Personalized early detection and prevention of breast cancer: ENVISION consensus statement

Will Absolute Risk Estimation for Time to Next Screen Work for an Asian Mammography Screening Population?

Personalized breast cancer risk profiling has the potential to promote shared decision-making and improve compliance with routine screening. We assessed the Gail model's performance in predicting the short-term (2- and 5-year) and the long-term (10- and 15-year) absolute risks in 28,234 asymptomatic Asian women. Absolute risks were calculated using different relative risk estimates and Breast cancer incidence and mortality rates (White, Asian-American, or the Singapore Asian population). Using linear models, we tested the association of absolute risk and age at breast cancer occurrence. Model discrimination was moderate (AUC range: 0.580-0.628). Calibration was better for longer-term prediction horizons (E/O_{long-term ranges}: 0.86-1.71; E/O_{short-term ranges}:1.24-3.36). Subgroup analyses show that the model underestimates risk in women with breast cancer family history, positive recall status, and prior breast biopsy, and overestimates risk in underweight women. The Gail model absolute risk does not predict the age of breast cancer occurrence. Breast cancer risk prediction tools performed better with population-specific parameters. Two-year absolute risk estimation is attractive for breast cancer screening programs, but the models tested are not suitable for identifying Asian women at increased risk within this short interval.

Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival

PURPOSE

A polygenic risk score (PRS) consisting of 313 common genetic variants (PRS313) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS313 with clinicopathologic characteristics of, and survival following, breast cancer.

METHODS

Women with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS313 and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS313 (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment.

RESULTS

The PRS313 was associated with more favorable tumor characteristics. In BCAC, increasing PRS313 was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS313 was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS313 was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent.

CONCLUSION

An increased PRS313 is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS313 has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS313 as increasing PRS313 is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.

Natural Products in Precision Oncology: Plant-Based Small Molecule Inhibitors of Protein Kinases for Cancer Chemoprevention

Striking progress is being made in cancer treatment by using small molecule inhibitors of specific protein kinases that are products of genes recognized as drivers for a specific type of cancer. However, the cost of newly developed drugs is high, and these pharmaceuticals are neither affordable nor accessible in most parts of the world. Accordingly, this narrative review aims to probe how these recent successes in cancer treatment can be reverse-engineered into affordable and accessible approaches for the global community. This challenge is addressed through the lens of cancer chemoprevention, defined as using pharmacological agents of natural or synthetic origin to impede, arrest, or reverse carcinogenesis at any stage in the disease process. In this regard, prevention refers to reducing cancer-related deaths. Recognizing the clinical successes and limitations of protein kinase inhibitor treatment strategies, the disciplines of pharmacognosy and chemotaxonomy are juxtaposed with current efforts to exploit the cancer kinome to describe a conceptual framework for developing a natural product-based approach for precision oncology.

Acceptability of risk stratification within population-based cancer screening from the perspective of healthcare professionals: A mixed methods systematic review and recommendations to support implementation

BACKGROUND

Introduction of risk stratification within population-based cancer screening programmes has the potential to optimise resource allocation by targeting screening towards members of the population who will benefit from it most. Endorsement from healthcare professionals is necessary to facilitate successful development and implementation of risk-stratified interventions. Therefore, this review aims to explore whether using risk stratification within population-based cancer screening programmes is acceptable to healthcare professionals and to identify any requirements for successful implementation.

METHODS

We searched four electronic databases from January 2010 to October 2021 for quantitative, qualitative, or primary mixed methods studies reporting healthcare professional and/or other stakeholder opinions on acceptability of risk-stratified population-based cancer screening. Quality of the included studies was assessed using the Mixed Methods Appraisal Tool. Data were analysed using the Joanna Briggs Institute convergent integrated approach to mixed methods analysis and mapped onto the Consolidated Framework for Implementation Research using a 'best fit' approach. PROSPERO record CRD42021286667.

RESULTS

A total of 12,039 papers were identified through the literature search and seven papers were included in the review, six in the context of breast cancer screening and one considering screening for ovarian cancer. Risk stratification was broadly considered acceptable, with the findings covering all five domains of the framework: intervention characteristics, outer setting, inner setting, characteristics of individuals, and process. Across these five domains, key areas that were identified as needing further consideration to support implementation were: a need for greater evidence, particularly for de-intensifying screening; resource limitations; need for staff training and clear communication; and the importance of public involvement.

CONCLUSIONS

Risk stratification of population-based cancer screening programmes is largely acceptable to healthcare professionals, but support and training will be required to successfully facilitate implementation. Future research should focus on strengthening the evidence base for risk stratification, particularly in relation to reducing screening frequency among low-risk cohorts and the acceptability of this approach across different cancer types.

Circ_0001667 accelerates breast cancer proliferation and angiogenesis through regulating CXCL10 expression by sponging miR-6838-5p

BACKGROUND

An increasing number of circular RNAs (circRNAs) have been shown to play an important role in the tumorigenesis of breast cancer. The aim of this study was to investigate the expression and function of circ_0001667 and its potential molecular mechanisms in breast cancer.

METHODS

The expression levels of circ_0001667, miR-6838-5p and CXC chemokine ligand 10 (CXCL10) in breast cancer tissues and cells were detected by quantitative real-time PCR. Cell counting kit-8 assay, EdU assay, flow cytometry, colony formation and tube formation assays were used to detect cell proliferation and angiogenesis. The binding relationship between miR-6838-5p and circ_0001667 or CXCL10 was predicted using the starBase3.0 database and verified by dual-luciferase reporter gene assay, RIP and RNA pulldown. Animal experiments were performed to assess the function of circ_0001667 knockdown on breast cancer tumor growth.

RESULTS

Circ_0001667 was highly expressed in breast cancer tissues and cells, and its knockdown inhibited proliferation and angiogenesis of breast cancer cells. Circ_0001667 sponged miR-6838-5p, and inhibition of miR-6838-5p reversed the inhibitory effect of silencing circ_0001667 on proliferation and angiogenesis of breast cancer cells. MiR-6838-5p targeted CXCL10, and overexpression of CXCL10 reverses the effect of miR-6838-5p overexpression on breast cancer cell proliferation and angiogenesis. In addition, circ_0001667 interference also reduced breast cancer tumor growth in vivo.

CONCLUSION

Circ_0001667 is involved in breast cancer cell proliferation and angiogenesis through regulation of the miR-6838-5p/CXCL10 axis.

