Potential unreliability of ALK variant allele frequency in the efficacy prediction of targeted therapy in NSCLC

Anaplastic lymphoma kinase(ALK)is the most common fusion gene involved in non-small cell lung cancer(NSCLC),and remarkable response has been achieved with the use of ALK tyrosine kinase inhibitors(ALK-TKIs).However,the clinical efficacy is highly variable.Pre-existing intratumoral heterogeneity(ITH)has been proven to contribute to the poor treatment response and the resistance to targeted therapies.In this work,we investigated whether the variant allele frequencies(VAFs)of ALK fusions can help assess ITH and predict targeted therapy efficacy.Through the application of next-generation sequencing(NGS),7.2%(326/4548)of patients were detected to be ALK positive.On the basis of the adjusted VAF(adjVAF,VAF normalization for tumor purity)of four different threshold values(adjVAF<50%,40%,30%,or 20%),the association of ALK subclonality with crizotinib efficacy was assessed.Nonetheless,no statistical association was observed between median progression-free survival(PFS)and ALK subclonality assessed by adjVAF,and a poor correlation of adjVAF with PFS was found among the 85 patients who received first-line crizotinib.Results suggest that the ALK VAF determined by hybrid capture-based NGS is probably unreliable for ITH assessment and targeted therapy efficacy prediction in NSCLC.

SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples

Accurate detection of low frequency mutations from plasma cell-free DNA in blood using targeted next generation sequencing technology has shown promising benefits in clinical settings.Duplex sequencing technology is the most commonly used approach in liquid biopsies.Unique molecular identifiers are attached to each double-stranded DNA template,followed by production of low-error consensus sequences to detect low frequency variants.However,high sequencing costs have hindered application of this approach in clinical practice.Here,we have developed an improved duplex sequencing approach called Sino Duplex,which utilizes a pool of adapters containing pre-defined barcode sequences to generate far fewer barcode combinations than with random sequences,and implemented a novel computational analysis algorithm to generate duplex consensus sequences more precisely.Sino Duplex increased the output of duplex sequencing technology,making it more cost-effective.We evaluated our approach using reference standard samples and cell-free DNA samples from lung cancer patients.Our results showed that Sino Duplex has high sensitivity and specificity in detecting very low allele frequency mutations.The source code for Sino Duplex is freely available at https://github.com/Sin Oncology/sinoduplex.