The DOI matches its Crossref record; 204 of the 204 references it cites were found in a registry or an index.
Towards targeting of shared mechanisms of cancer metastasis and therapy resistance
Open accessAbstract
Resistance to therapeutic treatment and metastatic progression jointly determine a fatal outcome of cancer. Cancer metastasis and therapeutic resistance are traditionally studied as separate fields using non-overlapping strategies. However, emerging evidence, including from in vivo imaging and in vitro organotypic culture, now suggests that both programmes cooperate and reinforce each other in the invasion niche and persist upon metastatic evasion. As a consequence, cancer cell subpopulations exhibiting metastatic invasion undergo multistep reprogramming that — beyond migration signalling — supports repair programmes, anti-apoptosis processes, metabolic adaptation, stemness and survival. Shared metastasis and therapy resistance signalling are mediated by multiple mechanisms, such as engagement of integrins and other context receptors, cell–cell communication, stress responses and metabolic reprogramming, which cooperate with effects elicited by autocrine and paracrine chemokine and growth factor cues present in the activated tumour microenvironment. These signals empower metastatic cells to cope with therapeutic assault and survive. Identifying nodes shared in metastasis and therapy resistance signalling networks should offer new opportunities to improve anticancer therapy beyond current strategies, to eliminate both nodular lesions and cells in metastatic transit. This Perspective outlines how the signalling pathways enabling metastasis are often shared with those supporting resistance to cancer therapies. Identifying nodes within these shared signalling networks that could be targeted might result in more effective therapies for the treatment of rapidly growing solid tumours.
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Metadata
- Authors
- Weiss, F., Lauffenburger, D., & Friedl, P.
- Venue
- Nature Reviews Cancer
- Published
- 2022-01-10
- Volume
- 22
- Issue
- 3
- Pages
- 157-173
- ISSN
- 1474-175X (ISSN-L)
- 1474-1768
- OpenAlex
- W4206722756
- Cited by
- 293
- References
- 204
- FWCI
- 10.59
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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