3D Tumor Research Articles

Characterization of EpCAM in thyroid cancer biology by three-dimensional spheroids in vitro model

BackgroundThyroid cancer (TC) is the most common endocrine malignancy. Nowadays, undifferentiated thyroid cancers (UTCs) are still lethal, mostly due to the insurgence of therapy resistance and disease relapse. These events are believed to be caused by a subpopulation of cancer cells with stem-like phenotype and specific tumor-initiating abilities, known as tumor-initiating cells (TICs). A comprehensive understanding of how to isolate and target these cells is necessary. Here we provide insights into the role that the protein Epithelial Cell Adhesion Molecule (EpCAM), a known TICs marker for other solid tumors, may have in TC biology, thus considering EpCAM a potential marker of thyroid TICs in UTCs.MethodsThe characterization of EpCAM was accomplished through Western Blot and Immunofluorescence on patient-derived tissue samples, adherent cell cultures, and 3D sphere cultures of poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) cell lines. The frequency of tumor cells with putative tumor-initiating ability within the 3D cultures was assessed through extreme limiting dilution analysis (ELDA). EpCAM proteolytic cleavages were studied through treatments with different cleavages’ inhibitors. To evaluate the involvement of EpCAM in inducing drug resistance, Vemurafenib (PLX-4032) treatments were assessed through MTT assay.ResultsVariable EpCAM expression pattern was observed in TC tissue samples, with increased cleavage in the more UTC. We demonstrated that EpCAM is subjected to an intense cleavage process in ATC-derived 3D tumor spheres and that the 3D model faithfully mimics what was observed in patient’s samples. We also proved that the integrity of the protein appears to be crucial for the generation of 3D spheres, and its expression and cleavage in a 3D system could contribute to drug resistance in thyroid TICs.ConclusionsOur data provide novel information on the role of EpCAM expression and cleavage in the biology of thyroid TICs, and our 3D model reflects the variability of EpCAM cleavage observed in tissue samples. EpCAM evaluation could play a role in clinical decisions regarding patient therapy since its expression and cleavage may have a fundamental role in the switch to a drug-resistant phenotype of UTC cells.

Use of an AI-powered visualization platform to support precision clinical decision-making in patients with breast cancer undergoing neoadjuvant chemotherapy.

e12618 Background: Chemotherapy to reduce cancer burden and tumor size ("downstaging") is widely used in neoadjuvant treatment of early-stage breast cancer (ESBC) and can have a dramatic impact on selection of further treatment courses, including surgery. The resulting decision-making process between physicians and cancer patients requires detailed and effective communication of the patient's disease status, and clear presentation of this information in Tumor Board settings. Artificial intelligence (AI) -powered visualization platforms offer the potential to aid in evaluating breast tumor location and morphology, and accordingly optimize treatment. Additionally, these tools offer enhanced communication with patients regarding future treatment options, particularly serving as clinical decision support (CDS) tools. Methods: We assessed the performance of an AI platform that employs dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to render three-dimensional (3D) visualizations of breast tumors and 5 additional chest tissues on an independent validation dataset comprise of 100 ESBC cases with ground-truth tumor labels vetted by 2 breast-specialized radiologists. The platform provides 3D depictions of the tumor and its multi-tissue context, as well as functionalities for quantifying tumor morphology, tumor-to-landmark structure distances, excision volumes, and approximate surgical margins. We subsequently evaluated the tool's utility in a real-world setting to understand how the tool impacts clinical decision-making and patient communication, specifically around surgical planning in the context of neoadjuvant chemotherapy (NACT). Results: The platform generated accurate 3D tumor maps, as evidenced by a median Dice score of 75.6% and a median Hausdorff distances of 15.1 mm relative to the radiologist validation set. The automatic longest tumor dimension calculations were linearly correlated with radiologist direct measurements (Pearson correlation coefficient = 0.78) and had a median absolute difference of 6.3 mm. We found strong overlap between the platform’s ground-truth convex hulls, as shown by a median Dice score of 81.5%. When used by a skilled breast-specialized surgeon, the tool enabled rapid and intuitive patient-physician communication of the location and extent of disease, and potential degrees of downstaging to breast-conserving surgery. Conclusions: Detailed 3D tumor and surrounding multi-tissue depictions offer both qualitative and quantitative comprehension of cancer topology and may aid in formulating an optimal treatment approach for breast cancer treatment. We show that detailed depictions enhance communication between physicians and patients and may aid in streamlining decision-making.

