Evidence map›Paper›PMID 29805696›Full record

ReviewJournal of Cancer2018

Hypothesis: Cancer Is a Disease of Evolved Trade-Offs Between Neoplastic Virulence and Transmission.

Michael Bordonaro

Abstract readReview
In one paragraph

Review in Journal of Cancer, 2018. 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
–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

3 citing papers in PubMed.

  1. Humans as an extended phenotype of their microbiota.Theory in biosciences = Theorie in den Biowissenschaften · 2026
    Article
  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

1 author.

Michael BordonaroDepartment of Basic Sciences, Geisinger Commonwealth School of Medicine, 525 Pine Street, Scranton, PA 18509, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Virulence is defined as the ability of a pathogen to cause morbidity and/or mortality in infected hosts. The relationship between virulence and transmissibility is complex; natural selection may promote decreased virulence to enhance host mobility and increase the probability for transmission, or transmissibility may be enhanced by increased virulence, leading to higher pathogen load and, in some cases, superior evasion from host defenses. An evolutionary trade-off exists between the ability of pathogens to maintain opportunities for long-term transmission via suppressed virulence and increased short-term transmission via enhanced virulence. We propose an analogy between transmissibility and virulence in microbial pathogens and in cancer. Thus, in the latter case, the outcome of invasive growth and metastasis is analogous to transmissibility, and virulence is defined by high rates of proliferation, invasiveness and motility, potential for metastasis, and the extent to which the cancer contributes to patient morbidity and mortality. Horizontal and vertical transmission, associated with increased or decreased pathogen virulence respectively, can also be utilized to model the neoplastic process and factors that would increase or decrease tumor aggressiveness. Concepts of soft vs. hard selection and evolutionary game theory can optimize our understanding of carcinogenesis and therapeutic strategies. Therefore, the language of transmissibility, horizontal vs. vertical transmission, selection, and virulence can be used to inform approaches to inhibit tumorigenic progression, and, more generally, for cancer prevention and treatment.

Indexed as

cancerevolutionselectiontransmissionvirulence

Identifiers

PMID29805696
PMCPMC5968758

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.