Risk-based breast cancer screening strategies in women

Implementing supplementary breast cancer screening in women with dense breasts: Insights from European radiographers and radiologists

INTRODUCTION

In response to the critical need for enhancing breast cancer screening for women with dense breasts, this study explored the understanding of challenges and requirements for implementing supplementary breast cancer screening for such women among clinical radiographers and radiologists in Europe.

METHOD

Fourteen (14) semi-structured online interviews were conducted with European clinical radiologists (n = 5) and radiographers (n = 9) specializing in breast cancer screening from 8 different countries: Denmark, Finland, Greece, Italy, Malta, the Netherlands, Switzerland, United Kingdom. The interview schedule comprised questions regarding professional background and demographics and 13 key questions divided into six subgroups, namely Supplementary Imaging, Training, Resources and Guidelines, Challenges, Implementing supplementary screening and Women's Perspective. Data analysis followed the six phases of reflexive thematic analysis.

RESULTS

Six significant themes emerged from the data analysis: Understanding and experiences of supplementary imaging for women with dense breasts; Challenges and requirements related to training among clinical radiographers and radiologists; Awareness among radiographers and radiologists of guidelines on imaging women with dense breasts; Challenges to implement supplementary screening; Predictors of Implementing Supplementary screening; Views of radiologists and radiographers on women's perception towards supplementary screening.

CONCLUSION

The interviews with radiographers and radiologists provided valuable insights into the challenges and potential strategies for implementing supplementary breast cancer screening. These challenges included patient and staff related challenges. Implementing multifaceted solutions such as Artificial Intelligence integration, specialized training and resource investment can address these challenges and promote the successful implementation of supplementary screening. Further research and collaboration are needed to refine and implement these strategies effectively.

IMPLICATIONS FOR PRACTICE

This study highlights the urgent need for specialized training programs and dedicated resources to enhance supplementary breast cancer screening for women with dense breasts in Europe. These resources include advanced imaging technologies, such as MRI or ultrasound, and specialized software for image analysis. Moreover, further research is imperative to refine screening protocols and evaluate their efficacy and cost-effectiveness, based on the findings of this study.

Development and validation of nomograms using photoacoustic imaging and 2D ultrasound to predict breast nodule benignity and malignancy

BACKGROUND

The application of photoacoustic imaging (PAI), utilizing laser-induced ultrasound, shows potential in assessing blood oxygenation in breast nodules. However, its effectiveness in distinguishing between malignant and benign nodules remains insufficiently explored.

PURPOSE

This study aims to develop nomogram models for predicting the benign or malignant nature of breast nodules using PAI.

METHOD

A prospective cohort study enrolled 369 breast nodules, subjecting them to PAI and ultrasound examination. The training and testing cohorts were randomly divided into two cohorts in a ratio of 3:1. Based on the source of the variables, three models were developed, Model 1: photoacoustic-BIRADS+BMI + blood oxygenation, Model 2: BIRADS+Shape+Intranodal blood (Doppler) + BMI, Model 3: photoacoustic-BIRADS+BIRADS+ Shape+Intranodal blood (Doppler) + BMI + blood oxygenation. Risk factors were identified through logistic regression, resulting in the creation of three predictive models. These models were evaluated using calibration curves, subject receiver operating characteristic (ROC), and decision curve analysis.

RESULTS

The area under the ROC curve for the training cohort was 0.91 (95% confidence interval, 95% CI: 0.88-0.95), 0.92 (95% CI: 0.89-0.95), and 0.97 (95% CI: 0.96-0.99) for Models 1-3, and the ROC curve for the testing cohort was 0.95 (95% CI: 0.91-0.98), 0.89 (95% CI: 0.83-0.96), and 0.97 (95% CI: 0.95-0.99) for Models 1-3.

CONCLUSIONS

The calibration curves demonstrate that the model's predictions agree with the actual values. Decision curve analysis suggests a good clinical application.

AI performance by mammographic density in a retrospective cohort study of 99,489 participants in BreastScreen Norway

OBJECTIVE

To explore the ability of artificial intelligence (AI) to classify breast cancer by mammographic density in an organized screening program.

MATERIALS AND METHOD

We included information about 99,489 examinations from 74,941 women who participated in BreastScreen Norway, 2013-2019. All examinations were analyzed with an AI system that assigned a malignancy risk score (AI score) from 1 (lowest) to 10 (highest) for each examination. Mammographic density was classified into Volpara density grade (VDG), VDG1-4; VDG1 indicated fatty and VDG4 extremely dense breasts. Screen-detected and interval cancers with an AI score of 1-10 were stratified by VDG.

RESULTS

We found 10,406 (10.5% of the total) examinations to have an AI risk score of 10, of which 6.7% (704/10,406) was breast cancer. The cancers represented 89.7% (617/688) of the screen-detected and 44.6% (87/195) of the interval cancers. 20.3% (20,178/99,489) of the examinations were classified as VDG1 and 6.1% (6047/99,489) as VDG4. For screen-detected cancers, 84.0% (68/81, 95% CI, 74.1-91.2) had an AI score of 10 for VDG1, 88.9% (328/369, 95% CI, 85.2-91.9) for VDG2, 92.5% (185/200, 95% CI, 87.9-95.7) for VDG3, and 94.7% (36/38, 95% CI, 82.3-99.4) for VDG4. For interval cancers, the percentages with an AI score of 10 were 33.3% (3/9, 95% CI, 7.5-70.1) for VDG1 and 48.0% (12/25, 95% CI, 27.8-68.7) for VDG4.

CONCLUSION

The tested AI system performed well according to cancer detection across all density categories, especially for extremely dense breasts. The highest proportion of screen-detected cancers with an AI score of 10 was observed for women classified as VDG4.

CLINICAL RELEVANCE STATEMENT

Our study demonstrates that AI can correctly classify the majority of screen-detected and about half of the interval breast cancers, regardless of breast density.

KEY POINTS

• Mammographic density is important to consider in the evaluation of artificial intelligence in mammographic screening. • Given a threshold representing about 10% of those with the highest malignancy risk score by an AI system, we found an increasing percentage of cancers with increasing mammographic density. • Artificial intelligence risk score and mammographic density combined may help triage examinations to reduce workload for radiologists.

Acceptability of risk-tailored cancer screening among Australian GPs: a qualitative study

BACKGROUND

Cancer screening that is tailored to individual risk has the potential to improve health outcomes and reduce screening-related harms, if implemented well. However, successful implementation depends on acceptability, particularly as this approach will require GPs to change their practice.

AIM

To explore Australian GPs' views about the acceptability of risk-tailored screening across cancer types and to identify barriers to and facilitators of implementation.

DESIGN AND SETTING

A qualitative study using semi-structured interviews with Australian GPs.

METHOD

Interviews were carried out with GPs and audio-recorded and transcribed. Data were first analysed inductively then deductively using an implementation framework.

