Breast cancer intratumour heterogeneity: current status and clinical implications

Integration of multiomics analyses reveals unique insights into CD24-mediated immunosuppressive tumor microenvironment of breast cancer

BACKGROUND

Tumor immunotherapy brings new light and vitality to breast cancer patients, but low response rate and limitations of therapeutic targets become major obstacles to its clinical application. Recent studies have shown that CD24 is involved in an important process of tumor immune regulation in breast cancer and is a promising target for immunotherapy.

METHODS

In this study, singleR was used to annotate each cell subpopulation after t-distributed stochastic neighbor embedding (t-SNE) methods. Pseudo-time trace analysis and cell communication were analyzed by Monocle2 package and CellChat, respectively. A prognostic model based on CD24-related genes was constructed using several machine learning methods. Multiple quantitative immunofluorescence (MQIF) was used to evaluate the spatial relationship between CD24+PANCK+cells and exhausted CD8+T cells.

RESULTS

Based on the scRNA-seq analysis, 1488 CD24-related differential genes were identified, and a risk model consisting of 15 prognostic characteristic genes was constructed by combining the bulk RNA-seq data. Patients were divided into high- and low-risk groups based on the median risk score. Immune landscape analysis showed that the low-risk group showed higher infiltration of immune-promoting cells and stronger immune reactivity. The results of cell communication demonstrated a strong interaction between CD24+epithelial cells and CD8+T cells. Subsequent MQIF demonstrated a strong interaction between CD24+PANCK+ and exhausted CD8+T cells with FOXP3+ in breast cancer. Additionally, CD24+PANCK+ and CD8+FOXP3+T cells were positively associated with lower survival rates.

CONCLUSION

This study highlights the importance of CD24+breast cancer cells in clinical prognosis and immunosuppressive microenvironment, which may provide a new direction for improving patient outcomes.

Patterns of distant metastasis and survival outcomes in de novo metastatic breast cancer according to age groups

Background

Is de novo metastatic breast cancer (dnMBC) the same disease in the elderly as in younger breast cancer remains unclear. This study aimed to determine the metastatic patterns and survival outcomes in dnMBC according to age groups.

Methods

We included patients from the Surveillance Epidemiology and End Results program. Chi-square test, multivariate logistic regression analyses, and multivariate Cox regression models were used for statistical analyses.

Results

A total of 17719 patients were included. There were 3.6% (n=638), 18.6% (n=3290), 38.0% (n=6725), and 39.9% (n=7066) of patients aged <35, 35-49, 50-64, and ≥65 years, respectively. Older patients had a significantly higher risk of lung metastasis and a significantly lower risk of liver metastasis. There were 19.1%, 25.6%, 30.9%, and 35.7% of patients with lung metastasis in those aged <35, 35-49, 50-64, and ≥65 years, respectively. Moreover, the proportion of liver metastasis was 37.6%, 29.5%, 26.3%, and 19.2%, respectively. Age was the independent prognostic factor associated with breast cancer-specific survival (BCSS) and overall survival (OS). Those aged 50-64 years had significantly inferior BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. Patients aged ≥65 years also had significantly lower BCSS (P<0.001) and OS (P<0.001) than those aged <35 years. However, similar outcomes were found between those aged 35-49 and <35 years.

Conclusion

Our study suggests that different age groups may affect the metastatic patterns among patients with dnMBC and the survival of younger patients is more favorable than those of older patients.

The correlation study between TOP2A gene expression in circulating tumor cells and chemotherapeutic drug resistance of patients with breast cancer

BACKGROUND

Patients with breast cancer (BC) at advanced stages have poor outcomes because of high rate of recurrence and metastasis. Biomarkers for predicting prognosis remain to be explored. This study aimed to evaluate the relationships between circulating tumor cells (CTCs) and outcomes of BC patients.

PATIENTS AND METHODS

A total of 50 female were enrolled in this study. Their diagnoses were determined by clinical characteristics, image data, and clinical pathology. CTC subtypes and TOP2A gene expression on CTCs were detected by CanPatrol™ technology and triple color in situ RNA hybridization (RNA-ISH), which divided into epithelial CTCs (eCTCs), mesenchymal CTCs (MCTCs), and hybrid CTCs (HCTCs) based on their surface markers. Hormone receptor, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) expression, was measured by immunohistochemistry (IHC) method before treatment. The risk factors for predicting recurrence and metastasis were calculated by COX risk regression model. The progression-free survival (PFS) of patients was determined using Kaplan-Meier survival curve.

RESULTS

The patients with a large tumor size (≥ 3 cm) and advanced tumor node metastasis (TNM) stages had high total CTCs (TCTCs) (P < 0.05). These patients also had high TOP2A expression level. COX risk regression analysis indicated that TOP2A expression levels in TCTCs, ER + , HER-2 + , and TNM stages were critical risk factors for recurrence and metastasis of patients (P < 0.05). The PFS of patients with ≥ 5 TCTCs, ≥ 3 HCTCs, and positive TOP2A expression in ≥ 3 TCTCs was significantly longer than that in patient with < 5 TCTCs, < 3 HCTCs, and TOP2A expression in < 3 TCTCs (P < 0.05). In contrast, the PFS of patients with positive hormone receptors (ER + , PR + , HER-2 +) also was dramatically lived longer than that in patients with negative hormone receptor expression.

CONCLUSIONS

High TCTC, HCTCs, and positive TOP2A gene expression on CTCs were critical biomarkers for predicting outcomes of BC patients. Positive hormone receptor expression in BC patients has significant favor PFS.

Biological Roles and Clinical Applications of Exosomes in Breast Cancer: A Brief Review

Breast cancer (BC) is a global health risk for women and has a high prevalence rate. The drug resistance, recurrence, and metastasis of BC affect patient prognosis, thus posing a challenge to scientists. Exosomes are extracellular vesicles (EVs) that originate from various cells; they have a double-layered lipid membrane structure and contain rich biological information. They mediate intercellular communication and have pivotal roles in tumor development, progression, and metastasis and drug resistance. Exosomes are important cell communication mediators in the tumor microenvironment (TME). Exosomes are utilized as diagnostic and prognostic biomarkers for estimating the treatment efficacy of BC and have the potential to function as tools to enable the targeted delivery of antitumor drugs. This review introduces recent progress in research on how exosomes influence tumor development and the TME. We also present the research progress on the application of exosomes as prognostic and diagnostic biomarkers and drug delivery tools.

Correlation Between miR-497-5p Expression With Clinicopathological Characteristics and Prognosis in Patients With Breast Cancer

Breast cancer (BC) comprises multiple biological and histologic properties. MicroRNAs show key functions in cancer prognosis. This paper explored the relationship between miR-497-5p with clinicopathological characteristics and prognosis in BC. Cancer tissues and normal adjacent tissues (NATs) were collected from 140 included patients with BC. The clinical baseline data, including age, tumor size, pathologic grade, clinical stage, modified Scraff-Bloom-Richardson grade, and lymph node metastasis, were recorded. miR-497-5p expression in cancer tissues and NAT was determined by reverse transcription-quantitative polymerase chain reaction. Patients with BC were followed up for 5 years to record their survival. Patients were divided into the miR-497-5p low expression and high expression groups to assess the correlation between miR-497-5p expression with clinicopathological characteristics and overall survival of patients. The role of miR-497-5p as an independent risk factor for death was further analyzed by a multivariate Cox regression model. miR-497-5p was downregulated in BC tissues than NAT. Tumor size, clinical stage, and lymph node metastasis showed significant differences among patients with high and low miR-497-5p expression levels. Patients with BC with low miR-497-5p expression presented decreased survival. Lowly-expressed miR-497-5p was an independent risk factor for death in patients. Collectively, cancer tissue miR-497-5p low expression increases the risk of death and serves as an independent risk factor for death in patients with BC.

Image-guided metabolomics and transcriptomics reveal tumour heterogeneity in luminal A and B human breast cancer beyond glucose tracer uptake

BACKGROUND

Breast cancer is a metabolically heterogeneous disease, and although the concept of heterogeneous cancer metabolism is known, its precise role in human breast cancer is yet to be fully elucidated.

