Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013

Impact of the COVID-19 pandemic on breast cancer incidence and tumor stage in the Netherlands and Norway: A population-based study

BACKGROUND

Comparing the impact of the COVID-19 pandemic on the incidence of newly diagnosed breast tumors and their tumor stage between the Netherlands and Norway will help us understand the effect of differences in governmental and social reactions towards the pandemic.

METHODS

Women newly diagnosed with breast cancer in 2017-2021 were selected from the Netherlands Cancer Registry and the Cancer Registry of Norway. The crude breast cancer incidence rate (tumors per 100,000 women) during the first (March-September 2020), second (October 2020-April 2021), and Delta COVID-19 wave (May-December 2021) was compared with the incidence rate in the corresponding periods in 2017, 2018, and 2019. Incidence rates were stratified by age group, method of detection, and clinical tumor stage.

RESULTS

During the first wave breast cancer incidence declined to a larger extent in the Netherlands than in Norway (27.7% vs. 17.2% decrease, respectively). In both countries, incidence decreased in women eligible for screening. In the Netherlands, incidence also decreased in women not eligible for screening. During the second wave an increase in the incidence of stage IV tumors in women aged 50-69 years was seen in the Netherlands. During the Delta wave an increase in overall incidence and incidence of stage I tumors was seen in Norway.

CONCLUSION

Alterations in breast cancer incidence and tumor stage seem related to a combined effect of the suspension of the screening program, health care avoidance due to the severity of the pandemic, and other unknown factors.

Artificial intelligence in breast imaging: potentials and challenges

Breast cancer, which is the most common type of malignant tumor among humans, is a leading cause of death in females. Standard treatment strategies, including neoadjuvant chemotherapy, surgery, postoperative chemotherapy, targeted therapy, endocrine therapy, and radiotherapy, are tailored for individual patients. Such personalized therapies have tremendously reduced the threat of breast cancer in females. Furthermore, early imaging screening plays an important role in reducing the treatment cycle and improving breast cancer prognosis. The recent innovative revolution in artificial intelligence (AI) has aided radiologists in the early and accurate diagnosis of breast cancer. In this review, we introduce the necessity of incorporating AI into breast imaging and the applications of AI in mammography, ultrasonography, magnetic resonance imaging, and positron emission tomography/computed tomography based on published articles since 1994. Moreover, the challenges of AI in breast imaging are discussed.

The Role of the Tumor Microenvironment in Triple-Positive Breast Cancer Progression and Therapeutic Resistance

Breast cancer (BRCA) is a highly heterogeneous systemic disease. It is ranked first globally in the incidence of new cancer cases and has emerged as the primary cause of cancer-related death among females. Among the distinct subtypes of BRCA, triple-positive breast cancer (TPBC) has been associated with increased metastasis and invasiveness, exhibiting greater resistance to endocrine therapy involving trastuzumab. It is now understood that invasion, metastasis, and treatment resistance associated with BRCA progression are not exclusively due to breast tumor cells but are from the intricate interplay between BRCA and its tumor microenvironment (TME). Accordingly, understanding the pathogenesis and evolution of the TPBC microenvironment demands a comprehensive approach. Moreover, addressing BRCA treatment necessitates a holistic consideration of the TME, bearing significant implications for identifying novel targets for anticancer interventions. This review expounds on the relationship between critical cellular components and factors in the TPBC microenvironment and the inception, advancement, and therapeutic resistance of breast cancer to provide perspectives on the latest research on TPBC.

Identification of Luminal A breast cancer by using deep learning analysis based on multi-modal images

Purpose

To evaluate the diagnostic performance of a deep learning model based on multi-modal images in identifying molecular subtype of breast cancer.

Materials and methods

A total of 158 breast cancer patients (170 lesions, median age, 50.8 ± 11.0 years), including 78 Luminal A subtype and 92 non-Luminal A subtype lesions, were retrospectively analyzed and divided into a training set (n = 100), test set (n = 45), and validation set (n = 25). Mammography (MG) and magnetic resonance imaging (MRI) images were used. Five single-mode models, i.e., MG, T2-weighted imaging (T2WI), diffusion weighting imaging (DWI), axial apparent dispersion coefficient (ADC), and dynamic contrast-enhanced MRI (DCE-MRI), were selected. The deep learning network ResNet50 was used as the basic feature extraction and classification network to construct the molecular subtype identification model. The receiver operating characteristic curve were used to evaluate the prediction efficiency of each model.

Results

The accuracy, sensitivity and specificity of a multi-modal tool for identifying Luminal A subtype were 0.711, 0.889, and 0.593, respectively, and the area under the curve (AUC) was 0.802 (95% CI, 0.657- 0.906); the accuracy, sensitivity, and AUC were higher than those of any single-modal model, but the specificity was slightly lower than that of DCE-MRI model. The AUC value of MG, T2WI, DWI, ADC, and DCE-MRI model was 0.593 (95%CI, 0.436-0.737), 0.700 (95%CI, 0.545-0.827), 0.564 (95%CI, 0.408-0.711), 0.679 (95%CI, 0.523-0.810), and 0.553 (95%CI, 0.398-0.702), respectively.

Conclusion

The combination of deep learning and multi-modal imaging is of great significance for diagnosing breast cancer subtypes and selecting personalized treatment plans for doctors.

Clinical, Pathological, and Prognostic Features of Male Breast Cancer: A Multicenter Study

Male breast cancer (BC) represents less than 1% of male tumors. Little is known about male BC characteristics, management, and survival, with many studies based on a small number of cases. Consequently, the treatment of male BC lacks specific guidelines. The aims of the study are to compare male and female breast cancer (FBC) in terms of cancer clinical and anatomopathological features and treatment approach, and to identify differences between male BC and FBC in terms of survival. Patients and methods: Data from 2006 to 2018 were retrospectively acquired. Amounts of 49 males and 680 postmenopausal females with primary non-metastatic BC who underwent breast surgery at Mauriziano Hospital or IRCCS Candiolo (TO-Italy) were included. The mean age at diagnosis for male BC was 68.6 years, and males presented a smaller tumor size than women (p < 0.05) at diagnosis. Most male BC patients received adjuvant endocrine therapy (AET) with tamoxifen (73.5%). AET drop-out rate due to side effects was 16.3% for males compared to 7.6% for women (p = 0.04). Comparing FBC and male BC, no differences have been identified in terms of DFS and OS, with a similar 10-year-relapse rate (12% male BC vs. 12.4% FBC). Propensity Score Matching by age, nodal status, pT, and molecular subtype had been performed and no differences in OS and DFS were seen between male BC and FBC. In conclusion, male BC and FBC have similar prognostic factors and survival outcomes. The drop-out rate of AET was higher in males, and side effects were the main reason for drug discontinuation.

Multimodal prediction of neoadjuvant treatment outcome by serial FDG PET and MRI in women with locally advanced breast cancer

PURPOSE

To investigate combined MRI and 18F-FDG PET for assessing breast tumor metabolism/perfusion mismatch and predicting pathological response and recurrence-free survival (RFS) in women treated for breast cancer.

METHODS

Patients undergoing neoadjuvant chemotherapy (NAC) for locally-advanced breast cancer were imaged at three timepoints (pre, mid, and post-NAC), prior to surgery. Imaging included diffusion-weighted and dynamic contrast-enhanced (DCE-) MRI and quantitative 18F-FDG PET. Tumor imaging measures included apparent diffusion coefficient, peak percent enhancement (PE), peak signal enhancement ratio (SER), functional tumor volume, and washout volume on MRI and standardized uptake value (SUVmax), glucose delivery (K1) and FDG metabolic rate (MRFDG) on PET, with percentage changes from baseline calculated at mid- and post-NAC. Associations of imaging measures with pathological response (residual cancer burden [RCB] 0/I vs. II/III) and RFS were evaluated.

RESULTS

Thirty-five patients with stage II/III invasive breast cancer were enrolled in the prospective study (median age: 43, range: 31-66 years, RCB 0/I: N = 11/35, 31%). Baseline imaging metrics were not significantly associated with pathologic response or RFS (p > 0.05). Greater mid-treatment decreases in peak PE, along with greater post-treatment decreases in several DCE-MRI and 18F-FDG PET measures were associated with RCB 0/I after NAC (p < 0.05). Additionally, greater mid- and post-treatment decreases in DCE-MRI (peak SER, washout volume) and 18F-FDG PET (K1) were predictive of prolonged RFS. Mid-treatment decreases in metabolism/perfusion ratios (MRFDG/peak PE, MRFDG/peak SER) were associated with improved RFS.

CONCLUSION

Mid-treatment changes in both PET and MRI measures were predictive of RCB status and RFS following NAC. Specifically, our results indicate a complementary relationship between DCE-MRI and 18F-FDG PET metrics and potential value of metabolism/perfusion mismatch as a marker of patient outcome.

Immunohistochemistry-derived subtypes of breast cancer distribution in four regions of Ethiopia

Purpose

Different biological characteristics, therapeutic responses, and disease-specific outcomes are associated with different molecular subtypes of breast cancer (BC). Although there have been different studies on BC in the Ethiopian capital city of Addis Ababa, there have been few studies in other parts of the nation, and none have evaluated biological characteristics in other locations in the context of the extensive ethnic and genetic diversity found in Ethiopia. This study was carried out to evaluate the distribution of immunohistochemistry (IHC) subtypes of BCs throughout four Ethiopian regions.

Methods

A total of 227 formalin-fixed paraffin-embedded (FFPE) tissue blocks were collected from tertiary hospitals in four Ethiopian regions between 2015 and 2021. The IHC staining was performed for subtyping, ER, PR, HER2, and Ki-67 proliferation markers.

