3D Tumor Research Articles

Ultrasmall Gold Nanoparticles Radiolabeled with Iodine-125 as Potential New Radiopharmaceutical.

The relatively high linear energy transfer of Auger electrons, which can cause clustered DNA damage and hence efficient cell death, makes Auger emitters excellent candidates for attacking metastasized tumors. Moreover, gammas or positrons are usually emitted along with the Auger electrons, providing the possibility of theragnostic applications. Despite the promising properties of Auger electrons, only a few radiopharmaceuticals employing Auger emitters have been developed so far. This is most likely explained by the short ranges of these electrons, requiring the delivery of the Auger emitters to crucial cell parts such as the cell nucleus. In this work, we combined the Auger emitter 125I and ultrasmall gold nanoparticles to prepare a novel radiopharmaceutical. The 125I labeled gold nanoparticles were shown to accumulate at the cell nucleus, leading to a high tumor-killing efficiency in both 2D and 3D tumor cell models. The results from this work indicate that ultrasmall nanoparticles, which passively accumulate at the cell nucleus, have the potential to be applied in targeted radionuclide therapy. Even better tumor-killing efficiency can be expected if tumor-targeting moieties are conjugated to the nanoparticles.

ABCB1-dependent collateral sensitivity of multidrug-resistant colorectal cancer cells to the survivin inhibitor MX106-4C

AimsTo investigate the collateral sensitivity (CS) of ABCB1-positive multidrug resistant (MDR) colorectal cancer cells to the survivin inhibitor MX106–4C and the mechanism. MethodsBiochemical assays (MTT, ATPase, drug accumulation/efflux, Western blot, RT-qPCR, immunofluorescence, flow cytometry) and bioinformatic analyses (mRNA-sequencing, reversed-phase protein array) were performed to investigate the hypersensitivity of ABCB1 overexpressing colorectal cancer cells to MX106–4C and the mechanisms. Synergism assay, long-term selection, and 3D tumor spheroid test were used to evaluate the anti-cancer efficacy of MX106–4C. ResultsMX106–4C selectively killed ABCB1-positive colorectal cancer cells, which could be reversed by an ABCB1 inhibitor, knockout of ABCB1, or loss-of-function ABCB1 mutation, indicating an ABCB1 expression and function-dependent mechanism. MX106–4C's selective toxicity was associated with cell cycle arrest and apoptosis through ABCB1-dependent survivin inhibition and activation on caspases-3/7 as well as modulation on p21-CDK4/6-pRb pathway. MX106–4C had good selectivity against ABCB1-positive colorectal cancer cells and retained this in multicellular tumor spheroids. In addition, MX106–4C could exert a synergistic anti-cancer effect with doxorubicin or re-sensitize ABCB1-positive cancer cells to doxorubicin by reducing ABCB1 expression in the cell population via long-term exposure. ConclusionsMX106–4C selectively kills ABCB1-positive MDR colorectal cancer cells via a novel ABCB1-dependent survivin inhibition mechanism, providing a clue for designing CS compound as an alternative strategy to overcome ABCB1-mediated colorectal cancer MDR.

Bioengineered in vitro three-dimensional tumor models in endocrine cancers.

Endocrine tumors are a heterogeneous cluster of malignancies that originate from cells that can secrete hormones. Examples include, but are not limited to, thyroid cancer, adrenocortical carcinoma, and neuroendocrine tumors. Many endocrine tumors are relatively slow to proliferate, and as such, they often do not respond well to common antiproliferative chemotherapies. Therefore, increasing attention has been given to targeted therapies and immunotherapies in these diseases. However, in contrast to other cancers, many endocrine tumors are relatively rare, and as a result, less is understood about their biology, including specific targets for intervention. Our limited understanding of such tumors is in part due to a limitation in model systems that accurately recapitulate and enable mechanistic exploration of these tumors. While mouse models and 2D cell cultures exist for some endocrine tumors, these models often may not accurately model nuances of human endocrine tumors. Mice differ from human endocrine physiology and 2D cell cultures fail to recapitulate the heterogeneity and 3D architectures of in vivo tumors. To complement these traditional cancer models, bioengineered 3D tumor models, such as organoids and tumor-on-a-chip systems, have advanced rapidly in the past decade. However, these technologies have only recently been applied to most endocrine tumors. In this review we provide descriptions of these platforms, focusing on thyroid, adrenal, and neuroendocrine tumors and how they have been and are being applied in the context of endocrine tumors.

