Evaluating the breast cancer predisposition role of rare variants in genes associated with low-penetrance breast cancer risk SNPs

DMOIT: denoised multi-omics integration approach based on transformer multi-head self-attention mechanism

Multi-omics data integration has become increasingly crucial for a deeper understanding of the complexity of biological systems. However, effectively integrating and analyzing multi-omics data remains challenging due to their heterogeneity and high dimensionality. Existing methods often struggle with noise, redundant features, and the complex interactions between different omics layers, leading to suboptimal performance. Additionally, they face difficulties in adequately capturing intra-omics interactions due to simplistic concatenation techiniques, and they risk losing critical inter-omics interaction information when using hierarchical attention layers. To address these challenges, we propose a novel Denoised Multi-Omics Integration approach that leverages the Transformer multi-head self-attention mechanism (DMOIT). DMOIT consists of three key modules: a generative adversarial imputation network for handling missing values, a sampling-based robust feature selection module to reduce noise and redundant features, and a multi-head self-attention (MHSA) based feature extractor with a noval architecture that enchance the intra-omics interaction capture. We validated model porformance using cancer datasets from the Cancer Genome Atlas (TCGA), conducting two tasks: survival time classification across different cancer types and estrogen receptor status classification for breast cancer. Our results show that DMOIT outperforms traditional machine learning methods and the state-of-the-art integration method MoGCN in terms of accuracy and weighted F1 score. Furthermore, we compared DMOIT with various alternative MHSA-based architectures to further validate our approach. Our results show that DMOIT consistently outperforms these models across various cancer types and different omics combinations. The strong performance and robustness of DMOIT demonstrate its potential as a valuable tool for integrating multi-omics data across various applications.

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

Disease risk prediction based on genomic sequence and transcriptional profile can improve disease screening and prevention. Despite identifying many disease-associated DNA variants, distinguishing deleterious non-coding DNA variations remains poor for most common diseases. In this study, we designed in vitro experiments to uncover the significance of occupancy and competitive binding between P53 and cMYC on common target genes. Analyzing publicly available ChIP-seq data for P53 and cMYC in embryonic stem cells showed that ~344-366 regions are co-occupied, and on average, two cis-overlapping motifs (CisOMs) per region were identified, suggesting that co-occupancy is evolutionarily conserved. Using U2OS and Raji cells untreated and treated with doxorubicin to increase P53 protein level while potentially reducing cMYC level, ChIP-seq analysis illustrated that around 16 to 922 genomic regions were co-occupied by P53 and cMYC, and substitutions of cMYC signals by P53 were detected post doxorubicin treatment. Around 187 expressed genes near co-occupied regions were altered at mRNA level according to RNA-seq data analysis. We utilized a computational motif-matching approach to illustrate that changes in predicted P53 binding affinity in CisOMs of co-occupied elements significantly correlate with alterations in reporter gene expression. We performed a similar analysis using SNPs mapped in CisOMs for P53 and cMYC from ChIP-seq data, and expression of target genes from GTEx portal. We found significant correlation between change in cMYC-motif binding affinity in CisOMs and altered expression. Our study brings us closer to developing a generally applicable approach to filter etiological non-coding variations associated with common diseases.

Metabolites Associated with Polygenic Risk of Breast Cancer

While hundreds of germline genetic variants have been associated with breast cancer risk, the mechanisms underlying the impacts of most of these variants on breast cancer remain uncertain. Metabolomics may offer valuable insights into the mechanisms underlying genetic risks of breast cancer. Among 143 cancer-free female participants, we used linear regression analyses to explore associations between the genetic risk of breast cancer, as determined by a previously developed polygenic risk score (PRS) that included 266 single-nucleotide polymorphisms (SNPs), and 223 measures of metabolites obtained from blood samples using nuclear magnetic resonance (NMR). A false discovery rate of 10% was applied to account for multiple comparisons. PRS was statistically significantly associated with 45 metabolite measures. These were primarily measures of very low-density lipoproteins (VLDLs) and high-density lipoproteins (HDLs), including triglycerides, cholesterol, and phospholipids. For example, the strongest effect was observed with the percent ratio of medium VLDL triglycerides to total lipids (0.53 unit increase in mean-standardized ln-transformed percent ratio per unit increase in PRS; q = 0.1). While larger-scale studies are needed to confirm these results, this exploratory study presents biologically plausible findings that are consistent with previously reported associations between lipids and breast cancer risk. If confirmed, these lipids could be targeted for lifestyle and pharmaceutical interventions among women at increased genetic risk of breast cancer.

