Introduction of a New Staging System of Breast Cancer for Radiologists: An Emphasis on the Prognostic Stage

US-based radiomics analysis of different machine learning models for differentiating benign and malignant BI-RADS 4A breast lesions

RATIONALE AND OBJECTIVES

To investigate and authenticate the effectiveness of various radiomics models in distinguishing between benign and malignant BI-RADS 4A lesions.

METHODS

A total of 936 patients with pathologically confirmed 4A lesions were included in the study (training cohort: n = 655; test cohort: n = 281). Radiomic features were derived from greyscale US images. Following dimensionality reduction and feature selection, radiomics models were developed using logistic regression (LR), support vector machine (SVM), random forest (RF), eXtreme gradient boosting (XGBoost) and multilayer perceptron (MLP) algorithms. Univariate and multivariable logistic regression analyses were employed to investigate clinical-radiological characteristics and determine variables for creating a clinical model. Five combined models integrating radiomic and clinical parameters were constructed by using each algorithm, and comparison with radiologists' performance was performed. SHapley Additive exPlanations (SHAP) approach was used to elucidate the radiomic model by ranking the significance of features based on their contribution to the evaluation.

RESULTS

A total of 1561 radiomic features were extracted. Thirty-six features were deemed significant by dimensionality reduction and selection. The radiomic models showed good performance with AUCs of 0.829-0.945 in training cohort; and 0.805-0.857 in test cohort. The combined model developed by using LR showed the best performance (AUC, training cohort: 0.909; test cohort: 0.905), which is superior to radiologists' performance. Decision curve analysis (DCA) of this combined model indicated better clinical efficacy than clinical and radiomic models.

CONCLUSIONS

The combined model integrating radiomic and clinical features demonstrated excellent performance in differentiating between benign and malignant 4A lesions. It may offer a non-invasive and efficient approach to aid in clinical decision-making.

Performance of MRI for standardized lymph nodes assessment in breast cancer: are we ready for Node-RADS?

OBJECTIVES

The Node-RADS score was recently introduced to offer a standardized assessment of lymph node invasion (LNI). We tested its diagnostic performance in accurately predicting LNI in breast cancer (BC) patients with magnetic resonance imaging. The study also explores the consistency of the score across three readers.

MATERIALS AND METHODS

A retrospective study was conducted on BC patients who underwent preoperative breast contrast-enhanced magnetic resonance imaging and lymph node dissection between January 2020 and January 2023. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value were calculated for different Node-RADS cut-off values. Pathologic results were considered the gold standard. The overall diagnostic performance was evaluated using receiver operating characteristic curves and the area under the curve (AUC). A logistic regression analysis was performed. Cohen's Kappa analysis was used for inter-reader agreement.

RESULTS

The final population includes 192 patients and a total of 1134 lymph nodes analyzed (372 metastatic and 762 benign). Increasing the Node-RADS cut-off values, specificity and PPV rose from 71.4% to 100% and 76.7% to 100%, respectively, for Reader 1, 69.4% to 100% and 74.6% to 100% for Reader 2, and from 64.3% to 100% and 72% to 100% for Reader 3. Node-RADS > 2 could be considered the best cut-off value due to its balanced performance. Node-RADS exhibited a similar AUC for the three readers (0.97, 0.93, and 0.93). An excellent inter-reader agreement was found (Kappa values between 0.71 and 0.83).

CONCLUSIONS

The Node-RADS score demonstrated moderate-to-high overall accuracy in identifying LNI in patients with BC, suggesting that the scoring system can aid in the identification of suspicious lymph nodes and facilitate appropriate treatment decisions.

CLINICAL RELEVANCE STATEMENT

Node-RADS > 2 can be considered the best cut-off for discriminating malignant nodes, suggesting that the scoring system can effectively help identify suspicious lymph nodes by staging the disease and providing a global standardized language for clear communication.

KEY POINTS

Axillary lymphadenopathies in breast cancer are crucial for determining the disease stage. Node-RADS was introduced to provide a standardized evaluation of breast cancer lymph nodes. RADS > 2 can be considered the best cut-off for discriminating malignant nodes.

The effectiveness and safety of palbociclib and ribociclib in stage IV HR+/HER-2 negative breast cancer: a nationwide real world comparative retrospective cohort study

Introduction

Palbociclib and ribociclib are indicated in the first-line treatment of hormonal receptor-positive HER-2 negative (HR+/HER2- negative) advanced breast cancer. Although randomized-controlled trials (RCTs) proved their clinical efficacy, there are no observational studies yet to validate the clinical findings in the real-world. Therefore, this study aimed to evaluate and compare the clinical effectiveness and safety profiles of palbociclib and ribociclib in Qatar.

Materials and methods

A retrospective observational study was conducted on HR+/HER-2-negative stage-IV breast cancer patients receiving palbociclib or ribociclib in the state of Qatar. Clinical data were collected from the National Center for Cancer Care and Research (NCCCR) in Qatar using Cerner®. Primary outcomes were progression-free-survival (PFS) and overall-survival (OS) generated by Kaplan-Meier curves. Moreover, safety profiles of both two treatments were evaluated.

Results

The data from 108 patients were included in the final analysis. There was no statistically significant difference in PFS between the palbociclib and ribociclib groups; PFS was 17.85 versus 13.55 months, respectively(p> 0.05). Similarly, there was no statistically significant difference in OS between the two medications, 29.82 versus 31.72 months, respectively(p>0.05). Adverse events were similar between the two groups. Neutropenia was the most common side effect in the study population accounting for 59.3% of the patients.

Conclusions

Therefore, both treatments have similar efficacy and safety profiles. Further research on a larger-scale population and longer follow-up period is recommeneded.

Early Echocardiography and ECG Changes Following Radiotherapy in Patients with Stage II-III HER2-Positive Breast Cancer Treated with Anthracycline-Based Chemotherapy with or without Trastuzumab-Based Therapy

BACKGROUND Cardiotoxicity from radiotherapy and anti-cancer therapies have been reported in patients with breast cancer. This study aimed to investigate the early echocardiography and ECG changes following radiotherapy in 68 patients ages 30-78 years with stages II-III HER2-positive breast cancer treated with anthracycline-based chemotherapy with or without trastuzumab-based therapy from 2015 to 2021. MATERIAL AND METHODS We analyzed data of 68 breast cancer patients aged 30-78 years, predominantly in AJCC stages II-III (61) and HER2-positive (58), treated and monitored from 2015 to 2021. Cardiac function was assessed using echo- and electrocardiography. We employed univariate logistic models to gauge associations between pre-existing cardiac conditions, treatment modalities, and changes in cardiac function. RESULTS A decrease in the left ventricle ejection fraction (EF) by >5% was associated with heart doses >49.3 Gy and with maximum and average doses to the left anterior descending artery (LAD) exceeding 46.9 Gy and 32.7 Gy, respectively. An EF drop of ≥10% was correlated with anti-HER2 therapy, pre-existing ECG changes, and the onset of conditions in the left ventricle, major vessels, and valves. Conditions were exacerbated in patients with prior echocardiographic abnormalities, while some emerged concurrent with the EF decline. CONCLUSIONS This research emphasizes the importance of personalized heart monitoring and care for breast cancer patients undergoing multimodal therapies. Significant and potentially irreversible EF declines can result from radiation and anti-HER2 treatments.

