Microcalcifications in breast cancer: From pathophysiology to diagnosis and prognosis

Dysregulated microRNAs in type 2 diabetes and breast cancer: Potential associated molecular mechanisms

Type 2 diabetes (T2D) is a multifaceted and heterogeneous syndrome associated with complications such as hypertension, coronary artery disease, and notably, breast cancer (BC). The connection between T2D and BC is established through processes that involve insulin resistance, inflammation and other factors. Despite this comprehension the specific cellular and molecular mechanisms linking T2D to BC, especially through microRNAs (miRNAs), remain elusive. miRNAs are regulators of gene expression at the post-transcriptional level and have the function of regulating target genes by modulating various signaling pathways and biological processes. However, the signaling pathways and biological processes regulated by miRNAs that are associated with T2D and BC have not yet been elucidated. This review aims to identify dysregulated miRNAs in both T2D and BC, exploring potential signaling pathways and biological processes that collectively contribute to the development of BC.

Mammographic features and risk of breast cancer death among women with invasive screen-detected cancer in BreastScreen Norway 1996-2020

OBJECTIVES

We explored associations between mammographic features and risk of breast cancer death among women with small (<15 mm) and large (≥15 mm) invasive screen-detected breast cancer.

METHODS

We included data from 17,614 women diagnosed with invasive breast cancer as a result of participation in BreastScreen Norway, 1996-2020. Data on mammographic features (mass, spiculated mass, architectural distortion, asymmetric density, density with calcification and calcification alone), tumour diameter and cause of death was obtained from the Cancer Registry of Norway. Cox regression was used to estimate hazard ratios (HR) with 95% confidence intervals (CI) for breast cancer death by mammographic features using spiculated mass as reference, adjusting for age, tumour diameter and lymph node status. All analyses were dichotomised by tumour diameter (small versus large).

RESULTS

Mean age at diagnosis was 60.8 (standard deviation, SD=5.8) for 10,160 women with small tumours and 60.0 (SD=5.8) years for 7454 women with large tumours. The number of breast cancer deaths was 299 and 634, respectively. Mean time from diagnosis to death was 8.7 (SD=5.0) years for women with small tumours and 7.2 (4.6) years for women with large tumours. Using spiculated mass as reference, adjusted HR for breast cancer death among women with small tumours was 2.48 (95% CI 1.67-3.68) for calcification alone, while HR for women with large tumours was 1.30 (95% CI 1.02-1.66) for density with calcification.

CONCLUSIONS

Small screen-detected invasive cancers presenting as calcification and large screen-detected cancers presenting as density with calcification were associated with the highest risk of breast cancer death.

CLINICAL RELEVANCE STATEMENT

Small tumours (<15 mm) presented as calcification alone and large tumours (≥ 15 mm) presented as density with calcification were associated with the highest risk of breast cancer death among women with screen-detected invasive breast cancer diagnosed 1996-2020.

KEY POINTS

• Women diagnosed with invasive screen-detected breast cancer 1996-2020 were analysed. • Small screen-detected cancers presenting as calcification alone resulted in the highest risk of breast cancer death. • Large screen-detected cancers presenting as density with calcification resulted in the highest risk of breast cancer death.

Does vitreous haemorrhage and calcification lead to increased risk of enucleation in advanced retinoblastoma?

PURPOSE

To explore whether varying degrees of vitreous haemorrhage (VH) and calcification act as risk factors for enucleation in patients with advanced retinoblastoma (RB).

METHODS

Advanced RB was defined by the international classification of RB (Philadelphia version). Basic information for retinoblastoma patients diagnosed as groups D and E in our hospital between January 2017 and June 2022 was reviewed by logistics regression models. Additionally, a correlation analysis was performed, excluding variables with a VIF (variance inflation factor) >10 from the multivariate analysis.

RESULTS

A total of 223 eyes diagnosed with RB were included in assessing VH and calcification; of these, 101 (45.3%) eyes experienced VH, and 182 (76.2%) eyes were found to have calcification within the tumour through computed tomography (CT) or B-scan ultrasonography. Ninety-two eyes (41.3%) were enucleated, of which 67 (72.8%) had VH and 68 (73.9%) calcification, both of which were significantly relevant to enucleation (p < 0.001*). Other clinical risk factors, such as corneal edema, anterior chamber haemorrhage, high intraocular pressure during treatment and iris neovascularization, correlated significantly with enucleation (p < 0.001*). Multivariate analysis included IIRC (intraocular international retinoblastoma classification), VH, calcification and high intraocular pressure during treatment as independent risk factors for enucleation.

CONCLUSIONS

Despite identifying different potential risk factors for RB, there remains significant controversy concerning which patients require enucleation, and the degree of VH varies. Such eyes need to be evaluated carefully, and management with appropriate adjuvant therapy may improve the outcome of these patients.

Inhibiting Pathological Calcium Phosphate Mineralization: Implications for Disease Progression

Pathological calcifications, especially calcium phosphate microcalcifications (MCs), appear in most early breast cancer lesions, and their formation correlates with more aggressive tumors and a poorer prognosis. Hydroxyapatite (HA) is a key MC component that crystallizes in the tumor microenvironment. It is often associated with malignant breast cancer lesions and can trigger tumorigenesis in vitro. Here, we investigate the impact of additives on HA crystallization and inhibition, and how precancerous breast cells respond to minerals that are deposited in the presence of these additives. We show that nonstoichiometric HA spontaneously crystallizes in a solution simulating the tumor microenvironmental fluids and exhibits lump-like morphology similar to breast cancer MCs. In this system, the effectiveness of poly(aspartic acid) and poly(acrylic acid) (PAA) to inhibit HA is examined as a potential route to improve cancer prognosis. In the presence of additives, the formation of HA lumps is associated with the promotion or only minimal inhibition of mineralization, whereas the formation of amorphous calcium phosphate (ACP) lumps is followed by inhibition of mineralization. PAA emerges as a robust HA inhibitor by forming spherical ACP particles. When precancerous breast cells are exposed to various HA and ACP minerals, the most influential factors on cell proliferation are the mineral phase and whether the mineral is in the form of discrete particles or particle aggregates. The tumorigenic effects on cells, ranging from cytotoxicity and suppression of proliferation to triggering of proliferation, can be summarized as HA particles < HA aggregates < ACP particles < ACP aggregates. The cellular response to minerals can be attributed to a combination of factors, including mineral phase, crystallinity, morphology, surface texture, aggregation state, and surface potential. These findings have implications for understanding mineral-cell interactions within the tumor microenvironment and suggest that, in some cases, the byproducts of HA inhibition can contribute to disease progression more than HA itself.

Study on the differential diagnosis of benign and malignant breast lesions using a deep learning model based on multimodal images

OBJECTIVE

To establish a multimodal model for distinguishing benign and malignant breast lesions.

MATERIALS AND METHODS

Clinical data, mammography, and MRI images (including T2WI, diffusion-weighted images (DWI), apparent diffusion coefficient (ADC), and DCE-MRI images) of 132 benign and breast cancer patients were analyzed retrospectively. The region of interest (ROI) in each image was marked and segmented using MATLAB software. The mammography, T2WI, DWI, ADC, and DCE-MRI models based on the ResNet34 network were trained. Using an integrated learning method, the five models were used as a basic model, and voting methods were used to construct a multimodal model. The dataset was divided into a training set and a prediction set. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the model were calculated. The diagnostic efficacy of each model was analyzed using a receiver operating characteristic curve (ROC) and an area under the curve (AUC). The diagnostic value was determined by the DeLong test with statistically significant differences set at P < 0.05.

RESULTS

We evaluated the ability of the model to classify benign and malignant tumors using the test set. The AUC values of the multimodal model, mammography model, T2WI model, DWI model, ADC model and DCE-MRI model were 0.943, 0.645, 0.595, 0.905, 0.900, and 0.865, respectively. The diagnostic ability of the multimodal model was significantly higher compared with that of the mammography and T2WI models. However, compared with the DWI, ADC, and DCE-MRI models, there was no significant difference in the diagnostic ability of these models.

CONCLUSION

Our deep learning model based on multimodal image training has practical value for the diagnosis of benign and malignant breast lesions.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy

Background

Malignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer.

Methods

The BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool.

Results

BRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans.

