Evidence map›Paper›PMID 41756421›Full record

ArticleResearch square2026

A phenotype-based cell culture model of melanoma cells that persist as residual disease after therapies leading to recurrence.

Balraj Singh, Vanessa N Sarli, Nikil Erry, Anthony Lucci

Abstract readPreprint
In one paragraph

Article in Research square, 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

4 authors.

Balraj SinghDepartment of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Vanessa N SarliDepartment of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Nikil ErryDepartment of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Anthony LucciDepartment of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

A crucial adaptability trait of stem-like melanoma cells that persist under all selection pressures, including therapies, is their ability to survive in deep quiescence. This ability coupled with their intrinsic ability to proliferate leads to recurrence. Here we describe an approach to modeling this trait in cell culture. A lack of glutamine proved to be a selection pressure for the highly metastatic human melanoma cell line A375SM, killing more than 99% of cells and selecting rare cells based on their ability to survive in deep quiescence. After 4 weeks, cells gradually exited quiescence and proliferated indefinitely. Interestingly, by not providing fresh glutamine-free medium at this stage, we could select rare cells that persist in deep quiescence as single cells. Alternatively, we could model deeper quiescence lasting longer than 4 weeks by increasing the severity of the selection pressure using dialyzed serum in medium. The cells selected in this manner were much more resistant to paclitaxel than was their parental cell line. We obtained similar results with the highly metastatic mouse melanoma cell line B16-BL6. Thus, our phenotype-based approach is suitable for modeling abnormal deep quiescence in melanoma that is responsible for therapy resistance, disease progression, and recurrence/metastasis.

Indexed as

abnormal quiescence modelcancer dormancycancer evolutionmelanoma recurrenceresidual diseaseresistant melanoma

Identifiers

PMID41756421
PMCPMC12934999

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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.