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Blood First Edition Paper, prepublished online February 5, 2014; DOI 10.1182/blood-2013-11-539726
CLINICAL IMPACT OF SMALL TP53 MUTATED SUBCLONES
IN CHRONIC LYMPHOCYTIC LEUKEMIA
Running head: Subclonal TP53 mutations in CLL
Davide Rossi,1§ Hossein Khiabanian,2§ Valeria Spina,1 Carmela Ciardullo,1 Alessio Bruscaggin,1
Rosella Famà,1 Silvia Rasi,1 Sara Monti,1 Clara Deambrogi,1 Lorenzo De Paoli,1 Jiguang Wang,2
Valter Gattei,3 Anna Guarini,4 Robin Foà,4* Raul Rabadan,2* Gianluca Gaidano1*
D.R. and H.K equally contributed; *R.F., R.R. and G.G equally contributed.
§
1
Division of Hematology, Department of Translational Medicine, Amedeo Avogadro University of
Eastern Piedmont, Novara, Italy; 2Department of Systems Biology and Department of Biomedical
Informatics, Center for Computational Biology and Bioinformatics, Institute for Cancer Genetics,
Columbia University, New York, USA; 3Clinical and Experimental Onco-Hematology, Centro di
Riferimento Oncologico, Aviano, Italy;
4
Division of Hematology, Department of Cellular
Biotechnologies and Hematology, Sapienza University, Rome, Italy.
Correspondence: Davide Rossi, MD, Division of Hematology, Department of Translational
Medicine, Amedeo Avogadro University of Eastern Piedmont, Via Solaroli 17, 28100 Novara,
Italy; Ph +39-0321-660698; Fax +39-0321-620421; E-mail [email protected].
Category: Lymphoid neoplasia
Copyright © 2014 American Society of Hematology
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Key points: small TP53 mutated subclones have the same unfavorable prognostic impact as clonal
TP53 defects in chronic lymphocytic leukemia
ABSTRACT
TP53 mutations are strong predictors of poor survival and refractoriness in chronic
lymphocytic leukemia (CLL) and have direct implications for disease management. Clinical
information on TP53 mutations is limited to lesions represented in >20% leukemic cells. Here we
tested the clinical impact and prediction of chemorefractoriness of very small TP53 mutated
subclones. The TP53 gene underwent ultra-deep-next generation sequencing (NGS) in 309 newly
diagnosed CLL. A robust bioinformatic algorithm was established for the highly sensitive detection
of few TP53 mutated cells (down to 3 out of ~1000 wild type cells). Minor subclones were
validated by independent approaches. Ultra-deep-NGS identified small TP53 mutated subclones in
28/309 (9%) untreated CLL that, due to their very low abundance (median allele frequency: 2.1%),
were missed by Sanger sequencing. Patients harboring small TP53 mutated subclones showed the
same clinical phenotype and poor survival (HR=2.01; p=.0250) as those of patients carrying clonal
TP53 lesions. By longitudinal analysis, small TP53 mutated subclones identified before treatment
became the predominant population at the time of CLL relapse and anticipated the development of
chemorefractoriness. This study provides a proof-of-principle that very minor leukemia subclones
detected at diagnosis are an important driver of the subsequent disease course.
Keywords: chronic lymphocytic leukemia, TP53, mutations, subclone, deep sequencing
2
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INTRODUCTION
TP53 mutations represent strong predictors of poor survival and refractoriness in chronic
lymphocytic leukemia (CLL),1-7 and, for these reasons, they have a well established clinical
relevance and direct implications for the management of this leukemia.8-11 To date, information on
the clinical relevance of TP53 mutations in CLL is limited to lesions that are clonally represented in
the leukemic population, as revealed by Sanger sequencing that is the most widely adopted method
to assess TP53 mutation status in this leukemia.4,5,6,7,12,13
Next generation sequencing (NGS) technologies provide a novel opportunity to examine in
depth the clonal heterogeneity of the CLL genome, with the potential for sensitive detection of
mutations restricted to a small fraction of the total tumor cell population. Exploiting these
approaches, recent genomic studies have disclosed the complexity of CLL clonal architecture and
provided the proof of principle that genetically diverse subclones may be admixed with a dominant
leukemic clone.12-15 Although genomic studies have depicted the landscape of the clonal complexity
of CLL, little is known about the clinical implications and dynamics of very small subclones that
may be present, but are commonly undetected, in the leukemic cell population.14-17
Understanding the significance of small CLL subclones might be particularly important if
they are driven by genetic lesions associated with treatment resistance, such as TP53 mutations. In
this respect, analysis of the subclonal architecture of TP53 mutations in the early disease phases
may help anticipate the genetic composition of later phases of the disease, including
chemorefractoriness and relapse, and may also predict the disease ultimate clinical course. In this
study, by using a highly sensitive ultra-deep-NGS approach capable of detecting few mutated cells,
we tested the clinical impact of small TP53 mutated subclones on CLL outcome.
