Functional sex differences in human primary auditory cortex

Background We used PET to study cortical activation during auditory stimulation and found sex differences in the human primary auditory cortex (PAC). Regional cerebral blood flow (rCBF) was measured in 10 male and 10 female volunteers while listening to sounds (music or white noise) and during a baseline (no auditory stimulation).
Introduction
Previously, investigators tried to relate sex differences in behaviour and cognition to differences in brain anatomy, function, or connectivity. A well-documented example of sex differences in the brain is the difference in overall brain size. We now know that the size of the male brain is on average 8–10% larger than the female brain [1–3]. It is also thought that, compared to the female brain, there is more hemispheric asymmetry in the anatomy of the male brain [4–7], which is supported by the finding that in the male brain, functions are represented more unilaterally [8–12].
Sexual dimorphism has also been reported for the anatomy and function of the auditory cortex. The human auditory cortex is located in the superior temporal lobe. The primary auditory cortex (PAC) is situated in the medial two-thirds of the transverse temporal gyrus, also called Heschl’s gyrus (Fig. 1). It is surrounded by secondary and associative auditory regions, which cover the lateral part of the transverse temporal gyrus and extend to the superior temporal plane. The primary auditory region was designated as area 41 by Brodmann [13], the secondary auditory regions are areas 42 and 22 [14]. An example of sexual dimorphism in the anatomy of the auditory system is in the study by Rademacher et al. [15] who reported that both left and right primary auditory cortices are larger in females than in males, although an earlier study found no differences [7]. Anatomical reports also show larger and more symmetrical auditory association cortices in females than in males [7, 16]. However, many studies emphasize that there is intersubject variability regarding the size and location of the primary and secondary auditory cortex [17–21].
Fig. 1Spatial distribution of significant increases in brain activation in men and women when comparing the auditory processing of noise, music, and a baseline. Activations are superimposed on an anatomical MRI template of SPM2. Clusters are significant at p < 0.05 FDR corrected for multiple comparisons. L=left hemisphere, y = −20 and y = −6 means a coronal plane, respectively, 20 mm and 6 mm posterior to the anterior commissure, z = 8 means a horizontal plane 8 mm dorsal to the anterior commissure, z  = −1 means a horizontal plane 1 mm ventral to the anterior commissure. a Contrasting music with noise, women showed activation in the secondary auditory areas only, whereas men showed activation in both PAC and secondary auditory areas. b Comparing music to the baseline, both women and men showed bilateral activation in the PAC and secondary auditory areas. c Comparing noise to the baseline, women showed bilateral activation in the PAC. In men, on the other hand, no significant activation was found. The differences between men and women in a and c are significant (see Table 2)
Functional sex differences in auditory processing are widely studied in the light of language. Females depend less on their left hemisphere for language processing than males in some studies [22], whereas in other studies the opposite was found [23, 24] or no sex difference could be detected [25, 26]. Whether a sex difference in language processing can be detected might depend on the nature of the task [10].
Sex-based influence on activation patterns in auditory regions is also found when manipulating the amount of background noise [27], and auditory working memory tasks induce different activation patterns in males and females [28]. These studies suggest that combining men and women in auditory neuroimaging studies may obscure or bias results.
However, most of these studies focus mainly on functional sex differences in higher order (associative) brain areas, thereby ignoring possible sex differences in primary auditory cortices. Previously, a sex difference in activation of the PAC during lipreading was found [29]. However, it has not been investigated whether nonspeech sounds can induce different activity in the PAC in both sexes.
In the present study, we investigated potential sex differences in the activity of the primary auditory region, using different auditory stimuli.
Material and methods
Subjects
Twenty healthy, right-handed volunteers participated in this study (10 males, 10 females). The mean age for men was 23 years (range 20–25) and for women 22 years (range 19–27). All volunteers gave written informed consent according to the Declaration of Helsinki and the Medical Ethics Committee of the University Medical Center Groningen approved the study. None of the subjects had any history of psychiatric or neurological disorders. Prior to the scanning, subjects were tested for their hearing thresholds using standard audiometric measures. All subjects had normal hearing thresholds (<20 dBHL, 0.25–8 kHz), and only small intersubject variations in hearing thresholds were observed.
Data acquisition
Regional cerebral blood flow (rCBF) was measured using radioactive water ([15O]-water, half-life 122 s) as a tracer. A Siemens Ecat Exact HR+PET scanner, operated in three-dimensional mode with a 15.5 cm axial field of view, acquired 63 slices simultaneously. Each subject was scanned 12 times to measure the distribution of [15O]-water with a 10 minute interval between two scans to allow for decay. Each scan was performed after an intravenous bolus injection of 500 MBq of [15O]-water per scan. Except for the first scan, scanning started 30 s prior to injection, to account for background activation. Scanning continued for 120 seconds. The activity measured during this period was summed and used as a measure of rCBF. A scan specific calculated attenuation correction was performed to minimize interscan displacement-induced variance [30]. All subjects were scanned at fixed times on fixed weekdays, and male and female subjects were addressed to the scan dates randomly.
Experimental design
Three conditions were used in this study: baseline (no auditory stimulation), white noise (at an intensity level of 75 dBSL), and music (music of the movie “The Piano” at 75 dBSL). Both music and noise have a wide frequency range, stimulating a large number of haircells in the cochlea and hence a large portion of the cortical auditory areas, but noise has a continuous and uniform frequency spectrum whereas music is a dynamic stimulus. Each condition was presented four times in a random order. For stimulus presentation we used a clinical audiometer (Interacoustics, model AC30), a Tandberg Educational tape recorder, and E.A.RTone 3A insert phones (with E.A.Rlink eartips), which have a flat frequency response between 100 and 4000 Hz, measured in a Zwislocki-coupler. Stimuli were presented binaurally. Ten seconds before injection of radioactive water, the stimulus was started. Because the tracer reaches the brain approximately 10 seconds after injection, subjects were exposed to the stimulus for 20 seconds before the distribution of [15O]-water in the brain starts. Subjects were instructed to close their eyes, not to move during the scans, and to listen to the auditory stimuli. Before each scan we informed the volunteers that the scan was about to start. Immediately after each scan the volunteers were questioned about the scan (did they hear the stimulus? were they uncomfortable or distracted?). During scanning we monitored the subjects with infrared cameras.
Data analysis
The 2002 version of Statistical Parametric Mapping (SPM2: software from the Wellcome Department of Cognitive Neurology, London, UK) was used for spatial transformations (realignment, transformation into standard stereotactic space, and smoothing with an isotropic Gaussian kernel of 8 mm FWHM), and statistical analysis [31]. An ANOVA estimated the following parameters: two groups (male and female), three conditions (baseline, noise, and music) and the mean perfusion to normalize for global flow differences (multigroup, conditions, and covariates). Each scan was scaled to a mean global activity of 50 ml/100 ml/min. Hypotheses about regionally specific condition effects were tested to compare the estimates by using linear compounds or contrasts. The resulting set of voxel values for these contrasts constituted the associated SPM of the t-statistics.
The significance threshold used for the analysis of the two groups separately (male–female) was p < 0.05 (false discovery rate (FDR) corrected for multiple comparisons [32]) with an extent cluster threshold of more than 8 voxels. We used AMIDE software (http://amide.sourceforge.net/) for colour scaling and display of the results on the anatomical MRI template of SPM2. For maximum statistical sensitivity and for testing the significance of the sex related differences, we conducted a region of interest (ROI) analysis in our a priori hypothesized areas, i.e. the left and right PAC, using the SPM anatomy toolbox [33] and the MarsBaR toolbox (MARSeille Boîte À Région d’intérêt [34]). Specifically, we created anatomical ROIs based on the three-dimensional probabilistic cytoarchitectonic maps from the SPM anatomy toolbox brains [18, 20, 33]. To compensate for differences in stereotactic space between SPM and the anatomy toolbox, a linear transformation was applied to the anatomical ROIs. MarsBaR was then used to conduct the statistical analyses on these ROIs. The statistical procedure in MarsBaR is the same as in SPM, but instead of analysing on a voxel-by-voxel basis like SPM does, all voxels in a region are averaged, and hence inferences about the whole region can be made. Also in MarsBaR, contrasts were considered significant at p < 0.05.
Results
Music versus noise
For this contrast, in females the SPM-analysis resulted in significant bilateral activation clusters with a maximal significant voxel in the secondary auditory areas. In men much larger bilateral clusters were found covering not only the secondary auditory areas but also the PAC (Fig. 1a and Table 1). This indicates that males have a much larger activation in the PAC during music than during noise. The voxel-wise analysis of SPM did not reveal any significant activation differences between the two sexes.
Table 1Overview of brain areas with statistically significant cerebral blood flow changes  SideRegionTalairach coordinatesNumber of voxelst-valuexyzMusic vs noiseFemalesRightBA 2261−6−11,4597.77LeftBA 22−51−10−13105.02MalesRightBA 41, 42, 22522−33,2347.87LeftBA 41, 42, 22−51−802,1907.87Music vs baselineFemalesRightBA 41, 42, 2257−4−12,7508.85LeftBA 41, 42, 22−48−1731,8667.97MalesRightBA 41, 42, 2251−1022,47510.36LeftBA 41, 42, 22−48−1212,3068.67Noise vs baselineFemalesRightBA 4146−2154466.49LeftBA 41−40−2354636.24MalesNo suprathreshold clustersBaseline vs noiseFemalesNo suprathreshold clustersMalesRightBA 92050299685.20Baseline vs musicMalesNo suprathreshold clustersFemalesNo suprathreshold clustersThe region, covered by the whole cluster and noted in Brodmann areas, and the number of voxels in the cluster are described [14]. BA 41 corresponds to the PAC, BA 22 and 42 correspond to secondary auditory areas. Only the stereotaxic (Talairach) coordinates and t-value of the maximum of the cluster are given. The significance threshold was p  < 0.05 FDR-corrected for multiple comparisons; extent threshold was 8 voxels; voxel size was 2 × 2 × 2 mm. Brain regions were identified using the Talairach atlas and the stereotactic atlas of the human brain of Mai et al. [52, 53]
The region of interest analysis in the PAC showed that females do have a larger activation in the PAC during music than during noise (p values 0.005 and 0.001 for the left and right PAC, respectively). But the difference between music and noise is much smaller than in males in both the left and right PAC (p values 0.016 and 0.008, respectively, Table 2, Fig. 2). No significant deactivations were found (i.e. noise versus music).
