Regional-specific calibration enables application of computational evidence for clinical classification of 5' cis-regulatory variants in Mendelian disease.

To date, clinical genetic testing for Mendelian disease variants has focused heavily on exonic coding and intronic gene regions. This multi-step study was undertaken to provide an evidence base for selecting and applying computational approaches for use in clinical classification of 5' cis-regulatory region variants. Curated datasets of clinically reported disease-causing 5' cis-regulatory region variants and variants from matched genomic regions in population controls were used to calibrate six bioinformatic tools as predictors of variant pathogenicity. Likelihood ratio estimates were aligned to code weights following ClinGen recommendations for application of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) classification scheme. Considering code assignment across all reference dataset variants, performance was best for CADD (81.2%) and REMM (81.5%). Optimized thresholds provided moderate evidence toward pathogenicity (CADD, REMM) and moderate (CADD) or supporting (REMM) evidence against pathogenicity. Both sensitivity and specificity of prediction were improved when further categorizing variants based on location in an EPDnew-defined promoter region. Combining predictions (CADD, REMM, and location in a promoter region) increased specificity at the expense of sensitivity. Importantly, the optimal CADD thresholds for assigning ACMG/AMP codes PP3 (≥10) and BP4 (≤8) were vastly different from recommendations for protein-coding variants (PP3 ≥25.3; BP4 ≤22.7); CADD <22.7 would incorrectly assign BP4 for >90% of reported disease-causing cis-regulatory region variants. Our results demonstrate the need to consider a tiered approach and tailored score thresholds to optimize bioinformatic impact prediction for clinical classification of 5' cis-regulatory region variants.

The clinical utility and costs of whole-genome sequencing to detect cancer susceptibility variants-a multi-site prospective cohort study.

BACKGROUND: Many families and individuals do not meet criteria for a known hereditary cancer syndrome but display unusual clusters of cancers. These families may carry pathogenic variants in cancer predisposition genes and be at higher risk for developing cancer. METHODS: This multi-centre prospective study recruited 195 cancer-affected participants suspected to have a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing (WGS) and a comprehensive cancer virtual gene panel analysis were undertaken. RESULTS: Pathogenic variants consistent with the presenting cancer(s) were identified in 5.1% (10/195) of participants and pathogenic variants considered secondary findings with potential risk management implications were identified in another 9.7% (19/195) of participants. Health economic analysis estimated the marginal cost per case with an actionable variant was significantly lower for upfront WGS with virtual panel ($8744AUD) compared to standard testing followed by WGS ($24,894AUD). Financial analysis suggests that national adoption of diagnostic WGS testing would require a ninefold increase in government annual expenditure compared to conventional testing. CONCLUSIONS: These findings make a case for replacing conventional testing with WGS to deliver clinically important benefits for cancer patients and families. The uptake of such an approach will depend on the perspectives of different payers on affordability.

SpliceAI-10k calculator for the prediction of pseudoexonization, intron retention, and exon deletion.

SUMMARY: SpliceAI is a widely used splicing prediction tool and its most common application relies on the maximum delta score to assign variant impact on splicing. We developed the SpliceAI-10k calculator (SAI-10k-calc) to extend use of this tool to predict: the splicing aberration type including pseudoexonization, intron retention, partial exon deletion, and (multi)exon skipping using a 10 kb analysis window; the size of inserted or deleted sequence; the effect on reading frame; and the altered amino acid sequence. SAI-10k-calc has 95% sensitivity and 96% specificity for predicting variants that impact splicing, computed from a control dataset of 1212 single-nucleotide variants (SNVs) with curated splicing assay results. Notably, it has high performance (≥84% accuracy) for predicting pseudoexon and partial intron retention. The automated amino acid sequence prediction allows for efficient identification of variants that are expected to result in mRNA nonsense-mediated decay or translation of truncated proteins. AVAILABILITY AND IMPLEMENTATION: SAI-10k-calc is implemented in R (https://github.com/adavi4/SAI-10k-calc) and also available as a Microsoft Excel spreadsheet. Users can adjust the default thresholds to suit their target performance values.