METHODS

We investigated in an explorative approach a cohort of 42 primary mamma carcinoma patients with positron emission tomography/magnetic resonance imaging (PET/MR) prior to surgery, followed by histopathology and molecular diagnosis. From a subset of patients, which showed high metabolic heterogeneity based on tracer uptake and pathology classification, tumour centre and periphery specimen tissue samples were further investigated by a targeted breast cancer gene expression panel and quantitative metabolomics by nuclear magnetic resonance (NMR) spectroscopy. All data were analysed in a combinatory approach.

RESULTS

[18 F]FDG (2-deoxy-2-[fluorine-18]fluoro-d-glucose) tracer uptake confirmed dominance of glucose metabolism in the breast tumour centre, with lower levels in the periphery. Additionally, we observed differences in lipid and proliferation related genes between luminal A and B subtypes in the centre and periphery. Tumour periphery showed elevated acetate levels and enrichment in lipid metabolic pathways genes especially in luminal B. Furthermore, serine was increased in the periphery and higher expression of thymidylate synthase (TYMS) indicated one-carbon metabolism increased in tumour periphery. The overall metabolic activity based on [18 F]FDG uptake of luminal B subtype was higher than that of luminal A and the difference between the periphery and centre increased with tumour grade.

CONCLUSION

Our analysis indicates variations in metabolism among different breast cancer subtypes and sampling locations which details the heterogeneity of the breast tumours. Correlation analysis of [18 F]FDG tracer uptake, transcriptome and tumour metabolites like acetate and serine facilitate the search for new candidates for metabolic tracers and permit distinguishing luminal A and B. This knowledge may help to differentiate subtypes preclinically or to provide patients guide for neoadjuvant therapy and optimised surgical protocols based on individual tumour metabolism.

Estrogen-Receptor-Low-Positive Breast Cancer: Pathological and Clinical Perspectives

The expression of estrogen receptors (ERs) in breast cancer (BC) represents a strong prognostic and predictive biomarker and directs therapeutic decisions in early and advanced stages. ER-low-positive BC, defined by the immunohistochemical (IHC) expression of ERs from 1% to 9%, constitutes a distinct subset of total BC cases. Guidelines recommend that a low expression of ERs be reported in pathology reports since the benefit of endocrine therapy in patients with ER-low-positive BC is uncertain. Recently, several cohorts, mostly of a retrospective nature, have been published, reporting the clinicopathological characteristics and outcomes of ER-low-positive BC. However, the majority of the data focus on early-stage BC and the use of (neo)adjuvant therapy, and there is a significant lack of data regarding metastatic ER-low-positive BC. Further factors, including tumor heterogeneity as well as the potential loss of ER expression due to endocrine resistance, should be considered. Including patients with ER-low-positive BC in clinical trials for triple-negative breast cancer (TNBC) might improve the understanding of this entity and allow novel therapeutic approaches. The design and conduction of randomized clinical trials regarding this subgroup of patients are greatly anticipated.

Chronic treatment with TNF-α, alone and in combination with Takinib, SB203580 and metformin induce cell death in breast cancer

Breast cancer (BC) is the most common malignancy, and the largest cause of cancer death among women. The interactions between tumor cells and tumor micro environmental factors have a major impact on tumor progression. One of the critical pro-inflammatory cytokines present in breast cancer tumor microenvironment is TNF-α. The aim of this study was to evaluate the long-term effect of TNF-α (1 week) along with p38 or TAK1 inhibitors as well as metformin on induction of cellular death, cancer stem cell and expression of metastatic marker CXCR4. MCF-7 and MDA-MB-231 cells were treated with TNF-α for one week and then were treated with combination of Takinib, SB203580 or Metformin; after all treatments were done, cell proliferation, cellular death, surface expression of CXCR4, CD44 and CD24 were determined. The results showed that treatment with TNF-α alone or in combination with Takinib, SB203580 and metformin elevated induction of cellular death in both cell lines compared to the control group. TNF-α also increased CXCR4 expression in MCF-7 cells, but it reduced its expression in the MDA-MB-231 cells. Also, breast cancer stem cells (BCSCs) population decreased in MDA-MB-231 cells treated with TNF-α alone or in combination with SB203580 and metformin. Although, in MCF-7 cells only combination of TNF-α and Takinib reduced BCSCs population in a time dependent manner. Altogether, we showed that TNF-α alone or in combination with other treatments can affect the progression of breast cancer.

NR1D1 Stimulates Antitumor Immune Responses in Breast Cancer by Activating cGAS-STING Signaling

Potentiating antitumor immunity is a promising therapeutic approach for treating a variety of cancers, including breast cancer. One potential strategy to promote antitumor immunity is targeting DNA damage response. Given that the nuclear receptor NR1D1 (also known as REV-ERBα) inhibits DNA repair in breast cancer cells, we explored the role of NR1D1 in antitumor CD8+ T-cell responses. First, deletion of Nr1d1 in MMTV-PyMT transgenic mice resulted in increased tumor growth and lung metastasis. Orthotopic allograft experiments suggested that loss of Nr1d1 in tumor cells rather than in stromal cells played a prominent role in increasing tumor progression. Comprehensive transcriptome analyses revealed that biological processes including type I IFN signaling and T cell-mediated immune responses were associated with NR1D1. Indeed, the expression of type I IFNs and infiltration of CD8+ T cells and natural killer cells in tumors were suppressed in Nr1d1-/-;MMTV-PyMT mice. Mechanistically, NR1D1 promoted DNA damage-induced accumulation of cytosolic DNA fragments and activated cGAS-STING signaling, which increased the production of type I IFNs and downstream chemokines CCL5 and CXCL10. Pharmacologic activation of NR1D1 by its ligand, SR9009, enhanced type I IFN-mediated antitumor immunity accompanied by the suppression of tumor progression and lung metastasis. Taken together, these findings reveal the critical role of NR1D1 in enhancing antitumor CD8+ T-cell responses, suggesting that NR1D1 may be a good therapeutic target for breast cancer.

SIGNIFICANCE

NR1D1 suppresses breast cancer progression and lung metastasis by enhancing antitumor immunity via cGAS-STING pathway activation, which provides potential immunotherapeutic strategies for breast cancer.

Evaluation of breast cancer malignancy, prognostic factors and molecular subtypes using a continuous-time random-walk MR diffusion model

PURPOSE

To assess the continuous-time random-walk (CTRW) model's diagnostic value in breast lesions and to explore the associations between the CTRW parameters and breast cancer pathologic factors.

METHOD

This retrospective study included 85 patients (70 malignant and 18 benign lesions) who underwent 3.0T MRI examinations. Diffusion-weighted images (DWI) were acquired with 16b-values to fit the CTRW model. Three parameters (Dm, α, and β) derived from CTRW and apparent diffusion coefficient (ADC) from DWI were compared among the benign/malignant lesions, molecular prognostic factors, and molecular subtypes by Mann-Whitney U test. Spearman correlation was used to evaluate the associations between the parameters and prognostic factors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) based on the diffusion parameters.

RESULTS

All parameters, ADC, Dm, α, and β were significantly lower in the malignant than benign lesions (P < 0.05). The combination of all the CTRW parameters (Dm, α, and β) provided the highest AUC (0.833) and the best sensitivity (94.3%) in differentiating malignant status. And the positive status of estrogen receptor (ER) and progesterone receptor (PR) showed significantly lower β compared with the negative counterparts (P < 0.05). The high Ki-67 expression produced significantly lower Dm and ADC values (P < 0.05). Additionally, combining multiple CTRW parameters improved the performance of diagnosing molecular subtypes of breast cancer. Moreover, Spearman correlations analysis showed that β produced significant correlations with ER, PR and Ki-67 expression (P < 0.05).

CONCLUSIONS

The CTRW parameters could be used as non-invasive quantitative imaging markers to evaluate breast lesions.

Transcriptional intra-tumour heterogeneity predicted by deep learning in routine breast histopathology slides provides independent prognostic information

BACKGROUND

Intra-tumour heterogeneity (ITH) causes diagnostic challenges and increases the risk for disease recurrence. Quantification of ITH is challenging and has not been demonstrated in large studies. It has previously been shown that deep learning can enable spatially resolved prediction of molecular phenotypes from digital histopathology whole slide images (WSIs). Here we propose a novel method (Deep-ITH) to predict and measure ITH, and we evaluate its prognostic performance in breast cancer.

