Cancer nucleus: morphology and beyond

Mining the interpretable prognostic features from pathological image of intrahepatic cholangiocarcinoma using multi-modal deep learning

BACKGROUND

The advances in deep learning-based pathological image analysis have invoked tremendous insights into cancer prognostication. Still, lack of interpretability remains a significant barrier to clinical application.

METHODS

We established an integrative prognostic neural network for intrahepatic cholangiocarcinoma (iCCA), towards a comprehensive evaluation of both architectural and fine-grained information from whole-slide images. Then, leveraging on multi-modal data, we conducted extensive interrogative approaches to the models, to extract and visualize the morphological features that most correlated with clinical outcome and underlying molecular alterations.

RESULTS

The models were developed and optimized on 373 iCCA patients from our center and demonstrated consistent accuracy and robustness on both internal (n = 213) and external (n = 168) cohorts. The occlusion sensitivity map revealed that the distribution of tertiary lymphoid structures, the geometric traits of the invasive margin, the relative composition of tumor parenchyma and stroma, the extent of necrosis, the presence of the disseminated foci, and the tumor-adjacent micro-vessels were the determining architectural features that impacted on prognosis. Quantifiable morphological vector extracted by CellProfiler demonstrated that tumor nuclei from high-risk patients exhibited significant larger size, more distorted shape, with less prominent nuclear envelope and textural contrast. The multi-omics data (n = 187) further revealed key molecular alterations left morphological imprints that could be attended by the network, including glycolysis, hypoxia, apical junction, mTORC1 signaling, and immune infiltration.

CONCLUSIONS

We proposed an interpretable deep-learning framework to gain insights into the biological behavior of iCCA. Most of the significant morphological prognosticators perceived by the network are comprehensible to human minds.

Characterizing Cellular Physiological States with Three-Dimensional Shape Descriptors for Cell Membranes

The shape of a cell as defined by its membrane can be closely associated with its physiological state. For example, the irregular shapes of cancerous cells and elongated shapes of neuron cells often reflect specific functions, such as cell motility and cell communication. However, it remains unclear whether and which cell shape descriptors can characterize different cellular physiological states. In this study, 12 geometric shape descriptors for a three-dimensional (3D) object were collected from the previous literature and tested with a public dataset of ~400,000 independent 3D cell regions segmented based on fluorescent labeling of the cell membranes in Caenorhabditis elegans embryos. It is revealed that those shape descriptors can faithfully characterize cellular physiological states, including (1) cell division (cytokinesis), along with an abrupt increase in the elongation ratio; (2) a negative correlation of cell migration speed with cell sphericity; (3) cell lineage specification with symmetrically patterned cell shape changes; and (4) cell fate specification with differential gene expression and differential cell shapes. The descriptors established may be used to identify and predict the diverse physiological states in numerous cells, which could be used for not only studying developmental morphogenesis but also diagnosing human disease (e.g., the rapid detection of abnormal cells).

Alterations in the chromatin packaging, driven by transcriptional activity, revealed by AFM

BACKGROUND

The gene expression differs in the nuclei of normal and malignant mammalian cells, and transcription is a critical initial step, which defines the difference. The mechanical properties of transcriptionally active chromatin are still poorly understood. Recently we have probed transcriptionally active chromatin of the nuclei subjected to mechanical stress, by Atomic Force Microscopy (AFM) [1]. Nonetheless, a systematic study of the phenomenon is needed.

METHODS

Nuclei were deformed and studied by AFM. Non-deformed nuclei were studied by fluorescence confocal microscopy. Their transcriptional activity was studied by RNA electrophoresis.

RESULTS

The malignant nuclei under the study were stable to deformation and assembled of 100-300 nm beads-like units, while normal cell nuclei were prone to deformation. The difference in stability to deformation of the nuclei correlated with DNA supercoiling, and transcription-depended units were responsive to supercoils breakage. The inhibitors of the topoisomerases I and II disrupted supercoiling and made the malignant nucleus prone to deformation. Cell nuclei treatment with histone deacetylase inhibitors (HDACIs) preserved the mechanical stability of deformed malignant nuclei and, at the same time, made it possible to observe chromatin decondensation up to 20-60 nm units. The AFM results were supplemented with confocal microscopy and RNA electrophoresis data.

CONCLUSIONS

Self-assembly of transcriptionally active chromatin and its decondensation, driven by DNA supercoiling-dependent rigidity, was visualized by AFM in the mechanically deformed nuclei.

GENERAL SIGNIFICANCE

We demonstrated that supercoiled DNA defines the transcription mechanics, and hypothesized the nuclear mechanics in vivo should depend on the chromatin architecture.

DSFF-GAN: A novel stain transfer network for generating immunohistochemical image of endometrial cancer

Immunohistochemistry (IHC) is a commonly used histological examination technique. Compared to Hematoxylin and Eosin (H&E) staining, it enables the examination of protein expression and localization in tissues, which is valuable for cancer treatment and prognosis assessment, such as the detection and diagnosis of endometrial cancer. However, IHC involves multiple staining steps, is time-consuming and expensive. One potential solution is to utilize deep learning networks to generate corresponding virtual IHC images from H&E images. However, the similarity of the IHC image generated by the existing methods needs to be further improved. In this work, we propose a novel dual-scale feature fusion (DSFF) generative adversarial network named DSFF-GAN, which comprises a cycle structure-color similarity loss, and DSFF block to constrain the model's training process and enhance its stain transfer capability. In addition, our method incorporates labeling information of positive cell regions as prior knowledge into the network to further improve the evaluation metrics. We train and test our model using endometrial cancer and publicly available breast cancer IHC datasets, and compare it with state-of-the-art methods. Compared to previous methods, our model demonstrates significant improvements in most evaluation metrics on both datasets. The research results show that our method further improves the quality of image generation and has potential value for the future clinical application of virtual IHC images.

Nuclear growth and import can be uncoupled

What drives nuclear growth? Studying nuclei assembled in Xenopus egg extract and focusing on importin α/β-mediated nuclear import, we show that, while import is required for nuclear growth, nuclear growth and import can be uncoupled when chromatin structure is manipulated. Nuclei treated with micrococcal nuclease to fragment DNA grew slowly despite exhibiting little to no change in import rates. Nuclei assembled around axolotl chromatin with 20-fold more DNA than Xenopus grew larger but imported more slowly. Treating nuclei with reagents known to alter histone methylation or acetylation caused nuclei to grow less while still importing to a similar extent or to grow larger without significantly increasing import. Nuclear growth but not import was increased in live sea urchin embryos treated with the DNA methylator N-nitrosodimethylamine. These data suggest that nuclear import is not the primary driving force for nuclear growth. Instead, we observed that nuclear blebs expanded preferentially at sites of high chromatin density and lamin addition, whereas small Benzonase-treated nuclei lacking DNA exhibited reduced lamin incorporation into the nuclear envelope. In summary, we report experimental conditions where nuclear import is not sufficient to drive nuclear growth, hypothesizing that this uncoupling is a result of altered chromatin structure.

Measuring Drug Response with Single-Cell Growth Rate Quantification

Intratumoral heterogeneity is a substantial cause of drug resistance development during chemotherapy or other drug treatments for cancer. Therefore, monitoring and measuring cell exposure and response to drugs at the single-cell level are crucial. Previous research suggested that the single-cell growth rate can be used to investigate drug-cell interactions. However, currently established methods for quantifying single-cell growth are limited to isolated or monolayer cells. Here, we introduce a technique that accurately measures both 2D and 3D cell growth rates using label-free ratiometric stimulated Raman scattering (SRS) microscopy. We use deuterated amino acids, leucine, isoleucine, and valine, as tracers and measure the C-D SRS signal from deuterium-labeled proteins and the C-H SRS signal from unlabeled proteins simultaneously to determine the cell growth rate at the single-cell level. The technique offers single-cell level drug sensitivity measurement with a shorter turnaround time (within 12 h) than most traditional assays. The submicrometer resolution of the imaging technique allows us to examine the effects of chemotherapeutic drugs, including kinase inhibitors, mitotic inhibitors, and topoisomerase II inhibitors, on both the cell growth rate and morphology. The capability of quantifying 3D cell growth rates provides insight into a deeper understanding of the cell-drug interaction in the actual tumor environment.

