Breast Cancer Status Research Articles

A Retrospective Cohort Study Assessing Ability of Radiological Investigations to Predict Axillary Nodal Status in Breast Cancer

A Retrospective Cohort Study Assessing Ability of Radiological Investigations to Predict Axillary Nodal Status in Breast Cancer

Predicting Ki-67 expression levels in breast cancer using radiomics-based approaches on digital breast tomosynthesis and ultrasound.

To construct and validate radiomics models that utilize ultrasound (US) and digital breast tomosynthesis (DBT) images independently and in combination to non-invasively predict the Ki-67 status in breast cancer. 149 breast cancer women who underwent DBT and US scans were retrospectively enrolled from June 2018 to August 2023 in total. Radiomics features were acquired from both the DBT and US images, then selected and reduced in dimensionality using several screening approaches. Establish radiomics models based on DBT, and US separately and combined. The area under the receiver operating characteristic curve (AUC), accuracy, specificity, and sensitivity were utilized to validate the predictive ability of the models. The decision curve analysis (DCA) was used to evaluate the clinical applicability of the models. The output of the classifier with the best AUC performance was converted into Rad-score and was regarded as Rad-Score model. A nomogram was constructed using the logistic regression method, integrating the Rad-Score and clinical factors. The model's stability was assessed through AUC, calibration curves, and DCA. Support vector machine (SVM), logistic regression (LR), and random forest (RF) were trained to establish radiomics models with the selected features, with SVM showing optimal results. The AUC values for three models (US_SVM, DBT_SVM, and merge_SVM) were 0.668, 0.704, and 0.800 respectively. The DeLong test indicated a notable disparity in the area under the curve (AUC) between merge_SVM and US_SVM (p = 0.048), while there was no substantial variability between merge_SVM and DBT_SVM (p = 0.149). The DCA curve indicates that merge_SVM is superior to unimodal models in predicting high Ki-67 level, showing more clinical values. The nomogram integrating Rad-Score with tumor size obtained the better performance in test set (AUC: 0.818) and had more clinical net. The fusion radiomics model performed better in predicting the Ki-67 expression level of breast carcinoma, but the gain effect is limited; thus, DBT is preferred as a preoperative diagnosis mode when resources are limited. Nomogram offers predictive advantages over other methods and can be a valuable tool for predicting Ki-67 levels in BC.

Characterisation ofIGF-1 (rs7136446) and IL-6 (rs1800795) polymorphisms among breast cancer patients in western Algeria.

Breast cancer (BC) is themost frequently diagnosed cancer among women worldwide, including Algeria. Certain single nucleotide polymorphisms (SNPs) have been linked to higher risk ofBC. Several studies have been performed on theinsulin- like growth factor 1 (IGF-1) T > C (rs7136446) and theinterleukin 6 (IL-6) 174 G > C (rs1800795) SNPs to explore their role in BC. Theaim ofthis study is to investigate theassociation between the2 SNPs, IL-6 (rs1800795) and IGF-1 (rs7136446) with BC in thepopulation ofwestern Algeria. This study was carried out for thefirst time among theAlgerian population. This case-control study included 109 BC patients and 112 healthy controls. Genomic DNA was extracted from peripheral blood samples. DNA concentration was determined using theQubit 2.0 fluorometer. Thegenotyping ofselected SNPs was performed by real-time polymerase chain reaction followed by statistical analysis to assess genotypic frequencies and genetic association with BC. Theresults showed that IGF-1 rs7136446 was positively associated with BC (p = 0.00001) and that thedistribution ofgenotype frequencies ofrs7136446 showed astatistically difference between human epidermal growth factor receptor 2 (HER-2) positive and HER-2 negative BC (p = 0.04), but this association did not last after thecorrection ofBonferroni. No association was found in genotype distribution oftheIL-6 (rs1800795) among controls and BC patients or with clinicopathological parameters including HER-2 status in BC (p > 0.05). In summary, our findings indicate that IGF-1 rs7136446 is associated with BC in our population ofwestern Algeria.

