Fine needle aspiration cytology of lymph nodes in breast cancer follow-up is a feasible alternative to watchful waiting and to histology

Background Early detection of loco-regional breast cancer recurrence improves patients’ overall survival, as treatment can be initiated or active treatment can be changed. If a suspicious lymph node is diagnosed during a follow-up exam, surgical excision is often performed. The aim of this study was to evaluate the diagnostic performance of the minor invasive ultrasound-guided fine-needle aspiration cytology (FNAC) in sonomorphologically suspicious lymph nodes in breast cancer follow-up. Methods Between April 2010 and November 2012, we performed ultrasound-guided FNAC in 38 sonographically suspicious lymph nodes of 37 breast cancer follow-up patients. Cytological specimens were evaluated if the sample material was sufficient for diagnosis and if they contained cancer cells. Patients with negative cytology were followed up clinically and sonographically. To evaluate the diagnostic performance we calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for physical examination, the different sonomorphological malignancy criteria and FNAC. Results In 36/38 (94.7 %) lymph nodes, the pathologist had enough material to establish a final diagnosis; in 2/38 (5.3 %) lymph nodes, the probe material was non-evaluable during cytology, these 2 were excluded from further statistical evaluation. Cytology revealed malignancy in 21 lymph nodes and showed no evidence for malignancy in 15 lymph nodes. There was no evidence for malignant disease in follow-up exams in the 15 cytologically benign lymph nodes with an average follow-up time of 3 years. The diagnostic performances of physical examination and FNAC were: Sensitivity 52/100 %, specificity 88/100 %, PPV 85/100 %, NPV 60/100 %, respectively. Conclusions Our preliminary results show that FNAC is a safe and fast diagnostic approach for the evaluation of suspicious lymph nodes in the follow-up of patients with breast cancer and, thus, together with follow-up represents a feasible alternative to surgery

Differentiation of ductal carcinoma in situ versus fibrocystic changes by magnetic resonance imaging: are there pathognomonic imaging features?

Background In breast magnetic resonance imaging (MRI), the diagnosis of ductal carcinoma in situ (DCIS) remains controversial; the most challenging cause of false-positive DCIS diagnosis is fibrocystic changes (FC). Purpose To search for typical and pathognomonic patterns of DCIS and FC using a standard clinical MRI protocol. Material and Methods Consecutive patients scheduled for breast MRI (standardized protocols @ 1.5T: dynamic-T1-GRE before/after Gd-DTPA [0.1 mmol/kg body weight (BW)]; T1-TSE), with subsequent pathological sampling, were investigated. Sixteen MRI descriptors were prospectively assessed by two experienced radiologists in consensus (blinded to pathology) and explored in patients with DCIS (n = 77) or FC (n = 219). Univariate and multivariate statistics were performed to identify the accuracy of descriptors (alone, combined). Furthermore, pathognomonic descriptor-combinations with an accuracy of 100% were explored (χ2 statistics; decision trees). Results Six breast MRI descriptors significantly differentiated DCIS from FC (Pcorrected < 0.05; odds ratio < 7.9). Pathognomonic imaging features were present in 33.8% (n = 100) of all cases allowing the identification of 42.9% of FC (n = 94). Conclusion Pathognomonic patterns of DCIS and FC were frequently observed in a standard clinical MRI protocol. Such imaging patterns could decrease the false-positive rate of breast MRI and hence might help to decrease the number of unnecessary biopsies in this clinically challenging subgroup

Automated Semi-Quantitative Analysis of Breast MRI: Potential Imaging Biomarker for the Prediction of Tissue Response to Neoadjuvant Chemotherapy

Background: We aimed to investigate an automated semi-quantitative software as an imaging biomarker for the prediction of tissue response (TR) after completion of neoadjuvant chemotherapy (NAC). Methods: Breast magnetic resonance imaging (MRI) (1.5T, protocol according to international recommendations) of 67 patients with biopsy-proven invasive breast cancer were examined before and after NAC. After completion of NAC, histopathologic assessments of TR were classified according to the Chevallier grading system (CG1/4: full/non-responder; CG2/C3: partial responder). A commercially available fully automatic software (CADstream) extracted MRI parameters of tumor extension (tumor diameter/volume: TD/TV). Pre- versus post-NAC values were compared (ΔTV and ΔTD). Additionally, the software performed volumetric analyses of vascularization (VAV) after NAC. Accuracy of MRI parameters to predict TR were identified (cross-tabs, ROC, AUC, Kruskal-Wallis). Results: There were 37 (34.3%) CG1, 7 (6.5%) CG2, 53 (49.1%) CG3, and 11 (10.2%) CG4 lesions. The software reached area under the curve levels of 79.5% (CG1/complete response: ΔTD), 68.6% (CG2, CG3/partial response: VAV), and 88.8% to predict TR (CG4/non-response: ΔTV). Conclusion: Semi-quantitative automated analysis of breast MRI data enabled the prediction of tissue response to NAC

