Cancer Cells as Dynamic System – Molecular and Phenotypic Changes During Tumor Formation, Progression and Dissemination

Control of Interleukin-1β Expression by Protein Kinase C and Cyclic Adenosine Monophosphate in Myeloid Leukemia Cells

Dynamic Regulation of 5-Hydroxymethylcytosine At the γ-Globin Promoter During Erythroid Differentiation

With a limiting dilution technique, clones have been established from the human pancreatic adenocarcinoma cell line, HPAF. Phenotypic analysis by a panel of murine monoclonal antibodies demonstrated distinct profiles of antigenic expression between the clones. However, identical isozyme patterns of different clones indicated their common origin from the parental HPAF cells. Two clones, CD11 and CD18, appeared to be arrested at different stages of secretory epithelial cell differentiation. CD11 cells demonstrated many characteristics of a well-differentiated state, including the formation of ductal structures with polarized, long columnar-shaped cells, the presence of secretory granules in the cytoplasm, high DU-PAN-2 antigen expression in nude mouse xenografts, and a longer doubling time (42 h) in tissue culture. In contrast, CD18 cells exhibited characteristics of a poorly differentiated state, including solid nests of isoprismatic cells without luminal spaces and cellular polarization, absence of secretory granules and DU-PAN-2 antigen expression in xenografts, and a shorter doubling time (26 h) in tissue culture. Since no culture systems of normal pancreatic ductal cells are currently available, these two pancreatic adenocarcinoma clones may provide a unique system to study genes and antigens related to pancreatic ductal cell differentiation.

Waddington’s epigenetic landscape, a famous metaphor in developmental biology, depicts how a stem cell progresses from an undifferentiated phenotype to a differentiated one. The concept of “landscape” in the context of dynamical systems theory represents a high-dimensional space, in which each cell phenotype is considered as an “attractor” that is determined by interactions between multiple molecular players, and is buffered against environmental fluctuations. In addition, biological noise is thought to play an important role during these cell-fate decisions and in fact controls transitions between different phenotypes. Here, we discuss the phenotypic transitions in cancer from a dynamical systems perspective and invoke the concept of “cancer attractors”—hidden stable states of the underlying regulatory network that are not occupied by normal cells. Phenotypic transitions in cancer occur at varying levels depending on the context. Using epithelial-to-mesenchymal transition (EMT), cancer stem-like properties, metabolic reprogramming and the emergence of therapy resistance as examples, we illustrate how phenotypic plasticity in cancer cells enables them to acquire hybrid phenotypes (such as hybrid epithelial/mesenchymal and hybrid metabolic phenotypes) that tend to be more aggressive and notoriously resilient to therapies such as chemotherapy and androgen-deprivation therapy. Furthermore, we highlight multiple factors that may give rise to phenotypic plasticity in cancer cells, such as (a) multi-stability or oscillatory behaviors governed by underlying regulatory networks involved in cell-fate decisions in cancer cells, and (b) network rewiring due to conformational dynamics of intrinsically disordered proteins (IDPs) that are highly enriched in cancer cells. We conclude by discussing why a therapeutic approach that promotes “recanalization”, i.e., the exit from “cancer attractors” and re-entry into “normal attractors”, is more likely to succeed rather than a conventional approach that targets individual molecules/pathways.

Therapeutic targeting of tumor vulnerabilities is emerging as a key area of research. This review is focused on exploiting the vulnerabilities of tumor cells and the immune cells in the tumor immune microenvironment (TIME), including tumor hypoxia, tumor acidity, the bidirectional proton-coupled monocarboxylate transporters (MCTs) of lactate, mitochondrial oxidative phosphorylation (OXPHOS), and redox enzymes in the tricarboxylic acid cycle. Cancer cells use glucose for energy even under normoxic conditions. Although cancer cells predominantly rely on glycolysis, many have fully functional mitochondria, suggesting that mitochondria are a vulnerable target organelle in cancer cells. Thus, one key distinction between cancer and normal cell metabolism is metabolic reprogramming. Mitochondria-targeted small molecule inhibitors of OXPHOS inhibit tumor proliferation and growth. Another hallmark of cancer is extracellular acidification due lactate accumulation. Emerging results show that lactate acts as a fuel for mitochondrial metabolism and supports tumor proliferation and growth. Metabolic reprogramming occurs in glycolysis-deficient tumor phenotypes and in kinase-targeted, drug-resistant cancers overexpressing OXPHOS genes. Glycolytic cancer cells located away from the vasculature overexpress MCT4 transporter to prevent overacidification by exporting lactate, and the oxidative cancer cells located near the vasculature express MCT1 transporter to provide energy through incorporation of lactate into the tricarboxylic acid cycle. MCTs are, therefore, a vulnerable target in cancer metabolism. MCT inhibitors exert synthetic lethality in combination with metformin, a weak inhibitor of OXPHOS, in cancer cells. Simultaneously targeting multiple vulnerabilities within mitochondria shows synergistic antiproliferative and antitumor effects. Developing tumor-selective, small molecule inhibitors of OXPHOS with a high therapeutic index is critical to fully exploiting the mitochondrial vulnerabilities. We and others developed small-molecule inhibitors containing triphenylphosphonium cation that potently inhibit OXPHOS in tumor cells and tissues. Factors affecting tumor cell vulnerabilities also impact immune cells in the TIME. Glycolytic tumor cells supply lactate to the tumor-suppressing regulatory T cells overexpressing MCTs. Therapeutic opportunities for targeting vulnerabilities in tumor cells and the TIME, as well as the implications on cancer health disparities and cancer treatment, are addressed.