Construction and validation of immune-associated lncRNA model for predicting immune status and therapeutic reactions of triple-negative breast cancer.

The immune status of the tumor microenvironment significantly impacts the clinical prognosis of triple-negative breast cancer (TNBC). The involvement of long noncoding RNAs (lncRNAs) in tumor immune infiltration is widely acknowledged. Therefore, it is crucial to explore the role of significant immune-related lncRNAs in TNBC. We acquired RNA, single-cell sequencing, and clinical information on TNBC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. To identify immune-related lncRNAs, immune infiltration subgroups were determined and verified using single-sample gene-set enrichment analysis, non-negative matrix factorization, and weighted gene co-expression network analysis. CIBERSORTx, deconvolution, drug sensitivity, and Scissor analyses revealed that differences in cell type and drug efficacy were associated with immune grouping. TNBC samples were classified into immune-desert (cold) and immune-inflamed (hot) subgroups based on a lncRNA model (including LINC01550, LY86-AS1, LINC00494, LINC00877, CHRM3-AS2, HCP5, MIR155HG, and PIK3CD-AS1). Furthermore, using in vitro experiments, we found that LINC01550 promoted malignant phenotypes, including proliferation, survival, and migration of TNBC. The immune-inflamed subgroup exhibited significantly lower half-maximal inhibitory concentration values for common anti-tumor drugs, including palbociclib, ribociclib, mitoxantrone, and sorafenib (T-test, P < 0.001). This may be related to the fact that the immune-inflamed subgroup has more plasmacytoid dendritic cells (pDCs) and B cells than those in immune-desert subgroups (P < 0.001). Differences in specific cell infiltration can lead to increased sensitivity of the immune-inflamed subgroup to anti-tumor drugs. The proposed lncRNA model holds great promise to assess the immune landscapes and therapeutic reactions of TNBC patients.

Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer.

Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified. The gene expression profiles datasets of TNBC patients were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Diagnostic biomarkers for stratifying individualized tumor immune microenvironment (TIME) were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Additionally, we explored their associations with response to immunotherapy via the multiplex immunohistochemistry (mIHC). A total of 60 costimulatory molecule genes (CMGs) were obtained, and we determined two different TIME subclasses ("hot" and "cold") through the K-means clustering method. The "hot" tumors presented a higher infiltration of activated immune cells, i.e., CD4 memory-activated T cells, resting NK cells, M1 macrophages, and CD8 T cells, thereby enriched in the B cell and T cell receptor signaling pathways. LASSO and SVM-RFE algorithms identified three CMGs (CD86, TNFRSF17 and TNFRSF1B) as diagnostic biomarkers. Following, a novel diagnostic nomogram was constructed for predicting individualized TIME status and was validated with good predictive accuracy in TCGA, GSE76250 and GSE58812 databases. Further mIHC conformed that TNBC patients with high CD86, TNFRSF17 and TNFRSF1B levels tended to respond to immunotherapy. This study supplemented evidence about the value of CMGs in TNBC. In addition, CD86, TNFRSF17 and TNFRSF1B were found as potential biomarkers, significantly promoting TNBC patient selection for immunotherapeutic guidance.

BRCA mutation status and pathological characterization of breast cancer in Zhoushan Islands, China.

To investigate BRCA1/2 gene mutations and their relationship with clinicopathological features in patients with breast cancer in Zhoushan Islands. High-throughput whole-exome gene sequencing was used to detect BRCA1/2 mutations in 776 breast cancer patients in Zhoushan Islands. The BRCA1/2 mutation rate of breast cancer patients in Zhoushan Islands was 4.38% (34/776). BRCA1 mutations were significantly correlated with age, molecular type, and family history of breast and ovarian cancers. BRCA2 mutations were most commonly found in invasive lobular carcinoma. Moreover, the BRCA2 mutation rate of cancers with molecular type luminal B (receptor protein-tyrosine kinase [HER2]-negative) was also relatively high. The rate of BRCA1/2 mutations in breast cancer patients from Zhoushan Islands is approximately 4.38%, and BRCA1 mutation is related to age, molecular type, and family history of breast and ovarian cancers.

