Unlocking FFPE Samples for HiFi Sequencing

Formalin-fixed, paraffin-embedded (FFPE) tissue samples are among the most abundant resources in cancer research. Collected routinely during clinical care and often linked to detailed clinical records, these archived specimens provide a valuable window into tumor biology, treatment response, and disease progression.

However, despite advancements in genomic sequencing technologies and the vast number of FFPE samples stored in hospitals, pathology labs, and biobanks across the world, researchers have struggled to fully exploit the potential of FFPE for genomics. Many of the most advanced sequencing technologies have historically required DNA quality that FFPE preservation can compromise, limiting the insights that can be extracted from these samples.

As we know, cancer is a highly complex genetic disease. As a result, there is a constant demand on researchers to broaden the genetic information they can capture, identifying unique variants, mutations, structural changes, and other alterations that can offer critical insights. Long-read sequencing has emerged as a powerful tool, helping them obtain a more comprehensive view of the genome to complement conventional short-read methods. However, applying long-read sequencing to FFPE samples can present significant technical challenges.

To help overcome these barriers, PacBio and Covaris have developed an integrated workflow. By combining optimized extraction, library prep, and high-fidelity (HiFi) sequencing technologies, the approach enables researchers to revisit archived collections with a more powerful genomic toolkit.

Technology Networks spoke with Amit Patel, senior director of product marketing at PacBio, and Greg Endress, senior vice president of technology and innovation at Covaris, about the opportunity to unlock FFPE archives and what this could mean for the future of cancer genomics.

Tackling the FFPE sequencing challenge

What challenges have limited the use of long-read sequencing in FFPE samples?

FFPE tissue is one of the most widely available sample types in oncology, yet it has historically been one of the most challenging matrices when it comes to analysis using long-read sequencing technologies. The fixation process can fragment DNA and introduce damage, making it difficult to generate the longer molecules traditionally required for long-read sequencing workflows.

According to Patel, this limitation has prevented researchers from fully leveraging long-read technologies in archived clinical specimens.

“FFPE samples have been largely untouched by long-read sequencing,” he said.

The challenge is particularly significant because many clinically important cancer samples exist only in FFPE form. While short-read sequencing has provided valuable insights, it can struggle to accurately characterize complex genomic regions and structural alterations that play important roles in cancer development and progression.

Recognizing this unmet need, PacBio and Covaris explored whether advances in sample preparation and library construction could make FFPE samples compatible with HiFi sequencing. The resulting collaboration was built upon existing expertise from both companies, combining optimized extraction methods with workflows specifically designed for degraded DNA.

By integrating these capabilities, researchers can now generate sequencing-ready material from samples that were previously considered unsuitable for long-read analysis.

Why this matters:

• FFPE preservation can damage and fragment DNA, limiting long-read sequencing applications.
• Archived clinical specimens contain valuable genomic information that has often remained inaccessible.
• New workflows are helping make long-read sequencing feasible and reliable for challenging FFPE samples.

Building a workflow from extraction to sequencing

How do your individual technologies work together to support FFPE analysis?

The workflow begins with Covaris’ truXTRAC^® FFPE extraction technology, which is designed to recover high-quality nucleic acids from preserved tissue samples. The process incorporates Adaptive Focused Acoustics^® (AFA^®) technology to improve tissue disruption and nucleic acid recovery while maintaining sample quality.

“Our AFA technology helps standardize FFPE tissue disruption so researchers can recover nucleic acids more consistently from challenging archived samples,” Endress explained.

Following extraction, PacBio’s AmpliFi workflow enables researchers to work with low-input DNA samples by increasing the amount of material available for downstream analysis. The DNA then enters the Kinnex workflow, which concatenates shorter DNA fragments into longer molecules suitable for HiFi sequencing.

This step addresses one of the central challenges of FFPE analysis: while the original DNA molecules may be fragmented, linking shorter fragments together creates sequencing templates that can be efficiently processed using long-read technologies.

The resulting workflow provides access to genomic information that is often difficult to capture using conventional approaches.

“You really get to see answers and data that you’ve never seen before from FFPE samples,” Patel said.