Abstract B013: Development of oropharyngeal tumor organoids for disease modeling and high throughput drug screening

Abstract Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide with approximately 550,000 new cases diagnosed each year. The oropharynx is one of the most common sites of occurrence, and disease in this region most often presents in the palatine tonsil, followed by the base of tongue and soft palate. Human papilloma virus (HPV) is a common cause of HNSCC, giving rise to a distinct subset of tumors with a different clinical presentation, disease course, and response to treatment. In order to further characterize HPV+ HNSCC tumors and their therapy response, we have leveraged our high throughput 3D tumor organoid screening platform. Our approach entails seeding tumor cells in extracellular matrix gels deposited around the perimeter of tissue culture wells in ring-like structures, with screening results available within a week from surgery (Phan et al, 2019; Al Shihabi et al, 2022; Nguyen et al, 2022; Al Shihabi et al 2023). We particularly focused on tonsil tumors, and develop organoids from both HNSCC and contralateral normal tonsil tissue. Thus far, we have procured tonsil samples from 31 patients to develop organoids, perform high throughput drug screening, and immunohistochemical characterization including H&E staining, Ki67, p16 and p53 immunohistochemical staining. We have leveraged dynamic optical contrast imaging (DOCI), a label-free tissue autofluorescence imaging method that is being investigated clinically (Kim et al, 2017), to assist in distinguishing tumor organoids from normal tissue organoids. Lastly, given the importance of radiation as a treatment modality for HPV+ HNSCC, we have also optimized a chemoradiation pipeline to test possible combinatorial effects. Taken together, our results demonstrate that 3D organoids of HNSCC generated from patient samples can successfully preserve native tissue characteristics and can be used for high throughput drug screening and radiation de-escalation testing, affording critical insight into the management of HNSCC in patients. Citation Format: Krishna K. Bommakanti, Luda Lin, Yazeed Alhiyari, Andreanne Sannajust, Brandon Mo, Lauran Evans, Peyton Tebon, Maie St. John, Alice Soragni. Development of oropharyngeal tumor organoids for disease modeling and high throughput drug screening [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B013.

Patient-derived organoids recapitulate glioma-intrinsic immune program and progenitor populations of glioblastoma.

Glioblastoma multiforme (GBM) is a highly lethal human cancer thought to originate from a self-renewing and therapeutically-resistant population of glioblastoma stem cells (GSCs). The intrinsic mechanisms enacted by GSCs during 3D tumor formation, however, remain unclear, especially in the stages prior to angiogenic/immunological infiltration. In this study, we performed a deep characterization of the genetic, immune, and metabolic profiles of GBM organoids from several patient-derived GSCs (GBMO). Despite being devoid of immune cells, transcriptomic analysis across GBMO revealed a surprising immune-like molecular program, enriched in cytokine, antigen presentation and processing, T-cell receptor inhibitors, and interferon genes. We find two important cell populations thought to drive GBM progression, Special AT-rich sequence-binding protein 2 (SATB2+) and homeodomain-only protein homeobox (HOPX+) progenitors, contribute to this immune landscape in GBMO and GBM in vivo. These progenitors, but not other cell types in GBMO, are resistant to conventional GBM therapies, temozolomide and irradiation. Our work defines a novel intrinsic immune-like landscape in GBMO driven, in part, by SATB2+ and HOPX+ progenitors and deepens our understanding of the intrinsic mechanisms utilized by GSCs in early GBM formation.

