Multiscale modeling reveals angiogenesis-induced drug resistance in brain tumors and predicts a synergistic drug combination targeting EGFR and VEGFR pathways

Comprehensive analysis of the value of angiogenesis and stemness-related genes in the prognosis and immunotherapy of ovarian cancer

Tumor angiogenesis and the presence of cancer stem cells (CSCs) are critical characteristics of tumors. Previous research has demonstrated that cancer stem cells promote tumor angiogenesis, while increased vascularity, in turn, fosters the growth of cancer stem cells. This creates a detrimental cycle that contributes to tumor progression. However, studies investigating the angiogenesis and stemness characteristics in ovarian cancer (OV) are limited. In this study, we employed cluster analysis and LASSO methods to assess the significance of angiogenesis- and stemness-related genes in the efficacy of OV immunotherapy. Through multivariate Cox regression analysis and Friends analysis, we identified TNFSF11 as the most significant prognostic gene associated with angiogenesis and stemness. Additionally, molecular docking results confirmed that TNFSF11 exhibits a high affinity for sorafenib and sunitinib. In summary, for the first time, we conducted a comprehensive analysis of the roles of angiogenesis and stemness-related genes in the prognosis and immunotherapy of OV patients, revealing TNFSF11 as a novel therapeutic target.

Novel curcumin-based analogues as potential VEGFR2 inhibitors with promising metallic loading nanoparticles: synthesis, biological evaluation, and molecular modelling investigation

VEGFR2 inhibition has been established as a therapeutic approach for managing cancer. A series of curcumin-based analogues were designed, synthesized, and screened for their anticancer activity against MCF-7 and HepG-2 cell lines and WISH normal cells. Compounds 4b, 4d, 4e, and 4f showed potent cytotoxicity against MCF-7 with IC50 values of 0.49, 0.14, 0.01, and 0.32 μM, respectively, compared to curcumin (IC50 = 13.8 μM) and sorafenib (IC50 = 2.13 μM). Interestingly, compound 4e, the most active compound, exhibited potent VEGFR2 inhibition with an IC50 value of 11.6 nM (96.5% inhibition) compared to sorafenib with an IC50 value of 30 nM (94.8% inhibition). Additionally, compound 4e significantly induced apoptotic cell death in MCF-7 cells by 41.1% compared to a control group (0.8%), halting cell division during the G2/M phase by 39.8% compared to the control (21.7%). Molecular docking-coupled dynamics simulations highlighted the bias of the VEGFR2 pocket towards compound 4e compared to other synthesized compounds. Predicting superior binding affinities and relevant interactions with the pocket's key residues recapitulated in vitro findings towards higher inhibition activity for compound 4e. Furthermore, compound 4e with adequate pharmacokinetic and drug-likeness profiles in terms of ADME and safety characteristics can serve as a promising clinical candidate for future lead optimization and development. Notably, 4e-Fe2O3-humic acid NPs exhibited potent cytotoxicity with IC50 values of 2.41 and 13.4 ng mL-1 against MCF-7 and HepG-2 cell lines, respectively. Hence, compound 4e and its Fe2O3-humic acid-NPs could be further developed as promising anti-breast cancer agents.

Cross-expression analysis reveals patterns of coordinated gene expression in spatial transcriptomics

Spatial transcriptomics promises to transform our understanding of tissue biology by molecularly profiling individual cells in situ. A fundamental question they allow us to ask is how nearby cells orchestrate their gene expression. To investigate this, we introduce cross-expression, a novel framework for discovering gene pairs that coordinate their expression across neighboring cells. Just as co-expression quantifies synchronized gene expression within the same cells, cross-expression measures coordinated gene expression between spatially adjacent cells, allowing us to understand tissue gene expression programs with single cell resolution. Using this framework, we recover ligand-receptor partners and discover gene combinations marking anatomical regions. More generally, we create cross-expression networks to find gene modules with orchestrated expression patterns. Finally, we provide an efficient R package to facilitate cross-expression analysis, quantify effect sizes, and generate novel visualizations to better understand spatial gene expression programs.

