3D Tumor Research Articles

A digital manufactured microfluidic platform for flexible construction of 3D co-culture tumor model with spatiotemporal resolution

The specific spatiotemporal distribution of diverse components in tumor microenvironment plays a crucial role in the cancer progression.In vitrothree-dimensional (3D) tumor models with polydimethylsiloxane (PDMS) based microfluidic platform have been applied as useful tool to conduct studies from cancer biology to drug screening. However, PDMS has not been welcomed as a standardized commercial application for preclinical screening due to inherent limitations in scale-up production and molecule absorption. Here, we present a novel microfluidic platform to flexibly construct 3D co-culture models with spatiotemporal resolution by using multiple digital manufacturing technologies. The platform, which consist of reduplicative microfluidic chips, is made of biocompatible poly methyl methacrylate by fast laser cutting. Each replica includes a simple microfluidic chamber without internal structures which can be flexibly post-fabricated according to various research requirements. Digital light processing based 3D bioprinting was used to pattern fine hydrogel structures for post-fabrication on-chip. By multi-step bioprinting and automatic image alignment, we show that this approach provides sufficient design flexibility to construct 3D co-culture tumor model with spatiotemporal resolution to replicate microarchitecture of tumor microtissuein situ. And the tumor model has the potential to mimic tumor biology behaviors which can be used for mechanism study and drug test. Our microengineered tumor model may serve as an enabling tool to recapitulate pathophysiological complexity of tumor, and to systematically examine the contribution of the tumor microenvironment to the cancer progression. The proposed strategy can also be applied to help engineer diverse meaningfulin vitromodels for extensive biomedical applications, from physiology and disease study to therapy evaluation.

Spatiotemporally Resolved Approach for Profiling Ferroptosis-Associated Metabolic Vulnerabilities in Tumors Using Mass Spectrometry Imaging and Stable Isotope Tracing.

Ferroptosis, as an iron-dependent cell death mediated by lipid peroxidation, has sparked great interest in the tumor research community. Targeting ferroptosis has been proven to be a new therapeutic opportunity for inhibiting tumor growth. However, it is challenging to precisely characterize the metabolic pattern of ferroptosis in heterogeneous tumors and further identify ferroptosis-associated metabolic vulnerabilities for tumor treatment. In this work, we developed a spatiotemporally resolved method to image ferroptosis-associated metabolic alterations in 3D tumor spheroids by combining mass spectrometry imaging and stable isotope tracing techniques. The construction of a 3D tumor spheroid model allows for a more accurate simulation of ferroptosis, and the introduction of MALDI-MSI enables in situ screening of abnormal molecules in tumor tissues. Using this method, we showed that the expression proportion of nC═C = 4 polyunsaturated fatty acids, including arachidonic acid (FA-20:4) and adrenic acid (FA-22:4), were upregulated in RSL3-induced 3D tumor ferroptosis models. And the isotope tracing experiment revealed that the absorption of fatty acids and the biosynthesis of polyunsaturated fatty acids were significantly increased during ferroptosis. In addition, we discovered that arachidonic acid and adrenic acid supplementation render tumor cell sensitive to ferroptosis, thereby limiting the growth of tumor cells and the formation of 3D tumor spheroids. Such findings provide significant clues for understanding the metabolic signatures of tumor ferroptosis and raise the possibility to screen potential metabolic vulnerabilities for better tumor treatment in combination with ferroptosis.

Advancing osteosarcoma 3D modeling in vitro for novel tumor microenvironment-targeted therapies development

