A gene expression-based classifier for HER2-low breast cancer.

In clinical trials evaluating antibody-conjugated drugs (ADCs), HER2-low breast cancer is defined through protein immunohistochemistry scoring (IHC) 1+ or 2+ without gene amplification. However, in daily practice, the accuracy of IHC is compromised by inter-observer variability. Herein, we aimed to identify HER2-low breast cancer primary tumors by leveraging gene expression profiling. A discovery approach was applied to gene expression profile of institutional INT1 (n = 125) and INT2 (n = 84) datasets. We identified differentially expressed genes (DEGs) in each specific HER2 IHC category 0, 1+, 2+ and 3+. Principal Component Analysis was used to generate a HER2-low signature whose performance was evaluated in the independent INT3 (n = 95), and in the publicly available TCGA and GSE81538 datasets. The association between the HER2-low signature and HER2 IHC categories was evaluated by Kruskal-Wallis test with post hoc pair-wise comparisons. The HER2-low signature discriminatory capability was assessed by estimating the area under the receiver operating characteristic curve (AUC). Gene Ontology and KEGG analyses were performed to evaluate the HER2-low signature genes functional enrichment. A HER2-low signature was computed based on HER2 IHC category-specific DEGs. The twenty genes included in the signature were significantly enriched with lipid and steroid metabolism pathways, peptidase regulation, and humoral immune response. The HER2-low signature values showed a bell-shaped distribution across IHC categories (low values in 0 and 3+; high values in 1+ and 2+), effectively distinguishing HER2-low from 0 (p < 0.001) to 3+ (p < 0.001). Notably, the signature values were higher in tumors scored with 1+ as compared to 0. The HER2-low signature association with IHC categories and its bell-shaped distribution was confirmed in the independent INT3, TCGA and GSE81538 datasets. In the combined INT1 and INT3 datasets, the HER2-low signature achieved an AUC value of 0.74 (95% confidence interval, CI 0.67-0.81) in distinguishing HER2-low vs. the other categories, outperforming the individual ERBB2 mRNA AUC value of 0.52 (95% CI 0.43-0.60). These results represent a proof-of-concept for an observer-independent gene-expression-based classifier of HER2-low status. The herein identified 20-gene signature shows promise in distinguishing between HER2 0 and HER2-low expressing tumors, including those scored as 1+ at IHC, and in developing a selection approach for ADCs candidates.

Plasma Profile of Immune Determinants Predicts Pathological Complete Response in Locally Advanced Breast Cancer Patients: A Pilot Study.

BACKGROUND: Complex interactions between cancer and the immune system have an impact on disease progression and therapeutic response. Our objective was to evaluate whether circulating immune-related determinants are associated with pathological complete response (pCR) in patients with locally advanced breast cancer (LABC) subjected to neoadjuvant chemotherapy (NACT). PATIENTS AND METHODS: Luminex technology was used to profile 22 cytokines, 10 chemokines, FGF2, PDGF-BB, VEGF, and Ca15-3/Ca125 glycoforms. Measurements were performed alongside standard hematological determinations on pretreatment plasma samples from 151 patients including 41 cases with pCR assessed following RECIST criteria. RESULTS: Random Forest model analysis selected platelets, eotaxin, IFN-γ, IP10, and TGFß2 as significant predictors of pCR. These immune-related features were combined into a quantitative score predictive of pCR. In patients who scored 0 or 1, none had pCR; the pCR frequency increased in relation to the score value (23.5%, 41.2%, and 78.6%, in score groups 2, 3, and 4, respectively). At multivariable logistic analysis, the pCR score was highly significant (odds ratio = 3.15 per unit increment; CI: 1.85-5.38; P < .0001); among clinical covariates (age, menopausal status, tumor stage, IHC subtype, Ki-67, CA15.3, and CA125), only Ki-67 was statistically significant (P = .013). CONCLUSION: This explorative study aimed to lay the conceptual and practical foundation that a distinctive pattern of the immune determinant blood signature at diagnosis of LABC significantly correlates with the patient's response to NACT and provides the groundwork for larger studies that could lead to a minimally invasive tool for personalized medicine.

Prediagnostic Levels of Copper and Zinc and Breast Cancer Risk in the ORDET Cohort.

