Report for: Variation in cancer risk among tissues can be explained by the number of stem cell divisions

Title	Variation in cancer risk among tissues can be explained by the number of stem cell divisions
Published in	Science, January 2015
DOI	10.1126/science.1260825
Pubmed ID	25554788
Authors	Cristian Tomasetti, Bert Vogelstein
Abstract	Some tissue types give rise to human cancers millions of times more often than other tissue types. Although this has been recognized for more than a century, it has never been explained. Here, we show that the lifetime risk of cancers of many different types is strongly correlated (0.81) with the total number of divisions of the normal self-renewing cells maintaining that tissue's homeostasis. These results suggest that only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions. The majority is due to "bad luck," that is, random mutations arising during DNA replication in normal, noncancerous stem cells. This is important not only for understanding the disease but also for designing strategies to limit the mortality it causes.

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Twitter Demographics

The data shown below were collected from the profiles of 1,251 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Geographical breakdown

Country	Count	As %
United States	245	20%
Japan	120	10%
United Kingdom	78	6%
Spain	52	4%
Canada	30	2%
Netherlands	24	2%
France	17	1%
Germany	16	1%
Australia	15	1%
Other	156	12%
Unknown	498	40%

Demographic breakdown

Type	Count	As %
Members of the public	904	72%
Scientists	241	19%
Practitioners (doctors, other healthcare professionals)	73	6%
Science communicators (journalists, bloggers, editors)	32	3%
Unknown	1	<1%

Mendeley readers

The data shown below were compiled from readership statistics for 2,587 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country	Count	As %
United States	45	2%
Germany	24	<1%
United Kingdom	18	<1%
France	10	<1%
Italy	6	<1%
Denmark	5	<1%
Switzerland	5	<1%
Canada	5	<1%
Japan	4	<1%
Other	44	2%
Unknown	2421	94%

Demographic breakdown

Readers by professional status	Count	As %
Student > Ph. D. Student	627	24%
Researcher	604	23%
Student > Bachelor	287	11%
Student > Master	241	9%
Other	143	6%
Other	513	20%
Unknown	172	7%

Readers by discipline	Count	As %
Agricultural and Biological Sciences	846	33%
Biochemistry, Genetics and Molecular Biology	568	22%
Medicine and Dentistry	411	16%
Chemistry	62	2%
Computer Science	62	2%
Other	382	15%
Unknown	256	10%

Attention Score in Context

This research output has an Altmetric Attention Score of 3071. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 June 2021.

All research outputs

#1,041

of 18,026,194 outputs

Outputs from Science

#68

of 71,711 outputs

Outputs of similar age

#10

of 315,221 outputs

Outputs of similar age from Science

of 1,060 outputs

Altmetric has tracked 18,026,194 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.

So far Altmetric has tracked 71,711 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 56.3. This one has done particularly well, scoring higher than 99% of its peers.

Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,221 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.

We're also able to compare this research output to 1,060 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.

Variation in cancer risk among tissues can be explained by the number of stem cell divisions

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