Cytological features of human papillomavirus-infected immature squamous metaplastic cells from cervical intraepithelial neoplasia grade 2

In reflex cytology, the presence of prominent nucleoli in immature metaplastic squamous cells (IM) may be underdiagnosed due to variations in interpretation. The aim of this study is to identify human papillomaviruses (HPVs) that infect IM clusters in cervical intraepithelial neoplasia 2 (CIN2) on Papanicolaou (Pap) smears to determine the cytological features of lesion-derived cells. Thirty-two patients with a simultaneous diagnosis of CIN2 on biopsy and high-grade squamous intraepithelial lesions (HSIL) on cytology as well as with IM clusters on HSIL smears were included. CIN2 tissues and HSIL and IM clusters on Pap smears were isolated by manual microdissection, and HPV types were identified by PCR-based genotyping. The nuclear area within the IM clusters was also measured. The median nuclear area of HPV-negative IM clusters was 48 μm2 , with a coefficient of variation (CV) of 0.20; those of HPV-positive clusters were 66 μm2 and 0.34, respectively. The cut-off values of the nuclear area and CV for HPV positivity were 62 μm2 and 0.25, respectively. IM clusters composed of cells with a nuclear area of more than twice that of neutrophils or cells with a wide variation in nuclear sizes are likely to be neoplastic cells caused by HPV.

Annotation-free learning of a spatio-temporal manifold of the cell life cycle

The cell cycle is a complex biological phenomenon, which plays an important role in many cell biological processes and disease states. Machine learning is emerging to be a pivotal technique for the study of the cell cycle, resulting in a number of available tools and models for the analysis of the cell cycle. Most, however, heavily rely on expert annotations, prior knowledge of mechanisms, and imaging with several fluorescent markers to train their models. Many are also limited to processing only the spatial information in the cell images. In this work, we describe a different approach based on representation learning to construct a manifold of the cell life cycle. We trained our model such that the representations are learned without exhaustive annotations nor assumptions. Moreover, our model uses microscopy images derived from a single fluorescence channel and utilizes both the spatial and temporal information in these images. We show that even with fewer channels and self-supervision, information relevant to cell cycle analysis such as staging and estimation of cycle duration can still be extracted, which demonstrates the potential of our approach to aid future cell cycle studies and in discovery cell biology to probe and understand novel dynamic systems.

Breast tissue analysis using a clinically compatible combined time-resolved fluorescence and diffuse reflectance (TRF-DR) system

OBJECTIVE

This work aims to develop a clinically compatible system that can perform breast tissue analysis in a more time efficient process than conventional histopathological assessment. The potential for such a system to be used in vivo in the operating room or surgical suite to improve patient outcome is investigated.

METHOD

In this work, 80 matched pairs of invasive ductal carcinoma and adjacent normal breast tissue were measured in a combined time-resolved fluorescence and diffuse reflectance (DA) system. Following measurement, the fluorescence intensity of collagen and flavin adenine dinucleotide (FAD); the fluorescence lifetime of collagen, nicotinamide adenine dinucleotide (NADH), and FAD; the DA; absorption coefficient; and reduced scattering coefficient were extracted. Samples then underwent histological processing and H&E staining to classify composition as tumor, fibroglandular, and/or adipose tissue.

RESULTS

Statistically significant differences in the collagen and FAD fluorescence intensity, collagen and FAD fluorescence lifetime, DA, and scattering coefficient were found between each tissue group. The NADH fluorescence lifetime and absorption coefficient were statistically different between the tumor and fibroglandular groups, and the tumor and adipose groups. While many breast tissue analysis studies label fibroglandular and adipose together as "normal" breast tissue, this work indicates that some differences between tumor and fibroglandular tissue are not the same as differences between tumor and adipose tissue. Observations of the reduced scatter coefficient may also indicate further classification to include fibro-adipose may be necessary. Future work would benefit from the additional tissue classification.

CONCLUSION

With observable differences in optical parameters between the three tissue types, this system shows promise as a breast analysis tool in a clinical setting. With further work involving samples of mixed composition, this combined system could potentially be used intraoperatively for rapid margin assessment.

AKT2-mediated nuclear deformation leads to genome instability during epithelial-mesenchymal transition

Nuclear deformation has been observed in some cancer cells for decades, but its underlying mechanism and biological significance remain elusive. To address these questions, we employed human lung cancer A549 cell line as a model in context with transforming growth factor β (TGFβ)-induced epithelial-mesenchymal transition. Here, we report that nuclear deformation induced by TGFβ is concomitant with increased phosphorylation of lamin A at Ser390, defective nuclear lamina and genome instability. AKT2 and Smad3 serve as the downstream effectors for TGFβ to induce nuclear deformation. AKT2 directly phosphorylates lamin A at Ser390, whereas Smad3 is required for AKT2 activation upon TGFβ stimulation. Expression of the lamin A mutant with a substitution of Ser390 to Ala or suppression of AKT2 or Smad3 prevents nuclear deformation and genome instability induced by TGFβ. These findings reveal a molecular mechanism for TGFβ-induced nuclear deformation and establish a role of nuclear deformation in genome instability during epithelial-mesenchymal transition.

Densely Convolutional Spatial Attention Network for nuclei segmentation of histological images for computational pathology

Introduction

Automatic nuclear segmentation in digital microscopic tissue images can aid pathologists to extract high-quality features for nuclear morphometrics and other analyses. However, image segmentation is a challenging task in medical image processing and analysis. This study aimed to develop a deep learning-based method for nuclei segmentation of histological images for computational pathology.

Methods

The original U-Net model sometime has a caveat in exploring significant features. Herein, we present the Densely Convolutional Spatial Attention Network (DCSA-Net) model based on U-Net to perform the segmentation task. Furthermore, the developed model was tested on external multi-tissue dataset - MoNuSeg. To develop deep learning algorithms for well-segmenting nuclei, a large quantity of data are mandatory, which is expensive and less feasible. We collected hematoxylin and eosin-stained image data sets from two hospitals to train the model with a variety of nuclear appearances. Because of the limited number of annotated pathology images, we introduced a small publicly accessible data set of prostate cancer (PCa) with more than 16,000 labeled nuclei. Nevertheless, to construct our proposed model, we developed the DCSA module, an attention mechanism for capturing useful information from raw images. We also used several other artificial intelligence-based segmentation methods and tools to compare their results to our proposed technique.

Results

To prioritize the performance of nuclei segmentation, we evaluated the model's outputs based on the Accuracy, Dice coefficient (DC), and Jaccard coefficient (JC) scores. The proposed technique outperformed the other methods and achieved superior nuclei segmentation with accuracy, DC, and JC of 96.4% (95% confidence interval [CI]: 96.2 - 96.6), 81.8 (95% CI: 80.8 - 83.0), and 69.3 (95% CI: 68.2 - 70.0), respectively, on the internal test data set.

Conclusion

Our proposed method demonstrates superior performance in segmenting cell nuclei of histological images from internal and external datasets, and outperforms many standard segmentation algorithms used for comparative analysis.

