Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer

WD repeat domain 43 as a new predictive indicator and its connection with tumor immune cell infiltration in pan-cancer

BACKGROUND

WD repeat domain 43 (WDR43) is a protein component that encodes WD-repeats and is involved in ribosome biogenesis. However, little is known about the role of WDR43 in cancer prognosis and immune modulation.

METHODS

In this study, we analyzed the expression and prognostic significance of WDR43 in pan-cancer using the Cancer Genome Atlas, the Genotype-Tissue Expression, and the Human Protein Atlas. We also examined the differential expression of WDR43 in liver hepatocellular carcinoma (LIHC) and adjacent tissues of 48 patients using immunohistochemistry. Additionally, we investigated the correlation between WDR43 and clinical characteristics, gene alterations, tumor mutation burden, microsatellite instability, mismatch repair, tumor microenvironment, immune infiltrating cells, and immune-related genes using bioinformatics methods. Gene set enrichment analysis was conducted, and potential biological mechanisms were identified.

RESULTS

Immunohistochemistry staining showed that WDR43 was overexpressed in LIHC among 48 patients. Upregulation of WDR43 was associated with unfavorable prognosis, including overall survival in various types of cancer such as LIHC, uterine corpus endometrial cancer, head and neck squamous cell carcinoma, and pancreatic adenocarcinoma. Differential expression of WDR43 was significantly correlated with microsatellite instability, mismatch repair, and immune cell infiltration. Gene ontology annotation analysis revealed that these genes were significantly enriched in immune-related functions, including immune response, immune regulation, and signaling pathways.

CONCLUSION

We conducted a thorough investigation of the clinical features, phases of tumor development, immune infiltration, gene mutation, and functional enrichment analysis of WDR43 in various types of cancer. This research offers valuable insight into the significance and function of WDR43 in clinical therapy.

A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer

Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.

Cis- and trans-eQTL TWASs of breast and ovarian cancer identify more than 100 susceptibility genes in the BCAC and OCAC consortia

Transcriptome-wide association studies (TWASs) have investigated the role of genetically regulated transcriptional activity in the etiologies of breast and ovarian cancer. However, methods performed to date have focused on the regulatory effects of risk-associated SNPs thought to act in cis on a nearby target gene. With growing evidence for distal (trans) regulatory effects of variants on gene expression, we performed TWASs of breast and ovarian cancer using a Bayesian genome-wide TWAS method (BGW-TWAS) that considers effects of both cis- and trans-expression quantitative trait loci (eQTLs). We applied BGW-TWAS to whole-genome and RNA sequencing data in breast and ovarian tissues from the Genotype-Tissue Expression project to train expression imputation models. We applied these models to large-scale GWAS summary statistic data from the Breast Cancer and Ovarian Cancer Association Consortia to identify genes associated with risk of overall breast cancer, non-mucinous epithelial ovarian cancer, and 10 cancer subtypes. We identified 101 genes significantly associated with risk with breast cancer phenotypes and 8 with ovarian phenotypes. These loci include established risk genes and several novel candidate risk loci, such as ACAP3, whose associations are predominantly driven by trans-eQTLs. We replicated several associations using summary statistics from an independent GWAS of these cancer phenotypes. We further used genotype and expression data in normal and tumor breast tissue from the Cancer Genome Atlas to examine the performance of our trained expression imputation models. This work represents an in-depth look into the role of trans eQTLs in the complex molecular mechanisms underlying these diseases.

rs2736098, a synonymous polymorphism, is associated with carcinogenesis and cell count in multiple tissue types by regulating TERT expression

rs2736098 is a synonymous polymorphism in TERT (telomerase reverse transcriptase), an enzyme involved in tumor onset of multiple tissues, and should play no roles in carcinogenesis. However, a search in cancer somatic mutation database indicated that the mutation frequency at rs2736098 is much higher than the average one for TERT. Moreover, there are significant H3K4me1 and H3K27Ac signals, two universal histone modifications for active enhancers, surrounding rs2736098. Therefore, we hypothesized that rs2736098 might be within an enhancer region, regulate TERT expression and influence cancer risk. Through luciferase assay, it was verified that the enhancer activity of rs2736098C allele is significantly higher than that of T in multiple tissues. Transfection of plasmids containing TERT coding region with two different alleles indicated that rs2736098C allele can induce a significantly higher TERT expression than T. By chromatin immunoprecipitation, it was observed that the fragment spanning rs2736098 can interact with USF1 (upstream transcription factor 1). The two alleles of rs2736098 present evidently different binding affinity with nuclear proteins. Database and literature search indicated that rs2736098 is significantly associated with carcinogenesis in multiple tissues and count of multiple cell types. All these facts indicated that rs2736098 is also an oncogenic polymorphism and plays important role in cell proliferation.

Expression- and splicing-based multi-tissue transcriptome-wide association studies identified multiple genes for breast cancer by estrogen-receptor status

BACKGROUND

Although several transcriptome-wide association studies (TWASs) have been performed to identify genes associated with overall breast cancer (BC) risk, only a few TWAS have explored the differences in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) breast cancer. Additionally, these studies were based on gene expression prediction models trained primarily in breast tissue, and they did not account for alternative splicing of genes.

METHODS

In this study, we utilized two approaches to perform multi-tissue TWASs of breast cancer by ER subtype: (1) an expression-based TWAS that combined TWAS signals for each gene across multiple tissues and (2) a splicing-based TWAS that combined TWAS signals of all excised introns for each gene across tissues. To perform this TWAS, we utilized summary statistics for ER + BC from the Breast Cancer Association Consortium (BCAC) and for ER- BC from a meta-analysis of BCAC and the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA).

RESULTS

In total, we identified 230 genes in 86 loci that were associated with ER + BC and 66 genes in 29 loci that were associated with ER- BC at a Bonferroni threshold of significance. Of these genes, 2 genes associated with ER + BC at the 1q21.1 locus were located at least 1 Mb from published GWAS hits. For several well-studied tumor suppressor genes such as TP53 and CHEK2 which have historically been thought to impact BC risk through rare, penetrant mutations, we discovered that common variants, which modulate gene expression, may additionally contribute to ER + or ER- etiology.

CONCLUSIONS

Our study comprehensively examined how differences in common variation contribute to molecular differences between ER + and ER- BC and introduces a novel, splicing-based framework that can be used in future TWAS studies.

