Search Results (3,649)

Background/Objectives: We provide a framework for determining how far into the future the spatiotemporal dynamics of tumor growth can be accurately predicted using routinely available magnetic resonance imaging (MRI) data. Our analysis is applied to a coupled set of reaction-diffusion equations describing the spatiotemporal development of tumor cellularity and vascularity, initialized and constrained with diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI data, respectively. Methods: Motivated by experimentally acquired murine glioma data, the rat brain serves as the computational domain within which we seed an in silico tumor. We generate a set of 13 virtual tumors defined by different combinations of model parameters. The first parameter combination was selected as it generated a tumor with a necrotic core during our simulated ten-day experiment. We then tested 12 additional parameter combinations to study a range of high and low tumor cell proliferation and diffusion values. Each tumor is grown for ten days via our model system to establish “ground truth” spatiotemporal tumor dynamics with an infinite signal-to-noise ratio (SNR). We then systematically reduce the quality of the imaging data by decreasing the SNR, downsampling the spatial resolution (SR), and decreasing the sampling frequency, our proxy for reduced temporal resolution (TR). With each decrement in image quality, we assess the accuracy of the calibration and subsequent prediction by comparing it to the corresponding ground truth data using the concordance correlation coefficient (CCC) for both tumor and vasculature volume fractions, as well as the Dice similarity coefficient for tumor volume fraction. Results: All tumor CCC and Dice scores for each of the 13 virtual tumors are >0.9 regardless of the SNR/SR/TR combination. Vasculature CCC scores with any SR/TR combination are >0.9 provided the SNR ≥ 80 for all virtual tumors; for the special case of high-proliferating tumors (i.e., proliferation > 0.0263 day⁻¹), any SR/TR combination yields CCC and Dice scores > 0.9 provided the SNR ≥ 40. Conclusions: Our systematic evaluation demonstrates that reaction-diffusion models can maintain acceptable longitudinal prediction accuracy—especially for tumor predictions—despite limitations in the quality and quantity of experimental data. Full article

Glioblastoma is the most aggressive and treatment-resistant form of primary brain tumors, characterized by rapid invasion and a poor prognosis. Its complex behavior continues to challenge both clinical interventions and research efforts. Mathematical modeling provides a valuable approach to unraveling a tumor’s spatiotemporal dynamics and supporting the development of more effective therapies. In this study, we built on the existing literature by refining and adapting mathematical models to better capture glioblastoma infiltration, using a partial differential equation (PDE) framework to simulate how cancer cell density evolves across both time and space. In particular, the role of cell diffusion and growth in tumor progression and their limitations due to cell crowding and competition were investigated. Experimental data of glioblastoma taken from the literature were exploited for the identification of the model parameters. The improved data reproduction when the limitations of cell diffusion and growth were taken into account proves the relevant impact of the considered mechanisms on the spread of the tumor population, which underscores the potential of the proposed framework. Full article

Background: Cervical cancer remains a major global health burden, and treatment failure due to radioresistance and secondary drug resistance severely limits clinical outcomes. Enhancer of zeste homolog 2 (EZH2) is a key epigenetic regulator implicated in tumor progression. This study aimed to determine whether EZH2-mediated PTEN silencing drives afatinib resistance via AKT activation in radiation-resistant cervical cancer cells. Methods: A radioresistant cervical cancer cell line (HeLaR) was established following cumulative irradiation (70 Gy). Cell viability, clonogenic survival, methylation-specific PCR (MSP), chromatin immunoprecipitation (ChIP), and Western blot analyses were conducted. EZH2 (Dznep; tazemetostat), PI3K, and AKT inhibitors were tested in combination with afatinib. A xenograft mouse model was used for in vivo validation. Results: HeLaR cells exhibited upregulation of EZH2 and H3K27me3, downregulation of PTEN, and sustained AKT activation. EZH2 inhibition restored PTEN expression, attenuated AKT phosphorylation, and re-sensitized cells to afatinib. MSP and ChIP confirmed EZH2-mediated PTEN promoter silencing. PI3K inhibition reproduced these effects, whereas ERK inhibition had minimal impact. In xenograft models, combined treatment with Dznep and afatinib significantly suppressed tumor growth compared to single agents. Conclusions: EZH2-driven PTEN suppression promotes AKT-dependent afatinib resistance in radiation-resistant cervical cancer. Targeting the EZH2–PTEN–AKT axis may provide a potential therapeutic approach to mitigate combined radioresistance and chemoresistance in recurrent cervical cancer, although further preclinical and clinical validation is required. Full article