Table 2Region of interest analysis of the left and right primary auditory cortex (PAC) P-valueLeft PACRight PACMusic vs noise females0.005*0.001* Males<0.001*<0.001* Females minus males0.9840.992 Males minus females0.016*0.008*Music vs baseline females<0.001*<0.001* Males<0.001*<0.001* Females minus males0.7210.779 Males minus females0.2790.221Noise vs baseline females<0.001*<0.001* Males0.016*0.005* Females minus males0.042*0.034* Males minus females0.9580.966One-sided statistical significance for various contrasts was tested for men and women separately as well as for the differences between both. *Significant at p < 0.05Fig. 2Regional cerebral blood flow relative to the baseline of each group, based on all voxels in the left and right PAC (with a global mean flow of 50 ml/100 g/min). Error bars indicate the 90% confidence interval of the mean across subjects per condition; the confidence interval of the baseline is also given
To determine whether this sex difference can be attributed to the processing of either music or noise, we compared these two stimuli with a baseline without experimental auditory stimulation.
Music versus baseline
For this contrast, the SPM-analysis showed large comparable activation clusters covering primary and secondary areas in both males and females (Fig. 1b and Table 1). The ROI analysis showed that there were no significant differences in the activation of the PAC between both sexes for this contrast (Table 2, Fig. 2). Again, no significant deactivations were found (baseline versus music).
Noise versus baseline
Comparing noise to the baseline, the SPM-analysis showed two significant bilateral activation clusters with maxima in the PAC for the female group. In contrast, no significant activations were found in the male brain at a corrected level of p < 0.05 (Fig. 1c and Table 1). Only when the data were analysed at an uncorrected threshold of p < 0.01, a small activation appeared in the PAC of males, primarily on the right side (Fig. 3). The ROI-analysis confirmed in men the involvement of the PAC while processing noise, showing significant bilateral increases of blood flow, but these activations were significantly less than in women in the left (0.042) and right PAC (p = 0.034) (Table 2).
Fig. 3Spatial distribution of significant increases in brain activation in men and women for the comparison of noise to the baseline. Clusters are significant at p < 0.01, uncorrected for multiple comparisons. L=left hemisphere, y = −20 means a coronal plane 20 mm posterior to the anterior commissure, z = 8 means a horizontal plane 8 mm dorsal to the anterior commissure. In contrast to Fig. 1c, at an uncorrected level men do show activation in PAC, but it is much smaller than in the female group
The voxel-wise analysis of SPM also revealed a significant deactivation in the male group. This deactivation was located in the right dorsolateral part of the prefrontal cortex extending to the posterior part of the middle frontal gyrus, covering primarily BA 9 (Fig. 4 and Table 1). In contrast, no significant deactivation was found in the female group.
Fig. 4Spatial distribution of significant decreases in brain activation in men and women for the comparison of noise to the baseline. Clusters are significant at p < 0.05, FDR corrected for multiple comparisons. x = 20 means a sagittal plane 20 mm on the right of the anterior commissure, z = 29 means a horizontal plane 29 mm dorsal to the anterior commissure. Only men showed a significant deactivation in the dorsolateral prefrontal cortex
Discussion
Our data demonstrate a sex difference in regional cerebral blood flow in the left and right primary auditory cortex (PAC) when comparing auditory processing of music and noise. The PAC was more activated by music than by noise in both men and women. But this difference between the two stimuli was significantly higher in men than in women. To determine whether this sex difference can be attributed to the processing of music, noise, or both, we compared the two stimuli with a baseline of no auditory stimulation. Comparing music with the baseline resulted in extensive activation of the primary and secondary auditory cortex in both sexes, but no significant sex difference was found. On the other hand, a sex difference was detected in the processing of noise, because females activated their PAC significantly more than males. The finding that sex differences in auditory processing can already be detected at the level of the primary cortex is very important, because it is often assumed that sex differences act exclusively upon higher-order cortical areas.
There appears to be a mismatch between the SPM and ROI analyses because there is a difference in power between the two analysing methods. The ROI analysis pools the data of all voxels in the PAC and gives a reduced standard error, resulting in a higher t-value and hence more power [34]. Although the SPM analysis showed no activation at all for the male group and a very significant activation for the female group, it did not have enough power to detect a significant difference between the two groups. Because of the enhanced sensitivity of an ROI analysis, this analysis did show a significant sex difference. Of course, caution has to be made when pooling data to improve the sensitivity and is therefore only allowed in a priori defined regions, in this case the PAC.
The question is whether the sex difference found is caused by the experimental conditions or by other factors like anatomical differences or methodological errors. The reported differences in activation of the PAC stand or fall by a correct identification of this area in the region of interest analysis. Several authors reported substantial intersubject variability in size and location of the PAC [17–21]. To overcome this problem of variability in size and location of the PAC, we employed linear resizing and shearing as well as nonlinear warping of the brain to normalize the individual brains into a standardized stereotactic frame. In addition, a Gaussian smoothing filter of 8 mm was used to remove residual variance in brain structure that remains after the stereotactic normalization. Furthermore, we used probability maps, based on the cytoarchitecture of 10 subjects, to identify the PAC [18, 20, 33]. Other studies suggested that the volume of the PAC is bilaterally larger in females than in males [15]. It is therefore necessary that the region of interest depicts the PAC of both men and women. This is the case, because the probability maps of the SPM anatomy toolbox are based on the cytoarchitecture of five male and five female brains [18, 20, 33]. For these reasons we believe that possible intersubject or intergroup differences in size and location of the PAC do not bias our results.
If the reported sex and contrast dependent differences in rCBF patterns are not caused by underlying anatomical differences, metabolic differences, or methodological errors, they must have been induced by the experimental stimulus. During the baseline condition, subjects had to lie quietly in the scanner and no auditory stimulus was applied. Without auditory stimulation and a specific task, the variance in rCBF might increase, resulting in less statistical power when comparing conditions to the baseline. However, as shown in Fig. 2, the confidence interval for the model parameters was very similar for the three conditions. In addition, the confidence interval was also very similar for the two sexes. This means that the different contrasts tested have similar statistical power. Considering the significant sexual dichotomy in the processing of music versus noise and the results when comparing either the music or noise with the baseline condition, we conclude that males and females differ in the processing of noise. Thus our data demonstrate a sexual dichotomy in auditory processing. But which mechanism could explain this sexual dichotomy? A key to answering this question is the role of the prefrontal cortex, which we found to be deactivated in men when listening to noise. In humans, the prefrontal cortex is engaged in diverse cognitive processes including cognitive control, working memory, and attention [35]. For example, Gisselgård et al. [36, 37] investigated the influence of irrelevant speech on working memory tasks and revealed a functional link between auditory and prefrontal regions. Tzourio et al. demonstrated that prefrontal areas are engaged in auditory tasks that involve sustained or selective auditory attention [38]. In the present study, no explicit (attention) task was implemented. Subjects lay passively in the scanner and were instructed to listen to the auditory stimuli. While listening to an insignificant stimulus like noise, males deactivated the prefrontal attention areas as compared to silence. Females, on the other hand, had no deactivation of the attention areas and had a higher activation in the primary auditory cortex. Deactivation of the prefrontal regions was only seen in the right hemisphere, which is consistent with Tzourio et al. who stated that a right hemisphere dominance exists for attention [38]. The present results suggest a relationship between activation of PAC and prefrontal cortex. From literature, anatomical evidence exists concerning auditory–prefrontal connections. Studies on monkeys have shown that the prefrontal cortex is reciprocally connected with auditory association areas (i.e. belt and parabelt in the monkey brain) [39]. The secondary and primary auditory areas are reciprocally connected (c.f. [40]). More recent studies on monkeys identified two auditory–prefrontal processing streams: dorso and ventrolateral auditory streams [41–43]. Although, one should be cautious when comparing human and nonhuman primate brains, a similar organization of several parts of the human and monkey prefrontal cortex has been reported [44, 45].
To summarize, we know from literature that the auditory and prefrontal regions are anatomically and functionally linked, and our data show a sexual dichotomy in the (de)activation of both regions. Apparently, the male and female brains handle an insignificant stimulus like noise differently, and we speculate that this is done by a different engagement of the auditory–prefrontal attention network. Namely, differences in attention result in a different deactivation of the right prefrontal cortex, which in turn modulates the activation of the PAC and thus explains the sex differences found in the activation of the PAC. This corresponds with previous findings that sex differences exist in the frontal–temporal network, namely, males have higher intrahemispheric functional connectivity of frontal and temporal areas than females [46]. It is also known from ERP studies that sex differences exist in orienting attention to auditory stimuli [47]. It must be noted that even though our data indicate differences in the auditory system, no independent behavioural data regarding the attention levels during scanning are available. Hence, the present experimental design only allows us to speculate about the correlation between the different deactivation of the prefrontal cortex and differences in attention. Further research is needed to fully clarify the role of attention on PAC activation and to determine whether our results can be repeated. Furthermore, other auditory conditions like pure tones, noise bursts, and speech (sense and nonsense) sounds are needed to fully map the influence of sex on central auditory processing and to investigate lateralization differences between the sexes.
