Evidence map›Paper›PMID 30082874›Full record

ArticleScientific reports2018

Estimation of the cancer risk induced by therapies targeting stem cell replication and treatment recommendations.

Michael Meyer-Hermann

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.1field-weighted citation impact, top 57% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Michael Meyer-HermannDepartment of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Rebenring 56, 38106, Braunschweig, Germany. mmh@theoretical-biology.de.
Helmholtz Centre for Infection Research · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rejuvenation of stem cell activity might increase life expectancy by prolonging functionality of organs. Higher stem cell replication rates also bear the risk of cancer. The extent of this risk is not known. While it is difficult to evaluate this cancer risk in experiments, it can be estimated using a mathematical model for tissue homeostasis by stem cell replication and associated cancer risk. The model recapitulates the observation that treatments targeting stem cell replication can induce a substantial delay of organ failure. The model predicts that the cancer risk is minor under particular conditions. It depends on the assumed implications for cell damage repair during treatment. The benefit of rejuvenation therapy and its impact on cancer risk depend on the biological age at the time of treatment and on the overall cell turnover rate of the organs. Different organs have to be considered separately in the planning of systemic treatments. In recent years, the transfer of blood from young to old individuals was shown to bear the potential of rejuvenation of stem cell activity. In this context, the model predicts that the treatment schedule is critical for success and that schedules successful in animal experiments are not transferable to humans. Guidelines for successful protocols are proposed. The model presented here may be used as a guidance for the development of stem cell rejuvenation treatment protocols and the identification of critical parameters for cancer risk.

Indexed as

Models, TheoreticalAnimalsCell DivisionCell Self RenewalHumansMiceNeoplasmsStem CellsStem Cell Transplantation

Identifiers

PMID30082874
PMCPMC6078959
OpenAlexW2886564714

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.