Expression of transferrin receptor 1 and β1-integrins correlates with estrogen receptor status and immune infiltration in breast cancer

To study of transferrin receptor 1 (CD71) expression by primary breast cancer cells in correlation with tumor cell phenotype. Determination of BC phenotype: immunohistochemical staining method (immunofluorescence). Antibodies to ER (estrogen receptors), KL-1 (pancytokeratin), CD71 (transferrin receptor), CD29 (β1-integrins). CD45, CD3, CD4, CD8, CD20 infiltration was also evaluated. ZEISS microscope (AXIOSKOP; Germany), method of G.J. Hammerling et al. Statistical processing: IBM-SPSS Statistics v.21. 63% of BC cases had CD71+ phenotype. CD71-mosaic tumors were observed in 14.4%. β1-integrin expression was monomorphic in 51.6% of cases and mosaic in 38.7%. 85% of ER-positive tumors were CD71-positive with a monomorphic type of reaction; p=0.014. Among ER-negative tumors, CD71-negative reactions were 2-fold more frequent and the monomorphic type was less frequent. ER-positive tumors were CD29-positive in 73%; p=0.031. 45.5% of ER+ tumors were CD29-monomorphic. Among ER-negative tumors, the frequency of CD29-monomorphic tumors was 55%. Significant infiltration by CD3+ cells was predominant in CD71-positive tumors; p=0.016. In the CD29-monomorphic phenotype, CD45+ infiltration was 31.3%, and in the mosaic phenotype, 67.1%. BC aberrantly expresses transferrin receptors, β1-integrins. CD71 expression is associated with ER expression. ER-positive tumors are often monomorphic for CD71. Prominent CD3+ infiltration was present in CD71+ tumors. Expression of β1-integrins correlated with ER+ status and weak immune infiltration.

Prognostic impact of tumor-associated neutrophils in breast cancer.

Neutrophils are the most common type of leukocyte in mammals and play an essential role in the innate immune system and anti-cancer responses. However, recent studies identified the presence of tumor-associated neutrophils (TANs) as a poor prognostic factor. The present study investigated whether relationships exist between TANs and the clinicopathological factors and genetic status of breast cancer. A total of 196 breast cancer patients with sufficient biopsy, breast-conserving surgery, or mastectomy specimens between 2014 and 2021 in Hokuto Hospital were included. TANs were individually counted in the tumor stroma (TS) and tumor nest (TN). A higher density of TANs in both TS and TN correlated with tumor size (TS P = 0.010; TN P = 0.001), a high histological grade (TS P < 0.001; TN P < 0.001), the histological type (TS P = 0.009; TN P = 0.034), a high ratio of lymph node metastasis (TS P < 0.001; TN P < 0.001), an advanced stage of cancer (TS P < 0.001; TN P = 0.002), intrinsic subtypes (TS P < 0.001; TN P < 0.001), ERBB2 (TS P < 0.001; TN P < 0.001), MAP3K1 (TS P = 0.002; TN P = 0.023), and TP53 (TS P < 0.001; TN P < 0.001). A higher density of TANs in TS and TN also correlated with shorter disease-free survival and overall survival (P < 0.001). The present results suggest that a higher density of TANs correlates with unfavorable prognostic factors in breast cancer. Further research on clinicopathological and genetic factors associated with TANs in breast cancer is needed.

