New Insights into Breast Cancer: Current Controversies and Future Perspectives

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Medical Research".

Deadline for manuscript submissions: 30 April 2025 | Viewed by 1954

Special Issue Editors


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Guest Editor
Multidisciplinary Breast Center, Dipartimento Scienze della Salute della Donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Rome, Italy
Interests: breast cancer; breast pathology; breast reconstruction; breast surgery; contralateral prophylactic mastectomy; mastectomy; oncoplastic surgery; surgical oncology
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Guest Editor
Multidisciplinary Breast Center—Dipartimento Scienze della Salute della donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A, Gemelli IRCCS, Roma, Italia
Interests: breast surgery; surgery; surgical oncology; breast cancer management; breast cancer screening; senology; breast imaging; mammography; breast cancer; breast cancer stem cells

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Guest Editor
Multidisciplinary Breast Center—Dipartimento Scienze della Salute della donna e del Bambino e di Sanità Pubblica, Fondazione Policlinico Universitario A, Gemelli IRCCS, Roma, Italia
Interests: breast surgery; surgery; surgical oncology; breast cancer management; breast cancer screening; senology; breast imaging; mammography; breast cancer; breast cancer stem cells

Special Issue Information

Dear Colleagues,

Breast cancer is the most frequently diagnosed cancer and the commonest cause of cancer death among women, despite diagnostic and therapeutic advances in the last few decades.

Thanks to advances in breast imaging, prevention campaigns, and public awareness, breast cancer is mostly diagnosed at an early stage. This translates into the possibility of applying “breast conserving therapies”, resulting in very high 5-year overall survival rates.

Nevertheless, approximately 8.5% of American and 4% of European patients still present with locally advanced breast cancer, whereas 6–7% have distant metastasis at diagnosis.

In such a variable scenario, the multidisciplinary calibration of therapeutic protocols, based on recent advances in breast imaging, breast conserving and reconstructive surgical techniques, multipanel gene essays, and systemic treatments (e.g., hormone therapy, poly-chemotherapy, and molecular-targeted therapy), can lead to more efficient local and systemic control of the disease.

The aim of this Special Issue is to provide a wide range of the most recent diagnostic and therapeutic protocols in breast cancer to provide the reader with updated information regarding every aspect of recent advances and future challenges.

Dr. Alejandro Martin Sanchez
Dr. Angela Bucaro
Dr. Flavia de Lauretis
Guest Editors

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Keywords

  • breast cancer treatment
  • oncoplastic surgery
  • conservative mastectomy
  • breast reconstruction
  • sentinel node biopsy
  • chemotherapy
  • radiotherapy
  • integrated therapies

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Published Papers (2 papers)

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Research

29 pages, 398 KiB  
Article
Extracting Knowledge from Machine Learning Models to Diagnose Breast Cancer
by José Manuel Martínez-Ramírez, Cristobal Carmona, María Jesús Ramírez-Expósito and José Manuel Martínez-Martos
Life 2025, 15(2), 211; https://doi.org/10.3390/life15020211 - 31 Jan 2025
Abstract
This study explored the application of explainable machine learning models to enhance breast cancer diagnosis using serum biomarkers, contrary to many studies that focus on medical images and demographic data. The primary objective was to develop models that are not only accurate but [...] Read more.
This study explored the application of explainable machine learning models to enhance breast cancer diagnosis using serum biomarkers, contrary to many studies that focus on medical images and demographic data. The primary objective was to develop models that are not only accurate but also provide insights into the factors driving predictions, addressing the need for trustworthy AI in healthcare. Several classification models were evaluated, including OneR, JRIP, the FURIA, J48, the ADTree, and the Random Forest, all of which are known for their explainability. The dataset included a variety of biomarkers, such as electrolytes, metal ions, marker proteins, enzymes, lipid profiles, peptide hormones, steroid hormones, and hormone receptors. The Random Forest model achieved the highest accuracy at 99.401%, followed closely by JRIP, the FURIA, and the ADTree at 98.802%. OneR and J48 achieved 98.204% accuracy. Notably, the models identified oxytocin as a key predictive biomarker, with most models featuring it in their rules. Other significant parameters included GnRH, β-endorphin, vasopressin, IRAP, and APB, as well as factors like iron, cholinesterase, the total protein, progesterone, 5-nucleotidase, and the BMI, which are considered clinically relevant to breast cancer pathogenesis. This study discusses the roles of the identified parameters in cancer development, thus underscoring the potential of explainable machine learning models for enhancing early breast cancer diagnosis by focusing on explainability and the use of serum biomarkers.The combination of both can lead to improved early detection and personalized treatments, emphasizing the potential of these methods in clinical settings. The identified markers also provide additional research and therapeutic targets for breast cancer pathogenesis and a deep understanding of their interactions, advancing personalized approaches to breast cancer management. Full article
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17 pages, 2881 KiB  
Article
Immediate Diagnosis of Breast Carcinoma on Core Needle Biopsy Using Ex Vivo Fluorescence Confocal Microscopy: Feasibility in a One-Stop Breast Clinic Workflow
by Marie-Christine Mathieu, Voichita Suciu, Marie-Laure Tanguy, Neila Ines Ben Romdhane, Salma Moalla, Sana Harguem-Zayani, Remy Barbe, Corinne Balleyguier, Angelica Conversano and Muriel Abbaci
Life 2024, 14(11), 1384; https://doi.org/10.3390/life14111384 - 28 Oct 2024
Cited by 1 | Viewed by 877
Abstract
Background: In the one-stop breast clinic setting, breast cytology traditionally provides immediate diagnosis of carcinoma. Fluorescence confocal microscopy (FCM) is an emerging optical technique enabling ex vivo analysis of breast biopsies in real-time. This study represents the first proof of concept for integrating [...] Read more.
Background: In the one-stop breast clinic setting, breast cytology traditionally provides immediate diagnosis of carcinoma. Fluorescence confocal microscopy (FCM) is an emerging optical technique enabling ex vivo analysis of breast biopsies in real-time. This study represents the first proof of concept for integrating FCM imaging into the routine workflow of breast core needle biopsies (CNB) at Gustave Roussy’s one-stop breast clinic. Methods: Fifty women with breast masses underwent consecutive enrollment. Biopsies were stained with acridine orange and fast green, followed by imaging using the Vivascope 2500M-G4 (FCM). Interpretation was conducted by two pathologists in real time (PT1) or postoperatively (PT2). Concordance with definitive histology, the duration of the FCM protocol, and its impact on conventional histopathology, immunohistochemistry, and FISH analyses were evaluated. Results: In our study of 50 biopsies, a concordant diagnosis of malignancy was performed using FCM on the malignant cases at definitive histology in 93.5% (29/31 cases) and in 90.3% (28/31 cases) according to PT1 and PT2, respectively. When the FCM suspicious cases were added, FCM identified 100% (31/31 cases) and 96.7% (30/31 cases) of the malignant cases according to PT1 and PT2, respectively. A notable false positive case was identified as a complex sclerosing lesion. The median time for sample preparation (including tissue reception) was 5 min, while the median time for imaging acquisition with interpretation was 3 min for PT1, but 1 min required for interpretation alone by PT2. Histopathological alterations were not more prevalent in FCM-imaged biopsies compared to conventionally treated biopsies. The immunophenotyping and molecular assessment of tissue were preserved after FCM protocol. Conclusions: FCM shows promise as a new histological method for the immediate diagnosis of breast carcinoma on core needle biopsies in a one-stop clinic setting, while also preserving tissue specimens for final histology. Full article
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