Heterogeneity in risk factors for ductal and lobular breast carcinomas: A case-control study

Machine learning algorithms to uncover risk factors of breast cancer: insights from a large case-control study

Introduction

This large case-control study explored the application of machine learning models to identify risk factors for primary invasive incident breast cancer (BC) in the Iranian population. This study serves as a bridge toward improved BC prevention, early detection, and management through the identification of modifiable and unmodifiable risk factors.

Methods

The dataset includes 1,009 cases and 1,009 controls, with comprehensive data on lifestyle, health-behavior, reproductive and sociodemographic factors. Different machine learning models, namely Random Forest (RF), Neural Networks (NN), Bootstrap Aggregating Classification and Regression Trees (Bagged CART), and Extreme Gradient Boosting Tree (XGBoost), were employed to analyze the data.

Results

The findings highlight the significance of a chest X-ray history, deliberate weight loss, abortion history, and post-menopausal status as predictors. Factors such as second-hand smoking, lower education, menarche age (>14), occupation (employed), first delivery age (18-23), and breastfeeding duration (>42 months) were also identified as important predictors in multiple models. The RF model exhibited the highest Area Under the Curve (AUC) value of 0.9, as indicated by the Receiver Operating Characteristic (ROC) curve. Following closely was the Bagged CART model with an AUC of 0.89, while the XGBoost model achieved a slightly lower AUC of 0.78. In contrast, the NN model demonstrated the lowest AUC of 0.74. On the other hand, the RF model achieved an accuracy of 83.9% and a Kappa coefficient of 67.8% and the XGBoost, achieved a lower accuracy of 82.5% and a lower Kappa coefficient of 0.6.

Conclusion

This study could be beneficial for targeted preventive measures according to the main risk factors for BC among high-risk women.

Family history and breast cancer risk for Asian women: a systematic review and meta-analysis

BACKGROUND

Studies of women of European ancestry have shown that the average familial relative risk for first-degree relatives of women with breast cancer is approximately twofold, but little is known for Asian women. We aimed to provide evidence for the association between family history and breast cancer risk for Asian women by systematically reviewing published literature.

METHODS

Studies reporting the familial relative risk of breast cancer for Asian women were searched in three online databases and complemented by a manual search. Odds ratios (ORs) for the association between family history and breast cancer risk were pooled across all included studies and by subgroups in terms of the type of family history, age, menopausal status and geographical region.

RESULTS

The pooled OR for women who have a first-degree relative with breast cancer was 2.46 (95% confidence interval [CI]: 2.03, 2.97). There was no evidence that the familial risk differed by the type of affected relative (mother versus sisters), the woman's age (< 50 years versus ≥ 50 years), menopausal status (pre versus post) and geographical region (East and Southeast Asia versus other regions) (all P > 0.3). The pooled ORs for women of Asian ancestry with a family history in any relative were similar for those living in non-Asian countries (2.26, 95% CI: 1.42, 3.59) compared with those living in Asian countries (2.18, 95% CI: 1.85, 2.58).

CONCLUSIONS

Family history of breast cancer is associated with an approximately twofold relative risk of breast cancer for Asian women, which is of similar magnitude to that observed for women of European ancestry. This implies that similar familial factors are implicated in breast cancer risk between women of European and Asian ancestries. Genetic factors are likely to play a substantial role in explaining the breast cancer familial risk for Asian women, as similar risks were observed across different living environments and cultures.

Adherence to a western dietary pattern and risk of invasive ductal and lobular breast carcinomas: a case-control study

Little is known about the role of diet in the risk of invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) of the breast, the most common histological subtypes of breast cancer (BC). This is because, the majority of studies on the association of diet and the risk of BC are focused on single food items, and studies considering the overall diet in terms of dietary patterns are limited. Also, the potential heterogeneity in the impact of Western diet (WD) on histological subtypes of BC is not established. This, the age-frequency-matched case–control study included 1009 incident BC cases and 1009 healthy controls. The required data was obtained from the patients’ medical files and interviews using a previously validated researcher-designed questionnaire for collecting data on socio-economic and anthropometric statuses and a valid food frequency questionnaire (FFQ) to measure the participants’ dietary intake. We used multinomial logistic regression, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. A positive and significant association was observed between higher adherence to a WD and risk of IDC (OR comparing highest with the lowest tertile: 2.45, 95% CI 1.88, 3.17; p-trend < 0.001), whereas no significant association was observed between adherence to the WD and the risk of ILC (OR comparing highest with the lowest tertile: 1.63, 95% CI 0.63, 3.25) (p for heterogeneity = 0.03). The results of an analysis stratified by menopausal status suggested a similar pattern. We provided evidence that adherence to a WD raises the risk of IDC, but not ILC, suggesting different etiological mechanisms for IDC and ILC.