Results

The mean age at diagnosis was 43.9 years. The percentage of ER and PR-negative tumors were 48.3% and 53.2%, respectively. The IHC subtypes showed the following distribution: 33.1% triple-negative breast cancer (TNBC), 27.6% luminal B, 25.2% luminal A, and 14.1% HER2 enriched. In multiple logistic regression analysis, grade III and HER2 positivity were associated with larger tumor size, and also originating from Jimma compared to Mekele.

Conclusion

Patients with ER-negative, PR-negative, and TNBC were found in 48.3%, 53.2%, and 33.1% of cases, respectively, showing that half the patients could potentially benefit from endocrine treatment. A considerably high prevalence of TNBC was reported in our study, demanding additional research that includes genetic predisposition factors. Additionally, aggressive tumors were found in a high percentage of younger age groups, which must be considered when planning personalized treatment strategies.

Multimodal imaging of metabolic activities for distinguishing subtypes of breast cancer

Triple negative breast cancer (TNBC) is a highly aggressive form of cancer. Detecting TNBC early is crucial for improving disease prognosis and optimizing treatment. Unfortunately, conventional imaging techniques fall short in providing a comprehensive differentiation of TNBC subtypes due to their limited sensitivity and inability to capture subcellular details. In this study, we present a multimodal imaging platform that integrates heavy water (D2O)-probed stimulated Raman scattering (DO-SRS), two-photon fluorescence (TPF), and second harmonic generation (SHG) imaging. This platform allows us to directly visualize and quantify the metabolic activities of TNBC subtypes at a subcellular level. By utilizing DO-SRS imaging, we were able to identify distinct levels of de novo lipogenesis, protein synthesis, cytochrome c metabolic heterogeneity, and lipid unsaturation rates in various TNBC subtype tissues. Simultaneously, TPF imaging provided spatial distribution mapping of NAD[P]H and flavin signals in TNBC tissues, revealing a high redox ratio and significant lipid turnover rate in TNBC BL2 (HCC1806) samples. Furthermore, SHG imaging enabled us to observe diverse orientations of collagen fibers in TNBC tissues, with higher anisotropy at the tissue boundary compared to the center. Our multimodal imaging platform offers a highly sensitive and subcellular approach to characterizing not only TNBC, but also other tissue subtypes and cancers.

Update on the Use of Molecular Subtyping in Breast Cancer

The standard of care for invasive cancers of the breast has been and continues to be to evaluate them for breast prognostic markers: estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 by immunohistochemistry. Over 2 decades ago, a study was the first to report on the molecular subtypes of breast cancer. Four main subtypes were reported. Since then there have been some changes in the molecular subtype classification, but overall many studies have shown that this subtyping has clinical prognostic and predictive value. More recently, molecular assays have been developed and studies have shown similar clinical prognostic and predictive value. We reviewed the literature for studies evaluating the clinical significance of all 3 of these methods of evaluation and the follow-up findings of that review are presented below.

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

Artificial intelligence in breast cancer: application and future perspectives

Breast cancer is one of the most common cancers and is one of the leading causes of cancer-related deaths in women worldwide. Early diagnosis and treatment are the key for a favorable prognosis. The application of artificial intelligence technology in the medical field is increasingly extensive, including image analysis, automated diagnosis, intelligent pharmaceutical system, personalized treatment and so on. AI-based breast cancer imaging, pathology and adjuvant therapy technology cannot only reduce the workload of clinicians, but also continuously improve the accuracy and sensitivity of breast cancer diagnosis and treatment. This paper reviews the application of AI in breast cancer, as well as looks ahead and poses challenges to the future development of AI for breast cancer detection and therapeutic, so as to provide ideas for future research.

Machine learning radiomics of magnetic resonance imaging predicts recurrence-free survival after surgery and correlation of LncRNAs in patients with breast cancer: a multicenter cohort study

BACKGROUND

Several studies have indicated that magnetic resonance imaging radiomics can predict survival in patients with breast cancer, but the potential biological underpinning remains indistinct. Herein, we aim to develop an interpretable deep-learning-based network for classifying recurrence risk and revealing the potential biological mechanisms.

METHODS

In this multicenter study, 1113 nonmetastatic invasive breast cancer patients were included, and were divided into the training cohort (n = 698), the validation cohort (n = 171), and the testing cohort (n = 244). The Radiomic DeepSurv Net (RDeepNet) model was constructed using the Cox proportional hazards deep neural network DeepSurv for predicting individual recurrence risk. RNA-sequencing was performed to explore the association between radiomics and tumor microenvironment. Correlation and variance analyses were conducted to examine changes of radiomics among patients with different therapeutic responses and after neoadjuvant chemotherapy. The association and quantitative relation of radiomics and epigenetic molecular characteristics were further analyzed to reveal the mechanisms of radiomics.

RESULTS

The RDeepNet model showed a significant association with recurrence-free survival (RFS) (HR 0.03, 95% CI 0.02-0.06, P < 0.001) and achieved AUCs of 0.98, 0.94, and 0.92 for 1-, 2-, and 3-year RFS, respectively. In the validation and testing cohorts, the RDeepNet model could also clarify patients into high- and low-risk groups, and demonstrated AUCs of 0.91 and 0.94 for 3-year RFS, respectively. Radiomic features displayed differential expression between the two risk groups. Furthermore, the generalizability of RDeepNet model was confirmed across different molecular subtypes and patient populations with different therapy regimens (All P < 0.001). The study also identified variations in radiomic features among patients with diverse therapeutic responses and after neoadjuvant chemotherapy. Importantly, a significant correlation between radiomics and long non-coding RNAs (lncRNAs) was discovered. A key lncRNA was found to be noninvasively quantified by a deep learning-based radiomics prediction model with AUCs of 0.79 in the training cohort and 0.77 in the testing cohort.

CONCLUSIONS

This study demonstrates that machine learning radiomics of MRI can effectively predict RFS after surgery in patients with breast cancer, and highlights the feasibility of non-invasive quantification of lncRNAs using radiomics, which indicates the potential of radiomics in guiding treatment decisions.

(Nano)platforms in breast cancer therapy: Drug/gene delivery, advanced nanocarriers and immunotherapy

Breast cancer is the most malignant tumor in women, and there is no absolute cure for it. Although treatment modalities including surgery, chemotherapy, and radiotherapy are utilized for breast cancer, it is still a life-threatening disease for humans. Nanomedicine has provided a new opportunity in breast cancer treatment, which is the focus of the current study. The nanocarriers deliver chemotherapeutic agents and natural products, both of which increase cytotoxicity against breast tumor cells and prevent the development of drug resistance. The efficacy of gene therapy is boosted by nanoparticles and the delivery of CRISPR/Cas9, Noncoding RNAs, and RNAi, promoting their potential for gene expression regulation. The drug and gene codelivery by nanoparticles can exert a synergistic impact on breast tumors and enhance cellular uptake via endocytosis. Nanostructures are able to induce photothermal and photodynamic therapy for breast tumor ablation via cell death induction. The nanoparticles can provide tumor microenvironment remodeling and repolarization of macrophages for antitumor immunity. The stimuli-responsive nanocarriers, including pH-, redox-, and light-sensitive, can mediate targeted suppression of breast tumors. Besides, nanoparticles can provide a diagnosis of breast cancer and detect biomarkers. Various kinds of nanoparticles have been employed for breast cancer therapy, including carbon-, lipid-, polymeric- and metal-based nanostructures, which are different in terms of biocompatibility and delivery efficiency.

Trajectories of body mass index in adulthood and risk of subtypes of postmenopausal breast cancer

BACKGROUND

Body fatness is a dynamic exposure throughout life. To provide more insight into the association between body mass index (BMI) and postmenopausal breast cancer, we aimed to examine the age at onset, duration, intensity, and trajectories of body fatness in adulthood in relation to risk of breast cancer subtypes.

METHODS

Based on self-reported anthropometry in the prospective Norwegian Women and Cancer Study, we calculated the age at onset, duration, and intensity of overweight and obesity using linear mixed-effects models. BMI trajectories in adulthood were modeled using group-based trajectory modeling. We used Cox proportional hazards models to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for the associations between BMI exposures and breast cancer subtypes in 148,866 postmenopausal women.

RESULTS

A total of 7223 incident invasive postmenopausal breast cancer cases occurred during follow-up. Increased overweight duration and age at the onset of overweight or obesity were associated with luminal A-like breast cancer. Significant heterogeneity was observed in the association between age at overweight and overweight duration and the intrinsic-like subtypes (pheterogeneity 0.03). Compared with women who remained at normal weight throughout adulthood, women with a descending BMI trajectory had a reduced risk of luminal A-like breast cancer (HR 0.54, 95% CI 0.33-0.90), whereas women with ascending BMI trajectories were at increased risk (HR 1.09; 95% CI 1.01-1.17 for "Normal-overweight"; HR 1.20; 95% CI 1.07-1.33 for "Normal-obesity"). Overweight duration and weighted cumulative years of overweight and obesity were inversely associated with luminal B-like breast cancer.

CONCLUSIONS

In this exploratory analysis, decreasing body fatness from obesity in adulthood was inversely associated with overall, hormone receptor-positive and luminal A-like breast cancer in postmenopausal women. This study highlights the potential health benefits of reducing weight in adulthood and the health risks associated with increasing weight throughout adult life. Moreover, our data provide evidence of intrinsic-like tumor heterogeneity with regard to age at onset and duration of overweight.

