We have designed a set of oligonucleotide primers to amplify the cDNA of mouse immunoglobulin heavy and light chain variable domains by the polymerase chain reaction. The primers incorporate restriction sites that allow the cDNA of the variable domains to be force-cloned for sequencing and expression. Here we have applied the technique to clone and sequence the variable domains of five hybridoma antibodies and to express a mouse-human chimeric antibody that binds to the human mammary carcinoma line MCF-7. The technique should also lead to the cloning of antigen-binding specificities directly from immunoglobulin genes.

Prediction of the clinical outcome of breast cancer is multi-faceted and challenging. There is growing evidence that the complexity of the tumour micro-environment, consisting of several cell types and a complex mixture of proteins, plays an important role in development, progression, and response to therapy. In the current study, we investigated whether invasive breast tumours can be classified on the basis of the expression of extracellular matrix (ECM) components and whether such classification is representative of different clinical outcomes. We first examined the matrix composition of 28 primary breast carcinomas by morphology and gene expression profiling using 22K oligonucleotide Agilent microarrays. Hierarchical clustering of the gene expression profile of 278 ECM-related genes derived from the literature divided the tumours into four main groups (ECM1-4). A set of selected differentially expressed genes was validated by immunohistochemistry. The robustness of the ECM classification was confirmed by studying the four ECM groups in a previously published gene expression data set of 114 early-stage primary breast carcinomas profiled using cDNA arrays. Univariate survival analysis showed significant differences in clinical outcome among the various ECM subclasses. One set of tumours, designated ECM4, had a favourable outcome and was defined by the overexpression of a set of protease inhibitors belonging to the serpin family, while tumours with an ECM1 signature had a poorer prognosis and showed high expression of integrins and metallopeptidases, and low expression of several laminin chains. Furthermore, we identified three surrogate markers of ECM1 tumours: MARCO, PUNC, and SPARC, whose expression levels were associated with breast cancer survival and risk of recurrence. Our findings suggest that primary breast tumours can be classified based upon ECM composition and that this classification provides relevant information on the biology of breast carcinomas, further supporting the hypothesis that clinical outcome is strongly related to stromal characteristics.

No abstract

Background:We previously selected a panel of 3 breast cancer biomarkers (BC1, BC2, and BC3) from serum samples collected at a single hospital based on their collective contribution to the optimal separation of breast cancer patients and noncancer controls by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The identities and general applicability of these markers, however, were unknown. In this study, we performed protein expression profiling on samples obtained from a second hospital, included a greater number of ductal carcinoma in situ (DCIS) cases, and performed purification and identification of the 2 confirmed markers. Methods: Using a case-control study design, we performed protein expression profiling on serum samples from the National Cancer Institute (Milan, Italy). The validation sample cohort consisted of 61 women with locally invasive breast cancer, 32 with DCIS, 37 with various benign breast diseases (including 13 atypical), and 46 age-matched apparently healthy women (age range, 44 -68 years). Validated biomarkers were purified and identified with serial chromatography, 1-dimensional gel electrophoresis, in-gel ASP-N digestion, peptide mass fingerprinting, and tandem mass peptide sequencing. Results: The BC3 and BC2 expression patterns in this sample set were consistent with the first study sample

Drs. Casali, Colecchia, and Gronchi received research and educational grants, honoraria for lectures and/or participation in educational/scientific projects, and travel coverage for medical meetings from Novartis Pharma.Drs. Messina and Grosso received honoraria for lectures and/or participation in educational/scientific projects and travel coverage for medical meetings from Novartis Pharma.Drs. Tamborini and Bertulli received travel coverage for medical meetings from Novartis Pharma.Drs. Ripamonti and Pilotti received research/educational grants from Novartis Pharma.Raffaello Bertieri is employed by Novartis in the division of Clinical Development, Oncology Department.

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.

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), PDGFRb 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 PDGFRb-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 PDGFRb 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 PDGFRb 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 PDGFRb 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 PDGFRb, 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. Ó2016 AACR.

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, β-estradiol induced ECM3 gene production in ER-positive breast carcinoma cell lines, whereas TGFβ 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.