Cis- and trans-eQTL TWAS of breast and ovarian cancer identify more than 100 risk associated genes in the BCAC and OCAC consortia

Transcriptome-wide association studies (TWAS) have investigated the role of genetically regulated transcriptional activity in the etiologies of breast and ovarian cancer. However, methods performed to date have only considered regulatory effects of risk associated SNPs thought to act in cis on a nearby target gene. With growing evidence for distal (trans) regulatory effects of variants on gene expression, we performed TWAS of breast and ovarian cancer using a Bayesian genome-wide TWAS method (BGW-TWAS) that considers effects of both cis- and trans-expression quantitative trait loci (eQTLs). We applied BGW-TWAS to whole genome and RNA sequencing data in breast and ovarian tissues from the Genotype-Tissue Expression project to train expression imputation models. We applied these models to large-scale GWAS summary statistic data from the Breast Cancer and Ovarian Cancer Association Consortia to identify genes associated with risk of overall breast cancer, non-mucinous epithelial ovarian cancer, and 10 cancer subtypes. We identified 101 genes significantly associated with risk with breast cancer phenotypes and 8 with ovarian phenotypes. These loci include established risk genes and several novel candidate risk loci, such as ACAP3, whose associations are predominantly driven by trans-eQTLs. We replicated several associations using summary statistics from an independent GWAS of these cancer phenotypes. We further used genotype and expression data in normal and tumor breast tissue from the Cancer Genome Atlas to examine the performance of our trained expression imputation models. This work represents a first look into the role of trans-eQTLs in the complex molecular mechanisms underlying these diseases.

Human-genome single nucleotide polymorphisms affecting transcription factor binding and their role in pathogenesis

Single nucleotide polymorphisms (SNPs) are the most common type of variation in the human genome. The vast majority of SNPs identified in the human genome do not have any effect on the phenotype; however, some can lead to changes in the function of a gene or the level of its expression. Most SNPs associated with certain traits or pathologies are mapped to regulatory regions of the genome and affect gene expression by changing transcription factor binding sites. In recent decades, substantial effort has been invested in searching for such regulatory SNPs (rSNPs) and understanding the mechanisms by which they lead to phenotypic differences, primarily to individual differences in susceptibility to diseases and in sensitivity to drugs. The development of the NGS (next-generation sequencing) technology has contributed not only to the identification of a huge number of SNPs and to the search for their association (genome-wide association studies, GWASs) with certain diseases or phenotypic manifestations, but also to the development of more productive approaches to their functional annotation. It should be noted that the presence of an association does not allow one to identify a functional, truly disease-associated DNA sequence variant among multiple marker SNPs that are detected due to linkage disequilibrium. Moreover, determination of associations of genetic variants with a disease does not provide information about the functionality of these variants, which is necessary to elucidate the molecular mechanisms of the development of pathology and to design effective methods for its treatment and prevention. In this regard, the functional analysis of SNPs annotated in the GWAS catalog, both at the genome-wide level and at the level of individual SNPs, became especially relevant in recent years. A genome-wide search for potential rSNPs is possible without any prior knowledge of their association with a trait. Thus, mapping expression quantitative trait loci (eQTLs) makes it possible to identify an SNP for which - among transcriptomes of homozygotes and heterozygotes for its various alleles - there are differences in the expression level of certain genes, which can be located at various distances from the SNP. To predict rSNPs, approaches based on searches for allele-specific events in RNA-seq, ChIP-seq, DNase-seq, ATAC-seq, MPRA, and other data are also used. Nonetheless, for a more complete functional annotation of such rSNPs, it is necessary to establish their association with a trait, in particular, with a predisposition to a certain pathology or sensitivity to drugs. Thus, approaches to finding SNPs important for the development of a trait can be categorized into two groups: (1) starting from data on an association of SNPs with a certain trait, (2) starting from the determination of allele-specific changes at the molecular level (in a transcriptome or regulome). Only comprehensive use of strategically different approaches can considerably enrich our knowledge about the role of genetic determinants in the molecular mechanisms of trait formation, including predisposition to multifactorial diseases.

TRMT61B rs4563180 G>C variant reduces hepatoblastoma risk: a case-control study of seven medical centers

N1-methyladenosine (m1A) is an essential chemical modification of RNA. Dysregulation of RNA m1A modification and m1A-related regulators is detected in several adult tumors. Whether aberrant RNA m1A modification is involved in hepatoblast carcinogenesis has not been reported. tRNA methyltransferase 61B (TRMT61B) is responsible for mitochondrial RNA m1A modification. Some evidence has shown that genetic variants of TRMT61B might contribute to cancer susceptibility; however, its roles in hepatoblastoma are unknown. This study attempted to discover novel hepatoblastoma susceptibility loci. With the TaqMan method, we examined genotypes of the TRMT61B rs4563180 G>C polymorphism among germline DNA samples from 313 cases and 1446 controls. The association of the rs4563180 G>C polymorphism with hepatoblastoma risk was estimated based on odds ratios (ORs) and 95% confidence intervals (CIs). We found that the TRMT61B rs4563180 G>C polymorphism correlated significantly with a reduction in hepatoblastoma risk (GC vs. GG: adjusted OR=0.65, 95% CI=0.49-0.85, P=0.002; GC/CC vs. GG: adjusted OR=0.66, 95% CI=0.51-0.85, P=0.002). In stratified analysis, significant associations were detected in children younger than 17 months old, girls, and subgroups with stage I+II or III+IV tumors. False-positive report probability analysis validated that children with the GC or CC genotype, particularly in those <17 months of age, had a decreased risk of hepatoblastoma. The rs4563180 G>C polymorphism also correlated with expression of TRMT61B and the nearby gene PPP1CB. We identified a high-quality biomarker measuring hepatoblastoma susceptibility, which may contribute to future screening programs.

Mitochondrial DNA-targeted therapy: A novel approach to combat cancer

Mitochondrial DNA (mtDNA) encodes proteins and RNAs that are essential for mitochondrial function and cellular homeostasis, and participates in important processes of cellular bioenergetics and metabolism. Alterations in mtDNA are associated with various diseases, especially cancers, and are considered as biomarkers for some types of tumors. Moreover, mtDNA alterations have been found to affect the proliferation, progression and metastasis of cancer cells, as well as their interactions with the immune system and the tumor microenvironment (TME). The important role of mtDNA in cancer development makes it a significant target for cancer treatment. In recent years, many novel therapeutic methods targeting mtDNA have emerged. In this study, we first discussed how cancerogenesis is triggered by mtDNA mutations, including alterations in gene copy number, aberrant gene expression and epigenetic modifications. Then, we described in detail the mechanisms underlying the interactions between mtDNA and the extramitochondrial environment, which are crucial for understanding the efficacy and safety of mtDNA-targeted therapy. Next, we provided a comprehensive overview of the recent progress in cancer therapy strategies that target mtDNA. We classified them into two categories based on their mechanisms of action: indirect and direct targeting strategies. Indirect targeting strategies aimed to induce mtDNA damage and dysfunction by modulating pathways that are involved in mtDNA stability and integrity, while direct targeting strategies utilized molecules that can selectively bind to or cleave mtDNA to achieve the therapeutic efficacy. This study highlights the importance of mtDNA-targeted therapy in cancer treatment, and will provide insights for future research and development of targeted drugs and therapeutic strategies.

