The role of the cell-cell interactions in cancer progression

Emerging cancer therapies: targeting physiological networks and cellular bioelectrical differences with non-thermal systemic electromagnetic fields in the human body - a comprehensive review

A steadily increasing number of publications support the concept of physiological networks, and how cellular bioelectrical properties drive cell proliferation and cell synchronization. All cells, especially cancer cells, are known to possess characteristic electrical properties critical for physiological behavior, with major differences between normal and cancer cell counterparts. This opportunity can be explored as a novel treatment modality in Oncology. Cancer cells exhibit autonomous oscillations, deviating from normal rhythms. In this context, a shift from a static view of cellular processes is required for a better understanding of the dynamic connections between cellular metabolism, gene expression, cell signaling and membrane polarization as states in constant flux in realistic human models. In oncology, radiofrequency electromagnetic fields have produced sustained responses and improved quality of life in cancer patients with minimal side effects. This review aims to show how non-thermal systemic radiofrequency electromagnetic fields leads to promising therapeutic responses at cellular and tissue levels in humans, supporting this newly emerging cancer treatment modality with early favorable clinical experience specifically in advanced cancer.

2D co-culture model reveals a biophysical interplay between activated fibroblasts and cancer cells

The tumor microenvironment (TME) comprises diverse cell types within an altered extracellular matrix (ECM) and plays a pivotal role in metastasis through intricate cell-cell and cell-ECM interactions. Fibroblasts, as key constituents of the TME, contribute significantly to cancer metastasis through their involvement in matrix deposition and remodeling mechanisms, modulated by their quiescent or activated states. Despite their recognized importance, the precise role of fibroblasts in cancer cell invasion remains incompletely understood. In this study, we investigated the impact of fibroblast activity on cancer cell progression using a 2D co-culture model. Michigan Cancer Foundation-7 (MCF7) breast cancer cells were co-cultured with normal human lung fibroblasts (NHLF), both with and without transforming growth factor β (TGFβ) treatment. Traction force microscopy (TFM) was employed to quantify traction and velocity forces associated with cellular migration. We observed that TGFβ-activated fibroblasts form a distinctive ring around cancer cells in co-culture, with increased traction and tension at the cell island boundary. This force distribution is associated with the localization of force-related proteins at these boundary regions, including vinculin and E-cadherin. Metabolic profiling revealed a strong OXPHOS signal specific to the activated fibroblasts, in contrast to normal fibroblasts, which primarily display migratory behavior and a more heterogeneous pattern of forces and metabolic activity in co-culture. Our findings offer valuable insights into the mechanical forces and metabolic dynamics governing cellular migration in the tumor microenvironment, where our co-culture model could complement in vivo studies and enable researchers to explore specific microenvironmental cues for a deeper understanding of TME mechanisms. STATEMENT OF SIGNIFICANCE: Cancer models mimicking the dynamics of tumor microenvironment (TME) are an ideal tool to study cancer mechanisms and treatment. However, the full understanding of how cancer cells interact with their surroundings and other cells is still unknown. To tackle this, we developed a simple yet effective 2D co-culture model that allows us to control the arrangement of cell cultures precisely and use various imaging techniques to study interactions between cancer cells and fibroblasts. Here we could measure cell movements, force distribution, metabolic activity, and protein localization and interplay those factors in vitro. Our model helps us observe the underlying mechanisms between cancer cells and fibroblasts, contributing to our understanding of the dynamics in the TME.

Exploring the Potential of Enhanced Prognostic Performance of NCCN-IPI in Diffuse Large B-Cell Lymphoma by Integrating Tumor Microenvironment Markers: Stromal FOXC1 and Tumor pERK1/2 Expression

BACKGROUND

FOXC1 and ERK1-2 are proteins implicated in aggressive biological behavior of various malignancies including lymphomas.

MATERIAL AND METHODS

We investigate the additive prognostic value of stromal FOXC1 expression and tumor phosphorylated ERK1-2 (pERK1-2) expression to the established National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI), in 92 diffuse large B-cell lymphoma (DLBCL) cases. Multidimensional analysis using statistics and machine learning (ML) models assessed prognostic value of established clinicopathologic variables with stromal FOXC1 and tumor pERK1-2 expressions.

RESULTS

Both high FOXC1 stroma group and high pERK1-2 tumor group were significantly associated with shorter progression-free survival (PFS) and overall survival (OS) compared with low group (p = 0.015, 0.034 and p = 0.025, 0.025 each respectively). In multivariable analysis, high FOXC1 stromal expression was an independent prognostic factor of OS (p = 0.037). The addition of stromal FOXC1 and tumor pERK1-2 to the NCCN-IPI score significantly improved prediction of time to death compared with NCCN-IPI score alone (Harrell's C-index = 0.801 vs. 0.764; p = 0.030). ML models reconfirmed the addition of stromal FOXC1 expression and tumor pERK1-2 to NCCN-IPI score had the highest C-index (0.952) among combinations. Stromal FOXC1 and tumor pERK1-2 were determinants of DLBCL prognosis, whose addition significantly improved prognostic performance of the NCCN-IPI.

Tackling exosome and nuclear receptor interaction: an emerging paradigm in the treatment of chronic diseases

Nuclear receptors (NRs) function as crucial transcription factors in orchestrating essential functions within the realms of development, host defense, and homeostasis of body. NRs have garnered increased attention due to their potential as therapeutic targets, with drugs directed at NRs demonstrating significant efficacy in impeding chronic disease progression. Consequently, these pharmacological agents hold promise for the treatment and management of various diseases. Accumulating evidence emphasizes the regulatory role of exosome-derived microRNAs (miRNAs) in chronic inflammation, disease progression, and therapy resistance, primarily by modulating transcription factors, particularly NRs. By exploiting inflammatory pathways such as protein kinase B (Akt)/mammalian target of rapamycin (mTOR), nuclear factor kappa-B (NF-κB), signal transducer and activator of transcription 3 (STAT3), and Wnt/β-catenin signaling, exosomes and NRs play a pivotal role in the panorama of development, physiology, and pathology. The internalization of exosomes modulates NRs and initiates diverse autocrine or paracrine signaling cascades, influencing various processes in recipient cells such as survival, proliferation, differentiation, metabolism, and cellular defense mechanisms. This comprehensive review meticulously examines the involvement of exosome-mediated NR regulation in the pathogenesis of chronic ailments, including atherosclerosis, cancer, diabetes, liver diseases, and respiratory conditions. Additionally, it elucidates the molecular intricacies of exosome-mediated communication between host and recipient cells via NRs, leading to immunomodulation. Furthermore, it outlines the implications of exosome-modulated NR pathways in the prophylaxis of chronic inflammation, delineates current limitations, and provides insights into future perspectives. This review also presents existing evidence on the role of exosomes and their components in the emergence of therapeutic resistance.

DNA-Directed Activation of Photocatalytic Labeling at Cell-Cell Contact Sites

Cell-cell interactions govern diverse biological activities, necessitating molecular tools for understanding and regulating these interactions. Photoredox chemistry can detect cell-cell interactions by anchoring photocatalysts on cellular membranes to generate reactive species that tag closely contacting cells. However, the activation of photocatalysts lacks precise spatial resolution for selectively labeling intercellular interfaces. Herein, we report a DNA-based approach to selectively activate photocatalytic reactions at cell-cell contacts. Two cell populations are coated with distinct DNA strands, which interact at intercellular contacts, mediating the site-specific turn-on of a Ru(bpy)3-type photocatalyst. We demonstrate high spatial specificity for intercellular chemical labeling in cultured mammalian cells. Furthermore, as a proof of concept, we activate the dynamic DNA catalyst at cell-cell contacts in response to customized DNA triggers. This study lays the foundation for designing versatile chemical tools with high spatial precision and programmable responsiveness, along with the temporal resolution afforded by photoirradiation, to investigate and manipulate cell-cell interactions.