To our knowledge, this is the first time that a sexual dichotomy in the function of the PAC is demonstrated using nonspeech sounds. Previously, a sex difference in the PAC was demonstrated while lip reading [29, 48]. These studies showed only female activation in the PAC during lip reading because they associate the absent speech sound with the visual lip movements. Males on the other hand, did not display activation in the PAC and focus on the present visual lip image itself. The current study shows that even simple sounds induce different activation patterns, especially in the PAC. Other sexual dichotomies in the central auditory system have been reported. For example, sex differences in auditory feedback loops of the corticofugal network have been found in which men showed more suppression of repeated acoustic stimuli than females. This sex difference in auditory gating is probably the result of differential neuronal inhibition to repeated stimulation [49]. Likewise, the stronger spontaneous otoacoustic emissions (SOAEs) in females are thought to originate from a relatively larger amount of efferent inhibition in males [50]. This efferent innervation would start in the olivary complex and terminate in the outer hair cells of the cochlea [50].
Although the present sexual dichotomy would be consistent with the concept of evolutionary advantages in a hunter–gatherer society (c.f. [51]) where the inhibition of constant irrelevant stimuli in men may facilitate them to focus their attention to a single task, e.g. hunting, this concept remains speculation.
In conclusion, a very significant sexual dichotomy was found in the activation of the PAC with different types of acoustic stimuli (noise and music) together with sex differences in deactivation of prefrontal areas. It is known that the auditory and prefrontal regions are anatomically and functionally linked, and the prefrontal cortex is engaged in auditory attention tasks. Hence, we hypothesize that differences in attention might result in a different involvement of the right prefrontal cortex, which in turn modulates the activation of the PAC. This shows that sex influences brain activity already at the level of primary sensory cortex and that in functional imaging studies on primary sensory cortical areas, sex cannot be ignored.


GTP avoidance in Tetrahymena thermophila requires tyrosine kinase activity, intracellular calcium, NOS, and guanylyl cyclase

Guanosine 5'-triphosphate (GTP) is a chemorepellent in Tetrahymena thermophila that has been shown to stimulate cell division as well as ciliary reversal. Previous studies have proposed that GTP avoidance is linked to a receptor-mediated, calcium-based depolarization. However, the intracellular mechanisms involved in GTP avoidance have not been previously documented. In this study, we examine the hypothesis that GTP signals through a tyrosine kinase pathway in T. thermophila. Using behavioral assays, enzyme immunosorbent assays, Western blotting, and immunofluorescence, we present data that implicate a tyrosine kinase, phospholipase C, intracellular calcium, nitric oxide synthase (NOS) and guanylyl cyclase in GTP signaling. The tyrosine kinase inhibitor genistein eliminates GTP avoidance in Tetrahymena in behavioral assays. Similarly, pharmacological inhibitors of phospholipase C, NOS, and guanylyl cyclase all eliminated Tetrahymena avoidance to GTP. Immunofluorescence data shows evidence of tyrosine kinase activity in the cilia, suggesting that this enzyme activity could be directly involved in ciliary reversal.
Introduction
Chemorepellents are molecules that inhibit or repel the migration of individual cells. In protozoans, chemorepellents are hypothesized to serve a defense mechanism, helping the organism to avoid predation and environmental hazards. For example, a damaged Tetrahymena thermophila cell may leak cytosolic purines such as adenosine triphosphate (ATP) or guanosine 5'-triphosphate (GTP) into the surrounding environment, causing other cells to avoid the area, thereby avoiding the source of damage to the original cell and increasing the survival rate of the species [1, 2]. It is possible that cytosolic purines may be secreted by these organisms as a means of communication between cells (analogous to paracrine secretion) or in order to trigger second-messenger pathways within the cell doing the secretion (analogous to autocrine secretion). At this time, secretion of purine nucleotide by Tetrahymena has not been documented, although Tetrahymena have been shown to secrete a number of enzymes and peptides.
In T. thermophila, extracellular GTP is a known chemorepellent [1, 3, 4]. GTP causes depolarization in the somatic membrane [2], which has been proposed to trigger opening of the voltage-dependent calcium channels in the ciliary membrane [2]. The increase in Ca2+ concentration causes the cilia to reverse their direction [1], resulting in a disruption of normal swimming. This “avoidance reaction” [1] is marked by jerky movements, backward swimming, or spinning. This chemokinetic response involves a series of avoidance reactions, resulting in a “biased random walk,” which orients the organism away from the source of the repellent [3]. Avoidance to chemorepellents may be quantified by observing the response of single cells exposed to repellent using a dissection microscope.
T. thermophila avoid micromolar concentrations of GTP [1]. An in vivo binding assay using [32P] GTP showed the KD for GTP binding to intact T. thermophila is 21 ± 2.5 nM. GTP binds to its receptor with high affinity, and binding is saturable as well as reversible [1], all of which are characteristic of membrane receptors. Fluorescent staining with 2′-(or 3′)-O-(2,4,6-trinitrophenyl) (TNP)-GTP has shown GTP binding on the cilia and cell surface of T. thermophila [4]. However, the second messenger pathways involved in GTP signaling have not been previously described.
Recently, Iwamoto and Nakaoka [4] found that addition of extracellular GTP to the medium induces cell division in T. thermophila, a result consistent with a tyrosine kinase signaling mechanism, as tyrosine kinases are involved in many major mitotic pathways. Tyrosine phosphorylation has previously been shown to modulate the interaction of calmodulin with target proteins, including protein phosphatase 2B (calcineurin) and neuronal nitric oxide synthase (nNOS) in an in vitro assay [5]. Tyrosine kinase activity has also been shown to activate phospholipase C, NOS (via protein kinase C), and guanylyl cyclase in the rat ileum [6]. Tyrosine kinases are frequently associated with activation of phospholipase C-γ, and with release of calcium from internal stores via the IP3 pathway [7].
In our current study, we examined the hypothesis that GTP signals through a tyrosine kinase pathway in T. thermophila. Our data confirm this hypothesis. In addition to tyrosine kinase signaling, we found that phospholipase C, intracellular calcium stores, NOS, and guanylyl cyclase are necessary for behavioral avoidance to occur. All of these second messengers are consistent with the existence of a tyrosine kinase signaling pathway in T. thermophila.
Materials and methods
Cell cultures
T. thermophila, strain B2086, a generous gift from T.M. Hennessey (SUNY-Buffalo) were used for all of the experiments. Cells were grown at 25°C in the axenic medium of Dentler [8] without shaking. Two-day-old cell cultures were used for all assays described below.
Chemicals and solutions
Behavioral assays were carried out in a buffer of pH 7.0 containing 10 mM Trizma base, 0.5 mM MOPS, and 50 μM CaCl2. All repellents and inhibitors used were dissolved in this buffer. Compounds that were insoluble in aqueous solutions were first dissolved in a small quantity of dimethylsulfoxide (DMSO) and then diluted 1:1,000 or more into the buffer and vortexed vigorously. The chemorepellent guanosine-5′-O-(3-thio)triphosphate (GTP-γ-S) was obtained from Alexis Biochemicals (San Diego, CA, USA), along with the G-protein inhibitor pertussis toxin. The tyrosine kinase inhibitor genistein was obtained from Acros Organics (New Jersey, USA). Calphostin C [a protein kinase C (PKC) inhibitor], diadzein a control for genistein inhibition), guanosine-5′-O- (2-thiodiphosphate) (GDP-β-S) (a G-protein inhibitor), Rp-8-Bromoguanosine-3′,5′-cyclic monophosphorothioate (Rp-8-Br-cGMPs) (a competitive inhibitor of PKG), 1-(6-(17β-3-methoxyestra-1,3,5(10)-trien-17-yl) amino)hexyl)-1H-pyrrole-2,5-dione (U73122) (a phospholipase C inhibitor), NG-monomethyl-L-arginine (L-NMMA), and N-(3-(Aminomethyl)benzyl)acetamidine (1400W) (NOS inhibitors), 4H-8-bromo-1,2,4-oxadiazolo(3,4-d) benz(b)(1,4)oxazin-1-one (NS2028) (a PKG inhibitor), and the Quantizyme nitric oxide (NO) assay kit were purchased from BIOMOL Research Laboratories (Plymouth Meeting, PA, USA). The polyclonal antiphosphotyrosine antibody was purchased from Upstate (Lake Placid, NY, USA); 30X Tris-buffered saline (TBS) and 30X TBS/nonidet P40 (NP40) were obtained from Modern Biology (West Lafayette, IN, USA). The guanosine 3′3;5′monophosphate (cGMP) emzyme immunosorbent assay (EIA) kit was purchased from Cayman Chemical (Ann Arbor, MI, USA). Sodium metavanadate (a phosphatase inhibitor) and theophylline (a phosphodiesterase inhibitor) were obtained from Sigma Chemical (St. Louis, MO, USA). All other chemicals were purchased from Sigma as well.
Behavioral assays
In vivo behavioral assays were carried out as previously described [1, 9, 10]. Briefly, cells were washed in buffer, and 300 μl of cell suspension was transferred to the first well of a three-well spot microtiter plate. Cells were then individually transferred by micropipette to the second well, which contained 300 μl of the test concentration of inhibitor dissolved in buffer. After at least 10–15 min of incubation time, individual cells were transferred to the third well, which contained 300 μl GTP-γ-S and the test concentration of inhibitor. Each cell was briefly observed (1–5 s) for signs of avoidance. Avoidance behavior was characterized by jerky, backward movements; swimming in small, tight circles; sudden reversal of swimming direction; or any deviation from the normal helical swimming pattern of T. thermophila.
