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New Insights into Breast Cancer Management: From Tumorigenesis to Personalized...
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New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Oncology".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 8649

Special Issue Editors

Dr. Paola Tiberio

E-Mail Website
Guest Editor
Medical Oncology and Hematology Unit, IRCCS Humanitas Research Hospital, 20089 Rozzano (Milan), Italy
Interests: breast cancer; neoadjuvant chemotherapy; supportive therapies; biomarkers; liquid biopsy
Dr. Rita De Sanctis

E-Mail Website
Co-Guest Editor
Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, Pieve Emanuele, 20090 Milan, Italy
Interests: breast cancer; neoadjuvant chemotherapy; pathological complete response; prognosis; predictive factors; microbiome; radiomics; headache disorders; quality of life; nomograms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Breast cancer is a very heterogeneous disease with multifactorial etiopathogenesis. Over the last few decades, a deeper understanding of the molecular mechanisms underlying breast cancer development and progression has led to the development of novel accurate prognostic analyses and new effective drugs, thus leading to an increase in the overall survival of breast cancer patients. Nevertheless, breast cancer remains the second leading cause of death in women globally. Thus, there is still a need for a better comprehension of the complexity of breast cancer and the interaction between the neoplasm and its microenvironment as well as the immune system in order to prevent disease development and to guide personalized treatments. Moreover, since individual response to therapy and long-term prognosis remain highly unpredictable, the current scenario requires the identification of biomarkers that accurately forecast the response to therapy and identify patients who will not benefit from standard regimens. On the other hand, since the number of breast cancer survivors is continuously increasing, knowing the complexity of breast cancer survivorship is essential for adequate patient management.

Dr. Paola Tiberio
Guest Editor

Dr. Rita De Sanctis
Co-Guest Editor

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Keywords

  • breast cancer
  • diagnosis
  • prognosis
  • treatment response prediction
  • biomarkers, risk factors
  • new therapies

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Published Papers (7 papers)

