ReviewFrontiers in cell and developmental biology2020
Dietary Energy Modulation and Autophagy: Exploiting Metabolic Vulnerabilities to Starve Cancer.
Review in Frontiers in cell and developmental biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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Who cites it
7 citing papers in PubMed, 52 citations in OpenAlex.
- Biomarker-Driven Strategies for Stromal Reprogramming in Pancreatic Ductal Adenocarcinoma.Cells · 2026Review
- Autophagy: mechanisms, roles in human diseases, and therapeutic perspectives.Frontiers in cell and developmental biology · 2026Review
- The Role of Diet and Nutrition in Cancer Development and Management: From Molecular Mechanisms to Personalized Interventions.Foods (Basel, Switzerland) · 2025Review
- Weight Management for Fertility-Preservation Therapy in Endometrial Cancer: Opportunities and Challenges.Current oncology reports · 2025Review
- Intermittent fasting interventions to leverage metabolic and circadian mechanisms for cancer treatment and supportive care outcomes.Journal of the National Cancer Institute. Monographs · 2023Article
- ULK1 Depletion Protects Mice from Diethylnitrosamine-Induced Hepatocarcinogenesis by Promoting Apoptosis and Inhibiting Autophagy.Journal of hepatocellular carcinoma · 2023Article
- Mitigation of Iron Irradiation-Induced Genotoxicity and Genomic Instability by Postexposure Dietary Restriction in Mice.BioMed research international · 2021Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Cancer cells experience unique and dynamic shifts in their metabolic function in order to survive, proliferate, and evade growth inhibition in the resource-scarce tumor microenvironment. Therefore, identification of pharmacological agents with potential to reprogram cancer cell metabolism may improve clinical outcomes in cancer therapy. Cancer cells also often exhibit an increased dependence on the process known as autophagy, both for baseline survival and as a response to stressors such as chemotherapy or a decline in nutrient availability. There is evidence to suggest that this increased dependence on autophagy in cancer cells may be exploitable clinically by combining autophagy modulators with existing chemotherapies. In light of the increased metabolic rate in cancer cells, interest is growing in approaches aimed at "starving" cancer through dietary and pharmacologic interventions that reduce availability of nutrients and pro-growth hormonal signals known to promote cancer progression. Several dietary approaches, including chronic calorie restriction and multiple forms of fasting, have been investigated for their potential anti-cancer benefits, yielding promising results in animal models. Induction of autophagy in response to dietary energy restriction may underlie some of the observed benefit. However, while interventions based on dietary energy restriction have demonstrated safety in clinical trials, uncertainty remains regarding translation to humans as well as feasibility of achieving compliance due to the potential discomfort and weight loss that accompanies dietary restriction. Further induction of autophagy through dietary or pharmacologic metabolic reprogramming interventions may enhance the efficacy of autophagy inhibition in the context of adjuvant or neo-adjuvant chemotherapy. Nonetheless, it remains unclear whether therapeutic agents aimed at autophagy induction, autophagy inhibition, or both are a viable therapeutic strategy for improving cancer outcomes. This review discusses the literature available for the therapeutic potential of these approaches.
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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.