SNPs related to vitamin D and breast cancer risk: a case-control study

Optimizing breast cancer diagnosis with photoacoustic imaging: An analysis of intratumoral and peritumoral radiomics

Background

The differentiation between benign and malignant breast tumors extends beyond morphological structures to encompass functional alterations within the nodules. The combination of photoacoustic (PA) imaging and radiomics unveils functional insights and intricate details that are imperceptible to the naked eye.

Purpose

This study aims to assess the efficacy of PA imaging in breast cancer radiomics, focusing on the impact of peritumoral region size on radiomic model accuracy.

Materials and methods

From January 2022 to November 2023, data were collected from 358 patients with breast nodules, diagnosed via PA/US examination and classified as BI-RADS 3-5. The study used the largest lesion dimension in PA images to define the region of interest, expanded by 2 mm, 5 mm, and 8 mm, for extracting radiomic features. Techniques from statistics and machine learning were applied for feature selection, and logistic regression classifiers were used to build radiomic models. These models integrated both intratumoral and peritumoral data, with logistic regressions identifying key predictive features.

Results

The developed nomogram, combining 5 mm peritumoral data with intratumoral and clinical features, showed superior diagnostic performance, achieving an AUC of 0.950 in the training cohort and 0.899 in validation. This model outperformed those based solely on clinical features or other radiomic methods, with the 5 mm peritumoral region proving most effective in identifying malignant nodules.

Conclusion

This research demonstrates the significant potential of PA imaging in breast cancer radiomics, especially the advantage of integrating 5 mm peritumoral with intratumoral features. This approach not only surpasses models based on clinical data but also underscores the importance of comprehensive radiomic analysis in accurately characterizing breast nodules.

Organoid bioinks: construction and application

Organoids have emerged as crucial platforms in tissue engineering and regenerative medicine but confront challenges in faithfully mimicking native tissue structures and functions. Bioprinting technologies offer a significant advancement, especially when combined with organoid bioinks-engineered formulations designed to encapsulate both the architectural and functional elements of specific tissues. This review provides a rigorous, focused examination of the evolution and impact of organoid bioprinting. It emphasizes the role of organoid bioinks that integrate key cellular components and microenvironmental cues to more accurately replicate native tissue complexity. Furthermore, this review anticipates a transformative landscape invigorated by the integration of artificial intelligence with bioprinting techniques. Such fusion promises to refine organoid bioink formulations and optimize bioprinting parameters, thus catalyzing unprecedented advancements in regenerative medicine. In summary, this review accentuates the pivotal role and transformative potential of organoid bioinks and bioprinting in advancing regenerative therapies, deepening our understanding of organ development, and clarifying disease mechanisms.

Metronomic chemotherapy and drug repurposing: A paradigm shift in oncology

Cancer represents a significant global health and economic burden due to its high mortality rates. While effective in some instances, traditional chemotherapy often falls short of entirely eradicating various types of cancer. It can cause severe side effects due to harm to healthy cells. Two therapeutic approaches have risen to the forefront to address these limitations: metronomic chemotherapy (MCT) and drug repurposing. Metronomic chemotherapy is an innovative approach that breaks from traditional models. It involves the administration of chemotherapeutic regimens at lower doses, without long drug-free intervals that have previously been a hallmark of such treatments. This method offers a significant reduction in side effects and improved disease management. Simultaneously, drug repurposing has gained considerable attraction in cancer treatment. This approach involves utilizing existing drugs, initially developed for other therapeutic purposes, as potential cancer treatments. The application of known drugs in a new context accelerates the timeline from laboratory to patient due to pre-existing safety and dosage data. The intersection of these two strategies gives rise to a novel therapeutic approach named 'Metronomics.' This approach encapsulates the benefits of both MCT and drug repurposing, leading to reduced toxicity, potential for oral administration, improved patient quality of life, accelerated clinical implementation, and enhanced affordability. Numerous clinical studies have endorsed the efficacy of metronomic chemotherapy with tolerable side effects, underlining the potential of Metronomics in better cancer management, particularly in low- and middle-income countries. This review underscores the benefits and applications of metronomic chemotherapy and drug repurposing, specifically in the context of breast cancer, showcasing the promising results of pre-clinical and clinical studies. However, we acknowledge the necessity of additional clinical investigations to definitively establish the role of metronomic chemotherapy in conjunction with other treatments in comprehensive cancer management.

