Standardization of Somatic Variant Classifications in Solid and Haematological Tumours by a Two-Level Approach of Biological and Clinical Classes: An Initiative of the Belgian ComPerMed Expert Panel

In most diagnostic laboratories, targeted next-generation sequencing (NGS) is currently the default assay for the detection of somatic variants in solid as well as haematological tumours. Independent of the method, the final outcome is a list of variants that differ from the human genome reference sequence of which some may relate to the establishment of the tumour in the patient. A critical point towards a uniform patient management is the assignment of the biological contribution of each variant to the malignancy and its subsequent clinical impact in a specific malignancy. These so-called biological and clinical classifications of somatic variants are currently not standardized and are vastly dependent on the subjective analysis of each laboratory. This subjectivity can thus result in a different classification and subsequent clinical interpretation of the same variant. Therefore, the ComPerMed panel of Belgian experts in cancer diagnostics set up a working group with the goal to harmonize the biological classification and clinical interpretation of somatic variants detected by NGS. This effort resulted in the establishment of a uniform, two-level classification workflow system that should enable high consistency in diagnosis, prognosis, treatment and follow-up of cancer patients. Variants are first classified into a tumour-independent biological five class system and subsequently in a four tier ACMG clinical classification. Here, we describe the ComPerMed workflow in detail including examples for each step of the pipeline. Moreover, this workflow can be implemented in variant classification software tools enabling automatic reporting of NGS data, independent of panel, method or analysis software.

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HGG-21. GERMLINE MUTATIONS IN MSH2 GENE IN PEDIATRIC PATIENTS WITH CONGENITAL AND SPORADIC GLIOBLASTOMA

Neuro-Oncology ◽

10.1093/neuonc/noaa222.308 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii348-iii348

Author(s):

Maria Ejmont ◽

Małgorzata Rydzanicz ◽

Wiesława Grajkowska ◽

Marta Perek-Polnik ◽

Agnieszka Sowińska ◽

...

Keyword(s):

Germline Mutations ◽

Response To Therapy ◽

Msh2 Gene ◽

Illumina Hiseq ◽

Adult Type ◽

Targeted Next Generation Sequencing ◽

Pathogenic Variants ◽

New Treatment ◽

Next Generation Sequencing Ngs ◽

Ngs Data

Abstract INTRODUCTION Glioblastoma (GBM) remains one of the biggest therapeutic challenges in neuro-oncology. In spite of multimodal treatment approaches the prognosis of GBM is extremely poor, median survival is estimated about 12–16 months. Although GBM is one of the most common and malignant primary brain tumors, pediatric glioblastoma, including congenital is a very rare tumor, with an incidence of about 1.1–3.4 per million live births. Moreover, the mode of presentation, behavior, response to therapy and molecular background of pediatric glioblastomas differs from adult type of GBM. Until now, about ten patients with congenital glioblastoma have been described and in none of them germline markers were examined. Here we report two patients with GBM, one with congenital tumor with germline mutations in MSH2 gene. METHODS Targeted Next-Generation Sequencing (NGS) of the probands DNA extracted from leucocytes was performed using the TruSight One sequencing panel on an Illumina HiSeq 1500. Applied gene panel investigated the coding sequence and splice sites of 4813 genes associated with known disease phenotypes. The NGS data were analyzed using an in-house procedure. Identified variants were validated by Sanger sequencing. RESULTS NGS analysis of patients constitutional DNA revealed know, pathogenic variants c.940C>T and c.942 + 3A>T in MSH2 gene (NM_000251.3) associated with MMR-dependent hereditary cancer syndromes. CONCLUSION Molecular analysis are heavily needed for better understanding of pediatric GBM etiology and new treatment modality implementation. Identification of this oncogenic driver may provide insight into the pathogenesis of GBM, including congenital cases. Funded by National Science Centre, Poland (2016/23/B/NZ2/03064 and 2016/21/B/NZ2/01785).

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The ICR96 exon CNV validation series: a resource for orthogonal assessment of exon CNV calling in NGS data

Wellcome Open Research ◽

10.12688/wellcomeopenres.11689.1 ◽

2017 ◽

Vol 2 ◽

pp. 35 ◽

Cited By ~ 7

Author(s):

Shazia Mahamdallie ◽

Elise Ruark ◽

Shawn Yost ◽

Emma Ramsay ◽

Imran Uddin ◽

...

Keyword(s):

Sequencing Data ◽

Targeted Next Generation Sequencing ◽

Negative Results ◽

Targeted Ngs ◽

Predisposition Genes ◽

Next Generation Sequencing Ngs ◽

Ngs Data ◽

Validation Series ◽

Generation Sequencing ◽

Dependent Probe

Detection of deletions and duplications of whole exons (exon CNVs) is a key requirement of genetic testing. Accurate detection of this variant type has proved very challenging in targeted next-generation sequencing (NGS) data, particularly if only a single exon is involved. Many different NGS exon CNV calling methods have been developed over the last five years. Such methods are usually evaluated using simulated and/or in-house data due to a lack of publicly-available datasets with orthogonally generated results. This hinders tool comparisons, transparency and reproducibility. To provide a community resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM or PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs, the most difficult type of exon CNV to detect. The FASTQ files for the ICR96 exon CNV validation series can be accessed through the European-Genome phenome Archive (EGA) under the accession number EGAS00001002428.