Shedding Light on Cellular Secrets: A Review of Advanced Optical Biosensing Techniques for Detecting Extracellular Vesicles with a Special Focus on Cancer Diagnosis

In the relentless pursuit of innovative diagnostic tools for cancer, this review illuminates the cutting-edge realm of extracellular vesicles (EVs) and their biomolecular cargo detection through advanced optical biosensing techniques with a primary emphasis on their significance in cancer diagnosis. From the sophisticated domain of nanomaterials to the precision of surface plasmon resonance, we herein examine the diverse universe of optical biosensors, emphasizing their specified applications in cancer diagnosis. Exploring and understanding the details of EVs, we present innovative applications of enhancing and blending signals, going beyond the limits to sharpen our ability to sense and distinguish with greater sensitivity and specificity. Our special focus on cancer diagnosis underscores the transformative potential of optical biosensors in early detection and personalized medicine. This review aims to help guide researchers, clinicians, and enthusiasts into the captivating domain where light meets cellular secrets, creating innovative opportunities in cancer diagnostics.

Design of a Multiparametric Biosensing Platform and Its Validation in a Study on Spontaneous Cell Detachment from Temperature Gradients

This article reports on a bioanalytical sensor device that hosts three different transducer principles: impedance spectroscopy, quartz-crystal microbalance with dissipation monitoring, and the thermal-current-based heat-transfer method. These principles utilize a single chip, allowing one to perform either microbalance and heat transfer measurements in parallel or heat transfer and impedance measurements. When taking specific precautions, the three measurement modalities can even be used truly simultaneously. The probed parameters are distinctly different, so that one may speak about multiparametric or "orthogonal" sensing without crosstalk between the sensing circuits. Hence, this sensor allows one to identify which of these label-free sensing principles performs best for a given bioanalytical application in terms of a high signal amplitude and signal-to-noise ratio. As a proof-of-concept, the three-parameter sensor was validated by studying the spontaneous, collective detachment of eukaryotic cells in the presence of a temperature gradient between the QCM chip and the supernatant liquid. In addition to heat transfer, detachment can also be monitored by the impedance- and QCM-related signals. These features allow for the distinguishing between different yeast strains that differ in their flocculation genes, and the sensor device enables proliferation monitoring of yeast colonies over time.

Cell-cell communication: new insights and clinical implications

Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.

Comprehensive Analysis of Expression and Pathway for CD27 in Esophageal Cancer

CD27 as a marker of memory B cells is belong to the tumor necrosis factor receptor (TNFR) superfamily, CD27 is ligated by CD70, they can co-stimulate T-cell growth and differentiation through their interaction. Uncertainty surrounds CD27's function in esophageal cancer (EC). This study investigated the role of CD27 in the prognosis of EC using the TCGA, cbioportal, linkedomics and GEPIA databases as well as the proliferation assay was applied. CD27 differential expression may be a key factor in the development of EC. different level of CD27 expression in EC has profound impacts on TOR complex, and many kinds of kinase (KIT proto-oncogene receptor tyrosine kinase, transforming growth factor beta receptor 1, and G protein-coupled receptor kinase 3.), as well as the cell membrane, and survival analysis revealed that it had a significant impact on both the overall survival and disease-free survival of EC. CD27 overexpression will suppress the viability of the KYSE150 and TE3 cells. Our findings suggested that the degree of CD27 expression could serve as an esophageal cancer prognosis biomarker.

scHyper: reconstructing cell-cell communication through hypergraph neural networks

Cell-cell communications is crucial for the regulation of cellular life and the establishment of cellular relationships. Most approaches of inferring intercellular communications from single-cell RNA sequencing (scRNA-seq) data lack a comprehensive global network view of multilayered communications. In this context, we propose scHyper, a new method that can infer intercellular communications from a global network perspective and identify the potential impact of all cells, ligand, and receptor expression on the communication score. scHyper designed a new way to represent tripartite relationships, by extracting a heterogeneous hypergraph that includes the source (ligand expression), the target (receptor expression), and the relevant ligand-receptor (L-R) pairs. scHyper is based on hypergraph representation learning, which measures the degree of match between the intrinsic attributes (static embeddings) of nodes and their observed behaviors (dynamic embeddings) in the context (hyperedges), quantifies the probability of forming hyperedges, and thus reconstructs the cell-cell communication score. Additionally, to effectively mine the key mechanisms of signal transmission, we collect a rich dataset of multisubunit complex L-R pairs and propose a nonparametric test to determine significant intercellular communications. Comparing with other tools indicates that scHyper exhibits superior performance and functionality. Experimental results on the human tumor microenvironment and immune cells demonstrate that scHyper offers reliable and unique capabilities for analyzing intercellular communication networks. Therefore, we introduced an effective strategy that can build high-order interaction patterns, surpassing the limitations of most methods that can only handle low-order interactions, thus more accurately interpreting the complexity of intercellular communications.

Basal-epithelial subpopulations underlie and predict chemotherapy resistance in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype, characterized by extensive intratumoral heterogeneity, high metastasis, and chemoresistance, leading to poor clinical outcomes. Despite progress, the mechanistic basis of these aggressive behaviors remains poorly understood. Using single-cell and spatial transcriptome analysis, here we discovered basal epithelial subpopulations located within the stroma that exhibit chemoresistance characteristics. The subpopulations are defined by distinct signature genes that show a frequent gain in copy number and exhibit an activated epithelial-to-mesenchymal transition program. A subset of these genes can accurately predict chemotherapy response and are associated with poor prognosis. Interestingly, among these genes, elevated ITGB1 participates in enhancing intercellular signaling while ACTN1 confers a survival advantage to foster chemoresistance. Furthermore, by subjecting the transcriptional signatures to drug repurposing analysis, we find that chemoresistant tumors may benefit from distinct inhibitors in treatment-naive versus post-NAC patients. These findings shed light on the mechanistic basis of chemoresistance while providing the best-in-class biomarker to predict chemotherapy response and alternate therapeutic avenues for improved management of TNBC patients resistant to chemotherapy.

Navigating the landscapes of spatial transcriptomics: How computational methods guide the way

Spatially resolved transcriptomics has been dramatically transforming biological and medical research in various fields. It enables transcriptome profiling at single-cell, multi-cellular, or sub-cellular resolution, while retaining the information of geometric localizations of cells in complex tissues. The coupling of cell spatial information and its molecular characteristics generates a novel multi-modal high-throughput data source, which poses new challenges for the development of analytical methods for data-mining. Spatial transcriptomic data are often highly complex, noisy, and biased, presenting a series of difficulties, many unresolved, for data analysis and generation of biological insights. In addition, to keep pace with the ever-evolving spatial transcriptomic experimental technologies, the existing analytical theories and tools need to be updated and reformed accordingly. In this review, we provide an overview and discussion of the current computational approaches for mining of spatial transcriptomics data. Future directions and perspectives of methodology design are proposed to stimulate further discussions and advances in new analytical models and algorithms. This article is categorized under: RNA Methods > RNA Analyses in Cells RNA Evolution and Genomics > Computational Analyses of RNA RNA Export and Localization > RNA Localization.

