Evidence map›Paper›PMID 35105671›Full record

ArticleMolecular cancer research : MCR2022

Blocking PI3K p110β Attenuates Development of PTEN-Deficient Castration-Resistant Prostate Cancer.

Xueliang Gao, Yubao Wang, Caroline F Ribeiro, Cherubin Manokaran, Hyeyoun Chang, Thanh Von, Silvia Rodrigues, Onur Cizmecioglu, Shidong Jia, Manav Korpal and 12 more

Open access · bronzeAbstract read
In one paragraph

Article in Molecular cancer research : MCR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Targeting PI3K/Akt signaling in prostate cancer therapy.Journal of cell communication and signaling · 2023
    Review
  10. Review
  11. AR and PI3K/AKT in Prostate Cancer: A Tale of Two Interconnected Pathways.International journal of molecular sciences · 2023
    Review
  12. Review
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors at 3 institutions in 2 countries.

Xueliang Gao *Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Yubao Wang *Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Caroline F Ribeiro *Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Masachusetts.ORCID 0000-0002-6785-6933
Cherubin ManokaranDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Hyeyoun ChangDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Thanh VonDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Silvia RodriguesDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Masachusetts.ORCID 0000-0002-7239-8324
Onur CizmeciogluDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Shidong JiaDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Manav KorpalOncology Disease Area, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts.
Joshua M KornOncology Disease Area, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts.
Zhigang WangDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Fabienne SchmitDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Lan JiangBiostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Raymond PagliariniOncology Disease Area, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts.
Yi YangOncology Disease Area, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts.
Isha SethiBiostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Sabina SignorettiDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Masachusetts.ORCID 0000-0002-5000-9105
Guo-Cheng YuanBiostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Massimo LodaDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Masachusetts.ORCID 0000-0001-9674-8379
Jean J ZhaoDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-4561-5688
Thomas M RobertsDepartment of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.
Harvard University · USDana-Farber Cancer Institute · USNovartis (Switzerland) · CH

Funding

Tumor and Circulating Markers as Links Between Obesity and Lethal Prostate CanceP50CA090381 · NCI · DANA-FARBER CANCER INSTITUTE · PI KANTOFF, PHILIP W · 2002 to 2017
$36.2M
Weill Cornell Medicine (WCM) SPORE in Prostate CancerP50CA211024 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI GUDAS, LORRAINE J · 2017 to 2021
$10.9M
Integrating targeted therapy and immunotherapy to break through cancerR35CA210057 · NCI · DANA-FARBER CANCER INST · PI Jean Zhao · 2016 to 2026
$10.8M
Maximizing the Effectiveness of PI3K Inhibitors in the Treatment of Pten null CancersR35CA231945 · NCI · DANA-FARBER CANCER INST · PI ROBERTS, THOMAS M · 2019 to 2025
$7.1M
Targeting the p110beta isoform of PI3 kinase in prostate cancerR01CA187918 · NCI · DANA-FARBER CANCER INST · PI LODA, MASSIMO, ROBERTS, THOMAS M · 2015 to 2019
$2.8M
Cancer Chemical Biology and Metabolism Training ProgramT32CA236754 · NCI · DANA-FARBER CANCER INST · PI Nika N Danial, THOMAS M ROBERTS · 2019 to 2026
$2.6M
COVID and Translational Science supercomputer (CATS)S10OD030463 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2021 to 2021
$2.0M
Big Omics Data Engine 2 SupercomputerS10OD026880 · OD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KOVATCH, PATRICIA · 2019 to 2019
$2.0M
NCI NIH HHS P50 CA090381NCI NIH HHS P50 CA211024NCI NIH HHS R01 CA187918NCI NIH HHS R35 CA210057NCI NIH HHS R35 CA231945NCI NIH HHS T32 CA236754NIH HHS S10 OD026880NIH HHS S10 OD030463
6 · The paper itself

Abstract

A common outcome of androgen deprivation in prostate cancer therapy is disease relapse and progression to castration-resistant prostate cancer (CRPC) via multiple mechanisms. To gain insight into the recent clinical findings that highlighted genomic alterations leading to hyperactivation of PI3K, we examined the roles of the commonly expressed p110 catalytic isoforms of PI3K in a murine model of Pten-null invasive CRPC. While blocking p110α had negligible effects in the development of Pten-null invasive CRPC, either genetic or pharmacologic perturbation of p110β dramatically slowed CRPC initiation and progression. Once fully established, CRPC tumors became partially resistant to p110β inhibition, indicating the acquisition of new dependencies. Driven by our genomic analyses highlighting potential roles for the p110β/RAC/PAK1 and β-catenin pathways in CRPC, we found that combining p110β with RAC/PAK1 or tankyrase inhibitors significantly reduced the growth of murine and human CRPC organoids in vitro and in vivo. Because p110β activity is dispensable for most physiologic processes, our studies support novel therapeutic strategies both for preventing disease progression into CRPC and for treating CRPC. IMPLICATIONS: This work establishes p110β as a promising target for preventing the progression of primary PTEN-deficient prostate tumors to CRPC, and for treating established CRPC in combination with RAC/PAK1 or tankyrase inhibitors.

Indexed as

Prostatic Neoplasms, Castration-ResistantTankyrasesAndrogen AntagonistsAnimalsHumansMaleMicePhosphatidylinositol 3-KinasesProstatePTEN PhosphohydrolaseAndrogen AntagonistsPhosphatidylinositol 3-KinasesPTEN PhosphohydrolasePTEN protein, humanTankyrases

Identifiers

PMID35105671
PMCPMC9081176
OpenAlexW4210483903

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.