Validity of mouse mammary tumour models for human breast cancer: comparative pathology

In March 1999, a panel of distinguished pathologists was convened by the U.S. National Institutes of Health Breast Cancer Think Tank to develop a classification of breast lesions based on their examination of 39 models of Genetically Engineered Mice (GEM) associated mouse mammary cancer (Cardiff et al., 2000). The meeting, in Annapolis, Maryland, resulted in a published summary report from the Pathology Panel (Cardiff et al., 2000). The Annapolis consensus report, developed from the Panel's deliberations, pointed out that the mammary lesions of GEM were different from most (spontaneous) mouse mammary tumors and could be divided into three distinct categories: (1) lesions that resemble those found in spontaneous mouse mammary tumorigenesis, (2) lesions that have a unique "signature" tumor phenotype that was specific for the transgene, and (3) lesions that resemble those found in human breast diseases (Cardiff et al., 2000). This review emphasizes the proposed nomenclature and the differences between the models and human breast cancer with the intention of stimulating discussion and the development of new models.     

Prognostic tumor microenvironment gene and the relationship with immune infiltration characteristics in metastatic breast cancer

The aim of this study was to reveal genes associated with breast cancer metastasis, to investigate their intrinsic relationship with immune cell infiltration in the tumor microenvironment, and to screen for prognostic biomarkers. Gene expression data of breast cancer patients and their metastases were downloaded from the GEO, TCGA database. R language package was used to screen for differentially expressed genes, enrichment analysis of genes, PPI network construction, and also to elucidate key genes for diagnostic and prognostic survival. Spearman’s r correlation was used to analyze the correlation between key genes and infiltrating immune cells. We screened 25 hub genes, FN1, CLEC5A, ATP8B4, TLR7, LY86, PTGER3 and other genes were differentially expressed in cancer and paraneoplastic tissues. However, patients with higher expression of CD1C, IL-18 breast cancer had a better prognosis in the 10 years survival period, while patients with high expression of FN1, EIF4EBP1 tumors had a worse prognosis. In addition, TP53 and HIF1 genes are closely related to the signaling pathway of breast cancer metastasis. In this study, gene expression of ATP8B4 and CD1C were correlated with cancer tissue infiltration of CD8⁺ T lymphocytes, while GSE43816, GSE62327 and TCGA databases showed that CD8⁺ T lymphocytes were closely associated with breast cancer progression. Functional enrichment analysis of genes based on expression differences yielded key genes of prognostic value in the breast cancer microenvironment.     

Segmentation of confocal microscope images of cell nuclei in thick tissue sections

Segmentation of intact cell nuclei from three-dimensional (3D) images of thick tissue sections is an important basic capability necessary for many biological research studies. However, segmentation is often difficult because of the tight clustering of nuclei in many specimen types. We present a 3D segmentation approach that combines the recognition capabilities of the human visual system with the efficiency of automatic image analysis algorithms. The approach first uses automatic algorithms to separate the 3D image into regions of fluorescence-stained nuclei and unstained background. This includes a novel step, based on the Hough transform and an automatic focusing algorithm to estimate the size of nuclei. Then, using an interactive display, each nuclear region is shown to the analyst, who classifies it as either an individual nucleus, a cluster of multiple nuclei, partial nucleus or debris. Next, automatic image analysis based on morphological reconstruction and the watershed algorithm divides clusters into smaller objects, which are reclassified by the analyst. Once no more clusters remain, the analyst indicates which partial nuclei should be joined to form complete nuclei. The approach was assessed by calculating the fraction of correctly segmented nuclei for a variety of tissue types: Caenorhabditis elegans embryos (839 correct out of a total of 848), normal human skin (343/362), benign human breast tissue (492/525), a human breast cancer cell line grown as a xenograft in mice (425/479) and invasive human breast carcinoma (260/335). Furthermore, due to the analyst's involvement in the segmentation process, it is always known which nuclei in a population are correctly segmented and which not, assuming that the analyst's visual judgement is correct.     

