Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup.

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

Increased gene expression variability in BRCA1-associated and basal-like breast tumours.

PURPOSE: Inherited variants in the cancer susceptibility genes, BRCA1 and BRCA2 account for up to 5% of breast cancers. Multiple gene expression studies have analysed gene expression patterns that maybe associated with BRCA12 pathogenic variant status; however, results from these studies lack consensus. These studies have focused on the differences in population means to identified genes associated with BRCA1/2-carriers with little consideration for gene expression variability, which is also under genetic control and is a feature of cellular function. METHODS: We measured differential gene expression variability in three of the largest familial breast cancer datasets and a 2116 breast cancer meta-cohort. Additionally, we used RNA in situ hybridisation to confirm expression variability of EN1 in an independent cohort of more than 500 breast tumours. RESULTS: BRCA1-associated breast tumours exhibited a 22.8% (95% CI 22.3-23.2) increase in transcriptome-wide gene expression variability compared to BRCAx tumours. Additionally, 40 genes were associated with BRCA1-related breast cancers that had ChIP-seq data suggestive of enriched EZH2 binding. Of these, two genes (EN1 and IGF2BP3) were significantly variable in both BRCA1-associated and basal-like breast tumours. RNA in situ analysis of EN1 supported a significant (p = 6.3 × 10-04) increase in expression variability in BRCA1-associated breast tumours. CONCLUSION: Our novel results describe a state of increased gene expression variability in BRCA1-related and basal-like breast tumours. Furthermore, genes with increased variability may be driven by changes in DNA occupancy of epigenetic effectors. The variation in gene expression is replicable and led to the identification of novel associations between genes and disease phenotypes.

Increased genomic burden of germline copy number variants is associated with early onset breast cancer: Australian breast cancer family registry.

BACKGROUND: Women with breast cancer who have multiple affected relatives are more likely to have inherited genetic risk factors for the disease. All the currently known genetic risk factors for breast cancer account for less than half of the average familial risk. Furthermore, the genetic factor(s) underlying an increased cancer risk for many women from multiple-case families remain unknown. Rare genomic duplications and deletions, known as copy number variants (CNVs), cover more than 10% of a human genome, are often not assessed in studies of genetic predisposition, and could account for some of the so-called "missing heritability". METHODS: We carried out a hypothesis-generating case-control study of breast cancer diagnosed before age 40 years (200 cases, 293 controls) using population-based cases from the Australian Breast Cancer Family Study. Genome-wide scanning for CNVs was performed using the Human610-Quad BeadChip and fine-mapping was conducted using PennCNV. RESULTS: We identified deletions overlapping two known cancer susceptibility genes, (BRCA1 and BLM), and a duplication overlapping SMARCB1, associated with risk. The number of deletions across the genome was 1.5-fold higher for cases than controls (P = 10-16), and 2-fold higher when only rare deletions overlapping genes (frequency <1%) were assessed (P = 5 × 10-4). Association tests of CNVs, followed by experimental validation of CNV calls, found deletions overlapping the OR4C11 and OR4P4 genes were associated with breast cancer (P = 0.02 and P = 0.03, respectively). CONCLUSION: These results suggest rare CNVs might have a role in breast cancer susceptibility, at least for disease at a young age.

Nanopore sequencing of full-length BRCA1 mRNA transcripts reveals co-occurrence of known exon skipping events.

BACKGROUND: Laboratory assays evaluating the effect of DNA sequence variants on BRCA1 mRNA splicing may contribute to classification by providing molecular evidence. However, our knowledge of normal and aberrant BRCA1 splicing events to date has been limited to data derived from assays targeting partial transcript sequences. This study explored the utility of nanopore sequencing to examine whole BRCA1 mRNA transcripts and to provide accurate categorisation of in-frame and out-of-frame splicing events. METHODS: The exon structure of BRCA1 transcripts from a previously studied control lymphoblastoid cell line were assessed using MinION nanopore sequencing of long-range reverse transcriptase-PCR amplicons. RESULTS: Our study identified and characterised 32 complete BRCA1 isoforms, including 18 novel isoforms which showed skipping of multiple contiguous and/or non-contiguous exons. Furthermore, we show that known BRCA1 exon skipping events, such as Δ(9,10) and Δ21, can co-occur in a single transcript, with some isoforms containing four or more alternative splice junctions. Fourteen novel isoforms were formed entirely from a combination of previously identified alternative splice junctions, suggesting that the total number of BRCA1 isoforms might be lower than the number of splicing events reported previously. CONCLUSIONS: Our results highlight complexity in BRCA1 transcript structure that has not been described previously. This finding has key implications for predicting the translation frame of splicing transcripts, important for interpreting the clinical significance of spliceogenic variants. Future research is warranted to quantitatively assess full-length BRCA1 transcript levels, and to assess the application of nanopore sequencing for routine evaluation of potential spliceogenic variants.

