Use of deep whole-genome sequencing data to identify structure risk variants in breast cancer susceptibility genes

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.

Contribution of large genomic rearrangements in PALB2 to familial breast cancer: implications for genetic testing

BACKGROUND

PALB2 is the most important contributor to familial breast cancer after BRCA1 and BRCA2. Large genomic rearrangements (LGRs) in BRCA1 and BRCA2 are routinely assessed in clinical testing and are a significant contributor to the yield of actionable findings. In contrast, the contribution of LGRs in PALB2 has not been systematically studied.

METHODS

We performed targeted sequencing and real-time qPCR validation to identify LGRs in PALB2 in 5770 unrelated patients with familial breast cancer and 5741 cancer-free control women from the same Australian population.

RESULTS

Seven large deletions ranging in size from 0.96 kbp to 18.07 kbp involving PALB2 were identified in seven cases, while no LGRs were identified in any of the controls. Six LGRs were considered pathogenic as they included one or more exons of PALB2 and disrupted the WD40 domain at the C terminal end of the PALB2 protein while one LGR only involved a partial region of intron 10 and was considered a variant of unknown significance. Altogether, pathogenic LGRs identified in this study accounted for 10.3% (6 of 58) of the pathogenic PALB2 variants detected among the 5770 families with familial breast cancer.

CONCLUSIONS

Our data show that a clinically important proportion of PALB2 pathogenic mutations in Australian patients with familial breast cancer are LGRs. Such observations have provided strong support for inclusion of PALB2 LGRs in routine clinical genetic testing.

Case Review: Whole-Exome Sequencing Analyses Identify Carriers of a Known Likely Pathogenic Intronic BRCA1 Variant in Ovarian Cancer Cases Clinically Negative for Pathogenic BRCA1 and BRCA2 Variants

Background: Detecting pathogenic intronic variants resulting in aberrant splicing remains a challenge in routine genetic testing. We describe germline whole-exome sequencing (WES) analyses and apply in silico predictive tools of familial ovarian cancer (OC) cases reported clinically negative for pathogenic BRCA1 and BRCA2 variants. Methods: WES data from 27 familial OC cases reported clinically negative for pathogenic BRCA1 and BRCA2 variants and 53 sporadic early-onset OC cases were analyzed for pathogenic variants in BRCA1 or BRCA2. WES data from carriers of pathogenic BRCA1 or BRCA2 variants were analyzed for pathogenic variants in 10 other OC predisposing genes. Loss of heterozygosity analysis was performed on tumor DNA from variant carriers. Results: BRCA1 c.5407-25T>A intronic variant, identified in two affected sisters and one sporadic OC case, is predicted to create a new splice effecting transcription of BRCA1. WES data from BRCA1 c.5407-25T>A carriers showed no evidence of pathogenic variants in other OC predisposing genes. Sequencing the tumor DNA from the variant carrier showed complete loss of the wild-type allele. Conclusions: The findings support BRCA1 c.5407-25T>A as a likely pathogenic variant and highlight the importance of investigating intronic sequences as causal variants in OC families where the involvement of BRCA1 is highly suggestive.

Distinct sequence features underlie microdeletions and gross deletions in the human genome

Microdeletions and gross deletions are important causes (~20%) of human inherited disease and their genomic locations are strongly influenced by the local DNA sequence environment. This notwithstanding, no study has systematically examined their underlying generative mechanisms. Here, we obtained 42,098 pathogenic microdeletions and gross deletions from the Human Gene Mutation Database (HGMD) that together form a continuum of germline deletions ranging in size from 1 to 28,394,429 bp. We analyzed the DNA sequence within 1 kb of the breakpoint junctions and found that the frequencies of non‐B DNA‐forming repeats, GC‐content, and the presence of seven of 78 specific sequence motifs in the vicinity of pathogenic deletions correlated with deletion length for deletions of length ≤30 bp. Further, we found that the presence of DR, GQ, and STR repeats is important for the formation of longer deletions (>30 bp) but not for the formation of shorter deletions (≤30 bp) while significantly (χ², p < 2E−16) more microhomologies were identified flanking short deletions than long deletions (length >30 bp). We provide evidence to support a functional distinction between microdeletions and gross deletions. Finally, we propose that a deletion length cut‐off of 25–30 bp may serve as an objective means to functionally distinguish microdeletions from gross deletions.

