Global and regional estimates of orphans attributed to maternal cancer mortality in 2020

Almeida M, M.S. Menezes G, dos-Santos-Silva I, Azevedo e Silva G, Teresa Bustamante-Teixeira M, Barreto ML, Vittal Katikireddi S, Leyland AH, Ferreira Campos L, Maria Dias Fernandes de Novaes E, de Almeida Pereira D, Rodrigues Santana E, Rodrigues Gonçalves Zeferino F, Cleide da Silva Dias A, Fernandes FG, Cristina de Oliveira Costa A, M.L. Aquino E. Do social protection programmes affect the burden of breast and cervical cancer? A systematic review

Background

Socioeconomic conditions are strongly associated with breast and cervical cancer incidence and mortality patterns; therefore, social protection programmes (SPPs) might impact these cancers. This study aimed to evaluate the effect of SPPs on breast and cervical cancer outcomes and their risk/protective factors.

Methods

Five databases were searched for articles that assessed participation in PPS and the incidence, survival, mortality (primary outcomes), screening, staging at diagnosis and risk/protective factors (secondary outcomes) for these cancers. Only peer-reviewed quantitative studies of women receiving SPPs compared to eligible women not receiving benefits were included. Independent reviewers selected articles, assessed eligibility, extracted data, and assessed the risk of bias. A harvest plot represents the included studies and shows the direction of effect, sample size and risk of bias.

Findings

Of 17,080 documents retrieved, 43 studies were included in the review. No studies evaluated the primary outcomes. They all examined the relationship between SPPs and screening, as well as risk and protective factors. The harvest plot showed that in lower risk of bias studies, participants of SPPs had lower weight and fertility, were older at sexual debut, and breastfed their infants for longer.

Interpretation

No studies have yet assessed the effect of SPPs on breast and cervical cancer incidence, survival, or mortality; nevertheless, the existing evidence suggests positive impacts on risk and protective factors.

Cervical Cancer: Precursors and Prevention

Cervical cancer, caused due to oncogenic types of human papillomavirus (HPV), is a leading preventable cause of cancer morbidity and mortality globally. Chronic, persistent HPV infection-induced cervical precursor lesions, if left undetected and untreated, can progress to invasive cancer. Cervical cancer screening approaches have evolved from cytology (Papanicolaou test) to highly sensitive HPV-based molecular methods and personalized, risk-stratified, management guidelines. Innovations like self-collection of samples to increase screening access, innovative triage methods to optimize management of screen positives, and scalable and efficacious precancer treatment approaches will be key to further enhance the utility of prevention interventions.

Socioeconomic inequities in care experienced by women with breast cancer in England: An intersectional cross-sectional study

PURPOSE

Guided by the Intersectionality Framework, we examined the differential in breast cancer care experience across population subgroups in England.

METHODS

Secondary data analysis using the 2017/2018 National Cancer Patient Experience Surveys. We used disaggregated descriptive statistics (mean, standard errors, 95% confidence interval) to analyse 26,030 responses from female breast cancer patients to a question relating to overall care experience categorised by age, ethnicity, and sexual orientation in their intersection with social position. We then used logistic regression to investigate the odds (Odds Ratio (OR), 95% confidence intervals) of reporting positive care experience adjusting for patient, clinical, and Trust level factors.

RESULTS

Poorer care experience was predominantly reported by the most deprived younger and minoritised ethnic groups. Statistically significant findings were observed in adjusted multivariable analyses. Compared to patients aged 65-74 years, younger respondents were less likely to rate their care favourably (16-34 years old ORadj. = 0.55 (0.36-0.84). Compared to White British, Asian (ORadj. = 0.51 (0.39-0.66)) and Black African women (ORadj. = 0.53 (0.33-0.88)) were less likely to rate their care favourably. The least affluent respondents were less likely to rate their care favourably (ORadj. = 0.79 (0.64-0.97)).

CONCLUSION

There is evidence of inequity in overall cancer care experience among female breast cancer patients in England, particularly among women living at the specific intersection of age, ethnicity, and socioeconomic position. Future research is necessary to understand the mechanisms underlying breast cancer inequities. Policymakers, commissioners, and providers should consider the existence of multiple forms of marginalisation to inform improvement initiatives targeting patients at higher risk of vulnerability.

