Abstract
Low skeletal muscle mass is highly prevalent in older cancer patients and affects 5% to 89% depending on the type and stage of cancer. Low skeletal muscle mass is associated with poor clinical outcomes such as postoperative complications, chemotherapy toxicity and mortality in older cancer patients. Little is known about the mediating pathophysiological mechanisms. In this review we summarize proposed pathophysiological mechanisms underlying the association between low muscle mass and poor clinical outcomes in older cancer patients including 1) systemic inflammation; 2) insulin-dependent glucose handling; 3) mitochondrial function; 4) protein status, and; 5) pharmacokinetics of anticancer drugs. The mechanisms of altered myokine balance negatively affecting the innate and adaptive immune system, and altered pharmacokinetics of anticancer drugs leading to a relative overdosage of anticancer drugs are best-substantiated. The effects of glucose intolerance and circulating mitochondrial DNA as a consequence of low muscle mass are topics of interest for future research. Restoring myokine balance through physical exercise, exercise mimetics, neuro-muscular activation and adapting anticancer drug dosing on muscle mass could be targeted approaches to improve clinical outcomes in older cancer patients with low muscle mass.
| Original language | English |
|---|---|
| Article number | e13516 |
| Pages (from-to) | 1-13 |
| Number of pages | 13 |
| Journal | Acta Physiologica |
| Volume | 231 |
| Issue number | 1 |
| Early online date | 1 Jun 2020 |
| DOIs | |
| Publication status | Published - Jan 2021 |
Bibliographical note
This article is protected by copyright. All rights reserved.Funding
This work was supported by the European Union's Horizon 2020 research and innovation programme under the Marie‐Sklodowska‐Curie grant agreement no. 675003 (PANINI programme) and by an unrestricted grant of the University of Melbourne, Australia, received by Professor Andrea B. Maier. The funders had no role in the design and conduct of the study, data collection and analysis, interpretation of data, writing of the manuscript, or the decision to submit the article for publication. This work was supported by the European Union's Horizon 2020 research and innovation programme under the Marie-Sklodowska-Curie grant agreement no. 675003 (PANINI programme) and by an unrestricted grant of the University of Melbourne, Australia, received by Professor Andrea B. Maier. The funders had no role in the design and conduct of the study, data collection and analysis, interpretation of data, writing of the manuscript, or the decision to submit the article for publication.
| Funders | Funder number |
|---|---|
| Horizon 2020 | |
| University of Melbourne | |
| Horizon 2020 Framework Programme | 675003 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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