Genomic Biomarkers for Breast Cancer Risk

Bioconjugates for Cancer Prevention: Opportunities for Impact

Cancer prevention encompasses both screening strategies to find cancers early when they are likely to be most treatable and prevention and interception strategies to reduce the risk of developing cancers. Bioconjugates, here defined broadly as materials and molecules that have synthetic and biological components, have roles to play across the cancer-prevention spectrum. In particular, bioconjugates may be developed as affordable, accessible, and effective screening strategies or as novel vaccines and drugs to reduce one's risk of developing cancers. Developmental programs are available for taking novel technologies and evaluating them for clinical use in cancer screening and prevention. While a variety of different challenges exist in implementing cancer-prevention interventions, a thoughtful approach to bioconjugates could improve the delivery and acceptability of the interventions.

Nucleolar Localization of the RNA Helicase DDX21 Predicts Survival Outcomes in Gynecologic Cancers

Cancer cells with DNA repair defects (e.g., BRCA1/2 mutant cells) are vulnerable to PARP inhibitors (PARPi) due to induction of synthetic lethality. However, recent clinical evidence has shown that PARPi can prevent the growth of some cancers irrespective of their BRCA1/2 status, suggesting alternative mechanisms of action. We previously discovered one such mechanism in breast cancer involving DDX21, an RNA helicase that localizes to the nucleoli of cells and is a target of PARP1. We have now extended this observation in endometrial and ovarian cancers and provided links to patient outcomes. When PARP1-mediated ADPRylation of DDX21 is inhibited by niraparib, DDX21 is mislocalized to the nucleoplasm resulting in decreased rDNA transcription, which leads to a reduction in ribosome biogenesis, protein translation, and ultimately endometrial and ovarian cancer cell growth. High PARP1 expression was associated with high nucleolar localization of DDX21 in both cancers. High nucleolar DDX21 negatively correlated with calculated IC50s for niraparib. By studying endometrial cancer patient samples, we were able to show that high DDX21 nucleolar localization was significantly associated with decreased survival. Our study suggests that the use of PARPi as a cancer therapeutic can be expanded to further types of cancers and that DDX21 localization can potentially be used as a prognostic factor and as a biomarker for response to PARPi.

SIGNIFICANCE

Currently, there are no reliable biomarkers for response to PARPi outside of homologous recombination deficiency. Herein we present a unique potential biomarker, with clear functional understanding of the molecular mechanism by which DDX21 nucleolar localization can predict response to PARPi.

Copper Chaperone for Superoxide Dismutase Subtypes as a Prognostic Marker in Luminal B Breast Cancer

Background

Copper chaperone for superoxide dismutase (CCS) is an essential component of the oxidation-reduction system. In breast cancer cells, CCS expression is highly up-regulated, which contributes to cellular proliferation and migration. Breast cancer is a multifaceted disease with different tumor prognoses and responses to clinical treatments, which may be associated with multiple molecular subtypes of CCS.

Methods

The CCS expression patterns in breast cancer were investigated by TNMplot, cBioPortal, and HPA network database. The correlation of CCS expression with clinicopathological parameters was analyzed using the UALCAN database. The Cancer Genome Atlas (TCGA) data set was used to analyze the Clinical characteristics of CCS in luminal B patients. The bc-GenExMiner database was used to analyze the effects of BReast-CAncer susceptibility gene (BRCA)1/2, TP53 mutation status, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER) expression on CCS expression. The survival curves and prognostic value of CCS in luminal B breast cancer were performed through Kaplan-Meier curves, univariate and multivariate Cox regression using the PrognoScan, bc-GenExMiner, and Clinical bioinformatics analysis platform.

Results

We found that CCS expression was associated with patient age, race, ER, and PR status. We also discovered that BRCA1/2 mutations had an effect on CCS expression. The luminal B subtype had the highest CCS expression, which was linked to poor survival compared with other subtypes. In addition, Kaplan-Meier curve analysis showed that luminal B patients with high CCS mRNA expression showed a poor survival and the CCS gene is an independent predictor of outcome in patients with luminal B breast cancer by univariate and multivariate Cox regression.

Conclusions

Our findings emphasize the significant expression of CCS in luminal B breast cancer and its potential as an autonomous prognostic determinant for this specific molecular subtype. These findings suggest that CCS holds promise as a prospective marker for the treatment of luminal B breast cancer.

