Dataset Information

Exon-based clustering of tumor transcriptomes reveals alternative exons associated with metastasis in breast cancer

ABSTRACT: Exonic profiling is an emerging topic in disease-associated transcriptome analysis, but is still facing major limitations. In this study, we performed a microarray-based analysis of the transcriptome at the exon level of mouse primary mammary tumors having different abilities to give rise to metastases. First, we developed a bioinformatics platform and used a stringent algorithm to identify 679 genes with differentially expressed exons in primary tumors of the 4T1 mouse model of mammary tumor progression. We tested 152 alternative exons by RT-PCR and validated 97 of them as being differentially expressed across primary tumors with different metastasis capability. Many of the 679 identified genes are involved in cellular morphology and movement. This analysis not only pointed to genes involved in cellular functions relevant to tumor progression, but also hinted to protein features targeted by variations at the exon level. Second, we developed a novel exon-based clustering analysis of tumor transcriptomes and identified alternative exons associated with the ability of cells to disseminate from primary mammary tumors into the lungs. A large set of these alternatively spliced exons was differentially expressed across normal tissues and/or conserved during evolution. These data indicated that the splicing events identified by comparing primary tumors were not aberrant events. Finally, we demonstrated that a set of differentially expressed variants, which we identified in the murine model, were associated with poor prognosis in a large cohort of breast cancer patients. In conclusion, this approach constitutes a valuable resource for both the understanding and the development of prognosis/diagnosis markers of tumor metastatic potential. Overall design: 12 Total samples were analyzed: 3 x 67NR primary tumors; 3 x 168FARN primary tumors; 3 x 4T07 primary tumors; 3 x 4T1 primary tumors;

INSTRUMENT(S): [MoEx-1_0-st] Affymetrix Mouse Exon 1.0 ST Array [probe set (exon) version]

SUBMITTER: didier auboeuf

PROVIDER: GSE19086 | GEO | 2009-11-19

SECONDARY ACCESSION(S): PRJNA120501

REPOSITORIES: GEO

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Exon-based clustering of murine breast tumor transcriptomes reveals alternative exons whose expression is associated with metastasis.

Dutertre Martin M Lacroix-Triki Magali M Driouch Keltouma K de la Grange Pierre P Gratadou Lise L Beck Samantha S Millevoi Stefania S Tazi Jamal J Lidereau Rosette R Vagner Stephan S Auboeuf Didier D

Cancer research 20100126 3

In the field of bioinformatics, exon profiling is a developing area of disease-associated transcriptome analysis. In this study, we performed a microarray-based transcriptome analysis at the single exon level in mouse 4T1 primary mammary tumors with different metastatic capabilities. A novel bioinformatics platform was developed that identified 679 genes with differentially expressed exons in 4T1 tumors, many of which were involved in cell morphology and movement. Of 152 alternative exons tested ...[more]

PMID: 20103641

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Project description:BACKGROUND: Breast cancer is the second most frequent type of cancer affecting women. We are increasingly aware that changes in mRNA splicing are associated with various characteristics of cancer. The most deadly aspect of cancer is metastasis, the process by which cancer spreads from the primary tumor to distant organs. However, little is known specifically about the involvement of alternative splicing in the formation of macroscopic metastases. Our study investigates transcript isoform changes that characterize tumors of different abilities to form growing metastases. METHODS AND FINDINGS: To identify alternative splicing events (ASEs) that are associated with the fully metastatic phenotype in breast cancer, we used Affymetrix Exon Microarrays to profile mRNA isoform variations genome-wide in weakly metastatic (168FARN and 4T07) and highly metastatic (4T1) mammary carcinomas. Statistical analysis identified significant expression changes in 7606 out of 155,994 (4%) exons and in 1725 out of 189,460 (1%) intronic regions, which affect 2623 out of 16,654 (16%) genes. These changes correspond to putative alternative isoforms-several of which are novel-that are differentially expressed between tumors of varying metastatic phenotypes. Gene pathway analysis showed that 1224 of genes expressing alternative isoforms were involved in cell growth, cell interactions, cell proliferation, cell migration and cell death and have been previously linked to cancers and genetic disorders. We chose ten predicted splice variants for RT-PCR validation, eight of which were successfully confirmed (MED24, MFI2, SRRT, CD44, CLK1 and HNRNPH1). These include three novel intron retentions in CD44, a gene in which isoform variations have been previously associated with the metastasis of several cancers. CONCLUSION: Our findings reveal that various genes are differently spliced and/or expressed in association with the metastatic phenotype of tumor cells. Identification of metastasis-specific isoforms may contribute to the development of improved breast cancer stage identification and targeted therapies. Overall design: We used RNA tumor tissues derived from three murine mammary carcinoma cell lines (168FARN, 4T07 and 4T1); four biological replicates of 168FARN, four biological replicates of 4T07, and four biological replicates of 4T1 were hybridized independently at McGill university site.