E-cadherin loss alters cytoskeletal organization and adhesion in non-malignant breast cells but is insufficient to induce an epithelial-mesenchymal transition.

BACKGROUND: E-cadherin is an adherens junction protein that forms homophilic intercellular contacts in epithelial cells while also interacting with the intracellular cytoskeletal networks. It has roles including establishment and maintenance of cell polarity, differentiation, migration and signalling in cell proliferation pathways. Its downregulation is commonly observed in epithelial tumours and is a hallmark of the epithelial to mesenchymal transition (EMT). METHODS: To improve our understanding of how E-cadherin loss contributes to tumorigenicity, we investigated the impact of its elimination from the non-tumorigenic breast cell line MCF10A. We performed cell-based assays and whole genome RNAseq to characterize an isogenic MCF10A cell line that is devoid of CDH1 expression due to an engineered homozygous 4 bp deletion in CDH1 exon 11. RESULTS: The E-cadherin-deficient line, MCF10A CDH1-/- showed subtle morphological changes, weaker cell-substrate adhesion, delayed migration, but retained cell-cell contact, contact growth inhibition and anchorage-dependent growth. Within the cytoskeleton, the apical microtubule network in the CDH1-deficient cells lacked the radial pattern of organization present in the MCF10A cells and F-actin formed thicker, more numerous stress fibres in the basal part of the cell. Whole genome RNAseq identified compensatory changes in the genes involved in cell-cell adhesion while genes involved in cell-substrate adhesion, notably ITGA1, COL8A1, COL4A2 and COL12A1, were significantly downregulated. Key EMT markers including CDH2, FN1, VIM and VTN were not upregulated although increased expression of proteolytic matrix metalloprotease and kallikrein genes was observed. CONCLUSIONS: Overall, our results demonstrated that E-cadherin loss alone was insufficient to induce an EMT or enhance transforming potential in the non-tumorigenic MCF10A cells but was associated with broad transcriptional changes associated with tissue remodelling.

APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP.

The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence.

Increased Ascorbate Content of Glioblastoma Is Associated With a Suppressed Hypoxic Response and Improved Patient Survival.

Glioblastoma multiforme is a challenging disease with limited treatment options and poor survival. Glioblastoma tumours are characterised by hypoxia that activates the hypoxia inducible factor (HIF) pathway and controls a myriad of genes that drive cancer progression. HIF transcription factors are regulated at the post-translation level via HIF-hydroxylases. These hydroxylases require oxygen and 2-oxoglutarate as substrates, and ferrous iron and ascorbate as cofactors. In this retrospective observational study, we aimed to determine whether ascorbate played a role in the hypoxic response of glioblastoma, and whether this affected patient outcome. We measured the ascorbate content and members of the HIF-pathway of clinical glioblastoma samples, and assessed their association with clinicopathological features and patient survival. In 37 samples (37 patients), median ascorbate content was 7.6 µg ascorbate/100 mg tissue, range 0.8 - 20.4 µg ascorbate/100 mg tissue. In tumours with above median ascorbate content, HIF-pathway activity as a whole was significantly suppressed (p = 0.005), and several members of the pathway showed decreased expression (carbonic anhydrase-9 and glucose transporter-1, both p < 0.01). Patients with either lower tumour HIF-pathway activity or higher tumour ascorbate content survived significantly longer than patients with higher HIF-pathway or lower ascorbate levels (p = 0.011, p = 0.043, respectively). Median survival for the low HIF-pathway score group was 362 days compared to 203 days for the high HIF-pathway score group, and median survival for the above median ascorbate group was 390 days, compared to the below median ascorbate group with 219 days. The apparent survival advantage associated with higher tumour ascorbate was more prominent for the first 8 months following surgery. These associations are promising, suggesting an important role for ascorbate-regulated HIF-pathway activity in glioblastoma that may impact on patient survival.

