Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two major histological types of breast cancer worldwide. Whereas IDC incidence has remained stable, ILC is the most rapidly increasing breast cancer phenotype in the United States and Western Europe. It is not clear whether IDC and ILC represent molecularly distinct entities and what genes might be involved in the development of these two phenotypes. We conducted comprehensive gene expression profiling studies to address these questions. Total RNA from 21 ILCs, 38 IDCs, two lymph node metastases, and three normal tissues were amplified and hybridized to ϳ42,000 clone cDNA microarrays. Data were analyzed using hierarchical clustering algorithms and statistical analyses that identify differentially expressed genes (significance analysis of microarrays) and minimal subsets of genes (prediction analysis for microarrays) that succinctly distinguish ILCs and IDCs. Eleven of 21 (52%) of the ILCs ("typical" ILCs) clustered together and displayed different gene expression profiles from IDCs, whereas the other ILCs ("ductal-like" ILCs) were distributed between different IDC subtypes. Many of the differentially expressed genes between ILCs and IDCs code for proteins involved in cell adhesion/motility, lipid/fatty acid transport and metabolism, immune/defense response, and electron transport. Many genes that distinguish typical and ductal-like ILCs are involved in regulation of cell growth and immune response. Our data strongly suggest that over half the ILCs differ from IDCs not only in histological and clinical features but also in global transcription programs. The remaining ILCs closely resemble IDCs in their transcription patterns. Further studies are needed to explore the differences between ILC molecular subtypes and to determine whether they require different therapeutic strategies.

GATA3 is an essential transcription factor that was first identified as a regulator of immune cell function. In recent microarray analyses of human breast tumors, both normal breast luminal epithelium and estrogen receptor (ESR1)-positive tumors showed high expression of GATA3. We sequenced genomic DNA from 111 breast tumors and three breast-tumor-derived cell lines and identified somatic mutations of GATA3 in five tumors and the MCF-7 cell line. These mutations cluster in the vicinity of the highly conserved second zinc-finger that is required for DNA binding. In addition to these five, we identified using cDNA sequencing a unique mis-splicing variant that caused a frameshift mutation. One of the somatic mutations we identified was identical to a germline GATA3 mutation reported in two kindreds with HDR syndrome/OMIM #146255, which is an autosomal dominant syndrome caused by the haplo-insufficiency of GATA3. The ectopic expression of GATA3 in human 293T cells caused the induction of 73 genes including six cytokeratins, and inhibited cell line doubling times. These data suggest that GATA3 is involved in growth control and the maintenance of the differentiated state in epithelial cells, and that GATA3 variants may contribute to tumorigenesis in ESR1-positive breast tumors.

ITC in BM is an independent predictor of DDFS and BCSS. An unfavorable prognosis was observed for node-positive patients and for node-negative patients not receiving systemic therapy. A combination of several independent prognostic factors can classify subgroups of patients into excellent and high-risk prognosis groups.

Distinct molecular subtypes of breast carcinomas have been identified, but translation into clinical use has been limited. We have developed two platform independent algorithms to explore genomic architectural distortion using array comparative genomic hybridization (aCGH) data to measure 1) whole arm gains and losses (WAAI) and 2) complex rearrangements (CAAI). By applying CAAI and WAAI to data from 595 breast cancer patients we were able to separate the cases into eight subgroups with different distributions of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Histological grade had prognostic impact only in the Luminal related groups while the complexity identified by CAAI had an overall independent prognostic power. This study emphasizes the relationship between structural genomic alterations, molecular subtype and clinical behavior, and show that objective score of genomic complexity (CAAI) is an independent prognostic marker in breast cancer.

There is compelling evidence from transgenic mouse studies and analysis of mutations in human carcinomas indicating that the TGF-β signal transduction pathway is tumor suppressive. We have shown that overexpression of TGF-β1 in mammary epithelial cells suppresses the development of carcinomas and that expression of a dominant negative type II TGF-β receptor (DNIIR) in mammary epithelial cells under control of the MMTV promoter/enhancer increases the incidence of mammary carcinomas. Studies of human tumors have demonstrated inactivating mutations in human tumors of genes encoding proteins involved in TGF-β signal transduction, including DPC4/Smad4, Smad2, and the type II TGF-β receptor (TβRII). There is also evidence that TGF-β can enhance the progression of tumors. This hypothesis is being tested in genetically modified mice. To attain complete loss of TβRII, we have generated mice with loxP sites flanking exon 2 of Tgfbr2 and crossed them with mice expressing Cre recombinase under control of the MMTV promoter/enhancer to obtain Tgfbr2 mgKO mice. These mice show lobuloalveolar hyperplasia. Mice are being followed for mammary tumor development. Tgfbr2 mgKO mice that also express polyoma virus middle T antigen under control of the MMTV promoter (MMTV-PyVmT) develop mammary tumors with a significantly shorter latency than MMTV-PyVmT mice and show a marked increase in pulmonary metastases. Our data do not support the hypothesis that TGF-β signaling in mammary carcinoma cells is important for invasion and metastasis, at least in this model system. The importance of stromal-epithelial interactions in mammary gland development and tumorigenesis is well established. These interactions probably involve autocrine and paracrine action of multiple growth factors, including members of the TGF-β family, which are expressed in both stroma and epithelium. Again, to accomplish complete knockout of the type II TGF-β receptor gene in mammary stromal cells, FSP1-Cre and Tgfbr2 flox/flox mice were crossed to attain Tgfbr2 fspKO mice. The loss of TGF-β responsiveness in fibroblasts resulted in intraepithelial neoplasia in prostate and invasive squamous cell carcinoma of the forestomach with high penetrance by 6 weeks of age. Both epithelial lesions were associated with an increased abundance of stromal cells. Activation of paracrine hepatocyte growth factor (HGF) signaling was identified as one possible mechanism for stimulation of epithelial proliferation. TGF-β signaling in fibroblasts thus modulates the growth and oncogenic potential of adjacent epithelia in selected tissues. More recently, we have examined the effects of Tgfbr2 fspKO fibroblasts on normal and transformed mammary epithelium. We analyzed the role of TGF-β signaling by stromal cells in mammary tumor progression. To avoid the possibility of endogenous wild-type fibroblasts masking potential effects of Tgfbr2 fspKO cells on tumor progression, we implanted PyVmT mammary carcinoma cells with Tgfbr2 fspKO or wildtype fibroblasts in the subrenal capsule of nude mice. Mamm...