The expression of glial fibrillary acidic protein (GFAP) and vimentin was investigated immunohistochemically in 104 experimental gliomas induced by transplancental application of ethylnitrosourea (ENU) in CDF rats. Immunoreactivity for vimentin was prominent in many astrocytic tumor cells and especially in small glioma cells forming anaplastic medulloblastoma-like foci in many tumors. The majority of tumor cells in oligodendroglial tumors were vimentin negative, except for some of the large polymorphous oligodendrogliomas which contained intermingled vimentin positive glioma cells. GFAP immunoreactivity was detectable only in a low fraction of tumor astrocytes and in a few exceptional cases some oligodendroglial tumor cells stained positive. Immunohistochemistry with antibodies against neurofilaments and cytokeratins revealed no staining in tumor cells of ENU-induced gliomas, while all oligodendrogliomatous tumors stained positive for HNK-1. Immunocytological and immunoblot investigations of the two rat glioma cell clones RG2 and F98, which are both derived from ENU-induced gliomas, showed a prominent expression of vimentin in monolayer cultures and in syngeneic intracerebral transplantation tumors. F98 additionally demonstrated a fraction of GFAP positive cells especially in confluent cultures and in intracerebral tumors. RG2, on the other hand, exhibited virtually no GFAP immunoreactivity in culture but showed individual GFAP positive tumor cells in intracerebral tumors. Our results revealed a more precise picture of the cellular differentiation in ENU-induced rat gliomas and in two widely used glioma cell lines. They underline the heterogeneity of experimental rat gliomas which may comprise cells at different stages of differentiation towards oligodendroglial or astroglial phenotype.

Cervical cancer remains a critical global health issue, responsible for over 600,000 new cases and 300,000 deaths annually. Pathological imaging of cervical cancer is a crucial diagnostic tool. However, distinguishing specific areas of cellular differentiation remains challenging because of the lack of clear boundaries between cells at various stages of differentiation. To address the limitations of conventional clinical and deep learning (DL) methods, we developed a mobile attention classification network (MacNet) with multiscale features, aiming to increase the accuracy of differentiation classification and quantitatively analyze cervical cancer cell differentiation. We investigated the application of MacNet for classifying non-background images into 3 stages of cervical cancer differentiation. The feature maps are processed through the Mobile Convolution Neural Network with Mobile Attention (MCMA) module, which integrates mobile convolutional blocks and mobile attention blocks. MacNet harnesses the benefits of the image pyramid structure and self-attention mechanism, enabling multiscale feature extraction and emulation of clinical pathologist analysis. The final prediction is generated by the adaptive fusion module, which aggregates features into a unified output. Comparative evaluations demonstrated that MacNet outperforms existing models. The proposed method achieved the best classification accuracy of 92.34% among all 7 DL-based models. Specifically, the result achieved by MacNet was 2.62% greater than that of Inception Version 3, 7.9% greater than that of vision transformer, 8.08% greater than that of the visual geometry group network, 3.21% greater than that of Densely Connected Convolutional Network, 2.85% greater than that of shifted window transformer (Swin transformer), 5.4% greater than that of Cross Stage Partial DarkNet, and 5.41% greater than that of Residual Neural Network. At the same time, MacNet also achieved superior results in recall, precision, and F1 score. We have proposed a lightweight neural network method that innovatively combines attention mechanisms with convolutional neural networks (CNNs) to efficiently utilize multiscale information from histopathological images. This integration enables the precise quantitative display of different stages of differentiation in cervical cancer. By doing so, our method not only enhances diagnostic accuracy but also provides clinicians with a more effective tool for faster and more reliable diagnosis, representing a significant advancement in the field of pathological imaging.

