbitrary boundaries were drawn to separate ADH from LG-DCIS, a separation that resulted in drastically different management approaches in the 1980s —i.e., mastectomy for those diagnosed as DCIS and follow-up for those with a diagnosis of ADH. Now, even with widespread use of conservative surgery, patient management differs significantly depending on whether a lesion is diagnosed as ADH or DCIS. The two most notable approaches for this separation have been based on: (a) the definition by Page et al. [21] who defined the minimum requirement for LG-DCIS as complete involvement of at least two spaces by a proliferation that cytologically and architecturally resembles DCIS and (b) the definition of Tavassoli and Norris [31] who required complete involvement of one or more ducts by a cribriform or micropapillary proliferation of uniform cells with low-grade nuclei exceeding 2 mm in aggregate diameter for a diagnosis of LG-DCIS. According to either of these two definitions, any intraductal proliferative lesion that demonstrated the qualitative cytologic and architectural features of LG-DCIS but failed to pass the defined quantitative threshold was to be designated as ADH.
Since then, no objective molecular, ultrastructural, immunohistochemical, or morphometric feature has been identified to reliably distinguish ADH from LG-DCIS [1, 11, 15, 16, 18, 25]. Therefore, the distinction of the two continues to be based solely on application of the arbitrary criteria mentioned above. Frequently cited studies in the literature, which have attempted to calculate the relative risk of various proliferative lesions, may have claimed to adhere to the criteria of Page et al. have actually deviated from the two-space rule and have accepted single-space involvement as DCIS, thereby blurring the distinction between levels of hyperplasia and atypia and diminishing the practical utility of such a distinction [8].
We conducted a survey 15 and 20 years postintroduction of these two sets of criteria to determine how much uniformity or discrepancy exists in the interpretation of these lesions and how it would impact current patient management.
Materials and methods
To investigate pathologists’ approach to selected problems in the diagnosis and management of intraductal proliferative lesions of the breast, a questionnaire was prepared with diagrammatic representations of five potentially problematic scenarios in breast pathology dealing with intraductal proliferative lesions (Figs. 1, 2, 3, 4, 5). It was decided to use diagrammatic representations rather than glass slides to facilitate distribution of the survey among a greater number of pathologists and to ensure that the participants focused on the same diagnostic issue, given the presence of certain lesions in the background. The questionnaire also inquired whether the respondents considered breast pathology their area of expertise, the average number of breast biopsies and lumpectomies or mastectomies they signed out each week, the practice setting in which they worked in (academic, community, or private), and how long they had been in practice.
Fig. 1The first scenario assessed how pathologists would diagnose a partially involved duct adjacent to unequivocal cribriform DCIS, and whether they would recommend reexcision if it were less than 0.1 mm from a resection marginFig. 2In question 2, participants were asked whether the number of partially involved ducts affects their decision to make a diagnosis of ADHFig. 3Responses to question 3 demonstrated what pathologists thought was the lowest size threshold required to make a diagnosis of DCISFig. 4Question 4 evaluated how participants would manage flat epithelial atypia close to a resection marginFig. 5Question 5 surveyed how pathologists measured invasive carcinoma in the presence of multifocal microinvasion
The questionnaire was distributed among over 300 pathologists who were either known for their expertise and specialization in breast pathology in various countries or who were interested in the field as evidenced by their participation in educational courses dedicated to breast pathology. If a participant left a response in the questionnaire blank, that response was considered null and excluded from calculations. Also, for all questions regarding diagnosis and management of lesions illustrated in the questionnaire, the respondents were given the option of choosing one of the two answers (i.e., ADH vs DCIS, Yes vs No). The responses of the small minority who chose both were similarly excluded from analyses. Also, if a participant responded to the questions regarding average number of biopsies or lumpectomies/mastectomies a week by providing a numeric range, the average value of the range was considered for calculations. The collected responses were anonymized and tabulated in a custom Microsoft Access database (Microsoft Corporation, Redmond, WA, USA), and custom queries were written for data analysis. Statistical significance of the results was evaluated using chi-square and t tests.