ERCC3 Gene Associated with Breast Cancer: A Genetic and Bioinformatic Study

Female breast cancer is the most common and the fifth deadliest cancer worldwide. It is influenced by a combination of genetic, hormonal, and environmental factors. The excision repair cross‐complementation group 3 gene (ERCC3) has recently been identified as a breast cancer susceptibility gene in various cohorts of different geographical and ethnic origin. To explore the role of ERCC3 mutations in breast cancer development and pathological diagnosis, genetic analysis was conducted in 291 patients and 291 controls from mainland China. Bioinformatic analysis and immunohistochemistry (IHC) were performed. A novel ERCC3 mutation p.Y116X was identified in a breast cancer family, while no frequency bias for the genotype and allele of rs754010782 and rs371627165 was observed (all P &gt; 0.05). Bioinformatic analysis revealed that ERCC3 expression was negatively associated with estrogen receptor (ER), progesterone receptor (PR), nontriple‐negative status, and nodal status of breast cancers. ERCC3 amplifications and deep deletions primarily occurred in breast invasive cancer not otherwise specified (NOS) and metaplastic breast cancer, respectively. The decreased ERCC3 expression in tumor tissues of patient with p.Y116X mutation was found by IHC. The ERCC3 mutation p.Y116X may increase breast cancer risk in the Han‐Chinese population. ERCC3 exhibits potential as a biomarker for the pathological diagnosis of breast cancer.

Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics.

Accurate axillary evaluation plays an important role in prognosis and treatment planning for breast cancer. This study aimed to develop and validate a dynamic contrast-enhanced (DCE)-MRI-based radiomics model for preoperative evaluation of axillary lymph node (ALN) status in early-stage breast cancer. A total of 410 patients with pathologically confirmed early-stage invasive breast cancer (training cohort, N = 286; validation cohort, N = 124) from June 2018 to August 2022 were retrospectively recruited. Radiomics features were derived from the second phase of DCE-MRI images for each patient. ALN status-related features were obtained, and a radiomics signature was constructed using SelectKBest and least absolute shrinkage and selection operator regression. Logistic regression was applied to build a combined model and corresponding nomogram incorporating the radiomics score (Rad-score) with clinical predictors. The predictive performance of the nomogram was evaluated using receiver operator characteristic (ROC) curve analysis and calibration curves. Fourteen radiomic features were selected to construct the radiomics signature. The Rad-score, MRI-reported ALN status, BI-RADS category, and tumour size were independent predictors of ALN status and were incorporated into the combined model. The nomogram showed good calibration and favourable performance for discriminating metastatic ALNs (N + (≥1)) from non-metastatic ALNs (N0) and metastatic ALNs with heavy burden (N + (≥3)) from low burden (N + (1-2)), with the area under the ROC curve values of 0.877 and 0.879 in the training cohort and 0.859 and 0.881 in the validation cohort, respectively. The DCE-MRI-based radiomics nomogram could serve as a potential non-invasive technique for accurate preoperative evaluation of ALN burden, thereby assisting physicians in the personalized axillary treatment for early-stage breast cancer patients. This study developed a potential surrogate of preoperative accurate evaluation of ALN status, which is non-invasive and easy-to-use.

Development of an Intratumoral and Peritumoral Radiomics Nomogram Using Digital Breast Tomosynthesis for Preoperative Assessment of Lymphovascular Invasion in Invasive Breast Cancer

This study aimed to create a nomogram model that combines clinical factors with radiomics analysis of both intra- and peritumoral regions extracted from preoperative digital breast tomosynthesis (DBT) images, in order to develop a reliable method for predicting the lymphovascular invasion (LVI) status in invasive breast cancer (IBC) patients. A total of 178 patients were randomly split into a training dataset (N=124) and a validation dataset (N=54). Comprehensive clinical data, encompassing DBT features, were gathered for all cases. Radiomics features were extracted and selected from intra- and peritumoral region to establish radiomics signature (Radscore). To construct the clinical model and nomogram model, univariate and multivariate logistic regression analyses were utilized to identify independent risk factors. To assess and validate these models, various analytical methods were employed, including receiver operating characteristic (ROC) curve analysis, calibration curve analysis, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discriminatory improvement (IDI). The clinical model is constructed based on two independent risk factors: tumor margin and the DBT-reported lymph node metastasis (DBT_reported_LNM). Incorporating Radscore_Combine(utilizing both intra- and peritumoral radiomics features), tumor margin, and DBT_reported_LNM into the nomogram achieved a reliable predictive performance, with area under the curve (AUC) values of 0.906 and 0.905 in both datasets, respectively. The significant improvement demonstrated by the NRI and IDI indicates that the Radscore_Combine could be a valuable biomarker for effectively predicting the status of LVI. The nomogram demonstrated a reliable ability to predict LVI in IBC patients.

