Female Cancer Mortality Research Articles

Evaluation of urban–rural difference in breast cancer mortality among Chinese women during 1987–2021: A hierarchical age-period-cohort analysis

BackgroundBreast cancer mortality varies in urban and rural areas in China. Studies have reported urban–rural difference across time period, however, the evaluation on urban–rural differences in age and birth cohort effects is limited. Our aim was to quantitatively assess urban–rural disparities in age, period and cohort effects in breast cancer mortality in China. MethodsWe collected age-specific breast cancer mortality rates for urban and rural females aged 20–84 years from 1987 to 2021. Hierarchical age-period-cohort (HAPC) models were used to evaluate the effect of area (urban, rural) on breast cancer mortality and investigate urban–rural differences in age, time period and birth cohort effects. ResultsWe found a significant area (urban, rural) effect on breast cancer mortality in that rural females had a lower mortality risk than urban females [−0.25 (95 % confidence interval (CI): −0.32, −0.17)]. Age trajectories of mortality based on the HAPC model showed nonlinear trends with adjustment for area variable. The urban–rural difference in age effect appeared to be divergent with age, and urban women had higher mortality risk in the senior age group. The urban–rural difference in birth cohort effect indicated a reversal around the birth cohort group of 1962–1966, after which rural females had a higher mortality risk than urban females. ConclusionThe area (urban, rural) could affect breast cancer mortality among women, and the effect of urban–rural difference varies with age and birth cohort. To promote the health of urban and rural females, the gap between urban and rural areas should be shorten.

Factors Associated with Women's Awareness of Early Detection of Cervical Cancer

Background: About 70% of women with cervical cancer present to health services at an advanced stage, making it difficult to treat and leading to high rates of female cancer mortality. Women's awareness of early detection of cervical cancer remains a problem. Objective: To determine the factors associated with women's awareness of early detection of cervical cancer. Methods: This type of research is a quantitative study with a cross-sectional design. The population in the study were all mothers in Padang City. The sample in this study amounted to 320 with simple random sampling technique. The analysis method used was univariate analysis to see the frequency distribution, bivariate analysis was performed to evaluate the relationship using the chi-square test with a confidence level of 95% (α = 0.05), and multivariate logistic regression analysis to identify independent variables that had the most significant effect on the dependent variable. Data were analyzed using a computer. Results: The study showed that cadre support, health worker support and motivation were factors associated with women's awareness of early detection of cervical cancer. Health worker support was the factor most associated with early detection of cervical cancer. Conclusion: Health worker support is the most important factor in sensitizing women to do cervical cancer early detection.

To study the utility of COX-2 as immunohistochemical prognostic marker in comparison to various histopathological parameters and TNM staging in breast carcinoma: an observational, cross-sectional study protocol.

Breast cancer is the most prevalent cancer among women worldwide and is a well-known cause for cancer mortality in females. COX-2 (cyclooxygenase) plays a vital role in development of some human cancers such as lung, colon and breast. It is a potent enzyme that is important for the conversion of arachidonic acid into prostaglandins. These prostaglandins mediate cellular proliferation, apoptosis and angiogenesis which contributes to carcinogenesis. Overexpression of COX-2 has been detected in several malignancies including breast cancer. COX-2 overexpression is regarded as a poor prognostic marker of breast cancer.The present study will aim to study the immunohistochemical expression of COX-2 in breast cancer and compare it with known histopathological parameters thus assessing its prognostic value. This will be an observational study conducted in the Department of Pathology, JNMC, Wardha (Sawangi). Radical mastectomy specimens will be studied for COX-2 expression by immunohistochemistry in patients diagnosed with breast carcinoma. COX-2 expression will be quantified as immunohistochemical score and results will be correlated with various histopathological parameters. The expected result of our study will suggest an association of COX-2 expression to the factors associated with poor prognosis in breast carcinoma. A positive correlation is expected between larger tumor size, positive lymph node status, higher T stage and N stage and lymphovascular invasion. Conclusions will be drawn from the obtained results of the immunohistochemical study by using COX-2- for detection of overexpression of COX-2 when evaluated with TNM staging, histological grading and molecular types of breast cancer.

