Integrated profiling of basal and luminal breast cancers.

Basal and luminal are two molecular subtypes of breast cancer with opposite histoclinical features. We report a combined, high-resolution analysis of genome copy number and gene expression in primary basal and luminal breast cancers. First, we identified and compared genomic alterations in 45 basal and 48 luminal tumors by using 244K oligonucleotide array comparative genomic hybridization (aCGH). We found various genome gains and losses and rare high-level gene amplifications that may provide therapeutic targets. We show that gain of 10p is a new alteration in basal breast cancer and that a subregion of the 8p12 amplification is specific of luminal tumors. Rare high-level amplifications contained BCL2L2, CCNE, EGFR, FGFR2, IGF1R, NOTCH2, and PIK3CA. Potential gene breaks involved ETV6 and FLT3. Second, we analyzed both aCGH and gene expression profiles for 42 basal and 32 luminal breast cancers. The results support the existence of specific oncogenic pathways in basal and luminal breast cancers, involving several potential oncogenes and tumor suppressor genes (TSG). In basal tumors, 73 candidate oncogenes were identified in chromosome regions 1q21-23, 10p14, and 12p13 and 28 candidate TSG in regions 4q32-34 and 5q11-23. In luminal breast cancers, 33 potential oncogenes were identified in 1q21-23, 8p12-q21, 11q13, and 16p12-13 and 61 candidate TSG in 16q12-13, 16q22-24, and 17p13. HORMAD1 (P = 6.5 x 10(-5)) and ZNF703 (P = 7 x 10(-4)) were the most significant basal and luminal potential oncogenes, respectively. Finally, among 10p candidate oncogenes associated with basal subtype, we validated CDC123/C10orf7 protein as a basal marker.

Moesin expression is a marker of basal breast carcinomas.

Basal breast cancers (BBCs) have a high risk of metastasis, recurrence and death. Formal subtype definition relies on gene expression but can be approximated by protein expression. New markers are needed to help in the management of the basal subtype of breast cancer. In a previous transcriptional analysis of breast cell lines we found that Moesin expression was a potential basal marker. We show here that Moesin protein expression is a basal marker in breast tumors. In a tissue microarray (TMA) containing 547 sporadic breast cancers, of which 108 were profiled for gene expression, Moesin was expressed in 31% of all tumors and in 82% of the basal tumors. To confirm that Moesin expression remained associated with the basal phenotype in specific types of BBCs, we analyzed Moesin expression in 2 other TMAs containing 40 medullary breast cancers (MBCs) and 27 BRCA1-associated breast cancers (BRCA1-BCs), respectively. Moesin was strongly expressed in MBCs (87%; p = 2.4 x 10(-5)) and in BRCA1-BCs (58%; p = 1.3 x 10(-5)) as compared with non-MBCs and sporadic cases. Moesin-expressing tumors display features of BBCs, such as high proliferation rate, hormone receptors negativity, expression of putative basal/myoepithelial markers (CAV1, CD10, CK5/6, CK14, EGFR, P53, P-cadherin and SMA). Survival analysis showed a reduced specific survival and metastasis-free survival in Moesin-expressing tumors by log-rank test (p(SS) = 0.014 and p(MFS) = 0.014). In multivariate analysis, Moesin expression was nearly an independent prognostic marker of poor outcome as shown by Cox proportional hazard model in patients without lymph node metastasis (p = 0.052, HR = 2.38, CI 95[0.99-5.69]).

Nectin-4 is a new histological and serological tumor associated marker for breast cancer.

