Ultrasonographic features of triple-negative breast cancer: a comparison with other breast cancer subtypes

Contrast-Enhanced Ultrasound and Conventional Ultrasound Characteristics of Breast Cancer With Different Molecular Subtypes

BACKGROUND

Identifying molecular subtypes of breast cancer (BC) is of great significance in selecting optimal treatment strategy. Different molecular subtypes of BC have various vascular distribution characteristics. Contrast-enhanced ultrasound (CEUS) can dynamically display the microcirculation of tumor. This study intends to explore the conventional ultrasound and CEUS characteristics of different molecular subtypes of BC.

METHODS

During this prospective study, 86 patients with BC who were divided into Luminal A (LA), Luminal B (LB), HER2 over-expression (H2), and triple-negative (TN). The CEUS qualitative and quantitative characteristics of BC with different molecular subtypes was explored, as well as the conventional ultrasound features. In addition, the diagnostic efficiency of CEUS quantitative parameters in differentiating molecular subtypes of BC was analyzed.

RESULTS

Our study found that the Adler grade differed significantly among 4 molecular subtypes (P < .05). The enhancement speed, enhancement degree and size after enhancement of 4 molecular subtypes were statistically different (P < .05). The wash in slope (WIS), peak intensity (PI), and wash-in area under the curve (WiAUC) differed significantly among 4 subtypes (P < .05). The diagnostic efficiency of PI was better for detecting LA and H2 subtype with the areas under the receiver operating characteristic curve was 0.778 and 0.734, respectively.

CONCLUSION

Different molecular subtypes of BC have different CEUS and conventional ultrasound characteristics. CEUS can provide valuable imaging basis for precise clinical diagnosis and individualized therapy of BC with different molecular subtypes.

Ultrasound Radiomics Features to Identify Patients With Triple-Negative Breast Cancer: A Retrospective, Single-Center Study

OBJECTIVES

Patients with triple-negative breast cancer (TNBC) exhibit a fast tumor growth rate and poor survival outcomes. In this study, we aimed to develop and compare intelligent algorithms using ultrasound radiomics features in addition to clinical variables to identify patients with TNBC prior to histopathologic diagnosis.

METHODS

We used single-center, retrospective data of patients who underwent ultrasound before histopathologic verification and subsequent neoadjuvant systemic treatment (NAST). We developed a logistic regression with an elastic net penalty algorithm using pretreatment ultrasound radiomics features in addition to patient and tumor variables to identify patients with TNBC. Findings were compared to the histopathologic evaluation of the biopsy specimen. The main outcome measure was the area under the curve (AUC).

RESULTS

We included 1161 patients, 813 in the development set and 348 in the validation set. Median age was 50.1 years and 24.4% (283 of 1161) had TNBC. The integrative model using radiomics and clinical information showed significantly better performance in identifying TNBC compared to the radiomics model (AUC: 0.71, 95% confidence interval [CI]: 0.65-0.76 versus 0.64, 95% CI: 0.57-0.71, P = .004). The five most important variables were cN status, shape surface volume ratio (SA:V), gray level co-occurrence matrix (GLCM) correlation, gray level dependence matrix (GLDM) dependence nonuniformity normalized, and age. Patients with TNBC were more often categorized as BI-RADS 4 than BI-RADS 5 compared to non-TNBC patients (P = .002).

CONCLUSION

A machine learning algorithm showed promising potential to identify patients with TNBC using ultrasound radiomics features and clinical information prior to histopathologic evaluation.

Artificial Intelligence Decision Support for Triple-Negative Breast Cancers on Ultrasound

OBJECTIVE

To assess performance of an artificial intelligence (AI) decision support software in assessing and recommending biopsy of triple-negative breast cancers (TNBCs) on US.

METHODS

Retrospective institutional review board-approved review identified patients diagnosed with TNBC after US-guided biopsy between 2009 and 2019. Artificial intelligence output for TNBCs on diagnostic US included lesion features (shape, orientation) and likelihood of malignancy category (benign, probably benign, suspicious, and probably malignant). Artificial intelligence true positive was defined as suspicious or probably malignant and AI false negative (FN) as benign or probably benign. Artificial intelligence and radiologist lesion feature agreement, AI and radiologist sensitivity and FN rate (FNR), and features associated with AI FNs were determined using Wilcoxon rank-sum test, Fisher's exact test, chi-square test of independence, and kappa statistics.

RESULTS

The study included 332 patients with 345 TNBCs. Artificial intelligence and radiologists demonstrated moderate agreement for lesion shape and orientation (k = 0.48 and k = 0.47, each P <.001). On the set of examinations using 6 earlier diagnostic US, radiologists recommended biopsy of 339/345 lesions (sensitivity 98.3%, FNR 1.7%), and AI recommended biopsy of 333/345 lesions (sensitivity 96.5%, FNR 3.5%), including 6/6 radiologist FNs. On the set of examinations using immediate prebiopsy diagnostic US, AI recommended biopsy of 331/345 lesions (sensitivity 95.9%, FNR 4.1%). Artificial intelligence FNs were more frequently oval (q < 0.001), parallel (q < 0.001), circumscribed (q = 0.04), and complex cystic and solid (q = 0.006).

CONCLUSION

Artificial intelligence accurately recommended biopsies for 96% to 97% of TNBCs on US and may assist radiologists in classifying these lesions, which often demonstrate benign sonographic features.

Utilizing grayscale ultrasound-based radiomics nomogram for preoperative identification of triple negative breast cancer

PURPOSE

This study aimed to develop a radiomics nomogram based on grayscale ultrasound (US) to distinguish triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (NTNBC) prior to surgery.