Histopathology-based breast cancer prediction using deep learning methods for healthcare applications.

Breast cancer (BC) is the leading cause of female cancer mortality and is a type of cancer that is a major threat to women's health. Deep learning methods have been used extensively in many medical domains recently, especially in detection and classification applications. Studying histological images for the automatic diagnosis of BC is important for patients and their prognosis. Owing to the complication and variety of histology images, manual examination can be difficult and susceptible to errors and thus needs the services of experienced pathologists. Therefore, publicly accessible datasets called BreakHis and invasive ductal carcinoma (IDC) are used in this study to analyze histopathological images of BC. Next, using super-resolution generative adversarial networks (SRGANs), which create high-resolution images from low-quality images, the gathered images from BreakHis and IDC are pre-processed to provide useful results in the prediction stage. The components of conventional generative adversarial network (GAN) loss functions and effective sub-pixel nets were combined to create the concept of SRGAN. Next, the high-quality images are sent to the data augmentation stage, where new data points are created by making small adjustments to the dataset using rotation, random cropping, mirroring, and color-shifting. Next, patch-based feature extraction using Inception V3 and Resnet-50 (PFE-INC-RES) is employed to extract the features from the augmentation. After the features have been extracted, the next step involves processing them and applying transductive long short-term memory (TLSTM) to improve classification accuracy by decreasing the number of false positives. The results of suggested PFE-INC-RES is evaluated using existing methods on the BreakHis dataset, with respect to accuracy (99.84%), specificity (99.71%), sensitivity (99.78%), and F1-score (99.80%), while the suggested PFE-INC-RES performed better in the IDC dataset based on F1-score (99.08%), accuracy (99.79%), specificity (98.97%), and sensitivity (99.17%).

Breast Cancer Awareness and Screening Perceptions of Women in Yerevan, Armenia.

Breast cancer is the leading cause of female cancer mortality in Armenia. The government is considering covering breast cancer screening, but prevailing attitudes towards it are unknown. This cross-sectional study assessed Armenian women's awareness and perceptions of breast cancer screening. We administered a validated telephone survey to women ages 35-65 registered in Yerevan's polyclinic system between 2019-2021, assessing sociodemographic characteristics, breast cancer exposure and screening attitudes, using an adapted Champion's Health Belief Model Scale (CHBMS). We analyzed the association, unadjusted and adjusted, between sociodemographic characteristics, screening exposure, and CHBMS scores. 170 women completed surveys. Most (82.9%) were aware of screening, 48.5% knew someone with breast cancer, but only 42.5% had undergone screening, predominantly without their physician's recommendation (63.2%). Despite elevated awareness, 76.2% had never discussed screening with their provider. Barriers included cost and mistreatment concerns. Education consistently predicted prior screening and most CHBMS scores. Armenian women are highly exposed to breast cancer, but knowledge and prior screening primarily emanate from non-physician sources. Results highlighted the influence of education, patient-provider relationships, and healthcare costs, underscoring the importance of multi-level interventions.

A gap analysis of UK biobank publications reveals SNPs associated with intrinsic subtypes of breast cancer