INTRODUCTION: Breast cancer is a complex and heterogeneous disease at the molecular level. Evolution is difficult to predict according to classical histoclinical prognostic factors. Different studies highlight the importance of large-scale molecular expression analyses to improve taxonomy of breast cancer and prognostic classification. Identification of new molecular markers that refine this taxonomy and improve patient management is a priority in the field of breast cancer research.Nectins are cell adhesion molecules involved in the regulation of epithelial physiology. We present here Nectin-4/PVRL4 as a new histological and serological tumor associated marker for breast carcinoma. METHODS: Expression of Nectin-4 protein was measured on a panel of 78 primary cells and cell lines from different origins and 57 breast tumors by FACS analysis and immunohistochemistry (IHC), respectively. mRNA expression was measured by quantitative PCR. Serum Nectin-4 was detected by ELISA and compared with CEA and CA15.3 markers, on panels of 45 sera from healthy donors, 53 sera from patients with non-metastatic breast carcinoma (MBC) at diagnosis, and 182 sera from patients with MBC. Distribution of histological/serological molecular markers and histoclinical parameters were compared using the standard Chi-2 test. RESULTS: Nectin-4 was not detected in normal breast epithelium. By contrast, Nectin-4 was expressed in 61% of ductal breast carcinoma vs 6% in lobular type. Expression of Nectin-4 strongly correlated with the basal-like markers EGFR, P53, and P-cadherin, and negatively correlated with the luminal-like markers ER, PR and GATA3. All but one ER/PR-negative tumors expressed Nectin-4. The detection of Nectin-4 in serum improves the follow-up of patients with MBC: the association CEA/CA15.3/Nectin-4 allowed to monitor 74% of these patients compared to 67% with the association CEA/CA15.3. Serum Nectin-4 is a marker of disease progression, and levels correlate with the number of metastases (P = 0.038). Serum Nectin-4 is also a marker of therapeutic efficiency and correlates, in 90% of cases, with clinical evolution. CONCLUSION: Nectin-4 is a new tumor-associated antigen for breast carcinoma. Nectin-4 is a new bio-marker whose use could help refine breast cancer taxonomy and improve patients' follow-up. Nectin-4 emerges as a potential target for breast cancer immunotherapy.

Frequency, prognostic impact, and subtype association of 8p12, 8q24, 11q13, 12p13, 17q12, and 20q13 amplifications in breast cancers.

BACKGROUND: Oncogene amplification and overexpression occur in tumor cells. Amplification status may provide diagnostic and prognostic information and may lead to new treatment strategies. Chromosomal regions 8p12, 8q24, 11q13, 17q12 and 20q13 are recurrently amplified in breast cancers. METHODS: To assess the frequencies and clinical impact of amplifications, we analyzed 547 invasive breast tumors organized in a tissue microarray (TMA) by fluorescence in situ hybridization (FISH) and calculated correlations with histoclinical features and prognosis. BAC probes were designed for: (i) two 8p12 subregions centered on RAB11FIP1 and FGFR1 loci, respectively; (ii) 11q13 region centered on CCND1; (iii) 12p13 region spanning NOL1; and (iv) three 20q13 subregions centered on MYBL2, ZNF217 and AURKA, respectively. Regions 8q24 and 17q12 were analyzed with MYC and ERBB2 commercial probes, respectively. RESULTS: We observed amplification of 8p12 (amplified at RAB11FIP1 and/or FGFR1) in 22.8%, 8q24 in 6.1%, 11q13 in 19.6%, 12p13 in 4.1%, 17q12 in 9.9%, 20q13Z (amplified at ZNF217 only) in 9.9%, and 20q13Co (co-amplification of two or three 20q13 loci) in 8.5% of cases. The 8q24, 12p13, and 17q12 amplifications were correlated with high grade. The most frequent single amplifications were 8p12 (9.8%), 8q24 (3.3%) and 12p13 (3.3%), 20q13Z and 20q13Co (1.6%) regions. The 17q12 and 11q13 regions were never found amplified alone. The most frequent co-amplification was 8p12/11q13. Amplifications of 8p12 and 17q12 were associated with poor outcome. Amplification of 12p13 was associated with basal molecular subtype. CONCLUSION: Our results establish the frequencies, prognostic impacts and subtype associations of various amplifications and co-amplifications in breast cancers.

Typical medullary breast carcinomas have a basal/myoepithelial phenotype.

