Efficacy of Neoadjuvant Cisplatin in Triple-Negative Breast Cancer

Abstract

Purpose
Cisplatin is a chemotherapeutic agent not used routinely for breast cancer treatment. As a DNA cross-linking agent, cisplatin may be effective treatment for hereditary BRCA1-mutated breast cancers. Because sporadic triple-negative breast cancer (TNBC) and BRCA1-associated breast cancer share features suggesting common pathogenesis, we conducted a neoadjuvant trial of cisplatin in TNBC and explored specific biomarkers to identify predictors of response.

Patients and Methods
Twenty-eight women with stage II or III breast cancers lacking estrogen and progesterone receptors and HER2/Neu (TNBC) were enrolled and treated with four cycles of cisplatin at 75 mg/m ² every 21 days. After definitive surgery, patients received standard adjuvant chemotherapy and radiation therapy per their treating physicians. Clinical and pathologic treatment response were assessed, and pretreatment tumor samples were evaluated for selected biomarkers.

Results
Six (22%) of 28 patients achieved pathologic complete responses, including both patients with BRCA1 germline mutations;18 (64%) patients had a clinical complete or partial response. Fourteen (50%) patients showed good pathologic responses (Miller-Payne score of 3, 4, or 5), 10 had minor responses (Miller-Payne score of 1 or 2), and four (14%) progressed. All TNBCs clustered with reference basal-like tumors by hierarchical clustering. Factors associated with good cisplatin response include young age (P = .001), low BRCA1 mRNA expression (P = .03), BRCA1 promoter methylation (P = .04), p53 nonsense or frameshift mutations (P = .01), and a gene expression signature of E2F3 activation (P = .03).

Conclusion
Single-agent cisplatin induced response in a subset of patients with TNBC. Decreased BRCA1 expression may identify subsets of TNBCs that are cisplatin sensitive. Other biomarkers show promise in predicting cisplatin response.

Full text

Efficacy of Neoadjuvant Cisplatin in Triple-Negative
Breast Cancer
Daniel P. Silver, Andrea L. Richardson, Aron C. Eklund, Zhigang C. Wang, Zoltan Szallasi, Qiyuan Li,
Nicolai Juul, Chee-Onn Leong, Diana Calogrias, Ayodele Buraimoh, Aquila Fatima, Rebecca S. Gelman,
Paula D. Ryan, Nadine M. Tung, Arcangela De Nicolo, Shridar Ganesan, Alexander Miron, Christian Colin,
Dennis C. Sgroi, Leif W. Ellisen, Eric P. Winer, and Judy E. Garber
From the Dana-Farber Cancer Institute;
Brigham and Women’s Hospital; Chil-
dren’s Hospital Informatics Program at
the Harvard–Massachusetts Institute of
Technology Division of Health Sciences
and Technology; Massachusetts General
Hospital Cancer Center; Beth Israel
Deaconess Hospital, Harvard Medical
School; Harvard School of Public Health,
Boston, MA; Center for Biological
Sequence Analysis, BioCentrum-Technical
University of Denmark, Lyngby, Denmark;
Cancer Institute of New Jersey, Robert
Wood Johnson Medical School, Univer-
sity of Medicine and Dentistry of New
Jersey, New Brunswick, NJ.
Submitted February 13, 2009; accepted
October 23, 2009; published online
ahead of print at www.jco.org on
January 25, 2010.
Supported by Grants No. CA089393
from the National Cancer Institute
Program of Research Excellence
(SPORE) in Breast Cancer at the Dana-
Farber/Harvard Cancer Center and No.
R21LM008823-01A1 from the National
Institutes of Health, and by the Breast
Cancer Research Foundation, Sidney
Kimmel Foundation, Avon supplement
to the Dana-Farber/Harvard Cancer
Center support grant, and Susan G.
Komen for the Cure.
D.P.S. and A.L.R. contributed equally to
this work.
Presented in part at the San Antonio
Breast Cancer Conference, December
14-17, 2006, San Antonio, TX, and the
National Cancer Institute Translational
Science Meeting, November 7-9, 2008,
Washington, DC.
Terms in blue are defined in the glos-
sary, found at the end of this article
and online at www.jco.org.
Authors’ disclosures of potential con-
flicts of interest and author contribu-
tions are found at the end of this
article.
Clinical Trials repository link available on
JCO.org.
Corresponding author: Judy E. Garber,
MD, MPH, Dana-Farber Cancer Insti-
tute, Department of Medical Oncology,
Smith 209, 1 Jimmy Fund Way,
Boston, MA 02115; e-mail: judy_
garber@dfci.harvard.edu.
© 2010 by American Society of Clinical
Oncology
0732-183X/10/2807-1145/$20.00
DOI: 10.1200/JCO.2009.22.4725
ABSTRACT
Purpose
Cisplatin is a chemotherapeutic agent not used routinely for breast cancer treatment. As a DNA
cross-linking agent, cisplatin may be effective treatment for hereditary BRCA1-mutated breast cancers.
Because sporadic triple-negative breast cancer (TNBC) and BRCA1-associated breast cancer share
features suggesting common pathogenesis, we conducted a neoadjuvant trial of cisplatin in TNBC
and explored specific biomarkers to identify predictors of response.
Patients and Methods
Twenty-eight women with stage II or III breast cancers lacking estrogen and progesterone
receptors and HER2/Neu (TNBC) were enrolled and treated with four cycles of cisplatin at 75
mg/m
2
every 21 days. After definitive surgery, patients received standard adjuvant chemotherapy
and radiation therapy per their treating physicians. Clinical and pathologic treatment response
were assessed, and pretreatment tumor samples were evaluated for selected biomarkers.
