Genetic Barcodes Reveal What Tumor Biopsies Miss

Every breast tumor is not a single disease but a patchwork of competing cell populations, each descended from a different founding cell and each carrying its own behavioral quirks. Some clones grow aggressively, others sit quietly, and a rare few possess the deadly ability to seed distant organs or shrug off chemotherapy. Clinicians trying to characterize this intra-tumoral heterogeneity, or ITH, rely on two main windows into the tumor: solid biopsies taken with a needle, and liquid biopsies that hunt for fragments of tumor DNA circulating in the blood. A new study published in Molecular Systems Biology has now put both sampling methods to a rigorous, quantitative test, and the results carry an important message for precision oncology: neither window alone tells the whole story, but together they capture far more of the tumor’s true diversity than either can on its own.

The research team, led by scientists at the Olivia Newton-John Cancer Research Institute, the Walter and Eliza Hall Institute, and collaborators in Australia and France, tackled a problem that has long frustrated the field. When a pathologist examines a needle biopsy, how much of the tumor’s clonal complexity is actually being seen? When circulating tumor DNA is detected in a patient’s plasma, which clones are shedding that DNA and which are hiding? Previous comparisons of the two approaches often focused on a handful of well-known driver mutations such as TP53 or KRAS, rather than the full landscape of clonal diversity. To go deeper, the team turned to a powerful lineage-tracing technology known as genetic barcoding.

The technique works like this: cancer cells are infected with a lentiviral library containing thousands of unique DNA sequences, each of which integrates permanently into the genome of a single cell and is inherited by all of its descendants. Every clone in the resulting tumor therefore carries a molecular name tag that can be recovered by PCR amplification and sequencing. In the study, the researchers applied this strategy to six preclinical breast cancer models, comprising two established cell lines, MDA-MB-231 and MDA-MB-468, and four patient-derived xenografts, or PDXs, established from drug-naive triple-negative breast cancer patients. Because the barcodes provide an unbiased record of clonal identity independent of any particular mutation, the researchers could track exactly which clones ended up in which sample.

The first major finding concerned geography. Using a stochastic agent-based simulation of three-dimensional tumor growth, adapted from a previously published model, the team predicted that clonal density would be higher in the center of a tumor than at its periphery. When they then dissected real barcoded tumors grown in mice into central and peripheral pieces and sequenced the barcode repertoire of each, the prediction held. In the MDA-MB-231 model, the tumor center contained on average roughly three times more distinct barcodes than peripheral pieces, and across all six models the center harbored a substantially larger share of the total clonal diversity. In one cell line model the center accounted for 66 percent of all detected barcodes, and in the other, 77 percent. The pattern was reproduced in all four PDX models, with the intriguing exception that a highly necrotic PDX showed a smaller center-periphery difference, presumably because cell death had erased many barcodes from the core.

This spatial bias has direct clinical implications, because radiologists typically aim needles toward the center of a lesion. The barcoding experiments showed that a needle biopsy reaching the tumor core captures a large fraction of the tumor’s biomass, with clones detected in needle samples representing roughly 80 to 90 percent of the total tumor reads. However, the content of any single needle varied considerably depending on the direction from which it was inserted. Several dominant clones present in the primary tumor were missed entirely by some needle tracks, and biopsies taken from opposite sides of the same tumor contained non-overlapping sets of barcodes. Minor clones, in particular, were frequently absent from needle samples, a sobering result given that low-frequency clones can drive metastasis and drug resistance.

The team then turned to the liquid side of the comparison. Blood was collected from tumor-bearing mice at three time points, corresponding to tumor volumes of 100, 300, and 800 cubic millimeters, and cell-free DNA was extracted from the plasma before the barcodes were amplified and sequenced. Barcode recovery in cfDNA proved strikingly variable. Some models, such as PDX-4295 and CRCM412, shed detectable DNA early and reliably, while others yielded little or nothing even when tumors were large. Recovery also increased with tumor burden, and within a given model the same clones could appear and disappear in the plasma of the same mouse over time. When the researchers implanted identical clonal pools into multiple recipient mice, the clonal composition of the resulting sister tumors was well conserved, yet barcode recovery still fluctuated between animals, suggesting that both intrinsic clone properties and stochastic factors influence how much DNA a tumor releases into the bloodstream.