A functional blood vessel network is required to deliver oxygen and nutrients to the cancer cells for their growth. Angiogenesis, the formation of new blood vessels from pre-existing ones, is one of the major mechanisms to create this vascular network. Anti-angiogenic therapy was conceived as the inhibition of the cellular and molecular players involved in tumor angiogenesis such as vascular endothelial growth factor and its main receptors. Due to limitations of this therapy, different approaches of vessel modulation such as vascular normalization or vascular promotion have been studied showing benefits in different tumor models and clinical trials. In contrast to anti-angiogenic therapy, which inhibits the blood vessels that are being formed, vascular disruption therapy aims to destroy already formed tumor vessels. These malignant vascular structures differ from other blood vessels in terms of endothelial cell states, pericyte coverage and basement membrane development. The molecules used for vascular disruption are microtubule-binding molecules, flavonoids that induce endothelial cell apoptosis or molecules vectorized to endothelial receptors. Many vascular disruption agents have been tested in clinical trials showing some promising results, but with some limitations that include resistant rim cells or the development of hypoxia that induces cancer regrowth and poor delivery of the anti-tumor agents. The main objective of this review is to focus on vascular disruption agents therapy, novel molecules, new ways to overcome therapy resistance to them, current clinical status and, especially, the upcoming challenges and applications of these molecules. Full article

Serotonin or 5-hydroxytryptamine (5-HT) has been implicated in promoting cancer cell growth by acting on 5-HT receptors, such as 5-HT1 and 5-HT2 receptors. However, the role of 5-HT3 receptor antagonists in gastric cancer cell lines remains unclear. This study aimed to evaluate the effect of 5-HT3 receptor antagonists (ondansetron, palonosetron, and ramosetron) on cancer cell growth using AGS and MKN-1 cell lines, as well as the xenograft mouse model. All the three antagonists inhibited cell proliferation, migration, and colony formation in AGS cells. Specifically, palonosetron induced G1 cell cycle arrest, autophagy, and phosphorylation of GSK3β, along with increased expression of p27, p53, and LC3B. In vivo studies demonstrated that palonosetron reduced tumor growth and modulated pro-inflammatory cytokines—tumor necrosis factor alpha, interleukin 6, and interleukin 1β. These findings suggest that 5-HT3 receptor antagonists, especially palonosetron, exert anti-tumor effects in gastric cancer through G1 cell cycle regulation and immunomodulation. The results position palonosetron as a promising lead for further preclinical development in gastric cancer. Full article

Breast cancer gene 1 (BRCA1) is a tumor suppressor gene essential for DNA repair, and its mutations are linked to aggressive breast cancers with poor prognosis. While poly (ADP-ribose) polymerase (PARP) inhibitors benefit some patients with BRCA1-mutant, human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer, issues such as limited efficacy and drug resistance persist. This is especially critical for triple-negative breast cancer (TNBC), which lacks targeted therapies. Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors such as abemaciclib—FDA-approved for estrogen receptor (ER)-positive/HER2-negative breast cancer—are emerging as potential treatments for TNBC. We evaluated abemaciclib in BRCA1-mutant TNBC cell lines (SUM149, HCC1937, and MDA-MB-436) and found them to be sensitive to the drug. However, treatment induced cellular senescence and Interleukin-6 (IL-6) secretion, which may promote drug resistance. To address this, we inhibited IL-6 signaling using bazedoxifene or glycoprotein 130 (GP130) siRNA, and both of which enhanced abemaciclib sensitivity. Combination treatment with bazedoxifene and abemaciclib synergistically inhibited cell migration and invasion, and induced apoptosis. In a mammary fat pad TNBC tumor model, the combination treatment significantly suppressed SUM149 tumor growth more than either agent alone. These findings support co-targeting IL-6 and CDK4/6 as a novel therapeutic strategy for BRCA1-mutant TNBC. Full article