Prognostic Role of p53 Immunohistochemical Status in Invasive Breast Cancer. A Retrospective Review of 1387 Cases With Luminal-Like/Her2 Negative Breast Tumors.

The aim of this study was to evaluate the prognostic role of p53 immunohistochemical (IHC) expression in a large cohort of patients with hormone receptors (HR)-positive/Her2-negative primary invasive breast cancer. Retrospective review of consecutive cases treated at our Breast Unit between 2003 and 2013. Patients were divided into 3 subgroups based on p53 IHC expression: null (0%), low (0.1%-49%), and high (≥50%) p53 expression. A total of 1387 patients were included in the study with a median follow-up of 86 months. After adjusting for age, size, node status, lymphovascular invasion, progesterone, and Ki67 expression, only null p53 immunophenotype was associated with worse disease-free survival (DFS) (OR 1.74, 95% IC, 1.11-2.71, P = .015) and distant recurrence-free survival (DRFS) (OR 1.73, 95% IC, 1.04-2.90, P = .036). Null p53 impacted significantly DFS and DRFS also in patients with early breast cancer. p53 IHC expression affects survival and, thus can be a valuable tool in the management of patients with HR-positive/Her2-negative breast cancer.

A Retrospective Study of the Epidemiology, Histomorphological Features, Hormonal Status, and Radiological Features of Breast Cancer Diagnosed on Biopsies in Women in Bahrain Up to the Age of 40: A Single-Center Study.

Breast cancer is the most commonly diagnosed cancer in women worldwide. There are many risk factors that contribute to breast cancer which involvemodifiable and non-modifiable factors. Most of the patients diagnosed with breast cancer are over 50 years of age, with breast cancer in women less than 40 years of age being relatively rare and typically more aggressive variants. Moreover, radiological examination is essential for diagnosis and triaging patients for further diagnostic procedures including tissue biopsy sampling. Despite the rarity of malignancy amongthe younger age group, all of their breast lesions are usually biopsied. Hence, this paper outlines the percentage of benign and malignant breast lesions detected on biopsies obtained from female patients who presented to our hospital before or at the age of 40. We conducted a single institution retrospective study on 267 breast biopsies done for female patientsbefore or at the age of 40 in the period from January 2020 to January 2023. The data was obtained from the National Health Information System at Salmaniya Medical Complex. The data collected included clinical history, histological, and radiological findings. Data on prognostic markers (estrogen receptor (ER)/progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) status) were also included. The distribution of samples was established according to age ranges, pathological diagnostic categories (B1-5), and prognostic marker interpretation. Further subdivision was performed on cases with malignancy according to tumor grade. The frequency distribution was obtained for ER, PR, and HER status jointly. The association between age and grade, as well as age and categories, was also determined. All the analyses were performed using SPSS Statistics version 26.0 (IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp), and the statistical significance was tested at a 5% level. Out of 267 samples, the majority (62.9%) were in patients with a range of age between 30 and 40. There were 68.5% of samples with the B2 (benign) category, followed by 20.2% with the B5b (malignant-invasive carcinoma) category. Out of 61 malignant samples, there were 17 (6.4%) samples positive on ER and PR but negative on HER2, 16 (6.0%) samples negative on ER, PR, and HER2, eight (3.0%) samples negative on ER and PR negative but positive on HER2, and five (8.2%) samples positive on ER, PR, and HER2. The majority of malignant cases were of grade II which accounted for 29 (10.9%) samples, followed by 23 (8.6%) with grade III. The association between age and grade was statistically not significant (p=0.113). However, the association between age and B categories was statistically significant with a p-value of 0.0002. A significantly higher proportion of cases with B5a (malignant-in situ carcinoma) or B5b (malignant-invasive carcinoma) categories were in the age range of 31-35 years and 36-40 years. Breast cancer is rare amongyounger women. It mostly occurs in women over the age of 40 years. In women under the age of 40, it usually presents as a self-detected palpable mass and can show various radiological findings in accordance with the histological grade. Ultrasonography is the main method for the diagnosis of breast cancer especially in younger women, whereas mammography and MRI can contribute to both diagnosis and assessment of the extent of the disease.

