This study evaluated the sensitivity of assaying tumor DNA circulating in the plasma to monitor breast cancer. This assay is compared with three other approaches: radiographic imaging, assay of ...cancer antigen 15-3 (CA 15-3) levels, and assay of circulating tumor cells.
Breast cancer is the most common cancer and the leading cause of cancer-related death in women worldwide.
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Metastatic breast cancer remains an incurable disease but is treatable by means of serial administration of endocrine, cytotoxic, or biologic therapies. The monitoring of treatment response is essential to avoid continuing ineffective therapies, to prevent unnecessary side effects, and to determine the benefit of new therapeutics. Treatment response is generally assessed with the use of serial imaging, but radiographic measurements often fail to detect changes in tumor burden. Therefore, there is an urgent need for biomarkers that measure tumor burden with high sensitivity . . .
IntClust is a classification of breast cancer comprising 10 subtypes based on molecular drivers identified through the integration of genomic and transcriptomic data from 1,000 breast tumors and ...validated in a further 1,000. We present a reliable method for subtyping breast tumors into the IntClust subtypes based on gene expression and demonstrate the clinical and biological validity of the IntClust classification.
We developed a gene expression-based approach for classifying breast tumors into the ten IntClust subtypes by using the ensemble profile of the index discovery dataset. We evaluate this approach in 983 independent samples for which the combined copy-number and gene expression IntClust classification was available. Only 24 samples are discordantly classified. Next, we compile a consolidated external dataset composed of a further 7,544 breast tumors. We use our approach to classify all samples into the IntClust subtypes. All ten subtypes are observable in most studies at comparable frequencies. The IntClust subtypes are significantly associated with relapse-free survival and recapitulate patterns of survival observed previously. In studies of neo-adjuvant chemotherapy, IntClust reveals distinct patterns of chemosensitivity. Finally, patterns of expression of genomic drivers reported by TCGA (The Cancer Genome Atlas) are better explained by IntClust as compared to the PAM50 classifier.
IntClust subtypes are reproducible in a large meta-analysis, show clinical validity and best capture variation in genomic drivers. IntClust is a driver-based breast cancer classification and is likely to become increasingly relevant as more targeted biological therapies become available.
MicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression.
Here we report the analysis of miRNA expression in ...93 primary human breast tumors, using a bead-based flow cytometric miRNA expression profiling method. Of 309 human miRNAs assayed, we identify 133 miRNAs expressed in human breast and breast tumors. We used mRNA expression profiling to classify the breast tumors as luminal A, luminal B, basal-like, HER2+ and normal-like. A number of miRNAs are differentially expressed between these molecular tumor subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumor subtypes in an independent data set. In some cases, changes in miRNA expression correlate with genomic loss or gain; in others, changes in miRNA expression are likely due to changes in primary transcription and or miRNA biogenesis. Finally, the expression of DICER1 and AGO2 is correlated with tumor subtype and may explain some of the changes in miRNA expression observed.
This study represents the first integrated analysis of miRNA expression, mRNA expression and genomic changes in human breast cancer and may serve as a basis for functional studies of the role of miRNAs in the etiology of breast cancer. Furthermore, we demonstrate that bead-based flow cytometric miRNA expression profiling might be a suitable platform to classify breast cancer into prognostic molecular subtypes.
Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is ...generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.