Breast cancer is a multifaceted disease and a leading cause of cancer morbidity and mortality in females across the globe. In 2020 alone, 2.3 million women were diagnosed and 685,000 died of breast cancer worldwide. With the number of diagnoses projected to increase to 3 million per year by 2040 it is essential that new methods of detection and disease stratification are sought to decrease this global cancer burden.Although significant improvements have been made in breast cancer diagnosis and treatment, the prognosis of breast cancer remains poor in some patient groups (i.e. triple negative breast cancer), necessitating research into better patient stratification, diagnosis and drug discovery. The UK Biobank, a comprehensive biomedical and epidemiological database with a wide variety of multiomics data (genomics, proteomics, metabolomics) offers huge potential to uncover groundbreaking discoveries in breast cancer research leading to improved patient stratification. Combining genomic, proteomic, and metabolic profiles of breast cancer in combination with histological classification, can aid treatment decisions through accurate diagnosis and prognosis prediction of tumor behaviour.Here, we systematically reviewed PubMed publications reporting the analysis of UK Biobank data in breast cancer research. Our analysis of UK Biobank studies in the past five years identified 125 publications, of which 76 focussed on genomic data analysis. Interestingly, only two studies reported the analysis of metabolomics and proteomics data, with none performing multiomics analysis of breast cancer. A meta-analysis of the 76 publications identified 2870 genetic variants associated with breast cancer across 445 genes. Subtype analysis revealed differential genetic alteration in 13 of the 445 genes and the identification of 59 well-established breast cancer genes. in differential pathways. Pathway interaction analyses illuminated their involvement in general cancer biomolecular pathways (e.g. DNA damage repair, Gene expression). While our meta-analysis only measured genetic differences in breast cancer due to current usage of UK Biobank data, minimal multi-omics analyses have been performed and the potential for harnessing multi-omics strategies within the UK Biobank cohort holds promise for unravelling the biological signatures of distinct breast cancer subtypes further in the future.

Association between consumption of small fish and all-cause mortality among Japanese: the Japan Multi-Institutional Collaborative Cohort Study.

Although small fish are an important source of micronutrients, the relationship between their intake and mortality remains unclear. This study aimed to clarify the association between intake of small fish and all-cause and cause-specific mortality. We used the data from a cohort study in Japan. The frequency of the intake of small fish was assessed using a validated FFQ. The hazard ratio (HR) and 95 % confidence interval (CI) for all-cause and cause-specific mortality according to the frequency of the intake of small fish by sex were estimated using a Cox proportional hazard model with adjustments for covariates. The Japan Multi-Institutional Collaborative Cohort Study. A total of 80 802 participants (34 555 males and 46 247 females), aged 35-69 years. During a mean follow-up of 9·0 years, we identified 2482 deaths including 1495 cancer-related deaths. The intake of small fish was statistically significantly and inversely associated with the risk of all-cause and cancer mortality in females. The multivariable-adjusted HR (95 % CI) in females for all-cause mortality according to the intake were 0·68 (0·55, 0·85) for intakes 1-3 times/month, 0·72 (0·57, 0·90) for 1-2 times/week and 0·69 (0·54, 0·88) for ≥ 3 times/week, compared with the rare intake. The corresponding HR (95 % CI) in females for cancer mortality were 0·72 (0·54, 0·96), 0·71 (0·53, 0·96) and 0·64 (0·46, 0·89), respectively. No statistically significant association was observed in males. Intake of small fish may reduce the risk of all-cause and cancer mortality in Japanese females.

Pancreatic cancer mortality in South Africa: A case-control study

Background. There are variations in the numbers of pancreatic cancer deaths reported annually in South Africa (SA). Since pancreatic cancer deaths in SA from 1997 to 2016, the number of cases has hugely increased, and reached 23 581 in both sexes. Sex differences are likely to contribute to the variations in the strength of associations between the risk factors and pancreatic cancer mortality. Objective. To identify factors associated with an increased risk of pancreatic cancer mortality in SA. Methods. A matched case-control study with 1:1 matching was conducted using data collected by Statistics SA from 1997 to 2016. Controls were randomly selected to be as similar as possible to the cases, and matched by age, sex and year of death. Conditional logistic regression was used to identify factors associated with pancreatic cancer mortality. Results. This case-control study comprised a final selection of 23 581 cases (12 171 males and 11 410 females) and 23 581 controls (12 171 males and 11 410 females). A significantly increased risk of pancreatic cancer mortality was observed among males who were managers (odds ratio (OR) 2.99; 95% confidence interval (CI) 1.36 - 6.60; p=0.006) and craft and related trade workers (OR 1.89; 95% CI 1.14 - 3.14; p=0.013). Elevated risks of pancreatic cancer mortality were also found among females who were managers (OR 6.13; 95% CI 1.32 - 28.52; p=0.021), professionals (OR 2.12; 95% CI 1.24 - 3.63; p=0.006), clerical support workers (OR 3.78; 95% CI 1.79 - 7.98; p=0.001) and elementary occupation workers (OR 1.41; 95% CI 0.99 - 2.00; p=0.059). Smoking was significantly associated with pancreatic cancer mortality in females (OR 1.36; 95% CI 1.02 - 1.82; p=0.039). Working in several occupations was associated with an increased risk of pancreatic cancer mortality in males (OR 1.31; 95% CI 1.01 - 1.71; p=0.045) and females (OR 1.66; 95% CI 1.30 - 2.12; p<0.001). Conclusion. Smoking and certain occupations increased the risk of pancreatic cancer mortality. Further research is needed to evaluate the associations between other extrinsic and intrinsic factors and pancreatic cancer mortality.

