Research Papers:

In-depth characterization of breast cancer tumor-promoting cell transcriptome by RNA sequencing and microarrays

Maurizio Callari, Alessandro Guffanti, Giulia Soldà, Giuseppe Merlino, Emanuela Fina, Elena Brini, Anna Moles, Vera Cappelletti _ and Maria Grazia Daidone

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Oncotarget. 2016; 7:976-994. https://doi.org/10.18632/oncotarget.5810

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Maurizio Callari1,*, Alessandro Guffanti2,*, Giulia Soldà3,4, Giuseppe Merlino1, Emanuela Fina1, Elena Brini2, Anna Moles2, Vera Cappelletti1, Maria Grazia Daidone1

1Department of Experimental Oncology and Molecular Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

2Genomnia Srl, Lainate, Milan, Italy

3Department of Biomedical Sciences, Humanitas University, Rozzano, Milan, Italy

4Humanitas Clinical and Research Center, Rozzano, Milan, Italy

*These authors have contributed equally to this work

Correspondence to:

Vera Cappelletti, e-mail: [email protected]

Keywords: tumor-promoting cells, breast cancer, gene expression, ncRNAs, cancer stem cells

Received: February 25, 2015     Accepted: October 22, 2015     Published: November 03, 2015


Numerous studies have reported the existence of tumor-promoting cells (TPC) with self-renewal potential and a relevant role in drug resistance. However, pathways and modifications involved in the maintenance of such tumor subpopulations are still only partially understood. Sequencing-based approaches offer the opportunity for a detailed study of TPC including their transcriptome modulation. Using microarrays and RNA sequencing approaches, we compared the transcriptional profiles of parental MCF7 breast cancer cells with MCF7-derived TPC (i.e. MCFS). Data were explored using different bioinformatic approaches, and major findings were experimentally validated. The different analytical pipelines (Lifescope and Cufflinks based) yielded similar although not identical results. RNA sequencing data partially overlapped microarray results and displayed a higher dynamic range, although overall the two approaches concordantly predicted pathway modifications. Several biological functions were altered in TPC, ranging from production of inflammatory cytokines (i.e., IL-8 and MCP-1) to proliferation and response to steroid hormones. More than 300 non-coding RNAs were defined as differentially expressed, and 2,471 potential splicing events were identified. A consensus signature of genes up-regulated in TPC was derived and was found to be significantly associated with insensitivity to fulvestrant in a public breast cancer patient dataset. Overall, we obtained a detailed portrait of the transcriptome of a breast cancer TPC line, highlighted the role of non-coding RNAs and differential splicing, and identified a gene signature with a potential as a context-specific biomarker in patients receiving endocrine treatment.

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