NIH CLINICAL CENTER GRAND ROUNDS
Episode 2009-019
Time: 1:01:46
Recorded June 3, 2009
Genomic and Transcriptional Evolution of Metastatic Melanoma: A Case Study
Ena Wang, MD
Staff Scientist and Director of Molecular Science, Infectious Diseases and Immunogenetics Section,
Department of Transfusion Medicine, CC
Biomarkers of Parkinson Disease and Related Disorders
David S. Goldstein, MD
Senior Investigator and Chief,
Clinical Neurocardiology Section, NINDS
ANNOUNCER: Discussing Outstanding Science of the Past, Present and Future - this is NIH Clinical Center Grand Rounds.
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ANNOUNCER: Greetings and welcome to NIH Clinical Center Grand Rounds, recorded June 3, 2009. We have two speakers on today's podcast. Dr. Ena Wang, staff scientist and Director of the Molecular Science, Infectious Diseases and Immunogenetics section at the Clinical Center's Department of Transfusion Medicine will discuss "Genomic and Transcriptional Evolution of Metastatic Melanoma, a Case Study. She will be followed by Dr. David S. Goldstein, Senior Investigator and Chief of the Clinical Neurology Section at the National Institute of Neurological Disorders and Stroke will speak about "Biomarkers of Parkinson's Disease and Related Disorders. We take you to the Lipsett Ampitheater at the NIH Clinical Center in Bethesda, Maryland, where Dr. John I. Gallin, director of the Clinical Center, will introduce today's first speaker.
(Music fades in, under VO)
GALLIN: Okay, good afternoon, and welcome to Grand Rounds. Today we have two different presentations so we'll introduce each speaker separately.
Our first presenter is from the Clinical Center's Department of Transfusion Medicine and is Dr. Ena Wang who's a staff scientist and director of the Molecular Sciences Departments, Infectious Disease in the immunogenetics section. And the topic for her talk is Genomic and Transcriptional Evolution of Metastatic Melanoma, the case report. Dr. Wang received her MD degree at Herbei in China and master of science at Shanghai Medical University. Before coming to the United States in 1991 she was a teacher associate at Shanda and chief resident at the Shanghai Dermatology Institute. She was a visiting research at the Department of Microbiology Immunology at the Arizona Health Sciences Area and the University of Arizona research fellow and in the NCI surgical branch in 1998 and she's been in her present position since 2007. Her research focuses on the identification of genetic traits in humans that could explain the relationships between pathogens and the host with particular interest in cancer and chronic infections. During her career here at the NIH, she has received a bench to bed side award in 2002, NCI Intramural Director's Award in 2006 and a Clinical Center Award For Scientific Excellence in 2007. She's a associate director of the Journal of Medicine and on the current board, the current immunology reviews. So it's a pleasure to welcome Dr. Wang to the podium.
WANG: Thanks Dr. Gallin for the nice introduction of me and also for this opportunity to speak here. I have nothing to disclose. The focus of my talk is to emphasize the genomic effects of globality. And the hopes will be informatic and about the significant aspect of cancer evolution in time and also we would like to take this opportunity to solicit suggestions, potential collaborations particularly in bioinformatic aspect of this project.
The case I'm going to report is a melanoma metastasis. I'm going to use this as an example to evaluate genomic and transcriptional evolution during the disease course. So in the past decade, our research interest has been focused to understand the mechanism of immune mediate tumor rejection. However, in the antigen specific vaccination, we could easily detect aspect specific T-cell precursor increase with the time and the correlated with the number of vaccination patient receipt. This had been identified by numerous doctors however, not only are the patient monitors with the clean core responsiveness. In fact, if we consider the steps necessary to induce tumor rejection, we are only considering the vaccine only taking care, the first interactive dimension, T-cell receptor and MHC interaction without accounting for the importance of co-stimulatory factors and whether the tumor localize the tumor.
Most important, we should consider the involving nature of immunoresponsiveness, especially the genetic instability of cancer as well as the the heterogeneity of tumor micro environment. So about a decade ago, in collaboration with the Dr. Jeffrey, and Dr. Bidner, we applied gene expression to melanoma metastisis. In this study we saw 2 things signified by 2 parts up or down [indiscernible]. Because of the lack of clinical information in this study, our interpretation at the moment is melanoma has 2 different taxonomies. With the specific genes, yes, yes we do.
