Patient-Derived Tumor Organoids for Drug Repositioning in Cancer Care: A Promising Approach in the Era of Tailored Treatment

Protocol for high throughput 3D drug screening of patient derived melanoma and renal cell carcinoma

High Throughput Screening (HTS) with 3D cell models is possible thanks to the recent progress and development in 3D cell culture technologies. Results from multiple studies have demonstrated different drug responses between 2D and 3D cell culture. It is now widely accepted that 3D cell models more accurately represent the physiologic conditions of tumors over 2D cell models. However, there is still a need for more accurate tests that are scalable and better imitate the complex conditions in living tissues. Here, we describe ultrahigh throughput 3D methods of drug response profiling in patient derived primary tumors including melanoma as well as renal cell carcinoma that were tested against the NCI oncologic set of FDA approved drugs. We also tested their autologous patient derived cancer associated fibroblasts, varied the in-vitro conditions using matrix vs matrix free methods and completed this in both 3D vs 2D rendered cancer cells. The result indicates a heterologous response to the drugs based on their genetic background, but not on their maintenance condition. Here, we present the methods and supporting results of the HTS efforts using these 3D of organoids derived from patients. This demonstrated the possibility of using patient derived 3D cells for HTS and expands on our screening capabilities for testing other types of cancer using clinically approved anti-cancer agents to find drugs for potential off label use.

A systematic review of patient-derived tumor organoids generation from malignant effusions

This review assesses the possibility of utilizing malignant effusions (MEs) for generating patient-derived tumor organoids (PDTOs). Obtained through minimally invasive procedures MEs broaden the spectrum of organoid sources beyond resection specimens and tissue biopsies. A systematic search yielded 11 articles, detailing the successful generation of 190 ME-PDTOs (122 pleural effusions, 54 malignant ascites). Success rates ranged from 33% to 100%, with an average of 84% and median of 92%. A broad and easily applicable array of techniques can be employed, encompassing diverse collection methods, variable centrifugation speeds, and the inclusion of approaches like RBC lysis buffer or centrifuged ME supernatants supplementation, enhancing the versatility and accessibility of the methodology. ME-PDTOs were found to recapitulate primary tumor characteristics and were primarily used for drug screening applications. Thus, MEs are a reliable source for developing PDTOs, emphasizing the need for further research to maximize their potential, validate usage, and refine culturing processes.

Tumor Organoids: The Era of Personalized Medicine

The strategies of future medicine are aimed to modernize and integrate quality approaches including early molecular-genetic profiling, identification of new therapeutic targets and adapting design for clinical trials, personalized drug screening (PDS) to help predict and individualize patient treatment regimens. In the past decade, organoid models have emerged as an innovative in vitro platform with the potential to realize the concept of patient-centered medicine. Organoids are spatially restricted three-dimensional clusters of cells ex vivo that self-organize into complex functional structures through genetically programmed determination, which is crucial for reconstructing the architecture of the primary tissue and organs. Currently, there are several strategies to create three-dimensional (3D) tumor systems using (i) surgically resected patient tissue (PDTOs, patient-derived tumor organoids) or (ii) single tumor cells circulating in the patient's blood. Successful application of 3D tumor models obtained by co-culturing autologous tumor organoids (PDTOs) and peripheral blood lymphocytes have been demonstrated in a number of studies. Such models simulate a 3D tumor architecture in vivo and contain all cell types characteristic of this tissue, including immune system cells and stem cells. Components of the tumor microenvironment, such as fibroblasts and immune system cells, affect tumor growth and its drug resistance. In this review, we analyzed the evolution of tumor models from two-dimensional (2D) cell cultures and laboratory animals to 3D tissue-specific tumor organoids, their significance in identifying mechanisms of antitumor response and drug resistance, and use of these models in drug screening and development of precision methods in cancer treatment.

