4.7 Article

The genes controlling normal function of citrate and spermine secretion are lost in aggressive prostate cancer and prostate model systems

期刊

ISCIENCE
卷 25, 期 6, 页码 -

出版社

CELL PRESS
DOI: 10.1016/j.isci.2022.104451

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资金

  1. Liaison Committee
  2. Norwegian Cancer Society
  3. European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [758306]
  4. NIH Prostate SPORE [P50CA69568, R01 R01CA132874]
  5. Early Detection Research Network [U01 CA111275]
  6. Department of Defense [W81XWH-11-1-0331]
  7. National Center for Functional Genomics [W81XWH-11-1-0520]
  8. Common Fund of the Office of the Director of the National Institutes of Health
  9. NCI
  10. NHGRI
  11. NHLBI
  12. NIDA
  13. NIMH
  14. NINDS

向作者/读者索取更多资源

This study created a gene signature connected to citrate and spermine secretion in the prostate, and validated its accuracy by integrating metabolic measurements with multiple transcriptomics datasets. Several genes not previously studied in the prostate were highlighted by the signature.
High secretion of the metabolites citrate and spermine is a unique hallmark for normal prostate epithelial cells, and is reduced in aggressive prostate cancer. However, the identity of the genes controlling this biological process is mostly unknown. In this study, we have created a gene signature of 150 genes connected to citrate and spermine secretion in the prostate. We have computationally integrated metabolic measurements with multiple transcriptomics datasets from the public domain, including 3826 tissue samples from prostate and prostate cancer. The accuracy of the signature is validated by its unique enrichment in prostate samples and prostate epithelial tissue compartments. The signature highlights genes AZGP1, ANPEP and metallothioneins with zinc-binding properties not previously studied in the prostate, and the expression of these genes are reduced in more aggressive cancer lesions. However, the absence of signature enrichment in common prostate model systems can make it challenging to study these genes mechanistically.

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