Evidence map›Paper›PMID 28261092›Full record

ArticleFrontiers in pharmacology2017

Screening for Small Molecule Inhibitors of Statin-Induced APP C-terminal Toxic Fragment Production.

Karen S Poksay, Douglas J Sheffler, Patricia Spilman, Jesus Campagna, Barbara Jagodzinska, Olivier Descamps, Olivia Gorostiza, Alex Matalis, Michael Mullenix, Dale E Bredesen and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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

12 authors at 5 institutions in 1 country.

Karen S PoksayBredesen Lab, Buck Institute for Research on Aging, Novato CA, USA.
Douglas J ShefflerCancer Metabolism and Signaling Networks Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla CA, USA.
Patricia SpilmanBredesen Lab, Buck Institute for Research on Aging, NovatoCA, USA; Drug Discovery Lab, Department of Neurology, University of California, Los AngelesCA, USA.
Jesus CampagnaDrug Discovery Lab, Department of Neurology, University of California, Los Angeles CA, USA.
Barbara JagodzinskaDrug Discovery Lab, Department of Neurology, University of California, Los Angeles CA, USA.
Olivier DescampsBredesen Lab, Buck Institute for Research on Aging, Novato CA, USA.
Olivia GorostizaBredesen Lab, Buck Institute for Research on Aging, Novato CA, USA.
Alex MatalisBredesen Lab, Buck Institute for Research on Aging, Novato CA, USA.
Michael MullenixEnzo Life Sciences, Inc., Farmingdale NY, USA.
Dale E BredesenBredesen Lab, Buck Institute for Research on Aging, NovatoCA, USA; Drug Discovery Lab, Department of Neurology, University of California, Los AngelesCA, USA.
Nicholas D P CosfordCancer Metabolism and Signaling Networks Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla CA, USA.
Varghese JohnDrug Discovery Lab, Department of Neurology, University of California, Los Angeles CA, USA.
University of California, Los Angeles · USBuck Institute for Research on Aging · USDiscovery Institute · USEnzo Life Sciences (United States) · USSanford Burnham Prebys Medical Discovery Institute · US

Funding

Tumor Microenvironment and Cancer ImmunologyP30CA030199 · NCI · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI Michael Jackson · 1985 to 2026
$107.2M
NCI NIH HHS P30 CA030199
6 · The paper itself

Abstract

Alzheimer's disease (AD) is characterized by neuronal and synaptic loss. One process that could contribute to this loss is the intracellular caspase cleavage of the amyloid precursor protein (APP) resulting in release of the toxic C-terminal 31-amino acid peptide APP-C31 along with the production of APPΔC31, full-length APP minus the C-terminal 31 amino acids. We previously found that a mutation in APP that prevents this caspase cleavage ameliorated synaptic loss and cognitive impairment in a murine AD model. Thus, inhibition of this cleavage is a reasonable target for new therapeutic development. In order to identify small molecules that inhibit the generation of APP-C31, we first used an APPΔC31 cleavage site-specific antibody to develop an AlphaLISA to screen several chemical compound libraries for the level of N-terminal fragment production. This antibody was also used to develop an ELISA for validation studies. In both high throughput screening (HTS) and validation testing, the ability of compounds to inhibit simvastatin- (HTS) or cerivastatin- (validation studies) induced caspase cleavage at the APP-D720 cleavage site was determined in Chinese hamster ovary (CHO) cells stably transfected with wildtype (wt) human APP (CHO-7W). Several compounds, as well as control pan-caspase inhibitor Q-VD-OPh, inhibited APPΔC31 production (measured fragment) and rescued cell death in a dose-dependent manner. The effective compounds fell into several classes including SERCA inhibitors, inhibitors of Wnt signaling, and calcium channel antagonists. Further studies are underway to evaluate the efficacy of lead compounds - identified here using cells and tissues expressing wt human APP - in mouse models of AD expressing mutated human APP, as well as to identify additional compounds and determine the mechanisms by which they exert their effects.

Indexed as

AD – Alzheimer’s diseaseAPP – amyloid precursor proteinAPP-C31 –C-terminal 31 amino acid fragment of APPAPPΔC31 – N-terminal APP fragment minus C-terminal 31 amino acids (alphabetical)statins

Identifiers

PMID28261092
PMCPMC5309220
OpenAlexW2588046192

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.