Breast Density Analysis Using Digital Breast Tomosynthesis

We evaluated an automated percentage of breast density (BD) technique (PDa) with digital breast tomosynthesis (DBT) data. The approach is based on the wavelet expansion followed by analyzing signal dependent noise. Several measures were investigated as risk factors: normalized volumetric; total dense volume; average of the DBT slices (slice-mean); a two-dimensional (2D) metric applied to the synthetic images; and the mean and standard deviations of the pixel values. Volumetric measures were derived theoretically, and PDa was modeled as a function of compressed breast thickness. An alternative method for constructing synthetic 2D mammograms was investigated using the volume results. A matched case-control study (n = 426 pairs) was analyzed. Conditional logistic regression modeling, controlling body mass index and ethnicity, was used to estimate odds ratios (ORs) for each measure with 95% confidence intervals provided parenthetically. There were several significant findings: volumetric measure [OR = 1.43 (1.18, 1.72)], which produced an identical OR as the slice-mean measure as predicted; [OR =1.44 (1.18, 1.75)] when applied to the synthetic images; and mean of the pixel values (volume or 2D synthetic) [ORs ~ 1.31 (1.09, 1.57)]. PDa was modeled as 2nd degree polynomial (concave-down): its maximum value occurred at 0.41×(compressed breast thickness), which was similar across case-control groups, and was significant from this position [OR = 1.47 (1.21, 1.78)]. A standardized 2D synthetic image was produced, where each pixel value represents the percentage of BD above its location. The significant findings indicate the validity of the technique. Derivations supported by empirical analyses produced a new synthetic 2D standardized image technique. Ancillary to the objectives, the results provide evidence for understanding the percentage of BD measure applied to 2D mammograms. Notwithstanding the findings, the study design provides a template for investigating other measures such as texture.

Psychological impact of risk-stratified screening as part of the NHS Breast Screening Programme: multi-site non-randomised comparison of BC-Predict versus usual screening (NCT04359420)

BACKGROUND

Adding risk stratification to standard screening via the NHS Breast Screening Programme (NHSBSP) allows women at higher risk to be offered additional prevention and screening options. It may, however, introduce new harms such as increasing cancer worry. The present study aimed to assess whether there were differences in self-reported harms and benefits between women offered risk stratification (BC-Predict) compared to women offered standard NHSBSP, controlling for baseline values.

METHODS

As part of the larger PROCAS2 study (NCT04359420), 5901 women were offered standard NHSBSP or BC-Predict at the invitation to NHSBSP. Women who took up BC-Predict received 10-year risk estimates: "high" (≥8%), "above average (moderate)" (5-7.99%), "average" (2-4.99%) or "below average (low)" (<2%) risk. A subset of 662 women completed questionnaires at baseline and at 3 months (n = 511) and 6 months (n = 473).

RESULTS

State anxiety and cancer worry scores were low with no differences between women offered BC-Predict or NHSBSP. Women offered BC-Predict and informed of being at higher risk reported higher risk perceptions and cancer worry than other women, but without reaching clinical levels.

CONCLUSIONS

Concerns that risk-stratified screening will produce harm due to increases in general anxiety or cancer worry are unfounded, even for women informed that they are at high risk.

Risk-Reducing Breast and Gynecological Surgery for BRCA Mutation Carriers: A Narrative Review

This narrative review aims to clarify the role of breast and gynecological risk-reduction surgery in BRCA mutation carriers. We examine the indications, contraindications, complications, technical aspects, timing, economic impact, ethical issues, and prognostic benefits of the most common prophylactic surgical options from the perspectives of a breast surgeon and a gynecologist. A comprehensive literature review was conducted using the PubMed/Medline, Scopus, and EMBASE databases. The databases were explored from their inceptions to August 2022. Three independent reviewers screened the items and selected those most relevant to this review's scope. BRCA1/2 mutation carriers are significantly more likely to develop breast, ovarian, and serous endometrial cancer. Because of the Angelina effect, there has been a significant increase in bilateral risk-reducing mastectomy (BRRM) since 2013. BRRM and risk-reducing salpingo-oophorectomy (RRSO) significantly reduce the risk of developing breast and ovarian cancer. RRSO has significant side effects, including an impact on fertility and early menopause (i.e., vasomotor symptoms, cardiovascular disease, osteoporosis, cognitive impairment, and sexual dysfunction). Hormonal therapy can help with these symptoms. Because of the lower risk of developing breast cancer in the residual mammary gland tissue after BRRM, estrogen-only treatments have an advantage over an estrogen/progesterone combined treatment. Risk-reducing hysterectomy allows for estrogen-only treatments and lowers the risk of endometrial cancer. Although prophylactic surgery reduces the cancer risk, it has disadvantages associated with early menopause. A multidisciplinary team must carefully inform the woman who chooses this path of the broad spectrum of implications, from cancer risk reduction to hormonal therapies.

The prognostic value and response to immunotherapy of immunogenic cell death-associated genes in breast cancer

Breast cancer (BRCA) remains the most prevalent cancer worldwide and the tumor microenvironment (TME) has been discovered to exert a wide influence on the overall survival and therapeutic response. Numerous lines of evidence reported that the effects of immunotherapy of BRCA were manipulated by TME. Immunogenic cell death (ICD) is a form of regulated cell death (RCD) that is capable of fueling adaptive immune responses and aberrant expression of ICD-related genes (ICDRGs) can govern the TME system by emitting danger signals or damage-associated molecular patterns (DAMPs). In the current study, we obtained 34 key ICDRGs in BRCA. Subsequently, using the transcriptome data of BRCA from the TCGA database, we constructed a risk signature based on 6 vital ICDRGs, which had a good performance in predicting the overall survival of BRCA patients. We also examined the efficacy of our risk signature in the validation dataset (GSE20711) in the GEO database and it performed excellently. According to the risk model, patients with BRCA were divided into high-risk and low-risk groups. Also, the unique immune characteristics and TME between the two subgroups and 10 promising small molecule drugs targeting BRCA patients with different ICDRGs risk have been investigated. The low-risk group had good immunity indicated by T cell infiltration and high immune checkpoint expression. Moreover, the BRCA samples could be divided into three immune subtypes according to immune response severity (ISA, ISB, and ISC). ISA and ISB predominated in the low-risk group and patients in the low-risk group exhibited a more vigorous immune response. In conclusion, we developed an ICDRGs-based risk signature that can predict the prognosis of BRCA patients and offer a novel therapeutic strategy for immunotherapy, which would be of great significance in the BRCA clinical setting.

Insurance Coverage of Prophylactic Mastectomies: A National Review of the United States

BACKGROUND

Breast cancer is associated with a multitude of risk factors, such as genetic predisposition and mutations, family history, personal medical history, or previous radiotherapy. A prophylactic mastectomy (PM) may be considered a suitable risk-reducing procedure in some cases. However, there are significant discrepancies between national society recommendations and insurance company requirements for PM.

MATERIALS AND METHODS

The authors conducted a cross-sectional analysis of insurance policies for a PM. One-hundred companies were selected based on the greatest state enrolment and market share. Their policies were identified through a Web-based search and telephone interviews, and their medical necessity criteria were extracted.

RESULTS

Preauthorized coverage of PMs was provided by 39% of insurance policies (n = 39) and 5 indications were identified. There was consensus amongst these policies to cover a PM for BRCA1/2 mutations (n = 39, 100%), but was more variable for other genetic mutations (15%-90%). Coverage of PM for the remaining indications varied among insurers: previous radiotherapy (92%), pathological changes in the breast (3%-92%), personal history of cancer (64%) and family history risk factors (39%-51%).