Nuclear growth and import can be uncoupled

What drives nuclear growth? Studying nuclei assembled in Xenopus egg extract and focusing on importin α/β-mediated nuclear import, we show that, while nuclear growth depends on nuclear import, nuclear growth and import can be uncoupled. Nuclei containing fragmented DNA grew slowly despite exhibiting normal import rates, suggesting nuclear import itself is insufficient to drive nuclear growth. Nuclei containing more DNA grew larger but imported more slowly. Altering chromatin modifications caused nuclei to grow less while still importing to the same extent or to grow larger without increasing nuclear import. Increasing heterochromatin in vivo in sea urchin embryos increased nuclear growth but not import. These data suggest that nuclear import is not the primary driving force for nuclear growth. Instead, live imaging showed that nuclear growth preferentially occurred at sites of high chromatin density and lamin addition, whereas small nuclei lacking DNA exhibited less lamin incorporation. Our hypothesized model is that lamin incorporation and nuclear growth are driven by chromatin mechanical properties, which depend on and can be tuned by nuclear import.

A dual decoder U-Net-based model for nuclei instance segmentation in hematoxylin and eosin-stained histological images

Even in the era of precision medicine, with various molecular tests based on omics technologies available to improve the diagnosis process, microscopic analysis of images derived from stained tissue sections remains crucial for diagnostic and treatment decisions. Among other cellular features, both nuclei number and shape provide essential diagnostic information. With the advent of digital pathology and emerging computerized methods to analyze the digitized images, nuclei detection, their instance segmentation and classification can be performed automatically. These computerized methods support human experts and allow for faster and more objective image analysis. While methods ranging from conventional image processing techniques to machine learning-based algorithms have been proposed, supervised convolutional neural network (CNN)-based techniques have delivered the best results. In this paper, we propose a CNN-based dual decoder U-Net-based model to perform nuclei instance segmentation in hematoxylin and eosin (H&E)-stained histological images. While the encoder path of the model is developed to perform standard feature extraction, the two decoder heads are designed to predict the foreground and distance maps of all nuclei. The outputs of the two decoder branches are then merged through a watershed algorithm, followed by post-processing refinements to generate the final instance segmentation results. Moreover, to additionally perform nuclei classification, we develop an independent U-Net-based model to classify the nuclei predicted by the dual decoder model. When applied to three publicly available datasets, our method achieves excellent segmentation performance, leading to average panoptic quality values of 50.8%, 51.3%, and 62.1% for the CryoNuSeg, NuInsSeg, and MoNuSAC datasets, respectively. Moreover, our model is the top-ranked method in the MoNuSAC post-challenge leaderboard.

A deep hybrid learning pipeline for accurate diagnosis of ovarian cancer based on nuclear morphology

Nuclear morphological features are potent determining factors for clinical diagnostic approaches adopted by pathologists to analyze the malignant potential of cancer cells. Considering the structural alteration of the nucleus in cancer cells, various groups have developed machine learning techniques based on variation in nuclear morphometric information like nuclear shape, size, nucleus-cytoplasm ratio and various non-parametric methods like deep learning have also been tested for analyzing immunohistochemistry images of tissue samples for diagnosing various cancers. We aim to correlate the morphometric features of the nucleus along with the distribution of nuclear lamin proteins with classical machine learning to differentiate between normal and ovarian cancer tissues. It has already been elucidated that in ovarian cancer, the extent of alteration in nuclear shape and morphology can modulate genetic changes and thus can be utilized to predict the outcome of low to a high form of serous carcinoma. In this work, we have performed exhaustive imaging of ovarian cancer versus normal tissue and developed a dual pipeline architecture that combines the matrices of morphometric parameters with deep learning techniques of auto feature extraction from pre-processed images. This novel Deep Hybrid Learning model, though derived from classical machine learning algorithms and standard CNN, showed a training and validation AUC score of 0.99 whereas the test AUC score turned out to be 1.00. The improved feature engineering enabled us to differentiate between cancerous and non-cancerous samples successfully from this pilot study.

A novel deep learning-based 3D cell segmentation framework for future image-based disease detection

Cell segmentation plays a crucial role in understanding, diagnosing, and treating diseases. Despite the recent success of deep learning-based cell segmentation methods, it remains challenging to accurately segment densely packed cells in 3D cell membrane images. Existing approaches also require fine-tuning multiple manually selected hyperparameters on the new datasets. We develop a deep learning-based 3D cell segmentation pipeline, 3DCellSeg, to address these challenges. Compared to the existing methods, our approach carries the following novelties: (1) a robust two-stage pipeline, requiring only one hyperparameter; (2) a light-weight deep convolutional neural network (3DCellSegNet) to efficiently output voxel-wise masks; (3) a custom loss function (3DCellSeg Loss) to tackle the clumped cell problem; and (4) an efficient touching area-based clustering algorithm (TASCAN) to separate 3D cells from the foreground masks. Cell segmentation experiments conducted on four different cell datasets show that 3DCellSeg outperforms the baseline models on the ATAS (plant), HMS (animal), and LRP (plant) datasets with an overall accuracy of 95.6%, 76.4%, and 74.7%, respectively, while achieving an accuracy comparable to the baselines on the Ovules (plant) dataset with an overall accuracy of 82.2%. Ablation studies show that the individual improvements in accuracy is attributable to 3DCellSegNet, 3DCellSeg Loss, and TASCAN, with the 3DCellSeg demonstrating robustness across different datasets and cell shapes. Our results suggest that 3DCellSeg can serve a powerful biomedical and clinical tool, such as histo-pathological image analysis, for cancer diagnosis and grading.

Nuclear Morphological Abnormalities in Cancer: A Search for Unifying Mechanisms

Irregularities in nuclear shape and/or alterations to nuclear size are a hallmark of malignancy in a broad range of cancer types. Though these abnormalities are commonly used for diagnostic purposes and are often used to assess cancer progression in the clinic, the mechanisms through which they occur are not well understood. Nuclear size alterations in cancer could potentially arise from aneuploidy, changes in osmotic coupling with the cytoplasm, and perturbations to nucleocytoplasmic transport. Nuclear shape changes may occur due to alterations to cell-generated mechanical stresses and/or alterations to nuclear structural components, which balance those stresses, such as the nuclear lamina and chromatin. A better understanding of the mechanisms underlying abnormal nuclear morphology and size may allow the development of new therapeutics to target nuclear aberrations in cancer.

Impact of explicit area scaling on kinetic models involving multiple compartments

BACKGROUND

Computational modelling of cell biological processes is a frequently used technique to analyse the underlying mechanisms and to generally understand the behaviour of these processes in the context of a pathway, network or even the whole cell. The most common technique in this context is the usage of ordinary differential equations that describe the kinetics of the relevant processes in mechanistic detail. Here, it is usually assumed that the content of the cell is well-stirred and thus homogeneous - which is of course an over-simplification, but often worked in the past. However, many processes happen at membranes and thus not in 3D, but in 2D. The scaling of the rates of these processes poses a special problem, if volumes of compartments are changed. They will typically scale with an area, but not with the volume of the involved compartment. However, commonly, this is neglected when setting up models and/or volume scaling also sometimes automatically happens when using modelling software in the field.

RESULTS

Here, we investigate generic as well as specific, realistic cases to find out, how strong the impact of the wrong scaling is for the outcome of simulations. We show that the importance of correct area scaling depends on the architecture of the reaction site and its changes upon volume alterations and it is hard to foresee, if it has a significant impact or not just by looking at the original model set-up. Moreover, scaled rates might exhibit more or less control over the behaviour of the system and therefore, accordingly, incorrect scaling will have more or less influence.

CONCLUSIONS

Working with multi-compartment reactions requires a careful consideration of the correct scaling of the rates when changing the volumes of the involved compartments. The error following incorrect scaling - often done by scaling with the volume of the respective compartments can lead to significant aberrations of model behaviour.

