Evidence map›Paper›PMID 33377150›Full record

ArticleBriefings in bioinformatics2021

Understanding the unimodal distributions of cancer occurrence rates: it takes two factors for a cancer to occur.

Shuang Qiu, Zheng An, Renbo Tan, Ping-An He, Jingjing Jing, Hongxia Li, Shuang Wu, Ying Xu

Open access · hybridAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. 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
0.2field-weighted citation impact, top 45% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Elucidation of Factors Affecting the Age-Dependent Cancer Occurrence Rates.International journal of molecular sciences · 2024
    Article
  2. Article
  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

8 authors at 6 institutions in 2 countries.

Shuang QiuCancer Systems Biology Center, China-Japan Union Hospital of Jilin University.
Zheng AnCancer Systems Biology Center, China-Japan Union Hospital of Jilin University.
Renbo TanCancer Systems Biology Center, China-Japan Union Hospital of Jilin University.
Ping-An HeZhejiang Sci-Tech University.
Jingjing JingChina Medical University and Jilin University First Hospital.
Hongxia LiChina Medical University and Jilin University First Hospital.
Shuang WuChangchun Normal University.
Ying XuUniversity of Georgia and Jilin University.
Jilin University · CNUnion Hospital · CNChangchun Normal University · CNChina Medical University · CNUniversity of Georgia · USZhejiang Sci-Tech University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Data from the SEER reports reveal that the occurrence rate of a cancer type generally follows a unimodal distribution over age, peaking at an age that is cancer-type specific and ranges from 30+ through 70+. Previous studies attribute such bell-shaped distributions to the reduced proliferative potential in senior years but fail to explain why some cancers have their occurrence peak at 30+ or 40+. We present a computational model to offer a new explanation to such distributions. The model uses two factors to explain the observed age-dependent cancer occurrence rates: cancer risk of an organ and the availability level of the growth signals in circulation needed by a cancer type, with the former increasing and the latter decreasing with age. Regression analyses were conducted of known occurrence rates against such factors for triple negative breast cancer, testicular cancer and cervical cancer; and all achieved highly tight fitting results, which were also consistent with clinical, gene-expression and cancer-drug data. These reveal a fundamentally important relationship: while cancer is driven by endogenous stressors, it requires sufficient levels of exogenous growth signals to happen, hence suggesting the realistic possibility for treating cancer via cleaning out the growth signals in circulation needed by a cancer.

Indexed as

Databases, FactualModels, BiologicalTesticular NeoplasmsTriple Negative Breast NeoplasmsUterine Cervical NeoplasmsAdultAgedFemaleHumansMaleMiddle Agedcancer occurrence ratecancer riskcervical cancertesticular cancertriple negative breast cancer

Identifiers

PMID33377150
PMCPMC8294564
OpenAlexW3114226805

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.