Results
Six (22%) of 28 patients achieved pathologic complete responses, including both patients with
BRCA1 germline mutations;18 (64%) patients had a clinical complete or partial response. Fourteen
(50%) patients showed good pathologic responses (Miller-Payne score of 3, 4, or 5), 10 had minor
responses (Miller-Payne score of 1 or 2), and four (14%) progressed. All TNBCs clustered with
reference basal-like tumors by hierarchical clustering. Factors associated with good cisplatin
response include young age (P⫽.001), low BRCA1 mRNA expression (P⫽.03), BRCA1 promoter
methylation (P⫽.04), p53 nonsense or frameshift mutations (P⫽.01), and a gene expression
signature of E2F3 activation (P⫽.03).
Conclusion
Single-agent cisplatin induced response in a subset of patients with TNBC. Decreased BRCA1
expression may identify subsets of TNBCs that are cisplatin sensitive. Other biomarkers show
promise in predicting cisplatin response.
J Clin Oncol 28:1145-1153. © 2010 by American Society of Clinical Oncology
INTRODUCTION
Triple-negative breast cancers (TNBCs), those
that do not express estrogen or progesterone re-
ceptors or contain an amplified HER2/Neu gene,
often demonstrate sensitivity to cytotoxic neoad-
juvant treatment regimens
1-4
; however, no specific
molecular targets or chemotherapeutic vulnerabili-
ties have been identified. TNBCs comprise 15% to
20% of breast cancers in Western countries, and
the vast majority are sporadic.
5
Approximately
70% of breast cancers in individuals carrying a
germline BRCA1 mutation are triple negative;
BRCA1-associated and sporadic TNBCs share many
histopathologic features. They are almost always
high grade,
6
with common histologic
7-11
and cyto-
keratin expression patterns,
12,13
and share molecu-
lar features, including frequent p53 mutation
14
and
abnormalities of the inactivated X chromosome.
15
Both BRCA1-associated and sporadic TNBCs are
typically basal-like by hierarchical clustering of tran-
scriptional profiles.
16,17
Further, these tumors share
a pattern of genomic instability characterized by al-
lelic loss.
6,15
These similarities have led to specula-
tion that BRCA1-associated and at least a subset of
sporadic TNBCs may share defects in a BRCA1-
associated pathway; DNA repair has received the
most attention.
18
BRCA1-deficient cells are particularly sus-
ceptible to the interstrand cross-linking agents
JOURNAL OF CLINICAL ONCOLOGY ORIGINAL REPORT
VOLUME 28 䡠NUMBER 7 䡠MARCH 1 2010
© 2010 by American Society of Clinical Oncology 1145

mitomycin and cisplatin. A cell line from a BRCA1-associated breast
tumor was shown to be defective in DNA double-strand break repair
19
and was also cisplatin sensitive
20
; these properties were reversed by
adding wild-type BRCA1.
19,20
BRCA1-deficient tumors in mouse
models also demonstrated cisplatin sensitivity.
21
Some cell lines rep-
resenting sporadic TNBCs show cisplatin and mitomycin sensitivity
(D. Silver and D.M. Livingston, unpublished data), suggesting that
these tumors may have defects in the BRCA1 pathway.
Given these observations, we conducted a neoadjuvant trial of
four cycles of cisplatin in TNBC. The trial end point was pathologic
response. We analyzed pretreatment specimens for predictors of re-
sponse to cisplatin, including BRCA1 expression levels, and BRCA1
promoter methylation. Other features that may predispose to cisplatin
sensitivity, including gene expression patterns, p53 mutation, and the
presence of a cisplatin-specific apoptosis pathway involving the p53
family members p63 and p73, were also explored.
PATIENTS AND METHODS
Patients
Newly diagnosed patients with T1, N1-3, M0 or T2-4, N0-3, M0 breast
cancers (with tumors ⱖ1.5 cm), negative for estrogen and progesterone
receptors defined as ⬍1% nuclear staining by immunohistochemistry, HER2/
Neu0or1⫹by immunohistochemistry, or HER2 nonamplified by fluorescent
in situ hybridization were eligible for this trial.
Study Design and Treatment Plan
A core biopsy was performed to obtain tumor tissue for study, and a
radio-opaque clip was placed in the tumor bed; four treatments of cisplatin at
75 mg/m
2
every 21 days were administered. Patients then received definitive
surgery, including an axillary lymph node dissection in patients with positive
sentinel lymph node biopsy. The specimen was evaluated for chemotherapy
response, with focused sampling of the tumor bed marked by the radio-
opaque clip. The Miller-Payne scoring system
21a
was used to assess tumor
response. A score of 3, 4, or 5, with 5 being a pathologic complete response
(pCR), is hereafter termed a good response.
For details of the patients on trial, study design and treatment plan,
specimen analysis, Exon Grouping Analysis genotyping, gene array analysis,
quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), and
microarray data analysis, see Supplemental Methods (online only).
