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Biology subjects

Mucci, L.

Publications and source records attributed to Mucci, L..

2 recordsLinked to original sources

Transcriptional landscape of PTEN loss in primary prostate cancer

PTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. Here, we applied a meta-analysis approach, leveraging two large PCa cohorts with experimentally validated PTEN and ERG status, to derive a transcriptomic signature of PTEN loss, while also accounting for potential confounders due to ERG rearrangements. Strikingly, the signature indicates a strong activation of both innate and adaptive immune systems upon PTEN loss, as well as an expected activation of cell-cycle genes. Moreover, we made use of our recently developed FC-R2 expression atlas to expand this signature to include many non-coding RNAs recently annotated by the FANTOM consortium. With this resource, we analyzed the TCGA-PRAD cohort, creating a comprehensive transcriptomic landscape of PTEN loss in PCa that comprises both the coding and an extensive non-coding counterpart.

cancer biology↗

Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration

Transcriptomic deconvolution in cancer and other heterogeneous tissues remains challenging. Available methods lack the ability to estimate both component-specific proportions and expression profiles for individual samples. We present DeMixT, a new tool to deconvolve high dimensional data from mixtures of more than two components. DeMixT implements an iterated conditional mode algorithm and a novel gene-set-based component merging approach to improve accuracy. In a series of experimental validation studies and application to TCGA data, DeMixT showed high accuracy. Improved deconvolution is an important step towards linking tumor transcriptomic data with clinical outcomes. An R package, scripts and data are available: https://github.com/wwylab/DeMixT/.

bioinformatics↗