Dynamic interplay between tumour, stroma and immune system can drive or prevent tumour progression

The YAP/TAZ Signaling Pathway in the Tumor Microenvironment and Carcinogenesis: Current Knowledge and Therapeutic Promises

The yes-associated protein (YAP) and the transcriptional coactivator with PDZ-binding motif (TAZ) are transcriptional coactivators, members of the Hippo signaling pathway, which play a critical role in cell growth regulation, embryonic development, regeneration, proliferation, and cancer origin and progression. The mechanism involves the nuclear binding of the un-phosphorylated YAP/TAZ complex to release the transcriptional enhanced associate domain (TEAD) from its repressors. The active ternary complex is responsible for the aforementioned biological effects. Overexpression of YAP/TAZ has been reported in cancer stem cells and tumor resistance. The resistance involves chemotherapy, targeted therapy, and immunotherapy. This review provides an overview of YAP/TAZ pathways’ role in carcinogenesis and tumor microenvironment. Potential therapeutic alternatives are also discussed.

Understanding the Complex Milieu of Epithelial-Mesenchymal Transition in Cancer Metastasis: New Insight Into the Roles of Transcription Factors

Epithelial-mesenchymal transition (EMT) is a physiological program during which polarised, immobile epithelial cells lose connection with their neighbours and are converted to migratory mesenchymal phenotype. Mechanistically, EMT occurs via a series of genetic and cellular events leading to the repression of epithelial-associated markers and upregulation of mesenchymal-associated markers. EMT is very crucial for many biological processes such as embryogenesis and ontogenesis during human development, and again it plays a significant role in wound healing during a programmed replacement of the damaged tissues. However, this process is often hijacked in pathological conditions such as tumour metastasis, which constitutes the most significant drawback in the fight against cancer, accounting for about 90% of cancer-associated mortality globally. Worse still, metastatic tumours are not only challenging to treat with the available conventional radiotherapy and surgical interventions but also resistant to several cytotoxic agents during treatment, owing to their anatomically diffuse localisation in the body system. As the quest to find an effective method of addressing metastasis in cancer intervention heightens, understanding the molecular interplay involving the signalling pathways, downstream effectors, and their interactions with the EMT would be an important requisite while the challenges of metastasis continue to punctuate. Unfortunately, the molecular underpinnings that govern this process remain to be completely illuminated. However, it is becoming increasingly clear that EMT, which initiates every episode of metastasis, significantly requires some master regulators called EMT transcription factors (EMT-TFs). Thus, this review critically examines the roles of TFs as drivers of molecular rewiring that lead to tumour initiation, progression, EMT, metastasis, and colonisation. In addition, it discusses the interaction of various signalling molecules and effector proteins with these factors. It also provides insight into promising therapeutic targets that may inhibit the metastatic process to overcome the limitation of “undruggable” cancer targets in therapeutic design and upturn the current spate of drug resistance. More so, it extends the discussion from the basic understanding of the EMT binary switch model, and ultimately unveiling the E/M cellular plasticity along a phenotypic spectrum via multiple trans-differentiations. It wraps up on how this knowledge update shapes the diagnostic and clinical approaches that may demand a potential shift in investigative paradigm using novel technologies such as single-cell analyses to improve overall patient survival.

Construction of a competing endogenous RNA network related to the prognosis of cholangiocarcinoma and comprehensive analysis of the immunological correlation

Background

Cholangiocarcinoma (CCA) is a malignant tumor of the digestive system, with occult onset in the early stage, a high degree of malignancy in the late stage, and poor prognosis. At present, the pathogenesis of CCA is not clear, and there is a lack of effective immunotherapy. The purpose of this study was to identify the potential regulatory mechanism of CCA and analyze the possibility of its related immunotherapy.

Methods

The circular RNAs (circRNAs) expression profile data of CCA was downloaded from the Gene Expression Omnibus (GEO) database; the miRNA and mRNA expression profile data of CCA were downloaded from The Cancer Genome Atlas (TCGA) database. Prognostic factors were screened by univariate Cox regression analysis, and the competing endogenous RNA (ceRNA) network was constructed via survival analysis. Multivariate Cox analysis was used to screen the independent prognostic factors and construct a prognostic correlation subnetwork. Analyzing the tumor microenvironment of CCA and survival analysis were performed according to the score of the microenvironment, and the distribution of tumor infiltrating immune cells (TICs) in CCA was calculated using the CIBERSORT algorithm. We explored the expression pattern of the target genes in pan-cancer, and the correlation between the key genes in the ceRNA subnetwork, TICs and immune checkpoints was analyzed using an online database. Finally, the expression levels of target genes were validated based on the Human Protein Atlas (HPA) databases.

Results

We screened four circRNAs, 10 miRNAs, and 17 mRNAs with significant differences, and constructed the ceRNA network. Independent prognostic factors were screened by multivariate Cox regression analysis, and a subnetwork containing five nodes (hsa_circ_0002073→hsa-mir-4524a-3p→SLC16A3/SLC35E4/DDX4) was constructed. Further analysis showed that SLC16A3 was not only an independent posterior factor of CCA, but was also closely correlated with immune cells, immune checkpoints, and immunotherapy, and had a certain regulatory effect on the tumor microenvironment.

Conclusions

Our study identified a novel prognostic marker of CCA, SLC16A3, and revealed the regulatory role of SLC16A3 in the tumor microenvironment, which is expected to provide new insights for the early diagnosis, prognosis, and targeted therapy of CCA.

Identification of pyroptosis-related subtypes, the development of a prognosis model, and characterization of tumor microenvironment infiltration in colorectal cancer

Pyroptosis is a newly discovered programmed cell death that is associated with tumor progression, prognosis, and treatment response. However, the potential roles of pyroptosis-related genes (PRGs) in the tumor microenvironment (TME) remain unclear. We described the alterations of PRGs in 1109 colorectal cancer (CRC) samples from genetic and transcriptional fields and evaluated their expression patterns from four independent datasets. We identified two distinct molecular subtypes and found that multi-layer PRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell-infiltrating characteristics. Then, a PRG_score for predicting recurrence-free survival (RFS) was constructed and its predictive capability in CRC patients was validated. Consequently, we constructed a highly accurate nomogram for improving the clinical applicability of the PRG_score. A low PRG_score, characterized by increased microsatellite instability-high (MSI-H), mutation burden, and immunity activation, indicated favorable odds of RFS. Moreover, the PRG_score was significantly associated with the cancer stem cell (CSC) index and chemotherapeutic drug sensitivity. Our comprehensive analysis of PRGs in CRC demonstrated their potential roles in the tumor-immune-stromal microenvironment, clinicopathological features, and prognosis. These findings may improve our understanding of PRGs in CRC and pave a new path for the assessment of prognosis and the development of more effective immunotherapy strategies.

The Dog as a Model to Study the Tumor Microenvironment

Cancer is a complex and dynamic disease with an outcome that depends on a strict crosstalk between tumor cells and other components in tumor microenvironment, namely, tumor-infiltrating immune cells, fibroblasts, cancer stem cells, adipocytes, and endothelial cells. Within the tumor microenvironment, macrophages and T-lymphocytes appear to be key effectors during the several steps of tumor initiation and progression. Tumor cells, through the release of a plethora of signaling molecules, can induce immune tolerance, by avoiding immune surveillance, and inhibit immune cells cytotoxic functions. Furthermore, as the tumor grows, tumor microenvironment reveals a series of dysfunctional conditions that potentiate a polarization of harmful humoral Th2 and Th17, an upregulation of Treg cells, and a differentiation of macrophages into the M2 subtype, which contribute to the activation of several signaling pathways involving important tissue biomarkers (COX-2, EGFR, VEGF) implicated in cancer aggressiveness and poor clinical outcomes. In order to maintain the tumor growth, cancer cells acquire several adaptations such as neovascularization and metabolic reprogramming. An extensive intracellular production of lactate and protons is observed in tumor cells as a result of their high glycolytic metabolism. This contributes not only for the microenvironment pH alteration but also to shape the immune response that ultimately impairs immune cells capabilities and effector functions.In this chapter, the complexity of tumor microenvironment, with special focus on macrophages, T-lymphocytes, and the impact of lactate efflux, was reviewed, always trying to demonstrate the strong similarities between data from studies of humans and dogs, a widely proposed model for comparative oncology studies.

Prognostic Value and Immunological Characteristics of a Novel RNA Binding Protein Signature in Cutaneous Melanoma

Background

The existing studies indicate that RNA binding proteins (RBPs) are closely correlated with the genesis and development of cancers. However, the role of RBPs in cutaneous melanoma remains largely unknown. Therefore, the present study aims to establish a reliable prognostic signature based on RBPs to distinguish cutaneous melanoma patients with different prognoses and investigate the immune infiltration of patients.

