Year: 2024
Type: article
Abstract: Cyclic fluorescence microscopy enables multiple targets to be detected simultaneously. This, in turn, has deepened our understanding of tissue composition, cell-to-cell interactions, and cell signaling. Unfortunately, analysis of these datasets can be time-prohibitive due to the sheer volume of data. In this paper, we present CycloNET, a computational pipeline tailored for analyzing raw fluorescent images obtained through cyclic immunofluorescence. The automated pipeline pre-processes raw image files, quickly corrects for translation errors between imaging cycles, and leverages a pre-trained neural network to segment individual cells and generate single-cell molecular profiles. We applied CycloNET to a dataset of 22 human samples from head and neck squamous cell carcinoma patients and trained a neural network to segment immune cells. CycloNET efficiently processed a large-scale dataset (17 fields of view per cycle and 13 staining cycles per specimen) in 10 min, delivering insights at the single-cell resolution and facilitating the identification of rare immune cell clusters. We expect that this rapid pipeline will serve as a powerful tool to understand complex biological systems at the cellular level, with the potential to facilitate breakthroughs in areas such as developmental biology, disease pathology, and personalized medicine.
Source: Scientific Reports
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,590
Awards: Early Detection through Novel OCEAN Technology - Ovarian Cancer Exosomal Analysis with Nanoplasmonics, Standardized Molecular Analyses of Glioma EVs, Imaging and Liquid Biopsy for Glioma Diagnosis and Treatment Monitoring, G5675554757, 3D Fourier Imaging System for High Throughput Analyses of Cancer Organoids, High throughput nanoplasmonic exosome testing (NEXT) of immunotherapies in bladder cancer, High-throughput Phenotyping of iPSC-derived Airway Epithelium by Multiscale Machine Learning Microscopy, FAST-FNA immune cell profiling in HNSCC, Bioorthogonal probe development for highly parallel in vivo imaging, Expanding early cancer detection with high throughput OCEANA - Ovarian Cancer Exosome Analysis with Nanoplasmonic Array, Composing CODAs to cervical cancer screening through an integrated CRISPR and fluorescent nucleic acid approach
OpenAlex ID: W4403246115