CT-X Antigen Expression in Human Breast Cancer

CT-X antigen expression in human breast cancer

Anita Grigoriadisa,1,2, Otavia L. Caballerob,1,3, Keith S. Hoekc, Leonard da Silvad, Yao-Tseng Chene, Sandra J. Shine, Achim A. Jungbluthb, Lance D. Millerf, David Cloustong, Jonathan Cebong, Lloyd J. Oldb,3, Sunil R. Lakhanid, Andrew J. G. Simpsonb, and A. Munro Nevillea

aLudwig Institute for Cancer Research, 605 Third Avenue, New York, NY 10158; bLudwig Institute for Cancer Research, New York Branch at Memorial Sloan–Kettering Cancer Center, 1275 York Avenue, New York, NY 10021; cDepartment of Dermatology, University Hospital of Zurich, Gloriastrasse 31/F2, CH-8091 Zurich, Switzerland; dMolecular and Cellular Pathology, UQ Centre for Clinical Research and The School of Medicine, Level 6 Building 71/918, University of Queensland, The Royal Brisbane and Women’s Hospital, Herston 4029, Brisbane, Queensland, Australia; eWeill Medical College of Cornell University, 1300 York Avenue, New York, NY 10021; fDepartment of Cancer Biology, Wake Forest University School of Medicine, Medical Center Boulevard, Hanes Building, Winston-Salem, NC 27157; and gAustin Health and the Cancer Vaccine Laboratory at the Ludwig Institute for Cancer Research, Austin Hospital, Heidelberg 3084, Australia

Contributed by Lloyd J. Old, June 18, 2009 (sent for review April 29, 2009) Cancer/testis (CT) genes are predominantly expressed in human the present study was to undertake a more comprehensive germ line cells, but not somatic tissues, and frequently become analysis of CT-X antigen expression in primary breast cancer in activated in different cancer types. Several CT antigens have the context of clinicopathological parameters. The results point already proved to be useful biomarkers and are promising targets to a restricted expression of members of the MAGEA and for therapeutic cancer vaccines. The aim of the present study was NY-ESO-1/CTAG1B gene families, primarily in ER negative to investigate the expression of CT antigens in breast cancer. Using tumors, some of which belong to the basal phenotype. Such previously generated massively parallel signature sequencing lesions have a poorer prognosis for which, currently, therapeutic (MPSS) data, together with 9 publicly available gene expression options are limited. CT-X-based immunotherapy strategies may datasets, the expression pattern of CT antigens located on the X thus represent an important therapeutic option for patients with chromosome (CT-X) was interrogated. Whereas a minority of these subtypes of breast tumors. unselected breast cancers was found to contain CT-X transcripts, a significantly higher expression frequency was detected in estrogen Results and progesterone receptor (ER) negative breast cancer cell lines Detection of CT-X Antigen Expression in Massively Parallel Signature MEDICAL SCIENCES and primary breast carcinomas. A coordinated pattern of CT-X Sequencing Data. As an initial step in exploring CT-X antigen antigen expression was observed, with MAGEA and NY-ESO-1/ expression in breast cancer, we interrogated our previously CTAG1B being the most prevalent antigens. Immunohistochemical published MPSS data (22). These data were derived from a pool staining confirmed the correlation of CT-X antigen expression and of normal human breast luminal epithelial cells, a pool of ER negativity in breast tumors and demonstrated a trend for their predominantly ER-positive epithelial enriched primary breast coexpression with basal cell markers. Because of the limited ther- tumors and 4 breast epithelial cell lines (22, 23). Sequence tags apeutic options for ER-negative breast cancers, vaccines based on corresponding to 6 of the 83 CT-X antigens, including those for CT-X antigens might prove to be useful. MAGEA (1,646 transcripts per million [tpm]), CSAG2 (680 tpm), CT45 (263 tpm), PASD1 (24 tpm), CSAG1 (15 tpm), and cancer/testis antigens ͉ estrogen receptor ͉ therapy FMR1NB/NY-SAR-35 (11 tpm), were detected in only one sample, an ER-negative breast cell line BT20. ancer/testis (CT) antigens are encoded by a unique group of Cgenes that are predominantly expressed in human germ line CT-X Antigen Expression in Breast Cancer Gene Expression Studies. To cells, have little or no expression in somatic adult tissues, but further examine the possible relationship of CT-X expression become aberrantly activated in various malignancies (1). A total with ER status, a list of 66 Affymetrix probe sets identifying 65 of 153 CT antigens has been described to date and are compiled different CT-X-encoding genes was prepared (supporting infor- in the CT database (www.cta.lncc.br/) (2, 3). Of these antigens, mation (SI) Table S1). Nine published microarray-based gene 83 are encoded by multigene families located on the X-chromo- expression datasets derived from a total of 1,259 primary breast some and are referred to as the CT-X antigens (1). Although tumors and 51 breast cancer cell lines were available, and the ER their possible involvement in chromosomal recombination, tran- status was known in most. Four hundred three of 1,310 samples scription, translation and signaling has been proposed, the were ER-negative (Table 1). Using the HG-U133A platform, we physiological function of the great majority of CT-X antigens interrogated for each dataset gene expression patterns differ- remains poorly elucidated (1, 4). entiating between ER-negative and ER-positive samples. Ap- The expression of CT-X antigens varies greatly between tumor plying multiple testing controls, a P value cut-off of 0.05 and a types, being most frequent in melanomas, bladder, non-small cell 2-fold change filter, this analysis identified a set of 147 probe sets lung, ovarian, and hepatocellular carcinomas. The occurrence of CT-X antigens is uncommon in renal, colon, and gastric cancers (4). Where present, CT-X expression is associated with a poorer Author contributions: A.G., O.L.C., A.J.G.S., and A.M.N. designed research; A.G., O.L.C., K.S.H., L.d.S., Y.-T.C., S.J.S., A.A.J., D.C., J.C., and S.R.L. performed research; Y.-T.C., S.J.S., outcome and tends to be more frequent in higher grade lesions L.D.M., and S.R.L. contributed new reagents/analytic tools; A.G., O.L.C., K.S.H., L.d.S., and advanced disease (5–8). Y.-T.C., L.D.M., S.R.L., A.J.G.S., and A.M.N. analyzed data; and A.G., O.L.C., K.S.H., L.d.S., The combination of their restricted expression, and in some Y.-T.C., L.J.O., S.R.L., A.J.G.S., and A.M.N. wrote the paper. cases potent immunogenicity, has led to intense research into The authors declare no conflict of interest. their utilization in therapeutic vaccines (9). Clinical trials of Freely available online through the PNAS open access option. vaccines containing the CT-X antigens MAGEA and NY-ESO- 1A.G. and O.L.C. contributed equally to this work. 1/CTAG1B are underway in patients with several cancers, 2Present address: Breakthrough Breast Cancer Research Unit, Guy’s Hospital, King’s Health including those of the lung, ovary, and melanoma (10–16). Partners AHSC, London, United Kingdom. Relatively few studies have explored the expression pattern of 3To whom correspondence may be addressed. E-mail: [email protected] or [email protected]. CT-X antigens in breast cancer and the few cases studied to date This article contains supporting information online at www.pnas.org/cgi/content/full/ have focused on NY-ESO-1/CTAG1B (17–21). The objective of 0906840106/DCSupplemental.