3
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PATIENTS AND METHODS
Patients
The study population was a consecutive series of 309 newly diagnosed CLL patients (Table
1) who were prospectively registered in the Amedeo Avogadro University CLL-database from
December 1996 through October 2011. CLL diagnosis was according to IWCLL-NCI criteria.9
Fifty-three cases presented with symptomatic disease according to guidelines,9 and were therefore
treated at diagnosis. The study population was provided with sequential tumor samples and clinical
information prospectively collected at clinically relevant time points. The database was updated in
May 2013. Median follow-up of alive patients was 8.1 years. No patient was lost to follow-up.
The study was designed to assess differences in overall survival (OS) between cases
harboring a wild type TP53 gene and cases harboring small TP53 mutated subclones. The exact
prevalence of small TP53 mutated subclones in CLL is currently unknown. Assuming that small
TP53 mutated subclones occur in at least 10% of the population, we estimated that 309 patients
would allow detecting at least a 25% difference in 5-year OS between patients harboring a wild type
TP53 gene (5-year-OS=75%) and patients harboring small TP53 mutated subclones (5-yearOS=50%) (power=81%; alpha=0.01).
The REMARK criteria were followed throughout this study (Table S1).18 Patients provided
informed consent in accordance with local IRB requirements and Declaration of Helsinki. The study
was approved by the Ethical Committee of the Ospedale Maggiore della Carità di Novara associated
with the Amedeo Avogadro University of Eastern Piedmont (Protocol Code 59/CE; Study Number
CE 8/11).
Specimen characteristics
TP53 mutation screening was performed on peripheral blood mononuclear cell (PBMC)
samples collected at CLL diagnosis. Clonal evolution analysis was performed on PBMC samples
4
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collected at progression requiring treatment, relapse, and last follow-up. In all cases, the fraction of
tumor cells corresponded to 70-98% as assessed by flow cytometry. To account for tumor
representation, the frequency of the mutant TP53 alleles provided by ultra-deep-NGS was corrected
for the proportion of CD19+/CD5+ cells in each sample.
TP53 sequencing
Ultra-deep-NGS of the TP53 mutation hotspots (exons 4-8, including splicing sites) was
performed using the 454 chemistry and was based on amplicon libraries. The TP53 region of
interest was covered by 6 sequence-specific primer pairs, each flanked by tagged-sequences to
barcode the samples (Table S2). In each experiment, 60 amplicons, corresponding to the TP53
region of interest of 10 distinct patients, were amplified from genomic DNA by using a high fidelity
Taq polimerase (FastStart High fidelity PCR System, Roche Diagnostics) and subjected to ultradeep-NGS on the Genome Sequencer Junior (454 Life Sciences) to obtain a ~2000-fold coverage
per amplicon. Through this approach, the average sequencing coverage across TP53 target regions
was 2660x and >87% of the sequenced amplicons had sequence coverage of >1000x. TP53
mutation analysis was also performed in parallel by Sanger sequencing as previously reported.4
Further details are available in the Supplementary Appendix.
Establishment of a bioinformatic approach to call subclonal TP53 mutations out of the
background error noise
In order to establish a robust bioinformatic approach to call subclonal TP53 mutations of
low abundance out of the background error noise of deep-NGS, a pivotal dilution experiment was
performed. This experiment allowed to: i) calibrate ultra-deep-NGS for systematic biases that lead
to sequencing errors; ii) derive the distribution of sequencing errors; iii) determine the sequencing
depth required for a highly sensitive detection of small (<0.5% allele frequency) mutations out of
the background error noise; and iv) statistically test the confidence in discovering subclonal events
5
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(Figures S1-S4). The dilution experiment established the negative binomial distribution as the best
fit for ultra-deep-NGS error distribution (Supplementary Methods; Figure S2) that was used to
estimate statistical frequency thresholds above which true subclonal mutations are distinguished
from the background error noise (Figures S3 and S4).19-24 Based on these observations, a robust
bioinformatic workflow was established to call subclonal TP53 variants from ultra-deep-NGS
experiments in patient samples. By this approach, we were able to detect subclonal TP53 mutations
represented in at least 0.3% of the alleles (3 mutated alleles out of 1000 alleles) (Figures S2 and
S3). Further details of the bioinformatic algorithm are available in the Supplementary Appendix.
Validation of small TP53 mutated subclones
Small TP53 mutated subclones called by the bioinformatic algorithm were validated by a
double step experimental approach. In the first step,25 subclonal variants were subjected to
independent PCR amplification and ultra-deep-NGS sequencing experiments using the same
experimental conditions and coverage described above. In the second step, subclonal TP53 variants
were further validated by allele specific PCR (AS-PCR).26 Further details are available in the
Supplementary Appendix.
Databases
TP53 mutations were annotated using the IARC TP53 database.27 For each TP53 missense
mutation, the CDKN1A promoter-specific transcriptional activity measured in yeast functional
assays was extracted and expressed as percent of wild-type activity.28 The molecular and functional
profiles of clonal TP53 mutations in CLL was derived from public databases.29
Statistical analysis
OS from diagnosis was the primary endpoint and was measured from date of initial
presentation to date of death from any cause (event) or last follow-up (censoring). Analysis of OS
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from first treatment was a secondary and exploratory endpoint, included 53 newly diagnosed
patients who presented with symptomatic disease requiring treatment, and was measured from date
of first treatment to date of death from any cause (event) or last follow-up (censoring). Molecular
studies were blinded to the study endpoints. Survival analysis was performed by Kaplan-Meier
method.30 To test the independence of the prognostic value of small TP53 mutated subclones on
OS, we performed a comprehensive multivariate Cox analysis with backward-stepwise elimination
of non-significant covariates.31 None of the covariates violated the proportional hazard regression
assumptions.32,33 Bias corrected c-index, calibration slope and heuristic shrinkage estimator of the
Cox model were calculated.32-37 Cox model stability was internally validated using bootstrapping
procedures.32-37 These approaches provided an estimate of prediction accuracy of the Cox model to
protect against overfitting. The maximally selected rank statistics was utilized to identify a cut-off
in the size of the TP53 mutated clone to best predict OS. Categorical variables were compared by
chi-square test and Fisher’s exact test. Continuous variables were compared by Mann-Whitney test.