Advancing precision medicine in cutaneous oncology through 3D high-frequency ultrasound imaging.

e13625 Background: Clinical assessment of tumor depth and shape often requires biopsy, especially when evaluating skin cancers. High Frequency Ultrasound (HFUS) is a non-invasive clinical tool that can quickly produce high resolution images ideally suited for evaluating topical tumors. In comparison to other imaging modalities, HFUS do not always provide the spatial data required to model 3-dimensional (3D) tumors. Currently, 3D-images are an amalgamation of many segmented image slices. However, in outpatient clinics it is unrealistic for HFUS devices and clinicians to gather large sets of image data. In our present original research, we aimed to overcome limited number of HFUS and dermatoscopic images by constructing a simple framework to process sparse and non-spatial data into working 3D skin tumor models. Methods: We analyzed two different skin tumors, the dermal duct tumor (DDT) and basal cell carcinoma (BCC), each with different number of HFUS images at 30Hz and 50Hz respectively. 1 set of 6 parallel images were obtained for the BCC, while 2 orthogonal sets of 6 parallel images were obtained for the DDT. For each tumor, a single dermatoscopic photo and sets of bitmap HFUS images with a resolution of 1024 x 512 were taken. Our study was IRB-approved. Mathematica and MATLAB, both with accessible documentation, were used to process images. Results: We developed a novel algorithmic approach to produce 3D tumor models with limited medical data. Both tumors appear corporally hypoechoic under HFUS. Mathematica was used to first reduce HFUS image noise and binarize the tumor region with a bilateral Gaussian filter. The user-friendly MATLAB Image Segmenter application manually filled the region of interest. Next, Mathematica was used to orient and plot tumor borders in 3D. Finally, we encompassed the borders with a 3D convex hull to conservatively predict tight margins around the tumor. Conclusions: Our simplified approach allows clinicians and scientists to produce 3D renderings of tumor margins. Margin control must always be balanced with a positive surgical outcome. By approaching our 3D-model with a convex hull around sampled border cross-sections, we chose a conservative approach that focuses skin tumor margin evaluation. Our results promote precision medicine and planning into the current standard of skin cancer treatment. Our findings can allow tracking tumor progression or treatment possible via non-invasive evaluation of tumor depth and contour. An aim of our present research is to lower the barrier of 3D construction in clinical settings. Simple algorithms, such as shown in our work, transform orthogonal and sparse data into usable data that can be implemented to train machine learning and artificial intelligent programs. Future research tailoring this approach may allow instant programming of HFUS images to non-invasively render cutaneous tumor borders and depth in real time during clinical examination.

INSIHGT: A scalable and homogeneous 3D multiplexed molecular mapping platform for spatial biology and precision medicine.

e15180 Background: The dynamic interplay between cancer cells and their microenvironment is a determinant of disease evolution and response to treatment. However, the current state of three-dimensional (3D) tumor microenvironment analysis is hindered by inadequate penetration of antibodies into thick tissue sections, leading to a substantial gap in acquiring unbiased, precise 3D multiplexed immunohistochemistry (IHC) images. Methods: We developed INSIHGT to surmount these limitations by enabling multi-round, multiplexed 3D IHC in standard formalin-fixed tissues. This fully automatable, fast-track method requires a simple series of chemical cocktail exchanges, translating to a tissue-to-image time of 6 days for 1 cm³ samples and as little as 6 hours for biopsy specimens. INSIHGT offers a scalable and efficient solution for detailed 3D spatial mapping of cancerous cells and their interactions within their native context. Results: 3D IHC with INSIHGT shows ideal penetration homogeneity, which quantitatively matches reference signals in 1cm3 samples. We further validated INSIHGT with 309 commercially available primary antibodies and is compatible with simultaneous fluorescent in situ hybridization (FISH) to detect RNA transcripts or DNA chromosomal abnormalities. Notably, the quality of post-INSIHGT traditional histological analyses, such as H&E and standard IHC, was not altered. We demonstrated a 3D mapping of over 20 markers in a 1 mm-thick tumor sample across seven INSIHGT cycles, and an atlas of multiple tumour samples with 3D IHC & H&E. The large datasets seamlessly integrates with single-cell segmentation and analysis workflows, yielding comprehensive maps that elucidate protein expression, cell morphology, spatial positioning, and potential cell-cell interactions. Conclusions: INSIHGT provides an unparalleled level of visualization and analytical detail concerning the spatial dynamics within the tumor microenvironment at a single-cell resolution. As a transformative next generation histopathology platform, it can uncover new structural and molecular details within clinical specimens, accelerating biomarker discovery and novel diagnostic assays development, thereby enriching the field of tumor biology and propelling the progress of personalized oncology treatments.

