Evidence mapPaperPMID 40900810Full record

ReviewMedComm2025

Programmed Cell Death in Cancer.

Yuang Wei, William Hankey, Dongliang Xu, Fuwen Yuan

Abstract readReview
In one paragraph

Review in MedComm, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
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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.

Yuang WeiCancer Research Center School of Integrative Medicine, Shanghai University of Traditional Chinese Medicine Shanghai China.
William HankeyDepartment of Genetics The University of North Carolina At Chapel Hill Chapel Hill North Carolina USA.
Dongliang XuUrology Centre Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine Shanghai China.
Fuwen YuanCancer Research Center School of Integrative Medicine, Shanghai University of Traditional Chinese Medicine Shanghai China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer remains the most lethal disease globally, despite the significant progress made in early screening, surgery, and therapeutic development in recent decades. Programmed cell death (PCD) is a genetically regulated process essential for eliminating aberrant cells, yet its dysregulation drives tumorigenesis and therapy resistance. In this review, we present a complete discovery timeline of them and comprehensively synthesize the roles and mechanisms of major PCD forms, such as apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, across diverse cancer types. We not only detail the molecular mechanisms, dual functions, and alterations of these PCD modalities in cancers, but also summarize their interconnections and intrinsic crosstalk. Furthermore, we comprehensively discuss how diverse therapies, including chemotherapy, radiotherapy, immunotherapy, targeted agents, and hormone therapy, engage and manipulate specific PCD pathways, revealing the involvement of PCD in cancer treatment mechanisms. This review integrates extensive preclinical and clinical evidence on PCD-targeted therapies with an in-depth focus on ferroptosis, including its regulatory networks and therapeutic relevance. Special emphasis is placed on prostate cancer, highlighting the PCD-based translational opportunities in this common malignancy. Taken together, we provide novel insights into the complex interplay between PCD and cancer biology and offer a framework for developing precision oncology therapies.

Indexed as

anticancer therapycancerferroptosisprogrammed cell deathprostate cancer

Identifiers

PMID40900810
PMCPMC12399603

What Socratic holds

Textmetadata
LicenceCC BY
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.