Breast Cancer

Breast cancer management depends on molecular subtypes. The aim was to compare disease-free survival (DFS) among the different subgroups. Overall survival (OS) is a secondary endpoint.

This cross-sectional study was done on breast cancer women that were treated in our center, from 2009 to 2015. Breast cancer molecular subtypes were determined based on clinicopathological criteria recommended by St Gallen and include; luminal A, luminal B Her- 2-neu positive, luminal B Her-2-neu negative, Her-2 enriched and triple negative. Patients with metastasis at diagnosis or those without follow-up were excluded. Patients were followed-up from 12 to 132 months. Cox regression analysis was used for analogy of DFS and OS between the subgroups.

Out of three hundred patients, 221 were enrolled with median age of 47 years old (26 to 83). Luminal B, Her-2 negative was the most common subgroup with 83 patients (35.5%). Five and 10 years PFS were 95% and 81% for luminal A, were 95.5% and 92% for luminal B Her-2 positive, were 92% and 91% for luminal B Her-2 negative, were both 84% for triple negative and were 76% and 74% for Her-2 enriched subgroups, respectively. With multivariate analysis, the stage of tumor (HR=5.9 CI=1.06-32.69) and triple negative subgroup (HR=5.2 CI=1.33-20.31) were independent factors for recurrence.

Based on the results of this study, the triple-negative breast cancer and possibly Her-2 enriched subgroup have a shorter DFS than luminal breast cancers. Also, the stage of tumor is an independent factor for recurrence.

Combining natural compounds with chemotherapeutic agents has emerged as a promising approach for cancer treatment. Curcumin (Cur), a natural polyphenol, is known for its anti-cancer properties, including the ability to induce apoptosis and arrest cell cycle progression.

This study aimed to evaluate the effects of Cur and etoposide (ETO), both individually and in combination, on the induction of apoptosis in breast cancer (BC) cell lines.

The impact of Cur and ETO on cell proliferation was assessed using MTT viability assays. Apoptosis induction by these drugs was evaluated through Annexin V flow cytometry and caspase-3 and caspase-9 activity assays. Quantitative real-time PCR was employed to measure Bax and Bcl-2 gene expression levels. Western blotting was conducted to determine protein levels of p53, p21, Bax, and Bcl-2.

A non-significant dose of ETO was selected based on MTT assay results and combined with 75 μM of Cur. Curcumin enhanced ETO’s pro-apoptotic effect by increasing caspase activities. The combination of Cur and ETO significantly reduced Bcl-2 gene expression while upregulating Bax expression. Furthermore, treatment with this combination elevated the protein levels of p53, p21, and Bax, compared to ETO or Cur alone, while significantly decreasing Bcl-2 protein levels.

Cur has the potential to amplify ETO-induced apoptosis in BC cells. This combination may offer a promising therapeutic approach for BC.

Hormone therapy is commonly used to treat breast cancer but can cause mood disorders and sleep disturbances, negatively impacting patients' well-being.

This trial aimed to evaluate the effects of melatonin on sleep problems and mood changes in breast cancer patients undergoing hormone therapy.

The study was conducted at Omid Hospital in Isfahan, Iran, using a randomized, double-blinded, placebo-controlled design. Participants were assessed using the Hospital Anxiety and Depression Scale (HADS) and were randomly assigned to receive either 6 mg of melatonin or a placebo daily for 4 weeks. Sleep quality, depression levels, and mood states were measured using the Pittsburgh Sleep Quality Index (PSQI), the Center for Epidemiological Studies-Depression Scale (CES-D), and the Profile of Mood States (POMS) Questionnaires at the beginning and end of the 4-week follow-ups.

Sixty participants (34 in the melatonin group and 26 in the placebo group) completed the study. Melatonin administration significantly improved sleep quality, latency, duration, and reduced the use of sleep-promoting medication, according to the PSQI scores. However, there were no significant improvements in depression severity or mood disorders, as assessed by the CES-D and POMS questionnaires, in either group following the 4-week melatonin supplementation period.

Melatonin supplementation effectively alleviated sleep disturbances caused by hormone therapy in breast cancer patients. However, the study did not find substantial evidence supporting the use of melatonin for improving mood disorders or depression in this specific context.