Conclusion

The MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

Evaluating the Role of Breast Ultrasound in Early Detection of Breast Cancer in Low- and Middle-Income Countries: A Comprehensive Narrative Review

Breast cancer, affecting both genders, but mostly females, exhibits shifting demographic patterns, with an increasing incidence in younger age groups. Early identification through mammography, clinical examinations, and breast self-exams enhances treatment efficacy, but challenges persist in low- and medium-income countries due to limited imaging resources. This review assesses the feasibility of employing breast ultrasound as the primary breast cancer screening method, particularly in resource-constrained regions. Following the PRISMA guidelines, this study examines 52 publications from the last five years. Breast ultrasound, distinct from mammography, offers advantages like radiation-free imaging, suitability for repeated screenings, and preference for younger populations. Real-time imaging and dense breast tissue evaluation enhance sensitivity, accessibility, and cost-effectiveness. However, limitations include reduced specificity, operator dependence, and challenges in detecting microcalcifications. Automatic breast ultrasound (ABUS) addresses some issues but faces constraints like potential inaccuracies and limited microcalcification detection. The analysis underscores the need for a comprehensive approach to breast cancer screening, emphasizing international collaboration and addressing limitations, especially in resource-constrained settings. Despite advancements, notably with ABUS, the primary goal is to contribute insights for optimizing breast cancer screening globally, improving outcomes, and mitigating the impact of this debilitating disease.

The metabolism-related lncRNA signature predicts the prognosis of breast cancer patients

Long non-coding RNAs (lncRNAs) involved in metabolism are recognized as significant factors in breast cancer (BC) progression. We constructed a novel prognostic signature for BC using metabolism-related lncRNAs and investigated their underlying mechanisms. The training and validation cohorts were established from BC patients acquired from two public sources: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The prognostic signature of metabolism-related lncRNAs was constructed using the least absolute shrinkage and selection operator (LASSO) cox regression analysis. We developed and validated a new prognostic risk model for BC using the signature of metabolism-related lncRNAs (SIRLNT, SIAH2-AS1, MIR205HG, USP30-AS1, MIR200CHG, TFAP2A-AS1, AP005131.2, AL031316.1, C6orf99). The risk score obtained from this signature was proven to be an independent prognostic factor for BC patients, resulting in a poor overall survival (OS) for individuals in the high-risk group. The area under the curve (AUC) for OS at three and five years were 0.67 and 0.65 in the TCGA cohort, and 0.697 and 0.68 in the GEO validation cohort, respectively. The prognostic signature demonstrated a robust association with the immunological state of BC patients. Conventional chemotherapeutics, such as docetaxel and paclitaxel, showed greater efficacy in BC patients classified as high-risk. A nomogram with a c-index of 0.764 was developed to forecast the survival time of BC patients, considering their risk score and age. The silencing of C6orf99 markedly decreased the proliferation, migration, and invasion capacities in MCF-7 cells. Our study identified a signature of metabolism-related lncRNAs that predicts outcomes in BC patients and could assist in tailoring personalized prevention and treatment plans.

Optical Emission Spectroscopy for the Real-Time Identification of Malignant Breast Tissue

Breast conserving resection with free margins is the gold standard treatment for early breast cancer recommended by guidelines worldwide. Therefore, reliable discrimination between normal and malignant tissue at the resection margins is essential. In this study, normal and abnormal tissue samples from breast cancer patients were characterized ex vivo by optical emission spectroscopy (OES) based on ionized atoms and molecules generated during electrosurgical treatment. The aim of the study was to determine spectroscopic features which are typical for healthy and neoplastic breast tissue allowing for future real-time tissue differentiation and margin assessment during breast cancer surgery. A total of 972 spectra generated by electrosurgical sparking on normal and abnormal tissue were used for support vector classifier (SVC) training. Specific spectroscopic features were selected for the classification of tissues in the included breast cancer patients. The average classification accuracy for all patients was 96.9%. Normal and abnormal breast tissue could be differentiated with a mean sensitivity of 94.8%, a specificity of 99.0%, a positive predictive value (PPV) of 99.1% and a negative predictive value (NPV) of 96.1%. For 66.6% patients all classifications reached 100%. Based on this convincing data, a future clinical application of OES-based tissue differentiation in breast cancer surgery seems to be feasible.

A Mammography-Based Radiomic Nomogram for Predicting Malignancy in Breast Suspicious Microcalcifications

RATIONALE AND OBJECTIVES

Preoperative accurate identification of benign and malignant breast lesions is vital for patients to achieve individualized treatment. This study aimed to develop and validate a mammography-based radiomic nomogram for predicting malignant risk of breast suspicious microcalcifications (MCs).

MATERIALS AND METHODS

496 patients with histologically confirmed breast suspicious MCs were randomly divided into the training set (n = 346) and validation set (n = 150). Radiomics features was extracted from the craniocaudal and mediolateral oblique images. Least absolute shrinkage and selection operator algorithm were used to select radiomics features, then radiomics score (Rad-score) was calculated. Univariate analysis was used to identify malignant MCs-related clinical independent risk factors. Multivariate logistic regression was used to establish a clinical-radiomics model by incorporating Rad-score and clinic factors. A nomogram was developed to visualize the clinical-radiomics model. The receiver operating characteristic curve, calibration curve and decision curve analysis (DCA) were used to evaluate the performance of the nomogram.

RESULTS

The Rad-score was consisted of 29 optimal radiomics features. We developed a nomogram by incorporating Rad-score, menopause status, MCs morphology and distribution, the area under the curve value of the combined model was 0.926(95% confidence interval [CI]: 0.878-0.975) for the validation set. The calibration curves and DCA indicated the combined model had favorable calibration and clinical utility.

CONCLUSION

The combined model could be considered as a potential imaging marker to predict malignant risk of breast suspicious MCs.

Clinicopathological and prognostic value of calcification morphology descriptors in ductal carcinoma in situ of the breast: a systematic review and meta-analysis

BACKGROUND

Calcifications on mammography can be indicative of breast cancer, but the prognostic value of their appearance remains unclear. This systematic review and meta-analysis aimed to evaluate the association between mammographic calcification morphology descriptors (CMDs) and clinicopathological factors.

METHODS

A comprehensive literature search in Medline via Ovid, Embase.com, and Web of Science was conducted for articles published between 2000 and January 2022 that assessed the relationship between CMDs and clinicopathological factors, excluding case reports and review articles. The risk of bias and overall quality of evidence were evaluated using the QUIPS tool and GRADE. A random-effects model was used to synthesize the extracted data. This systematic review is reported according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA).

RESULTS

Among the 4715 articles reviewed, 29 met the inclusion criteria, reporting on 17 different clinicopathological factors in relation to CMDs. Heterogeneity between studies was present and the overall risk of bias was high, primarily due to small, inadequately described study populations. Meta-analysis demonstrated significant associations between fine linear calcifications and high-grade DCIS [pooled odds ratio (pOR), 4.92; 95% confidence interval (CI), 2.64-9.17], (comedo)necrosis (pOR, 3.46; 95% CI, 1.29-9.30), (micro)invasion (pOR, 1.53; 95% CI, 1.03-2.27), and a negative association with estrogen receptor positivity (pOR, 0.33; 95% CI, 0.12-0.89).

CONCLUSIONS

CMDs detected on mammography have prognostic value, but there is a high level of bias and variability between current studies. In order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.

CRITICAL RELEVANCE STATEMENT

Mammographic calcification morphology descriptors (CMDs) have prognostic value, but in order for CMDs to achieve clinical utility, standardization in reporting of CMDs is necessary.

SYSTEMATIC REVIEW REGISTRATION

CRD42022341599 KEY POINTS: • Mammographic calcifications can be indicative of breast cancer. • The prognostic value of mammographic calcifications is still unclear. • Specific mammographic calcification morphologies are related to lesion aggressiveness. • Variability between studies necessitates standardization in calcification evaluation to achieve clinical utility.

A novel approach to quantify calcifications of thyroid nodules in US images based on deep learning: predicting the risk of cervical lymph node metastasis in papillary thyroid cancer patients

OBJECTIVE

Based on ultrasound (US) images, this study aimed to detect and quantify calcifications of thyroid nodules, which are regarded as one of the most important features in US diagnosis of thyroid cancer, and to further investigate the value of US calcifications in predicting the risk of lymph node metastasis (LNM) in papillary thyroid cancer (PTC).

METHODS

Based on the DeepLabv3+ networks, 2992 thyroid nodules in US images were used to train a model to detect thyroid nodules, of which 998 were used to train a model to detect and quantify calcifications. A total of 225 and 146 thyroid nodules obtained from two centers, respectively, were used to test the performance of these models. A logistic regression method was used to construct the predictive models for LNM in PTCs.

RESULTS

Calcifications detected by the network model and experienced radiologists had an agreement degree of above 90%. The novel quantitative parameters of US calcification defined in this study showed a significant difference between PTC patients with and without cervical LNM (p < 0.05). The calcification parameters were beneficial to predicting the LNM risk in PTC patients. The LNM prediction model using these calcification parameters combined with patient age and other US nodular features showed a higher specificity and accuracy than the calcification parameters alone.

