reconCNV: interactive visualization of copy number data from high-throughput sequencing.

SUMMARY: Copy number variation (CNV) is an important category of unbalanced structural rearrangement. While methods for detecting CNV in high-throughput targeted sequencing have become increasingly sophisticated, dedicated tools for interactive and dynamic visualization of CNV from these data are still lacking. We describe reconCNV, a tool that produces an interactive and annotated web-based dashboard for viewing and summarizing CNVs detected in next-generation sequencing (NGS) data. reconCNV is designed to work with delimited result files from most NGS CNV callers with minor adjustments to the configuration file. The reconCNV output is an HTML file that is viewable on any modern web browser, requires no backend server, and can be readily appended to existing analysis pipelines. In addition to a standard CNV track for visualizing relative fold change and absolute copy number, the tool includes an auxiliary variant allele fraction track for visualizing underlying allelic imbalance and loss of heterozygosity. A feature to mask assay-specific technical artifacts and a direct HTML link out to the UCSC Genome Browser are also included to augment the reviewer experience. By providing a light-weight plugin for interactive visualization to existing NGS CNV pipelines, reconCNV can facilitate efficient NGS CNV visualization and interpretation in both research and clinical settings. AVAILABILITY AND IMPLEMENTATION: The source code and documentation including a tutorial can be accessed at https://github.com/rghu/reconCNV as well as a Docker image at https://hub.docker.com/repository/docker/raghuc1990/reconcnv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genomic analysis and preclinical xenograft model development identify potential therapeutic targets for MYOD1-mutant soft-tissue sarcoma of childhood.

The myogenic differentiation 1 gene (MYOD1) p.L122R somatic mutation was first discovered in a subset of clinically aggressive embryonal rhabdomyosarcomas and has since been described in both pediatric and adult spindle cell/sclerosing rhabdomyosarcomas. Relatively little is known about the clinical, molecular, and histopathological features of these tumors in children. In order to further characterize the genomic and clinical features of pediatric MYOD1-mutant sarcomas, we evaluated a cohort of soft-tissue sarcoma patients treated at Texas Children's Hospital. Tumor DNA was subjected to next-generation panel sequencing and/or Sanger sequencing of the MYOD1 hotspot mutation. The MYOD1 p.L122R mutation was identified in six tumors, with a variant allele fraction greater than 0.8 in three cases, suggestive of loss of heterozygosity. One sclerosing rhabdomyosarcoma lacking the MYOD1 hotspot mutation was observed to have a MYOD1 copy number gain, also with evidence of loss of heterozygosity. Cancer gene panel sequencing revealed potentially targetable alterations in six of seven (86%) patients with MYOD1 alterations, including four patients with an alteration in the PI3K-AKT pathway: two hotspot PIK3CA mutations and deletions in PTEN and TSC2. On histopathologic review, MYOD1-altered tumors exhibited spindle and/or round cells and varying degrees of hyaline sclerosis. At last follow-up, six patients had died of disease and the seventh progressed early and was subsequently lost to follow-up. Both pre- and post-therapy patient-derived xenograft models were generated from one patient's tumor. These models were confirmed to harbor the MYOD1 and PIK3CA mutations seen in the primary tumor and were shown to be sensitive to PI3K/mTOR inhibition in vitro and in vivo. In conclusion, this study adds to recent reports describing the clinicopathologic and genomic features of MYOD1-altered soft-tissue sarcomas in children, including dismal prognosis and potential molecular targets for therapy. The novel preclinical models developed will facilitate further biological and preclinical study of this rare and aggressive tumor. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Integrated DNA and RNA sequencing reveals targetable alterations in metastatic pediatric papillary thyroid carcinoma.

