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Tumor Biology |
Department of Oncology, Albert Einstein Cancer Center, Bronx, New York 10467
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ABSTRACT |
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INTRODUCTION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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In fact, there is significant evidence that SCFAs play a physiological role as a key inducer of cell maturation pathways in the colon. In patients who suffer from colitis attributable to diversion of the fecal stream, introduction of SCFAs by enema promotes maturation of the mucosal cells (7) , and in rats, supplementation with SCFAs alleviates the intestinal atrophy that results from total parenteral nutrition (8) .
We and others have studied the cell biology of the response to the SCFA butyrate. There is a temporally ordered response, consisting of an early phase of commitment during which cells arrest in G0-G1 at 12–24 h and a late phase in which an apoptotic cascade is executed (2, 3, 4 , 9, 10, 11) . Cells also undergo a differentiation program in response to butyrate, with, for example, elevations in alkaline phosphatase mRNA and activity manifest as markers of differentiation along the absorptive cell lineage (2 , 12) . Our data from cell lines (2 , 9) and from a mouse model with a homozygous deletion of the gene for short chain acyl dehydrogenase (10) suggest that triggering and/or completing maturation pathways requires the mitochondrial ß-oxidation of SCFAs.
Thus, significant reprogramming of colonic epithelial cells takes place in response to the SCFA butyrate, but the underlying mechanisms are unclear. Butyrate is an inhibitor of HDAC activity (13, 14, 15) , butyrate-responsive elements have been identified in the promoters of a number of genes (16, 17, 18, 19) , and butyrate up-regulates ß-catenin-Tcf signaling (9) . Therefore, altered accessibility of cis acting elements to trans-acting factors by changes in extent of histone acetylation may all contribute to modulation of transcription by butyrate. However, the three maturation pathways (cell cycle arrest, lineage-specific differentiation, and apoptosis) of colonic epithelial cells stimulated by butyrate make it likely that there is a complex coordinated response to this physiological regulator. Array and imaging technology have permitted us to investigate this question.
In the first large-scale applications of array and quantitative imaging methods, we identified patterns of gene expression that characterized the mucosa of patients at genetic risk for development of colon cancer, distinguished benign and malignant tumors from each other and from the normal mucosa, and profiled gene expression in the butyrate-induced maturation of colonic epithelial cells (20 , 21) . These studies led to the discovery of a role of mitochondrial function in risk for, and progression of, colon tumors and eventually to our appreciation for a role of mitochondria in an apoptotic cascade (2, 3, 4 , 22 , 23) . Although this early work quantified level of expression of each of >4000 sequences, only relatively abundant sequences could be investigated, and until selected and sequenced, cDNA clones analyzed were anonymous. However, the advent of modern genomic approaches, coupled with microarray technology, permits a more detailed approach to these questions (24, 25, 26, 27, 28, 29) .
Here we identify a cascade of reprogramming of colonic epithelial cells that expands as a function of time of exposure to butyrate. This response has been compared to that induced by TSA, like butyrate, an inhibitor of HDAC (30) , which, in conjunction with data demonstrating the different kinetics of change in histone acetylation stimulated by the two agents, has identified a population of sequences that are likely coordinately regulated by changes in histone acetylation. Comparative analysis has also been done with the response to sulindac, a nonsteroidal anti-inflammatory agent that has significant chemopreventive activity (31, 32, 33, 34, 35) , and curcumin, a dietary chemopreventive agent from mustard and curry that is structurally related to sulindac (36, 37, 38, 39, 40, 41) . Sulindac (9 , 42, 43, 44) and TSA (9 , 45 , 46) induce a G0-G1 cell cycle arrest and an apoptotic response similar to that induced by butyrate, but curcumin induces a G2-M arrest without significant apoptosis (9 , 47) . Similarities in response demonstrate that butyrate and TSA are related in terms of mechanism of action, as are sulindac and curcumin. However, the data are more striking in terms of the marked differences in response among the agents and demonstrate, for example, that signaling pathways recruited into the butyrate and sulindac responses are different, and that the underlying mechanism of cell cycle arrest differs markedly between butyrate and curcumin, consistent with their induction of a G0-G1 and G2-M cell cycle arrest, respectively, but also between butyrate and sulindac, although both induce a G0-G1 arrest.4
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MATERIALS AND METHODS |
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RNA and Probe Preparation.
SW620 cells were grown in T150 flasks and RNA prepared using the RNeasy
Midi kit (Qiagen, Valencia, CA). For each microarray hybridization, two
separate probes were made: one labeled with Cy3 (control) and one with
Cy5 (treated). Aliquots of RNA (100 µg) were precipitated by addition
of 2.5 volumes of cold ethanol:0.1 volume 3 M sodium
acetate (pH 5.2), harvested by centrifugation, briefly lyophilized, and
resuspended in 17 µl of DEPC (diethylpyrocarbonate)-treated
dH20. To this was added 2 µl of oligo dT primer
(500 ng/µl; Life Technologies, Inc., Rockville, MD), and the mixture
was heated at 65°C for 5 min to denature the nucleic acid. The
following were then added: 8 µl 5x first-strand buffer(250
mM Tris, 375 mM KCl, and 15 mM
MgCl2, pH 8.3), 4 µl of 0.1 M DTT,
4 µl of deoxynucleotide triphosphate (25 mM each dATP,
dCTP, and dGTP, 10 mM dTTP; Amersham, Piscataway, NJ), 4
µl of Cy3 or Cy5 dUTP (1 mM; Amersham), 1 µl of RNase
inhibitor (30 units/µl; 5Prime,3Prime, Boulder, CO), and 2 µl of
Superscript II Reverse Transcriptase (200 units/µl; Life
Technologies, Inc.). The reaction was carried out for 1 h at
42°C. Probes were then denatured for 2 min at 95°C, diluted with 43
µl of distilled H2O; 10 µl of 10x reaction
buffer were added (100 mM Tris, 50 mM EDTA, and
2M sodium acetate, pH 7.5), and the RNA was hydrolyzed by
the addition of 2 µl of RNase ONE (10 units/µl, Promega
Corp., Madison, WI) and incubation for 10 min at 37°C.
The probe reactions were then clarified by a 10-min spin at high speed in a microfuge. The supernatants from the two reactions (control and treated, Cy3 and Cy5, respectively) were combined, diluted with 200 µl of distilled H2O, and applied to a Millipore YM-50 column (Millipore, Bedford, MA) to remove unincorporated nucleotides by three 400-µl washes with distilled H2O. The probes were recovered by inverting and spinning the column.
