Evidence map›Paper›PMID 34649609›Full record

ArticleGenome medicine2021

Integrating thousands of PTEN variant activity and abundance measurements reveals variant subgroups and new dominant negatives in cancers.

Kenneth A Matreyek, Jason J Stephany, Ethan Ahler, Douglas M Fowler

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

30 citing papers in PubMed, 46 citations in OpenAlex.

  1. Review
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  9. Phenotype-Specific Recalibration of MAVE Data Enables Repurposing ofmedRxiv : the preprint server for health sciences · 2026
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  10. Review
  11. Supervised learning of protein variant effects across large-scale mutagenesis datasets.Protein science : a publication of the Protein Society · 2026
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  12. Clinicogenomic Landscape and Function ofJCO precision oncology · 2026
    Article
  13. Article
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  18. Biophysics-based protein language models for protein engineering.bioRxiv : the preprint server for biology · 2025
    Article
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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

4 authors at 1 institution in 1 country.

Kenneth A MatreyekDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. kenneth.matreyek@case.com.ORCID 0000-0001-9149-551X
Jason J StephanyDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Ethan AhlerDepartment of Genome Sciences, University of Washington, Seattle, WA, USA.
Douglas M FowlerDepartment of Genome Sciences, University of Washington, Seattle, WA, USA. dfowler@uw.edu.
University of Washington · US

Funding

Technology to understand genetic variant effects in contextRM1HG010461 · NHGRI · UNIVERSITY OF WASHINGTON · PI Douglas M Fowler, Bruce Colston Trapnell · 2019 to 2026
$18.9M
Large-Scale Methods for Assessing the Consequences of Mutations in ProteinsR01GM109110 · NIGMS · UNIVERSITY OF WASHINGTON · PI FOWLER, DOUGLAS M · 2014 to 2021
$2.4M
Recombinant DNA technologies for multiplex genetic assays in human cellsR35GM142886 · NIGMS · CASE WESTERN RESERVE UNIVERSITY · PI MATREYEK, KENNETH A · 2021 to 2025
$2.0M
NHGRI NIH HHS RM1 HG010461NIGMS NIH HHS R01 GM109110NIGMS NIH HHS R35 GM142886
6 · The paper itself

Abstract

backgroundPTEN is a multi-functional tumor suppressor protein regulating cell growth, immune signaling, neuronal function, and genome stability. Experimental characterization can help guide the clinical interpretation of the thousands of germline or somatic PTEN variants observed in patients. Two large-scale mutational datasets, one for PTEN variant intracellular abundance encompassing 4112 missense variants and one for lipid phosphatase activity encompassing 7244 variants, were recently published. The combined information from these datasets can reveal variant-specific phenotypes that may underlie various clinical presentations, but this has not been comprehensively examined, particularly for somatic PTEN variants observed in cancers.

methodsHere, we add to these efforts by measuring the intracellular abundance of 764 new PTEN variants and refining abundance measurements for 3351 previously studied variants. We use this expanded and refined PTEN abundance dataset to explore the mutational patterns governing PTEN intracellular abundance, and then incorporate the phosphatase activity data to subdivide PTEN variants into four functionally distinct groups.

resultsThis analysis revealed a set of highly abundant but lipid phosphatase defective variants that could act in a dominant-negative fashion to suppress PTEN activity. Two of these variants were, indeed, capable of dysregulating Akt signaling in cells harboring a WT PTEN allele. Both variants were observed in multiple breast or uterine tumors, demonstrating the disease relevance of these high abundance, inactive variants.

conclusionsWe show that multidimensional, large-scale variant functional data, when paired with public cancer genomics datasets and follow-up assays, can improve understanding of uncharacterized cancer-associated variants, and provide better insights into how they contribute to oncogenesis.

Indexed as

Genetic VariationGene Expression Regulation, NeoplasticGenomicsGerm-Line MutationHEK293 CellsHumansMutationMutation, MissenseNeoplasmsPhenotypePTEN PhosphohydrolasePTEN PhosphohydrolasePTEN protein, humanCancer genomicsDominant-negativeMultiplex assays of variant effectProtein variantsPTENVAMP-seq

Identifiers

PMID34649609
PMCPMC8518224
OpenAlexW3205136345

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.