Abstract A034: 3D in-vitro model picturing cancer-stromal cell crosstalk & bone metastasis

Abstract Breast cancer is presently the most prevalent malignancy and the second leading cause of tumor-related deaths among women. Approximately 75% of patients with advanced breast cancer will develop bone metastasis. Despite the significant improvement in treating primary breast cancer, the 5-year survival rate for metastatic breast cancer remains at 25%. While we recognize the critical importance of cancer cells and Tumor Microenvironment (TME) communication, the field still suffers from a lack of a proper model system to reconstitute 3D multi-cellular TME in-vitro, especially for bone metastasis. Most of the current 3D in-vitro breast cancer models are composed of cancer cells only and are unable to mimic the complex cellular homeostasis within the TME. To address this deficiency along with the tumor heterogeneity, we aimed to develop a unique 3D multi-cellular culture system using patient-derived (PD) cancer cells. In this study, we implemented the “hanging drop” method to create 3D Tumor Spheroids (TSs). This method was not only sufficient to build the 3D structure, but also significantly enhanced patient-derived cancer cell line establishment rate up to 75%. 3D TSs maintained their histopathological characteristics and original hormone receptor status. Over time, TSs exhibited intratumoral hypoxia leading to significant induction of VEGF expression and EMT showcasing the quality of the system. To investigate the complex interrelation between the tumor and TME, we cultured TSs with Endothelial Cells (ECs) and pericytes to introduce the vascular component. To probe these tumor-stromal interactions, we incorporated Cancer-Associated Fibroblasts (CAFs) into TSs and observed the successful growth of Multi-Cellular Tumor Spheroids (MCTSs) alongside the tubular structure. Analysis of our data revealed that the presence of stromal cells in TME enhanced tumor survival. In this study, we define how CAFs aid in the formation of vascular structures of ECs. Recent studies also have found that the effects of CAFs are significantly high in aggressive TNBC and HER2+ cell lines compared to HR+. The long-term goal of this current study is to explore bone-mimicking nano-clay-based 3D scaffold culture systems to investigate the development of metastatic tumors and to understand the influence of bone TME on cellular responses in-vitro. Citation Format: Shrinwanti Ghosh. 3D in-vitro model picturing cancer-stromal cell crosstalk & bone metastasis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A034.

HTRA1 promotes EMT through the HDAC6/Ac-α-tubulin pathway in human GBM cells.

The infiltrative nature of human gliomas renders complete surgical removal of tumors futile. Thus, illuminating mechanisms of their infiltrative properties may improve therapies and outcomes of glioma patients. Comprehensive bioinformatic analyses of PRSS family were undertaken. Transfection of HTRA1 siRNAs was used to suppress HTRA1 expression. CCK-8, EdU, and colony formation assay were employed to assess cell viability, and cell migration/invasion was detected by transwell, wound healing, and 3D tumor spheroid invasion assays. Immunoprecipitation was applied to study the mechanism that HTRA1 affected cell migration. In addition, insitu xenograft tumor model was employed to explore the role of HTRA1 in glioma growth invivo. HTRA1 knockdown could lead to suppression of cell viability, migration and invasion, as well as increased apoptosis. Immunoprecipitation results indicates HTRA1 might facilitate combination between HDAC6 and α-tubulin to enhance cell migration by decreasing α-tubulin acetylation. Besides, HTRA1 knockdown inhibited the growth of xenografts derived from orthotopic implantation of GBM cells and prolonged the survival time of tumor-bearing mice. Our results indicate that HTRA1 promotes the proliferation and migration of GBM cells invitro and invivo, and thus may be a potential target for treatment in gliomas.

Engineering Mesoscopic 3D Tumor Models with a Self‐Organizing Vascularized Matrix (Adv. Mater. 5/2024)

Engineering Mesoscopic 3D Tumor Models with a Self‐Organizing Vascularized Matrix (Adv. Mater. 5/2024)

Loss of Myo19 increases metastasis by enhancing microenvironmental ROS gradient and chemotaxis

Tumor metastasis involves cells migrating directionally in response to external chemical signals. Reactive oxygen species (ROS) in the form of H2O2 has been demonstrated as a chemoattractant for neutrophils but its spatial characteristics in tumor microenvironment and potential role in tumor cell dissemination remain unknown. Here we investigate the spatial ROS distribution in 3D tumor spheroids and identify a ROS concentration gradient in spheroid periphery, which projects into a H2O2 gradient in tumor microenvironment. We further reveal the role of H2O2 gradient to induce chemotaxis of tumor cells by activating Src and subsequently inhibiting RhoA. Finally, we observe that the absence of mitochondria cristae remodeling proteins including the mitochondria-localized actin motor Myosin 19 (Myo19) enhances ROS gradient and promotes tumor dissemination. Myo19 downregulation is seen in many tumors, and Myo19 expression is negatively associated with tumor metastasis in vivo. Together, our study reveals the chemoattractant role of tumor microenvironmental ROS and implies the potential impact of mitochondria cristae disorganization on tumor invasion and metastasis.