Nutritional Genomics and Cancer Prevention

The scientific innovations have emphasized the importance of diet for one's health and wellbeing. The genetic revolution has enhanced our understanding about the effect of nutrients on genomic and transcriptomic profiles and gene-nutrition interactions (nutritional genomics). Furthermore, the contribution of micronutrient insufficiencies and macronutrient excess is evident in the development and progression of many diseases, especially cancer. It is speculated that nutrients have capacity to implicitly affect the physiological and pathophysiological processes via gene expression various regulatory processes. Moreover, the nutrients are known to affect the cellular networks involved in cancer progression and cancer inhibitory mechanisms targeting apoptosis or impaired angiogenesis. The interplay of regulatory processes in physiological systems and nutrients provides basis for the nutrigenomics. The functional genomics data further argue that cellular and molecular processes involved in the cancer progression are possibly programed genes during early development which may persist into adulthood and become detrimental. The incorporation of the functional interactions between nutrients and the genome has revolutionized the field of personalized medicine and provided the foundation for targeted cancer therapy through nutrients. There is growing evidence on the beneficial impacts of eating habits on lowering the risk of cancer, even if it can be difficult to pinpoint the precise role of nutrients. The nutrigenomic information may provide bases to develop disease prevention and treatment via nutrition, at the molecular level.

Extensive review on breast cancer its etiology, progression, prognostic markers, and treatment

As the most frequent and vulnerable malignancy among women, breast cancer universally manifests a formidable healthcare challenge. From a biological and molecular perspective, it is a heterogenous disease and is stratified based on the etiological factors driving breast carcinogenesis. Notably, genetic predispositions and epigenetic impacts often constitute the heterogeneity of this disease. Typically, breast cancer is classified intrinsically into histological subtypes in clinical landscapes. These stratifications empower physicians to tailor precise treatments among the spectrum of breast cancer therapeutics. In this pursuit, numerous prognostic algorithms are extensively characterized, drastically changing how breast cancer is portrayed. Therefore, it is a basic requisite to comprehend the multidisciplinary rationales of breast cancer to assist the evolution of novel therapeutic strategies. This review aims at highlighting the molecular and genetic grounds of cancer additionally with therapeutic and phytotherapeutic context. Substantially, it also renders researchers with an insight into the breast cancer cell lines as a model paradigm for breast cancer research interventions.

Omics-Based Investigations of Breast Cancer

Breast cancer (BC) is characterized by an extensive genotypic and phenotypic heterogeneity. In-depth investigations into the molecular bases of BC phenotypes, carcinogenesis, progression, and metastasis are necessary for accurate diagnoses, prognoses, and therapy assessments in predictive, precision, and personalized oncology. This review discusses both classic as well as several novel omics fields that are involved or should be used in modern BC investigations, which may be integrated as a holistic term, onco-breastomics. Rapid and recent advances in molecular profiling strategies and analytical techniques based on high-throughput sequencing and mass spectrometry (MS) development have generated large-scale multi-omics datasets, mainly emerging from the three "big omics", based on the central dogma of molecular biology: genomics, transcriptomics, and proteomics. Metabolomics-based approaches also reflect the dynamic response of BC cells to genetic modifications. Interactomics promotes a holistic view in BC research by constructing and characterizing protein-protein interaction (PPI) networks that provide a novel hypothesis for the pathophysiological processes involved in BC progression and subtyping. The emergence of new omics- and epiomics-based multidimensional approaches provide opportunities to gain insights into BC heterogeneity and its underlying mechanisms. The three main epiomics fields (epigenomics, epitranscriptomics, and epiproteomics) are focused on the epigenetic DNA changes, RNAs modifications, and posttranslational modifications (PTMs) affecting protein functions for an in-depth understanding of cancer cell proliferation, migration, and invasion. Novel omics fields, such as epichaperomics or epimetabolomics, could investigate the modifications in the interactome induced by stressors and provide PPI changes, as well as in metabolites, as drivers of BC-causing phenotypes. Over the last years, several proteomics-derived omics, such as matrisomics, exosomics, secretomics, kinomics, phosphoproteomics, or immunomics, provided valuable data for a deep understanding of dysregulated pathways in BC cells and their tumor microenvironment (TME) or tumor immune microenvironment (TIMW). Most of these omics datasets are still assessed individually using distinct approches and do not generate the desired and expected global-integrative knowledge with applications in clinical diagnostics. However, several hyphenated omics approaches, such as proteo-genomics, proteo-transcriptomics, and phosphoproteomics-exosomics are useful for the identification of putative BC biomarkers and therapeutic targets. To develop non-invasive diagnostic tests and to discover new biomarkers for BC, classic and novel omics-based strategies allow for significant advances in blood/plasma-based omics. Salivaomics, urinomics, and milkomics appear as integrative omics that may develop a high potential for early and non-invasive diagnoses in BC. Thus, the analysis of the tumor circulome is considered a novel frontier in liquid biopsy. Omics-based investigations have applications in BC modeling, as well as accurate BC classification and subtype characterization. The future in omics-based investigations of BC may be also focused on multi-omics single-cell analyses.

