The Prognostic Impact of Synchronous Ipsilateral Multiple Breast Cancer: Survival Outcomes according to the Eighth American Joint Committee on Cancer Staging and Molecular Subtype

Deep learning-based system for automatic prediction of triple-negative breast cancer from ultrasound images

To develop a deep-learning system for the automatic identification of triple-negative breast cancer (TNBC) solely from ultrasound images. A total of 145 patients and 831 images were retrospectively enrolled at Peking Union College Hospital from April 2018 to March 2019. Ultrasound images and clinical information were collected accordingly. Molecular subtypes were determined from immunohistochemical (IHC) results. A CNN with VGG-based architecture was then used to predict TNBC. The model's performance was evaluated using randomized k-fold stratified cross-validation. A t-SNE analysis and saliency maps were used for model visualization. TNBC was identified in 16 of 145 (11.03%) patients. One hundred fifteen (80%) patients, 15 (10%) patients, and 15 (10%) patients formed the train, validation, and test set respectively. The deep learning system exhibits good efficacy, with an AUC of 0.86 (95% CI: 0.64, 0.95), an accuracy of 85%, a sensitivity of 86%, a specificity of 86%, and an F1-score of 0.74. In addition, the internal representation features learned by the model showed clear differentiation across molecular subtype groups. Such a deep learning system can automatically predict triple-negative breast cancer preoperatively and accurately. It may help to get to more precise and comprehensive management.

Multicentre prospective cohort study of unmet supportive care needs among patients with breast cancer throughout their cancer treatment trajectory in Penang: a PenBCNeeds Study protocol

INTRODUCTION

Proper assessment of unmet supportive care needs of patients with breast cancer and its influencing factors at different treatment intervals will improve the rehabilitation of patients with breast cancer. Therefore, this study aims to determine the prevalence of unmet supportive care needs, changes of needs over time and associated factors during the treatment period.

METHODS AND ANALYSIS

This multicentre, prospective cohort study will be conducted in three governmental hospitals and one tertiary cancer institute in Penang, Malaysia. Adult women diagnosed with primary or recurrent tumour, node, metastases stage I-IV breast cancer based on pathological biopsy will be eligible for this study. At least 281 samples are required for this study. Participants will undergo follow-up at three time intervals: T1 at breast cancer diagnosis; T2 at 3 months after diagnosis and T3 at 6 months after diagnosis. Patients will complete a set of questionnaires at each time. The primary outcome of this study includes the changes in supportive care needs over three time points, followed by the secondary outcome examining patients' characteristics, coping behaviours and positive psychological components as they affect changes in unmet supportive care needs over time.

ETHICS AND DISSEMINATION

The study has received ethics approval from the Medical Research and Ethics Committee, Ministry of Health Malaysia (NMRR-19-268-45809 IIR) and the Human Research Ethics Committee of Universiti Sains Malaysia (USM/JEPeM/17100443). The results of the prospective study will be submitted for publication in a peer-reviewed journal.

Synchronous Multiple Breast Cancers-Do We Need to Reshape Staging?

Background and Objectives: Current recommendations and treatment regimens in breast cancer are a reflection of its heterogeneity on multiple levels including histological subtypes, grading, molecular profiling, and numerous prognostic indices. Although based on extensive research, current guidelines are not explicit in the case of surgical specimens showing various degrees of mismatch between different parts of the same tumor and even more so between multicentric lesions. Synchronous breast cancer is the ideal prototype for studying inter- and intra-tumoral heterogeneity, therefore we envisaged that a study on patients with multicentric and multifocal lesions could contribute to the reshaping of the staging, prognosis, and treatment of breast malignancies. Material and Methods: A prospective observational study was conducted between January 2013 and May 2017 on 235 patients diagnosed with breast cancer (BC) and surgically treated at Emergency University Hospital, Bucharest. Thirty-seven patients had multiple breast tumors and were eligible for assessment of the heterogeneity of their lesions. Results: 6 were multicentric and 31 multifocal. The number of foci varied from 2 to 11. We encountered numerous mismatches between the index and the secondary tumors, as follows: 3 cases (8.1%) with histopathological mismatch, 13 (35.1%) with different grades of differentiation, 11 (29.8%) with ER (Estrogen Receptors) status mismatch, 12 (32.4%) with PR (Progesterone Receptors) status mismatch, 8 (21.6%) with molecular phenotype mismatch, and 17 (45.9%) cases with variable Ki-67. After careful analysis of index and secondary tumors, apart from the mismatches reported above, we discovered that the secondary tumors were actually dominant in 5 cases (13.5%), and therefore at least those cases had to be reclassified/restaged, as the supplementary data commanded changes in the therapeutic decision. Conclusions: For synchronous breast tumors, the current Tumor-Node-Metastasis (TNM) staging system ignores not only the histopathological and immunohistochemical characteristics of the secondary foci, but also their size. When secondary lesions are more aggressive or their cumulative mass is significantly bigger than that of the index tumor, the treatment plan should be adapted accordingly. We believe that information obtained from examining secondary foci in synchronous breast cancer and assessment of the cumulative tumoral mass should be reflected in the final staging and definitive treatment. The clinical benefit of staging the patients based on the most aggressive tumor and the cumulative tumoral burden rather than according to the biggest single tumor, will avoid under-treatment in cases with multifocal/multicentric BC displaying intertumoral mismatch.