Prognostic value of glucose transporter proteins-1 (GLUT1) in breast carcinoma

ABSTRACT Several studies have reported increased glucose transporters (GLUT) expression in different cancer types, including breast cancer. The primary purpose of this study is to examine GLUT1 immunoexpression in breast cancer patients in Saudi Arabia and to determine its significance. The study examined the association between GLUT1 immunophenotype and the clinicopathological characteristics in breast cancer. GLUT1 expression was analyzed in retrospectively collected tissue samples (n = 578) from breast cancer patients using immunohistochemistry. A total of 311 (54%) of the cases expressed GLUT1 cytoplasmic immunohistochemical staining. In univariate analysis, we found a significant association between GLUT1 expression and high-grade tumors (p < 0.0001). Positive estrogen and progesterone receptor results predicted lower GLUT1 immunoexpression (p < 0.0001 for both). Vascular invasion showed a significant association with GLUT1 immunoexpression (p = 0.045). Our findings support that GLUT1 immunohistochemistry can be used as a marker to determine the grade and hormonal receptor status in breast cancer.

Noninvasive Staging of Lymph Node Status in Breast Cancer Using Machine Learning: External Validation and Further Model Development.

Most patients diagnosed with breast cancer present with a node-negative disease. Sentinel lymph node biopsy (SLNB) is routinely used for axillary staging, leaving patients with healthy axillary lymph nodes without therapeutic effects but at risk of morbidities from the intervention. Numerous studies have developed nodal status prediction models for noninvasive axillary staging using postoperative data or imaging features that are not part of the diagnostic workup. Lymphovascular invasion (LVI) is a top-ranked predictor of nodal metastasis; however, its preoperative assessment is challenging. This paper aimed to externally validate a multilayer perceptron (MLP) model for noninvasive lymph node staging (NILS) in a large population-based cohort (n=18,633) and develop a new MLP in the same cohort. Data were extracted from the Swedish National Quality Register for Breast Cancer (NKBC, 2014-2017), comprising only routinely and preoperatively available documented clinicopathological variables. A secondary aim was to develop and validate an LVI MLP for imputation of missing LVI status to increase the preoperative feasibility of the original NILS model. Three nonoverlapping cohorts were used for model development and validation. A total of 4 MLPs for nodal status and 1 LVI MLP were developed using 11 to 12 routinely available predictors. Three nodal status models were used to account for the different availabilities of LVI status in the cohorts and external validation in NKBC. The fourth nodal status model was developed for 80% (14,906/18,663) of NKBC cases and validated in the remaining 20% (3727/18,663). Three alternatives for imputation of LVI status were compared. The discriminatory capacity was evaluated using the validation area under the receiver operating characteristics curve (AUC) in 3 of the nodal status models. The clinical feasibility of the models was evaluated using calibration and decision curve analyses. External validation of the original NILS model was performed in NKBC (AUC 0.699, 95% CI 0.690-0.708) with good calibration and the potential of sparing 16% of patients with node-negative disease from SLNB. The LVI model was externally validated (AUC 0.747, 95% CI 0.694-0.799) with good calibration but did not improve the discriminatory performance of the nodal status models. A new nodal status model was developed in NKBC without information on LVI (AUC 0.709, 95% CI: 0.688-0.729), with excellent calibration in the holdout internal validation cohort, resulting in the potential omission of 24% of patients from unnecessary SLNBs. The NILS model was externally validated in NKBC, where the imputation of LVI status did not improve the model's discriminatory performance. A new nodal status model demonstrated the feasibility of using register data comprising only the variables available in the preoperative setting for NILS using machine learning. Future steps include ongoing preoperative validation of the NILS model and extending the model with, for example, mammography images.

