AOA Dx Pushes Mass Spectrometry Over DNA Tests For Cancer Detection

A team of scientists from liquid biopsy diagnostics firm AOA Dx and lipid-specialty consultancy Lipidomics Consulting is arguing that mass spectrometry, not the DNA sequencing technology behind today's best-known blood cancer tests, is the more promising route to catching tumors early. The argument, published by GEN (Genetic Engineering and Biotechnology News) and authored by AOA Dx chief scientific officer Abigail McElhinny, PhD, senior product scientist Rachel Culp-Hill, PhD, and Lipidomics Consulting founder and CEO Kim Ekroos, PhD, comes from the very executives whose companies would sell the technology it promotes. For patients waiting on a blood test that can reliably flag stage I or II cancer before it spreads, that detail is not a footnote, it is the whole story.

What the Research Found

Liquid biopsy (a minimally invasive blood-based technology that detects tumor-derived biomarkers instead of requiring a tissue sample) has become the dominant framework for early cancer detection research. Most assays currently in development target mutations, methylation patterns, or fragmentation patterns in circulating tumor DNA (ctDNA, fragments of tumor genetic material shed into the bloodstream) using next-generation sequencing, or NGS (a DNA-reading method that processes millions of genetic fragments in parallel). Two of the category's best-known products illustrate how far that approach has already spread: GRAIL's Galleri test, a multi-cancer early detection blood test, and Guardant Health's Guardant360, a ctDNA-based liquid biopsy test used in cancer treatment decisions. Neither product is named or benchmarked in the GEN piece itself; both simply illustrate how thoroughly NGS-based sequencing already dominates the liquid biopsy category that mass spectrometry proponents are now trying to enter.

McElhinny, Culp-Hill, and Ekroos argue that mass spectrometry-based omics approaches, the collective term for large-scale molecular profiling, offer a complementary or alternative path across multiple cancer types. Their piece covers three subdisciplines: proteomics (protein profiling), lipidomics (lipid profiling), and metabolomics (metabolite profiling). The pitch is direct: where NGS reads the tumor's genetic instructions, mass spectrometry reads what the cell actually built and is doing with them.

How the Science Works

Mass spectrometry (an analytical technique that identifies molecules by measuring the mass-to-charge ratio of their ionized fragments) is applied across oncology in three distinct layers. MS-based proteomics enables quantification of thousands of proteins at once and mapping of the proteome, the full set of proteins expressed in a cell or tissue, across multiple cancer types. That matters because genetic mutations common to several cancer types alter the proteins those genes produce, changing cellular function in ways that support what the authors describe as pro-cancer cellular activities. In effect, a mutation is an instruction; the protein it yields is the action the cell actually takes, and proteomics reads the action. That framing matters clinically because it points toward a different kind of test result: not which mutation a patient carries, but what that mutation is actually doing inside the tumor right now.

Metabolomics sits one layer further downstream. The authors describe it as the omics discipline that most closely reflects a real-time snapshot of the disease phenotype, since metabolites and lipids capture the cumulative effect of changes across the genome, transcriptome, and proteome rather than any single layer in isolation. Lipidomics, the newest of the three subdisciplines, has grown in recent years on the back of advances in mass spectrometry hardware and machine-learning-based bioinformatics tools capable of parsing the resulting data. According to the authors, lipidomics can capture thousands of distinct lipid species within a single liquid biopsy draw, a scale of molecular detail that ctDNA sequencing, focused on a narrower set of genetic markers, does not attempt to match.

What It Means for Patients

The clinical stakes hinge on cancer staging. Stage I and II disease is described in the field as localized, the window where treatment odds are best and where a reliable blood test would do the most good. Stage III and IV disease is described as advanced, meaning the cancer has metastasized, spread beyond its point of origin. A test that requires only a blood draw, rather than imaging, biopsy, or a more invasive diagnostic workup, is valuable specifically to the degree it can reliably catch disease in that earlier, localized window. The appeal of a blood-based test at that stage is less about replacing imaging or biopsy outright than about giving physicians a reason to order them sooner, before symptoms make the diagnosis obvious on their own.

That is precisely where the authors say NGS-based ctDNA testing has not yet delivered, framing its performance for early-stage cancer detection as largely unproven relative to the complexity and cost such assays carry. Neither GRAIL's Galleri test nor Guardant Health's Guardant360, the two most prominent NGS-based liquid biopsy products on the market, is named or benchmarked against mass spectrometry anywhere in the GEN piece. The comparison the authors draw is with ctDNA sequencing as a category, not a head-to-head test result against a specific rival product, which is itself a data point: the argument for mass spectrometry in oncology is being made without a single sensitivity or specificity figure attached to either side.

