Original Article
Exploratory analysis of introducing next-generation sequencing-based method to treatment-naive lung cancer patients
Abstract
Background: The utilization of cancer-linked genetic alterations for categorizing patients against optimal treatment is becoming increasingly popular, especially in non-small cell lung cancer (NSCLC). However, disadvantages of the conventional techniques, such as the low throughput and limited detectable alteration types, lead to the demand of large-scale parallel sequencing for different forms of genetic variants.
Methods: We evaluated the potential of performing next-generation sequencing (NGS)-based methods in a cohort of 61 treatment-naive NSCLC patients to profile their driver mutations, using a panel consisting of 8 well-established driver genes of lung cancer.
Results: Our data revealed that 80% of patients harbored driver mutations. Moreover, our data revealed a few rare mutations, such as BRAF K601E and EGFR exon 20 insertion, which cannot be detected using commercially available single gene testing kits of conventional methods. We detected one patient with dual driver mutations. Next, correlations between driver mutations and clinical characteristics were interrogated in this cohort. Our results revealed that EGFR alterations were positively correlated with early stage, adenocarcinoma, alveolar and papillary component, TTF1 expression, and negatively correlated with P40 and Ki67 expression. ERBB2 alterations were associated with younger age and micro-invasive feature of tumor. Rearrangements of ALK indicated tumor relapse.
Conclusions: Our study highlights the potential of NGS-based methods in treatment-naive patients, thus paving its way for routine clinical use. Investigation of clinical correlation of driver mutations might be helpful for clinicians in cancer diagnosis and has implications for seeking patients with specific gene alteration in clinical studies.
Methods: We evaluated the potential of performing next-generation sequencing (NGS)-based methods in a cohort of 61 treatment-naive NSCLC patients to profile their driver mutations, using a panel consisting of 8 well-established driver genes of lung cancer.
Results: Our data revealed that 80% of patients harbored driver mutations. Moreover, our data revealed a few rare mutations, such as BRAF K601E and EGFR exon 20 insertion, which cannot be detected using commercially available single gene testing kits of conventional methods. We detected one patient with dual driver mutations. Next, correlations between driver mutations and clinical characteristics were interrogated in this cohort. Our results revealed that EGFR alterations were positively correlated with early stage, adenocarcinoma, alveolar and papillary component, TTF1 expression, and negatively correlated with P40 and Ki67 expression. ERBB2 alterations were associated with younger age and micro-invasive feature of tumor. Rearrangements of ALK indicated tumor relapse.
Conclusions: Our study highlights the potential of NGS-based methods in treatment-naive patients, thus paving its way for routine clinical use. Investigation of clinical correlation of driver mutations might be helpful for clinicians in cancer diagnosis and has implications for seeking patients with specific gene alteration in clinical studies.