Invasive Breast Cancer: miR-24-2 Targets Genes Associated with Survival and Sensitizes MDA-MB-231 Cells to Berberine

MicroRNA aberrations including that of miR-24-2 have been reported in various cancers. However, the target genes for miR-24-2 are yet to be identified and validated in invasive breast cancer and the triple-negative breast cancer (TNBC). Using in silico approaches and gene expression analyses, we identified and validated the target genes of miR-24-2 in invasive breast cancer, majority of which were TNBC. We studied the translational potential of these target genes using berberine in a TNBC cell line. Differentially expressed genes targeted by miR-24-2 were identified and analyzed for their survival effects using the The Cancer Genome Atlas-Breast Invasive Carcinoma (-BRCA) samples. Furthermore, we carried out protein-protein interaction, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene expression, and Kaplan-Meier survival analyses using common targets of miR-24-2 in invasive breast cancer/TNBC. We identified 11 biomarker candidate genes as crucial targets of miR-24-2. The survival of breast cancer patients was significantly associated with the low expressions of nine genes, including RACGAP1, KIAA1199, TIMM17A, LYRM7, IL1R1, SLC1A3, DTX4, L1CAM, and SAP30-like (SAP30L), and high expressions of two genes, SOD2 and HLA-DQB2. These in silico findings were validated by overexpressing miR-24-2 and assessing the expression pattern of these target genes in the TNBC MDA-MB-231 cells. miR-24-2 overexpression inhibited (by 20%; p < 0.001) cell proliferation and sensitized the anticancer effect of berberine. In all, this study reports on the novel target genes of miR-24-2 in invasive breast cancer/TNBC, and that miR-24-2 sensitizes MDA-MB-231 cells to berberine. These data lend evidence for the translational potentials of miR-24-2 for invasive breast cancer diagnostic and therapeutic innovation.

Comparing Prognostic Factors of Cancers Identified by Artificial Intelligence (AI) and Human Readers in Breast Cancer Screening

Invasiveness status, histological grade, lymph node stage, and tumour size are important prognostic factors for breast cancer survival. This evaluation aims to compare these features for cancers detected by AI and human readers using digital mammography. Women diagnosed with breast cancer between 2009 and 2019 from three UK double-reading sites were included in this retrospective cohort evaluation. Differences in prognostic features of cancers detected by AI and the first human reader (R1) were assessed using chi-square tests, with significance at p < 0.05. From 1718 screen-detected cancers (SDCs) and 293 interval cancers (ICs), AI flagged 85.9% and 31.7%, respectively. R1 detected 90.8% of SDCs and 7.2% of ICs. Of the screen-detected cancers detected by the AI, 82.5% had an invasive component, compared to 81.1% for R1 (p-0.374). For the ICs, this was 91.5% and 93.8% for AI and R1, respectively (p = 0.829). For the invasive tumours, no differences were found for histological grade, tumour size, or lymph node stage. The AI detected more ICs. In summary, no differences in prognostic factors were found comparing SDC and ICs identified by AI or human readers. These findings support a potential role for AI in the double-reading workflow.

Calcium Homeostasis in the Development of Resistant Breast Tumors

Cancer is one of the main health problems worldwide. Only in 2020, this disease caused more than 19 million new cases and almost 10 million deaths, with breast cancer being the most diagnosed worldwide. Today, despite recent advances in breast cancer treatment, a significant percentage of patients will either not respond to therapy or will eventually experience lethal progressive disease. Recent studies highlighted the involvement of calcium in the proliferation or evasion of apoptosis in breast carcinoma cells. In this review, we provide an overview of intracellular calcium signaling and breast cancer biology. We also discuss the existing knowledge on how altered calcium homeostasis is implicated in breast cancer development, highlighting the potential utility of Ca²⁺ as a predictive and prognostic biomarker, as well as its potential for the development of new pharmacological treatments to treat the disease.

The Variety of 3D Breast Cancer Models for the Study of Tumor Physiology and Drug Screening

Breast cancer is the most common cancer in women and responsible for multiple deaths worldwide. 3D cancer models enable a better representation of tumor physiology than the conventional 2D cultures. This review summarizes the important components of physiologically relevant 3D models and describes the spectrum of 3D breast cancer models, e.g., spheroids, organoids, breast cancer on a chip and bioprinted tissues. The generation of spheroids is relatively standardized and easy to perform. Microfluidic systems allow control over the environment and the inclusion of sensors and can be combined with spheroids or bioprinted models. The strength of bioprinting relies on the spatial control of the cells and the modulation of the extracellular matrix. Except for the predominant use of breast cancer cell lines, the models differ in stromal cell composition, matrices and fluid flow. Organoids are most appropriate for personalized treatment, but all technologies can mimic most aspects of breast cancer physiology. Fetal bovine serum as a culture supplement and Matrigel as a scaffold limit the reproducibility and standardization of the listed 3D models. The integration of adipocytes is needed because they possess an important role in breast cancer.

Functionalization of curcumin nanomedicines: a recent promising adaptation to maximize pharmacokinetic profile, specific cell internalization and anticancer efficacy against breast cancer

Owing to its diverse heterogeneity, aggressive nature, enormous metastatic potential, and high remission rate, the breast cancer (BC) is among the most prevalent types of cancer associated with high mortality. Curcumin (Cur) is a potent phytoconstituent that has gained remarkable recognition due to exceptional biomedical viability against a wide range of ailments including the BC. Despite exhibiting a strong anticancer potential, the clinical translation of Cur is restricted due to intrinsic physicochemical properties such as low aqueous solubility, chemical instability, low bioavailability, and short plasma half-life. To overcome these shortcomings, nanotechnology-aided developments have been extensively deployed. The implication of nanotechnology has pointedly improved the physicochemical properties, pharmacokinetic profile, cell internalization, and anticancer efficacy of Cur; however, majority of Cur-nanomedicines are still facing grandeur challenges. The advent of various functionalization strategies such as PEGylation, surface decoration with different moieties, stimuli-responsiveness (i.e., pH, light, temperature, heat, etc.), tethering of specific targeting ligand(s) based on the biochemical targets (e.g., folic acid receptors, transferrin receptors, CD44, etc.), and multifunctionalization (multiple functionalities) has revolutionized the fate of Cur-nanomedicines. This study ponders the biomedical significance of various Cur-nanomedicines and adaptable functionalizations for amplifying the physicochemical properties, cytotoxicity via induction of apoptosis, cell internalization, bioavailability, passive and active targeting to the tumor microenvironment (TME), and anticancer efficacy of the Cur while reversing the multidrug resistance (MDR) and reoccurrence in BC. Nevertheless, the therapeutic outcomes of Cur-nanomedicines against the BC have been remarkably improved after adaptation of various functionalizations; however, this evolving strategy still demands extensive research for scalable clinical translation.