In validation studies, the workflow enabled detection of more than 11,000 structural variants per sample while also supporting extensive variant phasing.

How the technologies complement each other:

• truXTRAC extraction improves recovery of nucleic acids from FFPE tissue.
• PacBio’s Amplify and Kinnex workflows enable sequencing of fragmented DNA.
• HiFi sequencing provides access to structural variants and phased mutations often missed by traditional approaches.

Turning archived tumor samples into a genomic resource

What opportunities could be created by enabling long-read sequencing from FFPE archives?

The scientific value of FFPE tissue extends far beyond individual samples. Hospitals, pathology labs, and biobanks worldwide have accumulated vast collections of archived specimens, many linked to detailed clinical metadata and long-term patient outcomes.

“There are estimated to be more than a billion FFPE samples,” said Endress. “Some that are decades old.”

For researchers, these archives represent an incredible opportunity to revisit historical patient cohorts using a unique combination of technologies that did not exist when the samples were originally collected.

“Now that we have the workflow, you can enable more research and expanded profiling of the cancer samples,” Endress added.

The ability to reanalyze archived specimens may support a wide range of applications, including biomarker discovery, studies of tumor evolution, investigations into treatment resistance, and retrospective analyses of clinical trial populations.

Long-read sequencing may also help reveal genomic features that were not identified in the past. Structural variants, for example, are increasingly recognized as important contributors to cancer biology, yet many remain difficult to detect using short-read technologies alone.

Patel also noted that continued reductions in sequencing costs could further accelerate adoption. As workflows become more streamlined and economically accessible, researchers may be able to analyze larger cohorts and generate increasingly comprehensive genomic datasets.

Taken together, these developments could transform FFPE archives from static repositories into dynamic resources for future cancer discoveries.

The ability to unlock large FFPE archives could dramatically increase the volume of genomic data available to researchers. However, generating more data is only part of the challenge. As genomic profiling becomes increasingly comprehensive, researchers must also find ways to interpret, contextualize, and communicate these findings effectively.

The research opportunity:

• Billions of archived FFPE specimens exist worldwide.
• Long-read sequencing enables researchers to revisit historical cancer cohorts with new tools.
• Archived samples could support biomarker discovery, therapeutic development, and translational research.

 
Making genomic data more actionable

As researchers gain access to larger and more information-rich datasets, how can they ensure those insights translate into clinical impact?

Access to archived FFPE samples has the potential to expand cancer genomics datasets on an unprecedented scale. Long-read sequencing can reveal structural variants and other layers of genomic complexity that were previously difficult to capture. While these advances provide a more complete picture of tumor biology, they also create new challenges around data analysis and interpretation.

Patel believes artificial intelligence (AI) is already helping address part of this challenge by enabling researchers to extract meaningful insights from increasingly large and complex datasets.

“The greatest impact it [AI] is having is just taking huge data sets and making them more meaningful and actionable,” he said.

This is particularly relevant as long-read sequencing generates richer datasets that can increase the complexity of downstream interpretation.

Both Patel and Endress emphasized that translating genomic information into practical knowledge remains a significant challenge across healthcare.

“I think we’re not giving enough information to the end users, like the patients,” Patel said.

Endress noted that genomic reports can be difficult for both clinicians and patients to navigate. “You can get a CGP [Comprehensive Genomic Profiling] report or an MRD [Minimal Residual Disease] report, and they’re 20 pages; it’s a lot of technical detail,” he explained.

As precision medicine continues to advance, improving communication may become just as important as improving sequencing technology. Making genomic information more understandable, accessible, and actionable will be essential for ensuring that scientific advances ultimately benefit patients.

“It’s hard sometimes for patients to put test results into context,” said Endress. “They are interested in receiving the best care possible. The science part is secondary. It’s a tool to understand the disease.”

Turning data into insight:

• AI is helping researchers derive insights from increasingly complex genomic datasets.
• Richer sequencing data creates new opportunities but also new interpretation challenges.
• Improving communication with clinicians and patients will be critical for realizing the full potential of precision medicine.

This content includes text that has been created with the assistance of generative AI and has undergone editorial review before publishing. Technology Networks' AI policy can be found here.