A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density

Potential Role of Zinc Finger 365 rs10822013 and rs10995190 in Mammographic Density, Sporadic Breast Cancer Risk, and Prognosis

Background

Despite suggesting many genetic risk markers as the outcome of Genome-wide association studies (GWAS) for breast cancer, replicating the results in different populations has remained the main issue. In this regard, this study assessed the association of two variations in Zinc Finger 365 (ZNF365) in an Iranian population.

Methods

In a case-control study conducted at Mashhad University of Medical Sciences, Mashhad, Iran, between 2017 and 2020, ZNF365-rs10822013 and rs10995190 were genotyped using Allele-Specific PCR (AS-PCR). Breast density was assessed using mammography images. PHASE software module version 2 and SPSS version 16.0 were used for haplotype and statistical analyses. Quantitative and qualitative variables were compared between groups using independent t tests and Chi square tests, respectively. Binary logistic regression analysis was performed to calculate odds ratios. Multivariate analysis was then undertaken for the baseline variables, with a P<0.05 in the univariate analysis. The survival analysis was performed using the Kaplan-Meier method and the log-rank test.

Results

In this survey, 732 females, including 342 breast cancer patients and 390 healthy subjects, were enrolled. rs10822013-T allele (P=0.014), rs10995190-G allele (P=0.003), and TG haplotype (P=0.002) were significantly associated with the increased risk of breast cancer. Moreover, rs10995190-GG genotype (P=0.042) and C-G haplotype (P=0.019) revealed a significant association with better overall survival. However, considered polymorphisms and their haplotypes indicated no association with breast density and clinical features of breast cancer.

Conclusion

ZNF365 variants might be a potential risk marker of breast cancer in the Iranian population. The interaction between alleles in haplotypes may modulate the amount of the risk conferred by these variants. Further studies on different ethnic groups can validate these results.

AUTOSURV: INTERPRETABLE DEEP LEARNING FRAMEWORK FOR CANCER SURVIVAL ANALYSIS INCORPORATING CLINICAL AND MULTI-OMICS DATA

Accurate prognosis for cancer patients can provide critical information for optimizing treatment plans and improving life quality. Combining omics data and demographic/clinical information can offer a more comprehensive view of cancer prognosis than using omics or clinical data alone and can reveal the underlying disease mechanisms at the molecular level. In this study, we developed a novel deep learning framework to extract information from high-dimensional gene expression and miRNA expression data and conduct prognosis prediction for breast cancer and ovarian cancer patients. Our model achieved significantly better prognosis prediction than the conventional Cox Proportional Hazard model and other competitive deep learning approaches in various settings. Moreover, an interpretation approach was applied to tackle the "black-box" nature of deep neural networks and we identified features (i.e., genes, miRNA, demographic/clinical variables) that made important contributions to distinguishing predicted high- and low-risk patients. The identified associations were partially supported by previous studies.

Update Breast Cancer 2023 Part 1 - Early Stage Breast Cancer

With abemaciclib (monarchE study) and olaparib (OlympiA study) gaining approval in the adjuvant treatment setting, a significant change in the standard of care for patients with early stage breast cancer has been established for some time now. Accordingly, some diverse developments are slowly being transferred from the metastatic to the adjuvant treatment setting. Recently, there have also been positive reports of the NATALEE study. Other clinical studies are currently investigating substances that are already established in the metastatic setting. These include, for example, the DESTINY Breast05 study with trastuzumab deruxtecan and the SASCIA study with sacituzumab govitecan. In this review paper, we summarize and place in context the latest developments over the past months.

The correlation of leukocyte-specific protein 1 (LSP1) rs3817198(T>C) polymorphism with breast cancer: A meta-analysis

BACKGROUND

Multiple studies have investigated the correlation of single nucleotide polymorphisms (SNPs) in leukocyte-specific protein 1 (LSP1) with susceptibility to breast cancer (BC) and have yielded inconsistent conclusions, particularly rs3817198(T > C). Consequently, we performed a meta-analysis to estimate this relationship more comprehensively.

METHODS

Four databases were utilized to locate eligible publications: PubMed, Embase, Web of Science, and China National Knowledge Infrastructure. This meta-analysis included 14 studies, including 22 reports of 33194 cases and 36661 controls. The relationship of rs3817198 polymorphism with breast cancer was estimated using odds ratios (ORs) with 95% confidence intervals (CIs). The LSP1 co-expression network was constructed by STRING, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using DAVIDE. Download TCGA breast cancer mRNA-seq data and analyze the relationship between LSP1 expression and breast cancer chemotherapy sensitivity.

