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Profiling protease and protease inhibitor gene expression in tumors and their microenvironment

ABSTRACT: To assist in the identification of proteases, their endogenous inhibitors, and proteins that interact with proteases or proteolytic pathways in biological tissues, a dual species oligonucleotide microarray has been developed in conjunction with Affymetrix, Inc. To investigate the performance of the array, gene expression profiles were analyzed in pure mouse and human samples and orthotopically implanted xenografts of human A549 lung and MDA-MB-231 breast carcinomas. The Hu/Mu ProtIn array is a valuable discovery tool for the identification of components of human and murine proteolytic pathways in health and disease, and has particular utility in the determination of cellular origins of proteases and protease inhibitors in xenograft models of human cancer. Keywords: gene expression profiles were analyzed in pure mouse and human samples and orthotopically implanted xenografts of human A549 lung and MDA-MB-231 breast carcinomas Commercial pan human and mouse total RNA replicate samples (n=3) were profiled. In addition, human ductal stage II or III breast carcinoma biopsies (n=18) were compared to normal human breast biopsies (n=13). Spontaneous spontaneous murine mammary carcinomas from MMTV-PyMT+(FVB/n) (n=8) and MMTV-PyMT+/uPARAP-/-(FVB/n) (n=2) transgenic mice were compared to normal mouse mammary fat pads (n=4; female Rag-1 tm1Mom retired breeders at >6 weeks post lactation). In vitro cultures of MDA-MB-231 human breast carcinoma cells (n=3) and MDA-MB-231 orthotopic xenografts (n=3) were profiled. The xenografts were compared to normal mammary fat pads. A549 human lung adenocarcinoma cells (n=2), A549 orthotopic xenografts (n=3) and normal mouse lung tissue (n = 3) were profiled.

ORGANISM(S): Homo sapiens

SUBMITTER: Moin Kami

PROVIDER: S-ECPF-GEOD-6413 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Background: Breast cancer is a complex disease, encompassed by different clinically and molecularly stratified entities. In 2000, Perou and colleagues demonstrated that tumor phenotypic diversity correlates with differences in global gene expression patterns, which in turn reflect aspects of the biological behavior of the tumors. Gene expression profiling has distinguished sporadic breast tumor sub-classes with genetic, histopathological and clinical differences, however, little is known about the molecular classification of hereditary breast tumors. It has been recently suggested that most tumors arising in BRCA1 mutation carriers display a basal-like phenotype, with the percentages reported in different studies ranging from 44 to almost 100%. In the present study we used expression profiling to produce a molecular classification of BRCA1-associated breast tumors and applied an integrative approach to examine biological dependencies or differences. Methods and Findings: We used frozen tumor tissue from fourteen patients all of which harbored germline pathological mutations in BRCA1. Total RNA extraction, amplification and labeling with Cy5 were performed using standard protocols. Universal Human Reference RNA (Stratagene) was used as a reference and labeled with Cy3. Each pair of Cy3/Cy5 samples was hybridized onto the CNIO human OncoChip V2, which consists of a spotted microarray with 11,675 cDNA clones from the I.M.A.G.E. Consortium. Two channel ratios (Cy5/Cy3) for each spot were generated and quantified using GenePix Pro 5.1 (Axon Instruments, Inc., Union City, CA, USA). Data were normalized and filtered and multiple statistical analyses were performed. The data are deposited in the GEO database under the accession number GSE12350. A tissue microarray (TMA) containing an independent series of 15 BRCA1 tumors was used to validate some of the results obtained. We have described molecular signatures that define BRCA1 subclasses depending on the expression of the gene encoding for Estrogen Receptor, ESR1. Signatures were found to be molecularly associated with different biological processes and transcriptional regulatory programs. The signature of ESR1-positive tumors was mainly linked to cell proliferation-related processes and, therefore, regulated by the estrogen receptor, while the signature of ESR1-negative tumors was mainly linked to the immune response and possibly regulated by transcription factors of the REL/NFκB family. These signatures were then verified in an independent series of hereditary and sporadic breast tumors, which revealed a possible prognostic value for each subclass. Over-expression of immune response genes appears to be a common feature of ER-negative sporadic and hereditary breast cancer and is associated with good prognosis. Interestingly, the ESR1-negative tumors were sub-stratified into two groups presenting light differences in the magnitude of the expression of immune response transcripts and REL/NFκB transcription factors, and this could be dependent on the type of germline alteration. In addition, analysis of the human protein-protein interaction network provides the wiring diagram of critical molecular associations in BRCA1 tumorigenesis and identifies close relationships between the different signatures. Conclusions: In summary, in the present study we have established the gene expression profiling of a series of BRCA1 tumors and found that there is a further degree of heterogeneity beyond the main classification by the expression of ESR1 and the presence or absence of a basal-like phenotype. We have identified specific signatures for ESR1-positive and ESR1-negative BRCA1 tumors, the latter characterized by the enrichment of immune response and cell cycle genes, and have found that slight differences in the level of expression of the immune response stratify the ESR1-negative BRCA1 tumors into two additional sub-groups (A and B) with possible prognostic differences. NFkB could be a major driver responsible for the levels of both immune response and apoptotic genes in this group of tumors, which could in turn be related to the type of germline mutation in BRCA1. This study reveals the molecular complexity of BRCA1 breast tumors, which are found to display similarities to sporadic tumors, and suggests possible prognostic implications. 14 samples (primary breast tumors containing a BRCA1 mutation) were hybridized to a cDNA microarray in order to investigate the possible heterogeneity within the BRCA1 group.

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Profiling protease and protease inhibitor gene expression in tumors and their microenvironment

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