Osteosarcoma (OS) represents one of the most common primary bone cancers affecting children and young adults. The available treatments have remained unimproved for the past decades, hampered by the poor knowledge of OS etiology/pathophysiology and the lack of innovative, predictive and biologically relevant in vitro models, that can recapitulate the 3D OS tumor microenvironment (TME). Here, we report the development and characterization of an innovative 3D model of OS, composed of OS tumor cells, immune cells (macrophages) and mesenchymal stem cells (MSCs), that formed a multicellular tissue spheroid (MCTS). This fully humanized 3D model was shown to accurately mimic the native histological features of OS, while innately leading to the polarization of macrophages towards an M2-like phenotype, highly aggressive and pro-tumor profile. Upon the exposure to immunomodulatory molecules, the MCTS were shown to be responsive by shifting macrophages polarization, and dramatically altering the TME secretome. In agreement, when treated with immunomodulatory/stimulatory nanoparticles (NPSs), we were able to revert the TME secretome towards an anti-inflammatory profile. This study establishes an advanced 3D OS model capable of shedding light on macrophages and MSCs contributions to disease progression, paving the way for the development of innovative therapeutic approaches targeting the OS TME, while providing a biologically relevant in vitro tool for the efficacy screening of novel OS therapeutic approaches.

Unveiling potent bioactive compounds and anti-angiogenic pathways in Gekko swinhonis Guenther for gastric cancer therapy

Ethnopharmacological relevanceGekko swinhonis Guenther, commonly referred to as Gecko in the following text, belongs to the genus Gekko within the family Gekko. Its dried whole body is a widely utilized traditional Chinese medicine, demonstrating significant efficacy in the treatment of gastrointestinal malignancies, particularly gastric cancer (GC). Nevertheless, the composition of the gecko is complex, necessitating further research into its active ingredients for the treatment of GC. Aim of the studyIsolation and characterization of the most active components in Gecko based on their anti-GC mechanisms of vascular endothelial cell inhibition and anti-neovascularization. Materials and methodsWe utilized the enzymatic hydrolysate of Geckos to investigate its effectiveness and underlying mechanisms. Initially, we assessed its efficacy in ectopic and in-situ GC tumor-bearing mouse models. Subsequently, we evaluated the effectiveness of peptides, aliphatics, and small molecules derived from Gecko using CCK-8 and 3D tumor spheroid assays. The activities of peptides S1-S4 were further examined through these experiments. Finally, we screened, synthesized, and investigated five potential peptides for their pharmacodynamics in the CCK-8 assay and in the in-situ GC model mice. ResultsThe Gecko can inhibit the formation of blood vessels in the tumor microenvironment, providing a localized treatment for GC. The peptide components significantly inhibit vascular endothelial cells and impede the formation of new blood vessels, with the S2 peptide sections (0.3 KD - 3 KD) demonstrating the most potent inhibitory activity against angiogenesis. One of the active peptides effectively suppresses the growth of in-situ GC in nude mice through angiogenesis inhibition and also modulates immunity, all while exhibiting excellent biosafety. ConclusionsWe have achieved a significant breakthrough in the local treatment of GC using Gecko. Through pharmacodynamic experiments and a systematic process of isolation and identification, we identified the most effective anti-GC ingredients of Gecko, based on their mechanisms of inhibiting vascular endothelial cells and promoting anti-angiogenesis. Furthermore, we synthesized a lead peptide that demonstrates promising therapeutic efficacy and safety.

Multifunctional System with Camptothecin and [12]aneN3 Units for Effective In Vivo Anti Pancreatic Cancer through Synergistic Chemotherapy, Gene Therapy, and Photodynamic Therapy.

Maximizing drug cargo carrying capacity in blood circulation, controlling the in vivo fate of nanoparticles, and precisely drug release to tumor targets are the main aims of multifunctional nanomedicine-based antitumor therapy. Here we combined macrocyclic polyamine di(triazole-[12]aneN3) (M) and chemical drug camptothecin (CPT, C) through photosensitizer 1,1-dicyano-2-phenyl-2-(4-diphenylamino) phenyl-ethylene (DT) containing the cleavable disulfide (S) linkage as an all-in-one theranostic nanoprodrug, MDTSC. The corresponding compound with carbon chain (C) linkage, MDTCC, was also prepared for a comparison study. MDTSC showed the ability to carry plasmids, including the p53 tumor suppressor gene, to form lipoplexes with a size of ∼150 nm. Further addition of DOPE-PEG2k resulted in the hybrid lipoplexes MDTSC/DOPE-PEG2k@DNA, which showed good stability in blood circulation and good biocompatibility to normal cell lines. Experiments demonstrated that the hybrid lipoplexes were able to realize the successful cellular uptake and endosomal escape, to generate ROS under visible light irradiation as well as to trigger the localized release of CPT and the plasmid encoding p53 in tumor cells. In vitro, the hybrid lipoplexes showed better EGFP expression than the commercial Lipo2000, and markedly reduced tumor cell proliferation and migration rate irrespective of whether the BxPC-3 cell lines were grown on plates or 3D tumor spheroids. In vivo, the hybrid lipoplexes showed effective anticancer activity by reducing the BxPC-3 pancreatic tumor growth by 99% through the synergetic combination of chemotherapy, photodynamic therapy, and gene therapy. This research represented the first example of using a cocktail of three therapeutic approaches to achieve cooperative and effective anti pancreatic cancer treatment in vivo and in vitro.