RESULTS

The results indicated that rs3817198(T > C) was positively correlated to with breast malignancy (dominant model: OR = 1.11, 95%CI = 1.06-1.17; recessive model: OR = 1.10, 95%CI = 1.04-1.15; heterozygous model: OR = 1.09, 95%CI = 1.04-1.15; homozygous model: OR = 1.18, 95%CI = 1.09-1.28; additive model: OR = 1.09, 95%CI = 1.05-1.13), among Caucasians and Asians. However, rs3817198(T > C) may reduce the risk of breast carcinoma in Africans. Rs3817198(T > C) might result in breast carcinoma in individuals with BRCA1 and BRCA2 variants and can contribute to estrogen receptor (ER)-positive breast carcinoma. The expression of LSP1 was inversely correlated with the IC50 of doxorubicin (P = 8.91e-15, Cor = -0.23), 5-fluorouracil (P = 1.18e-22, Cor = -0.29), and cisplatin (P = 1.35e-42, Cor = -0.40).

CONCLUSION

Our study identified that LSP1 rs3817198 polymorphism might result in breast malignancy, particularly among Caucasians and Asians, but lower breast cancer susceptibility in African populations. The expression of LSP1 was negatively correlated with the IC50 of doxorubicin, 5-fluorouracil, and cisplatin.

Cross-ancestry Genome-wide Association Studies of Sex Hormone Concentrations in Pre- and Postmenopausal Women

OBJECTIVE

Concentrations of circulating sex hormones have been associated with a variety of diseases in women and are strongly influenced by menopausal status. We investigated the genetic architectures of circulating concentrations of estradiol, testosterone, and SHBG by menopausal status in women of European and African ancestry.

METHODS

Using data on 229 966 women from the UK Biobank, we conducted genome-wide association studies (GWASs) of circulating concentrations of estradiol, testosterone, and SHBG in premenopausal and postmenopausal women. We tested for evidence of heterogeneity of genetic effects by menopausal status and genetic ancestry. We conducted gene-based enrichment analyses to identify tissues in which genes with GWAS-enriched signals were expressed.

RESULTS

We identified 4 loci (5q35.2, 12q14.3, 19q13.42, 20p12.3) that were associated with detectable concentrations of estradiol in both pre- and postmenopausal women of European ancestry. Heterogeneity analysis identified 1 locus for testosterone (7q22.1) in the CYP3A7 gene and 1 locus that was strongly associated with concentrations of SHBG in premenopausal women only (10q15.1) near the AKR1C4 gene. Gene-based analysis of testosterone revealed evidence of enrichment of GWAS signals in genes expressed in adipose tissue for postmenopausal women. We did not find any evidence of ancestry-specific genetic effects for concentrations of estradiol, testosterone, or SHBG.

CONCLUSIONS

We identified specific loci that showed genome-wide significant evidence of heterogeneity by menopausal status for testosterone and SHBG. We also observed support for a more prominent role of genetic variants located near genes expressed in adipose tissue in determining testosterone concentrations among postmenopausal women.

The role of PLCγ2 in immunological disorders, cancer, and neurodegeneration

Phosphatidylinositol-specific phospholipase Cγ2 (PLCγ2) is a critical signaling molecule activated downstream from a variety of cell surface receptors that contain an intracellular immunoreceptor tyrosine-based activation motif. These receptors recruit kinases such as Syk, BTK, and BLNK to phosphorylate and activate PLCγ2, which then generates 1D-myo-inositol 1,4,5-trisphosphate and diacylglycerol. These well-known second messengers are required for diverse membrane functionality including cellular proliferation, endocytosis, and calcium flux. As a result, PLCγ2 dysfunction is associated with a variety of diseases including cancer, neurodegeneration, and immune disorders. The diverse pathologies associated with PLCγ2 are exemplified by distinct genetic variants. Inherited mutations at this locus cause PLCγ2-associated antibody deficiency and immune dysregulation, in some cases with autoinflammation. Acquired mutations at this locus, which often arise as a result of BTK inhibition to treat chronic lymphocytic leukemia, result in constitutive downstream signaling and lymphocyte proliferation. Finally, a third group of PLCγ2 variants actually has a protective effect in a variety of neurodegenerative disorders, presumably by increased uptake and degradation of deleterious neurological aggregates. Therefore, manipulating PLCγ2 activity either up or down could have therapeutic benefit; however, we require a better understanding of the signaling pathways propagated by these variants before such clinical utility can be realized. Here, we review the signaling roles of PLCγ2 in hematopoietic cells to help understand the effect of mutations driving immune disorders and cancer and extrapolate from this to roles which may relate to protection against neurodegeneration.

