Part 1 – Multimodal Diagnostics: Integrating tissue and blood biopsies

Disease is complex, dynamic, and heterogeneous, and no one biomarker modality can capture every dimension of that complexity. Liquid and tissue biomarkers answer different biological questions, each providing a distinct window into disease, from systemic biology to what is happening within specific tissues and cells.

The opportunity, though, is not simply to generate more data, but to understand biology in greater depth by bringing different modalities of biomarker information together. This multimodal approach could help uncover insights that may not emerge from any single biomarker modality alone, potentially opening new possibilities for the next generation of precision medicine and diagnostics.

We spoke with Jorge Marques Signes, PhD, VP of Accelerator & Clinical Services at Quanterix, to explore these questions and what the future of multimodal diagnostics could look like. In Part 1, below, we dive into the past, present, and future of multimodal diagnostics. Continue to Part 2 to explore the challenges, standardization, and the path toward clinical adoption.

Q1: What unique clinical insights emerge when blood-based proteomics and tissue-level spatial biology are used together, rather than in isolation?

JS: One of the biggest sources of confusion in biomarker testing is the assumption that tissue and blood are simply two ways of measuring the same thing. They are not. Each modality answers a different biological question, and each comes with very different implications for patients.

Blood-based testing is valuable because it is accessible. It can be performed early in the care journey, repeated over time, and integrated into routine clinical practice. That accessibility makes large-scale screening, early detection, and longitudinal monitoring possible.

Tissue testing serves a different purpose. Because biopsies are performed only when clinically justified and are typically collected infrequently, tissue provides a level of biological context that blood cannot. It reveals which cells express a target, how those cells are organized within the tumor microenvironment, and where a protein is localized within the cell.

That last part is underrated, and antibody-drug conjugates (ADCs) are the clearest example I know of. An ADC only works if the target is on the cell surface and the complex is internalized. So, how much protein is present in the tumor is not really the question.

The experience with TROP2 in non-small cell lung cancer illustrates this distinction. Conventional immunohistochemistry (IHC) scoring did not reliably identify patients who benefited from datopotamab deruxtecan. However, computational analysis measuring the proportion of TROP2 localized to the cell membrane relative to total cellular TROP2 showed predictive value. The tissue sample and antibody were the same; the difference was the biological question being asked.

You cannot get that answer from a concentration. Not from tissue, and not from plasma. So when people talk about combining the modalities, I do not think it is really about reconciling two numbers. Tissue is where you work out what the biology is. Blood is where you ask whether any part of it has a measurable correlate in circulation.

That is the direction I want the field to move in, and it is the harder problem. Take a tissue signature we already know means something, then find its surrogate in blood, so that what requires a biopsy today can eventually come from a blood draw.

It will not work for everything. A membrane ratio has no obvious plasma equivalent and I do not want to pretend otherwise. But for a good amount of biology, tissue tells you what to look for and blood is what makes it repeatable.

Q2: How are these integrated approaches already influencing diagnostic decision-making?

JS: The reality is that blood and tissue-based approaches are at very different stages of clinical adoption, and it is important not to blur that distinction.

Blood-based biomarkers have already entered clinical practice. In 2024, the Alzheimer’s Association published its first clinical practice guideline for blood biomarkers, focusing on performance standards rather than specific products. The framework is straightforward: highly sensitive tests can help rule out amyloid pathology, while tests that achieve both high sensitivity and specificity can support confirmation.

Several blood-based Alzheimer’s tests have now received FDA clearance, and payer coverage is beginning to expand. In specialist memory clinics, these advances are already changing the diagnostic pathway by reducing the need for more invasive procedures such as lumbar punctures and amyloid PET imaging.

Tissue is a different situation, and I would not claim spatial proteomics is influencing neurodegenerative diagnosis today. We cannot biopsy the brain. All the tissue work is postmortem, and the methods that define the reference standard are conventional neuropathology – the established staging of amyloid and tau – not high-plex spatial. That distinction matters more than people allow. Every blood assay in this field is ultimately anchored to autopsy confirmation, and the studies validating plasma p-tau217 against neuropathologically confirmed cohorts are what let a clinician trust the number in front of them. It is an essential contribution. It is also an upstream one. While it shapes the assay, it does not sit in the patient’s workup.

Where spatial methods on brain-bank material are contributing is in explaining what the blood cannot. Two patients with very similar plasma profiles can follow different clinical courses, and a lot of that is co-pathology: TDP-43, alpha-synuclein, small vessel disease. It is common, an amyloid or tau blood marker does not see it, and you can only characterize it in tissue. That work is mapping which cells and regions actually contribute to the circulating signal, and where the current panel is blind. It will inform the next generation of blood tests. I would call it translational science with a diagnostic destination rather than diagnostics.

If the goal is to see blood and tissue genuinely informing the same clinical decision today, oncology offers a clearer example. Tumor tissue is routinely available, and clinicians already integrate tissue-based and circulating biomarkers to build a more complete picture of disease, treatment response, and patient management.

Q3: Looking ahead five years, what do you think success will look like for multimodal diagnostics?

JS: My hope is that, five years from now, this is no longer considered newsworthy. That may sound modest, but it is actually the clearest measure of success. The goal is not novelty. The goal is routine clinical practice.

Five years is probably not enough for that across the board, so let me be concrete about what I would expect. Combined tissue and blood testing should be a routine orderable part of practice in a defined set of indications rather than a research add-on, with a few signatures validated well enough to sit inside guidelines.

In oncology, I would expect the tissue component of that to be multiplex immunofluorescence rather than sequential single-marker IHC, because the route from high-plex discovery to a defensible clinical assay now exists in practice. You use a high-plex platform, Akoya PhenoCycler-Fusion in our case, to find the signature. Then it is reduced to a robust automated assay on something built for clinical-trial scale, which for us is Akoya PhenoImager-HT 2.0. That reduction step is the part the field has historically skipped, and it is the part that decides whether a spatial signature ever becomes a test rather than a paper.

I would also expect a shift from single timepoints to longitudinal monitoring. Tissue gives you the reference architecture, blood gives you the repeated measure, and following a patient across both is where the combination justifies its cost. If dried or capillary collection matures on the timeline it promises, the repeated measure becomes something the patient can provide without a clinic visit at all, which changes what longitudinal really means.

The clearest sign of maturity will be at the reporting layer, when the pathologist receives one integrated result to interpret instead of three datasets to reconcile. Computational integration has a genuine opportunity to prove itself there, with the caveat I would apply to all of this: it only works on standardized, calibrated inputs. An integration layer sitting on unharmonized assays will produce confident numbers that do not reproduce, and one visible failure of that kind would cost the field more time than going slowly ever would.

Realistically, five years means real depth in oncology and neurology rather than universal adoption. Those are the two fields where the biology and the assays are furthest along. The indications with clear decision impact will move first, and I would expect the rest to follow the evidence.

Putting Multimodal Biomarker Science into Practice:

Multimodal diagnostics hold significant promise for situations where combining insights across liquid and tissue could provide a more complete view of health and disease biology. Realizing that potential, however, will require the right combination of technologies, expertise, and translational capabilities.

With realizing the full potential of multimodal diagnostics also raises important questions around integration, standardization, and clinical adoption. In Part 2, we continue the conversation with Jorge Marques Signes, PhD, VP of Accelerator & Clinical Services at Quanterix, to explore what it will take to move multimodal diagnostics from promise to practice.

Explore our liquid and tissue Accelerator Biomarker Services to learn how Quanterix can support your discovery, translational, and clinical research programs.