Anticancer Therapies Based on Oxidative Damage: Lycium barbarum Inhibits the Proliferation of MCF-7 Cells by Activating Pyroptosis through Endoplasmic Reticulum Stress

Lycium barbarum, commonly recognized as goji berry or wolfberry, is highly appreciated not only for its organoleptic and nutritional properties but also as an important source of bioactive compounds such as polysaccharides, carotenoids, phenolics, and various other non-nutritive compounds. These constituents give it a multitude of health benefits, including antioxidant, anti-inflammatory, and anticancer properties. However, the precise biochemical mechanisms responsible for its anticancer effects remain unclear, and the comprehensive composition of goji berry extracts is often insufficiently explored. This study aimed to investigate the biochemical pathways modulated in breast cancer cells by an ethanolic extract of Lycium barbarum fruit (LBE). Following metabolomic profiling using UHPLC-HRMS/MS, we assessed the antitumoral properties of LBE on different breast cancer cell lines. This investigation revealed that LBE exhibited cytotoxic effects, inducing a pro-oxidant effect that triggered pyroptosis activation through endoplasmic reticulum (ER) stress and subsequent activation of the P-IRE1α/XBP1/NLRP3 axis in MCF-7 cells. In addition, LBE did not display cytotoxicity toward healthy human cells but demonstrated antioxidant properties by neutralizing ROS generated by doxorubicin. These findings underscore the potential of LBE as a highly promising natural extract in cancer therapy.

Mitigating phospholipid peroxidation of macrophages in stress-induced tumor microenvironment by natural ALOX15/PEBP1 complex inhibitors

BACKGROUND

The intricate interactions between chronic psychological stress and susceptibility to breast cancer have been recognized, yet the underlying mechanisms remain unexplored. Danzhi Xiaoyao Powder (DZXY), a traditional Chinese medicine (TCM) formula, has found clinical utility in the treatment of breast cancer. Macrophages, as the predominant immune cell population within the tumor microenvironment (TME), play a pivotal role in orchestrating tumor immunosurveillance. Emerging evidence suggests that lipid oxidation accumulation in TME macrophages, plays a critical role in breast cancer development and progression. However, a comprehensive understanding of the pharmacological mechanisms and active components of DZXY related to its clinical application in the treatment of stress-aggravated breast cancer remains elusive.

PURPOSE

This study sought to explore the plausible regulatory mechanisms and identify the key active components of DZXY contributing to its therapeutic efficacy in the context of breast cancer.

METHODS

Initially, we conducted an investigation into the relationship between the phagocytic capacity of macrophages damaged by psychological stress and phospholipid peroxidation using flow cytometry and LC-MS/MS-based phospholipomics. Subsequently, we evaluated the therapeutic efficacy of DZXY based on the results of the tumor size, tumor weight, the phospholipid peroxidation pathway and phagocytosis of macrophage. Additionally, the target-mediated characterization strategy based on binding of arachidonate 15-lipoxygenase (ALOX15) to phosphatidylethanolamine-binding protein-1 (PEBP1), including molecular docking analysis, microscale thermophoresis (MST) assay, co-immunoprecipitation analysis and activity verification, has been further implemented to reveal the key bio-active components in DZXY. Finally, we evaluated the therapeutic efficacy of isochlorogenic acid C (ICAC) based on the results of tumor size, tumor weight, the phospholipid peroxidation pathway, and macrophage phagocytosis in vivo.

RESULTS

The present study demonstrated that phospholipid peroxides, as determined by LC-MS/MS-based phospholipidomics, triggered in macrophages, which in turn compromised their capacity to eliminate tumor cells through phagocytosis. Furthermore, we elucidate the mechanism behind stress-induced PEBP1 to form a complex with ALOX15, thereby mediating membrane phospholipid peroxidation in macrophages. DZXY, demonstrates potent anti-breast cancer therapeutic effects by disrupting the ALOX15/PEBP1 interaction and inhibiting phospholipid peroxidation, ultimately enhancing macrophages' phagocytic capability towards tumor cells. Notably, ICAC emerged as a promising active component in DZXY, which can inhibit the ALOX15/PEBP1 interaction, thereby mitigating phospholipid peroxidation in macrophages.

CONCLUSION

Collectively, our findings elucidate stress increases the susceptibility of breast cancer by driving lipid peroxidation of macrophages and suggest the ALOX15/PEBP1 complex as a promising intervention target for DZXY.

