Regression of Triple-Negative Breast Cancer in a Patient-Derived Xenograft Mouse Model by Monoclonal Antibodies against IL-12 p40 Monomer

Although some therapies are available for regular breast cancers, there are very few options for triple-negative breast cancer (TNBC). Here, we demonstrated that serum level of IL-12p40 monomer (p40) was much higher in breast cancer patients than healthy controls. On the other hand, levels of IL-12, IL-23 and p40 homodimer (p402) were lower in serum of breast cancer patients as compared to healthy controls. Similarly, human TNBC cells produced greater level of p40 than p402. The level of p40 was also larger than p402 in serum of a patient-derived xenograft (PDX) mouse model. Accordingly, neutralization of p40 by p40 mAb induced death of human TNBC cells and tumor shrinkage in PDX mice. While investigating the mechanism, we found that neutralization of p40 led to upregulation of human CD4+IFNγ+ and CD8+IFNγ+ T cell populations, thereby increasing the level of human IFNγ and decreasing the level of human IL-10 in PDX mice. Finally, we demonstrated the infiltration of human cytotoxic T cells, switching of tumor-associated macrophage M2 (TAM2) to TAM1 and suppression of transforming growth factor β (TGFβ) in tumor tissues of p40 mAb-treated PDX mice. Our studies identify a possible new immunotherapy for TNBC in which p40 mAb inhibits tumor growth in PDX mice.

MuTILs: explainable, multiresolution computational scoring of Tumor-Infiltrating Lymphocytes in breast carcinomas using clinical guidelines

Tumor-Infiltrating Lymphocytes (TILs) have strong prognostic and predictive value in breast cancer, but their visual assessment is subjective. We present MuTILs, a convolutional neural network architecture specifically optimized for the assessment of TILs in whole-slide image scans in accordance with clinical scoring recommendations. MuTILs is a concept bottleneck model, designed to be explainable and to encourage sensible predictions at multiple resolutions. Our computational scores match visual scores and have independent prognostic value in invasive breast cancers from the TCGA dataset.

Path to Clonal Theranostics in Luminal Breast Cancers

Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString®) and CDx (Foundation One®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.

Diagnostic performance of superb microvascular imaging combined with shear-wave elastography in distinguishing invasive ductal carcinoma molecular subtypes

IntroductionTo explore the diagnostic value of combining superb microvascular imaging (SMI), shear-wave elastography (SWE), and Breast Imaging Reporting and Data System (BI-RADS) to distinguish different molecular subtypes of invasive ductal carcinoma (IDC).Material and methodsA total of 239 surgically confirmed IDC masses in 201 patients underwent conventional ultrasound, SMI, and SWE examination, the information such as echo pattern, posterior features, margins, SMI pixels, and hardness of the masses was recorded. According to the St. Gallen standard, breast masses were classified as Luminal A, Luminal B, HER2 overexpression, and triple-negative subtype. We further explored the differences between different molecular subtypes of IDC.ResultsLuminal A subtype had the following characteristics: low histologic grade, posterior acoustic shadowing (p= 0.019), spiculated margins (p<0.001) , and relatively soft. Luminal B subtype was characterized by low histological grade (p <0.0001), posterior acoustic shadowing or indifference, and indistinct margins. HER2 overexpression breast cancers were characterized by high histological grade, enhanced posterior acoustics or indifference, calcifications (p= 0.005), spiculated or indistinct margins, vascularity (p=0.005), and relative stiffness. Triple-negative breast cancers had the characteristics of high histological grade, posterior echogenic enhancement, lack of calcifications, circumscribed or microlobulated margins, low blood flow signals, and stiff tissue (p=0.013).ConclusionsOur study demonstrated the significant differences and trends among the IDC four subtypes by the combined application of SMI, SWE, and BI-RADS lexicon, which are of great significance for early diagnosis, selection of treatment methods, and evaluation of prognosis of IDC.

The Research Progress of Trastuzumab-Induced Cardiotoxicity in HER-2-Positive Breast Cancer Treatment

In recent years, the incidence of breast cancer has been increasing on an annual basis. Human epidermal growth factor receptor-2 (HER-2) is overexpressed in 15-20% human breast cancers, which is associated with poor prognosis and a high recurrence rate. Trastuzumab is the first humanized monoclonal antibody against HER-2. The most significant adverse effect of trastuzumab is cardiotoxicity, which has become an important factor in limiting the safe use of the drug. Unfortunately, the mechanism causing this cardiotoxicity is still not completely understood, and the use of preventive interventions remains controversial. This article focuses on trastuzumab-induced cardiotoxicity, reviewing the clinical application, potential cardiotoxicity, mechanism and discussing the potential interventions through summarizing related researches over the past tens of years.