Project description:The present study was designed to identify genes induced by irradiation in the 4T1 breast cancer model mimicking aggressive local relapse after radiotherapy. For this purpose, we obtained the transcriptomes of 4T1 tumors grown in either preirradiated (IRR+4T1) or non-irradiated (4T1) mammary tissue. Overall design: Primary tumors were initiated by orthotopic injection of 4T1 (ATCC; CRL-2539) mammary carcinoma cells into BALB/c mice (Charles River Laboratories) as described (1). To investigate the effect of mammary tissue irradiation on gene expression, the fourth mammary gland was either pretreated with a single dose of 20 Gy X-ray irradiation or left untreated before implanting 4T1 tumor cells (1, 2). Tumor tissue samples were collected, flash-frozen and homogenized in RLT buffer using a Dispomix Drive (Medic Tools). Total RNA was isolated using the RNeasy Mini Kit (Qiagen), converted into labeled cDNA and hybridized to Affymetrix GeneChip Mouse Gene 1.0 ST arrays. RMA-normalized expression values were calculated with the affy package from Bioconductor 2.4 (3), and differentially expressed genes were identified using moderated t-statistics calculated with the empirical Bayes method as implemented in the Bioconductor limma package (4). To be considered as differentially expressed between tumors grown in preirradiated (IRR+4T1) and nonirradiated (4T1) mammary tissue, genes had to pass the filters: P-value ≤ 0.05, a log2 fold change ≥ 0.4 and a log2 average expression value ≥ 4.0. References: 1. Kuonen F, Laurent J, Secondini C, Lorusso G, Stehle JC, Rausch T, et al. Inhibition of the Kit ligand/c-Kit axis attenuates metastasis in a mouse model mimicking local breast cancer relapse after radiotherapy. Clin Cancer Res 2012;18:4365-74. 2. Monnier Y, Farmer P, Bieler G, Imaizumi N, Sengstag T, Alghisi GC, et al. CYR61 and αVβ5 integrin cooperate to promote invasion and metastasis of tumors growing in preirradiated stroma. Cancer Res 2008;68:7323-31. 3. Gentleman R, Carey V, Bates D, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 2004;5:R80. 4. Smyth GK, Speed T. Normalization of cDNA microarray data. Methods 2003;31:265-73.

Project description:Background:Breast cancer is the second most frequent type of cancer affecting women. We are increasingly aware that changes in mRNA splicing are associated with various characteristics of cancer. The most deadly aspect of cancer is metastasis, the process by which cancer spreads from the primary tumor to distant organs. However, little is known specifically about the involvement of alternative splicing in the formation of macroscopic metastases. Our study investigates transcript isoform changes that characterize tumors of different abilities to form growing metastases. Results:To identify alternative splicing events (ASEs) that are associated with the fully metastatic phenotype in breast cancer, we used Affymetrix Exon Microarrays to profile mRNA isoform variations genome-wide in weakly metastatic (168FARN and 4T07) and highly metastatic (4T1) mammary carcinomas. Statistical analysis identified significant expression changes in 7606 out of 155,994 (4%) exons and in 1725 out of 189,460 (1%) intronic regions, which affect 2623 out of 16,654 (16%) genes. These changes correspond to putative alternative isoforms - several of which are novel - that are differentially expressed between tumors of varying metastatic phenotypes. Gene pathway analysis showed that 1224 of genes expressing alternative isoforms were involved in cell growth, cell interactions, cell proliferation, cell migration and cell death and have been previously linked to cancers and genetic disorders. We chose ten predicted splice variants for RT-PCR validation, eight of which were successfully confirmed (MED24, MFI2, SRRT, CD44, CLK1 and HNRNPH1). These include three novel intron retentions in CD44, a gene in which isoform variations have been previously associated with the metastasis of several cancers. Conclusions:Our findings reveal that various genes are differently spliced and/or expressed in association with the metastatic phenotype of tumor cells. Identification of metastasis-specific isoforms may contribute to the development of improved breast cancer stage identification and targeted therapies. Keywords: Seek pre-mRNA changes associated with the fully metastatic phenotype in breast cancer We used RNA tumor tissues derived from three murine mammary carcinoma cell lines (168FARN, 4T07 and 4T1); four biological replicates of 168FARN, four biological replicates of 4T07, and four biological replicates of 4T1 were hybridized independently at McGill university site.