Proteomics analysis of tumor microenvironment: Implications of metabolic and oxidative stresses in tumorigenesis

Tumorigenesis is always concomitant with microenvironmental alterations. The tumor microenvironment is a heterogeneous and complex milieu, which exerts a variety of stresses on tumor cells for proliferation, survival, or death. Recently, accumulated evidence revealed that metabolic and oxidative stresses both play significant roles in tumor development and progression that converge on a common autophagic pathway. Tumor cells display increased metabolic autonomy, and the hallmark is the exploitation of aerobic glycolysis (termed Warburg effect), which increased glucose consumption and decreased oxidative phosphorylation to support growth and proliferation. This characteristic renders cancer cells more aggressive; they devour tremendous amounts of nutrients from microenvironment to result in an ever‐growing appetite for new tumor vessel formation and the release of more “waste,” including key determinants of cell fate like lactate and reactive oxygen species (ROS). The intracellular ROS level of cancer cells can also be modulated by a variety of stimuli in the tumor microenvironment, such as pro‐growth and pro‐inflammatory factors. The intracellular redox state serves as a double‐edged sword in tumor development and progression: ROS overproduction results in cytotoxic effects and might lead to apoptotic cell death, whereas certain level of ROS can act as a second‐messenger for regulation of such cellular processes as cell survival, proliferation, and metastasis. The molecular mechanisms for cancer cell responses to metabolic and oxidative stresses are complex and are likely to involve multiple molecules or signaling pathways. In addition, the expression and modification of these proteins after metabolic or oxidative stress challenge are diverse in different cancer cells and endow them with different functions. Therefore, MS‐based high‐throughput platforms, such as proteomics, are indispensable in the global analysis of cancer cell responses to metabolic and oxidative stress. Herein, we highlight recent advances in the understanding of the metabolic and oxidative stresses associated with tumor progression with proteomics‐based systems biology approaches. © 2012 Wiley Periodicals, Inc., Mass Spec Rev 32:267–311, 2013     

Mammary epithelial stem cells

It has recently been shown that the progeny from a single cell may comprise the epithelial population of a fully developed lactating mammary outgrowth in mice. Serial transplantation of epithelial fragments from this clonally derived gland demonstrates that the subsequently generated outgrowths are also comprised of progeny from the original antecedent. All epithelial cell types were found to be present within these clonal normal populations including luminal, myoepithelial, ductal, and lobule-committed epithelial progenitors and fully competent mammary epithelial stem cells. These observations demonstrate the presence of multipotent tissue-specific epithelial stem cells among the parenchyma of the murine mammary gland. Similarly, genetic analysis of contiguous portions of individual human mammary ducts within the same breast indicates their clonal derivation. Here, we discuss the properties, location, division-potential, senescence, and plasticity associated with mammary epithelial stem cells and present the developing evidence for their presence in human breast and their important role in the risk for breast cancer development. Further, we review the present morphologic and genetic evidence for the characterization of specific stem cell markers and lineage-limited progenitor cells in human and rodent mammary epithelium. Microsc. Res. Tech. 52:190-203, 2001. Published 2001 Wiley-Liss, Inc.     

三维培养结肠癌细胞的微流控芯片荧光成像研究

改良了一种微流控芯片,可用于对结肠癌细胞进行三维培养并实现实时荧光成像。在结肠癌细胞内植入内源性的红色荧光蛋白,使用激光共聚焦显微镜对芯片中三维培养的细胞进行成像。通过细胞内部红色荧光蛋白的表达,可以观测到细胞的生长状态,实现对细胞的实时监测和高分辨率荧光成像。同时,通过免疫荧光染色来表征反映细胞活性的特征蛋白,其荧光强度和蛋白表达呈正相关。研究结果提示,细胞活性相关蛋白的表达受到微环境的影响,其在芯片三维培养中的活性强于二维培养,表明芯片内环境更加接近真实的人体微环境。该方法为进一步探究肿瘤细胞转移机制及相关药物的筛选研究提供了一种新的技术手段及实验平台。     