Recapitulating the tumor microenvironment in a dish, one cell type at a time

The tumor microenvironment harbors a variety of different cell types that differentially impact tumor biology. In this issue of Cell Reports Methods, Raffo-Romero etal. standardized and optimized 3D tumor organoids to model the interactions between tumor-associated macrophages and tumor cells invitro.

Oxygen-releasing nanodroplets relieve intratumoral hypoxia in head and neck cancer spheroids.

Hypoxia in solid tumors, including head and neck cancer (HNC), contributes to treatment resistance, aggressive phenotypes, and poor clinical outcomes. Perfluorocarbon nanodroplets have emerged as promising oxygen carriers to alleviate tumor hypoxia. However, a thorough characterization of the hypoxia alleviation effects in terms of sustenance of oxygenated environments have not been thoroughly studied. In this study, we developed and characterized perfluoropentane nanodroplets (PFP NDs) for co-delivery of oxygen and the photoactivatable drug or photosensitizer benzoporphyrin derivative (BPD) to hypoxic HNC spheroids. The PFP NDs exhibited excellent stability, efficient oxygen loading/release, and biocompatibility. Using 3D multicellular tumor spheroids of FaDu and SCC9 HNC cells, we demonstrated the ability of oxygenated PFP NDs to penetrate the hypoxic core and alleviate hypoxia, as evidenced by reduced fluorescence of a hypoxia-sensing reagent and downregulation of hypoxia-inducible factors HIF-1α and HIF-2α. BPD-loaded PFP NDs successfully delivered the photosensitizer into the spheroid core in a time-dependent manner. These findings highlight the potential of PFP NDs as a co-delivery platform to overcome hypoxia-mediated treatment resistance and improve therapy outcomes in HNC.

Visible and Red Light-Triggered Anticancer Profile of a Ferrocene-Re(I)-Tricarbonyl Conjugate: Experimental and Theoretical Studies.

We have red-shifted the light absorbance property of a Re(I)-tricarbonyl complex via distant conjugation of a ferrocene moiety and developed a novel complex ReFctp, [Re(Fctp)(CO)3Cl], where Fctp = 4'-ferrocenyl-2,2':6',2″-terpyridine. ReFctp showed green to red light absorption ability and blue emission, indicating its potential for photodynamic therapy (PDT) application. The conjugation of ferrocene introduced ferrocene-based transitions, which lie at a higher wavelength within the PDT therapeutic window. The time-dependent density functional theory and excited state calculations revealed an efficient intersystem crossing for ReFctp, which is helpful for PDT. ReFctp elicited both PDT type I and type II pathways for reactive oxygen species (ROS) generation and facilitated NADH (1,4-dihydro-nicotinamide adenine dinucleotide) oxidation upon exposure to visible light. Importantly, ReFctp showed effective penetration through the layers of clinically relevant 3D multicellular tumor spheroids and localized primarily in mitochondria (Pearson's correlation coefficient, PCC = 0.65) of A549 cancer cells. ReFctp produced more than 20 times higher phototoxicity (IC50 ∼1.5 μM) by inducing ROS generation and altering mitochondrial membrane potential in A549 cancer cells than the nonferrocene analogue Retp, [Re(CO)3(tp)Cl], where tp = 2,2':6',2″-terpyridine. ReFctp induced apoptotic mode of cell death with a notable photocytotoxicity index (PI, PI = IC50dark/IC50light) and selectivity index (SI, SI = normal cell's IC50dark/cancer cell's IC50light) in the range of 25-33.