Herbal compounds sourced from various plants are becoming targeted therapies for breast cancer.

This study aims to explore the potential of focusing on herbal compounds as targeted therapies for breast cancer using computational techniques.

A total of 129 herbal compounds linked with breast cancer were identified from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. Molecular docking and MD simulation were carried out against three protein targets linked with breast cancer. Network pharmacology was used to identify the common plant sources for the bioactive compounds, and interaction networks were constructed. The ADME-toxicity profiles and density functional theory (DFT) analysis were calculated for the top docking hits.

Dipiperitylmagnolol and sophoranone were identified as the top docking hits and lead compounds. Network pharmacology analysis revealed Magnolia species as the common plant sources having multiple bioactive compounds. MD simulation analysis revealed conformational stability of the top docking hits. The analyses underscore the robust binding potential of dipiperitylmagnolol and its possible therapeutic relevance in targeting breast cancer pathways. ADME-toxicity and DFT analysis provided insights into the pharmacokinetic and electronic behavior of the top docking hit. Combinatorial study of herbal therapies with conventional treatments will increase the therapeutic efficacy for breast cancer treatment.

The study provides insights into the implications of herbal compounds as targeted therapy for breast cancer. Therefore, the study recommends further experimental validation and development of herbal-based compounds for the treatment of breast cancer.

Breast cancer is one of the most common types of cancer in women, and its incidence is increasing in Iran. HER- 2-positive breast cancer is invasive and often associated with poorer outcomes. Patients with this type of breast cancer can develop resistance to medications like trastuzumab. Trastuzumab-emtansine (TDM1) is a medication developed to reduce cancer cell resistance to trastuzumab. The TDM1 has been shown to decrease the incidence of death and recurrence in breast cancer.

This study aimed to evaluate the cost-utility and calculate the budget impact of TDM1 versus trastuzumab for the treatment of residual invasive HER-2-positive breast cancer.

A Markov model with a lifetime horizon was developed, incorporating four health states. Women aged 45 with residual invasive HER-2-positive breast cancer entered the model. The study adopted a healthcare system perspective, with costs reported in 2021 US dollars. Discount rates of 7% for costs and 3% for utility values were applied. Utility values and transition probabilities were derived from published literature. Costs were estimated based on guidelines, expert opinions, and Iranian tariffs. Iran’s pharmacoeconomic threshold of 1085$ was used for comparison. The incremental cost-effectiveness ratio (ICER) and budget impact of TDM1 were calculated, and sensitivity analyses were conducted to assess the robustness of the model.

The model indicated that treatment with TDM1 resulted in a 1.59 quality-adjusted life year (QALY) increase, with an additional cost of 1408$. This was deemed cost-effective, considering Iran’s pharmacoeconomic threshold of 1085$ (calculated ICER: 886$ per QALY gained). One-way sensitivity analysis revealed that the model was sensitive to the costs of TDM1 and trastuzumab, the discount rates for utility values and costs, and the probability of achieving invasive disease-free survival (IDFS). Probabilistic sensitivity analysis showed that 59.61% of simulations fell below Iran’s pharmacoeconomic threshold, supporting the model's robustness. The budget impact analysis revealed that the additional budget required for TDM1 treatment over a three-year period was 1,120,546$ compared to trastuzumab.

Although TDM1 imposes higher costs, it is more cost-effective than trastuzumab for the treatment of residual invasive HER-2-positive breast cancer in Iran

Context: 

Breast cancer poses significant challenges due to its high incidence and prevalence, necessitating heightened attention. Understanding how patients prioritize different treatment options based on various attributes can assist healthcare decision-makers in maximizing patient utility. The discrete choice experiment, a conjoint method, facilitates preference elicitation by presenting different attributes and choices. This systematic review aims to identify key factors in patient preference research related to adjuvant treatment for early breast cancer characterized by hormone receptor-positive, HER2- negative status.

Evidence Acquisition: 

PubMed, Embase, Web of Science, and Scopus were searched from 01.01.2000 to 31.03.2023. Original English articles reporting patient preferences in adjuvant breast cancer treatment were retrieved based on predefined inclusion and exclusion criteria. Included studies were examined through a narrative synthesis approach, with descriptive statistics employed for analysis.