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, characterized by aggressive tumor biology, poor vascularization, dense stromal barriers, and profound resistance to chemotherapy. GAIP-interacting protein C-terminus 1 (GIPC1), a PDZ-domain-containing adaptor protein, is highly overexpressed in PDAC and plays a critical role in tumor progression and chemoresistance. This study aimed to develop and evaluate a novel tumor-targeted liposomal siRNA delivery system (LGIPCsi) to silence GIPC1 and enhance the therapeutic efficacy of gemcitabine (GEM) in PDAC; Methods: LGIPCsi nanoparticles were synthesized and optimized for physicochemical stability, siRNA complexation efficiency, and tumor-targeting capability. Their therapeutic efficacy was assessed using in vitro pancreatic cancer cell models and in vivo orthotopic and patient-derived xenograft (PDX) models of PDAC. Biodistribution, tumor uptake, and antitumor efficacy were evaluated following systemic administration. Combination studies were performed to assess the synergistic effects of LGIPCsi and GEM; Results: GIPC1 silencing significantly sensitized pancreatic cancer cells to GEM, resulting in enhanced inhibition of tumor cell proliferation in vitro. In vivo, systemic administration of LGIPCsi achieved efficient intratumoral delivery of siGIPC1, leading to marked tumor growth suppression. Combination therapy with GEM and LGIPCsi produced synergistic antitumor effects, with substantial tumor regression compared to monotherapy groups. Importantly, no significant systemic toxicity was observed in treated animals; Conclusions: This study identifies GIPC1 as a promising therapeutic target in PDAC and demonstrates that tumor-targeted siRNA nanomedicine can effectively overcome chemoresistance when combined with standard chemotherapy. The LGIPCsi platform offers a rational and translational strategy to enhance treatment efficacy in PDAC through targeted RNAi-based combination therapy. Full article

Background/Objectives: Tumor growth delay is frequently used in preclinical experiments evaluating oncologic interventions. While treatment response in humans is based on imaging criteria for obvious reasons, manual caliper measurement of subcutaneous tumors is standard in animal studies. In a murine tumor model treated with immunotherapy (ImT) and radiotherapy (RT), the reliability of caliper measurements was tested by comparing normalized tumor growth delay (NTGD) rates derived from caliper- and image-based volumetrics. Methods: A 4T1 breast syngeneic murine model was used, in which thirty animals were inoculated in the right inguinal mammary fat pad and the right axilla. One RT fraction of 8 Gy was delivered to the right inguinal tumor on day 11 post-implant, and intraperitoneal ImT (PD-1 checkpoint inhibitor) injections were administered on days 11, 12, and 14. Each animal underwent three MRI scans (days 10, 17, and 20). Caliper measurements were also performed by two independent observers on the same days. The measurements were averaged and used to estimate ellipsoid tumor volumes. The acquired MRIs were used for image segmentation and volume estimation. Tumor volumes (days 17 and 20) were normalized against the baseline pre-treatment tumor volume (day 10). NTGD rates derived from hand- and image-based volumetrics were compared to assess the reliability of caliper vs. MRI estimation. Results: Caliper volumes between the two observers correlated at 0.799 (Pearson, p < 0.001). The averaged caliper volumes correlated with MRI volumes at 0.897 (Pearson, p < 0.001). Absolute volume differences between caliper and MRI increased with tumor growth. NTGD-derived rates showed no correlation, with only 15% of NTGD caliper rates falling within 10% of the MRI rates. Conclusions: NTGD rate based on caliper volumes is a suitable measure of treatment response in preclinical studies. In the experiment described herein, caliper-derived NTGD rates did not correlate with MRI ground truth. These findings suggest that more accurate tumor volumetrics, derived from stored and verifiable medical imaging sources, should be used in preclinical assessment of oncologic interventions instead of standard caliper estimates. Full article

