Subtypes molecular breast cancer

OBJECTIVES: Breast cancer is a prevalent disease that has a substantial impact on women's mortality rates. Shikonin, a naphthoquinone derived from Lithospermum erythrorhizon, has demonstrated substantial anticancer effects. This study aims to conduct a comprehensive review of the latest research findings regarding the therapeutic efficacy of shikonin in the context of breast cancer treatment, with a specific emphasis on elucidating the underlying molecular mechanisms. METHODS: A comprehensive literature review was conducted on shikonin and breast cancer by searching PubMed, Scopus, Web of Science, and Google Scholar databases...

Hormone receptor (HR)-positive breast cancer can become aggressive after developing hormone-treatment resistance. This study elucidated the role of long non-coding RNA (lncRNA) SOX2OT in tamoxifen-resistant (TAMR) breast cancer and its potential interplay with the tumor microenvironment (TME). TAMR breast cancer cell lines TAMR-V and TAMR-H were compared with the luminal type A cell line (MCF-7). LncRNA expression was assessed via next-generation sequencing, RNA extraction, lncRNA profiling, and quantitative RT-qPCR...

The C-X-C motif chemokine ligand 8 (CXCL8)-C-X-C chemokine receptor (CXCR)1/2 signalling axis is among numerous mechanisms which stimulate the immune system to defend against tumour growth and influence the tumour microenvironment to promote tumour growth. This pathway plays an important role in the development of a number of cancers including breast cancer (BC). The aim of the present study was to analyse the levels of the chemokine CXCL8 and its receptors, CXCR1 and CXCR2, in the serum of female patients with invasive BC and to assess the expression of these parameters at the mRNA level, considering molecular subtypes and degrees of cancer malignancy...

BACKGROUND: Breast cancer is a highly heterogeneous solid tumor, posing challenges in developing targeted therapies effective for all mammary carcinoma subtypes. WT1 emerges as a promising target for breast cancer therapy due to its potential oncogenic role in various cancer types. Previous works have yielded inconsistent results. Therefore, further studies are needed to clarify the behavior of this complex gene in breast cancer. METHODS AND RESULTS: In this study, we examined WT1 expression in both Formalin Fixed Paraffin Embedded breast tumors (n = 41) and healthy adjacent tissues (n = 41) samples from newly diagnosed cases of ductal invasive breast cancer...

Despite increasing numbers of regulatory approvals, deep learning-based computational pathology systems often overlook the impact of demographic factors on performance, potentially leading to biases. This concern is all the more important as computational pathology has leveraged large public datasets that underrepresent certain demographic groups. Using publicly available data from The Cancer Genome Atlas and the EBRAINS brain tumor atlas, as well as internal patient data, we show that whole-slide image classification models display marked performance disparities across different demographic groups when used to subtype breast and lung carcinomas and to predict IDH1 mutations in gliomas...

BACKGROUND: Inflammatory breast cancer (IBC) is the most pro-metastatic form of BC. Better understanding of its enigmatic pathophysiology is crucial. We report here the largest whole-exome sequencing (WES) study of clinical IBC samples. METHODS: We retrospectively applied WES to 54 untreated IBC primary tumor samples and matched normal DNA. The comparator samples were 102 stage-matched non-IBC samples from TCGA. We compared the somatic mutational profiles, spectra and signatures, copy number alterations (CNAs), HRD and heterogeneity scores, and frequencies of actionable genomic alterations (AGAs) between IBCs and non-IBCs...

RATIONALE AND OBJECTIVES: To evaluate the performance of deep learning (DL) in predicting different breast cancer molecular subtypes using DCE-MRI from two institutes. MATERIALS AND METHODS: This retrospective study included 366 breast cancer patients from two institutes, divided into training (n = 292), validation (n = 49) and testing (n = 25) sets. We first transformed the public DCE-MRI appearance to ours to alleviate small-data-size and class-imbalance issues...

Inflammatory breast cancer is an aggressive subtype of breast cancer with dismal patient prognosis and a unique clinical presentation. In the past two decades, molecular profiling technologies have been used in order to gain insight into the molecular biology of IBC and to search for possible targets for treatment. Although a gene signature that accurately discriminates between IBC and nIBC patient samples and preclinical models was identified, the overall genomic and transcriptomic differences are small and ambiguous, mainly due to the limited sample sizes of the evaluated patient series and the failure to correct for confounding effects of the molecular subtypes...

Inflammatory Breast Cancer (IBC) is a rare and aggressive form of locally advanced breast cancer, classified as stage T4d according to the tumor-node-metastasis staging criteria. This subtype of breast cancer is known for its rapid progression and significantly lower survival rates compared to other forms of breast cancer. Despite its distinctive clinical features outlined by the World Health Organization, the histopathological characteristics of IBC remain not fully elucidated, presenting challenges in its diagnosis and treatment...