Antiproliferative Activity of Piceamycin by Regulating Alpha-Actinin-4 in Gemcitabine-Resistant Pancreatic Cancer Cells

Although gemcitabine-based regimens are widely used as an effective treatment for pancreatic cancer, acquired resistance to gemcitabine has become an increasingly common problem. Therefore, a novel therapeutic strategy to treat gemcitabine-resistant pancreatic cancer is urgently required. Piceamycin has been reported to exhibit antiproliferative activity against various cancer cells; however, its underlying molecular mechanism for anticancer activity in pancreatic cancer cells remains unexplored. Therefore, the present study evaluated the antiproliferation activity of piceamycin in a gemcitabine-resistant pancreatic cancer cell line and patient-derived pancreatic cancer organoids. Piceamycin effectively inhibited the proliferation and suppressed the expression of alpha-actinin-4, a gene that plays a pivotal role in tumorigenesis and metastasis of various cancers, in gemcitabine-resistant cells. Long-term exposure to piceamycin induced cell cycle arrest at the G0/G1 phase and caused apoptosis. Piceamycin also inhibited the invasion and migration of gemcitabine-resistant cells by modulating focal adhesion and epithelial-mesenchymal transition biomarkers. Moreover, the combination of piceamycin and gemcitabine exhibited a synergistic antiproliferative activity in gemcitabine-resistant cells. Piceamycin also effectively inhibited patient-derived pancreatic cancer organoid growth and induced apoptosis in the organoids. Taken together, these findings demonstrate that piceamycin may be an effective agent for overcoming gemcitabine resistance in pancreatic cancer.

Challenges and Prospects of Patient-Derived Xenografts for Cancer Research

We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.

Patient-Derived Organoids as a Promising Tool for Multimodal Management of Sarcomas

The management of sarcomas, a diverse group of cancers arising from connective tissues, presents significant challenges due to their heterogeneity and limited treatment options. Patient-derived sarcoma organoids (PDSOs) have emerged as a promising tool in the multimodal management of sarcomas, offering unprecedented opportunities for personalized medicine and improved treatment strategies. This review aims to explore the potential of PDSOs as a promising tool for multimodal management of sarcomas. We discuss the establishment and characterization of PDSOs, which realistically recapitulate the complexity and heterogeneity of the original tumor, providing a platform for genetic and molecular fidelity, histological resemblance, and functional characterization. Additionally, we discuss the applications of PDSOs in pathological and genetic evaluation, treatment screening and development, and personalized multimodal management. One significant advancement of PDSOs lies in their ability to guide personalized treatment decisions, enabling clinicians to assess the response and efficacy of different therapies in a patient-specific manner. Through continued research and development, PDSOs hold the potential to revolutionize sarcoma management and drive advancements in personalized medicine, biomarker discovery, preclinical modeling, and therapy optimization. The integration of PDSOs into clinical practice can ultimately improve patient outcomes and significantly impact the field of sarcoma treatment.

Cutoff value of IC50 for drug sensitivity in patient-derived tumor organoids in colorectal cancer

Patient-derived tumor organoids (PDTOs) have the potential to be used to predict the patient response to chemotherapy. However, the cutoff value of the half-maximal inhibition concentration (IC₅₀) for PDTO drug sensitivity has not been validated with clinical cohort data. We established PDTOs and performed a drug test in 277 samples from 242 CRC patients who received FOLFOX or XELOX chemotherapy. After follow-up and comparison of the PDTO drug test and final clinical outcome results, the optimal IC₅₀ cutoff value for PDTO drug sensitivity was 43.26 μmol/L. This PDTO drug test-defined cutoff value could predict patient response with 75.36% sensitivity, 74.68% specificity, and 75% accuracy. Moreover, this value distinguished groups of patients with significant differences in survival benefit. Our study is the first to define the IC₅₀ cutoff value for the PDTO drug test to effectively distinguish CRC patients with chemosensitivity or nonsensitivity and predict survival benefits.

Antiproliferative Activity of Krukovine by Regulating Transmembrane Protein 139 (TMEM139) in Oxaliplatin-Resistant Pancreatic Cancer Cells

Krukovine (KV) is an alkaloid isolated from the bark of Abuta grandifolia (Mart.) Sandw. (Menispermaceae) with anticancer potential in some cancers with KRAS mutations. In this study, we explored the anticancer efficacy and mechanism of KV in oxaliplatin-resistant pancreatic cancer cells and patient-derived pancreatic cancer organoids (PDPCOs) with KRAS mutation. After treatment with KV, mRNA and protein levels were determined by RNA-seq and Western blotting, respectively. Cell proliferation, migration, and invasion were measured by MTT, scratch wound healing assay, and transwell analysis, respectively. Patient-derived pancreatic cancer organoids (PDPCOs) with KRAS mutations were treated with KV, oxaliplatin (OXA), and a combination of KV and OXA. KV suppresses tumor progression via the downregulation of the Erk-RPS6K-TMEM139 and PI3K-Akt-mTOR pathways in oxaliplatin-resistant AsPC-1 cells. Furthermore, KV showed an antiproliferative effect in PDPCOs, and the combination of OXA and KV inhibited PDPCO growth more effectively than either drug alone.

