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HER2 amplification is seen in 20–25% of primary breast cancer cases, and HER2 detection is performed routinely in primary operable, as well as metastatic breast cancer patients. Currently, HER2 is the only gene of which amplification is routinely assayed by fluorescent in situ hybridization (FISH) and/or immunohistochemistry (IHC). However, histochemical assay (FISH/IHC) of multiple target genes is laborious and time-consuming, and simultaneous amplification by microarray is preferred. OncoScan™ is a microarray-based assay capable of whole-genome copy number analysis using DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissues. In the current study, we aimed to investigate the impact of tumor cellularity on the accuracy of OncoScan™ in the determination of HER2 amplification. Our results demonstrated that HER2 amplification by OncoScan™ is accurate, and has a high concordance rate of 93.3% with FISH. However, the concordance rate is poor (66.7%) in cases with a tumor cellularity

Humoral immunity plays a substantial role in the suppression of breast cancer. We have revealed that a high serum concentration of anti‐HER2 autoantibody (HER2‐AAb) is associated with favorable outcomes in patients with invasive breast cancer. Thus, we aimed to clarify the association between high serum concentration of HER2‐AAb and humoral immune response in the tumor microenvironment. Out of 500 consecutive patients with invasive breast cancer, we selected those whose HER2‐AAb values were high (n = 33) or low (n = 20) based on the distribution of HER2‐AAb values of 100 healthy individuals. Tumor and regional lymph node formalin‐fixed paraffin‐embedded samples prepared from the surgical specimens were subjected to immunohistochemistry. We confirmed that the recurrence‐free survival of the high HER2‐AAb group was significantly longer than that of the low HER2‐AAb group (p = 0.015). The numbers of tumor‐infiltrating CD20+ immune cells (ICs) (p, Anti‐HER2 autoantibody in breast cancer patients is positively associated with their outcomes. Enhanced humoral immunity in the tumor microenvironment is associated with autoantibody, providing a rationale for favorable outcomes in such patients.

The aim of our study is to find microRNAs (miRNAs) associated with sentinel lymph node metastasis (SLNM) and to develop a prediction model for SLNM in ER-positive and HER2-negative (ER+/HER2-) breast cancer.In the present study, only ER+/HER2- primary breast cancer was considered. The discovery set for SLNM-associated miRNAs included 10 tumors with and 10 tumors without SLNM. The training and validation sets both included 100 tumors. miRNA expression in tumors was examined comprehensively by miRNA microarray in the discovery set and by droplet digital PCR in the training and validation sets.In the discovery set, miR-98, miR-22, and miR-223 were found to be significantly (P 0.001, fold-change 2.5) associated with SLNM. In the training set, we constructed the prediction model for SLNM using miR-98, tumor size, and lymphovascular invasion (LVI) with high accuracy (AUC, 0.877). The accuracy of this prediction model was confirmed in the validation set (AUC, 0.883), and it outperformed the conventional Memorial Sloan Kettering Cancer Center nomogram. In situ hybridization revealed the localization of miR-98 expression in tumor cells.We developed a prediction model consisting of miR-98, tumor size, and LVI for SLNM with high accuracy in ER+/HER2- breast cancer. This model might help decide the indication for SLN biopsy in this subtype.

ESR1 mutations in breast cancer are one of the mechanisms of resistance to aromatase inhibitors. These mutations are common in metastatic breast cancer; however, these are rare in primary breast cancer. However, these data have been analyzed mainly in formalin-fixed, paraffin-embedded tissue; thus, rare mutations that may be present in primary breast cancer may be overlooked. In this study, we developed a highly sensitive mutation detection method called locked nucleic acid (LNA)-clamp droplet digital PCR (ddPCR) and validated it. The mutation detection sensitivity was substantiated to 0.003%. Then, we used this method to analyze ESR1 mutations in fresh-frozen (FF) tissues of primary breast cancer. cDNA extracted from the FF tissues of 212 patients with primary breast cancers were measured. Twenty-eight ESR1 mutations were found in twenty-seven (12.7%) patients. Sixteen (7.5%) patients had Y537S mutations and twelve (5.7%) had D538G mutations. Two mutations with a variant allele frequency (VAF) of ≥0.1% and twenty-six mutations with a VAF of

