Spatial EGFR Dynamics and Metastatic Phenotypes Modulated by Upregulated EphB2 and Src Pathways in Advanced Prostate Cancer

A novel pathogenic mutation of MeCP2 impairs chromatin association independent of protein levels

Loss-of-function mutations in MECP2 cause Rett syndrome (RTT), a severe neurological disorder that mainly affects girls. Mutations in MECP2 do occur in males occasionally and typically cause severe encephalopathy and premature lethality. Recently, we identified a missense mutation (c.353G>A, p.Gly118Glu [G118E]), which has never been seen before in MECP2, in a young boy who suffered from progressive motor dysfunction and developmental delay. To determine whether this variant caused the clinical symptoms and study its functional consequences, we established two disease models, including human neurons from patient-derived iPSCs and a knock-in mouse line. G118E mutation partially reduces MeCP2 abundance and its DNA binding, and G118E mice manifest RTT-like symptoms seen in the patient, affirming the pathogenicity of this mutation. Using live-cell and single-molecule imaging, we found that G118E mutation alters MeCP2's chromatin interaction properties in live neurons independently of its effect on protein levels. Here we report the generation and characterization of RTT models of a male hypomorphic variant and reveal new insight into the mechanism by which this pathological mutation affects MeCP2's chromatin dynamics. Our ability to quantify protein dynamics in disease models lays the foundation for harnessing high-resolution single-molecule imaging as the next frontier for developing innovative therapies for RTT and other diseases.

Deciphering the Biology of Circulating Tumor Cells through Single-Cell RNA Sequencing: Implications for Precision Medicine in Cancer

Circulating tumor cells (CTCs) hold unique biological characteristics that directly involve them in hematogenous dissemination. Studying CTCs systematically is technically challenging due to their extreme rarity and heterogeneity and the lack of specific markers to specify metastasis-initiating CTCs. With cutting-edge technology, single-cell RNA sequencing (scRNA-seq) provides insights into the biology of metastatic processes driven by CTCs. Transcriptomics analysis of single CTCs can decipher tumor heterogeneity and phenotypic plasticity for exploring promising novel therapeutic targets. The integrated approach provides a perspective on the mechanisms underlying tumor development and interrogates CTCs interactions with other blood cell types, particularly those of the immune system. This review aims to comprehensively describe the current study on CTC transcriptomic analysis through scRNA-seq technology. We emphasize the workflow for scRNA-seq analysis of CTCs, including enrichment, single cell isolation, and bioinformatic tools applied for this purpose. Furthermore, we elucidated the translational knowledge from the transcriptomic profile of individual CTCs and the biology of cancer metastasis for developing effective therapeutics through targeting key pathways in CTCs.

Recent Advances in Single-Molecule Tracking and Imaging Techniques

Since the early 1990s, single-molecule detection in solution at room temperature has enabled direct observation of single biomolecules at work in real time and under physiological conditions, providing insights into complex biological systems that the traditional ensemble methods cannot offer. In particular, recent advances in single-molecule tracking techniques allow researchers to follow individual biomolecules in their native environments for a timescale of seconds to minutes, revealing not only the distinct pathways these biomolecules take for downstream signaling but also their roles in supporting life. In this review, we discuss various single-molecule tracking and imaging techniques developed to date, with an emphasis on advanced three-dimensional (3D) tracking systems that not only achieve ultrahigh spatiotemporal resolution but also provide sufficient working depths suitable for tracking single molecules in 3D tissue models. We then summarize the observables that can be extracted from the trajectory data. Methods to perform single-molecule clustering analysis and future directions are also discussed.