Medullary breast cancer (MBC) is a rare, diagnostically difficult, pathological subtype. Despite being high grade, it has a good prognosis. MBC patients have an excess of BRCA1 germ-line mutation and reliable identification of MBC could help to identify patients at risk of carrying germline BRCA1 mutations or in whom chemotherapy could be avoided. The aim of this study was therefore to improve diagnosis by establishing an MBC protein expression profile using immunohistochemistry (IHC) on tissue-microarrays (TMA). Using a series of 779 breast carcinomas ('EC' set), diagnosed initially as MBC, a double-reading session was carried out by several pathologists on all of the histological material to establish the diagnosis as firmly as possible using a 'medullary score'. Only MBCs with high scores, i.e. typical MBC (TMBC) (n=44) and non-TMBC grade III with no or low scores (n=160), were included in the IHC study. To validate the results obtained on this first set, a control series of TMBC (n=17) and non-MBC grade III cases (n=140) ('IPC' set) was studied. The expression of 18 proteins was studied in the 61 TMBCs and 300 grade III cases from the two sets. The global intra-observer concordance of the first reading for the diagnosis of TMBC was 94%, with almost perfect kappa (kappa) of 0.815. TMBC was characterized by a high degree of basal/myoepithelial differentiation. In multivariate analysis with logistic regression, TMBC was defined by the association of P-cadherin (R=2.29), MIB1 > 50 (R=3.80), ERBB2 negativity (R=2.24) and p53 positivity (RR=1.45).

Protein expression profiling identifies subclasses of breast cancer and predicts prognosis.

Breast cancer is a heterogeneous disease whose evolution is difficult to predict by using classic histoclinical prognostic factors. Prognostic classification can benefit from molecular analyses such as large-scale expression profiling. Using immunohistochemistry on tissue microarrays, we have monitored the expression of 26 selected proteins in more than 1,600 cancer samples from 552 consecutive patients with early breast cancer. Both an unsupervised approach and a new supervised method were used to analyze these profiles. Hierarchical clustering identified relevant clusters of coexpressed proteins and clusters of tumors. We delineated protein clusters associated with the estrogen receptor and with proliferation. Tumor clusters correlated with several histoclinical features of samples, including 5-year metastasis-free survival (MFS), and with the recently proposed pathophysiologic taxonomy of disease. The supervised method identified a set of 21 proteins whose combined expression significantly correlated to MFS in a learning set of 368 patients (P < 0.0001) and in a validation set of 184 patients (P < 0.0001). Among the 552 patients, the 5-year MFS was 90% for patients classified in the "good-prognosis class" and 61% for those classified in the "poor-prognosis class" (P < 0.0001). This difference remained significant when the molecular grouping was applied according to lymph node or estrogen receptor status, as well as the type of adjuvant systemic therapy. In multivariate analysis, the 21-protein set was the strongest independent predictor of clinical outcome. These results show that protein expression profiling may be a clinically useful approach to assess breast cancer heterogeneity and prognosis in stage I, II, or III disease.

Immunophenotypic analysis of inflammatory breast cancers: identification of an 'inflammatory signature'.

Inflammatory breast cancer (IBC) is a rare but very aggressive form of breast cancer. Its definition is based on clinical criteria, but a molecular definition could be useful when data are incomplete or features are missing. Recently, the identification of overexpression of E-cadherin in IBC has improved understanding of the molecular basis of this disease. Consequently, the aim of this study was to try to determine an immunophenotypic 'signature' of IBC. A series of 80 cases of IBC were compared with 552 non-IBC control cases and a model was elaborated to evaluate the probability of an inflammatory carcinoma being present in any clinical situation. Tissue microarrays (TMAs) were used to determine the immunohistochemical profile of eight proteins including E-cadherin, EGFR, oestrogen and progesterone receptor (ER and PR), MIB1, ERBB2, MUC1, and P53. All the parameters tested were differentially expressed between IBC and control cases in univariate analysis (p < 0.001). The five variables that were significantly associated with IBC in multivariate analysis were E-cadherin > or = 300 [HR = 5.64 (2.92-10.87)], ER negative [HR = 3.00 (1.67-5.51)], MIB1 > 20 [HR = 3.54 (1.87-6.71)], MUC1 cytoplasmic staining [HR = 2.72 (1.49-4.96)], and ERBB2 positive 2+ or 3+ [HR = 2.46 (1.26-4.78)]. The probability that a breast cancer with this full phenotype at diagnosis was an IBC was 90.5%. If any one of the five parameters was missing, this probability dropped to 75% and was less than 50% when one, two, or three parameters were present. The 5-year overall survival (OS) and 5-year disease-free survival (DFS) of patients with IBC were not significantly different from those of the non-IBC control group that expressed four or five parameters (nIBC-1), but this nIBC-1 control group had a significantly worse outcome than the non-IBC control group (nIBC-2) with only 0-3 parameters (p = 0.0049 for OS and p < 0.0001 for DFS). In conclusion, an immunophenotypic signature was suggested for IBC. This could help to determine the worst cases, independent of clinical criteria.