Tunable Cell-Adhesive Surfaces by Surface-Initiated Photoinduced Electron-Transfer-Reversible Addition-Fragmentation Chain-Transfer Polymerization

Cell adhesion involves many interactions between various molecules on the cell membrane (receptors, coreceptors, integrins, etc.) and surfaces or other cells. Cell adhesion plays a crucial role in the analysis of immune response, cancer treatment, tissue engineering, etc. Cell-cell adhesion can be quantified by measuring cell avidity, which defines the total interaction strength of the live cell binding. Typically, those investigations use tailor-made, reusable chips or surfaces onto which cells are cultured to form a monolayer to which other cells can bind. Cell avidity can then be measured by applying a force and quantifying cell-cell bond ruptures. The subsequent cleaning and reactivation of such biochip and biointeractive surfaces often require repeated etching, leading to device damage. Furthermore, it is often of great interest to harvest the cells that remain bound at the end of an avidity experiment for further analysis or use. It is, therefore, advantageous to pursue coating methods that allow tunable cell adhesion. This work presents temperature-switchable poly(di(ethylene glycol) methyl ether methacrylate) brush-based cell-interactive coatings produced by surface-initiated photoinduced electron-transfer reversible addition-fragmentation chain-transfer polymerization. The temperature switch of these brushes was explored by using a quartz crystal microbalance with dissipation monitoring, chemical composition, and physicochemical properties by atom force microscopy, X-ray photoelectron spectroscopy, single-molecule force spectroscopy, and ellipsometry.

microRNAs in exhaled breath condensate for diagnosis of lung cancer in a resource-limited setting: a concise review

Lung cancer is one of the common cancers globally with high mortality and poor prognosis. Most cases of lung cancer are diagnosed at an advanced stage due to limited diagnostic resources. Screening modalities, such as sputum cytology and annual chest radiographs, have not proved sensitive enough to impact mortality. In recent years, annual low-dose computed tomography has emerged as a potential screening tool for early lung cancer detection, but it may not be a feasible option for developing countries. In this context, exhaled breath condensate (EBC) analysis has been evaluated recently as a noninvasive tool for lung cancer diagnosis. The breath biomarkers also have the advantage of differentiating various types and stages of lung cancer. Recent studies have focused more on microRNAs (miRNAs) as they play a key role in tumourigenesis by regulating the cell cycle, metastasis and angiogenesis. In this review, we have consolidated the current published literature suggesting the utility of miRNAs in EBC for the detection of lung cancer.

The Prognosis of Cancer Depends on the Interplay of Autophagy, Apoptosis, and Anoikis within the Tumor Microenvironment

Within the tumor microenvironment, the fight between the immune system and cancer influences tumor transformation. Metastasis formation is an important stage in the progression of cancer. This process is aided by cellular detachment and resistance to anoikis, which are achieved by altering intercellular signaling. Autophagy, specifically pro-survival autophagy, aids cancer cells in developing treatment resistance. Numerous studies have shown that autophagy promotes tumor growth and resistance to anoikis. To regulate protective autophagy, cancer-related genes phosphorylate both pro- and anti-apoptotic proteins. Apoptosis, a type of controlled cell death, eliminates damaged or unwanted cells. Anoikis is a type of programmed cell death in which cells lose contact with the extracellular matrix. The dysregulation of these cellular pathways promotes tumor growth and spread. Apoptosis, anoikis, and autophagy interact meticulously and differently depending on the cellular circumstances. For instance, autophagy can protect cancer cells from apoptosis by removing cellular components that are damaged and might otherwise trigger apoptotic pathways. Similarly, anoikis dysregulation can trigger autophagy by causing cellular harm and metabolic stress. In order to prevent or treat metastatic disease, specifically, targeting these cellular mechanisms may present a promising prospect for cancer therapy. This review discourses the state of our understanding of the molecular and cellular mechanisms underlying tumor transformation and the establishment of metastatic tumors. To enhance the prognosis for cancer, we highlight and discuss potential therapeutic approaches that target these processes and genes involved in them.

Disruptions in cell fate decisions and transformed enteroendocrine cells drive intestinal tumorigenesis in Drosophila

Most epithelial tissues are maintained by stem cells that produce the different cell lineages required for proper tissue function. Constant communication between different cell types ensures precise regulation of stem cell behavior and cell fate decisions. These cell-cell interactions are often disrupted during tumorigenesis, but mechanisms by which they are co-opted to support tumor growth in different genetic contexts are poorly understood. Here, we introduce PromoterSwitch, a genetic platform we established to generate large, transformed clones derived from individual adult Drosophila intestinal stem/progenitor cells. We show that cancer-driving genetic alterations representing common colon tumor genome landscapes disrupt cell fate decisions within transformed tissue and result in the emergence of abnormal cell fates. We also show that transformed enteroendocrine cells, a differentiated, hormone-secreting cell lineage, support tumor growth by regulating intestinal stem cell proliferation through multiple genotype-dependent mechanisms, which represent potential vulnerabilities that could be exploited for therapy.

Role of exosomes in transferring chemoresistance through modulation of cancer glycolytic cell metabolism

Chemoresistance constitute a major obstacle in cancer treatment, leading to limited options and decreased patient survival. Recent studies have revealed a novel mechanism of chemoresistance acquisition: the transfer of information via exosomes, small vesicles secreted by various cells. Exosomes play a crucial role in intercellular communication by carrying proteins, nucleic acids, and metabolites, influencing cancer cell behavior and response to treatment. One crucial mechanism of resistance is cancer metabolic reprogramming, which involves alterations in the cellular metabolic pathways to support the survival and proliferation of drug-resistant cancer cells. This metabolic reprogramming often includes increased glycolysis, providing cancer cells with the necessary energy and building blocks to evade the effects of chemotherapy. Notably, exosomes have been found to transport glycolytic enzymes, as identified in proteomic profiling, leading to the reprogramming of metabolic pathways, facilitating altered glucose metabolism and increased lactate production. As a result, they profoundly impact the tumor microenvironment, promoting tumor progression, survival, immune evasion, and drug resistance.Understanding the complexities of such exosome-mediated cell-to-cell communication might open new therapeutic avenues and facilitate biomarker development in managing cancers characterized by aggressive glycolytic features. Moreover, given the intricate nature of metabolic abnormalities combining future exosome-based-targeted therapies with existing treatments like chemotherapy, immunotherapy, and targeted therapies holds promise for achieving synergistic effects to overcome resistance and improve cancer treatment outcomes.

Transición epitelio – mesenquima y cáncer

Cancer cell migration and invasion are critical components of metastatic disease, the leading cause of death in cancer patients. The epithe-lium-mesenchyme-transition (EMT) and mesenchyme-epithelium-transition (MET) are pathways involved in cancer metastasis. This process involves the degradation of cell-cell and cell-extracellular matrix junctions and the subse-quent loss of regulation of binding proteins such as E-cadherin. Cells undergo a reorganization of the cytoskeleton. These alterations are associated with a change in cell shape from epithelial to mesenchymal morphology. Understand-ing EMT and MET’s molecular and cellular basis provides fundamental insights into cancer etiology and may lead to new therapeutic strategies. In this review, we discuss some of the regulatory mechanisms and pathological role of epitheli-al-mesenchymal plasticity, focusing on the knowledge about the complexity and dynamics of this phenomenon in cancer

Controlling Cell Organization in 3D Coculture Spheroids Using DNA Interactions

The role of stromal and immune cells in transforming the tumor microenvironment is a key consideration in understanding tumor cell behavior and anticancer drug development. To better model these systems in vitro, 3D coculture tumor spheroids have been engineered using a variety of techniques including centrifugation to microwells, hanging drop, low adhesion cultures, and culture of cells in a microfluidic platform. Aside from using bioprinting, however, it has remained more challenging to direct the spatial organization of heterotypic cells in standalone 3D spheroids. To address this, we present an in vitro 3D coculture tumor model where we modulated the interactions between cancer cells and fibroblasts through DNA hybridization. When native heterotypic cells are simply mixed, the cell aggregates typically show cell sorting behavior to form phase separated structures composed of single cell types. In this work, we demonstrate that when MDA-MB-468 breast cancer and NIH/3T3 fibroblasts are directed to associate via complementary DNA, a uniform distribution of the two cell types within a single spheroid was observed. In contrast, in the absence of specific DNA interactions between the cancer cells and fibroblasts, individual clusters of the NIH/3T3 cells formed in each spheroid due to cell sorting. To better understand the effect of heterotypic cell organization on either cell-cell contacts or matrix protein production, the spheroids were further stained with anti-E-cadherin and antifibronectin antibodies. While the amounts of E-cadherin appeared to be similar between the spheroids, a significantly higher amount of fibronectin secretion was observed in the coculture spheroids with uniform mixing of two cell types. This result showed that different heterotypic cell distributions within 3D architecture can influence the ECM protein production that can again alter the properties of the tumor or tumor microenvironment. The present study thus describes the use of DNA templating to direct the organization of cells in coculture spheroids, which can provide mechanistic biological insight into how heterotypic distribution in tumor spheroids can influence tumor progression, metastasis, and drug resistance.

