scholarly journals Assessment of genomic alterations in non-syndromic von Hippel-Lindau: Insight from integrating somatic and germline next generation sequencing genomic data

Data in Brief ◽  
2021 ◽  
pp. 107653
Author(s):  
Danielle K. Manning ◽  
Priyanka Shivdasani ◽  
Diane R. Koeller ◽  
Alison Schwartz ◽  
Huma Q. Rana ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genomic Data ◽  
Next Generation ◽  
Genomic Alterations ◽  
Von Hippel Lindau ◽  
Generation Sequencing

scholarly journals Next-Generation Sequencing Approach to Non–Small Cell Lung Carcinoma Yields More Actionable Alterations

2017 ◽  
Vol 142 (3) ◽  
pp. 353-357 ◽  
Author(s):  
Mitra Mehrad ◽  
Somak Roy ◽  
Humberto Trejo Bittar ◽  
Sanja Dacic
Keyword(s):  
Next Generation Sequencing ◽  
Lung Adenocarcinoma ◽  
Small Cell ◽  
Gene Panel ◽  
Next Generation ◽  
Small Cell Lung ◽  
Genomic Alterations ◽  
Generation Sequencing ◽  
Gene Alterations ◽  
Cancer Panel

Context.— Different testing algorithms and platforms for EGFR mutations and ALK rearrangements in advanced-stage lung adenocarcinoma exist. The multistep approach with single-gene assays has been challenged by more efficient next-generation sequencing (NGS) of a large number of gene alterations. The main criticism of the NGS approach is the detection of genomic alterations of uncertain significance. Objective.— To determine the best testing algorithm for patients with lung cancer in our clinical practice. Design.— Two testing approaches for metastatic lung adenocarcinoma were offered between 2012–2015. One approach was reflex testing for an 8-gene panel composed of DNA Sanger sequencing for EGFR, KRAS, PIK3CA, and BRAF and fluorescence in situ hybridization for ALK, ROS1, MET, and RET. At the oncologist's request, a subset of tumors tested by the 8-gene panel was subjected to a 50-gene Ion AmpliSeq Cancer Panel. Results.— Of 1200 non–small cell lung carcinomas (NSCLCs), 57 including 46 adenocarcinomas and NSCLCs, not otherwise specified; 7 squamous cell carcinomas (SCCs); and 4 large cell neuroendocrine carcinomas (LCNECs) were subjected to Ion AmpliSeq Cancer Panel. Ion AmpliSeq Cancer Panel detected 9 potentially actionable variants in 29 adenocarcinomas that were wild type by the 8-gene panel testing (9 of 29, 31.0%) in the following genes: ERBB2 (3 of 29, 10.3%), STK11 (2 of 29, 6.8%), PTEN (2 of 29, 6.8%), FBXW7 (1 of 29, 3.4%), and BRAF G469A (1 of 29, 3.4%). Four SCCs and 2 LCNECs showed investigational genomic alterations. Conclusions.— The NGS approach would result in the identification of a significant number of actionable gene alterations, increasing the therapeutic options for patients with advanced NSCLCs.

scholarly journals Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data

2019 ◽  
Author(s):  
Kate Chkhaidze ◽  
Timon Heide ◽  
Benjamin Werner ◽  
Marc J. Williams ◽  
Weini Huang ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Tumour Growth ◽  
Evolutionary Dynamics ◽  
Clonal Selection ◽  
Genomic Data ◽  
Confounding Factors ◽  
Data Generation ◽  
Next Generation ◽  
Sequencing Data ◽  
Generation Sequencing