Exploring non-invasive precision treatment in non-small cell lung cancer patients through deep learning radiomics across imaging features and molecular phenotypes

BackgroundAccurate prediction of tumor molecular alterations is vital for optimizing cancer treatment. Traditional tissue-based approaches encounter limitations due to invasiveness, heterogeneity, and molecular dynamic changes. We aim to develop and validate a deep learning radiomics framework to obtain imaging features that reflect various molecular changes, aiding first-line treatment decisions for cancer patients.MethodsWe conducted a retrospective study involving 508 NSCLC patients from three institutions, incorporating CT images and clinicopathologic data. Two radiomic scores and a deep network feature were constructed on three data sources in the 3D tumor region. Using these features, we developed and validated the ‘Deep-RadScore,’ a deep learning radiomics model to predict prognostic factors, gene mutations, and immune molecule expression levels.FindingsThe Deep-RadScore exhibits strong discrimination for tumor molecular features. In the independent test cohort, it achieved impressive AUCs: 0.889 for lymphovascular invasion, 0.903 for pleural invasion, 0.894 for T staging; 0.884 for EGFR and ALK, 0.896 for KRAS and PIK3CA, 0.889 for TP53, 0.895 for ROS1; and 0.893 for PD-1/PD-L1. Fusing features yielded optimal predictive power, surpassing any single imaging feature. Correlation and interpretability analyses confirmed the effectiveness of customized deep network features in capturing additional imaging phenotypes beyond known radiomic features.InterpretationThis proof-of-concept framework demonstrates that new biomarkers across imaging features and molecular phenotypes can be provided by fusing radiomic features and deep network features from multiple data sources. This holds the potential to offer valuable insights for radiological phenotyping in characterizing diverse tumor molecular alterations, thereby advancing the pursuit of non-invasive personalized treatment for NSCLC patients.

Modelling the complex nature of the tumor microenvironment: 3D tumor spheroids as an evolving tool.

Cancer remains a serious burden in society and while the pace in the development of novel and more effective therapeutics is increasing, testing platforms that faithfully mimic the tumor microenvironment are lacking. With a clear shift from animal models to more complex in vitro 3D systems, spheroids emerge as strong options in this regard. Years of development have allowed spheroid-based models to better reproduce the biomechanical cues that are observed in the tumor-associated extracellular matrix (ECM) and cellular interactions that occur in both a cell-cell and cell-ECM manner. Here, we summarize some of the key cellular interactions that drive tumor development, progression and invasion, and how successfully are these interactions recapitulated in 3D spheroid models currently in use in the field. We finish by speculating on future advancements in the field and on how these can shape the relevance of spherical 3D models for tumor modelling.

Mechanical force-mediated interactions between cancer cells and fibroblasts and their role in the progression of hepatocellular carcinoma

Mechanical forces play a key role in the initiation and progression of cancer. Intercellular interactions between fibroblasts and cancer cells contribute a large portion of the mechanical forces in tumor tissue. Hence, further investigation of the mechanical force-mediated intercellular interactions between cancer cells and fibroblasts is urgently needed, given the slow progress in the management of various solid cancers. In our previous study, we observed obvious mechanical force-mediated interactions between hepatocellular carcinoma (HCC) cells and fibroblasts through integrins and ECM proteins by using our coculture model and discovered that these interactions play important roles in 3D structure formation and tumor growth, suggesting their potential application in HCC treatment. In this review, we summarize the recent research progress in this field in hopes of providing insight into the development of potential anticancer strategies, with a special focus on HCC.

Cancer-cell-specific Self-Reporting Photosensitizer for Precise Identification and Ablation of Cancer Cells.