Western blots
Western blots were performed as follows: For each sample, 10 ml of the same 2-day-old culture was washed 3× in behavioral buffer; 100 μM GTP-γ-S (the concentration required to elicit 100% avoidance) was added to the tube of cells marked GTP. The control tube received only buffer; no GTP was added. Both tubes were immediately extracted with 0.1% sodium dodecyl sulphate (SDS) in the presence of 1 mM sodium orthovanadate for 30 min at 4°C. Extracts were spun at 16,000 g at 4°C for 30 min to precipitate insoluble components. Supernatant was collected, and 5× loading buffer was applied in preparation for SDS polyacrylamide gel electrophoresis (PAGE); 100 μl of each sample was applied to a 10% SDS-PAGE. Amount of protein loaded onto the gel was standardized using the BIO-RAD protein assay; in addition, a control, Coomassie-stained gel, was run to show that equal amounts of protein were loaded into each well. Proteins were transferred from the SDS-PAGE to nitrocellulose for 30 min at 150 mA. Blots were then blocked overnight in a 3% solution of powdered milk. Blots were incubated with a 1:1,000 dilution of polyclonal phosphotyrosine antibody in the presence of 3% powdered milk for 1.5 h, washed 3× in TBS, then incubated with a 1:100 dilution of alkaline phosphate conjugated anti-rabbit antibody for 1.5 h in the presence of 3% powdered milk. Blots were then washed 3× with TBS and incubated for 5 min in an alkaline phosphatase buffer containing 100 mM NaCl, 5 mM MgCl2, 100 mM Trizma base, pH 9.5 with hydrogen chloride (HCl). Alkaline phosphatase buffer was then removed, and blots were developed using the Sigma-Fast system until bands were visible.
EIA assays
NO assays were carried out using 2-day-old cell cultures. Cells were washed twice in buffer and diluted to a final concentration of approximately 720 cells/ml. Cells were exposed to 100 μM GTP-γ-S for approximately 30 s, then spun down in a bench-top microcentrifuge for 30 s. Control cells were spun under identical conditions except that no GTP was added to the solution. Supernatant from both sets of cells was analyzed for NO using a kit from BIOMOL according to the manufacturer’s instructions.
cGMP assays were carried out using 2-day-old cell cultures. Cells were concentrated to approximately 7.66 × 106 cells/ml in order to maximize cGMP production. Cells were exposed to 100 μM GTP for approximately 30 s, then immediately lysed by freezing in liquid nitrogen and thawing. Theophylline (1 mM) was added to the lysate to inhibit phosphodiesterases. Lysate was spun at 16,000 g for 30 min. Control cells were treated in identical fashion except for the addition of GTP. Supernatant from both sets of cells was assayed for cGMP using a kit from Cayman Chemicals according to the manufacturer’s instructions.
Immunofluorescence
Ten milliliters of 2-day-old cells were starved overnight in behavioral buffer then washed 3× in behavioral buffer and concentrated down into 2 ml. Mucocysts were removed by adding Alcian Blue GX to a final concentration of 0.05%, then adding nine volumes of 0.25% proteose peptone [11]. Mucocysts were allowed to precipitate by standing the tube in a rack for 10 min. Supernatant (including cells) was removed from the top of the tube. The cells were then washed 3× in behavioral buffer to remove any remaining mucocysts or Alcian Blue and concentrated down into 3 ml total; 1 ml of cells was set aside as the control cells. Another milliliter of cells was incubated with 100 μM GTP-γ-S. A third aliquot was incubated with 100 μg/ml genistein prior to GTP treatment. Immediately, all three aliquots of cells were fixed in 3.7% formaldehyde (from 37% stock diluted into behavioral buffer) with gentle shaking for 20 min. Cells were washed 3× in 1× TBS/NP40 (Modern Biology) then incubated with a 1:100 dilution of polyclonal antibody in 1× TBS/NP40 for 1.5 h. Cells were again washed 3× in 1× TBS/NP40 then incubated in a 1:100 dilution of fluorescein isothiocyanate (FITC)-conjugated goat anti-rabbit IgG (ICN Biomedicals) for 1.5 h. Cells were washed 3× in 1× TBS before being viewed under a Nikon microscope at 400×. Cells were photographed using a SPOT digital camera using a 10-s exposure for each photograph.
Results
GTP-γ-S is a chemorepellent in Tetrahymena,, with a minimum concentration of 100 μM required for 100% avoidance (Fig. 1). This concentration was used in the inhibition studies that follow as well as in our biochemical studies. We used GTP-γ-S in our experiments rather than GTP to minimize the effects of the ecto-ATPase upon the assays [3]. However, the activity of apyrases and other ectoenzymes may still have degraded some of the GTP-γ-S before it could reach its intended receptor. The concentration of GTP-γ-S required in order to achieve 100% avoidance in this study was 5× higher than that previously published [1]; however, considering that the cell line and growth conditions were different than those published earlier, this finding is not unexpected. The EC50 of GTP-γ-S in this study was approximately 30 μM.
Fig. 1Guanosine-5′-O-(3-thio)triphosphate (GTP-γ-S) is an effective chemorepellent in Tetrahymena. In vivo behavioral bioassays (see “Materials and methods”) were used to show the concentration dependencies for avoidance reactions to GTP-γ-S. The percentage of cells showing avoidance was determined by observation of a single cell after transfer to the test solution. Each trial consisted of ten cells, which were individually scored as to whether or not avoidance occurred. Each point represents the mean ± standard deviation (SD) of at least three trials. Error bars, representing the standard deviation, are shown for each point. Minimum concentration required to give 100% avoidance was 100 μM for GTP-γ-S. This concentration was used in the inhibition studies that follow. The EC50 of this compound was approximately 30 μM
To determine whether a tyrosine kinase activity was involved in GTP avoidance, we used the tyrosine kinase inhibitor, genistein (Fig. 2). Genistein itself did not cause avoidance reactions, nor was it toxic to the cells. Baseline avoidance of ∼ 20% [9] to 100 μM GTP-γ-S was seen at a genistein concentration of 100 μg/ml. The inhibition constant (IC)50 of genistein was approximately 40 μg/ml. Another phytoestrogen, daidzein, served as a control for nonspecific side effects of genistein. As seen in Fig. 2, this compound had no measurable effect on avoidance at the tested concentrations, suggesting that the inhibitory effect of genistein was indeed due to its tyrosine kinase inhibition and not attributable to some side effect of the drug.
Fig. 2The tyrosine kinase inhibitor, genistein, blocks avoidance to 100 μM guanosine-5′-O-(3-thio)triphosphate (GTP-γ-S) in Tetrahymena. The phytoestrogens genistein (closed circles) and daidzein (open circles) were used as inhibitors of avoidance. Baseline avoidance was seen at a genistein concentration of 100 μg/ml. The IC50 of genistein was approximately 40 μg/ml. Daidzein served as a control for nonspecific effects of genistein and had no measurable effect on avoidance at the concentrations tested. Data shown represent the mean +/− standard deviation (SD) for three or more trials
As an additional control for specificity, we tested whether genistein had any effect on the transduction of another chemorepellent, adenosine 5′-O-(3-thio)triphosphate (ATP-γ-S). We used 150 μM ATP-γ-S, a concentration that normally causes 100% avoidance in T. thermophila [12]. When cells exposed to ATP-γ-S were first incubated for 10–15 min in 100 μg/ml genistein, no measurable effect on avoidance was seen. Cells continued to avoid 150 μM ATP-γ-S at a rate of 96.6 + 5.8% (n ≥ 3). Genistein also failed to affect avoidance to the chemorepellent pituitary adenylate cyclase-activating polypeptide (PACAP). When testing 0.1 μM PACAP, which normally causes 100% avoidance in T. thermophila [9], we found that prior incubation with 100 μg/ml genistein did not markedly affect avoidance. Cells continued to avoid 0.1 μM PACAP at a rate of 96.6 + 5.8% (n ≥ 3). These data suggest that tyrosine kinase activation is specifically related to GTP exposure rather than being a general response to chemorepellent exposure.
In an attempt to localize the phosphotyrosines within the cell, immunofluorescence experiments were performed using a polyclonal antiphosphotyrosine antibody. Three separate trials were done with this antibody, and representative photographs are compiled in Fig. 3a–c. GTP-exposed cells (Fig. 3b) showed higher overall fluorescence intensity than did the controls and genistein-treated GTP-exposed cells (Fig. 3a,c). Ciliary staining was seen in the GTP-exposed cells, along with punctuate staining of the cytosol. The control and genistein-treated GTP-exposed cells showed the same cytosolic staining pattern, but ciliary staining was not detected in these control groups, perhaps because the overall fluorescence level of these cells was so low.
Fig. 3Guanosine 5'-triphosphate (GTP) exposure increases tyrosine kinase activity in Tetrahymena. a–c Immunofluorescence labeling of phosphotyrosines in Tetrahymena is evidence of tyrosine kinase activity. Control (a), GTP-exposed (b), and genistein-treated GTP-exposed cells (c) were fixed and labeled with a polyclonal antiphosphotyrosine antibody. GTP-exposed cells showed higher fluorescence intensity than did control cells and cells treated with the tyrosine kinase inhibitor genistein. In addition, GTP-exposed cells showed ciliary staining in addition to punctuate staining of the cytosol. Total magnification 400×. Cell length ∼ 50 μm. d Western blot of whole-cell extract obtained from control and GTP-exposed cells using a polyclonal antiphosphotyrosine antibody shows increased phosphorylation levels in extract taken from GTP-exposed cells (lane 2) relative to extract from control cells (lane 3). A 66-kDa phosphoprotein stained similarly in both the GTP and control lanes, whereas bands of 42, 35, and 21 kDa were more heavily stained in the GTP lane relative to the control lane. Molecular weight markers are shown in the first lane (molecular weights in kDa). A Coomassie-stained sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) run as a loading control showed equivalent staining of proteins in all lanes (not shown)
To determine which proteins were being phosphorylated by the tyrosine kinase in response to GTP-γ-S, we also performed several Western blots of whole-cell extract obtained from control and GTP-γ-S -treated cells using the polyclonal antiphosphotyrosine antibody as a probe. Protein extracts were standardized so that lanes were loaded equally, and a control, Coomassie-stained gel, was also run to control for lane-loading artifacts (data not shown). A representative Western blot is pictured in Fig. 3d. Both GTP-treated and control cells showed similar staining at 66 kDa. However, increased phosphotyrosine levels were seen in the GTP-γ-S-treated cells at 42, 35, and 21 kDa, consistent with tyrosine kinase activity. These bands were also present in the control cell extract; however, the phosphorylation level in these lanes was so low that they were barely detectable with our staining procedure. Additional bands were also seen in both the GTP-exposed and the control lanes; however, they were also too light to be measurable. A more sensitive assay, such as chemiluminescence based Western blot detection, might help to give a more complete profile of the phosphotyrosine-containing proteins shown in this procedure.