Acid-exposed and hypoxic cancer cells do not overlap but are interdependent for unsaturated fatty acid resources

Cancer cells in acidic tumor regions are aggressive and a key therapeutic target, but distinguishing between acid-exposed and hypoxic cells is challenging. Here, we use carbonic anhydrase 9 (CA9) antibodies to mark acidic areas in both hypoxic and respiring tumor areas, along with an HRE-GFP reporter for hypoxia, to isolate distinct cell populations from 3D tumor spheroids. Transcriptomic analysis of CA9-positive, hypoxia-negative cells highlights enriched fatty acid desaturase activity. Inhibiting or silencing stearoyl-CoA desaturase-1 (SCD1) induces ferroptosis in CA9-positive acidic cancer cells and delays mouse tumor growth, an effect enhanced by omega-3 fatty acid supplementation. Using acid-exposed cancer cells and patient-derived tumor organoids, we show that SCD1 inhibition increases acidic cancer cell reliance on external mono-unsaturated fatty acids, depriving hypoxic cells of essential resources. This bystander effect provides unbiased evidence for a lack of full overlap between hypoxic and acidic tumor compartments, highlighting a rationale for targeting desaturase activity in cancer.

A Novel Method for 3D Lung Tumor Reconstruction Using Generative Models.

Lung cancer remains a significant health concern, and the effectiveness of early detection significantly enhances patient survival rates. Identifying lung tumors with high precision is a challenge due to the complex nature of tumor structures and the surrounding lung tissues. To address these hurdles, this paper presents an innovative three-step approach that leverages Generative Adversarial Networks (GAN), Long Short-Term Memory (LSTM), and VGG16 algorithms for the accurate reconstruction of three-dimensional (3D) lung tumor images. The first challenge we address is the accurate segmentation of lung tissues from CT images, a task complicated by the overwhelming presence of non-lung pixels, which can lead to classifier imbalance. Our solution employs a GAN model trained with a reinforcement learning (RL)-based algorithm to mitigate this imbalance and enhance segmentation accuracy. The second challenge involves precisely detecting tumors within the segmented lung regions. We introduce a second GAN model with a novel loss function that significantly improves tumor detection accuracy. Following successful segmentation and tumor detection, the VGG16 algorithm is utilized for feature extraction, preparing the data for the final 3D reconstruction. These features are then processed through an LSTM network and converted into a format suitable for the reconstructive GAN. This GAN, equipped with dilated convolution layers in its discriminator, captures extensive contextual information, enabling the accurate reconstruction of the tumor's 3D structure. The effectiveness of our method is demonstrated through rigorous evaluation against established techniques using the LIDC-IDRI dataset and standard performance metrics, showcasing its superior performance and potential for enhancing early lung cancer detection. This study highlights the benefits of combining GANs, LSTM, and VGG16 into a unified framework. This approach significantly improves the accuracy of detecting and reconstructing lung tumors, promising to enhance diagnostic methods and patient results in lung cancer treatment.