Temozolomide resistance mechanisms: unveiling the role of translesion DNA polymerase kappa in glioblastoma spheroids in vitro.

Temozolomide (TMZ) is the leading therapeutic agent for combating Glioblastoma Multiforme (GBM). Nonetheless, the persistence of chemotherapy-resistant GBM cells remains an ongoing challenge, attributed to various factors, including the translesion synthesis (TLS) mechanism. TLS enables tumor cells to endure genomic damage by utilizing specialized DNA polymerases to bypass DNA lesions. Specifically, TLS polymerase Kappa (Polκ) has been implicated in facilitating DNA damage tolerance against TMZ-induced damage, contributing to a worse prognosis in GBM patients. To better understand the roles of Polκ in TMZ resistance, we conducted a comprehensive assessment of the cytotoxic, antiproliferative, antimetastatic, and genotoxic effects of TMZ on GBM (U251MG) wild-type (WTE) and TLS Polκ knockout (KO) cells, cultivated as three-dimensional (3D) tumor spheroids in vitro. Initial results revealed that TMZ: (i) induces reductions in GBM spheroid diameter (10-200 µM); (ii) demonstrates significant cytotoxicity (25-200 μM); (iii) exerts antiproliferative effects (≤25 μM) and promotes cell cycle arrest (G2/M phase) in Polκ KO spheroids when compared with WTE counterparts. Furthermore, Polκ KO spheroids exhibit elevated levels of cell death (Caspase 3/7) and display greater genotoxicity (53BP1) than WTE following TMZ exposure. Concerning antimetastatic effects, TMZ impedes invadopodia (3D invasion) more effectively in Polκ KO than in WTE spheroids. Collectively, the results suggest that TLS Polκ plays a vital role in the survival, cell death, genotoxicity, and metastatic potential of GBM spheroids in vitro when subjected to TMZ treatment. While the precise mechanisms underpinning this resistance remain elusive, TLS Polκ emerges as a potential therapeutic target for GBM patients.

Deep learning for risk stratification of thymoma pathological subtypes based on preoperative CT images

ObjectivesThis study aims to develop an innovative, deep model for thymoma risk stratification using preoperative CT images. Current algorithms predominantly focus on radiomic features or 2D deep features and require manual tumor segmentation by radiologists, limiting their practical applicability.MethodsThe deep model was trained and tested on a dataset comprising CT images from 147 patients (82 female; mean age, 54 years ± 10) who underwent surgical resection and received subsequent pathological confirmation. The eligible participants were divided into a training cohort (117 patients) and a testing cohort (30 patients) based on the CT scan time. The model consists of two stages: 3D tumor segmentation and risk stratification. The radiomic model and deep model (2D) were constructed for comparative analysis. Model performance was evaluated through dice coefficient, area under the curve (AUC), and accuracy.ResultsIn both the training and testing cohorts, the deep model demonstrated better performance in differentiating thymoma risk, boasting AUCs of 0.998 and 0.893 respectively. This was compared to the radiomic model (AUCs of 0.773 and 0.769) and deep model (2D) (AUCs of 0.981 and 0.760). Notably, the deep model was capable of simultaneously identifying lesions, segmenting the region of interest (ROI), and differentiating the risk of thymoma on arterial phase CT images. Its diagnostic prowess outperformed that of the baseline model.ConclusionsThe deep model has the potential to serve as an innovative decision-making tool, assisting on clinical prognosis evaluation and the discernment of suitable treatments for different thymoma pathological subtypes.Key Points• This study incorporated both tumor segmentation and risk stratification.• The deep model, using clinical and 3D deep features, effectively predicted thymoma risk.• The deep model improved AUCs by 16.1pt and 17.5pt compared to radiomic model and deep model (2D) respectively.