BACKGROUND: Case-control studies show that copper (Cu) is high and zinc (Zn) low in blood and urine of women with breast cancer compared with controls. METHODS: To assess whether prediagnostic Cu and Zn are associated with breast cancer risk, OR of breast cancer according to Cu, Zn, and Cu/Zn ratio in plasma and urine was estimated in a nested case-control study within the ORDET cohort, using conditional logistic regression adjusted for multiple variables: First 496 breast cancer cases and matched controls, diagnosed ≥2 years after recruitment (to eliminate reverse causation) were analyzed. Then all eligible cases/controls were analyzed with stratification into years from recruitment to diagnosis. RESULTS: For women diagnosed ≥2 years, compared with lowest tertiles, breast cancer risk was higher in the highest tertile of plasma Cu/Zn ratio (OR, 1.75; 95% CI, 1.21-2.54) and the highest tertile of both plasma and urine Cu/Zn ratio (OR, 2.37; 95% CI, 1.32-4.25). Risk did not vary with ER/PR/HER2 status. For women diagnosed <2 years, high Cu/Zn ratio was strongly associated with breast cancer risk. CONCLUSIONS: Our prospective findings suggest that increased Cu/Zn ratio in plasma and urine may be both an early marker of, and a risk factor for, breast cancer development. Further studies are justified to confirm or otherwise our results and to investigate mechanisms. IMPACT: Our finding that prediagnostic Cu/Zn ratio is a strong risk factor for breast cancer development deserves further investigation and, if confirmed, might open the way to interventions to reduce breast cancer risk in women with disrupted Cu/Zn homeostasis.

Circulating miRNAs as Novel Non-Invasive Biomarkers to Aid the Early Diagnosis of Suspicious Breast Lesions for Which Biopsy Is Recommended.

In population-based screens, tissue biopsy remains the standard practice for women with imaging that suggests breast cancer. We examined circulating microRNAs as minimally invasive diagnostic biomarkers to discriminate malignant from benign breast lesions. miRNAs were analyzed by OpenArray in a retrospective cohort of plasma samples including 100 patients with malignant (T), 89 benign disease (B), and 99 healthy donors (HD) divided into training and testing sets and a prospective cohort (BABE) of 289 women with suspicious imaging findings who underwent tissue biopsy. miRNAs associated with disease status were identified by univariate analysis and then combined into signatures by multivariate logistic regression models. By combining 16 miRNAs differentially expressed in the T vs. HD comparison, 26 signatures were also able to significantly discriminate T from B disease. Seven of them, involving 5 specific miRNAs (miR-625, miR-423-5p, miR-370-3p, miR-181c, and miR-301b), were statistically validated in the testing set. Among the 7 signatures, the discriminatory performances of 5 were confirmed in the prospective BABE Cohort. This study identified 5 circulating miRNAs that, properly combined, distinguish malignant from benign breast disease in women with a high likelihood of malignancy.

Collagen ultrastructural symmetry and its malignant alterations in human breast cancer revealed by polarization-resolved second-harmonic generation microscopy.

Several specific alterations of the extracellular matrix can be considered a distinctive hallmark of cancer. In particular, a different morphology of the collagen scaffold is frequently found within the peritumoural environment. In this study, we report about a significant difference in the ultrastructural organization of collagen at the supra-molecular level between the perilesional scaffold and the tumour area in human breast carcinoma samples. In particular, we demonstrated that polarization-resolved second-harmonic generation (P-SHG) microscopy is able to link the altered collagen architecture at the ultrastructural level found in perilesional tissue with a different organization of collagen fibrils at the molecular level.

Extracellular Matrix Features Discriminate Aggressive HER2-Positive Breast Cancer Patients Who Benefit from Trastuzumab Treatment.