METHODS

A retrospective analysis of 454 breast carcinoma patients confirmed by pathology was conducted, with 317 patients in the training dataset (59 with TNBC) and 137 patients in the validation dataset (27 with TNBC). Clinical information, conventional US features, and radiomics features were collected, and the Radscore model was constructed after feature selection. Independent risk factors were identified using univariate and multivariate logistic regression analysis. The nomogram model was assessed using the receiver operating characteristic (ROC) curve analysis, calibration curve, decision curve analysis (DCA), net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

RESULTS

Tumor shape, margin, and calcification were independent risk factors in the clinical prediction model. Additionally, 16 radiomics features were selected to construct the Radscore model out of a total of 474 extracted features. The radiomics nomogram model, which incorporated tumor shape, margin, calcification, and Radscore, achieved an AUC value of 0.837 in the training dataset and 0.813 in the validation dataset, outperforming both the Radscore and clinical models in terms of predictive performance. The significant improvement of NRI and IDI indicated that the Radscore may be useful biomarkers for TNBC.

CONCLUSION

The US-based radiomics nomogram showed satisfactory preoperative prediction of TNBC.

Imaging features of breast cancer subtypes on contrast enhanced ultrasound: a feasibility study

The objective of this research was to study the contrast enhancement patterns of the different molecular subtypes of breast cancer on contrast-enhanced ultrasound (CEUS) using both qualitative and quantitative parameters. This prospective study included females with a single breast mass which was histopathologically proven carcinoma. B mode ultrasound (USG) and CEUS were performed in all patients during baseline assessment. Qualitative CEUS assessment encompassed enhancement pattern, presence of fill-in and washout. Quantitative assessment included measurement of peak enhancement, time to peak; area under the curve and mean transit time. A p-value < 0.05 was considered statistically significant for differentiating the subtypes. The included thirty masses were categorised into two subtypes-triple negative breast cancer (TNBC) (36.7%) and non-TNBC (63.3%) subtypes. With B-mode USG, a statistically significant difference was observed between the two groups with respect to their shape and margins. TNBC lesions showed an oval shape, circumscribed margins and peripheral nodular enhancement on CEUS with the absence of fill-in even in the delayed phase (p-value - 0.04). The two subtypes did not significantly differ in terms of quantitative perfusion parameters. The various subtypes of breast cancer therefore possess distinct contrast enhancement patterns. CEUS potentially allows differentiation amongst these molecular subtypes that may aid in radiology-pathology (rad-path) correlation and follow up of the patients.

Emerging role of ferroptosis-related circular RNA in tumor metastasis

Tumor metastasis is an important factor that contributes to the poor prognosis of patients with tumors. Therefore, to solve this problem, research on the mechanism of metastasis is essential. Ferroptosis, a new mode of cell death, is characterized by membrane damage due to lipid peroxidation caused by iron overload. Many studies have shown that excessive ferroptosis can affect tumor metastasis and thus inhibit tumor progression. Recently, circular RNA (circRNA), a type of non-coding RNA, has been shown to be associated with the progression of ferroptosis, thus influencing tumor development. However, the specific mechanisms by which circRNAs affect the progression of ferroptosis and their roles in tumor metastasis are not known. In this review, we systematically discuss the role of circRNAs in regulating tumor ferroptosis and their mechanism of action through sponging miRNAS in various tumors, thereby impacting metastasis. This review helps elucidate the relationship and role of ferroptosis-related circRNAs in tumor metastasis and may provide future researchers with new ideas and directions for targeted therapies.

Calcification, Posterior Acoustic, and Blood Flow: Ultrasonic Characteristics of Triple-Negative Breast Cancer

Previous studies suggest that triple-negative breast cancer (TNBC) may have unique imaging characteristics, however, studies focused on the imaging characteristics of TNBC are still limited. The aim of the present study is to analyze the ultrasonic characteristics of TNBC and to provide more reliable information on imaging diagnosis of TNBC. This retrospective study was performed including 162 TNBC patients with 184 TNBC lesions. 174 non-TNBC cases with 196 lesions were used as the control group. The median size of TNBC lesions and non-TNBC lesions were 23 mm × 16 mm and 21 mm × 15 mm, respectively. The shape of most breast cancer lesions was irregular. However, 15.30% (28/183) TNBC lesions and 16.84% (33/196) non-TNBC lesions were oval-shaped. Most breast cancer lesions (79.78% TNBC & 85.71% non-TNBC) were ill-defined. In comparison to non-TNBC, the distinctive ultrasonic characteristics of TNBC were summarized as three features: calcifications, posterior acoustic, and blood flow. Microcalcifications was less common in non-TNBC. The remarkable posterior acoustic characteristics on TNBC were no posterior acoustic features (136, 73.91%). Avascular pattern (21.74%) was also more common in TNBC. The other feature of TNBC was markedly hypoechoic lesions (23.91%). The above-mentioned differences between TNBC and non-TNBC were significant. 93.48% TBNC and 94.39% non–TNBC lesions were in BI-RADS-US category of 4A-5. The results indicate that TNBC has some distinctive ultrasound characteristics. Ultrasound is a useful adjunct in early detection of breast cancer. A combination of ultrasound with mammography is excellent for detecting breast cancer.

Value of Histogram of Gray-Scale Ultrasound Image in Differential Diagnosis of Small Triple Negative Breast Invasive Ductal Carcinoma and Fibroadenoma

Objective

To investigate the value of gray-scale ultrasound (US) image histogram in the differential diagnosis between small (≤2.00 cm), oval, or round triple negative breast invasive ductal carcinoma (TN-IDC) and fibroadenoma (FA).