Estrogens and the risk of breast cancer: A narrative review of literature

In female mammals, the development and regulation of the reproductive system and non-reproductive system are significantly influenced by estrogens (oestrogens). In addition, lipid metabolism is another physiological role of estrogens. Estrogens act through different types of receptors to introduce signals to the target cell by affecting many estrogen response elements. Breast cancer is considered mostly a hormone-dependent disease. Approximately 70% of breast cancers express progesterone receptors and/or estrogen receptors, and they are a good marker for cancer prognosis. This review will discuss estrogen metabolism and the interaction of estrogen metabolites with breast cancer. The carcinogenic role of estrogen is discussed in light of both conventional and atypical cancers susceptible to hormones, such as prostate, endometrial, and lung cancer, as we examine how estrogen contributes to the formation and activation of breast cancer. In addition, this review will discuss other factors that can be associated with estrogen-driven breast cancer.

Prediction of prognostic factors in breast cancer: A noninvasive method utilizing histogram parameters derived from Adc maps

Objective

The aim of this study is to investigate the relationship between histogram parameters and prognostic factors of breast cancer and to reveal the diagnostic performance of histogram parameters in predicting prognostic factors status.

Materials and methods

Ninety-two patients with a confirmed histopathological diagnosis of breast cancer were included in the study. Magnetic resonance imaging (MRI) was performed using a 1.5T scanner and two different b values were used for diffusion-weighted imaging (DWI) (b values: 0 s/mm², b: 800 s/mm²). For 3D histogram analysis, regions of interest (ROI) were drawn each slice of the lesion on apparent diffusion coefficient (ADC) maps. The following data were derived from the histogram analysis data: percentiles, skewness, kurtosis, and entropy. The relationship between prognostic factors and histogram analysis data was investigated using the Kolmogorov-Smirnov test, Shapiro-Wilk test, skewness-kurtosis test, independent t-test, Mann-Whitney U test, and Kruskal-Wallis test. Receiver operator characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the histogram parameters.

Results

ADC_max, kurtosis, and entropy parameters were statistically significantly correlated with tumor diameter (p = 0.002, p = 0.008, and p = 0.001, respectively). There was a significant difference in ADC_90% and ADC_max values, depending on estrogen receptor (ER) and progesterone receptor (PR) status. These values were lower in ER- and PR-positive than ER- and PR-negative patients (p = 0.02 and p = 0.001 vs. p = 0.018, p = 0.008). All ADC percentage values were lower in patients with a positive Ki-67 proliferation index as compared with those with a negative Ki-67 proliferation index (all p = 0.001). The entropy value was high in high-grade lesions and lesions with axillary involvement (p = 0.039 and p = 0.048, respectively). The highest area under the curve (AUC) for ER and PR status was calculated for the ADC_90% value with ROC curve analysis. The highest AUC for Ki-67 proliferation index was found for the ADC_50%.

Conclusion

Histogram analysis parameters derived from of ADC maps of whole lesions can reflect histopathological features of the tumors. Based on our study, it was concluded that histogram analysis parameters were related to the prognostic factors of the tumor.