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MegaPath: sensitive and rapid pathogen detection using metagenomic NGS data

BMC Genomics ◽

10.1186/s12864-020-06875-6 ◽

2020 ◽

Vol 21 (S6) ◽

Author(s):

Chi-Ming Leung ◽

Dinghua Li ◽

Yan Xin ◽

Wai-Chun Law ◽

Yifan Zhang ◽

...

Keyword(s):

Pathogen Detection ◽

High Sensitivity ◽

Reference Sequence ◽

Close Relative ◽

Read Mapping ◽

Seeding Strategy ◽

Multiple Species ◽

Next Generation Sequencing Ngs ◽

Ngs Data ◽

Unique Species

Abstract Background Next-generation sequencing (NGS) enables unbiased detection of pathogens by mapping the sequencing reads of a patient sample to the known reference sequence of bacteria and viruses. However, for a new pathogen without a reference sequence of a close relative, or with a high load of mutations compared to its predecessors, read mapping fails due to a low similarity between the pathogen and reference sequence, which in turn leads to insensitive and inaccurate pathogen detection outcomes. Results We developed MegaPath, which runs fast and provides high sensitivity in detecting new pathogens. In MegaPath, we have implemented and tested a combination of polishing techniques to remove non-informative human reads and spurious alignments. MegaPath applies a global optimization to the read alignments and reassigns the reads incorrectly aligned to multiple species to a unique species. The reassignment not only significantly increased the number of reads aligned to distant pathogens, but also significantly reduced incorrect alignments. MegaPath implements an enhanced maximum-exact-match prefix seeding strategy and a SIMD-accelerated Smith-Waterman algorithm to run fast. Conclusions In our benchmarks, MegaPath demonstrated superior sensitivity by detecting eight times more reads from a low-similarity pathogen than other tools. Meanwhile, MegaPath ran much faster than the other state-of-the-art alignment-based pathogen detection tools (and compariable with the less sensitivity profile-based pathogen detection tools). The running time of MegaPath is about 20 min on a typical 1 Gb dataset.

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Microbiome signatures in prostate cancer

Carcinogenesis ◽

10.1093/carcin/bgz008 ◽

2019 ◽

Vol 40 (6) ◽

pp. 749-764 ◽

Cited By ~ 10

Author(s):

Sagarika Banerjee ◽

James C Alwine ◽

Zhi Wei ◽

Tian Tian ◽

Natalie Shih ◽

...

Keyword(s):

Prostate Cancer ◽

Direct Pcr ◽

Prostate Hyperplasia ◽

Targeted Next Generation Sequencing ◽

Cellular Genes ◽

Prostate Tumor Cells ◽

Next Generation Sequencing Ngs ◽

Ngs Data ◽

Benign Prostate ◽

Generation Sequencing

Abstract We have established a microbiome signature for prostate cancer using an array-based metagenomic and capture-sequencing approach. A diverse microbiome signature (viral, bacterial, fungal and parasitic) was observed in the prostate cancer samples compared with benign prostate hyperplasia controls. Hierarchical clustering analysis identified three distinct prostate cancer-specific microbiome signatures. The three signatures correlated with different grades, stages and scores of the cancer. Thus, microbiome signature analysis potentially provides clinical diagnosis and outcome predictions. The array data were validated by PCR and targeted next-generation sequencing (NGS). Specific NGS data suggested that certain viral genomic sequences were inserted into the host somatic chromosomes of the prostate cancer samples. A randomly selected group of these was validated by direct PCR and sequencing. In addition, PCR validation of Helicobacter showed that Helicobacter cagA sequences integrated within specific chromosomes of prostate tumor cells. The viral and Helicobacter integrations are predicted to affect the expression of several cellular genes associated with oncogenic processes.

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Phenocopy of a heterozygous carrier of X-linked retinitis pigmentosa due to mosaicism for a RHO variant

Scientific Reports ◽

10.1038/s41598-020-80400-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Ine Strubbe ◽

Caroline Van Cauwenbergh ◽

Julie De Zaeytijd ◽

Sarah De Jaegere ◽

Marieke De Bruyne ◽

...

