Comparative Proteomic and Transcriptomic Analysis of the Impact of Androgen Stimulation and Darolutamide Inhibition.
Ekaterina NevedomskayaTatsuo SugawaraSimon J BaumgartRalf LescheHannes HahneDominik MumbergBernard HaendlerPublished in: Cancers (2022)
Several inhibitors of androgen receptor (AR) function are approved for prostate cancer treatment, and their impact on gene transcription has been described. However, the ensuing effects at the protein level are far less well understood. We focused on the AR signaling inhibitor darolutamide and confirmed its strong AR binding and antagonistic activity using the high throughput cellular thermal shift assay (CETSA HT). Then, we generated comprehensive, quantitative proteomic data from the androgen-sensitive prostate cancer cell line VCaP and compared them to transcriptomic data. Following treatment with the synthetic androgen R1881 and darolutamide, global mass spectrometry-based proteomics and label-free quantification were performed. We found a generally good agreement between proteomic and transcriptomic data upon androgen stimulation and darolutamide inhibition. Similar effects were found both for the detected expressed genes and their protein products as well as for the corresponding biological programs. However, in a few instances there was a discrepancy in the magnitude of changes induced on gene expression levels compared to the corresponding protein levels, indicating post-transcriptional regulation of protein abundance. Chromatin immunoprecipitation DNA sequencing (ChIP-seq) and Hi-C chromatin immunoprecipitation (HiChIP) revealed the presence of androgen-activated AR-binding regions and long-distance AR-mediated loops at these genes.
Keyphrases
- label free
- single cell
- high throughput
- prostate cancer
- genome wide
- gene expression
- mass spectrometry
- rna seq
- binding protein
- protein protein
- dna methylation
- electronic health record
- amino acid
- transcription factor
- dna damage
- public health
- big data
- machine learning
- small molecule
- genome wide identification
- circulating tumor cells
- high glucose
- circulating tumor
- copy number
- oxidative stress
- wastewater treatment
- dna binding
- benign prostatic hyperplasia
- artificial intelligence
- deep learning
- drug administration
- gas chromatography
- bioinformatics analysis