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Clinical Cancer Research : An Official... Aug 2016BRCA1/2-mutated and some sporadic triple-negative breast cancers (TNBC) have DNA repair defects and are sensitive to DNA-damaging therapeutics. Recently, three...
PURPOSE
BRCA1/2-mutated and some sporadic triple-negative breast cancers (TNBC) have DNA repair defects and are sensitive to DNA-damaging therapeutics. Recently, three independent DNA-based measures of genomic instability were developed on the basis of loss of heterozygosity (LOH), telomeric allelic imbalance (TAI), and large-scale state transitions (LST).
EXPERIMENTAL DESIGN
We assessed a combined homologous recombination deficiency (HRD) score, an unweighted sum of LOH, TAI, and LST scores, in three neoadjuvant TNBC trials of platinum-containing therapy. We then tested the association of HR deficiency, defined as HRD score ≥42 or BRCA1/2 mutation, with response to platinum-based therapy.
RESULTS
In a trial of neoadjuvant platinum, gemcitabine, and iniparib, HR deficiency predicted residual cancer burden score of 0 or I (RCB 0/I) and pathologic complete response (pCR; OR = 4.96, P = 0.0036; OR = 6.52, P = 0.0058). HR deficiency remained a significant predictor of RCB 0/I when adjusted for clinical variables (OR = 5.86, P = 0.012). In two other trials of neoadjuvant cisplatin therapy, HR deficiency predicted RCB 0/I and pCR (OR = 10.18, P = 0.0011; OR = 17.00, P = 0.0066). In a multivariable model of RCB 0/I, HR deficiency retained significance when clinical variables were included (OR = 12.08, P = 0.0017). When restricted to BRCA1/2 nonmutated tumors, response was higher in patients with high HRD scores: RCB 0/I P = 0.062, pCR P = 0.063 in the neoadjuvant platinum, gemcitabine, and iniparib trial; RCB 0/I P = 0.0039, pCR P = 0.018 in the neoadjuvant cisplatin trials.
CONCLUSIONS
HR deficiency identifies TNBC tumors, including BRCA1/2 nonmutated tumors more likely to respond to platinum-containing therapy. Clin Cancer Res; 22(15); 3764-73. ©2016 AACR.
Topics: Allelic Imbalance; Antineoplastic Combined Chemotherapy Protocols; Biomarkers, Tumor; Female; Genes, BRCA1; Genes, BRCA2; Homologous Recombination; Humans; Loss of Heterozygosity; Mutation; Neoplasm Staging; Odds Ratio; Platinum; Prognosis; Telomere; Treatment Outcome; Triple Negative Breast Neoplasms
PubMed: 26957554
DOI: 10.1158/1078-0432.CCR-15-2477 -
Pflugers Archiv : European Journal of... May 2019Mutations in cardiac myosin binding protein C (MYBPC3) represent the most frequent cause of familial hypertrophic cardiomyopathy (HCM), making up approximately 50% of... (Review)
Review
Mutations in cardiac myosin binding protein C (MYBPC3) represent the most frequent cause of familial hypertrophic cardiomyopathy (HCM), making up approximately 50% of identified HCM mutations. MYBPC3 is distinct among other sarcomere genes associated with HCM in that truncating mutations make up the vast majority, whereas nontruncating mutations predominant in other sarcomere genes. Several studies using myocardial tissue from HCM patients have found reduced abundance of wild-type MYBPC3 compared to control hearts, suggesting haploinsufficiency of full-length MYBPC3. Further, decreased mutant versus wild-type mRNA and lack of truncated mutant MYBPC3 protein has been demonstrated, highlighting the presence of allelic imbalance. In this review, we will begin by introducing allelic imbalance and haploinsufficiency, highlighting the broad role each plays within the spectrum of human disease. We will subsequently focus on the roles allelic imbalance and haploinsufficiency play within MYBPC3-linked HCM. Finally, we will explore the implications of these findings on future directions of HCM research. An improved understanding of allelic imbalance and haploinsufficiency may help us better understand genotype-phenotype relationships in HCM and develop novel targeted therapies, providing exciting future research opportunities.
