ArticleJournal of visualized experiments : JoVE2016
A Semi-automated Approach to Preparing Antibody Cocktails for Immunophenotypic Analysis of Human Peripheral Blood.
Article in Journal of visualized experiments : JoVE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Trial
- A phase II single-arm study of pembrolizumab with enzalutamide in men with metastatic castration-resistant prostate cancer progressing on enzalutamide alone.Journal for immunotherapy of cancer · 2020Trial
- INBRX-106: a hexavalent OX40 agonist that drives superior antitumor responses via optimized receptor clustering.Journal for immunotherapy of cancer · 2025Article
- A phase Ib trial of pembrolizumab plus paclitaxel or flat-dose capecitabine in 1st/2nd line metastatic triple-negative breast cancer.NPJ breast cancer · 2023Article
- Changes in T-cell subsets and clonal repertoire during chemoimmunotherapy with pembrolizumab and paclitaxel or capecitabine for metastatic triple-negative breast cancer.Journal for immunotherapy of cancer · 2022Article
- Enhancing clinical and immunological effects of anti-PD-1 with belapectin, a galectin-3 inhibitor.Journal for immunotherapy of cancer · 2021Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immunophenotyping of peripheral blood by flow cytometry determines changes in the frequency and activation status of peripheral leukocytes during disease and treatment. It has the potential to predict therapeutic efficacy and identify novel therapeutic targets. Whole blood staining utilizes unmanipulated blood, which minimizes artifacts that can occur during sample preparation. However, whole blood staining must also be done on freshly collected blood to ensure the integrity of the sample. Additionally, it is best to prepare antibody cocktails on the same day to avoid potential instability of tandem-dyes and prevent reagent interaction between brilliant violet dyes. Therefore, whole blood staining requires careful standardization to control for intra and inter-experimental variability. Here, we report deployment of an automated liquid handler equipped with a two-dimensional (2D) barcode reader into a standard process of making antibody cocktails for flow cytometry. Antibodies were transferred into 2D barcoded tubes arranged in a 96 well format and their contents compiled in a database. The liquid handler could then locate the source antibody vials by referencing antibody names within the database. Our method eliminated tedious coordination for positioning of source antibody tubes. It provided versatility allowing the user to easily change any number of details in the antibody dispensing process such as specific antibody to use, volume, and destination by modifying the database without rewriting the scripting in the software method for each assay. A proof of concept experiment achieved outstanding inter and intra- assay precision, demonstrated by replicate preparation of an 11-color, 17-antibody flow cytometry assay. These methodologies increased overall throughput for flow cytometry assays and facilitated daily preparation of the complex antibody cocktails required for the detailed phenotypic characterization of freshly collected anticoagulated peripheral blood.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.