Cancer-cell-specific fluorescent photosensitizers (PSs) are highly desired molecular tools for cancer ablation with minimal damage to normal cells. However, such PSs that can achieve cancer specification and ablation and a self-reporting manner concurrently are rarely reported and still an extremely challenging task. Herein, we have proposed a feasible strategy and conceived a series of fluorescent PSs based on simple chemical structures for identifying and killing cancer cells as well as monitoring the photodynamic therapy (PDT) process by visualizing the change of subcellular localization. All of the constructed cationic molecules could stain mitochondria in cancer cells, identify cancer cells specifically, and monitor cancer cell viability. Among these, IVP-Br has the strongest ability to produce ROS, which serves as a potent PS for specific recognition and killing of cancer cells. IVP-Br could translocate from mitochondria to the nucleolus during PDT, self-reporting the entire therapeutic process. Mechanism study confirms that IVP-Br with light irradiation causes cancer cell ablation via inducing cell cycle arrest, cell apoptosis, and autophagy. The efficient ablation of tumor through PDT induced by IVP-Br has been confirmed in the 3D tumor spheroid chip. Particularly, IVP-Br could discriminate cancer cells from white blood cells (WBCs), exhibiting great potential to identify circulating tumor cells (CTCs).

Pharmaceutical Approach to Develop Novel Photosensitizer Nanoformulation: An Example of Design and Characterization Rationale of Chlorophyll α Derivative.

In this study, we described physico-chemical properties of novel nanoformulation of photosensitizer-pyropheophorbide α 17-diethylene glycol ester (XL) (chlorophyll α derivative), revealing insights into antitumor activity and maintaining quality, meeting the pharmaceutical approach of new nanoformulation design. Our formulation, based on poly(lactic-co-glycolic acid) (PLGA) nanoparticles, increased XL solubility and selective tumor-targeted accumulation. In our research, we revealed, for the first time, that XL binding to polyvinyl alcohol (PVA) enhances XL photophysical activity, providing the rationale for PVA application as a stabilizer for nanoformulations. Results of FTIR, DSC, and XRD revealed the physical interactions between XL and excipients, including PVA, indicating that the encapsulation maintained XL binding to PVA. The encapsulated XL exhibited higher photophysical activity compared to non-encapsulated substance, which can be attributed to the influence of residual PVA. Gamma-irradiation led to degradation of XL; however, successful sterilization of the samples was achieved through the filtration. Importantly, the encapsulated and sterilized XL retained cytotoxicity against both 2D and 3D tumor cell models, demonstrating the potential of the formulated NP-XL for photodynamic therapy applications, but lacked the ability to reactivate epigenetically silenced genes. These findings provide valuable insights into the design and characterization of PLGA-based nanoparticles for the encapsulation of photosensitizers.

Increased stiffness of extracellular matrix enhanced chemoresistance in 3D-bioprinted ovarian cancer model

Ovarian cancer is a gynecological malignancy with a high mortality rate. The ovarian cancer microenvironment is a crucial factor affecting the overall and progression-free survival rates of patients with ovarian cancer. The biophysical factors of the tumor microenvironment, such as stiffness, can affect the gene expression and behavior of tumor cells. In this study, we utilized 3D bioprinting technology to construct ovarian cancer tumor models with varying levels of stiffness in vitro to investigate the effect of extracellular matrix stiffness on drug resistance of tumor cells. Our findings indicate that increasing the stiffness of extracellular matrix can attenuate the sensitivity of tumor cells to chemotherapeutic agents. Additionally, the increased stiffness of 3D tumor model may promote malignant phenotypes, such as tumor stemness and tumor progression.

Early prediction of pathological response to neoadjuvant chemotherapy of breast tumors: a comparative study using amide proton transfer-weighted, diffusion weighted and dynamic contrast enhanced MRI.

