The Advanced Centre for Treatment, Research and Education in Cancer (ACTREC) supports large-scale translational cancer genomics research, working closely with clinicians to study genomic alterations across patient-derived samples.

The laboratory runs a broad range of sequencing workflows, including whole genome sequencing (WGS), whole exome sequencing (WES), transcriptomics, targeted validation studies, and downstream genomic analyses focused primarily on cancer research.

Much of this work depends on FFPE (Formalin-Fixed Paraffin-Embedded) samples - one of the most operationally challenging sample types in molecular genomics.

FFPE samples are often highly variable and contain degraded nucleic acids, making extraction both technically demanding and time-sensitive. In many clinical cases, the FFPE block is also the only available patient material, leaving very little room for extraction inefficiencies or repeat processing.

Before automation, the lab relied on manual extraction workflows using commercial kits. Processing approximately 10 samples could take close to two days due to long incubation steps, repetitive manual handling, and extensive technician involvement throughout the workflow.

For a small research team managing approximately 24 samples daily with only two technicians, maintaining throughput while minimizing contamination risk and reducing turnaround time had become increasingly difficult.

“For manual extraction, processing 10 samples could take almost two days,” explains Anushree Kadam, a research fellow from the Cancer Genomics Laboratory. “With automation, we can process 24 samples more conveniently while reducing handling time.”

Moving routine FFPE extraction to automation

The laboratory adopted Manta to simplify routine FFPE DNA extraction and reduce dependence on lengthy manual protocols.

The objective was not simply increasing sample volume. The team wanted to reduce handling burden, minimize batch-to-batch variability, lower contamination risk, and improve overall workflow convenience for daily cancer genomics operations.

The transition to automation was straightforward. The team reported minimal learning curve and smooth day-to-day integration into existing workflows.

“It is very easy to handle,” says the Research Fellow. “The biggest advantage is processing multiple samples with very low chances of contamination.”

Supporting high-complexity cancer genomics workflows

At ACTREC, extraction sits upstream of multiple genomics applications, making workflow consistency critical for downstream sequencing reliability for:

Whole Genome Sequencing (WGS) • Whole Exome Sequencing (WES) • Transcriptomics • Targeted Validation Studies

By automating extraction, the laboratory was able to make routine processing more manageable while supporting demanding downstream sequencing workflows.

Reducing manual burden across daily FFPE processing

Before Manta, technicians spent substantial time managing repetitive extraction steps, extended incubation schedules, and manual sample handling. As daily workloads increased, this created growing operational pressure on a small research team.

With Manta, extraction workflows became easier to run and more predictable on a day-to-day basis. Reduced handling requirements helped minimize contamination risk while allowing technicians to process samples more efficiently.

For ACTREC, the operational value extended beyond extraction itself. By reducing time spent on repetitive manual processing, the research team could dedicate more effort toward downstream genomic analysis and cancer research activities.

“We can process multiple samples more conveniently, with less handling and lower chances of contamination,” says the team.

In translational cancer genomics, where valuable FFPE samples move through complex sequencing workflows every day, reducing extraction burden can have a significant impact on both operational efficiency and research continuity. For ACTREC, Manta helped make routine FFPE DNA extraction faster, simpler, and easier to sustain within a small high-throughput research team.