Protein array processing software for automated semiquantitative analysis of serum antibody repertoires

• Published in: Biomicrofluidics Vol. 17; no. 5; p. 054101
• Main Authors: Yadav, Ajeet Singh, Ooi, Chin Hong, An, Hongjie, Nguyen, Nam-Trung, Kijanka, Gregor S.
• Format: Journal Article
• Language: English
• Published: Melville American Institute of Physics 01.09.2023; AIP Publishing LLC
• Subjects: Antibodies; Anticancer properties; Arrays; Automation; Comparative studies; Data analysis; Data processing; Image analysis; Immunotherapy; Medical imaging; Open source software; Proteins; Regular; Software packages; Statistical analysis
• ISSN: 1932-1058; 1932-1058
• DOI: 10.1063/5.0169421

Effective immunotherapies activate natural antitumor immune responses in patients undergoing treatment. The ability to monitor immune activation in response to immunotherapy is critical in measuring treatment efficacy over time and across patient cohorts. Protein arrays are systematically arranged, large collections of annotated proteins on planar surfaces, which can be used for the characterization of disease-specific and treatment-induced antibody repertoires in individuals undergoing immunotherapy. However, the absence of appropriate image analysis and data processing software presents a substantial hurdle, limiting the uptake of this approach in immunotherapy research. We developed a first, automated semiquantitative open-source software package for the analysis of widely used protein macroarrays. The software allows accurate single array and inter-array comparative studies through the tackling of intra-array inconsistencies arising from experimental disparities. The innovative and automated image analysis process includes adaptive positioning, background identification and subtraction, removal of null signals, robust statistical analysis, and protein pair validation. The normalized values allow a convenient semiquantitative data analysis of different samples or timepoints. Enabling accurate characterization of sample series to identify disease-specific immune profiles or their relative changes in response to treatment may serve as a diagnostic or predictive tool of disease.