The Bonferroni test was utilized to correct for multiple comparisons. All statistical tests were twosided. Statistical significance was defined as p<0.05. The analysis was performed with SPSS v.21.0
and with R statistical package 3.0.1 (http://www.r-project.org). Further details of the statistical
analysis are available in the Supplementary Appendix.
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RESULTS
Small TP53 mutated subclones occur in a significant fraction of newly diagnosed CLL
We established an ultra-deep-NGS strategy coupled with a robust bioinformatic algorithm
for the highly sensitive detection of small mutated subclones in CLL. The sensitivity of the ultradeep-NGS approach allowed to detect mutant allele fractions down to 0.3% (3 mutant alleles in a
background of ~1000 wild type alleles) with a 95% confidence interval of 0.2-0.5%. Highly
sensitive ultra-deep-NGS was then applied to identify small TP53 mutated subclones in a
consecutive series of 309 newly diagnosed CLL patients (Table 1). Ultra deep-NGS identified 85
TP53 mutations in 14.8% (46/309) of CLL patients (Figure 1A). All mutations that had been
detected by Sanger sequencing (i.e. clonal TP53 mutations: 35 in 28 patients, 9.0%) were also
identified by ultra-deep-NGS.
Ultra deep-NGS identified 50 additional subclonal TP53 mutations that, due to their very
low abundance (median allele frequency corrected for tumor representation: 2.1%; range: 0.3-11%)
in the tumor clone, were missed by Sanger sequencing (Figure 1A; Table S3). All subclonal TP53
mutations were validated by at least two independent ultra-deep-NGS experiments and further
confirmed on a different experimental platform by AS-PCR (Figure 2). Subclonal TP53 mutations
were the sole TP53 variant in 5.8% (18/309) of CLL, while they co-existed in the same leukemic
population along with a clonal TP53 mutation in 3.2% (10/309) of cases (Figure 1B). By
considering also 17p13 deletion among the genetic defects targeting the TP53 gene, subclonal TP53
mutations were the sole TP53 lesion in 4.8% (15/309) of CLL (Figure 1B). Overall, patients
carrying solely subclonal mutations accounted for 30% (15/50) of all cases harboring TP53 defects
in this study cohort.
These data indicate that ultra-deep-NGS significantly adds to the analysis of TP53 genetic
defects in CLL by allowing the identification of small TP53 mutated subclones among patients that
would be otherwise considered wild type for the TP53 gene according to Sanger sequencing.
8
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Subclonal mutations have the same detrimental impact on TP53 function as clonal defects
The molecular profile and functional impact of subclonal TP53 mutations was dissected to
discriminate whether they act as pathogenic drivers or as irrelevant passengers in CLL. Subclonal
TP53 mutations were mainly missense substitutions (78%, 39/50) mapping in the DNA-binding
domain of the TP53 protein, and recurrently affecting hotspot codons (i.e. 179 and 248) that are
known to be required for DNA binding (Figure 1C-1E). These features predicted impairment of the
transcriptional activation of TP53 response genes. Consistently, the median residual
transactivational activity of subclonal TP53 mutations towards the CDKN1A (p21) promoter was
only 14.5% (interquartile range: 0.9-20.5%) compared to wild type TP53 (Figure 1F).28 The
remaining subclonal TP53 mutations were splice site (10%, 5/50), nonsense (8%, 4/50) and indel
(4%, 2/50) variants, that were selected to truncate or entirely remove the DNA binding domain of
TP53 (Figure 1C). Overall, the molecular and functional profiles of subclonal TP53 mutations did
not significantly differ from those of TP53 variants that gained clonal representation in CLL (Figure
1).29
These data indicate that subclonal TP53 mutations do not represent random passenger
events, but instead negatively impact on TP53 function as clonal TP53 variants.
Small TP53 mutated subclones have the same unfavorable prognostic impact as clonal defects
Cases harboring solely subclonal TP53 mutations and cases harboring clonal TP53 variants
shared the same clinical and immunogenetic picture at presentation (Table 1; Figure S6) and
showed a similarly poor clinical course. By univariate analysis, the OS of cases harboring solely
subclonal TP53 mutations was significantly shorter (5-year OS: 46.3%; p=.0042) than that of cases
with an unmutated TP53 gene (5-year OS: 75.1%), and was similar to that of cases harboring clonal
TP53 mutations (5-year OS: 34.6%; p=.6926) (Table 2; Figure 3A).