CONCLUSIONS

Our models not only detect the calcifications automatically, but also have value in predicting cervical LNM risk of PTC patients, thereby making it possible to investigate the relationship between calcifications and highly invasive PTC in detail.

CLINICAL RELEVANCE STATEMENT

Due to the high association of US microcalcifications with thyroid cancers, our model will contribute to the differential diagnosis of thyroid nodules in daily practice.

KEY POINTS

• We developed an ML-based network model for automatically detecting and quantifying calcifications within thyroid nodules in US images. • Three novel parameters for quantifying US calcifications were defined and verified. • These US calcification parameters showed value in predicting the risk of cervical LNM in PTC patients.

PI3K/AKT signaling activates HIF1α to modulate the biological effects of invasive breast cancer with microcalcification

Microcalcification (MC) is a valuable diagnostic indicator of breast cancer, and it is reported to be associated with increased tumor aggressiveness and poor prognosis. Nevertheless, the exact potential molecular mechanism is not completely understood. Here, we find that the mineralized invasive breast cancer (IBC) cells not only increased their proliferation and migration, but also showed the characteristic of doxorubicin resistance. The PI3K/AKT signaling pathway is associated with the generation of calcification in IBC, and it activates the transcription and translation of its downstream hypoxia-inducible factor 1α (HIF1α). Knockdown of HIF1α protein significantly downregulated cell proliferation and migration while calcification persists. Meanwhile, calcified breast cancer cells restored sensitivity to doxorubicin because of suppressed HIF1α expression. In addition, we provide initial data on the underlying value of HIF1α as a biomarker of doxorubicin resistance. These findings provide a new direction for exploring microcalcifications in IBC.

Metformin prevents osteoblast-like potential and calcification in lung cancer A549 cells

In spite of recent advances made in understanding its progression, cancer is still a leading cause of death across the nations. Molecular pathophysiology of these cancer cells largely differs depending on cancer types and even within the same tumor. Pathological mineralization/calcification is seen in various tissues including breast, prostate, and lung cancer. Osteoblast-like cells derived after trans-differentiation of mesenchymal cells usually drive calcium deposition in various tissues. This study aims to explore the presence of osteoblast-like potential in lung cancer cells and its prevention. ALP assay, ALP staining, nodule formation, RT-PCR, RT-qPCR, and western blot analysis experiments were carried out in lung cancer A549 cells to achieve said objective. Expressions of various osteoblast markers (e.g., ALP, OPN, RUNX2, and Osterix) along with osteoinducer genes (BMP-2 and BMP-4) were observed in A549 cells. Moreover, ALP activity and ability leading to nodule formation revealed the presence of osteoblast-like potential in lung cancer cells. Here, BMP-2 treatment increased expressions of osteoblast transcription factors such as RUNX2 and Osterix, enhanced ALP activity, and augmented calcification in this cell line. It was also observed that antidiabetic metformin inhibited BMP-2 mediated increase in osteoblast-like potential and calcification in these cancer cells. The current study noted that metformin blocked BMP-2 mediated increase in epithelial to mesenchymal transition (EMT) in A549 cells. The above findings for the first time unravel that A549 cells possess osteoblast-like potential which drives lung cancer calcification. Metformin might prevent BMP-2 induced osteoblast-like phenotype of the lung cancer cells with concomitant inhibition of EMT to inhibit lung cancer tissue calcification.

Multicellular spheroids containing synthetic mineral particles: an advanced 3D tumor model system to investigate breast precancer malignancy potential according to the mineral type

Mineral particles that form in soft tissues in association with disease conditions are heterogeneous in their composition and physiochemical properties. Hence, it is challenging to study the effect of mineral type on disease progression in a high-throughput and realistic manner. For example, most early breast precancer lesions, termed ductal carcinoma in situ (DCIS), contain microcalcifications (MCs), calcium-containing pathological minerals. The most common type of MCs is calcium phosphate crystals, mainly carbonated apatite; it is associated with either benign or malignant lesions. In vitro studies indicate that the crystal properties of apatite MCs can affect breast cancer progression. A less common type of MCs is calcium oxalate dihydrate (COD), which is almost always found in benign lesions. We developed a 3D tumor model of multicellular spheroids of human precancer cells containing synthetic MC analogs that link the crystal properties of MCs with the progression of breast precancer to invasive cancer. Using this 3D model, we show that apatite crystals induce Her2 overexpression in DCIS cells. This tumor-triggering effect is increased when the carbonate fraction in the MCs decreases. COD crystals, in contrast, decrease Her2 expression in the spheroids, even compared with a control group with no added MC analogs. Furthermore, COD decreases cell proliferation and migration in DCIS monolayers compared to untreated cells and cells incubated with apatite crystals. This finding suggests that COD is not randomly located only in benign lesions-it may actively contribute to suppressing precancer progression in its surroundings. Our model provides an easy-to-manipulate platform to better understand the interactions between mineral particles and their biological microenvironment. A better understanding of the effect of the crystal properties of MCs on precancer progression will potentially provide new directions for better precancer prognosis and treatment.

New insights into breast microcalcification for poor prognosis: NACT cohort and bone metastasis evaluation cohort

OBJECTIVES

The study aimed to analyze the poor prognosis of microcalcification in breast cancer (BC), including the pathological complete response (pCR) to neoadjuvant chemotherapy (NACT) and the risk of bone metastases.

MATERIALS AND METHODS

313 breast cancer patients received NACT to evaluate pCR and 1182 patients from a multicenter database to assess bone metastases were retrospectively included. Two groups were divided according to the presence or absence of mammography microcalcification. Clinical data, image characteristics, neoadjuvant treatment response, bone involvement, and follow-up information were recorded. The pCR and bone metastases were compared between subgroups using the Mann-Whitney and χ2 tests and logistic regression, respectively.

RESULTS

Mammographic microcalcification was associated with a lower pCR than uncalcified BC in the NACT cohort (20.6% vs 31.6%, P = 0.029). Univariate and multivariate analysis suggested that calcification was a risk factor for poor NACT response [OR = 1.780, 95%CI (1.065-2.974), P = 0.028], [OR = 2.352, 95%CI (1.186-4.667), P = 0.014]. Microcalcification was more likely to be necrosis on MRI than those without microcalcification (53.0% vs 31.7%, P < 0.001), multivariate analysis indicated that tumor necrosis was also a risk factor for poor NACT response [OR = 2.325, 95%CI (1.100-4.911), P = 0.027]. Age, menopausal status, breast density, mass, molecular, and pathology type were not significantly associated with non-pCR risk assessment. In a multicenter cohort of 1182 patients with pathologically confirmed BC, those with microcalcifications had a higher proportion of bone metastases compared to non-calcified BC (11.6% vs 4.9%, P < 0.001). Univariate and multivariate analysis showed that microcalcification was an independent risk factor for bone metastasis [OR = 2.550, 95%CI (1.620-4.012), P < 0.001], [OR = 2.268(1.263-4.071), P = 0.006)]. Osteolytic bone metastases predominated but there was no statistical difference between the two groups (78.9% vs 60.7%, P = 0.099). Calcified BC was mainly involved in axial bone, but was more likely to involve the whole-body bone than non-calcified BC (33.8% vs 10.7%, P = 0.021).

CONCLUSION

This study provides important insights into the poor prognosis of microcalcification, not only in terms of poor response to NACT but also the risk factor of bone metastases.

Efficacy and safety of inetetamab-containing regimens in patients with HER2-positive metastatic breast cancer: a real-world retrospective study in China

Background

Inetetamab (cipterbin) is an innovative anti-HER2 humanized monoclonal antibody. The efficacy and safety of a combination of inetetamab and vinorelbine in the first-line treatment of human epidermal receptor positive (HER2+) metastatic breast cancer (MBC) have been confirmed. We aimed to investigate real-world data of inetetamab in complex clinical practice.

Methods

We retrospectively reviewed the medical records of patients who received inetetamab as a salvage treatment at any line setting from July 2020 to June 2022. The main endpoint was progression-free survival (PFS).

Results

A total of 64 patients were included in this analysis. The median progression-free survival (mPFS) was 5.6 (4.6-6.6) months. Of the patients, 62.5% received two or more lines of therapy before treatment with inetetamab. The most common chemotherapy and anti-HER2 regimens combined with inetetamab were vinorelbine (60.9%) and pyrotinib (62.5%), respectively. Patients treated with inetetamab plus pyrotinib plus vinorelbine benefited the most (p=0.048), with the mPFS of 9.3 (3.1-15.5) months and an objective response rate of 35.5%. For patients with pyrotinib pretreatment, inetetamab plus vinorelbine plus pyrotinib agents resulted in mPFS of 10.3 (5.2-15.4) months. Regimens (inetetamab plus vinorelbine plus pyrotinib vs. other therapeutic agents) and visceral metastases (yes vs. no) were independent predictors of PFS. Patients with visceral metastases treated with inetetamab plus vinorelbine plus pyrotinib had a mPFS of 6.1(5.1-7.1) months. The toxicity of inetetamab was tolerable, with the most common grade 3/4 adverse event being leukopenia (4.7%).