Anoikis resistance of small airway epithelium is involved in the progression of chronic obstructive pulmonary disease

Background

Anoikis resistance is recognized as a crucial step in the metastasis of cancer cells. Most epithelial tumors are distinguished by the ability of epithelial cells to abscond anoikis when detached from the extracellular matrix. However, no study has investigated the involvement of anoikis in the small airway epithelium (SAE) of chronic obstructive pulmonary disease (COPD).

Methods

Anoikis-related genes (ANRGs) exhibiting differential expression in COPD were identified using microarray datasets obtained from the Gene Expression Omnibus (GEO) database. Unsupervised clustering was performed to classify COPD patients into anoikis-related subtypes. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were used to annotate the functions between different subtypes. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were leveraged to identify key molecules. The relative proportion of infiltrating immune cells in the SAE was quantified using the CIBERSORT and ssGSEA computational algorithms, and the correlation between key molecules and immune cell abundance was analyzed. The expression of key molecules in BEAS-2B cells exposed to cigarette smoke extract (CSE) was validated using qRT-PCR.

Results

A total of 25 ANRGs exhibited differential expression in the SAE of COPD patients, based on which two subtypes of COPD patients with distinct anoikis patterns were identified. COPD patients with anoikis resistance had more advanced GOLD stages and cigarette consumption. Functional annotations revealed a different immune status between COPD patients with pro-anoikis and anoikis resistance. Tenomodulin (TNMD) and long intergenic non-protein coding RNA 656 (LINC00656) were subsequently identified as key molecules involved in this process, and a close correlation between TNMD and the infiltrating immune cells was observed, such as activated CD4+ memory T cells, M1 macrophages, and activated NK cells. Further enrichment analyses clarified the relationship between TNMD and the inflammatory and apoptotic signaling pathway as the potential mechanism for regulating anoikis. In vitro experiments showed a dramatic upregulation of TNMD and LINC00656 in BEAS-2B cells when exposed to 3% CSE for 48 hours.

Conclusion

TNMD contributes to the progression of COPD by inducing anoikis resistance in SAE, which is intimately associated with the immune microenvironment.

Epithelial-Mesenchymal Plasticity: Implications for Ferroptosis Vulnerability and Cancer Therapy

Cancers polarized to a mesenchymal or poorly differentiated state can often evade cell death induced by conventional therapies. The epithelial-mesenchymal transition is involved in lipid metabolism and increases polyunsaturated fatty acid levels in cancer cells, contributing to chemo- and radio-resistance. Altered metabolism in cancer enables invasion and metastasis but is prone to lipid peroxidation under oxidative stress. Cancers with mesenchymal rather than epithelial signatures are highly vulnerable to ferroptosis. Therapy-resistant persister cancer cells show a high mesenchymal cell state and dependence on the lipid peroxidase pathway, which can respond more sensitively to ferroptosis inducers. Cancer cells may survive under specific metabolic and oxidative stress conditions, and targeting this unique defense system can selectively kill only cancer cells. Therefore, this article summarizes the core regulatory mechanisms of ferroptosis in cancer, the relationship between ferroptosis and epithelial-mesenchymal plasticity, and the implications of epithelial-mesenchymal transition for ferroptosis-based cancer therapy.

KISS1 metastasis suppressor in tumor dormancy: a potential therapeutic target for metastatic cancers?

Present therapeutic approaches do not effectively target metastatic cancers, often limited by their inability to eliminate already-seeded non-proliferative, growth-arrested, or therapy-resistant tumor cells. Devising effective approaches targeting dormant tumor cells has been a focus of cancer clinicians for decades. However, progress has been limited due to limited understanding of the tumor dormancy process. Studies on tumor dormancy have picked up pace and have resulted in the identification of several regulators. This review focuses on KISS1, a metastasis suppressor gene that suppresses metastasis by keeping tumor cells in a state of dormancy at ectopic sites. The review explores mechanistic insights of KISS1 and discusses its potential application as a therapeutic against metastatic cancers by eliminating quiescent cells or inducing long-term dormancy in tumor cells.

Integration of quantitative methods and mathematical approaches for the modeling of cancer cell proliferation dynamics

Physiological processes rely on the control of cell proliferation, and the dysregulation of these processes underlies various pathological conditions, including cancer. Mathematical modeling can provide new insights into the complex regulation of cell proliferation dynamics. In this review, we first examine quantitative experimental approaches for measuring cell proliferation dynamics in vitro and compare the various types of data that can be obtained in these settings. We then explore the toolbox of common mathematical modeling frameworks that can describe cell behavior, dynamics, and interactions of proliferation. We discuss how these wet-laboratory studies may be integrated with different mathematical modeling approaches to aid the interpretation of the results and to enable the prediction of cell behaviors, specifically in the context of cancer.

Breast cancer heterogeneity and its implication in personalized precision therapy

Breast cancer heterogeneity determines cancer progression, treatment effects, and prognosis. However, the precise mechanism for this heterogeneity remains unknown owing to its complexity. Here, we summarize the origins of breast cancer heterogeneity and its influence on disease progression, recurrence, and therapeutic resistance. We review the possible mechanisms of heterogeneity and the research methods used to analyze it. We also highlight the importance of cell interactions for the origins of breast cancer heterogeneity, which can be further categorized into cooperative and competitive interactions. Finally, we provide new insights into precise individual treatments based on heterogeneity.

SPOCK1 and POSTN are valuable prognostic biomarkers and correlate with tumor immune infiltrates in colorectal cancer

BACKGROUND

Immune cells and stromal cells in the tumor microenvironment play a vital role in the progression of colorectal cancer (CRC). The study aimed to screen valuable prognostic biomarkers in CRC based on stromal and immune scores.

METHOD

The ESTIMATE algorithm was used to calculate the immune and stromal scores of CRC samples in TCGA. Then samples were divided into high and low score groups based on the median value of the scores. Differentially expressed genes (DEGs) associated with immune and stromal scores were screened. WGCNA and univariate COX regression analysis were performed to further identify key prognostic genes. Analysis of scRNA-seq for CRC was used for verifying the main source of the key genes. The prognostic value of they was validated based on The Gene Expression Profiling Interactive Analysis and GSE17536 dataset. TIMER and CIBERSORT algorithms were applied to analyze the correlations among key genes and tumor-infiltrating immune cells. Several pairs of colon cancer tissue were used to be proven.