Correlation between Risk Factors and Protein Expression of ER, PR, and HER-2 in Breast Cancer Patients: A Population-Based Study in Makassar Indonesia

Background: Breast cancer is a condition characterized by abnormal and uncontrollable growth of cells in breast tissue. According to Global Cancer Statistics 2020, it ranks as the leading cause of female cancer mortality. The disease has four subtypes defined by protein expression, namely Luminal A (ER/PR (+), HER2 (-)), Luminal B (ER/PR (+), HER2 (+)), triple-negative/basal-like (ER, PR, HER2 (-)), and HER2-enriched (ER (-), PR (-), HER2 (+)), each with distinct characteristics influenced by various risk factors. Therefore, this study aimed to explore the correlation between breast cancer risk factors and protein expression of ER, PR, and HER2. Methods: The cross-sectional analytical study was conducted in Makassar, Indonesia, using secondary data from 259 breast cancer patients. Information on ER, PR, HER2 expression, and patient risk factors such as age, history of hormonal contraceptive use, and family history of breast cancer were extracted from medical records and subjected to statistical analysis using the Chi-square test, with significance set at p < 0.05. Results: The results showed that there was a significant correlation between age ≥ 40 years and the expression of ER, PR, and HER2 (p < 0.005). However, no significant correlations were observed between family history and hormonal contraceptive use with ER, PR, and HER2 expression. Conclusions: This study established a meaningful correlation between risk factors of age and breast cancer subtypes based on ER, PR, and HER2 expression.

To study the utility of COX-2 as immunohistochemical prognostic marker in comparison to various histopathological parameters and TNM staging in breast carcinoma: an observational, cross-sectional study protocol

Background: Breast cancer is the most prevalent cancer among women worldwide and is a well-known cause for cancer mortality in females. COX-2 (cyclooxygenase) plays a vital role in development of some human cancers such as lung, colon and breast. It is a potent enzyme that is important for the conversion of arachidonic acid into prostaglandins. These prostaglandins mediate cellular proliferation, apoptosis and angiogenesis which contributes to carcinogenesis. Overexpression of COX-2 has been detected in several malignancies including breast cancer. COX-2 overexpression is regarded as a poor prognostic marker of breast cancer. The present study will aim to study the immunohistochemical expression of COX-2 in breast cancer and compare it with known histopathological parameters thus assessing its prognostic value. Methods: This will be an observational study conducted in the Department of Pathology, JNMC, Wardha (Sawangi). Radical mastectomy specimens will be studied for COX-2 expression by immunohistochemistry in patients diagnosed with breast carcinoma. COX-2 expression will be quantified as immunohistochemical score and results will be correlated with various histopathological parameters. Results: The expected result of our study will suggest an association of COX-2 expression to the factors associated with poor prognosis in breast carcinoma. A positive correlation is expected between larger tumor size, positive lymph node status, higher T stage and N stage and lymphovascular invasion. Conclusions: Conclusions will be drawn from the obtained results of the immunohistochemical study by using COX-2- for detection of overexpression of COX-2 when evaluated with TNM staging, histological grading and molecular types of breast cancer.

