An Overview of Advances in Rare Cancer Diagnosis and Treatment.
rare cancer diagnosis
rare cancer treatment
rare cancers
Journal
International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791
Informations de publication
Date de publication:
18 Jan 2024
18 Jan 2024
Historique:
received:
01
12
2023
revised:
11
01
2024
accepted:
17
01
2024
medline:
23
1
2024
pubmed:
23
1
2024
entrez:
23
1
2024
Statut:
epublish
Résumé
Cancer stands as the leading global cause of mortality, with rare cancer comprising 230 distinct subtypes characterized by infrequent incidence. Despite the inherent challenges in addressing the diagnosis and treatment of rare cancers due to their low occurrence rates, several biomedical breakthroughs have led to significant advancement in both areas. This review provides a comprehensive overview of state-of-the-art diagnostic techniques that encompass new-generation sequencing and multi-omics, coupled with the integration of artificial intelligence and machine learning, that have revolutionized rare cancer diagnosis. In addition, this review highlights the latest innovations in rare cancer therapeutic options, comprising immunotherapy, targeted therapy, transplantation, and drug combination therapy, that have undergone clinical trials and significantly contribute to the tumor remission and overall survival of rare cancer patients. In this review, we summarize recent breakthroughs and insights in the understanding of rare cancer pathophysiology, diagnosis, and therapeutic modalities, as well as the challenges faced in the development of rare cancer diagnosis data interpretation and drug development.
Identifiants
pubmed: 38256274
pii: ijms25021201
doi: 10.3390/ijms25021201
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Research Foundation of Korea
ID : NRF-2022R1A2C1091563
Organisme : National Research Foundation of Korea
ID : NRF-2019M3E5D3073090
Organisme : National Research Foundation of Korea
ID : NRF-2019R1A5A8083404