CerviLearnNet: Advancing cervical cancer diagnosis with reinforcement learning-enhanced convolutional networks

Women tend to face many problems throughout their lives; cervical cancer is one of the most dangerous diseases that they can face, and it has many negative consequences. Regular screening and treatment of precancerous lesions play a vital role in the fight against cervical cancer. It is becoming increasingly common in medical practice to predict the early stages of serious illnesses, such as heart attacks, kidney failure, and cancer, using machine learning-based techniques. To overcome these obstacles, we propose the use of auxiliary modules and a special residual block, to record contextual interactions between object classes and to support the object reference strategy. Unlike the latest state-of-the-art classification method, we create a new architecture called the Reinforcement Learning Cancer Network, "RL-CancerNet", which diagnoses cervical cancer with incredible accuracy. We trained and tested our method on two well-known publicly available datasets, SipaKMeD and Herlev, to assess it and enable comparisons with earlier methods. Cervical cancer images were labeled in this dataset; therefore, they had to be marked manually. Our study shows that, compared to previous approaches for the assignment of classifying cervical cancer as an early cellular change, the proposed approach generates a more reliable and stable image derived from images of datasets of vastly different sizes, indicating that it will be effective for other datasets.

Feasibility of monitoring Global Breast Cancer Initiative Framework key performance indicators in 21 Asian National Cancer Centers Alliance member countries

Background

The Global Breast Cancer Initiative (GBCI) Framework, launched by the World Health Organisation (WHO) in 2023, emphasises assessing, strengthening, and scaling up services for the early detection and management of breast cancer. This study aims to determine the feasibility of monitoring the status of breast cancer control in the 21 Asian National Cancer Centers Alliance (ANCCA) countries based on the three GBCI Framework key performance indicators (KPIs): stage at diagnosis, time to diagnosis, and treatment completion.

Methods

We reviewed published literature on breast cancer control among 21 ANCCA countries from May to July 2023 to establish data availability and compiled the latest descriptive statistics and sources of the indicators using a standardised data collection form. We performed bivariate Pearson's correlation analysis to measure the strength of correlation between stage at diagnosis, mortality and survival rates, and universal health coverage.

Findings

Only 12 (57%) ANCCA member countries published national cancer registry reports on breast cancer age-standardised incidence rate (ASIR) and age-standardised mortality rate (ASMR). Indonesia, Myanmar, and Nepal had provincial data and others relied on WHO's Global Cancer Observatory (GLOBOCAN) estimates. GLOBOCAN data differed from the reported national statistics by 5-10% in Bhutan, Indonesia, Iran, the Republic of Korea, Singapore, and Thailand and >10% in China, India, Malaysia, Mongolia, and Sri Lanka. The proportion of patients diagnosed in stages I and II strongly correlated with the five-year survival rate and with the universal health coverage (UHC) index. Three countries (14%) reported national data with >60% of invasive breast cancer patients diagnosed at stages I and II, and a five-year survival rate of >80%. Over 60% of the ANCCA countries had no published national data on breast cancer staging, the time interval from presentation to diagnosis, and diagnosis to treatment. Five (24%) countries reported data on treatment completion. The definition of delayed diagnosis and treatment completion varied across countries.

Interpretation

GBCI's Pillar 1 KPI correlates strongly with five-year survival rate and with the UHC index. Most ANCCA countries lacked national data on cancer staging, timely diagnosis, and treatment completion KPIs. While institutional-level data were available in some countries, they may not represent the nationwide status. Strengthening cancer surveillance is crucial for effective breast cancer control. The GBCI Framework indicators warrant more detailed definitions for standardised data collection. Surrogate indicators which are measurable and manageable in country-specific settings, could be considered for monitoring GBCI indicators. Ensuring UHC and addressing health inequalities are essential to early diagnosis and treatment of breast cancer.

Funding

Funding for this research article's processing fee (APC) will be provided by the affiliated institution to support the open-access publication of this work. The funding body is not involved in the study design; collection, management, analysis and interpretation of data; or the decision to submit for publication. The funding body will be informed of any planned publications, and documentation provided.