Coumarin derivative as a potent drug candidate against triple negative breast cancer targeting the frizzled receptor of wingless-related integration site signaling pathway

Triple negative breast cancer constitutes to about 21.8 percent of the total breast cancer related cases. Its ability to affect young ladies and in pre-menstrual stage makes this a disease of concern worldwide. The current treatment regimens involve chemotherapy which are used for treatment of other cancer types. In this regard, there is a need for specific and targeted drug candidate for its effective treatment. In the current study, assessment of coumarin derivative 2-(2-(6- Methyl-2-Oxo-2H-chromen-4-yl) acetamido)-3-phenylpropanoic acid is carried out both In-silico and In-vitro methods. Frizzled transmembrane proteins of Wingless-related integration site signaling pathway was targeted in which Frizzled-7 proved to a prospective target and showed a binding energy of -6.78 kcal/mol. The complex was subjected to molecular dynamics simulation for 200 ns and showed stable interaction with cysteine rich domain of the receptor. Cell proliferation, viability and apoptosis assay were performed on MDA-MB-231 and MDA-MB-468 cell lines with an IC₅₀ value of 81.23 and 84.68 µM, respectively. The results provide a drug candidate which is derivative of a natural compound with targeted TNBC inhibitory effect. Communicated by Ramaswamy H. Sarma.

Discriminatory Ability and Clinical Utility of the AJCC7 and AJCC8 Staging Systems for Breast Cancer in a Middle-Income Setting

(1) Background: Differences in access to biomarker testing and cancer treatment in resource-limited settings may affect the clinical utility of the AJCC8 staging system compared to the anatomical AJCC7 system. (2) Methods: A total of 4151 Malaysian women who were newly diagnosed with breast cancer from 2010 to 2020 were followed-up until December 2021. All patients were staged using the AJCC7 and AJCC8 systems. Overall survival (OS) and relative survival (RS) were determined. Concordance-index was used to compare the discriminatory ability between the two systems. (3) Results: Migration from the AJCC7 to AJCC8 staging system resulted in the downstaging of 1494 (36.0%) patients and the upstaging of 289 (7.0%) patients. Approximately 5% of patients could not be staged using the AJCC8 classification. Five-year OS varied between 97% (Stage IA) and 66% (Stage IIIC) for AJCC7, and 96% (Stage IA) and 60% (Stage IIIC) for AJCC8. Concordance-indexes for predicting OS using the AJCC7 and AJCC8 models were 0.720 (0.694-0.747) and 0.745 (0.716-0.774), and for predicting RS they were 0.692 (0.658-0.728) and 0.710 (0.674-0.748), respectively. (4) Conclusions: Given the comparable discriminatory ability between the two staging systems in predicting the stage-specific survival of women with breast cancer in the current study, the continued use of the AJCC7 staging system in resource-limited settings seems pragmatic and justifiable.

Comparison of tumor size, histopathological grade, and molecular subtype of breast cancer at a single center study

BACKGROUND

Breast cancer (BC) is the second most frequent cancer-related death among women worldwide. Factors influencing BC patients' survival include histopathological grade, histopathological type, stage, hormonal receptors, and number of mitotic images.

OBJECTIVE

To compare the tumor size, histopathological grade, and molecular type of BC patients.

METHODS

This was an observational analytic retrospective study. The population was BC patients at Dr. Wahidin Sudirohusodo Hospital from 2017 to 2021. The Kruskal-Wallis test was used to compare statistically between tumor size, histopathological grade, and molecular subtype. Significance was set at p < 0.05.

RESULTS

The study included 784 patients. Most were aged 50-59 years (34.8%), with tumor size 4c (37.0%) and moderate grade (66.1%), and the most common molecular subtype was luminal A (34.2%). Bivariate analysis using the Kruskal-Wallis test found no significant difference in molecular subtypes based on tumor size (p = 0.079), but significant differences existed in molecular subtype by histopathological grade (p = 0.005) and tumor size by histopathological grade (p < 0.001).

CONCLUSIONS

Significant differences existed between histopathological grade by tumor size and molecular subtype. Early diagnosis and prompt treatment of BC patients are important to prevent morbidity and mortality.

Numerical Estimation of SAR and Temperature Distributions inside Differently Shaped Female Breast Tumors during Radio-Frequency Ablation

Radio-frequency (RF) ablation is a reliable technique for the treatment of deep-seated malignant tumors, including breast carcinoma, using high ablative temperatures. The paper aims at a comparative analysis of the specific absorption rate and temperature distribution during RF ablation with regard to different female breast tumors. In the study, four tumor models equivalent to an irregular tumor were considered, i.e., an equivalent sphere and ellipsoid with the same surfaces and volumes as the irregular tumor and an equivalent sphere and ellipsoid inscribed in the irregular tumor. An RF applicator with a specific voltage, operating at 100 kHz inserted into the anatomically correct female breast, was applied as a source of electromagnetically induced heat. A conjugated Laplace equation with the modified Pennes equation was used to obtain the appropriate temperature gradient in the treated area. The levels of power dissipation in terms of the specific absorption rate (SAR) inside the naturalistically shaped tumor, together with the temperature profiles of the four simplified tumor models equivalent to the irregular one, were determined. It was suggested that the equivalent tumor models might successfully replace a real, irregularly shaped tumor, and the presented numeric methodology may play an important role in the complex therapeutic RF ablation process of irregularly shaped female breast tumors.

Time to surgery and survival in breast cancer

Background

This study aimed to investigate the effect of the time from diagnosis to breast cancer surgery on breast cancer patients’ prognosis.

Methods

Of the 1900 patients diagnosed with invasive (stage 1–3) breast cancer who underwent surgery in KUH between 2012 and 2019, 279 patients were enrolled in this study. All patients, including those who received neoadjuvant chemotherapy, were classified as Model 1 subjects, and those who received immediate surgical treatment were classified as Model 2 subjects. We conducted a Cox regression analysis to identify prognostic factors of breast cancer associated with the time from diagnosis to surgery.