Development of Mg‐Alginate Based Self Disassociative Bio‐Ink for Magnetic Bio‐Patterning of 3D Tumor Models

AbstractAlginate forms a hydrogel via physical cross‐linking with divalent cations. In literature, Ca2+ is mostly utilized due to strong interactions but additional procedures are required to disassociate Ca‐alginate hydrogels. On the other hand, Mg‐alginate hydrogels disassociate spontaneously, which might benefit certain applications. This study introduces Mg‐alginate as the main component of a bio‐ink for the first time to obtain 3D tumor models by magnetic bio‐patterning technique. The bio‐ink contains magnetic nanoparticles (MNPs) for magnetic manipulation, Mg‐alginate hydrogel as a sacrificial material, and cells. The applicability of the methodology is tested for the formation of 3D tumor models using HeLa, SaOS‐2, and SH‐SY5Y cells. Long‐term cultures are examined by Live/dead and MTT analysis and revealed high cell viability. Subsequently, Collagen and F‐actin expressions are observed successfully in 3D tumor models. Finally, the anti‐cancer drug Doxorubicin (DOX) effect is investigated on 3D tumor models, and IC50 values is calculated to assess the drug response. As a result, significantly higher drug resistance is observed for bio‐patterned 3D tumor models up to tenfold compared to 2D control. Overall, Mg‐alginate hydrogel is successfully used to form bio‐patterned 3D tumor models, and the applicability of the model is shown effectively, especially as a drug screening platform.

PLLA Porous Scaffold as a 3D Breast Cancer Model to Investigate Drug Resistance.

Multidrug resistance remains one of the major challenges in breast cancer research, often leading to treatment failure. To better understand this mechanism, sophisticated three-dimensional (3D) tumor models are necessary, as they offer several advantages over traditional bidimensional (2D) cultures. In this study, poly-l-lactic-acid porous scaffolds were produced using a thermally induced phase separation technique and employed as 3D models for breast cancer cell lines: MDA-MB-231, MCF-7, and its multidrug-resistant variant, MCF-7R. The MTS assay was used to compare growth inhibition following doxorubicin treatment in 2D and 3D. Remarkably, the IC50 values increased in 3D cultures compared to 2D: MDA-MB-231 (445 vs. 54.5 ng/mL), MCF-7 (7.45 vs. 0.75 μg/mL), and MCF-7R (165 vs. 39 μg/mL). MCF-7R, which usually shows greater resistance in 2D, demonstrated even higher resistance in 3D. In fact, IC50 was not reached within 3 days as with the other models, but only after 6 days. Cellular morphology also played a crucial role. When treated with concentrations higher than the IC50, MDA-MB-231 cells lost their physiological 3D clustered structure, while MCF-7 and its resistant variant exhibited disrupted layers. All cell lines in 3D showed higher chemoresistance, suggesting a more biomimetic spatial architecture. Our work bridges the gap between monolayer and animal models, highlighting the potential of polymeric 3D scaffolds in breast cancer research.

Assessment of drug treatment response using primary human colon cancer cell spheroids cultivated in a microfluidic mixer chip

Chemotherapy is one of the main therapeutic methods for tumor treatment. However, improving the accuracy of personalized medication for chemotherapy remains challenging. In this study, we developed a novel microfluidic chip that features herringbone protrusions and three-dimensional (3D) microcolumn holes created from microcolumn arrays. This design allows for precise control over the size and number of 3D tumor cell spheroids. As tumor cells aggregate into clusters within the chip, an integrated microfluidic mixer enhances liquid mixing and improves contact between the spheroids and the culture medium, promoting their growth. By combining this 3D spheroid approach with a concentration gradient mixer, we effectively conducted dynamic and high-throughput evaluations of anti-tumor drugs. The chip successfully identified varying sensitivities of tumor cells from different patients to these drugs, aligning with clinical observations from postoperative follow-ups. These features indicated that the tumor cell spheroid integrated microfluidic chip is effective for drug evaluation methodologies and holds promising implications for clinical applications.