Optical Imaging in Human Lymph Node Specimens for Detecting Breast Cancer Metastases: A Review.

Assessment of regional lymph node status in breast cancer is of important staging and prognostic value. Even though formal histological examination is the currently accepted standard of care, optical imaging techniques have shown promising results in disease diagnosis. In the present article, we review six spectroscopic techniques and focus on their use as alternative tools for breast cancer lymph node assessment. Elastic scattering spectroscopy (ESS) seems to offer a simple, cost-effective, and reproducible method for intraoperative diagnosis of breast cancer lymph node metastasis. Optical coherence tomography (OCT) provides high-resolution tissue scanning, along with a short data acquisition time. However, it is relatively costly and experimentally complex. Raman spectroscopy proves to be a highly accurate method for the identification of malignant axillary lymph nodes, and it has been further validated in the setting of head and neck cancers. Still, it remains time-consuming. Near-infrared fluorescence imaging (NIRF) and diffuse reflectance spectroscopy (DFS) are related to significant advantages, such as deep tissue penetration and efficiency. Fourier-transform infrared spectroscopy (FTIR) is a promising method but has significant drawbacks. Nonetheless, only anecdotal reports exist on their clinical use for cancerous lymph node detection. Our results indicate that optical imaging methods can create informative and rapid tools to effectively guide surgical decision-making.

Fast walking reduces the risk of breast cancer: evidence from a Mendelian randomisation study

ABSTRACT Breast cancer is a prevalent malignancy that poses a serious threat to women’s health. Lifestyle modifications can alter the risk of breast cancer. Walking is a common lifestyle behaviour, but its impact on breast cancer remains unclear. We conducted a Mendelian randomisation (MR) study to explore this issue. Independent genetic variants closely associated with usual walking speed were selected as instrumental variables from publicly available genome-wide association studies (GWAS) databases. Genetic data on the estrogen receptor (ER) status of breast cancer and breast cancer were obtained from a large-scale GWAS meta-analysis. Inverse variance-weighted regression analysis revealed that brisk walking speed was associated with a lower risk of breast cancer [OR = 0.69; 95%CI = (0.54, 0.88); P = 0.006] and lower risk of ER− breast cancer [OR = 0.60; 95%CI = (0.38, 0.91); P = 0.018]. However, walking speed was not associated with the risk of ER + breast cancer [OR = 0.92; 95%CI = (0.70, 1.25); P = 0.641]. MR-Egger intercept and MR-PRESSO tests did not reveal significant levels of pleiotropy or heterogeneity, respectively. Sensitivity analyses also confirmed the robustness of the results. Our study provides strong evidence that faster walking speeds may reduce the risk of breast cancer and that a more widespread adoption of moderate or high-intensity exercise may be effective in reducing women’s health risks.

The expression of O-linked glycosyltransferase GALNT7 in breast cancer is dependent on estrogen-, progesterone-, and HER2-receptor status, with prognostic implications.

GALNT7 is a glycosyltransferase enzyme transferring N-acetylgalactosamine to initiate O-linked glycosylation in the Golgi apparatus. Breast cancer is the most common cancer in women globally. Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2; ERBB2) are important biomarkers in the prognosis and molecular subtyping of breast cancer. Here, we showed that ER-positive, PR-positive or HER2-positive breast tumors have higher expression of GALNT7 compared to ER-negative, PR-negative or HER2-negative breast tumors, respectively. We found that CpG-aggregated methylation of GALNT7 gene is decreased, and in parallel, its transcript levels are increased in breast cancer compared to healthy breast tissue. We observed that the difference in the expression of GALNT7 between negative and positive status of the receptors is the highest for HER2, followed by ER and PR, pointing that HER2 might be relatively more influential than ER and PR on the expression of GALNT7 in breast cancer. We reported that basal-like breast tumors have decreased expression of GALNT7 compared to non-basal-like tumors, and that high GALNT7 expression is associated with favorable relapse-free and distant metastasis-free survival in HER2 status-dependent manner in breast cancer patients. Moreover, we showed that GALNT7 expression in breast cancer is cell type- (epithelial vs stromal cells), tumor grade- and ethnicity-dependent. Combined, we propose that GALNT7 might contribute to different clinical outcomes depending on the receptor status in breast cancer, and that a better understanding of GALNT7 and its function in the context of breast cancer is needed.