Evaluation of the relationship between Ki67 expression level and neoadjuvant treatment response and prognosis in breast cancer based on the Neo-Bioscore staging system

BACKGROUND

Neoadjuvant chemotherapy (NAC) is widely used in the treatment of primary breast cancer. Different staging systems have been developed to evaluate the residual tumor after NAC and classify patients into different prognostic groups. Ki67, a proliferation marker, has been shown to be useful in predicting treatment response and prognosis. We aimed to investigate the prognostic importance Neo-Bioscore stage and pretreatment and posttreatment Ki67 levels in breast cancer patients who received NAC and correlations between Neo-Bioscore stage and pretreatment and posttreatment Ki67 levels.

METHODS

A total of 176 invasive breast carcinoma patients who underwent NAC were included in the study. Ki67 levels were evaluated by immunohistochemical methods in Trucut biopsy and surgical excision specimens. Patients were classified into prognostic groups using the Neo-Bioscore staging system.

RESULTS

Patients with high pretreatment Ki67 score were more likely to be in the higher Neo-Bioscore risk group (p < 0.001). Patients with a high posttreatment Ki67 score were more likely to be in the higher Neo-Bioscore prognostic risk group (p < 0.001). Overall survival (OS) and disease-free survival (DFS) were shorter in patients with high posttreatment Ki67 scores and in patients in the higher Neo-Bioscore risk group. We also determined a cutoff 37% for pathological complete response.

CONCLUSION

Neo-Bioscore staging system is found to be important in predicting survival. The posttreatment Ki67 level is more important than pretreatment Ki67 level in predicting survival.

The prognostic impact of body mass index on female breast cancer patients in underdeveloped regions of northern China differs by menopause status and tumor molecular subtype

There is growing evidence that higher body mass index (BMI) is associated with lower survival in breast cancer patients. The aim of this study was to investigate whether there is an association between body mass index (BMI) at breast cancer diagnosis and breast cancer prognosis and whether this association is dependent on menopausal status and tumor subtype in a less developed population in northern China. We collected 1,225 patients with primary invasive cancer in stage I-IIIC for retrospective analysis from October 2010 to December 2020. We used Kaplan-Meier and Cox regression analyses and estimated the relationship between baseline BMI and breast cancer-specific survival (BCSS). Next, we further evaluated whether the effect of BMI on breast cancer prognosis differed by menopausal status and tumor subtype. We found that death rate and prognosis were worse for patients with BMI ≥ 24, more than four positive lymph nodes, and triple negative status. Interestingly, BMI played a different prognostic role depending on tumor subtype and menopausal status. For premenopausal women, patients with BMI ≥ 24 had significantly lower BCSS compared to those with BMI < 24 in human epidermal growth factor receptor 2 (HER2) overexpression (HR: 4.305, p = 0.004) and triple negative subtypes (HR: 1.775, p = 0.048). By contrast, there was no association between BMI ≥ 24 and higher death regardless of tumor subtype in post-menopausal patients (p > 0.05). BMI influences breast cancer outcome depending on tumor subtype and menopause. BMI ≥ 24 might be a risk factor for BCSS, particularly in premenopausal women with HER2 overexpression or triple negative subtype. In contrast, BMI ≥ 24 was not associated with higher death regardless of tumor subtype in post-menopausal patients.

Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer

PAM50 gene expression subtypes represent a cornerstone in the molecular classification of breast cancer and are included in risk prediction models to guide therapy. We aimed to illustrate the impact of included genes and biological processes on subtyping while considering a tumor's underlying clinical subgroup defined by ER, PR, and HER2 status. To do this we used a population-representative and clinically annotated early-stage breast tumor cohort of 6233 samples profiled by RNA sequencing and applied a perturbation strategy of excluding co-expressed genes (gene sets). We demonstrate how PAM50 nearest-centroid classification depends on biological processes present across, but also within, ER/PR/HER2 subgroups and PAM50 subtypes themselves. Our analysis highlights several key aspects of PAM50 classification. Firstly, we demonstrate the tight connection between a tumor's nearest and second-nearest PAM50 centroid. Additionally, we show that the second-best subtype is associated with overall survival in ER-positive, HER2-negative, and node-negative disease. We also note that ERBB2 expression has little impact on PAM50 classification in HER2-positive disease regardless of ER status and that the Basal subtype is highly stable in contrast to the Normal subtype. Improved consciousness of the commonly used PAM50 subtyping scheme will aid in our understanding and interpretation of breast tumors that have seemingly conflicting PAM50 classification when compared to clinical biomarkers. Finally, our study adds further support in challenging the common misconception that PAM50 subtypes are distinct classes by illustrating that PAM50 subtypes in tumors represent a continuum with prognostic implications.

Correlation of Perfusion Metrics with Ki-67 Proliferation Index and Axillary Involvement as a Prognostic Marker in Breast Carcinoma Cases: A Dynamic Contrast-Enhanced Perfusion MRI Study

Our study aims to reveal clinically helpful prognostic markers using quantitative radiologic data from perfusion magnetic resonance imaging for patients with locally advanced carcinoma, using the Ki-67 index as a surrogate. Patients who received a breast cancer diagnosis and had undergone dynamic contrast-enhanced magnetic resonance imaging of the breast for pretreatment evaluation and follow-up were searched retrospectively. We evaluated the MRI studies for perfusion parameters and various categories and compared them to the Ki-67 index. Axillary involvement was categorized as low (N0-N1) or high (N2-N3) according to clinical stage. A total sum of 60 patients' data was included in this study. Perfusion parameters and Ki-67 showed a significant correlation with the transfer constant (Ktrans) (ρ = 0.554 p = 0.00), reverse transfer constant (Kep) (ρ = 0.454 p = 0.00), and initial area under the gadolinium curve (IAUGC) (ρ = 0.619 p = 0.00). The IAUGC was also significantly different between axillary stage groups (Z = 2.478 p = 0.013). Outside of our primary hypothesis, associations between axillary stage and contrast enhancement (x2 = 8.023 p = 0.046) and filling patterns (x2 = 8.751 p = 0.013) were detected. In conclusion, these parameters are potential prognostic markers in patients with moderate Ki-67 indices, such as those in our study group. The relationship between axillary status and perfusion parameters also has the potential to determine patients who would benefit from limited axillary dissection.

Hormone Receptor Signaling and Breast Cancer Resistance to Anti-Tumor Immunity

Breast cancers regroup many heterogeneous diseases unevenly responding to currently available therapies. Approximately 70-80% of breast cancers express hormone (estrogen or progesterone) receptors. Patients with these hormone-dependent breast malignancies benefit from therapies targeting endocrine pathways. Nevertheless, metastatic disease remains a major challenge despite available treatments, and relapses frequently ensue. By improving patient survival and quality of life, cancer immunotherapies have sparked considerable enthusiasm and hope in the last decade but have led to only limited success in breast cancers. In addition, only patients with hormone-independent breast cancers seem to benefit from these immune-based approaches. The present review examines and discusses the current literature related to the role of hormone receptor signaling (specifically, an estrogen receptor) and the impact of its modulation on the sensitivity of breast cancer cells to the effector mechanisms of anti-tumor immune responses and on the capability of breast cancers to escape from protective anti-cancer immunity. Future research prospects related to the possibility of promoting the efficacy of immune-based interventions using hormone therapy agents are considered.

In Vitro microRNA Expression Profile Alterations under CDK4/6 Therapy in Breast Cancer

BACKGROUND

Breast cancer is the most common type of cancer worldwide. Cyclin-dependent kinase inhibition is one of the backbones of metastatic breast cancer therapy. However, there are a significant number of therapy failures. This study evaluates the biomarker potential of microRNAs for the prediction of a therapy response under cyclin-dependent kinase inhibition.

METHODS

This study comprises the analysis of intracellular and extracellular microRNA-expression-level alterations of 56 microRNAs under palbociclib mono as well as combination therapy with letrozole. Breast cancer cell lines BT-474, MCF-7 and HS-578T were analyzed using qPCR.

RESULTS

A palbociclib-induced microRNA signature could be detected intracellularly as well as extracellularly. Intracellular miR-10a, miR-15b, miR-21, miR-23a and miR-23c were constantly regulated in all three cell lines, whereas let-7b, let-7d, miR-15a, miR-17, miR-18a, miR-20a, miR-191 and miR301a_3p were regulated only in hormone-receptor-positive cells. Extracellular miR-100, miR-10b and miR-182 were constantly regulated across all cell lines, whereas miR-17 was regulated only in hormone-receptor-positive cells.

CONCLUSIONS

Because they are secreted and significantly upregulated in the microenvironment of tumor cells, miRs-100, -10b and -182 are promising circulating biomarkers that can be used to predict or detect therapy responses under CDK inhibition. MiR-10a, miR-15b, miR-21, miR-23a and miR-23c are potential tissue-based biomarkers.

Small change - big consequence: The impact of C15-C16 double bond in a D‑ring of estrone on estrogen receptor activity

Estrogen receptor alpha (ER) is a key biomarker for breast cancer, and the presence or absence of ER in breast and other hormone-dependent cancers decides treatment regimens and patient prognosis. ER is activated after ligand binding - typically by steroid. 2682 steroid compounds were used in a molecular docking study to identify novel ligands for ER and to predict compounds that may show anticancer activity. The effect of the most promising compounds was determined by a novel luciferase reporter assay. Two compounds, 7 and 12, showing ER inhibitory activity comparable to clinical inhibitors such as tamoxifen or fulvestrant were selected. We propose that the inhibitory effect of compounds 7 and 12 on ER is related to the presence of a double bond in their D-ring, which may protect against ER activation by reducing the electron density of the keto group, or may undergo metabolism leading to an active compound. Western blotting revealed that compound 12 decreased the level of ER in the breast cancer cell line MCF7, which was associated with reduced expression of both isoforms of the progesterone receptor, a well-known downstream target of ER. However, compound 12 has a different mechanism of action from fulvestrant. Furthermore, we found that compound 12 interferes with mitochondrial functions, probably by disrupting the electron transport chain, leading to induction of the intrinsic apoptotic pathway even in ER-negative breast cancer cells. In conclusion, the combination of computational and experimental methods shown here represents a rapid approach to determine the activity of compounds towards ER. Our data will not only contribute to research focused on the regulation of ER activity but may also be useful for the further development of novel steroid receptor-targeted drugs applicable in clinical practice.