Pattern of Time-to-Surgery in Patients With Breast Cancer at Different Stages of the COVID-19 Pandemic

BackgroundThe management of cancer surgeries is under unprecedented challenges during the COVID-19 pandemic, and the breast cancer patients may face a time-delay in the treatment. This retrospective study aimed to present the pattern of time-to-surgery (TTS) and analyze the features of breast cancer patients under the different stages of the COVID-19 pandemic.MethodsPatients who received surgeries for breast cancers at West China Hospital between February 15, 2020 and April 30, 2020 (the outbreak and post-peak stages), and between March 10, 2021 and May 25, 2021 (the normalization stage) were included. TTS was calculated as the time interval between the pathological diagnosis and surgical treatment of breast cancer patients. And the pandemic was divided into three stages based on the time when the patients were pathologically diagnosed and the severity of pandemic at that time point. TTS, demographic and clinicopathological features were collected from medical records.ResultsA total of 367 patients were included. As for demographic features, it demonstrated statistically significant differences in insurance type (p&lt;0.001) and regular screening (p&lt;0.001), as well as age (p=0.013) and menstrual status (p=0.004). As for clinicopathological features, axillary involvement (p=0.019) was a factor that differed among three stages. The overall TTS was 23.56 ± 21.39 days. TTS for patients who were diagnosed during the outbreak of COVID-19 were longer than those diagnosed during pandemic post-peak and normalization stage (p&lt;0.001). Pandemic stage (p&lt;0.001) and excision biopsy before surgery (OR, 6.459; 95% CI, 2.225-18.755; p=0.001) were markedly correlated with the TTS of patients.ConclusionsTTS of breast cancer patients significantly varied in different stages of the COVID-19 pandemic. And breast cancer patients’ daily lives and disease treatments were affected by the pandemic in many aspects, such as health insurance access, physical screening and change of therapeutic schedules. As the time-delay may cause negative influences on patients’ disease, we should minimize the occurrence of such time-delay. It is vital to come up with comprehensive measures to deal with unexpected situations in case the pandemic occurs.

Biomarkers of everolimus efficacy in breast cancer therapy

Objective Everolimus is an inhibitor of serine/ threonine kinase mTOR. The drug is approved for the treatment of metastatic ER positive, HER2 negative breast cancers and benefits a subset of patients with these breast cancers in combination with hormonal therapies. Despite extensive efforts, no additional predictive biomarkers to guide therapeutic decisions for everolimus have been introduced in clinical practice. Data sources This paper discusses predictive biomarkers for everolimus efficacy in breast cancer. A search of the medline and web of science databases was performed using the words “everolimus” and “biomarkers”. References of retrieved articles were manually scanned for additional relevant articles. Data Summary Everolimus benefits a subset of patients with metastatic ER positive, HER2 negative breast cancers in combination with hormonal therapies. Despite extensive efforts no additional predictive biomarkers to guide therapeutic decisions for everolimus therapy have been confirmed for use in clinical practice. However, promising biomarker leads for everolimus efficacy in breast cancer have been suggested and include expression of proteins in the mTOR pathway in ER positive, HER2 negative breast cancers. In HER2 positive cancers PIK3CA mutations, and PTEN expression loss are prognostic. Other clinical predictive biomarkers with more limited data include characteristics derived from whole genome sequencing, subsets of circulating leukocytes and changes in Standardized Uptake Values (SUV) of Positron Emission Tomography (PET) scans. Conclusions Putative predictive biomarkers for everolimus efficacy in breast cancer patients, both genomic and clinical, deserve further study and could lead to a better selection of responsive patients.

Triple negative apocrine breast carcinoma has better prognosis despite poor response to neoadjuvant chemotherapy

Background: Apocrine carcinoma is a rare subtype of invasive ductal breast cancer that shows apocrine differentiation and largely with triple negative immunohistology. Triple negative breast cancers are known to have a more aggressive clinical course. However, unlike the most other types, it is reported that triple negative apocrine carcinoma has a better prognosis. Due to scarcity of reported studies, our knowledges for its clinical behavior, prognosis and response to therapy are very limited. Methods: In this study, we retrospectively retrieved 41 triple negative apocrine carcinoma cases from our breast cancer database with an average follow up 32.8 months.Results: It was found that triple negative apocrine carcinoma had poorer response to neoadjuvant therapy, but better prognosis compared with other non-apocrine types of triple negative breast cancer. Meanwhile, triple negative apocrine carcinoma has a low proliferative nature as indicated by its low Ki67 index. Analysis of SEER database showed that chemotherapy did not improve breast cancer specific survival in TNAC patients. Conclusions: Our results suggest that triple negative apocrine carcinoma is a special subtype of triple negative breast cancer for which de-escalation of chemotherapy should be considered.