图像处理和特征分析在评估乳腺癌近期发病风险中的应用

图像处理和特征分析在乳腺癌早期诊断中发挥着重要作用。为了将一个基于左右乳腺X光片图像密度特征不对称性的图像特征分析方法应用于乳腺癌近期发病风险的预测,训练开发了一个以多图像特征相融合的人工智能分辨模型来预测每个妇女在近期(比如,在最近一次的良性检测以后2年之内)由医学影像检测出来的早期癌症的风险程度。介绍这一个新癌症风险预测模型的基本原理,演示一个新型的人机交互式的计算机辅助图像特征分析和计算的工作平台。初步实验证明,应用这一个基于医学图像特征定量分析的模型能够取得比采用现行其他已知的乳腺癌风险因子有着显著提高的对于近期乳腺癌发病风险的预测精度,这将为建立更有效的个性化乳腺癌普查提供依据和帮助。     

The progress of combination therapy with immune checkpoint inhibitors in breast cancer

Immunotherapy targets the dysfunctional immune system to induce cancer cell killing by CD8-positive T cells. Immune checkpoint inhibitors (ICIs), specifically anti-PD-1 antibodies, anti-PD-L1 antibodies, and anti-CTLA4 antibodies, have revolutionized the management of many malignancies due to their significant role in generating a durable clinical response. However, clinical data suggest that response rates to ICI monotherapy are low due to the immunologically silent characteristics of breast cancer (BC). Chemotherapy, surgery, radiotherapy, and targeted therapy were recently reported to alter the tumor microenvironment and enhance the ICI response. Some clinical studies supported that ICIs, in combination with other treatment strategies, show superior efficacy in BC control, especially triple-negative breast cancer. Therefore, seeking a reasonable combination therapy is a promising way to improve ICI response. The present review highlights the clinical efficacy of ICIs treatment options in combination with standard-of-care therapies, such as chemotherapy and targeted therapy.     

Cancer risk related to mammary gland structure and development

The breast undergoes dramatic changes in size, shape, and function in association with growth, reproduction, and post-menopausal regression. Those changes impact women's lifetime breast cancer risk. An early first full-term pregnancy exerts a protective effect, emphasizing the need for understanding the role of reproductive influences on breast development and on cancer initiation and progression, and providing a paradigm for developing preventive strategies based on physiological principles. Even though the cause of breast cancer and the ultimate mechanisms through which an early pregnancy protects from cancer development remain largely unknown, a likely explanation for this protection has been provided by experimental in vivo and in vitro models. These studies have led to the conclusions that cancer initiation requires the interaction of a carcinogen with an undifferentiated and highly proliferating mammary epithelium, whereas differentiation of the mammary gland inhibits carcinogenic initiation. The process of mammary gland differentiation is the result of complex interactions of ovarian, pituitary, and placental hormones, which in turn induce inhibition of cell proliferation, downregulation of estrogen and progesterone receptors, activation of specific genes, such as inhibin, mammary derived growth factor inhibitor and a serpin-like gene, and expression of extracellular matrix proteins in the normal breast. Cell immortalization and transformation are associated with the expression of ferritin H and S100P protein, which serve as markers of cancer initiation. Comparative studies of normal and neoplastic breast development have unraveled similarities with experimental models that validate the extrapolation of findings for testing hypotheses on the initiation and progression of breast cancer.     

3D morphology of cell cultures: a quantitative approach using micrometer synchrotron light tomography

Current issues in both tissue engineering and cell biology deal with cell behavior extensively in 3D. Here, we explore synchrotron radiation micro-computed tomography as a tool for morphological characterization of such 3D cellular constructs, providing micrometer resolution in soft and hard tissues. Novel image processing techniques allowed quantification of local and global cell distributions, cell density, adhesive cell culture surface, and scaffold geometry. For proof of concept, we applied this technique to characterize the morphology of two cell cultures of different phenotypes, namely human dermal fibroblasts and mouse calvarial osteoblast-like cells, both seeded on a polymer multifilament yarn. From 3D visualizations in these case studies, we saw that the fibroblasts spanned between the yarn filaments and in this way encapsulated the yarn, whereas the osteoblast-like cells lined the filament surfaces and did not span between them. Differences found in cell distribution as a function of distance to the median yarn axis and the closest filament surface, respectively, quantified these qualitative impressions gained from 3D visualizations. Moreover, the volume-normalized adhesive surface differed by one order of magnitude between the two phenotypes. Our approach allows quantitative correlation of local scaffold geometry and cell morphology. It can be used to investigate the influence of cell phenotype as well as various biochemical agents on tissue engineering constructs and the behavior of cells in culture.     