RESULTS
Patient Characteristics
Twenty-nine women were enrolled on the study: one was ineli-
gible and never received protocol treatment. The last two patients
Table 1. Clinical Characteristics and Response to Treatment of the Study Population (N ⫽28)
Patient No. Age (years) BRCA1 Germline
ⴱ
Baseline Tumor
Diameter by MRI (cm)
Baseline
Nodal Status†
Clinical
Response
Pathologic Response
(Miller-Payne scale)‡
15 57 wt 6.5 ⫺SD Progression
21 59 wt 2.4 ⫺PD Progression
26 39 wt 3.2 ⫺PD Progression
27 63 wt 3.3 ⫹PD Progression
4 68 wt 2.5 ⫹SD 1
6 62 wt Not done ⫹cPR 1
12 53 wt 2.7 ⫺SD 1
13 56 wt 3.2 ⫺cPR 1
16 45 wt 7.0 ⫹SD 1
14 43 wt 2.3 ⫺cPR 2
20 69 wt 5.0 ⫹SD 2
22 67 wt 4.7 ⫹cPR 2
24 50 wt 3.3 ⫺cPR 2
28 60 wt 3.7 ⫹cPR 2
1 59 wt 3.0 ⫺cPR 3
11 41 wt 4.0 ⫹SD 3
23 29 wt 4.5 ⫺cPR 3
25 40 wt 2.4 ⫺cPR 3
2 49 wt 4.0 ⫹SD 4
7 39 wt 3.7 ⫹cCR 4
8 51 wt 4.2 ⫺cPR 4
10 43 wt 2.5 ⫺cCR 4
3 39 wt 4.5 ⫹cPR 5
5 44 mut 5.8 ⫺cPR 5
9 31 wt 4.0 ⫺cPR 5
17 52 wt 2.0 ⫹cCR 5
18 48 mut 2.8 ⫹cCR 5
29 44 wt 6.3 ⫺cPR 5
Abbreviations: MRI, magnetic resonance imaging; wt, wild type, no germline mutation; SD, stable disease; PD, progressive disease; cPR, clinical partial response;
cCR, clinical complete response; mut, presence of a pathogenic germline BRCA1 mutation.
ⴱ
BRCA1 germline genotype determined as in Patients and Methods section.
†Axillary lymph node status determine at baseline; ⫹indicates presence of lymph node metastasis determined by sentinel node biopsy or fine-needle aspiration;
⫺indicates sentinel node biopsy negative for metastasis.
‡Pathologic assessment of response to treatment using Miller-Payne method and grading scale: progression ⫽off study prior to surgery for clinical progression
or additional nonprotocol therapy, 1 ⫽no or minimal reduction in tumor, 2 ⫽up to 30% reduction, 3 ⫽30% to 90% reduction, 4 ⫽⬎90% reduction but with some
residual invasive (or axillary) disease, and 5 ⫽no residual invasive carcinoma or axillary metastasis (pathologic complete response).
Silver et al
1146 © 2010 by American Society of Clinical Oncology JOURNAL OF CLINICAL ONCOLOGY

entered signed consent forms concurrently, so a total of 28 instead of
27 women were treated on study. Patient age ranged from 29 to 69
years at diagnosis (Table 1). The median pretreatment tumor size,
determined by magnetic resonance imaging, was 3.7 cm (range, 2.0 to
7.0 cm); 13 patients had axillary metastases. Research genotyping
detected only the two BRCA1 germline mutations previously identi-
fied through clinical testing. Research biopsies of primary tumor pro-
vided adequate material for most molecular analyses from 24 of the
28 patients.
Treatment Response
Eighteen patients had a clinical response (Table 1, 14 had a partial
response and four had a complete response), for an estimated re-
sponse rate of 64% (95% conditional CI, 44% to 81%). The Miller-
Payne score for responses to four cycles of cisplatin are listed in Table
1. Six patients had pCR (21%; 95% conditional CI, 9% to 43%), and
eight additional patients had significant pathologic partial responses
defined as Miller-Payne 3 or 4 (29%, for an overall good response rate
of 50%; 95% conditional CI, 31% to 70%). Four patients had clinical
progression while on cisplatin.
Table 2 lists the distribution of various clinical and pathologic
characteristics by the response outcomes (Miller-Payne 3, 4, and 5
responses, pCR, and overall clinical response). Neither tumor size (by
magnetic resonance imaging) nor axillary lymph node positivity were
significantly related to any of the three response outcomes (Pⱖ.48
and Pⱖ.43, respectively).
Table 2. Covariates and Response Variables
Covariate
Miller-Payne 3,4,5 Responses pCR
Clinical Response
(CR and PR)
No. of Patients Observed (%) P
ⴱ
Observed (%) P
ⴱ
Observed (%) P
ⴱ
All 28 50 — 21 — 64 —
Age, years .001† .13† .46†
29-41 (Q1) 7 86 29 71
42-49 (Q2) 7 71 43 71
50-59 (Q3) 8 38 13 63
60-69 (Q4) 6 0 0 50
Tumor size, cm (by MRI) .75† .48† .83†
Unknown 1 — — —
2.0-2.7 (Q1) 6 50 17 67
2.8-3.7 (Q2) 7 29 14 57
3.8-4.5 (Q3) 8 88 25 75
4.6-7.0 (Q4) 6 33 33 50
Lymph nodes 1.00‡ 1.00‡ .43‡
Negative 15 53 20 73
Positive 13 46 23 54
BRCA1 mRNA levels,
arbitrary relative units
.03† .79† .65†
Unknown/NA 7 57 42 71
0.00-0.03 (Q1) 5 100 0 80
0.04-0.23 (Q2) 6 33 33 50
0.25-0.44 (Q3) 5 40 0 60
0.57-3.69 (Q4) 5 20 20 60
BRCA1 methylation .04‡ 1.00‡ .40‡
Unknown/NA 5 80 60 80
Negative 15 27 13 53
Positive 8 75 13 75
⌬Np63/TAp73 ratio .39‡ .26‡ .66‡
Unknown 6 50 33 67
⬎2 9 67 33 56
⬍21338869
Type of p53 mutation .03‡ .78‡ .09‡
Unknown 6 50 33 67
MSM 10 30 10 60
NSM 6 100 .01§ 33 1.00§ 100 .23§
wt 6 33 .64¶ 17 1.00¶ 33 .14¶
Abbreviations: pCR, pathologic complete response; CR, complete response; PR, partial response; Q1/Q2/Q3/Q4, first, second, third, and fourth quartiles, respectively; MRI,
magnetic resonance imaging; NA, not assessed because of BRCA1 mutation; MSM, missense mutation; NSM, nonsense or frameshift mutation; wt, wild type (no mutation).