BACKGROUND: Pediatric papillary thyroid carcinoma (PTC) is clinically and biologically distinct from adult PTC. We sequenced a cohort of clinically annotated pediatric PTC cases enriched for high-risk tumors to identify genetic alterations of relevance for diagnosis and therapy. METHODS: Tumor DNA and RNA were extracted from FFPE tissue and subjected to next-generation sequencing (NGS) library preparation using a custom 124-gene hybridization capture panel and the 75-gene Archer Oncology Research Panel, respectively. NGS libraries were sequenced on an Illumina MiSeq. RESULTS: Thirty-six pediatric PTC cases were analyzed. Metastases were frequently observed to cervical lymph nodes (29/36, 81%), with pulmonary metastases less commonly found (10/36, 28%). Relapsed or refractory disease occurred in 18 patients (18/36, 50%). DNA sequencing revealed targetable mutations in 8 of 31 tumors tested (26%), most commonly BRAF p.V600E (n = 6). RNA sequencing identified targetable fusions in 13 of 25 tumors tested (52%): RET (n = 8), NTRK3 (n = 4), and BRAF. Mutually exclusive targetable alterations were discovered in 15 of the 20 tumors (75%) with both DNA and RNA analyzed. Fusion-positive PTC was associated with multifocal disease, higher tumor staging, and higher American Thyroid Association risk levels. Both BRAF V600E mutations and gene fusions were correlated with the presence of cervical metastases. CONCLUSIONS: Targetable alterations were identified in 75% of pediatric PTC cases with both DNA and RNA evaluated. Inclusion of RNA sequencing for detection of fusion genes is critical for evaluation of these tumors. Patients with fusion-positive tumors were more likely to have features of high-risk disease.

Somatic genetic alterations in synchronous and metachronous low-grade serous tumours and high-grade carcinomas of the adnexa.

AIMS: Low-grade serous carcinomas (LGSCs) and their precursors serous borderline tumours (SBTs) characteristically harbour mutations in BRAF, KRAS or NRAS but rarely in TP53, whereas high-grade serous carcinomas (HGSCs) are characterised by frequent TP53 mutations but rare BRAF, KRAS or NRAS mutations. In a small subset of cases, LGSCs and/or SBTs develop into high-grade tumours, including HGSCs and poorly differentiated carcinomas (PDCs). Here, we sought to define the repertoire of somatic genetic alterations in low-grade serous tumours and synchronous or metachronous high-grade adnexal carcinomas. METHODS AND RESULTS: DNA extracted from five SBTs/LGSCs and synchronous or metachronous HGSCs/PDCs and matched normal tissue was subjected to massively parallel sequencing targeting all exons and selected non-coding regions of 341 cancer-related genes. The low-grade and high-grade tumours from a given case were related, and shared mutations and copy number alterations. Progression from low-grade to high-grade lesions was observed, and involved the acquisition of additional mutations and/or copy number alterations, or shifts from subclonal to clonal mutations. Only two (an HGSC and a PDC) of the five high-grade tumours investigated harboured TP53 mutations, whereas NRAS and KRAS hotspot mutations were seen in two HGSCs and one HGSC, respectively. CONCLUSIONS: Our results suggest that progression from SBT to HGSC may take place in a subset of cases, and that at least some of the rare HGSCs lacking TP53 mutations may be derived from a low-grade serous precursor.

Frequent IDH2 R172 mutations in undifferentiated and poorly-differentiated sinonasal carcinomas.

Sinonasal undifferentiated carcinoma (SNUC) is a high-grade malignancy with limited treatment options and poor outcome. A morphological spectrum of 47 sinonasal tumours including 17 (36.2%) SNUCs was analysed at genomic level. Thirty carcinomas (cohort 1) were subjected to a hybridization exon-capture next-generation sequencing assay (MSK-IMPACTTM ) to interrogate somatic variants in 279 or 410 cancer-related genes. Seventeen sinonasal tumours (cohort 2) were examined only for the presence of IDH1/2 exon 4 mutations by Sanger sequencing. IDH2 R172 single nucleotide variants were overall detected in 14 (82.4%) SNUCs, in two (20%) poorly-differentiated carcinomas with glandular/acinar differentiation, and in one of two high-grade neuroendocrine carcinomas, large cell type (HGNECs). No IDH2 mutation was detected in any of five olfactory neuroblastomas or in any of five SMARCB1-deficient carcinomas. Among 12 IDH2-mutated cases in cohort 1, five (41.7%) harboured co-existing TP53 mutations, four (33.3%) CDKN2A/2B loss-of-function alterations, four (33.3%) MYC amplification, and three (25%) had concurrent SETD2 mutations. AKT1 E17K and KIT D816V hotspot variants were each detected in one IDH2-mutated SNUC. The vast majority of SNUCs and variable proportions of other poorly-differentiated sinonasal carcinomas may be amenable to IDH2-targeted therapy. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A Validation Framework for Somatic Copy Number Detection in Targeted Sequencing Panels.