Methods

Fifty-five cases of triple negative breast invasive ductal carcinoma (TN-IDC group) and 57 cases of breast fibroadenoma (FA group) confirmed by pathology in Hubei cancer hospital from September 2017 to September 2021 were analyzed retrospectively. The gray-scale US images were analyzed by histogram analysis method, from which some parameters (including mean, variance, skewness, kurtosis and 1st, 10th, 50th, 90th and 99th percentile) can be obtained. Intraclass correlation coefficient (ICC) was used to evaluate the inter observer reliability of histogram parameters. Histogram parameters between the TN-IDC and FA groups were compared using independent Student’s t-test or Mann-Whitney U-test, respectively. In addition, the receiver operating characteristic (ROC) curve analysis was used for the significant parameters to calculate the differential diagnosis efficiency.

Results

All the histogram parameters showed excellent inter-reader consistency, with the ICC values ranged from 0.883 to 0.999. The mean value, 1st, 10th, 50th, 90th and 99th percentiles of TN-IDC group were significantly lower than those of FA group (P < 0.05). The area under ROC curve (AUC) values of mean and n percentiles were from 0.807 to 0.848. However, there were no significant differences in variance, skewness and kurtosis between the two groups (P > 0.05).

Conclusion

Histogram analysis of gray-scale US images can well distinguish small, oval, or round TN-IDC from FA.

Prediction for pathological and immunohistochemical characteristics of triple-negative invasive breast carcinomas: the performance comparison between quantitative and qualitative sonographic feature analysis

OBJECTIVE

Sonographic features are associated with pathological and immunohistochemical characteristics of triple-negative breast cancer (TNBC). To predict the biological property of TNBC, the performance using quantitative high-throughput sonographic feature analysis was compared with that using qualitative feature assessment.

METHODS

We retrospectively reviewed ultrasound images, clinical, pathological, and immunohistochemical (IHC) data of 252 female TNBC patients. All patients were subgrouped according to the histological grade, Ki67 expression level, and human epidermal growth factor receptor 2 (HER2) score. Qualitative sonographic feature assessment included shape, margin, posterior acoustic pattern, and calcification referring to the Breast Imaging Reporting and Data System (BI-RADS). Quantitative sonographic features were acquired based on the computer-aided radiomics analysis. Breast cancer masses were manually segmented from the surrounding breast tissues. For each ultrasound image, 1688 radiomics features of 7 feature classes were extracted. The principal component analysis (PCA), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM) were used to determine the high-throughput radiomics features that were highly correlated to biological properties. The performance using both quantitative and qualitative sonographic features to predict biological properties of TNBC was represented by the area under the receiver operating characteristic curve (AUC).

RESULTS

In the qualitative assessment, regular tumor shape, no angular or spiculated margin, posterior acoustic enhancement, and no calcification were used as the independent sonographic features for TNBC. Using the combination of these four features to predict the histological grade, Ki67, HER2, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI), the AUC was 0.673, 0.680, 0.651, 0.587, and 0.566, respectively. The number of high-throughput features that closely correlated with biological properties was 34 for histological grade (AUC 0.942), 27 for Ki67 (AUC 0.732), 25 for HER2 (AUC 0.730), 34 for ALNM (AUC 0.804), and 34 for LVI (AUC 0.795).

CONCLUSION

High-throughput quantitative sonographic features are superior to traditional qualitative ultrasound features in predicting the biological behavior of TNBC.

KEY POINTS

• Sonographic appearances of TNBCs showed a great variety in accordance with its biological and clinical characteristics. • Both qualitative and quantitative sonographic features of TNBCs are associated with tumor biological characteristics. • The quantitative high-throughput feature analysis is superior to two-dimensional sonographic feature assessment in predicting tumor biological property.

Dependability of Automated Breast Ultrasound (ABUS) in Assessing Breast Imaging Reporting and Data System (BI-RADS) Category and Size of Malignant Breast Lesions Compared with Handheld Ultrasound (HHUS) and Mammography (MG)

Purpose

This study aimed to evaluate the dependability of automated breast ultrasound (ABUS) compared with handheld ultrasound (HHUS) and mammography (MG) on the Breast Imaging Reporting and Data System (BI-RADS) category and size assessment of malignant breast lesions.

Patients and Methods

A total of 344 confirmed malignant lesions were recruited. All participants underwent MG, HHUS, and ABUS examinations. Agreements on the BI-RADS category were evaluated. Lesion size assessed using the three methods was compared with the size of the pathological result as the control. Regarding the four major molecular subtypes, correlation coefficients between size on imaging and pathology were also evaluated.

Results

The agreement between ABUS and HHUS on the BI-RADS category was 86.63% (kappa = 0.77), whereas it was 32.22% (kappa = 0.10) between ABUS and MG. Imaging lesion size compared to pathologic lesion size was assessed correctly in 36.92%/52.91% (ABUS), 33.14%/48.84% (HHUS) and 33.44%/43.87% (MG), with the threshold of 3 mm/5 mm, respectively. The correlation coefficient of size of ABUS-Pathology (0.75, Spearman) was statistically higher than that of the MG-Pathology (0.58, Spearman) with P < 0.01, but not different from that of the HHUS-Pathology (0.74, Spearman) with P > 0.05. The correlation coefficient of ABUS-Pathology was statistically higher than that of MG-Pathology in the triple-negative subtype, luminal B subtype, and luminal A subtype (P<0.01).

Conclusion

The agreement between ABUS and HHUS in the BI-RADS category was good, whereas that between ABUS and MG was poor. ABUS and HHUS allowed a more accurate assessment of malignant tumor size compared to MG.

Is There a Correlation between Multiparametric Assessment in Ultrasound and Intrinsic Subtype of Breast Cancer?