In many cells, activation of a tyrosine kinase activates phospholipase C-γ. We used the phospholipase C inhibitor, U73122, to determine whether phospholipase C might be involved in GTP avoidance. GTP avoidance was effectively eliminated at a U73122 concentration of 1 μM. This concentration was ten times lower than that used to inhibit phospholipase C in molluscan ciliary cells [12]. The IC50 of this compound was approximately 0.001 μM. Phospholipase C activates the PKC pathway through the generation of diacylglycerol (DAG) and inositol 1,4,5 trisphosphate (IP3). PKC is then activated by DAG binding in the presence of calcium. To determine whether PKC was involved in GTP avoidance, we used the PKC inhibitor calphostin C, which competes for DAG binding to PKC. In the presence of 10 μM calphostin C, avoidance to 100 μM GTP-γ-S was reduced only to 96.6 +/− 5.8%, compared with 100% avoidance in control cells. This concentration of calphostin C eliminated avoidance to 150 μM ATP-γ-S [13]. Because calphostin C had no measurable effect on GTP avoidance, we concluded that PKC activy is not required for GTP signaling. It is very likely that the two second messengers, IP3 and DAG, are generated by phospholipase C and that PKC is activated, but that PKC targets cellular substrates that are not directly involved in ciliary reversal.
Because calcium signaling is often associated with tyrosine kinase pathways and because calcium influx is associated with GTP exposure [2], we decided to eliminate calcium rom cells using the membrane-permeable calcium chelator 1,2-bis-(o-Aminophenoxy)-ethane-N,N,N',N'-tetraacetic acid, tetra (acetoxymethyl) ester (BAPTA-AM). As seen in Fig. 5a, exposure to this calcium chelator eliminated avoidance in a concentration-dependent manner, with baseline avoidance seen at a BAPTA-AM concentration of 5 μg/ml. This result was certainly not surprising, as all known chemorepellents that have been studied electrophysiologically in Tetrahymena have elicited depolarizations [2, 14, 15] that have been proposed to be linked to calcium. Because our data indicated that phospholipase C was involved in GTP avoidance, we decided to test the hypothesis that internal calcium stores may also contribute to avoidance, consistent with the liberation of IP3 from the plasma membrane. We used an inhibitor of the endoplasmic reticulum (ER) calcium ATPase, thapsigargin, to deplete ER calcium stores to determine whether these stores were necessary for avoidance. Baseline avoidance to GTP was seen at a thapsigargin concentration of 1,000 nM (Fig. 5b). The IC50 of thapsigargin was approximately 1 nM.
NO is another second messenger sometimes associated with tyrosine kinases [5, 17] and often associated with calcium signaling [5, 18]. In addition, NO has been found to be a critical second messenger in the Tetrahymena response to both ATP [13] and PACAP-38 [18]. To determine whether NO was involved in GTP signaling, we used the NOS inhibitors 1400W (Fig. 6a) and L-NMMA (Fig. 6b). Both inhibitors blocked avoidance to 100 μM GTP-γ-S in Tetrahymena, with baseline avoidance being reached at 100 nM for 1400W (Fig. 6a) and 50 μM for L-NMMA (Fig. 6b). The IC50 of 1400W was near 0.1 nM, whereas L-NMMA was approximately 3 μM.
To confirm the activity of NOS in GTP avoidance, we used the Quantizyme NO assay to determine whether there was a difference in NO metabolism between control and GTP-stimulated cells. Cells stimulated with 8 mg/ml GTP had a 146 +/− 4.7% increase in NO levels over control cells, consistent with the inhibitor studies (n = 3).
In many cells, NO activates guanylyl cyclase, which then produces cGMP. Previous studies by Christensen et al. [20] described an NO-linked, possibly soluble guanylyl cyclase activity in T. thermophila. More recent studies, reviewed by Linder and Schultz [20], described a membrane-associated and calcium-dependent guanylyl cyclase in these organisms. To determine whether any guanylyl cyclase isoform was involved in GTP avoidance, we used NS2028, an inhibitor of guanylyl cyclase (Fig. 7a), as well as Rp-8-bromo-cGMPs, a competitive inhibitor of cGMP (Fig. 7b), in behavioral assays. NS2028 and Rp-8-bromo-cGMPs both blocked avoidance to 100 μM GTP-γ-S in Tetrahymena. Baseline avoidance was obtained at 10 nM NS2028 (Fig. 7a) and at 50 μM Rp-8-bromo-cGMPs (Fig. 7b). The IC50 of NS2028 was approximately 0.05 nM and of Rp-8-bromo-cGMPs near 7 μM. To confirm these results biochemically, we performed an EIA assay to determine whether GTP exposure resulted in elevated cGMP levels within Tetrahymena. Exposure to 5 mg/ml GTP resulted in a 1,119 +/− 4.2% increase above control cGMP levels (n ≥ 3), consistent with the hypothesis that GTP avoidance is linked to a guanylyl cyclase.
Based on the data we collected, we put together a provisional model of GTP signaling (Fig. 8). In our model, GTP binds to a receptor, which activates tyrosine kinase while interacting with a membrane calcium channel, causing a depolarization. Phospholipase C is activated, generating IP3, which allows calcium efflux from ER stores. The high cytosolic calcium interacts with some (unknown) isoform of NOS, guanylyl cyclase, and other calcium-binding proteins, ultimately resulting in ciliary reversal. Whereas some of the relationships between second messengers are still unknown, the model has been put together to stimulate thought and discussion and to make some order out of a complex pathway.
Discussion
The data we have compiled here are consistent with the hypothesis that the previously described GTP receptor [1] signals through a tyrosine kinase (Fig. 2, 3). The GTP signaling pathway also involves phospholipase C (Fig. 4), intracellular calcium (Fig. 5), NOS (Fig. 6), and guanylyl cyclase (Fig. 7). The proposed GTP signaling pathway is outlined in Fig. 8.
Fig. 4The phospholipase C inhibitor 1-(6-(17β-3-methoxyestra-1,3,5(10)-trien-17-yl) amino)hexyl)-1H-pyrrole-2,5-dione (U73122) blocks avoidance to 100 μM guanosine-5′-O-(3-thio)triphosphate (GTP-γ-S) in Tetrahymena. Baseline avoidance was reached at a U73122 concentration of 1 μM. The inhibition constant IC50 of this compound was near 0.001 μM. Data shown is mean +/− standard deviation (SD) of three or more trialsFig. 5Intracellular calcium is required for guanosine 5'-triphosphate (GTP) avoidance in Tetrahymena. a The membrane-permeable calcium chelator 1,2-bis-(o-Aminophenoxy)-ethane-N,N,N',N'-tetraacetic acid, tetra (acetoxymethyl) ester (BAPTA-AM) blocks avoidance to 100 μM GTP-γ-S in Tetrahymena. Baseline avoidance was reached at a BAPTA-AM concentration of 5 μg/μl. The inhibition constant IC50 of this compound was near 0.5 μg/μl. Data shown is mean +/− standard deviation (SD) of three trials. b The endothelial reticulum (ER) calcium adenosine triphosphatase (ATPase) inhibitor thapsigargin also blocks avoidance to 100 μM guanosine-5′-O-(3-thio)triphosphate (GTP-γ-S) in Tetrahymena.. Baseline avoidance was reached at a thapsigargin concentration of 1,000 nM. The IC50 of this compound was near 1 nM. Data shown is mean +/− standard deviation (SD) of three or more trialsFig. 6Nitric oxide synthase (NOS) activity is required for guanosine 5'-triphosphate (GTP) avoidance in Tetrahymena. a The NOS inhibitor 1400W blocks avoidance to 100 μM guanosine-5′-O-(3-thio)triphosphate (GTP-γ-S) in Tetrahymena. Baseline avoidance was reached at a 1400W concentration of 100 nM. The inhibition constant IC50 of this compound was near 0.1 nM. Data shown is mean +/− standard deviation (SD) of three trials. b The NOS inhibitor NG-monomethyl-L-arginine (L-NMMA) also blocks avoidance to 100 μM GTP-γ-S in Tetrahymena. Baseline avoidance was reached at an L-NMMA concentration of 10 μM. The inhibition constant IC50 of this compound was near 3 μM. Data shown is mean +/− standard deviation (SD) of at least three trialsFig. 7Guanylyl cyclase activity is required for guanosine 5'-triphosphate (GTP) avoidance in Tetrahymena. a 4H-8-bromo-1,2,4-oxadiazolo(3,4-d) benz(b)(1,4)oxazin-1-one (NS2028), an inhibitor of guanylyl cyclase, blocked avoidance to 100 μM guanosine-5′-O-(3-thio)triphosphate (GTP-γ-S) in Tetrahymena. Baseline avoidance was obtained at 10 nM. The inhibition constant IC50 of NS2028 was approximately 0.05 nM. Data shown is mean + standard deviation (SD) of three trials. b Rp-8-Bromoguanosine-3′,5′-cyclic monophosphorothioate (Rp-8-Br-cGMPs), a competitive inhibitor of guanosine 3′3;5′monophosphate (cGMP), also blocked avoidance to 100 μM GTP-γ-S in Tetrahymena. Baseline avoidance was obtained at 50 μM. The IC50 of Rp-8-Br-cGMPs was approximately 7 μM. Data shown is mean + standard deviation (SD) of three or more trialsFig. 8Current model of guanosine 5'-triphosphate (GTP) signaling. Based on data obtained in this experiment, GTP appears to signal through a receptor linked to a tyrosine kinase. Phospholipase C, intracellular calcium release, nitric oxide (NO) production, and guanylyl cyclase are all involved in GTP avoidance. Some of the relationships between pathway components remain unknown. This model is based on the data presented in this paper, along with data obtained from the literature [26, 32, 33]
GTP is the first chemorepellent we have studied that does not signal through a G-protein-linked receptor, unlike ATP [13] and PACAP [18, 21]. In contrast to other repellents, GTP signaling is unaffected by either GDP-β-S or pertussis toxin (unpublished data). GTP is also the only one of these three repellents whose signaling is eliminated by genistein (Fig. 2; see “Results”). Previously published cross-adaptation data [2] indicated that GTP and ATP signal through different receptors. These data are consistent with the previously published literature and add the observation that both receptors and second-messenger pathways for these two repellents appear to be different.