Results
A total of 230 completed questionnaires were received and included in the study. Of the 230 respondents, 93 (40.4%) considered breast pathology their area of expertise, while 130 (56.5%) did not consider themselves experts but had special interest or responsibility for signing out breast pathology. The respondents signed out an average and standard deviation of 10.1±9.5 biopsies and 7.5±7.8 lumpectomies or mastectomies a week. These figures were 14.4±11.4 biopsies and 10.3±9.0 lumpectomies or mastectomies a week for the responding pathologists who considered breast pathology their area of expertise and 6.9±6.0 biopsies and 5.3±6.0 lumpectomies or mastectomies a week for those who did not. T test showed the differences between the means in these two groups to be statistically significant (p<0.0001 for both biopsies and lumpectomies/mastectomies).
Academic pathologists constituted 85 (37.0%) of the respondents, while 113 (49.1%) of the respondents worked in community hospitals and 20 (8.7%) in private laboratories. Nine pathologists (3.9%) worked in more than one practice setting. Sixty-five pathologists (28.3%) had been practicing pathology for less than 5 years, 37 (16.1%) for 6 to 10 years, and 125 (54.3%) had over 10 years of practice experience.
As shown in Fig. 1, the first question addressed whether respondents considered a partially involved duct adjacent to unequivocal cribriform DCIS as ADH or DCIS and, depending on their response, whether they would recommend reexcision if this partially involved duct was less than 0.1 mm from the excision margin. Of the 230 respondents, 130 (56.5%) considered this partial cribriform proliferation as ADH and, among these respondents, 49 (37.7%) recommended reexcision of the ADH if it were close to the excision margin. On the other hand, of the 100 (43.5%) who diagnosed this partially involved duct as DCIS, 28 (28.0%) would not recommend reexcision if the lesion were close to the excision margin. Although chi-square analysis showed that pathologists who made a diagnosis of DCIS were significantly more likely to recommend reexcision compared to those who made a diagnosis of ADH (p<0.001), the final impact on patient management was that, regardless of the diagnosis, 116 (50.4%) would recommend to have a reexcision while 108 (47.0%) would not.
Question 2 documented how respondents categorized a partial cribriform proliferation involving a few (five) or numerous (20 or more) ducts (Fig. 2). When only five ducts had a partial cribriform proliferation, 82 (35.7%) of the respondents considered it as DCIS. With ≥20 ducts so involved, 139 (60.4%) of the respondents designated the changes as DCIS. Chi-square testing showed this difference to be statistically significant (p<0.001).
In Question 3, as shown in Fig. 3, the minimum size requirement for diagnosis of LG-DCIS in a single duct was addressed. When a single duct with a complete cribriform pattern measured 0.5, 1.5, or 4 mm, a diagnosis of DCIS was made by 52 (22.6%), 72 (31.3%), and 218 (94.8%) of the respondents, respectively. Chi-square testing confirmed that pathologists were significantly more likely to diagnose DCIS if the single duct measured >2 mm (p<0.001).
Question 4 addressed the approach to management of flat epithelial atypia when it was present in multiple ducts located within less than 0.1 mm from the excision margin (Fig. 4). In this scenario, when multiple ducts with flat epithelial atypia were close to an excision margin, 48 respondents (20.9%) recommended reexcision.
Finally, question 5 evaluated how respondents measured invasive carcinoma when two foci of stromal microinvasion (measuring less than 1 mm each) emanated from two opposite poles of a 1-cm duct with high-grade comedo-type DCIS (Fig. 5). Of the 230 respondents, 185 (80.4%) measured these as two separate foci of microinvasion (less than 1 mm each), while 37 (16.1%) considered the total size of invasive carcinoma as the aggregate diameter of the high-grade DCIS plus the two microinvasive foci, namely, 1.19 cm.
Chi-square testing was performed to compare the responses of expert breast pathologists and nonexperts to all five questions. No statistically significant difference was found between the two groups in the proportion of responses to any of the questions.
Discussions
These results indicate that 15 and 20 years postintroduction of criteria for separation of ADH from DCIS [21, 31], interobserver variability in the diagnosis of intraductal proliferative lesions of the breast has not diminished. Given the significance of margin involvement or proximity in current management of DCIS, this survey demonstrates an even wider variability that exists in the management of such lesions and ultimately patient care.