CONCLUSION

There is a marked level of variability in both the indications and medical necessity criteria for PM insurance policies. The decision to undergo a PM must be carefully considered with a patient's care team and should not be affected by insurance coverage status.

Construction of a DNA damage repair gene signature for predicting prognosis and immune response in breast cancer

DNA damage repair (DDR) genes are involved in developing breast cancer. Recently, a targeted therapeutic strategy through DNA repair machinery, including PARPi, has initially shown broad development and application prospects in breast cancer therapy. However, few studies that focused on the correlation between the expression level of DNA repair genes, prognosis, and immune response in breast cancer patients have been recently conducted. Herein, we focused on identifying differentially expressed DNA repair genes (DEGs) in breast cancer specimens and normal samples using the Wilcoxon rank-sum test. Biofunction enrichment analysis was performed with DEGs using the R software "cluster Profiler" package. DNA repair genes were involved in multivariate and univariate Cox regression analyses. After the optimization by AIC value, 11 DNA repair genes were sorted as prognostic DNA repair genes for breast cancer patients to calculate risk scores. Simultaneously, a nomogram was used to represent the prognostic model, which was validated using a calibration curve and C-index. Single-sample gene set enrichment analysis (ssGSEA), CIBERSORT algorithms, and ESTIMATE scores were applied to evaluate the immune filtration of tumor samples. Subsequently, anticarcinogen sensitivity analysis was performed using the R software "pRRophetic" package. Unsupervised clustering was used to excavate the correlation between the expression level of prognostic-significant DNA repair genes and clinical features. In summary, 56 DEGs were sorted, and their potential enriched biofunction pathways were revealed. In total, 11 DNA repair genes (UBE2A, RBBP8, RAD50 , FAAP20, RPA3, ENDOV, DDB2, UBE2V2, MRE11 , RRM2B, and PARP3 ) were preserved as prognostic genes to estimate risk score, which was applied to establish the prognostic model and stratified breast cancer patients into two groups with high or low risk. The calibration curve and C-index indicated that they reliably predicted the survival of breast cancer patients. Immune filtration analysis, anticarcinogen sensitivity analysis, and unsupervised clustering were applied to reveal the character of DNA repair genes between low- and high-risk groups. We identified 11 prognosis-significant DNA repair genes to establish prediction models and immune responses in breast cancer patients.

Vision-Transformer-Based Transfer Learning for Mammogram Classification

Breast mass identification is a crucial procedure during mammogram-based early breast cancer diagnosis. However, it is difficult to determine whether a breast lump is benign or cancerous at early stages. Convolutional neural networks (CNNs) have been used to solve this problem and have provided useful advancements. However, CNNs focus only on a certain portion of the mammogram while ignoring the remaining and present computational complexity because of multiple convolutions. Recently, vision transformers have been developed as a technique to overcome such limitations of CNNs, ensuring better or comparable performance in natural image classification. However, the utility of this technique has not been thoroughly investigated in the medical image domain. In this study, we developed a transfer learning technique based on vision transformers to classify breast mass mammograms. The area under the receiver operating curve of the new model was estimated as 1 ± 0, thus outperforming the CNN-based transfer-learning models and vision transformer models trained from scratch. The technique can, hence, be applied in a clinical setting, to improve the early diagnosis of breast cancer.

Screening Programs for Breast Cancer: Toward Individualized, Risk-Adapted Strategies of Early Detection

Early detection of breast cancer (BC) comprises two approaches: screening of asymptomatic women in a specified target population at risk (usually a target age range for women at average risk), and early diagnosis for women with BC signs and symptoms. Screening for BC is a key health intervention for early detection. While population-based screening programs have been implemented for age-selected women, the pivotal clinical trials have not addressed the global utility nor the improvement of screening performance by utilizing more refined parameters for patient eligibility, such as individualized risk stratification. In addition, with the exception of the subset of women known to carry germline pathogenetic mutations in (high- or moderately-penetrant) cancer predisposition genes, such as BRCA1 and BRCA2, there has been less success in outreach and service provision for the unaffected relatives of women found to carry a high-risk mutation (i.e., "cascade testing") as it is in these individuals for whom such actionable information can result in cancers (and/or cancer deaths) being averted. Moreover, even in the absence of clinical cancer genetics services, as is the case for the immediate and at least near-term in most countries globally, the capacity to stratify the risk of an individual to develop BC has existed for many years, is available for free online at various sites/platforms, and is increasingly being validated for non-Caucasian populations. Ultimately, a precision approach to BC screening is largely missing. In the present chapter, we aim to address the concept of risk-adapted screening of BC, in multiple facets, and understand if there is a value in the implementation of adapted screening strategies in selected women, outside the established screening prescriptions, in the terms of age-range, screening modality and schedules of imaging.

Artificial intelligence for digital breast tomosynthesis: Impact on diagnostic performance, reading times, and workload in the era of personalized screening

The ultimate goals of the application of artificial intelligence (AI) to digital breast tomosynthesis (DBT) are the reduction of reading times, the increase of diagnostic performance, and the reduction of interval cancer rates. In this review, after outlining the journey from computer-aided detection/diagnosis systems to AI applied to digital mammography (DM), we summarize the results of studies where AI was applied to DBT, noting that long-term advantages of DBT screening and its crucial ability to decrease the interval cancer rate are still under scrutiny. AI has shown the capability to overcome some shortcomings of DBT in the screening setting by improving diagnostic performance and by reducing recall rates (from -2 % to -27 %) and reading times (up to -53 %, with an average 20 % reduction), but the ability of AI to reduce interval cancer rates has not yet been clearly investigated. Prospective validation is needed to assess the cost-effectiveness and real-world impact of AI models assisting DBT interpretation, especially in large-scale studies with low breast cancer prevalence. Finally, we focus on the incoming era of personalized and risk-stratified screening that will first see the application of contrast-enhanced breast imaging to screen women with extremely dense breasts. As the diagnostic advantage of DBT over DM was concentrated in this category, we try to understand if the application of AI to DM in the remaining cohorts of women with heterogeneously dense or non-dense breast could close the gap in diagnostic performance between DM and DBT, thus neutralizing the usefulness of AI application to DBT.

Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature

This systematic review aimed to assess the methods used to classify mammographic breast parenchymal features in relation to the prediction of future breast cancer. The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021 to extract published articles in English describing the relationship of parenchymal texture features with the risk of breast cancer. Twenty-eight articles published since 2016 were included in the final review. The identification of parenchymal texture features varied from using a predefined list to machine-driven identification. A reduction in the number of features chosen for subsequent analysis in relation to cancer incidence then varied across statistical approaches and machine learning methods. The variation in approach and number of features identified for inclusion in analysis precluded generating a quantitative summary or meta-analysis of the value of these features to improve predicting risk of future breast cancers. This updated overview of the state of the art revealed research gaps; based on these, we provide recommendations for future studies using parenchymal features for mammogram images to make use of accumulating image data, and external validation of prediction models that extend to 5 and 10 years to guide clinical risk management. Following these recommendations could enhance the applicability of models, helping improve risk classification and risk prediction for women to tailor screening and prevention strategies to the level of risk.