Out of 1163 articles reviewed, four met the inclusion criteria and were conducted in the USA, Canada, and the Netherlands. Attributes extracted from all studies included alopecia, sensory neuropathy, motor neuropathy, myalgia/arthralgia, nausea, vomiting, fatigue, neutropenia, mucositis/stomatitis, hand-foot syndrome, diarrhea, prevention of breast cancer recurrence, osteoporosis, risk of endometrial cancer, joint and muscle pain, fluid retention, libido decrease, hot flashes, ECG monitoring, efficacy, treatment regimen, 5-year invasive disease-free survival (iDFS), dosing schedule, and treatment duration. The most frequently reported attributes were side effects, efficacy, and treatment regimen. Systematic review was commonly used to determine which attributes and levels to include. The minimum number of attributes identified per study was seven, and the maximum was 12. Sample sizes ranged from 102 to 300, with none of the studies mentioning the method of sample size estimation. Ordinary Least Squares, logistic regression, and hierarchical Bayes regression were the most frequent analysis methods.

Side effects, 5-year iDFS, and treatment regimen are three attributes identified for conducting discrete choice experiment studies. Utilizing conjoint analysis to assess patient preferences for breast cancer treatment can aid in selecting optimal treatment regimens and improving patient adherence. Moreover, adhering to guidelines for developing experimental designs and conducting data analysis is essential for yielding robust results when employing preference elicitation methods.

Invasive ductal carcinoma (IDC) is a prevalent type of breast cancer with significant mortality rates. Early detection is crucial for effective treatment options. Deep learning techniques have shown promise in medical image analysis, but further improvements are needed.

A Wavelet-Convolutional Neural Network (WCNN) isproposed, incorporating wavelet filtersand convolutional filtersin each layer to capture both frequency and spatial domain features. The processed images resulting from both types of filters werecombined and passed through a MaxPooling layer to extract salient features.Four such hybrid layers were considered for extracting effective features.This novel approach allowedthe model to effectively learn multi-scale representations, leading to improved performance in breast cancer classification tasks.The model was trained and evaluated on a publicly available breast histopathology image dataset.

The proposed WCNN achieved a classification accuracy of 98.4% for breast cancer detection, outperforming existing state-of-the-art models.

The WCNN framework demonstratedthe potential of combining wavelet and convolutional filters for improved breast cancer detection, offering a promising approach for early diagnosis and better patient outcomes

Breast cancer (BC) is a common type of malignancy in females in Iraq. This study investigated BC's clinical and diagnostic features in 30 women and displayed its relationship with periodontal disease.

This cross-sectional study comprised 30 BC patients diagnosed in 2023. The clinical signs, ultrasound, biopsy, histopathology and Immunohistochemistry, treatment modules, and clinical signs of periodontal disease were reported and analysed.

The mean and standard deviation of patients’ age was 51.73± 11.41. The location of Breast Cancer lesions was on the left and right sides in 11 (36.66%) and 19 (63.33%) patients, respectively. All patients showed various sizes of non-painful lumps with well-defined masses in different areas of the breast tissue with regular or irregular borders in ultrasound and MRI. The gross and histopathological changes of cancerous tumors differed according to conditions, stage, and interaction with the cancer receptors in Immunohistochemistry. The percentage of metastases was 100% (in 30 cases) for the lymph nodes and 66.66% (in 20 cases) for the rest of the other organs. Different treatment modules were used, including chemotherapy, surgery, radiation, and hormonal therapy. The cases suffering from mild, moderate, and severe periodontal disease were 7 (23.33 %), 2 (6.66%), and 21 (70%), respectively.

The clinical signs, histopathological, IHC, and occurrence of periodontal disease in 30 women withbreast cancer were documented in this study. The authors recommend further studies on breast cancer to support its early diagnosis and prevention strategies.

Breast cancer is the most prevalent cancer among women, emphasizing the need for early detection and accurate diagnosis.This study investigates the role of the Apparent Diffusion Coefficient (ADC) in distinguishing between benign and malignant breast lesions using Magnetic Resonance Imaging (MRI) and Diffusion-Weighted Imaging (DWI). A retrospective cross-sectional study was conducted involving 96 patients with breast lesions who underwent MRI and DWI scans.