ⴱ
Pvalues when patients with unknown values were omitted.
†Fisher’s exact test on four ordered categories of the covariate (equivalent to a Wilcoxon rank sum test using the quartile number as the observation and comparing
responders to nonresponders).
‡Fisher’s exact test on unordered categories of the covariate.
§Fisher’s exact test on NSM vMSM.
¶Fisher’s exact test on wt vMSM ⫹NSM.
Neoadjuvant Cisplatin in Triple-Negative Breast Cancer
www.jco.org © 2010 by American Society of Clinical Oncology 1147

Toxicity
Severe toxicity was uncommon. One patient had a grade 4 eleva-
tion of AST/AST. There were nine grade 3 toxicities reported: tinnitus,
neutropenia, fatigue, hyperkalemia, elevation of ALT/ALT, nausea,
myalgia, skin toxicity, and GI toxicity.
Predictors of Response
The TNBCs tend to be classified as basal-like in gene expression
array hierarchical cluster analysis using the intrinsic genes.
12,22
We
determined the intrinsic subtype of all cases with adequate material
(n ⫽24) by co-clustering these cases with a reference set of tumors for
which intrinsic subtype had been determined independently (Supple-
mental Fig 1, Supplemental Methods). All of the trial TNBCs co-
clustered with the reference basal-like tumors (Fig 1A). Hierarchical
clustering with the intrinsic genes did not reveal distinct subclusters of
cisplatin-resistant or -sensitive tumors.
Age
There was a strong association between younger age and good
response (P⫽.001 based on quartiles of age, significant even after
A
B
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Subtype
Response
A22
A70
A72
A47
A96
A187
A43
A98
A5
A40
A71
A1
A1b
A29
A20
A91
A66
A90
A85
A7
A10
A12
A12b
A80
A80b
A28
A17
A44
A30
A54
A2
A55
A117
A115
A63
A63b
A25
A25b
A145
A113
A122
A136
A55b
Ayo2
A120
A124
P10
P28
P11
P4
P3
P22
A125
P25
P14
P1
P15
P27
A11
P17
P26
P6
P5
P16
A116
A116b
P29
A21
A21b
P7
A141
P2
P23
P12
A35
A38
A38b
P21
P8
A147
A134
A140
P24
A118
A123
Resistant Sensitive
Progress 12 345
Response Score
i) BRCA1
Mutation
ii) Low BRCA1 mRNA
iii) BRCA1 methylation
iv) ΔNp63/TAp73 > 2
v) p53 NSM
Sample No. 15 21 26 27 4 6 12 13 16 14 20 22 24 3 5 9 17 181 11 23 25 2 7 8 10
28 29
x x
xx
xx
x
x
x
x
x
x
x
x
xx x
xx x
xx
xx
****
Fig 1. Predictors of response to cisplatin therapy in triple-negative basal-like tumors. (A) The sample dendrogram of gene expression hierarchical cluster analysis with
the intrinsic genes
47
is shown. Cisplatin pretreatment samples (sample numbers in red) are co-clustered with a reference set of breast tumors (sample numbers in
black). Intrinsic subtype of the reference cases, determined by an independent hierarchical cluster analysis, is indicated by the color bar below the dendrogram as
follows: luminal A, dark blue; luminal B, light blue; ErbB2, green; normal-like, purple; basal-like, red. Cisplatin response of the trial patients is indicated on the lower row
as follows: resistant (progression, Miller-Payne score of 1 or 2) in gray; sensitive (Miller-Payne score of 3, 4, or 5) in black. (*) Trial cases with pathologic complete
response (pCR; Miller-Payne score of 5). (B) Relationship of BRCA1 biomarkers and p53 family biomarkers to cisplatin sensitivity. Each trial patient is indicated by sample
number, and patients are arranged according to relative response to cisplatin chemotherapy. Progression or Miller-Payne response scores are indicated above each
sample. Predictive biomarker positivity is indicated with solid circles as follows: i ⫽the presence of a BRCA1 germline mutation, ii ⫽the lowest quartile of BRCA1
mRNA expression measured by quantitative reverse transcriptase polymerase chain reaction, iii ⫽the presence of BRCA1 promoter methylation, iv ⫽the ratio of mRNA
expression levels of ⌬Np63/TAp73 measured by quantitative reverse transcriptase polymerase chain reaction ⬎2, and v ⫽the presence of p53 protein-truncating
mutations. For each biomarker, samples with no data are indicated by a gray X; in addition, for BRCA1 mRNA expression and promoter methylation, a gray X indicates
“not applicable”for the two cases with known BRCA1 germline mutation. NSM, nonsense or frameshift mutations.