RESULT

1314 upregulated and 4 downregulated genes were identified, which were significantly enriched in immune-related biological processes and pathways. Among these DEGs, SPOCK1 and POSTN were identified as key prognostic genes and mainly expressed in cancer-associated fibroblasts for CRC. High expression of SPCOK1 and POSTN was associated with advanced clinical stage, T stage, N stage, and poor prognosis of CRC. The results from CIBERSORT and TIMER revealed that SPOCK1 and POSTN were associated with tumor-infiltrating immune cells, especially macrophages and neutrophils. Meanwhile, in several pairs of human colorectal tissue samples, SPOK1 and POSTN were found to be significantly overexpressed in colorectal tissue compared with para-cancer tissue, and macrophage surface markers CD68 (co-expressed by M1 and M2 macrophages) and CD206 (M2-specific macrophage expression) were also overexpressed in cancer tissue. Besides, SPOCK1 and POSTN expression were positively correlated with the expression of immune checkpoints.

CONCLUSION

Collectively, our results indicate that SPOCK1 and POSTN associated with CAF may be novel prognostic biomarkers in CRC and correlate with immune infiltrates.

Engineering Biomimetic Trogocytosis with Farnesylated Chemically Self-Assembled Nanorings

Inspired by the natural intercellular material-transfer process of trans-endocytosis or trogocytosis, we proposed that targeted farnesylated chemically self-assembled nanorings (f-CSANs) could serve as a biomimetic trogocytosis vehicle for engineering directional cargo transfer between cells, thus allowing cell-cell interactions to be monitored and facilitating cell-cell communications. The membranes of sender cells were stably modified by hydrophobic insertion with the targeted f-CSANs, which were efficiently transferred to receiver cells expressing the appropriate receptors by endocytosis. CSAN-assisted cell-cell cargo transfer (C4T) was demonstrated to be receptor specific and dependent on direct cell-cell interactions, the rate of receptor internalization, and the level of receptor expression. In addition, C4T was shown to facilitate cell-to-cell delivery of an apoptosis inducing drug, as wells as antisense oligonucleotides. Taken together, the C4T approach is a potentially versatile biomimetic trogocytosis platform that can be deployed as a macro-chemical biological tool for monitoring cell-cell interactions and engineering cell-cell communications.

Anoikis-Associated Lung Cancer Metastasis: Mechanisms and Therapies

Simple Summary

Anoikis is a programmed cell death process resulting from the loss of interaction between cells and the extracellular matrix. Therefore, it is necessary to overcome anoikis when tumor cells acquire metastatic potential. In lung cancer, the composition of the extracellular matrix, cell adhesion-related membrane proteins, cytoskeletal regulators, and epithelial–mesenchymal transition are involved in the process of anoikis, and the initiation of apoptosis signals is a critical step in anoikis. Inversely, activation of growth signals counteracts anoikis. This review summarizes the regulators of lung cancer-related anoikis and explores potential drug applications targeting anoikis.

Abstract

Tumor metastasis occurs in lung cancer, resulting in tumor progression and therapy failure. Anoikis is a mechanism of apoptosis that combats tumor metastasis; it inhibits the escape of tumor cells from the native extracellular matrix to other organs. Deciphering the regulators and mechanisms of anoikis in cancer metastasis is urgently needed to treat lung cancer. Several natural and synthetic products exhibit the pro-anoikis potential in lung cancer cells and in vivo models. These products include artonin E, imperatorin, oroxylin A, lupalbigenin, sulforaphane, renieramycin M, avicequinone B, and carbenoxolone. This review summarizes the current understanding of the molecular mechanisms of anoikis regulation and relevant regulators involved in lung cancer metastasis and discusses the therapeutic potential of targeting anoikis in the treatment of lung cancer metastasis.

The effects of radiation therapy on the macrophage response in cancer

The efficacy of radiotherapy, a mainstay of cancer treatment, is strongly influenced by both cellular and non-cellular features of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are a heterogeneous population within the TME and their prevalence significantly correlates with patient prognosis in a range of cancers. Macrophages display intrinsic radio-resistance and radiotherapy can influence TAM recruitment and phenotype. However, whether radiotherapy alone can effectively "reprogram" TAMs to display anti-tumor phenotypes appears conflicting. Here, we discuss the effect of radiation on macrophage recruitment and plasticity in cancer, while emphasizing the role of specific TME components which may compromise the tumor response to radiation and influence macrophage function. In particular, this review will focus on soluble factors (cytokines, chemokines and components of the complement system) as well as physical changes to the TME. Since the macrophage response has the potential to influence radiotherapy outcomes this population may represent a drug target for improving treatment. An enhanced understanding of components of the TME impacting radiation-induced TAM recruitment and function may help consider the scope for future therapeutic avenues to target this plastic and pervasive population.

Systematic molecular analysis of the human secretome and membrane proteome in gastrointestinal adenocarcinomas

The human secretome and membrane proteome are a large source of cancer biomarkers. Membrane‐bound and secreted proteins are promising targets for many clinically approved drugs, including for the treatment of tumours. Here, we report a deep systematic analysis of 957 adenocarcinomas of the oesophagus, stomach, colon and rectum to examine the cancer‐associated human secretome and membrane proteome of gastrointestinal tract adenocarcinomas (GIACs). Transcriptomic data from these GIACs were applied to an innovative majority decision‐based algorithm. We quantified significantly expressed protein‐coding genes. Interestingly, we found a consistent pattern in a small group of genes found to be overexpressed in GIACs, which were associated with a cytokine–cytokine interaction pathway (CCRI) in all four cancer subtypes. These CCRI associated genes, which spanned both one secretory and one membrane isoform were further analysed, revealing a putative biomarker, interleukin‐1 receptor accessory protein (IL1RAP), which indicated a poor overall survival, a positive correlation with cancer stemness and a negative correlation with several kinds of T cells. These results were further validated in vitro through the knockdown of IL1RAP in two human gastric carcinoma cell lines, which resulted in a reduced indication of cellular proliferation, migration and markers of invasiveness. Following IL1RAP silencing, RNA seq results showed a consistent pattern of inhibition related to CCRI, proliferation pathways and low infiltration of regulatory T cells (Tregs) and CD8 naive cells. The significance of the human secretome and membrane proteome is elucidated by these findings, which indicate IL1RAP as a potential candidate biomarker for cytokine‐mediated cancer immunotherapy in gastric carcinoma.

Nanoparticles use for Delivering Ursolic Acid in Cancer Therapy: A Scoping Review

Ursolic acid is a natural pentacyclic triterpenoid that exerts a potent anticancer effect. Furthermore, it is classified as a BCS class IV compound possessing low permeability and water solubility, consequently demonstrating limited bioavailability in addition to low therapeutic effectiveness. Nanoparticles are developed to modify the physical characteristics of drug and can often be produced in the range of 30–200 nm, providing highly effective cancer therapy due to the Enhanced Permeation and Retention (EPR) Effect. This study aims to provide a review of the efficacy and safety of various types of Ursolic Acid-loading nanoparticles within the setting of preclinical and clinical anticancer studies. This literature study used scoping review method, where the extracted data must comply with the journal inclusion criteria of within years of 2010–2020. The identification stage produced 237 suitable articles. Duplicate screening was then conducted followed by the initial selection of 18 articles that had been reviewed and extracted for data analysis. Based on this review, the use of nanoparticles can be seen to increase the anticancer efficacy of Ursolic Acid in terms of several parameters including pharmacokinetic data, survival rates and inhibition rates, as well as the absence of serious toxicity in preclinical and clinical trials in terms of several parameters including body weight, blood clinical chemistry, and organ histipathology. Based on this review, the use of nanoparticles has been able to increase the anticancer efficacy of Ursolic Acid, as well as show the absence of serious toxicity in preclinical and clinical trials. Evenmore, the liposome carrier provides development data that has reached the clinical trial phase I. The use of nanoparticle provides high potential for Ursolic Acid delivery in cancer therapy.