AbstractQuantification of the effect of spatial tumour sampling on the patterns of mutations detected in next-generation sequencing data is largely lacking. Here we use a spatial stochastic cellular automaton model of tumour growth that accounts for somatic mutations, selection, drift and spatial constrains, to simulate multi-region sequencing data derived from spatial sampling of a neoplasm. We show that the spatial structure of a solid cancer has a major impact on the detection of clonal selection and genetic drift from bulk sequencing data and single-cell sequencing data. Our results indicate that spatial constrains can introduce significant sampling biases when performing multi-region bulk sampling and that such bias becomes a major confounding factor for the measurement of the evolutionary dynamics of human tumours. We present a statistical inference framework that takes into account the spatial effects of a growing tumour and allows inferring the evolutionary dynamics from patient genomic data. Our analysis shows that measuring cancer evolution using next-generation sequencing while accounting for the numerous confounding factors requires a mechanistic model-based approach that captures the sources of noise in the data.SummarySequencing the DNA of cancer cells from human tumours has become one of the main tools to study cancer biology. However, sequencing data are complex and often difficult to interpret. In particular, the way in which the tissue is sampled and the data are collected, impact the interpretation of the results significantly. We argue that understanding cancer genomic data requires mathematical models and computer simulations that tell us what we expect the data to look like, with the aim of understanding the impact of confounding factors and biases in the data generation step. In this study, we develop a spatial simulation of tumour growth that also simulates the data generation process, and demonstrate that biases in the sampling step and current technological limitations severely impact the interpretation of the results. We then provide a statistical framework that can be used to overcome these biases and more robustly measure aspects of the biology of tumours from the data.

Correlation of genomic alterations between tumor tissue and circulating tumor DNA by next-generation sequencing

2018 ◽  
Vol 144 (11) ◽  
pp. 2167-2175 ◽  
Author(s):  
Ya-Sian Chang ◽  
Hsin-Yuan Fang ◽  
Yao-Ching Hung ◽  
Tao-Wei Ke ◽  
Chieh-Min Chang ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Tumor Tissue ◽  
Circulating Tumor Dna ◽  
Next Generation ◽  
Genomic Alterations ◽  
Tumor Dna ◽  
Generation Sequencing

Comutation of PIK3CA and TP53 in Residual Disease After Preoperative Anti-HER2 Therapy in ERBB2 (HER2)-Amplified Early Breast Cancer

2019 ◽  
pp. 1-26
Author(s):  
Frankie Ann Holmes ◽  
Maren K. Levin ◽  
Ying Cao ◽  
Sohail Balasubramanian ◽  
Jeffrey S. Ross ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Next Generation Sequencing ◽  
Residual Disease ◽  
Preoperative Treatment ◽  
Next Generation ◽  
Her2 Positive ◽  
Genomic Alterations ◽  
Pik3ca Mutations ◽  
Her2 Breast Cancer ◽  
Generation Sequencing

PURPOSE To identify proteomic and genomic alterations in residual disease (RD) for human epidermal growth factor receptor 2 (HER2)-positive (HER2+) breast cancer (BC) after preoperative trastuzumab (H), lapatinib (L), or both (H+L) in combination with chemotherapy. PATIENTS AND METHODS Patients with stage II/III HER2+ BC (n = 100) were randomly assigned to preoperative treatment with H versus L 1,250mg versus H+L (L: 750 to 1,000 mg) plus 5-fluorouracil, epirubicin, and cyclophosphamide, followed by weekly paclitaxel. After receiving institutional review board–approved informed consent, targeted next-generation sequencing was performed on 20 patients’ formalin-fixed paraffin embedded tumors to characterize genomic alterations across 287 cancer-related genes. Reverse phase protein array (RPPA) analysis was performed on both the baseline biopsy and RD specimens, when available. RESULTS Two of 20 RD tissues were HER2 negative per next-generation sequencing; one sample had insufficient tissue. Of six pretreatment biopsy specimens, four were comutated with TP53 and PIK3CA. Of 17 HER2+ RD, seven specimens (41%) had PIK3CA mutations always comutated with TP53, and four (24%) also had concurrent CDK12 amplification. Overall, CDK12 amplification was observed in eight of the 17 (47%) HER2+ RD specimens. A total of 12 RD specimens (71%) had TP53 mutations. Although prevalence of individual TP53 and PIK3CA mutations was only modestly higher than published estimates for those in HER2+ primary BCs (55% and 32% for TP53 and PIK3CA, respectively), prevalence of these as comutations appeared higher (41%), compared with less than 10% in several series. On RPPA analysis of the RD tissue with comutations, the strongest Spearman ρ correlations were limited to EGFR and phospho-AKT (ρ, 0.999; P = .019) and phospho-mTOR and phospho-S6 ribosomal protein (ρ, 0.994; P = .048). CONCLUSION HER2-amplified RD tissue after preoperative H, L, or H+L plus chemotherapy was enriched for PIK3CA and TP53 comutations, and the RD tissue demonstrated activation of EGFR/AKT/mTOR signaling on RPPA.

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