Silver et al
1148 © 2010 by American Society of Clinical Oncology JOURNAL OF CLINICAL ONCOLOGY

Bonferroni adjustment for multiple comparisons; when the two
BRCA1 mutations carriers were excluded, P⫽.001 and the Miller-
Payne response rate in patients age 42 to 49 years decreased to 60%;
Table 2; Fig 2A). This effect was not attributable to decreased dose or
dose delays in older patients (data not shown). Age was not signifi-
cantly associated with pCR (P⫽.13) or clinical response (P⫽.46).
BRCA1 Genotype
The two BRCA1 mutation carriers achieved pCR; the other four
patients with pCR were germline BRCA1 wild type (Table 1, Fig 1Bi).
Without the two BRCA1 mutation carriers, the overall clinical re-
sponse rate was 16 (62%) of 26, the good response rate was 12 (46%)
of 26, and the pCR rate was four (15%) of 26.
BRCA1 mRNA Expression
Lower BRCA1 mRNA expression (measured by qRT-PCR) was
significantly associated with a larger percent of patients having good
response (P⫽.03; Table 2 and Figs 1Bii and 2B). All five patients with
the lowest quartile of BRCA1 expression had a good response while
only five of the 16 other patients with BRCA1 expression data had
good responses. Multiple pairs of primers gave similar results. Exclud-
ing the tumors from BRCA1 carriers, the remaining three evaluable
tumors showing pCR did not express BRCA1 at low levels. However,
five of seven evaluable tumors in the Miller-Payne 3 and 4 groups had
BRCA1 expression levels in the lowest quartile. The levels of the
BRCA1 transcriptional repressor, ID4, have been shown to correlate
inversely with BRCA1 expression levels
23
; we did not see an inverse
AB
P 1 E1/E2 E16/E17 E19/E202345
Age (years)
BRCA1 mRNA (2-ΔΔCT)
Miller-Payne Score Primer Pairs
70
10.0
1.0
0.1
0.01
60
50
40
30
***** *
DC
P12345
E2F3 Signature Score
Miller-Payne Score
0.3
0.2
0.0
-0.1
-0.2
-0.3
0.1
200 bp –
100 bp –
–+16
mm mmmmmmmuu uuuuuuu
17 20 21 22 23 24
MW
Fig 2. Relationship of cisplatin treatment response to clinical and molecular features. (A) The patient age in years (y-axis) and Miller-Payne pathologic response score
to neoadjuvant cisplatin therapy (x-axis) are plotted for each patient in the cohort as indicated by solid circles (P⫽.001 based on ordered quartiles of age). (B) Relative
BRCA1 mRNA level measured by quantitative reverse transcriptase polymerase chain reaction (PCR; 2
⫺⌬⌬CT
)
48
is plotted for resistant tumors (solid circles) and
sensitive tumors (open circles). The average mRNA level of each group is indicated by a black horizontal line. Measurements were performed using PCR primer pairs
encompassing exons 1 and 2 (E1/E2), exons 16 and 17 (E16/E17), and exons 19 and 20 (E19/E20) as indicated along the bottom of the plot. The Wilcoxon Pvalues
for difference between sensitive and resistant tumors are indicated above each primer pair as follows: (***) P⫽.020; (**) P⫽.048; (*) P⫽.098. (C) Electrophoresis
of PCR products spanning the BRCA1 promoter from bisulfite-treated DNA. Each lane contains products generated from separate PCR reactions using primers specific
for methylated (m) or unmethylated (u) DNA template. Bacterial methylase-treated lymphocyte DNA was used for the positive control (⫹). DNA from normal
lymphocytes was used as a negative control (⫺). The lane marked MW indicates molecular weight markers measured in base pairs (bp). Paired methylated- and
unmethylated-specific primer reactions are marked by a line over the paired lanes and labeled corresponding to the template DNA used in the reaction (positive control,
negative control, and patient No.). Patients 17 and 23 demonstrate bands in both the unmethylated (u) and methylated (m) lanes indicating the presenceofBRCA1
promoter methylation. Patients 16, 20, 21, 22, and 24 lack bands with the methylated primer pair, signifying the absence of BRCA1 promoter methylation. (D) The E2F3
signature score (y-axis) and Miller-Payne pathologic response scores (x-axis) plotted (solid circles) for each patient in the cohort with available gene expression array
data (Pearson correlation, 0.46; P⫽.025).
Neoadjuvant Cisplatin in Triple-Negative Breast Cancer
www.jco.org © 2010 by American Society of Clinical Oncology 1149

correlation between array-measured ID4 expression and BRCA1 ex-
pression measured by qRT-PCR (Spearman correlation ⫺0.05;
P⫽.84; data not shown).
BRCA1 Promoter Methylation
BRCA1 promoter methylation was analyzed by methylation-
specific PCR, a method sensitive to low levels of methylation (Fig 1Biii
and Fig 2C). BRCA1 expression levels were lower in tumors with
BRCA1 promoter methylation compared with tumors without (me-
dians of 0.025 and 0.33, respectively; Wilcoxon rank sum test P⫽.06;
Supplemental Fig 2). Tumors with BRCA1 promoter methylation
were more likely to have good response, but not pCR or clinical
response, than tumors without methylation (75% v27%; P⫽.04).
⌬Np63/TAp73 Ratio
The transcription factor ⌬Np63
␣
promotes survival in a subset
of tumors through its ability to repress the proapoptotic activity of the
related p53 family member TAp73.
24-26
Phosphorylation of TAp73
after cisplatin treatment causes TAp73 release from ⌬Np63
␣
, enabling
TAp73 to activate a program of apoptosis.
