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Prepublished online as a Blood First Edition Paper on May 15, 2003; DOI 10.1182/blood-2003-02-0359.
 Previous Article | Table of Contents | Next Article 
Blood, 1 September 2003, Vol. 102, No. 5, pp. 1613-1618
CLINICAL OBSERVATIONS, INTERVENTIONS, AND THERAPEUTIC
TRIALS
BAALC expression predicts clinical outcome of de novo acute myeloid leukemia patients with normal cytogenetics: a Cancer and Leukemia Group B Study
Claudia D. Baldus,
Stephan M. Tanner,
Amy S. Ruppert,
Susan P. Whitman,
Kellie J. Archer,
Guido Marcucci,
Michael A. Caligiuri,
Andrew J. Carroll,
James W. Vardiman,
Bayard L. Powell,
Steven L. Allen,
Joseph O. Moore,
Richard A. Larson,
Jonathan E. Kolitz,
Albert de la Chapelle, and
Clara D. Bloomfield
From The Comprehensive Cancer Center, The Ohio State University,
Columbus; The CALGB Statistical Center, Durham, NC; the University of Alabama
at Birmingham; the University of Chicago, IL; the Wake Forest University
School of Medicine, Winston-Salem, NC; the North Shore University Hospital,
Manhasset, NY; and the Duke University School of Medicine, Durham, NC.
 |
Abstract
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Cytogenetic aberrations are important prognostic factors in acute myeloid
leukemia (AML). Of adults with de novo AML, 45% lack cytogenetic
abnormalities, and identification of predictive molecular markers might
improve therapy. We studied the prognostic impact of BAALC (Brain And
Acute Leukemia, Cytoplasmic), a novel gene involved in leukemia, in 86 de novo
AML patients with normal cytogenetics who were uniformly treated on Cancer and
Leukemia Group B 9621. BAALC expression was determined by comparative
real-time reverse transcriptase–polymerase chain reaction in
pretreatment blood samples, and patients were dichotomized at BAALC's
median expression into low and high expressers. Low expressers had higher
white counts (P = .03) and more frequent French-American-British M5
morphology (P = .007). Compared to low expressers, high
BAALC expressers showed significantly inferior overall survival (OS;
median, 1.7 vs 5.8 years, P = .02), event-free survival (EFS; median,
0.8 vs 4.9 years, P = .03), and disease-free survival (DFS; median,
1.4 vs 7.3 years, P = .03). Multivariable analysis confirmed high
BAALC expression as an independent risk factor. For high
BAALC expressers the hazard ratio of an event for OS, EFS, and DFS
was respectively 2.7, 2.6, and 2.2. We conclude that high BAALC
expression predicts an adverse prognosis and may define an important risk
factor in AML with normal cytogenetics.
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Introduction
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Clonal cytogenetic abnormalities are one of the most important factors
predicting clinical outcome in acute myeloid leukemia (AML) and are used to
guide risk-adapted treatment
strategies.1-3
However, approximately 45% of adults younger than 60 with de novo AML have
normal cytogenetics and therefore lack informative chromosome
markers.4,5
With current therapies 42% to 43% of these patients are long-term survivors,
and 40% to 47% of complete responders remain in continuous remission at 5
years.3,6,7
To date, several pretreatment clinical or laboratory prognostic factors have
been identified in AML patients with intermediate risk
cytogenetics,8-13
but very few markers have been consistently shown to be predictive in patients
with normal
cytogenetics.14-17
Consequently, in patients with a normal karyotype new molecular markers
identifying those who are at risk to fail standard therapeutic approaches are
warranted to optimize treatment strategies.
