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	<title>cancer cell state differentiation in neuroblastoma &#8211; Science</title>
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	<title>cancer cell state differentiation in neuroblastoma &#8211; Science</title>
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		<title>Gene Signature Exposes Hidden Neuroblastoma Cells That Drive Poor Outcomes</title>
		<link>https://scienmag.com/gene-signature-exposes-hidden-neuroblastoma-cells-that-drive-poor-outcomes/</link>
		
		<dc:creator><![CDATA[Juliet Wilcox]]></dc:creator>
		<pubDate>Fri, 09 Oct 2026 12:14:08 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[adrenergic cell state]]></category>
		<category><![CDATA[adrenergic neuroblastoma cell states]]></category>
		<category><![CDATA[cancer cell state differentiation in neuroblastoma]]></category>
		<category><![CDATA[cancer prognosis]]></category>
		<category><![CDATA[gene expression profiling in neuroblastoma]]></category>
		<category><![CDATA[gene signature]]></category>
		<category><![CDATA[hidden neuroblastoma cell populations]]></category>
		<category><![CDATA[mesenchymal cell state]]></category>
		<category><![CDATA[multi-institutional neuroblastoma research]]></category>
		<category><![CDATA[neuroblastoma]]></category>
		<category><![CDATA[neuroblastoma gene signature]]></category>
		<category><![CDATA[neuroblastoma relapse mechanisms]]></category>
		<category><![CDATA[neuroblastoma tumor cell heterogeneity]]></category>
		<category><![CDATA[organoids]]></category>
		<category><![CDATA[patient-derived xenografts]]></category>
		<category><![CDATA[pediatric cancer]]></category>
		<category><![CDATA[poor prognosis neuroblastoma markers]]></category>
		<category><![CDATA[single-cell neuroblastoma analysis]]></category>
		<category><![CDATA[Single-Cell RNA Sequencing]]></category>
		<category><![CDATA[spatial omics]]></category>
		<category><![CDATA[St. Jude Children's Research Hospital]]></category>
		<category><![CDATA[treatment resistance]]></category>
		<category><![CDATA[treatment-resistant neuroblastoma cells]]></category>
		<category><![CDATA[tumor cell populations driving neuroblastoma outcomes]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=253753</guid>

					<description><![CDATA[St. Jude scientists and collaborators built a comprehensive single-cell dataset and patient-derived models to identify a malignant mesenchymal cell population in neuroblastoma that is linked to treatment resistance and poor outcomes.]]></description>
										<content:encoded><![CDATA[<p>Neuroblastoma is the most common solid tumor found outside of the brain in children, arising from immature nerve cells of the sympathetic nervous system, most often in the adrenal glands or along the spine. For decades, clinicians have grappled with a stubborn and unsettling pattern: two children diagnosed on the same day, with tumors that look nearly identical under the microscope, can follow radically different paths. One responds to therapy and recovers; the other relapses despite aggressive treatment. A team at St. Jude Children&#8217;s Research Hospital, working with collaborators at the Broad Institute of MIT and Harvard, Dana-Farber Cancer Institute, Stanford University and other institutions, has now delivered a major step toward explaining that divergence. In a study published in Cancer Cell, the researchers built one of the most comprehensive single-cell datasets of neuroblastoma assembled to date and used it to pinpoint, with unprecedented precision, the malignant cell population that has long been associated with treatment resistance and poor survival.</p>
<p>The biological heart of the discovery lies in a long-recognized but difficult-to-study distinction between two tumor cell states. Neuroblastoma cells can exist in an adrenergic state, which reflects the tumor&#8217;s origin in sympathetic nervous tissue and is generally associated with lower-risk disease, or in a mesenchymal state, which resembles connective-tissue-like cells and has been linked to high-risk disease, resistance to therapy and relapse. The problem, and it was a formidable one, is that a child&#8217;s body contains abundant healthy mesenchymal cells. Standard laboratory techniques that profile the cells within a tumor cannot easily distinguish a malignant mesenchymal cancer cell from a normal mesenchymal stromal cell sitting alongside it in the same tissue. That ambiguity has hampered efforts to quantify these dangerous cells, to study their biology and to determine how much they actually contribute to a patient&#8217;s prognosis.</p>
<p>To break through that barrier, the team analyzed 54 tumors from 50 patients using an arsenal of complementary technologies, including single-cell RNA sequencing, which reads the gene activity of individual cells, and spatial omics methods, which map where specific cells and molecules sit within intact tissue. But the decisive methodological move involved patient-derived xenografts, tumor cells taken from children and grown in mice, generated as part of the St. Jude Childhood Solid Tumor Network. Because healthy mesenchymal cells from the patient&#8217;s tumor do not survive and grow in xenografts, any mesenchymal-like cells that persisted in the mouse models were, by definition, malignant. By comparing the original patient tumors with the xenografts, the researchers could isolate a clean gene expression profile belonging specifically to the cancer-related mesenchymal population, free of the contaminating signal from normal stromal cells.</p>
<p>That purified profile became the basis for a new gene signature, a defined set of marker genes whose combined activity identifies malignant mesenchymal cells in a tumor sample. Co-corresponding author Michael Dyer, PhD, chair of the St. Jude Department of Developmental Neurobiology, emphasized the clinical significance of the advance, noting that with a reliable gene expression signature for mesenchymal cells in neuroblastoma, researchers can begin to dig into why outcomes vary so dramatically between different children with the same cancer. The signature effectively converts a previously invisible cell population into a measurable variable, one that can be scored in existing patient datasets and correlated with how each child fared.</p>