Enhancing Breast Cancer Detection and Classification Using Advanced Multi-Model Features and Ensemble Machine Learning Techniques

Breast cancer (BC) is the most common cancer among women, making it essential to have an accurate and dependable system for diagnosing benign or malignant tumors. It is essential to detect this cancer early in order to inform subsequent treatments. Currently, fine needle aspiration (FNA) cytology and machine learning (ML) models can be used to detect and diagnose this cancer more accurately. Consequently, an effective and dependable approach needs to be developed to enhance the clinical capacity to diagnose this illness. This study aims to detect and divide BC into two categories using the Wisconsin Diagnostic Breast Cancer (WDBC) benchmark feature set and to select the fewest features to attain the highest accuracy. To this end, this study explores automated BC prediction using multi-model features and ensemble machine learning (EML) techniques. To achieve this, we propose an advanced ensemble technique, which incorporates voting, bagging, stacking, and boosting as combination techniques for the classifier in the proposed EML methods to distinguish benign breast tumors from malignant cancers. In the feature extraction process, we suggest a recursive feature elimination technique to find the most important features of the WDBC that are pertinent to BC detection and classification. Furthermore, we conducted cross-validation experiments, and the comparative results demonstrated that our method can effectively enhance classification performance and attain the highest value in six evaluation metrics, including precision, sensitivity, area under the curve (AUC), specificity, accuracy, and F1-score. Overall, the stacking model achieved the best average accuracy, at 99.89%, and its sensitivity, specificity, F1-score, precision, and AUC/ROC were 1.00%, 0.999%, 1.00%, 1.00%, and 1.00%, respectively, thus generating excellent results. The findings of this study can be used to establish a reliable clinical detection system, enabling experts to make more precise and operative decisions in the future. Additionally, the proposed technology might be used to detect a variety of cancers.

The case for prioritizing malignant hematology services in low- and middle-income countries

A clear case for can be made for prioritizing malignant hematology services in low- and middle-income countries based on large public health burden, convincing demonstrations of cure and control, innovation opportunities with likely worldwide implications, and sizable returns on investment for health systems and societies. We must now ensure that need and opportunity are matched by commensurate levels of investment and attention.

Clinicopathological profile of breast cancer from Chhattisgarh India: A single-center hospital-based study

Background

Global breast cancer incidence is increasing at an annual rate of 3·1%. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%). However, the data from different parts of India are still lacking and the study was conducted to assess the burden of disease at tertiary referral centers in central India.

Material and Methods

Retrospective record analysis (June 2013-June 2017) of data from outdoor clinics and pathology reports. The patients aged <15 yrs, nonresidence of Chhattisgarh, and diagnosed outside the study period were excluded. The triple assessment was used to diagnose all breast lumps (sensitivity 99%).

Results

Eighty patients were diagnosed having breast carcinoma. The mean age for breast cancer was 39 ± 3.028 years (ranged 31-50 years). Twenty patients had locally advanced breast carcinoma. The predominant religion was Hindu 55.00%. The referral pathway to seek medical care for breast cancer was via a gynecologist in 40% (32/80). Familial breast cancers were in 0.03% (3/80) of patients. None breast cancer patients have previous histology-proven benign breast disease. The mean size of the breast cancer lump was 3.56 cm (ranged 1.0-11.0 cm). Overlying skin ulceration (n = 2), skin infiltration/peau-d'- orange (n = 2), skin tethering (n = 4), and bloody nipple discharge were found in one patient. Breast cancer was diagnosed during lactation (postnatal period) in one patient. The maximum number of patients have tumor size >5 cm (72.6%). Immunohistochemistry and pathological analysis was done on core biopsy (n = 20) and surgical procedure (n = 60). Modified radical mastectomy was done in 52, breast conservative surgery with Sentinal Lymph node biopsy and axillary lymph node dissection in 6, and toilet mastectomy in two patients. The predominant tumors were solid (n = 79/80), with both solid and cystic types (1/80). The solid and cystic lesion on FNAC was of C3b type, and an excision biopsy revealed medullary carcinoma of the breast. Invasive ductal carcinoma-no special type (IDC-NST) was observed to be the most common histopathologic type (n = 70/80), followed by medullary carcinoma (n = 2), metaplastic carcinoma (n = 1), papillary carcinoma (n = 4), Paget disease with DCIS (n = 1), mucinous carcinoma (n = 1), invasive lobular carcinoma (n = 1). One male patient with breast cancer and two female patient having bilateral breast cancer also have IDC-NST.Scarff Bloom Richardson Grade was predominantly graded 2 in 46.25% (37/80) of breast cancer patients (Grade 1 = 9, Grade 2 = 37, Grade 3 = 34). Lymphovascular (LVI) and perineural invasion (PNI) were predominantly without LVI and PVI. (Lymphovascular present and perineural invasion present = 4, Lymphovascular present and perineural invasion absent = 32, Lymphovascular absent and perineural invasion absent = 42, Lymphovascular absent and perineural invasion present = 2). Histological examination of axillary lymph nodes showed the presence of malignant cells in all. Triple-negative breast carcinoma was 26.58% (21/79). Most breast cancer presented at stage II A = 37.5% (30/80) and II B = 28.7% (23/80) of the AJCC staging system.