Molecular profile of breast cancer provides information about its biological activity, prognosis and treatment strategies. The purpose of our study was to investigate the correlation between ultrasound features and molecular subtypes of breast cancer. From June 2019 to December 2019, 86 patients (median age 57 years; range 32–88) with 102 breast cancer tumors were included in the study. The molecular subtypes were classified into five types: luminal A (LA), luminal B without HER2 overexpression (LB HER2−), luminal B with HER2 overexpression (LB HER2+), human epidermal growth factor receptor 2 positive (HER2+) and triple negative breast cancer (TNBC). Histopathological verification was obtained in core biopsy or/and post-surgery specimens in all cases. Univariate logistic regression analysis was performed to assess the association between the subtypes and ultrasound imaging features. Experienced radiologists assessed lesions according to the BIRADS-US lexicon. The ultrasound scans were performed with a Supersonic Aixplorer and Supersonix. Based on histopathological verification, the rates of LA, LB HER2−, LB HER2+, HER2+, and TNBC were 33, 17, 17, 16, 19, respectively. Both LB HER2+ and HER2+ subtypes presented higher incidence of calcification (OR = 3.125, p = 0.02, CI 0.0917–5.87) and HER2+ subtype presented a higher incidence of posterior enhancement (OR = 5.75, p = 0.03, CI 1.2257–32.8005), compared to other subtypes. The calcifications were less common in TNBC (OR = 0.176, p = 0.0041, CI 0.0469–0.5335) compared to other subtypes. There were no differences with regard to margin, shape, orientation, elasticity values and vascularity among five molecular subtypes. Our results suggest that there is a correlation between ultrasonographic features assessed according to BIRADS-US lexicon and BC subtypes with HER2 overexpression (both LB HER2+ and HER2+). It may be useful for identification of these aggressive subtypes of breast cancer.

CircGFRA1 facilitates the malignant progression of HER-2-positive breast cancer via acting as a sponge of miR-1228 and enhancing AIFM2 expression

CircRNAs (circular RNA) are reported to regulate onset and progress multiple cancers. Nonetheless, the function along with the underlying mechanisms of circRNAs in HER-2-positive breast cancer (BC) remains unclear. CircRNA microarrays were performed to elucidate expression profiles of HER-2-positive BC cells. circRNA levels were quantified using qRT-PCR assay. Various in vitro along with in vivo assays were employed to further explore the effects of circGFRA1 in the progress of HER-2-positive BC and interactions of circGFRA1, miR-1228 and AIFM2 in Her-2-positive BC. CircGFRA1 was remarkably upregulated in HER-2-positive BC. Knockdown of circGFRA1 could attenuate HER-2-positive BC progression by inhibiting the proliferation, infiltration and migratory ability of HER-2-positive BC cells. Through ceRNA mechanism, circGFRA1 could bind to miR-1228 and alleviate inhibitory activity of miR-1228 on targeted gene AIFM2. In summary, circGFRA1-miR-1228-AIFM2 axis regulates HER-2-positive BC. CircGFRA1 is a novel promising treatment option for HER-2-positive BC.

Predicting Molecular Subtypes of Breast Cancer with Mammography and Ultrasound Findings: Introduction of Sono-Mammometry Score

We studied the correlation of sonographic and digital mammographic features with molecular classification of breast cancer. Imaging features from 313 patients with preliminary ultrasound and digital mammogram between November 2017 and May 2020 were compared with histopathology and immunohistochemical analysis for the prediction of molecular classification of breast cancer. We also devised a score called “sono-mammometry” score consisting of few simple imaging features which can easily be performed in outpatient settings. We studied that non-triple-negative breast cancers are predominantly hypoechoic and strongly correlate with the presence of irregular spiculated margins along with peripheral echogenic halo, posterior shadowing, and microcalcifications, while there is considerable variation in imaging features of TNBC as some of its imaging features overlap with those of typical benign tumors. Although imaging characteristics are helpful in the prediction of molecular classification, the prognostication value of these imaging features is still weak. There is considerable variation in imaging features which warrants vigilance towards improved diagnostic performance. To help better understand these features, our sono-mammometry score can serve as straightforward test which is assumed to be functional and productive in resource-limited settings.

Sonographic Features of Triple-Negative Breast Carcinomas Are Correlated With mRNA-lncRNA Signatures and Risk of Tumor Recurrence

Background

To determine a correlation between mRNA and lncRNA signatures, sonographic features, and risk of recurrence in triple-negative breast cancers (TNBC).

Methods

We retrospectively reviewed the data from 114 TNBC patients having undergone transcriptome analysis. The risk of tumor recurrence was determined based on the correlation between transcriptome profiles and recurrence-free survival. Ultrasound (US) features were described according to the Breast Imaging Reporting and Data System. Multivariate logistic regression analysis determined the correlation between US features and risk of recurrence. The predictive value of sonographic features in determining tumor recurrence was analyzed using receiver operating characteristic curves.

Results

Three mRNAs (CHRDL1, FCGR1A, and RSAD2) and two lncRNAs (HIF1A-AS2 and AK124454) were correlated with recurrence-free survival in patients with TNBC. Among the three mRNAs, two were upregulated (FCGR1A and RSAD2) and one was downregulated (CHRDL1) in TNBCs. LncRNAs HIF1A-AS2 and AK124454 were upregulated in TNBCs. Based on these signatures, an integrated mRNA–lncRNA model was established using Cox regression analysis to determine the risk of tumor recurrence. Benign-like sonographic features, such as regular shape, circumscribed margin, posterior acoustic enhancement, and no calcifications, were associated with HIF1A-AS2 expression and high risk of tumor recurrence (P<0.05). Malignant-like features, such as irregular shape, uncircumscribed margin, no posterior acoustic enhancement, and calcifications, were correlated with CHRDL1 expression and low risk of tumor recurrence (P<0.05).

Conclusions

Sonographic features and mRNA–lncRNA signatures in TNBCs represent the risk of tumor recurrence. Taken together, US may be a promising technique in determining the prognosis of patients with TNBC.