To assess the impact of the TP53 mutation load on CLL survival, we divided patients into
subgroups according to their TP53 mutation abundance (0.3-1%, 1.1-10%, >10% of the variant
9
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allele frequency). By this analysis, patients harboring TP53 mutations, independent of the size of
the clone, were characterized by a homogeneously poor outcome and showed an OS shorter than
that of patients with a wild type TP53 gene (Figure S7). Consistently, the maximally selected rank
statistics failed to identify a cut-off in the size of the TP53 mutated clone capable of best predicting
CLL OS (Figure S8). This analysis is indicative of a “yes/no effect” of TP53 mutations on CLL
outcome irrespective of the abundance of the mutated clone.
Given the co-occurrence of TP53 mutations with 17p13 deletion (Table 1), this lesion was
incorporated in survival analysis to assess the impact of subclonal mutations as the sole TP53
defect. Also by this approach, patients harboring solely subclonal TP53 mutations showed a
significantly shorter OS than cases devoid of TP53 abnormalities. Conversely, the OS of patients
carrying solely subclonal TP53 mutations was similar to that of cases with clonal TP53 genetic
defects (Figure 3B).
The impact of small TP53 mutated subclones on CLL survival was independent of the
potential confounding effects of other variables that are clinically relevant in this leukemia.2,4 By
multivariate analysis for OS, CLL patients harboring small TP53 mutated subclones had a 2.0 fold
increased risk of death (HR 2.01; 95% CI, 1.24-4.38; p=.0250) after adjusting for age, gender,
disease stage, co-occurrence of clonal TP53 lesions and other biological prognostic factors (i.e.
IGHV mutation status, 11q22-23 deletion, mutations of NOTCH1 and SF3B1, and BIRC3
disruption) (Table 2). Notably, the adjusted hazard of death marked by small TP53 mutated
subclones was similar in magnitude to that of clonally represented TP53 lesions (Table 2).
Overall, these data document that CLL patients harboring small TP53 mutated subclones
have the same clinico-biological phenotype and poor outcome as patients in whom TP53 lesions are
clonally represented in the tumor.
10
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Small TP53 mutated subclones detected at diagnosis subsequently expand under the selective
pressure of treatment
The dynamics of small TP53 mutated subclones was assessed by longitudinal ultra-deepNGS analysis of sequential PB samples collected from patients immediately before first treatment
and then at disease relapse (n=13 patients; 61% treated with immuno-chemotherapy regimens).
Among these cases, the small TP53 mutated subclones identified before treatment became the
predominant tumor cell population at the time of CLL relapse (Figure 4). Selection of the small
TP53 mutated subclones occurred independent of the type of treatment (i.e. FCR, fludarabine-based
combinations or alkylating agents). This may have resulted from the removal of the dominant TP53
wild type clones by cytotoxic treatment, allowing the expansion of TP53 mutated subclones whose
selection, because of their chemoresistance, was favored by ineffective therapies. In these patients,
the expansion of small TP53 mutated subclones invariably paralleled the development of a
chemorefractory phenotype.
We also examined sequential samples from two patients (interval between sampling 48 and
38 months, respectively) who harbored solely small TP53 mutated subclones at diagnosis and who
did not require treatment during the clinical follow-up. In these two patients managed only by a
watch and wait policy, the small TP53 mutated subclones did not increase in their size during the
course of the disease (Figure S9).
Overall, these data indicate that chemotherapy is the major selective pressure favoring the
expansion of TP53 mutated clones in CLL.
Small TP53 mutated subclones detected before treatment anticipate the development of a
chemorefractory phenotype
Among CLL investigated at the time of treatment requirement (n=53; 36% treated with
FCR; Table S4), patients harboring small TP53 mutated subclones failed treatment and died of
chemorefractoriness in a proportion similar to that of cases with clonal TP53 variants (Figure 3C).
11
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In fact, based on an exploratory analysis, the OS of cases harboring solely subclonal TP53
mutations was significantly shorter (5-year OS: 0%; p=.0171) than that of cases with an unmutated
TP53 gene (5-year OS: 54.3%), and was similar to that of cases harboring clonal TP53 mutations
(5-year OS: 12.1%; p=.4170) (Figure 3C).
These data indicate that, among patients requiring treatment, the detection of small TP53
mutated subclones in the early disease phases invariably anticipates the genetic composition of the
disease at relapse and the development of a chemorefractory phenotype.
12
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DISCUSSION
This study shows that small TP53 mutated subclones detected by highly sensitive ultradeep-NGS i) occur in a significant fraction of newly diagnosed CLL; ii) have the same unfavorable
prognostic impact as clonal TP53 defects; and iii) anticipate the development of a chemorefractory
phenotype among CLL patients requiring treatment.
TP53 mutation analysis is currently advised for a proper management of CLL patients,8-11
and Sanger sequencing is the approach currently recommended by guidelines.11 Due to its limited
sensitivity,11 conventional Sanger sequencing misclassifies as wild type ~5% of newly diagnosed
CLL otherwise harboring TP53 mutations of low clonal abundance (0.3-11%), and ultimately
underestimates the TP53 mutation status in ~30% of cases harboring TP53 defects. Thanks to its
high sensitivity (down to 1-0.1%),38,39 ultra-deep-NGS is capable of detecting such minor, but
clinically relevant, TP53 mutated subclones. Therefore, ultra-deep-NGS should be considered as a
useful tool for a comprehensive assessment of TP53 disruption in CLL.