Ephrin B Activate Src Family Kinases in Fibroblasts Inducing Stromal Remodeling in Prostate Cancer

Simple Summary

Carcinoma associated fibroblasts (CAF) play a critical role in the tumor microenvironment (TME) of prostate cancer (PCa). Ephrin receptors (Eph) and ligands (EFN) have been implicated in distinct types of cancers. Alterations on EphB receptors are frequently found in PCa, but the role of ligands (EFNB1, EFNB2, EFNB3) activation in prostate fibroblasts and consequent effects on PCa is not known. We found increased EFNB ligands in fibroblasts isolated from PCa tissues. In this study, we assessed the effects of elevated stromal EFNB ligands on PCa tumor growth. Increased EFNB1 and EFNB3 expression transformed normal fibroblasts into CAF phenotypes through activation of Src family kinases. The secretome of EFNB-expressing CAF increased PCa cell proliferation and promoted TME remodeling. Overall, EFNB activation in CAF may participate in PCa progression via the release of soluble factors that modulate the surrounding tumor environment, which, in turn, promote prostate tumor growth and invasion.

Abstract

Through stromal-epithelial interactions, carcinoma associated fibroblasts (CAF) play a critical role in tumor growth and progression. Activation of erythrophoyetin-producing human hepatocellular (Eph) receptors has been implicated in cancer. Eph receptor interactions with Ephrin ligands lead to bidirectional signals in the recipient and effector cells. The consequences of continuous reverse Ephrin signaling activation in fibroblasts on prostate cancer (PCa) is unknown. When compared to benign prostate fibroblast, CAF displayed higher expression of Ephrin B1, B2, and B3 ligands (EFNB1, EFNB2, and EFNB3). In this study, we found that continuous activation of EFNB1 and EFNB3 in a benign human prostate stromal cell line (BHPrS1) increased the expression of CAF markers and induced a CAF phenotype. BHPrS1^EFNB1 and BHPrS1^EFNB3 displayed a pro-tumorigenic secretome with multiple effects on neovascularization, collagen deposition, and cancer cell proliferation, overall increasing tumorigenicity of a premalignant prostate epithelial cell line BPH1 and PCa cell line LNCaP, both in vitro and in vivo. Inhibition of Src family kinases (SFK) in BHPrS1^EFNB1 and BHPrS1^EFNB3 suppressed EFNB-induced ɑ-SMA (Alpha-smooth muscle actin) and TN-C (Tenascin-C) in vitro. Our study suggests that acquisition of CAF characteristics via SFK activation in response to increased EFNB ligands could promote carcinogenesis via modulation of TME in PCa.

The Roles of EphB2 in Cancer

The erythropoietin-producing hepatocellular carcinoma (Eph) receptors and their Eph receptor-interacting (ephrin) ligands together constitute a vital cell communication system with diverse roles. Experimental evidence revealed Eph receptor bidirectional signaling with both tumor-promoting and tumor-suppressing activities in different cancer types and surrounding environment. Eph receptor B2 (EphB2), an important member of the Eph receptor family, has been proved to be aberrantly expressed in many cancer types, such as colorectal cancer, gastric cancer and hepatocellular carcinoma, resulting in tumor occurrence and progression. However, there are no reviews focusing on the dual roles of EphB2 in cancer. Thus, in this paper we systematically summarize and discuss the roles of EphB2 in cancer. Firstly, we review the main biological features and the related signaling regulatory mechanisms of EphB2, and then we summarize the roles of EphB2 in cancer through current studies. Finally, we put forward our viewpoint on the future prospects of cancer research focusing on EphB2, especially with regard to the effects of EphB2 on tumor immunity.

Alternative splicing of NF-YA promotes prostate cancer aggressiveness and represents a new molecular marker for clinical stratification of patients

BACKGROUND

Approaches based on expression signatures of prostate cancer (PCa) have been proposed to predict patient outcomes and response to treatments. The transcription factor NF-Y participates to the progression from benign epithelium to both localized and metastatic PCa and is associated with aggressive transcriptional profile. The gene encoding for NF-YA, the DNA-binding subunit of NF-Y, produces two alternatively spliced transcripts, NF-YAs and NF-YAl. Bioinformatic analyses pointed at NF-YA splicing as a key transcriptional signature to discriminate between different tumor molecular subtypes. In this study, we aimed to determine the pathophysiological role of NF-YA splice variants in PCa and their association with aggressive subtypes.