Background: This study addresses an important vulnerability in the treatment of high-risk neuroblastoma (NB). NB is characterized by high rates of metastasis, drug resistance, relapse, and treatment-related toxicities. Current treatments, which include intensive chemotherapy, surgical removal of tumors, and stem cell transplants, have less than 50 percent survival rates among high-risk NB patients, demonstrating the need for novel targeted treatment approaches. CXC chemokine receptor 2 (CXCR2), a G-protein-coupled receptor, has been implicated in promoting cancer cell proliferation, invasion, metastasis, angiogenesis, chemoresistance, and maintaining cancer stem cells. Methods: We analyzed transcriptomic data from 1464 primary NB patient samples to evaluate the prognostic significance of CXCR2 expression. Pharmacological inhibition of CXCR2 using SB225002, a selective small-molecule antagonist, was evaluated to determine its effects on cell growth, colony formation, apoptosis, and cell cycle progression in different NB cell lines. Three-dimensional (3D) spheroid models were used to examine tumor growth under physiologically relevant conditions. Mechanistic studies included gene expression analyses and immunoblot validation of key signaling regulators. Results: High CXCR2 expression was found to be inversely correlated with overall survival in patient datasets, suggesting a role in NB pathogenesis. Treatment with SB225002 significantly inhibited NB proliferation and colony formation while inducing apoptosis and cell cycle arrest in a dose-dependent manner. In 3D spheroid models, SB225002 significantly impaired spheroid formation and growth, confirming its potent anti-tumor efficacy. Mechanistically, CXCR2 blockade inhibited the expression of key pathway targets, including GLIPR1, BACH2, JUN, CHEK1, AKT1, and CXCR2 itself. Immunoblot analysis confirmed significant inhibition of CXCR2 and GLIPR1 protein levels in response to SB225002 treatment. Conclusions: Taken together, our findings demonstrate that pharmacological inhibition of CXCR2 using SB225002 effectively inhibits NB tumor cell growth and tumorigenicity by modulating oncogenic signaling networks. This study provides strong evidence for elucidating CXCR2-targeted therapies as an attractive treatment option for NB. These findings support the development of CXCR2-targeted therapies for high-risk NB. Full article

CB₁ agonist compounds may be potential drug candidates for the treatment of gliomas, as they have been shown to inhibit tumor cell proliferation, induce apoptosis, and reduce angiogenesis in various preclinical models. Their ability to modulate the endocannabinoid system suggests a promising therapeutic approach for targeting glioma growth and progression. Herein, we report the design, synthesis, biological studies, and bioinformatics assays of novel benzo[d]imidazole–naphthalen-arylmethanone regioisomers with affinity for the CB₁ receptor, as well as propose an indirect methodology to evaluate their presumed CB₁ agonist activity. Compounds that showed a propensity for binding to the CB₁ receptor were regioisomers 4d, 5b, 5e, 5f, and 5f′. Likewise, derivatives that displaced more than 50% of the radioligand [³H]CP-55940 at the CB₁ receptor were subjected to in vitro viability experiments. Compounds 4d, 5b, 5e, and 5f′ showed toxicity against U87MG cells (malignant glioma) in a considerable percentage. Notably, compound 5f′ showed CB₁ affinity, with a K_i of 2.12 µM, and was selectively toxic to U87MG cells, which highly express the CB₁ receptor, while exhibiting no toxicity toward the healthy HEK293 cell line, which expresses both cannabinoid receptors at negligible levels. Docking studies at the CB₁ orthosteric site indicate that 5f′ forms π-π interactions, a T-shaped interaction, and hydrogen bonding through the oxygen atom of the furan ring. Biologically, our experimental indirect model-based on a simple viability assay is supported by well-established evidence that activation of CB₁ and CB₂ receptors by agonists induces cell death and inhibits tumor cell growth. Structurally, we conclude that the presence of a furan ring at the 2-position of the benzo[d]imidazole core is beneficial for the development of new ligands with potential CB₁ agonist activity. Full article

