Using genetics to inform the pharmacological targeting of neuroendocrine neoplasms.

molecular genetics neuroendocrine neoplasms oncology targeted therapy

Journal

Endocrine-related cancer
ISSN: 1479-6821
Titre abrégé: Endocr Relat Cancer
Pays: England
ID NLM: 9436481

Informations de publication

Date de publication:
09 2020
Historique:
received: 11 06 2020
accepted: 15 06 2020
pubmed: 17 6 2020
medline: 26 8 2021
entrez: 17 6 2020
Statut: ppublish

Résumé

Neuroendocrine neoplasms (NEN) are a class of tumours heterogeneous in terms of their anatomical sites of origin and clinical behaviour. Outdated perspectives of indolence have been superseded by appreciation for their myriad clinical challenges, such as the high rates of regional and distant metastases at initial diagnosis, lack of clarity on optimal treatment strategies/sequencing, and incompletely elucidated genetic/other pathophysiological drivers. The first randomised controlled trials in this arena were published approximately a decade ago - since then, increased understanding of the genetic drivers and signalling pathway perturbations in these tumours have suggested promise for precision therapy influenced by an individual tumour's molecular sub-type, but this is yet to be realised for manifold reasons. In this article, the authors review the genetic landscapes as currently understood for selected forms of NEN and discuss the current and developing evidence to support the use of genetic information to influence therapy. They provide a critical assessment of the potential limitations of using such approaches and also posit avenues for future developments in this arena.

Identifiants

pubmed: 32544880
doi: 10.1530/ERC-20-0074
pii: ERC-20-0074.R2
doi:
pii:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

R293-R305

Auteurs

Ashley K Clift (AK)

Department of Surgery and Cancer, Imperial College London, London, UK.
NHS Nightingale Hospital London, London, UK.

Andrea Frilling (A)

Department of Surgery and Cancer, Imperial College London, London, UK.

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Classifications MeSH