METHODS

Deep convolutional neural networks were used to spatially predict gene-expression (PAM50 set) from WSIs. For each predicted transcript, 12 measures of heterogeneity were extracted in the training data set (N = 931). A prognostic score to dichotomise patients into Deep-ITH low- and high-risk groups was established using an elastic-net regularised Cox proportional hazards model (recurrence-free survival). Prognostic performance was evaluated in two independent data sets: SöS-BC-1 (N = 1358) and SCAN-B-Lund (N = 1262).

RESULTS

We observed an increase in risk of recurrence in the high-risk group with hazard ratio (HR) 2.11 (95%CI:1.22-3.60; p = 0.007) using nested cross-validation. Subgroup analyses confirmed the prognostic performance in oestrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative, grade 3, and large tumour subgroups. The prognostic value was confirmed in the independent SöS-BC-1 cohort (HR=1.84; 95%CI:1.03-3.3; p = 3.99 ×10-2). In the other external cohort, significant HR was observed in the subgroup of histological grade 2 patients, as well as in the subgroup of patients with small tumours (<20 mm).

CONCLUSION

We developed a novel method for an automated, scalable, and cost-efficient measure of ITH from WSIs that provides independent prognostic value for breast cancer.

SIGNIFICANCE

Transcriptional ITH predicted by deep learning models enables prediction of patient survival from routine histopathology WSIs in breast cancer.

Prognostic and predictive biomarkers with therapeutic targets in breast cancer: A 2022 update on current developments, evidence, and recommendations

OBJECTIVE

To evaluate and validate the recent and emerging data for prognostic and predictive biomarkers with therapeutic targets in breast cancer.

DATA SOURCES

A literature search from January 2015 to March 2022 was performed using the key terms breast cancer, clinical practice guidelines, gene mutations, genomic assay, immune cancer therapy, predictive and/or prognostic biomarkers, and targeted therapies.

STUDY SELECTION AND DATA EXTRACTION

Relevant clinical trials, meta-analyses, seminal articles, and published evidence- and consensus-based clinical practice guidelines in the English language were identified, reviewed and evaluated.

DATA SYNTHESIS

Breast cancer is a biologically heterogeneous disease, leading to wide variability in treatment responses and survival outcomes. Biomarkers for breast cancer are evolving from traditional biomarkers in immunohistochemistry (IHC) such as estrogen receptor (ER), progesterone receptor (PR) and epidermal growth factor receptor type 2 (HER2) to genetic biomarkers with therapeutic implications (e.g. breast cancer susceptibility gene 1/2 [BRCA1/2], estrogen receptor α [ESR1] gene mutation, HER2 gene mutation, microsatellite instability [MSI], phosphatidylinositol 3-kinase catalytic subunit 3Cα [PIK3CA] gene mutation, neurotrophic tyrosine receptor kinase [NTRK] gene mutation). In addition, current data are most robust for biomarkers in immunotherapy (e.g. programmed cell death receptor ligand-1 [PD-L1], microsatellite instability-high [MSI-H] or deficient mismatch repair [dMMR]). Oncotype DX assay remains the best validated gene expression assay that is both predictive and prognostic whereas MammaPrint is prognostic for genomic risk.

CONCLUSIONS

Biomarker-driven therapies have the potential to confer greater therapeutic advantages than standard-of-care therapies. The purported survival benefits associated with biomarker-driven therapies should be weighed against their potential harms.

Magnetic resonance imaging features of invasive breast cancer association with the tumour stromal ratio

OBJECTIVE

To assess the association between breast cancer tumour stroma and magnetic resonance imaging (MRI) features.

MATERIALS AND METHODS

A total of 84 patients with treatment-naïve invasive breast cancer were enrolled into this retrospective study. The tumour stroma ratio (TSR) was estimated from the amount of tumour stroma in the pathology specimen of the breast tumour. The MRI images of the patients were analysed based on Breast Imaging Reporting and Data Systems (ACR-BIRADS) for qualitative features which include T2- weighted, diffusion-weighted images (DWI) and dynamic contrast-enhanced (DCE) for kinetic features. The mean signal intensity (SI) of Short Tau Inversion Recovery (STIR), with the ratio of STIR of the lesion and pectoralis muscle (L/M ratio) and apparent diffusion coefficient (ADC) value, were measured for the quantitative features. Correlation tests were performed to assess the relationship between TSR and MRI features.

RESULTS

There was a significant correlation between the margin of mass, enhancement pattern, and STIR signal intensity of breast cancer and TSR. There were 54.76% (n = 46) in the low stromal group and 45.24% (n = 38) in the high stromal group. A significant association were seen between the margin of the mass and TSR (p = 0.034) between the L/M ratio (p <0.001), and between STIR SI of the lesion and TSR (p<0.001). The median L/M ratio was significantly higher in the high TSR group as compared to the lower TSR group (p < 0.001).

CONCLUSION

Breast cancer with high stroma had spiculated margins, lower STIR signal intensity, and a heterogeneous pattern of enhancement. Hence, in this preliminary study, certain MRI features showed a potential to predict TSR.

TrkA expression directs the anti-neoplastic activity of MLK3 inhibitors in triple-negative breast cancer

Mixed Lineage Kinase 3 (MLK3) is a viable target for neoplastic diseases; however, it is unclear whether its activators or inhibitors can act as anti-neoplastic agents. We reported that the MLK3 kinase activity was higher in triple-negative (TNBC) than in hormone receptor-positive human breast tumors, where estrogen inhibited MLK3 kinase activity and provided a survival advantage to ER⁺ breast cancer cells. Herein, we show that in TNBC, the higher MLK3 kinase activity paradoxically promotes cancer cell survival. Knockdown of MLK3 or MLK3 inhibitors, CEP-1347 and URMC-099, attenuated tumorigenesis of TNBC cell line and Patient-Derived (PDX) xenografts. The MLK3 kinase inhibitors decreased both the expression and activation of MLK3, PAK1, and NF-kB protein and caused cell death in TNBC breast xenografts. RNA-seq analysis identified several genes downregulated by MLK3 inhibition, and the NGF/TrkA MAPK pathway was significantly enriched in tumors sensitive to growth inhibition by MLK3 inhibitors. The TNBC cell line unresponsive to kinase inhibitor had substantially lower TrkA, and overexpression of TrkA restored the sensitivity to MLK3 inhibition. These results suggest that the functions of MLK3 in breast cancer cells depend on downstream targets in TNBC tumors expressing TrkA, and MLK3 kinase inhibition may provide a novel targeted therapy.

Prediction of Ki-67 of Invasive Ductal Breast Cancer Based on Ultrasound Radiomics Nomogram

PURPOSE

The objective of this research was to develop and validate an ultrasound-based radiomics nomogram for the pre-operative assessment of Ki-67 in breast cancer (BC).

MATERIALS AND METHODS

From December 2016 to December 2018, 515 patients with invasive ductal breast cancer who received two-dimensional (2D) ultrasound and Ki-67 examination were studied and analyzed retrospectively. The dataset was distributed at random into a training cohort (n = 360) and a test cohort (n = 155) in the ratio of 7:3. Each tumor region of interest was defined based on 2D ultrasound images and radiomics features were extracted. ANOVA, maximum correlation minimum redundancy (mRMR) algorithm, and minimum absolute shrinkage and selection operator (LASSO) were performed to pick features, and independent clinical predictors were integrated with radscore to construct the nomogram for predicting Ki-67 index by univariate and multivariate logistic regression analysis. The performance and utility of the models were evaluated by plotting receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves.

RESULTS

In the testing cohort, the area under the receiver characteristic curve (AUC) of the nomogram was 0.770 (95% confidence interval, 0.690-0.860). In both cohorts, the nomogram outperformed both the clinical model and the radiomics model (P < .05 according to the DeLong test). The analysis of DCA proved that the model has clinical utility.

CONCLUSIONS

The nomogram based on 2D ultrasound images offered an approach for predicting Ki-67 in BC.

Whole Genome Sequencing of Single-Circulating Tumor Cell Ameliorates Unraveling Breast Cancer Heterogeneity

Objective

Because tumor tissues are most frequently heterogeneous and hard to characterize, the resulting therapeutic strategy could be misled. The most active and invasive tumor cells are circulating tumor cells (CTCs). In this study, we investigated the feasibility of individualized treatment of breast cancer patients based on whole genome sequencing (WGS) of single cell CTC.