Conclusion

The clinico-epidemio and histological profile of breast cancer in Chhattisgarh is similar to other parts of India. Scarff Bloom Richardson Grade was predominantly grade 2 in 46.25% (37/80) contrary to Grade III (70%) in other series from India.

Features and applications of Ehrlich tumor model in cancer studies: a literature review

Background and Objective

Breast cancer is the most prevalent cancer worldwide, responsible for a large number of deaths, especially among women. Therapeutic options for breast cancer include surgery, radiotherapy, chemotherapy, hormone therapy, and immunotherapy, but further studies of the pathogenesis of this disease and new treatments are still needed. In vitro and in vivo cancer models are important research tools. Murine Ehrlich tumors are one of these models, especially for hormone-positive breast cancer. The present narrative review discusses characteristics of the Ehrlich tumor model, laboratory manipulations of Ehrlich cells (ECs), and applications in pharmacological, pathological, and translational studies.

Methods

This review was based on scientific articles, books, and theses on Ehrlich tumors. We searched the PubMed, SciELO, Google Scholar, Google, and Clarivate databases.

Key Content and Findings

Hormone-positive ECs produce solid Ehrlich carcinoma (SEC) and ascitic Ehrlich carcinoma (AEC), with different features and applications. The presence of SEC or AEC induces systemic and immunological alterations that are similar to cancer in humans, what makes this model applicable to different studies in the cancer field.

Conclusions

Ehrlich tumors are a relevant tool for improving our understanding of the pathogenesis of breast cancer and investigating the tumor microenvironment, side effects of therapies, and new treatment options. Despite some limitations, such as the absence of an invasive phenotype to produce metastasis, both SEC and AEC are relevant in preclinical and translational studies of breast cancer.

Fabrication and Validation of a 3D Portable PEGDA Microfluidic Chip for Visual Colorimetric Detection of Captured Breast Cancer Cells

To guide therapeutic strategies and to monitor the state changes in the disease, a low-cost, portable, and easily fabricated microfluidic-chip-integrated three-dimensional (3D) microchamber was designed for capturing and analyzing breast cancer cells. Optimally, a colorimetric sensor array was integrated into a microfluidic chip to discriminate the metabolites of the cells. The ultraviolet polymerization characteristic of poly(ethylene glycol) diacrylate (PEGDA) hydrogel was utilized to rapidly fabricate a three-layer hydrogel microfluidic chip with the designed structure under noninvasive 365 nm laser irradiation. 2-Hydroxyethyl methacrylate (HEMA) was added to the prepolymer in order to increase the adhesive capacity of the microchip's surface for capturing cells. 1-Vinyl-2-pyrrolidone (NVP) was designed to improve the toughness and reduce the swelling capacity of the hydrogel composite. A non-toxic 3D hydrogel microarray chip (60 mm × 20 mm × 3 mm) with low immunogenicity and high hydrophilicity was created to simulate the real physiological microenvironment of breast tissue. The crisscross channels were designed to ensure homogeneous seeding density. This hydrogel material displayed excellent biocompatibility and tunable physical properties compared with traditional microfluidic chip materials and can be directly processed to obtain the most desirable microstructure. The feasibility of using a PEGDA hydrogel microfluidic chip for the real-time online detection of breast cancer cells' metabolism was confirmed using a specifically designed colorimetric sensor array with 16 kinds of porphyrin, porphyrin derivatives, and indicator dyes. The results of the principal component analysis (PCA), the hierarchical cluster analysis (HCA), and the linear discriminant analysis (LDA) suggest that the metabolic liquids of different breast cells can be easily distinguished with the developed PEGDA hydrogel microfluidic chip. The PEGDA hydrogel microfluidic chip has potential practicable applicability in distinguishing normal and cancerous breast cells.