🔬 oncology

A liquid biopsy-centered, pan-cancer, open next generation sequencing panel to support clinical decision-making (LION panel)

The study presents the development and validation of the LION panel, a cost-effective, manufacturer-independent 109-gene liquid biopsy NGS solution that demonstrates high sensitivity and specificity to identify targetable variants, monitor disease progression, and guide clinical decision-making across multiple cancer types, particularly when tissue samples are unavailable.

Original authors: Feierabend, S., Künstner, A., Forster, M., Helbing, T., Gebauer, N., Gemoll, T., Axt, F., Nimmagadda, S. C., Ranganathan, L., Schwandt, J., Heber, M., Szymczak, S., Hohensee, I., Fliedner, S. M. J.

Published 2026-06-08✓ Author reviewed ⓘ

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Feierabend, S., Künstner, A., Forster, M., Helbing, T., Gebauer, N., Gemoll, T., Axt, F., Nimmagadda, S. C., Ranganathan, L., Schwandt, J., Heber, M., Szymczak, S., Hohensee, I., Fliedner, S. M. J., Scherer, F., Oberländer, M., Derer-Petersen, S., Busch, H., von Bubnoff, N., Dazert, E.

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

The Big Picture: A "Swiss Army Knife" for Cancer DNA

Imagine a patient’s body as a bustling city. When cancer develops, it’s like a criminal gang taking over a neighborhood. These cancer cells constantly shed tiny pieces of their “ID cards” (DNA) into the bloodstream. By analyzing a blood sample for these DNA fragments—a method called liquid biopsy—doctors can gain important information about the cancer without having to remove tissue from the tumor.

For a long time, doctors had to take a big, invasive sample of the tumor (a tissue biopsy) to read these ID cards. But sometimes, the tumor is in a hard-to-reach place, or the patient is too sick for another surgery.

The authors of this paper created a new tool called the LION panel. Think of this as a highly specialized, open-source "Swiss Army knife" designed to scan the blood for those tiny cancer ID cards. Unlike expensive, closed commercial tools that only look for a few specific things, the LION panel is designed to be flexible, affordable, and able to spot a wide variety of genetic clues across many different types of cancer.

How They Built the Tool

The researchers didn't just guess which genes to look for. They built a list of 109 specific genes that are known to be the "bosses" of cancer.

The Recipe: They looked at the most popular commercial gene lists used by hospitals and combined the best parts of all of them into one custom list.
The Filter: They also added a special "noise-canceling" feature. As we age, our healthy blood cells sometimes pick up harmless mutations (like getting a scratch on a car). The LION panel has a smart filter to tell the difference between a scratch on a healthy car and a stolen car (cancer).
The Software: They wrote their own free computer code (a "pipeline") to read the data. This means any hospital can use it without paying a licensing fee to a big company.

The Test Drive: How Well Does It Work?

To see if the LION panel was any good, the team ran three different types of tests:

The "Fake" Test (Reference Samples): They used pre-made blood samples that contained known cancer mutations, like a teacher's answer key.
- Result: The LION panel found 92% of the known mutations and correctly said "no cancer" 99% of the time when there wasn't any. It was very good at spotting even tiny amounts of cancer DNA.
The "Real World" Test (Patient Samples): They compared the LION panel against two other gold-standard methods: ddPCR (a very sensitive but narrow test that looks for one specific mutation at a time) and WES (a massive scan of all tissue DNA).
- Result: The LION panel agreed with the other tests 82% of the time. Crucially, it found 14 extra mutations per patient that the other tests missed. It was like finding extra clues at a crime scene that the other detectives overlooked.
The "Time Travel" Test (Case Studies): They followed three patients over time to see if the test could track the cancer's movement.
- Breast Cancer: A patient had failed many treatments. Tissue biopsies kept failing (not enough material). The LION panel successfully tracked the cancer's mutations in the blood, showing which genes were growing stronger as the disease worsened.
- Melanoma: They watched a patient's cancer evolve. The test showed the cancer mutations rising and falling in sync with the patient's actual health, acting like a real-time weather report for the tumor.
- Rectal Cancer: After surgery, the test detected tiny traces of remaining cancer (minimal residual disease) that were too small to see on a CT scan, warning doctors that the cancer was coming back before it was visible on imaging.

