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Multiregion ultra‐deep sequencing reveals early intermixing and variable levels of intratumoral heterogeneity in colorectal cancer

Overview of attention for article published in Molecular Oncology, October 2016
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Title
Multiregion ultra‐deep sequencing reveals early intermixing and variable levels of intratumoral heterogeneity in colorectal cancer
Published in
Molecular Oncology, October 2016
DOI 10.1002/1878-0261.12012
Pubmed ID
Authors

Yuka Suzuki, Sarah Boonhsi Ng, Clarinda Chua, Wei Qiang Leow, Jermain Chng, Shi Yang Liu, Kalpana Ramnarayanan, Anna Gan, Dan Liang Ho, Rachel Ten, Yan Su, Alexandar Lezhava, Jiunn Herng Lai, Dennis Koh, Kiat Hon Lim, Patrick Tan, Steven G. Rozen, Iain Beehuat Tan

Abstract

Intratumor heterogeneity (ITH) contributes to cancer progression and chemoresistance. We sought to comprehensively describe ITH of somatic mutations, copy number, and transcriptomic alterations involving clinically and biologically relevant gene pathways in colorectal cancer (CRC). We performed multiregion, high-depth (384× on average) sequencing of 799 cancer-associated genes in 24 spatially separated primary tumor and nonmalignant tissues from four treatment-naïve CRC patients. We then used ultra-deep sequencing (17 075× on average) to accurately verify the presence or absence of identified somatic mutations in each sector. We also digitally measured gene expression and copy number alterations using NanoString assays. We identified the subclonal point mutations and determined the mutational timing and phylogenetic relationships among spatially separated sectors of each tumor. Truncal mutations, those shared by all sectors in the tumor, affected the well-described driver genes such as APC, TP53, and KRAS. With sequencing at 17 075×, we found that mutations first detected at a sequencing depth of 384× were in fact more widely shared among sectors than originally assessed. Interestingly, ultra-deep sequencing also revealed some mutations that were present in all spatially dispersed sectors, but at subclonal levels. Ultra-high-depth validation sequencing, copy number analysis, and gene expression profiling provided a comprehensive and accurate genomic landscape of spatial heterogeneity in CRC. Ultra-deep sequencing allowed more sensitive detection of somatic mutations and a more accurate assessment of ITH. By detecting the subclonal mutations with ultra-deep sequencing, we traced the genomic histories of each tumor and the relative timing of mutational events. We found evidence of early mixing, in which the subclonal ancestral mutations intermixed across the sectors before the acquisition of subsequent nontruncal mutations. Our findings also indicate that different CRC patients display markedly variable ITH, suggesting that each patient's tumor possesses a unique genomic history and spatial organization.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Unknown 64 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 26%
Researcher 16 24%
Student > Bachelor 7 11%
Student > Master 7 11%
Other 6 9%
Other 6 9%
Unknown 7 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 29%
Medicine and Dentistry 18 27%
Agricultural and Biological Sciences 14 21%
Engineering 2 3%
Sports and Recreations 1 2%
Other 3 5%
Unknown 9 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 October 2016.
All research outputs
#16,703,088
of 24,565,648 outputs
Outputs from Molecular Oncology
#1,169
of 1,643 outputs
Outputs of similar age
#205,198
of 321,618 outputs
Outputs of similar age from Molecular Oncology
#7
of 9 outputs
Altmetric has tracked 24,565,648 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,643 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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 321,618 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.