Performance of an AI-powered visualization software platform for precision surgery in breast cancer patients

Surgery remains the primary treatment modality in the management of early-stage invasive breast cancer. Artificial intelligence (AI)-powered visualization platforms offer the compelling potential to aid surgeons in evaluating the tumor’s location and morphology within the breast and accordingly optimize their surgical approach. We sought to validate an AI platform that employs dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to render three-dimensional (3D) representations of the tumor and 5 additional chest tissues, offering clear visualizations as well as functionalities for quantifying tumor morphology, tumor-to-landmark structure distances, excision volumes, and approximate surgical margins. This retrospective study assessed the visualization platform’s performance on 100 cases with ground-truth labels vetted by 2 breast-specialized radiologists. We assessed features including automatic AI-generated clinical metrics (e.g., tumor dimensions) as well as visualization tools including convex hulls at desired margins around the tumor to help visualize lumpectomy volume. The statistical performance of the platform’s automated features was robust and within the range of inter-radiologist variability. These detailed 3D tumor and surrounding multi-tissue depictions offer both qualitative and quantitative comprehension of cancer topology and may aid in formulating an optimal surgical approach for breast cancer treatment. We further establish the framework for broader data integration into the platform to enhance precision cancer care.

IMMU-63. MESSENGER RNA CHALLENGE PREDICTS CANCER IMMUNOGENICITY AND RESPONSE TO CHECKPOINT INHIBITORS

Abstract BACKGROUND Checkpoint inhibition has emerged as a promising cancer therapeutic approach. Checkpoint inhibitors (CIs) function by overcoming the adaptive T cell exhaustion induced by solid tumor microenvironment including brain tumors, particularly in the neoadjuvant setting. Unfortunately, not every patient who receives CIs will unlock effective antitumor immunity. Objectives: Microsatellite instability and high mutational burden are considered key criteria to predict response to CIs. However, only a minority of patients will fulfill these criteria suggesting the need to develop innovative technologies to identify CI responsive patients. METHODS To determine whether glioma tumors will respond to CIs, we have developed a novel multilamellar mRNA-lipid particle tool to predict response ex vivo. Messenger RNA is complexed into multilamellar lipid particles to form aggregates (RNA-LPAs) to induce pathogen recognition receptor signaling in tumor cells to define an inflammatory profile as an indirect predictor to CI response. RESULTS In naïve mice, we found that multilamellar RNA-LPAs induce activation of Type I IFN system as supported by decreased secretion of IFN-α in MyD88 KO mice compared with wild type mice. We next selected murine glioma cell lines with known response profile to CIs (responders – GL261 and SMA560 vs non-responders – KR158b and CT2A). Prior to evaluation of cytokine profiling, successful uptake of RNA-LPAs was achieved in all cell lines. In 2D cell lines cultures and their corresponding 3D tumor spheroids, we demonstrated that treatment of CI responsive murine glioma models showed a differential cytokine signature (increased secretion of IFN-β/IL-6/CCL4 versus non-responsive models). CONCLUSION We identified a unique inflammatory signature after ex vivo RNA-LPAs challenge that correlates with checkpoint blockade activity. These findings allow for creation of a diagnostic assay to quickly assess tumor immunogenicity, allowing for informed immunotherapeutic treatment.

DDEL-09. AS1411 APTAMER-CONJUGATED NANOSPHERES FOR TARGETING GLIOBLASTOMA THERAPY

Abstract Postoperative chemotherapy remains essential for treating glioblastoma (GBM), with nanocarrier-based drug delivery emerging as the most efficient method. However, non-specific delivery across the blood-brain barrier (BBB) can limit drug accumulation in tumors and cause damage to nearby tissues. As cancer progresses, angiogenic processes lead to the formation of an irregular blood-tumor barrier (BTB), necessitating nanodrug platforms for precise targeting and efficient drug delivery to cancer cells. In this study, we aimed to demonstrate targeted cancer therapy by selectively identifying tumor cells overexpressing nucleolin (NCL) protein using Dox-loaded AS1411 aptamer-conjugated nanospheres. Drug nanocarriers were synthesized from small molecules with sizes ranging from 100 to 300 nm to facilitate drug delivery. Selective drug delivery and cellular uptake were demonstrated for NCL-positive GBM cells (U87 and U251) compared to NCL-negative normal human astrocyte (NHA) cells. Flow cytometric analysis using FAM dye-labeled AS1411 aptamer-conjugated nanospheres confirmed that drug delivery to GBM U87 and U251 cells was actively targeted by specific AS1411-NCL interactions. Confocal laser scanning microscopy and cytotoxicity analysis confirmed that inoculation of Dox-loaded AS1411 aptamer-conjugated nanospheres induced selective internalization in GBM U87 and U251 cells. Moreover, to evaluate cytotoxicity and anti-tumor effects after treatment with PBS, Apt-Nanospheres, Free Dox, and Dox-Apt-Nanospheres, the results were analyzed through cell counting kit (CCK-8) analysis, evaluation of differences in 3D tumor sphere radii, and an in vivo GBM xenograft tumor model. The AS1411 aptamer-conjugated nanosphere drug delivery system was developed for dual-target treatment of GBM. AS1411-mediated specific recognition and drug accumulation significantly enhanced binding to NCL-positive U87 and U251 cells and improved cytotoxicity efficiency compared to Free Dox. Additionally, this study demonstrated that the active targeting model using aptamer-mediated drug delivery was more effective in improving drug penetration and retention in tumor cells than non-specific enhanced permeability and retention (EPR)-mediated delivery and passive drug delivery.