METHODS

Data on the expression of NF-YA isoforms were extracted from the TCGA (The Cancer Genome Atlas) database of tumor prostate tissues and validated in prostate cell lines. Lentiviral transduction and CRISPR-Cas9 technology allowed the modulation of the expression of NF-YA splice variants in PCa cells. We characterized 3D cell cultures through in vitro assays and RNA-seq profilings. We used the rank-rank hypergeometric overlap approach to identify concordant/discordant gene expression signatures of NF-YAs/NF-YAl-overexpressing cells and human PCa patients. We performed in vivo studies in SHO-SCID mice to determine pathological and molecular phenotypes of NF-YAs/NF-YAl xenograft tumors.

RESULTS

NF-YA depletion affects the tumorigenic potential of PCa cells in vitro and in vivo. Elevated NF-YAs levels are associated to aggressive PCa specimens, defined by Gleason Score and TNM classification. NF-YAl overexpression increases cell motility, while NF-YAs enhances cell proliferation in PCa 3D spheroids and xenograft tumors. The transcriptome of NF-YAs-spheroids has an extensive overlap with localized and metastatic human PCa signatures. According to PCa PAM50 classification, NF-YAs transcript levels are higher in LumB, characterized by poor prognosis compared to LumA and basal subtypes. A significant decrease in NF-YAs/NF-YAl ratio distinguishes PCa circulating tumor cells from cancer cells in metastatic sites, consistently with pro-migratory function of NF-YAl. Stratification of patients based on NF-YAs expression is predictive of clinical outcome.

CONCLUSIONS

Altogether, our results indicate that the modulation of NF-YA isoforms affects prostate pathophysiological processes and contributes to cancer-relevant phenotype, in vitro and in vivo. Evaluation of NF-YA splicing may represent a new molecular strategy for risk assessment of PCa patients.

Deep learning-based classification of breast cancer cells using transmembrane receptor dynamics

MOTIVATION

Motions of transmembrane receptors on cancer cell surfaces can reveal biophysical features of the cancer cells, thus providing a method for characterizing cancer cell phenotypes. While conventional analysis of receptor motions in the cell membrane mostly relies on the mean-squared displacement plots, much information is lost when producing these plots from the trajectories. Here we employ deep learning to classify breast cancer cell types based on the trajectories of epidermal growth factor receptor (EGFR). Our model is an artificial neural network trained on the EGFR motions acquired from six breast cancer cell lines of varying invasiveness and receptor status: MCF7 (hormone receptor positive), BT474 (HER2-positive), SKBR3 (HER2-positive), MDA-MB-468 (triple negative, TN), MDA-MB-231 (TN) and BT549 (TN).

RESULTS

The model successfully classified the trajectories within individual cell lines with 83% accuracy and predicted receptor status with 85% accuracy. To further validate the method, epithelial-mesenchymal transition (EMT) was induced in benign MCF10A cells, noninvasive MCF7 cancer cells and highly invasive MDA-MB-231 cancer cells, and EGFR trajectories from these cells were tested. As expected, after EMT induction, both MCF10A and MCF7 cells showed higher rates of classification as TN cells, but not the MDA-MB-231 cells. Whereas deep learning-based cancer cell classifications are primarily based on the optical transmission images of cell morphology and the fluorescence images of cell organelles or cytoskeletal structures, here we demonstrated an alternative way to classify cancer cells using a dynamic, biophysical feature that is readily accessible.