Conclusions

HER2+ MBC patients pretreated with multiple-line therapies still respond to inetetamab-based treatment. Inetetamab combined with vinorelbine and pyrotinib may be the most effective treatment regimen, with a controllable and tolerable safety profile.

CXC ELR-Positive Chemokines as Diagnostic and Prognostic Markers for Breast Cancer Patients

As the most common type of malignant lesison, breast cancer is a leading challenge for clinicians. Currently, diagnosis is based on self-examination and imaging studies that require confirmation by tissue biopsy. However, there are no easily accessible diagnostic tools that can serve as diagnostic and prognostic markers for breast cancer patients. One of the possible candidates for such markers is a group of chemokines that are closely implicated in each stage of tumorigenesis. Many researchers have noted the potential of this molecule group to become tumor markers and have tried to establish their clinical utility. In this work, we summarize the results obtained by scientists on the usefulness of the ELR-positive CXC group of chemokines in ancillary diagnosis of breast cancer.

DeepMiCa: Automatic segmentation and classification of breast MIcroCAlcifications from mammograms

BACKGROUND AND OBJECTIVE

Breast cancer is the world's most prevalent form of cancer. The survival rates have increased in the last years mainly due to factors such as screening programs for early detection, new insights on the disease mechanisms as well as personalised treatments. Microcalcifications are the only first detectable sign of breast cancer and diagnosis timing is strongly related to the chances of survival. Nevertheless microcalcifications detection and classification as benign or malignant lesions is still a challenging clinical task and their malignancy can only be proven after a biopsy procedure. We propose DeepMiCa, a fully automated and visually explainable deep-learning based pipeline for the analysis of raw mammograms with microcalcifications. Our aim is to propose a reliable decision support system able to guide the diagnosis and help the clinicians to better inspect borderline difficult cases.

METHODS

DeepMiCa is composed by three main steps: (1) Preprocessing of the raw scans (2) Automatic patch-based Semantic Segmentation using a UNet based network with a custom loss function appositely designed to deal with extremely small lesions (3) Classification of the detected lesions with a deep transfer-learning approach. Finally, state-of-the-art explainable AI methods are used to produce maps for a visual interpretation of the classification results. Each step of DeepMiCa is designed to address the main limitations of the previous proposed works resulting in a novel automated and accurate pipeline easily customisable to meet radiologists' needs.

RESULTS

The proposed segmentation and classification algorithms achieve an area under the ROC curve of 0.95 and 0.89 respectively. Compared to previously proposed works, this method does not require high performance computational resources and provides a visual explanation of the final classification results.

CONCLUSION

To conclude, we designed a novel fully automated pipeline for detection and classification of breast microcalcifications. We believe that the proposed system has the potential to provide a second opinion in the diagnosis process giving the clinicians the opportunity to quickly visualise and inspect relevant imaging characteristics. In the clinical practice the proposed decision support system could help reduce the rate of misclassified lesions and consequently the number of unnecessary biopsies.

Association between ultrasound BI-RADS signs and molecular typing of invasive breast cancer

Objective

To explore the correlation between ultrasound images and molecular typing of invasive breast cancer, so as to analyze the predictive value of preoperative ultrasound for invasive breast cancer.

Methods

302 invasive breast cancer patients were enrolled in Heping Hospital affiliated to Changzhi Medical College in Shanxi, China during 2020 to 2022. All patients accepted ultrasonic and pathological examination, and all pathological tissues received molecular typing with immunohistochemical (IHC) staining. The relevance between different molecular typings and ultrasonic image, pathology were evaluated.

Results

Univariate analysis: among the four molecular typings, there were significant differences in tumor size, shape, margin, lymph node and histological grade (P<0.05). 1. Size: Luminal A tumor was smaller (69.4%), Basal -like type tumors are mostly larger (60.9%); 2. Shape: Basal-like type is more likely to show regular shape (45.7%); 3. Margin: Luminal A and Luminal B mostly are not circumscribed (79.6%, 74.8%), Basal -like type shows circumscribed(52.2%); 4. Lymph nodes: Luminal A type tends to be normal (87.8%), Luminal B type,Her-2+ type and Basal-like type tend to be abnormal (35.6%,36.4% and 39.1%). There was no significant difference in mass orientation, echo pattern, rear echo and calcification (P>0.05). Multivariate analysis: Basal-like breast cancer mostly showed regular shape, circumscribed margin and abnormal lymph nodes (P<0.05).

Conclusion

There are differences in the ultrasound manifestations of different molecular typings of breast cancer, and ultrasound features can be used as a potential imaging index to provide important information for the precise diagnosis and treatment of breast cancer.

Calcifications in triple-negative breast cancer: Molecular features and treatment strategies

Despite the high prevalence of mammographic calcifications, our understanding remains limited regarding the clinical and molecular features of calcifications within triple-negative breast cancer (TNBC). To investigate the clinical relevance and biological basis of TNBC with calcifications of high suspicion for malignancy, we established a study cohort (N = 312) by integrating mammographic records with clinical data and genomic, transcriptomic, and metabolomic profiling. Despite similar clinicopathological features, patients with highly suspicious calcifications exhibited a worse overall survival than those without. In addition, TNBC with highly suspicious calcifications was characterized by a higher frequency of PIK3CA mutation, lower infiltration of immune cells, and increased abnormality of lipid metabolism. Overall, our study systematically revealed clinical and molecular heterogeneity between TNBC with or without calcifications of high suspicion for malignancy. These data might help to understand the clinical relevance and biological basis of mammographic calcifications.

Biomineralogical signatures of breast microcalcifications

Microcalcifications, primarily biogenic apatite, occur in cancerous and benign breast pathologies and are key mammographic indicators. Outside the clinic, numerous microcalcification compositional metrics (e.g., carbonate and metal content) are linked to malignancy, yet microcalcification formation is dependent on microenvironmental conditions, which are notoriously heterogeneous in breast cancer. We interrogate multiscale heterogeneity in 93 calcifications from 21 breast cancer patients using an omics-inspired approach: For each microcalcification, we define a "biomineralogical signature" combining metrics derived from Raman microscopy and energy-dispersive spectroscopy. We observe that (i) calcifications cluster into physiologically relevant groups reflecting tissue type and local malignancy; (ii) carbonate content exhibits substantial intratumor heterogeneity; (iii) trace metals including zinc, iron, and aluminum are enhanced in malignant-localized calcifications; and (iv) the lipid-to-protein ratio within calcifications is lower in patients with poor composite outcome, suggesting that there is potential clinical value in expanding research on calcification diagnostic metrics to include "mineral-entrapped" organic matrix.

Radiogenomic analysis of prediction HER2 status in breast cancer by linking ultrasound radiomic feature module with biological functions

BACKGROUND

Human epidermal growth factor receptor 2 (HER2) overexpressed associated with poor prognosis in breast cancer and HER2 has been defined as a therapeutic target for breast cancer treatment. We aimed to explore the molecular biological information in ultrasound radiomic features (URFs) of HER2-positive breast cancer using radiogenomic analysis. Moreover, a radiomics model was developed to predict the status of HER2 in breast cancer.

METHODS

This retrospective study included 489 patients who were diagnosed with breast cancer. URFs were extracted from a radiomics analysis set using PyRadiomics. The correlations between differential URFs and HER2-related genes were calculated using Pearson correlation analysis. Functional enrichment of the identified URFs-correlated HER2 positive-specific genes was performed. Lastly, the radiomics model was developed based on the URF-module mined from auxiliary differential URFs to assess the HER2 status of breast cancer.

RESULTS

Eight differential URFs (p < 0.05) were identified among the 86 URFs extracted by Pyradiomics. 25 genes that were found to be the most closely associated with URFs. Then, the relevant biological functions of each differential URF were obtained through functional enrichment analysis. Among them, Zone Entropy is related to immune cell activity, which regulate the generation of calcification in breast cancer. The radiomics model based on the Logistic classifier and URF-module showed good discriminative ability (AUC = 0.80, 95% CI).

CONCLUSION

We searched for the URFs of HER2-positive breast cancer, and explored the underlying genes and biological functions of these URFs. Furthermore, the radiomics model based on the Logistic classifier and URF-module relatively accurately predicted the HER2 status in breast cancer.

Correlation between conventional ultrasound features combined with contrast-enhanced ultrasound patterns and pathological prognostic factors in malignant non-mass breast lesions

OBJECTIVE

To investigate the correlation between ultrasound performance and prognostic factors in malignant non-mass breast lesions (NMLs).