Applying Explainable Machine Learning Models for Detection of Breast Cancer Lymph Node Metastasis in Patients Eligible for Neoadjuvant Treatment

BACKGROUND

Due to recent changes in breast cancer treatment strategy, significantly more patients are treated with neoadjuvant systemic therapy (NST). Radiological methods do not precisely determine axillary lymph node status, with up to 30% of patients being misdiagnosed. Hence, supplementary methods for lymph node status assessment are needed. This study aimed to apply and evaluate machine learning models on clinicopathological data, with a focus on patients meeting NST criteria, for lymph node metastasis prediction.

METHODS

From the total breast cancer patient data (n = 8381), 719 patients were identified as eligible for NST. Machine learning models were applied for the NST-criteria group and the total study population. Model explainability was obtained by calculating Shapley values.

RESULTS

In the NST-criteria group, random forest achieved the highest performance (AUC: 0.793 [0.713, 0.865]), while in the total study population, XGBoost performed the best (AUC: 0.762 [0.726, 0.795]). Shapley values identified tumor size, Ki-67, and patient age as the most important predictors.

CONCLUSION

Tree-based models achieve a good performance in assessing lymph node status. Such models can lead to more accurate disease stage prediction and consecutively better treatment selection, especially for NST patients where radiological and clinical findings are often the only way of lymph node assessment.

Construction of model animals to explore intestinal microbiome for detection of breast cancer

Breast cancer ranks first among female cancers and has become a major public health problem in the current society. More studies indicated that these cancers are related to the change in the gut microbiome that can cause metabolic and immune system disorders in the body. However, there are few studies on the changes in gut microbiome caused by the onset of breast cancer, and the relationship between breast cancer and gut microbiome needs to be further clarified. In this study, we inoculated 4T1 breast cancer cells to induce breast cancer tumorigenesis in mice and collected their feces samples at different stages during this process. These intestinal florae were analyzed using 16S rRNA gene amplicon sequencing, and the results showed that at the phylum level, the ratio of Firmicutes/Bacteroidetes decreased with the development of the tumor; at the family level, the intestinal microbiome had obvious variations of Lachnospiraceae, Bacteroidaceae, Erysipelotrichaceae, etc. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and COG annotation demonstrated that decreased abundance of cancer-related signaling pathways. This study elucidated the relationship between breast cancer and intestinal microbiome, and the research results can be used as an important biomarker for the diagnosis of breast cancer.

Genetic instability-related lncRNAs predict prognosis and influence the immune microenvironment in breast cancer

Genome instability is a hallmark of cancer, and the function of lncRNAs in regulating genomic stability has been gradually characterized. However, the prognostic value of lncRNAs related to genetic instability has not been found in breast cancer. Here we constructed a genetic instability-related lncRNA model including U62317.4, SEMA3B-AS1, MAPT-AS1, AC115837.2, LINC01269, AL645608.7, and GACAT2. This model can evaluate the risk and predict the survival outcomes of patients. Further analysis showed that the differentially expressed genes between the high- and low-risk groups were enriched in immunity and cornified envelope formation pathways. In addition, M2 macrophages infiltrated more obviously in the high-risk group. In summary, lncRNAs related to genetic instability may influence the development of breast cancer through immune infiltration and keratinization. This study provides a wider insight into breast cancer development and treatment.

Artificial intelligence to identify genetic alterations in conventional histopathology

Precision oncology relies on the identification of targetable molecular alterations in tumor tissues. In many tumor types, a limited set of molecular tests is currently part of standard diagnostic workflows. However, universal testing for all targetable alterations, especially rare ones, is limited by the cost and availability of molecular assays. From 2017 to 2021, multiple studies have shown that artificial intelligence (AI) methods can predict the probability of specific genetic alterations directly from conventional hematoxylin and eosin (H&E) tissue slides. Although these methods are currently less accurate than gold-standard testing (e.g. immunohistochemistry, polymerase chain reaction or next-generation sequencing), they could be used as pre-screening tools to reduce the workload of genetic analyses. In this systematic literature review, we summarize the state of the art in predicting molecular alterations from H&E using AI. We found that AI methods perform reasonably well across multiple tumor types, although few algorithms have been broadly validated. In addition, we found that genetic alterations in FGFR, IDH, PIK3CA, BRAF, TP53 and DNA repair pathways are predictable from H&E in multiple tumor types, while many other genetic alterations have rarely been investigated or were only poorly predictable. Finally, we discuss the next steps for the implementation of AI-based surrogate tests in diagnostic workflows. This article is protected by copyright. All rights reserved.