Bioinformatics and network biology approach to identifying type 2 diabetes genes and pathways that influence the progression of breast cancer

Breast cancer is the second most prevalent malignancy affecting women. Postmenopausal women breast tumor is one of the top causes of death in women, accounting for 23% of cancer cases. Type 2 diabetes, a worldwide pandemic, has been connected to a heightened risk of several malignancies, although its association with breast cancer is still uncertain. In comparison to non-diabetic women, women with T2DM had a 23% elevated likelihood of developing breast cancer. It is difficult to determine causative or genetic susceptibility that connect T2DM and breast cancer. We created a large-scale network-based quantitative approach employing unbiased methods to discover abnormally amplified genes in both T2DM and breast cancer, to solve these issues. We performed transcriptome analysis to uncover identical genetic biomarkers and pathways to clarify the connection between T2DM and breast cancer patients. In this study, two RNA-seq datasets (GSE103001 and GSE86468) from the Gene Expression Omnibus (GEO) are used to identify mutually differentially expressed genes (DEGs) for breast cancer and T2DM, as well as common pathways and prospective medicines. Firstly, 45 shared genes (30 upregulated and 15 downregulated) between T2D and breast cancer were detected. We employed gene ontology and pathway enrichment to characterize prevalent DEGs' molecular processes and signal transduction pathways and observed that T2DM has certain connections to the progression of breast cancer. Using several computational and statistical approaches, we created a protein-protein interactions (PPI) network and revealed hub genes. These hub genes can be potential biomarkers, which may also lead to new therapeutic strategies for investigated diseases. We conducted TF-gene interactions, gene-microRNA interactions, protein-drug interactions, and gene-disease associations to find potential connections between T2DM and breast cancer pathologies. We assume that the potential drugs that emerged from this study could be useful therapeutic values. Researchers, doctors, biotechnologists, and many others may benefit from this research.

Single-cell pair-wise relationships untangled by composite embedding model

In multicellular organisms, cell identity and functions are primed and refined through interactions with other surrounding cells. Here, we propose a scalable machine learning method, termed SPRUCE, which is designed to systematically ascertain common cell-cell communication patterns embedded in single-cell RNA-seq data. We applied our approach to investigate tumor microenvironments consolidating multiple breast cancer datasets and found seven frequently observed interaction signatures and underlying gene-gene interaction networks. Our results implicate that a part of tumor heterogeneity, especially within the same subtype, is better understood by differential interaction patterns rather than the static expression of known marker genes.

Levels of Vitamin D and Expression of the Vitamin D Receptor in Relation to Breast Cancer Risk and Survival

Previous research suggests associations between low systemic levels of vitamin D and poor breast cancer prognosis and between expression of the vitamin D receptor (VDR) in breast cancers and survival. This study aimed to study associations between pre-diagnostic systemic levels of vitamin D and expression of VDR in subsequent breast tumors, and interactions between vitamin D and VDR on breast cancer mortality. Systemic vitamin D levels were measured in women within the Malmö Diet and Cancer Study. The expression of VDR was evaluated immunohistochemically in a tissue microarray of subsequent breast cancers. Statistical analyses followed. Women with high levels of vitamin D had a smaller proportion of VDR negative breast tumors compared to women with low levels of vitamin D (odds ratio: 0.68; 95% confidence interval: 0.41–1.13). Vitamin D levels were not found to modify the association between low VDR expression and high breast cancer mortality. To conclude, there was no statistical evidence for an association between pre-diagnostic levels of vitamin D and the expression of VDRs in breast cancer, nor did vitamin D levels influence the association between VDR expression and breast cancer mortality. Further studies are needed in order to establish the effects of vitamin D on breast cancer.

Effect of physical exercise on cognitive function after chemotherapy in patients with breast cancer: a randomized controlled trial (PAM study)

BACKGROUND

Up to 60% of breast cancer patients treated with chemotherapy is confronted with cognitive problems, which can have a significant impact on daily activities and quality of life (QoL). We investigated whether exercise training improves cognition in chemotherapy-exposed breast cancer patients 2-4 years after diagnosis.