A Review of Margetuximab-Based Therapies in Patients with HER2-Positive Metastatic Breast Cancer

Breast cancer (BC) is the most commonly diagnosed cancer globally, with high mortality rates. Targeted drug therapies have revolutionized cancer treatment. For example, treatment with human epidermal receptor 2 (HER2) antagonists has markedly improved the prognosis of patients with HER2-positive BC (HER2 + BC). However, HER2+ metastatic BC (MBC) remains prevalent owing to its resistance to conventional anti-HER2 drugs. Therefore, novel agents are needed to overcome the limitations of existing cancer treatments and to enhance the progression-free and overall survival rates. Progress has been made by optimizing the fragment crystallizable (Fc) domain of trastuzumab, an IgG1 monoclonal, chimeric anti-HER2 antibody, to develop margetuximab. The modified Fc domain of margetuximab enhances its binding affinity to CD16A and decreases its binding affinity to CD32B, thereby promoting its antitumor activity. This review summarizes studies on the efficacy of margetuximab, discusses its utility as an anti-HER2 monoclonal antibody drug for the treatment of HER2 + BC, and presents the latest advances in the treatment of BC. This review provides insights into the clinical implication of margetuximab in HER2 + MBC treatment.

Breast cancer incidence among women with a family history of breast cancer by relative's age at diagnosis

BACKGROUND

Women with a first-degree family history of breast cancer are often advised to begin screening when they are 10 years younger than the age at which their relative was diagnosed. Evidence is lacking to determine how much earlier they should begin.

METHODS

Using Breast Cancer Surveillance Consortium data on screening mammograms from 1996 to 2016, the authors constructed a cohort of 306,147 women 30-59 years of age with information on first-degree family history of breast cancer and relative's age at diagnosis. The authors compared cumulative 5-year breast cancer incidence among women with and without a first-degree family history of breast by relative's age at diagnosis and by screening age.

RESULTS

Among 306,147 women included in the study, approximately 11% reported a first-degree family history of breast cancer with 3885 breast cancer cases identified. Women reporting a relative diagnosed between 40 and 49 years and undergoing screening between ages 30 and 39 or 40 and 49 had similar 5-year cumulative incidences of breast cancer (respectively, 18.6/1000; 95% confidence interval [CI], 12.1, 25.7; 18.4/1000; 95% CI, 13.7, 23.5) as women without a family history undergoing screening between 50-59 years of age (18.0/1000; 95% CI, 17.0, 19.1). For relative's diagnosis age from 35 to 45 years of age, initiating screening 5-8 years before diagnosis age resulted in a 5-year cumulative incidence of breast cancer of 15.2/1000, that of an average 50-year-old woman.

CONCLUSION

Women with a relative diagnosed at or before age 45 may wish to consider, in consultation with their provider, initiating screening 5-8 years earlier than their relative's diagnosis age.

Construction of an immunogenic cell death-based risk score prognosis model in breast cancer

Immunogenic cell death (ICD) is a form of regulated cell death that elicits immune response. Common inducers of ICD include cancer chemotherapy and radiation therapy. A better understanding of ICD might contribute to modify the current regimens of anti-cancer therapy, especially immunotherapy. This study aimed to identify ICD-related prognostic gene signatures in breast cancer (BC). An ICD-based gene prognostic signature was developed using Lasso-cox regression and Kaplan-Meier survival analysis based on datasets acquired from the Cancer Genome Atlas and Gene Expression Omnibus. A nomogram model was developed to predict the prognosis of BC patients. Gene Set Enrichment Analysis (GESA) and Gene Set Variation Analysis (GSVA) were used to explore the differentially expressed signaling pathways in high and low-risk groups. CIBERSORT and ESTIMATE algorithms were performed to investigate the difference of immune status in tumor microenvironment of different risk groups. Six genes (CALR, CLEC9A, BAX, TLR4, CXCR3, and PIK3CA) were selected for construction and validation of the prognosis model of BC based on public data. GSEA and GSVA analysis found that immune-related gene sets were enriched in low-risk group. Moreover, immune cell infiltration analysis showed that the immune features of the high-risk group were characterized by higher infiltration of tumor-associated macrophages and a lower proportion of CD8⁺ T cells, suggesting an immune evasive tumor microenvironment. We constructed and validated an ICD-based gene signature for predicting prognosis of breast cancer patients. Our model provides a tool with good discrimination and calibration abilities to predict the prognosis of BC, especially triple-negative breast cancer (TNBC).

The co-development of personalised 10-year breast cancer risk communications: a 'think-aloud' study

BACKGROUND

Risk stratified breast cancer screening is being considered as a means of improving the balance of benefits and harms of mammography. Stratified screening requires the communication of risk estimates. We aimed to co-develop personalised 10-year breast cancer risk communications for women attending routine mammography.

METHODS

We conducted think-aloud interviews on prototype breast cancer risk letters and accompanying information leaflets with women receiving breast screening through the UK National Breast Screening Programme. Risk information was redesigned following feedback from 55 women in three iterations. A deductive thematic analysis of participants' speech is presented.

RESULTS

Overall, participants appreciated receiving their breast cancer risk. Their comments focused on positive framing and presentation of the risk estimate, a desire for detail on the contribution of individual risk factors to overall risk and effective risk management strategies, and clearly signposted support pathways.

CONCLUSION

Provision of breast cancer risk information should strive to be personal, understandable and meaningful. Risk information should be continually refined to reflect developments in risk management. Receipt of risk via letter is welcomed but concerns remain around the acceptability of informing women at higher risk in this way, highlighting a need for co-development of risk dissemination and support pathways.

Enhancing the BOADICEA cancer risk prediction model to incorporate new data on RAD51C, RAD51D, BARD1 updates to tumour pathology and cancer incidence

BACKGROUND

BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) for breast cancer and the epithelial tubo-ovarian cancer (EOC) models included in the CanRisk tool (www.canrisk.org) provide future cancer risks based on pathogenic variants in cancer-susceptibility genes, polygenic risk scores, breast density, questionnaire-based risk factors and family history. Here, we extend the models to include the effects of pathogenic variants in recently established breast cancer and EOC susceptibility genes, up-to-date age-specific pathology distributions and continuous risk factors.

METHODS

BOADICEA was extended to further incorporate the associations of pathogenic variants in BARD1, RAD51C and RAD51D with breast cancer risk. The EOC model was extended to include the association of PALB2 pathogenic variants with EOC risk. Age-specific distributions of oestrogen-receptor-negative and triple-negative breast cancer status for pathogenic variant carriers in these genes and CHEK2 and ATM were also incorporated. A novel method to include continuous risk factors was developed, exemplified by including adult height as continuous.