Results

The univariate results indicated a sharp drop in both groups’ survival rates when the time to surgery was delayed for more than 8 weeks (Model 1 p = 0.000; Model 2 p = 0.001). In the multivariate analysis, the hazard ratio (HR) of Model 1increased (HR = 6.84, 95% CI 1.06–44.25) in response to a delay in surgery of more than 8 weeks. Smoking and the American Joint Committee on Cancer (AJCC) staging system had a negative effect on breast cancer prognosis, while hormone therapy had a positive effect.

Conclusion

For all patients, a delay in breast cancer surgery of more than 8 weeks was inversely associated with survival.

The Novel Diagnostic Techniques and Biomarkers of Canine Mammary Tumors

Canine mammary tumors (CMTs) are considered a serious clinical problem in older bitches. Due to the high malignancy rate and poor prognosis, an early diagnosis is essential. This article is a summary of novel diagnostic techniques as well as the main biomarkers of CMTs. So far, CMTs are detected only when changes in mammary glands are clinically visible and surgical removal of the mass is the only recommended treatment. Proper diagnostics of CMT is especially important as they represent a very diverse group of tumors and therefore different treatment approaches may be required. Recently, new diagnostic options appeared, like a new cytological grading system of CMTs or B-mode ultrasound, the Doppler technique, contrast-enhanced ultrasound, and real-time elastography, which may be useful in pre-surgical evaluation. However, in order to detect malignancies before macroscopic changes are visible, evaluation of serum and tissue biomarkers should be considered. Among them, we distinguish markers of the cell cycle, proliferation, apoptosis, metastatic potential and prognosis, hormone receptors, inflammatory and more recent: metabolomic, gene expression, miRNA, and transcriptome sequencing markers. The use of a couple of the above-mentioned markers together seems to be the most useful for the early diagnosis of neoplastic diseases as well as to evaluate response to treatment, presence of tumor progression, or further prognosis. Molecular aspects of tumors seem to be crucial for proper understanding of tumorigenesis and the application of individual treatment options.

Numerical study of magnetic hyperthermia ablation of breast tumor on an anatomically realistic breast phantom

Magnetic fluid hyperthermia (MFH) is a novel reliable technique with excellent potential for thermal therapies and treating breast tumours. This method involves injecting a magnetic nanofluid into the tumour and applying an external AC magnetic field to induce heat in the magnetic nanoparticles (MNPs) and raise the tumour temperature to ablation temperature ranges. Because of the complexity of considering and coupling all different physics involves in this phenomenon and also due to the intricacy of a thorough FEM numerical study, few FEM-based studies address the entire MFH process as similar to reality as possible. The current study investigates a FEM-based three-dimensional numerical simulation of MFH of breast tumours as a multi-physics problem. An anatomically realistic breast phantom (ARBP) is considered, some magnetic nanofluid is injected inside the tumour, and the diffusion phenomenon is simulated. Then, the amount of heat generated in the MNP-saturated tumour area due to an external AC magnetic field is simulated. In the end, the fraction of tumour tissue necrotized by this temperature rise is evaluated. The study's results demonstrate that by injecting nanofluid and utilizing seven circular copper windings with each coil carrying 400 A current with a frequency of 400 kHz for generating the external AC magnetic field, the temperature in tumour tissue can be raised to a maximum of about 51.4°C, which leads to necrosis of entire tumour tissue after 30 minutes of electromagnetic field (EMF) exposure. This numerical platform can depict all four various physics involved in the MFH of breast tumours by numerically solving all different equation sets coupled together with high precision. Thus, the proposed model can be utilized by clinicians as a reliable tool for predicting and identifying the approximate amount of temperature rise and the necrotic fraction of breast tumour, which can be very useful to opt for the best MFH therapeutic procedure and conditions based on various patients. In future works, this numerical platform's results should be compared with experimental in-vivo results to improve and modify this platform in order to be ready for clinical applications.

Advances in lipid-based nanocarriers for breast cancer metastasis treatment

Breast cancer (BC) is the most common cancer affecting women worldwide, with over 2 million women diagnosed every year, and close to 8 million women currently alive following a diagnosis of BC in the last 5-years. The side effects such as chemodrug toxicity to healthy tissues and drug resistance severely affect the quality of life of BC patients. To overcome these limitations, many efforts have been made to develop nanomaterial-based drug delivery systems. Among these nanocarriers, lipid-based delivery platforms represented one of the most successful candidates for cancer therapy, improving the safety profile and therapeutic efficacy of encapsulated drugs. In this review we will mainly discuss and summarize the recent advances in such delivery systems for BC metastasis treatment, with a particular focus on targeting the common metastatic sites in bone, brain and lung. We will also provide our perspectives on lipid-based nanocarrier development for future clinical translation.

Expression of NUCB2/NESF-1 in Breast Cancer Cells

Recently, the expression of NUCB2/NESF-1 has been linked to tumor development. We report NUCB2/NESF-1 expression and its relation to clinicopathological parameters in breast cancer cells. Immunohistochemical reactions were conducted on 446 cases of invasive ductal carcinoma (IDC) and 36 cases of mastopathy. The expression of NUCB2/NESF-1 was also examined at the mRNA and protein levels in breast cancer cell lines. A statistically significant higher level of NUCB2/NESF-1 in IDC cells was noted compared to that in mastopathy samples. The level of NUCB2 expression in the cytoplasm of IDC cells decreased with the increasing degree of tumor malignancy (G). Higher NUCB2 expression was found in tumors with estrogen receptor (ER)-positive and progesterone receptor (PR)-positive phenotypes compared to that in estrogen-receptor-negative and progesterone-receptor-negative cases. Moreover, a higher expression was shown in ER(+) and PR(+) MCF-7 and T47D cell lines compared to that in triple-negative MDA-MB-468 and normal human breast epithelial cells. The analysis of the five-year survival rate indicated that a positive NUCB2/NESF-1 expression in tumor cells was also associated with longer patient survival. The study results suggest that NUCB2/NESF1 may play an important role in malignant transformation and may be a positive prognostic factor in IDC.

Breast cancer: presentation, investigation and management

Breast cancer is the most common global malignancy and the leading cause of cancer deaths. Despite this, undergraduate and postgraduate exposure to breast cancer is limited, impacting on the ability of clinicians to accurately recognise, assess and refer appropriate patients. This article provides a comprehensive review of the pathology, epidemiology, clinical presentation, referral pathways and management of breast cancer in the UK. It also describes how to conduct a thorough clinical breast examination.