Methods

Twenty-four CTCs were identified in three breast cancer patients. For each patient, one polyploid CTC was captured, and on which the WGS was performed. WGS was considered due to its sequencing robustness compared to conventional sequencing approaches. Based on the histopathological Her-2 status in tumor tissue and the HER2 gene status in WGS results of CTC, we adjusted treatment strategies and monitored disease progression.

Results

Patients ID1 and ID2 are found to be Her-2 positive in primary tumors and HER2 gene amplification in the DNA of CTCs. In-patient ID3, histopathological examination of the primary tumor and liver metastases revealed Her-2 negative, but the WGS analysis of CTC showed HER2 gene amplification. After adjusting treatment by adding Her-2 inhibitors according to the results of CTC sequencing, liver metastases and pleural effusion were significantly reduced two months later, CTC number and ctDNA burden were decreased, and 18-months progression-free survival (PFS) was recorded. In addition, some potential therapeutic targets and mutations in drug-resistant genes were detected.

Conclusion

The results of CTC sequencing effectively guided the treatment of a patient with HER2 gene amplification in CTC but with Her-2 negative on tumor tissue. Therefore, CTC sequencing could help resolve the heterogeneity of tumors and provide precision medicine for patients.

Immune subtype identification and multi-layer perceptron classifier construction for breast cancer

Introduction

Breast cancer is a heterogeneous tumor. Tumor microenvironment (TME) has an important effect on the proliferation, metastasis, treatment, and prognosis of breast cancer.

Methods

In this study, we calculated the relative proportion of tumor infiltrating immune cells (TIICs) in the breast cancer TME, and used the consensus clustering algorithm to cluster the breast cancer subtypes. We also developed a multi-layer perceptron (MLP) classifier based on a deep learning framework to detect breast cancer subtypes, which 70% of the breast cancer research cohort was used for the model training and 30% for validation.

Results

By performing the K-means clustering algorithm, the research cohort was clustered into two subtypes. The Kaplan-Meier survival estimate analysis showed significant differences in the overall survival (OS) between the two identified subtypes. Estimating the difference in the relative proportion of TIICs showed that the two subtypes had significant differences in multiple immune cells, such as CD8, CD4, and regulatory T cells. Further, the expression level of immune checkpoint molecules (PDL1, CTLA4, LAG3, TIGIT, CD27, IDO1, ICOS) and tumor mutational burden (TMB) also showed significant differences between the two subtypes, indicating the clinical value of the two subtypes. Finally, we identified a 38-gene signature and developed a multilayer perceptron (MLP) classifier that combined multi-gene signature to identify breast cancer subtypes. The results showed that the classifier had an accuracy rate of 93.56% and can be robustly used for the breast cancer subtype diagnosis.

Conclusion

Identification of breast cancer subtypes based on the immune signature in the tumor microenvironment can assist clinicians to effectively and accurately assess the progression of breast cancer and formulate different treatment strategies for different subtypes.

Combining Organoid Models with Next-Generation Sequencing to Reveal Tumor Heterogeneity and Predict Therapeutic Response in Breast Cancer

Estrogen receptor-positive (ER+) breast cancer (BC) is a common subtype of BC with a relatively good prognosis. However, recurrence and death from ER+ BC occur because of tumor heterogeneity. This study aimed to explore tumor heterogeneity using next-generation sequencing (NGS) and tumor-organoid models to promote BC precise therapy. We collected needle biopsy, surgical excision, and cerebrospinal fluid (CSF) samples to establish tumor organoids. We found that the histological characteristics of organoids were consistent with original lesions and recapitulated their heterogenicity. In addition, the NGS results showed that PIK3CA and TP53 genes had detrimental mutations. BAP1, RET, AXIN2, and PPP2R2A genes had mutations with unknown function. The score for homologous recombination deficiency (HRD) of genome was 56, indicating that the tumor was likely sensitive to PARPi. The mutant-allele tumor heterogeneity (MATH) value of the tumor genome was 68.03, indicating high tumor heterogeneity. At last, we performed a drug screening on organoids. The toxicity of different drugs toward BC organoids originated from needle biopsy and surgical excision was tested, respectively. The IC₅₀ values in the needle biopsy groups were paclitaxel 2.83 μM, carboplatin 61.47 μM, neratinib 0.8 μM, lapatinib >100 μM; in the surgical excision groups: trastuzumab >100 μM, docetaxel 0.036 μM, tamoxifen 20.54 μM, olaparib 5.478 μM, BYL719 < 0.1 μM. The toxicity data showed that the BC organoids could show dynamic characteristics of tumor progression and reflect the heterogeneity of BC. Our study demonstrates that the combined use of tumor organoids and NGS is a potential way to test tumor heterogeneity and predict drug response in ER + BC, which contributes to the development of personalized therapy.

Characterisation of 3D Bioprinted Human Breast Cancer Model for In Vitro Drug and Metabolic Targeting

Monolayer cultures, the less standard three-dimensional (3D) culturing systems, and xenografts are the main tools used in current basic and drug development studies of cancer research. The aim of biofabrication is to design and construct a more representative in vivo 3D environment, replacing two-dimensional (2D) cell cultures. Here, we aim to provide a complex comparative analysis of 2D and 3D spheroid culturing, and 3D bioprinted and xenografted breast cancer models. We established a protocol to produce alginate-based hydrogel bioink for 3D bioprinting and the long-term culturing of tumour cells in vitro. Cell proliferation and tumourigenicity were assessed with various tests. Additionally, the results of rapamycin, doxycycline and doxorubicin monotreatments and combinations were also compared. The sensitivity and protein expression profile of 3D bioprinted tissue-mimetic scaffolds showed the highest similarity to the less drug-sensitive xenograft models. Several metabolic protein expressions were examined, and the in situ tissue heterogeneity representing the characteristics of human breast cancers was also verified in 3D bioprinted and cultured tissue-mimetic structures. Our results provide additional steps in the direction of representing in vivo 3D situations in in vitro studies. Future use of these models could help to reduce the number of animal experiments and increase the success rate of clinical phase trials.

The role of radiogenomics in the diagnosis of breast cancer: a systematic review

Background

One of the most common cancers diagnosed worldwide is breast cancer (BC), which is the leading cause of cancer death among women. The radiogenomics method is more accurate for managing and inhibiting this disease, which takes individual diagnosis on genes, environments, and lifestyles of each person. The present study aims to highlight the current state-of-the-art, the current role and limitations, and future directions of radiogenomics in breast cancer.

Method

This systematic review article was searched from databases such as Embase, PubMed, Web of Science, Google Scholar, Scopus, and Cochrane Library without any date or language limitations of databases. Searches were performed using Boolean OR and AND operators between the main terms and keywords of particular topic of the subject under investigation. All retrospective, prospective, cohort, and pilot studies were included, which were provided with more details about the topic. Articles such as letter to the editor, review, and short communications were excluded because of lack of information, discussions, or use of radiogenomics method on other cancers. For quality assessment of articles, STROBE checklist was used.

Result

For the systematic review, 18 articles were approved after assessing the full text of selected articles. In this review, 3614 patients with BC of selected articles were evaluated, and all radiogenomics were associated with more power in classification, differential diagnosis, and prognosis of BC. Among the various modalities to predict genomic indicators and molecular subtypes, DCE-MRI has the higher performance and finally the highest amount of AUC value (0.956) belonged to PI3K gene.

Conclusion

This review shows that radiogenomics can help with the diagnosis and treatment of breast cancer in patients. It has shown that recognizing and specifying radiogenomic phenotypes in the genomic signatures can be helpful in treatment and diagnosis of disease. The molecular methods used in these articles are limited to miRNAs expression, gene expression, Ki67 proliferation index, next-generation RNA sequencing, whole RNA sequencing, and molecular histopathology that can be completed in future studies by other methods such as exosomal miRNAs, specific proteins expression, DNA repair capacity, and other biomarkers that have prognostic and predictive value for cancer treatment response. Studies with control group and large sample size for evaluation of radiogenomics in diagnosis and treatment recommended.

The Radiological Response Rate Pattern Is Associated With Recurrence Free Survival in Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy

PURPOSE

The aim of this study was to evaluate the radiological response rate patterns during neoadjuvant chemotherapy (NAC) in patients with breast cancer.