When cfDNA barcodes were detected, they told a meaningful story. The plasma repertoire at the final time point broadly reflected the clonal makeup of the primary tumor, and the clones represented in cfDNA accounted for up to 80 percent of tumor biomass in the best-shedding model. Notably, cfDNA also served as a reasonable surrogate for the clonal composition of lung metastases, hinting that DNA in the blood may report on disease beyond the primary site. But the method had clear blind spots: only a small percentage of the tumor’s total barcodes appeared in the plasma in most models, and some dominant clones in the primary tumor were never detected in cfDNA at all.

The head-to-head comparison revealed that the two biopsy types are complementary rather than interchangeable. Deep needle biopsies generally captured a larger share of primary tumor barcodes and higher clonal diversity than cfDNA, except in the CRCM412 model, where cfDNA outperformed both deep and shallow needle sampling. Three distinct patterns emerged across individual mice: sometimes cfDNA better recapitulated tumor heterogeneity, sometimes the needle did, and sometimes both performed comparably. Crucially, combining the two methods significantly increased the percentage of tumor biomass captured compared with either alone in several models. In the MDA-MB-231 model, the researchers went one step further and retrieved circulating tumor cells from the blood; adding their barcodes to the combined needle-plus-cfDNA dataset pushed the captured biomass above 80 percent.

The authors are careful to note the limitations of their system. Xenograft experiments unfold over weeks rather than the years over which human tumors evolve, and barcode detection, which relies on amplifying tags shorter than 100 base pairs, may underestimate the cfDNA fragments detectable in clinical assays that query multiple genomic loci. Blood volumes in mice are also far smaller than those drawn from patients. Nevertheless, the barcoded models offer something patient samples cannot: a complete, ground-truth map of clonal composition against which every sampling method can be scored, tracked longitudinally, and manipulated experimentally without the confounding effects of treatment.

The broader takeaway for oncology is pragmatic. Solid biopsies deliver intact cells that support histology, receptor-status testing, single-cell omics, and assessment of tumor-infiltrating lymphocytes, while liquid biopsies offer a minimally invasive, repeatable readout that can integrate heterogeneity across multiple lesions that no needle could reach. This study provides quantitative backing for the growing consensus, supported by earlier analyses of hundreds of patient samples, that the two approaches should coexist in clinical practice. As barcoded preclinical models are combined with genomic and spatial transcriptomic profiling, researchers hope to identify the properties that make some clones prolific DNA shedders and others invisible, knowledge that could sharpen the interpretation of liquid biopsy results, flag false negatives, and ultimately guide more rational personalized therapies for breast cancer patients.

Subject of Research: Using genetic barcoding to quantify how well solid and liquid biopsies capture intra-tumoral heterogeneity in breast cancer models

Article Title: Genetic barcoding uncovers the clonal makeup of solid and liquid biopsies and their ability to capture intra-tumoral heterogeneity

Article References: Serrano, A., Weber, T. S., Berthelet, J., Ftouni, S., El-Saafin, F., Lee, S., Lim, E., Charafe-Jauffret, E., Ginestier, C., Williams, D., Hollande, F., Yeo, B., Dawson, S.-J., Naik, S. H., & Merino, D. (2026). Genetic barcoding uncovers the clonal makeup of solid and liquid biopsies and their ability to capture intra-tumoral heterogeneity. Molecular Systems Biology, 22(5), 659-684. https://doi.org/10.1038/s44320-026-00194-w

Image Credits: AI Generated

DOI: 10.1038/s44320-026-00194-w

Keywords: breast cancer, genetic barcoding, intratumoral heterogeneity, liquid biopsy, cell-free DNA, needle biopsy, patient-derived xenografts, circulating tumor DNA, clonal evolution, tumor sampling, precision oncology, Molecular Systems Biology