No abstract

This study aimed to compare the antiemetic efficacy and safety of a four-drug combination with those of a standard three-drug combination in Japanese patients with breast cancer treated with anthracycline. We retrospectively analyzed data from Japanese patients with breast cancer, who had received their first cycle of anthracycline and were treated with aprepitant, palonosetron, and dexamethasone with or without olanzapine. This retrospective observational study was performed at Ehime University Hospital using the electronic medical records. Multivariable and propensity score-adjusted analyses were performed to compare the onset of complete response (CR) failure between the groups. One-hundred and thirty patients were included in this study and the four- and three-drug group had 22 and 108 patients, respectively. Similar to multivariable logistic regression analysis, propensity-adjusted logistic regression analysis revealed that the four-drug group was markedly associated with a decreased odds of CR failure in the overall, acute, and delayed phases (odds ratio [OR]: 0.27, 95% confidence interval [CI]: 0.10–0.73; OR: 0.28, 95% CI: 0.10–0.76; and OR: 0.15, 95% CI: 0.04–0.57, respectively). Additionally, treatment-related adverse events were well tolerated in both the groups. These findings suggest that the antiemetic efficacy of the four-drug combination is superior to that of the standard three-drug combination.

Background Metaplastic carcinoma of the breast consists of both invasive ductal carcinoma and metaplastic carcinoma. This rare subtype of cancer has a poor prognosis. The development of metaplastic breast cancer and relationship with BRCA1 are not well known. Here, we report a rare case of germline BRCA1 mutation-positive breast cancer with chondroid metaplasia. Case presentation A 39-year-old Japanese woman with a family history of breast cancer in her mother and ovarian cancer in her maternal grandmother consulted at our hospital with a left breast mass. Needle biopsy for the mass was performed, leading to a diagnosis of invasive breast cancer with chondroid metaplasia. We performed left mastectomy + sentinel lymph node biopsy + tissue expander insertion and replaced with a silicone implant later. Pathological examination revealed that the patient had triple-negative breast cancer. Four courses of doxorubicin+ cyclophosphamide therapy were performed as adjuvant therapy after surgery. We performed genetic counseling and genetic testing, and the results suggested the germline BRCA1 mutation 307 T> A (L63*). She has currently lived without a relapse for 2 years post-surgery. Conclusions There have been only 6 cases of metaplastic breast carcinoma with germline BRCA1 mutations including our case. Patients with BRCA1 mutations may develop basal-like subtypes or M type of triple-negative breast cancer besides metaplastic breast cancers.

Fibroadenomas (FAs) and phyllodes tumors (PTs) are major benign breast tumors, pathologically classified as fibroepithelial tumors. Although the clinical management of PTs differs from FAs, distinction by core needle biopsy diagnoses is still challenging. Here, a combined technique of label-free imaging with multi-photon microscopy and artificial intelligence was applied to detect quantitative signatures that differentiate fibroepithelial lesions. Multi-photon excited autofluorescence and second harmonic generation (SHG) signals were detected in tissue sections. A pixel-wise semantic segmentation method using a deep learning framework was used to separate epithelial and stromal regions automatically. The epithelial to stromal area ratio and the collagen SHG signal strength were investigated for their ability to distinguish fibroepithelial lesions. An image segmentation analysis with a pixel-wise semantic segmentation framework using a deep convolutional neural network showed the accurate separation of epithelial and stromal regions. A further investigation, to determine if scoring the epithelial to stromal area ratio and the SHG signal strength within the stromal area could be a marker for differentiating fibroepithelial tumors, showed accurate classification. Therefore, molecular and morphological changes, detected through the assistance of computational and label-free multi-photon imaging techniques, enable us to propose quantitative signatures for epithelial and stromal alterations in breast tissues.