Biomarkers for Breast Adenocarcinoma Using In Silico Approaches

This work elucidates the idea of finding probable critical genes linked to breast adenocarcinoma. In this study, the GEO database gene expression profile data set (GSE70951) was retrieved to look for genes that were expressed variably across breast adenocarcinoma samples and healthy tissue samples. The genes were confirmed to be part of the PPI network for breast cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. For correlation analysis, the predictive biomarker of these hub genes, as well as GEPIA, was used. A total of 155 (85 upregulated genes and 70 downregulated genes) were identified. By integrating the PPI and CytoHubba data, the major key/hub genes were selected from the results. The KM plotter is employed to find the prognosis of those major pivot genes, and the outcome shows worse prognosis in breast adenocarcinoma patients. Further experimental validation will show the predicted expression levels of those hub genes. The overall result of our study gives the consequences for the identification of a critical gene to ease the molecular targeting therapy for breast adenocarcinoma. It could be used as a prognostic biomarker and could lead to therapy options for breast adenocarcinoma.

The distribution of reproductive risk factors disclosed the heterogeneity of receptor-defined breast cancer subtypes among Tanzanian women

Background

Recent epidemiological studies suggest that reproductive factors are associated with breast cancer (BC) molecular subtypes. However, these associations have not been thoroughly studied in the African populations. The present study aimed to investigate the prevalence of BC molecular subtypes and assess their association with reproductive factors in Tanzanian BC patients.

Methods

This hospital-based case-only cross-sectional study consisted of 263 histologically confirmed BC patients in Tanzania. Clinico-pathological data, socio-demographic characteristics, anthropometric measurements, and reproductive risk factors were examined using the Chi-square test and one-way ANOVA. The association among reproductive factors and BC molecular subtypes was analyzed using multinomial logistic regression. The heterogeneity of the associations was assessed using the Wald test.

Results

We found evident subtype heterogeneity for reproductive factors. We observed that post-menopausal status was more prevalent in luminal-A subtype, while compared to luminal-A subtype, luminal-B and HER-2 enriched subtypes were less likely to be found in post-menopausal women (OR: 0.21, 95%CI 0.10–0.41, p = 0.001; OR: 0.39, 95%CI 0.17–0.89, p = 0.026, respectively). Also, the luminal-B subtype was more likely to be diagnosed in patients aged ≤ 40 years than the luminal-A subtype (OR: 2.80, 95%CI 1.46–5.32, p = 0.002). Women who had their first full-term pregnancy at < 30 years were more likely to be of luminal-B (OR: 2.71, 95%CI 1.18–4.17, p = 0.018), and triple-negative (OR: 2.28, 95%CI 1.02–4.07, p = 0.044) subtypes relative to luminal-A subtype. Furthermore, we observed that breastfeeding might have reduced odds of developing luminal-A, luminal-B and triple-negative subtypes. Women who never breastfed were more likely to be diagnosed with luminal-B and triple-negative subtypes when compared to luminal-A subtype (OR: 0.46, 95%CI 0.22–0.95, p = 0.035; OR: 0.41, 95%CI 0.20–0.85, p = 0.017, respectively).

.

Conclusion

Our results are the first data reporting reproductive factors heterogeneity among BC molecular subtypes in Tanzania. Our findings suggest that breast-feeding may reduce the likelihood of developing luminal-A, luminal-B, and triple-negative subtypes. Meanwhile, the first full-term pregnancy after 30 years of age could increase the chance of developing luminal-A subtype, a highly prevalent subtype in Tanzania. More interventions to promote modifiable risk factors across multiple levels may most successfully reduce BC incidence in Africa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12905-021-01536-6.

Estrogen receptor-positive breast cancer survival prediction and analysis of resistance-related genes introduction

Background

In recent years, ER+ and HER2- breast cancer of adjuvant therapy has made great progress, including chemotherapy and endocrine therapy. We found that the responsiveness of breast cancer treatment was related to the prognosis of patients. However, reliable prognostic signatures based on ER+ and HER2- breast cancer and drug resistance-related prognostic markers have not been well confirmed, This study in amied to establish a drug resistance-related gene signature for risk stratification in ER+ and HER2- breast cancer.