Cetuximab chemotherapy resistance: Insight into the homeostatic evolution of head and neck cancer (Review)

The complex evolution of genetic alterations in cancer that occurs in vivo is a selective process involving numerous factors and mechanisms. Chemotherapeutic agents that prevent the growth and spread of cancer cells induce selective pressure, leading to rapid artificial selection of resistant subclones. This rapid evolution is possible because antineoplastic drugs promote alterations in tumor‑cell metabolism, thus creating a bottleneck event. The few resistant cells that survive in this new environment obtain differential reproductive success that enables them to pass down the newly selected resistant gene pool. The present review aims to summarize key findings of tumor evolution, epithelial‑mesenchymal transition and resistance to cetuximab therapy in head and neck squamous cell carcinoma.

Multiscale modeling of the dynamic growth of cancerous tumors under the influence of chemotherapy drugs

A comprehensive model of chemotherapy treatment of cancer can help us to optimize the drug administration/dosage and improve the treatment outcome. In the present study, a multiscale mathematical model of tumor growth during chemotherapy treatment is developed to predict its response to the medication and cancer progression. The modeling is a continuous multiscale simulation consisting of three tissue phases including cancer cells, normal cells, and extracellular matrix. In addition to the drug administration, the impacts of immune cells, programmed cell death, nutrient competition, and glucose concentration are included. The outputs of our mathematical model conform to the published experimental and clinical data, and it can be used in optimizing chemotherapy, and personalized cancer treatment.

Neovascularization directed by CAVIN1/CCBE1/VEGFC confers TMZ-resistance in glioblastoma

Acquisition of resistance to temozolomide (TMZ) poses a significant challenge in glioblastoma (GBM) therapy. Neovascularization, a pivotal process in tumorigenesis and development, remains poorly understood in its contribution to chemoresistance in GBMs. This study unveils aberrant vascular networks within TMZ-resistant (TMZ-R) GBM tissues and identifies the extracellular matrix (ECM) protein CCBE1 as a potential mediator. Through in vivo and in vitro experiments involving gain and loss of function assessments, we demonstrate that high expression of CCBE1 promotes hyper-angiogenesis and orchestrates partial endothelial-to-mesenchymal transition (EndMT) in human microvascular endothelial cells (HCMEC/d3) within GBM. This is likely driven by VEGFC/Rho signaling. Intriguingly, CCBE1 overexpression substantially fails to promote tumor growth, but endows resistance to GBM cells in a vascular endothelial cell-dependent manner. Mechanically, the constitutive phosphorylation of SP1 at Ser101 drives the upregulation of CCBE1 transcription in TMZ resistant tumors, and the excretion of CCBE1 depends on caveolae associated protein 1 (CAVIN1) binding and assembling. Tumor cells derived CCBE1 promotes VEGFC maturation, activates VEGFR2/VEGFR3/Rho signaling in vascular endothelial cells, and ultimately results in hyper-angiogenesis in TMZ-R tumors. Collectively, the current study uncovers the cellular and molecular basis of abnormal angiogenesis in a chemo resistant microenvironment, implying that curbing CCBE1 is key to reversing TMZ resistance.

Knockdown of ASF1B inhibits cell proliferation, migration, invasion and cisplatin resistance in gastric cancer through the Myc pathway