3D tumor spheroids promote activation, expansion, and anti-tumor effects of tumor-infiltrating lymphocytes in vitro

The adoptive immunotherapy mediated by tumor-infiltrating lymphocytes (TILs) has shown definite efficacy against various solid tumors. However, the inefficiency of the conventional method based on in vitro expansion of TILs fails to achieve the cell count and high tumor-killing activity required for therapeutic purposes. This study investigated the effect of 3D tumor spheroids on the activation and expansion of TILs in vitro, aiming to provide a novel approach for the expansion of TILs. We procured TILs and primary tumor cells from surgical samples of lung cancer patients and then compared the impacts of lung cancer cell line NCI-H1975 and primary lung cancer cells cultured under 2D and 3D conditions on the activation, expansion, and anti-tumor activity of TILs. Furthermore, we added the programmed cell death protein 1 (PD-1) antibody into the co-culture of primary tumor cells and TILs within a 3D environment to assess the effects of the antibody on TILs. The results showed that compared with 2D cultured tumor cells, the 3D cultured H1975 cells significantly enhanced the expansion of TILs, increasing the proportion of CD3+/CD8+ cells in TILs to 61.6%. The 3D primary tumor model also enhanced the proportion of CD3+/CD8+ cells in TILs (45.5%, 54.4%), induced apoptosis of tumor epithelial cells and decreased the overall tumor cells survival rate (16.7%) after co-culture. PD-1 antibodies further improved the in vitro expansion capacity of TILs mediated by 3D tumor spheroids, resulting in the proportions of 50.9% and 57.0% for CD3+/CD8+ cells and enhancing the antitumor activity significantly (reducing the overall tumor survival rate to 9.36%). In summary, the use of 3D tumor spheroids significantly promoted the expansion and improved the anti-tumor effect of TILs, and the use of the PD-1 antibody further promoted the expansion and tumor-killing effect of TILs.

Microbial β-Glucuronidase Hydrogel Beads Activate Chemotherapeutic Prodrug.

Bacteria-assisted chemotherapeutics have been highlighted as an alternative or supplementary approach to treating cancer. However, dynamic cancer-microbe studies at the in vitro level have remained a challenge to show the impact and effectiveness of microbial therapeutics due to the lack of relevant coculture models. Here, we demonstrate a hydrogel-based compartmentalized system for prodrug activation of a natural ingredient of licorice root, glycyrrhizin, by microbial β-glucuronidase (GUS). Hydrogel containment with Lactococcus lactis provides a favorable niche to encode GUS enzymes with excellent permeability and can serve as an independent ecosystem in the transformation of pro-apoptotic materials. Based on the confinement system of GUS expressing microbes, we quantitatively evaluated chemotherapeutic effects enhanced by microbial GUS enzyme in two dynamic coculture models in vitro (i.e., 2D monolayered cancer cells and 3D tumor spheroids). Our findings support the processes of prodrug conversion mediated by bacterial GUS enzyme which can enhance the therapeutic efficacy of a chemotherapy drug under dynamic coculture conditions. We expect our in vitro coculture platforms can be used for the evaluation of pharmacological properties and biological activity of xenobiotics as well as the potential impact of microbes on cancer therapeutics.

HCA-DAN: hierarchical class-aware domain adaptive network for gastric tumor segmentation in 3D CT images

BackgroundAccurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT images faces several challenges. The large variation of anisotropic spatial resolution limits the ability of 3D convolutional neural networks (CNNs) to learn features from different views. The background texture of gastric tumor is complex, and its size, shape and intensity distribution are highly variable, which makes it more difficult for deep learning methods to capture the boundary. In particular, while multi-center datasets increase sample size and representation ability, they suffer from inter-center heterogeneity.MethodsIn this study, we propose a new cross-center 3D tumor segmentation method named Hierarchical Class-Aware Domain Adaptive Network (HCA-DAN), which includes a new 3D neural network that efficiently bridges an Anisotropic neural network and a Transformer (AsTr) for extracting multi-scale context features from the CT images with anisotropic resolution, and a hierarchical class-aware domain alignment (HCADA) module for adaptively aligning multi-scale context features across two domains by integrating a class attention map with class-specific information. We evaluate the proposed method on an in-house CT image dataset collected from four medical centers and validate its segmentation performance in both in-center and cross-center test scenarios.ResultsOur baseline segmentation network (i.e., AsTr) achieves best results compared to other 3D segmentation models, with a mean dice similarity coefficient (DSC) of 59.26%, 55.97%, 48.83% and 67.28% in four in-center test tasks, and with a DSC of 56.42%, 55.94%, 46.54% and 60.62% in four cross-center test tasks. In addition, the proposed cross-center segmentation network (i.e., HCA-DAN) obtains excellent results compared to other unsupervised domain adaptation methods, with a DSC of 58.36%, 56.72%, 49.25%, and 62.20% in four cross-center test tasks.ConclusionsComprehensive experimental results demonstrate that the proposed method outperforms compared methods on this multi-center database and is promising for routine clinical workflows.