Patients were selected from among those who had MRI and DWI scans with b-values of 0, 800, and 1000 s/mm². ADC values were calculated by plotting the Region of Interest (ROI) and extracting corresponding values. Histological evaluations confirmed the diagnosis of the lesions. Statistical analyses included calculating accuracy, sensitivity, and specificity, along with Receiver Operating Characteristic (ROC) curve analysis to determine the optimal cut-off value.

The ADC values demonstrated an accuracy of 92.5%, sensitivity of 93.2%, and specificity of 91.2% in differentiating between benign and malignant lesions. The ROC curve analysis established a cut-off value of 1.44 × 10⁻³ mm²/s for effective differentiation.

ADC values can serve as a reliable biomarker for distinguishing breast lesions, potentially reducing unnecessary biopsies for benign cases and aiding clinicians in treatment decisions. The integration of ADC measurements into clinical practice could enhance patient management in breast cancer. Further research is warranted to validate these findings and explore additional markers to improve diagnostic accuracy in breast cancer management.

The study aimed to compare the effects ofthe combination of PECS Block II with GA and GA alone on the inflammation levels in breast cancer, measuredby Tumor Necrosis Factor-Alpha (TNF-α) and the red blood cell distribution width to platelet ratio (RPR).

This experimental analytical study which was aparallel randomized control trial was done on48 breast cancer patients who underwent breast removal surgery at Dr. Kariadi Hospital fromAugust toOctober,2023. Patients were randomly assignedto twogroups, control (GA only) and treatment (PECS Block II + GA). Demographic data were obtained preoperatively, with blood samples collected 24 hours before and after surgery. TNF-α levels were analyzed using enzyme-linked immunosorbant assay (ELISA), while RPR were obtained from complete blood counts.Independent t and mann-whitney tests were used, with a P-value <0.05 considered to be significant.

Postoperative TNF-α levels were similar in both groups (8.15 ± 5.31 vs 6.21 ± 5.58; P=0,135), but the difference between TNF-α levels wassignificantly higher in the treatment group (-5.08 ± 3.70; P= 0.001). Postoperative RPR levels were higher in the control group than in the treatmentgroup (0,64 ± 0,28vs 0,50 ± 0,20; P=0,031), where the difference between RPR levels was higher in the treatment group (-0,07 ± 0,19; P= 0,037).

Inflammatory biomarkers, in the form of TNF-α and RPR in breast cancer surgery were found to be lower with the usage of the combination of PECS Block II with general anesthesia than with general anesthesia only.

Breast cancer (BC) counts for half of the excess risk of second cancer after Hodgkin Lymphoma (HL), but evidence about the clinical and pathological features of these cancers is lacking. The aim of this study was to evaluate whether these secondary BCs have distinctive characteristics compared to sporadic ones.

This is a case-control study comparing patients who developed BC after receiving treatment for HL with an age-matched cohort of non-irradiated patients. All the cases were treated at the Veneto Institute of Oncology (Padua, Italy) between 2002 and 2017. We analyzed the clinical and pathologic features of BCs and compared treatment modalities using Chi-squared tests. Kaplan-Meier survival analyses were conducted to investigate overall and disease-free survival in the two groups.

In this study, 35 patients who were treated for HL and subsequently developed BCs were identified. BC occurred after a mean interval of 19.65 years (SD=10.08 years) from the HD diagnosis. According to the results, 4 of the patients treated for HL (11.4%) had a bilateral presentation. Also, 80% of the cases and 63% of the controls were ER+/HER- (p=0.516), while 20% of the HL group and 5.7% of the sporadic group were ER- /HER- (p=0.116). Ipsilateral BC recurrence (17.1% vs 8.6% in the sporadic BC group, p=0.346) and death events were more frequent in the HL group (11.4% vs 5.7% in the sporadic BC group, p=0.433), with a mean follow-up of 70 months (standard deviation=42.8months).

Our data show that BC arising after HL often presented with bilateral localization, aggressive biological profiles, and had high recurrence rates. Dedicated treatment modalities should be considered and evaluated in a multidisciplinary setting.

Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of paclitaxel-and taxanes-based chemotherapy, which is generally given to breast cancer and can lead to low quality of life along with neuropathy symptoms even after completion of the chemotherapy treatment.

In this paper, we present a narrative overview of CIPN, chemotherapy medication that causes neuropathy in breast cancer patients, treatment challenges for CIPN and pathological complications, current trends, and future research challenges, based on expertdiscussion and a current literature search.

At present, there are no gold-standard treatment protocols available, which has made it more devastating for the patients suffering from breast cancer. The incidence rate of CIPN is 19% to 85% or above, and it can only decrease if treatment is available. Moreover, treatments are available, but only based on the symptoms.

Worldwide, cancer is the primary cause of millions of deaths annually. We still lack an appropriate treatment plan for the adverse effects that follow chemotherapy treatment, despite the fact that cancer treatment has advanced over the last decade. CIPN isone of the most frequent side effects, and the patients will experience symptoms of neuropathy after one or two chemotherapy cycles. Oncology nurses play a very critical role in managing CIPN symptoms but are sometimes overlooked during the assessment period. Managing neuropathic pain, maintaining safety protocol, improving physical function, and proper standardized nursing CIPN treatment protocol should be the primary goals for managing the CIPN.

Breast cancer normally occurs in elderly women, although it also affects young women. In the Limpopo province, South Africa, over 38% of breast cancer occurs in younger women under 50 years of age. The main objectives of the study were to identify the characteristics of breast cancer in women >50 years and <50 years and to categorise any differences (histological type, stage, grading and molecular subtype) between these two groups of breast cancer patients.

This was a cross-sectional design study to analyse the profile of women >50 and <50 years with breast cancer who attended Mankweng Breast Oncology Clinic from July 2020 to December 2021. Patient demographics were summarised using descriptive statistics. Categorical variables were expressed as proportions and frequencies. The correlationbetween categorical variables was assessed using a Chi-square test.

A total of 222 patients participated in the study. The following results were obtained: Age: >50 years-old: 131 (59%); <50 years old: 91 (41%). Age: >50 years group: Early stage: 49 (37.4%), late stage: 82 (62.6%). Molecular subtype: luminal A: 23 (17.6%); luminal B: 67 (51.2%); HER-2 overexpression: 21 (16%); triple negative: 20 (15.3%). Histological type: invasive ductal carcinoma: 126(96.2%). Age: <50 years group: Early stage: 31 (34.1%), late stage: 60 (65.9%). Molecular subtype: luminal A: 28 (30.8%); luminal B: 40 (44%); HER-2 overexpression: 5 (5.5%); triple negative: 18 (19.8%). Histological type: invasive ductal carcinoma: 89 (98%).

Majority of patients presented at an advanced stage in both groups. HER2 overexpression molecular subtype was higher in the >50-year patient group compared to <50 year old group (P = 0.016). Health education and breast cancer awareness campaigns are essential for all women, young and elderly in the Limpopo province.

Breast cancer (BC) is the most prevalent and lethal cancer in women. Prognostic factors are used to guide treatment and predict the prognosis. This study aimedto assess the influence of prognostic factors on the survival of patients with non-metastatic invasive BC.

Data from invasive BC patients admitted to Medical Oncology Department of Süleyman Demirel University between October 2002 and October 2013 were retrospectively reviewed. Clinicopathologic features, treatment information, and follow-up data were noted. The Kaplan-Meier method was used to estimate survival functions. Multivariate Cox regression analysis was performed to identify prognostic factors for disease-free survival (DFS) and overall survival (OS), with P-values <0.05 for univariate results

A total of 717 patients entered the study.The median follow-up time was 41 months. Recurrence was detected in 17.4% of the patients, and 111 (15.5%) patients died. The 5-and 10-year DFS rates were 78% and 61%; OS rates were 86% and 70%, respectively. In multivariate analyses, DFS and OS were associated with axillary lymph node involvement (P<0.001 and P<0.05, respectively), tumor size (P<0.05), and histologic grade (P<0.05),whereas human epidermal growth factor receptor 2 positivity had only a statistically significant effect on poor OS (P=0.004).