Methods

After screening RBPs from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, Cox and least absolute shrinkage and selection operator (LASSO) regression analysis were then used to establish a prediction model. The relationship between the signature and the abundance of immune cell types, the tumor microenvironment (TME), immune-related pathways, and immune checkpoints were also analyzed.

Results

In total, 7 RBPs were selected to establish the prognostic signature. Patients categorized as a high-risk group demonstrated worse overall survival (OS) rates compared to those of patients categorized as a low-risk group. The signature was validated in an independent external cohort and indicated a promising prognostic ability. Further analysis indicated that the signature wasan independent prognostic indicator in cutaneous melanoma. A nomogram combining risk score and clinicopathological features was then established to evaluate the 3- and 5-year OS in cutaneous melanoma patients. Analyses of immune infiltrating, the TME, immune checkpoint, and drug susceptibility revealed significant differences between the two groups. GSEA analysis revealed that basal cell carcinoma, notch signaling pathway, melanogenesis pathways were enriched in the high-risk group, resulting in poor OS.

Conclusion

We established and validated a robust 7-RBP signature that could be a potential biomarker to predict the prognosis and immunotherapy response of cutaneous melanoma patients, which provides new insights into cutaneous melanoma immunotherapeutic strategies.

Mapping Mechanical Properties of the Tumor Microenvironment by Laser Speckle Rheological Microscopy

Altered mechanical properties of the tumor matrix have emerged as both the cause and consequence of breast carcinogenesis. Increased tumor stiffness has traditionally provided a viable metric to screen for malignancies via palpation or imaging. Previous studies have demonstrated that the microscale mechanical properties of the cell substrate influence tumor proliferation and invasive migration in vitro. Nevertheless, the association of the mechanical microenvironment with clinical hallmarks of aggressiveness in human breast tumors, including histopathological subtype, grade, receptor expression status, and lymph node involvement is poorly understood. This is largely due to the lack of tools for mapping tumor viscoelastic properties in clinical specimens with high spatial resolution over a large field of view (FoV). Here we introduce laser Speckle rHEologicAl micRoscopy (SHEAR) that for the first time enables mapping the magnitude viscoelastic or shear modulus, |G*(x,y,ω)|, over a range of frequencies (ω = 1-250 rad/second) in excised tumors within minutes with a spatial resolution of approximately 50 μm, over multiple cm² FoV. Application of SHEAR in a cohort of 251 breast cancer specimens from 148 patients demonstrated that |G*(x,y,ω)| (ω = 2π rad/second) closely corresponds with histological features of the tumor, and that the spatial gradient of the shear modulus, |∇|G*(x,y,ω)||, is elevated at the tumor invasive front. Multivariate analyses established that the metrics, (|G* |) and (|∇|G* ||), measured by SHEAR are associated with prognosis. These findings implicate the viscoelastic properties of the tumor microenvironment in breast cancer prognosis and likely pave the path for identifying new modifiable targets for treatment. SIGNIFICANCE: Laser speckle rheological microscopy establishes the links between microscale heterogeneities of viscoelasticity and histopathological subtype, tumor grade, receptor expression, as well as lymph node status in breast carcinoma.

Tumor Expression Profile Analysis Developed and Validated a Prognostic Model Based on Immune-Related Genes in Bladder Cancer

Background: Bladder cancer (BLCA) ranks 10th in incidence among malignant tumors and 6th in incidence among malignant tumors in males. With the application of immune therapy, the overall survival (OS) rate of BLCA patients has greatly improved, but the 5-year survival rate of BLCA patients is still low. Furthermore, not every BLCA patient benefits from immunotherapy, and there are a limited number of biomarkers for predicting the immunotherapy response. Therefore, novel biomarkers for predicting the immunotherapy response and prognosis of BLCA are urgently needed.

Methods: The RNA sequencing (RNA-seq) data, clinical data and gene annotation files for The Cancer Genome Atlas (TCGA) BLCA cohort were extracted from the University of California, Santa Cruz (UCSC) Xena Browser. The BLCA datasets GSE31684 and GSE32894 from the Gene Expression Omnibus (GEO) database were extracted for external validation. Immune-related genes were extracted from InnateDB. Significant differentially expressed genes (DEGs) were identified using the R package “limma,” and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the DEGs were performed using R package “clusterProfiler.” Least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the signature model. The infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The performance of the model was evaluated with receiver operating characteristic (ROC) curves and calibration curves.

Results: In total, 1,040 immune-related DEGs were identified, and eight signature genes were selected to construct a model using LASSO regression analysis. The risk score of BLCA patients based on the signature model was negatively correlated with OS and the immunotherapy response. The ROC curve for OS revealed that the model had good accuracy. The calibration curve showed good agreement between the predictions and actual observations.

Conclusions: Herein, we constructed an immune-related eight-gene signature that could be a potential biomarker to predict the immunotherapy response and prognosis of BLCA patients.

Genome Scale Modeling to Study the Metabolic Competition between Cells in the Tumor Microenvironment

The tumor's physiology emerges from the dynamic interplay of numerous cell types, such as cancer cells, immune cells and stromal cells, within the tumor microenvironment. Immune and cancer cells compete for nutrients within the tumor microenvironment, leading to a metabolic battle between these cell populations. Tumor cells can reprogram their metabolism to meet the high demand of building blocks and ATP for proliferation, and to gain an advantage over the action of immune cells. The study of the metabolic reprogramming mechanisms underlying cancer requires the quantification of metabolic fluxes which can be estimated at the genome-scale with constraint-based or kinetic modeling. Constraint-based models use a set of linear constraints to simulate steady-state metabolic fluxes, whereas kinetic models can simulate both the transient behavior and steady-state values of cellular fluxes and concentrations. The integration of cell- or tissue-specific data enables the construction of context-specific models that reflect cell-type- or tissue-specific metabolic properties. While the available modeling frameworks enable limited modeling of the metabolic crosstalk between tumor and immune cells in the tumor stroma, future developments will likely involve new hybrid kinetic/stoichiometric formulations.

Identification and validation of a ferroptosis-related gene signature predictive of prognosis in breast cancer

Ferroptosis, a novel form of regulated cell death, is closely associated with the occurrence and development of malignant tumors. Here, we utilized a bioinformatics approach to identify ferroptosis-related genes to establish a robust and reliable prognostic signature in breast cancer (BC). Univariate Cox regression and LASSO regression analyses of patient's survival and gene expression data identified a prognostic signature consisting of 10 ferroptosis-related genes (FRGs). The signature demonstrated a favorable prediction performance, and was validated in two independent datasets, GSE21653 and GSE25066. Analyses of immune infiltrates, tumor microenvironment, immune checkpoints, mutations, drug sensitivity, and clinicopathological features revealed significant differences between low- and high-risk BC patients. A multivariate analysis revealed that the signature was an independent prognostic predictor in BC, and a nomogram combining the risk score and tumor stage intuitively displayed high accuracy and reliability with respect to predicting the survival outcomes of BC patients. These findings indicate that the identified prognostic signature is a potential indicator predictive of prognosis and immunotherapeutic responses in BC patients.

Inflammatory Biomarkers as Promising Predictors of Prognosis in Cervical Cancer Patients

INTRODUCTION

Increasing evidence demonstrates a crucial role of inflammation in inducing and promoting several cancers. Pro-inflammatory upregulation of cytokines such as IL-6 has been implicated in cervical cancer development and progression through several mechanisms, for example, by inducing platelet production, activation, and aggregation. The aim of the study was to evaluate the effective prognostic impact of inflammatory biomarkers such as platelet count, platelet to lymphocyte ratio (PLR), and IL-6 in cervical cancer patients.

MATERIALS AND METHODS

Between 2016 and 2019, 108 out of 159 patients with cervical cancer have been enrolled. Cutoff level of pretreatment platelet count and PLR was identified by using the ROC curve. IL-6 tumoral and peritumoral expression was analyzed and stratified as low and high (low expression: 0 and +1; marked expression: +2 and +3).

RESULTS

Median follow-up duration was 30 months (range 16-44). Patients with higher platelet counts showed worse DFS and OS (DFS p < 0.001; OS p < 0.001). Cumulative rates of DFS and OS in patients with lower PLR were higher than in patients with higher values of PLR (DFS p = 0.032; OS p < 0.001). Survival analysis showed a better prognosis in patients with lower IL-6 expression (DFS p < 0.001; OS p < 0.001).