Why This Matters (According to the Paper)

The paper claims that the LION panel is a game-changer for Molecular Tumor Boards (MTBs). An MTB is a team of experts who meet to decide the best treatment for a patient.

It's Open: Because the code and the gene list are free and open, any hospital can build this tool themselves without being locked into a specific company's expensive ecosystem.
It's Dynamic: Unlike a tissue biopsy, which is a single snapshot in time, the LION panel allows doctors to take blood samples repeatedly. This lets them watch the cancer change and adapt in real-time, spotting resistance to drugs before the patient gets sicker.
It's Sensitive: It can find cancer DNA even when there is very little of it, helping to catch recurrence early.

The Caveats (What the Paper Admits)

The authors are honest about the limits of their work:

It's not magic: It only looks at 109 genes. If a patient has a rare cancer mutation outside those 109 genes, the panel won't see it.
It's early days: This was a "proof of concept" study with a relatively small number of patients. The authors say they need to test this on thousands of people to prove it works perfectly in every hospital.
It's not a replacement yet: It works best alongside tissue tests, not necessarily as a total replacement for them, especially for finding certain complex genetic markers like MSI (which predicts response to immunotherapy).

The Bottom Line

The LION panel is a new, free, and highly sensitive way to scan blood for cancer. It acts like a high-tech detective that can track a criminal gang's movements over time, even when the gang is hiding in a place that's hard to reach. The paper shows that this tool works well, finds more clues than older methods, and could help doctors make better, faster decisions about how to treat cancer patients.

Technical Summary: The LION Panel for Liquid Biopsy-Based Clinical Decision-Making

Problem Statement
The shift toward personalized cancer therapy relies heavily on molecular profiling, particularly in advanced disease where treatment resistance is a major challenge. While Molecular Tumor Boards (MTBs) are essential for interpreting complex genomic data, existing circulating tumor DNA (ctDNA) panels often present significant limitations. Commercially available comprehensive panels can be broad, generating numerous non-actionable variants that increase analytical complexity and cost, thereby hindering routine clinical implementation. Furthermore, current regulatory guidelines (e.g., Rili-BAEK in Germany) mandate a limit of detection (LOD) of 0.5% variant allele frequency (VAF), yet clinically relevant variants often exist below this threshold. There is a critical need for a cost-effective, highly sensitive, and transparent liquid biopsy workflow that can detect low-frequency variants, distinguish tumor-derived mutations from clonal hematopoiesis of indeterminate potential (CHIP), and support dynamic disease monitoring when tumor tissue is unavailable.

Methodology
The authors developed and validated the LION panel, a manufacturer-independent, open next-generation sequencing (NGS) panel combined with a custom bioinformatic pipeline.