25
Tumors with this pathway
intact would be predicted to be platinum sensitive and to have high
levels of ⌬Np63 relative to TAp73 to repress TAp73 activity in the
absence of cisplatin. For this reason, levels of ⌬Np63 and TAp73 were
measured by qRT-PCR using RNA from microdissected primary tu-
mor samples. Nine (41%) of the 22 evaluable tumors had a ⌬Np63/
TAp73 ratio ⬎2, the predetermined cutoff value suggesting active
repression of TAp73 by ⌬Np63
25
(data not shown). Of these nine
tumors, six (67%) had good responses to cisplatin and three (33%)
had a pCR. Of 13 tumors with ⌬Np63/TAp73 ⬍2, five (38%) had
good responses and only one (8%) had a pCR (Fig 1Biv; P⫽.39 for
good response; P⫽.26 for pCR; P⫽.66 for clinical response). Of the
complete responders with material available, three of four patients had
a⌬Np63/TAp73 ⬎2. These results provide preliminary evidence that
a⌬Np63/TAp73 ratio ⬎2 associates with a greater chance of response
to cisplatin.
p53 Mutation
The sequence of the p53 gene in tumor DNA was determined in
22 patients. Six tumors had nonsense or frameshift mutations (NSM),
10 had missense mutations (MSM), and six were wild type (wt),
confirming the high frequency of p53 mutation in TNBC. There was
no significant association of good response with the presence of a p53
mutation compared with wt (P⫽.64). However, the tumors with
NSM tended to have a higher good response percent than those in the
other two groups (100% v30% v33% in NSM, MSM, and wt groups,
respectively; P⫽.03), and the difference in response rate between
tumors with NSM and MSM was significant (P⫽.01). These tumors
also had a higher rate of pCR (33% v10% and 17%) and clinical
response (100% v60% and 33%) but these differences were not
significant (P⫽.30 and P⫽.11).
Several Predictors of Miller-Payne Response
Used Together
In an exploratory analysis of whether any of the other variables
might add to the prediction based on age, we did step-up logistic
regression for the outcome of good response, omitting the oldest age
quartile. Using this approach, BRCA1 mRNA added significantly to
predictions based on age alone (for details, see Supplemental Data).
Array Mining
We used several approaches to search for genes or gene signatures
associated with cisplatin response. First, we identified candidate genes
reported to have association with cisplatin response (eg, ERCC1,
BIRC5; see Supplemental Data 1) and genes associated with subsets
within TNBC (eg, basal keratins, EGFR,alpha B-crystallin). We eval-
uated the Pearson correlation between the Miller-Payne score and
gene expression array level of these 114 candidate genes. Only a single
gene correlation, AIFM1, remained significant after correction for
multiple hypothesis testing (corrected P⫽.041). However, the ex-
pression level and standard deviation were low for this probe, suggest-
ing random fluctuation. A complete list of candidate genes tested and
Pvalues are listed in Supplemental Data 1.
In addition, we evaluated published gene signatures consisting of
a set of co-regulated gene expression changes in response to a specific
oncogene pathway activation
27
or specific biologic processes, includ-
ing cell cycle,
28
chromosome instability,
29
and core serum response.
30
We also tested an immune response classifier reported to have prog-
nostic value in estrogen receptor–negative breast cancers.
31
For each
signature, we calculated a score estimating the relative level of the gene
signature present in the array data from each tumor. We tested this
score for association with response using Pearson correlation (see
Supplemental Data 2). No signature was statistically significant after
Bonferroni correction for multiple hypothesis testing. The strongest
association was with a signature of E2F3 oncogenic pathway activation
(Fig 2D; r⫽0.46; P⫽.025), which has been associated with general
chemotherapy responsiveness.
27
Finally, we identified all genes with correlation to the Miller-
Payne response score, a standard deviation ⬎0.5, and a Pvalue ⬍.01.
No correlation was significant after Bonferroni correction (see Sup-
plemental Data 3). The highest correlations were with inhibitor of
growth family member 3 (ING3;r⫽0.69; P⫽.0002) and metastasis-
associated lung adenocarcinoma transcript 1 (MALAT1), a non-
protein coding gene (r⫽.62; P⫽.001). The reproducibility of these
potential candidate biomarkers will have to be determined by analysis
of independent cohorts of similarly treated patients.
DISCUSSION
Six (21%) of 28 patients with TNBC achieved pCR with single-agent
neoadjuvant cisplatin. Among the 28 patients in this trial were two
BRCA1 carriers, both of whom achieved pCR; four (15%) of the 26
women with sporadic TNBC also achieved pCR to cisplatin. Overall,
50% of the patients had a good response to cisplatin defined by a
Miller-Payne score of 3, 4, or 5. These results are consistent with
preclinical and recent clinical data
32
showing that BRCA1-associated
tumors are responsive to cisplatin, and data that suggest a subset of
basal-like breast cancers with intact BRCA1 share some fundamental
molecular defects with BRCA1-deficient tumors.
The effect of increasing dose, intensity, and/or duration of cispla-
tin on response rates is unknown. Sporadic TNBCs show heterogene-
ity in response to other cytotoxic chemotherapies, with reported pCR
rates of TNBC ranging from 12% for single-agent taxane regimens to
27% to 45% in multiagent neoadjuvant trials.