SMC3 epigenetic silencing regulates Rab27a expression and drives pancreatic cancer progression

BackgroundPancreatic ductal adenocarcinoma (PDAC) is expected to soon surpass colorectal cancer as a leading cause of cancer mortality in both males and females in the US, only lagging behind lung cancer. The lethality of PDAC is driven by late diagnosis and inefficient therapies. The complex biology of PDAC involves various cellular components, including exosomes that carry molecular information between cells. Thus, recipient cells can be reprogrammed, impacting tumorigenesis. Rab27a is a GTPase responsible for the last step of exosomes biogenesis. Hence, dissecting the mechanisms that regulate the expression of Rab27a and that control exosomes biogenesis can provide fundamental insights into the molecular underpinnings regulating PDAC progression.MethodsTo assess the mechanism that regulates Rab27a expression in PDAC, we used PDAC cell lines. The biological significance of these findings was validated in PDAC genetically engineered mouse models (GEMMs) and human samples.ResultsIn this work we demonstrate in human PDAC samples and GEMMs that Rab27a expression decreases throughout the development of the disease, and that Rab27a knockout promotes disease progression. What is more, we demonstrate that Rab27a expression is epigenetically regulated in PDAC. Treatment with demethylating agents increases Rab27a expression specifically in human PDAC cell lines. We found that SMC3, a component of the cohesin complex, regulates Rab27a expression in PDAC. SMC3 methylation is present in human PDAC specimens and treatment with demethylating agents increases SMC3 expression in human PDAC cell lines. Most importantly, high levels of SMC3 methylation are associated with a worse prognosis in PDAC. Mechanistically, we identified an enhancer region within the Rab27a gene that recruits SMC3, and modulates Rab27a expression.ConclusionOverall, we dissected a mechanism that regulates Rab27a expression during PDAC progression and impacts disease prognosis.

Abstract 2154: Differential expression of the PI3K-Akt signaling pathway pre and post chemotherapy in relation to hormonal profile in African women

Abstract Background: Breast cancer (BC) is the most common cancer in US and Canadian women. Despite therapeutic advances, it remains the second leading cause of female cancer mortality. Aggressive breast cancers are represented as a clinical (inflammatory BC or locally advanced BC) or as a biopathological form (triple negative BC or HER2+ BC). These aggressive forms have a poor prognosis. In the US, African Americans have a 41% higher BC death rate than Caucasians women. As observed in the US, in African Gabon women, a more aggressive and cases of triple negative BC are found. Aggressive BC are mainly associated with African women. At this stage, chemotherapy is the main therapeutic treatment but chemoresistance is the major hurdle. One solution to chemoresistance would be to found candidates biomarkers that predict therapeutic responses. The goal of our study was to establish an RNA signature that could differentiate chemosensitive from chemoresistant patients in BC African women. Methods: RNA sequencing technique was used to establish expression profiling in African women before and after chemotherapy using three groups of aggressive BC patients treated with: Doxorubicin, 5-Fluorouracil or Navelbine. We first isolated RNA from tissues fixed in paraffin and sequenced it via the Nextseq 2000 system. A tximport (v1.20.0) and DESeq2 (v1.26.0) analysis then identified significantly and differentially expressed transcripts between the different groups. Results: In the doxorubicin group, post-chemotherapy patients had 962 significant genes out of the 46461 transcripts compared to pre-chemotherapy patients. The post-chemotherapy 5-FluoroUracil group had 3723 significant genes out of 43821 transcripts compared to pre-chemotherapy Fluorouracil group and the post-chemotherapy Navelbine group had 980 significant genes out of 44689 transcripts compared to pre-chemotherapy Navelbine group. Relevant overexpressed genes were selected for validation by immunohistochemistry (IHC). We found an enrichment in the KEGG and PI-3K/Akt pathways and observed that Akt downstream substrates were express differently between pre- and post-chemotherapy patients. Conclusion: Our study suggests that some of the overexpressed post chemotherapy genes could serve as biomarkers of aggressive BC. This is the first study in Canada to investigate Doxorubicin, Flurouracile and Navelbine chemoresistance-related genes in African women and could lead to the discovery of diagnostic markers and therapeutic targets. Citation Format: Hurette Junie Chansi Kengni. Differential expression of the PI3K-Akt signaling pathway pre and post chemotherapy in relation to hormonal profile in African women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2154.