MATERIALS AND METHODS

This study included 106 malignant NMLs in 104 patients. Different US features and contrast enhancement patterns were evaluated. Prognostic factors, including histological types and grades, axillary lymph node and peritumoral lymphovascular status, estrogen and progesterone receptor status and the expression of HER-2 and Ki-67 were determined. A chi-square test and logistic regression analysis were used to analyse possible associations.

RESULTS

Lesion size (OR: 3.08, p = 0.033) and posterior echo attenuation (OR: 8.38, p < 0.001) were useful in reflecting malignant NMLs containing an invasive carcinoma component. Posterior echo attenuation (OR: 7.51, p = 0.003) and unclear enhancement margin (OR: 6.50, p = 0.018) were often found in tumors with axillary lymph node metastases. Peritumoural lymphovascular invasion mostly exhibited posterior echo attenuation (OR: 3.84, p = 0.049) and unclear enhancement margin (OR: 8.68, p = 0.042) on ultrasound images. Perfusion defect was a comparatively accurate enhancement indicator for negative ER (OR: 2.57, p = 0.041) and PR (OR: 3.04, p = 0.008) expression. Calcifications (OR: 3.03, p = 0.025) and enlarged enhancement area (OR: 5.36, p = 0.033) imply an increased risk of positive HER-2 expression. Similarly, Calcifications (OR: 4.13, p = 0.003) and enlarged enhancement area (OR: 11.05, p < 0.001) were valid predictors of high Ki-67 proliferation index.

CONCLUSION

Ultrasound performance is valuable for non-invasive prediction of prognostic factors in malignant NMLs.

Establishment and validation of an ultrasound-based nomogram with risk stratification for short disease-free survival in breast cancer

PURPOSE

This retrospective study aimed to develop and validate an Ultrasound (US)-based nomogram to predict short disease-free survival (short-DFS, less than 120 months DFS) in breast cancer (BC).

METHODS

Nomogram was established based on a training data of 311 BC patients by multivariable logistic regression, and were assessed by discrimination, calibration, and clinical usefulness. Risk stratification was performed by X-tile. An independent testing data of 200 patients with BC was used for external validation.

RESULTS

Nine predictors including three US features and six clinical parameters were screened into the nomogram by Lasso (log λ = -3.594) in training data. Better performance was obtained in the training data (C-index: 0.942) and testing data (C-index: 0.914). Calibration analysis indicated optimal agreement between nomogram predictions and actual observations (p = 0.67). Decision curve analysis showed a great clinical benefit (Youden index: 0.634). Three risk levels are low-risk (<184.0), moderate-risk (184.0-345.3) and high-risk (>345.3). Our nomograms had larger area under the receiver operating characteristic (ROC) curves compared with Magee Equation and Nottingham Prognostic models (0.942 vs. 0.824, 0.790).

CONCLUSION

The US-based nomogram and the practical score system facilitate individualized prediction of short-DFS to optimize clinical decisions and improve prognosis in patients with BC.

Biomaterial-assisted tumor therapy: A brief review of hydroxyapatite nanoparticles and its composites used in bone tumors therapy

Malignant bone tumors can inflict significant damage to affected bones, leaving patients to contend with issues like residual tumor cells, bone defects, and bacterial infections post-surgery. However, hydroxyapatite nanoparticles (nHAp), the principal inorganic constituent of natural bone, possess numerous advantages such as high biocompatibility, bone conduction ability, and a large surface area. Moreover, nHAp's nanoscale particle size enables it to impede the growth of various tumor cells via diverse pathways. This article presents a comprehensive review of relevant literature spanning the past 2 decades concerning nHAp and bone tumors. The primary goal is to explore the mechanisms responsible for nHAp's ability to hinder tumor initiation and progression, as well as to investigate the potential of integrating other drugs and components for bone tumor diagnosis and treatment. Lastly, the article discusses future prospects for the development of hydroxyapatite materials as a promising modality for tumor therapy.

OLMALINC/OCT4/BMP2 axis enhances osteogenic-like phenotype of renal interstitial fibroblasts to participate in Randall's plaque formation

BACKGROUND

Randall's plaques (RP) are identified as anchored sites for kidney calcium oxalate stones, but the mechanism remains unclear. Given the importance of osteogenic-like cells in RP formation and OCT4 in reprogramming differentiated cells to osteoblasts, the current study explored the potential role of OCT4 in RP formation.

METHODS

OCT4 and biomineralization were evaluated in RP, and immunofluorescence co-staining was performed to identify these cells with alteration of OCT4 and osteogenic markers. Based on the analysis of tissue, we further investigated the mechanism of OCT4 in regulating osteogenic-like differentiation of primary human renal interstitial fibroblasts (hRIFs) in vitro and vivo.

RESULTS

We identified the upregulated OCT4 in RP, with a positive correlation to osteogenic markers. Interestingly, fibroblast marker Vimentin was partially co-localized with upregulated OCT4 and osteogenic markers in RP. Further investigations revealed that OCT4 significantly enhanced the osteogenic-like phenotype of hRIFs in vitro and in vivo. Mechanically, OCT4 directly bound to BMP2 promoter and facilitated its CpG island demethylation to transcriptionally promote BMP2 expression. Furthermore, combination of RIP and RNA profiling uncovered that lncRNA OLMALINC physically interacted with OCT4 to promote its stabilization via disrupting the ubiquitination. Additionally, OLMALINC was upregulated in fibroblasts in RP visualized by FISH, and a positive correlation was revealed between OLMALINC and OCT4 in RP.

CONCLUSIONS

The upregulation of OCT4 in hRIFs was a pathological feature of RP formation, and OLMALINC/OCT4/BMP2 axis facilitated hRIFs to acquire osteogenic-like phenotype under osteogenic conditions, through which the pathway might participate in RP formation. Our findings opened up a new avenue to better understand RP formation in which osteogenic-like process was partially triggered by lncRNAs and pluripotency maintenance related genes.

Predictive nomogram based on serum tumor markers and clinicopathological features for stratifying lymph node metastasis in breast cancer

BACKGROUND

This study was aimed to establish the nomogram to predict patients' axillary node status by using patients' clinicopathological and tumor characteristic factors.

METHODS

A total of 705 patients with breast cancer were enrolled in this study. All patients were randomly divided into a training group and a validation group. Univariate and multivariate ordered logistic regression were used to determine the predictive ability of each variable. A nomogram was performed based on the factors selected from logistic regression results. Receiver operating characteristic curve (ROC) analysis, calibration plots and decision curve analysis (DCA) were used to evaluate the discriminative ability and accuracy of the models.

RESULTS

Logistic regression analysis demonstrated that CEA, CA125, CA153, tumor size, vascular-invasion, calcification, and tumor grade were independent prognostic factors for positive ALNs. Integrating all the predictive factors, a nomogram was successfully developed and validated. The C-indexes of the nomogram for prediction of no ALN metastasis, positive ALN, and four and more ALN metastasis were 0.826, 0.706, and 0.855 in training group and 0.836, 0.731, and 0.897 in validation group. Furthermore, calibration plots and DCA demonstrated a satisfactory performance of our nomogram.

CONCLUSION

We successfully construct and validate the nomogram to predict patients' axillary node status by using patients' clinicopathological and tumor characteristic factors.

Development and internal validation of a conventional ultrasound-based nomogram for predicting malignant nonmasslike breast lesions

BACKGROUND

The aim of this study was to develop a conventional ultrasound (US) features-based nomogram for the prediction of malignant nonmasslike (NML) breast lesions.

METHODS

Consecutive cases of adult females diagnosed with NML breast lesions via US screening in our center from June 1st, 2017, to April 17th, 2020, were retrospectively enrolled. Candidate variables included age, clinical symptoms, and the image features obtained from the conventional US. Nomograms were developed based on the results of the multiple logistic regression analysis via R language. One thousand bootstraps were used for internal validation. The area under the curve (AUC) and the bias-corrected concordance index (C-index) were calculated. Decision curve analysis (DCA) was also performed for further comparison between the nomogram and the Breast Imaging Reporting and Data System (BI-RADS). The study has not yet been registered.

RESULTS

A total of 229 patients were included in the study after exclusion and follow-up. The overall malignant rate of NML breast lesions was 31.0%. Age, clinical symptoms, echo pattern, calcification, orientation, and Adler's classification were selected to generate the nomogram according to the results of the multivariable logistic regression analysis. The bias-corrected C-index and the AUC of our nomogram were 0.790 and 0.828, respectively. The DCA showed that our model had larger net benefits in a range from 0.2 to 0.7 when compared with the BI-RADS.

CONCLUSIONS

We developed a prediction model using a combination of age, clinical symptoms, echo pattern, calcification, orientation, and Adler's classification for malignant NML breast lesion prediction that yielded adequate discrimination and calibration.