Establishment of a N1-methyladenosine-related risk signature for breast carcinoma by bioinformatics analysis and experimental validation

OBJECTIVES

Breast carcinoma (BRCA) has resulted in a huge health burden globally. N1-methyladenosine (m¹A) RNA methylation has been proven to play key roles in tumorigenesis. Nevertheless, the function of m¹A RNA methylation-related genes in BRCA is indistinct.

METHODS

The RNA sequencing (RNA-seq), copy-number variation (CNV), single-nucleotide variant (SNV), and clinical data of BRCA were acquired via The Cancer Genome Atlas (TCGA) database. In addition, the GSE20685 dataset, the external validation set, was acquired from the Gene Expression Omnibus (GEO) database. 10 m¹A RNA methylation regulators were obtained from the previous literature, and further analyzed through differential expression analysis by rank-sum test, mutation by SNV data, and mutual correlation by Pearson Correlation Analysis. Furthermore, the differentially expressed m¹A-related genes were selected through overlapping m¹A-related module genes obtained by weighted gene co-expression network analysis (WGCNA), differentially expressed genes (DEGs) in BRCA and DEGs between high- and low- m¹A score subgroups. The m¹A-related model genes in the risk signature were derived by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. In addition, a nomogram was built through univariate and multivariate Cox analyses. After that, the immune infiltration between the high- and low-risk groups was investigated through ESTIMATE and CIBERSORT. Finally, the expression trends of model genes in clinical BRCA samples were further confirmed by quantitative real-time PCR (RT‒qPCR).

RESULTS

Eighty-five differentially expressed m¹A-related genes were obtained. Among them, six genes were selected as prognostic biomarkers to build the risk model. The validation results of the risk model showed that its prediction was reliable. In addition, Cox independent prognosis analysis revealed that age, risk score, and stage were independent prognostic factors for BRCA. Moreover, 13 types of immune cells were different between the high- and low-risk groups and the immune checkpoint molecules TIGIT, IDO1, LAG3, ICOS, PDCD1LG2, PDCD1, CD27, and CD274 were significantly different between the two risk groups. Ultimately, RT-qPCR results confirmed that the model genes MEOX1, COL17A1, FREM1, TNN, and SLIT3 were significantly up-regulated in BRCA tissues versus normal tissues.

CONCLUSIONS

An m¹A RNA methylation regulator-related prognostic model was constructed, and a nomogram based on the prognostic model was constructed to provide a theoretical reference for individual counseling and clinical preventive intervention in BRCA.

Molecular etiology of defective nuclear and mitochondrial ribosome biogenesis: Clinical phenotypes and therapy

Ribosomopathies are rare congenital disorders associated with defective ribosome biogenesis due to pathogenic variations in genes that encode proteins related to ribosome function and biogenesis. Defects in ribosome biogenesis result in a nucleolar stress response involving the TP53 tumor suppressor protein and impaired protein synthesis leading to a deregulated translational output. Despite the accepted notion that ribosomes are omnipresent and essential for all cells, most ribosomopathies show tissue-specific phenotypes affecting blood cells, hair, spleen, or skin. On the other hand, defects in mitochondrial ribosome biogenesis are associated with a range of clinical manifestations affecting more than one organ. Intriguingly, the deregulated ribosomal function is also a feature in several human malignancies with a selective upregulation or downregulation of specific ribosome components. Here, we highlight the clinical conditions associated with defective ribosome biogenesis in the nucleus and mitochondria with a description of the affected genes and the implicated pathways, along with a note on the treatment strategies currently available for these disorders.

Mitochondrial RNA methyltransferase TRMT61B is a new, potential biomarker and therapeutic target for highly aneuploid cancers

Despite being frequently observed in cancer cells, chromosomal instability (CIN) and its immediate consequence, aneuploidy, trigger adverse effects on cellular homeostasis that need to be overcome by anti-stress mechanisms. As such, these safeguard responses represent a tumor-specific Achilles heel, since CIN and aneuploidy are rarely observed in normal cells. Recent data have revealed that epitranscriptomic marks catalyzed by RNA-modifying enzymes change under various stress insults. However, whether aneuploidy is associated with such RNA modifying pathways remains to be determined. Through an in silico search for aneuploidy biomarkers in cancer cells, we found TRMT61B, a mitochondrial RNA methyltransferase enzyme, to be associated with high levels of aneuploidy. Accordingly, TRMT61B protein levels are increased in tumor cell lines with an imbalanced karyotype as well as in different tumor types when compared to control tissues. Interestingly, while TRMT61B depletion induces senescence in melanoma cell lines with low levels of aneuploidy, it leads to apoptosis in cells with high levels. The therapeutic potential of these results was further validated by targeting TRMT61B in transwell and xenografts assays. We show that TRM61B depletion reduces the expression of several mitochondrial encoded proteins and limits mitochondrial function. Taken together, these results identify a new biomarker of aneuploidy in cancer cells that could potentially be used to selectively target highly aneuploid tumors.

Cromolyn prevents cerebral vasospasm and dementia by targeting WDR43

Background

Cerebral vasospasm (CV) can cause inflammation and damage to neuronal cells in the elderly, leading to dementia.

Purpose

This study aimed to investigate the genetic mechanisms underlying dementia caused by CV in the elderly, identify preventive and therapeutic drugs, and evaluate their efficacy in treating neurodegenerative diseases.

Methods

Genes associated with subarachnoid hemorrhage and CV were acquired and screened for differentially expressed miRNAs (DEmiRNAs) associated with aneurysm rupture. A regulatory network of DEmiRNAs and mRNAs was constructed, and virtual screening was performed to evaluate possible binding patterns between Food and Drug Administration (FDA)-approved drugs and core proteins. Molecular dynamics simulations were performed on the optimal docked complexes. Optimally docked drugs were evaluated for efficacy in the treatment of neurodegenerative diseases through cellular experiments.

Results

The study found upregulated genes (including WDR43 and THBS1) and one downregulated gene associated with aneurysm rupture. Differences in the expression of these genes indicate greater disease risk. DEmiRNAs associated with ruptured aortic aneurysm were identified, of which two could bind to THBS1 and WDR43. Cromolyn and lanoxin formed the best docking complexes with WDR43 and THBS1, respectively. Cellular experiments showed that cromolyn improved BV2 cell viability and enhanced Aβ42 uptake, suggesting its potential as a therapeutic agent for inflammation-related disorders.

Conclusion

The findings suggest that WDR43 and THBS1 are potential targets for preventing and treating CV-induced dementia in the elderly. Cromolyn may have therapeutic value in the treatment of Alzheimer's disease and dementia.

SNP-Target Genes Interaction Perturbing the Cancer Risk in the Post-GWAS

Cancer ranks as the second leading cause of death worldwide, and, being a genetic disease, it is highly heritable. Over the past few decades, genome-wide association studies (GWAS) have identified many risk-associated loci harboring hundreds of single nucleotide polymorphisms (SNPs). Some of these cancer-associated SNPs have been revealed as causal, and the functional characterization of the mechanisms underlying the cancer risk association has been illuminated in some instances. In this review, based on the different positions of SNPs and their modes of action, we discuss the mechanisms underlying how SNPs regulate the expression of target genes to consequently affect tumorigenesis and the development of cancer.