Consistent withprevious studies, traditional prognostic factors had an important impact on prognosis in invasive BC patients. In the current era, where more conservative surgical approaches and new, effective systemic neoadjuvant and adjuvant therapies are widely used, the importance of the traditional prognostic factors highlighted in our study needs to be established by further studies.

Long non-coding RNAs (NKILA and LINC00993) are downregulated inbreast cancer(BC) and can have potential use as a novel tumor biomarker. The aim of thiswork was to investigate the LncRNAs (NKILA and LINC00993) and cytokines(NF-κB and CXCL-1) as potential biomarkers in BC.

This cross-sectionalstudy included sixty-four pairs of surgically resected human breast cancer tissues and adjacent breast tissues. Expressions of LncRNAs (NKILA, LINC00993) and (NF-κB, CXCL1) cytokineswere detected using real-time quantitative polymerase chain reaction (qPCR) analysis,

There was a significant decrease in LncRNAs (NKILA, LINC00993) levelsin tumor tissue compared to normal tissue (P<0.001). Also, there was a significant increase in NF-κB and CXCL1 levels in tumor tissue compared to normal tissue (P<0.001). ROC curve analysis indicated that the LncRNAs (NKILA, LINC00993) expression levels could be considered a promising marker for the diagnosis of breast cancer patients with a sensitivity of 90.6%, 92.2%,respectively. Also, cytokines(NF-κB and CXCL-1) expression levels could be considered a promising marker for the diagnosis of breast cancer patients with a sensitivity and specificity of 87.5%, and 89.1% respectively.

These findings suggest that LncRNAs (NKILA, LINC00993) and cytokines(NF-κB and CXCL-1) can be used as novel biomarkers for breast cancer.

Recognizing the family’s role as a vital source of support and care for cancer patients, along with the psychological burden borne by family caregivers, is crucial. Utilizing modern technologies presents a new approach to assisting these families.

This study aimed to evaluate the impact of web-based training on the caregiving burden of family caregivers of patients with cancer undergoing chemotherapy.

This quasi-experimental study was conducted on family caregivers of patients with breast cancer visiting the hematology department of Khatam Al Anbia Hospital in Zahedan in 2023. A total of 70 caregivers were randomly assigned to intervention and control groups (35 participants each). Caregivers in the intervention group received web-based training via a researcher-developed website for 20 days. The Caregiver Burden Inventory (CBI; Novak & Guest, 1989) was administered to participants in both groups before and one month after the intervention. Data were analyzed using independent samples t -test, paired samples t -test, chi-square test, Fisher’s exact test, and analysis of covariance (ANCOVA) with SPSS-27 software. A significance level of P < 0.05 was set for statistical analysis.

No significant difference was observed in the mean psychological burden scores between the two groups before the intervention (P = 0.68). However, ANCOVA analysis, controlling for the pre-test effect, revealed that the mean psychological burden score in the intervention group (77.42 ± 11.87) was significantly lower than that in the control group (85.82 ± 9.69) after the web-based training intervention (P = 0.001).

The web-based training intervention significantly reduced the psychological burden of family caregivers of patients with breast cancer. This study demonstrates that a web-based training approach can effectively support family caregivers of cancer patients who are unable to attend in-person training sessions.

Breast cancer is the most prevalent malignancy among women. Inflammatory cytokines such as tumor necrosis factor-α (TNF-α) play a critical role in cancer pathogenesis and malignancy.

This study aimed to evaluate serum levels of TNF-α across different subtypes and stages of breast cancer.

Serum samples were collected from 114 patients with various subtypes and stages of breast cancer. Tumor necrosis factor-α levels were measured using enzyme-linked immunosorbent assay (ELISA).

Serum TNF-α levels were significantly higher in patients with triple-negative breast cancer (TNBC) compared to those with other breast cancer subtypes (P < 0.0001). Additionally, TNF-α levels were markedly higher in patients with stage III carcinoma than in those with stages I and II (P < 0.0001). Among stage III TNBC patients, TNF-α concentrations were significantly higher than those in stage III patients from other groups (P < 0.05).

Evaluating serum TNF-α concentrations can provide valuable insights for estimating cancer prognosis and guiding patient management.