Discovery of structural deletions in breast cancer predisposition genes using whole genome sequencing data from > 2000 women of African-ancestry

Single germline nucleotide pathogenic variants have been identified in 12 breast cancer predisposition genes, but structural deletions in these genes remain poorly characterized. We conducted in-depth whole genome sequencing (WGS) in genomic DNA samples obtained from 1340 invasive breast cancer cases and 675 controls of African ancestry. We identified 25 deletions in the intragenic regions of ten established breast cancer predisposition genes based on a consensus call from six state-of-the-art SV callers. Overall, no significant case-control difference was found in the frequency of these deletions. However, 1.0% of cases and 0.3% of controls carried any of the eight putative protein-truncating rare deletions located in BRCA1, BRCA2, CDH1, TP53, NF1, RAD51D, RAD51C and CHEK2, resulting in an odds ratio (OR) of 3.29 (95% CI 0.74-30.16). We also identified a low-frequency deletion in NF1 associated with breast cancer risk (OR 1.93, 95% CI 1.14-3.42). In addition, we detected 56 deletions, including six putative protein-truncating deletions, in suspected breast predisposition genes. This is the first large study to systematically search for structural deletions in breast cancer predisposition genes. Many of the deletions, particularly those resulting in protein truncations, are likely to be pathogenic. Results from this study, if confirmed in future large-scale studies, could have significant implications for genetic testing for this common cancer.

Identifying Novel Susceptibility Genes for Colorectal Cancer Risk From a Transcriptome-Wide Association Study of 125,478 Subjects

BACKGROUND AND AIMS

Susceptibility genes and the underlying mechanisms for the majority of risk loci identified by genome-wide association studies (GWAS) for colorectal cancer (CRC) risk remain largely unknown. We conducted a transcriptome-wide association study (TWAS) to identify putative susceptibility genes.

METHODS

Gene-expression prediction models were built using transcriptome and genetic data from the 284 normal transverse colon tissues of European descendants from the Genotype-Tissue Expression (GTEx), and model performance was evaluated using data from The Cancer Genome Atlas (n = 355). We applied the gene-expression prediction models and GWAS data to evaluate associations of genetically predicted gene-expression with CRC risk in 58,131 CRC cases and 67,347 controls of European ancestry. Dual-luciferase reporter assays and knockdown experiments in CRC cells and tumor xenografts were conducted.

RESULTS

We identified 25 genes associated with CRC risk at a Bonferroni-corrected threshold of P < 9.1 × 10-6, including genes in 4 novel loci, PYGL (14q22.1), RPL28 (19q13.42), CAPN12 (19q13.2), MYH7B (20q11.22), and MAP1L3CA (20q11.22). In 9 known GWAS-identified loci, we uncovered 9 genes that have not been reported previously, whereas 4 genes remained statistically significant after adjusting for the lead risk variant of the locus. Through colocalization analysis in GWAS loci, we additionally identified 12 putative susceptibility genes that were supported by TWAS analysis at P < .01. We showed that risk allele of the lead risk variant rs1741640 affected the promoter activity of CABLES2. Knockdown experiments confirmed that CABLES2 plays a vital role in colorectal carcinogenesis.

CONCLUSIONS

Our study reveals new putative susceptibility genes and provides new insight into the biological mechanisms underlying CRC development.

Comprehensive assessments of germline deletion structural variants reveal the association between prognostic MUC4 and CEP72 deletions and immune response gene expression in colorectal cancer patients

Background

Functional disruptions by large germline genomic structural variants in susceptible genes are known risks for cancer. We used deletion structural variants (DSVs) generated from germline whole-genome sequencing (WGS) and DSV immune-related association tumor microenvironment (TME) to predict cancer risk and prognosis.

Methods

We investigated the contribution of germline DSVs to cancer susceptibility and prognosis by silicon and causal inference models. DSVs in germline WGS data were generated from the blood samples of 192 cancer and 499 non-cancer subjects. Clinical information, including family cancer history (FCH), was obtained from the National Cheng Kung University Hospital and Taiwan Biobank. Ninety-nine colorectal cancer (CRC) patients had immune response gene expression data. We used joint calling tools and an attention-weighted model to build the cancer risk predictive model and identify DSVs in familial cancer. The survival support vector machine (survival-SVM) was used to select prognostic DSVs.