Methods

We used the data from The Cancer Genoma Atlas (TCGA) breast cancer dataset and gene expression database (Gene Expression Omnibus, GEO), constructed a risk profile based on four drug resistance-related genes, and developed a nomogram to predict the survival of patients with I-III ER+ and HER2- breast cancer. At the same time, we analyzed the relationship between immune infiltration and the expression of these four genes or risk groups.

Results

Four drug resistance genes (AMIGO2, LGALS3BP, SCUBE2 and WLS) were found to be promising tools for ER+ and HER2- breast cancer risk stratification. Then, the nomogram, which combines genetic characteristics with known risk factors, produced better performance and net benefits in calibration and decision curve analysis. Similar results were validated in three separate GEO cohorts. All of these results showed that the model can be used as a prognostic classifier for clinical decision-making, individual prediction and treatment, as well as follow-up.

Case Report of a Breast Mass with Three Types of Malignant Tumors-Squamous Cell Carcinoma, Invasive Ductal Carcinoma, and Breast Sarcoma

Breast malignancy comprises malignant tumors originating from epithelial tissue and breast sarcoma arising from mesodermal tissues. Despite heterogeneity in tumors, most malignant tumors of the breast are composed of a single type of tumor. Here, we report a patient with breast tumor consisting of three different types of malignancies—squamous cell carcinoma, invasive ductal carcinoma, and high-grade breast sarcoma.

Hereditary and breastfeeding factors are positively associated with the aetiology of mammary gland hyperplasia: a case-control study

BACKGROUND

Hyperplasia of mammary gland (HMG) has become a common disorder in women. A family history of breast cancer and female reproductive factors may work together to increase the risk of HMG. However, this specific relationship has not been fully characterized.

METHODS

A total of 1881 newly diagnosed HMG cases and 1900 controls were recruited from 2012 to 2017. Demographic characteristics including female reproductive factors and a family history of breast cancer were collected. A multi-analytic strategy combining unconditional logistic regression, multifactor dimensionality reduction (MDR) and crossover approaches were applied to systematically identify the interaction effect of family history of breast cancer and reproductive factors on HMG susceptibility.

RESULTS

In MDR analysis, high-order interactions among higher-level education, shorter breastfeeding duration and family history of breast cancer were identified (odds ratio [OR] 7.07 [95% confidence interval {CI} 6.08 to 8.22]). Similarly, in crossover analysis, HMG risk increased significantly for those with higher-level education (OR 36.39 [95% CI 11.47 to 115.45]), shorter duration of breastfeeding (OR 27.70 [95% CI 3.73 to 205.70]) and a family history of breast cancer.

CONCLUSION

Higher-level education, shorter breastfeeding duration and a family history of breast cancer may synergistically increase the risk of HMG.

Dietary Patterns and Risk of Invasive Ductal and Lobular Breast Carcinomas: A Systematic Review and Meta-analysis

The histopathologic subtypes of breast cancer, including invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC), differ in terms of risk factors, progression, and response to treatment. The PubMed/Medline, Web of Science, and Scopus databases were searched up to February 2020 for published studies on the association between dietary patterns (Western diet [WD] or Mediterranean diet [WD]) and the risk of IDC/ILC of breast. Multivariable adjusted relative risk (RR) and 95% confidence intervals (CIs) comparing the highest and lowest categories of WD and MD patterns were combined by using the random-effects meta-analyses. After searching the databases, 10 eligible studies on the association of diet and IDC (7 articles) and ILC (3 articles) were included in the analysis. A statistically significant adverse association was observed between MD and IDC in case-control studies (RR = 0.47; 95% CI, 0.39-0.55; I² = 85.1%; P < .001). However, the association was nonsignificant in cohort studies (RR = 0.98; 95% CI, 0.92-1.05; I² = 88.8%; P = .003). The pooled analysis also suggested a significant and direct association between the WD and the risk of IDC (RR = 1.36; 95% CI, 1.18-1.53; I² = 63.7%; P = .017). The risk of ILC for the highest compared to the lowest category of MD was highly protective (RR = 0.76; 95% CI, 0.64-0.87; I² = 89.2%; P < .001), and a marginally significant association was found between the WD and risk of ILC (RR = 1.45; 95% CI, 1.04-1.86), with no heterogeneity (I² = 0; P = .52). This meta-analysis provides supporting evidence for the association between MD decreased risk of IDC and ILC of the breast and the association between WD and increased risk of IDC and ILC. Further investigations are needed to better understand the reasons behind the etiologic mechanisms of how dietary patterns affect patients differently by common breast cancer subtypes, including IDC and ILC.