Updates on Breast Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Clinical Research of Cancer".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 53356

Special Issue Editors


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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,

Breast cancer is the most prevalent cancer among women worldwide. In recent decades, substantial advances in screening methods and early diagnosis, and breakthroughs in treatments have increased survival rates among women with breast cancer. In particular, advances in medical imaging and genetic knowledge and the introduction of artificial intelligence technology into radiological practice have paved the way for true personalized medicine through the implementation of radiomics, radiogenomics, and liquid biopsy. This -omics era, together with liquid biopsy, have also made it possible to identify  novel biomarkers involved in breast cancer development, survival and invasion, which can be gradually incorporated either into clinical testing or clinical trials. Together, clinical and molecular criteria can contribute to a more personalized management of women with breast cancer, predicting prognosis and therapeutic effects, chemotherapy, and endocrine therapy based on intrinsic subtype. In our Special Issue, we aim to collect original studies and comprehensive reviews investigating the new frontiers of diagnosis and novel management approaches for breast cancer care.

Dr. Enrico Cassano
Dr. Filippo Pesapane
Guest Editors

Manuscript Submission Information

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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
  • breast imaging
  • oncology
  • personalized medicine
  • radiomics
  • radiogenomics
  • artificial intelligence
  • liquid biopsy
  • transitional oncology

Published Papers (19 papers)

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Editorial

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4 pages, 183 KiB  
Editorial
Updates on Breast Cancer
by Filippo Pesapane, Luca Nicosia and Enrico Cassano
Cancers 2023, 15(22), 5392; https://doi.org/10.3390/cancers15225392 - 13 Nov 2023
Viewed by 940
Abstract
This collection of 18 articles, comprising 12 original studies, 1 systematic review, and 5 reviews, is a collaborative effort by distinguished experts in breast cancer research, and it has been edited by Dr [...] Full article
(This article belongs to the Special Issue Updates on Breast Cancer)

Research

Jump to: Editorial, Review, Other

11 pages, 1071 KiB  
Article
ONEST (Observers Needed to Evaluate Subjective Tests) Analysis of Stromal Tumour-Infiltrating Lymphocytes (sTILs) in Breast Cancer and Its Limitations
by Bálint Cserni, Darren Kilmartin, Mark O’Loughlin, Xavier Andreu, Zsuzsanna Bagó-Horváth, Simonetta Bianchi, Ewa Chmielik, Paulo Figueiredo, Giuseppe Floris, Maria Pia Foschini, Anikó Kovács, Päivi Heikkilä, Janina Kulka, Anne-Vibeke Laenkholm, Inta Liepniece-Karele, Caterina Marchiò, Elena Provenzano, Peter Regitnig, Angelika Reiner, Aleš Ryška, Anna Sapino, Elisabeth Specht Stovgaard, Cecily Quinn, Vasiliki Zolota, Mark Webber, Sharon A. Glynn, Rita Bori, Erika Csörgő, Orsolya Oláh-Németh, Tamás Pancsa, Anita Sejben, István Sejben, András Vörös, Tamás Zombori, Tibor Nyári, Grace Callagy and Gábor Cserniadd Show full author list remove Hide full author list
Cancers 2023, 15(4), 1199; https://doi.org/10.3390/cancers15041199 - 14 Feb 2023
Cited by 4 | Viewed by 1624
Abstract
Tumour-infiltrating lymphocytes (TILs) reflect antitumour immunity. Their evaluation of histopathology specimens is influenced by several factors and is subject to issues of reproducibility. ONEST (Observers Needed to Evaluate Subjective Tests) helps in determining the number of observers that would be sufficient for the [...] Read more.
Tumour-infiltrating lymphocytes (TILs) reflect antitumour immunity. Their evaluation of histopathology specimens is influenced by several factors and is subject to issues of reproducibility. ONEST (Observers Needed to Evaluate Subjective Tests) helps in determining the number of observers that would be sufficient for the reliable estimation of inter-observer agreement of TIL categorisation. This has not been explored previously in relation to TILs. ONEST analyses, using an open-source software developed by the first author, were performed on TIL quantification in breast cancers taken from two previous studies. These were one reproducibility study involving 49 breast cancers, 23 in the first circulation and 14 pathologists in the second circulation, and one study involving 100 cases and 9 pathologists. In addition to the estimates of the number of observers required, other factors influencing the results of ONEST were examined. The analyses reveal that between six and nine observers (range 2–11) are most commonly needed to give a robust estimate of reproducibility. In addition, the number and experience of observers, the distribution of values around or away from the extremes, and outliers in the classification also influence the results. Due to the simplicity and the potentially relevant information it may give, we propose ONEST to be a part of new reproducibility analyses. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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24 pages, 3486 KiB  
Article
SETD7 Expression Is Associated with Breast Cancer Survival Outcomes for Specific Molecular Subtypes: A Systematic Analysis of Publicly Available Datasets
by Fátima Liliana Monteiro, Lina Stepanauskaite, Cecilia Williams and Luisa A. Helguero
Cancers 2022, 14(24), 6029; https://doi.org/10.3390/cancers14246029 - 7 Dec 2022
Cited by 2 | Viewed by 1811
Abstract
SETD7 is a lysine N-methyltransferase that targets many proteins important in breast cancer (BC). However, its role and clinical significance remain unclear. Here, we used online tools and multiple public datasets to explore the predictive potential of SETD7 expression (high or low quartile) [...] Read more.