The Impact of HER2-Low Expression on Oncologic Outcomes in Hormone Receptor-Positive Breast Cancer.

Breast cancer is a prevalent malignancy with increasing incidence, particularly in Asian countries. Classification based on estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status is pivotal in determining treatment. Recent advances have challenged the traditional dichotomy in HER2 classification, prompting investigation into the HER2-low subtype's characteristics and outcomes. This retrospective study analyzed 10,186 non-metastatic hormone receptor (HR)-positive, HER2-negative breast cancer cases treated from 2008 to 2020. Data encompassed clinical, pathological, and treatment information. Oncologic outcomes included disease-free survival (DFS), overall survival (OS), and breast cancer-specific survival (BCSS). In total, 56.5% were HER2-low cases. Differences in patient characteristics were noted, with more BRCA1/2 mutations and higher mastectomy rates in the HER2-low group (p = 0.002, p < 0.001, respectively). Fewer received adjuvant chemotherapy or radiation therapy, and fewer histologic and nuclear grade 1 tumors were identified (all p < 0.001). With a median follow-up of 64 months (range: 13-174), HER2-low cases exhibited better DFS, OS, and BCSS than HER2-0 cases (p = 0.012, p = 0.013, and p = 0.013, respectively). Notably, the prognosis differed between premenopausal and postmenopausal subgroups, with BCSS benefitting premenopausal patients (p = 0.047) and DFS and OS benefitting postmenopausal patients in the HER2-low group (p = 0.004, p = 0.009, respectively). Multivariate analysis confirmed HER2 status as an independent predictor of these outcomes (p = 0.010, p = 0.008, and p = 0.014, respectively). This extensive single-center study elucidates the favorable prognosis associated with HER2-low status in HR-positive breast cancer. However, this effect differs among premenopausal and postmenopausal patients, necessitating further research into the underlying tumor biology.

Prediction models for hormone receptor status in female breast cancer do not extend to males: further evidence of sex-based disparity in breast cancer

Breast cancer prognosis and management for both men and women are reliant upon estrogen receptor alpha (ERα) and progesterone receptor (PR) expression to inform therapy. Previous studies have shown that there are sex-specific binding characteristics of ERα and PR in breast cancer and, counterintuitively, ERα expression is more common in male than female breast cancer. We hypothesized that these differences could have morphological manifestations that are undetectable to human observers but could be elucidated computationally. To investigate this, we trained attention-based multiple instance learning prediction models for ERα and PR using H&E-stained images of female breast cancer from the Cancer Genome Atlas (TCGA) (n = 1085) and deployed them on external female (n = 192) and male breast cancer images (n = 245). Both targets were predicted in the internal (AUROC for ERα prediction: 0.86 ± 0.02, p < 0.001; AUROC for PR prediction = 0.76 ± 0.03, p < 0.001) and external female cohorts (AUROC for ERα prediction: 0.78 ± 0.03, p < 0.001; AUROC for PR prediction = 0.80 ± 0.04, p < 0.001) but not the male cohort (AUROC for ERα prediction: 0.66 ± 0.14, p = 0.43; AUROC for PR prediction = 0.63 ± 0.04, p = 0.05). This suggests that subtle morphological differences invisible upon visual inspection may exist between the sexes, supporting previous immunohistochemical, genomic, and transcriptomic analyses.