Evidence map›Paper›PMID 30463617›Full record

ArticleBMC systems biology2018

Instantaneous mutation rate in cancer initiation and progression.

Shuhao Sun, Fima Klebaner, Xinan Zhang, Tianhai Tian

Abstract read
In one paragraph

Article in BMC systems biology, 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. Review
  2. Article
  3. A Strategic Review on Carbon Quantum Dots for Cancer-Diagnostics and Treatment.Frontiers in bioengineering and biotechnology · 2022
    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

4 authors.

Shuhao SunSchool of Mathematical Sciences, Monash University, Melbourne, 3800, VIC, Australia.
Fima KlebanerSchool of Mathematical Sciences, Monash University, Melbourne, 3800, VIC, Australia.
Xinan ZhangSchool of Mathematics and Statistics, Central China Normal University, Wuhan, 430079, People's Republic of China.
Tianhai TianSchool of Mathematical Sciences, Monash University, Melbourne, 3800, VIC, Australia. tianhai.tian@monash.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes.

resultsTo accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time.

conclusionsThe proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.

Indexed as

Disease ProgressionMutation RateCarcinogenesisCell ProliferationHumansModels, BiologicalNeoplasm MetastasisCancerCancer cell doubling timeInitial mutation rateMathematical model

Identifiers

PMID30463617
PMCPMC6249718

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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.