Real-World Experiences of Next-Generation Sequencing in Oncology: From an Indian Multicenter Registry and Collaborative Centers
Background The integration of next-generation sequencing (NGS) in guiding personalized therapy for oncology faces the challenges, primarily, of cost and drug accessibility. Limited data from Indian academic centers accentuate the need for comprehensive insights into the real-world applications of NG...
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Veröffentlicht in: | Indian journal of medical and paediatric oncology 2024-01 |
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Sprache: | eng |
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Zusammenfassung: | Background The integration of next-generation sequencing (NGS) in guiding personalized therapy for oncology faces the challenges, primarily, of cost and drug accessibility. Limited data from Indian academic centers accentuate the need for comprehensive insights into the real-world applications of NGS in oncology.
Methods The Network of Oncology Clinical Trials in India (NOCI), accessible at www.noci-india.com, compiled data on patients who underwent NGS for solid organ cancers from January 1, 2018, to December 31, 2021. This study aimed to elucidate the testing indications, sample types analyzed, and the resultant impact on patient care.
Results Analysis of data from six centers included 278 subjects, with 24 specimens (9%) excluded due to quality test failure. Tissue constituted 59.7% of specimens, blood 38.5%, and both 1.8%. Predominantly, NGS was employed for identifying BRCA1/2 mutations (56%) and for targeted therapy in non-small-cell lung cancer (NSCLC; 28%). Only 41 (16%) patients with other cancers underwent multigene NGS panels in pursuit of targetable mutations. Among them, 13 exhibited targetable mutations, and 3 received treatment based on NGS findings.
Conclusion This study underscores that the majority of NGS applications focused on screening for BRCA1/2 mutations and identifying targetable mutations in NSCLC. However, among those undergoing NGS for advanced cancers, only a limited number received personalized therapy. The findings underscore the challenges of utilizing NGS in off-label indications within resource-constrained settings. |
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ISSN: | 0971-5851 0975-2129 |
DOI: | 10.1055/s-0044-1779275 |