JOURNAL ARTICLE

The Bridge: Supernatant Derived From Cytological Sample Preparations.

  • Published In: Cytopathology, 2025, v. 36, n. 3. P. 222 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Roy‐Chowdhuri, Sinchita 3 of 3

Abstract

The scope and extent of molecular cytopathology in the era of precision medicine has been expanding in recent years. The versatility of cytology specimen preparations has provided ample opportunity for the cytopathology community to evolve, innovate and 'do more with less' using limited amounts of tissue. More recently, cytology‐derived supernatant liquid biopsy samples have been identified as a substantial source of high‐quality genomic material that can be interrogated for genotyping for therapeutic decision‐making, as well as other roles in cancer screening for early‐stage disease, longitudinal monitoring for therapeutic response and disease prognostication. These novel substrates, including supernatants from body fluids such as urine, pleural effusion, ascitic fluid, cerebrospinal fluid, as well as fine‐needle aspiration (FNA) specimens, serve as a bridge between tissue‐based testing and conventional liquid biopsy testing from the patient's plasma. Cytologically derived liquid biopsy samples can only be used in situations where the tissue sample is inadequate for genotyping, or when plasma‐based liquid biopsy fails to identify an oncogenic driver alteration, but they can be used as a stand‐alone complementary specimen source that can provide reliable genomic information for therapeutic decisions. This review aims to highlight some of the advances in the field and the clinical applications of the cytology‐derived supernatant specimen. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Cytopathology. 2025/05, Vol. 36, Issue 3, p222
  • Document Type:Literature Review
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:0956-5507
  • DOI:10.1111/cyt.13475
  • Accession Number:184403890
  • Copyright Statement:Copyright of Cytopathology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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