Novel Foscan®-derived ring-fused chlorins for photodynamic therapy of cancer

Photodynamic therapy (PDT) is an established anticancer treatment that combines the use of a photosensitiser (PS) and a light source of a specific wavelength for the generation of reactive oxygen species (ROS) that are toxic to the tumour cells. Foscan® (mTHPC) is a clinically-approved chlorin used for the PDT treatment of advanced head and neck, prostate and pancreatic cancers but is characterized by being photochemically unstable and associated with prolonged skin photosensitivity. Herein, we report the synthesis of new 4,5,6,7-tetrahydropyrazolo[1,5-a]pyridine-fused chlorins, having the meso-tetra(3-hydroxyphenyl)macrocycle core of mTHPC, by exploring the [8π + 2π] cycloaddition of a meso-tetra(3-hydroxyphenyl)porphyrin derivative with diazafulvenium methides. These chlorins have photochemical properties similar to Foscan® but are much more photostable. Among the novel compounds, two chlorins with a hydroxymethyl group and its azide derivative present in the 4,5,6,7-tetrahydropyrazolo[1,5-a]pyridine-fused system, are promising photodynamic agents with activity in the 100 nM range against triple-negative breast cancer cells and, in the case of azidomethyl chlorin, a safer phototherapeutic index compared to Foscan®.

Analysis of Turkish Breast Cancer Patients With ATM-Heterozygous Germline Mutation According to Clinicopathological Features

OBJECTIVE

The ATM gene is one of the most common breast cancer (BC) susceptibility genes after BRCA1/2 and has been shown to be a moderate BC susceptibility gene. The association between ATM germline mutation and clinical features of BC is now unknown. In this article, clinicopathological features of BC patients with ATM germline heterozygous mutation were investigated.

MATERIALS AND METHODS

Patients admitted to the Medical Genetics department of a tertiary hospital between January 2020 and December 2022 were examined. Only invasive BC patients with pathogenic mutation, likely pathogenic mutation, or variants of uncertain significance (VUS) were included in the study.

RESULTS

In all, 121 patients were included in the study. The median age at the first cancer diagnosis of the patients was 44 years. Of the total number of patients, 75.2% (91) had the histological subtype of infiltrating ductal carcinoma, and 43% (52) had Luminal B molecular subtype features. At a median follow-up of 16 months, 5.8% (7) of patients developed cancer in the contralateral breast. In addition, 7.4% (9) of the patients developed a second primary cancer during follow-up. When the patients were compared according to ATM variant classification, the localization, histologic types, and molecular subtypes of the BC were not different between all groups (respectively; p=0.68, p=0.65, p=0.32).

CONCLUSIONS

To the best of our knowledge, this is the first publication that evaluates the clinical and pathological characteristics of BC patients with germline heterozygous ATM mutations in the Turkish population. When patients were compared according to variant classifications of ATM mutation, patients' histological and molecular subtypes were similar.

Low levels of WRAP53 predict decreased efficacy of radiotherapy and are prognostic for local recurrence and death from breast cancer: a long-term follow-up of the SweBCG91RT randomized trial

Downregulation of the DNA repair protein WD40-encoding RNA antisense to p53 (WRAP53) has been associated with radiotherapy resistance and reduced cancer survival. The aim of this study was to evaluate WRAP53 protein and RNA levels as prognostic and predictive markers in the SweBCG91RT trial, in which breast cancer patients were randomized for postoperative radiotherapy. Using tissue microarray and microarray-based gene expression, 965 and 759 tumors were assessed for WRAP53 protein and RNA levels, respectively. Correlation with local recurrence and breast cancer-related death was assessed for prognosis, and the interaction between WRAP53 and radiotherapy in relation to local recurrence was assessed for radioresistance prediction. Tumors with low WRAP53 protein levels had a higher subhazard ratio (SHR) for local recurrence [1.76 (95% CI 1.10-2.79)] and breast cancer-related death [1.55 (1.02-2.38)]. Low WRAP53 RNA levels were associated with almost a three-fold decreased effect of radiotherapy in relation to ipsilateral breast tumor recurrence [IBTR; SHR 0.87 (95% CI 0.44-1.72)] compared with high RNA levels [0.33 (0.19-0.55)], with a significant interaction (P = 0.024). In conclusion, low WRAP53 protein is prognostic for local recurrence and breast cancer-related death. Low WRAP53 RNA is a potential marker for radioresistance.

Development of an Anti-EphB4 Monoclonal Antibody for Multiple Applications Against Breast Cancers

The erythropoietin-producing hepatocellular carcinoma (Eph) receptors are the largest receptor tyrosine kinase family. EphB4 is essential for cell adhesion and motility during embryogenesis. Pathologically, EphB4 is overexpressed and contributes to poor prognosis in various tumors. Therefore, specific monoclonal antibodies (mAbs) should be developed to predict the prognosis for multiple tumors with high EphB4 expression, including breast and gastric cancers. This study aimed to develop specific anti-EphB4 mAbs for multiple applications using the Cell-Based Immunization and Screening method. EphB4-overexpressed Chinese hamster ovary (CHO)-K1 (CHO/EphB4) cells were immunized into mice, and we established an anti-EphB4 mAb (clone B4Mab-7), which is applicable for flow cytometry, Western blot, and immunohistochemistry (IHC). B4Mab-7 reacted with endogenous EphB4-positive breast cancer cell line, MCF-7, but did not react with EphB4-knockout MCF-7 (BINDS-52) in flow cytometry. Dissociation constant (KD) values were determined to be 2.9 × 10-9 M and 1.3 × 10-9 M by flow cytometric analysis for CHO/EphB4 and MCF-7 cells, respectively. B4Mab-7 detected the EphB4 protein bands from breast cancer cells in Western blot, and stained breast cancer tissues in IHC. Altogether, B4Mab-7 is very useful for detecting EphB4 in various applications.

The tremendous clinical potential of the microbiota in the treatment of breast cancer: the next frontier

Although significant advances have been made in the diagnosis and treatment of breast cancer (BC) in recent years, BC remains the most common cancer in women and one of the main causes of death among women worldwide. Currently, more than half of BC patients have no known risk factors, emphasizing the significance of identifying more tumor-related factors. Therefore, we urgently need to find new therapeutic strategies to improve prognosis. Increasing evidence demonstrates that the microbiota is present in a wider range of cancers beyond colorectal cancer. BC and breast tissues also have different types of microbiotas that play a key role in carcinogenesis and in modulating the efficacy of anticancer treatment, for instance, chemotherapy, radiotherapy, and immunotherapy. In recent years, studies have confirmed that the microbiota can be an important factor directly and/or indirectly affecting the occurrence, metastasis and treatment of BC by regulating different biological processes, such as estrogen metabolism, DNA damage, and bacterial metabolite production. Here, we review the different microbiota-focused studies associated with BC and explore the mechanisms of action of the microbiota in BC initiation and metastasis and its application in various therapeutic strategies. We found that the microbiota has vital clinical value in the diagnosis and treatment of BC and could be used as a biomarker for prognosis prediction. Therefore, modulation of the gut microbiota and its metabolites might be a potential target for prevention or therapy in BC.

Analysis of clinicopathological characteristics and prognostic factors of early-stage human epidermal growth factor receptor 2 (HER2)-low breast cancer: Compared with HER2-0 breast cancer

PURPOSE

To investigate the clinicopathological characteristics and prognostic factors of early-stage breast cancer (EBC) with human epidermal growth factor receptor 2 (HER2)-low expression.

METHODS

The clinicopathological data and follow-up information of EBC patients with HER2-low and HER2-0 expression treated at the Breast Disease Center of Peking University First Hospital from January 2014 to December 2017 were analyzed. The prognosis between HER2-low and HER2-0 expression groups and with different hormone receptor (HR) expression were compared by statistics. Meanwhile, the expression of Ki67, androgen receptor (AR), TOPIIa, P53, PTEN, and CK5/6 were also analyzed with the HER2-low expression and prognosis.

RESULTS

Retrospectively analyzed 1253 cases of EBC, including 583 (46.5%) cases of HER2-low breast cancer (BC) and 366 (29.2%) HER2-0 BC cases. Among the HER2-low BC patients, 487 (83.5%) were HR-positive, while 96 (16.5%) were HR-negative. Among the HER2-0 BC patients, 265 (72.4%) were HR-positive, while 101 (27.6%) were HR-negative. Median follow-up time was 53 months. The 5-year disease-free survival of HER2-low BC patients was 90.2% (95% confidence interval [CI]: 87.2-93.1), and the 5-year overall survival was 95.4% (95% CI: 93.3-97.6). Cox regression analysis showed that T stage, lymphovascular invasion, and/or perineural invasion were prognostic factors of HER2-low BC patients. However, the 5-year disease-free survival and overall survival of patients in the HER2-low and HER2-0 groups were not significantly different in all patients, but a tendency of better prognosis in HER2-low group was seen in HR-negative tumors.