Nanostructured Biomaterials in 3D Tumor Tissue Engineering Scaffolds: Regenerative Medicine and Immunotherapies.

The evaluation of nanostructured biomaterials and medicines is associated with 2D cultures that provide insight into biological mechanisms at the molecular level, while critical aspects of the tumor microenvironment (TME) are provided by the study of animal xenograft models. More realistic models that can histologically reproduce human tumors are provided by tissue engineering methods of co-culturing cells of varied phenotypes to provide 3D tumor spheroids that recapitulate the dynamic TME in 3D matrices. The novel approaches of creating 3D tumor models are combined with tumor tissue engineering (TTE) scaffolds including hydrogels, bioprinted materials, decellularized tissues, fibrous and nanostructured matrices. This review focuses on the use of nanostructured materials in cancer therapy and regeneration, and the development of realistic models for studying TME molecular and immune characteristics. Tissue regeneration is an important aspect of TTE scaffolds used for restoring the normal function of the tissues, while providing cancer treatment. Thus, this article reports recent advancements in the development of 3D TTE models for antitumor drug screening, studying tumor metastasis, and tissue regeneration. Also, this review identifies the significant opportunities of using 3D TTE scaffolds in the evaluation of the immunological mechanisms and processes involved in the application of immunotherapies.

Assessment of thermal damage for plasmonic photothermal therapy of subsurface tumors.

Plasmonic photothermal therapy (PPTT) involves the use of nanoparticles and near-infrared radiation to attain a temperature above 50°C within the tumor for its thermal damage. PPTT is largely explored for superficial tumors, and its potential to treat deeper subsurface tumors is dealt feebly, requiring the assessment of thermal damage for such tumors. In this paper, the extent of thermal damage is numerically analyzed for PPTT of invasive ductal carcinoma (IDC) situated at 3-9mm depths. The developed numerical model is validated with suitable tissue-tumor mimicking phantoms. Tumor (IDC) embedded with gold nanorods (GNRs) is subjected to broadband near-infrared radiation. The effect of various GNRs concentrations and their spatial distributions [viz. uniform distribution, intravenous delivery (peripheral distribution) and intratumoral delivery (localized distribution)] are investigated for thermal damage for subsurface tumors situated at various depths. Results show that lower GNRs concentrations lead to more uniform internal heat generation, eventually resulting in uniform temperature rise. Also, the peripheral distribution of nanoparticles provides a more uniform spatial temperature rise within the tumor. Overall, it is concluded that PPTT has potential to induce thermal damage for subsurface tumors, at depths of upto 9mm, by proper choice of nanoparticle distribution, dose/concentration and irradiation parameters based on the tumor location. Moreover, intravenous administration of nanoparticles seems a good choice for shallower tumors, while for deeper tumors, uniform distribution is required to attain the necessary thermal damage. In the future, the algorithm may be extended further, involving 3D patient-specific tumors and through mice model-based experiments.

Two-Photon Photodegradation of E3 Ubiquitin Ligase Cereblon by a Ru(II) Complex: Inducing Ferroptosis in Cisplatin-Resistant Tumor Cells.

Using photodynamic therapy (PDT) to trigger nonconventional cell death pathways has provided a new scheme for highly efficient and non-side effects to drug-resistant cancer therapies. Nonetheless, the unclear targets of available photosensitizers leave the manner of PDT-induced tumor cell death relatively unpredictable. Herein, we developed a novel Ru(II)-based photosensitizer, Ru-Poma. Possessing the E3 ubiquitin ligase CRBN-targeting moiety and high singlet oxygen yield of 0.96, Ru-Poma was demonstrated to specifically photodegrade endogenous CRBN, increase lipid peroxide, downregulate GPX4 and GAPDH expression, and consequently induce ferroptosis in cisplatin-resistant cancerous cells. Furthermore, with the deep penetration of two-photon excitation, Ru-Poma achieved drug-resistant circumvention in a 3D tumor cell model. Thus, we describe the first sample of the CRBN-targeting Ru(II) complex active in PDT.