The diagnostic accuracy of the multigene panel test (MPT) and OncoScan™ in the determination of HER2 amplification in breast tumors remains controversial. In the present study, HER2 copy number was analyzed using both MPT and OncoScan™ in 45 breast tumors and was compared with that in fluorescent in situ hybridization (FISH) analysis. Tumors with low cellularity were examined using tumor cell enrichment and fluorescence‑activated cell sorting. Both MPT and OncoScan™ exhibited significant correlations with FISH with respect to the determination of HER2 amplification in breast tumors. However, the correlation coefficient was significantly higher for the comparison of MPT and FISH (r=0.770) compared with that between OncoScan™ and FISH (r=0.564). The accuracy of MPT (93.3%) was slightly higher compared with that in OncoScan™ (84.4%) in determining the HER2 status, which was mostly explained by the higher sensitivity of MPT in tumors with low cellularity (83.3 vs. 33.3%), but not in those with high cellularity (81.8 vs. 72.7%). The specificity was 100% for both tests. The MPT exhibited higher sensitivity in the determination of the amplification of other genes, including MYC, fibroblast growth factor receptor 1 and GATA binding protein 3 in tumors with low cellularity compared with that in tumors with high cellularity. OncoScan™ exhibited low sensitivity without tumor cell enrichment. The results suggested that MPT could be a promising method to determine HER2 status in breast tumors and that it could exhibit improved accuracy compared with that in OncoScan™ in tumors with low cellularity.

Background/aim Magnetic resonance imaging (MRI)-guided breast biopsy is a complex and time-consuming procedure. This study aimed to clarify the factors that affect the duration of the procedure. Patients and methods Twenty-eight examinations performed at our institute for 27 lesions detected solely on MRI were analyzed. The correlations between the clinicopathological factors and duration of the procedure were estimated. Results The needle guidance method was the only factor that significantly affected the duration of the MRI-guided vacuum-assisted breast biopsy (VAB) (p=0.012). The use of a computer-aided detection (CAD) system with grid breast compression plates had significantly shorter durations (62±12 min) than the manual calculation of coordinates with pillar-type compression plates (76±13 min). Conclusion This preliminary study showed that the use of a CAD system might shorten the duration of MRI-guided VAB.

Background One-step nucleic acid amplification (OSNA) for cytokeratin 19 messenger RNA is an intraoperative diagnostic procedure for the detection of lymph node metastasis.

Fusion genes are involved in cancer, and their detection using RNA-Seq is insufficient given the relatively short reading length. Therefore, we proposed a shifted short-read clustering (SSC) method, which focuses on overlapping reads from the same loci and extends them as a representative sequence. To verify their usefulness, we applied the SSC method to RNA-Seq data from four types of cell lines (BT-474, MCF-7, SKBR-3, and T-47D). As the slide width of the SSC method increased to one, two, five, or ten bases, the read length was extended from 201 bases to 217 (108%), 234 (116%), 282 (140%), or 317 (158%) bases, respectively. Furthermore, fusion genes were investigated using STAR-Fusion, a fusion gene detection tool, with and without the SSC method. When one base was shifted by the SSC method, the reads mapped to multiple loci decreased from 9.7% to 4.6%, and the sensitivity of the fusion gene was improved from 47% to 54% on average (BT-474: from 48% to 57%, MCF-7: 49% to 53%, SKBR-3: 50% to 57%, and T-47D: 43% to 50%) compared with original data. When the reads are shifted more, the positive predictive value was also improved. The SSC method could be an effective method for fusion gene detection.