Keyword(s):

Retinitis Pigmentosa ◽

Somatic Mosaicism ◽

Retinal Disease ◽

Hair Follicles ◽

Disease Genes ◽

Female Carrier ◽

Autofluorescence Imaging ◽

Targeted Next Generation Sequencing ◽

Whole Exome ◽

Next Generation Sequencing Ngs

AbstractWe describe both phenotype and pathogenesis in two male siblings with typical retinitis pigmentosa (RP) and the potentially X-linked RP (XLRP) carrier phenotype in their mother. Two affected sons, two unaffected daughters, and their mother underwent detailed ophthalmological assessments including Goldmann perimetry, color vision testing, multimodal imaging and ISCEV-standard electroretinography. Genetic testing consisted of targeted next-generation sequencing (NGS) of known XLRP genes and whole exome sequencing (WES) of known inherited retinal disease genes (RetNet-WES). Variant validation and segregation analysis were performed by Sanger sequencing. The mutational load of the RHO variant in the mother was assessed in DNA from leucocytes, buccal cells and hair follicles using targeted NGS. Both affected sons showed signs of classical RP, while the mother displayed patches of hyperautofluorescence on blue light autofluorescence imaging and regional, intraretinal, spicular pigmentation, reminiscent of a carrier phenotype of XLRP. XLRP testing was negative. RetNet-WES testing revealed RHO variant c.404G > C p.(Arg135Pro) in a mosaic state (21% of the reads) in the mother and in a heterozygous state in both sons. Targeted NGQSS of the RHO variant in different maternal tissues showed a mutation load between 25.06% and 41.72%. We report for the first time that somatic mosaicism of RHO variant c.404G > C p.(Arg135Pro) mimics the phenotype of a female carrier of XLRP, in combination with heterozygosity for the variant in the two affected sons.

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Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma

Cells ◽

10.3390/cells10020416 ◽

2021 ◽

Vol 10 (2) ◽

pp. 416

Author(s):

Lorena Landuzzi ◽

Maria Cristina Manara ◽

Pier-Luigi Lollini ◽

Katia Scotlandi

Keyword(s):

Clinical Trials ◽

Tumor Heterogeneity ◽

Functional Studies ◽

Ngs Data Analysis ◽

The Many ◽

Orthotopic Xenografts ◽

Next Generation Sequencing Ngs ◽

Ngs Data ◽

Generation Sequencing ◽

Somatic Copy Number Alterations

Osteosarcoma (OS) is a rare malignant primary tumor of mesenchymal origin affecting bone. It is characterized by a complex genotype, mainly due to the high frequency of chromothripsis, which leads to multiple somatic copy number alterations and structural rearrangements. Any effort to design genome-driven therapies must therefore consider such high inter- and intra-tumor heterogeneity. Therefore, many laboratories and international networks are developing and sharing OS patient-derived xenografts (OS PDX) to broaden the availability of models that reproduce OS complex clinical heterogeneity. OS PDXs, and new cell lines derived from PDXs, faithfully preserve tumor heterogeneity, genetic, and epigenetic features and are thus valuable tools for predicting drug responses. Here, we review recent achievements concerning OS PDXs, summarizing the methods used to obtain ectopic and orthotopic xenografts and to fully characterize these models. The availability of OS PDXs across the many international PDX platforms and their possible use in PDX clinical trials are also described. We recommend the coupling of next-generation sequencing (NGS) data analysis with functional studies in OS PDXs, as well as the setup of OS PDX clinical trials and co-clinical trials, to enhance the predictive power of experimental evidence and to accelerate the clinical translation of effective genome-guided therapies for this aggressive disease.

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Optimization of a WGA-Free Molecular Tagging-Based NGS Protocol for CTCs Mutational Profiling

International Journal of Molecular Sciences ◽

10.3390/ijms21124364 ◽

2020 ◽

Vol 21 (12) ◽

pp. 4364

Author(s):

Giuseppa De Luca ◽

Barbara Cardinali ◽

Lucia Del Mastro ◽

Sonia Lastraioli ◽

Franca Carli ◽

...

Keyword(s):

Substantial Reduction ◽

Breast Cancer Patients ◽

Dna Templates ◽

Molecular Tagging ◽

Mutational Profiling ◽

Optimized Protocol ◽

Set Up ◽

Detection Of Mutations ◽

Almost All ◽

Next Generation Sequencing Ngs

Molecular characterization of Circulating Tumor Cells (CTCs) is still challenging, despite attempts to minimize the drawbacks of Whole Genome Amplification (WGA). In this paper, we propose a Next-Generation Sequencing (NGS) optimized protocol based on molecular tagging technology, in order to detect CTCs mutations while skipping the WGA step. MDA-MB-231 and MCF-7 cell lines, as well as leukocytes, were sorted into pools (2–5 cells) using a DEPArray™ system and were employed to set up the overall NGS procedure. A substantial reduction of reagent volume for the preparation of libraries was performed, in order to fit the limited DNA templates directly derived from cell lysates. Known variants in TP53, KRAS, and PIK3CA genes were detected in almost all the cell line pools (35/37 pools, 94.6%). No additional alterations, other than those which were expected, were found in all tested pools and no mutations were detected in leukocytes. The translational value of the optimized NGS workflow is confirmed by sequencing CTCs pools isolated from eight breast cancer patients and through the successful detection of variants. In conclusion, this study shows that the proposed NGS molecular tagging approach is technically feasible and, compared to traditional NGS approaches, has the advantage of filtering out the artifacts generated during library amplification, allowing for the reliable detection of mutations and, thus, making it highly promising for clinical use.

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