Topics: Animals; Cardiomyopathy, Hypertrophic; Carrier Proteins; Haploinsufficiency; Humans
PubMed: 30456444
DOI: 10.1007/s00424-018-2226-9 -
Bioinformatics (Oxford, England) Jul 2019Genetic analysis of cancer regularly includes two or more samples from the same patient. Somatic copy number alterations leading to allelic imbalance (AI) play a...
MOTIVATION
Genetic analysis of cancer regularly includes two or more samples from the same patient. Somatic copy number alterations leading to allelic imbalance (AI) play a critical role in cancer initiation and progression. Directional analysis and visualization of the alleles in imbalance in multi-sample settings allow for inference of recurrent mutations, providing insights into mutation rates, clonality and the genomic architecture and etiology of cancer.
RESULTS
The REpeat Chromosomal changes Uncovered by Reflection (RECUR) is an R application for the comparative analysis of AI profiles derived from SNP array and next-generation sequencing data. The algorithm accepts genotype calls and 'B allele' frequencies (BAFs) from at least two samples derived from the same individual. For a predefined set of genomic regions with AI, RECUR compares BAF values among samples. In the presence of AI, the expected value of a BAF can shift in two possible directions, reflecting an increased or decreased abundance of the maternal haplotype, relative to the paternal. The phenomenon of opposite haplotype shifts, or 'mirrored subclonal allelic imbalance', is a form of heterogeneity, and has been linked to clinico-pathological features of cancer. RECUR detects such genomic segments of opposite haplotypes in imbalance and plots BAF values for all samples, using a two-color scheme for intuitive visualization.
AVAILABILITY AND IMPLEMENTATION
RECUR is available as an R application. Source code and documentation are available at scheet.org.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
Topics: Alleles; Allelic Imbalance; DNA Copy Number Variations; Haplotypes; Humans; Polymorphism, Single Nucleotide
PubMed: 30462146
DOI: 10.1093/bioinformatics/bty885 -
Transcriptional bursts explain autosomal random monoallelic expression and affect allelic imbalance.PLoS Computational Biology Mar 2021Transcriptional bursts render substantial biological noise in cellular transcriptomes. Here, we investigated the theoretical extent of allelic expression resulting from...
Transcriptional bursts render substantial biological noise in cellular transcriptomes. Here, we investigated the theoretical extent of allelic expression resulting from transcriptional bursting and how it compared to the amount biallelic, monoallelic and allele-biased expression observed in single-cell RNA-sequencing (scRNA-seq) data. We found that transcriptional bursting can explain the allelic expression patterns observed in single cells, including the frequent observations of autosomal monoallelic gene expression. Importantly, we identified that the burst frequency largely determined the fraction of cells with monoallelic expression, whereas the burst size had little effect on monoallelic observations. The high consistency between the bursting model predictions and scRNA-seq observations made it possible to assess the heterogeneity of a group of cells as their deviation in allelic observations from the expected. Finally, both burst frequency and size contributed to allelic imbalance observations and reinforced that studies of allelic imbalance can be confounded from the inherent noise in transcriptional bursting. Altogether, we demonstrate that allele-level transcriptional bursting renders widespread, although predictable, amounts of monoallelic and biallelic expression in single cells and cell populations.
Topics: Allelic Imbalance; Animals; Female; Male; Mice; Models, Genetic; Sequence Analysis, RNA; Single-Cell Analysis; Transcription, Genetic; Transcriptome
PubMed: 33690599
DOI: 10.1371/journal.pcbi.1008772 -
Genetics Jun 2015In mammals, several classes of monoallelic genes have been identified, including those subject to X-chromosome inactivation (XCI), genomic imprinting, and random...