Organoids and organs-on-chips: insights into predicting the efficacy of systemic treatment in colorectal cancer

Cancer heterogeneity has posed a great challenge to traditional cancer treatment, with the reappearance of cancer heterogeneity of inter and intra patients being especially critical. Based on this, personalized therapy has emerged as significant research focus in recent and even future years. Cancer-related therapeutic models are developing, including cell lines, patient-derived xenografts, organoids, etc. Organoids are three-dimensional in vitro models emerged in the past dozen years and are able to reproduce the cellular and molecular composition of the original tumor. These advantages demonstrate the great potential for patient-derived organoids to develop personalized anticancer therapies, including preclinical drug screening and the prediction of patient treatment response. The impact of microenvironment on cancer treatment cannot be underestimated, and the remodeling of microenvironment also allows organoids to interact with other technologies, among which organs-on-chips is a representative one. This review highlights the use of organoids and organs-on-chips as complementary reference tools in treating colorectal cancer from the perspective of clinical efficacy predictability. We also discuss the limitations of both techniques and how they complement each other well.

Addressing Modern Diagnostic Pathology for Patient-Derived Soft Tissue Sarcosphere Models in the Era of Functional Precision Oncology

Responses to therapy often cannot be exclusively predicted by molecular markers, thus evidencing a critical need to develop tools for better patient selection based on relations between tumor phenotype and genotype. Patient-derived cell models could help to better refine patient stratification procedures and lead to improved clinical management. So far, such ex vivo cell models have been used for addressing basic research questions and in preclinical studies. As they now enter the era of functional precision oncology, it is of utmost importance that they meet quality standards to fully represent the molecular and phenotypical architecture of patients' tumors. Well-characterized ex vivo models are imperative for rare cancer types with high patient heterogeneity and unknown driver mutations. Soft tissue sarcomas account for a very rare, heterogeneous group of malignancies that are challenging from a diagnostic standpoint and difficult to treat in a metastatic setting because of chemotherapy resistance and a lack of targeted treatment options. Functional drug screening in patient-derived cancer cell models is a more recent approach for discovering novel therapeutic candidate drugs. However, because of the rarity and heterogeneity of soft tissue sarcomas, the number of well-established and characterized sarcoma cell models is extremely limited. Within our hospital-based platform we establish high-fidelity patient-derived ex vivo cancer models from solid tumors for enabling functional precision oncology and addressing research questions to overcome this problem. We here present 5 novel, well-characterized, complex-karyotype ex vivo soft tissue sarcosphere models, which are effective tools to study molecular pathogenesis and identify the novel drug sensitivities of these genetically complex diseases. We addressed the quality standards that should be generally considered for the characterization of such ex vivo models. More broadly, we suggest a scalable platform to provide high-fidelity ex vivo models to the scientific community and enable functional precision oncology.

3D dynamic cultures of HGSOC organoids to model innovative and standard therapies

High-grade serous ovarian cancer (HGSOC) needs new technologies for improving cancer diagnosis and therapy. It is a fatal disease with few options for the patients. In this context, dynamic culture systems coupling with patient-derived cancer 3D microstructures could offer a new opportunity for exploring novel therapeutic approaches. In this study, we optimized a passive microfluidic platform with 3D cancer organoids, which allows a standardized approach among different patients, a minimum requirement of samples, multiple interrogations of biological events, and a rapid response. The passive flow was optimized to improve the growth of cancer organoids, avoiding the disruption of the extracellular matrix (ECM). Under optimized conditions of the OrganoFlow (tilting angle of 15° and an interval of rocking every 8 min), the cancer organoids grow faster than when they are in static conditions and the number of dead cells is reduced over time. To calculate the IC ₅₀ values of standard chemotherapeutic drugs (carboplatin, paclitaxel, and doxorubicin) and targeted drugs (ATRA), different approaches were utilized. Resazurin staining, ATP-based assay, and DAPI/PI colocalization assays were compared, and the IC ₅₀ values were calculated. The results showed that in the passive flow, the IC ₅₀ values are lower than in static conditions. FITC-labeled paclitaxel shows a better penetration of ECM under passive flow than in static conditions, and cancer organoids start to die after 48 h instead of 96 h, respectively. Cancer organoids are the last frontiers for ex vivo testing of drugs that replicate the response of patients in the clinic. For this study, organoids derived from ascites or tissues of patients with Ovarian Cancer have been used. In conclusion, it was possible to develop a protocol for organoid cultures in a passive microfluidic platform with a higher growth rate, faster drug response, and better penetration of drugs into ECM, maintaining the samples' vitals and collecting the data on the same plate for up to 16 drugs.