Ascorbate content of clinical glioma tissues is related to tumour grade and to global levels of 5-hydroxymethyl cytosine.

Gliomas are incurable brain cancers with poor prognosis, with epigenetic dysregulation being a distinctive feature. 5-hydroxymethylcytosine (5-hmC), an intermediate generated in the demethylation of 5-methylcytosine, is present at reduced levels in glioma tissue compared with normal brain, and that higher levels of 5-hmC are associated with improved patient survival. DNA demethylation is enzymatically driven by the ten-eleven translocation (TET) dioxygenases that require ascorbate as an essential cofactor. There is limited data on ascorbate in gliomas and the relationship between ascorbate and 5-hmC in gliomas has never been reported. Clinical glioma samples (11 low-grade, 26 high-grade) were analysed for ascorbate, global DNA methylation and hydroxymethylation, and methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter. Low-grade gliomas contained significantly higher levels of ascorbate than high-grade gliomas (p = 0.026). Levels of 5-hmC were significantly higher in low-grade than high-grade glioma (p = 0.0013). There was a strong association between higher ascorbate and higher 5-hmC (p = 0.004). Gliomas with unmethylated and methylated MGMT promoters had similar ascorbate levels (p = 0.96). One mechanism by which epigenetic modifications could occur is through ascorbate-mediated optimisation of TET activity in gliomas. These findings open the door to clinical intervention trials in patients with glioma to provide both mechanistic information and potential avenues for adjuvant ascorbate therapy.

Copy number variants as modifiers of breast cancer risk for BRCA1/BRCA2 pathogenic variant carriers.

The contribution of germline copy number variants (CNVs) to risk of developing cancer in individuals with pathogenic BRCA1 or BRCA2 variants remains relatively unknown. We conducted the largest genome-wide analysis of CNVs in 15,342 BRCA1 and 10,740 BRCA2 pathogenic variant carriers. We used these results to prioritise a candidate breast cancer risk-modifier gene for laboratory analysis and biological validation. Notably, the HR for deletions in BRCA1 suggested an elevated breast cancer risk estimate (hazard ratio (HR) = 1.21), 95% confidence interval (95% CI = 1.09-1.35) compared with non-CNV pathogenic variants. In contrast, deletions overlapping SULT1A1 suggested a decreased breast cancer risk (HR = 0.73, 95% CI 0.59-0.91) in BRCA1 pathogenic variant carriers. Functional analyses of SULT1A1 showed that reduced mRNA expression in pathogenic BRCA1 variant cells was associated with reduced cellular proliferation and reduced DNA damage after treatment with DNA damaging agents. These data provide evidence that deleterious variants in BRCA1 plus SULT1A1 deletions contribute to variable breast cancer risk in BRCA1 carriers.

Variable expression quantitative trait loci analysis of breast cancer risk variants.

Genome wide association studies (GWAS) have identified more than 180 variants associated with breast cancer risk, however the underlying functional mechanisms and biological pathways which confer disease susceptibility remain largely unknown. As gene expression traits are under genetic regulation we hypothesise that differences in gene expression variability may identify causal breast cancer susceptibility genes. We performed variable expression quantitative trait loci (veQTL) analysis using tissue-specific expression data from the Genotype-Tissue Expression (GTEx) Common Fund Project. veQTL analysis identified 70 associations (p < 5 × 10-8) consisting of 60 genes and 27 breast cancer risk variants, including 55 veQTL that were observed in breast tissue only. Pathway analysis of genes associated with breast-specific veQTL revealed an enrichment of four genes (CYP11B1, CYP17A1 HSD3B2 and STAR) involved in the C21-steroidal biosynthesis pathway that converts cholesterol to breast-related hormones (e.g. oestrogen). Each of these four genes were significantly more variable in individuals homozygous for rs11075995 (A/A) breast cancer risk allele located in the FTO gene, which encodes an RNA demethylase. The A/A allele was also found associated with reduced expression of FTO, suggesting an epi-transcriptomic mechanism may underlie the dysregulation of genes involved in hormonal biosynthesis leading to an increased risk of breast cancer. These findings provide evidence that genetic variants govern high levels of expression variance in breast tissue, thus building a more comprehensive insight into the underlying biology of breast cancer risk loci.