AVAILABILITY AND IMPLEMENTATION

A python implementation of deep learning-based classification can be found at https://github.com/soonwoohong/Deep-learning-for-EGFR-trajectory-classification.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Hydrostatic pressure stabilizes HIF‑1α expression in cancer cells to protect against oxidative damage during metastasis

The tissue microenvironment is known to play a pivotal role in cancer metastasis. Interstitial fluid hydrostatic pressure generally increases along with the rapid growth of malignant tumors. The aim of the present study was to investigate the role and relevant mechanism of elevated hydrostatic pressure in promoting the metastasis of cancer cells. Using a commercial device, Lewis lung cancer (LLC) cells were exposed to 50 mmHg hydrostatic pressure (HP) for 24 h. The survival time and morphology of the cells did not notably change; however, the results from a PCR array revealed the upregulation of numerous metastasis‑promoting genes (Hgf, Cdh11 and Ephb2) and the downregulation of metastasis suppressing genes (Kiss1, Syk and Htatip2). In addition, compared with that in the control, the cells which had undergone exposure to 50 mmHg HP showed significantly higher protein expression level of HIF‑1α and the antioxidant enzymes, SOD1 and SOD2, as well as improved tolerance to oxidative stress (P<0.05 vs. control). Following an intravenous injection of the LLC cells into healthy mice, to induce lung metastasis, it was found that the exposure of the LLC cells to 50 mmHg HP for 24 h, prior to injection into the mice, resulted in higher cell survival/retention in the lungs 24 h later and also resulted in more metastatic tumor lesions 4 weeks later (P<0.05 vs. control). Further investigation is required to confirm the molecular mechanism; however, the results from the present study suggested that elevated interstitial fluid HP in malignant tumors may promote the metastasis of cancer cells by stabilizing HIF‑1α expression to defend against oxidative damage.

Post-Translational Modifications That Drive Prostate Cancer Progression

While a protein primary structure is determined by genetic code, its specific functional form is mostly achieved in a dynamic interplay that includes actions of many enzymes involved in post-translational modifications. This versatile repertoire is widely used by cells to direct their response to external stimuli, regulate transcription and protein localization and to keep proteostasis. Herein, post-translational modifications with evident potency to drive prostate cancer are explored. A comprehensive list of proteome-wide and single protein post-translational modifications and their involvement in phenotypic outcomes is presented. Specifically, the data on phosphorylation, glycosylation, ubiquitination, SUMOylation, acetylation, and lipidation in prostate cancer and the enzymes involved are collected. This type of knowledge is especially valuable in cases when cancer cells do not differ in the expression or mutational status of a protein, but its differential activity is regulated on the level of post-translational modifications. Since their driving roles in prostate cancer, post-translational modifications are widely studied in attempts to advance prostate cancer treatment. Current strategies that exploit the potential of post-translational modifications in prostate cancer therapy are presented.

Novel scaffold hopping of potent benzothiazole and isatin analogues linked to 1,2,3-triazole fragment that mimic quinazoline epidermal growth factor receptor inhibitors: Synthesis, antitumor and mechanistic analyses

A series of benzothiazole/isatin linked to 1,2,3-triazole moiety and terminal sulpha drugs 5a-e and 6a-e were synthesized and evaluated for cytotoxic activity against a panel of cancer cell lines. The novel compounds showed variable IC₅₀ range of activity and some of them were potent compared to reference drug. The promising compounds were subjected as postulated the mimicry proposal for quinazoline-based EGFR inhibitors for their inhibitory profile against EGFR TK enzyme. That data obtained revealed that most of these compounds were potent EGFR TK inhibitors at nanomolar concentrations. Among these, compounds 5a and 5b showed more potent activity on EGFR compared to erlotinib (IC₅₀ 103 and 104 versus 67.6 nM). Based upon the results, molecular docking analysis was performed on EGFR receptor and proved the strong contribution of fragments; benzothiazole, isatin, and triazole to the binding ATP pocket. When these selected compounds 5a and 5b were tested in an HepG2 model, they could effectively inhibited tumor growth, strongly induced cancer cell apoptosis, and suppressed cell cycle progression leading to DNA fragmentation. Well-DMET profile of the most active derivatives was presented and compared to the reference drugs. Taken together, we introduced novel triazole-sulpha drug hybrid for the first time as EGFR inhibitors and the results of our studies indicate that the newly discovered inhibitors have significant potential for anticancer treatment.