In a search for novel genes involved in leukemia, we identified
BAALC (Brain And Acute Leukemia, Cytoplasmic), a gene located on
chromosome
8q22.3.18 DNA
sequence and expression pattern were highly conserved among mammals, whereas
no orthologs were found in lower organisms. The protein sequence showed no
homology to any known proteins or functional domains. Expression of
BAALC was found mainly in neuroectoderm-derived tissues and
hematopoietic precursor cells. In hematopoietic cells, BAALC
expression was restricted to the compartment of progenitor cells, whereas no
expression was detected in mature bone marrow or circulating white blood
cells.19 In
leukemias, we found high BAALC expression in a subset of patients
with AML, acute lymphoblastic leukemia (ALL), and chronic myelogenous leukemia
(CML) in blast crisis, whereas no BAALC expression could be detected
in patients with chronic-phase CML or chronic lymphocytic leukemia
(CLL).18
High BAALC expression levels were first identified in a study of
AML patients with trisomy 8 as a sole
abnormality.18
Trisomy 8 has been associated with poor prognosis in
AML,2,5
and we therefore hypothesized that BAALC expression might assist in
prognosis of AML patients lacking cytogenetic aberrations. To do this, we
examined a well-defined cohort of adult patients younger than 60 years of age,
diagnosed with de novo AML, and treated on a single dose-intensive protocol
within the Cancer and Leukemia Group B (CALGB 9621). Since we have previously
shown that a FLT3 internal tandem duplication (ITD) in the absence of
a FLT3 wild-type (WT) allele identifies AML patients with a normal
karyotype with a very poor prognosis on CALGB
9621,14 in the
current study we focused on 86 AML patients with normal cytogenetics who
lacked this adverse prognostic factor. We used quantitative real-time reverse
transcriptase–polymerase chain reaction (RT-PCR) to analyze messenger
RNA levels of BAALC in pretreatment blood samples. Our data show that
high BAALC expression is an independent adverse prognostic factor
among intensively treated younger adults with cytogenetically normal de novo
AML.
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Patients and methods
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Patients
This study included 86 patients enrolled on CALGB treatment trial 9621 who
had a primary diagnosis of AML, a centrally confirmed pretreatment normal bone
marrow karyotype, a centrally determined pretreatment bone marrow
FLT3 genotype containing a wild-type allele, and available
pretreatment blood stored in the CALGB Leukemia Tissue Bank on CALGB protocol
9665.20-22
This represents 74% of all patients enrolled on CALGB 9621 who met the
eligibility criteria. There were no significant differences in outcome
(P  .54 for all endpoints) or clinical features for the remaining
31 patients not included in this study, except that patients not included had
a higher median percentage of bone marrow blasts (67% versus 58%, P =
.03). Pathologic diagnoses were reviewed centrally and classified according to
the French-American-British (FAB) schema. As required by CALGB 9621, all
patients were between ages 16 and 60, and patients with a prior history of
myelodysplasia, other antecedent hematologic malignancies, prior nonsteroidal
cytotoxic chemotherapy or radiation therapy, pre-existing liver disease, or
uncontrolled infection were excluded. Written informed consent was obtained
from all patients. Of the 86 AML patients, 26 were included in the first
published report on
BAALC.18
Approval was obtained from the Ohio State University institutional review
board for these studies according to the Declaration of Helsinki.
Cytogenetic and FLT3 studies
All patients included in this analysis were enrolled on CALGB 8461, a
prospective cytogenetics protocol. Cytogenetic analyses of bone marrow were
performed in institutional CALGB cytogenetics laboratories, and karyotypes
were reviewed centrally. Specimens were obtained at diagnosis from all
patients and processed using unstimulated short-term (24-, 48-, and 72-hour)
cultures with or without a direct method. G-banding was usually done, although
Q-banding also was acceptable. The criteria used to describe a cytogenetic
clone and description of karyotype followed the recommendations of the
International System for Human Cytogenetic Nomenclature (ISCN;
1995).23 A minimum
of 20 bone marrow metaphases was required to be examined for a patient to be
classified as having normal
cytogenetics.5
The FLT3 genotype was determined using previously described
techniques.14
Briefly, PCR and RT-PCR were carried out using primers that detect the length
mutations discovered for the FLT3
gene.24 Long-range
DNA PCRs were performed in the FLT3 gene extending from exon 10 to
the 3'-end of exon 12. Two genotypes including the WT allele were
distinguished, one with the ITD, designated FLT3ITD/WT,
and one without, designated FLT3WT/WT.
Treatment
Patients received induction chemotherapy consisting of cytarabine,
daunorubicin, and etoposide (ADE) with or without the multidrug resistance
protein modulator,
PSC-833.20 For
patients achieving complete remission (CR), this was followed by autologous
peripheral blood stem cell transplantation (PBSCT) using high-dose etoposide
and cytarabine for "in vivo purging" and stem cell mobilization
followed by a myeloablative regimen of busulfan and
etoposide.21
Patients unable to receive PBSCT were consolidated with a regimen consisting
of the "in vivo purging" portion of the PBSCT sequence followed by
2 cycles of high-dose cytarabine. Following consolidation, patients received a
90-day low-dose subcutaneous interleukin-2 (IL-2, Proleukin, Chiron,
Emeryville, CA) regimen interrupted with intermediate dose pulsing of
subcutaneous IL-2 every 2 weeks.