Identification and construction of a prognostic risk model based on multi-RNA methylation regulators in cervical cancer

AIM

Cervical cancer is one of the most aggressive female cancers. RNA methylation is a necessary epigenetic modification in biological process. This study aimed to construct an RNA methylation regulator-based risk model for predicting the prognosis of cervical cancer patients.

METHODS

The transcriptome profiles of cervical cancer data were obtained from The Cancer Genome Atlas (TCGA) and GSE44001. An RNA methylation-related risk model was constructed and assessed by the Least absolute shrinkage and selection operator (Lasso)-penalized Cox regression model and receiver operating characteristic (ROC). Kaplan-Meier and Cox regression analyses were used to evaluate the prognostic effect of the risk model and calculated scores. The immune infiltration difference was further analyzed between the subgroups with a single-sample gene set enrichment analysis (ssGSEA).

RESULTS

A total of 63 methylation modulators were included in this study, and 618 cervical cancer patients were identified from TCGA and GSE44001. Differential expression genes profiling RNA methylation regulators between normal and tumor samples were distinct. A four-gene signature panel was constructed to predict the prognostic risk. The predictive ability was satisfactory. Cervical cancer patients were classified into high- or low-risk subgroups according to the median risk score. Moreover, the immune infiltration patterns between them differed.

CONCLUSIONS

A risk model including four RNA methylation regulators was constructed, which will provide new perspectives for further investigation of the relationship between RNA methylation and cervical cancer.

TAaCGH Suite for Detecting Cancer-Specific Copy Number Changes Using Topological Signatures

Copy number changes play an important role in the development of cancer and are commonly associated with changes in gene expression. Persistence curves, such as Betti curves, have been used to detect copy number changes; however, it is known these curves are unstable with respect to small perturbations in the data. We address the stability of lifespan and Betti curves by providing bounds on the distance between persistence curves of Vietoris–Rips filtrations built on data and slightly perturbed data in terms of the bottleneck distance. Next, we perform simulations to compare the predictive ability of Betti curves, lifespan curves (conditionally stable) and stable persistent landscapes to detect copy number aberrations. We use these methods to identify significant chromosome regions associated with the four major molecular subtypes of breast cancer: Luminal A, Luminal B, Basal and HER2 positive. Identified segments are then used as predictor variables to build machine learning models which classify patients as one of the four subtypes. We find that no single persistence curve outperforms the others and instead suggest a complementary approach using a suite of persistence curves. In this study, we identified new cytobands associated with three of the subtypes: 1q21.1-q25.2, 2p23.2-p16.3, 23q26.2-q28 with the Basal subtype, 8p22-p11.1 with Luminal B and 2q12.1-q21.1 and 5p14.3-p12 with Luminal A. These segments are validated by the TCGA BRCA cohort dataset except for those found for Luminal A.

Update Breast Cancer 2022 Part 1 – Early Stage Breast Cancer

Evidence relating to the treatment of breast cancer patients with early-stage disease has increased significantly in the past year. Abemaciclib, olaparib, and pembrolizumab are new drugs with good efficacy in the relevant patient groups. However, some questions remain unanswered. In particular, it remains unclear which premenopausal patients with hormone receptor-positive breast cancer should be spared unnecessary treatment. The question of the degree to which chemotherapy exerts a direct cytotoxic effect on the tumor or reduces ovarian function through chemotherapy could be of key importance. This group of patients could potentially be spared chemotherapy. New, previously experimental biomarker analysis methods, such as spatial analysis of gene expression (spatial transcriptomics) are gradually finding their way into large randomized phase III trials, such as the NeoTRIP trial. This in turn leads to a better understanding of the predictive factors of new therapies, for example immunotherapy. This review summarizes the scientific innovations from recent congresses such as the San Antonio Breast Cancer Symposium 2021 but also from recent publications.

Two distinct mechanisms underlie estrogen-receptor-negative breast cancer susceptibility at the 2p23.2 locus

Genome wide-association studies (GWAS) have established over 400 breast cancer risk loci defined by common single nucleotide polymorphisms (SNPs), including several associated with estrogen-receptor (ER)-negative disease. Most of these loci have not been studied systematically and the mechanistic underpinnings of risk are largely unknown. Here we explored the landscape of genomic features at an ER-negative breast cancer susceptibility locus at chromosome 2p23.2 and assessed the functionality of 81 SNPs with strong evidence of association from previous fine mapping. Five candidate regulatory regions containing risk-associated SNPs were identified. Regulatory Region 1 in the first intron of WDR43 contains SNP rs4407214, which showed allele-specific interaction with the transcription factor USF1 in in vitro assays. CRISPR-mediated disruption of Regulatory Region 1 led to expression changes in the neighboring PLB1 gene, suggesting that the region acts as a distal enhancer. Regulatory Regions 2, 4, and 5 did not provide sufficient evidence for functionality in in silico and experimental analyses. Two SNPs (rs11680458 and rs1131880) in Regulatory Region 3, mapping to the seed region for miRNA-recognition sites in the 3' untranslated region of WDR43, showed allele-specific effects of ectopic expression of miR-376 on WDR43 expression levels. Taken together, our data suggest that risk of ER-negative breast cancer associated with the 2p23.2 locus is likely driven by a combinatorial effect on the regulation of WDR43 and PLB1.

TIGAR-V2: Efficient TWAS tool with nonparametric Bayesian eQTL weights of 49 tissue types from GTEx V8

Standard transcriptome-wide association study (TWAS) methods first train gene expression prediction models using reference transcriptomic data and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we developed Transcriptome-Integrated Genetic Association Resource V2 (TIGAR-V2), which directly reads Variant Call Format (VCF) files, enables parallel computation, and reduces up to 90% of computation cost (mainly due to loading genotype data) compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet process regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWASs using either individual-level or summary-level genome-wide association study (GWAS) data, and implement both burden and variance-component statistics for gene-based association tests. We trained gene expression prediction models by DPR for 49 tissues using Genotype-Tissue Expression (GTEx) V8 by TIGAR-V2 and illustrated the usefulness of these Bayesian cis-expression quantitative trait locus (eQTL) weights through TWASs of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes, respectively, for breast and ovarian cancer, most of which are either known or near previously identified GWAS (∼95%) or TWAS (∼40%) risk genes and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWASs can provide biological insight into the transcriptional regulation of complex diseases. The TIGAR-V2 tool, trained Bayesian cis-eQTL weights, and linkage disequilibrium (LD) information from GTEx V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.

Differential analysis of RNA methylation regulators in gastric cancer based on TCGA data set and construction of a prognostic model

Background

Methylation is one of the common forms of RNA modification, which mainly include N6-methyladenosine (m6A), C5-methylcytidine (m5C), and N1-methyladenosine (m1A). Numerous studies have shown that RNA methylation is associated with tumor development. We aim to construct prognostic models of gastric cancer based on RNA methylation regulators.