Since the early description more than a century ago, inflammatory breast cancer (IBC) remains an aggressive disease, with a different geographic repartition, with the highest ones incidence reported in the North of Africa (Tunisia, Algeria, Morocco, and Egypt), and the lowest incidence in Western countries (USA, Europe…). In this study, we reviewed the literature using the Surveillance, Epidemiology, and End Results (SEER) database compared to other published series. We observed that in the high incidence areas (North of Africa) when compared to "classical" breast cancer, IBC was associated to younger age (less than 50 years) with rapid evolution of signs and symptoms (in less than 3 up to 6 months), and more aggressive clinical and histopathological-molecular parameters, due to the predominance of triple-negative and HER2+ subtypes in around 60% of cases...

Breast cancer (BC) is the most common cancer among women with high morbidity and mortality. Therefore, new research is still needed for biomarker detection. GSE101124 and GSE182471 datasets were obtained from the Gene Expression Omnibus (GEO) database to evaluate differentially expressed circular RNAs (circRNAs). The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases were used to identify the significantly dysregulated microRNAs (miRNAs) and genes considering the Prediction Analysis of Microarray classification (PAM50)...

Triple-negative breast cancer (TNBC) is an aggressive subtype with poor prognosis of breast cancer. Thiostrepton exerts anti-tumor activities against several cancers including TNBC. Herein we discussed the new molecular mechanisms of thiostrepton in TNBC. Thiostrepton inhibited MDA-MB-231 cell viability, accompanied by a decrease of c-FLIP and p-SMAD2/3. c-FLIP overexpression reduced the sensitivity of MDA-MB-231 cells to thiostrepton, while SMAD2/3 knockdown increased the sensitivity of MDA-MB-231 cells to thiostrepton...

Breast cancer (BCa) is a complex and heterogeneous disease, with different intrinsic molecular subtypes that have distinct clinical outcomes and responses to therapy. Although intrinsic subtyping provides guidance for treatment decisions, it is now widely recognised that, in some cases, the switch of the BCa intrinsic subtype (which embodies cellular plasticity), may be responsible for therapy failure and disease progression. Aberrant FGFR4 signalling has been implicated in various cancers, including BCa, where it had been shown to be associated with aggressive subtypes, such as HER2-enriched BCa, and poor prognosis...

OBJECTIVE: This study aims to investigate the association between specific lipidomes and the risk of breast cancer (BC) using the Two-Sample Mendelian Randomization (TSMR) approach and Bayesian Model Averaging Mendelian Randomization (BMA-MR) method. METHOD: The study analyzed data from large-scale GWAS datasets of 179 lipidomes to assess the relationship between lipidomes and BC risk across different molecular subtypes. TSMR was employed to explore causal relationships, while the BMA-MR method was carried out to validate the results...

The high heterogeneity of breast cancer (BC) caused by pathogenic gene mutations poses a challenge to immunotherapy, but the underlying mechanism remains unknown. The difference in the infiltration of M1 macrophages induced by TP53 mutations has a significant impact on BC immunotherapy. The aim of this study was to develop a TP53-related M1 macrophage infiltration molecular typing risk signature in BC and evaluate the biological functions of the key gene to find new immunotherapy biomarkers. Weighted correlation network analysis (WGCNA) and negative matrix factorization (NMF) were used for distinguishing BC subtypes...

Community cohesion plays a critical role in the determination of an individual's health in social science. Intriguingly, a community structure of gene networks indicates that the concept of community cohesion could be applied between the genes as well to overcome the limitations of single gene-based biomarkers for precision oncology. Here, we develop community cohesion scores which precisely quantify the community ability to retain the interactions between the genes and their cellular functions in each individualized gene network...

Breast cancer is the most prevalent cancer among women, and its diagnosis requires the accurate identification and classification of histological features for effective patient management. Artificial intelligence, particularly through deep learning, represents the next frontier in cancer diagnosis and management. Notably, the use of convolutional neural networks and emerging Vision Transformers (ViT) has been reported to automate pathologists' tasks, including tumor detection and classification, in addition to improving the efficiency of pathology services...

Objective Triple-negative breast cancer (TNBC) represents an aggressive and prognostically poor variant of breast cancer. Over the years, detailed research has been conducted and published in Western literature. However, there lacks a detailed account of TNBC cases from the perspective of a low-volume institution. This study aims to assess the clinical features of TNBC, as well as their prognostic implications in a tertiary care centre. Methods and materials This prospective observational study took place at a tertiary health centre for two years, spanning from 2021 to 2023...

Breast cancer is a substantial source of morbidity and mortality worldwide. It is particularly more difficult to treat at later stages, and treatment regimens depend heavily on both staging and the molecular subtype of the tumor. However, both detection and molecular analyses rely on standard imaging and histological method, which are costly, time-consuming, and lack necessary sensitivity/specificity. The estrogen receptor (ER) is, along with the progesterone receptor (PR) and human epidermal growth factor (HER-2), among the primary molecular markers which inform treatment...

INTRODUCTION: The impact of distinct estrogen receptor (ER) and progesterone receptor (PR) expression patterns on tumor behavior and treatment outcomes within HER2-positive breast cancer is not fully explored. This study aimed to comprehensively examine the clinical differences among patients with HER2-positive breast cancer harboring distinct ER and PR expression patterns in the neoadjuvant setting. METHODS: This retrospective analysis included 871 HER2-positive breast patients treated with neoadjuvant therapy at our hospital between 2011 and 2022...