RESULTS

Participants (n = 20) found risk-tailored screening to be acceptable in principle, recognising potential benefits in offering enhanced screening to those at highest risk. However, they had significant concerns that changes in screening advice could potentially cause confusion. They also reported that a reduced screening frequency or exclusion from a screening programme for those deemed low risk may not initially be acceptable, especially for common cancers with minimally invasive screening. Other reservations about implementing risk-tailored screening in general practice included a lack of high-quality evidence of benefit, fear of missing the signs or symptoms of a patient's cancer, and inadequate time with patients. While no single preferred approach to professional education was identified, education around communicating screening results and risk stratification was considered important.

CONCLUSION

GPs may not currently be convinced of the net benefits of risk-tailored screening. Development of accessible evidence-based guidelines, professional education, risk calculators, and targeted public messages will increase its feasibility in general practice.

Harms and benefits of mammographic screening for breast cancer in Brazil

INTRODUCTION

In the absence of evidence on the effect of mammographic screening on overall mortality, comparing the number of deaths avoided with the number of deaths caused by screening would be ideal, but the only existing models of this type adopt a very narrow definition of harms. The objective of the present study was to estimate the number of deaths prevented and induced by various mammography screening protocols in Brazil.

METHODS

A simulation study of cohorts of Brazilian women screened, considering various age groups and screening interval protocols, was performed based on life tables. The number of deaths avoided and caused by screening was estimated, as was the absolute risk reduction, the number needed to invite for screening-NNS, the net benefit of screening, and the ratio of "lives saved" to "lives lost". Nine possible combinations of balances between benefits and harms were performed for each protocol, in addition to other sensitivity analyses.

RESULTS AND CONCLUSIONS

The most efficient protocol was biennial screening from 60 to 69 years of age, with almost three times more deaths avoided than biennial screening from 50 to 59 years of age, with a similar number of deaths avoided by biennial screening from 50 to 69 years of age and with the greatest net benefit. Compared with the best scenario of annual screening from 40 to 49 years of age, the NNS of the protocol with biennial screening from 60 to 69 years of age was three-fold lower. Even in its best scenario, the addition of annual screening from 40 to 49 years of age to biennial screening from 50 to 69 years of age results in a decreased net benefit. However, even in the 50-69 year age group, the estimated reduction in breast cancer mortality for Brazil was half that estimated for the United Kingdom.

The diagnostic performance of dual-layer spectral detector CT for distinguishing breast cancer biomarker expression and molecular subtypes

To evaluate the diagnostic performance of dual-layer spectral detector CT for differentiation of breast cancer molecular subtypes. This study was done in a retrospective approach including 104 female patients histopathologically proven to have breast cancer. These patients underwent chest arterial and venous phase dual-layer SDCT. CT values, iodine concentrations (IC)s, and Z-effective (Zeff) values of the lesions and arteries in the same layer were determined for both arterial and venous phases. Parameter values were normalized, and slopes of the spectral curves (λHu) were calculated. Breast cancer biomarkers were also analyzed. Afterward, correlations between the obtained parameters and biomarkers were analyzed. Eventually, the diagnostic performance was assessed using ROC curves. ER or PR-negative patients generally showed significantly higher mean iodine concentrations, CT, and Z-effective values. HER2-positive patients showed significantly higher CTVE, ZeffVE, N-ZeffVE, ICART, ICVE, NICART, NICVE, and λVE. Only ICVE and ZeffVE differed significantly between Ki67-positive and negative patients. All parameters showed significant diagnostic value for subtypes except N-ZeffART. Luminal and non-luminal types differed significantly and ROC curves indicated that multi-factors had the best diagnostic efficacy. The dual-layer SDCT distinguishes breast cancer biomarker expression and molecular subtypes. Thus, it can be used for preoperative assessment of breast cancer.

Evaluating clinical efficacy of hospital-based surveillance with mammography and ultrasonography for breast cancer

Periodic mammography and/or sonography examinations are conducted across numerous hospitals nationalwidely, especially for antedees with a positive mammography screening. Despite the regular practice, clinical efficacy of hospital-based breast cancer surveillance remains unclear. Specifically, the impact of surveillance interval upon survival and prognostic surrogates stratified by menopausal status, as well as malignant transition rate should be deciphered. We retrieved cancer registry to ascertain 841 breast cancers with surveillance history through administration data. Healthy controls underwent breast surveillance and were concurrently free of cancer. More benign diseases rather than cancers were identified from premenopausal women (age ≤50 years) with sonography alone within one year, as well as older women (age >50) with both mammography and sonography one to two years before a cancer or benign diagnosis. Among breast cancers, mammography alone during the antecedent one to two years had a protective effect for diagnosing carcinoma in situ rather than invasive cancer (age-adjusted odds ratio: 0.048, P = 0.016). Three-state time homogeneous Markov model showed that hospital-based breast surveillance within 2 years of disease onset reduced the malignant transition rate by 65.16% (59.79-76.74%). The clinical efficacy of breast cancer surveillance was evidenced.

The Effect of an Educational Intervention on Breast Cancer Screening of Rural Women: Application of the Theory of Planned Behavior

BACKGROUND

Early diagnosis of breast cancer is a key factor affecting patient survival, so screening can reduce the burden of this disease. The present study aimed to investigate the effect of education based on the theory of planned behavior (TPB) on breast cancer screening in rural women.

METHODS

In this quasi-experimental study, 480 women referring to the health care centers in the cities of Fasa and Shiraz were divided into two groups, intervention (n = 240) and control (n = 240), using cluster random sampling method, in 2021-2022. We randomly selected two health care centers in Shiraz and Fasa and invited them to participate in the study. The demographic information questionnaire and a researcher-made questionnaire based on the TPB were used to collect the data. The intervention included 50-minute sessions on topics such as breast cancer basics, screening methods, barriers to mammography, and the role of peer groups. Data were collected before and 4 months after the intervention.

RESULTS

The results showed no difference between the two groups in awareness, attitude, perceived behavioral control, subjective norms, behavioral intention, and breast cancer screening performance before the intervention. Four months after the intervention, a significant increase was found in the intervention group in awareness (7.46 ± 1.50 to 18.54 ± 1.20), attitude (28.55 ± 4.62 to 58.69 ± 4.35), perceived behavioral control (22.52 ± 3.32 to 40.88 ± 3.84), and subjective norms (20.37 ± 3.34 to 21.99 ± 3.38). Instead, no significant difference in the mentioned constructs (P < 0.05) was observed in the control group.

CONCLUSION

This study demonstrated that TPB-based education enhanced awareness, attitude, perceived behavioral control, subjective norms, and behavioral intention towards breast cancer screening. The TPB empowers women in rural communities to prioritize their health and seek timely breast cancer screening. Continued efforts and improved access to screening services are crucial for improved outcomes.