Multiple target proteins are phosphorylated in response to GTP exposure (Fig. 3d), yet the proteins remain unidentified except for molecular weight. Phosphotyrosine immunolocalization does not help us identify these proteins; however, the ciliary staining (Fig. 3b) opens up the possibility of direct interaction between tyrosine kinase activity and ciliary reversal. This is worthy of note, as Christensen et al. [22] report a similar increase in ciliary phosphotyrosine labeling after exposure to the chemoattractant insulin. However, in their report, the main protein that was phosphorylated was a 66 kDa protein, which they discovered was homologous to the insulin receptor. In the case of GTP exposure, we saw no increase in labeling of the 66 kDa protein (Fig. 3d). Taken together, these data raise the possibility that there are multiple tyrosine kinase pathways that act on cilia to increase forward swim speed in the case of a chemoattractant, or to cause ciliary reversal in the case of a chemorepellent. Becausxe there were multiple phosphotyrosine bands in our Western blot (Fig. 3d) and ciliary as well as cytosolic staining in our immunofluorescence (Fig. 3b), we see that GTP exposure has both ciliary and cytosolic effects. Ciliary reversal is seen immediately upon GTP exposure; however, other effects of GTP exposure, such as mitosis, are seen hours after GTP exposure [4]. Perhaps the cytosolic target proteins are involved in other, longer-term effects of GTP, such as mitosis.
Many tyrosine kinase pathways involve phospholipase C. In various Tetrahymena species, evidence for phospholipase C involvement has been seen in stomatin-induced differentiation [24] and in commitment to cell survival or death [25]. Studies by Leondaritis and Galanopoulou [26] suggest that Tetrahymena possess a functional phosphatidylinositol signaling system that is similar to higher eukaryotes. Indeed, in our previous studies of PACAP [10] and ATP [13], phospholipase C involvement is also implicated. In our current study, we found that U73122 effectively eliminated GTP avoidance (Fig. 4), indicating that phospholipase C signaling is involved in behavioral avoidance. However, our calphostin C data (see “Results”) indicate that PKC, a common downstream target of phospholipase C, is not required for GTP avoidance. IP3, a second messenger generated by phospholipase C, is likely involved in GTP signaling. Although we could not test IP3 involvement directly using our behavioral assay, the fact that the ER calcium ATPase inhibitor thapsigargin eliminated GTP avoidance (Fig. 5b) is indirect evidence that IP3 may be binding to the ER and causing release of calcium from internal stores.
Calcium is a ubiquitous signaling molecule and has been implicated in ciliary reversal in Tetrahymena. It was no surprise, then, that BAPTA-AM eliminated GTP avoidance (Fig. 5a), as it has previously been shown to eliminate avoidance to PACAP [18] and ATP [13]. Calcium is likely to play multiple roles in signaling. One possible scenario is the direct interaction of calcium with ciliary motor proteins. For example, inner arm dynein 1 (I1) is required for calcium-dependent ciliary reversals in T. thermophila [27]. In this study, a “calcium sensor,” which interacts with I1, was postulated. This calcium sensor protein remains to be isolated.
Intracellular calcium may also play other, less direct, roles in GTP avoidance. Indeed, in the protozoan parasite Leishmania donovani, both NOS and guanylyl cyclase are activated by intracellular calcium [28]. Both NOS (Fig. 6) and guanylyl cyclase (Fig. 7) activity are required for GTP avoidance. Previous studies that implicate NOS and guanylyl cyclase in Tetrahymena [13, 18, 19] do not indicate the type of NOS or guanylyl cyclases involved, though Christensen et al. [19] give evidence for a soluble guanylyl cyclase. In L. donovani, there is evidence for a constitutive, neuronal-type NOS that then activates a soluble guanylyl cyclase [28]. Both of these enzymes are activated by intracellular calcium. Our data would be consistent with a similar mechanism in Tetrahymena, as proposed in our model of GTP signaling (Fig. 8). However, neither a soluble guanylyl cyclase nor an nNOS isoform have been purified from Tetrahymena to date.
Calcium-binding proteins, such as calmodulin, may also be involved in GTP signaling in Tetrahymena, either by interacting with enzymes that generate second messengers or by interacting with the molecular motors responsible for ciliary reversal. Previous studies [29, 30] indicate that calmodulin activates a ciliary guanylyl cyclase in this organism. Our studies leave open the possibility that this cyclase, activated by calcium/calmodulin, is involved in GTP signaling. In addition to this enzyme, Hirano-Ohnishi and Watanabe [31] reported a calmodulin-dependent phosphorylation of ciliary beta tubulin in Tetrahymena, which they believe to be involved in ciliary reversal. Elongation factor 1α, which functions in protein translation, also interacts with ciliary calmodulin [32]. Whereas this would not necessarily function in ciliary reversal, it may modulate some of the longer-term effects of GTP. Finally, Ueno et al. [33] report that ciliary calmodulin interacts with proteins that are homologues of radial spoke proteins in Chlamydomonas, further implicating calmodulin directly in ciliary reversal. We have added some of these proteins to our model of GTP signaling (Fig. 8), though there are doubtless more proteins to be discovered.
In this study, we used behavioral assays and pharmacological inhibitors to explore the intracellular mechanisms employed in GTP signaling in T. thermophila. Because pharmacological inhibitors often have unknown side effects, we used multiple inhibitors when available. Some of these inhibitors had to be used at higher concentrations in our study than have been previously published for mammalian cells. Perhaps this is because of the differences in the structure of the Tetrahymena proteins compared with their mammalian counterparts. Recognizing the potential pitfalls of relying solely upon pharmacological data, we supplemented behavioral assays with other kinds of tests, such as Western blots, immunofluorescence, and EIA when available. In all cases, the additional tests confirmed the data we originally obtained using pharmacological inhibitors.
Taken together, our data indicate that a number of enzymes are involved in GTP signaling. However, further experimentation is needed to discern the interrelationships between enzymes in the pathway and to answer the myriad questions that remain. For example, are guanylyl cyclase and NOS truly activated by calcium in Tetrahymena? Would calcium chelation abolish their activity? Is there a soluble guanylyl cyclase in Tetrahymena? What NOS isoforms do Tetrahymena possess? Is tyrosine phosphorylation required for either NOS or guanylyl cyclase activity? Are any additional proteins, particularly ciliary proteins, involved in GTP signaling? Are all of the components of the pathway located in the cilia? These and many other questions remain to be answered. One question we have begun to answer is whether intracellular calcium is required for tyrosine kinase activity. Recent immunofluorescence shows no difference in phosphotyrosine levels between GTP-treated cells and GTP-treated cells that had been pretreated with BAPTA-AM (unpublished data). Similarly, calcineurin (PP2B) does not appear to be involved in GTP signaling, as ascomycin treatment had no effect on GTP avoidance (unpublished data). Endothall, a PP2A inhibitor, did inhibit avoidance (unpublished observation), consistent with observations by Deckman and Pennock [33] that PP2A is involved in ciliary reversal. Further experimentation will help us determine the interrelationship of pathway components and better establish the mechanism by which chemorepellents signal in Tetrahymena.

chemorepellent
extracellular nucleotide
purine metabolism


Pathological and Biological Differences Between Screen-Detected and Interval Ductal Carcinoma in situ of the Breast

Background The incidence of ductal carcinoma in situ (DCIS) has risen dramatically with the introduction of screening mammography. The aim was to evaluate differences in pathological and biological characteristics between patients with screen-detected and interval DCIS.
With the introduction of widespread screening mammography, the incidence rates of ductal carcinoma in situ (DCIS) have risen dramatically in Western Europe and North America.1–3 DCIS now accounts for nearly 20% of all screen-detected breast malignancies.4
As a consequence, treating physicians are confronted with a cumulative caseload because it is not known how many women with screen-detected DCIS will develop an invasive carcinoma in their lifetimes. The proportion of untreated cases of DCIS that would progress to invasive malignancy has been difficult to evaluate, because DCIS is usually excised when detected. Because DCIS is a nonobligatory precursor to invasive carcinoma, and, therefore, has a relatively benign nature, screen-detected DCIS has been argued to represent an overdiagnosis.5,6 This argument is supported by autopsy studies in which the median prevalence of DCIS was 8.9%, suggesting some cases do not progress to clinically significant lesions in a patient’s lifetime.7 On the contrary, patients with DCIS treated with biopsy alone in the premammography era had a higher rate of subsequent occurrences (14–50%) of invasive breast cancer than expected.8,9 Large clinical trials, in which patients had been treated with lumpectomy alone, have also indicated that DCIS can recur as invasive ductal carcinoma.10,11
Screen-detected DCIS is more often presented as linear branching microcalcifications on mammography than symptomatic DCIS.12 The screen-detected group in the previously mentioned study had a larger proportion of patients with comedocarcinoma. Therefore, it was suggested that linear branching microcalcifications were related with a more aggressive type of DCIS.12 This is confirmed in other reports that have indicated that linear branching microcalcifications on mammography are associated with high grade DCIS.13,14
We believe that screen-detected DCIS is more often associated with suspicious microcalcifications representing high-grade DCIS, which has been detected before it has had the chance to progress to invasive cancer. Therefore, it is hypothesized that screen-detected DCIS is biologically more aggressive than interval DCIS. To compare screen-detected DCIS with interval DCIS in such a retrospective study, the clinicopathological and biological characteristics of both groups were evaluated for differences. Screen-detected DCIS was classified as DCIS detected by screening mammography, when the examination from two years earlier failed to reveal an abnormality. Interval DCIS was classified as DCIS detected within the two-year interval between two subsequent screening rounds, when the earlier examination failed to reveal an abnormality. Age, tumor size, and pathological grade were studied for their known relation with local recurrence. Finally, the expression of established prognostic biomarkers in breast cancer was studied by immunohistochemistry for estrogen receptor (ER), progesterone receptor (PR), Her2/neu, p53, and cyclin D1.