Methods

The transcriptome and clinical data of gastric cancer and normal samples were obtained from the National Cancer Institute Genome Data Commons (NCI-GDC). Use Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis to construct risk models for different types of RNA methylation. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive efficiency of risk characteristics. Cluster heat maps are used to assess the correlation with clinical information. Univariate and multivariate Cox analyses were used to analyze prognostic effects of risk scores. Gene Set Enrichment Analysis (GSEA) analyzes the functional enrichment of RNA methylation genes. And make a separate analysis of the data of Asians.

Results

The expression of most of the 30 RNA methylation regulators were significantly different in cancer and paracancerous tissues (P<0.05). Three methylated genes (FTO, ALKBH5, and RBM15) were screened from m6A by LASSO Cox regression analysis. Five methylated genes (FTO, ALKBH5, TRMT61B, RBM15, and YXB1) were selected from the population, and were used to construct two risk ratio models. Survival analysis showed that the survival rate of patients in the low-risk group was significantly higher than that in the high-risk group (P<0.05). All ROC curves indicated that the predictive efficiency of risk characteristics was good [area under the ROC curve (AUC): 0.6-1].Cluster analysis reveals differences in clinical data between the two groups. Univariate and multivariate Cox regression results show that the risk score has independent prognostic value. GSEA showed that pathways such as cell cycle were significantly enriched in the low-risk group, while pathways such as calcium signaling pathway were significantly enriched in the high-risk group. In addition, three methylation models that can predict the prognosis of Asian gastric cancer patients were obtained.

Conclusions

The methylation prognosis model constructed in this study can effectively predict the prognosis of gastric cancer patients.

Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

BACKGROUND

Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.

METHODS

We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15).

RESULTS

Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy.

CONCLUSIONS

We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.

WD40 repeat 43 mediates cell survival, proliferation, migration and invasion via vimentin in colorectal cancer

Background

WD40 repeat (WDR)43 is an RNA-binding protein that belongs to the WDR domain protein family. Its biological function is largely unclear, particularly in colorectal cancer (CRC).

Methods

In the present study, we searched the TCGA database and found the correlation between WDR43 and CRC. Subsequently, the high expression of WDR43 in human clinical samples of CRC was validated and we further examined the biological functions of it in CRC cells. Finally, we explored potential downstream proteins or pathways and established subcutaneous xenograft model to verify our findings.

Results

Immunohistochemistry of 16 patient specimens confirmed that the expression of WDR43 was elevated in CRC. WDR43 knockdown was shown to increase apoptosis and inhibit the proliferation, migration and invasion of CRC cells in vitro and reduce tumorigenesis in animal models. In addition, it was found that WDR43 knockdown inhibited vimentin (VIM) expression in CRC cells and overexpression of VIM can partially reverse the effects of WDR43 both in vitro and in vivo.

Conclusion

In conclusion, the role of WDR43 in the occurrence and development of CRC was investigated in the present study. WDR43 may serve as a valuable biomarker and provide new options for the diagnosis and treatment of colorectal cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02109-1.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.

A search for modifying genetic factors in CHEK2:c.1100delC breast cancer patients

The risk of breast cancer associated with CHEK2:c.1100delC is 2-threefold but higher in carriers with a family history of breast cancer than without, suggesting that other genetic loci in combination with CHEK2:c.1100delC confer an increased risk in a polygenic model. Part of the excess familial risk has been associated with common low-penetrance variants. This study aimed to identify genetic loci that modify CHEK2:c.1100delC-associated breast cancer risk by searching for candidate risk alleles that are overrepresented in CHEK2:c.1100delC carriers with breast cancer compared with controls. We performed whole-exome sequencing in 28 breast cancer cases with germline CHEK2:c.1100delC, 28 familial breast cancer cases and 70 controls. Candidate alleles were selected for validation in larger cohorts. One recessive synonymous variant, rs16897117, was suggested, but no overrepresentation of homozygous CHEK2:c.1100delC carriers was found in the following validation. Furthermore, 11 non-synonymous candidate alleles were suggested for further testing, but no significant difference in allele frequency could be detected in the validation in CHEK2:c.1100delC cases compared with familial breast cancer, sporadic breast cancer and controls. With this method, we found no support for a CHEK2:c.1100delC-specific genetic modifier. Further studies of CHEK2:c.1100delC genetic modifiers are warranted to improve risk assessment in clinical practice.

Mitochondrial noncoding RNAs: new wine in an old bottle

Mitochondrial noncoding RNAs (mt-ncRNAs) include noncoding RNAs inside the mitochondria that are transcribed from the mitochondrial genome or nuclear genome, and noncoding RNAs transcribed from the mitochondrial genome that are transported to the cytosol or nucleus. Recent findings have revealed that mt-ncRNAs play important roles in not only mitochondrial functions, but also other cellular activities. This review proposes a classification of mt-ncRNAs and outlines the emerging understanding of mitochondrial circular RNAs (mt-circRNAs), mitochondrial microRNAs (mitomiRs), and mitochondrial long noncoding RNAs (mt-lncRNAs), with an emphasis on their identification and functions.

Role of tRNAs in Breast Cancer Regulation

Increased proliferation and protein synthesis are characteristics of transformed and tumor cells. Although the components of the translation machinery are often dysregulated in cancer, the role of tRNAs in cancer cells has not been well studied. Nevertheless, the number of related studies has recently started increasing. With the development of high throughput technologies such as next-generation sequencing, genome-wide differential tRNA expression patterns in breast cancer-derived cell lines and breast tumors have been investigated. The genome-wide transcriptomics analyses have been linked with many studies for functional and phenotypic characterization, whereby tRNAs or tRNA-related fragments have been shown to play important roles in breast cancer regulation and as promising prognostic biomarkers. Here, we review their expression patterns, functions, prognostic value, and potential therapeutic use as well as related technologies.

Update Breast Cancer 2021 Part 1 - Prevention and Early Stages

This review summarises not only the latest evidence on prevention, but also the current research on the treatment of early-stage breast cancer patients. Recent years have seen a growing body of evidence on the risk of high- and moderate-penetrance breast cancer susceptibility genes. A large international consortium has now been able to further refine the answer to the question of the significance of the so-called panel genes. Moreover, the data on treatment selection regarding endocrine efficacy and the decision for or against chemotherapy have also been advanced markedly. There is also new data on adjuvant CDK4/6 (cyclin-dependent kinase 4/6) inhibitors, which are standard in first-line treatment in patients with metastatic HER2-negative, hormone receptor-positive (HR+) breast cancer. For other therapies such as immune checkpoint inhibitors, which have successfully improved the rate of pathologic complete response (pCR) in neoadjuvant treatment settings for patients with triple-negative breast cancer (TNBC), there is a growing understanding of the quality of life and side effects. This is especially important in situations where patients could possibly be cured without such a regimen.