CONCLUSION

HER2-low EBC patients accounted for 46.5% of the patient population. T stage, lymphovascular invasion, and/or perineural invasion were factors affecting the prognosis of BC patients with low HER2 expression. No significant difference in prognosis was noted between HER2-low and HER2-0 EBC patients. But in HR-negative tumors, a tendency of better prognosis was seen in HER2-low versus HER2-0.

Early screening outcomes before, during, and after a randomized controlled trial with digital breast tomosynthesis

PURPOSE

To describe and compare early screening outcomes before, during and after a randomized controlled trial with digital breast tomosynthesis (DBT) including synthetic 2D mammography versus standard digital mammography (DM) (To-Be 1) and a follow-up cohort study using DBT (To-Be 2).

METHODS

Retrospective results of 125,020 screening examinations from four consecutive screening rounds performed in 2014-2021 were described and compared for pre-To-Be 1 (DM), To-Be 1 (DM or DBT), To-Be 2 (DBT), and post-To-Be 2 (DM) cohorts. Descriptive analyses of rates of recall, biopsy, screen-detected and interval cancer, distribution of histopathologic tumor characteristics and time spent on image interpretation and consensus were presented for the four rounds including five cohorts, one cohort in each screening round except for the To-Be 1 trail, which included a DBT and a DM cohort. Odds ratios (OR) with 95% CIs was calculated for recall and cancer detection rates.

RESULTS

Rate of screen-detected cancer was 0.90% for women screened with DBT in To-Be 2 and 0.64% for DM in pre-To-Be 1. The rates did not differ for the To-Be 1 DM (0.61%), To-Be 1 DBT (0.66%) and post-To-Be 2 DM (0.67%) cohorts. The interval cancer rates ranged between 0.13% and 0.20%. The distribution of histopathologic tumor characteristics did not differ between the cohorts.

CONCLUSIONS

Screening all women with DBT following a randomized controlled trial in an organized, population-based screening program showed a temporary increase in the rate of screen-detected cancer.

High Expression of NRF2 and Low Expression of KEAP1 Predict Worse Survival in Patients With Operable Triple-Negative Breast Cancer

PURPOSE

Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer. Currently, no effective treatment options for this condition exist. Nuclear factor erythroid 2-related factor 2 (NRF2), encoded by nuclear factor erythroid-derived 2-like 2 (NFE2L2) gene and its endogenous inhibitor, Kelch-like ECH-associated protein 1 (KEAP1), both participate in cellular defense mechanisms against oxidative stress and contribute to chemoresistance and tumor progression in numerous types of cancers. This study aimed to evaluate the expression patterns of NRF2 and KEAP1 and their prognostic value in operable TNBC.

METHODS

Tissue microarrays were prepared using tumor tissues collected from 203 patients with TNBC who underwent surgery. Immunohistochemical staining analyses of NRF2 and KEAP1 were performed. The expression of each immunomarker was categorized into two groups (low or high) based on the median H-score. We analyzed the association between the expression of each immunomarker and clinicopathological information to predict survival. A total of 225 TNBC samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were used to validate our results.

RESULTS

NRF2 immunoreactivity was detected in the nucleus and was associated with histologic grade and Ki-67 index, whereas KEAP1 immunoreactivity was detected in the cytoplasm and was associated with the Ki-67 index. Survival analyses showed that NRF2 and KEAP1 expressions were independent prognostic factors for overall survival (OS) (hazard ratio [HR], 2.45 and 0.30; p = 0.015 and 0.016, respectively) and disease-free survival (HR, 2.27 and 0.42; p = 0.019 and 0.022, respectively). NFE2L2 mRNA expression was an independent prognostic factor for OS (HR, 0.59; p = 0.009) in the METABRIC dataset.

CONCLUSION

High NRF2 and low KEAP1 expressions independently predicted poor survival in patients with operable TNBC. Further investigations are warranted to examine the possible therapeutic benefits of targeting the KEAP1-NRF2 pathway for TNBC treatment.

Accuracy of cytological grading in the carcinoma breast and its correlation with pathological prognostic parameters

BACKGROUND

Breast carcinoma is a significant contributor to cancer deaths worldwide. Tumor grade is an important parameter in planning out the treatment. Histology is the gold standard for grading the carcinoma breast. However, fine-needle aspiration cytology (FNAC) is still an important first-line diagnostic procedure in many parts of the world. Grading on cytology will help in pre-operative management. Although cytological grading of the carcinoma breast is a topic of research for many years, it is not yet included as a part of routine cytology reports.

MATERIALS AND METHODS

A prospective study was conducted over a period of 1 year at Kalinga Institute of Medical Sciences. A total of 42 cases of carcinoma breast, diagnosed on FNAC and subsequently confirmed on histology, were included. Cytological grading was performed using Robinson's grading system, and the results were compared with the histological grade. Also, the cytological grades were correlated with various pathological prognostic parameters such as tumor size, lymph node status, lympho-vascular invasion, estrogen and progesterone receptor status, Her-2-neu expression, and Ki-67 index. The kappa measure of agreement and Fisher's exact test were used for statistical analysis.

RESULTS

A moderate kappa measure of agreement (k = 0.415) was found between cytological and histological grades with an overall concordance rate of 66.67%. The accuracy of cytological grading was higher with increasing cytological grade. Except for estrogen receptor expression, none of the other prognostic parameters have a statistically significant correlation with cytological grade.

CONCLUSIONS

Tumor grading on cytology can be helpful in planning treatment, especially in resource-constrained settings. Subjective variation in assessing different parameters and non-inclusion of mitosis in this system might be the reasons behind wrong grading in some cases. Inclusion of mitosis in the scoring system can improve the accuracy of cytological grading and its importance in prognosis.

The quality and clinical translation of radiomics studies based on MRI for predicting Ki-67 levels in patients with breast cancer

OBJECTIVE

To evaluate the methodological quality of radiomics literature predicting Ki-67 levels based on MRI in patients with breast cancer (BC) and to propose suggestions for clinical translation.

METHODS

In this review, we searched PubMed, Embase, and Web of Science for studies published on radiomics in patients with BC. We evaluated the methodological quality of the studies using the Radiomics Quality Score (RQS). The Cochrane Collaboration's software (RevMan 5.4), Meta-DiSc (v. 1.4) and IBM SPSS (v. 26.0) were used for all statistical analyses.

RESULTS

Eighteen studies met our inclusion criteria, and the average RQS was 10.17 (standard deviation [SD]: 3.54). None of these studies incorporated any of the following items: a phantom study on all scanners, cut-off analyses, prospective study, cost-effectiveness analysis, or open science and data. In the meta-analysis, it showed apparent diffusion coefficient (ADC) played a better role to predict Ki-67 level than dynamic contrast-enhanced (DCE) MRI in the radiomics, with the pooled area under the curve (AUC) of 0.969.

CONCLUSION

Ki-67 index is a common tumor biomarker with high clinical value. Radiomics is an ever-growing quantitative data-mining method helping predict tumor biomarkers from medical images. However, the quality of the reviewed studies evaluated by the RQS was not so satisfactory and there are ample opportunities for improvement. Open science and data, external validation, phantom study, publicly open radiomics database and standardization in the radiomics practice are what researchers should pay more attention to in the future.

ADVANCES IN KNOWLEDGE

The RQS tool considered the radiomics used to predict the Ki-67 level was of poor quality. ADC performed better than DCE in radiomic prediction. We propose some measures to facilitate the clinical translation of radiomics.

Differences between the efficacy of HER2(2+)/FISH-positive and HER2(3+) in breast cancer during dual-target neoadjuvant therapy

INTRODUCTION

This study investigated the differences in efficacy between IHC(2+)/FISH-positive and IHC(3+) in HER2-positive breast cancer (BC) during neoadjuvant chemotherapy (NAC) combined with trastuzumab and pertuzumab. The research also aimed to provide insight into treatment strategies for clinical HER2(2+)/FISH-positive and HER2(3+) BC.

MATERIALS AND METHODS

A retrospective analysis was performed on the clinical and pathological data of patients with confirmed diagnoses of invasive BC treated via combined NAC and dual-target therapy who underwent surgery at the Breast Surgery Center of Sichuan Cancer Hospital between June 2019 and June 2022. The correlation between the clinicopathological characteristics and pathological complete response (pCR) was analyzed via the χ2 test, while logistic regression was performed using the SAS 9.4 statistical analysis software.

RESULTS

This study examined 224 patients with an overall pCR rate of approximately 59.82%, which included 36 IHC(2+)/FISH-positive and 188 IHC(3+) cases with approximate pCR rates of 41.67% and 63.30%, respectively. Univariate and multifactorial analysis of the clinical and pathological data determined that age, menstrual status, family history, Ki67 expression, number of treatment cycles, and treatment regimen did not influence pCR. No statistical differences were evident between the univariate and multivariate models. However, the clinical stage, hormone receptor, and HER2 expression status significantly impacted pCR, with considerable consistent differences between the univariate and multifactor analyses.

CONCLUSIONS

HER2 IHC(3+) BC displays a higher pCR rate than HER2 IHC(2+)/FISH-positive BC (p ≤ 0.05), with a positive correlation between the HER2 protein expression levels and the response to anti-HER2 therapy.

Breast cancer molecular subtype and relationship with clinicopathological profiles among Vietnamese women: A retrospective study

BACKGROUND

Molecular subtypes play an important role in predicting prognosis and guiding treatment for breast cancer. Having a better knowledge of ethnic molecular features is essential.

OBJECTIVES

Determining the distribution of various breast cancer molecular subtypes and investigating the relationship between these subtypes and clinicopathological features.