Patient-derived organoids for personalized gallbladder cancer modelling and drug screening

BACKGROUND

Gallbladder carcinoma (GBC) is a relatively rare but highly aggressive cancer with late clinical detection and a poor prognosis. However, the lack of models with features consistent with human gallbladder tumours has hindered progress in pathogenic mechanisms and therapies.

METHODS

We established organoid lines derived from human GBC as well as normal gallbladder and benign gallbladder adenoma (GBA) tissues. The histopathology signatures of organoid cultures were identified by H&E staining, immunohistochemistry and immunofluorescence. The genetic and transcriptional features of organoids were analysed by whole-exome sequencing and RNA sequencing. A set of compounds targeting the most active signalling pathways in GBCs were screened for their ability to suppress GBC organoids. The antitumour effects of candidate compounds, CUDC-101 and CUDC-907, were evaluated in vitro and in vivo.

RESULTS

The established organoids were cultured stably for more than 6 months and closely recapitulated the histopathology, genetic and transcriptional features, and intratumour heterogeneity of the primary tissues at the single-cell level. Notably, expression profiling analysis of the organoids revealed a set of genes that varied across the three subtypes and thus may participate in the malignant progression of gallbladder diseases. More importantly, we found that the dual PI3K/HDAC inhibitor CUDC-907 significantly restrained the growth of various GBC organoids with minimal toxicity to normal gallbladder organoids.

CONCLUSIONS

Patient-derived organoids are potentially a useful platform to explore molecular pathogenesis of gallbladder tumours and discover personalized drugs.

Grouped-seq for integrated phenotypic and transcriptomic screening of patient-derived tumor organoids

Patient-derived tumor organoids (PDOs) have emerged as a reliable in vitro model for drug discovery. However, RNA sequencing-based analysis of PDOs treated with drugs has not been realized in a high-throughput format due to the limited quantity of organoids. Here, we translated a newly developed pooled RNA-seq methodology onto a superhydrophobic microwell array chip to realize an assay of genome-wide RNA output unified with phenotypic data (Grouped-seq). Over 10-fold reduction of sample and reagent consumption together with a new ligation-based barcode synthesis method lowers the cost to ∼$2 per RNA-seq sample. Patient-derived colorectal cancer (CRC) organoids with a number of 10 organoids per microwell were treated with four anti-CRC drugs across eight doses and analyzed by the Grouped-seq. Using a phenotype-assisted pathway enrichment analysis (PAPEA) method, the mechanism of actions of the drugs were correctly derived, illustrating the great potential of Grouped-seq for pharmacological screening with tumor organoids.

Prognostic and immune infiltration signatures of proteasome 26S subunit, non-ATPase (PSMD) family genes in breast cancer patients

The complexity of breast cancer includes many interacting biological processes that make it difficult to find appropriate therapeutic treatments. Therefore, identifying potential diagnostic and prognostic biomarkers is urgently needed. Previous studies demonstrated that 26S proteasome delta subunit, non-ATPase (PSMD) family members significantly contribute to the degradation of damaged, misfolded, abnormal, and foreign proteins. However, transcriptional expressions of PSMD family genes in breast cancer still remain largely unexplored. Consequently, we used a holistic bioinformatics approach to explore PSMD genes involved in breast cancer patients by integrating several high-throughput databases, including The Cancer Genome Atlas (TCGA), cBioPortal, Oncomine, and Kaplan-Meier plotter. These data demonstrated that PSMD1, PSMD2, PSMD3, PSMD7, PSMD10, PSMD12, and PSMD14 were expressed at significantly higher levels in breast cancer tissue compared to normal tissues. Notably, the increased expressions of PSMD family genes were correlated with poor prognoses of breast cancer patients, which suggests their roles in tumorigenesis. Meanwhile, network and pathway analyses also indicated that PSMD family genes were positively correlated with ubiquinone metabolism, immune system, and cell-cycle regulatory pathways. Collectively, this study revealed that PSMD family members are potential prognostic biomarkers for breast cancer progression and possible promising clinical therapeutic targets.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

