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Updated: Oct 24, 2025
High-Throughput Automated Multiplex Immunofluorescence Assays for Translational Research
Published on: June 10, 2025
Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies
Rossana Lazcano1, Frank Rojas1, Caddie Laberiano1
1Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Insights
Pathology quality control (PQC) is crucial for multiplex immunofluorescence (mIF) analysis of tumor tissues. Ensuring sufficient malignant cells and appropriate tissue size are key to obtaining accurate immune profiling data from biopsies.
Area of Science:
- Pathology
- Immunology
- Biomedical Imaging
Background:
- Multiplex immunofluorescence (mIF) enables multi-biomarker analysis on single slides.
- Digital image analysis of core needle biopsies is vital for immune profiling.
- Established criteria for sample inclusion in mIF assays are currently lacking.
Purpose of the Study:
- To retrospectively analyze pathology quality control (PQC) data for mIF assays.
- To identify common exclusion criteria and their impact on tumor tissue immune profiling.
- To highlight the importance of PQC for accurate and reproducible mIF image analysis.
Main Methods:
- Retrospective review of PQC data from hematoxylin and eosin (H&E) and mIF samples.
- Analysis of 931 core needle biopsy reports.
- Identification of exclusion reasons and sample characteristics.
Main Results:
- 13.21% of 931 core needle biopsy samples were excluded during mIF PQC.
- Absence or low numbers (<100) of malignant cells were the primary exclusion reason (34.15%).
- Other exclusion factors included small tissue size (13.01%) and poor tissue quality (fibrosis, necrosis).
Conclusions:
- PQC is an essential step for reliable mIF image analysis.
- The absence of malignant cells is the most significant limiting factor for mIF analysis.
- Pathologists must consider sample characteristics to ensure reproducible image analysis data.
Abstract:
Immune profiling of formalin-fixed, paraffin-embedded tissues using multiplex immunofluorescence (mIF) staining and image analysis methodology allows for the study of several biomarkers on a single slide. The pathology quality control (PQC) for tumor tissue immune profiling using digital image analysis of core needle biopsies is an important step in any laboratory to avoid wasting time and materials. Although there are currently no established inclusion and exclusion criteria for samples used in this type of assay, a PQC is necessary to achieve accurate and reproducible data. We retrospectively reviewed PQC data from hematoxylin and eosin (H&E) slides and from mIF image analysis samples obtained during 2019. We reviewed a total of 931 reports from core needle biopsy samples; 123 (13.21%) were excluded during the mIF PQC. The most common causes of exclusion were the absence of malignant cells or fewer than 100 malignant cells in the entire section (n = 42, 34.15%), tissue size smaller than 4 × 1 mm (n = 16, 13.01%), fibrotic tissue without inflammatory cells (n = 12, 9.76%), and necrotic tissue (n = 11, 8.94%). Baseline excluded samples had more fibrosis (90 vs 10%) and less necrosis (5 vs 90%) compared with post-treatment excluded samples. The most common excluded organ site of the biopsy was the liver (n = 19, 15.45%), followed by soft tissue (n = 17, 13.82%) and the abdominal region (n = 15, 12.20%). We showed that the PQC is an important step for image analysis and that the absence of malignant cells is the most limiting sample characteristic for mIF image analysis. We also discuss other challenges that pathologists need to consider to report reliable and reproducible image analysis data.