METHODS

Chemotherapy-exposed breast cancer patients, with both self-reported cognitive problems and lower than expected performance on neuropsychological tests, were randomized to an exercise or control group. The 6-month exercise intervention consisted of supervised aerobic and strength training (2 h/week), and Nordic/power walking (2 h/week). Our primary outcome was memory functioning (Hopkins Verbal Learning Test-Revised; HVLT-R). Secondary outcomes included online neuropsychological tests (Amsterdam Cognition Scan; ACS), self-reported cognition (MD Anderson Symptom Inventory for multiple myeloma; MDASI-MM), physical fitness (relative maximum oxygen uptake; VO_2peak), fatigue (Multidimensional Fatigue Inventory), QoL (European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire; EORTC QLQ C-30), depression (Patient Health Questionnaire-9, Hospital Anxiety and Depression Scale; HADS), and anxiety (HADS). HVLT-R total recall was analyzed with a Fisher exact test for clinically relevant improvement (≥ 5 words). Other outcomes were analyzed using multiple regression analyses adjusted for baseline and stratification factors.

RESULTS

We randomized 181 patients to the exercise (n = 91) or control group (n = 90). Two-third of the patients attended ≥ 80% of the exercise sessions, and physical fitness significantly improved compared to control patients (B VO_2peak 1.4 ml/min/kg, 95%CI:0.6;2.2). No difference in favor of the intervention group was seen on the primary outcome. Significant beneficial intervention effects were found for self-reported cognitive functioning [MDASI-MM severity (B-0.7, 95% CI - 1.2; - 0.1)], fatigue, QoL, and depression. A hypothesis-driven analysis in highly fatigued patients showed positive exercise effects on tested cognitive functioning [ACS Reaction Time (B-26.8, 95% CI - 52.9; - 0.6) and ACS Wordlist Learning (B4.4, 95% CI 0.5; 8.3)].

CONCLUSIONS

A 6-month exercise intervention improved self-reported cognitive functioning, physical fitness, fatigue, QoL, and depression in chemotherapy-exposed breast cancer patients with cognitive problems. Tested cognitive functioning was not affected. However, subgroup analysis indicated a positive effect of exercise on tested cognitive functioning in highly fatigued patients. Trial Registration Netherlands Trial Registry: Trial NL5924 (NTR6104). Registered 24 October 2016, https://www.trialregister.nl/trial/5924 .

Markers Associated With Tumor Recurrence in Patients With Breast Cancer Achieving a Pathologic Complete Response After Neoadjuvant Chemotherapy

BACKGROUND

Patients who achieve a tumor pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) have better outcomes than patients with residual tumor. However, tumors still recur in the pCR patients. Therefore, we aim to explore factors associated with tumor recurrence in this patient population.

METHODS

A total of 1,913 patients diagnosed with breast cancer between 1995 and 2020 and received NAC were included in this analysis. Clinicopathological data of the patients were retrospectively collected. We used Cox regression analysis to assess the associations of clinicopathological factors with patients' outcome. Proteomic study of tumors was applied to identify differentially expressed proteins (DEPs) between tumors from the pCR patients with tumor recurrence and tumors from those without tumor recurrence. PPI network analysis of the corresponding genes of DEPs was used to identify the hub genes. The prognostic value of the corresponding genes of DEPs was evaluated using two online databases, Kaplan-Meier Plotter and bc-GenExMiner. The genes that were significantly associated with patients' survival in both databases, as well as being identified as hub genes, were considered as potential prognostic markers for pCR patients. Publicly available data from Gene Expression Omnibus (GEO) was used to verify the prognostic value of the identified marker.

RESULTS

Among the 1,913 included patients, 420 had tumor pCR. The median follow-up for the pCR patients was 32.6 months (IQR, 16.3-55.5). Overall estimated 5-year risk of tumor recurrence for the pCR patients was 11%. Multivariable analysis showed that a higher pre-NAC clinical T stage and N stage were independent predictors for increased risk of tumor recurrence (hazard ratio [HR] 2.57, 95% confidence interval [CI] 1.01-6.51, P=0.047 for clinical T stage and HR 3.48, 95%CI 1.37-8.83, P=0.009 for clinical N stage). NAC regimens, the type of breast and axillary surgery, and adjuvant chemotherapy were not associated with tumor recurrence. Finally, aldehyde dehydrogenase (ALDH) 3A2 was identified by the proteomic study and was verified as a potential predictor for tumor recurrence in the pCR patients (with a median follow up of 3.78 years for dataset GSE32603 and 2.74 years for dataset GSE25066 from GEO, tumor recurrence rate: low versus high expression, 20.7% versus 4.5% [data from GSE32603]; 10.9% versus 0% [data from GSE25066]).