Hybridization and Washing of Microarrays.
Microarray slides produced by the Albert Einstein College of
Medicine facility (49)
were prepared for hybridization by
moistening over boiling water and then immediately cross-linked with 60
mJ of UV light (UV Stratalinker; Stratagene, La Jolla, CA). Slides
were again moistened over boiling water, snap-dried on a hot plate, and
soaked for 1 h in 0.6 M succinic anhydride, 0.02
M sodium borate (pH 8.0) in 1-methyl-2-pyrrolidinone. After
15–20-s rinses in 0.1% SDS and distilled H2O,
they were placed in boiling water for 5 min, followed by an ethanol
rinse at 0°C. Slides were then prehybridized under a coverslip for
2 h at 42°C with 50% formamide, 6x SSPE (0.9 M
NaCl, 0.012 M
NaH2PO4, and 6
mM EDTA, pH 7.4), 2.5x Denhardt’s reagent (0.05% Ficoll,
0.05% polyvinylpyrrolidone, and 0.05% BSA), 0.5% SDS, and 100
µg/µl sheared salmon sperm DNA (Sigma). After prehybridization, the
coverslip and excess buffer were removed. The probe volume was adjusted
to 6.5 µl, to which was added 7 µl of deionized formamide, 4 µl
of 20x SSPE, 1 µl of 50x Denhardt’s reagent, 0.5 µl of SDS, and
1 µl of hybridization blockers (10 µg/µl human Cot-1 DNA, 4
µg/µl yeast tRNA, and 2 µg/µl poly(A); from Life Technologies,
Sigma, and Amersham, respectively), and the mixture was applied to the
slide, covered with a coverslip, and hybridized at 42°C for 16–18 h.
The slide was then washed in 1x SSC (0.015 M sodium
citrate, 0.15 M NaCl, pH 7.0), 0.1% SDS long enough to
remove the coverslip, and then washed for 5 min at room temperature in
0.2x SSC/0.1% SDS and twice for 5 min each in 0.2x SSC.
Microarrays and Scanning.
The Albert Einstein Microarray printer and laser scanner are custom
designed and built instruments that have been described
(49)
. The robotic printer is modeled after the design
described by Brown and colleagues at Stanford University (24
, 26
, 27)
.5
Arrays used in this report consisted of the PCR-amplified products of
8,063 cloned sequences selected from a library of approximately 18,000
sequences received from Genome Systems.
After hybridization and washing, the emission from the Cy3 and Cy5 fluorochromes were recorded in two separate high resolution scans. Excitation for Cy3 and Cy5 was at 532 and 633 nm, respectively, and detection centered on 570–580 nm and 670–680 nm, respectively. The two images were superimposed, and the emission at each wavelength was quantified using Scanalyze 1.41 software (50) . These data were transferred to an Excel spreadsheet, where the signal:background ratio for each channel was calculated as well as the ratio between these ratios (i.e., green signal:background ratio was divided by the red signal:background ratio). The data were then normalized among arrays by expressing this value as a ratio to the average of these values for all 8,063 genes. The data were transformed to a log(2) scale and transferred to Microsoft Access, where a combination of Access, Microsoft Excel, GeneCluster (50) , and TreeView (50) were used for analysis.
For initial analysis, we considered all time points for a given agent as a single experiment. For each agent, data for a gene (i.e., six time points) was included in the data set if the signal:background ratio was >1.25 for either the red or green channel for at least three of the six measurements. When considering comparisons among all agents (i.e., calculation of N-Euclidean distances), the gene had to be included in the data sets for all agents.
Euclidean distances were calculated by the formula:
DA1A2 =
where D
is the Euclidean distance for agents A1 and
A2 at any time points, N is each
sequence in the database, and R is the red:green ratio from
the microarray.
Western Blot Analysis.
For detection of acetylated histone H4, cells were harvested in PBS,
washed, and resuspended in 5 volumes of 10 mM HEPES (pH
7.9), 1.5 mM MgCl2, 10 mM
KCl, 0.5 mM DTT, and 1.5 mM
phenylmethylsulfonyl fluoride, sulfuric acid added to a final
concentration of 0.2 M, and samples incubated on ice for 30
min. Samples were centrifuged at 11,000 x g
for 10 min at 4°C, and the supernatant fraction containing the
acid-soluble proteins dialyzed in a porous membrane (molecular weight
cutoff of 3500; Spectrum Laboratories, Rancho Dominquez, CA) against
200 ml of 0.1 M acetic acid, twice for 1 h
each, and three times against 200 ml of distilled
H2O for 1 h, 3 h, and overnight,
respectively. Proteins were resolved on a 15% Tris-glycine SDS gel
(Bio-Rad, Richmond, CA) and transferred to a nitrocellulose membrane
overnight (Bio-Rad). Blots were blocked in 5% nonfat milk in PBS and
incubated with anti-acetylated histone H4 (Upstate Biotechnology, Lake
Placid, NY; 1:1000) and an horseradish peroxidase-conjugated antirabbit
secondary antibody (1:2000; Amersham) for 1 h each. Antibody
binding was detected using the ECL reagent according to the
manufacturer’s instructions.
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RESULTS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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). In contrast, as soon as 30 min after butyrate treatment,
there was a shift in this pattern, which continued to expand
progressively [note log(2) scale] as a function
of time over the 48-h time course of butyrate treatment (Fig. 1B
). Extensive alterations in gene expression were also
detected in response to sulindac (Fig. 1C
), with much more
limited changes induced by TSA and curcumin (Fig. 1 and E
).
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, with red representing increased expression, green representing
decreased expression, and the magnitude of the change depicted by the
intensity of color. Fig. 2
illustrates a progressive recruitment of
sequences as the cells responded to butyrate. During the first 30 min,
a small number of sequences were elevated in expression (Fig. 2A
) or were repressed (Fig. 2F
) by butyrate.
However, after this initial lag, the reprogramming expanded
considerably, with a striking number of sequences showing altered
expression beginning at 2 h (Fig. 2 and G
), and 12 h (Fig. 2 and H
).
This expansion of the response continued throughout the experiment but
began to moderate by 16–24 h (Fig. 2
, D, E, I, and
J).
