Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing

Abstract Analysis of circulating cell-free DNA (cfDNA) has opened new opportunities for characterizing tumour mutational landscapes with many applications in genomic-driven oncology. We developed a customized targeted cfDNA sequencing approach for breast cancer (BC) using unique molecular identifiers (UMIs) for error correction. Our assay, spanning a 284.5 kb target region, is combined with a novel freely-licensed bioinformatics pipeline that provides detection of low-frequency variants, and reliable identification of copy number variations (CNVs) directly from plasma DNA. We first evaluated our pipeline on reference samples. Then in a cohort of 35 BC patients our approach detected actionable driver and clonal variants at low variant frequency levels in cfDNA that were concordant (77%) with sequencing of primary and/or metastatic solid tumour sites. We also detected ERRB2 gene CNVs used for HER2 subtype classification with 80% precision compared to immunohistochemistry. Further, we evaluated fragmentation profiles of cfDNA in BC and observed distinct differences compared to data from healthy individuals. Our results show that the developed assay addresses the majority of tumour associated aberrations directly from plasma DNA, and thus may be used to elucidate genomic alterations in liquid biopsy studies.

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Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing

10.1101/733691 ◽

2019 ◽

Author(s):

Dimitrios Kleftogiannis ◽

Danliang Ho ◽

Jun Xian Liew ◽

Polly Poon ◽

Anna Gan ◽

...

Keyword(s):

Breast Cancer ◽

Solid Tumour ◽

Copy Number Variations ◽

Healthy Individuals ◽

Plasma Dna ◽

Single Nucleotide Variants ◽

Genomic Alterations ◽

Single Nucleotide ◽

Target Region ◽

Circulating Tumour Dna

AbstractAnalysis of circulating cell-free DNA (cfDNA) data has opened new opportunities for characterizing tumour mutational landscapes with many applications in genomic-driven oncology. We developed a customized targeted cfDNA sequencing approach for breast cancer (BC) using unique molecular identifiers (UMIs) for error correction. Our assay, spanning a 284.5 kb target region, is combined with freely-available bioinformatics pipelines that provide ultra-sensitive detection of single nucleotide variants (SNVs), and reliable identification of copy number variations (CNVs) directly from plasma DNA. In a cohort of 35 BC patients, our approach detected actionable driver and clonal SNVs at low (~0.5%) frequency levels in cfDNA that were concordant (83.3%) with sequencing of primary and/or metastatic solid tumour sites. We also detected ERRB2 gene CNVs used for HER2 subtype classification with 80% precision compared to immunohistochemistry. Further, we evaluated fragmentation profiles of cfDNA in BC and observed distinct differences compared to data from healthy individuals. Our results show that the developed assay addresses the majority of tumour associated aberrations directly from plasma DNA, and thus may be used to elucidate genomic alterations in liquid biopsy studies.

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Identifying Genomic Alterations in Stage IV Breast Cancer Patients using MammaSeq™: An International Collaborative Study

10.1101/2020.03.01.965632 ◽

2020 ◽

Author(s):