CONCLUSIONS

Clinical T stage, clinical N stage and tumor expression of ALDH3A2 were potential markers for predicting tumor recurrence in the pCR patients after NAC.

Molecular targets and therapeutics in chemoresistance of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a specific subtype of breast cancer (BC), which shows immunohistochemically negative expression of hormone receptor i.e., Estrogen receptor and Progesterone receptor along with the absence of Human Epidermal Growth Factor Receptor-2 (HER2/neu). In Indian scenario the prevalence of BC is 26.3%, whereas, in West Bengal the cases are of 18.4%. But the rate of TNBC has increased up to 31% and shows 27% of total BC. Conventional chemotherapy is effective only in the initial stages but with progression of the disease the effectivity gets reduced and shown almost no effect in later or advanced stages of TNBC. Thus, TNBC patients frequently develop resistance and metastasis, due to its peculiar triple-negative nature most of the hormonal therapies also fails. Development of chemoresistance may involve various factors, such as, TNBC heterogeneity, cancer stem cells (CSCs), signaling pathway deregulation, DNA repair mechanism, hypoxia, and other molecular factors. To overcome the challenges to treat TNBC various targets and molecules have been exploited including CSCs modulator, drug efflux transporters, hypoxic factors, apoptotic proteins, and regulatory signaling pathways. Moreover, to improve the targets and efficacy of treatments researchers are emphasizing on targeted therapy for TNBC. In this review, an effort has been made to focus on phenotypic and molecular variations in TNBC along with the role of conventional as well as newly identified pathways and strategies to overcome challenge of chemoresistance.

Automated Breast Ultrasound: Technical Aspects, Impact on Breast Screening, and Future Perspectives

Purpose of Review

Automated breast ultrasound (ABUS) is a three-dimensional imaging technique, used as a supplemental screening tool in women with dense breasts. This review considers the technical aspects, pitfalls, and the use of ABUS in screening and clinical practice, together with new developments and future perspectives.

Recent Findings

ABUS has been approved in the USA and Europe as a screening tool for asymptomatic women with dense breasts in addition to mammography. Supplemental US screening has high sensitivity for cancer detection, especially early-stage invasive cancers, and reduces the frequency of interval cancers. ABUS has similar diagnostic performance to handheld ultrasound (HHUS) and is designed to overcome the drawbacks of operator dependence and poor reproducibility. Concerns with ABUS, like HHUS, include relatively high recall rates and lengthy reading time when compared to mammography. ABUS is a new technique with unique features; therefore, adequate training is required to improve detection and reduce false positives. Computer-aided detection may reduce reading times and improve cancer detection. Other potential applications of ABUS include local staging, treatment response evaluation, breast density assessment, and integration of radiomics.

Summary

ABUS provides an efficient, reproducible, and comprehensive supplemental imaging technique in breast screening. Developments with computer-aided detection may improve the sensitivity and specificity as well as radiologist confidence and reduce reading times, making this modality acceptable in large volume screening centers.

In vivo test-driven upgrade of a time domain multi-wavelength optical mammograph

A recent upgrade of the time domain multi-wavelength optical mammograph developed by Politecnico di Milano achieved good performance in laboratory tests [Biomed. Opt. Express9, 755 (2018).10.1364/BOE.9.000755]. However, it proved unsatisfactory when in vivo measurements were finally performed. That led to a further upgrade, including the replacement of the time-to-digital converter with a new model, and the related set-up changes. The new instrument version offers improved laboratory performance (as assessed through established protocols: BIP and MEDPHOT) and good in vivo performance (extension of the scanned breast area, repeatability, consistency of estimated tissue composition with physiology). Besides introducing the new set-up and detailing its laboratory and in vivo performance, we highlight the importance of systematic in vivo testing before entering clinical trials.

