Charting clonal evolution and behavior with GoT-Multi.

Jonas A Gudera, Vijay G Sankaran

Abstract readComment

In one paragraph

Article in Cell genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jonas A GuderaDivision of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Vijay G SankaranDivision of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA. Electronic address: sankaran@broadinstitute.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tracking clonal evolution is critical to fully define the mechanisms of normal physiology and the disruptions of these processes in disease. In this issue of Cell Genomics, Pak and Saurty-Seerunghen et al. describe the development of Genotyping of Transcriptomes for multiple targets and sample types (GoT-Multi) and show how this new technology enables insights into cellular states that mediate clonal evolution in diseases, such as the Richter transformation of chronic lymphocytic leukemia, while also revealing convergence of cell states, even with distinct driver mutations.

Indexed as

Clonal EvolutionLeukemia, Lymphocytic, Chronic, B-CellTranscriptomeGene Expression ProfilingHumansMutation

Identifiers

PMID41539290

DOI10.1016/j.xgen.2025.101077

PMCPMC12926189

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.