www.pnas.org͞cgi͞doi͞10.1073͞pnas.0906840106 PNAS Early Edition ͉ 1of6 Downloaded by guest on September 30, 2021 Table 1. Datasets used in this study Samples Available annotations

Name Accession no. ERneg ERpos Unknown ER PR p53 HER2 Reference

Boersma GSE5847 26 21 1 Yes No No No 28 Desmedt GSE7390 64 134 — Yes No No No 46 Doane Website* 42 57 — Yes Yes No Yes 30 Hess Website† 51 82 — Yes Yes No Yes 29 Ivshina GSE4922 34 211 4 Yes No Yes No 44 Minn GSE2603 42 57 22 Yes No No Yes 31 Neve E-TABM-157 33 18 — Yes Yes Yes Yes 27 Sotiriou GSE2990 34 85 6 Yes No No No 47 Wang GSE2034 77 209 — Yes No No No 45 vandeVijver Website‡ 69 226 — Yes No No No 34

*https://caarraydb.nci.nih.gov/caarray/. †http://bioinformatics.mdanderson.org/pubdata.html. ‡http://microarray-pubs.stanford.edu/wound࿝NKI/.

(131 genes) that showed significant differential expression be- tion of CT-X expression and PR status, p53 mutation and HER2 tween ER-negative and ER-positive breast tumors in at least 5 status where available (Table 1). For each metric, the complete of the 9 datasets investigated. This list represents the ER specific datasets of the above mentioned 9 breast tumor cohorts were expression (ERSE) set (Table S2). Many of the ERSE genes interrogated for a significant relationship with metric status, and have previously been identified as differentially expressed in probe sets with less than a 2-fold change were discarded. This breast tumors in an ER status-dependent manner, or to be direct analysis was repeated for the CT-X antigen list (Table S1). There ER target genes (24–26). is a very strong overlap between the Doane (30) and Minn (31) The ERSE set was used to cluster the samples in each dataset 2-fold PR significant lists (137 probe sets, PRSE) (Table S12). (Fig. S1), confirming that ER status annotation was consistent The PRSE list also shared 105 probe sets in common with the in each dataset and that a CT-X-specific analysis would probably ERSE list (P value Ͻ0.001), confirming that PR and ER not be confounded by extraneous errors of annotation or data status-specific gene expression patterns are tightly linked. In the gathering. For each dataset, CT-X gene expression patterns were Minn (31) dataset, 3 CT-X antigens (MAGEA6, MAGEA3 and assessed for their relationship with ER status. This analysis used an identical test as was used to find the ERSE, except only the CT-X genes were tested and no fold-change filter was applied. The data are displayed as a summary (Table 2) and from the context of individual datasets (Tables S3–S11). To examine the enrichment of CT-X in the ER-negative tumors, we clustered the breast tumor datasets using the normalized CT-X expression data (Fig. 1). This analysis shows that relatively few CT-X genes are strongly expressed in breast cancer samples. For 3 datasets [Neve (27), Boersma (28), and Hess (29)], no statistically significant associations were found until multiple testing controls were subtracted from the analysis. The genes encoding CTAG1A/CTAG1B and CTAG2 (NY-ESO-1/CTAG1B family) showed the most consistent relationship with ER status (Table 2 and Fig. 2), being preferentially expressed in ER- negative samples (median adjusted P value Ͻ0.006). Other CT-X antigens showed consistent, but ultimately non-significant, re- lationships with ER status–notably MAGEA3 and MAGEA6 (Tables S3–S11). A similar analysis was performed for examining the correla-