Somatic copy number alterations (SCNAs) in tumors are clinically significant diagnostic, prognostic, and predictive biomarkers. SCNA detection from targeted next-generation sequencing panels is increasingly common in clinical practice; however, detailed descriptions of optimization and validation of SCNA pipelines for small targeted panels are limited. This study describes the validation and implementation of a tumor-only SCNA pipeline using CNVkit, augmented with custom modules and optimized for clinical implementation by testing reference materials and clinical tumor samples with different classes of copy number variation (CNV; amplification, single copy loss, and biallelic loss). Using wet-bench and in silico methods, various parameters impacting CNV calling, including assay-intrinsic variables (establishment of normal reference and sequencing coverage), sample-intrinsic variables (tumor purity and sample quality), and CNV algorithm-intrinsic variables (bin size), were optimized. The pipeline was trained and tested on an optimization cohort and validated using an independent cohort with a sensitivity and specificity of 100% and 93%, respectively. Using custom modules, intragenic CNVs with breakpoints within tumor suppressor genes were uncovered. Using the validated pipeline, re-analysis of 28 pediatric solid tumors that had been previously profiled for mutations identified SCNAs in 86% (24/28) samples, with 46% (13/28) samples harboring findings of potential clinical relevance. Our report highlights the importance of rigorous establishment of performance characteristics of SCNA pipelines and presents a detailed validation framework for optimal SCNA detection in targeted sequencing panels.

The Molecular Landscape of Recurrent and Metastatic Head and Neck Cancers: Insights From a Precision Oncology Sequencing Platform.

IMPORTANCE: Recurrent and/or metastatic head and neck cancer is usually incurable. Implementation of precision oncology for these patients has been limited by incomplete understanding of the molecular alterations underlying advanced disease. At the same time, the molecular profiles of many rare head and neck cancer types are unknown. These significant gaps in knowledge need to be addressed to rationally devise new therapies. OBJECTIVE: To illuminate the distinct biology of recurrent and metastatic head and neck cancers and review implementation of precision oncology for patients with advanced disease. DESIGN, SETTING, AND PARTICIPANTS: After exclusions, 151 patients with advanced, treatment-resistant head and neck tumors, including squamous cell carcinoma (HNSCC), adenoid cystic carcinoma (ACC), and other salivary and cutaneous cancers, whose tumors were sequenced between January 2014 and July 2015 at Memorial Sloan Kettering were recruited. Next-generation sequencing of tumors as part of clinical care included high-depth (median 600×) exonic coverage of 410 cancer genes and whole-genome copy number analysis. INTERVENTIONS: Next-generation sequencing of tumors and matched normal DNA. MAIN OUTCOMES AND MEASURES: Feasibility, the frequency of actionable molecular alterations, the effect on decision making, and identification of alterations associated with recurrent and metastatic disease. RESULTS: Overall, 151 patients (95 men and 56 women; mean [range] age, 61.8 [17-100] years) were included in the study. Next-generation sequencing ultimately guided therapy in 21 of 151 patients (14%) (13 of 53 [25%] of patients with HNSCC) by refining diagnoses and matching patients to specific therapies, in some cases with dramatic responses on basket studies. Molecular alterations were potentially actionable in 28 of 135 patients (21%). The genetic profiles of recurrent and metastatic tumors were often distinct from primary tumors. Compared to primary human papillomavirus (HPV)-positive tumors, many recurrent and metastatic HPV-positive tumors exhibited a molecular profile more similar to HPV-negative tumors, including enriched frequencies of TP53 mutation (3 of 20 tumors [15%]), whole genome duplication (5 of 20 tumors [25%]), and 3p deletion (11 of 20 tumors [55%]). There were high rates of TERT promoter mutation in recurrent and metastatic HPV-negative HNSCC (13 of 30 tumors [43%]), cutaneous SCC (11 of 21 tumors [52%]), basal cell carcinoma (3 of 4 tumors [75%]), and ACC (5 of 36 tumors [14%]). Activating NOTCH1 mutations were enriched in metastatic ACCs (8 of 36 tumors [22%]). CONCLUSIONS AND RELEVANCE: These findings reveal the molecular landscape of advanced disease and rare cancer subtypes, both predominant challenges in head and neck oncology. To understand the repertoire of targetable alterations in advanced cancers, it is necessary to sequence recurrent and metastatic tumors. These data are important first steps toward implementation of precision head and neck oncology.

Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients.

Tumor molecular profiling is a fundamental component of precision oncology, enabling the identification of genomic alterations in genes and pathways that can be targeted therapeutically. The existence of recurrent targetable alterations across distinct histologically defined tumor types, coupled with an expanding portfolio of molecularly targeted therapies, demands flexible and comprehensive approaches to profile clinically relevant genes across the full spectrum of cancers. We established a large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which we have compiled tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer and available pathological and clinical annotations. Using these data, we identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types. Patients were enrolled on genomically matched clinical trials at a rate of 11%. To enable discovery of novel biomarkers and deeper investigation into rare alterations and tumor types, all results are publicly accessible.

