Evidence map›Paper›PMID 37950065›Full record

ArticleCommunications biology2023

Mining cancer genomes for change-of-metabolic-function mutations.

Kevin J Tu, Bill H Diplas, Joshua A Regal, Matthew S Waitkus, Christopher J Pirozzi, Zachary J Reitman

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 2 countries.

Kevin J TuDepartment of Radiation Oncology, Duke University, Durham, NC, 27710, USA.ORCID 0000-0002-0089-3932
Bill H DiplasDepartment of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.
Joshua A RegalDepartment of Radiation Oncology, Duke University, Durham, NC, 27710, USA.
Matthew S WaitkusDepartment of Neurosurgery, Duke University, Durham, NC, 27710, USA.ORCID 0000-0002-7116-6978
Christopher J PirozziDepartment of Pathology, Duke University, Durham, NC, 27710, USA.
Zachary J ReitmanDepartment of Radiation Oncology, Duke University, Durham, NC, 27710, USA. zjr@duke.edu.ORCID 0000-0002-9122-9550
Duke University · USMemorial Sloan Kettering Cancer Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Medical Scientist Training Program Training GrantT32GM145449 · NIGMS · DUKE UNIVERSITY · PI Christopher D Kontos · 2022 to 2026
$6.6M
Enhancing the efficacy of Radiation Therapy for brainstem glioma by targeting ATMK08CA256045 · NCI · DUKE UNIVERSITY · PI Zachary Reitman · 2022 to 2026
$1.1M
NCI NIH HHS K08 CA256045NCI NIH HHS P30 CA008748NIGMS NIH HHS T32 GM145449
6 · The paper itself

Abstract

Enzymes with novel functions are needed to enable new organic synthesis techniques. Drawing inspiration from gain-of-function cancer mutations that functionally alter proteins and affect cellular metabolism, we developed METIS (Mutated Enzymes from Tumors In silico Screen). METIS identifies metabolism-altering cancer mutations using mutation recurrence rates and protein structure. We used METIS to screen 298,517 cancer mutations and identify 48 candidate mutations, including those previously identified to alter enzymatic function. Unbiased metabolomic profiling of cells exogenously expressing a candidate mutant (OGDHLp.A400T) supports an altered phenotype that boosts in vitro production of xanthosine, a pharmacologically useful chemical that is currently produced using unsustainable, water-intensive methods. We then applied METIS to 49 million cancer mutations, yielding a refined set of candidates that may impart novel enzymatic functions or contribute to tumor progression. Thus, METIS can be used to identify and catalog potentially-useful cancer mutations for green chemistry and therapeutic applications.

Indexed as

NeoplasmsHumansMutation

Identifiers

PMID37950065
PMCPMC10638295
OpenAlexW4388573732

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.