My focus is now going to focus on this specific study and we're going to talk about the later perhaps, then I can answer your question in a better way. So to further characterize these 2 different class of melanoma, we add temporal dimension to the study by using aspiration biopsy, following patients with the single lesion, and lesions along the disease history. In this study we apply the gene expression analysis and found that again, we found 2 distinguish cluster of melanoma. Within this big cluster, lesion obtained from the same patient are clustered closely to each other, suggesting that each individual patient reflect their own biological entity.
However with some exceptions. As the color line indicated, we see theune direction shifting to the small cluster. By looking at this biologic sample information, we realize that within this cluster, a hundred% of the lesions are later time points of biopsy. Based on the fact that 2 biopsy obtained from the same lesion, at 2 different time point, can segregate into 2 cluster, suggests that this cluster is not a different taxonomy of melanoma, but a temporal change. To understand the genetic component to contribute this cluster segregation where currently study in vivo, through the collaboration with Anderson University of Virginia and the surgery branch at NCI to following patients in the natural way.
In the meanwhile, we also do in vitro study using the special keys I'm going to present here. If you have listened to Dr. Rosenberg's presentation years ago, this patient is perhaps familiar with you. We call patient 888.
Patient was diagnosed with primary melanoma in 1988, with a local metastasis. A year after, patient experience a soft pallet reoccurrence from this lesion, melanoma cell line 888 was generated. Tumor infiltrating lymphocyte was expended and adopted transfer 2 a patient in combination with il2. Which will result, a complete clinical regression. Three year after, patient experienced a pelvic mass, this lesion was partially resected to generate tumor treating lymphocyte 2090, in the meanwhile 1290 was generated. Patient was treat wide combination [indiscernible] plus high dose of IL2 which result in secondary complete tumor rejection. A year after, patient experience the third recurrence from the same lesions, we were able to generate a 3 melanoma cell line using different methods. And however, patient did not respond to the similar therapy previous given to patient, a year after patient disease progressed and multiple lesions occur from last 2 lesions we were able to generate an additional 2 cell lines.
Those cell lines collected spanning 12 years along the patient history provided us the opportunity to answer some important questions. First is this melanoma is derive a single clone expansion. We will be able to assess the kinetic genetic transcription load degeneracy during the melanoma history. We could evaluate the weight over epigenetic changes and also the result could shed light on the melanoma stem cell hypothesis. To insure that, all the cell sign will utilize this study, so this has no in vitro culture incorporated artifact work contamination, we sequence analyze, MHC class 1 to conform that each individual cell line carry identical types. However at the cell line level, 1 derived from the same lesions generate the line of the same lesions lost MHC protein expression during to the beta 2 deficiency. The first question we ask is whether those cell lines generated from different time points from different lesions are derived from the single clone expansion.
But clonality analysis and most of the matter utilized to analyze x chromosome normalized patterns. In the normal mix of tissues, paternal and maternal x chromosome maturation is 50% distributed. Therefore because the antigen receptor, antigen receptor localized on chromosome carry different tri nucleotide repeat, and paternal and maternal tri nucleotide lens are different. Therefore if you use amplification, both allele can be amplified. In the mixed tissue lesion, mixed clone tissues, if you use modulation sensitive restriction enzyme status, whole status, then you still can amplify both allele because the 50/50% distribution. Our, from a single clone expansion, only 1, either paternal or maternal x chromosome are exclusively modulated therefore use methylation sensitive restriction enzyme, can you not get the rate of the allele, only the modulator can be amplified.
Here this shows the result this, is before restriction that is all the cell lines were utilized for this study, post restriction only 1 allele maintained. This result strong suggests that a patient 888 cell lines are derived from the same progenitor founder. In the independent study, beta catinine mutation was identified in melanoma patient. Out of the 27 melanoma cell line studied, 6 cell line carry beta catinine mutation. All of this 6, 4 cell line carry identical single point mutation exemplified by the switch which result in immuno assay subsidiary tuition. And out of this, this is 4 cell lines, 2 cell lines are derived from patient 888.