The Clinical, Biological, Psychological and Psychiatric Impact of the Diagnosis of Breast Cancer in Women

OBJECTIVE

Psychosocial factors are correlated with the risk of breast cancer, by the lack of externalization of feelings and aggressive tendencies, or with a negative prognosis, by the presence of a high level of stress and reduced coping abilities. Impairment of psychological status should be assessed early to identify quantifiable psychooncological changes, such as depression, anxiety, and self-esteem. These indicators, measured in this study, may become psychometric markers for predicting the existence of the neoplastic process, prior to histopathological evaluations.

METHODS

58 patients diagnosed with breast cancer and in different stages of evolution and 61 breast lumps patients were evaluated for depression, anxiety and self-esteem.

RESULTS

The correlation of depression and anxiety levels according to the evolutionary stage of the disease was as follows: in stage I cases of severe depression with significant anxiety predominate, in stage II mild depression predominates with insignificant anxiety, in stage III depression predominates moderate with significant anxiety, while in stage IV moderate depression with significant anxiety predominates.

CONCLUSIONS

The presence of significant anxiety in the uncertainty phase and the anxious-depressive clinical picture can be an alarm signal for the initiation of specific psychotherapeutic strategies, to increase the adaptive potential and resilience to the disease to ensure a therapeutic collaboration of the patient by increasing adherence and compliance. the proposed therapeutic plan. Relatively sudden anxiety in a young woman, risk factors for breast cancer, and deficient cognitive impairment require intensified clinical and paraclinical investigations to confirm early oncological diagnosis.

Role of MRI in Breast Cancer Staging: A Case-Based Review

Breast cancer is the most commonly diagnosed cancer in women in the United States and is also the second leading cause of cancer deaths in women. The five-year survival rate and overall prognosis are largely dependent on the stage at diagnosis. Our article highlights the role of magnetic resonance imaging (MRI) in breast cancer staging and updates to the American Joint Committee on Cancer (AJCC) 8th edition guidelines regarding breast cancer staging that are relevant to radiologists. It provides a case-based approach to emphasize the key findings that the radiologist should report on a breast MRI to aid the clinicians in staging and management.

Machine Learning Models That Integrate Tumor Texture and Perfusion Characteristics Using Low-Dose Breast Computed Tomography Are Promising for Predicting Histological Biomarkers and Treatment Failure in Breast Cancer Patients

Simple Summary

Tumor angiogenesis and heterogeneity are associated with poor prognosis for breast cancer. Advances in computer technology have made it possible to noninvasively quantify tumor angiogenesis and heterogeneity appearing in imaging data. We investigated whether low-dose CT could be used as a method for functional oncology imaging to assess tumor heterogeneity and angiogenesis in breast cancer and to predict noninvasively histological biomarkers and molecular subtypes of breast cancer. Low-dose breast CT has advantages in terms of radiation safety and patient convenience. Our study produced promising results for the use of machine learning with low-dose breast CT to identify histological prognostic factors including hormone receptor and human epidermal growth factor receptor 2 status, grade, and molecular subtype in patients with invasive breast cancer. Machine learning that integrates texture and perfusion features of breast cancer with low-dose CT can provide valuable information for the realization of precision medicine.

Abstract

This prospective study enrolled 147 women with invasive breast cancer who underwent low-dose breast CT (80 kVp, 25 mAs, 1.01–1.38 mSv) before treatment. From each tumor, we extracted eight perfusion parameters using the maximum slope algorithm and 36 texture parameters using the filtered histogram technique. Relationships between CT parameters and histological factors were analyzed using five machine learning algorithms. Performance was compared using the area under the receiver-operating characteristic curve (AUC) with the DeLong test. The AUCs of the machine learning models increased when using both features instead of the perfusion or texture features alone. The random forest model that integrated texture and perfusion features was the best model for prediction (AUC = 0.76). In the integrated random forest model, the AUCs for predicting human epidermal growth factor receptor 2 positivity, estrogen receptor positivity, progesterone receptor positivity, ki67 positivity, high tumor grade, and molecular subtype were 0.86, 0.76, 0.69, 0.65, 0.75, and 0.79, respectively. Entropy of pre- and postcontrast images and perfusion, time to peak, and peak enhancement intensity of hot spots are the five most important CT parameters for prediction. In conclusion, machine learning using texture and perfusion characteristics of breast cancer with low-dose CT has potential value for predicting prognostic factors and risk stratification in breast cancer patients.

Potential association of prolonged patient interval and advanced anatomic stage in breast cancer patients in the area affected by the 2011 triple disaster in Fukushima, Japan: Retrospective observational study

For five years after the 2011 triple disaster (earthquake, tsunami, and nuclear disaster) in Japan, the proportion of patients with undiagnosed symptomatic breast cancer remained elevated in the coastal area of Fukushima. These individuals experienced a prolonged interval from first symptom recognition to initial medical consultation (hereafter referred to as the patient interval). We aimed to investigate how this prolonged patient interval affected disease staging.Using patient records, we retrospectively extracted females with newly and pathologically diagnosed breast cancer who initially presented to Minamisoma Municipal General Hospital from March 2011 to March 2016. We estimated the proportion with advanced-stage disease (III, IV) according to the patient interval duration (<3 months, 3-12 months, and 12 months plus). A cut-off patient interval value was determined based on the previous evidence with regards to impacts on survival prospects. Logistic regression approaches were used to fulfill the study outcome.The proportion of patients with advanced-stage disease was 10.3% for < 3 months (7/68), 18.2% for 3-12 months (2/11), and 66.7% for more than 12 months (12/18). We found a similar trend using the multivariate logistic regression analyses.Prolongation of the patient interval was associated with advanced-stage disease among female patients with breast cancer.

Machine learning with multiparametric breast MRI for prediction of Ki-67 and histologic grade in early-stage luminal breast cancer

OBJECTIVES

To investigate whether machine learning-based prediction models using 3-T multiparametric MRI (mpMRI) can predict Ki-67 and histologic grade in stage I-II luminal cancer.

METHODS

Between 2013 and 2019, consecutive women with luminal cancers who underwent preoperative MRI with diffusion-weighted imaging (DWI) and surgery were included. For prediction models, morphology, kinetic features using computer-aided diagnosis (CAD), and apparent diffusion coefficient (ADC) at DWI were evaluated by two radiologists. Logistic regression analysis was used to identify mpMRI features for predicting Ki-67 and grade. Diagnostic performance was assessed using eight machine learning algorithms incorporating mpMRI features and compared using the DeLong method.