Role of ultrasound in predicting the molecular subtypes of invasive breast ductal carcinoma

Background

Breast cancer is a heterogeneous disease that was explained recently by the presence of multiple molecular subtypes. These subtypes are the luminal A (LA), luminal B (LB), human epidermal growth factor receptor 2 (HER2), and triple-negative (TN). In this study, we aim to investigate whether ultrasound imaging features can play a role in predicting the molecular subtypes of invasive ductal breast cancer (IDC) and to assess whether the nodal metastasis is an independent predictor for each subtype.

Results

The predictive sonographic signs for each subtype are as follows: echogenic halo, posterior shadowing, angular or spiculated margin, and unifocal mass for LA subtype; irregular shape for LB subtype; unifocal mass, abrupt interface of the tumor boundary, and posterior enhancement or no posterior change for HER2 subtype; and circumscribed or lobulated margin, oval or rounded shape, posterior enhancement or no posterior change, abrupt interface of the tumor boundary, and parallel orientation of the mass for TN. By multivariate logistic regression, presence of nodal metastasis is the strongest independent predictor for HER2 subtype, and its absence is the strongest independent predictor for LA subtype.

Conclusions

Certain sonographic signs are predictors for each molecular subtype of IDC. Nodal metastasis is an independent predictor for HER2 subtype when present and for LA subtype when absent.

Systematic Review and Meta-analysis of the Malignant Ultrasound Features of Triple-Negative Breast Cancer

OBJECTIVES

The malignant ultrasound (US) features of breast cancer are known to include an irregular shape, a noncircumscribed margin, an echogenic halo, a nonparallel orientation, posterior acoustic attenuation, microcalcification, and others. However, these US features are uncertain and controversial for the diagnosis of triple-negative breast cancer (TNBC). This study aimed to analyze the diagnostic value of malignant US features for TNBC by a systematic review and meta-analysis, analyze the US characteristics of TNBC, and provide US evidence for clinical diagnosis.

METHODS

A comprehensive search was performed to identify relevant English articles concerning the US diagnosis of TNBC (from the date of database establishment to November 2019). The pooled sensitivity, pooled specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio with 95% confidence interval, summary receiver operating characteristic curve, and area under the curve for the different malignant US features were calculated.

RESULTS

Ten studies (620 patients) met the eligibility criteria. The sensitivity (range, 0.14-0.68) and specificity (range, 0.19-0.66) of the malignant US features were not high. Summary receiver operating characteristic curves showed that the area under the curve (range, 0.25-0.47) of the malignant US features was low, demonstrating that these features have poor diagnostic value for TNBC. The positive likelihood ratio (range, 0.4-to 0.9) of the malignant US features was low, and the negative likelihood ratio (range, 1.09-2.02) was not low, revealing that these features had a poor ability to confirm or exclude TNBC.

CONCLUSIONS

Triple-negative breast cancer lacks the typical malignant US features of breast cancer and has its own US features.

Tumor Proliferation and Invasiveness Derived From Ultrasound Appearances of Invasive Breast Cancers: Moving Beyond the Routine Differential Diagnosis

OBJECTIVES

To investigate the correlation between ultrasound (US) appearances of invasive breast cancers and tumor proliferation and invasiveness measured according to the histologic grade, Ki-67 expression, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI).

METHODS

This study evaluated 676 patients who underwent primary surgical treatment of invasive breast cancers. The preoperative US reports and postoperative pathologic and immunohistochemical results of the patients were retrospectively reviewed. Ultrasound characteristics were evaluated according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) lexicon. Logistic regression analyses were used to identify independent predictive US features that were correlated with tumor proliferation and invasiveness of breast cancers. Odds ratios (ORs) were calculated.

RESULTS

Posterior acoustic enhancement and calcifications on US images were independent predictive factors of a higher histologic grade and a higher Ki-67 level (OR, 1.69-6.54; P < .05). Meanwhile, a noncircumscribed margin (OR, 2.61; P < .05) and posterior acoustic shadow (OR, 1.62; P < .05) were independent predictors of ALNM. An irregular shape (OR, 2.13; P < .05) and calcifications (OR, 1.69; P < .05) were independent risk factors for LVI. Infiltrative breast cancers scored as BI-RADS category 5 had higher probability to be associated with ALNM (OR, 3.33; P < .0005) and LVI (OR, 2.87; P < .0005).

CONCLUSIONS

Ultrasound features of invasieve breast cancers might have a predictive value for tumor proliferation and invasiveness. The US features correlated with a high cellular proliferation rate were different from those associated with ALNM. The tumor shape, margin, posterior acoustic pattern, and calcifications at US are suggested to be considered by clinicians when making clinical decisions.

The Association Between Ultrasound Features and Biological Properties of Invasive Breast Carcinoma Is Modified by Age, Tumor Size, and the Preoperative Axilla Status

OBJECTIVES

To investigate the value of ultrasound (US) feature-based models in predicting the proliferation and invasiveness of invasive breast cancer (IBC) and to compare the performance of models based solely on US features with models that combined US features, patient age, tumor size, and axilla status from US.

METHODS

With ethical approval, 746 patients with a pathologic diagnosis of IBC were reviewed for preoperative clinical, US, and postoperative pathologic data. The proliferation and invasiveness properties of the IBC included the histologic grade and Ki-67 status and lymphovascular invasion (LVI) and axillary lymph node metastasis (ALNM), respectively. Logistic regression analyses were used to identify independent risk factors for tumor proliferation and invasiveness.

RESULTS

Posterior echo enhancement, calcification, a tumor size larger than 2 cm, and suspicion of ALNM from axillary US were independent risk factors for a high histologic grade and high Ki-67 expression of IBC (P < .05). A posterior echo shadow, patient age younger than 45 years, and suspicious findings on axillary US imaging were independent variables for predicting the presence of LVI and ALNM in IBC (P < .05). Calcification was the independent factor for predicting LVI (P = .013). The predictive performance of the combined models was improved compared with the US feature-based models, with a higher accuracy rate and negative predictive value. The area under curve of the combined models was also significantly higher than that of the single models (P < .05).