We sequence analyze all the cell lines, we use indeed in study and conformed each individual cell line carried this unique real beta catinine mutation and this result strongly suggests they're monoclonallity. To understand genetic imbalance contributed to disease progression with applying genetic analysis at different levels, first we look at the chromosome structural changes gene copying variation and now also, nonnuclear DNA, mutation analysis.
So chromosome structure change, we apply in the typing, the 50 column indicated the change in the cells as we see in the early stage, 16 out of 25 macrophase of cells analyze are tetraemployed. As a disease progressing, the change back to majority diploid status, however, at the last stage of the patient, the ploidy totally disrupted. Cell and 1936 carry diploid, employed and tetraemployed, and therefore it's disrupted and the typing could not be summarized. At cellular level, we found that 4 out of 5 macrophase analyze from cell line 888, carry almost identical car o typing suggesting the disease is homogenius, as the disease progressing, you see each individual cells care o typing. Common recurrence deletions are highlighted and those deletions, some are replaced biomarker chromosomes. To analyze, to obtain a global way of genetic imbalance at the different time points we also applied chromosome comparative genomic hybridization.
This result reviewed that average genetic imbalance are very different from time point to time point. However, recurrence imbalance summarize indicated by color coated blue, indicate deletion, red indicate amplication. Because chromosome CDH is not as progressive as rebased genetic imbalance analysis, we further applied a high density oligo, KCTH, which we can identify with the 5 kb deletion, very precisely. So in this study, the data shows the genome well, the y axis is ratio, the samples verses done more samples, and yellow indicate amplification and green indication a deletion, as we see across all the different cell lines, recurrence imbalance indicated by those arrows which include chromosome 3 p amplification, 7 q, and 17, amplification. Those amplifications are carried through the whole heat streak, in addition to that, it's deleted by chrome so 10 p, 17 p, and 8 p. And with the 1 exception, in this cell line derived from 3 cell line derived from the same lesion, 1 of the cell lines do not carry this chromosome 3?amplication. Interestingly, we found the sum of this amplification and deletions are not appeared in a sequential way but sporadically distributed along the patient disease history as we can exemplify it by chrome so 20?amplification and the 20 p deletion which spanned 8 years apart.
The commonality suggests that they are derive the same founder, however, the spread of non-sequential appeared imbalance and indicate that each BD cell line are not derived from the previous cell lines but from the same founder. That's a good suggestion we do not say what you do the data analysis you can find what the breaking point, segregation base range. This 1 we apply the 5 kb. We could apply for...
[ inaudible question from audience ]
WANG: You mean the non-sequential imbalance. We will try that, thank you for the suggestion. This observation suggests strong support of this stem cell theory. Interesting things we note is that as in the previous table, I show that 1 of the cell lines loss of beta 2 expression lead to the MHC expression, the protein level deficiency and we found this unique cell line carry 1 very fine chromosome 15 deletion which encoded a beta 2 microglobulin. At the control, we also arbitrarily select a growth of melanoma cell lines. As we can see in general, imbalance region are much more, either in the numerical way or in the range of extended way and among those cell lines, 2 cell lines are derived from the same parental cell lines subcloned, they share the similar genetic imbalance patterned. To summarize, what is the recurrence genetic imbalance, along the disease history with the melanoma patient 888, we found that predominant amplification are localized on chromosome 3 p, chromosome 7, chromosome 17?amplification, part close to 50% carried from chromosome 20 deletion.
Deletions are indicate indeed chromosome 1, 8, 9, 10, 14, 16, and 22. If we look at the heterologous cell lines, those regions are very much cover the whole genome and in addition to that we do see similarity across those 2 compare groups, we see chromosome 3, 7, 17?ampplification, and also we see deletion, but most of the deletion are not representative in the patient 888. However, those imbalance deletion and amplification has also been report indeed the NCI 16 melanoma cell line cario typing cell analysis. To compare the genetic imbalance at the gene by gene level, we summarize the encoded genes across the chromosome by cluster analysis. As we see that patient 888, cluster closely to each other, carry the majority of the identical genetic imbalance, this is very interesting because the patient spend 12 years in their disease history, and yet, keep their genetic identity. As you see the heterologous cell line, each cell line carry the unique genetic imbalance. Two cell lines clone from the same parental share similar genetic imbalance patterns.
