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Abstract Background Diffuse large B-cell lymphoma (DLBCL), an aggressive and heterogenic malignant entity, is still a challenging clinical problem, since around one-third of patients are not cured with primary treatment. Next-generation sequencing (NGS) technologies have revealed common genetic mutations in DLBCL. We devised an NGS multi-gene panel to discover genetic features of Chinese nodal DLBCL patients and provide reference information for panel-based NGS detection in clinical laboratories. Methods A panel of 116 DLBCL genes was designed based on the literature and related databases. We analyzed 96 Chinese nodal DLBCL biopsy specimens through targeted sequencing. Results The most frequently mutated genes were KMT2D (30%), PIM1 (26%), SOCS1 (24%), MYD88 (21%), BTG1 (20%), HIST1H1E (18%), CD79B (18%), SPEN (17%), and KMT2C (16%). SPEN (17%) and DDX3X (6%) mutations were highly prevalent in our study than in Western studies. Thirty-three patients (34%) were assigned as genetic classification by the LymphGen algorithm, including 12 cases MCD, five BN2, seven EZB, seven ST2, and two EZB/ST2 complex. MYD88 L265P mutation, TP53 and BCL2 pathogenic mutations were unfavorable prognostic biomarkers in DLBCL. Conclusions This study presents the mutation landscape in Chinese nodal DLBCL, highlights the genetic heterogeneity of DLBCL and shows the role of panel-based NGS to prediction of prognosis and potential molecular targeted therapy in DLBCL. More precise genetic classification needs further investigations.

Background: Diffuse large B-cell lymphoma (DLBCL), an aggressive and heterogenic malignant entity, is still a challenging clinical problem, since around one-third of patients are not cured with primary treatment. Next-generation sequencing (NGS) technologies have revealed common genetic mutations in DLBCL. We devised an NGS multi-gene panel to discover genetic features of Chinese nodal DLBCL patients and provide reference information for panel-based NGS detection in clinical laboratories. Methods: A panel of 116 DLBCL genes was designed based on the literature and related databases. We analyzed 96 Chinese nodal DLBCL biopsy specimens through targeted sequencing. Results: The most frequently mutated genes were KMT2D (30%), PIM1 (26%), SOCS1 (24%), MYD88 (21%), BTG1 (20%), HIST1H1E (18%), CD79B (18%), SPEN (17%), and KMT2C (16%). SPEN (17%) and DDX3X (6%) mutations were highly prevalent in our study than in Western studies. Thirty-three patients (34%) were assigned as genetic classification by the LymphGen algorithm, including 12 cases MCD, five BN2, seven EZB, seven ST2, and two EZB/ST2 complex. MYD88 L265P mutation, TP53 and BCL2 pathogenic mutations were unfavorable prognostic biomarkers in DLBCL. Conclusions: This study presents the mutation landscape in Chinese nodal DLBCL, highlights the genetic heterogeneity of DLBCL and shows the role of panel-based NGS to prediction of prognosis and potential molecular targeted therapy in DLBCL. More precise genetic classification needs further investigations. [ABSTRACT FROM AUTHOR]

Abstract Background Hereditary retinopathy is a significant cause of blindness worldwide. Despite the discovery of many mutations in various retinopathies, a large number of patients remain genetically undiagnosed. Targeted next-generation sequencing of the human genome is a suitable approach for the molecular diagnosis of retinopathy. Methods We describe a cohort of 211 families from central China with various forms of retinopathy; 95 patients were investigated using multigene panel sequencing, and the other 116 with suspected Leber hereditary optic neuropathy (LHON) were tested by Sanger sequencing. The detected variation of targeted sequencing was verified by PCR-based Sanger sequencing. We performed a comprehensive analysis of the cases using sequencing data and ophthalmologic examination information. Results Potential causal mutations were identified in the majority of families with retinopathy (57.9% of 95 families) and suspected LHON (21.6% of 116 families). There were 68 variants of a certain significance distributed in 31 known disease-causing genes in the 95 families; 37 of the variants are novel and have not been reported to be related to hereditary retinopathy. The NGS panel solution provided a 45.3% potential diagnostic rate for retinopathy families, with candidate gene mutations of undefined pathogenicity revealed in another 12.6%of the families. Conclusion Our study uncovered novel mutations and phenotypic aspects of retinopathy and demonstrated the genetic and clinical heterogeneity of related conditions. The findings show the detection rate of pathogenic variants in patients with hereditary retinopathy in central China as well as the diversity and gene distribution of these variants. The significance of molecular genetic testing for patients with hereditary retinopathy is also highlighted.