TET Enzymes and 5hmC Levels in Carcinogenesis and Progression of Breast Cancer: Potential Therapeutic Targets

Breast Cancer (BC) was the most common female cancer in incidence and mortality worldwide in 2020. Similarly, BC was the top female cancer in the USA in 2022. Risk factors include earlier age at menarche, oral contraceptive use, hormone replacement therapy, high body mass index, and mutations in BRCA1/2 genes, among others. BC is classified into Luminal A, Luminal B, HER2-like, and Basal-like subtypes. These BC subtypes present differences in gene expression signatures, which can impact clinical behavior, treatment response, aggressiveness, metastasis, and survival of patients. Therefore, it is necessary to understand the epigenetic molecular mechanism of transcriptional regulation in BC, such as DNA demethylation. Ten-Eleven Translocation (TET) enzymes catalyze the oxidation of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) on DNA, which in turn inhibits or promotes the gene expression. Interestingly, the expression of TET enzymes as well as the levels of the 5hmC epigenetic mark are altered in several types of human cancers, including BC. Several studies have demonstrated that TET enzymes and 5hmC play a key role in the regulation of gene expression in BC, directly (dependent or independent of DNA de-methylation) or indirectly (via interaction with other proteins such as transcription factors). In this review, we describe our recent understanding of the regulatory and physiological function of the TET enzymes, as well as their potential role as biomarkers in BC biology.

Refining the genetic risk of breast cancer with rare haplotypes and pattern mining

Hundreds of common variants have been found to confer small but significant differences in breast cancer risk, supporting the widely accepted polygenic model of inherited predisposition. Using a novel closed-pattern mining algorithm, we provide evidence that rare haplotypes may refine the association of breast cancer risk with common germline alleles. Our method, called Chromosome Overlap, consists in iteratively pairing chromosomes from affected individuals and looking for noncontiguous patterns of shared alleles. We applied Chromosome Overlap to haplotypes of genotyped SNPs from female breast cancer cases from the UK Biobank at four loci containing common breast cancer-risk SNPs. We found two rare (frequency <0.1%) haplotypes bearing a GWAS hit at 11q13 (hazard ratio = 4.21 and 16.7) which replicated in an independent, European ancestry population at P < 0.05, and another at 22q12 (frequency <0.2%, hazard ratio = 2.58) which expanded the risk pool to noncarriers of a GWAS hit. These results suggest that rare haplotypes (or mutations) may underlie the "synthetic association" of breast cancer risk with at least some common variants.

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

Background and methods

Disease risk prediction based on DNA sequence and transcriptional profile can improve disease screening, prevention, and potential therapeutic approaches by revealing contributing genetic factors and altered regulatory networks. Despite identifying many disease-associated DNA variants through genome-wide association studies, distinguishing deleterious non-coding DNA variations remains poor for most common diseases. We previously reported that non-coding variations disrupting cis-overlapping motifs (CisOMs) of opposing transcription factors significantly affect enhancer activity. We designed in vitro experiments to uncover the significance of the co-occupancy and competitive binding and inhibition between P53 and cMYC on common target gene expression.

Results

Analyzing publicly available ChIP-seq data for P53 and cMYC in human embryonic stem cells and mouse embryonic cells showed that ~ 344-366 genomic regions are co-occupied by P53 and cMYC. We identified, on average, two CisOMs per region, suggesting that co-occupancy is evolutionarily conserved in vertebrates. Our data showed that treating U2OS cells with doxorubicin increased P53 protein level while reducing cMYC level. In contrast, no change in protein levels was observed in Raji cells. ChIP-seq analysis illustrated that 16-922 genomic regions were co-occupied by P53 and cMYC before and after treatment, and substitutions of cMYC signals by P53 were detected after doxorubicin treatment in U2OS. Around 187 expressed genes near co-occupied regions were altered at mRNA level according to RNA-seq data. We utilized a computational motif-matching approach to determine that changes in predicted P53 binding affinity by DNA variations in CisOMs of co-occupied elements significantly correlate with alterations in reporter gene expression. We performed a similar analysis using SNPs mapped in CisOMs for P53 and cMYC from ChIP-seq data in U2OS and Raji, and expression of target genes from the GTEx portal.