Use of independent component analysis to improve signal‐to‐noise ratio in multi‐probe fluorescence microscopy

In conventional multi‐probe fluorescence microscopy, narrow bandwidth filters on detectors are used to avoid bleed‐through artefacts between probes. The limited bandwidth reduces the signal‐to‐noise ratio of the detection, often severely compromising one or more channels. Herein, we describe a process of using independent component analysis to discriminate the position of different probes using only a dichroic mirror to differentiate the signals directed to the detectors. Independent component analysis was particularly effective in samples where the spatial overlap between the probes is minimal, a very common case in cellular microscopy. This imaging scheme collects nearly all of the emitted light, significantly improving the image signal‐to‐noise ratio. In this study, we focused on the detection of two fluorescence probes used in vivo, NAD(P)H and ANEPPS. The optimal dichroic mirror cutoff frequency was determined with simulations using the probes spectral emissions. A quality factor, defined as the cross‐channel contrast‐to‐noise ratio, was optimized to maximize signals while maintaining spatial discrimination between the probes after independent component analysis post‐processing. Simulations indicate that a ～3 fold increase in signal‐to‐noise ratio using the independent component analysis approach can be achieved over the conventional narrow‐band filtering approach without loss of spatial discrimination. We confirmed this predicted performance from experimental imaging of NAD(P)H and ANEPPS in mouse skeletal muscle, in vivo. For many multi‐probe studies, the increased sensitivity of this ‘full bandwidth’ approach will lead to improved image quality and/or reduced excitation power requirements.     

An automated feedback system with the hybrid model of scoring and classification for solving over-segmentation problems in RNAi high content screening

Background: High content screening (HCS) via automated fluorescence microscopy is a powerful technology for generating cellular images that are rich in phenotypic information. RNA interference is a revolutionary approach for silencing gene expression and has become an important method for studying genes through RNA interference‐induced cellular phenotype analysis. The convergence of the two technologies has led to large‐scale, image‐based studies of cellular phenotypes under systematic perturbations of RNA interference. However, existing high content screening image analysis tools are inadequate to extract content regarding cell morphology from the complex images, thus they limit the potential of genome‐wide RNA interference high content screening screening for simple marker readouts. In particular, over‐segmentation is one of the persistent problems of cell segmentation; this paper describes a new method to alleviate this problem. Methods: To solve the issue of over‐segmentation, we propose a novel feedback system with a hybrid model for automated cell segmentation of images from high content screening. A Hybrid learning model is developed based on three scoring models to capture specific characteristics of over‐segmented cells. Dead nuclei are also removed through a statistical model. Results: Experimental validation showed that the proposed method had 93.7% sensitivity and 94.23% specificity. When applied to a set of images of F‐actin‐stained Drosophila cells, 91.3% of over‐segmented cells were detected and only 2.8% were under‐segmented. Conclusions: The proposed feedback system significantly reduces over‐segmentation of cell bodies caused by over‐segmented nuclei, dead nuclei, and dividing cells. This system can be used in the automated analysis system of high content screening images.     

Exosomes: Key tools for cancer liquid biopsy

Precision medicine is based on the identification of biomarkers of tumor development and progression. Liquid biopsy is at the forefront of the ability to gather diagnostic and prognostic information on tumors, as it can be noninvasively performed prior or during treatment. Liquid biopsy mostly utilizes circulating tumor cells, or free DNA, but also exosomes. The latter are nanovesicles secreted by most cell types, found in any body fluid that deliver proteins, nucleic acids and lipids to nearby and distant cells with a unique homing ability. Exosomes function in signalling between the tumor microenvironment and the rest of the body, promoting metastasis, immune remodelling and drug resistance. Exosomes are emerging as a key tool in precision medicine for cancer liquid biopsy, as they efficiently preserve their biomarker cargo. Moreover, exosomes strongly resemble the parental cell, which can help in assessing the oxidative and metabolic state of the donor cell. In this respect, exosomes represent one of the most promising new tools to fight cancer. This review will discuss the clinical applications of profiling exosomal proteins and lipids by high-throughput proteomics and metabolomics, and nucleic acids by next generation sequencing, as well as how this may allow cancer diagnosis, therapy response monitoring and recurrence detection.     