Suggesting that although the disease progressing with a time, but the genetic identity of very well preserved. To analyze the genetic imbalance contributed to the cell biology, we applied gene expression analysis to look at transcript level, by using nonsupervised cluster, we identify 2 distinguished cluster. One is an exclusively include the patient 8 cell line and the cluster representative of the control cell lines. This different also reflect this dimensionagonal as you see that 888 cluster closed the types to each other distant away from heterologous melanoma cell line and those cell lines maintain their own identity away from each other, 2 cell line derived from the same parental cell line, cluster closely to each other, which is very interesting. To correlate the genetic imbalance correlate contributed to the transcription changes, we applied correlation analysis using pure correlation algorithms, from the patient 888, we identified 3700 genes coded within the imbalance regions. Out of those genes, 361 genes at the transcript level are in the positive correlation. Which means if you have a gene [indiscernible] increase, have you expression upregulation as well.
This is similar phenomenon we found in the heterologous cell lines in the imbalance region which encoded 10,000 genes about 1000 transcript in the positive correlation. This result is different than previous or reported which states that genetic imbalance contribute to 60 to 80% of transcriptional program changes. We found that the maximum, the transcript of changes contribute about 10% of contributed 10% of correlation with a genetic imbalance. This is not only in the patient 888, but also in other melanoma cell lines. To understand those genetic imbalance encoded regions, encoded a message differential expression, we wonder if we remove, if those message RNA are predominant to segregate this 2 cluster at transcript level, we simply subtract those genes from the common gene pool and recluster analysis we found there's no impact to this cluster segregation suggested that genetic imbalance can make up contribute to part but not solely governing the transcription pattern changes. We also look at the mitochondrial mutation, it's highly prevalent in the cell, each cell carry 100 to 10,000 copies. It encodes 37 unique genes in 13 proteins, unique proteins. Mitochondrial DNA functions highly associated with the rest for chain reaction, oxidative stress and most importantly, associated with apoptosis, cell cycle rest and emulation of p53 pathways. Recently attention has been made to analyze mitochondrial DNA with a variety of cancer. To analyze, to understand the mitochondrial DNA, contribute to disease progression we also applied mitochondrial DNA sequence analysis. In this analysis we include all the patient 888 and heterologous cell line, plus some normal done air samples. Red indicated sequence variance from the defined cons sensor sequence as we see that each individual cell line carry their unique mitochondrial DAN sequence genome type. Patient 888, share the similar mitochondrial DAN pattern except 1 of the last cell lines drifted away from the main cluster.
Interestingly from the same parental cell line shared identical mitochondrial DNA patterns. We further analyze whether genetic, there is a mutation at the mitochondrial DNA level, we use the patient cells as a reference to see the cancer samples where the mutation has been created during the disease history. We found there is a 2 mutation cariat exclusively along the history strongly suggests again for the clonality.
In addition over that, each individual cell line carry their unique mutation and those mutation are not carried into the subsequent cell lines and those mutations, some is in the since, mutation, in is the sinon mouse mutation. The contribution of mitochondrial DNA mutation especially at functional level is currently under study and investigation. In addition of genetic make up and genetic imbalance we contribute to the transcriptional changes, epigenetic play a important role. A CPG methylation localized at more than half of the promoter region it's highly regulated of the transcriptional changes, therefore we applied DNA methylation analysis using a ray based technology. In this technology we use might o [indiscernible] antibody to specifically capture methalated DNA. And then after purification enrichment, co hybridize to themselves now reach the DNA by differentiat fluorescence labeling. Co hybridize in the differential express are identified by hyper or hypomethylation.
We first want to say those methalated promoter distribution correlated with the genetic imbalance, within the coding regions, there's the 2200 genes promoter, has promoter cpt and all of them 60 genes are in the reverse correlation which means, when you have a gene copy, increase, because it's a hyper methalated, their functional enactivated. However, if we look, the whole transcript ohm away, independent of genetic imbalance region, we found that out of 9000 promoter, we analyze, 755 genes transcript are inversed correlated with the promoter region methylation status. And to understand whether those inverse correlations status contribute to the gene expression cluster segregation, we remove those genes out of the common denominator, recluster them, again we don't see much impact of the cluster changing.
