Presentation and characteristics of breast cancer in young women under age 40

Screening and Diagnostic Mammography During Pregnancy and Lactation: A Systematic Review of the Literature

In recent years, the age of childbearing has been increasing in Western countries, and consequently the need to conduct mammography during pregnancy and lactation is also increasing. The aim of the present study was to systematically review the existing evidence regarding the overall use of mammography during pregnancy and lactation. A systematic review of the literature was conducted in PubMed, Epistemonikos, and clinicaltrials.gov, by using the search terms "pregnancy" AND "mammography", and "lactation" AND "mammography". The review protocol was prospectively registered in PROSPERO (CRD42024543971). Initially, 1,038 articles were identified; the titles and abstracts of 441 studies were screened; 40 studies were retrieved; after assessment of full texts, 20 studies were included for data extraction and further analysis. All 20 studies were retrospective; 14 studies included women with pregnancy-associated breast cancer, five studies included women with breast symptoms during pregnancy and/or lactation and one study included young breast cancer patients under age 40. Overall, 420 diagnostic and one incidental screening mammography examinations were performed during pregnancy and/or lactation with a 78.6% cumulative detection rate of breast cancer. The role of mammography was confounded by the use of breast ultrasound in most studies. In conclusion, the use of mammography during pregnancy and lactation is based on empirical data from retrospective studies, not directly addressing this issue. Hence, well-designed, focused, prospective clinical studies are needed in order to improve existing evidence regarding the use of diagnostic and screening mammography during pregnancy and lactation.

Comparison of Explainable Artificial Intelligence Model and Radiologist Review Performances to Detect Breast Cancer in 752 Patients

OBJECTIVES

Breast cancer is a type of cancer caused by the uncontrolled growth of cells in the breast tissue. In a few cases, erroneous diagnosis of breast cancer by specialists and unnecessary biopsies can lead to various negative consequences. In some cases, radiologic examinations or clinical findings may raise the suspicion of breast cancer, but subsequent detailed evaluations may not confirm cancer. In addition to causing unnecessary anxiety and stress to patients, such diagnosis can also lead to unnecessary biopsy procedures, which are painful, expensive, and prone to misdiagnosis. Therefore, there is a need for the development of more accurate and reliable methods for breast cancer diagnosis.

METHODS

In this study, we proposed an artificial intelligence (AI)-based method for automatically classifying breast solid mass lesions as benign vs malignant. In this study, a new breast cancer dataset (Breast-XD) was created with 791 solid mass lesions belonging to 752 different patients aged 18 to 85 years, which were examined by experienced radiologists between 2017 and 2022.

RESULTS

Six classifiers, support vector machine (SVM), K-nearest neighbor (K-NN), random forest (RF), decision tree (DT), logistic regression (LR), and XGBoost, were trained on the training samples of the Breast-XD dataset. Then, each classifier made predictions on 159 test data that it had not seen before. The highest classification result was obtained using the explainable XGBoost model (X2GAI) with an accuracy of 94.34%. An explainable structure is also implemented to build the reliability of the developed model.

CONCLUSIONS

The results obtained by radiologists and the X2GAI model were compared according to the diagnosis obtained from the biopsy. It was observed that our developed model performed well in cases where experienced radiologists gave false positive results.

Long-term oncologic outcomes following breast cancer surgery in adolescents and young adults: a single-center retrospective analysis

Background

Breast cancer (BC) in adolescents and young adults (AYAs, aged 15-39 years), remains inadequately understood. The incidence of BC in AYAs has been steadily increasing, making it the second leading cause of cancer-related mortality among females aged 0-39 globally. This study aimed to elucidate the clinical characteristics and long-term outcomes of AYAs and older adults (OAs, aged > 39 years) with BC who underwent surgery.

Methods

From January 2011 to June 2017, BC patients who underwent surgery were enrolled in this study and divided into AYA group and OA group. Clinical characteristics, recurrence-free survival (RFS), and overall survival (OS) were compared between these two groups, both before and after propensity score matching (PSM). Univariate and multivariate Cox proportional hazard regression analyses were performed to assess the influence of age on OS and RFS.