The IL6-like Cytokine Family: Role and Biomarker Potential in Breast Cancer

IL6-like cytokines are a family of regulators with a complex, pleiotropic role in both the healthy organism, where they regulate immunity and homeostasis, and in different diseases, including cancer. Here we summarise how these cytokines exert their effect through the shared signal transducer IL6ST (gp130) and we review the extensive evidence on the role that different members of this family play in breast cancer. Additionally, we discuss how the different cytokines, their related receptors and downstream effectors, as well as specific polymorphisms in these molecules, can serve as predictive or prognostic biomarkers with the potential for clinical application in breast cancer. Lastly, we also discuss how our increasing understanding of this complex signalling axis presents promising opportunities for the development or repurposing of therapeutic strategies against cancer and, specifically, breast neoplasms.

Opposing effects of BRCA1 mRNA expression on patient survival in breast and colorectal cancer and variations among African American, Asian, and younger patients

Breast cancer (BC) and colorectal cancer (CRC) are common and show poor survival in advanced stages. Using The Cancer Genome Atlas (TCGA) computational tool cBioPortal, we evaluated overall patient survival in BRCA1 mRNA-low versus -high cohorts (<-1.29 versus >1.05 SD from mean BRCA1 expression, respectively). Analysis included 1082 BC patients with mRNA data (PanCancer Atlas), 382 CRCs (Firehose Legacy) and 592 CRCs (PanCancer Atlas). As previously reported, BRCA1 mRNA-low tumor expression positively correlated with BC patient survival but was negatively associated in CRC. We observed a correlation between BRCA1 mRNA-high and age <45 years at CRC diagnosis using a Fisher's exact test [Firehose Legacy database (p-value = 0.0091); CRC PanCancer Atlas (p-value = 0.0778)]. We correlated BRCA1 mRNA-low expression and basal BC (p-value = 0.0016) and BRCA1 mRNA-low tumors and frequency of African American patients (p-value = 0.0448) with BC. Other trends included higher frequency of advanced lymph node stage and mucinous adenocarcinoma among BRCA1 mRNA-low CRC and higher frequency of males in BRCA1 mRNA-high BC and CRC. African Americans more frequently had BRCA1 mRNA-low BC and BRCA1 mRNA-high CRC and the opposite was observed among Asians. Using a gene co-expression tool (cBioPortal), we observed TOP2A and ATAD5 levels correlate (Spearman's correlation>0.6) with BRCA1 in BC and CRC, whereas LMNB2 correlates with BRCA1 in CRC, suggesting tissue-specific BRCA1 interactions. Our results indicate potential for BRCA1 mRNA expression levels as a prognostic biomarker in BC and CRC, suggest tissue-specificity in BRCA1 molecular interactions, and point to BRCA1 mRNA-high levels as a characteristic of CRC tumors in younger versus older individuals.

In Silico-Analysis of the Multi-Omics Data Identified the Ataxia Telangiectasia Mutated Gene as a Potential Biomarker of Breast Invasive Carcinoma

Background: The elevated global burden of the breast invasive carcinoma (BRIC) and lack of appropriate biomarkers for its early detection and treatment requires extensive investigation to enhance understanding regarding BRIC associated molecular alterations. Ataxia telangiectasia mutated (ATM) is a multifunctional tumor suppressor gene, which participates in the DNA damage response pathway and cellular checkpoint activation. Several studies have reported the reduction of ATM expression as a reliable biomarker of BRIC. However, its role as a clinicopathological feature-specific biomarker still needs to be explored. Aim: The present study was designed to investigate the mutational spectrum and expression variations of ATM in BRIC patients exhibiting various clinicopathological features. Furthermore, we also performed a correlational analysis of clinicopathological feature-specific ATM expression with its promoter methylation, status genetic alterations, copy number variation (CNVs), overall survival (OS), and effectiveness of various anticancerous drugs in BRIC patients. Methods: We utilized multiple online platforms, including UALCN, cBioportal, and CCLE GDSC tool kit. Results: The ATM exhibited decreased expression in the majority of the BRIC patients, and its promoter was hypermethylated compared to healthy controls. Hence, the degree of promoter methylation and ATM expression level were inversely correlated in BRIC. In addition, we also investigated if BRIC patients that had higher ATM expression had lower OS. We found that elevated expression of ATM was found to promoted or decreased the effectiveness of various anticancer drugs. Conclusion: This study revealed the overall and clinicopathological feature-specific role of the ATM, gene, however, these findings need to be validated via larger scale studies.

Human Papillomavirus in Breast Carcinogenesis: A Passenger, a Cofactor, or a Causal Agent?