SETD7 is a lysine N-methyltransferase that targets many proteins important in breast cancer (BC). However, its role and clinical significance remain unclear. Here, we used online tools and multiple public datasets to explore the predictive potential of SETD7 expression (high or low quartile) considering BC subtype, grade, stage, and therapy. We also investigated overrepresented biological processes associated with its expression using TCGA-BRCA data. SETD7 expression was highest in the Her2 (ERBB2)-enriched molecular subtype and lowest in the basal-like subtype. For the basal-like subtype specifically, higher SETD7 was consistently correlated with worse recurrence-free survival (p < 0.009). High SETD7-expressing tumours further exhibited a higher rate of ERBB2 mutation (20% vs. 5%) along with a poorer response to anti-Her2 therapy. Overall, high SETD7-expressing tumours showed higher stromal and lower immune scores. This was specifically related to higher counts of cancer-associated fibroblasts and endothelial cells, but lower B and T cell signatures, especially in the luminal A subtype. Genes significantly associated with SETD7 expression were accordingly overrepresented in immune response processes, with distinct subtype characteristics. We conclude that the prognostic value of SETD7 depends on the BC subtype and that SETD7 may be further explored as a potential treatment-predictive marker for immune checkpoint inhibitors. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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14 pages, 1803 KiB  
Article
Survival in Breast Cancer Patients with Bone Metastasis: A Multicenter Real-World Study on the Prognostic Impact of Intensive Postoperative Bone Scan after Initial Diagnosis of Breast Cancer (CSBrS-023)
by Liu Yang, Wei Du, Taobo Hu, Miao Liu, Li Cai, Qiang Liu, Zhigang Yu, Guangyu Liu and Shu Wang
Cancers 2022, 14(23), 5835; https://doi.org/10.3390/cancers14235835 - 26 Nov 2022
Cited by 2 | Viewed by 1415
Abstract
The prognostic value of intensive postoperative bone scan (BS) screening, which is performed in asymptomatic patients with breast cancer (BC) after surgery, remained unclear. Patients diagnosed with BC with bone metastasis (BM) from five medical centers in China during the years 2005–2013 were [...] Read more.
The prognostic value of intensive postoperative bone scan (BS) screening, which is performed in asymptomatic patients with breast cancer (BC) after surgery, remained unclear. Patients diagnosed with BC with bone metastasis (BM) from five medical centers in China during the years 2005–2013 were retrospectively collected. Propensity score matching (PSM) was performed to balance the baseline characteristics. The survival outcomes were overall survival (OS) and overall survival after BM (OSABM). Among 1059 eligible patients, 304 underwent intensive postoperative BS while 755 did not. During a median follow-up of 6.67 years (95%CI 6.45, 7.21), intensive postoperative BS prolonged the median OS by 1.63 years (Log-Rank p = 0.006) and OSABM by 0.66 years (Log-Rank p = 0.002). Intensive postoperative BS was an independent prognostic factor for both OS (adjusted HR 0.77, 95%CI 0.64, 0.93, adjusted p = 0.006) and OSABM (adjusted HR 0.71, 95%CI 0.60, 0.86, adjusted p < 0.001). The prognostic value of intensive postoperative BS was consistently favorable for OS among clinical high-risk patients, including those with ages younger than 50, stage II, histology grade G3 and ER-Her2- subtype. This multicenter real-world study showed that intensive postoperative BS screening improved survival for BC patients with BM and should probably be recommended for postoperative surveillance, especially for patients at clinical high-risk. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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12 pages, 807 KiB  
Article
Immune-Related Gene Signatures to Predict the Effectiveness of Chemoimmunotherapy in Triple-Negative Breast Cancer Using Exploratory Subgroup Discovery
by Olha Kholod, William I. Basket, Jonathan B. Mitchem, Jussuf T. Kaifi, Richard D. Hammer, Christos N. Papageorgiou and Chi-Ren Shyu
Cancers 2022, 14(23), 5806; https://doi.org/10.3390/cancers14235806 - 25 Nov 2022
Cited by 2 | Viewed by 1675
Abstract
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited therapeutic options. Although immunotherapy has shown potential in TNBC patients, clinical studies have only demonstrated a modest response. Therefore, the exploration of immunotherapy in combination with chemotherapy is warranted. In [...] Read more.