FokI polymorphism of Vitamin D receptor gene and deficiency of serum Vitamin D increases the risk of breast cancer in North Indian women.

Breast cancer is a leading cause of cancer morbidity and mortality in females. Decreased availability of Vitamin D within breast cells, contributed by deficiency of serum Vitamin D and polymorphisms of Vitamin D receptor genes are possible risk factors for breast cancer. To study the association of FokI polymorphism of the Vitamin D Receptor gene with breast cancer in females and to study the levels of Vitamin D in breast cancer patients. VDR gene FokI genotyping was done by PCR-RFLP method and levels of serum Vitamin D were estimated by ELISA. Statistical analysis was done with SPSS v.21. Serum Vitamin D was significantly lower in newly diagnosed breast cancer patients than in healthy controls (P = 0.016). Females with serum Vitamin D levels in the highest quartile have a lesser risk of breast cancer than those with serum Vitamin D levels in the lowest quartile (O. R = 2.4421, C.I = 1.09-5.45, P = 0.029). The risk of developing breast cancer is higher in women with the polymorphic T allele for VDR FokI genotype (CT/TT) than those homozygous for the wild C allele (CC). (O.R. = 4.295, C.I. = 2.2110-8.3451, p-value = <0.0001). Levels of serum Vitamin D were significantly higher (p < 0.001) in ER + patients and significantly low in those presenting with higher stages of cancer (p = 0.009). FokI polymorphism of VDR gene and low circulating Vitamin D levels increase the risk of developing breast cancer in North Indian females. Serum Vitamin D can be used as a prognostic factor.

Diagnostic Dilemma in a Rare Jaw Metastasis: A Case Report

Malignant tumors that have metastasized to the oral and maxillofacial region from distant sites account for only 1% of all malignancies of the jaw. These metastasize most often to the mandibular molar region. The commonest primary sources of metastatic tumors found in the oral and maxillofacial region are the lung, kidney and prostate gland for the males, and the breast, genital organs and kidneys for females. Uterine cervix cancer is the second most common female cancer and the third most common cause of female cancer mortality. The tumor spreads into the surrounding tissues by direct infiltration, but hematogenous dissemination is relatively unusual and the involvement of oral and maxillofacial region is extremely rare in gynecological cancer. Here a case of a 45-year-old woman is presented, who had a lesion of sunburst type appearance radiographically and poorly differentiated squamous cell carcinoma histologically involving the maxillofacial region, which metastasized from uterus cervix.

Association of circadian BMAL1 gene expression and its polymorphism and risk of breast cancer in females

ObjectiveBreast cancer as the principal reason for cancer mortality in females. Any abnormalities in the circadian might increase breast cancer progression. The aim was to examine the association between a genetic variant in the circadian gene BMAL1 and the chance of developing breast cancer, as well as the effect of gene expression of the circadian gene on breast cancer tissue. Patients and methodsThis study conducted on 100 subjects: 50 breast cancer cases and 50 age-matched healthy women. All subjects had a complete medical history, general clinical examination, mammography, and laboratory investigations, including serum CEA and serum CA15-3, and detection of circadian BMAL1 (rs2279287) genotypes and its MRNA expression by real-time PCR. ResultsSerum CA15.3 levels were greater in breast cancer cases than in controls. The frequency of T/C and T/T genotypes is considerably greater in breast cancer patients. BMAL1 expression was higher in breast cancer tissues with a TC/TT genetic variance. The expression of the circadian gene BMAL1 was found to be significantly related to tumor status, relapse status, and BMAL1 genotypes. BMAL1 genotypes were associated with pathological stage and grade. Women with the T/C genotype had a greater risk of ER-/PR-tumors than ER+/PR-tumors. ConclusionCircadian BMAL1 gene was more common TC/TT genotypes than CC genotypes. BMAL1 expression was lower in breast cancer tissues with a TC/TT genetic variance, so BMAL1 may have a role in the development of breast cancer.

