Estrogen drives key transcriptional changes in breast cancer and stimulates breast cancer cells' growth with multiple mechanisms to coordinate transcription and translation. In addition to protein-coding transcripts, estrogen can regulate long non-coding RNA (lncRNA) transcripts, plus diverse non-coding RNAs including antisense, enhancer, and intergenic. LncRNA genes comprise the majority of human genes. The accidental, or regulated, translation of their short open reading frames by ribosomes remains a controversial topic. Here we report for the first time an integrated analysis of RNA abundance and ribosome occupancy level, using Ribo-seq combined with RNA-Seq, in the estrogen-responsive, estrogen receptor α positive, human breast cancer cell model MCF7, before and after hormone treatment. Translational profiling can determine, in an unbiased manner, which fraction of the genome is actually translated into proteins, as well as resolving whether transcription and translation respond concurrently, or differentially, to estrogen treatment. Our data showed specific transcripts more robustly detected in RNA-Seq than in the ribosome-profiling data, and vice versa, suggesting distinct gene-specific estrogen responses at the transcriptional and the translational level, respectively. Here, we showed that estrogen stimulation affects the expression levels of numerous lncRNAs, but not their association with ribosomes, and that most lncRNAs are not ribosome-bound. For the first time, we also demonstrated the transcriptional and translational response of expressed pseudogenes to estrogen, pointing to new perspectives for drug-target development in breast cancer in the future.
Keywords: Breast cancer; Estrogen; Long non-coding RNA (lncRNA); Pseudogenes; RNA-Seq; Ribo-Seq.
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