Recapitulating the Angiogenic Switch in a Hydrogel-Based 3D In Vitro Tumor-Stroma Model

To ensure nutrient and oxygen supply, tumors beyond a size of 1–2 mm³ need a connection to the vascular system. Thus, tumor cells modify physiological tissue homeostasis by secreting inflammatory and angiogenic cytokines. This leads to the activation of the tumor microenvironment and the turning of the angiogenic switch, resulting in tumor vascularization and growth. To inhibit tumor growth by developing efficient anti-angiogenic therapies, an in depth understanding of the molecular mechanism initiating angiogenesis is essential. Yet so far, predominantly 2D cell cultures or animal models have been used to clarify the interactions within the tumor stroma, resulting in poor transferability of the data obtained to the in vivo situation. Consequently, there is an abundant need for complex, humanized, 3D models in vitro. We established a dextran-hydrogel-based 3D organotypic in vitro model containing microtumor spheroids, macrophages, neutrophils, fibroblasts and endothelial cells, allowing for the analysis of tumor–stroma interactions in a controlled and modifiable environment. During the cultivation period of 21 days, the microtumor spheroids in the model grew in size and endothelial cells formed elongated tubular structures resembling capillary vessels, that appeared to extend towards the tumor spheroids. The tubular structures exhibited complex bifurcations and expanded without adding external angiogenic factors such as VEGF to the culture. To allow high-throughput screening of therapeutic candidates, the 3D cell culture model was successfully miniaturized to a 96-well format, while still maintaining the same level of tumor spheroid growth and vascular sprouting. The quantification of VEGF in the conditioned medium of these cultures showed a continuous increase during the cultivation period, suggesting the contribution of endogenous VEGF to the induction of the angiogenic switch and vascular sprouting. Thus, this model is highly suitable as a testing platform for novel anticancer therapeutics targeting the tumor as well as the vascular compartment.

Evaluation of breast cancer stem cells in human primary breast carcinoma and their role in aggressive behavior of the disease

BACKGROUND AND AIM

To delineate the underlying molecular mechanisms responsible for the intratumoral enrichment of breast cancer stem cells (BCSCs) in aggressive breast tumors, we evaluated the frequency and characteristics of BCSCs within the tumor tissue in primary human breast carcinomas. We assessed the expression profiles of various genes in cancer cells (CC) and stromal cells (SC) from these tumors to delineate the role played by the cellular niche in de novo origin or expansion of intra-tumoral cancer stem cells (CSC).

METHOD

The study included primary tumor and adjacent normal breast tissue specimens from chemotherapy-naïve breast carcinoma patients. The BCSCs, identified as Lin^-CD44⁺CD24^- and aldehyde dehydrogenase 1 A1 positive, were enumerated. The flow-cytometrically sorted stromal, and CC were processed for gene expression profiling using a custom-designed polymerase chain reaction array of genes known to facilitate disease progression.

RESULTS

The frequency of BCSCs within the tumor mass correlated significantly with histopathological and molecular grades of tumors, indicating a direct relationship of BCSC with the aggressive behavior of breast cancer. Further, a significantly increased expression of the genes associated with growth factors, cytokines and matricellular proteins in tumors were found in high BCSCs compared to Lo-BCSC tumors, suggesting the possible contribution of stromal and CC in an intratumoral expansion of CSCs. Similarly, a significant upregulation of genes associated with hypoxia and angiogenesis in Hi-BCSCs tumors further supported the role of a hypoxic environment.

CONCLUSION

Overall, the findings suggest the molecular crosstalk between SC and CC potentially (directly or indirectly) contributes to the expansion of CSC.

RELEVANCE FOR PATIENTS

The current study highlights the importance of CSC as a potential future predictive/prognostic marker for aggressive breast cancer. The present study predicts the potential risk stratification based on the frequency of BCSCs in primary breast tumors and existing prognostic factors.

Pathophysiological Roles of Histamine Receptors in Cancer Progression: Implications and Perspectives as Potential Molecular Targets

High levels of histamine and histamine receptors (HRs), including H1R~H4R, are found in many different types of tumor cells and cells in the tumor microenvironment, suggesting their involvement in tumor progression. This review summarizes the latest evidence demonstrating the pathophysiological roles of histamine and its cognate receptors in cancer biology. We also discuss the novel therapeutic approaches of selective HR ligands and their potential prognostic values in cancer treatment. Briefly, histamine is highly implicated in cancer development, growth, and metastasis through interactions with distinct HRs. It also regulates the infiltration of immune cells into the tumor sites, exerting an immunomodulatory function. Moreover, the effects of various HR ligands, including H1R antagonists, H2R antagonists, and H4R agonists, on tumor progression in many different cancer types are described. Interestingly, the expression levels of HR subtypes may serve as prognostic biomarkers in several cancers. Taken together, HRs are promising targets for cancer treatment, and HR ligands may offer novel therapeutic potential, alone or in combination with conventional therapy. However, due to the complexity of the pathophysiological roles of histamine and HRs in cancer biology, further studies are warranted before HR ligands can be introduced into clinical settings.

Double emulsion-pretreated microwell culture for the in vitro production of multicellular spheroids and their in situ analysis

Multicellular spheroids have served as a promising preclinical model for drug efficacy testing and disease modeling. Many microfluidic technologies, including those based on water-oil-water double emulsions, have been introduced for the production of spheroids. However, sustained culture and the in situ characterization of the generated spheroids are currently unavailable for the double emulsion-based spheroid model. This study presents a streamlined workflow, termed the double emulsion-pretreated microwell culture (DEPMiC), incorporating the features of (1) effective initiation of uniform-sized multicellular spheroids by the pretreatment of double emulsions produced by microfluidics without the requirement of biomaterial scaffolds; (2) sustained maintenance and culture of the produced spheroids with facile removal of the oil confinement; and (3) in situ characterization of individual spheroids localized in microwells by a built-in analytical station. Characterized by microscopic observations and Raman spectroscopy, the DEPMiC cultivated spheroids accumulated elevated lipid ordering on the apical membrane, similar to that observed in their Matrigel counterparts. Made possible by the proposed technological advancement, this study subsequently examined the drug responses of these in vitro-generated multicellular spheroids. The developed DEPMiC platform is expected to generate health benefits in personalized cancer treatment by offering a pre-animal tool to dissect heterogeneity from individual tumor spheroids.

High-throughput microscopy reveals the impact of multifactorial environmental perturbations on colorectal cancer cell growth

BACKGROUND

Colorectal cancer (CRC) mortality is principally due to metastatic disease, with the most frequent organ of metastasis being the liver. Biochemical and mechanical factors residing in the tumor microenvironment are considered to play a pivotal role in metastatic growth and response to therapy. However, it is difficult to study the tumor microenvironment systematically owing to a lack of fully controlled model systems that can be investigated in rigorous detail.

RESULTS

We present a quantitative imaging dataset of CRC cell growth dynamics influenced by in vivo-mimicking conditions. They consist of tumor cells grown in various biochemical and biomechanical microenvironmental contexts. These contexts include varying oxygen and drug concentrations, and growth on conventional stiff plastic, softer matrices, and bioengineered acellular liver extracellular matrix. Growth rate analyses under these conditions were performed via the cell phenotype digitizer (CellPD).

CONCLUSIONS

Our data indicate that the growth of highly aggressive HCT116 cells is affected by oxygen, substrate stiffness, and liver extracellular matrix. In addition, hypoxia has a protective effect against oxaliplatin-induced cytotoxicity on plastic and liver extracellular matrix. This expansive dataset of CRC cell growth measurements under in situ relevant environmental perturbations provides insights into critical tumor microenvironment features contributing to metastatic seeding and tumor growth. Such insights are essential to dynamical modeling and understanding the multicellular tumor-stroma dynamics that contribute to metastatic colonization. It also establishes a benchmark dataset for training and testing data-driven dynamical models of cancer cell lines and therapeutic response in a variety of microenvironmental conditions.