RESULTS

Of 300 women, 203 (67.7%) had low Ki-67 and 97 (32.3%) had high Ki-67; 242 (80.7%) had low grade and 58 (19.3%) had high grade. In multivariate analysis, independent predictors for higher Ki-67 were washout component > 13.5% (odds ratio [OR] = 4.16; p < 0.001) and intratumoral high SI on T2-weighted image (OR = 1.89; p = 0.022). Those for higher grade were washout component > 15.5% (OR = 7.22; p < 0.001), rim enhancement (OR = 2.59; p = 0.022), and ADC value < 0.945 × 10^-3 mm²/s (OR = 2.47; p = 0.015). Among eight models using these predictors, six models showed the equivalent performance for Ki-67 (area under the receiver operating characteristic curve [AUC]: 0.70) and Naive Bayes classifier showed the highest performance for grade (AUC: 0.79).

CONCLUSIONS

A prediction model incorporating mpMRI features shows good diagnostic performance for predicting Ki-67 and histologic grade in patients with luminal breast cancers.

KEY POINTS

• Among multiparametric MRI features, kinetic feature of washout component >13.5% and intratumoral high signal intensity on T2-weighted image were associated with higher Ki-67. • Washout component >15.5%, rim enhancement, and mean apparent diffusion coefficient value < 0.945 × 10^-3 mm²/s were associated with higher histologic grade. • Machine learning-based prediction models incorporating multiparametric MRI features showed good diagnostic performance for Ki-67 and histologic grade in luminal breast cancers.

Relationship between Prognostic Stage in Breast Cancer and Fluorine-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography

This retrospective study examined the relationship between the standardized uptake value max (SUVmax) of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and the prognostic stage of breast cancer. We examined 358 breast cancers in 334 patients who underwent ¹⁸F-FDG PET/CT for initial staging between January 2016 and December 2019. We extracted data including SUVmax of ¹⁸F-FDG PET and pathological biomarkers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and nuclear grade. Anatomical and prognostic stages were determined per the American Joint Committee on Cancer (eighth edition). We examined whether there were statistical differences in SUVmax between each prognostic stage. The mean SUVmax values for clinical prognostic stages were as follow: stage 0, 2.2 ± 1.4; stage IA, 2.6 ± 2.1; stage IB, 4.2 ± 3.5; stage IIA, 5.2 ± 2.8; stage IIB, 7.7 ± 6.7; and stage III + IV, 7.0 ± 4.5. The SUVmax values for pathological prognostic stages were as follows: stage 0, 2.2 ± 1.4; stage IA, 2.8 ± 2.2; stage IB, 5.4 ± 3.6; stage IIA, 6.3 ± 3.1; stage IIB, 9.2 ± 7.5, and stage III + IV, 6.2 ± 5.2. There were significant differences in mean SUVmax between clinical prognostic stage 0 and ≥II (p < 0.001) and I and ≥II (p < 0.001). There were also significant differences in mean SUVmax between pathological prognostic stage 0 and ≥II (p < 0.001) and I and ≥II (p < 0.001). In conclusion, mean SUVmax increased with all stages up to prognostic stage IIB, and there were significant differences between several stages. The SUVmax of ¹⁸F-FDG PET/CT may contribute to prognostic stage stratification, particularly in early cases of breast cancers.

Nanoparticles Targeting Receptors on Breast Cancer for Efficient Delivery of Chemotherapeutics

The journey of chemotherapeutic drugs from the site of administration to the site of action is confronted by several factors including low bioavailability, uneven distribution in major organs, limited accessibility of drug molecules to the distant tumor tissues, and lower therapeutic indexes. These unavoidable features of classical chemotherapeutics necessitate an additional high, repetitive dose of drugs to obtain maximum therapeutic responses with the result of unintended adverse side effects. An erratic tumor microenvironment, notable drawbacks of conventional chemotherapy, and multidrug-resistant mechanisms of breast cancer cells warrant precisely designed therapeutics for the treatment of cancers. In recent decades, nanoparticles have been deployed for the delivery of standard anticancer drugs to maximize the therapeutic potency while minimizing the adverse effects to increase the quality and span of life. Several organic and inorganic nanoplatforms that have been designed exploiting the distinctive features of the tumor microenvironment and tumor cells offer favorable physicochemical properties and pharmacokinetic profiles of a parent drug, with delivery of higher amounts of the drug to the pathological site and its controlled release, thereby improving the balance between its efficacy and toxicity. Advances to this front have included design and construction of targeted nanoparticles by conjugating homing devices like peptide, ligand, and Fab on the surface of nanomaterials to navigate nanoparticledrug complexes towards the target tumor cell with minimal destruction of healthy cells. Furthermore, actively targeting nanoparticles can facilitate the delivery and cellular uptake of nanoparticle-loaded drug constructs via binding with specific receptors expressed aberrantly on the surface of a tumor cell. Herein, we present an overview of the principle of targeted delivery approaches, exploiting drug-nanoparticle conjugates with multiple targeting moieties to target specific receptors of breast cancer cells and highlighting therapeutic evaluation in preclinical studies. We conclude that an understanding of the translational gap and challenges would show the possible future directions to foster the development of novel targeted nanotherapeutics.

Breast cancer, screening and diagnostic tools: All you need to know

Breast cancer is one of the most frequent malignancies among women worldwide. Methods for screening and diagnosis allow health care professionals to provide personalized treatments that improve the outcome and survival. Scientists and physicians are working side-by-side to develop evidence-based guidelines and equipment to detect cancer earlier. However, the lack of comprehensive interdisciplinary information and understanding between biomedical, medical, and technology professionals makes innovation of new screening and diagnosis tools difficult. This critical review gathers, for the first time, information concerning normal breast and cancer biology, established and emerging methods for screening and diagnosis, staging and grading, molecular and genetic biomarkers. Our purpose is to address key interdisciplinary information about these methods for physicians and scientists. Only the multidisciplinary interaction and communication between scientists, health care professionals, technical experts and patients will lead to the development of better detection tools and methods for an improved screening and early diagnosis.

Breast Tumor Malignancy Classification using Smartphone Compression-induced Sensing System and Deformation Index Ratio

Smartphone-based compression-induced sensing system uses the light diffusion pattern to characterize the early-stage breast tumor noninvasively. The system is built on a smartphone and cloud platform to capture, transfer, and interface with the user. The compressed tissue's deforming pattern creates distinctive tactile images due to the size and hardness of the tumor. From the compression-induced images, we estimate the size of the tumor using projection analysis and the tumor's malignancy using the tissue deformation index ratio. Deformation index ratio is based on the changes of a healthy region over the tumorous region. By using the projection analysis, the human patient tumor size estimation resulted in 52.3% of the average error. For a small number (seven) of the feasibility test, the tumor's malignancy was classified based on the deformation index ratio with 67.0% of sensitivity and 100% specificity.