In a survey done by Rosai in 1991, 17 ductal and lobular proliferative breast lesions were distributed among five experts in breast pathology [24]. The participants were asked to categorize such lesions, which had already been circled on glass slides, as either hyperplasia, atypical hyperplasia, carcinoma in situ, or “other” (to be specified) based on the diagnostic criteria they used in their daily practice. In that study, there was no a single case in which all five pathologists agreed on the diagnosis, and there were only three cases (18%) in which four of the five pathologists agreed. Also, some pathologists tended to make more malignant diagnoses than others. In his report, Rosai considered this interobserver variability to be unacceptably high and suggested the adoption of a terminology such as mammary intraepithelial neoplasia with a grading system similar to that which was being used for the uterine cervix.
A possible explanation for such a high degree of interobserver variability set forth in that report was that the pathologists were not using a standard set of criteria. Therefore, a year later, Schnitt et al. [27] tried a different approach to assess interobserver variability in the diagnosis of intraductal proliferative lesions of the breast. In their 1992 survey, they asked six experts in breast pathology to evaluate 24 proliferative ductal lesions. In this survey, the participating pathologists agreed to use the criteria of Page et al., and 15 teaching slides representing classic examples of usual ductal hyperplasia, atypical ductal hyperplasia, and noncomedo DCIS were circulated among the six pathologists to foster concordance before initiation of the study. The specific area of interest on each study slide was indicated by masking all the surrounding tissue so that all the participants focused on the same lesion and to prevent any bias that may result from assessment of changes in the surrounding breast tissue. The participants in this survey were asked to adhere to the provided criteria rather than the ones they used in their daily practice. Despite all these efforts, there was complete agreement among all six pathologists in only 14 (58%) of the 24 cases and among five or more pathologists in 17 cases (71%). The most common diagnostic problem was the distinction of atypical hyperplasia from DCIS in six cases. Although this study showed a significant improvement in interobserver agreement compared to Rosai’s survey, the persistence of significant differences among expert breast pathologists even under optimal and highly artificial conditions conveyed a more widespread problem in the pathology community with potential impact on patient management.
Responses to the current survey also demonstrate that although criteria to distinguish ADH from DCIS have been introduced over two decades ago, there is still no agreement on how to categorize these two types of mammary intraductal proliferation. While the sole partially involved duct described in question 1 would not qualify as DCIS according to the criteria set forth by either Page et al. or Tavassoli and Norris, 43.5% of practicing pathologists, nevertheless, diagnosed it as DCIS. This might seem logical because the partially involved duct probably reflects an extension of the same process present in the nearby unequivocal cribriform DCIS. However, the fact remains that there is no consensus on what to designate a partially involved duct adjacent to unequivocal LG-DCIS and how to manage such a lesion when it is near or on the surgical excision margin [10]. Even among the respondents who considered the partially involved duct in question 1 as ADH, more than a third recommended reexcision if it were close to the margin of resection, and of those who considered this partially involved duct as DCIS, close to 30% would not recommend reexcision even if the in situ carcinoma were within 0.1 mm of the resection margin. This interobserver variability in diagnosis and management was so high that, in the end, patients would have an almost 50:50 chance of having a reexcision or not, regardless of the diagnosis of the partially involved duct as ADH or DCIS. This was due to a combination of the high proportion diagnosing it as DCIS and the high proportion of those who recommended reexcision even though they interpreted it as ADH. Obviously, the impact of this issue goes beyond simply margin involvement; it is also crucial in the assessment of lesion size, resulting in widely varied assessment of size/extent of LG-DCIS.
Question 2 addressed the concept of extensive ADH. Cognizant of the fact that available criteria require complete involvement of duct cross sections for a diagnosis of low-grade (cribriform or micropapillary) variants of DCIS, it was surprising to find that even when only five ducts were involved by a partial cribriform proliferation, over 35% of the respondents considered it as DCIS. Furthermore, when greater than 20 ducts were partially involved by such a cribriform proliferation, the proportion of respondents who treated it as DCIS rose significantly to over 60%. Chi-square testing showed that as the number of partially involved ducts increased, the number of patients diagnosed with cancer significantly increased. Nevertheless, even with drastic differences in the number of involved ducts (5 vs ≥20), there was no unanimity in the diagnosis of carcinoma in situ vs atypical hyperplasia.