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7% of the sequences assayed. We believe, however, that
this is a minimum estimate of the extent of reprogramming that takes
place in response to butyrate (see "Discussion"). Blast searches of each of the sequences altered in expression with butyrate were performed to update the data bases. Of the 589 altered sequences, 345 represent named sequences in the database, whereas the remainder are unnamed or expressed sequence tags.6
Also shown in these analyses is the extent of altered expression of
each sequence during the time course of treatment with the other
agents. There were clusters of similar change in response to the agents
(e.g., in Fig. 2
, clusters 1, 2, 3, and 8), whereas two
clusters (nos. 4 and 6) behaved similarly only for butyrate and
sulindac. In contrast, clusters 5 and 7 responded similarly to sulindac
and curcumin but were markedly different in response to butyrate. In
fact, the data are most striking in terms of the differences in
response among the agents.
To more fully investigate the relationships among the agents, Treeview
was used to produce a dendrogram that reflects the relative extent of
relatedness among all of the time points for each of the agents (Fig. 3A
). The 30-min time points for all of the agents clustered
together, reflecting the fact that at this early time, there had been
limited change in response to each agent (Fig. 1
), and hence in each
case, the cells still were most like untreated controls. In addition,
the time points for each agent tended to cluster, and the butyrate
response clustered most closely to that of TSA.
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. Response to all of the agents was most related to butyrate affects at early time points, reflecting the fact that alterations in expression proceed as a function of time, as noted above. With increasing time, the similarities diverged as the cells responded to each agent. As reflected in the dendrogram, among the agents, the profiles of gene expression induced by TSA were more like that of butyrate than were those induced by either sulindac or curcumin.
Because butyrate and TSA are both inhibitors of HDAC activity, we hypothesized that the greater similarity between butyrate and TSA may in part be attributable to this shared mechanism of action. We therefore investigated whether we could identify a population of genes for which altered expression by butyrate and TSA was attributable to altered HDAC activity by each.
Inhibition of HDAC activity results in histone hyperacetylation. We
therefore measured the degree to which histone H4 was acetylated by
western blot analysis (Fig. 4A
) and normalized to total histone H1 level for each time
point after either butyrate or TSA treatment (Fig. 4B
). The
kinetics of alteration were markedly different for the two agents. As
shown in Fig. 4 and B
, butyrate induced a
gradual increase in histone H4 acetylation that peaked at 16 h and
then fell but remained well above baseline through 48 h. In
contrast, TSA produced a rapid and short-lived increase in H4
acetylation that peaked at 2 h and then returned to baseline. We
then selected all genes from the database that were altered in
expression at any time point for butyrate and TSA but not for
sulindac or curcumin. Five hundred eighty four sequences were selected
based on these criteria, and the profile of altered expression of these
genes in Treeview is shown in Fig. 4C
. There are two gene
clusters in this population of sequences (clusters 9 and 10 in Fig. 4C
) that were elevated or repressed in expression,
respectively, with the same kinetics as the alterations in H4
acetylation induced by butyrate and TSA, i.e., altered
expression beginning at 2 h with butyrate that persisted but a
sharp spike of alteration with TSA at only 2 h. The tight
correspondence between the kinetics of altered histone acetylation and
kinetics of altered expression for genes in clusters 9 and 10 strongly
argue that changes in HDAC activity, known to be inhibited by both
butyrate and TSA, underlie the changes in expression for these genes.
The identity of genes in these clusters is listed on the web site.
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). This was, therefore,
investigated more closely. Similar to the analysis presented in Fig. 2
for butyrate, the Cluster and Treeview programs were used to display
the gene alterations in response to sulindac, a representative of a
class of agents, nonsteroidal anti-inflammatory drugs, that have
significant chemopreventive activity for colon cancer. Similar to
butyrate, there was a progressive recruitment of sequences over the
48 h treatment with sulindac (Fig. 5
). In total, 534 sequences were recruited into the response to sulindac,
similar to the 589 recruited by butyrate. However, the overlap between
these populations was limited, consisting of 145 sequences (Fig. 6 and B
). Even more surprising was that of these
145 sequences, 53 (37%) showed the opposite response to butyrate and
sulindac, rising with one of the agents but decreasing with the other
(Fig. 6
).
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, group 1 signaling genes), and 45 were repressed (Fig. 7C
,
group 2 signaling genes). The 78 genes that encode components of
signaling pathways that are altered over the time course of butyrate
treatment represent 27% of all named genes that change in the
experiment. Thus, extensive alterations in a large number of signaling
pathways and their components characterize the butyrate response.
However, for the group 1 signaling genes, all of which were induced by
butyrate (Fig. 7A
), most sequences did not respond to
sulindac, and of those that did, the number of genes that showed the
same response (induction) and the opposite response (repression) was
similar (Fig. 7B
). A similar relationship between response
to butyrate and sulindac exists for the group II genes, all of which
were repressed by butyrate (Fig. 7C
) but showed marked
heterogeneity in response to sulindac, with most showing no change in
expression with sulindac treatment (Fig. 7D
). This
illustrates that the signaling pathways that responded to butyrate and
sulindac overlapped only to a very limited degree.
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). By analysis of the Euclidean distances for this gene subset for all
of the agents, it was first determined that the time points at which
the response was maximal for the cell cycle genes (i.e.,
maximally different from control) were 48 h for sulindac and
curcumin, 16 h for butyrate, and 12 h for TSA (Fig. 4
). We
then calculated the Euclidean distances for the cell cycle genes
comparing each of TSA, sulindac, and curcumin to butyrate at these time
points. The analysis (Fig. 8A
) demonstrated that for the
functional class of genes responsible for cell cycle progression and
arrest, the profile of expression in response to butyrate was most like
the profile initiated by TSA and less like that initiated by sulindac,
although all three agents cause a
G0-G1 cell cycle arrest.
Interestingly, the cell cycle response to butyrate was least like that
initiated by curcumin, which is consistent with the
G2-M, rather than
G0-G1, arrest caused by
this compound. Finally, we extended the analysis to the Caco-2 cell
line, a colonic carcinoma cell line that undergoes spontaneous
G0-G1 cell cycle arrest and
absorptive cell differentiation upon contact inhibition of growth
(48)
. For the cell cycle genes, the butyrate response was
most like that of arrested Caco-2 cells and close to that of TSA. Fig. 8
, B and C, present analyses of the cell cycle
genes involved in these responses and lists their identities. These
analyses confirmed the closer relationship of the underlying mechanism
of cell cycle arrest between butyrate and TSA cell cycle arrest than
between butyrate and sulindac and demonstrated closest similarity in
mechanism between the physiological regulator butyrate in SW620 cells
and the spontaneous Caco-2 cell cycle arrest. Finally, these data
reflect the clear differences in mechanism of the
G0-G1 cell cycle arrest
induced by butyrate and the G2-M arrest induced
by curcumin.
