Review of Therapeutic Strategies for Anaplastic Lymphoma Kinase-Rearranged Non-Small Cell Lung Cancer
Non-small cell lung cancer (NSCLC) with anaplastic lymphoma kinase rearrangement (ALK) was first reported in 2007. ALK-rearranged NSCLC accounts for about 3-8% of NSCLC. The first-line therapy for ALK-rearranged advanced NSCLC is tyrosine kinase inhibitors (TKI) targeting ALK. Following the developm...
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Published in | Cancers Vol. 14; no. 5; p. 1184 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
MDPI AG
01.03.2022
MDPI |
Subjects | |
Online Access | Get full text |
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Summary: | Non-small cell lung cancer (NSCLC) with anaplastic lymphoma kinase rearrangement (ALK) was first reported in 2007. ALK-rearranged NSCLC accounts for about 3-8% of NSCLC. The first-line therapy for ALK-rearranged advanced NSCLC is tyrosine kinase inhibitors (TKI) targeting ALK. Following the development of crizotinib, the first ALK-TKI, patient prognosis has been greatly improved. Currently, five TKIs are approved by the FDA. In addition, clinical trials of the novel TKI, ensartinib, and fourth-generation ALK-TKI for compound ALK mutation are ongoing. Treatment with angiogenesis inhibitors and immune checkpoint inhibitors is also being studied. However, as the disease progresses, cancers tend to develop resistance mechanisms. In addition to ALK mutations, other mechanisms, including the activation of bypass signaling pathways and histological transformation, cause resistance, and the identification of these mechanisms is important in selecting subsequent therapy. Studies on tissue and liquid biopsy have been reported and are expected to be useful tools for identifying resistance mechanisms. The purpose of this manuscript is to provide information on the recent clinical trials of ALK-TKIs, angiogenesis inhibitors, immune checkpoint inhibitors, and chemotherapy to describe tissue and liquid biopsy as a method to investigate the mechanisms of resistance against ALK-TKIs and suggest a proposed treatment algorithm. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 |
ISSN: | 2072-6694 2072-6694 |
DOI: | 10.3390/cancers14051184 |