This scenario has become increasingly more frequent since the introduction of screening mammography. It was not addressed in the criteria introduced by either Page et al. or Tavassoli and Norris because both those retrospective studies were based on predominantly premammographic era biopsies. With the increasing number of such “extensive ADH” cases (≥ 20 partially involved ducts) seen in her consultation practice, Tavassoli suggested that even when these are designated as extensive ADH due to strict adherence to previously defined criteria, they should be managed as DCIS and reexcised if close to or at the margin of resection [29].
Question 3 demonstrated that the majority of respondents used the 2-mm size criterion rather than the two spaces in diagnosing DCIS. When the single duct described in the question measured greater than 2 mm (4 mm), close to 95% of the respondents considered it DCIS. However, if this single duct measured less than 2 mm, i.e., 0.5 or 1.5 mm, 22.6 and 31.3% of the respondents considered it DCIS, respectively. Although this difference in the probability of diagnosing DCIS when the lesion measured less than or greater than 2 mm was statistically significant, it is interesting to note that over 30% of the respondents considered a single duct measuring 1.5 mm as DCIS and over 20% designated a single duct measuring only 0.5 mm as carcinoma in situ despite the fact that these two scenarios meet neither the criteria of Page et al., which require two completely involved spaces not otherwise specified as to size [21], nor the criteria of Tavassoli and Norris, which require one or more spaces greater than 2 mm in maximal cross-sectional diameter [31]. Even with a substantial 4 mm duct, 5.2% did not designate the lesion as DCIS presumably because of the two-space requirement of Page et al. These responses demonstrate that in the current day to day practice of pathology, some women with a 0.5-mm lesion would be diagnosed as having DCIS, with a reexcision if it were close to or at the resection margin, and most probably radiation therapy, whereas some women with 4 mm lesions interpreted as ADH would get no reexcision, would be simply followed up, or at most would enter some form of prevention trial with hormone therapy [2, 9].
Question 4 in our survey documented the confusion that exists regarding the management of flat epithelial atypia, with over 20% of respondents recommending reexcision if the lesion were close to an excision margin. As a result, over a fifth of the patients would have reexcision, while the remaining 80% would not.
The last question showed the various approaches pathologists take in measuring invasive carcinoma when multifocal early invasion emanating from a single duct is present. Although over 80% of respondents would consider foci of invasion less than 1 mm emanating from opposite poles of a duct with DCIS as microinvasion, slightly over 16% of respondents would measure DCIS with its associated microinvasion from opposite poles as one continuous invasive carcinoma, which would entail a drastically different treatment approach.
The results of this survey raise numerous questions about studies performed in different countries and even different institutions within the same country regarding risk factors, treatment, prognosis, and outcome of intraductal proliferative lesions of the breast, which include LG-DCIS and/or ADH—a significant proportion of mammographically detected noninvasive lesions. Even when the criteria used are explicitly stated, application of criteria varies remarkably among pathologists and from one study to the next. Certainly, the issues raised in this study are not uncommon but have not been specifically addressed in any of the major single-, multiinstitutional, or multinational studies on DCIS cases that include LG-DCIS. Most if not all such studies lack a central review of the diagnosis and even many rely on multiple pathologists at sometimes multiple institutions. This study also illustrates that 15 to 20 years of education of pathologists at local, national, and international courses has not helped much in increasing the level of agreement and uniformity in the diagnosis and interpretation of these common lesions using the criteria available for separating ADH from LG-DCIS. Chi-square testing failed to reveal any statistically significant difference in the response behavior of expert breast pathologists and pathologists who did not consider themselves experts.
Since the institution of widespread screening mammography, the number of early, LG-DCIS lesions that are diagnosed has dramatically increased [13, 14, 19]. How partially involved ducts, often spread around completely involved ducts, are interpreted could change the size/extent of the lesion by several centimeters. This potentially undermines the internal consistency and comparability of epidemiological studies and clinical trials regarding such lesions.
