Assessing the effects of a 3D pathology tissue-processing workflow on downstream molecular analyses
Year: 2026
Type: preprint
Abstract: Non-destructive 3D pathology methods have emerged in recent years with the potential to enhance standard 2D histopathology by greatly increasing the amount of tissue sampled by imaging and by providing volumetric morphological context. Another key advantage is that tissues remain intact, allowing re-embedding after imaging for potential long-term storage and future histological or molecular analyses. However, the impact of 3D pathology protocols on biomolecules - including DNA, RNA, and proteins - and their compatibility with downstream assays, has not been systematically evaluated. Here, we applied a previously optimized 3D pathology protocol - involving deparaffinization, fluorescent H&E-analog staining, optical clearing, and open-top light-sheet microscopy - to formalin-fixed paraffin-embedded (FFPE) specimens of breast, prostate, and head and neck cancer. Following the protocol, tissues were re-embedded in paraffin and compared with paired FFPE controls that did not undergo 3D pathology processing. DNA and RNA were extracted and subjected to quality assessments. Amplifiability was tested by PCR and reverse transcription quantitative PCR (RT-qPCR) of housekeeping genes. Although the results showed a slight decrease in the average yield and increased fragmentation of both DNA and RNA, amplifiability was largely preserved. Sanger sequencing of the PCR products confirmed accurate sequence determinations, while total RNA sequencing indicated that the global transcriptomic profile was largely unchanged. IHC staining of common biomarkers produced comparable signals, suggesting those proteins are well preserved after the 3D pathology workflow. These results demonstrate the feasibility of combining 3D pathology with downstream molecular applications.
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: Prostate cancer risk stratification via computational 3D pathology, The microbiome ecosystem of Barrett's esophagus and progression to cancer, Computational 3D pathology for Barrett's esophagus risk stratification, G7967259766, G9000006838, G9000022155, G9000095745, G9000338765, Multiscale modeling of spatiotemporal evolution in Barrett's esophagus, Genetics, Epigenetics, and Risk Prediction for Esophageal Adenocarcinoma, Understanding adenoma progression: Interplay among tissue microenvironment, clonal architecture, and gut microbiome, Modeling Neoplastic Progression in Barrett's Esophagus - Renewal -2, Translational Science of Gastrointestinal Cancer Initiation and Progression
OpenAlex ID: W7128930359
