Evidence map›Paper›PMID 29250983›Full record

ReviewCritical reviews in biochemistry and molecular biology2018

The impact of non-genetic heterogeneity on cancer cell death.

Zintis Inde, Scott J Dixon

Abstract readReview
In one paragraph

Review in Critical reviews in biochemistry and molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
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

27 citing papers in PubMed.

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  20. Intracellular CaFrontiers in cell and developmental biology · 2020
    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

2 authors.

Zintis Indea Cancer Biology Program , Stanford University School of Medicine , Stanford , CA , USA.
Scott J Dixona Cancer Biology Program , Stanford University School of Medicine , Stanford , CA , USA.ORCID 0000-0001-6230-8199

Funding

Leveraging innovative technologies in basic and clinical cancer researchT32CA009302 · NCI · STANFORD UNIVERSITY · PI LAURA D ATTARDI, Aaron M Newman · 1985 to 2026
$19.1M
Characterizing the Regulation of FerroptosisR01GM122923 · NIGMS · STANFORD UNIVERSITY · PI Scott Dixon · 2017 to 2026
$3.4M
Targeting Tumor Cell Iron Addiction to Achieve Tumor-Selective Cell DeathR00CA166517 · NCI · STANFORD UNIVERSITY · PI DIXON, SCOTT · 2014 to 2016
$708k
NCI NIH HHS R00 CA166517NCI NIH HHS T32 CA009302NIGMS NIH HHS R01 GM122923
6 · The paper itself

Abstract

The goal of cancer chemotherapy is to induce homogeneous cell death within the population of targeted cancer cells. However, no two cells are exactly alike at the molecular level, and sensitivity to drug-induced cell death, therefore, varies within a population. Genetic alterations can contribute to this variability and lead to selection for drug resistant clones. However, there is a growing appreciation for the role of non-genetic variation in producing drug-tolerant cellular states that exhibit reduced sensitivity to cell death for extended periods of time, from hours to weeks. These cellular states may result from individual variation in epigenetics, gene expression, metabolism, and other processes that impact drug mechanism of action or the execution of cell death. Such population-level non-genetic heterogeneity may contribute to treatment failure and provide a cellular "substrate" for the emergence of genetic alterations that confer frank drug resistance.

Indexed as

Drug Resistance, NeoplasmAnimalsAntineoplastic AgentsCell DeathCell ProliferationEpigenesis, GeneticGene Expression Regulation, NeoplasticHumansMetabolic Networks and PathwaysNeoplasmsProtein Processing, Post-TranslationalSignal TransductionAntineoplastic AgentsapoptosiscancerCell deathheterogeneitysingle-cell

Identifiers

PMID29250983
PMCPMC6089072

What OpenQuestion holds

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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.