Human Mitoribosome Biogenesis and Its Emerging Links to Disease

Mammalian mitochondrial ribosomes (mitoribosomes) synthesize a small subset of proteins, which are essential components of the oxidative phosphorylation machinery. Therefore, their function is of fundamental importance to cellular metabolism. The assembly of mitoribosomes is a complex process that progresses through numerous maturation and protein-binding events coordinated by the actions of several assembly factors. Dysregulation of mitoribosome production is increasingly recognized as a contributor to metabolic and neurodegenerative diseases. In recent years, mutations in multiple components of the mitoribosome assembly machinery have been associated with a range of human pathologies, highlighting their importance to cell function and health. Here, we provide a review of our current understanding of mitoribosome biogenesis, highlighting the key factors involved in this process and the growing number of mutations in genes encoding mitoribosomal RNAs, proteins, and assembly factors that lead to human disease.

Genetic Association Analysis Implicates Six MicroRNA-Related SNPs With Increased Risk of Breast Cancer in Australian Caucasian Women

INTRODUCTION

Breast cancer (BC), a heterogeneous disease, features microRNA-related single nucleotide polymorphisms (miRSNPs) as underlying factors of BC development, thus providing targets for novel diagnostic and therapeutic strategies. This study investigated miRSNPs in BC susceptibility in Australian Caucasian women.

PATIENTS AND METHODS

The study population included patients 33 to 80 years of age stratified by molecular subtypes of breast tumors (luminal A, 47.59%), stage (stage I, 36.96%), tumor-type (ductal, 44.95%), grading (intermediate, 35.52%), size (10.1-25 mm, 31.14%), and lymph node (sentinel negative, 38.93%). Sixty-five miRSNPs underwent allelic analysis in two independent case-control cohorts (GU-CCQ-BB, 377 cases and 521 controls; GRC-BC, 267 cases and 201 controls) using a MassARRAY platform. GU-CCQ-BB, GRC-BC, and the combined populations (BC-CA) (644 cases and 722 controls) underwent independent statistical analysis.

RESULTS

In the GU-CCQ-BB population, miRSNPs TET2-rs7670522, ESR1-rs2046210, FGFR2-rs1219648, MIR210-rs1062099, HIF1A-rs2057482, and CASC16-rs4784227 were found to be associated with increased BC risk (P ≤ .05). Only ESR1-rs2046210 was also significantly associated (P ≤ .05) when replicated in the GRC-BC and BC-CA populations. No significant association was correlated with BC-clinical features (pathological types and ER/PR/HER2 status); however, MIR210-rs1062099 was found to be significantly associated (P ≤ .05) with age (>50 years) in the GU-CCQ-BB cohort.

CONCLUSION

This is the first study to demonstrate the association of MIR210-rs1062099 and TET2-rs7670522 with increased BC risk. Additionally, four previously reported SNPs (ESR1-rs2046210, FGFR2-rs1219648, HIF1A-rs2057482, and CASC16-rs4784227) were confirmed as BC risk variants. Replication and functional studies in larger Caucasian cohorts are necessary to elucidate the role of these miRSNPS in the development of BC.

From BRCA1 to Polygenic Risk Scores: Mutation-Associated Risks in Breast Cancer-Related Genes

Background

There has been huge progress over the last 30 years in identifying the familial component of breast cancer.

Summary

Currently around 20% is explained by the high-risk genes BRCA1 and BRCA2, a further 2% by other high-penetrance genes, and around 5% by the moderate risk genes ATM and CHEK2. In contrast, the more than 300 low-penetrance single-nucleotide polymorphisms (SNP) now account for around 28% and they are predicted to account for most of the remaining 45% yet to be found. Even for high-risk genes which confer a 40-90% risk of breast cancer, these SNP can substantially affect the level of breast cancer risk. Indeed, the strength of family history and hormonal and reproductive factors is very important in assessing risk even for a BRCA carrier. The risks of contralateral breast cancer are also affected by SNP as well as by the presence of high or moderate risk genes. Genetic testing using gene panels is now commonplace.

Key-Messages

There is a need for a more parsimonious approach to panels only testing those genes with a definite 2-fold increased risk and only testing those genes with challenging management implications, such as CDH1 and TP53, when there is strong clinical indication to do so. Testing of SNP alongside genes is likely to provide a more accurate risk assessment.

Genome-wide association meta-analysis identifies pleiotropic risk loci for aerodigestive squamous cell cancers

Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes rel to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10-8, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.

Human transfer RNA modopathies: diseases caused by aberrations in transfer RNA modifications

tRNA molecules are post-transcriptionally modified by tRNA modification enzymes. Although composed of different chemistries, more than 40 types of human tRNA modifications play pivotal roles in protein synthesis by regulating tRNA structure and stability as well as decoding genetic information on mRNA. Many tRNA modifications are conserved among all three kingdoms of life, and aberrations in various human tRNA modification enzymes cause life-threatening diseases. Here, we describe the class of diseases and disorders caused by aberrations in tRNA modifications as 'tRNA modopathies'. Aberrations in over 50 tRNA modification enzymes are associated with tRNA modopathies, which most frequently manifest as dysfunctions of the brain and/or kidney, mitochondrial diseases, and cancer. However, the molecular mechanisms that link aberrant tRNA modifications to human diseases are largely unknown. In this review, we provide a comprehensive compilation of human tRNA modification functions, tRNA modification enzyme genes, and tRNA modopathies, and we summarize the elucidated pathogenic mechanisms underlying several tRNA modopathies. We will also discuss important questions that need to be addressed in order to understand the molecular pathogenesis of tRNA modopathies.

Update Breast Cancer 2020 Part 3 - Early Breast Cancer

The treatment of patients with early breast cancer has always been characterised by escalation by new therapies and de-escalation through identification of better treatment regimens or introduction of better tools to estimate prognosis. Efforts in some of these areas in the last few years have led to solid data. The results of the large studies of de-escalation through use of multi-gene tests are available, as are the results of some studies that investigated the new anti-HER2 substances T-DM1 and pertuzumab in the early treatment situation. Several large-scale studies examining the role of CDK4/6 inhibitors will soon be concluded so innovations can be anticipated in this area also. This review article will summarise and classify the results of the latest publications.

Supervariants identification for breast cancer

In genome-wide association studies, signals associated with rare variants and interactions between genes are hard to detect even when the sample size is in tens of thousands. To overcome these problems, we examine the concept of supervariant. Like the classic concept of the gene, a supervariant is a combination of alleles in multiple loci, but the contributing loci can be anywhere in the genome. We hypothesize that supervariants are easy to detect and the aggregated signals are more stable in their associations with the disease than that from a single nucleoid polymorphism. Using the UK Biobank databases, we develop a ranking and aggregation method for identifying supervariants. Specifically, we examine 9,377 breast cancer cases with 46,861 controls matched by sex and age. In our simulations, the use of supervariants outperforms single-nucleotide polymorphism-based association method in detecting rare variants and signals with interactive structure. In real data analysis, we identify supervariants on Chromosomes 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 16, and 22 which cover previously reported loci that have associations with breast or other cancers, and several novel loci on Chromosomes 2, 5, 9, and 12. These findings demonstrate the validity of supervariants and its potential of discovering replicable and novel results for complex disease.

