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Cancers
Special Issues
New Challenges in Breast Cancer Diagnosis and Management
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New Challenges in Breast Cancer Diagnosis and Management

A special issue of Cancers (ISSN 2072-6694).

Deadline for manuscript submissions: closed (10 February 2023) | Viewed by 11640

Special Issue Editors

Dr. Luca Nicosia

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Guest Editor
Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
Interests: breast imaging
Special Issues, Collections and Topics in MDPI journals
Dr. Filippo Pesapane

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Guest Editor
Breast Imaging Unit, European Institute of Oncology (IEO), 20141 Milan, Italy
Interests: radiology; artificial intelligence; radiomics; cancer imaging; breast imaging
Special Issues, Collections and Topics in MDPI journals
Dr. Enrico Cassano

E-Mail Website
Guest Editor
Breast Imaging Unit, IEO European Institute of Oncology IRCCS, Milan, Italy
Interests: breast cancer; breast Imaging; radiology; biopsies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

We would like to propose a Special Issue on the new challenges in the treatment of breast cancer. The diagnosis and management of breast neoplasia have evolved remarkably in recent years, especially with increased knowledge in the field of radiomics, artificial intelligence, and precision medicine. It is now widely acknowledged that imaging data contain numerous and useful information concerning the tumour’s biology, behaviour, and pathophysiology. In this scenario, personalized and precision medicine is one of the main protagonists of scientific development nowadays, especially considering the advances in molecular imaging and genetic knowledge and the introduction of artificial intelligence technology into clinical practice.

We are pleased to invite you to submit research that may improve our knowledge of new diagnostic procedures in the field of breast cancer. Research that improves our knowledge in the management post-diagnosis of these patients will also be appreciated.

This Special Issue aims to create an increasingly precise and personalized diagnosis and post-diagnosis pathway that will improve the outcome for people with breast cancer.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: new methods for the diagnosis of breast neoplasia (including radiomics and artificial intelligence) and new methods for the management of patients with breast neoplasia (including molecular and genetics studies).

 

Dr. Luca Nicosia
Dr. Enrico Cassano
Dr. Filippo Pesapane

Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • breast cancer imaging
  • radiomics
  • artificial intelligence
  • oncology
  • radiology
  • radiogenomics
  • future prospectives
  • radiogenomics

Published Papers (4 papers)

