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Regenerative potential of prostate luminal cells revealed by single-cell analysis.

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Title: Regenerative potential of prostate luminal cells revealed by single-cell analysis.
Authors: Karthaus, Wouter R., Hofree, Matan, Choi, Danielle, Linton, Eliot L., Turkekul, Mesruh, Bejnood, Alborz, Carver, Brett, Gopalan, Anuradha, Abida, Wassim, Laudone, Vincent, Biton, Moshe, Chaudhary, Ojasvi, Xu, Tianhao, Masilionis, Ignas, Manova, Katia, Mazutis, Linas, Pe’er, Dana, Regev, Aviv, Sawyers, Charles L.
Source: Science (pre-March 2025). 5/1/2020, Vol. 368 Issue 6490, p497-505. 9p. 5 Color Photographs.
Subjects: Androgens, Prostate cancer treatment, Glands, RNA sequencing, Growth factors
Abstract: Androgen deprivation is the cornerstone of prostate cancer treatment. It results in involution of the normal gland to ~90% of its original size because of the loss of luminal cells. The prostate regenerates when androgen is restored, a process postulated to involve stem cells. Using single-cell RNA sequencing, we identified a rare luminal population in the mouse prostate that expresses stemlike genes (Sca1+ and Psca+) and a large population of differentiated cells (Nkx3.1+, Pbsn+). In organoids and in mice, both populations contribute equally to prostate regeneration, partly through androgen-driven expression of growth factors (Nrg2, Rspo3) by mesenchymal cells acting in a paracrine fashion on luminal cells. Analysis of human prostate tissue revealed similar differentiated and stemlike luminal subpopulations that likewise acquire enhanced regenerative potential after androgen ablation. We propose that prostate regeneration is driven by nearly all persisting luminal cells, not just by rare stem cells. [ABSTRACT FROM AUTHOR]
Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Regenerative potential of prostate luminal cells revealed by single-cell analysis.
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  Data: <searchLink fieldCode="AR" term="%22Karthaus%2C+Wouter+R%2E%22">Karthaus, Wouter R.</searchLink><br /><searchLink fieldCode="AR" term="%22Hofree%2C+Matan%22">Hofree, Matan</searchLink><br /><searchLink fieldCode="AR" term="%22Choi%2C+Danielle%22">Choi, Danielle</searchLink><br /><searchLink fieldCode="AR" term="%22Linton%2C+Eliot+L%2E%22">Linton, Eliot L.</searchLink><br /><searchLink fieldCode="AR" term="%22Turkekul%2C+Mesruh%22">Turkekul, Mesruh</searchLink><br /><searchLink fieldCode="AR" term="%22Bejnood%2C+Alborz%22">Bejnood, Alborz</searchLink><br /><searchLink fieldCode="AR" term="%22Carver%2C+Brett%22">Carver, Brett</searchLink><br /><searchLink fieldCode="AR" term="%22Gopalan%2C+Anuradha%22">Gopalan, Anuradha</searchLink><br /><searchLink fieldCode="AR" term="%22Abida%2C+Wassim%22">Abida, Wassim</searchLink><br /><searchLink fieldCode="AR" term="%22Laudone%2C+Vincent%22">Laudone, Vincent</searchLink><br /><searchLink fieldCode="AR" term="%22Biton%2C+Moshe%22">Biton, Moshe</searchLink><br /><searchLink fieldCode="AR" term="%22Chaudhary%2C+Ojasvi%22">Chaudhary, Ojasvi</searchLink><br /><searchLink fieldCode="AR" term="%22Xu%2C+Tianhao%22">Xu, Tianhao</searchLink><br /><searchLink fieldCode="AR" term="%22Masilionis%2C+Ignas%22">Masilionis, Ignas</searchLink><br /><searchLink fieldCode="AR" term="%22Manova%2C+Katia%22">Manova, Katia</searchLink><br /><searchLink fieldCode="AR" term="%22Mazutis%2C+Linas%22">Mazutis, Linas</searchLink><br /><searchLink fieldCode="AR" term="%22Pe’er%2C+Dana%22">Pe’er, Dana</searchLink><br /><searchLink fieldCode="AR" term="%22Regev%2C+Aviv%22">Regev, Aviv</searchLink><br /><searchLink fieldCode="AR" term="%22Sawyers%2C+Charles+L%2E%22">Sawyers, Charles L.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Science+%28pre-March+2025%29%22">Science (pre-March 2025)</searchLink>. 5/1/2020, Vol. 368 Issue 6490, p497-505. 9p. 5 Color Photographs.
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  Data: <searchLink fieldCode="DE" term="%22Androgens%22">Androgens</searchLink><br /><searchLink fieldCode="DE" term="%22Prostate+cancer+treatment%22">Prostate cancer treatment</searchLink><br /><searchLink fieldCode="DE" term="%22Glands%22">Glands</searchLink><br /><searchLink fieldCode="DE" term="%22RNA+sequencing%22">RNA sequencing</searchLink><br /><searchLink fieldCode="DE" term="%22Growth+factors%22">Growth factors</searchLink>
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  Data: Androgen deprivation is the cornerstone of prostate cancer treatment. It results in involution of the normal gland to ~90% of its original size because of the loss of luminal cells. The prostate regenerates when androgen is restored, a process postulated to involve stem cells. Using single-cell RNA sequencing, we identified a rare luminal population in the mouse prostate that expresses stemlike genes (Sca1+ and Psca+) and a large population of differentiated cells (Nkx3.1+, Pbsn+). In organoids and in mice, both populations contribute equally to prostate regeneration, partly through androgen-driven expression of growth factors (Nrg2, Rspo3) by mesenchymal cells acting in a paracrine fashion on luminal cells. Analysis of human prostate tissue revealed similar differentiated and stemlike luminal subpopulations that likewise acquire enhanced regenerative potential after androgen ablation. We propose that prostate regeneration is driven by nearly all persisting luminal cells, not just by rare stem cells. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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