Protein phosphatase 6 activates NF-κB to confer sensitivity to MAPK pathway inhibitors in KRAS- and BRAF-mutant cancer cells.

The Ras-mitogen-activated protein kinase (MAPK) pathway is a major target for cancer treatment. To better understand the genetic pathways that modulate cancer cell sensitivity to MAPK pathway inhibitors, we performed a CRISPR knockout screen with MAPK pathway inhibitors on a colorectal cancer (CRC) cell line carrying mutant KRAS. Genetic deletion of the catalytic subunit of protein phosphatase 6 (PP6), encoded by PPP6C, rendered KRAS- and BRAF-mutant CRC and BRAF-mutant melanoma cells more resistant to these inhibitors. In the absence of MAPK pathway inhibition, PPP6C deletion in CRC cells decreased cell proliferation in two-dimensional (2D) adherent cultures but accelerated the growth of tumor spheroids in 3D culture and tumor xenografts in vivo. PPP6C deletion enhanced the activation of nuclear factor κB (NF-κB) signaling in CRC and melanoma cells and circumvented the cell cycle arrest and decreased cyclin D1 abundance induced by MAPK pathway blockade in CRC cells. Inhibiting NF-κB activity by genetic and pharmacological means restored the sensitivity of PPP6C-deficient cells to MAPK pathway inhibition in CRC and melanoma cells in vitro and in CRC cells in vivo. Furthermore, a R264 point mutation in PPP6C conferred loss of function in CRC cells, phenocopying the enhanced NF-κB activation and resistance to MAPK pathway inhibition observed for PPP6C deletion. These findings demonstrate that PP6 constrains the growth of KRAS- and BRAF-mutant cancer cells, implicates the PP6-NF-κB axis as a modulator of MAPK pathway output, and presents a rationale for cotargeting the NF-κB pathway in PPP6C-mutant cancer cells.

Chondrosarcoma evaluation using hematein-based x-ray staining and high-resolution 3D micro-CT: a feasibility study

BackgroundChondrosarcomas are rare malignant bone tumors diagnosed by analyzing radiological images and histology of tissue biopsies and evaluating features such as matrix calcification, cortical destruction, trabecular penetration, and tumor cell entrapment.MethodsWe retrospectively analyzed 16 cartilaginous tumor tissue samples from three patients (51-, 54-, and 70-year-old) diagnosed with a dedifferentiated chondrosarcoma at the femur, a moderately differentiated chondrosarcoma in the pelvis, and a predominantly moderately differentiated chondrosarcoma at the scapula, respectively. We combined a hematein-based x-ray staining with high-resolution three-dimensional (3D) microscopic x-ray computed tomography (micro-CT) for nondestructive 3D tumor assessment and tumor margin evaluation.ResultsWe detected trabecular entrapment on 3D micro-CT images and followed bone destruction throughout the volume. In addition to staining cell nuclei, hematein-based staining also improved the visualization of the tumor matrix, allowing for the distinction between the tumor and the bone marrow cavity. The hematein-based staining did not interfere with further conventional histology. There was a 5.97 ± 7.17% difference between the relative tumor area measured using micro-CT and histopathology (p = 0.806) (Pearson correlation coefficient r = 0.92, p = 0.009). Signal intensity in the tumor matrix (4.85 ± 2.94) was significantly higher in the stained samples compared to the unstained counterparts (1.92 ± 0.11, p = 0.002).ConclusionsUsing nondestructive 3D micro-CT, the simultaneous visualization of radiological and histopathological features is feasible.Relevance statement3D micro-CT data supports modern radiological and histopathological investigations of human bone tumor specimens. It has the potential for being an integrative part of clinical preoperative diagnostics.Key points• Matrix calcifications are a relevant diagnostic feature of bone tumors.• Micro-CT detects all clinically diagnostic relevant features of x-ray-stained chondrosarcoma.• Micro-CT has the potential to be an integrative part of clinical diagnostics.Graphical