Table 2. ER status-speciﬁc CT-X gene expression (summary) Probe set Gene symbol Median P value

211674࿝x࿝at CTAG1A CTAG1B 0.005 210546࿝x࿝at CTAG1A CTAG1B 0.005 215733࿝x࿝at CTAG2 0.005 217339࿝x࿝at CTAG1A CTAG1B 0.006 209942࿝x࿝at MAGEA3 0.154 220325࿝at TAF7L 0.239 214612࿝x࿝at MAGEA6 0.263 Fig. 1. CT-X gene expression in breast cancer. Normalized gene expression 219702࿝at PLAC1 0.274 data for CT-X genes were used to cluster breast cancer samples. Samples are 205564࿝at PAGE4 0.314 arranged as columns and CT-X antigens in rows. Expression levels are pseudo- 214254࿝at MAGEA4 0.317 colored, red indicating transcript levels above the median for that probe set 206626࿝x࿝at SSX1 0.317 across all samples and green below the median. The bar below each heatmap indicates the ER-negative (red) and ER-positive (green) status of the samples.

2of6 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.0906840106 Grigoriadis et al. Downloaded by guest on September 30, 2021 Table 3. Fraction of ER-negative samples expressing increased levels of CT-X genes* Probe set Gene symbol Criteria I† Criteria II‡

209942࿝x࿝at MAGEA3 26.1% 26.7% 214612࿝x࿝at MAGEA6 23.9% 25.8% 211674࿝x࿝at CTAG1B; CTAG1A 18.4% 20.4% 210546࿝x࿝at CTAG1B; CTAG1A 17.1% 20.2% 210467࿝x࿝at MAGEA12 15.8% 18.5% 217339࿝x࿝at CTAG1B 15.0% 19.6% 215733࿝x࿝at CTAG2 14.1% 17.8% 220445࿝s࿝at CSAG2 14.1% 17.4% 214603࿝at MAGEA2; MAGEA2B 13.2% 14.5% 214642࿝x࿝at MAGEA5 9.4% 15.6% 214254࿝at MAGEA4 8.5% 7.7% 210503࿝at MAGEA11 7.7% 6.7% 210437࿝at MAGEA9 7.3% 8.6%

Calculated using 9 separate datasets (Table 1). *Top 13 probes. †Average percentage of ER-negative samples with Ͼ2-fold above mean expression level of all genes. ‡Average percentage of ER-negative samples in which expression is in the top tenth percentile of all genes.

Table 3 shows the fraction of ER-negative samples that expresses increased levels of CT-X antigens. In this series of 403 ER-negative primary breast cancers, members of the MAGEA and NY-ESO-1/CTAG1B families are expressed in 38.9% and MEDICAL SCIENCES 20.1% of the cases, respectively. Forty-four percent of the ER-negative tumors express members of either MAGEA or NY-ESO-1/CTAG1B families.

CT-X Antigen Expression in Molecular Subtypes of Breast Cancers. Using molecular profiling, breast cancers can be subdivided into luminal, HER2-positive, basal-like and so-called normal breast- like tumors (32, 33). We were able to evaluate whether the expression of CT-X antigens is subtype-specific using the van de Vijver dataset (Table 1) (34). The correlation of CT antigen expression with the different breast cancer subtypes in the van de Vijver data were tested with ANOVA analysis. A significant correlation of CT-X expression with the basal subgroup was