Gastric cancer (GC) is a prevalent malignancy in the digestive system that poses a serious threat to human health. Anti-silencing function 1B (ASF1B) performs an important role in the progression of numerous tumors; however, its function in GC still requires further elucidation. Using data from The Cancer Genome Atlas, the expression levels of ASF1B in GC tissues were analyzed and a survival curve for high-ASF1B expression and low-ASF1B expression groups was plotted using the Kaplan-Meier method. Reverse transcription-quantitative PCR was performed to evaluate ASF1B expression in GC tissues and cells. Small interfering RNAs targeting ASF1B were transfected into HGC-27 and AGS cells to silence ASF1B expression. Cell viability, proliferation, migration, invasion, and apoptosis in HGC-27 and AGS cells was assessed using cell counting kit-8 assay, colony formation assay, wound healing assay, Transwell assay and flow cytometry, respectively. The protein changes were assessed using western blotting. Gene Set Enrichment Analysis (GSEA) was used to identify ASF1B related pathways. The results demonstrated that ASF1B expression was increased in GC tissues and cells compared with adjacent healthy tissues and normal cells (GES-1), and high expression of ASF1B was associated with poor survival outcomes in patients with GC. Silencing ASF1B inhibited cell viability, colony formation, migration, invasion and cisplatin resistance, while also attenuating the apoptotic capability of HGC-27 and AGS cells. GSEA showed that ASF1B could activate the Myc-targets-v1 and Myc-targets-v2 pathways. Moreover, silencing ASF1B inhibited the Myc pathway-related proteins Myc, minichromosome maintenance (MCM)4 and MCM5. Overexpression of Myc reversed the inhibitory effect of ASF1B silencing on AGS cell proliferation, invasion and cisplatin resistance. In conclusion, the results indicate that knockdown of ASF1B may suppress GC cell proliferation, migration and invasion, and promote cell apoptosis and cisplatin sensitivity by modulating the Myc pathway, thereby offering novel possibilities for reversing cisplatin resistance in GC.

The mechanism of action and biodistribution of a novel EGFR/VEGF bispecific fusion protein that exhibited superior antitumor activities

Despite the promising clinical benefits of therapies targeting epidermal growth factor receptor (EGFR) or vascular endothelial growth factor (VEGF) with antibodies in various cancers, resistance to these therapies will inevitably develop following treatment. Recent studies suggest that crosstalk between the EGFR and VEGF signaling pathways might be involved in the development of resistance. Therefore, simultaneous blockade of EGFR and VEGF signaling may be able to counteract this resistance and improve clinical outcomes. Here, we devised a fusion protein with two copies of VEGFR1 domain 2 connected to the C-terminus of cetuximab that can simultaneously bind to EGFR and VEGF and effectively inhibit target cell growth mediated by these two pathways. Furthermore, the fusion protein could bring soluble VEGF into target cells for degradation through internalization upon binding to EGFR. Tissue distribution in mice confirmed that the fusion protein effectively accumulated in tumors compared to its mAb counterpart cetuximab. These features resulted in stronger antitumor efficacies in vivo than the combination of bevacizumab and cetuximab. Thus, we provide a promising new strategy for the treatment of EGFR-overexpressing cancers.

MiR-218-5p/EGFR Signaling in Arsenic-Induced Carcinogenesis

BACKGROUND

Arsenic is a well-known carcinogen inducing lung, skin, bladder, and liver cancer. Abnormal epidermal growth factor receptor (EGFR) expression is common in lung cancer; it is involved in cancer initiation, development, metastasis, and treatment resistance. However, the underlying mechanism for arsenic-inducing EGFR upregulation remains unclear.

METHODS

RT-PCR and immunoblotting assays were used to detect the levels of miR-218-5p and EGFR expression. The Luciferase assay was used to test the transcriptional activity of EGFR mediated by miR-218-5p. Cell proliferation, colony formation, wound healing, migration assays, tube formation assays, and tumor growth assays were used to study the function of miR-218-5p/EGFR signaling.

RESULTS

EGFR and miR-218-5p were dramatically upregulated and downregulated in arsenic-induced transformed (As-T) cells, respectively. MiR-218-5p acted as a tumor suppressor to inhibit cell proliferation, migration, colony formation, tube formation, tumor growth, and angiogenesis. Furthermore, miR-218-5p directly targeted EGFR by binding to its 3'-untranslated region (UTR). Finally, miR-218-5p exerted its antitumor effect by inhibiting its direct target, EGFR.

CONCLUSION

Our study highlights the vital role of the miR-218-5p/EGFR signaling pathway in arsenic-induced carcinogenesis and angiogenesis, which may be helpful for the treatment of lung cancer induced by chronic arsenic exposure in the future.

