High‐Throughput Single‐Nucleus RNA Profiling of Minimal Puncture FFPE Samples Reveals Spatiotemporal Heterogeneity of Cancer

Puncture biopsy, especially those preserved by formalin fixed paraffin embedding (FFPE) samples, play an important role in various research purposes. Diverse single-nucleus RNA sequencing (snRNA-seq) techniques have been developed for FFPE samples, however, how to perform high-throughput snRNA-seq on small FFPE puncture samples is still a challenge. Here, the previously developed snRNA-seq technique (snRandom-seq) is optimized by implementing a pre-indexing procedure for the minimal puncture FFPE samples. In analyzing 20 samples from various solid tumors, optimized snRandom-seq still detected ≈17 000 genes and 12 000 long non-coding RNAs (lncRNAs), achieving precise clustering based on tissue origin. A head-to-head comparison with 10× Genomics on fresh biopsy samples showed a similar gene detection rate, with significantly enhanced lncRNA detection, indicating that the optimized snRandom-seq technique maintains its established gene detection advantages even when applied to small samples. Utilizing 7 puncture FFPE samples of liver metastases from 3 colorectal cancer patients pre- and post-immunotherapy, the cellular developmental trajectories are reconstructed and revealed dynamic spatiotemporal heterogeneity during treatment, including insights into pseudoprogression of immunotherapy. Therefore, the optimized snRandom-seq offers a solution for high-throughput single-cell RNA and non-coding RNA analysis in minimal puncture FFPE sample.

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Publication Details

Journal
Advanced Science
Published
2024-12-04
DOI
https://doi.org/10.1002/advs.202410713
Citations
5
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
1.43

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article

High‐Throughput Single‐Nucleus RNA Profiling of Minimal Puncture FFPE Samples Reveals Spatiotemporal Heterogeneity of Cancer

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5 citations
Advanced Science
Cancer-related molecular mechanisms research
1.43
article

High‐Throughput Single‐Nucleus RNA Profiling of Minimal Puncture FFPE Samples Reveals Spatiotemporal Heterogeneity of Cancer

Yuyi Zhu, Weixiang Zhong, Longjiang Fan, Weiqin Jiang, Ling Dong, Linghui Zeng, Fangru Lu, Yongcheng Wang, Xiang Zhang, Xiaohan Li, Qing Cheng, Ziye Xu, Hongyu Chen
article en
5 citations

Abstract

Puncture biopsy, especially those preserved by formalin fixed paraffin embedding (FFPE) samples, play an important role in various research purposes. Diverse single-nucleus RNA sequencing (snRNA-seq) techniques have been developed for FFPE samples, however, how to perform high-throughput snRNA-seq on small FFPE puncture samples is still a challenge. Here, the previously developed snRNA-seq technique (snRandom-seq) is optimized by implementing a pre-indexing procedure for the minimal puncture FFPE samples. In analyzing 20 samples from various solid tumors, optimized snRandom-seq still detected ≈17 000 genes and 12 000 long non-coding RNAs (lncRNAs), achieving precise clustering based on tissue origin. A head-to-head comparison with 10× Genomics on fresh biopsy samples showed a similar gene detection rate, with significantly enhanced lncRNA detection, indicating that the optimized snRandom-seq technique maintains its established gene detection advantages even when applied to small samples. Utilizing 7 puncture FFPE samples of liver metastases from 3 colorectal cancer patients pre- and post-immunotherapy, the cellular developmental trajectories are reconstructed and revealed dynamic spatiotemporal heterogeneity during treatment, including insights into pseudoprogression of immunotherapy. Therefore, the optimized snRandom-seq offers a solution for high-throughput single-cell RNA and non-coding RNA analysis in minimal puncture FFPE sample.

Advanced ScienceVol. 12(4)
BGI Group (China) (CN), First Affiliated Hospital Zhejiang University (CN), Hangzhou City University, Zhejiang University (CN), Lanzhou University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Zhejiang Province
Good health and well-being
Openalex Percentile: Top 17%
Cancer-related molecular mechanisms research
1.43
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