Evaluation of association studies and a systematic review and meta-analysis of CYP1A1 T3801C and A2455G polymorphisms in breast cancer risk

Background

Nine previous meta-analyses have been published to analyze the CYP1A1 T3801C and A2455G polymorphisms with BC risk. However, they did not assess the credibility of statistically significant associations. In addition, many new studies have been reported on the above themes. Hence, we conducted an updated systematic review and meta-analysis to further explore the above issues.

Objectives

To explore the association on the CYP1A1 T3801C and A2455G polymorphisms with BC risk.

Methods

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (The PRISMA) were used.

Results

In this study, there were 63 case–control studies from 56 publications on the CYP1A1 T3801C polymorphism (including 20,825 BC cases and 25,495 controls) and 51 case–control studies from 46 publications on the CYP1A1 A2455G polymorphism (including 20,124 BC cases and 29,183 controls). Overall, the CYP1A1 T3801C polymorphism was significantly increased BC risk in overall analysis, especially in Asians and Indians; the CYP1A1 A2455G polymorphism was associated with BC risk in overall analysis, Indians, and postmenopausal women. However, when we used BFDP correction, associations remained significant only in Indians (CC vs. TT + TC: BFDP < 0.001) for the CYP1A1 T3801C polymorphism with BC risk, but not in the CYP1A1 A2455G polymorphism. In addition, when we further performed sensitivity analysis, no significant association in overall analysis and any subgroup. Moreover, we found that all studies from Indians was low quality. Therefore, the results may be not credible.

Conclusion

This meta-analysis strongly indicates that there is no significant association between the CYP1A1 T3801C and A2455G polymorphisms and BC risk. The increased BC risk may most likely on account of false-positive results.

Genetic Variation and Hot Flashes: A Systematic Review

CONTEXT

Approximately 70% of women report experiencing vasomotor symptoms (VMS, hot flashes and/or night sweats). The etiology of VMS is not clearly understood but may include genetic factors.

EVIDENCE ACQUISITION

We searched PubMed and Embase in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. We included studies on associations between genetic variation and VMS. We excluded studies focused on medication interventions or prevention or treatment of breast cancer.

EVIDENCE SYNTHESIS

Of 202 unique citations, 18 citations met the inclusion criteria. Study sample sizes ranged from 51 to 17 695. Eleven of the 18 studies had fewer than 500 participants; 2 studies had 1000 or more. Overall, statistically significant associations with VMS were found for variants in 14 of the 26 genes assessed in candidate gene studies. The cytochrome P450 family 1 subfamily A member 1 (CYP1B1) gene was the focus of the largest number (n = 7) of studies, but strength and statistical significance of associations of CYP1B1 variants with VMS were inconsistent. A genome-wide association study reported statistically significant associations between 14 single-nucleotide variants in the tachykinin receptor 3 gene and VMS. Heterogeneity across trials regarding VMS measurement methods and effect measures precluded quantitative meta-analysis; there were few studies of each specific genetic variant.

CONCLUSIONS

Genetic variants are associated with VMS. The associations are not limited to variations in sex-steroid metabolism genes. However, studies were few and future studies are needed to confirm and extend these findings.

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.

Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses

Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important because the mechanisms through which they are associated with breast cancer are not well known. Here, using mammographic screening history and detailed questionnaire data from 56,820 women from the KARMA prospective cohort study, we investigated the association between a genetic predisposition to breast cancer and mammographic features among women with a family history of breast cancer (N = 49,674) and a polygenic risk score (PRS, N = 9,365). The heritability of mammographic features such as dense area (MD), microcalcifications, masses, and density change (MDC, cm²/year) was estimated using 1,940 sister pairs. Heritability was estimated at 58% [95% confidence interval (CI), 48%-67%) for MD, 23% (2%-45%) for microcalcifications, and 13% (1%-25%)] for masses. The estimated heritability for MDC was essentially null (2%; 95% CI, -8% to 12%). The association between a genetic predisposition to breast cancer (using PRS) and MD and microcalcifications was positive, while for masses this was borderline significant. In addition, for MDC, having a family history of breast cancer was associated with slightly greater MD reduction. In summary, we have confirmed previous findings of heritability in MD, and also established heritability of the number of microcalcifications and masses at baseline. Because these features are associated with breast cancer risk and can improve detecting women at short-term risk of breast cancer, further investigation of common loci associated with mammographic features is warranted to better understand the etiology of breast cancer. SIGNIFICANCE: These findings provide novel data on the heritability of microcalcifications, masses, and density change, which are all associated with breast cancer risk and can indicate women at short-term risk.