Nuclear Morphology and the Biology of Cancer Cells

BACKGROUND

For more than a century, diagnostic pathologists have used morphologic abnormalities of the nucleus as essential diagnostic features to distinguish benign from malignant cells. These features include nuclear enlargement and increased nuclear-to-cytoplasmic ratio, nuclear membrane irregularities, hyperchromasia, and abnormal chromatin distribution. As our knowledge about the genetic and epigenetic abnormalities of cancer cells has increased in recent decades, the pathophysiologic mechanisms that underlie these morphologic abnormalities remain incompletely understood.

SUMMARY

This review attempts to summarize biologic abnormalities in malignant cells related to these morphologic changes. The molecular anatomy of the nuclear envelope in normal and malignant cells is discussed as well as regulation of nuclear size and shape, regulation of signal transduction pathways by molecules of the nuclear envelope, chromatin distribution, and the effects of HPV infection on dysplastic cells in the uterine cervix. Key Message: Causes of morphologic nuclear abnormalities in malignant cells are likely multifactorial. They probably include mutations, dysregulation of signal transduction pathways, abnormal gene expression patterns, alterations of nuclear envelope proteins and chromatin, and aneuploidy.

Bioinformatics analysis of whole slide images reveals significant neighborhood preferences of tumor cells in Hodgkin lymphoma

In pathology, tissue images are evaluated using a light microscope, relying on the expertise and experience of pathologists. There is a great need for computational methods to quantify and standardize histological observations. Computational quantification methods become more and more essential to evaluate tissue images. In particular, the distribution of tumor cells and their microenvironment are of special interest. Here, we systematically investigated tumor cell properties and their spatial neighborhood relations by a new application of statistical analysis to whole slide images of Hodgkin lymphoma, a tumor arising in lymph nodes, and inflammation of lymph nodes called lymphadenitis. We considered properties of more than 400, 000 immunohistochemically stained, CD30-positive cells in 35 whole slide images of tissue sections from subtypes of the classical Hodgkin lymphoma, nodular sclerosis and mixed cellularity, as well as from lymphadenitis. We found that cells of specific morphology exhibited significantly favored and unfavored spatial neighborhood relations of cells in dependence of their morphology. This information is important to evaluate differences between Hodgkin lymph nodes infiltrated by tumor cells (Hodgkin lymphoma) and inflamed lymph nodes, concerning the neighborhood relations of cells and the sizes of cells. The quantification of neighborhood relations revealed new insights of relations of CD30-positive cells in different diagnosis cases. The approach is general and can easily be applied to whole slide image analysis of other tumor types.

In pathology, histological diagnosis is still challenging, in particular, for tumor diseases. Pathologists diagnose the disease and its stage of development on the basis of evaluation and interpretation of images of tissue sections. The quantification of experimental data to support decisions of diagnosis and prognosis, applying bioinformatics methods, is an important issue. Here, we introduce a new, general approach to analyze tissue images of tumor and non-tumor patients and to evaluate the distribution of tumor cells in the tissue. Moreover, we consider neighborhood relations between immunostained cells of different cell morphology. We focus on a special type of lymph node tumor, the Hodgkin lymphoma, exploring the two main types of the classical Hodgkin lymphoma, the nodular sclerosis and the mixed cellularity, and the non-tumor case, the lymphadenitis, representing an inflammation of the lymph node. We considered more than 400, 000 cells immunohistochemically stained with CD30 in 35 whole slide images of tissue sections. We found that cells of specific morphology exhibited significant relations to cells of certain morphology as spatial nearest neighbor. We could show different neighborhood patterns of CD30-positive cells between tumor and non-tumor. The approach is general and can easily be applied to other tumor types.

Acute Cytotoxic Effects on Morphology and Mechanical Behavior in MCF-7 Induced by TiO2NPs Exposure

The side effects induced by nanoparticle exposure at a cellular level are one of the priority research topics due to the steady increase in the use of nanoparticles (NPs). Recently, the focus on cellular morphology and mechanical behavior is gaining relevance in order to fully understand the cytotoxic mechanisms. In this regard, we have evaluated the morphomechanical alteration in human breast adenocarcinoma cell line (MCF-7) exposed to TiO₂NPs at two different concentrations (25 and 50 µg/mL) and two time points (24 and 48 h). By using confocal and atomic force microscopy, we demonstrated that TiO₂NP exposure induces significant alterations in cellular membrane elasticity, due to actin proteins rearrangement in cytoskeleton, as calculated in correspondence to nuclear and cytoplasmic compartments. In this work, we have emphasized the alteration in mechanical properties of the cellular membrane, induced by nanoparticle exposure.

The nucleoporin ELYS regulates nuclear size by controlling NPC number and nuclear import capacity

How intracellular organelles acquire their characteristic sizes is a fundamental question in cell biology. Given stereotypical changes in nuclear size in cancer, it is important to understand the mechanisms that control nuclear size in human cells. Using a high-throughput imaging RNAi screen, we identify and mechanistically characterize ELYS, a nucleoporin required for post-mitotic nuclear pore complex (NPC) assembly, as a determinant of nuclear size in mammalian cells. ELYS knockdown results in small nuclei, reduced nuclear lamin B2 localization, lower NPC density, and decreased nuclear import. Increasing nuclear import by importin α overexpression rescues nuclear size and lamin B2 import, while inhibiting importin α/β-mediated nuclear import decreases nuclear size. Conversely, ELYS overexpression increases nuclear size, enriches nuclear lamin B2 at the nuclear periphery, and elevates NPC density and nuclear import. Consistent with these observations, knockdown or inhibition of exportin 1 increases nuclear size. Thus, we identify ELYS as a novel positive effector of mammalian nuclear size and propose that nuclear size is sensitive to NPC density and nuclear import capacity.

Transforming Growth Factor-β Promotes Morphomechanical Effects Involved in Epithelial to Mesenchymal Transition in Living Hepatocellular Carcinoma

The epithelial mesenchymal transition (EMT) is a physiological multistep process involving epithelial cells acquiring a mesenchymal-like phenotype. It is widely demonstrated that EMT is linked to tumor progression and metastasis. The transforming growth factor (TGF)-β pathways have been widely investigated, but its role in the hepatocarcinoma EMT is still unclear. While the biochemical pathways have been extensively studied, the alteration of biomechanical behavior correlated to cellular phenotype and motility is not yet fully understood. To better define the involvement of TGF-β1 in the metastatic progression process in different hepatocarcinoma cell lines (HepG2, PLC/PRF/5, HLE), we applied a systematic morphomechanical approach in order to investigate the physical and the structural characteristics. In addition, we evaluated the antitumor effect of LY2157299, a TGF-βR1 kinase inhibitor, from a biomechanical point of view, using Atomic Force and Confocal Microscopy. Our approach allows for validation of biological data, therefore it may be used in the future as a diagnostic tool to be combined with conventional biomolecular techniques.

Persistent Erectile Dysfunction after Discontinuation of 5-Alpha Reductase Inhibitor Therapy in Rats Depending on the Duration of Treatment

Purpose

The current study is aimed to assess whether a longer duration of 5α-reductase inhibitor (5α-RI) exposure was associated with higher rate of permanent erectile dysfunction (ED) in a rat model.

Materials and Methods

Male Sprague-Dawley rats (n=76) were assigned to five groups: (i) normal control group; (ii) dutasteride (0.5 mg/rat/d) for 4-weeks group; (iii) dutasteride for 4-weeks plus 2-weeks of resting group; (iv) dutasteride for 8-weeks group; and (v) dutasteride for 8-weeks plus 2-weeks of resting group. In vivo erectile responses to electrical stimulation, and changes of fibrotic factors and smooth muscle/collagen contents in the corpus cavernosum were evaluated in each group.