Though the retrospective design represents a limitation of this analysis, a strong biological
rationale supports the clinical relevance of subclonal TP53 mutations in CLL and their more general
application as a biomarker in this disease. Subclonal TP53 variants show molecular and functional
clues that are highly consistent with those of TP53 mutations with known pathogenicity,29 thus
indicating that they have been selected to damage the TP53 protein.28 The pathogenic effect of
subclonal TP53 mutations is confirmed by the observation that, in patients, small TP53 mutated
subclones are resistant to chemo +/- immunotherapy, and are positively selected by treatments to
progressively become the dominant leukemic population at the time of CLL relapse. Ultra-deepNGS may capture newly born and highly fit TP53 mutations at the initial phases of their clonal
selection. In this scenario, beside the intrinsic fitness imposed by the TP53 variant, the small TP53
mutant subclone needs further environmental pressures/constraint (i.e. microenvironmental
interactions, chemotherapy) to overcome and substitute the TP53 wild type cell population.14-17
13
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Our disease model provides a proof-of-concept that small tumor cell populations of very low
clonal abundance (down to 0.3%) can drive the disease course and may represent informative and
highly sensitive biomarkers of outcome prediction in cancer patients. These data suggest that
limiting the knowledge of tumor genetics to the dominant clone may be uninformative for an
accurate prediction of outcome and optimal therapeutic decision. Consequently, the genetic
characterization of CLL, and possibly also of other tumors, should be tailored at disclosing in depth
the architecture of cancer cell populations, at least for those molecular lesions that are known to
harbor prognostic information or to mark chemoresistance.
These pivotal findings may have potential implications for the design of clinical trials and,
possibly, for disease management. CLL patients harboring clonal TP53 defects are currently
considered at high risk of failing conventional therapies and therefore represent the best candidates
for new treatment strategies or stem cell transplant.2,8,10,11 Because patients harboring small TP53
mutated subclones have the same risk of failing and dying as patients harboring clonal TP53
defects, both at diagnosis and at treatment requirement, their identification is advisable in order to
manage them as high risk CLL. Treatment approaches should be selected to target both the major
TP53 wild type clone as well as small TP53 mutated subclones to avoid their subsequent selection
and outgrowth that is otherwise destined to occur in all cases exposed to ineffective treatments, as
documented by the current study.40 Given their promising activity against CLL cells with TP53
defects,41,42 new targeted drugs (e.g. ABT-199 and ibrutinib) may represent a rational treatment to
suppress or even eradicate small subclones harboring TP53 lesions.
14
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Acknowledgment: This study was supported by Special Program Molecular Clinical Oncology 5 x
1000 No. 10007, My First AIRC Grant No. 13470, and Investigator Grant IG-13227, Associazione
Italiana per la Ricerca sul Cancro Foundation Milan, Italy; Progetto Giovani Ricercatori 2010,
Grant No. GR-2010-2317594, Ministero della Salute, Rome, Italy; Compagnia di San Paolo, Grant
No. PMN_call_2012_0071, Turin, Italy; Fondazione Cariplo, Grant No. 2012-0689; Futuro in
Ricerca 2012 Grant No. RBFR12D1CB, Ministero dell'Istruzione, dell'Università e della Ricerca,
Rome, Italy; U54 CA121852-05; 2012 Stewart Trust Cancer Research Fellows, Stewart
Foundation. S.M. is being supported by a fellowship from Novara-AIL Onlus Foundation, Novara,
Italy. C.D. is being supported by a fellowship from Comitato Gigi Ghirotti, Turin, Italy.
Contributions: D.R., H.K., R. Foà, R.R. and G.G. designed the study, interpreted data and wrote
the manuscript; D.R., and H.K. performed statistical analysis; V.S., C.C., A.B., R. Famà., and S.R.
performed and interpreted molecular studies; S.M. and C.D performed and interpreted FISH
analysis; L.D.P collected clinical data; J.W., V.G., A.G. contributed to data interpretation.
Conflict-of-interest disclosure: The authors have no conflict of interest to disclose.