TET Enzymes and 5hmC Levels in Carcinogenesis and Progression of Breast Cancer: Potential Therapeutic Targets

Breast Cancer (BC) was the most common female cancer in incidence and mortality worldwide in 2020. Similarly, BC was the top female cancer in the USA in 2022. Risk factors include earlier age at menarche, oral contraceptive use, hormone replacement therapy, high body mass index, and mutations in BRCA1/2 genes, among others. BC is classified into Luminal A, Luminal B, HER2-like, and Basal-like subtypes. These BC subtypes present differences in gene expression signatures, which can impact clinical behavior, treatment response, aggressiveness, metastasis, and survival of patients. Therefore, it is necessary to understand the epigenetic molecular mechanism of transcriptional regulation in BC, such as DNA demethylation. Ten-Eleven Translocation (TET) enzymes catalyze the oxidation of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) on DNA, which in turn inhibits or promotes the gene expression. Interestingly, the expression of TET enzymes as well as the levels of the 5hmC epigenetic mark are altered in several types of human cancers, including BC. Several studies have demonstrated that TET enzymes and 5hmC play a key role in the regulation of gene expression in BC, directly (dependent or independent of DNA de-methylation) or indirectly (via interaction with other proteins such as transcription factors). In this review, we describe our recent understanding of the regulatory and physiological function of the TET enzymes, as well as their potential role as biomarkers in BC biology.

An optimization framework to guide the choice of thresholds for risk-based cancer screening

It is uncommon for risk groups defined by statistical or artificial intelligence (AI) models to be chosen by jointly considering model performance and potential interventions available. We develop a framework to rapidly guide choice of risk groups in this manner, and apply it to guide breast cancer screening intervals using an AI model. Linear programming is used to define risk groups that minimize expected advanced cancer incidence subject to resource constraints. In the application risk stratification performance is estimated from a case-control study (2044 cases, 1:1 matching), and other parameters are taken from screening trials and the screening programme in England. Under the model, re-screening in 1 year for the highest 4% AI model risk, in 3 years for the middle 64%, and in 4 years for 32% of the population at lowest risk, was expected to reduce the number of advanced cancers diagnosed by approximately 18 advanced cancers per 1000 diagnosed with triennial screening, for the same average number of screens in the population as triennial screening for all. Sensitivity analyses found the choice of thresholds was robust to model parameters, but the estimated reduction in advanced cancers was not precise and requires further evaluation. Our framework helps define thresholds with the greatest chance of success for reducing the population health burden of cancer when used in risk-adapted screening, which should be further evaluated such as in health-economic modelling based on computer simulation models, and real-world evaluations.

Vacuum-assisted biopsy system for breast lesions: a potential therapeutic approach

Purpose

The primary objective is to optimize the population eligible for Mammotome Minimally Invasive Surgery (MIS) by refining selection criteria. This involves maximizing procedure benefits, minimizing malignancy risk, and reducing the rate of malignant outcomes.

Patients and methods

A total of 1158 female patients who came to our hospital from November 2016 to August 2021 for the Mammotome MIS were analyzed retrospectively. Following χ2 tests to screen for risk variables, binary logistic regression analysis was used to determine the independent predictors of malignant lesions. In addition, the correlation between age and lesion diameter was investigated for BI-RADS ultrasound (US) category 4a lesions in order to better understand the relationship between these variables.

Results

The malignancy rates of BI-RADS US category 3, category 4a and category 4b patients who underwent the Mammotome MIS were 0.6% (9/1562), 6.4% (37/578) and 8.3% (2/24) respectively. Malignant lesions were more common in patients over the age of 40, have visible blood supply, and BI-RADS category 4 of mammography. In BI-RADS US category 4a lesions, the diameter of malignant tumor was highly correlated with age, and this correlation was strengthened in patients over the age of 40 and with BI-RADS category 4 of mammography.

Conclusion

The results of this study demonstrate that the clinical data and imaging results, particularly age, blood supply, and mammography classification, offer valuable insights to optimize patients' surgical options and decrease the incidence of malignant outcomes.

Evaluation of an AI Model to Assess Future Breast Cancer Risk

Background Accurate breast cancer risk assessment after a negative screening result could enable better strategies for early detection. Purpose To evaluate a deep learning algorithm for risk assessment based on digital mammograms. Materials and Methods A retrospective observational matched case-control study was designed using the OPTIMAM Mammography Image Database from the National Health Service Breast Screening Programme in the United Kingdom from February 2010 to September 2019. Patients with breast cancer (cases) were diagnosed following a mammographic screening or between two triannual screening rounds. Controls were matched based on mammography device, screening site, and age. The artificial intelligence (AI) model only used mammograms at screening before diagnosis. The primary objective was to assess model performance, with a secondary objective to assess heterogeneity and calibration slope. The area under the receiver operating characteristic curve (AUC) was estimated for 3-year risk. Heterogeneity according to cancer subtype was assessed using a likelihood ratio interaction test. Statistical significance was set at P < .05. Results Analysis included patients with screen-detected (median age, 60 years [IQR, 55-65 years]; 2044 female, including 1528 with invasive cancer and 503 with ductal carcinoma in situ [DCIS]) or interval (median age, 59 years [IQR, 53-65 years]; 696 female, including 636 with invasive cancer and 54 with DCIS) breast cancer and 1:1 matched controls, each with a complete set of mammograms at the screening preceding diagnosis. The AI model had an overall AUC of 0.68 (95% CI: 0.66, 0.70), with no evidence of a significant difference between interval and screen-detected (AUC, 0.69 vs 0.67; P = .085) cancer. The calibration slope was 1.13 (95% CI: 1.01, 1.26). There was similar performance for the detection of invasive cancer versus DCIS (AUC, 0.68 vs 0.66; P = .057). The model had higher performance for advanced cancer risk (AUC, 0.72 ≥stage II vs 0.66 Collapse

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MESH Headings

• Humans
• Female
• Middle Aged
• Breast Neoplasms/diagnostic imaging
• Carcinoma, Intraductal, Noninfiltrating
• Artificial Intelligence
• Case-Control Studies
• Retrospective Studies
• State Medicine

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Grants

• 28689 Cancer Research UK
• C49757/A28689 Cancer Research UK

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Affiliation(s)

Celeste Damiani From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Grigorios Kalliatakis From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Muthyala Sreenivas From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Miaad Al-Attar From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Janice Rose From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Clare Pudney From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Emily F Lane From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Jack Cuzick From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Giovanni Montana From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)
Adam R Brentnall From the Center for Human Technologies, Istituto Italiano di Tecnologia, Via Melen 83, Genoa 16152, Italy (C.D.); Wolfson Institute of Population Health, Queen Mary University of London, London, UK (C.D., E.F.L., J.C., A.R.B.); Institute of Computer Science (ICS), Foundation of Research and Technology Hellas, Heraklion, Crete, Greece (G.K.); Joint for Director Breast Screening, University Hospitals Coventry and Warwickshire NHS Trust Coventry, Coventry, UK (M.S.); Department of Oncoplastic Breast Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK (M.A.A.); Consumer member at National Cancer Research Institute, Breast Group, London, UK (J.R., C.P.); and University of Warwick, WMG, Coventry, UK (G.M.)