METHODS

Retrospective data was collected from Hanoi National Cancer Hospital and Bach Mai Hospital that included 274 women diagnosed with invasive breast cancer between January 2017 and June 2019. Patients were categorized into five subtypes according to the 2015 St. Gallen molecular classification. The variables analyzed were molecular subtypes and tumor-related characteristics. To evaluate the relationship between these subtypes and clinicopathological features, a Chi-squared test and Fisher exact test were performed.

RESULTS

The most prominent subtype was Luminal A (33.2%), followed by Luminal B/Her2- (19.7%) and Luminal B/Her2 + (17.5%), then HER2 overexpression (16.4%), whereas triple negative was the least popular subtype (13.1%). Particularly, 33.9% of all patients, including the Luminal B/Her2 + and the HER2 overexpressing groups, were Her2 positive. There was a statistically significant difference between molecular subtypes and histological type (p = 0.01), tumor grade (p < 0.001), but it was independent of age, tumor size, lymph node metastasis, and lymphovascular invasion.

CONCLUSIONS

In contrast to the triple negative variant, the Luminal A variant is the most common among Vietnamese women. The rate of positive tests for HER2 was rather high. These subtypes were closely related to tumor grade and histopathological type. Understanding the molecular subtypes and their relation to clinicopathological features helps clinicians with patient treatment, and prognosis. The application of the 2015 St. Gallen molecular classification should be recommended for use in clinical practice.

MAP3K1 expression is associated with progression and poor prognosis of hormone receptor-positive, HER2-negative early-stage breast cancer

PURPOSE

In this study, we assessed whether the overexpression of MAP3K1 promotes the proliferation, migration, and invasion of breast cancer cells, which affect the prognosis of hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative early stage breast cancer.

METHODS

Two HR-positive, HER2-negative breast cancer cell lines (MCF7 and T-47D) overexpressing MAP3K1 were transfected with two MAP3K1 short hairpin RNA plasmids (shMAP3K1 [#3] and shMAP3K1 [#5]). The proliferation, migration, and invasion of these cells were then examined. We assessed whether shMAP3K1 affects the cell cycle, levels of downstream signaling molecules (ERK, JNK, p38 MAPK, and NF-κB), and sensitivity to chemotherapeutic and hormonal agents. To assess the anti-tumor effect of MAP3K1 knockdown in the breast cancer orthotopic model, MCF7 and T-47D cells treated with or without shMAP3K1 (#3) and shMAP3K1 (#5) were inoculated into the mammary fat pads of mice. In total, 182 patients with HR-positive, HER2-negative T1 and T2 breast cancer and 0-3 nodal metastases were included. Additionally, 73 patients with T1 and T2 breast cancer and negative nodes who received adjuvant endocrine therapy alone were selected as an independent validation cohort.

RESULTS

In both cell lines, shMAP3K1 (#3) and shMAP3K1 (#5) significantly reduced cell growth, migration, and invasion by downregulating MMP-9 and by blocking the G2/M phase of the cell cycle and its regulatory molecule cyclin B1. Moreover, both shMAP3K1 (#3) and shMAP3K1 (#5) downregulated ERK-, JNK-, p38 MAPK-, and NF-κB-dependent gene transcription and enhanced the sensitivity of both cell lines to doxorubicin, docetaxel, and tamoxifen. We observed that both shMAP3K1 (#3) and shMAP3K1 (#5) inhibited tumor growth compared with that in the scrambled group of MCF7 and T-47D cell orthotopic tumors. Patients with MAP3K1 overexpression exhibited significantly poorer 10-year disease-free survival (DFS) (70.4% vs. 88.6%, p = 0.003) and overall survival (OS) (81.9% vs. 96.3%, p = 0.001) than those without MAP3K1 overexpression. Furthermore, phospho-ERK (p < 0.001) and phospho-JNK (p < 0.001) expressions were significantly associated with MAP3K1 expression, and both phospho-ERK and phospho-JNK expressions were significantly correlated with poor 10-year DFS and OS. These biological findings, including a significant association between DFS and OS, and the expressions of MAP3K1, phospho-ERK, and phospho-JNK were further validated in an independent cohort. Multivariate analysis identified MAP3K1 expression as an independent poor prognostic factor for DFS and OS.

CONCLUSION

Our results indicate that the overexpression of MAP3K1 plays a major role in the poor prognosis of HR-positive, HER2-negative early stage breast cancer.

Pathological complete response, category change, and prognostic significance of HER2-low breast cancer receiving neoadjuvant treatment: a multicenter analysis of 2489 cases

BACKGROUND

HER2-low breast cancers (BC) show a good response to novel anti-HER2 antibody-drug conjugates (ADCs) in advanced setting. Nevertheless, little is known about the response, category change, and prognosis of HER2-low BC receiving neoadjuvant treatment (NAT).

METHODS

Consecutive invasive BC patients who underwent ≥ 4 cycles of NAT and surgery from January 2009 to December 2020 were retrospectively reviewed. HER2-low was defined as IHC 1+ or 2+ and FISH negative. Concordance rates of HER2 and other biomarkers were analyzed by Kappa test. Kaplan-Meier analysis and Cox regression were used to assess the recurrence-free interval (RFI) and overall survival (OS).

RESULTS

A total of 2489 patients were included, of whom 1023 (41.1%) had HER2-low tumors. HER2-low patients had a higher ER positivity rate than HER2-0 patients (78.5% vs. 63.6%, P < 0.001), and a similar breast pathological complete response (pCR) rate (20.6% vs. 21.8%, P = 0.617). Among non-pCR cases, 39.5% of HER2-0 tumors changed to HER2-low, and 14.3% of HER2-low tumors changed to HER2-0 after NAT. Low concordance rates of HER2-low status were found in both ER-positive (Kappa = 0.368) and ER-negative (Kappa = 0.444) patients. Primary HER2-low patients had a significantly better RFI than HER2-0 patients (P = 0.014), especially among ER-positive subset (P = 0.016). Moreover, HER2-low category change was associated with RFI in ER-positive subset (adjusted P = 0.043).

CONCLUSIONS

Compared with HER2-0 patients, HER2-low patients had a high proportion of ER-positive tumor and a similar pCR rate, which were related with better prognosis, especially in residual cases after NAT. A remarkable instability of HER2-low status was found between the primary and residual tumor, indicating re-testing HER2 status after NAT in the new era of anti-HER2 ADCs therapy.

Application of ultrasound-based radiomics models of breast masses to predict invasive components of encapsulated papillary carcinoma

Background

Axillary lymph node (ALN) metastasis is seen in encapsulated papillary carcinoma (EPC), mostly with an invasive component (INV). Radiomics can offer more information beyond subjective grayscale and color Doppler ultrasound (US) image interpretation. This study aimed to develop radiomics models for predicting an INV of EPC in the breast based on US images.

Methods

This study retrospectively enrolled 105 patients (107 masses) with a pathological diagnosis of EPC from January 2016 to April 2021, and all masses had preoperative US images. Of the 107 masses, 64 were randomized to a training set and 43 to a test set. US and clinical features were analyzed to identify features associated with INVs. Then, based on the manually segmented US images to obtain radiomics features, the models to predict INVs were built with 5 ensemble machine learning classifiers. We estimated the performance of the predictive models using accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, and specificity.

Results

The mean age was 63.71 years (range, 31 to 85 years); the mean size of tumors was 23.40 mm (range, 9 to 120 mm). Among all clinical and US features, only shape was statistically different between EPC with INVs and those without (P<0.05). In this study, the models based on Random Under Sampling (RUS) Boost, Random Forest, XGBoost, AdaBoost, and Easy Ensemble methods had good performance, among which RUS Boost had the best performance with an AUC of 0.875 [95% confidence interval (CI): 0.750-0.974] in the test set.

Conclusions

Radiomics prediction models were effective in predicting the INV of EPC, whereas clinical and US features demonstrated relatively decreased predictive utility.

Validation of the Xpert Breast Cancer STRAT 4 Assay on the GeneXpert instrument to Assess Hormone Receptor, Ki67, and HER2 Gene Expression Status in Breast Cancer Tissue Samples

Breast cancer is the commonest cause of cancer-related mortality in African females where patients often present later and with advanced disease. Causes for delayed diagnosis include restricted diagnostic access and international controversy on interpretation of ancillary tests like immunohistochemistry (IHC). Fine needle aspirates (FNAC) are an attractive alternative although may have reduced sensitivity. The Xpert Breast Cancer STRAT4 (STRAT4) (CE-IVD*) assay (Cepheid, Sunnyvale) is a semi-quantitative reverse-transcription polymerase chain reaction assay which detects messenger RNA (mRNA) expression in breast samples for estrogen receptor ( ESR1 ), progesterone receptor ( PGR1 ), human epidermal growth factor receptor/Erb-B2 receptor tyrosine kinase 2 (HER2/ ERBB2 ) and the proliferation marker, MKi67 . We assessed the performance of this assay on both formalin-fixed paraffin-embedded (FFPE, n=31) and matched FNAC (n=20) samples from patients presenting with breast cancer to the Johannesburg academic hospitals. IHC and Fluorescent in situ hybridization analysis (performed on HER2-indeterminate samples) was compared with the mRNA expression of the corresponding target genes in FFPE samples, and mRNA expression on FNAC samples was compared with the FFPE results for both mRNA expression and IHC. Concordance between IHC/FISH and Xpert Breast Cancer STRAT4 in FFPE and FNAC samples using the Quick lysis (Q) method (a research-use-only modification of the validated FFPE-lysis method), showed an overall percentage agreement for ESR1 expression of 90.3% and 81.3%, and for PGR1 expression at 86.7% and 81.3% respectively in FFPE and FNAC samples. Concordance was lowest for Ki67 expression, using a binary IHC cutoff for Ki67 positivity at ≥20% staining) at 83.9% and 62.5%, for FFPE and FNAC samples, respectively. This suggests that the STRAT4 assay may be a useful ancillary test in determining HR and Ki67 status in FFPE samples and that use on FNAC samples may be feasible. Future studies should expand the sample numbers and establish locally relevant cutoffs.