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Table 1. Characteristics of the whole CLL series, of patients harboring solely subclonal TP53
mutations and of patients harboring clonal TP53 mutations
Solely subclonal
Clonal
TP53 mutations
TP53 mutations
(n=18)
(n=28)
N
%
n
%
N
%
pc
Age >70 years
160
51.8
11
61.1
19
67.9
.6391
Male
165
53.4
10
55.6
19
67.9
.3988
Binet A
245
79.3
13
72.2
16
57.1
Binet B
37
12.0
2
11.1
5
17.9
.5848
Binet C
27
8.7
3
16.7
7
25.0
IGHV identity >98% b
108
35.5
6
35.3
13
46.4
.4634
Stereotyped VH CDR3 b
68
22.4
6
35.3
8
28.6
.6367
13q14 deletion
158
51.1
12
66.7
17
60.7
.6831
Trisomy 12
64
20.7
5
27.8
3
10.7
.2316
11q22-q23 deletion
24
7.8
2
11.1
2
7.1
.6386
17p13 deletion
29
9.4
3
16.7
22
78.6
<.0001
NOTCH1 mutations
34
11.0
1
5.6
3
10.7
1.00
SF3B1 mutations
22
7.1
3
16.7
3
10.7
.6655
BIRC3 deletion
13
4.2
1
5.6
2
7.1
1.00
BIRC3 mutations
7
2.3
0
0
0
0
BIRC3 disruption
17
5.5
1
5.6
2
7.1
1.00
MYD88 mutations
10
3.2
0
0
0
0
a
IGHV, immunoglobulin heavy variable gene; CDR3, complementarity determining region 3
b
IGHV mutation status was assessable in 304 patients; 5 patients lacked productive IGHV-IGHD-IGHJ rearrangements
c
p, p value for the comparison between cases harboring solely subclonal TP53 mutations vs clonal TP53 mutations
Characteristics a
All
(n=309)
20
Table 2. Univariate and multivariate analysis of OS a
Univariate analysis
Events Total 5-year OS (%) LCI UCI
HR LCI UCI
P
Multivariate analysis
Initial full model
Final model
HR LCI UCI
p
HR LCI UCI
p
21
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31
149
81.9
75.3 88.5
Age <70 years
<.0001
<.0001
<.0001
74
160
57.7
49.3 64.1 3.19 2.06 4.94
3.42 2.14 5.46
3.23 2.05 5.11
Age >70 years
47
144
70.2
62.0 78.4
Female
.3319
.6376
58
165
68.7
61.1 76.3 1.21 0.82 1.70
1.10 0.72 1.68
Male
66
245
75.8
70.0 81.6
Binet A
19
37
53.1
34.9 71.3 1.97 1.18 3.30 <.0001 d 1.46 0.84 2.53 .0349 d 1.52 0.89 2.60 .0079 d
Binet B
20
27
33.9
15.3 52.5 3.77 2.24 6.32
2.28 1.20 4.33
2.56 1.39 4.71
Binet C
55
196
76.4
69.9 82.9
IGHV homology <98%
.0039
.6647
49
108
55.6
45.2 66.0 1.77 1.29 2.61
1.11 0.68 1.80
IGHV homology >98%
No subclonal TP53 mutations
87
281
73.0
67.3 78.7
<.0001
.0252
.0250
18
28
34.5
15.5 53.5 3.22 1.93 5.38
2.03 1.09 3.77
2.01 1.24 4.38
Subclonal TP53 mutations
91
285
71.2
65.5 76.9
No 11q22-q23 deletion
.0035
.3087
1.55 0.66 3.64
14
24
46.4
22.3 70.5 2.42 1.33 4.39
11q22-q23 deletion
b
81
274
74.6
68.9 80.3
No clonal TP53 lesions
<.0001
.0273
.0201
24
35
31.9
15.2 48.6 3.28 2.07 5.20
1.88 1.07 3.31
1.91 1.10 3.32
Clonal TP53 lesions b
85
275
72.5
66.8 78.2
No NOTCH1 mutations
.0015
.0221
.0107
1.97 1.10 3.54
2.00 1.17 3.42
20
34
36.3
18.3 54.3 2.20 1.35 3.59
NOTCH1 mutations
93
287
70.8
65.1 76.5
No SF3B1 mutations
.0014
.0109
.0114
SF3B1 mutations
12
22
53.0
31.4 74.6 2.67 1.45 4.88
2.35 1.21 4.55
2.31 1.20 4.44
94
292
71.0
65.3 76.7
No BIRC3 disruption c
.0008
.1319
.0032
11
17
41.6
15.9 67.3 2.92 1.56 5.48
1.94 0.82 4.50
2.62 1.38 4.99
BIRC3 disruption c
a
OS, overall survival; HR, hazard ratio; LCI, 95% lower confidence interval; UCI, 95% upper confidence interval; IGHV, immunoglobulin heavy variable gene
b
Clonal TP53 mutations and/or 17p13 deletion
c
BIRC3 mutations and/or BIRC3 deletion
d
p-trend
Total number of patients included in the multivariate analysis: 304; Events: 104; 5 patients lacked productive IGHV-IGHD-IGHJ rearrangements
Shrinkage coefficient of the final model: 0.92
Internal bootstrapping validation
Bootstrap parameters (mean)
Bootstrap
HR
LCI
UCI
selection
100%
3.40
2.11
5.48
1.36
0.78
2.17
92%
2.24
1.31
4.13
74%
2.12
1.13
3.99
79%
2.11
1.19
3.74
85%
2.18
1.25
3.82
79%
2.60
1.30
5.19
88%
2.77
1.41
5.46
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FIGURE LEGENDS
Figure 1. Molecular profile of subclonal TP53 mutations. (A) Allele frequency of the 85 TP53
mutations identified by ultra-deep-next generation sequencing. Mutations are ordered according to
their allelic abundance. Mutations that tested positive (clonal mutations: gray bars) and negative
(subclonal mutations: red bars) by Sanger sequencing are indicated. (B) Prevalence of TP53 lesions
according to their clonal representation in the study cohort of 309 newly diagnosed CLL (for each
category, the crude number of patients is represented). (C) Comparison of the molecular profile of
subclonal mutations from the CLL study cohort (n=50; red bars) vs clonal mutations from public
CLL databases (n=257; gray bars; see ref 27). p, p values by Fisher's exact test corrected for
multiple hypothesis testing. (D) Comparison of the transition/transversion profile between subclonal
TP53 substitutions from the CLL study cohort (n=48; red bars) and clonal TP53 substitutions from
public CLL databases (n=210; gray bars; see ref 27). p, p values by Fisher's exact test corrected for
multiple hypothesis testing. (E) Schematic diagram of the TP53 protein with its conserved
functional domains. Color-coded shapes indicate the position of subclonal TP53 mutations from the
CLL study cohort (n=50; red shapes) and clonal TP53 mutations from public CLL databases
(n=257; gray shapes; see ref 27). Hot spot codons recurrently affected by both subclonal and clonal
TP53 mutations are highlighted. (F) Residual CDKN1A transactivation capacity of subclonal TP53
missense substitutions from the CLL study cohort (n=39; red box) vs clonal TP53 missense
substitutions from public CLL databases (n=193; gray box; see ref 27). The band inside the box is
the median value. The bottom and top of the box are the 25th and 75th quartiles. The ends of the
whiskers are the 2nd percentile and the 98th percentile. p, p value by Mann-Whitney test.
