Background: The present study was conducted to evaluate the clinical, pathological response, and prognosis characteristics of human epidermal growth factor receptor 2 (HER2)-low breast cancer in the neoadjuvant chemotherapy setting.
Methods: Patients with HER2-negative breast cancer who received neoadjuvant chemotherapy from January 2017 to December 2019 were retrospectively analyzed. HER2-negative breast cancer was divided into two groups: HER2-zero (defined as immunohistochemistry [IHC] 0) and HER2-low (defined as IHC 1+, or IHC 2+ and fluorescence in-situ hybridization-negative.
Results: Overall, 314 patients with HER2-negative breast cancer were analyzed. The proportion of HER2-low patients with hormone receptor (HR)-positive disease was higher than in triple-negative breast cancer (TNBC; 75.3% vs. 63.2%, p = 0.032). In HR-positive breast cancer, HER2-low tumors presented less nodal involvement (p = 0.023) and earlier clinical stage (p = 0.015) compared with HER2-zero tumors; however, in TNBC, HER2-low patients had a later clinical stage (p = 0.028). With the pathological complete response (pCR) defined as ypTis/0ypN0, there was no difference in pCR rates among the entire cohort, HR-positive disease, and TNBC. However, with the pCR defined as ypT0ypN0, the pCR rate in HER2-low breast cancer was significantly lower than HER2-zero breast cancer in the entire cohort (24.3% vs. 36.4%, p = 0.032) and the HR-positive subgroup (18.7% vs. 32.1%, p = 0.035), but not for TNBC. Multivariate analysis demonstrated that HER2 status (low vs. zero) was an independent predictive factor for pCR (p = 0.013) in HR-positive breast cancer. There were no statistically significant differences in 3-year disease-free survival and overall survival between HER2-low and HER2-zero breast cancer among the entire cohort, HR-positive disease, and TNBC.
Conclusions: HER2-low breast cancer exhibits specific clinical features and different response to treatment associated with HR status in the neoadjuvant chemotherapy setting.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1245/s10434-022-12369-4 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
GradeDiff-IM: An Ensembles Model-based Grade Classification of Breast Cancer.
Biomed Phys Eng Express
January 2025
School of Engineering and Computing, University of the West of Scotland, University of the West of Scotland - Paisley Campus, Paisley PA1 2BE, UK, City, Paisley, PA1 2BE, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.
Cancer grade classification is a challenging task identified from the cell structure of healthy and abnormal tissues. The partitioner learns about the malignant cell through the grading and plans the treatment strategy accordingly. A major portion of researchers used DL models for grade classification.
View Article and Find Full Text PDFUnveiling Sociocultural Barriers to Breast Cancer Awareness Among the South Asian Population: Case Study of Bangladesh and West Bengal, India.
JMIR Hum Factors
January 2025
New College of Florida, Sarasota, FL, United States.
Background: Bangladesh and West Bengal, India, are 2 densely populated South Asian neighboring regions with many socioeconomic and cultural similarities. In dealing with breast cancer (BC)-related issues, statistics show that people from these regions are having similar problems and fates. According to the Global Cancer Statistics 2020 and 2012 reports, for BC (particularly female BC), the age-standardized incidence rate is approximately 22 to 25 per 100,000 people, and the age-standardized mortality rate is approximately 11 to 13 per 100,000 for these areas.
View Article and Find Full Text PDFFASN inhibition shows the potential for enhancing radiotherapy outcomes by targeting glycolysis, AKT, and ERK pathways in breast cancer.
Int J Radiat Biol
January 2025
Department of Biomedical Imaging and Radiological Sciences, National Yang Ming Chiao Tung University, Taipei City, Taiwan.
Purpose: Breast cancer ranks as the most prevalent cancer in women, characterized by heightened fatty acid synthesis and glycolytic activity. Fatty acid synthase (FASN) is prominently expressed in breast cancer cells, regulating fatty acid synthesis, thereby enhancing tumor growth and migration, and leading to radioresistance. This study aims to investigate how FASN inhibition affects cell proliferation, migration, and radioresistance in breast cancer, as well as the mechanisms involved.
View Article and Find Full Text PDFPreliminary characterisation of the spatial immune and vascular environment in triple negative basal breast carcinomas using multiplex fluorescent immunohistochemistry.
PLoS One
January 2025
Department of Pathology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
Triple negative breast cancers often contain higher numbers of tumour-infiltrating lymphocytes compared with other breast cancer subtypes, with their number correlating with prolonged survival. Since little is known about tumour-infiltrating lymphocyte trafficking in triple negative breast cancers, we investigated the relationship between tumour-infiltrating lymphocytes and the vascular compartment to better understand the immune tumour microenvironment in this aggressive cancer type. We aimed to identify mechanisms and signaling pathways responsible for immune cell trafficking in triple negative breast cancers, specifically of basal type, that could potentially be manipulated to change such tumours from immune "cold" to "hot" thereby increasing the likelihood of successful immunotherapy in this challenging patient population.
View Article and Find Full Text PDFFractional and stochastic modeling of breast cancer progression with real data validation.
PLoS One
January 2025
Biology Department, Faculty of Science, Islamic University of Madinah, Madinah, Saudi Arabia.
This study presents a novel approach to modeling breast cancer dynamics, one of the most significant health threats to women worldwide. Utilizing a piecewise mathematical framework, we incorporate both deterministic and stochastic elements of cancer progression. The model is divided into three distinct phases: (1) initial growth, characterized by a constant-order Caputo proportional operator (CPC), (2) intermediate growth, modeled by a variable-order CPC, and (3) advanced stages, capturing stochastic fluctuations in cancer cell populations using a stochastic operator.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!