An engineered microenvironment for multidimensional microscopy of live cells

Multidimensional imaging (MD) of live cells is gaining importance in biomedical research as the commercial availability of confocal, nonlinear optical microscopes, environmental chambers, and specific fluorescence probes grows. One crucial aspect of the MD live cell imaging involves the proper immobilization of cells, which refers to the rapid and sufficient immobilization of cells on the microscope stage, neither disrupting the cellular structure and functions nor affecting the optical properties of the cells and the environments. Conventional cell immobilization methods glue the anchoring cells to coated surfaces, but such methods require centrifugation or extended incubation and are not suitable for cells in suspension. Most of the current three-dimensional (3-D) gels either exhibit unsatisfactory optical properties or have adverse effects on cell functions in culture. Recently, an engineered 3-D microcapsule has been developed that involves the complex coacervation of a positively charged collagen and a negatively charged polymer of 2-hydroxyethyl methacrylate--methacrylic acid--methyl methacrylate (HEMA-MMA-MAA). Hence, confocal imaging of live cells in this engineered 3-D microenvironment was investigated for its optical properties and cellular function compatibility. We report here that this microenvironment facilitates efficient cell immobilization, exhibits good optical properties, and can preserve cellular structures and functions, which will be useful in MD imaging of live cells for various applications.     

Semi-automated imaging system to quantitate estrogen and progesterone receptor immunoreactivity in human breast cancer

A semi‐automated imaging system is described to quantitate estrogen and progesterone receptor immunoreactivity in human breast cancer. The system works for any conventional method of image acquisition using microscopic slides that have been processed for immunohistochemical analysis of the estrogen receptor and progesterone receptor. Estrogen receptor and progesterone receptor immunohistochemical staining produce colorimetric differences in nuclear staining that conventionally have been interpreted manually by pathologists and expressed as percentage of positive tumoral nuclei. The estrogen receptor and progesterone receptor status of human breast cancer represent important prognostic and predictive markers of human breast cancer that dictate therapeutic decisions but their subjective interpretation result in interobserver, intraobserver and fatigue variability. Subjective measurements are traditionally limited to a determination of percentage of tumoral nuclei that show positive immunoreactivity. To address these limitations, imaging algorithms utilizing both colorimetric (RGB) as well as intensity (gray scale) determinations were used to analyze pixels of the acquired image. Image acquisition utilized either scanner or microscope with attached digital or analogue camera capable of producing images with a resolution of 20 pixels /10 μ. Areas of each image were screened and the area of interest richest in tumour cells manually selected for image processing. Images were processed initially by JPG conversion of SVS scanned virtual slides or direct JPG photomicrograph capture. Following image acquisition, images were screened for quality, enhanced and processed. The algorithm‐based values for estrogen receptor and progesterone receptor percentage nuclear positivity both strongly correlated with the subjective measurements (intraclass correlation: 0.77; 95% confidence interval: 0.59, 0.95) yet exhibited no interobserver, intraobserver or fatigue variability. In addition the algorithms provided measurements of nuclear estrogen receptor and progesterone receptor staining intensity (mean, mode and median staining intensity of positive staining nuclei), parameters that subjective review could not assess. Other semi‐automated image analysis systems have been used to measure estrogen receptor and progesterone receptor immunoreactivity but these either have required proprietary hardware or have been based on luminosity differences alone. By contrast our algorithms were independent of proprietary hardware and were based on not just luminosity and colour but also many other imaging features including epithelial pattern recognition and nuclear morphology. These features provide a more accurate, versatile and robust imaging analysis platform that can be fully automated in the near future. Because of all these properties, our semi‐automated imaging system ‘adds value’ as a means of measuring these important nuclear biomarkers of human breast cancer.     