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited therapeutic options. Although immunotherapy has shown potential in TNBC patients, clinical studies have only demonstrated a modest response. Therefore, the exploration of immunotherapy in combination with chemotherapy is warranted. In this project we identified immune-related gene signatures for TNBC patients that may explain differences in patients’ outcomes after anti-PD-L1+chemotherapy treatment. First, we ran the exploratory subgroup discovery algorithm on the TNBC dataset comprised of 422 patients across 24 studies. Secondly, we narrowed down the search to twelve homogenous subgroups based on tumor mutational burden (TMB, low or high), relapse status (disease-free or recurred), tumor cellularity (high, low and moderate), menopausal status (pre- or post) and tumor stage (I, II and III). For each subgroup we identified a union of the top 10% of genotypic patterns. Furthermore, we employed a multinomial regression model to predict significant genotypic patterns that would be linked to partial remission after anti-PD-L1+chemotherapy treatment. Finally, we uncovered distinct immune cell populations (T-cells, B-cells, Myeloid, NK-cells) for TNBC patients with various treatment outcomes. CD4-Tn-LEF1 and CD4-CXCL13 T-cells were linked to partial remission on anti-PD-L1+chemotherapy treatment. Our informatics pipeline may help to select better responders to chemoimmunotherapy, as well as pinpoint the underlying mechanisms of drug resistance in TNBC patients at single-cell resolution. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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26 pages, 2772 KiB  
Article
A Multi-Center Clinical Study to Harvest and Characterize Circulating Tumor Cells from Patients with Metastatic Breast Cancer Using the Parsortix® PC1 System
by Evan N. Cohen, Gitanjali Jayachandran, Richard G. Moore, Massimo Cristofanilli, Julie E. Lang, Joseph D. Khoury, Michael F. Press, Kyu Kwang Kim, Negar Khazan, Qiang Zhang, Youbin Zhang, Pushpinder Kaur, Roberta Guzman, Michael C. Miller, James M. Reuben and Naoto T. Ueno
Cancers 2022, 14(21), 5238; https://doi.org/10.3390/cancers14215238 - 26 Oct 2022
Cited by 16 | Viewed by 3246
Abstract
Circulating tumor cells (CTCs) captured from the blood of cancer patients may serve as a surrogate source of tumor material that can be obtained via a venipuncture (also known as a liquid biopsy) and used to better understand tumor characteristics. However, the only [...] Read more.
Circulating tumor cells (CTCs) captured from the blood of cancer patients may serve as a surrogate source of tumor material that can be obtained via a venipuncture (also known as a liquid biopsy) and used to better understand tumor characteristics. However, the only FDA-cleared CTC assay has been limited to the enumeration of surface marker–defined cells and not further characterization of the CTCs. In this study, we tested the ability of a semi-automated device capable of capturing and harvesting CTCs from peripheral blood based on cell size and deformability, agnostic of cell-surface markers (the Parsortix® PC1 System), to yield CTCs for evaluation by downstream techniques commonly available in clinical laboratories. The data generated from this study were used to support a De Novo request (DEN200062) for the classification of this device, which the FDA recently granted. As part of a multicenter clinical trial, peripheral blood samples from 216 patients with metastatic breast cancer (MBC) and 205 healthy volunteers were subjected to CTC enrichment. A board-certified pathologist enumerated the CTCs from each participant by cytologic evaluation of Wright-Giemsa-stained slides. As proof of principle, cells harvested from a concurrent parallel sample provided by each participant were evaluated using one of three additional evaluation techniques: molecular profiling by qRT-PCR, RNA sequencing, or cytogenetic analysis of HER2 amplification by FISH. The study demonstrated that the Parsortix® PC1 System can effectively capture and harvest CTCs from the peripheral blood of MBC patients and that the harvested cells can be evaluated using orthogonal methodologies such as gene expression and/or Fluorescence In Situ Hybridization (FISH). Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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11 pages, 483 KiB  
Article
HER2-Low Status Does Not Affect Survival Outcomes of Patients with Metastatic Breast Cancer (MBC) Undergoing First-Line Treatment with Endocrine Therapy plus Palbociclib: Results of a Multicenter, Retrospective Cohort Study
by Francesca Carlino, Anna Diana, Anna Ventriglia, Antonio Piccolo, Carmela Mocerino, Ferdinando Riccardi, Domenico Bilancia, Francesco Giotta, Giulio Antoniol, Vincenzo Famiglietti, Salvatore Feliciano, Rodolfo Cangiano, Lorenzo Lobianco, Benedetta Pellegrino, Ferdinando De Vita, Fortunato Ciardiello and Michele Orditura
Cancers 2022, 14(20), 4981; https://doi.org/10.3390/cancers14204981 - 11 Oct 2022
Cited by 20 | Viewed by 3296
Abstract
Background: Approximately 45–50% of breast cancers (BCs) have a HER2 immunohistochemical score of 1+ or 2+ with negative in situ hybridization, defining the “HER2-low BC” subtype. No anti-HER2 agents are currently approved for this subgroup in Europe, where treatment is still determined by [...] Read more.