Initial clinical results with a fusion prototype for mammography and three-dimensional ultrasound with a standard mammography system and a standard ultrasound probe

Background Combinations *Equal contributors. of different imaging techniques in fusion devices appear to be associated with improvements in diagnostic assessment. Purpose The aim of this study was to test the feasibility of using an automated standard three-dimensional (3D) ultrasound (US) device fused with standard mammography for the first time in breast cancer patients. Material and Methods Digital mammograms and 3D automated US images were obtained in 23 patients with highly suspicious breast lesions. A recently developed fusion machine consisting of an ABVS 3D US transducer from an Acuson S2000 machine and a conventional Mammomat Inspiration device (both Siemens Healthcare GmbH, Erlangen, Germany) were used for the purpose. The feasibility of the examinations, imaging coverage, and patients' experience of the procedure were examined. Results In 15 out of 19 patients, the region of interest (ROI) with the tumor marked in the mammogram was visible on US. The examination was experienced positively by the patients, with no unexpected pain or injury. The examination was time-saving and well tolerated. Conclusion In conclusion, we have shown initial clinical feasibility of an US/radiography fusion prototype with good localization and evaluation of the ROIs. The combined examination was well tolerated. The simultaneous evaluation with mammography and US imaging may be able to improve detection and reduce examiner-related variability

Circulating Micro-RNAs as Potential Blood-Based Markers for Early Stage Breast Cancer Detection

INTRODUCTION: MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls. METHODS: We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718). RESULTS: Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202. CONCLUSIONS: MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use

HLA-G and HLA-F protein isoform expression in breast cancer patients receiving neoadjuvant treatment

The immunosuppressive human leukocyte antigens HLA-G and HLA-F are expressed on trophoblast and malignant cells. Four membrane-bound and three soluble HLA-G protein isoforms have been described, which have different immunosuppressive potentials. HLA-F has three transcript variants, resulting in three different protein isoforms. The aim of this study was to evaluate the prognostic and predictive value of HLA-G and HLA-F protein isoform expression patterns in patients with breast cancer. Core biopsies were taken at diagnosis in patients with HER2+ (n = 28), luminal B-like (n = 49) and triple-negative (n = 38) breast cancers who received neoadjuvant chemotherapy. Expression levels of HLA-F and -G were correlated with the pathological complete response (pCR). Protein expression was determined by Western blot analysis, using two antibodies for each HLA, specific for different isoforms. The protein expression of HLA isoforms did not significantly differ between breast cancer subtypes. However, some initial indications were found for an association between the soluble HLA-G6 protein isoform and pCR in HER2+ breast cancer. The study provides preliminary evidence for the evaluation of HLA-G isoform expression, in particular HLA-G6, as a possible new marker for pCR in HER2+ breast cancer

Variable Expression of the Disialoganglioside GD2 in Breast Cancer Molecular Subtypes

Simple Summary GD2 is an antigen that is tumor-specific and can be used as a target for specific immunotherapies. Since the knowledge about GD2 in breast cancer is limited, we analyzed the frequency of GD2 expression in breast cancer using two different staining methods and the impact of GD2 expression on the survival of breast cancer patients. GD2 expression was found in more than 50% of breast cancer cases, with the highest frequency in hormone receptor-positive tumors. GD2 expression was not significantly associated with patient outcome. Unlike previous studies with smaller sample sizes that lacked correlation with clinical data, this study includes a larger cohort and associations with survival data and shows that GD2 is expressed on human breast cancer cells, providing a potential target for immunotherapies (e.g., anti-GD2 antibodies or GD2 CAR T cells), that are currently undergoing clinical testing. Abstract The disialoganglioside GD2 is a tumor-associated antigen that may allow for the application of targeted immunotherapies (anti-GD2 antibodies, GD2 CAR T cells) in patients with neuroblastoma and other solid tumors. We retrospectively investigated GD2 expression in a breast cancer cohort, using immunohistochemistry (IHC) and immunofluorescence (IF) on tissue microarrays (TMAs), and its impact on survival. GD2 expression on IHC (n = 568) and IF (n = 503) was investigated in relation to subtypes and patient outcome. Overall, 50.2% of the 568 IHC-assessed samples and 69.8% of the 503 IF-assessed samples were GD2-positive. The highest proportion of GD2-positive tumors was observed in luminal tumors. Significantly fewer GD2-positive cases were detected in triple-negative breast cancer (TNBC) compared with other subtypes. The proportion of GD2-expressing tumors were significantly lower in HER2-positive breast cancer in comparison with luminal tumors on IF staining (but not IHC). GD2 expression of IHC or IF was not significantly associated with disease-free or overall survival, in either the overall cohort or in individual subtypes. However, GD2 expression can be seen in more than 50% of breast cancer cases, with the highest frequency in hormone receptor-positive tumors. With this high expression frequency, patients with GD2-positive advanced breast cancer of all subtypes may benefit from GD2-targeting immunotherapies, which are currently subject to clinical testing