Novel considerations on EGFR-based therapy as a contributor to cancer cell death in NSCLC

Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) represented by gefitinib and erlotinib are widely used in treating non-small cell lung cancer (NSCLC). However, acquired resistance to EGFR-TKI treatment remains a clinical challenge. In recent years, emerging research investigated in EGFR-TKI-based combination therapy regimens, and remarkable achievements have been reported. This article focuses on EGFR-TKI-based regimens, reviews the standard and novel application of EGFR targets, and summarizes the mechanisms of EGFR-TKI combinations including chemotherapy, anti-vascular endothelial growth factor monoclonal antibodies, and immunotherapy in the treatment of NSCLC. Additionally, we summarize clinical trials of EGFR-TKI-based combination therapy expanding indications to EGFR mutation-negative lung malignancies. Moreover, novel strategies are under research to explore new drugs with good biocompatibility. Nanoparticles encapsulating non-coding RNA and chemotherapy of new dosage forms drawn great attention and showed promising prospects in effective delivery and stable release. Overall, as the development of resistance to EGFR-TKIs treatment is inevitable in most of the cases, further research is needed to clarify the underlying mechanism of the resistance, and to evaluate and establish EGFR-TKI combination therapies to diversify the treatment landscape for NSCLC.

Recent progress on vascular endothelial growth factor receptor inhibitors with dual targeting capabilities for tumor therapy

Vascular endothelial growth factor receptors (VEGFRs) are a family of receptor protein tyrosine kinases that play an important role in the regulation of tumor-induced angiogenesis. Currently, VEGFR inhibitors have been widely used in the treatment of various tumors. However, current VEGFR inhibitors are limited to a certain extent due to limited clinical efficacy and potential toxicity, which hinder their clinical application. Thus, the development of new strategies to improve the clinical outcomes and minimize the toxic effects of VEGFR inhibitors is required. Given the synergistic effect of VEGFR and other therapies in tumor development and progression, VEGFR dual-target inhibitors are becoming an attractive approach due to their favorable pharmacodynamics, low toxicity, and anti-resistant effects. This perspective provides an overview of the development of VEGFR dual-target inhibitors from multiple aspects, including rational target combinations, drug discovery strategies, structure–activity relationships and future directions.

Optimal chemotherapy counteracts cancer adaptive resistance in a cell-based, spatially-extended, evolutionary model

Most aggressive cancers are incurable due to their fast evolution of drug resistance. We model cancer growth and adaptive response in a simplified cell-based (CB) setting, assuming a genetic resistance to two chemotherapeutic drugs. We show that optimal administration protocols can steer cells resistance and turned it into a weakness for the disease. Our work extends the population-based (PB) model proposed by Orlando et al. (Physical Biology, 2012), in which a homogeneous population of cancer cells evolves according to a fitness landscape. The landscape models three types of trade-offs, differing on whether the cells are more, less, or equal effective when generalizing resistance to two drugs as opposed to specializing to a single one. The CB framework allows us to include genetic heterogeneity, spatial competition, and drugs diffusion, as well as realistic administration protocols. By calibrating our model on Orlando et al.'s assumptions, we show that dynamical protocols that alternate the two drugs minimize the cancer size at the end of (or at mid-points during) treatment. These results significantly differ from those obtained with the homogeneous model---suggesting static protocols under the pro-generalizing and neutral allocation trade-offs---highlighting the important role of spatial and genetic heterogeneities. Our work is the first attempt to search for optimal treatments in a CB setting, a step forward toward realistic clinical applications.

Systems biology of angiogenesis signaling: Computational models and omics

Angiogenesis is a highly regulated multiscale process that involves a plethora of cells, their cellular signal transduction, activation, proliferation, differentiation, as well as their intercellular communication. The coordinated execution and integration of such complex signaling programs is critical for physiological angiogenesis to take place in normal growth, development, exercise, and wound healing, while its dysregulation is critically linked to many major human diseases such as cancer, cardiovascular diseases, and ocular disorders; it is also crucial in regenerative medicine. Although huge efforts have been devoted to drug development for these diseases by investigation of angiogenesis‐targeted therapies, only a few therapeutics and targets have proved effective in humans due to the innate multiscale complexity and nonlinearity in the process of angiogenic signaling. As a promising approach that can help better address this challenge, systems biology modeling allows the integration of knowledge across studies and scales and provides a powerful means to mechanistically elucidate and connect the individual molecular and cellular signaling components that function in concert to regulate angiogenesis. In this review, we summarize and discuss how systems biology modeling studies, at the pathway‐, cell‐, tissue‐, and whole body‐levels, have advanced our understanding of signaling in angiogenesis and thereby delivered new translational insights for human diseases.