1,3,4,33
Our data also
suggest heterogeneity among these patients on the basis of their re-
sponse to cisplatin. Clinical progression on cisplatin was also ob-
served: other neoadjuvant studies of TNBC either have used different
Silver et al
1150 © 2010 by American Society of Clinical Oncology JOURNAL OF CLINICAL ONCOLOGY

criteria or have not reported on progression, making it difficult to
make meaningful comparisons of progression rates.
3,4
We studied
a variety of biomarkers to try to discover those that would distin-
guish patients likely to respond from patients unlikely to respond
to cisplatin.
In our hands, triple negativity using a strict criteria of ⬍1%
nuclear staining for estrogen and progesterone receptor immuno-
histochemistry, criteria for HER2 negativity of 0 or 1⫹by immu-
nohistochemistry, or HER2 nonamplification by fluorescent in situ
hybridization reliably predicted classification into the basal-like sub-
type by hierarchical cluster analysis of the intrinsic genes.
Age correlated with response whether or not the two patients
with BRCA1 mutations were included, with younger patients more
likely to respond. The biologic explanation for this finding is unclear.
It does not seem related to cisplatin dosing or dose intensity because
these did not vary with age. Younger patients may develop subtypes of
TNBC that are more responsive to chemotherapy in general or cispla-
tin in particular. Of note, younger age was a predictor of breast cancer
sensitivity to neoadjuvant therapy with paclitaxel, fluorouracil, doxo-
rubicin, and cyclophosphamide in a recent study.
34
We tested the hypothesis that low BRCA1 expression is an expla-
nation of the phenotypic similarity of sporadic TNBC and BRCA1-
related breast cancer. BRCA1 mRNA levels were lower in patients with
cisplatin sensitivity, consistent with the suggestion that the “BRCA-
ness” of these tumors may be related to decreased BRCA1 expres-
sion.
18,23
However, the lowest BRCA1-expressing tumors were not
those with pCR (excluding the BRCA1 germline mutation tumors),
but rather were those with moderate responses to cisplatin (Miller-
Payne score of 3 or 4). BRCA1 promoter methylation, assessed by a
sensitive methylation-specific PCR assay, was also statistically signifi-
cantly correlated with response to cisplatin (P⫽.04) and was inversely
correlated to BRCA1 mRNA levels (P⫽.06). These data suggest that a
subset of TNBCs may be sensitive to cisplatin on the basis of low
BRCA1 expression levels. The rarity of low BRCA1 levels among
tumors with pCR to cisplatin may be a reflection of the small number
of patients analyzed and emphasizes the need to validate results of
this exploratory trial in an independent cohort. In this regard, it is
interesting that low levels of BRCA1 expression in ovarian tumors
correlate with better survival in patients treated with cisplatin-
containing regimens.
35
Our trial and a recent report
32
of a neoadjuvant trial using the
same cisplatin regimen in women with germline BRCA1 mutations
suggest that tumors from women with hereditary BRCA1 mutations
have a high rate of response to cisplatin. Whether tumors from BRCA1
mutation carriers truly represent a homogeneous group with respect
to cisplatin response or to other cytotoxic agents will require further
experience. The small number of BRCA1 mutation carriers treated to
date does not provide sufficient data for clinical use of neoadjuvant
cisplatin outside of a trial.
p53 mutation status has been investigated as a potential predictor
of chemotherapy responsiveness in solid tumors
36-40
: Nonsense and
truncating p53 mutations have been shown to be common in BRCA1-
mutated breast cancer.
41
We found a significant association of tumor
p53 protein-truncating mutations (NSM) with cisplatin response.
A pathway of apoptosis activated by cisplatin involving the p53
family members TAp73 and ⌬Np63
␣
may play a role in cisplatin
sensitivity.
25
We measured the ratio of the mRNA of these two genes as
a marker of the potential integrity of this pathway. Although not
statistically significant, three (75%) of four patients with pCR related
to cisplatin were positive for this biomarker. This finding is consistent
with a recent retrospective analysis of response following neoadjuvant
cisplatin-based chemotherapy.
42
In exploratory analyses (given the small sample size and large
number of measured genes), no single gene on transcriptional arrays
convincingly segregated responders from nonresponders. None of a
smaller set of candidate genes reported to have some relationship to
cisplatin response showed a strong association with response. Notable
negatives include ERCC1, reported prognostic in cisplatin-treated
lung cancer,
43
and alpha B-crystallin.
44
Of several signatures consisting
of responses of many genes to a perturbation relevant for tumorigen-
esis, only one stood out in this analysis, a signature derived by overex-
pression of the transcription factor E2F3.
27
A proportion of TNBCs
have copy number gain on chromosome 6p at the E2F3 locus (Z.C.
Wang, unpublished data), and there is evidence for inactivation of the
Rb pathway in a proportion of TNBCs,
45,46
which leads to E2F3
overexpression. Furthermore, the E2F3 pathway signature is associ-
ated with response of TNBC to neoadjuvant chemotherapy using
drugs other than cisplatin.
40
It is unclear whether any of the biomar-
kers correlated with cisplatin response reported here represent specific
markers of cisplatin response; they may indicate general chemothera-
py responsiveness. However, in cell culture experiments and in a
retrospective clinical analysis, the p63/p73 pathway is related specifi-
cally to cisplatin response and not to response to a variety of other
chemotherapeutic agents.
25,26
We emphasize that patients in this neoadjuvant trial received
standard therapy after surgery, and the relatively low pCR rate to
single-agent cisplatin (21% for all patients, 15% excluding the BRCA1
mutation carriers) argues against administration of single-agent cis-
platin as adjuvant or neoadjuvant therapy for unselected TNBCs.