We previously identified an extracellular matrix (ECM) gene expression pattern in breast cancer (BC), called ECM3, characterized by a high expression of genes encoding structural ECM proteins. Since ECM is reportedly implicated in response to therapy of BCs, the aim of this work is to investigate the prognostic and predictive value of ECM3 molecular classification in HER2-positive BCs. ECM3 resulted in a robust cluster that identified a subset of 25-37% of HER2-positive tumors with molecular aggressive features. ECM3 was significantly associated with worse prognosis in two datasets of HER2-positive BCs untreated with adjuvant therapy. Analyses carried out on two of our cohorts of patients treated or not with adjuvant trastuzumab showed association of ECM3 with worse prognosis only in patients not treated with trastuzumab. Moreover, investigating a dataset that includes gene profile data of tumors treated with neoadjuvant trastuzumab plus chemotherapy or chemotherapy alone, ECM3 was associated with increased pathological complete response if treated with trastuzumab. In the in vivo experiments, increased diffusion and trastuzumab activity were found in tumors derived from injection of HER2-positive cells with Matrigel that creates an ECM-rich tumor environment. Taken together, these results indicate that HER2-positive BCs classified as ECM3 have an aggressive phenotype but they are sensitive to trastuzumab treatment.

MicroRNA co-expression patterns unravel the relevance of extra cellular matrix and immunity in breast cancer.

BACKGROUND: Aberrant microRNA (miRNA) expression is associated with human tumors, including breast cancer (BC), and has diagnostic and therapeutic potential. BC tissue is characterized by distinctive miRNA signatures associated with cancer development or progression. METHODS: We explored miRNA profiles from BC tissues by unsupervised hierarchical clustering. Functional analysis was based on miRNA-mRNA data integration and Gene Set Enrichment Analysis. RESULTS: Partition of miRNA expression data from BC samples of Chinese Han and Caucasian subjects identified clusters of correlated miRNAs that were subjected to a global and integrative analysis aimed at identifying novel associations with biological and clinical value. Co-expression of miRNAs clustered in the same module was partially explained by co-transcription of the same genomic locus or involvement in similar biological functions. No significant associations were found among miRNA clusters and clinical-pathological variables, except for ER status and immune infiltration estimated by CIBERSORT. A large number of miRNA clusters, instead, were significantly differentially expressed in PAM 50 and extracellular matrix (ECM) subgroups. Specifically, a new cluster including several relatively new miRNAs was overexpressed in ECM3 tumors, characterized by increased epithelial to mesenchymal transition (EMT). An integrative approach to extract meaningful relationships on miRNA/mRNA networks and predict the functional role of the miRNA clusters indicates that immune system, ECM, proliferation, transcription and DNA repair were the biological functions more targeted by miRNAs aberrantly expressed in BC. CONCLUSIONS: We then identified novel miRNA patterns associated with BC molecular features, and described a complex regulatory network where miRNAs belonging to the same module cooperate in finely tuning gene expression.

Extracellular matrix proteins as diagnostic markers of breast carcinoma.

Changes in amount and composition of extracellular matrix (ECM) are considered a hallmark of tumor development. We tested the hypothesis that abnormal production of ECM components leads to blood-released ECM molecules representing tumor circulating biomarkers. Candidate genes were selected through class comparison in two publicly available datasets and confirmed in paired normal and tumor associated fibroblasts from breast carcinoma (BC) specimens. Production and release of ECM molecules were evaluated in normal human dermal fibroblasts (NHDFs) treated with conditioned media from three BC cell lines. Plasma samples from healthy donors and from patients with malignant or benign breast disease were tested by ELISA for the presence of collagen 11a1 (COL11A1), collagen oligomeric matrix protein (COMP), and collagen 10a1 (COL10A1). Selected ECM molecules were investigated by IHC in malignant and benign specimens. In silico analysis of gene expression profiles identified 11 ECM genes significantly up-regulated in tumor versus normal tissue. Western blot analyses revealed increased levels of molecules encoded by three of these genes, COL11A1, COMP, and COL10A1, in cell lysates and supernatants of conditioned NHDFs. Class comparison and class prediction analyses of two independent series of human plasma samples identified the combination of COL11A1, COMP, and COL10A1 as potentially informative in discriminating BC patients from those with benign disease. The three molecules resulted expressed in the stroma of BC tissue samples. Our results indicate that circulating COL11A1, COMP, and COL10A1 may be useful in diagnostic assessment of suspicious breast nodules and ECM molecules could represent an avenue to biomarker identification.

Expression of Iron-Related Proteins Differentiate Non-Cancerous and Cancerous Breast Tumors.