Clinical Application of Picodroplet Digital PCR Technology for Rapid Detection of EGFR T790M in Next-Generation Sequencing Libraries and DNA from Limited Tumor Samples.

Although next-generation sequencing (NGS) is a robust technology for comprehensive assessment of EGFR-mutant lung adenocarcinomas with acquired resistance to tyrosine kinase inhibitors, it may not provide sufficiently rapid and sensitive detection of the EGFR T790M mutation, the most clinically relevant resistance biomarker. Here, we describe a digital PCR (dPCR) assay for rapid T790M detection on aliquots of NGS libraries prepared for comprehensive profiling, fully maximizing broad genomic analysis on limited samples. Tumor DNAs from patients with EGFR-mutant lung adenocarcinomas and acquired resistance to epidermal growth factor receptor inhibitors were prepared for Memorial Sloan-Kettering-Integrated Mutation Profiling of Actionable Cancer Targets sequencing, a hybrid capture-based assay interrogating 410 cancer-related genes. Precapture library aliquots were used for rapid EGFR T790M testing by dPCR, and results were compared with NGS and locked nucleic acid-PCR Sanger sequencing (reference high sensitivity method). Seventy resistance samples showed 99% concordance with the reference high sensitivity method in accuracy studies. Input as low as 2.5 ng provided a sensitivity of 1% and improved further with increasing DNA input. dPCR on libraries required less DNA and showed better performance than direct genomic DNA. dPCR on NGS libraries is a robust and rapid approach to EGFR T790M testing, allowing most economical utilization of limited material for comprehensive assessment. The same assay can also be performed directly on any limited DNA source and cell-free DNA.

EGFR Kinase Domain Duplication (EGFR-KDD) Is a Novel Oncogenic Driver in Lung Cancer That Is Clinically Responsive to Afatinib.

UNLABELLED: Oncogenic EGFR mutations are found in 10% to 35% of lung adenocarcinomas. Such mutations, which present most commonly as small in-frame deletions in exon 19 or point mutations in exon 21 (L858R), confer sensitivity to EGFR tyrosine kinase inhibitors (TKI). In analyzing the tumor from a 33-year-old male never-smoker, we identified a novel EGFR alteration in lung cancer: EGFR exon 18-25 kinase domain duplication (EGFR-KDD). Through analysis of a larger cohort of tumor samples, we detected additional cases of EGFR-KDD in lung, brain, and other cancers. In vitro, EGFR-KDD is constitutively active, and computational modeling provides potential mechanistic support for its auto-activation. EGFR-KDD-transformed cells are sensitive to EGFR TKIs and, consistent with these in vitro findings, the index patient had a partial response to the EGFR TKI afatinib. The patient eventually progressed, at which time resequencing revealed an EGFR-dependent mechanism of acquired resistance to afatinib, thereby validating EGFR-KDD as a driver alteration and therapeutic target. SIGNIFICANCE: We identified oncogenic and drug-sensitive EGFR-KDD that is recurrent in lung, brain, and soft-tissue cancers and documented that a patient with metastatic lung adenocarcinoma harboring the EGFR-KDD derived significant antitumor response from treatment with the EGFR inhibitor afatinib. Findings from these studies will be immediately translatable, as there are already several approved EGFR inhibitors in clinical use.

Targeted massively parallel sequencing of angiosarcomas reveals frequent activation of the mitogen activated protein kinase pathway.

