Maximizing the clinical utility and performance of cytology samples for comprehensive genetic profiling

David Kim (), Chad M. Vanderbilt, Soo-Ryum Yang, Subhiksha Nandakumar, Khedoudja Nafa, Rusmir Feratovic, Natasha Rekhtman, Ivelise Rijo, Jacklyn Casanova, Anita Yun, A. Rose Brannon, Michael F. Berger, Marc Ladanyi, Oscar Lin and Maria E. Arcila
Additional contact information
David Kim: Memorial Sloan Kettering Cancer Center
Chad M. Vanderbilt: Memorial Sloan Kettering Cancer Center
Soo-Ryum Yang: Memorial Sloan Kettering Cancer Center
Subhiksha Nandakumar: Memorial Sloan Kettering Cancer Center
Khedoudja Nafa: Memorial Sloan Kettering Cancer Center
Rusmir Feratovic: Memorial Sloan Kettering Cancer Center
Natasha Rekhtman: Memorial Sloan Kettering Cancer Center
Ivelise Rijo: Memorial Sloan Kettering Cancer Center
Jacklyn Casanova: Memorial Sloan Kettering Cancer Center
Anita Yun: Memorial Sloan Kettering Cancer Center
A. Rose Brannon: Memorial Sloan Kettering Cancer Center
Michael F. Berger: Memorial Sloan Kettering Cancer Center
Marc Ladanyi: Memorial Sloan Kettering Cancer Center
Oscar Lin: Memorial Sloan Kettering Cancer Center
Maria E. Arcila: Memorial Sloan Kettering Cancer Center

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: Abstract Comprehensive molecular profiling by next-generation sequencing has revolutionized tumor classification and biomarker evaluation. However, routine implementation is challenged by the scant nature of diagnostic material obtained through minimally invasive procedures. Here, we describe our long-term experience in profiling cytology samples with an in-depth assessment of the performance, quality metrics, biomarker identification capabilities, and potential pitfalls. We highlight the impact of several optimization strategies to maximize performance with 4,871 prospectively sequenced clinical cytology samples tested by MSK-IMPACTTM. Special emphasis is given to the use of residual supernatant cell-free DNA (ScfDNA) as a valuable source of tumor DNA. Overall, cytology samples are similar in performance to surgical samples in identifying clinically relevant genomic alterations, achieving success rates up to 93% with full optimization. While cell block (CB) samples have excellent performance overall, low-level cross-contamination is identified in a small proportion of cases (4.7%), a common pitfall intrinsic to the processing of paraffin blocks, suggesting that more stringent precautions and processing modifications should be considered in quality control initiatives. By contrast ScfDNA samples have negligible contamination. Finally, ScfDNA testing exclusively used as a rescue strategy, delivered successful results in 71% of cases where tumor tissue from CB was depleted.

Date: 2025
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DOI: 10.1038/s41467-024-55456-8

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