In mammals, several classes of monoallelic genes have been identified, including those subject to X-chromosome inactivation (XCI), genomic imprinting, and random monoallelic expression (RMAE). However, the extent to which these epigenetic phenomena are influenced by underlying genetic variation is unknown. Here we perform a systematic classification of allelic imbalance in mouse hybrids derived from reciprocal crosses of divergent strains. We observe that deviation from balanced biallelic expression is common, occurring in ∼20% of the mouse transcriptome in a given tissue. Allelic imbalance attributed to genotypic variation is by far the most prevalent class and typically is tissue-specific. However, some genotype-based imbalance is maintained across tissues and is associated with greater genetic variation, especially in 5' and 3' termini of transcripts. We further identify novel random monoallelic and imprinted genes and find that genotype can modify penetrance of parental origin even in the setting of large imprinted regions. Examination of nascent transcripts in single cells from inbred parental strains reveals that genes showing genotype-based imbalance in hybrids can also exhibit monoallelic expression in isogenic backgrounds. This surprising observation may suggest a competition between alleles and/or reflect the combined impact of cis- and trans-acting variation on expression of a given gene. Our findings provide novel insights into gene regulation and may be relevant to human genetic variation and disease.
Topics: Alleles; Allelic Imbalance; Animals; Cluster Analysis; Crosses, Genetic; Gene Expression Profiling; Genetic Variation; Genomic Imprinting; Genotype; Mice; Organ Specificity; Transcriptome
PubMed: 25858912
DOI: 10.1534/genetics.115.176263 -
Pflugers Archiv : European Journal of... May 2019Hypertrophic cardiomyopathy (HCM) is mainly caused by mutations in sarcomeric proteins. Thirty to forty percent of identified mutations are found in the ventricular... (Review)
Review
Hypertrophic cardiomyopathy (HCM) is mainly caused by mutations in sarcomeric proteins. Thirty to forty percent of identified mutations are found in the ventricular myosin heavy chain (β-MyHC). A common mechanism explaining how numerous mutations in several different proteins induce a similar HCM-phenotype is unclear. It was proposed that HCM-mutations cause hypercontractility, which for some mutations is thought to result from mutation-induced unlocking of myosin heads from a so-called super-relaxed state (SRX). The SRX was suggested to be related to the "interacting head motif," i.e., pairs of myosin heads folded back onto their S2-region. Here, we address these structural states of myosin in context of earlier work on weak binding cross-bridges. However, not all HCM-mutations cause hypercontractility and/or are involved in the interacting head motif. But most likely, all mutations alter the force generating mechanism, yet in different ways, possibly including inhibition of SRX. Such functional-hyper- and hypocontractile-changes are the basis of our previously proposed concept stating that contractile imbalance due to unequal fractions of mutated and wildtype protein among individual cardiomyocytes over time will induce cardiomyocyte disarray and fibrosis, hallmarks of HCM. Studying β-MyHC-mutations, we found substantial contractile variability from cardiomyocyte to cardiomyocyte within a patient's myocardium, much higher than in controls. This was paralleled by a similarly variable fraction of mutant MYH7-mRNA (cell-to-cell allelic imbalance), due to random, burst-like transcription, independent for mutant and wildtype MYH7-alleles. Evidence suggests that HCM-mutations in other sarcomeric proteins follow the same disease mechanism.
Topics: Allelic Imbalance; Animals; Cardiac Myosins; Cardiomyopathy, Hypertrophic; Humans; Mutation; Myocardial Contraction; Myocytes, Cardiac
PubMed: 30740621
DOI: 10.1007/s00424-019-02260-9 -
RNA (New York, N.Y.) Oct 2016Clonal level random allelic expression imbalance and random monoallelic expression provides cellular heterogeneity within tissues by modulating allelic dosage. Although...
Clonal level random allelic expression imbalance and random monoallelic expression provides cellular heterogeneity within tissues by modulating allelic dosage. Although such expression patterns have been observed in multiple cell types, little is known about when in development these stochastic allelic choices are made. We examine allelic expression patterns in human neural progenitor cells before and after epigenetic reprogramming to induced pluripotency, observing that loci previously characterized by random allelic expression imbalance (0.63% of expressed genes) are generally reset to a biallelic state in induced pluripotent stem cells (iPSCs). We subsequently neuralized the iPSCs and profiled isolated clonal neural stem cells, observing that significant random allelic expression imbalance is reestablished at 0.65% of expressed genes, including novel loci not found to show allelic expression imbalance in the original parental neural progenitor cells. Allelic expression imbalance was associated with altered DNA methylation across promoter regulatory regions, with clones characterized by skewed allelic expression being hypermethylated compared to their biallelic sister clones. Our results suggest that random allelic expression imbalance is established during lineage commitment and is associated with increased DNA methylation at the gene promoter.
