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The Science Behind FFPE Single-Cell RNA-Seq

7’
Protocol and guide

Valuable Insights from FFPE single-cell RNA sequencing

Do the best data really always comes from the freshest tissue? In reality, some of the most clinically valuable biological material isn’t fresh at all. It’s formalin-fixed, paraffin-embedded (FFPE) and stored in pathology archives around the world. FFPE samples hold decades of clinical history and today, with optimized single-cell sequencing of FFPE samples, we can analyze those archived samples at a single-cell level.

A Brief History of FFPE: A Century of preservation

Formalin fixation followed by paraffin embedding has been a cornerstone of diagnostic pathology for over 100 years. Formalin preserves tissue morphology by forming crosslinks, primarily methylene bridges, between amino groups in proteins and nucleic acids. This stabilizes cellular structure and allows room-temperature storage for decades.

As a result, hospitals worldwide have accumulated millions of FFPE blocks, representing vast clinical cohorts across oncology, immunology, neurology, and rare diseases. These archives often include detailed clinical annotations and long-term follow-up data, something freshly collected samples rarely offer.

However, from a molecular perspective, FFPE preservation comes at a cost.

What Formalin does to RNA

Formalin fixation induces chemical modifications including methylol additions and methylene bridge formation, leading to crosslinking between nucleic acids and proteins and fragmentation of RNA (Masuda et al., 1999; Srinivasan et al., 2002). Over time, RNA extracted from FFPE tissue typically shows fragment sizes under 200 nucleotides and low RIN scores. Although RIN is not always fully informative for FFPE-derived RNA due to systematic fragmentation patterns.

Comprehensive analyses have demonstrated that fixation time, processing conditions, and storage duration significantly affect nucleic acid integrity (von Ahlfen et al., 2007; Farragher et al., 2008). While the fixation process itself causes chemical modifications, prolonged storage at room temperature or higher is the most significant factor in RNA fragmentation. To maintain high-quality RNA for cDNA synthesis, FFPE blocks should be stored at 4°C (Figure 1).

Figure 1. Structural and functional impact of formalin fixation on RNA. (A) Capillary electrophoresis profiles demonstrate reduced RNA integrity in formalin-fixed, paraffin-embedded (FFPE) samples compared to fresh or stabilized tissue, with progressive degradation influenced by storage conditions. RNA isolated immediately after embedding was intact, yielding a RIN >7. RNA remained relatively stable at 4°C after one year, with ribosomal bands being visible and RIN values around 5–6. However, storage at room temperature or 37°C led to significant RNA fragmentation. (B) One-step RT-PCR analysis reveals decreasing amplification efficiency with increasing amplicon length in fixed samples, illustrating the length-dependent consequences of fixation-induced RNA fragmentation.Adapted from von Ahlfen et al., PLOS ONE (2007), CC BY 4.0. Panels combined and layout modified for presentation. https://doi.org/10.1371/journal.pone.0001261. 

For years, these biochemical limitations restricted transcriptomic analysis of FFPE samples. Microarray-based studies struggled with reproducibility, and early RNA-seq approaches often underperformed when applied to degraded RNA.

But as next-generation sequencing matured, so did library preparation chemistry.

Single-Cell mRNA-Seq Can Now be Performed Even on Fragmented RNA

Advances in library preparation chemistry and sequencing technologies have reshaped the landscape. A landmark comparative study by Adiconis et al., 2013 (Nature Methods) systematically evaluated RNA-seq library construction methods and demonstrated that certain protocols are robust to degraded input RNA.

Around the same time, researchers began testing FFPE RNA-seq in real clinical cohorts, and it held up. Hedegaard et al. (2014, PLoS ONE) reported strong concordance between FFPE and matched fresh frozen bladder cancer samples (Figure 2) , Zhao et al. (2014, BMC Genomics) demonstrated reproducible gene expression profiling from archived tumors, and Esteve-Codina et al. (2017, Scientific Reports) confirmed high transcriptomic correlation across multiple cancer types.

Figure 2. RNA-seq mapping performance in matched fresh frozen and FFPE samples. (A) Distribution of reads mapping to genomic targets demonstrates comparable overall alignment profiles between fresh frozen (FF) and FFPE specimens. (B) Fraction of non-perfect matches reflects modest increases in mismatch rates in some FFPE samples, consistent with fixation-associated sequence artifacts. (C) Proportion of reads mapping to exon regions indicates preserved transcriptomic signal in FFPE material despite RNA fragmentation.Adapted from Hedegaard et al., PLOS ONE (2014), CC BY 4.0. Layout modified for presentation. https://doi.org/10.1371/journal.pone.0098187

Meanwhile, large-scale initiatives such as The Cancer Genome Atlas helped standardize RNA-seq quality metrics and analysis pipelines. That reinforces transcriptomics, even from challenging samples, as a robust foundation for modern cancer research (Cancer Genome Atlas Research Network, 2013).