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DISCUSSION |
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The response of the cells to butyrate, which stimulates a
G0-G1 cell cycle arrest,
differentiation along the absorptive cell lineage, and an apoptotic
cascade, is complex. There is a progressive recruitment of genes into
the reprogramming as a function of time, which is similar to an
expansion seen in the Caco-2 model of spontaneous differentiation
(unpublished). Overall, >7% of the sequences exhibit sustained
alterations in expression beyond levels defined by the distribution of
95% of the sequences in a control experiment in which two populations
of untreated cells were compared. Because the cells express a
complement of approximately 10,000–15,000 genes (51)
,
this implies that at least 1000 sequences show substantial alterations
in expression, an extent of change consistent with other reports on
reprogramming in differentiation and transformation (20
, 51, 52, 53, 54, 55, 56)
. This is a minimal estimate of the complexity of the
response for two reasons: (a) we have limited our analyses
to those sequences for which altered expression persists during the
experiment once the sequence is recruited into the response. There are
many more sequences that show transient increases or decreases over a
more limited period (not shown–entire database available on web site).
These changes may also be quite important in generating and regulating
the response to butyrate; and (b) we have also limited the
presentation to genes showing relatively large changes in expression.
In fact, ANOVA for sequences that fall within the ratios seen in
comparing two control cultures (Fig. 1
) shows significant alterations
in butyrate-treated cells compared with control (data not shown),
therefore adding another, more subtle, dimension to the cell maturation
program. The first conclusion, therefore, is that a physiological
regulator of colonic cell maturation initiates a highly complex
reprogramming of the cell.
The complexity of this reprogramming has important implications for
understanding how pathways of cell cycling, lineage-specific
differentiation, and cell death are coordinated to maintain homeostasis
and proper functioning of the mucosa. For example, within two
functional classes we have presented, genes involved in signal
transduction and cell cycling, there are a large number of significant
modulations in expression of many genes that are generally considered
fundamentally important in pathways of cell maturation
(e.g., phospholipase 3, NF-
B, integrin ß5, cyclins A,
B, and C, c-myc), and many of these distinguish the butyrate
response from the response to sulindac. It would be straightforward to
select any one of these as an example of an important change possibly
critical for the response of the cells and pursue questions of its
regulation and effects of its altered expression by methods now
standard in molecular biology. However, the large number of such
alterations suggest that each cannot be considered out of context of
the overall response. In addition, for any individual sequence,
measurement of expression alone cannot reflect contributions of
translational or posttranslational regulation. Consequently,
consideration of the interactions of expression of large numbers of
genes, which would encompass altered expression of genes involved in
these other levels of regulation, may more accurately reflect cell
phenotype. Thus, it is the integration of many altered regulatory and
functional circuits that determines the probability of a cell’s
behavior, such as continuation of proliferation, or cell cycle arrest
accompanied by differentiation and/or apoptosis
This complex reprogramming appears to be organized into a cascade of altered pathways, as evidenced by the smooth expansion of the magnitude of the response as a function of time and the recruitment of a large number of signaling pathways and their components. In contrast, TSA and curcumin induce more limited changes, and these are transient and do not expand with time. Sulindac also stimulates extensive alterations that increase with time, but it is clear that the response of signaling pathways, genes involved in cell cycle progression and of other genes in general shows little overlap between sulindac and butyrate. Therefore, the second conclusion is that colonic cells use links that have evolved between pathways to integrate the response to a physiological regulator (butyrate), but these links are not recruited, and the integration is abrogated, in response to novel agents that cells have not seen during evolution or development.
In characterizing the altered profiles of gene expression induced by the agents, clusters of genes could be identified that exhibited similarity in response among the four different profiles. Thus, there are underlying mechanisms that the agents have in common. The potential for uncovering particular classes of genes that are coregulated was clearly demonstrated by the use of the differing kinetics of inhibition of HDAC activity by butyrate and TSA, coupled with the profiles of gene expression specifically altered by these agents, to identify two clusters of genes that are likely to be coordinately regulated by this mechanism.
However, despite instances of similarity in response among the agents,
a most striking observation was how different the responses were at a
molecular level, although three of the agents, butyrate, sulindac, and
TSA, all generate a G0-G1
cell cycle arrest, dissipate the 
m, trigger
an apoptotic cascade, and up-regulate ß-catenin-Tcf (9)
.
This was most dramatically illustrated by analysis of two functional
classes of genes: (a) there was little consistency in genes
involved in signal transduction pathways when butyrate was compared
with sulindac; (b) within a population of genes related to
cell cycle progression, butyrate was shown to induce alterations in the
profile of gene expression that were very similar to that induced
during spontaneous Caco-2 cell maturation. However, although both
butyrate and sulindac induce a
G0-G1 arrest, the mechanism
of sulindac-induced cell cycle arrest was quite different from that
induced by butyrate, although not as different as the mechanisms of
curcumin-induced G2-M arrest.
The third conclusion, therefore, is that molecular profiling of response to a physiological regulator of cell maturation can provide important information for design and interpretation of chemopreventive strategies for colon cancer in at least three ways:
(a) Agents can be characterized that have similar and different mechanisms of action, and combinations may be chosen that may be synergistic in effect, and this synergism evaluated by experiments on cell lines similar to those reported here. An excellent example of this was the analysis of the responses by N-dimensional Euclidean distance, which demonstrated greater similarity of response between butyrate and TSA and between sulindac and curcumin than between the two groups.
(b) The potential for toxicity or adverse side effects of agents may be evaluated by comparison to the response to a physiological regulator, in this case, butyrate. This is of particular importance in chemoprevention, where intervention is contemplated in essentially healthy individuals over many decades, and harmful effects must be minimal. In this regard, it is important that the response to sulindac, which is an inhibitor of gastrointestinal tumor formation, differed so markedly from that induced by butyrate, especially in regards to two important functional classes: signaling genes and cell cycle genes. Sulindac is known to have extensive side effects, including mucosal ulceration, and a potentially important association with development of rectal tumors in patients treated over lengthy periods (57, 58, 59) , and cecal tumors in mice that inherit a mutant apc allele.7
(c) These databases on response in vitro will be useful for the evaluation of the effects of both chemopreventive and chemotherapeutic agents in clinical trials. As the databases are expanded, it will be possible to link responses in tumors to specific cellular behavior, such as pathways of cell cycle arrest, apoptosis, and lineage-specific differentiation by reference to these databases and to tailor treatment based on the knowledge of which pathways are defective in the tumor in combination with these data on which pathways respond to a given agent.