Assessment of the additional clinical potential of X-ray dark-field imaging for breast cancer in a preclinical setup

Background: Mammography can identify calcifications up to 50–100 μm in size as a surrogate parameter for breast cancer or ductal carcinoma in situ (DCIS). Microcalcifications measuring <50 µm are also associated with breast cancer or DCIS and are frequently not detected on mammography, although they can be detected with dark-field imaging. This study examined whether additional breast examination using X-ray dark-field imaging can increase the detection rate of calcifications. Advances in knowledge:  (1) evaluation of additional modality of breast imaging;  (2) specific evaluation of breast calcifications. Implications for patient care: the addition of X-ray dark-field imaging to conventional mammography could detect additional calcifications. Methods: Talbot–Lau X-ray phase–contrast imaging and X-ray dark-field imaging were used to acquire images of breast specimens. The radiation dosage with the technique is comparable with conventional mammography. Three X-ray gratings with periods of 5–10 µm between the X-ray tube and the flat-panel detector provide three different images in a single sequence: the conventional attenuation image, differential phase image, and dark-field image. The images were read by radiologists. Radiological findings were marked and examined pathologically. The results were described in a descriptive manner. Results: A total of 81 breast specimens were investigated with the two methods; 199 significant structures were processed pathologically, consisting of 123 benign and 76 malignant lesions (DCIS or invasive breast cancer). X-ray dark-field imaging identified 15 additional histologically confirmed carcinoma lesions that were visible but not declared suspicious on digital mammography alone. Another four malignant lesions that were not visible on mammography were exclusively detected with X-ray dark-field imaging. Conclusions: Adding X-ray dark-field imaging to digital mammography increases the detection rate for breast cancer and DCIS associated lesions with micrometer-sized calcifications. The use of X-ray dark-field imaging may be able to provide more accurate and detailed radiological classification of suspicious breast lesions. Adding X-ray dark-field imaging to mammography may be able to increase the detection rate and improve preoperative planning in deciding between mastectomy or breast-conserving therapy, particularly in patients with invasive lobular breast cancer

Characterizing mammographic images by using generic texture features

Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy

TILGen: A Program to Investigate Immune Targets in Breast Cancer Patients - First Results on the Influence of Tumor-Infiltrating Lymphocytes

Background: Despite advancements in the treatment of primary and metastatic breast cancer, many patients lack a durable response to these treatments. Patients with triple-negative breast cancer (TNBC) and human epidermal growth factor receptor 2(HER2)-positive breast cancer who do not have a pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) have a very poor prognosis. Tumor-infiltrating lymphocytes (TILs) have been identified as a predictive marker for pCR after NACT in TNBC and HER2-positive breast cancer. These patient populations could also be suitable for novel treatment strategies including neoepitope-based therapies. This work analyses the effect of TILs on the pCR in neoadjuvantly treated patients in the TILGen study and presents the procedures aimed at establishing neoepitope-based therapies in this study. Methods: Neoadjuvantly treated HER2-positive and TNBC patients were eligible for the presented analysis concerning the association between TILs and pCR. A total of 146 patients could be identified within the TILGen study. TILs were evaluated as percentage of stromal tumor tissue in core biopsies at primary diagnosis. The phenotype ‘lymphocyte-predominant breast cancer' (LPBC) was associated with pCR by logistic regression adjusted for estrogen receptor status, progesterone receptor status, HER2 status, age at diagnosis, and grading. Results: LPBC was seen in 24 (16.4%) patients. In this patient group, 66.7% achieved a pCR, while the pCR rate was 32.8% in patients with a low TIL count. The adjusted odds ratio was 6.60 (95% confidence interval 2.02-21.56; p < 0.01). Conclusion: TILs are a strong predictor of pCR in TNBC and HER2-positive breast cancer patients. Implications for the use of this information including the effect on prognosis might help to identify patients most likely to benefit from a neoepitope-based therapy approach