Results

Compared to the OA group, the AYA group exhibited a younger age at menarche (p < 0.001), a lower prevalence of menopausal status (p < 0.001), a reduced occurrence of comorbid conditions (p < 0.001), fewer instances of undergoing mastectomy (p = 0.031), a higher incidence of Triple-Negative Breast Cancer (TNBC) (p = 0.046), and elevated Ki-67 levels (p = 0.036). In terms of prognostic outcomes, within the study cohort, AYAs had a higher mortality rate and poorer long-term survival compared to OAs, both before and after PSM. In the PSM cohort, AYAs experienced a significantly shorter median OS (p < 0.001) and RFS (p < 0.001). Young age (15-39 years) emerged as an independent risk factor for OS (HR 2.659, 95% CI 1.385-5.106, p = 0.003) and RFS (HR 3.235, 95% CI 2.085-5.022, p < 0.001) in BC patients following surgery.

Conclusion

Significant differences were identified in the clinicopathological characteristics between AYA and OA patients with BC. In comparison to OA patients, AYA patients exhibited a less favorable long-term prognosis, with young age emerging as an independent prognostic risk factor for both OS and RFS in BC patients following surgery. Further investigations are warranted to develop age-specific therapeutic approaches for AYA BC patients.

Identification of potential therapeutic targets for breast cancer using Mendelian randomization analysis and drug target prediction

Breast cancer stands as the foremost cause of cancer-related mortality among women, presenting a substantial economic impact on society. The limitations in current therapeutic options, coupled with poor patient tolerance, underscore the urgent need for novel treatments. Our study embarked on a genomic association exploration of breast cancer, leveraging whole-genome sequencing data from the Finngen database, complemented by expression quantitative trait loci (eQTL) insights from the eQTLGen and GTEx Consortiums. An initial investigation was conducted through summary-based Mendelian randomization (MR) to pinpoint primary eQTLs. Analysis of blood specimens revealed 103 eQTLs significantly correlated with breast cancer. Focusing our efforts, we identified 19 candidates with potential therapeutic significance. Further scrutiny via two-sample MR pinpointed UROD, LMO4, HORMAD1, and ZSWIM5 as promising targets for breast cancer therapy. Our research sheds light on new avenues for the treatment of breast cancer, highlighting the potential of genomic association studies in uncovering viable therapeutic targets.

1-Benzylimidazole attenuates the stemness of breast cancer cells through partially targeting CYP4Z1

Cytochrome P450 (CYP) 4Z1 (CYP4Z1) has recently garnered much interest as its expression predicts a poor prognosis and as a oncogene in breast cancer, and overexpressed in other many cancers. We previously showed that CYP4Z1 acts as a promoter of cancer stem cells (CSCs) to facilitate the occurrence and development of breast cancer. Here, RNA sequencing found that 1-benzylimidazole (1-Benzy) held a preferable correlation with breast cancer and suppressed the expression of CSC makers. Further functional experiments, including mammary spheroid formation, wound-healing, transwell-invasion, detection of tumor initiation, and metastatic ability, showed that 1-Benzy suppressed the stemness and metastasis of breast cancer cells. Additionally, we further demonstrated that CYP4Z1 is necessary for 1-Benzy-mediated suppression on breast cancer stemness and 1-Benzy exerted a weaker effect in breast cancer cells with CYP4Z1 knockdown. Taken together, our data suggest that 1-Benzy might be a potential drug suppressing breast cancer stemness via targeting CYP4Z1.

Breast Cancer Disparities and Innovations: A Focus on Kosovo

Due to the current limited capacity to provide digital mammography-based screening to all women, and the lack of modern surgical oncology methods, mastectomy is still the predominant form of surgical treatment in many parts of the world. As such there is little incentive to detect breast cancer earlier and significant fear of treatment and outcomes continues to contribute to late presentations. Neoadjuvant chemotherapy, pre-operative breast MRI and surgical mapping techniques can combine forces to allow for more women to be treated with breast conservation, decrease fear of treatment and improve outcomes.

A Population-Based Research Utilized a Risk Stratification Model to Forecast the Overall Survival of Young Women With Diagnosed Stage IV Breast Cancer

BACKGROUND

The goal of this study is to develop a risk prediction model for estimating overall survival (OS) in young females diagnosed with stage IV breast cancer.