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LncRNA-SNPs in a Brazilian Breast Cancer Cohort: A Case-Control Study

Long noncoding RNAs (lncRNAs) are a class of non-coding RNAs that contain more than 200 nucleotides and exhibit a versatile regulatory capacity. Genomic alterations in lncRNAs have already been investigated in several complex diseases, including breast cancer (BC). BC is a highly heterogeneous disease and is the most prevalent cancer type among women worldwide. Single nucleotide polymorphisms (SNPs) in lncRNA regions appear to have an important role in BC susceptibility; however, little is known about lncRNA-SNPs in the Brazilian population. This study used Brazilian tumor samples to identify lncRNA-SNPs with a biological role in BC development. We applied a bioinformatic approach intersecting lncRNAs that are differentially expressed in BC tumor samples using The Cancer Genome Atlas (TCGA) cohort data and looked for lncRNAs with SNPs associated with BC in the Genome Wide Association Studies (GWAS) catalog. We highlight four lncRNA-SNPs-rs3803662, rs4415084, rs4784227, and rs7716600-which were genotyped in Brazilian BC samples in a case-control study. The SNPs rs4415084 and rs7716600 were associated with BC development at higher risk. These SNPs were also associated with progesterone status and lymph node status, respectively. The rs3803662/rs4784227 haplotype GT was associated with BC risk. These genomic alterations were also evaluated in light of the lncRNA's secondary structure and gain/loss of miRNA binding sites to better understand its biological functions. We emphasize that our bioinformatics approach could find lncRNA-SNPs with a potential biological role in BC development and that lncRNA-SNPs should be more deeply investigated in a highly heterogeneous disease population.

Breast cancer genetics and risk assessment: an overview for the clinician

Breast cancer is the most common cancer in women globally with enormous associated morbidity, mortality and economic impact. Prevention of breast cancer is a global public health imperative. To date, most of our global efforts have been directed at expanding population breast cancer screening programs for early cancer detection and not at breast cancer prevention efforts. It is imperative that we change the paradigm. As with other diseases, prevention of breast cancer starts with identification of individuals at high risk, and for breast cancer this requires improved identification of individuals who carry a hereditary cancer mutation associated with an elevated risk of breast cancer, and identification of others who are at high risk due to non-genetic, established modifiable and non-modifiable factors. This article will review basic breast cancer genetics and the most common hereditary breast cancer mutations associated with increased risk. We will also discuss the other non-genetic modifiable and non-modifiable breast cancer risk factors, available risk assessment models and an approach to incorporating screening for genetic mutation carriers and identifying high-risk women in clinical practice. A discussion of guidelines for enhanced screening, chemoprevention and surgical management of high-risk women is beyond the scope of this review.

Potential Role of Fourier Transform Infrared Spectroscopy as a Screening Approach for Breast Cancer

Breast cancer is a heterogeneous disease, and its spread involves a succession of clinical and pathological stages. Screening is predominantly based on mammography, which has critical limitations related to the effectiveness and production of false-positive or false-negative results, generating discomfort and low adherence. In this context, infrared with attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy emerges as a non-destructive sample tool, which is non-invasive, label-free, has a low operating-cost, and requires only a small amount of sample, including liquid plasma samples. We sought to evaluate the clinical applicability of ATR FT-IR in breast cancer screening. ATR FT-IR spectroscopy through its highest potential spectral biomarker could distinguish, by liquid plasma biopsy, breast cancer patients and healthy controls, obtaining a sensitivity of 97%, specificity of 93%, a receiver operating characteristic ROC curve of 97%, and a prediction accuracy of 94%. The main variance between the groups was mainly in the band 1511 cm^-1 of the control group, 1502 and 1515 cm^-1 of the cancer group, which are the peaks of the bands referring to proteins and amide II. ATR FT-IR spectroscopy has demonstrated to be a promising tool for breast cancer screening, given its time efficiency, cost of approach, and its high ability to distinguish between the liquid plasma samples of breast cancer patients and healthy controls.

Magnetic resonance imaging in screening women at high risk of breast cancer: A meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is more accurate than mammography in screening for breast cancer. Exposure to ionizing radiation from repeated diagnostic X-rays may be a cause of breast cancer.

METHODS

We conducted systematic searches on PubMed, Cochrane and Embase to identify studies on women who underwent mammography or MRI screening. A meta-analysis was performed to compare the detection rate of breast cancer by mammography, MRI or both.

RESULTS

A total of 18 diagnostic publications were identified and included in the meta-analysis. Among the 1000 screened women, MRI alone increased the detection rate of breast cancer by 8 compared with mammography alone (RR 0.48, 95% CI 0.42-0.54), and MRI plus mammography increased the detection rate of breast cancer by 1 compared with MRI alone (RR 0.86, 95% CI 0.78-0.96). Subgroup analysis demonstrated that the diagnostic efficacy of MRI plus mammography in breast was obviously better than that of MRI alone or mammography alone.

CONCLUSIONS

Screening with MRI alone might be the best choice for women at high risk of breast cancer.

Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review

BACKGROUND

The benefits and harms of breast screening may be better balanced through a risk-stratified approach. We conducted a systematic review assessing the accuracy of questionnaire-based risk assessment tools for this purpose.

METHODS

Population: asymptomatic women aged ≥40 years; Intervention: questionnaire-based risk assessment tool (incorporating breast density and polygenic risk where available); Comparison: different tool applied to the same population; Primary outcome: breast cancer incidence; Scope: external validation studies identified from databases including Medline and Embase (period 1 January 2008-20 July 2021). We assessed calibration (goodness-of-fit) between expected and observed cancers and compared observed cancer rates by risk group. Risk of bias was assessed with PROBAST.

RESULTS

Of 5124 records, 13 were included examining 11 tools across 15 cohorts. The Gail tool was most represented (n = 11), followed by Tyrer-Cuzick (n = 5), BRCAPRO and iCARE-Lit (n = 3). No tool was consistently well-calibrated across multiple studies and breast density or polygenic risk scores did not improve calibration. Most tools identified a risk group with higher rates of observed cancers, but few tools identified lower-risk groups across different settings. All tools demonstrated a high risk of bias.

CONCLUSION

Some risk tools can identify groups of women at higher or lower breast cancer risk, but this is highly dependent on the setting and population.

Comparing the performance of three modalities of breast cancer screening within a combined programme targeting at-risk women in Indonesia: An implementation study

ABSTRACTAlthough mammography is the gold standard for breast cancer screening, the World Health Organization recommends clinical breast examination (CBE) as the preferred early detection method in countries with limited resources. However, its effectiveness as a 'stand-alone' screening modality compared with other techniques remains unclear. Therefore, we evaluated a risk-based opportunistic breast cancer screening programme using three modalities. Between June and December 2018, we conducted a cross-sectional study in Yogyakarta, Indonesia, of women aged >40 years with at least one risk factor for breast cancer. Subjects underwent CBE, mammography, and ultrasonography. We calculated the proportion of breast lesions detected through each modality and compared their mass size. A total of 503 eligible subjects were screened. Five cases of potential malignant lesions were detected; pathological tests conducted for 4 of them confirmed breast cancer diagnoses. A combined assessment of mammography and ultrasonography examinations revealed 343 breast lesions (68.2%), whereas CBE screening detected only 76 breast lesions (15.1%). The mean lesion sizes detected by mammography or ultrasonography, but not through CBE, were significantly smaller (p-values of 0.037 and 0.007 for mammography and ultrasonography, respectively). In conclusion, mammography and ultrasonography produced higher detection rates for benign and malignant breast lesions compared with CBE.