BAALC determination
Mononuclear cells from pretreatment blood samples were enriched by
Ficoll-Hypaque gradient and frozen in liquid nitrogen. Total RNA was extracted
from thawed samples using Trizol reagent (Invitrogen, Carlsbad, CA) following
the manufacturer's directions. Complementary DNA (cDNA) was synthesized using
0.5 µg RNA, avian myeloblastosis virus reverse transcriptase (Roche,
Indianapolis, IN), and gene-specific primers for glucose-phosphate isomerase
(GPI) and BAALC at 50°C for 60 minutes in the presence
of RNase inhibitor (RNasin; Roche).
Comparative real-time RT-PCR assays were performed for each sample in
triplicate in a final reaction volume of 25 µL. GPI and
BAALC were coamplified in the same tube using 2 µL cDNA, 1 x
universal master mix (Applied Biosystems, Foster City, CA), 250 nM human
GPI probe (VIC-labeled) with 600 nM each of the GPI forward
and reverse primers, and 250 nM of BAALC probe (6-FAM-labeled) with
900 nM each of the BAALC forward and reverse primers. Final
concentrations of primers and probes were chosen based on optimization
experiments. Primers for GPI and BAALC were intron spanning.
Probes were labeled with quencher TAMRA at the 3'-end. Amplification was
carried out at 50°C for 2 minutes, 95°C for 10 minutes, followed by 40
PCR cycles at 95°C for 15 seconds, and 60°C for 1 minute. All
reactions were done in MicroAmp optical 96-well plates using an ABI Prism 7700
sequence detection system (Applied Biosystems). Sequences of primers and
probes are available upon request. The comparative cycle threshold
(CT) method was used to determine the relative expression levels of
BAALC (Applied Biosystems). The threshold cycles for BAALC
and GPI were determined, and the cycle number difference
( CT = GPI-BAALC) was calculated for each
replicate. Relative BAALC expression values were calculated using the
mean of CT from the 3 replicates, that is,
µ(CT) = ( CT)/3, and expressed as
2µ(CT).
Positive and negative controls were included in all assays. To assess
reproducibility of the assay, samples from 28 AML patients with high and low
BAALC expression values were split and evaluated on different days.
Data generated showed high reproducibility of the results (Pearson correlation
coefficient, r = 0.98).
In addition to real-time RT-PCR, comparative semiquantitative RT-PCR was
carried out in a final volume of 50 µL containing 1 µL cDNA, 2.5 U
AmpliTaq Gold, 100 nM of each dNTP (all Roche), and 20 pmol of each primer.
Conditions were 95°C for 10 minutes, 32 cycles of 95°C for 15 seconds,
58°C for 15 seconds, and 72°C for 1 minute with a final step of
72°C for 5 minutes. Levels of BAALC amplification products were
estimated relative to the expression levels of the housekeeping gene
GPI on nondenaturing polyacrylamide gel electrophoresis after
staining with silver
nitrate.18,25
Statistical methods
To evaluate the impact of BAALC expression values on clinical
outcome without seeking an optimal cut point, AML samples were dichotomized at
the median value and divided into 2 expression groups: a low BAALC
group with BAALC values less than 0.166 (n = 43; median expression,
0.050; range, 0.000 03-0.163) and a high BAALC group consisting of
patients with BAALC values of more than 0.166 (n = 43; median
expression, 0.547; range, 0.170-4.532). BAALC values were calculated
as described in "BAALC determination."
Baseline clinical features were compared for patients expressing low
BAALC and those expressing high BAALC. Categorical variables
were compared using Fisher exact test and continuous variables using the
Wilcoxon rank sum test. The 2-sided level of significance was set at .05.
Complete remission required an absolute neutrophil count of at least
1500/µL, a platelet count of at least an  value of 100 x
109/L, no leukemic blasts in the blood, bone marrow cellularity
greater than 20% with maturation of all cell lines, no Auer rods, fewer than
5% bone marrow blast cells, and no extramedullary leukemia, with persistence
for at least one
month.26 Relapse
was defined as the reappearance of circulating blast cells not attributable to
"overshoot" following recovery from myelosuppressive therapy, or
greater than 5% blasts in the marrow not attributable to another cause, or
development of extramedullary leukemia.