Methylation of Ribosomal RNA: A Mitochondrial Perspective

Ribosomal RNA (rRNA) from all organisms undergoes post-transcriptional modifications that increase the diversity of its composition and activity. In mitochondria, specialized mitochondrial ribosomes (mitoribosomes) are responsible for the synthesis of 13 oxidative phosphorylation proteins encoded by the mitochondrial genome. Mitoribosomal RNA is also modified, with 10 modifications thus far identified and all corresponding modifying enzymes described. This form of epigenetic regulation of mitochondrial gene expression affects mitoribosome biogenesis and function. Here, we provide an overview on rRNA methylation and highlight critical work that is beginning to elucidate its role in mitochondrial gene expression. Given the similarities between bacterial and mitochondrial ribosomes, we focus on studies involving Escherichia coli and human models. Furthermore, we highlight the use of state-of-the-art technologies, such as cryoEM in the study of rRNA methylation and its biological relevance. Understanding the mechanisms and functional relevance of this process represents an exciting frontier in the RNA biology and mitochondrial fields.

Characterization and in silico analyses of the BRCA1/2 variants identified in individuals with personal and/or family history of BRCA-related cancers

Pathogenic variants in the coding regions of the BRCA1/2 lead dysfunctional or nonfunctional BRCA proteins however the contribution of non-coding BRCA1/2 variants to BRCA-related disease risk has not been fully elucidated. Thus, we characterized the functional impact of both coding and non-coding BRCA1/2 variants identified in individuals with personal and/or family history of BRCA-related cancers. The data were produced by resequencing the exons and exon-intron junctions of the BRCA1/2 in 125 individuals and were comprehensively analyzed by using bioinformatics tools and databases. A total of 96 variants (59 coding and 37 non-coding) including 7 novel variants were identified and analyzed for their functional importance. We identified 11 missense variants that potentially affect protein function; 22 variants were likely to alter different types of posttranslational modifications. Also, multiple non-coding BRCA1/2 variants were found to reside in the critical regulatory regions that have the potential to act as eQTLs and affect alternative splicing. The results of our study shed light on the possible contributions of not only coding variants but also non-coding BRCA1/2 variants in BRCRA-related cancers. Further investigation is required to fully understand their potential associations with phenotypes which may ultimately lead their utilization on cancer management as a biomarker.

Update Breast Cancer 2020 Part 1 - Early Breast Cancer: Consolidation of Knowledge About Known Therapies

This review is intended to present the latest developments in the prevention and treatment of early breast cancer. The risk of breast cancer can be increasingly better characterised with large epidemiological studies on genetic and non-genetic risk factors. Through new analyses, the evidence for high-penetrance genes as well as for low-penetrance genes was able to be improved. New data on denosumab and atezolizumab are available in the neoadjuvant situation as is a pooled appraisal of numerous studies on capecitabine in the curative situation. There is also an update to the overall survival data of pertuzumab in the adjuvant situation with a longer follow-up observation period. Finally, digital medicine is steadily finding its way into science. A recently conducted study on automated breast cancer detection using artificial intelligence establishes the basis for a future review in clinical studies.

Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium

BACKGROUND

Previous gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.

METHODS

Analyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.

RESULTS

Noteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.

CONCLUSIONS

Overall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.

The atypical cyclin-like protein Spy1 overrides p53-mediated tumour suppression and promotes susceptibility to breast tumourigenesis

Background

Breast cancer is the most common cancer to affect women and one of the leading causes of cancer-related deaths. Proper regulation of cell cycle checkpoints plays a critical role in preventing the accumulation of deleterious mutations. Perturbations in the expression or activity of mediators of cell cycle progression or checkpoint activation represent important events that may increase susceptibility to the onset of carcinogenesis. The atypical cyclin-like protein Spy1 was isolated in a screen for novel genes that could bypass the DNA damage response. Clinical data demonstrates that protein levels of Spy1 are significantly elevated in ductal and lobular carcinoma of the breast. We hypothesized that elevated Spy1 would override protective cell cycle checkpoints and support the onset of mammary tumourigenesis.

Methods

We generated a transgenic mouse model driving expression of Spy1 in the mammary epithelium. Mammary development, growth characteristics and susceptibility to tumourigenesis were studied. In vitro studies were conducted to investigate the relationship between Spy1 and p53.

Results

We found that in the presence of wild-type p53, Spy1 protein is held ‘in check’ via protein degradation, representing a novel endogenous mechanism to ensure protected checkpoint control. Regulation of Spy1 by p53 is at the protein level and is mediated in part by Nedd4. Mutation or abrogation of p53 is sufficient to allow for accumulation of Spy1 levels resulting in mammary hyperplasia. Sustained elevation of Spy1 results in elevated proliferation of the mammary gland and susceptibility to tumourigenesis.

Conclusions

This mouse model demonstrates for the first time that degradation of the cyclin-like protein Spy1 is an essential component of p53-mediated tumour suppression. Targeting cyclin-like protein activity may therefore represent a mechanism of re-sensitizing cells to important cell cycle checkpoints in a therapeutic setting.

Identification of two novel breast cancer loci through large-scale genome-wide association study in the Japanese population

Genome-wide association studies (GWAS) have successfully identified about 70 genomic loci associated with breast cancer. Owing to the complexity of linkage disequilibrium and environmental exposures in different populations, it is essential to perform regional GWAS for better risk prediction. This study aimed to investigate the genetic architecture and to assess common genetic risk model of breast cancer with 6,669 breast cancer patients and 21,930 female controls in the Japanese population. This GWAS identified 11 genomic loci that surpass genome-wide significance threshold of P < 5.0 × 10⁻⁸ with nine previously reported loci and two novel loci that include rs9862599 on 3q13.11 (ALCAM) and rs75286142 on 21q22.12 (CLIC6-RUNX1). Validation study was carried out with 981 breast cancer cases and 1,394 controls from the Aichi Cancer Center. Pathway analyses of GWAS signals identified association of dopamine receptor medicated signaling and protein amino acid deacetylation with breast cancer. Weighted genetic risk score showed that individuals who were categorized in the highest risk group are approximately 3.7 times more likely to develop breast cancer compared to individuals in the lowest risk group. This well-powered GWAS is a representative study to identify SNPs that are associated with breast cancer in the Japanese population.