To fully exploit the information gained from these experiments, the databases, analyses, and gene clusters identified, as well as expansions of the work that will encompass many more sequences and models of lineage-specific differentiation of colonic epithelial cells and response to additional chemopreventive agents, will be made available.8
In summary, we have extended our original observations on quantitative profiling of gene expression that characterize risk for tumor formation in the colonic mucosa and response of transformed colonic cells to the physiological inducer butyrate. The data are expanded from an approach that encompassed middle abundant and abundant sequences (20 , 21) to a greater complexity of >8,000 genes. Over a decade ago, we suggested that such quantitative profiling of gene expression would be important in understanding cell phenotype (60) and would have significant clinical utility (20 , 21 , 61) . This is now borne out by these studies, as well as elegant work from other laboratories (28 , 62, 63, 64, 65) . Continued expansion of these databases to other systems and analysis of a larger proportion of the expressed sequences will provide new approaches for strategies and evaluation of chemoprevention of colon cancer.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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1 Supported in part by Grants CA75246, CA77552,
and P13330 from the National Cancer Institute and by a fellowship (to
J. M.) from the American Institute for Cancer Research. 
2 To whom requests for reprints should be
addressed, at Department of Oncology, Albert Einstein Cancer Center,
Montefiore Hospital, 111 East 210th St., Bronx, NY 10467.
Phone: (718) 920-4663; Fax: (718) 882-4464; Email: augen{at}aecom.yu.edu
3 The abbreviations used are: SCFA, short-chain
fatty acid; HDAC, histone deacetylase; TSA, trichostatin A.
4 All databases, analyses, and gene clusters
identified are made available on our web site at
http://sequence.aecom.yu.edu/genome/.
5 Details of the robot and methods for producing
and analyzing the arrays can be found at
http://sequence.aecom.yu.edu/genome/.
6 A listing of all of the sequences and how they
are differentially expressed as a function of time is posted on our web
site at http://sequence.aecom.yu.edu/genome/.
7 K. Yang and M. Lipkin, unpublished
observations.
8 Internet address:
http://sequence.aecom.yu.edu/genome/.
Received 4/13/00. Accepted 6/29/00.
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 E. K. Murray, A. Hien, G. J. de Vries, and N. G. Forger Epigenetic Control of Sexual Differentiation of the Bed Nucleus of the Stria Terminalis Endocrinology, September 1, 2009; 150(9): 4241 - 4247. [Abstract] [Full Text] [PDF]
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 H. Bhatia, J. L. Hallock, A. Dutta, S. Karkashon, L. S. Sterner, T. Miyazaki, A. Dean, and J. A. Little Short-chain fatty acid-mediated effects on erythropoiesis in primary definitive erythroid cells Blood, June 18, 2009; 113(25): 6440 - 6448. [Abstract] [Full Text] [PDF]
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 C. Haumaitre, O. Lenoir, and R. Scharfmann Histone Deacetylase Inhibitors Modify Pancreatic Cell Fate Determination and Amplify Endocrine Progenitors Mol. Cell. Biol., October 15, 2008; 28(20): 6373 - 6383. [Abstract] [Full Text] [PDF]
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 M. S. Makki, T. Heinzel, and C. Englert TSA downregulates Wilms tumor gene 1 (Wt1) expression at multiple levels Nucleic Acids Res., July 1, 2008; 36(12): 4067 - 4078. [Abstract] [Full Text] [PDF]
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 N. Wakamatsu, J. B. Collins, J. S. Parker, M. Tessema, N. P. Clayton, T.-V. T. Ton, H.-H. L. Hong, S. Belinsky, T. R. Devereux, R. C. Sills, et al. Gene Expression Studies Demonstrate that the K-ras/Erk MAP Kinase Signal Transduction Pathway and Other Novel Pathways Contribute to the Pathogenesis of Cumene-induced Lung Tumors Toxicol Pathol, July 1, 2008; 36(5): 743 - 752. [Abstract] [Full Text] [PDF]
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 H. T. Tan, S. Tan, Q. Lin, T. K. Lim, C. L. Hew, and M. C. M. Chung Quantitative and Temporal Proteome Analysis of Butyrate-treated Colorectal Cancer Cells Mol. Cell. Proteomics, June 1, 2008; 7(6): 1174 - 1185. [Abstract] [Full Text] [PDF]
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 V. Cucciolla, A. Borriello, M. Criscuolo, A. A. Sinisi, D. Bencivenga, A. Tramontano, A. C. Scudieri, A. Oliva, V. Zappia, and F. D. Ragione Histone deacetylase inhibitors upregulate p57Kip2 level by enhancing its expression through Sp1 transcription factor Carcinogenesis, March 1, 2008; 29(3): 560 - 567. [Abstract] [Full Text] [PDF]
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 L. M. Laguinge, R. N. Samara, W. Wang, W. S. El-Deiry, G. Corner, L. Augenlicht, L. Mishra, and J. M. Jessup DR5 Receptor Mediates Anoikis in Human Colorectal Carcinoma Cell Lines Cancer Res., February 1, 2008; 68(3): 909 - 917. [Abstract] [Full Text] [PDF]
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 K. K.W. To, O. Polgar, L. M. Huff, K. Morisaki, and S. E. Bates Histone Modifications at the ABCG2 Promoter following Treatment with Histone Deacetylase Inhibitor Mirror Those in Multidrug-Resistant Cells Mol. Cancer Res., January 1, 2008; 6(1): 151 - 164. [Abstract] [Full Text] [PDF]
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 S. S. N. Kolar, R. Barhoumi, E. S. Callaway, Y.-Y. Fan, N. Wang, J. R. Lupton, and R. S. Chapkin Synergy between docosahexaenoic acid and butyrate elicits p53-independent apoptosis via mitochondrial Ca2+ accumulation in colonocytes Am J Physiol Gastrointest Liver Physiol, November 1, 2007; 293(5): G935 - G943. [Abstract] [Full Text] [PDF]