Figure 2. Experimental validation of subclonal TP53 mutations identified by ultra-deep-next
generation sequencing. (A) Representation of the variant frequency of two exemplificative
subclonal TP53 mutations (c.743G>A p.R248Q and c.673-2A>T) of very low allelic abundance
22
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(<0.5%). The first bar of the graphs shows the variant allele frequency in the discovery ultra-deepnext generation sequencing experiment. The second and the third bars show the variant allele
frequency in independent ultra-deep-next generation sequencing validation experiments. The
number of mutated reads out of the total number of reads covering the variant position is reported.
(B) Conventional agarose-gel electrophoresis of the AS-PCR products. Patient 10642, harboring the
subclonal TP53 c.743G>A p.R248Q missense substitution (left), and patient 7561, harboring the
subclonal TP53 c.673-2A>T splice site mutation (right), are represented. After AS-PCR for the
mutant allele, a mutation-specific band is amplified from the patient sample and from the mutated
plasmid DNA (positive control). No bands are amplified from the wild type plasmid DNA and the
wild type genomic DNA from a healthy donor (negative controls), thus confirming the specificity of
the assay. (C) Due to their low clonal abundance (<0.5%), the subclonal TP53 c.743G>A p.R248Q
missense substitution (left) and the subclonal TP53 c.673-2A>T splice site mutation (right) are not
detectable by conventional Sanger sequencing in patient 10642 and patient 7561, respectively.
Asterisks point to the positions of the subclonal variants.
Figure 3. Kaplan-Meier estimates of overall survival of patients harboring small TP53
mutated subclones. (A) Comparison of overall survival (OS) from CLL diagnosis between patients
harboring solely subclonal TP53 mutations (red line), cases harboring clonal TP53 mutations
(yellow line), and cases harboring an unmutated TP53 gene (blue line). (B) Comparison of OS from
CLL diagnosis between patients harboring solely subclonal TP53 mutations (red line), cases
harboring solely clonal TP53 lesions (i.e. mutations or deletions) (yellow line), cases harboring
clonal TP53 lesions coexisting with subclonal TP53 mutations (green line), and cases harboring a
wild type TP53 gene (blue line). (C) Comparison of OS from first treatment between patients
harboring solely subclonal TP53 mutations (red line), cases harboring clonal TP53 mutations
(yellow line), and cases harboring an unmutated TP53 gene (blue line). p, p values by log-rank test.
23
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Figure 4. Longitudinal analysis of clonal evolution in CLL patients harboring small TP53
mutated subclones. Graphical illustration of the kinetics of the TP53 mutated populations in four
representative CLL patients who required treatment at diagnosis and who have been longitudinally
investigated by deep-next generation sequencing. The x axis represents time and the y-axis
represents allele frequency. TP53 mutations and 17p13 deletion are represented by color-coded
circles. The size of the circles is proportional to the allele frequency of the lesion. Arrows indicate
the time point at which tumor samples were collected. The relationship between sample collection
and treatments is also indicated. CLB, chlorambucil; FCR, fludarabine, cyclophosphamide,
rituximab; BR, bendamustine, rituximab; FCM, fludarabine, cyclophosphamide, mitoxantrone,
RDHAP, rituximab, dexamethasone, high dose cytarabine, cisplatin; CR, complete response
according to the IWCLL-NCI criteria; PR, partial response according to IWCLL-NCI criteria; PD,
progressive disease according to the IWCLL-NCI criteria; Richter, Richter syndrome.
