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Microbiomic differences in tumor and paired-normal tissue in head and neck squamous cell carcinomas

Overview of attention for article published in Genome Medicine, February 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)

Mentioned by

blogs
1 blog
twitter
21 tweeters

Citations

dimensions_citation
54 Dimensions

Readers on

mendeley
81 Mendeley
citeulike
3 CiteULike
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Title
Microbiomic differences in tumor and paired-normal tissue in head and neck squamous cell carcinomas
Published in
Genome Medicine, February 2017
DOI 10.1186/s13073-017-0405-5
Pubmed ID
Authors

Hannah Wang, Pauline Funchain, Gurkan Bebek, Jessica Altemus, Huan Zhang, Farshad Niazi, Charissa Peterson, Walter T. Lee, Brian B. Burkey, Charis Eng

Abstract

While the role of the gut microbiome in inflammation and colorectal cancers has received much recent attention, there are few data to support an association between the oral microbiome and head and neck squamous cell carcinomas. Prior investigations have been limited to comparisons of microbiota obtained from surface swabs of the oral cavity. This study aims to identify microbiomic differences in paired tumor and non-tumor tissue samples in a large group of 121 patients with head and neck squamous cell carcinomas and correlate these differences with clinical-pathologic features. Total DNA was extracted from paired normal and tumor resection specimens from 169 patients; 242 samples from 121 patients were included in the final analysis. Microbiomic content of each sample was determined using 16S rDNA amplicon sequencing. Bioinformatic analysis was performed using QIIME algorithms. F-testing on cluster strength, Wilcoxon signed-rank testing on differential relative abundances of paired tumor-normal samples, and Wilcoxon rank-sum testing on the association of T-stage with relative abundances were conducted in R. We observed no significant difference in measures of alpha diversity between tumor and normal tissue (Shannon index: p = 0.13, phylogenetic diversity: p = 0.42). Similarly, although we observed statistically significantly differences in both weighted (p = 0.01) and unweighted (p = 0.04) Unifrac distances between tissue types, the tumor/normal grouping explained only a small proportion of the overall variation in the samples (weighted R(2) = 0.01, unweighted R(2) < 0.01). Notably, however, when comparing the relative abundances of individual taxa between matched pairs of tumor and normal tissue, we observed that Actinomyces and its parent taxa up to the phylum level were significantly depleted in tumor relative to normal tissue (q < 0.01), while Parvimonas was increased in tumor relative to normal tissue (q = 0.01). These differences were more pronounced among patients with more extensive disease as measured by higher T-stage. Matched pairs analysis of individual tumor-normal pairs revealed significant differences in relative abundance of specific taxa, namely in the genus Actinomyces. These differences were more pronounced among patients with higher T-stage. Our observations suggest further experiments to interrogate potential novel mechanisms relevant to carcinogenesis associated with alterations of the oral microbiome that may have consequences for the human host.

Twitter Demographics

The data shown below were collected from the profiles of 21 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 15 19%
Student > Master 13 16%
Researcher 8 10%
Student > Ph. D. Student 7 9%
Professor > Associate Professor 5 6%
Other 17 21%
Unknown 16 20%
Readers by discipline Count As %
Medicine and Dentistry 22 27%
Agricultural and Biological Sciences 14 17%
Biochemistry, Genetics and Molecular Biology 12 15%
Immunology and Microbiology 6 7%
Engineering 2 2%
Other 7 9%
Unknown 18 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 27 October 2018.
All research outputs
#1,186,965
of 17,193,520 outputs
Outputs from Genome Medicine
#266
of 1,144 outputs
Outputs of similar age
#34,359
of 365,094 outputs
Outputs of similar age from Genome Medicine
#3
of 3 outputs
Altmetric has tracked 17,193,520 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,144 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.4. This one has done well, scoring higher than 76% 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 365,094 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 90% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.