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Paired Expression Analysis of Tumor Cell Surface Antigens

Overview of attention for article published in Frontiers in oncology, August 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Title
Paired Expression Analysis of Tumor Cell Surface Antigens
Published in
Frontiers in oncology, August 2017
DOI 10.3389/fonc.2017.00173
Pubmed ID
Authors

Rimas J. Orentas, Sivasish Sindiri, Christine Duris, Xinyu Wen, Jianbin He, Jun S. Wei, Jason Jarzembowski, Javed Khan

Abstract

Adoptive immunotherapy with antibody-based therapy or with T cells transduced to express chimeric antigen receptors (CARs) is useful to the extent that the cell surface membrane protein being targeted is not expressed on normal tissues. The most successful CAR-based (anti-CD19) or antibody-based therapy (anti-CD20) in hematologic malignancies has the side effect of eliminating the normal B cell compartment. Targeting solid tumors may not provide a similar expendable marker. Beyond antibody to Her2/NEU and EGFR, very few antibody-based and no CAR-based therapies have seen broad clinical application for solid tumors. To expand the way in which the surfaceome of solid tumors can be analyzed, we created an algorithm that defines the pairwise relative overexpression of surface antigens. This enables the development of specific immunotherapies that require the expression of two discrete antigens on the surface of the tumor target. This dyad analysis was facilitated by employing the Hotelling's T-squared test (Hotelling-Lawley multivariate analysis of variance) for two independent variables in comparison to a third constant entity (i.e., gene expression levels in normal tissues). We also present a unique consensus scoring mechanism for identifying transcripts that encode cell surface proteins. The unique application of our bioinformatics processing pipeline and statistical tools allowed us to compare the expression of two membrane protein targets as a pair, and to propose a new strategy based on implementing immunotherapies that require both antigens to be expressed on the tumor cell surface to trigger therapeutic effector mechanisms. Specifically, we found that, for MYCN amplified neuroblastoma, pairwise expression of ACVR2B or anaplastic lymphoma kinase (ALK) with GFRA3, GFRA2, Cadherin 24, or with one another provided the strongest hits. For MYCN, non-amplified stage 4 neuroblastoma, neurotrophic tyrosine kinase 1, or ALK paired with GFRA2, GFRA3, SSK1, GPR173, or with one another provided the most promising paired-hits. We propose that targeting these markers together would increase the specificity and thereby the safety of CAR-based therapy for neuroblastoma.

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X Demographics

The data shown below were collected from the profiles of 5 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 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 21%
Student > Bachelor 7 11%
Student > Master 7 11%
Student > Ph. D. Student 7 11%
Professor 3 5%
Other 6 10%
Unknown 18 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 16%
Medicine and Dentistry 10 16%
Agricultural and Biological Sciences 8 13%
Immunology and Microbiology 5 8%
Pharmacology, Toxicology and Pharmaceutical Science 3 5%
Other 8 13%
Unknown 17 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 23 December 2017.
All research outputs
#7,962,193
of 25,382,440 outputs
Outputs from Frontiers in oncology
#2,902
of 22,428 outputs
Outputs of similar age
#116,288
of 325,576 outputs
Outputs of similar age from Frontiers in oncology
#24
of 93 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 22,428 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 86% 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 325,576 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 93 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 74% of its contemporaries.