Iranian Journal of Breast Diseases
Year:2021 | Volume:14 | Issue:1 (52)|Papers Count:7

The COVID-19 pandemic has adversely affected physical, mental, social, and economic aspects of people’ s lives worldwide over the last year. In the early days of the pandemic, major public health priorities changed toward mobilization of resources for the care of COVID-19 patients and the protection of health workers and patients from exposure to the disease. This significantly influenced all aspects of cancer control strategies including screening, diagnosis, treatment, and supportive care. The cancer guidelines developed during the pandemic insisted on the management of urgent cases, which would naturally result in a decrease in preventive visits, screening tests, follow-up of abnormal test results, and symptom follow-ups (1). It was estimated that breast and cervix cancer screening tests had decreased by up to 94% and that 285000 breast screening tests had been missed in the United States (2). In the chain of cancer management, delays in each step can change the outcome of the next step. A reduction in the number of screening tests could result in missing the cancer diagnosis or recurrence. Studies from different countries reflect a reduction in the number of diagnosed breast cancer cases, ranging from one-third in the Netherlands to 52% in the US (1, 3, 4). Therefore, lower survival probability, fewer treatment options, more intensive treatment, and poor prognosis, as consequences of late diagnosis, can be expected (1). During the COVID-19 pandemic, some breast cancer treatment guidelines were developed based on the multidisciplinary approach and regional health facilities. One of those guidelines suggests categorizing breast cancer patients into three priority levels. Priority category A consists of patients with an urgent situation that requires immediate treatment, such as breast abscess and post-operative patients with unstable clinical and oncologic conditions. This group profits from in-person visits. Patients in priority category B should be treated before the end of the pandemic. It includes newly diagnosed breast cancer cases and patients who have completed neoadjuvant therapy and should undergo surgery. Because of the non– life-threatening nature of the situation of the patients in this category, a delay of 6-12 weeks would not impact patient outcomes. Finally, patients at the priority level C can have their treatment postponed until the end of the pandemic, for example, those who would present for routine follow-up for benign or malignant conditions and survivorship visits (5). However, priorities may change based on the patient’ s situation or local health policies. Some breast cancer patients experience their survivorship during the COVID-19 pandemic, which has affected their economic, social, and psychological status. Survivors’ financial situation has changed, causing concerns about palliative care costs and insurance support. Patients had to stay at home, which has led to social isolation and psychological stress. A survey on cancer patients aimed to assess the impact of the pandemic on health care delivery was conducted by the American Cancer Society Cancer Action Network. According to this survey, in which 52% of the participants were breast cancer survivors (6), access to supportive services during the pandemic, including physical therapy or mental health care, had decreased by 20% (1). Although the impact of COVID-19 on cancers may be more evident in the following years, an analysis of the effect of the pandemic on breast and colorectal cancer screening and treatment has predicted an increase of 1% (or 10000 deaths) in breast and colorectal deaths over the next decade (7). It is necessary to note that 60% of cancer research programs have also been postponed due to funding for the COVID-19 pandemic as a global priority (1). It is expected that the management of and research into breast cancer care in Iran, as one of the first countries affected by the pandemic, would have been disrupted, too. Unfortunately, no data is available regarding the impact of COVID-19 on different aspects of breast cancer in Iran. So, breast cancer burden control strategies should be considered a health policy priority through future programming and research. Iranian Journal Breast Diseases welcomes research articles, from different disciplines, that strive to shed light on the associations between the COVID-19 pandemic and various aspects of breast cancer (prevention, diagnosis, treatment, and rehabilitation). By giving priority to publishing these articles, we would hope to take positive steps toward addressing the gaps in the current knowledge and contribute to an improved health policy at a country level.