Mammogram Image Enhancement Techniques for Online Breast Cancer Detection and Diagnosis.

Breast cancer is the type of cancer with the highest incidence and global mortality of female cancers. Thus, the adaptation of modern technologies that assist in medical diagnosis in order to accelerate, automate and reduce the subjectivity of this process are of paramount importance for an efficient treatment. Therefore, this work aims to propose a robust platform to compare and evaluate the proposed strategies for improving breast ultrasound images and compare them with state-of-the-art techniques by classifying them as benign, malignant and normal. Investigations were performed on a dataset containing a total of 780 images of tumor-affected persons, divided into benign, malignant and normal. A data augmentation technique was used to scale up the corpus of images available in the chosen dataset. For this, novel image enhancement techniques were used and the Multilayer Perceptrons, k-Nearest Neighbor and Support Vector Machines algorithms were used for classification. From the promising outcomes of the conducted experiments, it was observed that the bilateral algorithm together with the SVM classifier achieved the best result for the classification of breast cancer, with an overall accuracy of 96.69% and an accuracy for the detection of malignant nodules of 95.11%. Therefore, it was found that the application of image enhancement methods can help in the detection of breast cancer at a much earlier stage with better accuracy in detection.

Epidemiological trends of female breast and gynecologic cancers in adolescents and young adults in China from 1990 to 2019: Results from the Global Burden of Disease Study 2019.

BackgroundResearch on the incidence, mortality, and disability-adjusted life years (DALYs) of female breast and gynecologic cancers (FeBGCs) and the relevant risk factors for adolescents and young adults (AYAs) are valuable for policy-making in China. We aimed to estimate the incidence, deaths, and DALYs and predict epidemiological trends of FeBGCs among AYAs in China between 1990 and 2019.MethodsData from the 2019 Global Burden of Disease (GBD) study between 1990 and 2019 in 195 countries and territories were retrieved. Data about the number of FeBGC incident cases, deaths, DALYs, age-standardized rates (ASRs), and estimated annual percentage changes (EAPCs) were extracted. A comparative risk assessment framework was performed to estimate the risk factors attributable to breast cancer deaths and DALYs, and autoregressive integrated moving average (ARIMA) models were fitted for time-series analysis to predict female cancer morbidity and mortality among Chinese AYAs until 2030.ResultsIn 2019, there are 61,038 incidence cases, 8,944 deaths, and 529,380 DALYs of FeBGCs among the AYAs in China, respectively. The estimated annual percentage change (EAPC) values were positive scores (>0) in ASIRs and negative scores (<0) in ASMR and ASDR. Furthermore, in 2030, the incidence rate of FeBGCs would grow to 30.49 per 100,000 in China, while the mortality rate would maintain a steady state. Of the deaths and DALYs, diet high in red meat was the greatest contributor to breast cancer, while a high body mass index (BMI) was the greatest contributor to cervical, ovarian, and uterine cancers.ConclusionThe increasing Chinese FeBGC burden is mainly observed in AYAs and non-red meat diet, and the control of body weight could reduce FeBGC burden in China.

A genomic and transcriptomic study toward breast cancer.