Axillary Surgical Attitude Changing with Retrospective Application of ACOSOG Z0011 Eligible Criteria: An Institutional Evaluation

Objective

Sentinel lymph node biopsy (SLNB) represents the gold standard for axillary surgical staging. The aim of this study was to assess the proportion of axillary lymph node dissection (ALND) that could be avoided after retrospective application of the ACOSOG Z0011 criteria and to evaluate the shortterm complications associated with axillary surgery.

Materials and Methods

We reviewed breast cancer (BC) patients treated by primary breast-conserving surgery from 2012 to 2015. The percentage of SLNB vs ALND performed before and after the application of the ACOSOG Z0011 criteria was calculated. Complications were analyzed using crosstabs, with p<0.05 considered significant.

Results

Two hundred fifty one patients with a median age of 59.3 years were included. BC tumors had a median size of 13 mm and were mostly unifocal (83.9%). There were 30.3% with 1-2 metastatic lymph nodes (MLN). ALND was performed in 44.2%. The patients with 1-2 MLN, had only SLNB in 14.5% of cases. By applying the ACOSOG Z0011 criteria, ALND would have been avoided in 40.2% of patients. At least one postoperative complication was reported after SLNB or ALND for 45.7% and 74.7% of patients respectively. Seroma was the most frequent complication, and occurred in 29.3% of cases after SLNB and in 59.5% after ALND.

Conclusion

SNLB is the most commonly used axillary surgical staging procedure in this series (55.8%). With a retrospective application of the ACOSOG Z0011 criteria in our population, ALND could have been avoided for 40.2% patients. Post-operative complications rate was higher after ALND, with a seroma rate at 59.5%.

AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis

Background Few studies have evaluated the role of artificial intelligence (AI) in prior screening mammography. Purpose To examine AI risk scores assigned to screening mammography in women who were later diagnosed with breast cancer. Materials and Methods Image data and screening information of examinations performed from January 2004 to December 2019 as part of BreastScreen Norway were used in this retrospective study. Prior screening examinations from women who were later diagnosed with cancer were assigned an AI risk score by a commercially available AI system (scores of 1-7, low risk of malignancy; 8-9, intermediate risk; and 10, high risk of malignancy). Mammographic features of the cancers based on the AI score were also assessed. The association between AI score and mammographic features was tested with a bivariate test. Results A total of 2787 prior screening examinations from 1602 women (mean age, 59 years ± 5.1 [SD]) with screen-detected (n = 1016) or interval (n = 586) cancers showed an AI risk score of 10 for 389 (38.3%) and 231 (39.4%) cancers, respectively, on the mammograms in the screening round prior to diagnosis. Among the screen-detected cancers with AI scores available two screening rounds (4 years) before diagnosis, 23.0% (122 of 531) had a score of 10. Mammographic features were associated with AI score for invasive screen-detected cancers (P < .001). Density with calcifications was registered for 13.6% (43 of 317) of screen-detected cases with a score of 10 and 4.6% (15 of 322) for those with a score of 1-7. Conclusion More than one in three cases of screen-detected and interval cancers had the highest AI risk score at prior screening, suggesting that the use of AI in mammography screening may lead to earlier detection of breast cancers. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Mehta in this issue.

Modulation of JAK-STAT Signaling by LNK: A Forgotten Oncogenic Pathway in Hormone Receptor-Positive Breast Cancer

Breast cancer remains the most frequently diagnosed cancer in women worldwide. Tumors that express hormone receptors account for 75% of all cases. Understanding alternative signaling cascades is important for finding new therapeutic targets for hormone receptor-positive breast cancer patients. JAK-STAT signaling is commonly activated in hormone receptor-positive breast tumors, inducing inflammation, proliferation, migration, and treatment resistance in cancer cells. In hormone receptor-positive breast cancer, the JAK-STAT cascade is stimulated by hormones and cytokines, such as prolactin and IL-6. In normal cells, JAK-STAT is inhibited by the action of the adaptor protein, LNK. However, the role of LNK in breast tumors is not fully understood. This review compiles published reports on the expression and activation of the JAK-STAT pathway by IL-6 and prolactin and potential inhibition of the cascade by LNK in hormone receptor-positive breast cancer. Additionally, it includes analyses of available datasets to determine the level of expression of LNK and various members of the JAK-STAT family for the purpose of establishing associations between expression and clinical outcomes. Together, experimental evidence and in silico studies provide a better understanding of the potential implications of the JAK-STAT-LNK loop in hormone receptor-positive breast cancer progression.

Complete pathological response in patients with HER2 positive breast cancer treated with neoadjuvant therapy in Colombia

Introduction

Breast cancer is the most common type of cancer and the leading cause of death by cancer in women in Colombia. Approximately 15 to 20% of breast cancers overexpress HER2.

Objective

To analyze the relationship between multiple clinical and histological variables and pathological complete response in patients with HER2-positive breast cancer undergoing neoadjuvant therapy in a specialized cancer center in Colombia.

Materials and methods

We performed a retrospective analysis of non-metastatic HER2-positive breast cancer patients who received neoadjuvant therapy between 2007 and 2020 at the Instituto de Cancerología Las Americas Auna (Medellín, Colombia). Assessed parameters were tumor grade, proliferation index, estrogen receptor, progesterone receptor, HER2 status, type of neoadjuvant therapy, pathologic complete response rates, and overall survival.

Results

Variables associated with low pathologic complete response rates were tumor grades 1-2 (OR = 0.55; 95% CI = 0.37-0.81; p = 0.03), estrogen receptor positivity (OR =0.65; 95%; CI = 0.43-0.97; p=0.04), and progesterone receptor positivity (OR = 0.44; 95% CI = 0.29-0.65; p = 0.0001). HER2 strong positivity (score 3+) was associated with high pathological complete response rates (OR = 3.3; 95% CI = 1.3-8.35; p=0.013). Five-year overall survival was 91.5% (95% CI = 82.6-95.9) in patients with pathological complete response and 73.6% (95% CI = 66.4-79.6) in patients who did not achieve pathological complete response (p = 0.001). Additionally, the pathological complete response rate was three times higher in patients receiving combined neoadjuvant chemotherapy with anti-HER2 therapy than in those with chemotherapy alone (48% versus 16%).

Conclusions

In patients with HER2-positive breast cancer, tumor grade 3, estrogen receptor negativity, progesterone receptor negativity, strong HER2 positivity (score 3+), and the use of the neoadjuvant trastuzumab are associated with higher pathological complete response rates.

The Possible Role of Anti- and Protumor-Infiltrating Lymphocytes in Pathologic Complete Response in Early Breast Cancer Patients Treated with Neoadjuvant Systemic Therapy

The tumor microenvironment, composed of pro- and antitumor immune cells, affects cancer cell behavior. We aimed to evaluate whether tumor-infiltrating lymphocyte (TIL) density and TIL subtypes in core biopsies at the diagnosis of breast cancer patients could predict a pathologic complete response (pCR; ypT0/is ypN0) from neoadjuvant systemic therapy (NST). The TIL subtypes were determined based on the proportions of presumably antitumor (CD8+, CXCL13+) and protumor (PD-1+, FOXP3+) immune cells. A prospective, noninterventional study, including 171 participants undergoing NST, was performed. The median TIL density for the entire cohort was 10% (IQR: 3.5-23.8), and 59 (35%) patients achieved pCR. TIL density was positively associated with pCR (univariately and multivariably). In the multivariable logistic regression model, TIL density was an independent predictor of pCR (p = 0.012, OR 1.27; 95% CI 1.05-1.54) when controlled for age (p = 0.232), Ki-67 (p = 0.001), node-negative status (p = 0.024), and HER2+/triple negative vs. luminal B-like subtype (p < 0.001). In our sample, higher proportions of PD-1+ TILs and FOXP3+ TILs were associated with a higher probability of pCR but the association was not statistically significant and we could not make any conclusions on the direction of associations in the model with all four biomarkers. In the exploratory multivariable analysis, we showed that only higher CD8+ TILs were associated with pCR. In conclusion, TIL density and its subtypes are associated with pCR.

The clinical relevance of OSM in inflammatory diseases: a comprehensive review

Oncostatin M (OSM) is a pleiotropic cytokine involved in a variety of inflammatory responses such as wound healing, liver regeneration, and bone remodeling. As a member of the interleukin-6 (IL-6) family of cytokines, OSM binds the shared receptor gp130, recruits either OSMRβ or LIFRβ, and activates a variety of signaling pathways including the JAK/STAT, MAPK, JNK, and PI3K/AKT pathways. Since its discovery in 1986, OSM has been identified as a significant contributor to a multitude of inflammatory diseases, including arthritis, inflammatory bowel disease, lung and skin disease, cardiovascular disease, and most recently, COVID-19. Additionally, OSM has also been extensively studied in the context of several cancer types including breast, cervical, ovarian, testicular, colon and gastrointestinal, brain,lung, skin, as well as other cancers. While OSM has been recognized as a significant contributor for each of these diseases, and studies have shown OSM inhibition is effective at treating or reducing symptoms, very few therapeutics have succeeded into clinical trials, and none have yet been approved by the FDA for treatment. In this review, we outline the role OSM plays in a variety of inflammatory diseases, including cancer, and outline the previous and current strategies for developing an inhibitor for OSM signaling.

