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Validation of biomarkers to predict response to immunotherapy in cancer: Volume I — pre-analytical and analytical validation

Overview of attention for article published in Journal for Immunotherapy of Cancer, November 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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5 patents

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311 Mendeley
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Title
Validation of biomarkers to predict response to immunotherapy in cancer: Volume I — pre-analytical and analytical validation
Published in
Journal for Immunotherapy of Cancer, November 2016
DOI 10.1186/s40425-016-0178-1
Pubmed ID
Authors

Giuseppe V. Masucci, Alessandra Cesano, Rachael Hawtin, Sylvia Janetzki, Jenny Zhang, Ilan Kirsch, Kevin K. Dobbin, John Alvarez, Paul B. Robbins, Senthamil R. Selvan, Howard Z. Streicher, Lisa H. Butterfield, Magdalena Thurin

Abstract

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, there have been many clinical successes using checkpoint receptor blockade, including T cell inhibitory receptors such as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death-1 (PD-1). Despite demonstrated successes in a variety of malignancies, responses only typically occur in a minority of patients in any given histology. Additionally, treatment is associated with inflammatory toxicity and high cost. Therefore, determining which patients would derive clinical benefit from immunotherapy is a compelling clinical question. Although numerous candidate biomarkers have been described, there are currently three FDA-approved assays based on PD-1 ligand expression (PD-L1) that have been clinically validated to identify patients who are more likely to benefit from a single-agent anti-PD-1/PD-L1 therapy. Because of the complexity of the immune response and tumor biology, it is unlikely that a single biomarker will be sufficient to predict clinical outcomes in response to immune-targeted therapy. Rather, the integration of multiple tumor and immune response parameters, such as protein expression, genomics, and transcriptomics, may be necessary for accurate prediction of clinical benefit. Before a candidate biomarker and/or new technology can be used in a clinical setting, several steps are necessary to demonstrate its clinical validity. Although regulatory guidelines provide general roadmaps for the validation process, their applicability to biomarkers in the cancer immunotherapy field is somewhat limited. Thus, Working Group 1 (WG1) of the Society for Immunotherapy of Cancer (SITC) Immune Biomarkers Task Force convened to address this need. In this two volume series, we discuss pre-analytical and analytical (Volume I) as well as clinical and regulatory (Volume II) aspects of the validation process as applied to predictive biomarkers for cancer immunotherapy. To illustrate the requirements for validation, we discuss examples of biomarker assays that have shown preliminary evidence of an association with clinical benefit from immunotherapeutic interventions. The scope includes only those assays and technologies that have established a certain level of validation for clinical use (fit-for-purpose). Recommendations to meet challenges and strategies to guide the choice of analytical and clinical validation design for specific assays are also provided.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 311 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 311 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 69 22%
Student > Ph. D. Student 44 14%
Student > Master 38 12%
Other 35 11%
Student > Bachelor 22 7%
Other 39 13%
Unknown 64 21%
Readers by discipline Count As %
Medicine and Dentistry 67 22%
Biochemistry, Genetics and Molecular Biology 58 19%
Agricultural and Biological Sciences 44 14%
Immunology and Microbiology 21 7%
Chemistry 10 3%
Other 36 12%
Unknown 75 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 22 November 2022.
All research outputs
#3,798,945
of 25,374,647 outputs
Outputs from Journal for Immunotherapy of Cancer
#1,045
of 3,421 outputs
Outputs of similar age
#59,703
of 311,950 outputs
Outputs of similar age from Journal for Immunotherapy of Cancer
#14
of 33 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,421 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. This one has gotten more attention than average, scoring higher than 69% 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 311,950 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 33 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 57% of its contemporaries.