This results suggests that there's multiple factors contribute to the governor of the transcriptal changes. The last component we looked is microarray which is recently discovered and has functionally has protein translating repression or leading to degradation by targeting the 3 nonprime region of MRNA, by micro RNA, expression analysis, we found if you use whole micro RNA profiling to do cluster analysis this, is only analysis we can not distinguish a patient 888 from heterologous melanoma cell line which allows the patient identity at this level.
However, we do see some changes with the time. We see the early cell lines, cluster closely to each other, as the disease progressing, other cell lines kind of blend into the heterologous and melanoma cell line. To understand the contribution of micro RNA to a transcript ohm is a challenge and we than each micro RNA targeting 200 to 400 different targets in the diverser, 1 method can be targeted by multiple micro RNA, so the correlation is hard to be summarized here, however we were able to add the micro RNA coding to the chromosome location to see if gene copy number increased or deletion is associate wide the micro RNA expression changes. We found that chromosome 7 amplication is associated with micro RNA localized chromosome 7 region upregulation and also in the chromosome 16 deletion is associated with the encoded micro RNA down regulation, 1 interesting things is in at chromosome 17 which encoded ONA mere cluster is malignancy is not upregulated in this specific patient. With further analyze the patient according to their disease profiles in history, to select a micro RNA changes with 2 fold different from the early cell line in summarize into this heat map and as we see that each individual time point carry their unique micro RNA expression patterns. Among them we see some trend, some of the micro RNA down regulated down point as disease progressing upregulation, vice versa, upregulated micro RNA reduced expression as the disease progressing. We're currently trying to understand what their impact to the transcription only array and we need help especially bioinformatic aspect to this data. Before the end of my talk, I would like to emphasize the key to the report is anecdote, however we were able to collect internationally 10 more cases with a long disease history, multiple samples. Hopefully those data will support our current finding and to helpitous interpret our result.
In summary, our result suggests that metastasized melanoma is a clonal disease. The car o typing and the CDH result, identified the consistent core trait instead of the phenotype, together with the mutation analysis, of a result suggests that all the metastasis are derived from the same or primary founder clone. However, now cumulative difference in genetic imbalance among virus cell lines suggest that each cell lines were not derived from the most previous 1 and it's a common progenitor cell gave rise to the genetic unstable progeny in malignant melanoma while maintain the conserve core of genetic imbalance. Genetic imbalance by the limit factor on the transcription pattern, at best is 10%, epigenetic changes such as micro RNA methylation may play important role in the behavior of cancer in time, therefore, a better understand of tumor biology, multidimensional analysis with the time is very important. In addition of that, the key of patient 888, could be a model system, to test a varying bioinformatic [indiscernible] and to understand the genetic and epigenetic relationship. I would like to stop here.
Thank you.
[ applause ]
GALLIN: Thank you very much, I suggest you write down your questions and we have them at the end because we've gone a little over. Thank you that was great.
Our second presenter is Dr. David Goldstein who is a senior investigator and chief of the Neuroendocrinology Program in the neurosciences program of the NINDS. His topic is Biomarkers of Parkinson's Disease and Related Disorders.
He received his BA from Yale and MD/Ph.D from Johns Hopkins. Was in behaviorial sciences. After residency in internal medicine at the University of Washington, he came to the NIH in 1978 with the clinical associate in NHLBI, and he has been in NINDS since 1990. In 1999, he founded and has since led the endoneural and cardial section within NINDS. He's an authority in the chemistry and autonomic function testing and discoveries include cardiac sympathetic innovation and Parkinson's disease and differential regulation of the sympathetic neurogenic and adrenal modulatory hormonal systems of stress and distress and adrenal imbalance proceeding [indiscernible] and autonomic failure and he's a fellow of the American of the Heart Association and has numerous honors. Welcome Dr. Goldstein.
GOLDSTEIN: All right, thanks, John. My talk today will be in 3 parts, we'll see if I can get to the third part. The most important would be the first 2 anyway. I'm going to be going over neuropathologic and neurochemical discoveries that are related to the biomarkers of Parkinson's disease. And we'll be spending a good deal of time on central and peripheral colomenergic denervation and Parkinson's. If I have time, I'll propose a hypothesis about the mechanism of loss of catacolomenergic neurons in Parkinson's disease.
