Evidence map›Paper›PMID 42769291›Full record

ReviewMedComm2026

The Sleeping Giant: Metabolism and Autophagy in the Generation and Survival of Dormant Polyploid Giant Cancer Cells.

Silvia Guil-Luna, María Teresa Sánchez-Montero, Alejandra Díaz-Chacón, Antonio Rodríguez-Ariza

Abstract readReview
In one paragraph

Review in MedComm, 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.

Silvia Guil-LunaMaimonides Biomedical Research Institute of Cordoba (IMIBIC) Cordoba Spain.
María Teresa Sánchez-MonteroMaimonides Biomedical Research Institute of Cordoba (IMIBIC) Cordoba Spain.
Alejandra Díaz-ChacónMaimonides Biomedical Research Institute of Cordoba (IMIBIC) Cordoba Spain.
Antonio Rodríguez-ArizaMaimonides Biomedical Research Institute of Cordoba (IMIBIC) Cordoba Spain.ORCID https://orcid.org/0000-0001-5304-5745

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A major limitation in preventing cancer relapse is our incomplete understanding of therapy resistance and tumor dormancy, including the role of therapy-induced polyploidy in generating rapidly proliferating progeny that repopulate the tumor. In this context, polyploid giant cancer cells (PGCCs) are a unique subpopulation traditionally considered terminally senescent due to large size, abnormal DNA content, and inability to undergo mitosis. However, compelling evidence shows that PGCCs generate progeny via amitotic mechanisms (neosis), producing highly proliferative, chemo-resistant tumor-initiating cells that drive cancer relapse. Although metabolic adaptations and autophagy support PGCC formation and survival, the mechanisms underlying these processes and their contribution to tumor relapse remain poorly understood. This review explores the complex interplay between autophagy and metabolic adaptations in PGCCs, emphasizing their role in PGCC formation, long-term survival and dormancy, and in the generation of amitotic progeny that drive tumor regrowth and cancer relapse. Mechanistic insights into how autophagy and metabolic plasticity enable PGCCs to withstand stress, maintain energy homeostasis, and escape therapy are highlighted. Additionally, we discuss therapeutic approaches targeting PGCCs by disruption of autophagy and metabolic pathways, evaluating their potential to impair progeny formation, overcome therapy resistance, and prevent cancer recurrence.

Indexed as

autophagyendoreplicationmetabolismneosisPGCCstumor dormancy

Identifiers

PMID42769291
PMCPMC13591023

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.