RNAscope compatibility with image analysis platforms for the quantification of tissue-based colorectal cancer biomarkers in archival formalin-fixed paraffin-embedded tissue.

RNAscope®, has emerged as an important in-situ hybridisation method to validate mRNA expression within single cells whilst preserving tissue morphology in histological samples. The aim of this research was to compare the utility of various open-source and commercial image analysis methods, to quantify mRNA transcripts identified by RNAscope within formalin fixed paraffin embedded (FFPE) histological samples and cell monolayer preparations. Examination of MLH1 expression from 10 histological FFPE colorectal cancer specimens using four image analysis tools (Colour Deconvolution, SpotStudio, WEKA and the LEICA RNA-ISH algorithm) showed the WEKA tool as having the greatest level of agreement with manual quantification. Comparing image analysis methods to qRT-PCR for quantifying MLH1, GFI1 and TNFRSF11A expression within two colorectal cell lines results suggest that these image analysis methods perform at a similar level to qRT-PCR. Furthermore, we describe the strengths and limitations for each image analysis method when used in combination with RNAscope assays. Our study concludes that there are several freely available and commercial image analysis tools that enable reliable RNA in situ expression analysis, however operators need to consider factors, such as expected expression levels of target genes, software usability and functionality.

Differential Expression of BARD1 Isoforms in Melanoma.

Melanoma comprises <5% of cutaneous malignancies, yet it causes a significant proportion of skin cancer-related deaths worldwide. While new therapies for melanoma have been developed, not all patients respond well. Thus, further research is required to better predict patient outcomes. Using long-range nanopore sequencing, RT-qPCR, and RNA sequencing analyses, we examined the transcription of BARD1 splice isoforms in melanoma cell lines and patient tissue samples. Seventy-six BARD1 mRNA variants were identified in total, with several previously characterised isoforms (γ, φ, δ, ε, and η) contributing to a large proportion of the expressed transcripts. In addition, we identified four novel splice events, namely, Δ(E3_E9), ▼(i8), IVS10+131▼46, and IVS10▼176, occurring in various combinations in multiple transcripts. We found that short-read RNA-Seq analyses were limited in their ability to predict isoforms containing multiple non-contiguous splicing events, as compared to long-range nanopore sequencing. These studies suggest that further investigations into the functional significance of the identified BARD1 splice variants in melanoma are warranted.

Genome-Wide Gene Expression Analyses of BRCA1- and BRCA2-Associated Breast and Ovarian Tumours.

Germline pathogenic variants in BRCA1 and BRCA2 increase cumulative lifetime risk up to 75% for breast cancer and 76% for ovarian cancer. Genetic testing for BRCA1 and BRCA2 pathogenic variants has become an important part of clinical practice for cancer risk assessment and for reducing individual risk of developing cancer. Genetic testing can produce three outcomes: positive (a pathogenic variant), uninformative (no pathogenic variant) and uncertain significance (a variant of unknown clinical significance). More than one third of BRCA1 and BRCA2 variants identified have been classified as variants of uncertain significance, presenting a challenge for clinicians. To address this important clinical challenge, a number of studies have been undertaken to establish a gene expression phenotype for pathogenic BRCA1 and BRCA2 variant carriers in several diseased and normal tissues. However, the consistency of gene expression phenotypes described in studies has been poor. To determine if gene expression analysis has been a successful approach for variant classification, we describe the design and comparability of 23 published gene expression studies that have profiled cells from BRCA1 and BRCA2 pathogenic variant carriers. We show the impact of advancements in expression-based technologies, the importance of developing larger study cohorts and the necessity to better understand variables affecting gene expression profiles across different tissue types.

Comprehensive Assessment of BARD1 Messenger Ribonucleic Acid Splicing With Implications for Variant Classification.