Northern and slot blot analyses were used to examine the sizes, variability, and changes in amounts of alpha, beta A and beta B inhibin/activin subunit mRNAs following increases in size and during different stages of differentiation or atresia of bovine non-ovulatory follicles. In Study I, a major 1.3-kb band and minor 2.2-, 3.3- and 6.4-kb bands of alpha mRNA; a major 6.4-kb band and minor 2.6 and 4.0-kb bands of beta A; and major 3.5- and 4.6-kb bands of beta B mRNA were detected in total and/or poly(A)+ RNA isolated from pools of small (1-5 mm), medium (6-10 mm), or large (> 10 mm) follicles. In Study II, 18 of 19 follicles had a 1.3-kb alpha mRNA, and amounts of 1.3 kb alpha mRNA increased with follicle size. However, 0 of 19, 9 of 19, and 3 of 19 follicles had 2.2-, 3.3-, and 6.4-kb alpha mRNA bands. In Study III, the ratio of estradiol (E) to progesterone (P) in follicular fluid (FF) was used to separate follicles into the following three stages of differentiation and atresia: estrogen-active (EA; E > P in FF), atretic (P:E = 1-100), and highly atretic (P:E > 100). Total amounts of alpha and beta A mRNAs were 2.4- and 5.8-fold greater in EA follicles compared with small follicles. Alpha and beta A mRNAs and concentration of total inhibin immunoactivity were 4.4-, 9.8- and 1.8-fold lower in highly atretic follicles compared with EA follicles. Changes in amounts of follicular alpha and beta A mRNAs were highly positively correlated with intrafollicular concentrations of E, ratio of E to P, and total inhibin immunoreactivity, but negatively correlated with P. Ratio of amounts of alpha to beta A mRNAs was 3.9- and 6.5-fold greater in small and highly atretic follicles compared with EA follicles. Amounts of beta B subunit mRNAs were unchanged during follicular development and unrelated to changes in follicular concentrations of E, P, or total inhibin immunoactivity. On the basis of these results, we concluded that 1) multiple forms of each inhibin/activin subunit mRNA are expressed in follicular tissue; 2) alpha and beta A subunit mRNAs and inhibin transiently increase; 3) alpha and beta mRNAs are not co-regulated similarly; and 4) beta B mRNA is constitutively expressed during differentiation and atresia of non-ovulatory follicles.

Modulating the activation of hepatic stellate cells: a cunning way for metastatic cells to create a permissive soil for seeding in the liver?

A 43-year-old man underwent surgical removal of L4-L5 nerve root tumor which bulged to the extra and intradural spaces and extended as a dumbbell through the intervertebral foramen. Histological examination showed pleomorphic tumor cells with heavy melanin pigmentation. Most of the tumor cells were immunohistochemically positive for vimentin, S-100 protein and HMB-45 antigen; basic myelin protein was detectable in single tumor cells. Electron-microscopy revealed melanosomes in different stages of differentiation and some characteristics of Schwann cells, such as redundant basal lamina production. Taken together the tumor showed features of histological malignancy and incomplete schwannian differentiation with considerable overlap between melanoma and malignant melanotic schwannoma.

Cancer cells can be distinguished from non-cancer cells by acquired characteristics, often referred to as the hallmarks of cancer. One of these hallmarks is metabolic reprogramming, which is essential to meet energy requirements, synthesise building blocks and maintain the redox balance of rapidly dividing cells. The best-known metabolic adaptation of cancer cells is aerobic glycolysis. This is defined as increased glucose uptake and high glycolysis rates despite the presence of sufficient oxygen. The metabolic characteristics of tumour cells and their microenvironment are considered important for understanding cancer development and treatment resistance, and are of interest as treatment targets. To date, translation of the interesting preclinically observed anticancer effects of glucose metabolism inhibitors into the clinic has not yet been successful. This translation may be supported by the development of tools for characterising metabolic hallmarks in patient tumours. Therefore, the research described in this thesis aimed to improve understanding of glucose metabolism in human tumours through characterisation and modulation of specific metabolic pathways, and by studying metabolic heterogeneity in tumours of cancer patients. <br/><br/>We investigated heterogeneity of glucose uptake in non-small cell lung cancer tumour lesions and heterogeneity of expression patterns of glucose metabolism-related proteins in glioblastoma and high-grade serous ovarian cancer patient tumours. Furthermore, we studied the effects of inhibiting glycogen degradation, alone and in combination with radiotherapy, on glioblastoma cell growth and studied the subsequent intracellular effects. Lastly, we determined outcome of patients with metastatic melanoma experiencing solitary progression after initial response to immune checkpoint inhibition and described the role of local therapy in this setting.