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 A. Belenguer, S. H. Duncan, G. Holtrop, S. E. Anderson, G. E. Lobley, and H. J. Flint Impact of pH on Lactate Formation and Utilization by Human Fecal Microbial Communities Appl. Envir. Microbiol., October 15, 2007; 73(20): 6526 - 6533. [Abstract] [Full Text] [PDF]
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L. Klampfer, J. Huang, S. Shirasawa, T. Sasazuki, and L. Augenlicht Histone Deacetylase Inhibitors Induce Cell Death Selectively in Cells That Harbor Activated kRasV12: The Role of Signal Transducers and Activators of Transcription 1 and p21 Cancer Res., September 15, 2007; 67(18): 8477 - 8485. [Abstract] [Full Text] [PDF]
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L. Magnaghi-Jaulin, G. Eot-Houllier, G. Fulcrand, and C. Jaulin Histone Deacetylase Inhibitors Induce Premature Sister Chromatid Separation and Override the Mitotic Spindle Assembly Checkpoint Cancer Res., July 1, 2007; 67(13): 6360 - 6367. [Abstract] [Full Text] [PDF]
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 P. R. Kiela, N. Kuscuoglu, A. J. Midura, M. T. Midura-Kiela, C. B. Larmonier, M. Lipko, and F. K. Ghishan Molecular mechanism of rat NHE3 gene promoter regulation by sodium butyrate Am J Physiol Cell Physiol, July 1, 2007; 293(1): C64 - C74. [Abstract] [Full Text] [PDF]
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S. H. Duncan, A. Belenguer, G. Holtrop, A. M. Johnstone, H. J. Flint, and G. E. Lobley Reduced Dietary Intake of Carbohydrates by Obese Subjects Results in Decreased Concentrations of Butyrate and Butyrate-Producing Bacteria in Feces Appl. Envir. Microbiol., February 15, 2007; 73(4): 1073 - 1078. [Abstract] [Full Text] [PDF]
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 J. M. A. Oliveira, S. Chen, S. Almeida, R. Riley, J. Goncalves, C. R. Oliveira, M. R. Hayden, D. G. Nicholls, L. M. Ellerby, and A. C. Rego Mitochondrial-Dependent Ca2+ Handling in Huntington's Disease Striatal Cells: Effect of Histone Deacetylase Inhibitors J. Neurosci., October 25, 2006; 26(43): 11174 - 11186. [Abstract] [Full Text] [PDF]
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 L. H. Augenlicht, W. Yang, J. Mariadason, A. Velcich, L. Klampfer, M. Lipkin, and K. Yang Interaction of Genetic and Dietary Factors in Mouse Intestinal Tumorigenesis J. Nutr., October 1, 2006; 136(10): 2695S - 2696S. [Full Text] [PDF]
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K. E. Joung, K. N. Min, J. Y. An, D.-K. Kim, G. Kong, and Y. Y. Sheen Potent In vivo Anti-Breast Cancer Activity of IN-2001, a Novel Inhibitor of Histone Deacetylase, in MMTV/c-Neu Mice. Cancer Res., May 15, 2006; 66(10): 5394 - 5402. [Abstract] [Full Text] [PDF]
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 E. J. Yoo, J.-J. Chung, S. S. Choe, K. H. Kim, and J. B. Kim Down-regulation of Histone Deacetylases Stimulates Adipocyte Differentiation J. Biol. Chem., March 10, 2006; 281(10): 6608 - 6615. [Abstract] [Full Text] [PDF]
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W. Huang, S. Batra, S. Korrapati, V. Mishra, and K. D. Mehta Selective Repression of Low-Density Lipoprotein Receptor Expression by SP600125: Coupling of Histone H3-Ser10 Phosphorylation and Sp1 Occupancy Mol. Cell. Biol., February 15, 2006; 26(4): 1307 - 1317. [Abstract] [Full Text] [PDF]
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 I. A. Kim, J. H. Shin, I. H. Kim, J. H. Kim, J. S. Kim, H. G. Wu, E. K. Chie, S. W. Ha, C. I. Park, and G. D. Kao Histone Deacetylase Inhibitor-Mediated Radiosensitization of Human Cancer Cells: Class Differences and the Potential Influence of p53 Clin. Cancer Res., February 1, 2006; 12(3): 940 - 949. [Abstract] [Full Text] [PDF]
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L. H. Augenlicht Pathways in Nutritional Modulation of Homeostasis and Tumorigenesis J. Nutr., December 1, 2005; 135(12): 3025S - 3026S. [Full Text] [PDF]
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B. G. Heerdt, M. A. Houston, and L. H. Augenlicht The Intrinsic Mitochondrial Membrane Potential of Colonic Carcinoma Cells Is Linked to the Probability of Tumor Progression Cancer Res., November 1, 2005; 65(21): 9861 - 9867. [Abstract] [Full Text] [PDF]
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 I. Nusinzon and C. M. Horvath Histone Deacetylases as Transcriptional Activators? Role Reversal in Inducible Gene Regulation Sci. Signal., August 9, 2005; 2005(296): re11 - re11. [Abstract] [Full Text] [PDF]
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A. W. Walker, S. H. Duncan, E. C. McWilliam Leitch, M. W. Child, and H. J. Flint pH and Peptide Supply Can Radically Alter Bacterial Populations and Short-Chain Fatty Acid Ratios within Microbial Communities from the Human Colon Appl. Envir. Microbiol., July 1, 2005; 71(7): 3692 - 3700. [Abstract] [Full Text] [PDF]
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 A. M. Melnick, K. Adelson, and J. D. Licht The Theoretical Basis of Transcriptional Therapy of Cancer: Can It Be Put Into Practice? J. Clin. Oncol., June 10, 2005; 23(17): 3957 - 3970. [Abstract] [Full Text] [PDF]
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B. L. Pool-Zobel, V. Selvaraju, J. Sauer, T. Kautenburger, J. Kiefer, K. K. Richter, M. Soom, and S. Wolfl Butyrate may enhance toxicological defence in primary, adenoma and tumor human colon cells by favourably modulating expression of glutathione S-transferases genes, an approach in nutrigenomics Carcinogenesis, June 1, 2005; 26(6): 1064 - 1076. [Abstract] [Full Text] [PDF]
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X. Tong, L. Yin, S. Joshi, D. W. Rosenberg, and C. Giardina Cyclooxygenase-2 Regulation in Colon Cancer Cells: MODULATION OF RNA POLYMERASE II ELONGATION BY HISTONE DEACETYLASE INHIBITORS J. Biol. Chem., April 22, 2005; 280(16): 15503 - 15509. [Abstract] [Full Text] [PDF]