To examine amide proton transfer-weighted (APTw) combined with diffusion weighed (DWI) and dynamic contrast enhanced (DCE) MRI for early prediction of pathological response to neoadjuvant chemotherapy in invasive breast cancer. In this prospective study, 50 female breast cancer patients (49.58 ± 10.62 years old) administered neoadjuvant chemotherapy (NAC) were enrolled with MRI carried out both before NAC (T0) and at the end of the second cycle of NAC (T1). The patients were divided into 2 groups based on tumor response according to the Miller-Payne Grading (MPG) system. Group 1 included patients with a greater degree of decrease in major histologic responder (MHR, Miller-Payne G4-5), while group 2 included non-MHR cases (Miller-Payne G1-3). Traditional imaging protocols (T1 weighted, T2 weighted, diffusion weighted, and DCE-MRI) and APTw imaging were scanned for each subject before and after treatment. APTw value (APTw0 and APTw1), Dmax (maximum diameter, Dmax0 and Dmax1), V (3D tumor volume, V0 and V1), and ADC (apparent diffusion coefficient, ADC0 and ADC1) before and after treatment, as well as changes between the two times points (ΔAPT, ΔDmax, ΔV, ΔADC) for breast tumors were compared between the two groups. APT0 and APT1 values significantly differed between the two groups (p = 0.034 and 0.01). ΔAPTw values were significantly lower in non-MHR tumors compared with MHR tumors (p = 0.015). ΔDmax values were significantly higher in MHR tumors compared with non-MHR tumors (p = 0.005). ADC0 and ADC1 values were significantly higher in MHR tumors than in non-MHR tumors (p = 0.038 and 0.035). AUC (Dmax+DWI + APTw) = AUC (Dmax+APTw) > AUC (APTw) > AUC (Dmax+DWI) > AUC (Dmax). APTw imaging along with change of tumor size showed a significant potential in early prediction of MHR for NAC treatment in breast cancer, which might allow timely regimen refinement before definitive surgical treatment.

Abstract B061: Development of a pancreatic ductal adenocarcinoma 3D tumor model for high-throughput drug screening

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a persistent malignancy that is difficult to diagnose in its early stage and is one of the leading cancer-related deaths worldwide. Currently, limited therapeutic options are available for PDAC, resulting in an extremely low 5-year survival rate. To speed up the discovery of novel therapeutics, a reliable 3D model that highly simulates the PDAC tumor microenvironment is needed for large-scale drug screening. In this study, we propose a novel 3D model for restoring the PDAC tumor microenvironment by targeting cancer-associated fibroblasts (CAFs), which serve as the key component of the PDAC, providing its heterogeneity and contributing to reciprocal signaling and drug resistance. Our previous studies have demonstrated that Adipose-derived mesenchymal stem cells can differentiate into varying subtypes CAFs when co-cultured with PDAC cells both in vitro and in vivo. Following this strategy, we utilize the fibroblast-populated collagen lattice (FPCL) modeling approach, which relies on the contractility of fibroblasts in a collagen gel matrix, to provide the mechanical stress and hypoxic conditions for the 3D tumor models. Human Adipose-derived mesenchymal stem cells as CAF precursors and PDAC cell lines were mixed with collagen solution to make the collagen discs, resulting in the formation of 3D PDAC tumor models within a week. The morphological analyses, along with global transcriptome and metabolomic analyses, were performed to confirm the clinical-like mature ductal glands of PDAC cells and CAFs-like spindle-shaped of mesenchymal stem cells in the interior of PDAC-FPCL (PDAC-F). Moreover, the PDAC-F has shown a high tumorigenic potential in vivo animal model. Additionally, PDAC-F was shown to allow combination therapies screening of anticancer and antifibrotic drugs in the drug screening test, demonstrating that the combination therapeutics have better efficacy. In conclusion, our PDAC-F is built with distinct features of PDAC, reproducing the heterogeneous and high stiffness with a clinical-like PDAC morphology. In addition, the short modeling time and the high reproducibility of this PDAC-F open the possibilities for large-scale drug screening, which is expected to accelerate new drug development and provide effective treatment for pancreatic cancer patients. Citation Format: Xiaoyu Song, Yuma Nihashi, Yasuyuki S. Kida. Development of a pancreatic ductal adenocarcinoma 3D tumor model for high-throughput drug screening [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr B061.

Polydopamine-Based Resveratrol-Hyaluronidase Nanomedicine Inhibited Pancreatic Cancer Cell Invasive Phenotype in Hyaluronic Acid Enrichment Tumor Sphere Model.