Grade ER MAGEA4 MAGEB1 MAGEA10 MAGEA5 MAGEA2B MAGEA6 MAGEA12 PLAC1 SSX1 CSAG2 CTAG2 MAGEA1 FATE1 TFDP3 Fig. 2. NY-ESO-1 gene expression in breast cancer. Normalized gene expres- CTAG1B sion data for NY-ESO-1 genes were used to cluster breast cancer samples, CXorf61 highlighting the association that NY-ESO-1 genes have with ER-negative CTAG1B samples. Samples are arranged as columns and CT-X antigens in rows. Expres- Sorlie.type sion levels are pseudocolored, red indicating transcript levels above the median for that probe set across all samples and green below the median. The Fig. 3. CT-X antigen expression in breast tumor subtypes. The Van de Vivjer bar below each heatmap indicates the ER-negative (red) and ER-positive dataset (34) was used to determine distribution of CT-X antigen expression. (green) status of the samples. The color bar at the bottom indicates the 5 subtypes deﬁned by Sorlie et al. (33), whereby red indicates basal-like, purple HER2, luminal A blue and B orange, and green the normal like subtype. In the expression matrix, red MAGEA9) showed PR status-specific gene expression, but none indicates increased and blue decreased CT-X antigen expression. The upper of these showed a Ͼ2-fold differential expression. No consistent, color bars show biological and clinical aspects of the tumors. Blue and yellow significant relationship was detected between CT-X antigens and represent a positive and negative status for ER, whereas gold, light green, and any of the 3 metrics examined. dark green represent grades 1, 2, and 3.

Grigoriadis et al. PNAS Early Edition ͉ 3of6 Downloaded by guest on September 30, 2021 Table 4. Immunohistochemistry expression of CT antigens in breast cancer No. of tumors with expression No. (%)

Series Tumor Description n MAGEA NY-ESO-1 MAGEA/ NY-ESO-1 MAGEA/ NY-ESO-1

1 Primary 153 6 3 3 12 (8) 2 Primary 19 3 4 2 9 (47) 3a Primary 29 13 0 1 14 (45) 3b Brain mets from 3a 53 29 2 4 35 (66)

confirmed for MAGEA4 (P value Ͻ0.001), MAGEA10 (P value observed in 29, 2, and 4 deposits, respectively. Twenty-one of 0.022), MAGEA5 (P value 0.013), MAGEA2B (P value Ͻ0.001), these CT-X positive metastases were ER-negative, of which 12 MAGEA5 (P value 0.013), MAGEA6 (P value Ͻ0.01), MAGEA12 were also PR-negative (Tables 4–7). (P value 0.046), CTAG2 (P value Ͻ0.001), MAGEA1 (P value The overall distribution of ER-positive and ER-negative tu- Ͻ0.011), and NY-ESO-1/CTAG1B (P value Ͻ0.001). Such tumors mors positive for MAGEA and NY-ESO-1/CTAG1B is shown in are of a higher grade and predominantly ER-negative (Fig. 3). Table 7. The data confirm the relative frequency of expression and distribution by ER status found by transcriptional analysis, Immunohistochemical Demonstration of CT Antigens in Tissue Arrays with NY-ESO-1/CTAG1B being expressed more particularly in of Breast Cancer. To confirm CT-X antigen expression in breast ER-negative tumors. cancer at the tissue level, 3 TMA-based immunohistochemical (IHC) studies were carried out to complement the gene expres- Discussion sion studies. The second and third studies built on the results The present study suggests that CT-X antigen expression is obtained from the first. The salient features are summarized in frequent in ER-negative breast cancer. The single result in the Tables 4–7, and detailed results are shown in Dataset S1.Ina original MPSS data where CT-X antigens were found in an first analysis, a series of 153 unselected cases of infiltrating breast ER-negative breast cell line, and not generally in breast cancer carcinomas were examined revealing 12/153 (8%) tumors posi- samples or in normal breast tissue, stimulated the subsequent tive for MAGEA, and/or NY-ESO-1/CTAG1B or both (Fig. 4, more detailed analysis aimed at determining whether the rela- Tables 4–7). CT-X antigen expression was taken as positive when tionship between ER status and CT-X expression was of broad at least 1–2% of the tumor cell population was positively stained. significance in breast cancer. The ability to access published Heterogeneity was a feature for both CT-X antigens. Whereas microarray datasets and carry out a series of defined analyses 103 of the 153 tumors in the series were ER-positive, all but one proved to be invaluable. The analyses of 51 breast cell lines and of the CT-X antigen positive tumors (11/12) fell into the the 1,259 breast tumors highlighted the association of steroid ER/PR-negative category. It was notable that p53 expression was receptor negative breast cancer and a propensity to express CT-X more prominent in the CT-X group (Fig. 4, Tables 4–7) and that antigens. The previous assumption of a general low expression of most had a high proliferative index as assessed by Ki-67 staining CT antigens in breast cancer is a result of studying unselected series (Dataset S1). The second series comprised a highly selected in which ER-negative tumors usually comprise only Ϸ25% of cases. group of 19 triple negative breast tumors (ER, PR, and HER2- Indeed, the very first immunopathology study of this work exem- negative). Antigens of the MAGEA or NY-ESO-1/CTAG1B plifies this conclusion where less than one-third of the tumors were family were present in 9/19 (47%) of these breast tumors (Tables ER-negative. As a result, only 8% (12/153) of the lesions were CT-X 4–7). Thirteen of these 19 cases were of the basal type, of which positive, but 11 of the cancers with CT-X expression lacked estrogen 5 were positive for CT-X antigens (Tables 4–7). The final IHC receptors (series 1, Tables 4–7). series consisted of 29 matched pairs of primary breast tumors On the basis of molecular profiling, Perou and Sorlie and their and 53 corresponding brain metastases. These breast tumors had colleagues have classified breast cancer into 5 groups, namely spread preferentially and/or initially to the brain, a feature not luminal A, luminal B, basal-like, HER2 positive, and so-called infrequently associated with the basal subtype (35). Fourteen of normal breast-like (27, 28). Neve et al. (27) have delineated some 29 (48%) of these primary tumors showed MAGEA and/or of the breast cell lines used in the present study (Fig. 1) as being NY-ESO-1/CTAG1B expression (Tables 4–7). Of these 14 CT-X basal-like due to their expression of cytoplasmic components antigen positive tumors, 9 were ER-negative, 7 of which were typically found in the basal cells of the normal breast. In our also PR- negative (Tables 4–7). Thirty-five of 53 (66%) breast various analyses of the gene arrays, basal-like cell lines and cancer metastases to the brain showed the presence of MAGEA tumors both exhibited higher expression of CT-X antigens. and/or NY-ESO/CTAG1B at the protein level. MAGEA and Breast cancers with basal–like features are a recently recognized NY-ESO-1/CTAG1B expression individually and combined, was entity of increasing importance. These lesions are generally of

