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Identification and validation of genes with expression patterns inverse to multiple metastasis suppressor genes in breast cancer cell lines

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Abstract

Metastasis suppressor genes (MSGs) have contributed to an understanding of regulatory pathways unique to the lethal metastatic process. When re-expressed in experimental models, MSGs block cancer spread to, and colonization of distant sites without affecting primary tumor formation. Genes have been identified with expression patterns inverse to a single MSG, and found to encode functional, druggable signaling pathways. We now hypothesize that common signaling pathways mediate the effects of multiple MSGs. By gene expression profiling of human MCF7 breast carcinoma cells expressing a scrambled siRNA, or siRNAs to each of 19 validated MSGs (NME1, BRMS1, CD82, CDH1, CDH2, CDH11, CASP8, MAP2K4, MAP2K6, MAP2K7, MAPK14, GSN, ARHGDIB, AKAP12, DRG1, CD44, PEBP1, RRM1, KISS1), we identified genes whose expression was significantly opposite to at least five MSGs. Five genes were selected for further analysis: PDE5A, UGT1A, IL11RA, DNM3 and OAS1. After stable downregulation of each candidate gene in the aggressive human breast cancer cell line MDA-MB-231T, in vitro motility was significantly inhibited. Two stable clones downregulating PDE5A (phosphodiesterase 5A), an enzyme involved in the regulation of cGMP-specific signaling, exhibited no difference in cell proliferation, but reduced motility by 47 and 66 % compared to the empty vector-expressing cells (p = 0.01 and p = 0.005). In an experimental metastasis assay, two shPDE5A-MDA-MB-231T clones produced 47–62 % fewer lung metastases than shRNA-scramble expressing cells (p = 0.045 and p = 0.009 respectively). This study demonstrates that previously unrecognized genes are inversely related to the expression of multiple MSGs, contribute to aspects of metastasis, and may stand as novel therapeutic targets.

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Abbreviations

MSGs:

Metastasis suppressor genes

PDE5A:

Phosphodiesterase 5A

UGT1A:

UPD-glucoronosyltransferase 1 A family

H&E:

Hematoxylin and eosin

IL11RA:

Interleukin-11 receptor alpha

DNM3:

Dynamin-3

OAS1:

2′-5′-Oligoadenylate synthetase-1

FBS:

Fetal bovine serum

siRNA:

Small interfering RNA

shRNA:

Small hairpin RNA

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Acknowledgments

This work was supported by the Intramural program of the National Cancer Institute and Breast Cancer Research Stamp Fund awarded through competitive peer review by National Cancer Institute (to PSS). The authors would like to acknowledge Manjula Kasoji and Dr Fathi Elloumi of the CCRIFX Bioinformatics Core operated by Leidos Biomedical Research, Inc and funded by the NCI Center for Cancer Research for their contributions to the bioinformatics analysis.

Conflict of interest

The authors declare that they have no conflicts of interest.

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Author notes

  1. George W. Sledge Jr

    Present address: Stanford University School of Medicine, Palo Alto, CA, USA

Authors and Affiliations

  1. Women’s Malignancies Branch, Center for Cancer Research, National Cancer Institute, Building 37/Room 1126, 37 Convent Drive, Bethesda, MD, 20892, USA

    Natascia Marino, Joshua W. Collins & Patricia S. Steeg

  2. Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA

    Changyu Shen

  3. Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA

    Natasha J. Caplen

  4. CCRIFX Bioinformatics Core, Advanced Biomedical Computing Center, Leidos Biomed, Frederick, MD, USA

    Anand S. Merchant

  5. Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

    Yesim Gökmen-Polar

  6. Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA

    Chirayu P. Goswami

  7. Takeda Pharmaceutical Company Ltd, Tsukuba, Japan

    Takashi Hoshino

  8. Laboratory Animal Sciences Program, SAIC-Frederick, National Cancer Institute, Frederick, MD, USA

    Yongzhen Qian

  9. Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

    George W. Sledge Jr

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  1. Natascia Marino
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Marino, N., Collins, J.W., Shen, C. et al. Identification and validation of genes with expression patterns inverse to multiple metastasis suppressor genes in breast cancer cell lines. Clin Exp Metastasis 31, 771–786 (2014). https://doi.org/10.1007/s10585-014-9667-0

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