Competitive Landscape

No MS-based oncology diagnostic from AOA Dx or Lipidomics Consulting is named or described as commercially available in their GEN piece, and the piece does not identify a specific competitor pursuing the same mass-spectrometry-based approach to early cancer detection. The broader commercial landscape any such test would eventually depend on, the instrument makers whose mass spectrometry hardware underlies proteomics, lipidomics, and metabolomics workflows industry-wide, is not detailed in the source material either. For a category this early, that absence is not unusual on its own, but it does mean readers have no independent yardstick, no rival company's data and no analyst note, against which to weigh the authors' pitch for mass spectrometry over ctDNA sequencing. Independent analyst commentary specifically on this announcement was not publicly available at publication time.

The Road to Clinic

The authors' strongest evidence is precedent, not oncology data. MS-based proteomics is already used clinically for non-oncology disease detection and therapeutic monitoring, a use case the authors credit to its multiplexing capacity and high throughput over conventional methods, citing research published in Clinical Proteomics by Birhanu et al. in 2023. That existing clinical footprint, built over the past few decades, is the template the authors argue oncology applications could follow rather than a novel technology entering medicine cold. That precedent is doing real work in the authors' argument: if a technology already meets the bar for one class of clinical decisions, the case for extending it to a second, harder one, cancer detection, rests on adapting existing infrastructure rather than proving a method from scratch.

Any such test would still need to clear the U.S. Food and Drug Administration, the agency responsible for enforcing the Federal Food, Drug, and Cosmetic Act. Existing molecular diagnostics offer a sense of what clearing that bar looks like in practice: genomic profiling products like Foundation Medicine's FoundationOne CDx built their regulatory case on large validated databases accumulated over years of clinical use, the kind of scale a new MS-based oncology test would eventually need to approach. The GEN piece itself offers no timeline, no regulatory strategy, and no target approval pathway for how AOA Dx or Lipidomics Consulting intend to get there.

What's Next

Before mass spectrometry-based diagnostics can move toward that kind of clinical scale, the field needs standardized reporting. The authors point to the Lipidomics Minimal Reporting Checklist, published by McDonald et al. in Nature Metabolism in 2022, as evidence that harmonization efforts have already made lipid data more adaptable to clinical diagnostics. Supporting translational work is accumulating outside oncology too: Ekroos, one of the GEN piece's own authors, previously co-authored a 2020 review in Progress in Lipid Research on lipid-based biomarkers for cardiovascular disease, COPD, and aging, and a separate 2025 paper in Frontiers in Endocrinology by Hou et al. examined lipidomics' strategic role in biomarker identification for gynecological disease diagnosis.

None of that constitutes oncology-specific validation yet. What it establishes is a growing evidence base for lipid and protein biomarkers in disease detection generally, the foundation the authors are betting oncology-specific applications can be built on next. Taken together, the three citations describe a discipline still building its basic infrastructure, standardized checklists, cross-disease biomarker catalogs, before it can make an oncology-specific case, which is consistent with the authors' own framing of this as an emerging rather than an established diagnostic approach.

For retail investors watching the liquid biopsy sector without an obvious winner to back, the more durable exposure may sit one layer up the supply chain: the mass spectrometry instrument makers whose hardware any proteomics, lipidomics, or metabolomics workflow ultimately runs on collect a toll regardless of whether the winning oncology diagnostic comes from AOA Dx, a rival, or a company that does not exist yet. The GEN piece names no specific instrument maker, and this analysis is not naming one either; the point for an investor watching this space is structural, not a stock pick.

The most telling number in this story is the one that is missing: no sensitivity, no specificity, no sample size, no timeline to clinic. That does not make the underlying science wrong, mass spectrometry's non-oncology track record is real, but it does mean the case for it in cancer detection is currently being made by exactly the people who would profit if it wins.

-- Zara Velez, Emerging Technology Editor

Sources: GEN - Genetic Engineering and Biotechnology News · National Library of Medicine, PMC · Federal Register

AOA Dx Pushes Mass Spectrometry Over DNA Tests For Cancer DetectionAOA Dx Pushes Mass Spectrometry Over DNA Tests For Cancer DetectionAOA Dx Pushes Mass Spectrometry Over DNA Tests For Cancer DetectionAOA Dx Pushes Mass Spectrometry Over DNA Tests For Cancer Detection