Overall survival (OS) was measured from the protocol on-study date until
the date of death regardless of cause, censoring for patients alive at last
follow-up. Event-free survival (EFS) was defined for those achieving CR as the
time from on-study until relapse or death regardless of cause, censoring for
those alive at last follow-up. If a patient did not achieve CR but expired
within 2 months of the on-study date, then EFS was defined as the time from
on-study until death, regardless of cause. Otherwise, EFS was set at 2 months.
Disease-free survival (DFS) was defined only for those patients achieving a
CR. It was measured from the CR date until date of relapse or death,
regardless of cause, censoring for patients alive at last follow-up. Overall,
event-free and disease-free survival all were analyzed using the Kaplan-Meier
method, and the log-rank test was used to compare differences between survival
curves.27,28
To further investigate the effect of increasing expression of
BAALC, a Cox proportional hazards model was constructed, adjusting
for potential confounding covariates, using backward
elimination.29
Fractional polynomials were used to identify the most appropriate scaling for
the continuous
covariates.30
Univariate models integrating an artificial time-dependent covariate,
expressed as the product of the fixed-time covariate and the log of time, were
fit to check the proportional hazards assumption in conjunction with assessing
the scaled Schoenfeld
residuals.31 The
log-transformed BAALC failed to satisfy the proportional hazards
assumption, so BAALC was dichotomized at its median value, where the
assumption of proportional hazards was met, to represent high BAALC
expression versus low BAALC expression (see first paragraph in this
section). All covariates, including the BAALC indicator, whose
univariate models reflected a P value less than .20 from the a
likelihood ratio test were included in a full model. Variables with least
significance from the Wald statistic were eliminated one at a time until the
only variables in the model were significant at a P value of .05. Any
variables that were initially excluded from the model were added back into the
model to confirm that they were neither statistically significant nor an
important confounder, defined by a change in the estimated coefficients of at
least 20%. Lastly, interactions were considered important if the associated
P value was less than .05. Statistical analyses were performed by the
CALGB Statistical Center.
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Results
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BAALC expression in adult de novo AML with normal
karyotype
Pretreatment blood samples of 86 patients were evaluated for BAALC
expression by comparative real-time RT-PCR. BAALC values were calculated as
described in "BAALC determination." BAALC expression
levels represented a continuum ranging from 0.00003 to 4.532. High
BAALC expression was defined as the upper 50% of BAALC
values and low BAALC expression as the lower 50% of BAALC
values. In addition to the real-time RT-PCR assay, conventional
semiquantitative RT-PCR was performed and confirmed the results obtained by
the real-time RT-PCR (Figure
1).
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Figure 1.. BAALC mRNA expression in pretreatment AML samples as determined
by comparative RT-PCR and real-time RT-PCR.The gel illustrates the
comparative RT-PCR. The values shown below (expressed as
2µ(CT); see "Patients and
methods") are from real-time RT-PCR experiments on samples from the same
individuals. AML samples 1 to 3 represent cases with high level of
BAALC transcripts. Samples 4 to 6 represent AML cases from the low
BAALC group. M indicates size marker; R, reagent control.
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Clinical and laboratory characteristics at presentation and
treatment
There were no significant differences between high BAALC- and low
BAALC-expressing patients with respect to age, sex, hemoglobin,
platelet count, percentage of blasts in bone marrow or blood, race,
FLT3 genotype, or other presenting physical findings such as gum
hypertrophy, lymphadenopathy, splenomegaly, and hepatomegaly
(Table 1). Low BAALC
expression was associated with a significantly higher white blood count (WBC)
(median, 31.6 x 109/L versus 13.8 x 109/L,
P = .03), and M5 FAB morphology (24% versus 3%, P =
.007).
No significant differences were seen between high BAALC- and low
BAALC-expressing patients in the type of induction, consolidation, or
maintenance therapy received (Table
2). Fifty-three percent of patients in both groups were randomized
to induction chemotherapy with PSC-833. Sixty-six percent of low
BAALC expressers and 76% of high BAALC expressers received
autologous PBSCT in first CR. Sixteen high and 17 low BAALC
expressers received low-dose subcutaneous IL-2 maintenance therapy.