Introduction: Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The aim of this study was to analyze the trend and predict the incidence of breast cancer using time series analysis. Methods: In this study, data on breast cancer incidence in Qazvin province between 2007 and 2016 were analyzed using time series analysis with autoregressive integrated moving average (ARIMA) modeling to forecast the future pattern. The Box-Jenkins time series model and its diagnosis and evaluation methods were used to show the trend and forecasting the next year new cancers. To describe and fit the appropriate models, R statistical software version 3. 6. 3 was used. Results: Between 2007 and 2016, a total number of 1229 new patients had been registered (monthly mean [SD]: 10. 24 [1. 03]). Although the overall trend in the raw number of new breast cancer cases has been increasing over time, the change in observations over time has been increasing and decreasing. According to Bartlett test results, the variances of the data were not constant. Also, according to the results of Kolmogorov-Smirnov test, breast cancer series data were not normal. Among the studied models, ARIMA (1, 1, 1) was selected due to lower AIC criteria than other models, and this model was selected as the final model for predicting breast cancer for the next year. The confidence interval of the predicted values was relatively narrow, which indicates the appropriateness of the final model in the prediction. Conclusion: Time series analysis is an efficient tool to model the past and future data on the raw number of new cancer cases, and the goodness-of-fit indicators of the model showed that the Box-Jenkins model is a reliable model for fitting similar data.

Introduction: Breast cancer is one of the most common cancers among women worldwide. Patients with cancer may die due to disease progression or other types of events. These different event types are called competing risks. This study aimed to determine the factors affecting the survival of patients with breast cancer using three different approaches: cause-specific hazards regression, subdistribution hazards regression, and the random survival forest for competing risks. Methods: A historical cohort study was conducted on 527 breast cancer patients diagnosed in Mahdieh Medical Center, Hamadan, between 2004 and 2015. To determine risk factors for death due to cancer progression or other competing risks, cause-specific hazards and substandard hazards models and a random survival forest for competing risk were fitted. Data analysis was performed with R 3. 4. 3. Results: Findings showed that for death from the progression of breast cancer, age and number of involved lymph nodes were significant in both models (P  <  0. 05), and in the random survival forest model for death due to cancer progression, tumor size, number of involved lymph nodes, progesterone, estrogen, and family history were the important identified variables. Conclusion: In the presence of competing risks, when the underlying assumptions of cause-specific and subdistribution hazard regression models are not established, the use of random survival forest for competing events data to determine the risk factors affecting survival according to the coordination index and Brier score is more appropriate.

Introduction: Breast cancer is the most prevalent cancer among women, and mastectomy, the surgical treatment for this cancer, affects different aspects of patients’ life. This study aimed to describe women’ s lived experiences of femininity after mastectomy and treatment. Methods: This qualitative study was conducted on 17 breast cancer survivors in Tehran in 2018-2019. The participants, who were selected through snowball sampling, had undergone mastectomy at least 6 months before and were younger than 50 years. Data were collected using in-depth semi-structured interviews and analyzed with the contractual content analysis method. Results: The analysis of patients’ experiences led to the identification of 7 main themes (and 18 subtheme): social life (social isolation, quitting the job or getting a part-time job, and dropping out of school), body image (being asymmetric, being unattractive, and requiring reconstructive surgery), others’ opinions (complaining about how others look at them and concerns of being pitied), marital relationships (fear of abandonment, fear of spouse’ s pity, shame of being nude, and compromised sexual intimacy), reproductive health (premature menopause and possible infertility), perceived support (attending support group meetings and keeping in touch with cured ones), taking responsibilities of household works (inability to do housewife affairs and inability to do the housework). Conclusion: Mastectomy and treatment for breast cancer greatly affect many areas of individual and social life and marital relationships of patients, necessitating the need to develop and establish free support resources by NGOs and highlighting the government’ s role in reducing the psychological and family damage caused by the disease.