RESULTS

BARD1, RAD51C and RAD51D explain 0.31% of the breast cancer polygenic variance. When incorporated into the multifactorial model, 34%-44% of these carriers would be reclassified to the near-population and 15%-22% to the high-risk categories based on the UK National Institute for Health and Care Excellence guidelines. Under the EOC multifactorial model, 62%, 35% and 3% of PALB2 carriers have lifetime EOC risks of <5%, 5%-10% and >10%, respectively. Including height as continuous, increased the breast cancer relative risk variance from 0.002 to 0.010.

CONCLUSIONS

These extensions will allow for better personalised risks for BARD1, RAD51C, RAD51D and PALB2 pathogenic variant carriers and more informed choices on screening, prevention, risk factor modification or other risk-reducing options.

Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study

BACKGROUND

The multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort.

METHODS

We validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45-63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes: BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D and BARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC).

RESULTS

Among the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%).

CONCLUSION

The multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.

What are the views of three key stakeholder groups on extending the breast screening interval for low-risk women? A secondary qualitative analysis

INTRODUCTION

There is increasing interest in risk-stratified breast screening, whereby the prevention and early detection offers vary by a woman's estimated risk of breast cancer. To date, more focus has been directed towards high-risk screening pathways rather than considering women at lower risk, who may be eligible for extended screening intervals. This secondary data analysis aimed to compare the views of three key stakeholder groups on how extending screening intervals for low-risk women should be implemented and communicated as part of a national breast screening programme.

METHODS

Secondary data analysis of three qualitative studies exploring the views of distinct stakeholder groups was conducted. Interviews took place with 23 low-risk women (identified from the BC-Predict study) and 17 national screening figures, who were involved in policy-making and implementation. In addition, three focus groups and two interviews were conducted with 26 healthcare professionals. A multiperspective thematic analysis was conducted to identify similarities and differences between stakeholders.

FINDINGS

Three themes were produced: Questionable assumptions about negative consequences, highlighting how other stakeholders lack trust in how women are likely to understand extended screening intervals; Preserving the integrity of the programme, centring on decision-making and maintaining a positive reputation of breast screening and Negotiating a communication pathway highlighting communication expectations and public campaign importance.

CONCLUSIONS

A risk-stratified screening programme should consider how best to engage women assessed as having a low risk of breast cancer to ensure mutual trust, balance the practicality of change whilst ensuring acceptability, and carefully develop multilevel inclusive communication strategies.

PATIENT AND PUBLIC CONTRIBUTION

The research within this paper involved patient/public contributors throughout including study design and materials input.

UNCAN.eu, a European Initiative to UNderstand CANcer

"UNCAN.eu" refers to a collective European effort seeking to enable a leap forward in our understanding of cancer. This initiative, which includes the creation of a European cancer research data hub, will pave the way to new advances in cancer care. Starting on September 1, 2022, a 15-month coordination and support action will generate a blueprint for UNCAN.eu. Here, we summarize the cancer research issues that the blueprint will propose to tackle at the European level.

Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition

PURPOSE

Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases.

MATERIALS AND METHODS

Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution.

RESULTS

In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; P = 8.6 × 10-308) and within each major ancestry. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women.

CONCLUSION

The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.

Healthcare professionals' views following implementation of risk stratification into a national breast cancer screening programme

Background

It is crucial to determine feasibility of risk-stratified screening to facilitate successful implementation. We introduced risk-stratification (BC-Predict) into the NHS Breast Screening Programme (NHSBSP) at three screening sites in north-west England from 2019 to 2021. The present study investigated the views of healthcare professionals (HCPs) on acceptability, barriers, and facilitators of the BC-Predict intervention and on the wider implementation of risk-based screening after BC-Predict was implemented in their screening site.

Methods

Fourteen semi-structured interviews were conducted with HCPs working across the breast screening pathway at three NHSBSP sites that implemented BC-Predict. Thematic analysis interpreted the data.

Results

Three pre-decided themes were produced. (1) Acceptability of risk-based screening: risk-stratification was perceived as a beneficial step for both services and women. HCPs across the pathway reported low burden of running the BC-Predict trial on routine tasks, but with some residual concerns; (2) Barriers to implementation: comprised capacity constraints of services including the inadequacy of current IT systems to manage women with different risk profiles and, (3) Facilitators to implementation: included the continuation of stakeholder consultation across the pathway to inform implementation and need for dedicated risk screening admin staff, a push for mammography staff recruitment and guidance for screening services. Telephone helplines, integrating primary care, and supporting access for all language needs was emphasised.

Conclusion

Risk-stratified breast screening was viewed as a progressive step providing it does not worsen inequalities for women. Implementation of risk-stratified breast screening requires staff to be reassured that there will be systems in place to support implementation and that it will not further burden their workload. Next steps require a comprehensive assessment of the resource needed for risk-stratification versus current resource availability, upgrades to screening IT and building screening infrastructure. The role of primary care needs to be determined. Simplification and clarification of risk-based screening pathways is needed to support HCPs agency and facilitate implementation. Forthcoming evidence from ongoing randomised controlled trials assessing effectiveness of breast cancer risk-stratification will also determine implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10134-0.

A systematic assessment of online international breast density information

BACKGROUND

Breast density has become a topic of international discussion due to its associated risk of breast cancer. As online is often a primary source of women's health information it is therefore essential that breast density information it is understandable, accurate and reflects the best available evidence. This study aimed to systematically assess online international breast density information including recommendations to women.

METHODS

Searches were conducted from five different English-speaking country-specific Google locations. Relevant breast density information was extracted from the identified websites. Readability was assessed using the SHeLL Editor, and understandability and actionability using the Patient Education Materials Assessment Tool (PEMAT). A content analysis of specific recommendations to women was also conducted.

RESULTS

Forty-two eligible websites were identified and systematically assessed. The included informational content varied across websites. The average grade reading level across all websites was 12.4 (range 8.9-15.4). The mean understandability was 69.9% and the mean actionability was 40.1%, with 18/42 and 39/42 websites respectively scoring lower than adequate (70%). Thirty-six (85.7%) of the websites had breast density-related recommendation to women, with 'talk to your doctor' (n = 33, 78.6%) the most common.

CONCLUSIONS

Online information about breast density varies widely and is not generally presented in a way that women can easily understand and act on, therefore greatly reducing the ability for informed decision-making. International organisations and groups disseminating breast density information need to ensure that women are presented with health literacy-sensitive and balanced information, and be aware of the impact that recommendations may have on practice.

[PAPPS Expert Groups. Cancer prevention recommendations: Update 2022]

Cancer is a major cause of morbidity and mortality. Tobacco use, unhealthy diet, and physical inactivity are some of the lifestyle risk factors that have led to an increase in cancer. This article updates the evidence and includes recommendations for prevention strategies for each of the cancers with the highest incidence. These are based on the reduction of risk factors (primary prevention) and early diagnosis of cancer through screening and early detection of signs and symptoms, in medium-risk and high-risk populations. This update of the 2022 PAPPS has taken into account the vision of the National Health System Cancer Strategy, an update approved by the Interterritorial Council of the National Health System on January 2021 and the European Strategy (Europe's Beating Cancer Plan) presented on 4 February 2021.