Correlation between BAALC expression and clinical
outcome
There was no significant difference in response to induction therapy
between the 2 cohorts: 35 (81%) of low BAALC and 33 (77%) of high
BAALC expressers achieved CR (P = .79,
Table 3). AML patients with
high BAALC expression tended to relapse more frequently than those
with low BAALC expression (52% versus 29%, P = .08). High
BAALC expression predicted significantly shorter OS (median, 1.7
versus 5.8 years, P = .02; Table
3). The probability of survival at 3 years was 39% in the high
BAALC group versus 60% in the low BAALC group
(Table 3;
Figure 2A). Event-free survival
also was significantly shorter in patients with high BAALC expression
compared to those with low BAALC expression (median, 0.8 versus 4.9
years, P = .03; Figure
2B), as was DFS (median, 1.4 versus 7.3 years, P = .03;
Figure 2C).
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Figure 2.. Kaplan-Meier analysis of OS, EFS, and DFS for de novo AML patients with
normal cytogenetics. AML patients with high BAALC expression show
significantly inferior OS (A), EFS (B), and DFS (C) compared to low
BAALC patients.
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We also looked at fitting a model based upon the 4 quartiles of
BAALC expression; this resulted in 4 fairly small groups. If the
first quartile was used as the reference group, the second quartile was
similar in outcome, whereas the third quartile had a worse outcome, and the
fourth quartile had an even worse outcome. Thus, we preferred to use the
median, grouping the second and first quartiles and then grouping the third
and fourth quartiles. However, there was strong evidence, using the test for
trend,32 that a
worse outcome was observed in at least one quartile of patients when compared
to patients in the preceding quartile (OS and DFS, P < .01; EFS,
P = .01), indicating that the higher the BAALC expression,
the higher the likelihood of an event.
Multivariable analysis of BAALC expression for OS, EFS, and
DFS
A multivariable analysis was conducted to determine if high BAALC
expression was a significant independent prognostic factor for OS, EFS, and
DFS once the model was adjusted for other characteristics. Variables
considered for model inclusion were log-transformed WBC, platelets,
hemoglobin, percentage of blasts in bone marrow and blood, age, FAB (M4/M5
versus others), sex, race (white versus other), treatment (ADE plus autologous
PBSCT versus ADE/PSC-833 plus autologous PBSCT), FLT3 genotype, and
BAALC expression. The variables included in the final models were
BAALC (OS, EFS, DFS), log-transformed WBC (OS, EFS), and age (EFS).
Controlling for all other covariates in the models, older patients (EFS) and
those with a higher WBC (OS, EFS) had a worse prognosis. After adjusting for
other covariates, BAALC expression remained a significant predictor
for OS and EFS.
Patients with high BAALC expression were 2.7 (95% CI: 1.4-5.0)
times more likely to die than patients with low BAALC expression. The
hazard ratio of an event for the high BAALC group in EFS was 2.6 (95%
CI: 1.4-4.7). BAALC expression was the only significant predictor for
DFS. The hazard ratio for high BAALC patients to fail treatment after
achieving CR, in the form of relapse or death, was 2.2 (95% CI: 1.1-4.5;
Table 4).
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Table 4.. Multivariable analysis of BAALC expression for overall
survival, event-free survival, and disease-free survival
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Discussion
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In this well-defined cohort of uniformly treated AML patients with a normal
karyotype, we have identified high BAALC expression in pretreatment
blood samples as an independent adverse prognostic factor for OS, EFS, and
DFS. Within this group of relatively young de novo AML patients who lack other
important risk factors, such as adverse chromosomal aberrations and the ITD of
FLT3 in the absence of a FLT3 WT allele, we were able to
identify a new subset of patients with a relatively unfavorable outcome. Even
in the setting of intensive chemotherapy and autologous transplantation, at 3
years only 39% of patients with high BAALC expression were alive and
only 39% of those achieving CR remained in continuous CR. In contrast, 60% of
low BAALC expressers were alive and 68% of those achieving CR
remained continuously disease-free at 3 years. Indeed, high BAALC
expression helped identify patients otherwise classified as "standard
risk" who were more than twice as likely to fail to achieve long-term
disease-free survival despite dose-intensive chemotherapy and autologous
peripheral stem cell transplantation.