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Research

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14 pages, 2792 KiB  
Article
Breast Cancer Molecular Subtype Prediction: A Mammography-Based AI Approach
by Ana M. Mota, João Mendes and Nuno Matela
Biomedicines 2024, 12(6), 1371; https://doi.org/10.3390/biomedicines12061371 - 20 Jun 2024
Cited by 1 | Viewed by 1275
Abstract
Breast cancer remains a leading cause of mortality among women, with molecular subtypes significantly influencing prognosis and treatment strategies. Currently, identifying the molecular subtype of cancer requires a biopsy—a specialized, expensive, and time-consuming procedure, often yielding to results that must be supported with [...] Read more.
Breast cancer remains a leading cause of mortality among women, with molecular subtypes significantly influencing prognosis and treatment strategies. Currently, identifying the molecular subtype of cancer requires a biopsy—a specialized, expensive, and time-consuming procedure, often yielding to results that must be supported with additional biopsies due to technique errors or tumor heterogeneity. This study introduces a novel approach for predicting breast cancer molecular subtypes using mammography images and advanced artificial intelligence (AI) methodologies. Using the OPTIMAM imaging database, 1397 images from 660 patients were selected. The pretrained deep learning model ResNet-101 was employed to classify tumors into five subtypes: Luminal A, Luminal B1, Luminal B2, HER2, and Triple Negative. Various classification strategies were studied: binary classifications (one vs. all others, specific combinations) and multi-class classification (evaluating all subtypes simultaneously). To address imbalanced data, strategies like oversampling, undersampling, and data augmentation were explored. Performance was evaluated using accuracy and area under the receiver operating characteristic curve (AUC). Binary classification results showed a maximum average accuracy and AUC of 79.02% and 64.69%, respectively, while multi-class classification achieved an average AUC of 60.62% with oversampling and data augmentation. The most notable binary classification was HER2 vs. non-HER2, with an accuracy of 89.79% and an AUC of 73.31%. Binary classification for specific combinations of subtypes revealed an accuracy of 76.42% for HER2 vs. Luminal A and an AUC of 73.04% for HER2 vs. Luminal B1. These findings highlight the potential of mammography-based AI for non-invasive breast cancer subtype prediction, offering a promising alternative to biopsies and paving the way for personalized treatment plans. Full article
(This article belongs to the Special Issue New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments)
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15 pages, 2609 KiB  
Article
BRCA1, BRCA2 and PALB2 mRNA Expression as Prognostic Markers in Patients with Early Breast Cancer
by Ina Shehaj, Slavomir Krajnak, Katrin Almstedt, Yaman Degirmenci, Sophia Herzog, Antje Lebrecht, Valerie Catherine Linz, Roxana Schwab, Kathrin Stewen, Walburgis Brenner, Annette Hasenburg, Marcus Schmidt and Anne-Sophie Heimes
Biomedicines 2024, 12(6), 1361; https://doi.org/10.3390/biomedicines12061361 - 19 Jun 2024
Cited by 1 | Viewed by 847
Abstract
Breast cancer (BC) poses a challenge in establishing new treatment strategies and identifying new prognostic and predictive markers due to the extensive genetic heterogeneity of BC. Very few studies have investigated the impact of mRNA expression of these genes on the survival of [...] Read more.
Breast cancer (BC) poses a challenge in establishing new treatment strategies and identifying new prognostic and predictive markers due to the extensive genetic heterogeneity of BC. Very few studies have investigated the impact of mRNA expression of these genes on the survival of BC patients. Methods: We examined the impact of the mRNA expression of breast cancer gene type 1 (BRCA1), breast cancer gene type 2 (BRCA2), and partner and localizer of BRCA2 (PALB2) on the metastasis-free survival (MFS) of patients with early BC using microarray gene expression analysis. Results: The study was performed in a cohort of 461 patients with a median age of 62 years at initial diagnosis. The median follow-up time was 147 months. We could show that the lower expression of BRCA1 and BRCA2 is significantly associated with longer MFS (p < 0.050). On the contrary, the lower expression of PALB2 was correlated with a shorter MFS (p = 0.049). Subgroup survival analysis identified the prognostic influence of mRNA expression for BRCA1 among patients with luminal-B-like BC and for BRCA2 and PALB2 in the subset of patients with luminal-A-like BC (p < 0.050). Conclusions: According to our observations, BRCA1, BRCA2, and PALB2 expression might become valuable biomarkers of disease progression. Full article
(This article belongs to the Special Issue New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments)
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18 pages, 6498 KiB  
Article
Temporal Association Rule Mining: Race-Based Patterns of Treatment-Adverse Events in Breast Cancer Patients Using SEER–Medicare Dataset
by Nabil Adam and Robert Wieder
Biomedicines 2024, 12(6), 1213; https://doi.org/10.3390/biomedicines12061213 - 29 May 2024
Viewed by 761
Abstract
PURPOSE: Disparities in the screening, treatment, and survival of African American (AA) patients with breast cancer extend to adverse events experienced with systemic therapy. However, data are limited and difficult to obtain. We addressed this challenge by applying temporal association rule (TAR) mining [...] Read more.
PURPOSE: Disparities in the screening, treatment, and survival of African American (AA) patients with breast cancer extend to adverse events experienced with systemic therapy. However, data are limited and difficult to obtain. We addressed this challenge by applying temporal association rule (TAR) mining using the SEER–Medicare dataset for differences in the association of specific adverse events (AEs) and treatments (TRs) for breast cancer between AA and White women. We considered two categories of cancer care providers and settings: practitioners providing care in the outpatient units of hospitals and institutions and private practitioners providing care in their offices. PATIENTS AN METHODS: We considered women enrolled in the Medicare fee-for-service option at age 65 who qualified by age and not disability, who were diagnosed with breast cancer with attributed patient factors of age and race, marital status, comorbidities, prior malignancies, prior therapy, disease factors of stage, grade, and ER/PR and Her2 status and laterality. We included 141 HCPCS drug J codes for chemotherapy, biotherapy, and hormone therapy drugs, which we consolidated into 46 mechanistic categories and generated AE data. We consolidated AEs from ICD9 codes into 18 categories associated with breast cancer therapy. We applied TAR mining to determine associations between the 46 TR and 18 AE categories in the context of the patient categories outlined. We applied the spark.mllib implementation of the FPGrowth algorithm, a parallel version called PFP. We considered differences of at least one unit of lift as significant between groups. The model’s results demonstrated a high overlap between the model’s identified TR-AEs associated set and the actual set. RESULTS: Our results demonstrate that specific TR/AE associations are highly dependent on race, stage, and venue of care administration. CONCLUSIONS: Our data demonstrate the usefulness of this approach in identifying differences in the associations between TRs and AEs in different populations and serve as a reference for predicting the likelihood of AEs in different patient populations treated for breast cancer. Our novel approach using unsupervised learning enables the discovery of association rules while paying special attention to temporal information, resulting in greater predictive and descriptive power as a patient’s health and life status change over time. Full article
(This article belongs to the Special Issue New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments)
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14 pages, 1875 KiB  
Article
Retrospective Evaluation of Bone Turnover Markers in Serum for the Prediction of Metastases Development in Breast Cancer Patients: A Cohort Study
by Mariz Kasoha, Sebastian Findeklee, Meletios P. Nigdelis, Gilda Schmidt, Erich-Franz Solomayer and Bashar Haj Hamoud
Biomedicines 2024, 12(6), 1201; https://doi.org/10.3390/biomedicines12061201 - 29 May 2024
Viewed by 770
Abstract
Background: Serum bone turnover markers might play a role in the prediction of the development of bone metastases in breast cancer (BC) patients. We conducted a retrospective cohort study to address the association of serum bone turnover markers with oncologic outcomes. Methods: We [...] Read more.
Background: Serum bone turnover markers might play a role in the prediction of the development of bone metastases in breast cancer (BC) patients. We conducted a retrospective cohort study to address the association of serum bone turnover markers with oncologic outcomes. Methods: We included 80 women with BC, who were operated on at the Department of Gynecology, Obstetrics and Reproductive Medicine, Homburg/Saar, Germany. Serum samples were obtained prior to surgery and were used for estimation of the concentration of tumor and bone turnover markers using enzyme-linked immunosorbent assay (ELISA) and radioimmunoassay (RIA). Results: At baseline, pyridinoline cross-linked carboxy-terminal telopeptide of type-1 collagen (ICTP) concentrations were higher in nodal positive vs. negative tumors (Mann–Whitney test p = 0.04). After a median follow-up of 79.4 months, 17 patients developed metastases, with 9 demonstrating, among other organs, osseous metastases. ICTP demonstrated the best area under the curve in the predection of osseous metastases in our cohort (AUC = 0.740, DeLong Test p = 0.005). Univariable Cox proportional hazard models failed to demonstrate significant associations between serum bone turnover markers and oncologic outcomes (progression-free survival, overall survival). Conclusions: Serum bone turnover markers (e.g., ICTP) were able to predict the development of osseous metastases but were not associated with oncologic outcomes. Further investigation and validation are required for the use of such markers in clinical practice. Full article
(This article belongs to the Special Issue New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments)
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11 pages, 816 KiB  
Article
Prognostic Value of Tumor Budding for Early Breast Cancer
by Diogo J. Silva, Gonçalo Miranda, Teresina Amaro, Matilde Salgado and Alexandra Mesquita
Biomedicines 2023, 11(11), 2906; https://doi.org/10.3390/biomedicines11112906 - 27 Oct 2023
Cited by 3 | Viewed by 1658
Abstract
Background: Tumor budding (TB) is a dynamic process associated with the epithelial–mesenchymal transition and a well-established prognostic biomarker for colorectal cancer. As part of the tumor microenvironment, tumor buds demonstrate increased cell motility and invasiveness. Current evidence demonstrates that high levels of TB [...] Read more.
Background: Tumor budding (TB) is a dynamic process associated with the epithelial–mesenchymal transition and a well-established prognostic biomarker for colorectal cancer. As part of the tumor microenvironment, tumor buds demonstrate increased cell motility and invasiveness. Current evidence demonstrates that high levels of TB correlate with disease progression and worst outcomes across different solid tumors. Our work aims to demonstrate the clinical applicability of TB analysis and its utility as a prognostic factor for patients with early breast cancer (EBC). Methods: Retrospective, single-center, observational study, enrolling patients with EBC diagnosed in a Portuguese hospital between 2014 and 2015. TB classification was performed according to the International Tumor Budding Conference 2016 guidelines. Results: A statistically significant relation was found between higher TB score and aggressive clinicopathological features (angiolymphatic/perineural invasion-p < 0.001; tumor size-p = 0.012; nuclear grading-p < 0.001; and Ki-67 index-p = 0.011), higher number of relapses (p < 0.001), and short disease-free survival (DFS) (p < 0.001). Conclusion: We demonstrate that high TB correlates with shorter DFS and aggressive clinicopathological features used in daily practice to decide on the benefit of chemotherapy for EBC. TB represents a needed prognostic biomarker for EBC, comprising a new factor to be considered in the adjuvant decision-making process by identifying patients at a high risk of relapse and with higher benefit on treatment intensification. Clinical trials incorporating TB are needed to validate its prognostic impact. Full article
(This article belongs to the Special Issue New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments)
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Review