NGAL as a Potential Target in Tumor Microenvironment

The signaling network between cancer and stromal cells plays a crucial role in tumor microenvironment. The fate of tumor progression mainly depends on the huge amount of information that these cell populations exchange from the onset of neoplastic transformation. Interfering with such signaling has been producing exciting results in cancer therapy: just think of anti-PD-1/anti-PD-L1/anti-CTLA-4 antibodies that, acting as immune checkpoint inhibitors, interrupt the inhibitory signaling exerted by cancer cells on immune cells or the CAR-T technology that fosters the reactivation of anti-tumoral immunity in a restricted group of leukemias and lymphomas. Nevertheless, many types of cancers, in particular solid tumors, are still refractory to these treatments, so the identification of novel molecular targets in tumor secretome would benefit from implementation of current anti-cancer therapeutical strategies. Neutrophil Gelatinase-Associated Lipocalin (NGAL) is a secreted protein abundantly expressed in the secretome of various human tumors. It represents a promising target for the multiple roles that are played inside cancer and stromal cells, and also overall in their cross-talk. The review focuses on the different roles of NGAL in tumor microenvironment and in cancer senescence-associated secretory phenotype (SASP), highlighting the most crucial functions that could be eventually targetable in cancer therapy.

Potential Prognostic Biomarkers of NIMA (Never in Mitosis, Gene A)-Related Kinase (NEK) Family Members in Breast Cancer

Breast cancer remains the most common malignant cancer in women, with a staggering incidence of two million cases annually worldwide; therefore, it is crucial to explore novel biomarkers to assess the diagnosis and prognosis of breast cancer patients. NIMA-related kinase (NEK) protein kinase contains 11 family members named NEK1-NEK11, which were discovered from Aspergillus Nidulans; however, the role of NEK family genes for tumor development remains unclear and requires additional study. In the present study, we investigate the prognosis relationships of NEK family genes for breast cancer development, as well as the gene expression signature via the bioinformatics approach. The results of several integrative analyses revealed that most of the NEK family genes are overexpressed in breast cancer. Among these family genes, NEK2/6/8 overexpression had poor prognostic significance in distant metastasis-free survival (DMFS) in breast cancer patients. Meanwhile, NEK2/6 had the highest level of DNA methylation, and the functional enrichment analysis from MetaCore and Gene Set Enrichment Analysis (GSEA) suggested that NEK2 was associated with the cell cycle, G2M checkpoint, DNA repair, E2F, MYC, MTORC1, and interferon-related signaling. Moreover, Tumor Immune Estimation Resource (TIMER) results showed that the transcriptional levels of NEK2 were positively correlated with immune infiltration of B cells and CD4+ T Cell. Collectively, the current study indicated that NEK family genes, especially NEK2 which is involved in immune infiltration, and may serve as prognosis biomarkers for breast cancer progression.

Human three-dimensional dental pulp organoid model for toxicity screening of dental materials on dental pulp cells and tissue

AIM

To establish a 3D model for screening the biocompatibility of dental materials/drugs on dental pulp cells and tissue.

METHODOLOGY

Human dental pulp cells (hDPC) and endothelial cells (EC) were mixed with or without human dental pulp derived extracellular matrix (hDP-ECM) according to several protocols and cultured in 3D plates to fabricate 3D organoids. Cell viability and proliferation in organoids were evaluated using Live/Dead cell viability assay and ATPase assay. Organoids were fixed, cut and stained with a H&E staining kit. The expressions of DSPP, DMP-1, CD31, vWF and COL1A in 3D organoids were evaluated using immunofluorescence. To assess the feasibility of 3D organoids on drug/material toxicity screening, the organoids were treated with lipopolysaccharides (LPS) or iRoot BP. Then, cell viability and apoptosis were assessed. The expressions of IL-6, TNF-α, and IL-1β were compared in LPS-treated and non-treated organoids. Alizarin Red S staining was used to evaluate calcium deposit formation in organoids. Data were analysed using one-way anova followed by Tukey's post hoc comparison.