CONCLUSIONS

Compared with the US feature-based models, the combined models yielded better predictive performance. This may provide a more robust model to predict the tumor biological properties of IBC before surgery.

Ultrasonographic appearance of triple-negative invasive breast carcinoma is associated with novel molecular subtypes based on transcriptomic analysis

Background

Various sonographic features of triple-negative invasive breast carcinomas (TNBC) expected to be associated with the molecular subtypes based on transcriptomic analysis were examined. The effects of clinical, sonographic, pathological, and molecular features on survival outcome was also studied.

Methods

One hundred and fourteen patients with breast cancer with negative expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal receptor 2 (HER2) were included in our retrospective study. Based on the transcriptomic profiles, four stable clusters named immunomodulatory (IM), luminal androgen receptor (LAR), mesenchymal-like (MES), and basal-like and immune-suppressed (BLIS) were identified. Ultrasound (US) images were reviewed by two US physicians according to Breast Imaging Reporting and Data System (BI-RADS). Multivariate Cox regression was used to determine the variables associated with recurrence-free survival (RFS) and overall survival (OS).

Results

There were 21 IM, 18 LAR, 36 MES, and 39 BLIS cases. The four molecular subtypes showed significant differences in terms of tumor shape (P=0.008) and posterior acoustic pattern (P=0.028). Compared with the subtypes LAR and MES, the IM and BLIS subtypes had higher probability of presenting benign-like sonographic features, such as regular shape, no angular/spiculated margin, and posterior acoustic enhancement (P<0.05). The independent risk factors for RFS events and death were axillary lymph node metastasis (P<0.05) and BLIS subtype (P<0.05). BLIS subtype showed worse OS than other subtypes (log rank P=0.05). TNBCs with benign sonographic features tended to have less death events (3.3% vs. 15.2%, P=0.088).

Conclusions

Sonographic appearance of TNBCs is associated with transcriptome-based molecular subtypes, and tends to correlate with the survival outcome.

Probability analysis of axillary lymph node metastasis in breast cancer patients using particle space-time distribution model

The possibility of axillary lymph node metastasis differs in different breast cancer patients and is the strongest prognostic indicator in breast cancer. The existing studies mainly explored the relationship of axillary ultrasound imaging and axillary lymph node metastasis, without exploring whether ultrasound imaging of breast tumour can affect and perform axillary lymph node prediction. Therefore, this Letter proposes a novel particle space-time distribution model to find the correlation between contrast-enhanced ultrasonography of breast tumour and axillary lymphatic metastasis. Starting from the imaging principle of dynamic contrast-enhanced ultrasonography, the particle space-time distribution model not only comprises space-time features of contrast-enhanced ultrasonography with an encoder-decoder network, but also the flow field information of microbubble particles is integrated into the space-time features that better serves the metastasis prediction by enhancing the particle distribution information. Extensive experiments on real patients have demonstrated that dynamic contrast-enhanced ultrasonography of breast tumour can be used to predict the probability of lymphatic metastasis. This conclusion can be interpretable from the clinical and pathological perspectives.

Upregulated expression of AT-rich interactive domain-containing protein 1B predicts poor prognosis in patients with triple-negative breast cancer

The expression of AT-rich interactive domain-containing protein 1B (ARID1B) was investigated in triple-negative breast cancer (TNBC). The association between ARID1B protein expression and the prognosis of patients with TNBC was investigated. The expression of ARID1B was examined in TNBC (n=142) and adjacent normal breast tissues (n=64) using immunohistochemical staining prior to the patients receiving any treatment. Furthermore, the association between ARID1B protein expression and various clinicopathological features was analyzed, including the survival status of patients with TNBC. Of the 142 TNBC tissues, ARID1B was highly expressed in 89 (62.7%) and poorly expressed in 53 (37.3%). ARID1B expression was associated with lymph node metastasis status, histological grade and p53 expression. ARID1B expression was upregulated significantly in the nuclei of TNBC cells compared with those of normal mammary epithelial cells. This upregulation was associated with a decreased progression-free survival rate (P=0.002) and overall survival rate (P=0.003). The results of the present study indicate that significant association exists between the nuclear expression of ARID1B and adverse prognosis in TNBC. Therefore, ARID1B may be a useful prognostic biomarker in TNBC.

Downregulation of miR-638 promotes progression of breast cancer and is associated with prognosis of breast cancer patients

Background

Breast cancer is the most common tumor among women. miR-638 has been demonstrated to play an important role in various cancers.

Purpose

In this study, we aimed to investigate the function and prognostic value of miR-638 in breast cancer.

Methods

Quantitative real-time polymerase chain reaction analysis was used to evaluate the expression of miR-638 in breast cancer tissues and cell lines. The correlation of miR-638 with clinicopathological features was analyzed using the chi-squared test. Kaplan–Meier survival analysis and Cox regression assay were performed to investigate the prognostic value of miR-638 in breast cancer patients. The effects of miR-638 on the biological behavior of breast cancer cells were evaluated using functional assays.

Results

The expression of miR-638 was downregulated in breast cancer tissues and cell lines (all P<0.05). Decreased expression of miR-638 was significantly correlated with lymph node metastasis (P=0.015) and TNM stage (P=0.021). Patients with low miR-638 expression had shorter overall survival compared with those with high levels (Log-rank P=0.025). The miR-638 could be considered as an independent prognostic factor for the patients (HR =0.321, 95% CI =0.117–0.882, P=0.027). Downregulation of miR-638 was capable of promoting cell proliferation, migration, and invasion in MDA-MB-231 and MCF-7 cells.

Conclusion

All the results indicate that miR-638 is a tumor suppressor in breast cancer and is involved in the progression of breast cancer. Thus, it may serve as a prognostic biomarker for breast cancer.