Conclusions

We found a significant correlation between change in motif-predicted cMYC binding affinity by SNPs in CisOMs and altered gene expression. Our study brings us closer to developing a generally applicable approach to filter etiological non-coding variations associated with P53 and cMYC-dependent diseases.

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.

The Association Between Breast Cancer and Blood-Based Methylation of CD160, ISYNA1 and RAD51B in the Chinese Population

Recent studies have identified DNA methylation signatures in the white blood cells as potential biomarkers for breast cancer (BC) in the European population. Here, we investigated the association between BC and blood-based methylation of cluster of differentiation 160 (CD160), inositol-3-phosphate synthase 1 (ISYNA1) and RAD51 paralog B (RAD51B) genes in the Chinese population. Peripheral blood samples were collected from two independent case-control studies with a total of 272 sporadic early-stage BC cases (76.5% at stage I&amp;II) and 272 cancer-free female controls. Mass spectrometry was applied to quantitatively measure the levels of DNA methylation. The logistic regression and non-parametric tests were used for the statistical analyses. In contrast to the protective effects reported in European women, we reported the blood-based hypomethylation in CD160, ISYNA1 and RAD51B as risk factors for BC in the Chinese population (CD160_CpG_3, CD160_CpG_4/cg20975414, ISYNA1_CpG_2, RAD51B_CpG_3 and RAD51B_CpG_4; odds ratios (ORs) per -10% methylation ranging from 1.08 to 1.67, p &lt; 0.05 for all). Moreover, hypomethylation of CD160, ISYNA1 and RAD51B was significantly correlated with age, BC subtypes including estrogen receptor (ER)-negative BC tumors, triple negative tumors, BC cases with larger size, advanced stages and more lymph node involvement. Our results supported the report in European women that BC is associated with altered methylation of CD160, ISYNA1 and RAD51B in the peripheral blood, although the effects are opposite in the Chinese population. The difference between the two populations may be due to variant genetic background or life styles, implicating that the validations of epigenetic biomarkers in variant ethnic groups are warranted.

Dysregulated TET Family Genes and Aberrant 5mC Oxidation in Breast Cancer: Causes and Consequences

Simple Summary

Both genetic and epigenetic mechanisms contribute to the pathogenesis of breast cancer. Since Tahiliani et al. identified TET1 as the first methyl-cytosine dioxygenase in 2009, accumulating evidence has shown that aberrant 5mC oxidation and dysregulated TET family genes are associated with diseases, including breast cancer. In this review we provide an overview on the diagnosis and prognosis values of aberrant 5mC oxidation in breast cancer and emphasize the causes and consequences of such epigenetic alterations.

Abstract

DNA methylation (5-methylcytosine, 5mC) was once viewed as a stable epigenetic modification until Rao and colleagues identified Ten-eleven translocation 1 (TET1) as the first 5mC dioxygenase in 2009. TET family genes (including TET1, TET2, and TET3) encode proteins that can catalyze 5mC oxidation and consequently modulate DNA methylation, not only regulating embryonic development and cellular differentiation, but also playing critical roles in various physiological and pathophysiological processes. Soon after the discovery of TET family 5mC dioxygenases, aberrant 5mC oxidation and dysregulation of TET family genes have been reported in breast cancer as well as other malignancies. The impacts of aberrant 5mC oxidation and dysregulated TET family genes on the different aspects (so-called cancer hallmarks) of breast cancer have also been extensively investigated in the past decade. In this review, we summarize current understanding of the causes and consequences of aberrant 5mC oxidation in the pathogenesis of breast cancer. The challenges and future perspectives of this field are also discussed.

Identification of Novel CircRNA-miRNA-mRNA Regulatory Network and Its Prognostic Prediction in Breast Cancer

Aim

This study aimed to investigate the expression profiles of circRNAs and candidate circRNA-miRNA-mRNA network in BC.

Methods

Differentially expressed circRNAs, miRNAs, and mRNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) between BC and normal breast tissue samples were screened by analyzing raw data of the RNA sequencing profile. The expression levels of hub genes in 48 pairs of cancerous and tumor-free breast tissues surgically resected from BC patients were determined by RT-qPCR analysis.