Unraveling Microviscosity Changes Induced in Cancer Cells by Photodynamic Therapy with Targeted Genetically Encoded Photosensitizer.

Despite the fundamental importance of cell membrane microviscosity, changes in this biophysical parameter of membranes during photodynamic therapy (PDT) have not been fully understood. In this work, changes in the microviscosity of membranes of live HeLa Kyoto tumor cells were studied during PDT with KillerRed, a genetically encoded photosensitizer, in different cellular localizations. Membrane microviscosity was visualized using fluorescence lifetime imaging microscopy (FLIM) with a viscosity-sensitive BODIPY2 rotor. Depending on the localization of the phototoxic protein, different effects on membrane microviscosity were observed. With nuclear localization of KillerRed, a gradual decrease in microviscosity was detected throughout the entire observation period, while for membrane localization of KillerRed, a dramatic increase in microviscosity was observed in the first minutes after PDT, and then a significant decrease at later stages of monitoring. The obtained data on cell monolayers are in good agreement with the data obtained for 3D tumor spheroids. These results indicate the involvement of membrane microviscosity in the response of tumor cells to PDT, which strongly depends on the localization of reactive oxygen species attack via targeting of a genetically encoded photosensitizer.

Culturally responsive strategies and practical considerations for live tissue studies in Māori participant cohorts.

Indigenous communities globally are inequitably affected by non-communicable diseases such as cancer and coronary artery disease. Increased focus on personalized medicine approaches for the treatment of these diseases offers opportunities to improve the health of Indigenous people. Conversely, poorly implemented approaches pose increased risk of further exacerbating current inequities in health outcomes for Indigenous peoples. The advancement of modern biology techniques, such as three-dimensional (3D) in vitro models and next generation sequencing (NGS) technologies, have enhanced our understanding of disease mechanisms and individualized treatment responses. However, current representation of Indigenous peoples in these datasets is lacking. It is crucial that there is appropriate and ethical representation of Indigenous peoples in generated datasets to ensure these technologies can be used to maximize the benefit of personalized medicine for Indigenous peoples. This project discusses the use of 3D tumor organoids and single cell/nucleus RNA sequencing to study cancer treatment responses and explore immune cell roles in coronary artery disease. Using key pillars from currently available Indigenous bioethics frameworks, strategies were developed for the use of Māori participant samples for live tissue and sequencing studies. These were based on extensive collaborations with local Māori community, scientific leaders, clinical experts, and international collaborators from the Broad Institute of MIT and Harvard. Issues surrounding the use of live tissue, genomic data, sending samples overseas and Indigenous data sovereignty were discussed. This paper illustrates a real-world example of how collaboration with community and the incorporation of Indigenous worldviews can be applied to molecular biology studies in a practical and culturally responsive manner, ensuring fair and equitable representation of Indigenous peoples in modern scientific data.

Preoperative predictors of biochemical remission in somatotroph adenoma resections: a single-institution retrospective review.