Results

Dutasteride administration for 4 and 8 weeks significantly decreased erectile parameters compared with the control group. Reduced erectile responses were recovered during 2 weeks of drug-free time in the 4-week treatment group, but were not in the 8-week group. Protein levels of fibrosis-related factors transforming growth factor (TGF)-β1, TGF-β2, and p-Smad/Smad (Smad 2/3) in the corpus cavernosum showed no significant change after 4 weeks of dutasteride oral administration, but were enhanced after 8 weeks. Dutasteride markedly decreased smooth muscle content and increased collagen after 4 and 8 weeks of use, but no nuclear size changes; however, neither group showed significant improvement in the smooth muscle to collagen ratio after the rest period.

Conclusions

Our study showed that recovery from ED depended on the duration of medication, and administration of dutasteride for more than 8-weeks in rats could result in irreversible ED even after discontinuation of medication.

Advances in the computational and molecular understanding of the prostate cancer cell nucleus

Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that may not be visually perceptible to a pathologist, to the nucleus and its ultrastructural components can precede visual histopathological recognition of cancer. Alterations to nuclear features, such as nuclear size and shape, texture, and spatial architecture, reflect the complex molecular-level changes that occur during oncogenesis. Quantitative nuclear morphometry, a field that uses computational approaches to identify and quantify malignancy-induced nuclear changes, can enable a detailed and objective analysis of the PCa cell nucleus. Recent advances in machine learning-based approaches can now automatically mine data related to these changes to aid in the diagnosis, decision making, and prediction of PCa prognoses. In this review, we use PCa as a case study to connect the molecular-level mechanisms that underlie these nuclear changes to the machine learning computational approaches, bridging the gap between the clinical and computational understanding of PCa. First, we will discuss recent developments to our understanding of the molecular events that drive nuclear alterations in the context of PCa: the role of the nuclear matrix and lamina in size and shape changes, the role of 3-dimensional chromatin organization and epigenetic modifications in textural changes, and the role of the tumor microenvironment in altering nuclear spatial topology. We will then discuss the advances in the applications of machine learning algorithms to automatically segment nuclei in prostate histopathological images, extract nuclear features to aid in diagnostic decision making, and predict potential outcomes, such as biochemical recurrence and survival. Finally, we will discuss the challenges and opportunities associated with translation of the quantitative nuclear morphometry methodology into the clinical space. Ultimately, accurate identification and quantification of nuclear alterations can contribute to the field of nucleomics and has applications for computationally driven precision oncologic patient care.

Nuclear Pores Promote Lethal Prostate Cancer by Increasing POM121-Driven E2F1, MYC, and AR Nuclear Import

Nuclear pore complexes (NPCs) regulate nuclear-cytoplasmic transport, transcription, and genome integrity in eukaryotic cells. However, their functional roles in cancer remain poorly understood. We interrogated the evolutionary transcriptomic landscape of NPC components, nucleoporins (Nups), from primary to advanced metastatic human prostate cancer (PC). Focused loss-of-function genetic screen of top-upregulated Nups in aggressive PC models identified POM121 as a key contributor to PC aggressiveness. Mechanistically, POM121 promoted PC progression by enhancing importin-dependent nuclear transport of key oncogenic (E2F1, MYC) and PC-specific (AR-GATA2) transcription factors, uncovering a pharmacologically targetable axis that, when inhibited, decreased tumor growth, restored standard therapy efficacy, and improved survival in patient-derived pre-clinical models. Our studies molecularly establish a role of NPCs in PC progression and give a rationale for NPC-regulated nuclear import targeting as a therapeutic strategy for lethal PC. These findings may have implications for understanding how NPC deregulation contributes to the pathogenesis of other tumor types.

Nuclear organization mediates cancer-compromised genetic and epigenetic control

Nuclear organization is functionally linked to genetic and epigenetic regulation of gene expression for biological control and is modified in cancer. Nuclear organization supports cell growth and phenotypic properties of normal and cancer cells by facilitating physiologically responsive interactions of chromosomes, genes and regulatory complexes at dynamic three-dimensional microenvironments. We will review nuclear structure/function relationships that include: 1. Epigenetic bookmarking of genes by phenotypic transcription factors to control fidelity and plasticity of gene expression as cells enter and exit mitosis; 2. Contributions of chromatin remodeling to breast cancer nuclear morphology, metabolism and effectiveness of chemotherapy; 3. Relationships between fidelity of nuclear organization and metastasis of breast cancer to bone; 4. Dynamic modifications of higher-order inter- and intra-chromosomal interactions in breast cancer cells; 5. Coordinate control of cell growth and phenotype by tissue-specific transcription factors; 6. Oncofetal epigenetic control by bivalent histone modifications that are functionally related to sustaining the stem cell phenotype; and 7. Noncoding RNA-mediated regulation in the onset and progression of breast cancer. The discovery of components to nuclear organization that are functionally related to cancer and compromise gene expression have the potential for translation to innovative cancer diagnosis and targeted therapy.

Fantastic nuclear envelope herniations and where to find them

Morphological abnormalities of the bounding membranes of the nucleus have long been associated with human diseases from cancer to premature aging to neurodegeneration. Studies over the past few decades support that there are both cell intrinsic and extrinsic factors (e.g. mechanical force) that can lead to nuclear envelope 'herniations', a broad catch-all term that reveals little about the underlying molecular mechanisms that contribute to these morphological defects. While there are many genetic perturbations that could ultimately change nuclear shape, here, we focus on a subset of nuclear envelope herniations that likely arise as a consequence of disrupting physiological nuclear membrane remodeling pathways required to maintain nuclear envelope homeostasis. For example, stalling of the interphase nuclear pore complex (NPC) biogenesis pathway and/or triggering of NPC quality control mechanisms can lead to herniations in budding yeast, which are remarkably similar to those observed in human disease models of early-onset dystonia. By also examining the provenance of nuclear envelope herniations associated with emerging nuclear autophagy and nuclear egress pathways, we will provide a framework to help understand the molecular pathways that contribute to nuclear deformation.

Morphomechanical Alterations Induced by Transforming Growth Factor-β1 in Epithelial Breast Cancer Cells

The Epithelial to mesenchymal transition (EMT) is the process that drives epithelial tumor cells to acquire an invasive phenotype. The role of transforming growth factor-β1 (TGF-β1) in EMT is still debated. We used confocal laser scanning microscopy and scanning force spectroscopy to perform a morphomechanical analysis on epithelial breast cancer cells (MCF-7), comparing them before and after TGF-β1 exogenous stimulation (5 ng/mL for 48 h). After TGF-β1 treatment, loss of cell⁻cell adherence (mainly due to the reduction of E-cadherin expression of about 24%) and disaggregation of actin cortical fibers were observed in treated MCF-7. In addition, TGF-β1 induced an alteration of MCF-7 nuclei morphology as well as a decrease in the Young's modulus, owing to a rearrangement that involved the cytoskeletal networks and the nuclear region. These relevant variations in morphological features and mechanical properties, elicited by TGF-β1, suggested an increased capacity of MCF-7 to migrate, which was confirmed by a wound healing assay. By means of our biophysical approach, we highlighted the malignant progression of breast cancer cells induced by TGF-β1 exposure. We are confirming TGF-β1's role in EMT by means of morphomechanical evidence that could represent a turning point in understanding the molecular mechanisms involved in cancer progression.

