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Background Since humoral hypercalcemia of malignancy (HHM) in breast cancer patients without bone metastasis is rare, the clinical features of this condition are not fully understood. Case presentation During the recent 12 years, 3602 patients were diagnosed with breast cancer in our institution, and only three patients developed HHM without bone metastasis. They were all recurrent breast cancer patients with visceral metastases including the lung and the liver. It took no more than 2 months since symptomatic onset to hospitalization because of hypercalcemia. The maximum serum calcium concentrations were 15.0 mg/dL or higher. All patients had symptoms related to hypercalcemia. Treatment of hypercalcemia including hydration, calcitonin, bisphosphonate, and diuretics was initially effective in the three patients. However, two of three cases were eventually fatal because of unsuccessful treatment of breast cancer. Conclusions The common features of HHM without bone metastasis in breast cancer patients include acute onset, severe symptomatic hypercalcemia, and presence of visceral metastasis. Treatment of hypercalcemia decreased serum calcium level in a short period, while successful treatment of breast cancer was essential for a long-term management of HHM. This report provides a consideration to help elucidate the pathophysiology and medical care of breast cancer patients with HHM without bone metastasis.

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

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.

Highlights • Whole exome sequencing can assess HRD status as well as the SNP array in breast cancer. • HRD scores were higher in tumors with the germline HRR gene mutations than in those with the somatic HRR gene mutations and the wild-type HRR genes, between which no difference was found. • Acquisition of LOH induced HRD status even in tumor with the somatic HRR gene mutations. • In the luminal subset, HRD-high tumors were associated with a favorable response to neoadjuvant paclitaxel followed by 5-fluorouracil/epirubicin/cyclophosphamide., Recent studies demonstrated that homologous repair deficiency (HRD) score is a useful marker for response to poly (ADP-ribose) polymerase inhibitors or platinum-based chemotherapy. We determined HRD scores and elucidated the clinicopathologic characteristics of HRD-high tumors and their response to non-platinum-based chemotherapy. Primary breast cancer patients (n = 120) were pre-operatively treated with paclitaxel followed by 5-fluorouracil/epirubicin/cyclophosphamide (P-FEC). Germline and somatic homologous recombination related gene mutations (gHRRm and sHRRm, respectively) and HRD scores were analyzed using whole exome sequencing (WES) in tumor tissues obtained before chemotherapy. Of 120 tumors, 30 were determined to be HRD-high tumors, significantly associated with high Ki-67 (P = 0.014), ER negativity (P = 0.007), and PR negativity (P = 0.021). Triple-negative cancers showed significantly higher HRD scores than the luminal, luminal-HER2, and HER2 subtypes (P = 0.023, 0.016, and 0.033, respectively). HRD scores were significantly higher in tumors with gHRRm than in those with sHRRm (P = 0.002) or wild-type HRR genes (P = 1.44e-4), but no significant difference was found in HRD scores between tumors with sHRRm and wild-type HRR genes (P = 0.206). HRD-high tumors had significantly (P = 0.003) higher pCR rates and higher near-pCR rates (P = 0.049) compared with those of the HRD-low tumors in all tumors and the luminal subtype, respectively. HRD-high tumors were associated with aggressive phenotypes and gHRRm, but not sHRRm. Our findings suggested that HRD scores might be useful in predicting response to P-FEC in the luminal subtype.

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.

Fusion genes make for one of the mechanisms of tumorigenesis. The identification of fusion genes by RNA-Seq has attracted attention. Various methods for detecting fusion genes have been proposed, but their accuracy is not sufficient. One of the causes of this problem is the relatively short reading length in RNA-Seq data. Therefore, before mapping RNA-Seq data, we proposed a method, which is based on shifted short-read clustering (SSC), to identify shifted reads of the same origin and extend them as representative sequences. As a result, we assumed that the percentage of uniquely mapped reads would be increased, and the detection rates of the fusion genes could be improved. To verify these hypotheses, we applied the SSC method to RNA-Seq data from three cell lines (BT-474, MCF-7, and SKBR-3). When only one base was shifted, the average read lengths of BT-474, MCF-7, and SKBR-3 were extended from 201 to 223 bases (111%), 201 to 214 bases (106%), and 201 to 213 bases (106%), respectively. Furthermore, the effectiveness of the SSC method is demonstrated by comparing the performances of a fusion gene detection tool's results, STAR-Fusion, with and without the SSC method of the reads. The percentage of uniquely mapped reads of BT-474, MCF-7, and SKBR-3 were improved from 88% to 93%, 88% to 94%, and 92% to 95%, respectively. Finally, the fusion gene detection rates of BT-474, MCF-7, and SKBR-3 were increased from 48% to 57%, 49% to 53%, and 50% to 53% respectively. The SSC method is considered to be an effective method not only for improving the percentage of uniquely mapped reads but also for fusion gene detection.

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.

Gene expression profiling has been increasingly used in clinical practice. Integration of expression data across multiple experiments provides better insight into the heterogeneity of the biology being examined. A problem of the data integration, an experimental batch from platform or laboratory sources, remains a barrier to systematically analyzing data across different datasets. Several methods (such as, ComBat) have been proposed to remove batch effects. However, these methods often make assumptions about ideal distribution of the underlying data. Difficulties might be expected when comparing datasets that have fundamentally different (dataset-dependent) distributions. For example, clinical datasets are often collected from patient samples with various disease stages or conditions. Therefore, we have compared several mathematical transformations across many datasets, including the nonparametric Z scaling transformation method (NPZ) we have proposed for clinical use. We selected 2,813 patients with available information on estrogen receptor (ER) status or human epidermal growth factor receptor 2 (HER2) status from 24 Affymetrix HG-U133 (GPL96) or Affymetrix HG-U133 plus 2.0 (GPL570) datasets in the Gene Expression Omnibus database. The microarray expression data were processed with one of the four following methods: Raw (background correction and log transformation only), Microarray Suite 5.0 (MAS5), frozen robust multiarray analysis (fRMA), and radius minimax (RMX). The normalized data were sequentially transformed by using one of the following five methods: untransformed (without transformation), single-array-based transformations (RANK, Z, NPZ, or YuGene). Finally, we compared the ER and HER2 statuses assessed by immunohistochemical (IHC) staining with mRNA expression. We found that single-array-based transformation in addition to normalization improved the concordance rates of the IHC staining. We demonstrated the influence of transformation by using breast cancer samples and showed that adding single-array-based transformations to microarray expression data resulted in stronger correlations with IHC staining.

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.