Analysis on Incidence and Mortality Trends and Age-Period-Cohort of Breast Cancer in Chinese Women from 1990 to 2019

AIMS

To analyze the incidence and mortality trends of breast cancer among women in China from 1990 to 2019 and explore the effects of age, period, and cohort on the incidence and mortality of breast cancer.

METHODS

We performed a Joinpoint regression model to describe trends in breast cancer incidence and mortality. We used an age-period-cohort analysis model to estimate the impact of age, period, and cohort on breast cancer incidence and mortality. We collected breast cancer incidence and mortality among women aged 20-89 in China (1990-2019) from the Global Health Data Exchange (GHDx) database.

RESULTS

The crude incidence and mortality of breast cancer from 1990 to 2019 in Chinese women showed an increasing trend, with an average annual increase percentage (AAPC) of 4.69% and 2.18%, respectively. The analysis on the age-period-cohort model revealed that the risk of incidence increased first and then decreased with age and peaked at 55-59 years old, whereas the risk of mortality increased by approximately 60.34 times from 20 to 89 years old. The risk of incidence and mortality increased by 2.64 and 1.49 times with the passage of time, respectively. The later the birth cohort is, the lower the risk of incidence and mortality will be.

CONCLUSION

From 1990 to 2019, the incidence and mortality of breast cancer among Chinese women showed an increasing trend, and the prevention and control situation of breast cancer was still grim. Therefore, visual examination and palpation examination should be actively carried out in adult women with breast cancer, and the conventional population after 40 years of age, the high-risk population carrying hereditary breast cancer gene and the elderly population should be assisted with imaging examination along with palpation examination. When treating patients suffering from breast cancer, in order to reduce the death rate, a personalized treatment plan should be developed based on the characteristics of different patients.

Breast Cancer Screening in Women With Dense Breasts: Current Status and Future Directions for Appropriate Risk Stratification and Imaging Utilization

Breast density continues to be a prevailing topic in the field of breast imaging, with continued complexities contributing to overall confusion and controversy among patients and the medical community. In this article, we explore the current status of breast cancer screening in women with dense breasts including breast density legislation. Risk-based approaches to supplemental screening may be more financially cost-effective. While all advanced imaging modalities detect additional primarily invasive, node-negative cancers, the degree to which this occurs can vary by density category. Future directions include expanding the use of density-inclusive risk models with appropriate risk stratification and imaging utilization. Further research is needed, however, to better understand how to optimize population-based screening programs with knowledge of patients' individualized risk, including breast density assessment, to improve the benefit-to-harm ratio of breast cancer screening.

"It Will Lead You to Make Better Decisions about Your Health"-A Focus Group and Survey Study on Women's Attitudes towards Risk-Based Breast Cancer Screening and Personalised Risk Assessments

Singapore launched a population-based organised mammography screening (MAM) programme in 2002. However, uptake is low. A better understanding of breast cancer (BC) risk factors has generated interest in shifting from a one-size-fits-all to a risk-based screening approach. However, public acceptability of the change is lacking. Focus group discussions (FGD) were conducted with 54 women (median age 37.5 years) with no BC history. Eight online sessions were transcribed, coded, and thematically analysed. Additionally, we surveyed 993 participants in a risk-based MAM study on how they felt in anticipation of receiving their risk profiles. Attitudes towards MAM (e.g., fear, low perceived risk) have remained unchanged for ~25 years. However, FGD participants reported that they would be more likely to attend routine mammography after having their BC risks assessed, despite uncertainty and concerns about risk-based screening. This insight was reinforced by the survey participants reporting more positive than negative feelings before receiving their risk reports. There is enthusiasm in knowing personal disease risk but concerns about the level of support for individuals learning they are at higher risk for breast cancer. Our results support the empowering of Singaporean women with personal health information to improve MAM uptake.

Mammographic breast density and the risk of breast cancer: A systematic review and meta-analysis

OBJECTIVES

Mammographic density is a well-defined risk factor for breast cancer and having extremely dense breast tissue is associated with a one-to six-fold increased risk of breast cancer. However, it is questioned whether this increased risk estimate is applicable to current breast density classification methods. Therefore, the aim of this study was to further investigate and clarify the association between mammographic density and breast cancer risk based on current literature.

METHODS

Medline, Embase and Web of Science were systematically searched for articles published since 2013, that used BI-RADS lexicon 5th edition and incorporated data on digital mammography. Crude and maximally confounder-adjusted data were pooled in odds ratios (ORs) using random-effects models. Heterogeneity regarding breast cancer risks were investigated using I² statistic, stratified and sensitivity analyses.

RESULTS

Nine observational studies were included. Having extremely dense breast tissue (BI-RADS density D) resulted in a 2.11-fold (95% CI 1.84-2.42) increased breast cancer risk compared to having scattered dense breast tissue (BI-RADS density B). Sensitivity analysis showed that when only using data that had adjusted for age and BMI, the breast cancer risk was 1.83-fold (95% CI 1.52-2.21) increased. Both results were statistically significant and homogenous.

CONCLUSIONS

Mammographic breast density BI-RADS D is associated with an approximately two-fold increased risk of breast cancer compared to having BI-RADS density B in general population women. This is a novel and lower risk estimate compared to previously reported and might be explained due to the use of digital mammography and BI-RADS lexicon 5th edition.

Cervical Cancer in the Baltic States: Can Intelligent and Personalised Cancer Screening Change the Situation?

The three Baltic States (Estonia, Latvia, and Lithuania) are among the European Union countries with the highest incidence and mortality rates for cervical cancer. In order to tackle this public health challenge, there is an urgent need to implement more advanced and effective methods in cervical cancer prevention in Baltic countries.

Nationwide cervical cancer screening programs in the Baltic States commenced in 2004–2009. While the organized screening programs in these countries differ in some relevant details (target age groups, screening interval), the underlying principles and problems, barriers are universal. However, the outcomes of present screening programs are unsatisfactory. In addition, universal screening programs are extremely costly. There is a potential need for more intelligent and personalized cervical cancer screening program. In 2019 the project “Towards elimination of cervical cancer: intelligent and personalized solutions for cancer screening” (2020–2023) was developed with the main objective – to develop improved and personalized cancer screening methods within a sustainable health care system.

It is expected, that more sophisticated cervical cancer screening model will be implemented in Estonia, Latvia, and Lithuania, and will have a positive impact to epidemiology of cervical cancer and public health in general.