Osama Shiraz Shah ◽

Atilla Soran ◽

Mustafa Sahin ◽

Serdar Ugras ◽

Esin Celik ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Patients ◽

Clinical Significance ◽

Copy Number ◽

Stage Iv ◽

Copy Number Variations ◽

Breast Cancer Patients ◽

Genomic Alterations ◽

Single Nucleotide ◽

Stage Iv Breast Cancer

ABSTRACTBackgroundIdentification of genomic alterations present in cancer patients may aid in cancer diagnosis and prognosis and may identify therapeutic targets. In this study, we aimed to identify clinically actionable variants present in stage IV breast cancer (BC) samples.Materials and MethodsDNA was extracted from formalin fixed paraffin embedded (FFPE) samples of BC (n=41). DNA was sequenced using MammaSeq™, a BC specific next generation sequencing panel targeting 79 genes and 1369 mutations. Ion Torrent Suite 4.0 was used to make variant calls on the raw data and the resulting single nucleotide variants were annotated using CRAVAT toolkit. SNVs were filtered to remove common polymorphisms and somatic variants. CNVkit was employed to identify copy number variations. The Precision Medicine Knowledgebase (PMKB) and OncoKB Precision Oncology Database were used to associate clinical significance with the identified variants.ResultsA total of 41 Turkish BC patient samples were sequenced (read depth of 94 – 13340, median of 1529). These samples were from patients diagnosed with various BC subtypes including invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), apocrine BC and micropapillary BC. In total, 59 different alterations (49 SNVs and 10 CNVs) were identified. From these, 8 alterations (3 CNVs – ERBB2, FGFR1 and AR copy number gains and 5 SNVs – IDH1.R132H, TP53.E204*, PI3KCA.E545K, PI3KCA.H1047R and PI3KCA.R88Q) were identified to have some clinical significance by PMKB and OncoKB. Moreover, the top five genes with most SNVs included PIK3CA, TP53, MAP3K1, ATM and NCOR1. Additionally, copy number gains and losses were found in ERBB2, GRB7, IGFR1, AR, FGFR1, MYC and IKBKB, and BRCA2, RUNX1 and RB1 respectively.ConclusionWe identified 59 unique alterations in 38 genes in 41 stage IV BC tissue samples using MammaSeq™. Ten of these alterations were found to have some clinical significance by OncoKB and PKMB. This study highlights the potential use of cancer specific NGS panels in clinic to get better insight into the patient-specific genomic alterations.Highlights- 41 stage IV stage breast cancer patients of Turkish descent were sequenced using MammaSeq™- 49 single nucleotide variations and 10 copy number variations identified- PIK3CA and TP53 mutations were present in 24% and 17% of the samples respectively- 37% of the samples had ERBB2/GRB7 gains and 7% had loss of BRCA2/RB1 locus- Eight clinically significant alterations were identifiedMicro AbstractWe performed targeted sequencing using DNA from FFPE samples of 41 stage IV breast cancer patients using MammaSeq™, a breast cancer gene specific targeted sequencing panel. In total, 49 single nucleotide variations (SNVs) and 10 copy number variations (CNVs) were identified. Eight alterations (3 CNVs – ERBB2, FGFR1 and AR copy number gains and 5 SNVs – IDH1.R132H, TP53.E204*, PI3KCA.E545K, PI3KCA.H1047R and PI3KCA.R88Q) were identified to have clinical significance by PMKB and OncoKB databases.

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Genomic Drivers in Breast Cancers

European Oncology & Haematology ◽

10.17925/eoh.2016.12.01.28 ◽

2016 ◽

Vol 12 (01) ◽

pp. 28

Author(s):

Luis Teixeira ◽

Françoise Rothé ◽

Christos Sotiriou ◽

◽

...

Keyword(s):

Breast Cancer ◽

Next Generation Sequencing ◽

Precision Medicine ◽

Liquid Biopsy ◽

Targeted Drugs ◽

Breast Cancers ◽

Genomic Alterations ◽

Sequencing Technologies ◽

Circulating Tumour Dna ◽

Generation Sequencing

Significant advances in next-generation sequencing technologies have allowed the identification of genomic alterations in breast cancer. These alterations offer the opportunity to conduct studies with targeted drugs. However, there are still several scientific challenges to be addressed before precision medicine is widely used in the clinic. Nonetheless, different solutions are developed to overcome these obstacles such as the improvement of bioinformatics tools and the use of “liquid biopsy” to assess circulating tumour DNA.