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18 pages, 3176 KiB  
Review
CAF-Associated Genes in Breast Cancer for Novel Therapeutic Strategies
by Kanako Naito, Takafumi Sangai and Keishi Yamashita
Biomedicines 2024, 12(9), 1964; https://doi.org/10.3390/biomedicines12091964 - 29 Aug 2024
Viewed by 751
Abstract
Breast cancer (BC) is the most common cancer in women, and therapeutic strategies for it are based on the molecular subtypes of luminal BC, HER2 BC, and triple-negative BC (TNBC) because each subtype harbors different unique genetic aberrations. Recently, features of the tumor [...] Read more.
Breast cancer (BC) is the most common cancer in women, and therapeutic strategies for it are based on the molecular subtypes of luminal BC, HER2 BC, and triple-negative BC (TNBC) because each subtype harbors different unique genetic aberrations. Recently, features of the tumor microenvironment (TME), especially cancer-associated fibroblasts (CAFs), have been demonstrated to play a critical role in BC progression, and we would like to understand the molecular features of BC CAFs for novel therapeutic strategies. In a recent study, 115 CAF-associated genes (CAFGs) were identified in a public database of microdissection and microarray data (GSE35602) from 13 colorectal cancer (CRC) tumors. Using a public database (GSE10797) of 28 BC tumors, a similar analysis was performed. In BC, 59 genes from the 115 CAFGs identified in CRC (CRC CAFGs) were also closely associated with a CAFs marker, SPARC (R = 0.6 or beyond), and POSTN was of particular interest as one of the BC CAFGs with the highest expression levels and a close association with SPARC expression (R = 0.94) in the cancer stroma of BC tumors. In BC stroma, POSTN was followed in expression levels by DKK3, MMP2, PDPN, and ACTA2. Unexpectedly, FAP and VIM were not as highly associated with SPARC expression in the cancer stroma of BC tumors and exhibited low expression. These findings suggested that ACTA2 might be the most relevant conventional CAFs marker in BC, and ACTA2 was actually correlated in expression with many CRC CAFGs, such as SPARC. Surprisingly, the SE ratio values of the BC CAFGs were much lower (average SE = 3.8) than those of the CRC CAFGs (SE = 10 or beyond). We summarized the current understanding of BC CAFs from the literature. Finally, in triple-negative BC (TNBC) (n = 5), SPARC expression uniquely showed a close association with COL11A1 and TAGLN expression, representing a myofibroblast (myCAFs) marker in the cancer stroma of the BC tumors, suggesting that myCAFs may be molecularly characterized by TNBC in contrast to other BC phenotypes. In summary, CAFs could have unique molecular characteristics in BC, and such TME uniqueness could be therapeutically targeted in BC. Full article
(This article belongs to the Special Issue New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments)
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Other