Breast calcification micromorphology classification

OBJECTIVES

The importance of consistent terminology in describing the appearance of breast calcifications in mammography is well recognised. Imaging of calcifications using electron microscopy is a globally growing field of research. We therefore suggest that the time is ripe to develop a lexicon of terms for classifying the micromorphology of breast calcifications.

METHODS

Calcifications within a wide range of histological sections of breast tissue, both benign and malignant, were imaged by Scanning Electron Microscopy (SEM). These images were examined, and the micromorphology of calcifications present was grouped to create a classification system.

RESULTS

Based on the appearance of the calcifications observed, we propose five main categories for classification of the micromorphology of breast calcifications, namely, Dense Homogenous, Punctulate, Banded, Spongy and Aggregate.

CONCLUSIONS

Use of the descriptive categories outlined here will help to ensure consistency and comparability of published observations on the micromorphology of breast calcifications.

ADVANCES IN KNOWLEDGE

This is the first time a lexicon and classification system has been proposed for the micromorphology of breast calcifications, as observed by scanning electron microscopy of histological sections. This will facilitate comparability of observed relationships between micromorphology, mammographic appearance, chemistry and pathology.

A Novel Nomogram for Predicting Prognosis and Tailoring Local Therapy Decision for Ductal Carcinoma In Situ after Breast Conserving Surgery

Purpose: We sought to explore the role of nomogram-combined biomarkers, mammographic microcalcification and inflammatory hematologic markers in guiding local therapy decisions in ductal carcinoma in situ (DCIS) subgroups with different ipsilateral breast tumour recurrence (IBTR) risk. Methods: Between January 2009 and December 2018, consecutive patients with DCIS and breast conserving surgery (BCS) were enrolled and randomly assigned to a training cohort (n = 181) and internally validation cohort (n = 78). Multivariate analyses were performed to identify predictors of IBTR. Model performance was evaluated by the concordance index (C-index) and calibration plot. The time-to-event curves were calculated by the Kaplan−Meier methods and compared by the log-rank test. Results: In total, 259 patients were enrolled and 182 of them received whole breast irradiation (WBI). After a median follow-up of 51.02 months, 23 IBTR events occurred in the whole cohort. By multivariate analyses of training cohort, presence of microinvasion, Ki67 index >14%, mammographic-clustered fine linear microcalcifications and neutrophil/lymphocyte ratio before BCS (preop-NLR), >1.1 remained independent risk factors of IBTR to develop a nomogram. The C-indexes of the nomogram were 0.87 and 0.86 in the training and internal validation set, respectively. Calibration plots illustrated good agreement between the predictions and actual observations for 5-year IBTR. Cut-off values of nomogram point were identified as 53 and 115 points, which divided all patients into low-, intermediate- and high-risk groups. Significant differences in IBTR existed between low-, intermediate- and high-risk subgroups (p < 0.01). For the whole cohort and ER-positive tumours, the benefit of WBI was found only in the intermediate-risk subgroup, but not in those with low or high risk. Fourteen out of 23 IBTRs occurred outside the original quadrant and all occurred in the high-risk group. Conclusions: The novel nomogram demonstrated potential to separate the risk of IBTR and locations of IBTR. For the whole cohort and ER-positive tumours, the benefit of WBI was restricted to an intermediate-risk subgroup.

A Comprehensive Model for Diagnosis of Primary Breast Lymphoma Differentiated From Breast Cancer and Prognosis Evaluation of Surgical Treatment

Background

The objective of this work was to discriminate between primary breast lymphoma (PBL) and breast cancer by systematically analyzing clinical characteristics, laboratory examination results, ultrasound features, and mammography findings to establish a diagnostic model for PBL and to analyze the influence of surgical treatment on the prognosis of PBL patients.

Method

We analyzed 20 PBL and 70 breast cancer patients treated during the same period by comparing several characteristics: clinical features, such as age, tumor position, and breast complaints; laboratory examination findings, such as the lactate dehydrogenase (LDH) level, and imaging features such as the maximum diameter, shape, margins, aspect ratio, and calcification of the mass and axillary lymph node involvement. A diagnostic model was then developed using logistic regression analysis. The impact of surgery on the prognosis of PBL patients was assessed through Kaplan–Meier survival analysis.

Result

Breast cancer and PBL could be distinguished based on imaging features, including the maximum diameter, shape, margin, and calcification of the mass, and lymph node involvement (P < 0.05). There were no significant differences between PBL and breast cancer patients in terms of clinical features, or the LDH level. The area under the receiver operating characteristic curve was 0.821. The log-rank test showed that surgery had no significant influence on the prognosis of PBL patients.

Conclusion

Ultrasound and mammography are the most useful methods for detecting malignant breast tumors. Compared with breast cancer tumors, breast lymphoma tumors are larger with a more regular shape and less calcification and are often accompanied by axillary lymph node involvement. Patients with a breast malignancy should not undergo surgical excision without an accurate diagnosis.

Microcalcifications and Peritumoral Edema Predict Survival Outcome in Luminal Breast Cancer Treated with Neoadjuvant Chemotherapy

Background Little is known regarding findings at imaging associated with survival in patients with luminal breast cancer treated with neoadjuvant chemotherapy (NAC). Purpose To determine the relationship between imaging (MRI, US, and mammography) and clinical-pathologic variables in predicting distant metastasis-free survival (DMFS) and overall survival (OS) in patients with luminal breast cancer treated with NAC. Materials and Methods In this retrospective study, consecutive women with luminal breast cancer who underwent NAC followed by surgery were identified from the breast cancer registries of two hospitals. Women from one hospital between January 2003 and July 2015 were classified into the development cohort, and women from the other hospital between January 2007 and July 2015 were classified into the validation cohort. MRI scans, US scans, and mammograms before and after NAC (hereafter, referred to as pre- and post-NAC, respectively) and clinical-pathologic data were reviewed. Peritumoral edema was defined as the water-like high signal intensity surrounding the tumor on T2-weighted MRI scans. The prediction model was developed in the development cohort by using Cox regression and then tested in the validation cohort. Results The development cohort consisted of 318 women (68 distant metastases, 54 deaths) and the validation cohort consisted of 165 women (37 distant metastases, 14 deaths) (median age, 46 years in both cohorts). Post-NAC MRI peritumoral edema, age younger than 40 years, clinical N2 or N3, and lymphovascular invasion were associated with worse DMFS (all, P < .05). Pre-NAC mammographic microcalcifications, post-NAC MRI peritumoral edema, age older than 60 years, and clinical T3 or T4 were associated with worse OS (all, P < .05). The prediction model showed good discrimination ability (C index, 0.67-0.75 for DMFS and 0.70-0.77 for OS) and stratified prognosis into low-risk and high-risk groups (10-year DMFS rates, 79% vs 21%, respectively; and 10-year OS rates, 95%-96% vs 63%-67%, respectively) in the validation cohort. Conclusion MRI features and clinical-pathologic variables were identified that were associated with prolonged survival of patients with luminal breast cancer treated with neoadjuvant chemotherapy. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Kataoka in this issue.

Patterns of aggressiveness: risk of progression to invasive breast cancer by mammographic features of calcifications in screen-detected ductal carcinoma in situ

BACKGROUND

Mammographic features of calcifications on mammograms showing invasive breast cancer are associated with survival. Less is known about mammographic features and progression to invasive breast cancer among women treated for ductal carcinoma in situ (DCIS).

PURPOSE

To investigate mammographic features of calcifications in screen-detected DCIS in women who later did and did not get diagnosed with invasive breast cancer.

MATERIAL AND METHODS

This registry-based nested case-control study analyzed data from women with screen-detected DCIS in BreastScreen Norway, 1995-2016. Within this cohort of women with DCIS, those who were later diagnosed with invasive breast cancer (cases) were matched (1:2) to women who were not diagnosed with invasive breast cancer (controls) after their DCIS and by the end of 2016. Information on mammographic features were collected by a national radiological review, where screening mammograms were reviewed locally at each of the 16 breast centers in Norway. We used conditional logistic regression analysis to estimate associations between mammographic features of calcifications in the DCIS mammogram and the risk of subsequent invasive breast cancer.

RESULTS

We found a higher risk of invasive breast cancer associated with fine linear branching (casting) morphology (odds ratio 20.0; 95% confidence interval [CI] 2.5-158.9) compared to fine linear or fine pleomorphic morphology. Regional or diffuse distribution showed an odds ratio of 2.8 (95% CI 1.0-8.2) compared to segmental or linear distribution.

CONCLUSION

Mammographic features of calcifications in screen-detected DCIS were of influence on the risk of invasive breast cancer. Unfavorable characteristics of DCIS were fine linear branching morphology, and regional or diffuse distribution.