Radiomics of US texture features in differential diagnosis between triple-negative breast cancer and fibroadenoma

Triple-negative breast cancer (TNBC) is sometimes mistaken for fibroadenoma due to its tendency to show benign morphology on breast ultrasound (US) albeit its aggressive nature. This study aims to develop a radiomics score based on US texture analysis for differential diagnosis between TNBC and fibroadenoma, and to evaluate its diagnostic performance compared with pathologic results. We retrospectively included 715 pathology-proven fibroadenomas and 186 pathology-proven TNBCs which were examined by three different US machines. We developed the radiomics score by using penalized logistic regression with a least absolute shrinkage and selection operator (LASSO) analysis from 730 extracted features consisting of 14 intensity-based features, 132 textural features and 584 wavelet-based features. The constructed radiomics score showed significant difference between fibroadenoma and TNBC for all three US machines (p < 0.001). Although the radiomics score showed dependency on the type of US machine, we developed more elaborate radiomics score for a subgroup in which US examinations were performed with iU22. This subsequent radiomics score also showed good diagnostic performance, even for BI-RADS category 3 or 4a lesions (AUC 0.782) which were presumed as probably benign or low suspicious of malignancy by radiologists. It was expected to assist radiologist’s diagnosis and reduce the number of invasive biopsies, although US standardization should be overcome before clinical application.

Triple-negative invasive breast carcinoma: the association between the sonographic appearances with clinicopathological feature

In this study, we aimed to evaluate the clinical and pathological factors that associated with sonographic appearances of triple-negative (TN) invasive breast carcinoma. With the ethical approval, 560 patients who were pathologically confirmed as invasive breast carcinoma were reviewed for ultrasound, clinical, and pathological data. Logistic regression analysis was used to identify the typical sonographic features for TN invasive breast carcinomas. The effect of clinical and pathological factors on the sonographic features of TN invasive breast carcinoma was studied. There were 104 cases of TN invasive breast carcinoma. The independent sonographic features for the TN subgroup included regular shape (odds ratio, OR = 2.14, p = 0.007), no spiculated/angular margin (OR = 1.93, p = 0.035), posterior acoustic enhancement (OR = 2.14, p = 0.004), and no calcifications (OR = 2.10, p = 0.008). Higher pathological grade was significantly associated with regular tumor shape of TN breast cancer (p = 0.012). Higher Ki67 level was significantly associated with regular tumor shape (p = 0.023) and absence of angular/spiculated margin (p = 0.005). Higher human epidermal growth factor receptor 2 (HER2) score was significantly associated with the presence of calcifications (p = 0.033). We conclude that four sonographic features are associated with TN invasive breast carcinoma. Heterogeneity of sonographic features was associated with the pathological grade, Ki67 proliferation level and HER2 score of TN breast cancers.

miR-221 stimulates breast cancer cells and cancer-associated fibroblasts (CAFs) through selective interference with the A20/c-Rel/CTGF signaling

Background

MicroRNA (miRNAs) are non-coding small RNA molecules that regulate gene expression by inhibiting the translation of target mRNAs. Among several dysregulated miRNAs in human cancer, the up-regulation of miR-221 has been associated with development of a variety of hematologic and solid malignancies. In this study, we investigated the involvement of miR-221 in breast cancer.

Methods

TaqMan microRNA assay was used to detect the miR-221 levels in normal cells and in MDA-MB 231 and SkBr3 breast cancer cells as well as in main players of the tumor microenvironment, namely cancer-associated fibroblasts (CAFs). miR-221 mimic sequence and locked nucleic acid (LNA)-i-miR-221 construct were used to induce or inhibit, respectively, the miR-221 expression in cells used. Quantitative PCR and western blotting analysis were performed to evaluate the levels of the miR-221 target gene A20 (TNFAIP3), as well as the member of the NF-kB complex namely c-Rel and the connective tissue growth factor (CTGF). Chromatin immunoprecipitation (ChIP) assay was performed to ascertain the recruitment of c-Rel to the CTFG promoter. Finally, the cell growth and migration in the presence of LNA-i-miR-221 or silencing c-Rel and CTGF by specific short hairpin were assessed by cell count, colony formation and boyden chambers assays. Statistical analysis was performed by ANOVA.

Results

We first demonstrated that LNA-i-miR-221 inhibits both endogenous and ectopic expression of miR-221 in our experimental models. Next, we found that the A20 down-regulation, as well as the up-regulation of c-Rel induced by miR-221 were no longer evident using LNA-i-miR-221. Moreover, we established that the miR-221 dependent recruitment of c-Rel to the NF-kB binding site located within the CTGF promoter region is prevented by using LNA-i-miR-221. Furthermore, we determined that the up-regulation of CTGF mRNA and protein levels by miR-221 is no longer evident using LNA-i-miR221 and silencing c-Rel. Finally, we assessed that cell growth and migration induced by miR-221 in MDA-MB 231 and SkBr3 breast cancer cells as well as in CAFs are abolished by LNAi-miR-221 and silencing c-Rel or CTGF.

Conclusions

Overall, these data provide novel insights into the stimulatory action of miR-221 in breast cancer cells and CAFs, suggesting that its inhibition may be considered toward targeted therapeutic approaches in breast cancer patients.