Glioblastoma (GBM) is the most common and aggressive malignant brain tumor in adults. This review explains the connections between the genesis and progression of GBM and particular cellular tumorigenic mechanisms, such as angiogenesis, invasion, migration, growth factor overexpression, genetic instability, and apoptotic disorders, as well as possible therapeutic targets that help predict the course of the disease. Glioblastoma multiforme (GBM) diagnosis relies heavily on histopathological features, molecular markers, extracellular vesicles, neuroimaging, and biofluid-based glial tumor identification. In order to improve miRNA stability and stop the proliferation of cancer cells, nanoparticles, magnetic nanoparticles, contrast agents, gold nanoparticles, and nanoprobes are being created for use in cancer treatments, neuroimaging, and biopsy. Targeted nanoparticles can boost the strength of an MRI signal by about 28–50% when compared to healthy tissue or controls in a preclinical model like mouse lymph node metastasis. Combining the investigation of CNAs and noncoding RNAs with deep learning-driven global profiling of genes, proteins, RNAs, miRNAs, and metabolites presents exciting opportunities for creating new diagnostic markers for malignancies of the central nervous system. Artificial intelligence (AI) advances precision medicine and cancer treatment by enabling the real-time analysis of complex biological and clinical data through wearable sensors and nanosensors; optimizing drug dosages, nanomaterial design, and treatment plans; and accelerating the development of nanomedicine through high-throughput testing and predictive modeling. Full article

Peripheral edema is a pathological condition caused by abnormal fluid accumulation in the interstitial space due to elevated vascular permeability and inflammation. This study evaluated the therapeutic efficacy of Terminalia chebula fruit extract (TCE) in inflammation-induced peripheral edema and clarified its molecular mechanisms. Using hydrogen peroxide (H₂O₂)-stimulated human umbilical vein endothelial cells (HUVECs), TCE was tested for effects on cell viability, inflammatory gene expression, intracellular reactive oxygen species, endothelial barrier integrity, and vascular endothelial growth factor (VEGF)-induced migration. Its influence on nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) and mitogen-activated protein kinase (MAPK) signaling was examined. In vivo, TCE was assessed in acetic acid-induced peritoneal vascular permeability and carrageenan-induced paw edema models, followed by histological analysis and serum tumor necrosis factor-α (TNF-α) measurement. TCE restored cell viability (76.2% to 94.8%), reduced TNF, IL6, and PTGS2 mRNA expression, and decreased reactive oxygen species by 27.2%. It enhanced barrier integrity, increased transendothelial electrical resistance, and inhibited VEGF-induced migration. TCE suppressed NF-κB and MAPK activation. In vivo, TCE reduced Evans blue extravasation by 41.6% and paw edema by 67.5%. Histology showed reduced dermal thickening and inflammatory infiltration, and serum TNF-α levels were lowered. TCE attenuates peripheral edema by preserving endothelial barrier function and suppressing inflammatory signaling, supporting its potential as a therapeutic agent for inflammation-associated vascular dysfunction and edema. Full article