Ductal Carcinoma in Situ: Molecular Changes Accompanying Disease Progression

Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive ductal carcinoma (IDC), whereby if left untreated, approximately 12% of patients develop invasive disease. The current standard of care is surgical removal of the lesion, to prevent potential progression, and radiotherapy to reduce risk of recurrence. There is substantial overtreatment of DCIS patients, considering not all DCIS lesions progress to invasive disease. Hence, there is a critical imperative to better predict which DCIS lesions are destined for poor outcome and which are not, allowing for tailored treatment. Active surveillance is currently being trialed as an alternative management practice, but this approach relies on accurately identifying cases that are at low risk of progression to invasive disease. Two DCIS-specific genomic profiling assays that attempt to distinguish low and high-risk patients have emerged, but imperfections in risk stratification coupled with a high price tag warrant the continued search for more robust and accessible prognostic biomarkers. This search has largely turned researchers toward the tumor microenvironment. Recent evidence suggests that a spectrum of cell types within the DCIS microenvironment are genetically and phenotypically altered compared to normal tissue and play critical roles in disease progression. Uncovering the molecular mechanisms contributing to DCIS progression has provided optimism for the search for well-validated prognostic biomarkers that can accurately predict the risk for a patient developing IDC. The discovery of such markers would modernize DCIS management and allow tailored treatment plans. This review will summarize the current literature regarding DCIS diagnosis, treatment, and pathology.

Error Reduction and Diagnostic Concordance in Breast Pathology

Errors in anatomic pathology can result in patients receiving inappropriate treatment and poor patient outcomes. Policies and procedures are necessary to decrease error and improve diagnostic concordance. Breast pathology may be more prone to diagnostic errors than other surgical pathology subspecialties due to inherit borderline diagnostic categories such as atypical ductal hyperplasia and low-grade ductal carcinoma in situ. Mandatory secondary review of internal and outside referral cases before treatment is effective in reducing diagnostic errors and improving concordance. Assessment of error through amendment/addendum tracking, implementing an incident reporting system, and multidisciplinary tumor boards can establish procedures to prevent future error.

The Skeleton and Biomineralization Mechanism as Part of the Innate Immune System of Stony Corals

Stony corals are among the most important calcifiers in the marine ecosystem as they form the coral reefs. Coral reefs have huge ecological importance as they constitute the most diverse marine ecosystem, providing a home to roughly a quarter of all marine species. In recent years, many studies have shed light on the mechanisms underlying the biomineralization processes in corals, as characterizing the calicoblast cell layer and genes involved in the formation of the calcium carbonate skeleton. In addition, considerable advancements have been made in the research field of coral immunity as characterizing genes involved in the immune response to pathogens and stressors, and the revealing of specialized immune cells, including their gene expression profile and phagocytosis capabilities. Yet, these two fields of corals research have never been integrated. Here, we discuss how the coral skeleton plays a role as the first line of defense. We integrate the knowledge from both fields and highlight genes and proteins that are related to biomineralization and might be involved in the innate immune response and help the coral deal with pathogens that penetrate its skeleton. In many organisms, the immune system has been tied to calcification. In humans, immune factors enhance ectopic calcification which causes severe diseases. Further investigation of coral immune genes which are involved in skeleton defense as well as in biomineralization might shed light on our understanding of the correlation and the interaction of both processes as well as reveal novel comprehension of how immune factors enhance calcification.

Breast microcalcifications: Past, present and future (Review)

Mammary microcalcifications (MCs) are calcium deposits that are considered as robust markers of breast cancer when identified on mammography. MCs are frequently associated with premalignant and malignant lesions. The aim of the present review was to describe the MC types and associated radiological and pathological aspects in detail, provide insights and approaches to the topic, and describe specific clinical scenarios. The primary MC types are composed of calcium oxalate, hydroxyapatite and hydroxyapatite associated with magnesium. The first type is usually associated with benign conditions, while the others remain primarily associated with malignancy. Radiologically, MCs are classified as benign or suspicious. MCs may represent an active pathological mineralization process rather than a passive process, such as degeneration or necrosis. Practical management of breast specimens requires finely calibrated radiological pathological procedures. Understanding the molecular and structural development of MCs may contribute to breast lesion detection and treatment.

Case Report: Acute Kidney Injury Due to Chronic Milk-Alkali Syndrome in a Patient With Colon Cancer

Background

Common causes of hypercalcemia include primary hyperparathyroidism and paraneoplastic syndrome of malignancy. Because of this, physicians can easily miss extrinsic causes of hypercalcemia such as milk-alkali syndrome in patients with cancer. We successfully treated a case of acute kidney injury due to severe hypercalcemia caused by milk-alkali syndrome due to long-term milk drinking in a patient with colon cancer.

Case Description

A 62-year-old man was referred to nephrology for hypercalcemia and azotemia that was found during preoperative evaluation for colon cancer surgery. The patient had experienced several months of dizziness and anorexia. We started hemodialysis because hypercalcemia and azotemia were not improved despite large amounts of hydration and diuretics. We suspected paraneoplastic syndrome because of concomitant colon cancer and low intact parathyroid hormone (PTH). Renal microcalcifications were observed on ultrasonography. Metastatic calcifications of the lung and stomach were present, but no malignant metastasis appeared on bone scans. There was no evidence of metastatic malignant lesions on chest or abdominal enhanced computed tomography. PTH-related peptide was not detected. Thus, other causes of hypercalcemia beyond malignancy were considered. On history-taking, the patient reported consuming 1,000 to 1,200 mL of milk daily for the prior 3 months. Hypercalcemia was due to chronic milk-alkali syndrome. We advised withdrawal of milk and nutritional pills. Hemodialysis was stopped after 2 weeks since azotemia and hypercalcemia were resolving. Acute kidney injury was improved, and mild hypercalcemia remained when he underwent hemicolectomy after 1 month. Thereafter, serum calcium and creatinine remained normal at discharge and follow-up for 1 year in the outpatient clinic. However, lung calcifications still remained on bone scan after 1 year.

Conclusions

Chronic milk-alkali syndrome is a rare condition resulting from excessive calcium and alkali intake through various routes, like milk, nutritional supplements, and medicines for osteoporosis. Therefore, early management for hypercalcemia should include precise history taking including diet, previous diagnoses, and current medications.

Ductal Carcinoma in Situ: State-of-the-Art Review

Ductal carcinoma in situ (DCIS) is a nonobligate precursor of invasive cancer, and its detection, diagnosis, and management are controversial. DCIS incidence grew with the expansion of screening mammography programs in the 1980s and 1990s, and DCIS is viewed as a major driver of overdiagnosis and overtreatment. For pathologists, the diagnosis and classification of DCIS is challenging due to undersampling and interobserver variability. Understanding the progression from normal breast tissue to DCIS and, ultimately, to invasive cancer is limited by a paucity of natural history data with multiple proposed evolutionary models of DCIS initiation and progression. Although radiologists are familiar with the classic presentation of DCIS as asymptomatic calcifications at mammography, the expanded pool of modalities, advanced imaging techniques, and image analytics have identified multiple potential biomarkers of histopathologic characteristics and prognosis. Finally, there is growing interest in the nonsurgical management of DCIS, including active surveillance, to reduce overtreatment and provide patients with more personalized management options. However, current biomarkers are not adept at enabling identification of occult invasive disease at biopsy or accurately predicting the risk of progression to invasive disease. Several active surveillance trials are ongoing and are expected to better identify women with low-risk DCIS who may avoid surgery.

Classification of microcalcification clusters in digital breast tomosynthesis using ensemble convolutional neural network

BACKGROUND

The classification of benign and malignant microcalcification clusters (MCs) is an important task for computer-aided diagnosis (CAD) of digital breast tomosynthesis (DBT) images. Influenced by imaging method, DBT has the characteristic of anisotropic resolution, in which the resolution of intra-slice and inter-slice is quite different. In addition, the sharpness of MCs in different slices of DBT is quite different, among which the clearest slice is called focus slice. These characteristics limit the performance of CAD algorithms based on standard 3D convolution neural network (CNN).

METHODS

To make full use of the characteristics of the DBT, we proposed a new ensemble CNN, which consists of the 2D ResNet34 and the anisotropic 3D ResNet to extract the 2D focus slice features and 3D contextual features of MCs, respectively. Moreover, the anisotropic 3D convolution is used to build 3D ResNet to avoid the influence of DBT anisotropy.