There is persistent debate in the literature surrounding the true predictors of biochemical remission after resection of somatotroph adenoma. A multimodal analysis of a large number of patients is needed to better understand which patients may be at higher or lower risk for remission failure after surgery. A retrospective review was performed on patients undergoing somatotroph adenoma resection. Biochemical remission was defined as age- and sex-adjusted normalization of serum insulin growth factor-1 (IGF-1) levels at least 6 months after surgery. Patient case characteristics and clinicopathologic variables were tested for statistical associations with remission and were included in a random forest machine learning model to assess for their importance in determining remission status. Preoperative variables found to be significant remission predictors on statistical testing and important in the random forest model were subsequently assessed via receiver operating characteristic (ROC) analysis to determine numeric thresholds that optimally predicted preoperative likelihood of remission success or failure. Eighty patients were identified with somatotroph adenoma who underwent transsphenoidal resection, with 60 patients (75%) achieving biochemical remission. Statistical testing found that patients with failed remission were more likely to have larger tumors (1.9 vs 1.6 cm by the largest axis, p = 0.014; and 3.61 vs 2.66 cm3 by 3D volume, p = 0.013) that invaded the cavernous sinus more frequently (70% vs 22% of patients, p < 0.001) and have higher preoperative IGF-1 level (860 vs 660 ng/ml, p = 0.044). An optimized random forest machine learning model with 10,000 iterations found that tumor size, preoperative growth hormone and IGF-1 levels, and cavernous sinus invasion were important preoperative predictors of remission status. ROC analysis revealed that 96% of patients with preoperative 3D tumor volume less than 1.51 cm3 (area under the curve [AUC] 0.691, p = 0.003) and 100% with nonadjusted preoperative IGF-1 level less than 718.5 ng/ml (AUC 0.736, p = 0.002) achieved remission. Important preoperative predictors of postoperative remission for somatotroph adenoma resection include serum IGF-1 level, cavernous sinus invasion, and tumor size. Ninety-five percent of patients who achieved postoperative remission had preoperative 3D tumor volume less than 1.51 cm3.

RNAi Screen Identifies AXL Inhibition Combined with Cannabinoid WIN55212-2 as a Potential Strategy for Cancer Treatment.

Background and objective: Cannabinoids are commonly used as adjuvant cancer drugs to overcome numerous adverse side effects for patients. The aim of this study was to identify the target genes that show a synergistic anti-tumor role in combination with the cannabinoid WIN55212-2 in vitro and in vivo. Methods: A human kinome RNAi library was used to screen the targeted gene that silencing plus WIN55212-2 treatment synergistically inhibited cancer cell growth in an INCELL Analyzer 2000. Cell viability, cell phase arrest and apoptosis were evaluated by MTT and flow cytometry assay. In vivo combined anti-tumor effects and regulatory mechanisms were detected in immunocompromised and immunocompetent mice. Results: Using RNAi screening, we identified the tyrosine receptor kinase AXL as a potential gene whose silencing plus WIN55212-2 treatment synergistically inhibited the proliferation of cancer cells in an INCELL Analyzer 2000. Subsequently, we demonstrated that inhibition of AXL by TP-0903 potentiated the inhibitory role of WIN55212-2 on cellular viability, colony formation and 3D tumor sphere in HCT-8 cells. Meanwhile, TP-0903 plus WIN55212-2 treatment promoted the apoptosis of HCT-8 cells. We then investigated the synergistic anti-tumor effect of TP-0903 and WIN55212-2 using colon cancer cell xenografts in immunocompromised and immunocompetent mice. The in vivo study demonstrated that combined administration of TP-0903 plus WIN55212-2 effectively reduced tumor volume and microvessel density and promoted apoptotic cells of tumor tissues in HCT-8 exogenous mice compared to either TP-0903 or WIN55212-2 treatment alone. Moreover, in addition to tumor suppression, the combination therapy of TP-0903 and WIN55212-2 induced the infiltration of cytotoxic CD8+ T cells and significantly reduced mTOR and STAT3 activation in tumor tissues of C57BL/6J mice bearing MC-38 cells. Conclusions: This study demonstrated that targeting AXL could sensitize cannabinoids to cancer therapy by interfering with tumor cells and tumor-infiltrating CD8+ T cells.