CONCLUSION

Nowadays, causal relationship between inflammation, innate immunity, and cancer is more widely accepted. However, many of the molecular and cellular mechanisms mediating this relationship remain unresolved. Ongoing inflammatory response was associated with poor outcomes in cervical cancer patients. A higher pretreatment platelet count and PLR value associated with higher IL-6 tumoral expression could be used to predict poor prognosis in cervical cancer patients.

Molecular insights into phytochemicals-driven break function in tumor microenvironment

Advanced knowledge about the role of tumor microenvironment (TME) in cancer progression has opened various ways to target the vast signaling pathways for cancer treatment. Failures of the currently used drugs have raised out the need to look for novel drugs which can target various crucial aspects of cancer progression (e.g., angiogenesis, uncontrolled cell division, and metastasis). Phytochemicals behaving as potent anticancer agents shows promise as therapeutics. Various phytochemicals, such as curcumin, Epigallocatechin Gallate (EGCG), resveratrol, plumbagin, genistein, and others, have been identified with modulatory effect on TME. These phytochemicals often target the molecular pathways that reside in the tumor vicinity associated with endothelial cells, cancer-associated fibroblasts, immune cells, mesenchymal stem cells, other cell types, vascular and lymphatic networks, and extracellular matrix which are important for tumor progression and development. Some phytochemicals also target the internal signaling pathways, including STAT3, NF-қB, ERK-1/2, and PI3K/Akt signaling of noncancer cell, residing in the microenvironment, and thus inhibiting the supportive effect from these cells in tumor development. However, much information needs to be acquired before using these phytochemicals in cancer treatment. The primary objective of this review is to provide a better knowledge about the role of TME in cancer progression and development, focusing on the different targets which can be used for therapeutic approach, and then to give a brief account on some known phytochemicals to date, which have shown remarkable TME modulatory effects. PRACTICAL APPLICATIONS: For the use of phytochemicals as therapeutics, it is highly recommended that their precise target should be known; therefore studies should be encouraged such that the effects of these phytochemicals can be evaluated on the individual cellular level like how the phytochemical is targeting the tumor-associated macrophage, or any other cell residing in the tumor microenvironment (TME), and the compound should target a specific component of TME to avoid off target effects.

Recapitulating Tumorigenesis in vitro: Opportunities and Challenges of 3D Bioprinting

Cancer is considered one of the most predominant diseases in the world and one of the principal causes of mortality per year. The cellular and molecular mechanisms involved in the development and establishment of solid tumors can be defined as tumorigenesis. Recent technological advances in the 3D cell culture field have enabled the recapitulation of tumorigenesis in vitro, including the complexity of stromal microenvironment. The establishment of these 3D solid tumor models has a crucial role in personalized medicine and drug discovery. Recently, spheroids and organoids are being largely explored as 3D solid tumor models for recreating tumorigenesis in vitro. In spheroids, the solid tumor can be recreated from cancer cells, cancer stem cells, stromal and immune cell lineages. Organoids must be derived from tumor biopsies, including cancer and cancer stem cells. Both models are considered as a suitable model for drug assessment and high-throughput screening. The main advantages of 3D bioprinting are its ability to engineer complex and controllable 3D tissue models in a higher resolution. Although 3D bioprinting represents a promising technology, main challenges need to be addressed to improve the results in cancer research. The aim of this review is to explore (1) the principal cell components and extracellular matrix composition of solid tumor microenvironment; (2) the recapitulation of tumorigenesis in vitro using spheroids and organoids as 3D culture models; and (3) the opportunities, challenges, and applications of 3D bioprinting in this area.

Transcriptional and Microenvironmental Landscape of Macrophage Transition in Cancer: A Boolean Analysis

The balance between pro- and anti-inflammatory immune system responses is crucial to face and counteract complex diseases such as cancer. Macrophages are an essential population that contributes to this balance in collusion with the local tumor microenvironment. Cancer cells evade the attack of macrophages by liberating cytokines and enhancing the transition to the M2 phenotype with pro-tumoral functions. Despite this pernicious effect on immune systems, the M1 phenotype still exists in the environment and can eliminate tumor cells by liberating cytokines that recruit and activate the cytotoxic actions of TH1 effector cells. Here, we used a Boolean modeling approach to understand how the tumor microenvironment shapes macrophage behavior to enhance pro-tumoral functions. Our network reconstruction integrates experimental data and public information that let us study the polarization from monocytes to M1, M2a, M2b, M2c, and M2d subphenotypes. To analyze the dynamics of our model, we modeled macrophage polarization in different conditions and perturbations. Notably, our study identified new hybrid cell populations, undescribed before. Based on the in vivo macrophage behavior, we explained the hybrid macrophages’ role in the tumor microenvironment. The in silico model allowed us to postulate transcriptional factors that maintain the balance between macrophages with anti- and pro-tumoral functions. In our pursuit to maintain the balance of macrophage phenotypes to eliminate malignant tumor cells, we emulated a theoretical genetically modified macrophage by modifying the activation of NFκB and a loss of function in HIF1-α and discussed their phenotype implications. Overall, our theoretical approach is as a guide to design new experiments for unraveling the principles of the dual host-protective or -harmful antagonistic roles of transitional macrophages in tumor immunoediting and cancer cell fate decisions.

Metabolic Reprogramming of Colorectal Cancer Cells and the Microenvironment: Implication for Therapy

Colorectal carcinoma (CRC) is one of the most frequently diagnosed carcinomas and one of the leading causes of cancer-related death worldwide. Metabolic reprogramming, a hallmark of cancer, is closely related to the initiation and progression of carcinomas, including CRC. Accumulating evidence shows that activation of oncogenic pathways and loss of tumor suppressor genes regulate the metabolic reprogramming that is mainly involved in glycolysis, glutaminolysis, one-carbon metabolism and lipid metabolism. The abnormal metabolic program provides tumor cells with abundant energy, nutrients and redox requirements to support their malignant growth and metastasis, which is accompanied by impaired metabolic flexibility in the tumor microenvironment (TME) and dysbiosis of the gut microbiota. The metabolic crosstalk between the tumor cells, the components of the TME and the intestinal microbiota further facilitates CRC cell proliferation, invasion and metastasis and leads to therapy resistance. Hence, to target the dysregulated tumor metabolism, the TME and the gut microbiota, novel preventive and therapeutic applications are required. In this review, the dysregulation of metabolic programs, molecular pathways, the TME and the intestinal microbiota in CRC is addressed. Possible therapeutic strategies, including metabolic inhibition and immune therapy in CRC, as well as modulation of the aberrant intestinal microbiota, are discussed.

Prognostic and Predictive Value of Immune-Related Gene Pair Signature in Primary Lower-Grade Glioma Patients

Immune-related gene pairs (IRGPs) have been associated with prognosis in various cancer types, but few studies have examined their prognostic capabilities in glioma patients. Here, we gathered the gene expression and clinical profile data of primary lower-grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA, containing CGGAseq1 and CGGAseq2), the Gene Expression Omnibus (GEO: GSE16011), and Rembrandt datasets. In the TCGA dataset, univariate Cox regression was performed to detect overall survival (OS)-related IRGs, Lasso regression, and multivariate Cox regression were used to screen robust prognosis-related IRGs, and 19 IRGs were selected for the construction of an IRGP prognostic signature. All patients were allotted to high- and low-risk subgroups based on the TCGA dataset median value risk score. Validation analysis indicated that the IRGP signature returned a stable prognostic value among all datasets. Univariate and multivariate Cox regression analyses indicated that the IRG -signature could efficiently predict the prognosis of primary LGG patients. The IRGP-signature-based nomogram model was built, revealing the reliable ability of the IRGP signature to predict clinical prognosis. The single-sample gene set enrichment analysis (ssGSEA) suggested that high-risk samples contained higher numbers of immune cells but featured lower tumor purity than low-risk samples. Finally, we verified the prognostic ability of the IRGP signature using experiments performed in LGG cells. These results indicated that the IRGP signature could be regarded as a stable prognostic assessment predictor for identifying high-risk primary LGG patients.

Integrated in silico and 3D in vitro model of macrophage migration in response to physical and chemical factors in the tumor microenvironment

Macrophages are abundant in the tumor microenvironment (TME), serving as accomplices to cancer cells for their invasion. Studies have explored the biochemical mechanisms that drive pro-tumor macrophage functions; however the role of TME interstitial flow (IF) is often disregarded. Therefore, we developed a three-dimensional microfluidic-based model with tumor cells and macrophages to study how IF affects macrophage migration and its potential contribution to cancer invasion. The presence of either tumor cells or IF individually increased macrophage migration directedness and speed. Interestingly, there was no additive effect on macrophage migration directedness and speed under the simultaneous presence of tumor cells and IF. Further, we present an in silico model that couples chemokine-mediated signaling with mechanosensing networks to explain our in vitro observations. In our model design, we propose IL-8, CCL2, and β-integrin as key pathways that commonly regulate various Rho GTPases. In agreement, in vitro macrophage migration remained elevated when exposed to a saturating concentration of recombinant IL-8 or CCL2 or to the co-addition of a sub-saturating concentration of both cytokines. Moreover, antibody blockade against IL-8 and/or CCL2 inhibited migration that could be restored by IF, indicating cytokine-independent mechanisms of migration induction. Importantly, we demonstrate the utility of an integrated in silico and 3D in vitro approach to aid the design of tumor-associated macrophage-based immunotherapeutic strategies.