Germline pathogenic SMARCA4 variants in neuroblastoma.

Heterozygous germline pathogenic variants (GPVs) in SMARCA4, the gene encoding the ATP-dependent chromatin remodelling protein SMARCA4 (previously known as BRG1), predispose to several rare tumour types, including small cell carcinoma of the ovary, hypercalcaemic type, atypical teratoid and malignant rhabdoid tumour, and uterine sarcoma. The increase in germline testing of SMARCA4 in recent years has revealed putative GPVs affecting SMARCA4 in patients with other cancer types. Here we describe 11 patients with neuroblastoma (NBL), including 4 previously unreported cases, all of whom were found to harbour heterozygous germline variants in SMARCA4 Median age at diagnosis was 5 years (range 2 months-26 years); nine were male; and eight of nine cases had tumour location information in the adrenal gland. Eight of the germline variants were expected to result in loss of function of SMARCA4 (large deletion, truncating and canonical splice variants), while the remaining four were missense variants. Loss of heterozygosity of the wild-type SMARCA4 allele was found in all eight cases where somatic testing was performed, supporting the notion that SMARCA4 functions as a classic tumour suppressor. Altogether, these findings strongly suggest that NBL should be included in the spectrum of SMARCA4-associated tumours.

Analysis of hereditary cancer gene variant classifications from ClinVar indicates a need for regular reassessment of clinical assertions.

The clinical classification of variants may change with new information, however, there is limited guidance on how often significant changes in variant classification occur. We used ClinVar to examine how variant classification changes over time. We developed a custom parser and accessed variant data from ClinVar between January 2015 and July 2021. The ClinVar-assigned "aggregate" classification of variants in 121 hereditary cancer genes was harmonized across releases to align to the American College of Medical Genetics and Genomics and the Association for Molecular Pathology terms. Aggregate classification categories were grouped as: benign/likely benign (B/LB); likely pathogenic/pathogenic (LP/P); variant of uncertain significance (VUS); conflicting interpretations of pathogenicity (Conflicting); or Other. We profiled changes in aggregate variant classification between consecutive semi-annual ClinVar releases. The proportion of variants that changed aggregate classification between semi-annual ClinVar releases ranged from 0.6% to 6.4%. The most frequent changes were "VUS to conflicting," "other to LP/P," and "B/LB to Conflicting." A limited number of variants changed aggregate classification from "LP/P to B/LB," or vice versa. Our analysis indicates need for regular reassessment of clinical variant interpretations. The parser developed for this project will facilitate extraction of relevant interpretation data from ClinVar.

Comprehensive genomic and tumour immune profiling reveals potential therapeutic targets in malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials. METHODS: We analysed somatic mutations from 229 MPM samples, including previously published data and 58 samples that had undergone WGS within this study. This was combined with RNA-seq analysis to characterize the tumour immune environment. RESULTS: The comprehensive genome analysis identified 12 driver genes, including new candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed SBS5/40 were dominant in 93% of samples, and defects in homologous recombination repair were infrequent in our cohort. The tumour immune environment contained high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immune suppressive environment. The expression of TGFB1 was associated with overall survival. A small subset of samples (less than 10%) had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a 'hot' immune environment independent of the somatic mutations. CONCLUSIONS: We propose accounting for genomic and immune microenvironment status may influence therapeutic planning in the future.

Patient-derived xenograft models capture genomic heterogeneity in endometrial cancer.

BACKGROUND: Endometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprises four molecular subtypes with differing etiology, prognoses, and responses to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. As pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models. METHODS: Here, we report whole exome or whole genome sequencing of 11 PDX models and their matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC. RESULTS: PDX models were successfully generated from grade 2/3 tumors, including three uterine carcinosarcomas. The models showed similar histomorphology to the primary tumors and represented all four molecular subtypes of EC, including five mismatch-repair deficient models. The different PDX lineages showed a wide range of inter-tumor and intra-tumor heterogeneity. However, for most PDX models, one arm recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease; however, all lacked the HR deficiency genomic signature. CONCLUSIONS: EC PDX models represent the four molecular subtypes of disease and can capture intra-tumor heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi; however, deeper and more durable responses will likely require combination of PARPi with other agents.

