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Signaling Interplay between Bone Marrow Adipose Tissue and Multiple Myeloma cells

Overview of attention for article published in Frontiers in endocrinology, June 2016
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  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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Title
Signaling Interplay between Bone Marrow Adipose Tissue and Multiple Myeloma cells
Published in
Frontiers in endocrinology, June 2016
DOI 10.3389/fendo.2016.00067
Pubmed ID
Authors

Carolyne Falank, Heather Fairfield, Michaela R. Reagan

Abstract

In the year 2000, Hanahan and Weinberg (1) defined the six Hallmarks of Cancer as: self-sufficiency in growth signals, evasion of apoptosis, insensitivity to antigrowth mechanisms, tissue invasion and metastasis, limitless replicative potential, and sustained angiogenesis. Eleven years later, two new Hallmarks were added to the list (avoiding immune destruction and reprograming energy metabolism) and two new tumor characteristics (tumor-promoting inflammation and genome instability and mutation) (2). In multiple myeloma (MM), a destructive cancer of the plasma cell that grows predominantly in the bone marrow (BM), it is clear that all these hallmarks and characteristics are in play, contributing to tumor initiation, drug resistance, disease progression, and relapse. Bone marrow adipose tissue (BMAT) is a newly recognized contributor to MM oncogenesis and disease progression, potentially affecting MM cell metabolism, immune action, inflammation, and influences on angiogenesis. In this review, we discuss the confirmed and hypothetical contributions of BMAT to MM development and disease progression. BMAT has been understudied due to technical challenges and a previous lack of appreciation for the endocrine function of this tissue. In this review, we define the dynamic, responsive, metabolically active BM adipocyte. We then describe how BMAT influences MM in terms of: lipids/metabolism, hypoxia/angiogenesis, paracrine or endocrine signaling, and bone disease. We then discuss the connection between BMAT and systemic inflammation and potential treatments to inhibit the feedback loops between BM adipocytes and MM cells that support MM progression. We aim for researchers to use this review to guide and help prioritize their experiments to develop better treatments or a cure for cancers, such as MM, that associate with and may depend on BMAT.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 88 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 21%
Student > Master 11 12%
Student > Bachelor 11 12%
Student > Postgraduate 9 10%
Other 7 8%
Other 16 18%
Unknown 16 18%
Readers by discipline Count As %
Medicine and Dentistry 23 26%
Biochemistry, Genetics and Molecular Biology 21 24%
Agricultural and Biological Sciences 12 13%
Immunology and Microbiology 3 3%
Neuroscience 2 2%
Other 10 11%
Unknown 18 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 07 August 2016.
All research outputs
#15,517,992
of 25,374,647 outputs
Outputs from Frontiers in endocrinology
#3,519
of 13,012 outputs
Outputs of similar age
#206,877
of 368,616 outputs
Outputs of similar age from Frontiers in endocrinology
#21
of 69 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,012 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 72% 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 368,616 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.