Single-Cell Sequencing of FFPE Samples in Translational Research

Fresh frozen tissue is invaluable, but it rarely comes with 10 or 20 years of clinical follow-up attached. FFPE archives do. There are matched samples of primary and metastatic tumors, pre- and post-treatment biopsies, rare subtypes you may never collect again, and carefully documented patient outcomes. When we enable robust RNA-seq from FFPE material, we are not just generating expression data. Actually, we connect molecular profiles to real-world clinical trajectories.

In oncology especially, where tumor heterogeneity and immune microenvironment dynamics shape progression and therapy response, retrospective transcriptomics becomes incredibly powerful. FFPE RNA-seq supports biomarker validation, immune landscape characterization, therapy response prediction, and precision medicine strategies, all grounded in clinically annotated cohorts.

Therefore, single-cell sequencing of FFPE samples does not just provide insights into old samples, it unlocks clinically annotated datasets that cannot be recreated.

Technical Considerations for FFPE Single-Cell Sequencing Analysis

FFPE RNA is already fragmented, and that’s okay. Instead of trying to force it into a “fresh RNA” workflow, successful approaches are built around that reality. That means using random priming instead of relying only on intact poly(A) tails, preparing short-insert libraries that match the natural fragment size, carefully reversing formaldehyde crosslinks during extraction, and applying bioinformatics pipelines designed for degraded input.

When you work with the sample, not against it, FFPE material can support robust gene expression profiling, fusion detection, and immune signature analysis. FFPE single-cell RNA-seq is now a well-established strategy for gaining deep insights into archived clinical samples.

References

  1. Masuda N., Ohnishi T., Kawamoto S., Monden M., Okubo K. (1999).
    Analysis of chemical modification of RNA from formalin-fixed samples and optimization of molecular biology applications. Nucleic Acids Research, 27(22), 4436–4443.
    https://doi.org/10.1093/nar/27.22.4436
  2. Srinivasan M., Sedmak D., Jewell S. (2002).
    Effect of fixatives and tissue processing on the content and integrity of nucleic acids. The American Journal of Pathology, 161(6), 1961–1971.
    https://doi.org/10.1016/S0002-9440(10)64472-0
  3. von Ahlfen S., Missel A., Bendrat K., Schlumpberger M. (2007).
    Determinants of RNA quality from formalin-fixed, paraffin-embedded tissue samples. PLOS ONE, 2(12), e1261.
    https://doi.org/10.1371/journal.pone.0001261
  4. Farragher S.M., Tanney A., Kennedy R.D., Paul Harkin D. (2008).
    RNA expression analysis from formalin-fixed paraffin-embedded tissues. Histochemistry and Cell Biology, 130, 435–445.
    https://doi.org/10.1007/s00418-008-0479-7
  5. Adiconis X., Borges-Rivera D., Satija R., et al. (2013).
    Comparative analysis of RNA sequencing methods for degraded or low-input samples. Nature Methods, 10, 623–629.
    https://doi.org/10.1038/nmeth.2483
  6. Hedegaard J., Thorsen K., Lund M.K., et al. (2014).
    Next-generation sequencing of RNA and DNA isolated from paired fresh-frozen and formalin-fixed paraffin-embedded samples of human cancer. PLOS ONE, 9(5), e98187.
    https://doi.org/10.1371/journal.pone.0098187
  7. Zhao W., He X., Hoadley K.A., et al. (2014).
    Comparison of RNA-Seq by poly(A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling. BMC Genomics, 15, 419.
    https://doi.org/10.1186/1471-2164-15-419
  8. Esteve-Codina A., Arpi O., Martinez-García M., et al. (2017).
    A comparison of RNA-seq results from paired formalin-fixed paraffin-embedded and fresh-frozen glioblastoma tissue samples. PLOS ONE, 12(3), e0170632.
    https://doi.org/10.1371/journal.pone.0170632
  9. The Cancer Genome Atlas Research Network. (2013).
    The Cancer Genome Atlas Pan-Cancer analysis project. Nature Genetics, 45, 1113–1120.
    https://doi.org/10.1038/ng.2764

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A post by Samantha Langer

Samantha is defined by her journey from the lab bench to strategic leadership. Her scientific foundation, rooted in a PhD in Molecular Biology and hands-on experience as an Application Scientist, provides a critical advantage. She has supported researchers across complex areas like oncology, hematology, and niche fields like gravitational biology, giving her a comprehensive view of scientific challenges.

As Senior Marketing Manager, she directs the team and drives the strategic vision for the European market. Samantha is focused on creating and managing digital campaigns that ensure maximum market recognition and commercial success. Her mission is to effectively bridge Singleron’s innovative technologies with the researchers who rely on them to achieve their next major scientific breakthrough.

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