Protein absorption alters the cellular targeting of glycopolymeric nanoparticles

Glycopolymeric nanoparticles are widely employed in biomedical applications due to their high targeting ability, biocompatibility, and biodegradability. The pendant saccharides serve as targeting ligands to be explicitly coordinated to receptors on cell membrane surfaces. However, proteins in the blood often absorb onto the nanoparticle surface, potentially impacting the exposure and effectiveness of the saccharide ligands for targeted delivery. To elucidate the protein absorption effects, we prepared micelles decorated with different percentages of fructose moieties and evaluated the bioactivity of nanoparticles using 2D cell culture, tumor spheroid, liver organoid, and coculture models. The 2D cell culture model did not show a significant difference in activity between protein-coated and non-coated micelles. However, a dramatic decrease in cellular uptake and penetration ability of micelles was observed in 3D tumor spheroids after protein absorption. Additionally, protein absorption notably increased micelle uptake in liver organoids. In the coculture model, protein absorption reduced micelle uptake in tumor spheroids while favoring uptake in liver organoids. Our work suggests that decreasing non-specific protein absorption of glycopolymeric nanoparticles could enhance their delivery efficiency. These findings underscore the importance of understanding protein interactions in nanoparticle applications for drug delivery.

Biosynthesis of pH-Responsive Mesoporous Silica Nanoparticles from Cucumber Peels for Targeting 3D Lung Tumor Spheroids.

Lung adenocarcinoma is considered to be one of the primary causes of cancer-related deaths globally. Conventional treatments, such as chemotherapy and radiation therapy taken together, have not significantly lowered mortality rates. Repositioning of authorized anticancer medications supported by nanotechnology has therefore emerged as an effective strategy to close such gaps. In this context, mesoporous silica nanoparticles (MSNs) were biosynthesized from cucumber peels and were loaded with doxorubicin, a common anticancer drug to form doxorubicin-bound mesoporous silica nanoparticles (DMSNs). The study addresses a sustainable method for turning waste materials into MSNs, which can be used to create multifunctional nanosystems. The therapeutic module (DMSNs) was designed specifically to target 2D monolayer cells and 3D tumor spheroids of lung adenocarcinoma cancer. The DMSNs demonstrated notable antiproliferative activity and effective intracellular localization in addition to being biocompatible and innately fluorescent. Subsequent investigations revealed significant antibacterial activity against Staphylococcal infection, which is primarily prevalent in lung cancer patients. Thus, the developed MSNs held promising potential for anticancer drug delivery systems and have antibacterial potential to treat bacterial infections in patients with lung cancer. Furthermore, the cucumber peel-mediated synthesis of MSNs could also aid in the management of food waste and promote the adoption of the waste-to-health paradigm for sustainable solutions.

Biobased hydrogel bioinks of pectin, nanocellulose and lysozyme nanofibrils for the bioprinting of A375 melanoma cell-laden 3D in vitro platforms

Melanoma is one of the most aggressive types of skin cancer, and the need for advanced platforms to study this disease and to develop new treatments is rising. 3D bioprinted tumor models are emerging as advanced tools to tackle these needs, with the design of adequate bioinks being a fundamental step to address this challenging process. Thus, this work explores the synergy between two biobased nanofibers, nanofibrillated cellulose (NFC) and lysozyme amyloid nanofibrils (LNFs), to create pectin nanocomposite hydrogel bioinks for the 3D bioprinting of A375 melanoma cell-laden living constructs. The incorporation of LNFs (5, 10 or 15 wt%) on a pectin-NFC suspension originates inks with enhanced rheological properties (shear viscosity and yield point) and proper shear-thinning behavior. The crosslinked hydrogels mimic the stiffness of melanoma tissues, being stable under physiological and cell-culture conditions, and non-cytotoxic towards A375 melanoma cells. P-NFC-LNFs (10 %) reveals good printability (Pr = 0.89) and printing accuracy (51 ± 2 %), and when loaded with A375 cells (3 × 106 cells mL−1) the bioink originates 3D-constructs with high cell viability (92 ± 1 %) after 14 days. The potential of the constructs as 3D in vitro platforms is corroborated by a drug-screening test with doxorubicin, where cells within the model displayed high sensitivity to the drug.