Topics: Allelic Imbalance; Cells, Cultured; Cellular Reprogramming; DNA Methylation; Epigenesis, Genetic; Humans; Induced Pluripotent Stem Cells; Neural Stem Cells
PubMed: 27539784
DOI: 10.1261/rna.058347.116 -
BMC Research Notes Nov 2021Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Methods for testing AI...
OBJECTIVE
Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Methods for testing AI exist, but methods are needed to estimate type I error and power for detecting AI and difference of AI between conditions. As the costs of the technology plummet, what is more important: reads or replicates?
RESULTS
We find that a minimum of 2400, 480, and 240 allele specific reads divided equally among 12, 5, and 3 replicates is needed to detect a 10, 20, and 30%, respectively, deviation from allelic balance in a condition with power > 80%. A minimum of 960 and 240 allele specific reads divided equally among 8 replicates is needed to detect a 20 or 30% difference in AI between conditions with comparable power. Higher numbers of replicates increase power more than adding coverage without affecting type I error. We provide a Python package that enables simulation of AI scenarios and enables individuals to estimate type I error and power in detecting AI and differences in AI between conditions.
Topics: Alleles; Allelic Imbalance; Bayes Theorem; Computer Simulation; Humans
PubMed: 34838135
DOI: 10.1186/s13104-021-05851-x -
ELife Feb 2022Mapping of allelic imbalance (AI) at heterozygous loci has the potential to establish links between genetic risk for disease and biological function. Leveraging...
Mapping of allelic imbalance (AI) at heterozygous loci has the potential to establish links between genetic risk for disease and biological function. Leveraging multi-omics data for AI analysis and functional annotation, we discovered a novel functional risk variant rs1047643 at 8p23 in association with systemic lupus erythematosus (SLE). This variant displays dynamic AI of chromatin accessibility and allelic expression on gene in B cells with SLE. We further found a B-cell restricted super-enhancer (SE) that physically contacts with this SNP-residing locus, an interaction that also appears specifically in B cells. Quantitative analysis of chromatin accessibility and DNA methylation profiles further demonstrated that the SE exhibits aberrant activity in B cell development with SLE. Functional studies identified that STAT3, a master factor associated with autoimmune diseases, directly regulates both the AI of risk variant and the activity of SE in cultured B cells. Our study reveals that STAT3-mediated SE activity and cis-regulatory effects of SNP rs1047643 at 8p23 locus are associated with B cell deregulation in SLE.
Topics: Alleles; Allelic Imbalance; B-Lymphocytes; Genetic Predisposition to Disease; Humans; Lupus Erythematosus, Systemic; Polymorphism, Single Nucleotide; STAT3 Transcription Factor
PubMed: 35188103
DOI: 10.7554/eLife.72837 -
BMC Medical Genomics May 2021Allelic imbalance (AI) in tumors is caused by chromosomal and sub-chromosomal gains and losses.
BACKGROUND
Allelic imbalance (AI) in tumors is caused by chromosomal and sub-chromosomal gains and losses.
RESULTS
We evaluated AI at 109,086 germline exonic SNP loci in four cancer types, and identified a set of SNPs that demonstrate strong tumor allele specificity in AI events. Further analyses demonstrated that these alleles show consistently different frequencies in the cancer population compared to the healthy population and are significantly enriched for predicted protein-damaging variants. Moreover, genes harboring SNPs that demonstrate allele specificity are enriched for cancer-related biological processes and are more likely to be essential in cancer cells.
CONCLUSIONS
In summary, our study provides a unique and complementary method to identify genes and variants that are relevant to carcinogenesis.
Topics: Allelic Imbalance
PubMed: 34059054
DOI: 10.1186/s12920-021-00984-1