Chromosomal abnormalities provide a powerful tool to stratify AML patients
into different prognostic risk groups. Patients lacking cytogenetic
aberrations, accounting for approximately 45% of newly diagnosed de novo AML
cases, are contained in an intermediate risk
group.1-3
In reality this is a heterogeneous cohort of patients with either favorable,
intermediate, or relatively poor clinical
outcome.5 Little is
known about underlying molecular mechanisms contributing to the clinical
heterogeneity of AML with a normal karyotype. For these patients the
identification of novel molecular markers is necessary to overcome the
limitations of current risk assessment and to design new risk-adapted
treatment strategies. Additional stratification could prevent overtreatment
and undertreatment by discriminating patients who would benefit from more
aggressive procedures including allogeneic stem cell transplantation.
Furthermore, molecular markers may elucidate underlying mechanisms involved in
leukemogenesis and may also serve as potential targets for new therapies.
Molecular studies have provided additional insights into prognostically
relevant markers in cytogenetically normal AML
patients.14-17
Most important have been mutations of the FLT3
gene.14,15
For the purpose of this study we excluded patients without a wild-type
FLT3 allele, as we have already documented very poor outcome on this
same CALGB treatment protocol 9621 for this small group of
patients.14 We
included patients with the more favorable FLT3WT/WT and
FLT3ITD/WT genotypes and found that the 2 groups were
equally frequent in the low and high BAALC expressers and did not
differ in clinical outcome. High BAALC expression remained a
significant adverse prognostic factor for FLT3ITD/WT and
FLT3WT/WT patients, compared to those with low
BAALC expression (OS, P = .002; hazard ratio [HR] = 2.7;
DFS, P = .04, HR = 2.2), even when the 8 additional patients
harboring a FLT3ITD/– genotype (4 showed
high BAALC expression and 4 showed low BAALC expression)
with normal cytogenetics and treated on CALGB 9621 were included in the
multivariable analyses for OS and DFS. However, no difference in OS and DFS
between the FLT3ITD/– patients with high
BAALC expression compared to those with low BAALC expression
was observed. High BAALC was an independent adverse prognostic factor
for EFS regardless of the FLT3 status (P = .008, HR = 2.2).
Thus, identification of high BAALC expression within AML patients
harboring the more favorable FLT3 genotypes further identified AML
patients with normal cytogenetics who are at higher risk to fail chemotherapy
and autologous transplantation.
Future studies may facilitate the design of new molecular-based risk
stratification for AML patients with normal cytogenetics. In this respect,
determination of the BAALC status may be useful to predict long-term
disease-free survival and to guide postremission therapy. Low levels of
BAALC expression identified patients with a favorable outcome treated
with chemotherapy and autologous stem cell transplantation. In contrast, high
BAALC expression predicted a relatively poor outcome in this study of
intensively treated patients. For these high-risk patients, more aggressive
procedures including early allogeneic transplantation or alternative
investigative therapies might be beneficial.
Several lines of evidence suggest that increased expression of
BAALC identifies a distinct subset among the leukemic phenotypes.
Whereas normal blood and bone marrow show very low levels of BAALC
expression, high levels of BAALC transcript can be detected in
hematopoietic progenitor cells as well as in leukemic blasts in some AML
patients. Furthermore, BAALC expression can be detected in patients
with ALL and CML in blast crisis, but BAALC transcripts are absent in
chronic phase CML and in
CLL.18 Given the
fact that BAALC expression in normal bone marrow is restricted to the
compartment of progenitor cells and that it shows high expression in a subset
of leukemic blasts, BAALC may be seen as a stage-specific marker
regulated during hematopoiesis and aberrantly expressed in leukemogenesis. The
function of the BAALC protein in hematopoiesis and leukemogenesis contributing
to a more aggressive behavior of AML has yet to be identified.
In summary, in AML patients with normal cytogenetics we have found that
high-level expression of the novel gene BAALC identified patients
less likely to achieve prolonged survival. Obviously, additional prospective
studies, including ones using standard less-intensive treatment regimens, are
needed to confirm and expand our results before BAALC expression can
be used routinely as a potential marker for risk stratification in adult de
novo AML. Furthermore, investigations are indicated to understand how the
BAALC protein contributes to a more aggressive leukemic phenotype.
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Appendix
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The following Cancer and Leukemia Group B institutions, principal
investigators, and cytogeneticists participated in this study:
Wake Forest University School of Medicine, Winston-Salem, NC: David D.