METHODS

Patients who underwent NAC with two specific chemotherapy regimens (doxorubicin with cyclophosphamide or doxorubicin with docetaxel) and who underwent a response evaluation every two cycles were included in the study. The initial response ratio was defined as the ratio of the largest tumor diameter at diagnosis to that after two cycles of NAC. The latter response ratio was defined as the ratio between the tumor size after two cycles and that after four cycles of NAC. The radiological response rate pattern was divided into three groups: the fast-to-slow response group (F-S group, initial response ratio > latter response ratio + 20%), slow-to-fast response group (S-F group, latter response ratio > initial response ratio + 20%), and constant response group (less than 20% difference between the initial and latter response ratios).

RESULTS

In total, 177 patients were included in the analysis. Forty-two (23.9%) patients were categorized into the F-S group, 26 (14.8%) into the S-F group, and 108 (61.2%) into the constant group. Clinicopathologic factors did not differ according to radiologic response rate patterns. The median follow-up period was 50 months (range, 3-112) months. In the univariate analysis, the F-S group had a significantly worse recurrence-free survival than the S-F and constant groups (hazard ratio [HR], 3.63; 95% confidence interval [CI], 1.05-12.46; p = 0.041). The F-S group also presented with significantly worse survival than the S-F group in the multivariate analysis (HR, 3.45; 95% CI, 1.00-11.89; p = 0.049).

CONCLUSION

The F-S group had a poorer survival rate than the S-F group. Radiological response rate patterns may be useful for accurate prognostic assessments, especially when considering post-neoadjuvant therapy.

Heterogeneity and tumor evolution reflected in liquid biopsy in metastatic breast cancer patients: a review

Breast cancer is a spatially and temporally dynamic disease in which differently evolving genetic clones are responsible for progression and clinical outcome. We review tumor heterogeneity and clonal evolution from studies comparing primary tumors and metastasis and discuss plasma circulating tumor DNA as a powerful real-time approach for monitoring the clonal landscape of breast cancer during treatment and recurrence. We found only a few early studies exploring clonal evolution and heterogeneity through analysis of multiregional tissue biopsies of different progression steps in comparison with circulating tumor DNA (ctDNA) from blood plasma. The model of linear progression seemed to be more often reported than the model of parallel progression. The results show complex routes to metastasis, however, and plasma most often reflected metastasis more than primary tumor. The described patterns of evolution and the polyclonal nature of breast cancer have clinical consequences and should be considered during patient diagnosis and treatment selection. Current studies focusing on the relevance of clonal evolution in the clinical setting illustrate the role of liquid biopsy as a noninvasive biomarker for monitoring clonal progression and response to treatment. In the clinical setting, circulating tumor DNA may be an ideal support for tumor biopsies to characterize the genetic landscape of the metastatic disease and to improve longitudinal monitoring of disease dynamics and treatment effectiveness through detection of residual tumor after resection, relapse, or metastasis within a particular patient.

Radiomics of dynamic contrast-enhanced magnetic resonance imaging parametric maps and apparent diffusion coefficient maps to predict Ki-67 status in breast cancer

Purpose

This study was aimed at evaluating whether a radiomics model based on the entire tumor region from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parametric maps and apparent diffusion coefficient (ADC) maps could indicate the Ki-67 status of patients with breast cancer.

Materials and methods

This retrospective study enrolled 205 women with breast cancer who underwent clinicopathological examination. Among them, 93 (45%) had a low Ki-67 amplification index (Ki-67 positivity< 14%), and 112 (55%) had a high Ki-67 amplification index (Ki-67 positivity ≥ 14%). Radiomics features were extracted from three DCE-MRI parametric maps and ADC maps calculated from two different b values of diffusion-weighted imaging sequences. The patients were randomly divided into a training set (70% of patients) and a validation set (30% of patients). After feature selection, we trained six support vector machine classifiers by combining different parameter maps and used 10-fold cross-validation to predict the expression level of Ki-67. The performance of six classifiers was evaluated with receiver operating characteristic (ROC) analysis, sensitivity, and specificity in both cohorts.

Results

Among the six classifiers constructed, a radiomics feature set combining three DCE-MRI parametric maps and ADC maps yielded an area under the ROC curve (AUC) of 0.839 (95% confidence interval [CI], 0.768-0.895) within the training set and 0.795 (95% CI, 0.674-0.887) within the independent validation set. Additionally, the AUC value, compared with that for a single parameter map, was moderately increased by combining features from the three parametric maps.

Conclusions

Radiomics features derived from the DCE-MRI parametric maps and ADC maps have the potential to serve as imaging biomarkers to determine Ki-67 status in patients with breast cancer.

The Place of Chemotherapy in The Evolving Treatment Landscape for Patients With HR-positive/HER2-negative MBC

Endocrine therapy (ET) for the treatment of patients with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR-positive/HER2-negative) metastatic breast cancer (MBC) has changed markedly over recent years with the emergence of new ETs and the use of molecularly targeted agents. Cytotoxic chemotherapy continues, however, to have an important role in these patients and it is important to maximize its efficacy while minimizing toxicity to optimize outcomes. This review examines current HR-positive/HER2-negative MBC clinical guidelines and addresses key questions around the use of chemotherapy in the face of emerging therapeutic options. Specifically, the indications for chemotherapy in patients with HR-positive/HER2-negative MBC and the choice of optimal chemotherapy are discussed.

Specific cell differentiation in breast cancer: a basis for histological classification

Breast parenchyma progenitor cells show a high degree of phenotypic plasticity reflected in the wide range of morphology observed in benign and malignant breast tumours. Although there is evidence suggesting that all breast cancer (BC) arises from a common epithelial progenitor or stem cell located at the terminal duct lobular units (TDLUs), BC shows a broad spectrum of morphology with extensive variation in histological type and grade. This is related to the complexity of BC carcinogenesis including initial genetic changes in the cell of origin, subsequent genetic and epigenetic alterations and reprogramming that occur at various stages of BC development and the interplay with the surrounding microenvironment, factors which influence the process of differentiation. Differentiation in BC determines the morphology, which can be measured using histological grade and tumour type. Histological grade, which measures the similarity to the TDLUs, reflects the degree of differentiation whereas tumour type reflects the type of differentiation. Understanding BC phenotypic differentiation facilitates the accurate diagnosis and histological classification of BC with corresponding clinical implications in terms of disease behaviour, prognosis and management plans. In this review, we highlight the potential pathways that BC stem cells follow resulting in the development of different histological types of BC and how knowledge of these pathways impacts our ability to classify BC in diagnostic practice. We also discuss the role of cellular differentiation in producing metaplastic and neuroendocrine carcinomas of the breast and how the latter differ from their counterparts in other organs, with emphasis on clinical relevance.

Self-assembled small messenger RNA nanospheres for efficient therapeutic apoptin expression and synergistic Gene-Chemotherapy of breast cancer

In this work, small self-assembled messenger RNA nanospheres (mRNA-NSs) were successfully prepared by rolling circle transcription on a constructed apoptin plasmid. The self-assembled mRNA-NSs have a uniform diameter of approximately 65 nm, good dispersity in solution, and efficient therapeutic apoptin expression ability. In addition, the mRNA-NSs have a high loading capacity of 8.2% for the antitumor drug doxorubicin (Dox), which can effectively deliver the loaded Dox into 4 T1 cells. Cellular experiments show that Dox-loaded self-assembled messenger RNA nanospheres (mRNA-NSs@Dox) can reduce the viability of 4 T1 breast cancer cells by significantly upregulating Bax protein, thereby inducing the activation of Caspase 3 in 4 T1 cells. In vivo experiments show that mRNA-NSs@Dox can effectively increase the necrosis of tumor tissue, reduce the expression of Ki67, and exhibit a synergistic gene-chemotherapy effect in breast cancer-bearing mice. Taken together, this study successfully prepared self-assembled apoptin messenger RNA nanospheres (mRNA-NSs), which can improve the expression of the therapeutic protein apoptin and exhibit excellent synergistic antitumor effects after loading Dox, providing new ideas for the gene treatment and chemotherapy of breast cancer.