Comparative multi-methodological measurement of ERBB2 status in breast cancer.

The ERBB2 transmembrane tyrosine kinase receptor is both a prognostic marker and a therapeutic target in breast cancer. Accurate determination of ERBB2 status is a prerequisite for the establishment of prognostic significance and for the selection of ERBB2-overexpressing breast tumours for specific treatment. Unfortunately, there is no complete agreement on how this determination should be performed. This study has compared four methods of assessment of ERBB2 status. Two global, extraction-based methods using real-time quantitative PCR on DNA (Q-PCR) or RNA (RQ-PCR) and two non-global, tissue-based methods, ie fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC), were used. The 94 breast cancers tested were enriched in cases scoring 2+ using the IHC scoring system currently in use and for which the actual ERBB2 status remains ill defined. To determine the best parameters and reagents for assessment, two protocols for FISH and five anti-ERBB2 antibodies were used, and both FISH and IHC were carried out on the same tissue microarrays (TMAs). It is shown that the combination of the two tissue-based methods gives the best results. The use of either PCR-based method did not improve the results significantly. A new combined IHC score based on the association of two selected anti-ERBB2 antibodies (HercepTest trade mark and TAB250) and a dual scale for improved assessment of ERBB2 protein expression, particularly in 2+ cases, are proposed.

Identification and validation of an ERBB2 gene expression signature in breast cancers.

ERBB2 is a transmembrane tyrosine kinase receptor encoded by a gene located in chromosome region 17q12. Overexpression of ERBB2, generally by way of gene amplification, plays a role in mammary oncogenesis. This alteration can be overcome by use of the humanized monoclonal antibody trastuzumab (Herceptin). Accurate determination of ERBB2 status is required for appropriate use of this targeted therapy and is currently analysed by immunohistochemistry (IHC) on tissue sections and/or fluorescence in situ hybridisation (FISH) on interphase chromosomes. We have studied the gene expression profiles of a series of 213 breast tumours and 16 breast cancer cell lines with known ERBB2 status, using Ipsogen's DiscoveryChip microarrays with approximately 9000 cDNAs. We have identified 36 genes and expressed sequence tags that were differentially expressed in tumours and in cell lines with and without ERBB2 protein overexpression. This ERBB2-specific gene expression signature (GES) contained 29 overexpressed genes including the ERBB2 gene itself, five genes located in its immediate vicinity on 17q12, non-17q genes such as GATA4 and eight downregulated genes including oestrogen receptor alpha (ER). Some correlations were validated at the protein level using IHC on tissue microarrays. The GES was able to distinguish ERBB2-negative and -positive cancer samples, as well as FISH-negative and FISH-positive ERBB2 2+ IHC samples.

Loss of FHIT protein expression is a marker of adverse evolution in good prognosis localized breast cancer.

The FHIT tumor suppressor gene, which encompasses the fragile site FRA3B at 3p14.2, is altered frequently in many types of human cancers. To determine its importance as a prognostic marker in breast cancer, the expression of the FHIT protein was studied in a series of 452 breast carcinomas by using immunohistochemistry on sections of tissue microarrays. Three distinct levels of FHIT expression were observed: in 154 cases (34.1%) expression was unchanged as compared to normal level; in 78 (17.2%) no expression was found; in the remaining 220 cases (48.7%), expression was intermediate. Overall, two-thirds of the cases had abnormal levels of the protein. Absence of FHIT was significantly associated with a higher grade (p < 0.01) and absence of hormone receptors (p < 0.001). The patients were separated into Group I (153 node-negative good prognosis patients who did not receive adjuvant chemotherapy) and Group II (226 high-risk patients treated by adjuvant chemotherapy) according to the St.-Gallen conference consensus. The median follow-up was 48 months. Among Group I but not Group II patients, a multivariate analysis showed that FHIT expression was significantly associated with disease-free survival. The relative risk of recurrence for FHIT-negative Group I patients was 2.37 (1.21-4.64; p = 0.03). Thus, among the patients who present with tumors of apparent good prognosis, FHIT is an independent prognostic factor that distinguishes a subgroup of patients who could benefit from adjuvant treatment.