METHODS

The clinical information was retrieved from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. To identify the dependent risk factors, we utilized the Cox proportional hazards regression model in both single and multivariate analyses. We then created a new nomogram to predict the 1-, 3-, and 5-year overall survival probability for these patients based on the identified risk factors.

RESULTS

Six hundred seventy-six patients who met the eligibility requirements were stochastically partitioned into training (n = 475) and validation (n = 201) groups in a 7:3 ratio. Histology, breast subtype, T classification, brain metastasis, bone metastasis, liver metastasis, and surgery were identified as independent prognostic factors for cancer. To predict the 1-, 3-, and 5-year overall survival (OS) probabilities, all of these independent factors were incorporated into nomograms. Our nomogram demonstrated a favorable discriminatory power, as evidenced by a C-index of 0.737 (95% CI: 0.708-0.766) and 0.717 (95% CI: 0.664-0.770) for the training and validation cohorts, respectively. The calibration curves showed satisfactory consistency in both cohorts. Using this nomogram, we developed a risk stratification model that categorized patients into low-, intermediate-, and high-risk groups.

CONCLUSION

The prediction model was more precisely to predict the OS of young females with stage IV breast cancer and could enable individualized risk estimation that could be conducive to physicians exploring therapeutic strategies for effectiveness.

Integrated Multi-Omics Profiling of Young Breast Cancer Patients Reveals a Correlation between Galactose Metabolism Pathway and Poor Disease-Free Survival

In recent years, there has been a notable rise in the incidence of breast cancer among young patients, who exhibit worse survival outcomes and distinct characteristics compared to intermediate and elderly patients. Therefore, it is imperative to identify the specific features unique to young patients, which could offer insights into potential therapeutic strategies and improving survival outcomes. In our study, we performed an integrative analysis of bulk transcriptional and genomic data from extensive clinical cohorts to identify the prognostic factotrs. Additionally, we analyzed the single-cell transcriptional data and conducted in vitro experiments. Our work confirmed that young patients exhibited higher grading, worse disease-free survival (DFS), a higher frequency of mutations in TP53 and BRCA1, a lower frequency of mutations in PIK3CA, and upregulation of eight metabolic pathways. Notably, the galactose metabolism pathway showed upregulation in young patients and was associated with worse DFS. Further analysis and experiments indicated that the galactose metabolism pathway may regulate the stemness of cancer cells and ultimately contribute to worse survival outcomes. In summary, our finding identified distinct clinicopathological, transcriptional, and genomics features and revealed a correlation between the galactose metabolism pathway, stemness, and poor disease-free survival of breast cancer in young patients.

Clinical features and prognostic factors of breast cancer in young women: a retrospective single-center study

PURPOSE

This research aims to characterize the differences in clinical features and prognostic factors between younger and older breast cancer (BC) patients in China.

METHODS

All patients who were recently diagnosed with BC between January 1, 2015 and December 31, 2016 at Shanxi Province Cancer Hospital were recruited. We collected the epidemiological and clinical data as well as the follow-up information.

RESULTS

Out of the 1968 BC patients who met the criteria for analysis, 227 (11.53%) were under 40 years of age with a median age of 34 years at diagnosis. All patients were classified into the age < 40, age 40-59, and age ≥ 60 groups. There were significant differences in the histology, tumor size, T stage, grade, and human epidermal growth factor receptor-2 (HER-2) levels among the three groups (all P < 0.05). The 5-year overall survival (OS) rates were 86.34%, 89.58%, and 84.84% for the age < 40, age 40-59, and age ≥ 60 groups, respectively. The TNM stage was the only predictor of clinical outcome in all BC patients. The prognostic value of intrinsic subtypes for OS was different among the three groups.

CONCLUSION

Our study helped identify an age-related prognostic indicator of adverse events in BC patients and showed that young women with BC exhibited more aggressive clinical and pathological features. Our findings may facilitate clinical management and therapeutic interventions in young BC patients, especially in young women with a history of exposure to risk factors and age < 40 years.

Cancer-related symptoms among young and middle-aged women undergoing chemotherapy for breast cancer: Application of latent class analysis and network analysis

PURPOSE

To identify subgroups and symptom networks of cancer-related symptoms for women under 60 years who are undergoing chemotherapy for breast cancer.