This article is categorized under:

Cardiovascular Diseases > Computational Models

Cancer > Computational Models

iTAGPred: A Two-Level Prediction Model for Identification of Angiogenesis and Tumor Angiogenesis Biomarkers

A crucial biological process called angiogenesis plays a vital role in migration, growth, and wound healing of endothelial cells and other processes that are controlled by chemical signals. Angiogenesis is the process that controls the growth of blood vessels within tissues while angiogenesis proteins play a significant role in the proper working of this process. The balancing of these signals is necessary for the proper working of angiogenesis. Unbalancing of these signals increases blood vessel formation, which causes abnormal growth or several diseases including cancer. The proposed work focuses on developing a two-layered prediction model using different classifiers like random forest (RF), neural network, and support vector machine. The first level performs in silico identification of angiogenesis proteins based on the primary structure. In the case the protein is an angiogenesis protein, then the second level predicts whether the protein is linked with tumor angiogenesis or not. The performance of the model is evaluated through various validation techniques. The model was evaluated using k-fold cross-validation, independent, self-consistency, and jackknife testing. The overall accuracy using an RF classifier for angiogenesis at the first level was 97.8% and for tumor angiogenesis at the second level was 99.5%, ANN showed 94.1% accuracy for angiogenesis and 79.9% for tumor angiogenesis, and the accuracy of SVM for angiogenesis was 78.8% and for tumor angiogenesis was 65.19%.

Mathematical simulation of tumour angiogenesis: angiopoietin balance is a key factor in vessel growth and regression

Excessive tumour growth results in a hypoxic environment around cancer cells, thus inducing tumour angiogenesis, which refers to the generation of new blood vessels from pre-existing vessels. This mechanism is biologically and physically complex, with various mathematical simulation models proposing to reproduce its formation. However, although temporary vessel regression is clinically known, few models succeed in reproducing this phenomenon. Here, we developed a three-dimensional simulation model encompassing both angiogenesis and tumour growth, specifically including angiopoietin. Angiopoietin regulates both adhesion and migration between vascular endothelial cells and wall cells, thus inhibiting the cell-to-cell adhesion required for angiogenesis initiation. Simulation results showed a regression, i.e. transient decrease, in the overall length of new vessels during vascular network formation. Using our model, we also evaluated the efficacy of administering the drug bevacizumab. The results highlighted differences in treatment efficacy: (1) earlier administration showed higher efficacy in inhibiting tumour growth, and (2) efficacy depended on the treatment interval even with the administration of the same dose. After thorough validation in the future, these results will contribute to the design of angiogenesis treatment protocols.

Dextran methacrylate hydrogel microneedles loaded with doxorubicin and trametinib for continuous transdermal administration of melanoma

Microneedles (MNs) technology has many advantages and is an ideal local transdermal drug delivery method. Here we synthesized photocrosslinkable dextran methacrylate (DexMA), and its degree of substitution is 5 % higher than the previous method. We used DexMA hydrogel for the first time to develop a new type of MNs for continuous transdermal administration. The prepared hydrogel MNs can successfully penetrate the epidermal layer and achieve sustained drug release. Doxorubicin (DOX) and trametinib (Tra) are anticancer drugs approved by FDA. Besides, Tra can also reverse P-gp-mediated multidrug resistance (MDR) to effectively block the efflux of DOX by P-gp. We used MNs to simultaneously load Tra and DOX, and achieved synergy in a B16 cell xenograft nude mouse model. The DexMA hydrogel MNs developed in this study can be used to enhance the transdermal delivery of small molecule drugs and reduce systemic toxicity and side effects.