Published by Elsevier B.V. All rights reserved. IntroductionGenome-wide expression profiling has demonstrated great power in deciphering molecular portraits of human breast tumors and has identified gene signatures that can be correlated to many different aspects of breast cancer such as tumor progression, prediction of outcome and sensitivity to therapy (Ayers et al., 2004;Chang et al., 2005Chang et al., , 2003Dai et al., 2005;Ma et al., 2003;Sorlie et al., 2001;van't Veer et al., 2002;Wang et al., 2004). Distinct subtypes that are associated with significant differences in overall and disease-free survival have been identified and validated in different patient cohorts (Bertucci et al., 2005;Sorlie et al., 2003;Sotiriou et al., 2003;Yu et al., 2004). Molecular profiling by microarray technologies will improve our understanding of primary tumor biology and the mechanisms behind tumorigenesis, and also provide

The prevalence of and predictive factors for emotional morbidity (measured by the Hospital Anxiety and Depression Scale (HAD)) one year following surgery, with special focus on dispositional optimism/pessimism (measured by the Life Orientation Test (LOT-R), was examined in 165 women, newly diagnosed with breast cancer. Patients characteristics, appraisal of cancer diagnosis, beliefs about treatment efficacy, treatment decision-making participation, coping and emotional morbidity was assessed by self-rating questionnaires. Prevalence of anxiety and depression cases at time of diagnosis was 34 and 12%, respectively, and 26 and 9% after one year. Prevalence of emotional morbidity was significantly enlarged among pessimists at all assessments. Pessimism was the strongest predictor for anxiety (OR: 0.86 C.I. 95% 0.77 - 0.95) and depression (OR: 0.83, C.I. 95% 0.73 - 0.95) one year following breast cancer surgery. Optimists and pessimists differed not only in regard to coping styles, but also in regards to predictors of emotional morbidity. Optimists experiencing anxiety at time of breast cancer diagnosis had about six times higher risk of experiencing anxiety after one year, compared to optimists without preoperative anxiety. For pessimists, the more pessimistic one was about one's overall future the higher risk for developing anxiety following one year of breast cancer surgery. Pessimists, who endorse helpless/hopeless coping style when receiving a diagnosis of breast cancer, had three times greater risk for experiencing depression one year after breast cancer surgery, than pessimists who did not. Health care professionals should therefore provide intervention for pessimists, as well as for patients with high anxiety scores at time of diagnosis.

Purpose: The aim of the study was to explore the value of analyzing bone marrow (BM) for the presence of isolated tumor cell(s) (ITCs) in disease-free breast cancer patients 3 years after diagnosis.Experimental Design: ITCs in BM at operation was found to be an independent prognostic factor in 817 breast cancer patients. Among these, 356 disease-free patients were analyzed with a second BM after 3 years follow-up (median 40 months, SD 3 months, range 29 -52). ITC was detected by immunocytochemistry with anticytokeratine antibodies (AE1/AE3).Results: The population consisted of 70% T 1 and 72% node-negative patients. ITC in BM was detected in 15%. At a median of 25 months since the second BM aspiration (66 months since diagnosis), 32 patients had developed relapse, 12 local and 20 systemic. Of the patients with ITC in BM, 21% relapsed compared with 7% of the ITC-negative patients (P < 0.001). Ten patients died of breast cancer. Survival analyses showed that ITC in BM predicted reduced distant disease-free survival (DDFS) and breast cancer specific survival (BCSS; P < 0.001, log-rank test). Uni-and multivariate analyses of the prognostic value of N, T, estrogen receptor/progesterone receptor, and BM status, histological grade, vascular invasion, p53-, c-erb-B2-, and cathepsin D expression were performed. BM status was the only independent prognostic factor for both DDFS and BCSS, whereas c-erbB-2 and N status were independent for BCSS and vascular invasion and T status for DDFS.Conclusions: ITC in BM 3 years after diagnosis in disease-free breast cancer patients is an independent prognostic factor. Detection of residual disease by BM analysis at follow-up may unravel insufficient adjuvant treatment. The clinical implications should be further explored.