Single nucleotide variants in metastasis-related genes are associated with breast cancer risk, by lymph node involvement and estrogen receptor status, in women with European and African ancestry

Functional annotation with expression validation identifies novel metastasis-relevant genes from post-GWAS risk loci in sporadic colorectal carcinomas

BACKGROUND

Colorectal cancer (CRC) is the third highest incidence cancer and is the leading cause of cancer mortality worldwide. Metastasis to distal organ is the major cause of cancer mortality. However, the underlying genetic factors are unclear. This study aimed to identify metastasis-relevant genes and pathways for better management of metastasis-prone patients.

METHODS

A case-case genome-wide association study comprising 2677 sporadic Chinese CRC cases (1282 metastasis-positive vs 1395 metastasis-negative) was performed using the Human SNP6 microarray platform and analysed with the correlation/trend test based on the additive model. SNP variants with association testing -log10 p value ≥5 were imported into Functional Mapping and Annotation (FUMA) for functional annotation.

RESULTS

Glycolysis was uncovered as the top hallmark gene set. Transcripts from two of the five genes profiled, hematopoietic substrate 1 associated protein X 1 (HAX1) and hyaluronan-mediatedmotility receptor (HMMR), were significantly upregulated in the metastasis-positive tumours. In contrast to disease-risk variants, HAX1 appeared to act synergistically with HMMR in significantly impacting metastasis-free survival. Examining the subtype datasets with FUMA and Ingenuity Pathway Analysis (IPA) identified distinct pathways demonstrating sexual dimorphism in CRC metastasis.

CONCLUSIONS

Combining genome-wide association testing with in silico functional annotation and wet-bench validation identified metastasis-relevant genes that could serve as features to develop subtype-specific metastasis-risk signatures for tailored management of patients with stage I-III CRC.

A review of genetic variant databases and machine learning tools for predicting the pathogenicity of breast cancer

Studies continue to uncover contributing risk factors for breast cancer (BC) development including genetic variants. Advances in machine learning and big data generated from genetic sequencing can now be used for predicting BC pathogenicity. However, it is unclear which tool developed for pathogenicity prediction is most suited for predicting the impact and pathogenicity of variant effects. A significant challenge is to determine the most suitable data source for each tool since different tools can yield different prediction results with different data inputs. To this end, this work reviews genetic variant databases and tools used specifically for the prediction of BC pathogenicity. We provide a description of existing genetic variants databases and, where appropriate, the diseases for which they have been established. Through example, we illustrate how they can be used for prediction of BC pathogenicity and discuss their associated advantages and disadvantages. We conclude that the tools that are specialized by training on multiple diverse datasets from different databases for the same disease have enhanced accuracy and specificity and are thereby more helpful to the clinicians in predicting and diagnosing BC as early as possible.

Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer

A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (BW=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity (AUC 0.77, Brown/Wilson p-value<0.0001). Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk.

Dietary phytochemicals/nutrients as promising protector of breast cancer development: a comprehensive analysis

Genetic change, particularly epigenetic alteration, is one of the imperative factors for sporadic breast cancer development in the worldwide population of women. The DNA methylation process is essential and natural for human cellular renewal and tissue homeostasis, but its dysregulation contributes to many pathological changes, including breast tumorigenesis. Chemopreventive agents mainly protect the abnormal DNA methylation either by hindering the division of pre-malignant cells or looming the DNA damage, which leads to malignancy. The present review article is about understanding the potential role of dietary phytochemicals in breast cancer prevention. Accordingly, a literature search of the published article until August 2021 has been performed. Further, we have investigated the binding affinity of different phytochemicals isolated from diverse dietary sources against the various oncogenic proteins related to breast cancer initiation to understand the common target(s) in breast cancer prevention mechanisms. Various small phytochemicals, especially dietary phytochemicals including sulforaphane, mahanine, resveratrol, linolenic acid, diallyl sulfide, benzyl/phenethyl isothiocyanate, etc. are being investigated as the chemopreventive agent to manage breast cancer development, and some of them have shown promising outcomes in the cited research. In this present review, we discuss the recent advancement in acceptance of such types of potential dietary phytochemicals as a chemopreventive agent against breast cancer development and their inner lining mechanism. The critical clinical trials and cohort studies have also been considered to understand the progress in contemporary perspectives.

Uncovering Evidence: Associations between Environmental Contaminants and Disparities in Women's Health

Over the years, industrial accidents and military actions have led to unintentional, large-scale, high-dose human exposure to environmental contaminants with endocrine-disrupting action. These historical events, in addition to laboratory studies, suggest that exposure to toxicants such as dioxins and polychlorinated biphenyls negatively impact the reproductive system and likely influence the development of gynecologic diseases. Although high-level exposure to a single toxicant is rare, humans living in industrialized countries are continuously exposed to a complex mixture of manmade and naturally produced endocrine disruptors, including persistent organic pollutants and heavy metals. Since minorities are more likely to live in areas with known environmental contamination; herein, we conducted a literature review to identify potential associations between toxicant exposure and racial disparities in women's health. Evidence within the literature suggests that the body burden of environmental contaminants, especially in combination with inherent genetic variations, likely contributes to previously observed racial disparities in women's health conditions such as breast cancer, endometriosis, polycystic ovarian syndrome, uterine fibroids, and premature birth.