METHODS

A cross-sectional survey in Mainland China was conducted between August 2020 and November 2021. Participants completed questionnaires that collected demographic and clinical characteristics and featured the PROMIS-57 and the PROMIS-Cognitive Function Short Form.

RESULTS

A total of 1033 participants were included in the analysis, and three-class model was identified: "severe symptom group" (17.6%; Class 1), "moderately severe anxiety, depression, and pain-interference group" (38.0%; Class 2), and "mild symptom group" (44.4%; Class 3). Patients who were in menopause (OR = 3.05, P < .001), undergoing a combination of medical treatments (OR = 2.39, P = .003), and who had experienced complications (OR = 1.86, P = .009) were more likely to belong to Class 1. However, having two or more children increased the likelihood of belonging to Class 2. Additionally, network analysis showed that severe fatigue level was the core symptom among the full sample. As for Class 1, feeling helpless and severe fatigue level were the core symptoms. Regarding Class 2, the impact of pain interfere on the ability to participate in social activities and feeling hopeless were found to be the targeted symptoms for intervention.

CONCLUSION

Menopause, receiving a combination of medical treatments, and experiencing complications characterize the group with the most symptom disturbance. Moreover, different interventions should be performed for core symptoms in patients with varied symptom disturbances.

Development and validation of a short-term breast health measure as a supplement to screening mammography

Background

There is a growing body of evidence to support tears as a non-traditional biological fluid in clinical laboratory testing. In addition to the simplicity of tear fluid processing, the ability to access key cancer biomarkers in high concentrations quickly and inexpensively is significantly enhanced. Tear fluid is a dynamic environment rich in both proteomic and genomic information, making it an ideal medium for exploring the potential for biological testing modalities.

Methods

All protocols involving human subjects were reviewed and approved by the University of Arkansas IRB committee (13-11-289) prior to sample collection. Study enrollment was open to women ages 18 and over from October 30, 2017-June 19, 2019 at The Breast Center, Fayetteville, AR and Bentonville, AR. Convenience sampling was used and samples were age/sex matched, with enrollment open to individuals at any point of the breast health continuum of care. Tear samples were collected using the Schirmer strip method from 847 women. Concentration of selected tear proteins were evaluated using standard sandwich ELISA techniques and the resulting data, combined with demographic and clinical covariates, was analyzed using logistic regression analysis to build a model for classification of samples.

Results

Logistic regression analysis produced three models, which were then evaluated on cases and controls at two diagnostic thresholds and resulted in sensitivity ranging from 52 to 90% and specificity from 31 to 79%. Sensitivity and specificity variation is dependent on the model being evaluated as well as the selected diagnostic threshold providing avenues for assay optimization.

Conclusions and relevance

The work presented here builds on previous studies focused on biomarker identification in tear samples. Here we show successful early classification of samples using two proteins and minimal clinical covariates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40364-022-00420-1.

Establishment and Verification of Prognostic Nomograms for Young Women With Breast Cancer Bone Metastasis

Purpose

The prognosis of patients with metastatic breast cancer usually varies greatly among individuals. At present, the application of nomogram is very popular in metastatic tumors. The present study was conducted to identify independent survival predictors and construct nomograms among young women with breast cancer bone metastasis (BCBM).

Patients and Methods

We searched the Surveillance, Epidemiology, and End Results (SEER) database to identify young women diagnosed with BCBM between 2010 and 2016. We first analyzed the potential risk factors of overall survival (OS) and cancer-specific survival (CSS) by applying univariate Cox regression analysis. Then we conducted multivariate Cox analysis to identify independent survival predictors. Based on significant independent predictors, we developed and validated novel prognostic nomograms by using the R version 4.1.0 software.

Results

We finally identified 715 eligible young women with BCBM for survival analysis, of which 358 patients were in the training set, and 357 patients in the validation set. Approximately four-fifths of patients are between 31 and 40 years old. The 5-year OS and CSS rates of this research population were 41.9 and 43.3%, respectively. Multivariate analysis revealed seven independent predictors of both OS and CSS, including race, tumor subtype, tumor size, surgical treatment, brain metastasis, liver metastasis, and lung metastasis. Based on these predictors, we developed and validated OS and CSS nomograms. The C-index of the OS nomogram reached 0.728 and 0.73 in the training and validation sets, respectively. The C-index of the CSS nomogram reached 0.743 and 0.695 in the training and validation sets, respectively. Meanwhile, high quality calibration plots were revealed in both OS and CSS nomograms.