External Validation of a Mammography-Derived AI-Based Risk Model in a U.S. Breast Cancer Screening Cohort of White and Black Women

Despite the demonstrated potential of artificial intelligence (AI) in breast cancer risk assessment for personalizing screening recommendations, further validation is required regarding AI model bias and generalizability. We performed external validation on a U.S. screening cohort of a mammography-derived AI breast cancer risk model originally developed for European screening cohorts. We retrospectively identified 176 breast cancers with exams 3 months to 2 years prior to cancer diagnosis and a random sample of 4963 controls from women with at least one-year negative follow-up. A risk score for each woman was calculated via the AI risk model. Age-adjusted areas under the ROC curves (AUCs) were estimated for the entire cohort and separately for White and Black women. The Gail 5-year risk model was also evaluated for comparison. The overall AUC was 0.68 (95% CIs 0.64−0.72) for all women, 0.67 (0.61−0.72) for White women, and 0.70 (0.65−0.76) for Black women. The AI risk model significantly outperformed the Gail risk model for all women p < 0.01 and for Black women p < 0.01, but not for White women p = 0.38. The performance of the mammography-derived AI risk model was comparable to previously reported European validation results; non-significantly different when comparing White and Black women; and overall, significantly higher than that of the Gail model.

Implementing Risk-Stratified Breast Screening in England: An Agenda Setting Meeting

It is now possible to accurately assess breast cancer risk at routine NHS Breast Screening Programme (NHSBSP) appointments, provide risk feedback and offer risk management strategies to women at higher risk. These strategies include National Institute for Health and Care Excellence (NICE) approved additional breast screening and risk-reducing medication. However, the NHSBSP invites nearly all women three-yearly, regardless of risk. In March 2022, a one-day agenda setting meeting took place in Manchester to discuss the feasibility and desirability of implementation of risk-stratified screening in the NHSBSP. Fifty-eight individuals participated (38 face-to-face, 20 virtual) with relevant expertise from academic, clinical and/or policy-making perspectives. Key findings were presented from the PROCAS2 NIHR programme grant regarding feasibility of risk-stratified screening in the NHSBSP. Participants discussed key uncertainties in seven groups, followed by a plenary session. Discussions were audio-recorded and thematically analysed to produce descriptive themes. Five themes were developed: (i) risk and health economic modelling; (ii) health inequalities and communication with women; (iii); extending screening intervals for low-risk women; (iv) integration with existing NHSBSP; and (v) potential new service models. Most attendees expected some form of risk-stratified breast screening to be implemented in England and collectively identified key issues to be resolved to facilitate this.

[CD40LG is a novel immune- and stroma-related prognostic biomarker in the tumor microenvironment of invasive breast cancer]

OBJECTIVE

To identify tumor microenvironment (TME)- related genes associated with the occurrence of invasive breast cancer as potential prognostic biomarkers and therapeutic targets.

METHODS

RNA transcriptome data and clinically relevant data were retrieved from TCGA database, and the StromalScore and ImmuneScore were calculated using the ESTIMATE algorithm. The differentially expressed genes (DEGs) were screened by taking the intersection. A protein- protein interaction network was established, and univariate COX regression analysis was used to identify the core genes among the DEGs. A core gene was selected for GSEA and CIBERSORT analysis to determine the function of the core gene and the proportion of tumor-infiltrating immune cells, respectively. Western blotting and qRT-PCR were performed to verify the expression level of CD40LG in breast cancer cell lines and clinical specimens.

RESULTS

A total of 1222 samples (124 normal and 1098 tumor samples) were extracted from TCGA for analysis, from which 487 DEGs were identified. These genes were mainly enriched in immune-related pathways, and crossover analysis identified 11 key genes (CD40LG, ITK, CD5, CD3E, SPN, IL7R, CD48, CCL19, CD2, CD52, and CD2711) associated with breast cancer TME status. CD40LG was selected as the core gene, whose high expression was found to be associated with a longer overall survival of breast cancer patients (P=0.002), and its expression level differed significantly with TNM stage and tumor size (P < 0.05). GSEA and CIBERSORT analyses indicated that CD40LG expression level was associated with immune activity in the TME. Western blotting and qRT-PCR showed that the protein and mRNA expression of CD40LG were significantly lower in breast cancer cells and cancer tissues than in normal breast cells and adjacent tissues.

CONCLUSIONS

The high expression of CD40LG in TME is positively correlated with the survival of patients with invasive breast cancer, suggesting its value as a potential new biomarker for predicting prognosis of the patients.

Considerations of biomarker application for cancer continuum in the era of precision medicine

Purpose of the review

The goal of this review is to highlight emerging biomarker research by the key phases of the cancer continuum and outline the methodological considerations for biomarker application.

Recent findings

While biomarkers have an established role in targeted therapy and to some extent, disease monitoring, their role in early detection and survivorship remains to be elucidated. With the advent of omics technology, the discovery of biomarkers has been accelerated exponentially, therefore careful consideration to ensure an unbiased study design and robust validity is crucial.

Summary

The rigor of biomarker research holds the key to the success of precision health care. The potential clinical utility and the feasibility of implementation should be central to future biomarker research study design.

Feasibility and Acceptability of Personalized Breast Cancer Screening (DECIDO Study): A Single-Arm Proof-of-Concept Trial

The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40-50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants' intention to participate in risk-based screening and satisfaction at 1-year were very high.

Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.

Does receiving high or low breast cancer risk estimates produce a reduction in subsequent breast cancer screening attendance? Cohort study

Risk-stratified breast cancer screening may improve the balance of screening benefits to harms.

We assess a potential new harm: reduced screening attendance in women receiving below average-risk (false reassurance) or higher-risk results (screening avoidance). Following initial screening, 26,668 women in the PROCAS study received breast cancer risk estimates, with attendance recorded for two subsequent screening rounds. First-screen attendance was slightly reduced in below-average (85.6%) but not higher-risk women, compared to other women (86.4%). Second-screen attendance increased for women at higher-risk (89.2%) but not below-average, compared to other women (78.8%). Concerns about this potential harm of risk-stratified screening therefore appear unfounded.

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A potential harm of risk-stratified screening is a reduction in future attendance.

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Some evidence of a small reduction in future attendance in below-average women.

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Large increase in attendance in higher-risk women at future screening rounds.

Personalized Approaches for the Prevention and Treatment of Breast Cancer

Breast cancer (BC) remains a major public health issue worldwide [...]

Molecular perspective on targeted therapy in breast cancer: a review of current status

Breast cancer is categorized at the molecular level according to the status of certain hormone and growth factor receptors, and this classification forms the basis of current diagnosis and treatment. The development of resistance to treatment and recurrence of the disease have led researchers to develop new therapies. In recent years, most of the research in the field of oncology has focused on the development of targeted therapies, which are treatment methods developed directly against molecular abnormalities. Promising advances have been made in clinical trials investigating the effect of these new treatment modalities and their combinations with existing therapeutic treatments in the treatment of breast cancer. Monoclonal antibodies, tyrosine kinase inhibitors, antibody–drug conjugates, PI3K/Akt/mTOR pathway inhibitors, cyclin-dependent kinase 4/6 inhibitors, anti-angiogenic drugs, PARP inhibitors are among the targeted therapies used in breast cancer treatment. In this review, we aim to present a molecular view of recently approved target agents used in breast cancer.

Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta-analysis

BACKGROUND

Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

METHODS

We conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

RESULTS

Our systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.

CONCLUSION

Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

Antiprogestins reduce epigenetic field cancerization in breast tissue of young healthy women

Background

Breast cancer is a leading cause of death in premenopausal women. Progesterone drives expansion of luminal progenitor cells, leading to the development of poor-prognostic breast cancers. However, it is not known if antagonising progesterone can prevent breast cancers in humans. We suggest that targeting progesterone signalling could be a means of reducing features which are known to promote breast cancer formation.

Methods

In healthy premenopausal women with and without a BRCA mutation we studied (i) estrogen and progesterone levels in saliva over an entire menstrual cycle (n = 20); (ii) cancer-free normal breast-tissue from a control population who had no family or personal history of breast cancer and equivalently from BRCA1/2 mutation carriers (n = 28); triple negative breast cancer (TNBC) biopsies and healthy breast tissue taken from sites surrounding the TNBC in the same individuals (n = 14); and biopsies of ER+ve/PR+ve stage T1–T2 cancers and healthy breast tissue taken from sites surrounding the cancer in the same individuals (n = 31); and (iii) DNA methylation and DNA mutations in normal breast tissue (before and after treatment) from clinical trials that assessed the potential preventative effects of vitamins and antiprogestins (mifepristone and ulipristal acetate; n = 44).

Results

Daily levels of progesterone were higher throughout the menstrual cycle of BRCA1/2 mutation carriers, raising the prospect of targeting progesterone signalling as a means of cancer risk reduction in this population. Furthermore, breast field cancerization DNA methylation signatures reflective of (i) the mitotic age of normal breast epithelium and (ii) the proportion of luminal progenitor cells were increased in breast cancers, indicating that luminal progenitor cells with elevated replicative age are more prone to malignant transformation. The progesterone receptor antagonist mifepristone reduced both the mitotic age and the proportion of luminal progenitor cells in normal breast tissue of all control women and in 64% of BRCA1/2 mutation carriers. These findings were validated by an alternate progesterone receptor antagonist, ulipristal acetate, which yielded similar results. Importantly, mifepristone reduced both the TP53 mutation frequency as well as the number of TP53 mutations in mitotic-age-responders.

Conclusions

These data support the potential usage of antiprogestins for primary prevention of poor-prognostic breast cancers.

Trial registration

Clinical trial 1 Mifepristone treatment prior to insertion of a levonorgestrel releasing intrauterine system for improved bleeding control – a randomized controlled trial, clinicaltrialsregister.eu, 2009-009014-40; registered on 20 July 2009.

Clinical trial 2 The effect of a progesterone receptor modulator on breast tissue in women with BRCA1 and 2 mutations, clinicaltrials.gov, NCT01898312; registered on 07 May 2013.

Clinical trial 3 A pilot prevention study of the effects of the anti- progestin Ulipristal Acetate (UA) on surrogate markers of breast cancer risk, clinicaltrialsregister.eu, 2015-001587-19; registered on 15 July 2015.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01063-5.

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.

Overdetection of Breast Cancer

Overdetection (often referred to as overdiagnosis) of cancer is the detection of disease, such as through a screening program, that would otherwise remain occult through an individual’s life. In the context of screening, this could occur for cancers that were slow growing or indolent, or simply because an unscreened individual would have died from some other cause before the cancer had surfaced clinically. The main harm associated with overdetection is the subsequent overdiagnosis and overtreatment of disease. In this article, the phenomenon is reviewed, the methods of estimation of overdetection are discussed and reasons for variability in such estimates are given, with emphasis on an analysis using Canadian data. Microsimulation modeling is used to illustrate the expected time course of cancer detection that gives rise to overdetection. While overdetection exists, the actual amount is likely to be much lower than the estimate used by the Canadian Task Force on Preventive Health Care. Furthermore, the issue is of greater significance in older rather than younger women due to competing causes of death. The particular challenge associated with in situ breast cancer is considered and possible approaches to avoiding overtreatment are suggested.

Study protocol comparing the ethical, psychological and socio-economic impact of personalised breast cancer screening to that of standard screening in the "My Personal Breast Screening" (MyPeBS) randomised clinical trial

Background

The MyPeBS study is an ongoing randomised controlled trial testing whether a risk-stratified breast cancer screening strategy is non-inferior, or eventually superior, to standard age-based screening at reducing incidence of stage 2 or more cancers. This large European Commission-funded initiative aims to include 85,000 women aged 40 to 70 years, without prior breast cancer and not previously identified at high risk in six countries (Belgium, France, Italy, Israel, Spain, UK). A specific work package within MyPeBS examines psychological, socio-economic and ethical aspects of this new screening strategy. It compares women’s reported data and outcomes in both trial arms on the following issues: general anxiety, cancer-related worry, understanding of breast cancer screening strategy and information-seeking behaviour, socio-demographic and economic characteristics, quality of life, risk perception, intention to change health-related behaviours, satisfaction with the trial.

Methods

At inclusion, 3-months, 1-year and 4-years, each woman participating in MyPeBS is asked to fill online questionnaires. Descriptive statistics, bivariate analyses, subgroup comparisons and analysis of variations over time will be performed with appropriate tests to assess differences between arms. Multivariate regression models will allow modelling of different patient reported data and outcomes such as comprehension of the information provided, general anxiety or cancer worry, and information seeking behaviour. In addition, a qualitative study (48 semi-structured interviews conducted in France and in the UK with women randomised in the risk-stratified arm), will help further understand participants’ acceptability and comprehension of the trial, and their experience of risk assessment.

Discussion

Beyond the scientific and medical objectives of this clinical study, it is critical to acknowledge the consequences of such a paradigm shift for women. Indeed, introducing a risk-based screening relying on individual biological differences also implies addressing non-biological differences (e.g. social status or health literacy) from an ethical perspective, to ensure equal access to healthcare. The results of the present study will facilitate making recommendations on implementation at the end of the trial to accompany any potential change in screening strategy.

Trial registration

Study sponsor: UNICANCER. My personalised breast screening (MyPeBS). Clinicaltrials.gov (2018) available at: https://clinicaltrials.gov/ct2/show/NCT03672331

Contact: Cécile VISSAC SABATIER, PhD, + 33 (0)1 73 79 77 58 ext + 330,142,114,293, contact@mypebs.eu.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09484-6.