Mitotic Gene Bookmarking: An Epigenetic Program to Maintain Normal and Cancer Phenotypes

Reconfiguration of nuclear structure and function during mitosis presents a significant challenge to resume the next cell cycle in the progeny cells without compromising structural and functional identity of the cells. Equally important is the requirement for cancer cells to retain the transformed phenotype, that is, unrestricted proliferative potential, suppression of cell phenotype, and activation of oncogenic pathways. Mitotic gene bookmarking retention of key regulatory proteins that include sequence-specific transcription factors, chromatin-modifying factors, and components of RNA Pol (RNAP) I and II regulatory machineries at gene loci on mitotic chromosomes plays key roles in coordinate control of cell phenotype, growth, and proliferation postmitotically. There is growing recognition that three distinct protein types, mechanistically, play obligatory roles in mitotic gene bookmarking: (i) Retention of phenotypic transcription factors on mitotic chromosomes is essential to sustain lineage commitment; (ii) Select chromatin modifiers and posttranslational histone modifications/variants retain competency of mitotic chromatin for gene reactivation as cells exit mitosis; and (iii) Functional components of RNAP I and II transcription complexes (e.g., UBF and TBP, respectively) are retained on genes poised for reactivation immediately following mitosis. Importantly, recent findings have identified oncogenes that are associated with target genes on mitotic chromosomes in cancer cells. The current review proposes that mitotic gene bookmarking is an extensively utilized epigenetic mechanism for stringent control of proliferation and identity in normal cells and hypothesizes that bookmarking plays a pivotal role in maintenance of tumor phenotypes, that is, unrestricted proliferation and compromised control of differentiation. Mol Cancer Res; 16(11); 1617-24. ©2018 AACR.

Intranuclear and higher-order chromatin organization of the major histone gene cluster in breast cancer

Alterations in nuclear morphology are common in cancer progression. However, the degree to which gross morphological abnormalities translate into compromised higher-order chromatin organization is poorly understood. To explore the functional links between gene expression and chromatin structure in breast cancer, we performed RNA-seq gene expression analysis on the basal breast cancer progression model based on human MCF10A cells. Positional gene enrichment identified the major histone gene cluster at chromosome 6p22 as one of the most significantly upregulated (and not amplified) clusters of genes from the normal-like MCF10A to premalignant MCF10AT1 and metastatic MCF10CA1a cells. This cluster is subdivided into three sub-clusters of histone genes that are organized into hierarchical topologically associating domains (TADs). Interestingly, the sub-clusters of histone genes are located at TAD boundaries and interact more frequently with each other than the regions in-between them, suggesting that the histone sub-clusters form an active chromatin hub. The anchor sites of loops within this hub are occupied by CTCF, a known chromatin organizer. These histone genes are transcribed and processed at a specific sub-nuclear microenvironment termed the major histone locus body (HLB). While the overall chromatin structure of the major HLB is maintained across breast cancer progression, we detected alterations in its structure that may relate to gene expression. Importantly, breast tumor specimens also exhibit a coordinate pattern of upregulation across the major histone gene cluster. Our results provide a novel insight into the connection between the higher-order chromatin organization of the major HLB and its regulation during breast cancer progression.

Feasibility of clinical detection of cervical dysplasia using angle-resolved low coherence interferometry measurements of depth-resolved nuclear morphology

This study sought to establish the feasibility of using in situ depth-resolved nuclear morphology measurements for detection of cervical dysplasia. Forty enrolled patients received routine cervical colposcopy with angle-resolved low coherence interferometry (a/LCI) measurements of nuclear morphology. a/LCI scans from 63 tissue sites were compared to histopathological analysis of co-registered biopsy specimens which were classified as benign, low-grade squamous intraepithelial lesion (LSIL), or high-grade squamous intraepithelial lesion (HSIL). Results were dichotomized as dysplastic (LSIL/HSIL) versus non-dysplastic and HSIL versus LSIL/benign to determine both accuracy and potential clinical utility of a/LCI nuclear morphology measurements. Analysis of a/LCI data was conducted using both traditional Mie theory based processing and a new hybrid algorithm that provides improved processing speed to ascertain the feasibility of real-time measurements. Analysis of depth-resolved nuclear morphology data revealed a/LCI was able to detect a significant increase in the nuclear diameter at the depth bin containing the basal layer of the epithelium for dysplastic versus non-dysplastic and HSIL versus LSIL/Benign biopsy sites (both p < 0.001). Both processing techniques resulted in high sensitivity and specificity (>0.80) in identifying dysplastic biopsies and HSIL. The hybrid algorithm demonstrated a threefold decrease in processing time at a slight cost in classification accuracy. The results demonstrate the feasibility of using a/LCI as an adjunctive clinical tool for detecting cervical dysplasia and guiding the identification of optimal biopsy sites. The faster speed from the hybrid algorithm offers a promising approach for real-time clinical analysis.

Evaluating Nuclear Membrane Irregularity for the Classification of Cervical Squamous Epithelial Cells

Pap test involves searching of morphological changes in cervical squamous epithelial cells by pathologists or cytotechnologists to identify potential cancerous cells in the cervix. Nuclear membrane irregularity is one of the morphological changes of malignancy. This paper proposes two novel techniques for the evaluation of nuclear membrane irregularity. The first technique, namely, penalty-driven smoothing analysis, introduces different penalty values for nuclear membrane contour with different degrees of irregularity. The second technique, which can be subdivided into mean- or median-type residual-based analysis, computes the number of points of nuclear membrane contour that deviates from the mean or median of the nuclear membrane contour. Performance of the proposed techniques was compared to three state-of-the-art techniques, namely, radial asymmetric, shape factor, and rim difference. Friedman and post hoc tests using Holm, Shaffer, and Bergmann procedures returned significant differences for all the three classes, i.e., negative for intraepithelial lesion or malignancy (NILM) versus low grade squamous intraepithelial lesion (LSIL), NILM versus high grade squamous intraepithelial lesion (HSIL), and LSIL versus HSIL when the span value equaled 3 was employed with linear penalty function. When span values equaled 5, 7, and 9, NILM versus LSIL and HSIL showed significant differences regardless of the penalty functions. In addition, the results of penalty-driven smoothing analysis were comparable with those of other state-of-the-art techniques. Residual-based analysis returned significant differences for the comparison among the three diagnostic classes. Findings of this study proved the significance of nuclear membrane irregularity as one of the features to differentiate the different diagnostic classes of cervical squamous epithelial cells.

A Cell-Free Assay Using Xenopus laevis Embryo Extracts to Study Mechanisms of Nuclear Size Regulation

A fundamental question in cell biology is how cell and organelle sizes are regulated. It has long been recognized that the size of the nucleus generally scales with the size of the cell, notably during embryogenesis when dramatic reductions in both cell and nuclear sizes occur. Mechanisms of nuclear size regulation are largely unknown and may be relevant to cancer where altered nuclear size is a key diagnostic and prognostic parameter. In vivo approaches to identifying nuclear size regulators are complicated by the essential and complex nature of nuclear function. The in vitro approach described here to study nuclear size control takes advantage of the normal reductions in nuclear size that occur during Xenopus laevis development. First, nuclei are assembled in X. laevis egg extract. Then, these nuclei are isolated and resuspended in cytoplasm from late stage embryos. After a 30 - 90 min incubation period, nuclear surface area decreases by 20 - 60%, providing a useful assay to identify cytoplasmic components present in late stage embryos that contribute to developmental nuclear size scaling. A major advantage of this approach is the relative facility with which the egg and embryo extracts can be biochemically manipulated, allowing for the identification of novel proteins and activities that regulate nuclear size. As with any in vitro approach, validation of results in an in vivo system is important, and microinjection of X. laevis embryos is particularly appropriate for these studies.