Now there are 2 pivotal fundamental discoveries about Parkinson's disease, which have informed research in this area ever since these discoveries were made. The first is that??whoops??sorry, as depicted here Lewy bodies characterize Parkinson's disease. Lewy is name was levy, and he was a German pathologist who described these eoscenphilic inclusions in neurons in this substantia nigra, in the midbrain. This is a discovery made about a century ago.
And this is the pathologic hallmark of Parkinson'sdisease. About a half century ago, the neurochemical hallmark of Parkinson's disease was discovered. And that was the loss of dopamine in the striatum but at the beginning you'll notice that there's also a decrease in nor adrenaline or epineff rin that was described at the beginning. So these 2 fundamental discoveries, louis body's the pathology, things can you see, and the loss of dopamine, the catecholamine, something you measure in neurochemical assay, have informed research on Parkinson's disease to this very day. Now, 3 follow up discoveries, that continue directly from these 2 fundamental discoveries. The first is, has to do with a protein called alphasynuclean and we'll get into that momentarily and the second is that by fluora dopa?pet scanning, there's a way developed to see the loss of dopamine terminals in the brain in living patients with Parkinson's disease. And the third is that just as there's a loss of catecholamines and epineff rin in the brain and Parkinson's, there's also a loss of {...} in the heart.
It was in 1997 that a large group was here and described the first genotypic abnormality identified to cause Parkinson's disease and this was a mutation of a gene encoding a protein called alpha sinew clean. Nobody knew was alphasynuclean does and to a large extent nobody knows now, but it is abundant in synapses and that's part of the reason that alpha sinew clean has its name. Almost immediately thereafter in 1997 it was found that Lewy bodies, the hall mark of Parkinson's disease, contained this alphasynuclean, this meant that alphaynucleanopathy was not just an obtuse finding in a rare family that inherited Parkinson's but is a player in the pathogenesis of most forms of sporadic Parkinson's disease as well. Even as a subsequently confirmed that Lewy bodies contained alphasynuclean. And the concept rapidly evolved that there's a family alphasynuclean bodies and in addition to Parkinson's disease there's a Lewy bodies which overlaps Parkinson's disease and dementia. There's a rare but very important disease called pure autonomic failure which is a Lewy body disease but it's not Parkinson's, they do have orthostatic hypotension from a loss of nora energic neurons from the brain and there's 1 that's not in the disease, and it's used to be called the Shy Drager's syndrome. These accumulations are in glial cells, helper cells rather than in neurons.
The second discovery had to do with the ability to visualize the dopamine lesion in Parkinson's disease and this is illustrated here. This is high resolution PET scan done here, overlaid on the patient's MRI, which is kind of a blue?black?gray background. And you can see obviously here, the basal ganglia, the striatum looks like a sad clown's eyes and the beady eyes are the caudate and the mascars coming down is the putamin. And that's the main target region in Parkinson's disease and as you see here in this patient with Parkinson's disease, there's almost a complete loss of fluorondopa derived activity in the cutammine visualizing the dopaminergic lesion. In our experience if you express the amount of radioactivity and imputamin there's a function of that in the control area, the occipital cortex where there's not much dopaminergic innovation, you see all patients with Parkinson's disease with that exception have at least a part of that containment activity compared to normal. This means that the PET scanning provides an excellent sensitive biomarker of parkinsonism.
However, as shown here, the parkinsonian form of multiple system atrophy which is difficult to distinguish from Parkinson's disease involves just as much of a fall in flouradopa derived activity as if Parkinson's disease itself. So although flouradopa PET scanning is a biosensitive marker of parkinsonism, there's no specificity in distinguishing Parkinson's disease of multiple system atrophy.