Panel Design: The LION panel targets 109 genes covering approximately 500 kb of coding sequence. The gene selection was derived from a consensus of major commercial panels (e.g., TruSight Oncology 500, Ion AmpliSeq), national networks (nNGM 2.0), and specific literature on cancer drivers, therapy resistance, CHIP, and fusion genes. The design includes:
- 346 kb of major cancer driver genes (e.g., KRAS, BRAF, EGFR).
- 87 kb of therapy resistance genes.
- 34 kb of CHIP-associated genes to facilitate discrimination between hematopoietic and tumor variants.
- 21 kb of fusion gene regions (targeting intronic breakpoints for ALK, RET, ROS1, etc.).
- Hotspot enrichment (approx. 2-fold depth) and sample-tracking SNPs for quality control.
Bioinformatic Pipeline (LION Pipeline): The workflow utilizes unique molecular identifiers (UMIs) for error correction. Key steps include:
- Preprocessing: UMI extraction, quality filtering, and alignment to GRCh38.
- Error Correction: Consensus calling using fgbio to merge reads with identical UMIs, reducing PCR and sequencing errors.
- Variant Calling: Dual-caller approach using VarDict and Mutect2.
- Filtering: A Panel of Normals (PoN) derived from 21 healthy blood donors is used to filter recurrent background artifacts. Variants are filtered against gnomAD and classified based on tumor-informed (LOD 0.05%) or tumor-uninformed (LOD 0.5%) contexts.
- Annotation: Variants are annotated using OncoKB, COSMIC, and ClinVar for pathogenicity and clinical actionability.
Study Cohort: The validation included 87 samples: 17 technical replicates of commercial reference cfDNA (Seraseq) with VAFs ranging from 0.25% to 1.0%, 21 healthy blood donor controls, and 49 patient samples (plasma, buffy coat, and FFPE) representing nine tumor entities.

Key Results

Analytical Performance: In reference samples, the LION panel achieved 92% sensitivity and 99% specificity. It demonstrated high concordance with digital droplet PCR (ddPCR) ( $r = 0.99$ $r = 0.99$ ).
- Sensitivity by VAF: The panel detected variants down to 0.05% VAF in tumor-informed analyses and 0.5% VAF in tumor-uninformed analyses.
- Clinical Concordance: In patient samples, the panel showed 82% concordance with ddPCR and 75% concordance with whole-exome sequencing (WES) of tissue for known driver mutations.
- Reproducibility: Technical replicates showed high reproducibility with low standard deviations in VAF measurements.
Fusion Detection: The panel successfully detected gene fusions (e.g., TPR-ALK, NCOA4-RET) in reference samples at low VAFs (1%–0.25%), with detection rates increasing with higher VAFs and DNA input.
CHIP Differentiation: The inclusion of CHIP-associated genes and matched germline controls allowed for the differentiation of clonal hematopoiesis from tumor-derived mutations, a critical step in liquid biopsy interpretation.
Clinical Utility in Case Studies: Three longitudinal case studies (breast cancer, melanoma, rectal cancer) demonstrated the panel's ability to:
- Detect minimal residual disease (MRD) and emerging resistance mutations when tissue biopsies were unavailable or failed.
- Correlate VAF dynamics with disease progression and treatment response.
- Identify additional targetable variants (e.g., NF1, KMT2C, SMAD4) beyond the primary driver mutations, expanding the molecular landscape for MTB decision-making.

Significance and Claims
The paper claims that the LION panel and pipeline offer a feasible, cost-effective, and clinically informative solution for ctDNA-based molecular profiling in MTB settings. Its primary significance lies in:

Open-Source Transparency: Unlike proprietary commercial panels, the LION panel and pipeline are fully transparent, manufacturer-independent, and available as an open resource (Docker container), ensuring reproducibility and adaptability.
Enhanced Sensitivity: By utilizing UMI-based error correction and optimized sequencing depth, the panel achieves sensitivity beyond standard regulatory requirements (down to 0.05% VAF in specific contexts), enabling earlier detection of recurrence and resistance.
Dynamic Monitoring: The study demonstrates that liquid biopsy-based NGS captures dynamic clonal evolution and subclonal changes that static tissue biopsies (like WES) may miss, providing a more comprehensive view of tumor evolution.
Clinical Decision Support: The panel supports treatment stratification by identifying targetable variants and monitoring disease burden longitudinally, particularly in patients where repeated tissue sampling is not feasible.

The authors conclude that while the study serves as a technical validation and proof-of-concept in a limited, retrospective cohort, the LION panel effectively complements established tissue-based approaches and warrants further validation in larger, prospective MTB populations to confirm its impact on routine clinical decision-making.