AIM: We have previously reported that the serum concentration of anti-HER2 autoantibodies (HER2-AAb) is associated with favorable outcomes in patients with invasive breast cancer (Tabuchi et al., Breast Cancer Res Treat 157:55-63, 2016). This study aimed to investigate the prognostic impact of HER2-AAb by examining the tumor microenvironments for humoral immunity. PATIENTS AND METHODS: From 500 consecutive patients with invasive breast cancer (Ibid.), we selected those whose log-transformed HER2-AAb values were above mean + 2SD (high HER2-AAb group, N = 33) or below mean − 2SD (low HER2-AAb group, N = 20). Tumor formalin-fixed paraffin-embedded (FFPE) samples and regional lymph node FFPE samples prepared from the patients’ surgical specimens were subjected to immunohistochemistry. Tumor-infiltrating immune cells (ICs) localized inside the tumor, in the adjacent stroma, and in the tumor stroma were separately counted. Expression of some proteins in tumor cells (TCs) was evaluated by the percentages of tumor cells showing presence of those proteins. RESULTS: We confirmed in the selected patients that the recurrence-free interval of the high HER2-AAb group was significantly longer than that of the low HER2-AAb group (log-rank P = 0.017; hazard ratio = 0.12). Tumor-infiltrating CD20-positive ICs (intratumoral + adjacent stromal ICs, P < 0.001), IGKC-positive ICs (intratumoral + adjacent stromal ICs, P = 0.023), and CXCL13-positive ICs (total ICs, P = 0.044) were significantly greater in the high HER2-AAb group than in the low HER2-AAb group. CD4-positive ICs in B-cell follicles of the regional lymph nodes were also significantly greater in the high HER2-AAb group than in the low HER2-AAb group (P = 0.026). Tumor-infiltrating PD-L1-positive ICs, CD8-positive ICs, FOXP3-positive ICs, as well as CD8/FOXP3 ratios, were not significantly different between the two groups. The expression of CXCL13, HLA-A/B/C, and PD-L1 in TCs was not significantly different between the two groups. The repertoire of B-cell receptors in ICs was not significantly different between the two groups but was considered to be skewed. HER2 expression and gene amplification and the existence of HER2 missense mutations were similar between the two groups. CONCLUSIONS: Increased HER2-AAb concentration was associated with enhanced humoral immunity in tumor microenvironments. Our findings indicate that a patient subpopulation with enhanced humoral immunity protecting against breast cancer recurrence exists. The recognition site of HER2-AAb may not be located in the HER2 polypeptide, but may be located in modifying factors, such as sugar chains. Citation Format: Masafumi Shimoda, Yasufumi Sato, Yoshiaki Sota, Tomohiro Miyake, Tomonori Tanei, Naofumi Kagara, Yasuto Naoi, Kenzo Shimazu, Seung Jin Kim, Shinzaburo Noguchi. Association of autoantibodies to HER2 with tumor microenvironments for humoral immunity and prognosis in patients with breast cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1604.

The purpose of this study was to evaluate whether the baseline breast MRI findings would be useful for the prediction for pathological complete response (pCR) by breast cancer patients to neoadjuvant chemotherapy. Primary breast cancer patients (stage II-III) preoperatively treated with sequential paclitaxel (12 cycles) and fluorouracil, epirubicin, and cyclophosphamide (4 cycles), followed by surgery were retrospectively enrolled, and 229 patients were eligible. Before chemotherapy, breast MRI studies were performed. Breast tumors were dichotomized into round + oval and irregular types based on MRI morphology. The round + oval tumors showed a significantly higher pCR rate than the irregular tumors (42.0% vs 17.3%; P < 0.001). In addition, PAM50 analysis revealed that basal and HER2-enriched tumors were significantly more prevalent among round + oval than irregular type tumors (P = 0.015). Baseline MRI morphology appears to be a significant predictor for pCR. The higher rate of the basal and HER2-enriched tumors among the round + oval tumors may explain their better chemo-sensitivity.

Background The aim of this study was to construct a novel prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) using immune-related gene expression data. Patients and methods DNA microarray data were used to perform a gene expression analysis of tumor samples obtained before NAC from 117 primary breast cancer patients. The samples were randomly divided into the training (n = 58) and the internal validation (n = 59) sets that were used to construct the prediction model for pCR. The model was further validated using an external validation set consisting of 901 patients treated with NAC from six public datasets. Results The training set was used to construct an immune-related 23-gene signature for NAC (IRSN-23) that is capable of classifying the patients as either genomically predicted responders (Gp-R) or non-responders (Gp-NR). IRSN-23 was first validated using an internal validation set, and the results showed that the pCR rate for Gp-R was significantly higher than that obtained for Gp-NR (38 versus 0%, P = 1.04E-04). The model was then tested using an external validation set, and this analysis showed that the pCR rate for Gp-R was also significantly higher (40 versus 11%, P = 4.98E-23). IRSN-23 predicted pCR regardless of the intrinsic subtypes (PAM50) and chemotherapeutic regimens, and a multivariate analysis showed that IRSN-23 was the most important predictor of pCR (odds ratio = 4.6; 95% confidence interval = 2.7–7.7; P = 8.25E-09). Conclusion The novel prediction model (IRSN-23) constructed with immune-related genes can predict pCR independently of the intrinsic subtypes and chemotherapeutic regimens.