Angiosarcomas are rare malignant mesenchymal tumors of endothelial differentiation. The clinical behavior is usually aggressive and the prognosis for patients with advanced disease is poor with no effective therapies. The genetic bases of these tumors have been partially revealed in recent studies reporting genetic alterations such as amplifications of MYC (primarily in radiation-associated angiosarcomas), inactivating mutations in PTPRB and R707Q hotspot mutations of PLCG1. Here, we performed a comprehensive genomic analysis of 34 angiosarcomas using a clinically-approved, hybridization-based targeted next-generation sequencing assay for 341 well-established oncogenes and tumor suppressor genes. Over half of the angiosarcomas (n = 18, 53%) harbored genetic alterations affecting the MAPK pathway, involving mutations in KRAS, HRAS, NRAS, BRAF, MAPK1 and NF1, or amplifications in MAPK1/CRKL, CRAF or BRAF. The most frequently detected genetic aberrations were mutations in TP53 in 12 tumors(35%) and losses of CDKN2A in9 tumors (26%). MYC amplifications were generally mutually exclusive of TP53 alterations and CDKN2A loss and were identified in 8 tumors (24%), most of which (n = 7, 88%) arose post-irradiation. Previously reported mutations in PTPRB (n = 10, 29%) and one (3%) PLCG1 R707Q mutation were also identified. Our results demonstrate that angiosarcomas are a genetically heterogeneous group of tumors, harboring a wide range of genetic alterations. The high frequency of genetic events affecting the MAPK pathway suggests that targeted therapies inhibiting MAPK signaling may be promising therapeutic avenues in patients with advanced angiosarcomas.

Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): A Hybridization Capture-Based Next-Generation Sequencing Clinical Assay for Solid Tumor Molecular Oncology.

The identification of specific genetic alterations as key oncogenic drivers and the development of targeted therapies are together transforming clinical oncology and creating a pressing need for increased breadth and throughput of clinical genotyping. Next-generation sequencing assays allow the efficient and unbiased detection of clinically actionable mutations. To enable precision oncology in patients with solid tumors, we developed Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), a hybridization capture-based next-generation sequencing assay for targeted deep sequencing of all exons and selected introns of 341 key cancer genes in formalin-fixed, paraffin-embedded tumors. Barcoded libraries from patient-matched tumor and normal samples were captured, sequenced, and subjected to a custom analysis pipeline to identify somatic mutations. Sensitivity, specificity, reproducibility of MSK-IMPACT were assessed through extensive analytical validation. We tested 284 tumor samples with previously known point mutations and insertions/deletions in 47 exons of 19 cancer genes. All known variants were accurately detected, and there was high reproducibility of inter- and intrarun replicates. The detection limit for low-frequency variants was approximately 2% for hotspot mutations and 5% for nonhotspot mutations. Copy number alterations and structural rearrangements were also reliably detected. MSK-IMPACT profiles oncogenic DNA alterations in clinical solid tumor samples with high accuracy and sensitivity. Paired analysis of tumors and patient-matched normal samples enables unambiguous detection of somatic mutations to guide treatment decisions.

Benchmarking RNA-Seq quantification tools.

RNA-Seq, a deep sequencing technique, promises to be a potential successor to microarrays for studying the transcriptome. One of many aspects of transcriptomics that are of interest to researchers is gene expression estimation. With rapid development in RNA-Seq, there are numerous tools available to estimate gene expression, each producing different results. However, we do not know which of these tools produces the most accurate gene expression estimates. In this study we have addressed this issue using Cufflinks, IsoEM, HTSeq, and RSEM to quantify RNA-Seq expression profiles. Comparing results of these quantification tools, we observe that RNA-Seq relative expression estimates correlate with RT-qPCR measurements in the range of 0.85 to 0.89, with HTSeq exhibiting the highest correlation. But, in terms of root-mean-square deviation of RNA-Seq relative expression estimates from RT-qPCR measurements, we find HTSeq to produce the greatest deviation. Therefore, we conclude that, though Cufflinks, RSEM, and IsoEM might not correlate as well as HTSeq with RT-qPCR measurements, they may produce expression values with higher accuracy.

Systematic Assessment of RNA-Seq Quantification Tools Using Simulated Sequence Data.

RNA-sequencing (RNA-seq) technology has emerged as the preferred method for quantification of gene and isoform expression. Numerous RNA-seq quantification tools have been proposed and developed, bringing us closer to developing expression-based diagnostic tests based on this technology. However, because of the rapidly evolving technologies and algorithms, it is essential to establish a systematic method for evaluating the quality of RNA-seq quantification. We investigate how different RNA-seq experimental designs (i.e., variations in sequencing depth and read length) affect various quantification algorithms (i.e., HTSeq, Cufflinks, and MISO). Using simulated data, we evaluate the quantification tools based on four metrics, namely: (1) total number of usable fragments for quantification, (2) detection of genes and isoforms, (3) correlation, and (4) accuracy of expression quantification with respect to the ground truth. Results show that Cufflinks is able to use the largest number of fragments for quantification, leading to better detection of genes and isoforms. However, HTSeq produces more accurate expression estimates. Moreover, each quantification algorithm is affected differently by varying sequencing depth and read length, suggesting that the selection of quantification algorithms should be application-dependent.