Towards implementation of comprehensive breast cancer risk prediction tools in health care for personalised prevention

Advances in knowledge about breast cancer risk factors have led to the development of more comprehensive risk models. These integrate information on a variety of risk factors such as lifestyle, genetics, family history, and breast density. These risk models have the potential to deliver more personalised breast cancer prevention. This is through improving accuracy of risk estimates, enabling more effective targeting of preventive options and creating novel prevention pathways through enabling risk estimation in a wider variety of populations than currently possible. The systematic use of risk tools as part of population screening programmes is one such example. A clear understanding of how such tools can contribute to the goal of personalised prevention can aid in understanding and addressing barriers to implementation. In this paper we describe how emerging models, and their associated tools can contribute to the goal of personalised healthcare for breast cancer through health promotion, early disease detection (screening) and improved management of women at higher risk of disease. We outline how addressing specific challenges on the level of communication, evidence, evaluation, regulation, and acceptance, can facilitate implementation and uptake.

Prognostic and Immune Implications of a Novel Pyroptosis-Related Five-Gene Signature in Breast Cancer

Background

Breast cancer (BC) is the most common cancer among women worldwide, with enormous heterogeneity. Pyroptosis has a significant impact on the development and progression of tumors. Nonetheless, the possible correlation between pyroptosis-related genes (PRGs) and the BC immune microenvironment has yet to be investigated.

Materials and methods

In The Cancer Genome Atlas Breast Cancer cohort, 38 PRGs were shown to be significantly different between malignant and non-malignant breast tissues. The 38 PRGs’ consensus clustering grouped 1,089 individuals into two pyroptosis-related (PR) patterns. Using univariate and LASSO-Cox analyses, a PR five-gene predictive signature was constructed based on the differentially expressed genes between two clusters. The tools estimation of stromal and immune cells in malignant tumours using expression data (ESTIMATE), cell type identification by estimating relative subsets Of RNA transcripts (CIBERSORT), and single-sample gene set enrichment analysis (ssGSEA) were used to investigate the BC tumor microenvironment (TME).

Results

In TME, the two PR clusters displayed distinct clinicopathological characteristics, survival outcomes, and immunocyte infiltration features. The developed five-signature model (SEMA3B, IGKC, KLRB1, BIRC3, and PSME2) classified BC patients into two risk groups based on the estimated median risk score. Patients in the low-scoring category had a higher chance of survival and more extensive immunocyte infiltration. An external validation set can yield similar results.

Conclusion

Our data suggest that PRGs have a significant impact on the BC immunological microenvironment. The PR clusters and associated predictive signature stimulate additional research into pyroptosis in order to optimize therapeutic strategies for BC patients and their responses to immune therapy.

Breast cancer screening and early diagnosis in Chinese women

Breast cancer is the most common malignant tumor in Chinese women, and its incidence is increasing. Regular screening is an effective method for early tumor detection and improving patient prognosis. In this review, we analyze the epidemiological changes and risk factors associated with breast cancer in China and describe the establishment of a screening strategy suitable for Chinese women. Chinese patients with breast cancer tend to be younger than Western patients and to have denser breasts. Therefore, the age of initial screening in Chinese women should be earlier, and the importance of screening with a combination of ultrasound and mammography is stressed. Moreover, Chinese patients with breast cancers have several ancestry-specific genetic features, and aiding in the determination of genetic screening strategies for identifying high-risk populations. On the basis of current studies, we summarize the development of risk-stratified breast cancer screening guidelines for Chinese women and describe the significant improvement in the prognosis of patients with breast cancer in China.

The current status of risk-stratified breast screening

Apart from high-risk scenarios such as the presence of highly penetrant genetic mutations, breast screening typically comprises mammography or tomosynthesis strategies defined by age. However, age-based screening ignores the range of breast cancer risks that individual women may possess and is antithetical to the ambitions of personalised early detection. Whilst screening mammography reduces breast cancer mortality, this is at the risk of potentially significant harms including overdiagnosis with overtreatment, and psychological morbidity associated with false positives. In risk-stratified screening, individualised risk assessment may inform screening intensity/interval, starting age, imaging modality used, or even decisions not to screen. However, clear evidence for its benefits and harms needs to be established. In this scoping review, the authors summarise the established and emerging evidence regarding several critical dependencies for successful risk-stratified breast screening: risk prediction model performance, epidemiological studies, retrospective clinical evaluations, health economic evaluations and qualitative research on feasibility and acceptability. Family history, breast density or reproductive factors are not on their own suitable for precisely estimating risk and risk prediction models increasingly incorporate combinations of demographic, clinical, genetic and imaging-related parameters. Clinical evaluations of risk-stratified screening are currently limited. Epidemiological evidence is sparse, and randomised trials only began in recent years.

Views of health professionals on risk-based breast cancer screening and its implementation in the Spanish National Health System: A qualitative discussion group study

BACKGROUND

With the aim of increasing benefits and decreasing harms, risk-based breast cancer screening has been proposed as an alternative to age-based screening. This study explores barriers and facilitators to implementing a risk-based breast cancer screening program from the perspective of health professionals, in the context of a National Health Service.

METHODS

Socio-constructivist qualitative research carried out in Catalonia (Spain), in the year 2019. Four discussion groups were conducted, with a total of 29 health professionals from primary care, breast cancer screening programs, hospital breast units, epidemiology units, and clinical specialties. A descriptive-interpretive thematic analysis was performed.

RESULTS

Identified barriers included resistance to reducing the number of screening exams for low-risk women; resistance to change for health professionals; difficulties in risk communication; lack of conclusive evidence of the benefits of risk-based screening; limited economic resources; and organizational transformation. Facilitators include benefits of risk-based strategies for high and low-risk women; women's active role in their health care; proximity of women and primary care professionals; experience of health professionals in other screening programs; and greater efficiency of a risk-based screening program. Organizational and administrative changes in the health system, commitment by policy makers, training of health professionals, and educational interventions addressed to the general population will be required.

CONCLUSIONS

Despite the expressed difficulties, participants supported the implementation of risk-based screening. They highlighted its benefits, especially for women at high risk of breast cancer and those under 50 years of age, and assumed a greater efficiency of the risk-based program compared to the aged-based one. Future studies should assess the efficiency and feasibility of risk-based breast cancer screening for its transfer to clinical practice.

Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review

Objective: The risk prediction model is an effective tool for risk stratification and is expected to play an important role in the early detection and prevention of esophageal cancer. This study sought to summarize the available evidence of esophageal cancer risk predictions models and provide references for their development, validation, and application.

Methods: We searched PubMed, EMBASE, and Cochrane Library databases for original articles published in English up to October 22, 2021. Studies that developed or validated a risk prediction model of esophageal cancer and its precancerous lesions were included. Two reviewers independently extracted study characteristics including predictors, model performance and methodology, and assessed risk of bias and applicability with PROBAST (Prediction model Risk Of Bias Assessment Tool).