Results

We identified 671 DSVs that could predict cancer risk. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) of the attention-weighted model was 0.71. The 3 most frequent DSV genes observed in cancer patients were identified as ADCY9, AURKAPS1, and RAB3GAP2 (p < 0.05). The DSVs in SGSM2 and LHFPL3 were relevant to colorectal cancer. We found a higher incidence of FCH in cancer patients than in non-cancer subjects (p < 0.05). SMYD3 and NKD2DSV genes were associated with cancer patients with FCH (p < 0.05). We identified 65 immune-associated DSV markers for assessing cancer prognosis (p < 0.05). The functional protein of MUC4 DSV gene interacted with MAGE1 expression, according to the STRING database. The causal inference model showed that deleting the CEP72 DSV gene affect the recurrence-free survival (RFS) of IFIT1 expression.

Conclusions

We established an explainable attention-weighted model for cancer risk prediction and used the survival-SVM for prognostic stratification by using germline DSVs and immune gene expression datasets. Comprehensive assessments of germline DSVs can predict the cancer risk and clinical outcome of colon cancer patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-020-00302-3.

A Systematic Literature Review of Whole Exome and Genome Sequencing Population Studies of Genetic Susceptibility to Cancer

The application of next-generation sequencing (NGS) technologies in cancer research has accelerated the discovery of somatic mutations; however, progress in the identification of germline variation associated with cancer risk is less clear. We conducted a systematic literature review of cancer genetic susceptibility studies that used NGS technologies at an exome/genome-wide scale to obtain a fuller understanding of the research landscape to date and to inform future studies. The variability across studies on methodologies and reporting was considerable. Most studies sequenced few high-risk (mainly European) families, used a candidate analysis approach, and identified potential cancer-related germline variants or genes in a small fraction of the sequenced cancer cases. This review highlights the importance of establishing consensus on standards for the application and reporting of variants filtering strategies. It also describes the progress in the identification of cancer-related germline variation to date. These findings point to the untapped potential in conducting studies with appropriately sized and racially diverse families and populations, combining results across studies and expanding beyond a candidate analysis approach to advance the discovery of genetic variation that accounts for the unexplained cancer heritability.

Evaluation of pathogenetic mutations in breast cancer predisposition genes in population-based studies conducted among Chinese women

Purpose

Limited studies have been conducted to evaluate pathogenetic mutations in breast cancer predisposition genes among Chinese women. To fully characterize germline mutations of these genes in this population, we used the whole-exome sequencing data in a population-based case–control study conducted in Shanghai, China.

Methods

We evaluated exonic, splicing, and copy number variants in 11 established and 14 candidate breast cancer predisposition genes in 831 invasive breast cancer cases and 839 controls. We identified 55 pathogenic variants, including 15 newly identified in this study.

Results

Approximately 8% of the cases and 0.6% of the cancer-free controls carried these pathogenetic variants (P = 3.05 × 10⁻¹⁵). Among cases, 3.7% had a BRCA2 pathogenic variant and 1.6% had a BRCA1 pathogenic variant, while 2.5% had a pathogenic variant in other genes including ATM, CHEK2, NBN, NF1, CDH1, PALB2, PTEN, TP53 as well as BARD1, BRIP, and RAD51D. Patients with BRCA1/2 pathogenic variants were more likely to have a family history of breast cancer and hormone receptor negative tumors compared with patients without pathogenic variants.

Conclusions

This study highlighted the importance of hereditary breast cancer genes in the breast cancer etiology in this understudied population. Together with previous studies in East Asian women, this study suggested a relatively more prominent role of BRCA2 compared to BRCA1. This study also provides additional evidence to design cost-efficient genetic testing among Chinese women for risk assessment and early detection of breast cancer.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05643-0) contains supplementary material, which is available to authorized users.

Integrative genomic analyses of APOBEC-mutational signature, expression and germline deletion of APOBEC3 genes, and immunogenicity in multiple cancer types

BACKGROUND

Although APOBEC-mutational signature is found in tumor tissues of multiple cancers, how a common germline APOBEC3A/B deletion affects the mutational signature remains unclear.