Breast cancer remains a significant global health concern, with challenges in treating advanced stages necessitating the exploration of novel therapeutic approaches. Bacterial outer membrane vesicles (OMVs) have shown promise in cancer immunotherapy by targeting cancer cells and modulating immune responses. This study investigated the effects of Helicobacter pylori-derived OMVs on the activation of the Snail/β-Catenin gene cascade in regulating inflammation and cell migration in a mouse model of breast cancer.

The OMVs were extracted from the culture of H. pylori strain 26695 (ATCC 700392) using ultracentrifugation. In the mouse model, the vesicles were injected intraperitoneally into Balb/c mice with breast tumors. Tumor growth was assessed through histological examination of tumor samples. IgA and IgG antibodies were measured using ELISA. The expression of E-cadherin and vimentin proteins was evaluated by immunohistochemistry, and real-time PCR was used for vimentin, Snail, α-SMA, and β-catenin in serum samples from the different groups.

The OMV treatment led to a significant increase in the expression of α-SMA, β-catenin, Snail, and vimentin genes, indicating a potential induction of epithelial-mesenchymal transition and enhanced cancer cell growth. Additionally, a decrease in vimentin expression and an increase in E-cadherin expression were observed, suggesting inhibition of cell migration. The study also revealed alterations in systemic IgA and IgG antibody levels, indicating potential immunomodulatory effects of OMVs.

These findings highlight the therapeutic potential of OMVs derived from H. pylori in breast cancer treatment by targeting gene cascades involved in cancer progression and modulating immune responses.

Breast cancer is a leading cause of female mortalities worldwide. This study has used machine learning techniques to determine the most critical factors influencing the survival rate of breast cancer patients in Isfahan.

 A list of variables influencing the survival of breast cancer patients was initially extracted from the data sets of two Isfahan hospitals for this analytical investigation, leading to the extraction of 16 critical factors based on the opinions of oncologists. In the next step, the missing values were identified and deleted or corrected, followed by converting some features into numerical ranges. Ultimately, the key variables influencing the survival rate of breast cancer patients were determined by applying 11 machine learning algorithms.

 Forward selection is more accurate than other techniques. Of the 15 input features, 13 were extracted as influential survival rates at least once using different techniques, with BC-ER-PR-HER2 ranking first among the features. The six first features, including Bc-ER-PR-HER2, lymph node dissection, behavior, primary surgery procedure, the exact number of nodes examined, and the exact number of positive nodes, were determined as the best combination for identifying breast cancer patients. Even though cancer behavior patterns differ in various societies, there are still similarities in risk factors.

 Forward selection combined with principal component analysis using support vector machines, neural networks, and random forests can be the best model for breast cancer prediction. Neural networks, random forests, and support vector machines are very good at predicting breast cancer survival.

Cardiotoxicity from chemotherapy may result in cardiomyopathy and heart failure. Clinicians can use the evaluation of cardiotoxicity?specific biomarkers, such as microRNA, as a tool for the early detection of cardiotoxicity. The study’s objective was to assess miR?146a levels as a potential biomarker for the detection of cardiotoxicity brought on by chemotherapy in patients with breast cancer.

Using quantitative reverse transcription?polymerase chain reaction, the levels of miR?146a were assessed in the blood of 37 breast cancer patients receiving anthracyclines without cardiotoxicity and 33 breast cancer patientsexperiencing cardiotoxicity brought on by chemotherapy after chemotherapy. Left ventricular ejection fraction (LVEF) ?50% was used to define heart failure by echocardiography.

MiR?146a did not show any significant difference in expression between these two study groups (P = 0.48, t?test). The expression level of miR?146a was not significantly associated with LVEF, age, and body mass index (P > 0.05), according to Pearson correlation.

MiR?146a may be a diagnostic or prognostic biomarker for cardiotoxicity brought on by chemotherapy, even though there was no discernible difference in the expression level of miR?146a between the control group and the breast cancer patients who were experiencing this side effect of chemotherapy. Therefore, miR?146a expression needs to be examined in a sizable cohort of breast cancer patients who are experiencing cardiotoxicity brought on by chemotherapy.