Tanshinone IIA Reverses Gefitinib-Resistance In Human Non-Small-Cell Lung Cancer Via Regulation Of VEGFR/Akt Pathway

Background

Gefitinib-resistance is a primary obstacle for the treatment of non-small-cell lung cancer (NSCLC). It has been shown that tanshinone IIA (Tan IIA) could induce apoptosis of NSCLC cells. However, the role of combination of gefitinib with Tan IIA on gefitinib-resistance NSCLC cells remains unclear. Thus, this study aimed to investigate the role of combination on the proliferation, apoptosis and invasion of gefitinib-resistance NSCLC cells.

Methods

CCK-8, flow cytometric and transwell assays were applied to detect proliferation, apoptosis and invasion in gefitinib-resistance NSCLC cells, respectively. In addition, Western blotting assay was used to detect the expressions of p-EGFR, p-VEGFR2, and p-Akt in HCC827/gefitinib cells.

Results

In this study, Tan IIA enhanced the cytotoxic effect of gefitinib in gefitinib-resistance NSCLC cells. In addition, the inhibitory effects of gefitinib on the proliferation, migration and invasion of gefitinib-resistance NSCLC cells were enhanced in the presence of Tan IIA. Moreover, Tan IIA enhanced the pro-apoptotic effect of gefitinib in gefitinib-resistance NSCLC cells via increasing the level of cleaved caspase 3. Meanwhile, Tan IIA enhanced the sensitivity of HCC827/gefitinib cells to gefitinib via downregulation of the VEGFR2/Akt pathway. In vivo experiments further confirmed that combination of gefitinib with Tan IIA inhibited tumor growth in mouse xenograft model of HCC827/gefitinib.

Conclusion

We found that Tan IIA could enhance gefitinib sensitivity in gefitinib-resistance NSCLC cells. Therefore, combination of gefitinib with Tan IIA might be considered as a therapeutic approach for the treatment of gefitinib-resistant NSCLC.

Multicellular gene network analysis identifies a macrophage-related gene signature predictive of therapeutic response and prognosis of gliomas

BACKGROUND

The tumor-associated microenvironment plays important roles in tumor progression and drug resistance. However, systematic investigations of macrophage-tumor cell interactions to identify novel macrophage-related gene signatures in gliomas for predicting patient prognoses and responses to targeted therapies are lacking.

METHODS

We developed a multicellular gene network approach to investigating the prognostic role of macrophage-tumor cell interactions in tumor progression and drug resistance in gliomas. Multicellular gene networks connecting macrophages and tumor cells were constructed from re-grouped drug-sensitive and drug-resistant samples of RNA-seq data in mice gliomas treated with BLZ945 (a CSF1R inhibitor). Subsequently, a differential network-based COX regression model was built to identify the risk signature using a cohort of 310 glioma samples from the Chinese Glioma Genome Atlas database. A large independent validation set of 690 glioma samples from The Cancer Genome Atlas database was used to test the prognostic significance and accuracy of the gene signature in predicting prognosis and targeted therapeutic response of glioma patients.

RESULTS

A macrophage-related gene signature was developed consisting of twelve genes (ANPEP, DPP4, PRRG1, GPNMB, TMEM26, PXDN, CDH6, SCN3A, SEMA6B, CCDC37, FANCA, NETO2), which was tested in the independent validation set to examine its prognostic significance and accuracy. The generation of 1000 random gene signatures by a bootstrapping scheme justified the non-random nature of the macrophage-related gene signature. Moreover, the discovered gene signature was verified to be predictive of the sensitivity or resistance of glioma patients to molecularly targeted therapeutics and outperformed other existing gene signatures. Additionally, the macrophage-related gene signature was an independent and the strongest prognostic factor when adjusted for clinicopathologic risk factors and other existing gene signatures.

CONCLUSION

The multicellular gene network approach developed herein indicates profound roles of the macrophage-mediated tumor microenvironment in the progression and drug resistance of gliomas. The identified macrophage-related gene signature has good prognostic value for predicting resistance to targeted therapeutics and survival of glioma patients, implying that combining current targeted therapies with new macrophage-targeted therapy may be beneficial for the long-term treatment outcomes of glioma patients.