A Personal Breast Cancer Risk Stratification Model Using Common Variants and Environmental Risk Factors in Japanese Females

CD8+ T cell‑related KCTD5 contributes to malignant progression and unfavorable clinical outcome of patients with triple‑negative breast cancer

Triple‑negative breast cancer (TNBC) is a highly aggressive and heterogeneous subtype of breast cancer that lacks expression of estrogen receptor, progesterone receptor, and HER2, making it more challenging to treat with targeted therapies. The present study aimed to identify CD8+ T cell‑associated genes, which could provide insight into the mechanisms underlying TNBC to facilitate developing novel immunotherapies. TNBC datasets were downloaded from public databases including The Cancer Genome Atlas, Molecular Taxonomy of Breast Cancer International Consortium, and Gene Expression Omnibus. Candidate genes were identified integrating weighted gene co‑expression network analysis (WGCNA), differential gene expression, protein‑protein‑interaction network construction and univariate Cox regression analysis. Kaplan‑Meier survival, multivariate Cox regression and receiver operating characteristic analysis were performed to evaluate the prognostic value of hub genes. Knockdown experiments, alongside wound healing, Cell Counting Kit‑8 and Transwell migration and invasion assays were performed. In total, seven gene modules were associated with CD8+ T cells using WGCNA, among which potassium channel tetramerization domain 5 (KCTD5) was significantly upregulated in TNBC samples and was associated with poor prognosis. KCTD5 expression inversely associated with infiltration ratios of 'Macrophages M1', 'Plasma cells', and 'γδ T cells', but positively with 'activated Mast cells', 'Macrophages M0', and 'Macrophages M2'. As an independent prognostic indicator for TNBC, KCTD5 was also associated with drug sensitivity and the expression of programmed cell death protein 1, Cytotoxic T‑Lymphocyte‑Associated Protein 4 (CTLA4), CD274), Cluster of Differentiation 86 (CD86), Lymphocyte‑Activation Gene 3 (LAG3), T Cell Immunoreceptor with Ig and ITIM Domains (TIGIT). Knockdown of KCTD5 significantly inhibited viability, migration and invasion of TNBC cells in vitro. KCTD5 was suggested to impact the tumor immune microenvironment by influencing the infiltration of immune cells and may serve as a potential therapeutic target for TNBC.

Temporal trends of breast cancer burden in the Western Pacific Region from 1990 to 2044: Implications from the Global Burden of Disease Study 2019

INTRODUCTION

Breast cancer (BC) is a malignant disease that occurs worldwide and poses serious health burden.

OBJECTIVES

To assess the prevalence of BC burden in the Western Pacific region (WPR) from 1990 to 2019, and to predict trends from 2020 to 2044. To analyze the driving factors and put forward the region-oriented improvement.

METHODS

Based on the Global Burden of Disease Study 2019, BC cases, deaths, disability-adjusted life years (DALYs) cases, age-standardized incidence rate (ASIR), age-standardized death rate (ASDR), and age-standardized DALYs rate in WPR from 1990 to 2019 was obtained and analysed. Age-period-cohort (APC) model was used to analyze age, period, and cohort effects in BC, and Bayesian APC (BAPC) was used to predict trends over the next 25 years.

RESULTS

In conclusion, BC incidence and deaths in the WPR have increased rapidly over the past 30 years and are expected to continue to increase between 2020 and 2044. Among behavioral and metabolic factors, high body-mass index was the main risk factor for BC mortality in middle-income countries, whereas alcohol use was the main risk factor in Japan. Age is a key factor in the development of BC, with 40 years being the critical point. Incidence trends coincide with the course of economic development.

CONCLUSIONS

The BC burden remains an essential public health issue in the WPR and will increase substantially in the future. More efforts should be made in middle-income countries to prompt the health behavior and minimize the burden of BC because these nations accounts for the majority of BC burden in the WPR.

Functions of Breast Cancer Predisposition Genes: Implications for Clinical Management

Approximately 5–10% of all breast cancer (BC) cases are caused by germline pathogenic variants (GPVs) in various cancer predisposition genes (CPGs). The most common contributors to hereditary BC are BRCA1 and BRCA2, which are associated with hereditary breast and ovarian cancer (HBOC). ATM, BARD1, CHEK2, PALB2, RAD51C, and RAD51D have also been recognized as CPGs with a high to moderate risk of BC. Primary and secondary cancer prevention strategies have been established for HBOC patients; however, optimal preventive strategies for most hereditary BCs have not yet been established. Most BC-associated CPGs participate in DNA damage repair pathways and cell cycle checkpoint mechanisms, and function jointly in such cascades; therefore, a fundamental understanding of the disease drivers in such cascades can facilitate the accurate estimation of the genetic risk of developing BC and the selection of appropriate preventive and therapeutic strategies to manage hereditary BCs. Herein, we review the functions of key BC-associated CPGs and strategies for the clinical management in individuals harboring the GPVs of such genes.

Investigating How Reproducibility and Geometrical Representation in UMAP Dimensionality Reduction Impact the Stratification of Breast Cancer Tumors

Advances in next-generation sequencing have provided high-dimensional RNA-seq datasets, allowing the stratification of some tumor patients based on their transcriptomic profiles. Machine learning methods have been used to reduce and cluster high-dimensional data. Recently, uniform manifold approximation and projection (UMAP) was applied to project genomic datasets in low-dimensional Euclidean latent space. Here, we evaluated how different representations of the UMAP embedding can impact the analysis of breast cancer (BC) stratification. We projected BC RNA-seq data on Euclidean, spherical, and hyperbolic spaces, and stratified BC patients via clustering algorithms. We also proposed a pipeline to yield more reproducible clustering outputs. The results show how the selection of the latent space can affect downstream stratification results and suggest that the exploration of different geometrical representations is recommended to explore data structure and samples’ relationships.