The third recent discovery was in 1997 and this was by our group and it shows that there's a loss of sympathetic noragenergic part in the heart and these are PET scans for people. These are slices, sort of going across here on the left side, this appearing structure is the heart, the lob on the the right is the liver and you can by 13 anmomia scanning all patients had normal profusion of the heart. Normally the flouradopamine scan showing icismathetic innervation of the heart march what is you see in terms of profusion, but in pure autonomic failure remember that rare Lewy body disease, they have hypostatic tension but they don't have Parkinson's, you don't see any flouraopamine derive indeed the heart indicating denervation. In multiple system atrophy, the inernation was present and with this patient at least, with hypotension, there was no flouradopamine derived in the hare, similar what we see in pure autonomic failure and with this finding we're confirmed in other patients, it would be really important because it would demonstrate that Parkinson'sdisease is not just a brain disease, and not just a movement disorder, but also a disease of the autonomic nervous system. And so we followed up on this conducted many, many studies of patients with Parkinson's disease, multiple system atrophy and control patients and you can see that essential le all patient who is had Parkinson's disease with orthostatic hypotension and 40% of Parkinson's patients have orthostatic hypotension, all have cardiac innervation, about half of patients with Parkinson's have this hypotension also have cardiac denervation and complete systems with atrophy and so with no floweroscoping with the brain have no Parkinson's atrophy, flouroscanning of the heart produced it distinguishing between Parkinson's disease and multiple system atrophy. This slide is to demonstrate that the loss of flourodopamine activity in the heart does reflect sympathetic denervation. This epicardial nerve stained for tyroseen hydrox lace, the rates in synthesis and you see abundantant hydroxylase reactivity indicating sympathetic inernation and this patient, you don't see any reactivity providing pathologic confirmation that Parkinson's disease does involve cardiac denervation. There are 2 biomarkers questions, that we wanted to address, first, if Parkinson'sdisease involves both a nigrastopal lesion, and a cardiac lesion, are they related?
After all, they're like father and son in the catecholamine family. And second it's no wonder that virtually all patients with Parkinson's disease have some loss of sense of smell. In patients with Parkinson's and hypotension all of them have no sense of smell. Well, is the loss of or sense of smell related to the dopamine lesion in the striatum or related to the cardiac menergic lesion in the heart or both or neither? This slide demonstrates that there's no relationship between the extent of loss of the dopamine terminals and the nigra striatal system and the loss of cardiac sympathetic nerves in Parkinson's disease or in multiple system atrophy. So these are independent lesions. And remarkably, on the University of Pennsylvania smell identification test, upset were perfect scores of 40, there's a positive correlation between the sense of smell and the cardiac sympathetic innervation and yet there's no relationship between the sense of smell and the nigrastriatal dopamine lesion, in fact it looks like an inverted u.
In the last couple minutes I'll try to provide a hypothesis about the link. What's the link between the Lewy bodies and the neurochemical hallmark, the catacolla mine lesion in Parkinson's disease? Well, first of all we know that alphasynuclean is responsible or can be responsible for the loss of sympathetic nerves in the heart and here we see in patients who have that original mutation of alphasynuclean, now it's called park 1 that the patient has cardiac sympathetic denervation and in part 4 where there's a triplication of a normal alpha sinew clean gene, again there's cardiac denervation just as in sporadic Parkinson's disease, these findings implies that alphaynucleanopathy can cause cardiam denervation, just as it causes Parkinson's disease in these rare families and in the part fore forum, there's been pathologic confirmation that the neuroimaging finding are correct in indicating cardiac sympathetic denervation and you see in this patient with the replication of the sinew clean gene there's an almost complete absence of the normal amount of tyroseen hydrox lace hyperactivity in the epicardial nerve.
Conversely, there's a rare form of Parkinson's called park 2, due to park and gene mutation where the patients don't have an alphasynucleanopathy and they don't have the Lewy body disease, they don't have orthostatic hypotension and as shown here they have normal innerervation of the heart so approximate you don't have the this, you don't have the denervation. This is a diagram illustrating what we believe is a sequence of the of the pathogenesis of Parkinson's disease at least as far as the heart goes. First there's precipitation and aggregation of alpha sinew clean and distal sympathetic nerves in the heart. There's a small amount of loss, tyrosin hydroxylace immuno reactivity because of cardiac denervation. Subsequently this is an incidental Lewy body disease where the patients don't have Parkinson's disease, they have Lewy body and they are thought to have presimattic Parkinson's. Subsequently the lewition moveslase grade and approximatelily and chose now you see alphasynuclean deposits in the ganglia, the sympathetic ganglian cells. In Parkinson's disease, there's no alpha sinew clean anymore in the distal nerves because the distal nerves aren't there, at least the distal catacolomenergic nerves are not there and instead you see antibodies in Lewy body which is consist went Parkinson's disease.