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Faculty Opinions recommendation of Cerebrospinal fluid-derived circulating tumour DNA better represents the genomic alterations of brain tumours than plasma.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725929208.793516240 ◽

2016 ◽

Author(s):

Nicholas Leslie

Keyword(s):

Cerebrospinal Fluid ◽

Brain Tumours ◽

Genomic Alterations ◽

Circulating Tumour Dna

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Increased yields of duplex sequencing data by a series of quality control tools

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqab002 ◽

2021 ◽

Vol 3 (1) ◽

Author(s):

Gundula Povysil ◽

Monika Heinzl ◽

Renato Salazar ◽

Nicholas Stoler ◽

Anton Nekrutenko ◽

...

Keyword(s):

Low Frequency ◽

Variant Calling ◽

Data Loss ◽

Sequencing Data ◽

Bioinformatics Pipeline ◽

Consensus Sequences ◽

Sequencing Errors ◽

Data Output ◽

Reverse Strand ◽

Duplex Sequencing

Abstract Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences (DCS), and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics toolset that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain polymerase chain reaction and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which likely reflect barcode collisions. Finally, we also developed a tool that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. With this tool, we can include reads without a family and check the reliability of the call, that increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

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Association between the nucleosome footprint of plasma DNA and neoadjuvant chemotherapy response for breast cancer

npj Breast Cancer ◽

10.1038/s41523-021-00237-5 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Xu Yang ◽

Geng-Xi Cai ◽

Bo-Wei Han ◽

Zhi-Wei Guo ◽

Ying-Song Wu ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Neoadjuvant Chemotherapy ◽

Cancer Patients ◽

Cell Receptor ◽

Chemotherapy Response ◽

Breast Cancer Patients ◽

Plasma Dna ◽

Transcription Start Sites ◽

Response To Chemotherapy

AbstractGene expression signatures have been used to predict the outcome of chemotherapy for breast cancer. The nucleosome footprint of cell-free DNA (cfDNA) carries gene expression information of the original tissues and thus may be used to predict the response to chemotherapy. Here we carried out the nucleosome positioning on cfDNA from 85 breast cancer patients and 85 healthy individuals and two cancer cell lines T-47D and MDA-MB-231 using low-coverage whole-genome sequencing (LCWGS) method. The patients showed distinct nucleosome footprints at Transcription Start Sites (TSSs) compared with normal donors. In order to identify the footprints of cfDNA corresponding with the responses to neoadjuvant chemotherapy in patients, we mapped on nucleosome positions on cfDNA of patients with different responses: responders (pretreatment, n = 28; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 12) and nonresponders (pretreatment, n = 10; post-1 cycle, post-3/4 cycles, and post-8 cycles of treatment, n = 10). The coverage depth near TSSs in plasma cfDNA differed significantly between responders and nonresponders at pretreatment, and also after neoadjuvant chemotherapy treatment cycles. We identified 232 TSSs with differential footprints at pretreatment and 321 after treatment and found enrichment in Gene Ontology terms such as cell growth inhibition, tumor suppressor, necrotic cell death, acute inflammatory response, T cell receptor signaling pathway, and positive regulation of vascular endothelial growth factor production. These results suggest that cfDNA nucleosome footprints may be used to predict the efficacy of neoadjuvant chemotherapy for breast cancer patients and thus may provide help in decision making for individual patients.

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Mapping of Genomic Vulnerabilities in the Post-Translational Ubiquitination, SUMOylation and Neddylation Machinery in Breast Cancer

Cancers ◽

10.3390/cancers13040833 ◽

2021 ◽

Vol 13 (4) ◽

pp. 833

Author(s):

Jesús Fuentes-Antrás ◽

Ana Lucía Alcaraz-Sanabria ◽

Esther Cabañas Morafraile ◽

María del Mar Noblejas-López ◽

Eva María Galán-Moya ◽

...

