Activating ESR1 mutations in hormone-resistant metastatic breast cancer
TL;DR: Five new LBD-localized ESR1 mutations identified here were shown to result in constitutive activity and continued responsiveness to anti-estrogen therapies in vitro, suggesting that activating mutations in E SR1 are a key mechanism in acquired endocrine resistance in breast cancer therapy.
Abstract: Arul Chinnaiyan and colleagues report the results of prospective clinical sequencing of 11 estrogen receptor–positive metastatic breast cancers. They identify ESR1 mutations affecting the ligand-binding domain in six hormone-resistant metastatic breast cancers and show that the mutant estrogen receptors are constitutively active and continue to be responsive to anti-estrogen therapies in vitro. Breast cancer is the most prevalent cancer in women, and over two-thirds of cases express estrogen receptor-α (ER-α, encoded by ESR1). Through a prospective clinical sequencing program for advanced cancers, we enrolled 11 patients with ER-positive metastatic breast cancer. Whole-exome and transcriptome analysis showed that six cases harbored mutations of ESR1 affecting its ligand-binding domain (LBD), all of whom had been treated with anti-estrogens and estrogen deprivation therapies. A survey of The Cancer Genome Atlas (TCGA) identified four endometrial cancers with similar mutations of ESR1. The five new LBD-localized ESR1 mutations identified here (encoding p.Leu536Gln, p.Tyr537Ser, p.Tyr537Cys, p.Tyr537Asn and p.Asp538Gly) were shown to result in constitutive activity and continued responsiveness to anti-estrogen therapies in vitro. Taken together, these studies suggest that activating mutations in ESR1 are a key mechanism in acquired endocrine resistance in breast cancer therapy.
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TL;DR: A large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer are compiled and identified clinically relevant somatic mutations, novel noncoding alterations, and mutational signatures that were shared by common and rare tumor types.
Abstract: 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.
2,330 citations
TL;DR: The current state of the art in this field is summarized, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and a European consortium of PDX models is introduced.
Abstract: Recently, there has been an increasing interest in the development and characterization of patient-derived tumor xenograft (PDX) models for cancer research. PDX models mostly retain the principal histologic and genetic characteristics of their donor tumor and remain stable across passages. These models have been shown to be predictive of clinical outcomes and are being used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. This article summarizes the current state of the art in this field, including methodologic issues, available collections, practical applications, challenges and shortcomings, and future directions, and introduces a European consortium of PDX models. Significance: PDX models are increasingly used in translational cancer research. These models are useful for drug screening, biomarker development, and the preclinical evaluation of personalized medicine strategies. This review provides a timely overview of the key characteristics of PDX models and a detailed discussion of future directions in the field. Cancer Discov; 4(9); 998–1013. ©2014 AACR .
1,309 citations
TL;DR: Among patients with hormone-receptor-positive metastatic breast cancer who had progression of disease during prior endocrine therapy, palbociclib combined with fulvestrant resulted in longer progression-free survival than fulvestrants alone.
Abstract: BackgroundGrowth of hormone-receptor–positive breast cancer is dependent on cyclin-dependent kinases 4 and 6 (CDK4 and CDK6), which promote progression from the G1 phase to the S phase of the cell cycle. We assessed the efficacy of palbociclib (an inhibitor of CDK4 and CDK6) and fulvestrant in advanced breast cancer. MethodsThis phase 3 study involved 521 patients with advanced hormone-receptor–positive, human epidermal growth factor receptor 2–negative breast cancer that had relapsed or progressed during prior endocrine therapy. We randomly assigned patients in a 2:1 ratio to receive palbociclib and fulvestrant or placebo and fulvestrant. Premenopausal or perimenopausal women also received goserelin. The primary end point was investigator-assessed progression-free survival. Secondary end points included overall survival, objective response, rate of clinical benefit, patient-reported outcomes, and safety. A preplanned interim analysis was performed by an independent data and safety monitoring committee af...
1,109 citations
TL;DR: It has been proposed that the isolation, ex vivo culture, and characterization of CTCs may provide an opportunity to noninvasively monitor the changing patterns of drug susceptibility in individual patients as their tumors acquire new mutations.