Microfluidic microscopy-assisted label-free approach for cancer screening: automated microfluidic cytology for cancer screening

Each year, about 7-8 million deaths occur due to cancer around the world. More than half of the cancer-related deaths occur in the less-developed parts of the world. Cancer mortality rate can be reduced with early detection and subsequent treatment of the disease. In this paper, we introduce a microfluidic microscopy-based cost-effective and label-free approach for identification of cancerous cells. We outline a diagnostic framework for the same and detail an instrumentation layout. We have employed classical computer vision techniques such as 2D principal component analysis-based cell type representation followed by support vector machine-based classification. Analogous to criminal face recognition systems implemented with help of surveillance cameras, a signature-based approach for cancerous cell identification using microfluidic microscopy surveillance is demonstrated. Such a platform would facilitate affordable mass screening camps in the developing countries and therefore help decrease cancer mortality rate.

Moving Cell Boundaries Drive Nuclear Shaping during Cell Spreading

The nucleus has a smooth, regular appearance in normal cells, and its shape is greatly altered in human pathologies. Yet, how the cell establishes nuclear shape is not well understood. We imaged the dynamics of nuclear shaping in NIH3T3 fibroblasts. Nuclei translated toward the substratum and began flattening during the early stages of cell spreading. Initially, nuclear height and width correlated with the degree of cell spreading, but over time, reached steady-state values even as the cell continued to spread. Actomyosin activity, actomyosin bundles, microtubules, and intermediate filaments, as well as the LINC complex, were all dispensable for nuclear flattening as long as the cell could spread. Inhibition of actin polymerization as well as myosin light chain kinase with the drug ML7 limited both the initial spreading of cells and flattening of nuclei, and for well-spread cells, inhibition of myosin-II ATPase with the drug blebbistatin decreased cell spreading with associated nuclear rounding. Together, these results show that cell spreading is necessary and sufficient to drive nuclear flattening under a wide range of conditions, including in the presence or absence of myosin activity. To explain this observation, we propose a computational model for nuclear and cell mechanics that shows how frictional transmission of stress from the moving cell boundaries to the nuclear surface shapes the nucleus during early cell spreading. Our results point to a surprisingly simple mechanical system in cells for establishing nuclear shapes.

Nuclear size is sensitive to NTF2 protein levels in a manner dependent on Ran binding

Altered nuclear size is associated with many cancers, and determining whether cancer-associated changes in nuclear size contribute to carcinogenesis necessitates an understanding of mechanisms of nuclear size regulation. Although nuclear import rates generally positively correlate with nuclear size, NTF2 levels negatively affect nuclear size, despite the role of NTF2 (also known as NUTF2) in nuclear recycling of the import factor Ran. We show that binding of Ran to NTF2 is required for NTF2 to inhibit nuclear expansion and import of large cargo molecules in Xenopus laevis egg and embryo extracts, consistent with our observation that NTF2 reduces the diameter of the nuclear pore complex (NPC) in a Ran-binding-dependent manner. Furthermore, we demonstrate that ectopic NTF2 expression in Xenopus embryos and mammalian tissue culture cells alters nuclear size. Finally, we show that increases in nuclear size during melanoma progression correlate with reduced NTF2 expression, and increasing NTF2 levels in melanoma cells is sufficient to reduce nuclear size. These results show a conserved capacity for NTF2 to impact on nuclear size, and we propose that NTF2 might be a new cancer biomarker.

A Fuzzy-C-Means-Clustering Approach: Quantifying Chromatin Pattern of Non-Neoplastic Cervical Squamous Cells

Despite the effectiveness of Pap-smear test in reducing the mortality rate due to cervical cancer, the criteria of the reporting standard of the Pap-smear test are mostly qualitative in nature. This study addresses the issue on how to define the criteria in a more quantitative and definite term. A negative Pap-smear test result, i.e. negative for intraepithelial lesion or malignancy (NILM), is qualitatively defined to have evenly distributed, finely granular chromatin in the nuclei of cervical squamous cells. To quantify this chromatin pattern, this study employed Fuzzy C-Means clustering as the segmentation technique, enabling different degrees of chromatin segmentation to be performed on sample images of non-neoplastic squamous cells. From the simulation results, a model representing the chromatin distribution of non-neoplastic cervical squamous cell is constructed with the following quantitative characteristics: at the best representative sensitivity level 4 based on statistical analysis and human experts' feedbacks, a nucleus of non-neoplastic squamous cell has an average of 67 chromatins with a total area of 10.827 μm2; the average distance between the nearest chromatin pair is 0.508 μm and the average eccentricity of the chromatin is 0.47.

Chromatin interaction analysis reveals changes in small chromosome and telomere clustering between epithelial and breast cancer cells

Background

Higher-order chromatin structure is often perturbed in cancer and other pathological states. Although several genetic and epigenetic differences have been charted between normal and breast cancer tissues, changes in higher-order chromatin organization during tumorigenesis have not been fully explored. To probe the differences in higher-order chromatin structure between mammary epithelial and breast cancer cells, we performed Hi-C analysis on MCF-10A mammary epithelial and MCF-7 breast cancer cell lines.

Results

Our studies reveal that the small, gene-rich chromosomes chr16 through chr22 in the MCF-7 breast cancer genome display decreased interaction frequency with each other compared to the inter-chromosomal interaction frequency in the MCF-10A epithelial cells. Interestingly, this finding is associated with a higher occurrence of open compartments on chr16–22 in MCF-7 cells. Pathway analysis of the MCF-7 up-regulated genes located in altered compartment regions on chr16–22 reveals pathways related to repression of WNT signaling. There are also differences in intra-chromosomal interactions between the cell lines; telomeric and sub-telomeric regions in the MCF-10A cells display more frequent interactions than are observed in the MCF-7 cells.

Conclusions

We show evidence of an intricate relationship between chromosomal organization and gene expression between epithelial and breast cancer cells. Importantly, this work provides a genome-wide view of higher-order chromatin dynamics and a resource for studying higher-order chromatin interactions in two cell lines commonly used to study the progression of breast cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0768-0) contains supplementary material, which is available to authorized users.

Cancer cell migration in 3D tissue: negotiating space by proteolysis and nuclear deformability

Efficient tumor cell invasion into the surrounding desmoplastic stroma is a hallmark of cancer progression and involves the navigation through available small tissue spaces existent within the dense stromal network. Such navigation includes the reciprocal adaptation of the moving tumor cell, including the nucleus as largest and stiffest organelle, to pre-existent or de-novo generated extracellular matrix (ECM) gaps, pores and trails within stromal compartments. Within the context of migration, we briefly summarize physiological and tumor-related changes in ECM geometries as well as tissue proteolysis. We then focus on mechanisms that ensure the successful translocation of a nucleus through a confining pore by cytoskeleton-mediated coupling, as well as regulators of cell and nuclear deformability such as chromatin organization and nuclear lamina expression. In summary, understanding dynamic nuclear mechanics during migration in response to confined space will add to a better conceptual appreciation of cancer invasion and progression.

cPKC regulates interphase nuclear size during Xenopus development

During Xenopus development, increased nuclear cPKC activity and decreased nuclear association of lamins mediate nuclear scaling.

Dramatic changes in cell and nuclear size occur during development and differentiation, and aberrant nuclear size is associated with many disease states. However, the mechanisms that regulate nuclear size are largely unknown. A robust system for investigating nuclear size is early Xenopus laevis development, during which reductions in nuclear size occur without changes in DNA content. To identify cellular factors that regulate nuclear size during development, we developed a novel nuclear resizing assay wherein nuclei assembled in Xenopus egg extract become smaller in the presence of cytoplasmic interphase extract isolated from post-gastrula Xenopus embryos. We show that nuclear shrinkage depends on conventional protein kinase C (cPKC). Increased nuclear cPKC localization and activity and decreased nuclear association of lamins mediate nuclear size reductions during development, and manipulating cPKC activity in vivo during interphase alters nuclear size in the embryo. We propose a model of steady-state nuclear size regulation whereby nuclear expansion is balanced by an active cPKC-dependent mechanism that reduces nuclear size.