PATIENTS AND METHODS
Patients and Tumors
The Dutch screening program for breast cancer has been gradually implemented in the North Netherlands since 1991. It offered biennial mammography to women 50–69 years old, and since 1999 women 70–74 years old have also been included. Women received mammography in the cranio-caudal and medio-latero-oblique direction for each breast. Two radiologists evaluated the mammograms by a double independent reading.
From January 1992 to December 2001, 128 consecutive patients were treated for pure DCIS at our institution. To identify patients for inclusion in the study, all women who had actually attended the screening program at least two subsequent rounds with a two-year interval at the time of diagnosis were considered as attenders. Patients who had skipped one or more screening rounds previous to the diagnosis and patients who had not been attending the program at all were considered nonattenders. Patients’ records were checked to obtain this information, and if there was no information regarding the participation of the screening program at the time of diagnosis the general practitioner was consulted. Out of the 128 consecutive patients, 102 attenders and 26 nonattenders could be identified. For immunohistochemistry, patients were selected on the availability of sufficient paraffin-embedded tissue. Thirteen out of the 26 nonattenders and 74 out of the 102 attenders remained, respectively, for evaluation of Her2/neu overexpression, estrogen receptor (ER) expression, progesterone receptor (PR) expression, p53 expression, and cyclin D1 expression using tissue microarray analysis as part of a project protocol that had been approved by the medical ethics committee. The patients in the study-group (n = 74) were divided into two groups. Patients with DCIS that had been detected by screening mammography were classified as screen-detected patients, when the examination two years earlier failed to reveal an abnormality (n = 54). Patients with DCIS that had been detected within the two-year interval between two subsequent screening rounds were classified as interval patients, when the earlier examination failed to reveal an abnormality (n = 20).
Mammography and Pathological Assessment
Mammographic and pathological characteristics were derived from mammography and pathological reports, respectively. Data were delivered and evaluated anonymously. If data were missing, mammography and pathological slides were reevaluated. Mammographic appearances were scored as microcalcifications, a mass, a combination of the two, or as occult. Microcalcifications were scored as fine granular, coarse granular, or as linear branching. Pathological size had been estimated, and the grade had been scored according to the European Pathologists Working Group (EPWG15) and according to the Van Nuys classification.16
Tissue Microarray Construction
Slides from all blocks were evaluated for representative areas with DCIS, and tissue microarrays were prepared as described earlier.17 In brief, the most representative area of DCIS was marked on the original hematoxylin and eosin (H&E) stained section. With this marked section as an orientation, three 0.6-mm punches were taken from the selected area in the donor blocks and mounted in a recipient block containing approximately 110 biopsies, using a manual tissue microarray device (Beecher Instruments, Silver Springs, MD). The presence of DCIS in the arrayed samples was verified on hematoxylin eosin stained sections.
Immunohistochemistry
For immunohistochemistry, 3 μm sections of the paraffin-embedded tissue arrays were deparaffinized in 2 changes of xylene for 5 minutes each and gradually rehydrated through changes of graded ethanol from 100% to distilled water. Antigen retrieval methods and antibodies are summarized in Table 1. The endogenous peroxidase reaction was blocked by incubating the sections in 3% perhydrol for 30 minutes. Primary antibodies were diluted in phosphate-buffered saline (PBS) containing 1% bovine serum albumin and incubated at room temperature for 1 hour. Samples were then washed in PBS and incubated with secondary and tertiary antibodies. For visualization of the antibody-antigen complex, the diaminobenzidine tetrahydrochloride/peroxidase reaction was used. After a final wash with distilled water, sections were counterstained with hematoxylin. Sections were dehydrated through rising concentrations of ethanol and mounted. Immunohistochemistry was successful in 81/87 cases for Her2/neu staining, 73/87 cases for ER staining, 71/87 for PR and cyclin D1 staining, and 70/87 for p53 staining.
TABLE 1.Antigen retrieval methods and antibodiesAntibodyCloneSupplierDilutionAntigen retrievalSecondary antibodySupplierTertiary antibodySupplierER6F11VentanaaTris/HCL 0.1M (pH 9.5) 30’ 98°C microwaveRAMBIODakoSARBIODakoPR1A6VentanaaTris/HCL 0.1M (pH 9.5) 30’ 98°C microwaveRAMBIODakoSARBIODakoHer-2/NeuCB11VentanaaTris/HCL 0.1M (pH 9.5) 30’ 98°C microwaveRAMBIODakoSARBIODakop53BP-53-12-1Biogenix1:800Tris/HCL 0.1M (pH 9.5) 30’ 98°C microwaveRAMBIODakoSARBIODakoCyclin D1SP4Neomarkers1:50Tris/HCL 0.1M (pH 9.5) 30’ 98°C microwaveRAMBIODakoSARBIODakoa Prediluted by supplier.ER, estrogen receptor; PR, progesterone receptor;; RAMBIO, rabbit anti-mouse biotin; SARBIO, swine anti-rabbit biotin.
Evaluation of Immunohistochemical Staining
All slides stained for molecular markers were read by two authors (MdR and BvdV). The slides were randomly reviewed by a third author (JW) and in case of disagreement between the other two authors. ER, PR, and p53 were graded based on the percentage of cells showing positive nuclear staining in the ducts with DCIS. ER and PR were considered positive if nuclear staining was present in ≥10% of the cases, and p53 was considered positive in case of a substantial percentage of positively stained nuclei (>30%). Her2/neu expression was graded as recommended by the HercepTestTM scoring guidelines: 0: no staining at all or membrane staining in <10% of tumor cells; 1+: a faint/barely perceptible partial membrane staining in >10% of the tumor cells; 2+: weak to moderate complete membrane staining in >10% of tumor cells; 3+: strong complete membrane staining in >10%. Her-2/neu was considered to be overexpressed if the score was 3+. Cyclin D1 expression was scored using a semiquantitative system as described by Vos et al.18 This system was based on the staining intensity scored as 0 (none), 1 (weak), 2 (moderate), and 3 (strong), and the percentage of positive tumor cell nuclei scored as 0 (0%), 1 (1–25%), 2 (25–50%), 3 (50–75%), and 4 (>75%). The cyclin D1 staining score was calculated as the sum of the intensity and the percentage of positive tumor cells.
Statistical Analysis
Differences in clinicopathological characteristics between screen-detected and interval patients with DCIS in the study group, and between the study group and the excluded group of patients were analyzed by chi-square analysis. Differences in clinicopathological and biological characteristics between the study group and the nonattenders were also analyzed by chi-square analysis. Differences in age were tested by using the Mann-Whitney U test. Univariate analyses, investigating differences in pathological and biological features, was performed by logistic regression, using screen detection as a dependent variable. Multivariate analyses were performed with a logistic-regression model. The elimination of variables in a stepwise manner identified the statistically significant pathological and biological parameters. A p value of ≤.050 was considered as significant. All calculations were performed with SPSS 12.01 (SPSS inc., Chicago, IL).
RESULTS
Table 2 shows the clinicopathological characteristics of the patients in the study group (n = 74). Screen-detected DCIS was less often symptomatic than interval DCIS (p < .001). Five patients (25%) in the interval group had no objective signs on presentation; all patients had felt a lump in the breast that could not be verified on clinical examination. On mammography, microcalcifications were more often seen in screen-detected DCIS (p = .002). Screen-detected DCIS was more often presented as linear branching (44.9%) and coarse granular (55.9%) microcalcifications than interval DCIS (p<0.001). High-grade DCIS (Van Nuys, 53.1%, p = .025) was also more often observed in screen-detected DCIS.
TABLE 2.Clinicopathological characteristics of the patients in the study group and differences between screen-detected and interval patientsClinicopathological characteristicsScreen-detected n = 54Interval n = 20p-valueaAge (mean), years58.960.7.187Family history of breast cancer.055  Yes8 (14.8)7 (35)  No46 (85.2)13 (65)Signs  Palpable mass5 (9.3)6 (30)<.001  Nipple discharge2 (3.7)9 (45)  Mastodynia1 (1.9)0 (0)  No objective signs46 (85.1)5 (25)Mammography.002  Microcalcifications46 (85.2)10 (50)  Mass2 (3.7)6 (30)  Combination mc’s and mass6 (11.1)4 (20)Microcalcifications <.001  Linear branching22 (44.9)4 (28.6)  Coarse granular27 (55.1)4 (28.6)  Fine granular0 (0)6 (42.9)Mammographic size.183  ≤2 cm21 (42.6)12 (60)  >2 cm33 (57.4)8 (40)  BCS23 (42.6)8 (40).841  Mastectomy31 (57.4)12 (60)Tumor size.787  <16mm19 (35.2)6 (30)  16–40mm17 (31.5)8 (40)>40 mm18 (33.3)6 (30)Grade (EPWG).229  14 (7.5)4 (20)  229 (53.7)11 (55)  321 (38.9)5 (25)Grade (Van Nuys).025  14 (7.4)6 (30)  224 (44.4)9 (45)  326 (53.1)5 (25)Mann-Whitney U test.Values between parentheses are percentages.BCS, breast conserving surgery; EPWG, European Pathologist Working Group.a Chi-square analyses.
Differences in clinicopathological characteristics between the study-group (n = 74) and the group of patients that had been excluded (n = 28) because of insufficient paraffin embedded tissue are outlined in Table 3. There was no marked difference in age, microcalcifications, tumor size, and pathological grade according to the EPWG classification between both groups. The excluded group of patients represented a relatively large proportion of low-grade DCIS according to the Van Nuys classification (p < .001) in comparison with the TMA group.