Table 5. Characteristics of tumors positive for MAGEA or NY-ESO-1 antigens by immunohistochemistry Tumor characteristics

Series Tumor description MAGEA or NY-ESO-1 positive ER neg P53 pos Basal ER neg Basal

1 Primary 12 11 10 ND ND 2 Primary 9 9* ND 5 5 3a Primary 14 9† 9107 3b Brain mets from 3a 35 21‡ 16 25 12

ND, not done. *Also PR-negative. †7/9 also PR-negative. ‡12/21 also PR-negative.

4of6 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.0906840106 Grigoriadis et al. Downloaded by guest on September 30, 2021 Table 6. Characteristics of tumors included in the immunohistochemistry series Tumor characteristics

Series Tumor description n ER neg P53 pos HER2 neg Basal EGFR pos

1 Primary 153 50 66 ND ND ND 2 Primary 19 19 ND 19 13 16 3a Primary (initial mets to brain) 29 16 17 12 19 1 3b Brain mets from 3a 53 30 23 42 34 4

ND, not done.

higher grade, have a lower propensity to metastasize to local series, it would seem that there is a restricted expression of lymph nodes, exhibit a distinct tendency to spread to brain, and members of the MAGEA family as well as NY-ESO-1/CTAG1B carry a very poor prognosis (35–37). Usually they are ER/PR- in almost half of all ER-negative breast cancers, including triple negative and do not overexpress HER2. Therefore, these tumors negative and basal-like cancers. In conclusion, our study suggests constitute a subset of the so-called triple negative breast cancers. that a high percentage of ER-negative breast cancer patients may Consequently, we addressed the question of a potential asso- benefit from CT-X antigen-based vaccine treatment. ciation of CT-X expression with hormone receptor and/or HER2 status by an immunohistochemical analysis of 2 more collections Materials and Methods of breast tumors (series 2 and 3) comprising a high number of Datasets, Gene Annotations, and Expression Analyses. The CT antigen database ER-negative breast cancers, many of which resembled the basal- (www.cta.lncc.br/) (2) was used as a reference to extract data corresponding to like type. We clearly show that MAGEA and NY-ESO/CTAG1B the CT-X-encoding genes from the 9 microarray datasets analyzed in this study are frequently expressed in such tumors (Tables 4–7). using mRNA accession numbers as cross-references (27–31, 34, 44–47). When several probe sets were available for the same gene, all were used for analysis. Current clinical management of breast cancer (early detection, Ͻ surgery, and cytotoxic drug regimens often in the adjuvant Each dataset was subjected to a standard normalization procedure. Values 0.01 were set to 0.01. Each measurement was divided by the 50th percentile of all setting) has resulted in significant gains in disease-free and measurements in that sample. Each probe set was divided by the median of its overall survival in recent times (38). Some additional advances measurements in all samples. A statistical analysis (ANOVA) was used to identify MEDICAL SCIENCES have been achieved through the use of targeted forms of therapy probe sets with class-specific expression patterns using unfiltered data (22,283 such as Tamoxifen and aromatase inhibitors for those breast probe sets). For determining the ER-specific expression (ERSE) set, the statistical cancers possessing estrogen receptors (39, 40). Trastuzumab analysis used the Student 2-sample t test, a P value cut-off of 0.05, and the (Herceptin), a humanized monoclonal antibody against the Benjamini and Hochberg false discovery rate (48) to control for multiple testing extracellular domain of HER2, has been shown recently to benefit patients with HER2-positive primary and metastatic disease (41, 42). Vaccine studies with HER2 peptide in breast AD cancers expressing ERBB2 are also in progress (43). There remains a need to develop further tumor-specific targets, particularly for those tumors that lack steroid receptors and do not have amplification of HER2. To date, immunotherapeutic regimens for breast cancer have also been used mainly in end-stage disease and have generally used antigens expressed in normal tissues with elevated expression or expression of mutated forms in tumor cells. Included in this category are antigens such as MUC1, CEA, and the carbo- hydrate antigens (39). By contrast, current thinking places the BE role of immunotherapy as being most likely to be effective when patients only have minimal residual disease after initial treatment. CT-X antigens through their restricted distribution in the testis and cancer cells offer a more specific opportunity for vaccine development and therapy. Currently, vaccines comprising members of the MAGEA and NY-ESO-1 families are in clinical trials in patients with melanoma and lung cancer, where such antigens are frequently expressed (11–18). The present results, therefore, highlight a group of CT-X CF antigen-expressing steroid receptor-negative breast cancers for which therapeutic options are limited. From the data of this

