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Antibody-based proteomics applied to tissue microarray (TMA) technology provides a very efficient means of visualizing and locating antigen expression in large collections of normal and pathological tissue samples. To characterize antigen expression on TMAs, the use of image analysis methods avoids the effects of human subjectivity evidenced in manual microscopical analysis. Thus, these methods have the potential to significantly enhance both precision and reproducibility. Although some commercial systems include tools for the quantitative evaluation of immunohistochemistry-stained images, there exists no clear agreement on best practices to allow for correct and reproducible quantification results. Our study focuses on practical aspects regarding (i) image acquisition (ii) segmentation of staining and counterstaining areas and (iii) extraction of quantitative features. We illustrate our findings using a commercial system to quantify different immunohistochemistry markers targeting proteins with different expression patterns (cytoplasmic, nuclear or membranous) in colon cancer or brain tumor TMAs. Our investigations led us to identify several steps that we consider essential for standardizing computer-assisted immunostaining quantification experiments. In addition, we propose a data normalization process based on reference materials to be able to compare measurements between studies involving different TMAs. In conclusion, we recommend certain critical prerequisites that commercial or in-house systems should satisfy in order to permit valid immunostaining quantification.
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http://dx.doi.org/10.1002/pmic.200800936 | DOI Listing |
Funct Integr Genomics
September 2025
Department of Plastic Surgery, the First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China.
Keloid scarring and Metabolic Syndrome (MS) are distinct conditions marked by chronic inflammation and tissue dysregulation, suggesting shared pathogenic mechanisms. Identifying common regulatory genes could unveil novel therapeutic targets. Methods.
View Article and Find Full Text PDFArthritis Rheumatol
August 2025
Department of Rheumatology and Immunology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Objective: To evaluate dynamic changes in autoantibody and proteomic profiles in treatment-naïve systemic sclerosis (SSc) patients and identify biomarkers and mechanisms associated with disease progression.
Methods: Serum samples from 30 baseline and 49 follow-up SSc patients, along with 38 controls, were analyzed. Autoantibody profiles were assessed using an autoantigen microarray targeting 120 autoantibodies, while proteomic analysis was conducted via liquid chromatography-mass spectrometry in data-independent acquisition mode.
Diabetes Metab Syndr Obes
September 2025
Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, People's Republic of China.
Background: The methylation of and its influence on protein stability and degradation could play a crucial role in the pathogenesis of type 2 diabetes mellitus (T2DM), although the underlying molecular mechanisms are not yet fully understood. This study investigates the molecular and bioinformatic features of methylation in T2DM.
Methods: Bioinformatics analyses were conducted on the T2DM database chip.
Cancer Med
September 2025
School of Public Health, Sun Yat-sen University, Guangzhou, China.
Objective: Eukaryotic elongation factor 1 gamma (EEF1G) has emerged as a potential prognostic marker in various malignancies. Yet, its association with breast cancer (BC) prognosis, particularly in the context of body mass index (BMI) status, remains unexplored. Therefore, we investigated the prognostic value and role of EEF1G in BC across different BMI categories.
View Article and Find Full Text PDFBr J Cancer
September 2025
School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Background: Activin A/Smad signaling plays an important role in promoting cancer stemness and chemoresistance in pancreatic ductal adenocarcinoma (PDAC), however the precise regulation on the termination of this pathway has not been fully understood.
Methods: LncRNA SLC7A11-AS1 interacting proteins were identified through RNA pull-down followed by LC-MS/MS. The protein interaction was analyzed by co-immunoprecipitation.