Results: A total of 20 studies including 30 original models were identified. The median area under the receiver operating characteristic curve of risk prediction models was 0.78, ranging from 0.68 to 0.94. Age, smoking, body mass index, sex, upper gastrointestinal symptoms, and family history were the most commonly included predictors. None of the models were assessed as low risk of bias based on PROBST. The major methodological deficiencies were inappropriate date sources, inconsistent definition of predictors and outcomes, and the insufficient number of participants with the outcome.

Conclusions: This study systematically reviewed available evidence on risk prediction models for esophageal cancer in general populations. The findings indicate a high risk of bias due to several methodological pitfalls in model development and validation, which limit their application in practice.

Docosahexaenoic acid (DHA) and linoleic acid (LA) modulate the expression of breast cancer involved miRNAs in MDA-MB-231 cell line

BACKGROUND AND AIMS

Docosahexaenoic acid (DHA) and linoleic acid (LA) have modulatory effects on breast cancer (BC) cell lines. We aimed to investigate the effects of DHA, LA alone, in combination, and in the presence of paclitaxel on the expression of five microRNAs involved in the pathology of BC in MDA-MB-231 cell line.

METHODS

MDA-MB-231 cells were treated with either DHA or LA or in combination in the presence/absence of paclitaxel (Taxol). Total RNA was extracted and cDNA synthesized from the cells before and after treatment. The expression levels of miR-30, miR-106b, miR-20, miR-126, and miR-194 were determined by quantitative real-time PCR (qPCR).

RESULTS

Treatment of MDA-MB-231 cells with DHA modulated the gene expression of miR-30 (increased by 7.74-fold (p < 0.0001), miR-194 (decreased by 11-fold (p < 0.0001)), miR-106b (increased by 2.64-fold (p = 0.0004), miR-126 (decreased by 50-fold (p < 0.0001)), and miR-20 (decreased by 4-fold (p < 0.0001)). Additionally, treatment of MDA-MB-231 cells with LA modulated the gene expression of miR-30 (increased by 2.38-fold (p = 0.0001)), miR-194 (decreased by 100-fold (p < 0.0001)), miR-106b (decreased by 10-fold (p < 0.0001)). The combined DHA/LA treatment of MDA-MB-231 cells showed regulatory effect on the expression of studied microRNAs in which decreased the expression of miR-30 (5.5-fold (p < 0.0001)), miR-194 (11-fold (p < 0.0001)), miR-20 (3.5-fold (p = 0.0006)), and increased the expression of miR-106b (9.78-fold (p < 0.0001)).

CONCLUSIONS

Modulation of the expression levels of BC-involved microRNAs could be one of the possible mechanisms of action through which DHA and LA may exert their biologic effects on MDA-MB-231 cell line.

Risk factors and nursing countermeasures of postoperative pulmonary infection in patients with breast cancer: A retrospective analysis

It is necessary to elucidate the potential risk factors of pulmonary infection to provide references for the management of breast cancer.Our study was a retrospective design, patients who underwent modified radical mastectomy for breast cancer in our department of breast surgery from January 2019 to November 2020 were included. The personal and clinical data of included patients with and without pulmonary infection were compared.A total of 234 patients with radical mastectomy were included, the incidence of pulmonary infection was 15.38% with 95%confidence interval (CI) 11.42% to 18.98%. There were significant differences in the age, body mass index, diabetes, duration of surgery, combined radiotherapy and chemotherapy, and duration of drainage between patients with and without pulmonary infections (all P < .05). Logistic regression analysis indicated that age ≥55 years (odds ratio [OR] 2.128, 95%CI 1.105-3.426), body mass index ≥ 24 kg/m2(OR 2.344, 95%CI 1.031-3.299), diabetes (OR 2.835, 95%CI 1.132-4.552), duration of surgery ≥120 minutes (OR 1.394, 95%CI 1.012-1.044), combined radiotherapy and chemotherapy (OR 3.122, 95%CI 1.124-5.273), duration of drainage ≥5 days (OR 1.851, 95%CI 1.112-2.045) might be the independent risk factors of pulmonary infection in patients after radical mastectomy(all P < .05). Pseudomonas aeruginosa and Klebsiella pneumoniae are the most commonly seen bacteria.The incidence of postoperative pulmonary infections in breast cancer patients is high, and there are many associated risk factors. The perioperative management of patients should be strengthened targeted on those risk factors in clinical practice.

Acceptability of risk-stratified population screening across cancer types: Qualitative interviews with the Australian public

BACKGROUND

There is mounting evidence of the benefit of risk-stratified (risk-tailored) cancer population screening, when compared to standard approaches. However, shifting towards this approach involves changes to practice that may give rise to implementation challenges.

OBJECTIVES

To explore the public's potential acceptance of risk-stratified screening across different cancer types, including reducing screening frequency if at low risk and the use of personal risk information, to inform implementation strategies.

METHOD

Semi-structured interviews were conducted with 40 public participants; half had received personal genomic risk information and half had not. Participants were prompted to consider different cancers. Data were analysed thematically as one dataset.

RESULTS

Themes included the following: (a) a sense of security; (b) tailored screening is common sense; (c) risk and the need to take action; (d) not every cancer is the same; and (e) trust and belief in health messages. Both groups expressed similar views. Participants were broadly supportive of risk-stratified screening across different cancer types, with strong support for increased screening frequency for high-risk groups. They were less supportive of reduced screening frequency or no screening for low-risk groups. Findings suggest the public will be amenable to reducing screening when the test is invasive and uncomfortable; be less opposed to forgo screening if offered the opportunity to screen at some stage; and view visible cancers such as melanoma differently.

CONCLUSIONS

Approaching distinct cancer types differently, tailoring messages for different audiences and understanding reasons for participating in screening may assist with designing future implementation strategies for risk-stratified cancer screening.

The role of androgens in women's health and wellbeing

Androgens in women, as well as in men, are intrinsic to maintenance of (i) reproductive competency, (ii) cardiac health, (iii) appropriate bone remodeling and mass retention, (iii) muscle tone and mass, and (iv) brain function, in part, through their mitigation of neurodegenerative disease effects. In recognition of the pluripotency of endogenous androgens, exogenous androgens, and selected congeners, have been prescribed off-label for several decades to treat low libido and sexual dysfunction in menopausal women, as well as, to improve physical performance. However, long-term safety and efficacy of androgen administration has yet to be fully elucidated. Side effects often observed include (i) hirsutism, (ii) acne, (iii) deepening of the voice, and (iv) weight gain but are associated most frequently with supra-physiological doses. By contrast, short-term clinical trials suggest that the use of low-dose testosterone therapy in women appears to be effective, safe and economical. There are, however, few clinical studies, which have focused on effects of androgen therapy on pre- and post-menopausal women; moreover, androgen mechanisms of action have not yet been thoroughly explained in these subjects. This review considers clinical effects of androgens on women's health in order to prevent chronic diseases and reduce cancer risk in gynecological tissues.