Table 7. Overall distribution of MAGEA and NY-ESO-1/CTAG1B positive tumors by ER status No.

Tumor description CT-X positivity MAGEA NY-ESO-1/CTAG1B Fig. 4. Expression of MAGEA, NY-ESO-1/CTAG1B and p53 in primary and Primaries ER-negative 23 3 metastatic breast tumors. Shown is IHC staining demonstrating the protein Primaries ER-positive 5 0 expression of MAGEA, NY-ESO-1/CTAG1B, and p53 in primary (A,10ϫ; B,20ϫ; ϫ ϫ ϫ ϫ Metastases ER-negative 19 2 C, 100 ) and breast cancer metastases to the brain (D,10 ; E,20 ; F, 100 ), Metastases ER-positive 11 0 NY-ESO-1/CTAG1B revealing a mostly cytoplasmic presence of CT-X antigens and the typical nuclear expression of p53.

Grigoriadis et al. PNAS Early Edition ͉ 5of6 Downloaded by guest on September 30, 2021 error. A 2-fold change filter was then applied, and probe sets that met these blocks for the TMAs. The TMAs and series 2 samples were dewaxed in xylene and conditions in at least 5 of the 9 datasets investigated were retained. The proba- rehydrated through alcohols. Antigen retrieval was performed by microwave bility of probe sets meeting these criteria by chance can be estimated using boiling in 100 mM citrate buffer (pH 6.0) for 15 min or for series 2 and 3 in EDTA binomial distribution to be ϷP Ͻ 3.32 ϫ 10Ϫ5. This analysis was repeated sepa- (pH 8.0) buffer for 2 min. Endogenous peroxidase activity was quenched with rately for the CT-X antigen-encoding genes (66 probe sets). 0.3% hydrogen peroxide for 5 min. Sections were then incubated with affinity purified NY-ESO-1/CTAG1B-specific rabbit polyclonal antibody (NY45) (series 1) CT-X Antigen Expression in Molecular Subtypes of Breast Cancers. An analysis or monoclonal antibodies ES121 or E978 specific to NY-ESO-1/CTAG1B (series 2 of variance (ANOVA) was performed to examine the correlation between the and 3) and monoclonal antibody specific to MAGEA (detecting multiple MAGE-A CT-X antigen expression level and the 5 breast tumor subtypes of the van de antigens, including MAGE-A1, -A3, -A4, and -A6) (6C1, Santa Cruz Biotechnology) Vijver dataset as categorized in their original study (34). The P values were diluted in Tris-buffered saline with 10% BSA at 1:1,000 for1hatroom temper- adjusted for multiple comparisons using the method of Benjamini and Hoch- ature. The slides were then processed using Dako Envisionϩ HRP (DakoCytoma- berg, whereby P values Յ0.05 were considered significant. tion, Glostrup, Denmark), following the manufacturer’s protocol, counterstained briefly with Mayer’s hematoxylin (Amber Scientific, Belmont, WA), and cover Immunohistochemistry of CT-X Antigens and Tissue Microarray Analysis. Rou- slipped. Specimens of known antigen-positive tumors were used as a positive tinely fixed paraffin-embedded tissue blocks containing mammary carcinomas control, and negative controls were prepared by omission of the primary anti- excised at the time of surgery were extracted from the files of the Department of body or by using a relevant subclass negative control. The various antibodies and Surgical Pathology, Weill-Cornell Medical College (IHC series 1), from the files of their source used to demonstrate breast cancer features are shown in Table S13. the Department of Pathology, Austin Hospital, Melbourne (IHC series 2), or from the files of the Department of Pathology, University of Brisbane, Medical Faculty ACKNOWLEDGMENTS. This work was conducted as part of the Hilton–Ludwig of Charles University in Plzen-Czech Republic, Instituto Nacional do Cancer-Brazil, Cancer Metastasis Initiative, funded by the Conrad N. Hilton Foundation and and Laboratorio Salomao Zoppi-Brazil (IHC series 3). Series 1 and 3 served as donor the Ludwig Institute for Cancer Research Ltd.

