[Non-metastatic triple-negative breast cancer in 2016: Definitions and management]

A case report and literature review on a rare subtype of triple-negative breast cancer in children

BACKGROUND

Triple-negative breast cancer (TNBC) is a type of breast tumor with a poor prognosis because it lacks or expresses low levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2). TNBC is more common in middle-aged and older women, and cases of TNBC in children are rarely reported. This is the only case of childhood SBC in our hospital in more than 70 years, and the disease is extremely rare internationally. We analyzed and studied the disease and TNBC from both clinical and pathological aspects and found that SBC is very different from TNBC.

CASE PRESENTATION

We report a case of secretory breast cancer (SBC), a subtype of TNBC, in an 8-year-old girl from our institution. The child presented with a single mass in the left breast only, with no skin rupture and no enlargement of the surrounding lymph nodes. The child underwent two surgeries and was followed up for one year with a good prognosis.

CONCLUSIONS

SBC is highly prevalent among the multiple pathological types of pediatric breast cancer. Almost all pediatric SBC patients are characterized by the ETV6-NTRK3 fusion gene, which has a good prognosis and a 10-year survival rate of more than 90% when compared with other TNBC subtypes. According to the patient, we performed local mass resection and a postoperative pathological diagnosis of SBC (a subtype of BL-TNBC). The TNBC case had a good prognosis and differed from basal TNBC in several aspects, including clinical presentation, treatment, and prognosis. It is necessary to exclude SBC from BL-type TNBC, enhance understanding of the disease, and individualize the treatment plan, so as to avoid medical errors.

Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a rare cancer, characterized by high metastatic potential and poor prognosis, and has limited treatment options. The current standard of care in nonmetastatic settings is neoadjuvant chemotherapy (NACT), but treatment efficacy varies substantially across patients. This heterogeneity is still poorly understood, partly due to the paucity of curated TNBC data. Here we investigate the use of machine learning (ML) leveraging whole-slide images and clinical information to predict, at diagnosis, the histological response to NACT for early TNBC women patients. To overcome the biases of small-scale studies while respecting data privacy, we conducted a multicentric TNBC study using federated learning, in which patient data remain secured behind hospitals' firewalls. We show that local ML models relying on whole-slide images can predict response to NACT but that collaborative training of ML models further improves performance, on par with the best current approaches in which ML models are trained using time-consuming expert annotations. Our ML model is interpretable and is sensitive to specific histological patterns. This proof of concept study, in which federated learning is applied to real-world datasets, paves the way for future biomarker discovery using unprecedentedly large datasets.

Metastatic Triple Negative Breast Cancer: The New Era of Thinking

The heterogeneity of triple negative breast cancer (TNBC) is reflected in a bizarre response to therapy. Although it is chemotherapy sensitive, the failure is the usual pathway either in local or distance status. With progression in Gene Expression Profile (GEP) and other molecular techniques, TNBC is divided into sub-types with unique pathways. In the current review, we are trying to highlight based on the molecular classification of TNBC and the management based on every type.

Phase II study of adjuvant docetaxel and carboplatin with/without doxorubicin and cyclophosphamide in triple negative breast cancer: a randomised controlled clinical trial

Aim of the study

The aim of this trial was to compare overall survival (OS), disease-free survival (DFS), and toxicity of two adjuvant regimens in triple negative patients with Iranian ethnicity.

Material and methods

In a phase II trial, patients with previously untreated triple negative breaststroke cancer were randomly assigned by using docetaxel 70 mg/m² and carboplatin AUC = 7 every three weeks with granulocyte colony-stimulating factor for sin courses (arm A) or doxorubicin hydrochloride 60 mg/m² and cyclophosphamide 600 mg/m² every three weeks with G-CSF for four courses followed by docetaxel 70 mg/m² and carboplatin AUC = 7 every three weeks with G-CSF for four courses (arm B).

Results

A total of 119 patients were randomly enrolled in our study (60 patients in Arm A and 59 patients in Arm B) between 2011 and 2016. The mean follow-up was 40 months at the time of treatment analysis. The 2-year and 5-year DFS rates for Arm A were 92.7% vs. 85% and for Arm B were 82.6% vs. 64.4%. The 2-year and 5-year OS rates for Arm A were 96.5% vs. 91.7% and for Arm B were 90.5% vs. 81.3%. There was a significant correlation for DFS and OS in the two arms. There was no significant difference between adverse events with the two regimens.

Conclusions

In our research, less progression was found with Arm A as compared to Arm B. Adding of anthracyclines such as doxorubicin hydrochloride did not increase OS and DFS in triple negative breast cancer (TNBC) patients.