<p>The validation process was deliberately rigorous. The researchers first tested the signature against an independent database of RNA sequencing data from patient tumors, a dataset the team had not used to build the signature. The result was striking: the new mesenchymal signal significantly improved predictions of patient outcomes, whereas a pre-existing signature derived from decades-old laboratory cell lines did not. That comparison matters because much of what the field believed about neuroblastoma cell states had been built on long-established cell lines that, as the new work makes clear, failed to capture the malignant mesenchymal population as it actually exists in children. The old tools, in other words, were looking in the wrong place.</p>
<p>To confirm the signature across every platform available, the scientists created organoids, three-dimensional laboratory-grown assemblies of cancer cells, along with new cell lines, in addition to their xenografts. They then applied spatial transcriptomics, spatial proteomics, electron microscopy and chromatin profiling, techniques that probe, respectively, gene activity in place, protein abundance in place, ultrastructural anatomy and the regulatory landscape of the genome. In every system and with every method, the signature cleanly separated the two neuroblastoma cell states. The separation went deeper than gene expression: the adrenergic and mesenchymal cells displayed distinct cellular shapes, different internal spatial organization and different behaviors, indicating that the two states represent genuinely different cell types within the tumor rather than subtle shifts in a single program.</p>
<p>First author Anand Patel, MD, PhD, of the St. Jude Department of Oncology, described the robustness of the marker as endlessly fascinating, observing that regardless of which test the team applied, the signature held up, and that these markers will be powerful tools for understanding neuroblastoma better. That kind of cross-platform consistency is rare in cancer genomics, where signatures identified by one technology often dissolve when measured another way. The convergence of evidence from sequencing, imaging, proteomics and electron microscopy gives the field unusually strong confidence that the malignant mesenchymal population is real, reproducible and clinically meaningful.</p>
<p>With the marker validated, the group went a step further and built the research infrastructure the field has lacked. They generated additional in vitro models and new cell lines from xenografts derived from patient samples containing varying proportions of mesenchymal to adrenergic cells, creating a spectrum of models that mirror the diversity seen in actual patients. All of these resources are available to other researchers upon request through the Childhood Solid Tumor Network, a St. Jude initiative that distributes pediatric cancer models freely to the scientific community. Co-corresponding author Elizabeth Stewart, MD, of the St. Jude Department of Oncology, called the new models a launching point for neuroblastoma research, saying that with the dataset as a foundation, the field is poised to explore the biology of this pediatric cancer more deeply and, ultimately, to move toward improving outcomes for patients.</p>
<p>The implications extend well beyond a single tumor type. The study demonstrates a general strategy for a problem that plagues pediatric oncology broadly: when a tumor&#8217;s dangerous cells resemble normal cells of the host tissue, single-cell analysis alone can mislead. By exploiting the selective growth behavior of xenografts to separate malignant from benign populations, then locking down the finding with spatially resolved, multi-omic validation, the St. Jude-led team has provided a template other researchers can adapt. For neuroblastoma specifically, the immediate consequences are concrete. Clinicians and researchers can now measure the malignant mesenchymal fraction of a tumor accurately, incorporate it into risk assessment, investigate why those cells resist therapy and screen candidate drugs against models that actually contain them. The study was supported by the National Cancer Institute, the National Institutes of Health, the Howard Hughes Medical Institute, the Tully Family Foundation, the Peterson Foundation, Hyundai Hope on Wheels, the Damon Runyon Cancer Foundation, Alex&#8217;s Lemonade Stand Foundation and the American Lebanese Syrian Associated Charities. What began as an effort to clean up a noisy dataset has ended by giving the neuroblastoma field something it has needed for decades: a clear view of the enemy within.</p>
<p><strong>Subject of Research:</strong> Identification of a malignant mesenchymal cell state and gene signature associated with poor prognosis in pediatric neuroblastoma</p>
<p><strong>Article Title:</strong> Scientists identify the neuroblastoma cells that signal poor outcomes</p>
<p><strong>Article References:</strong> Scientists identify the neuroblastoma cells that signal poor outcomes. (n.d.). <a href="https://www.eurekalert.org/news-releases/1147064" rel="noopener noreferrer">Original publication</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> Not provided</p>
<p><strong>Keywords:</strong> neuroblastoma, pediatric cancer, gene signature, single-cell RNA sequencing, spatial omics, mesenchymal cell state, adrenergic cell state, patient-derived xenografts, treatment resistance, cancer prognosis, organoids, St. Jude Children&#x27;s Research Hospital</p>
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