METHODS

Using data from 10 cancer types generated as part of TCGA, we performed integrative genomic and association analyses to assess inter-relationship of expressions for isoforms APOBEC3A and APOBEC3B, APOBEC-mutational signature, germline APOBEC3A/B deletions, neoantigen loads, and tumor infiltration lymphocytes (TILs).

RESULTS

We found that expression level of the isoform uc011aoc transcribed from the APOBEC3A/B chimera was associated with a greater burden of APOBEC-mutational signature only in breast cancer, while germline APOBEC3A/B deletion led to an increased expression level of uc011aoc in multiple cancer types. Furthermore, we found that the deletion was associated with elevated APOBEC-mutational signature, neoantigen loads and relative composition of T cells (CD8+) in TILs only in breast cancer. Additionally, we also found that APOBEC-mutational signature significantly contributed to neoantigen loads and certain immune cell abundances in TILs across cancer types.

CONCLUSIONS

These findings reveal new insights into understanding the genetic, biological and immunological mechanisms through which APOBEC genes may be involved in carcinogenesis, and provide potential genetic biomarker for the development of disease prevention and cancer immunotherapy.

Identification of intermediate-sized deletions and inference of their impact on gene expression in a human population

Background

Next-generation sequencing has allowed for the identification of different genetic variations, which are known to contribute to diseases. Of these, insertions and deletions are the second most abundant type of variations in the genome, but their biological importance or disease association is not well-studied, especially for deletions of intermediate sizes.

Methods

We identified intermediate-sized deletions from whole-genome sequencing (WGS) data of Japanese samples (n = 174) with a novel deletion calling method which considered multiple samples. These deletions were used to construct a reference panel for use in imputation. Imputation was then conducted using the reference panel and data from 82 publically available Japanese samples with gene expression data. The accuracy of the deletion calling and imputation was examined with Nanopore long-read sequencing technology. We also conducted an expression quantitative trait loci (eQTL) association analysis using the deletions to infer their functional impacts on genes, before characterizing the deletions causal for gene expression level changes.

Results

We obtained a set of polymorphic 4378 high-confidence deletions and constructed a reference panel. The deletions were successfully imputed into the Japanese samples with high accuracy (97.3%). The eQTL analysis identified 181 deletions (4.1%) suggested as causal for gene expression level changes. The causal deletion candidates were significantly enriched in promoters, super-enhancers, and transcription elongation chromatin states. Generation of deletions in a cell line with the CRISPR-Cas9 system confirmed that they were indeed causative variants for gene expression change. Furthermore, one of the deletions was observed to affect the gene expression levels of a gene it was not located in.

Conclusions

This paper reports an accurate deletion calling method for genotype imputation at the whole genome level and shows the importance of intermediate-sized deletions in the human population.

Electronic supplementary material

The online version of this article (10.1186/s13073-019-0656-4) contains supplementary material, which is available to authorized users.

Discovery of a Pathogenic Variant rs139379666 (p. P2974L) in ATM for Breast Cancer Risk in Chinese Populations

BACKGROUND

Pathogenic variants in susceptibility genes lead to increased breast cancer risk.

METHODS

To identify coding variants associated with breast cancer risk, we conducted whole-exome sequencing in genomic DNA samples from 831 breast cancer cases and 839 controls of Chinese women. We also genotyped samples, including 4,580 breast cancer cases and 6,695 controls, using whole exome-chip arrays. We further performed a replication study using a Multi-Ethnic Global Array in samples from 1,793 breast cases and 2,059 controls. A single marker analysis was performed using the Fisher exact test.

RESULTS

We identified a missense variant (rs139379666, P2974L; AF = 0.09% for breast cancer cases, but none for controls) in the ATM gene for breast cancer risk using combing data from 7,204 breast cancer cases and 9,593 controls (P = 1.7 × 10^-5). To investigate the functionality of the variant, we first silenced ATM and then transfected the overexpression vectors of ATM containing the risk alleles (TT) or reference alleles (CC) of the variant in U2OS and breast cancer SK-BR3 cells, respectively. Our results showed that compared with the reference allele, the risk allele significantly disrupts the activity of homologous recombination-mediated double-strand breaks repair efficiency. Our results further showed that the risk allele may play a defected regulation role in the activity of the ATM structure.

