Fluorescent multiplexing of 3D spheroids: Analysis of biomarkers using automated immunohistochemistry staining platform and multispectral imaging

Abstract

In preclinical cancer studies, three-dimensional (3D) cell spheroids and aggregates are preferred over monolayer cell cultures due to their architectural and functional similarity to solid tumors. We performed a proof-of-concept study to generate physiologically relevant and predictive preclinical models using non-small cell lung adenocarcinoma, and colon and colorectal adenocarcinoma cell line-derived 3D spheroids and aggregates. Distinct panels were designed to determine the expression profiles of frequently studied biomarkers of the two cancer subtypes. The lung adenocarcinoma panel included ALK, EGFR, TTF-1, and CK7 biomarkers, and the colon and colorectal adenocarcinoma panel included BRAF V600E, MSH2, MSH6, and CK20. Recent advances in immunofluorescence (IF) multiplexing and imaging technology enable simultaneous detection and quantification of multiple biomarkers on a single slide. In this study, we performed IF staining of multiple biomarkers per section on formalin-fixed paraffin-embedded 3D spheroids and aggregates. We optimized protocol parameters for automated IF and demonstrated staining concordance with automated chromogenic immunohistochemistry performed with validated protocols. Next, post-acquisition spectral unmixing of the captured fluorescent signals were utilized to delineate four differently stained biomarkers within a single multiplex IF image, followed by automated quantification of the expressed markers. This workflow has the potential to be adapted to preclinical high-throughput screening and drug efficacy studies utilizing 3D spheroids from cancer cell lines and patient-derived organoids. The process allows for cost, time, and resource savings through concurrent staining of several biomarkers on a single slide, the ability to study the

Patient-derived organoids of lung cancer based on organoids-on-a-chip: enhancing clinical and translational applications

“…(2) Low-effectiveness: Manually operating the traditional organoid culture systems is complicated (Bhaumik et al, 2020), especially in investigated expression patterns of key biomarkers or testing drug sensitivity and response at indicated time points to each well. Meanwhile, it is generally recognized that PDOs successfully cultivated during passage 3 were regarded as success in organoid formation (Kim et al, 2019).…”

“…Furthermore, PDOs can also be used as discovery tools for novel biomarker and combination therapy approaches. The researchers (Bhaumik et al, 2020) also constructed lung cancer PDOs to detect the expression of multiple critical biomarkers on a single slide, demonstrating that the expression status and spatial arrangement of multiple disease-relevant biomarkers can be studied in a preclinical nontumor microenvironment setting. Overall, PDOs have proven to be a valuable tool for biomarker discovery in lung cancer research, with the potential to improve diagnosis and treatment options for patients.…”

The application of patient-derived organoid in the research of lung cancer

“…Lung cancer PDO-related microchips and microfluidic platforms have been developed to enable large-scale drug testing within a week [ 9 , 69 ]. The researchers also developed an automatic IF multiplexing for FFPE sections from lung cancer PDO to detect the expression of multiple critical biomarkers on a single slide [ 88 ]. With machine learning, SigMaps can integrate and generate molecular interactions of specific tumor-associated proteins in lung cancer and perform large-scale validation of predicted proteins in PDO [ 89 ].…”

Mem-GAN: A Pseudo Membrane Generator for Single-cell Imaging in Fluorescent Microscopy

“…Moreover, during the pre-processing process of the raw images stained with different membrane biomarkers, carefully choosing different antibodies and well-designed aggregation strategies for these images ensures the maximum detection of the target and the appropriate definition of the cell boundaries [1]. Inappropriate choices exacerbate the difficulty of obtaining high-quality images with high cell border contrast.…”