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Using an ORF kinome screen in MCF-7 cells treated with the CDK4/6 inhibitor ribociclib plus fulvestrant, we identified FGFR1 as a mechanism of drug resistance. FGFR1-amplified/ER+ breast cancer cells and MCF-7 cells transduced with FGFR1 were resistant to fulvestrant ± ribociclib or palbociclib. This resistance was abrogated by treatment with the FGFR tyrosine kinase inhibitor (TKI) lucitanib. Addition of the FGFR TKI erdafitinib to palbociclib/fulvestrant induced complete responses of FGFR1-amplified/ER+ patient-derived-xenografts. Next generation sequencing of circulating tumor DNA (ctDNA) in 34 patients after progression on CDK4/6 inhibitors identified FGFR1/2 amplification or activating mutations in 14/34 (41%) post-progression specimens. Finally, ctDNA from patients enrolled in MONALEESA-2, the registration trial of ribociclib, showed that patients with FGFR1 amplification exhibited a shorter progression-free survival compared to patients with wild type FGFR1. Thus, we propose breast cancers with FGFR pathway alterations should be considered for trials using combinations of ER, CDK4/6 and FGFR antagonists.
Insertional mutagenesis is an important risk with all genetically modified cell therapies, including chimeric antigen receptor (CAR)-T cell therapy used for hematological malignancies. Here we describe a new tagmentation-assisted PCR (tag-PCR) system that can determine the integration sites of transgenes without using restriction enzyme digestion (which can potentially bias the detection) and allows library preparation in fewer steps than with other methods. Using this system, we compared the integration sites of CD19-specific CAR genes in final T cell products generated by retrovirus-based and lentivirus-based gene transfer and by the piggyBac transposon system. The piggyBac system demonstrated lower preference than the retroviral system for integration near transcriptional start sites and CpG islands and higher preference than the lentiviral system for integration into genomic safe harbors. Integration into or near proto-oncogenes was similar in all three systems. Tag-PCR mapping is a useful technique for assessing the risk of insertional mutagenesis.
Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Functional disruptions of susceptibility genes by large genomic structure variant (SV) deletions in germlines are known to be associated with cancer risk. However, few studies have been conducted to systematically search for SV deletions in breast cancer susceptibility genes. We analysed deep (> 30x) whole-genome sequencing (WGS) data generated in blood samples from 128 breast cancer patients of Asian and European descent with either a strong family history of breast cancer or early cancer onset disease. To identify SV deletions in known or suspected breast cancer susceptibility genes, we used multiple SV calling tools including Genome STRiP, Delly, Manta, BreakDancer and Pindel. SV deletions were detected by at least three of these bioinformatics tools in five genes. Specifically, we identified heterozygous deletions covering a fraction of the coding regions of BRCA1 (with approximately 80kb in two patients), and TP53 genes (with ∼1.6 kb in two patients), and of intronic regions (∼1 kb) of the PALB2 (one patient), PTEN (three patients) and RAD51C genes (one patient). We confirmed the presence of these deletions using real-time quantitative PCR (qPCR). Our study identified novel SV deletions in breast cancer susceptibility genes and the identification of such SV deletions may improve clinical testing.
Multiplex genomic profiling is standard of care for patients with advanced lung adenocarcinomas. The Lung Cancer Mutation Consortium (LCMC) is a multi-institutional effort to identify and treat oncogenic driver events in patients with lung adenocarcinomas. Sixteen U.S. institutions enrolled 1,367 patients with lung cancer in LCMC2; 904 were deemed eligible and had at least one of 14 cancer-related genes profiled using validated methods including genotyping, massively parallel sequencing, and IHC. The use of targeted therapies in patients with or p.V600E mutations, , or rearrangements, or amplification was associated with a survival increment of 1.5 years compared with those with such mutations not receiving targeted therapy, and 1.0 year compared with those lacking a targetable driver. Importantly, 60 patients with a history of smoking derived similar survival benefit from targeted therapy for alterations in //, when compared with 75 never smokers with the same alterations. In addition, coexisting mutations were associated with shorter survival among patients with , or alterations. Patients with adenocarcinoma of the lung and an oncogenic driver mutation treated with effective targeted therapy have a longer survival, regardless of prior smoking history. Molecular testing should be performed on all individuals with lung adenocarcinomas irrespective of clinical characteristics. Routine use of massively parallel sequencing enables detection of both targetable driver alterations and tumor suppressor gene and other alterations that have potential significance for therapy selection and as predictive markers for the efficacy of treatment. .
©2017 American Association for Cancer Research.
BACKGROUND - High throughput sequencing technology enables the both the human genome and transcriptome to be screened at the single nucleotide resolution. Tools have been developed to infer single nucleotide variants (SNVs) from both DNA and RNA sequencing data. To evaluate how much difference can be expected between DNA and RNA sequencing data, and among tissue sources, we designed a study to examine the single nucleotide difference among five sources of high throughput sequencing data generated from the same individual, including exome sequencing from blood, tumor and adjacent normal tissue, and RNAseq from tumor and adjacent normal tissue.
