A UMAP graphical depiction of 45,963 cancer cells from patients whose chronic lymphocytic leukemia has transformed into a more aggressive type. The different colors represent different cell states (e.g., light green represents an inflammatory state, hot pink represents proliferating). GoT-Multi linked these cell states with their mutational status to reveal the commonalities in gene activity that lead to treatment resistance. Credit: the Nam Lab

A new tool developed by Weill Cornell Medicine and the University of Adelaide investigators has enhanced the ability to track multiple gene mutations while simultaneously recording gene activity in individual cancer cells. The technology, which can now use diverse types of pathology samples and quickly process large numbers of cells, has enabled the investigators to glean new insights into how cancers evolve toward greater aggressiveness and therapy resistance.

Described in a paper published in Cell Genomics, the new tool, GoT-Multi, is a next-generation advance over an earlier tool called GoT (Genotyping of Transcriptomes). GoT was highly innovative but limited in detecting certain gene mutations as well as the number of mutations it could detect at once, and it was restricted to fresh or frozen tissue samples.

GoT-Multi substantially overcomes those limitations and can handle tissue samples preserved with a chemical called formalin and embedded in wax—a sample type that comprises a vast scientific resource in hospital pathology labs worldwide. The researchers highlighted GoT-Multi’s potential by using it to reveal new details of how a relatively indolent leukemia can evolve into an aggressive lymphoma.

“This technology gives us substantial new power to answer important questions about how cancers evolve, from the beginnings of pre-cancerous neoplastic outgrowths to transformation into malignancy and finally to therapy resistance,” said study co-senior author Dr. Anna Nam, an assistant professor of pathology and laboratory medicine, the Gellert Family/John P. Leonard, M.D. Research Scholar in Hematology and Medical Oncology, and a member of the Englander Institute for Precision Medicine and the Sandra and Edward Meyer Cancer Center at Weill Cornell Medicine.

The study’s other co-senior author was Dr. Luciano Martelotto, associate professor and team lead at the Adelaide Centre for Epigenetics, University of Adelaide. Post-doctoral fellows Dr. Minwoo Pak and Dr. Mirca Saurty-Seerunghen of Dr. Nam’s laboratory co-led this work.

Dr. Nam, who is also a pathologist at New York-Presbyterian/Weill Cornell Medical Center, led the development of the GoT tool in the late 2010s as a postdoctoral researcher in the laboratory of Dr. Dan Landau, the Bibliowicz Family Professor of Medicine and a member of the Englander Institute for Precision Medicine and the Sandra and Edward Meyer Cancer Center at Weill Cornell Medicine, and a core faculty member of the New York Genome Center.

GoT and GoT-Multi are considered “single-cell multi-omics” tools because they enable researchers to record multiple layers of information from individual cells.

In a striking demonstration of GoT-Multi’s unique capabilities, the researchers applied it to tissue samples, including the sample type they had been unable to analyze, from patients with chronic lymphocytic leukemia transitioning toward the more malignant large B-cell lymphoma—a change known as the Richter Transformation.

The tool allowed the researchers to profile tens of thousands of individual tumor cells, track the presence of more than two dozen different gene mutations, and see how these mutations related to the cells’ activities—some cells growing faster, others stoking inflammation—as the cancer evolved. Overall, GoT-Multi illuminated this malignant progression as never before.

The researchers are now applying GoT-Multi to a large cohort of therapy-resistant lymphomas, as well as using it to map the development of other cancers and precancerous states. They expect the insights provided by GoT-Multi to suggest new therapeutic strategies.

More information: Co-mapping Clonal and Transcriptional Heterogeneity in Somatic Evolution via GoT-Multi., Cell Genomics (2025). DOI: 10.1016/j.xgen.2025.101036. www.cell.com/cell-genomics/ful … 2666-979X(25)00292-7

Citation: Enhanced multi-omics tool illuminates cancer progression (2025, October 10) retrieved 10 October 2025 from https://medicalxpress.com/news/2025-10-multi-omics-tool-illuminates-cancer.html

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