Investigations of a Possible Role of SNPs in KAI1 Gene on Its Down-Regulation in Breast Cancer

Objective:

KAI1 (CD82) is a metastasis suppressor gene known to be down-regulated in carcinomas of breast, prostate and many other organs. The mechanism of KAI1 down-regulation is complex and not well understood. Here, we investigate the role of 8 SNPs (not previously studied) in KAI1 gene that could influence its expression in tumor tissue samples of breast cancer patients from the Eastern province of Saudi Arabia.

Methods:

Single nucleotide polymorphisms (SNPs) in KAI1 gene were selected from the NCBI website (dbSNP) and were then filtered for those SNPs causing stop codon mutations (rs139889503 and rs150533529) or nonsynonymous mutation in the 5’-UTR (rs11541048, rs77359459, rs115500759, rs182579675, rs200238062, and rs372733853). SNPs genotyping was performed using TaqMan SNP Genotyping Assay and the results were correlated with KAI1 protein expression profile by immunohistochemistry (IHC) on formalin-fixed paraffin-embedded (FFPE) samples of breast cancer and control none-neoplastic tissues.

Results:

KAI1 expression by IHC was observed in all none-neoplastic breast tissue samples and only in 35% out of the 59 breast cancer tissue samples. None of the samples was homozygous for the stop codon allele A in the SNP rs139889503 or allele T in the SNP rs150533529. The SNPs in the 5-UTR, rs11541048, rs115500759, and rs182579675, were only present in the homozygous state for the G and C alleles respectively in both cancer and control samples. The other SNPs in the 5’-UTR (rs77359459, rs200238062, and rs372733853) had no significant difference in the allele distribution between KAI1 expressing or none-expressing tissue samples.

Conclusion:

Our findings showed no significant effect of the studied SNPs on down-regulation of KAI1 expression.

Association between NME1 polymorphisms and cancer susceptibility: A meta-analysis based on 1644 cases and 2038 controls

The association between polymorphisms in the nucleoside diphosphate kinase 1 (NME1) gene and overall risk of cancer remains to be elucidated. Here, we performed a meta-analysis of the association between rs16949649, rs2302254, and rs34214448 polymorphisms in the NME1 gene and cancer risk. PubMed, Web of Science, and CNKI databases (as of June 6, 2017) were searched. Eight studies, encompassing 1644 cases and 2038 controls, were selected. The results revealed no significant relationship between NME1 polymorphisms and overall cancer susceptibility. Interestingly, the rs16949649 polymorphism was associated with increased susceptibility to gynecological cancer (heterozygous model: odds ratio [OR] = 1.74, 95% confidence interval [CI] = 1.06-2.86, P = 0.029). The rs2302254 polymorphism was linked to decreased susceptibility to gastric cancer in the other groups (recessive model: OR = 0.53, 95% CI = 0.28-0.98, P = 0.045). The rs34214448 polymorphism correlated significantly with increased susceptibility to non-small cell lung cancer according to all genetic models (P < 0.05) and was linked to decreased risk in cervical cancer (recessive model: OR = 0.51, 95% CI = 0.27-0.94, P = 0.031). Thus, our meta-analysis found rs16949649 associated with increased susceptibility to gynecological cancer and rs2302254 was linked to reduced gastric cancer risk; additional, larger studies are required to confirm these findings.

Risk Factors and Preventions of Breast Cancer

Breast cancer is the second leading cause of cancer deaths among women. The development of breast cancer is a multi-step process involving multiple cell types, and its prevention remains challenging in the world. Early diagnosis of breast cancer is one of the best approaches to prevent this disease. In some developed countries, the 5-year relative survival rate of breast cancer patients is above 80% due to early prevention. In the recent decade, great progress has been made in the understanding of breast cancer as well as in the development of preventative methods. The pathogenesis and tumor drug-resistant mechanisms are revealed by discovering breast cancer stem cells, and many genes are found related to breast cancer. Currently, people have more drug options for the chemoprevention of breast cancer, while biological prevention has been recently developed to improve patients' quality of life. In this review, we will summarize key studies of pathogenesis, related genes, risk factors and preventative methods on breast cancer over the past years. These findings represent a small step in the long fight against breast cancer.

Expression and clinical significance of SATB1 and TLR4 in breast cancer

This study investigated the expression of special AT-rich sequence-binding protein 1 (SATB1) and toll-like receptor 4 (TLR4) protein in breast cancer and its clinical significance. We collected breast cancer tissues from 120 patients and adjacent non-cancerous tissue from 53 patients. SATB1 was expressed in 89 cases of breast cancer (74.17%) and in 7 cases of adjacent non-cancerous tissue (13.21%). TLR4 was expressed in 70 cases of breast cancer tissues (58.33%) and in 48 cases of adjacent non-cancerous tissue (90.57%). The differences of SATB and TLR4 in breast cancer and adjacent non-cancerous tissue were statistically significant. We found a negative correlation between the expression of SATB1 and TLR4 (r=−0.624, P<0.05). The expression of SATB1 and TLR4 were not significantly correlated with age, menopause, and PR and HER-2 protein expression, but were significantly correlated with tumor size, local lymphatic metastasis, histopathological grade, tumor stage, and ER protein expression (P<0.05). Overall, SATB1 and TLR4 proteins are involved in the development of breast cancer, a finding of great significance to identify therapeutic targets and prognosis markers for breast cancer.