Background: Approximately 45–50% of breast cancers (BCs) have a HER2 immunohistochemical score of 1+ or 2+ with negative in situ hybridization, defining the “HER2-low BC” subtype. No anti-HER2 agents are currently approved for this subgroup in Europe, where treatment is still determined by HR expression status. In this study, we investigated the prognostic significance of HER2-low status in HR+/HER2- metastatic BC (MBC) patients treated with endocrine therapy (ET) plus palbociclib as first line. Methods: We conducted a retrospective study including 252 consecutive HR+/HER2- MBC patients who received first-line ET plus palbociclib at six Italian Oncology Units between March 2016 and June 2021. The chi-square test was used to assess differences in the distribution of clinical and pathological variables between the HER-0 and HER2-low subgroups. Survival outcomes, progression-free survival (PFS) and overall survival (OS), were calculated by the Kaplan–Meier method, and the log-rank test was performed to estimate the differences between the curves. Results: A total of 165 patients were included in the analysis: 94 (57%) and 71 (43%) patients had HER2-0 and HER2-low disease, respectively. The median age at treatment start was 64 years. No correlation between patients and tumor characteristics and HER2 status was found. Median PFS (mPFS) for the entire study cohort was 20 months (95% CI,18–25 months), while median OS (mOS) was not reached at the time of analysis. No statistically significant differences, in terms of PFS (p = 0.20) and OS (p = 0.1), were observed between HER2-low and HER2-0 subgroups. Conclusions: In our analysis, HR+ MBC patients with low HER2 expression who received first-line treatment with ET plus Palbociclib reported no statistically different survival outcomes compared to HER2-0 patients. Further prospective studies are needed to confirm the clinical role of HER2 expression level. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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18 pages, 1282 KiB  
Article
Splicing Analysis of 16 PALB2 ClinVar Variants by Minigene Assays: Identification of Six Likely Pathogenic Variants
by Alberto Valenzuela-Palomo, Lara Sanoguera-Miralles, Elena Bueno-Martínez, Ada Esteban-Sánchez, Inés Llinares-Burguet, Alicia García-Álvarez, Pedro Pérez-Segura, Susana Gómez-Barrero, Miguel de la Hoya and Eladio A. Velasco-Sampedro
Cancers 2022, 14(18), 4541; https://doi.org/10.3390/cancers14184541 - 19 Sep 2022
Cited by 1 | Viewed by 2279
Abstract
PALB2 loss-of-function variants are associated with significant increased risk of breast cancer as well as other types of tumors. Likewise, splicing disruptions are a common mechanism of disease susceptibility. Indeed, we previously showed, by minigene assays, that 35 out of 42 PALB2 variants [...] Read more.
PALB2 loss-of-function variants are associated with significant increased risk of breast cancer as well as other types of tumors. Likewise, splicing disruptions are a common mechanism of disease susceptibility. Indeed, we previously showed, by minigene assays, that 35 out of 42 PALB2 variants impaired splicing. Taking advantage of one of these constructs (mgPALB2_ex1-3), we proceeded to analyze other variants at exons 1 to 3 reported at the ClinVar database. Thirty-one variants were bioinformatically analyzed with MaxEntScan and SpliceAI. Then, 16 variants were selected for subsequent RNA assays. We identified a total of 12 spliceogenic variants, 11 of which did not produce any trace of the expected minigene full-length transcript. Interestingly, variant c.49-1G > A mimicked previous outcomes in patient RNA (transcript ∆(E2p6)), supporting the reproducibility of the minigene approach. A total of eight variant-induced transcripts were characterized, three of which (∆(E1q17), ∆(E3p11), and ∆(E3)) were predicted to introduce a premature termination codon and to undergo nonsense-mediated decay, and five (▼(E1q9), ∆(E2p6), ∆(E2), ▼(E3q48)-a, and ▼(E3q48)-b) maintained the reading frame. According to an ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based classification scheme, which integrates mgPALB2 data, six PALB2 variants were classified as pathogenic/likely pathogenic, five as VUS, and five as likely benign. Furthermore, five ±1,2 variants were catalogued as VUS because they produced significant proportions of in-frame transcripts of unknown impact on protein function. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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24 pages, 2849 KiB  
Article
Mitochondrial Protein Cox7b Is a Metabolic Sensor Driving Brain-Specific Metastasis of Human Breast Cancer Cells
by Marine C. N. M. Blackman, Tania Capeloa, Justin D. Rondeau, Luca X. Zampieri, Zohra Benyahia, Justine A. Van de Velde, Maude Fransolet, Evangelos P. Daskalopoulos, Carine Michiels, Christophe Beauloye and Pierre Sonveaux
Cancers 2022, 14(18), 4371; https://doi.org/10.3390/cancers14184371 - 8 Sep 2022
Cited by 5 | Viewed by 2701
Abstract
Distant metastases are detrimental for cancer patients, but the increasingly early detection of tumors offers a chance for metastasis prevention. Importantly, cancers do not metastasize randomly: depending on the type of cancer, metastatic progenitor cells have a predilection for well-defined organs. This has [...] Read more.
