Evidence map›Paper›PMID 41025566›Full record

ReviewCancer control : journal of the Moffitt Cancer Center

Unveiling the Paradoxical Nature of Autophagy in Cancer Cell Fate.

Jannatul Shifa, Tasbir Amin, Md Fakruddin, Kazi Rahman, S M Bakhtiar Ul Islam

Abstract readReview
In one paragraph

Review in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
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

5 authors.

Jannatul ShifaDepartment of Biochemistry and Microbiology, North South University, Dhaka, Bangladesh.
Tasbir AminDepartment of Biochemistry and Microbiology, North South University, Dhaka, Bangladesh.ORCID 0000-0001-5265-8769
Md FakruddinDepartment of Biochemistry and Microbiology, North South University, Dhaka, Bangladesh.
Kazi RahmanDepartment of Biochemistry and Microbiology, North South University, Dhaka, Bangladesh.
S M Bakhtiar Ul IslamDepartment of Biochemistry and Microbiology, North South University, Dhaka, Bangladesh.ORCID 0000-0002-3335-3289

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autophagy is an ancient conserved and catabolic process required to maintain cellular homeostasis through sequestration and lysosomal degradation of cytosolic dysfunctional contents. The bulk degradation of cytosolic material through autophagy provides the necessary nutrients that cells utilize under starvation. Autophagy can play a mixed role in both the growth and survival of cancer cells. As a damaged cellular content-clearing mechanism, autophagy is involved in the early stage of tumor regression. Subsequently, in a mature tumor cell microenvironment, autophagy protects tumor cells from cellular stress, immune evasion, and therapeutic resistance. Therapeutic resistance mediated by autophagic regulators can make anticancer therapy less effective. This review discusses the molecular mechanism of mammalian autophagy, evaluates the dynamic role of autophagy in cancer, highlights autophagy-mediated therapeutic resistance, and suggests the use of biomarkers. In cancer therapy, the addition of biomarkers can provide specific identification, and the conjugation of biomarkers with chemo-drugs can reduce the side effects and ensure normal cell integrity.

Indexed as

AutophagyNeoplasmsAnimalsBiomarkers, TumorDrug Resistance, NeoplasmHumansTumor MicroenvironmentBiomarkers, TumorATGsautophagic biomarkersdichotomous rolemammalian autophagytherapeutics resistance

Identifiers

PMID41025566
PMCPMC12484922

What OpenQuestion holds

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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 OpenQuestion graph.