Simple Summary

Breast cancer (BC) is the most frequent tumor in women worldwide. A minority of BC patients have a family history of the disease, suggesting the importance of environmental and lifestyle factors. Human papillomavirus (HPV) infection has been detected in a subset of tumors, suggesting a potential role in BC. In this review, we summarized relevant information in respect to this topic and we propose a model of HPV-mediated breast carcinogenesis. Evidence suggests that breast tissue is accessible to HPV, which may be a causal agent of BC in a subset of cases.

Abstract

Breast cancer (BC) is the most commonly diagnosed malignancy in women worldwide as well as the leading cause of cancer-related death in this gender. Studies have identified that human papillomavirus (HPV) is a potential risk factor for BC development. While vaccines that protect against oncogenic HPVs infection have been commercially available, global disparities persist due to their high cost. Interestingly, numerous authors have detected an increased high risk (HR)-HPV infection in BC specimens when compared with non-tumor tissues. Therefore, it was suggested that HR-HPV infection could play a role in breast carcinogenesis in a subset of cases. Additional epidemiological and experimental evidence is still needed regarding the role of HR-HPV infection in the development and progression of BC.

The Signal Transducer IL6ST (gp130) as a Predictive and Prognostic Biomarker in Breast Cancer

Novel biomarkers are needed to continue to improve breast cancer clinical management and outcome. IL6-like cytokines, whose pleiotropic functions include roles in many hallmarks of malignancy, rely on the signal transducer IL6ST (gp130) for all their signalling. To date, 10 separate independent studies based on the analysis of clinical breast cancer samples have identified IL6ST as a predictor. Consistent findings suggest that IL6ST is a positive prognostic factor and is associated with ER status. Interestingly, these studies include 4 multigene signatures (EndoPredict, EER4, IRSN-23 and 42GC) that incorporate IL6ST to predict risk of recurrence or outcome from endocrine or chemotherapy. Here we review the existing evidence on the promising predictive and prognostic value of IL6ST. We also discuss how this potential could be further translated into clinical practice beyond the EndoPredict tool, which is already available in the clinic. The most promising route to further exploit IL6ST's promising predicting power will likely be through additional hybrid multifactor signatures that allow for more robust stratification of ER+ breast tumours into discrete groups with distinct outcomes, thus enabling greater refinement of the treatment-selection process.

A SEMA3 Signaling Pathway-Based Multi-Biomarker for Prediction of Glioma Patient Survival

Glioma is a lethal central nervous system tumor with poor patient survival prognosis. Because of the molecular heterogeneity, it is a challenge to precisely determine the type of the tumor and to choose the most effective treatment. Therefore, novel biomarkers are essential to improve the diagnosis and prognosis of glioma tumors. Class 3 semaphorin proteins (SEMA3) play an important role in tumor biology. SEMA3 transduce their signals by using neuropilin and plexin receptors, which functionally interact with the vascular endothelial growth factor-mediated signaling pathways. Therefore, the aim of this study was to explore the potential of SEMA3 signaling molecules for prognosis of glioma patient survival. The quantitative real-time PCR method was used to evaluate mRNA expression of SEMA3(A-G), neuropilins (NRP1 and NRP2), plexins (PLXNA2 and PLXND1), cadherins (CDH1 and CDH2), integrins (ITGB1, ITGB3, ITGA5, and ITGAV), VEGFA and KDR genes in 59 II-IV grade glioma tissues. Seven genes significantly associated with patient overall survival were used for multi-biomarker construction, which showed 64%, 75%, and 68% of accuracy of predicting the survival of 1-, 2-, and 3-year glioma patients, respectively. The results suggest that the seven-gene signature could serve as a novel multi-biomarker for more accurate prognosis of a glioma patient’s outcome.

Regulation and pharmacological targeting of RAD51 in cancer

Regulation of homologous recombination (HR) is central for cancer prevention. However, too little HR can increase cancer incidence, whereas too much HR can drive cancer resistance to therapy. Importantly, therapeutics targeting HR deficiency have demonstrated a profound efficacy in the clinic improving patient outcomes, particularly for breast and ovarian cancer. RAD51 is central to DNA damage repair in the HR pathway. As such, understanding the function and regulation of RAD51 is essential for cancer biology. This review will focus on the role of RAD51 in cancer and beyond and how modulation of its function can be exploited as a cancer therapeutic.