Background: Breast carcinoma is well recognized to be having the highest global occurrence rate among all cancers, being the leading cause of cancer mortality in females. The aim of this study was to elucidate breast cancer at the genomic and transcriptomic levels in different subtypes so that we can develop more personalized treatments and precision medicine to obtain better outcomes. Method: In this study, an expression profiling dataset downloaded from the Gene Expression Omnibus database, GSE45827, was re-analyzed to compare the expression profiles of breast cancer samples in the different subtypes. Using the GEO2R tool, different expression genes were identified. Using the STRING online tool, the protein–protein interaction networks were conducted. Using the Cytoscape software, we found modules, seed genes, and hub genes and performed pathway enrichment analysis. The Kaplan–Meier plotter was used to analyze the overall survival. MicroRNAs and transcription factors targeted different expression genes and were predicted by the Enrichr web server. Result: The analysis of these elements implied that the carcinogenesis and development of triple-negative breast cancer were the most important and complicated in breast carcinoma, occupying the most different expression genes, modules, seed genes, hub genes, and the most complex protein–protein interaction network and signal pathway. In addition, the luminal A subtype might occur in a completely different way from the other three subtypes as the pathways enriched in the luminal A subtype did not overlap with the others. We identified 16 hub genes that were related to good prognosis in triple-negative breast cancer. Moreover, SRSF1 was negatively correlated with overall survival in the Her2 subtype, while in the luminal A subtype, it showed the opposite relationship. Also, in the luminal B subtype, CCNB1 and KIF23 were associated with poor prognosis. Furthermore, new transcription factors and microRNAs were introduced to breast cancer which would shed light upon breast cancer in a new way and provide a novel therapeutic strategy. Conclusion: We preliminarily delved into the potentially comprehensive molecular mechanisms of breast cancer by creating a holistic view at the genomic and transcriptomic levels in different subtypes using computational tools. We also introduced new prognosis-related genes and novel therapeutic strategies and cast new light upon breast cancer.

Breast Cancer Identification Using Machine Learning

Breast cancer is a cancer disease that seriously threatens women’s health and occupies the first place in female cancer mortality. At present, the incidence rate of breast cancer in China is the first in the world and is on the rise. In view of the serious harm of breast cancer to life and health, researchers and institutions are making unremitting efforts to find a perfect diagnosis and treatment plan. With the improvement of computer performance and machine learning levels, intelligent algorithms have been able to replace human behavior and judgment in some fields. The traditional breast cancer diagnosis process requires medical experts to observe patient data repeatedly. In this case, the algorithm technology is used to quickly feedback a high probability reference result to doctors, which is particularly important to increase the diagnosis efficiency and reduce the burden of doctors. In order to improve the accuracy of existing breast cancer recognition methods, this paper proposes and implements a scheme based on a whale optimization algorithm to iteratively adjust the key parameters of the support vector machine to improve the accuracy of breast cancer recognition. In order to verify the performance of the WOA-SVM algorithm, this paper uses the Wisconsin breast cancer data in the UCI database for performance verification experiments. Experiments show that the WOA-SVM model has higher recognition accuracy than the traditional breast cancer recognition model.

MODERN VIEW ON THE EPIDEMIOLOGY OF BREAST CANCER:&#x0D; A LITERATURE REVIEW

Relevance: Breast cancer (BC) is the leading cause of female cancer mortality worldwide. The constant development of treatment strategies&#x0D; and diagnostic tools has increased the survival rate for BC. Next-generation genome sequencing (NGS) identifies the genetic changes responsible&#x0D; for tumor emergence, development, and metastasis. NGS has expanded the capacities of BC diagnostics, treatment, and early prevention in women.&#x0D; The study aimed to identify breast cancer risk factors in women.&#x0D; Methods: Publications were obtained from the following databases: PubMed, Google Scholar, and eLibrary. The depth of the search was 5 to&#x0D; 10 years. As a result, 100 literary sources were identified, of which 26 publications formed the scientific material for this review.&#x0D; Results: Breast cancer is a heterogeneous disease driven by genetic abnormalities and epigenetic alterations.&#x0D; Conclusion: Gene mutations do not change. Genetic testing shall be introduced and used as a preventive measure to reduce BC incidence.&#x0D; Lifestyle-related BC risk factors can be modified to reduce BC risk.