PAM50 Intrinsic Subtype Profiles in Primary and Metastatic Breast Cancer Show a Significant Shift toward More Aggressive Subtypes with Prognostic Implications

Simple Summary

The majority of breast cancer deaths are caused by the spread of the disease to distant locations. The biological processes and molecular characteristics that eventually transform breast cancer into a life-threatening metastatic disease are not fully understood. The molecular subtyping of breast cancer into four tumor subtypes—namely luminal A, luminal B, human epidermal growth factor receptor 2-enriched, and basal-like subtypes—has been implemented for therapeutic guidance in patients with early breast cancer. It is not settled whether molecular subtypes in metastatic tissue can guide the choice of systemic therapy and how these subtypes may change throughout tumor progression. In this study, breast cancer subtypes at different stages of the disease were investigated, and we found changes to more unfavorable subtypes to be common throughout the progression of the disease. These findings suggests that molecular subtyping in metastatic disease could add important prognostic and predictive information to complement information from the primary tumor.

Abstract

Background: PAM50 breast cancer intrinsic subtyping adds prognostic information in early breast cancer; however, the role in metastatic disease is unclear. We aimed to identify PAM50 subtypes in primary tumors (PTs) and metastases to outline subtype changes and their prognostic role. Methods: RNA was isolated from PTs, lymph node metastases (LNMs), and distant metastases (DMs) in metastatic breast cancer patients (n = 140) included in a prospective study (NCT01322893). Gene expression analyses were performed using the Breast Cancer 360 (BC360) assay from Nano-String. The subtype shifts were evaluated using McNemar and symmetry tests, and clinical outcomes were evaluated with log-rank tests and Cox regression. Results: The PAM50 subtype changed in 25/59 of paired samples between PTs and LNMs (P_symmetry = 0.002), in 31/61 between PTs and DMs (P_symmetry < 0.001), and in 16/38 between LNMs and DMs (P_symmetry = 0.004). Shifts toward subtypes with worse outcomes were the most common. Patients with shifts from the luminal PT to non-luminal DM subtypes had worse progression-free survival compared to patients with a stable subtype (hazard ratio (HR): 2.3; 95% confidence interval (CI): 1.14–4.68, p = 0.02). Conclusion: Strong evidence of PAM50 subtype shifts toward unfavorable subtypes were seen between PTs and metastatic samples. For patients with a shift in subtype from luminal PT to non-luminal DM, a worse prognosis was noted.

α)

AIMS

The mechanisms that drive breast cancer (BC) progression and poor outcome are not fully understood. The human heat shock protein 90 alpha family class A member 1 (HSP90α) encoded by the HSP90ΑA1 gene has a vital role in cellular responses to stress and is implicated in the development and progression of many cancers. The current study aims to explore the clinical and prognostic importance of HSP90α in BC.

METHODS

The Molecular Taxonomy of Breast Cancer International Consortium (n=1980); The Cancer Genome Atlas (n=1097) and the Breast Cancer Gene-Expression Miner (Bc-GenExMiner) BC datasets (n=5056) were used to evaluate HSP90ΑA1 mRNA expression. HSP90α protein expression was further assessed using immunohistochemistry in a large (n=911) well-characterised BC series. The association between mRNA and protein expressions with other clinicopathological parameters and outcome was analysed.

RESULTS

High expression of HSP90ΑA1 both at the mRNA and protein levels was significantly associated with characteristics of BC poor prognosis, including high grade, lymphovascular invasion, poor Nottingham Prognostic Index and positive expression of p53 and PIK3CA. Outcome analysis revealed that high HSP90α protein expression is an independent predictor of shorter BC-specific survival.

CONCLUSION

HSP90α can be used as a potential prognostic marker in BC. Further mechanistic studies are warranted to determine the underlying molecular mechanisms mediated by HSP90α in BC.

Bevacizumab Plays a double-edged role in Neoadjuvant Therapy for Non-metastatic Breast Cancer: A Systemic Review and Meta-Analysis

The anti-angiogenic drug Bevacizumab (Bev) is engaged in neoadjuvant therapy for non-metastatic breast cancer (NMBC). However, whether neoadjuvant Bev providing a greater benefit to patients is debatable. Our study aimed to review Bev's role in Neoadjuvant therapy (NAT) in NMBC and identify predictive markers associated with its efficacy by systemic review and meta-analysis. Eligible trials were retrieved from the Pubmed, Embase, and Cochrane Library, and random or fixed effects models were applied to synthesize data. Power of pCR to predict DFS or OS was evaluated by nonlinear mixed effect model. In NMBC, Bev significantly improved the rate of patients achieving pCR, but this benefit discontinued in DFS or OS. Biomarkers such as PAM50 intrinsic subtype, VEGF overexpression, regulation of VEGF signaling pathway, hypoxia-related genes, BRCA1/2 mutation, P53 mutation and immune phenotype can be used to predict Bev-inducing pCR and/or DFS/OS. Unfortunately, although patients with pCR survived longer than those without pCR when ignoring the use of Bev, but patients achieving pCR with Bev might survive shorter than those achieving pCR without Bev. Subgroup analyses found Bev prolonged patients' OS when given pre- and post-surgery. Lastly, adding Bev increased adverse effects. Overall, Bev offered limited effect for patients with NMBC in an unscreened population. However, in biomarkers - identified subgroup, Bev could be promising to ameliorate the prognosis of specific patients with NMBC.

Integration of Multitargeted Polymer-Based Contrast Agents with Photoacoustic Computed Tomography: An Imaging Technique to Visualize Breast Cancer Intratumor Heterogeneity

One of the primary challenges in breast cancer diagnosis and treatment is intratumor heterogeneity (ITH), i.e., the coexistence of different genetically and epigenetically distinct malignant cells within the same tumor. Thus, the identification of ITH is critical for designing better treatments and hence to increase patient survival rates. Herein, we report a noninvasive hybrid imaging technology that integrates multitargeted and multiplexed patchy polymeric photoacoustic contrast agents (MTMPPPCAs) with single-impulse panoramic photoacoustic computed tomography (SIP-PACT). The target specificity ability of MTMPPPCAs to distinguish estrogen and progesterone receptor-positive breast tumors was demonstrated through both fluorescence and photoacoustic measurements and validated by tissue pathology analysis. This work provides the proof-of-concept of the MTMPPPCAs/SIP-PACT system to identify ITH in nonmetastatic tumors, with both high molecular specificity and real-time detection capability.

Study on <em>CCDC69</em> interfering with the prognosis of patients with breast cancer through PPAR signal pathway

Coiled-coil domain-containing protein 69 (CCDC69) is a novel gene and limited knowledge in known in breast cancer. In the present study, we aimed to explore the relationship between CCDC69 and breast cancer, demonstrate the clinicopathological significance and prognostic role of CCDC69 in breast cancer, and analyze the possible mechanism of CCDC69 affecting the prognosis of breast cancer. First, from GEO database, TIMER, GEPIA, and OncoLnc, we selected CCDC69 as the potential gene which closely involved in breast cancer progression. Next, by real-time PCR detection, the expression of CCDC69 in breast cancer tissue was notably lower than that in normal breast tissues (p=0.0002). In addition, our immunohistochemistry indicated that the positive expression rate of CCDC69 in the triple-negative breast cancer (TNBC) was lower than that in the non-TNBC (p=0.0362), and it was negatively correlated with the expression of Ki67 (p=0.001). Further enrichment analysis of CCDC69 and the similar genes performed on FunRich3.1.3 revealed that these genes were significantly associated with fat differentiation, and most of them were related to peroxisome proliferator-activated receptor (PPAR) signal pathway. Collectively, our findings suggest that CCDC69 is down regulated in breast cancer tissue especially in TNBC which has higher malignant grade and poorer clinical prognosis.