MicroRNAs in the development and neoplasia of the mammary gland

Study on the role of microRNAs (miRs) as regulators of gene expression through posttranscriptional gene silencing is currently gaining much interest,due to their wide involvement in different physiological processes. Understanding mammary gland development, lactation, and neoplasia in relation to miRs is essential. miR expression profiling of the mammary gland from different species in various developmental stages shows their role as critical regulators of development. miRs such as miR-126, miR-150, and miR-145 have been shown to be involved in lipid metabolism during lactation. In addition, lactogenic hormones influence miR expression as evidenced by overexpression of miR-148a in cow mammary epithelial cells, leading to enhanced lactation. Similarly, the miR-29 family modulates lactation-related gene expression by regulating DNA methylation of their promoters. Besides their role in development, lactation and involution, miRs are responsible for breast cancer development. Perturbed estrogen (E2) signaling is one of the major causes of breast cancer. Increased E2 levels cause altered expression of ERα, and ERα-miR cross-talk promotes tumour progression. miRs, such as miR-206, miR-34a, miR-17-5p, and miR-125 a/b are found to be tumour suppressors; whereas miR-21, miR-10B, and miR-155 are oncogenes. Oncogenic miRs like miR-21, miR-221, and miR-210 are overexpressed in triple negative breast cancer cases which can be diagnostic biomarker for this subtype of cancer.  This review focuses on the recent findings concerning the role of miRs in developmental stages of the mammary gland (mainly lactation and involution stages) and their involvement in breast cancer progression. Further studies in this area will help us to understand the molecular details of mammary gland biology, as well as miRs that could be therapeutic targets of breast cancer.

HER-2 Positive Breast Cancer - a Mini-Review

Breast cancer is one of among all cancers with increased incidence, high mortality rate, and high economic and social costs. The the most common type of cancer among females worldwide, breast cancer is actually the uncontrolled proliferation of cells which attain malignancy. Recently it has shown that breast cancer contributes 11% among all types of cancer diagnosed globally on an annual basis and it is one of the leading causes of death among women. The human epidermal growth factor receptor 2 (HER-2) is a receptor tyrosine-protein kinase erbB-2 normally involved in the proliferation and division of breast cells. In some abnormal cases the HER2 gene does not work correctly and makes too many copies of itself. HER2-positive (HER2+) breast cancers constitute an aggressive type of breast cancer and tend to grow faster and are more likely to spread. However, therapies that specifically target HER2, such as Herceptin® (traztuzumab), are very effective. HER2 targeted therapies, has significantly improved the therapeutic outcome for patients with HER2 positive breast cancer.

Imaging features of automated breast volume scanner: Correlation with molecular subtypes of breast cancer

OBJECTIVES

To investigate the correlation between the imaging features obtained by an automated breast volume scanner (ABVS) and molecular subtypes of breast cancer.

METHODS

We examined 303 malignant breast tumours by ABVS for specific imaging features and by immunohistochemical analysis to determine the molecular subtype. ABVS imaging features, including retraction phenomenon, shape, margins, echogenicity, post-acoustic features, echogenic halo, and calcifications were analysed by univariate and multivariate logistic regression analyses to determine the significant predictive factors of the molecular subtypes.

RESULTS

By univariate logistic regression analysis, the predictive factors of the Luminal-A subtype (n=128) were retraction phenomenon (odds ratio [OR]=10.188), post-acoustic shadowing (OR=5.112), and echogenic halo (OR=3.263, P<0.001). The predictive factors of the Human-epidermal-growth-factor-receptor-2-amplified subtype (n=39) were calcifications (OR=6.210), absence of retraction phenomenon (OR=4.375), non-mass lesions (OR=4.286, P<0.001), absence of echogenic halo (OR=3.851, P=0.035), and post-acoustic enhancement (OR=3.641, P=0.008). The predictors for the Triple-Negative subtype (n=47) were absence of retraction phenomenon (OR=5.884), post-acoustic enhancement (OR=5.255, P<0.001), absence of echogenic halo (OR=4.138, P=0.002), and absence of calcifications (OR=3.363, P=0.001). Predictors for the Luminal-B subtype (n=89) had a relatively lower association (OR≤2.328). By multivariate logistic regression analysis, retraction phenomenon was the strongest independent predictor for the Luminal-A subtype (OR=9.063, P<0.001) when present and for the Triple-Negative subtype (OR=4.875, P<0.001) when absent.

CONCLUSIONS

ABVS imaging features, especially retraction phenomenon, have a strong correlation with the molecular subtypes, expanding the scope of ultrasound in identifying breast cancer subtypes with confidence.

Identification of Specific miRNA Signature in Paired Sera and Tissue Samples of Indian Women with Triple Negative Breast Cancer

Of several subtypes of breast cancer, triple negative breast cancer (TNBC) is a highly aggressive tumor that lacks expression of hormone receptors for estrogen, progesterone and human epidermal growth factor receptor 2 and shows a worst prognosis. The small noncoding RNAs (miRNAs) considered as master regulator of gene expression play a key role in cancer initiation, progression and drug resistance and have emerged as attractive molecular biomarkers for diagnosis, prognosis and treatment targets in cancer. We have done expression profiling of selected miRNAs in paired serum and tissue samples of TNBC patients and corresponding cell lines and compared with that of other subtypes, in order to identify novel serum miRNA biomarkers for early detection and progression of TNBC. A total of 85 paired tumor tissues and sera with an equal number of adjacent normal tissue margins and normal sera from age matched healthy women including tissue and sera samples from 15 benign fibroadenomas were employed for the study. We report for the first time an extremely high prevalence (73.9%) of TNBC in premenopausal women below 35 years of age and a significant altered expression of a panel of three specific oncogenic miRNAs- miR-21, miR-221, miR-210, and three tumor suppressor miRNAs- miR-195, miR-145 and Let-7a in both tissues and corresponding sera of TNBC patients when compared with triple positive breast cancer (TPBC) patients. While miR-21, miR-221 and miR-210 showed significant over-expression, miR-195 and miR-145 were downregulated and well correlated with various clinicopathological and demographic risk factors, tumor grade, clinical stage and hormone receptor status. Interestingly, despite being a known tumor suppressor, Let-7a showed a significant overexpression in TNBCs. It is suggested that this panel of six miRNA signature may serve as a minimally invasive biomarker for an early detection of TNBC patients.