The mammalian target of rapamycin (mTOR) kinase is a master regulator of protein synthesis that couples nutrient sensing to cell growth and cancer. However, the downstream translationally regulated nodes of gene expression that may direct cancer development are poorly characterized. Using ribosome profiling, we uncover specialized translation of the prostate cancer genome by oncogenic mTOR signalling, revealing a remarkably specific repertoire of genes involved in cell proliferation, metabolism and invasion. We extend these findings by functionally characterizing a class of translationally controlled pro-invasion messenger RNAs that we show direct prostate cancer invasion and metastasis downstream of oncogenic mTOR signalling. Furthermore, we develop a clinically relevant ATP site inhibitor of mTOR, INK128, which reprograms this gene expression signature with therapeutic benefit for prostate cancer metastasis, for which there is presently no cure. Together, these findings extend our understanding of how the ‘cancerous’ translation machinery steers specific cancer cell behaviours, including metastasis, and may be therapeutically targeted.

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Despite the fluid and nonlinear nature of data analysis, specifically in qualitative research, published work in comparative education has rarely discussed the messy aspects of data analysis. This Forum addresses the complexity of the analysis stage faced by three doctoral researchers in terms of: considering data analysis when selecting data collection tools; messiness of data analysis deriving from fieldwork and data collection; integrating different data sources; practising reflexivity during data analysis; and ethical issues arising from data analysis. The Forum aims not only to offer suggestions and tips to deal with data analysis but also to encourage more open discussions on this topic within the research community.

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