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11 pages, 4298 KiB  
Case Report
Takotsubo Syndrome during Pertuzumab and Trastuzumab Therapy for HER2-Positive Metastatic Breast Cancer
by Azzurra Irelli, Laura Ceriello, Leonardo Valerio Patruno, Alessandra Tessitore, Edoardo Alesse, Katia Cannita and Donatello Fabiani
Biomedicines 2024, 12(1), 179; https://doi.org/10.3390/biomedicines12010179 - 14 Jan 2024
Viewed by 1457
Abstract
Pertuzumab and trastuzumab have been shown to improve the outcomes of patients with metastatic breast cancer, with a rate of left ventricular dysfunction of approximately 6%. We report the case of a postmenopausal woman who presented with Takotsubo syndrome during maintenance therapy with [...] Read more.
Pertuzumab and trastuzumab have been shown to improve the outcomes of patients with metastatic breast cancer, with a rate of left ventricular dysfunction of approximately 6%. We report the case of a postmenopausal woman who presented with Takotsubo syndrome during maintenance therapy with pertuzumab and trastuzumab, in association with fulvestrant (an anti-estrogen) and denosumab. After normalization of cardiac function, therapy with pertuzumab and trastuzumab was resumed in the absence of new cardiac toxicity. We report the first clinical case of Takotsubo syndrome during double anti-HER2 blockade in association with an antiestrogen. Furthermore, we show how anti-HER2 therapy can be safely resumed after the detection of Takotsubo syndrome. Full article
(This article belongs to the Special Issue New Insights into Breast Cancer Management: From Tumorigenesis to Personalized Treatments)
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