Association of genetic variants of FBXO32 and FOXO6 in the FOXO pathway with breast cancer risk

Forkhead box class O (FOXO) transcription factors play a pivotal role in regulating a variety of biological processes, including organismal development, cell signaling, cell metabolism, and tumorigenesis. Therefore, we hypothesize that genetic variants in FOXO pathway genes are associated with breast cancer (BC) risk. To test this hypothesis, we conducted a large meta-analysis using 14 published genome-wide association study (GWAS) data sets in the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study. We assessed associations between 5214 (365 genotyped in DRIVE and 4849 imputed) common single-nucleotide polymorphisms (SNPs) in 55 FOXO pathway genes and BC risk. After multiple comparison corrections by the Bayesian false-discovery probability method, we found five SNPs to be significantly associated with BC risk. In stepwise multivariate logistic regression analysis with adjustment for age, principal components, and previously published SNPs in the same data set, three independent SNPs (i.e., FBXO32 rs10093411 A>G, FOXO6 rs61229336 C>T, and FBXO32 rs62521280 C>T) remained to be significantly associated with BC risk (p = 0.0008, 0.0011, and 0.0017, respectively). Additional expression quantitative trait loci analysis revealed that the FBXO32 rs62521280 T allele was associated with decreased messenger RNA (mRNA) expression levels in breast tissue, while the FOXO6 rs61229336 T allele was found to be associated with decreased mRNA expression levels in the whole blood cells. Once replicated by other investigators, these genetic variants may serve as new biomarkers for BC risk.

Making Sense of Genetic Information: The Promising Evolution of Clinical Stratification and Precision Oncology Using Machine Learning

Precision medicine is a medical approach to administer patients with a tailored dose of treatment by taking into consideration a person's variability in genes, environment, and lifestyles. The accumulation of omics big sequence data led to the development of various genetic databases on which clinical stratification of high-risk populations may be conducted. In addition, because cancers are generally caused by tumor-specific mutations, large-scale systematic identification of single nucleotide polymorphisms (SNPs) in various tumors has propelled significant progress of tailored treatments of tumors (i.e., precision oncology). Machine learning (ML), a subfield of artificial intelligence in which computers learn through experience, has a great potential to be used in precision oncology chiefly to help physicians make diagnostic decisions based on tumor images. A promising venue of ML in precision oncology is the integration of all available data from images to multi-omics big data for the holistic care of patients and high-risk healthy subjects. In this review, we provide a focused overview of precision oncology and ML with attention to breast cancer and glioma as well as the Bayesian networks that have the flexibility and the ability to work with incomplete information. We also introduce some state-of-the-art attempts to use and incorporate ML and genetic information in precision oncology.

Machine Learning Models to Improve the Differentiation Between Benign and Malignant Breast Lesions on Ultrasound: A Multicenter External Validation Study

Purpose

This study aimed to establish and evaluate the usefulness of a simple, practical, and easy-to-promote machine learning model based on ultrasound imaging features for diagnosing breast cancer (BC).

Materials and Methods

Logistic regression, random forest, extra trees, support vector, multilayer perceptron, and XG Boost models were developed. The modeling data set of 1345 cases was from a tertiary class A hospital in China. The external validation data set of 1965 cases were from 3 tertiary class A hospitals and 2 primary hospitals. The area under the receiver operating characteristic curve (AUC) was used as the main evaluation index, and pathological biopsy was used as the gold standard for evaluating each model. Diagnostic capability was also compared with that of clinicians.

Results

Among the six models, the logistic model showed superior diagnostic efficiency, with an AUC of 0.771 and 0.906 and Brier scores of 0.181 and 0.165 in the test and validation sets, respectively. The AUCs of the clinician diagnosis and the logistic model were 0.913 and 0.906. Their AUCs in the tertiary class A hospitals were 0.915 and 0.915, respectively, and were 0.894 and 0.873 in primary hospitals, respectively.

Conclusion

The externally validated logical model can be used to distinguish between malignant and benign breast lesions in ultrasound images. Compared with clinician diagnosis, the logistic model has better diagnostic efficiency, making it potentially useful to assist in screening, particularly in lower level medical institutions.

Trial Registration

http://www.clinicaltrials.gov. ClinicalTrials.gov ID: NCT03080623.

Mechanisms of Resistance to Chemotherapy in Breast Cancer and Possible Targets in Drug Delivery Systems

Breast cancer (BC) is one of the most important cancers worldwide, and usually, chemotherapy can be used in an integrative approach. Usually, chemotherapy treatment is performed in association with surgery, radiation or hormone therapy, providing an increased outcome to patients. However, tumors can develop resistance to different drugs, progressing for a more aggressive phenotype. In this scenario, the use of nanocarriers could help to defeat tumor cell resistance, providing a new therapeutic perspective for patients. Thus, this systematic review aims to bring the molecular mechanisms involved in BC chemoresistance and extract from the previous literature information regarding the use of nanoparticles as potential treatment for chemoresistant breast cancer.

Screening detects a myriad of breast disease - refining practice will increase effectiveness and reduce harm

For many individuals, the term 'cancer' equates to a disease that if untreated will progress, spread from the area initially affected and ultimately cause death. 'Breast cancer', however, is a diverse of range of pathological entities, incorporating indolent to fast-growing and aggressive lesions, with varying histological patterns, clinical presentations, treatment responses and outcomes. Screening for malignancy is based on the assumption that cancer has a gradual, orderly progression and that detecting lesions earlier in their natural history, and intervening, will reduce mortality. The natural history of epithelial atypia, ductal carcinoma in situ and even invasive breast cancer is poorly understood, but widely variable. We believe that population breast screening methodology needs to change to focus on diagnosis of lesions of greatest clinical relevance.

Spectrochemical analysis of liquid biopsy harnessed to multivariate analysis towards breast cancer screening

Mortality due to breast cancer could be reduced via screening programs where preliminary clinical tests employed in an asymptomatic well-population with the objective of identifying cancer biomarkers could allow earlier referral of women with altered results for deeper clinical analysis and treatment. The introduction of well-population screening using new and less-invasive technologies as a strategy for earlier detection of breast cancer is thus highly desirable. Herein, spectrochemical analyses harnessed to multivariate classification techniques are used as a bio-analytical tool for a Breast Cancer Screening Program using liquid biopsy in the form of blood plasma samples collected from 476 patients recruited over a 2-year period. This methodology is based on acquiring and analysing the spectrochemical fingerprint of plasma samples by attenuated total reflection Fourier-transform infrared spectroscopy; derived spectra reflect intrinsic biochemical composition, generating information on nucleic acids, carbohydrates, lipids and proteins. Excellent results in terms of sensitivity (94%) and specificity (91%) were obtained using this method in comparison with traditional mammography (88-93% and 85-94%, respectively). Additional advantages such as better disease prognosis thus allowing a more effective treatment, lower associated morbidity, fewer false-positive and false-negative results, lower-cost, and higher analytical frequency make this method attractive for translation to the clinical setting.