Keyword(s):

Breast Cancer ◽

Drug Development ◽

Gene Mutations ◽

Complete Response ◽

Breast Cancer Patients ◽

Clinical Value ◽

Luminal A ◽

Genomic Alterations ◽

Cancer Hallmarks ◽

Worse Prognosis

The dysregulation of post-translational modifications (PTM) transversally impacts cancer hallmarks and constitutes an appealing vulnerability for drug development. In breast cancer there is growing preclinical evidence of the role of ubiquitin and ubiquitin-like SUMO and Nedd8 peptide conjugation to the proteome in tumorigenesis and drug resistance, particularly through their interplay with estrogen receptor signaling and DNA repair. Herein we explored genomic alterations in these processes using RNA-seq and mutation data from TCGA and METABRIC datasets, and analyzed them using a bioinformatic pipeline in search of those with prognostic and predictive capability which could qualify as subjects of drug research. Amplification of UBE2T, UBE2C, and BIRC5 conferred a worse prognosis in luminal A/B and basal-like tumors, luminal A/B tumors, and luminal A tumors, respectively. Higher UBE2T expression levels were predictive of a lower rate of pathological complete response in triple negative breast cancer patients following neoadjuvant chemotherapy, whereas UBE2C and BIRC5 expression was higher in luminal A patients with tumor relapse within 5 years of endocrine therapy or chemotherapy. The transcriptomic signatures of USP9X and USP7 gene mutations also conferred worse prognosis in luminal A, HER2-enriched, and basal-like tumors, and in luminal A tumors, respectively. In conclusion, we identified and characterized the clinical value of a group of genomic alterations in ubiquitination, SUMOylation, and neddylation enzymes, with potential for drug development in breast cancer.

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207P Concordance of genomic alterations by next-generation sequencing in tumour tissue versus circulating tumour DNA in urothelial carcinoma

Annals of Oncology ◽

10.1016/j.annonc.2020.10.219 ◽

2020 ◽

Vol 31 ◽

pp. S1322

Author(s):

W. Wang ◽

H.H. Liu ◽

T. Zhou ◽

H. Wang ◽

F. Lou ◽

...

Keyword(s):

Next Generation Sequencing ◽

Urothelial Carcinoma ◽

Tumour Tissue ◽

Next Generation ◽

Genomic Alterations ◽

Circulating Tumour Dna ◽

Generation Sequencing

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CSMD: a computational subtraction-based microbiome discovery pipeline for species-level characterization of clinical metagenomic samples

Bioinformatics ◽

10.1093/bioinformatics/btz790 ◽

2019 ◽

Author(s):

Yu Liu ◽

Paul W Bible ◽

Bin Zou ◽

Qiaoxing Liang ◽

Cong Dong ◽

...

Keyword(s):

Species Level ◽

Supplementary Information ◽

Clinical Samples ◽

Plasma Dna ◽

Bioinformatics Pipeline ◽

Microbial Identification ◽

Reference Databases ◽

Microbial Dna ◽

Higher Sensitivity

Abstract Motivation Microbiome analyses of clinical samples with low microbial biomass are challenging because of the very small quantities of microbial DNA relative to the human host, ubiquitous contaminating DNA in sequencing experiments and the large and rapidly growing microbial reference databases. Results We present computational subtraction-based microbiome discovery (CSMD), a bioinformatics pipeline specifically developed to generate accurate species-level microbiome profiles for clinical samples with low microbial loads. CSMD applies strategies for the maximal elimination of host sequences with minimal loss of microbial signal and effectively detects microorganisms present in the sample with minimal false positives using a stepwise convergent solution. CSMD was benchmarked in a comparative evaluation with other classic tools on previously published well-characterized datasets. It showed higher sensitivity and specificity in host sequence removal and higher specificity in microbial identification, which led to more accurate abundance estimation. All these features are integrated into a free and easy-to-use tool. Additionally, CSMD applied to cell-free plasma DNA showed that microbial diversity within these samples is substantially broader than previously believed. Availability and implementation CSMD is freely available at https://github.com/liuyu8721/csmd. Supplementary information Supplementary data are available at Bioinformatics online.

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