Introduction: HER2-enriched subtype of breast cancer has a worse prognosis than luminal subtypes. Recently, the discovery of targeted therapies in other groups of breast cancer has increased patient survival. The aim of this study was to identify genes that affect the overall survival of this group of patients based on a systems biology approach. Methods: Gene expression data and clinical information on 58 patients with HER2-enriched cancer were downloaded from The Cancer Genome Atlas (TCGA). Co-expression modules were identified using the weighted gene co-expression network analysis (WGCNA). The Cox regression was used to determine the modules that had a significant relationship with the overall survival (OS) endpoint. Single-gene survival analysis was performed within the selected module. Finally, functional annotation to explore the significance of genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Results: Of the six identified co-expression modules, two had significantly poor prognoses. Single-gene survival analysis showed that 39% of genes in the selected modules were identified as significant. The genes were mainly related to the biological pathways such as Ubiquitin-mediated proteolysis and RNA degradation. CHAMP1, PPP1R26, PRRC2B, KANSL3, and ANAPC2 were identified as the 5 most important genes associated with reduced OS, in order of significance. Conclusion: The systems biology approach can provide appropriate results relate to patient survival analysis. In this study, some genes were identified to be used as prognostic biomarkers in experimental studies related to the OS in the HER2-enriched subgroup. These genes can be considered potential candidates for therapeutic targets in this group of patients.

Introduction: The use of chemotherapy drugs has side effects, and the use of herbal compounds in the treatment of cancer faces challenges. Nanoparticles, especially liposomes, with appropriate properties in drug delivery, such as slow drug release and low toxicity at the target cell site, can solve some of these problems. Therefore, the aim of the present study was to develop a liposomal system containing Artemisia absinthium extract and to investigate its toxicity against the MCF-7 cell line. Methods: Three liposomal systems containing extracts with different molar percentages of soybean phosphatidylcholine (80% and 60%) along with cholesterol were prepared using the thin-film hydration method. The most suitable formulation was selected according to the loading percentage and release rate. Extract release from the selected formulation, particle size, and zeta potential were investigated. Finally, the toxicity of the extractloaded system, the free extract, and the unloaded system against the MCF-7 cell line was measured. Results: Extract loading, particle size, dispersion index, and zeta potential for the selected formulation are 49. 2%  ±   0. 4%, 121. 9 nm, 0. 129, and − 10. 6 mV. The system showed a slow release at temperatures similar to healthy and cancer cells. Also, the liposome-encapsulated extract was more toxic against MCF-7 cells compared with the free extract, and extract-free liposomes had little toxicity against MCF-7 cells. Conclusion: The liposomal system containing Artemisia absinthium extract has a higher toxicity than the free extract against breast cancer cells, which can be due to the physicochemical properties of the system, including targeted release.

Introduction: Breast cancer is the most important cause of cancer mortality among women, therefore the study of its causative or aggravating factors seems necessary. In this study, the mRNA levels of the PHB2 gene were evaluated in tumor and adjacent non-tumor tissues of 50 women diagnosed with invasive ductal carcinoma of the breast. Methods: RNX-Plus solution was used to isolate total RNA from tumor and adjacent non-tumor tissues of breast cancer patients. Thereafter, total RNA was converted to cDNA using PrimeScript RT reagent kit. The mRNA levels of PHB2 were quantified by qRTPCR and data were analyzed with a paired-samples t test. Furthermore, ROC curve analysis was performed to evaluate the diagnostic capacity of PHB2 expression in breast cancer tumor tissues. TM Results: A significantly lower level of PHB2 mRNA was observed in tumor tissues of breast cancer patients compared with adjacent non-tumor tissues (P<0. 0001). PHB2 mRNA levels showed an approximately 2. 5-fold reduction in tumor tissues compared with normal tissues (P  =  0. 001). Roc cure analysis showed that PHB2 mRNA level can discriminate tumors from non-tumor tissues with 91. 3% specificity and 64. 3% sensitivity (AUC=0. 712, P<0. 001). Conclusion: Downregulation of PHB2 in breast cancer patients shows that its mRNA levels can possibly discriminate tumors from non-tumor tissues.