CONCLUSIONS

Our findings identified a novel mutation that disrupts ATM function, conferring to breast cancer risk.

IMPACT

Functional investigation of genetic association findings is necessary to discover a pathogenic variant for breast cancer risk.

Germline Genetic Testing: What the Breast Surgeon Needs to Know

PURPOSE

The American Society of Breast Surgeons (ASBrS) sought to provide educational guidelines for breast surgeons on how to incorporate genetic information and genomics into their practice.

METHODS

A comprehensive nonsystematic review was performed of selected peer-reviewed literature. The Genetics Working Group of the ASBrS convened to develop guideline recommendations.

RESULTS

Clinical and educational guidelines were prepared to outline the essential knowledge for breast surgeons to perform germline genetic testing and to incorporate the findings into their practice, which have been approved by the ASBrS Board of Directors.

RECOMMENDATIONS

Thousands of women in the USA would potentially benefit from genetic testing for BRCA1, BRCA2, and other breast cancer genes that markedly increase their risk of developing breast cancer. As genetic testing is now becoming more widely available, women should be made aware of these tests and consider testing. Breast surgeons are well positioned to help facilitate this process. The areas where surgeons need to be knowledgeable include: (1) identification of patients for initial breast cancer-related genetic testing, (2) identification of patients who tested negative in the past but now need updated testing, (3) initial cancer genetic testing, (4) retesting of patients who need their genetic testing updated, (5) cancer genetic test interpretation, posttest counseling and management, (6) management of variants of uncertain significance, (7) cascade genetic testing, (8) interpretation of genetic tests other than clinical cancer panels and the counseling and management required, and (9) interpretation of somatic genetic tests and the counseling and management required.

Dynamic genome and transcriptional network-based biomarkers and drugs: precision in breast cancer therapy

Despite remarkable progress in medium-term overall survival benefit in the adjuvant, neoadjuvant and metastatic settings, with multiple recent targeted drug approvals, acquired resistance, late relapse, and cancer-related death rates remain challenging. Integrated technological systems have been developed to overcome these unmet needs. The characterization of structural and functional noncoding genome elements through next-generation sequencing (NGS) systems, Hi-C and CRISPR/Cas9, as well as computational models, allows for whole genome and transcriptome analysis. Rapid progress in large-scale single-biopsy genome analysis has identified several novel breast cancer driver genes and oncotargets. The exploration of spatiotemporal tumor evolution has returned exciting while inconclusive data on dynamic intratumor heterogeneity (ITH) through multiregional NGS and single-cell DNA/RNA sequencing and circulating genomic subclones (cGSs) by serial circulating cell-free DNA NGS to predict and overcome intrinsic and acquired therapeutic resistance. This review discusses reliable breast cancer genome analysis data and focuses on two major crucial perspectives. The validation of ITH, cGSs, and intrapatient genetic/genomic heterogeneity as predictive biomarkers, as well as the valid discovery of novel oncotargets within patient-centric genomic trials, encouraging early drug development, could optimize primary and secondary therapeutic decision-making. A longer-term goal is to identify the individualized landscape of both coding and noncoding key mutations. This progress will enable the understanding of molecular mechanisms perturbating regulatory networks, shaping the pharmaceutical controllability of deregulated transcriptional biocircuits.

Genetics of breast cancer in African populations: a literature review

Breast cancer (BC) is one of the most complex, diverse and leading cause of death in women worldwide. The present investigation aims to explore genes panel associated with BC in different African regions, and compare them to those studied worldwide.

We extracted relevant information from 43 studies performed in Africa using the following criteria: case-control study, association between genetic variations and BC risk. Data were provided on mutations and polymorphisms associated with BC without fixing a specific date. Case-only studies and clinical trials were excluded.

Our study revealed that the majority of African BC genetic studies remain restricted to the investigation of BRCA1 and BRCA2 genes and differences in their mutations spectrum. Therefore, it is necessary to encourage African researchers to characterize more genes involved in BC using methods generating global information such as next-generation sequencing in order to guide specific and more effective therapeutic strategies for the African community.