1. Simpson AJ, Caballero OL, Jungbluth A, Chen YT, Old LJ (2005) Cancer/testis antigens, 24. Lin CY, et al. (2004) Discovery of estrogen receptor alpha target genes and response gametogenesis and cancer. Nat Rev Cancer 5:615–625. elements in breast tumor cells. Genome Biol 5:R66. 2. Almeida LG, et al. (2008) CTdatabase: A knowledge-base of high-throughput and 25. Voduc D, Cheang M, Nielsen T (2008) GATA-3 expression in breast cancer has a strong curated data on cancer-testis antigens. Nucleic Acids Res 37:D816–D819. association with estrogen receptor but lacks independent prognostic value. Cancer 3. Hofmann O, et al. (2008) Genome-wide analysis of cancer/testis gene expression. Proc Epidemiol Biomarkers Prev 17:365–373. Natl Acad Sci USA 105:20422–20427. 26. Smith DD, et al. (2008) Meta-analysis of breast cancer microarray studies in conjunction 4. Scanlan MJ, Simpson AJ, Old LJ (2004) The cancer/testis genes: Review, standardization, with conserved cis-elements suggest patterns for coordinate regulation. BMC Bioin- and commentary. Cancer Immun 4:1. formatics 9:63. 5. Gure AO, et al. (2005) Cancer-testis genes are coordinately expressed and are markers 27. Neve RM, et al. (2006) A collection of breast cancer cell lines for the study of function- of poor outcome in non-small cell lung cancer. Clin Cancer Res 11:8055–8062. ally distinct cancer subtypes. Cancer Cell 10:515–527. 6. Velazquez EF, et al. (2007) Expression of the cancer/testis antigen NY-ESO-1 in primary 28. Boersma BJ, et al. (2008) A stromal gene signature associated with inflammatory breast and metastatic malignant melanoma (MM)–correlation with prognostic factors. Can- cancer. Int J Cancer 122:1324–1332. cer Immun 7:11. 29. Hess KR, et al. (2006) Pharmacogenomic predictor of sensitivity to preoperative che- 7. Andrade VC, et al. (2008) Prognostic impact of cancer/testis antigen expression in motherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in advanced stage multiple myeloma patients. Cancer Immun 8:2. breast cancer. J Clin Oncol 24:4236–4244. 8. Napoletano C, et al. (2008) MAGE-A and NY-ESO-1 expression in cervical cancer: 30. Doane AS, et al. (2006) An estrogen receptor-negative breast cancer subset character- Prognostic factors and effects of chemotherapy. Am J Obstet Gynecol 198:99 e91–97. ized by a hormonally regulated transcriptional program and response to androgen. 9. Scanlan MJ, Gure AO, Jungbluth AA, Old LJ, Chen YT (2002) Cancer/testis antigens: An Oncogene 25:3994–4008. expanding family of targets for cancer immunotherapy. Immunol Rev 188:22–32. 10. Bender A, et al. (2007) LUD 00–009: Phase 1 study of intensive course immunization 31. Minn AJ, et al. (2005) Genes that mediate breast cancer metastasis to lung. Nature with NY-ESO-1 peptides in HLA-A2 positive patients with NY-ESO-1-expressing cancer. 436:518–524. Cancer Immun 7:16. 32. Perou CM, et al. (2000) Molecular portraits of human breast tumours. Nature 406:747–752. 11. Atanackovic D, et al. (2008) Booster vaccination of cancer patients with MAGE-A3 33. Sorlie T, et al. (2003) Repeated observation of breast tumor subtypes in independent protein reveals long-term immunological memory or tolerance depending on priming. gene expression data sets. Proc Natl Acad Sci USA 100:8418–8423. Proc Natl Acad Sci USA 105:1650–1655. 34. van de Vijver MJ, et al. (2002) A gene-expression signature as a predictor of survival in 12. Jager E, et al. (2006) Recombinant vaccinia/fowlpox NY-ESO-1 vaccines induce both breast cancer. N Engl J Med 347:1999–2009. humoral and cellular NY-ESO-1-specific immune responses in cancer patients. Proc Natl 35. Fulford LG, et al. (2007) Basal-like grade III invasive ductal carcinoma of the breast: Acad Sci USA 103:14453–14458. Patterns of metastasis and long-term survival. Breast Cancer Res 9:R4. 13. van Baren N, et al. (2005) Tumoral and immunologic response after vaccination of 36. Fulford LG, et al. (2006) Specific morphological features predictive for the basal melanoma patients with an ALVAC virus encoding MAGE antigens recognized by T phenotype in grade 3 invasive ductal carcinoma of breast. Histopathology 49:22–34. cells. J Clin Oncol 23:9008–9021. 