Abstract: Circulating tumor cells (CTCs) are present at low concentrations in the peripheral blood of patients with solid tumors. It has been proposed that the isolation, ex vivo culture, and characterization of CTCs may provide an opportunity to noninvasively monitor the changing patterns of drug susceptibility in individual patients as their tumors acquire new mutations. In a proof-of-concept study, we established CTC cultures from six patients with estrogen receptor-positive breast cancer. Three of five CTC lines tested were tumorigenic in mice. Genome sequencing of the CTC lines revealed preexisting mutations in the PIK3CA gene and newly acquired mutations in the estrogen receptor gene (ESR1), PIK3CA gene, and fibroblast growth factor receptor gene (FGFR2), among others. Drug sensitivity testing of CTC lines with multiple mutations revealed potential new therapeutic targets. With optimization of CTC culture conditions, this strategy may help identify the best therapies for individual cancer patients over the course of their disease.
796 citations
TL;DR: Results of pivotal phase III trials investigating palbociclib in patients with advanced-stage oestrogen receptor (ER)-positive breast cancer have demonstrated a substantial improvement in progression-free survival, with a well-tolerated toxicity profile.
Abstract: Uncontrolled cellular proliferation, mediated by dysregulation of the cell-cycle machinery and activation of cyclin-dependent kinases (CDKs) to promote cell-cycle progression, lies at the heart of cancer as a pathological process. Clinical implementation of first-generation, nonselective CDK inhibitors, designed to inhibit this proliferation, was originally hampered by the high risk of toxicity and lack of efficacy noted with these agents. The emergence of a new generation of selective CDK4/6 inhibitors, including ribociclib, abemaciclib and palbociclib, has enabled tumour types in which CDK4/6 has a pivotal role in the G1-to-S-phase cell-cycle transition to be targeted with improved effectiveness, and fewer adverse effects. Results of pivotal phase III trials investigating palbociclib in patients with advanced-stage oestrogen receptor (ER)-positive breast cancer have demonstrated a substantial improvement in progression-free survival, with a well-tolerated toxicity profile. Mechanisms of acquired resistance to CDK4/6 inhibitors are beginning to emerge that, although unwelcome, might enable rational post-CDK4/6 inhibitor therapeutic strategies to be identified. Extending the use of CDK4/6 inhibitors beyond ER-positive breast cancer is challenging, and will likely require biomarkers that are predictive of a response, and the use of combination therapies in order to optimize CDK4/6 targeting.
760 citations
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TL;DR: SAMtools as discussed by the authors implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Abstract: Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Availability: http://samtools.sourceforge.net
Contact: [email protected]
45,957 citations
TL;DR: This protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results, which takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
Abstract: Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
10,913 citations
TL;DR: The ANNOVAR tool to annotate single nucleotide variants and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP is developed.
Abstract: High-throughput sequencing platforms are generating massive amounts of genetic variation data for diverse genomes, but it remains a challenge to pinpoint a small subset of functionally important variants. To fill these unmet needs, we developed the ANNOVAR tool to annotate single nucleotide variants (SNVs) and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP. ANNOVAR can utilize annotation databases from the UCSC Genome Browser or any annotation data set conforming to Generic Feature Format version 3 (GFF3). We also illustrate a 'variants reduction' protocol on 4.7 million SNVs and indels from a human genome, including two causal mutations for Miller syndrome, a rare recessive disease. Through a stepwise procedure, we excluded variants that are unlikely to be causal, and identified 20 candidate genes including the causal gene. Using a desktop computer, ANNOVAR requires ∼4 min to perform gene-based annotation and ∼15 min to perform variants reduction on 4.7 million variants, making it practical to handle hundreds of human genomes in a day. ANNOVAR is freely available at http://www.openbioinformatics.org/annovar/.
10,461 citations
Daniel C. Koboldt1, Robert S. Fulton1, Michael D. McLellan1, Heather Schmidt1 +352 more•Institutions (35)
TL;DR: The ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity.
Abstract: We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.
9,355 citations
5,867 citations