Obesity is a condition characterized by uncontrolled expansion of adipose tissue mass resulting in pathological weight gain. Histone deacetylases (HDACs) have emerged as crucial players in epigenetic regulation of adipocyte metabolism. Previously, we demonstrated that selective inhibition of class I HDACs improves white adipocyte functionality and promotes the browning phenotype of murine mesenchymal stem cells (MSCs) C3H/10T1/2 differentiated to adipocytes. These effects were also observed in db/db and diet induced obesity mouse models and in mice with adipose-selective inactivation of HDAC3, a member of class I HDACs. The molecular basis of class I HDACs action in adipose tissue is not deeply characterized and it is not known whether the effects of their inhibition are exerted on adipocyte precursors or mature adipocytes. Therefore, the aim of the present work was to explore the molecular mechanism of class I HDAC action in adipocytes by evaluating the effects of HDAC3-specific silencing at different stages of differentiation. HDAC3 was silenced in C3H/10T1/2 MSCs at different stages of differentiation to adipocytes. shRNA targeting HDAC3 was used to generate the knock-down model. Proper HDAC3 silencing was assessed by measuring both mRNA and protein levels of mouse HDAC3 via qPCR and western blot, respectively. Mitochondrial DNA content and gene expression were quantified via qPCR. HDAC3 silencing at the beginning of differentiation enhanced adipocyte functionality by amplifying the expression of genes regulating differentiation, oxidative metabolism, browning and mitochondrial activity, starting from 72 h after induction of differentiation and silencing. Insulin signaling was enhanced as demonstrated by increased AKT phosphorylation following HDAC3 silencing. Mitochondrial content/density did not change, while the increased expression of the transcriptional co-activator Ppargc1b suggests the observed phenotype was related to enhanced mitochondrial activity, which was confirmed by increased maximal respiration and proton leak linked to reduced coupling efficiency. Moreover, the expression of pro-inflammatory markers increased with HDAC3 early silencing. To the contrary, no differences in terms of gene expression were found when HDAC3 silencing occurred in terminally differentiated adipocyte. Our data demonstrated that early epigenetic events mediated by class I HDAC inhibition/silencing are crucial to commit adipocyte precursors towards the above-mentioned metabolic phenotype. Moreover, our data suggest that these effects are exerted on adipocyte precursors.

Granulosa cells at different stages of differentiation were collected from ovarian follicles and oviducts during the periovulatory period, and their nuclear DNA content was monitored by flow cytometry to establish their cell cycle characteristics (G0 + G1, S, G2 + M). The proportion of cells in the three phases of the cell cycle varied in characteristics patterns depending upon the time they were collected, before or following ovulation. Granulosa (cumulus) cells recovered from ovulated oocytes were mitotically inactive as shown by the large proportion of cells with a 2C amount of DNA and the absence of cells in S phase. The proportion of granulosa cells in G2 + M decreased when recovery from the oviducts was delayed. In contrast, granulosa (cumulus and/or mural) cells recovered from preovulatory follicles prior to luteinizing hormone (LH) exposure contained a considerable population of cells undergoing DNA synthesis, and a decreased proportion of cells with a 2C DNA content. Our findings indicate that granulosa cells undergo dynamic and characteristics changes in all cell cycle phases during the periovulatory period, within follicular and oviductal environments. Intrafollicular events appear to play a major role in controlling DNA synthesis, proliferation, and related cell cycle events in the granulosa cells. Flow cytometric techniques provide objective and detailed information on the cell cycle characteristics of granulosa cell populations at different stages of differentiation. Elucidation of the mechanisms regulating cell cycle parameters of granulosa cells and their physiological significance thus seems feasible.

NJGCG: A node-based joint Gaussian copula graphical model for gene networks inference across multiple states

Therapy-induced DNA methylation inactivates MCT1 and renders tumor cells vulnerable to MCT4 inhibition.