Anhydroicaritin Inhibits EMT in Breast Cancer by Enhancing GPX1 Expression: A Research Based on Sequencing Technologies and Bioinformatics Analysis

Background: Breast cancer (BC) is the leading cause of cancer-related deaths among women worldwide. The application of advanced technology has promoted accurate diagnosis and treatment of cancer. Anhydroicaritin (AHI) is a flavonoid with therapeutic potential in BC treatment. The current study aimed to determine AHI's mechanism in BC treatment via RNA sequencing, comprehensive bioinformatics analysis, and experimental verification. Methods: Network pharmacology and MTT (3-(4,5)-dimethylthiazolyl-3,5- diphenyltetrazolium bromide) experiments were conducted to first confirm AHI's anti-BC effect. RNA sequencing was performed to identify the genes affected by AHI. Differential expression analysis, survival analysis, gene set enrichment analysis, and immune infiltration analysis were performed via bioinformatics analysis. Western blot analysis, reverse transcription-polymerase chain reaction (RT-PCR) experiment, molecular docking, and drug affinity responsive target stability (DARTS) experiments were also performed to confirm AHI's direct effect on glutathione peroxidase 1 (GPX1) expression. Confocal immunofluorescence analysis was conducted to verify AHI's effect on the occurrence and development of epithelial-mesenchymal transition (EMT). Finally, BC nude mouse xenografts were established, and AHI's molecular mechanism on BC was explored. Results: Network pharmacology results demonstrated that AHI's therapeutic targets on BC were related to the proliferation, invasion, and metastasis of BC cells. AHI significantly inhibited the proliferation of 4T1 and MDA-MB-231 BC cells in the MTT experiments. RNA sequencing results showed that AHI upregulated the GPX1 expression in the 4T1 and MDA-MB-231 BC cells. Next, bioinformatics analysis revealed that GPX1 is less expressed in BC than in normal breast tissues. Patients with high GPX1 expression levels tended to have prolonged overall survival and disease-free survival than patients with low GPX1 expression levels in BC. Western blot and RT-PCR experiments revealed that AHI increased the protein and mRNA levels of GPX1. Molecular docking and DARTS experiments confirmed the direct binding combination between AHI and GPX1. After the evaluation of the EMT scores of 1,078 patients with BC, we found a potential anti-BC role of GPX1 possibly via suppression of the malignant EMT. The confocal immunofluorescence analysis showed that AHI increased E-cadherin expression levels and reduced vimentin expression levels in BC cells. Animal experiments showed that AHI significantly inhibited tumor growth. AHI also inhibited EMT by enhancing GPX1 and caspase3 cleavage, hence inhibiting EMT markers (i.e., N-cadherin and vimentin) and Ki-67. Conclusion: GPX1 plays a critical role in BC, which may be a biomarker for the prognosis. In addition, AHI suppressed EMT by increasing GPX1 expression, which may serve as a potential therapy for BC treatment.

Metabolic traits ruling the specificity of the immune response in different cancer types

Cancer immunotherapy aims to augment the response of the patient's own immune system against cancer cells. Despite effective for some patients and some cancer types, the therapeutic efficacy of this treatment is limited by the composition of the tumor microenvironment (TME), which is not well-suited for the fitness of anti-tumoral immune cells. However, the TME differs between cancer types and tissues, thus complicating the possibility of the development of therapies that would be effective in a large range of patients. A possible scenario is that each type of cancer cell, granted by its own mutations and reminiscent of the functions of the tissue of origin, has a specific metabolism that will impinge on the metabolic composition of the TME, which in turn specifically affects T cell fitness. Therefore, targeting cancer or T cell metabolism could increase the efficacy and specificity of existing immunotherapies, improving disease outcome and minimizing adverse reactions.

Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types

Studies describing the expression patterns and biomarkers for the tumoral process increase in number every year. The availability of new datasets, although essential, also creates a confusing landscape where common or critical mechanisms are obscured amidst the divergent and heterogeneous nature of such results. In this work, we manually curated the Gene Expression Omnibus using rigorous filtering criteria to select the most homogeneous and highest quality microarray and RNA-seq datasets from multiple types of cancer. By applying systems biology approaches, combined with machine learning analysis, we investigated possible frequently deregulated molecular mechanisms underlying the tumoral process. Our multi-approach analysis of 99 curated datasets, composed of 5,406 samples, revealed 47 differentially expressed genes in all analyzed cancer types, which were all in agreement with the validation using TCGA data. Results suggest that the tumoral process is more related to the overexpression of core deregulated machinery than the underexpression of a given gene set. Additionally, we identified gene expression similarities between different cancer types not described before and performed an overall survival analysis using 20 cancer types. Finally, we were able to suggest a core regulatory mechanism that could be frequently deregulated.

Phase I study of liposomal irinotecan in patients with metastatic breast cancer: findings from the expansion phase

Purpose

Metastatic breast cancer (mBC) remains incurable and is associated with low survival rates. This study assessed the efficacy and safety of liposomal irinotecan in heavily pretreated patients with mBC, with or without active brain metastases (BM).

Methods

Following the dose escalation phase and determination of recommended phase 2 dose, the expansion phase of this phase I, open-label, non-randomized study, assigned adult women to cohorts based on mBC subtype: cohort 1, hormone receptor +/human epidermal growth factor receptor 2−; cohort 2, triple-negative breast cancer; or cohort 3, any mBC subtype with active BM. Patients received liposomal irinotecan 50 or 70 mg/m² free base every 2 weeks. Here, we report secondary outcomes including best overall response (BOR), objective response rate (ORR), and treatment-emergent adverse events (TEAEs).

Results

For non-central nervous system (non-CNS) disease across all cohorts (intent-to-treat population, N = 29), the ORR was 34.5% (95% confidence interval: 17.94–54.33), with a BOR of partial response in 10 patients (34.5%), stable disease in five (17.2%), progressive disease in 10 (34.5%); four patients were unevaluable (13.8%). The ORR for the CNS cohort was 30.0% (95% confidence interval: 6.67–65.25) using modified Response Evaluation Criteria in Solid Tumors. Common grade 3 or higher TEAEs were diarrhea (27.6%), nausea (17.2%), fatigue (13.8%), asthenia (10.3%), and hypokalemia (10.3%). Serious treatment-related TEAEs were reported in six patients (20.7%). No treatment-related TEAEs resulted in death.

Conclusions

Liposomal irinotecan monotherapy demonstrated antitumor activity in heavily pretreated patients with mBC, with or without BM. The observed safety profile was consistent with that in previous studies.

Clinical trial registration: Trial registration ID NCT01770353.

Electronic supplementary material

The online version of this article (10.1007/s10549-020-05995-7) contains supplementary material, which is available to authorized users.

Screening detects a myriad of breast disease - refining practice will increase effectiveness and reduce harm

For many individuals, the term 'cancer' equates to a disease that if untreated will progress, spread from the area initially affected and ultimately cause death. 'Breast cancer', however, is a diverse of range of pathological entities, incorporating indolent to fast-growing and aggressive lesions, with varying histological patterns, clinical presentations, treatment responses and outcomes. Screening for malignancy is based on the assumption that cancer has a gradual, orderly progression and that detecting lesions earlier in their natural history, and intervening, will reduce mortality. The natural history of epithelial atypia, ductal carcinoma in situ and even invasive breast cancer is poorly understood, but widely variable. We believe that population breast screening methodology needs to change to focus on diagnosis of lesions of greatest clinical relevance.

Lipidomic study of cell lines reveals differences between breast cancer subtypes

Breast cancer (BC) is the most prevalent type of cancer in women in western countries. BC mortality has not declined despite early detection by screening, indicating the need for better informed treatment decisions. Therefore, a novel noninvasive diagnostic tool for BC would give the opportunity of subtype-specific treatment and improved prospects for the patients. Heterogeneity of BC tumor subtypes is reflected in the expression levels of enzymes in lipid metabolism. The aim of the study was to investigate whether the subtype defined by the transcriptome is reflected in the lipidome of BC cell lines. A liquid chromatography mass spectrometry (LC-MS) platform was applied to analyze the lipidome of six cell lines derived from human BC cell lines representing different BC subtypes. We identified an increased abundance of triacylglycerols (TG) ≥ C-48 with moderate or multiple unsaturation in fatty acyl chains and down-regulated ether-phosphatidylethanolamines (PE) (C-34 to C-38) in cell lines representing estrogen receptor and progesterone receptor positive tumor subtypes. In a cell line representing HER2-overexpressing tumor subtype an elevated expression of TG (≤ C-46), phosphatidylcholines (PC) and PE containing short-chained (≤ C-16) saturated or monounsaturated fatty acids were observed. Increased abundance of PC ≥ C-40 was found in cell lines of triple negative BC subtype. In addition, differences were detected in lipidomes within these previously defined subtypes. We conclude that subtypes defined by the transcriptome are indeed reflected in differences in the lipidome and, furthermore, potentially biologically relevant differences may exist within these defined subtypes.

