Evidence map›Paper›PMID 41994101›Full record

ReviewToxicology reports2026

The autophagy switch: A critical determinant of arsenic-induced carcinogenesis and cancer therapy.

Marzieh Zeinvand-Lorestani, Fakher Rahim, Hamed Zeinvand-Lorestani

Abstract readReview
In one paragraph

Review in Toxicology reports, 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

3 authors.

Marzieh Zeinvand-LorestaniDepartment of Chemical Technologies, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran.
Fakher RahimFaculty of Medicine, Department of Medical Biology, Kocaeli University, Kocaeli 41001, Türkiye.
Hamed Zeinvand-LorestaniDepartment of Toxicology, Faculty of Pharmacy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Arsenic, a widespread environmental toxicant and unexpectedly effective chemotherapeutic agent, has complex and significant effects on cellular homeostasis. Autophagy, a conserved lysosomal degradation process, plays a key role in arsenic's dual functions as a carcinogen and a treatment. While current reviews have documented interactions between arsenic and autophagy, this review introduces a new conceptual model: the "Autophagy Switch." We propose that the cellular choice between autophagy-assisted survival and autophagy-dependent death is not simply black and white but exists within a dynamic balance called the Arsenic Contextual Triad-comprising chemical form, exposure pattern (dose and duration), and the cell's oncogenic background. We compile evidence showing how this switch influences outcomes across the cancer spectrum, from promoting skin cancer through p62/Nrf2 feedback loops to breaking down oncogenic factors like PML-RARα and BCR-ABL in leukemia. Additionally, we critically assess the therapeutic potential of targeting this switch, emphasizing how drugs that either inhibit or promote autophagy can work together with arsenic trioxide (ATO) to combat drug resistance in solid tumors such as glioblastoma and ovarian cancer. By shifting from simple descriptions to a detailed mechanistic and contextual understanding, this review offers a valuable guide for future research aiming to harness the autophagy switch for cancer prevention and personalized treatment.

Indexed as

Arsenic exposureAutophagyAutophagy switchCarcinogenesisOxidative stress

Identifiers

PMID41994101
PMCPMC13080596

What Socratic holds

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LicenceCC BY
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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.