Rationally designed β-cyclodextrin-crosslinked polyacrylamide hydrogels for cell spheroid formation and 3D tumor model construction

In vitro tumor models are essential for understanding tumor behavior and evaluating tumor biological properties. Hydrogels that can mimic the tumor extracellular matrix have become popular for creating 3D in vitro tumor models. However, designing biocompatible hydrogels with appropriate chemical and physical properties for constructing tumor models is still a challenge. In this study, we synthesized a series of β-cyclodextrin (β-CD)-crosslinked polyacrylamide hydrogels with different β-CD densities and mechanical properties and evaluated their potential for use in 3D in vitro tumor model construction, including cell capture and spheroid formation. By utilizing a combination of β-CD-methacrylate (CD-MA) and a small amount of N,N′-methylene bisacrylamide (BIS) as hydrogel crosslinkers and optimizing the CD-MA/BIS ratio, the hydrogels performed excellently for tumor cell 3D culture and spheroid formation. Notably, when we co-cultured L929 fibroblasts with HeLa tumor cells on the hydrogel surface, co-cultured spheroids were formed, showing that the hydrogel can mimic the complexity of the tumor extracellular matrix. This comprehensive investigation of the relationship between hydrogel mechanical properties and biocompatibility provides important insights for hydrogel-based in vitro tumor modeling and advances our understanding of the mechanisms underlying tumor growth and progression.

Zebrafish Avatars: Toward Functional Precision Medicine in Low-Grade Serous Ovarian Cancer.

Ovarian cancer (OC) is an umbrella term for cancerous malignancies affecting the ovaries, yet treatment options for all subtypes are predominantly derived from high-grade serous ovarian cancer, the largest subgroup. The concept of "functional precision medicine" involves gaining personalized insights on therapy choice, based on direct exposure of patient tissues to drugs. This especially holds promise for rare subtypes like low-grade serous ovarian cancer (LGSOC). This study aims to establish an in vivo model for LGSOC using zebrafish embryos, comparing treatment responses previously observed in mouse PDX models, cell lines and 3D tumor models. To address this goal, a well-characterized patient-derived LGSOC cell line with the KRAS mutation c.35 G>T (p.(Gly12Val)) was used. Fluorescently labeled tumor cells were injected into the perivitelline space of 2 days' post-fertilization zebrafish embryos. At 1 day post-injection, xenografts were assessed for tumor size, followed by random allocation into treatment groups with trametinib, luminespib and trametinib + luminespib. Subsequently, xenografts were euthanized and analyzed for apoptosis and proliferation by confocal microscopy. Tumor cells formed compact tumor masses (n = 84) in vivo, with clear Ki67 staining, indicating proliferation. Zebrafish xenografts exhibited sensitivity to trametinib and luminespib, individually or combined, within a two-week period, establishing them as a rapid and complementary tool to existing in vitro and in vivo models for evaluating targeted therapies in LGSOC.

The influence of spheroid maturity on fusion dynamics and micro-tissue assembly in 3D tumor models

Three-dimensional (3D) cell culture has been used in many fields of biology because of its unique advantages. As a representative of the 3D systems, 3D spheroids are used as building blocks for tissue construction. Larger tumor aggregates can be assembled by manipulating or stacking the tumor spheroids. The motivation of this study is to investigate the behavior of the cells distributed at different locations of the spheroids in the fusion process and the mechanism behind it. To this aim, spheroids with varying grades of maturity or age were generated for fusion to assemble micro-tumor tissues. The dynamics of the fusion process, the motility of the cells distributed in different heterogeneous architecture sites, and their reactive oxygen species profiles were studied. We found that the larger the spheroid necrotic core, the slower the fusion rate of the spheroid. The cells that move were mainly distributed on the spheroid’s surface during fusion. In addition to dense microfilament distribution and low microtubule content, the reactive oxygen content was high in the fusion site, while the non-fusion site was the opposite. Last, multi-spheroids with different maturities were fused to complex micro-tissues to mimic solid tumors and evaluate Doxorubicin’s anti-tumor efficacy.