Computational Simulation of Exosome Transport in Tumor Microenvironment

Cellular exosome-mediated crosstalk in tumor microenvironment (TME) is a critical component of anti-tumor immune responses. In addition to particle size, exosome transport and uptake by target cells is influenced by physical and physiological factors, including interstitial fluid pressure, and exosome concentration. These variables differ under both normal and pathological conditions, including cancer. The transport of exosomes in TME is governed by interstitial flow and diffusion. Based on these determinants, mathematical models were adapted to simulate the transport of exosomes in the TME with specified exosome release rates from the tumor cells. In this study, the significance of spatial relationship in exosome-mediated intercellular communication was established by treating their movement in the TME as a continuum using a transport equation, with advection due to interstitial flow and diffusion due to concentration gradients. To quantify the rate of release of exosomes by biomechanical forces acting on the tumor cells, we used a transwell platform with confluent triple negative breast cancer cells 4T1.2 seeded in BioFlex plates exposed to an oscillatory force. Exosome release rates were quantified from 4T1.2 cells seeded at the bottom of the well following the application of either no force or an oscillatory force, and these rates were used to model exosome transport in the transwell. The simulations predicted that a larger number of exosomes reached the membrane of the transwell for 4T1.2 cells exposed to the oscillatory force when compared to controls. Additionally, we simulated the interstitial fluid flow and exosome transport in a 2-dimensional TME with macrophages, T cells, and mixtures of these two populations at two different stages of a tumor growth. Computational simulations were carried out using the commercial computational simulation package, ANSYS/Fluent. The results of this study indicated higher exosome concentrations and larger interstitial fluid pressure at the later stages of the tumor growth. Quantifying the release of exosomes by cancer cells, their transport through the TME, and their concentration in TME will afford a deeper understanding of the mechanisms of these interactions and aid in deriving predictive models for therapeutic intervention.

Pancreatic Ductal Adenocarcinoma: Characteristics of Tumor Microenvironment and Barriers to Treatment

Pancreatic ductal adenocarcinoma remains a highly aggressive disease, with a 5-year relative survival rate of 10%. Numerous barriers to treatment exist, such as dense desmoplasia, infiltration of immune suppressor cells, inhibitory cytokines, low effector T-cell infiltration, and low tumor mutational burden. These factors help form a highly suppressive tumor microenvironment unique to pancreatic ductal adenocarcinoma. This review outlines barriers to treatment of pancreatic ductal adenocarcinoma by discussing the unique characteristics of the pancreatic tumor microenvironment and the factors that contribute to making pancreatic ductal adenocarcinoma such a challenging disease to treat.

Engineering approaches for studying immune-tumor cell interactions and immunotherapy

This review describes recent research that has advanced our understanding of the role of immune cells in the tumor microenvironment (TME) using advanced 3D in vitro models and engineering approaches. The TME can hinder effective eradication of tumor cells by the immune system, but immunotherapy has been able to reverse this effect in some cases. However, patient-to-patient variability in response suggests that we require deeper understanding of the mechanistic interactions between immune and tumor cells to improve response and develop novel therapeutics. Reconstruction of the TME using engineered 3D models allows high-resolution observation of cell interactions while allowing control of conditions such as hypoxia, matrix stiffness, and flow. Moreover, patient-derived organotypic models are an emerging tool for prediction of drug efficacy. This review highlights the importance of modeling and understanding the immune TME and describes new tools for identifying new biological targets, drug testing, and strategies for personalized medicine.

Hydrogels to engineer tumor microenvironments in vitro

Illustration of engineered hydrogel to recapitulate aspects of the tumor microenvironment.

Mechanical strain induces phenotypic changes in breast cancer cells and promotes immunosuppression in the tumor microenvironment

Breast cancer (BCa) proliferates within a complex, three-dimensional microenvironment amid heterogeneous biochemical and biophysical cues. Understanding how mechanical forces within the tumor microenvironment (TME) regulate BCa phenotype is of great interest. We demonstrate that mechanical strain enhanced the proliferation and migration of both estrogen receptor⁺ and triple-negative (TNBC) human and mouse BCa cells. Furthermore, a critical role for exosomes derived from cells subjected to mechanical strain in these pro-tumorigenic effects was identified. Exosome production by TNBC cells increased upon exposure to oscillatory strain (OS), which correlated with elevated cell proliferation. Using a syngeneic, orthotopic mouse model of TNBC, we identified that preconditioning BCa cells with OS significantly increased tumor growth and myeloid-derived suppressor cells (MDSCs) and M2 macrophages in the TME. This pro-tumorigenic myeloid cell enrichment also correlated with a decrease in CD8⁺ T cells. An increase in PD-L1⁺ exosome release from BCa cells following OS supported additive T cell inhibitory functions in the TME. The role of exosomes in MDSC and M2 macrophage was confirmed in vivo by cytotracking fluorescent exosomes, derived from labeled 4T1.2 cells, preconditioned with OS. In addition, in vivo internalization and intratumoral localization of tumor-cell derived exosomes was observed within MDSCs, M2 macrophages, and CD45-negative cell populations following direct injection of fluorescently-labeled exosomes. Our data demonstrate that exposure to mechanical strain promotes invasive and pro-tumorigenic phenotypes in BCa cells, indicating that mechanical strain can impact the growth and proliferation of cancer cell, alter exosome production by BCa, and induce immunosuppression in the TME by dampening anti-tumor immunity.

Immune Remodeling of the Extracellular Matrix Drives Loss of Cancer Stem Cells and Tumor Rejection

The nature of the tumor microenvironment (TME) influences the ability of tumor-specific T cells to control tumor growth. In this study, we performed an unbiased comparison of the TME of regulatory T-cell (Treg)-replete and Treg-depleted carcinogen-induced tumors, including Treg-depleted responding (regressing) and non-responding (growing) tumors. This analysis revealed an inverse relationship between extracellular matrix (ECM) and T-cell infiltrates where responding tumors were T-cell rich and ECM poor, whereas the converse was observed in non-responder tumors. For this reason, we hypothesized that the ECM acted as a barrier to successful T-cell infiltration and tumor rejection. However, further experiments revealed that this was not the case but instead showed that an effective T-cell response dramatically altered the density of ECM in the TME. Along with loss of ECM and high numbers of infiltrating T cells, responder tumors were distinguished by the development of lymphatic and blood vessel networks with specialized immune function. ECM-rich tumors exhibited a stem cell-like gene expression profile and superior tumor-initiating capacity, whereas such features were absent in responder tumors. Overall, these findings define an extended role for an effective immune response, not just in direct killing of tumor cells but in widescale remodeling of the TME to favor loss of ECM, elimination of cancer stem cells, and propagation of adaptive immunity.

Simultaneous Tumor and Stroma Targeting by Oncolytic Viruses

Current cancer therapeutics often insufficiently eradicate malignant cells due to the surrounding dense tumor stroma. This multi-componential tissue consists of mainly cancer-associated fibroblasts, the (compact) extracellular matrix, tumor vasculature, and tumor-associated macrophages, which all exert crucial roles in maintaining a pro-tumoral niche. Their continuous complex interactions with tumor cells promote tumor progression and metastasis, emphasizing the challenges in tumor therapy development. Over the last decade, advances in oncolytic virotherapy have shown that oncolytic viruses (OVs) are a promising multi-faceted therapeutic platform for simultaneous tumor and stroma targeting. In addition to promoting tumor cell oncolysis and systemic anti-tumor immunity, accumulating data suggest that OVs can also directly target stromal components, facilitating OV replication and spread, as well as promoting anti-tumor activity. This review provides a comprehensive overview of the interactions between native and genetically modified OVs and the different targetable tumor stromal components, and outlines strategies to improve stroma targeting by OVs.