Loss of heterozygosity at microsatellite markers from region p11-21 of chromosome 8 in microdissected breast tumor but not in peritumoral cells.

Alterations of chromosomal region 8p11-21 are very frequent in human cancers, and especially in breast cancer; yet, most of the genes involved have not been identified. We performed laser capture microdissection in a series of 52 consecutive breast tumor samples to obtain pure tumor cells without surrounding normal breast. To determine genomic subregions in which some of the cancer genes may be located, we conducted a search for loss of heterozygosity (LOH) at 13 microsatellite markers from this region. Two-thirds of the tumors showed LOH at least at one marker. Microdissection of pure tumor samples was helpful to precisely define four LOH subregions. No LOH was observed in the corresponding peritumoral tissues. We studied by immunohistochemistry (IHC) on tissue-microarrays the expression in the same tumors, of the protein product of three potential tumor genes lying close to or within the subregions of LOH. In most samples, the TACC1 gene product was downregulated in tumor cells as compared to normal cells. Our results show that the centromeric portion of chromosome arm 8p is frequently altered in breast tumor cells.

Distinct and complementary information provided by use of tissue and DNA microarrays in the study of breast tumor markers.

Emerging high-throughput screening technologies are rapidly providing opportunities to identify new diagnostic and prognostic markers and new therapeutic targets in human cancer. Currently, cDNA arrays allow the quantitative measurement of thousands of mRNA expression levels simultaneously. Validation of this tool in hospital settings can be done on large series of archival paraffin-embedded tumor samples using the new technique of tissue microarray. On a series of 55 clinically and pathologically homogeneous breast tumors, we compared for 15 molecules with a proven or suspected role in breast cancer, the mRNA expression levels measured by cDNA array analysis with protein expression levels obtained using tumor tissue microarrays. The validity of cDNA array and tissue microarray data were first verified by comparison with quantitative reverse transcriptase-polymerase chain reaction measurements and immunohistochemistry on full tissue sections, respectively. We found a good correlation between cDNA and tissue array analyses in one-third of the 15 molecules, and no correlation in the remaining two-thirds. Furthermore, protein but not RNA levels may have prognostic value; this was the case for MUC1 protein, which was studied further using a tissue microarray containing approximately 600 tumor samples. For THBS1 the opposite was observed because only RNA levels had prognostic value. Thus, differences extended to clinical prognostic information obtained by the two methods underlining their complementarity and the need for a global molecular analysis of tumors at both the RNA and protein levels.

Carcinogenesis and translational controls: TACC1 is down-regulated in human cancers and associates with mRNA regulators.

The three human TACC genes encode a family of proteins that are suspected to play a role in carcinogenesis. Their function is not precisely known; a Xenopus TACC protein called Maskin is involved in translational control, while the Drosophila D-TACC associates with microtubules and centrosomes. We have characterized the human TACC1 gene and its products. The TACC1 gene is located in region p12 of chromosome 8; its mRNA is ubiquitously expressed and encodes a protein with an apparent molecular mass of 125 kDa, which is cytoplasmic and mainly perinuclear. We show that TACC1 mRNA gene expression is down-regulated in various types of tumors. Using immunohistochemistry of tumor tissue-microarrays and sections, we confirm that the level of TACC1 protein is down-regulated in breast cancer. Finally, using the two-hybrid screen in yeast, GST pull-downs and co-immunoprecipitations, we identified two potential binding partners for TACC1, LSM7 and SmG. They constitute a conserved subfamily of Sm-like small proteins that associate with U6 snRNPs and play a role in several aspects of mRNA processing. We speculate that down-regulation of TACC1 may alter the control of mRNA homeostasis in polarized cells and participates in the oncogenic processes.