Engineering confining microenvironment for studying cancer metastasis

The physical microenvironment of cells plays a fundamental role in regulating cellular behavior and cell fate, especially in the context of cancer metastasis. For example, capillary deformation can destroy arrested circulating tumor cells while the dense extracellular matrix can form a physical barrier for invading cancer cells. Understanding how metastatic cancer cells overcome the challenges brought forth by physical confinement can help in developing better therapeutics that can put a stop to this migratory stage of the metastatic cascade. Numerous in vivo and in vitro assays have been developed to recapitulate the metastatic processes and study cancer cell migration in a confining microenvironment. In this review, we summarize some of the representative techniques and the exciting new findings. We critically review the advantages, as well as challenges associated with these tools and methodologies, and provide a guide on the applications that they are most suited for. We hope future efforts that push forward our current understanding on metastasis under confinement can lead to novel and more effective diagnostic and therapeutic strategies against this dreaded disease.

The prospects of tumor chemosensitivity testing at the single-cell level

Tumor chemosensitivity testing plays a pivotal role in the optimal selection of chemotherapeutic regimens for cancer patients in a personalized manner. High-throughput drug screening approaches have been developed but they failed to take into account intratumor heterogeneity and therefore only provided limited predictive power of therapeutic response to individual cancer patients. Single cancer cell drug sensitivity testing (SCC-DST) has been recently developed to evaluate the variable sensitivity of single cells to different anti-tumor drugs. In this review, we discuss how SCC-DST overcomes the obstacles of traditional drug screening methodologies. We outline critical procedures of SCC-DST responsible for single-cell generation and sorting, cell-drug encapsulation on a microfluidic chip and detection of cell-drug interactions. In SCC-DST, droplet-based microfluidics is emerging as an important platform that integrated various assays and analyses for drug susceptibility tests for individual patients. With the advancement of technology, both fluorescence imaging and label-free analysis have been used for detecting single cell-drug interactions. We also discuss the feasibility of integrating SCC-DST with single-cell RNA sequencing to unravel the mechanisms leading to drug resistance, and utilizing artificial intelligence to facilitate the analysis of various omics data in the evaluation of drug susceptibility. SCC-DST is setting the stage for better drug selection for individual cancer patients in the era of precision medicine.

Molecular MR Imaging of Prostate Cancer

This review summarizes recent developments regarding molecular imaging markers for magnetic resonance imaging (MRI) of prostate cancer (PCa). Currently, the clinical standard includes MR imaging using unspecific gadolinium-based contrast agents. Specific molecular probes for the diagnosis of PCa could improve the molecular characterization of the tumor in a non-invasive examination. Furthermore, molecular probes could enable targeted therapies to suppress tumor growth or reduce the tumor size.

Tumor-associated macrophages derived from cancer stem cells

Macrophages are the most abundant immune cells in the microenvironment of solid tumors. The present study displayed histological and immunohistochemical analyses of a malignant tumor model developed from cancer stem cells (CSCs) converted from human induced pluripotent stem cells (hiPSCs) in a cancer microenvironment prepared from the conditioned medium (CM) of a pancreatic cancer cell line. We focused on the localization and the origin of tumor-associated macrophages (TAMs), To the best of our knowledge this may be the first study to suggest the potential differentiation of CSCs to TAMs. hiPSCs were converted into CSCs in the presence of CM from PK8 cells. CSCs were then transplanted in vivo and formed primary tumors. Primary cultures for these tumors were serially transplanted again to obtain secondary tumors. Secondary tumors exhibited histopathological features of malignancy. Cells derived from tumors maintained the expression of endogenous stemness markers and pancreatic CSCs markers. Simultaneously, high immunoreactivity to anti-mouse CD68, anti-human CD68, CD206 and CD11b antibodies were detected revealing that the tumor tissue derived from CSCs was enriched for macrophages which can originate from both human and mouse cells. The model of CSCs highlighted the possibility of CSCs to differentiate into TAMs.

Secreted sphingomyelins modulate low mammary cancer incidence observed in certain mammals

Determining mechanisms that naturally protect species from developing cancer is critical in order to prevent and treat cancer. Here, we describe a novel cancer-suppressing mechanism, via the secretion of bioactive factors by mammary cells, that is present in domesticated mammals with a low mammary cancer incidence. Specifically, these bioactive factors induced triple-negative breast cancer cell (TNBC) death in vitro and reduced tumorigenicity in a xenograft TNBC mouse model in vivo. RNA deep sequencing showed significant downregulation of genes associated with breast cancer progression in secretome-cultured TNBC cells. Further in-depth multi-omics analysis identified sphingomyelins as key secreted factors, and their role was confirmed via inhibition of the sphingomyelin signaling pathway. We speculate that secreted sphingomyelins in the mammary gland of mammals with a naturally low incidence of mammary cancer mediate the elimination of cancer cells. This study contributes to the growing list of protective mechanisms identified in cancer-proof species.

Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet

We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent at Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, were collected from a retrospective cohort of patients diagnosed in 2004–2014. Patients were followed-up, for three years. Clinical data collected include complete information about the clinical course of the patients including treatment schedule, response according to RECIST classification, and survival. The core of the platform is the mathematical model, in the form of a system of ordinary differential equations, describing dynamics of platinum-sensitive and platinum-resistant cancer cells and interactions reflecting competition for space and resources. The model is simulated stochastically by sampling the parameter values from a joint probability distribution function. The machine learning model is applied to calibrate the mathematical model and to fit it to the overall survival curve. The model simulations faithfully reproduce the clinical cohort at three levels long-term response (OS), the initial response (according to RECIST criteria), and the relationship between the number of chemotherapy cycles and time between two consecutive chemotherapy cycles. In addition, we investigated the relationship between initial and long-term response. We showed that those two variables do not correlate which means that we cannot predict patient survival solely based on the initial response. We also tested several chemotherapy schedules to find the best one for patients treated with palliative intent. We found that the optimal treatment schedule depends, among others, on the strength of competition among various subclones in a tumor. The computational platform developed allows optimizing chemotherapy protocols, within admissible limits of toxicity, for palliative treatment of metastatic NSCLC. The simplicity of the method allows its application to chemotherapy optimization in different cancers.

Lung cancer is usually diagnosed at an advanced stage because of non-specific symptoms. The most common subtype of lung cancer is non-small cell lung cancer, which constitutes 80% of lung cancer cases. Here, we developed the methodology for finding the optimal treatment schedule for patients treated with palliative intent. The goal is not to cure the patients who are at an advanced stage but to prolong their survival by the administration of platinum-based chemotherapy. The method is based on the mathematical model describing the growth of tumors and its response to chemotherapy which is calibrated using real clinical data.

Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis

Technological advances enable assaying multiplexed spatially resolved RNA and protein expression profiling of individual cells, thereby capturing molecular variations in physiological contexts. While these methods are increasingly accessible, computational approaches for studying the interplay of the spatial structure of tissues and cell-cell heterogeneity are only beginning to emerge. Here, we present spatial variance component analysis (SVCA), a computational framework for the analysis of spatial molecular data. SVCA enables quantifying different dimensions of spatial variation and in particular quantifies the effect of cell-cell interactions on gene expression. In a breast cancer Imaging Mass Cytometry dataset, our model yields interpretable spatial variance signatures, which reveal cell-cell interactions as a major driver of protein expression heterogeneity. Applied to high-dimensional imaging-derived RNA data, SVCA identifies plausible gene families that are linked to cell-cell interactions. SVCA is available as a free software tool that can be widely applied to spatial data from different technologies.