Distant metastases are detrimental for cancer patients, but the increasingly early detection of tumors offers a chance for metastasis prevention. Importantly, cancers do not metastasize randomly: depending on the type of cancer, metastatic progenitor cells have a predilection for well-defined organs. This has been theorized by Stephen Paget, who proposed the “seed-and-soil hypothesis”, according to which metastatic colonization occurs only when the needs of a given metastatic progenitor cell (the seed) match with the resources provided by a given organ (the soil). Here, we propose to explore the seed-and-soil hypothesis in the context of cancer metabolism, thus hypothesizing that metastatic progenitor cells must be capable of detecting the availability of metabolic resources in order to home in a secondary organ. If true, it would imply the existence of metabolic sensors. Using human triple-negative MDA-MB-231 breast cancer cells and two independent brain-seeking variants as models, we report that cyclooxygenase 7b (Cox7b), a structural component of Complex IV of the mitochondrial electron transport chain, belongs to a probably larger family of proteins responsible for breast cancer brain tropism in mice. For metastasis prevention therapy, this proof-of-principle study opens a quest for the identification of therapeutically targetable metabolic sensors that drive cancer organotropism. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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16 pages, 951 KiB  
Article
Connected-SegNets: A Deep Learning Model for Breast Tumor Segmentation from X-ray Images
by Mohammad Alkhaleefah, Tan-Hsu Tan, Chuan-Hsun Chang, Tzu-Chuan Wang, Shang-Chih Ma, Lena Chang and Yang-Lang Chang
Cancers 2022, 14(16), 4030; https://doi.org/10.3390/cancers14164030 - 20 Aug 2022
Cited by 10 | Viewed by 2361 | Correction
Abstract
Inspired by Connected-UNets, this study proposes a deep learning model, called Connected-SegNets, for breast tumor segmentation from X-ray images. In the proposed model, two SegNet architectures are connected with skip connections between their layers. Moreover, the cross-entropy loss function of the original SegNet [...] Read more.
Inspired by Connected-UNets, this study proposes a deep learning model, called Connected-SegNets, for breast tumor segmentation from X-ray images. In the proposed model, two SegNet architectures are connected with skip connections between their layers. Moreover, the cross-entropy loss function of the original SegNet has been replaced by the intersection over union (IoU) loss function in order to make the proposed model more robust against noise during the training process. As part of data preprocessing, a histogram equalization technique, called contrast limit adapt histogram equalization (CLAHE), is applied to all datasets to enhance the compressed regions and smooth the distribution of the pixels. Additionally, two image augmentation methods, namely rotation and flipping, are used to increase the amount of training data and to prevent overfitting. The proposed model has been evaluated on two publicly available datasets, specifically INbreast and the curated breast imaging subset of digital database for screening mammography (CBIS-DDSM). The proposed model has also been evaluated using a private dataset obtained from Cheng Hsin General Hospital in Taiwan. The experimental results show that the proposed Connected-SegNets model outperforms the state-of-the-art methods in terms of Dice score and IoU score. The proposed Connected-SegNets produces a maximum Dice score of 96.34% on the INbreast dataset, 92.86% on the CBIS-DDSM dataset, and 92.25% on the private dataset. Furthermore, the experimental results show that the proposed model achieves the highest IoU score of 91.21%, 87.34%, and 83.71% on INbreast, CBIS-DDSM, and the private dataset, respectively. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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13 pages, 1262 KiB  
Article
Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography
by Antonella Petrillo, Roberta Fusco, Elio Di Bernardo, Teresa Petrosino, Maria Luisa Barretta, Annamaria Porto, Vincenza Granata, Maurizio Di Bonito, Annarita Fanizzi, Raffaella Massafra, Nicole Petruzzellis, Francesca Arezzo, Luca Boldrini and Daniele La Forgia
Cancers 2022, 14(9), 2132; https://doi.org/10.3390/cancers14092132 - 25 Apr 2022
Cited by 29 | Viewed by 2912
Abstract
Purpose: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. Methods: A [...] Read more.