TABLE 3.Comparison of clinicopathological characteristics between the study group and the group of patients that were excluded because of insufficient paraffin-embedded tissueClinicopathological characteristicsStudy group n = 74Excluded n = 28p-valueaAge (mean)59.661.5.381Microcalcifications (n = 86).063  Linear branching26 (41.3)5 (25)  Coarse granular31 (49.2)9 (45)  Fine granular6 (9.5)6 (30)Tumor size.458  <16mm25 (33.8)7 (25)  16–40mm25 (33.8)9 (32.1)  >40 mm24 (32.6)12 (42.9)Grade (EPWG).184  18 (10.8)6 (21.4)  240 (54.1)10 (35.7)  326 (35.1)12 (42.9)Grade (Van Nuys)<.001  110 (13.5)15 (53.6)  233 (44.6)6 (21.4)  331 (41.9)7 (25)Mann-Whitney U test.Values between parentheses are percentages.EPWG, European Pathologist Working Group.a Chi-square analyses.
There were no differences in clinicopathological and biological characteristics between the study group and the nonattenders (n = 13), except the fact that nonattenders were younger than the patients in the study group (55.9 years versus 59.6 years; p = .042).
Table 4 displays the relation among pathological characteristics, biological marker expression, and mode of detection in the study group. Univariate logistic regression analysis indicated that in screen-detected DCIS Her2/neu is more often overexpressed (odds ratio [OR] = 6.5; 95% confidence interval [CI] 1.3–31.0; p = .020). Interval DCIS is more frequently positive for PR staining (OR = 0.3; 95% CI 0.1–1.0; p = .042) and is related to low pathological grade according to the Van Nuys classification (OR = 7.3; 95% CI 1.6–33.3; p = .010). In multivariate logistic regression, including pathological grade according to the EPWG and Van Nuys classification, Her2/neu overexpression and PR expression in the model, Her2/neu overexpression was the only independent indicator for screen-detected DCIS (OR = 12.8; 95% CI 1.6–104.0; p = .018).
TABLE 4.Univariate analysis of pathological and biological characteristics in screen-detected versus interval DCIS in the study groupPathological and biological featuresScreen-detected n = 54Interval n = 20OR by screen-detected95% CIp-valueTumor size  <16mm19 (35.2)6 (30)0.80.20.744  16–40mm17 (31.5)8 (40)1.10.20.827  >40 mm18 (33.3)6 (30)1Grade (EPWG)  14 (7.5)4 (20)3.8000.50.377  229 (53.7)11 (55)1.7030.70.124  321 (38.9)5 (25)1Grade (Van Nuys)  14 (7.4)6 (30)7.31.6  224 (44.4)9 (45)1.60.50.416  326 (53.1)5 (25)11.60.010Her2/neu (n = 68)  Positive29 (60.4)2 (10)6.51.3–31.00.020  Negative19 (39.6)18 (90)1ER(n = 62)  Positive33 (75)16 (88.9)0.4  Negative11 (25)2 (11.1)10.1–1.90.236PR (n = 60)  Positive18 (42.9)13 (65)0.3  Negative24 (57.1)5 (35)10.1–1.00.042p53 (n = 60)  Positive10 (24.4)4 (21.1)0.8  Negative31 (75.6)15 (78.9)10.2–3.10.776Cyclin D1 (n = 60)  Positive29 (69.1)13 (72.2)0.90.3–2.90.806  Negative13 (30.9)5 (27.8)1Univariate analysis using logistic regression.Figures in parentheses are percentages.OR, odds ratio; EPWG, European Pathologist Working Group; ER, estrogen receptor; PR, progesterone receptor. 95% CI, 95% confidence interval.
DISCUSSION
Approximately 1 in every 1300 screening mammography examinations leads to a diagnosis of DCIS.4 Data from a large trial and service screening programs in the United Kingdom, the Netherlands, Australia, and the United States have demonstrated that a woman attending prevalence screen has a 19 times greater chance of having a progressive DCIS or an invasive tumor diagnosed than of having a nonprogressive DCIS diagnosed.19 It is questioned what to do with the high detection rate of screen-detected DCIS. It was hypothesized that screen-detected DCIS is biologically more aggressive than interval DCIS because suspicious microcalcifications, detected by the screening program, will probably more frequently represent high-grade DCIS. Therefore screen-detected DCIS was characterized pathologically and biologically to determine whether screen-detected DCIS differed from interval DCIS. The results of this study indicate that screen-detected DCIS is pathologically (OR = 7.3; 95% CI 1.6–33.3; p = .010) and biologically (OR = 12.8; 95%CI 1.6–104.0; p = .018) more aggressive than interval DCIS. Indeed screen-detected DCIS was related with more suspicious microcalcifications (p < .001). DCIS detected by a prevalence screen was pathologically and biologically comparable to DCIS detected in later rounds (data not shown) suggesting prevalence and incident cases to both be of clinical relevance.
The relative incidence of high-grade DCIS in our series of screen-detected patients was 53%, which is comparable to the incidence of high-grade DCIS in a screening population from the Netherlands Cancer Institute (47%).20 Much data point out that poorly differentiated or high-grade DCIS lesions have a greater potential to progress to invasive disease than low-grade DCIS.21 High grade is also an independent risk factor of local recurrence after lumpectomy for DCIS, and approximately 50% of these recurrences are invasive cancers.22,23 There are no studies available comparing screen-detected with interval DCIS in a group of patients that had all been attending the screening program. Reports on screen-detected DCIS regarding histopathological grade vary markedly describing a higher incidence of low grade,24 no difference,25 or a higher incidence of high grade12,26,27 in screen-detected DCIS. In these reports screen-detected DCIS is compared to symptomatic DCIS or to DCIS detected in a period before the screening program was introduced. In the present study, a higher incidence of high-grade lesions, which were classified according Van Nuys (OR = 7.3; 95% CI 1.6–33.3; p = .010) classification, was found in screen-detected DCIS, indicating a higher malignant potential in screen-detected DCIS. These results are consistent with the results from the studies of Evans et al.26 and Kessar et al.27
DCIS lesions from patients in the study group were compared to DCIS lesions from patients who had not attended the screening program. Out of the 26 nonattenders, there were only 13 patients from whom sufficient paraffin-embedded tissue was available. Using chi-square analysis there were no differences in pathological and biological characteristics between the two groups. The difference in age could be explained by the fact that the nonattenders group also contained patients under 50-years of age. From these analyses it seems that DCIS in nonattenders is not pathologically and biologically more aggressive than DCIS in attenders of the screening program. However, because of the very small number of patients in the nonattenders group no hard conclusions can be drawn.
Her2/neu overexpression has been found to correlate with various pathologic and biological factors believed to be associated with more aggressive behavior; high grade, presence of necrosis, ER and PR negativity, and overexpression of Ki-67 (indicating an increased proliferation rate) are features that are strongly related with Her-2/neu overexpression.28–30 The report of Walker et al.24 displayed a Her-2/neu expression of 59% in symptomatic DCIS and of 42% in mammographically detected DCIS. Another study by Idvall et al.25 reported no difference in Her-2/neu expression between DCIS before and after introduction of mammographic screening. In this present study Her2/neu overexpression was the only independent feature to be related with screen-detected DCIS in multivariate analysis (OR = 12.8; 95%CI 1.6–104.0; p = .018), which indicates a more aggressive profile of screen-detected DCIS when compared to interval DCIS.
Although the statistical methods used were univariate and multivariate analysis, the numbers in both groups are small, which explains the broad 95% CI. The small numbers are due to the selection of patients in this study for study period, attendance of screening rounds, and availability of sufficient paraffin-embedded tissue. Clearly, further studies with larger populations are needed to elucidate the relative significance of the Her2/neu overexpression in women with screen-detected DCIS. Although 28 out of 102 patients were excluded because of lack of sufficient paraffin-embedded tissue, there is no reason to assume that this exclusion results in a significant selection bias. Apart from pathological grade according to Van Nuys, there were no differences in clinicopathological characteristics between the study group and the group of excluded patients. The group of excluded patients displayed a relatively large amount of low-grade DCIS according to Van Nuys (53.6%, p < .001), which is mainly derived from the interval group (n = 10, data not shown). If all patients would have been included the relation of pathological grade and probably Her2/neu expression with screen-detected patients would be even more significant. The inclusion of patients that actually took part in the screening program was necessary to analyze differences between screen-detected and interval DCIS, which, to our knowledge, has not been performed previously.
Expression of ER, p53, and cyclin D1 was not related to screen-detected or interval DCIS. There was, however, a relation between screen-detected DCIS and PR negativity in univariate analysis (OR = 0.288; 95%CI 0.087–0.957; p = .042). Other studies could not demonstrate a relation of screen-detected DCIS with the expression of the aforementioned markers.12,24,25 In a review by Boland et al.31 ER and PR positivity are related to low-grade DCIS, whereas p53 and cyclin D1 expression are associated with high grade. The fact that screen-detected DCIS is associated with PR negativity provides indirect evidence for the presence of a more aggressive tumor biology. Obviously, PR expression is related to Her2/neu expression, because PR expression was not significant in multivariate analysis.
Ultimately, the question is how we should interpret these findings. The authors think the results from this study represent no evidence to alter patient management and screening recommendations. Instead, they should rather be regarded as support of current clinical practice in DCIS of the breast. They confirm that every DCIS should be treated until we are able to identify DCIS that will progress to invasive cancer if left untreated.
In conclusion, since the advent of screening, the increased incidence of DCIS has raised concerns about the possibility of overdiagnosis of DCIS. This study has shown that screen-detected DCIS has a more aggressive tumor profile than interval DCIS. Therefore, screen-detected DCIS should not be regarded as an overdiagnosis per se, and every woman diagnosed with DCIS by mammographic screening should be treated properly according to existing guidelines or standards of care.

screening
ductal carcinoma in situ
immunohistochemistry
biological markers
breast neoplasm