Comparison of two high-throughput semiconductor chip sequencing platforms in noninvasive prenatal testing for Down syndrome in early pregnancy.

BACKGROUND: Noninvasive prenatal testing (NIPT) to detect fetal aneuploidy using next-generation sequencing on ion semiconductor platforms has become common. There are several sequencers that can generate sufficient DNA reads for NIPT. However, the approval criteria vary among platforms and countries. This can delay the introduction of such devices and systems to clinics. A comparison of the sensitivity and specificity of two different platforms using the same sequencing chemistry could be useful in NIPT for fetal chromosomal aneuploidies. This would improve healthcare authorities' confidence in decision-making on sequencing-based tests. METHODS: One hundred and one pregnant women who were predicted at high risk of fetal defects using conventional prenatal screening tests, and who underwent definitive diagnosis by full karyotyping, were enrolled from three hospitals in Korea. Most of the pregnant women (69.79 %) received NIPT during weeks 11-13 of gestation and 30.21 % during weeks 14-18. We used Ion Torrent PGM and Proton semi-conductor-based sequencers with 0.3× sequencing coverage depth. The average total reads of 101 samples were approximately 4.5 and 7.6 M for PGM and Proton, respectively. A Burrows-Wheeler Aligner (BWA) algorithm was used for the alignment, and a z-score was used to decide fetal trisomy 21. Interactive dot diagrams from the sequencing data showed minimal z-score values of 2.07 and 2.10 to discriminate negative versus positive cases of fetal trisomy 21 for the two different sequencing systems. RESULTS: Our z-score-based discrimination method resulted in 100 % positive and negative prediction values for both ion semiconductor PGM and Proton sequencers, regardless of their sequencing chip and chemistry differences. Both platforms performed well at an early stage (11-13 weeks of gestation) compared with previous studies. CONCLUSIONS: These results suggested that, using two different sequencers, NIPT to detect fetal trisomy 21 in early pregnancy is accurate and platform-independent. The data suggested that the amount of sequencing and the application of common, simple, and robust statistical analyses are more important than sequencing chemistry and platform types. This result has practical implications in countries where PGM is approved for NIPT but the Proton system is not.

Identification of genomic mutations associated with clinical outcomes of induction chemotherapy in patients with head and neck squamous cell carcinoma.

PURPOSE: We performed deep sequencing of target genes in head and neck squamous cell carcinoma (HNSCC) tumors to identify somatic mutations that are associated with induction chemotherapy (IC) response. METHODS: Patients who were diagnosed with HNSCC were retrospectively identified. Patients who were treated with IC were divided into two groups: good responders and poor responders by tumor response and progression-free survival. Targeted gene sequencing for 2404 somatic mutations of 44 genes was performed on HNSCC tissues. Mutations with total coverage of <500 were excluded, and the cutoff for altered allele frequency was >10 %. RESULTS: Of the 71 patients, 45 were treated upfront with IC. Mean total coverage was 1941 per locus, and 42.2 % of tumors had TP53 mutations. Thirty-three mutations in TP53, NOTCH3, FGFR2, FGFR3, ATM, EGFR, MET, PTEN, FBXW7, SYNE1, and SUFU were frequently altered in poor responders. Among the patients who were treated with IC, those with unfavorable genomic profiles had significantly poorer overall survival than those without unfavorable genomic profiles (hazard ratio 6.45, 95 % confidence interval 2.07-20.10, P < 0.001). CONCLUSIONS: Comprehensive analysis of mutation frequencies identified unfavorable genomic profiles, and the patients without unfavorable genomic profiles can obtain clinical benefits from IC in patients with HNSCC.

An adaptive detection method for fetal chromosomal aneuploidy using cell-free DNA from 447 Korean women.

BACKGROUND: Noninvasive prenatal testing (NIPT) using massively parallel sequencing of cell-free DNA (cfDNA) is increasingly being used to predict fetal chromosomal abnormalities. However, concerns over erroneous predictions which occur while performing NIPT still exist in pregnant women at high risk for fetal aneuploidy. We performed the largest-scale clinical NIPT study in Korea to date to assess the risk of false negatives and false positives using next-generation sequencing. METHODS: A total of 447 pregnant women at high risk for fetal aneuploidy were enrolled at 12 hospitals in Korea. They underwent definitive diagnoses by full karyotyping by blind analysis and received aneuploidy screening at 11-22 weeks of gestation. Three steps were employed for cfDNA analyses. First, cfDNA was sequenced. Second, the effect of GC bias was corrected using normalization of samples as well as LOESS and linear regressions. Finally, statistical analysis was performed after selecting a set of reference samples optimally adapted to a test sample from the whole reference samples. We evaluated our approach by performing cfDNA testing to assess the risk of trisomies 13, 18, and 21 using the sets of extracted reference samples. RESULTS: The adaptive selection algorithm presented here was used to choose a more optimized reference sample, which was evaluated by the coefficient of variation (CV), demonstrated a lower CV and higher sensitivity than standard approaches. Our adaptive approach also showed that fetal aneuploidies could be detected correctly by clearly splitting the z scores obtained for positive and negative samples. CONCLUSIONS: We show that our adaptive reference selection algorithm for optimizing trisomy detection showed improved reliability and will further support practitioners in reducing both false negative and positive results.

The tiger genome and comparative analysis with lion and snow leopard genomes.

Tigers and their close relatives (Panthera) are some of the world's most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats' hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species.