Spatial Clustering Analysis with Spectral Imaging-based Single-Step Multiplex Immunofluorescence (SISS-mIF) for Assisting Histological Diagnosis

Abstract

Precision medicine, based on spatial biology, is crucial for accurately diagnosing cancer and predicting drug responses. Here, we introduce the Spectral Imaging-based Single-Step Multiplex Immunofluorescence (SISS-mIF) technique, utilizing hyperspectral imaging to capture fluorescence spectra simultaneously. This approach optimizes tissue autofluorescence spectra for each image automatically, allowing the use of fluorescent direct-labeled antibodies for multicolor staining in a single step. Unlike conventional methods, the images are generated as standardized intensity independent of capture conditions, enabling consistent comparisons under different imaging conditions. This technique allows the detection of CD3, CD5, and CD7 in T-cell lymphoma on a single slide. The use of fluorescent direct-labeled antibodies enables triple staining of CD3, CD5, and CD7 without cross-reactivity, maintaining the same intensity as single stains. Furthermore, we developed a joint Non-Negative Matrix Factorization-based Spatial Clustering Analysis (jNMF-SCA) with a modified spectral unmixing system, highlighting its potential as a supportive diagnostic tool for T-cell lymphoma.