Targeting p53-MDM2 Interaction Using Small Molecule Inhibitors and the Challenges Needed to be Addressed

MDM2 protein is the core negative regulator of p53 that maintains the cellular levels of p53 at a low level in normal cells. Mutation of the TP53 gene accounts for 50% of all human cancers. In the remaining malignancies with wild-type TP53, p53 function is inhibited through other mechanisms. Recently, synthetic small molecule inhibitors have been developed which target a small hydrophobic pocket on MDM2 to which p53 normally binds. Given that MDM2-p53 antagonists have been undergoing clinical trials for different types of cancer, this review illustrates different aspects of these new cancer targeted therapeutic agents with the focus on the major advances in the field. It emphasizes on the p53 function, regulation of p53, targeting of the p53-MDM2 interaction for cancer therapy, and p53-dependent and -independent effects of inhibition of p53-MDM2 interaction. Then, representatives of small molecule MDM2-p53 binding antagonists are introduced with a focus on those entered into clinical trials. Furthermore, the review discusses the gene signatures in order to predict sensitivity to MDM2 antagonists, potential side effects and the reasons for the observed hematotoxicity, mechanisms of resistance to these drugs, their evaluation as monotherapy or in combination with conventional chemotherapy or with other targeted therapeutic agents. Finally, it highlights the certainly intriguing questions and challenges which would be addressed in future studies.

Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder: Review and Discussion of Recent Advancements

An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.

Identification of the Mutational Landscape of Gynecological Malignancies

Background: Cancer is a complex disease that arises from the accumulation of multiple genetic and non-genetic changes. Advances in sequencing technologies have allowed unbiased and global analysis of patient-derived tumor samples and the discovery of genetic and transcriptional changes in key genes and oncogenic pathways. That in turn has facilitated a better understanding of the underlying causes of cancer initiation and progression, resulting in new therapeutic targets. Methods: In our study, we have analyzed the mutational landscape of gynecological malignancies using datasets from The Cancer Genome Atlas (TCGA). We have also analyzed Oncomine datasets to establish the impact of their alteration on disease recurrence and survival of patients. Results: In this study, we analyzed a series of different gynecological malignancies for commonly occurring genetic and non-genetic alterations. These studies show that white women have higher incidence of gynecological malignancies. Furthermore, our study identified 16 genes that are altered at a frequency >10% among all of the gynecological malignancies and tumor suppressor TP53 is the most altered gene in these malignancies (>50% of the cases). The top 16 genes fall into the categories of either tumor suppressor or oncogenes and a subset of these genes are associated with poor prognosis, some affecting recurrence and survival of ovarian cancer patients. Conclusion: In sum, our study identified 16 major genes that are broadly mutated in a large majority of gynecological malignancies and in some cases predict survival and recurrence in patients with gynecological malignancies. We predict that the functional studies will determine their relative role in the initiation and progression of gynecological malignancies and also establish if some of them represents drug targets for anti-cancer therapy.

Evaluation of non-coding region sequence variants and mitochondrial haplogroups as potential biomarkers of sporadic breast cancer in individuals of Sri Lankan Sinhalese ethnicity

Mitochondrial DNA (mtDNA) mutations have been reported to be associated with various diseases, including cancer. The present study investigated the mtDNA non-coding region mutations and mitochondrial haplogroups as potential biomarkers of sporadic breast cancer in Sri Lankan Sinhalese women. Mitochondrial macro-haplogroups were determined using PCR-restriction fragment length polymorphism, whereas non-coding region sequences were determined using Sanger sequencing. The sequence of the non-coding region was also used to confirm haplogroup status. Neither the mutations in the non-coding region nor the mitochondrial haplogroups that were reported as risk factors in other populations, were determined to be potential risk factors for sporadic breast cancer in the present study. Furthermore, several novel mutations were identified in the present matched pairs case-controlled study. The M65a haplogroup with an additional mutation at position 16311 (P=0.0771) and mutations at the ori-b site (P=0.05) were considered a weak risk factor and protective factor, respectively, for sporadic breast cancer in Sinhalese women. Previous studies have indicated the use of mtDNA mutations as a biomarker; however, the present study showed that such biomarkers need to be validated for individual ethnic groups before they can be recommended for use in the prediction of disease.

Nutrigenomics and Breast Cancer: State-of-Art, Future Perspectives and Insights for Prevention

Proper nutrition plays a major role in preventing diseases and, therefore, nutritional interventions constitute crucial strategies in the field of Public Health. Nutrigenomics and nutriproteomics are arising from the integration of nutritional, genomics and proteomics specialties in the era of postgenomics medicine. In particular, nutrigenomics and nutriproteomics focus on the interaction between nutrients and the human genome and proteome, respectively, providing insights into the role of diet in carcinogenesis. Further omics disciplines, like metabonomics, interactomics and microbiomics, are expected to provide a better understanding of nutrition and its underlying factors. These fields represent an unprecedented opportunity for the development of personalized diets in women at risk of developing breast cancer.