The subgross morphology of breast carcinomas: a single-institution series of 2033 consecutive cases documented in large-format histology slides

A large-format histology technique represents the most convenient method for documenting and assessing the subgross morphological prognostic parameters of breast cancer (i.e., the distribution of the tumor's invasive and in situ components, disease extent, and tumor size), especially when used in conjunction with systematic radiological-pathological correlation. Here we report a consecutive series of 2033 breast carcinomas operated on in Dalarna, Sweden, with a particular focus on these subgross parameters. We separately analyzed the distributions of the in situ and invasive components of the tumors and then combined these into an aggregate pattern when both components were present. We found that 40% of breast carcinomas had a simple (unifocal) subgross morphology, while 60% had a complex morphology presenting with multifocal or diffuse components. Extensive tumors (occupying a total volume of breast tissue with the greatest dimension being ≥ 40 mm) were more common in complex cases, occurring in 66% of multifocal cases and 88% of diffuse cases, compared with only 5% of unifocal cases. Compared with luminal A-like tumors, HER2-expressing tumors exhibited a significantly larger extent. Triple-negative and basal-like carcinomas tended to have a larger tumor size (based on the largest dimension of the largest invasive focus). In this report, we discuss the prognostic impact of these parameters and the necessity of their correct assessment in the diagnostic routine.

Molecular mechanism of triple-negative breast cancer-associated BRCA1 and the identification of signaling pathways

BRAC1 has multiple important interactions with triple-negative breast cancer, the specific molecular characteristics of this interaction, however, have not yet been completely elucidated. By examining cell signaling pathways, important information for comprehending the potential mechanisms of this cancer may become known. The aim of the present study was to identify the effects of BRAC1 and to find the signaling pathway(s) involved in the pathogenic mechanism of triple-negative breast cancer. In this study, GSE27447 microarray data were obtained from the Gene Expression Omnibus (GEO) database of the National Center for Biotechnology Information, and differentially expressed genes (DEGs) from GSE27447 were distinguished by Significant Analysis of Microarray. Gene ontology (GO) analysis was carried out on 132 upregulated and 198 downregulated genes with DAVID. The signaling was forecast by the Kyoto Encyclopedia of Genes and Genomes (KEGG). Transcription factors were recognized by TFatS. The BRAC1 relevant protein-protein interaction networks (PPI) were fixed by STRING and visualized by CytoScape. Overall, the upregulated DEGs, which included CR2, IGHM, PRKCB, CARD11, PLCG2, CD79A, IGKC and CD27, were primarily enriched in the terms associated with immune responses, and the downregulated DEGs, which included STARD3, ALDH8A1, SRD5A3, CACNA1H, UGT2B4, SDR16C5 and MED1, were primarily enriched in the hormone metabolic process. In addition, 13 pathways, such as the B-cell receptor-signaling pathway, the hormone synthesis signaling pathway and the oxytocin-signaling pathway, were chosen. MYC, SP1 and CTNNB1 were determined to be enriched in triple-negative breast cancer. A total of 8 genes were identified to be downregulated in the BRAC1-related PPI network. The results of the present study show a fresh angle on the molecular mechanism of triple-negative breast cancer and indicate a possible target for its treatment.