RNA sequencing effectively identifies gene fusions undetected by DNA sequencing in lung adenocarcinomas.

3052 Background: Next-generation sequencing of DNA, which can provide valid information for clinical therapeutic decision-making, has been widely used in the management of lung cancer especially adenocarcinoma. However, due to its technical limitations for detecting certain alterations such as gene rearrangement, the DNA-based sequencing (DNA-seq) may miss the actionable alteration in some cases, who would have benefited from targeted therapy. The study aimed to evaluate the capability of RNA sequencing (RNA-seq) in identifying DNA-seq undetectable gene alterations in lung adenocarcinomas. Methods: A total of 219 lung adenocarcinomas, which had no driver alteration detected by DNA-seq (OncoScreen Plus, Burning Rock Biotech) and had a max AF ≥5%, underwent capture-based RNA-seq using a custom panel (OncoRNA, Burning Rock Biotech) spanning full transcripts of 115 genes commonly involved in cancer genomic rearrangements. Furthermore, an independent cohort of 100 DNA-seq driver–negative lung adenocarcinomas were also subjected to RNA-seq with the same panel. Results: In the discovery cohort, 166/219 samples (75.8%) generated qualified RNA-seq data for subsequent analyses. RNA-seq identified 44 previously undetected alterations (26.5%), including 40 gene fusions (24.1%), 1 MET exon14 skipping variant ( METex14, 0.6%) and 3 other alternative splicing variants (1.8%). Among them, 14 (8.4%) were potential actionable alterations, consisting of METex14 and in-frame fusions containing functional domain of the driver gene (4 ROS1 fusions, 3 BRAF fusions, 2 NRG1 fusions, 2 EGFR fusions, 1 ALK fusion and 1 MET fusion). In the validation cohort, 69/100 samples (69.0%) generated qualified data. RNA-seq identified 22 DNA-seq undetected alterations (31.9%), with 7 of them being potential actionable fusions (10.1%). ROS1 fusion remained as the most common actionable alteration (n = 3), followed by ALK fusion (n = 2), EGFR fusion (n = 1) and MET fusion (n = 1). Further analyses of the two datasets revealed that lacking sufficient coverage spanning the rearrangement breakpoint in the DNA-seq panel mainly accounted for the failure of DNA-seq on detecting these fusions. This can be improved by increasing the corresponding probe coverage in the DNA-seq panel. In addition, complex genomic rearrangement at DNA level and the presence of repetitive sequence in the intronic region spanning or adjacent to the breakpoint might lead to missed calling of canonical fusions by DNA-seq. Conclusions: Targeted RNA-seq can effectively identify genomic rearrangements that are undetectable by DNA-seq and provide lung adenocarcinoma patients with more opportunities for targeted therapy. Therefore, it should be recommended for all patients, in whom DNA-seq fails to detect driver alteration.

Concordance of copy number abnormality detection using SNP arrays and Multiplex Ligation-dependent Probe Amplification (MLPA) in acute lymphoblastic leukaemia

In acute lymphoblastic leukaemia, MLPA has been used in research studies to identify clinically relevant copy number abnormality (CNA) profiles. However, in diagnostic settings other techniques are often employed. We assess whether equivalent CNA profiles are called using SNP arrays, ensuring platform independence. We demonstrate concordance between SNP6.0 and MLPA CNA calling on 143 leukaemia samples from two UK trials; comparing 1,287 calls within eight genes and a region. The techniques are 99% concordant using manually augmented calling, and 98% concordant using an automated pipeline. We classify these discordant calls and examine reasons for discordance. In nine cases the circular binary segmentation (CBS) algorithm failed to detect focal abnormalities or those flanking gaps in IKZF1 probe coverage. Eight cases were discordant due to probe design differences, with focal abnormalities detectable using one technique not observable by the other. Risk classification using manually augmented array calling resulted in four out of 143 patients being assigned to a different CNA risk group and eight patients using the automated pipeline. We conclude that MLPA defined CNA profiles can be accurately mirrored by SNP6.0 or similar array platforms. Automated calling using the CBS algorithm proved successful, except for IKZF1 which should be manually inspected.

Development of Assisted Software for TOFD Testing

The detection of flaws is essential as the defects of pipes and containers affect the safe operation of many kinds of equipment. During the industrial production process, it is usually use the ray method to detect the flaws which has radiant effect on the testing personnel. The ultrasonic time-of-flight diffraction (TOFD) is a new type acoustic detection method and it is relatively safe for users. When using the TOFD technique, the selection of the probe separation is the important parameter which related to the effect of the test and the coverage range of the probe identifies the effective range of the detection. In this paper, the probe separation distance and the probe coverage range procedures which can help the testing personnel set the parameters quickly is devised. The experimental results indicate that this algorit