A supervised Bayesian factor model for the identification of multi-omics signatures

MOTIVATION

Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are iden-tified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive model-ing. However, multi-omics integration and predictive modeling are generally performed independent-ly in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful.

RESULTS

We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the recon-struction of underlying factors in synthetic examples and prediction accuracy of COVID-19 severity and breast cancer tumor subtypes.

AVAILABILITY

SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.

A retrospective comparative study on the diagnostic efficacy and the complications: between CassiII rotational core biopsy and core needle biopsy

Accurate pathologic diagnosis and molecular classification of breast mass biopsy tissue is important for determining individualized therapy for (neo)adjuvant systemic therapies for invasive breast cancer. The CassiII rotational core biopsy system is a novel biopsy technique with a guide needle and a "stick-freeze" technology. The comprehensive assessments including the concordance rates of diagnosis and biomarker status between CassiII and core needle biopsy were evaluated in this study. Estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki67 were analyzed through immunohistochemistry. In total, 655 patients with breast cancer who underwent surgery after biopsy at Sir Run Run Shaw Hospital between January 2019 to December 2021 were evaluated. The concordance rates (CRs) of malignant surgical specimens with CassiII needle biopsy was significantly high compared with core needle biopsy. Moreover, CassiII needle biopsy had about 20% improvement in sensitivity and about 5% improvement in positive predictive value compared to Core needle biopsy. The characteristics including age and tumor size were identified the risk factors for pathological inconsistencies with core needle biopsies. However, CassiII needle biopsy was associated with tumor diameter only. The CRs of ER, PgR, HER2, and Ki67 using Cassi needle were 98.08% (kappa, 0.941; p<.001), 90.77% (kappa, 0.812; p<.001), 69.62% (kappa, 0.482; p<.001), and 86.92% (kappa, 0.552; p<.001), respectively. Post-biopsy complications with CassiII needle biopsy were also collected. The complications of CassiII needle biopsy including chest stuffiness, pain and subcutaneous ecchymosis are not rare. The underlying mechanism of subcutaneous congestion or hematoma after CassiII needle biopsy might be the larger needle diameter and the effect of temperature on coagulation function. In summary, CassiII needle biopsy is age-independent and has a better accuracy than CNB for distinguishing carcinoma in situ and invasive carcinoma.

Estrogen Receptor Signaling in Breast Cancer

Estrogen receptor (ER) signaling is a critical regulator of cell proliferation, differentiation, and survival in breast cancer (BC) and other hormone-sensitive cancers. In this review, we explore the mechanism of ER-dependent downstream signaling in BC and the role of estrogens as growth factors necessary for cancer invasion and dissemination. The significance of the clinical implications of ER signaling in BC, including the potential of endocrine therapies that target estrogens' synthesis and ER-dependent signal transmission, such as aromatase inhibitors or selective estrogen receptor modulators, is discussed. As a consequence, the challenges associated with the resistance to these therapies resulting from acquired ER mutations and potential strategies to overcome them are the critical point for the new treatment strategies' development.

Prognostic significance of TP53 and PIK3CA mutations analyzed by next-generation sequencing in breast cancer

Breast cancer is one of the most prevalent malignant tumors affecting women globally. It is a heterogeneous disease characterized by mutations in several genes. Several gene panels have been applied to assess the risk of breast cancer and determine the appropriate treatment. As a powerful tool, Next-generation sequencing (NGS) has been widely utilized in cancer research due to its advantages, including high speed, high throughput, and high accuracy. In this study, we aim to analyze the correlation between somatic mutations in breast cancer, analyzed using NGS, and the prognosis of patients. Between May 2018 and May 2019, a total of 313 patients with breast cancer underwent surgical treatment, which included total mastectomy and breast-conserving surgery. Among these patients, 265 were diagnosed with invasive ductal carcinoma. In this study, we analyzed the NGS results, clinicopathological characteristics, and their correlation with prognosis. Using a gene panel, we examined 143 somatic mutations in solid cancers. Notably, the study population included patients who had received neoadjuvant chemotherapy. The mean age of the patients was 53.1 (±10.28) years, and the median follow-up time was 48 months (range, 8-54). Among the 265 patients, 68 had received prior systemic therapy. Of these, 203 underwent breast-conserving surgery, and 62 underwent a mastectomy. Various somatic mutations were observed in NGS, with the most frequent mutation being PIK3CA mutations, which accounted for 44% of all mutations. TP53 mutations were the second most frequent, and ERBB2 mutations were the third most frequent. TP53 mutations were associated with poor disease-free survival (P = .027), while PIK3CA mutations were associated with better disease-free survival (P = .035) than PIK3CA wild-type. In our study, we identified various somatic mutations in breast cancer. Particularly, we found that TP53 and PIK3CA mutations are potentially associated with the prognosis of breast cancer. These findings suggest that the presence of specific mutations may have implications for predicting the prognosis of breast cancer. Further research and validation are needed to gain a deeper understanding of the role of these mutations and their mechanisms in prognosis prediction.

ASAP1 Expression in Invasive Breast Cancer and Its Prognostic Role

Breast cancer is a major global health burden with high morbidity and mortality rates. Previous studies have reported that increased expression of ASAP1 is associated with poor prognosis in various types of cancer. This study was conducted on 452 breast cancer patients who underwent surgery at Hanyang University Hospital, Seoul, South Korea. Data on clinicopathological characteristics including molecular pathologic markers were collected. Immunohistochemical staining of ASAP1 expression level were used to classify patients into high and low groups. In total, 452 cases low ASAP1 expression group was associated with significantly worse recurrence-free survival (p = 0.029). In ER-positive cases (n = 280), the low ASAP1 expression group was associated with significantly worse overall survival (p = 0.039) and recurrence-free survival (p = 0.029). In multivariate cox analysis, low ASAP1 expression was an independent significant predictor of poor recurrence-free survival in the overall patient group (hazard ratio = 2.566, p = 0.002) and ER-positive cases (hazard ratio = 4.046, p = 0.002). In the analysis of the TCGA dataset, the low-expression group of ASAP1 protein demonstrated a significantly poorer progression-free survival (p = 0.005). This study reports that low ASAP1 expression was associated with worse recurrence-free survival in invasive breast cancer.

Sociodemographic disparities associated with advanced stages and distant metastatic breast cancers at diagnosis in Indonesia: a cross-sectional study

Background

The global health burden of breast cancer is increasing with 5-year survival rates being much shorter in low-income and middle-income countries. Sociodemographic and clinical disparities in early cancer detection affect long-term outcome.

Methods

The authors compared social, demographic, and pathological characteristics associated with metastatic and late stages of breast cancer diagnosis using data collected from a special registry developed by Perhimpunan Bedah Onkologi Indonesia (PERABOI) in 2015.

Results

Of 4959 patients recruited in this study, 995 women (20.1%) were diagnosed with metastatic breast cancer. Lower education status and living in rural areas were significantly associated with Stage IV at diagnosis [odds ratio (OR)=1.256, 95% CI=1.093-1.445, P=0.001; and OR=1.197, 95% CI=1.042-1.377, P=0.012; respectively). Main complaints other than lump (ulceration, breast pain, and discharge) and occupation as a housewife were also associated with the presentation of metastatic diseases (OR=2.598, 95% CI=2.538-3.448, P<0.001 and OR=1.264, 95% CI=1.056-1.567, P=0.030, respectively). Having lower education and living outside Java and Bali islands were associated with the diagnosis of late-stage breast cancers (OR=1.908, 95% CI=1.629-2.232, P<0.001 and OR=3.039, 95% CI=2.238-4.126, P<0.001; respectively). A higher proportion of breast cancer patients were relatively younger with bigger tumour size, positive axillary nodal involvement, and more frequent Human epidermal growth factor receptor 2 overexpression.

Conclusion

The authors identified sociodemographic disparities in the metastatic and late-stage diagnosis of breast cancers among Indonesian women. The subsequent action is required to reduce disparities faced by women with lower social and educational levels for early diagnosis and better healthcare access.

Heterogeneity and potential therapeutic insights for triple-negative breast cancer based on metabolic-associated molecular subtypes and genomic mutations

Objective: Due to a lack of effective therapy, triple-negative breast cancer (TNBC) is extremely poor prognosis. Metabolic reprogramming is an important hallmark in tumorigenesis, cancer diagnosis, prognosis, and treatment. Categorizing metabolic patterns in TNBC is critical to combat heterogeneity and targeted therapeutics. Methods: 115 TNBC patients from TCGA were combined into a virtual cohort and verified by other verification sets, discovering differentially expressed genes (DEGs). To identify reliable metabolic features, we applied the same procedures to five independent datasets to verify the identified TNBC subtypes, which differed in terms of prognosis, metabolic characteristics, immune infiltration, clinical features, somatic mutation, and drug sensitivity. Results: In general, TNBC could be classified into two metabolically distinct subtypes. C1 had high immune checkpoint genes expression and immune and stromal scores, demonstrating sensitivity to the treatment of PD-1 inhibitors. On the other hand, C2 displayed a high variation in metabolism pathways involved in carbohydrate, lipid, and amino acid metabolism. More importantly, C2 was a lack of immune signatures, with late pathological stage, low immune infiltration and poor prognosis. Interestingly, C2 had a high mutation frequency in PIK3CA, KMT2D, and KMT2C and displayed significant activation of the PI3K and angiogenesis pathways. As a final output, we created a 100-gene classifier to reliably differentiate the TNBC subtypes and AKR1B10 was a potential biomarker for C2 subtypes. Conclusion: In conclusion, we identified two subtypes with distinct metabolic phenotypes, provided novel insights into TNBC heterogeneity, and provided a theoretical foundation for therapeutic strategies.