RESULTS

The proposed method was evaluated on 495 MCs in DBT images of 275 patients, which are collected from our collaborative hospital. The area under the curve (AUC) of receiver operating characteristic (ROC) and accuracy of classifying benign and malignant MCs using decision-level ensemble strategy were 0.8837 and 82.00%, which were significantly higher than the experimental results of 2D ResNet34 (AUC: 0.8264, ACC: 76.00%) and anisotropic 3D ResNet (AUC: 0.8455, ACC: 76.00%). Compared with the results of 3D features classification in the radiomics, the AUC of the deep learning method with decision-level ensemble strategy was improved by 0.0435, and the F1 score was improved from 79.37 to 85.71%. More importantly, the sensitivity increased from 78.13 to 84.38%, and the specificity increased from 66.67 to 77.78%, which effectively reduced the false positives of diagnosis CONCLUSION: The results fully prove that the ensemble CNN can effectively integrate 2D features and 3D features, improve the classification performance of benign and malignant MCs in DBT, and reduce the false positives.

Ten years follow-up of histologically benign calcifications in the breast after vacuum-assisted stereotactic biopsy (VASB): Is additional mammographic follow-up warranted?

Objective

This study assessed the short-term and the long-term breast cancer rate in patients with benign histopathologic results after a vacuum-assisted stereotactic biopsy (VASB) for calcifications.

Methods

In a retrospective cohort study, all consecutive patients who had a benign diagnosis after VASB to analyze breast calcifications. Data of breast cancer development at short-term (four years) and long-term follow-up was gathered. Breast cancer rates in our cohort were compared to the breast cancer incidence in the general population.

Results

Of 1376 patients who underwent VASB to analyze breast calcifications, 823 had a benign histopathologic diagnosis. During short-term follow-up, eight patients developed breast cancer. During the mean long-term follow-up period of 9.3 ± 3.1 years, 22 patients were diagnosed with ipsilateral breast cancer. The incidence rate of breast cancer after benign biopsy was comparable to the rate in the general population.

Conclusion

In patients with VASB-confirmed benign calcifications of the breast, we found no excess incidence of ipsilateral breast cancer during ten years follow-up. Therefore, in patients with an increased risk of breast cancer (due to a history of breast cancer or familial risk) annual mammography should be sufficient. Patients with a population-based risk may be monitored via biennial mammography by the national screening program. More frequent screening would provide no benefit.

•

1% developed ipsilateral breast cancer in four-year follow-up after biopsy.

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3% developed ipsilateral breast cancer in ten-years follow-up after biopsy.

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No statistically significant excess incidence of breast cancer after benign calcifications.

•

A benign histopathologic result after VASB can be considered a safe decision tool.

Optimized alginate-based 3D printed scaffolds as a model of patient derived breast cancer microenvironments in drug discovery

The cancer microenvironment influences tumor progression and metastasis and is pivotal to consider when designingin vivo-like cancer models. Current preclinical testing platforms for cancer drug development are mainly limited to 2D cell culture systems that poorly mimic physiological environments and traditional, low throughput animal models. The aim of this work was to produce a tunable testing platform based on 3D printed scaffolds (3DPS) with a simple geometry that, by extracellular components and response of breast cancer reporter cells, mimics patient-derived scaffolds (PDS) of breast cancer. Here, the biocompatible polysaccharide alginate was used as base material to generate scaffolds consisting of a 3D grid containing periostin and hydroxyapatite. Breast cancer cell lines (MCF7 and MDA-MB-231) produced similar phenotypes and gene expression levels of cancer stem cell, epithelial-mesenchymal transition, differentiation and proliferation markers when cultured on 3DPS and PDS, contrasting conventional 2D cultures. Importantly, cells cultured on 3DPS and PDS showed scaffold-specific responses to cytotoxic drugs (doxorubicin and 5-fluorouracil) that were different from 2D cultured cells. In conclusion, the data presented support the use of a tunable alginate-based 3DPS as a tumor model in breast cancer drug discovery.

Unravelling the Encapsulation of DNA and Other Biomolecules in HAp Microcalcifications of Human Breast Cancer Tissues by Raman Imaging

Simple Summary

Although microcalcifications can be considered one of the first indicators of suspicious cancer lesions, depending on their morphology and distribution, the formation of hydroxyapatite calcifications and their relationship with malignancy remains unknown. In this work, we investigate in depth the biochemical composition of breast cancer microcalcifications, combining Raman spectroscopy imaging and advanced multivariate analysis. We demonstrate that DNA is naturally adsorbed and encapsulated inside hydroxyapatite found in breast cancer tissue. Furthermore, we also show the encapsulation of other relevant biomolecules such as lipids, proteins, cytochrome C and polysaccharides. The demonstration of the natural DNA biomineralization in cancer tissues represents an unprecedented advance in the field, as it can pave the way to understanding the role of hydroxyapatite in malignant tissues.

Abstract

Microcalcifications are detected through mammography screening and, depending on their morphology and distribution (BI-RADS classification), they can be considered one of the first indicators of suspicious cancer lesions. However, the formation of hydroxyapatite (HAp) calcifications and their relationship with malignancy remains unknown. In this work, we report the most detailed three-dimensional biochemical analysis of breast cancer microcalcifications to date, combining 3D Raman spectroscopy imaging and advanced multivariate analysis in order to investigate in depth the molecular composition of HAp calcifications found in 26 breast cancer tissue biopsies. We demonstrate that DNA has been naturally adsorbed and encapsulated inside HAp microcalcifications. Furthermore, we also show the encapsulation of other relevant biomolecules in HAp calcifications, such as lipids, proteins, cytochrome C and polysaccharides. The demonstration of natural DNA biomineralization, particularly in the tumor microenvironment, represents an unprecedented advance in the field, as it can pave the way to understanding the role of HAp in malignant tissues.

Advances in Ultrasound-Guided Vacuum-Assisted Biopsy of Breast Microcalcifications

Microcalcification is one of the significant indications for or can even be the sole mammographic feature of breast cancer, especially occult breast cancer. Biopsy and pathologic examination are the most important methods used to identify the nature of suspicious microcalcifications. Stereotactic vacuum-assisted breast biopsy (S-VAB) is the most commonly used biopsy method for microcalcifications currently because of the high detection rate of mammography for microcalcifications. However, in recent years, several clinical studies have gradually found that ultrasound-guided vacuum-assisted breast biopsy (US-VAB) could be an alternative to S-VAB for microcalcifications to some extent, and has its own advantages of flexibility, real-time performance, comfort and high accessibility compared with mammography. An overview of US-VAB of microcalcifications is provided with respect to success rate, diagnostic accuracy, advantages and limitations. On the basis of numerous studies and clinical experience, US-VAB proved to be a valid alternative to S-VAB, with comparable diagnostic accuracy if the microcalcification foci could be detected by ultrasound. And for patients with ultrasound-invisible microcalcifications who are not suitable for or tolerable of S-VAB, US-VAB combined with mammography localization of microcalcifications can also be considered.

The metabolic adaptation mechanism of metastatic organotropism

Metastasis is a complex multistep cascade of cancer cell extravasation and invasion, in which metabolism plays an important role. Recently, a metabolic adaptation mechanism of cancer metastasis has been proposed as an emerging model of the interaction between cancer cells and the host microenvironment, revealing a deep and extensive relationship between cancer metabolism and cancer metastasis. However, research on how the host microenvironment affects cancer metabolism is mostly limited to the impact of the local tumour microenvironment at the primary site. There are few studies on how differences between the primary and secondary microenvironments promote metabolic changes during cancer progression or how secondary microenvironments affect cancer cell metastasis preference. Hence, we discuss how cancer cells adapt to and colonize in the metabolic microenvironments of different metastatic sites to establish a metastatic organotropism phenotype. The mechanism is expected to accelerate the research of cancer metabolism in the secondary microenvironment, and provides theoretical support for the generation of innovative therapeutic targets for clinical metastatic diseases.

Microcalcification-Based Tumor Malignancy Evaluation in Fresh Breast Biopsies with Hyperspectral Stimulated Raman Scattering

Precise evaluation of breast tumor malignancy based on tissue calcifications has important practical value in the disease diagnosis, as well as the understanding of tumor development. Traditional X-ray mammography provides the overall morphologies of the calcifications but lacks intrinsic chemical information. In contrast, spontaneous Raman spectroscopy offers detailed chemical analysis but lacks the spatial profiles. Here, we applied hyperspectral stimulated Raman scattering (SRS) microscopy to extract both the chemical and morphological features of the microcalcifications, based on the spectral and spatial domain analysis. A total of 211 calcification sites from 23 patients were imaged with SRS, and the results were analyzed with a support vector machine (SVM) based classification algorithm. With optimized combinations of chemical and geometrical features of microcalcifications, we were able to reach a precision of 98.21% and recall of 100.00% for classifying benign and malignant cases, significantly improved from the pure spectroscopy or imaging based methods. Our findings may provide a rapid means to accurately evaluate breast tumor malignancy based on fresh tissue biopsies.