Finasteride treatment alters tissue specific androgen receptor expression in prostate tissues

BACKGROUND

Normal and pathologic growth of the prostate is dependent on the synthesis of dihydrotestosterone (DHT) from testosterone by 5α-reductase. Finasteride is a selective inhibitor of 5α-reductase 2, one isozyme of 5α-reductase found in abundance in the human prostate. The objective of this study was to investigate the effects of finasteride on androgen receptor expression and tissue morphology in human benign prostatic hyperplasia specimens.

METHODS

Patients undergoing transurethral resection of the prostate and either treated or not treated with finasteride between 2004 and 2010 at the University of Wisconsin-Hospital were retrospectively identified using an institutional database. Prostate specimens from each patient were triple-stained for androgen receptor, prostate-specific antigen, and basal marker cytokeratin 5. Morphometric analysis was performed using the multispectral imaging, and results were compared between groups of finasteride treated and non-treated patients.

RESULTS

Epithelial androgen receptor but not stromal androgen receptor expression was significantly lower in patients treated with finasteride than in non-treated patients. Androgen receptor-regulated prostate-specific antigen was not significantly decreased in finasteride-treated patients. Significant luminal epithelial atrophy and basal cell hyperplasia were prevalent in finasteride treated patients. Epithelial androgen receptor expression was highly correlated to the level of luminal epithelial atrophy.

CONCLUSIONS

In this study, finasteride decreased the expression of epithelial androgen receptor in a tissue specific manner. The correlation between epithelial androgen receptor and the extent of luminal epithelial atrophy suggests that epithelial androgen receptor may be directly regulating the atrophic effects observed with finasteride treatment.

Cancer diagnosis by nuclear morphometry using spatial information

Methods for extracting quantitative information regarding nuclear morphology from histopathology images have been long used to aid pathologists in determining the degree of differentiation in numerous malignancies. Most methods currently in use, however, employ the naïve Bayes approach to classify a set of nuclear measurements extracted from one patient. Hence, the statistical dependency between the samples (nuclear measurements) is often not directly taken into account. Here we describe a method that makes use of statistical dependency between samples in thyroid tissue to improve patient classification accuracies with respect to standard naïve Bayes approaches. We report results in two sample diagnostic challenges.

Nuclear envelope invaginations and cancer

The nuclear envelope (NE) surrounds the nucleus and separates it from the cytoplasm. The NE is not a passive structural component, but rather contributes to various cellular processes such as genome organization, transcription, signaling, and stress responses. Although the NE is mostly a smooth surface, it also forms invaginations that can reach deep into the nucleoplasm and may even traverse the nucleus completely. Cancer cells are generally characterized by irregularities and invaginations of the NE that are of diagnostic and prognostic significance. In the current chapter, we describe the link between nuclear invaginations and irregularities with cancer and explore possible mechanistic roles they might have in tumorigenesis.

Fractal dimension of chromatin: potential molecular diagnostic applications for cancer prognosis

Fractal characteristics of chromatin, revealed by light or electron microscopy, have been reported during the last 20 years. Fractal features can easily be estimated in digitalized microscopic images and are helpful for diagnosis and prognosis of neoplasias. During carcinogenesis and tumor progression, an increase of the fractal dimension (FD) of stained nuclei has been shown in intraepithelial lesions of the uterine cervix and the anus, oral squamous cell carcinomas or adenocarcinomas of the pancreas. Furthermore, an increased FD of chromatin is an unfavorable prognostic factor in squamous cell carcinomas of the oral cavity and the larynx, melanomas and multiple myelomas. High goodness-of-fit of the regression line of the FD is a favorable prognostic factor in acute leukemias and multiple myelomas. The nucleus has fractal and power-law organization in several different levels, which might in part be interrelated. Some possible relations between modifications of the chromatin organization during carcinogenesis and tumor progression and an increase of the FD of stained chromatin are suggested. Furthermore, increased complexity of the chromatin structure, loss of heterochromatin and a less-perfect self-organization of the nucleus in aggressive neoplasias are discussed.

Sex steroid receptor expression and localization in benign prostatic hyperplasia varies with tissue compartment

Androgens and estrogens, acting via their respective receptors, are important in benign prostatic hyperplasia (BPH). The goals of this study were to quantitatively characterize the tissue distribution and staining intensity of androgen receptor (AR) and estrogen receptor-alpha (ERα), and assess cells expressing both AR and ERα, in human BPH compared to normal prostate. A tissue microarray composed of normal prostate and BPH tissue was used and multiplexed immunohistochemistry was performed to detect AR and ERα. We used a multispectral imaging platform for automated scanning, tissue and cell segmentation and marker quantification. BPH specimens had an increased number of epithelial and stromal cells and increased percentage of epithelium. In both stroma and epithelium, the mean nuclear area was decreased in BPH relative to normal prostate. AR expression and staining intensity in epithelial and stromal cells was significantly increased in BPH compared to normal prostate. ERα expression was increased in BPH epithelium. However, stromal ERα expression and staining intensity was decreased in BPH compared to normal prostate. Double positive (AR and ERα) epithelial cells were more prevalent in BPH, and fewer double negative (AR and ERα) stromal and epithelial negative cells were observed in BPH. These data underscore the importance of tissue layer localization and expression of steroid hormone receptors in the prostate. Understanding the tissue-specific hormone action of androgens and estrogens will lead to a better understanding of mechanisms of pathogenesis in the prostate and may lead to better treatment for BPH.

Epigenetically induced changes in nuclear textural patterns and gelatinase expression in human fibrosarcoma cells

OBJECTIVE

Chromatin texture patterns of tumour cell nuclei can serve as cancer biomarkers, either to define diagnostic classifications or to obtain relevant prognostic information, in a large number of human tumours. Epigenetic mechanisms, mainly DNA methylation and histone post-translational modification, have been shown to influence chromatin packing states, and therefore nuclear texture. The aim of this study was to analyse effects of these two mechanisms on chromatin texture, and also on correlation with gelatinase expression, in human fibrosarcoma tumour cells.

MATERIALS AND METHODS

We investigated effects of DNA hypomethylating agent 5-aza-2'-deoxycytidine (5-azadC) and histone deacetylase inhibitor trichostatin A (TSA) on nuclear textural characteristics of human HT1080 fibrosarcoma cells, evaluated by image cytometry, and expression of gelatinases MMP-2 and MMP-9, two metalloproteinases implicated in cancer progression and metastasis.

RESULTS

5-azadC induced significant variation in chromatin higher order organization, particularly chromatin decondensation, associated with reduction in global DNA methylation, concomitantly with increase in MMP-9, and to a lesser extent, MMP-2 expression. TSA alone did not have any effect on HT1080 cells, but exhibited differential activity when added to cells treated with 5-azadC. When treated with both drugs, nuclei had higher texture abnormalities. In this setting, reduction in MMP-9 expression was observed, whereas MMP-2 expression remained unaffected.

CONCLUSIONS

These data show that hypomethylating drug 5-azadC and histone deacetylase inhibitor TSA were able to induce modulation of higher order chromatin organization and gelatinase expression in human HT1080 fibrosarcoma cells.

The nuclear envelope environment and its cancer connections

Because of the association between aberrant nuclear structure and tumour grade, nuclear morphology is an indispensible criterion in the current pathological assessment of cancer. Components of the nuclear envelope environment have central roles in many aspects of cell function that affect tumour development and progression. As the roles of the nuclear envelope components, including nuclear pore complexes and nuclear lamina, are being deciphered in molecular detail there are opportunities to harness this knowledge for cancer therapeutics and biomarker development. In this Review, we summarize the progress that has been made in our understanding of the nuclear envelope and the implications of changes in this environment for cancer biology.