Multiagent neoadjuvant therapy has achieved higher pCR rates: 45%
to 24 weeks of paclitaxel/fluorouracil, doxorubicin, and cyclophosph-
amide (T/FAC),
4
and 24% to doxorubicin and cyclophosphamide
(AC) often followed by a taxane.
3
In this study, we could not assess
whether the tumors that responded to cisplatin were the same as or
different from tumors that would have responded to established mul-
tiagent regimens. We believe that these results justify exploring thera-
peutic combinations including platinum agents in TNBC and invite
additional efforts at discovering biomarkers predictive of response.
AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS
OF INTEREST
Although all authors completed the disclosure declaration, the following
author(s) indicated a financial or other interest that is relevant to the subject
matter under consideration in this article. Certain relationships marked
with a “U” are those for which no compensation was received; those
relationships marked with a “C” were compensated. For a detailed
description of the disclosure categories, or for more information about
ASCO’s conflict of interest policy, please refer to the Author Disclosure
Declaration and the Disclosures of Potential Conflicts of Interest section in
Information for Contributors.
Employment or Leadership Position: None Consultant or Advisory
Role: None Stock Ownership: None Honoraria: None Research
Funding: Judy E. Garber, AstraZeneca Expert Testimony: None Other
Remuneration: None
Neoadjuvant Cisplatin in Triple-Negative Breast Cancer
www.jco.org © 2010 by American Society of Clinical Oncology 1151

AUTHOR CONTRIBUTIONS
Conception and design: Daniel P. Silver, Andrea L. Richardson, Rebecca
S. Gelman, Paula D. Ryan, Shridar Ganesan, Leif W. Ellisen, Eric P.
Winer, Judy E. Garber
Financial support: Daniel P. Silver, Andrea L. Richardson, Leif W.
Ellisen, Eric P. Winer, Judy E. Garber
Administrative support: Daniel P. Silver, Andrea L. Richardson, Eric P.
Winer, Judy E. Garber
Provision of study materials or patients: Daniel P. Silver, Andrea L.
Richardson, Diana Calogrias, Paula D. Ryan, Nadine M. Tung, Dennis C.
Sgroi, Eric P. Winer, Judy E. Garber
Collection and assembly of data: Daniel P. Silver, Andrea L. Richardson,
Zhigang C. Wang, Chee-Onn Leong, Diana Calogrias, Ayodele
Buraimoh, Aquila Fatima, Arcangela De Nicolo, Shridar Ganesan,
Alexander Miron, Christian Colin, Dennis C. Sgroi, Leif W. Ellisen, Eric
P. Winer, Judy E. Garber
Data analysis and interpretation: Daniel P. Silver, Andrea L.
Richardson, Aron C. Eklund, Zhigang C. Wang, Zoltan Szallasi, Qiyuan
Li, Nicolai Juul, Chee-Onn Leong, Rebecca S. Gelman, Arcangela De
Nicolo, Shridar Ganesan, Alexander Miron, Christian Colin, Dennis C.
Sgroi, Leif W. Ellisen, Eric P. Winer, Judy E. Garber
Manuscript writing: Daniel P. Silver, Andrea L. Richardson, Zoltan
Szallasi, Rebecca S. Gelman, Nadine M. Tung, Christian Colin, Eric P.
Winer, Judy E. Garber
Final approval of manuscript: Daniel P. Silver, Andrea L. Richardson,
Aron C. Eklund, Zhigang C. Wang, Zoltan Szallasi, Qiyuan Li, Nicolai
Juul, Chee-Onn Leong, Diana Calogrias, Ayodele Buraimoh, Aquila
Fatima, Rebecca S. Gelman, Paula D. Ryan, Nadine M. Tung, Arcangela
De Nicolo, Shridar Ganesan, Alexander Miron, Christian Colin, Dennis
C. Sgroi, Leif W. Ellisen, Eric P. Winer, Judy E. Garber
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■■■
Glossary Terms
Promoter methylation: Methylation of DNA sequences
within the promoters of genes; this often occurs on the cytosine
residue of CpG dinucleotides and is correlated with decreased
expression of the adjacent gene.
BRCA1 expression: A tumor suppressor gene, the breast
cancer 1 susceptibility gene is known to play a role in repairing
DNA breaks. Mutations in this gene are associated with increased
risks of developing breast or ovarian cancer.
Hierarchical cluster: An analytical tool used to find the clos-
est associations among gene profiles and specimens under evaluation.
PCR (polymerase chain reaction): PCR is a method that
allows exponential amplification of short DNA sequences within a
longer DNA molecule.
Double-strand break repair: Any of several DNA repair pro-
cesses used by organisms to repair breaks in DNA that span both
strands of DNA at a single location.
BRCA1: A tumor suppressor gene that prevents ovarian and
breast cancer.
Gene signature: The coordinated response of many genes to a particu-
lar stimulus; for example, the “myc oncogene signature” is the response of
many genes to the forced overexpression of the myc oncogene.
Intrinsic genes: A set of genes whose level of expression is used to sort
breast cancers into subtypes.
Methylation-specific PCR: A molecular assay that detects methyl-
ation of a particular stretch of DNA.
Gene array: A microchip on which DNA sequences for many genes
are embedded; used to measure gene expression of many genes
simultaneously.
BRCA-ness: A term applied to breast cancers, referring to the
degree of relationship of a given breast cancer to one deficient in the
BRCA1 gene.
Neoadjuvant Cisplatin in Triple-Negative Breast Cancer
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