In his 1991 survey, Rosai lamented the fact that there were no known morphometric, ultrastructural, immunohistochemical, or molecular features to distinguish ADH from LG-DCIS [24]. Unfortunately, this issue continues to be the case [1, 11, 15, 16, 18, 25]. Pathologists must assign lesions within the ADH–DCIS continuum to one end of the spectrum or the other based on the morphologic features present on an H&E-stained slide and an arbitrary set of quantitative criteria that cannot be applied to every lesion encountered. Not only the subjective nature of interpreting the morphologic findings but also the existence of different and in some cases conflicting diagnostic criteria create considerable interobserver variability in distinguishing ADH from LG-DCIS.
This diagnostic variability in turn leads to confusion regarding the optimal management approach to such intraductal proliferative lesions because a diagnosis of LG-DCIS is automatically associated with a significantly worse prognosis and usually requires a more drastic surgical approach compared to ADH. Furthermore, the negative impact of the diagnosis of “carcinoma”, albeit an in situ one, on patients’ psychological well-being (depression and anxiety) has been well documented [12, 23] and should be a consideration in the choice of optimal terminology.
Molecular, immunohistochemical, and morphologic similarities indicate that the only difference between ADH and LG-DCIS is a quantitative one [1, 11, 15, 16, 18, 25]. The claim that separation of ADH from LG-DCIS is justified based on the development of carcinomas post-ADH in either breast while those that develop after LG-DCIS occur in the same breast is questionable [20, 22, 26]. Over a period of 23 years, three papers have appeared on this topic based on a group of 28 women with a median follow-up of 31 years, noting that the invasive carcinomas that occur after LG-DCIS treated by biopsy alone develop in the same breast and in the same quadrant from which the original biopsy with DCIS was taken. Seven of the 11 women who developed subsequent invasive carcinoma were diagnosed within 10 years of the DCIS biopsy, 1 was diagnosed within 12 years, and the remaining 3 developed infiltrating carcinomas over 23–42 years. The authors conclude that these results “indicate a striking dividing point biologically and histopathologically between LG-DCIS lesions and the cytologically similar but lesser lesions of ADH” [26]. When 7 of the 28 women developed invasive carcinoma within 10 years, one wonders why the remaining patients were not contacted to receive appropriate therapy for their disease rather than continuing the study for another 20 years.
Judging from the microscopic description and the sampling documented for these 28 cases, a substantial number of these lesions were probably not low grade because they had some atypia and/or necrosis, albeit not diffusely, suggesting that those who died within 10 years most likely had substantial amount of residual disease and/or higher grade DCIS lesions [6]. The gross and pathologic features of these 28 cases are described in detail in the initial paper published in 1982, which did not refer to them as low grade [20]. Therefore, it is more likely that this study reflects the natural history of a wide variety of intraductal carcinomas, only some of which were LG-DCIS. A more simple explanation for any differences that might exist between ADH and LG-DCIS in the frequency of subsequent progression would be that a minuscule lesion, once totally removed, results in near equalization of the risk for subsequent development of carcinoma in the two breasts of that individual patient. A more extensive process, however, is less likely to be completely eliminated by conservative surgical excision alone, leading to the development of recurrences at the same site due to residual disease [6].
A recent epidemiological study has shown a nearly equal incidence rate (5.4 vs 4.5/1,000 person-years) for development of subsequent invasive carcinoma in either breast after a diagnosis of DCIS among close to 37,700 patients diagnosed between January 1988 and December 2002, many of whom were treated by surgery and radiation therapy [17]. This confirms the fact that once a DCIS is adequately treated, it results in equalization of risk for either breast. Furthermore, it indicates that complete excision is an adequate therapy for small lesions. Therefore, complete excision with adequate margins should be explored further as the only therapy for small DIN 1 (DCIS grade 1) lesions that do not exceed 3–4 mm in maximum extent, particularly when there is no evidence of even any flat epithelial atypia around the DCIS.
It seems only logical to adopt a terminology in which two morphologically identical lesions are not given diagnostic designations as different as “hyperplasia” and “carcinoma”. The use of the DIN terminology may help solve this problem [28, 30]. Although the DIN terminology does not claim to reduce interobserver variability, it diminishes the effect of drastically different designations for similar lesions by including the spectrum of atypical ductal hyperplasia and LG-DCIS under the umbrella designation of grade 1 DIN.

breast
ductal carcinoma in situ
hyperplasia
ductal intraepithelial neoplasia
interobserver variability