Systems biology comprehensive analysis on breast cancer for identification of key gene modules and genes associated with TNM-based clinical stages

Breast cancer (BC), as one of the leading causes of death among women, comprises several subtypes with controversial and poor prognosis. Considering the TNM (tumor, lymph node, metastasis) based classification for staging of breast cancer, it is essential to diagnose the disease at early stages. The present study aims to take advantage of the systems biology approach on genome wide gene expression profiling datasets to identify the potential biomarkers involved at stage I, stage II, stage III, and stage IV as well as in the integrated group. Three HER2-negative breast cancer microarray datasets were retrieved from the GEO database, including normal, stage I, stage II, stage III, and stage IV samples. Additionally, one dataset was also extracted to test the developed predictive models trained on the three datasets. The analysis of gene expression profiles to identify differentially expressed genes (DEGs) was performed after preprocessing and normalization of data. Then, statistically significant prioritized DEGs were used to construct protein-protein interaction networks for the stages for module analysis and biomarker identification. Furthermore, the prioritized DEGs were used to determine the involved GO enrichment and KEGG signaling pathways at various stages of the breast cancer. The recurrence survival rate analysis of the identified gene biomarkers was conducted based on Kaplan-Meier methodology. Furthermore, the identified genes were validated not only by using several classification models but also through screening the experimental literature reports on the target genes. Fourteen (21 genes), nine (17 genes), eight (10 genes), four (7 genes), and six (8 genes) gene modules (total of 53 unique genes out of 63 genes with involving those with the same connectivity degree) were identified for stage I, stage II, stage III, stage IV, and the integrated group. Moreover, SMC4, FN1, FOS, JUN, and KIF11 and RACGAP1 genes with the highest connectivity degrees were in module 1 for abovementioned stages, respectively. The biological processes, cellular components, and molecular functions were demonstrated for outcomes of GO analysis and KEGG pathway assessment. Additionally, the Kaplan-Meier analysis revealed that 33 genes were found to be significant while considering the recurrence-free survival rate as an alternative to overall survival rate. Furthermore, the machine learning calcification models show good performance on the determined biomarkers. Moreover, the literature reports have confirmed all of the identified gene biomarkers for breast cancer. According to the literature evidence, the identified hub genes are highly correlated with HER2-negative breast cancer. The 53-mRNA signature might be a potential gene set for TNM based stages as well as possible therapeutics with potentially good performance in predicting and managing recurrence-free survival rates at stages I, II, III, and IV as well as in the integrated group. Moreover, the identified genes for the TNM-based stages can also be used as mRNA profile signatures to determine the current stage of the breast cancer.

Proteomics of Sentinel Lymph Nodes in Early Breast Cancer for Identification of Thymidylate Synthase as a Potential Biomarker to Flag Metastasis: A Preliminary Study

Introduction

Breast cancer is the second most common cancer in women across the world. Some of the patients who present in the early stage of disease are affected by metastasis to the axillary group of lymph nodes. The first among this group that is affected is called as sentinel lymph node, and its diagnosis is crucial for the staging of cancer thereby dictating the type of surgical therapy. Therefore, the sentinel lymph node status provides the most relevant information to the surgeon and patient prognosis. The expanded utilization of breast conservation surgery has declined the morbidity associated with mastectomy and axillary lymph node surgery. Recent interest is, therefore, centered on techniques that allow accurate assessment of the sentinel lymph node metastasis. A current procedure such as sentinel lymph node biopsy (SLNB) that is used to assess axillary lymph node metastasis is neither specific nor sensitive, and besides, it is time-consuming.

Objective

To compare the protein profiles between metastatic and non-metastatic lymph nodes to identify a biomarker that can flag lymph node metastasis.

Materials and Methods

Women with early breast cancer were screened using mammography imaging and recruited to the study. Surgical resection was done to remove the breast tissue, and sentinel lymph node was identified using fluorescein and methylene blue tracer. Lymph node was sliced, and one set was sent for histopathology, which was considered the gold standard to assess the metastatic status of the lymph node. One set of slices was taken for proteomic experiments. Proteins were labelled with fluorescent cyanine tags and were subjected to difference gel electrophoresis experiment. Differentially expressed spots that had at least a twofold relative ratio and consistent pattern across three sets of biological replicate experiments were marked. Gel spots were trypsin digested and identified on mass spectrometry machine. Validation study was done by Western blot experiment on the same set of samples.

Results

Thymidylate synthase has a twofold higher expression in the metastatic sentinel lymph nodes as compared to non-metastatic lymph nodes in early breast cancer patients.

Conclusion

Differential in gel expression proteomics is an ideal platform for the identification of potential protein biomarker candidates that can differentiate metastatic from non-metastatic lymph nodes in early breast cancer. The identification of thymidylate synthase offers a scope to develop an on-table diagnostic kit to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical management of axillary lymph nodes in early breast cancer.

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An experimental and algorithm-based study of the spectral features of breast cancer patients by a photodiagnosis approach

In the present study, the spectral diagnosis of blood plasma samples of breast cancer patients and an equal number of normal controls was investigated. A set of ratio parameters was acquired by employing SXS and FES. The samples were also analyzed statistically by employing Welch two-sample t-tests, and the effects of three ratio parameters, R₁, R₂, and R₃, were also studied by plotting them against the subject numbers. A linear discriminant was also applied to verify the exact classification of normal control and breast cancer patients. It was observed that the levels of biofluorophores such as porphyrin, NADH, tryptophan and flavins were elevated 2- to 3-fold for breast cancer patients compared to normal controls, with an accuracy of approximately 100 %. We have also confirmed the validity of the obtained experimental results by using an advanced robust diagnostic algorithm. The experimental results of the current study may have a vital and substantial impact on the detection and screening protocols used for future breast cancer patients. The spectral analysis of body fluid could be of great value to add to and enhance the current procedures with an accuracy of approximately 100 % with limited number of samples. The results and objectives of this preliminary study were encouraging and useful for the discrimination of the features of breast cancer patients compared to those of normal controls.

