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Increasing the Clinical Efficacy of NK and Antibody-Mediated Cancer Immunotherapy: Potential Predictors of Successful Clinical Outcome Based on Observations in High-Risk Neuroblastoma

Overview of attention for article published in Frontiers in Pharmacology, January 2012
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Title
Increasing the Clinical Efficacy of NK and Antibody-Mediated Cancer Immunotherapy: Potential Predictors of Successful Clinical Outcome Based on Observations in High-Risk Neuroblastoma
Published in
Frontiers in Pharmacology, January 2012
DOI 10.3389/fphar.2012.00091
Pubmed ID
Authors

Tony A. Koehn, Lori L. Trimble, Kory L. Alderson, Amy K. Erbe, Kimberly A. McDowell, Bartosz Grzywacz, Jacquelyn A. Hank, Paul M. Sondel

Abstract

Disease recurrence is frequent in high-risk neuroblastoma (NBL) patients even after multi-modality aggressive treatment [a combination of chemotherapy, surgical resection, local radiation therapy, autologous stem cell transplantation, and cis-retinoic acid (CRA)]. Recent clinical studies have explored the use of monoclonal antibodies (mAbs) that bind to disialoganglioside (GD(2)), highly expressed in NBL, as a means to enable immune effector cells to destroy NBL cells via antibody-dependent cell-mediated cytotoxicity (ADCC). Preclinical data indicate that ADCC can be more effective when appropriate effector cells are activated by cytokines. Clinical studies have pursued this by administering anti-GD(2) mAb in combination with ADCC-enhancing cytokines (IL2 and GM-CSF), a regimen that has demonstrated improved cancer-free survival. More recently, early clinical studies have used a fusion protein that consists of the anti-GD(2) mAb directly linked to IL2, and anti-tumor responses were seen in the Phase II setting. Analyses of genes that code for receptors that influence ADCC activity and natural killer (NK) cell function [Fc receptor (FcR), killer immunoglublin-like receptor (KIR), and KIR-ligand (KIR-L)] suggest patients with anti-tumor activity are more likely to have certain genotype profiles. Further analyses will need to be conducted to determine whether these genotypes can be used as predictive markers for favorable therapeutic outcome. In this review, we discuss factors that affect response to mAb-based tumor therapies such as hu14.18-IL2. Many of our observations have been made in the context of NBL; however, we will also include some observations made with mAbs targeting other tumor types that are consistent with results in NBL. Therefore, we hypothesize that the NBL observations discussed here may also be relevant to mAb therapy for other cancers, in which ADCC is known to play a role.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 40 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 20%
Student > Ph. D. Student 8 20%
Student > Master 7 17%
Student > Bachelor 5 12%
Other 3 7%
Other 6 15%
Unknown 4 10%
Readers by discipline Count As %
Medicine and Dentistry 13 32%
Agricultural and Biological Sciences 10 24%
Biochemistry, Genetics and Molecular Biology 6 15%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Unspecified 1 2%
Other 2 5%
Unknown 7 17%
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 02 December 2012.
All research outputs
#14,605,487
of 22,675,759 outputs
Outputs from Frontiers in Pharmacology
#5,019
of 15,845 outputs
Outputs of similar age
#158,027
of 244,088 outputs
Outputs of similar age from Frontiers in Pharmacology
#62
of 137 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,845 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 67% 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 244,088 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 137 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 54% of its contemporaries.