We have previously reported hepcidin and ferritin increases in the plasma of breast cancer patients, but not in patients with benign breast disease. We hypothesized that these differences in systemic iron homeostasis may reflect alterations in different iron-related proteins also play a key biochemical and regulatory role in breast cancer. Thus, here we explored the expression of a bundle of molecules involved in both iron homeostasis and tumorigenesis in tissue samples. Enzyme-linked immunosorbent assay (ELISA) or reverse-phase protein array (RPPA), were used to measure the expression of 20 proteins linked to iron processes in 24 non-cancerous, and 56 cancerous, breast tumors. We found that cancerous tissues had higher level of hepcidin than benign lesions (p = 0.012). The univariate analysis of RPPA data highlighted the following seven proteins differentially expressed between non-cancerous and cancerous breast tissue: signal transducer and transcriptional activator 5 (STAT5), signal transducer and activator of transcription 3 (STAT3), bone morphogenetic protein 6 (BMP6), cluster of differentiation 74 (CD74), transferrin receptor (TFRC), inhibin alpha (INHA), and STAT5_pY694. These findings were confirmed for STAT5, STAT3, BMP6, CD74 and INHA when adjusting for age. The multivariate statistical analysis indicated an iron-related 10-protein panel effective in separating non-cancerous from cancerous lesions including STAT5, STAT5_pY694, myeloid differentiation factor 88 (MYD88), CD74, iron exporter ferroportin (FPN), high mobility group box 1 (HMGB1), STAT3_pS727, TFRC, ferritin heavy chain (FTH), and ferritin light chain (FTL). Our results showed an association between some iron-related proteins and the type of tumor tissue, which may provide insight in strategies for using iron chelators to treat breast cancer.

Mesenchymal Transition of High-Grade Breast Carcinomas Depends on Extracellular Matrix Control of Myeloid Suppressor Cell Activity.

The extracellular matrix (ECM) contributes to the biological and clinical heterogeneity of breast cancer, and different prognostic groups can be identified according to specific ECM signatures. In high-grade, but not low-grade, tumors, an ECM signature characterized by high SPARC expression (ECM3) identifies tumors with increased epithelial-to-mesenchymal transition (EMT), reduced treatment response, and poor prognosis. To better understand how this ECM3 signature is contributing to tumorigenesis, we expressed SPARC in isogenic cell lines and found that SPARC overexpression in tumor cells reduces their growth rate and induces EMT. SPARC expression also results in the formation of a highly immunosuppressive microenvironment, composed by infiltrating T regulatory cells, mast cells, and myeloid-derived suppressor cells (MDSCs). The ability of SPARC to induce EMT depended on the localization and suppressive function of myeloid cells, and inhibition of the suppressive function MDSCs by administration of aminobisphosphonates could revert EMT, rendering SPARC-overexpressing tumor cells sensitive to Doxil. We conclude that that SPARC is regulating the interplay between MDSCs and the ECM to drive the induction of EMT in tumor cells.

miR-9 and miR-200 Regulate PDGFRß-Mediated Endothelial Differentiation of Tumor Cells in Triple-Negative Breast Cancer.

Organization of cancer cells into endothelial-like cell-lined structures to support neovascularization and to fuel solid tumors is a hallmark of progression and poor outcome. In triple-negative breast cancer (TNBC), PDGFRß has been identified as a key player of this process and is considered a promising target for breast cancer therapy. Thus, we aimed at investigating the role of miRNAs as a therapeutic approach to inhibit PDGFRß-mediated vasculogenic properties of TNBC, focusing on miR-9 and miR-200. In MDA-MB-231 and MDA-MB-157 TNBC cell lines, miR-9 and miR-200 promoted and inhibited, respectively, the formation of vascular-like structures in vitro Induction of endogenous miR-9 expression, upon ligand-dependent stimulation of PDGFRß signaling, promoted significant vascular sprouting of TNBC cells, in part, by direct repression of STARD13. Conversely, ectopic expression of miR-200 inhibited this sprouting by indirectly reducing the protein levels of PDGFRß through the direct suppression of ZEB1. Notably, in vivo miR-9 inhibition or miR-200c restoration, through either the generation of MDA-MB-231-stable clones or peritumoral delivery in MDA-MB-231 xenografted mice, strongly decreased the number of vascular lacunae. Finally, IHC and immunofluorescence analyses in TNBC specimens indicated that PDGFRß expression marked tumor cells engaged in vascular lacunae. In conclusion, our results demonstrate that miR-9 and miR-200 play opposite roles in the regulation of the vasculogenic ability of TNBC, acting as facilitator and suppressor of PDGFRß, respectively. Moreover, our data support the possibility to therapeutically exploit miR-9 and miR-200 to inhibit the process of vascular lacunae formation in TNBC. Cancer Res; 76(18); 5562-72. ©2016 AACR.