RESULTS - Through careful quality control and analysis of the SNVs, we found little difference between DNA-DNA pairs (1%-2%). However, between DNA-RNA pairs, SNV differences ranged anywhere from 10% to 20%.
CONCLUSIONS - Only a small portion of these differences can be explained by RNA editing. Instead, the majority of the DNA-RNA differences should be attributed to technical errors from sequencing and post-processing of RNAseq data. Our analysis results suggest that SNV detection using RNAseq is subject to high false positive rates.
We hypothesize that the relative mitochondria copy number (MTCN) can be estimated by comparing the abundance of mitochondrial DNA to nuclear DNA reads using high throughput sequencing data. To test this hypothesis, we examined relative MTCN across 13 breast cancer cell lines using the RT-PCR based NovaQUANT Human Mitochondrial to Nuclear DNA Ratio Kit as the gold standard. Six distinct computational approaches were used to estimate the relative MTCN in order to compare to the RT-PCR measurements. The results demonstrate that relative MTCN correlates well with the RT-PCR measurements using exome sequencing data, but not RNA-seq data. Through analysis of copy number variants (CNVs) in The Cancer Genome Atlas, we show that the two nuclear genes used in the NovaQUANT assay to represent the nuclear genome often experience CNVs in tumor cells, questioning the accuracy of this gold-standard method when it is applied to tumor cells.
Copyright © 2017 Elsevier Inc. All rights reserved.
Power/sample size (power) analysis estimates the likelihood of successfully finding the statistical significance in a data set. There has been a growing recognition of the importance of power analysis in the proper design of experiments. Power analysis is complex, yet necessary for the success of large studies. It is important to design a study that produces statistically accurate and reliable results. Power computation methods have been well established for both microarray-based gene expression studies and genotyping microarray-based genome-wide association studies. High-throughput sequencing (HTS) has greatly enhanced our ability to conduct biomedical studies at the highest possible resolution (per nucleotide). However, the complexity of power computations is much greater for sequencing data than for the simpler genotyping array data. Research on methods of power computations for HTS-based studies has been recently conducted but is not yet well known or widely used. In this article, we describe the power computation methods that are currently available for a range of HTS-based studies, including DNA sequencing, RNA-sequencing, microbiome sequencing and chromatin immunoprecipitation sequencing. Most importantly, we review the methods of power analysis for several types of sequencing data and guide the reader to the relevant methods for each data type.
Purpose - To identify the causes of autosomal dominant retinitis pigmentosa (adRP) in a cohort of families without mutations in known adRP genes and consequently to characterize a novel dominant-acting missense mutation in SAG.
Methods - Patients underwent ophthalmologic testing and were screened for mutations using targeted-capture and whole-exome next-generation sequencing. Confirmation and additional screening were done by Sanger sequencing. Haplotypes segregating with the mutation were determined using short tandem repeat and single nucleotide variant polymorphisms. Genealogies were established by interviews of family members.
Results - Eight families in a cohort of 300 adRP families, and four additional families, were found to have a novel heterozygous mutation in the SAG gene, c.440G>T; p.Cys147Phe. Patients exhibited symptoms of retinitis pigmentosa and none showed symptoms characteristic of Oguchi disease. All families are of Hispanic descent and most were ascertained in Texas or California. A single haplotype including the SAG mutation was identified in all families. The mutation dramatically alters a conserved amino acid, is extremely rare in global databases, and was not found in 4000+ exomes from Hispanic controls. Molecular modeling based on the crystal structure of bovine arrestin-1 predicts protein misfolding/instability.
Conclusions - This is the first dominant-acting mutation identified in SAG, a founder mutation possibly originating in Mexico several centuries ago. The phenotype is clearly adRP and is distinct from the previously reported phenotypes of recessive null mutations, that is, Oguchi disease and recessive RP. The mutation accounts for 3% of the 300 families in the adRP Cohort and 36% of Hispanic families in this cohort.
Cyclooxygenase-2 catalyses the biosynthesis of prostaglandins from arachidonic acid but also the biosynthesis of prostaglandin glycerol esters (PG-Gs) from 2-arachidonoylglycerol. Previous studies identified PG-Gs as signalling molecules involved in inflammation. Thus, the glyceryl ester of prostaglandin E, PGE-G, mobilizes Ca and activates protein kinase C and ERK, suggesting the involvement of a G protein-coupled receptor (GPCR). To identify the endogenous receptor for PGE-G, we performed a subtractive screening approach where mRNA from PGE-G response-positive and -negative cell lines was subjected to transcriptome-wide RNA sequencing analysis. We found several GPCRs that are only expressed in the PGE-G responder cell lines. Using a set of functional readouts in heterologous and endogenous expression systems, we identified the UDP receptor P2Y as the specific target of PGE-G. We show that PGE-G and UDP are both agonists at P2Y, but they activate the receptor with extremely different EC values of ~1 pM and ~50 nM, respectively. The identification of the PGE-G/P2Y pair uncovers the signalling mode of PG-Gs as previously under-appreciated products of cyclooxygenase-2.