Abstract A072: Are fresh specimens really all that fresh? An examination of cell loss over time in high-parameter cytometry

Abstract Fresh specimens have traditionally been regarded as the gold standard for cytometry analysis, a notion that has remained largely unquestioned with the advent of high-parameter cytometry tools. However, cell subsets vary in stability, and with high-parameter cytometry now capable of resolving a wider range of subsets—including rare populations previously unassessed in conventional flow cytometry stability assays—it is essential to thoroughly evaluate the stability of each cell type individually. The assumption that all "fresh" specimens are equivalent for high-parameter cytometry deserves scrutiny, as processing time after collection significantly affects sample quality. Specifically, fresh blood processed after 72 hours exhibits distinct differences compared to blood processed within 1 hour. We introduce the term "Fresh-hour" to precisely indicate processing time post-collection, with "Fresh-1" and "Fresh-72" representing samples processed 1 and 72 hours post-collection, respectively. To quantify the relationship between processing delay and sample quality, we conducted a performance analysis using blood drawn from three healthy donors. Each blood sample was divided into six aliquots: one processed 3 hours post-collection as a baseline, with the remaining aliquots processed at 5, 7, 9, 27, and 51 hours post-draw. All aliquots were analyzed simultaneously on a Helios mass cytometer to minimize technical variation due to batch effects. We compared the percent change in population frequency at each Fresh-hour time point to the baseline sample. A threshold of 25% change in frequency was used to determine whether samples remained within specifications. Our analysis revealed that all cell populations maintained stability through Fresh-5 (processed 5 hours after collection). By Fresh-7, however, several monocyte populations began showing significant changes in frequency, including classical monocytes (38.1% change) and intermediate monocytes (42.3% change). By Fresh-51, all monocyte populations exceeded the 25% threshold for frequency change (range = 65.2%–97.9%). While most lymphocyte populations remained stable, rare subsets—including double-negative/positive T cells, CD4+ TEMRA, and specific NK and DC populations—exceeded the 25% threshold by Fresh-51. Notably, our observations align with the Cytek 25-color immunoprofiling assay validation report, which documented similar quality degradation patterns by Fresh-72, particularly among rare cell populations, where there was a >25% change in frequency. To further investigate this impact across cytometry platforms, we performed parallel analyses on the Cytek Aurora using Fresh-0, Fresh-24, Fresh-48, and Fresh-72 timepoints. Our multi-platform approach demonstrates that Fresh-72 samples show substantially different characteristics compared to Fresh-1 samples, challenging the conventional broad classification of "fresh" specimens in high-parameter cytometry. Citation Format: Ramji Srinivasan, Kristina Magee, Gage Black, Will Chronister, Carly Lancaster, Lee Leavitt, Justin Jarrell, Li-Chun Cheng. Are fresh specimens really all that fresh? An examination of cell loss over time in high-parameter cytometry [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr A072.

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Journal
Cancer Immunology Research
Published
2025-02-23
DOI
https://doi.org/10.1158/2326-6074.io2025-a072
Primary Topic
Single-cell and spatial transcriptomics
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article
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article

Abstract A072: Are fresh specimens really all that fresh? An examination of cell loss over time in high-parameter cytometry

Lichun Cheng, Carly L. Lancaster, Justin A. Jarrell, Ramji Srinivasan et al.
Cancer Immunology Research
Single-cell and spatial transcriptomics
article

Abstract A072: Are fresh specimens really all that fresh? An examination of cell loss over time in high-parameter cytometry

Lichun Cheng, Carly L. Lancaster, Justin A. Jarrell, Ramji Srinivasan, Kristina Magee, Lee Leavitt, Gage Black, Will Chronister
article en

Abstract

Abstract Fresh specimens have traditionally been regarded as the gold standard for cytometry analysis, a notion that has remained largely unquestioned with the advent of high-parameter cytometry tools. However, cell subsets vary in stability, and with high-parameter cytometry now capable of resolving a wider range of subsets—including rare populations previously unassessed in conventional flow cytometry stability assays—it is essential to thoroughly evaluate the stability of each cell type individually. The assumption that all "fresh" specimens are equivalent for high-parameter cytometry deserves scrutiny, as processing time after collection significantly affects sample quality. Specifically, fresh blood processed after 72 hours exhibits distinct differences compared to blood processed within 1 hour. We introduce the term "Fresh-hour" to precisely indicate processing time post-collection, with "Fresh-1" and "Fresh-72" representing samples processed 1 and 72 hours post-collection, respectively. To quantify the relationship between processing delay and sample quality, we conducted a performance analysis using blood drawn from three healthy donors. Each blood sample was divided into six aliquots: one processed 3 hours post-collection as a baseline, with the remaining aliquots processed at 5, 7, 9, 27, and 51 hours post-draw. All aliquots were analyzed simultaneously on a Helios mass cytometer to minimize technical variation due to batch effects. We compared the percent change in population frequency at each Fresh-hour time point to the baseline sample. A threshold of 25% change in frequency was used to determine whether samples remained within specifications. Our analysis revealed that all cell populations maintained stability through Fresh-5 (processed 5 hours after collection). By Fresh-7, however, several monocyte populations began showing significant changes in frequency, including classical monocytes (38.1% change) and intermediate monocytes (42.3% change). By Fresh-51, all monocyte populations exceeded the 25% threshold for frequency change (range = 65.2%–97.9%). While most lymphocyte populations remained stable, rare subsets—including double-negative/positive T cells, CD4+ TEMRA, and specific NK and DC populations—exceeded the 25% threshold by Fresh-51. Notably, our observations align with the Cytek 25-color immunoprofiling assay validation report, which documented similar quality degradation patterns by Fresh-72, particularly among rare cell populations, where there was a >25% change in frequency. To further investigate this impact across cytometry platforms, we performed parallel analyses on the Cytek Aurora using Fresh-0, Fresh-24, Fresh-48, and Fresh-72 timepoints. Our multi-platform approach demonstrates that Fresh-72 samples show substantially different characteristics compared to Fresh-1 samples, challenging the conventional broad classification of "fresh" specimens in high-parameter cytometry. Citation Format: Ramji Srinivasan, Kristina Magee, Gage Black, Will Chronister, Carly Lancaster, Lee Leavitt, Justin Jarrell, Li-Chun Cheng. Are fresh specimens really all that fresh? An examination of cell loss over time in high-parameter cytometry [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr A072.

Cancer Immunology ResearchVol. 13(2_Supplement)
BioFire Diagnostics (United States) (US)
Openalex Percentile: Top 97%
Single-cell and spatial transcriptomics
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