Noninvasive strategies for breast cancer early detection.

Breast cancer screening and presurgical diagnosis are currently based on mammography, ultrasound and more sensitive imaging technologies; however, noninvasive biomarkers represent both a challenge and an opportunity for early detection of cancer. An extensive number of potential breast cancer biomarkers have been discovered by microarray hybridization or sequencing of circulating DNA, noncoding RNA and blood cell RNA; multiplex analysis of immune-related molecules and mass spectrometry-based approaches for high-throughput detection of protein, endogenous peptides, circulating and volatile metabolites. However, their medical relevance and their translation to clinics remain to be exploited. Once they will be fully validated, cancer biomarkers, used in combination with the current and emerging imaging technologies, represent an avenue to a personalized breast cancer diagnosis.

Plasma hepcidin in early-stage breast cancer patients: no relationship with interleukin-6, erythropoietin and erythroferrone.

OBJECTIVE: Hepcidin-25 production is stimulated by systemic inflammation, and it interferes with iron utilization, leading to anemia. This study aimed to investigate the relationships between the plasma levels of hepcidin, interleukin-6 (IL-6), erythropoietin (EPO) and erythroferrone (ERFE) in patients with benign breast disease or cancer. METHODS: Plasma samples from a cohort of 131 patients (47 with benign breast disease and 84 with breast cancer) were subjected to the evaluation of hepcidin, IL-6, EPO and ERFE using SELDI-TOF-MS or immunoassays. RESULTS: An elevated hepcidin was observed in malignant breast tumors compared to benign ones. No correlation was observed between hepcidin and IL-6, EPO or ERFE. CONCLUSION: Since the study included a cohort of patients (87%) with breast cancers smaller than 2 cm, these results may support our previous evidence about the potential role of hepcidin in breast cancer disease.

Secondary electrospray ionization-mass spectrometry and a novel statistical bioinformatic approach identifies a cancer-related profile in exhaled breath of breast cancer patients: a pilot study.

Breath analysis represents a new frontier in medical diagnosis and a powerful tool for cancer biomarker discovery due to the recent development of analytical platforms for the detection and identification of human exhaled volatile compounds. Statistical and bioinformatic tools may represent an effective complement to the technical and instrumental enhancements needed to fully exploit clinical applications of breath analysis. Our exploratory study in a cohort of 14 breast cancer patients and 11 healthy volunteers used secondary electrospray ionization-mass spectrometry (SESI-MS) to detect a cancer-related volatile profile. SESI-MS full-scan spectra were acquired in a range of 40-350 mass-to-charge ratio (m/z), converted to matrix data and analyzed using a procedure integrating data pre-processing for quality control, and a two-step class prediction based on machine-learning techniques, including a robust feature selection, and a classifier development with internal validation. MS spectra from exhaled breath showed an individual-specific breath profile and high reciprocal homogeneity among samples, with strong agreement among technical replicates, suggesting a robust responsiveness of SESI-MS. Supervised analysis of breath data identified a support vector machine (SVM) model including 8 features corresponding to m/z 106, 126, 147, 78, 148, 52, 128, 315 and able to discriminate exhaled breath from breast cancer patients from that of healthy individuals, with sensitivity and specificity above 0.9.Our data highlight the significance of SESI-MS as an analytical technique for clinical studies of breath analysis and provide evidence that our noninvasive strategy detects volatile signatures that may support existing technologies to diagnose breast cancer.