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Research

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17 pages, 47207 KiB  
Article
Mir-153-3p Modulates the Breast Cancer Cells’ Chemosensitivity to Doxorubicin by Targeting KIF20A
by Khalil Ur Rahman, Shuo Yang, Nasir Azam, Zhen Yuan, Jiawen Yu, Chunhui Zhao and Bin Feng
Cancers 2023, 15(6), 1724; https://doi.org/10.3390/cancers15061724 - 11 Mar 2023
Viewed by 1597
Abstract
Breast cancer is considered the solid tumor most sensitive to chemotherapy. However, it can become resistant to various chemotherapeutic drugs, including doxorubicin, which triggers cell death by intercalation between DNA bases, free radical formation, and topoisomerase II inhibition. When drug resistance develops, several [...] Read more.
Breast cancer is considered the solid tumor most sensitive to chemotherapy. However, it can become resistant to various chemotherapeutic drugs, including doxorubicin, which triggers cell death by intercalation between DNA bases, free radical formation, and topoisomerase II inhibition. When drug resistance develops, several miRNAs are dysregulated, suggesting that miRNAs may play a significant role in resistance formation. In the current study, we investigated how doxorubicin sensitivity of breast cancer cells is affected by miR-153-3p and its target gene. The MTT method was used to determine the chemo-sensitizing effect of miR-153-3p on doxorubicin in MCF-7 and MDA-MB-231 cell lines. Results of Western blot and dual luciferase confirmed that miR-153-3p targets KIF20A and decreases its expression. Transwell and flow cytometry experiments showed that miR-153-3p and doxorubicin together had higher effects on MCF-7 and MDA-MB-231 cell proliferation, migration, and invasion, as well as increasing apoptosis and arresting cells in the G1 phase. Proteins related to apoptosis and the cell cycle exhibited the same tendency. Intracellular vesicle formation was inhibited and RAB26 was also downregulated by treatment with miR-153-3p alone or in combination with doxorubicin. Doxorubicin’s ability to suppress tumors may be enhanced by miR-153-3p, according to in vivo studies. According to our findings, miR-153-3p has a direct effect on KIF20A and may regulate the formation of intracellular vesicles, which in turn makes breast cancer cells more susceptible to doxorubicin. Full article
(This article belongs to the Special Issue New Challenges in Breast Cancer Diagnosis and Management)
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10 pages, 1350 KiB  
Article
Prediction of the Malignancy of a Breast Lesion Detected on Breast Ultrasound: Radiomics Applied to Clinical Practice
by Luca Nicosia, Filippo Pesapane, Anna Carla Bozzini, Antuono Latronico, Anna Rotili, Federica Ferrari, Giulia Signorelli, Sara Raimondi, Silvano Vignati, Aurora Gaeta, Federica Bellerba, Daniela Origgi, Paolo De Marco, Giuseppe Castiglione Minischetti, Claudia Sangalli, Marta Montesano, Simone Palma and Enrico Cassano
Cancers 2023, 15(3), 964; https://doi.org/10.3390/cancers15030964 - 02 Feb 2023
Cited by 5 | Viewed by 5482
Abstract
The study aimed to evaluate the performance of radiomics features and one ultrasound CAD (computer-aided diagnosis) in the prediction of the malignancy of a breast lesion detected with ultrasound and to develop a nomogram incorporating radiomic score and available information on CAD performance, [...] Read more.
The study aimed to evaluate the performance of radiomics features and one ultrasound CAD (computer-aided diagnosis) in the prediction of the malignancy of a breast lesion detected with ultrasound and to develop a nomogram incorporating radiomic score and available information on CAD performance, conventional Breast Imaging Reporting and Data System evaluation (BI-RADS), and clinical information. Data on 365 breast lesions referred for breast US with subsequent histologic analysis between January 2020 and March 2022 were retrospectively collected. Patients were randomly divided into a training group (n = 255) and a validation test group (n = 110). A radiomics score was generated from the US image. The CAD was performed in a subgroup of 209 cases. The radiomics score included seven radiomics features selected with the LASSO logistic regression model. The multivariable logistic model incorporating CAD performance, BI-RADS evaluation, clinical information, and radiomic score as covariates showed promising results in the prediction of the malignancy of breast lesions: Area under the receiver operating characteristic curve, [AUC]: 0.914; 95% Confidence Interval, [CI]: 0.876–0.951. A nomogram was developed based on these results for possible future applications in clinical practice. Full article
(This article belongs to the Special Issue New Challenges in Breast Cancer Diagnosis and Management)
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12 pages, 2150 KiB  
Article
A Score to Predict the Malignancy of a Breast Lesion Based on Different Contrast Enhancement Patterns in Contrast-Enhanced Spectral Mammography
by Luca Nicosia, Anna Carla Bozzini, Simone Palma, Marta Montesano, Filippo Pesapane, Federica Ferrari, Valeria Dominelli, Anna Rotili, Lorenza Meneghetti, Samuele Frassoni, Vincenzo Bagnardi, Claudia Sangalli and Enrico Cassano
Cancers 2022, 14(17), 4337; https://doi.org/10.3390/cancers14174337 - 05 Sep 2022
Cited by 10 | Viewed by 1652
Abstract
Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January [...] Read more.
Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January 2013 and February 2022. All participants underwent CESM prior to breast biopsy, and eventually surgery. A radiologist with 20 years’ experience in breast imaging evaluated the presence or absence of enhancement and the following enhancement descriptors: intensity, pattern, margin, and ground glass. A score of 0 or 1 was given for each descriptor, depending on whether the enhancement characteristic was predictive of benignity or malignancy (both in situ and invasive). Then, an overall enhancement score ranging from 0 to 4 was obtained. The histological results were considered the gold standard in the evaluation of the relationship between enhancement patterns and malignancy. Results: A total of 321 women (median age: 51 years; range: 22–83) with 377 suspicious breast lesions were evaluated. Two hundred forty-nine lesions (66%) have malignant histological results (217 invasive and 32 in situ). Considering an overall enhancement score ≥ 2 as predictive of malignancy, we obtain an overall sensitivity of 92.4%; specificity of 89.8%; positive predictive value of 94.7%; and negative predictive value of 85.8%. Conclusions: Our proposed predictive score on the enhancement descriptors of CESM to predict the malignancy of a breast lesion shows excellent results and can help in early breast cancer diagnosis and in avoiding unnecessary biopsies. Full article
(This article belongs to the Special Issue New Challenges in Breast Cancer Diagnosis and Management)
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Review

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15 pages, 319 KiB  
Review
Surgical Management of Inherited Breast Cancer: Role of Breast-Conserving Surgery
by Francesca Magnoni, Virgilio Sacchini, Paolo Veronesi, Beatrice Bianchi, Elisa Bottazzoli, Valentina Tagliaferri, Erica Mazzotta, Giulia Castelnovo, Giulia Deguidi, Elisabetta Maria Cristina Rossi and Giovanni Corso
Cancers 2022, 14(13), 3245; https://doi.org/10.3390/cancers14133245 - 01 Jul 2022
Cited by 4 | Viewed by 2007
Abstract
Recent studies have demonstrated that hereditary breast cancer (BC) has a prevalence of 5–10% among all BC diagnoses. Nowadays, significant technological advances in the identification of an increasingly broad spectrum of genetic mutations allow for the discovery of an ever-growing number of inherited [...] Read more.
Recent studies have demonstrated that hereditary breast cancer (BC) has a prevalence of 5–10% among all BC diagnoses. Nowadays, significant technological advances in the identification of an increasingly broad spectrum of genetic mutations allow for the discovery of an ever-growing number of inherited pathogenic (P) or likely pathogenic (LP) variants of breast cancer susceptibility genes. As the management of BC patients carrying mutations in the BRCA1/2 genes or other high-penetrance genes is currently a challenge, extensive research is being carried out and a lively scientific debate has been taking place on what the most appropriate local therapy, especially surgical treatment, of patients with inherited BC should be. In many studies, BC outcomes in BRCA carriers and non-carriers have been compared. A number of them showed that, when compared with mastectomy, breast-conserving surgery in BRCA patients is oncologically safe in terms of overall survival, although an increased risk of ipsilateral recurrence was reported. In these patients, devising a specific therapeutic strategy is an inevitably complex process, as it must take into consideration a series of factors, require a multimodal approach, guarantee personalization, strictly adhere to scientific international guidelines, and consider all available evidence. The present narrative review purposes to identify and illustrate evidence from significant selected studies that discussed those issues, as well as to suggest useful tools to clinicians managing this specific clinical condition in daily clinical practice. Full article
(This article belongs to the Special Issue New Challenges in Breast Cancer Diagnosis and Management)
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