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 M. J. Peart, G. K. Smyth, R. K. van Laar, D. D. Bowtell, V. M. Richon, P. A. Marks, A. J. Holloway, and R. W. Johnstone Identification and functional significance of genes regulated by structurally different histone deacetylase inhibitors PNAS, March 8, 2005; 102(10): 3697 - 3702. [Abstract] [Full Text] [PDF]
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J. Hu and N. H. Colburn Histone Deacetylase Inhibition Down-Regulates Cyclin D1 Transcription by Inhibiting Nuclear Factor-{kappa}B/p65 DNA Binding Mol. Cancer Res., February 1, 2005; 3(2): 100 - 109. [Abstract] [Full Text] [PDF]
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I. R. Sanderson Short Chain Fatty Acid Regulation of Signaling Genes Expressed by the Intestinal Epithelium J. Nutr., September 1, 2004; 134(9): 2450S - 2454S. [Abstract] [Full Text] [PDF]
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L. Klampfer, J. Huang, T. Sasazuki, S. Shirasawa, and L. Augenlicht Oncogenic Ras Promotes Butyrate-induced Apoptosis through Inhibition of Gelsolin Expression J. Biol. Chem., August 27, 2004; 279(35): 36680 - 36688. [Abstract] [Full Text] [PDF]
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 K. F. Toth, T. A. Knoch, M. Wachsmuth, M. Frank-Stohr, M. Stohr, C. P. Bacher, G. Muller, and K. Rippe Trichostatin A-induced histone acetylation causes decondensation of interphase chromatin J. Cell Sci., August 15, 2004; 117(18): 4277 - 4287. [Abstract] [Full Text] [PDF]
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L. Klampfer, J. Huang, L.-A. Swaby, and L. Augenlicht Requirement of Histone Deacetylase Activity for Signaling by STAT1 J. Biol. Chem., July 16, 2004; 279(29): 30358 - 30368. [Abstract] [Full Text] [PDF]
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M. K. Yu, P. J. Moos, P. Cassidy, M. Wade, and F. A. Fitzpatrick Conditional Expression of 15-Lipoxygenase-1 Inhibits the Selenoenzyme Thioredoxin Reductase: MODULATION OF SELENOPROTEINS BY LIPOXYGENASE ENZYMES J. Biol. Chem., July 2, 2004; 279(27): 28028 - 28035. [Abstract] [Full Text] [PDF]
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C. Muller-Tidow, B. Steffen, T. Cauvet, L. Tickenbrock, P. Ji, S. Diederichs, B. Sargin, G. Kohler, M. Stelljes, E. Puccetti, et al. Translocation Products in Acute Myeloid Leukemia Activate the Wnt Signaling Pathway in Hematopoietic Cells Mol. Cell. Biol., April 1, 2004; 24(7): 2890 - 2904. [Abstract] [Full Text] [PDF]
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S. M. Dehm, T. L. Hilton, E. H. Wang, and K. Bonham SRC Proximal and Core Promoter Elements Dictate TAF1 Dependence and Transcriptional Repression by Histone Deacetylase Inhibitors Mol. Cell. Biol., March 15, 2004; 24(6): 2296 - 2307. [Abstract] [Full Text] [PDF]
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T.-H. Leu, H. H. Yeh, C.-C. Huang, Y.-C. Chuang, S. L. Su, and M.-C. Maa Participation of p97Eps8 in Src-mediated Transformation J. Biol. Chem., March 12, 2004; 279(11): 9875 - 9881. [Abstract] [Full Text] [PDF]
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C. S. Mitsiades, N. S. Mitsiades, C. J. McMullan, V. Poulaki, R. Shringarpure, T. Hideshima, M. Akiyama, D. Chauhan, N. Munshi, X. Gu, et al. Transcriptional signature of histone deacetylase inhibition in multiple myeloma: Biological and clinical implications PNAS, January 13, 2004; 101(2): 540 - 545. [Abstract] [Full Text] [PDF]
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J. M. Mariadason, D. Arango, Q. Shi, A. J. Wilson, G. A. Corner, C. Nicholas, M. J. Aranes, M. Lesser, E. L. Schwartz, and L. H. Augenlicht Gene Expression Profiling-Based Prediction of Response of Colon Carcinoma Cells to 5-Fluorouracil and Camptothecin Cancer Res., December 15, 2003; 63(24): 8791 - 8812. [Abstract] [Full Text] [PDF]
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L. Klampfer, J. Huang, G. Corner, J. Mariadason, D. Arango, T. Sasazuki, S. Shirasawa, and L. Augenlicht Oncogenic Ki-Ras Inhibits the Expression of Interferon-responsive Genes through Inhibition of STAT1 and STAT2 Expression J. Biol. Chem., November 21, 2003; 278(47): 46278 - 46287. [Abstract] [Full Text] [PDF]
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J. Zhang, H. Wong, S. Ramanan, D. Cheong, A. Leong, and S. C. Hooi The Proline-Rich Acidic Protein Is Epigenetically Regulated and Inhibits Growth of Cancer Cell Lines Cancer Res., October 15, 2003; 63(20): 6658 - 6665. [Abstract] [Full Text] [PDF]
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B. G. Heerdt, M. A. Houston, A. J. Wilson, and L. H. Augenlicht The Intrinsic Mitochondrial Membrane Potential ({Delta}{psi}m) Is Associated with Steady-State Mitochondrial Activity and the Extent to Which Colonic Epithelial Cells Undergo Butyrate-mediated Growth Arrest and Apoptosis Cancer Res., October 1, 2003; 63(19): 6311 - 6319. [Abstract] [Full Text] [PDF]
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L. Klampfer, J. Huang, T. Sasazuki, S. Shirasawa, and L. Augenlicht Inhibition of Interferon {gamma} Signaling by the Short Chain Fatty Acid Butyrate Mol. Cancer Res., September 1, 2003; 1(11): 855 - 862. [Abstract] [Full Text] [PDF]
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J. A. Plumb, P. W. Finn, R. J. Williams, M. J. Bandara, M. R. Romero, C. J. Watkins, N. B. La Thangue, and R. Brown Pharmacodynamic Response and Inhibition of Growth of Human Tumor Xenografts by the Novel Histone Deacetylase Inhibitor PXD101 Mol. Cancer Ther., August 1, 2003; 2(8): 721 - 728. [Abstract] [Full Text] [PDF]
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L. H. Augenlicht, A. Velcich, L. Klampfer, J. Huang, G. Corner, M. Aranes, C. Laboisse, B. Rigas, M. Lipkin, K. Yang, et al. Application of Gene Expression Profiling to Colon Cell Maturation, Transformation and Chemoprevention J. Nutr., July 1, 2003; 133(7): 2410S - 2416. [Abstract] [Full Text] [PDF]