The splicing effect of variants at branchpoint elements in cancer genes.

PURPOSE: Branchpoint elements are required for intron removal, and variants at these elements can result in aberrant splicing. We aimed to assess the value of branchpoint annotations generated from recent large-scale studies to select branchpoint-abrogating variants, using hereditary cancer genes as model. METHODS: We identified branchpoint elements in 119 genes associated with hereditary cancer from 3 genome-wide experimentally-inferred and 2 predicted branchpoint data sets. We then identified variants that occur within branchpoint elements from public databases. We compared conservation, unique variant observations, and population frequencies at different nucleotides within branchpoint motifs. Finally, selected minigene assays were performed to assess the splicing effect of variants at branchpoint elements within mismatch repair genes. RESULTS: There was poor overlap between predicted and experimentally-inferred branchpoints. Our analysis of cancer genes suggested that variants at -2 nucleotide, -1 nucleotide, and branchpoint positions in experimentally-inferred canonical motifs are more likely to be clinically relevant. Minigene assay data showed the -2 nucleotide to be more important to branchpoint motif integrity but also showed fluidity in branchpoint usage. CONCLUSION: Data from cancer gene analysis suggest that there are few high-risk alleles that severely impact function via branchpoint abrogation. Results of this study inform a general scheme to prioritize branchpoint motif variants for further study.

Considerations for using population frequency data in germline variant interpretation: Cancer syndrome genes as a model.

Aggregate population genomics data from large cohorts are vital for assessing germline variant pathogenicity. However, there are no specifications on how sequencing quality metrics should be considered, and whether exome-derived and genome-derived allele frequencies should be considered in isolation. Germline genome sequence data were simulated for nine read-depths to identify a minimum acceptable read-depth for detecting variants. gnomAD exome-derived and genome-derived datasets were assessed for read-depth, for six key cancer genes selected for variant curation by ClinGen expert panels. Non-Finnish European allele frequency (AF) or filter AF of coding variants in these genes, assigned into frequency bins using modified ACMG-AMP criteria, was compared between exome-derived and genome-derived datasets. A 30X read-depth achieved acceptable precision and recall for detection of substitutions, but poor recall for small insertions/deletions. Exome-derived and genome-derived datasets exhibited low read-depth for different gene exons. Individual variants were mostly assigned to non-divergent AF bins (>95%) or filter AF bins (>97%). Two major bin divergences were resolved by applying the minimal acceptable read-depth threshold. These findings show the importance of assessing read-depth separately for population datasets sourced from different short-read sequencing technologies before assigning a frequency-based ACMG-AMP classification code for variant interpretation.

Implementing gene curation for hereditary cancer susceptibility in Australia: achieving consensus on genes with clinical utility.

BACKGROUND: The strength of evidence supporting the validity of gene-disease relationships is variable. Hereditary cancer has the additional complexity of low or moderate penetrance for some confirmed disease-associated alleles. METHODS: To promote national consistency in interpretation of hereditary cancer/tumour gene test results, we requested opinions of representatives from Australian Family Cancer Clinics regarding the clinical utility of 157 genes initially collated for a national research project. Viewpoints were sought by initial survey, face-to-face workshop and follow-up survey. Subsequent review was undertaken by the eviQ Cancer Genetics Reference Committee, a national resource providing evidence-based and consensus-driven cancer treatment protocols. RESULTS: Genes were categorised by clinical actionability as: relevant for testing on presentation of common cancer/tumour types (n=45); relevant for testing in the context of specific rare phenotypes (n=74); insufficient clinical utility (n=34) or contentious clinical utility (n=3). Opinions for several genes altered during the study time frame, due to new information. CONCLUSION: Through an iterative process, consensus was achieved on genes with clinical utility for hereditary cancer/tumour conditions in the Australian setting. This study highlighted need for regular review of gene-disease lists, a role assumed in Australia for hereditary cancer/tumour predisposition genes by the eviQ Cancer Genetics Reference Committee.