24
A
B
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
TP53 mutations
10
263
18
TP53 lesions
4
15
3
3
15
18
3
Sanger sequencing
negative n=50
C
7
clonal M+subclonal M+del17p
clonal M+subclonal M
clonal M+del17p
clonal M
subclonal M+del17p
subclonal M
del17p
wt
wt
subclonal M
clonal M
clonal M+subclonal M
TP53 mutations
D
Clonal M
80%
46
2
257 50
18% 4%
p=.0408
60%
40%
20%
100%
Subclonal M
10
4
257 50
4% 8%
p=1
6
5
257 50
2% 10%
p=.0808
Nonsense
Splicing sites
Frequency
195 39
257 50
76% 78%
p=1
100%
80%
60%
86 19
210 48
41% 40%
p=1
40%
Clonal M
42 13
210 48
20% 27%
p=1
20%
17 6
210 48
8% 13%
p=1
29 4
210 48
14% 8%
p=1
GC>CG
GC>TA
Subclonal M
18 2
210 48
9% 4%
p=1
18 4
210 48
9% 8%
p=1
AT>CG
AT>TA
0%
0%
Missense
Insdel
GC>AT
272
248
220
234
205
F
179
E
Subclonal M
1
393
L
1
L
2
DNA binding
L
3
Clonal M
Missense
Nonsense
Frameshift indel
AT>GC
Splice site
In frame indel
TP53 residual
transactivation of CDKN1A
Frequency
259
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Allele frequency
Sanger sequencing
positive n=35
50%
p=.6674
40%
30%
20%
10%
0%
Clonal M
Subclonal M
Fig. 1
25
c.673-2A>T
1.00%
0.80%
0.60%
0.54%
0.39%
(21/5365)
0.40%
0.28%
(28/5194)
(4/1431)
0.20%
0.00%
Allele frequency
c.743G>A p.R248Q
1.00%
0.58%
0.80%
0.48%
0.60%
(16/3346)
0.30%
(25/4310)
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Allele frequency
A
(5/1634)
0.40%
0.20%
0.00%
Discovery
Validation 1
Validation 2
Discovery
Validation 1
Validation 2
B
Mutant
amplicon
300bp
200bp
210bp
Mutant
amplicon
200bp
175bp
100bp
Wild type
amplicon
210bp
300bp
200bp
Wild type
amplicon
200bp
175bp
100bp
C
c.736
*
c.748
c.673-5
*
c.680
Fig. 2
26
A
B
TP53 WT
Solely subclonal TP53 M
Solely clonal TP53 lesion
Clonal lesion + Subclonal TP53 M
p<0.0001
p<0.0001
No. at risk
263
18
28
Events
77
9
19
122
4
6
Total
263
18
28
15
0
0
5-year OS
95% CI
75.1%
69.5-80.7%
46.3%
22.0-70.6%
34.6%
15.8-53.4%
p from pairwise comparisons
.0042 .<.0001
.0042
.6926
<.0001 .6926
-
0
0
0
No. at risk
259
15
22
13
Events
74
7
13
11
TP53 unmutated
Solely subclonal TP53 M
Clonal TP53 M
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TP53 unmutated
Solely subclonal TP53 M
Clonal TP53 M
C
p=0.0037
121
3
6
1
Total
259
15
22
13
14
0
1
0
5-year OS
95% CI
76.0%
70.4-81.6%
51.3%
25.3-77.3%
40.4%
18.3-62.5%
17.9%
0-40.0%
p from pairwise comparisons
.0280
.0280
.0006 .7123
<.0001 .1513
.0006 <.0001
.7123 .1513
.1125
.1125
-
0
0
0
0
No. at risk
36
6
11
Events
21
5
10
15
0
1
Total
36
6
11
4
0
0
0
0
0
5-year OS
95% CI
54.3%
36.9-71.7%
0%
12.1%
0-33.6%
p from pairwise comparisons
.0051
.0171
.0051
.4170
.0171
.4170
-
Fig. 3
27
p.R273C
70.0%
80%
60%
40%
63.0%
2.2%
100%
0
5
months
40%
58.0%
20%
0.9%
del17p
5 10 15 20 25 30 35 40 45
months
FCR
Relapse
Refractoriness
p.R248W
CR
Relapse
Refractoriness
Diagnosis
del17p
ID10642
p.R248Q
100%
60.0%
80%
60%
40%
1.7%
39.0%
0.3%
0%
Allele frequency
100%
Allele frequency
60%
CR
Diagnosis
20%
80%
-20%
-10 -5 0
10 15 20 25 30 35 40
CLB
ID5564
66.0%
0%
0%
-20%
-10 -5
p.G244D
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Allele frequency
100%
20%
del17p
ID9245
Allele frequency
del17p
ID9630
60.0%
80%
60%
33.8%
40%
20%
30.0%
0.4%
0%
-20%
-10 0 10 20 30 40 50 60 70 80 90100110
months
FCR
Diagnosis
CR
-20%
-10 -5
0
5
FCM
BR
Relapse
5.5%
PD
Refractoriness
Diagnosis
10
PR
15
months
20
RDHAP
Relapse
Richter
25
30
35
PR
Relapse
Richter
Refractoriness
Fig. 4
28
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Prepublished online February 5, 2014;
doi:10.1182/blood-2013-11-539726
Clinical impact of small TP53 mutated subclones in chronic lymphocytic
leukemia
Davide Rossi, Hossein Khiabanian, Valeria Spina, Carmela Ciardullo, Alessio Bruscaggin, Rosella Famà,
Silvia Rasi, Sara Monti, Clara Deambrogi, Lorenzo De Paoli, Jiguang Wang, Valter Gattei, Anna Guarini,
Robin Foà, Raul Rabadan and Gianluca Gaidano
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