The effects of luminal and trans-endothelial fluid flows on the extravasation and tissue invasion of tumor cells in a 3D in vitro microvascular platform

Throughout the process of metastatic dissemination, tumor cells are continuously subjected to mechanical forces resulting from complex fluid flows due to changes in pressures in their local microenvironments. While these forces have been associated with invasive phenotypes in 3D matrices, their role in key steps of the metastatic cascade, namely extravasation and subsequent interstitial migration, remains poorly understood. In this study, an in vitro model of the human microvasculature was employed to subject tumor cells to physiological luminal, trans-endothelial, and interstitial flows to evaluate their effects on those key steps of metastasis. Luminal flow promoted the extravasation potential of tumor cells, possibly as a result of their increased intravascular migration speed. Trans-endothelial flow increased the speed with which tumor cells transmigrated across the endothelium as well as their migration speed in the matrix following extravasation. In addition, tumor cells possessed a greater propensity to migrate in close proximity to the endothelium when subjected to physiological flows, which may promote the successful formation of metastatic foci. These results show important roles of fluid flow during extravasation and invasion, which could determine the local metastatic potential of tumor cells.

Evaluation of immune infiltrating of thyroid cancer based on the intrinsic correlation between pair-wise immune genes

INTRODUCTION

Unlike most mutation-driven cancers, thyroid cancer is thought to be highly dependent on changes in human hormone levels. It has become research hotspot using the change of gene expression level as a detection and diagnostic marker. The internal relationship between two genes and disease development is used to avoid the instability caused by single gene fluctuation. Aim It is possible to achieve early diagnosis in thyroid cancer during tumorigenesis and recurrence using IGPS (immune gene pairs).

METHODS

We extracted thyroid cancer data from The Cancer Genome Atlas (TCGA), using CIBERSORT algorithm to infiltrate out 22 immune cells types. We screened out IGPS that differ significantly between different groups, then used LinearSVC model to learn and screen features, combined with deep learning neural network model to predict benign and malignant cancer as well as patients at different groups.

KEY FINDINGS

There are significant differences of immune cell ratio in tumor stages and relapse samples. We screen out 42 and 64 IGPS for in normal-tumor and non-relapsed groups respectively, for example ASCC3-MAP3K7 and ATF2-SOCS5, have significant correlation in IGPS expression. Then we use the IGPS to train the tumor diagnostic classifier, obtain average AUC are both 0.99 after ten times cross-validation.

SIGNIFICANCE

The IGPS gives us new insight to explore immune cell infiltration of thyroid cancer, deep learning model can be further used in early diagnosis of thyroid cancer and estimation of the risk of recurrence.

Combination of Haemoglobin and Prognostic Nutritional Index Predicts the Prognosis of Postoperative Radiotherapy for Esophageal Squamous Cell Carcinoma

Purpose

To investigate the predictive effect of the combined markers of haemoglobin and prognostic nutritional index (PNI) on the long-term survival of patients undergoing postoperative radiotherapy for esophageal squamous cell carcinoma (ESCC).

Patients and Methods

A total of 238 patients were included in this retrospective analysis. PNI was calculated as the serum albumin level (g/L) + 5 × absolute lymphocyte count, and the cut-off values of PNI and haemoglobin were calculated by receiver operating characteristic (ROC) curve analysis. Then, we combined haemoglobin and PNI, named the H-PNI score, as a predictor of tumour prognosis. The patients were divided into three groups: H-PNI score of 2 (having both hyper-haemoglobin and high PNI), H-PNI score of 1 (having one of these haematological abnormalities), and H-PNI score of 0 (having neither hyper-haemoglobin nor high PNI). The overall survival (OS) rate was calculated using the Kaplan–Meier method, and survival differences between groups were evaluated using the Log rank test. Cox proportional hazards models were used for univariate and multivariate analyses. P values <0.05 indicated statistical significance.

Results

The cut-off values of haemoglobin and PNI were 132.5 (g/L) and 46.55, respectively. Kaplan–Meier analysis showed that patients with high haemoglobin and PNI levels had a significantly better prognosis than those with low haemoglobin and PNI levels (P = 0.015 and P = 0.002, respectively). Similarly, the survival rate was significantly lower in patients with an H-PNI score of 0 than in those with an H-PNI score of 1–2 (P=0.000). Univariate analysis indicated that differentiation, T and N classification, and H-PNI score were significantly associated with OS. Finally, differentiation (P=0.002), T and N classification (P=0.000), and H-PNI score (P=0.01) were independent prognostic factors for ESCC patients undergoing postoperative radiotherapy.

Conclusion

The H-PNI score was an independent prognostic factor for ESCC patients undergoing postoperative radiotherapy.

Deep learning-based image analysis methods for brightfield-acquired multiplex immunohistochemistry images

BACKGROUND

Multiplex immunohistochemistry (mIHC) permits the labeling of six or more distinct cell types within a single histologic tissue section. The classification of each cell type requires detection of the unique colored chromogens localized to cells expressing biomarkers of interest. The most comprehensive and reproducible method to evaluate such slides is to employ digital pathology and image analysis pipelines to whole-slide images (WSIs). Our suite of deep learning tools quantitatively evaluates the expression of six biomarkers in mIHC WSIs. These methods address the current lack of readily available methods to evaluate more than four biomarkers and circumvent the need for specialized instrumentation to spectrally separate different colors. The use case application for our methods is a study that investigates tumor immune interactions in pancreatic ductal adenocarcinoma (PDAC) with a customized mIHC panel.

METHODS

Six different colored chromogens were utilized to label T-cells (CD3, CD4, CD8), B-cells (CD20), macrophages (CD16), and tumor cells (K17) in formalin-fixed paraffin-embedded (FFPE) PDAC tissue sections. We leveraged pathologist annotations to develop complementary deep learning-based methods: (1) ColorAE is a deep autoencoder which segments stained objects based on color; (2) U-Net is a convolutional neural network (CNN) trained to segment cells based on color, texture and shape; and ensemble methods that employ both ColorAE and U-Net, collectively referred to as (3) ColorAE:U-Net. We assessed the performance of our methods using: structural similarity and DICE score to evaluate segmentation results of ColorAE against traditional color deconvolution; F1 score, sensitivity, positive predictive value, and DICE score to evaluate the predictions from ColorAE, U-Net, and ColorAE:U-Net ensemble methods against pathologist-generated ground truth. We then used prediction results for spatial analysis (nearest neighbor).

RESULTS

We observed that (1) the performance of ColorAE is comparable to traditional color deconvolution for single-stain IHC images (note: traditional color deconvolution cannot be used for mIHC); (2) ColorAE and U-Net are complementary methods that detect 6 different classes of cells with comparable performance; (3) combinations of ColorAE and U-Net into ensemble methods outperform using either ColorAE and U-Net alone; and (4) ColorAE:U-Net ensemble methods can be employed for detailed analysis of the tumor microenvironment (TME). We developed a suite of scalable deep learning methods to analyze 6 distinctly labeled cell populations in mIHC WSIs. We evaluated our methods and found that they reliably detected and classified cells in the PDAC tumor microenvironment. We also present a use case, wherein we apply the ColorAE:U-Net ensemble method across 3 mIHC WSIs and use the predictions to quantify all stained cell populations and perform nearest neighbor spatial analysis. Thus, we provide proof of concept that these methods can be employed to quantitatively describe the spatial distribution immune cells within the tumor microenvironment. These complementary deep learning methods are readily deployable for use in clinical research studies.

The Adenosine System at the Crossroads of Intestinal Inflammation and Neoplasia

Adenosine is a purine nucleoside, resulting from the degradation of adenosine triphosphate (ATP). Under adverse conditions, including hypoxia, ischemia, inflammation, or cancer, the extracellular levels of adenosine increase significantly. Once released, adenosine activates cellular signaling pathways through the engagement of the four known G-protein-coupled receptors, adenosine A₁ receptor subtype (A₁), A_2A, A_2B, and A₃. These receptors, expressed virtually on all immune cells, mitigate all aspects of immune/inflammatory responses. These immunosuppressive effects contribute to blunt the exuberant inflammatory responses, shielding cells, and tissues from an excessive immune response and immune-mediated damage. However, a prolonged persistence of increased adenosine concentrations can be deleterious, participating in the creation of an immunosuppressed niche, ideal for neoplasia onset and development. Based on this evidence, the present review has been conceived to provide a comprehensive and critical overview of the involvement of adenosine system in shaping the molecular mechanisms underlying the enteric chronic inflammation and in promoting the generation of an immunosuppressive niche useful for the colorectal tumorigenesis.