Results

A total of 145 DEcircRNAs, 140 DEmiRNAs, and 2451 DEmRNAs between BC and normal breast tissue samples were screened out. There were 5 pairs of upcircRNA-downmiRNA-upmRNA network and 20 pairs of downcircRNA-upmiRNA-downmRNA network. EIF4EBP1, DUSP1, EGR2, EZH1, and CBX7 were found to be correlated with overall survival of the patients with BC. The expression level of EIF4EBP1 was increased and the expression levels of DUSP1, EGR2, EZH1, and CBX7 were decreased in cancerous breast tissues compared to tumor-free breast tissues (p < 0.0001). The RT-qPCR results from 48 BC patients were consistent with the bioinformatics results.

Conclusion

This study provides a novel perspective to study circRNA-miRNA-mRNA network in BC and assists in the identification of new potential biomarkers to be used for diagnostic and prognostic purposes.

Prevalence and Clinicopathological Characteristics of Moderate and High-Penetrance Genes in Non-BRCA1/2 Breast Cancer High-Risk Spanish Families

(1) Background: Over the last decade, genetic counseling clinics have moved from single-gene sequencing to multigene panel sequencing. Multiple genes related to a moderate risk of breast cancer (BC) have emerged, although many questions remain regarding the risks and clinical features associated with these genes. (2) Methods: Ninety-six BC index cases (ICs) with high-risk features for hereditary breast and ovarian cancer (HBOC) and with a previous uninformative result for BRCA1/2 were tested with a panel of 41 genes associated with BC risk. The frequency of pathogenic variants (PVs) was related to the clinical characteristics of BC. (3) Results: We detected a PV rate of 13.5% (excluding two cases each of BRCA1 and MUTYH). Among the 95 assessed cases, 17 PVs were identified in 16 ICs, as follows: BRCA1 (n = 2), CHEK2 (n = 3), ATM (n = 5), MUTYH (n = 2), TP53 (n = 2), BRIP1 (n = 1), CASP8 (n = 1), and MSH2 (n = 1). We also identified a novel loss-of-function variant in CASP8, a candidate gene for increased BC risk. There was no evidence that the clinical characteristics of BC might be related to a higher chance of identifying a PV. (4) Conclusions: In our cohort, which was enriched with families with a high number of BC cases, a high proportion of mutations in ATM and CHEK2 were identified. The clinical characteristics of BC associated with moderate-risk genes were different from those related to BRCA1/2 genes.

Evaluation of the association of heterozygous germline variants in NTHL1 with breast cancer predisposition: an international multi-center study of 47,180 subjects

Bi-allelic loss-of-function (LoF) variants in the base excision repair (BER) gene NTHL1 cause a high-risk hereditary multi-tumor syndrome that includes breast cancer, but the contribution of heterozygous variants to hereditary breast cancer is unknown. An analysis of 4985 women with breast cancer, enriched for familial features, and 4786 cancer-free women revealed significant enrichment for NTHL1 LoF variants. Immunohistochemistry confirmed reduced NTHL1 expression in tumors from heterozygous carriers but the NTHL1 bi-allelic loss characteristic mutational signature (SBS 30) was not present. The analysis was extended to 27,421 breast cancer cases and 19,759 controls from 10 international studies revealing 138 cases and 93 controls with a heterozygous LoF variant (OR 1.06, 95% CI: 0.82-1.39) and 316 cases and 179 controls with a missense variant (OR 1.31, 95% CI: 1.09-1.57). Missense variants selected for deleterious features by a number of in silico bioinformatic prediction tools or located within the endonuclease III functional domain showed a stronger association with breast cancer. Somatic sequencing of breast cancers from carriers indicated that the risk associated with NTHL1 appears to operate through haploinsufficiency, consistent with other described low-penetrance breast cancer genes. Data from this very large international multicenter study suggests that heterozygous pathogenic germline coding variants in NTHL1 may be associated with low- to moderate- increased risk of breast cancer.