Background/Objectives: T cell dysfunction represents a fundamental barrier to effective cancer immunotherapy. Although immune checkpoint blockades and adoptive cell transfer have achieved clinical success, therapeutic resistance remains prevalent across cancer types. Thymopentin (TP5), a synthetic immunomodulatory pentapeptide (Arg-Lys-Asp-Val-Tyr), has demonstrated immunostimulatory properties, yet its anticancer potential remains unexplored. The aim of this study was to investigate TP5’s antitumor efficacy and underlying immunological mechanisms. Methods: We evaluated TP5’s therapeutic effects in multiple murine tumor models, including B16-F10 melanoma, MC38 colorectal carcinoma, Hepa 1-6, and LM3 hepatocellular carcinoma. Immune cell populations and functional states were characterized using flow cytometry, ELISAs, and immunofluorescence analyses. The potential of TP5 as an adjuvant for T cell-based therapies was also systematically assessed. Results: The TP5 treatment markedly suppressed tumor growth across caner models through strictly T cell-dependent mechanisms. Critically, TP5 promoted thymic rejuvenation under immunocompromised conditions, restoring the thymus–tumor immunological balance and revitalizing peripheral T cell immunity. TP5 functionally reprogrammed T cell states, preserving effector function while ameliorating exhaustion. Furthermore, TP5 demonstrated synergistic efficacy when combined with adoptive T cell therapies, enhancing both proliferation and effector functions. Conclusions: TP5 represents a promising immunomodulator that addresses fundamental limitations of current T cell therapies by simultaneously enhancing T cell function and reversing thymic involution under immunocompromised conditions. Our findings provide compelling evidence for TP5’s clinical translation in cancer treatment. Full article

Cancer-associated fibroblasts (CAFs) are key components of the tumor microenvironment (TME) that influence cancer progression via extracellular matrix (ECM) remodeling and secretion of growth factors and cytokines. Endothelial-to-mesenchymal transition (EndMT) is emerging as an important axis among the heterogeneous origins of CAFs. This review introduces the diverse methods used to induce EndMT in cancer—mouse tumor models, conditioned-medium treatment, co-culture, targeted gene perturbation, ligand stimulation, exosome exposure, irradiation, viral infection, and three-dimensional (3D) culture systems—and summarizes EndMT cell-type evidence uncovered using transcriptomic and proteomic technologies. Hallmark EndMT features include spindle-like morphology, increased motility, impaired angiogenesis and barrier function, decreased endothelial markers (CD31, VE-cadherin), and increased mesenchymal markers (α-SMA, FN1). Reported mechanisms include signaling via TGF-β, cytoskeletal/mechanical stress, reactive oxygen species, osteopontin, PAI-1, IL-1β, GSK-3β, HSP90α, Tie1, TNF-α, HSBP1, and NOTCH. Cancer-induced EndMT affects tumors and surrounding TME—promoting tumor growth and metastasis, expanding cancer stem cell-like cells, driving macrophage differentiation, and redistributing pericytes—and is closely associated with poor survival and therapy resistance. Finally, we indicate each study’s stance: some frame cancer-induced EndMT as a source of CAFs, whereas others, from an endothelial perspective, emphasize barrier weakening and promotion of metastasis. Full article

Breast cancer is the most commonly diagnosed cancer in women globally and represents the leading cause of mortality related to malignant tumors. Currently, healthcare professionals are focused on developing and implementing innovative techniques to improve the early detection of this disease. Thermography, studied as a complementary method to traditional approaches, captures infrared radiation emitted by tissues and converts it into data about skin surface temperature. During tumor development, angiogenesis occurs, increasing blood flow to support tumor growth, which raises the surface temperature in the affected area. Automatic classification techniques have been explored to analyze thermographic images and develop an optimal classification tool to identify thermal anomalies. This study aims to design a concise description using statistical and texture features to accurately classify thermograms as control or highly probable to be cancer (with thermal anomalies). The importance of employing a short description lies in facilitating interpretation by medical professionals. In contrast, a characterization based on a large number of variables could make it more challenging to identify which values differentiate the thermograms between groups, thereby complicating the explanation of results to patients. A maximum accuracy of 91.97% was achieved by applying only seven features and using a Coarse Decision Tree (DT) classifier and robust Machine Learning (ML) model, which demonstrated competitive performance compared with previously reported studies. Full article