A Splice Site Variant of CDK12 and Breast Cancer in Three Eurasian Populations

CDK12 is a member of the cyclin-dependent kinase family that acts as regulator of DNA damage response gene expression. A c.1047-2A>G splice site variant of the CDK12 gene was recently reported to strongly associate with hereditary breast and ovarian cancer in patients of Tatar ethnic origin. To gain more insight into the potential risk and the population spread of the c.1047-2A>G variant, we have genotyped three breast cancer case-control series of Tatar, Bashkir and Kazakh ethnicity. We identified c.1047-2A>G in 6/155 cases and 12/362 controls of Tatar ancestry, 0/96 cases and 9/189 controls of Bashkir ancestry, and 1/131 cases and 0/154 controls of Kazakh ancestry (Mantel-Haenszel odds ratio 0.72, 95% CI 0.30-1.70, p = 0.45). Consistent with the absence of a large effect, bioinformatic analyses predicted that c.1047-2A>G modulates alternative splicing of a NAGNAG sequence rather than constituting a loss-of-function allele, and RT-PCR analyses of c.1047-2A>G heterozygous lymphocytes verified the usage of the predicted alternative acceptor site. Our study confirms a high prevalence of CDK12*c.1047-2A>G in the Tatar and Bashkir population but excludes a role as a clinically actionable high-risk breast cancer mutation.

Genetic variation and radiation quality impact cancer promoting cellular phenotypes in response to HZE exposure

There exists a wide degree of genetic variation within the normal human population which includes disease free individuals with heterozygote defects in major DNA repair genes. A lack of understanding of how this genetic variation impacts cellular phenotypes that inform cancer risk post heavy ion exposure poses a major limitation in developing personalized cancer risk assessment astronauts. We initiated a pilot study with Human Mammary Epithelial Cell strains (HMEC) derived from wild type, a p16 silenced derivative of wild type, and various genetic variants that were heterozygote for DNA repair genes; BRCA1, BRCA2 and ATM. Cells strains were exposed to different high and low LET radiation qualities to generate both simple and complex lesions and centrosome aberrations were examined as a surrogate marker of genomic instability and cancer susceptibility post different exposures. Our results indicate that centrosome aberration frequency is higher in the genetic variants under study. The aberration frequency increases with dose, complexity of the lesion generated by different radiation qualities and age of the individual. This increase in genomic instability correlates with elevated check-point activation post radiation exposure. These studies suggest that the influence of individual genetics on cell cycle regulation could modify the degree of early genomic instability in response to complex lesions and potentially define cancer predisposition in response to HZE exposure. These results will have significant implications in estimating cancer susceptibility in genetically variant individuals exposed to HZE particles.

Canine mammary tumor risk is associated with polymorphisms in RAD51 and STK11 genes

Cancer is a complex disease involving genetic and phenotypic changes. Several single nucleotide polymorphisms (SNPs) have been associated with the risk of breast cancer development in women; however, little is known regarding their influence on canine mammary tumor risk. We assessed the influence of SNPs in genes related to human breast cancer susceptibility, with respect to the risk of development of mammary tumors in dogs. Sixty-seven canine SNPs in proto-oncogenes, tumor suppressor genes, genes involved in DNA repair, and in hormonal metabolism were evaluated in 212 bitches with mammary tumors and in 161 bitches free of mammary neoplasia. A significant association with mammary neoplasia risk was identified for 2 SNPs in RAD51 ( rs23623251 and rs23642734) and one SNP in the STK11 gene ( rs22928814). None of the other SNPs were related to the risk of mammary tumor development. The identification of genetic profiles associated with risk of mammary neoplasia is of great importance, supporting the implementation of specific clinical management strategies in high-risk animals.

Reproductive risk factors in breast cancer and genetic hormonal pathways: a gene-environment interaction in the MCC-Spain project

BACKGROUND

Reproductive factors are well known risk factors for breast cancer; however, little is known about how genetic variants in hormonal pathways interact with that relationship.

METHODS

One thousand one hundred thirty nine cases of breast cancer in women and 1322 frequency-matched controls were compared. Genetic variants in hormonal pathways (identified in the Kyoto Encyclopedia of Genes and Genomes) were screened according to their relationship with breast cancer using the Cochran-Armitage statistic. Information on reproductive factors was obtained using a face-to-face questionnaire. The interaction among the selected genetic variants and reproductive factors was tested with logistic regression.

RESULTS

Concerning C allele in rs2229712, compared to nulliparity in non-carriers the ORs for 1-2 and > 2 deliveries were 0.48 (0.28-0.81) and 0.34 (0.19-0.59), and in C carriers they were 0.92 (0.42-1.98) and 0.71 (0.31-1.61). Similar results were found in women carrying the C allele in rs1269851. Carriers of Allele T in rs35652107 and allele C in rs6018027 had the delivery number effect more pronounced.

CONCLUSIONS

The number of deliveries had a dose-response protective effect on breast cancer; women carrying C allele in rs2229712 did not benefit from this protective effect.