Purpose: To evaluate radiomics features in order to: differentiate malignant versus benign lesions; predict low versus moderate and high grading; identify positive or negative hormone receptors; and discriminate positive versus negative human epidermal growth factor receptor 2 related to breast cancer. Methods: A total of 182 patients with known breast lesions and that underwent Contrast-Enhanced Mammography were enrolled in this retrospective study. The reference standard was pathology (118 malignant lesions and 64 benign lesions). A total of 837 textural metrics were extracted by manually segmenting the region of interest from both craniocaudally (CC) and mediolateral oblique (MLO) views. Non-parametric Wilcoxon–Mann–Whitney test, receiver operating characteristic, logistic regression and tree-based machine learning algorithms were used. The Adaptive Synthetic Sampling balancing approach was used and a feature selection process was implemented. Results: In univariate analysis, the classification of malignant versus benign lesions achieved the best performance when considering the original_gldm_DependenceNonUniformity feature extracted on CC view (accuracy of 88.98%). An accuracy of 83.65% was reached in the classification of grading, whereas a slightly lower value of accuracy (81.65%) was found in the classification of the presence of the hormone receptor; the features extracted were the original_glrlm_RunEntropy and the original_gldm_DependenceNonUniformity, respectively. The results of multivariate analysis achieved the best performances when using two or more features as predictors for classifying malignant versus benign lesions from CC view images (max test accuracy of 95.83% with a non-regularized logistic regression). Considering the features extracted from MLO view images, the best test accuracy (91.67%) was obtained when predicting the grading using a classification-tree algorithm. Combinations of only two features, extracted from both CC and MLO views, always showed test accuracy values greater than or equal to 90.00%, with the only exception being the prediction of the human epidermal growth factor receptor 2, where the best performance (test accuracy of 89.29%) was obtained with the random forest algorithm. Conclusions: The results confirm that the identification of malignant breast lesions and the differentiation of histological outcomes and some molecular subtypes of tumors (mainly positive hormone receptor tumors) can be obtained with satisfactory accuracy through both univariate and multivariate analysis of textural features extracted from Contrast-Enhanced Mammography images. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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11 pages, 2419 KiB  
Article
A Model to Predict Upstaging to Invasive Carcinoma in Patients Preoperatively Diagnosed with Low-Grade Ductal Carcinoma In Situ of the Breast
by Luca Nicosia, Anna Carla Bozzini, Silvia Penco, Chiara Trentin, Maria Pizzamiglio, Matteo Lazzeroni, Germana Lissidini, Paolo Veronesi, Gabriel Farante, Samuele Frassoni, Vincenzo Bagnardi, Cristiana Fodor, Nicola Fusco, Elham Sajjadi, Enrico Cassano and Filippo Pesapane
Cancers 2022, 14(2), 370; https://doi.org/10.3390/cancers14020370 - 12 Jan 2022
Cited by 6 | Viewed by 2038
Abstract
Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: A total of [...] Read more.
Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: A total of 3100 VABBs were retrospectively reviewed, among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients’ features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate and multivariate analysis. Finally, we developed a nomogram for predicting the upstage at surgery, according to the multivariate logistic regression model. Results: The overall upgrade rate to invasive carcinoma was 10.8%. At univariate analysis, the risk of upgrade was significantly lower in patients with greater age (p = 0.018), without post-biopsy residual lesion (p < 0.001), with a smaller post-biopsy residual lesion size (p < 0.001), and in the presence of low-grade DCIS only in specimens with microcalcifications (p = 0.002). According to the final multivariable model, the predicted probability of upstage at surgery was lower than 2% in 58 patients; among these 58 patients, only one (1.7%) upstage was observed, showing a good calibration of the model. Conclusions: An easy-to-use nomogram for predicting the upstage at surgery based on radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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Review

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17 pages, 1262 KiB  
Review
Impact of the Cancer Cell Secretome in Driving Breast Cancer Progression
by Syazalina Zahari, Saiful Effendi Syafruddin and M. Aiman Mohtar
Cancers 2023, 15(9), 2653; https://doi.org/10.3390/cancers15092653 - 8 May 2023
Cited by 5 | Viewed by 2992
Abstract
Breast cancer is a complex and heterogeneous disease resulting from the accumulation of genetic and epigenetic alterations in breast epithelial cells. Despite remarkable progress in diagnosis and treatment, breast cancer continues to be the most prevalent cancer affecting women worldwide. Recent research has [...] Read more.
Breast cancer is a complex and heterogeneous disease resulting from the accumulation of genetic and epigenetic alterations in breast epithelial cells. Despite remarkable progress in diagnosis and treatment, breast cancer continues to be the most prevalent cancer affecting women worldwide. Recent research has uncovered a compelling link between breast cancer onset and the extracellular environment enveloping tumor cells. The complex network of proteins secreted by cancer cells and other cellular components within the tumor microenvironment has emerged as a critical player in driving the disease’s metastatic properties. Specifically, the proteins released by the tumor cells termed the secretome, can significantly influence the progression and metastasis of breast cancer. The breast cancer cell secretome promotes tumorigenesis through its ability to modulate growth-associated signaling pathways, reshaping the tumor microenvironment, supporting pre-metastatic niche formation, and facilitating immunosurveillance evasion. Additionally, the secretome has been shown to play a crucial role in drug resistance development, making it an attractive target for cancer therapy. Understanding the intricate role of the cancer cell secretome in breast cancer progression will provide new insights into the underlying mechanisms of this disease and aid in the development of more innovative therapeutic interventions. Hence, this review provides a nuanced analysis of the impact of the cancer cell secretome on breast cancer progression, elucidates the complex reciprocal interaction with the components of the tumor microenvironment and highlights emerging therapeutic opportunities for targeting the constituents of the secretome. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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26 pages, 1183 KiB  
Review
Clinical Utility of Genomic Tests Evaluating Homologous Recombination Repair Deficiency (HRD) for Treatment Decisions in Early and Metastatic Breast Cancer
by Loïck Galland, Nicolas Roussot, Isabelle Desmoulins, Didier Mayeur, Courèche Kaderbhai, Silvia Ilie, Audrey Hennequin, Manon Reda, Juliette Albuisson, Laurent Arnould, Romain Boidot, Caroline Truntzer, François Ghiringhelli and Sylvain Ladoire
Cancers 2023, 15(4), 1299; https://doi.org/10.3390/cancers15041299 - 18 Feb 2023
Cited by 4 | Viewed by 3697
Abstract
Breast cancer is the most frequently occurring cancer worldwide. With its increasing incidence, it is a major public health problem, with many therapeutic challenges such as precision medicine for personalized treatment. Thanks to next-generation sequencing (NGS), progress in biomedical technologies, and the use [...] Read more.