Molecular portrait of breast cancer in China reveals comprehensive transcriptomic likeness to Caucasian breast cancer and low prevalence of luminal A subtype.

The recent dramatic increase in breast cancer incidence across China with progressive urbanization and economic development has signaled the urgent need for molecular and clinical detailing of breast cancer in the Chinese population. Our analyses of a unique transethnic collection of breast cancer frozen specimens from Shanghai Fudan Cancer Center (Chinese Han) profiled simultaneously with an analogous Caucasian Italian series revealed consistent transcriptomic data lacking in batch effects. The prevalence of Luminal A subtype was significantly lower in Chinese series, impacting the overall prevalence of estrogen receptor (ER)-positive disease in a large cohort of Chinese/Caucasian patients. Unsupervised and supervised comparison of gene and microRNA (miRNA) profiles of Chinese and Caucasian samples revealed extensive similarity in the comprehensive taxonomy of transcriptional elements regulating breast cancer biology. Partition of gene expression data using gene lists relevant to breast cancer as "intrinsic" and "extracellular matrix" genes identified Chinese and Caucasian subgroups with equivalent global gene and miRNA profiles. These findings indicate that in the Chinese and Caucasian groups, breast neoplasia and the surrounding stromal characteristics undergo the same differentiation and molecular processes. Transcriptional similarity across transethnic cohorts may simplify translational medicine approaches and clinical management of breast cancer patients worldwide.

Subtype-dependent prognostic relevance of an interferon-induced pathway metagene in node-negative breast cancer.

The majority of gene expression signatures developed to predict the likelihood to relapse in breast cancer (BC) patients assigns a high risk score to patients with Estrogen Receptor (ER) negative or highly proliferating tumors. We aimed to identify a signature of differentially expressed (DE) metagenes, rather than single DE genes, associated with distant metastases beyond classical risk factors. We used 105 gene expression profiles from consecutive BCs to identify metagenes whose prognostic role was defined on an independent series of 92 ESR1+/ERBB2- node-negative BCs (42 cases developing metastases within 5 years from diagnosis and 50 cases metastasis-free for more than 5 years, comparable for age, tumor size, ER status and surgery). Findings were validated on publicly available datasets of 684 node-negative BCs including all the subtypes. Only a metagene containing interferon-induced genes (IFN metagene) proved to be predictive of distant metastasis in our series of patients with ESR1+/ERBB2- tumors (P = 0.029), and such a finding was validated on 457 ESR1+/ERBB2- BCs from public datasets (P = 0.0424). Conversely, the IFN metagene was associated with a low risk of metastasis in 104 ERBB2+ tumors (P = 0.0099) whereas it did not prove to significantly affect prognosis in 123 ESR1-/ERBB2- tumors (P = 0.2235). A complex prognostic interaction was revealed in ESR1+/ERBB2- and ERBB2+ tumors when the association between the IFN metagene and a T-cell metagene was considered. The study confirms the importance of analyzing prognostic variables separately within BC subtypes, highlights the advantages of using metagenes rather than genes, and finally identifies in node-negative ESR1+/ERBB2- BCs, the unfavorable role of high IFN metagene expression.

Down-modulation of SEL1L, an unfolded protein response and endoplasmic reticulum-associated degradation protein, sensitizes glioma stem cells to the cytotoxic effect of valproic acid.

Valproic acid (VPA), an histone deacetylase inhibitor, is emerging as a promising therapeutic agent for the treatments of gliomas by virtue of its ability to reactivate the expression of epigenetically silenced genes. VPA induces the unfolded protein response (UPR), an adaptive pathway displaying a dichotomic yin yang characteristic; it initially contributes in safeguarding the malignant cell survival, whereas long-lasting activation favors a proapoptotic response. By triggering UPR, VPA might tip the balance between cellular adaptation and programmed cell death via the deregulation of protein homeostasis and induction of proteotoxicity. Here we aimed to investigate the impact of proteostasis on glioma stem cells (GSC) using VPA treatment combined with subversion of SEL1L, a crucial protein involved in homeostatic pathways, cancer aggressiveness, and stem cell state maintenance. We investigated the global expression of GSC lines untreated and treated with VPA, SEL1L interference, and GSC line response to VPA treatment by analyzing cell viability via MTT assay, neurosphere formation, and endoplasmic reticulum stress/UPR-responsive proteins. Moreover, SEL1L immunohistochemistry was performed on primary glial tumors. The results show that (i) VPA affects GSC lines viability and anchorage-dependent growth by inducing differentiative programs and cell cycle progression, (ii) SEL1L down-modulation synergy enhances VPA cytotoxic effects by influencing GSCs proliferation and self-renewal properties, and (iii) SEL1L expression is indicative of glioma proliferation rate, malignancy, and endoplasmic reticulum stress statuses. Targeting the proteostasis network in association to VPA treatment may provide an alternative approach to deplete GSC and improve glioma treatments.