Update Breast Cancer 2019 Part 4 - Diagnostic and Therapeutic Challenges of New, Personalised Therapies for Patients with Early Breast Cancer

The further development of therapies for women with early breast cancer is progressing far more slowly than in the case of patients with advanced breast cancer and is additionally delayed compared to developments in metastatic breast cancer. Nonetheless, significant advancements have been able to be recorded recently. This review summarises the latest developments in view of the most recent publications and professional conferences. For hormone-receptor-positive patients, new aspects for the duration of antihormone therapy and with regard to the benefits of multigene tests have been published. In the case of HER2-positive patients, the value of post-neoadjuvant therapy and de-escalation of the therapy is discussed. In patients with triple-negative breast cancer, there is a question of whether the knowledge of the biological background of a homologous recombination deficiency (HRD) helps develop new therapies for this subtype. In particular the "use" of a BRCA1/2 mutation or the biological characteristic HRD as a potential motive for therapy plays a role here in specifying the significance of platinum therapy and therapy with PARP inhibitors.

DNA damage and hormone-related cancer: a repair pathway view

In this short review, we examine the overlap between genes known to be mutated in the germlines of individuals at risk of breast, ovarian and prostate cancers, and their positions in DNA damage repair pathways. Cancer risk mutations have been consistently reported in certain genes at the top of these pathways, but none have been reported in others. We consider whether some of these gene products are too crucial to life for mutations to be tolerated, whilst others, further down the pathways, are less essential.

Recent advances of therapeutic targets based on the molecular signature in breast cancer: genetic mutations and implications for current treatment paradigms

Breast cancer is the most common malignancy in women all over the world. Genetic background of women contributes to her risk of having breast cancer. Certain inherited DNA mutations can dramatically increase the risk of developing certain cancers and are responsible for many of the cancers that run in some families. Regarding the widespread multigene panels, whole exome sequencing is capable of providing the evaluation of genetic function mutations for development novel strategy in clinical trials. Targeting the mutant proteins involved in breast cancer can be an effective therapeutic approach for developing novel drugs. This systematic review discusses gene mutations linked to breast cancer, focusing on signaling pathways that are being targeted with investigational therapeutic strategies, where clinical trials could be potentially initiated in the future are being highlighted.

Systematic evaluation of cancer-specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts

BACKGROUND

Genetic risk score (GRS) is an odds ratio (OR)-weighted and population-standardized method for measuring cumulative effect of multiple risk-associated single nucleotide polymorphisms (SNPs). We hypothesize that GRS is a valid tool for risk assessment of most common cancers.

METHODS

Utilizing genotype and phenotype data from The Cancer Genome Atlas (TCGA) and Electronic Medical Records and Genomics (eMERGE), we tested 11 cancer-specific GRSs (bladder, breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, prostate, renal, and thyroid cancer) for association with the respective cancer type. Cancer-specific GRSs were calculated, for the first time in these cohorts, based on previously published risk-associated SNPs using the Caucasian subjects in these two cohorts.

RESULTS

Mean cancer-specific GRS in the population controls of eMERGE approximated the expected value of 1.00 (between 0.98 and 1.02) for all 11 types of cancer. Mean cancer-specific GRS was consistently higher in respective cancer patients than controls for all 11 types of cancer (P < 0.05). When subjects were categorized into low-, average-, and high-risk groups based on cancer-specific GRS (<0.5, 0.5-1.5, and >1.5, respectively), significant dose-response associations of higher cancer-specific GRS with higher OR of respective type of cancer were found for nine types of cancer (P_-trend  < 0.05). More than 64% subjects in the population controls of eMERGE can be classified as high risk for at least one type of these cancers.

CONCLUSION

Validity of GRS for predicting cancer risk is demonstrated for most types of cancer. If confirmed in larger studies, cancer-specific GRS may have the potential for developing personalized cancer screening strategy.

Height and Body Mass Index as Modifiers of Breast Cancer Risk in BRCA1/2 Mutation Carriers: A Mendelian Randomization Study

BACKGROUND

BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear.

METHODS

We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided.

RESULTS

Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer.

CONCLUSION

Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.

Cross-Cancer Pleiotropic Associations with Lung Cancer Risk in African Americans

BACKGROUND

Identifying genetic variants with pleiotropic associations across multiple cancers can reveal shared biologic pathways. Prior pleiotropic studies have primarily focused on European-descent individuals. Yet population-specific genetic variation can occur, and potential pleiotropic associations among diverse racial/ethnic populations could be missed. We examined cross-cancer pleiotropic associations with lung cancer risk in African Americans.

METHODS

We conducted a pleiotropic analysis among 1,410 African American lung cancer cases and 2,843 controls. We examined 36,958 variants previously associated (or in linkage disequilibrium) with cancer in prior genome-wide association studies. Logistic regression analyses were conducted, adjusting for age, sex, global ancestry, study site, and smoking status.

RESULTS

We identified three novel genomic regions significantly associated (FDR-corrected P <0.10) with lung cancer risk (rs336958 on 5q14.3, rs7186207 on 16q22.2, and rs11658063 on 17q12). On chromosome16q22.2, rs7186207 was significantly associated with reduced risk [OR = 0.43; 95% confidence interval (CI), 0.73-0.89], and functional annotation using GTEx showed rs7186207 modifies DHODH gene expression. The minor allele at rs336958 on 5q14.3 was associated with increased lung cancer risk (OR = 1.47; 95% CI, 1.22-1.78), whereas the minor allele at rs11658063 on 17q12 was associated with reduced risk (OR = 0.80; 95% CI, 0.72-0.90).

CONCLUSIONS

We identified novel associations on chromosomes 5q14.3, 16q22.2, and 17q12, which contain HNF1B, DHODH, and HAPLN1 genes, respectively. SNPs within these regions have been previously associated with multiple cancers. This is the first study to examine cross-cancer pleiotropic associations for lung cancer in African Americans.

IMPACT

Our findings demonstrate novel cross-cancer pleiotropic associations with lung cancer risk in African Americans.

Matching tRNA modifications in humans to their known and predicted enzymes

tRNA are post-transcriptionally modified by chemical modifications that affect all aspects of tRNA biology. An increasing number of mutations underlying human genetic diseases map to genes encoding for tRNA modification enzymes. However, our knowledge on human tRNA-modification genes remains fragmentary and the most comprehensive RNA modification database currently contains information on approximately 20% of human cytosolic tRNAs, primarily based on biochemical studies. Recent high-throughput methods such as DM-tRNA-seq now allow annotation of a majority of tRNAs for six specific base modifications. Furthermore, we identified large gaps in knowledge when we predicted all cytosolic and mitochondrial human tRNA modification genes. Only 48% of the candidate cytosolic tRNA modification enzymes have been experimentally validated in mammals (either directly or in a heterologous system). Approximately 23% of the modification genes (cytosolic and mitochondrial combined) remain unknown. We discuss these 'unidentified enzymes' cases in detail and propose candidates whenever possible. Finally, tissue-specific expression analysis shows that modification genes are highly expressed in proliferative tissues like testis and transformed cells, but scarcely in differentiated tissues, with the exception of the cerebellum. Our work provides a comprehensive up to date compilation of human tRNA modifications and their enzymes that can be used as a resource for further studies.