Breast cancer is the most frequently occurring cancer worldwide. With its increasing incidence, it is a major public health problem, with many therapeutic challenges such as precision medicine for personalized treatment. Thanks to next-generation sequencing (NGS), progress in biomedical technologies, and the use of bioinformatics, it is now possible to identify specific molecular alterations in tumor cells—such as homologous recombination deficiencies (HRD)—enabling us to consider using DNA-damaging agents such as platinum salts or PARP inhibitors. Different approaches currently exist to analyze impairment of the homologous recombination pathway, e.g., the search for specific mutations in homologous recombination repair (HRR) genes, such as BRCA1/2; the use of genomic scars or mutational signatures; or the development of functional tests. Nevertheless, the role and value of these different tests in breast cancer treatment decisions remains to be clarified. In this review, we summarize current knowledge on the clinical utility of genomic tests, evaluating HRR deficiency for treatment decisions in early and metastatic breast cancer. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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34 pages, 459 KiB  
Review
Recent Advances in Optimizing Radiation Therapy Decisions in Early Invasive Breast Cancer
by Nazia Riaz, Tiffany Jeen, Timothy J. Whelan and Torsten O. Nielsen
Cancers 2023, 15(4), 1260; https://doi.org/10.3390/cancers15041260 - 16 Feb 2023
Cited by 8 | Viewed by 2925
Abstract
Adjuvant whole breast irradiation after breast-conserving surgery is a well-established treatment standard for early invasive breast cancer. Screening, early diagnosis, refinement in surgical techniques, the knowledge of new and specific molecular prognostic factors, and now the standard use of more effective neo/adjuvant systemic [...] Read more.
Adjuvant whole breast irradiation after breast-conserving surgery is a well-established treatment standard for early invasive breast cancer. Screening, early diagnosis, refinement in surgical techniques, the knowledge of new and specific molecular prognostic factors, and now the standard use of more effective neo/adjuvant systemic therapies have proven instrumental in reducing the rates of locoregional relapses. This underscores the need for reliably identifying women with such low-risk disease burdens in whom elimination of radiation from the treatment plan would not compromise oncological safety. This review summarizes the current evidence for radiation de-intensification strategies and details ongoing prospective clinical trials investigating the omission of adjuvant whole breast irradiation in molecularly defined low-risk breast cancers and related evidence supporting the potential for radiation de-escalation in HER2+ and triple-negative clinical subtypes. Furthermore, we discuss the current evidence for the de-escalation of regional nodal irradiation after neoadjuvant chemotherapy. Finally, we also detail the current knowledge of the clinical value of stromal tumor-infiltrating lymphocytes and liquid-based biomarkers as prognostic factors for locoregional relapse. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
15 pages, 1817 KiB  
Review
Current Biological, Pathological and Clinical Landscape of HER2-Low Breast Cancer
by Huina Zhang and Yan Peng
Cancers 2023, 15(1), 126; https://doi.org/10.3390/cancers15010126 - 25 Dec 2022
Cited by 19 | Viewed by 8460
Abstract
HER2-low breast cancer (BC) is a newly defined subset of HER2-negative BC that has HER2 immunohistochemical (IHC) score of 1+ or score of 2+/in situ hybridization (ISH) negative phenotype. Recent clinical trials have demonstrated significant clinical benefits of novel HER2 directing antibody-drug conjugates [...] Read more.
HER2-low breast cancer (BC) is a newly defined subset of HER2-negative BC that has HER2 immunohistochemical (IHC) score of 1+ or score of 2+/in situ hybridization (ISH) negative phenotype. Recent clinical trials have demonstrated significant clinical benefits of novel HER2 directing antibody-drug conjugates (ADCs) in treating this group of tumors. Trastuzumab-deruxtecan (T-Dxd), a HER2-directing ADC was recently approved by the U.S. Food and Drug Administration as the first targeted therapy to treat HER2-low BC. However, HER2-low BC is still not well characterized clinically and pathologically. This review aims to update the current biological, pathological and clinical landscape of HER2-low BC based on the English literature published in the past two years and to propose the future directions on clinical management, pathology practice, and translational research in this subset of BC. We hope it would help better understand the tumor biology of HER2-low BC and the current efforts for identifying and treating this newly recognized targetable group of BC. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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21 pages, 1740 KiB  
Review
The Role of the Aryl Hydrocarbon Receptor (AhR) and Its Ligands in Breast Cancer
by Stephen Safe and Lei Zhang
Cancers 2022, 14(22), 5574; https://doi.org/10.3390/cancers14225574 - 14 Nov 2022
Cited by 20 | Viewed by 2216
Abstract
Breast cancer is a complex disease which is defined by numerous cellular and molecular markers that can be used to develop more targeted and successful therapies. The aryl hydrocarbon receptor (AhR) is overexpressed in many breast tumor sub-types, including estrogen receptor -positive (ER+) [...] Read more.