Neoplastic and stromal cells contribute to an extracellular matrix gene expression profile defining a breast cancer subtype likely to progress.

We recently showed that differential expression of extracellular matrix (ECM) genes delineates four subgroups of breast carcinomas (ECM1, -2, -3- and -4) with different clinical outcome. To further investigate the characteristics of ECM signature and its impact on tumor progression, we conducted unsupervised clustering analyses in 6 additional independent datasets of invasive breast tumors from different platforms for a total of 643 samples. Use of four different clustering algorithms identified ECM3 tumors as an independent group in all datasets tested. ECM3 showed a homogeneous gene pattern, consisting of 58 genes encoding 43 structural ECM proteins. From 26 to 41% of the cases were ECM3-enriched, and analysis of datasets relevant to gene expression in neoplastic or corresponding stromal cells showed that both stromal and breast carcinoma cells can coordinately express ECM3 genes. In in vitro experiments, ß-estradiol induced ECM3 gene production in ER-positive breast carcinoma cell lines, whereas TGFß induced upregulation of the genes leading to ECM3 gene classification, especially in ER-negative breast carcinoma cells and in fibroblasts. Multivariate analysis of distant metastasis-free survival in untreated breast tumor patients revealed a significant interaction between ECM3 and histological grade (p = 0.001). Cox models, estimated separately in grade I-II and grade III tumors, indicated a highly significant association between ECM3 and worse survival probability only in grade III tumors (HR = 3.0, 95% CI = 1.3-7.0, p = 0.0098). Gene Set Enrichment analysis of ECM3 compared to non-ECM3 tumors revealed significant enrichment of epithelial-mesenchymal transition (EMT) genes in both grade I-II and grade III subsets of ECM3 tumors. Thus, ECM3 is a robust cluster that identifies breast carcinomas with EMT features but with accelerated metastatic potential only in the undifferentiated (grade III) phenotype. These findings support the key relevance of neoplastic and stroma interaction in breast cancer progression.

Tumor suppressor genes are frequently methylated in lymph node metastases of breast cancers.

INTRODUCTION: Metastasis represents a major adverse step in the progression of breast carcinoma. Lymph node invasion is the most relevant prognostic factor; however little is known on the molecular events associated with lymph node metastasis process. This study is to investigate the status and role of methylation in lymph node metastatic tumors. MATERIALS AND METHODS: Bisulfite pyrosequencing is used to screen 6 putative tumor suppressor genes (HIN-1, RASSF1A, RIL, CDH13, RARbeta2 and E-cadherin) in 38 pairs of primary breast tumors and lymph node metastases. RESULTS: We found that HIN-1, CDH13, RIL, RASSF1A and RARbeta2 were frequently methylated both in primary and metastatic tissues (range: 55.3% approximately 89.5%). E-cadherin was not frequently methylated in either setting (range: 18.4% approximately 23.7%). The methylation status of HIN-1, CDH13, RIL, and RARbeta2 in lymph nodes metastasis were correlated with that in primary tumors. The Pearson correlation values ranged from 0.624 to 0.472 (p values < 0.01 to 0.001). Interestingly, we observed an association between HIN-1 methylation and hormone status in metastatic lymph nodes. Hypermethylation of HIN-1 in metastasis lymph nodes was significantly associated with expression of ER (odds ratio, 1.070; P = 0.024) and with PR (odds ratio, 1.046; P = 0.026). CONCLUSIONS: This study suggests that hypermethylation of tumor suppressor genes is extended from primary to metastatic tumors during tumor progression.