37. Crabb SJ, et al. (2008) Basal breast cancer molecular subtype predicts for lower 14. Valmori D, et al. (2007) Vaccination with NY-ESO-1 protein and CpG in Montanide incidence of axillary lymph node metastases in primary breast cancer. Clin Breast induces integrated antibody/Th1 responses and CD8 T cells through cross-priming. Proc Cancer 8:249–256. Natl Acad Sci USA 104:8947–8952. 38. Quinn MJ, Cooper N, Rachet B, Mitry E, Coleman MP (2008) Survival from cancer of the 15. Odunsi K, et al. (2007) Vaccination with an NY-ESO-1 peptide of HLA class I/II specific- breast in women in England and Wales up to 2001. Br J Cancer 99(Suppl 1):S53–S55. ities induces integrated humoral and T cell responses in ovarian cancer. Proc Natl Acad 39. Herold CI, Blackwell KL (2008) Aromatase inhibitors for breast cancer: Proven efficacy Sci USA 104:12837–12842. across the spectrum of disease. Clin Breast Cancer 8:50–64. 16. Davis ID, et al. (2004) Recombinant NY-ESO-1 protein with ISCOMATRIX adjuvant 40. Ponzone R, et al. (2006) Antihormones in prevention and treatment of breast cancer. ϩ ϩ induces broad integrated antibody and CD4( ) and CD8( ) T cell responses in humans. Ann NY Acad Sci 1089:143–158. Proc Natl Acad Sci USA 101:10697–10702. 41. Madarnas Y, et al. (2008) Adjuvant/neoadjuvant trastuzumab therapy in women with 17. Theurillat JP, et al. (2007) NY-ESO-1 protein expression in primary breast carcinoma and HER-2/neu-overexpressing breast cancer: A systematic review. Cancer Treat Rev 34:539– metastases: Correlation with CD8ϩ T-cell and CD79aϩ plasmacytic/B-cell infiltration. 557. Int J Cancer 120:2411–2417. 42. Park IH, et al. (2009) Trastuzumab treatment beyond brain progression in HER2- 18. Bandic D, et al. (2006) Expression and possible prognostic role of MAGE-A4, NY-ESO-1, positive metastatic breast cancer. Ann Oncol. 20:56–62. and HER-2 antigens in women with relapsing invasive ductal breast cancer: Retrospec- 43. Benavides LC, et al. (2009) The impact of HER2/neu expression level on response to the tive immunohistochemical study. Croat Med J 47:32–41. E75 vaccine: From U.S. Military Cancer Institute Clinical Trials Group Study I-01 and I-02. 19. Mischo A, et al. (2006) Prospective study on the expression of cancer testis genes and Clin Cancer Res 15:2895–2904. antibody responses in 100 consecutive patients with primary breast cancer. Int J Cancer 118:696–703. 44. Ivshina AV, et al. (2006) Genetic reclassification of histologic grade delineates new 20. Sugita Y, et al. (2004) NY-ESO-1 expression and immunogenicity in malignant and clinical subtypes of breast cancer. Cancer Res 66:10292–10301. benign breast tumors. Cancer Res 64:2199–2204. 45. Wang Y, et al. (2005) Gene-expression profiles to predict distant metastasis of lymph- 21. Taylor M, Bolton LM, Johnson P, Elliott T, Murray N (2007) Breast cancer is a promising node-negative primary breast cancer. Lancet 365:671–679. target for vaccination using cancer-testis antigens known to elicit immune responses. 46. Desmedt C, et al. (2007) Strong time dependence of the 76-gene prognostic signature Breast Cancer Res 9:R46. for node-negative breast cancer patients in the TRANSBIG multicenter independent 22. Grigoriadis A, et al. (2006) Establishment of the epithelial-specific transcriptome of validation series. Clin Cancer Res 13:3207–3214. normal and malignant human breast cells based on MPSS and array expression data. 47. Sotiriou C, et al. (2006) Gene expression profiling in breast cancer: Understanding the Breast Cancer Res 8:R56. molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst 98:262–272. 23. Jongeneel CV, et al. (2005) An atlas of human gene expression from massively parallel 48. Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I (2001) Controlling the false discovery signature sequencing (MPSS). Genome Res 15:1007–1014. rate in behavior genetics research. Behav Brain Res 125:279–284.

6of6 ͉ www.pnas.org͞cgi͞doi͞10.1073͞pnas.0906840106 Grigoriadis et al. Downloaded by guest on September 30, 2021