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◆ Molecular Diagnosis & Therapy2026-03-14· Best practice

Pre-analytical Best Practices for RNA Sequencing from Small Biopsies and Cytologic Specimens

Gloria H. Sura, Kelly B. Engel, Sarah R. Greytak, Sandra M. Gaston, Kelsey Dillehay McKillip, Abhilasha Rao, Ping Guan, W. Fraser Symmans, Rachael Clark, Maria E. Arcila, Sayak Ghatak, Karol Bomsztyk, Lokesh Agrawal

原始摘要(英文原文)· Original abstract
RNA sequencing is becoming increasingly common in precision oncology, in both clinical and research settings, for transcriptome profiling, gene-fusion detection, and biomarker discovery. RNA-sequencing analysis of specimens obtained via minimally invasive procedures such as small biopsy, fine needle aspiration, and exfoliation offers a powerful method for analyzing gene expression patterns and detecting RNA-level changes associated with cancers that are either difficult to collect or require longitudinal sampling. However, pre-analytical factors (e.g., details of specimen collection, processing, and storage workflow) influence not only RNA-sequencing success rates but also the quality and accuracy of sequencing results, which may affect patient care and research progress. Minimally invasive specimens are associated with a unique set of pre-analytical challenges owing to their small size, limited RNA yield, and distinct workflows. To address the need for evidence-based guidance, this review by a working group of National Cancer Institute grantees and intramural and extramural researchers identifies pre-analytical best practices for minimally invasive specimens destined for RNA-sequencing analysis, based on the available literature and their collective experience. Strategies for assessing specimen adequacy and RNA quality, maximizing tumor content, and minimizing specimen loss and RNA degradation due to pre-analytical handling are specified for small tissue and cytology specimens. By integrating current evidence and institutional insights, this review provides a practical framework for enhancing RNA-sequencing reliability and reproducibility in both clinical and research workflows.
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