Overview of Breast Cancer and Implications of Overtreatment of Early-Stage Breast Cancer: An Indian Perspective

The prevalence and mortality of breast cancer is increasing in Asian countries, including India. With advances in medical technology leading to better detection and characterization of the disease, it has been possible to classify breast cancer into various subtypes using markers, which helps predict the risk of distant recurrence, response to therapy, and prognosis using a combination of molecular and clinical parameters. Breast cancer and its therapy, mainly surgery, systemic therapy (anticancer chemotherapy, hormonal therapy, targeted therapy, and immunotherapy), and radiation therapy, are associated with significant adverse influences on physical and mental health, quality of life, and the economic status of the patient and her family. The fear of recurrence and its devastating effects often leads to overtreatment, with a toxic cost to the patient financially and physically in cases in which this is not required. This article discusses some aspects of a breast cancer diagnosis and its impact on the various facets of the life of the patient and her family. It further elucidates the role of prognostic factors, the currently available biomarkers and prognostic signatures, and the importance of ethnically validating biomarkers and prognostic signatures.

Optimized Cylindrical Diffuser Powers for Interstitial PDT Breast Cancer Treatment Planning: A Simulation Study

Purpose

It is well known that interstitial photodynamic therapy (iPDT) of large tumors requires effective planning to ensure efficient delivery of therapeutic dose to the target tumors. This should be achieved in parallel with minimal damage to the nearby intact tissues. To that end, clinical iPDT can be attained using cylindrical diffusing optical fibers (CDFs) as light sources. In this work, we optimize output CDF powers in order to deliver a prescribed light dose to a spherical volume such as a tumor node.

Methods

Four CDFs are placed vertically inside the tumor node. The fluence rate is calculated using the diffusion equation. Therapeutic target dose is (20-50) J·cm⁻². The optical properties (μ_a = 0.085 cm⁻¹, μ_s′ = 16 cm⁻¹) of a breast tumor and the treatment time of 150 sec are used to calculate the fluence rate.

Results

For four CDFs, the therapeutic target dose (20-50) J·cm⁻² is delivered to more than 90%. This is the ratio of the total points that receive the target dose in proportion to the total points in the volume of the node of 3 cm in diameter, whereas, in larger nodes, the ratio is decreased to approximately 67%. Five CDFs are required to improve this ratio by more than 10%.

Conclusion

Optimizing delivered powers enables the distribution of the therapeutic dose uniformly in the medium. In addition, this simulation study represents an essential part of a development dosimetry system for measuring and controlling the optical dose in the breast tumors.

[Cytokine production by blood immune cells, tumor and its microenvironment, characteristic of extracellular matrix in patients with invasive ductal carcinoma of no special type]

The aim of this research was to study cytokine production by blood immune cells, tumor, and its microenvironment, and characterize extracellular matrix of patients with invasive ductal carcinoma of no special type and lymphatic metastases. Spontaneous and polyclonal activators stimulated production of cytokines by blood immune cells, tumor and its microenvironment were studied in 95 patients with invasive ductal carcinoma of no special type. The concentration of IL-2, IL-4, IL-6, IL-8, IL-10, IL-17, IL-18, IL-1β, IL-1Ra, TNF-α, IFN-γ, G-CSF, GM-CSF, VEGF and MCP-1 was determined by the solid-phase enzyme-linked immunosorbent assay. The condition of fibrous component and presence of neutral glycoproteins and sulfated glycosaminoglycans were evaluated during the research of extracellular matrix. Regional lymphatic metastases were detected in 35 of 95 patients. It was shown that in the presence or absence of lymphatic metastases index of polyclonal activators influence on the production of cytokines by blood immune cells was different for IL-6, IL-8, and IL-1β; while in the case of cytokine production by tumor and its microenvironment the index of influence was different for IL-2 and IL-17. The presence of lymphatic metastases corresponded with the rise of cytokines spontaneous production, while the absence of lymphatic metastases corresponded with the rise of cytokines production stimulated by polyclonal activators. The value of indices of polyclonal activators influence on the production of cytokines by blood immune cells pointed to the highly stimulating effect of polyclonal activators while the value of indices of polyclonal activators influence on cytokines production by tumor and its microenvironments pointed to the low and sometimes even absent effect of polyclonal activators. Basing on these data we propose a ratio of indices of polyclonal activators influence for the better evaluation of the probability of lymphatic metastases during preoperative period. After characterizing extracellular matrix we found out a point threshold, which, in 100% of cases, predicted the presence of lymphatic metastases basing on the condition of extracellular matrix. Using the data acquired, we are proposing a risk group for metastasis among women with no lymphatic metastases in the moment of check-up.

Proposal for a Histological Staging System of Mammary Carcinomas in Dogs and Cats. Part 1: Canine Mammary Carcinomas

Background: Staging of mammary carcinomas of dogs and cats is not only important for prognostic purposes, but also to guide therapy, in particular regarding adjuvant chemotherapy. The classical staging system relies on T, the clinical tumor size, N, the clinical nodal stage, and M, distant metastasis, evaluated by the clinician. However, a more precise and reliable staging system is applied to human stage I–III breast cancer, i.e., without distant metastasis, in which T is replaced by the pathologic tumor size (pT), and N is replaced by the pathologic nodal stage (pN), both evaluated by the pathologist. This staging system is strongly associated with patient outcomes, and is used to select treatment options. The purpose of this study was to design a histologic staging system for Canine Mammary Carcinomas (CMCs, part 1 of this article), and Feline Mammary Carcinomas (part 2), inspired from human oncology, and to assess its association with patient outcomes.

Materials and Methods: This retrospective study included 433 female dogs with a surgically removed CMC. Patient outcomes were recorded over a 2-years follow up period. CMCs were staged according to pT (greatest diameter in millimeters on histological slides), lymphovascular invasion (LVI), and pN (confirmed by cytokeratin AE1/AE3 immunohistochemistry). The histological stages were defined as: Stage 0 (CMCs in situ, surrounded by a continuous layer of p63+ myoepithelial cells), Stage I (pT1 ≤ 20 mm, LVI–, pN0–pNX, where pNX refers to the absence of lymph node sample), Stage II (pT2 > 20 mm, LVI–, pN0–pNX), Stage IIIA (pT1, LVI+, and/or pN+), and Stage IIIB (pT2, LVI+, and/or pN+).

Results: Disease-free-interval, overall survival and specific survival significantly differed by histological stage. For specific survival, median survival times and hazard ratios (HR) by Cox proportional hazards regression (p < 0.0001) were: Stage 0 (median survival not reached; HR = 1.00; N = 89; 21% of the dogs), Stage I (1,720 days; HR = 3.05; p = 0.0018; N = 81; 19%), Stage II (1,181 days; HR = 4.39; p < 0.0001; N = 79; 18%), Stage IIIA (348 days; HR = 10.59; p < 0.0001; N = 79; 18%), and Stage IIIB (163 days; HR = 16.59; p < 0.0001; N = 105; 24%).

Conclusion: The proposed histological staging system (invasiveness, pT, LVI, pN) is a very strong prognostic factor for CMCs.