The dense storm microenvironment formed by an excessively cross-linked extracellular matrix, such as hyaluronic acid and collagens, serves as a major barrier that prevents drugs from reaching the deeper tumor. Current traditional two-dimensional (2D) cultures are not capable of modeling this drug delivery barrier in vitro. Thus, tumor spheroids have become increasingly important in cancer research due to their three-dimensional structure. Currently, various methods have been developed to construct tumor spheroids. However, there are still challenges, such as lengthy construction time, complex composition of added growth factors, and high cultivation costs. To address this technical bottleneck, our study combined the GelMA hydrogel system to develop a rapid and high-yield method for tumor spheroids generation. Additionally, we proposed an evaluation scheme to assess the effects of drugs on tumor spheroids. Building on the hyaluronic acid-rich pathological tumor microenvironment, we constructed a resveratrol-loaded nano-drug delivery system with tumor stroma modulation capability and used a three-dimensional (3D) tumor sphere model to simulate in vivo tumor conditions. This process was utilized to completely evaluate the ability of the nano-drug delivery system to enhance the deep penetration of resveratrol in the tumor microenvironment, providing new insights into future oncology drug screening, efficacy assessment, and drug delivery methods.

Assessment of Mononuclear/Dinuclear copper acylhydrazone complexes for lung cancer treatment

Non-platinum metal-based complexes have good potential for cancer treatment. Here, we designed and synthesized five hydrazone copper(II) complexes, [Cu2(HL)2Cl2] 1A, [Cu2(HL)2(NO3)H2O]·NO3 2A, [Cu2(HL)2Br2] 3A, [Cu(L)pyridine] 1B and [Cu(HL)(pyridine)Br] 3B, and evaluated their anti-lung cancer activities. MTT experiments revealed that these copper(II) complexes exhibit higher anticancer activity than cisplatin. Mechanism studies revealed that complex 3A induced G1 phase cell cycle arrest, and induced cell apoptosis via reactive oxygen species (ROS)-mediated mitochondrial dysfunction. Scratch wound healing assay was also performed, revealing that complex 3A have good anti-cell migration activity. Hemolysis assays showed good blood biocompatibility of complex 3A. Furthermore, complex 3A can significantly inhibit the proliferation of A549 3D tumor spheroid. An in vivo anticancer study showed that complex 3A could delays the growth of A549 tumor xenografts with lower systemic toxicity. These results highlight the great possibility of developing highly active copper complexes as anti-lung cancer agents.

Clinical application of CT-based radiomics model in differentiation between laryngeal squamous cell carcinoma and squamous cell hyperplasia.

To evaluate the clinical application of the CT-based radiomics prediction model for discriminating SCC and SCH. A total of 254 clinical samples were selected from 291 patients with larynx-occupying lesions who underwent primary surgery. All lesions were validated via histopathological examination at The Second Hospital of Jilin University between June 2004 and December 2019. All patients were randomly allocated to the training (n = 177) and validation (n = 77) cohorts. After the acquisition of CT images, manual 3D tumor segmentation was performed using the CT images of the arterial, venous, and non-contrast phases via ITK-SNAP software. Subsequently, radiomics features were extracted using A.K. software. Based on the above features, three different diagnostic models (CTN, CTA+CTV, and CTN+CTA+CTV) were constructed to classify squamous cell carcinoma (SCC) and squamous cell hyperplasia (SCH). Additionally, receiver operating characteristic (ROC) and decision curve analysis (DCA) curves were measured to evaluate the diagnostic characteristics and clinical safety of the proposed three prognostic models. In the radiomic prediction Model 1 (CTN), the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the training cohorts in differentiating SCC and SCH were 0.883, 0.785, 0.645, 1.000, 1.000, and 0.648, while in the testing cohorts, these values were 0.852, 0.792, 0.66, 1.000, 1.000, and 0.652, respectively. In the radiomic prediction Model 2 (CTA+CTV), the AUC, accuracy, sensitivity, specificity, PPV, and NPV values of the training cohorts were 0.965, 0.91, 0.916, 0.9, 0.933, and 0.875, respectively, while in the testing cohorts, the corresponding values were 0.902, 0.805, 0.851, 0.733, 0.833, and 0.759, respectively. In the radiomic prediction Model 3(CTN+CTA+CTV), the AUC, accuracy, sensitivity, specificity, PPV, and NPV values of the training cohorts were 0.985, 0.944, 0.953, 0.929, 0.953, and 0.929, while in the testing cohorts, the corresponding values were 0.965, 0.857, 0.894, 0.8, 0.875, and 0.828, respectively. The radiomic prediction Model 3, based on the arterial-venous-plain combined scan phase of CT, achieved promising diagnostic performance, expected to be regarded as a preoperative imaging tool in classifying SCC and SCH to guide clinicians to develop individualized treatment programs.