Introduction: Case-control analyses have shown BARD1 variants to be associated with up to >2-fold increase in risk of breast cancer, and potentially greater risk of triple negative breast cancer. BARD1 is included in several gene sequencing panels currently marketed for the prediction of risk of cancer, however there are no gene-specific guidelines for the classification of BARD1 variants. We present the most comprehensive assessment of BARD1 messenger RNA splicing, and demonstrate the application of these data for the classification of truncating and splice site variants according to American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines. Methods: Nanopore sequencing, short-read RNA-seq (whole transcriptome and targeted), and capillary electrophoresis analysis were performed by four laboratories to investigate alternative BARD1 splicing in blood, breast, and fimbriae/ovary related specimens from non-cancer affected tissues. Splicing data were also collated from published studies of nine different tissues. The impact of the findings for PVS1 annotation was assessed for truncating and splice site variants. Results: We identified 62 naturally occurring alternative spliced BARD1 splicing events, including 19 novel events found by next generation sequencing and/or reverse transcription PCR analysis performed for this study. Quantitative analysis showed that naturally occurring splicing events causing loss of clinically relevant domains or nonsense mediated decay can constitute up to 11.9% of overlapping natural junctions, suggesting that aberrant splicing can be tolerated up to this level. Nanopore sequencing of whole BARD1 transcripts characterized 16 alternative isoforms from healthy controls, revealing that the most complex transcripts combined only two alternative splicing events. Bioinformatic analysis of ClinVar submitted variants at or near BARD1 splice sites suggest that all consensus splice site variants in BARD1 should be considered likely pathogenic, with the possible exception of variants at the donor site of exon 5. Conclusions: No BARD1 candidate rescue transcripts were identified in this study, indicating that all premature translation-termination codons variants can be annotated as PVS1. Furthermore, our analysis suggests that all donor and acceptor (IVS+/-1,2) variants can be considered PVS1 or PVS1_strong, with the exception of variants targeting the exon 5 donor site, that we recommend considering as PVS1_moderate.

Correction: Evaluation of copy-number variants as modifiers of breast and ovarian cancer risk for BRCA1 pathogenic variant carriers.

This Article was originally published under a CC BY-NC-SA 4.0 license, but has now been made available under a CC BY 4.0 license. The PDF and HTML versions of the Article have been modified accordingly.

Evaluation of copy-number variants as modifiers of breast and ovarian cancer risk for BRCA1 pathogenic variant carriers.

Genome-wide studies of patients carrying pathogenic variants (mutations) in BRCA1 or BRCA2 have reported strong associations between single-nucleotide polymorphisms (SNPs) and cancer risk. To conduct the first genome-wide association analysis of copy-number variants (CNVs) with breast or ovarian cancer risk in a cohort of 2500 BRCA1 pathogenic variant carriers, CNV discovery was performed using multiple calling algorithms and Illumina 610k SNP array data from a previously published genome-wide association study. Our analysis, which focused on functionally disruptive genomic deletions overlapping gene regions, identified a number of loci associated with risk of breast or ovarian cancer for BRCA1 pathogenic variant carriers. Despite only including putative deletions called by at least two or more algorithms, detection of selected CNVs by ancillary molecular technologies only confirmed 40% of predicted common (>1% allele frequency) variants. These include four loci that were associated (unadjusted P<0.05) with breast cancer (GTF2H2, ZNF385B, NAALADL2 and PSG5), and two loci associated with ovarian cancer (CYP2A7 and OR2A1). An interesting finding from this study was an association of a validated CNV deletion at the CYP2A7 locus (19q13.2) with decreased ovarian cancer risk (relative risk=0.50, P=0.007). Genomic analysis found this deletion coincides with a region displaying strong regulatory potential in ovarian tissue, but not in breast epithelial cells. This study highlighted the need to verify CNVs in vitro, but also provides evidence that experimentally validated CNVs (with plausible biological consequences) can modify risk of breast or ovarian cancer in BRCA1 pathogenic variant carriers.

The Role of Constitutional Copy Number Variants in Breast Cancer.

Constitutional copy number variants (CNVs) include inherited and de novo deviations from a diploid state at a defined genomic region. These variants contribute significantly to genetic variation and disease in humans, including breast cancer susceptibility. Identification of genetic risk factors for breast cancer in recent years has been dominated by the use of genome-wide technologies, such as single nucleotide polymorphism (SNP)-arrays, with a significant focus on single nucleotide variants. To date, these large datasets have been underutilised for generating genome-wide CNV profiles despite offering a massive resource for assessing the contribution of these structural variants to breast cancer risk. Technical challenges remain in determining the location and distribution of CNVs across the human genome due to the accuracy of computational prediction algorithms and resolution of the array data. Moreover, better methods are required for interpreting the functional effect of newly discovered CNVs. In this review, we explore current and future application of SNP array technology to assess rare and common CNVs in association with breast cancer risk in humans.