Abstract Background Systematic cancer screening has led to the increased detection of pre-malignant lesions (PMLs). The absence of reliable prognostic markers has led mostly to over treatment resulting in potentially unnecessary stress, or insufficient treatment and avoidable progression. Importantly, most mutational profiling studies have relied on PML synchronous to invasive cancer, or performed in patients without outcome information, hence limiting their utility for biomarker discovery. The limitations in comprehensive mutational profiling of PMLs are in large part due to the significant technical and methodological challenges: most PML specimens are small, fixed in formalin and paraffin embedded (FFPE) and lack matching normal DNA. Methods Using test DNA from a highly degraded FFPE specimen, multiple targeted sequencing approaches were evaluated, varying DNA input amount (3–200 ng), library preparation strategy (BE: Blunt-End, SS: Single-Strand, AT: A-Tailing) and target size (whole exome vs. cancer gene panel). Variants in high-input DNA from FFPE and mirrored frozen specimens were used for PML-specific variant calling training and testing, respectively. The resulting approach was applied to profile and compare multiple regions micro-dissected (mean area 5 mm2) from 3 breast ductal carcinoma in situ (DCIS). Results Using low-input FFPE DNA, BE and SS libraries resulted in 4.9 and 3.7 increase over AT libraries in the fraction of whole exome covered at 20x (BE:87%, SS:63%, AT:17%). Compared to high-confidence somatic mutations from frozen specimens, PML-specific variant filtering increased recall (BE:85%, SS:80%, AT:75%) and precision (BE:93%, SS:91%, AT:84%) to levels expected from sampling variation. Copy number alterations were consistent across all tested approaches and only impacted by the design of the capture probe-set. Applied to DNA extracted from 9 micro-dissected regions (8 PML, 1 normal epithelium), the approach achieved comparable performance, illustrated the data adequacy to identify candidate driver events (GATA3 mutations, ERBB2 or FGFR1 gains, TP53 loss) and measure intra-lesion genetic heterogeneity. Conclusion Alternate experimental and analytical strategies increased the accuracy of DNA sequencing from archived micro-dissected PML regions, supporting the deeper molecular characterization of early cancer lesions and achieving a critical milestone in the development of biology-informed prognostic markers and precision chemo-prevention strategies.

Abstract Background Targeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs). Methods To address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection. Results Our tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments. Conclusions AmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve.

Background: Hereditary retinopathy is a significant cause of blindness worldwide. Despite the discovery of many mutations in various retinopathies, a large number of patients remain genetically undiagnosed. Targeted next-generation sequencing of the human genome is a suitable approach for the molecular diagnosis of retinopathy. Methods: We describe a cohort of 211 families from central China with various forms of retinopathy; 95 patients were investigated using multigene panel sequencing, and the other 116 with suspected Leber hereditary optic neuropathy (LHON) were tested by Sanger sequencing. The detected variation of targeted sequencing was verified by PCR-based Sanger sequencing. We performed a comprehensive analysis of the cases using sequencing data and ophthalmologic examination information. Results: Potential causal mutations were identified in the majority of families with retinopathy (57.9% of 95 families) and suspected LHON (21.6% of 116 families). There were 68 variants of a certain significance distributed in 31 known disease-causing genes in the 95 families; 37 of the variants are novel and have not been reported to be related to hereditary retinopathy. The NGS panel solution provided a 45.3% potential diagnostic rate for retinopathy families, with candidate gene mutations of undefined pathogenicity revealed in another 12.6%of the families. Conclusion: Our study uncovered novel mutations and phenotypic aspects of retinopathy and demonstrated the genetic and clinical heterogeneity of related conditions. The findings show the detection rate of pathogenic variants in patients with hereditary retinopathy in central China as well as the diversity and gene distribution of these variants. The significance of molecular genetic testing for patients with hereditary retinopathy is also highlighted. [ABSTRACT FROM AUTHOR]