Conclusion

The current novel nomograms can provide an individualized survival evaluation of young women with BCBM and instruct clinicians to treat them appropriately.

Urgent and emergent breast lesions - A primer for the general radiologist, on-call resident and sonographer

There are very few true breast emergencies. While infrequent, women do present to emergency departments or urgent care centres with breast-related concerns. In this case-based review, both common and uncommon urgent and emergent breast lesions are presented, emphasising ultrasound characteristics and imaging optimisation to improve accurate diagnosis and appropriate recommendations.

Diagnostic delay in moderately/poorly differentiated breast cancer types

BACKGROUND

Diagnostic delay of breast cancer related to the false-negative assessment of the healthcare provider leads to tumor progression and might worsen the outcome. Previous studies found some factors associated with provider-related diagnostic delay; however, tumor biology has tended not to be considered. The aim of our study was to find differences in diagnostic delay of poorly differentiated breast cancer types.

METHODS

Data of 970 patients with newly diagnosed moderately/poorly differentiated (G2/3) breast cancer at the age ≥40 years was retrospectively analyzed regarding breast cancer type, diagnostic delay and its consequence, clinical factors and physician's assessment. Multivariate analysis was used to evaluate associated factors with diagnostic delay.

RESULTS

We observed a diagnostic delay in 3.8% (n = 37) of all patients. Mean delay time was 128 days, and clinically relevant tumor growth was observed in 43.2% of these cases. Delay was significantly higher in the group of triple-negative breast cancer (9.9% versus 2.7, 5.3 and 1.8% in hormonal receptor (HR)+/human epidermal growth factor receptor 2 (HER2)-, HR-/Her2+ and HR+/Her2+, respectively; P value <0.001). Age, breast density and reason for presentation were not correlated to diagnostic delay.

CONCLUSION

Patients with triple-negative breast cancer are at higher risk of receiving a false-negative assessment and experiencing a diagnostic delay. Our results emphasize the importance of a detailed consideration of clinical risk factors and provider training and suggest a broad indication for a core needle biopsy.

Oncologic outcomes of immediate breast reconstruction in young women with breast cancer receiving neoadjuvant chemotherapy

BACKGROUND

Oncologic safety of postmastectomy breast reconstruction in young women with breast cancer is not well-defined, especially in the setting of neoadjuvant chemotherapy (NACT). We retrospectively compared the oncologic outcomes following nipple-sparing (NSM)/skin-sparing mastectomy (SSM) with immediate breast reconstruction (IBR) and conventional mastectomy (CM) alone in young breast cancer patients after NACT.

METHODS

A total of 1266 women with primary breast cancer who underwent NACT followed by total mastectomy with or without IBR were reviewed. Of these, only young patients (age ≤ 40 years at diagnosis) were included in the outcome analysis (n = 375). After propensity score-matching by clinical T and N stage, molecular subtype, response to NACT, and adjuvant radiotherapy status, 228 patients were 1:1 matched, comprising balanced IBR group (with NSM/SSM) and CM-alone group.

RESULTS

The 5-year locoregional recurrence-free, disease-free, distant metastasis (DM)-free, and breast cancer-specific survival (BCSS) rates for the entire cohort of young patients were 83.4%, 65.3%, 71.7%, and 85.4%, respectively. Locoregional recurrence rates between the matched groups were similar (14% vs. 15.8%; p = 0.710); however, IBR group had significantly lower DM rate (27.2% vs. 40.4%; p = 0.036) and breast cancer mortality (14.9% vs. 27.2%; p = 0.023) than CM-alone group. IBR group showed significantly improved 5-year DM-free survival (74.1% vs. 62.6%; p = 0.043) and BCSS (89.1% vs. 77.6%; p = 0.048) rates than CM-alone group.

CONCLUSIONS

Our results indicated that IBR with NSM/SSM does not negatively affect long-term oncologic outcomes compared to CM alone in young women with breast cancer receiving NACT.