The history and advances in cancer immunotherapy: understanding the characteristics of tumor-infiltrating immune cells and their therapeutic implications

Immunotherapy has revolutionized cancer treatment and rejuvenated the field of tumor immunology. Several types of immunotherapy, including adoptive cell transfer (ACT) and immune checkpoint inhibitors (ICIs), have obtained durable clinical responses, but their efficacies vary, and only subsets of cancer patients can benefit from them. Immune infiltrates in the tumor microenvironment (TME) have been shown to play a key role in tumor development and will affect the clinical outcomes of cancer patients. Comprehensive profiling of tumor-infiltrating immune cells would shed light on the mechanisms of cancer-immune evasion, thus providing opportunities for the development of novel therapeutic strategies. However, the highly heterogeneous and dynamic nature of the TME impedes the precise dissection of intratumoral immune cells. With recent advances in single-cell technologies such as single-cell RNA sequencing (scRNA-seq) and mass cytometry, systematic interrogation of the TME is feasible and will provide insights into the functional diversities of tumor-infiltrating immune cells. In this review, we outline the recent progress in cancer immunotherapy, particularly by focusing on landmark studies and the recent single-cell characterization of tumor-associated immune cells, and we summarize the phenotypic diversities of intratumoral immune cells and their connections with cancer immunotherapy. We believe such a review could strengthen our understanding of the progress in cancer immunotherapy, facilitate the elucidation of immune cell modulation in tumor progression, and thus guide the development of novel immunotherapies for cancer treatment.

Tumor Immune Microenvironment Clusters in Localized Prostate Adenocarcinoma: Prognostic Impact of Macrophage Enriched/Plasma Cell Non-Enriched Subtypes

Background: Prostate cancer (PCa) is characterized by significant heterogeneity in its molecular, genomic, and immunologic characteristics. Methods: Whole transcriptome RNAseq data from The Cancer Genome Atlas of prostate adenocarcinomas (n = 492) was utilized. The immune microenvironment was characterized using the CIBERSORTX tool to identify immune cell type composition. Unsupervised hierarchical clustering was performed based on immune cell type content. Analyses of progression-free survival (PFS), distant metastases, and overall survival (OS) were performed using Kaplan–Meier estimates and Cox regression multivariable analyses. Results: Four immune clusters were identified, largely defined by plasma cell, CD4⁺ Memory Resting T Cells (CD4 MR), and M0 and M2 macrophage content (CD4 MR^HighPlasma Cell^HighM0^LowM2^Mid, CD4 MR^LowPlasma Cell^HighM0^LowM2^Low, CD4 MR^HighPlasma Cell^LowM0^HighM2^Low, and CD4 MR^HighPlasma Cell^LowM0^LowM2^High). The two macrophage-enriched/plasma cell non-enriched clusters (3 and 4) demonstrated worse PFS (HR 2.24, 95% CI 1.46–3.45, p = 0.0002) than the clusters 1 and 2. No metastatic events occurred in the plasma cell enriched, non-macrophage-enriched clusters. Comparing clusters 3 vs. 4, in patients treated by surgery alone, cluster 3 had zero progression events (p < 0.0001). However, cluster 3 patients had worse outcomes after post-operative radiotherapy (p = 0.018). Conclusion: Distinct tumor immune clusters with a macrophage-enriched, plasma cell non-enriched phenotype and reduced plasma cell enrichment independently characterize an aggressive phenotype in localized prostate cancer that may differentially respond to treatment.

Understanding Metal Dynamics Between Cancer Cells and Macrophages: Competition or Synergism?

Metal ions, such as selenium, copper, zinc, and iron are naturally present in the environment (air, drinking water, and food) and are vital for cellular functions at chemical, molecular, and biological levels. These trace elements are involved in various biochemical reactions by acting as cofactors for many enzymes and control important biological processes by binding to the receptors and transcription factors. Moreover, they are essential for the stabilization of the cellular structures and for the maintenance of genome stability. A body of preclinical and clinical evidence indicates that dysregulation of metal homeostasis, both at intracellular and tissue level, contributes to the pathogenesis of many different types of cancer. These trace minerals play a crucial role in preventing or accelerating neoplastic cell transformation and in modulating the inflammatory and pro-tumorigenic response in immune cells, such as macrophages, by controlling a plethora of metabolic reactions. In this context, macrophages and cancer cells interact in different manners and some of these interactions are modulated by availability of metals. The current review discusses the new findings and focuses on the involvement of these micronutrients in metabolic and cellular signaling mechanisms that influence macrophage functions, onset of cancer and its progression. An improved understanding of "metallic" cross-talk between macrophages and cancer cells may pave the way for innovative pharmaceutical or dietary interventions in order to restore the balance of these trace elements and also strengthen the chemotherapeutic treatment.

Role of Complex Networks for Integrating Medical Images and Radiomic Features of Intracranial Ependymoma Patients in Response to Proton Radiotherapy

Human cancers exhibit phenotypic diversity that medical imaging can precisely and non-invasively detect. Multiple factors underlying innovations and progresses in the medical imaging field exert diagnostic and therapeutic impacts. The emerging field of radiomics has shown unprecedented ability to use imaging information in guiding clinical decisions. To achieve clinical assessment that exploits radiomic knowledge sources, integration between diverse data types is required. A current gap is the accuracy with which radiomics aligns with clinical endpoints. We propose a novel methodological approach that synergizes data volumes (images), tissue-contextualized information breadth, and network-driven resolution depth. Following the Precision Medicine paradigm, disease monitoring and prognostic assessment are tackled at the individual level by examining medical images acquired from two patients affected by intracranial ependymoma (with and without relapse). The challenge of spatially characterizing intratumor heterogeneity is tackled by a network approach that presents two main advantages: (a) Increased detection in the image domain power from high spatial resolution, (b) Superior accuracy in generating hypotheses underlying clinical decisions.

Tumor-derived CCL20 affects B16 melanoma growth in mice

BACKGROUND

Chemokine ligand-20 (CCL20) expressed in the epidermis is a potent impetus for the recruitment of CC-chemokine receptor 6 (CCR6)-expressing subsets of DCs, B-cells and memory T-cells into the skin. CCL20 and CCR6+ immune cells have been detected in chronic inflammatory skin diseases and several malignancies, including melanoma. Yet, the functional contribution of the CCR6/CCL20 axis for melanoma progression remains controversial.

OBJECTIVE

The functional contribution of CCR6-expressing immune cell subsets and local CCL20 in the tumor microenvironment for the immune control of melanoma was studied.

METHODS

Homeostatic and inducible CCL20 secretion of murine (B16, Ret) and human (A375, C32) melanoma cells was analyzed by ELISA. To assess the functional relevance of CCR6/CCL20 interactions on local tumor progression, prestimulated or retrovirally transduced B16/F1 melanoma cells overexpressing CCL20 (B16-CCL20) were injected subcutaneously into C57BL/6 Wt mice and congenic CCR6-deficient (CCR6^-/-) mice. Infiltrating leucocytes were examined by flow cytometry in tumors and draining lymph nodes (DLNs).

RESULTS

Melanoma cell lines up-regulate CCL20 secretion upon stimulation with pro-inflammatory cytokines in vitro. While only moderate changes in phenotype and composition of leucocytes were detected in advanced tumors and DLNs, mice injected with CCR6+ B16-CCL20 cells developed smaller tumors compared to B16-Control injected littermates, with CCR6-/- mice displaying the most pronounced reduction in tumor growth and incidence.

CONCLUSION

Our results suggest that CCR6/CCL20 interactions and individual independent effects of CCL20 and CCR6 in the microenvironment may be essential for melanoma progression and suggest a decisive role of this chemokine axis for melanoma pathogenesis beyond chemoattraction.

Coley's immunotherapy revived: Innate immunity as a link in priming cancer cells for an attack by adaptive immunity

There is no doubt that immunotherapy lies in the spotlight of current cancer research and clinical trials. However, there are still limitations in the treatment response in certain types of tumors largely due to the presence of the complex network of immunomodulatory and immunosuppressive pathways. These limitations are not likely to be overcome by current immunotherapeutic options, which often target isolated steps in immune pathways preferentially involved in adaptive immunity. Recently, we have developed an innovative anti-cancer immunotherapeutic strategy that initially elicits a strong innate immune response with subsequent activation of adaptive immunity in mouse models. Robust primary innate immune response against tumor cells is induced by toll-like receptor ligands and anti-CD40 agonistic antibodies combined with the phagocytosis-stimulating ligand mannan, anchored to a tumor cell membrane by biocompatible anchor for membrane. This immunotherapeutic approach results in a dramatic therapeutic response in large established murine subcutaneous tumors including melanoma, sarcoma, pancreatic adenocarcinoma, and pheochromocytoma. Additionally, eradication of metastases and/or long-lasting resistance to subsequent re-challenge with tumor cells was also accomplished. Current and future advantages of this immunotherapeutic approach and its possible combinations with other available therapies are discussed in this review.