R, Bousoik E, Hall R, Barbarino A, Thapa B, Coyle M, Mahdipoor P, Uludağ H. A systematic comparison of lipopolymers for siRNA delivery to multiple breast cancer cell lines: In vitro studies

Small interfering RNA (siRNA) therapy is a promising approach for treatment of a wide range of cancers, including breast cancers that display variable phenotypic features. To explore the general utility of siRNA therapy to control aberrant expression of genes in breast cancer, we conducted a detailed analysis of siRNA delivery and silencing response in vitro in 6 separate breast cancer cell models (MDA-MB-231, MDA-MB-231-KRas-CRM, MCF-7, AU565, MDA-MB-435 and MDA-MB-468 cells). Using lipopolymers for siRNA complexation and delivery, we found a large variation in siRNA delivery efficiency depending on the specific lipopolymer used for siRNA complexation and delivery. Some lipopolymers were effective in all cell types used in this study, indicating the possibility of universal carriers for siRNA therapy. The delivery efficiency for effective lipopolymers was not correlated with dextran uptake in the cells tested, which indicated a receptor-mediated internalization for siRNA complexes with lipopolymers, unlike fluid-phase transfer associated with dextran uptake. Consistent with this, specific inhibitors involved in clathrin- and caveolin-mediated endocytosis significantly (>50%) reduced the internalization of siRNA complexes in all cell types. Using JAK2 and STAT3 silencing in MDA-MB-231 and MDA-MB-468 cells, a general correlation between the uptake and silencing efficiency at the mRNA level was evident, but it appeared that the choice of the target rather than the cell type was more critical for consistent silencing. We conclude that siRNA therapy with lipopolymers can be undertaken in multiple breast cancer cell phenotypes with similar efficiency, indicating the general applicability of non-viral RNAi in clinical management of molecularly heterogeneous breast cancers. STATEMENT OF SIGNIFICANCE: The manuscript investigated the efficacy of siRNA carriers across multiple breast cancer cell lines. The lipopolymeric carriers were capable of delivering effective dose of siRNA to a range of breast cancer cells. Despite some differences in uptake efficiency among cell types, the mechanism of delivery was similar, with CME and CvME significantly involved in the internalization of polyplexes, while fluid-phase endocytosis was not significant. Specific target silencing was correlated to delivery efficiency, but we did notice the presence of lipopolymers that achieved high silencing with minimal siRNA delivery. Silencing specific targets in different cell types were more uniformly achieved as compared to targeting different targets in the same cells. Our studies enhance the feasibility of delivering siRNA to different types of breast cancer cells.

Invasive ductal breast cancer: preoperative predict Ki-67 index based on radiomics of ADC maps

PURPOSE

The purpose of this study is to develop a radiomics model for predicting the Ki-67 proliferation index in patients with invasive ductal breast cancer through magnetic resonance imaging (MRI) preoperatively.

MATERIALS AND METHODS

A total of 128 patients who were clinicopathologically diagnosed with invasive ductal breast cancer were recruited. This cohort included 32 negative Ki67 expression (Ki67 proliferation index < 14%) and 96 cases with positive Ki67 expression (Ki67 proliferation index ≥ 14%). All patients had undergone diffusion-weighted imaging (DWI) MRI before surgery on a 3.0T MRI scanner. Radiomics features were extracted from apparent diffusion coefficient (ADC) maps which were obtained by DWI-MRI from patients with invasive ductal breast cancer. 80% of the patients were divided into training set to build radiomics model, and the rest into test set to evaluate its performance. The least absolute shrinkage and selection operator (LASSO) was used to select radiomics features, and then, the logistic regression (LR) model was established using fivefold cross-validation to predict the Ki-67 index. The performance was evaluated by receiver-operating characteristic (ROC) analysis, accuracy, sensitivity and specificity.

RESULTS

Quantitative imaging features (n = 1029) were extracted from ADC maps, and 11 features were selected to construct the LR model. Good identification ability was exhibited by the ADC-based radiomics model, with areas under the ROC (AUC) values of 0.75 ± 0.08, accuracy of 0.71 in training set and 0.72, 0.70 in test set.

CONCLUSIONS

The ADC-based radiomics model is a feasible predictor for the Ki-67 index in patients with invasive ductal breast cancer. Therefore, we proposed that three-dimensional imaging features from ADC maps could be used as candidate biomarker for preoperative prediction the Ki-67 index noninvasively.

Intratumoral Estrogen Receptor Heterogeneity of Expression in Human Epidermal Growth Factor Receptor 2-Positive Breast Cancer as Evaluated by a Brightfield Multiplex Assay

Breast cancer (BC) is a heterogeneous disease with evolving genetic alterations and expressions of receptor proteins. Intratumoral heterogeneity (ITH) is considered to be a resistance factor in response to targeted therapies. The current single-slide, single-marker immunohistochemistry techniques cannot accurately assess ITH at the individual cancer cell level. In this study, we develop a novel brightfield multiplex assay to simultaneously assess estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) protein markers, together with the HER2 gene and the centromere of chromosome 17 (CEP17) copy numbers, using a single tissue section. The data presented herein demonstrate heterogeneous cancer cell subpopulations in 11 HER2-positive/ER-positive (HER2+/ER+) tumors among 33 BCs analyzed immunohistochemically (HER2 score of 2+ or 3+). The predominant cancer cell subpopulation was HER2+/ER- (50.18%), followed by HER2+/ER+ (39.05%), HER2-/ER+ (4.26%), ER- with HER2 microheterogeneity cancer cells (3.58%), and ER+ with HER2 microheterogeneity cancer cells (2.93%). The three other tumor subtypes, namely, HER2-/ER+, HER2+/ER-, and HER2-/ER-, were more homogeneous, representing 82.59%, 99.22%, and 100% of cancer cells, respectively. This novel assay revealed that HER2+ cancer cells were more predominant than ER+ cancer cells in HER2+/ER+ tumors and provided new insights toward our understanding of BC carcinogenesis.

Low-Frequency Mutational Heterogeneity of Invasive Ductal Carcinoma Subtypes: Information to Direct Precision Oncology

Information regarding the role of low-frequency hotspot cancer-driver mutations (CDMs) in breast carcinogenesis and therapeutic response is limited. Using the sensitive and quantitative Allele-specific Competitor Blocker PCR (ACB-PCR) approach, mutant fractions (MFs) of six CDMs (PIK3CA H1047R and E545K, KRAS G12D and G12V, HRAS G12D, and BRAF V600E) were quantified in invasive ductal carcinomas (IDCs; including ~20 samples per subtype). Measurable levels (i.e., ≥ 1 × 10-5, the lowest ACB-PCR standard employed) of the PIK3CA H1047R, PIK3CA E545K, KRAS G12D, KRAS G12V, HRAS G12D, and BRAF V600E mutations were observed in 34/81 (42%), 29/81 (36%), 51/81 (63%), 9/81 (11%), 70/81 (86%), and 48/81 (59%) of IDCs, respectively. Correlation analysis using available clinicopathological information revealed that PIK3CA H1047R and BRAF V600E MFs correlate positively with maximum tumor dimension. Analysis of IDC subtypes revealed minor mutant subpopulations of critical genes in the MAP kinase pathway (KRAS, HRAS, and BRAF) were prevalent across IDC subtypes. Few triple-negative breast cancers (TNBCs) had appreciable levels of PIK3CA mutation, suggesting that individuals with TNBC may be less responsive to inhibitors of the PI3K/AKT/mTOR pathway. These results suggest that low-frequency hotspot CDMs contribute significantly to the intertumoral and intratumoral genetic heterogeneity of IDCs, which has the potential to impact precision oncology approaches.

Viewing the Eph receptors with a focus on breast cancer heterogeneity

Aberrant expression of different family members of the Eph/ephrin system, which comprises the Eph receptors (Ephs) and their ligands (ephrins), has been implicated in various malignancies including breast cancer. The latter presents as a heterogeneous disease with diverse molecular, morphologic and clinical behavior signatures. This review reflects the existing Eph/ephrin literature while focusing on breast cancer heterogeneity. Hormone positive, HER2 positive and triple negative breast cancer (TNBC) cell lines, xenografts/mutant animal models and patient samples are examined separately as, in humans, they represent entities with differences in prognosis and treatment. EphA2, EphB4 and EphB6 are the members most extensively studied in breast cancer. Existing research points to the potential use of various Eph/ephrin members as biomarkers for assessing prognosis and selecting the most suitable therapeutic strategies in variable clinical scenarios, also for overcoming drug resistance, in the era of breast cancer heterogeneity.