The R/Bioconductor package beadarray allows raw data from Illumina experiments to be read and stored in convenient R classes. Users are free to choose between various methods of image processing, ...background correction and normalization in their analysis rather than using the defaults in Illumina's; proprietary software. The package also allows quality assessment to be carried out on the raw data. The data can then be summarized and stored in a format which can be used by other R/Bioconductor packages to perform downstream analyses. Summarized data processed by Illumina's; BeadStudio software can also be read and analysed in the same manner. Availability: The beadarray package is available from the Bioconductor web page at www.bioconductor.org. A user's; guide and example data sets are provided with the package. Contact: md392@cam.ac.uk
Oestrogen receptor-α (ER) is the defining and driving transcription factor in the majority of breast cancers and its target genes dictate cell growth and endocrine response, yet genomic understanding ...of ER function has been restricted to model systems. Here we map genome-wide ER-binding events, by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq), in primary breast cancers from patients with different clinical outcomes and in distant ER-positive metastases. We find that drug-resistant cancers still recruit ER to the chromatin, but that ER binding is a dynamic process, with the acquisition of unique ER-binding regions in tumours from patients that are likely to relapse. The acquired ER regulatory regions associated with poor clinical outcome observed in primary tumours reveal gene signatures that predict clinical outcome in ER-positive disease exclusively. We find that the differential ER-binding programme observed in tumours from patients with poor outcome is not due to the selection of a rare subpopulation of cells, but is due to the FOXA1-mediated reprogramming of ER binding on a rapid timescale. The parallel redistribution of ER and FOXA1 binding events in drug-resistant cellular contexts is supported by histological co-expression of ER and FOXA1 in metastatic samples. By establishing transcription-factor mapping in primary tumour material, we show that there is plasticity in ER-binding capacity, with distinct combinations of cis-regulatory elements linked with the different clinical outcomes.
The COVID-19 pandemic is shifting teaching to an online setting all over the world. The Galaxy framework facilitates the online learning process and makes it accessible by providing a library of ...high-quality community-curated training materials, enabling easy access to data and tools, and facilitates sharing achievements and progress between students and instructors. By combining Galaxy with robust communication channels, effective instruction can be designed inclusively, regardless of the students' environments.
Synaptotagmin-IV (syt-IV) is a membrane trafficking protein that influences learning and memory, but its localization and role in synaptic function remain unclear. We found that syt-IV localized to ...brain-derived neurotrophic factor (BDNF)-containing vesicles in hippocampal neurons. Syt-IV/BDNF-harboring vesicles underwent exocytosis in both axons and dendrites, and syt-IV inhibited BDNF release at both sites. Knockout of syt-IV increased, and overexpression decreased, the rate of synaptic vesicle exocytosis from presynaptic terminals indirectly via changes in postsynaptic release of BDNF. Thus, postsynaptic syt-IV regulates the trans-synaptic action of BDNF to control presynaptic vesicle dynamics. Furthermore, selective loss of presynaptic syt-IV increased spontaneous quantal release, whereas a loss of postsynaptic syt-IV increased quantal amplitude. Finally, syt-IV knockout mice showed enhanced long-term potentiation (LTP), which depended entirely on disinhibition of BDNF release. Thus, regulation of BDNF secretion by syt-IV emerges as a mechanism for maintaining synaptic strength in a useful range during LTP.
Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput ...characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.
The contribution of microglia in neurological disorders is emerging as a leading disease driver rather than a consequence of pathology. RNAseT2‐deficient leukoencephalopathy is a severe childhood ...white matter disorder affecting patients in their first year of life and mimicking a cytomegalovirus brain infection. The early onset and resemblance of the symptoms to a viral infection suggest an inflammatory and embryonic origin of the pathology. There are no treatments available for this disease as our understanding of the cellular drivers of the pathology are still unknown. In this study, using a zebrafish mutant for the orthologous rnaset2 gene, we have identified an inflammatory signature in early development and an antiviral immune response in mature adult brains. Using the optical transparency and the ex utero development of the zebrafish larvae we studied immune cell behavior during brain development and identified abnormal microglia as an early marker of pathology. Live imaging and electron microscopy identified that mutant microglia displayed an engorged morphology and were filled with undigested apoptotic cells and undigested substrate. Using microglia‐specific depletion and rescue experiments, we identified microglia as drivers of this embryonic phenotype and potential key cellular player in the pathology of RNAseT2‐deficient leukoencephalopathy. Our zebrafish model also presented with reduced survival and locomotor defects, therefore recapitulating many aspects of the human disease. Our study therefore placed our rnaset2 mutant at the forefront of leukodystrophy preclinical models and highlighted tissue‐specific approaches as future therapeutic avenues.
Main Points
Loss of rnaset2 results in inflammation and lysosomal‐deficient microglia failing to digest dying neurons.
Targeting microglia restores embryonic microglial defects to clear neurodevelopmental apoptosis.
Mutants have reduced survival and locomotor defects.
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