Analysis of breast cancer subtypes and their correlations with receptors and ultrasound

Genetic Signature of Breast Cancer Defines Therapeutic Interventions and Indicates Early Drug Resistance

Breast cancer (BC) is the most prevalent cancer in women and ranks first in diagnosed cancers worldwide, thanks to effective screening strategies. However, morbidity and mortality rates remain high among aggressive subtypes, forcing oncologists to adopt the philosophy of precision oncology in clinical practice. Immunohistochemical analysis of the tumour establishes diagnosis and stratifies BC into four types, according to a globally recognised classification. Tumour cells present a wide diversity in morphological, histological and molecular characteristics, indicating the heterogeneous nature of BC that reflects on different proliferation rates, risks of relapse and metastasis. The differentiation in prognosis and response to treatment underscores the vital need for targeted therapy, specific for each tumour's genetic status, that enhances therapeutic effectiveness. The aim of the present article is to designate the potential of using a novel molecular modality as a diagnostic tool that enlightens oncologists during their therapeutic decisions and raises awareness of therapeutic failure. Next-generation sequencing (NGS) detects a wide gamut of biomarkers and gene mutations in biopsy samples, revealing the precise genetic profile and implicating a personalised therapy. Incorporation of molecular testing in the diagnostic algorithm promises amelioration of therapeutic outcomes, prevention of recurrence and reduction of BC-related mortality.

Breast Cancer: Clinical-Epidemiological Profile and Toxicities of Women Receiving Treatment with Taxanes in the Amazon Region

Breast cancer is the most common malignant disease and the leading cause of mortality among women worldwide. Antineoplastic chemotherapy is one of its primary treatments, typically based on the class of drugs known as taxanes. Despite their proven therapeutic efficacy, these drugs can induce severe toxicities, leading to dose limitations or even treatment discontinuation. The objective of this study was to describe the clinical-epidemiological profile, risk factors, and toxicities of taxane-based chemotherapy treatment in women with breast cancer in the Amazon region. This is a cross-sectional, quantitative, and descriptive study conducted with 300 women diagnosed with breast cancer undergoing taxane treatment. Most patients were in the 40-49 age range, of brown ethnicity, and had completed elementary school. The majority of patients had risk factors such as alcoholism and a sedentary lifestyles. Most women had their first pregnancy between the ages of 18 and 21, breastfed their children, had menarche between the ages of 12 and 13, and were pre-menopausal and with a family history of cancer. The most frequent histological type was non-special invasive carcinoma and the Luminal B subtype. Most participants in this study showed taxane toxicity, with neurotoxicity being the most frequent. These findings reveal the importance of early detection, comprehensive risk factors, and effective management of treatment toxicities to improve patient outcomes in breast cancer care in the Amazon region.

Intermammary breast cancer: A rare case of cancer with origin of breast cells in an unusual location

The most common type of cancer among the female population is breast cancer. The most common site for the occurrence of breast cancer is the upper outer quadrant; the upper inner quadrant is the second site, and both the lower outer and the lower inner quadrants are in the third place. This problem is rarely seen in the central portion. Intermammary metastasis due to breast cancer is an infrequent finding. This article presents a 62-year-old lady who presented to the surgical ward with intermammary swelling that appeared suddenly 3 months ago. Ultrasound examination showed a hypoechoic micro-lobulated mass with internal vascularity on the chest wall. Although core needle biopsy suspected invasive ductal carcinoma, both right and left axillary lymph nodes were normal and free. The patient was consulted by an oncologist who recommended radiotherapy before surgery and chemotherapy before and after surgery. This study aims to report and discuss a rare case of intermammary cancer with the origin of breast cells without breast and axillary lymph node involvement. Although the intermammary region is an extremely rare location where breast cancer could occur, its management strategy is the same as other breast cancers.

Deep learning radiomics model based on breast ultrasound video to predict HER2 expression status

Purpose

The detection of human epidermal growth factor receptor 2 (HER2) expression status is essential to determining the chemotherapy regimen for breast cancer patients and to improving their prognosis. We developed a deep learning radiomics (DLR) model combining time-frequency domain features of ultrasound (US) video of breast lesions with clinical parameters for predicting HER2 expression status.

Patients and Methods

Data for this research was obtained from 807 breast cancer patients who visited from February 2019 to July 2020. Ultimately, 445 patients were included in the study. Pre-operative breast ultrasound examination videos were collected and split into a training set and a test set. Building a training set of DLR models combining time-frequency domain features and clinical features of ultrasound video of breast lesions based on the training set data to predict HER2 expression status. Test the performance of the model using test set data. The final models integrated with different classifiers are compared, and the best performing model is finally selected.

Results

The best diagnostic performance in predicting HER2 expression status is provided by an Extreme Gradient Boosting (XGBoost)-based time-frequency domain feature classifier combined with a logistic regression (LR)-based clinical parameter classifier of clinical parameters combined DLR, particularly with a high specificity of 0.917. The area under the receiver operating characteristic curve (AUC) for the test cohort was 0.810.

Conclusion

Our study provides a non-invasive imaging biomarker to predict HER2 expression status in breast cancer patients.