Breast cancer is a complex disease which is defined by numerous cellular and molecular markers that can be used to develop more targeted and successful therapies. The aryl hydrocarbon receptor (AhR) is overexpressed in many breast tumor sub-types, including estrogen receptor -positive (ER+) tumors; however, the prognostic value of the AhR for breast cancer patient survival is not consistent between studies. Moreover, the functional role of the AhR in various breast cancer cell lines is also variable and exhibits both tumor promoter- and tumor suppressor- like activity and the AhR is expressed in both ER-positive and ER-negative cells/tumors. There is strong evidence demonstrating inhibitory AhR-Rα crosstalk where various AhR ligands induce ER degradation. It has also been reported that different structural classes of AhR ligands, including halogenated aromatics, polynuclear aromatics, synthetic drugs and other pharmaceuticals, health promoting phytochemical-derived natural products and endogenous AhR-active compounds inhibit one or more of breast cancer cell proliferation, survival, migration/invasion, and metastasis. AhR–dependent mechanisms for the inhibition of breast cancer by AhR agonists are variable and include the downregulation of multiple genes/gene products such as CXCR4, MMPs, CXCL12, SOX4 and the modulation of microRNA levels. Some AhR ligands, such as aminoflavone, have been investigated in clinical trials for their anticancer activity against breast cancer. In contrast, several publications have reported that AhR agonists and antagonists enhance and inhibit mammary carcinogenesis, respectively, and differences between the anticancer activities of AhR agonists in breast cancer may be due in part to cell context and ligand structure. However, there are reports showing that the same AhR ligand in the same breast cancer cell line gives opposite results. These differences need to be resolved in order to further develop and take advantage of promising agents that inhibit mammary carcinogenesis by targeting the AhR. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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Other

1 pages, 359 KiB  
Correction
Correction: Alkhaleefah et al. Connected-SegNets: A Deep Learning Model for Breast Tumor Segmentation from X-ray Images. Cancers 2022, 14, 4030
by Mohammad Alkhaleefah, Tan-Hsu Tan, Chuan-Hsun Chang, Tzu-Chuan Wang, Shang-Chih Ma, Lena Chang and Yang-Lang Chang
Cancers 2023, 15(8), 2237; https://doi.org/10.3390/cancers15082237 - 11 Apr 2023
Cited by 1 | Viewed by 790
Abstract
In the original publication [...] Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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11 pages, 550 KiB  
Systematic Review
The Use of Artificial Intelligence (AI) in the Radiology Field: What Is the State of Doctor–Patient Communication in Cancer Diagnosis?
by Alexandra Derevianko, Silvia Francesca Maria Pizzoli, Filippo Pesapane, Anna Rotili, Dario Monzani, Roberto Grasso, Enrico Cassano and Gabriella Pravettoni
Cancers 2023, 15(2), 470; https://doi.org/10.3390/cancers15020470 - 12 Jan 2023
Cited by 21 | Viewed by 3886
Abstract
Background: In the past decade, interest in applying Artificial Intelligence (AI) in radiology to improve diagnostic procedures increased. AI has potential benefits spanning all steps of the imaging chain, from the prescription of diagnostic tests to the communication of test reports. The use [...] Read more.
Background: In the past decade, interest in applying Artificial Intelligence (AI) in radiology to improve diagnostic procedures increased. AI has potential benefits spanning all steps of the imaging chain, from the prescription of diagnostic tests to the communication of test reports. The use of AI in the field of radiology also poses challenges in doctor–patient communication at the time of the diagnosis. This systematic review focuses on the patient role and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Methods: A systematic search was conducted on PubMed, Embase, Medline, Scopus, and PsycNet from 1990 to 2021. The search terms were: (“artificial intelligence” or “intelligence machine”) and “communication” “radiology” and “oncology diagnosis”. The PRISMA guidelines were followed. Results: 517 records were identified, and 5 papers met the inclusion criteria and were analyzed. Most of the articles emphasized the success of the technological support of AI in radiology at the expense of patient trust in AI and patient-centered communication in cancer disease. Practical implications and future guidelines were discussed according to the results. Conclusions: AI has proven to be beneficial in helping clinicians with diagnosis. Future research may improve patients’ trust through adequate information about the advantageous use of AI and an increase in medical compliance with adequate training on doctor–patient diagnosis communication. Full article
(This article belongs to the Special Issue Updates on Breast Cancer)
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