I don't think I'll have time to go over the mechanism but I do want to comment that just as alphasynucleanopathy can cause the loss of sympathetic neurons it's also the case that a cotta colaldahyde that's made from theoxidated deanimation of dopamine called dope?al. Can oligmerrize and aggregate alphasynuclean.
So in summary, the putanmen of the activity is a very sensitive biomarker of parkinsonism, but it doesn't distinguish Parkinson's disease from the parksonian form of multiple system atrophy. Cardiac nor dinervation characterize Parkinson's disease especially Parkinson's with orthostatic hypotension. The strital is independent of the deficiency, even though both involve loss of cataminergic neurons. Olfactually coralates better with the loss of sympathetic nerves in the heart than the striadal lesion or the parksonian movement disorder. As far as mechanisms go, I just very briefly mention that alphaynucleanopathy can precede and cause catacolomeergic dinervation not oldsmobile in the brain and in the the periphery and Parkinson'sdisease and it's possible that there's a pathogenic positive feedback loop in which cataolated hides oligmerrize alpha sinew clean and the alphaynucleanopathy causes destruction of dopaminergic terminals. Finally, I want to thank my many colleagues and collaborators over the years that this project has gone on and thanks for your attention.
[ applause ]
GALLIN: We have a question for Dr. Wang or Dr. Goldstein. Yes?
[inaudible question from audience]
GOLDSTEIN: Thanks for the question, this has to do with [...] verses synucleanopathy and Alzheimer's verses Parkinson's disease with dementia or Lewy bodies. The short answer is that Lewy body diseases whether they're associate wide Parkinson's disease or orthostatic hypertension and pure autonomic failure or Lewy bodies, all of them are associate with profound cardiac sympathetic denervation, so it seems that the alphasynucleanopathy which results in the Lewy pathology, underlies the autonomic lesion. And it's even been proposed that can you distinguish Alzheimers disease from a dementia with Lewy bodies by doing cardiac sympathetic imaging, whereas the imaging of the brain has been much in terms of [...] has been very difficult. I hope that begins to answer the question.
[ inaudible question from audience ]
GOLDSTEIN: Exactly how the catical aldehyde results in polymerization with alpha sinew clean I don't think is known. It's not just that alpha sinew clean polymerizes, it's not just that can you get polymerization of the aldahydes in condensation, but in addition, dopamine itself can polymerize, it's really pretty remarkable that if you have dopamine and an alkaline solution, it will coat anything. And there was a science article a couple of years ago, on that coating property of polydopamine. So I'm not sure exactly what the what the content are in terms of in the Lewy body, but it can very well be that it's not just alpha sinew clean that's precipitated but also in a very complex way, there's polydopamine and there's condensation products of the aldahydes. So I think it's going to be a very complex story.
GALLIN: I want to thank both speakers for a great presentation.
[ applause ]
ANNOUNCER: You've been listening to NIH Clinical Center Grand Rounds, recorded June 3, 2009. Our speakers were Dr. Ena Wang, staff scientist and Director of the Molecular Science, Infectious Diseases and Immunogenetics section at the Clinical Center's Department of Transfusion Medicine who discussed "Genomic and Transcriptional Evolution of Metastatic Melanoma, a Case Study. She was followed by Dr. David S. Goldstein, Senior Investigator and Chief of the Clinical Neurology Section at the National Institute of Neurological Disorders and Stroke who spoke about "Biomarkers of Parkinson's Disease and Related Disorders. You can see a closed-captioned videocast of this lecture by logging onto http://videocast.nih.gov -- click the "Past Events" link -- or by clicking the "View Videocast" link on the podcast homepage at www.cc.nih.gov/podcast. The NIH CLINICAL CENTER GRAND ROUNDS podcast is a presentation of the NIH Clinical Center, Office of Communications, Patient Recruitment and Public Liaison. For more information about clinical research going on every day at the NIH Clinical Center, log on to http://clinicalcenter.nih.gov. From America's Clinical Research Hospital, this has been NIH CLINICAL CENTER GRAND ROUNDS. In Bethesda, Maryland, I'm Bill Schmalfeldt at the National Institutes of Health, an agency of the United States Department of Health and Human Services.