Hurd, Mark J. Pettenati, and Wendy L. Flejter (grant no. CA03927); North
Shore–Long Island Jewish Health System, Manhasset, NY: Daniel R. Budman
and Prasad R. K. Koduru (grant no. CA35279); Duke University Medical Center,
Durham, NC: Jeffrey Crawford and Mazin B. Qumsiyeh (grant no. CA47577); The
Ohio State University Medical Center, Columbus, OH: Clara D. Bloomfield and
Karl S. Theil (grant no. CA77658); Roswell Park Cancer Institute, Buffalo, NY:
Ellis G. Levine and AnneMarie W. Block (grant no. CA02599); University of
Massachusetts Medical Center, Worcester, MA: Mary Ellen Taplin and Vikram
Jaswaney (grant no. CA37135); Vermont Cancer Center, Burlington, VT: Hyman B.
Muss and Elizabeth F. Allen (grant no. CA77406); University of Iowa Hospitals,
Iowa City, IA: Gerald H. Clamon and Shivanand R. Patil (grant no. CA47642);
Washington University School of Medicine, St Louis, MO: Nancy L. Bartlett and
Michael S. Watson (grant no. CA77440); Mount Sinai School of Medicine, New
York, NY: Lewis R. Silverman and Vesna Najfeld (grant no. CA04457); University
of Chicago Medical Center, Chicago, IL: Gini Fleming, Michelle M. LeBeau, and
Diane Roulston (grant no. CA41287); Christiana Care Health Services, Inc.,
Newark, DE: Stephen S. Grubbs, Jeanne M. Meck, and Digamber S. Borgaonkar
(grant no. CA45418); Dana-Farber Partners Cancer Care, Boston, MA: George P.
Canellos, Paola Dal Cin, Cynthia C. Morton, Leonard L. Atkins, and Ramana
Tantravahi (grant no. CA32291); Eastern Maine Medical Center CCOP, Bangor, ME:
Philip L. Brooks and Laurent J. Beauregard (grant no. CA35406); Ft. Wayne
Medical Oncology/Hematology, Ft. Wayne, IN: Sreenivasa Nattam and Patricia I.
Bader; University of Illinois at Chicago: Thomas E. Lad and Maureen M.
McCorquodale (grant no. CA74811); University of Missouri/Ellis Fischel Cancer
Center, Columbia, MO: Michael C. Perry and Tim Huang (grant no. CA12046);
University of North Carolina at Chapel Hill: Thomas C. Shea and Kathleen W.
Rao (grant no. CA47559); University of Puerto Rico School of Medicine, San
Juan, PR: Enrique Velez-Garcia, Paola Dal Cin, Cynthia C. Morton, and Leonard
L. Atkins; Weill Medical College of Cornell University, New York, NY: Scott
Wadler and Prasad R. K. Koduru (grant no. CA07968); University of California
at San Diego: Stephen L. Seagren and Marie L. Dell'Aquila (grant no. CA11789);
Southern Nevada Cancer Research Foundation, Las Vegas, NV: John Ellerton and
Renée Bernstein (grant no. CA35421); University of Tennessee Memphis
Cancer Center: Harvey B. Niell and Sugandhi A. Tharapel (grant no. CA47555);
Walter Reed Army Medical Center, Washington, DC: Joseph J. Drabeck and Karl S.
Theil (grant no. CA26806).
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Acknowledgements
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We are grateful to John Byrd for critical reading of the manuscript.
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Footnotes
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|---|
Submitted February 3, 2003;
accepted April 30, 2003.
Prepublished online as Blood First Edition Paper, May 15, 2003;
DOI 10.1182/blood-2003-02-0359.
Supported by National Cancer Institute grants CA16058, CA101140
[GenBank]
, CA31946,
CA77658, CA03927, CA41287, and CA35279, and the Coleman Leukemia Research
Fund. C. D. Baldus was supported by a grant from the Deutsche Krebshilfe.
Additional grant support for participating CALGB institutions is listed in the
"Appendix."
C. D. Baldus and S.M.T. contributed equally to this work.
Participating institutions and principal investigators are listed in the
"Appendix."
The publication costs of this article were defrayed in part by page charge
payment. Therefore, and solely to indicate this fact, this article is hereby
marked "advertisement" in accordance with 18 U.S.C. section
1734.
Reprints: Clara D. Bloomfield, The Ohio State University,
Starling-Loving Hall, 320 West 10th Ave, Columbus, OH 43210; e-mail:
bloomfield-1{at}medctr.osu.edu.
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Top
Abstract
Introduction