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.

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.

Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration

Purpose

Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability.

Methods

We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis.

Results

We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) "drive" the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P < 0.0001) across KEGG, Reactome, GO, and NetPath pathways.

Conclusions

We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD.

Primary Sclerosing Cholangitis, Part 2: Cancer Risk, Prevention, and Surveillance

Primary sclerosing cholangitis (PSC) is a chronic, fibroinflammatory, progressive cholangiopathy. In a clinically significant proportion of patients, the disease course of PSC is punctuated by carcinogenesis, namely cholangiocarcinoma, gallbladder carcinoma, hepatocellular carcinoma, and/or colorectal carcinoma. Indeed, malignancy is arguably the most consequential sequela and the cause of nearly 50% of deaths in patients with PSC. This statistic is multifactorial, relating partly to the premalignant nature of PSC, challenges in diagnosis due to obscuration of cancer by the inflammation and fibrosis inherent to PSC, and the unpredictability of which type of cancer will develop in PSC and when. Here, in the second of a 2-part series, we review cancer risk, prevention, and surveillance in patients with PSC. We also discuss potential cancer surveillance strategies in PSC and, where evidence is limited, make pragmatic recommendations based on current data and expert opinion.

Risk, Prediction and Prevention of Hereditary Breast Cancer - Large-Scale Genomic Studies in Times of Big and Smart Data

Over the last two decades genetic testing for mutations in BRCA1 and BRCA2 has become standard of care for women and men who are at familial risk for breast or ovarian cancer. Currently, genetic testing more often also includes so-called panel genes, which are assumed to be moderate-risk genes for breast cancer. Recently, new large-scale studies provided more information about the risk estimation of those genes. The utilization of information on panel genes with regard to their association with the individual breast cancer risk might become part of future clinical practice. Furthermore, large efforts have been made to understand the influence of common genetic variants with a low impact on breast cancer risk. For this purpose, almost 450 000 individuals have been genotyped for almost 500 000 genetic variants in the OncoArray project. Based on first results it can be assumed that – together with previously identified common variants – more than 170 breast cancer risk single nucleotide polymorphisms can explain up to 18% of familial breast cancer risk. The knowledge about genetic and non-genetic risk factors and its implementation in clinical practice could especially be of use for individualized prevention. This includes an individualized risk prediction as well as the individualized selection of screening methods regarding imaging and possible lifestyle interventions. The aim of this review is to summarize the most recent developments in this area and to provide an overview on breast cancer risk genes, risk prediction models and their utilization for the individual patient.

Refining Breast Cancer Risk Stratification: Additional Genes, Additional Information

Recent advances in genomic technology have enabled far more rapid, less expensive sequencing of multiple genes than was possible only a few years ago. Advances in bioinformatics also facilitate the interpretation of large amounts of genomic data. New strategies for cancer genetic risk assessment include multiplex sequencing panels of 5 to more than 100 genes (in which rare mutations are often associated with at least two times the average risk of developing breast cancer) and panels of common single-nucleotide polymorphisms (SNPs), combinations of which are generally associated with more modest cancer risks (more than twofold). Although these new multiple-gene panel tests are used in oncology practice, questions remain about the clinical validity and the clinical utility of their results. To translate this increasingly complex genetic information for clinical use, cancer risk prediction tools are under development that consider the joint effects of all susceptibility genes, together with other established breast cancer risk factors. Risk-adapted screening and prevention protocols are underway, with ongoing refinement as genetic knowledge grows. Priority areas for future research include the clinical validity and clinical utility of emerging genetic tests; the accuracy of developing cancer risk prediction models; and the long-term outcomes of risk-adapted screening and prevention protocols, in terms of patients' experiences and survival.

Challenges of Cholangiocarcinoma Detection in Patients with Primary Sclerosing Cholangitis

Primary sclerosing cholangitis (PSC) is a chronic, cholestatic, idiopathic liver disease characterized by fibro-obliterative inflammation of the hepatic bile ducts. In a clinically significant proportion of patients, PSC progresses to cirrhosis, end-stage liver disease, and in some cases, cholangiocarcinoma (CCA). The development of CCA in PSC is unpredictable, its surveillance and diagnosis complex, and its treatment options limited unless detected early. Herein we provide a focused review of the current literature regarding CCA surveillance in patients with PSC and discuss the diagnostic and management challenges that exist. Where evidence is limited, we present our perspective and approach as well as directions for future research.