多尺度区域生长与去粘连模型的乳腺细胞分割

乳腺癌已经成为女性最常见的恶性肿瘤,组织切片显微图像的病理分析是诊断的主要手段,细胞的准确分割是病理分析的重要环节。该文提出了一种新的乳腺细胞显微图像的自动分割算法:首先结合小波分解和多尺度区域生长算法分离细胞和背景,实现对细胞的精确定位;然后采用改进的数学形态学对粘连细胞进行一次细分割;接着再采用基于曲率尺度空间(CSS)的角点检测分割算法对粘连细胞进行二次细分割;两次细分割方法构成了一个双策略去粘连模型,保证了去粘连的准确性和鲁棒性。将算法应用到22幅乳腺细胞显微图像上,可以对不同类型的乳腺细胞图像进行全自动分割,有较高的分割灵敏度(0.944±0.024)和特异度(0.937±0.038),且具有较好的普适性。     

Molecular markers and therapeutic targets in ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) of the breast is a premalignant condition which accounts for approximately 20% of all new breast cancers and up to 40% of neoplastic lesions detected by mammographic screening. Since recurrence is common after DCIS treated with breast conservation surgery, there is a need to determine molecular factors that predict recurrence. In parallel with this and with the finding that oestrogen receptor (ER) positive breast cancer can be prevented with anti-oestrogens, there have been recent advances in the understanding of the molecular biology of DCIS. Receptor coexpression in DCIS has been determined largely by immunohistochemistry. Animal models have provided evidence for the signalling pathways involved in the regulation and dysregulation of proliferation and apoptosis in both normal breast and in situ cancer. ER-negative DCIS has been shown to be hormone-independent. Blockade of the pathways involved in cell proliferation in ER-negative DCIS is possible and will be necessary to prevent ER-negative breast cancers if the goal of breast cancer chemoprevention is to be realistically achieved.     

Role of PTX3 and complement modulation in the tumor microenvironment

Pentraxin-3 (PTX3), the prototype of long pentraxins, seems to influence complement system (CS) modulation. PTX3 and CS sustain carcinogenesis, enriching tumor microenvironment (TME) with pro-inflammatory molecules promoting angiogenesis in prostate cancer (PC) and renal cell carcinoma (RCC). Furthermore, cancer cells overexpress complement regulatory proteins, such as CD46, CD55 and CD59, which negatively affect complement pathways for support cancer cells survival. This viewpoint aims to elucidate the ambivalent role of PTX3 and the CS in the context of tumor microenvironment (TME).     

Four-dimensional factor analysis of confocal image sequences (4D-FAMIS) to detect and characterize low copy numbers of human papillomavirus DNA by FISH in HeLa and SiHa cells

Visualization and localization of specific DNA sequences were performed by fluorescence in situ hybridization, confocal laser scanning microscopy (CLSM), and four-dimensional factor analysis of biomedical image sequences (4D-FAMIS). HeLa and SiHa cells containing, respectively 20–50 and 1–2 copies per cell of human papillomavirus (HPV) DNA type 18 and 16 integrated in cellular DNA were used as models. HPV-DNA was identified using DNA probes containing the whole genome of HPV-DNA type 18 or 16, and DNA–DNA hybrids were revealed by alkaline phosphatase and Fast Red. Cell nuclei were counterstained with thiazole orange (TO) or TOTO-iodide. 4D image sequences were obtained using successive dynamic or spectral sequences of images on different optical sections from CLSM. The location of fluorescent signals within the preparations was determined by FAMIS. This original method summarizes image sequences into a reduced number of images called factor images, and curves called factors. Factors estimate different individual physical behaviours in the sequence such as extinction velocity, spectral patterns and depth emission profiles. Factor images correspond to spatial distributions of the different factors. We distinguished between Fast Red and nucleus stainings in HPV-DNA hybridization signals by taking into account differences in their extinction velocities (fluorescence decay rate) or spectral patterns, and in their focus (depth emission profiles). In HeLa cells, factor images showed that Fast-Red-stained targets could be distinguished from nucleus stainings, and were located on different focal planes of the nuclei. In SiHa cells, 4D-FAMIS determined as few as 1–2 copies per cell of HPV-DNA type 16 located in continuous focal planes. Therefore, 4D-FAMIS, together with CLSM, made the detection and characterization of low copy numbers of genes in whole cells possible.