Metabolic crosstalk in the breast cancer microenvironment

During tumorigenesis, breast tumour cells undergo metabolic reprogramming, which generally includes enhanced glycolysis, tricarboxylic acid cycle activity, glutaminolysis and fatty acid biosynthesis. However, the extension and functional importance of these metabolic alterations may diverge not only according to breast cancer subtypes, but also depending on the interaction of cancer cells with the complex surrounding microenvironment. This microenvironment comprises a variety of non-cancerous cells, such as immune cells (e.g. macrophages, lymphocytes, natural killer cells), fibroblasts, adipocytes and endothelial cells, together with extracellular matrix components and soluble factors, which influence cancer progression and are predictive of clinical outcome. The continuous interaction between cancer and stromal cells results in metabolic competition and symbiosis, with oncogenic-driven metabolic reprogramming of cancer cells shaping the metabolism of neighbouring cells and vice versa. This review addresses current knowledge on this metabolic crosstalk within the breast tumour microenvironment (TME). Improved understanding of how metabolism in the TME modulates cancer development and evasion of tumour-suppressive mechanisms may provide clues for novel anticancer therapeutics directed to metabolic targets.

Clinical developments of antitumor polymer therapeutics

Polymer therapeutics encompasses polymer-drug conjugates that are nano-sized, multicomponent constructs already in the clinic as antitumor compounds, either as single agents or in combination with other organic drug scaffolds. Nanoparticle-based polymer-conjugated therapeutics are poised to become a leading delivery strategy for cancer treatments as they exhibit prolonged half-life, higher stability and selectivity, water solubility, longer clearance time, lower immunogenicity and antigenicity and often also specific targeting to tissues or cells. Compared to free drugs, polymer-tethered drugs preferentially accumulate in the tumor sites unlike conventional chemotherapy which does not discriminate between the cancer cells and healthy cells, thereby causing severe side-effects. It is also desirable that the drug reaches its site of action at a particular concentration and the therapeutic dose remains constant over a sufficiently long period of time. This can be achieved by opting for new formulations possessing polymeric systems of drug carriers. However, many challenges still remain unanswered in polymeric drug conjugates which need to be readdressed and therefore, can broaden the scope of this field. This review highlights some of the antitumor polymer therapeutics including polymer-drug conjugates, polymeric micelles, polymeric liposomes and other polymeric nanoparticles that are currently under investigation.

Targeting the Tumor Microenvironment in Renal Cell Cancer Biology and Therapy

Renal cell cancer (RCC) is a highly vascularized and immunogenic tumor type. The inhibition of vessel formation by anti-angiogenic therapies, as well as the stimulation of the immune system by immunotherapy has revolutionized the therapeutic landscape of RCC in recent years. Nevertheless, both therapies are associated with therapy resistance due to a highly dynamic, adaptive and heterogeneous tumor microenvironment (TME). The aim of this short review article is to provide an overview of the components of the RCC TME as well as to discuss their contribution to disease progression. In addition, we report on preclinical and clinical findings and how the different TME components can be modulated to impede treatment progression as well as to overcome therapy resistance to anti-angiogenic or immunomodulating therapy concepts. Furthermore, we discuss the predictive and prognostic role of the TME in RCC therapy. We also report on the concept of combinational targeting of anti-angiogenic therapies and immune checkpoint inhibitor therapy, also including the latest results of clinical studies discussed at recent oncological meetings. Finally, promising new therapeutic targets within the TME are mentioned.

The matrix environmental and cell mechanical properties regulate cell migration and contribute to the invasive phenotype of cancer cells

The minimal structural unit of a solid tumor is a single cell or a cellular compartment such as the nucleus. A closer look inside the cells reveals that there are functional compartments or even structural domains determining the overall properties of a cell such as the mechanical phenotype. The mechanical interaction of these living cells leads to the complex organization such as compartments, tissues and organs of organisms including mammals. In contrast to passive non-living materials, living cells actively respond to the mechanical perturbations occurring in their microenvironment during diseases such as fibrosis and cancer. The transformation of single cancer cells in highly aggressive and hence malignant cancer cells during malignant cancer progression encompasses the basement membrane crossing, the invasion of connective tissue, the stroma microenvironments and transbarrier migration, which all require the immediate interaction of the aggressive and invasive cancer cells with the surrounding extracellular matrix environment including normal embedded neighboring cells. All these steps of the metastatic pathway seem to involve mechanical interactions between cancer cells and their microenvironment. The pathology of cancer due to a broad heterogeneity of cancer types is still not fully understood. Hence it is necessary to reveal the signaling pathways such as mechanotransduction pathways that seem to be commonly involved in the development and establishment of the metastatic and mechanical phenotype in several carcinoma cells. We still do not know whether there exist distinct metastatic genes regulating the progression of tumors. These metastatic genes may then be activated either during the progression of cancer by themselves on their migration path or in earlier stages of oncogenesis through activated oncogenes or inactivated tumor suppressor genes, both of which promote the metastatic phenotype. In more detail, the adhesion of cancer cells to their surrounding stroma induces the generation of intracellular contraction forces that deform their microenvironments by alignment of fibers. The amplitude of these forces can adapt to the mechanical properties of the microenvironment. Moreover, the adhesion strength of cancer cells seems to determine whether a cancer cell is able to migrate through connective tissue or across barriers such as the basement membrane or endothelial cell linings of blood or lymph vessels in order to metastasize. In turn, exposure of adherent cancer cells to physical forces, such as shear flow in vessels or compression forces around tumors, reinforces cell adhesion, regulates cell contractility and restructures the ordering of the local stroma matrix that leads subsequently to secretion of crosslinking proteins or matrix degrading enzymes. Hence invasive cancer cells alter the mechanical properties of their microenvironment. From a mechanobiological point-of-view, the recognized physical signals are transduced into biochemical signaling events that guide cellular responses such as cancer progression after the malignant transition of cancer cells from an epithelial and non-motile phenotype to a mesenchymal and motile (invasive) phenotype providing cellular motility. This transition can also be described as the physical attempt to relate this cancer cell transitional behavior to a T1 phase transition such as the jamming to unjamming transition. During the invasion of cancer cells, cell adaptation occurs to mechanical alterations of the local stroma, such as enhanced stroma upon fibrosis, and therefore we need to uncover underlying mechano-coupling and mechano-regulating functional processes that reinforce the invasion of cancer cells. Moreover, these mechanisms may also be responsible for the awakening of dormant residual cancer cells within the microenvironment. Physicists were initially tempted to consider the steps of the cancer metastasis cascade as single events caused by a single mechanical alteration of the overall properties of the cancer cell. However, this general and simple view has been challenged by the finding that several mechanical properties of cancer cells and their microenvironment influence each other and continuously contribute to tumor growth and cancer progression. In addition, basement membrane crossing, cell invasion and transbarrier migration during cancer progression is explained in physical terms by applying physical principles on living cells regardless of their complexity and individual differences of cancer types. As a novel approach, the impact of the individual microenvironment surrounding cancer cells is also included. Moreover, new theories and models are still needed to understand why certain cancers are malignant and aggressive, while others stay still benign. However, due to the broad variety of cancer types, there may be various pathways solely suitable for specific cancer types and distinct steps in the process of cancer progression. In this review, physical concepts and hypotheses of cancer initiation and progression including cancer cell basement membrane crossing, invasion and transbarrier migration are presented and discussed from a biophysical point-of-view. In addition, the crosstalk between cancer cells and a chronically altered microenvironment, such as fibrosis, is discussed including the basic physical concepts of fibrosis and the cellular responses to mechanical stress caused by the mechanically altered microenvironment. Here, is highlighted how biophysical approaches, both experimentally and theoretically, have an impact on classical hallmarks of cancer and fibrosis and how they contribute to the understanding of the regulation of cancer and its progression by sensing and responding to the physical environmental properties through mechanotransduction processes. Finally, this review discusses various physical models of cell migration such as blebbing, nuclear piston, protrusive force and unjamming transition migration modes and how they contribute to cancer progression. Moreover, these cellular migration modes are influenced by microenvironmental perturbances such as fibrosis that can induce mechanical alterations in cancer cells, which in turn may impact the environment. Hence, the classical hallmarks of cancer need to be refined by including biomechanical properties of cells, cell clusters and tissues and their microenvironment to understand mechano-regulatory processes within cancer cells and the entire organism.

Mechanical stress-induced autophagic response: A cancer-enabling characteristic?