Genomic analysis of low-grade serous ovarian carcinoma to identify key drivers and therapeutic vulnerabilities

Low-grade serous ovarian carcinoma (LGSOC) is associated with a poor response to existing chemotherapy, highlighting the need to perform comprehensive genomic analysis and identify new therapeutic vulnerabilities. The data presented here represent the largest genetic study of LGSOCs to date (n = 71), analysing 127 candidate genes derived from whole exome sequencing cohorts to generate mutation and copy-number variation data. Additionally, immunohistochemistry was performed on our LGSOC cohort assessing oestrogen receptor, progesterone receptor, TP53, and CDKN2A status. Targeted sequencing identified 47% of cases with mutations in key RAS/RAF pathway genes (KRAS, BRAF, and NRAS), as well as mutations in putative novel driver genes including USP9X (27%), MACF1 (11%), ARID1A (9%), NF2 (4%), DOT1L (6%), and ASH1L (4%). Immunohistochemistry evaluation revealed frequent oestrogen/progesterone receptor positivity (85%), along with CDKN2A protein loss (10%) and CDKN2A protein overexpression (6%), which were linked to shorter disease outcomes. Indeed, 90% of LGSOC samples harboured at least one potentially actionable alteration, which in 19/71 (27%) cases were predictive of clinical benefit from a standard treatment, either in another cancer's indication or in LGSOC specifically. In addition, we validated ubiquitin-specific protease 9X (USP9X), which is a chromosome X-linked substrate-specific deubiquitinase and tumour suppressor, as a relevant therapeutic target for LGSOC. Our comprehensive genomic study highlighted that there is an addiction to a limited number of unique 'driver' aberrations that could be translated into improved therapeutic paths. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The TP53 mutation rate differs in breast cancers that arise in women with high or low mammographic density

Mammographic density (MD) influences breast cancer risk, but how this is mediated is unknown. Molecular differences between breast cancers arising in the context of the lowest and highest quintiles of mammographic density may identify the mechanism through which MD drives breast cancer development. Women diagnosed with invasive or in situ breast cancer where MD measurement was also available (n = 842) were identified from the Lifepool cohort of >54,000 women participating in population-based mammographic screening. This group included 142 carcinomas in the lowest quintile of MD and 119 carcinomas in the highest quintile. Clinico-pathological and family history information were recorded. Tumor DNA was collected where available (n = 56) and sequenced for breast cancer predisposition and driver gene mutations, including copy number alterations. Compared to carcinomas from low-MD breasts, those from high-MD breasts were significantly associated with a younger age at diagnosis and features associated with poor prognosis. Low- and high-MD carcinomas matched for grade, histological subtype, and hormone receptor status were compared for somatic genetic features. Low-MD carcinomas had a significantly increased frequency of TP53 mutations, higher homologous recombination deficiency, higher fraction of the genome altered, and more copy number gains on chromosome 1q and losses on 17p. While high-MD carcinomas showed enrichment of tumor-infiltrating lymphocytes in the stroma. The data demonstrate that when tumors were matched for confounding clinico-pathological features, a proportion in the lowest quintile of MD appear biologically distinct, reflective of microenvironment differences between the lowest and highest quintiles of MD.

Combined Tumor Sequencing and Case-Control Analyses of RAD51C in Breast Cancer

BACKGROUND

Loss-of-function variants in RAD51C are associated with familial ovarian cancer, but its role in hereditary breast cancer remains unclear. The aim of this study was to couple breast tumor sequencing with case-control data to clarify the contribution of RAD51C to hereditary breast cancer.

METHODS

RAD51C was sequenced in 3080 breast cancer index cases that were negative in BRCA1/2 clinical tests and 4840 population-matched cancer-free controls. Pedigree and pathology data were analyzed. Nine breast cancers and one ovarian cancer from RAD51C variant carriers were sequenced to identify biallelic inactivation of RAD51C, copy number variation, mutational signatures, and the spectrum of somatic mutations in breast cancer driver genes. The promoter of RAD51C was analyzed for DNA methylation.

RESULTS

A statistically significant excess of loss-of-function variants was identified in 3080 cases (0.4%) compared with 2 among 4840 controls (0.04%; odds ratio = 8.67, 95% confidence interval = 1.89 to 80.52, P< .001), with more than half of the carriers having no personal or family history of ovarian cancer. In addition, the association was highly statistically significant among cases with estrogen-negative (P <. 001) or triple-negative cancer (P < .001), but not in estrogen-positive cases. Tumor sequencing from carriers confirmed bi-allelic inactivation in all the triple-negative cases and was associated with high homologous recombination deficiency scores and mutational signature 3 indicating homologous recombination repair deficiency.