Exome sequencing and case-control analyses identify RCC1 as a candidate breast cancer susceptibility gene

Breast cancer is a genetic disease but the known genes explain a minority of cases. To elucidate the molecular basis of breast cancer in the Tunisian population, we performed exome sequencing on six BRCA1/BRCA2 mutation-negative patients with familial breast cancer and identified a novel frameshift mutation in RCC1, encoding the Regulator of Chromosome Condensation 1. Subsequent genotyping detected the 19-bp deletion in additional 5 out of 153 (3%) breast cancer patients but in none of 400 female controls (p = 0.0015). The deletion was enriched in patients with a positive family history (5%, p = 0.0009) and co-segregated with breast cancer in the initial pedigree. The mutant allele was lost in 4/6 breast tumors from mutation carriers which may be consistent with the hypothesis that RCC1 dysfunction provides a selective disadvantage at the stage of tumor progression. In summary, we propose RCC1 as a likely breast cancer susceptibility gene in the Tunisian population.

Sleep and circadian disruption and incident breast cancer risk: An evidence-based and theoretical review

Opportunities for restorative sleep and optimal sleep-wake schedules are becoming luxuries in industrialized cultures, yet accumulating research has revealed multiple adverse health effects of disruptions in sleep and circadian rhythms, including increased risk of breast cancer. The literature on breast cancer risk has focused largely on adverse effects of night shift work and exposure to light at night (LAN), without considering potential effects of associated sleep disruptions. As it stands, studies on breast cancer risk have not considered the impact of both sleep and circadian disruption, and the possible interaction of the two through bidirectional pathways, on breast cancer risk in the population at large. We review and synthesize this literature, including: 1) studies of circadian disruption and incident breast cancer; 2) evidence for bidirectional interactions between sleep and circadian systems; 3) studies of sleep and incident breast cancer; and 4) potential mechanistic pathways by which interrelated sleep and circadian disruption may contribute to the etiology of breast cancer.

Hormone receptor status and survival of medullary breast cancer patients. A Turkish cohort

Objectives:

To analyze the relationship between clinical features, hormonal receptor status, and survival in patients who were diagnosed with medullary breast cancer (MBC).

Methods:

Demographic characteristics, histopathological features, and survival statuses of 201 patients diagnosed with MBC between 1995 and 2015 were retrospectively recorded. Survival analyses were conducted with uni- and multivariate cox regression analysis.

Results:

Median follow-up time was 54 (4-272) months. Median patient age at the time of diagnosis was 47 years old (26-90). Of the patients, 91.5% were triple negative. Five-year recurrence free survival time (RFS) rate was 87.4% and overalll survival (OS) rate 95.7%. For RFS, progesterone receptor (PR) negativity, atypical histopathological evaluation, absence of lymphovascular invasion, smaller tumor, lower nodal involvement were found to be favourable prognostic factors by univariate analysis (p<0.05). The PR negativity and smaller tumor were found to be favourable factors by univariate analysis (p<0.05). However, none of these factors were determined as significant independent prognostic factors for OS (p>0.05).

Conclusion:

Turkish MBC patients exhibited good prognosis, which was comparable with survival outcomes achieved in the literature. The PR negativity was related to a better RFS and OS rates.

Recommendations for Childhood Cancer Screening and Surveillance in DNA Repair Disorders

DNA repair syndromes are heterogeneous disorders caused by pathogenic variants in genes encoding proteins key in DNA replication and/or the cellular response to DNA damage. The majority of these syndromes are inherited in an autosomal-recessive manner, but autosomal-dominant and X-linked recessive disorders also exist. The clinical features of patients with DNA repair syndromes are highly varied and dependent on the underlying genetic cause. Notably, all patients have elevated risks of syndrome-associated cancers, and many of these cancers present in childhood. Although it is clear that the risk of cancer is increased, there are limited data defining the true incidence of cancer and almost no evidence-based approaches to cancer surveillance in patients with DNA repair disorders. This article is the product of the October 2016 AACR Childhood Cancer Predisposition Workshop, which brought together experts from around the world to discuss and develop cancer surveillance guidelines for children with cancer-prone disorders. Herein, we focus on the more common of the rare DNA repair disorders: ataxia telangiectasia, Bloom syndrome, Fanconi anemia, dyskeratosis congenita, Nijmegen breakage syndrome, Rothmund-Thomson syndrome, and Xeroderma pigmentosum. Dedicated syndrome registries and a combination of basic science and clinical research have led to important insights into the underlying biology of these disorders. Given the rarity of these disorders, it is recommended that centralized centers of excellence be involved directly or through consultation in caring for patients with heritable DNA repair syndromes. Clin Cancer Res; 23(11); e23-e31. ©2017 AACRSee all articles in the online-only CCR Pediatric Oncology Series.