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J. R. Davie Inhibition of Histone Deacetylase Activity by Butyrate J. Nutr., July 1, 2003; 133(7): 2485S - 2493. [Abstract] [Full Text] [PDF]
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M. Ferguson, P. A. Henry, and R. A. Currie Histone deacetylase inhibition is associated with transcriptional repression of the Hmga2 gene Nucleic Acids Res., June 15, 2003; 31(12): 3123 - 3133. [Abstract] [Full Text] [PDF]
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 J. C. Fleet, L. Wang, O. Vitek, B. A. Craig, and H. J. Edenberg Gene expression profiling of Caco-2 BBe cells suggests a role for specific signaling pathways during intestinal differentiation Physiol Genomics, March 18, 2003; 13(1): 57 - 68. [Abstract] [Full Text] [PDF]
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K. B. Glaser, M. J. Staver, J. F. Waring, J. Stender, R. G. Ulrich, and S. K. Davidsen Gene Expression Profiling of Multiple Histone Deacetylase (HDAC) Inhibitors: Defining a Common Gene Set Produced by HDAC Inhibition in T24 and MDA Carcinoma Cell Lines Mol. Cancer Ther., February 1, 2003; 2(2): 151 - 163. [Abstract] [Full Text] [PDF]
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L. H. Augenlicht, J. M. Mariadason, A. Wilson, D. Arango, W. Yang, B. G. Heerdt, and A. Velcich Short Chain Fatty Acids and Colon Cancer J. Nutr., December 1, 2002; 132(12): 3804S - 3808. [Abstract] [Full Text] [PDF]
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C. N. Johnstone, L. M. Chang, and M. Ernst AACR Special Meeting in Cancer Research: Colon Cancer--Genetics to Prevention Cancer Res., November 15, 2002; 62(22): 6779 - 6783. [Full Text] [PDF]
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A. J. Wilson, A. Velcich, D. Arango, A. R. Kurland, S. M. Shenoy, R. C. Pezo, J. M. Levsky, R. H. Singer, and L. H. Augenlicht Novel Detection and Differential Utilization of a c-myc Transcriptional Block in Colon Cancer Chemoprevention Cancer Res., November 1, 2002; 62(21): 6006 - 6010. [Abstract] [Full Text] [PDF]
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Y.-Y. E. Chuang, Y. Chen, Gadisetti, V. R. Chandramouli, J. A. Cook, D. Coffin, M.-H. Tsai, W. DeGraff, H. Yan, S. Zhao, et al. Gene Expression after Treatment with Hydrogen Peroxide, Menadione, or t-Butyl Hydroperoxide in Breast Cancer Cells Cancer Res., November 1, 2002; 62(21): 6246 - 6254. [Abstract] [Full Text] [PDF]
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J. M. Mariadason, D. Arango, G. A. Corner, M. J. Aranes, K. A. Hotchkiss, W. Yang, and L. H. Augenlicht A Gene Expression Profile That Defines Colon Cell Maturation in Vitro Cancer Res., August 15, 2002; 62(16): 4791 - 4804. [Abstract] [Full Text] [PDF]
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P. Gelebart, T. Kovacs, J.-P. Brouland, R. van Gorp, J. Grossmann, N. Rivard, Y. Panis, V. Martin, R. Bredoux, J. Enouf, et al. Expression of Endomembrane Calcium Pumps in Colon and Gastric Cancer Cells. INDUCTION OF SERCA3 EXPRESSION DURING DIFFERENTIATION J. Biol. Chem., July 12, 2002; 277(29): 26310 - 26320. [Abstract] [Full Text] [PDF]
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G. K. Scott, C. Marden, F. Xu, L. Kirk, and C. C. Benz Transcriptional Repression of ErbB2 by Histone Deacetylase Inhibitors Detected by a Genomically Integrated ErbB2 Promoter-reporting Cell Screen Mol. Cancer Ther., April 1, 2002; 1(6): 385 - 392. [Abstract] [Full Text] [PDF]
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P. R. Kiela, E. R. Hines, J. F. Collins, and F. K. Ghishan Regulation of the rat NHE3 gene promoter by sodium butyrate Am J Physiol Gastrointest Liver Physiol, October 1, 2001; 281(4): G947 - G956. [Abstract] [Full Text] [PDF]
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 W. Zhang, P. D. Bardwell, C. J. Woo, V. Poltoratsky, M. D. Scharff, and A. Martin Clonal instability of V region hypermutation in the Ramos Burkitt's lymphoma cell line Int. Immunol., September 1, 2001; 13(9): 1175 - 1184. [Abstract] [Full Text] [PDF]
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W. Yang, A. Velcich, J. Mariadason, C. Nicholas, G. Corner, M. Houston, W. Edelmann, R. Kucherlapati, P. R. Holt, and L. H. Augenlicht p21WAF1/cip1 Is an Important Determinant of Intestinal Cell Response to Sulindac in Vitro and in Vivo Cancer Res., August 1, 2001; 61(16): 6297 - 6302. [Abstract] [Full Text] [PDF]
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S. Srivastava, M. Verma, and D. E. Henson Biomarkers for Early Detection of Colon Cancer Clin. Cancer Res., May 1, 2001; 7(5): 1118 - 1126. [Abstract] [Full Text]
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J. M. Mariadason, M. Bordonaro, F. Aslam, L. Shi, M. Kuraguchi, A. Velcich, and L. H. Augenlicht Down-Regulation of {beta}-Catenin TCF Signaling Is Linked to Colonic Epithelial Cell Differentiation Cancer Res., April 1, 2001; 61(8): 3465 - 3471. [Abstract] [Full Text]
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H. Brinkmann, A. L. Dahler, C. Popa, M. M. Serewko, P. G. Parsons, B. G. Gabrielli, A. J. Burgess, and N. A. Saunders Histone Hyperacetylation Induced by Histone Deacetylase Inhibitors Is Not Sufficient to Cause Growth Inhibition in Human Dermal Fibroblasts J. Biol. Chem., June 15, 2001; 276(25): 22491 - 22499. [Abstract] [Full Text] [PDF]
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A. McCampbell, A. A. Taye, L. Whitty, E. Penney, J. S. Steffan, and K. H. Fischbeck Histone deacetylase inhibitors reduce polyglutamine toxicity PNAS, December 18, 2001; 98(26): 15179 - 15184. [Abstract] [Full Text] [PDF]
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