The feasibility of implementing risk stratification into a national breast cancer screening programme: a focus group study investigating the perspectives of healthcare personnel responsible for delivery

BACKGROUND

Providing women with personalized estimates of their risk of developing breast cancer, as part of routine breast cancer screening programmes, allows women at higher risk to be offered more frequent screening or drugs to reduce risk. For this to be feasible, the concept and practicalities have to be acceptable to the healthcare professionals who would put it in to practice. The present research investigated the acceptability to healthcare professionals who were responsible for the implementation of this new approach to screening in the ongoing BC-Predict study.

METHODS

Four focus groups were conducted with 29 healthcare professionals from a variety of professional backgrounds working within three breast screening services in north-west England. An inductive-manifest thematic analysis was conducted.

RESULTS

Overall, healthcare professionals viewed the implementation of personalised breast cancer risk estimation as a positive step, but discussion focused on concerns. Three major themes are presented. (1) Service constraints highlights the limited capacity within current breast services and concerns about the impact of additional workload. (2) Risk communication concerns the optimal way to convey risk to women within resource constraints. (3) Accentuating inequity discusses how risk stratification could decrease screening uptake for underserved groups.

CONCLUSIONS

Staff who implemented risk stratification considered it a positive addition to routine screening. They considered it essential to consider improving capacity and demands on healthcare professional time. They highlighted the need for skilled communication of risks and new pathways of care to ensure that stratification could be implemented in financially and time constrained settings without impacting negatively on women.

[Moving toward personalized breast cancer screening: The role of Primary Care]

Breast cancer is the leading cause of death in the world among women. The Spanish National Health System (SNHS) introduced population-based breast cancer screening in 2006. As in most European programs, risk is identified on the basis of age and a mammogram is offered every two years to women aged 50-69 years. Scientific evidence is moving toward personalized screening, based on individual risk. This article presents the clinical trials that will evaluate the efficacy of personalized screening and some studies carried out in our environment on the effect of informing women of the benefits and adverse effects of screening or the acceptability and feasibility of offering personalized screening, in the Shared Decision Making context. The Preventive Activities and Health Promotion Program can help transform screening in our SNHS.

Evidence from a BreastScreen cohort does not support a longer inter-screen interval in women who have no conventional risk factors for breast cancer

Objectives

To determine screening outcomes in women who have no recorded risk factors for breast cancer.

Methods

A retrospective population-based cohort study included all 1,026,137 mammography screening episodes in 323,082 women attending the BreastScreen Western Australia (part of national biennial screening) program between July 2007 and June 2017. Cancer detection rates (CDR) and interval cancer rates (ICR) were calculated in screening episodes with no recorded risk factors for breast cancer versus at least one risk factor stratified by age. CDR was further stratified by timeliness of screening (<27 versus ≥27 months); ICR was stratified by breast density.

Results

Amongst 566,948 screens (55.3%) that had no recorded risk factors, 2347 (40.9%) screen-detected cancers were observed. In screens with no risk factors, CDR was 50 (95%CI 48–52) per 10,000 screens and ICR was 7.9 (95%CI 7.4–8.4) per 10,000 women-years, estimates that were lower than screens with at least one risk factor (CDR 83 (95%CI 80–86) per 10,000 screens, ICR 12.2 (95%CI 11.5–13.0) per 10,000 women-years). Compared to timely screens with risk factors, delayed screens with no risk factors had similar CDR across all age groups and a higher proportion of node positive cancers (26.1% vs 20.7%). ICR was lowest in screens that had no risk factors nor dense breasts in all age groups.

Conclusions

Majority of screens had no recorded breast cancer risk factors, hence a substantial proportion of screen-detected cancers occur in these screening episodes. Our findings may not justify less frequent screening in women with no risk factors.

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40.9% of screen-detected breast cancers occurred in women with no risk factors.

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Cancer detection rate was 50/10,000 in screens with no risk factors.

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Cancer size and nodal status were no more favourable in screens with no risk factors.

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Interval cancer rate was lowest in screens with no risk factors nor dense breasts.

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Our findings may not justify less frequent screening in women with no risk factors.

Transforming Passive into Active: Multimodal Pheophytin-Based Carbon Dots Customize Protein Corona to Target Metastatic Breast Cancer

Formation of protein corona on nanomaterials surface in vivo is usually considered as an unpredictable event for a predefined targeted delivery system for malignant cancers. In most situations, these protein coronas substantially change targeting efficiency or even cause adverse reactions which both hinder the clinical translation of the cargo-delivery systems. Active customization of protein corona onto nanomaterials surfaces can benefit their biomedical performances and open up new opportunities in construction of targeted delivery systems. Herein, lipid-PEG/pheophytin carbon dots (LPCDs) are prepared from natural chlorophyll and integrate seamlessly with positron emission tomography imaging, near-infrared fluorescence imaging, and photodynamic therapy capacity. In vitro measurements demonstrate that the LPCDs can actively absorb apolipoproteins into the protein corona to enhance their uptakes in breast cancer cells. In vivo studies confirm that LPCDs can give accurate delineation of metastatic breast cancer foci from surrounding normal tissues with multimodal biomedical functions. The feasibility of using LPCDs as a multimodal imaging and cancer-targeting nanoplatform may provide impetus for developing precise yet facile protein corona-targeted delivery systems for future clinical practice.

The future of early cancer detection

A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish inconsequential changes from lesions that will lead to life-threatening cancer. Progress relies on a detailed understanding of individualized risk, clear delineation of cancer development stages, a range of testing methods with optimal performance characteristics, and robust evaluation of the implications for individuals and society. In the future, advances in sensors, contrast agents, molecular methods, and artificial intelligence will help detect cancer-specific signals in real time. To reduce the burden of cancer on society, risk-based detection and prevention needs to be cost effective and widely accessible.

Development and validation of clinical prediction models for breast cancer incidence and mortality: a protocol for a dual cohort study

INTRODUCTION

Breast cancer is the most common cancer and the leading cause of cancer-related death in women worldwide. Risk prediction models may be useful to guide risk-reducing interventions (such as pharmacological agents) in women at increased risk or inform screening strategies for early detection methods such as screening.

METHODS AND ANALYSIS

The study will use data for women aged 20-90 years between 2000 and 2020 from QResearch linked at the individual level to hospital episodes, cancer registry and death registry data. It will evaluate a set of modelling approaches to predict the risk of developing breast cancer within the next 10 years, the 'combined' risk of developing a breast cancer and then dying from it within 10 years, and the risk of breast cancer mortality within 10 years of diagnosis. Cox proportional hazards, competing risks, random survival forest, deep learning and XGBoost models will be explored. Models will be developed on the entire dataset, with 'apparent' performance reported, and internal-external cross-validation used to assess performance and geographical and temporal transportability (two 10-year time periods). Random effects meta-analysis will pool discrimination and calibration metric estimates from individual geographical units obtained from internal-external cross-validation. We will then externally validate the models in an independent dataset. Evaluation of performance heterogeneity will be conducted throughout, such as exploring performance across ethnic groups.

ETHICS AND DISSEMINATION

Ethics approval was granted by the QResearch scientific committee (reference number REC 18/EM/0400: OX129). The results will be written up for submission to peer-reviewed journals.