Induction of ZCCHC6 expression in peripheral blood mononuclear cells by HNSCC secretions

Cancer secretion can change the properties of adjacent cells, including peripheral blood mononuclear cells (PBMCs). We investigated whether such secretion influences messenger RNA expression in PBMCs of patients with head and neck squamous cell carcinoma (HNSCC). In the present study, co-culture model of normal PBMCs and HNSCC cell lines were established. The PBMCs were subsequently subjected to RNA sequencing for transcriptome analysis. Furthermore, expression data from the Gene Expression Omnibus repository, platform GPL4133, series GSE39400, were gathered to analyze, afterward identify zinc finger CysCysHisCys (CCHC)-type domain-containing protein 6 (ZCCHC6) as the main gene involved in HNSCC. This gene was then validated by a quantitative real-time polymerase chain reaction. The results showed that ZCCHC6 was expressed at significantly higher levels in the patients with HNSCC than in the healthy controls, and the sensitivity and specificity of these findings for diagnostic purposes were 100.00% and 70.83%, respectively. In summary, our findings demonstrated that the secretion of HNSCC cells could cause the alterations in messenger RNA expression by PBMCs. The ZCCHC6 expression level may apply in HNSCC screening.

Choosing The Right Animal Model for Renal Cancer Research

The increase in the life expectancy of patients with renal cell carcinoma (RCC) in the last decade is due to changes that have occurred in the area of preclinical studies. Understanding cancer pathophysiology and the emergence of new therapeutic options, including immunotherapy, would not be possible without proper research. Before new approaches to disease treatment are developed and introduced into clinical practice they must be preceded by preclinical tests, in which animal studies play a significant role. This review describes the progress in animal model development in kidney cancer research starting from the oldest syngeneic or chemically-induced models, through genetically modified mice, finally to xenograft, especially patient-derived, avatar and humanized mouse models. As there are a number of subtypes of RCC, our aim is to help to choose the right animal model for a particular kidney cancer subtype. The data on genetic backgrounds, biochemical parameters, histology, different stages of carcinogenesis and metastasis in various animal models of RCC as well as their translational relevance are summarized. Moreover, we shed some light on imaging methods, which can help define tumor microstructure, assist in the analysis of its metabolic changes and track metastasis development.

YAP regulates cell size and growth dynamics via non-cell autonomous mediators

The Hippo pathway regulates organ size, regeneration, and cell growth by controlling the stability of the transcription factor, YAP (Yorkie in Drosophila). When there is tissue damage, YAP is activated allowing the restoration of homeostatic tissue size. The exact signals by which YAP is activated are still not fully understood, but its activation is known to affect both cell size and cell number. Here we used cultured cells to examine the coordinated regulation of cell size and number under the control of YAP. Our experiments in isogenic HEK293 cells reveal that YAP can affect cell size and number by independent circuits. Some of these effects are cell autonomous, such as proliferation, while others are mediated by secreted signals. In particular CYR61, a known secreted YAP target, is a non-cell autonomous mediator of cell survival, while another unidentified secreted factor controls cell size.

Patient's quality of life after surgery and radiotherapy for extremity soft tissue sarcoma - a retrospective single-center study over ten years

Background and objectives

The purpose of this study is to analyze major complication rates and different aspects of health-related quality of life (HRQoL) in extremity soft tissue sarcoma (STS) patients treated with or without radio (chemo) therapy and surgery.

Methods

We performed a retrospective analysis of all patients who underwent Extremity STS excision from 2004 to 2014 (182 patients included). Patients’ data were collected from patients’ records. HRQoL was assessed by using EORTC QLQ-C30.

Results

A total of 182 patients underwent sarcoma resection. After neoadjuvant radiochemotherapy (RCT), the major-complication rate amounted to 28% (vs. 7%, no radiotherapy, p <  0.001). Major-complication rates after adjuvant radiotherapy (RT) occurred in 8% (vs. 7%, no radiotherapy, p = 0.265). Comparison QoL scores between treating with neoadjuvant RCT or without RT revealed significant worse scores with neoadjuvant RCT. Further stratification of disease control of these patients showed significant reduced scores in the group of disease-free patients with neoadjuvant RCT compared to irradiated disease-free patients.

Discussion

To date, there have only been a few investigations of QoL in STS. Retrospective study on quality of life have limitations, like a lack of baseline evaluation of QoL. Patient candidated to radiation therapy could have had worse QoL baseline due to more advanced disease. Disease status of the patients who answered the questionnaires could have been an influence of QoL and we could show reduced scores in the group of disease-free patients with neoadjuvant RCT, but not for the patients with recurrence or metastasis, so it is very hard to discriminate whether radiation therapy could really have an impact or not.

Conclusion

This study might assist in further improving the understanding of QoL in STS patients and may animate for prospective studies examining the oncological therapies impact on HRQoL.

Metastatic renal cell carcinoma cells growing in 3D on poly‑D‑lysine or laminin present a stem‑like phenotype and drug resistance

3D spheroids are built by heterogeneous cell types in different proliferative and metabolic states and are enriched in cancer stem cells. The main aim of the study was to investigate the usefulness of a novel metastatic renal cell carcinoma (RCC) 3D spheroid culture for in vitro cancer stem cell physiology research and drug toxicity screening. RCC cell lines, Caki-1 (skin metastasis derived) and ACHN (pleural effusion derived), were efficiently cultured in growth-factor/serum deprived, defined, StemXvivo and Nutristem medium on laminin-coated or poly-D-lysine-coated plates. In optimal 3D culture conditions, ACHN cells (StemXVivo/poly-D-lysine) formed small spheroids with remaining adherent cells of an epithelial phenotype, while Caki-1 cells (StemXVivo/laminin) formed large dark spheroids with significantly reduced cell viability in the center. In the 3D structures, expression levels of genes encoding stem transcription factors (OCT4, SOX2, NES) and RCC stem cell markers (CD105, CD133) were deregulated in comparison to these expression levels in traditional 2D culture. Sunitinib, epirubicin and doxycycline were more toxic to cells cultured in monolayers than for cells in 3D spheroids. High numbers of cells arrested in the G0/G1 phase of the cell cycle were found in spheroids under sunitinib treatment. We showed that metastatic RCC 3D spheroids supported with ECM are a useful model to determine the cancer cell growth characteristics that are not found in adherent 2D cultures. Due to the more complex architecture, spheroids may mimic in vivo micrometastases and may be more appropriate to investigate novel drug candidate responses, including the direct effects of tyrosine kinase inhibitor activity against RCC cells.

Comprehensive Characterization of Somatic Mutations Impacting lncRNA Expression for Pan-Cancer

Somatic mutations have long been recognized as an important feature of cancer. However, analysis of somatic mutations, to date, has focused almost entirely on the protein coding regions of the genome. The potential roles of somatic mutations in human long noncoding RNAs (lncRNAs) are therefore largely unknown, particularly their functional significance across different cancer types. In this study, we characterized some lncRNAs whose expression was affected by somatic mutations (defined as MutLncs) and constructed global MutLnc landscapes across 17 cancer types by systematically integrating multiple levels of data. MutLncs were commonly downregulated and carried low mutation frequencies and non-silent mutations in most cancer types. Co-occurrence analysis in pan-cancer highlighted combined patterns of specific MutLncs, suggesting that a number of MutLncs influence diverse cancer types through combination effects. Several conserved and cancer-specific functions of MutLncs were determined. We further explored the somatic mutations affecting lncRNA expression via mixed and unmixed effects, which led to specific functions in pan-cancer. Survival analysis indicated that MutLncs and co-occurrence pairs can potentially serve as cancer biomarkers. Clarification of the specific roles of MutLncs in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types and developing the appropriate treatments.