Metastasis is the leading cause of cancer mortality. Throughout the cascade of metastasis, cancer cells are exposed to both chemical and mechanical cues which influence their migratory behavior and survival. Mechanical forces in the milieu of cancer may arise due to excessive growth of cells in a confinement as in case of solid tumors, interstitial flows within tumors and due to blood flow in the vasculature as in case of circulating tumor cells. The focus of this review is to highlight the mechanical forces prevalent in the cancer microenvironment and discuss the impact of mechanical stresses on cancer progression, with special focus on mechanically induced autophagic response in cancer cells. Autophagy is a cellular homeostatic mechanism that a cell employs not only for recycling of damaged organelles and turnover of proteins involved in cellular migration but also as an adaptive response to survive through unfavourable stresses. Elucidation of the role of mechanically triggered autophagic response may lead to a better understanding of the mechanobiological aspects of metastatic cancer and unravelling the associated signaling mechanochemical pathways may hint at potential therapeutic targets.

Fiber Density Modulates Cell Spreading in 3D Interstitial Matrix Mimetics

Cellular phenotype is heavily influenced by the extracellular matrix (ECM), a complex and tissue-specific three-dimensional structure with distinct biophysical and biochemical properties. As naturally derived cell culture platforms are difficult to controllably modulate, engineered synthetic ECMs have facilitated our understanding of how specific matrix properties direct cell behavior. However, synthetic approaches typically lack fibrous topography, a hallmark of stromal and interstitial ECMs in vivo. To construct tunable biomimetic models with physiologic microstructure, we developed a versatile approach to generate modular fibrous architectures in 3D. Photo-cross-linkable polymers were electrospun, photopatterned into desired lengths, and coencapsulated alongside cells within natural biopolymer, semisynthetic, and synthetic hydrogels. Cells encapsulated within fiber-reinforced hydrogel composites (FHCs) demonstrated accelerated spreading rates compared to in gels lacking such fibrous topography. Furthermore, increases in fiber density at constant bulk hydrogel elastic modulus produced morphologically distinct cell populations and modulated cellular mechanosensing in 3D, as evidenced by increased nuclear localization of the mechanosensitive transcription factor, Yes-associated protein (YAP). This work documents the impact of physical guidance cues in 3D and establishes a novel approach to generating more physiologic tissue- and disease-specific biomimetic models.

Long-term impact of prognostic nutritional index in cervical esophageal squamous cell carcinoma patients undergoing definitive radiotherapy

Background

The prognostic nutritional index (PNI) has been found to have prognostic value in several cancers, and we aimed to determine its predictive value for the long-term prognosis of cervical esophageal squamous cell carcinoma (CESCC) patients treated with chemoradiotherapy (CRT).

Methods

The data for 106 CESCC patients who received radiotherapy with or without chemotherapy at the Cancer Hospital of Fujian Medical University from June 1, 2000 to December 31, 2015 were retrospectively analyzed. According to serum measurements taken before therapy, the PNI was calculated as albumin (g/L) + 5 × total lymphocyte count. The association between PNI and overall survival (OS) was determined by the Kaplan-Meier method and Cox proportional regression model analysis.

Results

The median follow-up time was 19 months. The optimal cutoff value for PNI was calculated to be 48.15, and patients were divided into a low PNI group (<48.15) and high PNI group (≥48.15). Univariate analysis showed that a low survival rate was significantly associated with male gender (P=0.004), tumor length ≥5.0 cm (P=0.043), radiotherapy technique (P=0.016), synchronous chemotherapy (P=0.012), lymphocyte-monocyte ratio (LMR) (P=0.007), neutrophil-lymphocyte ratio (NLR) (P=0.007), lung cancer inflammation index (ALI) (P=0.008), cervical esophageal carcinoma inflammation index (CEI) (P=0.043), and PNI (P<0.001). The OS was higher in the high PNI group than in the low PNI group. On multivariate analysis, gender (P=0.004), radiotherapy technique (P=0.029), and PNI (P=0.007) were independent prognostic factors in CESCC treated with CRT.

Conclusions

The PNI value is a simple, reliable, and reproducible indicator for improving the accuracy of patient prognosis. And larger-scale studies are warranted to validate these findings.

Deconstructing Immune Microenvironments of Lymphoid Tissues for Reverse Engineering

The immune microenvironment presents a diverse panel of cues that impacts immune cell migration, organization, differentiation, and the immune response. Uniquely, both the liquid and solid phases of every specific immune niche within the body play an important role in defining cellular functions in immunity at that particular location. The in vivo immune microenvironment consists of biomechanical and biochemical signals including their gradients, surface topography, dimensionality, modes of ligand presentation, and cell-cell interactions, and the ability to recreate these immune biointerfaces in vitro can provide valuable insights into the immune system. This manuscript reviews the critical roles played by different immune cells and surveys the current progress of model systems for reverse engineering of immune microenvironments with a focus on lymphoid tissues.

Immunotherapy: enhancing the efficacy of this promising therapeutic in multiple cancers

Cancer treatments often reach a refractory period leading to treatment failure and patients developing disease recurrence. This can be due to tumour cells escaping the immune response and creating an immunosuppressive microenvironment enhancing cancer progression. Immunotherapy has become a promising tool for cancer treatment as it restores the anti-tumour response of the patient's immune system. Immune checkpoint inhibitors are the most widely studied immunotherapies worldwide and are now approved for multiple cancers. However, chimeric antigen receptor (CAR)-T cell therapy has also shown promise by targeting T lymphocytes that are genetically modified ex vivo to express CARs and this is now approved to treat some haematological cancers. Although immunotherapy has shown successful treatment outcomes in multiple cancers, some patients do not respond to this treatment. Therefore, approaches to enhance the efficacy of immunotherapies are likely to be the key to improve their effectiveness. Therefore, combination therapies of checkpoint inhibitors +/- chemotherapy are at the forefront of current research. Furthermore, biomarkers that predict treatment response are now beginning to emerge. Additionally, utilising nanoparticles as a newly targeted drug delivery system to enhance CAR-T cell therapy may enhance the efficacy of the cells when re-infused within the patient. Even if efficacy is enhanced, severe immune-related adverse events (irAEs) occur that are life-threatening and could lead to therapy being stopped. Therefore, predictive biomarkers for toxicity are also needed to improve both the patient's quality of life and treatment outcomes. This review will look at the current immunotherapies in clinical trials and discuss how to enhance their efficacy.

Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment

Multiscale systems biology and systems pharmacology are powerful methodologies that are playing increasingly important roles in understanding the fundamental mechanisms of biological phenomena and in clinical applications. In this review, we summarize the state of the art in the applications of agent-based models (ABM) and hybrid modeling to the tumor immune microenvironment and cancer immune response, including immunotherapy. Heterogeneity is a hallmark of cancer; tumor heterogeneity at the molecular, cellular, and tissue scales is a major determinant of metastasis, drug resistance, and low response rate to molecular targeted therapies and immunotherapies. Agent-based modeling is an effective methodology to obtain and understand quantitative characteristics of these processes and to propose clinical solutions aimed at overcoming the current obstacles in cancer treatment. We review models focusing on intra-tumor heterogeneity, particularly on interactions between cancer cells and stromal cells, including immune cells, the role of tumor-associated vasculature in the immune response, immune-related tumor mechanobiology, and cancer immunotherapy. We discuss the role of digital pathology in parameterizing and validating spatial computational models and potential applications to therapeutics.

Tumor-Associated T-Lymphocytes and Macrophages are Decreased in Endometrioid Endometrial Carcinoma with MELF-Pattern Stromal Changes

Microcystic, elongated, fragmented (MELF)-pattern is an unusual morphology of myometrial invasive front in endometrioid endometrial carcinoma (EA). The aim of the study was to investigate potential correlation between MELF-pattern and peritumoral inflammatory immune response. A total of 96 out of 368 patients were included in this study. CD3, CD20, CD57. CD68 and S100 markers were used for the detection of tumor-associated T-lymphocytes (TAT), tumor-associated B-lymphocytes (TAB), tumor-associated NK-lymphocytes (NK), tumor-associated macrophages and dendritic cells respectively. Mann-Whitney tests, receiver operating characteristic (ROC) curve analysis, and Spearman correlation were used as methods for statistical analyses. Odds ratio with 95% confidence interval (95% CI) was determined with the use of a logistic regression model. A p < 0.05 was considered statistically significant. Our results suggested that the number of CD3 and CD68 cells were significantly lower (p < 0.001) in cases of endometrioid carcinoma with MELF-pattern. A significant correlation between the presence of MELF-pattern and decrease of CD3 positive T-lymphocytes (r = 0.691; p < 0.001) was also observed. Additionally, we found an inverse correlation between the presence of MELF-pattern and TAM (r = 0.568; p = 0.001). Therefore, our data suggest that MELF-pattern may be associated with EA stroma fibrosis that contains immune cells infiltration and demonstrated a decrease in the number of TAT and TAM cells. This may indicate the poor clinical prognosis of this disease.