RESULTS

The 3D spheres/organoids were formed at day 1 or day 2. Cells in 3D organoids maintained a high viability rate and low proliferation activity. The level of CD31 increased significantly (p < .05) when EC were added to coculture with hDPC. The expressions of odontogenesis-associated proteins (DSPP, COL1A) upregulated (p < .05) with the addition of hDP-ECM. Level of IL-6 expression and rates of dead and apoptotic cells in 3D organoids were increased significantly (p < .05) in response to LPS. Calcium deposit formation was observed in iRoot BP-treated organoids.

CONCLUSIONS

Coculture of hDPC and EC in the presence of hDP-ECM formed functional dental pulp organoids. The experimental model provides an alternative tool for toxicity screening of dental pulp capping agents and dental pulp regeneration research.

Cascade Deep Forest With Heterogeneous Similarity Measures for Drug-Target Interaction Prediction

Drug repositioning is a method of systematically identifying potential molecular targets that known drugs may act on. Compared with traditional methods, drug repositioning has been extensively studied due to the development of multi-omics technology and system biology methods. Because of its biological network properties, it is possible to apply machine learning related algorithms for prediction. Based on various heterogeneous network model, this paper proposes a method named THNCDF for predicting drug-target interactions. Various heterogeneous networks are integrated to build a tripartite network, and similarity calculation methods are used to obtain similarity matrix. Then, the cascade deep forest method is used to make prediction. Results indicate that THNCDF outperforms the previously reported methods based on the 10-fold cross-validation on the benchmark data sets proposed by Y. Yamanishi. The area under Precision Recall curve (AUPR) value on the Enzyme, GPCR, Ion Channel, and Nuclear Receptor data sets is 0.988, 0.980, 0.938, and 0.906 separately. The experimental results well illustrate the feasibility of this method.

Accelerating vein-to-vein cell therapy workflows with new bioanalytical strategies

Cell therapies represent a new era of treatment modalities for cancer. Through agile bioprocessing and bioengineering, patient-derived T-cells can be directed toward cancer biomarkers to impart a more robust and targeted immune response. In order to avoid delays in critical treatment timeframes, new bioanalytical tools are needed to accelerate, streamline, and maximize the throughput of T-cell bioprocessing. This review offers a survey of recent biotechnological advances supporting enhanced and expedited biomanufacturing workflows for autologous and allogeneic cell therapies, ranging from novel genetic engineering techniques and cell sorting platforms to stem cells and tumor organoid models. Collectively, these methods can increase the clinical impact of cancer therapeutics by improving the specificity, efficacy, and timely delivery of cell-based products.

Experimental Models of Hepatocellular Carcinoma-A Preclinical Perspective

Hepatocellular carcinoma (HCC), the most frequent form of primary liver carcinoma, is a heterogenous and complex tumor type with increased incidence, poor prognosis, and high mortality. The actual therapeutic arsenal is narrow and poorly effective, rendering this disease a global health concern. Although considerable progress has been made in terms of understanding the pathogenesis, molecular mechanisms, genetics, and therapeutical approaches, several facets of human HCC remain undiscovered. A valuable and prompt approach to acquire further knowledge about the unrevealed aspects of HCC and novel therapeutic candidates is represented by the application of experimental models. Experimental models (in vivo and in vitro 2D and 3D models) are considered reliable tools to gather data for clinical usability. This review offers an overview of the currently available preclinical models frequently applied for the study of hepatocellular carcinoma in terms of initiation, development, and progression, as well as for the discovery of efficient treatments, highlighting the advantages and the limitations of each model. Furthermore, we also focus on the role played by computational studies (in silico models and artificial intelligence-based prediction models) as promising novel tools in liver cancer research.

The Use of Antihypertensive Drugs as Coadjuvant Therapy in Cancer

Cancer is a complex group of diseases that constitute the second largest cause of mortality worldwide. The development of new drugs for treating this disease is a long and costly process, from the discovery of the molecule through testing in phase III clinical trials, a process during which most candidate molecules fail. The use of drugs currently employed for the management of other diseases (drug repurposing) represents an alternative for developing new medical treatments. Repurposing existing drugs is, in principle, cheaper and faster than developing new drugs. Antihypertensive drugs, primarily belonging to the pharmacological categories of angiotensin-converting enzyme inhibitors, angiotensin II receptors, direct aldosterone antagonists, β-blockers and calcium channel blockers, are commonly prescribed and have well-known safety profiles. Additionally, some of these drugs have exhibited pharmacological properties useful for the treatment of cancer, rendering them candidates for drug repurposing. In this review, we examine the preclinical and clinical evidence for utilizing antihypertensive agents in the treatment of cancer.