CASC15 Polymorphisms are Correlated With Breast Cancer Susceptibility in Chinese Han Women

INTRODUCTION

Breast cancer (BC) is a prevalent malignant tumor among women. Numerous studies have been reported that long noncoding RNAs (lncRNAs) were associated with various human diseases.

MATERIALS AND METHODS

In the current study, 681 patients with BC and 680 unrelated controls were recruited to investigate the correlation between lncRNA cancer susceptibility candidate 15 (CASC15) polymorphisms and BC risk in Chinese Han women. We performed single-nucleotide polymorphism genotyping using the Agena MassARRAY platform. The relationship between lncRNA CASC15 polymorphisms and the risk of BC were evaluated through odds ratios and 95% confidence intervals.

RESULTS

Our results suggested that the lncRNA CASC15 rs7740084 "G/G" genotype and rs1928168 "T/C" genotype significantly reduced BC risk in different genetic models (P = .045, P = .029, and P = .047, respectively). However, rs9393266 "C/T" and "C/T-T/T" genotypes were correlated with the risk of BC (P = .021 and P = .048). In addition, we also observed that rs1928168 was related to the risk of BC in patients with age > 50 years (P = .025), body mass index > 24 (P = .006), and tumor size (P = .035). For rs9393266, it was revealed that the "C/T" and "C/T-T/T" genotypes were related to BC risk in people with age ≤ 50 years (P = .005) and body mass index > 24 (P = .023).

CONCLUSION

In summary, our results revealed a potential interaction between lncRNA CASC15 polymorphisms and BC susceptibility. The results provided an important insight into lncRNA CASC15 function in the development of BC.

Development of an individualized risk calculator for poor functioning in young people victimized during childhood: A longitudinal cohort study

BACKGROUND

Childhood victimization elevates the average risk of developing functional impairment in adulthood. However, not all victimized children demonstrate poor outcomes. Although research has described factors that confer vulnerability or resilience, it is unknown if this knowledge can be translated to accurately identify the most vulnerable victimized children.

OBJECTIVE

To build and internally validate a risk calculator to identify those victimized children who are most at risk of functional impairment at age 18 years.

PARTICIPANTS

We utilized data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative birth cohort of 2232 UK children born in 1994-95.

METHODS

Victimization exposure was assessed repeatedly between ages 5 and 12 years along with a range of individual-, family- and community-level predictors. Functional outcomes were assessed at age 18 years. We developed and evaluated a prediction model for psychosocial disadvantage and economic disadvantage using the Least Absolute Shrinkage and Selection Operator (LASSO) regularized regression with nested 10-fold cross-validation.

RESULTS

The model predicting psychosocial disadvantage following childhood victimization retained 12 of 22 predictors, had an area under the curve (AUC) of 0.65, and was well-calibrated within the range of 40-70% predicted risk. The model predicting economic disadvantage retained 10 of 22 predictors, achieved excellent discrimination (AUC = 0.80), and a high degree of calibration.

CONCLUSIONS

Prediction modelling techniques can be applied to estimate individual risk for poor functional outcomes in young adulthood following childhood victimization. Such risk prediction tools could potentially assist practitioners to target interventions, which is particularly useful in a context of scarce resources.

Influence of vitamin D on cancer risk and treatment: Why the variability?

The association between vitamin D and cancer has long been studied, but the results have been variable. Thus, there does not seem to be a consensus on whether vitamin D has a beneficial anti-cancer effect. This review not only summarizes the association between vitamin D and cancer risk and results of clinical trials involving vitamin D, but explores some of the reasons that contribute to the variability of study outcomes. Highlighted are single nucleotide polymorphisms (SNPs) that contribute to variability in the efficacy of vitamin D supplementation. Understanding these differences can personalize approaches to optimize the effectiveness of vitamin D in limiting cancer risk.