CONCLUSIONS

This study provides evidence that germline loss-of-function variants of RAD51C are associated with hereditary breast cancer, particularly triple-negative type. RAD51C-null breast cancers possess similar genomic and clinical features to BRCA1-null cancers and may also be vulnerable to DNA double-strand break inducing chemotherapies and poly ADP-ribose polymerase inhibitors.

Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field

Polygenic factors are estimated to account for an additional 18% of the familial relative risk of breast cancer, with those at the highest level of polygenic risk distribution having a least a twofold increased risk of the disease. Polygenic testing promises to revolutionize health services by providing personalized risk assessments to women at high-risk of breast cancer and within population breast screening programs. However, implementation of polygenic testing needs to be considered in light of its current limitations, such as limited risk prediction for women of non-European ancestry. This article aims to provide a comprehensive review of the evidence for polygenic breast cancer risk, including the discovery of variants associated with breast cancer at the genome-wide level of significance and the use of polygenic risk scores to estimate breast cancer risk. We also review the different applications of this technology including testing of women from high-risk breast cancer families with uninformative genetic testing results, as a moderator of monogenic risk, and for population screening programs. Finally, a potential framework for introducing testing for polygenic risk in familial cancer clinics and the potential challenges with implementing this technology in clinical practice are discussed.

A Frameshift Variant in the CHST9 Gene Identified by Family-Based Whole Genome Sequencing Is Associated with Schizophrenia in Chinese Population

Recent studies imply that rare variants contribute to the risk of schizophrenia, however, the exact variants or genes responsible for this condition are largely unknown. In this study, we conducted whole genome sequencing (WGS) of 20 Chinese families. Each family consisted of at least two affected siblings diagnosed with schizophrenia and at least one unaffected sibling. We examined functional variants that were found in affected sibling(s) but not in unaffected sibling(s) within a family. Matching this criterion, a frameshift heterozygous deletion of CA (–/CA) at chromosome 18:24722722, also referred to as rs752084147, in the Carbohydrate Sulfotransferase 9 (CHST9) gene, was detected in two families. This deletion was confirmed by PCR-based Sanger sequencing. With the observed frequency of 0.00076 in Han Chinese population, we performed both case-control and family-based analyses to evaluate its association with schizophrenia. In the case-control analyses, Chi-square test P-value was 6.80e-12 and the P-value was 0.0008 after one million simulations. In family-based segregation analyses, segregation P-value was 7.72e-7 and simulated P-value was 5.70e-6. For both the case-control and family-based analyses, the CA deletion was significantly associated with schizophrenia in the Chinese population. Further investigation of this gene  is warranted in the development of schizophrenia by utilizing larger and more ethnically diverse samples.

Molecular comparison of interval and screen-detected breast cancers

Breast cancer (BC) diagnosed after a negative mammogram but prior to the next screening episode is termed an 'interval BC' (IBC). Understanding the molecular differences between IBC and screen-detected BCs (SDBC) could improve mammographic screening and management options. Therefore, we assessed both germline and somatic genomic aberrations in a prospective cohort. Utilising the Lifepool cohort of >54 000 women attending mammographic screening programs, 930 BC cases with screening status were identified (726 SDBC and 204 IBC). Clinico-pathological and family history information were recorded. Germline and tumour DNA were collected where available and sequenced for BC predisposition and driver gene mutations. Compared to SDBC, IBCs were significantly associated with a younger age at diagnosis and tumour characteristics associated with worse prognosis. Germline DNA assessment of BC cases that developed post-enrolment (276 SDBCs and 77 IBCs) for pathogenic mutations in 12 hereditary BC predisposition genes identified 8 carriers (2.27%). The germline mutation frequency was higher in IBC versus SDBC, although not statistically significant (3.90% versus 1.81%, p = 0.174). Comparing somatic genetic features of IBC and SDBC matched for grade, histological subtype and hormone receptor revealed no significant differences, with the exception of higher homologous recombination deficiency scores in IBC, and copy number changes on chromosome Xq in triple negative SDBCs. Our data demonstrates that while IBCs are clinically more aggressive than SDBC, when matched for confounding clinico-pathological features they do not represent a unique molecular class of invasive BC, but could be a consequence of timing of tumour initiation and mammographic screening. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.